SEE 2018, NAGOYA, JAPANSCIENCE, ENGINEERING AND ENVIRONMENTiPROCEEDINGS OF FOURTH INTERNATIONAL CONFERENCE – SEE 2018
SCIENCE, ENGINEERING & ENVIRONMENT NAGOYA, JAPAN 12-14 NOVEMBER, 2018

Science, Engineeringand Environment
Edited byProf. Zakaria Hossain
Graduate School of Bioresources
Mie University, Japan

Dr. Jim Shiau
School of Civil Engineering and Surveying
University of Southern Queensland, Australia

THE GEOMATE INTERNATIONAL SOCIETYii

Copyright @ 2018 by The GEOMATE International Society
All rights reserved. In principle, no part of this publication or the information contained herein may be
reproduced in any form or by any means, translated in any language, stored in any data base or retrieval
system, or transmitted in any form or by any means without prior permission in writing from the publisher.
Disclaimer: The editors and the publisher have tried their best effort to ensure the integrity and the quality ofthis publication and information herein. However, they give no warranty of any kind, expressed or impliedwith regard to the material contained in this book, and will not be liable in any event for the consequences of
its use.
Published by:
The GEOMATE International Society
Tsu city, Mie, Japan
E-mail: society@geomate.org
http://www.geomate.org/

ISBN Number: 978-4-909106018 C3051

iii

Fourth International Conference on Science, Engineering & Environment,
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

Table of Contents
Prefacexii

Organization

xiii
1

ID

Keynote Papers

1k

RUNOFF CHARACTERISTICS OF DEBRIS FLOW FLOWING DOWN A TORRENT OF MILD GRADIENT
Naomasa Honda

2k

MECHANICAL PROPERTY OF CHLOROPRENE BEARING PAD FOR BRIDGE UNDER CYCLICTEMPERATURE CHANGE
Hidenori Tanaka, Kazuki Kurosawa and Masatake Yoshino

2

7

13

Technical Papers
ID

Science4503

EFFECT OF OKRA AND TANGERINE RATIOS ON PRODUCTION OF MIXED JUICE WITH LYCOPENE
SUPPLEMENTATION
Wattana Wirivutthikorn

4508

4513

4519

4521

4527

OPTIMAL RAIN GAUGES NETWORK USING GEOSTATISTICS AND HYBRID PARTICLE
SWARM-SIMULATED ANNEALING OPTIMIZATION
Mohd Khairul Bazli Mohd Aziz, Fadhilah Yusof, Zalina Mohd Daud, Zulkifli Yusop, Mohammad
Afif Kasno
SCREENING CRUDE EXTRACTS FROM PIPER SPP. ON COLLETOTRICHUM SP. AND
PHYTOPHTHORA SP. CAUSING PLANT DISEASE
Pornprapa Kongtragoul, Parinya Janthong, Theerachart Leepasert, and Chalermpol
Suwanphakdee
EXPRESSION OF HYALURONAN SYNTHASE (hasA) AND PRODUCTION OF HYALURONIC ACID
THROUGH BIOSYNTHESIS IN RECOMBINANT ESCHERICHIA COLI
Lai Zee Wei, Aayushree Kharel and Chong Jun Yi
THE UTILIZATION OF THE MITOCHONDRIAL COI AND THE NUCLEAR HISTONE H3 GENES FOR
DNA BARCODING STUDY OF INTERTIDAL SHELLED GASTROPODS FROM NADA COAST IN
WAKAYAMA PREFECTURE, JAPANNagisa Nakaji, Shoma Iwamoto, Shinnosuke Teruya, Masataka Kusube, Akira Kosaka, Takenori
Sasaki, Davin H. E. Setiamarga
THE EFFECTS OF THAI MASSAGE ON LEG MUSCLE OXYGENATION AND TIME TO FATIGUE IN
HEALTHY MALE SUBJECTS
Wirapong Sucharit, Wichai Eungpinichpong, Uraiwan Chatchawan, and PanneePeungsuwan

14

15

20

26

30

38

46

4551

APPLICATION OF SCMR AND FLUORESCENCE FOR CHLOROPHYLL MEASUREMENT IN
SUGARCANE
Darika Bunphan, Naris Sinsiri and Ruchuon Wanna

53

4567

THE EFFECTS OF AGROCHEMICAL RESIDUES ON AQUATIC INVERTEBRATES IN SEMI-ORGANICRICE FIELDS
Pattira Kasamesiri and Wipavee Thaimuangphol

59

4577

THE EFFECT OF SOIL DEPTH ON GROWTH OF CLOVER FERN AND USING CLOVER FERN ON THE
GERMINATION OF FERN SPORE
Sawat Pimsuwan and Yaowarat Wongsrisakulkaew

64

4580

CHEMICAL COMPOSITION AND INSECTICIDAL ACTIVITY OF ESSENTIAL OIL FROM INDIAN
BORAGE AGAINST MAIZE WEEVIL
Ruchuon Wanna and Jiraporn Krasaetep

70

iv

4583

4590

4594

4629

4638

4645

4650

4658

4673

4679
4688

ANGIOTENSIN CONVERTING ENZYME INHIBITOR ACTIVITY OF THE SOYBEAN TEMPEH PROTEIN
AS FUNCTIONAL FOOD
Sri Yadial Chalid, Sandra Hermanto Amalia Rahmawati
THE MODIFIED DECOMPOSITION METHOD FOR SOLVING VOLTERRA INTEGRAL EQUATION OF
THE SECOND KIND USING MAPLE
Dalal Adnan Maturi
STRUCTURE-BASED VIRTUAL SCREENING OF INDONESIAN NATURAL PRODUCT COMPOUNDS ASEBOLA VIRUS VP30 PROTEIN INHIBITORS
Givan Andris Tio, Andrei Bernadette, Mochammad Arfin Fardiansyah Nasution, Puteri Aprilia
Sitadevi, Syahrul Ridzki Pratama, and Usman Sumo Friend Tambunan
EFFECTS OF PIPERACEAE PLANTS EXTRACTS ON INHIBITION OF Aspergillus flavus AND SEEDGERMINATION OF MAIZE (Zea mays)
Chuajedton, A. and Boonkorn, P.
FORMULATION OF THE BODY SCRUB CREAM CONTAINING MORINGA SEED POWDER (MORINGA
OLEIFERA) AND ITS EXAMINATION DERMAL ACUTE IRRITATION
Hendrawati , Annita Karunia Savitri, Nina Fitriyati, Aulia Andi Mustika
COMPATIBLE ACTION GRAPH FOR FINITE CYCLIC GROUPS OF p-POWER ORDER
Mohammed Khalid Shahoodh, Mohd Sham Mohamad, Yuhani Yusof, Sahimel Azwal Sulaiman
and Nor Haniza Sarmin
FRAGMENT-BASED DRUG DESIGN TO INHIBIT DNA METHYLTRANSFERASE 1 (DNMT1) FOR
BREAST CANCER THERAPY
Ade Hanna Natalia, Ahmad Husein Alkaff, Mutiara Saragih, Ina Nur Istiqomah, and Usman Sumo
Friend Tambunan
CONSTRUCTION AND ANALYSIS OF M-POINT NON-STATIONARY SUBDIVISION SCHEME
Mehwish Bari, Najma Abdul Rehman and Mehboob AlamECOLOGY OF RUMINAL MICROORGANISMS UNDER THE INFLUENCE OF QUERCUS CORTEXEXTRACT
Galimzhan Duskaev, Il'shat Karimov, Georgy Levakhin, Baer Nurzhanov, Albert Rysaev andHamdiya Dusaeva
STUDY OF THE UTILIZATION OF CU(II) MODIFIED LIQUID SMOKE TO INHIBIT THE GROWTH OFFUNGI (SCHIZOPHYLLUM COMMUNE)
Muhammad Faisal, Shara Utari, Zammera Hayvia, and Ilham Maulana
SHORT-TERM EFFECTIVENESS OF INNOVATION PILLOW RELAX TO STRESS AND HEART RATEVARIABILITY IN THE ELDERLY
Peerada Damapong and Pongmada Damapong

75

81

84

91

95

101

107

113

118

126

131

4689

EFFECTIVENESS OF HERBAL STEAM FOR REDUCING STRESS IN PATIENTS DIABETICS
Pongmada Damapong and Peerada Damapong

135

4690

EFFICIENCY OF INDIAN BORAGE ESSENTIAL OIL AGAINST COWPEA BRUCHIDS
Ruchuon Wanna and Phanthiwa Kwang-Ngoen

139

4694

4696

4697

4698

THE CAPACITY OF SOIL WATER INFILTRATION UNDER HORTICULTURAL CROPS IN THE
WATERSHED UPSTREAM SUMANI
Aprisal and Bambang Istijono
DISCOVERY OF NOVEL DNMT-1 INHIBITOR BY FRAGMENT-BASED DRUG DESIGN AS A
POTENTIAL BREAST CANCER TREATMENT
Mutiara Saragih, Ahmad Husein Alkaff, Ade Hanna Natalia, Ina Nur Istiqomah, and Usman Sumo
Friend Tambunan
NITRIDING OF PURE TITANIUM BY HIGH DENSITY PLASMA USING H2-N2 GAS MIXTURE AT LOW
TEMPERATURE
Dionysius J. D. H. Santjojo, Masruroh, Setyawan P. Sakti, Maharani S. Rajapadni
OPTICAL EMISSION SPECTROSCOPY STUDIES DURING NITROGEN PLASMA OF POLYSTYRENE
SURFACES MODIFICATION
Masruroh, Dionysius J. D. H. Santjojo Heraniawati, Muhamad A. Abdillah, Tyas N Zafirah and Eka
Maulana, Setyawan P. Sakti

v

144

149

155

160

4706

EFFECTS OF SOIL QUALITY ON EATING QUALITY OF ‘Namwa’ BANANA (Musa ABB) FRUIT
Pannipa Youryon and Suriyan Supapvanich

164

4708

ASSESSMENT OF N-(3-OXOHEXANOYL)-L-HOMOSERINE LACTONE AND VEGETABLE MOLECULESIN VITRO
Il'shat Fayzelgayanovich Karimov, Galimzhan Kalikhanovich Duskaev

169

4709

SIMULATION SEA SURFACE TEMPERATURE OVER GULF OF THAILAND BY USING ROMS MODEL
Pramet Kaewmesri, Usa Humphries and Zhu Jiang

176

4726

4728

4738

4739

4749

4756

4782

4786

4792

4799

4801

4813

EFFECTS OF SEED PREPARATION, SOWING MEDIA, SEED SOWING RATE AND HARVESTINGPERIOD ON THE PRODUCTION OF CHIA MICROGREENS
Anjana Junpatiw, Akarapon Sangpituk
EFFECTS OF PLANTING SUBSTRATES SUPPLEMENTED WITH VERMICOMPOST AND
VERMICOMPOST FORTIFIED WITH Trichoderma asperellum CB-PIN-01 ON GROWTH ANDPYTHIUM ROOT ROT OF LETTUCE
Phraomas Charoenrak, Chiradej Chamswarng, Wanwilai Intanoo and Naowarat keawprasert
EFFECT OF OZONE MICROBUBBLES WITH VARIOUS TEMPERATURES ON THE CHLORPYRIFOSINSECTICIDE REMOVAL IN TANGERINE CV. SAI NAM PHUENG
Wirin Singtoraj, Jamnong Uthaibutra and Kanda Whangchai
EFFECTS OF ACIDIC ELECTROLYZED WATER WITH DIFFERENT TEMPERATURES ON MICROBIALCONTROL AND QUALITY OF FRESH-CUT BANANA LEAVES DURING STORAGE
Varumporn Kuljaroensub, Kanda Wangchai and Usawadee Chanasut
ESTIMATION OF AMMONIUM SOURCES IN ALLUVIAL GROUNDWATER USING Cl- AND GIS:A CASE STUDY OF INDRAMAYU CITY, INDONESIA
Anna Rusydi, Mitsuyo Saito, Seiichiro Ioka, Rizka Maria, Shin-ichi Onodera
ESTIMATION OF SEDIMENTATION RATE AND FRESH-SALINE ENVIRONMENT IN A COASTALALLUVIAL PLAIN, USING BORING CORES OF ALLUVIUM IN THE CENTRAL PART AREA OF SETO
INLAND SEA, JAPAN
Tohru Takeuchi , Shin-ichi Onodera , Kazuhiro Yamaguchi and Koiti Kitaoka
IMMEDIATE EFFECTIVENESS OF HERBAL STEAM ON CERVICAL RANGE OF MOTION WITH STRESSIN THE ELDERLY
Chamiporn Kongmong, Peerada Damapong and Pongmada Damapong
EFFECTS OF LOW INTENSITY EXERCISES ON BODY BALANCE AND MUSCLE STRENGTH OFCOMMUNITY ELDERLY PEOPLE
Worawut Chompoopan, Warangkana Chompoopan, Wichai Eungpinichpong, and Wilai
Eungpinichpong
INVESTIGATION OF CATHEPSIN B (CTSB) and CATHEPSIN L (CTSL) POLYMORPHISM FOR CARCASSAND MEAT QUALITY IN SWINE
Doungnapa Promket, Kajorngiat Nabundit, and Khanitta Ruangwittayanusorn
EFFECT OF HARVESTING STAGES ON JELLY SEED SYMPTOM OF PLANGO (Bouae burmanica) CV.
THUNL KLAO FRUITSPattarawan Wattanakeeboot and Usawadee Chanasut
USING BEEF MORPHOLOGY TO PREDICT CARCASS WEIGHT WHICH CUTTING IN THAI-ISAAN
STYLEKhanitta Ruangwittayanusorn, Doungnapa Promket, Songsak Champawadee, Jaturaput
Muapkunton, Ornicha Sriboon, Kewlin Pukkawan
DETERMINATION OF CAROTENOIDS AND DOBI CONTENT IN CRUDE PALM OIL BY
SPECTROSCOPY TECHNIQUES: COMPARISON OF RAMAN AND FT-NIR SPECTROSCOPY
Rayakorn Nokkaew, Vittaya Punsuvon, Tetsuya Inagaki and Satoru Tsuchikawa

181

186

192

197

203

208

213

216

221

226

230

235

4822

THE USE OF FISH AGGREGATING DEVICES (FAD’S) TO REDUCE DESTRUCTIVE FISHING IN PACITANCOASTAL INDONESIA
Tuty Handayani, Cinthia, Jarot Mulyo Semedi and Sajiharjo Marto Suro

241

4849

ANTIMICROBIAL RESISTANCE IN SALMONELLA ISOLATED FROM BEEF IN UPPER NORTHEASTERNTHAILANDNatthamon Tangjitwattanachai and Denpong Sakhong

246

vi

4851

ID

STUDY OF QUALITY AND CONSUMER TEST OF EMULSION SAUSAGE FROM BUFFALO AND
TURKEY MEAT
Thassawan Somchan and Suthipong Uriyapongson

Engineering

251

254

4501

PARAMETRIC STUDY ON THE RESPONSE OF COMPOSITE SINGLE PILES TO LATERAL LOAD BY
NUMERICAL SIMULATION (FDM)
Alex Otieno Owino, Zakaria Hossain, Jim Shiau

255

4510

EXTRACTION OF STATIC FEEDBACK COEFFICIENT FOR SPICE MODEL OF DRAIN INDUCEDBARRIER LOWERING IN JUNCTIONLESS DOUBLE GATE MOSFET
Hakkee Jung

261

4514

PERFORMANCE EVALUATION OF PARTIALLY PRESTRESSED CONCRETE BEAMS UNDER LIMITEDCYCLES OF REPEATEDLY APPLIED LOADING
Nazar K. Oukaili and Mohammed M. Khattab

267

4516

THE EFFECT OF FGD GYPSUM AND BOTTOM ASH ADDITION IN SHOTCRETE MIXTURE
Pisut Rodvinij , Pitiwat Wattanachai and Sattaya Chaiwithee

273

4523

4524

4525

USE OF DRY MIXING METHOD IN FLY ASH BASED GEOPOLYMER AS A STABILIZER FOR DREDGED
SOIL
Jonathan R. Dungca, Kimberly D. Ang, Aila Mae L. Isaac, John Joshua R. Joven and Ma. Beatrice
T. Sollano
RADIAL FLOW PERMEAMETER: A PROPOSED APPARATUS TO MEASURE HORIZONTALHYDRAULIC GRADIENT OF FLY-ASH BASED GEOPOLYMER-SOIL MIX
Jonathan R. Dungca, Winchell Dunley T. Lao, Matthew Lim, Wilson D. Lu and Juan Carlos P.
Redelicia
VERTICAL PERMEABILITY OF DREDGED SOIL STABILIZED WITH FLY-ASH BASED GEOPOLYMER
FOR ROAD EMBANKMENT
Jonathan R. Dungca, Winchell Dunley T. Lao, Matthew Lim, Wilson D. Lu and Juan Carlos P.
Redelicia

279

284

290

4528

PERFORMANCE OF SOIL SUBGRADE IMPROVEMENT USING WASTE MATERIAL
Harnedi Maizir, Reni Suryanita, Ulfa Jusi and Raihan Arditama

296

4529

EFFECT OF GRADATION OF BOTTOM ASH AS FINE AGGREGATE ON ENGINEERING PROPERTIESOF SHOTCRETE
Sattaya Chaiwithee, Pitiwat Wattanachai and Pisut Rodvinij

300

4530

A STUDY OF THE QUALITY OF SOIL INFILTRATION AT THE DOWNSTREAM OF KURANJI RIVER,
PADANG CITY
Aprisal, Bambang Istijono, Taufika Ophiyandri and Nurhamidah

306

4537

MICROSTRUCTURE AND MECHANICAL PROPERTIES OF CONCRETE WITH TREATED RECYCLED
CONCRETE AGGREGATESRichard De Jesus, Anthony Tang and Alvin Cunanan

311

4549

A COMPARATIVE STUDY ON VIBRATION SIGNALS OF A MOTORCYCLE AT VARIOUS POSITIONSSuphattharachai Chomphan

317

4550

FREQUENCY ANALYSIS OF THE ENGINE SUPPORT VIBRATION WITH HYDROGEN-DIESELDUAL-FUELING
Boonthum Wongchai, Poranat Visuwan, Sathaporn Chuepeng

322

4552

ASSESSMENT OF OUT-OF-PLANE FAILURE OF NON-ENGINEERED MASONRY WALL DUE TO
TYPHOON HAIYAN-INDUCED STORM SURGES
Jenes P. Borais, and Richard De Jesus

328

4555

WALKABILITY AND RAIL NODES ALONG THE TRANSEUROPEAN TRANSPORT NETWORK: THE
CASE OF GENOA BRIGNOLE STATION
Noriko Otsuka, Dirk Wittowsky, and Marlene Damerau

334

vii

4564

THE COMPARISON OF DRAINED SHEAR STRENGTH BETWEEN SINGLE STAGE AND MULTISTAGE
OF KHON KAEN LOESS FROM TRIAXIAL TEST
S. Chatchawan , R. Nuntasarn and D. Hormdee

340

4565

BEARING CAPACITY OF KHON KAEN LOESS BY PLATE BEARING TEST
P. Thaowandee, R Nuntasarn and P Punrattanasin

346

4566

DRAINED SHEAR STRENGTH PARAMETERS OF COMPACTED KHON KAEN LOESS BY DIRECT SHEAR
TEST
Atchariya Saengthongthip, Ratamanee Nuntasarn and Chinawat Muktabhant

352

4568

ABSORPTION OF NI, CU AND ZN ON BENTONITE CLAY MIXED WITH POZZOLANIC MATERIALSNatta Orprasert, Pongsakorn Punrattanasin and Dolrerdee Hormdee

358

4569

ADSORPTION OF ZINC ON BENTONITE CLAY MIXED WITH POZZOLANIC MATERIALSBY COLUMN LEACHING TEST
Pittaya Satiman, Pongsakorn Punrattanasin and Chinawat Muktabhant

363

4570

EFFECT OF INITIAL CONCENTRATION OF HEAVY METALS ON THE ADSORPTION CAPACITY OF
BENTONIRE CLAY MIXED WITH PORTLAND CEMENT
Anunt Sirisombunphatthana, Pongsakorn Punrattanasin and Ratamanee Nuntasarn

369

4571

4572

4576

ADSORPTION CAPACITY OF HEAVY METALS ON ILLITE, KAOLINITE AND MONTMORILLONITE
CLAYS FROM BATCH TEST
Keatniyom Teerawattanaparpha, Pongsakorn Punrattanasin and Dolrerdee Hormdee
ADSORPTION CAPACITIES OF HEAVY METALS TO SAND MIXED WITH SODIUM BENTONITE USINGBATCH SORPTION TESTS
Yuttapong Chaipanha, Pongsakorn Punrattanasin, Dolrerdee Hormdee and Chinawat
Muktabhant
OPTICAL RESPONSE ANALYSIS OF InGaAs HIGH-ELECTRONMOBILITY TRANSISTORS WITH A
1550-nm WAVELENGTH FEMTOSECOND PULSE LASERTaiki Kozakai, Itsuki Takagi, Shun Nakajima, and Hirohisa Taguchi

375

381

386

4581

VIBRATION AND SOUND SIGNAL ANALYSIS FOR A GASOLINE ENGINE WITH LPG-INSTALLATION
AND FAULT SIMULATIONSSuphattharachai Chomphan, Theerathan Kingrattanase and Saereephap Boonsit

390

4585

AN ARTIFICIAL NEURAL NETWORK MODEL FOR THE CORROSION CURRENT DENSITY OF STEEL IN
MORTAR MIXED WITH SEAWATER
Cheryl Lyne C. Roxas and Bernardo A. Lejano

396

4589

IMPLEMENTATION OF CONNECTION SYSTEM OF WOODEN PLATE AND WOODEN CLAMP ON
JOINT MODEL OF BAMBOO TRUSS STRUCTURES
Astuti Masdar, Suprapto Siswosukarto, Noviarti and Des Suryani

401

4592

EXPERIMENTAL INVESTIGATION OF SEISMIC PERFORMANCE OF REINFORCED BRICK MASONRYINFILLED REINFORCED CONCRETE FRAMES WITH A CENTRAL OPENING
Maidiawati, Jafril Tanjung, Yulia Hayati and Hamdeni Medriosa

407

4596

THE ANALISIS OF RIVER RUNOFF IN THE ABUKUMA RIVER BASIN
Masanobu Taniguchi and Hiroyuki Ii

413

4599

INFLUENCE OF POZZOLANIC MATERIALS IN THE ADSORPTION OF HEAVY METALS ON RED LOESS
SOIL
Pongsakorn Punrattanasin, Arnun Chantaduang and Chinawat Muktabhant

419

4609

EXPERIMENTAL STUDY AND MODELLING OF STRESS-STRAIN RELATIONSHIP OF RC COLUMNSSTRENGTHENED BY BAMBOO REINFORCED CONCRETE JACKETS
Ari Wibowo, Indradi Wijatmiko and Christin Remayanti Nainggolan

425

4615

STUDY OF MODULUS ELASTICITY OF PVC COATED WELDED MESH FIBER CONCRETE
Christin Remayanti Nainggolan, Indradi Wijatmiko and Ari Wibowo

431

viii

4617

4620

4628

4635

EFFECT OF BRICK MASONRY INFILLS TO SEISMIC CAPACITY OF INDONESIA MULTI-STORY RC
BUILDING
Jafril Tanjung, Maidiawati and Aditya Alfajri
STRENGTH CHARACTERISTICS OF WASTED SOFT DRINKS CAN AS FIBER REINFORCEMENT IN
LIGHTWEIGHT CONCRETE
Indradi Wijatmiko, Ari Wibowo and Christin Remayanti Nainggolan
OPTIMIZED PREPARATION OF RICE HUSK ASH (RHA) AS ASUPPLEMENTARY CEMENTITIOUS
MATERIAL
Carmela Denise C. Isberto, Krystoffer Lloyd D. Labra, Jan Marielle B. Landicho, andRichard M. De Jesus
INVESTIGATION OF CHANGES IN INDOOR RADON CONCENTRATIONS BEFORE AND AFTERSEISMIC ACTIVITIES IN GYEONGJU AND POHANG, KOREA
Hanyoung Joo, Jae Wook Kim and Joo Hyun Moon

437

443

449

455

4636

FIELD PERFORMANCE OF THE CAPILLARY WICK IRRIGATION (CAPILLARIGATION) SYSTEM FOR
RICE-BASED CROPS
Ricardo F. Orge and Derose A. Sawey

461

4639

INTERNATIONAL WATER MODEL UNDER PRODUCTIVITY CONDITIONS: THE CASE OF THE TIGRISAND THE EUPHRATES
Abdulamir Hussein Qasim

470

4644

UNDRAINED SHEAR STRENGTH OF SOFT CLAY REINFORCED WITH SINGLE ENCAPSULATED LIMEBOTTOM ASH COLUMN
Muzamir Hasan,Kwan Hui Yee, Fat-hi Muhamad and Masayuki Hyodo

475

4646

IMPROVEMENT OF ENZYMATIC CATALYSIS IN ORGANIC SOLVENTS VIA IMMOBILIZATION ON
BIOCHAR
Hidetaka Noritomi, Jumpei Nishigami, Nobuyuki Endo, Satoru Kato and Shinsuke Takagi

480

4651

PROPERTIES OF LIGHTWEIGHT AERATED GEOPOLYMER SYNTHESIS FROM HIGH-CALCIUM FLY
ASH AND ALUMINIUM POWDER
Charoenchai Ridtirud and Prinya Chindaprasirt

486

4654

4655

4657

FLUIDIZED BED COAL-BARK FLY ASH GEOPOLYMER WITH ADDITIVES CURED AT AMBIENTTEMPERATURE
Prinya Chindaprasirt, Pornnapa Kasemsiri, Suttipong Poomsrisa and Patcharapol Posi
EFFECT OF CUTTING PARAMETER AND FIBER PULL-OUT ON MACHINABALITY KENAF FIBER
REINFORCED PLASTIC COMPOSITE MATERIALS USING DOE
Azmi Harun, Che Hassan Che Haron, Jaharah A. Ghani, Yuzairi Abdul Rahim, Roshaliza Hamidon,
Tan Chye Lih
EMBEDDED INTELLIGENCE FOR QUALITY OF SERVICE-BASED VERTICAL HANDOVER
MANAGEMENT IN SEAMLESS WIRELESS NETWORKS
Sunisa Kunarak

495

501

508

4661

GREEN CARGO MOVEMENT, LOCALITY: MEKONG
Leonard Johnstone, Vatanavongs Ratanavaraha

512

4662

EFFECT OF FLY ASH FINENESS ON COMPRESSIVE, FLEXURAL AND SHEAR STRENGTHS OF HIGH
STRENGTH-HIGH VOLUME FLY ASH JOINTING MORTAR
Patcharapol Posi, Pornnapa Kasemsiri, Surasit Lertnimoolchai and Prinya Chindaprasirt

520

4665

THE USE OF BOTTOM ASH TO IMPROVE THE STRENGTH OF POOR SUBBASE LATERITIC SOIL IN
ROAD CONSTRUCTION
Chotikan Ratchakrom

526

4668

DAMAGE LEVEL PREDICTION OF MULTI-STORY STEEL STRUCTURE IN SUMATRA USINGBACKPROPAGATION NEURAL NETWORK
Reni Suryanita, Harnedi Maizir, Ismeddiyanto, Vindi Trisatria and Raihan Arditama

532

4670

BRAIN TISSUE SWELLING DURING ISCHAEMIA-REPERFUSION: 2D FINITE ELEMENT ANALYSISUSING POROELASTICITY
Mohamed Mokhtarudin, M. J., Shabudin, A. and Payne, S. J.

538

ix

4672

DESIGN OF BASE ISOLATED REINFORCED CONCRETE BUILDING SUBJECTED EARTHQUAKEEXCITATION USING EC 8
Norliyati Mohd Amin, Nabihan Ayub and Anizahyati Alisibramulisi

544

4676

STRENGTH AND BEHAVIORS OF DRY-JOINT RETAINIG NANO-BLOCK
PoungchompuPongsagorn, Buyarat Tanakrit, Bubpi Attaphol

550

4683

4695

4702

ASSESSMENT OF STRENGTH PARAMETERS OF UNREINFORCED MASONRY (URM) BLOCKS IN
HERITAGE STRUCTURES IN THE PHILIPPINES
Lessandro Estelito Garciano, Darlene Clarice Campado, Nitchell Andrei Castillo, Mary Grace
Odiamar, and Marcelino Tongco, Jr.
EFFECTS OF WATERSHED TOPOGRAPHY AND LAND USE ON BASE FLOW HYDROLOGY IN
EQUATORIAL REGION: A CASE STUDY IN UPPER KOMERING WATERSHED SOUTH SUMATERA,INDONESIA
Rosmalinda Permatasari, Arwin Sabar, Dantje Kardana Natakusumah and Hazairin Samaulah
TENSILE CREEP BEHAVIOR CONSIDERING YOUNG’S MODULUS DEVELOPMENT OF FLY ASH
CONCRETE AT EARLY AGE
Yuki Watanabe, Yoichi Mimura, Vanissorn Vimonsatit, Isamu Yoshitake and Itaru Horiguchi

557

563

568

4710

DATA BASE STRUCTURE MANAGEMENT INFORMATION SYSTEM LAND ALLOCATION IN SPATIALPLANNING
Sarino, Dinar DA Putranto, Agus Lestari Yuono, and I.C. Juliana

574

4721

ANALYSIS OF TRAFFIC ENVIRONMENT AND DYNAMIC BEHAVIOR OF BRIDGE GIRDERS BASED ON
IMAGE SENSING TECHNIQUES
Kouichi Takeya, Koharu Ota, Shiho Takagi and Junji Yoshida

581

4722

NON-CONTACT ESTIMATION OF STRAIN PARAMETER-TRIGGERING LIQUEFACTION
Erica Elice Saloma Uy, Toshihiro Noda, Kentaro Nakai and Jonathan Rivera Dungca

587

4729

INFLUENCE OF DEVELOPMENT/DIMINISHING OF ANISOTROPY ON THE MECHANICAL BEHAVIOR
OF CLAYEY SPECIMEN
Imran Khan, Kentaro Nakai, Toshihiro Noda and Kota Mizukami

593

4732

FACTORS IMPACTING PRECAST UTILIZATION IN CAMBODIA CONSTRUCTION
Kaya Ting, Phatsaphan Charnwasununth, Vachara Peansupap and Nobuyoshi Yabuki

599

4733

4740

DEVELOPMENT OF INTEGRATED SATELLITE-BASED DROUGHT MODEL IN THAILAND USINGMULTIPLE LINEAR REGRESSION
Mongkol Raksapatcharawong and Watcharee Veerakachen
COMPARATIVE ANALYSIS AND DESIGN OF TRANSVERSE BOX GIRDER BRIDGE BETWEENSTAAD.PRO AND MIDAS CIVIL SOFTWARES
Muhammad Naim Abdul Halim, Anizahyati Alisibramulisi, Mohammad Noor Abu Hassan,
Ahmad Ramlan Abu Talib, Noor Rita Ismail, and Norliyati Mohd Amin

605

611

4746

THE SPEED LIMIT FOR MOTORCYCLE: URBAN ARTERIAL ROAD IN KHON KAEN CITY, THAILAND
Jetsada Kumphong, Thaned Satiennam and Wichuda Satiennam

617

4747

MOTORCYCLE HELMET USE INTENTION WITH THE THEORY OF TRAFFIC PSYCHOLOGY FOR
BEHAVIOR CHANGE IN LAO PDR
Jetsada Kumphong, Thaned Satiennam, Wichuda Satiennam and Phongsavanh Inthavongsa

622

4748

4755

4759

PSYCHOLOGICAL MOTIVATION OF ELDERLY’ INTENTION TO USE PUBLIC TRANSIT: A CASE STUDY
OF LIGHT RAIL TRANSIT SYSTEM (LRT) IN KHON KAEN, THAILAND
Kawin Muenrit, Wichuda Satiennam
DEVELOPMENT OF A CRACK REPAIR METHOD USING YEAST-INDUCED CALCIUM CARBONATE
PRECIPITATION AND MODELING THE PRECIPITATION OF CALCIUM CARBONATE USING
GEOCHEMICAL SIMULATION
Yoko Sakakihara and Shinichirou Okazaki
ELECTRET CONDENSER MICROPHONE AS SENSOR IN ARTERIAL PULSE RECORDING DEVICE
Erni Yudaningtyas, Waru Djuriatno, Achsanul Khabib and Dionysius J.D.H. Santjojo

x

628

633

638

4764

EXPERIMENTAL INVESTIGATION OF HOLLOW BRICK UNREINFORCED MASONRY BUILDINGRETROFITTED BY FERROCEMENT LAYERS
Fauzan, Abdul Hakam, Febrin Anas Ismail and Jonathan Vincensius Osman

644

4765

USING FUZZY MULTI ATTRIBUTE DECISION MAKING (FMADM) APPROACH FOR RAILWAY TRACKREHABILITATION PLANNING: A CASE STUDY IN THAILAND
Thawatchai Phanyakit and Thaned Satiennam

651

4766

VEHICLE ACTUATED SIGNAL CONTROL FOR LOW CARBON SOCIETY
Thanapol Promraksa and Thaned Satiennam

658

4772

EXPERIMENTAL STUDY ON THE EFFECT OF STEEL FIBER WASTE TYRE ON HIGH STRENGTHCONCRETE
Fauzan, Rudy Kurniawan, Oscar Fitrah N and Claudia Lovina A. N

665

4778

AN ANALYTICAL INVESTIGATION OF EWECS COMPOSITE COLUMN WITH AND WITHOUT SHEAR
STUD
Fauzan, Ruddy Kurniawan and Zev Al Jauhari

671

4779

WATER RESOURCES AND STORMWATER MANAGEMENT STRATEGIES USING DUAL FUNCTION
RAINWATER TANK IN LABU RIVER BASIN MALAYSIA
Y.F. Huang, Effie Nyanong, K.F. Fung

678

4783

A PRICE SETTING FOR AN EXCESS-BAGGAGE SERVICE AS A FUNCTION OF FREIGHT PRICE
I.A. Shaban, F.T.S. Chan, and S.H. Chung

684

4785

BOND STRENGTH PREDICTION MODEL OF CORRODED REINFORCEMENT IN CONCRETE USINGNEURAL NETWORK
Nolan C. Concha and Andres Winston C. Oreta

690

4800

DIFFERENTIAL SETTLEMENT OF SHORT PILED RAFT FOUNDATION SYSTEM ON PEAT DURING
LOADING TEST
Sajiharjo Marto Suro, Adnan Zainorabidin, Agus Sulaeman and Ismail Bakar

696

4804

SETTLEMENT BEHAVIOR OF ROAD SURFACES CAUSED BY DISSOLUTION OF SALT LAYERS
Siwadol Saenseela, Pongsagorn Poungchompu and Gomin Chairatanangamdej

701

4808

PRODUCTION OF ETHYL ESTER BIODIESEL FROM USED COOKING OIL WITH ETHANOL AND ITSQUICK GLYCEROL-BIODIESEL LAYER SEPARATION USING PURE GLYCEROL
Mallika Tapanwong, Vittaya Punsuvon

706

4810

AN INTEGRATED APPROACH FOR SUSTAINABILITY IN THE APPLICATION OF INDUSTRIALISEDBUILDING SYSTEM (IBS)
Riduan Yunus, Abdul Rahim Abdul Hamid and Siti Rahimah Mohd Noor

711

4816

PRODUCTION OF Cu MICROPARTICLES UTILIZING HIGH PURITY Cu DENDRITE CRYSTALS AND
DEVELOPMENT OF CONDUCTIVE PAINTS
Junya Kuroda, Risa Uda, Honoka Tanabe, Kimihiro Yamanaka and Hirohisa Taguchi

717

4817

THERMOGRAVIMETRIC ANALYSIS OF TREATED WASTE ABACA FOR FLY ASH-BASEDGEOPOLYMER REINFORCEMENT
Janne Pauline S. Ngo, Roy Alvin Malenab and Michael Angelo Promentilla

721

4819

INTEGRATED MAINTENANCE SCHEDULING AND STAFF SCHEDULING FOR AN AIRCRAFT HANGAR
MAINTENANCE PROBLEM
Yichen Qin, Felix T.S. Chan, S.H. Chung, B. NIU, T. QU

725

4825

SYNTHESIS OF ONE-PART GEOPOLYMER USING D-OPTIMAL MIXTURE DESIGN FOR SOIL
STABILIZATION
April Anne S. Tigue, Jonathan R. Dungca, and Michael Angelo B. Promentilla

731

4828

FLOW INVESTIGATIONS WITHIN A CONCENTRIC CYLINDERS OF GAS SENSOR MODULE FOR I.C.
ENGINES
Tatsuya Kawaguchi, Yoona Jeong, Takushi Saito and Isao Satoh

737

xi

4830

APPLICATION STATIC LOAD TEST (SLT) AND PILE INTEGRITY TESTING (PIT) OF PILES IN SEA PORT“PRORVA” (WEST KAZAKHSTAN)
Askar Zhussupbekov, Zhanbolat Shakhmov and Gulshat Tleulenova

742

4840

DAMAGE DETECTION OF TRUSS STRUCTURES BY APPLYING MACHINE LEARNING ALGORITHMS
Koji Unno, Atsushi Mikami and Masaki Shimizu

746

4841

DAMAGE DETECTION OF TRUSS STRUCTURES BASED ON VIBRATION CHARACTERISTICS
Masaki Shimizu, Atsushi Mikami and Koji Unno

752

4961

AN AGENT-BASED SUPPLY CHAIN NETWORK WITH QUALITY AGENT MEDIATORS FOR QUALITY
COORDINATION
C.Y. Lam

758

4863

DESIGN, ANALYSIS, FABRICATION AND ANALYSIS OF SMALL WATER TURBINE
Gwo-Chung Tsai

764

4864

FLEXURAL STRENGTH OF RIGID PAVEMENT USING RECYCLED CONCRETE AGGREGATESIMPROVED BY POLYVINYL ALCOHOL
Suksun Horpibulsuk, Teerasak Yaowarat, Arul Arulrajah, Mehdi Mirzababaei and Ahmad Safuan
A Rashid

770

ID

Environment

776

4504

OPERATING CONDITIONS EFFECTS OF AN ELECTRODIALYSIS MODULE ON HYDROCHLORIC ACID
AND HYDROXIDE FORMATION FROM A SODIUM CHLORIDE MODEL SOLUTION
Medina Juan, Diaz Zoila and Rojas Jorge

777

4507

WOODY DEBRIS RECRUITMENT CAUSED BY DISASTERS RELATED TO TROPICAL STROM
NANMADOL (2017) IN HEADWATER OF ASAKURA CITY, FUKUOKA, JAPANThapthai Chaithong, Daisuke Komori and Yuto Sukegawa

784

4509

REVERSIBLE JUMP MCMC METHOD FOR HIRARCHICAL BAYESIAN MODEL SELECTION IN MA
MODELS WITH EXPONENTIAL NOISE
Suparman

791

4532

GAP COMPETENCY ANALYSIS FOR EMPLOYEE OF ANIMAL FEED WAREHOUSE DEPARTMENT
Siti Rochaeni, Siska Nurita, Eny Dwiningsih and Farahdita Soeyatno

795

4534

ENVIRONMENTAL REGENERATION AND MANAGEMENT IN PARTNERSHIP IN THE NORTHWEST
OF ENGLAND
Tomoko Miyagawa, Clare Olver, Noriko Otsuka, and Hirokazu Abe

801

4535

THE INCORPORATION OF LEAN SIX-SIGMA INITIATIVES TO REDUCE WATER FOOTPRINT OF A
PUBLIC UNIVERSITY
Karin Kandananond

807

4536

PREPARATION OF GEOPOLYMER CEMENT FROM CRUSHED STONE BY-PRODUCT USING ALKALIFUSION
Kazuki Sakamoto1, Takaaki Wajima1

811

4538

DESALINATION OF SEAWATER USING NATURAL ZEOLITE FOR AGRICULTURAL UTILIZATION
Takaaki Wajima

817

4539

COMPARISON OF COD AND TSS REMOVALS FROM ARTIFICIAL RIVER WATER BY MUDBALLSMADE WITH ACTIVATED EM1 AND EM4 SOLUTIONS
Fadjari Lucia Nugroho, Deni Rusmaya and Muthia Damayanti

822

4553

THE ESTIMATION OF THE LAKE COLAC WATER BALANCE USING ISOTOPIC RATIO OF WATER,AMOUNT OF PRECIPITATION AND EVAPORATION VALUES IN VICTORIA, AUSTRALIA
Hiroki Kitagawa, Peter G Dahlhaus Hiroyuki Ii

828

xii

4554

EFFECT OF α17-METHYLTESTOSTERONE ON SEX REVERSAL OF RED TILAPIA (OREOCHROMISNILOTICUS X OREOCHROMIS MOSSAMBICUS) IN FREE-SWIMMING STAGE
Supamas Sriwongpuk

834

4558

SEASONAL VARIATION AND SOURCE ANALYSIS OF MONITORING PM10 DATA IN NORTHERNTHAILAND
Pantitcha Outapa and Katiya Ivanovitch

840

4575

SPATIAL ANALYSIS OF COMMUNITY’S ACCEPTANCE FOR SUDS APPLICATIONS IN NHIEU LOC –THI NGHE SUB-BASIN, HO CHI MINH CITY, VIETNAM
Nguyen Hoang My Lan, Vo Le Phu and Le Van Trung

846

4578

4579
4587
4595

4597

4601

4603

4606
4608
4619
4630

4631

4632

4633

4634

DEVELOPING FINE PARTICLE FILTERING SYSTEM FOR MOTORCYCLE EXHAUST USING COCO
FIBERS
Arinto Y.P. Wardoyo, Firdy Yuana, and Selly Y. A. Elbasari
POLYETHYLENETEREPHTHALATE-BASED ACTIVATED CARBON PRODUCTION: PRELIMINARYSTUDY ON KOH ACTIVATION WITH MICROWAVE ASSIST
Sirasit Meesiri, Nattawut Seayang, Weeraphong Homnan, Navadol Laosiripojana, and Anusorn
Boonpoke
EFFECT OF SUSPENDING TRAFFIC ON A HIGHWAY IN A MOUNTAINOUS REGION IN CENTRALJAPAN ON THE SUCCESSION OF SLOPE VEGETATION
Teruo Arase, Akane Nishio, Tetsuo Okano and Taizo Uchida
ISOTOPIC RATIOS AND CHEMICAL COMPOSITION OF PRECIPITATION BETWEEN FOOT OF THE
BUILDING AND TOP OF THE BUILDING IN OSAKA CITY AND WAKAYAMA CITY, JAPANToshiki Ueda and Hiroyuki Ii
REGENERATION FOR SOCIO ECOLOGICAL PRODUCTION LANDSCAPE IN SERIOUSLYENVIRONMENTAL DAMAGED RURAL AREA
Takato Azegami, Hirokazu Abe, Noriko Otsuka and Tomoko Miyagawa
HOLISTIC LANDSCAPE PLANNING`S VALUE FOR NATURAL DISASTER RECONSTRUCTION:WILLINGNESS TO PAY FOR NEW RESIDENCE IN DIFFERENT RECONSTRUCTION PLANNING
APPROACHES
Misato Uehara
THE ADSORPTION OF HEAVY METALS FROM INDUSTRIAL WASTEWATER USING SARGASSUM
CRASSIFOLIUM
Lily Surayya Eka Putri and Eka Syafiqa
MEDICAL WASTE MANAGEMENT IN PRIVATE CLINICS IN SURABAYA AND FACTORS AFFECTING IT
Susi A Wilujeng, Enri Damanhuri and Mochammad Chaerul
PUBLIC HEARING WITHIN THE ENVIRONMENTAL AND HEALTH IMPACT ASSESSMENT SYSTEM: A
CASE STUDY FORM THAILAND
Chutarat Chompunth
SEMI–ARTIFICIAL SLUDGE PRODUCTION BY UTILIZING INORGANIC MATTERS OBTAINED FROM
NATURAL "HEDORO"
Hirosuke Hirano, Davin H. E. Setiamarga
EFFECTIVENESS OF USING CICADA SHELL AND RIVER BRYOPHYTE AS AN INDEX OF AVAILABLE
CU, ZN, PB, AS, NI AND CR CONTAMINATION
Hiroyuki Ii1
STUDY ON REMOVAL OF CONTAMINATED SOIL ON FOREST SLOPE FOCUSING ON DIFFERENCE IN
DENSITY OF SUBSURFACE GROUND
Keiichiro Shibata, Hidenori Yoshida, Daisuke Matsumori, Matsumoto Naomichi and Kazushi
Moriki
MAPPING STABLE ISOTOPIC RATIOS OF STREAM WATER AND CU, ZN, PB AND AS
CONCENTRATIONS OF BRYOPHYTE ALONG STREAMS IN THE EAST OF OKAYAMA AND TOTTORIPREFECTURES, JAPAN
Hiroyuki Ii and Masahito Yoshimura
REDUCTION OF NUTRIENTS IN PUBLIC MARKET WASTEWATER BY PHYCOREMEDIATIONRadin Maya Saphira Radin Mohamed, Alfituri Ibrahim Abdullah Abuala, Najeeha Mohd. Apandi,
Adel Al-Gheethi , Aisha A. Amhimmid Alqantosh and Amir Hashim Mohd. Kassim
AMOUNT OF PRECIPITATION ON TOPOGRAPHY FROM OSAKA PLAIN TO NARA BASIN ACROSSIKOMA MOUNTAINS, JAPANHiroki Nishiwaki and Hiroyuki Ii

xiii

852

857
863
869

875

882

888

895
901
907
914

920

925

931

935

4641

STUDY ON ADSORPTION PERFORMANCE OF FOOD WASTES FOR VARIOUS HEAVY METALS
Keiichiro Shibata, Hidenori Yoshida, Tsumugi Inoue, Matsumoto Naomichi and Yoshihiro
Suenaga

941

4656

THE ACUTE EFFECT OF TRADITIONAL THAI MASSAGE ON RECOVERY FROM FATIGUE IN
BASKETBALL PLAYERS
Nopparak Kaesaman and Wichai Eungpinichpong

947

4680

THE POTENTIAL OF TROPICAL MICROALGAE AS FLOCCULANT IN HARVESTING PROCESS
Astri Rinanti, Ronny Purwadi

953

4681

UTILIZATION OF WATER QUALITY MODELING TO DETERMINE MAXIMUM BOD LOAD OF
UPSTREAM CITARUM RIVER
Yonik Meilawati Yustiani, Sri Wahyuni and Syarifah Nur Fitria Dewi

959

4682

TURBIDITY REDUCTION OF THE RAW DRINKING WATER FOR PILOT SCALEELECTROCOAGULATION DEVELOPMENT
E. Afiatun, H. Pradiko and E. Fabian

964

4684

GEOSPATIAL MODEL OF PHYSICAL AND SOCIAL VULNERABILITY FOR TSUNAMI RISK ANALYSIS
Abu Bakar Sambah, F. Miura, Guntur, Sunardi, and A. F. Febriana

970

4687

HYDROLOGICAL AND NITRATE LOADING MODELING IN LAM TAKLONG WATERSHED, THAILAND
Chau Ngoc Tran, Chatpet Yossapol

976

4693

WATER QUALITY ASSESSMENT BASED ON THE WATER QUALITY INDEX (WQI) APPROACH USINGGEOSPATIAL ANALYSIS
Rina Febrina and Abu Bakar Sambah

981

4700

THE AWARENESS OF ENVIRONMENT CONSERVATION BASED ON OPINION DATA MINING FROMSOCIAL MEDIA
Kunyanuth Kularbphettong

987

4703

LIFE CYCLE IMPACT ASSESSMENT OF NEWGROUND MATERIAL AND EMBANKMENTCONSTRUCTION METHODS CONSIDERING RECYCLING
Hideyuki Ito, Kento Aimono and Takahiro Fujii

992

4712

TRACE ELEMENTS CONCENTRATIONS OF SEAWEED BESIDE MANY CLOSED COPPER MINES IN
SADAMISAKI PENINSULA
Erika Ueno and Hiroyuki Ii

999

4715

HEATING VALUE ENHANCEMENT BY BIOGAS PURIFICATION USING NATURAL ZEOLITE AND RICESTRAW-BASED BIOCHAR
Ambar Pertiwiningrum, Margaretha Arnita Wuri, Andang Widi Harto, Rachmawan Budiarto andMisri Gozan

1005

4720

THE POTENTIAL IMPROVEMENT OF PUBLIC TRANSPORT IN MINIMIZING AIR POLLUTION
Lasmini Ambarwati, and Amelia K. Indriastuti

1010

4735

PURIFICATION EXPERIMENTS ON THE PASIG RIVER, PHILIPPINES USING A CIRCULATION-TYPE
PURIFICATION SYSTEM
Okamoto Kyoichi, Komoriya Tomoe, Toyama Takeshi, Hirano Hirosuke

1016

4736

PERFORMANCE OF A CIRCULATION TYPE PURIFICATION SYSTEM DURING THE TREATMENT OFSLUDGE FROM MANILA BAY AND TWO PORTS IN JAPANKomoriya Tomoe, Okamoto Kyoichi , Toyama Takeshi, Hirano Hirosuke

1021

4742

ESTIMATION OF GROUNDWATER RECHARGE AND SALINIZATION IN A COASTAL ALLUVIAL PLAIN
AND OSAKA MEGACITY, JAPAN, USING δ18O, δD, AND Cl−
Yusuke Tomozawa, Shin-ichi Onodera, Mitsuyo Saito

1026

xiv

4751

ANALYSIS OF STATISTICAL METHODS FOR WATER-LEVEL FORECASTS OF NIGER INNER DELTA IN
MALIBarry Kassambara, Homayoon Ganji and Takamitsu Kajisa

1032

4773

ENHANCEMENT OF BIOMETHANE PRODUCTION POTENTIAL FROM THE ALKALINE PRETREATEDPOLY (LACTIC ACID) WASTE BY THE CO-DIGESTION PROCESS
Sutisa Samitthiwetcharong and Orathai Chavalparit

1039

4774

PERFORMANCE OF AIR CONDITIONING SYSTEM IN EDUCATIONAL BUILDING FOR ENERGYCONSERVATION
Nantamol Limphitakphong, Nuttasate Chaikatetham, Therdthai Khaimook, and Orathai
Chavalparit

1045

4780

WILLINGNESS TO PAY (WTP) BY CONTINGENT VALUATION METHOD (CASE STUDY: WASTE
MANAGEMENT SERVICES)
Marselina, Ria Virsa

1051

4795

BIOETHANOL PRODUCTION FROM AGRICULTURAL PRODUCTS AND FRUITS OF BANGLADESH
Md. Abul Kalam Azad and Nilufa Yesmin

1056

4796

ISOLATION OF STRESS TOLERANCE YEAST STRAIN FROM PAPAYA WASTES
Gemilang Lara Utama, Dwi Wahyudha Wira and Roostita L. Balia

1060

4815

MOBILE DEVICES: ITS IMPACT TO ACADEMIC PERFORMANCE
Charito G. Ong, Cipriana P. Flores

1066

4821

GEOPOLYMER BEADS FROM COAL FLY ASH AND WASTE PEN SHELLS
Kimmie Dela Cerna, Jose Isagani Janairo Roy Alvin Malenab and Michael Angelo Promentilla

1070

4823

DIFFUSION OF MERCURY FROM ARTISANAL SMALL-SCALE GOLD MINING (ASGM) SITES IN
MYANMAR
Tomonori Kawakami, Misa Konishi, Yuki Imai and Pyae Sone Soe

1075

4824

REMOVING ARSENIC AND FLUORIDE FROM HOT SPRING WATER BY ELECTROLYSIS
Yuki Imai, Misa Konishi, and Tomonori Kawakami

1082

4832

A DEVELOPMENT OF WASTE MANAGEMENT MODEL: A CASE STUDY OF SI MUM MUANG
MARKET IN THAILAND
Anucha Jaisai and Chutarat Chompunth

1089

4834

MECHANICAL PERFORMANCE OF ABACA-GEOPOLYMER COMPOSITE EXPOSED TO ELEVATEDTEMPERATURES
Roy Alvin J. Malenab and Michael Angelo B. Promentilla

1094

4838

ON THE IMAGE BASED ON SMART PHONE USERS IN PUBLIC SPACE
Yuki Ogimoto and Kazunari Tanaka

1100

4847

IMAGE ANALYSIS ON NIGHT SEQUENTIAL IMAGES
Hiroki Komai and Kazunari Tanaka

1104

4848

ON THE SPATIAL ELEMENTS FROM A BIRD’S-EYE VIEW SCAPE
Nobuaki Tanaka, Kazunari Tanaka

1107

4857

THE EFFICIENCY OF FLY ASH AND CEMENT SLAG TO DEVELOPMENT BUILDING
Ranti Hidayawanti, Supriadi Legino, Iriansyah Sangadji,Rony Panca Adi Widodo

1111

xv

4862

GEOSPATIAL PREDICTION OF SOIL EROSION USING MODIFIED BIVARIATE FREQUENCY RATIOTECHNIQUE
Abdulkadir Taofeeq Sholagberu, Muhammad Raza Ul Mustafa, Khamaruzaman Wan Yusof,
Ahmad Mustafa Hashim, Muhammad Waris A. Khan

1116

4642

NONLINEAR BEHAVIOR AND THERMAL DAMAGE OF THERMAL LAGGING IN CONCENTRIC
LIVING TISSUES SUBJECTED TO GAUSSIAN DISTRIBUTION SOURCE
Hamdy M. Youssef and Najat A. Al-Ghamdi

1122

4707

THE COMPLEX OF FIELD PILING STATIC LOADING TESTS ON AKSAI, NORTHWEST
KAZAKHSTAN
Askar Zhussupbekov, Iwasaki Yoshinori, Abdulla Omarov, Karlygash Borgekova and Sungat
Akhazhanov

1129

xvi

Fourth International Conference on Science, Engineering & Environment,
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PrefaceOn behalf of the SEE 2018 Organizing Committee, it is our great pleasure to welcome you to the FourthInternational Conference on Science, Engineering & Environment, held at the Meitetsu New Grand Hotel,
Nagoya,, Japan organized in conjunction with Mie University Research Center for Environmental Load
Reduction, The GEOMATE International Society, Useful Plant Spread Society, Glorious International, AOIEngineering, HOJUN, JCK, CosmoWinds and Beppu Construction, Japan.
The conference covers three major themes with many specific themes including:Engineering•Environmental Engineering•Chemical Engineering•Civil and Structural Engineering•Computer Software Web
Engineering•Electrical and Electronic
Engineering•Energy and Thermal Engineering•Aerospace Engineering•Agricultural Engineering•Biological Engineering and Sciences•Biological Systems Engineering•Biomedical and Genetic Engineering•Bioprocess and Food Engineering•Geotechnical Engineering•Industrial and Process Engineering•Manufacturing Engineering•Mechanical and Vehicle Engineering•Materials and Nano Engineering•Nuclear Engineering•Petroleum and Power Engineering•Forest Industry Engineering

Science•Environmental Sciences•Chemistry and Chemical Sciences•Fisheries and Aquaculture Sciences•Astronomy and Space Sciences•Atmospheric Sciences•Botany and Biological Sciences•Genetics and Bacteriology•Forestry Sciences•Geological Sciences•Materials Science and Mineralogy•Statistics and Mathematics•Microbiology and Medical
Sciences•Meteorology and Palaeo Ecology•Pharmacology•Physics and Physical Sciences•Plant Sciences and Systems Biology•Psychology and Systems Biology•Zoology and Veterinary Sciences

Environment•Environmental Technology•Recycle Solid Wastes•Environmental dynamics•Meteorology and Hydrology•Atmospheric and Geophysics•Physical oceanography•Bio-engineering•Environmental sustainability•Resource management•Modelling and decision support tools•Institutional development•Suspended and biological processes•Anaerobic and Process modelling•Modelling and numerical prediction•Interaction between pollutants•Water treatment residuals•Quality of drinking water•Distribution systems on potable water•Reuse of reclaimed waters

As expected, this year we have received many submissions from different countries all over the world. The
technical papers were selected from the vast number of contributions submitted after a review of the abstracts.
The final papers in the proceedings have been peer reviewed rigorously and revised as necessary by theauthors. It relies on the solid cooperation of numerous people to organize a conference of this size. Hence, we
appreciate everyone who support as well as participate in the joint conferences.
Last but not least, we would like to express our gratitude to all the authors, session chairs, reviewers,
participants, institutions and companies for their contribution to SEE 2018. We hope you enjoy theconference and find this experience inspiring and helpful in your professional field. We look forward toseeing you at our upcoming conference next year.
Best regards,
Prof. Dr. Zakaria Hossain, Chairman

Dr. Jim Shiau, USQ, Australia (Assistant to Chairman)xvii

Fourth International Conference on Science, Engineering & Environment,
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

Organization
Scientific Committees:
Honorary Chairman: Dr. Sohji Inoue, E/Prof. Mie University, Japan
Conference Chairman: Dr. Zakaria Hossain, Prof. Mie University, Japan
Assistant to Chairman Dr. Jim Shiau, University of Southern Queensland, Australia
Conference Organizing Committee:
Dr. Zakaria Hossain, Prof. Mie University, Japan (Chair)
Dr. Jim Shiau, USQ, Australia (Assistant to Chairman)
Dr. Satoshi Kaneco, Prof., Mie University, Japan (Co-Chair)Dr. Sohji Inoue, E/Prof. Mie University, Japan (Co-Chair)
Dr. Toshinori Sakai, Prof. Mie University, Japan (Co-Chair)
Dr. Takamitsu Kajisa, Prof. Mie University, Japan (Co-Chair)Dr. Masaaki Kondo, A/Prof. Mie University, Japan (Co-Chair)
National & International Advisory Committee:
Dr. Fumio Tatsuoka, Prof., Tokyo University of Science, Japan
Dr. Junichiro Takeuchi, Prof., Kyoto University, Japan
Dr. Kingshuk Roy, Prof., Nihon University, Japan
Dr. Nakib Dan Khan, A/Prof. Mie University, Japan
Dr. Sai Vanapalli, Prof., University of Ottawa, Canada
Dr. Musharraf Zaman, Prof. Univ. of Oklahama, USA
Dr. Rafiqul Tarefder, Prof. University of New Mexico, USA
Dr. M. Bouassida, Prof., National Sch. of Engg. of Tunis
Dr. L.R. Austriaco, Prof., Angles Univ. Found., Philippines
Dr. A.S.M. Abdul Awal, Prof., Univ. Technology Malaysia
Dr. M. Ibn Ibrahimy, Prof., Int. Islamic Univ., Malaysia
Dr. Mohammad Shariful Islam, Prof., BUET, Bangladesh.
Dr. Bujang B.K. Huat, Prof., Univ. Putra Malaysia
Dr. Nemy Banthia, Prof., UBC, Canada
Dr. Ian Jefferson, Prof., Univ. of Birmingham, UK
Dr. John Bolander, Prof., Univ. of California, USA
Dr. Shamsul Chowdhury, Prof., Roosevelt Univ., USA
Dr. Isabel Pinto, Prof., University of Coimbra, Portugal
Dr. Mark Jaksa, Prof., University of Adelaide, Australia
Dr. Jim Shiau, A/Prof., USQ, Australia
Dr. Hj. Ramli Bin Hj. Nazir, A/Prof., UTM, Malaysia
Dr. H.M. Shahin, Prof., Islamic University of Technology, Bangladesh
Dr. Md. Ariful Islam, A/Prof. Dhaka University, Bangladesh
Dr. Md. Nurul Amin, Prof. Dhaka University, Bangladesh
Dr. D.K. Chauhan, Prof. Noida International Univ., India
Dr. Chan Chee-Ming, A/Prof. Universiti Tun Hussein Onn Malaysia
Dr. Ahmed H. A. Dabwan, A/Prof. TATI Univ. College, Malaysia

xviii

International Technical Program Committee:
Prof. Adolf Heinrich Horn, Geological Institute - Federa University of Minas Gerais, Brazil
Prof. Bang-Fuh Chen, National Sun Yat-sen University, Taiwan
Prof. Bindeshwar Singh, Kamla Nehru Institute of Technology, India
Prof. Catherine Mulligan, Concordia Institute of Water, Energy and Sustainable Systems, Canada
Prof. Chi-Min Liu Chienkuo Technology University, Taiwan
Prof. Daffalla Rabih, Kenana Sugar Company, Sudan
Prof. Essaid Bilal, Ecole Nationale Superieure Des Mines De Saint Etienne, France
Prof. Hakan Caliskan, Usak University, Faculty of Engineering, Turkey
Prof. Ibrahim Maiyza, National Institute of Oceanography & Fisheries, Egypt
Prof. Loc Nguyen, Sunflower Soft Company, Vietnam
Prof. Marilia Hagen, Indiana University, United States
Prof. Md Najib bin Ibrahim, Universiti Teknologi MARA, Malaysia
Prof. Md. Abdul Baset Mia, BSMR Agri. Univ., Bangladesh
Prof. Mihaela Popescu, University of Craiova, Romania
Prof. Mohamed Abdou, Faculty of Education Department of Mathematics, Egypt
Prof. Mohamed Tahiri, Présidnce de l'Université Hassan II de Casablanca, MoroccoProf. Nazar Oukaili, University of Baghdad, Iraq
Prof. Radim Cajka, Technical University Ostrava, Faculty of Civil Engineering, Czech RepublicProf. Rajaraman Jambunathan, AMET University, India
Prof. Saad Farhan Ibrahim Alabdullah, University of Almustansiriyah, Iraq
Prof. Salem Alsanusi, Benghazi, Libya
Prof. Sudhir Kumar Das, Retired Senior Project Manager of Indian Railways, India
Prof. Zachary Senwo, Alabama A&M University, United States
Prof. Imed Jabri, University of Tunis, Tunisia
A/Prof. Bindeshwar Singh Kamla Nehru Institute of Technology, India
A/Prof. Hasi Rani Barai, Yeungnam University, South Korea
A/Prof. Jamaluddin Mahmud, Universiti Teknologi MARA, Malaysia
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A/Prof. Nurbek Saparkhojayev, Almaty Management University, Kazakhstan
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A/Prof. Abdull Halim Abdul, OIl and Gas department, Malaysia
A/Prof. Baoping Cai, China University of Petroleum, China
A/Prof. Dariusz Jakóbczak, Koszalin University of Technology, Poland
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A/Prof. Hêriş Golpîra, Islamic Azad University, Sanandaj, Iran
A/Prof. Muhammad Aslam, King Abdulaziz University, Saudi Arabia
A/Prof. Tomasz Plech, Medical University of Lublin, Poland
A/Prof. Fellah Mamoun, Abbes laghrour University, Algeria
A/Prof. R. S. Ajin, GeoVin Solutions Pvt. Ltd., India
A/Prof. Roman Szewczyk, Industrial Research Institute for Automation and Measurements, PolandxixDr. Abolghasem Akbari, University Malaysia Pahang, Malaysia
Dr. Ahmad Safuan A Rashid, Universiti Teknologi Malaysia, Malaysia
Dr. Akinola Johnson Olarewaju, Federal Polytechnic Ilaro, Ogun State, Nigeria
Dr. Alexandre Costa, Federal University of the valleys of Jequitinhonha and Mucuri, Brazil
Dr. Angelo Gallone, Scotland’s Rural College (SRUC), United Kingdom
Dr. Azizul Azhar Ramli, Universiti Tun Hussein Onn Malaysia
Dr. Bashir Dar, University of kashmir Delina Baramulla J&K India, India
Dr. Bassam Abdellatif, National Authority for Remote Sensing and Space Sciences, Egypt
Dr. Binh Phu Nguyen, National University of Singapore, Singapore
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Dr. Evgeni Starikov, KIT, Karlsruhe, Germany; Chalmers, Gothenburg Sweden, Germany
Dr. Fatma Khanchel, University of Tunis El Manar, Tunisia
Dr. Hamidreza Khataee, Griffith University, Australia
Dr. Hêriş Golpîra, Islamic Azad University, IranDr. Iskhaq Iskandar, Dept. Physics, University of Sriwijaya, Indonesia
Dr. Jingwei Zhao, University of Wollongong, Australia
Dr. Jitendra Agrawal, Rajiv Gandhi Proudyogiki Vishwavidyalaya, India
Dr. Liza Patacsil, Malayan Colleges Laguna, Philippines
Dr. Mohamed Amine, Ferrag Guelma University, Algeria
Dr. Mohd Afendi Rojan, Universiti Malaysia Perlis, Malaysia
Dr. Mohd Altaf, University of kashmir Delina Baramulla J&K India, India
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Dr. Mostafa Khater, Egypt - El sharqia - Zagazig, Egypt
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Dr. Zongyan Zhou, Monsh University, Australia
Dr. Purnanand Savoikar, Goa Engineering College, India
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Dr. Emanuele Quaranta, Politecnico di Torino, Italy
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Dr. Khor Shing Fhan, Universiti Malaysia Perlis, Malaysia
Dr. Mario Chauca, Ricardo Palma University, Peru
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Dr. Vikas Panthi, National Institute of Technology, India
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Dr. Subhasis Roy, University of Calcutta, India
Conference Correspondence:Prof. Dr. Zakaria Hossain (Director)
Dept. of Environmental Science and Technology, Mie University, Japan
Mr. Md. Aminul Islam (Secretary)Dept. of Environmental Science and Technology, Mie University, Japan
E-mail: conference@geomate.org
Tel & Fax: +81-59-231-9578
Editorial and Executive Committee:
Prof. Dr. Zakaria Hossain
Dr. Jim Shiau
Engr. Alex Otieno Owino
Engr. Mohamed Mahmoud Ahmed Eltaherxxi

SEE - Nagoya, Japan, Nov.12-14, 2018

Keynote Papers

14th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

RUNOFF CHARACTERISTICS OF DEBRIS FLOWFLOWING DOWN A TORRENT OF MILD GRADIENT

1

Naomasa Honda1
Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan

ABSTRACT
When a river bed slope is steep, the debris flow generally erodes the bed material and travels down on a large
scale. When the bed slope becomes gentle at an equilibrium bed slope for a debris flow that corresponds to asediment concentration based on volume as a boundary, the debris flow allows sediment deposits and stops soon.
But when the debris flow includes such fine sand as volcanic ash, it may flow down at a smaller incline than ageneral stop gradient. We discuss the factors under which a debris flow moves downhill even if the bed slope isvery small, based on the relationship between the bed slope and the sediment concentration. We investigated two
actual debris flows in Japan: Ohkanazawa torrent of Izuohshima in Tokyo Prefecture in 2013 (caused by heavy
rainfall) and Sanohdani torrent of the Aso district in Kumamoto Prefecture in 2016 (caused by two huge
earthquakes). Judging from the results, when the debris flow structure consisted of a high sand-water mixture,
the material of a small size particle raised the density of the pore water. A mudflow formed in the mild gradienttorrent, arrived downstream, and overflowed.
Keywords: Torrent of mild gradient, Debris flow, Pore water, Fine sand concentration, Mudflow

very small, based on the relationship between the
bed slope and the debris flow’s sediment centration.
We chose two actual debris flows in Japan forinvestigation and discussion: one caused by a heavy
rainfall and another due to huge earthquakes.

INTRODUCTION
The characteristics of debris flow runoff strongly
depend on the river bed slope as shown in Fig. 1. A
debris flow is generally formed in the reach wheresediments exist that might be eroded and the bed
slope is 15° above. The debris flow erodes the bed
material and flows down on a large scale [1] – [3].
When the bed slope becomes gentle at an
equilibrium bed slope for a debris flow that
corresponds to a sediment concentration by volume
as a boundary, the sediment transport mode changes
from debris flow into an earthflow with the bed
slope’s decrease [4]. Then the debris flow allows asediment deposit and stops quickly [5], [6]. But
when the debris flow includes such fine sand as
volcanic ash, it may flow down at a smaller incline
than a general stop gradient [7], [8].
Next we discuss the factors under which a debris
flow moves downhill even if the bed slope gradient isCollapse

・・・・・・・・・

Occurrencezone( Erosion )cθDevelopmentzone( Erosion and
Deposition )

・
・・・・・
・
・ ・・・ ・・ ・・ ・・・・・・・・・・・・・ ・
・

・・
・・・
・・・ ・
・

θ ＝15～20°

Stop and
Deposition zone
( Deposition )METHOD AND PROCEDURE
Relationship between debris flow’s bed slope andsediment concentration
The following shows the relationship between
the bed slope and the sediment concentration of thedebris flow [1]:tan  e (1)where θe is the equilibrium bed slope for a debris
flow that corresponds to the sediment concentration
by volume c, which is a bed slope that produces
neither erosion nor deposition on the bed. σ is themass density of gravel, ρ is the mass density of thepore water, and φ is the sediment’s interparticle
friction angle.
Equation (1) is updated as follows:

Water
flooding

・ ・・・・ ・ ・ ・・ ・・ ・ ・・ ・・ ・ ・・・ ・・・・ ・・ ・・・・・ ・・ ・ ・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・

River bed
θ ＝about 10°( /   1) ctan ( /   1) c  1

ce θ ＝2～3°tan ( /   1) tan   tan  (2)where ce is the equilibrium sediment concentration
by volume corresponding to a bed slope θ, which isFig. 1 Debris flow runoff process

2

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018the sediment concentration where neither erosion
nor deposition is produced on the bed.
For Eq. (1), Egashira et al. [7] proposed thefollowing formula based on the mudflow
characteristics:
tan  e ( /   1) c hstan ( /   1) c  1 h(3)(Nagoya city)where h is the flow depth and hs is the thickness ofthe bedload layer (hs≦h).
In Eq. (3), when hs / h equals 0.3, the flow forms
a mudflow. When hs / h equals 1.0, Eq. (3)completely agrees with Eq. (1) and the flow forms adebris flow.
The mudflow consists of water and material ofsmall particle size. On the other hand, the debris
flow consists of water and sediment of relatively
large scale. Eq. (3) shows that the mudflow has
higher fluidity than the debris flow.

Izuohshima
Kumamoto Prefecture

Fig. 2 Location of debris flow occurrences
ash of small particle size. The soil layer under thesurface layer was aquiclude.
The mud flow, which consisted of water andvolcanic ash, flowed down at a mild gradient,reached the sea, and overflowed over a wide area.
By this mud flow, 39 peoples were left dead or
missing and such serious damage as house collapses
occurred successively.

Previous work on relationship between bed slopeand debris flow runoff characteristics
Egashira et.al [8] performed a numerical analysisof the debris flow of the Gamaharazawa torrent (atributary of the Hime river) caused by snowmelt in
1996, based on one-dimensional governing
equations for the sediment-water mixture. In theirsimulations, they assumed that the debris flow
consists of sediment and muddy water containing alarge amount of fine sand (concentration assumed torange from 30 to 50 %). Based on their results, they
explained the sediment runoff phenomenon as
follows:
・Since the debris flow added to the fluidity due tothe increase of buoyancy with muddy water, thedebris flow flowed down the channel works of asmall incline less than 3°.
・When the influence of the fine sand was ignored,
the debris flow was deposited in the middle of thetorrent and didn’t arrive downstream.
・The sediment flowed down the Hime River withlittle sediment deposition in the channel works.

600
27.7°

Altitude （m）

500
400

18.9°

300

11.6°
6.8°

200

3.8°

100
0
0

500

1000

1500

2000

2500

Distance （m）

Fig. 3 Bed profile of Okanazawa torrent
Case 2: Debris flow at Sanohdani torrent [11]Two huge earthquakes of Japanese seismic
intensity scale 6 and 7 struck Kumamoto Prefecture(Fig. 2) in April 14 and 16, 2016. By theseearthquakes named “the 2016 Kumamoto
Earthquake” later, 50 people died over two days.
Such serious damage as house collapses, roadsurface cave-ins, and train derailments also
occurred.
Such sediment-related disaster occurrences aslandslides, collapses, and debris flows wereconcentrated near the earthquake faults. Ten people
died in two days from sediment-related disasters. In
Minamiaso village, a debris flow occurred in
Sanohdani torrent.
Sanohdani torrent has a watershed area of 2.34
km2, a reach of about 5km and a mean bed slope of
6.9 °. It is designated as a debris flow torrent based

Outline of actual debris flows
Case 1: Mud flow at Ohkanazawa torrent [10]Izuohsima is an island in Tokyo Prefecture asshown in Fig .2. In October, 2013, typhoon No.26
caused a record-breaking heavy rainfall (824 mm/24
hours), following by a huge mud flow of
Ohkanazawa torrent.
Ohkanazawa torrent was formed by the eruptionof Mt. Mihara in the center of Izuohshima. As
shown in Fig. 3, its downstream bed slope was loose.
The surface layer of the mountain slope that
constituted both sides of the torrent included volcanic
3SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

The sediment,
Figure 5 shows the relationship between c and θ
by Eq. (1) and Eq. (3). In Fig. 5, φ is set at 33°. It
ranges from 33 ° to 39 ° and is frequently in the debris
flow runoff analysis [8], [11]. It is also a minimum
value in the range considering the debris flow’s highfluidity. In Eq. (1), cs’s values are 0, 30 and 50 %. In
Eq. (3), hs/h is set at 0.3, which shows thecharacteristics of the mud flow, and ρ equals ρw [7].
In Fig. 3, the mean gradient of the downstreamthat reaches Ohkanazawa torrent is 3.8 °. In Fig. 5,
when θ is 3.8 ° in Eq. (1), the flow, whose cs is 30 %,has around 15 % of c and keeps the earthflow
characteristics; the flow whose cs is 50 %, has a little
less than 30 % of c and retains the hyper
concentrated debris flow characteristics. Similarly,
in Fig. 5, when θ is 3.8 ° in Eq. (3), the mudflow
may have a high sediment concentration over than
30 %.
When hs/h equals 0.3 in Eq. (3), cs, which is θefrom Eqs. (1) and (3), approximately equals 55 %and almost equals the sediment concentration of the
bed layer (the critical concentration at which thedebris flow can entrain the sediment). In addition,
the range from 30 to 50 % of cs is in good agreementwith the results of Egashira et al. [8].
Judging from the results, in Ohkanazawa torrent,
the material of the small particle size, which was
mainly composed of volcanic ash, raised the massdensity of the pore water that constituted the debris
flow and increased the fluid’s buoyancy. The
mudflow was formed by a sediment-muddy water
mixture and flowed down a mild gradient torrent. It
arrived downstream with high fluidity and overflowed.

1200(A) : Confluence of a triburary(B) : Heisei-Nagano bridge(C) : Sanoujidanigawa check dam(D) : Nagano bridge

Altitude (m)

1000
800

(A)
(B)

(C)

600

(D)

400

(6.8°)(11.6°)(5.4°)(7.7°)((2.9°))：mean gradient

200
0

1000

2000

3000

4000

5000

Distance (m)Fig. 4 Bed profile of Sanohdani torrent
which was produced by the hillside landslide due tothe earthquake, formed a debris flow without a watersupply, arrived downstream, and overflowed. The
debris flow’s soil material was mainly composed ofclay and silt of a small particle size, except just after
the earthquake. Its reference grain size, d50, was lessthan 0.1mm.
Calculation Conditions
To clarify the factors under which a debris flow
moves downhill even if the bed slope gradient is verysmall, we investigated the relationship between the
bed slope and the sediment concentration of thedebris flow using Eqs.(1), (2) and (3).
When the pore water includes fine sand, wecannot ignore how it influences the buoyancy [8].
Therefore, ρ is given as follows:     w cs   w(4)Case 2: Debris flow at Sanohdani torrent

where ρw is the mass density of the fresh water andcs is the fine sand concentration in the pore water. In
this study, we used σ=2.70 g/cm3 and ρw=1.00
g/cm3.

Figure 6 shows the relationship between φ andce by Eq. (2) when the θ values are 3 ° and 6 °. In
Eq. (2), cs’s values are 0, 30 and 50 %. When φequals to 35 ° (it ranges from 33 ° to 39 ° , it isfrequently used for debris flow runoff analysis [7],[11] and is a middle value in the range), and cs
ranges from 30 to 50 %, ce is as follows:

RESULTS AND DISCUSSIONS
Case 1: Mud flow at Ohkanazawa torrent
Eq.(1) (c s =0%)

σ=2.70g/cm3
ρw=1.00g/cm3
φ=33°
cs=0，30，50%

15Equilibruim sediment concenration

Gradient θ（°）

20

Eq.(1) (c s =30%)

10

Eq.(1) (c s =50%)

5
Eq.(3) (hs / h = 0.3)

0
0

10

20

30

40

50

50
[b]
[b]

30
[b]

Eq.(2):[a]：θ = 3°[b]：θ = 6°

20
10

cs :

0
0

Sediment concentration by volume c (%)

[a]

[a]

[a]

40

by volume ce (％)

on Japanese law as shown in Fig. 4.

0%

5

10

30%

15

50%

20

25

30

35

Internal friction angle φ （°）

Fig. 5 Relationship between c and θ

Fig. 6 Relationship betweenφand ce
4

40

45

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

Equilibrium gradient θe （°）

20

20

20

[1]～[3]: Eq.(1)[1] c s= 0％，[2] c s=30％ [3] c s=50%[1]～[3]: Eq.(1)[1] c s= 0％，[2] c s=30％ [3] c s=50%

15[1]～[3]: Eq.(1) , [1] c s= 0％[2] c s=30％ [3] c s=50%

15[4]: Eq.(3)hs / h=0.3，

1015[4]: Eq.(3)hs / h=0.3，

[1]

[2]

[2]

[3]

[3]

[3]

5

5

5

0

0

0
10

20

30

40

[4]

[4]

[4]

0

[2]

c s= 0％10c s= 0％10c s= 0％[1][4]: Eq.(3)hs / h=0.3，

[1]

50

Sediment concentration by volume c (%)(a) φ=25°

0

10

20

30

40

50

Sediment concentration by volume c (%)

0

10

20

30

40

50

Sediment concentration by volume c (%)(b) φ=30°(c) φ=35°

Fig. 7 Relationship between c and θe・ When θ is 6 °, the flow has a sedimentconcentration from 22 to 38 % and retains thehyper concentrated debris flow characteristics.
・ When θ is 3 °, the flow has a sedimentconcentration from 10 to 18 % and retains theearthflow characteristics even if the bed is gentle.

downstream with high fluidity and overflowed.
CONCLUSION
With both cases (Ohkanazawa torrent andSanohdani torrent), the material of small particle size
raised the mass density of the pore water that
constituted the debris flow and increased the fluid’s
buoyancy.
A debris flow is generally recognized as asediment-related disaster of steep slopes. But runoff
characteristics strongly depend on the materials thatcomprise the debris flow (sediment and the muddy
water) with the bed slope. As a result, the sedimenttransport mode changes from a debris flow into
general contact loads and the disaster form and its
scale change, too. They must be examined incountermeasures against debris flow hazards.

The reference grain size of the soil material
constituting debris flow d50 was very small (less than
0.1 mm.) and φ was probably smaller than anormal value of the debris flow, which is mainlycomposed of relatively large-scale gravel.
Figures 7(a), (b), and (c) show the relationshipbetween c and θe whenφ is 25 °, 30 ° and 35 ° in
Eqs. (1) and (3). In Eq. (1), the values of cs are 0, 30,
and 50 %, hs/h equals 0.3, and cs is 0 % in Eq. (3).
In Fig. 7(a) (φ=25°), c, where θe equals 3 °,ranges from 16 to 28 % in Eq. (1) (cs ranges from 30
to 50 %) and around 35 % in Eq. (2). Similarly, inFig. 7(b) (φ=30°), c, where θe equals 3 ° ranges from13 to 22 % in Eq. (1) (cs ranges from 30 to 50 %)and around 26 % in Eq. (2). As shown in thesefigures, the flow can keep the hyper-concentrated
debris flow characteristics on a mild bed slope.
When hs/h equals 0.3 in Eq. (3), cs, which is θeby Eqs. (1) and (3), approximately equals 55 % andalmost equals the sediment concentration of the bed
layer, too. In addition, the range from 30% to 50 %of cs is in good agreement with the results ofEgashira et al. [8].
Judging from our results, in Sanohdani torrent,
the material of small particle size, which is mainlycomposed of clay and silt, raised the mass density ofthe pore water that constituted the debris flow andincreased the fluid’s buoyancy. Such hyper
concentrated flow as earthflow and mudflow wasformed by a sediment-muddy water mixture andflowed down a mild gradient torrent. It arrived

ACKNOWLEDGEMENTS
Part of the present study was supported by
Strategic Research Project from Tokyo University ofAgriculture.
REFERENCES[1] Takahashi T., A Mechanism of Occurrence of
Mud-Debris Flows and Their Characteristics in
Motion. Annuals of Disaster Prevention
Research Institute, Kyoto University, Vol. 20,
Issue B-2, 1977, pp.405-435 (in Japanese).
[2] Takahashi T., Study on the Deposition of Debris
Flow (3) -Erosion of Debris Fan -. Annuals ofDisaster Prevention Research Institute, Kyoto
University, Vol. 25, Issue B-2, 1982, pp.327–
348 (in Japanese).
[3] Takahashi T. and Fu Kuang, Formation of
Debris Flow on Varied Slope Bed. Annuals ofDisaster Prevention Research Institute, Kyoto
5

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

University, Vol. 29, Issue B-2, 1986, pp.343–
359 (in Japanese).
[4] Hashimoto H., Tsubaki T. and Hirano M.,
Sediment Gravity Flow on Relatively Gentle
Slopes. Annual Journal of HydraulicEngineering, Japan Society of Civil Engineering,Vol. 30, 1986, pp.235-240 (in Japanese).
[5] Egashira S., Mechanism of Sediment
Deposition from Debris Flow (Part 1). Journalof the Japanese Society of Erosion Engineering,Vol. 46, Issue 1, 1993, pp.45-49 (in Japanese).
[6] Egashira S., Mechanism of Sediment
Deposition from Debris Flow (Part 2). Journalof the Japanese Society of Erosion Engineering,Vol. 46, Issue 2, 1993, pp.51-56 (in Japanese).
[7] Egashira S., Sato T. and Chishiro K., Effect ofParticle Size on the Flow Structure of SandWater Mixture. Annuals of Disaster Prevention
Research Institute, Kyoto University, Vol. 37,
Issue B-2, 1994, pp.359–369 (in Japanese).
[8] Egashira S., N Honda. and Miyamoto K.,

Numerical Simulation of Debris Flow at the
Gamaharazawa in the Hime River Basin.
Annual Journal of Hydraulic Engineering, Japan
Society of Civil Engineering, Vol. 42, 1998,
pp.919-924 (in Japanese).
[9] Japan Society of Civil Engineering, theJapanese Geotechnical Society, Japan Society ofEngineering Geology and the JapaneseLandslide Society, Investigation Report of
Heavy Rainfall Disasters caused by Typhoon
No. 26 in Izuoshima in October 2013, 2014, pp.
1–90 (in Japanese).
[10] Japan Society of Erosion Control Engineering,
Urgent Investigation Report of the sedimentrelated disasters caused by the 2016 Kumamoto
Earthquake, 2016, 81pp (in Japanese).
[11] Egashira S., Honda N., Itoh T. and Arimura S.,
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pp.645-650.

6

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

MECHANICAL PROPERTY OF CHLOROPRENE BEARING PAD FOR
BRIDGE UNDER CYCLIC TEMPERATURE CHANGE
Hidenori Tanaka1, Kazuki Kurosawa2 and Masatake Yoshino3
Civil Engineering, Gunma National College of Technology, Japan; 2,3 Former student, Japan

1

ABSTRACT
Rubber materials are very indispensable to keep infrastructure safe against earthquakes. In Japan, these arenormally used to support the structures (bridges, buildings). Generally speaking, They are non-compressive andhyper-elastic material so that the mechanical properties of them have not been clarified sufficiently into designcodes. Based on this, we conducted simple compressive creep and thermal fatigue tests by using cylindrical
specimens (the diameter is 80mm, the height is 80mm) made of chloroprene rubber as a bearing pad for bridge.
We pressed the specimen to equivalent forces which are equal to the serviceability state. We have kept them andset into freeze-thaw test machine. And then, we applied cyclic temperature change (from -10 to 3 Celsius)
Finally, we have compared the creep properties at normal temperature with those of cyclic temperature change forseven months. We found that the elastic damage would be occurred in proportion to cyclic numbers.
Keywords: Chloroprene, Irreparable creep, Cyclic temperature change, Fatigue, Finite displacement theory

The quasi-compressive loads were applied on thecylindrical specimen ( φ 80mm, H=80mm) withupper and lower steel plates (refer Fig.1).
Figure 2 shows the relationship between applied
loads and longitudinal displacements.
In this test, The applied loading speed was
10mm/minute.

INTRODUCTION
Seismic isolation rubber has been used for bearing
pad of bridges and buildings. The isolated effectwould be dependent on the horizontal deformation ofrubber under earthquakes. There were many
experiments to evaluate the horizontal deformation
without considering axial (vertical) mechanicalproperties
which are creep, visco-plasticity andthermal fatigue .
Rubber is usually non-compressive and nonvolumetric material. So, if there is residual
deformation caused by vertical inelastic behavior
such as creep or visco-plasticity. The horizontal
deformation is restricted. And, the isolated effectwould become smaller. On the top of these, The
inelastic behavior including large displacement will
be occurred even though the applied loads are small.
Finally, it is very important to take into account of
the isolated effect due to inelasticity of rubber.
Rubber also has a great influence on temperaturechange. Especially, the mechanical property causedby thermal fatigue has not been cleared sufficiently.
Therefore, we have conducted simple compressive
creep and thermal fatigue test under cyclic lowtemperature change using chloroprene specimen [1].
In this study, we show the numerical analysis ofcompressive deformation by Ogden’s model that isthe basic theory to explain large displacement
behavior in two dimensional axisymmetric problem
comparing with the result of experiment [2].

Fig 1. Deformation of rubber (compressive test)

COMPRESSIVE TESTThe load-displacement curve

Fig.2 Loads-displacements curve
7

SEE - Nagoya, Japan, Nov.12-14, 2018

The curve was typical compressive behavior andshowed the strong non-linearity after the applied
loads passed 10 (kN) [3].

We set the specimen into the freeze-thaw test
machine to evaluate the affection by cyclic
temperature change for seven months at theserviceability state .

Compressive creep test
We conducted the Compressive creep test as
follows. At first, we measured the displacements andapplied loads until serviceability state which was
supporting the self-weight of bridge girders. Secondly,
The stresses have been holding for seven months to
fix securely upper steel plate by four bolts with nuts
at the corner (refer to Fig.3).
Finally, we measured the displacements again after
stresses were released unfastening the bolts and nuts
(refer to Fig.4). We could evaluate non-linear statethat including unloading elasticity, delayed elasticity
and irreparable creep to describe the deformation
curve after the stresses were released.
We determined serviceability state to consider
relationship between real chloroprene pad section
area and girders weight.
The red point in Fig.5 was equivalent to theserviceability state ( Load (P)=5.5 (kN)).
This point was approximately within linear state .

P=5.5 (kN)Fig.5 Serviceability state (red point)

Fig.6 Specimen at serviceability stateFig.3 holding stress (serviceability state)Fig.7 Freeze and thaw test machine
The specimen was shown in Fig.6. We checked thecreep properties of the specimen at normal
temperature and under cyclic temperature change
which indicated the mean temperature of winter in
Tohoku area. We determined the change period byspecified machine property as long as we could.

Fig.4 Releasing stress8SEE - Nagoya, Japan, Nov.12-14, 2018

The freeze-thaw test machine was shown in Fig.7.
The applied temperature change was shown in Fig.8.
The maximum and the minimum temperature were+3 ,-10 Celsius respectively.

curves were similar like ellipses.
So , Each curve was approximately represented as
ellipses.
Figure 12 indicated the strain energy which was
equivalent to the area of ellipse responding to cyclic
numbers.
The energy of 500 cycles or after has been
decreasing proportional to cyclic numbers. We
considered that the energy was one of the indexes toevaluate the damage caused by thermal fatigue.

Fig.8 Temperature change

Fig.10 Set the strain gauge

Fig.9 Irreparable creep properties
The curve after releasing stresses indicated creep
characteristics (refer to Fig.9). This curve was mainly
consist of three parts. The sharp descending line near
0 (hour) was unloading elasticity, by 80 (hours) it
showed delayed elasticity, and after 80 (hours) it
showed irreparable creep, respectively.
Even though the holding times were less than for ayear , it was found that the irreparable creep reachedabout 20 % of total displacement. In addition, The
creep would be occurred under the small load that was
equal to serviceability state.
‘Normal’ showed the result at normal temperatureand ‘Change’ showed the result of that the cyclic
number reached 3,200 in Fig.9. It was found that
there were not much difference about creep properties
between two curves.

Fig.11 Hysteresis curves by 500 cycles

FATIGUE TEST
Hysteresis curves
The strain gauge was set the middle of specimen toevaluate the damage or deterioration caused by cyclic
temperature change (refer to Fig.10).
Figure 11 showed the relationship between
principal strain and temperature change . The plasticstrain was increased by 500 cycles. These hysteresis

Fig.12 Relationship strain-energy and cyclic numbers

9SEE - Nagoya, Japan, Nov.12-14, 2018

ｘ
X
F : Deformation gradient tensor

Equivalent thermal expansion coefficient changeF

We focused on the equivalent thermal expansion
coefficient (ETEC) change derived from hysteresis
curves , because the value was closely related withdamage by thermal fatigue [4].
We defined ETEC as the linear gradient whichshown the average gradient of ellipses (refer toFig.13).

(1)

ｘ : infinitesi mal line element vector (after deformation)
X : infinitesi mal line element vector (beforedeformation)

Green-Lagrange strain tensor
The strain should be described more than second
rank orders to apply this analysis. Green-Lagrange
strain tensor was reasonable for variational principle[7].

1 dｘ 2  dX 22
dX 2
u j u k u k 
1  u  i 
2  X j X i X i X j 
E : Green  Lagrange strain tensor
E

ETEC

(2)

u i , j , k : displacement
Fig.13 ETEC of hysteresis curve

The Second Piola-Kirchhoff stress tensor
This stress tensor is the best expression
corresponding to the Green-Lagrange strain tensor.
And then, This form is useful formulation in analysis
because of the symmetric form[5].

S  JF1 σ FT(3)

S : second Piola  Kirchhoff stressJ : det(F)F1 : Inverse tensor ofT

F : Transpose of

Fig.14 Relation ETEC and cyclic numbers

FF

σ : Cauchy stress tensor

We showed relationship between ETEC andcyclic numbers in Fig.14.
ETEC was decreased due to cyclic numbers. So,
we found that ETEC was one index to evaluate thedamage by cyclic temperature change.

Ogden’s model
Strain energy function has been used to analyze thelarge deformation of rubber under various loads.
Moony-Rivlin and Neo- Hooke models are popularfunctions for analysis. But, these models are
inadequate for nonlinearity in high strain region. So,
here, we adopted Ogden’s model to simulate highnonlinearity region in analysis[8].

NUMERICAL ANALYSIS
Base of finite displacement theory
Rubber has generally large deformation undercompressive loads. So, There are some limitations toapply the infinitesimal deformation theory.
The deformation gradient tensor has been used todescribe the mechanical properties of rubber. For
example, Cauchy stress , Green strain tensor[5].
In this paper, The deformation gradient tensor was
defined as follows[6].

n (1  2  3  3)n 1  n
W : strain energy function
 n ,  n : material constant1 , 2 , 3 : principal stretch ratio
N

W 

10

n

n

n

(4)

SEE - Nagoya, Japan, Nov.12-14, 2018

In this paper, we considered third rank (N=3). The
material properties were shown in Table.1.
Table.1 Material properties
Constant valueαμFirst rank

α1=1.3μ1=1.491 (N/mm2)

Second rank

α2=5.0μ2=0.003 (N/mm2)

Third rank

α3=-2.0μ3=-0.0237(N/mm2)

Results of deformation analysis
We carried out two dimensional axisymmetricanalysis considering the shape of specimen [2].
Therefore, The analysis area was half model.
Figure 15 showed the deformation and theequivalent stress distribution .

Fig.16 Thermal distributions

We have carried out the freeze and thaw test
keeping the deformation of rubber at serviceability
state. So, In this analysis, the compressive final
deformation was the initial form .
For example, Figure 16 showed the thermal
distributions when the temperature reached 0 from
-10 ℃. The center line was heat insulation and theothers of model were heat transferable borders. The
material properties were shown in Table 2.
Table 2 Thermal properties

Fig.15 Deformation and equivalent stressSpecific heat

1.65 (J/g・K)

Specific gravity

1.39

Heat transfer

14 (W/m2℃)

coefficientEquivalent stress was defined in equation (5).

 eq  3 J 2'

Thermal distributions was changed in about four
degrees from the surface to the center of rubber. The
model was also half considering axisymmetric.

(5)

 eq : Equivalent stress(N/mm2 )CONCLUSION

J 2' : Second invariant of deviatric stress

The knowledge found in this research are as below.
The irreparable creep is occurred under theserviceability state even though the elapsed time is
only for seven months. And this value is about 20 ％of total displacement. This means that the 20 ％of
total deformation energy is dissipated by creep.
About thermal fatigue, The equivalent thermal
expansion coefficient as well as the strain energy
provides the indication of damage caused by thermal
fatigue. Because the relationship between bothparameters and cyclic numbers are closely similar.
Specially, The equivalent thermal expansion
coefficient will be approximately linear and reduced
about 15 ％ comparing with the initial value. This
reduction shows damage quantitatively.

We adopted the displacement control method.
The equivalent stress distribution was typical forcompression state. The highest stress was distributedat the corner of specimen which was contacted withsteel plates (upper and lower). The maximum
equivalent stress was approximately 0.6 (N/mm2).
Unsteady thermal conduction analysis
The unsteady thermal analysis is simulated undercyclic temperature change (refer to Fig.8). This ispreliminary step to check the evolution of viscoplastic and damageable properties of this pad undercyclic temperature change [9].

11SEE - Nagoya, Japan, Nov.12-14, 2018

After the thermal fatigue test, the irreparable creep
value is almost same result at normal temperature.
From these results, we found that the thermal fatigue
damage in this case is elastic.
From the results of simulation, we found that the
maximum equivalent stress at serviceability state is
distributed at the corner of specimen which iscontacted with steel plates. The damage also would
be distributed same parts. And then, There are only
four degrees difference from surface to center by the
conduction analysis. Second Piola-Kirchhoff stressand Green-Lagrange strain tensor are suitable
expression for large displacement problem of rubber.
Finally, as the next stage, we have a plan to adopt
F-bar method that is the popular numerical way todescribe elasto-viscoplasticity of rubber . And, wewould like to analyze the thermal fatigue behavior
keeping serviceability state under cyclic temperature .

[2] EA de Souza Neto, D Peric, DRJ Owen,” Nonlinear finite element method”, June, 2012.
[3] Hisanari Uruta, Kazuhiko Kawashima etal ,“Evaluation of stress-strain relation for a rubber
rectangular shock absorbing device under an
extreme compression stress”, Journal of JACE,
No.661,Oct,2000,pp.71-83.
[4] Masakazu Takagaki, Tutaka Toi,” Thermal
Fatigue Analysis of Toroidal Cracks by Local
Approach to Fracture,2005,3C01[5] Takashi Kyoya,”Continuum Mechanics ”,Japan
Association for Non-linear CAE,Dec,2008[6] Shigeru
Kuranishi,”Introduction
toMathematical
ModelsofMaterial
Characteristics”, Subcommittee of Structural
Mechanics Committee of Structural Engineering,
J.S.C.E.,Aug.,1989[7] B.R.Seth, “Generalized strain measure withapplications to physical problems”, IUTAM
Symposium on Second Order Effects in
Elasticity, Plasticity and Fluid Mechanics, 1962,
pp. 1-14.
[8] R.W.Ogden,D.G.Roxburgh, “A pseudo-elastic
model for the Mullins effect in filled rubber”,The
royal society, 1999, pp. 2861-2877.
[9] Hidenori Tanaka, Fimiyasu Makinoshima,”The
adhesive characteristic of concrete block withfiber sheets under cyclic temperature”,
International Conference on the Regeneration
And Conservation of Concrete Structures
2015,I-17

ACKNOWLEDGEMENTS
The author appreciates Tokyo Fabric Co.,Ltd forproviding the chloroprene specimens. And, ResearchCenter of Computational Mechanics, Inc. forsupporting two dimensional unsteady thermal
conduction analysis.
REFERENCES[1] Yoichi Yuki, Hiroki Tamai et al, “Fundamental
experiment of shape and confining effect onrubber pieces’ cushioning characteristics”,
Journal of structural engineering, Vol.61A,
March,2015, pp. 313–321.

12

SEE - Nagoya, Japan, Nov.12-14, 2018

Technical Papers

13SEE - Nagoya, Japan, Nov.12-14, 2018

Science14

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECT OF OKRA AND TANGERINE RATIOS ON PRODUCTION OF
MIXED JUICE WITH LYCOPENE SUPPLEMENTATION
Wattana Wirivutthikorn
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi (RMUTT) 2
Phaholyothin 87 Soi 2 Phaholyothin Road Thanyaburi Pathumthani 12130 Thailand

ABSTRACT
Thailand has many herbal plants. The major advantage is that there are good bioactive ingredients andantioxidants that are beneficial to the body are possible when used as a drink. There are research reports related
to the production of various Thai herbal drinks and fruits such as okra and tangerine were used as raw materials.
The objective of this research was to study the optimum ratios of okra and tangerine with lycopene
supplementation on Thai herbal beverage production. Four ratios of okra and tangerine were performed into 4experiments; Experiment 1: (control formula) okra juice: tangerine juice 50:50 ratio; Experiment 2: okra juice:tangerine juice 60:40 ratio; Experiment 3: okra juice: tangerine juice 70:30 ratio; Experiment 4: okra juice:tangerine juice 80:20 ratio. Physical properties, i.e. L*,a*,b* and turbidity showed that all experiments weresignificantly different except for L* and a* value. Chemical properties, i.e. pH, percent of total acidity and totalsoluble solid revealed that all experiments were statistically significant differences. (P<0.05) Sensory evaluation
was done by using 9-points hedonic scale. The results indicated that Experiment 1 had the highest scores of
sensory acceptance. From the information obtained, the formulation of beverages produced from Thai herbal andfruit can be developed to be accepted by consumers, which has increased steadily and expanded in the large
future level in beverage industry.
Keywords: Okra, Tangerine, Juice, Lycopene, Supplementation

mandarin orange. It is a good source of vitamin C,
folate and -carotene. It also contains somepotassium, magnesium, vitamins B1, B2, and B3 [3].
There are some researches about blended okra, gac
fruit and passion fruit juice to produce Thai herbal
drink. The result found that the different ratios of
okra, gac fruit and passion fruit had influence on
consumer acceptance [4]. For this reason, of okra
and tangerine benefits, the researchers are interested
in producing water-based okra and tangerine withhealthy drink by studying appropriate amounts ofokra and tangerine ratios with lycopene
supplementation which help with the quenching ofthirst and help relax or make the body. The dataobtained from this research was an alternative to
make okra and tangerine as raw materials forbeverage production to improve the nutritional
quality and good health of consumers. The purposeof this research was to study the appropriatequantities of okra and tangerine ratios withlycopene supplementation for the development ofbeverage products.

INTRODUCTION
Nowadays, health drink products enroll a greaterrole in everyday life. Most of the health drinks arederived from the ingredients of plants or herbs to beprocessed to meet the needs. Some consumers may
not consume vegetables. Some fruits or herbs due toodor, spicy or bitter taste. It is not very popular with
consumers. But because of the benefits of thevarious types of Thai herbal that can be processedin the form of health drinks, the benefits will bedifferent according to the properties of the raw
materials [1]. Okra is a popular health food due toits high fiber, vitamin C and folate content. It is also
known for being high in antioxidants have a goodsource of calcium and potassium and the mucilage
contains soluble fiber. Some people prefer tominimize the sliminess; keeping the pods intact, andbrief cooking. Some of the advantages of okra areaids in improving digestion, help to relax bloodvessels and arteries and protect heart against
clotting [2]. Tangerine is an orange-colored citrus
fruit that is closely related to, or possibly a type of15

SEE - Nagoya, Japan, Nov.12-14, 2018

Technology Thanyaburi (RMUTT), Thailand.
Panelists was asked to analyze their level ofpreference for each treatment using a 9-point
hedonic scale test based on the attributes of color,
odor, taste, sediment and overall liking. A
randomized complete block design was used withanalysis of variance. Analysis of the meandifferences of experiments was performed using
Duncan’s new multiple range test [10].

MATERIALS AND METHOD
The research was carried out at the Faculty ofAgricultural Technology, Rajamangala University ofTechnology Thanyaburi. (RMUTT) Pathumthani
Province Thailand. The samples used in this study
were purchased from Rangsit Market Pathumthani
Province Thailand.
Okra Preparation

RESULTS AND DISCUSSION

The okra was washed and cut into small pieces

Physical measurement

and boiled in hot water for 15 minutes. Okra
samples were dried by using hot air oven at 75 C

The values of L, a* and b* and physicalfor 3 hours [5].

appearance depending on different ratios of okra andtangerine [11]. The results showed that b* and %T

Tangerine preparation

value had differences (P <0.05). For L* value, it was

The tangerine was washed with clean water andslice into thin small pieces as 2.1 and peeled theirs
to juice with fruit juice extractor. The blended
aliquots were placed in clean container [6].
This was performed as four experiments (tworeplications): 1) blended okra and tangerine juice
50:50 (the control); 2) blended okra and tangerine
juice 60:40; 3) blended okra and tangerine juice
70:30 and 4) blended okra and tangerine juice 80:20.
The ingredients were detailed in Table 1 [6].

found to be decreasing compared to control samples.
Because of the increase in okra juice which gavedark brown color. For a* value, they were found to
be decreasing compared to control samples. Due tothe reduction of tangerine juice revealed orange
yellow color. For b* value, they were found to be
decreasing compared to control samples (the same as
a* value). Due to the increasing of okra juice

Production of okra and tangerine juice withlycopene supplementation

indicated green color.

For percent of transmittance,clarification value increased with comparison to

The blended dried okra and tangerine juice wereplaced in a stainless steel pot (3 liters of clean water)and heated to 50°C. for 15 minutes, then, filteredthrough a cloth. Addition of some detailed
ingredients followed as Table 1 [5], [6].

control samples. The Experiment 4 gave the highest
value, while the Experiment 1 gave the lowest value.
Possible reasons were that the reduction of tangerine
juice contained pulp could be affected on the cause

Physical Measurementof turbidity [12].
Brightness (L*), color as red (a*) and yellow(b*) and the clarification value measured aspercentage of transmittance (%T) were recorded as
adapted from [8].

Chemical measurement

Results, pH values depending on different ratios

Chemical Measurementof okra and tangerine, there was a tendency towards

The pH, percentage of total acidity and the totalsoluble solids (TSS) were measured as adapted from[9].

increased acidity and alkalinity when compared tocontrol samples due to the reduction of tangerine
juice. In tangerine juice contains of citric acid, it has

Sensory Evaluation

an increased amount of acidity and alkalinity [13].

The sensory evaluation was carried out by 30
untrained panelists in Rajamangala University of

For total soluble solid values showed that there was
16

SEE - Nagoya, Japan, Nov.12-14, 2018a tendency of decrease compared to the control

samples. The taste indicated that all experiments

sample due to the reduction of tangerine juice.

were sweet and sour. Due to the taste adjustment

Organic acids, i.e., citric acid naturally occurring inwith same amount of sugar and citric acid [17].

many foods including citrus, such as orange andTable 1 Optimum ratios of okra juice and tangerine withlime reduces low total acidity values. [14].

lycopene supplementation [17].
Ingredients (g)Sensory evaluationokra juice
tangerine juice
lycopene
sugar
salt
citric acid

The results of the sensory analysis showed that
there were differences in all experiments. (P < 0.05)
When considering the average all score tests,
Experiment

1

was

the

most

acceptable

Experiment no.
1

2

3

4

300
300
0.1
40
1
0.3

360
240
0.1
40
1
0.3

420
180
0.1
40
1
0.3

480
120
0.1
40
1
0.3

Table 2 Physical measurement of blended okra juice
and tangerine juiceincomparison to other experiments. One possible

Experiment

Physical value

reason might be due to the proportion of okra andsmell of okra, which is a smell that consumers did
not like. As a result, the characteristics of color,

%T*

1

L*ns
27.88

a*ns
9.89

b*
1.79a

15.53d

2

24.74

9.56

0.85a

22.63c

9.26

0.84a

26.47btangerine was equal. Tangerine juice can reduce the

23.12

3

22.33
7.44 -3.35b
30.67a4
a-d The different letters in the same column meansignificant difference (P < 0.05) ns non significant
difference (P>0.05)

smell, taste, sediment, and overall acceptance,
received the highest scores [15].

Physical appearance

Table 3 Chemical measurement of blended okra juice andtangerine juice
Chemical value

From the Fig 1, the images could be seen that

Experimentsignificantly different. As a result of the ratio of

1

3.81c

Total acidity(percent)*
3.41aokra juice and tangerine juice. When considering the

2

3.97b

2.56b

11.90bappearance, it was found that all the experiments

3

3.99b

1.92c

11.00cwere suspended, which is the pulp of tangerine,

4

4.16a

1.28d

10.70dthe red color in all experiments were

pH*

not

Total soluble solid(Brix)*13.00aa-d The different letters in the same column meansignificant difference (P < 0.05)

which is derived from tangerine. When considering
the color, revealed that all the samples were reddish
orange as the color result of the lycopene [16]. The

Table 4 Mean score of preference for sensory propertiesof okra and tangerine juice

color is yellow, orange, red and orange - red. Okra

Experimentand tangerine consist of three pigments (chlorophyll,

Scores*color*

odor*

taste*

sediment*

1

7.37a

7.40a

7.50a

7.17aboverallliking*7.40a

different chemical compositions and structures such

2

6.70

b

a

7.27

a

7.50

7.47a

7.30a

as carotenoid in tangerine, chlorophyll in okra and

3

6.90b

6.53b

6.43b

6.87bc6.60blycopene supplementation. The odor will vary with

4

6.73b

6.47b

6.20b

6.63c

6.33b

carotenoid and lycopene) were quite distinct anda-d The different letters in the same column meansignificant difference (P < 0.05)

the amount of increased okra juice and the decreaseamount of tangerine juice which compared to control

17

SEE - Nagoya, Japan, Nov.12-14, 2018

ACKNOWLEDGEMENTS
The researchers would like to thank the 4 th
students and personal officials of Division of Food
Science and Technology, Faculty of Agricultural
Technology Rajamangala University of Technology
Thanyaburi (RMUTT) Pathumthani Thailand that
contributed some part in the research. We would
also like to thank the Faculty of Agricultural
Technology for their support facilities and budgets
E1

E2

E3

E4

on our research and travel expense for thisconference.

Fig. 1 Product of different ratios of okra blended
with gac fruit and passion fruit.
E1: okra: tangerine juice 50:50 (control
experiment)
E2: okra: tangerine juice 60 :40
E3: okra: tangerine juice 70:30
E4: okra: tangerine juice 80:20

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[13] Rebecca, L,J., et al., Extraction and purificationof carotenoids from vegetables, Journal of Chemicaland Pharmaceutical Research, Vol. 6, 2014, pp. 594598.
[14] Wirivutthikorn, W. and Jenkunawatt, S., Colordifferences of okra blended with green tea powder
on consumer acceptabilities, ACA 2016 The 3 rdInternational Conference of Asia Color Association,

19

pp.

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

OPTIMAL RAIN GAUGES NETWORK USING GEOSTATISTICS ANDHYBRID PARTICLE SWARM-SIMULATED ANNEALINGOPTIMIZATION
Mohd Khairul Bazli Mohd Aziz1, Fadhilah Yusof2, Zalina Mohd Daud3, Zulkifli Yusop4, Mohammad Afif
Kasno5
1
Faculty of Industrial Sciences & Technology, Universiti Malaysia Pahang, Malaysia,
2
Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, Malaysia,
3
UTM Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia, Malaysia,
4Institute of Environmental and Water Resource Management (IPASA), Faculty of Civil Engineering,
Universiti Teknologi Malaysia, Malaysia, 5Department of Electronic & Computer Engineering Faculty
Universiti Teknikal Malaysia, Melaka, Malaysia.

ABSTRACTAn optimal design of rain gauge network is important as it produces fast, accurate and important rainfall data
which can be used to design an effective and economic hydraulic structure for flood control. In this paper,
geostatistical method integrated with hybrid of particle swarm optimization-simulated annealing is proposed todetermine the optimal number and location of rain gauge network. This paper considers the repositioning of theexisting rain gauge into new locations to improve its effectiveness and accuracy. The analyses of daily rainfall
data, latitude and longitude of the rain gauge location, elevation, humidity, wind speed, temperature and solar
radiation reveal that the proposed method is successful in providing the optimum number and location of thestations. It also indicates that the repositioning of all rain gauge stations to new locations would provide better
results in terms of the estimated variance value but, is not cost effective due to its expensive costs.
Keywords: Rain Gauge Network, Geostatistics, Particle Swarm Optimization, Simulated Annealing

technique in combination with other techniques suchas entropy [3] and multivariate factor analysis [7] forthe network design. A few studies also combined
optimization method based on simulation tools (e.g.
simulated annealing) with the kriging technique [2],[8],[9] to obtain the optimal rain gauge network.
A network design methodology was developed inthis paper to determine optimal number and locationsof the existing stations in the current rain gauge
network located in the Johor state, Malaysia is basedon geostatistical and hybrid of particle swarm
optimization-simulated annealing (PSO-SA) as an
optimization method. The basic idea of the hybridalgorithms study in this paper is simply based onrunning PSO algorithm first and then improving theresult by employing a SA. The major contribution
here is that unlike the work of [2], the developed
methodology considered the hybrid of PSO-SA
technique as an optimization method which capableof escaping from a local optimum with a fast
convergence.

INTRODUCTION
A reliable and optimal rain gauge network canprovide accurate and precise rainfall data as rainfall
data are employed in numerous water resourcesmanagement tasks such as water budget analysis andassessment, flood analysis and forecasting,streamflow estimation, and design of hydraulicstructures. Good rainfall data will help the researchers
to minimize the hydrological and economic risk anderrors involved in different water resources projects.
A well-designed rain gauge network thus should
contain a sufficient number of rain gauges, whichreflect the spatial and temporal variability of rainfall
in a catchment [3].
Thus, identification and selection of the optimalrain gauge network configuration with optimal
number and locations of rain gauge stations is themain objective of the network design. Hence, theoptimal rain gauge network should contain thenumber and locations of rain gauge stations in such a
way that it can produce optimum rainfall informationand data with minimum uncertainty and cost [2]-[4].
One can approach the problem either by removing
redundant stations from the network to minimize thecost or by expanding the network with installation of
additional stations to reduce the estimation
uncertainty [5]. Some studies applied the kriging

STUDY AREA AND DATA DESCRIPTION
Johor is the second largest state in the Malaysia
Peninsular, with an area of 18,941 km2. The
catchment area contains a dense rain gauge network,
84 rain gauges covering 19,210 km2 in Johor (see20

SEE - Nagoya, Japan, Nov.12-14, 2018

Figure 1). The current overall network density for thewhole of Johor state is about 194 km2 per gauge,
which surpasses even the ideal WMO
recommendation of one gauge per 600 – 900 km2 forflat areas. In fact, it also fulfills the ideal density for
mountainous region of 100 – 200 km2 per gauge. The
data used to perform the analysis was from the daily
rainfall data, latitude and longitude of the rain gauge
location, elevation, humidity, wind speed,
temperature and solar radiation from November until
February of 1975 through 2008 from 84 rain gauge
stations that are located all over Johor obtained from
Department of Irrigation and Drainage (DID)
Malaysia and Malaysia Meteorological Department(MMD).

a sampling of size N. Then the following expression
is an unbiased estimator for the semivariogram of therandom function: h  n h 
2
 Z xi  h  Z xi2nh  i11  

(1)

Equation 1 is used to compute experimental
semivariogram from the data under study. Bychanging h, both in distance and direction, a set of thesample (or experimental) semivariograms for the data
is obtained [10].
The exponential semivariogram models are
selected to fit the data. The exponential
semivariogram model equation is as follow: 3h  h   C  1  e a 

(2)




where C is the sill and a is the range.
Once the model of the semivariogram is fixed, theestimation variance only depends on the number N
and the location of the rain gauges. To calculate theestimation variance using ordinary kriging,2

x0   2ik1i xi , x0   ik1 jk1 i  j xi , x j 

(3)

Where

 

!H

Rain Gauge Station
River
Mountain

Fig.1

 

k
Zˆ x0   i Z xi
(4)
i 1
k
Subject to  i  1 .
i 1This is an algorithm for the ordinary kriging
estimation to calculate the estimation variance [13]:1. Calculate each term in matrix G.
Let xi ’s be the sampling sites of a sample subset

LegendRain gauge locations

METHODOLOGY

Geostatistical Methodof size k , i  1,2, , k and let  xi , x j ’s be the

The network design problem consists in obtaining
the number N and the location of rain gauges stations
that give the best estimate areal mean rainfall. The

experimental variogram. Then the G is the matrix  x1, x1   x2 , x1    xk , x1  1  x , x   x , x    x , x  1 
2 2
k 2
 1 2

G 




 x1, xk   x2 , xk    xk , xk  1 
 1
1
1
0 


estimation variance  is a basic tool of variancereduction techniques for optimal selection ofsampling locations. For the application of thevariance reduction method to optimal location ofsampling sites, a semivariogram must be modelled.
A semivariogram,  h  is one of the significant
functions to indicate spatial correlation in
observations measured at sample locations.
Semivariogram is represented as a graph that shows
the difference in measure with distance between all
pairs of sampled locations. The estimated variancedepends on the semivariogram model, the number N
of rain gauges and its spatial location. Therefore,choosing an appropriate semivariogram model is vitalin determined the optimal estimation variance.
Let h be the lag or distance, and Z be an intrinsic
random function and let Z xi , for i  1,2, , N be2(5)

2. Calculate each term in matrix g.
Let x 0 be the estimation location, then the g is thematrixg   x0 , x1   x0 , x2    x0 , xk  1 (6)3. Solve the system of equations
GW  g , W  gG

1,

Where W  1 2  k

21




 .

SEE - Nagoya, Japan, Nov.12-14, 2018

4. Calculate the ordinary kriging estimation variance

2

x0   g W  g G 1g.

6. Loop to Step 2, until criterion is met, usually asufficiently good fitness or a maximum number of
iterations (generations).

(7)

Simulated Annealing
Partical Swarm Optimization
Annealing is a family of techniques for creating
metals with desirable mechanical properties. The SA
technique originates from the theory of statisticalmechanics and is based upon the analogy between theannealing of solids and solving optimization problem.
SA was first introduced by Kirkpatrick and Vecchi[6].
Basic SA algorithm:
1.
Select an initial solution x and initial

PSO was developed by Kennedy and Eberhart,[12] in 1995, inspired by the social behavior of bird
flocking. The movement of each swarming particle isdetermined by a combination of a stochastic element
and a deterministic element, [1]. A population(swarm) of particles is initialized in an n-dimensional
search
space
in
which
each
particlexi  xi1, xi 2 , , xin represents a possible solution.



temperature T0 , set k  0 . Set x  x0 , xˆ  x0 .

Each particle is aware of its current position, its own
personal best position, its current velocity and thesingle global (or local) best position. The global best
position is represented as gi  gi1, gi 2 , , gin and



symbolizes the best position of all particles in the
population (swarm). The personal best position
represents the best position found by a particle so far
and is denoted as pi  pi1, pi 2 , , pin .

The velocity vi  vi1, vi 2 , , vin  gives the

xi  xi  vi



3.

If

4.

  0or  0and   U 0,1 then accept the new
solution x and set x  x . Else keep x.
If F  x   F  xˆ  , then set xˆ  x and  / Tk 

Tˆ  Tk .

position change of a particle. In the original proposed
PSO of Kennedy and Eberhart, the new velocity foreach particle is calculated according to Eq. (8). To
update the new position of each particle, Eq. (9) is
used:



Choose a solution x in N(x) and compute  F  x   F  x e

vi  vi  c1.r1. pi  xi  c2 .r2 . g  xi

2.

5.
6.

If some stopping criteria are satisfied, stop.
Update the temperature Tk 1  g Tk  Tk , 

set k  k  1 and go to step 2.

Hybrid of Particle Swarm Optimization and
Simulated Annealing(8)

The basic idea of the hybrid algorithms study inthis research is simply based on running PSO
algorithm first and then improving the result by
employing a simulated annealing. As we know, themost significant character of SA is the probabilistic
jumping property, i.e. probability to accept a worse
solution to be a new solution. Therefore, throughintegration of SA to PSO, the proposed algorithm iscapable of escaping from a local optimum with a fast
convergence. Based on the PSO and SA
characteristics, the whole procedure of PSO-SA isdescribed as follows:
1. Initialization:
1a. Randomly initialize the x particles representing
different combinations of N rain gauge
placements.
1b. Evaluate each particle in the population using
the fitness function in Eq. (7) and minimum
fitness function is set as pbest.

(9)

where i  1,2,, N , with N as population size. c1
and c 2 are two positive constants; r1 and r2 are two
random numbers with range (0,1).
The original version of PSO is as follows:
1. Initialize a population (swarm) of particles withrandom positions and velocities on d dimensions
in the problem space.
2. For each particle, evaluate the desired
optimization fitness function in d variables.
3. Compare particle’s fitness evaluation withparticle’s pbest. If current value is better thanpbest, then set pbest value equal to the current
value and the pbest location equal to the current
location in d-dimensional space.
4. Generate new particles from the neighbourhood.
Compare fitness evaluation with the population’s
overall previous best. If current value is better
than gbest, then reset gbest to the current particles
array index and value.
5. Change the velocity and position of the particle
according to Equations 8 and 9 respectively.

1c. Set all parameters, including c1 and c 2 , vmax ,initial temperature T0 , cooling rate α.
2.

22

Repeat this step until the stopping criterion issatisfied:

SEE - Nagoya, Japan, Nov.12-14, 2018k
 i  1i 1
xj  pj

2a. Evaluate velocity and position of each particle
by Eq. (8) and Eq. (9).
2b. Calculate the fitness of each particle, x .
2c. Calculate  = f  x   f  x  and then randomly

generate a number   0,1 . If   0 , as theobjective is to minimum, meaning that the newposition is improved, then the new position is
accepted as the new position of particle i.
Otherwise, new position is accepted accordingTk
to the following criterion:   e. Proceed tostep 2d when the velocity of all particles are
determined, or return to step 2a for thoseparticles failing to be accepted. And generate
new velocities using the same evaluation
process.
2d. Renew each particle to the new velocity andposition and modify gbest and pbest by simple
comparison of their fitness values.
2e. When the evolution process has achieved astopping criterion (or maximum iteration isreached), proceed to step 3, otherwise, modify
the annealing temperature and return to step 2.
Output the best solution gbest and its fitness
value. The output is the optimal number and locationof stations with the minimum estimated variance.

where


 3h  h   C 1  e a 1, if a rain gauge is placed at a point 𝑗
𝒙𝒋 = {
0, otherwisep  number of rain gauges relocated
RESULTS AND DISCUSSION
The variance reduction technique requires anappropriate semivariogram model that fitted theobserved
data.
Initially,anexperimental
semivariogram from the experimental data is derived.
Then, a functional semivariogram model is fitted tothe experimental variogram. The obtained
semivariogram model has essential information to be
used in kriging interpolation of observed data. Fitting
and selection of suitable semivariogram model can beaccomplished through the variogram modelling
technique. Once a proper semivariogram model isselected for the observed dataset, kriging is applied
for the generation of interpolated surfaces and theestimation of the corresponding kriging error. The
semivariogram model fitted to the experimental datais shown as in table below:

Optimization Procedure
The optimization model to determine the optimal
number and locations of rain gauge can be divided
into two different scenarios and formulated
mathematically as below.
1. The model for optimal number and locations of
the rain gauges:

Table 1
Exponential semivariogram model
NuggetSill
Range
0.939171.55681.05449

Minimize

2x   2  i hi 0     i  j hij 
k

k

i 1

i 1 j 1kWhen the semivariogram is successfully fitted tothe empirical rainfall data, the PSO-SA method isapplied to find the minimum objective function(equation 3) in order to get the optimum number andlocation of rain gauge stations. The optimization
technique done based on the steps mentioned earlier.
The results of the optimization process were shown in
Figure 1 and Table 2.

subject tok i  1
i 1
where



 3h 



Estimated Variance h   C  1  e a 

2. The model for relocating the rain gauges:
Minimizekk k2
  x   2  i hi 0    i  j  hiji 1i 1 j 1
subject to

 

 

1
0.95

0.9
0.85
0

20

40

60

80

100

Number of Stations

Fig. 2 Estimation variance versus number ofstations
23

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Estimated variance value with optimal
number of stations
No. ofNumber of

Estimated

RemovedIterations

Stations

Variance

Stations

Mediterranean and tropical zone need to be in the areaof 100-250km² each.
The PSO-SA algorithm is applied once again to
determine the optimal rain gauge location for the
scenario 1 and 2. The humidity, temperature, solar
radiation, wind speed and elevation data will help thealgorithm locates suitable locations for the rain
gauges.

Selected
50

62

0.8608

22

100

61

0.8607

23

500

59

0.8604

25

1000

59

0.860425

The new optimal rain gauge network
demonstrates that the high density of existing rain
gauge in Johor has been reduced by removing several
stations. Fig. 2 depicts that the estimated variancevalue decreased as the number of rain gauges
increased. This value approach optimal value when
the optimization process gives the number of optimalrain gauge stations. In Table 2, it is shown that the
optimal number of rain gauge stations is 59 stations
with estimated variance value 0.8604 is achieved
when the iterations is more than 500. The locations of
the 59 selected locations are as shown in Fig. 3 below.
From Fig. 3, most of the removed stations are
redundant stations that are unnecessary needed.

Fig. 4 Johor with grids
Table 4 shows the resulted estimated variance forboth scenarios. For scenario 1, the estimated variancevalue reduces when the removed stations werelocated into new optimal locations. This shows thatthe removed stations were able to improve theaccuracy of the network by placing it in an optimum
location. For scenario 2, the estimated variancedecreases lower than scenario 1 and previous
estimated variance. This shows that in order toachieve an optimal network with the existing stations,
all stations must be reorganized and relocated into
new locations. Elevation, temperature, wind speed,solar radiation and humidity data has help in
identifying the optimal locations in the discretizedJohor and the new locations of the restructured rain
gauge networks for both scenarios are as shown in
Fig.5. The PSO-SA algorithm managed to determine
a new site for each rain gauge stations.

LegendRetained stations+E

Removed stations

Fig. 3 Optimal locations for 59 selected rain gauge
stations.

Table 4 Estimated variance
Scenario 1
Scenario 2
Estimated Variance0.84730.7163After the execution of the optimization process,two scenarios were considered for the 25 removed
stations in Table 2.
 Scenario-1: Optimal positioning of 25 removed
stations to find their new optimal locations.
 Scenario-2: All 84 existing stations were reset into
new optimal locations
For the redesignation purpose of the network, thewhole study area is discretized into 250 square gridswith each unit equivalent to 100km² (Fig. 4). This is
in line with the criterion set by the World
Meteorological Centre [11] which stated that everyrain gauge in the mountain region of temperate,
24

SEE - Nagoya, Japan, Nov.12-14, 2018

REFERENCES[1] Yang, X. S., Enggineering optimization: An
introduction with metaheuristics applications.
Wiley Publications. 2010.
[2] Pardo-Igúzquiza, E. Optimal selection of number
and location of rainfall gauges for areal rainfall
estimation using geostatistics and simulated
annealing. Journal of Hydrology 210: 206–220.
DOI: 10.1016/S0022-1694(98)00188-7. 1998.
[3] Yeh, H. C., Chen, Y.C., Wei, C., Chen, R. H.,
Entropy and kriging approach to rainfall network
design. Paddy and Water Environment 9: 343–
355. DOI: 10.1007/s10333-010-0247-x. 2011.
[4] Kassim, A. H. M., Kottegoda, N.T. Rainfall
network design through comparative kriging
methods. Hydrological Sciences Journal 36: 223–240. DOI: 10.1080/02626669109492505. 1991.
[5] Mishra, A. K., Coulibaly, P. Developments inhydrometric network design: a review. ReviewsofGeophysics
47:
RG2001.
DOI:
10.1029/2007RG000243. 2009.
[6] Kirkpatrick, S., & Vecchi, M. P. (1983).
Optimizationbysimmulated
annealing. Science, 220(4598), 671-680.
[7] Shaghaghian, M. R., Abedini, M. J. Rain gauge
network design using coupled geostatistical andmultivariate techniques. Scientia Iranica 20: 259–
269. DOI: 10.1016/j.scient.2012.11.014. 2013.
[8] Barca, E., Passarella, G., Uricchio, V. Optimal
extension of the rain gauge monitoring network of
the Apulian regional consortium for crop
protection. Environmental Monitoring andAssessment 145: 375–386. DOI: 10.1007/s10661007-0046-z. 2008.
[9] Chebbi, A., Bargaoui, Z. K., Cunha, M. D. C.,
Optimal extension of rain gauge monitoring
network for rainfall intensity and erosivity index
interpolation. Journal of Hydrologic Engineering
16: 665–676. DOI: 10.1061/(ASCE)HE.19435584.0000353. 2011.
[10]Burrough, P. A. Principles of Geographical
Information Systems for Land Resources
Assessment. Clarendon Press, Oxford, pg. 147165. 1987.
[11]Guide to Meteorological Instruments andMethods of Observation, (WMO-No.8, Seventh
edition), WMO, Geneva, 2008.
[12]Eberhart, R. and Kennedy, J. A new optimizer
using particle swarm theory. In Proceedings of the
Sixth International Symposium on Micro
Machine and Human Science (MHS ’95), pages
39–43. IEEE Press, 1995.
[13]Olea, R. A. Geostatistics for Engineers and Earth
Scientists, Kluwer Academic Publishers, ISBN 07923-8523-3, Massachusetts, 2003.

Legend!.

Optimal stations+E

Relocated stations(a) Scenario 1

Legend!.

Optimal stations(b) Scenario 2
Fig. 5 New optimal locations for 84 rain gauge
stations
CONCLUSIONS
Combination of geostatistics methods and PSOSA as an algorithm of optimization can be used as aframework for rain gauge network design models as
it improves the existing rainfall network byminimizing the variance of estimation value. Overall,this study has illustrated that the geostatistics methodwith PSO-SA annealing can be used as the
optimization method to provide the solution indesigning an optimal rain gauges network system.
This optimal network also is essential in providing
better rainfall data. This model and methodology canprovide information that will help decision makers tounderstand the relationship between numbers andlocations of rain gauge stations in order to provide a
better and more accurate rainfall data. Further
researches on the optimization technique are requiredfor better results.
ACKNOWLEDGEMENTS
The authors would like to thank the Universiti
Malaysia Pahang under UMP grant RDU1703196 fortheir financial funding and support.

25

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

SCREENING CRUDE EXTRACTS FROM PIPER SPP. ON
COLLETOTRICHUM SP. AND PHYTOPHTHORA SP. CAUSING PLANTDISEASE
Pornprapa Kongtragoul1, Parinya Janthong1, Theerachart Leepasert2, and Chalermpol Suwanphakdee2
1
King Mongkut’s Institute of Technology Ladkrabang, Prince of Chumphon, THAILAND
2
Faculty of Science, Kasetsart University, Bangkhen, Bangkok, THAILAND

ABSTRACTThe effect of crude extracts from Piper spp. on Colletotrichum sp. and Phytophthora sp. causing plant diseases
were studies in vitro test. The paper disc diffusion method was applied for evaluation the mycelial growth at 0,
25,000, 50,000 and 100,000 ppm and the spore germination test was implemented for determining the inhibitionof spore germination at 0, 12,500, 25,000 and 50,000 ppm. The results show that crude extracts at 100,000 ppm
had the greatest activities compared to others in inhibition of the mycelia growth of Colletotrichum sp. at 35.50%
with samples no. P18 and P39 and Phytophthora sp. at 50% and 53.33% with samples no. P38 and P8, respectively.
Moreover, all samples with all concentrations evaluated completely prevented the germination of spores (100%).
.
Keywords: Piper, Plant extract, Plant disease, Botanical fungicides

and cyclopentenediones. Some of them extraction
shows antifungal activity against several pathogenic
fungi [3], [4]. Therefore, the objective of this study
was to screen the antifungal activity of crude extracts
from samples of Piper spp. in Thailand against
Colletotrichum sp. and Phytophthora sp. causing
plant disease in vitro test.

INTRODUCTION
Plant diseases have caused severe losses tohumans in several ways. They are causing economic
losses of plant production and reducing the aesthetic
values of landscape plants. The chemical fungicides
have been used for more than a hundred years andnew fungicides continue to be developed forcontrolling plant diseases. However, the side effects
of fungicides cause risks such as serious hazards toenvironment and humans, including to thedevelopment of fungicide-resistance in plant
pathogen. Several researcher have attempted to findalternative ways to solve this problems. Currently, thesearch for natural products with novel uses,
particularly related to plant disease management isvery active. Aromatic and medicinal plants haveattracted interests in the field of plant disease control,
particularly plant extracts with antimicrobial
properties and contain a spectrum of secondary
metabolites. The concentration of these bioactive
compounds in each plant species depends on theenvironmental conditions.
Piper is a genus of family Piperaceae, with morethan 2,000 species. These plants distributed mainly intropical and subtropical regions of the world. Some ofthese species are also found in Thailand. They havebeen used for many other purpose such as foods andmedicines in Thai culture [1], [2]. They are reported
for potential pharmaceutical or agricultural fungicide
development. A total of 68 compounds isolated from
22 Piper species have been reported to possess
significant antifungal activities. These compounds
include amides, flavonoids, prenylated benzoic acidderivatives, lignans, phenylpropanoids, butenolides,

MATERIALS AND METHODS
Plant material
The leaves of the plants used in this study werecollected from wild vegetation in Thailand forests.
Sixteen samples were processed for extraction.
Leaves of sample plants were cut into small pieces
and air dried. The small pieces of dry leaves wereblended to obtain fine powder and used for crude
extraction. The crude extracts were collected using
ethanol extraction process, using vacuum rotary
evaporator.
Test plant pathogenic fungiTwo plant pathogenic fungi: Colletotrichum sp.,and Phytophthora sp. were tested for antifungal
activity. They were respectively isolated from
infected mango and durian fruits.
Determination of antifungal activity of crude
extract
Mycelial growth test
Antifungal activity test of the crude extracts (the26SEE - Nagoya, Japan, Nov.12-14, 2018

original plant extracts without separation) were tested
on mycelial growth by using agar disc diffusion
method. Sixteen samples of crude extracts at 25,000,
50,000 and 100,000 ppm were used in thisexperiment. Mycelia discs (5 mm diameter) weretaken from the peripheral region of 5 day old of
culture, which grown on PDA plates. Each of themycelia discs was then transferred to the center of the
PDA and incubated for 2 days at room temperature.
After incubation, the 20 µl of each crude extract
solution was loaded on the sterile paper discs (6 mmin diameter). Sterilized distilled water were used as acontrol. The plates were then incubated at room
temperature. Radius of each colony was measured
and the percentage inhibition of mycelia growth was
calculated. Each treatment was performed in fourwith a complete randomized design.

Colletotrichum
capsici,C.
acutatum,C.
gloeosporioides, B. theobromae, and Fusarium
oxysporum f.sp. cubense [5]-[10].
Table 1 Effect of crude extracts from 16 samples ofPiper spp. on the mycerial growth of
Phytophthora sp. and Colletotrichum sp.
Sample Concentration
Mycerial inhibition (%)
Phytophthora sp. Colletotrichum sp.
code
(ppm)
control
00.00 V
0.00 V
mancozeb
1007.73 R-U
6.60 P-S
P825,00025.50 D-F
12.20 L-N
50,00036.63 BC
17.73 H-K
100,000
53.33 A
29.97 BCP9
25,0005.50 TU
1.10 UV
50,00010.00 P-T
4.40 R-U
100,000
15.50 K-O
11.10 M-O
P11
25,00021.10 F-J
12.20 L-N
50,00024.40 D-G
19.97 G-I
100,000
28.83 D25.50 DEP12
25,00015.53 K-O
4.40 R-U
50,00021.10 F-J
12.20 L-N
100,000
28.83 D
21.10 F-H
P14
25,0007.73 R-U
2.20 T-V
50,00011.10 O-S
8.87 N-Q
100,000
21.10 F-J
23.30 E-G
P15
25,00011.10 O-S
8.87 N-Q
50,00019.97 G-K
14.40 K-M
100,000
24.40 D-G
18.83 HIJ
P16
25,0006.60 S-U
4.40 R-U
50,00011.10 O-S
6.60 P-S
100,000
17.73 I-M
11.10 M-O
P17
25,0008.87 Q-U
3.30 S-V
50,00013.30 M-Q
7.73 O-R
100,000
17.73 I-M
12.20 L-N
P18
25,00011.07 O-S
17.73 H-K
50,00016.63 J-N
26.63 C-E
100,000
21.06 F-J
35.50 A
P22
25,00015.50 K-O
11.10 M-O
50,00021.10 F-J
15.50 J-L
100,000
26.63 DE
17.73 H-K
P23
25,0007.7333 R-U
10.00 N-P
50,00011.10 O-S
14.40 K-M
100,000
18.87 H-L
19.97 G-I
P24
25,00013.30 M-Q
11.10 M-O
50,00021.10 F-J
16.60 I-K
100,000
24.40 D-G
31.10 BP26
25,00011.10 O-S
16.60 I-K
50,00017.73 I-M
23.30 E-G
100,000
25.50 D-F
28.83 B-D
P27
25,00012.20 N-R
16.63 I-K
50,00012.20 N-R
18.83 H-J
100,000
22.20 E-I
24.40 EFP38
25,00034.40 BC
12.20 L-N
50,00041.10 B
18.87 H-J
100,000
50.00 A
25.50 DEP39
25,0005.50 TU
15.50 J-L
50,0007.73 R-U
25.50 DE
100,000
11.10 O-S
35.50 A

Spore germination test
The conidia of Colletotrichum sp., andsporangium of Phytophthora sp. were obtained froma 10 day old culture grown on PDA and V8,
respectively. The spore suspension were harvested byflooding the medium surface with sterilized distilledwater and adjusted to 1 x 106 spores/ml and using ahemacytometer cell counting. Each crude extract
solution and spore suspension were dropped into
Eppendrof tube to give a final concentration at 12,500,
25,000 and 50,000 ppm. The mixture was transferred
onto water agar. 100 spores were observed for
germination and recorded using a compound
microscope at 24 hr.
RESULTS AND DISCUSSION
The results of this study indicate that all Piper
species ethanol crude extracts could inhibit growth ofColletotrichum sp., and Phytophthora sp., which are
the causative agents of mango and durian diseases inThailand. However, the crude extracts of sample no.
P18 and P39 at 100,000 ppm gave the highest
inhibition activity to the mycelial growth ofColletotrichum sp. at 35.50%, followed by the sample
no. P24 at 31.10%. Moreover, it was also found that,the crude extracts of sample no. P8 and P38 at
100,000 ppm showed the highest inhibition activity tomycelial growth of Phytophthora sp. at 53.33% and
50% respectively, followed by the sample P38 at
50,000 ppm (Table 1). This situation is similar to that
Piper species have been reported to possess
significant antifungal activities. Many researchersreported that the crude extract from Piper species
exhibited pronounced antifungal activity against
phytopathogenic fungi, such as Aspergillus flavus,
A. fumigatus, A. niger, Rhyzopus sp., Microsporum
canis, M. gypseum, Trichophyton mentagrophytes,
T. rubrum, Epidermophyton flocosum, Cryptococcus
neoformans, Candida albicans, C. tropicalis,Moreover, it was observed that after 24 hr. of
incubation, all tested those Piper species with alltested concentrations could completely prevented the27

SEE - Nagoya, Japan, Nov.12-14, 2018

germination of spores in Phytophthora sp. andColletotrichum sp. (Table 2). This results indicatedthat the active compound contained in crude extractof Piper species possesses fungicidal activity to killor inhibit the spores of fungi [3]-[4].

CONCLUSION
In conclusion, the preliminary screening in thisstudy indicate that ethanol crude extract of Piper
species leaves significantly inhibited the mycelial
growth and spore germination of Colletotrichum sp.,and Phytophthora sp. There is a great scope instudying that Piper are potentially to be develop as anatural and effective alternative to synthetic fungicide
for using in the treatment of plant diseases
management in the future. However, we will study
the chemical composition of the bioactive materials
in Piper species leaves from different location in
Thailand.

Table 2 Effect of crude extracts from 16 samples ofPiper spp. on spore germination of
Phytophthora sp. and Colletotrichum sp.
Samplecode

Concentration(ppm)

controlmannoseP8

0100
12,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,00012,50025,00050,000

P9

P11

P12

P14

P15

P16

P17

P18

P22

P23

P24

P26

P27

P38

P39

Inhibition of spore germination(%)
Phytophthora sp. Colletotrichum sp.

0C
68 B
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A

0B
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A
100 A

ACKNOWLEDGEMENTS
The authors express the sincere appreciation to theKing Mongkut’s Institute of Technology Ladkrabang,
Prince of Chumphon Campus and Kasetsart
University for supporting the study financially.
REFERENCES[1] Chaveerach, A., Tanee, T., Sudmoon, R. andMokkamul, P. 2009. The genus Piper in Thailand.
Second edition. Khon Kaen: Khon Kaen Karnpim.
163 pp. ISBN 978-616-549-005-4. (in Thai).
[2] Chaveerach, A., Sudmoon, R., Tanee, T. andMokkamul, P. 2008. The species diversity of the
genus
Piper
from
Thailand.
Acta
Phytotaxonomica et Geobotanica, Vol. 59, No. 2,
pp.105-163.
[3] Xu, Li, Antifungal Compounds from Piper
Species, Current Bioactive Compounds, Vol.7,
No.4, 2011, pp. 262-267.
[4] Ghosh R., Darin K., Payel N., and Deb P. An
Overview of Various Piper Species for Their
Biological Activities. International Journal of
Pharma Research & Review, Vol. 3, No.1, 2014,
pp. 67-75.
[5] Nazmul M.H.M., Salmah I., Syahid A. and
Mahmood AA. In-vitro screening of antifungal
activity of plants in Malaysia. Biomedical
Research, Vol. 22, No.1, 2011, pp. 28-30.
[6] Marina P. D. C., Valdir C., Rosi Z. D. S., Rosendo
A. Y., Susana Z., Sabina J., Rosana C. C., andAlexandre B. C., Evaluation of Antifungal
Activity of Piper solmsianum C. DC. var.
solmsianum (Piperaceae)., Biol. Pharm. Bull. Vol.
28, No. 8, 2005. pp. 1527-1530.
[7] Singburaudom N., Hydroxychavicol from Piper
betel Leave is An Antifungal Activity Against
Plant Pathogenic Fungi. JBiopest., Vol. 8, No. 2,
2015. pp.82-92.
[8] Rodrigo P. M., Samuel V. P., Carlos M. G. P.,
Jesús H. Gil G.1, and Diego L. Durango R.,
Chemical Composition and Antifungal Activityof Piper auritum KUNTH and Piper holtonii C.
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SEE - Nagoya, Japan, Nov.12-14, 2018

DC. Against Phytopathogenic Fungi, Chilean
Journal of Agricultural Research, Vol.74, No. 4,
2012, pp. 507-515.
[9] Ounchokdee, U., Rueangrit, S. and Dethoup, T. ,Antifungal Activity Profile of Piper longum Fruit
Extract Against Plant Pathogenic Fungi,
JBiopest, Vol.9, No. 2, 2016, pp. 97-103.

[10] Jorge R., Luis C., Vladimir M., Silvio A., Omar
M.., Antifungal Activity of Raw Extract andFlavanons Isolated From Piper ecuadorensefrom
Ecuador,
Revista
BrasileiradeFarmacognosia
Brazilian
JournalofPharmacognosy, Vol.23, No. 2, 2013, pp. 370373.

29

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EXPRESSION OF HYALURONAN SYNTHASE (hasA) AND
PRODUCTION OF HYALURONIC ACID THROUGH BIOSYNTHESISIN RECOMBINANT ESCHERICHIA COLI

1

Lai Zee Wei1, Aayushree Kharel1 and Chong Jun Yi 1
School of Biosciences, Faculty of Health and Medical Sciences, Taylor’s University, Malaysia

ABSTRACT
Hyaluronic acid (HA) is a biodegradable, high molecular weight polymer and a major component of mucoid
capsule in bacteria and extracellular matrix (ECM) of vertebrate tissue. Due to its unique characteristics, HA isused extensively in medical and cosmetic field. HA was extracted from animal tissues or produced byfermentation using native producer of the biopolymer, Streptococcus zooepidemicus. However, due to exotoxins
production from these sources, HA production by recombinant microorganisms has gained interest. A fragmentof an approximate size of 1.5kb that encodes the hyaluronan synthase (hasA) gene from S. zooepidemicus ATCC
39920 was amplified by PCR using the designated primers. The hasA gene was ligated into the plasmid
pLbADH and cloned into the expression host, Escherichia coli BL21 strain and further identified by miniprep
and DNA sequencing. Then, genetically engineered E. coli strain BL21 was used for the production of HA byfermentation using different glucose concentration in shake flask culture. Varying glucose concentration (10-50g/L) was used and carried out at 200 rpm for 7 hours in shaking incubator. Biomass concentration wasdetermined using dry cell weight (DCW) method, whereas, colorimetric method was used to determine theamount of glucose consumption and HA concentration. Amongst varying glucose concentrations, results showedthat 50 g/L glucose produced the highest HA concentration (0.074±0.001 g/L) and HA productivity (0.018 g/L.h 1). The use of nutrient rich media containing nitrogen source along with 50 g/L glucose was able to produce thehighest HA concentration (0.115±0.002 g/L) and HA productivity (0.028 g/L. h -1).

Keywords: hyaluronic acid, hyaluronan synthase, Streptococcus zooepidemicus, Escherichia colibiochemical can be risky due to zoonosis andunpremeditated infection transfer [3]. Hence,currently, HA production from microbial
fermentation is the commonly used method to meetthe demands of the market. Since the 1980s, HA
was produced by fermentation of group C
Streptococci [7]. However, these microorganisms
are potential human pathogens, thus making HApurification costly. Genetic engineering of
microorganisms for HA synthesis has allowed HA
production from non-pathogenic microorganisms[8]. HA production is commonly observed in
Gram-positive bacteria, but by genetic engineeringof gram negative bacteria such as Escherichia coli,
synthesis of HA has been possible and they can beused as potential host candidate for industrial HA
production [7]. Scientists have used Generally
Regarded as Safe (GRAS) microorganisms for HA
production, such as recombinant Lactococcus lactis
that produced 0.65 g/L of HA [9], recombinant
Escherichia coli that produced 0.203 g/L of HA[10].
Since the biosynthesis pathway of HA ispartially similar to cell wall biosynthesis, theheterologous expression of hasA gene alone is

INTRODUCTION
Hyaluronic acid (or hyaluronan or HA) is apolysaccharide that belongs to glycosaminoglycan
family and consists of D-glucuronic acid (GlcUA)
and N-acetylglucosamine (GlcNAc), linked
alternately by β-1,3 and β-1,4 glycosidic bond [1].
HA is a high molecular weight linear
polysaccharide with the molecular weight ranging
from 104 to 107 Da [2]. HA is abundantly present
in the umbilical cord, synovial fluid and vitreous
humor (eye). Due to its biocompatibility,
viscoelasticity and hygroscopicity, HA is
extensively used for the treatment of ulcer and burn[3], in ophthalmology, rheumatology anddermatology [4]. In conjunction with the properties
of HA, it is also widely used in cosmetic products,
medicine and specialty foods. According to Widner
et al. [5], the market value of HA was estimated to
be over a billion dollars.
Previously, HA was extracted from rooster
comb. According to a study conducted by Rosa etal. [6] they concluded that rooster comb wascomposed of about 90% HA, making it suitable forextraction. However, use of animal-derived
30

SEE - Nagoya, Japan Nov.12-14, 2018sufficient to induce production of hyaluronic acid inthese organisms. The effort of using recombinantsystems to produce HA started when the
hyaluronan synthase gene (hasA) encoding for the
enzyme that polymerizes UDP-GlcNAc and UDPGlcUA into hyaluronan was isolated from
Streptococcus pyogenes [11]. In HA fermentation,
carbon source plays a vital role as the intermediates
are shared for both biomass formation and HA
production [2]. There is limited study on thebiosynthetic capabilities of recombinant E. coli
BL21 for the production of HA. Hence, the aim of
this research study is to clone and express hasA
gene into E.coli BL21 and use this recombinant E.
coli strain BL21 as host in order to explore thebiosynthetic capabilities for HA production in batch
fermentation using shake flask culture.

bacteria culture was put on ice for 10 minutes tocool down to 0°C.
The E. coli cells were recovered bycentrifugation at 4100 rpm for 10 minutes at 4°C.
The medium was separated and removed
completely from the cell pellets. The pellets werethen resuspended in 30 mL of ice-cold MgCl2CaCl2 solution by gently swirling. The cells were
centrifuged again at 4100 rpm for 10 minutes at
4°C and separated it from medium. The pellet wasthen added with ice-cold 0.1M CaCl2 solution andresuspended by gently swirling. The competent E.
coli cells culture was then aliquoted into 1.5mL
microcentrifuge tubes with 100 µL of culture ineach tube.
Cloning of hasA Gene into Bacteria Expression
Vector (pLbADH)

MATERIALS AND METHODSThe PCR product obtained from hasA gene andthe plasmid pLbADH were digested separately with
FastDigest enzyme EcoRI and HindIII in an
incubator at 37°C for 1 hour. The tubes were thenput on a rack in an 80°C water bath for 20 minutes
to heat inactivate the enzyme.
Both digestion products were transferred to asame 0.5mL microcentrifuge tube for ligation using
T4 DNA ligase enzyme. The ligation takes place ina thermal cycler at 22°C for overnight. The ligation
product was then used for transformation.

Bacteria Strains and Plasmid
Streptococcus equi sub sp. zooepidemicus(American Type Culture Collection® 39920™) wasused and stored at -80°C in 50% (v/v) glycerol
stock, Escherichia coli BL21 was used as therecombinant host cell and plasmid pLbADH wasused.
Isolation of hasA Gene using PCR Amplificationfrom S. zooepidemicus

Transformation of Recombinant E. coli Bacteria
The hasA gene was isolated from S.
zooepidemicus and amplified by PCR using thedesigned forward (5’ GGG GAA TTC ATG AGA
ACA TTA AAA AAC CTC 3’) and reverse(5’GCC AAG CTT ATT ATA ATA ATT TTTTAC GTG TTC CCC 3’) primers, which named
HasA_01F and HasA_01R, respectively. With thebacteria S. zooepidemicus used as the template,polymerase chain reaction (PCR) was performed
with KOD Hot Start DNA polymerase in a thermal
cycler using the following program: 1 cycle at 95°C
for 3 minutes, 30 cycles of 95°C for 15 seconds,
60°C for 30 seconds, 72°C for 90 seconds and 1
cycle of 72°C for 5 minutes. 5μL of PCR productwas taken to perform gel electrophoresis, and theremaining were stored in the freezer at -20°C until
use.

Five µL of the ligation product were transferred
into the tube containing the competent cells. The
contents of the cells were mixed by swirling gently.
The tubes were rested on ice for 30 minutes before
the heat shock step. The tubes were then put on arack in a pre-heated 42°C water bath for exactly 90
seconds. The tubes were immediately transferredback to the ice for 5 minutes. 900 mL of LB broth
was added into the tubes, and placed in a shaking
incubator at 37°C, 200rpm for an hour.
The tubes were centrifuged at 5000 rpm for 5
minutes. 900 mL of medium was removed by
pipetting. The remaining medium was resuspended
with the cell pellets, and transferred onto a LB agar
plate with ampicillin. Spread plate was applied andincubated in a 37°C incubator for 12 to 16 hours.

Preparation of Competent E.coli Cell

PCR Screening for Positive Transformant

A single E. coli bacteria colony from an
overnight bacteria culture was transferred into a
50mL falcon tube with 50mL of LB broth. The
culture was incubated in a growth incubator at 37°C
for about 4 hours. The growth of the culture wasmonitored after 2 hours. The OD600 of the culture
was until the reading of cell OD600 reach 0.35. The

All the colonies grown on the LB agar plates
were collected and screened with PCR using thefollowing program: 1 cycle at 95°C for 3 minutes,
30 cycles of 95°C for 15 seconds, 60°C for 30
seconds, 72°C for 90 seconds and 1 cycle of 72°C
for 5 minutes. HasA_01F and HasA¬_01R wereused as primer in selection of positive transformant.
31

SEE - Nagoya, Japan Nov.12-14, 2018

PCR products were performed with gelelectrophoresis and gel documentation allowed thecomparison of base pairs with the original hasA
gene to be made. PCR products that showed
difference were discarded, while the colonies
containing the hasA gene were subcultured for HA
analysis.

precipitate HA. The precipitate was re-dissolved in
1 ml of 0.15 mol/L of NaCl solution andcentrifuged at 3,000 x g for 20 min; then was redissolved with a 2 to 3-fold volume of distilledwater. The HA concentration was determined using
the carbazole method [12] and the optical density
was measured at 530 nm. The HA concentration
was calculated using a standard curve prepared at
different concentrations of HA standards (SigmaAldrich,
Malaysia).
For
reducing
sugar
concentration, 3,5-dinitrosalicylic acid (DNS)
method was used [13].

Medium and Fermentation
The cells were grown at 37oC with 200 rev/min
shaking speed for 5 h in the LB broth (as an
inoculum) supplemented with 100 mg/ml of
ampicillin. The fermentation medium contained
two different types of components; one is LB andglucose (10-50 g/L) only; one is nutrient richmedium which consisted of (in g/L) glucose 50,
tryptone 15, yeast extract 5, KH2PO4 2, K2HPO4 2,
MgSO4.7H2O 0.5. The culture medium wassterilized at 121oC for 15 min. The glucose andMgSO4.7H2O were autoclaved separately. The
ampicillin was sterilized by filtration using 0.45 µm
nylon syringe membrane filter. Fermentations werecarried out in duplicates and the mean value of eachexperiment was obtained.
To investigate the effect of glucose
concentrations (10 – 50 g/L) for HA biosynthesisby the recombinant E. coli strain, experiments werecarried out using a 500 mL Erlenmeyer flask. The
flask cultures were incubated in rotary shaker at
200 rev/min with different glucose concentrations.
To initiate the fermentation, 1 loop of colony
culture was transferred to 50 mL of LB inoculum
medium for 5 hours at pH 7, and 10 % (v/v) of
inoculum was inoculated into the 500 mL shakeflask containing 180 mL of the production medium
and run for another 7 hours at initial pH 7, 37oC.
Inducerof
0.5mM
isopropyl
β-D-1thiogalactopyranoside (IPTG) was added to induce
the expression of hasA genes when OD600 reachedabout 0.6.

RESULTS AND DISCUSSIONS
Cloning of hasA gene from S. zooepidemicus
The hasA gene from S. zooepidemicus was
successfully amplified by PCR and cloned into theplasmid pLbADH as shown in Fig. 1 with ProTAC
promoter (constitutive promoter). There wasseveral plasmid constructed along with different
promoters to transformed hasA gene into otherrecombinant hosts. Jeong, Shim & Kim [14]utilized two types of plasmid, pAO815 and
pGAPZB which have an inducible promoter (AOX)
and a constitutive promoter (GAP), respectively.
Their study use the vector with constitutive
promoters to accumulate of both sugar precursors
of HA in the cell, then activate the inducible
promoter preceding the hasA gene, leading to anincreased production and higher MW of HA.
Plasmid Rearrangement
Recombinant E. coliinTransformed

PCR analysis on initial culture of recombinant
E. coli colony showed that hasA gene issuccessfully cloned and transformed into E. coli
BL21 (Fig. 1). Interestingly, no hasA gene was
detected in second subculture of recombinant E.
coli. In addition, restriction enzyme analysis carriedout on the recombinant hasA plasmid isolated fromsecond subculture showed multiple bands withdifferent MW (data not shown). To confirm
whether the unidentified extra bands are fromcontamination or due to the rearrangement ofrecombinant hasA plasmid, the miniprep products
were digested separately using different
combination of restriction enzymes to evaluate theplasmid size. Further restriction analysis on isolated
plasmid DNA confirmed that the recombinant hasA
plasmid was rearranged. A cloned plasmid will be
more prone to be selected against by the host cell,
either by deletion or rearrangement when theplasmid size is too large [15].

Analytical Methods
All samples were withdrawn at regular timeintervals for analysis of cell, HA and glucose
concentration. Cell growth was observed bymeasuring the optical density of the culture broth at
600 nm using a spectrophotometer. Correlation
between the dry cell weight (DCW) and OD wasestimated from several batch experiments using theequation: DCW (g/L) = 2.2511 x OD
The supernatants were used for HA andreducing sugar determination. After the removal of
the cell pellet for cell growth determination, twovolumes of ethanol were added to one volume ofthe supernatant in a 15 ml centrifuge tube and thesolution was refrigerated at 4°C for 1 h to32

SEE - Nagoya, Japan Nov.12-14, 2018

1 2

3

4

per gram of glucose. It is suggested that glucose
concentration above 50 g/L glucose concentration
causes reduction in water activity which may leadto growth inhibition. Glucose is a monosaccharide
and hence its’ osmotic pressure will be higher, so
microorganisms will detect the changes in osmoticpressure and alter their metabolic pathway [17].
Ding & Tan [18] also stated that high initial glucose
concentration in batch fermentation method cancause low cell mass due to substrate inhibition.
At 50 g/L, product yield per substrate produced(YP/S) and maximum productivity (Pr) had
maximum values of 0.004 g HA/g cell and 0.018 g
HA/L.h-1 respectively. At 40 g/L, Y P/S was 0.003 g
HA/ g cell and at 50 g/L, Y P/S was 0.004 g HA/gcell suggesting that glucose was more efficiently
consumed at 50 g/L. Values for product yield per
biomass produced (YP/X) increased with increase inglucose concentration, reaching a maximum valueof 0.010 g HA/g cell at 50 g/L glucose
concentration. This suggested that as the number ofcells increased, the amount of HA production also
increased. Hence, the results showed that HA
fermentation by recombinant E. coli BL21 is highly
growth associated as shown in Fig. 2. However,studies conducted by Huang et al. [19] suggested
that HA production was delayed-growth associatedwhich was in accordance to several other reports.
At 50 g/L, YX/S was least and YP/S was highest,
suggesting glucose was mainly used for HA
production. Precursors such as glucose-1phosphate,
UDP-glucose
andUDP-Nacetylglucosamine are shared in HA synthesis andcell growth. Hence, competition between these twopathways exist to consume the same precursors. In
addition, competition for carbon flux exists
between HA synthesis and glycolysis [2].
Metabolites such as glucose-6-phosphate andfructose-6-phosphateareconsumedbyhexomonophosphate
shunt
and
glycolysis,
respectively. Hence, there is strong competition for
metabolites between HA production and cell
growth [20]. HA production is an energy intensive
process and total of 4 mol ATP is required for
production of 1 mol of repeating unit of HA
disaccharide. Hence, in order to balance between
biomass and HA production, maintenance of
metabolic balance is important as well [21].
Izawa et al [21] suggested that use of aerobic
bacteria for HA production can cause increase inviscosity of the culture broth, inhibiting thetransport of nutrients and gas. However, it has beenfound that aeration can improve the yield of HA
compared to corresponding anaerobic culture. But
Mausolf et al. [22] suggested that under aerobic
conditions, degradation of HA can take place due tothe presence of oxygen-derived free radicals.

5

kbp
12
5
2
1.65
1
0.85
0.65
0.5
0.4
0.3
200 1 Screening for positive transformant. Lane 1:Fig.
1kb plus DNA ladder; Lane 2: positive control ofhasA gene; lane 3-5: Sample 1-3.
This is further supported by the evidence thatfurther analysis with carbazole method showed thepresence of HA produced by the recombinant E.
coli, and the ability of the bacteria to propagate
under selection of 100mg/mL ampicillin.
Effect of Different Glucose Concentrations on
HA Production by Recombinant E. coli BL21
Based on the kinetic parameter values (Table 1),highest biomass concentration (Xm) and highest HA
concentration (Pm) was 3.031±0.004 g/L and
0.074±0.001 g/L respectively, both achieved at 50g/L glucose concentration. However, lowest Xm
and Pm was 2.161±0.002 g/L and 0.018±0.013 g/L
respectively, both achieved with control. This is inaccordance to our expected results, as the bacteria
requires carbon source for cell growth and HA
production. In control, there was no glucose
present, so there was insufficient precursor for HA
production. However, as glucose concentration
increased, the precursors, GlcUA and GlcNAc weremade and HA concentration increased. According
to a study conducted by Don & Shoparwe [1]highest HA concentration of 0.589 g/L wasachieved at 50 g/L glucose concentration. However,in their experiment, when glucose concentration
was increased to 60 g/L, HA concentration
decreased.
Highest cell yield coefficient (YX/S) was
achieved at 20 g/L glucose concentration. This
result suggests that highest YX/S does not mean
highest productivity. The result matches with anexperiment conducted by Holmstrom & Ricica[16], which also proposed that highest yield of cell
does not necessarily mean highest HA production.
At 50 g/L, the YX/S value was the least, 0.313 g cell/g substrate, suggesting that less cells were produced

33

3.5

0.08

3

0.07
0.06

2.5

0.05

2

0.04
1.5

0.03

1

0.02

0.5

0.01

0

Mean HA concentration (g/L)

Mean Biomass Concentration (g/L)

SEE - Nagoya, Japan Nov.12-14, 2018

0
0

1

2

3
4
Time (hours)

5

6

7

Fig. 2 Graph of mean biomass and HA concentration (g/L) by recombinant E. coli BL21 in shake flask cultureusing 50 g/L glucose. All concentrations were represented as the mean value of duplicated results fromindependent fermentation. ( ■) HA (♦) Biomass

Table 1 Kinetic parameter values of HA production by recombinant E. coli BL21 using different glucose
concentrations
Kinetic
parameters

Glucose concentration (g/L)

Xm (g cell /L)

10
2.501±0.010

20
2.602±0.011

30
2.656±0.002

40
2.879±0.004

50
3.031±0.004

Pm (g HA/L)

0.026b±0.001

0.029c±0.0001

0.037d±0.0001

0.057e±0.003e

0.074±0.001f

S (gglucose/L)µm (h-1)

5.260

6.396

6.476

8.686

11.341

0.500

0.520

0.531

0.575

0.606

YX/S (g cell/g
substrate)

0.669

0.682

0.415

0.446

0.313

YP/S (g HA/g
0.001
0.001
0.001
0.003
0.004
substrate)
YP/X (g HA/g
0.002
0.002
0.004
0.005
0.010
cell)
Pr (g HA/L.h0.006
0.007
0.009
0.014
0.018
1
)
Legend: (Xm) maximum biomass concentration; (P m) maximum HA concentration; (S) consumed substrateconcentration; (µm) maximum specific growth rate; (YX/S) cell yield coefficient; (YP/S) product yield coefficient;(YP/X) product yield per biomass produced; (P r) maximum productivity. All results are expressed as means ±standard deviation of means; Values are means of duplicates from two separate runs (n = 2). p-value for average
HA concentration in accordance to glucose concentration was obtained using two way ANOVA statisticalanalysis (α=0.05). a b c d e f :Values with different lowercase superscript are significantly different.

Effect of Nutrient Rich Media on
fermentation by Recombinant E.coli BL21

alone. As shown in Table 2, maximum biomass
concentration (Xm) was 3.280±0.108 g/L when 50
g/L glucose along with nutrient rich media was used.
However, when only 50 g/L glucose was used, thebiomass concentration was 3.031±0.004 g/L. Studies
by other researchers were conducted with constant

HA

The use of nutrient rich media for HA production
yielded higher biomass concentration and HA
concentration when compared to use of glucose
34

SEE - Nagoya, Japan Nov.12-14, 2018

glucose concentration and varying yeast extract
concentration (as nitrogen source). The results
supported our results, suggesting that presence oforganic nitrogen source improves the microorganism
growth, with maximum cell growth when C: N ratio
is 2:1 [23]. The increase in biomass concentration is
because yeast extract is a good substrate for many
microorganisms as it contains important components
such as amino acid, peptide, water-soluble vitamins
and carbon source which are required for growth andmetabolism.
Withnutrient
rich
media,
maximum HA concentration (Pm) was 0.115±0.002 g
HA/ L, whereas with 50 g/L glucose concentration it
was only 0.074±0.001 g HA/L. This might havebeen due to availability of amino acid and Bvitamins provided by organic nitrogen source, yeast
extract and tryptone. Additionally, presence of theseorganic nitrogen source provides large portion ofcarbon for the growth and production of cells [24].
The specific growth rate (µm) was slightly higher at
50 g/L glucose concentration. This can be explainedby the cell yield coefficient (YX/S) which is also
higher for 50 g/L glucose concentration, whichsuggests that more cells are produced per substrateconsumed at 50 g/L. In nutrient rich media, more of
the metabolised carbon source might have been usedfor HA production, as a result slightly lower specificgrowth rate was achieved. The product yieldcoefficient (YP/S) and product yield per biomass
coefficient (YP/S) was higher with nutrient richmedia containing 50 g/L glucose. The productivity isalso higher in nutrient rich media, with a value of
0.028 g HA/ L.h-1 which is in accordance to results
obtained by other researchers which suggests that
presence of nitrogen source increases the productionof HA [24].
According to Aroskar, Kamat & Kamat [25], theoverall HA production is dependent on the nitrogensources present in the fermentation media. However,there is limited information about the consequenceof medium carbon-to-nitrogen (C/N) ratios which
will cause an effect on the metabolic flux [23].
Studies show that presence of potassium dihydrogen
phosphate (KH2PO4) and magnesium sulphate
heptahydrate (MgSO4.7H2O) also contribute toincrease in biomass and HA productivity [25].
Hence, the presence of these substances in nutrient
rich media may have also contributed to higher
biomass and HA concentration.

The results obtained from this study showed thatamongst the range of glucose concentration usedfrom 10-50 g/L, 50 g/L glucose produced highest
concentration of HA of 0.074±0.001 g/L at 4th hourof fermentation in shake flask culture. Comparison
between HA production in media consisting of only
glucose and nutrient rich media containing glucose
showed that higher HA production was achieved innutrient rich media with HA concentration of
0.115±0.002 g/L. The findings can be used to further
optimize HA production by varying other parameterssuch as nitrogen source, agitation rate and aeration
rate before upscaling the process.
Table 2 Kinetic parameter values of HA production
by recombinant E. coli BL21 using different media
Kinetic
parameters

Glucose concentration (g/L)

Xm (g cell /L)

50 without
nutrient richcomponents
3.031±0.004

50 &Nutrient
Rich Media
3.280±0.108

Pm (g HA/L)

0.074±0.001

0.115±0.002

S (g glucose/L)

11.341

13.126µm (h )

0.606

0.546

YX/S (g cell/g
substrate)
YP/S (g HA/g
substrate)
YP/X (g HA/g
cell)
Pr (g HA/L.h-1)

0.313

0.259

0.004

0.006

0.010

0.01950.018

0.0287-1

Legend: (Xm) maximum biomass concentration;(Pm) maximum HA concentration; (S) consumed
substrate concentration; (µm) maximum specificgrowth rate; (YX/S) cell yield coefficient; (YP/S)
product yield coefficient; (YP/X) product yield per
biomass produced; (Pr) maximum productivity. All
results are expressed as means ± standard deviationof means; Values are means of duplicates from two
separate runs (n = 2). p-value was obtained using
two-way ANOVA statistical analysis(α=0.05).
ACKNOWLEDGEMENTS
This work was financially supported by Emerging
Research Funding Scheme funded by Taylor’s
University Lakeside Campus.

CONCLUSIONREFERENCES

The hasA gene was cloned from S. zooepidemicus
and successfully expressed in recombinant E.coli
BL21 cells. 50 g/L glucose concentration along withnitrogen source such as yeast and tryptone is thepreferred combination to produce the highest
concentration of HA through fermentation byrecombinant E. coli BL21 using shake flask culture.

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[2] Liu, L., Liu, Y., Li, J., Du, G., and Chen,
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[6] Rosa, C.S., Tovar, A.F., Mourao, P., Pereira, R.,
Barreto, P., and Beirao, L.H., Purification andCharacterization of Hyaluronic Acid from
Chicken Combs. Ciencia Rural, Vol. 42, Issue 9,2012, pp. 1682-1687.
[7] Yamada, T., and Kawasaki, T., Microbial
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[8] de Oliveira, J.D., Carvalho, L.S., Gomes,
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[9] Chien, L.J., and Lee, C.K., Hyaluronic Acid
Production by Recombinant Lactococcus lactis.
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[10] Yu, H., and Stephanopoulos, G., MetabolicEngineeringofEscherichia
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[11] DeAngelis, P.L., Molecular Directionality ofPolysaccharide
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SEE - Nagoya, Japan Nov.12-14, 201837

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE UTILIZATION OF THE MITOCHONDRIAL COI AND THE
NUCLEAR HISTONE H3 GENES FOR DNA BARCODING STUDYOF INTERTIDAL SHELLED GASTROPODS FROM NADA COAST
IN WAKAYAMA PREFECTURE, JAPANNagisa Nakaji1, Shoma Iwamoto1, Shinnosuke Teruya2, Masataka Kusube1, Akira Kosaka4,
Takenori Sasaki3, Davin H. E. Setiamarga1,3,*
12

National Institute of Technology, Wakayama College, Gobo, Wakayama, Japan
Okinawa Prefectural Deep Sea Water Research Center, Kumejima, Okinawa, Japan
3
The University Museum, The University of Tokyo, Bunkyo, -ku, Tokyo, Japan 4
4Wakayama Prefectural Museum of Natural History, Kainan, Wakayama, Japan†
Equal contributions (Co-first Authors)* Corresponding Author / Senior Author (email: davin@wakayama-nct.ac.jp)

ABSTRACTDNA Barcoding, especially when coupled with Environmental DNA (eDNA), has been acknowledged
as a powerful method for biodiversity monitoring due to its minimal invasiveness and relatively highaccuracy. However, this method depends heavily on the availability of useful DNA markers and a reliablereference DNA data base. Although the coasts of Wakayama Prefecture are known to be among the most
biologically diverse coastal areas of Japan and thus have a rich assemblage of shelled gastropods, very little
molecular-based biodiversity studies have been conducted in the area. In this paper, we report the result of
our study to provide a reliable reference DNA data of the mitochondrial gene COI and the nuclear gene
Histone H3, for the shelled gastropods of the intertidal area of the Nada Coast in central Wakayama. In
order to do so, we collected up to five individuals of nine species of shelled gastropods from the intertidal
rocky beach. Samples were identified morphologically and then vouchered at the University Museum of
the University of Tokyo. PCR and sequencings were conducted using previously reported Histone H3 and
COI primers. We also found that the Histone H3 of most of our target species are not available on Genbank.
Sequence comparisons and phylogenetic analyses indicated that the both genes have enough substitutions
to differentiate species. Our result thus contributed to the building of a set of reference DNA sequences for
future DNA-based environment and biodiversity monitoring.
Keywords: DNA Barcoding, Gastropoda, Monitoring, Intertidal

INTRODUCTION
Recent development in sequencing technology
has made DNA Barcoding a powerful and practicalmethod for taxonomic identification of samples
collected from the field, due to its relatively highaccuracy [1]. DNA barcoding, which can be
defined as "Identification of organism samples byinterrogating query samples against data baseregistered DNA data of taxonomically identified
samples", depends heavily on the availability ofuseful DNA markers and a reliable reference DNA
data base.

However, the lacks of reliable databases,
including those of DNA, have been a problem. For
example, Troudet et al [2] has reported biases intaxon sample representatives in the Global
Biodiversity Information Facility (GBIF) database.
They found that while popular vertebrate taxa suchas bird and mammals were over-represented, data
for all major invertebrate lineages, such as
gastropods and arthropods, were poorly
represented.
Marine gastropods and other mollusks have
38

SEE - Nagoya, Japan, Nov.12-14, 2018

Figure1. Target species of this study. A: Eurytrochus cognatus, B: Turbo stenogyrus, C: Reishia
clavigena D: Chlorostoma xanthostigma, E: Omphalius nigerrimus, F: Japeuthria ferrea, G: Patelloida
saccharina lanx, H: Nipponacmea fuscoviridis, I: Siphonaria sirius, J: Siphonaria japonica.
been known to be sensitive to environmental
changes [3, 4]. Meanwhile, with an estimatednumber of extant species to be ca. 32,000-40,000,
intertidal shelled marine Gastropod is a mollusk
taxon with high biodiversity. Members of thisgroup are distributed widely around the coastal
area around the world. Accordingly, this group is a
useful model taxon for the assessment of the
impacts of environmental changes, at both theglobal and local scales.
The coasts of Wakayama Prefecture, including
the Nada Coast in central Wakayama, are known tobe among the most biologically diverse coastal
areas of Japan [5, 6], and thus have a richassemblage of shelled gastropods. However,
although many ecological and species observation
studies have been reported (e.g. [7] [8]), very little
molecular-based biodiversity studies have been
conducted in the area.
In this study, we report the result of our DNA
Barcoding study on the shelled gastropods of theintertidal area of the Nada Coast in central
Wakayama, using the mitochondrial gene COI andthe nuclear gene Histone H3 (H3). We aimed to test
the usefulness of these two gene markers, and toprovide reliable sequence data linked to vouchered
museum samples, for intertidal shelled gastropods
barcoding studies.

41 individuals of shelled gastropods from ninespecies were collected from the rocky intertidal
area of the Nada Coast in central Wakayama.
(Table 1, Fig. 1). Samples were identified
morphologically based on current taxonomicalclassification [9] and then preserved in 95%
ethanol and vouchered at the University Museumof the University of Tokyo.
DNA extraction and amplification
Pieces of muscle tissue (ca. 0.25 mg) were
excised from samples. DNA was extracted using
standard CTAB-phenol-chloroform method. The
mitochondrial cytochrome c oxidase I (COI) gene
was amplified using LCO1490 and HCO2198 [10]and LCO mod_Kano2008 and HCO mod_Kano
2008 [11]. Primer pairs H3aF’ and H3aR [12] wereused for the nuclear Histone H3 gene. PCR
reactions were then conducted at the annealing
temperatures of 45° and 50°, respectively. PCR
products were visualized on a 0.7% agarose gel.
Sanger sequencings of successful PCR products
were performed by FASMAC (Japan).
We confirmed our sequence data using BLAST
on NCBI optimized for highly similar sequences
setting (megablast). When we obtained no hit, we
researched using the somewhat similar sequences
setting (blastn).
Sequences were aligned using MAFFT version 7[13]. we used the online version of Gblocks 0.91b
to remove ambiguously aligned positions with theleast stringent settings [14]. We used Mesquiteversion 3.40 [15] for sequence visualizations.

MATERIALS AND METHODS
Taxon sampling39

Table.1 Sample list

SEE - Nagoya, Japan, Nov.12-14, 201840

SEE - Nagoya, Japan, Nov.12-14, 2018

Outgroup bivalves were selected based on theavailability of gene sequence data. We usedsequences of Crassostrea gigas (Genbank:
AB904889) and Pinctada fucata [16] (Genbank:
GQ355871) for COI. The out groups for H3 were
C. gigas [17] (Genbank: HQ809488) and P. fusca(Genbank: HQ329300) [18].
We made five datasets for phylogenetic analyses:
Dataset A: COI sequences; Dataset B: COI
sequence with the 3rd codon removed; Dataset C:
Histone H3 sequences, D: concatenated A and C
dataset, E: concatenated B and C dataset. The
outgroup sequences C. gigas and P. fusca werechimeric on D and E datasets.
Phylogenetic tree of A-E datasets wereconstructed by two inference methods: theMaximum Likelihood (ML) analysis using
RaxmlGUI v.1.5 on the GTR-GAMMMA
substitution model, with 1000 bootstrap
replications [19], and Neighbor-joining (NJ)
analysis using MEGA 7 with the partial deletion
option and the Maximum Composite Likelihood
model, also with 1000 bootstrap replications [20].

nigerrimus were not monophyletic in the H3 trees.
The topologies of the COI and H3 gene trees
were different (Fig. 2). At the family level, thetopologies of both gene trees disagree withmorphology-based systematics by Sasaki [21]. For
example, Siphonaria (Pulmonata) was notincluded in Neogastropoda, in both gene trees.
On the other hand, ML and NJ analyses on the
concatenated datasets resulted in trees with wellresolved topologies, regardless of the inclusion of
the 3rd codons of COI. Monophyly was observedat the species, genus and order levels in bothinference methods. The monophylies at the family
and subfamily level were observed on
phylogenetic trees inferred on dataset E (COI 3rd
codon excluded), but not on trees of dataset D (COI
3rd codon included). For example, Turbinidae wasfound to be paraphyletic to Trochidae on dataset D
trees, while Turbinidae was monophyletic ondataset E trees.

DISCUSSION
Phylogenetic analyses on our concatenated data
showed that removing 3rd codon data improves
tree topology and the taxonomic placements ofsamples. Taxonomic grouping of samples also
agreed with the morphology-based classification
by Sasaki [21]. Mitochondrial genomes are known
to have fast evolutionary rates, and thus the 3rdcodons of the mitochondrial gene COI were
probably saturated [22], causing homoplasies andthus incorrect phylogenetic inference caused bylong branch attractions. However, the nuclear gene
Histone H3 is known to have a low substitution rate,
and was considered useful for phylogenetic
analyses at the higher taxonomic levels. Exclusionof the 3rd codon positions of this gene might be
detrimental, because of the lack of enoughnucleotide variations for phylogenetic inference.
When we use only one gene, all samples weremonophyletic at the species level, but at the genus
level and above, many clades were taxonomicallymisplaced. This was remedied when both genes
were concatenated and analyzed as a single dataset.
However, despite the lack of resolution at thehigher taxonomic level, both genes weresuccessful in placing conspecific samples in asingle monophyletic group with high bootstrap
supports regardless of the inference method (NJ or
ML). Therefore, we suggest that both genes areuseful to differentiate species for barcoding and

RESULTS
Sequencing results and GenBank availability
Using various primers mentioned previously, we
succeeded in amplifying both genes of all samples.
We obtained 700 bases for COI, and 313 bases for
Histone H3. After sequence editing, alignment,
and removals ambiguously aligned regions, we
obtained 607 positions for COI and 269 positionsfor Histone H3. When the 3rd codon positions wereomitted on COI, 406 positions were left.
All BLAST searches of the obtained COI andH3 sequences using megablast of blastn on the nr
databases, hit gastropod sequences of the samefamilies, and, if reference sequence data wereavailable, genera and species (Table1). In COI,
reference sequences for nine species wereavailable in Genbank database. The one species hit
a congeneric sequence. Meanwhile, for the H3,
only the reference sequence of one species wasavailable. six species hit at the genus level, while
three species hit only at the family level.
Phylogenetic analysis
Phylogenetic analyses on the datasets A (only
COI), C (only H3), and concatenated datasets (Dand E) showed well supported trees (Fig2, Fig3).
All species were monophyletic in the COI trees,
but Chlorostoma xanthostigma and Omphalius

41

Figure2. Maximum-likelihood tree of our samples under GTR+Gamma model with support rate of Neighbor-joining(NJ) tree. The tree on the right side was analyzed using whole H3 sequence data, while
the left one using whole COI sequence data. Numbers above the node represent bootstrap values (1000 replicates).

SEE - Nagoya, Japan, Nov.12-14, 201842

Figure2. Maximum-likelihood tree of our samples under GTR+Gamma model with support rate of Neighbor-joining(NJ) tree. The tree on the right side was analyzed using whole edited sequence data,
while the left one using sequence data of removing no-3rd codon position. The number above the node represent bootstrap analysis after 100 replicates.

SEE - Nagoya, Japan, Nov.12-14, 201843

SEE - Nagoya, Japan, Nov.12-14, 2018

identification purposes. All results considered,
we thus suggest that using at least two genemarkers, the mitochondrial COI and nuclear
Histone H3, for barcoding purposes, will provide
more reliable results. Moreover, utilizing two genemarkers or more is useful as a fail-safe in DNA
Barcoding and eDNA studies: one marker genemight pick sequences of organisms uncollectedusing another marker gene.

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104–106.
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[9] Okutani T., Marine Mollusks in Japan inJapanese, The Association of Japanese
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1–20.
[12] Colgan D.J., McLauchlan A., Wilison G.D.F.,
Livingston S.P., Edgecombe G.D., MacaranasJ., Cassis G., Gray M.R., Histone H3 and U2
snRNA DNA sequences and arthropod
molecular evolution, Australian journal of
Zoology, Vol. 46, Issue 5, 1998, pp. 419–437.
[13] Katoh, K., Rozewicki J., Yamada K.D.,
MAFFT online service: multiple sequencealignment, interactive sequence choice andvisualization, Briefings in Bioinformatics,
bbx108, 2017, pp. 1–7.
[14] Castresana J., Selection of conserved blocks
from multiple alignments for their use in
phylogenetic analysis, Molecular Biology and
Evolution, Vol. 17, Issue 4, 2002, pp. 540–552.
[15] Maddision W., Maddison D., MESQUITE: amodular system for evolutionary analysis,
Evolution Vol. 11, Issue 5, 2009, 824[16] Cunha R. L., Blanc F., Bonhomme F. andArnaud-Haond S., Evolutionary patterns in

CONCLUSION
We were successful in providing novel sequence
data for 10 intertidal shelled gastropod species
collected from Nada coast in central Wakayama,
especially for the Histone H3 gene. Since oursamples are vouchered as museum collections(Table. 1), the sequences we provide here will be
useful as references for future DNA Barcoding andeDNA studies. Moreover, the sequences could also
be useful for future molecular phylogenetic studies
on gastropods.

REFFERENCES[1] Hebert P.D., Cywinska A., Ball S.L.,
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barcodes, Vol. 270, Issue 1512, 2003, pp. 313–
321.
[2] Appeltan W., Ahyong S.T., and other 111
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Species Diversity, Current Biology, Vol. 22
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[3] Orr J.C., Fabry V.J., Yool A., and other 24
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over the twenty-first century and its impact on
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pp. 681–686.
[4] Rodolfo-Metalpa R., Houlbaèque F.,
Tambutté É., Boisson F., Gabbini C., Patti F.P.,
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[5] Fuse S., Nishikawa T., Abe N., Fukui Y.,
Yamamoto T., Yamanishi R., Reef organisms
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Wakayama Prefecture (1). The Nanki

44

SEE - Nagoya, Japan, Nov.12-14, 2018

pearl oysters of the genus Pinctada (bivalvia:
Pteriidae), Vol. 13, Issue 2, 2011, pp. 181–192.
[17] Bouilly K., Chaves R., Fernandes M. andGuedes-Pinto H., Histone H3 gene in the
Pacific oyster, Crassostrea gigas Thunberg,
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andcytogenetic
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Issue 2, 2010, pp. 111–121.
[18] Temkin I., Molecular phylogeny of Pearl andtheir
Relatives(Mollusca,
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Pterioidea), BMC Evolutionary Biology, Vol.
10, 2010, 342.
[19] Silvestro D., Michalak I., raxmlGUI: agraphical front-end for RaxML, Vol. 12, Issue
4, 2012, pp. 335–337.

[20] Kumar S., Stecher G., Tamura K., MEGA7:
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1870–1874.
[21] Sasaki T., Malacology (in Japanese),
University of Tokyo Press, 2010, pp. 57–58.
[22] Phillips M.J., Penny D., The root ofmammalian tree inferred from whole
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171-185.

45

4th Int. Conf.on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

THE EFFECTS OF THAI MASSAGE ON LEG MUSCLEOXYGENATION AND TIME TO FATIGUE IN
HEALTHY MALE SUBJECTS
Wirapong Sucharit1, Wichai Eungpinichpong2, Uraiwan Chatchawan3, and PanneePeungsuwan4
1Back, Neck and Other Joint Pain Research Center (BNOJP), Thailand
2,3,4
Faculty of Associated Medical Science, KhonKaen University, Thailand

ABSTRACT
Thai massage is a kind of the alternative medicine commonly used in Thailand for relieving of muscle fatigue
and pain. Several studies reported that it can increase blood circulation. This may be due to increasing muscle
oxygenation and time to fatigue. However, there is no evidence to support. A cross-over study design was
employed to evaluate the effects of Thai massage on leg muscle oxygenation, time to fatigue and muscle force.
Twenty-five healthy males were allocated to receive isometric exercise by performing series of 10s of sustained
contraction and 5s rest until they reach peripheral fatigue point where the quadriceps torque declined to less than
60% of peak torque in the last 10 times (control period). Conversely they received a 60-minutesession of Thai
massage before isometric exercise (massage period). The results showed that after massage, the muscle
oxygenation was significantly increased (79.47±9.24%) (P< 0.05) when comparing to control period(75.04±10.68%). In addition, the time to fatigue and quadriceps muscle force revealed no significant differences(P>0.05) although the massage period tended to have more prolonged duration (8.74±2.68 min.) than the control
period (7.82±1.79 min), and massage period showed higher quadriceps muscle force. As a result, Thai massage
is effective to increase muscle oxygenation levels. Also, it seems to be associated with increased duration ofisometric muscle fatigue and higher muscle force.
Keywords: Thai massage, muscle oxygenation, time to fatigue, isometric exercise.
assessment [7]-[10].
The sustain isometric muscles contraction
increasing intramuscular pressure (IMP) linearly andultimately reaches a critical level which compresses
intramuscular blood vessel resulting in impaired
circulation [11], alterations in O2 delivery, and othersubstrate. These affect working muscles and lead tolower muscle oxygen saturation throughout exercise[12], which causes increased acidity of blood andmuscle cells [13], [14].Additionally, the study ofHepple [15] on localized muscle fatigue reports thathypoxic or ischemia condition of exercise is related
to muscle force decreased. Therefore, oxygen is an
important factor contributing to muscle fatigue[16]-[18]. However, the study of Murthy [19]determining the relationship between muscle
oxygenation and twitch force demonstrates positive
correlation (r = 0.78). Also, this study shows thatischemia and muscle hypoxemia is probably thecause of muscle fatigue. Conversely, TTM canincrease local muscle microcirculation, lymph flow,
and muscle flexibility but reduce muscle stiffness[1]. Thus, this study speculates that TTM may
improve muscle oxygenation, time to localizedmuscle fatigue, and muscle force.

INTRODUCTION
Basic characteristic of Traditional Thai Massage(TTM or Nuad Thai) includes deep pressure
massage along the meridian lines (SenSib) of the
body using sustained pressure by thumbs, palms or
elbows of a practitioner, and muscle stretching
technique.Moreover, TTM is also used in many
athletes or patientsfor increasing muscle blood
circulation and time to fatigue; however, there is not
any evidence to support these methods [1]. Several
studies report that TTM can increase skin blood
flow, skin temperature, and muscle blood volume,
but the study has used Laser Doppler technique
where the depth of measurement may not reach themuscle layer, so stimulation of muscle blood flow
has not been verified [2].
Recently, near infrared spectroscopy (NIRS) was
developed to measure clinical muscle with
17.5mm.depth length of measurement. NIRS is a
non-invasive technique and multiple-wave-length
method based on the principle of Beer-Lambert law
used for continuous measurement of muscle bloodflow including intravascular hemoglobin (Hb), intra
muscular myoglobin (Mb), muscle oxygenation, andtissue oxygen index [3]-[5]. Currently, NIRS hashigh reproducibility and agreement with gold
standard techniques [6]. Previous studies show thatNIRS can be used to study both athlete and clinical46

4th Int. Conf.on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

maximal isometric voluntary contraction (MIVC)
i.e. 10s for sustain and 5s for rest until reaching the
localized muscle fatigue; the point at which the last
10 contractions decreased less than 60% of peaktorque. The peak torque was defined as the highest
torque obtained from the first 3 maximal isometriccontractions at baseline [29] (Fig.2).

MATERIALS AND METHOD
Subjects
Male healthy subjects were recruited using oral
requests and bulletin boards. They were screenedby researcher and rechecked by internist usingdeveloped inclusion criteria; male between 18-35
years of age, no history of cardiopulmonary
problems (i.e. heart arrhythmias, aortic stenosis,
pulmonary embolus), no reported hypertension (i.e.
uncontrolled hypertension with diastolic above
110mmHg. and systolic above 180 mmHg.) [2],[20]-[21], no present acute pain in isometric exercise[21], and values of adipose tissue thickness (ATT)
less than 6.7 mm [5].Subjects must not recently
receive caffeine, nicotine, alcohol, and mixed mealor a glucose load within 30 min well as perform any
extensive physical activity [20].
Twenty eight male subjects initially enrolled inthis study. But, two subjects dropped out from thestudy due to loss of follow up in final session.
Twenty six subjects (22.62±2.43 years of age; height
173.2±6.6 cm; body mass 68.8±6.9 kg; BMI
22.9±2.0; ATT 3.9±1.2 mm) completed the study.
Each subject was informed about the experimental
procedures and signed an informed consent
statement before taking part in the study. The study
was approved by the Human Research Ethics
Committee of KhonKaen University (Fig.1).

Assessed for eligibility (n=28)
Randomization

Period I

Sequence I
Rest(n=14)

Sequence II
Arterial
Compression(n=14)

Period II

Washout period 1 week

Arterial
Compression(n=12)

Rest(n=14)

Fig. 1 Procedures of experimental study
Measurements

Procedures
Muscle oxygenation was measured by NIRS(MOXY oxygen monitor; SROC: r = 0.842-0.993,
ICC: r = 0.773-0.992) [30]. It is noninvasive
technique which is able to continuously measure
covering after received intervention, highest muscle
force period, continuous MVIC to fatigue muscle
force period, and recovery period to monitor thechanges in muscle tissue saturation. The probe of
NIRS was positioned on the belly of right vastus
lateralis muscle (about 10 cm from the center of thepatella and 25º laterals to the midline of the thigh)[31]. Pen-marks were made in transparent to confirm
the margins of the probe to enable reproduction of
the placement position in the subsequent procedure.
The probe was secured with tape. Then black elastic
bandages were wrapped around the leg with MOXY
to protect artifacts.
Time to fatigue was recorded by video recording
starting from the first MVIC to fatigue point.
The quadriceps muscle force was measured
using a quadriceps broad [24] that Rt. distal leg atlateral malleolus was fixed with electronic scale(ICC=0.908) which passed calibrates. Then muscle
torque and muscle force were calculated by equationof joint moment as Eq. 1, 2, and 3.

Each of twenty-six male participated in two
experimental sessions conducted on separate days.
The interval between each session was one week[22] in order to avoid carrying over effects. The
subjects who meet the inclusion criteria wererandomly assigned to the first experimental session
control group or TMM group based on a computergenerated block randomization code. Then theyreceived intervention in reverse order [23].
Before getting into TTM or control group, thesubjects were allowed to wear comfortable clothes
and familiarized with the testing procedure by
performing isometric muscle contraction for 5 times.
Later, subjects who were randomized into TTM
group were asked to lie in a supine position on atreatment table for one-hour Thai massage by anexperienced therapist while control group lie in thesame position only. Then both groups received
fatiguing protocols using a quadriceps broadconnected with electronic scale. The subjects
comfortably lied supine with the Rt. Knee joint
flexion at 25º-30º on quadriceps broad while theopposite leg was placed in the appropriate posture,
and arms were placed across the chest with eachhand clasping the opposite shoulder during testing[24]-[28]. The subjects were asked to perform47

4th Int. Conf.on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

oxygenation was statistically significant higher inmuscle oxygenation after received TTM period thancontrol group 4.43% (79.47±9.24%, 75.04±10.68%;
P<0.05 respectively). However, when both of themreceived MIVC exercise, both TTM and control
groups tend to be statistically significant lower inmuscle oxygenation (P<0.05) comparing to after
received intervention period. Moreover, in recovery
period after subjects received MIVC exercise
protocol, they showed higher muscle oxygenation ofboth groups comparing to resting period. However,
TTM tended to be higher in recovery muscle
oxygenation than control groups without statisticalsignificance (Tab. 1 and Fig.3).

Fig. 2 Position of moment arms and joint angle
EquationsTime to Fatigue

Muscle torque can be calculated based on
magnitude of force multiplied by distance from thefulcrum dragged perpendicular to the force as theequations below [32]:F2 = ma
F2 = (kg) (9.8m/s2)
M2 = F2 ×r2
M2 = F2 cos35º ×r2

Time to quadriceps muscle fatigue in TTM group(8.74±2.68 min.) was increased to 0.92 mincomparing with control group (7.82±1.79 min).
However, there was not statistically significant(P >0.05) between groups (Fig.4).

(1)

Quadriceps Muscle Force(2)

The highest quadriceps muscle force tended toincrease in TTM group (2727.50±860.84 N.) to
156.60 N. comparing with control group(2570.90±669.64 N.), but it was not statisticallysignificant. In addition, the fatigue quadriceps muscle
force was higher in TTM (1334.37±449.12 N.) thancontrol group (1218.96±248.42 N.), but it was notstatistically significant (Tab.1).

Quadriceps muscle force can be calculated onbalance of joint moment.
ΣM = 0M1+M2 = 0
F1 cos X°(r1) + (-)F2 cos 35° (r2) = 0
F1 = F2 cos 35° (r2)/ cos X°(r1)(3)

Muscle Oxygenation(M =magnitude of moment or torque, F= magnitudeof leg kick (kg), r=distance (m) from the fulcrum
dragged perpendicular to the force)
Statistical Analysis
Subjects’ baseline characteristics were presented
as mean ± standard deviation (SD). Each variable
was evaluated by Shapiro–Wilk test in terms ofnormal distribution. The carryover effects were
measured sequence, period, and treatment effects
using cross analysis methods [36] and sample t-tests.
Comparisons for the dependent variables withingroups were analyzed using repeated measures
ANOVA. Paired sample t-tests analyses were used tocompare the pairs of means between groups. Data
were analyzed using the SPSS (IBM SPSS, version23.0). Statistical significance was set at P<0.05.

Time (min.)Fig. 3 The mean value of vastus lateralis muscle
oxygenationlevels(n=26)
after
receivedintervention (I), highest muscle force period (II),continuous MVIC to fatigue muscle force period(III-IV), and recovery period (V).

RESULTS
Muscle Oxygenation
Muscle oxygenation represented data fromtwenty-six subjects. TTM revealed that muscle
48

4th Int. Conf.on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

Minutebetween muscle oxygenation and muscle force. Thiscan be described that measurement method
implemented in the study has an effect on IMP
increases during MVIC exercise that affects
mechanical compression of local blood vessel
resulting from force of contraction going up thatcauses an increase in the capillary perfusion. Thus,
fluid from the vascular space gets into the interstitial
tissue resulting in the increase of IMP [11], [12].
Moreover, MVIC leads to hypoxic condition thatcauses the decrease of arterial oxygen content(CaO2). As a result, hypoxic sensor such as
endothelium cells, vascular smooth muscle cells, andRBC is stimulated to produce NO and PGs, sohigher blood flow and muscle oxygenation was
found in recovery period. In addition, in recovery
period of TTM group tends to get higher thancontrol group because massage can stimulate thecreation of NO, and it is possible to decrease IMP.
Nevertheless, further study should be carried on[34], [35].
Time to localized muscle fatigue of TTM groupis longer than control group for 0.92 min. that can beseen from muscular acidity. In other words, duringisometric exercise, anaerobic respiration is
stimulated and inorganic phosphate (Pi) includinghydrogen ions (H+) are produced influencing acidityof blood and muscle cells [14]. Moreover, thisacidity slow down enzyme activity, and muscle isaggravated that can lead to nerve ending, pain, andirritation of the central nervous system [14]. On thecontrary, the present study shows increased muscle
oxygenation that reduces the acidity of the muscle
cells. In other words, when O2 in both bloodconcentration and muscle oxygenation increases,
bicarbonate (HCO3-) also increase at the same time,
so acidity is lower. This is the theory clarifying thatfatigue can be delayed, and exercise can becontinuously carried on. However, there is notstatistical significance for time to localized muscle
fatigue. Also, local muscular fatigue protocol may
be inappropriate, so different metabolic demands are
imposed.
Highest quadriceps muscle force increase to156.60 N. after TTM, but there is not statisticalsignificance. However, the increase of muscle force
can be explained by physiological effect thatmassage can increase blood circulation and oxygen
delivery to working muscle. Additionally, it candecrease metabolic waste products from anaerobic
respiration [33]. On the other hand, during MVIC,
metabolic waste products is produced metabolize
from anaerobic respiration such as Pi, H+ and lactic
acid. This metabolize is stored within the muscle
cells where the Pi is allowed to bind to Ca2+ andprecipitate, respectively. As a result, Ca2+ isdecreased, and cross-bridge turnover is decreased,
eventually [15].

Fig. 4 Time to fatigue between TTM and control
group (n=26)

DISCUSSION
TTM affects many mechanism such asmechanical pressure on tissues (increased muscle
compliance, ROM, and decreased tissue adhesion)[1] and changes tissue circulation (increased skinand muscle blood flow) described by physiologicaleffects [33]. This investigation evaluates the possible
increased muscle oxygenation, time to fatigue, andmuscle force.
Influence of TTM can stimulate both skin andmuscle blood circulations measured by laser
Doppler flow meter. However, this effect is thought
to help enhance muscle oxygenation which ismeasured by NIRS. The present study shows
significant increase of muscle oxygenation in periodof after received intervention 4.43% after receiving
TTM for one hour. This result is consistent withprevious studies [1], [33], and it is supported byphysiological mechanism. After massage, local
heatingincreases and results in hyperaemia of skinand intramuscular temperature, so O2 circulated withhemoglobin into myoglobin may be higher. The
present study also reveals higher level of muscle
oxygenation which agrees with previous studies [3],[4], [6], [9], [33]. Conversely, the study of
Weerapong [33] shows that there could be several
possible mechanisms such as psycho physiological,
biomechanical, and neurological effects. Besides,
the result shows that during MVIC exercise at
highest muscle force period of both TTM andcontrol group, muscle oxygenation is rapidly lower
and gradually increases reversing with the decreaseof muscle force until recovery period which tends tobe higher in muscle oxygenation comparing to after
received intervention period. The present study isdifferent from the study of Murthy [19] in case ofmeasurement method of the muscle contraction
amplitude. Murthy uses electrical muscular
stimulation, but compression to vascular cannot beseen, so it can lead to positive correlation between
muscle oxygenation and muscle force. Nevertheless,the present study discovers negative correlation49

4th Int. Conf.on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051
Table 1 the comparisons of muscle oxygenation, muscle force, and time to fatigue between control and TTM
group.
OutcomeSeq.

Period 1
Mean ± SD

Period 2
Mean ± SD

Mo2 after
received
INT.

177.66±9.95

77.46±11.19

2

81.48±7.2872.42±11.41

1

25.75±23.52

24.91±20.37

2

32.14±26.36

32.07±26.26

1

48.83±27.42

50.33±22.82

2

59.07±23.62

54.50±22.49

1

83.83±7.04

83.25±7.46

285.79±5.06

81.86±7.28

12527.39±599.57

2747.95±613.80

22707.06±1107.88

2614.42±739.70

11222.52±230.60

1347.71±427.40

21321.034±70.84

1215.40±266.23

1

7.56±2.21

8.90±2.65

28.59±2.70

8.08±1.37

Mo2 ofhighestforce
Mo2 offatigueforce
Mo2 ofrecoveryHighestmuscleforce
Fatiguemuscleforce
Time toFatigue

Effect size

95% Conf. IntervalP

I (-4.62)
II (0.31)
III (-4.43)(-8.10 to -1.14)(-3.38 to 4.00)(-7.91 to -1.90)

0.01*
0.86
0.01*

I (-4.50)
II (-3.38)
III (0.38)(-10.12 to 9.22)(-12.04 to 5.27)(-9.29 to 10.05)

0.92
0.42
0.94

I (-1.54)
II (-3.60)
III (-3.04)(-7.18 to 4.10)(-12.96 to 5.76)(-8.68 to 2.61)

0.57
0.43
0.28

I (-2.26)
II (-0.14)
III (-1.67)(-5.49 to 0.98)(-2.35 to 2.07 )(-4.91 to 1.56)

0.16
0.90
0.30

I (63.96)
II (-11.54)
III (-156.6)(-163.22 to 291.14)(-318.32 to 295.24)(-383.78 to 70.58)

0.57
0.94
0.17

I (9.78)
II (8.45)
III (-115.41)(-140.18 to 159.75)(-119.40 to 136.30)(-265.37 to 34.55)

0.90
0.90
0.12

I (0.41)
II (-0.06)
III (-0.92)(-0.83 to 1.65)(-0.77 to 0.66)(-2.16 to 0.33)

0.50
0.88
0.14

Abbreviations: INT.; Intervention, I; Period effect, II; Carryover effect and III; Treatment effectNote: The data were presented using mean ± SD which were analyzed by cros analysis (method of Alman DG.).
*P < 0.05
CONCLUSION

University, Thailand.

This study evaluated the effects of TTM on
muscle oxygenation, time to fatigue, and muscle
force. The results show that TTM increases muscle
oxygenation after received intervention period, andit seems prolong duration of time to fatigue andhigher muscle force. It would be interesting tocharacterize the effect of TTM for boxing, tennis or
endurance exercise and to analyze its possible
influence on muscle oxygenation, time to fatigue,
and muscle force in the subsequent performance.

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ACKNOWLEDGEMENTS
Financial support for this research is granted by
Back, Neck and Other Joint Pain Research Center(BNOJP), and this research work is partially
supported by Thai massage room at 5thfloor,
Faculty of Associated Medical Science, Khon Kaen50

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

APPLICATION OF SCMR AND FLUORESCENCE FOR
CHLOROPHYLL MEASUREMENT IN SUGARCANE
Darika Bunphan1*, Naris Sinsiri1 and Ruchuon Wanna1
Department of Agricultural Technology Faculty of Technology, Mahasarakham University,
Mahasarakham 44150, Thailand*Corresponding author: e-mail; darika.bu@msu.ac.th
1

ABSTRACT
Chlorophyll is necessary for photosynthesis in plant and also affecting for crop yield, chlorophyll can bedirectly measured however, that method is destructive leaves. In sugarcane, indirect methods were used for
drought or stress condition however literature is lacking for normal condition. The objective of this research was
to study on relationship between directly and indirectly chlorophyll measurement. The experiment was conductedunder two locations in Mahasarakham Thailand. RCBD with 4 replications and 16 varieties were used. The
chlorophyll content (CC), SPAD chlorophyll meter reading (SCMR) and chlorophyll fluorescence (CF) were
measured five times and a month interval between 8-12 months after planting. The results revealed that CC andSCMR of sixteen varieties in both locations were significantly different however, CF was not significantly
different. The interaction between location and varieties were found. The relationships between methods ofmeasurement were also found. At Kut Rung, CC and SCMR was positive correlated in 8 to 12 months except 11
months (0.71**, 0.55*, 0.77** and 0.78** respectively). Another location, CC and SCMR was correlated in 8 and9 months (0.51*and 0.73** respectively) and CF was not correlated with CC and SCMR. Combined analysis, CC
was positive correlated with SCMR at 8-12 months except 11 months (0.61*, 0.55*, 0.63** and 0.50*
respectively). SCMR is a useful strategy for indirectly chlorophyll measurement in sugarcane. However, CF could
not apply for measurement in this case. For further research, we are looking for relationship between chlorophyll
content and sugarcane yield or other desirable characteristics in sugarcane.
Keywords: Correlation, Chlorophyll content, SPAD chlorophyll, SCMR

indirect methods however direct method must be
destructive leaves, expensive, laborious and time
consuming. Indirect methods are the alternative
methods which are more rapid and straightforward.
Generally, chlorophyll measurements are usuallyusing for drought condition for detecting droughttolerance in plant including sugarcane, howeverliterature is lacking for normal condition and therelationship between direct and indirect methods
require more study in normal condition. Therefore,
the objective of this research was to study on
relationship between directly and indirectly
chlorophyll measurement to determine the rapid andaccurate methods for chlorophyll measurement insugarcane.

INTRODUCTION
Sugarcane (Saccharum officinarum L.) is known
as effective crop for sugar and biomass production
according to bio-fuel production. It can produce highcane yield and high quality of juice, however seem tobe greatly reduced by drought stress and others [1].
Sugarcane is one of the most important cash crop in
Thailand which occupies around 1.76 million ha [2],and most of sugarcane production in Thailand isunder rain-fed condition and drought is usuallyappearance during growth season and it affect toreduce growth and yield of sugarcane. Several
previously researches studied on effect of drought tophysiological characteristics such as chlorophyll
content, SCMR [3]-[5], chlorophyll fluorescence [5],cane yield [6]-[7], root length, root dry weight,
root/shoot ratio, stalk diameter and biomass [8].
Chlorophyll is a pigment that is important forphotosynthesis in plant and also related to crop yield.
Photosynthetically active radiation (PAR) is absorbed
by chlorophyll and accessory pigments of chlorophyll
protein complexes and related to PS I and II [9].
Analysis of chlorophyll content is important forevaluating health or detecting and quantifying plants
tolerance to drought stress [10]. Chlorophyllmeasurement can be measured both direct and

MATERIAL AND MATHEODS
Plant Material
Sixteen varieties of sugarcane namely KK06501, KK07-478, NSUT08-22-3-13, RT2004-085,
CSB06-2-15, CSB06-2-21, CSB06-4-162, CSB06-520, TBy27-1385, TBy28-0348, MPT02-458, MPT03166, 91-2-527, KK3, LK92-11 and KPS01-12 wereused. All of varieties were improved fromgovernment agency and private company in Thailand.

53

SEE - Nagoya, Japan, Nov.12-14, 2018

found interaction between location and varieties in
SCMR and CC and also two parameters weresignificantly difference, however an interaction
between CF was not found. At 8 months after
planting, KKU06-501 had the highest SCMR (44.15
SPAD Unit) following CSB06-2-21 and NSUT0822-3-13 (42.30 and 41.86 SPAD unit, respectively),
however, at 9 months NSUT08-22-3-13 had thehighest SCMR following KK06-501 (42.06 and 40.76
SPAD unit, respectively). Whereas 91-2-527 had thehighest SCMR at 10 months following RT2004-085
and CSB06-2-15, however at 11 and 12 months
KK06-501 had the highest SCMR (40.73 and 40.13
SPAD unit, respectively) following CSB06-4-162(40.09 and 39.24 SPAD unit, respectively) (Table 1).
In previous studies, SCMR was measured at 90, 100
and 110 days after transplanting (DAT), they reported
that SCMR at 90 and 110 DAT compared between
drought and FC was not significantly different(average SCMR at 90 and 100 DAT was 33.23 and33.44 SPAD unit, respectively) but SCMR at 100
DAT had significant between stress and FC (27.36
and 30.06 SPAD unit, respectively) [3]. In normal
condition, SCMR was observed at 60, 90, 120 and
150 days after planting (DAP), they found that
increasing trend of SCMR up to 120 DAP in all
promising clones and decreasing trend was noticed insome clones and SCMR of all clones was under 50
SPAD unit [6] and this value was similar to present
study however, in present study SCMR was observed
during 8 to 12 months after planting whereas previous
study was done 4 times during 60-150 DAP.
Sudhakar [4] reported that SCMR at 60 and 120 DAP
of 14 genotypes under irrigated condition was
significantly different and the value ranged between
35.0 to 40.5 for 60 DAP and 35.5 to 46.6 for 120
DAP, the SCMR values were slightly lower thanpresent study. Radhamani, Kannan and Pakkiyappan[13] reported that SCMR at 3 growth stages wasinvestigated in 15 cultivars of sugarcane and they
showed significant at different stages, an average
SCMR value at tillering, grand growth and maturity
was 24.34, 24.04 and 22.00 respectively. SCMR
value at 120 DAP of 12 cultivars was significant that
ranged between 39.63 to 51.15 [14]. Moreover,
SCMR was measured in other crops in normal
condition i.e. sweet sorghum [15], [16], sorghum andbarley. The SCMR of sweet sorghum in 50% days toflowering ranged between 36.03-48.36 that the values
were not different with sugarcane and SCMR had
related to biomass yield (r=0.39*) [15] but thisrelationship did not study in our research. It would bestudied in further research.
Chlorophyll content (CC) at Kut Rung was
significantly different all of five times interval amonth during 8-12 months. At 8 months, NSUT0822-3-13 had highest CC whereas KK06-501 had thehighest CC at 9 months, however at 10 months bothvariety NSUT08-22-3-13 and CSB06-5-20 had

Experimental design
The experiment was conducted in 2016-2017
under rain-fed condition at two locations in Maha
Sarakham province where is located in Northeast of
Thailand. The first location was Kut Rang district and16 varieties were planted in November 9 2016.
Another location was Wapi Prathum district, it is andsugarcane was planted in December 18 2016. The
experiment was laid out in randomized complete
block design (RCBD) with 4 replications, 4 rows aplot, 50 cm between plant and 130 cm between row,plot size was 5.2 × 5 m2 (Wapi Prathum district) and5.2 × 6 m2 (Kut Rang district). Chemical fertilizer
formula 15-15-15 at rate 50 kg/rai at 4 and 6 months
after planting.
Data Collection
Chlorophyll content (CC), SPAD chlorophyll
meter reading (SCMR) and chlorophyll fluorescence(CF) were observed 5 times from 8 to 12 months after
planting and a month interval, three parameters were
measured on 2nd or 3rd expanded leaf from the top.
The SCMR was measured using by SPAD-502 meter(Minolta SPAD-502 meter, Tokyo, Japan). The data
points were recorded at three positions along thelength of leaf blade (avoid veins and midribs) andthen data points were averaged as a single value. The
CC in leaves was measured by the method describedby Moran [11]. Briefly the leaf was cut one small leaf
disc with the area 1 cm2 using cork border, the leaf
disc was placed in a vial containing 5 ml DMF (N, Ndimethylformamide) and incubated in 4 °C for 24 hin dark. The chlorophyll extract was measured at 647
and 664 nm by spectrophotometer. The equations to
calculate for total chlorophyll, chlorophyll a (Chl a)and b (Chl b) were as follows: Chl a = 12.64 A664-2.99
A647, Chl b= -5.6 A664+23.24 A647, expressed in µg
cm-2. The CF was measured two positions in middleof leaf and midrib was avoided, Fv/Fm was used andaveraged as single value, the CF was measured using
chlorophyll fluorescence meter (PAM-2000, Heinz
Walz GmbH, Germany). The measured leaf was darkadapted for 30 min using leaf clips (FL-DC, OptiScience) before fluorescence measurements. The
chlorophyll fluorescence was determined following
the procedures of Maxwell and Johnson [12].
Statistical Data Analysis
Analysis of variance (ANOVA) was conductedon the collected data using STATISTICS 9 andtreatment means were separated using DMRT at 5 %probability level. Location × treatment was analyzed
and correlation among CC SCMR and CF were done.
RESULTS AND DISCUSSIONS
The results showed that SCMR and CC weresignificantly different in both locations however, CF
was not significantly different.
For combine analyzed between location we
54

SEE - Nagoya, Japan, Nov.12-14, 2018highest CC, moreover NSUT08-22-3-13 had thehighest CC at 11 months as well and CSB06-4-162
had the highest CC at 12 months (data not show). The
CC at Wapi Prathum district was significantly
different, KK06-501 had the highest CC at 8 months
whereas CSB06-5-20 had the highest CC at 9 months.

However, at 10 months CSB06-2-15 gave the highest
CC and MPT02-458 gave the highest CC at 11
months, 91-2-527 have the highest CC in 12 months(data not show).

Table 1 SCMR of 16 sugarcane varieties during 8-12 months after planting under two locations
variety

SCMR (SPAD unit)
10 m
35.04abc
29.20e34.86abc
35.63ab35.60ab
31.81d33.69a-d
35.01abc
34.25a-d
32.01d35.53ab
31.81d35.86a34.20a-d
32.71cd
33.21bcd
**
7.54

8m
9m
11 m
KK06-501
44.15a40.76ab40.73a
KK07-478
37.94c-g
33.18e33.30fgh
NSUT08-22-3-13
41.86abc
42.06a34.66d-h
RT2004-85
37.90d-g
33.31e36.05c-f
CSB06-2-15
40.14b-f
39.28abc
36.40cde
CSB06-2-21
42.30ab37.20bcd
36.70cd
CSB06-4-162
41.45a-d
37.94bc
40.09ab
CSB06-5-20
37.85d-g
37.54bcd
33.69e-h
TBy27-1385
41.13a-d
37.03cd
32.84ghi
TBy28-0348
35.56g36.08cde38.28abc
MPT02-458
37.06efg
36.50cde36.60cd
MPT03-166
36.50fg
34.18de35.45c-g
91-2-527
40.74a-e
36.43cde37.38bcd
KK3
38.61b-g
38.74abc
32.08hi
LK92-1139.04b-g
36.60cde30.08i
KPS01-1240.56a-e
37.48bcd
34.71d-hF-test******CV (%)
10.07
9.71
8.02
** significant at P< 0.01,
Mean in the same column followed by the same letter(s) are not significantly different
For combined analysis, CC was significantly at 812 months except 11 months after planting. At 8
months, both variety KK06-501 and CSB06-4-162
gave the highest CC following NSUT08-22-3-13(8.92, 8.68 and 7.41 µg cm-2 respectively). At 9
months we found that CSB06-2-15 had the highest
CC following CSB06-5-20, whereas NSUT08-22-313 showed the highest CC at 10 months following
CSB06-5-20 and CSB06-2-15 and 12 months
CSB06-4-162 had the highest CC following 91-2-527
and KK06-501 (8.84. 8.41 and 8.26 µg cm-2
respectively) (Table 2). The previous researches,
chlorophyll content under drought and field capacity(FC) was not significantly different at 90 and 110
except 100 DAT, it was different CC between drought
and FC (3.78 and 6.64 µg cm-2 respectively). The
average CC of 10 cultivars ranged between 4.07 to
7.65 (90 DAT), 4.07 to 6.07 (100 DAT) and 4.89 to
9.21 µg cm-2 (110 DAT) [3], in the one hand, total
chlorophyll under stress was lower than non-stresscondition [17], that results were slightly lower than

12 m
40.13a33.49cde33.78cde36.37a-d
39.16ab35.40bcd
39.24ab32.06de33.63cde
36.66abc
36.14a-d
33.78cde
39.09ab33.80cde32.41cde
29.64e**12.31

present study especially CC under FC condition
because present research studied on non-stresscondition and chlorophyll content was observed at
different growth stage. Chlorophyll content wasmeasured under non-stress condition at 3 growthstage; tillering, grand growth and maturity stage, theresults showed that chlorophyll content of 15 varieties
had significant and total chlorophyll content
decreased with stage of plant [13]. However, present
study chlorophyll content was observed 5 times and amonth interval therefore the results of both study wasdifferent.
The association between SCMR, CC and CF, at
Kut Rung, CC and SCMR were positive correlated in
8 to 12 months except 11 months (0.71**, 0.55*,
0.77** and 0.78** respectively) (data not show). For
another location, CC and SCMR were positive
correlated only in 8 and 9 months (0.51* and 0.73**
respectively) (data not show) and CF was notcorrelated with CC and SCMR.

55

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Chlorophyll content (CC) of 16 sugarcane varieties during 8-12 months after planting under two locations
variety
KK06-501
KK07-478
NSUT08-22-3-13
RT2004-85
CSB06-2-15
CSB06-2-21
CSB06-4-162
CSB06-5-20
TBy27-1385
TBy28-0348
MPT02-458
MPT03-166
91-2-527
KK3
LK92-11
KPS01-12
F-testCV (%)

8m
8.92a
5.09e
7.41b
5.93cde6.73bc
6.14cde
8.68a
6.50bcd
6.53bcd
6.42bcd
5.96cde5.63cde6.11cde6.06cde5.84cde5.31de**19.55

Chlorophyll content (µg cm-1)
9m
10 m
11 m
9.03abc
13.85a-d
5.89
5.70g
12.56efg
4.81
8.40a-e14.94a6.29
8.24a-e12.89d-g
6.56
9.39a
14.48ab
6.14
7.88c-f
12.31fg
5.36
8.74a-d14.16abc
6.04
9.37ab
14.63ab
4.87
7.72c-f
12.54efg
4.61
6.69fg12.21fg
6.54
7.19ef13.97a-d
7.24
8.12a-e12.04g5.79
7.53def
13.76a-e
6.21
7.49def
12.95c-g
4.86
8.04b-e13.80a-d
6.24
8.79a-d13.44b-f
4.88
**
**
ns
16.95
9.23
19.94

12 m
8.26ab4.97e
7.07bcd
5.77de6.11cde5.97cde
8.84a
7.37bc
5.97cde6.74cd
6.65cd
7.27bc
8.41ab
6.30cde6.71cd
6.16cde**21.05** and ns; significant at P< 0.01 and not significant,Mean in the same column followed by the same letter(s) are not significantly different
CC was found during 40 to 100 DAP [16], wheat
For combined analysis, the correlation(r=0.90) [19] and also found in maize [20], moreover
coefficients between SCMR and CC were calculated
SCMR was positively correlated with biomass yieldfrom means of 16 sugarcane cultivars of two locationsin sweet sorghum (r=0.39**) [15]. However, SCMR
we found that SCMR had positive correlated with CC
had positive correlated with other traits i.e. stalkat 8-12 months except 11 months after planting.
number and tiller number (r=0.72* and 0.77**
At 8 months after planting, the correlation
respectively) [7].
coefficient between SCMR and CC was positive andsignificant (r=0.61, p≤0.05) (Fig. 1a). At 9 months,
CONCLUSIONSCMR had positive correlated with CC andsignificantly different (r=0.55, p≤0.05) (Fig. 1b)
Chlrophyll content and SCMR of 16 varieties inwhereas at 10 months the relationship between
both locations were significantly different however,
SCMR and CC was positive and highly significant
CF was not significantly different. The interaction(r=0.63, p≤0.01) (Fig. 1c) and 12 months, thebetween location and varieties were found. The
correlation coefficient between SCMR and CC was
relationships between methods of measurement werepositive and significant different (r=0.50, p≤0.05)
also found. At Kut Rung, CC and SCMR had(Fig. 1d). For previous studies, the correlation
correlated in 8 to 12 months except 11 months
coefficients between chlorophyll content and SCMR
(0.71**, 0.55*, 0.77** and 0.78** respectively). For
were calculated from means of 10 sugarcane cultivars
another location, CC and SCMR were correlated in 8
at 90 and 100 DAT (r=0.78**, 0.74**) [3] whereas
and 9 months (0.51* and 0.73** respectively) and CF
SCMR and CC were calculated from 15 cultivars andwas not correlated with CC and SCMR bothsignificant correlation was found (r=0.833**) [13].
locations. Combined analysis, CC was significantly
The relationship between SCMR and chlorophyll
correlated with SCMR in 8 to 12 months except 11
content of 24 cultivars both control and ironmonths (0.61*, 0.55*, 0.63** and 0.50*
deficiency had positive correlated (0.900**) [18], thisrespectively). SCMR is a useful tool for indirectly
results were slightly higher than present study. In
chlorophyll measurement in sugarcane. However, CF
species more closely related to sugarcane such as
could not apply for measurement in this case. For the
sweet sorghum, the relationship between SCMR andfurther study, we are looking forward using the56

SEE - Nagoya, Japan, Nov.12-14, 2018knowledge from present study to estimation yield ordesirable traits in sugarcane. It could be alternative
SCMR

methods for selection or
performances of sugarcane.

good
b

SCMR

a

60

investigation

60
55

55
y = 1.3515x + 30.827
R² = 0.61*

50

50

45

45

40

40

35

35

30

30

25

25

20
4

5

6

7

8

9

20

CC10

4

5

6

7

8

9

10
CC

d

SCMR

c

SCMR

50

y = 1.3333x + 26.452
R² = 0.55*

50

45

45
y = 1.2633x + 16.838
R² = 0.63**

40

y = 1.4275x + 25.612
R² = 0.50*

40

35

35

30

30

25

25

20

20
8

9

10

11

12

13

14

15 CC
16

4

5

6

7

8

9

10
CC

Fig. 1 Relationship between SCMR and CC of 16 sugarcane varieties at 8, 9, 10 and 12 months after planting (1a,1b, 1c and 1d, respectively) under two locations in Maha Sarakham province.
ACKNOWLEDGEMENTS
This research was supported by grant from National
Science and Technology Development Agency(NSTDA). I would like to thank you Department ofAgricultural Technology, Faculty of Technology
Mahasarakham University and 4th year of undergraduate students of Department of Agricultural
Technology Mahasarakham University.

[3] Jangpromma N., Songsri P., Thammasirirak S.
and Jaisil P., Rapid Assessment of ChlorophyllContent in Sugarcane using a SPAD Chlorophyll
Meter Across Different Water Stress Conditions,
Asian Journal of Plant Sciences Vol.9, No.6,
2010, pp. 368-374.
[4] Sudhakar P., Latha P. and Babu A.M.,
Evaluation of Sugarcane Genotypes for High
Water Use Efficiency and Thermostability
Tolerance Under Imposed Moisture Stress at
Formative Stage, Sugar Tech Vol.12, No.1,
2010, pp. 72-75.
[5] Khonghintaisong J., Songsri P., Toomsan B. andJongrunglang N., Rooting and Physiology Traits
Responses to Early Drought Stress of Sugarcane
Cultivars, Sugar Tech Vol.20, No.4, 2018, pp.
396-406.
[6] Reddy A.N.G., Madhudi K.V.N., Rajeswari V.R.
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dimethylformamide, Plant Physiology Vol.69,
1982, pp.1376-1381.
[12] Maxwell K. and Johnson G.N., Chlorophyll
fluorescence-A practical guide, Journal of
Experimental Botany Vol.51, No.345, 2000, pp.
659-668.
[13] Radhamani R., Kannan R. and Rakkiyappan P.,
Leaf chlorophyll meter reading as an indicator forsugarcane yield under Iron deficient Typic
Haplustert, Sugar Tech Vol.18, No.1, 2016,
pp.61-66.

[14] Bhavana M., Kumar M.V., Bindu G.S.M. andReddy D.V.V., Study on Morpho-Physiological
Characters in Different Clones of Sugarcane(Saccharum officinarum L.), International
Journal of Current Microbiology and Applied
Sciences Vol.6, No.11, 2017, pp. 205-217.
[15] Bunphan D., Jaisil P. and Sanitchon J., Genetic
Variation and Correlation of Some Agronomic
Traits, Biomass and Ethanol Yield in Diverse
Sweet Sorghum (Sorghum bicolor L. Moench)
Cultivars, Khon Kaen Agriculture Journal
Vol.46, No.1, 2018, pp. 155-162.
[16] Bunphan D., Jaisil P., Sanitchon J., Knoll J.E.
and Anderson W.F., Association of ChlorophyllContent and Spad Chlorophyll in Diverse Sweet
Sorghum
Cultivars
Under
Different
Environments, Khon Kaen Agriculture Journal
Vol.42, No.4, 2014, pp. 605-616.
[17] Medeiros D.B., da Silva E.C., Nogueira R.J.M.C.,
Teixeira M.M., Buckeridge M.S., Physiologicallimitations in Two Sugarcane Varieties Under
Water Suppression and After recovering,
Theoretical and Experimental Plant Physiology
Vol.25, No.3, 2013, pp. 213-222.
[18] Radhamani R. and Kannan R., Nondestructive
and Rapid Estimation of Leaf ChlorophyllContent of Sugarcane using a SPAD Meter,
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Vol.5 No.4, 2013, pp.2392-2397.
[19] Udding J., Gelang-Alfredsson J., Piikki K. andPleijel H., Evaluating the relationship between
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[20] Markwell J., Osterman J.C. and Mitchell J.L,
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46, 1995, pp. 467-472.

58

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE EFFECTS OF AGROCHEMICAL RESIDUES ON AQUATIC
INVERTEBRATES IN SEMI-ORGANIC RICE FIELDS
Pattira Kasamesiri1 and Wipavee Thaimuangphol1
Faculty of Technology, Mahasarakham University, Thailand

1

ABSTRACT
We present a case study of semi-organic rice farming in which a farmer decided to change the rice farming
system from conventional to organic. This study compared the alteration of aquatic invertebrate composition anddiversity between semi-organic and conventional rice farming. Aquatic invertebrates were collected in semiorganic and conventional rice fields during the flooding periods from August to October. The results showed thata total of 4 phylum 12 taxa of aquatic invertebrates. The average abundance of aquatic invertebrates in semiorganic and conventional samples were 10,676 and 5,735 individuals/m2, respectively. The Shannon diversity
index in conventional and semi-organic samples ranged between 0.45-0.62 and 0.35-0.59, respectively. Water
quality parameter, temperature, dissolved oxygen and pH were not significantly different between two sites. The
present study found signs of chemical substance contamination in semi-organic rice fields. The abundance ofpollution indicator species in semi-organic paddies indicated that agrochemical residues persisted from former
conventional rice farming.
Keywords: Ecotoxicology, Semi-Organic Rice Farming, Aquatic Invertebrate, Soil Ecology

study to investigate the influence of rice fieldmanagements between conventional and semiorganic farming on the abundance and community ofbenthic animals.

INTRODUCTION
Rice is a semi-aquatic annual grass that is
cultivated on almost countries of the world [1]-[2].
Rice fields are temporary wetland that are important
habitats for many aquatic organisms such as
earthworm, aquatic insect, water bird and fish [3]-[5].
Agrochemical induce the rice fields are contaminatedfrom pesticides and chemical fertilizers [4]-[7]. In
conventional rice cultivation, herbicides andinsecticides are applied during the rice vegetative
growth stage to the reproductive growth stage, thismay cause a variation of benthic community [8].
Many groups of benthic invertebrate have been used
as indicator of freshwater ecology [9]-[10], [21]. The
Chironomidae in rice fields had statisticallysignificant relationship with dissolved oxygen [11].
Usually, in the soil of flooded rice fields
predominated by aquatic oligochaetes such as thetubificid Branchiura sowerbyi [12].
The rice cultivation have categories into threegroups based on cultivated methods: (1) conventional
rice farming, which have application mineral
fertilizers and pesticides, and source of water comefrom irrigation water (2) semi-organic farming, has
just developed to organic farming, the farmer appliedorganic fertilizer and bio pesticides but may havesome chemical compounds remain contamination
into rice field areas and may applied some inorganic
fertilizers [13], (3) organic rice cultivation,completely without chemical fertilizers andpesticides and the water source is fully from springwater or rainfed paddy fields [14]. The aim of this

MATERIALS AND METHODS
Study Sites and Sampling Methods
The study areas were located at Maha Sarakham
Province, northeast of Thailand. The sampling sites
cultivated rice crops by conventional and semiorganic techniques. The conventional rice cultivation
technique, the farmers burned straw stubbles with fire,applied inorganic fertilizers, herbicides, insecticides
and used gravity-fed irrigation water. In the semiorganic rice farming, the farmer prepared the soil byincorporated stubbles and soil with the tractor,
applied inorganic and organic fertilizers, avoided
herbicides or insecticides and used irrigation water.
The invertebrate samples were collected from 3
paddy fields of conventional plots (16° 20' 15" N;
103° 9' 56" E) and semi-organic plots (16° 20' 9" N;
103° 10' 13" E) and 3 replicates of each paddy field
by using sediment corer 12 cm diameter during
flooding period from August to October 2015. The
benthos were sieved through a 0.5 mm mesh net andpreserved in 80% ethanol. The water quality(temperature, pH and dissolved oxygen) were
investigated by using OAKTON (Eutech PCD 650).
Aquatic Invertebrates Identification

59

SEE - Nagoya, Japan, Nov.12-14, 2018

Benthos samples were sorted under the lightmicroscope and identified taxa to the lowest possiblelevel according taxonomic keys [20]. The benthos ofeach taxa were counted and recorded total number.

showed no significant difference because of highvariability of abundance between sampling sites.

Data Analysis

The diversity index in conventional and semiorganic was ranged between 0.45-0.62 and 0.35-0.59,
respectively. The benthos diversity index of bothstudy sites lower than previous report in conventionaland organic rice fields of Kalasin province, Thailand(0.88 in conventional, 1.36 in organic) [5].

The diversity, Evenness and Dominant Indices

The diversity and evenness indices [15] were
calculated following Eq. (1) to (3) and dominanceindex [16] used Eq. (4).

H ' = −∑ pi ln pi(1)pi = ni / N(2)

Water Quality of Soil Surface Water

E H = H ' / ln S

(3)

The water quality parameters, temperature,
dissolved oxygen and pH ranged between 26.3333.34, 2.93-8.08 and 6.11-7.50, respectively (Table
3). All parameters were no significant difference
between conventional and semi-organic paddy fields(p>0.05)

D=∑p

2
i

(4)

While H ' is the Shannon’s diversity index; pi isthe proportion of individuals found in a taxon i; ni is
the number of individuals in a taxon i; N is the total
number of individuals of all taxa; E H is the evenness
index; S is the total number of taxa; D is the dominant
index.
The benthos abundance, diversity, evenness anddominance indices between the conventional andsemi-organic rice farming were compared by using
Levene’s test for equality of variances and t-test forequality of means (significant level p-values less than0.05).

Gastropoda
10%

Arthropoda
2%(a)Oligocheata
88%
Gastropoda
8%

RESULT AND DISCUSSION

Arthropoda
1%

The Composition and Abundance of Benthos(b)
The freshwater invertebrates were found 3
phylum 12 taxa in conventional rice fields and 4
phylum 11 taxa in semi-organic rice fields. The taxa
richness showed no difference between conventionaland semi-organic. Five taxa as Chironomidae,
Ephemerellidae, Cyclopoida, Oligochaeta andViviparidae were found in all plots. While 3 taxa
(Odonata, Anisoptera, and Hirudinea) were only
observed in conventional rice fields and 3 taxa
(Nematoda, Tipulidae and Baetidae) found only semiorganic plots (Table 1).
The total numbers of benthos found inconventional and semi-organic rice fields were 1,753
and 3,266 individuals, respectively. The compositionin conventional rice fields included Oligochaeta(88%), followed by Gastropoda (10%) and Insecta(2%) whereas the semi-organic rice fields composedof Oligochaeta (91%), Gastropoda (8%) and
Arthropoda (1%) (Fig. 1). The Oligochaeta were
dominant taxa of all sampling sites.
The average abundance of benthos inconventional and semi-organic were 5,735 and
10,676 individuals/m2, respectively (Table 2).
Average abundance between rice field treatments

Oligocheata
91%
Fig. 1 The composition of benthos in (a)Conventional (b) Semi-organic rice fields.
The effects of rice field managements have notshowed significant difference in taxa richness,abundance, diversity, evenness and dominant indices(p>0.05). In contrast, apparent of some taxa may
resulted from agrochemical used in rice field areas.
Abundance of aquatic insect (Baetidae) were
negatively correlated with pesticide used inconventional rice fields [4], which this taxa waspresent only conventional paddy fields. Cyclopoida
was high abundance in semi-organic fields, it wasused as indicator of non-polluted area [17]-[18].
Same as Chironomidae was applied to indicator of
nutrient enrichment in water and sediment [6], foundmore abundance in semi-organic rice fields thanconventional plot.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Total number (individuals) of Benthos classified to taxa between conventional and semi-organic rice
farming during the cycle of flooded.
Benthos Taxa
ANNELIDA
Oligochaeta
Hirudinea
NEMATODAMOLLUSCA
Gastropoda
Architaenioglossa
Hydrobiidae
Viviparidae
ARTHROPODA
Insecta
Odonata
Anisoptera
Zygoptera
Diptera
Chironomidae
Tipulidae
Ephemeroptera
Ephemerellidae
Baetidae
Copepoda
Cyclopoida
Entognatha
Collembola
Branchiopoda
Cladocera
Crustacea
Decapoda
Ostracoda
Total number

Conventional

Semi-0rganic

1550
1
0

2964
0
7

9
161

12
247

1
1
5

0
0
0

7
0

11
1

13
0

3
1

2

16

1

0

1

0

1
0

3
1

1753

3266

Table 2 Abundance (individuals/m2), diversity index, evenness index and dominant index of benthos during theflooding period
Index

Conventional

Semi-Organic

Aug

Sep

Oct

Aug

Sep

Oct

Abundance

1,990

8,328

6,833

2,510

21,843

7,676

Diversity

0.62

0.45

0.58

0.59

0.35

0.42

Evenness

0.65

0.26

0.39

0.71

0.23

0.28

Dominant

0.63

0.78

0.69

0.63

0.81

0.78

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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 3 Water quality in rice fields
Rice fields
Conventional

Semi-Organic

Parameters
Temperature (°C)
DO (mg/l)pH
Temperature (°C)
DO (mg/l)
pH

Aug
33.33
8.08
7.14
33.43
6.97
7.50

However, the oligochaete was used as indicator of
application herbicide and positively correlated withpH in rice fields [4], [19]. The present study,
oligochaetes were found more total number in semiorganic than conventional rice fields. The represent
semi-organic rice fields in this study used water from
irrigation canal, this may cause of chemical substancecontaminated in semi-organic paddy fields, whichmake similarity of benthic community between twosites. Moreover, the farmer just change ricecultivation method from conventional to semiorganic which the chemical substance may remain insoil. This cause of low diversity and more abundanceof oligochaetes were found in both sites.

Sep
29.43
3.04
6.31
30.33
4.83
6.53

Oct
26.33
2.93
6.64
26.83
4.53
6.65

[3] Schoenly K.G., Justo H.D., Barrion A.T., Harris
M.K. and Bottrell D.G., Analysis of
Invertebrate Biodiversity in a Philippine
Farmer’s Irrigated Rice Field, Community andEcosystem Ecology, Vol. 27, Issue 5, 1998, pp.
1125-1136.
[4] Mesleard F., Garnero S., Beck N. and Rosecchi
E., Uselessness and Indirect Negative Effects ofan Insecticide on Rice Field Invertebrates,
Comtes Rendus Biologies, Vol. 328, 2005, pp.
955-962.
[5] Kasamesiri P. and Thaimuangphol W., The
Benthic Communities Comparison between
Organic and Conventional Rice Fields,
Communications in Agricultural and Applied
Biological Science, Vol. 80, Issue 3, 2015, pp.
367-374.
[6] Al-Shami S.A., Rawi C.S.M., Ahmad A.H.,
Hamid S.A. and Nor S.A.M., Influence ofAgricultural, Industrial, and Anthropogenic
Stresses on the Distribution and Diversity ofMacroinvertebrates in Juru River Basin, Penang,
Malaysia, Ecotoxicology and Environment
Safety, Vol. 74, 2011, pp. 1195-1202.
[7] Maeder P., Fliessbach A., Dubois D., Gunst L.,
Fried P. and Niggli U., Soil Fertility andBiodiversity in Organic Farming, Science, Vol.
296, 2002, pp.1694-1697.
[8] Miranda M.S., Fonseca M.L., Lima A., Moraes
T.F. and Rodrigues F.A., Environmental Impactsof Rice Cultivation, American Journal of Plant
Science, Vol. 6, 2015, pp. 2009-2018.
[9] Azrina M.Z., Yap C.K., Ismail A.R., Ismail A.
and Tan S.G., Anthropogenic Impacts on theDistribution and Biodiversity of Benthic
Macroinvertebrates and Water Quality of theLangatRiver,
Pennisular
Malaysia,
Ecotoxicology and Environmental Safety, Vol.
64, 2006, pp. 337-347.
[10] Kasamesiri P. and Thaimuangphol W.,
Oligochaeta as Bioindicator on Ecotoxicology ofConventional and Organic Rice Fields,
Communications in Agricultural and Applied
Biological Science, Vol. 82, Issue 2, 2017, pp.
81-86.
[11] Al-Shami S.A., Salmah M.R.C., Hassan A.A.
and Azizah M.N.S., Temporal Distribution of
Larval Chironomidae (Diptera) in Experimental

CONCLUSION
The present study is a case study of farmer that
decided to change the rice farming system fromconventional to semi-organic. However, we found asign of the chemical substance contamination in semiorganic farming system. The abundance of polluted
indicator species (Oligochaeta and Chironomidae) insemi-organic system was effect of pesticide or
herbicide that contaminated from source of water orresidue of agrochemical in former conventional rice
farming system.

ACKNOWLEDGEMENTS
For jointed conference was supported by
Mahasarakham University Development Fund.
Moreover, we would like to special thanks to Ms.
Thidarat Yimphung, Mr.Utai Wannagul, Ms.
Natthida Thaneepoon and Ms. Duanghathai Maliloest
for ensuring the success of the field operations.

REFERENCES[1] Muthayya S., Jonathan D.S., Montgomery S.
and Maberly G.F., An Overview of Global Rice
Production, Supply, Trade, and Consumption.
Annals of the New York Academy of Sciences,Vol. 1324, 2014, pp. 7-14.
[2] FAO, The State of Food Insecurity in theWorld, Italy: Food and Agriculture
Organization of the United Nations, 1999.
62

SEE - Nagoya, Japan, Nov.12-14, 2018

Rice Fields in Penang, Malaysia, Journal of AsiaPacific Entomology, Vol. 13, 2009, pp. 17-22.
[12] Kimura
M.,
Population,
Community
Composition and Biomass of Aquatic
Organisms in the Floodwater of Rice Fields andEffects of Field Management, Soil Science andPlant Nutrition, Vol. 51, Issue 2, 2010, pp. 159181.
[13] Lestari Y.K., Comparative Analysis ofTechnical Efficiency of Semi Organic andConventional Rice Farming in Bogor (Case in
Situ Gede and Sindang Barang Villages), Bogor
Agricultural University, 2013, pp. 7-8.
[14] Sukritiyonubowo R., Wiwik H., Sofyan A.,
Benito H.P., and De Neve S., Change from
Conventional to Organic Rice Farming System:
Biophysical and Socioeconomic Reasons,International Research Journal of Agricultural
Science and Soil Science, Vol. 1, Issue 5, 2011,
pp. 172-182.
[15] Shannon C.E. and Weaver W., The
Mathematical Theory of Communication.
University of Illinois Press, 1949, 114 p.
[16] Simpson E.H. Measurement of Diversity,
Nature, Vol. 163, 1949, p. 688.
[17] Lim R.P., Abdullah M.F. and Fernando C.H.,
Ecological Studies of Cladocera in the
Ricefields of Tanjung Karang, Malaysia,

Subjected
toPesticide
Treatment,
Hydrobiologia, Vol. 113, 1984, pp. 99-103.
[18] Adamczuk M., Mieczan T., TarkowskaKukuryk M. and Demetraki-Paleolog A.,
Rotatoria-Cladocera-Copepoda Relations in theLong-term Monitoring of Water Quality in
Lakes with Trophic Variation (E. Poland),Environmental Earth Science, Vol. 73, 2015, pp.
8189-8196.
[19] Ilyashuk B.P., Littoral Oligochaete (Annelida:
Oligochaeta) Communities in Neutral andAcidic Lakes in the Republic of Karelia, Russia,
Boreal Environment Research, Vol. 4, 1999, pp.
277-284.
[20] Mekong River Commission, Identification ofFreshwater Invertebrates of the Mekong Riverand Its Tributaries, Mekong River Commission,
2006, 274 p.
[21] Krupnova T.G., Mashkova I.V., Kostryukova
A.M. and Artyukov E.V., The Distribution and
Accumulation of Chemical Elements in The
Ecosystem of Lake Ilmenskoe, International
Journal of GEOMATE, Vol. 12, Issue 34, 2017,
pp. 82-88.

63

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE EFFECT OF SOIL DEPTH ON GROWTH OF CLOVER FERN
AND USING CLOVER FERN ON THE GERMINATION OF FERN
SPORE

1

Sawat Pimsuwan1 and Yaowarat Wongsrisakulkaew1
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi, Thailand

ABSTRACT
Clover fern is water fern weed. It grows well in soft mud by most likely shallow water. Some country used it
for vegetable and medicine. After this fern dies every part still has the sticky fiber. It can be used for plant material.
This experiment was conducted in pots at the nursery. As follow the depths of soil: 5, 10, 15, 20 and 25 cm in theplanting pots were expected to demonstrate some effects on the growth of clover fern (Marsilea crenata C. Presl.).
The observations were made on 3 replications in a RCBD experiment. The mean comparisons were made with the
Duncan’s test at 0.05 significant level. It was found that the ferns on the 15 cm deep soil possessed the longest
internode length of 7.43 cm, while those with the 20 cm depth possessed the longest stalk of 16.16 cm and thoseof the 25 cm depth showed the widest leaf diameter at 4.00 cm. However, there was no significant difference forthe latter three measurements. The clover ferns on the soil with 25 cm depth demonstrated the highest fresh weightof 971.11 g and dry weight of 146.11 g (p<0.05). The spores germinated on the mixed media with clover fern andpeat moss, it was only observed in one chamber containing 1:2 clover fern to peat moss, and another one with 2:1
mixture but the germination rate was low. Clover fern should study for use as agricultural materials, vegetables
and medicine
Keywords: Clover fern, Water fern, Planting material, weeds

been proved for estrogen therapies [14]. The use forhepatitis and colic treatment by Thai folk healers inthe south of Thailand has long been known [15].
In an environmental point of view, this fern could
be used to test the soil for lead contamination. A
stronger inhibition to the growth of the fern was foundin relation to the increasing of lead in soil [16].
This research team has been looking for some
native plants that can replace the imported peat moss.
In nursery environment, it was notice that the clover
fern grew well on clay, in containers with some water,
especially in the rainy season. In the dry season, theferns became disrepair and died off. They could be
harvested, dried, and then used as a planting material.
Some other fern species and epiphytic plants cangrow on them when they have a suitable moisture
content. Drying and cracking of clover fern are very
similar physical properties to peat moss. Usually, peatmoss is popular in use for sowing seeds and fern
spores, also transplanting some fern seedlings [17].
However, potentially, the stems and petioles of clover
ferns consist of aerenchymal tissues which allow
good gas exchange. [18], [8]The objectives of this study were to determine1) the effects of the soil depths on clover fern growthand 2) the effects of clover fern in germination media
for bird-nest-fern spores.

INTRODUCTION
Weeds are defined as native plant species thatgrow in cultivating fields. Most weeds give important
impact on crop yields [1]. Some of them grow along
and compete with the cultivating crops [2] whilesome clog irrigation networks [3]. In wetland
plantation such as rice field, there are also weed
problems. Some water weed outbreaks have beenreported “In press” [4]. Clover fern (M. crenata C.
Presl) is one of the cause. This fern is known asaquatic, semi-aquatic fern or water fern [5], [6] which
has been classified as a weed. It grows well in
shallow water such as in the rice field. It is foundmainly in Southeast Asia, the rainforest zone withhigh humidity [7]. The general characters of theclover fern are: rhizome (stem) consisting nodes andinternodes, growing on soil or the mud surface,having four leaflets (frond) on the top of a petiole thatgrows from node of the rhizome. It has fibrous roots
and sporocarps growing from the nodes [8]. The
clover fern is one of edible wild plants. Some Thais
take this fern as a vegetable, and it could be found inmany Thai recipes. So, it is a part of Thai culture [9],[10], [11].
The clover fern can also be an ornamental plant. It
is unique when it is planted in a pot and placed in agarden or a pond [12]. It can also be grown inaquarium or shallow water basin [13]. This fern has
some medicinal properties as well. Its extract has
64

SEE - Nagoya, Japan, Nov.12-14, 2018

(971.11 g in average). They also showed the highest
dry weight (146.11 g) as well. These figures weresignificantly different (p < 0.05) and the details could
be found (Table 2, fig. 8-9)
On the other hand, the bird-nest-fern spores could
germinate in all chambers with pure peat moss but nogermination was found with pure clover fern. Some
spores could germinate on the mixed media but thegermination rate was low. It was only observed in one
chamber containing 1:2 clover fern to peat moss, andanother one with 2:1 mixture (Table 3, fig. 10-14)

MATERIAL PREPARATION
Fern stock preparation: The clover fern tips werecollected from the ferns naturally grown on rice field.
The tips were then planted on clay in large plastic
bowls. After two months, the ferns grew up and filled
up each bowl. These ferns were used as the fern stock
for this experiment. Some small clusters of the ferns
were collected from the stock with their roots
attached on the clay on which they were grown. Eachcluster was allowed a 10 x 10 cm clay block with it(fig.1). Five clusters each were then planted in acontainer containing some clay. The same procedure
was applied to other containers. All containers were
60 cm in diameter and 30 cm in height. After
planting, some water was added up to the top of thecontainers. (fig.2)
Germinating media preparation: Some dried
clover ferns were ground and sieved. The groundproduct was mixed with some peat moss at threedifferent ratios: 1:1, 1:2 and 2:1 (table 3). The mixture
was added into moisture chambers (6.5 cm in width,
8.5 cm in length and 3 cm in height) and spread
evenly. It was then sprayed with some water prior touse.

TablesTable 1 The growth of Clover ferns planted on clay
with different depths, at 13 weeks
Growth of Clover fern (x̄/cm)
Internode
Stalk
Leaf
lengthlengthdiameter
5cm
6.97
15.00
3.79
10cm
7.26
13.39
3.94
15cm
7.43
14.84
3.91
20cm
7.24
16.16
3.87
25cm
7.16
14.09
4.00
CV%
6.83
13.38
6.18
F testns
ns
ns
1
depth of clay soil
Treatment1

METHOD
Planting experiment: Some clay was used as theas planting soil for the clover ferns in this experiment.
It was added into planting containers to achieve fivedifferent depths: 5, 10, 15, 20 and 25 cm and waterheight was 30 cm. These depths were expected todemonstrate some effects on the growth of clover
ferns. The observations were made on 3 replications
in a randomized complete block design (RCBD). Theinternode lengths, stalk lengths, leaf diameters, fresh
weights and dry weights were collected and analyzed.
The mean comparisons were made with the Duncan
multiple range test at 0.05 significant level.
Germinating experiment: The spores from birdnest fern (Asplenium nidus) were chosen for thisexperiment. They were sown onto the moisten media
prepared early on, at amount of 2.5 mg per chamber.
The chamber were closed and observed for thepresence of prothalli.

Table 2 The fresh and dry weights of clover fern at
13 weeks on clay with different depths.
Weight of Clover fern (x̄/g)Fresh weight/gDry weight/g
5cm
524.99 c
66.11 c10cm
683.88 b
89.99 bc
15cm
798.88 b
118.88 ab
20cm
793.88 b
123.33 ab
25cm
971.11 a
146.11 a
CV%
11.52
2.60
F test**1depth of clay soil, * = significantly different (p <0.05)
Treatments1

Table 3 The germination of bird-nest fern spores ondried-ground clover fern, peat moss and their
mixturesRESULTS
Material ratio

It was found that the clover ferns on the 15 cm
deep soil possessed the longest internode length withan average of 7.43 cm. Those on the 20 cm depth
demonstrated the longest stalk of 16.16 cm inaverage. On the other hand, the ones on the 25 cm
depth showed the average width of leaves of 4.00 cm.
However, there was no significant difference(p>0.05. (Table 1, fig. 3-7)
In term of weights, the clover ferns which planted
on 25 cm deep soil were the heaviest by fresh weight1+-

Box number
2 3 4 5- - - + + + +- - - - + - + - - -CP
C: P =1:1
C: P =1:2
C: P =2:1
C= clover fern, P= peat moss,
presence of prothalli: + = found, - = not found

65

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SEE - Nagoya, Japan, Nov.12-14, 2018

Figures
The clover ferns in the soil depth experiment are
shown in figure 1-9. The bird-nest ferns spore in thegerminating experiment are shown in figure 10-14.

Fig.4 The clover ferns on 10cm deep clay soil
Fig.1 Collected clover fern clusters

Fig.5

Fig.2 The experimental clover ferns in thenursery

The clover ferns on 15cm deep clay soil

Fig.6 The clover ferns on 20cm deep clay soil

Fig.3 The clover ferns on 5cm deep clay soil

66

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig.10 The germination of bird-nest fern spores onground clover fern
Fig.7

The clover ferns on 25cm deep clay soil
Prothallus

Fig.11 The germination of bird-nest fern spores onpeat moss

Fig.8 The fresh clover ferns

Fig.12 The germination of bird-nest fern spores on
1:1 clover fern: peat moss mixture

Fig.9 The dried clover ferns

67

SEE - Nagoya, Japan, Nov.12-14, 2018

be developed for use as agricultural materials because
it free material from nature and also research to bevegetable commercial and medicine.
Fungi

ACKNOWLEDGEMENTS

Prothallus

This research was partially funded by The Facultyof Agricultural Technology, Rajamangala Universityof Technology Thanyaburi, Thailand. And this report
was edited by Dr. Satain Pogool.
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Samadiyanc F. and Beyginiyad V., Effects ofcover crops and weed management on corn yield.
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[2] Gaba S., Reboud X., and Fried G., Agroecology
and conservation of weed diversity inagricultural lands. Botany Letters, Vol.163,
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[3] Kamoshita A., Araki Y., and Nguye Y.T.B.,
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[4] Seng T., Sou C., Goh S., and Sahi I., Weedmanagement
issues,challenges,
andopportunities in Malaysia. Crop protection. 2017
(In press)[5] Short P.S., MARSILEACEAE in Short P.S. and
Cowie I. D. (eds), Ferns and allied plants. Floraof the Darwin Region. Vol.1,2011,pp.17-20[6] Pimsuwan s., Wongsrisakulkaew Y., JumradjitN., Thumsuk P., and Mulmanee S., The effectsof watering frequencies and slow releasedfertilizer levels on the growth of Platycerium
coronarium in young sporophyte phase Vol.13,
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[7] Wu T-C., and Wen-Yuan Kao W-Y.,
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Marsilea Species Distributed in Different
Geographical Regions, Taiwania,Vol.56, No.4,
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[8] Agil M, Kusumawati I., and Purwitasari N.,
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Presl. Cultivated in Water and in the Soil. Journalof Botany. Volume 2017,2017, pp.1-6.
[9] Cruz-Garcia G.S., Struikc P.C., and Johnson
D.E., Wild harvest: distribution and diversity ofwild food plants in rice ecosystems of Northeast
Thailand, Wageningen Journal of Life Sciences
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[10] Cruz-Garcia G.S., and Price L.L., Weeds asimportant vegetables for farmers. Acta Soc Bot
Pol, Vol.81, No.4, 2012, pp.397–403[11] Calvert G. and Liessmann L., Wetland Plants of
the Townsville–Burdekin Flood Plain. Lower

Fig.13 The germination of bird-nest fern spores on
2:1 clover fern: peat moss mixture

Prothallus

Fig.14 The germination of bird-nest fern spores on
1:2 clover fern: peat moss mixture

CONCLUSION

The values of many native plants have not been
well studied. This study chose to test the clover fern
for its production potential and its potential use as aplanting material. The study was conducted in a plant
nursery for 13 weeks in a rainy season. On the basisof fresh weight and dry weight, ferns appeared to
grow well on 25 cm deep clay soil and 5 cm shallow
water.
To be used as a germination material, the groundclover fern did not show a positive result with respectpeat moss. Although some bird-nest-fern spores cangerminate on 1:2 and 2:1 clover fern for mixing peatmoss, germination has been delayed for a few weeks.
In contrast, fern spores completed their germinationin the first month.
The observation made during the experiment had
noticed that the ground clover fern was looked
perfectly sound, but it generated some decomposition
odor. This may suggest the negative effect found in
this experiment. It might be caused by some toxins
generated during the decomposition process which
are required some further studies. Clover fern should
68

SEE - Nagoya, Japan, Nov.12-14, 2018

Burdekin Landcare Association Inc., Ayr. 2014,
pp.1-144

gastrointestinal disorders from southern
Thailand: Krabi and Songkhla provinces. Journalof Ethnopharmacology, Vol.209,2017,pp.318–
327.
[16] Nurhayatia A.Y., Hariadia Y. C., and LestariaP., Early detection of lead stress on Marsilea
crenata using. biolectricity measurement.
Procedia Environmental Science, Vol.28, 2015,
pp.57 – 66.
[17] Pimsuwan S, Hongthong P, Krangpanich P., andSuwanpinta C., The Effect of Fertilizer on
Growth of Staghorn Fern at Seedling Stage.
International Journal of GEOMATE, Vol.11,
Issue28, 2016, pp.2879-2882.
[18] Jung J.D., Lee S.C., and Choi H.K., Anatomicalpatterns of aerenchyma in aquatic and wetland
plants. Journal of Plant Biology, Vol. 51, Issue 6,
2008, pp.428–439.

[12] Yusuf U.K., Ferns of Malaysian Rain Forest a
Journey
throughthe
FernWorld.
Serdang ;Universiti Putra Malaysia Press, 2010,
pp.1-107[13] Zhigila D.A., Sawa F.B.J., Oladele F.A., andMuhammad S., Aesthetic Values andSignificance of Ferns to Landscaping Industries– A Taxonomic Review. International Journal of
Current Research in Biosciences and Plant
Biology, Vol.2,No.3,2015,pp.7-13[14] Titisari N., Fauzi A., Adyana A., andTrisunuwati P., The Effects of Water Clover( Marsilea crenata ) Extract against Estrogen,
Progesterone And Uterine Histology on Rat(Ratus norvegicus). International Journal of
Pharm Tech Research, Vol.9, No.6, 2016,
pp.165-171[15] Neamsuvan O., and Ruangrit T., A survey of
herbal weeds that are used to treat69

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

CHEMICAL COMPOSITION AND INSECTICIDAL ACTIVITY OF
ESSENTIAL OIL FROM INDIAN BORAGE AGAINST MAIZE WEEVIL*Ruchuon Wanna1 and Jiraporn Krasaetep1
Faculty of Technology, Mahasarakham University, Thailand

1

ABSTRACT
Biopesticide has become more important in stored product pest management, since the use of synthetic
insecticides causes adverse effects to human health and the environment. The aim of this research was todetermine the chemical composition and toxicity of essential oil from Indian borage, Plectranthus amboinicu(Lour.), leaves against adults of maize weevil, Sitophilus zeamais Motschulsky. The essential oil wasinvestigated by Gas Chromatograph-Mass Spectrometer (GC-MS) technique. The efficacy of this essential oil
against S. zeamais using impregnated filter paper and vapor-phase tests. Experiments were performed underCompletely Randomized Design (CRD) with 4 replications. Contact toxicity towards maize was investigated at 6
concentrations of essential oil 0 5,000 10,000 15,000 20,000 and 25,000 ppm and fumigant activity was
performed using bioassay at 6 concentrations including 0 50 100 150 200 and 250 µL/L air. Data were recorded
as number of deaths maize weevil from 24 to 168 hours. The principal compounds in the oil were carvacrol(40.49%), caryophyllene (16.76%), Ç-terpinene (11.61%), o-Cymene (8.50%), humulene (5.88%),
caryophyllene oxide (2.75), p-mentha-1,4(8)-diene (2.17%), and terpinen-4-ol (1.19%). The essential oil of P.
amboinicu leaves showed strong contact toxicity at 120 hours and fumigant toxicity at 72 hours against adults ofS. zeamais with 100% adult mortality of 25,000 ppm and 250 µL/L air, respectively. The results indicated thatthe essential oil of P. amboinicu leaves showed potent for management of S. zeamais population.
Keywords: Chemical composition, Toxicity, Essential oil, Plectranthus amboinicu, Sitophilus zeamais

stored products [10]. Some components cause
larvicidal effect and oviposition deterrence inagricultural pests [11]. Phenolic compounds inessential oils react with chemical groups of enzymes
throughhydrogenbondsorhydrophobic
interactions, inhibiting activity [12]. Essential oilfrom wild L. palmeri is a good option for controllingmaize weevil. The aim of this research were
determination of chemical composition of theessential oil of Indian borage, Plectranthus
amboinicu (Lour.), from fresh leaves and evaluationof the insecticidal activities against adult stage of S.
zeamais as a possible alternative for synthetic
chemical insecticidal compounds.

INTRODUCTION
Preservation and protection of stored grain are
dietary, economic, and social requirements [1].
Damage caused by insects in stored maize, Zea mays
L., is a serious problem worldwide. Losses are 10%
in developed countries and 20% in developing
countries [2]. A major insect pest of stored maize isthe maize weevil, Sitophilus zeamais Mostchulsky(Coleoptera: Curculionidae) found in moist tropics
and subtropics and temperate zones [3]. This specie
is generally controlled by insecticides such as
phosphine [1]. However, insecticides are toxic tohumans and pollute the environment such as ozone
depletion, environmental pollution, increasing costs
of application, pesticide residue in food, insects
develop insecticidal resistance and toxicity hazards
on non-target organisms in addition to direct toxicity
to users [4], [5]. These problems have highlighted
the need to develop new types of selective insectcontrol alternatives.
Plant essential oils have traditionally been used
to kill or repel insects [4] being considered as analternative to stored grain conventional pesticides
because of their low toxicity to warm-blooded
mammals, their high volatility [6], [7], rapid
degradation [8], and the most terpenoids and phenols
found in plant essential oil have low toxicity [9], [1].
Essential oils are effective against insect pests of

MATERIALS AND METHODS
Insect Rearing
Maize weevil, Sitophilus zeamais Mostchulsky,
from the grain store located in Kantharawichai
district, Maha Sarakham Province, Thailand wereused throughout this study. Fifteen pairs of adults
were maintained in a plastic box (diameter 15 cm,
height 30 cm). The cultures were reared on 1 kg ofjasmine rice, Oryza sativa L. at 30±5°C and 70±5%relative humidity and 16:8 h light/dark cycle andwere allowed for mating and oviposition. Adult ofmaize weevil used for tests were 7 days old.
70

SEE - Nagoya, Japan, Nov.12-14, 2018set of treatment was repeated four times andpercentage adult mortality was calculated by using
the Abbott formula.

Extraction of Essential Oil
Essential oil was extracted from fresh leaves ofIndian borage, Plectranthus amboinicu (Lour.),using a Clevenger-type apparatus, (200 g of an airdried sample, 1:3 plant/distilled water ratios) werehydrodistilled for 3 hours. Anhydrous sodium
sulphate was used to remove water after the
extraction. Essential oil was kept in a refrigerator at
4 ºC until its use.

Fumigant Toxicity
Whatman (no.1) filter paper strips (1.5x5 cm)
were impregnated with 100 µL of 0 (100 %Acetone; control) 50 100 150 200 and 300 µL/L air
dilution of essential oils as prepared earlier. Afterevaporating the solvent for 2 min. Filter paper strips
were placed into the hanging of glass vials (diameter
2.5 cm x height 5 cm) from the center of screw capof fumigation bottle (diameter 5.5 cm x height 10.5cm) to avoid contact effect of insects with paper
strip. Ten active of female adults S. zeamais (7 days)
were placed inside the fumigation bottle by vaporphase test. The cap of each bottle was screwed
tightly and kept at 30±5 ºC, 70±5% relative
humidity, and 16:8 hours light/dark cycle. Adult
mortality was observed after 24 hours exposure to
168 hours. The insects were considered to be dead as
no leg or antennal movements were detected. A
control experiment was maintained in which
treatment was made with 100% acetone alone. Eachset of treatment was repeated four times andpercentage adult mortality was calculated by using
the Abbott formula.

Analytical Essential Oil
Essential oil constituents from fresh leaves ofIndian borage P. amboinicu were established by thegas chromatograph-mass spectrometry (GC-MS)
analyses. GC-MS analyses were performed on a
PerkinElmer Clarus SQ8 GC/MS system (Roster,USA) operating in EI mode (70 eV).A Rtx-5MS
capillary column (with a 5% phenyl-methylpoly
siloxane stationary phase, 30 m x 0.25 mm, 0.25 µm
film thickness) was used. The GC settings were as
follows: the initial oven temperature was kept at 60ºC for 1 min and increased to 180 ºC at a rate of 10ºC/min, held for 1 min, and then increased at 3
ºC/min to 246 ºC for 15 min. The injector
temperature was maintained at 250 ºC. The samples(1 µL, dilute to 1% with acetone) were injected, witha split ratio of 1:10. The carrier gas was helium witha flow rate of 1.0 mL/min. Spectra were scanned
from 50 to 550 m/z. The identification of essential
oil components was undertaken firstly by comparing
their mass spectra with those stored in National
Institute of Standard and Technology (NIST) Mass
Spectral Search Program and Chemstation Wiley
Spectral Library. Essential oil components weredone by comparison of their retention times withauthentic samples to a series of n-alkanes under thesame operating conditions.

RESULTS AND DISCUSSION
Identification of Compounds
Chemical composition of essential oil from theleaves of Indian borage, Plectranthus amboinicu, isgiven in Table 1. The major components in theessential oil from P. amboinicu leaves were:carvacrol (40.49%); caryophyllene (16.76%); Çterpinene (11.61%); p-cymene (8.50%); humulene(5.88%);caryophyllene oxide (2.75%); terpinolene(2.17%); α-bergamotene (1.97%); germacra-4(15),5,10(14)-trien-1α-ol (1.28%); and terpinen-4-ol(1.19%).
Chemical analysis indicated clearly thatcarvacrol was the main component of Indian borage
essential oil. Ortega et al. [13] indicated thechemical constituents varied according to genetic
and environmental factors as well as harvest. Erler
and Cetin [14] evaluated components and potential
larvicidal effects of Origanum onites and O.
minutiflorum against brown-tail moth, Euproctis
chrysorrhoea (L.), and found carvacrol, thymol, cterpinene, and terpinen-4-ol, with the major
component being carvacrol for both species oforegano. Toxic effects of terpenoid compounds canbe attributed to reversible competitive acetylcholinesterase inhibition occupying the hydrophobic
site of the enzyme active site [15].

Contact Toxicity
A series of dilutions of essential oil from Indian
borage P. amboinicu (0 5,000 10,000 15,000 and
25,000 ppm) was prepared using 100% acetone assolvent as described. Aliquot of each dilution (100μL) was separately applied on top surface of filter
paper (whatman no.1, diameter 9 cm) with amicropipette. The solvent was allowed to evaporatefor 2 min and placed into each petri-dish (diameter 9cm). Ten active of female adults S. zeamais (7 days)
were introduced into the each petri-dish separately.
After incubation at 30±5°C and 70±5% relative
humidity and 16:8 hours light/dark cycle and 24
hours exposure to 168 hours, adult mortality wasrecorded. The insects were considered to be dead as
no leg or antennal movements were observed. A
control experiment was maintained in which
treatment was made with 100% acetone alone. Each
71

SEE - Nagoya, Japan, Nov.12-14, 2018carvacrol, and ρ-cymene. Successful insecticidal
plant constituents are monoterpenes and because ofvolatility, fungicidal, bactericidal, and insecticidal
activity might be used to control stored productinsects [16].

Carvacrol has insecticidal activity against pestsof stored products and is toxic to termites and tonymphs and adults of rice weevil, S. oryzae,
Callosobruchus
chinensis,
andLasioderma
serricorne. Toxic effects in the current study could
be attributed to constituents such as thymol,

Table 1 Chemical composition of the essential oil from leaves of Indian borage Plectranthus amboinicu (Lour.)
Retention time (min)

Area%

No.

Compounds

1

2-Thujene; β-Thujene

8.224

0.35

2

Orthodene

8.534

0.13

3

á-Myrcene

10.0680.84

41-Hepten-3-ol

10.0680.24

5à-Pellandrene

11.294

0.23

6

Terpinolene

11.8172.17

7p-Cymene

12.1728.50

8trans-1,2-bis-(1-methylethenyl)cyclobutane

12.3400.40

9

Ç-Terpinene

13.688

11.61

10

Terpinolene

14.9790.13

11Linalool

15.3450.28

12Terpinen-4-ol

19.1201.19

13

à-Terpineol

19.6980.10

142-isopropyl-5-methylphenol

23.802

0.10

15

Thymol24.1040.25

16Carvacrol

24.77540.49

17

Caryophyllene

30.05916.76

18

α-Bergamotene

30.449

1.97

19

Humulene

31.4205.88

20α-Amorphene33.187

0.37

21

Cadina-1(6),4-diene

34.0950.10

22Caryophyllene oxide

36.664

2.75

23

Humulene epoxide II37.6550.33

24

11,11-Dimethyl-4,8-dimethylenebicyclo[7.2.0]undecan-3-ol

38.624

0.12

25

Germacra-4(15),5,10(14)-trien-1α-ol

39.835

1.28

26

á-Longipinene

41.2180.10

27

1,3-Bis-(2-cyclopropyl,2-methylcyclopropyl)-but-2-en-1-one

41.4630.10

28

n-Hexadecanoic acid49.2750.1029Ethyltetramethylcyclopentadiene

52.8180.10

30

3,7,11,15-Tetramethyl-2-hexadecen-1ol

54.091

0.38

Total identified

97.31

72

SEE - Nagoya, Japan, Nov.12-14, 2018

Contact Toxicity
Mortality of maize weevil (S. zeamais) at 120 h
after treatment was highest at the concentration of
25,000 ppm of essential oil from Indian borage (P.
amboinicu) leaves with cumulative values of 100%and there was a significant difference (P<0.01) in
relation to the other concentrations. However,thatwas not different compared with 20,000 ppm(Table 2). The number of dead insects increased as
the concentration of the essential oil and time of
exposure increased.

leaves to adults of maize weevil (S. zeamais) after
treatment at 72 h resulted in mortality values 100%and it caused the highest significant difference(P<0.01). However, it was not different comparedwith 100 150 and 200 µL/L air (Table 3). Allconcentrations of essential oil had greater efficiency
against maize weevil (S. zeamais) at 168 h with
100% of adult mortality when comparison with 0µL/L air, acetone treatments and also was highsignificant different. Maize weevil (S. zeamais) was
more sensitive to oil at greater concentrations
during the first 72 hours and adapted as time
passed. Compared with data from this study, Indian
borage oil shows greater potential as an insecticide.

Fumigant Toxicity
Mortality value exposed with 250 µL/L air ofessential oil from Indian borage (P. amboinicu)

Table 2 Mortality of maize weevil S. zeamais with contact toxicity treated Indian borage essential oil
Mean (±SE) of adult mortality (%) of maize weevil S. zeamais
Conc.
(ppm)
24 h
48 h
72 h
96 h
120 h
144 h
168 h
0
0.0±0.0d
0.0±0.0c
0.0±0.0e
0.0±0.0e
0.0±0.0e
0.0±0.0d
0.0±0.0c
5,000
2.5±5.0d15±12.6b
17.5±5.0d
30.0±8.2d
40.0±8.2d
50.0±8.2c
92.5±9.6b
c
b
c
c
c
b
10,00012.5±5.0
20.0±8.2
30.0±8.2
47.5±5.0
60.0±8.2
77.5±5.0
100.0±0.0a
b
a
b
b
b
a
15,00032.5±9.6
55.0±5.8
65.0±5.8
67.5±5.0
72.5±9.6
95.0±5.8
100.0±0.0a
b
a
a
a
a
a
20,00047.5±12.6
80.0±8.2
87.5±5.0
92.5±9.6
92.5±9.6
100.0±0.0
100.0±0.0a
25,00070.0±8.2a
77.5±9.6a
85.0±5.8a
95.0±5.8a
100.0±0.0a 100.0±0.0a 100.0±0.0a
Means within the same column followed by the same letter are not significantly different (DMRT: P>0.05)

Table 3 Mortality of maize weevil S. zeamais with fumigant toxicity treated Indian borage essential oil
Mean (±SE) of adult mortality (%) of maize weevil S. zeamais
Conc.
(µL/L air)
24 h
48 h
72 h
96 h
120 h
144 h
168 h
0
0.0±0.0c
0.0±0.0c
0.0±0.0c
0.0±0.0c
0.0±0.0c
0.0±0.0b
0.0±0.0b50
10.0±8.2b
50.0±14.1b 67.5±12.6b 77.5±15.0b
92.5±9.6b
97.5±5.0a
100.0±0.0a
b
ab
a
a
ab
a
100
17.5±9.6
70.0±8.2
87.5±12.6
95.0±5.895.0±5.0
100.0±0.0
100.0±0.0a
ab
a
a
a
a
a
150
25.0±5.0
85.0±5.8
87.5±5.0
97.5±5.0
100.0±0.0
100.0±0.0
100.0±0.0a
b
ab
a
a
a
a
200
17.5±17.1
65.0±28.992.5±9.6
100.0±0.0
100.0±0.0
100.0±0.0
100.0±0.0a
25047.5±15.0a
82.5±5.0a
100.0±0.0a 100.0±0.0a 100.0±0.0a 100.0±0.0a 100.0±0.0a
Means within the same column followed by the same letter are not significantly different (DMRT: P>0.05)

Copyright form signed by all authors isnecessary for GEOMATE. It should be submitted
along with the paper submission. Copyright form
can be downloaded from geomate web site.

borage essential oil is an alternative control method
for maize weevil S. zeamais because it results inhigher adult mortality by contact and fumigant
toxicity. The effectiveness of the components ofessential oils might be a viable option to control
insect pests in stored maize.

CONCLUSIONACKNOWLEDGEMENTS

Indian borage P. amboinicu (Lour.) essential oil
could be used as a botanical insecticide postharvest
since it consists of potential terpenoids such as
carvacrol, p-cymene, terpinen-4-ol, and thymol
complementary to conventional insecticide. IndianThis research was financially supported by
Mahasarakham University. The laboratory assistancefrom Miss Phitchanart Kaewwichean is gratefully
acknowledged.

Copyright Form

73

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74

4th Int. Conf. on Science, Engineering & Environment ( SEE) ,Nagoya, Japan, Nov. 12-14, 2018, ISBN: 978-4-909106018 C3051

ANGIOTENSIN CONVERTING ENZYME INHIBITOR ACTIVITY
OF THE SOYBEAN TEMPEH PROTEIN AS FUNCTIONAL FOOD
1,2,3

* Sri Yadial Chalid1, Sandra Hermanto2 Amalia Rahmawati3
Chemistry dept. Faculty of Science and Technology, Islamic State University Syarif Hidayatullah,
Indonesia
ABSTRACT

Tempeh is an Indonesia’s indigenous fermented food that is widely preferred by the community.
Fermented food have functional food as an antihypertensive by angiotensin converting enzyme (ACE)inhibitor. This study was aimed to measure protein activity of tempeh as ACE inhibitor. Soybean was
fermented using Rhizopus sp. with various fermentation times of 0, 6, 12, 18, 24, 30, 36, 42 and 48 hours.
Protein extraction was performed at the isoelectric point, the degree of hydrolysis was considered astrichloroacetic-dissolved nitrogen. The best fermentation time was determined by the degree of hydrolysis(DH) and protein content. Protein extract was fractionated by using an ultra membrane with 3 kDa cutt of.
Proximate analysis was performed by AOAC method. The measurement of ACE inhibitor was based on theformation of hippurate acid-H-Histidyl-L-leucine (HHL). Results of this study revealed that the lipid content
of tempeh was lower than that of soybean while the water content of tempeh was higher than soybean. The
best fermentation time was found at 24 hours. Protein content was 236.31 ppm and DH was 36.03%. The best
fraction that was able to inhibit ACE was a fraction below 3 kDa with an inhibitory capability of 67.43%.
Protein of tempeh contained proline, valine, isoleucine, histidine, teonine, tyrosine, leucine, aspartic acid,lysine, glycine, arginine, alanine, phenylalanine, glutamic acid, serine and methionine. This study concludes
that tempeh was able to inhibit ACE by in vitro and is potentially continued to in vivo examination, thus
tempeh can be claimed as a functional food
Keywords: Tempeh, Indigenous fermented, Angiotension converting enzym, Isoelectic point

Therefore, the functional effect of soy protein whichacts as ACE inhibitor can be enhanced byfermentation [8].
Hypertension and cardiovascular disease increase
along with an unhealthy lifestyle and a low facility
for prevention of hypertension [9]. Currently, there
are available various synthetic drugs for thetreatment of hypertension. Although those are
effective, synthetic drugs have many side effects
such as a chronic dry cough that causes acuterespiratory distress even to death [10].
Synthetic antihypertensive drugs such as
Captopril® and Lisinopril® inhibit the ACE
enzyme, increase bradykinin and reduce angiotensin
II, but the long-term using the medcines may causeside effects. A total of 36% of patients complained
about the side effects of captopril and as many as
45% complained of amlodipine [11]. Several studies
indicated that hydrolyzed soy protein could lower
blood pressure in vitro basis.
The objective of this study was to determine
fermentation time, the degree of hydrolysis, protein
fractionation and inhibitory activity assessment ofangiotensin converting enzyme (ACE). The ACE
inhibitor assessment was based on the release ofhippurate acid from hippuryl-L-histidyl-L-leucine
substrate [12], [13].

INTRODUCTION
Tempeh is a traditional Indonesian food which ismade by fermentation, is widely preferred andproven to provide benefits for the health of humanbody. Opportunity to develop local food such astempeh to be recognized internationally is not
impossible since Indonesia has proposed to the 34th
Codex Alimentarius Commission (CAC) meeting in
Geneva on July 9, 2011.
Tempeh has the potential to be developed intofunctional foods as antihypertensive if there isscientific data obtained through in vitro and in vivo
assessment. Tempeh is made by fermentation using
Rhizopus sp. This fungus produces several
antibiotics that are active against Bacillus species,
particularly Bacillus subtillis [1], has anticancer andantiangionesis (the formation of new blood vessels)
properties which are also shown by genistein
compound of isoflavone derivative extracted fromtempeh [2]. Ansarullah [3] states that blood pressureofhypertension
sufferers
decreases
after
consumption of soybean drink. Tempeh is useful ininhibiting the formation of blood vessels of cancer
cells [2], improving bone health [4], as anti-bacterial
agent [5] and active antioxidant. In addition, [6]tempeh extract is beneficial in the management andprevention of dementia and Alzheimer’s disease [7].
75SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

The degree of hydrolysis was calculated using
the SN-TCA method [18], a total of 2 mg of proteinhydrolysate was added with 2 mL 10% (w/v)
trichloroacetic acid solution. The mixture wasallowed for 30 minutes to obtain the precipitate andthen centrifuged (7.800 g, 4 oC, for 15 minutes).
Protein levels of supernatant and precipitate were
measured by using Kjedhal method.

METHOD
Soybean Fermentation
The fermentation period of soybeans was varied
as follows 0, 6, 12, 18, 24, 30, 36, 42 and 48 hours.
A total of 1000 grams soybeans (from traditional
market) were soaked in the water with ratio of 2:1
for 18 hours, it was further removed from the skin.
Cleaned soybeans were steamed using the corm for
30-40 minutes (until tender) and were then cooled. 2grams starter Raprima (from PT Aneka Fermentasi
Industri (AFI) Indonesia) was inoculated by mixing
the starter with steamed soybean evenly.
Furthermore, it was inserted into the measuring
plastic that has been given small holes. Inoculation
result was incubated at 30oC until tempeh wasformed.

ACE inhibitory Examination
Enzyme activity was determined using the HipHis-Leu (HHL) synthetic peptide as a substrate
which was based on the developed method [12],[13].
A protein extract solution of 15 μl was added with125 μl of 100 mM sodium borate buffer solution (pH8.3) containing 7.6 mM Hip-His-Leu and 608 mM
NaCl, and was preincubated for 5 min at temperatureof 37 °C. The reaction begins with the addition of 50
μL ACE enzyme (rabbit lung-derived angiotensin Iconverting enzyme) dissolved in the aquadest. The
mixture was incubated for 30 minutes at temperatureof 37 °C. As a blank, it was used 50 μL aquadest.
The reaction was discontinued with the additionof 125 μL 1N HCl. Hippurate acid released by ACE
was extracted by adding 750 μL ethyl acetate to the
mixture and was immediately shaken using vortex.
The mixture was centrifuged at a velocity of 13.760
x g for 10 min, a total of 500 μL top layer of thesupernatant was collected and dried at 90 °C for 30
min. Furthermore, hippurate acid was dissolved in 1
mL distilled water and the absorbance was measured
by spectrophotometer at 228 nm wavelength.

Disposal of Lipid from Tempeh Flour
Tempeh was crushed using blender and soaked
in a hexane solution at a ratio of 1: 5 (sample:
hexane) for 1 hour at a room temperature whilestirring. The supernatant was removed and theprecipitate was repeated with the same process byadding hexane solution twice with the same ratio forremoving the remaining lipid. The lipid-free flour
was collected and dried to liberate hexane [14] thus
resulting in lipid-free tempeh flour .
Protein Extraction of Tempeh
Proteinextraction
was
performedbyprecipitation method at isoelectric point [15]. Lipidfree tempeh flour was soaked in the water a ratio of
1:10 (w/v), pH 8.5 with addition of 1N NaOH
solution. Suspension was stirred using a magnetic
stirrer at a room temperature for 1 hour andcentrifuged (6000 x g) for 20 minutes at 4°C.
Supernatant was collected and adjusted to pH 4.5
with the addition of 1.0 N HCl solution. The
suspension was centrifuged at 6000×g for 20 min, atemperature of 4°C [16]. The resulting hydrolysis
was lyophilized and stored in freezer withtemperature of -20°C, thus protein hydrolysates
would be obtained.

% Inhibitory Activity = [(C-A)/(C-B)] x100%
Description:
A= sample absorbanceB= blank absorbanceC= control absorbance (aquadest).
Amino Acid Analysis
Amino acid composition analysis determined
was the result of fractionation with 3 kDa
membrane. Sample was added with 5 mL 6 N HCl
while stirring with stirrer, and flowed with nitrogenand hydrolyzed at temperature of 110 °C for 22hours. Hydrolysates obtained was then cooled atroom temperature, and transferred into a 50 ml
measuring flask, also added with aquabidest. The
solution was filtered by a filter membrane with asize of 0.45 μm. A total of 500 μl filtrate was addedwith 40 μL AABA (alpha amino butyric acid) and460 μl aquabidest. A total of 10 μl solution wasadded with 70 μl AccQ-fluor borate and shaken
using vortex. Furthermore, a total of 20 μl fluorine A
reagent was added and shaken using a vortex, andallowed to stand for 1 minute. Subsequently, thesolution was incubated for 10 minutes at a

Protein Analysis and Degree of Hydrolysis
Hydrolysate of tempeh protein was dissolved inaquadest with a ratio of 1:10 (g/v) while stirring
until dissolved evenly. The mixture was centrifuged(13000 xg, 15 min, 4oC). A total of 100 μL
supernatant was piped into the test tube and addedwith 5 mL of Bradford solution while shaking andallowed to stand for 15 min. The absorbance wasmeasured using a spectrophotometer at a wavelengthof λ 595 nm [17].
76SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

temperature of 55 oC and injected in UPLC (ultrahigh performance liquid chromatography) [19].

compared with tempeh in the other studies. Good
tempeh has a fresh aroma such as the scent ofmycelium and free amino acids. The quality oftempeh can be known from the growth of mycelium.
If the mycelium grows evenly on the surface oftempeh, it can be declared as good tempeh.
Otherwise, if the mycelium is accumulated on thecertain points of soybean surface, it is declared as a
not good tempeh [21].

RESULTS AND DISCUSSION
TempehThere are four steps in the making process oftempeh, namely soaking, boiling, inoculation of
Rhizopus and incubation at room temperature [20].
Tempeh was made using a starter containing a
mixture of Rhizopus sp. Variety of fermentation
times used were 0 hour as control 0, 6, 12, 18, 24,
30, 36, 42 and 48 hours. The best physicalappearance of tempeh depends on the duration of
fermentation (hour) which is based on observation ofphysical shape, odor and the increase of Rhizopus
mycelium on the surface of the soybean. The
physical appearance of tempeh during fermentationis shown in Fig. 1.
Fig. 1 Physical appearance of tempeh at various
fermentation times (H)Contol

6H

Proximate Analysis Results
Table 1 Results of proximate analysis of tempeh of
24 hours incubation
SampleParameter
SoybeaTempehWater content (%)
11.81
57.42
Ash content (%)
4.95
1.64
Lipid (%)
15.28
9.86
Protein (%)
37.17
21.84
Dissolved Protein (ppm)
75.19
236.31
Based on Table 1, it is known that lipid content offermented soybean (tempeh) was lower than that ofunfermented soybean (control) with a decrease of
64.53%. Similar with 22], lipid content of soybean
was 18.38%. Meanwhile, dissolved protein content
for control and tempeh was 75.19 and 236.31 ppm,
respectively.

12 H

Lipid on tempeh
18 H

24 H

30 H

36 H

42 H

48 H

Lipid disposal from tempeh in this study was
aimed to obtain a higher protein extract. Wu [15]states that the samples with lipid disposal have ahigh protein content of 72.35% while samples
without lipid disposal have a protein content of
55.88%. Results of this study indicate thatfermentation can reduce lipid content in tempeh.
Furthermore, the lowest lipid content obtained at 24hours fermentation was 9.04%. We presume thislipid reduction activity is caused by lipase.

The 24 hours fermentation produced tempeh
with better texture and good odor in which Rhizopus
sp. mycelium covered the surface of soybean evenly.
Rhizopus sp. started to grow at 18th hour andcontinued to next hours. The best growth of
Rhizopus sp. was obtained at 24th hour fermentation.
Rhizopus mycelium of 30 hours fermentation
showed a black color which indicates that tempeh
began to rot. Types of Rhizopus which primarilyfound on tempeh starter are Rhizopus oligosporus
dan Rhizopus oryzae [20].
Fermentation of soybean into tempeh that is
widely done by Indonesian people lasts between 18
to 36 hours. After 36 hours, tempeh begins todecompose which can be seen from discoloration oftempeh such as blackening color and bad odor. Yetin this study, 30 hours fermentation had producedout of odor tempeh, thus we conclude that tempeh
produced in this study is faster to decompose

Degree of Hydrolysis and Protein Content
Degree of hydrolysis (DH) is defined as the
proportion of peptide bonding broken down inprotein hydrolysates. The DH value increased
significantly at 18 hours fermentation and thehighest value was obtained at 24 hours fermentationin which the mycelium has been seen to growcovering the surface of tempeh. The result of thecalculation is presented in Table 2. The DH value
increased rapidly over 18 hours fermentation since
the mycelium is already grown.
Table 2 Value of degree of hydrolysis and amount ofprotein on tempeh
Fermentation
Degree ofProtein Level
77

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

Time (H)
0
6
12
18
24
30

Hydrolysis (%)
1.76
4.48
2.94
31.71
36.03
30.93

antihypertensive food [33] so that the above
products can be claimed as functional food.
In order to make tempeh as afunctional food, it
must be obtained in vitro and in vivo data fromresearch findings. For in vitro, it was obtained avalue of 67.43%, which is the result of measurementof ACE inhibitory activity of protein extract oftempeh. This value was obtained from the fraction
below 3 KDa.

(g)
0.54
1.17
1.65
0.24
3.13
0.45

A high degree of hydrolysis indicates that theprotein is easily hydrolyzed (Table 1). In accordancewith this study, increased DH value and protein
content are suspected as a result of protease activity
produced by Rhizopus sp. The main function of
Rhizopus in fermentation is the synthesis of enzymes
that hydrolyze compounds in soybean [21].
The DH value increased significantly on tempehof 18 hours fermentation, where mycelium was seen
growing on the surface of soybean (Fig.1). Bioactive
peptide of the food is produced during the enzymatichydrolysis process and fermentation or in thegastrointestinal tract. The resulting peptide has
antihypertensive activity [23]. “Hrckova [24]showedthat the highest degree of hydrolysis was 39.5% withlipid content had been disposed from protease ofcommercial soy flour”. The high dissolved protein
content in this study was obtained in fermented
soybean (tempeh) for 6 and 24 hours (data notshown).

Amino Acid Composition of Protein Hydrolysatesusing 3 Kda Membrane
Amino acid analysis was performed to determine
the type and level of amino acid found in soybeanhydrolysate. Results of the amino acid analysis
using UPLC are presented in Table 3. The result
showed that tempeh contains both essential and nonessential amino acids. Predominant amino acids areglutamic acid, lysine, leucine, alanine, valine andphenylalanine, while predominant essential aminoacids are Thr, Leu, Lys, Val, Met and Phe.
Table 3. Amino acid content of tempeh hydrolysate
using 3 KDa membrane

ACE InhibitorActivity
Bioactive peptide released from dietary protein is
widely used for the management of hypertension
based on the Angiotensin I-Converting Enzyme(ACE) inhibitory activity, which is an enzyme
regulates the mechanism of regulation of Renin
Angiotensin System (RAS), which is food peptidethat interacts with RAS and the vascular system andcontributes to a decrease in blood pressure [25].
Peptides with sequences of Leu-Val-Tyr, Leu-GlnPro and Leu-Lys-Tyr of soy flour indicate
Angiotensin I-Converting Enzyme (ACE) inhibitory
activity [26]. Peptides with sequences of Met-AsnPro, As-Pro-Pro, Pro-Pro-Lys, Ile-Thr-Thr, Thr-ThrAsn, and Thr-Asn-Pr have ACE inhibitory activity[13]. Angiotensin I-Converting Enzyme (ACE)catalyzes the conversion of angiotensin I toangiotensin II, which is a vasoconstrictor and also
inactivates the antihypertensivity of a bradykinin asa vasodilator. Peptides derived from food proteins
may have ACE inhibitory activity [27].
Some fermented foods have ACE inhibitory
activity such as brown rice [28], tofuyo extract [29],a traditional Japanese food like steamed soybeans
fermented by Bacillus (natto) [30]. By in vivo, Nattois antihypertensive [31], also pigeon pea fermented
using Bacillus subtilis [32], a pasta made from
Korean soybeans is proven to act as an

NoType of Amino
Acid

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18

L-Histidine
L-Threonine
L-Proline
L-Tyrosine
L-Leucine
L- Aspartic acid
L-Lysine HCl
GlycineL-Arginine
L-Alanine
L-Valine
L-Isoleusine
L-Phenylalanine
L- Glutamic acid
L-Serine
L-Methionine
L- Cysteine
L-Tryptopane

Amino Acid
Content (ppm)1106.79
1442.295
1636.755
2907.284774.595
895.453688.065
1516.235
2276.61
3257.362235.715
2053.843905.976936.845
1005.745
614.43-“Kitts [34] revealed that bioactive peptides generally
have low molecular weight consisting 2-9 aminoacid residues and are resistant to digestive enzymes
have hydrophobic amino acid residues from the typeof proline, lysine or arginine”. In this study, it was
obtained hydrophobic amino acids such us alanine,
valine, isoleucine, proline, phenylalanine, andmethionine, thus authors presume that the functional
properties of tempeh as ACE inhibitors are obtained
from the above amino acids.
CONCLUSION
78

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

Fermentation for 24 hours produced tempeh with thebest texture, low lipid and high protein content.
Protein extract showed a high ACE inhibitory
capacity with a total of 16 essential and nonessential amino acid compositions. Tempe has thepotential to be developed as a functional food.

[8]

ACKNOWLEDGEMENT[9]
Authors thank the Rector of UIN Syarif
Hidayatullah Jakarta for research funding throughPuslitpen LP2M 2017[10]

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Agricultural and Food Chemistry, Vol. 49,
Issue 6, 20011, pp. 3004–3009.
Kitts D. D., and Weiler K., Bioactive
proteins and peptides from food sources.
Applications of bioprocesses used inisolation
andrecovery.
Current
pharmaceutical design, Vol. 9, Issue. 16,
2003, pp. 1309–1323.

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE MODIFIED DECOMPOSITION METHOD FOR SOLVING
VOLTERRA INTEGRAL EQUATION OF THE SECOND KIND USING
MAPLE

1

Dalal Adnan Maturi1
Departement of Mathematics, Faculty of Science, king Abdulaziz University, Saudi Arabia

ABSTRACTIn this paper , we obtain the approximate solution for Volterra integral equation of the second kind throughusing modified decomposition method by using Maple program, so all calculations can be easily using Maple tofind that exact solution.
Keywords: Volterra integral equation of the second kind, Modified Decomposition method, Maple .
namely, and  . Under this assumption weset =   +  .
(3)
Accordingly, a slight variation was proposed only
for the components !"  and !  The
suggestion was that onlythe part   will beassigned to the zeroth component !" ,whereas theremaining part  will be combined with theother terms given into (1) to define 1().
Consequently, the modified recursive relation  =  ,INTRODUCTION
The modified decomposition method [1]-[4] hasbeen efficiently used to solve linear and nonlinear
problems such as differential equations and integral
equations.
A Modification in successive approximation
method for solving nonlinear Volterra Hammerstein
integral equations of the second kind by Sh. Javadi[5]. Also, Modification of Laplace Adomian
Decomposition method for solving nonlinear
Volterra integral and integro-differential equations
based on Newton Raphson formula by Dimple Rani.,and Vinod Mishra [6].
The modified decomposition needs only a slightvariation from the standard decomposition method
may provide the exact solution by using iterations
only and sometimes without using the so-called
adomain polynomials, its effectiveness is based on
the assumption that the function  can be divided
into two parts and the paper choice of  and  .

  =   + # ,   ,THE MODIFIED DECOMPOSITIONMETHODThe standard decomposition method,  = ,,  ,  ≥ 0,EXAMPLE   =(1)
Having determined the components 0(), 1(),2(), . . .,the solution () in a series form definedby = ∑  (4)   =  ,   ,  ≥ 1.
was developed. It is important to note here that there
were some conclusions made in [1]. First, the slightvariation in reducing the number of terms of  
will result in a reduction of the computational
work and will accelerate the convergence. Second,
this slight variation in the definition of thecomponents   and   may provide thesolution by using two iterations only.
Third, there is no need sometimes to evaluate the socalled Adomian polynomials required for the
nonlinear equations.

Example1. Consider the Volterra integral equationof second kind = 1 + 2 + sin  +  − cos  − #  t .




(2)

Applying the Modified Decomposition Method
using Maple we find

The modified decomposition method [3] . The
modification is based on the assumption that thefunction () can be divided into two parts,

Table 1 Numerical results and exact solution of
Volterra integral equation for example 1

81

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017



!

0.10000
0.20000
0.30000
0.40000
0.50000
0.60000
0.70000
0.80000
0.90000
1.00000

0.2998334
0.5986693
0.8955202
1.1894183
1.4794255
1.7646425
2.0442177
2.3173561
2.5833269
2.8414710

-./0

-4454

0.2998334
0.5986693
0.8955202
1.1894184
1.4794256
1.7646429
2.0442191
2.3173603
2.5833376
2.8414958

0.0000000
0.0000000
0.0000000
0.0000000
0.0000001
0.0000004
0.0000014
0.0000042
0.0000107
0.0000248=  + 123 

0.40000
0.50000
0.60000
0.70000
0.80000
0.90000
1.00000

2.4810724
2.6276260
2.7854652
2.9551690
3.1374349
3.3330864
3.5430806

2.4810723
2.6276259
2.7854652
2.9551674
3.1374288
3.3330613
3.5429900

0.0000000
0.0000001
0.0000000
0.0000016
0.0000061
0.0000251
0.0000900

Fig. 2 Plot 2D of the exact solutions result Of
Volterra integral equation for example 1.
Example 3. Consider the Fredholm integral equationof second kindFig.1 Plot 2D of the exact solutions result Of
Volterra integral equation for example 1.



Table 3 Numerical results and exact solution of
Volterra integral equation for example 3.

− #  t .


Applying the Modified Decomposition Method
using Maple we findTable 2 Numerical results and exact solution of
Volterra integral equation for example 2
!

-./0

=+

-4454

+ ;<1= 0.10000
0.20000
0.30000

2.1050042
2.2200668
2.3453385

2.1050042
2.2200667
2.3453385

Applying the Modified Decomposition Method
using Maple we find

Example2. Consider the Volterra integral equationof second kind1 = 1 +  +   +  6 + cosℎ  + 89:ℎ
2






> = ? − ? + sin  +  cos  − # > t .


0.0000000
0.0000000
0.0000000

82



!

0.10000
0.20000
0.30000
0.40000
0.50000
0.60000
0.70000
0.80000
0.90000
1.00000

1.2050043
1.4200721
1.6453790
1.8812430
2.1281468
2.3867613
2.6579704
2.9428970
3.2429300
3.5597528

-./0

-4454

1.2050000
1.4200000
1.6450000
1.8820000
2.1290000
2.3890000
2.6580000
2.9450000
3.2430000
3.5610000

0.0000043
0.0000721
0.0003790
0.0007570
0.0008532
0.0022387
0.0000296
0.0021030
0.0000700
0.0000000= @ + 123 

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

Fig. 3[3] Abdul-Majid. W., Linear and Nonlinear Integral
Equations, Higher Education Press, Beijing,
China, 2011.
[4] Lie-june Xie., A New Modification of Adomian
Decomposition Method for Volterra Integral
Equations of the Second Kind,Volume 2013,
Article ID 795015, 7pages.
[5] Sh. Javadi., A Modification in Successive
Approximation Method for Solving Nonlinear
Volterra Hammerstein Integral Equations of theSecond Kind, Journal of Mathematical Extension,
Vol.8, No.1, 2014, 69-86.
[6] Dimple Rani., and Vinod Mishra., Modificationof Laplace Adomian Decomposition Method for
Solving Nonlinear Volterra Integral andIntegro-differential Equations based on Newton
Raphson Formula, European Journal Of Pure
And Applied Mathematics, Vol.11, No.1, 2018,202-214.
[7] Peter. L., Analytical and Numerical Methods for
Volterra Equations, Studies in Applied
Mathematics 7, SIAM, Philadelphia, 1985.
[8] Dalal A.M, Amani..Z.B.l, Badreeh..M. G.,
Numerical Solution of Volterra Integral
Equation of Second Kind Using Implicit
Trapezoidal, Journal of Advances In
Mathematics, Vol8,No.2,pp.1540-1553,2014.
[9] Dalal .A. M., Adomian Decomposition Method
of Fredholm Integral Equation of the Second
Kind Using Maple, Journal of Advances In
Mathematics, Vol9,No.1,pp.1868-1875,2014.
[10] Dalal. A.M., Application of Adomian
Decomposition Method for Solving ofFredholm Integral Equation of the Second Kind,
European Journal of Science and Engineering,
Vol9,No.2,pp.1-9,2014.

Plot 2D of the exact solutions result Of
Volterra integral equation for example 3.

CONCLUSION
In this paper, the Modified Decomposition
Method to the solution of Volterra integral equation
numerical results demonstrate that our method is an
accurate and reliable numerical technique forsolving Volterra integral equation . Finally, The
Modified Decomposition Method using Maple canbe easily extended and applied to linear or nonlinear
Fredholm and Volterra integral equations of the firstor second kind.

[11] Dalal .A.M., Adomian Decomposition Method
for Solving of Fredholm Integral Equation of
the Second Kind Using Matlab, International
Journal of GEOMATE, Dec., 2016, Vol. 11,
Issue 28, pp.2830-2833.Special Issue on
Science, Engineering and Environment, ISSN:
2186-2990, Japan.

ACKNOWLEDGEMENTS
This paper was supported by the Deanship ofScientific Research (DSR), King Abdulaziz
University, Jeddah..

REFERENCES[12] Dalal A.M. and Honida M.M., Numerical
Solution of System of Three Nonlinear Volterra
Integral Equation Using Implicit Trapezoidal,
Journal of Mathematics Research, Vol.10, No. 1,
February 2018,ISSN 1916-9795 E-ISSN 19169809.

[1] Abdul-Majid. W., A reliable Modification of
Adomain Decomposition Method,. Applied
Mathematics and Computation, Vol. 102, No.1,
1999, pp.77-86.
[2] Abdul-Majid. W., and Said. A. El-S., Anew
Modification of the Adomain Decomposition
Method for Linear and Nonlinear Operators,.
Applied Mathematics and Computation, Vol. 122,
No.3, 2001 , pp.393-405.

83

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

STRUCTURE-BASED VIRTUAL SCREENING OF INDONESIANNATURAL PRODUCT COMPOUNDS AS EBOLA VIRUS VP30
PROTEIN INHIBITORS
Givan Andris Tio1, Andrei Bernadette1, Mochammad Arfin Fardiansyah Nasution1, Puteri Aprilia Sitadevi1,
Syahrul Ridzki Pratama1, and Usman Sumo Friend Tambunan*
1
Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Indonesia

ABSTRACT
Indonesia is the second-highest biodiversity in the world. At least 9,600 out of 30,000 plant species exist inIndonesian tropical forests known to have medicinal properties. Hence lots of potentials still need to be explored
including their abilities as an antiviral agent. Ebola virus (EBOV) continues as a major health threat worldwide
with currently neither effective vaccine nor drug available. VP30 is one of the most important proteins for viraltranscription activator of EBOV. Therefore, inhibiting this protein can be a viable choice for disturbing the life
cycle of this virus. In this research, about 3,430 Indonesian natural product compounds had been screened throughcomputational studies. These compounds were subjected into computational ADMET test using DataWarrior
v4.7.2 while the molecular interaction and Gibbs free binding energy (∆Gbinding) value of the selected compounds
were analyzed and calculated using MOE 2014.09 software. Finally, the oral bioavailability of the selectedcompounds would be predicted using SwissADME software. Through this study, three compounds were selected
to be potential VP30 inhibitors due to the lowest ∆Gbinding value. They were aglamide C, IDNP-206, and scoulerine,
which have ∆Gbinding value of -9.7940 kcal/mol, -8.2686 kcal/mol, and -7.3823 kcal/mol, respectively. Moreover,
the all of these compounds did not possess any toxicity properties, nor have low oral bioavailability, suggested
that all three compounds may be highly absorbed in the human body through oral administration. Thus, thesecompounds should be liable to be selected as the drug candidate of EBOV targeting VP30 and analyzed its antiviral
activities further through molecular dynamics simulation and in vitro experiment.
Keywords: Indonesian natural products, EBOV, VP30, Molecular docking, ADMET test.
INTRODUCTION

replication and reducing destruction of the hostimmune system [6].
Due to the high mutable genome that resides in
EBOV, the developments of EBOV drug are focusedon the high-conserved regions. One of them is VP30,
the transcription activator domain in EBOV. Thisvirus had multiple functions, such as transcription
activator and involved in nucleocapsid assembly.
VP30 phosphorylation assumed to be a crucial
regulatory factor in establishing if the protein isindeed involved in transcription or assembly of thevirus. The N-terminal of EBOV VP30 presents witha Cys3-His zinc-binding domain native to M2-1
proteins of pneumoviruses and MARV VP30 [7]–[9].
Natural products have been considered as one ofthe potential lead compound sources because of their
attractive bioactivities. Furthermore, many drugs
have been sold on the market are either acquired orderived from natural sources compounds [10]. As thesecond-highest biodiversity country in the world,
Indonesia has a high potential to produce a new drugcandidate from its natural sources, either from its
plants or animals [11]. Thus, this research aims to
obtain new drugs from Indonesian natural products
for combating Ebola disease by inhibiting in the
VP30 protein through in silico drug design method.

Ebola virus disease (EVD) is one of the fatal
diseases around the globe, which infected no less than
28,642 people and killed 11,319 people globally [1].
Although extensive ongoing research has been
performed, to date, no approved cure has been
affirmed for this malignant disease. EVD can beeasily characterized by severe hemorrhagic fever,
focal necrosis of the liver, kidney, and spleen,
bleeding diathesis and sudden shock with a mortality
rate of 90% [2]. EVD caused by Ebola virus (EBOV),
a lipid-enveloped negatively stranded RNA virus
affecting both human and non-human primates. There
are five species of the virus been identified; include
Zaire, Sudan, Ivory Coast, Bundibugyo and Reston
EBOV with the highest fatality attributed to the Zaire
species [3].
EBOV outbreak drew much attention to the drug
discovery and development for this deadly pathogen.
Currently, several approaches have been undergone
to effectively combat EBOV, such as thedevelopment of peptides, application of monoclonal
antibodies, small molecules inhibitors, recombinant
DNA vectors as well as repurposing existing drugs[4], [5]. Therapeutics target and attack the virus at
different stages of its life cycle, thereby halting virus
84

SEE – Nagoya, Japan, Nov.12-14, 2018

RESEARCH METHODOLOGY

Bioavailability and Pharmacokinetics Predictions
In this study, SwissADME online web service wasutilized to predict the bioavailability andpharmacokinetic properties of the selected
Indonesian natural products that have remained after
the docking simulation. In the end, about three
ligands that have the best properties were selected as
best drug candidates for treating Ebola through the
inhibition of EBOV VP30.

Tools and Materials
This study was conducted using both offline andonline software such as Molecular Operating
Environment (MOE) 2014.09 [12], DataWarrior
v4.7.2 [13], SWISS-MODEL [14], and SwissADME[15]. Then, the structure of Indonesian Natural
Products that used as ligands was obtained from
Herbal Database (HerbalDB), which developed by
the Faculty of Pharmacy, Universitas Indonesia(http://herbaldb.farmasi.ui.ac.id/v3/index.php) [11].
This research was conducted based on the research
pipeline that has been previously performed by our
research group [16]–[18].

RESULTS AND DISCUSSIONS
Pre-docking Simulation
In this study, the Indonesian natural products
molecular structures were retrieved from HerbalDB
in .mol file format. The compounds itself wereobtained through the literature study that mentioned
any plants, fungi, or microbes that resides or can befound exclusively in Indonesia according to literatureand extensive study [11]. Throughout this method,about 3,429 Indonesian natural product compounds
were retrieved from this database. This step was
followed up by computational ADME-Tox test to
determine their drug-likeness and toxicity properties.
Any toxicity properties that owned by any ligand may
lower their efficiency and effectivity when used as the
drug. Hence, this step was compulsory to eliminate
any compounds that have a low probability as drugcandidates. According to the results from this step,
about 3128 Indonesian natural product compounds
were omitted through this test because they possessed
either toxicity properties, such as mutagenic,
tumorigenic, reproductive effect, and irritant
properties, or have a low possibility to be developed
as a drug, according to their druglikeness score. Thus,
only 301 ligands have passed this stage and can beprepared further in the ligand optimization processes.
In this study, the optimization of ligand structure
was utterly achieved using MOE 2014.09 software.
This step was conducted to obtain the ligand pose that
resembles the molecular structure when treated in thereal condition, especially in the human body. At first,
the remaining 301 Indonesian natural productcompounds, which saved earlier in .sdf file format,
were opened and prepared according to the default
protocols in the respective software, including the‘Wash’, ‘Partial Charge’ and ‘Energy Minimization’features in Database Viewer, MOE 2014.09. The
prepared ligands were later saved in .mdb file format
for the docking simulation processes.
The 3D structure of EBOV VP30 that used for the
research was listed with PDB ID: 2I8B [19], whichobtained from RSCB-PDB. The corresponding 3D
structure was prepared using MOE 2014.09 software
as well. First, The forcefield that used for the protein
preparation was selected. In this research,
Amber10:EHT with Gas Phase solvation was used.
After that EBOV VP30 is prepared and optimized
using ‘LigX’ that is featured on MOE 2014.09. The

Preparation and Optimization of Indonesian
Natural Products
The molecular structures of Indonesian Natural
Products were retrieved from HerbalDB in .mol fileformat. Followed by the computational ADME-Tox
test using DataWarrior v4.7.2 software. All
Indonesian natural product ligands were screened
based on their druglikeness and their toxicity
properties, such as mutagenic, tumorigenic, irritant,and reproductive effect. Then, the remaining ligands
were prepared and optimized by using default
protocol on MOE 2014.09 software.
Preparation of EBOV VP30
In this research, EBOV VP30 sequence wasobtained from the National Center for Biotechnology
Information(NCBI)
database(http://www.ncbi.nlm.nih.gov/) in FASTA file format.
Then, the 3D-structure of EBOV VP30 was searchedby using SWISS-MODEL then downloaded from the
Research Collaboratory for Structural Bioinformatics
Protein
Data
Bank(RSCB-PDB)(http://rcsb.org/pdb/home/home.do) in .pdb fileformat. The downloaded structure was prepared andoptimized by using ‘LigX’ protocol on MOE 2014.09
software, which slight modification has been madecompared to the default protocol.
Molecular docking simulations
The docking simulations of EBOV VP30 protein
was done by using MOE 2014.09 software. Moleculardocking simulations were divided into four stages.
First, the prepared ligands underwent rigid docking
with 30-1 retains. Then, these ligands were selectedbased on RMSD (Root Mean Square Deviation) andfree binding energy calculations. Second, the selected
ligands underwent rigid docking with 100-1 retains.
Third, 100-1 retains flexible docking protocol was
performed to decrease the number of selected ligands.
Finally, these selected ligands underwent flexible
docking with 300-3 retains.

85SEE – Nagoya, Japan, Nov.12-14, 2018

these ligands have a ∆GBinding value of -7.3054, 7.1857 and -7.8649 kcal/mol, respectively.
Furthermore, the docking simulation results revealed
about five ligands have better molecular interaction,and some of them have lower ∆GBinding value
compared to the standard ligands, as shown in Table
1. In this study, aglamide C was determined as theIndonesian natural product compounds which havethe lowest ∆GBinding value, sitting at -9.7940 kcal/mol.
In addition, lissoclibadin 4, IDNP-206 (IUPAC
Name:
3,10,11-trihydroxydibenzo[b,e]oxonine7,13(6H,8H)-dione), epiafzelechin and scoulerine
also have ∆GBinding value as well, respectively at 8.7101, -8.2686, -7.8768, and -7.3823 kcal/mol.
Except for scoulerine, which has lower binding
affinity than taxifolin, all of these ligands possessedhigher binding affinity on EBOV VP30 protein on its
binding site. Thus, these compounds, regarding Gibbs
free binding energy, are suitable to be progressed as
Ebola drug candidates.
In addition to free binding energy, the molecularinteraction between the ligands and the binding siteof EBOV VP30 protein is another important aspect ofdetermining whether the ligand can be considered asa suitable inhibitor or not.

preparation was done by removing the watermolecules and tether the receptors and the
optimization was done by fixing the atoms positions
and hydrogen that will interact with EBOV VP30
position with the ligands. The optimized EBOV VP30
protein structure was later saved in .moe file format
to retain its forcefield and structure, which can beused later on for the docking simulation.
Molecular Docking Simulation of EBOV VP30
and Indonesian Natural Products
In this study, the determination of binding sites
of VP30 protein was obtained through ‘Site Finder’feature in MOE 2014.09 software by searching thefavorable binding sites based on several parameters,such as solvent’s exposures and lipophilicity of thebinding sites. The result shows that the binding sites
of VP30 protein are Leu144, Arg179, Lys 180,
Phe181, Ser182, Lys183, Ser184, Gln185, Leu188,
His215, Leu249, Pro250, Cys251, Glu252, andSer253. These binding sites were selected due to theirresemblance to the previous research [20], [21]. Thus,
the molecular docking simulation would be
performed on these binding sites.
The docking simulation of EBOV VP30 protein
was done by using MOE 2014.09 software. The
inhibition of EBOV VP30 protein can be achieved if
the ligands capable of binding to a target receptor of
the VP30 binding site. In this study, 301 compoundsof Indonesian natural product, which alreadyunderwent ADME-Tox test, acted as “ligands” toinhibit the EBOV VP30 protein. These ligands went
into molecular docking simulation. The simulation
was done to determine the free binding energy
calculations and the number of molecular interactions
between the complexes of ligand and protein. Freebinding energy (∆GBinding) is associated with thebinding affinity between ligand and receptor and canbe determined by the stability of ligand-protein
complexes. To find a suitable candidate ligand forinhibiting the target receptor of EBOV VP30, thatligand must have a higher Gibbs free binding energy
and better molecular interaction with the binding siteof EBOV VP30 pocket regarding binding energy andmolecular interaction. The free binding energy valueof the ligands was expected to have a negative value
and lower than the standard ligands. So, this ligand
can be applied as a novel compound for inhibiting
EBOV VP30 protein [17].
In this study, BCX4430, gossypetin, andtaxifolin were selected as the standard ligands. The
first ligand was chosen because it has been utilized asa drug for combating Ebola through in vitro and invivo experiments, while the latter two ligands werechosen because they have the highest binding affinity
among all tested ligand through in silico experimentthat performed in the previous research [22], [23].
According to the docking results from this research,

Table 1. The docking results of EBOV VP30 and thebest Indonesian natural product compounds, alongwith three standard ligands
No. Ligand CodeΔGbinding value(Compound Name)(RMSD (Å))
1.
IDNP-268-9.7940(Aglamide C)
kcal/mol(1.4500)
2.
IDNP-206-8.7101(Lissoclibadin 4)
kcal/mol(1.4388)
3.
IDNP-204-8.2686(3,10,11kcal/mol
Trihydroxydibenzo[b,e]ox (1.6453)
onine-7,13(6H,8H)-dione)
4
IDNP-70-7.8768(Epiafzelechin)kcal/mol(1.0326)
5
IDNP-123-7.3823(Scoulerine)
kcal/mol(1.0382)
S1
Galidesivir / BCX4430-7.3054
kcal/mol(0.9212)
S2
Gossypetin-7.1857
kcal/mol(1.2655)
S3
Taxifolin-7.8649
kcal/mol(0.8521)First, the molecular interactions of standard
ligands were observed. As is displayed in Fig. 1.
86

SEE – Nagoya, Japan, Nov.12-14, 2018

BCX4430 formed a molecular interaction with
Lys180 via hydrogen bonds through its backbone,with other two molecular interaction with Cys251
were observed that act as sidechain donor and several
other interactions within the binding pocket throughvan der Waals interaction. Moreover, gossypetin
formed a molecular interaction with Gln185 as asidechain acceptor, with two molecular interaction
with Cys251 that act as sidechain donor. Finally,taxifolin has two molecular interaction with Cys251
as a sidechain donor.

though scoulerine has the highest Gibbs free binding
energy compared to other four ligands, but thiscompound has better molecular interaction within the
EBOV VP30 binding pocket. Scoulerine has fourinteresting molecular interactions formed in EBOVVP30 binding site, such as arene-H interaction with
Phe181, hydrogen bonds with the side chain of
Gln185, and two hydrogen bonds interaction with the
backbone of Lys180. Other Indonesian natural
product ligands such as lissoclibadin 4, IDNP-206,
aglamide C, and epiafzelechin only have one to twointeractions within the binding pocket, which is notpreferred, even though they have better Gibbs freebinding energy. Thus, scoulerine has the better resultin terms of molecular interaction compared to any
other Indonesian natural product compounds. The
molecular interactions of scoulerine in the bindingsite of EBOV VP30 is displayed in Fig. 2.

Fig. 1. The molecular interaction of BCX4430 (top),
gossypetin (middle) and taxifolin (bottom) in thebinding site of EBOV VP30.

Fig. 2. The two-dimensional and three-dimensional
molecular interaction of scoulerine in the binding siteof EBOV VP30.

In this research, the molecular interaction
between the Indonesian natural product compounds
and EBOV VP30 were also compared as well. Even

Results of Bioavailability and Pharmacokinetics
Predictions
In this study, the remaining five Indonesian87

SEE – Nagoya, Japan, Nov.12-14, 2018

natural product compounds, along with the threemolecular properties prediction tests. From the result,standard
compounds,
were
subjected
toall of the Indonesian natural product ligands have abioavailability and pharmacokinetics prediction test.
molecular weight less than 500 Daltons, logP lessThis test was done to measure the pharmacokinetic
than 5.0, hydrogen bond acceptor less than 10 andproperties of the ligands, as well as the oralhydrogen bond donor less than 5, which obey
bioavailability of the selected ligands according to
Lipinski’s Rule of Five [24]. This means that all of
several parameters such as physicochemical
the Indonesian natural product ligands have likableproperties (e.g., molecular weights, TPSA) that haveproperties to be absorbed and administrated throughbeen predicted through this test. This prediction was
the oral system in the human body. However,entirely made by using SwissADME online web
according to the same prediction test, only two out ofservice, which can be accessed through this website
five Indonesian natural product compounds, namely
http://www.swissadme.ch/. Also, DataWarrior v4.7.2
IDNP-206 and aglamide C, that has the positive
software was also utilized to measure thedruglikeness value, which indicates these ligands
druglikeness score and molecular properties that also
have a likeness to become the drug compounds thandetermine the oral bioavailability of the compound.
any other ligands, based on their molecular fragments.
Table 2 shows the results of the druglikeness andAlso, the oral bioavailability prediction of
one on Egan’s, while it did not break any Lipinski’s
Table 2. The physicochemical properties of the selected Indonesian natural products and the standard ligands
Druglikeness
LigandHHTPSAMW
clogP
Druglikenessacceptor donor(Å2)
Lissoclibadin 4-1.5525484.704.32
44152.52
3,10,11-Trihydroxydibenzo[b,e]oxonine300.26

1.16

6

3

104.060.29065

Scoulerine

328.38

3.07

4

3

63.36

-1.4498

Aglamide C

300.40

2.86

2

1

49.41

2.9194

Epiafzelechin274.27

1.51

5

4

90.15

0.3153

BCX4430

266.280.12

5

6

144.89-0.2121

Gossypetin

318.241.33

8

6

151.59-0.0083

7,13(6H,8H)-dione

Taxifolin

304.25Indonesian natural product compound was also
conducted as well along with the molecular properties
prediction using the same web service. The result canbe seen in Table 3. According to the results, both thebest Indonesian natural product compounds and thestandard ligands owned the average bioavailability
score; it is indicated by the low violation number of
any rules that determined the oral bioavailability inany compounds. For instance, lissoclibadin 4 ligand
violates two rules of Ghose’s, one on Veber’s, and

0.44480.71
75127.45rule. Although the bioavailability of this compound ismediocre, the high violation number of these rules
made lissoclibadin 4 has a low gastrointestinal
absorption prediction. Surprisingly, other four
compounds (IDNP-206, scoulerine, aglamide C andepiafzelchin) did not break any of these rules. Hencethese ligands have higher gastrointestinal absorption
than lissoclibadin 4, even higher than BCX4430 andgossypetin.

Table 3. The oral bioavailability prediction of the selected Indonesian natural products and the standard ligands
Bioavailability
Ligands
GI
Lipinski’s Ghose’s Veber’s
Egan’sScore
Lissoclibadin 4
Low
0
2
1
1
0.55
3,10,11High
0
0
0
0
0.55
Trihydroxydibenzo[b,e]oxonine7,13(6H,8H)-dione
Scoulerine
High
0
0
0
0
0.55
Aglamide C
High
0
0
0
0
0.55
Epiafzelechin
High
0
0
0
0
0.55
BCX4430
Low
1
1
1
1
0.55
Gossypetin
Low
1
0
1
1
0.55
Taxifolin
High
0
0
0
0
0.55
88

SEE – Nagoya, Japan, Nov.12-14, 2018[7]
CONCLUSIONSIn this research, about 3,429 Indonesian natural
product compounds were subjected into thecomputational ADME-Tox screening test, moleculardocking simulation, and bioavailability prediction
test to determine the best compounds that can beutilized as the EBOV VP30 inhibitors. In the end,
after the series of docking simulations and prediction
test, three Indonesian natural product compounds,
namely IDNP-206, scoulerine, and aglamide C wereselected as the best Indonesian natural productcompounds to inhibit EBOV VP30 due to theirbinding affinity, in terms of Gibbs free binding
energies and molecular interactions, towards thebinding site of EBOV VP30, lacks of toxicity
properties and high oral bioavailability throughgastrointestinal system. Thus, the antiviral activitiesof these compounds should be determined further
through molecular dynamics simulation and in vitro
studies, to determine their complex stability andmolecular interaction under real environment, andtheir antiviral activities toward EBOV VP30,
respectively.

[8]

[9]

[10]

[12]

ACKNOWLEDGMENTS
This research publication has been funded entirely by
Hibah Penelitian Kerjasama Luar Negeri No:
538/UN2.R3.1/HKP.05.00/2017,
given
byKementerian Riset, Teknologi dan Pendidikan
Tinggi, Republic of Indonesia through Direktorat
Riset dan Pengabdian Masyarakat, Universitas
Indonesia. Finally, no conflict of interest was
declared.

[13]

[14]

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Rewar S. and Mirdha D., Transmission of
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of Global Health, Vol. 80, Issue 6, 2014, pp.
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Nyakatura E. K., Frei J. C., and Lai J. R.,
Chemical and Structural Aspects of Ebola
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Haemorrhagic Fever. Lancet, Vol. 377, Issue
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Groseth A., Charton J. E., Sauerborn
M., Feldmann F., Jones S. M., Hoenen
T., Feldmann H., The Ebola Virus
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Chemistry, 5th Ed. Oxford: Oxford
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[11] Yanuar A., Mun’im A., Lagho A. B. A.,
Syahdi R. R., Rahmat M., and Suhartanto H.,
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BiasiniM., Bienert
S., Waterhouse
A., Arnold K., Studer G., Schmidt T., Kiefer
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Cyclic Peptides as β-OG Pocket Binder
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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECTS OF PIPERACEAE PLANTS EXTRACTS ON
INHIBITION OF Aspergillus flavus AND SEEDGERMINATION OF MAIZE (Zea mays)
Chuajedton, A.1 and Boonkorn, P.1
Faculty of Science, Lampang Rajabhat University, Thailand

1

ABSTRACTThis study investigated the effects of Piperaceae plants extracts on inhibition of Aspergillus flavus andseed germination of maize (Zea mays). The crude extracts of four Piperaceae, namely, Betel (Piper betle),
Wild betel (P. sarmentosum), Long pepper (P. retrofractum) and Sakhan (P. interruptum) were extractedwith 95% ethanol and prepared in PDA agar by using poisoned food technique at several concentrations(0, 1500, 3000 and 4500 ppm). The result showed that the crude extract from Betel at 3000 and 4500 ppm
completely inhibited (100%) the growth of A. flavus meanwhile Wild betel and Long pepper crude extract
could inhibit the growth about 82.50 % and 82.20 %, respectively, after incubation for 72 hr. For seedgermination of maize, the experiment was done through 7 days. It was found that the crude extract from
Wild betel at 4500 and Sakhan at 3000 ppm revealed percentage of germination were 85.56 % and82.22 %, respectively. Therefore, the antifungal activity from Piperaceae extract may control plant
pathogenic fungi and had no effect on seed germination.
Keywords: antifungal activity, crude extract, Piperaceae, seed germination.
Prochloraz. Nowadays, the research of using
natural antimicrobial and antifungal substancewere increasing and had much attention.
Application of control pathogenic fungi inagricultural products by direct contact with plant
extracts had been reported. The controlling of
Zingiberaceae family (Ginger, Turmeric andChinese keys) were used for inhibition of
Penicillium digitatum [9]. The studied on control
of Rhizoctonia spp. and Selerotium hydrophilumof rice found that using clove extract had the best
growth inhibition[10].
Piperaceae family
showed the several secondary metabolites andpotential antimicrobial activity. Examples ofcontrolling of A. flavus and F. verticillicides byusing Betal extracts [11], The essential oil of
Amezon Piper species showed the powerful
antifungal
activity
with
Cladosporium
cladosporioides and C. sphareospernum [12]and the leaves of Piper marginatium contain theantifungal compounds [13]. The extract from P.
sarmentosum stems and leaves exhibits
antimicrobial activity against Escherichia coli
and Bacillus subtilis ([14].
The damaging effects on maize seed andseedling disease may be minimized with proper
seed handling, culture practice and seed applied,
especially, good culture practice can reduce
seedling disease [15]. However, the study about
the effects of seed treatments with natural
antifungal substances on seed germination ofmaize was little known, especially, seed infected

INTRODUCTION
Maize (Zea mays) is the most produced cereal
crop and belong to Gramineae. It is the one ofimportant cereal crop in the world. However, themaize seed faced the common problem caused
by various fungi infection which have beenfound to causing seed-borne pathogens [1].
Maize seed and seedling are susceptible to soil
and seed-borne pathogens before or after
germination. It may suffer from stunted growthor die as a result of poor root system [2].The
high quality seed of maize required theapplication of chemicals for seed treatment withfungicide. Seed treatment also had disadvantages
by increased the risk of phytotoxicity. It has beenreported that some fungicide could act as
suppressors or stimulators of germination [3].
Fungi of the genera Aspergillus, Fusarium
and Penicillium are known to produce the toxic
metabolites [4] and the toxic metabolites such as
mycotoxins has been degrade seed quality andreduce viability [5]. Especially, Aspergillus
flavus was contaminated maize seed duringstorage and seed infection [6]. Ng´ ang a´ [7]reported that A. flavus reduced the quality andeconomic value of products. Therefore, the fungi
found to contaminate maize seeds usuallycontrolled by chemical fungicide but these agents
had effects on human health and environment [8].
Normally, the fungicide those applied during thepostharvest period are Benzimidazoles and91

SEE - Nagoya, Japan, Nov.12-14, 2018

by A. flavus. Thus, the objective of this research
was to determine the effects of Piperaceae plants
extracts on inhibition of A. flavus and seedgermination of maize.

(28±1°C) for 7 days. Then, the maize seeds wereanalyzed for the percentage of germination byusing standard germination tests. All treatments
were conducted according to the method of theInternational Seed Testing Association [16].
Seeds were placed on moisture germination
paper at 30 seeds per paper towel. Paper towels
were placed in incubator at 25±1°C. Percentage
germination was determined after 7 days. Results
were presented as the percentage of germination.
They were calculated using the following
formula: Percentage of germination = [Seedgerminated/Total seed] x100

MATERIALS AND METHODS
The plant materials and extraction
Four Piperaceae, namely, Betel (P. betle),
Wild betel (P. sarmentosum), Long pepper (P.
retrofractum) and Sakhan (P. interruptum) wererinsed with distilled water and dried in the air.
Dried of plants were grinded into fine powderusing a grinding machine. The powders wereextracted with 95% ethanol (1:5 w/v ratio) at
room temperature for 48 hr and then filteredthrough the filter paper Whatman No. 1. The
filtrates were evaporated with rotary evaporator
at 40°C. The crude extracts were dried with
Vacuum Freeze Dryer until the weight constant.

Statistical analysis
All experiments were replicated three times
and evaluated with regression procedure using
SPSS version 17. Differences among treatments
performed using Duncan’s Multiple Range test
(P = 0.05).

Antifungal assay
A. flavus was obtained from Faculty of
Science,
Lampang
Rajabhat
University,
Lampang, Thailand. The fungus was cultured on
potato dextrose agar (PDA) slants at 30°C for 7
days. A spore suspension was harvested bypouring old cultures of A. flavus with sterile
distilled water. Subsequently the spore
suspension was transferred into 100 ml of sterile
distilled water in a 250 ml in flask. Then, thesuspension was shaken for 10 min on an orbital
shaker at 27°C and it was filtered through twolayers of steriled muslin cloth. The cell numbers
were counted with a haemacytometer and theinitial concentration was adjusted with sterile
distilled water to a concentration of 106 CFU/ml.
Then, Maize seeds were soaked in A. flavus
spore suspension (106 CFU/ml) and allowed toair dry after that seeds were placed onto thecenter of PDA containing the crude extracts offour Piperaceae by using poisoned foodtechnique at several concentrations (0, 1500,
3000 and 4500 ppm) and incubated at room
temperature (28±1°C) for 72 hr. The antifungal
effects were estimated by the following formula:
Antifungal activity (%) = [(Diameter of growthin control plate – Diameter of growth in the platecontaining plant extracts)/ Diameter of growth incontrol plate] x100.

RESULTS AND DISCUSSION

Standard germination test
Maize seeds were obtained from the farmer in
Lampang Province, Thailand. And then seeds
were coating with plant extracts {Betel (P. betle),
Wild betel (P. sarmentosum), Long pepper (P.
retrofractum) and Sakhan (P. interruptum)} at
various concentrations (0, 1500, 3000 and 4500ppm) and incubated at room temperature

The effects of crude extracts on seedgermination
Seed germination was evaluated by thepercentage of germination. Seed germination ofmaize effected by crude extracts was showed inTable 2. The control had germination of 74.44 %meanwhile the crude extract from P.
sarmentosum at 4500 and P. interruptum at 3000

Antifungal activity of crude extracts
Crude extracts from four Piperaceae, Betel(Piper betle), Wild betel (P. sarmentosum), Long
pepper (P. retrofractum) and Sakhan (P.
interruptum) were sticky and dark green.
Antifungal activity of crude extracts was showedin Table 1. At 3000 and 4500 ppm of P. betle
extracts exhibited the best result in growth
inhibition (100%) meanwhile P. sarmentosum at
4500 ppm and P. retrofractum at 4500 ppm
crude extract could inhibit the growth about
82.50 % and 82.20 %, respectively whencompared to control (Fig. 1). Ounchokdee [17]reported that the crude extract with diethyl ether
and ethyl acetate from P. longum exhibited
potent antifungal activity against tested plant
pathogens (C. cladosporioides, C. capsici and F.
oxysporum) as well as the extraction of Betel leaf
with 95% ethanol at 10000 ppm completely
inhibited the growth of A. flavus and F.
verticillicides [11]. Reigada [13] reported thatthe extract from leaves of P. maginatum containthe antifungal compounds. The result of thisresearch also suggested that the crude extracts
from Piperaceae might contain the several
secondary metabolites and antifungal activity forcontrolling plant pathogen fungi.

92

SEE - Nagoya, Japan, Nov.12-14, 2018

ppm revealed percentage of germination were
85.56 % and 82.22 %, respectively and the result
showed no significantly difference (same letter
showed in Table 2) In the another report, Perelló[18] reported the garlic extract promoted thegrowth activities on wheat seedling and percent
seedling germination for wheat cultivars tested

was > 85% and was greatly increased by either
fungicide or garlic juice treatments. However,
the antifungal activity from Piperaceae extract
had no effect on seed germination.

Table 1 Growth inhibition of A. flavus (%) after treated with plant extracts
Growth inhibition of A. flavus (%)
Treatments
Concentrations of plant extracts (ppm)
0
1500
3000
4500
P. sarmentosum
0.00g
68.50d75.50c82.50bP. betle
0.00g
80.50b100.00a100.00agdc
P. interruptum
0.00
66.25
72.91
75.50cgfe
P. retrofractum (leaf)
0.00
58.33
62.58
68.75dgccP. retrofractum (fruit)
0.00
72.91
75.50
82.20bData followed by the same letter within the column are not significantly different (*P=0.05)
Table 2 Percentage of germination of Maize seed after coating with plant extracts% Germination
Treatments
Concentrations of Plant Extracts (ppm)
0
1500
3000
P. sarmentosum
74.44abcde
47.78f71.11abcde
P. betle
74.44abcde
56.67ef
75.56abcde
abcde
abcd
P. interruptum
74.44
76.67
82.22ababcde
abcde
P. retrofractum (leaf)
74.44
73.33
62.22cdef
abcde
bcdef
P. retrofractum (fruit)
74.44
65.56
58.89def
Data followed by the same letter within the column are not significantly different (*P=0.05)

4500
85.56a64.47bc
60.00def
81.11abc
74.47abcde

CONCLUSION

Fig. 1

a

b

c

d

e

f

The crude extracts of four Piperaceae might
contain antifungal compound for controlling
plant pathogen fungi. The crude extract from
Betel at 3000 and 4500 ppm completely
inhibited (100%) the growth of A. flavus. For
seed germination of maize, the crude extractfrom Wild betel at 4500 and Sakhan at 3000
ppm revealed percentage of germination were
85.56 % and 82.22 %, respectively. The resultof this research also suggested that theantifungal activity from Piperaceae extract
could control plant pathogenic fungi and had noeffect on seed germination.
ACKNOWLEDGEMENTS
This work has been supported by
Department of Biology, Faculty of Science,Lampang Rajabhat University.

Effect of plant extracts (a) Control (b)P. sarmentosum (c) P. betle (d) P.
interruptum (e) P. retrofractum (leaf)(f) P. retrofractum (fruit) after
incubated at room temperature(28±1°C) for 72 hr

REFERENCES[1]Shetty, H. S. Different Types of Damages in
Seed Caused by Seed-borne Fungi. Seed
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Denmark, 20th-25th June, 1998, pp. 53-62.

93

SEE - Nagoya, Japan, Nov.12-14, 2018[2]Vincelli, P. Seed and Seedling Disease ofCorn. Plant Pathology Fact Sheet Universityof Kentucky- College of Agriculture PPESAG-C-02. 2008.
[3]Stevanovic, V., Indic, D. and Knezevic, B.
The effect of fungicide for seed treatment on
germination of barley. Pesticidi I
Fitomedicina. Vol. 24, 2009, pp. 35-41.
[4]Caster, L. and Frederikson, R. A. Fusarium
head blight, occurrence of effect on sorghum
yield and grain characteristics in Texas.
Journal of Plant disease. Vol. 64, 1980, pp.
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[5] Jalander, V. and Gachande, B. D. Effect of
Fungal Metabolites of Some Rhizosphere
Soil Fungi on Seed Germination andSeedling
Growth of Some Pules andCereals. Science research reporter. Vol. 2,
Issue. 3, 2012, pp. 265-267.
[6]Ellis, W. O., Smith, J. P., Simpson, B. K.,
Oldham, J. H. and Scott, P. M. Aflatoxins infood: occurrence, biosynthesis, effects onorganism, detection, and methods of control.
Crit. Rev. Food Sci. Nutr. Vol. 30, 1991, pp.
403-439.
[7] Ng´ ang a´, J., Mutungi, C., Imathiu, S. and
Affognon, H. Effect of triple- layer hermatic
bagging on mold infection and aflatoxin
contamination of maize during multi-monthon farm storage in Kenya. J. Stored Prod.
Res. Vol. 69, 2016, pp. 119-128.
[8]Vicente, A., Arques, F. A., Villabi, J. R.,
Centrich, F., Serrahima, E., Ilebaria, E. andCasa, C. X. Plguicides en la dieta: aportando
piezas al rompecabezas. Gac. Sanit. Vol. 18,
2004, pp. 425-430.
[9]Matvijit, S., Techavuthiporn, C., Khewkhom,N., Wongsaree, C. and Kanlayanarat, S.
Effect of Zingiberaceae crude extract on
inhibition of Penicillium digitatum Sacc.
Agricultural Sci. J. Vol. 42, Issue.
3(Suppl.),2011, pp. 303-306.
[10]Aye S. S. and Mutsumoto M. Effect ofsome plant extracts on Rhizoctonia spp. andSclerotium hydrophilum. Journal of
Medicinal Plants Research., Vol. 5, Issue 5,2011, pp. 3751-3757.
[11] Srichana D., Phumruang A. and Chongkid
B. Inhibition Effect of Betal Leaf Extract
on the Growth of Aspergillus flavus andFusarium verticillioides. Thammasat Int. J.
Sc. Tech., Vol. 14, No.3, July-September
2009.
[12]Silva, J. K. R., Pinto, L. C., Burbano, R. M.
R. and Montenegro, R. C. Essential oils of
Amezon Piper species and their cytotoxic,
antifungal,
antioxidant
andanticholinesterase activities. Indrustrial Crops
and Products. Vol. 58, 2014, pp. 55-60.

[13] Reigada, J. B., Tcacenco, C. M., Andrade,L. H. and Kato, M. J. Chemical constituentsfrom Piper marginatum Jacq.(Piperaceae)antifungal activities and kinetic resolutionof(RS)-marginatumol
byCandidaantrctica
lipase(Novozym
435).
Trtrahedron Asymmetry. Vol. 18, 2007, pp.
1054-1058.
[14]Masuda, T., Inazumi, A., Yamada, Y.,
Padolina, W. G., Kikuzaki, H. and
Nakatani,N.
Antimicrobial
phynylpropanoides from Piper samentosum. Phytpchemistry. Vol. 30, 1991, pp. 32273228.
[15]McGee, D. C. Seed pathology: its place inmodern seed production. Plant Dis. Vol. 65,
pp. 638-641.
[16] International Seed Testing Association.
(2007). International Rule for Seed Testing.
Seed Sci. & Technol. 27 Supplement.
[17] Ounchokdee U., Rueangrit S. and Dethoup
T. Antifungal activity profile of Piperlongum fruit extract against plant
pathogenic fungi. JBiopest. Vol. 9, Issue 2,
2016, pp 97-103.
[18] Perelló, A., Gruhlke, M. and Slusarenko,
A. J. Effect of Garlic Extract on Seed
Germination, Seedling Health, and Vigour
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2013, pp. 317-323.

94

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

FORMULATION OF THE BODY SCRUB CREAM CONTAINING
MORINGA SEED POWDER (MORINGA OLEIFERA) AND ITS
EXAMINATION DERMAL ACUTE IRRITATION
Hendrawati1 , Annita Karunia Savitri1 , Nina Fitriyati1, Aulia Andi Mustika2
1

Departement of Chemistry Faculty of Science and Technology State Islamic University Syarif
Hidayatullah Jakarta. Jl. Ir. H Djuanda no. 95 Ciputat Tangerang Selatan Banten Indonesia
2

Bogor Agricultural University IPB. Jl Raya Dramaga, Bogor 16680, West Java, Indonesia.
ABSTRACT

Moringa seeds (Moringa oleifera) have many substances such as antioxidants, minerals and vitamins that are
useful for skin health. Moringa seed could be used as an additional material of cosmetic. One of the misscrub
cream by using moringa seed as abrasive material (abrasiver). The purpose of this research are to know the
optimal formulation of scrub cream moringa seed and characterization based on the requirement of quality skinmoisturizers according to SNI 16-4399-1996, and the safety of its use by conducting dermal acute irritation test.
The dermalacute irritation test was performed by Draize test method on white rats (Rattus norvegicus) malesprague-dawley strain. The results of the study show that the most optimum scrub cream products based on
panelist preferences level is scrub cream with the addition of 4.5% moringa seed with a score of 5.67.
Formulation scrub cream with the addition of 3.5; 4.5; and 5.5 % moringa seed qualify skin moisturizers
according to SNI 16-4399-1996 with pH value of 6.88-7.31; density 1 g/mL; emulsion stability of 95.1996.61%; and negative microbial contamination. The three formulations of moringa seed scrub cream also do notgive skin irritation effect to test animals at 24 and 48 hours with primary dermal irritation index or PDII=0.
Keywords: Body scrub cream, Bioseed, Draize test, Moringa oleifera, Cosmetics

product used for other skin care is scrub cream.
Based on the content of vitamins, minerals, andhigh antioxidant content in moringa seeds,
researchers have an interest in using moringa seed
powder as an active component of skin abrasive andalso as a nutritional addition to cream scrub. The
effort to add moringa seed powder in scrub creamhas never been done before. Scrub cream is made byvarying the concentration of moringa seed powder
3,5; 4,5; and 5.5%, followed by organoleptic test by
30 panelists and characterization test (pH analysis,
emulsion stability, species weight, and total
microbial contamination) in accordance with thequality standard of National Standardization Body
1996. Body scrub cream fulfill the quality
requirement of Agency National Standardization
1996 followed by dermal acute irritation test.
The content of the substances used for
production of scrub cream has the possibility tocause irritation to the skin, therefore to know thesafety of the use of cream scrubs on the skin, thenthis study conducted dermal acute irritation test [9].
This test uses the white rat rats (Rattus norvegicus)
Sprague-Dawley strain with the method Draize [10].
Draize method is done by observing the reaction oferythema and edema in the skin that occurs after
cream scrub products applied to the skin of test
animals for 24 hours and 48 hours.

INTRODUCTION
Moringa seeds produce oil commercially known
as the behen oil. The oil is widely used in beauty
products because it has a high antioxidant content
with an IC50 value of 91.13 μg/mL [1] – [2].
Moringa seeds are also known to have nutrients suchas vitamins and minerals that are beneficial to skinhealth. Compaore et al [3] states that moringa
contains high enough minerals such as calcium,
copper, phosphorus, zinc, magnesium, manganese,potassium and sodium. Mineral content of calcium,
sulfur, magnesium, and potassium can lift dead skincells (exfoliator) and nourish the skin so the skinfeels soft and smooth [4]. Moringa seeds are rich invitamins B1, B2, B3, C, and E [5]. Vitamin B1, B2,
B3 are known to have a role in maintaining skinmoisture and brightening the skin [4].
Burlando et al. [6] states that moringa seeds havepotential as raw materials in cosmetic because they
have a high nutrient content that is beneficial to theskin. Cosmetics has now become a necessity that is
considered important for some people. Various typesof cosmetic products are used for skin care in order
to appear more attractive. Ojiako and Okeke [7]utilize high antioxidant content in moringa seed oil
in body lotion, while Duraivel et al. [8] utilizes
moringa seed oil in an anti-wrinkle cream. Cosmetic

95

SEE - Nagoya, Japan, Nov.12-14, 2018

powder respectively 0; 3.5; 4.5; and 5.5% (w / w) of
the dough weight.

METHODTime and Place of Implementation

Table 1 The basic formula of cream
The research was conducted in January until
September 2017 in Chemical Laboratory, Central
Integrated Laboratory (PLT), Syarif HidayatullahState Islamic University Jakarta and Laboratory
Animal Laboratory Unit (UPHL), Faculty of
Veterinary Medicine, Bogor Agricultural University.

Material
Glycerin
Stearic acid
Cetyl alcohol
Trietanolamine
Isopropyl misle
Propylparabene
Fragnance
Distilled water, up to

Tools and Materials
The tool used in this research is oven
(Memmert), analytical scale (Ohaus), pH meter(Martini MI 150), incubator (Lequeux), bath
(Heidolph MR 3001 K), micro tube (Eppendorf),
petri dish (Pyrex ), vortex mixer (Thermolyne M
16700 Maxi), micropipet (Socorex), filter paper 0.45
μm (Whattman), thermometer (Boeco), magnetic
stirrer, spiritus, stopwatch, glassware, organoleptic
test equipment, sterile gauze (DRC) hypoallergenic
plaster (Mikropore), and hair shaver (Wahl).
The materials used in this study were Moringa
oleifera samples obtained from Pamulang, Ciputat,
South Tangerang, stearic acid, cetyl alcohol,
triethanolamine, glycerin, methyl paraben, propyl
paraben, isopropyl mericate (BratacoChemika),fragrance , aquadest, commercial cream scrubs forcomparison, sterile NaCl, plate count agar, andwhite rat test animals (Rattus norvegicus) SpragueDawley strains of male sex with age 2-3 months andweight 200-250 grams (UPHL FKH IPB). Approvalof ethical review for experimental animals (rats) inthis study was obtained from Animal Ethics
Committee, Faculty of Veterinary Medicine, Bogor
Agricultural University, with number 076 / KEH /SKE / XI / 2017.

Weight(gram)
15
12
4
3
2
0,02
0,2
100

The method of making moringa seed creamscrub is as follows stearic acid and cetyl alcohol
which is the oil phase mixed and melted in porcelain
cup until it reaches 70 °C above water bath, after aperfect melt the temperature is lowered to 65 °C thenfed into a cup of trophies and then added propyl
paraben and isopropyl impregnate into the oil phasemixture while stirring until homogeneous (Dough 1).
Glycerin and water which is a water phase mixed
and heated to temperature 80°C in different
containers and then cooled to a temperature of 65 °C
while slowly incorporating triethanolamine (Dough
2). Dough 1 and 2 are mixed while stirring until afine cream emulsion (dough 3) is formed. Dough 3
is allowed until the temperature drops to 40 °C.
Moringa flower dust and powder with concentration
variation (b/b) is added while continuous stirring. A
cold cream scrub is inserted into a plastic bottle.
Organoleptic test scrubs cream [14]Procedures
Organoleptic test conducted on herbal cream
products include: color, aroma, consistency, texture,and overall product acceptance. Sample used include
Moringa seed cream scrub and cream scrubs on themarket (commercial). Panelists who conducted theorganoleptic test were 30 untrained panelists. The
result of organoleptic test was processed bystatistical method using SPSS application with one
way Anova test method.

Preparation of moringa seed [11]Moringa selected fruit that is dark brown thentaken the seeds. Seeds selected moringa good quality(has a round and whole shape dry) then the seeds
moringa peeled skin. The contents of moringa seeds
are dried with oven at 60 oC for 1 hour. The content
of moringa seeds was then smoothed using a blenderand sieved with a particle size filter of 595-420 μm
according to Yuliati and Binarjoresearch [12].

Characterization scrubs cream

Formula scrubs cream [13]Analysis of the scrub cream produced include
analysis of pH [15], the stability of the emulsion[15], the specific gravity [16] and total microbial
contamination [17]. As a comparison used

The preparation of a cream base is carried out
according to the composition of the formula shownin Table 1. F0; F1; F2; F3 is a cream scrub
formulation with the addition of moringa seed96

SEE - Nagoya, Japan, Nov.12-14, 2018

commercial
cream
scrubs.
Scrub
creamcharacterization test results processed with statisticalmethods using SPSS with one way ANOVA test
method.

Table 2 Organoleptic test results of scrubs cream

Dermal Acute irritation scrusb cream [10] – [18]

Color
Aroma
Viscosity
TextureGeneralParameter

The number of rats required for each group isdetermined by Federer's (n-1) (t-1) ≥15, where t
represents the number of treatments and n is thenumber of replications. This research has 6
treatments to get the number of rats each treatment 4
mouse (value n≥4). Samples tested were cream base,
3 moringa cream seed scrub; 4,5; 5.5%. The normal
control treatment is mice without treatment.
The acclimatized mice for 14 days had theirheads shaved with an electric razor on the back withan area of 3x3 cm until cleaned up before the sample
application. The shaving is done carefully so as not
to injure the rats' backs. The test material is applied
to the back of the mice that has been shaved hair of
0.3 grams per head, then covered with sterile gauze
and glued with hypoallergic plaster. The rats werethen placed and left in individual cages. The plasterand sterile gauze are opened and the test area rinsed
with water after 24 hours. Observation on mouseskin was done after 40 minutes of plaster and thesterile gauze was opened and then scoring oferythema and edema formed based on Draize
Method. Observations continued at 48 hours after
treatment (mice smeared test material).

0.000
0.434
0.001
0.000
0.000

Based on statistical test results using one-way
Anova, there are significant differences in the color
preferences level of each treatment is indicated by aprobability value of 0.000 (P <0.05). According toDiana and Thaman[19] color formed on the productis affected by the color of its constituent materials.
Moringa seed powder that is added to the formula
was instrumental in giving color to the product.
Moringa seed powder has a brownish yellow color.
The more moringa seed powder added then the colorof cream scrubs formed will be more brown.

Aroma

Here is the result of organoleptic test scrub
cream produced in this study.

F1

Anova
results

Color

Organoleptic Test Scrubs Cream

KK

KK
5.12
5.20
4.57
5.67
6.03

Noted: F0 = formulation scrub cream without addition ofmoringa seed scrub, F1 = formulation scrub cream withaddition of 3.5% (w / w) moringa scrub, F2 = formulation
scrub cream with addition of 4.5% (b / w) moringa scrub,
F3 = formulation scrub cream with addition of 5.5%(w/w) Moringa scrub, KK = commercial scrub cream .

RESULT AND DISCUSSION

F0

F0
5.90
5.10
4.10
3.57
2.60

Treatment
F1
F2
F3
5.20 4.00 4.03
5.43 5.53 5.63
4.40 5.67 4.27
4.73 5.30 4.90
4.93 5.67 4.33

F2

The smell of cream scrub products is influenced
by the ingredients. The most influential ingredientsgive the flavor of Moringa seed powder, so it isadded fragrance to the formula to reduce the aroma
from the sample of moringa. The scent produced bycream scrub depends on the concentration of themoringa seed powder. The more moringa seed
powder added to the formula the stronger the aroma.
Based on the organoleptic test, the highest scores
were obtained in F3 cream scrub with a score of 5.63
followed by cream scrub F2; F1; LK; and F0 with ascore of 5.53; 5.43; 5.20; and 5.10.
Based on statistical test results using one-way
Anova, there is no significant difference in aroma
preferences level of each treatment which is shownwith probability value of 0.434 (P> 0.05). Thissuggests that the addition of moringa seed powder inthe cream formula does not affect the panelist'spreference level. This is because the panelists who
conduct the assessment are panelists who are nottrained so as not to be sensitive to the aroma of the
products produced.

F3

The results of color organoleptic test showedthat the highest panelist's favorite level was on thecream formula without the addition of Moringa seed
powder (K0%) of 5.9. Formula cream without
Moringa seed dust has a typical white cream scrubcolor. This indicates that the panelists prefer acreamy white scrub. Cream formula with theaddition of moringa seed powder 3.5; 4.5; 5.5% (w/w) respectively decreased favor rate by 5.20; 4.50;
and 4.03. This indicates that the more concentrated
the color of herbal cream scrubs the panelist'sfavorite level decreases.

97

SEE - Nagoya, Japan, Nov.12-14, 2018

Viscosityseeds. This proves that moringa seeds capable ofaffecting the acidity of the cream product. Creamformula with addition of 3.5; 4,5; 5.5% (b / b) ofmoringa seeds increased pH value compared withcream formula without moringa seed powder due tomoringa seed powder is base with pH value of 7.55.5.

Based on the results of organoleptic test, themost preferred scrub cream by the panelists is theformula scrub cream with the addition of 4.5 moleseed (F2) with an average score of 5.67. The resultof statistical test using one-way anova shows that
there is significant (mean) difference between theviscosity favorite level of each treatment. It is shownwith the probability value of 0.001 (P <0.05).
Generally panelists prefer a product scrub
cream that is not too thick. The more moringa seed
powder added to the formula will make the more
thickness of the scrub cream. Likewise, when theless the Moringa seed powder, will be shaped lessscrub and look watery. This is because Moringa
seeds have stearic acid content of 12.62% [20].
Stearic acid is an emulsion stabilizer and a
thickening agent which is useful in forming athickened or semi-solid (cream) [21].

Table 3 Characteristics of scrubs cream
Parameter

Based on organoleptic tests, scrub cream F2
with a score of 5.3 is more preferable to scrub creamF3 and F1 with a score of 4.9 and 4.73. Based on
statistical test results using one-way Anova, there issignificant difference in texture preferences level ofeach treatment is indicated by probability value of
0,000 (P <0.05). This suggests that the addition ofmoringa seed powder in the cream formula affects
the panelist's preference level. This is due to theincreasing percentage of scrub increase the friction
power contained in the product with the skin so it iseasier to remove dead skin cells and impurities in theskin. The scrub grinder also serves as a massaging
effect on the body. The percentage of good scrubs
ranges from 34% of the cream scrub weights
because the amount is ideal for stimulating
exfoliation of skin epidermis. Percentage of scrub
above 5% will damage skin tissue and make skin dry
[22].

6,8
8

7,12

7,22

7,45

7,31

Specific
gravity(g/mL)

1,0
0

1,00

1,00

1,00

1,00

0,951,05

Stability ofemulsion
(%)

95,
1

95,3

95,4

95,8

96,0

-

Nol

Nol

Nol

Nol

Nol

Max
102

Total
microbial
contaminan(colony/ g)

KK

SNI

F1

pH

TextureTreatment
F2
F3

F0

4,5-8

Specific gravity

Results of Scrubs Cream Characteristics

The test results scrub cream characteristics
indicate that the value of specific gravity is still
within the range of quality requirements SNI 164399-1996 with the average value of a specificgravity of 1 g/ mL. This means that the resulting
scrub cream product has a good level of stability.
The result of stastistic test with one-way Anova
showed that scrub cream F0 with F1; F2; F3; andLK did not show any significant difference. This
proves that with the addition of moringa seed
powder does not affect the specific gravity of acream product.

The following is the result of characteristic testof scrub cream produced in this research.

Stability of emulsion
The test results of cream scrub characteristics
showed that the average emulsion stability value
reached 95.19 - 96.01%. These results indicate thatthe sample hardly indicates a phase separation or avery small phase separation indicating that the cream
product has a stable emulsion. The result of
statistical test with one-way Anova showed nosignificant difference, probability value 0.453 (P>0,05). This indicates that moringa seed powder tend
not affect the stability of the emulsion on a scrub
cream products.

pH value
The result of pH analysis of scrub cream producteach treatment has pH value which is still in therange of quality requirement according to SNI 164399-1996, that is with pH value range 6,88-7,45.
Based on statistical test results with one-way anova
showed a significant difference in the four samples.
The pH value on the Moringa seed cream scrub
product increased when compared with the scrub
cream product without the addition of moringa

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SEE - Nagoya, Japan, Nov.12-14, 2018

Total microbial contamination

Some components in cosmetics can potentially
irritate the skin such as preservatives (antimicrobial
substances), surfactants, fragrances, and dyes [25].
Scrub cream products in this study using commercial
preservatives are methyl and propyl paraben. The
JECFA (Joint FAO / WHO Expert Committee on
Food Additives) [26] in 1990 stated that methyl andpropyl paraben had an ADI (Acceptable Daily
Intake) value of 0-10 mg / kg body weight, while
methyl and propyl paraben toxicity data in miceorally is 0.5-2 g / 250 grams of body weight. This
study used methyl paraben as much as 0.2 gram andpropyl paraben as much as 0.02 gram which is stillin safe range according to JECFA guideline. The
study also used cetyl alcohol, stearic acid, andtriethanolamine

The result of characteristic test of total microbial
contamination to cream scrub product showed thatmicroorganisms contained in the four negative
products. This is due to the addition of propyl
paraben and methyl paraben formula scrub cream
products. Propyl and methyl paraben is apreservative that can prevent the growth of bacteria
and fungi. Moringa seed is also able to optimize theprevention of microbial contamination in cream
product samples in addition. This is because
Moringa seeds contain active compounds of seeds
that are antimicrobial, including saponins, tannins,
flavonoids, and alkaloids. Moringa seed active
compounds work by inhibiting protein synthesis anddestroying bacterial cell membranes so as to be
antimicrobial [23].

CONCLUSION

Test Result Dermal Acute Scrub Cream

Based on the research that has been done can beconcluded: The most optimum scrub cream
formulation is scrub cream with the addition of 4.5%
moringa seed which has the highest general favorite
level with a score of 5.67. Characteristic of scrub
cream with addition of moringa seed 3,5; 4,5; and5.5% fulfill the standard that has been determined
SNI 16-4399-1996, that is with pH value 6.88-7,31;
weight of type 1 g/mL; emulsion stability of 95.1996,61%; and negative microbial contamination.
The irritation test results showed that the scrub
cream with the addition of moringa seed 3,5; 4,5;
5.5% and the base do not cause irritation effect on
the skin of white rat test animals (Rattus norvegicus)
with the value of primary skin irritation index (PDII)
equal to 0 that indicates scrub cream moringa seedsafe to use.

Based on the irritation test results (Table 3), noerythema and edema reaction in the skin of test
animals of any formula with the value of the primaryskin irritation index (PDII) was 0. If seen from thecategory of skin irritation index response then the
PDII value goes into the range 0-0,4 so that it can be
categorized as a material that does not irritate theskin. These results indicate that the scrub cream withthe addition of a moringa seed scrub 3.5; 4,5; 5.5%
and the base is safe to use. Test animal skin does notshow an erythema reaction and edema is probably
caused by the resulting moringa seed cream scrub
having a pH still in the range of SNI 16-4399-1996
quality requirements so that its use does not cause
irritation. According to Tranggono and Fatmah [24],pH is one of the things that can trigger theoccurrence of side effects on the skin such as
erythema and edema.

ACKNOWLEDGEMENTS
This research was supported by Centre for Researchand Publication of UIN Jakarta. The authors would
like to thank for helpful supports.

Table 4. Primary irritation test results of moringa
seed scrub cream on Sprague-Dawley's white rats
skin

REFERENCES
24th hours

48th Hours

Treatment
F0
F1
F2
F3
KK
KN

PDII
Erythema

Edema

Erythema

Edema

0
0
0
0
0
0

0
0
0
0
0
0

0
0
0
0
0
0

0
0
0
0
0
0

[1] Ogbunug H.A., Uneh. F.U., Ozumba A. N.,
Ezikpe O., IgwiloI. O., Adenekan S.O., andOnyekwelu O.A, Physico-chemical andAntioxidant Properties of Moringa oleifera
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[3] Compaore W.R., Nikiema P.A., Bassole H. I.,
Savadogo A., Mouecoucou J., Hounhouigan D.
J., and Traore S.A, Chemical Composition and

0
0
0
0
0
0

Note: F0 = rat smeared cream formula without addition ofmoringa seed scrub, F1 = rat smeared cream formula withaddition of 3.5% (b/ w) moringa seed scrub, F2 = rat smeared
cream formula with addition of 4.5% (w / w) moringa seed scrub,
F3 = rat smeared cream formula with addition of 5,5% (b/b)
moringa seed scrub, KK = rat smeared cream of commercial
cream, KN = untreated rat.

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SEE - Nagoya, Japan, Nov.12-14, 2018

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[5] Gopalakrishnan L., Doriya K., dan Kumar D.,
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[7] Ojiako EN. And Okeke C. 2013. Determinationof Antioxidant of Moringa oleifera Seed Oil and
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[11] Hendrawati, Rohaeti E., Effendi H., andDarusman L. K., Characterization of PhysicoChemical Properties of Nano-Sized Moringa
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[14] Badan Standarisasi Nasional BSN, SNI 012346-2006 Petunjuk Pengujian Organoleptik
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[19] Diana Z. D. and Thaman A, Cosmetic
Formulation Skin Care Products, Taylor andFrancis Group, 2006.
[20] Ijarotimi O., Oluwole A., and Oluwaseun A.,
Comparative Study on Nutrient Composition,
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oleifera Seed Flour, Food ScienceandNutrition,
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[21] Rowe R.C., Sheskey P.J., and Owen, Handbookof Pharmaceutical Exipients, Pharmacetical
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[22] Lassen C., Hansen S. F., Magnusson K.,
Hartmann N. B., Rehne Jensen P., Nielsen T.
G., and Brinch A., Microplastics Scubber in
Cosmetic Products, Danish Environmental
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[23] Buckle K. A., Edwards R. A., Fleet G. H.,
andWotton M, Ilmu Pangan,
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[24] Tranggono R.I. and Fatma L., Buku Pegangan
ilmu Pengetahuan Kosmetik, PT. Gramedia
Pustaka Utama, 2007[25] Barrel A.O., Paye M., Maibach H.I., Handbookof Cosmetic Science and Technology, Informa
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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

COMPATIBLE ACTION GRAPH FOR FINITE CYCLIC GROUPS OF
p-POWER ORDER
Mohammed Khalid Shahoodh1, Mohd Sham Mohamad2, Yuhani Yusof3, Sahimel Azwal Sulaiman4 and
Nor Haniza Sarmin5
1,2,3,4Applied & Industrial Mathematics (AIMs) Research Cluster, Faculty of Industrial Sciences &Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak,
26300 Gambang, Kuantan, Pahang Darul Makmur, Malaysia
5
Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia,
81310 UTM Johor Bahru, Johor, Malaysia
ABSTRACTThe compatible actions are important in determining the nonabelian tensor product of groups. In this paper,
finite cyclic groups of p-power order, where p is an odd prime are considered. The purpose of the paper is tointroduce a new graph called the compatible action graph for the nonabelian tensor product for the finite cyclic
groups of p-power order, where p is an odd prime. Furthermore, some properties of the compatible action graphhave been studied.
Keywords: Cyclic Groups, Nonabelian Tensor Product, Compatible Actions, Number Theory, Graph Theory.

of 3-power order and they determined the exact
number of the compatible pairs of actions with theactions that have order one, order three and thehighest 3-power order.
Nowadays, there are many studies have been
considered the theoretical relationship between grouptheory and graph theory. The study of thisrelationship can establish graphs in different ways
based on the algebraic structures of the group or thesemigroup by using the properties of graph. For
example, Alireza et al. [7] investigated some resultson the power graphs of the finite groups, while
Kelarev and Quinn [8] defined the directed powergraph of the semigroups. Meanwhile, Mansoori, et al.
[9] defined the non-coprime graph associated to thegroup G, where the vertex set is G \{e} and two

INTRODUCTION
It is well-known that the compatible actions
played an important role in determining the
nonabelian tensor product of groups. The concept of
the nonabelian tensor product has been defined for apair of groups G and H that satisfy the compatibility
conditions. Recently, much attention has been given
to investigate the compatible actions and the
nonabelian tensor products. Bardakov andNeshchadim [1] studied the compatible actions byproviding some necessary conditions for thecompatibility of the actions. They have focused on thecase that for the given groups G and H such that G
acts on H, whether it is possible to define an action of
H on G such that this pair of the actions arecompatible. Moreover, Ellis and McDermott [2]investigated the compatible actions for two different
groups D4 and Q4 . They found that there are only

distinct vertices are adjacent connected by the edge
with the orders relatively the non-prime. They
determined the general properties of the non-coprime
graph, such as diameter, girth, connectivity,
Hamiltonian, independence number and domination
number. The conjugacy class graph of some finitegroups with its energy have been investigated by
Mahmoud et al. [10]. They computed the energy of
the conjugacy class graphs of the dihedral groups oforder 2n , then generalized quaternion groups oforder 4n and quasidihedral groups. Again, they
introduced the general formulas for the energy of the
conjugacy class graphs of those types of groups. In
this paper, a new graph namely compatible action
graph has been defined for the nonabelian tensor

292 compatible pairs of actions between D4 ⊗ Q4 .
Visscher [3] gave a complete conditions for theactions to be compatible for the finite cyclic groupsof p-power order when one of the actions is trivial orboth actions are trivial. Furthermore, Mohamad [4]used the order of the action as a condition and provide
new necessary and sufficient conditions for the pairof finite cyclic groups of p-power order acts
compatibly on each other. Meanwhile, Sulaiman et al.
[5] studied the compatible pairs of actions for finite
cyclic groups of 2-power order. They determined theexact number of compatible pairs of actions that canbe identified between the nonabelian tensor productfor two finite cyclic groups of 2-power order. In
addition, Shahoodh et al. [6] investigated thecompatible pairs of actions for the finite cyclic groups
101

SEE - Nagoya, Japan, Nov.12-14, 2018

The following theorem stated the compatibility forthe pair of the actions that have p-power order for thetwo finite cyclic groups of p-power order, where p is
an odd prime.

product for the finite cyclic groups of the p-power
order where p is an odd prime. Furthermore, thisgraph is denoted by ΓCp α ⊗C β , then some properties ofppthis graph have been studied.
This paper is organized as follows. In Section
Two, some preparatory results and definitions on thecompatible pairs of actions and automorphism groupof such type of groups are given with somefundamental concepts of graph theory that are neededin this research. While, the main results of this paper
are presented in Section 3. Lastly, the conclusions of
this paper are given in Section 5.

Theorem 2[4]
Let =
G

=
k 1, 2,..., α − 1 and σ ′ ∈ Aut( H )σ = p k , where=k ′ 1, 2,..., β − 1. Then (σ , σ ′)with σ ′ = p k ′ whereis a compatible pair of actions if and only if
k + k ′ ≤ min {α , β } .

This section contains some of the definitions andprevious results on the automorphism group and thecompatible actions for the finite cyclic groups of the
p-power order, where p is an odd prime with somefundamental concepts on the graph theory. We started
with the definition of the compatible actions which is
given as follows.

The next theorem gives the exact number of thecompatible pairs of actions that can be identified
between the nonabelian tensor product of two finite
cyclic groups of p-power order where p is an odd
prime.
Theorem 3 [13]Let G ≅ C pα and H ≅ C p β be finite cyclic groups ofDefinition 1 [11]Let G and H be the groups, which act on each otherand each of which acts on itself by conjugation. Thesemutual actions are said to be compatible ifg−1

g = g ( h ( g g ′)) andg , g ′ ∈ G and h, h′ ∈ H .

( g) ′hh ≅ C p β be groups suchthat α , β ≥ 3. Furthermore, let σ ∈ Aut(G ) withTHE PREPARATORY RESULTS( h) ′g ≅ C pα and =H

p-powerorderwith α , β ≥ 3. Then, there exist−1h = h ( g ( h h′)) for allcompatible pairs of actions whenand=k 1, 2,...,α − 1=r min {α , β } − k .

The automorphism group of the finite cyclic
group of p-power order is an isomorphic with a direct
product of two finite cyclic groups as stated infollowing theorem.

Next, the following proposition gives the numberof the compatible pairs of actions when one of theactions is trivial.

Theorem 1 [12]Let p be an odd prime and α ∈  . If G is a cyclic
group of order p , then

Proposition 1[ 13]
Let G ≅ C pα and H ≅ C p β be finite cyclic groups ofAut(G ) ≅ C p −1 × C pα −1 ≅ C( p −1) pα −1 andthe p-power order. Furthermore, let ρ ∈ Aut(G ) withα

ρ = 1 and α , β ≥ 1. Then, the number of theAut(G=) ϕ ( pα=
) ( p − 1) pα −1 .

compatible pairs of actions is ( p − 1) p
The following corollary showed that when G isabelian, then the trivial action is always compatible
with any other action.

β −1

.

The next proposition presented the number of thecompatible pairs of actions for every value of k where=
k 1, 2,..., α − 1.

Corollary 3.1 [3]Let G and H be groups. Furthermore, let G act
trivially on H. If G is abelian, then for any action of
H on G, the mutual actions are compatible.

Proposition 2[13]Let G ≅ C pα and H ≅ C p β be finite cyclic groups of
p-power order where p is an odd prime such thatα , β ≥ 3. Furthermore, let ρ ∈ Aut(G ) with ρ = p k

102

SEE - Nagoya, Japan, Nov.12-14, 2018=
k 1, 2,..., α − 1. Then, the number of thewherecompatible pairs of actions ispresented. The compatible action graph for the
nonabelian tensor product for the finite cyclic groupsof the p-power order, where p is an odd prime are
introduced. Furthermore, some properties ofcompatible action graph have been investigated. We
started with the definition of compatible action graphwhich is given as follows.

r( p − 1) p k −1 + ( p − 1) p k −1 ∑ ( p − 1) p i −1
i =1=
where r min {α , β } − k=and k 1, 2,..., α − 1.
Next, some definitions and fundamental conceptsof graph theory that are needed in this research arepresented as follows. These fundamental concepts
with the definitions can be found in [14].

Definition 3.1
Let G and H be two finite cyclic groups of p-power
order with p an odd prime. Furthermore, let ( ρ , ρ ′)A graph G is a mathematical structure consistingof two sets, the set of the vertices and the set of theedges which are denoted by V (G ) and E (G )be a pair of the compatible actions for the nonabeliantensor product of G ⊗ H , where ρ ∈ Aut(G ) andrespectively. Then, the order of the graph G is thenumber of the vertices in the graph G which isdenoted by V (G ) . In addition, the graph G is called( E (Γ

ρ ′ ∈ Aut(H ).

ΓCp α ⊗C β =(V (ΓCp α ⊗C β ),

Then,

p

p
C α ⊗C β
p

p

p

p

)) is a compatible action graph with thep

set of vertices V (ΓCp α ⊗C β ) , which is the set ofpconnected graph if there is a path between every pairof distinct vertices. Moreover, the graph G is said tobe complete if each ordered pair of the vertices are
adjacent to each other. Then, a simple graph G is said
to be bipartite graph if its vertex set can be partitioned
into two disjoint sets V1 and V2 such that every edgep

Aut(G ) and Aut(H ) , and the set of edges,

E (ΓCp α ⊗C β ) that connects these vertices which is thepp

set of all compatible pairs of actions ( ρ , ρ ′).
Furthermore, two vertices ρ and ρ ′ are adjacent if
they are compatible.

in the graph G connects vertex in V1 and vertex inV2 , and there is no edge in the graph G connects

The order of the graph G is defined as the numberof the vertices in the graph G, which is denoted by
V (G ) . Thus, the order of the compatible action
graph has been determined and is denoted byeither two vertices in V1 or two vertices in V2 .
Additionally, the graph which consists of the setof vertices and the set of directed edges, is called the
directed graph such that the directed edges areassociated with the ordered pair (u , v) is said to start

V (ΓCp α ⊗C β ) . The order of the compatible actionppgraph has been considered into two cases whenHence, the order of theG ≠ H and G = H .
compatible action graph is presented in the following
proposition.

at u and end at v, where u , v ∈ V . Furthermore, in the
directed graph, the degree of the vertex v has two
types, the out-degree and the in-degree. The outdegree is denoted by deg + (v) which is the number of

Proposition 3.1
Let G ≅ C pα and H ≅ C p β be the finite cyclic groups

the edges with v as their initial vertex, while the indegree is the number of the edges with v as theirterminal vertex which is denoted by deg − (v). For theof p-power order where p is an odd prime andα , β ≥ 3. Then, the order of the compatible action

directed graph G, the path of the length n from u to v,
where n is positive integer, is defined as a sequence(i) V (ΓCp α ⊗C β ) =( p − 1)( pα −1 + p β −1 ) if G ≠ H .

graph ispof edges e1 , e2 ,..., en of G such that e1 is associatedp(ii) V (ΓCp α ⊗C β ) =( p − 1) pα −1 if G = H .

with ( x0 , x1 ), e2 is associated with ( x1 , x2 ) and so on,pwith en is associated with ( xn −1 , xn ), where x0 = upProof:
From the definition of the order of the graph, the orderof the compatible action graph is the number of thevertices in V (ΓCp α ⊗C β ). Furthermore, by Definition

and x1 = v.
MAIN RESULTSp

3.1, V (ΓIn this section, our main results of this paper arep
C α ⊗C β
p

103

p

p

) is the nonempty set of Aut(G ) andSEE - Nagoya, Japan, Nov.12-14, 2018

Aut(H ). Thus, there are two cases needed to beconsidered, which are G ≠ H and G = H .
Case I: Suppose that G ≠ H . Then,
V (ΓCp α ⊗C β ) = Aut(G ) + Aut(H )pp5= ( p − 1) pα −1 + ( p − 1) p β −1
( p − 1)( pα −1 + p β −1 ).
=Case II: Suppose that G = H . Without loss ofgenerality, let α be the order where α = β , thenV (ΓCp α ⊗C β ) =Aut(G ) =( p − 1) pα −1 .
pΓp
C α ⊗C βp

Therefore,7p=( p − 1)( p

α −1

+p

β −1

) when G ≠ H andpΓCp α ⊗C β =( p − 1) pα −1 when G = H .
p

3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3

7
8
9
3
4
5
6
7
8
9
3
4
5
6
7
8
9

1494
4410
13158
300
700
2700
12700
62700
3127001562700
882
2646
14994
101430706482494184634589394p

Since the compatible action graph has been
considered as a directed graph, then the compatible
pairs of actions ( ρ , ρ ′) is defined as a directed edge

Since the action of the group G on the group H is
the mapping Φ : G → Aut(H ), then the compatible
action graph of the finite cyclic groups of the p-power
order is considered as a directed graph. Thus, thecardinality of the edges of the compatible action
graph for such type of groups are presented in thefollowing proposition.

of the compatible action graph. Therefore, according
to the definition of the directed graph, the vertex ρis considered as an initial vertex of ( ρ , ρ ′) and ρ ′ isthe terminal vertex of ( ρ , ρ ′). Furthermore, the outdegree of the vertex v in the directed graph is denotedby deg + (v), where it needs to be found in order to

Proposition 3.2
Let G ≅ C pα and H ≅ C p β be the finite cyclic groups

investigate the number of the edges in the graph.
Thus, in the following proposition the out-degree forthe given vertex ρ in the compatible action graph isof p-power order where p is an odd prime andα , β ≥ 3. Then,
E (ΓCp α ⊗C β ) =presented.

α −1
 α −1 r
( p − 1) p β −1 + ∑ ( p − 1) p k −1 1 + ∑∑ ( p − 1) p i −1 ,k 1=
 =k 1 =i 1
Proposition 3.3pp=
where r min {α , β } − k=and k 1, 2,..., α − 1.

Let G ≅ C pα and H ≅ C p β be the finite cyclic groups

Proof:of the p-power order where p is an odd prime andα , β ≥ 3. Furthermore, let v ∈ V (ΓCp α ⊗C β ) where

It follows from Definition 3.1 and Theorem 3.

pv ∈ Aut(G ) and v = p . Then deg (v) is one of theTable 1 is given as some examples for the
cardinality of the edges for ΓCp α ⊗C β with the same

following:prime p and α , β ∈  .

(i) ( p − 1) p β −1 if k = 0.

Table 1 Cardinality of the edges for ΓCp α ⊗C β .

(ii) ( p − 1) p k −1 + ( p − 1) p k −1 ∑ ( p − 1) p i −1 ,

p

p

+

k

p

r

p

p

α

β

with r = min {α , β } −=k if k 1, 2,..., α − 1.
E (ΓCp α ⊗C β )
p

3

3
3
3
3

3
4
5
6

i =1

p

Proof:
It follows from Propositions 1 and 2

p

54
90
198
522



From Theorem 2, the actions that have the ppower order are always compatible when
104

SEE - Nagoya, Japan, Nov.12-14, 2018

k + k ′ ≤ min{α , β }. Thus, we conclude in the

The next proposition shows that the compatible
action graph is a bipartite graph when G ≠ H .

following corollary that the out-degree and the indegree for the compatible action graph are the same.

Proposition 3.5
Let G ≅ C pα and H ≅ C p β be two finite cyclic groups

Corollary 3.1
Let G and H be the finite cyclic groups of the p-power
order where p is an odd prime and v ∈ V (ΓCp α ⊗C β ) .
pThen, deg − (v) = deg + (v) for Γ Cp

of p-power order where p is an odd prime such thatα , β ≥ 3. Then, Γ Cp α ⊗C β is the bipartite graph if andpp

α ⊗C βp.

only if G ≠ H .
Proof:Let G ≅ C pα and H ≅ C p β be two finite cyclic groupsp

Proof:
From

Propositionsv ∈ V (ΓpC α ⊗C β
p

3.3,

for

any

vertex) where v ∈ Aut(G ) andv = pk ,whenof p-power order where p is an odd prime such thatα , β ≥ 3. First need to show that if the compatiblepwe have deg + (v=) ( p − 1) p β −1

if

k = 0,=
k 1, 2,..., α − 1,andaction graph ΓCp α ⊗C β is a bipartite graph thenthen

G ≠ H . By contradiction method, assume that
G = H , then Aut(G) = Aut(H). Thus, there exists apr

deg + (v) = ( p − 1) p k −1 + ( p − 1) p k −1 ∑ ( p − 1) p i −1 ,where r = min {α , β } − k . By Theorem 2, the actionsG ≠ H.

are compatible when k + k ′ ≤ min{α , β }, which

Next, if G ≠ H then any v ∈ Aut(G) only
compatible with some v′ ∈ Aut(H). Thus, clearly it
can be partitioned into two disjoint sets Aut(G) andAut(H) respectively. Therefore, ΓCp α ⊗C β is apresent that the vertices are adjacent. Similarly, whenv = pk′ .

andTherefore,deg − (v) = deg + (v) for Γ Cp ⊗C .
pα



pβ

p

loop which cannot be partitioned into two disjoint
sets, which contradicts on the assumption. Thus,

i =1v ∈ Aut(H )

p

p

p



bipartite graph.
Next, the connectivity of the compatible action
graph is studied. The next proposition presented theconnectivity of the compatible action graph.

The complete graph K n contains exactly oneedge between each pair of the vertices. As a result, thecompatible action graph is not a complete graph. This
result is given as follows.

Proposition 3.4
Let G ≅ C pα and H ≅ C p β be the finite cyclic groups

Proposition 3.6of the p-power order where p is an odd prime suchthat α , β ≥ 3. Then, Γ C ⊗C
p

pα

pβ

is a connected graph.

Let G ≅ C pα and H ≅ C p β be the finite cyclic

Proof:Let G ≅ C pα and H ≅ C p β be the finite cyclic groups

groups of the p-power order where p is an odd primeand α , β ≥ 3. Then, Γ Cp ⊗C
pαof the p-power order where p is an odd prime suchthat α , β ≥ 3. Furthermore, let v1 ∈ V (ΓCp α ⊗C β )p

Proof:
By Proposition 3.1, there are ( p − 1)( pα −1 + p β −1 )pwith v1 ∈ Aut(G ) and v1 is trivial action. By+

Proposition 3.3, deg (v1=
) ( p − 1) p

β −1

. Similarly, if

completeexist

graph,

then

p

there

E (ΓCp α ⊗C β ) =
p

p

p

α −1
 α −1 r
( p − 1) p β −1 + ∑ ( p − 1) p k −1 1 + ∑∑ ( p − 1) p i −1  ≤=k 1
 =k 1 =i 12

( p − 1)( pα −1 + p β −1 )  .

105

a

p

( p − 1)( pα −1 + p β −1 )  edges. By Proposition 3.2,

pcompatible with every v ∈ Aut(G ). Thus, ΓCp α ⊗C β
is a connected graph.

is

p

2

and v2 is trivial action, then by Corollary 3.1, v2 ispnumber of vertex in ΓCp α ⊗C β . If ΓCp α ⊗C βpwe have v2 ∈ V (ΓCp α ⊗C β ) such that v2 ∈ Aut(H )pis not a complete graph.

pβSEE - Nagoya, Japan, Nov.12-14, 2018

Thus, ΓCp α ⊗C β is not a complete graph.
pOrder. International Journal of Simulation-Systems, Science & Technology, Vol. 18, Issue.
4, 2017.
[6] Shahoodh M. K., Mohamad S. M, Yusof Y. andSulaiman S, A., Number of Compatible Pair of
Actions for Finite Cyclic Groups of 3-Power
Order, International Journal of Simulation-Systems, Science & Technology, Vol. 18, Issue
4, 2017.
[7] Alireza D., Ahmad E., and Abbas J., Some
Results on the Power Graphs of Finite Groups.
ScienceAsia, Vol. 41, 2015, pp. 73-78.
[8] Kelarev A. V. and Quinn. S. J, Directed Graph
and Combinatorial Properties of Semigroups. J.
Algebra Vol. 251, 2002, pp. 16–26.
[9] Mansoori F., Erfanian A. and Tolue B., Noncoprime Graph of a Finite Group. In AIP
Conference Proceedings Vol. 1750, No. 1, 2016,
pp. 050017). AIP Publishing.
[10] Mahmoud R., Sarmin N. H. and Erfanian A., The
Conjugacy Class Graph of Some Finite Groups
and its Energy. Malaysian Journal of
Fundamental and Applied Sciences, Vol.
13,Issue. 4, 2017,pp.659-665.
[11] Brown R. and Loday J., Van Kampen Theorem
for Diagrams of Spaces. J. of Topology, Vol. 26,
Issue. 3,1987, pp. 311-335.
[12] Dummit D. and Foote R., Abstract Algebra. John
Wiley and Sons, USA., 2004, pp. 136-137.
[13] Shahoodh M. K., Mohamad S. M., Yusof Y. andSulaiman S. A., Number of Compatible Pair of
Actions for Finite Cyclic Groups of p-Power
Order, Jurnal Teknologi (Sciences andTechnology): Vol.80. 2018.
[14] Rosen K., Discrete Mathematics and Its
Applications. 7 Ed. McGraw-Hill. New York,2012, pp. 641-735.

p

CONCLUSION
In this paper, the compatible action graph has
been introduced for the nonabelian tensor product for
the finite cyclic groups of p-power order, where p is
an odd prime. Some properties of the compatible
action graph are studied, such as the cardinality of theedge, the order of the compatible action graph, andthe out-degree for the given vertex in this graph. As aresult, the compatible action graph is a connected andbipartite graph but it is not a complete graph. The
results can be extended by introducing the subgraphof the compatible actions graph. Then, the number ofthe edges and the order of the subgraph of compatible
action graph can be determined.
ACKNOWLEDGEMENTS
This research is supported by UMP research grant,
RDU1703265.
REFERENCES[1] Bardakov V. G., and Neshchadim M. V.,
Compatible Actions and Non-abelian Tensor
Products. arXiv preprint arXiv:1709.07708,
2017.
[2] Ellis G. and McDermott A., Tensor Products ofPrime Power Groups. J. Pure Applied Algebra.
Vol. 132, Issue. 2, 1998, pp.119-128.
[3] Visscher M, On the Non-abelian Tensor Productsof Groups, PhD Dissertation, State University of
New York, Binghamton, NY. 1998.
[4] Mohamad M. S., Compatibility Conditions andNon-abelian Tensor Products of Finite CyclicGroups of p-Power Order, PhD Dissertation,
Universiti Teknologi Malaysia, 2012.
[5] Sulaiman S. A., Mohamad S. M, Yusof Y. andShahoodh M. K., The Number of Compatible
Pair of Actions for Cyclic Groups of 2-Power

106

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

FRAGMENT-BASED DRUG DESIGN TO INHIBIT DNA
METHYLTRANSFERASE 1 (DNMT1) FOR BREAST CANCER THERAPY
Ade Hanna Natalia1, Ahmad Husein Alkaff1, Mutiara Saragih1, Ina Nur Istiqomah1, and Usman Sumo
Friend Tambunan1
1
Faculty of Mathematics and Natural Science, Universitas Indonesia, Indonesia

ABSTRACT
Breast cancer is the biggest cancer among women in the worldwide. The uncontrollably high DNA
Methyltransferase-1 (DNMT1) activity which leads to abnormal gene expression is one of the primary cause ofbreast cancer. Therefore, DNMT1 as an essential enzyme in epigenetic regulation is considered as a potential
therapeutic target for breast cancer treatment. In this research, the inhibitors of DNMT1 were designed throughfragment-based drug design. About 168,646 natural products from PubChem database were used as fragment
candidates. Initial screening based on toxicity and Lipinski’s Rule of Three by Osiris DataWarrior was performed
to obtain 2,601 favorable fragments. Pharmacophore-based rigid and flexible molecular docking simulation was
employed with DNMT1 as the target protein. The selected fragments from docking simulation underwent fragment
linking modification and second toxicity screening, generating 23 ligands. Subsequently, the newly designed
ligands were subjected to pharmacophore-based flexible molecular docking simulation. Two ligands, HAMI_9
and HAMI_14, with Gibbs free binding energy of -11.6095 and -11.5904 kcal/mol, respectively, are considered
as a promising inhibitor of DNMT1. The pharmacological properties of the ligands were analyzed using Osiris
DataWarrior, Toxtree, SwissADME, admetSAR, and Molinspiration. The ligands show not only superior affinity
and molecular interaction to DNMT1 but also have advantageous pharmacological properties compared to thestandards. Additional in silico as well as in vivo experiments are needed to further assess the potency of HAMI_9
and HAMI_14 as drug candidates against breast cancer.
Keywords: Breast cancer, DNA methyltransferase, natural products, fragment-based drug design, moleculardocking simulation.

the S phase [5], [8]. The misregulation of DNMT1
initiates to hypermethylation in DNA promoter geneand hypomethylation which lead to the abnormal
growth of cancer cells [5]. In breast cancer, theDNMT1 is overexpressed; it has uncontrollably highactivity [8]. Therefore, the inhibition of the DNMT1
enzyme, which keeping its activity under control, is apromising method of epigenetic therapy for thetreatment of breast cancer [5], [6], [8].
The in silico method is one of the methods thatwidely used in drug discovery for various diseases.
The natural products have long been used by in silico
method for drugs discovery and development invarious diseases, such as cancer, because of its
pharmacological activity and bioavailability in livingorganisms [9]. The natural products can be used as
fragment library for lead compound discovery
through fragment-based drug design. The fragmentbased drug design is a method to construct the ligands
by linking, merging or growing the ligands fromsmall fragments to improve its interaction with target
protein binding site [10]. In this research, the natural
products are selected as the source of fragments
which then modified by fragment-based drug design
to inhibit DNMT1 protein. Thus, obtaining theinhibitor of DNMT1 for breast cancer therapy.

INTRODUCTION
Breast cancer is the biggest evidence of cancer
among women and the second prominent cause ofcancer mortality after lung cancer in the world [1],[2]. Breast cancer occurs due to genetic aberrationsuch as gene deletions, point mutations, chromosomal
rearrangements and epigenetic misregulation [1].
DNA methylation pattern guides epigenetic
regulation. DNA methylation plays an essential rolein the regulation of the gene expression and thestructure of chromatin, which leads to the
manifestation of diseases in humans, such as various
types of cancer [3]-[6].
DNA methylation pattern managed by the DNA
methyltransferase (DNMT) enzymes, which will
catalyze the transfer of methyl groups from SAdenosyl-L-Methionine (SAM) to the C5 position ofcytosine residues in CpG dinucleotides. DNMT in
human is classified into three families: DNMT1,
DNMT2, and DNMT3 [7].
DNMT1 is an enzyme composed of 1616 aminoacids in humans and is the ubiquitous
methyltransferase in humans. DNMT1 maintained
the methylation pattern of the DNA parent strand to
the new DNA daughter strand and expressed during

107

SEE - Nagoya, Japan, Nov.12-14, 2018

Lipinski’s Rule of Three using Osiris DataWarrior to
obtain favorable fragments that can be used formolecular docking [16], [17].
Afterward, all of the fragments underwent
preparation and energy minimization by MOE
2014.09 software with MMFF94x modified as aforcefield. Three ligands, namely S-Adenosyl-LMethionine (SAM), S-Adenosyl-L-Homocysteine(SAH), and sinefungin (SFG), were selected as
standard compounds for the experiment. Finally, thefragment library was stored in .mdb format.

METHODSIn silico method were used in this research toobtain the compounds that have high affinity andhave advantageous pharmacological properties. The
compounds through in silico method were used for
drug discovery in human disease, and the compounds
would be used to inhibit DNMT1 protein. In thisresearch, the in silico method were performed
through Molecular Operating Environment (MOE),
Osiris DataWarrior v04.07.02, Toxtree v2.6.13,
SwissADME, AdmetSAR, and Molinspiration
software.

Molecular Docking Simulation and Fragment
Linking Method

Preparation of DNMT1 Protein
The fragments underwent pharmacophore-based
rigid and flexible molecular docking with DNMT1
protein using MOE 2014.09 software with AMBER
10: EHT as the forcefield and R-field solvation. The
fragments were eliminated if their root-mean-squaredeviation (RMSD) value lower than 2.0 Å and havehigher Gibbs free binding energy (∆Gbinding) than thestandards.
Afterward, the fragments were linked todeveloping new ligands through fragment linking
method. Fragment linking is one of fragment-based
drug design method, the fragment linking method
applied to acquire compounds that have higher
affinity to bind with the pocket [18]. The new ligands
were acquired from the fragments that do not overlap
and have been linked. Afterward, the new ligands
were dockedwith DNMT1 protein bypharmacophore-based rigid and flexible moleculardocking using retain 100 through MOE 2014.09
software.

The three-dimensional (3D) structures of DNMT1
protein were acquired from RCSB Protein Data Bank
with PDB ID: 3AV5, 3AV6, 3SWR, 3PTA, and
4WXX. The DNMT1 proteins were acquired fromRCSB as one of protein structures source formolecular docking. Afterward, the protein structures
were prepared and optimized by protonation andenergy minimization using the LigX function in MOE
2014.09 with R-field solvation and AMBER 10: EHT
as a forcefield. Finally, the DNMT1 proteins werestored in .moe format.
Protein-Ligand Interaction Fingerprints (PLIF)
and Pharmacophore Selection of DNMT1 Protein
The pharmacophore construction of DNMT1
proteins was performed through PLIF method using
MOE 2014.09 software with Amber10: EHT as aforcefield, and R-field solvation. The PLIF method
used to determine interaction fingerprints between
ligand−protein based on surface contacts according to
the residues, hydrogen bonds, and ionic interactions[11]. Afterward, the proteins were performed
superpose to compare three-dimensional (3D)
structure of the protein and to superimpose the protein
structures that differ based on protein sequence, sizeor shape [12].
Afterward, the pharmacophore feature that
commonly applied in drug discovery were used in thisresearch [13]. The pharmacophore feature is used todetermine interaction site between the ligands andprotein target. Therefore, the molecules that
potentially trigger the desired biological effect wereobtained [14], [15]. The pharmacophore site wasstored in .ph4 format.

Analysis of Pharmacological Properties
The pharmacological properties of the best
ligands were analyzed through some software. The
tumorigenic, mutagenic, and drug-likeness properties
were identified by Osiris DataWarrior. The ligands
mutagenicity and carcinogenicity properties werepredicted by Toxtree software [19]. The
physicochemical, pharmacokinetics and druglikeness of ligands were evaluated by SwissADME(http://www.swissadme.ch/) [20]. The admetSAR(http://lmmd.ecust.edu.cn/admetsar1) used to predict
absorption, distribution, metabolism, excretion, andtoxicity (ADMET) properties of ligands [21]. The
bioactivity properties of ligands were analyzed
through Molinspiration software [22].

Preparation of The Fragments
RESULT AND DISCUSSION
The natural products from PubChem databasewere used as fragment library and were stored in sdf
format. The fragment library was screened based on
toxicity prediction test (tumorigenic, mutagenic,
irritant, reproductive effect predictions) andPreparation of DNMT1 Protein
The DNMT1 protein has responsibility for DNA
methylation and can lead as promising target for the108

SEE - Nagoya, Japan, Nov.12-14, 2018

treatment of breast cancer [7], [8]. The water, metal,
and unnecessary molecules in DNMT1 proteins fromRCSB Protein Data Bank were removed because can
influence interactions between the protein and ligand.
The binding site of DNMT1 protein can be
determined based on site finder feature in MOE
2014.09 software.

the calculated clogP of molecules are three [23]. Afterscreening by Osiris Data Warrior, there are 2,601
fragments obtained.
Molecular Docking Simulation and Fragment
Linking Method
The 2,601 fragments were docked with DNMT1
protein based on Acc and HydA pharmacophore site
and also based on Hyd and Don pharmacophore site.
The molecular docking simulation was performed
twice in rigid docking simulations using retain 30 in
the first simulation and retain 100 in the second
simulation with AMBER10: EHT as a forcefield.
After docked using retain 100, there are 11 ligands
based on Acc and HydA pharmacophore points, andalso there are 76 ligands based on Hyd and Don
pharmacophore site.
The linker between fragments was generated
through fragment linking; there are three ligands
which did not overlap and eligible to create linker.
About 31 ligands were acquired from the fragments
and the linkers screened by Osiris DataWarrior.
Afterward, 23 linkers were obtained after screened
and were docked with DNMT1 protein based on Acc,
HydA and Don pharmacophore site bypharmacophore-based rigid and flexible moleculardocking simulation using retain 100 with
AMBER100: EHT as a forcefield. Finally, two best
compounds were potential can inhibit DNMT1 referto standard RMSD value, ∆Gbinding, andpharmacological properties.
The two of best compounds structure, namely
HAMI_9 and HAMI_14, can be seen in Fig. 2.

Protein-Ligand Interaction Fingerprints (PLIF)
and Pharmacophore Selection of DNMT1 Protein
The interactions between DNMT1 proteins andligands were compared through PLIF method. Fiveproteins of DNMT1 (3AV5, 3AV6, 3SWR, 3PTA,
4WXX) have similarity interactions. The protein of
DNMT1 with PDB ID: 4WXX were chosen because
its 3D structure has an excellent resolution (2.622 Å)
and it comes from a human. The pharmacophore of
DNMT1 protein was analyzed and was validated
using standard ligands. Finally, there are threepharmacophore site namely HydA, Don and Acc
indicated in green, pink, and blue respectively (Fig.
1). The 3D structures and the pharmacophore site of
the DNMT1 protein can be seen in Fig. 1.

Fig. 1The pharmacophore site and SAH in thebinding pocket of DNMT1 protein (4WXX)

Preparation of The Fragments(A)
In this research were used 168,646 natural
products from PubChem database. All of the natural
products were screened through Osiris Data Warrior
v04.07.02 to find the potential fragment as inhibitor
candidate of the DNMT1 protein. The natural
products were screened based on toxicity prediction
test to predict and to eliminate the compounds thathave tumorigenic, mutagenic, reproductive effect andirritant characteristics. The natural products also werescreened based on Lipinski’s Rule of Three, which
are they must fulfill three parameters: (1) mass of themolecules are less than 300Da, (2) the hydrogen
donor and acceptor molecules are up to three, and (3)Fig. 2(B)

The structure of (A) HAMI_9 and (B) The
structure of HAMI_14

The HAMI_9 and HAMI_14 are the best drugcandidate because they have RMSD value lower than
2.0 Å and have lower ∆Gbinding energy compared to
the SAM and Sinefungin as a standard, even though
their ∆Gbinding energy is not lower than SAH. The
properties of the standards and all of the best ligands
are appropriate with the Lipinski’s Rule of Five andVeber’s rule, even though the HAMI_14 has a logP
value higher than five (Table 1).

109

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Molecular properties of the selected linked compounds and standard ligands

Ligand Name

Flexible Docking

MW∆Gbinding
RMSD*SAM-11.1980
1.6134399.451*SFG-10.9068
1.1838382.400*SAH-11.8062
0.9106384.416
HAMI_9-11.6094
1.7746484.618
HAMI_14-11.5903
1.5264498.641
Note: The meaning of * is the standard compound.

LogP

H-Don

H-Acc

TPSA

Rotatable
Bond-3.9384-3.9574-3.7275
3.89485.1464

4
5
4
5
4

11
12
11
6
5

187.08214.72212.38110.02
94.37

7
7
7
8
9

The HAMI_9 interacts with 22 amino acidresidues DNMT1 protein and has four hydrogen bondinteractions with Asparagine 1578, Glutamine 1223,
and Cysteine 1148. On the other hand, HAMI_14
interacts with 21 amino acid residues and has twohydrogen bond interactions with Asparagine 1578,
Alanine 1579 (Fig. 3 and 4).

Fig. 3

The HAMI_9 molecular interactions.

Fig. 4

The HAMI_14 molecular interactions.

absorption. The HAMI_9 and HAMI_14 havesubcellular localization in mitochondria.
The kinase and protease inhibitors of the ligands
have a different value; the score higher than 0.00
indicates the ligand has high activity, while a score
between 0.00 to −0.5 indicates that the ligand has
moderate activity, and score less than −0.5 indicatesthe ligand does not have activity [24]. HAMI_9 is thebest drug candidate based on kinase and proteaseinhibitor value because of its moderate activity as
kinase inhibitor and high activity as a proteaseinhibitor. Protein kinases are essential for
proliferation, metabolism, and apoptosis cells. The
molecule that inhibits kinases cause a decreased
cellular proliferation and increased apoptosis cells.
The inhibition of protein kinase is one strategy ofcancer therapy such as breast cancer therapy [25].
HAMI_9 also has high activity as protease inhibitorthat can be used to against cancer. Metastases andcancer progression are highly dependent on nutrientand oxygen supply, which are affected by various
proteases in the tumor and organs. The proteases are
essential for cell death, cell differentiation, gene
expression, cancer growth and metastases [26]. The
protease inhibitors have activity as anti-cancer
because they can inhibit proteolytic activity in cancer
development and metastases [27]. Therefore,
HAMI_9 has an activity to interfere with thedevelopment of cancer.
HAMI_9 and HAMI_14 are not organic cationtransporter (SLC22A2) and CYP inhibitor. It
indicates that they are able to translocate themolecules, have proper drug elimination, and does
not lead unwanted effects because of theaccumulation of the drug [20], [28]. The ligands areboth none in carcinogens and AMES toxicity test.
Therefore, the ligands are non-carcinogens and nonmutagenic [29] (Table 2).
The best ligands have good drug-likenessproperties refer to Veber’s and Egan’s Rule. The
bioavailability of the best ligands is at moderate level
because their bioavailability score is 0.55. All of thebest ligands are more readily synthesized than thestandard because it has lower synthetic accessibility
value than standard ligands [20]. All of the best
ligands do not have PAINS alerts, but the HAMI_9 as
the best ligand has 3 BRENK alerts (Table 3).

Analysis of Pharmacological Properties
Both ligands have similar molecular properties.
However, they show different characteristics in thepharmacological tests through SWISSADME,
Molinspiration, and ADMETSAR. The results ofpharmacological tests can be seen in Table 2. All of
the best ligands are better than Sinefungin as thestandard because they have high gastrointestinal (GI)110

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 ADME-Tox prediction all of the ligands using admetSAR, Molinspiration, and SwissADME software
ADME-Tox

Properties

Absorption
Distribution

GI Absorption
Sub Localization
Kinase Inhibitor
Protease InhibitorCYP Inhibitor
SLC22A2
AMES Toxicity
Carcinogens
Biodegradation

Metabolism
Excretion
Toxicity

Ligands*SAM
High
Nucleus
0.56
0.38
No
No
No
No
No

*SFG
Low
Nucleus
0.58
0.10
No
No
No
No
No

*SAH
High
Nucleus
0.57
0.23
No
No
No
No
No

HAMI_9High
Mitochondria
-0.04
0.19
No
No
No
No
No

HAMI_14High
Mitochondria
-0.14
-0.04
No
No
No
No
No

Table 3 The druglikeness and medicinal chemistry properties all of the ligands using SwissADME software
DruglikenessBioavailability
Veber
Egan
score
*SAM
Yes
No
0.55
*Sinefungin
Yes
No
0.55
*SAH
Yes
No
0.55
HAMI_9Yes
Yes
0.55
HAMI_14
Yes
Yes
0.55
Note: The meaning of * is the standard compound.
Ligand Name

PAINS
0 alert0 alert0 alert0 alert0 alert

Medicinal Chemistry
Synthetic
Brenk
accessibility
1 alert
4.94
0 alert
4.78
0 alert
4.69
3 alert
4.31
1 alert
4.44

CONCLUSIONREFERENCES

The in silico method is essential in drug
discovery, especially in the identification of new leadcompounds as drug candidate through fragmentbased drug design. The new lead compounds namely
HAMI_9 and HAMI_14 derived from the natural
products. The HAMI_9 and HAMI_14 can be used asa DNMT1 inhibitor for breast cancer therapy becauseof its excellent molecular properties, pharmacologicalproperties to inhibit DNMT1 protein. Based on the
result, the HAMI_9 is the best drug candidate to
inhibit DNMT1 because HAMI_9 has the lowest
Gibbs free binding energy, has the most significant
molecular interaction, and has the best
pharmacological properties. Therefore, the HAMI_9
is the promising drug candidates against breast
cancer.

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ACKNOWLEDGMENTS
The authors would like to give appreciation
toward Directorate of Research and Community
Engagement (DRPM) Universitas Indonesia for thefacilities and financial through Hibah PublikasiInternasional Terindeks Untuk Tugas Akhir
Mahasiswa(PITTA)No:
2328/UN2.R3.1/HKP.05.00/2018.
The
authors
declare that there is no conflict of interest regarding
this manuscript.
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112

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

CONSTRUCTION AND ANALYSIS OF M-POINT NONSTATIONARY SUBDIVISION SCHEME* Mehwish Bari1, Najma Abdul Rehman2 and Mehboob Alam3
1,3

Department of Mathematics, NCBA&E,Sub-Campus, Bahawalpur, Pakistan; 2 Department ofMathematics, COMSATS, Sahiwal, Pakistan
ABSTRACTIn this article, construction of m-point non-stationary ternary interpolating subdivision schemes having
tension parameter with the help of Lagrange identities have been discussed. Different limit curves can beobtained by adjusting the appropriate value of parameter in the proposed schemes. Tension or bagginess of the
final (curve) depends upon the raise or drop the value of parameter. The proposed hyperbolic non-stationary
schemes are as consistent as the regular curves by the control polygon as compared to the existing nonstationary schemes by trigonometric Lagrange polynomial. Few existing parametric and non-parametricstationary schemes are the counter part of proposed schemes. Asymptotically equivalence relation is used todetermine the continuity or smoothness of the proposed schemes. The main demand of this article is toreproduce hyperbolic functions and the proposed schemes reproduce hyperbolic functions very well. Numericalexamples show that the proposed scheme has the potential to reproduce hyperbolas and parabolas.
Keywords: Subdivision; Non-stationary; Interpolation; hyperbolas; parabolas

INTRODUCTION
Nowadays one of the important approach in geometricmodeling is the subdivision approach. It deals withsymbolization, interpolation, construction andhypothesis of curves and surfaces. the subdivision
schemes are more appropriate because these schemes
are simple, affecting, easy to understand, easy toanalyze, their applications are easy and have goodcordiality and best for geometric design. Deslauriersand Dubucpresented an iterative symmetricinterpolation processes [1]. They showed thesymmetric behavior of different subdivision schemes.
Hassan et al. [2] proposed an interpolating 4-point
ternary stationary subdivision scheme and they provethat the scheme has 𝑪𝟐 continuity. A class of binary,
ternary,a-ary subdivision schemes are produced by [3].
Currently, technology and science emphasize on theapplications that should allow to control the shape ofthe different objects and being capable of reproducing
different curves widely used in Computer Graphics,
Computer Aided Design and in geometric modeling,such as conics and polynomials. In the end of twentiethcentury stationary schemes are constructed but they do
not have the competency to produce conics. The workon non-stationary schemes grows fast in twenty first
century. Binary 4-point non-stationary scheme wasproposed in [4] in which two rules of subdivision areused to subdivide the initial control polygon. Beccari
et al. [5] proposed a 4-point scheme with a single
tension parameter and it preserve the shape because ofinterpolating property. Ternary 4-point interpolating
non-stationary scheme was proposed by Daniel andShunmugaraj [6]. A family of 4-point non-stationary

113

interpolating schemes were proposed Bari and Mustafa[7]. Odd-point non-stationary interpolating subdivision
schemes are also mentioned in [8]. Novara and Romani[9] gave a new direction to obtain new class of nonstationary schemes by building blocks. Siddiqi et al.
[12-14] construct binary and ternary non-stationary
subdivision schemes by using hyperbolic B-spline,
they show that the proposed scheme has the potential
to produce hyperbolic curves. To find the continuity of
their schemes they used the asymptotic equivalence
approach. Using the Lagrange polynomial andtrigonometric identities, Bari and Mustafa [15]construct some new non-stationary subdivision scheme.
This paper consists of four sections. First, definesome results which are helpful to generate a class of
non-stationary schemes in section 2. Construction of
non-stationary m-point ternary interpolating schemesin Section 3. Convergence of proposed interpolating
schemes is presented in section 4.
PRELIMINARIESIn terms of mask 𝒂𝒌 = {𝒂𝒌𝒊 : 𝒊 ∈ 𝒁}, a ternary univariate
subdivision scheme is according to the following
subdivision rule:𝒇𝒌+𝟏= ∑𝒋∈𝒁 𝒂𝒌𝒊−𝟑𝒋 𝒇𝒌𝒊 , 𝒊 ∈ 𝒁.
𝒊
Independence of k (level) in the mask 𝒂𝒌 shows thatthe subdivision scheme𝑺𝒂𝒌 is called stationary and thedependence of k (level) in the mask 𝒂𝒌 shows that thesubdivision scheme 𝑺𝒂𝒌 is called non-stationary

SEE - Nagoya, Japan, Nov.12-14, 2018

Definition-1: [5] Let 𝑺𝒂𝒌 and 𝑺𝒃𝒌 be two ternary
subdivision schemes and𝑺𝒂𝒌 , 𝑺𝒃𝒌 are asymptoticallyequivalent if

where
𝒍

𝝈𝟏 = 𝟏(5)𝒍𝟐

The values of∞∑‖𝑺𝒂𝒌 − 𝑺𝒃𝒌 ‖ < ∞,𝒍𝟏 and 𝒍𝟐 are𝑙1 = (−1)𝑛 (3𝑛 − 1)(3𝑛 − 4) ! , 𝑙2 =33𝑛−4 (1 − 3𝑝)(𝑛 − 2)!,

𝒌=𝟎

where

and
𝜎2 = (−1)𝑛−𝑚 (𝑛 − 𝑝)! (𝑛 + 𝑝 − 2)!.
When 𝑝 = −𝑛 + 1 in Eq. (3), we have

‖𝑺𝒂𝒌 ‖∞ = 𝒎𝒂𝒙 {∑|𝒂𝒌𝟑𝒊 |, ∑|𝒂𝒌𝟑𝒊+𝟏 |, ∑|𝒂𝒌𝟑𝒊+𝟐 |}.
𝒊∈𝒁
𝒊∈𝒁
𝒊∈𝒁

Dyn and Levin [10] gave the idea behind asymptotic
equivalence.
Theorem-1: [10] Let 𝑺𝒂 (stationary) and 𝑺𝒂𝒌 (nonstationary) ternary subdivision schemes having finite
masks. If 𝑺𝒂 is 𝑪𝒎 and𝟏(−𝟏)−𝒏+𝟏 (𝟑𝒏−𝟏)!

𝟑

𝟑𝟑𝒏−𝟐 (𝟑𝒏−𝟐)(𝟐𝒏−𝟏)(𝒏−𝟏)!

𝝈𝟑 = 𝑳𝒎−𝒏+𝟏 ( ) =

(6)

(7)

Furthermore, we have to calculate
1

1

𝑚−1
𝜎4 = 𝐿𝑚()=𝑝 ( ) − 𝐿𝑝3(−1)𝑝 (3𝑛−1)!

3(8)

33𝑛−2 (𝑛−1)!(3𝑛−2)(𝑛−𝑝)!(𝑛+𝑝−1)!

∞∑ 𝟑𝒎𝒌 ‖𝑺𝒂𝒌 − 𝑺𝒂 ‖∞ < ∞,where 𝒑 = −(𝒏 − 𝟐), −(𝒏 − 𝟑), … 𝒏.

𝒌=𝟎

holds, then 𝑺𝒂𝒌 is also 𝑪𝒎 .

We refer to [11] for further details.

CONSTRUCTION
OF
M-POINTSTATIONARY SUBDIVISION SCHEME

M-POINT TERNARY INTERPOLATINGSCHEMENON-

We are going to present general formulae to constructnon-stationary 𝐦 -point ternary interpolating
subdivision scheme.
Let 𝒏 ≥ 𝟐, the rules of 𝐦-point ternary interpolating
scheme are𝒌𝒇𝒌+𝟏
𝟑𝒊 = 𝒇𝒊 ,Lagrange interpolation was first used by
Deslauriers and Dubuc [1] to construct subdivision
schemes. We are also going to use Lagrange
polynomial to build a class of hyperbolic nonstationary schemes. First we define the Lagrange
fundamental polynomials of degree m and m-1, wherem=2n , for 𝑛 ≥ 2, corresponding to {𝑡𝑗 }𝑛−(𝑛−1) and{𝑡𝑗 }𝑛−(𝑛−2) respectively,𝑛𝐿𝑚𝑝 (𝑡) = ∏𝑡𝑗 =−(𝑛−1),𝑝≠𝑡𝑗

𝑡−𝑡𝑗
𝑝−𝑡𝑗

, 𝑝 = −(𝑛 −1), −(𝑛 − 2) … 𝑛and𝐿𝑚−1(𝑡) = ∏𝑛𝑡𝑗 =−(𝑛−2),𝑝≠𝑡𝑗
𝑝

𝒏−𝟏

𝒇𝒌+𝟏
𝟑𝒊+𝟏 =

𝒑=−𝒏
𝒏

(1)

𝒇𝒌+𝟏
𝟑𝒊+𝟐 =
{

𝑡−𝑡𝑗
𝑝−𝑡𝑗

𝒌
∑ 𝝁𝒌,𝒎−𝒑 𝒇𝒊+𝒑+𝟏 ,

∑

𝒌
𝝁𝒌,𝒎
𝒑 𝒇𝒊+𝒑 ,𝒑=−(𝒏−𝟏)(9), 𝑝 = −(𝑛 −2), −(𝑛 − 3) … 𝑛

by introducing hyperbolic sine function, triadic(2)

𝟏

subdivision 𝒌+𝟏 = 𝜿, the parameter 𝝎, we get the𝟑

Applying the arithmetical processes on the
Lagrange identities in Eq. (1) and Eq. (2), we get
Eq. (3) and Eq. (4):first coefficient 𝝁𝒌,𝒎
−𝒑 for 𝒑 = −𝒏. The othercoefficients 𝝁𝒌,𝒎
−𝒑 for 𝒑 = −𝒏 + 𝟏, … , 𝒏 − 𝟏 areformed by the equations (5)-(8).

(−1)𝑛 (3𝑛−1)!
33𝑛−2 (1−3𝑝)(𝑛−1)!
𝐿𝑚𝑝 (𝑡) = (−1)𝑛−𝑝 (𝑛−𝑝)!(𝑛+𝑝−1)!

(3)

𝒑 = −(𝒏 − 𝟏), − (𝒏 − 𝟐), … 𝒏 and(−1)𝑛 (3𝑛−1)(3𝑛−4)!
33𝑛−4 (1−3𝑝)(𝑛−2)!

(𝑡) =
𝐿𝑚−1
=
𝑝
(−1)𝑛−𝑝 (𝑛−𝑝)!(𝑛+𝑝−2)!

𝜎1
,
𝜎2

𝝎
𝜿
𝟏
𝐬𝐢𝐧𝐡( )
𝜿
𝝈𝟒 𝝎
𝐬𝐢𝐧𝐡(
)
𝜿
𝝈
𝐬𝐢𝐧𝐡( 𝟑 )𝜿𝝁𝒌,𝒎−𝒏+𝟏 ={(4)

implies𝝈(𝒕) = 𝟏, for 𝒑 = −(𝒏 − 𝟐), −(𝒏 − 𝟑), … 𝒏
𝑳𝒎−𝟏
𝒑
𝝈𝟐

114

𝝁𝒌,𝒎
=
𝒑

𝝈
𝜿
𝝈
𝐬𝐢𝐧𝐡( 𝟐 )𝜿𝐬𝐢𝐧𝐡( 𝟏 )+𝐬𝐢𝐧𝐡( )

, 𝝎<𝟏
(10)
, 𝒑 = −𝒏 + 𝟐, … 𝒏.

SEE - Nagoya, Japan, Nov.12-14, 2018

Zhu [16] gave the following inequalities

Using Eq. (9) and Eq. (10), we get 4-point ternary
scheme having parameter 𝜔 , so by substituting𝑛 = 2,
𝐬𝐢𝐧𝐡 𝒂𝑓𝑘+1= 𝑓𝑘𝑖 ,
3𝑖
𝑓𝑘+1
= 𝜇𝑘,4𝑓𝑘𝑖−1 + 𝜇𝑘,4
𝑓𝑘𝑖 + 𝜇𝑘,4
𝑓𝑘𝑖+1 + 𝜇𝑘,4
𝑓𝑘 ,
2
1
0
−1 𝑖+2
3𝑖+1
𝑓𝑘+1= 𝜇𝑘,4
𝑓𝑘 + 𝜇𝑘,4
𝑓𝑘𝑖 + 𝜇𝑘,4
𝑓𝑘𝑖+1 +
−1 𝑖−1
0
1
3𝑖+2
𝜇𝑘,4
𝑓𝑘𝑖+2 ,
2

(11)

where
𝜔

𝐬𝐢𝐧𝐡 𝒂𝜿

10sinh( )
9.𝜅2
sinh( )
𝜅

−

𝜇𝑘,4
=
1

For m=4 the proposed scheme has the following
inequalities:

5𝜔
)
27.𝜅
5
sinh(
)
81.𝜅

sinh(

,

5
5𝜔
) sinh(
)
9. 𝜅
27. 𝜅
+
,
1
5
sinh( )
sinh(
)
𝜅
81. 𝜅

sinh(

1

cos ℎ( )
𝜅

5

(ii)

9
5

(iii)
𝜇𝑘,4
=−
2

5
)
81.𝜅

𝜔 cos ℎ(𝜔 ≤ 𝛾𝑘,4
≤
−1

(i)

and
2
5𝜔
) sinh(
)
9. 𝜅
81. 𝜅
−
,
2
5
sinh( )
sinh (
)
𝜅
81. 𝜅

9
5

sinh(

9

−

cosh(

5
)
81.𝜅

𝑘,4
𝜇−1
+ 𝜇0𝑘,4 + 𝜇1𝑘,4 +𝜇2𝑘,4=𝜿1sinh( )

+

𝜿

5𝜔
)
27.𝜅
5
sinh(
)
81.𝜅

sinh (

−

10
)
9.𝜅
2
sinh( )
𝜅2
sinh( )
9.𝜅2
sinh( )
𝜅

sinh(

−

−

5𝜔
)
27.𝜅
5
sinh(
)
81.𝜅
5𝜔
sinh(81.𝜅)
5

sinh(

sinh(

𝟖𝟏.𝜿

+

)

5
)
9.𝜅
1
sinh( )
𝜅

sinh(

+ 3𝜔
1
2

9 cosh( )−+Taking 𝝎 = −

(i)

𝑓𝑘+1
= 𝑓𝑘𝑖 ,
3𝑖
𝑓𝑘+1
= 𝛾𝑘,4𝑓𝑘𝑖−1 + 𝛾𝑘,4
𝑓𝑘𝑖 + 𝛾𝑘,4
𝑓𝑘𝑖+1 + 𝛾𝑘,4
𝑓𝑘 ,
2
1
0
−1 𝑖+2
3𝑖+1
𝑓𝑘+1= 𝛾𝑘,4
𝑓𝑘 + 𝛾𝑘,4
𝑓𝑘𝑖 + 𝛾𝑘,4
𝑓𝑘𝑖+1 +
−1 𝑖−1
0
1
3𝑖+2
𝛾𝑘,4
𝑓𝑘𝑖+2 ,
2

(ii)

(14)

𝜇 𝑘,𝑚

of

weights𝟏

1 1, ) in the scheme
15 9− 𝒖 or u  (
𝟏

𝟏𝟖

𝟔

1

1

− 18 − 6 𝑢 ≤ 𝛾𝑘,4
≤
−1
1

5
)
81.𝜅

𝜅

𝛾𝑖𝑘,𝑚 = 𝜃𝑖𝑘,𝑚 , 𝑖 = −𝑛 + 1, … 𝑛.
sum)cosh( )

Remark-1: Generally we can write the coefficients ofthe proposed schemes for 𝒏 ≥ 𝟐 by

the

81.𝜅

1 1
18 6

where

that

5

9

(− − 𝑢) cosh((13)

Remember1≤ 𝛾𝑘,4≤2(13), we have

We can define the normalized scheme as𝑖 = −1, … ,2.

5
)
81.𝜅

Lemma-2:
.

(12)

𝜇 𝑘,4
𝛾𝑖𝑘,4 = 𝜃𝑖𝑘,4 ,

𝜔
cosh(

Proof: The proof of above inequalities can be followedby [12].

𝜃𝑘,4

=

𝜔

5

− − 𝜔 cosh(

By introducing the normalized scheme, we get
𝜔

≤

5
𝛾𝑘,4
≤ −3
0
9

+ 3𝜔 cosh (81.𝜅) ≤ 𝛾𝑘,4
≤
1

−

(iv)

3𝜔

𝜅

sinh( )

𝟏

Lemma-1:sinh( )
𝑘,4
𝜿
𝜇−1
=
1 ,
sinh( )

𝜇𝑘,4
=
0

𝒂

≤ for 𝟎 < 𝐚 ≤ 𝐛 < ∞, and< (𝟏 +𝒃𝒂𝟐
𝐜𝐨𝐬𝐡𝒂) for 𝟎 < 𝐚 < ∞,Convergence of proposed scheme can be found by
using
the
above
mentioned
inequalities.
Asymptotically equivalence is necessary to prove theconvergence of non-stationary schemes.
𝐬𝐢𝐧𝐡 𝒃

5

−3

9

(iii)

5

(iv)

−

9

1 1
18 6

(− − 𝑢)
5
)
81.𝜅

cosh(

+ 3 (−

−5 5

− 𝑢

1

2

9 cosh( )

(−

1
18

81.𝜅

1

1

1

− 𝑢) cosh( 18 6 ) ≤

18
6
7
1
𝑘,4
𝛾1 ≤ − 𝑢
18
6

𝜅

of

1

13

≤ 𝛾𝑘,4
≤ + 𝑢
0
18
6

−

1

(−18−6𝑢)≤ 𝛾2𝑘,4 ≤5cosh(81.
)𝜅1+ 𝑢) cosh(
6

5
)
81.𝜅

proposed(normalized scheme) is 1.
Lemma-3:
Following inequalities also hold for scheme (13):SMOOTHNESS for m=4

(i)

115

1

− 𝜔| ≤ 𝐺0 ( 2𝑘 )
|𝛾𝑘,4
−1
3

SEE - Nagoya, Japan, Nov.12-14, 2018

5

3𝜔

1

(ii)

|𝛾𝑘,4
−( −
0
9

(iii)

5
5𝜔
+ ( + 3𝜔 cosh (
))| ≤
|𝛾𝑘,4
1
9
27.𝜅

5

)| ≤ 𝐺1 (32𝑘 )cosh(81.𝜅)For 𝝎 = −

1

|𝛾𝑘,4
− (−
2

1

2 −

9 cosh(𝜅 )𝟏− 𝒖, scheme 𝑺𝒂𝒌 by Eq. (13) and𝟔

scheme 𝑺𝒂 of [2] we can write as
𝟐𝒌∑∞‖𝑺𝒂𝒌 − 𝑺𝒂 ‖∞ < ∞, so the scheme in
𝒌=𝟎 𝟑

𝐺2 (32𝑘 )
(iv)

𝟏
𝟏𝟖

[2] is 𝑪𝟐 so by Theorem-2, hyperbolic non-

𝜔
5

)| ≤

stationary scheme (13) is 𝑪𝟐 .

cosh(81.𝜅)1

𝐺3 (32𝑘 )Numerical Examples
The solid boxes (initial control points) insertion in Fig.
1 are calculated by the parametric form of hyperbola
and parabola. The solid boxes in Fig 1. (a)-(b) show theinitial control points of parabola and hyperbola and thelimit curve formed by proposed subdivision scheme.

𝑮𝟎 , 𝑮𝟏 , 𝑮𝟐 and 𝑮𝟑 are k-independent.
Similarly we can construct another lemma by
𝟏
𝟏
adding the value of parameter 𝝎 = − − 𝒖 in
𝟏𝟖
𝟔
Lemma 3 to find out the continuity of proposed
scheme by asymptotic equivalence.
Remark: By making the above inequalities for thenormalized scheme as done in [8] and applying theasymptotic equivalence relation on the prescribed nonstationary scheme with the stationary scheme, we get
the 𝑪𝟐 𝐬𝐦𝐨𝐨𝐭𝐡𝐧𝐞𝐬𝐬.
Theorem 2: The proposed hyperbolic scheme with𝟏𝟏
𝝎 = − − 𝒖 having range 𝒖 ∈ (𝟎. 𝟎𝟔𝟔, 𝟎. 𝟏𝟏𝟏) is
𝟏𝟖

𝟔

𝑪𝟐 .
Proof. Since(a) parabola∞(b) hyperbola

Fig. 1 Shows the parabola and hyperbola byproposed scheme.

∑ 𝟑𝟐𝒌 ‖𝑺𝒂𝒌 − 𝑺𝒂 ‖∞ < ∞,𝒌=𝟎

We already define
CONCLUSION‖𝑺𝒂𝒌 − 𝑺𝒂 ‖∞ = 𝒎𝒂𝒙 {∑|𝒂𝒌𝒊−𝟑𝒋 − 𝒂𝒊−𝟑𝒋 |: 𝒊

Lagrange identities are useful to construct m-point
non-stationary hyperbolic subdivision schemes to
produce parabolas and hyperbolas in well-designed
manner. The proposed schemes in this article arecounterpart of the existing stationary schemes. The
established schemes in this article has the potential toreproduce important parts in conics such as hyperbolas
and parabolas. Our next target to extend this work for
3-D modeling such that to create hyperboloid andparaboloid.

𝒊∈𝒁∈ 𝟎, 𝟏, 𝟐, 𝟑}.
We can write now∞∑ 𝟑𝟐𝒌 ‖𝑺𝒂𝒌 − 𝑺𝒂 ‖∞𝒌=𝟎∞= ∑ 𝟑𝟐𝒌 {|𝜸𝒌,𝟒−𝟏
𝒌=𝟎

ACKNOWLEDGEMENTS

𝟏 𝟏− 𝒖)| , |𝜸𝒌,𝟒
𝟎
𝟏𝟖 𝟔
𝟏𝟑 𝟏
− ( + 𝒖)| , |𝜸𝒌,𝟒
𝟏
𝟏𝟖 𝟐
𝟕 𝟏
− ( − 𝒖)| , |𝜸𝒌,𝟒
𝟐
𝟏𝟖 𝟐
𝟏 𝟏
+ (−
− 𝒖)|},
𝟏𝟖 𝟔− (−This work is supported by the SRGP Project No. 1741
of Higher Education Commission (HEC) Pakistan.
REFERENCES[1]

It follows
𝟐𝒌
∑∞
|𝜸𝒌,𝟒
𝒌=𝟎 𝟑
−𝟏 − (−

𝟏𝟏𝟖

𝟏− 𝒖)| ≤
𝟔

𝟏
𝟐𝒌 `
∑∞
𝒌=𝟎 𝟑 𝑮𝟎 (𝟑𝟐𝒌 )<∞

[2]

116

Deslauriers, G. and Dubuc, S. Symmetric
iterative
interpolation
processes
inConstructive approximation, ed: Springer,
1989, pp. 49-68.
Hassan, M. F., Ivrissimitzis, I. P., Dodgson, N.
A., and Sabin, M. A., An interpolating 4-

SEE - Nagoya, Japan, Nov.12-14, 2018

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

point C 2 ternary stationary subdivision
scheme. Computer Aided Geometric Design,
Vol 19, 2002, pp. 1-18.
Lian, J. A. On a-ary subdivision for curve
design, I. 4-point and 6-point interpolatory
schemes.
Applications
andAppliedMathematics, Vol. 3, 2008, pp. 18-29.
Jena, M., Shunmugaraj, P. and Das, P. A nonstationary subdivision scheme for curveinterpolation. Anziam Journal, Vol. 44, 2008,
pp. 216-235.
Beccari, C., Casciola, G. and Romani, L, A
non-stationary uniform tension controlledinterpolating 4-point scheme reproducing
conics. Computer Aided Geometric Design,Vol. 24, 2007, pp. 1-9.
Daniel, S. and Shunmugaraj, P. Someinterpolating non-stationary subdivision
schemes. In Computer Science and Society(ISCCS), 2011, International Symposium on,
2011, pp. 400-403.
Bari, M. and Mustafa, G. A Family of 4-Point
n-Ary Interpolating Scheme Reproducing
Conics. American Journal of Computational
Mathematics, Vol. 3, 2013, pp. 217-221.
Mustafa, G. and Bari, M. A new class of oddpoint ternary non-stationary schemes. British
Journal of Mathematics & Computer Science,Vol. 4, 2014, pp. 133, 2014.
Novara, P. and Romani, L. Building blocks
for designing arbitrarily smooth subdivision
schemes with conic precision. Journal ofComputational and Applied Mathematics,
Vol. 279, 2015, pp. 67-79.
Dyn, N. and Levin, D. Analysis ofasymptotically equivalent binary subdivision
schemes. Journal of mathematical analysis

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[16]

117

and applications, Vol. 193, 1995, pp. 594621.
Aslam, M., Mustafa, G. and Ghaffar, A. (2n1)-Point Ternary Approximating andInterpolating Subdivision Schemes. Journalof Applied Mathematics, Vol. 2011, 2011.
Siddiqi,
S.S.,
Salam,
W.Us.
andRehan, K Binary 3-point and 4-point nonstationary subdivision scheme using
hyperbolic
function.
AppliedMathematics andComputation, Vol
258, 2015, pp. 120-129.
Siddiqi, S. S., Salam, W. U. andRehan,K., Hyperbolic forms of ternary nonstationary
subdivision
schemesoriginatedfrom
hyperbolic
Bsplines. Journal of Computational andApplied Mathematics, Vol 301, 2016, pp.
16-27.
Siddiqi, S.S., Salam, W. U. andRehan, K., Construction of binary four
and
five
point
non-stationary
subdivision schemes from hyperbolic Bsplines. Journal of Computational andApplied Mathematics, Vol 280, 2016, pp.
30-38.
Bari, M. and Mustafa, G. A family of
2n-point
Ternary
Non-Stationary
Interpolating
Subdivision
Scheme.
Mehran university research journal ofengineering and technology. Vol. 36, No
4, 2017, pp. 921-932.
Zhu, L. Inequalities for hyperbolic
function and applications. Journal of
inequalities and applications, 2010.

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ECOLOGY OF RUMINAL MICROORGANISMS UNDER THE
INFLUENCE OF QUERCUS CORTEX EXTRACT
Galimzhan Duskaev, 1 Il'shat Karimov1,2, Georgy Levakhin1, Baer Nurzhanov1, Albert Rysaev1 and Hamdiya
Dusaeva2
1

Federal Research Center of Biological Systems and Agro-technologies of the Russian Academy of Sciences,
Orenburg, Russia
2
Orenburg State University, Orenburg, Russia
ABSTRACTThe study was performed for assessing the elemental status and the bacterial composition of the rumen fluid
microflora in cattle after incubation in vitro with Quercus cortex extract and exogenous enzymes. The mixture ofalfalfa hay, Sudan grass and concentrates (60:40) was used as the substrate. The results showed that in the
protozoa a decrease in such elements as P, Na, Ca (P≤0.05) was observed when substrate with enzyme wasadded. The level of essential elements in bacteria three hours after the incubation together with the enzyme
changed similar to the protozoa, except for copper, the content of which increased two times (P≤0.05). The
introduction of Quercus cortex extract into the substrate with the enzyme preparation three hours after the
incubation promoted a significant increase in iron, manganese and cobalt content in the protozoa (P≤0.05).
Unlike other variants, incubation of the substrate with the enzyme together with the extract increased the numberof representatives of the taxa Firmicutes by 13.2%, Bacteroidetes - by 13.4% (P≤0.05) against the background ofa slight decrease in Proteobacteria, Saccharibacteria and Fibrobacteres. An increase was observed in the numberof microorganisms belonging to the taxa Clostridia (by 23.7%; P≤0.05) and Bacteroidia (by 13.4%; P≤0.05). The
biosensor based on B.subtilis on samples with the extract reacted by quenching the luminescence by 60% on the
5th minutes and by 32% on the 60th minute contact. Thus, the chemical composition of oak bark extract
significantly influenced the elemental profile and the bacterial composition of cattle rumen microorganisms.
Keywords: Quercus cortex extract, elemental status, rumen microorganisms, cattle.
INTRODUCTION

In this regard, the research aimed at studying
the ability of plant extracts to inhibit
microorganisms, and the influence on the elemental
status of microflora of the rumen of cattle is ofinterest.
The aim of the research. Studying the effect of
feeding Quercus cortex extract on the elemental
status and the bacterial composition of cattle rumen
fluid in vitro against the background of enzyme
diet.

Limitations in the use of antibiotic substances
for preventing diseases and increasing cattle
productivity make it urgent to search for new
substances with similar properties. Among thesesubstances, there are plant extracts (essential oils,
saponins, tannins, etc.) with positive effect onprotein metabolism, production of volatile fatty
acids and gases in the rumen of ruminants [1, 2, 3].
At the same time, a number of scientists identified
in plant extracts a new class of substances capableof efficiently preventing development of infectious
and inflammatory processes in human and animalorganisms through the system of intercell chemicalcommunication in bacteria ("quorum sensing") [4].
Thus, when screening 20 medicinal plants used by
the Russian (Eastern European) folk medicine, themost pronounced ability to inhibit the "quorum
sensing" system of wild and mutant strains of
C. violaceum was identified in extracts of oak bark(cortex Quercus), birch buds (Betula verucosa) andeucalyptus leaves (Eucalyptus viminalis) [5]. At thesame time, the need for studying the influence of
these extracts directly on the microbiome, changes
in its biochemical parameters may be of interest
whenstudying
intercellularchemicalcommunication in bacteria in the rumen. The
previously obtained results confirm the promising
nature of these studies [6,7].

MATERIALS AND METHODS
Phytochemical analysis. Dry Quercus cortex
extract was used for the research, which wasdissolved in ethanol before chromatography-mass
spectrometry, and injected into the analytical cell of
the chromatograph using microsyringe Hamilton
1700. Chemicals in Quercus cortex extract wereidentified in the gas chromatograph with mass
selective detector GQCMS 2010 Plus (Shimadzu,
Japan), in column HP-5MS. The research results
were interpreted with the following software:
GCMS Solutions, GCMS PostRun Analysis;compounds were identified with a set of spectra
libraries CAS, NIST08, Mainlib, Wiley9 andDD2012 Lib. The quantitative presence ofindividual identified components was assessed byrelative value (%), which correlated the area of thepeak to the total area of the extract. In the extract of118

SEE - Nagoya, Japan, Nov.12-14, 2018oak bark 35 substances were identified (according
to IUPAC): propanetriol-1,2,3*; decane*; 2furancarboxylic acid*;
1,3,5-triazine-2,4,6triamine*; pentadecane*; 2,3-dihydroxypropyl*;butanedioic acid*;
2,3-dihydro-3,5-dihydroxy-6methyl-4H-pyran-4-one*;
2-amino-9-[3,4dihydroxy-5-(hydroxymethyl) oxolan-2-yl] -3Hpurine-6-one*; cyclopentane-1,2-diol**; 1,2:5,6dianhydrogalaxytole**; 5-hydroxymethylfurfural*;acetylcysteine, -2-acetamido-3-mercaptopropionic
acid*; 1-methylundecyl ether 2-propenoic acid**;
2,3-dihydro-3,5-dihydroxy-6-methyl-4H-pyran-4one**; 1- (2-hydroxyethyl) -4-methylpiperazine**;
6- (4-hydroxy-6-methoxy-2-methyl -, tetrahydropyran-3-yloxy) -2-methyl-dihydro-pyran-3-one**;
1,2,3-trihydroxybenzene* (pyrogallol); 2-methyl-5nitro-pyrimidine-4,6-diol**;
4-hydroxy-3methoxybenzaldehyde*(vanilla); 2-amino-9- [3,4dihydroxy-5- (hydroxymethyl) oxolan-2-yl] -3Hpurine-6-one*; 1,6-anhydro-β-D-glucopyranose*;
1- (β-D-arabinofuranosyl) -4-O-trifluoromethyl
uracil**; 4-hydroxy-3-methoxy benzoic acid**;
1,6-anhydro-β-D-glucofuranose*;
4-propyl-1,3benzenediol*(propylresorcinol);
1,2,3,4,5cyclohexanol*;4-(hydroxymethyl)-2,6dimethoxyphenol*; 4- (3-hydroxy-1-propenyl) -2methoxyphenol*(coniferyl alcohol); 9 -[(2R, 3R,
4S, 5R) -3,4-dihydroxy-5- (hydroxymethyl) oxolan2-yl]-3H-purine-2,6-dione*; 7-hydroxy-6-methoxy2H-1-benzopyran-2-one*(coumarine); methyl-α-Dglucopyranoside*;
2H-1-benzopyran-2one*(scopoletin);
2 ethoxy-6(methoxymethyl) phenol**;
3,4,5trimethoxyphenol**(antiarol)(*components
identified with the probability of over 90%; **components identified with the probability of atleast 90%).
Scheme of the experiment. Reference - ruminal
fluid + ethanol (0.5% of volume), variant I –ruminal fluid + exogenous enzyme + ethanol (0.5%of volume), variant II - scar liquid + phytoextract inethanol (0.5% of total) + exogenous enzyme.
The exogenous enzyme preparation contained
glucoamylase and related cellulosolytic enzymes(xylanase, β-glucanase, cellulase). The preparation
was dosed in the amount of 0.05% of dry
ingredients.
Experimental studies were performed at thescientific equipment common use center of Federal
Research Center of Biological Systems and Agrotechnologies of the Russian Academy of Sciences.
Ruminal digestion in vitro. The previously
used method of studying ruminal fermentation invitro [8] was considered to be an acceptable method
for assessing the influence of phytocompounds on
ruminal microflora. Two heads of cattle (males)with chronic rumen fistula were kept on a dietconsisting of 60% coarse forage (alfalfa hay andSudan grass) and 40% pellets containing barley
grain, wheat bran, wastes of vegetable oil,limestone, salt, vitamins and a premix. The
chemical composition of the diet: (g/kg of dry
matter) was 153 non-decomposing protein, 485
neutral detergent fiber, 47 crude fat, 85 ash and10.00 MJ/kg exchange energy of dry matter. The
fodder was supplied twice a day, and animals had
free access to drinking water. The animals wereused as donors of ruminal fluid.
Two hundred milligrams of dry matter in theforage consisting of hay and concentrates (pellets)
in the ratio of 60:40 were used as substrate forfermentation in vitro. The incubation medium was
prepared as described by Menke and Steingass [9],and 30 ml of it were anaerobically placed into a 100
ml syringe.
The mixture of substances was dissolved inethanol; the substrate based on dry matter (9 mg)
was introduced into each syringe at theconcentration of 4.5% (by weight). The final
concentration of ethanol in each syringe was 0.5%.
The reference was substrate with 0.5% ethanol. The
syringes were incubated at 39° C for 24 hours.
Degradability of the dry matter, quantitative
assessment of the rumen microorganisms’population, and their elemental composition were
measured. The total of nine syringes were used foreach research.
Assessment of the effect on luminescent bacterial
biosensors. Strains of Escherichia coli MG1655
pXen7, Salmonella typhimurium LT2 pACXen and
Bacillus subtilis EG168-1 were used as test objects.
Cells were grown within 24 hours on LB agar
(Sigma-Aldrich, USA) with a selectable marker,
and then suspended in a 0.5% solution of sodium
chloride to OD450 = 0.50 rel. units in transparent
wells at a volume of 200 μl using StatFax 303+
photometer (Awareness, USA). Two-fold dilutions
from 100% to 1.56% were prepared in wells of a
96-well plate with a volume of 50 μl from samples
of ruminal fluid, then 150 μl of biosensor cellsuspension were added. The luminescence ofbacteria was registered in a kinetic mode using LM01T luminometer (Immunotech, Czech Republic)for 60 minutes [10].
Analysis of the rumen microbial population.
Assessment of the microbial biodiversity included:
sampling, isolation, purification, measuring DNA
concentration, PCR, validation and normalizationof libraries followed by sequencing at the platformof high-performance sequencer MiSeq Illumina(USA). Bioinformatical analysis of the results wasmade in application PEAR (Pair-End AssembeR,
PEAR v0.9.8, April 9, 2015) [11].
Analysis of the substrates’ elemental status. The
elemental composition of the extract, animalculines
and bacteria (liquid samples) was determined byatomic emission and mass spectrometry (AES-ISP
and MS-ISP) at the test laboratory of Autonomous
Nonprofit
Organization"Biotic
Medicine
Centre",Moscow (Registration Certificate of ISO

119SEE - Nagoya, Japan, Nov.12-14, 2018

9001: 2000, Number 4017-5.04.06). Biologicalsubstrates were ashed using a microwave
decomposition system MD-2000 (USA). Elements’content in the obtained ash was assessed using a
mass spectrometer Elan 9000 (Perkin Elmer, USA)and an atomic emission spectrometer Optima 2000
V (Perkin Elmer, USA). Elemental composition of
Quercus cortex extract, mg/g was the following: Ca- 246; P - 8.22; K - 124; Mg - 32.5; Na - 85.0; Zn 1.75; Mn - 5.8; Cu - 0.05; Fe - 2.01; Co - 0.018; Se- 0.02; I - 0.037; Al - 0.46; Sr - 0.7; Cr - 0.11; Cd 0.001; Pb - 0.008.
Statistical processing. Statistical processing was
made in application IBM "SPSS Statistics Version20", calculating the mean value (M), the standard
deviation (σ), the standard deviation error (m). The
level of significance was considered veracious with
p<0.05. The student's t-criterion was used forstatistical processing.

manganese (8.8%) and cobalt (16.5 times). Similar
pattern was observed in studying the compositionof bacteria: for copper, the increase was 11.3 times,
for zinc – 3.3 times, and for iron – 2.4 times (Table
1). Due to the fact that the topic has been poorly
studied, and to the lack of direct data in theliterature, one can see the need for using indirect
facts in the discussion. Thus, it is necessary toconsider the fact that bacteria are in some ways
"food" for the animalculines, and increasing theamount of macro- and essential elements in them
may be explained by ingestion, or by normal
digestion process. Besides, it should be noted thatmicroelements’ concentration in plants largely
depends on the environment, the climate, the age,as well as the composition of diets, and otherfactors [12, 13, 14, 15, 16]. It is known that metal
ions are cofactors for a number of enzymes,
including microorganisms and protozoa [17];therefore, the probability of their influence on theactivity of the enzyme systems of the ruminal
microflora is quite high.
At the same time Quercus cortex, which is
positioned as the source of tannins, has no adverse
effect on fermentation in the rumen of cattle,
positively influences energy exchange and protein
utilization in the rumen [18,19], the number ofprotozoa [20], although this requires further
research [21,22].

RESULTS AND DISCUSSION
According to the research results, the level of
essential elements in protozoa after incubation ofvariant I decreased, except for copper, the value of
which increased 2 times, compared to the reference.
Incubation of the II variant contributed toa significantly increased amount of substances; thiswas particularly evident for iron (21.8%),

Table 1 The mean values of essential elements’ content in protozoa and bacteria, µg/g
Diet

Zn

reference

1.6
±0.24

MD+E

1.2
±0.18
5.7
±0.85

MD+E+extractreference

1.3
±0.19

MD+E

1.2
±0.18
3.9
±0.6

MD+E+extract

Mn

Cu
Fe
Protozoa
1.6
0.14
7.5
±0.25
±0.028±1.12
Protozoa (after 3 hours)
0.7
0.31
4.0
±0.148±0.063
±0.61
6.2
1.6
87.4
±0.93
±0.24
±13.11Bacteria
0.5
0.2
2.6
±0.108±0.039±0.39
Bacteria (after 3 hours)
0.5
0.3
2.9
±0.099
±0.06
±0.44
0.7
3.4
7.0
±0.148±0.51±1.06

In turn, the use of enzyme-containing diet could
not influence the microflora in view of thenumerous data indicating their efficient use infeeding cattle [23, 24, 25]. In studying
bioavailabilityofmicroelements
inthegastrointestinal tract of ruminants, it is necessary toveraciously consider their bonding with the coarse
fiber part of the fodder, with undigested fodder
components and newly formed complexes insoluble

Co

Se

I

0.003
±0.00094<0.00390.007±0.00229

0.002±0.00067
0.033±0.0080.004±0.00133
0.004±0.00130.007±0.00218<0.00390.017±0.004<0.0039<0.0039<0.00390.006±0.00198
0.027±0.0070.005±0.00158
0.008±0.00245
0.012±0.003in acidic environment [26, 27, 28]. The results of
the research show low bioavailability of selenium
for both protozoa and bacteria. This is determinedby the results of previous experiments that showed
low digestion of selenium by these animals, and thetransition of its available form into a less available
one directly in the ruminal medium [29]. Someauthors [30] indicate that high levels of calcium in

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SEE - Nagoya, Japan, Nov.12-14, 2018

the diet result in low selenium absorption, which
was also observed in this experiment.
The results of the research show the prevalenceof iron concentration over the same value of copperin the experiment in both protozoa and bacteria,
especially against the background of enzyme diet.
This increase is also due to the high iron content in
Quercus cortex extract. Several researchers in theirstudies indicated a decreased level of copper in theorganism of ruminants with increasing the level ofiron in the diet [31]. Zinc concentration in
protozoa and bacteria in the reference and after the
incubation virtually did not change, probably due tothe relatively high absorption capacity of thiselement in the rumen, and the availability of thephytaze activity of the microflora [32]. Manganeseis absorbed insignificantly in the rumen of
ruminants [33]. This may explain its low content in
the bacteria after fermentation of the fodder, but
after the extract had been included into the diet, theconcentration of the element in animalculines
increased.
Analysis of the microbiocenosis of ruminal
content showed that before incubation it had been
represented by bacteria (82.1%) and microscopic
fungi (17.9%) (Table 2).

Table 2 – Taxonomic diversity of the bacterial composition of the ruminal fluid
Group

Taxon
phylumFirmicutes(32.4%)

class
Bacilli(17.3%)
Clostridia(11.1%)
Negativicutes(3.99%)

Proteobacteria(12.8%)
MD

Lactobacillaceae (13.9%)

Lactobacillus (13.9%)

Lachnospiraceae (6.93%)-

Clostridiaceae (4.2%)
Acidaminococcaceae(3.99%)
Moraxellaceae (2.52%)

Faecalibacterium (4.2%)
Succiniclasticum(3.99%)
Acinetobacter (2.52%)

Enterobacteriaceae(10.3%)

Escherichia (5.04%)
Enterobacter (5.25%)
Prevotella (18.1%)

Fibrobacteria(5.04%)

Fibrobacteraceae (5.04%)

Fibrobacter (5.04%)

-

-

-

Other* (19.7%)

Other*(23%)

Other* (42%)

Clostridia(34.8%)

Ruminococcaceae (17.4%)-

Lachnospiraceae (13%)-

Clostridiaceae (4.35%)-

Bacteroidia(30.1%)

Fibrobacteres(5.04%)
Saccharibacteria(18.7%)
Other* (1%)-

Saccharibacteria
(13%)

-

-

-

Bacteroidetes(43.5%)

Bacteroidia(43.5%)

Bacteroidaceae (17.4%)-

Prevotellaceae (26.1%)

Prevotella (26.1%)
Other*(73.9%)

-

MD+En
zyme

genus

Prevotellaceae (19.4%)
Porphyromonadaceae
3.15%)
Bacteroidaceae (7.56%)

Bacteroidetes(30.1%)

Firmicutes(43.5%)
MD+En
zyme+extract

Gammaproteobacte
ria(12.8%)

familyOther*(21.7%)
Clostridia(2%)
Bacteroidia(83.5%)

Other* (21.7%)

Firmicutes(2.11%)
Bacteroidetes
Prevotella
Prevotellaceae (59%)
(85%)
(58%)
Saccharibacteria(5.32%)
Other* (7.6%)
Other* (14.5%)
Other* (41%)
Other* (42%)* This group combines the taxa, with number of each not exceeding 2% of the total

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SEE - Nagoya, Japan, Nov.12-14, 2018

The
bacteriologicalcomposition
wasrepresented by phyla such as Firmicutes (32.4%),
Saccharibacteria (18.7%), Proteobacteria (12.8%),
Fibrobacteres (5.04%), and others (1% from thereference), where the dominant classes were Bacilli(17.3%),
Gammaproteobacteria(12.8%),
Bacteroidia (30.1%), and Clostridia (11.1%).
Species diversity was represented by bacteria
belonging to genera such as g. Lactobacillus(13.9%), g. Prevotella (18.1%), g. Escherichia(5.04%), g. Enterobacter (5.25%), g. Fibrobacter(5.04% of the reference), etc. The most abundant in
the samples were Lactobacillus salivarius (13%),and Prevotella ruminicola (2.94%). The use of the
enzyme in the diet was accompanied by asignificant decrease in the number of bacteria in therumen, which related to the taxa Firmicutes by
30.3% (P≤0.05), Saccharibacteria - by 13.4%, andProteobacteria - up to 2% of the total, and by anincrease in the number of the phylum Bacteroidetes
by 54.9% (P≤0.05) from the reference, which wasreflected in the change in the percentage ofrepresentatives of classes Clostridia, Bacteroidia,
and Bacilli in the microbiocenosis.
For taxa Firmicutes and Proteobacteria, adecreased number was observed for bacteria ofclasses Clostridia (9.1%), Bacilli (less than 2% of
the total) and Gammaproteobacteria (less than 2%of the total). At the same time, an increased numberof bacteria of class Bacteroidia by 53.4% (P≤0,05)
was observed within the Bacteroidetes taxon, which
was mainly due to the increase in representatives ofg. Prevotella ( by 39.9%; P≤0.05). On the contrary,
the use of the enzyme together with the extract inthe diet increased the number of representatives oftaxon Firmicutes by 13.2%, and taxon
Bacteroidetes by 13.4% (P≤0.05), but decreased thenumber of bacteria that belong to phyla
Proteobacteria, Saccharibacteria, and Fibrobacteresup to 2% of the total number in the sample. The
similar effect when using tannin-containing
substances was observed in recent experiments byother researchers as well [34].
An increase was observed in the number ofmicroorganisms belonging to the taxa Clostridia(by 23.7%; P≤0.05) and Bacteroidia (by 13.4%;
P≤0.05). Analysis of the microbiocenosis showed
an increase, compared to the reference, in thenumber of bacteria of g. Prevotella (by 8% of thereference), and a decrease in the number of bacteriaof other genera that were the most numerous in thereference.
Since there is currently no accurate method fordescribing changes in microorganisms in a complex
system such as rumen, this study has been focusedon bacteria. Quercus cortex extract in thecomposition of the fodder contributed to decreasing
the number of cellulosolytic microorganisms(Fibrobacteres). This result is consistent with theprevious studies [35,36,37], where a similar process
was also observed in sheep and rats after
introducing plants (extract) containing tannins into
the diet. The decreased levels of Proteobacteria andFibrobacteres may be explained by different
molecular weights of the substances in the extract,
including tannins [38]; this fact was not consideredin this experiment.
Assessment of acute toxicity with luminescentbacteria showed that during the first five minutes ofcontact with the whole ruminal fluid theluminescence in the control samples is inhibited by
no more than 25% for E. coli pXen7 and up to 20%
for S. typhimurium pACXen, andindicators remain
at the level of control for I and II variants (Figure1). Nevertheless, the use of samplesdiluted two or
more times for these strains removes toxic effectand leads to an increase in luminescence, most
likely associated with a change in membrane
permeability and activation of proton systems due
to acidification of the medium. On the other hand,the biosensor based on B. subtilis EG168-1 also
reacted on the control samples with a drop in
luminescence up to 15%, however, samples of the I
and II variants led to quenching by 65% and 60%,
respectively.
A similar effect was registered earlier [6], it wasestablished that after contact of native ruminal fluidwith bioluminescent E. coli strain, a dosedependent inhibition of luminescence wasregisteredon the first seconds of contact.
Assessment of luminescence on the 60th minuteof contact showed that it exceeded the control by
35%for E. coli pXen7 in the case of samples of thesecond variant, indicating a restoration of
luminosity and no bactericidal effect,. In general,similar effects were recorded for S.typhimurium
pACXen, - luminescence was restored in control
variants, in the samples with the extract, aluminescence was observed, only variants with a
vervum were characterized by a 19.5% drop.
Studies are known [39] with positive effects ofinhibition against E. coli isolated from cattle arefound against the background of Caryocar
brasiliense plant extracts. In this case, the role oftannins in the manifestation of antibacterial effects
was registered. In our case, the results of studies
using ruminal fluid of cattle are presented. A highinhibitory effect of Quercus infectoria gall extracts
against Staphylococcus aureus was also observed in
the study of antibacterial activity in vitro [40].
A different picture was developed for B. subtilis
EG168-1, where the luminescence of the control
sample exceeded the initial level 8 times, in the firstvariant - 1.6 times, and the II variant inhibited theluminescence by 32%. Moreover, the second
variant in the case of B.subtilis biosensor was

122

SEE - Nagoya, Japan, Nov.12-14, 2018

characterized by the absence of a luminescencedependence on the sample concentration. The dataobtained are in agreement with the studies [41],where positive results were registered whenevaluating the antibacterial activity of the oak
extract against B. subtilis.

Luminescence index, I(test)/I (control)

1.2
1
0.8
0.6
0.4
0.2
0
E.coliS.typhimurium

B.subtilis

control
control (ruminal fluid)
variant I (ruminal fluid + exogenous enzyme)
variant II (ruminal fluid + phytoextract + exogenous enzyme)

Fig. 1 Luminescence of bacterial biosensors on the fifth minute in the presence of ruminal
fluid from cows with various feeding factors.

CONCLUSION
The chemical composition of Quercus cortex
extracthas a significant effect on the elemental
profile of cattle rumen microorganisms. At thesame time, the introduction of the extract into thediet does not change the overall bacterial structureof rumen microflora. The ratio of phyla Firmicutes
and Bacteroidetes, the parameter associated withthe energy accumulation function, was increased,same as the number of microorganisms thatbelonged to the taxon Clostridia. Further study isrequired for assessing the influence of plant extracts
on ruminal microorganisms and changing the
products of fermentation associated with the
productivity of animals. The biosensor based on B.
subtilis EG168-1 reacted more actively to theintroduction of the extract into ruminal fluid.
Further work is required to assess the effect ofindividual components of plant extracts on ruminal
microorganisms and changes in fermentation
products associated with animal productivity.

This research was performed with financial support
from the Russian Science Foundation (project No.
16-16-10048).
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[38] Saminathan M., Sieo C.C., Gan H.M., Ravi S.,
Venkatachalam K., Abdullah N., Wong C.M., andHo Y.W. Modulatory effects of condensed tannin
fractions of different molecular weights from a
Leucaena leucocephala hybrid on the bovine
rumen bacterial community in vitro. J Sci Food
Agric. Oct;96(13), 2016, pp.4565-74.
[39] de O Ribeiro I.C., Mariano E.G.A., Careli
R.T., Morais-Costa F., de Sant'Anna F.M., Pinto
M.S., de Souza M.R. and Duarte E.R. Plants of
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30;14(1): p.32.
[40] Wan Nor Amilah W.A., Masrah M., Hasmah A.
and Noor Izani N.J. In vitro antibacterial activityof Quercus infectoria gall extracts against
multidrug resistant bacteria. Trop Biomed. 2014,
Dec;31(4): pp.680-8.
[41] Qadir M. A., Shahzadi S. K., Bashir A., Munir
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Chem. 2017; 2017: p.3475738.

1254th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

STUDY OF THE UTILIZATION OF CU(II) MODIFIED LIQUIDSMOKE TO INHIBIT THE GROWTH OF FUNGI (SCHIZOPHYLLUMCOMMUNE)

Muhammad Faisal1, Shara Utari2, Zammera Hayvia2, and Ilham Maulana2
Department of Chemical Engineering, Engineering Faculty, Syiah Kuala University, Banda Aceh,
Indonesia; 2Department of Chemistry, Faculty of Mathematics and Natural Sciences, Syiah Kuala University,
Banda Aceh, Indonesia
1

ABSTRACTThis study aims to examine the possibility of utilizing Cu(II) modified liquid smoke as an antifungal agent
against Schizophyllum commune Fr. in a laboratory test. The liquid smoke was obtained through the pyrolysis ofoil palm kernel shells at 300°C, 340°C, and 380°C. The analysis of liquid smoke as an antifungal agent was
performed using potato dextrose agar (PDA) media and nystatin as positive controls. The white-rot fungi of
Schizophyllum commune Fr. were isolated from fungally infected wood and regenerated for 5x24 hours.
Observation of the inhibiting zone was done in 24 hours. The results showed that the presence of Cu(II) can
increase the inhibiting zone of white rot fungus. The Cu(II)-modified liquid smoke was able to significantly
inhibit the growth of white-rot fungi even in low liquid smoke concentrations. The highest inhibiting zone of
Schizophyllum commune Fr. was obtained with 3% Cu(II)-modified liquid smoke (obtained from a pyrolysis
temperature of 380°C).
Keywords: Liquid smoke, Wood damage, White-rot fungi, Inhibiting zone, Antifungal[17]-[19]. These compounds are made syntheticallyusing several metal combinations. However, some ofthese substances have been discontinued because
they are detrimental to the environment due to theirdangerous metal contents, such as arsenic andchromium. Copper (Cu) has the best antimicrobial
properties that do not harm the environment. A
combination of organic biocides with antioxidants,
such as metal, provide prospective alternatives in thedevelopment of wood-preserving materials [20].
This research is a preliminary study on the effect ofCu(II) modified liquid smoke. as an antifungal agent
against Schizophyllum commune Fr. in-vitro, whichis expected to benefit the wood preservation industry
by discovering an environmentally friendly
alternative to preserving wood.

INTRODUCTION
Liquid smoke is produced from the condensationof smoke resulting from the pyrolysis of wood
containing acid, phenol, and carbonyl compounds[1], [2]. These compounds act as antibacterial [3],antifungal [4], [5], biopreservative [6], antioxidant[7], insecticide [8], and flavoring agents [9]-[11].
Compounds such as phenol and derivatives ofcarboxylate acid can produce differences in
antifungal activities [12], [13]. Velmurugan et al.
[14] report that their research shows that liquidsmoke can inhibit the growth of Ophiostoma
polonicum, O. flexuosum, O. narcissi, and O.
tetropii. This means that liquid smoke has thepotential to be used as an alternative for preserving
wood because it can control microorganisms such as
fungi and termites. The main compounds in liquidsmoke are phenolic and organic acid, which canwork effectively to control microbial growth andincrease the wood’s resistance to fungi, such as
white-rot (Schizophyllum commune Fr.). The whiterot fungus is capable of degrading lignins and woodcomponents [15], making the wood brittle andsignificantly reducing the elasticity of its fibers.
Moreover, this fungus grows quickly and easily, so
it requires effective handling.
Current and commonly used wood preservatives
are chromated copper arsenate (CCA) [16], copperazole (CuAz), and alkaline copper quaternary (ACQ)METHODOLOGY
Processing the Liquid Smoke
The liquid smoke was produced based on
previous research [4], [21]. Thus, 5 kg of oil palm
kernel shells were processed in a pyrolysis reactor
made of stainless steel with temperatures set
between 300°C and 380°C. The resulting smoke wasthen condensated into a liquid called liquid smoke,which was then left for one day to separate from thetar content. The liquid smoke was then filteredthrough filtering paper to remove dirt and dust
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SEE - Nagoya, Japan, Nov.12-14, 2018

before it was analyzed using Gas Chromatography
Mass Spectrometry (GCMS-QP2010, Shimatsu,
Japan).

shown in Figure 1. There are two possible reactions
between the copper and the organic compounds,
since the liquid smoke that have the potential to
become ligands, such as carbonyl derivatives ofaniline, which are capable of forming complex
compounds. First, these liquid smoke compounds
play important roles in metal binding. Phenol canbind metal with its hydroxyl group, whereas
carbonyl and acid can bind metal with their carbonyland carboxylate groups. These organic compounds
donate multiple free electron pairs (chelation).
Second, copper is reduced from oxidation +2 to 0
due to the carboxylate’s derivatives acting as
redactors. This is shown in the color change seen
when it returned to its basic, liquid smoke color after
a while and from the presence of small particles thatmade the solution cloudy. These fine particles
signify the formation of Cu(0) in very small amounts
within the liquid smoke.

Preparing the Cu(II)-Modified Liquid Smoke
The concentrations of liquid smoke used to test
the antimicrobial effectiveness were 1%, 2%, and3%. Each concentration was added into a CuSO4
solution to create a Cu content of 0.2 M before it
was homogenized. This Cu-modified liquid smoke
was then characterized using an Fourier Transform
InfraRed (FT-IR) test.
Processing the Potato Dextrose Agar (PDA)
Solution
As much as 3.9 g of PDA powder was poured
into an Erlenmeyer before 100 mL of distilled water
was added. This solution was then heated on a hot
plate with occasional stirring to mix the content well.
The Erlenmeyer was then covered with cotton andpaper and sterilized in an autoclave at 121ºC for 15
minutes [22].
Isolating the White-Rot Fungi
The fungi were extracted from the infectedwood, cleaned and isolated in the PDA for 4-7 days,
then inoculated into a new PDA for another 4-7 days
before it was suspended in a Potato Dextrose Broth(PDB). Afterwards, it was homogenized in a shaker
for 4×24 hours. Finally, the fungi were placed undera microscope to identify their hypha.

(a) before mixing
Fig. 1(b) Cu-Liquid smoke

The liquid smoke’s changes in color.

Testing the Effectiveness of Liquid Smoke against
Schizophyllum Commune Fr. Fungi
Sample testing was carried out using the
diffusion disk method on paper disks with 6mm
diameters. As much as 100 μl of the fungi’s pureisolates were extracted and evenly dripped onto the
PDA media using a triangle stir bar. Then, they
were left for ±15 minutes. Afterwards, each paper
disk was dipped into the 1%, 2%, and 3% Cu(II)modified solutions and left for ±10 minutes to dry atroom temperature. The discs were then lined up on
the surface of the testing media using tweezers andincubated at room temperature for 24 hours.
Afterwards, the clear-colored area that formed oneach disc was analyzed [23].

(a)RESULTS AND DISCUSSION
Characteristics of Cu(II) in Liquid Smoke Using
FT-IR

(b)

When the liquid smoke reacted with the 0.2 M of
Cu(II) sulphate, it resulted in the color changes

Fig. 2 FT-IR results: (a) Liquid smoke, (b) Cu (II)modified liquid smoke
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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Inhibition zone testing of liquid smoke(temperature pyrolysis of 300ºC)

The FT-IR test results are shown in Figure 2.
The bonding between the liquid smoke and the Cu(II) is indicated by the shifts and peaks recorded. In
Figure 2(a), the peaks are recorded at 3355.9 cm-1
(signifying O-H (alcohol)), 1636.91 cm-1 (signifying
C-C (aromatic)), 1387.66 cm-1 (signifying C-H(alkyl)), 1270 cm-1 (signifying C-O (phenol)), and1015 cm-1 (signifying C-O). In Figure 2(b), the IR
spectrum does not indicate meaningful changes inwave numbers, but the shifts in the peaks signify thebinding of new compounds after adding Cu(II)sulphate into the liquid smoke. The shift from 1701
cm-1 to 1636 cm-1 and at 1274 cm-1 also signifies
missing groups (-C-O). The new peak at 1989.96
cm-1 signifies reactions occurring. Wen et al. [26]state that the shifts indicate changes in functionalgroups.

Treatment

Inhibition zone(mm)

Control (+)

23.3

Liquid smoke 1 % + CuSO4

21

Liquid smoke 2 % + CuSO4

22

Liquid smoke 3 % + CuSO4

24

CuSO4

15.3

Liquid smoke 2%

19.3

Control (-)

0

Table 2 Inhibition zone testing of liquid smoke(temperature pyrolysis of 340ºC)

Testing Liquid Smoke Against White-Rot Fungi
The diffusion disc method was used to test theCu(II)-modified liquid smoke against the white-rot
fungi. The effectiveness of the liquid smoke wasshown by the formation of an inhibiting zone, which
was a clean or clear area around the antifungal
agent. The inhibiting zone was then compared withthe diameters of the positive control, nystatin, andthe negative control, distilled water.
The analysis showed that the modified liquidsmoke’s concentration level had a significant
impacted on the resulting antifungal index: thehigher the concentration, the higher the index was.
This was seen from the formation of inhibiting zones
on the discs in each concentration variation, whereina stronger concentration produced a wider diameter.
The liquid smoke that was formed from oil palm
kernel shells had antibacterial and antifungal
properties due to its alcohol, phenol, and organicacid compounds. Its antimicrobial properties weresuspected to be able to disrupt the cytoplasm of
fungal by destroying the membrane’s surfacepressure, causing a loss of active transport throughthe membrane and destabilizing various cellfunctions and structures.
The fungal growth inhibiting zones for thevarious concentrations of liquid smoke are shown in
Tables 1-3. The copper-modified liquid smoke hadsignificant effects on the diameters of the fungal
growths. The inhibiting zones that formed using 1%,2%, and 3% of the copper-modified liquid smokethat was formed from pyrolysis at 300ºC had
diameters of 21 mm, 22 mm, and 24 mm (onaverage), respectively. The inhibiting zones formed
using the same concentrations of copper-modified
liquid smoke that were formed from pyrolysis at
340ºC had diameters of 22.3 mm, 23.6 mm, and 26
mm, respectively.

Treatment

Inhibition zone(mm)

Control (+)

23.3

Liquid smoke 1 % + CuSO4

22.3

Liquid smoke 2 % + CuSO4

23.6

Liquid smoke 3 % + CuSO4

26

CuSO4

15.3

Liquid smoke 2%

19.3

Control (-)

0

Table 3 Inhibition zone testing of liquid smoke(temperature pyrolysis of 380ºC)
Treatment
Inhibition zone(mm)
Control (+)

23.3

Liquid smoke 1 % + CuSO4

24.5

Liquid smoke 2 % + CuSO4

26

Liquid smoke 3 % + CuSO4

27.3

CuSO4

15.3

Liquid smoke 2%

19.3

Control (-)

0

Pyrolysis at 380ºC resulted in inhibiting zone
diameters of 24.3 mm, 26 mm, and 27.3 mm,
respectively. The inhibiting zones formed using 2%
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SEE - Nagoya, Japan, Nov.12-14, 2018liquid smoke and .02 M of CuSO4 had diameters of
15.3 mm and 19.3 mm, respectively, while thepositive and negative controls formed inhibitingzones of 23.3 mm and 0 mm in diameter,
respectively. The antifungal property tests conductedon the Cu-modified liquid smoke showed the highest
inhibiting zones at a pyrolysis temperature of 380ºC.
Oramahi et al. [27] stated that liquid smoke
produced from oil palm trunks (pyrolysed at 350°C)
can inhibit the growth of the white-rot fungus, T.
versicolor, at concentrations of 1.5%.

Anthracnose Disease on Chili (Capsicum
annum L.). Journal of Engineering and Applied
Sciences, Vol.11, Issue. 12, 2016, pp. 25832587.
[5] Ariestya, D.I., Swastawati, F. and Susanto, E.,
Antimicrobial Activity of Microencapsulation
Liquid Smoke on Tilapia [Oreochromis
Niloticus (Linnaeus, 1758)] Meat for
Preservatives in Cold Storage (±5 C°). Aquatic
Procedia, Vol.7, 2016, pp.19-27.
[6] Faisal M., and Gani A. The Effectiveness of
Liquid Smoke Produced from Palm Kernel
Shells Pyrolysis as a Natural Preservative inFish Ball. International Journal of GEOMATE,
Vol. 15 Issue 47, 2018, pp. 145-150.
[7] Faisal M., Gani A., Husni, and Daimon H., A
Preliminary Study of the Utilization of Liquid
Smoke from Palm Kernel Shells for Organic
Mouthwash.
International Journal of
GEOMATE, Vol. 13 Issue 37, 2017, pp. 116120.
[8] Gani, A., Husni, H., Baihaqi, A. and Faisal, M.,
Potential Development of Liquid Smoke fromOil Palm Solid Waste as Biofungicides.
International
Journalof
ScienceandEngineering, Vol.7, Issue 1, 2014, pp.65-69.
[9] Tian, J., Zeng, X., Feng, Z., Miao, X., Peng, X.
and Wang, Y., Zanthoxylum Molle Rehd.
Essential Oil as a Potential Natural Preservativein Management of Aspergillus flavus. Industrial
Crops and Products, Vol. 60, 2014, pp.151-159..
[10] Varlet V., Serot T., and Prost C., Smoke
Flavoring Technology in Seafood. In Nollet
LML, Toldra F. (Eds.), Handbook of seafoodand seafood products analysis Boca Raton, FL:
CRC Press. 2010, pp. 233-254.
[11] Guillen M.D., and Ibargoitia M.L., New
Components with Potential Antioxidant andOrganoleptic Properties, Detected for the FirstTime in Liquid Smoke Flavoring Preparations.
Journal of Agricultural and Food Chemistry,
Vol. 46, Issue 44, 1998, pp. 1276-1285[12] Oramahi, H.A., Diba, F. and Yoshimura, T.,
Optimization of Production of Lignocellulosic
Biomass Bio-Oil from Oil Palm Trunk.
Procedia Environmental Sciences, Vol. 28, 2015,
pp.769-777.
[13] Oramahi, H.A. and Yoshimura, T., Antifungaland Antitermitic Activities of Wood Vinegarfrom Vitex Pubescens Vahl. Journal of woodscience, Vol. 59, Issue 4, 2013, pp.344-350.
[14] Velmurugan, N., Han, S.S. and Lee, Y.S.,
Antifungal Activity of Neutralized Wood
Vinegar with Water Extracts of Pinus
Densiflora and Quercus Serrata Saw Dusts.
International
JournalofEnvironmental
Research, Vol. 3, Issue 2, 2009, pp.167-176.
[15] Zhang, Z., Yang, T., Mi, N., Wang, Y., Li, G.,
Wang, L. and Xie, Y., Antifungal activity of

CONCLUSION
Liquid smoke formed from the pyrolysis of oilpalm kernel shells at various temperatures has thepotential to be used as an antifungal agent against
Schizophyllum commune Fr., as proven by the
inhibiting zones that formed around the fungal
growths. The copper-modified liquid smoke
displayed significant effects in producing effective
inhibiting zones, which are equally effective
compared to the liquid smoke concentrations. This
research shows that copper-modified liquid smoke
can be categorized as a powerful and effective
antifungal agent due to its ability to produce ≥20mm inhibiting zones.
ACKNOWLEDGEMENTS
The authors would like to acknowledge andthank the Ministry of Research, Technology, andHigher Education of Indonesia and Syiah Kuala
University for the research funding (Contract
no.57/UN11.2/PP/SP3/2018).
REFERENCES[1] Zuraida, I. and Budijanto, S., Antibacterial
Activity of Coconut Shell Liquid Smoke (CSLS) and Its Application on Fish Ball
Preservation. International Food Research
Journal, Vol. 18, Issue 1, 2011, pp. 405-410.
[2] Faisal M., Chamzurni T., and Daimon H., A
study on the Effectiveness of Liquid Smoke
Produced from Palm Kernel Shells in Inhibiting
Black Pod Disease in Cacao Fruit In Vitro.
International Journal of GEOMATE, Vol. 14
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[3] Saloko, S., Darmadji, P., Setiaji, B. and Pranoto,
Y.,. Antioxidative and Antimicrobial Activitiesof Liquid Smoke Nanocapsules Using Chitosan
and Maltodextrin and Its Application on TunaFish Preservation. Food Bioscience, Vol.7,
2014, pp.71-79.
[4] Faisal M, Gani A, Husni, Baihaqi A, Daimon H.,
Pyrolysis of Oil Palm Kernel Shell into Liquid
Smoke and Its Application to Control
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SEE - Nagoya, Japan, Nov.12-14, 2018

monoterpenes against wood white-rot fungi.
International Biodeterioration & Biodegradation,
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[16] Ahn, S.H., Oh, S.C., Choi, I.G., Han, G.S.,
Jeong, H.S., Kim, K.W., Yoon, Y.H. and Yang,
I.,
Environmentally
Friendly
Wood
Preservatives Formulated with EnzymaticHydrolyzed Okara, Copper and/or Boron Salts.
Journal of hazardous materials, Vol.178, Issue
1-3, 2010, pp.604-611.
[17] Gerengi, H., Tascioglu, C., Akcay, C. andKurtay, M., Impact of Copper Chrome Boron(CCB) Wood Preservative on the Corrosion of
St37 Steel. Industrial & Engineering Chemistry
Research, Vol. 53, Issue 49, 2014, pp.1919219198.
[18] Hingston, J.A., Collins, C.D., Murphy, R.J. andLester, J.N., Leaching of Chromated Copper
Arsenate Wood Preservatives: A Review.
Environmental Pollution, Vol. 111, No. 1, 2001,
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[19] Freeman, M.H. and McIntyre, C.R., A
Comprehensive Review of Copper-Based Wood
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Issue 11, 2008, pp. 6-27.
[20] Schultz, T.P. and Nicholas, D.D., Developmentof Environmentally-Benign Wood Preservatives
Based on the Combination of Organic Biocides
with Antioxidants and Metal Chelators.
Phytochemistry, Vol. 61, Issue 5, 2002, pp.555560.

[21] Faisal M., Gani A., and AbuBakar, Removal of
Copper Ions from Aqueous Solution using Palm
Shell
Charcoal
Activatedby NaOH,International Journal of GEOMATE, Vol. 15
Issue 48, 2018, pp. 143-147.
[22] Berlian,Z., Aini, F., and Lestari, W.. Aktivitas
Antifungi Ekstrak Daun Kemangi (Ocimum
americanum L.) Terhadap Fungi Fusarium
oxysporum Schlecht. (In Indonesia), Jurnal
Biota, Vol. 2, Issue 1, 2016, pp.99-105.
[23] Sutton, S., Determination of Inoculum forMicrobial Testing. Microbiology Topic, Vol. 15,
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[24] Maga, J.A., The Flavor Chemistry of Wood
Smoke. Food Reviews International, Vol.3,
Issue 1-2, 1987,mpp.139-183.
[25] Girard, J.P., Technology of Meat and Meat
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[26] Wen, Y., Huang, W., Wang, B., Fan, J., Gao, Z.,
and Yin, L. Synthesis of Cu Nanoparticles forLarge-scale Preparation. Materials Science andEngineering: B, Vol. 177, Issue 8, 2012, pp.
619-624.
[27] Oramahi, H.A., Yoshimura, T., Diba, F. and
Setyawati, D., Antifungal and Antitermitic
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2018, pp.311-317.

130

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

SHORT-TERM EFFECTIVENESS OF INNOVATION PILLOW RELAXTO STRESS AND HEART RATE VARIABILITY IN THE ELDERLY
Peerada Damapong1, Pongmada Damapong1,
1College of Allied Health Science Suan Sunandha Rajabhat University, Bangkok 10300, Thailand

ABSTRACTThis research aims to innovate a relaxing pillow for elders, and study short-term effectiveness of theaforementioned pillow innovation regarding reduction of stress and heart rate variability among elders. This
research is a Quasi–Experimental Research. Volunteers comprise of elders suffering from stress, selected
through a survey on stress level. There are 19 individuals whose SPST–20 is higher than 3 . The relaxing
pillows were provided to all volunteers to nap on for the duration of 10 minutes per day for 3 consecutive days.
The assessment measures heart rate variability using Hear Rate Variability (HRV) machine both before and after
the experiment. The research reveals a difference in results of Heart Rate Variability (HRV) comparatively,
before and after. It appears that the SDNN value has increased significantly (P<0.05). From the research, it canbe concluded that the relaxing pillow innovation helps increase the parasympathetic nerve pathway’s function,
thus reducing the volunteers’ stress level. It decreases factors related to stress level and helps creates positive.

change among stressed elders

Keywords: Effectiveness, innovation, pillow relax, stress, heart rate variability, the elderly

Mental relaxation is also another thing to be worked
on simultaneously with physical relaxation. For stressmanagement, WHO has created Guidelines for theManagement of Conditions Specifically Related toStress to serve as a guideline and standard for stressmanagement [5]. This is applicable to patients withstress, both through medication, alternative approach,or natural healing. There are also herbal treatment andaromatherapy as another alternative in treating
patients with stress [6]Due to this issue, the researcher is therefore
interested in developing a relaxing pillow innovation
to help treat stress among elders, and study the shortterm effectiveness of pillow innovation in reducing
stress and heart rate variability among elders. The
results can be used to address stress among elder
people.

INTRODUCTION
Stress is a health issue that can occur to any
individuals. It is a reaction of the body, the mind,
thoughts, and behavior of a person to both external
and internal stimuli. The stimuli may be anotherindividual, thoughts, circumstance or theenvironment. An individual would recognize athreatening and high pressure situation. If one fails toadapt, then the person would feel stress. This may
impact their life balance as they live in society. In the
study by World Health Organization (WHO) on a
global scale of situations or pain related to the levelof stress and mental health, it appears that being awitness to violent acts comprises 21.8%, being
involved in interpersonal violence 18.8%, having an
accident 17.7%, experiencing warfare 16.2%, andhaving a loved one who is a victim of trauma
12.5%.[1] Among elders, stress is an important factor
affecting their health [2]. If an elder became stress, it
may lead to insomnia and depression respectively.[3]The likelihood of stress among elders is increasing
continuously. Thai society is moving forward
towards an ‘elderly society.’ Therefore, it is importantto place an emphasis on stress among elders [4]. The
older humans become, the more stress they are.
Elders are the age of changes, both physically andmentally. This can directly induce stress. Relaxation
methods are simple, and one of the most effective
methods is to sleep for the body to restore itself.

MATERIALS AND METHODS
DesignThis research is a Quasi – Experimental Researchand took place at the Health Clinic build to honor theLate His Majesty for coming to 60 years old, in Bang
Khan Tak sub-district, Meung District, SamutSongkram.
This research has been approved by the ethics
committee for researches with humans, bySirindhorn College of Public Health, Khon Khaen(number 80/2561, number HE 610661).
.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Phase 3 Effectiveness of the relaxing pillow
innovation
From the experiment in using relaxing pillow
innovation, the results can be analyzed and converted
to collect data on the innovation’s effectiveness.

Participants
The sampling group comprises of elders at least
60 years old with stress. They were identified
through a survey inquiring of their stress level.
There are 19 individuals whose SPST–20is higher.than 3. In this research, the Inclusion criteria is asfollows: Males or females, of at least 60 years old,with the stress level of at least 3. They must be able
to travel on their own to participate in the program.
The Exclusion criteria is as follows: those withsevere contagious diseases, depression, infection,
migraine, nausea, allergic to Aromatherapy, andthose taking medicines affecting the nervous and theheart system, such as sleeping and calming
Intervention
Volunteers received a relaxing pillow innovation,
and are requested to use it during the nap for 10
minutes per day for 3 consecutive days. They would
use a private room, with the room temperature at 25
degrees, with no odor or noise to disturb, or
impacting their nervous system, mental and physicalhealth.
Measurement Instruments
The tools used in the research Suanprung Stress
Test 20 (SPST-20), satisfactory surveys, and Heart
Rhythm Scanner PE (Biocom Technologies, USA)for measurement the heart rate variability (HRV).
Procedures
The process composites of 3 phrases, as follows:
P has 1 Develo p ment o f r elaxing p illo w
innovation
1.1 Study fundamental information withregards to pillows, properties of coconut fiber, andjasmine oil in stress treatment
1.2 Utilize the information in the developmentof relaxing pillow case for elders, by designing anddeveloping a prototype
1.3 Test the prototype in a representative
groups similar to the targeted sample group
1.4 Make use of the test results and feedback
for further improvement. Develop the second
prototype for usage with the sample group.
Phase 2 Test the relaxing pillow innovation
Researchers recruit volunteers meeting thecriteria to participate in the project and provide theresearch details to volunteers. Volunteers wereselected according to inclusion criteria, and wererequested to respond surveys with regards to personal
information and stress information. Once a volunteer
is officially selected, the researchers would thenallow the volunteer to sign in for participation.
Afterwards, volunteers would be tested prior
to treatment, via Suanprung Stress Test 20 (SPST20) a n d Heart rate variability (HRV) test. Once thepre- treatment assessment is completed, volunteers
will receive the relaxing pillow innovation to use for10 minutes per days for 3 consecutive days. Variables
will be measured before and after the treatment. The
assessment should take only 15 minutes in total.

Statistical Analysis
Descriptive statistics is used to explain thecharacteristics of volunteers, average, the standard
deviation. Analysis of the pre- and post- variables
are conducted using paired t-test, setting the level ofstatistical significance (α) at less or equal to 0.05.
RESULTS
The study results can be divided into 3 phases.
Results in phase 1: development of relaxing
pillow innovation for elders, using researches
information on
the appropriate coconut fiber,
appropriate size of pillow, anatomical science andergonomics. The research eventually yields a relaxing
pillow case, whose design has a hold in the middle tosupport the neck and the head. The stuffing of thepillow is made with coconut fiber and candle-roasted
jasmine, providing a calming scent. For the test, a
representative groups, of 10 people, similar to thetarget groups was studied. Results of the test was used
for the first improvement. The test reveals that thepillow was too hard. Furthermore, because of thehole, the stuffed coconut fibred is too packed, andcandle-roasted jasmine was too diluted. For the new
design, there is no holes and the aroma was changed
to 100% jasmine oil.
Upon implementation, the results can be
developed for the second time. The pillow is adjusted
to have flexibility, and to have larger gap for aromaoil. It
becomes the prototype. For the 3rd
improvement, the functional features become evenmore convenient, resulting in the final relaxing
pillow innovation for elders.
Phase 2 of the study: Testing relaxing pillow
innovation, and Phase 3: Effectiveness of therelaxing pillow innovation.
Results of the study on participating volunteers’
characteristics.
Personal information of the research reveals thatthe majority of the sampling group is at 64-67 years
old, 26.3%; mostly are female at 63.2%, and males at
36.8%. Most of the volunteers are married at 57.9%
Test results comparing the Heart rate variability(HRV)
The research results compare the average Heartrate variability by studying Time Domain Analysis is
SDNN an Frequency Domain Analysis, which are:
LF, HF. By comparing the pre- and post-test result, it
appears that SDNN, LF and HF increase significantly(P<0.05) in Table 1.

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Table 1 Compare outcome measures between before
and after the treatment
OutcomeBaseline(Mean± SD)(N=19)

Short-term
effectiveness(Day 3)(Mean± SD)

P-valueHeart ratevariability(HRV)- SDNN(Ms)

52.93±56.48

60.33±57.36< 0.05*- LF (ms2)4.49±2.04

4.36±1.67

0.005*- HF (ms2)4.34±2.01

4.26±1.67

0.010*

Massage versus Amitriptyline in Patients with
Chronic Tension-Type Headache. A study for thosewith stress-induced migraine. By measuring the heart
rate variability (HRV) both before and after thetreatment, it appears that the treatment using CourtType Traditional Thai Massage shows changes in theheart rate variability =, demonstrating an increased
work by parasympathetic nervous system (P < 0.05)[ 10]. The result here explains why relaxing pillow
innovation and jasmine aromatherapy helps increaseparasympathetic nervous system, reducing elders’stress level.
CONCLUSION
Study of short-term effectiveness of relaxing
pillow innovation in reducing stress and heart
variability among elders, by measuring before andafter the test the heart rate variability, it appears that
the SDNN has increased with statistical significance.
After receiving a relaxing pillow innovation,
volunteers became less stress (more relaxed). It cantherefore be concluded that the use of relaxing pillow
case with jasmine aromatherapy helps increase theparasympathetic nervous system’s function. This
enables a stressed individual to become less stressed.
It also decreases variables correlating to stress, andtherefore creates positive changes among stressed
elders.

Note.* 𝑃𝑃 < 0.05 is statistically significant
differences as compare between before and after thetreatment from baseline.
DISCUSSION
From the pre- and post-test result, uponcomparison, it appears that the SDNN value has
increased with statistic significance (P<0.05). The
result affects the parasympathetic nerve, reducing thestress according to the research by Lee YT, 2016.
There was a study of the effect of lavender floralwater eye-mask aromatherapy on the autonomous
nervous system, which reveals that, based on the NN
data analysis, the relationship weightings of thepsychological factors regarding the autonomic
nervous system increased from 1.6 to 9.1 times
following the eye-mask aromatherapy. Furthermore,
the physical stress index decreased by 33.5% and thetotal degree of HRV went up by 44.5%, whichshowed that the lavender floral-water eye-mask
aromatherapy resulted in the relief of stress. In
addition, there was improvement with regard to thecondition of the autonomic nervous system as can beseen by the LF/HF ratio being closer to the normal
value for people in good health [7]. This is consistent
with the study by Yang et al., 2015 on Comparison of
the efficacy of aroma-acupressure and aromatherapy
for the treatment of dementia-associated agitation.
The study reveals that, in comparison to the control
group, the results of the HRV test for the sympathetic
nervous system showed that the LF/HF ratio wassignificantly higher in the aroma-acupressure group[ 8]. Relaxing pillow innovation helps relax muscles,
and therefore reduce the stress level. There isconsistency with the research by Peerada Damapong
et al., 2 0 1 6 . The study was on Short-term effects of
Court-type Traditional Thai massage on Pressure
Pain Threshold and pain intensity in patients with
Chronic tension-type headache [ 9]. It is also in
consistent with the research by Peerada Damapong etal, on A Randomized Controlled Trial on the
Effectiveness of Court-Type Traditional Thai

ACKNOWLEDGEMENTS
This publication has been supported by Suan
Sunandha Rajabhat University, Bangkok, Thailand.
REFERENCES[1]. Stein, D.J., Chiu, W.T., Hwang, I., Kessler,
R.C., Sampson, N., Alonso, J., Borges, G., Bromet,
E., Bruffaerts, R., de Girolamo, G., Florescu, S.,
Gureje, O., He, Y., Kovess-Masfety, V., Levinson,
D., Matschinger, H., Mneimneh, Z., Nakamura, Y.,
Ormel, J., Posada-Villa, J., Sagar, R., Scott, K.M.,
Tomov, T., Viana, M.C., Williams, D.R., Nock,
M.K. Cross-national analysis of the associations
between traumatic events and suicidal behavior:findings from the WHO World Mental Health
Surveys. PLoS One. 2010 May 13;5(5):e10574.
[2]. Luchesi BM, Souza ÉN, Gratão ACM, Gomes
GADO, Inouye K, Alexandre TDS, et al. The
evaluation of perceived stress and associated factors
in elderly caregivers. Vol. 67, Archives ofGerontology and Geriatrics. 2016. p. 7–13.
[3]. Liu Y, Li T, Guo L, Zhang R, Feng X, Liu K. The
mediating role of sleep quality on the relationshipbetween perceived stress and depression among theelderly in urban communities: a cross-sectional study.
Public Health. 2017;149:21–7.
[4]. Ministry of Public Health. Public healthstatistics A.D.2015. Strateg Plan Div [Internet].
133

SEE - Nagoya, Japan, Nov.12-14, 20182016;8(5):781–8. Available from:http://dx.doi.org/10.1016/j.eujim.2016.05.008[8]. Yang MH, Lin LC, Wu SC, Chiu JH, Wang PN,
Lin JG. Comparison of the efficacy of aromaacupressure and aromatherapy for the treatment ofdementia-associated agitation. BMC Complement
Altern Med. 2015;15(1):1–8.
[9]. Damapong, P. Kanchanakhan, N.
Eungpinichpong, W., Putthapitak, P, and Damapong
P., Short-Term Effects of Court-Type Traditional
Thai Massage on Pressure PainThreshold and Pain
Intensity in Patients with Chronic Tension-Type
Headach. International Journal of GEOMATE.vol.
11, no. Dec., 2016..
[10]. Damapong P, Kanchanakhan N,
Eungpinichpong W, Putthapitak P, Damapong P. A
Randomized Controlled Trial on the Effectiveness of
Court-Type Traditional Thai Massage versus
Amitriptyline in Patients with Chronic Tension-Type
Headache. Evidence-based Complement Altern
Med. 2015;2015.

2016;233.Availablefrom:http://bps.moph.go.th/new_bps/sites/default/files/hea
lth_statistic2558.pdf[5]. World Health Organisation. Guidelines for theManagement of Conditions Specifically Related toStress. Assess Manag Cond Specifically Relat toStress mhGAP Interv Guid Modul (version 10)[Internet]. 2013;1–273. Available from:http://www.ncbi.nlm.nih.gov/pubmed/24649518[6]. Hozumi H, Hasegawa S, Tsunenari T, Sanpei N,
Arashina Y, Takahashi K, et al. Aromatherapies
using Osmanthus fragrans oil and grapefruit oil are
effective complementary treatments for anxious
patients undergoing colonoscopy: A randomized
controlled study. Complement Ther Med [Internet].
2017;34(February):165–9. Available from:http://dx.doi.org/10.1016/j.ctim.2017.08.012[7]. Lee YT. A study of the effect of lavender floralwater eye-mask aromatherapy on the autonomous
nervous system. Eur J Integr Med [Internet].

134

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECTIVENESS OF HERBAL STEAM FOR REDUCING STRESS IN
PATIENTS DIABETICS
Pongmada Damapong1 and Peerada Damapong1
1College of Allied Health Science Suan Sunandha Rajabhat University, Bangkok 10300, Thailand

ABSTRACTThis research aims to study the immediate effectiveness of herbal streaming in reducing stress among type 2
diabetic patients. This research is a Quasi – Experimental Research. The volunteers are type 2 diabetic patientswith stress, who were selected basing on the questionnaire measuring the stress level. There were 30 people
tested for SPST-20 at higher than Level 3. The volunteers received herbal stream treatment for 30 minutes. There
were 2 sessions, 15 minutes each; alternating with a 5 minute rest outside. The heart rate variability will bemeasured with a Heart Rate Variability (HRV) Machine both before and after the experiment. Results on Heart
Rate Variability (HRV) was conducted using a Time Domain Analysis, which are SDNN, RMS-SD; and a
Frequency Domain Analysis, which are: LF, HF, LF/HF. A comparison before and after the experiment reveals
that the values of SDNN, RMS-SD and LF/HF have increased with statistical significance (P<0.05). From thestudy results, it can be concluded that herbal steaming helps increase the functions of parasympathetic nervous
system, enabling individuals’ stress to reduce. This helps ameliorate factors related to stress among Type 2
diabetic patients.

Keywords: Effectiveness, Herbal steam, Hear Rate Variability, Reduce stress, Diabetics

condition. This can impact patients to the point ofblinding [2]. There were studies on how the dietaryintake of fish of patients with type 2 diabetes is related
to diabetic retinopathy and retinal vascular caliber[3].
In Thailand, diabetic is a high priority public healthissue of the country. According to national statistics
during 2010-2014, the numbers of patients increase
continuously [4]. The frequency rate of diabetes
among males has decreased from 6.4% to 6.0%. For
females, the rate increases slightly from 7.3% to 7.7%[5]. Diabetes is commonly found and is more likely
to be found among elder people. The cause fordiabetes may vary. One of the key cause is genetics
and obesity, particularly for direct family, such as
parents. Diabetes cannot be completely treated. 90%
of diabetic patients suffer from the type of diabetic
which does not require insulin. This is chronic andaffects patients physically, mentally and socially,
even their quality of life. As it was chronic and lifethreatening, resulting in many inevitable changes indaily life. This causes them to lose their selfconfident, resulting in stress. If the patients cannot
address this stress, it would affect the quality of life
and well-being of the patients. In terms of stressmanagement WHO established Guidelines for theManagement of Conditions Specifically Related toStress to serve as a guideline and an approach in stressmanagement [6]. For treatment of patients with stress,
options include medication, alternative treatment,
natural treatment, relaxing massage, the use of

INTRODUCTION
Diabetes is high up in the priority public healthissues globally, as noted by WHO. In 2014, there
were approximately 422 million adults living withdiabetes worldwide, a significant increase from 108
million in 1980. The global prevalence (agestandardized) of diabetes, which has increased to
8.5% from 4.7% in the adult population, is nearly twotimes as high as it was in 1980. These statistics
indicate that the associated risk factors, such as being
overweight or obese, have also risen. Throughout theprevious decade, diabetes prevalence has increased
more rapidly in low- and middle-income countries
than in high-income countries. In 2012, diabetes
resulted in 1.5 million deaths, while an additional 2.2
million deaths were caused by having excessive blood
glucose levels, which increases the risks ofcardiovascular disease and other serious healthconditions. A total of 43% of these 3.7 million deaths
occurred prior to 70 years of age. High blood glucose
or diabetes is responsible for a higher percentage ofdeaths occurring before the age of 70 in low- andmiddle-income countries than those occurring in
high-income countries.[1] Diabetes is a condition
which may allow for dangerous complication to thebody, such as an eye complication, abnormally highsugar level due to tear excretion from the lens, which
disrupt the retina. A common condition found among
diabetic patients is Retinopathy, a sight-related
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SEE - Nagoya, Japan, Nov.12-14, 2018

Aromatherapy and herbal streaming. Apart from
helping with respiratory disease, herbal streaming [7],it uses heat and the herbs is of aroma therapeutic
properties, enabling relaxation for patients withstress. Due to this premise, the researcher became
interested in studying the immediate effectiveness of
herbal streaming for stress reduction among Type 2
diabetic patients. The study’s results will be used as a
guideline to treat patients suffering stress.

volunteers, and selected diabetic patients with stressthrough doctors’ diagnosis. Volunteers would thenrespond the questionnaire with regards to personal
information and stress-related information. Whenvolunteers pass the inclusion criteria, they will be
accepted for herbal streaming. Research team would
then let the volunteers sign for participation in the
research.
Volunteers will be assessed for certain conditions
prior to the treatment, for example, their stress level
using Suanprung Stress Test 20 (SPST-20), and Heartrate variability (HRV). Once the assessment prior to
the treatment is completed, then volunteers will
receive herbal streaming. In the experiment, doctors
practiced in traditional medicine or modern medicine,with no less than 3 years of work experience, will bemonitoring the herbal streaming process. The process
takes 30 minutes in duration. Before the treatment,
volunteers will be assessed before and after thetreatment. The entire process of the assessm
Statistical Analysis
Use descriptive statistics to explain thevolunteers’ characteristics, the average, the standard
derivation. Then analyze the results of comparative
factors of the same group before and after thetreatment using paired t-test.

MATERIALS AND METHODS
DesignThis research is a Quasi – Experimental
Research, operated in Phakdi District, Chaiyaphum
province.
This study has been approved by the Ethics
Committee of Sirindhorn Public Health College ofKhon Khaen (No. 81/2561, No. HE 610662).
Participants
The sampling group comprises of Type 2 diabetic
patients age 35-85 with stress. They have been
identified with a questionnaire on stress level. There
were 30 people whose SPST–20 is at 3 or higher.
Volunteers receive stress treatment, utilizing herbal
streaming. The heart rate variability (HRV) is
monitored by the machine, both before and after the
study for result comparison. The research has an
Inclusion criteria, as follows: females or males, age
35-85 years, diagnosed as Type 2 diabetic, withstress level of SPST–20 at more than 3. The
exclusion criteria comprises of a fever higher than
38 degree, as there may be further contamination,
severe contagious disease, conditions: kidneydisease, heart disease, epilepsy, chronic asthma,
severe respiratory disease, females on period who
were having fever, infection from various wounds,
migraine, nausea or those with history of allergies toherbs.
Intervention
Volunteers received herbal streaming for 30
minutes, allocated into two sessions; 15 minutes
each. Then there is a 5 minute rest. There will be a
Heart Rate Variability (HRV) assessment before andafter the herbal streaming immediately. (Figures 1)
The treatment used in herbal streaming is aformulae with relaxing properties, relieving muscle
pains, such as Phlai, Turmeric, Bergamot’s skin,jasmine, and bullet wood etc.
Measurement Instruments
The tool used for research is one that measures thelevel of stress, Suanprung Stress Test 20 (SPST-20).
It is a test created by Suanprung Hospital, Chiang
Mai. This was complemented by the Heart Rhythm
Scanner PE (Biocom Technologies, USA) for
measurement the heart rate variability (HRV).
Procedures

Figure 1: The Herbal Steam.
RESULTS
Results of the research on volunteers participatingin the research project demonstrates the following
personal information: there are 30 volunteers, withfemales being the majority, at 24. 80% of thevolunteers age between 49 to 61 years old, there were
16 volunteers in this range. 53.30% of the volunteers,
the majority, weight between 5 2 - 6 9 kilograms or
63.30%. Those in the height range between 1 5 0 to
159 centimeters makes up15 people or 50%.

The research team announced for volunteer
recruitment, explained the research project details to
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SEE - Nagoya, Japan, Nov.12-14, 2018

The result compares Heart rate variability (HRV).
Research results demonstrates the comparative
Heart rate variability, by studying Time Domain
Analysis, comprises SDNN, RMS-SD; and study
Frequency Domain Analysis (LF, HF, LF/HF). By
comparison before and after the study, the SDNN,
RMS-SD and LF/HF have a value that increases withstatistic difference (P<0.05) in Table 1.

frequency (P = 0.009) were significantly lower,
while, in contrast, high frequency (P = 0.006) andhigh frequency (P = 0.003) were significantly higher
following exercise. Additionally, when using a
Poincare plot, the standard deviation perpendicular tothe line of the Poincare plot (P = 0.027) greatly
increased following exercise [ 8]. There are alsostudies related to Antihypertensive treatment andheart rate variability in diabetic patients: role ofcardiac autonomic neuropathy [ 9 ]. For this research,
volunteers receive herbal streaming which helps
volunteers’ muscle to relax. This helps stress level toreduce. There is consistency with the study by
Peerada Damapong et al, 201 6 . There were alsostudies related to Short-Term Effects of Court-Type
Traditional Thai Massage on Pressure Pain Thresholdand Pain Intensity in Patients with Chronic TensionType Headach [ 1 0 ]. This is also consistent with thestudy by Peerada Damapong et al., on A Randomized
Controlled Trial on the Effectiveness of Court-Type
Traditional Thai Massage versus Amitriptyline inPatients with Chronic Tension-Type Headache It
studied patients with migraine induced by stress. Thiswas measured through an assessment on Heart ratevariability both before and after the treatment. The
study reveals that after treating the patients with
Court-Type Traditional Thai Massage, there was achange in HRV. This demonstrates the increased
functions of parasympathetic nervous system (P <0 . 0 5 ) [ 11]. The study’s result reveals that herbal
streaming helps increase the work of parasympathetic
nervous system, enabling receivers of herbal
streaming to have less stress; this was amongst Type2 diabetic patients.

Table 1 Compare outcome measures between
before and after the treatment
OutcomeBaseline(Mean±
SD)
22.71±14.89

Immediate
Effectiveness(Mean± SD)
37.76±18.74

P-value- RMS-SD(Ms)

17.92±15.02

31.60±18.26< 0.05*- LF (ms2)

27.16±21.12

24.60±22.74

0.348- HF (ms2)

22.11±20.59

24.20±23.38

0.346- LF/ HF
(ms2)

1.59±0.68

2.01±1.10

0.047*

Heart ratevariability(HRV)- SDNN(Ms)< 0.05*Note.* 𝑃𝑃 < 0.05 is statistically significant
differences as compare between before and after thetreatment from baseline.
DISCUSSION
From the study results before and after theexperiment, it appears that volunteers receiving theherbal streaming will have SDNN , RMS-SD, andLF/HF of HRV which increased with statisticaldifference (P<0.05). Result of the study affects theparasympathetic nerve. This reduces stress, inconsistent with the research by Rajesh Kumar Goit etal. in 2014. The study was on Mild-to-moderateintensity exercise improves cardiac autonomic drivein type 2 diabetes. The following materials andmethods were applied: assessment of heart ratevariability was conducted with 20 patients with type2 diabetes by recording the resting electrocardiogram
for the heart rate variability analysis at spontaneous
respiration for 5 min in the supine position prior toand following 6 months of supervised aerobic trainingthat was conducted three times each week. The resultsof the study show that: in the time domain measures,the square root of the mean of the sum of the squaresof differences between the adjacent R-R intervals(RMSSD; P = 0.023) and the percentage ofconsecutive RR intervals that differ by more than 50
ms (pNN50; P = 0.025) rose significantly following
exercise. In the frequency domain measures, lowfrequency (P = 0.003) and low frequency/high

CONCLUSION
By studying the immediate effectiveness of herbal
streaming in stress reduction for type 2 diabetic
patients. Results of the Heart rate variability frombefore and after the treatment demonstrates that
SDNN, RMS-SD and LF/HF values increased withstatistical significance. After the herbal streaming,
volunteers become less stress. However, it can beconcluded that herbal streaming helps increase thefunctions of parasympathetic nervous system. This
enables type 2 diabetic patients to become less stress.
ACKNOWLEDGEMENTS
The researchers are very grateful to all participants
for contributing important information.
This research was supported by National ResearchCouncil of Thailand and Suan Sunandha Rajabhat
University, Thailand.
REFERENCES[1]. World Health Organization. Global Report on
Diabetes. Isbn [Internet]. 2016;978:88. Available
137

SEE - Nagoya, Japan, Nov.12-14, 2018from:http://www.who.int/about/licensing/%5Cnhttp://apps.who.int/iris/bitstream/10665/204871/1/9789241565
257_eng.pdf[2]. Al-Kharashiv AS. Role of oxidative stress,
inflammation, hypoxia and angiogenesis in thedevelopment of diabetic retinopathy. Saudi J
Ophthalmol [Internet]. 2018;1–6. Available from:http://linkinghub.elsevier.com/retrieve/pii/S1319453
418301826[3]. Chua J, Chia A-R, Chee ML, Man REK, Tan
GSW, Lamoureux EL, et al. The relationship of
dietary fish intake to diabetic retinopathy and retinal
vascular caliber in patients with type 2 diabetes. Sci
Rep [Internet]. 2018;8(1):730. Available from:http://www.nature.com/articles/s41598-017-18930-6[4]. Ministry of Public Health. Public healthstatistics A.D.2015. Strateg Plan Div [Internet].
2016;233. Available from:http://bps.moph.go.th/new_bps/sites/default/files/hea
lth_statistic2558.pdf[5]. Ministry of Public Health.Bureau of Non
Communicable Diseases. Annual Report 2015 ;13–
4. Available from:http://www.thaincd.com/document/file/download/pa
per-manual/Annual-report-2015.pdf[6]. World Health Organisation. Guidelines for theManagement of Conditions Specifically Related toStress. Assess Manag Cond Specifically Relat toStress mhGAP Interv Guid Modul (version 10)[Internet]. 2013;1–273. Available from:http://www.ncbi.nlm.nih.gov/pubmed/24649518[7]. P. T, P. N, W. W. Efficacy and safety of herbal
steam bath in allergic rhinitis: a randomized
controlled trial. J Integr Med [Internet].
2018;16(1):39–44. Available from:http://www.elsevier.com/journals/journal-ofintegrative-medicine/20954964%0Ahttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=emexb&NEWS=N&AN=619975684[8]. Goit RK, Paudel BH, Khadka R, Roy RK,
Shrewastwa MK. Mild-to-moderate intensity
exercise improves cardiac autonomic drive in type 2
diabetes. J Diabetes Investig. 2014;5(6):722–7.
[9]. Salo TM, Viikari JSA, Antila KJ, Voipio-Pulkki
L-M, Jalonen JO, Välimäki IAT. Antihypertensive
treatment and heart rate variability in diabetic
patients: role of cardiac autonomic neuropathy. J
Auton Nerv Syst [Internet]. 1996;60(1–2):61–70.
Available from:http://linkinghub.elsevier.com/retrieve/pii/01651838
96000367[10]. Damapong, P. Kanchanakhan, N.
Eungpinichpong, W., Putthapitak, P, and Damapong
P., Short-Term Effects of Court-Type Traditional
Thai Massage on Pressure Pain Threshold and Pain
Intensity in Patients with Chronic Tension-Type
Headach. International Journal of GEOMATE.vol.
11, no. Dec., 2016..
[11]. Damapong P, Kanchanakhan N,
Eungpinichpong W, Putthapitak P, Damapong P. A
Randomized Controlled Trial on the Effectiveness of
Court-Type Traditional Thai Massage versus
Amitriptyline in Patients with Chronic Tension-Type
Headache. Evidence-based Complement Altern
Med. 2015;2015.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFICIENCY OF INDIAN BORAGE ESSENTIAL OIL AGAINSTCOWPEA BRUCHIDS*Ruchuon Wanna1 and Phanthiwa Kwang-Ngoen2
Faculty of Technology, Mahasarakham University, Thailand
2
Faculty of Agriculture, Chiang Mai University, Thailand

1

ABSTRACT
Cowpea bruchids is a one of the most important insect pests in stored products, especially of whole grainsused for breeding or consumption. Currently, synthetic insecticides cause adverse effects to human health andthe environment, thus new alternative biopesticides from herb or plant are needed for cowpea bruchids control.
The aim of this research was to evaluate insecticidal activities of essential oil from Indian borage, Plectranthus
amboinicus. Efficacy of this essential oil against C. maculatus was investigated by impregnated filter paper andvapor-phase tests. Experiments were conducted under Completely Randomized Design (CRD) with 4
replications. Contact activity was considered on essential oil at 6 concentrations of 0 300 600 900 1,200 and
1,500 ppm and fumigant activity was performed at 6 concentrations including 0 3 6 9 12 and 15 µL/L air. All
experiments were assessed under laboratory conditions (30±2ºC, 70-80%RH and 16L:8D photoperiods). Data ofdeaths cowpea bruchids were recorded after treated at 24 to 168 hours. Contact activity showed 1,200 ppm of P.
amboinicus essential oil at 168 hours was the best performance in the contact toxicity on cowpea bruchids andfumigation activity presented 12 µL/L air of P. amboinicus essential oil at 72 hours had the highest effectivenessin the fumigation toxicity on cowpea bruchids, with 100% adult mortality. The data pointed that P. amboinicus
essential oil showed high potential of insecticidal activity for cowpea bruchids control. Hence, the essential oil ofP. amboinicus might be used as an alternative for grain protection against stored product insects.
Keywords: Insecticidal activity, Essential oil, Plectranthus amboinicus, Callosobruchus maculatus

weight, become unsuitable for human or animal
consumption and have poor germinating ability [6].
Synthetic pesticides are currently the method of
choice to protect stored grain from insect damage.
However, continuous or excessive uses of synthetic
pesticides have created serious problems arisingfrom factors such as ozone depletion, environmental
pollution, increasing costs of application, pesticide
residue in food, insects develop insecticidal
resistance and toxicity hazards on non-target
organisms in addition to direct toxicity to users [7],[8]. Therefore, environment needs some otheralternatives of chemical pesticides. These problems
have highlighted the need to develop new types of
selective insect-control alternatives. One alternative
to synthetic insecticides is the botanical pesticides
i.e. insecticidal plants or plant compound and the useof natural compounds, such as essential oils that
result from secondary metabolism in plants.
Currently, essential oil is in use for insect
management [7].
Essential oils and their constituents in relation tocontact and fumigant insecticidal actions have been
well demonstrated to be a potent source of botanicalpesticide against stored grain product pests [9], [10].
Especially their main compounds monoterpenoids,
offer promising alternatives to classical fumigants[11] and also have some effects on the physiological,

INTRODUCTION
Callosobruchus
maculatus(Fabricius)(Coleoptera: Chrysomelidae: Bruchinae), thecowpea bruchids which is the most important pest ofduring the storage period [1], has involved the great
attention because it is widely distributed throughout
the tropical and sub-tropical regions. Generally theinfestation starts in the field where the adults lay
eggs on green or drying pods. Infestation in the field
has no serious implications as the damage in thefield is low. However, once infested seeds are
stored, enormous damage occurs due to rapid
multiplication of insects in a very short time. This
specie can cause damage of legume seeds up to 100% during storage [2], resulting in maximum damageof 2 to 5 kg seeds within 45 to 90 days in optimum
temperature (30±1ºC) and moisture conditions (75±3%). The adult female lays eggs on the seed surface
and the hatching larvae bore into the seed. The
neonate larvae penetrate the grains causing serious
damage, such as grain weight loss, and reductions ingermination and nutritional value [3], [4]. The wholedevelopment takes place inside a single seed and theadults emerge out by leaving behind holed seed [5].
More than one larva can develop within a single
grain. Damaged legume seeds have thus reduced

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SEE - Nagoya, Japan, Nov.12-14, 2018

biological and behavior of insects such as growthrate, life span, reproduction and can cause their
death [12], [13]. Studies on essential oils havestimulated research on stored grain pest control, withvery promising results. Mahmoudvand et al. [14]demonstrated the contact insecticidal activity ofessential oils of Lippia citrodora Kunth.,
Rosmarinus officinalis L., Mentha piperita L. andJuniperus sabina L. presented activity against C.
maculatus (F.). According to Raja et al. [15], theessential oil of Mentha spicata L. caused increased
mortality, decreased oviposition and emergence ofinsects in cowpeas. Some chemical components ofessential oils, extracted from plants of the Labiatae
family, exhibit low toxicity to mammals but caninterfere in specific regions of the nervous system ofpest insects [16] causing the insect death. In thepresent investigation the essential oil of Indian
borage, Plectranthus amboinicus (Lour.), from fresh
leaves was studied for their contact and fumigant
activities on the adult C. maculatus. The results may
be used for C. maculatus control in storage units,providing direct and indirect benefits for small andmedium cowpea producers.

water after the extraction. Essential oil waspreserved in sealed glass containers and refrigerated
in the dark at 4 ºC until its use. The essential oils
were tested separately in a completely randomized
design, consisting of six treatments (essential oils
and control) with four replicates.
Contact activity
The insecticidal contact activity of essential oilof Indian borage P. amboinicus against adults ofcowpea bruchids C. maculatus was evaluated byimpregnated filter paper test. Essential oil preparedin acetone (1mL) at different concentrations (0 300
600 900 1,200 and 1,500 ppm) were applied on filter
papers (Whatman No. 1, diameter 9 cm). The
solvent was allowed to evaporate for 2 min andplace at the bottom of each petri-dish (diameter 9cm). Ten adults (unsex) of cowpea bruchids C.
maculatus (3 day olds) were introduced into eachpetri dish and covered with a lid, in a room condition
at 30±5°C, 70±5% relative humidity, and aphotoperiod of 16 h: 8 h (L:D). Control wasmaintained in which treatment was made with 1 mLof acetone alone. Adult mortality was assessed after
treatment 24 hours exposure to 168 hours. The
insects were considered to be dead as no leg or
antennal movements were observed.

MATERIALS AND METHODS
Insect rearing
Cowpea bruchids, Callosobruchus maculatus(Fabricius) was used for the present experiment. A
small population of C. maculatus was obtained fromthe seed store located in Maha Sarakham province,
Thailand. Fifteen pairs of cowpea bruchids adults
were maintained in a plastic box (diameter 22 cm,
height 10 cm). The cultures were reared on diet of
500 g of mungbean seeds, Vigna radiata (L)Wilczek, They were reared and allowed for mating
and oviposition under laboratory conditions, inside a
growth chamber at 30±5°C, 70±5% relative
humidity, and a photoperiod of 16 h: 8 h (L:D).
Adult insects of cowpea bruchids used for tests were
3 days old.

Fumigant activity
The insecticidal fumigant activity of Indian
borage P. amboinicus was assessed by vapour phase
test. In brief, each filter paper strip (Whatman No. 1,
cut into 1.5x5 cm) treated with each test oils (0 3 6 912 and 15 µL/L air) previously dissolved in acetone(100 µL), it was placed into the hanging of glass
vials (diameter 2.5 cm x height 5 cm) from thecenter of screw cap of fumigation bottle (diameter
5.5 cm x height 10.5 cm) to avoid contact effect ofinsects with paper strip. Ten adults (unsex) ofcowpea bruchids C. maculatus (3 day olds) wereplaced in fumigation bottles and covered with a lid,in condition at 30±5°C, 70±5% relative humidity,
and a photoperiod of 16 h: 8 h (L:D). Controls
received 100 µL of acetone only. Adult mortality
was observed after 24 hours exposure to 168 hours.
The insects were considered to be dead as no leg or
antennal movements were detected.

Extraction of essential oil
Essential oil was extracted from fresh leaves ofIndian borage, Plectranthus amboinicus (Lour.)following by using hydrodistillation in a modified
Clevenger-type apparatus. In carrying out the steam
distillation process, 200 g of an air-dried sample of
P. amboinicus was weighed in to the distillation
flask and 600 ml of distilled water added. The
apparatus was set up using a clamp on a heating
mantle and heated for a period of 3 hours. The
essential oil deposited on water was then collected
through the attached graduated measuring tube by
opening the tap. The essential oils treated withanhydrous sodium sulphate to remove the remaining

RESULTSContact toxicity
Mortality of cowpea bruchids C. maculatus at
168 hours after treatment was highest at theconcentration of 1,200 ppm of essential oil from
Indian borage P. amboinicus with cumulative valuesof 100% and there was a significant difference
140

SEE - Nagoya, Japan, Nov.12-14, 2018

(P<0.01) in relation to the other concentrations,However, it did not show any differences comparedwith 600 900 and 1,500 ppm (Figure 1). The numberthat died increased as the concentration of theessential oil and time of exposure increased for

insect. At all concentrations treated of essential oilfor 120 hours caused more than 50% adult mortalityof cowpea bruchids C. maculatus compared with thecontrol.

% Adult mortality
120
0 ppm
300 ppm
600 ppm
900 ppm
1,200 ppm
1,500 ppm

100

80

ab a
ab
ab a

bc
abc

a

b

c

ab
ab

a

a aa
ab

a
b

60

a
ab

b

a
ab ab

ab a
20

b

ab

40
ab

a

b

b

a

ab
0

b
24 h

c

c

c
48 h

72 h

96 h

c

d

c
120 h

144 h

168 h

Fig. 1 Contact activity of essential oil of Indian borage P. amboinicus on adult mortality of cowpea bruchids C.
maculatus within 168 hours

bruchids C. maculatus. Cowpea bruchids C.
maculatus was more sensitive to essential oil of
Indian borage P. amboinicus by insecticide
fumigant than contact activities at greater mortality
during the first 72 hours.

Fumigant toxicity
Mortality value exposed with 12 µL/L air ofessential oil from Indian borage P. amboinicus
leaves to adults of cowpea bruchids C. maculatus
after treatment at 72 h resulted in 100%mortality
and it caused the highest significant difference(P<0.01). However, it did not show differencescompared with 9 and 15 µL/L air (Figure 2). Allconcentrations of essential oil were significantly
different efficiency against cowpea bruchids C.
maculatus with adult mortality when comparison
with 0 µL/L air, acetone treatments and at 120
hours showed >50% adult mortality of cowpea

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141

SEE - Nagoya, Japan, Nov.12-14, 2018

% Adult mortality
120
0 µL/L air
3 µL/L air
6 µL/L air
9 µL/L air
100
12 µL/L air
15µL/L air

ab a aabb ab a a

ab a abaa

b aaaa

a

b

bc

a

80

b

a

b

b
c

b
a

60

b

a
a

a

40

20

0

c

b
24 h

d
48 h

c
72 h

96 h

c

c

c
120 h

144 h

168 h

Fig. 2 Fumigant activity of essential oil of Indian borage P. amboinicus on adult mortality of cowpea bruchids
C. maculatus within 168 hours[20]. The results obtained suggest good potential forthe use of essential oils of Indian borage P.
amboinicus as both fumigant and contact toxic
agents against cowpea bruchids C. maculatus.
Though the examined essential oils had contact aswell as fumigant activity, the fumigant toxicity ofthe essential oils were much more potential inshorter period (72 hours). From this study, it isconcluded that Indian borage P. amboinicus (Lour.)essential oil could be used as botanical insecticides
postharvest or fumigant since it is a potential
alternative control method for cowpea bruchids C.
maculatus.

CONCLUSION AND DISCUSSION
In the current study, the essential oils obtained
from leaves of Indian borage P. amboinicus
demonstrated fumigant and contact activity tocowpea bruchids C. maculatus. In contact method,tested essential oil showed a significant increase of
mortality (P< 0.001) to the test insects at higher
dosage (1,200 ppm) after 120 hours of treatment
with 100% adult mortality, whereas in fumigation
method insecticidal properties were more rapid totest insects within 72 hours of treatment. In
fumigation method, cowpea bruchids C. maculatus
showed high susceptibility to essential oil of Indian
borage P. amboinicus oil, even at low
concentrations (12 µL/L air) after 72 hours oftreatment with 100% adult mortality. The
insecticidal activity of many plant essential oils
might be attributed to monoterpenoids [17]. Due tothe high volatility they have fumigant activity thatmight be of importance for controlling stored
product insects. Monoterpenoids were reported
earlier as fumigants and contact toxicants on various
insect pests [18]. Many studies have demonstrated
differential susceptibility of stored product beetle
species to the essential oils. Callosobruchus species
was more susceptible to essential oils or theircomponents than those of other insect species [19],ACKNOWLEDGEMENTS
This research was financially supported by
Mahasarakham University. The laboratory assistancefrom Miss Jiraporn Krasaetep and Miss Kanokorn
Kotraksa are gratefully acknowledged.
REFERENCES[1] Deshpande V. K., Makanur B., Deshpande S.
K., Adiger S., and Salimath P.M., Quantitative
andQualitative
Losses
CausedbyCallosobruchus maculates in Cowpea During

142SEE - Nagoya, Japan, Nov.12-14, 2018

Seed Storage, Plant Arch., Vol. 11, 2011, pp.
723-731.
[2] Gbaye O. A., Millard J. C., and Holloway G. J.,
Legume Type and Temperature Effects on The
Toxicity of Insecticide to The Genus
Callosobruchus(Coleoptera:
Bruchidae).
Journal of Stored Products Research, Vol. 47,
2011, pp. 8-12.
[3] Melo R. A., Forti V. A., Cicero S. M.,
Novembre A. D. L. C., and Melo P. C. T., Useof Xray to Evaluate Damage Caused by Weevils
in Cowpea Seeds. Horticultura Brasileira, Vol.
28, 2010, pp. 472-476.
[4] Oke O. A. and Akintunde E. M., Reduction of
The Nutritional Values of Cowpea Infested with
Callosobruchus
maculatus(Coloeptera:bruchidae).
International
Journal of Agri
Science, Vol. 3, 2013, pp. 30-36.
[5] Messina F. J. and Jones J. C., Does Rapid
Adaptation to a Poor-Quality Host By
Callosobruchus maculatus (F.) Cause CrossAdaptation to Other Legume Hosts. Journal of
Stored Products Research, Vol. 45, 2009, pp.
215-219.
[6] Elhag E. A., Deterrent Effects of Some
Botanical Products on Oviposition of the
Cowpea Bruchid Callosobruchus maculatus (F.)(Coleoptera:
Bruchidae).
International
Journal of Pest Management, Vol. 46, Issue 2,
2000, pp. 109-113.
[7] Isman M. B., Botanical Insecticides, Deterrents
and Repellents in Modern Agriculture and An
Increasingly Regulated World. Annual Review
of Entomology, Vol. 51, 2006, pp. 45-66.
[8] Ogendo O., Kostyukovsky M., Ravid U.,
Matasyoh J., Deng A., and Omolo E.,
Bioactivity of Ocimum gratissimum L. and Twoof Its Constituents Against Five Insect Pests
Attacking Stored Food Products. Journal of
Stored Products Research, Vol. 44, 2008, pp.
328-334.
[9] Ahmed M. E. A., Fumigant Toxicity of Seven
Essential Oils Against the Cowpea Weevil,
Callosobruchus maculatus (F.) and the Rice
Weevil, Sitophilus oryzae. Egyptian Academic
Journal of Biological Sciences, Vol. 2, 2010, pp.
1-6.
[10] Ayvaz A., Sagdic O., Karaborklu S., and Ozturk
I., Insecticidal Activity of the Essential Oils
From Different Plants Against Three StoredProduct Insects. Journal of Insect Science, Vol.
10, 2010, pp.1-13.
[11] Papachristos D. P. and Stamopoulos D. C.,
Selection of Acanthoscelides obtectus (Say) for
Resistance to Lavender Essential Oil Vapour.
Journal of Stored Products Research, Vol. 39,
2003, pp. 433-441.

[12] Pascual-Villalobos J. M., Evaluation of theInsecticidal Activity of Chrysanthemum
coronarium L. Plant Extracts. Boletín de
Sanidad Vegetal Plagas, Vol. 22, 1996, pp. 411420.
[13] Islam R., Khan R. I., Al-Reza S. M., Jeong Y.
T., Song C. H., and Khalequzzaman M.,
Chemical Composition and Insecticidal
Properties of Cinnamomum aromaticum (Nees)
Essential Oil Against the Stored Product Beetle
Callosobruchus maculatus (F.). Journal of the
Science of Food and Agriculture, Vol.89, 2009,
pp. 1241-1246.
[14] Mahmoudvand M., Abbasipour H., Hosseinpour
M. H., Rastegar F., and Basij M., Using Some
Plant Essential Oils As Natural Fumigants
Against Adults of Callosobruchus maculatus(F.)(Coleoptera:
Bruchidae).
Munis
Entomology and Zoology, Vol. 6, 2011, pp.
150-154.
[15] Raja N. S., Gnacimusthu S. I., and Dorn S.,
Effect of Plant Volatile Oils in Protecting
Stored Cowpea Vigna unguiculata (L.) Walpers
Against Callosobruchus maculatus (F.)(Coleoptera: Bruchidae) Infestation. Journal of
Stored Products Research, Vol. 37, 2001, pp.
127-132.
[16] Kostyukovsky M., Rafaeli A., Gileadi C.,
Demchenkoand N., and Shaaya E., Activationof Octopaminergic Receptors By Essential Oil
Constituents Isolated From Aromatic Plants:
Possible Mode of Action Against Insect Pests.
Pest Management Science, Vol. 58, 2002, pp.
1101-1106.
[17] Tong F. and Coats J. R., Effects ofMonoterpenoid Insecticides on [3H]-TBOB
Binding in House Fly GABA Receptor and 36
Cluptake in American Cockroach Ventral Nerve
Cord. Pesticide Biochemistry and Physiology,
Vol. 98, Issue 3, 2010, pp. 317-324.
[18] Rice P. J. and Coats J. R., Insecticidal
Properties of Several Monoterpenoids to theHouse Fly (Diptera: Muscidae), Red Flour
Beetle (Coleoptera: Tenebrionidae), andSouthern Maize Rootworm (Coleoptera:
Chrysomelidae).
Journalof
Economic
Entomology, Vol. 87, 1994, 1172-1179.
[19] Tripathi A. K., Prajapati V., and Kumar S.,
Bioactivities of L-Carvone, D-Carvone, andDihydrocarvone toward Three Stored ProductBeetles. Journal of Economic Entomology, Vol.
96, 2003, pp. 1594-1601.
[20] Lee B. H., Annis P. C., Tumaalii F., and Lee S.
E., Fumigant Toxicity of Eucalyptus blakelyi
and Melaleuca fulgens Essential Oils and 1,8Cineole Against Different Development Stagesof the Rice Weevil Sitophilus oryzae.
Phytoparasitica, Vol. 32, 2004, pp. 498-506.

143

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE CAPACITY OF SOIL WATER INFILTRATION UNDERHORTICULTURAL CROPS IN THE WATERSHED UPSTREAM
SUMANI

Aprisal 1 and Bambang Istijono 2
1

Agriculture Faculty, Andalas University, Padang, Indonesia

2, Engineering Faculty, Andalas University, Padang, Indonesia

ABSTRACT
Generally, the farming activities in the Sumani upstream watershed community are; cultivating horticulture orvegetables such as cabbage, onions, potatoes, carrots and flowers. The land cultivation for these purposes is madepossible due to the high fertility rate of the land in this region which is suitable for horticultural crops. The soil inthis area (including the order Andisol) develops from the weathering of the residue from the eruption of Mount
Talang. Most farmers do not implement soil and water conservation which invariably leads to erosion and on thelong run, the land will finally be degraded. A base research is very vital to assess the ability of the soil water topenetrate to the ground floor. The purpose of this research is to assess the capacity of water infiltration on some
types of horticultural crops in the Sumani Upper watershed. The survey method is used to determine the sampling
points and the measurement of the rate of infiltration is read using a ring infiltrometer. The soil samples wereanalyzed in the laboratory of the Department of Soil Science under the Faculty of Agriculture, Andalas University.
While the infiltration rate of the data was processed using Horton’s equation. To determine the main factor
affecting the infiltration rate, the principal component analysis (PCA) was performed. The results showed that
infiltration rate in three groups of farmers ranged from moderate to fast. The main factors affecting it are; bulk
density, texture and depth of the root zonee.
Keyword; Horticulture, infiltration capacity, soil degradation.

Several factors influence the infiltration rate of soil,
some of them include; slope, texture and soil
structure, vegetation cover, management system, soil
moisture content, and organic material[1]. If thefactors that affect infiltration are not kept in optimal
conditions, more rainwater will flow and erode thesoil surface and leading to the loss of many nutrients.

INTRODUCTION

Water penetrates the soil through pores to theground this process is also called infiltration.
Infiltration is very important in restoring the soil
water lost due evapotranspiration.

Horticulture farming around the upstream of Sumani
watershed is mostly practiced by farmers who do not
apply soil and water conservation procedures.
Allegedly, the land erodes every growing season. The
soil is the main natural resource of the people livingin the [3] upstream of Sumani watershed which is
why they practice intensive farming to meet their life
necessities. This dynamic and intensive farming
causes rapid land degradation.

The characteristics of infiltration greatly depends on
the soil’s physical properties amongst other soil
properties and is a good indicator of changes in the
soil’s physical and biological characteristics [1]. The
availability of water in the soil greatly affects theprocess of plants taking up nutrients from the soil;
this is because nutrients are taken up in form of ionsin solution. Water infiltration greatly affects the
production of crops and also, the drainage of
agricultural land. [2].

The issue above causes damage to the soil’s
biophysical properties in horticulture, such as soil
pores and infiltration rate. If water absorption is
144

SEE - Nagoya, Japan, Nov.12-14, 2018

interfered with I the root zone of plants, this affects
the development of the plant roots in this zone and inturn will reduce the productivity of the soil. The
purpose of this research is to study the infiltration
capacity in horticulture farming in the upstream areaof the Sumani watershed.

farmers were be scored, and the results of these scores
were used as supporting information on thehorticultural productivity in the upstream of Sumani
watershed, Solok. ((3) The data analysis method
which is determined based on the least influential
nature in determining the quality of the soil or at least
the data set (MDS) using Minitab 17.0 software.
Minimum Data Set obtained from the calculation of
Principal Component Analysis (PCA).

MATERIALS AND METHODSTime and Location

RESULT AND DISCUSSION

The has been done on February 2018 to June
2018. It was conducted at several sample points on
the horticultural lands in upstream of Sumani
watershed, Solok Regency, West Sumatera. The
soil Quality Indicator Analysis was carried out inthe Laboratory of the Department of Soil Science
under the Faculty of Agriculture, Andalas
University.

Principal Component Analysis of Soil PhysicalCharacteristics
The main component in determining the main
properties of the soil determines the infiltration
capacity of the soil. Based on the PCA, the eigenvalue
is greater than one, i.e. there are four main
components, i.e. PC1, PC2, PC3 and PC4 (Table 1).
The selected variables from PC 1 to PC4 are taken as
factors to determine the rate of infiltration capacity inhorticultural farming.

Research Tools and Materials
The materials used were aquades, chemicals, aswell as materials for the analysis of the physicalproperties of the laboratory. The tools used to identify
the soil quality for horticultural biomass productivity
in the field include GPS, loops, maps, sample rings,
knives, plastics, label paper. The tools used forLaboratory analysis includes desiccators, ovens,erlenmeyers, bottles, measuring cylinders, analyticalscales, eksikator, trophy glasses, wet screen, filter,
mouthpiece, Kjeldhal tube, burette, distillation flask,
stative, and measuring pipette.

Table 1. Principal component analysis results

Research Methodology
The research was conducted in the field to collectsecondary and primary data. Secondary data wastaken from rainfall data, interview with farmers andrelated institutions. (1) Primary data were landsamplers from several points of land units in the threehorticultural farmer's field. Soil samples were taken
by means of purposive random sampling as an
example of representative land from established land
units.
The soil samples taken were natural soil samples
for analysis of the soil’s physical properties. While
the altered soil samples were taken for the analyzing
the chemical and biological properties of the soil. Soilsamples were taken from a 20 cm depth. (2)Secondary data was required in this research, and wascollected in form of the area’s condition and an aspectof horticultural cultivation of the area. The techniqueof collecting secondary data by collecting data fromseveral related agencies and interviews with thefarmers as supporting data. Results of interviews with

Eigenvalue
Proportion
Cumulative
Variable
Infiltration
capacity
Bulk
density
Total ofpore space
Organic
matterSoil Depth

2.9122
0.364
0.364
PC1
0.404

2.0070
0.251
0.615
PC2
0.285

1.4565
0.182
0.797
PC3
0.314

1.0767
0.135
0.932
PC4
-0.2950.522-0.2140.018-0.295-0.5220.214 -

0.018

0.295

0.033

-0.4560.496-0.191

0.053

0.460

0.516

-0.152

Sand-0.023

0.527

0.527

0.023

Dust

0.396

-0.107

0.287

0.605

Clay

-0.360-0.3430.169-0.559The main components selected are the four variables
which are highly influential in infiltration capacity,i.e. bulk density, sand-fraction texture, effective
depth of soil, and dust fraction.
Infiltration Capacity
The high rate of infiltration capacity in thehorticultural farming area in upstream of Sumani
watershed is strongly influenced by the soil’s physicalnature and the dominant soil is micropore. Lands
dominated by macropores will have a higher
infiltration rate compared to the land dominated by
145

SEE - Nagoya, Japan, Nov.12-14, 2018

Capasity of Infintration (cm/hour)

micropores. Weahatni horticultural field in the study
has infiltration capacity of 6cm/h to 12cm/h with themedium to fast range. Farmer groups A and B lands
have a moderate level infiltration capacity. The
infiltration capacity of farmer group C land is on thequick range. The variations in infiltration capacity ofthe three horticultural farming groups (Figures 1, 2
and 3) are due to the differences in soil properties andplanted crops as well as land management practices
conducted by farmers.
Based on regression analysis seen in the equation of
the line on the farmers group A is exponential withvalue R2 = 0.678 While in group B the equation ofline of exponential infiltration capacity with value R2= 0.935 In farmer group C, the equation of line of
exponential infiltration capacity with value R2 =
0.162

140
120
100
y = 343.82e-1.04x
R² = 0.9643

80
60
40
20
0
0

1

2

3

4

5

Time (hour)

Figure 2. Infiltration capacity on farmland B

The infiltration capacity is a dynamic trait that canchange significantly during certain precipitation
events, in response to seasonal changes ingroundwater, temperature, and plant type, as a resultof annual farming activities. Increasing infiltration
capacity decreases the flow of water in the soil
surface. Conversely, a smaller infiltration capacity is
due to a large number of clogged soil pores, thesurface water flow increases [4]. Furthermore, [5]regarding hydrology, infiltration is important as itmarks a shift from the surface of the earth that moves
rapidly into the water in the slow-moving ground.

Capacity of Infiltration (cm/jam)35

The infiltration capacity of soil is influenced by its
physical properties and its degree of ability, watercontent, and permeability of the subsurface layers.

3025

y = 26.185e-0.206x
R² = 0.1616

20
15
10
5

Capacity of Infiltration (cm/hour)

0
0

200

2

4

6

Time (hour)

180
160

Figure 3. Infiltration capacity on farmland C

140
120
100

y = 307.27e-0.687x
R² = 0.6784

80

Effect of texture on infiltration capacity
Soil texture at the research location of farmer group A
was clay, farmer group B was dust, and group C withthe texture of fine clay. According to [6] the soils withcoarse fraction, the level of the aeration is good andwater conductivity is fast, but the holding power of thewater is low. Because the soil is dominated bymacropores, Figure 2 shows the effect of soil textureof the study sites on infiltration capacity.

60
40
20
0
0

2

4

6

8

Time (hours)
Figure 1. Infiltration capacity on farmland A

146

SEE - Nagoya, Japan, Nov.12-14, 2018

12.00

70

Cumulative Infiltrationi (cm/Jam)

Kapasitas infiltrasi (cm/jam)

14.00

10.00
y = 0.113x + 1.7263
R² = 0.6176

8.00
6.00
4.00
2.00
0.00
0.0

20.0

40.0

60.0

80.0

Persentase pasir (%)

Figure 4. Sand percentage correlation with infiltration
capacity

60
50
40
30
20
10
0
1

2

3

4

Measurement timeA

B

C

Figure 5. Cumulative infiltration rate on the threefarming groups (A, B, and C)

Based on simple regression analysis, therelationship between infiltration capacity and texture
was quite close with R2 value as 0.617 This meantthat infiltration capacity of 61.7 percent was
influenced by the soil texture of the research locations
in farmer groups A, B, and C, the influence from otherfactors amounted to 38.3 percent. This proved thatsoil texture greatly influenced the infiltration rate of
the soil. For the infiltration capacity of the farming
land, a routine management is required to increase thesoil absorption matrix by adding organic fertilizer orcrop residue to the soil to retain the groundwater
ensure it doesn’t penetrate to the lower layers of theroot zone. The addition of organic material fromremaining plants acts as a cemented agent for soil
grains, nutrient sources, increasing CEC and energy
for soil microbes [7].

Cumulative infiltration in the three locations of
the farmland group is shown in Figure 4. Cumulative
infiltration varied considerably between the three
types of land farming groups based on measurement
time. Higher cumulative infiltration is found in groupB, followed by group C then next, group A. This wascaused by soil type and crop management which
troubled each of farming group. Group B farmers
usually return the rest of the plant to the land toincreases the ability of soil to absorb water. Good
management of soil can improve soil quality such as
cumulative infiltration. According to the study [8] italso showed that improving soil quality may increase
cumulative infiltration up to five times. However,continuous land acquisition without proper
management can reduce cumulative infiltration.
According to the results of the study, [9] the
improvement in infiltration capacity and cumulative
infiltration is by addition of materials that canincrease total pore space of soil such as ameliorantmaterial from rice husk biochar. This is because
biochar is an active charcoal capable of increasing thesoil cavity and biochar is not easily decomposed bysoil microbes.

Cumulative Infiltration
Cumulative infiltration is incoming water into thesoil in a specific time and duration in a certain amountof volume, depending on the total soil pore space tostore and hold it.

CONCLUSION

147

Based on the research of the infiltration capacity
in the upstream watershed of Sumani, it can beconcluded that; the research area of soil infiltration
capacity is influenced by soil physics properties, i.e.
bulk density, texture, and depth of root zone. The rateof infiltration in the three farmer groups of the study
sites was from the moderate to rapid range. From theequation of infiltration capacity, soil texture factor

SEE - Nagoya, Japan, Nov.12-14, 2018[4] Kartasapoetra, AG. 1989. Introduction to Soil
Science, Land Formation, and AgriculturalLand. Jakarta: Rineka Cipta.

influence is more dominant and equals about to 61.7
percent.

[5] Lee, R. 1990. Forest Hydrology. Yogyakarta:
UGM Press

ACKNOWLEDGEMENT
I am grateful to the chairman of Universitas
Andalas for the opportunity and assistance given to us
to do the research and the transportation assistanceprovided. Hopefully, this would be useful to improve
the performance of the research team as a lecturer ofUniversitas Andalas.

[6]

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Science.

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Hardjowigeno S. 2003. Soil
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Mukhtar S., Baker J.L., Horton R. and Erbach
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[3] Istijono.B. 2006. Watershed Conservation andFarmers Income: Studies on Watershed
Management Integration (Case Study: Sumani
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Sumatera). PPs.Unand Dissertation.

148

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DISCOVERY OF NOVEL DNMT-1 INHIBITOR BY FRAGMENT-BASEDDRUG DESIGN AS A POTENTIAL BREAST CANCER TREATMENT
Mutiara Saragih1, Ahmad Husein Alkaff1, Ade Hanna Natalia1, Ina Nur Istiqomah1, and Usman Sumo
Friend Tambunan1*
1Faculty of Mathematics and Natural Science, Universitas Indonesia, Indonesia
ABSTRACT
Breast cancer is the deadliest and the most common type of cancer among women in the world. Epimutation is
the leading cause of the tumorigenesis of breast cancer. DNA methyltransferase 1 (DNMT1) is the key enzyme
which involved in the regulation of DNA methylation pattern. In this research, fragment-based drug design
approach on natural products was performed to discover novel inhibitor of the DNMT1 as a therapeutic strategy
against breast cancer. About 2,601 fragments out of 168,646 compounds were obtained from the Lipinski’s Ruleof Three and toxicity screening. The fragments were docked into the S-Adenosyl-L-methionine (SAM) bindingsite of DNMT1. The potential fragments were merged with S-Adenosyl-L-homocysteine (SAH), generating nine
ligands. The ligands underwent flexible docking simulation and ADME-Tox prediction by using AdmetSAR,
Toxtree, SwissADME software. Three ligands show favorable characteristics as a new drug candidate for the
DNMT1 inhibitor according to the interaction of the amino acid residues, RMSD, and ∆Gbinding. MAHI1 being thebest ligands in term of ∆Gbinding -12.6300 kcal/mol, molecular interaction, and pharmacological properties.
Keywords: Breast cancer, DNA methyltransferase, natural products, molecular docking simulation, fragmentbased drug design
a possible way to reactivate gene silenced bymethylation of their promoters in some disease,including breast cancer [9]Natural products have been known as one of acandidate drug. It is a potential source of drugs due to
its molecular diversity and low toxicity[9], [10]. Oneof the methods of lead compound discovery is
fragment-based drug design (FBDD). One of theadvantages of FBDD is that it results in a lower
molecular weight lead, that is likely to have higher
oral bioavailability [11]. Fragment merging is anelaboration of the fragment which incorporates a
structural portion of overlapping molecules, usuallyan already known substrate or inhibitor of the target
protein, into a fragment [12]. Hence, preserving theessential molecular interaction of initial substrate or
inhibitor while improving the activity by the
introduction of new fragment. In this research, thefragment merging approach is utilized on thepotential natural product compounds and the alreadyknown product of the DNMT1 enzymatic reaction, SAdenosyl-L-homocysteine (SAH), to generate leadcompounds as an inhibitor for DNMT1 through insilico molecular docking simulation method andpharmacological test.

INTRODUCTION
Cancer is a major public health problem
worldwide [1]. Breast cancer is among the maincauses of death in women [2]. It is also the mostcurrent cancer in women worldwide with 1.7 million
diagnosed cases in 2012 [3]. The human genome
consists of genetic information and epigenetic.
Epigenetics regulate how and where the genetic
information should be used [4]. DNA methylation is
one of the essential mechanism in functional
epigenetic [5]. DNA methyltransferases (DNMTs) isthe leading enzyme in the epigenetic regulation ofgene expression in mammalian cells [6]. DNMT1 is
the most abundant DNMTs in the mammalian cells
and have a role in maintaining methylation pattern[7].
DNA methylation, whether hypomethylation or
hypermethylation, affects gene expression andchromosomal instabilities. Hypomethylation causes
overexpression of transcription of proto-oncogenes,
and reactivation of transposable elements anddemethylation of xenobiotic [8]. On the other hand,
hypermethylation causes suppression of tumor
suppressor genes and downregulation of DNA repair
genes. DNA hypermethylation also plays an essential
role in silencing the tumor suppressor genes as one of
the most consistent hallmarks of human cancer [7].
Aberrant DNMT1 activity leads to local
hypermethylation in DNA promoter gene and global
hypomethylation which pose potential causes for theabnormal growth of cancer cells [8]. Thus, theinhibition of DNMT1 activity has been established as

RESEARCH METHODOLOGYThis research has been done through an in silico
method by employing Molecular Operating
Environment (MOE) 2014.09, Osiris DataWarrior
v04.07.02, ChemBioDraw Ultra 14.0, Toxtree
v2.6.13, SwissADME (http://www.swissadme.ch/),149

SEE - Nagoya, Japan, Nov.12-14, 2018

andAdmetSAR(http://lmmd.ecust.edu.cn/1)
software. The 3D structure of DNMT1 protein was
obtained from Protein Data Bank at the Research
Collaboratory for Structural Bioinformatics (RCSB
PDB). The database of natural products was acquired
from PubChem.

Molecular Docking of Ligands
The molecular docking simulation for ligands andstandard were conducted with rigid docking and thenflexible docking protocol. All the parameters for themolecular docking simulation have been done
according to MOE 2014.09 software with AMBER
10: EHT as the forcefield.

Preparation of DNMT1 Protein
The 3D structure of DNMT1 with PDB ID 3AV5,
3AV6, 3PTA, 3SWR, and 4WXX were obtained fromthe RCSB. The chosen 3D structures were saved in
PDB format. The optimization DNMT1 was doneusing MOE 2014.09 by removing water molecules
and unnecessary metal atoms and optimizing thestructure using LigX with the default setting. Last, allof the DNMT1 protein were saved in .moe format.

Pharmacological Properties ADMETThe potential ligands from molecular docking
simulation underwent pharmacological properties
prediction. Toxtree was used to screened the
carcinogenicity and mutagenicity. The toxic
properties of the ligands were analyzed using Osiris
DataWarrior and AdmetSAR. The health effects of
the ligands on human organ were predicted using
SWISSADME.

Protein-Ligand Interaction Fingerprints (PLIF)
PLIF was applied to summarize the interaction
between ligands and protein using a fingerprinting
scheme. This method has been done using MOE
2014.09 with potential setup AMBER 10EHT,
forcefield, R-field solvation and superpose.
Superpose generates sequence alignment, structurealignments, PDB coordinates, RMSD statistics,
difference distance plots, and interactive image of thesuperimposed structures [13], [14]. The procedure of
PLIF has been done based on standard default in
MOE 2014.09.

RESULT AND DISCUSSIONS
Preparation and Visualization of DNMT1
DNMT1 is responsible for replicating the DNA
methylation pattern during replication. DNMT1 has
also been considered as an essential target for cancer
therapy [16]. In this research, the 3D structures of
DNMT1 were obtained from RCSB PDB. The watermolecule and other unnecessary molecule were
eliminated because solvation effect is not taken into
account in the molecular docking simulation [17].
Hydrogen atoms were incorporated into the protein.
The protein structures from RCSB PDB is generated
from X-ray crystallography which commonly does
not have a hydrogen atom because of the limited
resolution of the instrumentation. The presence ofcomplete atom on protein structures is essential
because it will affect the molecular mechanics,
dynamics, and electrostatic calculations involved inmolecular docking simulation [17], [18]. The last stepof protein preparation was energy minimization to
generate zero gradients of all atoms; the lowest
energy and the most stable condition that can be used
to investigate the mechanism of a chemical or
biological process [19]. PLIF method is employed toquantify and compare ligand-protein interactions. In
this method, fingerprints are covered into anormalized quantitative score that expresses thesimilarity between the interaction profile of docking
pose and that of a reference protein-ligand complex[20]. Furthermore, the pharmacophore was validated
to assess its ability to distinguish active compounds
that have potentially inhibit DNMT1 to the other [21].
In addition, the purpose of pharmacophore validation
is to evaluate the quality of pharmacophore featuresthat have been created. Standard ligands were utilized
to perform the validation test. Visualization on the

Preparation of The Natural Product Fragments
The standard ligands SAM, SAH, and Sinefungin(SFG), as well as the natural products as candidate
fragment, were obtained from PubChem database.
The ligands were then optimized through MOE
2014.09. MMF94x force field with RMS gradient of
0.001 was selected as the optimization parameters.
Natural products of The optimized ligands werestored in .mdb format. The prepared natural products
were screened to get fragments which fulfill
Lipinski’s Rule of Three (RO3) [15] and Toxicity test
by Osiris DataWarrior.
Molecular Docking of Natural Product Fragments
and Fragment Merging
The selected fragments were on docked into the
SAM-binding site of DNMT1 by using
pharmacophore query through using MOE 2014.09.
The fragments with favorable Gibbs binding energy,
RMSD, and molecular interaction were selected to bemerged with the standard molecule, SAH. Thismerging process of fragments and standards havebeen done using MOE 2014.09 and ChemBioDraw
Ultra 14.0 [12].

150SEE - Nagoya, Japan, Nov.12-14, 2018of the fragment in the binding site were determined tochoose the best fragments (Table 1).

binding site of DNMT1 was done with ‘Surface
Navigation and Maps’ tools in MOE 2014.09 (Fig. 1).

Preparation of Natural Product Ligands
The fragment merging was performed bydeploying MOE 2014.09. The fragments wereconnected to the part of the lead compound (SAH) bybuilding a bond and replace the overlap part. New
ligands were generated based on Lipinski's Rule ofFive (RO5) and Veber rule). Molecular weight lower
than 500 Da, TPSA lower than 140, and logP between-0.5 and 5.6, number of hydrogen donor no more than5, and number of hydrogen acceptor no more than 10[25]. The produced ligands must undergo the ADMETOX screening following druglikeness, and toxicity
prediction test (carcinogenic, mutagenic, irritant, andreproductive effect risks). A total of 9 ligands
generated from this process. The best ligands throughthis process were shown in Fig. 2.

Fig. 1. Binding site visualization of DNMT1 withpharmacophore, The green color is HydA, the pinkcolor is Don&Acc, and the blue color is Acc.
Preparation of Natural Product Fragments
About 168,646 compounds of natural products
were obtained from PubChem database. It was
screened by RO3 which has parameters such as,
molecular weight lower than 300 Da, LogP lower
than 3.0, the number of hydrogen donor less than 3,
and the number of hydrogen acceptor less than 3,
which suitable for the screening of small compound
for fragment development [15]. The natural products
also screened based on the veber rule [22], rotatablebond no more than 3 and polar surface area (TPSA)
lower than 60 Ǻ. Natural products which druglikenesslower than 0, and shows the toxicity potential such as
mutagenic, tumorigenic, reproductive effective andirritant were also eliminated. From the initial
screening, 2,601 compounds were saved in a .mdb
format as the fragment for the next experiment.

(A)

(B)

(C)

Fig. 2. The Selected Fragments and the merging
position (A) MAHI1. (B) MAHI2. (C) MAHI3. The
red color is the part of lead compounds, and the blackcolor is the fragment.

Analysis of Molecular Docking Simulation of
DNMT1 Protein and Fragments

Analysis of Molecular Docking Simulation of
DNMT1 Protein and The Ligands

Molecular docking simulation has become an
essential tool in drug design and discovery to predictthe conformation of small molecule ligands withcompatible target binding site and define binding
affinity of the ligand to form a stable complex
structure [23], [24]. The selected fragments from theprevious step were further screened moleculardocking simulation. In the first molecular docking
simulation, only 543 compounds bind to thepharmacophore point in the binding pocket. Then, thesecond molecular docking simulation produced only
282 compounds that bind to the pharmacophore point.
Only 77 compounds fulfilled the RMSD lower than
2.0. The ∆Gbinding, the number of a hydrogen bond
between the ligand and the protein, and the position

Nine ligands and standards underwent moleculardocking simulation using MOE 2014.09. ‘Rigid
Receptor’ protocol was used for first and second
simulation with the retain of 1 and 30 repetitions,
respectively. In the first step, only 7 ligands bind to
the site and have RMSD value lower than 2.0. Only
six ligands have potential properties such as ∆Gbinding
lower than standard. The six ligands were dockedwith ‘Induced Fit’ protocol, and retain the value of100. The most potential ligands were obtained byexamining the molecular interaction of the ligandswith the binding pocket of DNMT1. The result of thebest three ligands along with the standards from151

SEE - Nagoya, Japan, Nov.12-14, 2018

flexible molecular docking simulation is shown in
Table 2.
Table 1. List of the best natural product fragments

268.34

HAcc
3

HDon
2

33.90
33.90
37.03

222.31
236.33211.33

3
3
3

2
2
2

40.46
57.53
37.30

299.44240.26224.26

3
3
2

3
2
1

No

Compound Name

logP

TPSA

Weight12-hydroxy-1-methoxy-5,6,6a,7-tetrahydro-4Hdibenzo[de,g]guinolin-6-ium
2-(3-hydroxyphenyl)-4-propylmorpholin-4-um
2-(3-hydroxyphenyl)-5-methyl-4-propylmorpholin-4-ium(Z)-1-((1-hydroxy-2methylbutylidene)amino)octahydropyrrolizin-4-ium
1-(hydroxymethyl)octahydropyrrolizin-4-ium(E)-1,3-bis(2-hydroxyphenyl)prop-2-en-1-one(E)-1-(2-hydroxyphenyl)-3-phenylprop-2-en-1-one

2.69

46.07

-0.25
0.08
-0.47
1.26
2.61
2.96

2
3
4
5
6
7

Table 2. The ∆Gbinding, RMSD value, and molecular properties of ligands
Ligand∆Gbinding

RMSD

logP

TPSA

Weight

H-Acc

H-Don

MAHI1

-12.6301

0.4025-0.49

132.98457.55

10

4

MAHI2

-12.7872

1.64310.57

130.31490.63

9

5

MAHI3

-11.6353

1.0117-0.46

112.15428.54

93

SAM*-11.2605

1.3306-3.94

187.08399.45

11

4

SAH*

-11.2323

1.8644-3.73

212.38384.47

11

4

SFG*

-10.9262

1.6747-3.96

214.72382.40125Note: *Standard Ligand

residue in the binding site. Seven hydrogen bonds arebinding the ligands in the pocket binding such as
Asp1190, Cys1191, Gly1223, Phe1145, Asn 1578,
and Glu1168.
Analysis of Molecular Docking Simulation of
DNMT1 Protein and The Ligands
The ADME-Tox analysis of the best ligands thathave been obtained from the molecular docking
simulation was performed by employing admeSAR[26], and SwissADME [27] software. Determining
the pharmacological properties is essential because
not all of the best ligands may be ready to prepare as
drug candidates due to its toxicity and low ADME
properties that may reduce the efficiency of theligands to served as a drug in the human body. The
result of the ADME-Tox analysis using admeSAR
and SwissADME is shown in Table 3. The
gastrointestinal (GI) absorption and Cytochrome
P450 (CYP) inhibitors parameters were analyzed
using SwissADME software, and the subcellular
localization, organic cation transporter, AMES
toxicity, carcinogens, and biodegradation parameters
were checked using the admetSAR software. Two of
the best ligands had subcellular localization inlysosome and one of these in the nucleus. The
ADME-Tox properties should be same for all of thebest ligands. Besides, standard ligands have several
bad ADME-Tox properties. For example, SFG has
low GI absorption compared to other ligands.

Fig. 3. Interaction of SAMI1 ligand with Amino acidresidue (A) in 3D and (B) in 2D visualization
As the best ligand, MAHI1 has the lower ∆Gbinding
value than standards and have bound on the best
position in the binding site. As shown in Fig. 3,
MAHI1 has 20 interaction with the amino acids
152

SEE - Nagoya, Japan, Nov.12-14, 2018

The druglikeness and the medicinal chemistry
properties of the best and standard ligands wereobtained by using SwissAdme software. The
druglikeness based on Veber’s and Egan’s rule wasdetermined, and the bioavailability value wasobtained. Furthermore, the PAINS (Pan-assay
interference compounds), Brenk, and synthetic
accessibility value were also predicted. The result isshown in Table 4. Based on this test, all of the best
ligands have good druglikeness according to both
Veber’s and Egan’s Rule. All of ligands shown thesame bioavailability value (0.55). According to theresult of analysis from SwissADME software, thebioavailability of all the best ligands was at similarlevel. The synthetic accessibility score of the ligands
was relatively the same as well, varying such as 4.82
(MAHI1). Furthermore, MAHI1 and MAHI3 were
not determined to have any Brenk fragments.
However, some of the best ligands were obtained tohave one molecular fragment that contains PAINS
property. In addition, MAHI1 were not predicted tohave PAINS property.

Table 3. ADME-Tox prediction using admetSAR and SwissADME software

LigandGI
Absorption

Subcellular
LocalizationCYP Inhibitor

MAHI1
MAHI2
MAHI3
SAM*
SAH*
SFG*

High
High
High
High
High
Low

Lysosome
Lysosome
Nucleus
Nucleus
Nucleus
Nucleus

None
None
None
None
None
None

Organic Cation
BiodegradTransporter AMES toxicityCarcinogens
ation(SLC22A2)
Non-inhibitor
Non-inhibitor
Non-inhibitor
Non-inhibitor
Non-inhibitor
Non-inhibitor

No
No
No
No
No
No

No
No
No
No
No
No

No
No
No
No
No
No

Table 4. The druglikeness and medicinal chemistry properties of selected and standards compounds using
SwissADME software
Druglikeness
Ligand
MAHI1
MAHI2
MAHI3
SAM*
SAH*
SFG*

Medicinal Chemistry

Veber

Egan

Bioavailability
score

PAINS

Brenk

Synthetic
accessibility

Yes
Yes
Yes
No
No
No

Yes
Yes
Yes
No
No
No

0.55
0.55
0.55
0.55
0.55
0.55

0 alert1 alert0 alert1 alert0 alert0 alert0 alert0 alert1 alert1 alert0 alert0 alert

4.82
5.13
5.05
4.94
4.69
4.78

Note: *Standard Ligand
Publikasi Internasional Terindeks Untuk Tugas Akhir
Mahasiswa(PITTA)
UI
No:
2328/UN2.R3.1/HKP.05.00/2018 All authors were
responsible in writing of the manuscript. Herewith,the authors declare that there is no conflict of interest
regarding of the manuscript.

CONCLUSION
MAHI1, MAHI2, and MAHI3 have lower∆Gbinding energy and better interaction with DNMT1.
After all process, the selected ligands MAHI1 shows
the best conformation and interaction in the bindingsite of DNMT1 and have better ADME-Tox
properties than all the ligands. The result indicatesthat fragment-based drug design can be an essential
method to discovered in developing a new drug forinhibiting the DNMT1. Finally, our result must be
examined through in vitro and in vivo methods todetermine its potential in the biological condition.

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ACKNOWLEDGEMENTS
This research is financially supported by the
Directorate of Research and Community Engagementof Universitas Indonesia (DRPM UI) through Hibah

153

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

NITRIDING OF PURE TITANIUM BY HIGH DENSITY PLASMAUSING H2-N2 GAS MIXTURE AT LOW TEMPERATURE
Dionysius J. D. H. Santjojo 1, Masruroh 1, Setyawan P. Sakti 1, Maharani S. Rajapadni
11Department of Physics, FMIPA, Brawijaya University, Malang, 65145, Indonesia

ABSTRACT
Most plasma nitriding of titanium was successfully carried out at the temperature higher than 500 ºC. A lower
temperature process is needed to save energy. The experiment was carried out by varying the substrate temperaturefrom 350 to 450 ºC. The plasma was generated in a vacuum chamber by a 2 MHz RF power supply. A gas mixtureof nitrogen and hydrogen was introduced into the chamber resulted in a significantly effective nitriding of thetitanium. The plasma was intensified to a higher density by utilizing a combination of DC bias technique and ahollow cathode. At the optimum mixture of 80% N2 and 20% H2, by the pressure of 35 Pa, a four-hour nitriding
resulted in 20 µm nitrided layer. The hardness of the treated surface was varied between 550 and 1990 HV
depending on the process temperature. XRD measurements showed that the nitriding leads to the formation of
Ti2N and TiN precipitates. Expansion of the original hcp-structured lattices was also noticed. The hardening wasa result of a lattice straining induced by the precipitates and also a possible small percentage of nitrogen solidsolution.
Keywords: Plasma nitriding, High density plasma, Low temperature, Titanium, Hardening

method which has been established for metals [9].
The method has proven itself to be efficient due to its
shorter process time and reduction of gas usage. In
addition, it is an environmentally friendly process[10]. Other advantages of the plasma nitriding comefrom its flexibility for selective nitriding and highpossibility to be implemented in industrial scale.
A study of the plasma nitriding for a titanium
alloy Ti6Al4V, show that the process carried out at atemperature of 1000 ºC for 10 hours was able toincrease the hardness up to 1365 HV [11]. Anotherresearcher successfully hardened a Ti5Al4V2Mo
titanium alloy by plasma nitriding at 1173 K for 4
hours. The surface hardness was 1.7 times higher thanthe original hardness. The thickness of the nitrided
layer was 30 µm containing nitride precipitates [12].
Researchers found that the increase of the surface
hardness in the plasma nitriding was caused by theincrease of nitrogen concentration in the surface andsubsurface in the form of a solid solution and TiN[13]. Despite the many advantages of the plasma
nitriding technique, the high temperature thermochemical process for titanium may cause degradationof fatigue strength and a detrimental of
microstructural changes in titanium substrates [14].
Further advancements of the technique should beundertaken to reduce the holding temperature during
the process which can minimize the degradation of
the fatigue strength and the microstructural
deterioration. The low temperature process is also
desirable for reducing the usage of energy.
This work was focused on the plasma treatment ofpure titanium to gain fundamental knowledge of an

INTRODUCTION
Titanium has been tremendously the interest in
many fields of applications, such as aerospace [1],automobile industries [2], home appliances, andmedical implants [3]. The metal is lightweight and yet
performs high mechanical performances. It has highstability at high temperature and high corrosion
resistance. Alloying the titanium with other metals
such as aluminum, vanadium and molybdenum
produces a wider range of application [4].
However, the drawback of the utilization of thetitanium is due to its poor tribological properties, i.e.,
low surface hardness, low wear resistance and highfriction coefficient. It is important to enhance thetribological properties so that even wider utilizationis possible in the future. The enhancement should also
consider the durability and usage life especially when
frictions cannot be avoided [5].
There have been many efforts to enhance thetribological properties of pure titanium by surface
modifications such as nitriding process. It is wellknown that he nitriding process can increase thesurface hardness and hence the wear resistance of
metals [6]. From the history of titanium nitriding, it
has been learned that the metal can be hardened
effectively by incorporating the nitrogen into the hcp
structured or the α-phase. A number of methods andtechniques have been proposed such as a gas nitriding
by a nitrogen thermo-diffusional treatment [7] ordepositing a layer of nitride by physical vapor
deposition (PVD) [8].
Recently, a plasma nitriding is utilized to modify
the titanium’s surface. It is a common nitriding
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alternative high density plasma utilized for surface
hardening. Other researchers reported that at a
relatively low holding temperature of 500 ºC, thehardening was controlled by the nitrogen solid
solution. On the other hand, at higher holding
temperature the hardening was also affected by theformation of TiN and Ti2N precipitates [15]. The
application of the alternative high density plasma wasintended to compensate the lower holding
temperature. A combination of a DC bias voltage anda hollow cathode was employed to produce the highdensity nitrogen plasma. Other than the combination,
the previous study has shown that incorporation of asmall amount of hydrogen in the nitrogen plasma
produced active nitrogen species in the plasma which
resulted in highly effective nitriding [16]. The amountof the hydrogen inclusion was determined by meansof optical emission spectroscopy (OES) andLangmuir impedance measurement. It was found thatthe appropriate concentration of the hydrogen to bearound 17%. The ratio resulted in nitrogen plasma
containing a large density of N2*, N2+ and NH
complexes behaving as positively charged species.
The species are chemically active and are able toproduce a high concentration of high energy atomic
nitrogen which diffuses into the metal uniformly via
complex surface reactions.

Fig. 1A schematic representation of the hollow
cathode plasma nitriding system.

After the loading procedure, the chamber was
pumped down to 0.5 Pa to evacuate the air. The heater
was then turned on to increase the substratetemperature to the process temperature, i.e., 350, 375,
400, 425 or 450 ºC. Before the main plasma treatment
process, the samples underwent a pre-treatment for 1
hour. The pre-treatment process was carried out by
applying a 100% nitrogen plasma at the processtemperature and at the chamber pressure of 70 Pa.
The RF and DC bias voltage during the pre-treatment
process was 250 and 500 volts respectively. The main
plasma nitriding treatment was carried out
immediately at a lower pressure of 35 Pa with amixture of 80% N2 and 20% H2 for 4 hours. The RF
and DC bias voltage during the main process was 250
and 600 volts respectively.
Surface hardness characterization of thespecimens was carried out using a Vickers microhardness testing system (Akashi MVK-H1). The
measurement was taken at five different points on
every specimen with the applied load of 1N or 100
gfs. Cross-sectional hardness measurements wereconducted to obtain a hardness depth profile
characteristic of the specimens. The measurements
were taken at points having the distance of 10, 20, 30,
40, 50 and 60 µm from the surface. Accompanying
the depth profiling measurement, cross-sectional
micrograph observations were conducted by using ascanning electron microscope (JEOL JSM-7100 F).
An X-ray diffractometer (XRD, Rigaku
SmartLab) was utilized to identify the
crystallographic phases of the specimens. The
observation was carried out under a monochromatedCu Kα radiation with λ = 1.54598 Å at a range ofdiffraction angle of 30 to 90 degrees with a step angleof 0.010 degrees.

EXPERIMENTS
A high density nitrogen plasma reactor was
utilized to achieve the successful low temperaturenitriding. The reactor consists of a vacuum chamber,an RF generator a high voltage DC generator. The
nitrogen plasma was generated by applying the RF
generator on the two floating electrodes (anodes) inthe chamber. The base frequency of the RF was 2MHz. The reflected power was minimized by anelectronic matching system shifting the frequency
around the base. A high DC voltage was applied to acathode to accelerate ions toward it. The applicationof the DC bias increased the density of the plasma inthe cathode area [6]. Further enhancement of theplasma density was achieved by setting up a hollow
rectangular metal tube on the cathode. Due to theelectrical connection, the tube functioned as a hollow
cathode. The cathode assembly was equipped with acontrolled heater providing a constant temperature.
The system is described in Figure 1.
Samples for this study was obtained from a 1 mm
thick pure titanium (Industrial Grade I) sheet which
was cut into 20 x 20 mm rectangular pieces. A
cleaning procedure was applied including alkaline
degreasing and ultrasonic cleaning. After a drying
process, the sample was immediately loaded into theplasma reactor by placing it in the hollow cathode as
seen in Figure 1.

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SEE - Nagoya, Japan, Nov.12-14, 2018

The SEM image shows a whitish area indicatedthe existence of a nitrided layer reaching the depth of
23 µm. The thicker layer was observed on thespecimen treated at higher holding temperature.
Further study was carried out by examining thechange of the titanium phase before and after thetreatment by means of XRD measurements as shownin Figure 4.

RESULTS AND DISCUSSIONSThe high density nitrogen plasma treatment by
the application of a combination of DC bias voltage
and a hollow cathode resulted in an effective
hardening of pure titanium. The original hardness ofthe titanium was 319.4 HV. Depending on the sample
temperature during the plasma treatment, the surface
hardness was increased up to 1989 HV (at 450 ºC).
Measurement of the hardness on the cross-sectionalsurface revealed the depth hardness profile due to theplasma treatment as shown in Figure 2.

Fig. 2 Hardness depth profile of pure titanium
specimens treated with the high density plasma at various
temperature for 4 hours.

It can be seen from the Figure 2, the hardness
profile shows preservation of a relatively highhardness to the deep and abruptly decrease at around
20 µm depth. The SEM micrographic observation
confirmed that the profile is related to the nitrogen
distribution in the nitriding area. Figure 3 shows arelational illustration of the SEM micrograph and thehardness depth profile measurement.

Fig. 4 X-ray diffractogram of untreated and plasma
treated specimens.

Pure titanium used in this work has an ideallyhexagonal close packed (hcp) structure. This
untreated α-titanium can be confirmed by the peaks
shown in Figure 4 which match the database for thepure titanium (α-Ti). In the plasma treated specimens,
some of these line peaks are shifted to the lower
angles. The shift of the peak indicates the occurrenceof lattice straining of the α-Ti due to the interstitial
nitrogen resulted in α’(N)-Ti. The expansion can beobserved from the shift of peak at 40.5 degree toward̅ 1] plane as
39.5 degree. The peak is assigned to [101seen in Figure 5.

Interstitial
NitrogenFig. 3 SEM micrograph observation related to thehardness depth profile of pure titanium specimen treatedwith the high density plasma at a temperature of 400 ºC for
4 hours.

(a)(b)

Fig. 5 Illustration of: (a) the [101̅1] plane in the hcp
structure; and (b) interstitial nitrogen residing at theoctahedral vacancy site.

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The solid solution interstitial nitrogen can resideat either octahedral or tetrahedral site in the hcp
structure. However, the expansion of the [101̅1]
plane indicated that the interstitial nitrogen prefers theoctahedral vacancy sites (Figure 5). The radius of
nitrogen solute or rN is 0.92 Å, while the size of theoctahedral rO and tetrahedral r T vacancy sites are =0.6 Å and 0.33 Å respectively. The relative available
space size of the vacancy and the replacement solute
size determine the possibility of site occupation forthe solute to vacancy [17]. Generally, the wider sizeof octahedral vacancy site is preferable for thenitrogen solute occupation in the localization process.
Since the rN > rO , the occupation of the nitrogen is
accompanied with lattice expansions, especially inthe c-axis.
Other than the shift, new peaks were observed in
the diffractogram of the treated specimens. The peaks
are related to the phase of TiN and Ti2N. The peak at
37.15 and 43.4 degree are related to the TiN
diffraction plane, while the Ti2N phase was indicatedby the peaks at 51.3 degree and 40.3 which overlap
with the previous [101̅1] plane reflection. The
previous study suggested a possibility of theoccurrence of a phase transformation from α-Ti to Ti which was indicated by the peak at 37.15 degree[18]. However, the transformation should include the-Ti which was not observed in the diffractogram.
This is due to the plasma treatment process was
conducted far below the  to  transformation
temperature, i.e., 1156 K (883ºC) [15]. The effect of
the holding temperature during the plasma nitriding
on the lattice straining is summarized in Table 1.

hardening as a function of the holding temperature isshown in Figure 6.

Fig. 6 Illustration of: (a) the [101̅1] plane in the hcp
structure; and (b) interstitial nitrogen residing at theoctahedral vacancy site.

The hardening was evidently controlled by thelattice straining. In this low temperature process, thenitrogen diffuse into the α-Ti matrix forming fineprecipitation of TiN and Ti2N and also the interstitialsolid solution, i.e., α’(N)-Ti. The combination of thethree phases was varied with the change of theholding temperature. In the high temperaturenitriding, the hardening was strongly controlled byboth the precipitation reaction and also the  to phase transformation [11], [14]. Closely observationon the peak at 43.4 degree for the [200] plane of the
TiN and 61.5 degree for the [112̅0] plane of theα’(N)-Ti in Figure 4 reveals that the increase of theincrease of the holding temperature decrease the TiN
population. At the same time, the intensity of theα’(N)-Ti was increased. This indicates that theformation of the solid solution phase was related tonitrogen super-saturation state in the hcp structure.
The hardening of the pure titanium by means of the
low temperature nitriding is strongly affected by thepresence of the interstitial nitrogen in the hcp
structure.

Table 1 The effect of holding temperature during
plasma nitriding process on lattice straining
α-Ti phase
Lattice
NitridingStrainingacTemp. (C)
c/a
(%)
(Å)
(Å)
Unprocessed 2.9421 4.6703 1.5874
350
2.9642 4.8669 1.6419
4.21375
2.9658 4.8681 1.6414
4.24
400
2.9658 4.8694 1.6419
4.26
1.6423425
2.9658 4.8707
4.29
450
2.9658 4.8719 1.6427
4.32

CONCLUSION
The high density plasma nitriding using a
mixture of 80% nitrogen and 20% has effectively
hardened the pure titanium at low temperature. The
nitrogen diffused deep into the α-Ti matrix forming
TiN, Ti2N and α’(N)-Ti phases. A nitrided layer withthe thickness of 30 µm was obtained with the holding
temperature of 425 ºC resulted in surface hardness of
1696 HV. The hardness of the surface reached 1989
HV after the nitriding with the temperature of 450 ºC.
The nitrided layer was anisotropically strained in
the c-axis. The lattice straining which was noticeably
increased with the increase of the increase of theIt can be seen from the table, the plasma nitriding
treatment resulted in lattice strains. However, theexpansion was anisotropic since the crystalline strainsin the c-axis is larger than those in the a-axis. The
straining in the a-axis was not changed at thetemperature above 375 ºC. On the other hand, thestraining in the c-axis continues to grow with theincrease of the holding temperature. The relation
between the lattice straining in c-axis and the158

SEE - Nagoya, Japan, Nov.12-14, 2018

α’(N)-Ti phases. The nitrogen solid solution resides
at the octahedral vacancy sites. Although the highhardness is usually attributed to fine precipitation of
Ti2N and TiN, evidently the existence of nitrogen
super-saturation in the α-Ti lattices greatly affect thehardness.
Further study of the diffusion and the formationof phases related to the high density nitrogen plasma
will open new possibilities in hardening titanium andits alloy efficiently.

[8] S. H. N. Lim, D. G. McCulloh, S. Russo, M. M.
M.
Bilek,andD.
R.
McKenzie,“Characterisation of titanium nitride thin films
prepared using PVD and a plasma immersion ion
implantation system,” Nucl. Instruments
Methods Phys. Res. B, vol. 190, pp. 723–727,
2002.
[9] Istiroyah, I. N. G. Wardana, and D. J. Santjojo,
Comparison of AISI 316L plasma nitriding
behavior in low and medium temperature, vol.
493. 2014.
[10] L. Han, J. T. Dai, X. R. Huang, and C. Zhao,“Study on the fast nitriding process of active
screen plasma nitriding,” Phys. Procedia, vol. 50,
no. October 2012, pp. 94–102, 2013.
[11] E. Koyuncu, F. Kahraman, and Ö. Karadeniz,“Investigation of surface properties of hightemperature nitrided titanium alloys,” J. Achiev.
Mater. Manuf. Eng., vol. 37, no. 2, pp. 434–441,
2009.
[12] Y. V. Borisyuk, N. M. Oreshnikova, M. A.
Berdnikova, A. V. Tumarkin, G. V.
Khodachenko, and A. A. Pisarev, “Plasma
nitriding of titanium alloy Ti5Al4V2Mo,” Phys.
Procedia, vol. 71, no. February, pp. 105–109,
2015.
[13] A. Samanta et al., “Nano- and micro-tribologicalbehaviours of plasma nitrided Ti6Al4V alloys,”
J. Mech. Behav. Biomed. Mater., vol. 77, no.
August 2017, pp. 267–294, 2018.
[14] H. Yilmazer, S. Yilmaz, and M. E. Acma,“Treatment of Surface Properties of Titanium
with Plasma (Ion) Nitriding,” Defect Diffus.
Forum, vol. 283–286, no. March, pp. 401–405,
2009.
[15] A. Zhecheva, W. Sha, S. Malinov, and A. Long,“Enhancing the microstructure and properties oftitanium alloys through nitriding and othersurface engineering methods,” Surf. Coatings
Technol., vol. 200, no. 7, pp. 2192–2207, 2005.
[16] D. J. Santjojo, T. Aizawa, and Istiroyah, “THEROLE OF HYDROGEN IN HIGH RATE
PLASMA NITRIDING OF MARTENSITESTAINLESS STEEL,” in 4th Asian
Sysmposium on Materials and Processing, 2015,
vol. 2, pp. 3–4.
[17] A. Gicquel, N. Laidani, and P. Saillard, “Plasma
and nitrides: application to the nitriding oftitanium,” Pure Appl. Chem., vol. 62, no. 9, pp.
1743–1750, 1990.
[18] J. M. Windajanti, D. J. Djoko H S, andAbdurrouf, “Low-Temperature Nitriding of Pure
Titanium by using Hollow Cathode RF-DC
Plasma,” IOP Conf. Ser. Mater. Sci. Eng., vol.
202, no. 012026, 2017.

ACKNOWLEDGMENTS
The authors would like to express their gratitude
to Prof. Tatsuhiko Aizawa of Shibaura Institute ofTechnology, Japan for the long-life research anddevelopment collaboration especially in the field of
surface modification. This study is managed by
Collaborative Research Center for Advanced System
and Material Technology (Brawijaya University) andpartly supported by JSPS-DGHE program on theinternational collaborative research in 2017.

REFERENCES[1] X. Zhang, Y. Chen, and J. Hu, “Recent advancesin the development of aerospace materials,”
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35–60, 2018.
[2] S. Yadav, S. Gangwar, and S. Singh,“Micro/Nano Reinforced Filled Metal Alloy
Composites: A Review over Current
Development in Aerospace and Automobile
Applications,” Mater. Today Proc., vol. 4, no. 4,
pp. 5571–5582, 2017.
[3] M. Kaczmarek et al., “In vitro biocompatibilityof titanium after plasma surface alloying withboron,” Mater. Sci. Eng. C, vol. 69, pp. 1240–
1247, 2016.
[4] C. Veiga, J. P. Devim, and A. J. R. Loureiro,“Properties and applications of titanium alloys:a brief review,” Rev. Adv. Mater. Sci., vol. 32,
no. 2, pp. 133–148, 2012.
[5] Y. Yang, C. Zhang, Y. Dai, and J. Luo,
“Tribological properties of titanium alloys underlubrication of SEE oil and aqueous solutions,”
Tribol. Int., vol. 109, no. November 2016, pp.
40–47, 2017.
[6] D. Santjojo, T. Aizawa, S. Muraishi, and H.
Morita, “Micro-Texturing of Stainless Steels
Via High Density Plasma Nitriding,” inProceedings of the 9th International Conferenceon MicroManufacturing, 2014.
[7] D. B. Lee, I. Pohrelyuk, O. Yaskiv, and J. C. Lee,“Gas nitriding and subsequent oxidation of Ti6Al-4V alloys,” Nanoscale Res. Lett., vol. 7, no.
1, p. 21, 2012.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

OPTICAL EMISSION SPECTROSCOPY STUDIES DURINGNITROGEN PLASMA OF POLYSTYRENE SURFACESMODIFICATION
Masruroh1*, Dionysius J. D. H. Santjojo1 Heraniawati1, Muhamad A. Abdillah1, Tyas N Zafirah1 and Eka
Maulana2, Setyawan P. Sakti1
1

Department of Physics, FMIPA, Brawijaya University, Malang, 65145, Indonesia

2

Department of Electrical Engineering, Brawijaya University, Malang, 65145, Indonesia*corresponding author: Masruroh, email: ruroh@ub.ac.id
ABSTRACT

Nitrogen plasma treatment was successfully performed to modify polystyrene surfaces from hydrophobic intohydrophilic. The objective of the work was to achieve better wettability of the polystyrene surfaces. Various
surface characters of the polystyrene were obtained by synthesising the polystyrene layer from different molecularweight (Mw) solution using a spin coating method. The solution prepared for the coating procedure was made bydissolving monomers which have Mw of 35,000 g/mol, 192,000 g/mol, and 280,000 g/mol into toluene solvent at
the concentration of 6%. The polystyrene surfaces then treated by means of the nitrogen plasma using a 2MHz
plasma generator with the power of 40 watts and the gas flow of 20 ml/minutes for 2 minutes. The optical emission
spectroscopy (OES) provided the measurement of plasma species and the calculated electron temperature (Te) andelectron density (𝑛𝑛𝑒𝑒 ). The species N2+ ion was identified from the intensity emission of OES. The existence of theN2+ ion and corresponding to the condition of Te and ne in the plasma plays a key role in the polystyrene’s surfacechanges as found in the polystyrene surface after plasma treatment. After plasma treatment, nitrile functional group(C≡N) was found in the polystyrene surface which is indicated by the FTIR fingerprint of the nitrile functionalgroup at the vibration peak of 2300-2400 cm-1. The existence of the C≡N represent the surface changed fromhydrophobic to hydrophilic. This result was in agreement with a lower contact angle of the polystyrene surface.
Keywords: Nitrogen Plasma, N2+ ion, OES, nitrile and polystyrene

Optical Emission Spectroscopy (OES) in UV-vis
regions is a method that can be used to diagnose
plasma as non-invasive and in situ method. Since
most of the plasma is generated in a vacuum chamber,the OES system measure the emission via an opticalfiber attached to the chamber. These emissions are theresult of the particle de-excitation [5]. It provides
valuable information such as electron temperature,ion density, and electron density. Where the data arepresented in the form of line-ratio. That is, each line
spectrum shows an optical transition between twolevels of quantum energy [6].
Polymeric materials are widely used in many
applications due to their mechanical properties(including flexibility) of thermal conductivity,transparency, chemical inertia, etc. However, some
applications require certain surface properties(wettability, adhesion, biocompatibility), which canbe achieved by plasma treatment [7, 8]. Polystyrene(PS) is one of the most widely used materials forapplications included in sensor development. The
polystyrene can be used as itself and also combinedwith other materials. One of the objectives of the

INTRODUCTION
Plasma-based approach has gained considerable
popularity for modifying interfacial polymers toenhance bondings with subsequent molecularimmobilization layer designed to contact withspecific biological responses [1]. This is because theplasma has the ability to change physical andchemical properties of surfaces without affecting bulk
properties [2] . In addition, this method also requiresa shorter treatment time compared to other surface
modification methods. When the plasma is exposed
to polymer surfaces, formation of new functionalgroup, graft polymerization, coating, and molecularcrosslink is occurred [2]. In general, modification
using plasma will increase the surface energy andcause the surface of the polymer increasinglyhydrophilic [3]. Modification of polymers using aplasma nitrogen can also cause the formation of polargroups such as amine, imine, amide, and nitrile on thepolymer surface [4]. The presence of such functionalgroups is due to the chemical interactions between theplasma species (ions, electrons, neutrals, and radicals)with the polymer chains.
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polystyrene modification in the sensor world is toachieve better adsorption of biomolecules on thesurface. In the present paper, OES was used todiagnose and determine the state of the nitrogenplasma i.e., plasma species, electron temperature Te
and electron density 𝑛𝑛𝑒𝑒 during the plasma treatment
process. This characterization is important to control
the nitrogen plasma processing on polystyrene′s
surface. The relationship between the species plasma,
Te and 𝑛𝑛𝑒𝑒 with the surface wettability and functionalpolar group is discussed.

line at wavelength of 387.8 nm, 424.1 nm, and 467.4
nm. The relative intensity for selected spectral line of
the NII was used to calculate temperature electron byusing Boltzmann’s equation:
𝐥𝐥𝐥𝐥

𝑰𝑰𝝀𝝀
𝑬𝑬𝒊𝒊
= 𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪𝑪 −
𝒈𝒈𝒈𝒈
𝒌𝒌𝒌𝒌

(1)

I = observed emission intensity
𝝀𝝀 = wavelength of the emission line
𝑔𝑔 = statistical weight𝑨𝑨 = transition probability for spontaneous emission
Ei = excitation energy
K = Boltzmann constant
T = temperature

EXPERIMENTAL DETAILSSamples in this work were a layer of polystyrene
thin film deposited on a QCM surface. The raw
materials were polystyrene granules with various
molecular weight of 35,000 g.mol-1, 192,000 g.mol-1,
and 280,000 g.mol-1. The granules of each Mw weredissolved in toluene solvent to make of 6% solutionof the polymer. The polystyrene solution was
deposited on the QCM surface with spin coating
technique with a rotational speed of 3000 rpm and adeposition time of 60 seconds.
Modification polystyrene surface was performed
using a 2 MHz plasma generator at 40 watt RF power,
40 Pa pressure, 20 ml / min gas flow rate andtreatment time for 2 min. During the plasma treatment
process, the plasma spectrum was characterized by
Optical Emission Spectroscopy (AURORA-4000).
The experimental set-up for identifiying the plasma
species is shown in Fig. 1. An optical sensor was
fixed to the chamber window and connected to an
optical spectrometer. The active plasma species thenanalyzed using a computer controlled system with
software spectral analysis which appear the graphbetween wavelength (λ) vs. the intensity. The
measurable wavelength detected in the spectrometeris from 200 nm to 1000 nm. Then the emission
spectra was performed with NIST's Atomic Databaseto determine species plasma, the electron
Temperature (Te) and electron density (𝑛𝑛𝑒𝑒 ).

Te is calculated from the slope of the straight line
𝟏𝟏(− ) fitted to a plot of the left-hand side of equation
𝒌𝒌𝒌𝒌(1) against Ei.
The calculated electron density was determinedby from spectral line broadening by the Stark-effect[9, 10]. This method was selected due to the appeared
relative emission intensities only singly ionizedspecies. The Stark broadening can be deduced and the
FWHM of Stark broadening is related to the electron
density by the following equation:∆𝜆𝜆1/2 = 2𝜔𝜔 �𝑛𝑛𝑒𝑒 = �

𝑛𝑛𝑒𝑒
�
1016

∆𝜆𝜆1/2 1016
�2𝜔𝜔𝑛𝑛𝑒𝑒 ≥ 1,6 𝑥𝑥 1016 𝑇𝑇1/2 (∆𝐸𝐸)3

(2)

(3)

(4)

𝑛𝑛𝑒𝑒 = electron density in m-3∆𝜆𝜆 = full-width at half-maximum (FWHM) in nm∆𝑬𝑬 = energy of the emitting level

The contact angle was measured using the contact
angle [11]. Measurement and the polar functionalgroups are observed with Fourier Transfrom Infrared(FTIR) before and after treated by nitrogen plasma.

RESULTS AND DISCUSSION
In nitrogen plasma, the active species that interact
with polystyrene surfaces, electron temperature andelectron density are observed with OES. Fig. 2 showsa typical emission spectrum of nitrogen plasma asfunction of wavelength and intensity obtained fromMw with 35,000 g/mol.

Fig. 1 Scheme of the optical emission spectroscopy
for measurement of species in the plasma process
In this work, the NII was selected for theestimation of the temperature electron. Based on theexperimental results the NII was found at the spectral
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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 2 Emission spectra of nitrogen plasma at Mw of
35,000 g/mol

Fig 3. The OES intensity of emission spectral ion
N2+ in the polystyrene surfaces during plasma
process with different Mw.

As seen in Fig. 2, the main emitted species areobserved at the wavelength of 387.810 nm, 424.123
nm and 467.7 nm. Based on the Atomic Database
NIST spectrum, this main emission spectrum is NII[12]. The presence of 𝑵𝑵𝟐𝟐+
which show ion 𝑵𝑵+
𝟐𝟐species has a very important role in the polystyrene
surface modification process.
The 𝑵𝑵𝟐𝟐+ ionic state is essentially produced theelectron impact process [13], the reaction mechanism
can be seen below:
e + 𝑁𝑁2 (X, 0) → e + e + 𝑁𝑁𝟐𝟐+ (B, ν′)(5)As shown in Fig 3, the intensity of emission of N2+ions in a variation of Mw indicates a decreasing
intensity change. This corresponds to the increasing
number of N2+ ions reacting with the C atom to form
the C≡N group. The appearance of ion 𝑵𝑵+
𝟐𝟐 in theOES spectra is attributed to the observation withFTIR as shown in Fig. 4. The FTIR spectra show the
new peaks at the wavelength of 2300-2400 cm-1 after
treated by plasma nitrogen. This peaks represent to
the nitrile functional group (C≡N) which is the polargroup. The presence of such polar groups indicates athin layer of polystyrene having wettability due tochanges in functional groups which make thepolystyrene surface properties more reactive. The
presence of a polar group indicates that the surface ishydrophilic as indicated by the low angle of contact
as shown in Fig. 5. The contact angle reduced withthe higher molecular weights after treated by plasma
treatment. The higher the molecular weight theabsorbance intensity of the C≡N increases.

Fig. 4 The FTIR nitrile spectra of the polystyrene
surface treated by nitrogen plasma withdifferent Mw.

Fig. 5 Contact angle of the polystyrene surface before
and after treated by nitrogen plasma variedwith different Mw.
Fig. 6 shows the plotted graphic between electron
temperature (Te) and electron density (𝒏𝒏𝒆𝒆 ) andvarious Mw. The electron temperature indicates theenergetic electrons that initiate dissociations andionizations. Plasmas with high electron temperatures(i.e., energies) give the ion 𝑵𝑵+
𝟐𝟐 bombard the surfaceof polystyrene and their energies are enough to break
the C atom from polystyrene to form the C-N bond.
The higher the Te, the more the ion bombardment

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occurred and affected by the ionization process. The
higher the ionization, the stronger the bond between
N and C atom. The electron temperature is increased
until Mw of 192,000 g/mol then slightly decreased at
28,000 Mw. However, the FTIR absorption spectra
show the increasing of the C≡N functional group.
This phenomena cannot be described clearly due tocomplex plasma chemistry and will be investigated in
the future. On the other hand, the electron density
show decrease with the increasing Mw. Thisphenomenon due to the more the formation of C≡Nbond results in the reduction of the species ion N2+
due to the N ion incorporate with C atom to form CN bond.

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Surf. Coat. Technol., vol. 233, 2013, pp. 99–107.
[3] S. Ebnesajjad and C. F. Ebnesajjad, Surface
Treatment of Materials for Adhesive Bonding,
2nd edition., Waltham, USA, Elsevier Inc, 2014.
[4] D. Pal, S. Neogi, and S. De, Surface Modifi
cationofPolyacrylonitrile
Co-Polymer
Membranes Using Pulsed Direct Current
Nitrogen Plasma, Thin Solid Films, vol. 597,
2015, pp. 171–182.
[5] J. Koo et al., Design of Optical Emission
Spectroscopy
Based
PlasmaParameter
Controller for Real-Time Advanced Equipment
Control, Comput. Chem. Eng., vol. 100, 2017,
pp. 38–47.
[6] K. E. Evdokimov, M. E. Konischev, V. F.
Pichugin, and Z. Sun, “Study of Argon Ions
Density and Electron Temperature and Density
in Magnetron Plasma by Optical Emission
Spectroscopy and Collisional-Radiative Model,
Resour. Technol., vol. 3, no. 2, pp. 187–193,
2017.
[7] M. D. Ionita, M. Teodorescu, T. Acsente, M.
Bazavan, E.R. Ionita, G. Dinescu, Romanian
Journal of Physics, 56, 2011.
[8] M. D Ionita, M. Teodorescu, C. Stancu, E.C.
Stancu, E.R. Ionita, A. Moldovan, T. Acsente, M.
Bazavan, and G. Dinescu, Journal of
Optoelectronics and Advanced Materials, 12,2010, pp. 3.
[9] Musadiq, M., Nasir Amin, Yasir Jamil, Munawar
Iqbal, M. Asif Naeem, Hafiz Akif Shahzad,
Measurement of Electron Number Density andElectron temperature of Laser-Induced Silver
Plasma, International Journal of Engineering andTechnology. Vol. 2, No. 1, 2013.

Fig. 6 The relationship between electron temperature(Te) and electron density (𝑛𝑛𝑒𝑒 ) for variation
molecular weight.
CONCLUSION
The wettability of the polystyrene′s surfacechanges from hydrophobic to hydrophilic after
treated in nitrogen plasma using 2 MHz RF generator.
The results proved that the enhanced wettability due
to reaction of the C≡N and the N2+ ion detected withcorresponding Te and 𝒏𝒏𝒆𝒆 of the plasma. The intensityof the N2+ ion and electron density decrease with theincreasing the Mw. However, the Te was slightly
increase with the Mw then decreasing. Thisphenomenon cannot be described clearly due to thecomplex plasma chemistry and will be studied in the
future.

[10] Dezhi Xiao, Yuedong Meng, Cheng Cheng, Jiangang Li, Jie
Shen, Yan Lan, Paul K. Chu, Hongbing Xie, and Xingsheng
Shu, Electron density measurements of atmospheric-pressure
non-thermal N2 plasma jet by Stark broadening andirradiance intensity methods, Physics of Plasma 21, 2014,
053510[11] Setyawan P Sakti, Rizal Y Aji, Laili Amaliyah and Masruroh,
Low-Cost Contact Angle Measurement System for QCM
Sensor, Telkomnika Vol. 15, 2017, pp. 560-569.
[12] Z. Machala, M. Janda, K. Hensel, I. Jedlovsky, L. Lestinska,
V. Foltin, V. Martisovits, and M. Morvova, Emission
Spectroscopy of Atmospheric Pressure Plasmas for BioMedical and Environmental Applications, Journal of
Molecular Spectroscopy 243,2007, pp.194–201[13] L. M. Isola, BJG omez and V Guerra, Determination of The
Electron Temperature and Density in The Negative Glow ofa Nitrogen Pulsed Discharge Using Optical Emission
Spectroscopy, J. Phys. D: Appl. Phys. 43, 2010, 015202(10pp)ACKNOWLEDGEMENTS
This work is supported by Ministry of Research,
Technology and Higher Education of the Republic ofIndonesia.
REFERENCES[1] Kim Shyong Siow, Leanne Britcher, Sunil
Kumar, Hans J. Griesser, Plasma Methods for
The Generation of Chemically Reactive Surfaces1634th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECTS OF SOIL QUALITY ON EATING QUALITY OF ‘Namwa’
BANANA (Musa ABB) FRUIT
Pannipa Youryon1 and Suriyan Supapvanich2
Department of Agricultural Technology, Prince of Chumphon Campus, King Mongkut’s Institute ofTechnology Ladkrabang, Chumphon Province, Thailand
2
Department of Agricultural Education, Faculty of Industrial Education and Technology, King Mongkut’s
Institute of Technology Ladkrabang, Bangkok, Thailand
1

ABSTRACTThe purpose of this research was to investigate the quality of ‘Namwa’ banana fruit grown in different soil
quality places. The bananas were cultivated at Pathiu, Thasae and Muang districts, Chumphon province (Southern
Thailand), where the pH an organic matter are 5.58 and 0.75%, 5.32 and 1.66%, and 6.93 and 2.45%, respectively.
Physicochemical quality attributes of the ripe banana (2 days after colour break) were determined. The results
show that the banana grown in Pathiu had the highest fruit weight compared to the others. No significant difference
in total acidity, total soluble solids contents, texture and peel colour of all bananas were found. Pulp yellownessof the banana grown in Muang was significantly higher than the bananas grown in Pathiu and Thasae (P < 0.05).
The banana grown in Muang and Thasae had antioxidant activity being higher than the banana grown in Pathiu
district. The highest total phenolic compounds and flavonoids contents were found in the banana grown in Muang
followed by the banana grown in Thasae and Pathiu, respectively. In conclusion, the soil quality such as neutral
pH and high organic matter content promotes high edible quality of ‘Namwa’ banana fruit.
Keywords: ‘Namwa’ banana, soil quality, eating quality and bioactive compounds

AAA or Musa AA which the research work of
postharvest quality of Musa ABB is rare. Thus, weare interested to investigate the physicochemical
quality of ‘Kluai Nam Wa’ banana grown in different
areas in Chomphon province. The quality of ‘Kluai
Nam Wa’ banana fruit grown in three districts of
Chomphon province such as Muang, Thasae andPathiu where having different soil quality were
investigated.

INTRODUCTION
Banana is an important commercial tropical fruit
belonging to the family Musaceae genus Musa. In
Thailand, the most three banana cultivars grown forcommercial are Hom Thong (Musa AAA group),‘Kluai Khai’ (Musa AA group) and ‘Kluai Nam Wa’(Musa ABB group) [1]. Banana is an exotic fruit
which commonly recognized having high nutrients
including oligosaccharides, vitamins, potassium aswell as a rich source of bioactive compounds such as
antioxidants, phenolic and flavonoid compounds [2,3]. Many previous works had been reported thenutritional value of bananas which consisting of highvaluable phytochemicals such as gallic acid, catechin,gallocatechin and naringenin [4]. Moreover, banana
has been proven having free radical scavenging
activity more than guava and rose apple [5].
‘Kluai Nam Wa’ banana (Musa ABB group) is
one of the most popular commercial bananas inThailand. The banana is mostly produced fordomestic market which 70 % of this banana has beengrown around Thailand [1]. It is commonly acceptedthat preharvest factors such as climate, season, thelevel of rainfall and soil quality affecting postharvest
quality of fruits including bananas. Elgar et al. [6]Lentheric et al. [7] and Streif and Saquet [8] suggestthat preharvest factors especially climate of season
and soil characteristics influence on eating andnutritional qualities of fruit. Recently, the mostresearches of banana have been focused on Musa

MATERIALS AND METHODS
Raw Materials
The soil quality of banana plantations of each
district was also determined and the data of soil
quality was shown in Table 1.
Table 1 Soil quality of banana plantation at Pathiu,
Thasae and Muang districts, Chumphon
province, Southern Thailand.
Soil compositions
pH
Organic

matters(%)
P (mg kg-1)
K (mg kg-1)
Ca (mg kg-1)
Mg (mg kg-1)

164

Banana plantation area
PathiuThasae Muang
5.85
5.32
6.93
0.75
1.66
2.45
25.21
35.93
5002.27853.0212.56
62.05
642.73286.1536.89
33.84
109.5620.46

SEE - Nagoya, Japan, Nov.12-14, 2018

Colour Measurement

Statistical Analysis

Peel and pulp colour attributes were measured
using a Chroma meter CR 400 (Minolta, Japan).
Lightness (L*) and yellowness (b*) values of banana
peel were observed and L*, b* and whiteness index(WI) values of banana pulp were monitored.

The data were statistically analysed using
ANOVA and the means of each treatment wascompared by Duncan’s New Multiple Rang Test
(DMRT). The data were shown as the mean of ten
replications and standard deviation.

Colour Measurement

RESULTS AND DISCUSSIONS

Peel and pulp colour attributes were measured
using a Chroma meter CR 400 (Minolta, Japan).
Lightness (L*) and yellowness (b*) values of banana
peel were observed and L*, b* and whiteness index(WI) values of banana pulp were monitored.

Colour Attributes
Table 2 show colour attributes of peel and pulp of‘Namwa’ banana fruit cultivated in three places
having different soil quality. The results show that no
significant differences in L* and b* values of thebanana fruit peel grown in Pathiu, Thasae and Muang
districts. Interestingly, we found that cultivation area
where having different soil quality had influence on
pulp colour of the ripe banana fruits. The yellownessof banana pulp fruits grown in Pathiu was higher thanthat of the fruit grown in Thasae and Muang as the b*
value being higher than other samples. The WI of
banana pulp grown in Muang seemed to be higher
than other samples. However, no statisticaldifferences in the WI values of all samples wasobserved. The L* value of pulp banana fruits
cultivated from the three places was similar.
Regarding to Table 1, the low organic matters andhigh Ca and Mg contents in soil might effect on theyellowness of banana pulp which the soil sampledfrom banana plantation at Pathiu contained markedly
high Ca and Mg contents compare to the soil fromThasae and Muang. The lowest Ca and Mg contents
were observed in the soil from Muang which WI of
banana pulp from Muang was higher than that fromThasae and Pathiu, respectively. However, previous
work reported that high Ca content in media caused
the low carotenoids content of tomato fruit [13].
Whereas,magnesium
application
increased
carotenoids content in apple fruit [14]. Thus, the highMg content in soil might cause the high carotenoids
content in banana pulp resulting the high pulp
yellowness.

Texture, TSS and TA Measurements
Texture of the banana fruit pulp was determinedusing cutting force. The whole peeled fruit was cut
using shear blade prob at the middle part of the fruitby using a TA-Plus Texture Analyser (Lloyds,
England). The maximum force of the measurement
was recorded and the data was presented as N.
TSS content was measured using a hand-held
refractometer (ATAGO MNL-1125, Japan). The fruit
pulp was squeezed using cloth sheet and the banana
juice was used to determine TSS content and the data
were expressed as º Brix.
TA content was determined using the method of
AOAC [9]. Five grams of banana pulp was
homogenised with 10 mL of distilled water and thencentrifuged at 6,000 rpm. Three mL of supernatant
was titrated with 0.1 N NaOH until pH of the solution
was 7.0 by using 1 % (w/v) of phenolphthalene as theindicator. TA was defined as the percentage of malic
acid content.
DPPH Free Radical Scavenging Activity andBioactive Compounds Assays
A 3 grams of banana pulp was homogenised with
10 mL of absolute ethanol and then added the volume
to 30 mL using distilled water. The mixture wasvortexed for 5 min and then centrifuged at 6,000 rpm
for 20 min. The supernatant was collected todetermine DPPH free radical scavenging activity andbioactive compounds concentrations. DPPH free
radical scavenging activity was determined following
the method of Brand-William et al. [10]. The data
were expressed as the percentage of DPPH free
radical scavenging activity (%) per min.
Total phenols and flavonoids concentrations wereassayed using the method described by Slinkard andSingleton [11], Zhishen Mengcheng and Jianming[12] and the data were presented as mg gallic acid per
kilogram fresh weight (mg kg-1) and mg catechin per
kilogram fresh weight (mg kg-1), respectively.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Peel and pulp colour attributes of ripe
‘Namwa’ banana fruit cultivated in Pathiu,
Thasae and Muang Districts, Chumphon
province, Southern Thailand.
Peel colourcontent of banana fruit from Pathiu were related to thehigh Ca and Mg contents in soil. This recent work was
agreed with the work of Awad and Jager [17] whichsuggested that Ca and Mg concentration in soil had
positively correlation with the high content offlavonoids and phenolic compounds in the skin ofapple fruits.

Pulp colour

Area
L*

b*

L*

b*

WI

72.91 45.83

84.32

21.50a73.36

Thasae69.80 49.21

83.31

18.68b

74.89

84.37

b

76.91

Muang

72.18 49.22

17.00

Shear force (N)8PathiuData represent mean of 10 replications. Difference
letter indicates statistically difference.

*

A

6
4
2
0
PathiuThasaeMuang

30
TSS (°Brix)

Texture, TSS and TA
Texture, TSS and TA values of ripe ‘Namwa’banana fruits grown in the three districts were shownin Figure 1. Shear force of the banana fruit was
identified as the fruit texture. The texture of thebanana fruit from Pathiu was significantly higher thanthat of banana fruit from Thasae and Muang (P <0.05). The TSS and TA contents of banana fruits
grown in the three districts did not different. We
found that the texture of the banana fruit was
associated with the Ca content in soil. Soil sampledfrom Pathiu contained higher Ca than others which
positively associated with the higher cutting force ofthe banana compared to other samples. The TSS
content of all samples in this study was similar. This
indicates that quality of soil from the three district has
no influence on TSS content of the banana fruit. The
TA of the fruits grown in Thasae trended to be higher
than that of fruits grown in Pathiu and Muang. Thismight be related to the high potassium content of soil
from Thasae which potassium content in soil and theacidity of the fruit are closely correlated [15, 16].

B

24
18
12
6
0
PatieuThasae

Muang

0.2
C

TA (%)

0.16
0.12
0.08
0.04
0
PatieuThasaeMuang

Cultivation area
Fig. 1 Texture (A), TSS (B) and TA (C) of ripe
‘Namwa’ banana fruit cultivated in Pathiu, Thasae
and Muang Districts, Chumphon province, Thailand.
Error bar represent the mean ± standard deviation (n= 10).

Antioxidant Activity and Bioactive Compounds
Figure 2 shows antioxidant activity and certain
bioactive compounds concentration such as total
phenols and flavonoids of the “Namwa” banana
fruits. The results show that DPPH free radical
scavenging activity of the banana fruits grown in
Pathiu and Thasae was slightly higher than that of the
fruit grown in Muang. The banana fruits grown in
Thasae had both phenols and flavonoids
concentrations being significantly lower than thebanana fruits grown in Pathiu and Muang (P < 0.05).
The banana fruit grown in Pathiu had total phenols
and flavonoids concentrations being higher than the
fruit grown in Muang and Thasae, consequently.
Regarding to the soil quality as shown in Table 1, thehigh concentrations both total phenols and flavonoids

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SEE - Nagoya, Japan, Nov.12-14, 2018

Free radical
scavenging
activity (%)

10

REFERENCES

A

8[1] Youryon P., and Supapvanich S., Quality andbioactive compounds of ripe ‘Kluai Nam Wa’ and‘KluaiKhai’bananasduringstorage.
International Food Research Journal. Vol. 23,
Issue 3, 2016, pp. 1027-1032.
[2] Sulaiman S.F., Yusoff N.A.M., Eldeen I.M.,
Seow E.M., Sajak A.A.B., and Supriatno O.K.L..
Correlation between total phenolic and mineralcontents with antioxidant activity of eight
Malaysian bananas (Musa sp.). Journal of Food
Composition Analysis. Vol. 24, 2011, pp. 1-10.
[3] Ummarat N., Matsumoto T.K., Wall M.M., andSeraypheap K. Changes in antioxidants and fruit
quality in hot water-treated ‘Hom Thong’ banana
fruit during storage. Scientia Horticulturae. Vol.
130, 2011, pp. 801- 807.
[4] ] Bennett R.N., Shiga T.M., Hassimotto N.M.A.,
Rosa E.A.S., Lajolo F.M., and Cordenunsi B.R.
Phenolics and antioxidant properties of fruit pulp
and cell wall fractions of postharvest banana(Musa acuminate Juss.) cultivars. Journal of
Agriculture and Food Chemistry. Vol. 58, 2010,
pp. 7991-8003.
[5] Kondo S., Kittikorn M., and Kanlayanarat S.
Preharvest antioxidant activities of tropical fruit
and the effect of low temperature storage on
antioxidants and jasmonates. Postharvest Biology
and Technology. vol. 36, 2005, pp. 309-318.
[6] ] Elgar H.J., Watkins C.B., and Lallu, N. Harvest
date and crop load effects on a carbon dioxide
related storage injury of ‘Braeburn’ apple.
HortScience. Vol. 34, 1999, pp. 305–309.
[7] Lentheric I., Pinto E., Vendrell, M., andLarrigaudi`ere C. Harvest date affects theantioxidative systems in pear fruits. The Journalof Horticultural Science and Biotechnology. Vol.
74, 1999, pp. 791–795[8] Streif J., and Saquet A.A. Internal flesh browningof ‘Elstar’ apples as influenced by pre- andpostharvest factors. Acta Horticulturae. Vol. 599,
2003, pp. 523–527.
[9] AOAC. Official Methods of Analysis, 16th ed.
Association of Official Analytical Chemists
International, 1995, Washington, DC.
[10] Brand-Williams W., Cuvelier M. E., and Berset
C., Use of Free Radical Method to Evaluate
Antioxidant Activity. LWT – Food Science and.
Technology. Vol. 28: 1995, pp. 25–30.
[11] Slinkard, K., and Singleton, V.L., Total Phenol
Analysis: Automation and Comparison Manual
Methods. American journal of Enology and
Viticulture, Vol. 28, Issue 1, 1977, pp. 49-55.
[12] ] Zhishen J., Mengcheng T., and Jianming W.,
The Determination of Flavonoid Contents in
Mulberry and their Scavenging Effects on
Superoxide Radical. Food Chemistry. Vol. 64,
1999, pp. 555–559.

6420
PatieuThasaeMuang

Total phenols(mg kg-1)

5
B

4

*

3
2
1
0

Total flavonoids(mg kg-1)

PatieuThasae

12
10
8
6
4
2
0

Muang
C

*

PatieuThasaeMuang
Cultivation area
Fig. 2 Free radical scavenging activity (A), total
phenols content (B) and flavonoids content (C) of ripe
‘Namwa’ banana fruit cultivated in Pathiu, Thasae
and Muang Districts, Chumphon province, Thailand.
Error bar represent the mean ± standard deviation (n= 10).
CONCLUSION
Soil quality of difference plantation areas
influence on eating quality of ‘Namwa’ banana fruits.
The banana fruit grown in the soil containing high Mg(Pathiu) had higher pulp yellowness and lower WI
compared to the fruit grown in soil containing low
Mg, Thasae and Muang. The banana fruit grown inthe soil containing high organic matter (Muang) had
higher pulp WI compared to others. Ca content in soil
might be positively related to the fruit texture andhigh acidity content in the banana might be related tothe high K content in soil. High Ca and Mg contents
in soil caused high total phenolic compounds andflavonoids contents of the banana fruits. Thesesuggest that soil quality has influence on eating andnutritional qualities of ‘Namwa’ banana fruit.
ACKNOWLEDGEMENTS
Author would like to thank Prince of Chomphon
campus, King Mongkut’s Institute of Technology
Ladkrabang for supporting laboratory facilities.
167

SEE - Nagoya, Japan, Nov.12-14, 2018[16] Moor U., Põldma P., Tõnutare T., Karp K.,
Starast M., and Vool E., Effect of Phosphate
Fertilization on Growth, Yield and Fruit
Composition of Strawberries. Vol. 119, Issue 3,
2009, pp. 264-269.
[17] Awad M. A., and Jager, A., Relationships
between Fruit Nutrients and Concentrations of
Flavonoids and Chlorogenic Acid in ‘Elstar’Apple Skin. Scientia Horticulturae, Vol. 92,
Issues 3-4, 2002, pp. 265-276.

[13] Paiva E. A. S., Sampaio R. A., and Martinez H.
E. P., Composition and Quality of Tomato Fruit
Cultivated in Nutrient Solutions Containing
Different Calcium Concentrations. Journal of
Plant Nutrition, Vol. 21, Issue 12, 1998, pp. 26532661.
[14] Reay P. F., Fletcher R. H., and Thomas V. J.,
Chlorophylls, Carotenoids and Anthocyanin
Concentrations in the Skin of ‘Gala’ Apples
during Maturation and the Influence of Foliar
Applications of Nitrogen and Magnesium. Journalof the Science of Food and Agriculture, Vol. 76,
1998, pp. 63-71.
[15] Davies J. N., and Windsor, G. W., Effect of
Nitrogen, Phosphorus, Potassium, Magnesium
and Liming on the Composition of Tomato Fruit.
Journal of the Science of Food and Agriculture,
Vol. 18, Issue 10, 1967, pp. 459-466.

168

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ASSESSMENT OF N-(3-OXOHEXANOYL)-L-HOMOSERINELACTONE AND VEGETABLE MOLECULES IN VITRO
1,2

1

Il'shat Fayzelgayanovich Karimov, 1 Galimzhan Kalikhanovich Duskaev
Federal Research Centre of Biological Systems and Agro-technologies of the Russian Academy of
Sciences, Russia, 460000, Orenburg, 29, 9 Yanvarya St.
2

Orenburg State University, Russia, 460018, Orenburg, 13 Pobedy Pr.

SUMMARY
The ban on the use of antibiotics in the feed of farm animals has promoted an active search for new
substances with similar properties. Particular attention of researchers has been devoted to the search for thesesubstances among medicinal plants. The effect of substances of vegetable origin, such as coumarin and coniferyl
alcohol which both form part of oak bark, on the activity of acyl homoserine lactone (AHL) molecules has been
investigated. Reporter luminescent test systems were used to quantify the stress effects using bioluminescentanalysis. It was found that the absorption spectrum of coumarin is characterised by the presence of four peaks at
205, 215, 275, 310 nm. The interaction with coniferyl alcohol was characterised by a shift in the absorption
maxima (250 and 265 nm). The introduction of a molecule of AHL into the system led to the disappearance ofthe peak at 250 nm and a significant decrease in the absorption at 265 nm. The formation of a complex ofruminal fluid and coumarin led to a decrease in the expression efficiency of the sensory promoter luxI to a levelof 476626 RLU using the same concentration of GSL (homoserine lactone). The combination of ruminal fluidand coniferyl alcohol led to a decrease in the quantum yield of the E. coli strain to the level of 345896 RLU
following the use of GSL at a concentration of 10-4 M. The use of natural plant components (synthetic analogues)
enhances the level of inhibition of quorum sensing (QS) system activity by the inactivation of regulatory
molecules.
Keywords: Coumarin, Coniferyl Alcohol, Quorum Sensing

INTRODUCTION[5], were conducted. It was noted that naturalindoles inhibit the activation of T cells of thestaphylococcal enterotoxin [6].
When assessing molecules of plant origin, it isnecessary to take into account the species of plants.
This establishes a 100-fold difference in toxicity
between saponin-rich extracts of different plant
species [7] and individual vegetative parts [8].
The safety of plant matter is also assessed using
laboratory animals. Thus, it was established thatextracts from tea flowers do not contain toxic
substances, based on the assessment ofmutagenicity, and acute and subchronic toxicity inrats [9]. A significant number of studies are being
conducted to assess the toxicity of plant extracts andtheir anti-inflammatory properties, for example in
Parinari kerstingii Engl [10], their toxicologicaleffects [11], and the anti-tumour and cytotoxic
activityofessentialoils(Haplophyllum
tuberculatum A. Juss) [12], as well as acute andsubchronic studies of the toxicity of the aqueous
extract of Desmodium adscendens (Sw) DC [13].
The subchronic toxicity, immunoregulation andanti-tumour effect of Nordamnacantal andanthraquinone, extracted from the stems of Morinda
citrifolia L. [14], and the antifungal and cytotoxic
activity of selected medicinal plants from Malaysia
were detected [15].

The ban on the use of antibiotics in the feed offarm animals has promoted an active search for new
substances with similar properties. Particularattention has been given to the search for thesesubstances among medicinal plants, which werepreviously used in the treatment of animal diseases.
Therefore, substances from natural sources targetedat certain types of molecules have been extracted
and found to be useful for preventing insulin
resistance [1]. Methylated quercetin derivatives,
which are usually found in fruits and vegetables, andwhich have antioxidant and anti-inflammatory
properties (block the enzymes responsible for
inflammation)[2]
wereidentified.
Other
investigators [3] observed the inhibition of secretory
phospholipase A 2 by bioactive molecules from theextract of Boerhaavia diffusa L both in vitro and invivo. The possible application of polyphenolic
extracts for plant protection is considered in view of
the absence of any toxicity of these compounds. The
inhibition of Pseudomonas savastanoi bypolyphenolic extracts isolated from plant residues
was registered [4]. Studies on the extraction,
identification and evaluation of cytotoxicity of the
new terpene saponin from Salicornia bigelovii Torr,a potential chemotherapy drug for cancer treatment
169

SEE - Nagoya, Japan, Nov.12-14, 2018

Substances with anti-quorum activity have been
isolated from plant extracts, with Zingerone (ginger
substance) not only having a marked effect on the
production of quorum sensing signalling molecules
by Pseudomonas aeruginosa clinical isolates, butalso showing a significant effect on the activation ofreporter QS strains [16].
In our studies, we used substances withconfirmed antibacterial and QS activity that had
been previously isolated from the extract of Quercus
cortex [17].
The aim of the work was to estimate the toxicity
of chemically synthesised small molecules isolated
from the extract of Quercus cortex using strains ofEscherichia coli JLD271 pAL103 bacteria as test
objects, including against the background of cattle
ruminal fluid.

1. Autoinducers - N-(3-oxo)-hexanoyl-Lhomoserine lactone (oxo-C6-GSL) in theconcentration range from 10-8 to 10-4 M.
2. Bovine ruminal fluid, subjected tocentrifugation at 5000 rpm for 10 minutes.
Equipment: luminometer LM-01T (Immunotech,
Czech Republic), with the level of luminescence
expressed in RLU (relative luminescent units);
spectrophotometer
Fluorat-02M"Panorama"(Lumex, Russia); multicentrifuge CM-6M.
Statistical processing was performed using the
program "Statistica 10 RU", calculating the averagevalue (M), standard deviation (σ), and standard
deviation error (m). The significance level was
considered reliable at p <0.05.

MATERIALS AND METHODSAt the first stage, the absorption spectra of N-(3oxo)-hexanoyl-L-homoserine lactone and plant
molecule complexes were evaluated. The change in
the absorption spectra of these compounds wasstudied in the range from 200 to 400 nm, with themost typical and widespread AHL of gram-negative
bacteria: N-(3-oxo)-hexanoyl-L-homoserine lactone.
The absorption spectrum of coumarin was found to
be characterised by the presence of four peaks
corresponding to 205 nm (I = 0.255), 215 nm (I =0.269), 275 nm (I = 0.211), and 310 nm (I = 0.112)(Table 1, Fig. 2).
The results of interactions with coniferyl alcohol
turned out to be somewhat different and werecharacterised by a shift in the absorption maxima(Table 2).
It was found that the original substance has two
significant approximate absorption maxima at 250
nm and 265 nm, with an intensity of 1.389 and 1.293
relative units, respectively. In addition, there areinsignificant peaks at 205 nm, 220 nm and 230 nm(Fig. 3).
However, the introduction of AHL molecules
into the system led to the disappearance of the peakat 250 nm and a significant decrease in theabsorption at 265 nm. In this case, the peculiarity ofthis interaction was the formation of a pronounced
maximum at 220 nm with an absorbance value of0.853 relative units, which exceeds the initial levelby 66%. As a result, the curve acquired qualitatively
different characteristics compared to the original
version.
In the second stage, studies were performed on
ruminal tissue with natural and chemicallysynthesised inhibitors added, including the aqueous
extract of oak and solutions of coumarin andconiferyl alcohol. In this case, N-(3-oxo)-hexanoylL-homoserine lactone (oxo-C6-GSL) was used as an
autoinducer in the concentration range from 10 -8 to
10-4 M.

RESULTSThe bacterial strains of E. coli K12, transformedby plasmids with cross-linking receptor genes (rhlR,lasR from Pseudomonas aueruginosa and luxR
Vibrio fisheri) and luminescence genes (luxCDABE)
of Photorhabdus luminescens, as well as additional
molecular factors such as aqueous oak extractcontaining coniferyl alcohol and coumarin (Fig. 1),
which are part of the oak bark, were used; the ability
to inhibit the production of violacecine from
Chromobacterium violaceum was subsequently
detected.

Figure 1 – Structural formulas of coumarin (left)
and coniferyl alcohol (right).
Cultivation was performed on LB agar (Sigma,
USA), with the addition of 10 μg/ml doxycycline for18 hours at 37°C. Then, cells were transferred to LB
broth (Sigma, USA) and incubated for 90 minutes at
37°C to reach the early exponential phase.
The reporter luminescent test systems (E. coli K12 pAL103) were used as the material for the study,
due to the possibility of the quantitative evaluationof stress effects using widely applied bioluminescentanalysis.
As objects of research we used:
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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1. The absorption intensity of coumarin and its complex with N-(3-oxo)-hexanoyl-L-homoserine
lactone (oxo-C6-HSL).
Name

Maxima of the absorption curve
215 nm
275 nm
0.269
0.211
0.134
0.100
-50%
-53%

205 nm
0.255
0.106
-58%

Coumarin
Coumarin + oxo-C6-HSL
Character of change

310 nm
0.112
0.069
-38%

0,3

1

Absorption intensity

0,25

0,2

0,15

2
0,1

0,05

3

0
200

220

240

260

280

300

320

340

360

380

400

Wavelength, nm

Figure 2 – Absorption spectrum of coumarin (1), N-(3-oxo)-hexanoyl-L-homoserine lactone (3) and theircomplex in the aqueous medium (2).

Table 2. Intensity of absorption of coniferyl alcohol and its complex with N- (3-oxo)-hexanoyl-L-homoserine
lactone (oxo-C6-GSL).
Name
Coniferyl alcohol
Coniferyl alcohol + oxo-С6HSL
Decrease percentage

205 nm0.442
0.430

Maxima of the absorption curve
220 nm
230 nm
250 nm
0.513
0.584
1.389
0.853
0.719
0.568

265 nm
1.293
0.862

-3%

+66%

-33%

171

+23%

-59%

SEE - Nagoya, Japan, Nov.12-14, 2018

1,6

1

1,4

Absorption intensity

1,2
1

2

0,8
0,6
0,4
0,2

3
0
200

220

240

260

280

300

320

340

360

380

400

Wavelength, nm

Figure 3 – Absorption of coniferyl alcohol (1), N-(3-oxo)-hexanoyl-L-homoserine lactone (3) and theircomplex in aqueous medium (2).

Figure 4 – Enhancement of inhibition activity of N-(3-oxo)-hexanoyl-L-homoserine lactone molecules byruminal fluid (black figures) in combination with coumarin (A) and coniferyl alcohol (B) (white figures).
In this context, a sample of ruminal tissue diluted
to 12.5% served as a control group, and the level ofluminescence of E. coli JLD271 pAL103 was
676031 ± 10521 RLU at an autoinducer
concentration of 10-4 M (Fig. 4).
The formation of a complex of ruminal fluid andcoumarin led to a decrease in expression of the luxI

sensory promoter to a level of 476626 ± 13791 RLU
using the same concentration of oxo-C6-GSL,
indicating an additional 29% of signalling
molecules. Likewise, lower concentrations reduced
the luminescence level to 241603 ± 7791 RLU at 105
M and to 39960 ± 2791 RLU at 10 -6 M, which is an

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SEE - Nagoya, Japan, Nov.12-14, 2018

additional inhibition of 29% and 55% of themolecules, respectively (Fig. 4A).
The creation of a similar system representing the
combination of ruminal tissue and coniferyl alcohol
also led to a decrease in the quantum yield of the E.
coli strain JLD271 pAL103 to a level of 345896 ±
11669 RLU using oxo-C6-GSL at a concentration of
10-4 M, indicating the decrease of an additional 48%
of signalling
molecules.
Likewise,lower
concentrations reduced the luminescence level to187329 ± 5238 RLU at 10-5 M and to 42525 ± 1988
RLU at 10-6 M, which is an additional inhibition of
45% and 52% of the molecules, respectively (Fig.
4B).
On the other hand, the formation of a mixture of
ruminal tissue and oak bark extract, representing awhole set of different molecules, demonstrated aneven more pronounced change in anti-quorum
activity (Figure 5).

communication between bacteria in the rumen. At
the same time, scientists have revealed a new classof substances in plant extracts that can effectively
prevent the development of infectious andinflammatory processes in animal bodies due tosuppression of the system of intercellularcommunication in bacteria.
In the first stage, the absorption spectra of N-(3oxo)-hexanoyl-L-homoserine lactone and plant
molecule complexes were evaluated. The formationof mixtures of coumarin and AHL did not lead toqualitative changes in the absorption spectrum, but
resulted in a decrease in amplitude instead. This isdue to the formation of aggregates that increase thearea to more than that of 340 nm and reduce theconcentration of coumarin in the system by about
half of the initial amount.
The results of the interaction with coniferyl
alcohol turned out to be somewhat different,
apparently due to covalent interactions, which leads
to the formation of new types of compounds withdifferent characteristics; in the context of our work,
it potentially leads to the inactivation of mechanisms
of intercellular communication using acyl
derivatives of homoserine lactone.
In the second stage, studies on ruminal tissue
were performed with natural and chemicallysynthesised inhibitors added, including the aqueous
extract of oak and solutions of coumarin andconiferyl alcohol. The formation of a complex ofruminal fluid with coumarin and coniferyl alcohol
resulted in a decrease in the expression of thesensory promoter and a decrease in the quantum
yield of E. coli strain JLD271 pAL103. This canprobably be explained by the dose-dependent
inhibition of luminescence, as shown by the resultsof previous studies [18] on the assessment of
toxicity degree in cattle ruminal fluid, using
indicator luminescent strains designed on the basisof E. coli.
Inhibition can be associated with an ambiguous
action of the molecules. Therefore, an earlier
toxicity assessment (in vitro) of Quercus cortex
inhibitory molecules showed that coumarin did notaffect the luminescence kinetics of the E. coli strain
MG1655 pXen7 [19], which is different from theresults of the E. coli strain JLD271 pAL103. At thesame time, it exerted a toxic effect on Stylonychia
mytilus, 24 hours before the triplicate dilution (0.10.025).
The EC50 values for coniferyl alcohol withrespect to E. coli strain MG1655 pXen7 were 0.54
mg/ml [19]; a similar inhibition of luminescence wasconfirmed in this study.
In view of the limited information on the effectof coumarin on microorganisms living in thegastrointestinal tract of animals, an analysis of its
possible complex effect on the body was carried out.
For example, coumarins in Hydrangea paniculata

Figure 5 – Increased activity inhibition of N-(3oxo)-hexanoyl-L-homoserine lactone with ruminal
fluid (black figures) in combination with an extractof the oak bark (white figures).
Therefore, the effect of inhibition is increased by
61% in the maximum concentration of oxo-C6-HSL,
corresponding to a level of 259479 ± 854 RLU,
which is 57% of that at 10-6 M.
DISCUSSION
Because the feed substrate of cattle is formed
from plant material, its composition or individualcomponents can influence the signal molecules or
receptor proteins of representatives of the microbialcommunity. Therefore, to study the effect of plant
extracts directly on ruminal tissue, it may be relevant
to undertake investigations into the intercellular
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SEE - Nagoya, Japan, Nov.12-14, 2018

caused the inhibition of caspase splitting, theinfiltration of neutrophils and macrophages in thetissues of kidneys and the production of cytokinesand chemokines, and could be metabolised into two
biologically active compounds, umbelliferone andesculetin [20,21]. Thus, the probability of theinteraction of coumarin with biologically active
substances present in the composition of ruminal
tissue is high, which can lead to the formation of
new compounds.
It should also be taken into account that
coumarin can exert a selective effect on certain
microorganisms. Thus, coumarin derivatives wereassessed as potential inhibitors of the production of
the virulent factor of the Pseudomonas aeruginosa
pyocyanin; the results show that coumarinderivatives suppress the growth of P. aeruginosa[22,23].
The presence of a quorum inhibitory effect canbe considered here as a possible mechanism ofaction, as confirmed earlier [17]; this is from thecoumarin extracted from oak bark.
This was also confirmed in recent studies
comparing seven structurally related coumarins andinhibition of the quorum sensitivity of Pseudomonas
aeruginosa and Chromobacterium violaceum[23,24].
As for coniferyl alcohol, its effect on
gastrointestinal tract microorganisms is unknown,
while at the same time there is evidence that it
reduces the growth of Nicotiana cells at highconcentrations [25]; it is also metabolised by BY-2
cells into several compounds as proposed earlier.

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Bittencourt Rodrigues C., Ramos da Cruz CostaC., de Oliveira Toyama D., Domingues Passero
L.F., Dalastra Laurenti M., and Hikari Toyama
M. Evaluation of rhamnetin as an inhibitor of
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Vol. 9, Issue 2, 2017, 174-181. doi:
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[4] Biancalani C., Cerboneschi M., TadiniBuoninsegni F., Campo M., Arianna Scardigli,
Romani A., and Tegli S. Global analysis of typethree secretion system and quorum sensing
inhibition of Pseudomonas savastanoi bypolyphenol extracts from vegetable residues.
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[8] Guo N., Tong T., Ren N., Tu Y. & Li B.
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[9] Chen Y., Zhou Y., Zeng L., Dong F., Tu Y., andYang Z. Occurrence of functional molecules in
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and Qi L. W. The new plant Parinari kerstingii
Engl.: Toxicity studies and anti-inflammatory

CONCLUSION
The data obtained made it possible to state thatthe use of natural plant components and theirsynthetic analogues increases the inhibition level of
Quorum Sensing activity by inactivating regulatory
molecules. In the future, this will make it possible todetermine the nature of diet and the type of feed
substrates used, as well as additives which act asadditional factors in regulation of the activity ofbiochemical communication channels in the ruminal
microbial community of ruminant animals.
ACKNOWLEDGEMENTS
The study was performed according to the projectNo.0761-2014-0010
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175

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

SIMULATION SEA SURFACE TEMPERATURE OVER GULF OFTHAILAND BY USING ROMS MODEL
Pramet Kaewmesri1, Usa Humphries1,* and Zhu Jiang2
Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi(KMUTT), 126 Pracha-Uthit Road, Bang mod, Thung khru, Bangkok 10140, Thailand
2
International Center for Climate and Environment Sciences (ICCES), Institute of Atmospheric Physics,
Chinese Academy of Sciences
1

ABSTRACTThe Gulf of Thailand and neighbor area was studied using the Regional Oceanic Model System (ROMS). The
horizontal resolution and vertical levels were 10 km × 10 km and 40 layers respectively. The domain situatedbetween longitudes 95o E to 109o E and latitudes 0o N to 17o N. The initial and boundary conditions was used inthis study that includes potential temperature, salinity, u-component of current, v-component of current and sea
surface height relative to geoid from NCEP-CFSV2 data. The simulation dates were the end of month of May,
June and July. Discussion from the literature review is found that the Sea Surface Temperature (SST) is a very
important factor in the ocean and coupled atmosphere-ocean interaction. In this study used Generic Length Scale(GLS) vertical mixing method to simulate SST. The results from the model simulation are compared with spatial
pattern with grids global observation data from the Optimum Interpolation Sea Surface Temperature (OISST)
observation data. Overall the ROMS model can capture trend of SST pattern similarly OISST observation
especially June 30 and July 31, 2018. In future work will simulate monthly mean SST from ROMS model and willcompare with OISST monthly observation data in spatial pattern and statistical.

Keywords: The Gulf of Thailand, ROMS, GLS, and OISST

checking performance of SST from ROMS model.
Because a good simulation and forecasting SST
are main factor for improving the rainfall fromcoupled model over Thailand. Then a good rainfall
simulation that can manage and decrease the risk
from natural disasters.
In this study, to use the ROMS model simulating
SST pattern over The Gulf of Thailand and neighborarea. The vertical mixing scheme was used in thisresearch that was Generic Length Scale (GLS). The
dates of simulation was on May 31, June 30, and July
31, 2018. The results were basic spatial patterncomparing with gridded data from NOAA OISST
observation data.

INTRODUCTION
The Gulf of Thailand is located in Southeast Asia
immediately to the west of the South China Sea. The
Gulf is a semi-enclosed sea that measuresapproximately 400 km by 800 km, covering an areaof about 320,000 square kilometers. The Gulf ofThailand is the main factor agriculture, fishing,industrial, oil and etc. in Thailand. The location is
between Latitude at 6oN to 14oN and Longitudes at
99oE to 105oE. It is surrounded by the Kingdom of
Cambodia, Malaysia, the Kingdom of Thailand andthe Socialist Republic of Vietnam. Over the Sunda
Shelf, which is a submerged connection between
Southeast Asia, Malaysia, Sumatra, Java and Borneo[1].
Since a study about SST over the Gulf of Thailand
didn't receive a lot of attention studies emphasizing
on oceanic model.
From [2] were used the coupled model to simulate
rainfall over Thailand. The SST parameter was main
to exchange between atmospheric and Oceanic incoupled model for simulating rainfall. But in thisstudy was used ROMS ideal case simulation tosimulate SST in oceanic model. So the rainfall
simulation can be less accuracy SST than ROMS realtime simulation. So, this study was simulated the
ROMS real time over the Gulf of Thailand for

2. METHODOLOGY
2.1 MODEL DESCRIPTION
2.1.1 The Regional Oceanic Model System(ROMS)The Regional Oceanic Model System (ROMS) isa member of a general class of three-dimensional,
free-surface, terrain-following numerical models thatsolve the Reynolds-averaged Navier-Stokes
equations using the hydrostatic and Boussinesq

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SEE - Nagoya, Japan, Nov.12-14, 2018

assumptions. The governing equations in Cartesian
coordinates can be written:

Table 1. The variables used in the description of theocean model
Variable
Description
Du , Dv , DT , DS
Diffusive terms
Fu , Fv , FT , FS
Forcing terms

The momentum balance in the x  and y 
directions are:u  
u 
 v u  fv     u w  v   Fu  Dut
x z z 
(1)v  
v 
 v v  fu    vw  v   Fv  Dvt
y z z 
(2)   g

z
0
(3)
with the continuity equation:u v w 0
x y z
(4)
and temperature and salinity given by:
T

T 
 v T    T w  v  FT  DT
t
z 
z 
(5)
S

S 
 v S    S w  v  FS  DS
t
z 
z 
(6)
An equation of state is also required   T , S , P f  x, y gh  x, y v, v
K m , KT , K S
P  x, y , z , t  0    x, y , z , t S  x, y , z , t tT  x, y , z , t 

Total in situ density
SalinityTime
Potential temperature
The  x, y, z  components ofu , v, wzvector velocity v
Horizontal coordinates
Vertical coordinate  x, y , t 

The surface elevation

x, y

(7)
The variables are shown in Table 1. An over bar
represents a time average and a prime represents a
ﬂuctuation about the mean. These equations areclosed by parameterizing the Reynolds stresses andturbulent tracer ﬂuxes as:uvTu w   K M; vw   KM ; T w   KT
;
z
z
z
S
S w   K S;
z(8)Equation (1) and (2) express the momentum
balance in the x  and y  directions, respectively.
In the Boussinesq approximation, density variations
are neglected in the momentum equations except for
their contribution to the buoyancy force in the vertical
momentum equation (3). Under the hydrostatic
approximation, it is further assumed that the verticalpressure gradient balances the buoyancy force.
Equation (4) expresses the continuity equation for an
incompressible ﬂuid. The time evolution oftemperature and salinity are governed by theadvective-diffusive equation (5 and 6). For the
moment, the effects of forcing and horizontal
dissipation will be represented by the schematic terms
F and D , respectively.

Coriolis parameter
Acceleration of gravity
Bottom depth
Molecular viscosity anddiffusivity
Vertical eddy viscosity anddiffusivity
Total pressure P   0 gz
Dynamic pressure   P  
0 
2.2 Vertical Mixing Parameterizations
2.2.1 Generic Length Scale
A generic two-equation turbulence closure
scheme [3] which can be tuned to be have similarly
several of the traditional schemes, including that
Generic Length Scale (GLS) vertical mixing scheme
and was introduced to ROMS in [4]. The first of
Warner et al. (2005)'s [4] equations is definek  0.5q 2 . Their dissipation is given by   c0 

3 p / nk 3/ 2  m / n 1/ n

where  is a generic parameter that is used toestablish the turbulence length scale. The equation for
 is:

D

  
  K   c1 Ps  c3 Pb  c2 Fwall Dt z z  kCoefficients c1 and c2 are chosen to be consistent
with observations of decaying homogeneous,isotropic turbulence. The parameter c3 has differingvaluesforstablestratification. Also

177

c 

3

and

unstablec 
3SEE - Nagoya, Japan, Nov.12-14, 2018

   c0  k m l m , l   c0  k 3/ 2  1
pTable 2. Summary method used in this study.
Parameters
DetailThe Regional Oceanic
Model
Model System (ROMS)
Generic Length Scale
Vertical Mixing(GLS)
Parameterizations
The National Centers forEnvironmental Prediction
Initial andBoundary Condition Climate Forecast System
Version 2 (NCEP-CFSV2)
Observation
OISST version 2
Data- Potential temperature- Salinity
Parameter from- U-component of Current
Initial and- V-component of Current
Boundary Condition- Sea Surface Height
relative to geoid
Longitudes 95o E to 109o E
andDomainLatitudes 0o N to 17o N
10 km×10 km
Horizontal Grids
40 layers
Vertical Levels- May 31, 2018
- June 30, 2018
Date of Simulation- July 31, 20183

2.3 Initial condition, boundary condition and data
observations
The initial condition and boundary condition wereused the National Centers for Environmental
Prediction Climate Forecast System Version 2(NCEP-CFSV2). The data is 6 hourly atmospheric,oceanic and land surface reanalysis products andforecast. In this study, five parameters was included
potential temperature, salinity, U-component of
current, V-component of current and sea surface
height relative to geoid to use initial and boundary
condition in ROMS model [5].
The observation data was used the OISST version
2 AVHRR SST. This data is cover global observation
data and developed by National Oceanic andAtmospheric Administration (NOAA) from UnitedState of America. This data is an analysis constructedby combining observations from different platforms(satellites, ships, buoys) on a regular global grid [6].
2.4 Domain description and Experiments design

RESULTS AND DISCUSSION

The domain experiment is cover on the Gulf
Thailand and neighbor area. The domain situatedbetween longitudes 95o E to 109o E and latitudes 0o N
to 17o N (Fig 1). The horizontal and vertical level inthis study that were 10 km ×10 km and 40 layers
respectively.

Fig 2 shows the Sea Surface Temperature fromthe NOAA OISST version 2 and ROMS on May 31,
2018.
The OISST observation data show the SST
pattern (in the rage of 28.2 oC to 28.4 oC) almost overAndaman Ocean. But the SST pattern with hightemperature (more than 29.4 oC) almost over nearly
Malay Peninsula, eastern Indonesia Peninsula, Gulfof Thailand nearly Cambodia, Prachuap Khiri Khan
province and lower southern Thailand, as shown in
Fig 2(a).
The ROMS model show the SST pattern (in therage of 28.2 oC to 28.4 oC) almost over Andaman
Ocean similarly OISST observation data. But the SST
pattern with high temperature (more than 29.4 oC)
almost over nearly Malay Peninsula, western andeastern Indonesia Peninsula, Gulf of Thailand nearly
Cambodia, eastern and lower southern Thailand, as
shown in Fig 2(b).
Fig 3 shows the Sea Surface Temperature fromthe NOAA OISST version 2 and ROMS on June 30,
2018.
The OISST observation and ROMS model show
similar the SST pattern (in the rage of 28.2 oC to 28.4oC) almost over Andaman Ocean. In case temperature
more than 29.4 oC OISST observation and ROMS
model can capture SST pattern over Malay Peninsula
and Indonesia Peninsula. Over eastern Malay
Peninsula ROMS model and capture temperature
over 28.8 oC similarly OISST observation.

Fig. 1 The domain was used in this study.
In this study, the experiments design was included
three cases simulation. The first of simulation was on
May 31, 2018. The second of simulation was on June30, 2018. The last simulation was on July 31, 2018.
Table 2 was shown about summary of methodology
part in this study.
178

SEE - Nagoya, Japan, Nov.12-14, 2018

(a)

(b)

Fig. 2 Spatial SST (Degree Celsius) pattern on May 31, 2017: a) OISST observation and b) ROMS model.

(a)

(b)

Fig. 3 Spatial SST (Degree Celsius) pattern on June 30, 2017: a) OISST observation and b) ROMS model.

179

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig 4 shows the Sea Surface Temperature from the
NOAA OISST version 2 and ROMS on July 31, 2018.
The OISST observation and ROMS model show
similar the SST pattern (in the rage of 28.2 oC) almost

over Andaman Ocean. In case temperature more than
29.4 oC OISST observation and ROMS model cancapture SST pattern over Malay Peninsula andIndonesia Peninsula.

(a)

(b)

Fig. 4 Spatial SST (Degree Celsius) pattern on July 31, 2017: a) OISST observation and b) ROMS model.
Variabilities in the Gulf of Thailand. Advance inAtmospheric Science, Vol 25, No 3, 2008,
pp.489-506.
[2] Kaewmesri. P, Humphries. U, Archevarapuprok.
B, and Sooktawee. S., The Performance Rainfall
during Rainy Seasonal over Thailand by Using
Preliminary Regional Coupled Atmospheric andOceanic model. International Journal of
GEOMATE, Vol. 14, Issue 45, 2018, pp.109-115.
[3] Umlauf L, and Burchard H., A generic lengthscale equation for geophysical turbulence models.
J. Marine Res., Vol 61, 2003, pp.235–265.
[4] Warner C J, Sherwood R C, Arango G H, andSignell P R., Performance of four turbulence
closure models implemented using a genericlength scale method. Ocean Modelling, Vol 8,
2005, pp.81–113.
[5] Saha S, Suranjana M, Xingren W, Jiande W,
Sudhir N, Patrick T, Davie B, Yu T H, Hui Y C,
Mark I, Michael E, Rongqian Y, Malaquias M,
Huug V D D, Qin Z, Wanqiu W, Mingyue C, andEmily B., The NCEP Climate Forecast System
Version 2, Vol 27, 2014, pp.2185-2208.
[6] Reynold R W, Smith M T, Liu C, Chelton B D,
Casey S K, and Schlax G M., Operational
processing of Satellite Sea surface temperature
retrivals at the Naval Oceanographic Office, Bull.
Amer. Met. Soc, Vol 79, pp 5473-5496.

CONCLUSION
In this study, to use the ROMS mode simulation
performance SST on 3 cases that included May 31,
June 30 and July 31, 2018 over the Gulf of Thailand
and neighbor area. Overall the ROMS model cancapture trend of SST pattern similarly OISST
observation especially June 30 and July 31, 2018. In
Future work will simulate monthly mean SST fromROMS model and will compare with OISST monthly
observation data in spatial pattern and statistical.
ACKNOWLEDGEMENTS
The authors are also grateful NCEP for the
CFSV2 data sets, NOAA for the gridded data sets,
IMCS for the ROMS model and the Department ofMathematics, Faculty of Science, King Mongkut’s
University of Technology Thonburi (KMUTT). The
authors acknowledge the financial support provided
by National Research Council Thailand (NRCT).
This research was fully supported by the International
Research Net-work (IRN) (IRN5701PDW0002).
REFERENCES[1] Aschariyaphotha N., Wongwises P., Wongwises
S., Humphries W U., and Xiaobao Y., Simlationof Seasonal Circularion and Thermohaline180

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECTS OF SEED PREPARATION, SOWING MEDIA, SEEDSOWING RATE AND HARVESTING PERIOD ON THE PRODUCTION
OF CHIA MICROGREENS

1

Anjana Junpatiw1, Akarapon Sangpituk1
Faculty of Agricultural, King Mongkut's Institute of Technology Ladkrabang Prince of Chumphon Campus,
Thailand
ABSTRACT

Chia (Salvia hispanica L.), a species of seeds with high essential fatty acid and nutraceutical content has
encouraged increased crop production worldwide. Keeping value-added products into consideration, four
experiments were conducted with the CRD method. In the first experiment, seed preparation was done by soaking
the seeds in water, followed by being sown in the media. In the first treatment, T1, seeds were sown without
soaking. In T2, seeds were sown after being soaked for 6 hours at room temperature and for 12 hours, in T3. In
T4, after being soaked at 70-80°C, the seeds were allowed to cool down at room temperature for 6 hours and for
12 hours in T5, before sowing. According to the results, T4 treatment produced the highest germination percentage,
microgreen height, and fresh weight. In the second experiment, seeds were sowed in 5 different seeding media for
7 days. The mix of coconut coir with sand and rice husk ash (1:1:1) produced the highest percentage ofgermination, microgreen height, and fresh weight. The third experiment was conducted to study the best seedsowing rate amongst 56, 93, 130, 167 and 204 g/m2. The results showed that the seed sowing rate of 204 g/m2 gave
the highest fresh weight. The fourth experiment was to study the effect of harvesting period, by focusing on theharvesting periods of 5, 6, 7, 8 and 9 days, after sowing. The results showed that the period of 6-9 days after sowing
gave the highest fresh weight.
Keywords: Chia, Microgreens, Seed Preparation, Sowing Media, Harvesting Period

Microgreens can be served in salads, soups,
sandwiches and main dishes [3], [4], [5].
Chia (Salvia hispanica L.) is an annual plant
belonging to the Lamiaceae family, native to Mexicoand Guatemala [6]. Recently, chia seeds have become
important for human health and nutrition because it
has a high content of ω-3 fatty acids and highantioxidant properties that promote beneficial healtheffects [7]. It is considered as a Dietetic Nutritional
Supplement by the Food and Drug Administration(FDA) [8]. Chia is now widely cultivated, its
cultivation is not only limited to America but is also
extended to other areas such as Australia andSoutheast Asia [9].
The objectives of this work are to study the effects
of seed preparation, sowing media, seed sowing rateand harvesting period of chia microgreen for use as
information and guidelines for the production of Chia
microgreen.

INTRODUCTION
Today, more attention is given to a healthynutrition to prevent certain diseases [1]. As publichealth awareness is increasing day by day, throughout
the world, the demand for functional food withmultiple health benefits is also increasing.
Microgreens are considered “functional foods”
which are food products that possess particular healthpromoting or disease preventing properties, above
their normal nutritional values [2]. These are alsoclassified as a good source of minerals in the humandiet [3].
Microgreens are a new class of edible vegetables,
a very specific type which includes seedlings ofedible vegetables, herbs or other plants [3]. The
commonly cultivated microgreens are spinach,mustard, buckwheat, arugula, bull’s blood beet,celery, cilantro, amaranth, golden pea, basil, spinach,mizuna, peppercress, popcorn shoots, red mustard,
red beet, red cabbage, red orach, sorrel, red sorrel,
wasabi, cabbage, broccoli, radish, lettuce. The size ofthese greens is between 3 and 10 cm in height whichusually occurs within 7–14 days after germination,
depending on the plant species. Over the past few
years, microgreens have gained increasing popularity
as new culinary ingredients due to their wide range ofintense flavors, attractive colors, and tender texture.

MATERIALS AND METHODSIn these experiments, we only used Chia seeds
that were free from any defect and physical damage.
They were obtained from a commercial microgreens
seed source (Jamthong Farmshop, Thailand).

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Chia seeds were soaked in water for 12 hours atroom temperature and then sown in a plastic basket(20 cm × 27 cm) containing coconut coir mixed withsand and rice husk ash (1:1:1) which was sprayed
twice a day with the same amount of water. In thisexperiment, to study the harvesting period, by
focusing on the harvesting periods at 5, 6, 7, 8 and 9days after sowing.
Four replicates per treatment were used in theexperiment. Chia microgreens were randomly
selected from each replicate to measure microgreen
height and fresh weight per 100 microgreens.
The experiment was completely randomized bydesign (CRD). All data were analyzed using therepeated measurement of the ANOVA procedure.
Means were separated by Duncan’s New Multiple
Range Test (DMRT).

Experiment 1: To study the effect of seed
preparation and soaking treatments on the
production of Chia microgreens.
Chia seed preparation for germination was doneby soaking the seeds, followed by them being sownin media. In the first treatment, seeds were sown
without being soaked. In the second and third
treatment, seeds were soaked in water at 70-80°C andthen allowed to cool down at room temperature 6
hours and 12 hours, respectively, before it’s sown inmedia. They were sown in a plastic basket (20 cm ×27 cm) containing coconut coir mixed with sand andrice husk ash (1:1:1) which was sprayed twice a daywith the same amount of water.
Four replicates were used per treatment in theexperiment. Chia microgreens were randomly
selected from each replicate to measure thegermination percentage, microgreen height and fresh
weight per 100 microgreens after sowing for 7 days.

RESULTS AND DISCUSSION
Experiment 1: To study the effect of seed
preparation by soaking treatments on the
production of Chia microgreens.

Experiment 2: To study the effect of sowing media
on the growth of Chia microgreens.

This was to study the influence of soaking
treatments on growth characteristics of Chia
microgreens after it’s grown for 7 days. The results
showed that different soaking treatments had
significantly different effects on the germination
percentage, microgreen height and fresh weight ofChia seeds. The germination percentage of soaking
the seeds at different water temperature and durationof soaking ranged from 96-98%. Seeds that were
soaked initially at 70-80°C and then allowed to cool
down at room temperature for 12 hours had thehighest microgreen height (7.25 cm) and fresh weight(1.63 g/100 microgreens) (Table 1).
The germination percentage in Chia seeds thatwere soaked was higher than in the seeds that weren’t
soaked (Table 1) agreed with published results fortable beet [10], carrot, snap bean, bell pepper [11],beet and chard [12]. Khan Abawi and Maguire [10]found that washing the seeds for 8 or 24 hours inrunning water improved table beet germination, andthe subsequent osmotic priming led to further
improvement.
Many species germinate easily and growpromptly while others are slow and may require presowing treatments to improve, standardize andshorten the production cycle. Seed preparation used
to advance the early stages of germination range from
simple water soaking to physiological treatments,
such as matrix priming and seed pre-germination. The
substances inhibitory to germination are removed
during seed washing [12], [13].

Chia seeds were soaked in water at 70-80°C andthen allowed to cool down at room temperature for 12hours before it’s sown in media. Seeds were sown ina plastic basket (20 cm × 27 cm) with five medias;coconut coir, rice husk ash, sand, coconut peat mixed
with rice husk ash (1:1) and coconut peat mixed withsand and rice husk ash (1:1:1) which is sprayed twice
a day with the same amount of water.
Four replicates per treatment were used in theexperiment. Chia microgreens were randomly
selected from each replicate to measure thegermination percentage, microgreen height and fresh
weight per 100 microgreens after sowing for 7 days.
Experiment 3: To study the effect of seed sowing
rate on the growth of Chia microgreens.
Chia seeds were sown at the seeding rate of 56,
93, 130, 167 and 204 g/m2. Soaked in water initiallyat 70-80°C and then allowed to cool down at room
temperature for 12 hours, before it’s sown in media.
Seeds were sowed in a plastic basket (20 cm×27 cm)
containing coconut peat mixed with sand and ricehusk ash (1:1:1) and which is sprayed twice a daywith the same amount of water.
Four replicates per treatment were used in theexperiment. Chia microgreens were randomly
selected from each replicate to measure thegermination percentage, microgreen height and fresh
weight per 100 microgreens after sowing for 7 days.
Experiment 4: To study the effect of harvesting
period on the production of Chia microgreens

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SEE - Nagoya, Japan, Nov.12-14, 2018

after sowing. Results showed significant differencesin microgreen height and fresh weight.
The results showed that the seeds harvested after
9 days of sowing provided the best results of thehighest microgreen height (7.5 cm) whereas the seeds
harvested after 6 - 9 days of sowing gave the highest
fresh weight (1.43-1.45 g/100 microgreens) (Table 4).
This crop has a quick production cycle (one to three
weeks) and occupies very little space in production.
However, to shorten the production cycle and thus toreduce the production cost is one of the major goalsof the current production [19], [20]. So, the best
harvesting period of Chia microgreen is harvesting
after 6 days of sowing.
This study, in agreement with the publishedresults for lettuce [21] found that young lettuce
seedlings, 7 days after germination, had the highest
fresh weight and total phenolic concentration andantioxidant capacity in comparison to the older
seedling. Unlike the result of Murphy Llort and Pill[17] found that at 15 days after planting table beetgave the highest shoot fresh weight.
Microgreens are edible greens having two or moredeveloped cotyledonary leaves. Harvesting of
microgreens at the right stage is one of the mostimportant production strategies. They are harvested at
7-14 days after germination with short crop cycle andusually with the average height of 2.5-7.6 centimeters,
depending on the species [2], [3], [17].

Experiment 2: To study the effect of sowing media
on the growth of Chia microgreens.
The influence of seeding media on growth
characteristics of Chia microgreens after grown for 7
days. The result showed that Chia seeding media weresignificantly different in germination percentage,
microgreen height, and fresh weight. Seeds weresown in coconut coir and coconut coir mixed withsand and rice husk ash (1:1:1) provided the highest
germination percentage range from 96-98%.
Especially, seeds that were sown in coconut coir withsand and rice husk ash (1:1:1) provided the highest
microgreen height (7.02 cm) and fresh weight (1.12g/100 microgreens) (Table 2).
Muchjajib Muchjajib Suknikom and Butsai [14],Di Gioia De Bellis Mininni Santamaria and Serio [15]had documented the same result on a comparison ofalternative media to provide maximum yield. Natural
fiber-based media have also been developed andcurrently commercialized for microgreens. Low-cost
alternatives of natural and renewable origin (e.g.
cellulose pulp, cotton, jute, kenaf and sunn hemp
fibers) and mixtures of materials combining desirable
properties constitute potential as growing media for
microgreens [15].
Experiment 3: To study the effect of seed sowing
rate on the growth of Chia microgreen.
The result of the effect of seed sowing rate on thegrowth of Chia microgreens after grown for 7 days,presented that there was no significant difference(P≤0.05) in the microgreen height. While fresh
weight showed statistically different in seed sowing
rate. Chia seeds with sowing rate of 204 g/m2 had thehighest fresh weight (1.83 g/100 microgreens) (Table3). On arugula and table beet, Murphy and Pill [16]and Murphy Llort and Pill [17] observed a linear
increase in fresh yield per unit area by increasing
sowing rate. Increasing sowing rate to maximize yield
will reflect on the cost of production, while excessive
stand density may produce undesirably elongatedshoots and limited air circulation, conducive to thedevelopment of fungal diseases. Optimal sowing rateis crop-specific, based on average seed weight,
germinability and desired shoot population density,
ranging from 1 seed/cm2 in large-seeded species suchas pea, chickpea, and sunflower, up to 4 seeds/cm2 insmall-seeded species like arugula, watercress,
mustard [18].

CONCLUSION
Study of the effect of seed preparation, sowing
media, seed sowing rate and harvesting period of Chia
microgreen can be concluded as follows:
Chia seeds that were soaked initially at 70-80°C
and then allowed to cool down at room temperaturefor 12 hours had the highest germination percentage(98%) microgreen height (7.25 cm) and fresh weight(1.63 g/100 microgreens).
Chia seeds sown in coconut coir with sand andrice husk ash (1:1:1) provided the best results ofhighest germination percentage (98%), microgreen
height (7.02 cm) and fresh weight (1.12 g/100
microgreens).
Chia seeds sown at the rate of 204 g/m2 provided
the highest fresh weight (1.83 g/100 microgreens).
The harvest of 6 days after sowing gave highest
fresh weight (1.45 g/100 microgreens).
ACKNOWLEDGMENTS

Experiment 4: To study the effect of harvesting
period on the growth of Chia microgreens.

We are grateful for the financial support provided
by King Mongkut’s Institute of Technology
Ladkrabang Prince of Chumphon Campus.

The effect of different harvesting period on thegrowth of Chia microgreens at 5, 6, 7, 8 and 9 days

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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Effect of soaking treatments on the germination percentage, microgreen height and fresh weight per
100 microgreens of Chia seeds after sowing for 7 days.
soaking treatments

without soaking
6 hours at room temperature
12 hours at room temperature
initial temperature at 70-80°C until
cool down at room temperature for 6 hours
initial temperature at 70-80°C until
cool down at room temperature for 12 hours
F-testgermination
percentage
(%)
92 b
96 a
97 a
96 a

microgreen height(cm)
5.97 d6.30 c6.75 b
6.50 bfresh weight per
100 microgreens(g)0.83 d
1.15 c1.12 c1.43 b

98 a7.25 a1.63 aCV (%)

*

**

**

2.38

7.12

22.09

**Significantly different at P<0.01, *significantly different at P<0.05. Means within the same column withthe different letters are significantly different to DMRT at P<0.05.
Table 2 Effect of sowing media on the germination percentage, microgreen height and fresh weight per 100
microgreens of Chia seeds after sowing for 7 days.
soaking media

coconut coirrice husk ash
sand
coconut peat mixed with rice husk ash (1:1)
coconut peat mixed with sand and rice husk ash(1:1:1)
F-testCV (%)

germination
percentage
(%)
96 ab
88 c
92 cb
94 b

microgreen height(cm)
6.27 b
5.67 c5.70 c6.32 bfresh weight per
100 microgreens(g)
0.97 b0.90 c0.93 c1.08 ab98 a7.02 a1.12 a

*

**

*

3.36

9.13

3.33

**Significantly different at P<0.01, *significantly different at P<0.05. Means within the same column withthe different letters are significantly different to DMRT at P<0.05.
Table 3 Effect of seed sowing rate on microgreen
height and fresh weight per 100 microgreens of Chia
seeds.
**Significantly different at P<0.01, ns = not

Table 4 Effect of harvesting period on microgreen
height and fresh weight per 100 microgreens of Chia
seeds.
**Significantly different at P<0.01. Means within theseed sowing rate
g/m2

microgreen
height(cm)

harvesting period(days after sowing)

microgreen
height
(cm)

56
93
130
167

7.62
7.51
7.36
7.34

fresh weightper 100
microgreens(g)1.63 c1.63 c1.65 c1.70 b5
6
7
8

3.62 e4.56 d5.38 c7.22 bfresh weight per
100
microgreens(g)
0.78 b
1.45 a1.42 a1.43 a204

7.23

1.83 a9

7.57 a1.43 aF-testns**

F-test****CV (%)

9.89

1.98

CV (%)

9.23

10.58

significantly different. Means within the same
column with the different letters are significantly
different from DMRT at P<0.05.

same column with the different letterssignificantly different from DMRT at P<0.05.

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[21] Oh M.M., Carey E.E., Rajashekar C.B.
Regulated water deficits improve phytochemical
concentration in lettuce, J. Am. Soc. Hortic. Sci.
2010, 135, 223−229.

185

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECTS OF PLANTING SUBSTRATES SUPPLEMENTED WITH
VERMICOMPOST AND VERMICOMPOST FORTIFIED WITH
Trichoderma asperellum CB-PIN-01 ON GROWTH ANDPYTHIUM ROOT ROT OF LETTUCE

1

Phraomas Charoenrak1, Chiradej Chamswarng2, Wanwilai Intanoo2 and Naowarat keawprasert2
Faculty of Agricultural Technology, Rajamangala University of Technology, Thanyaburi, Thailand
2
Faculty of Agriculture at Kamphaeng Saen, Kasetsart University, Kamphaeng Saen Campus,
Nakhon Pathom, Thailand

ABSTRACT
Vermicompost products are the efficient organic fertilizers. Therefore, vermicompost fortified with abiocontrol agent may have potential to improve plant growth and also suppress plant disease. In this research,
planting substrates (chopped coconut husk: coirdust; 50:30 % by volume) supplemented with vermicompost(VC) (20 % by volume) or VC fortified with Trichoderma asperellum CB-Pin-01 (VCT) (20 % by volume) were
evaluated for the effects on lettuce growth and root rot caused by Pythium aphanidermatum (Pa). The 14-day-old
lettuce (Butter Head) seedlings grown in sowing substrate (perlite:vermiculite; 2:1 V/V) were transplanted into
the 6-inch plastic pot contained with prepared substrates. Plant nutrient solution with electrical conductivity (EC)of 1.6 mS/cm and pH 5.5-6.0 was applied weekly on substrate at 200 ml/pot. Results revealed that both VC and
VCT increased plant growth after planting for 42 days as compared to a control (substrate without
vermicompost). However, a substrate contained with VCT significantly increased the height, leaf number, leafarea, basal stem cutting surface area, plant fresh and dry weights when compared with the control. When thesubstrates were inoculated with Pa, the VCT (+Pa) treatment increased the height, leaf number, leaf area, basal
stem cutting surface area, plant fresh and dry weights when compared with a Pythium treated control (VC(+Pa)).
After lettuce harvesting, T. asperellum CB-Pin-01 could be completely recovered from planting substrate (100%)and lettuce root (100%), while this fungus help reduce substrate and lettuce root colonization by Pa whencompared with a control (VC(+Pa)).
Keywords: Trichoderma, Vermicompost, Planting substrate, Root rot, Biocontrol

the lettuce was grown during high temperature(>35°C) season.
At present, biological control (biocontrol) is analternative method for the control of plant diseases.
The most widely used biocontrol agent (BCA)
throughout the world belongs to the genus
Trichoderma [6], [7]. Trichoderma has been wellknown BCA which provides high efficacy to control
fungal pathogens directly by antibiosis andmycoparasitism. However, abilities to induce
resistance to plant disease and increase plant growth
are indirect benefits [6], [7], [8].
In Thailand, Chamswarng and Intanoo [9]prepared Trichoderma asperellum strain CB-Pin-01(Ta) (formerly identified as T. harzianum) as purestock culture in the form of course powder. Thissemi-finished bioproduct has been used for
producing a fresh culture bioproduct (fungal
colonized semi-cooked rice seeds) by using thesimple technique [9]. Spore suspension derived from
fresh culture can be used for seed soaking, soil
drenching and plant spraying for the control of
fungal diseases on fruits, vegetables, cereals,
ornamental crops and hydroponically grown lettuce

INTRODUCTION
Lettuce (Lactuca sativa) is the most importantcrop in the group of leafy vegetables [1]. Butter
Head lettuce (Lactuca sativa L. var. capitata L.) is aheading type with soft and tender leaves, eaten raw.
It is most popular in England, France, theNetherlands and other western and central European
countries [2]. In recent decades many cultivars havebeen bred and grown in the USA [3].
Soilless culture, can increase productivity
whatever the climate conditions, but also optimize
the management of inputs (fertilizers or pesticides),within a given economic and environmental
framework. They also aim at controlling diseases
more efficiently [4]. For hydroponically and soilless
substrate grown lettuce, Pythium spp. particularly P.
aphanidermatum (Pa) is a major fungal pathogen
causing root rot disease. Zoospores produced by Pa
are asexually motile biflagellate spores which canlive in water and move toward to infect the roots,
causing root rot disease on various kinds of lettuce[5]. This disease causes significant reduction of
lettuce growth, yield and quality, especially when186

SEE - Nagoya, Japan, Nov.12-14, 2018[10]. Incorporation of Ta-spore suspension into themineral nutrient solutions using for growing lettuce(Green Cos) in the Nutrient Film Technique (NFT)
system effectively reduced Pythium root rot andpromoted lettuce growth [11]. Similar results wereobtained by Kaensarn [12] who reported that sowing
and planting Butter Head lettuce in biosubstrates
supplemented with T. asperellum CB-Pin-01 could
enhance plant growth and control root rot diseasecaused by Pythium aphanidermatum.
Vermicomposting is the non-thermophilic
biodegradation of organic material through theinteraction between earthworms and microorganisms
as an environmentally friendly highly costeffective conversion method of biodegradableorganic
wastesintovaluable
products.
Vermicompost products have been proved to beefficient as organic fertilizers and biologicalcontrol agents providing suppression on many plantdisease incidences caused by soil-borne or foliar
plant pathogens and pests [13], [14]. Application ofcompost not only suppress disease severity but also
involved induced systemic resistance [15], [16].
Compost fortified with plant growth promoting
microorganisms (PGPM) have shown that it
increased its disease suppressiveness against fungal
pathogens, plant growth and soil health [17].
Therefore, this study was conducted to evaluate
the efficacy of planting substrates supplemented
with vermicompost and vermicompost fortified withT. asperellum CB-Pin-01 (Ta) for promoting plant
growth and yield of Butter Head lettuce and for
reducing lettuce root and substrate colonization by
Pa.

Pythium Inoculation
The plant pathogenic isolate of Pythiumaphanidermatum (Pa) was isolated from rotted rootsof lettuce (Green Cos). The Pa fungus was cultured
on potato dextrose agar (PDA) for 48 hr at room
temperature (25-30 °C). The agar contained with Pa
mycelia in each plate was cut into small pieces
before added with 100 ml of sterile water. To
prepare mycelial suspension, agar pieces were
homogenized at 9500 rpm for 15 sec [11]. For Pa
inoculation, 200 ml/pot of mycelial suspension wereapplied onto planting substrate at 14 d after planting.
Preparation of Basal Nutrient Solution
Mineral nutrient solution stocks modified fromCooper [19] were prepared according to the methods
provided by Chiemchaisri [20]. In 1 L of eachconcentrated nutrient solution stock comprised of
220.0 g calcium nitrate for stock A; 53.0 g
potassium dihydrogen phosphate, 117.0 g potassium
nitrate and 112.8 g magnesium sulfate for stock B;
10.0 g Fe DTPA, 5.0 g Fe DDHA, 2.0 g Mn EDTA,
0.1 g ammonium molybdate, 0.06 g nickle sulfate
and 10.0 g Nic-Spray® (7.0% Mg, 1.8% Fe, 1.8%
Mn, 1.9% Ca, 1.7% Zn, 1.7% B, 0.01% Mo) as
micronutrient fertilizer for stock C. To preparedbasal nutrient solution, 200 ml of concentrated stock
solutions A, B and C were mixed with 100 L ofwater. The pH and EC in nutrient solution were
adjusted at 5.5-6.5 and 1.6-1.8 mS/cm, respectively.
Lettuce Planting and Experimental Design
The formula of planting substrate was developedby Associate Prof. Dr. Chiradej Chamswarng. There
are included by chopped coconut husk : coirdust;(50:30 % by volume) supplemented withvermicompost (VC) (20 % by volume) or VC
fortified with T. asperellum CB-Pin-01 (VC+T and
VCT) (20 % by volume) was used for lettuce
planting. Butter head seedlings were grown in smallcup (36 ml) contained with perlite : vermiculite (2:1v/v) for 14 d using nutrient solution. The seedlings
were transplanted into the 6-inch plastic pot (1,000ml) contained with prepared substrates. Plant
nutrient solution was added for 200 ml with weekly
adjustments of pH (5.5-6.5) and EC (1.6-1.8 mS/cm)
during plant growth.
The completely randomized design (CRD) was
performed in seven treatments, four replications foreach treatment, four pots per replication and one
plant per pot. Treatments 1-4 comprised of using (1)substrate only (control), (2) substrate supplemented
with VC (20% v/v) (VC), (3) substrate
supplemented with VC (20 % v/v) and added with
200 ml/pot of Ta spore suspension prepared fromTa-fresh culture at 14 d after sowing (VC+T) and (4)MATERIALS AND METHODSTrichoderma Fresh Culture
For fresh culture preparation, four parts ofbroken milled rice were added with two parts of tap
water (v/v) in automatic rice cooker. After theswitch turn off, 250 g of semi-cooked rice wasplaced into 8x12 inch heat tolerant plastic bag. The
bags with folded open-end were left for cooling
down. Warm semi-cooked rice was inoculated withaliquot (0.3-0.5 g/bag) of pure Ta stock culture. Allbags were sealed with stapler or plastic sealer andthen each bag was punched along under the sealed
line with fine needle for 20-30 holes. The Tainoculated bags were incubated at 25-30oC for 6-7
days (d). To prepare the spore suspension, 50 g of
Ta fresh culture were added into 10L of clean watercontained in a bottle. The bottle was vigorously
shaked in order to remove dark greenish Ta spores
form the surface of semi-cooked rice. The spore
suspension was filtered through double layers ofcheesecloth [18].

187SEE - Nagoya, Japan, Nov.12-14, 2018

substrate supplemented with VCT (20% v/v) (VCT).
All four treatments were not inoculated with Pa(-Pa). While treatments 5-7 were the same astreatments 2-4 but were inoculated with Pa (+Pa) as
previously described.

VC+T (+Pa) significantly increased the heights ofbutter head lettuce by 9.43 and 9.43 % %,respectively when compared with a control (VC(+Pa)) (substrate supplemented with vermicompostand Pa- inoculation). Similar results were obtained
for the width of Butter Head lettuces, which VCTand VC+T treatments without Pa inoculation (-Pa)
significantly increased the width of butter headlettuce by 12.16 and 18.56 %, respectively. While
only VCT treatment with Pa inoculation (VCT(+Pa)) significantly increased the width of butter
head lettuce by 6.27 % when compared with acontrol (VC (+Pa)) (Table 1).

Promotion of Plant Growth
After harvesting of 42-d-old lettuce (Butter
Head) plants, plant growth characteristics wererecorded. These included the height, width, freshand dry weights of lettuce leaves, leaf numbers, leaf
area (measured by Li-3100 Area Meter) and basal
stem cutting surface area of each plant.

Table 1 Effects of planting substrates supplemented
withvermicompost(VC)
andvermicompost fortified with Trichoderma
asperellum CB-Pin-01 (VCT and VC+T) on
the height and width of 42-d-old Butter
Head lettuce

Fungal Colonization of Roots
Colonization of lettuce roots by Pa and Ta weredetected on modified BNPRA [21] and Martin’s
medium, respectively. The samples of roots
collected from 42-d-old lettuce plants weredisinfested in 0.525% sodium hypochlorite for 3
min, washed three times with sterile distilled water,
blotted dry and cut into 1.0 cm pieces before placing
on the selective media. Mycelial growth developed
from the lettuce root samples were detected andrecorded.
Substrate Colonization
Trichoderma

byPythium

Treatment
1.Control (-Pa)
2.VC (-Pa)

Height (cm)Width (cm)
16.58 c1/
24.67 cd
18.83 b24.75 cd2/(+13.57%)(+0.32%)
3.VC+T (-Pa)
19.08 b29.25 a(+15.07%)(+18.56%)
4.VCT (-Pa)
20.25 a27.67 b(+22.13%)(+12.16%)
5.VC (+Pa)
16.75 c23.92 d6. VC+T (+Pa)
18.33 b24.33 cd(+9.43%)3/(+1.71%)
7. VCT (+Pa)
18.33 b25.42 c(+9.43%)(+6.27%)
C.V. (%)
1.98
1.97
1/
Means in each column followed by the same letter(s) are not significantly different according to the
Least Significant Difference (LSD) (P≤0.05).
2/
Percentage of increment (+) of each treatment
mean when compared with a control (-Pa) (substrate
without VC, Pa-uninoculation).
3/
Percentage of increment (+) of each treatment
mean when compared with a control (VC (+Pa))(substrate with VC and inoculated with Pa).

and

Substrate samples from all treatments werecollected and enumerated for surviving populationsof Pa and Ta using modified BNPRA and Martin’s
medium, respectively. All plates were incubated for
3-5 days at room temperature (25-30 °C). Colonies
developed from substrate samples were observedand counted.
Statistical Analyses
All data were statistical analysis using analysis
of variance (ANOVA). The significance ofdifference between the treatment means wasdetermined by Least Significant Difference (LSD)
using the statistical programs R [22]. The
significance level was set at P≤0.05.

Two Trichoderma treatments (VC+T and VCT)
increased leaf number, leaf area and basal stem
cutting surface area by 13.06 and 21.05 %, 8.44 and16.97% and 10.56 and 32.54 %, respectively whencompared with a control (-Pa). When treatments
were inoculated with Pa (+Pa), the Trichoderma
treatments, VC+T (+Pa) and VCT (+Pa) could also
increase leaf number, leaf area and basal stem
cutting surface area by 10.73 and 11.18 %, 7.19 and20.16% and 27.62 and 39.15 %, respectively whencompared with a control (VC (+Pa)) (Table 2).

RESULTS
Effects of VCT and VC+T on Plant Growth
Promotion
Both of treatments without Pa inoculation, VCT(-Pa) and VC+T (-Pa) significantly enhanced theheights of butter head lettuce by 22.13 and 15.07 %,respectively as compared to a control (-Pa). While
treatments inoculated with Pa, VCT (+Pa) and

188

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Effects of planting substrates supplemented
withvermicompost(VC)
andvermicompost fortified with Trichoderma
asperellum CB-Pin-01 (VCT, VC+T) on
leaf number, leaf area and basal stem
cutting surface area of 42-d-old Butter Headlettuce
Treatment

Leaf
numberLeaf area(cm2)

fresh and dry weight of 42-d-old Butter
Head lettuce
Treatment

Fresh weight(g)
98.83 b1/

Dry weight(g)
3.40 d

1.Control
(-Pa)
2.VC
99.44 b3.94 bc(-Pa)(+0.61%)2/(+15.88%)
3.VC+T
111.00 a
4.39 ab(-Pa)(+12.51%)(+29.11%)
4.VCT
127.10 a4.61 a(-Pa)(+28.60%)(+35.58%)
5.VC
89.17 c3.08 d(+Pa)
6.VC+T
91.25 c3.31 d3/(+Pa)(+2.33%)(+7.36%)
7.VCT
97.92 c3.55 cd(+Pa)(+9.81%)(+15.07%)
C.V. (%)
1.96
2.08
1/
Means in each column followed by the same letter(s) are not significantly different according to Least
Significant Difference (LSD) (P≤0.05).
2/
Percentage of increment (+) of each treatment
mean when compared with a control (-Pa) (substrate
without VC, Pa-uninoculation).
3/
Percentage of increment (+) of each treatment
mean when compared with a control (VC (+Pa))(substrate with VC and inoculated with Pa).

Basal stem
cuttingsurfacearea (cm2)1.84 e1.Control
25.5 cd1/
64.27 ab(-Pa)
2.VC
26.33 c71.48 ab2.44 bcd(-Pa)(+3.35%)2/ (+11.21%) (+32.54%)
3.VC+T
28.83 b75.57 a2.04 cd(-Pa)(+13.06%) (+16.97%) (+10.56%)
4.VCT
30.92 a69.70 ab3.01 a(-Pa)(+21.25%)(+8.44%)(+63.61%)
5.VC
24.13 d61.02 c1.99 de(+Pa)
6.VC+T
26.72 c65.41 bc
2.55 bc(+Pa)(+10.73%)3/(+7.19%)(+27.62%)
7.VCT
26.83 c73.36 a2.78 ab(+Pa)(+11.18%) (+20.16%) (+39.15%)
C.V. (%)
1.97
1.96
2.10
1/
Means in each column followed by the same letter(s) are not significantly different according to Least
Significant Difference (LSD) (P≤0.05).
2/
Percentage of increment (+) of each treatment
mean when compared with a control (-Pa) (substrate
without VC, Pa-uninoculation).
3/
Percentage of increment (+) of each treatment
mean when compared with a control (VC (+Pa))(substrate with VC and inoculated with Pa).

Effects of VCT and VC+T on Root and Substrate
Colonization by Pa and T
Lettuce roots and planting substrates from all
Trichoderma treatments were found highlycolonized by T. asperellum CB-Pin-01 by 30-100
and 100 %, respectively. Colonization of roots andplanting substrates by Pa in treatments using VCT(+Pa) and VC+T (+Pa) were 0, 53.33 and 0, 80.00%, respectively, whereas 100 % of colonization was
found from the treatment of VC (+Pa) without T(Table 4 and 5).

Effects of VCT and VC+T on Plant Weight
The treatments of VC+T and VCT significantly
increased fresh and dry weights of 42-d-old butter
head lettuce by 12.51, 28.60 and 29.11, 35.58 %,respectively when compared with a control (-Pa).
The treatments inoculated with Pa, VC+T (+Pa) andVCT (+Pa) increased fresh and dry weights of Butter
Head lettuce by 2.33, 9.81 and 7.36, 15.07 %,respectively. When VC treatment (substrate
supplemented with only vermicompost and Pauninoculation) could increase butter head lettuce
fresh and dry weight by 0.61 and 15.88 % whencompared with a control (-Pa) (Table 3).

Table 4 Colonization percentages of Pythiumaphanidermatum (Pa) and Trichoderma
asperellum (T) on 42-d-old lettuce roots
planted in substrates supplemented withvermicompost (VC) and vermicompost
fortified with T. asperellum CB-Pin-01(VCT, VC+T)
Treatment

Table 3 Effects of planting substrates supplemented
withvermicompost(VC)
andvermicompost fortified with Trichoderma
asperellum CB-Pin-01 (VCT, VC+T) on

1.Control (-Pa)
2.VC (-Pa)
3.VC+T (-Pa)
189

Root colonization (%)
Pa
T
nd1/
nd
nd
nd
nd
100

SEE - Nagoya, Japan, Nov.12-14, 2018nd
4.VCT (-Pa)
5.VC (+Pa)
100
6.VC+T (+Pa)
53.33
7.VCT (+Pa)
01/
nd = Non determinedof lettuce growth. Root colonization by T.
asperellum CB-Pin-01 also resulted in theenhancement of phosphorus, potassium and nitrogenin lettuce leaves by 70, 18 and 6% as compared tountreated control, respectively. Similar to Kansarn[12] who reported that the transplanting of lettuce
seedlings sown in sowing substrate suplemented
with spore suspension of T. harzianum CB-Pin-01
into planting substrate with a ratio 70:20:10 (percent
by volume) of T. harzianum CB-Pin-01 – soaked
chopped coconut husks, compost and ash powder
reduced the percentage of P. aphanidermatum
infected roots and promoted growth of lettuce whencompared with the Pythium inoculated control.
Buasuwan [24] reported that the treatment used
Bacillus mycoides FL17 bacteria bioproductvermicompost combination could promote plant
growth by giving the highest fresh weight of butter
head lettuce plant (149.19 g/plant). Chaohem [25]reported that T. asperellum CB-Pin-01 (Ta)fortifield vermicompost (VCT) and cow manure(CM+Ta) promoted the growth of yard-long bean byincreasing plant height and root length. While thesetreatments also increased percentages of seedgermination and survived seedlings of yard longbean grown in planting substrate inoculated with
Rhizoctonia solani.

35
nd
100
30

Table 5 Colonization percentages of Pythiumaphanidermatum
andTrichoderma
asperellum
onplanting
substrates
supplemented with vermicompost andvermicompost fortified with T. asperellum
CB-Pin-01 (T) at 42 d after sowing
Treatment

1.Control (-Pa)
2.VC (-Pa)
3.VC+T (-Pa)
4.VCT (-Pa)
5.VC (+Pa)
6.VC+T (+Pa)
7.VCT (+Pa)
1/
nd = Non determined

Planting substrates
colonization (%)
Pa
T
nd1/
nd
nd
nd
nd
100
nd
100
100
nd
80
100
0
100

DISCUSSIONCONCLUSIONS

Enhancement of plant growth induced by
Trichoderma species has been reported for a large
number of different groups of plants including
cereal, vegetable, ornamental and forestry crops.
Various mechanisms have been proposed to explain
plant
growthpromotion
associatedwith
Trichoderma species. These include synthesis ofphytohormones, either by microbe or plants;
production of vitamins; increased uptake andtranslocation of nutrient; enhanced solubilization ofsoil nutrient; enhanced root development andincreased in the rate of carbohydrate metabolism;
photosynthesis and plant defense mechanisms[6],[7]. Benitez et al. [23] reported that Trichoderma
strains were able to produce plant growth hormones
like cytokinin-like molecules, e.g. zeatin andgibberellin GA3 or GA3-related which directly
affected on plant growth.
There were many researchers reported theabilities of root colonization by T. harzianum toincrease nutrient uptake and fertilizer utilization
efficiency which resulted in plant growth promotion.
T. harzianum T22 treated maize seed showed thehigh efficacy to increase the nitrogen use efficacy[6], [7]. Similar to Lamool [11] who reported thatthe application of spore suspension of T. asperellum
CB-Pin-01 (1 kg-fresh culture 2,000 L-1) into
nutrient solution of lettuce grown in the NFT
hydroponic system effectively provided not only the
reduction of Pythium root rot but also the promotion

This study revealed that the planting substrate
supplemented with VCT provided the highest
growth promotion of lettuce by increasing theheight, leaf number, leaf area, basal stem cutting
surface area, plant fresh and dry weights whencompared with the control (substrate without
vermicompost). When the substrates were inoculatedwith P. aphanidermatum (+Pa), the treatment VCT(+Pa) completely reduced Pa-colonization on lettuceroots and planting substrates. Moreover, T.
asperellum CB-Pin-01 could be completely
recovered from planting substrates (100%) andlettuce roots (100%).
ACKNOWLEDGEMENTS
The authors are grateful to members of the Plant
Disease Biocontrol Laboratory, Department of Plant
Pathology, Kasetsart University, Kamphaeng Saen
Campus for their warm co-operation in all
experiments.
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Codon. Biocontrol mechanisms of Trichoderma
strains. Int. Microbiol. Vol. 7. 2004, pp. 249-260.
[24] Buasuwan, J. Efficacy of Bacillus spp.
bioproducts for the control of root rot caused by
Pythiumaphanidermatumon
NFThydroponically grown lettuce. M.S. Thesis,
Kasetsart Univ. Bangkok. 2013.
[25] Chaohem, S. Efficacy of organic fertilizers
fortified with Trichoderma asperellum CB-Pin01 for the control of damping-off on yard longbean caused by Rhizoctonia solani. B.S. Thesis,
Kasetsart Univ. Bangkok. 2017.

191

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECT OF OZONE MICROBUBBLES WITH VARIOUS
TEMPERATURES ON THE CHLORPYRIFOS INSECTICIDEREMOVAL IN TANGERINE CV. SAI NAM PHUENG
Wirin Singtoraj1,4, Jamnong Uthaibutra1,3,4 and Kanda Whangchai1,2,3,4*
Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand;
2
Center of Excellence in Bioresources for Agriculture, Industry and Medicine Chiang Mai University,
Chiang Mai 50200, Thailand; 3Postharvest Technology Research Institute, Chiang Mai University, Chiang
Mai 50200, Thailand; 4Postharvest Technology Innovation Center, Office of the Higher Education
Commission, Bangkok 10400, Thailand
1

ABSTRACT
Chlorpyrifos, a type of organophosphate insecticide, is widely used to destroy pests in tangerine orchard for
reduce the loss and maintain the quality of fruit. Consequently, the application of insecticides during production
leads to the insecticide residues problem in tangerine that can be dangerous to human health. This study
investigated the effect of ozone microbubbles (OMBs) on the removal of chlorpyrifos residues in the fruit.
Tangerines were sprayed with chlorpyrifos solution at a concentration of 10 minutes. Then, they were treatedwith OMBs at different temperatures (15, 20 and 25 oC) for various exposing times (0, 10, 20, 30, 40, 50 and 60
minutes). Removal percentage of chlorpyrifos residues in tangerines was determined by gas chromatographyflame photometric detector (GC-FPD). The results showed that chlorpyrifos residues in tangerines was decreased
at lower water temperature, especially at 15 oC resulting in the removal up to 81% after treating with OMBs for
30 minutes when compared to control (distilled water). After that, the fruits were stored at 25 oC for 7 days todetermine quality changes. The percentage of weight loss, total soluble solids (TSS), titratable acidity (TA),disease incidence and ascorbic acid content in all treatments were not affected by OMBs. These results
demonstrate that OMBs treatment at 15 oC is the most effective treatment for removing chlorpyrifos residues intangerine and have no effects on the fruit quality.
Keywords: Tangerine, Chlorpyrifos, Insecticide residues, Ozone microbubbles

hygiene and to extend shelf life of many postharvest
agricultural products [4]. Moreover, it was foundthat oxidation by ozone is an effective treatment todegrade the insecticide residues on agricultural
products [5]. For example, Whangchai et al. [6]reported that using ozone gas for 60 minutes can
reduce 45% chlorpyrifos insecticide on lychee fruits
without changes in fruit quality. Kusvuran et al. [7]found that fumigation with 10 minutes of ozone gas
for 5 minutes can reduce the tetradifon andchlorpyrifos insecticides on the surface of citrus
fruits in the ratio of 100% and 98.6% respectively
and Wu et al. [8]. stated that low level dissolved
ozone (1.4 mg/L) was abled to reduce diazinon,
parathion and methyl parathion insecticide residues
in Pak Choi (Brassica rapa) in 30 minutes.
Nevertheless, the low water solubility and rapid
degradation of ozone are problems for an attack on
insecticide molecules.
Ozone microbubbles (OMBs) is a goodalternative technique that can transform ozone gas
into micro-size bubbles (less than 10 µm) in thewater. These micro-bubbles can keep the ozone
inside for a longer period and they will be slowly
floated up to the water surface that increased thedissolving potential of ozone. In this process, the

INTRODUCTION
Chlorpyrifos, a type of organophosphate
insecticide, is widely used to destroy pests intangerine orchard for reduce the loss and maintainthe quality of fruit. Consequently, the application of
insecticides during production leads to theinsecticide residues problem in tangerine that can be
dangerous to human health. Thai Pesticide Alert
Network reported that tangerine in northern
Thailand had chlorpyrifos, insecticide residues morethan 1.0 mg/L and this exceeded the Maximums
Residue Limits (MRLs) [1]. This leads to possible
chronic or acute health risk for consumers.
Therefore, there is a requirement for effective
oxidation technology such as ozone microbubbles
that has been applied for removing insecticide
residues in tangerine.
Ozone is environmentally friendly and confirmed
as a Generally Recognized As Safe (GRAS) for foodcontact application. Ozone is a powerful oxidant
with a wide range of sanitizing application. Due toits instability with a half-life of 20-30 minutes indistilled water at 20 oC [2], it degrades quickly into
oxygen and leaves no residues after application [3].
Ozone has been used as sanitizer in food surface
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SEE - Nagoya, Japan, Nov.12-14, 2018

surface of microbubbles will be surrounded byanionic molecules, therefore they will not be
combined together to form big- bubbles. Likewise,
the microbubbles enhance the oxidizing efficiencyof the ozone which help to destroy the insecticide
structures [9]-[11]. It has been reported that OMBs
removed water pollutants (ammonia and diethyl
phthalate) from wastewater in a pilot plant [12], [13].
Furthermore, Ikeura et al. [14] found that sanitizing
with OMBs (2 mg/L) for 20 minutes could reduce
the fenitrothion insecticide residues in lettuce, cherry
tomatoes and strawberries with no effect on productquality. Therefore, the objective of this research is to
study the effect of OMBs with various temperatureson the chlorpyrifos insecticide removal in tangerine
cv. Sai Nam Phueng.

concentration of dissolved ozone was determined byan ozone solution detector (Prominent Dulcotest
DT1B photometer) and the removal percentages ofeach standard chlorpyrifos insecticide sample wasdeterminedbygaschromatography-flame
photometric detector (GC-FPD).
Ozone Microbubbles Treatment on the Removalof Chlorpyrifos Insecticides and Postharvest
Quality Changes in Tangerine
Organic tangerines (Citrus reticulata Blanco cv.
Sai Nam Pueng) were purchased from the orchards
in Mae Tang district, Chiang Mai Province, Thailand.
The fruits were sorted for free of wound fromharvesting and insect bites. Each fruit sample wassprayed with 10 mg/L chlorpyrifos insecticide
solution and then air dried at room temperature.
Then, they were sanitized in OMBs with the same
conditions as the best result from above Experiment.
Insecticide residues of tangerine was extracted with
the Agilent Quick, Easy, Cheap, Effective, Rugged
and Safe (QuEChERS) extraction kit. Then thesamples were analyzed insecticide residues by GCFPD to determine the removal percentage ofchlorpyrifos insecticide.

MATERIALS AND METHODS
Chemicals Preparation
Standard chlorpyrifos insecticide was purchasedfrom Sigma-Aldrich Laborchemikalien GmbH
(Stienheim, Germany) with 99% purity. Standard
chlorpyrifos insecticide stock solution (1000 mg/L)
for the insecticide residues analysis was prepared in
acetone. The chlorpyrifos insecticide solution was
diluted with distilled water to appropriate working
concentrations.

Postharvest quality changes in tangerine
Ozone Microbubbles Preparation
Tangerines were immersed into OMBs water inthe same way as the previous experiment. Samples
were stored at 25 oC and taken everyday for 7 days
to determine the fruit quality. The percentage of
weight loss, total soluble solids (TSS), titratable
acidity (TA), disease incidence and ascorbic acidcontent were measured.

The OMBs used ozone generator (Ozonizer,
Model SO5AE) and microbubbles water generator(Model 15KED02S, Nikuni Co., Ltd., Japan) at aflow rate of 7L/minute with an internal pressure of
0.25 MPa for distilled water. OMBs water came out
from the microbubbles nozzle and circulated in the
microbubbles bath.

Statistic Analysis
Effect of Ozone Microbubbles on the Removal ofStandard Chlorpyrifos Insecticide at Different
Temperatures and Exposing Times

All the experiments were replicated 3 times andevaluated with regression procedure using the SPSS
version 17, while the differences among various
treatments by Duncan’s New Multiple Range test
(p<0.05).

The optimum condition for the removal ofchlorpyrifos insecticide using OMBs water wasdetermined at various conditions at different
temperatures (15, 20 and 25 oC) and various
exposing times (0, 10, 20, 30, 40, 50 and 60
minutes). Standard chlorpyrifos insecticide solution
were prepared in the flask. Each standard
chlorpyrifos insecticide solution sample was addedwith 20 ml of OMBs water treatment previously
mentioned and distilled water (control). The

RESULTS AND DISCUSSION
Effect of Ozone Microbubbles on the Removal ofStandard Chlorpyrifos Insecticide at Different
Temperatures and Exposing Times
The concentration of dissolved ozone in water
was determined using an ozone solution detector
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SEE - Nagoya, Japan, Nov.12-14, 2018

(Prominent Dulcotest DT1B photometer). It was
found that OMBs treatments at 25 oC obtained theconcentration of 0.22, 0.24, 0.29, 0.24, 0.26 and 0.29
mgO3/L, at 20 oC obtained the concentration of 0.25,
0.30, 0.35, 0.30, 0.30 and 0.35 mgO3/L and at 15 oC
obtained the concentration of 0.49, 0.53, 0.61, 0.52,
0.48 and 0.48 mgO3/L at 10, 20, 30, 40, 50 and 60
minute, respectively (Fig. 1). The dissolved ozone
concentration of OMBs treatment were increased
when exposure time 10-30 minutes and then they
were stabled during experiment times. All OMBs
treatment at 15 oC obtained the concentration ofdissolved ozone more than at 20 and 25 ºC. Due tothe low temperature may increase the dissolved
ozone in water, while the high temperature increase
the chemical reaction between substrate and oxidant,
but decrease the dissolved ozone in water [15].

which can maintain the ozone for a long time. In
addition, the usefulness effect of low OMBs watertemperature may be due to the increasing dissolved
ozone in water, which enhance the oxidizing
efficiency of the OMBs to collapse with insecticide
structure [19].

Fig. 2

Removalpercentage
ofstandard
chlorpyrifos solution after OMBs treatment
at different temperatures and exposing
times.

Ozone Microbubbles Treatment on the Removalof Chlorpyrifos Residues and Postharvest Quality
Changes in Tangerine

Fig. 1

Tangerines were sanitized in OMBs treatment inorder to remove residual chlorpyrifos insecticide.
The results showed that OMBs at 15 oC for 30
minutes was the most effective to remove
chlorpyrifos insecticide from tangerine that relatedwith concentration of dissolved ozone. It was foundthat the chlorpyrifos residues on fresh tangerine
showed the highest removal percentage ofchlorpyrifos residues (81%) with significant(P<0.05) different when compared with anindividual treatment and the control, which was

Concentration of dissolved ozone after
OMBs at different temperatures andexposing times.

The effect of OMBs to remove the standard
chlorpyrifos insecticide solution was also examined.
It was found that the removal percentage of standard
chlorpyrifos insecticide was significantly inducedwith low temperature and prolonged OMBs
exposure time for 30 minutes. Furthermore, OMBs
at 15 oC for 30 minutes was the most effective
treatment for removing standard chlorpyrifos
insecticide residues, insecticide removal was 42%.
But, the trend of standard chlorpyrifos insecticide
residues removal percentage after exposure time for40-60 minutes in all OMBs treatment was decreased.
There were significant (P<0.05) difference in each
OMBs treatment (Fig. 2).
Ozone is a powerful oxidant, probably modified
the chemical structure of chlorpyrifos insecticide byoxidizing sulfate ion in thiophosphorile bonds (P=S)
of chlorpyrifos insecticide into phosphorile bonds(P=O) [16], [17]. And, decreasing of ozonated watertemperature cause positive effect on the removal
percentage of organophosphate insecticides [18].
Moreover, microbubbles has a high surface area,

Fig. 3

194

Removal percentage of chlorpyrifos in fruit
after OMBs at different temperatures andexposing times.

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Changes in percentage of weight loss, TSS, TA, disease incidence and ascorbic acid content oftangerine after sanitizing with ozone microbubbles at 15oC for 60 minutes, and storage at 25 oC for 7
days

treatment

Weightloss (%)

TSS (%)

TA (%)

Control
OMBs 10 minutes
OMBs 20 minutes
OMBs 30 minutes
OMBs 40 minutes
OMBs 50 minutes
OMBs 60 minutes

0.92a
0.80a
0.83a
0.82a
0.81a
0.81a
0.83a

10.76a10.42a
9.60a
9.80a
9.82a
9.75a
9.75a

0.23a
0.28ab0.32ab
0.28ab
0.30ab
0.29ab
0.29ab

Diseaseincidence(%)
3.43ab
3.33a
3.33a
3.33a
3.43ab
3.43ab
3.43abAscorbic
content(mg/ml)0.91ab
1.01a
1.09a
1.04a
1.06a
1.05a
1.06a

Note: The data followed by the same letter within the column are not significantly different (P<0.05)

sanitized in distilled water (Fig. 3). This trend could
be explained by the reaction of OMBs with low
temperature increasing dissolved ozone in waterleading to high hydroxyl radical producing, which
effectively distinguished chlorpyrifos residues on thetangerine surface. Similarly, Wu et al. [8] reported
that application of the ozonated water at 14oC for
insecticide removal from Pak Choi (Brassica rapa)
was more effective than at 24 oC.
Thus, this research showed that the efficiency of
OMBs on chlorpyrifos insecticide removal depended
on the decreasing of the temperature of OMBs waterand exposure times. Temperature of OMBs water
related to the efficacy of dissolved ozone in water.
Therefore, the low temperature could be increase theability of dissolved ozone in water.
The postharvest quality changes in the tangerine
after sanitizing with OMBs treatment, and thenstoring at 25 oC and taken everyday for 7 days wereconcluded and shown in Table 1. All treatments had
non-significant differences as fruit quality changes
during storage at 25 oC for 7 days. The percentage of
weight loss, TSS, TA, disease incidence andascorbic acid content in all treatment were notsignificant changes during storage in all thetreatments. Similarly, treatment of vegetables suchas arugula, bell pepper, cabbage, carrot, cucumber,leek, pasley and tomatoes with ozonated water at 25o
C can remove chlorpyrifos insecticide residues
higher than at 35 oC without changing in antioxidant
capacity, total phenolic and ascorbic acid [20].

ACKNOWLEDGEMENTS
This research has been supported by Postharvest
Technology Innovation Center, Office of the Higher
Education Commission, Bangkok, Thailand.,
Postharvest Technology Research Institute, Chiang
Mai University, Chiang Mai, Thailand and the
Graduate School Chiang Mai University, Chiang
Mai, Thailand.
REFERENCES[1] Ousap P., Road Map of Food Safety, Reportfrom Thai Pesticide Alert Network, 2017.
http://www.thaipan.org/node/831.
[2] Chelme-Ayala P., El-Din M.G., and Smith
D.W.,
Kinetics and Mechanism of the
Degradation of Two Pesticides in Aqueous
Solutions by Ozonation, Chemosphere, Vol. 78,
Issue 5, 2010, pp. 557–562.
[3] Carletti L., Botondi R., Moscetti R., Stella E.,
Monarca D., Cecchini M., and Massantini, R.,
Use of Ozone in Sanitation and Storage of Fresh
Fruits and Vegetables, Journal of Food,
Agriculture and Environment, Vol. 11, 2013,
pp. 585-589.
[4] Coke A.L., For Chapter in a Book, Ozone inFood Processing, Ed. Blackwell Publishing Ltd.,
2012, pp. 48-51.
[5] Ormad M.P., Miguel N., and Claver A.,
Pesticides Removal in the Process of Drinking
Water Production, Journal of Antimicrobial
Chemotherapy, Vol. 71, Issue 1, 2008,
pp. 97-106.
[6] Whangchai K., Uthaibutra J., Phiyanalinmat S.,
Pengphol S., and Nomura N., Effect of Ozone
Treatment on the Reduction of Chlorpyrifos
Residues in Fresh Lychee Fruits, Ozone:
Science and Engineering, Vol. 33, 2011, pp.
232-235.

CONCLUSIONOMBs at different temperatures had effects on
the removal of chlorpyrifos insecticide. The
exposure times of OMBs at 15ºC for 30 minutes
provide the best result on the removal ofchlorpyrifos insecticide (81%) in tangerine and haveno effects on the fruit quality.
195

SEE - Nagoya, Japan, Nov.12-14, 2018

[7] Kusvuran E., Yildirim D., Mavruk F., andCeyhan M., Removal of Chlorpyrifos Ethyl,
Tetradifon and Chlorothalonil Pesticide
Residues from Citrus by Using Ozone, Journalof Hazardous Materials, Vol. 2, Issue 4, 2012,
pp.287-300.

[14] Ikeura H., Hamasaki S., and Tamaki M., Effectsof Ozone Microbubble Treatment on Removalof Residual Pesticides and Quality of
Persimmon Leaves, Food Chemistry, Vol. 138,
Issue 1, 2013, pp. 366-371.
[15] Hart E.J., and Henglein A., Free Radical andFree Atom Reactions in the Sonolysis of
Aqueous Iodide and Formate Solutions, Journalof Physic Chemistry, Vol. 89, 1985, pp. 43424347.
[16] Pond A.L., Chambers H.W., and Chambers J.E.,
Organophosphate Detoxication Potential of
Various Rat Tissues via A-esterase andAliesterase Activities, Toxicology Letters, Vol.
78, Issue 3, 1995, pp. 245–252.
[17] Wu J.G., Lan C.Y., and Chan G.Y.S.,
Organophosphorus Pesticide Ozonation andFormation of Oxon Intermidiates, Chemosphere,
Vol. 76, 2009, pp. 1308-1314.
[18] Kusvuran E., Yildirim D., Mavruk F., andCeyhan M., Removal of Chlorpyrifos Ethyl,
Tetradifon and Chlorothalonil Pesticide
Residues from Citrus by Using Ozone, Journalof Hazardous Materials, Vol. 2, Issue 4, 2012,
pp. 287-300.
[19] Guidance Manual Alternative technique andOxidant, Information from United States
Environmental Protection Agency, 2001.
http://water.epa.gov/lawsregs/rulesregs/sdwa/m
dbp/upload_2001_12_mdbp_alter.pdf.
[20] Khaled A.O., Fahad B., and Abdullah A., Ozone
as a Safety Post-Harvest Treatment for
Chlorpyrifos Removal from Vegetables and Its
Effects on Vegetable Quality, International
Journal of Food and Nutritional Science, Vol. 3,
Issue 2, 2017, pp. 1-11.

[8] Wu J.G., Luan T., Lan C.Y., Lo T.W.H., andChan G.Y.S., Removal of Residual Pesticides
on Vegetable Using Ozonated Water, FoodControl, Vol. 18, 2007, pp. 466-472.
[9] Sumikura M., Hidaka M., Murakami H.,
Nobutomo Y., and Murakami T., Ozone
Microbubble
Disinfection
Methodfor
Wastewater Reuse System, Water Science andTechnology, Vol. 56, Issue 5, 2007, pp. 53-61.
[10] Takahashi M., Chiba K., and Li P., Formationof Hydroxyl Radicals by Collapsing Ozone
Microbubbles under Strong Acid Conditions,
The Journal of Physical Chemistry, Vol. 111,
2007, pp. 11443-11446.
[11] An T., Gao Y., Li G., Kamat P.V., Peller J., andJoyce M.V., Kinetics and Mechanism of OH
Mediated Degradation of Dimethyl Phthalate in
Aqueous
Solution:
Experimental
andTheoretical Studies, Environmental Science andTechnology, Vol. 48, Issue 1, 2014, pp. 641-648.
[12] Khuntia S., Majumder S.K., and Gosh P.,
Removal of Ammonia from Water by Ozone
Microbubbles, Industrial and Engineering
Chemistry Research, Vol. 52, Issue 1, 2013,
pp. 318-326.
[13] Jabesa A., and Ghosh P., Removal of Diethyl
Phthalate from Water by Ozone Microbubbles
in a Pilot Plant, Journal of Environmental
Management, Vol. 180, 2016, pp. 476-484.

196

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECTS OF ACIDIC ELECTROLYZED WATER WITH DIFFERENTTEMPERATURES ON MICROBIAL CONTROL AND QUALITY OF
FRESH-CUT BANANA LEAVES DURING STORAGE
Varumporn Kuljaroensub1, Kanda Wangchai1,2 and Usawadee Chanasut1,2
Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand;
2
Postharvest Technology Institute/ Postharvest Technology Innovation Center, Chiang Mai University,
Chiang Mai 50200, Thailand
1

ABSTRACTThe effects of acidic electrolyzed water (AEW) on microbial control and quality of fresh-cut banana leaves
during storage were studied. Fresh-cut banana leaves cv. Tanee (TN) and cv. Klauay Namwa (KN) were
sanitized with either 4°C or 27+2°C of 50 ppm acidic AEW for various times (10, 20 and 30 minutes). The
sanitized sample were packed in polyethylene (PE) bag and storage at 5+2◦C for 7 days, before transferred to
27+2°C to evaluate their shelf-life. The results showed that sanitization with 4°C and 27+2°C of AEW for 30
minutes were completely eliminated the microorganism on fresh-cut samples from both cultivars. Nevertheless,these contact time had the highest loss more than 78% after 5 days at room temperature. Sanitized samples with
AEW for 20 and 30 minutes effectively delayed the microbial growth, therefore the amount of microorganism
remained below EU Regulation (EC) No. 2073/2005 criteria after storage. The shelf-life of fresh-cut samples
was 13 days and terminated after their visual appearance such as yellowing or browning occurred. Fresh-cut
samples sanitization with both treatments had similar quality changes such as color changes and chlorophyll
contents. However, sanitization with 4°C AEW had lower weight loss than those of with 27°C AEW duringstorage at room temperature. It also effectively reduced the microorganism on fresh-cut samples and had thelowest loss which was 22%. Therefore, sanitization with 4°C AEW for 20 minutes was an appropriate method tosanitized fresh-cut banana leaves for both cultivars.
Keywords: Sanitization, Fresh-cut, Acidic electrolyzed water, Banana leaves

the microbial growth in the products. Raw fresh
produce could be contaminated with pathogens
during harvesting through fecal material (manure,both of human and animal origin), human handling,
washing
procedure,
processing
equipment,
transportation, and distribution [4].
Electrolyzed Water (EW) has been used as
sanitizer in the food industry for many years [5][6].
AEW are conventionally generated by electrolysis ofaqueous sodium chloride (0.5–1.0% NaCl), and anelectrolyzed acidic solution is produced at the anode.
Aidic Electrolyzed water (AEW) has a strong
bactericidal effect on pathogenic and spoilage
microorganisms [7][8]. This effect is attributed to its
low pH (2.1–4.5), high oxidation–reduction potential(higher than 1000 mV), and the presence of active
oxidizers such as hypochlorous acid [9][10].
Previously, Issa-Zacharia et al. [11] reported that
Slightly
AEW
technology
hadstrongerdecontamination ability than other sanitizers infresh-cut lettuce and carrot. Tomas-Callejas et al.
[12] also reported that acidic electrolyzed water has
the most effective on microbial reduction of mizuna
baby leaves compared with other sanitizers.
There are numerous reports which describe theefficacy of AEW on the microbial growth on fruitand vegetables [13][14]. Therefore, this sanitizer

INTRODUCTION
Banana leaves have been used for food wrapped anddecoration since the ancient times due to theirappearance and aroma made food is appetizing.
Nowadays cut banana leaves are widely used forfood wrapping and decoration in restaurants both inThailand and oversea. The banana leaves exported
from Thailand was frozen. The bag of banana leaves
contained at least 5 kilograms of cut banana leaf
sheath. However there were less than 50% can beused from each bag, and the rest became waste
because of the trimming to suitable for consumer
purposes.
Today’s consumer is demanding for foods that
require minimal process, for example, Fresh cut fruitand vegetables, initially called minimally processedor lightly processed products, are those that havebeen trimmed, peeled and/or cut into 100% usable
product that is bagged or pre-packed and kept at
refrigerated storage. These foods are in great
demand because of their convenience [1]. The foodservice industry and restaurants are the major usersof minimally processed products [2]. However,
fresh-cut products deteriorate quickly and have
limited shelf-life [3]. Major problems ofdeterioration in fresh-cut products associated with197

SEE - Nagoya, Japan, Nov.12-14, 2018

should effectively remove microbial contaminationon the fresh-cut banana leaves too. The purpose of
the current study was to evaluate the efficacy of 4°C
and 27+2°C AEW at different time (10, 20 and 30
minutes) for controlling microbial growth and theireffect on quality of fresh-cut banana leaves duringstorage at low temperature.

The weight loss of samples was determined byweighing each fresh-cut leaf samples on the day
after each period of storage using a laboratory level
weighing balance. Values are reported as percentage
of weight loss per initial sample weight.

MATERIALS AND METHODSThe upper and lower surface color of fresh-cut
banana leaves were determined using a HunterLabcolourimeter (ColourFlex, Hunter Associates
Laboratory, Inc., VA, USA). Color was measured
using the CIE L*, a* and b* scale. The color values
were expressed as L* (whiteness or brightness/darkness), a* (redness/greenness) and b*(yellowness/blueness) at any time, respectively.
Each sample was scanned at three different locations
to determine the average L*, a* and b* values
during the measurements.

Color evaluation

Plant Materials(Musa balbisiana
Banana leaves cv. Tanee
Colla.) and cv. Klauy namwa (M. sapientum Linn.)from Muang mai market (Chaing mai, Thailand)
were transported to the postharvest laboratory(Chiangmai University, Thailand). The leaves were
physically inspected and defective parts such asmechanical damage or yellowing pieces were
removed. Selected leaves were cut into 7 inches
diameter of circle for following study.

Chlorophyll content
The chlorophyll pigments were extracted from 5
g. of fresh-cut sample with 20 ml acetone for 20
minutes and then filter with filter paper No.1.
Quantification
was
performed
inaspectrophotometer (UV-1603 Shimadzu Tokyo,
Japan) The total chlorophyll, chlorophyll a andchlorophyll b content was expressed as mg per 100 gof fresh weight using [15] method.

Processing and Storage Conditions
The fresh-cut samples were sanitized with either
4°C or 27°C acidic electrolyzed water (final chlorine
concentration 50 ppm, pH 2-4) for 10, 20, 30
minutes. After air dried, sanitized samples wereplaced in PE bags. All steps were performed undersanitary conditions. Samples were stored at 5+2°C
for 7 days and then transfer at room temperature(27+2°C) for 8 days. For each treatment, ten
replicated were used. The microbial growth, qualitychanges such as, chlorophyll content, percentage of
weight loss and color changes of sample were
evaluated on the day 0) and after 3, 5, 7 days ofstorage at 5+2°C and after 9, 11, 13, 15 days at room
temperature.

Experimental Design and Statistical Analysis
The experimental units were bags and there were
ten replications per sanitizing treatment, application
system and evaluation period. ANOVA tests wereused depending on the homogeneity of thevariances. The differences among various treatments
by Tukey’s range test (P<0.05) using SPSS version
14 [16].

Microbial Content Determination
Samples were examined according to thestandard methods for the microbiological analysis.
Thirty nine grams of potato dextrose agar (PDA)
were suspended in 1 L distilled water and sterilizing
at 120 psi pressured for an hour. Spread platetechnique after serial dilution in sterile distilledwater was used in all tests. The first dilution was
prepared by shaking 5x5 cm2 of leaf samples with
5.8 ml of sterile distilled water and further dilutions
were made according to the need. Ten plates wereused for each treatment. Total viable plate countagar was determined after incubation at 37°C for 48
hours.

RESULTS AND DISCUSSION
Microbial Content Determination
The initial total microorganism on the TN leaves
was 313.33 and the KN leaves was 434.44
CFU/cm2. Cleaning with distilled water reduced themicrobial population to 48.75 (TN). and 90.93 (KN)
CFU/cm2 The longer contact time, the higher
effective of microorganism inactivation (Fig. 1,2)
for both temperatures. the sanitizing treatment.

Quality Changes Determination
Weight loss

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SEE - Nagoya, Japan, Nov.12-14, 2018

Lopez-Galvez [20] that found the microbial growthon fresh-cut products even stored at low
temperature.

Fig. 1 The number of microorganism on TN freshcut banana leaves after sanitization with
AEW and after storage at 5+2°C for 7 days.

Fig. 2

Fig. 3

Effects of AEW on % weight loss of TN
fresh-cut banana leaf storage at 5+2°C for 7
days and 27+2°C for 6 days.

Fig. 4

Effects of AEW on % weight loss of KN
fresh-cut banana leaf storage at 5+2°C for 7
days and 27+2°C for 6 days.

The number of microorganism on KN
fresh-cut banana leaves after sanitization
with AEW and storage at 5+2°C for 7 days.

The maximum reduction of total microorganism
on fresh-cut banana leaves was observed by AEW
4°C for 30 minutes which were completely
eliminated the microorganism on fresh-cut samples
from both cultivars at the day 0. The number ofmicroorganism slightly increased to 5.00 (TN) and6.75 (KN) CFU/cm2 after 7 days storage at 5+2°C.
Sanitization with 4°C AEW for 20 minutes weresignificantly reduced the total microbial content on
both cultivars to 1.5 (TN) and 1.77 (KN) CFU/cm2.
Although the number of microbial population in theleaves sample increased to 8.75 (TN) and 12.5 (KN)
CFU/cm2 after 7 days storage. [Fig 1,2], they were
below the EU Regulation and acceptable for using as
fresh cut. The temperature of sanitizer and washingtime were factors that affected the microbial efficacy
of AEW [17]. Koide et al. [18] also reported thatwhen fresh-cut cabbage was wash by slightly AEW,
the reduction were found in total bacteria count. The
number of bacteria increased during storage. Similar
results were reported by Beltran et al [19] andQuality Changes Determination
In this study, the shelf life of fresh-cut banana
leaves was 13 days regardless to their visualappearances such as the occurrence of yellowing or
browning. No difference in the appearance quality
were observed among sanitizing agents after
washing on day 0 and after7 days of storage at
5+2°C. However, the visual appearance rapidly
deteriorated after transferred to 27+2°C. Fresh-cut
banana leaves that sanitized with 4°C AEW hadlower quality loss than fresh-cut banana leaves thatsanitized with 27°C AEW. The appearance of freshcut banana leaves sanitized with 4°C AEW for 30
minutes quickly declined and more than 78% of thesample had to be discarded. The lowest quality loss
was found on fresh-cut banana leaves sanitized with
4°C AEW for 20 minutes which were 22%. Park et
199

SEE - Nagoya, Japan, Nov.12-14, 2018

al. [22] also report that long treatment times
The percentage of weight loss from all treatment
adversely affect the general appearance andslightly increased during storage at 5°C for 7 days
nutritional content of the product.
Table 1 Changes of surface color and chlorophyll content in TN fresh-cut banana leaves after sanitized withelectrolyzed water and storage for 13 days.
treatment

Upper surface colorL*a*b*37.32a -7.29a 24.58a

Lower surface colorL*a*b*
48.49a -7.16a 26.59a

total
0.14 aChlorophyll content
a
b
0.09a
0.01a

control
RT-AEW-10 mins
42.36a -5.16a 24.65a 52.13a -7.52a 31.53a
0.14 a0.10a-20 mins
35.59a -6.16a 24.14a 47.12a -6.77a 25.26a
0.19 a0.10a- 30 mins
49.08a -6.54a 28.23a 50.55a -6.50a 27.53a
0.14 a0.10a
4°C-AEW-10 mins
34.13a -7.05a 23.65a 47.51a -7.83a 27.05a
0.15 a0.07a-20 mins
35.69a -7.16a 24.46a 47.22a -8.07a 26.12a
0.17a
0.10a
- 30 mins
35.55a -7.93a 23.95a 47.95a -7.46a 26.22a
0.16a
0.10a
Note: The data followed by the same letter within the column are not significantly different (P<0.05)

0.02a
0.08a
0.04a
0.06a
0.06a
0.05a

Table 2 Changes of surface color and chlorophyll content in KN fresh-cut banana leaves after sanitized withelectrolyzed water and storage for 13 days.
treatment

Upper surface colorL*a*b*
43.35a-9.28a26.67aLower surface colorL*a*b*
54.66a-6.54a30.13aChlorophyll content
total
a
b
0.06a
0.04a
0.02a

control
RT-AEW-10 mins
40.16a-9.42a27.21a59.17a-6.16a31.51a
0.06a
0.05a
0.01a
-20 mins
52.12a-8.24a31.21a57.84a-5.16a31.45a
0.07a
0.05a
0.01a
- 30 mins
50.42a-8.15a31.30a54.91a-6.52a32.55a
0.07a
0.05a
0.01a
4°C-AEW-10 mins
44.15a-8.54a27.65a52.23a-8.63a32.01a
0.06a
0.04a
0.01a
-20 mins-9.16a32.20a53.13a-6.79a30.01a
0.06a
0.05a
0.01a
41.20a- 30 mins
41.16a-9.12a25.22a52.52a-6.15a30.45a
0.09a
0.06a
0.02a
Note: The data followed by the same letter within the column are not significantly different (P<0.05)
chlorophyll content during storage. Similarly results
and they rapidly increased after transferred towere reported by Izumi [25] on mizuna baby leaves
27+2°C. There were no significant differences
and Wang et al. [26] on cilantro leaves. However,among AEW treatments during storage period fromboth on TN and KN fresh-cut banana leaves
the effect of sanitization treatment on fresh-cut[Fig.3,4].
product quality depends on the fruit or vegetable,
The surface color of fresh-cut banana leaves bothtime of exposure, and concentration of sanitizer [27].
upper and lower sides were evaluated. The L*, a*,and b* value exhibited no significant differences
CONCLUSION
among washing treatments after storage for 13 days.
Furthermore, the chlorophyll contents of fresh-cut
Sanitization with 4°C AEW for 20 minutes wasbanana leaves from each sanitizing temperature
an appropriate method to sanitized fresh-cut banana
exhibited no significant differences after storage forleaves for both cultivars. The treatment used had
13 days [table1, 2]. Therefore, the temperatures ofleast effect on the appearance quality of fresh-cut
the sanitizers had no effect on the color changes andbanana leaves such as weight loss, surface color andthe chlorophyll content of the fresh-cut banana
chlorophyll content after washing and storage.
leaves. This finding agreed with a previous study
Therefore, this method will be applied in sanitizingthat no significant differences in weight loss, color
process of fresh-cut banana leaves for export inand chlorophyll content were found on fresh-cut
foreign market.
banana leaves after sanitized with sanitizers [23]. In
addition, Martinez-Sanchez et al [24] reported that
ACKNOWLEDGEMENTS
sanitized rocket leaves with sanitizers before storage
did not affects the quality such as color andThis research has been support by Postharvest
200

SEE - Nagoya, Japan, Nov.12-14, 2018

Technology
Research
Institute/Postharvest
Technology Innovation Center, Chiang Mai
University and The Graduate School Chiang Mai
University, Chiang Mai, Thailand., Science
Achievement Scholarship of Thailand.

Microbiology, vol. 132, Issue 2–3, 2009, pp.
134–140.
[10] Rico D., Martin-Diana A.B., Barat J.M. andBarry-Ryan C., Extending and measuring thequality of fresh-cut fruit and vegetables: A
review, Trends in Food Science & Technology,
vol. 18, Issue 7, 2007, pp. 373–386.
[11] Cadwell K.N., Adler B.B., Anderson G.L.,
Williams P.L. and Beuchat L.R., Ingestion of
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sanitizers,
AppliedEnvironmental
Microbiology, vol. 69, 2003, pp. 4103–4110.
[12] Rodgers S.L., Cash J.N., Siddiq M. and Ryser
E.T., A comparison of different chemical
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67, 2004, pp. 721–731.
[13] Issa-Zacharia A., Kamitani Y., Miwa N.,
Muhimbula H. and Iwasaki K., Application ofslightly acidic electrolyzed water as a potential;
non-thermal food sanitizer for decontaminationof fresh ready-to-eat vegetables and sprouts,
Food Control, vol. 22, 2011, pp. 601-607.
[14] Tomas-Callejas A., Martinnez-Hernadez G.B.,
Artes F., Artes-Hernadez F., Neutral and acidic
electrolyzed water as emergent sanitizer for
fresh-cut mizuna baby leaves, Postharvest
Biology and Technology, vol. 59, 2011, pp.
298-306.
[15] Witham F.H., Blaydes D.F. and Devlin R.M.,
Experiment in Plant Physiology. D. Van
Nostrand Company, NY., 1971.
[16] FDA, Food and drugs administration, Center fir
Food Safety and Applied Nutrition, Draft final
guidance for industry: guide to minimize foodsafety hazards for fresh-cut fruits andvegetables, 2007, pp.11364-11368.
[17] Ding T., Rahman S.M.E., Oh D.H., Inhibitory
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on oyster mushroom, Food Control, vol. 22,
2011, pp. 318-322.
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acidic electrolyzed water on fresh-cut cabbage,
Food Control, vol. 20, 2009, pp. 294-297.
[19] Beltran D., Selma M.V., Tudela J.A., Gil M.I.,
Effect of difference sanitizers on microbial andsensory quality of fresh-cut potato strips stored
under modified atmosphere or vacuum
packaging, Postharvest Biology Technology,
vol. 37, 2005, pp. 37-46.
[20] Lopez-Galvez F., Allende A., Selma M.V. and
Gil M.I., Prevention of Escherichia coli.crosscontaminationbydifferent
commercial

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Bakhara C.K. and Panda M.K., Evaluation ofphysic-chemical changes of fresh-cut unripe
papaya during storage, Food packing and shelf
life international, 2014, pp. 190-197.
[2] Watada A.E., Ko N.P. and Minott, D.A., Factors
affecting quality of fresh-cut horticultural
products, Postharvest Biology and Technology,
vol. 9, 1996, pp. 115-125.
[3] Montero-Calderón M., Rojas-Graü M.A. andMartín-Belloso O.. Effect of packaging
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[4] Hyun J.E., Bae Y. M., Yoon J.H. and Lee S.Y.,
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[5] Liao L.B., Chen W.M., Xiao X.M., The
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[6] Rico D., Martín-Diana A., Barry-Ryan C., FríasJ., Henehan G., Barat J.M., Use of neutralelectrolyzed
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Technologies, vol. 20, 2013, pp. 1-15.
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202

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov. 12-14, 2018, ISBN: 978-4-909106018 C3051

ESTIMATION OF AMMONIUM SOURCESIN ALLUVIAL GROUNDWATER USING Cl- AND GIS:A CASE STUDY OF INDRAMAYU CITY, INDONESIA*Anna RUSYDI14, Mitsuyo SAITO2, Seiichiro IOKA3, Rizka MARIA4, Shin-ichi ONODERA1
1

Graduate School of Integrated Arts and Sciences, Hiroshima University, Japan; 2Graduate School ofEnvironmental and Life Sciences, Okayama University, Japan; 3Research Institute for Sustainable Energy,
Hirosaki University, Japan; 4 Research Center for Geotechnology, Indonesian Institute of Sciences, Indonesia

ABSTRACTThe aim of this study was to evaluate the sources of ammonium (NH4+) in a groundwater of coastal alluvial
plain in Indonesia, using both chemical properties and geographic information. The study site was Indramayu,
a developing rural area located in the northern part of West Java. The site is an ideal location for studying theimpacts on groundwater during the initial stages of urbanization. In August 2017, 20 groundwater and riverwater samples were collected from sites representative of various types of land-use. The chloride (Cl-)
concentration in the samples ranged from 15 ppm to 12,000 ppm. These concentrations represented freshbrackish to brackish-salt water conditions, indicating the influence of seawater on the groundwater samples.
Furthermore, analysis of several nitrogen species identified high NH4+ concentrations in the samples. Based on
the relationship between Cl- and NH4+, samples were clustered into three groups. The first and second groups
exhibited linear correlations, while in the third group, no relationship between these two parameters was
identified. The land-use associated with each group was then evaluated. The main NH4+ source in the firstgroup was identified as organic sediment, where NH4+ may be released through ion exchange with sodium,
facilitated by the high salinity conditions and potentially, from dissimilatory nitrate reduction to ammonium(DNRA) reactions. The source of NH4+ in the second group was suggested to be a combination of sediment,
fertilizer, and human and animal waste. Finally, it was hypothesized that the source of NH4+ in the third groupis mainly human waste.
Keywords: groundwater, alluvial plain, chloride, ammonium, land-use

1. INTRODUCTION
Groundwater is the largest unfrozen freshwater
resource on earth, with a total volume of
approximately 11 million km3 [1]. This highly
valuable resource could be used as drinking water forat least 50% of the world’s population [2]. Despite
this, unsustainable groundwater abstraction has led toa global groundwater depletion problem [1], [3]–[4].
Groundwater depletion can have knock-on effects,
which are usually complex and dependent on thecondition of the aquifer [1]. The direct effect, adecrease in the water table, can lead to serious issues,
such as land subsidence and groundwatercontamination. Such problems are already occurringin Indonesia. According to UNESCO [3], Indonesia
is one of the top ten groundwater abstracting
countries, with an abstraction rate of 14 km3/year; thisis predicted to increase by 1–2% annually [3].
Recently, these groundwater depletion effects
have been increasingly observed in Indonesiancoastal alluvial plains. An aquifer in alluvial plain has
a large groundwater storage capacity, and thus forms

the main source of clean water for many developing
cities. Thus, urbanization is one of the major triggers
of groundwater contamination in these environments[5]-[6]. Jakarta and Semarang are examples ofIndonesian coastal alluvial plain cities facing
groundwater perturbation and nitrogen species
contamination because of urbanization. For example,
in Jakarta, extensive groundwater depletion has
caused land-subsidence [7]-[8], shallow and deep
groundwater mixing, seawater intrusion, and nitrogencontamination [5], [9]–[10]. Similarly, groundwater
abstraction in Semarang has also resulted in landsubsidence [11], seawater intrusion, and nitratecontamination [12].
In this study, an investigation of groundwater in acoastal alluvial plain located in Indramayu, Indonesia,
which can be found in the northern part of West Java
(Fig. 1), was conducted. Indramayu is currently arural area, but has a potential to become urbanized in
the future. Unlike the big cities of Jakarta andSemarang, human environmental impact is not
significant in Indramayu. This relatively pristinecondition is ideal for studying the nature of the203

SEE - Nagoya, Japan, Nov. 12-14, 2018

groundwater environment during the early stages ofurbanization.
In this study, the nitrogen concentration in the
groundwater, particularly ammonium (NH4+), wasstudied. Furthermore, NH4+ source apportionment is
attempted by evaluating the relationship between
NH4+ and chloride (Cl-) concentrations, in addition toan assessment of land-use.

2.1.2

Land-uses

Land-use in the Indramayu area is depicted in Fig.
2. The dominant land-use types are paddy fields andbrackish fishponds. Settlements are concentrated on
the delta formation, next to Cimanuk River. Oil andgas operations are also present, as this is the mainindustry located in the northeastern region of Java.
This industry is owned by the Indonesian government.

2. METHODS
2.1 Study area
The study site was located in the eastern part ofIndramayu, on the north Coast of Java (Fig. 1). The
total area of Indramayu is approximately 2,100 km2,
with a coastline length of about 147 km [13]. The
topography of the area is low land to shore, with anaverage slope of 0-2%. The area has a tropical climate,with an average annual rainfall of 2,146 mm/year.
2.1.1 Geology
The Indramayu coast is a river delta, formed by
sedimentation processes fed by the Cimanuk River[14]. Generally, Indramayu soil was formed from analluvial plain environment, but also includes deposits
from beach ridge, coastal, deltaic, and floodplain
environments, along with the erosion of tuffaceous
sandstone and conglomerate (Fig. 1).

Fig. 2 Land-use types of Indramayu and sampling
locations.

2.2 Sample collection
A total of 20 samples were collected fromunconfined groundwater aquifers (18 samples) andthe Cimanuk River (2 samples), in August 2017 (Fig.
2). Sampling locations were selected to represent thedominant land-use types in Indramayu area. The field
campaign took place during the dry season with
rainfall amounts between 20 – 50 mm.
2.3

Parameter and chemical analysis

This study focuses on the analysis of nitrogenspecies, including nitrate (NO3-), nitrite (NO2-), andammonium (NH4+), in addition to chloride (Cl-).
Initially, samples were filtered through a 0.2 µm
cellulose ester membrane filter and stored in a freeze
condition until analysis. The concentrations of
nitrogen species were determined with a continuousflow automated nutrient analyzer and Cl- wasquantified with ion chromatography.

Fig. 1 Geology of Indramayu.
Alluvial plain is the dominant geologic formation in
the area, with a groundwater water level ofapproximately 0.4 m to 3.2 m [15] and unconfinedgroundwater reserves of approximately 370 L/s [16].
The alluvial plain groundwater is also highly
vulnerable to contamination.

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SEE - Nagoya, Japan, Nov. 12-14, 2018

NO3-. In contrast, groundwater analysis of samples
fromIndramayu,
exhibitedhigherNH4+
concentrations in comparison to NO3 (Fig. 4). The
concentration of NH4+ fell between < 0.01 – 11 ppm
and was detected at the majority of sites, while NO3could only dominant at two sites. The presence ofhigh NH4+-N indicates the presence of human andanimal wastes, and agricultural influences, such as
fertilizer [23]-[25].

3. RESULTS AND DISCUSSION
3.1 Chloride and nitrogen species
3.1.1 Chloride concentration
The groundwater Cl- concentrations varied from15 ppm to 12,000 ppm. Using the Stuyfzand
classification [17], the groundwater samples can beclassified as fresh, fresh-brackish, brackish, brackishsalt, and salt water based on Cl- concentration (Fig.
3). Freshwater was mainly identified in the settlement
areas, while other classifications were identified inpaddy fields and brackish fishpond areas. Samples
with high Cl- (> 150 ppm) were dominant over low
Cl- (<150 ppm).
108°10'0"E

108°20'0"EClassification based on Cl- (ppm)(Stuyfzand, 1986)
Fresh : < 150 ppm
Fresh - Brackish : 150 - 300
Brackish : 300 - 1,000

3Brackish salt : 1,000 - 10,000´
Kilometers

6°20'0"S

6°20'0"S

Salt : >10,000

As shown in Fig. 4, relatively high concentrationsof NH4+-N were not only found in the settlement andpaddy field areas, but also in the brackish fishpond.
Therefore, another source of NH4+ other than humanand animal wastes and fertilizer is suspected.

6°30'0"S

6°30'0"S

Fig. 4 Nitrogen species percentage at eachsampling point.

108°10'0"E

108°20'0"E

Fig. 3 Cl- classification distribution.

3.1.3 Ammonium sources based on chloride
distribution and land-uses evaluation

Cl- is ubiquitous in water and is relatively stable
to chemical reactions. Therefore, Cl- is usually used
as a tracer to help evaluate water quality and chemical
reactions occurring in aquatic environment. There areseveral natural sources of Cl- in the freshwater
environment, including the intrusion of saltwaterfrom the ocean, natural weathering of bedrock or
geologic deposits containing halite, unconsolidated
sediments and soils, saline groundwater (brines), andvolcanic activity [18]. In coastal regions, a major
source of Cl- is likely the result of saltwater intrusionfrom the ocean. Therefore, it was assumed thegroundwater associated with a coastal area in thisstudy, is heavily influenced by the seawater
intrusions, owing to the high Cl- concentrations
observed.

To evaluate the source apportionment of NH4+, it
was assumed that the non-reactive nature of Cl- alongwith land-use type variability, could be used to tracesources of NH4+ other than human and animal waste.
Fig. 5 depicts the correlation between observed NH4+
and Cl- concentrations. Based on the correlations,
underlying values can be clustered into three groups (Ⅰ–Ⅲ).

3.1.2 Nitrogen species concentrations
Recent research suggests, that nitrogencontamination poses significant risks to theenvironment [19]–[22]. According to many previous
studies [5]–[6], [23]–[24], the dominant speciation of
nitrogen contamination in groundwater worldwide is205

SEE - Nagoya, Japan, Nov. 12-14, 2018

Therefore, the source of NH4+ for samples from group
II is suggested to be from organic sediment, fertilizer,
and human and animal wastes.
Finally, group III demonstrates no relationshipbetween NH4+ and Cl- concentrations. The samples
for this group were associated with the lowest Clconcentrations (<110 ppm). The land-use typeassociated with this group is mainly settlements. It istherefore suggested, that the source of NH4+ for group
III is mainly human waste.
4. CONCLUSION+

Fig. 5 Correlation between NH4 and Cl-

In the early stages of urbanization of a coastal
alluvial plain, groundwater resources may have highconcentrations of NH4+. The source of NH4+ is not
limited to fertilizer and human and animal waste, butalso from organic sediment. Organic sediment NH4+
can be released through ion exchange reactions withsodium (Na+) under high salinity conditions, andpossibly from the dissimilatory nitrate reduction to
NH4+.

Groups I and II form linear correlations, whilegroup III shows no relationship between NH4+ and Cl.
Based on the groups formed, a land-use evaluation
was conducted to determine the possible sources of
NH4+ (Fig. 6).
108°10'0"E#*

108°20'0"EGroup I, Cl- (ppm) = <110Group II, Cl- (ppm) = 110 - 2,400^_

Group III, Cl- (ppm) = 2,400 - 12,0003´

Kilometers

5. ACKNOWLEDGMENTS
^_

^_

^_

The authors acknowledge the Graduate School ofIntegrated Arts and Sciences, Hiroshima University
and the Research Center for Geotechnology LIPI for
facilitating this research. We would also like toexpress our gratitude for the valuable comments
provided by reviewers and the editor of GEOMATE.

6°20'0"S

6°20'0"S

#
*

#
*
*
#
* #
#
*

#
*

6°30'0"S#*#*

108°10'0"E

6°30'0"S^_

6. REFERENCES[1]

Hertig W.A., and Gleeson T., Regional
strategies for the accelerating global problem ofgroundwater depletion, Nature Geoscience 5,2012, pp. 853-861.
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[6] Onodera S., Subsurface pollution in Asian

108°20'0"E

Fig. 6 Distribution of 3 groups clustered by Cl- andNH4+ concentrations
Samples in group I exhibited the largest range in
Cl- concentration and also the strongest correlation
with NH4+ concentrations (R2 = 0.99). Group I
samples are mainly located in the brackish fishpond,with the exception of a single point is located in apaddy field area. This point has a much higher Clconcentration (2,470 ppm) compared to other points
located in paddy field areas. We therefore suggest that
the NH4+ associated with group I is mainly derived
from organic sediment, where NH4+ ion exchangewith sodium (Na+) could be facilitated under the highsalinity conditions, and possibly from dissimilatory
nitrate reduction to ammonium (DNRA) reactions[26].
Group II also produced a strong correlation
between NH4+ and Cl- concentrations (R2 = 0.97). The
concentration of Cl- ranged from 1,100 and 2,400
ppm. The land-use type associated with this group is
more varied than other two groups, and include
brackish fishpond, paddy field, and settlement.
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SEE - Nagoya, Japan, Nov. 12-14, 2018

Megacities, for Chapter in a Book: Groundwaterand subsurface environments: Human impacts in
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[7] Abidin H.Z., Andreas H., Djaja, R., DarmawanD., and Gamal M., Land subsidence
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[8] Lubis R.F., Onodera S., Onishi K., Saito M.,
Bakti H., Delinom R., and Shimizu Y.,
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2011, pp. 151 - 155.
[9] Saito M., Onodera S., Umezawa Y., Hosono T.,
Shimizu Y., Delinom M., Lubis R.F., andTaniguchi M., Transport and transformation ofchemical components in the groundwater flow
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[10] Delinom R.M., and Taniguchi M., Ancaman
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[11] Abidin H.Z., Andreas H., Gumilar I., Sidiq T.P.,
and Fukuda Y., Land subsidence in coastal cityof Semarang (Indonesia): Characteristics,
impacts, and causes. Geomatics, Natural
Hazards and Risk, Vol. 4, Issue 3, 2013, pp. 226– 240.
[12] Sudaryanto M., and Wibawa Y.S., Sejarah
perkembangan Kota Semarang (Jawa Tengah)
di masa lalu dan dampak kehadiran polutan
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[14] Yuanita N., and Tingsanchali T., Developmentof a river delta: a case study of Cimanuk rivermouth, Indonesia. Hydrological Processes, Vol.
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[15] Rusydi A.F., Maria R., and Sudaryanto M., The
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[16] Saputra S.F., Perhitungan potensi air tanah di
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[17] Stuyfzand P.J., A new hydrochemicalclassification of water types with examples ofapplication to The Netherlands. H20, Issue 19,
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Chloride in groundwater and surface water inareas underlain by the glacial aquifer system,
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Tayasu I., Nagata T., and Taniguchi M.,
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207

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ESTIMATION OF SEDIMENTATION RATE AND FRESH-SALINEENVIRONMENT IN A COASTAL ALLUVIAL PLAIN, USING BORINGCORES OF ALLUVIUM IN THE CENTRAL PART AREA OF SETO
INLAND SEA, JAPAN.

1

Tohru Takeuchi 1, Shin-ichi Onodera 2, Kazuhiro Yamaguchi3 and Koiti Kitaoka3
Fujita Geology co. Ltd., 2 Hiroshima University, 3Okayama University of Science

ABSTRACTTo estimate the sedimentary environment between the last glacial stage and the Holocene epoch of an
enclosed sea in the Okayama Plain, which constitutes a portion of the Seto Inland Sea coast, we collected 4boring cores at depths of 6 to 19 m, performed radiocarbon dating of the organic matter contained in the clay,
identified the volcanic glass from the Aira Caldera eruption, and measured the electrical conductivity of the porewater. Based on these dating analyses, it was evident that the Holocene clay layer that is widely distributed
throughout the Okayama Plain had already accumulated prior to 10,000 years ago. In addition, the different
hardness and the presence of Aira volcanic ash in the clay layer indicated the sedimentation since Pleistocene.
Because the sea level at the time was lower than this clay sedimentation level, those facts suggest freshwaterlakes existed in the Okayama Plain which was dammed up by the shallower granite basement in the mouth of
Kojima Bay. Based on the long clay core and date for the last 30,000 years, the sedimentation rates were
estimated to be 0.18 mm/ year before 8,100 years ago and 1.19 mm/year for the last 8,100 years, respectively. In
the sea water rising after 7,000 years ago, the sea level exceeded the dam and the bay became saline condition.
Keywords: Holocene clay, radiocarbon dating, volcanic-ashes analysis, Sea-level change

INTRODUCTION

environment from the land area to the sea area
(brackish water area) is recorded in the sedimentarystrata but also the clay of low permeability retains
some water of those days[1][4][5][9].
Based on the chronological values obtained at thetime of installation of the observation wells and theage determination obtained in the previous studies,
we proved that the old Lake Kojima had existed in
the Okayama Plain at the end of the Pleistocene[8].
It turned out that the deposition rate could beassumed to be unique in either age of the Pleistocene
and the Holocene by connecting measured
chronological values at each observation point. So,
we were able to estimate the time of the seawater
intrusion into the Okayama Plain and the elevationof the surface of the deposition at that time.

Various studies have revealed that the current
Seto Inland Sea, which was a land area withfreshwater lakes scattered in the Last Glacial Stage,changed to a sea area after the Holocene glacial
retreat[2][6]. Therefore, it can be said that the
sediments of the Seto Inland Sea and its coastal
areas have recorded and preserved the sedimentary
environments from the period when the area wasland through to when it was a sea or brackish water
area. This is a valuable information source forobtaining findings about environmental changes
after the Pleistocene in the southwestern region of
the Japanese Archipelago as well as in the Seto
Inland Sea region.
Land water brought by rainfall flows out into the
Seto Inland Sea in the form of river water orgroundwater and plays an important role incharacterizing the water quality as a part of the water
source in the closed sea area. It is clear that
sedimentary strata in the coastal area with low water
permeability lowers the velocity of the passage ofgroundwater but affects not only the quality of theriver water and groundwater but also that of thewater in the closed sea area [3]. The current coastal
zone, where the land and the sea area are in contact,
has continued to be a water passage area in the water
circulation from the ancient times. So, there is apossibility that not only the transition of sedimentary

ANALYSISOUTLINE OF ANALSISs
In order for fine grain particles from rivers to bedeposited as sediment, water zones with low flow
velocities such as lakes and seas are necessary.
Sedimentation process is different depending onwhether freshwater or seawater is in the water area,
and in the water area where river water encountersseawater, the particles floating until then are more
likely to aggregate and precipitate. Agglomeration
occurs because the thickness of the electric double
layer around the particle decreases in the208SEE - Nagoya, Japan, Nov.12-14, 2018

concentrated solution and the particles tend tocollide and coalesce and the size of the clusteredparticles increases. Therefore, the rate of
sedimentation varies depending on whether theprocess is in fresh water or in sea water.
The transition from the Pleistocene to the
Holocene is generally supposed to have begun withthe seawater intrusion into land area due to the risein sea level caused by global warming after the Last
Glacial Stage[2].
It is presumed that the difference in thesedimentation rate before and after the seawater
intrusion has been recorded and preserved in theformation.

Number
GaK-5784

34.60

Nakasange
No.4
Hachihama

34.55

Nadasaki
Mizushima

34.50
Seto Inland Sea

34.45

133.70 133.75 133.80 133.85 133.90 133.95 134.00 134.05 134.10

longitude (deg)IAAA-90201
IAAA-90202
IAAA-90203
IAAA-90204
IAAA-90205
AhsType
K-Ah
AT

Well

Depth

Elevation

Libby Age

No.

(m)

(m)

(yr B.P.)(cal B.P.)

6.60- 6.70

- 2.72 ~ - 2.82

6,560±40

7,510 - 7,420

8.60- 8.70

- 4.72 ~ - 4.82

9,100±40

10,300 - 10,200

5.60- 5.70

- 3.05 ~ - 3.15

5,620±40

6,480 - 6,310

8.00- 8.10

- 5.45 ~ - 5.55

7,600±40

8,460 - 8,350

5.00- 5.10

- 3.67 ~ - 3.77

2,240±30

2,270 - 2,160

13.00-13.10 -11.67 ~ -11.77

8,270±40

9,420 - 9,130

No.2
No.3
No.4

Depth

Elevation

Libby Age

Calibrated Age

No.

(m)

(m)

(yrBP)(calBP)

11.6-10.27

6,300

7,300

14.5

-13.17-23.424900+3450-2450

28,80822,390 - 35,225

-14.7
-15.9
-11.8
-14.3
1.8
-1.2
-17
0.7
0.1
0

10,500±125
29,000±720
8,150±90
21,100±410
2,670±70
19,270±220
8,230±40
2,790±110
6,220±95
3,820±40

12,33633,242
9,130
25,212
2,828
22,975
9,189
2,976
7,104
4,229

12,021 - 12,650
31,685 - 34,799
8,927 - 9,332
24,125 - 26,298
2,700 - 2,956
22,385 - 23,564
9,070 - 9,308
2,730 - 3,221
6,881 - 7,327
4,140 - 4,317

literature
Right bank of Asahi River

0
-5
-10
-15

-20
-25
10,000 20,000 30,000
Measured Age (a, B.P.)

40,000

It is clear that not only the Holocene but the
Pleistocene is also included in the sedimentary layerof the Okayama Plain, as the samples cover therange period of 2,000 to 30,000 calibrated BP.
Therefore, sediments before and after the seawater
intrusion are mixed in the measurement samples.

Calibrated Age

Well

No.4

TuchidaCalibrated Age(calBP)
8,876
8,311 - 9,441

Fig. 2 Relation between age value and altitude

Tabl.1 Radioactive carbon dating result of 2008
and age of volcanic ash

IAAA-90200

No Data0

Fig.1 Position diagram of dating measurement
sampling

NumberFujitaLibby Age(yrBP)
7,920±2505No.3
FujitaNo Data

Elevation of core sample (m, a.s.l.)latitude (deg)No.2

Hachihama

Elevation
(m)
-14.5

Fig. 2 shows the relationship between theelevation of the sampling points and the measured
ages. As a whole, although the samples obtained at
the lower elevation tend to be older, the correlation
between the data does not appear to be high. The
low correlation is presumed to be mainly due to thefact that the elevation of the sedimentary surfaces
varies depending on the location, even if their ages
are identical.

literature
Asahi R.
Right bank of Asahi River
Minamikata
Tsuchida

34.65

No Data

Beta-168007 Mizushima
No Data Nakasange
KN-89028 Nakasange
No Data Minamigata

By means of radiocarbon dating and identificationof volcanic glass, eight sets of data of chronologicalvalues were obtained from cores collected from theright bank of the Asahi river (Tabl.1)[8]. In addition,
12 sets of data were obtained from the materials of
the previous studies in the Okayama Plain(Tabl.2)[7]. The points where the chronologicalvalues were obtained are shown in Fig.1.

34.70

Nadasaki

GaK-5786

MATERIALS FOR ANALYSIS

34.75

Place

ANALYSIS METHOD
The elevation distribution of the chronologicalmeasurement is considered to include the event ofseawater intrusion and the amount of fine particles
in the river water can be influenced by the weather
and hydrological conditions of the upstream area.
However, it is presumed that no significant changes
will occur in the long-term average hydrologicalclimate of the catchment basin, so we can assume

24,000~25,000 26,000~29,000

Tabl.2 Radioactive carbon dating result by pastrecord of Okayama plain
209

SEE - Nagoya, Japan, Nov.12-14, 2018that the amount of fine grain soil particles
transported from the upstream is almost invariant.
Therefore, the sedimentation rate of the lake bottom
is largely dependent on whether the lake water isfresh water or brackish water. For the sake of
convenience, we call the point at which seawater
intrusion occurred the “transition year” and the
hypotheses for analysis are set as follows.
1. The sedimentation rate is unique for
either period (the Holocene and the
Pleistocene) before and after thetransition year.
2. The relationship between elevation andage at a sampling site can be represented
by two straight lines with different
inclinations before and after thetransition year.
3. In order to correlate geographicallywidespread data, it is assumed that there
was a lake vast enough to include thesampling sites.
4. The sedimentation rate was identicalover the most area in the vast lake.
By making the above assumptions, mutual parallel
relationships between elevations and ages areformed among points of different elevation of
sedimentary level (at the lake bottom). This meansthat we can arrange all the data on a single straightline by shifting the elevation of the sample at eachpoint upward or downward. By applying the leastsquares method, a regression line representing the
average elevation of the sedimentation surface foreach point is obtained, and the sedimentation rate
and the shift amount for each point can also be
estimated.
When the material covers the periods both before
and after the transition year, two regression lines
with different inclinations are required. In that case,the intersection of the two straight lines represents
the transition year and the average elevation of thesedimentation surface at that time.
First, we consider the case where all the material
is from the Holocene. With the shift amount(adjustment amount) for each observation well as aparameter, we estimate the value of this parameterso that the entire line becomes a single straight line.
Therefore, the regression line is set to y=ax+b, andthe coefficients a and b are also included in theparameters and are also estimated. Here, y represents
the average elevation of the sedimentary surface (atlake bottom) when set to a single straight line, whilex represents the measured age of the material, and a
represents the average sedimentation rate.
We will name the measured elevation of eachmaterial to which shift amount has been added the"adjusted elevation". This method is aimed to obtaina regression line between adjusted elevation andmeasured age. In other words, we can obtain theshift amount at each point and the most probablevalue of the coefficients of the regression line thatwould minimize the mean square deviation from theregression line of the adjusted elevation of eachmaterial. Once the coefficients of the regression line
and the shift amount for each point are obtained, theshift amount for each point is subtracted from theregression line. Also, the elevation of thesedimentary surface at x, a certain point of time(age), can be obtained by subtracting the shift
amount from y, the adjusted elevation calculatedwith the regression line y=ax+b.
In the same way, we assume that the regression
line y=cx+d and the shift amount at each point arealso obtained in the Pleistocene stratum, too. Here,the coefficient c represents the sedimentation rate of
the Pleistocene.
When applying the least-squares method, an
initial value is given to the transition year, whilesamples from the ages later than the transition year
are to be assumed as those of the Holocene layers,
and older samples are to be assumed as those ofPleistocene layers. Then, we obtain the optimal
parameters that would minimize the mean squaredeviation by giving some initial value to theelevation shift amount for each point and to theparameters of the coefficients of the two regression
lines.
The x-coordinate of the intersection of the twostraight lines thus obtained is called the “crossovertransition year”. When the crossover transition year
obtained deviates from the initial value of thetransition year, the optimum value is to be recalculated with this crossover transition year as a
new initial value. By repeating this process, the final
optimum value can be obtained.
RESULTS AND DISCUSSION
The optimum value 8,078 calibrated BP of thecrossover transition year obtained by means ofregression with two straight lines of the Holocene
and Pleistocene is shown (Fig. 3).
The decor relation of the data is remarkable, andthe mean square deviation around the regression line,of which the range is indicated with the dotted line, islarge. Estimated deviation of the transition year is ±1, 200 years. This significant deviation is presumed
to be due to radiocarbon dating performed indifferent ways.
Analyses only on the basis of the material fromthe right bank of the Asahi river show that thetransition year was 8,100 calibrated BP, which isfairly accurate with the deviation only ± 0.003 years.
The deviation of the elevation (y-coordinate) in thetransition year, which is the intersection of the twostraight lines, is 0.005 mm.

210

SEE - Nagoya, Japan, Nov.12-14, 2018

4
2
0Adjusted elevation (m a.s.l.)

We found out that, given the condition that the
sedimentation rate was unique either in the Holoceneor Pleistocene era, the chronological data could bearranged on a single straight line by shifting theelevation of the observation points upward or
downward in either of the periods. By doing so, thechronological data of sediments obtained bymeasurements at different locations were related toeach other, andIt was possible to estimate that the sedimentation
rate was almost unique over a vast area at either ofthe periods.
1. It was possible to estimate the average of
sedimentation rate either in the Holocene orPleistocene.
2. It was possible to estimate the time of seawater
intrusion from the point of intersection of thetwo straight lines.
3. It was possible to estimate the elevation of thesedimentary surface when the seawater
intrusion occurred at each observation well.

Pleistocene
Holocenereg. in Pleistoocene
reg. in Holocene

8078 B.P.

-2
-4
-6
-8
-10
-12
-14

0

10,000 20,000 30,000
Measured age (a b.p.)

40,000

Fig.3 Relationship between adjusted altitude andAs a result, seawater intrusion into the Okayama
Plain is considered to have occurred in 8,100
calibrated BP with the elevation of the sedimentarysurface 8.89 meters below sea level. The
sedimentation rate proved to have been 1.19 mm/y in
the Holocene, and 0.18 mm/y in the Pleistocene.

measured age

It is noteworthy that the transition year 8,080 ±
1,200 calibrated BP obtained from wide areasamples and the transition year 8,100 ± 0.003
calibrated BP obtained from the samples along the
Asahi river have high identity in terms of the meanvalue. This suggests that the assumption of theunique sedimentation rate applied in this method is
not so far from reality.
The sedimentation rate observed in the entire
Okayama Plain is 1.0±0.2 mm/y in the Holocene,
and 0.18±0.05 mm/y in the Pleistocene stratum,
which are considered to be the average value
observed in the vast area of the Okayama Plain.
Thus, it appears to be clear under certain
assumptions that the seawater intrusion into the
Okayama Plain occurred in 8,100 calibrated BP,
while the sedimentation surface at the transition year
can be described as 8.89 meters below sea level.
Therefore, it is generally considered that if there
are about ten chronological materials available
including those of the Holocene and Pleistocene,accurate estimation of the transition year will bemade possible by means of this method.
On the basis of the distribution of Jomon ruins,
we can estimate that the surface of the brackish lake
formed after the seawater intrusion was several
meters higher than the current sea level. It isconsidered that the alluvial clay layer of the
Okayama Plain developed in the warm weather ofthis Jomon Transgression.

REFERENCES
2

3

4

5

6

CONCLUDING REMARKS
7

211

F. Larsen, L.V. Tran, H. Van. Hoang,
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Masuda, F. Miyahara, B. Hirotsu, J.
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Masuda, H.: The future of urban water
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Quaternary evolution of a large alluvial fan in aperiglacial setting (Crau Plain, SE France)
constrained by terrestrial cosmogenic nuclide(10Be). Geomorphology, 195, 2013, pp. 45-52.
Piovan, S., Mozzi, P., Zecchin, M.: Theinterplay between adjacent Adige and Po
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Shimada, J.: Water beneath the sea
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9(The Association for the Environmental
Conservation of The Seto Inland Sea), 43, 2005,
pp. 22-27.
Suzuki, S.:Relative sea-level changes of
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Takeuchi, T. Kitaoka, K. Yamaguchi, K.
Onodera, S.: Formation process of the Holocene
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enclosed sea: case study of the Okayama Plain.
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Wild, M., Cochrane, T., Davies, T.,
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212

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

IMMEDIATE EFFECTIVENESS OF HERBAL STEAM ON CERVICALRANGE OF MOTION WITH STRESS IN THE ELDERLY
Chamiporn Kongmong1, Peerada Damapong2 and Pongmada Damapong3
College of Allied Health Science Suan Sunandha Rajabhat University, Bangkok 10300, Thailand

1,2,3

ABSTRACT
Stress is one of the common psychological problems. This study aimed to evaluate the effects oftheHerbal Steam on cervical range of motion with reduce stress in the elderly. The data was compiled using
the quasi-experimental research design; the populations of this research were 30 patients with stress inthe elderly, the assessment was before and after receiving 30-minute of Herbal Steam. The results were assessed
immediately after the intervention which consisted of the increased cervical range of motion after receiving the
Herbal Steam while a significant difference was occurring (P < 0.05). In conclusion, the effectiveness of Herbal
Steam will reduce stress in the elderly by reducing its pain and increase the cervical range of motion.
Keywords: Immediate Effectiveness, Cervical Range of Motion, Herbal Steam, Stress, The elderly

It is still used today. Herbal Steam It is used forheat therapy. Traditional herbal steam is used inwomen. The new baby, which will have hot baths.
Drink hot water with boiled water. And lay a fire on
bamboo lined with herbs, but now has developed.
Sauna Heater Thai people in traditional medicine use
herbal steam over the sauna. it has herbs that help
the airway. Skin care or treatment. types of Herbal
Steam Herbal Steam 1) Drying is a traditional
method of cooking. There are rituals that maintainmorale. For mothers after birth Herbal bath andturmeric treatment to maintain inflammation in theskin and is popular after birth with fire on the litter,warm wood to the body will help stimulate theuterus contraction. 2) Wetting is one of thetreatments. The beginning of the tent of the woman
after birth. Using cloth to make a tent covered withboiled herbal boiling pot. Bake and smoke steam.
Nowadays, this method has been developed to suitthe present society by creating a modern herbal
steam room [3], [4].
The composition of herbs used may vary bypurpose. To treat such symptoms as refreshing thebody. Skin shine Helps to sweat, relieve stress.
Relaxation and tightness of the joints and pain in thecurrent medical conditions have accepted that heat
treatment can help blood circulation. The vapor ofherbs will have properties according to theproperties of the herb, which in most cases helps the
body freshen up. [3], [4].
In consequence, the researcher is interested in theuse of traditional herbal medicine. Take care ofstress problems of the elderly. To reduce the stressthat is the cause of other diseases followed.

INTRODUCTION
Stress is a mental health problem that can happen
to the general public. Stress is a reaction. The
response of the body, mind, thoughts and behaviorof the person to the inner and outer vesicles, which
may be person, the feeling. Situation or environment
The person will recognize that the pressure isthreatening and the uncontrolled cave will make theperson stress. This may result in a disproportionate
loss of life. Stress is a barrier and the problem thatmany people in many age to meet on a daily basis.
Whether it comes fromwork. Personal life
problems And especially the money. And the older
the elderly. It is very easy to face stress. Start by
yourself. The body began to regress. With thedisease that comes to arouse discomfort, physicaland mental stress. In addition, the external
environment is not good, such as the elderly awayfrom their children. Some people are alone, it causes
more stress. It also causes depression as well. Thechanges in the elderly population in Thai society
have shown that the proliferation of chronic diseases
and disability has led to an increase in the elderly isdependence and increased need for care. And care in
the service [1].
The current state of problems and conditions,although the knowledge of medical science hasadvanced. And is widely accepted in the care. But
still find that. The health care and maintenance. For
the elderly there is a distinction of the traditional
way of life in Thailand. Especially the rural elderly
who have a culture of faith and lifestyle that is
linked to the path of nature. This is different fromthe people in the city. Health care behaviors of rural
people are characterized by social stereotypes. And
that culture has been instilled and transferredknowledge to maintain their own health. In the formof local wisdom (Local wisdom)213

SEE - Nagoya, Japan, Nov.12-14, 2018

MATERIALS AND METHODSRESULTS
DesignThe findings of the general information of 30
sample revealed that; most of them were female(80.00%), most of the marital status was married(80.00%) and most of have a farming career(40.00%).
The assessment of the cervical range of motion;
cervical flexion, cervical extension, cervical leftlateral flexion, cervical right lateral flexion before
and after the Herbal steam immediately revealed thatthe immediate cervical range of motion wasincreased with 0.95 level of significance (P <0.05)(Table 1).

This research was the quasi-experimental
research design which the cervical range of motion
assessment was conducted in the public healthcenter, Phakdi Chumphon District, Chaiyaphum
Province, Thailand. This study was approved by
Ethics Review Committee Sirindhorn College of
Public Health Khon kaen (HE NO.610660)
Subjects
The sample used in this study is Elderly people
over 60 years old 30 people with stress. the elderly
have moderate stress.

Table 1 Comparison of the outcome measures
between baseline (pre-test) and post-test
assessments in Cervical range of motion(degree) (paired t-tests).

Assessment
This research was the cervical range of motion
assessment, the questionnaires and Perceived Stress
Scale.

Cervicalflexion±53.509.39

Immediate(Mean ±
SD)
±58.83
8.57

Cervicalextension(%); mean ±SD±54.5010.28±60.339.99<0.05

Cervicalleft lateral
flexion±38.668.29±44.337.84<0.05

Cervicalright lateral
flexion;mean± SD

±34.337.27±42.669.07<0.05

Outcome

Measurement Instruments
In this research, The instruments used in theexperiment were 2 parts: A screening test to screen
elderly people with stress. Three levels of stress,
low, moderate and high, Recorded results aremoderate.Additionally, the Cervical Range Of
Motion (CROM) was used to assess the cervicalrange of motion; cervical flexion, cervical extension,
cervical left lateral flexion, cervical right lateral
flexion, will measure before healing herbs. And after
measure herbal immediately. and the results wererecorded as degree.

Baseline

Pvalue
<0.05

Note:

Intervention
The samples were treated by getting 15-minuteof Herbal steam.

DISCUSSION

Statistical Analysis

This research was aimed to evaluate the effects
of Herbal Steam on cervical range of motion with
reduce stress in the elderly. The findings of theimmediate cervical range of motion assessment weredifferent in each motion with 0.95 level ofsignificance ( P < 0.05). In consequence, it wasdifferent in the clinical significance that the sample
were treated Herbal Steam.

In this research, descriptive statistics were used
to describe the characteristics of the sample. meanand standard deviation It also uses a pair t-test to
analyze the variables negatively by analyzing theimmediate effect of the evaluation.

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ACKNOWLEDGEMENTS

The findings were consistent with the study of“Kitkra [2] shows 58.3% of the respondents used
the herbal steam service twice a week, 68.0% ofthem drank 2-5 times, 33.5% of them tried to keep
their body healthy. 88.0% found that herbal steam
helped to work more. 86.3% helped to sleep well
84.7% help to lighten the mobility 81.3% help tobreathe fluently 80.0% help relieve pain. Maps For
those with knee pain, knee pain, muscle aches andback pain, waist circumference 90.5 percent 82.2 .

This study was supported by Suan Sunandha
Rajabhat University, Bangkok, Thailand.
REFERENCES[1] BodhiSita, C. Science and Arts of Qualitative
Research (4th ed.). Bangkok: Amarin Printing,2009.
[2] Kitkra, J. Buddharak, S. Wattanachai, A.
Vadisai, N. Wattanapichakul, A. Herbal Steam:Health Care Options for People. Journal of
Pharmacy; 9 (1): 28, 2013.
[3] Subcharoen, P. Herbal Steam for Health. And totreat the disease. Prachinburi: Office of Public
Health Prachinburi Ministry of Public Health,
1995.
[4] Thai Traditional Herbs and Herbs Promotion
Group Thai Traditional Medicine Institute.
Traditional Thai Medicine Practice in Public
Health Facilities. 4th edition. Nonthaburi:
Department of Alternative Medicine andAlternative Medicine. Ministry of Public
Health, 2011.

CONCLUSION
Thai herbal steam results in a neck movement.
The effect of neck movement increased in all
directions from the corm measurements, which weredifferent before and after herbal steam. It can beconcluded that the herbal baking herbs haveproperties that make the muscles in all parts of the
body more flexible. Heat causes circulatory system
to work effectively. As a result, stress is reduced.

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EFFECTS OF LOW INTENSITY EXERCISES ON BODY BALANCE
AND MUSCLE STRENGTH OF COMMUNITY ELDERLY PEOPLE
Worawut Chompoopan1,3, Warangkana Chompoopan1,3, Wichai Eungpinichpong2,3, andWilai Eungpinichpong11
Sirindhorn College of Public Health, Khon Kaen, Thailand
Faculty of Associated Medical Sciences, Khon Kaen University, Khon Kaen, Thailand
3
Research Center in Back, Neck, Other Joint Pain and Human Performance, Khon Kaen University, Thailand
2

ABSTRACTThe purpose of this experimental study was to determine the effects of low-intensity group exercise on
muscle strength and balance of elderly people in the communities. Seventy-two healthy elderly people from two
communities participated in this study. Thirty-six elderly people were randomly selected and allocated into an
experimental group and control group. The experimental group performed a supervised group exercise programin every work day’s evening for three months. The exercise program began with warming up for five minutes,
followed with low-intensity exercise program, and cooling down for another five minutes. The data werecollected before and after three months of performing the exercise program. The outcome measures included
muscle strength, body balance, and fear of falling. The data were analyzed by using ANCOVA to compare
between the experimental group and the control group. After performing the exercise program for three months,
the experimental group had developed better health status than before participating the program and it wassignificantly different from the control group. The experimental participants’ muscle strength was increased by
1.79 points. Their dynamic balance periods were shorter than before receiving the exercise program by 1.32
seconds. Moreover, it was revealed that the experimental participants’ fear of falling was decreased by 17.74
points. After three months of involving in the low-intensity exercise program, their health status remained betterand healthier while the participants’ health status of the control group remained the same as the starting period.
The results revealed that the low-intensity group exercise program could improve muscle strength, body balance,
and fear of falling among elderly people.
Keywords: Exercise, Balance, Muscle strength, Elderly

health conditions in the ageing people including
injuries from falls indicate degenerative healthstatus among the older adults [4].
Falling is one of the common and major
health problems occurring in the old-age
people. In 2007, a study on falls in the ageing
people found that, within six months, thepercentage of the falls in the seniors was up to
10.3. As far as gender is concerned, theproportion of falls among female elderly people
was 12.6 percent while in the same-age maleproportion was 7.4 percent. In addition, agealso plays a part. The very senior citizens had
the highest proportion of falls at 12.7% whereas
the proportion of falls in the middle or early age
group was 11.7% and 9.2%, respectively [4].
The major physical cause associated with falls
in the elder people is a decline in muscle mass
which could result a decrease in physicalactivities. The decline in muscle mass has
always been replaced by free fat, collagen, andfibrous tissue
[5].
This
includesthedeterioration of the neuro-musculoskeletal
system, especially in lower extremities which
could also cause muscle weakness and fall inthe old-age people [6].

INTRODUCTION
The world has been becoming an aging society.
Each country where has senior citizen accounting
for over 10% of the total population can beclassified as an aging society [1]. For example,
by the year 2004, the proportion of elderly people
in Japan was the highest percentage (31%),
followed by Italy and Germany (27% and 26%
respectively) [2]. In 2007, in the Southeast Asia
region, the proportion of elderly people in
Singapore was almost equal to Thailand of which
Singapore was 11.9 while Thailand was 10.7 [3].
Not only the proportion of elderly people has
been increasing, but the seniors have also encountered an increase in age-related diseases. Around34.6 percent of people over 80 years through selfassessment were found having poor health status [3].
Naturally, people tend to get chronic healthconditions when they are getting older. For example,
high blood pressure was commonly found in theseniors at 31.7%, meanwhile, the prevalence ofdiabetes was 13.3%. Other chronic health conditions
prevalence like heart disease, paralysis, coronary
artery disease, and cancer prevalence were 7.0, 2.5,
1.6 and 0.5 percent, respectively [3]. These common
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Therefore, an exercise program to improvemuscular strength and body balance for elderly
people is crucial to prevent their health problems. A
low intensity exercise has been recommended formaintaining and improving health status in elderly
people because it has low risk and yet could
gradually let the elderly participants adapt tophysiological as well as psychological effects
resulting from the exercise training program. To
accomplish and maintain these effects, the exercise
program should be regularly performed, enjoyable,
and relevant to local culture of physical activities.
The main purpose of this study was to develop an
appropriate exercise program to improve bothmuscular strength and body balance of elderly
people living in a community.

Calf exercise
The participants stood on the feet while thehands grasp the chair back to balance the body. Thenthey raised their heels up, and put the body weighton the toes, and old in this position for 5 seconds.
Then returned to the starting position and repeated
10 times. They performed 2 sets and rested 30
seconds in between.
Sideways walking
The participants stood with their feet together,and knees slightly bent. Then, they stepped sideways
in a slow and controlled manner by moving one footto the side, then they moved the other to join it.
Repeat 10 steps each way or step from one side of
the room to the other. They repeated the movements
10 sets.

METHODS
Design and setting
A parallel two-arm, randomized control trial(RCT) was applied. The settings for intervention anddata collection were at two districts in Khon Kaen,
Thailand.

Heel to toe walk
They stood upright. Then, they placed the rightheel on the floor directly in front of the left foot.
Then they did the same with the left heel. They were
instructed to keep looking forward at all times. If
necessary, they were allowed to put their fingers
against the wall for stability. Repeated 10 steps andperformed 5 sets
Participants in the control group were suggested
to maintain their routine daily life activities
although they didn’t participate in the exercise
program.

Participants
The participants were healthy elderly people
aged 60 years and over recruited from the communities. The inclusion criteria were healthy elderly
people and have been living in the community over
one year. Participants with disability, body balance
problem, contra-indications to exercise were
excluded. Seventy-two participants who met thecriteria were randomly allocated either in the experimental or control arms by using a block randomized
method (Block of 4).

Procedure
The objectives and the study design were
described to all the participants for both theexperimental and control groups. The consent form
was read and signed at the Local Health Promoting
Hospital. The appointment was arranged right after
screening accordingly to the criteria in order toparticipate in the study and signed the informed
consent. Every participant was provided with arecording-book to sign every time he/she
participated in the exercise. The exercise program
was performed at the community meeting center inthe village where most of the elderly people
regularly came for chatting.
Outcome measures including dynamic bodybalance (timed up-and-go test), muscle strength(thirty-second chair stand test), and fear of falling(Falls Efficacy Scale) were recorded before and 3
months after participating the study. Village healthvolunteers supervised the daily group exercise
whereas Health Promoting Hospital officers
followed up to ensure the exercise program had been

Intervention
The exercise program was designed based on thecriteria which included low intensity, simple,
enjoyable, relevant to local culture, and group
participation. The components of exercise consistedof the following supervised group exercises.
Squats exercise
The instructor commanded with demonstration to
the group of participants as follows. “Stand as tall as
you can with your feet apart about shoulder-width.
Lower your body as far as you can by pushing yourhips back and bending your knees. Push yourself
back to the starting position while squeezing yourglutes. Repeat the movement 10 times, performing 2
sets. For each repetition, count to 3 on the way up
and on the way down to ensure you are not going too
fast. Then rest 30 seconds in between sets.”

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Shapiro-Wilk test was used to verify the normal
distribution of continuous variables. An intentionto-treat analysis was used for avoiding misleading
data. The data were analyzed by using Independent t-test for comparing between the experimenttal and control groups before the experiment.
After experiment data were analyzed by using
analysis of covariance (ANCOVA) for betweengroup comparison. Paired t-test was used forwithin-group comparison. Differences wereconsidered statistically significant at p < 0.05.

regularly performed. All the participants wereencouraged to regularly participate accordingly tothe study design. The researcher and research
assistants regularly visited and interviewed theparticipants.
Measurement Equipments
The timed up-and-go test (TUG) was used tomeasure the dynamic body balance purposely toassess the balance, walking ability, and fall risk ofelderly people. The participants were suggested towear their regular footwear while they were
performing the test. The procedure of TUG measurement began with the advice for each of theparticipants to sit on a chair. When the researcher
gave a signal, he/she got up and walked along thethree-meter line, then went back to the seat. The
duration of this performance was timed andrecorded.
A thirty-second chair stand was tested (30CST).
This test aimed to measure leg strength andendurance of elderly people. Each participant sat at
the middle of the chair. Place their hand on the
opposite shoulder while keeping the feet flat on thefloor, back straight, and arms against the chest. After
receiving the signal “Go” he/she stood up straight,
then sat down again. This was repeated for 30
seconds. The researcher counted the number ofcompleted rounds.
A Falls Efficacy Scale (FES) was a test
aimed to assess perception of balance andstability during activities of daily living andfear of falls among the elderly population. The
Falls Efficacy Scale was a 10-item questionnaire designed to assess confidence of theirability to perform 10 daily tasks without fallingas an indicator of how one's fear of falling
impacts physical performance. Each item was
rated from 1 ("very confident") to 10 ("notconfident at all"), and the per item ratings wereadded to generate a summary total score. Total
scores could be ranged from 10 (best possible)
to 100 (worst possible). Thus, lower scoresindicated more confidence and higher scoresindicated lack of confidence and greater fear of
falling.

RESULTS
The demographic variables based on gender,
age, income, and occupation were stratified
between the experimental and the control
groups (EX and CON). Thirty-six participants
were allocated in each group. Most of themwere female (52.78% in EX group, and 72.22%
in CON group). The average age was
70.89(5.38), and 70.58(7.03) years and theiraverage income were 2,500(3,600), and
1,000(3,025) Baht/Month for the EX and CON
respectively. Most of the participants worked
as farmers. (Table 1)
Table 1 This is the example of table formatting
Characteristics
GenderMale
Female
Age
60-69
70-79
≥80
( X±S.D.)(MIN, MAX)
Income (Baht)
500-1000
1001-1500
Over 1500( X±S.D.)(MIN-MAX)

EX
n(%)

CON
n(%)

17(47.22)
19(52.78)

10(27.78)
26(72.22)

17(47.22)
15(41.67)
4(11.11)70.89±5.38(63, 86)

18(50.00)
15(41.67)
3(8.33)70.58±7.03(60, 83)

19(52.78)
12(33.33)
5(13.89)
2500±3600
600-20000

26(72.22)
7(19.44)3(8.33)1000±3025
600-10000

27(75.00)
4(11.11)5(13.89)

26(72.22)
6(16.72)4(11.11)STATISTICAL ANALYSES

Occupation
FarmerHomework
RetireData were analyzed by using SPSS for Windows
Version 19 (IBM Corp. Released 2010, IBM SPSS
Statistics for Windows, Version 19.0. Armonk, NY:
IBM Corp.) under licensed of Khon Kaen University.

Baseline data before the intervention werecompared between the two groups and found no
significant difference in terms of body balance,
muscle strength, and fear of falling (Table 2).
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Table 2 Baseline data before the intervention ofboth groups.
Variables
Balance
Musclestrength
Fear offalling
Note: T-test

EX Group
X±S.D.
11.91±2.0712.42±2.85

CON Group
X±S.D.
12.89±4.3412.44±3.48

0.231
0.971

22.50±36.20

17.42±27.36

0.504

Table 5 After the experiment in CON group
Variablesp

Balance
Musclestrength
Fear of17.42(27.36)
falling
Note: Paired t-test

Table 3 Comparison between the two groups after 3
months of intervention.
EX Group
X±S.D.
11.28±2.01
13.94±2.80

CON Group
X±S.D.
12.60±4.4312.15±4.64p

Balance
0.002
Muscle0.006
strength
Fear of15.91±22.51 33.65±36.09 0.001
falling
Note: ANCOVA, adjusted mean using baseline ascovariate
Within-group analysis of the experimentalgroup revealed that after 3 months of participating in the exercise program, the participants
had significantly increased their body balance
and muscle strength, whereas the fear of falling
was not significantly improved (Table 4).
Table 4 Within-group analysis of the experimental
group
Variables

Baseline
X±S.D.
11.91(2.07)
12.42(2.85)

Balance
Musclestrength
Fear of22.50(36.20)
falling
Note: Paired t-test

After 3 m.
X±S.D.
10.97(2.02)
14.14(2.80)

0.004
0.001

10.33(22.51)

0.089

After 3 m.
X±S.D.
12.96(4.44)
11.94(4.64)

p
0.784
0.318

36.97(36.09)

0.010

The results showed that participating in the 3months of low-intensity exercise could significantly
improve both body balance and muscle strength.
None of the participants had shown any serious
adverse effect. These findings were in the line withthose of the previous study that employed the threemonth home based low intensity exercise for elderly
people in different settings and cultures [7]-[9]. In
the current study, the participants’ fear of falling
after 3 months of the intervention had significantly
decreased in the experimental group compared to thecontrol group. This could be due to the increase inmuscle strength of the lower extremities and bodybalance of the experimental group as a result ofparticipating in the low intensity exercise program[10].
According to the study design, this study
employed a randomized controlled trial of which
has been known as the gold standard forintervention study. This could provide the highquality of the study. However, this study hadsome limitations because the blind assessment
was not possible due to the nature of thecommunity trial. In addition, it might be possiblethat group contamination might occur since theparticipants in the control group could easily
access in the exercise group. Fortunately, thisgroup contamination did not occur since theparticipation to this exercise program was strictly
controlled by the community’s health volunteers
and the research assistants.

After 3 months of participating in the intervenetion, the experimental group had signifycantly improved in their body balance, muscle
strength, and fear of falling when compared tothe control group (Table 3).

Variables

Baseline
X±S.D.
12.87(4.34)
12.44(3.48)

p
CONCLUSION
Based on the results of this study, participation
on regular (low intensity) exercise, 5 times a week
and lasted for 3 months, may increase muscle
strength, improve the dynamic body balance andreduce fear of falling in elderly people. This kindof activity could contribute a lot to the communities
where there are a lot of elderly people in termsof health promotion, opportunities for social
gathering, having fun, more importantly low cost.
Any elderly people with any social status canperform this exercise program. Beneficially, older
people could use their leisure time worthwhile forthe rest of their lives.

Within-group analysis of the control grouprevealed that after 3 months without any
intervention, the participants had no signifycantly changed in their body balance andmuscle strength, but the fear of falling was
significantly increased from the baseline(Table5).
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[7] Arai, T., Obuchi, S., Inaba, Y., Shiba, Y., &Satake, K. (2009). The relationship between
physical condition and change in balance
functions on exercise intervention and 12-monthfollow-up in Japanese community-dwelling older
people. Arch Gerontol Geriatr, Vol. 48, Issue 1,
2009, pp. 61-66.
[8] Karabulut, M., Abe, T., Sato, Y., & Bemben, M.
G., The effects of low-intensity resistancetraining with vascular restriction on leg muscle
strength in older men. Eur J Appl Physiol, Vol.
108, Issue 1, 2010, pp. 147-155.
[9] Arai, T., Obuchi, S., Inaba, Y., Shiba, Y., &Satake, K. (2009). The relationship between
physical condition and change in balance
functions on exercise intervention and 12-monthfollow-up in Japanese community-dwelling older
people. Arch Gerontol Geriatr, Vol. 48, Issue 1,
2009, pp. 61-66.
[10] Gusi, N., Carmelo Adsuar, J., Corzo, H., Del
Pozo-Cruz, B., Olivares, P. R., & Parraca, J. A.
(2012). Balance training reduces fear of fallingand improves dynamic balance and isometricstrength in institutionalised older people: arandomised trial. [Randomized Controlled Trial
Research Support, Non-U.S. Gov't]. J
Physiother, Vol. 58, Issue 2, 2012, pp. 97-104.

ACKNOWLEDGEMENTS
This study would not have been possible
without the generous cooperation of the 72 elderly
participants, research grants from the ResearchCenter in Back, Neck, Other Joint Pain and
Human Performance (BNOJPH), Khon Kaen
University, Thailand.
REFERENCES[1] David A. Swanson. The Methods and Materials
of Demography, Second Edition, Academic
Press 2004, pp. 159.
[2] John, B., Simon, B., David, B., Linda, F., Paul,
H., Alexandre, K., & Jay, O. Global Population
Ageing: Peril or Promise?, World Economic
Forum. 2000, pp. 6.
[3] Bureau of Socio-Economic and Opinion 1,
National Statistical Office Thailand, Report on
the 2007 survey of the older persons in Thailand,
2008, pp. 35-48.
[4] Chuenta Witchawut, Review and Synthesis ofThai Elderly Knowledge. Foundation of Thai
Gerontology Research and Development Institute(TGRI), 2009, pp. 41-43.
[5] Payton, O. D., & Poland, J. L., Aging Process:Implications for Clinical Practice. Phys Ther,
Vol. 63, Issue 1, 1983, pp. 41-48.
[6] Moreland, J. D., Richardson, J. A., Goldsmith, C.
H., & Clase, C. M., Muscle weakness and falls inolder adults: a systematic review and meta‐
analysis. J Am Geriatr Soc, Vol. 52, Issue 7,
2004, pp. 1121-1129.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
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INVESTIGATION OF CATHEPSIN B (CTSB) and CATHEPSIN L(CTSL) POLYMORPHISM FOR CARCASS AND MEAT QUALITY IN
SWINE
1Doungnapa Promket1*, Kajorngiat Nabundit2, and Khanitta Ruangwittayanusorn1
Lecture of Animal science, Department of Agricultural Technology, Faculty of Technology, Mahasarakham
University, Thailand
2
Graduate student of Animal science, Department of Agricultural Technology, Faculty of Technology,
Mahasarakham University, Thailand
ABSTRACTThe objectives of the research were to evaluate genotype frequencies and to investigate polymorphismin the cathepsin B gene (CTSB) and cathepsin L gene (CTSL) with carcass and meat quality in 288 crossbreeds(large white x landrace x duroc). Pigs whose weights ranged from 78-134 kg were assigned to slaughter. PCRRFLP protocols were used to identify polymorphisms of both genes. The frequencies of AA, AC and CC
genotypes of CTSB were 0.340, 0.615, and 0.045, respectively. The frequencies of A and C alleles of CTSB were0.648 and 0.352, respectively. Regarding CTSL, the frequencies of CC, CT and TT genotypes were 0.625, 0.354,
and 0.021, respectively. The frequencies of C and T alleles of CTSL were 0.802 and 0.198, respectively. The
significant effects of CTSB polymorphism were detected on body length (BL), scan of loin eye area (U_LAE),
loin eye area (LAE), and weight loss (WL) (P<0.05). The pigs carrying the AC genotype had higher level of BL,
U_LEA and LEA than the ones carrying the homozygous genotype (AA or CC). The pigs with the CC genotypeof CTSB had lower WL (1.86 kg) than the ones carrying the AA or the AC genotype (2.19 and 1.97 kg). The
CTSL variants represented statistically significant effects on BL trait (P<0.05). The CC genotype (77.92 cm) had
higher BL value compared to the CT (76.14 cm) and the TT genotypes (76.92 cm). The CTSB and CTSL werehigh polymorphism and their alleles could be as the potential genetic markers for swine selection.
Keywords: Cathepsin B, Cathepsin L, Swine, Polymorphism

swine. The prediction meat and carcass quality ofmeasurement carried out in live pigs before
slaughter and interesting aspect for producer and forthe industry.
Marker assisted selection (MAS) is one ofthe possibilities related to breeding program. Several
studies have identified gene marker associated withthe genetic variation process through MAS that has
an increased possibility for implementation [7]. The
cathepsin genes belong to the enzyme family (CTSL,CTSB, CTSD, CTSH, CTSF and CTSZ), which are agroup of genes that produce lysosomal proteinases
and are important for the degradation of proteins.
Their main role is in the post-mortem proteolysis ofmeat. These genes or their mutations may
profoundly affect the qualitative properties of meat[8], [9]. Recent studies have shown that thepolymorphism in the cathepsinB (CTSB) andcathepsinL (CTSL) gene is associated with carcass
and meat quality traits in swine. Vera [8] has found atrend of allele T increased fatness and the effect ofallele C on lean meat in swine. The significant
results of CTSB mutation was observed for higher
carcass yield and weight of ham [9]. Moreover,
Russo [10] also found the marker identified at the
CTSB loci involved in meat quality traits. CTSL
marker shows a tendency towards back fat thickness
and weight of lean cuts [11], [12]. In the present

INTRODUCTION
The selection of pig has focused on increaseof carcass and meat quality. The carcass and meatcharacteristics, especially the back fat thickness andham weight, are economically important for the pig
industry [1]. However, making genetic progress bytraditional breeding is challenging because meat andcarcass qualities are low to moderately heritable [2],[3]. The meat and carcass quality are of complex
nature, influenced by several genes with high impact
of environmental effect [4].
Ultrasound technique has been used to
predict carcass and meat traits of live animals forseveral years. Deza [1] has found that the R2 model
between hams weight and slaughter live weight andultrasound fat thickness was 0.82. Moreover, thecorrelation between 10th rib back fat measurement
by real – time ultrasound and 10th rib back fat was
0.84 [5]. Newcom [6] has used real-time ultrasoundtechnique to predict intramuscular fat percentage inlive swine and found that the product moment
correlation and rank correlation coefficients between
predict loin intramuscular fat percentage and carcass
loin intramuscular fat percentage of Duroc
population were 0.60 and 0.56, respectively. Results
show that real-time ultrasound image analysis can beused to predict intramuscular fat percentage in live
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study, we predicted the carcass and meat quality byreal – time ultrasound that might improve theefficiency of measure methods for evaluating meat
quality on a routine basis. Thus, the objectives ofthis research are to investigate genotype of CTSB
and CTSL polymorphism and confirm theassociation between the polymorphisms and carcass
and meat quality in Thai crossbred swine. The
results from this study might improve the efficiencyof selection swine.

was added. The DNA was precipitated at 10,000rpm for 5 min at 4°C. The supernatant was
discarded, and DNA pellet was washed 2 to 3 times
with 75% ethanol. The DNA pellet was air-dried atroom temperature and dissolved in DNA hydrationbuffer. Deoxyribonucleic acid quality andconcentration were determined by UV spectroscopy.
The DNA was diluted to 50 ng/μL as a working
solution and stored at −20°C before use.
PCR –Restriction fragment length polymorphism
analysis (PCR-RFLP)

MATERIALS AND METHODS

The reactions of PCR were carried out in a total
volume of 10 µL containing: 1 μL of diluted DNA
template (50 ng/µL); 1X PCR buffer (1 μL of
10XPCR buffer), 4 mM MgCl2 (0.8 μL of 50 mM
MgCl2), 0.1 mM dNTP (1 μL of 1 mM dNTP), 0.5µM of each primer (1 μL of 5 μM of each primer),and add 0.1 μL of Taq DNA polymerase (Promega,
San Diego, CA). PCR amplification was carried out
in a PCR thermal cycle (COBETT RECHEARCH,
Australia 2003, iCycler thermal cycler, BioLad,
U.S.A) using the following amplifying program:preheating at 95˚C for 5 min followed by 35 cycles
at denature 95˚C, 30 s; annealing temperature (Table1), 40 s; and extension 72˚C, 30 s. Final extension
was carried out at 72˚C for 5 minutes and theamplified products were hold at 4˚C until needed. At
the end of PCR cycle, amplified products wereanalyzed by 0.8% agarose gel with 1X loading dye.
After electrophoresis at 100 V for 35 min, gel was
stained with GELSTARTM (Gelstar Inc, NY) for 10
min. DNA fragments were visualized by gel
documentation.

Animals
Two hundred and eighty eight cross breeds pig(Large White × Landrace × Duroc Jersey) werepurchased from commercial farm with an initial live
weight of 78 to 134 kg and no any phenotypic
criteria.
Ultrasound Image Collection
All pigs were weighed body weight (BW), bodylength (BL) and were scaled of loin eye area
(U_LAE), back fat thickness (U_BF) obtained 2 hwere scanned before slaughter by real – time
ultrasound (Honda electronic Inc., a 3.5 MHz, 10 cmlong probe and a 1.5 - 2 MHz, 13 cm long). Images
were recorded and then linear and area
measurements were taken by means of the between
10th rib. The pigs were slaughtered at commercial
slaughter house after electrical stunning.
Carcass and Meat Data Collection

Table 1 Sequences of primer and Ta (annealing
temperatures) for PCR amplification

At the slaughterhouse, within 10 min of postmortem, hot carcass weight (Hot_C, kg), pH0 at 0 h
Post – mortem (pH0) and carcass length (CL) werecollected. pH at 45 min post – mortem (pH45) were
determined using pH meter. After chilling, carcass
weight after chilling (Chill_C), pH 22 h (pH22),
back fat thickness (BF), loin weight (LW), hamweight (HW), fillet weight (FW) and shoulder
weight (SW) were determined.

Genes
CTSB1/

Primer sequence
Forward:5´GTGGCCGGGT
GGTTTTA 3´
Reverse:5´TCCTCCTGGTG
CTGCTAATTCTGAC 3´
CTSL 2/ Forward:5´TCACTGCCGTGAAGAATCAG 3´
Reverse:5´GCAGAGCTGT
AATGGCAAGA 3´
Note: 1/ [16], [12]2/[12], [8]Tissue Collection and DNA Extraction
Approximately 20-30 mg of tissue was collectedfrom the carcass of each pig into tube containing
99% of ethanol. Genomic DNA was isolated fromtissue using Puregene (Gentra Inc., Minneapolis,
MN) according to the supplied protocol. Briefly,
tissues were separately minced were washed twicewith 0.9% NaCl sample were centrifuged for 5 min
at 3,000 rpm at room temperature. Cell lysis buffer
and protein precipitation buffer were added to thepellet. Cell lysate was then centrifuged for 5 min at
10,000 rpm at 4°C. The supernatant was thentransferred to 1.5 ml tube, and absolute isopropanol

Ta (0C)

55

64

Restriction of PCR Products
Polymerase chain reaction (PCR) products fromeach pig were digested separately with 1 restriction
endonucleases, Mspl for CTSB and Taql for CTSL.
Each digestion reaction contained 2 μL of PCR
products, 1 μL of cut smart, and 0.2 μL of enzyme,
add water 4.8 μL in a total volume of 10 μL.
Subsequently, each reaction was incubated at 37°C
for Mspl and 65°C for Taql for at least 6 h.
222

223

Genotyping of CTSB deoxyribonucleic acidfragments
weredetectedonavertical
electrophoresis(Mini-Protein
III,
Bio-RadLaboratories, Richmond, CA) using a 12%
denaturing polyacrylamide gel (Sigma Inc., St.
Louis, MO) with 1X polyacrylamide dry 5 μL. Afterelectrophoresis at 150 V for 120 min, gels were
stained with GelStar (Gelstar Inc., Patchogue, NY)
for 10 min. Deoxyribonucleic acid fragments werevisualizedby
UV
transillumination
andphotographed with the Syngene gel documentary
system (Syngene Inc., Cambridge. IL). For CTSL,
detected on a horizontally electrophoresis unit
(Mini-Protein III, Bio-Rad Laboratories, Richmond,CA) using a 2% agarose gel.

VariableBW, kgBL, cmU_LAE, cm2
U_BF, mmCL, cm
Hot_C, kg
Chill_C, kg%carcass, %Weight loss, kg
LAE, cm2
BF, mm
pH0
pH45
pH22
FW, kg
LW, kg
HW, kgSW, kgStatistical analysis
The means of ultrasound, carcass and meat
quality traits were analyzed by PROC MEANS. [13]Associations between the genotypes of thecandidated genes (CTSB and CTSL) on carcass andmeat quality were assessed by the procedure
MIXED in SAS version 8.02 (SAS Institute Inc.
Cary, NC, USA), with a model that included sire asa random effect and the fixed effects sex andgenotype of the analyzed DNA markers.

Means
105.62
73.28
38.30
17.09
76.64
78.96
77.04
74.79
2.43
40.20
31.98
6.40
6.22
6.00
0.80
4.94
9.87
7.04

Std.
9.63
6.41
4.61
3.45
3.14
8.04
7.94
4.23
0.42
5.14
8.19
0.16
0.15
0.21
0.13
0.83
1.02
0.81

Min.
80.00
58.80
20.29
8.80
69.00
57.10
55.60
61.69
0.24
39.00
14.00
5.98
5.82
5.32
0.54
3.06
7.25
5.32

Max.
126
90.00
50.25
25.60
84.00
95.90
93.80
95.77
3.81
56.00
51
6.79
6.66
6.78
1.32
7.49
12.08
9.58

PCR-RFLP analysis and genotype frequency
The expression of CTSB and CTSL genes
was analyzed by PCR-RFLP. The length of PCR
products were 139 bp (CTSB) and 380 bp (CTBL)(Fig.1). The frequencies of three investigatedgenotypes in the CTSB (AA, AC and CC) and CTSL
(CC, CT and TT) gene are presented in Table 3. Of
177 investigated pigs, 0.61 were heterozygous AC
genotype, 0.34 were homozygous AA genotype, and0.05 were homozygous CC genotype in CTSB. The
frequencies of A and C alleles of CTSB were 0.65
and 0.35, respectively. Russo [16] showed thatalleles frequency A was higher than alleles C.
Regarding CTSL, the frequencies of CC, CT and TT
genotypes were 0.625, 0.354, and 0.021,
respectively. The frequencies of C alleles (0.80)
were higher than T alleles (0.20) (Table 3).The highfrequency of CC genotype of CTSL is in accordancewith previous reports [8]. However, Fontanesi [12]reported the highest frequency of TC genotype,which is not in accordance with results of this study.

Results and discussion

Phenotypic analysis
The means (Means), standard deviation(Std.), minimum (Min.) and maximum (Max.) of
carcass and meat quality traits in the pigs are showedin Table 2. Means of BW and Hot_C weight were105.62 kg and 78.96 kg, respectively. Data fromultrasound showed that, U_LEA and U_BF were
38.30 cm2 and 17.09 mm, respectively. The previous
study of Schwab [2] reported that ultrasound 10th ribloin muscle areas were 41.05 cm2 and showed larger
than this study. Ayuso [14] found the means of 10th
rib by ultrasound were 38.12 mm and carcass
measurements were 43.11 mm. Moeller [15]reported loin eye area of swine was 35.2 cm2.

Table 2 Means, standard deviations (Std.), minimum(min) and maximum (max) values forcarcass and meat quality parameters

223

224

Figure 1 The genotype of CTSB gene: AA (108,31+24 bp), AC (108, 84, 31+24 bp) and CC (84,31+24); CTSL gene: CC (218, 162 bp), CT (380,218, 162 bp ) and TT (380 bp) digested with Mspl
and Taql, respectively

AA
AC
BW
102.54 101.93
BL
75.38 77.81
U_LEA
36.52 39.43
U_BF
16.34 15.68
CL76.16 76.93
Hot_C
78.72 79.05
Chill_C
76.52 77.07%Carcass
73.38 74.21
Weight loss 2.19
1.97
CTSB
LEA
39.79 41.32
BF
31.55 30.78
pH0
6.42
6.49
pH45
6.25
6.33
pH22
6.01
6.03
FW
0.75
0.83
LW
4.92
5.13
HW
9.88
9.86
SW
7.12
7.16
CC
CT
BW
103.30 103.75
BL
77.92 76.14
U_LEA
37.61 37.32
U_BF
15.74 15.92
CL76.12 76.44
Hot_C
78.64 78.33
Chill_C
76.65 76.28% Carcass74.19 73.51
2.05
CTSL Weight loss 1.99
LEA
40.35 40.16
BF
30.13 31.96
pH0
6.47
6.47
pH45
6.31
6.27
pH22
6.07
6.05
FW
0.80
0.76
LW
4.92
4.98
HW
10.00 9.85
SW
7.18
7.12
Note: * P < 0.05; ** P < 0.01
CONCLUSION

Table 3 Genotype and allele frequency of CTSB andCTSL in crossbreed swine
Genotype
frequency

Genes

Total

AA

AC

CC

CTSB

0.34

0.61

0.05

1

N

98

177

13

288

CC

CT

TT

CTSL

0.63

0.35

0.02

1

N

180

102

6

288

AlleleTotal
Frequency
A

C

0.65

0.35

C

T

0.80

0.20

1

1

Association of CTSB and CTSL polymorphism on
carcass and meat quality
Thesignificant
effectsof
CTSB
polymorphism were detected on body length (BL),ultrasound scan of loin eye area (U_LAE), weightloss (WL) and loin eye area (LAE) (P<0.05,
P<0.01). The pigs carrying the AC genotype hadhigher level of BL, U_LEA and LEA than the ones
carrying the homozygous genotype (AA or CC). The
pigs with the CC genotype of CTSB had lower WL(1.86 %) than the ones carrying the AA or the AC
genotype (2.19 % and 1.97 %). The CTSL variants
represented statistically significant effects on BL
trait (P<0.05). The CC genotype (77.92 cm) had
higher BL value compared to the CT (76.14 cm) andthe TT genotypes (76.92 cm). The CTSB and CTSL
were high polymorphism and their alleles could be
potential genetic markers for swine selection (Table4). Previous studies have shown that the significant
associations were observed between CTSB and backfat thickness [10]. In addition, Piorkowska [9] foundthat AC genotype characterized higher carcass yieldand loin than in AA pig.
CTSL is a gene that produce lysosomal
proteinases and is important for the degradation ofproteins. Its main role is in the post-mortem
proteolysis of meat [8]. Fontanesi [12] have claimed
that CTSL marker showed a tendency towards
association with back fat thickness and weight oflean cuts. On the other hand, Vera [8], nostatistically significant differences were detected inqualitative traits. However, we identified a trend ofallele T on increased fatness and the effect of allele
C on lean meat.

traitsGenotypes

value
0.83
*
**
0.23
0.17
0.88
0.85
0.23
*
**
0.68
0.09
0.15
0.37
0.37
0.13
0.88
0.96
0.73
*
0.57
0.68
0.45
0.71
0.71
0.18
0.50
0.75
0.06
0.96
0.26
0.58
0.41
0.61
0.28
0.60

CTSB and CTSL were analyzed using the PCRRFLP technique for detection of genotypes. Threealleles were found on CTSB gene (AA, AC and CC)
and CTSL gene (CC, CT and TT) with frequency
ranging from 0.20 to 0.80. The results obtained fromthe present study indicated that the investigated
CTSB and CTSL gene markers were associated withcarcass and meat quality traits in Thai cross breedspig (Large White × Landrace × Duroc Jersey). The
means of Hot_C and Chill_C were 78.78 and 76.71
kg, respectively. LEA was 40.20 cm2. For the CTSB
polymorphism was significant with BL, U_LEA,

Table 4 Association of CTSB and CTSL on carcass
and meat quality in crossbreed swine
Genes

CC
100.90
77.79
36.56
15.71
75.71
77.71
75.84
73.85
1.86
38.70
30.78
6.49
6.31
6.10
0.77
4.80
10.01
7.20
TT
98.29
76.92
36.94
14.97
78.99
75.69
73.17
74.57
2.52
39.43
29.83
6.50
6.36
6.26
0.78
5.00
9.73
6.60

P224

225

[7] Dekkers, J. C. M, Commercial application of markerand gene-assisted selection in livestock: Strategies
and lessons. Journal of Animal Science, Vol. 82,
2004, pp. 313-328.
[8] Vera, D., Roman S., Michal S., Jaroslav C., Monika
O., Eva K., Lubos B, The effect of gene CTSL on
the quantitative and qualitative production traits ofpork meat. Journal of Maso international brno, Vol.
1, 2011, pp. 47-50.
[9] Piorkowska, K., Ropka-Molik K., Eckert R., Tyra M.,
Zukowski K, Analysis of polymorphisms ofcathepsin B and cystatin B impact on economicallyimportant traits in pigs raised in Poland. Journal ofLivestock Science, Vol. 146, 2012, pp. 99-104.
[10] Russo V., Fontanesi L., Davoli R., Nanni Costa L.,
Cagnazzo M., Buttazzoni L., Virgili R., Yerle M,
Investigation of candidate genes for meat quality indry-cured ham production: the porcine cathepsin B(CTSB ) and cystatin B (CSTB ) genes. Journal ofAnimal Genetics, Vol. 33, 2002, pp. 123-131.
[11] Fontanesi, L., Speroni C., Buttazzoni L., Scotti E.,
Nannicosta L., Davoli R., Russo V, Association
between cathepsin L (CTSL) and cathepsin S (CTSS)
polymorphisms and meat production and carcass
traits in Italian Large White pigs. Journal of Meat
Science, Vol. 85, 2010, pp. 331-338.
[12] Fontanesi, L., Speroni C., Buttazzoni L., Scotti E.,
Dallolio S., Davoli R., Russo V, Association between
polymorphisms in cathepsin and cystatin genes withmeat production and carcass traits in Italian Duroc
pigs: confirmation of the effects of a cathepsin L(CTSL) gene marker. Journal of Molecular Biology,
Vol. 39, 2012, pp. 109-115.
[13] SAS.User’s Guide: Statistics, V.6.12, 1998, SAS
Institute Inc., Cary. NC.
[14] Ayuso D., Gonzalez A., Hernandez F., Corral J. M.,
Izquierdo M, Prediction of carcass composition, hamand foreleg weights, and lean meat yields of Iberianpigs using ultrasound measurements in live animals.
Journal of Animal Science, Vol. 91, 2014, pp. 18841892.
[15] Moeller S. J., Evolution and use of ultrasonictechnology in the swine industry. Journal of Animal
Science, Vol. 80(E. Suppl. 2), 2002, pp. E19–E27.
[16] Russo, V., Fontanesi L., Scotti E., Beretti F., DavoliR., Nannicosta L., Virgili R., Buttazzoni L., Single
nucleotide polymorphisms in several porcine
cathepsin genes are associated with growth, carcass,
and production traits in Italian Large White pigs.
Journal of Animal Science, Vol. 86, 2008, pp. 330033

WL and LEA. The pigs carrying the AC genotype
had higher level of BL, U_LEA and LEA thanhomozygous genotype (AA or CC). CC genotype of
CTSB had lower WL (1.86 kg) than AA or the AC
genotype (2.19 and 1.97 kg). CTSL was related to
BL traits. The CC genotype (77.92 cm) had higher
BL than CT (76.14 cm) and TT genotypes (76.92
cm).Therefore, this polymorphism of CTSB andCTSL could be of interest in marker assisted
selection programs.
ACKNOWLEDGEMENTS
We would like to thank Mahasalakham
University, Mahasakham, Thailand, for financial
support and Betagro Company Limited, Thailand,
for tissue supply and the data, which were the main
information of this research.
.
REFERENCES[1] Daza A., Mateos A., Lopez C. C., Rey A., Ovejero I.,
Lopez-Bote C. J, Effect of feeding system on thegrowth and carcass characteristics of Iberian pigs, andthe use of ultrasound to estimate yields of joints.
Journal of Meat Science, Vol. 72, 2006, pp. 1–8.
[2] Schwab, C. R., Baas T. J., Stalder K. J, Results fromsix generations of selection for intramuscular fat in
Duroc swine using real – time ultrasound. Journal ofAnimal Science, Vol. 88, 2010, pp. 69-79.
[3] Miar Y., Plastow G. S., Moore S. S., Manafiazar G.,
Charagu P., Kemp R. A., Van Haandel B., Huisman
A. E., Zhang C. Y., McKay R. M., Bruce H. L.,
Wang Z, Genetic and phenotypic parameters forcarcass and meat quality traits in commercial
crossbred pigs. Journal of Animal Science, Vol. 92,
2014, pp. 2869-2884.
[4] Zhang, Q., Boichard D., Hoeschele I., Ernst C.,
Eggen A., Murkve B., Pfister-Genskow M., Witte
L.A., Grignola F.E., Uimari P., Thaller G., Bishop
M.D, Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred
pedigree. Journal of Genetics, Vol. 149, 1998, pp.
1959–1973.
[5] Ragland K. D., Christian L. L., Baas T. J, Evaluationof real-time ultrasound and carcass characteristics forassessing carcass composition in swine. Journal of
Zootec, Vol. 41, 2004, pp. 2463-2466.
[6] Newcom D. W., Baas T. J., Lampe J. F, Prediction of
intramuscular fat percentage in live swine using realtime ultrasound. Journal of Animal Science, Vol. 80,
2014, pp. 3046–3052.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECT OF HARVESTING STAGES ON JELLY SEED SYMPTOM OF
PLANGO (Bouae burmanica) CV. THUNL KLAO FRUITS
1Pattarawan Wattanakeeboot and 2Usawadee Chanasut
Postharvest Technology Research Center, Faculty of Agriculture, Chiang Mai University, Chiang Mai 50200
2Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200

1

ABSTRACT
Plango or Marian plum (Bouae burmanica) has a short harvesting period and usually harvested at ripe fruit
stage. Therefore, the jelly- seed often occurred inside the fruit. The jelly- seed is a physiological disorder andcauses fruit softening and wilting. This symptom will affect the storage period and shelf- life of the fruit. Jellyseed also found after harvesting. This study was determined the activities of two important cell wall degradation
enzymes which were PG and PME from 3 harvesting stages of plango fruits at 75, 85 and 95 days after full bloom( DAFB) . Fruits were storage at 10 and 25°C. It was found that the jelly- seed symptom only occurred in the 95
DAFB fruits after harvest and storage at 25°C. This fruits also had the highest activity of PG and increased withthe ripen stages and storage period. The activity of PG and PME were delayed when storage at 10°C comparedwith the activity of PG and PME from the fruit kept at 25°C
Keywords: cell wall degradation, polygalacturonase, pectin methyl esterase
INTRODUCTION
Plango (Bouea burmanica) in Thai is called
Ma-yong-chid. It names from plum mix mango thennew commercial name “Plango”. Plango are same
Marian plum but it is big fruit, oblong and not
sweetest or irritate in oesophagus. We are Thai
people call the Marian plum is Ma-prang, small andsour taste somebody eaten are feel irritate. Marianplum (Bouea burmanica Griff) is tropical fruit, tree
belonging to Anacardiacceae family and it is native
Southest Asia and commercially grown in the
ASEAN region in Malaysia, Thailand and Indonesia[17]. Other popular names of this fruit are Mayuncalled in Myanmar, Ramania ugandaria in Indonesia
and Kundang rembunia and setar called in Malaysia.
It is flowering occurs during the cool season on
January and fruits are mature on March. Color of
maturity stages; green, orange and dark orange. Ripe
fruit is orange pulp and stone is purple color. Plango
belong to same family as mango but the taste is notreally the same. It is tastes of flesh a bit like mango,
texture rind of fruit a bit like plum.
Plango has a short harvesting period andripening stage of plango when harvested, it’s mostimportant influencing for textural properties whenharvested over ripe, the textural are like jelly aroundseed. The major textural changes are resulting insoftening of fruits, due to enzyme mediatedalteration of the compositions and structure of cellwall polysaccharides such as pectic polysaccharides
and cellulose, which leads to their partial
solubilisation [18]. Enzymes are about softening,
pectin methyl esterase (PME), polygalacturonase(PG) and cellulose are among enzymes generally

recognised as haveing a crucial effect on fruit texture
during ripening [4] such as disorder in plums, they
are very sensitive to low temperature and benefits ofcold storage maybe limited by development ofvarious physiological disorders for example flesh
translucency (gel breakdown), internal browning,
reddening or bleeding, loss of favor and delayed
softening or retarded ripening after prolonged cold
storage [11]. Flesh translucency is one of the mostfrequently observed chilling injury symptoms, it
showed as translucent gelatinous breakdown inmesocarp and related to the presence of watersoluble pectin [2] besides disorder in plum it showedalso mango. Mango fruit qualities are respected totaste, flavor, color, aroma, weight, size and shape[9], quality performance of mangoes depend on
maturity stage at harvest. Generally, physical,
physiological and chemical parameters are used todefine the maturity stage. Therefore, fruit has to be
harvested at suitable stage of maturity for develop
the optimum sensory quality attributes and extended
postharvest life [19]. Fruit harvested at over maturity
stage is highly susceptible to mechanical damage
such as bruising, decay and water loss and showed
defects like jelly seeds or jelly pulp after harvest[19]. ‘Amrapali’ mango fruit is a physiologicaldisorder of unknown aetiology called jelly seed (JS)which adversely affects the eating quality of matureripe pulp [13]. Therefore, the present study wasplango quality and to effect of harvesting stages
caused jelly seed symptom.

226

SEE - Nagoya, Japan, Nov.12-14, 2018absorbance at 620 nm. PME activity was expressedin Units/ mg protein/min.

MATERIALS AND METHODS
Fruits harvest and storage

Statistical analysis‘Thul Klao’ plango (Bouea burmanica) were
harvested on 75 (Immature ripe), 85 (Mature ripe)
and 95 (Over ripe) day after full bloom of March
2017, from Dussanee orchard located in Mae Thang
district, Chiang Mai province, Thailand. Plango
were picked by hand and sorted accordind touniformity of shape, color and size. Fruits werestorged at 10 and 25°C.

Data were analyzed by SPSS 18.0, Significant
difference were considered at the level of p < 0.05.
RESULTS
Firmness
The softening of plango all harvesting stages
was delayed during storage at 10°C. The firmness offruits declined during storage at 25°C. Plango, 75
day after full bloom at 10°C were decreased slowly
and beginning of softening after 6 day (Fig. 1). The
firmness of plango storage at 25°C in 95 day after
full bloom were declined during storage.

Color of plango
Fruits were measured Lightness (L) and b* bycolorimeter, Color Quote XE.
Measurements of fruit firmness, total soluble solid(TSS)
Measurements of plango fruit firmness were
measured using Texture analyzer TA.XT plus,
plunger set to pierce 8 mm depth. Firmness was
expressed as the maximum force (N). The juice fromplango were measured using a digital refractometer(Agro Pocket refractometer PAL-1) the results
expressed in °Brix. Titratable acidity (TA) was
measured from three grams of plango pulp with 100
ml of deionized water. It used automatic titrator,
Schott Titroline easy M2-230V.

Fig. 1. Firmness in plango fruit on 75, 85 and 95
harvesting stages storage at 10 and 25 °C

Quantification of enzymatic activity
The enzymatic activity of PG and PME were
measured on fresh plango.
Polygalacturonase (PG) activity was quantified
according to the method by [7]. Plango mesocarp
tissues were sliced into around seed 1 cm wide
segment was frozen immediately in liquid Nitrogen.
An enzymatic extract was 3 g of pulp plango with
0.1 M sodium phosphate buffer (pH 6.4) and adding
1 mM EDTA. They were centrifuged at 8,000 rpm
for 30 min at 4 °C [5]. Supernatants were used as
enzyme extracts for assaying PG activity measured
enzymatic activities. The reaction mixture
contraining 0.1 ml of 200 mM Sodium chloride,
0.5% polygalacturonic acid, 0.1 ml of crude enzyme.
It was in cubated at 37 °C for 1 hr. followed byaddition of 3,5 dinitrosalicylate (DNS) reagent. The
absorbance was measured at wavelength 540 nm in
UV-VIS spectrophotometer, Analytik Jena AG,
SPECORD 40. PG activity was expressed asUnits/mg protein.
PME activity was measured follow [12].
Enzyme extract was adjusted 7.5 with 0.01 M
NaOH. Each 5 ml assay mixture contrain 2 ml of 1%
pectin solution (w/v), 0.2 ml of NaCl, 0.15 ml of
0.01% (w/v) bromothymolblue, 0.45 ml of distilledwater and 0.2 enzyme extract and was mixed. The

Fig. 2. Total soluble solid (TSS %Brix) of plango
on 75, 85 and 95 harvesting stages storage at 10 and
25 °C
Plango were found highest total soluble solid(TSS) in mature ripe (85 DAFB). Immature ripe (75
DAFB) were found that TSS decreased slowly.
Mature ripe (85 DAFB) and Over ripe (95DAFB)
were decreased during storage (Fig. 2)
Enzyme activity
PG activity was increased with harvestingstage and during storage and found low level inimmature ripe (75 DAFB) and fruit was storage at
10°C for 12 day. PG are 7.99 Unit/mg protein.
Mature ripe (85 DAFB) were 15.91 Unit/ mg protein

227

SEE - Nagoya, Japan, Nov.12-14, 2018

in fruit storage 10°C for 9 day and found highest PG
activity in the over ripe (95 DAFB) at 25°C 33.68
Unit/ mg protein on 6 day at storage time. (Fig.3).
PME activity was increased slowly on all
harvesting stage and during storage. Fruits werestorage at 10 °C, immature ripe, mature ripe andover ripe found that 3.34, 3.20 and 3.69 Unit/ mg
protein respectively (Fig.4).

Fig. 5. Changes in lightness of plango fruit on 75, 85
and 95 harvesting stages storage at 10 and 25 °C

Fig. 3. Changes in activity of PG in plango on 75,
85 and 95 harvesting stages storage at 10 and 25 °C

Fig. 6. Changes in yellow color (b*) in pulp ofplango on 75, 85 and 95 harvesting stages storage at
10 and 25 °C
DISCUSSION
The plango are short harvesting period,
harvesting stages are important for quality. The fruit
harvested at the suitable stage of maturity in order todevelop the optimum sensory quality attribute andextend postharvest life [19]. Plango was threeharvesting stages, immature ripe (75 DAFB), matureripe (85 DAFB) and over ripe (95 DAFB), maturelevel at harvest is crucial factor for the developmentof acceptable flavor quality during ripening [8]. It is
optimum harvesting, mature ripe. According to [6],during fruit maturation, Total soluble solid tend toincrease while titratable acidity (TA) decrease.
Three harvesting stages of jelly seed during storage
were 25 °C on over ripe, pulp of fruits were showedjelly and dark yellow color. According to [10] flesh
translucency manifests itself as a translucent
gelatinous breakdown of the mesocarp of stone
fruits and related to presence of WSP in the tissues.
In this study, fruits are showed jelly seed, highpolygalacturonase based on an increase duringstorage. Resulting in severe texture change andsoftening, the increase of polygalacturonase andcellulose activities during ripening should contributeto the loss of texture through action on cell wall
pectic polysaccharide and cellulose, charing theirstructure and solubilizing cell wall component [1][14] therefore softening is a developmentallyprogrammed ripening process in many fruits,
providing difference texture with various fruits
including juiciness, crispness and stiffness [14].

Fig. 4. Changes in activity of PME in plango on 75,
85 and 95 harvesting stages storage at 10 and 25 °C
Lightness (L) was decreased with harvestingstages, immature ripe, mature and over ripe.
Lightness value were found that high value, 66.94 inimmature ripe (75 DAFB). Color changes occured inpulp are dark yellow and show jelly texture on fruits
storage at 10 °C found beginning of color changes
on 8, 7 and 7 storage time (day), (immature ripe,
mature ripe and over ripe respectively) (Fig. 5).
Plango were showed jelly severe around seedstorage at 25 °C then showed on 9, 8 and 6 storage
time (Day); immature ripe, mature ripe and over ripe
respectively (Fig. 5).Yellow color (b*) wereincreased with harvesting stages, Over ripe (95
DAFB) are high b* value on 6 storage time (Day),49.1 confrom with PG activity and firmness due tojelly texture in pulp (Fig. 6).

228

SEE - Nagoya, Japan, Nov.12-14, 2018

Journal of the Science of food and Agricultural,80(10), 1503-1509.
[6] Dharini, S., Yuming, J., & Elhadi, M. Y. (2011).
Maintaining mango (Mangifera indicra L.) fruit
quality during the export chain. Food researchInternational, 44, 1254-1263.
[7] Gross, K. C. (1982). A rapid and sensitive
spectrophotometricmethodforassaying
poligalacturonaseusing
2–cyanoacetamide.
HortScience, 17, 933-934.
[8] Kader, A., & Mitcham, B. (2008). Optimum produres
for ripening mangoes. Fruit Ripening and Ethylene
Management. Postharvest thechnology, 47-48.
[9] Kader, A. A. (2002). Quality and safety factors:
Definition and evaluation for fresh horticultural crops.
Postharvest technology of horticultural crops, 279285.
[10]
Manganaris, G. A., Vicente, A. R., Crisosto, C.
H., & Labavitch, J. M. (2008b). Effect of delayed
storage and continuous ethylene exposure on flesh
reddening of ‘Royal Diamond’ plums. J. Sci. Food
Agric. 88, 2108-2185.
[11] Minas, I. S., Crisosto, G. M., Holcroft, D.,
Vasilakakis, M., Crisosto, C. H., (2013). Postharvest
handing of plums (Prunus salicina Lindl.) at 10 °C tosave energy and preserve fruit quality using andinnovative application system of 1-MCP. Postharvest
Biol. Thechnol. 76, 1-9.
[12] Nunes, C. S., Castro, S. M., Saraiva, J. A., Coimbra,
M. A., Hendrickx, M. E., & Van Loey, A. M. (2006).
Thermal and high-pressure stability of purified pectin
methylesterase from plums (Prunus domestica).
Jounal of food Biochemistry, 30(2), 138-154.
[13] Seshadri, S., Manoharan, S., & Hari, S. S. (2016).
Premature seed germination induced by very-longchain fatty acids causes jelly seed disorder in the
mango (Mangifera indica L.) cultivar ‘Amrapali’ inIndia. Horticultural Science and Biotechnology, 91:2,
138-147.
[14] Seymour, G. B., Manning, K., Eriksson, E. M.,
Popovich, A. H., & King, G. J. (2002). Genetic
identification and genomic organization of factors
affect fruit texture. J. Exp. Bot, 53, 2065-2071.
[15] Tieman, D. M., Harriman, R. W., Ramamohan, G. &Handa, A. K. (1992)/ An antisense pectin
methylesterase gene alters pectin chemistry andsoluble solid in tomato fruit. The plant Cell 4: 667679.
[16] Thakur, B. R., Singh, R. K., & Handa, A. K. (1996).
Effect of an antisense pectin methylesterase gene on
the chemistry of pectin in tomato (Lycopersiconesculentum) juice. J. Agric. Food chem. 44: 628-630.
[17] Vusie, L. M., & Yapwattanapun, C. (2001). Effect ofenvironmental conditions on flower induction of
marian plum (Bouea burmanica Griff). Agriculturaland natural resources, 51, 243-246.
[18] Waldron, K. W., Smith, A. C., Parr, A. J., Ng, A., &Parker, M. L. (1997). New approaches tounderstanding and controlling cell separation to fruitand vegetable texture. Trends in Food Science andThechnology, 8(7), 213-221.
[19] Yahia, E, M. (1998a). Modified and controlled
atmospheres for tropical fruits. Horticultural
Reviews., 22, 123-183.

Pectin methyl esterase are increase slowly all
harvesting stages. According to [13], jelly seed had
higher polygalacturonase (PG) and increase pectin
methyl esterase activities (PME). Pectin methyl
esterase (PME) catalyses the removal of methy ester
groups from pectin chains making them more
susceptible
toPG-mediateddegradation.
Subsequently, the rapid increase in PG activity
deploymerised cell wall polygalaturonides to
produce galacturonic acid [3]. According to [15] and[16], PME activity had little effect on fruit firmness
or ripening characteristics but resulted in significant
favorable changes is soluble solids content of raw
juice.
CONCLUSION
This study 3 harvesting stage of plango fruits
at 75, 85 and 95 days after full bloom (DAFB).
Fruits were storage at 10 and 25°C. It was found thatthe jelly-seed symptom only occurred in the 95
DAFB fruits after harvest and storage at 25°C. This
fruits also had the highest activity of PG andincreased with the ripen stages and storage period.
The activity of PG and PME were delayed whenstorage at 10°C compared with the activity of PG
and PME from the fruit kept at 25°C.
ACKNOWLEDGEMENT
We would like to thank the Postharvest
Technology Research Center, Faculty ofAgriculture, Chiang Mai University, Department of
Biology, Faculty of Science, Chiang Mai University,
Chiang Mai, Thailand and The Graduate School
Chiang Mai University, Chiang Mai, Thailand.

REFERENCES[1] Ali, Z. M., Chin, L.-H., & Lazan, H. (2004). A
comparative study on wall degrading enzymes, pectin
modifications and solftening during ripening of
selected tropical fruits. Plant Science, 167(2), 317327.
[2] Candan, A. P., Graell, J., Larrigudiere, C. 2011.
Postharvest quality and Chilling injury of plums:
benefits of 1-methylcycopropene. Span. J. Agric. Res.
9, 554-564.
[3] Carpita, N. C., & Gibeaut, D. M. (1993). Structuralmodels of primary cell walls in flowering plants:
Consistency of molecular structure with the physicalproperties of the wall during growth. The Plant
Journal, 3, 1-30.
[4] Claudia, N., Conceicao, S., Gloria, P., Sonia, S., Jose,A., and Lopes-da, V. (2009). Effect of ripening on
microstructure and texture of ‘Ameixa d’Elvas’
candied plums. Food Chemistry, 115, 1094-1101.
[5] Denes, J. M., Baron, A., & Drilleau, J F. (2000).
Purification, properties and heat inactivation of pectin
methylesterase from apple (cv Golden Delicious).

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

USING BEEF MORPHOLOGY TO PREDICT CARCASS WEIGHT
WHICH CUTTING IN THAI-ISAAN STYLE
Khanitta Ruangwittayanusorn1*, Doungnapa Promket1, Songsak Champawadee1,
Jaturaput Muapkunton1, Ornicha Sriboon1, Kewlin Pukkawan1
Division of Animal Science, Department of Agriculture Technology, Faculty of Technology, Mahasarakham
University, Thailand
ABSTRACTThe trading of beef cattle market in Thailand is based on price satisfaction agreement between sellers
and buyers. The rancher, the middlemen and the butcher shop will estimate the return from carcass composition
by beef characteristic. The forecast of return from carcass composition depends on personal skill. The highest
price of carcass cutting in Thai-Isaan style compost with all meat, liver, spleen, kidney, heart, tongue and gastric.
The objective of the study was to determine the best-fitted regression model for predicting the carcass
composition using different linear body measurements. Data on carcass composition cutting in Thai-Isaan styleand linear body measurements recorded form 100 crossbred male beefs in Isaan region were used for this study.
The simple and multiple regression models were fitted with carcass composition as dependent variable and heartgrit, body height, body length, hip width and hip length as independent variables. The correlation coefficients
between carcass composition and body measurements were strongly and significantly (P<0.01). Body length wasbest fit to simple regression model for predict carcass composition weight (R2=0.712). Stepwise method wasused to select factor effect in multiple regression models. Multiple regression for predict carcass composition
had highest R2 when all body measurements were included (R2=0.816), however the recommend model was the
3 factors model (heart girth, body length and hip length) with R2=08101. The study concludes that linear bodymeasurements can predict carcass composition weight and their return. The rancher, the middlemen and the
butcher shop can use this equation to forecast the return and setting the beef price for trading.
Keywords: Carcass, Estimate the return, Total trimmed meat, Morphology, cattle
Estimation from sight, there will be a lot oferror if not expert. Body measurements taken on live
animals have been used expansively for a variety ofreasons both in experiments and in selection purpose[3]. The accuracy of prediction carcass weight fromlive weight is a financial contribution to livestock
enterprise. The producers and buyers can estimate
revenue from the sale of live cattle and access valuebased trading systems.
The purpose of this study was to predict thecarcass weight from body measurement using simple
and multiple linear regression.

INTRODUCTION
Number of beef cattle in Thailand in year 2017
was around 4,876,000. Forty-seven percent of all
were in Isaan region [1]. With extensive areas andIsan people prefer to consume meat from beef andthey have a culture about consumption beef, so there
are a lot of beef cattle in Isan.
The butcher shops in Isaan region mostly
trimming meats that were killed in the municipal
slaughterhouse. They buy live cattle from the
middlemen or some from local beef cattle market.
The trading of beef cattle market is based on pricesatisfaction agreement between sellers and buyers.
The rancher, the middlemen and the butcher shop
will estimate the return from carcass composition bybeef characteristic. Estimate of the carcass to be
derived from the appearance of cattle is a unique
skill expertise and the wisdom of beef buyer.
Weight of carcasses directly depends on bodyweight [2]. Forecasting the carcass weight of cattle
must have information on live weight. Nevertheless,the trading in the countryside, no scale is used toweight. As a reason, the linear type trait of live
animal is applied to estimate the live weight and thecarcass weight and inference to the return.

Slaughter and cutting Thai-Isaan style Thailand.
Several percent of beef cattle in Thailand are
cutting in standard way but for Isaan, they cutting tosuitable for the local cooking. The people in Isaan
eat almost every part of the cattle carcass except for
skin, bone, horn. Parts of carcass are grouped by thevalue, each group sale in the same price, although
they are different types of tissues.
The slaughter method starts with stunning
cattle by a hammer at the front of the skull, X
crossing line between horn and eye. After cattle fall
down use a sharp knife to pierce the jugular vein to
bleed until the blood flow is negligible. Hang 4 legs
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SEE - Nagoya, Japan, Nov.12-14, 2018

separately and clean body outside. Cut the skinalong the middle line to the tail. Skin for 4 legsshould be removed accepts under knee to hoof. The
horns are removed and the head is skinned. The headis detached by cutting through the neck muscles andthe occipital joint. Cut along middle line to open a flamprediction equations. R-square assessed the accuracyof the equations.
RESULTS AND DISCUSSION
Mean and ranges of body measurement andcarcass weight were showed in Table 1. All
observations were normally distributed. The highcorrelation between body measurements were foundfor hip width and hip length (0.926), Hip width andheart girth (0.824). The balance and relationships ofanimal body part is stable when they rise in nearly
management. [4]. Correlation between all bodymeasurements and carcass group weight weresignificant correlated (Table 2). Body length wasreported to have the highest correlation with W1 andheart grid was the highest correlation with W1_1.

and removed internal organs such as stomach intestine
liver heart, etc. Front legs, from scapula to hoof, hindlegs from femur to hoof (round bottom) wereseparated out for hanging show in a butcher shop.
All red meat remaining in frame is trimmed out of
the bone. Each part is weight before sent to butcher
shop. Hot carcass weight cannot done because of theslaughterhouse does not have the instrument to pull
the body up and that trait is less important for local
trading.
MATERIAL AND METHODS

Table 1 Descriptive value of body measurement andcarcass weight groups

Crossbred Brahmans were bought from many
provinces around Isaan region to municipality
slaughterhouse in Kalasin province, Thailand. About
8-10 heads per week of beef were slaughtered,
totally 100 beefs were used in this study. Before
slaughter process, beef were taken in to restraint box
for body measurement. The parameters compost
with heart girth (HG): the body circumference
posterior to the front legs, body length (BL): thedistance between the point of shoulder to the outerand central tuberosity of left humerus to left tuber
ischii, body height (BH): the vertical distance fromground to scapular of the withers, hip width (HW):
the widest point at the center of the stifles, hip length(HL): the distance between pin bone to the stifle.

Variable
Body measurement

N

Mean

Std
Dev

Mini
mum

Maxi
mum

Heart grid (cm)Body height (cm)Body length (cm)Hip width (cm)Hip length (cm)

100
100
100
100
100

177.08131.60133.2045.08
52.21

11.461
11.34713.505
6.552
6.392

155
112
102
30
37

220
170
165
59
67

Weight of carcass groupW1 (kg)100 170.00 23.680
118230
W1_1 (kg)
100
17.82
1.493
15
24
W2 (kg)
100
25.25
3.955
17
39
W3 (kg)
100
25.06
3.348
17
36
W1
= weight of first price group composted with total
trimmed meat.
W1_1 = weight of internal organ high value group composted
tongue, heart, liver, spleen and kidney.
W2= weight of second price group composted with rib, meat
scraps, fat, colon, and intestine.
W3= weight of third price group composted with lung,trachea, bladder, cartilage, rumen, reticulum, omasumabomasum and their ligament.

Several beef were slaughter in a day, one by
one for tracking and recording each part of body.
Beef carcasses were trimmed in the style of Isaan.
Carcass compositions were group by price. The firstprice group (W1) was a high value group composted
with total trimmed meat such as shanks, chuck,
sirloin, rump, round, loin, brisket, etc. Internal organ
high value group (W1_1) composted with tongue,
heart, liver, spleen and kidney. Second price group
was intermediate price (W2) composted with rib,meat scraps, fat, and intestine. Third price group was
the lowest price (W3) compost with lung, trachea,
bladder, cartilage, rumen, reticulum, omasumabomasum and their ligament. Each group was
weighed after trimmed and recorded. Whole legswith bone-in were weighed before sold and weighed
only bone again after meat sold out to calculate
meat.
Simple correlation coefficients between bodymeasurements and weight of each carcass groupwere calculated and test for significant. To predict
carcass weight, the stepwise procedure was used to
select the variable of body measurements for fitting

Table 2 Correlation between body measurements
and carcass weightparameters
Heart grid

W1

W1_1

W2

W3

0.80540.47270.4066
0.6037
***
***
***
***
Body height
0.71960.45400.47420.5762
***
***
***
***
Body length
0.84530.33160.23590.5115
***
***
***
***
Hip width
0.79660.37730.36920.6298
***
***
***
***
Hip length
0.74030.39870.4546
0.6357
***
***
***
***
W1
= weight of first price group composted with total
trimmed meat.
W1_1 = weight of internal organ high value group composted
tongue, heart, liver, spleen and kidney.
W2= weight of second price group composted with rib, meat
scraps, fat, colon, and intestine.

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SEE - Nagoya, Japan, Nov.12-14, 2018

W3

= weight of third price group composted with lung,trachea, bladder, cartilage, rumen, reticulum, omasumabomasum and their ligament.
*** p<0.01

W1= 0.959(HG)
W1= 1.129((BH)
W1= 1.278(BL)W1= 3.752(HW)W1= 3.248(HL)

Prediction equation for carcass weight group

W1

Simple linear regression for prediction 4 pricegroup weights were calculated from their highest
correlation with body measurement (Table 3).
Highest correlation between W1, W1_1, W2 and W3
were body length, heart girth, body height and hiplength, respectively. Body length explained 71.5%of the variation in W1. It was observed that one cm
change in HG resulted in approximately 1.482 kg
change in weight of first price group.

W1
W1_1
W2
W3

Equations= weight of first price group composted with total
trimmed meat.

R2

Table 5 Variable left in the multiple linear
regression for estimation of first price group= -27.500+1.482BL

0.715

W1_1

= 6.872+0.06HG

0.223

W2

= 3.491+0.165BH

0.225

Variable

Parameter
EstimateW3= 7.676+0.333HL

0.404

INTERCEP-89.782

Heart girth
Body
length
Hip length= weight of first price group composted with total
trimmed meat.
= weight of internal organ high value group composted
tongue, heart, liver, spleen and kidney.
= weight of second price group composted with rib, meat
scraps, fat, colon, and intestine.
= weight of third price group composted with lung,trachea, bladder, cartilage, rumen, reticulum, omasumabomasum and their ligament.

Partial
R2

Model
R2

p-value

0.547

49.6330.715

0.71450.0001

0.898

13.5850.075

0.78910.0001

0.820

4.864

0.021

0.81010.0015

In previous studies, body measurement in beef
cattle were focused on live weight such as in Brown
Swiss [12] in Kamphaengsaen beef [13], in Sahiwal
cattle [9] and in Brahman crossbred [14] for rural
livestock enterprises or for selection purpose
because of the measure of body measurement wereeasier from a live animal and can determine bodyweight approximately lacking of a scale. The use of
linear measurements to predict carcass compositionin cattle was rear; there were some studies in sheep[15], [16] and goat [17]. In this study, we calculated
the predictive equation to estimate the total trimmed
meat from the live appearance. It is very useful for
predicting carcass weight without expensive

Table 4 Simple linear regression equations for
estimation of weight of first price group from bodymeasurements
R2
P-Value
Regression equations
0.64860.51780.7144
0.63450.5479C(p)Carcass weight is an important trait in animalhusbandry, due to economic profit. Carcass weightmight be depended on many effects such as gender,
age, breed, feeding condition etc. [10]. In this study,
we used only male cattle and age approximately 1836 months. Dressing percentage was not affected byduring this age [11]. Beef cattle in the Isaan market
were usually Native-Brahman and raised in small
farming system. Management in small farming
system was not quite different, cattle grazing in the
pasture and sometime supplemented withconcentrated food.

The main return for the butcher from beefcarcass was the W1, it made around 80.00%, of all
income from whole carcass, as a reason theprediction equations were focus on this trait.
In prediction of W1, when only one parameterof body measurement included the model, the R2
was highest for body length (Table 4). For making
the equation easier, non-intercept model were also
calculated. In many studies, heart girth is the best
body measurement for prediction body weight inbuffalo [5], in Brahman crossbred [6], in Bali cattle[7] but for the carcass weight, body length wasbetter.

W1 = -125.86+1.66(HG)
W1 = -27.74+1.50(BH)
W1 = -27.49+1.48(BL)W1 = 40.15+2.87(HW)W1 = 26.76+2.74(HL)

0.00010.00010.00010.00010.0001

For prediction equation using all bodymeasurements in the model, the R2 was highest(0.8157) according to many prediction study [8, 9].
The model was W1= -106.30 +0.525(HG)+0.201(BH) +0.922(BL) -0.657(HW) +1.212(HL).
However, when all parameter were in the model, it
was not practical to use. Stepwise was used to selectthe appropriate parameter in the model. There were
3 parameters, BL, HG, HL with p-value better than
0.15 were remain in the equation with R2=08101(Table 5).

Table 3 Simple linear regression equations for
estimation of weight of first price group, weight ofsecond price group and weight of third price group
Dependent
variables
W1

0.99120.9906
0.99430.99190.99100.00010.00010.00010.00010.0001

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SEE - Nagoya, Japan, Nov.12-14, 2018

instruments such as ultrasound. Although the use ofultrasound could improve accuracy in predicting
carcass weight [18] and could reduce the cost ofcollection estimates of carcass composition in live
seedstock [19], conversely it is not suitable for use
in the rural situation. In a report from Afolayan [20]they suggest to predict meat weight by live weight,
stifle width, body height and hip width with higher
R2 (0.87) than this study, however, they used moreparameter.
The butcher in Isaan gets income of carcass
mostly from W1. The average incomes from eachgroup were 79.77%, 8.38%,7.63%, and 4.22% for
W1, W1_1, W2 and W3, respectively. Economic
weighting price of W1 W2 and W3 varied according
to the quality of the carcass and the likelihood of
consumption. Price per kilogram of W1 and W1_1
were 3.0 times of W3 and W2 was 1.8 times of W3,
it fluctuated in a narrow range depended on demandand supply.
The one composition measurement could
predict total trimmed meat was the body length. A
prediction chart for determining total trimmed meatweight form various body lengths have been
prepared and shown in figure 1.

and the butcher shop to forecast the return andsetting the beef price for trading. This study issignificant for the prediction of carcass weight, so,
the buyers can estimate revenue from the sale of live
cattle and access value-based trading system. For
fitting equation, The fitting equation to predict the
total trimmed meat using three parameters was
W1= -89.782+0.547(HG)+0.898(BL)+0.820(HL).

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Body Length (cm)Fig. 1 Prediction chart for determining total trimmed
meat weight from body length in male crossbred
Brahmans.

CONCLUSION
Linear body measurements in crossbred
Brahman can predict carcass composition weight
and their return. The practical application of theresult in those situations that weight measurements
might not be feasible to setting the price such as insmall farmers or in a cattle market where do nothave access to a weighbridge. Linear bodymeasurements will help the rancher, the middlemen,
233

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[15] Agamy R., Abdel-Moneim A.Y., Abd-Alla
M.S., Aboel-Mageed I.I. and Ashmawi G.M.
Using Linear Body Measurements to Predict
Body Weight and Carcass Characteristics ofThree Egyptian Fat Tailed Sheep Breed. Asian J.
of Anim. Vet. Adv. Vol. 10, Issue 7, 2015, pp.
335-344.

[16] Cam M.A., Olfax M. and Soydan E. Body
Measurements Reflect Body Weights andCarcass Yields in Karayaka Sheep. Asian J. of
Anim. Vet. Adv. 2010, pp.1-8.
[17] Rahman MD. F. Prediction of Carcass Weight
From the Body Characteristics of Black Bengal
Goats. Int. J. Agri. Biol., Vol. 9. Issue 3, 2007,
pp. 431-434.
[18] Silva1 S. da L., Tarouco J. U., Ferraz1 J. B. S.,
Gomes R. da C., Leme1 P. R., Navajas E. A.
Prediction of Retail Beef Yield, Trim Fat andProportion of High-Valued Cuts in Nellore Cattle
Using Ultrasound Live Measurements. R. Braz.
Zootec. Vol. 41, Issue 9, 2012, pp. 2015-2031.
[19] Bergen R., Miller S. P., Mandell I. B., andRobertson W. M. Use of Live Ultrasound,
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[20]Afolayan R.A., Deland M.P.B., Rutley D.L,
Bottema C.D.K., Ewers A.L., Ponzoni R.W. and
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and Bone Yield across Diverse Cattle Genotypes
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Aust. Vol. 24, 2002, pp. 13-16.

234

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DETERMINATION OF CAROTENOIDS AND DOBI CONTENT INCRUDE PALM OIL BY SPECTROSCOPY TECHNIQUES:COMPARISON OF RAMAN AND FT-NIR SPECTROSCOPY

Rayakorn Nokkaew1, Vittaya Punsuvon1,2, Tetsuya Inagaki3, Satoru Tsuchikawa3
1
Center of Excellence-Oil Palm, Kasetsart University, Bangkok, 10900 Thailand
2
Department of Chemistry, Faculty of Science, Kasetsart University, Bangkok, 10900 Thailand
3
Graduate School of Bioagricultural Sciences, Nagoya University, 4648601 Japan
ABSTRACT
Crude palm oil (CPO) is a rich source of carotenoids which are a precursor of vitamin A as an importantantioxidant. Carotenoids and Deterioration Of Bleachability Index (DOBI) are important factors to indicatedquality of CPO. The conventional method for DOBI and carotenoids determination use UV-Vis spectrophotometryand HPLC, respectively which methods use solvents and spend time for analysis. This research interests Raman
and FT-NIR spectroscopy for carotenoids and DOBI determination due to those techniques are alternativetechnique for rapid measurement, non-destruction of material, and environmental suitability. The results indicatedthat Raman is better for determination than FT-NIR spectrometry. In Raman analysis, multiplicative scattercorrection (MSC) and standard normal variate (SNV) treated methods were the best models for carotenoids and
DOBI, respectively. The bands of carotenoids were at 1,100 and 1,500 cm-1 wavenumber. Validation on
carotenoids produced 0.94 of correlation coefficient (R), 0.88 of coefficient of determination (R2), 40.65 ppm ofroot mean square error of prediction (RMSEP), and 3.25 of ratio of standard error of prediction to standard
deviation (RPD). The validation of DOBI produced 0.76 of R, 0.57 of R2, 0.31 of RMSEP, 1.92 of RPD of 1.92.
The limitation of carotenoids and DOBI determination using FT-NIR is having sufficient concentration of
carotenoids for analysis. In addition, data for various samples regarding location, season, and oil palm species areimportant to build models for precise prediction.
Keywords: DOBI, Carotenoids, Crude palm oil, Rapid analysis, Raman, FT-NIR

the CPO in the commercial is decided by the CPO
quality. There are a premium quality (The DOBI≥3),
a good quality (grade A; 2.3<DOBI<3) and a poor
quality (grade B; DOBI<2.3). The high quality gives
the high price for purchase. The DOBI is an index fordetermining the bleachability of palm oil [2] andcarotenoids in CPO. However, mills cannot detect itthemselves because they lack the knowhow,laboratory skills, and instruments for analysis. GoodCPO quality requires not only high carotene but also
should contain low secondary oxidation products(peroxide, aldehyde, ketone, acid, etc.) [3], [4]. Other
characteristics of the DOBI could indicate theripeness of palm fruits, the amounts of carotenoids,
and the freshness of palm fruits.
The conventional methods for DOBI andcarotenoids
determination
involve
UV-Visspectrophotometry or high performance liquid
chromatography [2], [3], [5]. However, the sample
preparation uses chemical solvent (introducing awaste chemical problem) and the analysis is time
consuming. Many researchers have studied
spectroscopy techniques for carotenoids analysis invarious vegetables and fruits. Spectroscopy offers a

INTRODUCTION
Thailand is an agricultural country where themajor crops include rice, para rubber, cassava, oilpalm, sugarcane, and corn as top exports [1].
However several years ago, oil palm became
important as an economic crop because it has many
advantages for consumption (such as in food,cosmetics, pharmaceuticals, etc.) and alternative
energy (such as lubrication oil, biodiesel, biofuel,etc.). Furthermore, the Thai government haspromoted oil palm plantations to farmers bylaunching several policies to facilitate and create
stakeholder activity. Consequently, oil palm
cultivation and the crude palm oil (CPO) yield haveincreased every year.
At present, commercial palm oil is a highly
competitive commodity with importance placed on
CPO properties such as free fatty acid, iodine value,
peroxide value, oil content and Deterioration Of
Bleachability Index (DOBI). The CPO quality is atrade barrier and the DOBI value is of interest because
it is an important factor for CPO classification of
crude palm mills Thailand and the carotenoids
content is depended on the DOBI value. The price of235

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powerful, nondestructive, and intensively applied
method for rapid analysis such as; (1) Fourier
Transform Raman (FT-Raman) and Fourier
Transform Near Infrared (FT-NIR) techniques wereapplied to determine carotenoid in tomato fruits. The
concentration range of carotenoids was 28.5-631.83
ppm and the major component of carotenoids was
lutein. The results indicated that FT-Raman produced
better analysis than FT-NIR with the coefficient ofdetermination (R2) and standard error of crossvalidation (SECV) using FT-Raman and FT-NIR
being 0.91, 74.31 and 0.85, 91.19, respectively [6].
(2) FTIR spectroscopy was determine the commercial
β-carotene in refined-bleached and deodorized(RBD) palm olein. The commercial carotene was
spiked into RBD at 200-2,000 ppm. A partial leastsquares (PLS) calibration model indicated this was agood method that was efficient and accurate for
quality control analysis [7]. (3) Raman was used todetermine carotenoids in various vegetables and fruits(such as apricot, carrot, saffron, Broccoli, chamomile,
nautilus, periwinkle, etc.). They found two strong
bands in the 1,100-1,200 cm-1 and 1,400-1,600 cm-1
region, of the Raman spectrum. These bands are due
to C-C stretching vibrations of the polyene chain,
C=C stretching of conjugate carotenoids, with theshift of bands depending on the length of the chain
and the number of double bonds of carotenoids [8].
(4) The application of NIR for carotenoids
determination in CPO, a calibration curve range from
200 to 800 ppm was prepared by spiking a known
concentration of carotenoid into a normal CPO. PLS
calibration was developed from 18,315-12,210 cm-1of the spectral region. The R2 and standard error
calibration (SEP) values were 0.95 and 23.6,
respectively, while validation produced an R2 of 0.98
and an SEP of 19.96 [9]. (5) Using NIR spectroscopy
to study the chemical properties of oils (a mixture ofsoybean, rapeseed and palm oil) such as the iodine
value, moisture content, acid value, etc. [10].
Although many researchers have studied carotenoids
determination using spectroscopy techniques, there
has been no report on the study of the DOBI or
carotenoids content in extracted CPO from under-ripe
palm fruits, with the reported work involving
extracted CPO from ripe-palm fruits, whereas thepalm oil mills extract CPO from under-ripe and ripe
palm fruits. The under-ripe palm fruits (inner sectionof the spikelet from the oil palm bunch) have a very
low carotenoids content which may affectmeasurement using spectrometry.
This research investigated the application ofRaman and FT-NIR for rapid and direct measurementof carotenoids and DOBI in extracted CPO from ripe
and under-ripe palm fruits. The results werecompared and the best calibration model was
determined using the Unscrambler program toconfirm possible implementation in a palm oil mill.
The Raman and the NIR techniques are the novelty ofdetermination of the DOBI and carotene content in
the crude palm oil. They are destructure of crude palm
oil which the conventional method has to sample
preparation with n-hexane solvent and the bothtechniques can reduce the operated time of analysis
from 5 mins to less than 1 min. One advantage of theboth technique is friendly environment. The one
objective of my research was determination the DOBI
and carotene from unripe-palm fruit which is notfound in any research.
MATERIAL AND METHOD
Sample preparation
This research focused on the Tenera species of oilpalm obtained from the Oil Palm Technology
Development for Local Commercial Biodiesel
Industry in Newly Planted Area Project, in the
Faculty of Agriculture, Kasetsart University,
Thailand. For sample preparation, the fresh palm
bunches (FPBs) were divided into three zones (apical,
equatorial and basal zones). Each zone was divided
into two categories of palm fruit sample—ripe andunder-ripe palm fruit. The ripe palm fruits were theouter section of the spikelet having dark-orange or
dark-red palm fruits while the under-ripe palm fruits
were from the inner section of the spikelet and werelight-yellow to light-orange whole fruit. For eachsample the CPO was obtained using solvent
extraction with hexane solvent and solvent
evaporation in a vacuum evaporator. Oil palm fruit
samples were collect every day for a week, resulting
in 126 CPO samples.
Measurement using spectroscopy techniques
Raman spectra measurement
The all samples were warmed at 60°C using a hotair oven before measurement of Raman. Then, Raman
spectra were recorded using a Serstech Indicator Kit(model Serstech 100 Indicator; Serstech Chemical
Intelligence Solutions, Sweden). Spectra data of CPO
were accumulated at 20.50 seconds of scan time in therange 400-2,300 cm-1 with a laser power of 300 mW.
For each sample, two spectra were collected andsubsequently averaged.
NIR spectra measurement
The all samples were analyzed using a Bruker
spectrometer (model MPA, Bruker, Gmbh, Ettlingen,Germany). This FT-NIR spectrometer is designed fortransmittance analysis of a liquid sample. The oilsample was dropped in a quartz with 1mm path length(S10-SQ-1; GLSciences Inc. Japan) and all samples
were warmed in a dry thermo bath (model MG-2000,
Eyela thermo bath, Germany) at 60°C before analysis
236

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determination of validation (Rv2); root mean squareerror of prediction (RMSEP); and the ratio ofstandard error of prediction to standard deviation(RPD), being the ratio of the standard deviation ofdata (SD) to RMSEC. Models with a high R, R2, and
RPD and a low RMSEC and RMSEP are considered
to be optimum.

for homogeneous CPO samples. NIR spectra were
measured directly on the sample and acquired
between 4,000 to 12,500 cm-1, setting the resolution
to 8 cm-1 at 60°C, and 64 scans of the average reading.
For each sample, two spectra were collected andsubsequently averaged.
DOBI and carotenoids content analysis (reference
analysis)

RESULTS AND DISCUSSION
The DOBI and carotenoids content of theextracted CPO from ripe palm fruits were greater thanin the extracted CPO from under-ripe palm fruits.
With increased palm fruit ripening (observed from thecolor change from light yellow to dark red), thecarotenoids content in the CPO increased but the
DOBI only increased to a maximum value at 3 daysof storage time and after that the DOBI decreased dueto the autoxidation reaction of oil over longer storage.
The fatty acid or triglyceride was in radical forms.
The hydrogen atom from the fatty acid or triglyceridein oils is removed and lipid alkyl radicals areconverted into lipid peroxide for which oxygen, UV,
and heat are the catalysts for autoxidation. The lipid
peroxide decomposed to alkoxy radicals and thenformed aldehydes, ketones, acids, esters, alcohols,and short-chain hydrocarbons (secondary products ofoxidation). Table 1 shows the distribution of the
DOBI and carotenoids content in all samples. The
maximum carotenoids content was 539.79 ppm in
CPO extracted from ripe palm fruit while theminimum carotenoids content was 2.79 ppm in CPO
extracted from under-ripe palm fruit. In general,commercial CPO has a carotenoids content between
400 and 700 ppm [3] – [6] but the current experimentresulted in a low carotenoids content because of thedrought in Thailand at the time the samples werecollected and this affected the production of oil palm
products (less weight of oil palm bunch, less palm oilyield, slow growth of oil palm, slow ripeness of oilpalm bunch, etc.).

DOBI was determined according to the Palm Oil
Research Institute of Malaysia (PORIM) test method
which was developed by Swoboda (1982) and the
carotenoids content was determined according to the
PORIM test method (1995). About 0.1 g of CPO wasweighed and dissolved in 25 ml of hexane solvent.
The solution sample was placed in a 1 cm wide of
cuvette and absorbance measured at 446 nm(measurement of carotenoids) and at 269 nm using aspectrophotometer (T70+UV/VIS spectrometer, PG
Instruments, USA). The DOBI and carotenoids
content were calculated using eq. 1 and eq. 2,
respectively.

DOBI =

A446
A269

Carotenoids (ppm) =(1)

383 × A446 × V
W × 100(2)where: A446 = absorbance at 446 nm, A269 =absorbance at 269 nm, 383 = diffusion coefficient, V= value of hexane (ml) and W = weight of CPO
sample (g).
Calibration parameters and prediction model
PLS regressions were fitted to describe therelationship between dependent variables (DOBI andcarotenoids in CPO samples) and Raman or NIR
spectra using a multivariate statistic program (theUnscrambler 9.7 version). The calibration models
were developed from the 126 spectra of all CPO
samples. PLS calibrations were fitted using the PLS1 method. Model validation was performed using thefull cross validation method. The number of latentvariables (factor) adopted for each model was
suggested by the statistical program.
The statistical results of PLS models built using
original and pretreated spectra were compared using
MSC (multiplicative correction), SNV (standard
normal variate), 1D (first derivative), and 2D (second
derivative).
The criteria for selection of the prediction model
included: factor-number of latent variables;
correlation coefficient of calibration (Rc); coefficientof determination of calibration (Rc2); root meansquare error of calibration (RMSEC); correlation
coefficient of calibration (Rc); coefficient ofTable 1 Distribution of DOBI and carotenoids
content in crude palm oil samples
Parameters
DOBI
Carotenoids

Min.
0.07
2.79

Max.
2.09
539.79X
0.87
191.02SD
0.50
121.96

Spectra analysis
Carotenoids are a group of tetraterpenoids
consisting of isoprenoid units. Double bonds incarotenoids are conjugated forms and usually are alltrans forms. CPO is a source of carotenoids, having
60% β-carotene and 40% α-carotene [6]. Fig. 1 andFig. 2 show Raman spectra and NIR spectra for the
DOBI and carotenoids content determination,
respectively.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Raman spectra

combination of bands and the first overtone of the CH of methylene of the aliphatic group of oil and thesecond overtone being observed at 8,211 cm-1 [15].
The bands at around 4,655 and 4,535 cm-1 may be
attributed to combination bands of C-C and C-Hstretching vibrations of cis-unsaturated fatty acids,
and at 7,058 and 7,139 cm-1 are attributed to a C-H
combination band of methylene [11]. Quantitative
analysis of carotenoids by FT-Raman was based on
the trans-CH=CH-functional group but thischaracteristic band did not exist in the NIR region [9].
In the current research, the best conditions for NIR
spectra pretreatment were in the wavenumber range
between 5,500 and 4,600 cm-1 (Fig. 2 (b)) where there
were strong correlations.

Figure 1 (a) compares spectra between theextracted CPO from ripe and under-ripe oil palm
fruits. The spectra show the C=C stretching vibrationof carotenoids with a dominant signal observed in therange 1,500-1,550 cm-1; the position of this band
depends on the ripeness of the oil palm fruit. At 1,168cm-1 the C-C group with the C-CH3 of carotenoids ispresented. The two wavenumber positions of the
carotenoids are characteristic of the spectrum of the
β-carotene standard (Fig. 1 (b)). In the spectrum ofthe β-carotene standard, the characteristic bands havethree main peaks which are located at 1,512, 1,154,
and 1,004 cm-1. These wavenumber positions arecorrelated with the wavenumbers of the polyene chain(C=C), C-C coupled with C-CH3, and C-C stretchingof carotenoids, respectively [9] – [14]. At otherpositions in the CPO, 1,442 and 1,656 cm-1 arecorrelated with the wavenumbers of CH2 or CH3
deformation of fatty acid or triglyceride, and C=C
stretching of unsaturated fatty acid or triglyceride,
respectively.

Fig. 2 Comparison between NIR spectra of CPO fromripe and under-ripe palm fruits, 12,500-4,000
cm-1 wavenumber (a), and 5,500-4,600 cm-1
wavenumber (b).
Calibration and cross-validation results
Fig. 1 Comparison between Raman spectra of CPO
from ripe and under-ripe palm fruit (a), and βcarotene spectrum (b).

Raman analysis
The precision calibration models can be checkedusing the cross-validation method. The model wascalibrated using different mathematical treatments ofspectra, selected by the variable uncertainty test used
for the validation method. The criteria for best model
selection were the highest R2 and RPD, and the lowest
RMSEP. MSC pretreatment was the best method forall spectral improvement and this model can predictthe carotenoids content in CPO. The statistical resultsof the prediction model were 0.94 for Rv, 0.88 for Rv2,
40.65 ppm for RMSEC, and 3.25 for RPD. RPD is
calculated from the ratio of the standard deviation of

NIR spectra
The NIR region was more difficult to explain
mainly because of the extensive band overlapping due
to overtones and combinations of fundamental
vibrations involving hydrogen stretching modes.
However, it was possible to predict the DOBI andcarotenoids content in CPO. Fig. 2 (a) shows thecomparison of NIR spectra between the extracted
CPO from ripe and under-ripe palm fruits. The results
indicated that the spectra had the same patterns, withthe bands at around 5,789 and 5,681 cm-1 due to the238

SEE - Nagoya, Japan, Nov.12-14, 2018

cm-1 range for spectral samples pretreatment. The
results indicated that the PLS model built using the
1D method was the best model for carotenoids and
DOBI determination. The data on the carotenoids
content and DOBI following analysis using theUnscramble program showed very low contents(2.79-537.79 ppm for carotenoids and 0.07-2.09 forDOBI) and the regression of carotenoids showed awavelength of 5,276 cm-1 (Fig. 5 (b)) which is near
the 5,263 cm-1 of H-O-H stretching and bending
vibrations of water [13]. Therefore, the amount ofcarotenoids, the DOBI, and the amount of water
affected measurement using FT-NIR.

the data to RMSEC thus providing a ratio of theperformance to the deviation. Hence, the highest RPD
value indicates the best method too. In the DOBI
prediction model, the SNV pretreatment was the best.
The statistical results of the prediction model were0.76 for Rv, 0.57 for Rv2, 0.31 for RMSEP, and 1.92
for RPD using the cross-validation method.
Figure 3 (a) and Fig. 3 (b) show the MSC-Raman
spectra for carotenoids and the SNV -Raman spectra
for DOBI, respectively. In the 400-2,300 cm-1
wavelength range of the Raman spectra, the results
showed broad bands around 1,100 and 1,500 cm-1 dueto the C-C group with C-CH3 and C=C stretching of
carotenoids [7] – [9], [12] – [13], [15]. Bothwavenumbers were significant for carotenoids
determination and they were clearly confirmed withthe regression coefficients in Fig. 5 (a). The otherpositions, around 1,400 and 1,600-1,700 cm-1 havebeen assigned to the fatty acid or triglyceride.

Fig. 4 1D NIR spectra pretreatment of crude palm oil
on DOBI and carotenoids.

Fig. 3 Raman spectra pretreatment of crude palm oil
on carotenoids and DOBI, carotenoids- MSC(a), and DOBI-SNV (b).
FT-NIR analysis
Fig. 5 Regression coefficients of the MSCpretreated PLS model measured using Raman(a) and the 1D-pretreated PLS model
measured using FT-NIR (b) on carotenoids
content in the extracted crude palm oil frompalm fruits

The calibration models using cross validation for
carotenoids and DOBI determination in CPO where
all samples were measured using FT-NIR. The 1D
pretreatment using the Gap-Segment method was thebest method for improvement of CPO spectral basefor carotenoids and DOBI. The statistical results for
carotenoids were 0.71 for Rv, 0.50 for Rv2, 86.70 ppm
for RMSEP, and 1.63 for RPD. In the DOBI
prediction, the 1D pretreatment by the Gap-Segment
method was the best method. The statistical results
were 0.80 for Rv, 0.64 for Rv2, 0.29 for RMSEP, and1.72 for RPD.
Figure 4 shows the NIR spectra in the 5,500-4,600

CONCLUSION
Raman
and
FT-NIR
techniques
areenvironmentally friendly, use no solvent, and provide
rapid measurement which is required for industrial
239

SEE - Nagoya, Japan, Nov.12-14, 2018

application. The results showed that Raman
spectrometry was better than the conventional
method and FT-NIR spectrometry. Raman provided
good DOBI and carotenoids determination in CPO
and provided clear carotenoids determination ataround 1,100 and 1,500 cm-1 in CPO. Raman was
better at measuring both parameters than FT-NIR,
although the concentration of carotenoids was very
low. In addition, model development has to beextended with calibrations using more samples ofpalm fruits obtained from many locations, in different
seasons, and for different species to ensure maximum
accuracy of analysis.

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Comparison of FT-Raman, ATR-IR, and NIR
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Near Infrared Spectroscopy Models, J. Near.
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and Ozaki Y., A Feasibility Study on Nondestructive Determination of Oil Content in Palm
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ACKNOWLEDGEMENTS
We would like to thank the Oil Palm Technology
Development for Local Commercial Biodiesel
Industry in Newly Planted Area Project in the Facultyof Agriculture of Kasetsart University, Thailand for
raw material support. We also would like to thank the
Graduate School of Bioagricultural Sciences, Nagoya
University, Japan, the Bruker Company, Japan, andthe Center of Excellence Oil Palm, Kasetsart
University, Thailand for partial support of thisresearch.
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Agricultural Exports and Imports, 2011.
[2] Swoboda P.A.T., Bleachability and the DOBI,PORIM Bulletin. 1982. 5: 28-38.
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Constituents of Commercial Red Palm Olein:
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[4] Choe E. and Min D.B., Mechanisms and Factors
for Edible Oil Oxidation, Compre. Rev. Food Sci.
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[7] Baranska M., Schultze W. and Schulz H.,240

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE USE OF FISH AGGREGATING DEVICES (FAD’S) TO REDUCE
DESTRUCTIVE FISHING IN PACITAN COASTAL INDONESIA
Tuty Handayani1, Cinthia1, Jarot Mulyo Semedi1 and Sajiharjo Marto Suro2
1
Unversitas Indonesia, Indonesia; 2 STT-PLN, Indonesia

ABSTRACT
Pacitan regency is located on the south coast of East Java Province, Indonesia. The Pacitan coastal
regions consist of a bay and open sea. The number of the populations who work as fishermen as many as 7228
people. Mostly they catch fish in Pacitan Bay. Initially, there were some fishermen who carry out fishing bydestructive methods such as using bombs and poisons. Fish Aggregating Devices (FADs) are tools that helps
fishermen to increase their catch in a definite location. The purpose of this study was to determine how big theuse of FADs so as to reduce destructive fishing and the possibility of FADs placement area development in
Pacitan coastal. The research method was done by using interview technique to fishermen for fishery production
with and without FADs. While for observing the development of FADs, GIS Techniques and Remote Sensing
were used. To obtain the suitability of FAD’s location, NOOA and Landsat 8 Images were used, with parameterssuch as sea surface temperature, salinity, current, brightness and chlorophyll-a. The depth was obtained from thebathymetry map. The results showed that FAD’s greatly increased production up to 200%, accompanied by anincrement in the quality of fish. However, due to the location of FADs in the open sea. needed a modern fishingequipment, so that only about 20% of fishermen take advantage of FADs. Nevertheless the arresting
destructively method has decreased. The development of FADs can be done at suitable area, about 70% of
Pacitan coastal about 12 miles from the coast line.
Key word : Fish Aggregating Devices (FADs), Destructive fishing, Suitable area

tons / year with average fish utilization rate of
49.48%. The condition of fish utilization in the area
is still below the allowable catch amount of 80% [2].
MSY values for tuna species (yellow fin tuna andlarge eye tuna) in the southern waters of East Javaare estimated to be around 2,568 tons / year with autilization rate of about 78.81% .
The Pacitan Regency Government [1] throughthe Office of Marine and Fisheries introduced theuse of Fish Aggregating Devices (FADs) tofishermen in early 2005, as well as bringing ships
measuring above 30 GT with a seine fishing gear.
Fads installed by fishermen Pacitan is a type of fixedrumpon (CTF 2014) installed in waters with a depthof 1,500-5,500 meters, so it is classified as deep sea
rumpon.
The use of FADs as a tool for collecting fish infishing activities has proven able to increase
production and productivity of catch in Pacitan
Regency. Production of catches in this district prior
to the use of FADs is only 500 tons. The use of
FADs increased production to 1,560 tons in 2005
and continued to increase in the following years toreach 7.823 tons in 2013.
This encourages fishermen to install new Fads sothat the number of fishing FADs installed by more
and more. By 2015 Pacitan fishermen have begun tocomplain that as more FADs are installed in thewaters, their catch is declining. The size of the fish

INTRODUCTION
The exploration of fish resources in the waters ofPacitan by local fishermen mostly located around thecoast and using traditional fishing facilities ofvarious shapes and types. Fishing activities in
Pacitan Regency until 2004 were dominated byboats without engines and boats under 10 GT insizes with outboard motors. The ships are equippedwith fishing gear, gill net, and fishing line that only
operate in coastal waters up to 3 miles from thecoast. The fishermen’s catch usually only small
pelagic fishes with low economic value such asmackarel tuna, scads, beltfish, and anchovies [1].
Although the production of fisheries is not much,
but from year to year the number of fishing fleets isincreasing, especially boats with engines. To
increase the production, there are fishermen that use
catching methods that tend to damage theenvironment, such as the use of potassium andexplosives, or placing nets and anchors carelessly.
That causes environmental damage is inevitable.
According [2] Pacitan off-shore sea is rich inresources of large pelagic fish such as skipjack andtuna. The utilization rate of pelagic fish resources inthese waters is still below the maximum potential of
its sustainability. The value of maximum
sustainability yield (MSY) of pelagic fish in theSouth of East Java in 2009- 2013 was 219,189,453
241

SEE - Nagoya, Japan, Nov.12-14, 2018is also smaller, so the selling price is low. For that
we need to find the location of something for the
expansion of FADs. So that the new installation does
not decrease production.
RESEARCH OBJECTIVES
1. Search for a suitable location for expansion of
FADs
2. Knowing the readiness of traditional fishermen
using FADs to reduce destructive fishing.
METHOD

Traditional fishermen with small incomes andactivities that often disturb the environment, areexpected to be larger incomes and leave the way oflooking for a tie that tend to be distruktif. For thatneed to find new locations to be used as a place to
put Fads. Remote Sensing Techniques can help findthe location.

Pacitan regency is located on the south coast of
East Java. Overlooking the Indian Ocean. lies on1100 55 '- 1110 25' east and 070 55 '- 080 17' LS.
The Pacitan coastal region consists of bays and open
seas. On the coast of Pacitan residents who work as
fishermen as many as 7228 people[1].

Figure 2. Research framework
Methode of Collection and Data Analysis
To describe the data to find a suitable location for
Fads development site, two ways are done with
Landsat 8 and NOOA Image. [5]Various oseaografi
variables such as temperature, salinity, current
velocity, turbidity and depth using Landsat image 8.
As for chorophyl using NOOA image, with wider
coverage. To find out the pH is done by taking water
samples around the Fads location. By using GPS, thesampling location is marked.
To find out the readiness of local fishermen to
move from traditional fishing gear to Fads,
interviews were conducted. The sampling frame
consists of the traditional fishermen born in Pacitan,
the head of the household, may be the owner of theship or just as a worker. The selection of
respondents was done by technical random samplingfor 30 traditional fishermen.[4]Fig.1. Resarch Site
This research was conducted along the Pacitan
seaport. Includes Pacitan bay. In Pacitan Bay there
are no Fads, but on the bay there is Fishery Port ofTamperan Beach, Fish Landing Base accompanied
by Fish Auction Place, Teleng and traditional
Plumbung fish landing. Plumbung is one of 17
traditional fish landing sites.[4] The Tamperan
Fisheries Port, a modern port, is very importantbecause it is a landing and fish trade place thatcomes from Fads.
Research Framework.
There are two types of fishermen catch in Pacitan
local residents who generally do the traditional andmodern way, utilizing Fads. Fishermen of Fads are
not only local Pacitan titles but also from outside
Pacitan

To obtain the conformity region, data analysis
uses overlay techniques. As for knowing the
preparedness of traditional fishermen using Fads as atool to find fish, conducted by descriptive analysis.

242

SEE - Nagoya, Japan, Nov.12-14, 2018the ocean color product satellite sensors including
the Sea-viewing Wide Field-of-view Sensor(SeaWiFS), the Moderate Resolution Imaging
Spectroradiometer (MODIS), and the Visible
Infrared Imaging Radiometer Suite (VIIRS) on theSuomi National Polar-orbiting Partnership (SNPP)
and the Joint Polar Satellite System (JPSS), as wellas various satellite sensors from other countries(https://www.star.nesdis.noaa.gov/sod/mecb/color/).
Figure 1 shows the spatial temporal pattern ofchlorophyll-a concentration of Pacitan Regency
Coast during the west monsoon season (October –April).
The image from NASA ocean color data wereselected based on the lowest cloud cover during west
monsoon season.[5] The spatial pattern of thechlorophyll-a concentration shows that by time thehigh concentration are moving more closer to thecoastline. This phenomena also explained why
fisherman cannot sail to the open seas, it is becauseof the chlorophyll-a concentration are very low
towards the ocean. The west monsoon also called bya rainy season where the ocean waves are high andwill give a high risk for fisherman to sail.

In the overlay technique of each layer the resulting
map is given scores as follows in table 1.
Table 1 Water Suitability Requirements for Fads
Parameter Very
Suitable
Not
Suitable
Suitable
Velocity
0.01- 0.1
0.1-0.5>0.5
of current
Depth100-500
100 - >30 <30
Turbidity<5
5 – 15>15
Temperate
14.358.35-14.35 <8.35
20.35
30-34
Salinity
30-34
7.95-8.2>34
pH
7.95-8.2<7.95
Source : Modification from [6]

RESULT AND DISCUSSION
Expansion Area of Fads
Suitability of Oceanographic parameters withlandsat 8.
The suitability of oceanographic parameters in
Pacitan Bay indicates that most of the bay area isless suitable for Fads.[5] Although chlorophyl
concentrations are quite high, the production is low.
This is because Pacitan bay is also used for 30 GTsized vessel traffic carrying catches from Fads toTamperan Fish Port and there are tourist sites inTeleng. Fishermen who used the ships with a GT
motor. Fish landing used besides TPI Teleng also
PPI Lumbung.[3]The suitability of the Landsat data.
From Image Processing results downloaded fromhttps://www.usgs.gov/ and sampling pH at sea
Pacitan show, in terms of Salinity, turbidity, current
velocity and pH of almost entire sea in Pacitan
suitable for Fads. Based on the edge depth is notsuitable for deep sea fads. However, the chorofilabundance at the high edges, making it suitable forsimple shallow sea fads. The temperature parameter
indicates that there is a less suitable area. The
statements of the overlay analysts show like fig, 4,
below:

Suitability with NOAA Satellite Imagery

Fig. 3. Chlorophyll-A concentration of Pacitan
Regency coast during west monsoon season(source: Ocean color data, NASA OB.DAAC)
Fig.4. The suitability of the location for the
expansion of Fads

NOAA Satellite Applications and Research,
NOAA STAR) which is part of NOAA’s Satellite
and Information Service (NESDIS) are managing
243

SEE - Nagoya, Japan, Nov.12-14, 2018

At this time at sea off Pacitan, deep Sea Fads are
installed at locations between latitudes 8oLS to
10oLS. Each Ships and Tonda Fishing Line install 35 Fads at each point. Until 2013 it is estimated that
there are 250 units of Fads installed by fishermen,
mostly fishermen, who are based in VAT tamperan[1]
The advantages of using FADs
Fig.5. The reason remains a traditional fisherman

Fishing vessels / boat in Pacitan based on usedmachine is divided into boat without motor (PTM),
outboard motor boat (PMT), and motor boat (KM).
Boat without motor is only 6%.[8] PMT dominates
the number of fishing vessels in Pacitan Regency asmuch as 1 240 units or 84 percent. While the motor
boat size 30 GT or more as much as 10%.
Tradiisonal fishermen use boats under 10 GT, as
they only fish up to 4 miles. Motorboats are mostly
owned by fishermen from outside Pacitan. The
engine power used illustrates the range of fishing
operations. [7]explains that fishing gear used bysmall-scale fishermen is generally passive, selective,
and used and adapted to specific seasons.

The narrower the fishing ground and theincreasing number of fishing boats, the destructive
fishing is still happening. Although the current
destructive fishing form is no longer the case withBlast. They are already aware that the blast isdamaging the environment. But what can not be
avoided is in the operation of fishing gear is often
negligent. Both from how to throw anchors, crashingreefs, or using the eyes of a wide net. It is done
because it has to compete to get adequate production.
The hope that if you have a simple Fads, then the
negligence that is destructif fishing is declining.

Traditional fishing boats and fishing gear using
vessels cost 4000 USD [8] 70%, using vessels
costing 18,000 USD as much as 20%, and only 10%
using vessels cost 36,000 USD. With a daily charge
per trip averages 25 USD ranges from 25 USD - 40
USD. As for fishermen who use FADs, the vessels
owned worth more than 100,000 USD with theexpenditure of 1 trip, for 10 days about 7000 USD 85 USD. Using the Productivity tool approach is
calculated by the Setyorini equation in [2] namely:

CONCLUSION
1. The results show that using FADs greatly
increases the production up to almost 10-fold,accompanied by an increase in the quality of fishthat is the number of large pelagic fish that catch.
2. Pacitan fishermen only about 20% utilize
Fads in pairs in the deep sea. However, thedestructive arrest has been greatly reduced.
Fishing ground Pacitan bay which is in shallow
sea utilized by fisherman with traditional boat.
Fads Fumps location development can be done in
about 70% of Coastal Pacitan. On a shallow
coast 4 miles away, simple Fads can be installed
at low cost for traditional fishermen∑∑

The results shown that the average productivity
increased 10 to 12 times when using Fads.
ACKNOWLEDGEMENTS
Benefits of FADs on local fishermen
The research work reported in this paper was
funded by PITTA Grant No. 2326/UN2.R3.1/HKP.05.00/2018 Universitas Indonesia (UI).
Thank to directorate Research and Community
Service Universitas Indonesia also my sudents in
Hibah Pitta group

From the results of spatial analysis of the
expansion area of Fads, shows most of the Pacitan
waters are very suitable. But the fact is there aremany local fishermen who do not utilize Fads
technology. The reasons are mostly due to large
capital, expensive operational costs, long distancesthat must be at sea up to 10 days and some people
feel they can not follow the technology. The results
can be seen as Figure below

244

SEE - Nagoya, Japan, Nov.12-14, 2018[5] Martin. Seelye.An Introduction to Ocean Remote
Sensing.
2014TJ
International
Ltd.
Padstow.Cornwall. UK

REFERENCE[1].Laporan Statistik Perikanan Kabupaten Pacitan
Tahun 2014. DKP Dinas Kelautan dan Perikanan
Kabupaten Pacitan DKP 2015.

[6]Pradipta Gede Yatha. Sistem Pengambilan
Keputusan Penempatan Rumpon Laut.Institut
Teknologi Bandung, 2014 p16-18[7]Kurien J. Overcapacity, overfishing andsubsidies: howdo they relate to smallscale
fisheries? In: Presented at the 8th Pacific Rim
Fisheries Conference 2006., Hanoi, 22–24
March.
[8] Rully Indra Taruna . Konstruksi Kapal Perikanandan Ukuran ukuran Utama Dalam Penentuan
Konstruksi Kapal. Universitas Pajajaran. 2012. P
45-51[9]Handayani, Tuty. Youth Education in SelfPreparing as Marine Ecotourism Guide in
Kepulauan Seribu.] 1st Internasional conferenceo Geography Education. Malang Indonesia. No.
29.10.3/UN32.7/DL/2016. P 3-2[2] Muhamad RE. Prayitno1,Domu Simbolon, Roza
Yusfiandayani, Budy Wiryawan Produktivitas
Alat Tangkap yang dioperasionalkan di Sekitar
Rumpon Laut Dalam. Marine Fisheries Vol. 8,
No. 1, Mei 2017 Hal: 101-112[3] Mohammad Rizal Kurniawan,
Daduk Setyohadi, Gatut Bintoro Pengaruh
Pemasanagn Rumpon Pada musim Barat
Terhadap Hasil Tangkapan. Alat Tangkap
Payang.PSPK Student Journal, VOL. I NO.
Universitas Brawijjaya pp 16-20 =15 May 2013[4]Yusuf Fathanah.Analisis Karakteristik Perikanan
Tangkap Skala Kecil di Kabupaten Pacitan.IPB
Bogor. .2014 p 8-8

245

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ANTIMICROBIAL RESISTANCE IN SALMONELLA ISOLATEDFROM BEEF IN UPPER NORTHEASTERN THAILAND
Natthamon Tangjitwattanachai1 and Denpong Sakhong2
Division of Animal Science, Faculty of Technology, Mahasarakham University, Thailand
2
Veterinary Research and Development Centre (upper northeastern region), Department of Livestock
Development, Thailand
1

ABSTRACTThis study investigates the distribution of Salmonella serotypes, antimicrobial susceptibility and patterns ofmultidrug resistance of Salmonella spp. isolated from beef, received from different slaughterhouses and butcher
shops in Upper Northeastern Thailand. Amongst the beef samples, one hundred and forty-five isolates was
detected. There are three serogroups of salmonella which can be classified into eight serovars; five serovars
belonging in three serogroups were contaminated on meat from slaughterhouses, likewise, seven serovars which
included two serogroups were detected from butcher shops; by which, 12.50 % (32/145) of the salmonella strains
was resistant to antimicrobial agents and almost 6.89 % (10/145) were multidrug resistant. The most multiresistant
serotype was Salmonella Derby, with a pattern of multi-resistance to six antibiotics, followed by S. Rissen, S.
Anatum, and S. Muenchen, respectively. Moreover, the most of salmonella strains were resistant to ampicillin,
oxytetracycline and sulfamethoxazole/trimethoprim, whilst, colistin, gentamicin, kanamycin, nalidixic acid, andnorfloxacin are considered highly susceptible drugs. In summary, beef from the local slaughterhouses and retailbutcher shops in Upper Northeastern Thailand, was found to be contaminated with Salmonella spp., notably, fromthe serogroups B, C and E, which are multidrug resistant. For this reason, veterinarian and all relevant authorities
need to strictly regulate the use of antibiotics in animal production, whether for use as therapy, prophylaxis, or
growth promotion.
Keywords: Antibiotics, Contamination, Drug-resistance, Salmonella spp.

[3]. The processes during the pre-slaughter, slaughterand the storage period after slaughter are suitable forcontamination of pathogenic salmonella, which cancause serious diseases in humans and animals. Thus,
the purpose of this study was to investigate the
distribution of Salmonella serotypes, and Salmonella
spp. that are resistant to antibiotics, which has
contaminated beef from difference slaughterhouses
and which available for purchase in a retail butcher
shops in Upper Northeastern Thailand.

INTRODUCTION
Antimicrobial resistance is a public healthproblem throughout the world, and causes increased
morbidity and mortality among humans and animals.
If not strictly regulated, the application of antibiotics
delivered to animals for therapy, prophylaxis, or
growth promotion/feed efficiency in domestic
livestock, can potentially lead to widespreaddissemination of antimicrobial-resistant bacteria. The
antibiotics resident in animal products may be
harmful or provide an antibiotic-resistant bacteria
from animals to the consumer, and lead to increase apathogenic resistance to antibiotics, becoming areservoir of resistance genes for pathogenictransmission in and between microorganisms andspread into humans through various routes [1, 2].
Salmonella as a foodborne pathogen in animal
products, is a major cause of human salmonellosis
and food poisoning. They are common inhabitants on
the intestinal tract of humans and mammals, which
can be distributed in the environment andcontaminate the food chain in the process of foodproduction. Normally, humans are infected by eatingor touching an infected animal or their faeces, inparticular, during the processing of meat production

MATERIALS AND METHODS
A total of 145 beef samples were taken from local
slaughterhouses and a retail butcher shops within 12
provinces of the Northeastern Region of Thailand, foranalysis of Salmonella spp. contamination andresistance to antimicrobial drugs.
Isolation and Identification
Salmonella were isolated from beef samples bystandard methods [4]. Briefly, a beef sample wasminced, then 225 ml sterile Buffered peptone water(BPW) was added into 25 g minced sample, this was
incubated at 37±1°C overnight. After that, the pre246

SEE - Nagoya, Japan, Nov.12-14, 2018enriched cultures were transferred to two enrichment
media; Rappaport Vassiliadis (RV) was incubated at
41.5±1°C for 24±3 h and Muller-Kauffmann
tetrathionate novobiocin broth (MKTTn) was
incubated at 37±1°C for 24±3 h. Subsequently, theenriched cultures from RVS and MKTTn weretransferred to Xylose lysine desoxycholate agar
(XLD) and Brilliant green agar modified (BGM) wereincubated at 37±1°C for 24±3 h. Then, pick a pinkcolony with or without black centres with sterile
inoculating loop are selected and inoculated to the
Nutrient agar (NA) then incubated at 37±1°C for
24±3 h. Subsequently, the samples were
biochemically tested on Triple sugar iron agar (TSI),
L-lysine decarboxylation medium (LIM), Urea agar,
VP medium incubated at 37±1°C, 24±3 h, and ONPG
disc incubated at 35±1°C, observed every 1 h for 6 h
to identify the species of salmonella resign asserotypes. The slide agglutination test was carried out
by slurry agglutination test somatic-antiserum
specific for O-antigen on slides, read reaction results,
sedimentation and serotyping by culture on swarm
agar. The flagella-antiserum is specific for H-antigen
on slides and reads the precipitation reaction. The
results of the tests were compared with antigenic
formulas of the salmonella serovars according to
Kauffmann-White Scheme [5, 6].

Upper Northeastern region of Thailand were included
for determination of Salmonella spp. prevalence.
The results as shown in Table 1, indicated that, a
total of sixteen samples (11.03 %) detected
Salmonella spp., nine samples (14.06 %) were fromslaughterhouses and the other seven samples (8.64 %)were from butcher shops. There were five serovars
from three serogroups in contaminated meat fromslaughterhouses and seven serovars, which included
two serogroups, were detected from butcher shops.
Notably, only S. Derby was found in beef from aslaughterhouse iner Roi-Et province. In addition, S.
Kouka and S. Okefoko were detected in beef from abutcher shop in Sakon Nakhon province only. The
serovar S. Lexington was found in beef from thebutcher shop in Nakhon Phanom only. Furthermore,
the most prevalent serovars was S. Weltevreden(4.68 %), followed by S. Rissen (2.07 %), S. Anatum(2.07 %) and S. Muenchen (1.38 %), which is same
serotypes as [8]. The presence of Salmonella spp. inbeef suggests poor hygiene management. Salmonella
is commonly found in the animal gastrointestinal tract,
therefore food contamination with this pathogen
could happen throughout the food chain. This study
was found Salmonella spp. contamination in beefcarcasses (11.03 %) much less than in previous
reported [8] which found a prevalence of 52 %(28/54) in beef samples and included Thai selfservice style restaurants in Khon Kaen municipality,
Thailand.
When comparing the rate of Salmonella spp
contamination in beef between a slaughterhouse andretail butcher shop, there are no statistically significant
differences. This shows that the transportation from thelocal slaughterhouse to the butcher shop, including
the preservation and deliver to the butchers shop, arecarried out hygienically. The production of Thai beef
is in the process of developing into a standard, wheremost slaughtering is carried out in a local, municipal
slaughterhouses or private slaughterhouses that are
certified by the Department of Livestock Development.
Most slaughterhouses now operate to a good standardof practice.
However, some local slaughterhouses still operatewith poor hygiene and meat is usually delivered inopen buckets in a cars. Typically, meat in butcher
shops are sold at ambient temperatures, this indicatesthe application of strict hygiene practices is therefore
essential. The regulatory authorities should control
policy for a good manufacturing practice for cattle
abattoir’ together with stringent sanitation in fresh
meat production.

Antimicrobial susceptibility testing
Salmonella isolates were tested for antimicrobial
susceptibility by disk diffusion method andinterpreted according to standards established by theClinical and Laboratory Standards Institute (CLSI,2008), E. coli ATCC 25922 were used as a quality
control strain. The following antimicrobial were
tested: amoxicillin/clavulanic acid (AMC) 20/10
μg/mL, ampicillin (AMP) 10 μg/mL, cephalothin(KF) 30 μg/mL, chloramphenicol (C) 30 μg/mL,
ciprofloxacin (CIP) 5 μg/mL, colistin (CT) 10 μg/mL,
enrofloxacin (ENR) 5 μg/mL, gentamicin (CN) 10
μg/mL, kanamycin (K) 30 μg/mL, nalidixic acid(NA) 30 μg/mL, neomycin (N) 30 μg/mL,
norfloxacin (NOR) 10 μg/mL, oxytetracyclin (OT) 30
μg/mL, streptomycin (S) 10 μg/mL, sulfamethoxazole/
trimethoprim (SXT) 1.25/23.75 μg/mL and tetracycline(TE) 30 μg/mL. The diameter zone of growth
inhibition surrounding the paper disk is measured andcompared to the standard inhibition diameter [7].
RESULTS AND DISCUSSION
Salmonella contamination in meatslaughterhouses and butcher shops.

fromOne hundred and forty-five samples thatoriginated from beef carcasses at sixty fourslaughterhouses and eighty one butcher shops, in the247

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Prevalent of Salmonella serotypes obtained from beef carcasses in slaughterhouse and butcher shop
Number of positive samples (%)
Salmonella spp.

Group B
S. Derby
Group CS. Muenchen
S. RissenGroup E

Slaughterhouse

Butcher shop

Total

(n=64)(n=81)(n=145)

1 (1.56)
1 (1.56)
3 (4.69)
1 (1.56)0 (0.00)0 (0.00)
2 (2.47)
1 (1.23)

1 (069.)1 (0.69)
5 (3.45)
2 (1.38)

2 (3.13)

1 (1.23)

3 (2.07)5 (7.81)

5 (6.17)

Provinces*

Roi Et(Sh:1)
Roi Et(Bs:1), Sakon Nakhon(Sh:1)
Roi Et(Sh:1), Sakon Nakhon(Bs:1),
Khon Kaen(Sh:1)

10 (6.90)

S. Anatum

2 (3.13)

1 (1.23)

3 (2.07)

S. Kouka
S. Lexington
S. Okefoko

0 (0.00)0 (0.00)0 (0.00)

1 (1.23)
1 (1.23)
1 (1.23)

1 (069.)1 (069.)1 (0.69)

Kalasin(Sh:1), Maha Sarakham(Bs:1),
Roi Et(Sh:1)
Sakon Nakhon(Bs:1)
Maha Sarakham(Bs:1)
Sakon Nakhon(Bs:1)

S. Weltevreden

3 (4.68)

1 (1.23)

4 (2.76)

Kalasin(Sh:1), Maha Sarakham(Bs:1),
Sakon Nakhon(Sh:2)

9 (14.06)

7 (8.64)

16 (11.03)

Kalasin, Khon Kaen, Maha Sarakham,
Sakon Nakhon, Roi Et

Total* Sh=Slaughterhouse; Bs=Butcher shop
It is astonishing to observe the isolates resistant tochloramphenicol, in spite of the fact that the drug has
been forbidden use in food-producing animals. It wassuggested that this phenomenon may be generated byother antibiotics on co-selection or cross-resistance.
[11]. This suggests that the removal of certain
antimicrobial selections may not completely
eliminate AMR and be a transfer of resistance to otherimportant human pathogens.
As shown in Table 3, nine salmonella isolates
were classified with six antimicrobial resistancepatterns, which were resistant to three, four and six
antimicrobial agents. The most common resistancepatterns were AMP-OT-S-TE and AMP-OT-TESXT, whereas the highest number antimicrobial
resistance pattern is AMP-C-CIP-OT-SXT-TE.
Similar results have been reported recently too [12].
The previous survey showed that the resistancepattern of isolated salmonella contaminated withpork, identified as multidrug resistant and the mostresistance pattern was AMP-TE-SXT. Whereas
chloramphenicol is the one antibiotic agent found in
the resistance pattern, like in accordance with thoseof this study. For this reason, veterinarian andrelevant authorities need to regulate the use ofantibiotics in animal production strictly, whether for
disease treatment, prevention, or growth promotion.

Antimicrobial susceptibility testing results wereisolated from beef showed that 12.50 % of isolates
were resistant to at least one antimicrobial agents and25.00 % were multi-drug resistant. Resistance rate toamoxicillin/clavulanic acid, ampicillin, cephalothin,chloramphenicol, ciprofloxacin, oxytetracycline,
streptomycin, sulfamethoxazole/trimethoprim andtetracycline were 6.25 %, 43.75 %, 6.25 %, 6.25 %,6.25 %, 43.75 %, 12.50 %, 43.75 % and 31.25 %,respectively. (Table 2).
These antibiotics residues in meat are present infarmed animals being treated under veterinary
control. The presence of these antibiotic residues inmeat may be due to the short withdrawal period
before slaughtering or prolonged courses ofantibiotics. The misuse of antibiotics may lead to thedevelopment of drug-resistant salmonella. Besides
this, resistant salmonella present in meat, may betransmitted to consumers and be the cause of poor
response of treatment with human medicines.
Likewise,arecentreport[9].
foundamoxicillin/clavulanic acid, ampicillin, cephalothin,chloramphenicol, ciprofloxacin, oxytetracycline,
streptomycin, sulfamethoxazole/trimethoprim andtetracycline are used in human medicine too [10].

248SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Antimicrobial susceptibility of Salmonella spp. isolated from beef by disk diffusion methods

Antimicrobial disk

Group B
(n=1)

Number of antimicrobial susceptibility*
Group CGroup E(n=5)
(n=10)

S
I
R
S
I
1
0
0
3 1
AMC (20/10 µg)
0
0
1
1 0
AMP (10 µg)
1
0
0
3 1
KF (30 µg)
0
0
1
5 0
C (30 µg)0015 0
CIP (5 µg)
1
0
0
5 0
CT (10 µg)
0
1
0
5 0
ENR (5 µg)
1
0
0
5 0
CN (10 µg)
1
0
0
5 0
K (30 µg)100
5 0
NA (30 µg)
0
1
0
2 3
N (30 µg)
100
5 0
NOR (10 µg)
0
0
1
2 0
OT (30 µg)
0
1
0
2 1
S (10 µg)
SXT (1.25/23.75
0
0
1
2 0
0
0
1
4 0
TE (30 µg)
7
3
6
59 6
Total
* S = sensitive, I = intermediate, R = resistant

R
1
4
1
0
0
0
0
0
0
0
0
0
3
2
3
1
15

S
10
8
10
10
10
10
10
10
10
10
7
10
7
8
7
7
144

I
0
0
0
0
0
0
0
0
0
0
3
0
0
2
0
0
5

R
0
2
0
0
0
0
0
0
0
0
0
0
3
0
3
3
11

Total (%)
(n=16)SIR
14 (87.50)
1 (6.25) 1 (6.25)
9 (56.25)
0 (0.00) 7 (43.75)
14 (87.50)
1 (6.25) 1 (6.25)
15 (93.75)
0 (0.00) 1 (6.25)
15 (93.75)
0 (0.00) 1 (6.25)
16 (100.00)
0 (0.00) 0 (0.00)
15 (93.75)
1 (6.25) 0 (0.00)
16 (100.00)
0 (0.00) 0 (0.00)
16 (100.00)
0 (0.00) 0 (0.00)
16 (100.00)
0 (0.00) 0 (0.00)
9 (56.25) 7 (43.75) 0 (0.00)
16 (100.00)
0 (0.00) 0 (0.00)
9 (56.25)
0 (0.00) 7 (43.75)
10 (62.50) 4 (25.00) 2 (12.50)
9 (56.25)
0 (0.00) 7 (43.75)
11 (68.75)
0 (0.00) 5 (31.25)
210 (82.03) 14 (35.84) 32 (12.50)

Table 3 Patterns of multidrug resistance of Salmonella spp. isolated from beef receiving difference slaughterhouse andbutcher shop
Number ofmultidrug
resistance

The pattern of Salmonella isolate showed multidrug resistance (n)Group B

Group CGroup E

S. Derby

S. Muenchen

S. Rissen

S. Anatum

3-

AMC-AMP-C (1)-OT-TE-SXT (1)

4

-

-

6

AMP-C-CIP-OT-SXT-TE (1)-

AMP-OT-S-TE (2)AMP-OT-TE-SXT (1)-AMP-OT-TE-SXT (2)-ACKNOWLEDGEMENTS

In conclusion, the results demonstrate the low
contamination rate of MDR Salmonella spp. in beefcarcasses in local slaughterhouses and retail butcher
shops of Northeastern Thailand. Evidently,
antimicrobial use in beef production is controlled
more strictly and under supervision by veterinarians.
This confirms that slaughterhouses and butcher shops
in Thailand generally have a good manufacturing
practice and are developing to international standards.

The authors would like to thank the Northeasternveterinary research and development centre (upperpart) which facilitating on the laboratory for isolationand identification of Salmonella spp. in this study. In
addition, thank Mr. Andrew Michael Chilcott forassistance with the English language presentation of
the manuscript.

249

SEE - Nagoya, Japan, Nov.12-14, 2018

REFERENCES[1] Yang B., Qiao L., Zhang X., Cui Y., Xia X., Cui
S., Wang X., Meng X., Ge W., Shi X., Wang
D., Meng J.
Serotyping, antimicrobial
susceptibility, pulse field gel electrophoresis
analysis of Salmonella isolates from retail foodsin Henan Province, China. Food Control
Volume 32, Issue 1, 2013, pp. 228-235.
[2] Sanchez-Maldonado A.F., Aslam M., Service C.,
Narváez-Bravo C., Avery B.P., Johnson R.,
Jones T.H. Prevalence and antimicrobial
resistance of Salmonella isolated from two pork
processing plants in Alberta, Canada.
International Journal of Food Microbiology
Volume 241, 2017, pp. 49-59.
[3] Bailey, J. S. and Maurer J.J. Salmonella Species.
In: Food Microbiology: Fundamentals andFrontiers, 2nd ed., Doyle, M. P., Beuchat L. R.,
and Montville T. J., ASM Press, Washington
D.C., 2001, pp. 141–178.
[4] ISO. Microbiology of food and animal feeding
stuff - Horizontal method for the detection of
Salmonella spp. ISO 6579:2002(E) 4th ed.
International Organization of Standardization,
Geneva, Switzerland, 2002, pp.1-27.
[5] Popoff M., Bockemühl J., Brenner F.W.,
Gheesling L.L. Supplement 2000 (no. 44) to the
Kauffmann-White scheme. Res. Microbiol.
Volume 152, 2001, pp. 907–909.
[6] Grimont, P.A.D., Weill, F.X.
Antigenic
Formulae of the Salmonella Serovars, (9th ed.)Paris: WHO Collaborating Centre for Reference
and Research on Salmonella, Institute Pasteur.
2007.
Availableat:
http://www.
pasteur.fr/sante/clre/cadrecnr/salmoms/WKLM_En.pdf.

[7] Clinical and Laboratory Standards Institute.
Performance standards for antimicrobial
susceptibility disk and dilution susceptibility
tests bacteria isolated from animals; Approved
Standard 3rd ed. Vol. 28 No. 8. Pennsylvania,
USA, 2008, pp. 1-75.
[8] Angkititrakul S., Polpakdee A., and Chuanchuen
R. Prevalence of Salmonella enterica,
Escherichia coli and Staphylococcus aureus in
raw meat in Thai self-service style restaurants inKhon Kaen Municipality. Thai J Vet Med. Vol.
43, Issue 2, 2013, pp.265-268.
[9] Hao H., Cheng G., Iqbal Z. et al. Benefits andrisks of antimicrobial use in foo-producing
animals. Frontiers in microbiology. Vol. 5, Issue
288, 2014, pp. 1-11.
[10] Marshall B.M. and Levy S.B. Food animals andantimicrobials: Impacts on human health.
Clinical microbiology reviews. Vol. 24, Issue 4,2011, pp. 718-733.
[11] Bischoff K.M., White D.G., Hume M.E., Poole
T.L., and Nisbet D.J. The chloramphenicol
resistance gene cmlA is disseminated ontransferable plasmids that confer multiple-drugresistance in swine Escherichia coli. FEMS
Microbiol Lett. Vol. 243, 2005, pp. 285-291.
[12] Pulsrikarn C., Chaichana P., Pornruangwong S.,
Morita Y., Yamamoto S., and Boonmar S.
Serotype, antimicrobial susceptibility, andgenotype of Salmonella isolated from swine andpork. Thai J Vet Med. Vol. 42, Issue 1, 2012,
pp.21-27.

250

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

STUDY OF QUALITY AND CONSUMER TEST OF EMULSION
SAUSAGE FROM BUFFALO AND TURKEY MEAT
1

Thassawan Somchan1 and Suthipong Uriyapongson2
Graduagate Student, 2 Associate Professor, 1, 2 Department of Animal Science,
Faculty of Agriculture, Khon kaen University Thailand

ABSTRACTThe objective of this research were to study of quality and consumer test of emulsion sausage from buffalo
and turkey meat. The experiment was assigned in the completely randomized block design(RCBD). Sausage
from buffalo and turkey meat were produced in 5 treatments include turkey meat 100 % (T1), buffalo meat
100% (T2), turkey meat 75 % : buffalo meat 25% (T3), turkey meat 50% : buffalo meat 50% (T4) and turkey
meat 25% : buffalo meat 75% (T5). Sausages were stored in refrigerator (4℃ ) for 24 hours before determinedfor pH, color (L* a* b*). Lipid oxidation (TBA) of sausage were determined after stored in refrigerator for
0,7,14 and 21 days. The results showed that pH of sausages were approximately 5-5.9. Color of T1 sausages had
the highest L*(27.54) and b*(19.39) but had the lowest a*(6.38) value (p<0.05), T5 sausages had the highest
a*(7.58) . The TBA of T1 sausage after stored for 1,7, 14 and 21 day were higher (p<0.05) than in other groups.
Consumer acceptance score of T1 and T3 sausages received the highest score and 6.9 5.8 (score of the 9 level).
It could be concluded that buffalo meat reduced lightness, yellowness score and improved redness score insausage. Higher buffalo meat reduced lipid oxidation in the turkey sausage.
Keywords: Emulsion sausages, Turkey meat, Buffalo meatsausage of turkey were produced with theingredients as showed in table 1. Buffalo meat wasadded to substitute for turkey meat at 25, 50, 75 and
100 % respectively.

INTRODUCTION
In Thailand, turkey farming is getting popular.
Government agencies are promoting new livestock.
Turkey meat was high calcium but lower chicken
and saturated than other meats [1]. It also had higher
protein and essentials amino acids. However, turkey
meat was a white meat [2] and meat products werewhite and pale. Buffalo meat consumption is related
to its nutritional advantages compared to beef. It isricher in iron, contains a higher amount of highbiological value protein and essential fatty acids,
along with lower quantities of fat and cholesterol[3]. Buffalo meat had dark red color and also hadhigh water holding capacity [4]. The main
ingredients of the sausage are chicken, pork, beef
and lamb meat. At present, emulsion such as Vienna
and Frankfurter sausage are the popular meatproducts around the world. Turkey and Buffalo meat
are interesting on raw material of emulsion sausagein Thailand. Therefore, buffalo meat mixes to turkey
meat by in emulsion sausage may improve color andtexture sausage. The objectives of this research are
to study on quality ( pH, color and lipid oxidation)and consumer test of emulsion sausage from turkey
meat with difference level of buffalo meat.

a. Buffalo meatb. Turkey meat

Fig. 1 Fresh meata. Turkey sausages

b. Buffalo sausages

Fig. 2 Emulsion sausages (Vienna sausages)
Sausage products were stored overnight at 4℃( 24 hour) before determined pH valued usedportable pH-meter (Hanna Instrument, Eibar, Spain).
Color of sausage samples were evaluated using by
Konica Minolta CR-410 and reported as

MATERIALS AND METHODFresh meat from turkey and buffalo werepurchased and chill overnight at 4℃. Emulsion
251

SEE - Nagoya, Japan, Nov.12-14, 2018

L*(lightness), a*(redness) and b*(yellowness). Lipid
oxidation was evaluated by measure thiobabituric
acid (TBA) after stored in refrigerator (4℃) for
1,7,14 and 21 days according to the methods
suggested by Turk Standards Institute 2409 [5].
Consumer test was performed using of 1 to 9 in the
Hedonic scale [6] [7].

Meat

46.87

material components include turkey and buffalo on
the quality characteristics of the sausages showed in
the Table 2. The pH values of turkey sausages were
found range pH 5.0-5.9. In the pH, lightness andyellowness values of the treatment T1 (100% turkey)
exhibited the highest value than the others (p<0.05).
Also, all of treatments show significant difference inthe lightening values. The redness values of thetreatment T1 indicated the lowest value was 6.38.
The redness value of the T2, T3, T4 and T5 (7.53,
7.5, 17.29 and 7.58 respectively) did not
significantly differ but had higher value than T1(p<0.05). Added buffalo meat reduced pH but
increased redness value of emulsion sausage.

Leaf fat

24

Table 2 pH and color of emulsion sausage

Ice

24

Soy protein isolate

2

Table 1 Ingredients for emulsion sausage
Ingredients

Ratio 100 (%)

NaCl

1

Vienna Powder

0.48

Sodium tri-polyphosphate

0.28

Sodium Erythorbate

0.28

pH

L*

a*

b*

T1
T2

5.94a

27.54a6.38b19.39a

ab

23.87

b

7.53

a

14.30dT3

5.35b

19.63c

7.51a

17.17b

T4

5.36b

16.57d

7.29a

15.17cT5

5.61ab

14.16e7.58a

14.66cd

5.73

SE

0.11
0.34
0.11
0.26
Means with different letters within the same
colum were significantly different (p<0.05).
SE = Standard error
T1 = Turkey meat 100%
T2 = Buffalo meat 100%
T3 = Turkey meat 75% : Buffalo meat 25%
T4 = Turkey meat 50% : Buffalo meat 50%
T5 = Turkey meat 25% : Buffalo meat 75%
a,b,c,dSmoke powder

0.28

Monosodium glutamate

0.2

Sugar

0.2

Pepper powder

0.2

Coriander seeds

0.2

Sodium nitrite
Source: [8]0.01

Lipid oxidation analysis
Table 3 Thiobabituric acid (TBA) of emulsion
sausage at different storage time.

The experimental design was Randomized
completely block design (RCBD) experiment with 5treatments and 3 replications as follow:
Treatment 1 Turkey meat 100% (T1)Treatment 2 Buffalo meat 100% (T2)
Treatment 3 Turkey meat 75% : Buffalo meat 25%(T3)
Treatment 4 Turkey meat 50% : Buffalo meat 50%(T4)
Treatment 5 Turkey meat 25% : Buffalo meat 75%(T5)
Statistical analysis were performed using SAS [9].
Mean of all values were analyzed of variance(ANOVA) and compared using Duncan New
Multiple Rang Test (DMRT)

1Storage time (day)
7

14

21

T1

0.88

a

1.03

a

0.99

a

0.97a

T2

0.43c

0.41c

0.51c

0.43c

T3

0.77ab0.80b0.78ab0.72b

T40.64bc0.70b

0.69bc

0.68b

T5

0.53c

0.50c

0.57bc0.56bc

SE

0.07
0.05
0.07
0.07
Means with different letters within the same
colum were significantly different (p<0.05).
SE = Standard error
TBA = µg MA/g.
T1 = Turkey meat 100%
T2 = Buffalo meat 100%
T3 = Turkey meat 75% : Buffalo meat 25%
T4 = Turkey meat 50% : Buffalo meat 50%
a,b,c,dResults
The effects of variation in the ratio of the raw
252

SEE - Nagoya, Japan, Nov.12-14, 2018

T5 = Turkey meat 25% : Buffalo meat 75%
The sausages were stored at 1,7,14 and 21 days.
The T1 showed the highest TBA value (1.03 µg
MA/g.) at 7 day of storage. The TBA of T1 sausage
was higher (p<0.05) compared to in other groups.
However, TBA values of T2 and T5 sausages werelower than other groups.

meat found that: pH values were similar among
treatments. Added buffalo meat reduced pH but
increased redness value of emulsion sausage.
Sausages with more buffalo meat had lower
rancidity during storage time. Consumer acceptancescore showed that more buffalo meat sausages
received lower acceptant score. There should be a
study on odor reduction in buffalo meat sausages.

Consumer test
ACKNOWLEDGEMENTS
Table 4 showed consumer acceptance score ofemulsion sausage. The T1 and T3 sausages had thehighest score of color, odor, flavor, juiciness,tenderness and overall acceptability while T2 and T5
sausages received the lowest score.

Thanks for the teacher development fund.
Mahasarakham
University.Animal
ScienceLaboratory, Department of Animal Science, Facultyof Technology, Mahasarakham University. MeatLaboratory, Department of Animal Science
Khonkaen University.

Table 4 Consumer acceptant test on Hedonic scaleof emulsion sausage.
Col
Od
flav
Juic Tend Over
T1 6.74a 6.30a 6.87a 6.91a 6.97a 6.86a
T2 3.99c 3.80b 4.21b 3.54c 3.87d 3.95c
T3 6.40a 5.85a 6.51a 6.39a 6.32ab 6.47a
T4 5.45b 4.80b 5.30b 5.31b 5.31bc 5.44b
T5 4.41c 4.36b 4.83b 4.38bc 4.57cd 4.90bc
SE 0.29 0.32 0.34
0.31
0.33 0.31
a,b,c,dMeans with different letters within the same
colum were significantly different (p<0.05).
SE = Standard error
Col = Color
Od = Odor
flav = Flavor
Juic = Juiciness
Tend = Tenderness
Over = Overall acceptability
T1 = Turkey meat 100%
T2 = Buffalo meat 100%
T3 = Turkey meat 75% : Buffalo meat 25%
T4 = Turkey meat 50% : Buffalo meat 50%
T5 = Turkey meat 25% : Buffalo meat 75%

REFERENCES[1] Kerdsang P., Turkey.http://www.eto.ku.ac.th/[2] Kantapanit C., Meat Science. Thai Wattana
Panich Publishing Bangkok, 1986, pp.1-260.
[3] Voloski F.L.S., Tonello L., Ramires T., Reta
G.G., Dewes C., Iglesias M., Mondadori R.G.,
Gandra E.A., da Silva W.P.., and Duval E.H.,
Influence of cutting and deboning operations on
the microbiological quality and shelf life of
buffalo meat Journal of Meat Science 116 , 2016,
pp. 207–212.
[4] Uriyapongson S., Buffalo and Buffalo Meat in
Thailand, World Buffalo Congress and the 7th
Asian Buffalo Congress, Buffalo Bulletin(Special Issue 1),Vol.32 , 2013, pp.329-332.
[5] Available from Department of Livestock
Development. 2003.
[6] Turkish Standart Instiýtute .Chicken
carcass meat. Chemical properties. Ankara,
Turkey.2007.
[7] Anprung P., Principles analysis of food with
Sensory Chulalongkorn University
Publishing, 2008, pp. 1-360.
[8] Peryam D.R., & Pilgrim, F.J. Hedonic scale
method of measuring food preferences. Food
Technology, 11(9) , 1957, pp. 9–14.
[9] Steel R. G. D. and Torrie J. H., Principle
and procedures of statistics: A Biomaterial
Approach 2nd. McGraw Hill Book Co,
New York.1980.
[10] Mariutti L., Influence of salt on lipid oxidation
in meat and seafood product: A review. Food
Research International, 2017,pp. 90-100.

DISCUSSION
Redness ( a*) score of T2 , T4 and T5 sausage
were higher with the mixture of buffalo meat dude to
the darker color of buffalo meat. The T1 and T3
sausage had the highest lightness and yellowness
value Sausages with more buffalo meat had less
TBA because of less unsaturated fatty acids [10]compared to turkey meat. Consumer acceptant ofsausages with buffalo meat had low accepted value.
Because of odor and hard of texture from buffalo
meat.
CONCLUSION
Study of quality and consumer test of turkey
emulsion sausage with difference level of buffalo

253

SEE - Nagoya, Japan, Nov.12-14, 2018

Engineering2544th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PARAMETRIC STUDY ON THE RESPONSE OF COMPOSITESINGLE PILES TO LATERAL LOAD BY NUMERICALSIMULATION (FDM)
1Alex Otieno Owino, 1Zakaria Hossain, 2Jim Shiau
Dept. of Environmental Science Graduate School of Bioresources, Mie University, Japan
2
School of Civil Engineering and Surveying, University of Southern Queensland, Queensland, Australia
1

ABSTRACTThis paper entails a detailed numerical and parametric study on the lateral behaviour of piles in foundation
designs. Single-piles are one of the major components of a foundation as they act as the primary component in thetransmission of the weights above the structure into the ground for stability to be attained. For this reason, a detailed
study on the influence generated on the p-y curves is mandatory to create a numerically valid model for use in theprocess of foundation design without much ado. Modelling procedure under consideration employs the use of thefinite difference method (FMD) embedded in FLAC2D. FDM is used to implement a solution to the coded input
for example soil and pile element parameters. The model validation process done in this paper involves thevariation of some of the critical parameters such as the variation on the type of soil in the area under consideration.
Next, modification of the elastic modulus of the given soil as a check on the cohesiveness, change on the loading
velocity at the top of the pile, a variation of the pile material stiffness and the difference of the pile eccentricity.
The results obtained from the p-y curves generated from the parameters undergo sifting through for any effects on
the ultimate loading capacity of the pile to the allowed design loading limits upon full structural installation. Thisvariation is necessary for the approval of the validity of the model in engineering design. The parametric study
from this study shows that the structure is of functional strength and a tolerable factor of safety.
Keywords: Lateral load, p-y curve, Soil-pile interaction, Finite difference method, FLAC2D

the analysis, and numerical methods are used toobtain the pile load-displacement response [3]. Fromthe p-y curve obtained, the pile foundations, in thiscase, the single pile foundation should be able towithstand the imposed load with a reasonable factorof safety, the pile head displacement should notexceed the tolerable movements for the structure it
supports, for example, the solar panels in this study
and lastly the intermediate soil should not receive
excessive stresses that may make it achieve theultimate load carrying capacity upon full construction
and operation [4]. A closer consideration is given on
the response of the soil to the short piles as thisprovides a clear understanding of the pile element
because at this depth the displacement is entirely
reliant on the resistance of the soil as illustrated by [5].
To obtain a clear picture of the pile responses inthis study, the parametric research is necessary toinvestigate the sensitivity towards fluctuating some of
the typical inputs to the program. Klepikov [6],conducted a study to examine the influence generated
by the modulus of subgrade reaction at the groundsurface as the primary parameter influencing the pile
structure response to the soil grid. The subgrade
reaction has also enabled the engineer to develop
models that can withstand seismic activities without
the fear of structural failure as stipulated by [7], who
predicted the foundation response to seismic anddynamic loads. As a step to simplify and ease theanalysis of pile foundations, 2D and 3D modelling

INTRODUCTION
The response of laterally loaded piles is a functionthat is dictated by many related parameters that act
upon the pile foundation during loading. At any
considerable time of loading, the effects of eachparameter input can cause a substantial influence on
the reaction of the pile foundation and the adjacentsoil components. Engineers always propose pilefoundation for the transfer of loads of overlying
structures as it offers adequate bearing capacity forlateral loads and also gravity loads. In the past studies
on pile foundations, several approaches have been
carried out to analyze this response from loads. These
approaches include force method, beam on elastic
foundation method, soil plasticity, and elasticity
continuum method. But most recently the practice offinite element method FEM [1], finite difference
method FDM [2] is being put in to use. FEM andFDM are flexible and can be manipulated to give avariety of responses and an in-depth analysis of thepile and the soil interface.
The analysis of laterally loaded piles in most cases
is expressed mostly by using the load-displacement
curve methods also referred to as the p-y curve
method. Using the p-y curves, the response of the soil
during loading is shown by a series of springs that
produce the resistance offered by the load whenacting upon them. The curvilinear load-displacementp-y characteristics of the springs are given as input to255

SEE - Nagoya, Japan, Nov.12-14, 2018

have become handy as it allows for the closer analysis
and input of flexible functions that can be executedby any given geotechnical software like FLAC2D
using finite difference method. Numerical models
have been developed to help comprehend the pile andsoil structures [8], to perceive the effect of theparameters to the pile setup when subjected to various
modes of loading. This study, therefore, employs theuse of FLAC2D in the development of a model torepresent the soil and pile interaction and the resultant
displacements used to investigate the various
parameters discussed in the analysis section.

shows the stresses involved during stress and stain
development process. On the other hand, a, b and cindicated the grid points upon which the velocities areapplied to produce deformations that lead to the griddisplacement.
Finite-difference method (FDM) is numericalmethods for solving differential equations byapproximating them with difference equations, inwhich finite differences approximate the derivatives.
FDMs [9] are thus discretization methods and are thedominant approach to numerical solutions of partial
differential equations. FLAC2D applies the FDM to
implement a solution to the coded input, for example,
the analysis if the pile foundation. FLAC2D therefore,
allow for the vector quantities for example forces,
velocities and displacements storage in the finite
difference grid generated while all scalar quantities,
for example, stresses, pressure, and material
properties stored in the zone locations. To ensurestability in the numerical scheme, FLAC2D includes
the dynamic equations of motion (equilibrium
equation) in the formulation. The balance thus
provides there is no sudden failure or collapse to thestructural component during the lateral loading
procedures [10]. The primary explicit calculation
cycle is as shown in Fig. 3.

FLAC2D FINITE DIFFERENCE MODELLINGPROCEDURE
The model was made using FLAC2D which is asufficient way to solve such complex matters as it
gives a clear picture of the performance of thestructure for the applied load. By finite difference
analysis, a mesh was generated to represent the
ground/soil conditions which had fixed grids points
with pinned boundary conditions (B) applied along
the bottom of the model and roller boundaries (X) on
both sides. The final model has been chosen so thatthe overall velocity field is distributed within thedomain and no boundary effect is presented. In
general, the model size has to be greater than 2 times
the pile length (i.e. 2.8 m radius from pile element
axis by 2.8 m depth) as shown in Fig. 1.

Velocity pulse applied to the boundary condition
Displaceme
nts from
velocityStressesderived fromstrainVelocity calculated stress

Pile element
Fig. 3 Basic explicit calculation cycle
Boundary

The response of a pile element during loading issimilar to the elastic model in FLAC2D. Regarding
Fig. 2, three main equations that dictate the responseof the pile element include Stress-Strain Constitutive
Law (Hooke's Law), Equation of Motion for Dynamic
Equilibrium (wave equation) and FDM formulation
using central finite difference equation as shown in
Eqn. (1), (2) and (3) respectively.

Fig. 1 Mesh, boundary condition, and pile
displacement pattern
Pile
elem
2

1

3

i-1

i

i+1
𝜕𝑢

𝜎𝑥𝑥 = 𝐸 𝜕 𝑥
a

b

c

d

i-1

i-1

(1)

𝑥

𝜕𝑢

𝜕𝜎 ̈

𝑡

𝑥𝑗

𝜌 𝜕 𝑖 = 𝜕 𝑦 + 𝜌𝑔𝑖

i-1

Fig. 2 Schematic representation of the grid points
and the zones
Figure 2 is a representative of an extended viewof the top of the model with 1,2 and 3 indicating thezones and inscribed within the zones (i-1, i, and i+1),

𝑖 (𝑡)𝑢𝑖+1 (𝑡)−𝑢𝑥

𝑖 (𝑡)
𝜎̃𝑥𝑥
=𝐸 𝑥

𝛥𝑥

(2)
(3)

Where ρ is the mass density, ux is the velocity
component, E is the elastic modulus, t is the time, xi
is the component of the coordinate vector, gi is the256SEE - Nagoya, Japan, Nov.12-14, 2018

component of gravitational acceleration and σ is thecomponent of the stress tensor. Equation 2 illustrates
the dynamic force equilibrium which indeed shows
the relationship between gravitational forces and thechanges in stress in the model grid. As reflected
earlier in this paper, FLAC2D consists of mainly
useful formulations where the variations in velocity
are quickly solved. Consequently, the rate at which
strain is experienced in the model grid can be related
to the velocity [11]. The finite difference equation for
the equation of motion using central finite difference
Eqn. 3, can further be simplified and classified into
two sections, with the left side of the equation
showing the changes in velocity while the right side
represents the changes in the stresses involved during
the model code execution as shown in Eqn. 4.

JOB TITLE : hdhdg

Lateral Load, kN

on the standard pressure induced by the pressing
nature of the pile element as well as the modulus ofsubgrade reaction, Ks and the displacement, yproduced at the pile head as shown in Eqn. 7. The soil
movements of FLAC2D output are as shown in Fig.
5 and Fig. 6.
High-pressure side: P=P*+Kh y
(7)

(4)

silty soil
clay soil

0

5
10
15
20
Pile Head Displacement, mm
Fig. 4 Effects of different soils: Silty soil and clay
soils

FLAC (Version 7.00)(5)LEGEND(6)
15-Jan-18 13:47
This paper, therefore, presents
a numericalstep 101184-3.111E-01
5.911E+00 ofparametric study that investigates
the<x<effects-1.611E+00 <y< 4.611E+00
several parameters such as pile head displacement
Pile Plotsoil and clayey
variations for two types of soil (silty
Structural Displacementsoil), soil elastic modulus, loading
stiffness
Max velocity,
Value = 2.000E-02
plotof the standard coupling springBoundary
represented
by thepile element and the pile eccentricity
on
the
p-y
0
1E 0
curves. The p-y curves will help Displacement
inJOB
theTITLE
determination
vectors:of the pile bearing capacity, themaxfactor
safety as
vector = of1.061E-03
FLAC (Version 7.00)
well as a step towards the model
validation for0
2E -3
engineering use in structural design for solar panel
LEGEND
foundations.
RESULTS AND DISCUSSION

18
16
14
12
10
8
6
4
2
0

4.000

3.000

2.000

High-pressureside:
P=P*+Kh y

Low-pressure
side: P=0

1.000

Silty
Soil

4.000

0.000

Fig. 5 Soil-pile displacement patterns for silty soil

24-Apr-18 12:23
step 101153-3.111E-01 <x< 5.911E+00-1.611E+00 <y< 4.611E+00

3.000-1.000Effects different soils: silty soil Boundaryand clayplot soils
0

0.500

1E 0

The type of soil is one of the main parameters to
Displacement vectors
be put into consideration formaxany
vector =construction
3.531E-04
procedure to be practiced. The cohesive nature of0
1E -3
different soils dictates the bearing capacity of thePile Plot
foundation. In addition to bearing
capacity,
the soil
Structural
Displacement
Value = 2.000E-02
type also dictates the modulus ofMax
subgradereaction,
Ks which is a ratio of contact pressure intensity, P and
the soil settlement, y. Due to the fact that clayey soil
has a higher modulus of subgrade reaction, 80,000
kN/m3, it attains a higher ultimate load of 15 kN at
lower pile head displacement of 4mm as compare to
the silty soils (Ks=48,000 kN/m3) that achieves the
final pressure at more massive movements of 10mm
as shown in Fig. 4.
A closer examination of the pile element and thesoil displacement patterns depicts the more verticalmovement of the ground in the clay soil than in thesilty soil. This high-intensity soil movement depends

1.500

2.500

3.500

4.500

5.500

Highpressure side:
P=P*+Kh y

Low-pressure
side: P=0

2.000

1.000

Clayey soils
0.000

Fig. 6 Soil-pile displacement patterns for clayey soil
Effects of soil elastic modulus-1.000In this case, it’s the elastic modulus of the soil thatis studied. The value for the elastic modulus is ranged
from 11e6 to 31e6 kPa for silty soils and 40e6 to 60e6
kPa for the clayey soils. The other conditions are held
constant as per the design parameters (Pile length=
1.4m, pile diameter=0.13m, the rate of loading force
constant). The p-y curves generated from FLAC2D at
0.500

257

1.500

2.500

3.500

4.500

5.500

SEE - Nagoya, Japan, Nov.12-14, 2018

the design depth shows that the elastic modulus, E,
has minimal effects in the silty soils whereas in theclay soils deviations in the ultimate load are noticed
at displacements of 5 mm as shown in Fig. 7 and 8.
This E variation is a clear indication that thecohesiveness of the soils should be highly consideredin the clayey soils if the design bearing capacity is tobe achieved.

capacity reduces once the ultimate load is attained at
2.0e7. At the pile depth of 2.8m, increasing thevelocity have detrimental effects on the ultimate
loading capacity as in both cases (silty and clay soils)
there is significant decrease in the ultimate loads asshown in Fig. 9.

16depth 1.4m: silty soil

depth 2.8m: silty soil

depth 0.7m: clayey soil

depth 1.4m: clayey soil

depth 2.8m: clayey soil

40

14
Lateral Load, kN

depth 0.7m:silty soil

Ultimate Load, kN

12
10
E: 11e6 ,1.4m depth86

E: 21e6 ,1.4m depth4
E: 31e6 ,1.4m depth

2

30
20
10

0
0
0.00E+00

0

5
10
15
20
Pile Head Displacement, mm
Fig. 7 Effects of elastic modulus for silty soil

1.00E-07
2.00E-07
Loading velocity in FLAC2D

3.00E-07

Fig. 9 Effects of Loading velocity with depth on
ultimate load

18
16
14
12
10
8
6
4
2
0

Lateral Load, kN

Effects of pile stiffness: stiffness of normal
coupling spring
In FLAC2D, the coupling springs are a
representative of the interaction between the soil andthe pile element under consideration. The normal
coupling spring is the medium in which the lateralforces applied at the given velocity transmission,
occur to the grid at the prescribed location along thepile element nodes. To obtain a desirable ultimate
loading capacity of the pile, then the choice of the pilematerial should also be put on a check. A numericaldescription of the action of the normal coupling
spring stiffness and the displacements produced
during loading is as shown in equation 8

E: 40e6 ,1.4m depth
E: 50e6 ,1.4m depth
E: 60e6 ,1.4m depth

0

5
10
15
20
Pile Head Displacement, mm
Fig. 8 Effects of elastic modulus for clayey soil
Effects of loading velocity with depth on ultimate
load

(8)
Where Fn represents the normal force that develops in
the normal coupling spring, csnstiff is the normal
coupling spring stiffness, unp is the displacement of
the pile in the axial direction, unm is the displacementof the grid(soil) normal to the axial direction of thepile, and L is the pile element length.
In this study, the stiffness of the normal coupling
springs was varied from 1.3e7 kN/m2 to 1.3e11 kN/m2
with all other parameters held constant (Pile length=
1.4m, pile diameter=0.13m, the rate of loading force
constant) for the two types of soils (silty and clayeysoils). Based on the output, it's seen that an increasein the stiffness of the coupling spring increases theultimate loading capacity of the pile. Clayey soils
depict high ultimate loads up to 16 kN at 1.3e11 kN/m2

Velocity is a time-dependent parameter whenincorporated into FLAC2D. It ensures that the
deformations on the grid follow the stress/strain law.
To achieve the ultimate bearing capacity, the correct
loading velocity should be determined as it plays asignificant role in the damping of the equations of
motion to provide static or quasi-static also known as
non-inertial solutions. The non-inertial solutions help
in achieving the equilibrium state in a numericallystable way with minimal computation effort in
FLAC2D. In this study, the velocity was varied from
1.0e7 to 2.5e7 for the single pile foundation depths of
0.7m, 1.4m, and 2.8m. Base on the results, it is evident
that increasing the velocity at 0.7m and 1.4m depth
increases the ultimate loading capacity in the silty
soil, but in the clayey soil, the ultimate loading
258

SEE - Nagoya, Japan, Nov.12-14, 2018

8.4kN hence this shows that the point of the load
applied to a pile is also a strong determinant of theultimate strength concerning bearing capacity.

18

16

16

14

14

12
Lateral Load, kN

Lateral Load, kN

at minimum displacements 7mm as compared to silty
soils at 15kN. Figure 10 and Fig. 11 shows a plot of
the stiffness parameter influence in ultimate loading
capacity for silty and clayey soils respectively.

12

10

10
8

1.30E+07

6

1.30E+08

4

1.30E+112

8
e: o.2m

6

e: o.4m

4

e: 0.6m2

e: 0.8m

0

0
0

5
10
15
Pile Head Displacement, mm

20

-2

18
16
14
12
10
8
6
4
2
0
-2 0

Lateral Load, kN

Lateral Load, kN

5

10

15

20

Pile Head Displacement, mm
Fig. 12 Effects of pile eccentricity in silty soil

Fig. 10 Effects of pile stiffness silty soil

18
16
14
12
10
8
6
4
2
0

0

1.30E+07
1.30E+08
1.30E+11

e: 0.2m
e: 0.4m
e: 0.6m
e: 0.8m

5
10
15
20
Pile Head Displacement, mm
Fig. 13 Effects of pile eccentricity in clayey soil

0

5
10
15
20
Pile Head Displacement, mm
Fig. 11 Effects of pile stiffness clayey soil

CONCLUSION
Effects of eccentricity, e
The primary objective of this study was toevaluate the response of the load transfer curve andthe displacements produced. This response shows theinfluence factor of the lateral load under different
circumstances depending on the parameter understudy. The parametric study, therefore, acts as amodel validation process as it shows clearly the
influence produced by a given setting concerning thedesign value at hand. From this study, it is evident
that the integration of the stresses in the grid element
around the pile element is an obvious way ofunderstanding the p-y curve characteristics in the soil.
Additionally, the variation of the parameters such as
pile stiffness, loading velocity, and eccentricity haveshown that clayey soils have the highest ultimate load
bearing capacities of between 15.5kN to 15.8kN at
minimal pile displacements of below 5mm.
It is also valid that FLAC2D as a numerical techniquein the modelling field is a vital tool for investigating
the realistic soil behaviour under different conditions

The height of the pile above the ground is an
excellent determinant on the moments above theground level. The moment equilibrium equation is the
product of the lateral force and the eccentricity. Whenthe bending moments tend to increase then theultimate load that the pile element can withstandreduces considerably. This reduction is due to therotational effect produced by the lateral pressure
above the ground level. When this rotational effectcannot be transmitted to the grid, then the pile tends
to fail closer to the ground level at minimal lateralloads. In this study, the eccentricity effect is evaluatedat 0.2m, 0.4m, 0.6m and 0.8m for both types of soil
and the corresponding ultimate load plotted as shownin Fig. 12 and Fig. 13 for silty soil and clayey soil
respectively. Based on the results, the eccentricity of
0.2m produced the highest ultimate loading capacityof 15kN in silty soil and 15.8kN in clayey soils. An
eccentricity of 0.8m recorded the minimum value of259

SEE - Nagoya, Japan, Nov.12-14, 2018

and is helpful in simulating all construction sequences
concerning the provided design parameters.

subgrade reaction. Soil Mechanics andFoundation Engineering, 2(5), pp.296-299.
[7] Caseiro, C 1986, Behavior of Elastomeric
Materials Under Dynamic Loads -- IV. The
Shock and Vibration Digest, 18(1), pp.3-6.
[8] O'Neill, MW, Blaney, GG & Muster, GL 1982,
Behavior of Single Pile and Pile Group in
Overconsolidated Clay Under Relatively LowFrequency Loading, Fugro-Gulf, Inc., and Univ.
of Houston-University Park.
[9] Cundall, PA 1976, Explicit Finite Difference
Methods in Geomechanics, in Numerical
Methods in Engineering, Proceedings of the EF
Conference on Numerical Methods inGeomechanics, Blacksburg, Virginia, Vol. 1, pp.
132-150.
[10] Britto, AM, & Gunn, MJ 1987, Critical State Soil
Mechanics via Finite Elements. Chichester U.K.:
Ellis Horwood Ltd.
[11] Banerjee, PK, and Davis, TG 1978. The
behaviour of axially and laterally loaded single
piles embedded in non-homogeneous soils,
Geotechnique, 28, No. 3, 309-326.
[12] Trochanis, AM, Bielak, J & Christiano, P 1991,
Three-dimensional nonlinear study of piles.
Journal of Geotechnical Engineering, ASCE,
117, 429-447.

ACKNOWLEDGEMENTS
Thanks are also to Japan International Cooperation
Agency (JICA) for giving the postgraduate
scholarship to the first author
REFERENCES[1] Poulos, HG 1971, The behaviour of laterally
loaded piles: I- single piles. Journal of Solid
Mechanics, Foundation Division, ASCE, 97,
711-731.
[2] Brown, DA, Shie, C & Kumar, M 1989, P-ycurves for laterally loaded piles derived fromthree-dimensional finite element model,
Numerical Models in Geomechanics, NUMOG
III, 683-690 Elsevier Applied Science.
[3] Cox, W & Reese, L 1978, Pullout Tests of
Grouted Piles in Stiff Clay. Journal of Petroleum
Technology, 30(03), pp.349-356.
[4] Duncan, JM, Jr. Evans, LT & P. S. K.Ooi 1994,
Lateral Load Analysis of Single Piles and Drilled
Shafts, Journal of Geotechnical Engineering
ASCE, Vol. 120, No. 5, pp.1018- 33.
[5] Broms, B 1964 The lateral resistance of piles incohesionless soils. J Soil Mech Found Div,ASCE 90(SM3):123–156[6] Klepikov, S 1965, Calculation of beams on anelastic foundation with a variable modulus of260

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EXTRACTION OF STATIC FEEDBACK COEFFICIENT FOR SPICEMODEL OF DRAIN INDUCED BARRIER LOWERING IN
JUNCTIONLESS DOUBLE GATE MOSFET
Hakkee Jung1
Department of Electronic Engineering, Kunsan National University, South Korea

1

ABSTRACTA SPICE model of Drain Induced Barrier Lowering (DIBL) has been proposed for a Junctionless Double Gate (JLDG)MOSFET. For this purpose, the potential distribution in the channel is obtained using the Poisson equation, and the thresholdvoltage is determined by the third derivative (TD) method. The DIBL should be expressed as a function of silicon thickness
as well as channel length and oxide thickness due to the effect of silicon thickness on carrier transport in a nanostructure
JLDG MOSFET, even though it is only defined by channel length and oxide thickness in SPICE model of conventional
MOSFET. As a result, it is found that the DIBL is proportional to the power of -3 for the channel length, 2 for the silicon
thickness, and 1 for the oxide thickness, where the proportional constant is 22.0. It is observed that the SPICE parameter, thestatic feedback coefficient, is reasonably between 0.2 and 0.9. The DIBLs obtained by using the threshold voltage model
published in other papers show a good agreement with those of this model regardless of the channel length at 20 nm or more,
but the DIBLs of the other models are different at the sub-20 nm channel lengths from one another. The DIBL model proposedin this paper is consistent with results of other models in all range of channel length.
Keywords: Junctionless cylindrical surrounding, Threshold voltage, DIBL, Static feedback coefficienteffect. The threshold voltage will be derived from thetransfer characteristics between the drain current andthe gate voltage by the third derivative (TD) methodthat has already been verified [6].
The SPICE model 𝝈𝑫 of the DIBL for a Junction
Based Double Gate (JBDG) MOSFET has been
proposed [7]. In the case of JLDG MOSFETs, thechannel shows a fully depleted state in thesubthreshold voltage, and is partially depleted at thethreshold voltage, indicating the on-statecharacteristic as the current flows into the partiallyformed neutral region [8]. When the voltage further
increases to reach a flat voltage, the entire channel
becomes a neutral state and enters the accumulation
state. In the conventional MOSFET, the current
amount is determined by the amount of charge
formed in the inversion layer. The inversion layer
thickness has more influence on the current amountthan the silicon thickness in the case of theconventional MOSFET, but the amount of current for
the JLDG MOSFET will be determined, dependingon the oxide film thickness and silicon thickness aswell as channel length. Therefore, in this paper, 𝝈𝑫
will be expressed mathematically after observing thechange of DIBL according to channel length, silicon
thickness, and oxide thickness. The model will be set
so that the static feedback coefficient, which is a
SPICE parameter of 𝝈𝑫 , has a reasonable value.
Raksharam et al. described the change in thethreshold voltage for a JLDG MOSFET with achannel length of 22 nm as an analytical model [9].

INTRODUCTION
The conventional MOSFET structure is no longer
usable due to the short channel effect in the structure
below 20 nm. In particular, it is necessary to improve
the ON/OFF current ratio due to the increase of thepower consumption by the increase of the parasitic
current, and it is required to improve the control
ability of the carriers in the channel by the gate
voltage. In addition, the variation of the doping
concentration between the source/drain region andthe channel shows the limit of the conventional
MOSFET process while the channel length isdecreased [1]. To solve this problem, the transistor
structure of a Junctionless Double Gate (JLDG)MOSFET is developed. The JLDG MOSFET has
advantages of simplifying the process because it has
no junctions between source/drain and channel, and it
can use the existing MOSFET process as well as
reducing the process cost. Therefore, transport modeland process development for a JLDG MOSFET aswell as junctionless structure FET such as
Junctionless Cylindrical Surrounding Gate (JLCSG)
MOSFET are under study [2]-[4]. Especially, it isnecessary to develop a model for SPICE simulation
because it has reached the stage of analyzing
characteristics in circuit configuration using a JLDGMOSFET [5]. Therefore, in this paper, we propose
SPICE-used model of Drain Induced Barrier
Lowering (DIBL) 𝝈𝑫 , induced by threshold voltage
in JLDG MOSFET, as known as the short channel
261

SEE - Nagoya, Japan, Nov.12-14, 2018

𝑪𝒏

Jiang et al. defined the threshold voltage using thepotential distribution of the series form and expressed
analytically the change of threshold voltage due todrain voltage [10]. In addition, Lin et al. obtained thepotential distribution by solving the one-dimensional
Poisson equation and the two-dimensional Laplace
equation, and calculated the threshold voltages for
JLDG MOSFETs with channel lengths of 20 nm or
more [11]. We will verify the validity of the proposedmodel by comparing the DIBL values derived fromthe threshold voltage model obtained from otherpapers with those procured from the model presented
in this paper.
In Section 2, we will explain the DIBL derivation
process using the analytical potential distribution andcurrent-voltage characteristics of JLDG MOSFETs.
In Section 3, we will present the SPICE-used modelby analyzing the obtained DIBL according to thechannel structure. Conclusions are given in Section 4.

=

𝟏
𝟐𝜶𝒏

𝟐 𝟏
(𝑽 − 𝑽𝒈𝒔 )√𝑳𝒈 𝒌𝒏 𝑭𝑩[
𝒇𝒏 = −

𝒒𝑵𝒅
𝝐𝒔𝒊 𝒌𝒏

𝟐

𝒏𝝅

𝒈

𝒈

√𝑳 [𝟏 − (−𝟏)𝒏 ] , 𝒌𝒏 = 𝑳]𝜺𝒔𝒊𝒕𝒔𝒊 𝒌𝒏𝒕𝒔𝒊 𝒌𝒏𝜶𝒏 = 𝒕𝒐𝒙
𝒌𝒏 𝐬𝐢𝐧𝐡 () + 𝐜𝐨𝐬𝐡 (
)
𝜺𝒐𝒙
𝟐
𝟐
where 𝑽𝒓𝒆𝒇 is the reference potential, 𝑽𝒅𝒔 is the drain
voltage, and 𝝐𝒔𝒊 is the dielectric constant of silicon. In
this study, we used the results calculated up to n = 30.
The relationship between the drain current and thegate voltage is derived using the potential distribution
in Eq. (2) and the following diffusion-drift current
equation.

DIBL OF JLDG MOSFET

𝑰𝒅 =

−𝒒𝑽𝒅𝒔
)}
𝒌𝑻

𝒒𝒏𝒊 𝝁𝒏 𝑾𝒌𝑻{𝟏−𝒆𝒙𝒑(
𝑳𝒈

∫𝟎

𝟏
𝒅𝒙
𝒕𝒔𝒊
𝒒𝝓(𝒙,𝒚)𝟐∫ 𝒕 𝒆𝒙𝒑{ 𝒌𝑻 }𝒅𝒚
− 𝒔𝒊
𝟐

(3)

where 𝑾 is the channel width, 𝒏𝒊 is the intrinsic
semiconductor concentration of silicon, 𝝁𝒏 is themobility, 𝒌 is the Boltzmann constant and 𝑻 is theabsolute temperature. Since the validity of Eq. (3) is
described in the previous paper [12], the relationshipbetween drain current and gate voltage obtained using
Eq. (3) is used to obtain the threshold voltages. Figure2(a) shows the relationship between drain current andgate voltage obtained in this study. We used the TD
method proposed by Wong et al. [6] to extract thethreshold voltage. As shown in Fig. 2(b), theFig. 1 Schematic cross sectional diagram ofJunctionless Double Gate (JLDG) MOSFET
Figure 1 shows the cross sectional view of JLDGMOSFET. As shown in Fig. 1, the JLDG MOSFET isa junctionless structure with the same doping type andconcentration for source/drain and channel. In thisstudy, 𝑵𝑫 = 𝟏𝟎𝟏𝟗 /𝒄𝒎𝟑 is used. Most of the carriers inthe symmetrical structure will be transmitted throughthe center of the channel, and the potential
distribution is obtained using the following Poisson
equation when the channel length changes from 10
nm to 50 nm, the silicon thickness from 5 nm to 10
nm, and the oxide thickness from 1 nm to 4 nm.
𝝏𝟐 𝝓
𝝏𝟐 𝝓
𝒒𝑵
+
=− 𝝐 𝒅
𝟐
𝝏𝒙
𝝏𝒚𝟐
𝒔𝒊

𝒇𝒏
𝟐 (−𝟏)−𝒏+(𝑽𝒅𝒔 + 𝑽𝑭𝑩 − 𝑽𝒈𝒔 ) −√𝒌𝟐𝒏
𝑳𝒈 𝒌 𝒏(1)

In the case of JLDG MOSFET, as shown in Jiang
et al.'s method, the potential distribution can beobtained as follows [10].
𝑽

𝝓(𝒙, 𝒚) = 𝑽𝒓𝒆𝒇 + 𝒅𝒔 𝒙 +
𝑳𝒈

𝟐

𝒇𝒏
𝒏𝝅
∞
√𝑳 ∑𝒏=𝟏 [𝟐𝑪𝒏 𝒄𝒐𝒔𝒉(𝒌𝒏 𝒚) − 𝒌𝟐 ] 𝒔𝒊𝒏 ( 𝑳 𝒙)
𝒈
𝒈
𝒏

(2)

Fig. 2. (a) Transfer characteristics for drain current vs.
gate voltage with channel length as a parameter, and(b) the threshold voltage extraction method by third
262

SEE - Nagoya, Japan, Nov.12-14, 2018

derivatives for transfer characteristics of (a).
threshold voltage is extracted as the minimum of thethird-order differential coefficient obtained by using
the current-voltage relationship in Fig. 2(a) because
the TD method can be used efficiently in determining
the threshold voltage including the physical meaning.
As shown in Fig. 2(b), the gate voltage
corresponding to the inflection point of the curve isdefined as the threshold voltage, and the DIBL is
obtained using the following Eq. (4).

𝝈𝑫 =the conventional MOSFET. Figure 3(b) shows the[𝑽𝒕𝒉 (𝑽𝒅𝒔 =𝟎.𝟎𝟓 𝑽)−𝑽𝒕𝒉 (𝑽𝒅𝒔 =𝟎.𝟓𝟓 𝑽)]
𝟎.𝟓(4)
In general, DIBL is varied according to thechannel size and oxide thickness, and DIBL model𝝈𝑫 in SPICE is expressed using these variables andthe static feedback coefficient as a parameter. In theconventional MOSFET, the static feedback
coefficient is generally 0.7 [13]. In this paper, we
propose SPICE model of DIBL which depends onchannel size and oxide thickness with reasonablestatic feedback coefficient for JLDG MOSFET. In
the nanostructure JLDG MOSFET, unlike theconventional MOSFET, the size of the channel must
be involved in obtaining DIBLs because the entire
channel affects current flow when JLDG MOSFET
changes from a fully depleted state to a partiallydepleted state. That is, not only the channel length but
also the silicon thickness will affect the carriertransmission. It is known that the 𝝈𝑫 is proportionalto 𝑳−𝟑𝒈 for the channel length in the conventional
MOSFET [13]. In addition, the 𝝈𝑫 is proportional to
the square of silicon thickness for a nanostructure
junction-based double gate MOSFET [7]. Therefore,
in this paper we will derive the 𝝈𝑫 of JLDGMOSFET including all of the above mentioned
variables.

change in DIBL with respect to the silicon thickness,
Fig. 3 (a) DIBLs for channel length of JLDGMOSFET. Dotted line denotes proportional line forpower of -3 for channel length, (b) DIBLs for silicon
thickness of JLDG MOSFET with channel length asa parameter. The dotted line denotes proportional line
for power of 2 for silicon thickness, and (c) DIBLs forgate oxide thickness of JLDG MOSFET with channel
length as a parameter for silicon thickness of 5 and 7
nm. We know DIBLs are proportional for power of 1
for gate oxide thickness.
with the relation of 𝝈𝑫 ∝ 𝒕𝟐𝒔𝒊 denoted as a dotted line,
and the 𝝈𝑫 shows good agreement with theproportional relation to the power of 2 for silicon
thickness. As shown in Fig. 3 (b), the inclination is
the same when the channel length is 10 nm and 20
nm. Finally, in order to observe the relationshipbetween oxide thickness and DIBL, the relationshipbetween DIBL and oxide thickness is shown in Fig. 3

SPICE DIBL MODEL FOR JLDG MOSFETIn this paper, we use Eq. (4) to find the DIBL fromthreshold voltage at the drain voltage of 0.05 V and
0.55 V, and present the SPICE-used DIBL model byobserving the change of DIBL, with respect tochannel length, silicon thickness and oxide thickness.
Figures 3(a), 3(b), and 3(c) show the variation of
DIBLs with respect to channel length, silicon
thickness, and oxide thickness, respectively. As
shown in Fig. 3(a), the relation of 𝜎𝐷 ∝ 𝐿−3
𝑔 is
indicated by a dotted line to observe whether DIBL is
proportional to 𝐿−3
𝑔 . Figures 3(a) and (b) use alogarithm-logarithmic graphs. In these graph, it iseasy to grasp the multiplier by using the slope of thestraight line since the relationship appears as astraight line. As shown in Fig. 3(a), the 𝜎𝐷 for thechannel length is proportional to the power of -3 as in
263

SEE - Nagoya, Japan, Nov.12-14, 2018(c) when the silicon thickness is 5 nm and 7 nm withthe channel length as a parameter. Note that the linear
scale for x and y axis is used in Fig. 3 (c), unlike Figs.
3(a) and (b). As shown in Fig. 3(c), the relations
between DIBL and oxide film thickness are linear
regardless of channel length and silicon thickness
although the slope is different. It will be inversely
proportional to the gate oxide capacitance since it islinear to the oxide thickness. That is, the influence ofthe gate voltage on the carrier transmission in thechannel will be further blocked when gate oxide
capacitance increases; as a result, the carriertransmission control ability of the gate voltage will be
weakened. The threshold voltage will be less affected
and the DIBL will also decrease as the oxide film
thickness decreases. Therefore, it is reasonable toassume that the 𝝈𝑫 representing DIBL in Eq. (4) islinearly proportional to 𝒕𝒐𝒙 . As a result, the 𝝈𝑫 can be
expressed as a function of the following channel sizeand oxide thickness.
𝟐
𝝈𝑫 = 𝑨𝜼𝑳−𝟑
𝒈 𝒕𝒔𝒊 𝒕𝒐𝒙

model presented in other papers are shown in Fig. 5.
Since the potential model used in this paper basicallyuses the model proposed by Jiang et al., it can be seenthat the results are in good agreement with the results(5)Fig. 4. Static feedback coefficients for JLDGMOSFET in the range of 10 nm ≤ 𝐿𝑔 ≤ 50 𝑛𝑚 ,5 nm ≤ 𝑡𝑠𝑖 ≤ 10 𝑛𝑚, and (a) 𝑡𝑜𝑥 = 1 𝑛𝑚, (b) 𝑡𝑜𝑥 =2 𝑛𝑚, (c) 𝑡𝑜𝑥 = 3 𝑛𝑚, and (d) 𝑡𝑜𝑥 = 4 𝑛𝑚.

In the case of the JLDG MOSFET of Eq. (5), the
SPICE-used DIBL model, which can be expressed byonly the channel size and the oxide thickness, isderived by setting the A value to have the static
feedback coefficient 𝜼 of between 0 and 1 that is
SPICE parameter of 𝝈𝑫 . First, the value of 𝑨𝜼 in Eq.
(5) is obtained in the range of 𝟏𝟎 𝐧𝐦 ≤ 𝑳𝒈 ≤𝟓𝟎 𝒏𝒎 , 𝟓𝐧𝐦 ≤ 𝒕𝒔𝒊 ≤ 𝟏𝟎 𝒏𝒎 , 𝟏 𝐧𝐦 ≤ 𝒕𝒐𝒙 ≤𝟒 𝒏𝒎, and the maximum value of 𝑨𝜼 is set as 𝑨 tosustain the static feedback coefficient 𝜼 between 0
and 1. The value of 𝑨 thus obtained is 22.0.
Therefore, the SPICE-used DIBL model of the JLDGMOSFET can be obtained as follows.

of Jiang et al. except for the case of Fig. 5 (c) with thesilicon thickness of 3 nm. The smaller the silicon
thickness, the greater the difference between Jiang’s
model and this model. The reason for this is that Jiang
et al. calculated the potential distribution using theseries form and defined the threshold voltage modelusing only the first term. That is, the smaller thesilicon thickness becomes, the larger the error
between Jiang’s model and this model is. The error
increases as the channel length increases as shown in
Fig. 5 (c). To clarify this point, Fig. 6 shows thevariation of 𝟏/𝜶𝒏 which is used to calculate thethreshold voltage in the model of Jiang et al.

𝟐𝝈𝑫 = 𝟐𝟐. 𝟎𝜼𝑳−𝟑
𝒈 𝒕𝒔𝒊 𝒕𝒐𝒙 .
(6)

Figure 4 shows the static feedback coefficient𝜼 obtained using Eq. (6) from the range of the channel
size and the oxide thickness as mentioned in theprevious paragraph. As can be seen in Fig. 4, thevalues of 𝜼 is ranged from 0.2 to 1.0. As the channel
length increases, the variation rate of 𝜼 increases.
Especially, the variation of the static feedback
coefficient 𝜼 increases as the oxide thickness andsilicon thickness increases. Note that it is smallenough that the 𝜼 varies between 0.4 and 0.8 asknown in the results in Fig. 4 (a) with oxide film
thicknesses down to 1 nm. From the above results, it
can be concluded that Eq. (6) is a SPICE-used DIBL
model which can fully express the DIBL phenomenon
of JLDG MOSFET.
In order to verify the validity of Eq. (6) presented
in this paper, the results of the comparison with the
DIBL values obtained using the threshold voltage

Fig. 5. Comparisons this model with various models
for DIBL of JLDG MOSFET in the range of264

SEE - Nagoya, Japan, Nov.12-14, 2018

𝟏𝟎 𝐧𝐦 ≤ 𝑳𝒈 ≤ 𝟓𝟎 𝒏𝒎, and (a) 𝒕𝒐𝒙 = 𝟐 𝒏𝒎, 𝒕𝒔𝒊 =𝟏𝟎 𝒏𝒎 , (b) 𝒕𝒐𝒙 = 𝟏 𝒏𝒎, , 𝒕𝒔𝒊 = 𝟏𝟎 𝒏𝒎 (c) 𝒕𝒐𝒙 =𝟏 𝒏𝒎 , 𝒕𝒔𝒊 = 𝟑 𝒏𝒎 and (d) 𝒕𝒐𝒙 = 𝟎. 𝟔 𝒏𝒎, 𝒕𝒔𝒊 =𝟏𝟎 𝒏𝒎.
As shown in Fig. 6, when n increases, the value of
𝟏/𝜶𝒏 sharply decreases, and the value of 𝟏/𝜶𝒏decreases more sharply with increasing silicon
thickness and smaller channel length. If the silicon
thickness is small and the channel length is large, it
can be seen that the approximation of n = 1 in Eq. (2)is not valid.
It is clear that Jiang's model shows a big
difference from other models as the channel length
increases in Fig. 5 (c) due to this reason. Comparedwith Lin's model, results of Lin’s model show good
agreement with those of other models only when theoxide thickness is very small (0.6 nm). In addition,
Lin et al. calculated for the channel length over 20 nm
and found that results agree well with other models inthis range. There is a large difference from othermodels when the thickness of the oxide film isincreased at a channel length of 20 nm or less. Even
though Raksharam’s model uses a different potential
distribution model than the one proposed in thisstudy, it is observed that the their results are good
agreement to these results when the silicon thickness
and the oxide thickness are small as shown in Fig. 5(c). The results are well matched regardless of themodel in the range of the channel length of 20 nm or
more, but note the differences of DIBL models are
more significant in case that the channel length is 20
nm or less.

In this paper, a SPICE-used DIBL model for a
JLDG MOSFET has been presented. Since theparameters of the SPICE-used DIBL model are static
feedback coefficients, the model equations areconstructed to represent the reasonable range in the
SPICE simulation. For this purpose, the thresholdvoltage was derived by the TD method in the relation
between drain current and gate voltage to obtain using
the potential distribution of the series form derived
from the Poisson equation. The validity of the DIBL
obtained using this threshold voltage was verified bycomparing it with other papers. As a result, it was
found that the 𝝈𝑫 representing DIBL is proportional
to the channel length by the power of -3, the silicon
thickness by 2, and the oxide thickness by 1 where theproportional constant A is 22.0. In this case, the static
feedback coefficient 𝜼, SPICE parameter, is found in
the range of 𝟏𝟎 𝐧𝐦 ≤ 𝑳𝒈 ≤ 𝟓𝟎 𝒏𝒎, 𝟓𝐧𝐦 ≤ 𝒕𝒔𝒊 ≤𝟏𝟎 𝒏𝒎 , and 𝟏 𝐧𝐦 ≤ 𝒕𝒐𝒙 ≤ 𝟒 𝒏𝒎 , and is in therange of 0.2≤ 𝛈 ≤ 𝟎. 𝟗. The variation of the static
feedback coefficient 𝜼 decreased with decrease in theoxide and silicon thickness. Especially, the static
feedback coefficient 𝜼 was nearly constant regardlessof the silicon thickness when the oxide thickness was
1 nm and the channel length was below 30 nm. These
results will be useful for circuit simulation using
JLDG MOSFET.

REFERENCES[1] Chen Z., Xiao Y., Tang M., Xiong Y., Huang J.,
Li J., Gu X., and Zhou Y., Surface-PotentialBased Drain Current Model for Long-Channel
Junctionless Double-Gate MOSFETs, IEEE
Trans. on Electron Devices, Vol. 59, Issue 12,2012, pp.3292-3298.
[2] Pradhan K. P., Kumar M. R., Mohapatra S. K., andP. K. Sahu, Analytical modeling of thresholdvoltage for Cylindrical Gate All Around (CGAA)MOSFET using center potential, Ain Shams
Engineering Journal, Vol. 6, Issue 4, 2015, pp.
1171-1177.
[3] Hu G., Xiang P., Ding Z., Liu R., Wang L., andTang T. A., Analytical Models for ElectricalPotential, Threshold Voltage, and Subthreshold
Swing of Junctionless Surrounding-Gate
Transistors, IEEE Trans. on Electron Devices,Vol. 61, Issue 3, 2014, pp.688-695.
[4] Trivedi N., Kumar M., Haldar S., Deswal S.,
Gupta M., and Gupta R. S., Analytical modelingof Junctionless Accumulation Mode Cylindrical
Surrounding Gate MOSFET (JAM-CSG),
International Journal of Numerical Modeling,
Vol.29, Issue 6, 2016, pp. 1036-1043.
[5] Baidya A., Lenka T. R., and Baishya S., Mixedmode simulation and analysis of 3D double gatejunctionless nanowire transistor for CMOS circuit
applications, Superlattices and Microstructures,

Fig. 6. Deviations of 1/𝛼𝑛 for higher order terms in
Jiang et. al.’s potential model in the range of (a) 𝑡𝑜𝑥 =2 𝑛𝑚, 𝐿𝑔 = 10 𝑛𝑚 , and (b) 𝑡𝑜𝑥 = 2 𝑛𝑚, 𝐿𝑔 =50 𝑛𝑚.

CONCLUSION

265

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Vol. 100, 2016, pp.14-23.
[6] Wong J. S., Ma J. G., Yeo K. S., and Do M. A., A
New Approach for the Extraction of Threshold
Voltage for MOSFET’s, Technical Proceedingsof the 2001 International Conference on Modelingand Simulation of Microsystems, (North
Carolina, NC, 2001) p. 534-537.
[7] Jung H. K., Drain Induced Barrier
Lowering(DIBL) SPICE Model for Sub-10 nm
Low Doped Double Gate MOSFET, Journal of the
Korea
InstituteofInformation
andCommunication Engineering, Vol. 21, Issue 8,
2017, pp. 1465-1473.
[8] Colinge J. P., Kranti A., Yan R., Lee C. W., Ferain
I., Yu R., Akhavan N. D., and Razavi P.,
Junctionless Nanowire Transistor (JNT):
Properties and design guidelines, Solid-StateElectronics, Vol. 65-66, 2011, pp. 33-37.
[9] Raksharam, and Dutta A. K., A unified analyticaldrain current model for Double-Gate junctionlessField-Effect Transistors including short channel
effects, Solid-State Electronics, Vol. 130, 2017,

pp. 33-40.
[10] Jiang C., Liang R., Wang J., and Xu J., A twodimensional analytical moel for short channel
junctionless double-gate MOSFETs, AIP
ADVANCES, Vol. 5, Issue 5, 2015, pp.057122-113.
[11] Lin Z., Lin H., Liu K., and Huang T., Analytical
Model of Subthreshold Current and Threshold
Voltage for Fully Depleted Double-Gated
Junctionless Transistor, Japanese Journal ofApplied Physics, Vol. 51, Issue 2S, 2012, pp.
02BC14-1-7.
[12] Jin X., Liu X., Wu M., Chuai R., Lee J., and Lee
J., Modelling of the nanoscale channel length
effect on the subthreshold characteristics ofjunctionless field-effect transistors with asymmetric double-gate structure, J. Phys. D:
Appl. Phys., Vol. 45, Issue 37, 2012, pp. 3751021-5.
[13] Dimitrijev S., Principles of Semiconductor
Devices, 2nd ed. New York, NY:
OxfordUniversity Press, 2012, p.453.

266

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PERFORMANCE EVALUATION OF PARTIALLY PRESTRESSEDCONCRETE BEAMS UNDER LIMITED CYCLES OF REPEATEDLYAPPLIED LOADING
1

Nazar K. Oukaili1 and Mohammed M. Khattab2
Professor, University of Baghdad, Iraq; 2Ph.D. Candidate, University of Baghdad, Iraq

ABSTRACTThis paper involves results of the study undertaken on the partially prestressed concrete beams with bonded
prestressing steel subjected to limited cycles of repeated loading. The flexural behavior of partially prestressed
concrete beams has been investigated through an experimental program involving testing six full-scale simply
supported beams with a clear span of (3000) mm. The goal of this study was to investigate the effect of limited
repeated loading cycles on strength and serviceability (cracking and deformability) of partially prestressed
concrete beams. Accordingly, these beams were divided into two identical sets. The first set consisted of three
beams, one of tension-controlled, the second of transition-controlled, and the last one is compression-controlled.
These beams are tested under static loading and considered as controlled beams. They were subjected to fourpoint bending by using two symmetrical concentrated static loads up to destruction. The loads were applied at
the middle third of the clear span length. The second set consisted of exactly the same three beams as in set one
but they were subjected to ten cycles of repeated load. The range of repeated load was between “0.4 to 0.6” ofultimate load produced from the static test. After the ten cycles, the load was released and then the beams were
subjected to monotonic static test until failure. Readings were made for strains in nonprestressed and prestressedsteel, midspan deflections, crack widths and crack spacing at different loading increments. Findings show thatpartially prestressed compression-controlled beams were less sensitive to the repeated loading.
Keywords: Partial Prestressing, Bonded, Flexure, Deflection, Cracking, Repeated Load, Concrete Beams.

researchers [1] – [5], however, suitable experimental
information is still poor. The objective of the current
research is to examine the influence of limited
number of repeated load cycles on the flexural
characteristics of partially prestressed concretebeams with bonded strands.

INTRODUCTION
Civil engineering structures may be exposed todifferent types of loads and among these loads is therepeated loading. The nature of loads that are
exposed to bridges, offshore and multistory car
parking are in fact repeated loading. Extensive
theoretical and experimental studies of prestressed
concrete beams over so many years have led to very
well established methods for strength andserviceability design under static loads. However,
the influence of repeated loading on deformability
and cracking of prestressed concrete beams are still
limited and rarely understood. Moreover, having
clear understanding and reasonable interpretation of
the basics of deformability and cracking of concretebeams under different types of loading will improve
the serviceability design and help handling any
difficult situation, particularly if not addressed byavailable codes and standards. For that research onserviceability of concrete structures under repeatedloading has become more essential in the last years.
Concrete structures subjected to repeated loading
experience higher deflection comparing to those
exposed to static loading. These deflections were
including significant permanent sets. With theincreasing of the number of load cycles, thepermanent deflections are also increased. Thisphenomenon has been observed by several

EXPERIMENTAL PROGRAM
The experimental program involves testing six
full-scale simply supported beams with overall
dimensions of (200x300x3300) mm, which weredivided into two groups. The first group consisted ofthree beams, PP-B-TC-S, PP-B-TRC-S, and PP-BCC-S. According to ACI code [6], these specimens
were tension–controlled, transition-controlled andcompression-controlled, respectively. Beams of thefirst group (I) were tested under monotonic static
loading to collapse and regarded as controlled beams.
The static loading was applied with increments
ranged approximately between 2.5% to 5% of thepredicted ultimate load. The deflection readings at
midspan section were monitored by mechanical dialgauge at the end of each increment. The time
consuming for testing one beam under static loading
on average is between four to six hours dependingon the load capacity of tested beam.
The second group (II) is consisted of three beams,
also, which identical to the beams of the first group
267

SEE - Nagoya, Japan, Nov.12-14, 2018

but they were subjected to repeat loading as follows:• Stage one: the minimum and maximum cyclicloads 𝑷𝑷𝒎𝒎𝒎𝒎𝒎𝒎 and 𝑷𝑷𝒎𝒎𝒎𝒎𝒎𝒎 were taken, respectively, as
40% and 60% of the ultimate load of theaccompanying beams of group (I). The repeatedstatic load was applied by increments each equals
to 5% of static ultimate load until reaching 𝑷𝑷𝒎𝒎𝒎𝒎𝒎𝒎
and then unloaded to 𝑷𝑷𝒎𝒎𝒎𝒎𝒎𝒎 by the same
increments. Ten cycles of loading and unloadingwere implemented. The deflections, crack widths,
crack spacing, crack numbers, and strand slip wererecorded for each loading increment.
• Stage two: after ten cycles of loading, the load
was released to zero. The residual deflections,crack width and strand slip were investigated.
• Stage three: in this stage, the beams were
subjected to monotonic static loading until failure
with increment equal to approximately 5% of theultimate load of the accompanying beams of group(I). During the third stage, the same measurements(deflections, crack width, number of cracks,
distance between cracks and strand slip) weretaken for each load increments. The whole
repeated load test took on average between 10 to
14 hours.
For the six rectangular pretensioned beams, thereference concrete mix was designed to achieve thetarget compressive strength of 40 MPa at 28 days for(150x300) mm cylinder specimen. Concrete
proportions by weight, cement: sand: gravel, were 1:
1.5: 2 with a maximum aggregate size of 9.5 mm
and water cement ratio by weight of 0.40. The
beams were designed in such a way that the
expected failure should occur due to flexure rather
than shear; therefore, steel stirrups of ∅10 mm @100 mm c/c were used in shear spans. The steel
stirrups were tied to two longitudinal bars of (10mm) diameter at the top and to different number ofbars at the bottom depending on whether the beam is
tension-controlled, transition or compressioncontrolled. In all prestressed concrete beams, two
low-relaxation seven wires strands were used withtarget initial prestress 𝑓𝑓𝑝𝑝𝑝𝑝 of 70% of the steel
ultimate strength 𝑓𝑓𝑝𝑝𝑝𝑝 . Yield stress of the longitudinal
and the transverse mild steel bars was (570 MPa)and the characteristics strength of prestressed lowrelaxation strand was (1862 MPa). Table 1 illustrates
the PPR value and the nonprestressing tensile steelof each tested beams. Figure 1 shows thereinforcement details of each tested beam.
Two variables were investigated in this study,
they are:• Type of test (monotonic static and repeatedloading)• Partial Prestressing Ratio (PPR) which defined as
the ratio of ultimate resisting moment due toprestressing steel to the ultimate resisting moment
due to the total tensile steel [7].

All beams were loaded in four-point bending
using two symmetrical concentrated static loads
applied at the middle-third of span length. All themeasurements, such as midspan beam deflection,
crack width and strand slip was recorded twice,
immediately after the application of the load and 10
minutes later.
Deflection was measured at midspan of the beamusing dial gauge of (0.01) mm accuracy. The cracks
along the beams, the maximum crack width, averagecrack spacing and number of cracks were measured
during loading, sequentially. Strain in both types ofsteel (prestressed and nonprestressed) was recorded
starting from stress transfer passing through load test
until failure by using two electrical strain gauges
fixed on each reinforcing bar.
Table 1 Details of experimental beams
First
group
Second
group
PPR
Mild
steel intensionzone

PP-B-TC-S

PP-B-TRC-S

PP-B-CC-S

PP-B-TC-R

PP-B-TRC-R

PP-B-CC-R

0.771

0.529

0.358

2-Ø10

2-Ø10 +
2-Ø12

6-Ø12

Fig. 1 Reinforcement details of experimental beams.
EXPERIMENTAL RESULTS
All beams in this study showed no fracture ofsteel or bond slip between concrete and any type ofreinforcement (prestressed and nonprestressed). The
failure was due to yielding of steel followed bycrushing of concrete at compression zone fortension-controlled beams or by crushing of concretefor compression-controlled beams.
Load - Deflection Response
The load deflection curves for the tested beams
are shown in (Fig. 2). Each two curves for identicalbeams were depicted together (one for the specimen
under monotonic static loading and the other for the268

SEE - Nagoya, Japan, Nov.12-14, 2018

specimen which exposed to ten cycles of repeatedloading) to simplify comparison process. Also, theten load cycles behavior was magnified for moreclarity.

geometrical location of this steel relative to themember neutral axis.
• Beams with low amount of nonprestressed steel(high level of PPR) exhibited more ductile
behavior by their flatter and longer load deflection
curve.
• After ten cycles of repeated loading, when theload is decreased gradually to zero, all the beams
suffered from permanent deflection. For specimen
PP-B-TC-R which has high PPR, the permanent
deflection was minimum (0.85 mm) and this may
attributed to the fact that, the high ratio ofprestressing moment to the total nominal moment
has considerable effect to decrease the permanent
deflection to minimum value. Otherwise beam PPB-CC-R which has high nonprestressing steel (lowPPR), the permanent deflection after load release
was the higher and it was 1.55 mm. It seems thatthe small ratio of prestressing moment to the total
nominal moment has no ability to restrain the
deformability of that beam.
Table 2 illustrates the load carrying capacities forboth beam’s groups.
It can be seen that the difference in load carrying
capacity for the identical beams are very small inboth tests. The maximum difference was about 5%
only. It can be seen also that both values of ultimate
load in both tests are very close to the theoreticalvalue [8].

𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒,𝑆𝑆
𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒,𝑅𝑅

𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒,𝑅𝑅 ,(kN)

Fig. 2 Load-deflection curves for the tested beams.

𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒,𝑆𝑆 ,(kN)

Beam'slabeling

𝑃𝑃𝑡𝑡ℎ𝑒𝑒𝑒𝑒𝑒𝑒,𝑆𝑆 ,(kN)

Table 2 Theoretical and experimental load carrying
capacities

PP-B-TC-S,R
172
182
177
1.03
PP-B-TRC-S,R
213
230
243
0.95
PP-B-CC-S,R
209
310
312
0.99
Note: 𝑃𝑃𝑡𝑡ℎ𝑒𝑒𝑒𝑒,𝑆𝑆 = theoretical ultimate load due tomonotonic static loading [8]; 𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒,𝑆𝑆 = ultimate load
produced from monotonic static test; 𝑃𝑃𝑒𝑒𝑒𝑒𝑒𝑒,𝑅𝑅 =ultimate load produced from repeated static test.

Inspecting these diagrams, the following
observations may be recorded:• In monotonic static test, tension-controlled andtransition-controlled concrete beams, three
distinctive points could be observed. These points
are characterized by cracking, yielding andultimate loads. Compression-controlled concretebeams are characterized by two points only which
are the cracking and ultimate loads. Thus, clear
yielding point cannot be distinguished.
• Prior to cracking all beams deformed elastically.
After cracking, beams with low (PPR) developed
approximately a linear load-deflection response.
• All beams experienced decreasing of stiffness
after cracking, depending on the level of (PPR).
Increasing the area of tension reinforcement
produced stiffer beam which led to low rate ofdeflection progress versus the applied load.
• For tension-controlled and transition-controlled
beams, almost nonprestressed steel in tension zone
yielded prior to prestressed steel due to the far

Figure 3 characterizes midspan deflection at
maximum service load stage (0.6 𝑃𝑃𝑢𝑢 ) versus numberof load cycles for the three tested beams under
repeated loading.
The diagram shows that the variation ofdeflection with respect to load cycles can be
represented by the following regression logarithmic
expression:∆ = ∆𝑠𝑠𝑠𝑠 + 𝛼𝛼 𝑙𝑙𝑙𝑙(𝑁𝑁)

(1)

where
∆ = midspan deflection due to repeated static

269

SEE - Nagoya, Japan, Nov.12-14, 2018loading;∆𝑠𝑠𝑠𝑠 = midspan deflection due to monotonic static
loading immediately before the application of therepeated loading;𝛼𝛼 = parameter depends on PPR value; and𝑁𝑁 = number of cycles of repeated static loading.
The above mentioned expression can be regarded
as a general equation because the number of beams
which were tested under repeated loading in thisstudy is not sufficient to get a satisfied value of 𝛼𝛼. It
is required to test further beams with different PPR
value to find a reliable value of the parameter 𝛼𝛼.

PP-B-CC-R

𝜀𝜀𝑝𝑝𝑝𝑝𝜀𝜀𝑝𝑝𝑝𝑝(1)𝜀𝜀𝑝𝑝𝑝𝑝(10)𝜀𝜀𝑝𝑝𝑝𝑝(𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟)
𝜀𝜀𝑝𝑝𝑝𝑝𝑓𝑓𝑝𝑝𝑝𝑝 , (MPa)𝜀𝜀𝑠𝑠𝑠𝑠𝜀𝜀𝑠𝑠(1)𝜀𝜀𝑠𝑠(10)𝜀𝜀𝑠𝑠(𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟)
𝜀𝜀𝑠𝑠
𝑓𝑓𝑠𝑠 , (MPa)PP-B-TRC-R

Beam'slabeling

PP-B-TC-R

loading

+6032
+7014
+7211
+6189
+11299
1786
-786
+480
+848
-327
+3021
570

+6091
+7272
+7350
+6209
+11128
1786
-393
+624
+746
-218
+3211
570

+5741
+6677
+6794
+5897
+8783
1683
-236
+1412
+1735
+227
+2652
530

where: 𝜀𝜀𝑝𝑝𝑝𝑝 =effective prestrain; 𝜀𝜀𝑝𝑝𝑝𝑝(1) , 𝜀𝜀𝑝𝑝𝑝𝑝(10) = totalstrain in prestressed steel strain at the first and thetenth loading cycles, respectively; 𝜀𝜀𝑝𝑝𝑝𝑝(𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟) =strain in prestressed steel at load release; 𝜀𝜀𝑝𝑝𝑝𝑝 , 𝑓𝑓𝑝𝑝𝑝𝑝
prestressed steel total strain and stress at failure,
respectively; 𝜀𝜀𝑠𝑠𝑠𝑠 = strain in nonprestressed steel atthe beginning of test; 𝜀𝜀𝑠𝑠(1) , 𝜀𝜀𝑠𝑠(10) = nonprestressedsteel strain at the first and the tenth loading cycles,
respectively; 𝜀𝜀𝑠𝑠(𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟) = residual nonprestressedsteel strain at load release; and 𝜀𝜀𝑠𝑠 , 𝑓𝑓𝑠𝑠 nonprestressedsteel total strain and stress at failure, respectively.

Fig. 3 Midspan deflection at the maximum load
range (0.6 𝑃𝑃𝑢𝑢 ) for each loading cycle.
Strain in Steel Reinforcement

The strain in both types of steel has been
documented starting from the moment of initialprestressing passing through stress transfer, testing
until failure. Two strain gauges were fixed at eachstrand as well as nonprestressing tensile steel. Table
3 shows prestressed and nonprestressed steel strain
at different stages for the tested beam under repeatedloading.
Analyzing Table 3, the following findings may
be noticed:• The difference in strain between the first and thetenth loading cycles was very small in prestressedsteel. It was between 1% and 2.8%. While, thechange was significant in nonprestressed steel, it
was between 20% and 29%.
• The residual strain after ten cycles of repeatedloading and load release to zero was very little inboth types of steel. Actually, this strain is due toplastic deformation of concrete because neither
prestressed steel nor nonprestressed steel reachyielding when they subjected to these cycles.
• At failure, all strands in the three tested beams
under repeated loading reached yielding (thestress was beyond 90% of ultimate strength ofprestressed steel).

Crack Spacing and Crack Width
The evaluation of flexural crack width anddistances between cracks and how to control theirdevelopment becomes very essential. Studies in thisarea are very limited due to the various parameters
affecting crack width. Primary cracks initiated when
the applied load reaches the cracking load. As theapplied loading increased, additional cracks willappear. The number of cracks will be stabilized if
the stress in concrete does not exceed the tensile
strength irrespective of loading increase. Thiscondition produces the absolute minimum crack
spacing which happens at high stress in steel. This iscalled "stabilized minimum crack spacing". The
maximum crack spacing is twice the minimum andis called "stabilized maximum crack spacing". The
stabilized mean crack is the mean value of the above
two extremes [9].
Number of expressions was developed byresearchers to expect stabilized mean crack spacing
but the most reliable equation was anticipated by
Nawy [9] which is as follows:(2)
𝑎𝑎𝑐𝑐𝑐𝑐 = 𝑘𝑘 𝐴𝐴𝑡𝑡 ⁄∑ 𝑜𝑜

Table 3 Progress of steel micro-strains during
270

SEE - Nagoya, Japan, Nov.12-14, 2018

cracks is stabilized from the first load cycle forcompression-controlled beam (PP-B-CC-R) while
for the other beams; it is stabilized at the fifthloading cycle.
Table 4 illustrates experimental mean crack
spacing for beams under monotonic static test andthe value determined using Nawy’s expression (Eq.
(2)). Table 4 shows also mean crack spacing forbeams subjected to repeated test at service load stage(0.6 𝑃𝑃𝑢𝑢 ) for the first and the tenth loading cycles.
Since the number of cracks is increased forbeams PP-B-TC-R and PP-B-TRC-R between thefirst and the tenth loading cycles, therefore, themean crack spacing due to that is decreased asshown in Table 4. The crack spacing is decreased forbeam PP-B-TRC-R but with a small difference incomparison to specimen PP-B-TC-R. Except for
beam PP-B-TC-R, Nawy’s equation gave acomparable crack spacing results with respect to theexperimental results of static test.

where
𝑎𝑎𝑐𝑐𝑐𝑐 = stabilized mean crack spacing;𝑘𝑘 = 1.2 for pretensioned beams and 1.54 forposttensioned beams;
𝐴𝐴𝑡𝑡 = area of concrete surrounding the tensile
reinforcement bars; and∑ 𝑜𝑜 = sum of the reinforcement element's
circumferences.
Recent studies on crack width control aresupported on experimental studies. Based on thesestudies, some concluding points can be considered,mainly, using of deformed bars is minimizing thecrack widths, the maximum crack width is
proportional to reinforcement stress, the distributionof reinforcement over the concrete tension zone will
minimize the flexural crack widths, and the crack
width at the extreme tensile concrete fiber is
proportional to the concrete cover.
Gergely and Lutz [10] suggested the following
equation to determine crack width:

Table 4 Mean crack spacing for tested beams

where
𝑹𝑹𝒊𝒊 = ratio of distances from tension face and steel
centroid to neutral axis;∆𝒇𝒇𝒔𝒔 = net tensile stress in reinforcing steel;𝒅𝒅𝒄𝒄 = thickness of concrete cover measured from
center of bar closest to the concrete face to thetension concrete face; and𝑨𝑨𝒃𝒃 = concrete area surrounding one bar, equal tototal effective tension area of concretesurrounding reinforcement and having same
centroid divided by number of bars.

Beam'slabeling

PP-B-TC-S,R
PP-B-TRC-S,R
PP-B-CC-S,R

Monotonic
staticloading

Repeated static
loadingExp. 𝒂𝒂𝒄𝒄𝒄𝒄 , (mm)at 1stcycle

at 10th
cycle

185
115
85

140
125
115

115
120
115

(mm)

(3)

110
100
100

Table 5 shows crack width of the beams tested
under static loading and the counterpart beams thatwere exposed to repeated loading. As in Table 4, theresults are at service load stage (0.6 𝑃𝑃𝑢𝑢 ) and for
repeated test, the table shows crack width at the first
and tenth loading cycles.

Most cracks in all tested beams were propagatedat the location of the middle third perpendicular tothe longitudinal axis of the beam and extended to thetensile reinforcement. Mean crack spacing, crack
width and number of cracks were monitored andmeasured throughout the test.
Figure 4 illustrates number of cracks versus load
cycles at the maximum service load range of (0.6 𝑃𝑃𝑢𝑢 )for the beams tested under repeated loading.

Table 5 Crack width at loading stage of (0.6 𝑃𝑃𝑢𝑢 )Monotonic
staticloading

Beam'slabeling

PP-B-TC-S,R
PP-B-TRC-S,R
PP-B-CC-S,R

Repeated static
loadingExp.
𝑤𝑤𝑐𝑐𝑐𝑐 , (mm)Exp.
𝑤𝑤𝑐𝑐𝑐𝑐 , (mm)𝑤𝑤𝑐𝑐𝑐𝑐 = 1.10276 × 10 𝑅𝑅𝑖𝑖 ∆𝑓𝑓𝑠𝑠 �𝑑𝑑𝑐𝑐 𝐴𝐴𝑏𝑏

Theor.
𝒂𝒂𝒄𝒄𝒄𝒄 ,(mm)
Exp. 𝒂𝒂𝒄𝒄𝒄𝒄

3

Theor.
𝑤𝑤𝑐𝑐𝑐𝑐 , (mm)−5

at 1stcycle

at10th
cycle

0.05
0.10
0.15

0.03
0.17
0.12

0.10
0.15
0.10

0.15
0.15
0.10

From Table 5, the following observations may bereported:• Crack width calculated using Gergely and Lutz
expression, for specimens under monotonic static

Fig. 4 Number of cracks versus number of load
cycles at load level of (0.6 𝑃𝑃𝑢𝑢 ).
These diagrams indicate that the number of271

SEE - Nagoya, Japan, Nov.12-14, 2018loading, gave good agreements of resultscomparing to the experimental results.
• Only for beam PP-B-TC-R, the crack width isinfluenced by repeated loading. It is increased byabout 50% during the ten loading cycles.
Figure 5 shows all the tested beams at failure. It
can be observed that, the limited repeated loading
has no significant effect on the number of cracks,
cracks propagation and crack alignment. The figure
shows also that, in compression-controlled beams
the cracks were of flexural and flexural-shear types.
On the other hand, in tension-controlled beams, thecracks were only of flexural type and they wereapproximately located at the pure bending momentzone (the middle third).

decreased. Accordingly, in beams with highnonprestressing steel (i.e., low level of PPR) theprestressing force has no ability to restrain the
deformability of the beam in small range.
8. All strands in all the beams, attained yielding
strength.
REFERENCES[1] Kulkarni, G., & Ng, S., Behavior of limited
prestressed concrete beams under repeated loads,
Canadian Journal of Civil Engineering, Vol. 6,
Issue 4, 1979, pp. 544-556.
[2] Naaman, A., Fatigue in partially prestressed
beams, Fatigue of Concrete Structures, SP-75,
American Concrete Institute, 1982, Farmington
Hills, Michigan, pp. 25-46.
[3] Wong, Y., the Deflection of Reinforced andPartially Prestressed Concrete Box Beams
under Repeated Loading, Ph.D. Thesis,
University of Wollongong, 1984.
[4] Harajli, M., & Namman, A., Cracking inpartially prestressed beams under static andcyclic fatigue loading, Cracking in Prestressed
Concrete Structures, SP-113, American
Concrete Institute, 1989, Farmington Hills,
Michigan, pp. 29-54.
[5] Harajli, M., Strengthening of concrete beams
by external prestressing, PCI Journal, Vol. 38,
Issue 6, 1993, pp. 76-88.
[6] ACI 318M-2014, Building code requirements
for structural concrete (ACI 318M-14) andcommentary, ACI Committee 318, 2014,
Farmington Hills, Michigan.
[7] Harajli, M.H. and Naaman, A. E., Deformation
and Cracking of Partially Prestressed Concrete
Beams Under Static and Cycles Fatigue
Loading, Report No. UMEE 84R1 Department
of Civil Engineering, the University ofMichigan, College of Engineering, 1984, pp. 21.
[8] Oukaili, N. K. and Khattab, M. M., Cracking
and Deformability of Bonded and Unbonded
Prestressed Concrete Beams under Monotonic
Static Loading, Third International Conference
on Science, Engineering & Environment (SEE),
USQ, Brisbane, Australia, Nov.13-16, 2017,
ISBN: 978-4-9905958-9-0 C3051[9] Nawy, E. G., Prestressed Concrete: A
Fundamental Approach, Prentice Hall, 5th
Edition, 2009, pp. 198 - 20.
[10] Gergely, P., and Lutz, L., Maximum Crack
Width in Reinforced Concrete Flexural
Members, Cracks, Mechanism, and Control of
Cracking in Concrete, ACI Publication SP-20,
pp.87-11, 1966.

Figure 5 Crack propagation of tested beams.
CONCLUSIONS
The following conclusions can be drawn:
1. The ultimate load carrying capacities of partiallyprestressed concrete beams exposed to limited
cycles of repeated loading was approximately thesame as the capacities of accompanying beams
under monotonic static loading.
2. The response of load-deflection curve under
repeated loading can be represented by theenvelope curve of monotonic static loading.
3. The increasing rate of deflection, crack width, andcrack spacing was significant in the first five load
cycles especially for tension-controlled beam.
4. All beams in this study showed no bond slip
between concrete and any type of reinforcement.
The failure was due to steel yielding followed bycrushing of concrete at compression zone fortension-controlled beams or by crushing of
concrete for compression-controlled beams.
5. Partially prestressed concrete beams with large
area of nonprestressing tension reinforcement,(i.e., low level of PPR), were less sensitive torepeated loading.
6. Increasing the amount of nonprestressing steelenhanced the flexural characteristics and theability of partially prestressed concrete beams toresist the effect of repeated loading.
7. The residual deflection depends on the value of
PPR, as PPR increased the residual deflection272

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

THE EFFECT OF FGD GYPSUM AND BOTTOM ASH ADDITION IN
SHOTCRETE MIXTURE
Pisut Rodvinij 1, Pitiwat Wattanachai 1 and Sattaya Chaiwithee 1
1
Faculty of Engineering, Chiang Mai University, Thailand

ABSTRACTThe slope in Mae Moh mine has been eroded when it is exposed to weather changes. Therefore, shotcrete
was used for temporary protection of slope surfaces. In order to improve the efficiency and reduced cost of
shotcrete, by-product materials from Mae Moh power plant is a good alternative to use in the mixture. This study
focused on the influence of flue gas desulphurization (FGD) gypsum on the properties of shotcrete used bottom
ash as fine aggregate. The mixture of mortar mixed with by-product materials was a combination of Portland
cement type 1 and bottom ash is a ratio of 1:3. FGD gypsum added in the mixture 0-12% by weight of cement.
Water to cement ratio for a mortar is 0.6. The results demonstrated the slump flow of mortar decreases with FGD
gypsum increment. However, the initial setting time and final setting time of the shotcrete were longer with
gypsum increment. The compressive strength of the samples contains FGD gypsum 4% can be developed thestrength of approximately 8-20% of the samples without FGD gypsum. Moreover, the compressive strength anddurability of mortar which contains gypsum at 4% could be able to give the highest strength. Nevertheless, thecompressive strength and durability of mortar tend to decrease when the samples containing FGD gypsum
exceed 4%. In conclusion, the development of the properties of shotcrete was the most efficient when adding 4%of FGD gypsum in the mixture.
Keywords: Shotcrete, FGD gypsum, Bottom ash, Compressive strength, Durability

surface water infiltration [4]. Shotcrete offers highwork performance in larger areas. However, a lot of
shotcretes might spray on the face of the slope. This
induced a high cost for the slope stabilization.
Therefore, by-product materials from Mae Moh
power plant is a good alternative to be used in the
mixture of shotcrete to reduce the cost. By-productmaterials consist of fly ash, bottom ash, and FGD
gypsum. Literature review demonstrated by-productmaterials from Mae Moh power plant is pozzolanicmaterials. The pozzolanic reaction can increase thestrength of mortar in a long term. Moreover, byproduct materials can be increased the efficiency of
the fresh mortar [5].
This study focused on bottom ash used as fineaggregate and FGD gypsum used as an admixture in
the mixture of shotcrete. The bottom ash particles
were relatively large and very irregular, showing
agglomeration of some spherical particles and otherfragments with observable pores [6]. The
replacement of sand by bottom ash in the mixture
mortar can be reduced the unit weight approximately
20% due to the unit weight of bottom ash particles isless than sand [7], [8]. However, bottom ash used asfine aggregates in mortar can only reach 60%-70%
the compressive strength of natural fine aggregates
mortar [9].
SO2 is one of the major environmental
contaminations generated from coal-burning power
stations. It is very important to develop flue gas

INTRODUCTION
Mae Moh mine is the largest surface mine inSoutheast Asia. Its annual production isapproximately 15 million tons [1]. The overburden
consists of claystone layer. Beneath claystone layer
was lignite layer. To excavate lignite for generated
the electricity, claystone must be mined out.
Therefore, the surface of claystone slopes orclaystone backfill might be exposed to weatherchange. The deterioration and erosion can occur on
the surface of the slope and induced the reduction of
the slope stability.
Pisut and Pitiwat [2] suggested that claystone
deteriorated when it has been exposed to weatherchange. This can lead to slope stability problems.
The failure of claystone slope can be induced many
problems with mining activities. However, theprotection of claystone from weather change canmaintain the physical characteristics of claystone
and the strength of claystone [2].
Therefore, shotcrete becomes the suitablestabilization method to stabilize the stability ofslopes in Mae Moh mine. Shotcrete is often used for
temporary protection of exposed rock surfaces thatwill deteriorate when exposed to the air. Moreover,shotcrete also used to permanently cover slopes or
cut that may erode in time or otherwise deteriorate[3]. Application of shotcrete to the surface oflandfills and other waste area is beneficial to prevent
273

SEE - Nagoya, Japan, Nov.12-14, 2018

desulphurization (FGD) technologies to remove SO2
for FGD clean coal combustion. Although FGD
technology is successful in reducing SO2 discharge,
it generates a large quantity of FGD gypsum at thesame time. Normally, FGD gypsum contains in mix
proportion of mortar can be increased the flexuralstrength and compressive strength was higher thanthe mixture without FGD gypsum. Although thesetting time was prolonged for the composition of
FGD gypsum [10]. Moreover, FGD gypsum can beincreased the durability of concrete from the sulfate
attack [11]. However, the suitable amount of FGD
gypsum contains in the mixture should bedetermined. This is due to the excessive amount of
FGD gypsum in the mixture can decrease
workability and the strength of mortar.
Therefore, the influence of FGD gypsum on theproperties of shotcrete used bottom ash as a fineaggregate is an important determinant. The
properties of shotcrete containing FGD gypsum
should be passed the requirement of the properties of
shotcrete for the slope stabilization. Thus, the test
results can suggest the optimum content of FGD
gypsum contain in the shotcrete mixture. The
optimum FGD gypsum content is the most efficient
to develop the properties of shotcrete.

The mixture of a normal mortar was a
combination of Portland cement type 1 and natural
sand is in a ratio of 1:3 by weight. However, themixture of a mortar mixed with by-product materials
was a combination of Portland cement type 1 andbottom ash is in a ratio of 1:3 by weight. FGD
gypsum adds in the mixture 0-12% by weight of
cement. Water to cement ratio for a normal mortar
and a mortar mixed with by-product materials is 0.6.
The mix proportion of shotcrete used in theexperimental shown in Table 1.
Table 1 Mix proportion of shotcrete mortar
FGD
BottomMixture code

Cement

Sand

Water

Gypsum

Ash
(%)

M01
MB01
MB01G4
MB01G8MB01G12

1
1
1
1
1

3
-

3
3
3
3

0.6
0.6
0.6
0.6
0.6

4
8
12

Note: The amount of FGD gypsum in the mixture is
the percent by weight of cement.
THE EXPERIMENTAL PROGRAM

MATERIALS PREPARATION ANDPROPORTION OF SHOTCRETE

MIX
Shotcrete mortar mixed according to Table 1
were used in the test. Fresh properties and hardened
properties of mortar were conducted on eachexperiment to measure the influence of FGD
gypsum on the properties of shotcrete.
The fresh properties evaluation consists of theslump flow and setting time. The slump flow test isintended to be used to determine the flows of mortar,
according to ASTM C1437 [13]. The setting time isintended to be used to determine the initial setting
time of mortar according to ASTM C191 [14]. The
hardened properties evaluation consists of thecompressive strength and durability. The
compressive strength test is intended to be used todetermine the compressive strength of mortar
according to ASTM C109 [15]. The specimen foreach mix proportion cast in the mold of mortar at
5×5×5 cm cube. The specimens were cured in thewater for 3, 7, 14, 28 and 56 days.
Shotcrete will be used as the surface protectionof claystone slopes from weather change. Therefore,
the durability of shotcrete is an important property
has been considered. The durability test was
conducted on the cube samples at 5×5×5 cm after
curing in the water for 28 days. The wet-dry process
was used to accelerate a deterioration of the samples.
The samples were immersed in the water for 24 hr
and heating in an oven at 100±5 °C for 24 hr. This
represents one cycle [16]. The experimental
investigated the durability of mortar in six cycles.
The unconfined compression test was conducted on

Percent Finer (%)

This study focused on the wet mix shotcrete. Wet
mix shotcrete is predominantly used because of its
homogeneity in quality and high work efficiency[12]. The normal mixture proportion of shotcreteconsists of sand used as fine aggregate, cement, andwater. For the shotcrete mixed with by-productmaterials, the mixture proportion consists of bottom
ash used as fine aggregate, cement, water and FGD
gypsum used as an admixture. However, the fineaggregate should comply with the quality
requirements of ASTM C 33 [4]. Particle size
distribution of fine aggregate in this experiment was,according to Fig. 1. Ordinary Portland cement type 1
is used throughout the experiments. Bottom ash and
FGD gypsum obtained from a Mae Moh power plantin Lampang province of Thailand.
100
90
80
70
60
50
40
30
20
10
0

Particle size distribution
used in the test
Boundary (ASTM C33)

0.1

1

10

Particle Size (mm)Fig. 1

Particle size distribution of fine aggregate.
274

SEE - Nagoya, Japan, Nov.12-14, 2018the samples which throughout the wet-dry process
for each cycle to determine the compressive strengthof deteriorated samples. The results can be
represented by the alteration of the compressive
strength of shotcrete mortar during the wet-dry
process.
The results obtained from the experiment can bedemonstrated the influence of FGD gypsum on theproperties of shotcrete. Moreover, the properties ofthe samples in each mixture have compared with therequired target properties of shotcrete in Table 2. Inorder to determine the optimum content of FGD
gypsum in the mixture of shotcrete for stabilizing
the slope in Mae Moh mine.

was similar. The flow of mortar which is notcontained FGD gypsum in the mixture wasapproximately 215 mm. The slump flow was in therange of the recommendation between 203-248 mm.
However, the flow of mortar tends to decrease
with an increase in the amount of FGD gypsum
contain in the mixture. The flow of the samples
which contains FGD gypsum 4%, 8%, and 12% was
209 mm, 207 mm and 191 mm, respectively. The
mixture which contains FGD gypsum more than 8%
demonstrated the slump flow was lower than theminimum required. Therefore, the optimum amountof FGD gypsum adds in the shotcrete mixture should
not exceed 8% by the weight of cement.

Table 2 The requirement for the properties of
shotcrete

Setting Time

Test

TargetStandard of testing

Initial setting time (min)≥ 180

ASTM C191

Slump flow (mm)203-248

ASTM C1437>100

ASTM C109

The requirement for the initial setting time of the
shotcrete mortar should be longer than 180 minutes.
The setting time for each mix of mortar as shown in
Fig. 3.

300

Compressive strength (ksc)

Final Setting time

28 days> 100

6 cyclesTime ( Minutes)

250

Durability (ksc)-

FRESH PROPERTIES OF SHOTCRETE

100

M01

Fig. 3

The requirement of flowability of mortar should
be between 203-248 mm. The results of slump flowfor each mix shown in Fig. 2.

200
180
160
140
120
100
MB01

MB01G4

MB01G8MB01

MB01G4

MB01G8MB01G12The setting time of shotcrete mortar foreach mixture.

The results demonstrated that the initial setting
time and the final setting time of the mortar usedbottom ash as a fine aggregate was shorter than themortar used sand as a fine aggregate. The initial andfinal setting times of M01 were 18 minutes and 13
minutes longer than MB01. The initial and final
setting time of M01 was 183 minutes and 250
minutes respectively. However, the requirement for
the initial setting time, it should be longer than 180
minutes. Thus, the initial setting time of mortar usedbottom ash as a fine aggregate was 165 minutes thatless than the minimum requirement.
Although, the initial setting time of MB01 lessthan the minimum requirement but FGD gypsum
add in the mixture can be increased the setting timesof mortar. This phenomenon caused by theabsorbability of FGD gypsum. The soluble gypsum
provides a range of available sulfate ions during
cement hydration. When gypsum exists, the sulfates
react with tricalcium aluminates to from ettringite

220

Slump Flow (mm)1500Slump Flow

Fig. 2200

50

Slump flow tests and setting time tests wereconducted on the fresh mortar to determine the fresh
properties of shotcrete. The trial mixes according toTable 1 were used in the test.

M01 (Control)

Initial setting time

MB01G12

The flowability of shotcrete mortar.

The results demonstrated that the slump flow of
shotcrete mortar used sand as fine aggregate andshotcrete mortar used bottom ash as a fine aggregate
275

SEE - Nagoya, Japan, Nov.12-14, 2018

immediately. It is assumed that ettringite forms
initially on the reacting C3A surface, a more or lessimpermeable coating that impends diffusion of theion needed to form hydrates that cause setting.
Consequently, the solubility of gypsum becomes
lower than ever and therefore cannot form ettringite
to retard setting time until gypsum is released [10].
The results demonstrated the initial and final
setting time tend to increase with an increase in theamount of FGD gypsum contains in the mixture. The
initial setting time of MB01G4, MB01G8, andMB01G12 was 180 minutes, 183 minutes and 191
minutes, respectively. The final setting time of
MB01G4, MB01G8, and MB01G12 was 255
minutes, 260 minutes and 271 minutes, respectively.
Thus, the mixture which contains FGD gypsum
exceeds 4% can be increased the initial setting timeof mortar was longer than the requirement.
Moreover, MB01G4 demonstrated the initial setting
time and the final setting time was near M01.

the failure plane of the mortar samples which usedbottom ash as fine aggregate. The samples
demonstrated the failure plane occur on the bottom
ash particles.
Bottom ash fine aggregates mortar can only
reach 75-85% of the compressive strength of thenormal shotcrete mortar. However, the pores in theparticle of bottom ash can be reduced the unit weightof shotcrete mortar. The unit weight of the bottom
ash aggregate mortar was approximately 1.8 T/m3
which is lower than sand aggregates mortar
approximately to 0.2-0.3 T/m3. Therefore, thereduction of the unit weight of MB01 wasapproximately 10-15% of M01.

HARDENED PROPERTIES OF SHOTCRETE
Compressive strength tests and durability tests
were conducted on the mortar samples to determine
the hardened properties of shotcrete.

Fig. 5

However, the compressive strength of bottom
ash aggregates mortar was increased when the
mixture containing FGD gypsum. The results
demonstrated the mixture which containing FGD
gypsum 4% by weight of cement can be increased
the compressive strength nearly the normal mortar in
3-14 days. However, MB01G4 can only reach 90%
the compressive strength of the normal mortar at 28
and 56 days. The influence of FGD gypsum on thecompressive strength of shotcrete used bottom ash as
fine aggregate represented in Fig. 6. The relationshipbetween the amount of FGD gypsum in the mixture
and compressive strength was shown.

Compressive Strength
The trial mixes according to Table 2 and curingin the water in 0-56 days were conducted on thecompression machine to determine the compressive
strength of mortar. The minimum requirement forthe compressive strength of shotcrete is 100 ksc at
the curing time 28 days. The results of thecompressive strength of each mix as shown in Fig. 4.
160
140
120
100

150

Compressive Strength (ksc)Compressive Strength (ksc)

The failure plane of shotcrete mortar usedbottom ash as fine aggregate.

80
60
40

M01

MB01

MB01G4

MB01G8MB01G12

20
0

10

20

30

40

50

Curing time (days)

100

50
3 Days
14 Days
56 Days

7 Days28 Days0

Fig. 40

The compressive strength of the shotcretemortar of each mix.

2

4

6

8

10

12

FGD Gypsum (%)

Fig. 6

The results show the compressive strength of thenormal shotcrete mortar was higher than the
shotcrete mortar used bottom ash as fine aggregate.
This is because the particle strength of bottom ash
was less than the particle strength of sand. The
bottom ash particles were with the much pores causeof a low strength of the particles [6]. Fig. 5 shows

The influence of FGD gypsum on thecompressive strength of shotcrete mortar.

The result demonstrated FGD gypsum 4%
contain in the mixture was the most efficient toincrease the compressive strength. The compressive
strength was higher than the samples without
276

SEE - Nagoya, Japan, Nov.12-14, 2018

gypsum approximately 8-20%. This is because FGD
gypsum obtained from Mae Moh power plant consistof SO3 approximately 49.54%. Therefore, thestrength increased when the content ratio of SO3 was
the optimum percentage [10]. SO3 seems to be
responsible for the higher early compressive strength[17].
The early strength of the samples contains
gypsum exceed 4% tend to decrease with an increasein the amount of gypsum. The compressive strengthof MB01G8 and MB01G12 can be reached 90% and
70% of the compressive strength of MB01G4 in 314 days. However, the compressive strength of
MB01G8 and MB01G12 was near the samples
contain gypsum 4% at 56 days. This is due to thelater age strength of the mixture is controlled mainly
by calcium silicate hydrate [17]. Consideration of
the minimum required strength at 28 days was 100
ksc, the strength of MB01, MB01G4, MB01G8 and
MB01G12 passed the requirement.

severely affects decreased the compressive strengthof MB01G12. The reduction of the compressive
strength was approximate to 12% in the first cycle
followed by slight decreased. However, MB01G8
and MB01 demonstrated the compressive strength
was similar in cycles 0-6. The compressive strengthof MB01 and MB01G8 decreased approximately
15% in six cycles.
The requirement for the compressive strength of
the shotcrete mortar which through the wet-dry
process in six cycles should be more than 100 ksc.
However, the remaining compressive strength of
MB01, MB01G4, MB01G8 MB01G12 in cycle six
was 105 ksc, 115 ksc, 102 ksc and 93 ksc
respectively. Therefore, the compressive strength of
the samples with gypsum 12% was lower than therequirement.
The influence of FGD gypsum on thecompressive strength of deteriorated samples shownin Fig. 8. The highest strength was demonstrated in
the samples with 4% FGD gypsum. The
compressive strength of the samples containing
gypsum 8% and 12% were less than MB01G4 inevery cycle. Moreover, the results show the
reduction of the compressive strength occurs incycles 1-2. However, the compressive strength tends
to similar in cycles 3-6. The compressive strength of
MB01G8 and MB01G12 was less than MB01G4
approximately 10% and 17% respectively in cycle 36. Thus, the deceleration of deterioration occurs inthe samples which through the wet-dry process morethan three cycles. This result demonstrated the mostdeterioration of shotcrete mortar due to wet-dry
conditions.

The Durability of Shotcrete Mortar
The investigation on the durability of shotcretemortar which through the wet-dry process for eachcycle shown in Fig. 7. The results demonstrated thecompressive strength of shotcrete mortar decreased
due to the deterioration. The compressive strength ofmortar tends to decrease with an increase in thenumber of wet-dry cycles. This is because thedeterioration occurs in the shotcrete mortar when it
has been exposed to the wet-dry conditions.

130
120

140

110

Compressive Strength (ksc)Compressive Strength (ksc)

140

100
90
80
70

MB01G460

MB01

MB01G8MB01G12

50
0

1

2

3

4

5

6

130
120
110
100
90
80
70

Wet-dry process (Cycles)

0 Cycle1 Cycle2 Cycle4 Cycle5 Cycle6 Cycle3 Cycle60
0Fig. 7

4

The compressive strength of the samples
for each cycle.

8

12

FGD Gypsum (%)

Fig. 8MB01G4 demonstrated the highest compressive
strength in six cycles. The compressive strength of
MB01G4 for each cycle was higher than MB01 andMB01G8 approximately 4-10%. Moreover, thestrength of MB01G4 for each cycle was higher than
MB01G12 approximately 15% - 23%. In cycle six,the compressive strength of MB01G4 reduced
approximately 9% of the strength at the curing age
28 days. The remaining compressive strength in thesixth cycle was 115 ksc.
The results demonstrated that the deterioration

The influence of FGD gypsum on thecompressive strength of deteriorated
samples.

CONCLUSION
In order to investigate the effect of FGD gypsumon the properties of shotcrete used bottom ash as
fine aggregate. This study investigated the fresh
properties and hardened properties of the shotcrete
samples. The fresh properties were carried out by
setting time tests and slump flow tests. The hardened
277

SEE - Nagoya, Japan, Nov.12-14, 2018

properties were carried out by the compressive
strength tests and durability tests.
Based on the experimental test obtained in thisstudy, the following conclusion was made:1. The slump flow of shotcrete mortar usedbottom ash as fine aggregate decreased with anincrease in the amount of FGD gypsum. However,
the initial setting time and final setting time of
shotcrete were longer with an increase in the amountof gypsum.
2. The compressive strength of the samples
contains FGD gypsum 4% can be developed thestrength 8-20% of the samples without gypsum.
However, the compressive strength tends to decrease
when the amount of FGD gypsum in the mixture
exceeds 4%.
3. The samples with 4% FGD gypsum
demonstrated the highest compressive strength when
the samples through the wet-dry process in six
cycles. The remaining compressive strength in thesixth cycle was 115 ksc. Therefore, the mixture of
shotcrete containing FGD gypsum 4% was the mostefficient to develop the durability of mortar.
4. Bottom ash aggregate mortar can be reduced
the cost approximately 40% of the normal mortar.

characteristics of fly ash and bottom ash
geopolymers", Waste Management, 29, 2008,
pp.539-543.
[6] Sathonsawaphak A, Chindaprasirt P, Pimraksa
K, "Workability and strength of lignite bottom
ash geopolymer mortar", Journal of Hazardous
Materials, 168, 2009, pp. 44-50.
[7] Juturapitakkul C, Cheerarot R, "Development ofbottom ash as pozzolanic material", Journal of
Materials in Civil Engineering, volume 15,
Issue 1, 2003.
[8] Kim HK, Lee HK, "Use of power plant bottom
ash as fine and coarse aggregates in highstrength concrete", Construction and Building
Materials, Vol. 25, 2010, pp. 1115-1122.
[9] Yang MJ, Wang HY, Liang CF, "Effects on
Strengths of Cement Mortar When Using
Incinerator Bottom Ash as Fine Aggregate,
World Journal of Engineering and Technology,
2, 2014, pp.42-47.
[10] Guo XL, Shi HS, "Thermal treatment andutilization of flue gas desulphurization gypsum
as an admixture in cement and concrete",
Construction and Building Materials, Vol. 22,
2008, pp. 1471-1476.
[11] Guo XL, Shi HS, Liu HY, "Effects of a
combined admixture of slag powder andthermally treated flue gas desulphurization(FGD) gypsum on the compressive strength anddurability of concrete", Materials andStructures, Vol. 42, 2009, pp. 263-270.
[12] Samaru Y, Sugiyama K, " Slope Stabilization
Using the Shotcrete Grid Beam System inJapan", Shotcrete Spring, 2005, pp. 36-40.
[13] ASTM C1437, Standard Test Method for Flowof Hydraulic Cement Mortar, 2007.
[14] ASTM C191, Standard Test Method for Timeof Setting of Hydraulic Cement by Vicat
Needle, 2007.
[15] ASTM C109, Standard Test Method forCompressive Strength of Hydraulic Cement
Mortars Cube Specimens, 2007.
[16] Sadisun IA, Shimada H, Ichinose M, Matsui K,"Study on the physical disintegration
characteristics of Subang claystone subjected tomodified slaking index test", Geotechnical andGeological Engineers, pp. 199-218.
[17] Agahabaglou AM, Boyaci OC, Hosseinnezhad
H, Felekoglu B, Ramyar K, "Effect of gypsum
type on properties of cementitious materials
containing high range water reducing
admixture", Cement and Concrete Composites,
Vol 68, 2016, pp. 15-26.

ACKNOWLEDGMENTS
The research work was done during the study at
Chiang Mai University. The authors would like toexpress their appreciation to the Graduate School,
Chiang Mai University, for the financial support.
REFERENCES[1] Leelasuksaree C, Mavong N, Khosravi MH,
Pipatpongsa T, "Physical and numerical models
of undercut slope lying on steeply inclined
bedding plane", in 17th National Convention on
Civil Engineering, 2012, pp.GTE045-1GTE045-10.
[2] Rodvinij P, Wattanachai, P, "Influence ofclaystone deterioration on shear strength of
backfill", International Journal of GEOMATE,
Vol. 13, 2017, pp. 54-59.
[3] Abramson LW, Lee TS, Shama S, Boyce GM,
Slope Stability and Stabilization Methods,
Second Edition, New Jersey: John Wiley &Sons, 1996.
[4] US Army Corps of Engineering, "Engineeringand Design Standard Practice for Shotcrete",
1993, pp. 2-1 -4-7.
[5] Chindaprasirt P, Jaturapitakkul C, Chalee W,
Rattanasak U, "Comparative study on the278

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

USE OF DRY MIXING METHOD IN FLY ASH BASED GEOPOLYMER
AS A STABILIZER FOR DREDGED SOIL
Jonathan R. Dungca1, Kimberly D. Ang2, Aila Mae L. Isaac2, John Joshua R. Joven2 and Ma. Beatrice T.
Sollano2
1
Faculty, De La Salle University, Philippines; 2Graduate, De La Salle University, Philippines
ABSTRACTThis study aims to improve the properties of dredged soil obtained from a river in the Philippines. Different
percentages of fly-ash based geopolymer, namely 10%, 20%, 30% were used using dry mixing method todetermine the optimum mix. The procedures based on the ASTM standards were conducted to determine the index
properties namely Grain Size Distribution Curve (ASTM D422), Specific Gravity (ASTM D854), Atterberg’s
Limits (D4318), and CBR Test (ASTM D1833) and UCS test (ASTM D2166) of untreated soil. While only the
California Bearing Ratio Test and UCS test were conducted on the treated soil. The experimental results showedthat the fly-ash based geopolymer improved both the CBR index and the Unconfined Compression Strength of thedredged soil. The optimum mix for the soil-geopolymer mix was 30% because it displayed the largest increase in
the CBR index (50.23%) and Unconfined Compressive Strength (912.88 Kpa).
.
Keywords: fly ash, geopolymer, soil stabilization, california bearing ratio, unconfined compressive strength

such as blast furnace slag, silica fume, fly ash or
bottom ash and an alkali activator. Through this
synthesis, a structured polymer is created forming
series of sialate monomers that has similar properties
to cement. Fly-ash based geopolymers have alreadybeen studied as an alternative for cement that haveshowed an increase in compressive strength,
resistance to acid and low shrinkage. With the
reduction of carbon dioxide in the production of acementitious material through geopolymer, the study
aims to create an effective geopolymer mix that willstabilize the dredged soil. Thus for this study, ageopolymer based on fly ash will be used to modify
and improve the geotechnical properties of dredged
soil that will be obtained from a river beside a coal
fired power plant in Mindanao. Numerous studies
have shown that coal combustion by-products, ormore commonly known as CCPs, have been found to
be a good choice because it is very abundant in the
country and has a problem in disposal [3-10]. The
tests that will be conducted in the study are theStandard Proctor test, CBR and UnconfinedCompression Test [11-13].

INTRODUCTION
Soil stabilization is an engineering process which
is used to modify and improve the properties of thenatural soil. The main objective of soil stabilization is
to increase its soil strength and stability. Other soil
properties like its durability, permeability and bearing
capacity must also be considered in order to achieve
the required soil specifications for construction
applications. This process can be applied to theconstruction of roads, pavements, embankments andother uses. Two processes of soil stabilization include
mechanical stabilization and chemical stabilization.
Chemical stabilization is subjected to chemical
reactions of the stabilizer and the minerals of the soil.
Based on previous studies, cement, lime, bitumen andfly ash are the commonly used stabilizing agents thatutilize the industrial wastes and natural resources [1].
The use of dredged material as a resource has broadsocial, environmental, and financial benefits, thus,
contributes to global sustainability. Its two broad
categories of uses are engineering uses andenvironmental uses and the utilization of the dredged
soil for beneficial uses may be considered as anenvironmental friendly and economical option. In
order to achieve this goal, chemical admixtures are to
be added to the dredged material so that its properties
are modified. Past studies have been attempted tomodify dredged material as the fill materials, forinstance, the use of blast furnace slag cement andquicklime as additives to modify the dredged materialas the embankment fill [2].

The primary objective of the study is to investigate
the effects of using dry mixing method of fly ash
based geopolymer as stabilizer to improve on thegeotechnical properties of dredged soil. Moreover,the study aims to incorporate the soil stabilization
process by performing tests on the untreated soil andat the same time evaluate the increase on the shear
strength and load bearing capacity. Lastly is todetermine the application of the various mixture
proportions of dredged soil and geopolymer.

Geopolymer is synthesized through a mixture ofaluminosilicate raw material from industrial wastes
279

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RESULTS AND DISCUSSIONSMETHODOLOGY

Compressive Strength of Pure Geopolymer Paste

Tests in accordance to the ASTM standards are
utilized on the dredged soil sample to determine theeffect of using dry-mixing method in fly ash based
geopolymer as a stabilizing agent on the untreatedsoil.

A compressive strength test was conducted on
the pure geopolymer paste using the two different fly
ash that was given by the power plant. The differencewith the two types of fly ash was that, Fly Ash 1(FA1) did not undergo desulfurization in the
production of power, however Fly Ash 2 (FA2)undergone desulfurization in its production of power.
The geopolymer paste was consisted of of 0% soil and100% geopolymer using the dry mix method. Table 1
shows that it garnered an average compressive
strength of 10.46MPa, while at Table 2 shows that it
only reached a strength of 2.2MPa.

In this study, the soil that was dredged from aheavily silted river beside the coal fired power plantin Mindanao was used as the soil specimen. The
properties and characterizations of the dredged
material were obtained by conducting several test
procedures. The determination of its water content
and its optimum moisture content are its prime
importance.

Table 1. Compressive Strength of FA1 (Without
Desulfurization)
Strength
Area (mm2)
F (N)
(MPa)
2,451.28
31,10012.69
2,450.91
31,6008.81
2,429.08
34,000
9.88
Average
10.46

Dry alkaline activators which are the sodium
silicate and sodium hydroxide were utilized in thisstudy. Sodium silicate is a common name for sodium
metasilicate and its term is also known as a waterglass solution. This can be both in solid and in liquid
form, thus, it is constant in both neutral and alkaline
solution. Sodium silicate alone is not advisable to be
used as an alkaline activator, since it does not possessenough potential to initiate pozzolanic reaction
independently. Thus, it is commonly mixed with
Sodium hydroxide as an assisting agent to improve
the overall strength of specimen. Sodium hydroxide,
NaOH, is an organic compound and is also known ascaustic soda. It is described as a white solid with ahighly caustic metallic base and alkali salt. It can bein powdered form or any granular or flakey material.
It is a commonly used activator for
geopolymerization and it can be combined withsodium silicate for the production of geopolymer
paste.

Table 2. Compressive Strength of FA2 (With
Desulfurization)
Strength
Area (mm2)
F (N)
(MPa)
2,409.70
5,400
2.24
2,437.65
4,800
1.98
2,353.70
4,300
1.83
Average
2.20
Characterization of Geotechnical Properties ofDredged Material
The basic physical characterization of the puredredged soil such as the specific gravity, particle size
analysis, atterberg limits and standard proctor test
were examined to obtain its geotechnical properties.
More so, based on the Unified Soil Classification
System (USCS) and AASHTO, the dredged soil wasclassified as Poorly Graded Sand (SP) and Fine Sand
(A-3) respectively. The untreated soil was oven-driedprior to testing to attain consistent results, following
the ASTM procedures and thus, Table 3 shows thegarnered results from the three trials that wereconducted per test.

The study involved experimental procedures in
the laboratory including its soil characterization tests,
design mix, soil-geopolymer mix, soil-cement mix,
curing of specimen, testing of the strength of the soil
stabilized with geopolymer and analysis of results.
Before the specimens were prepared, thegeopolymer paste was prepared first prior to mixing
with the dredged soil. The formulation of thegeopolymer mix was already determined. Sodium
Hydroxide and Sodium Silicate were mixed in themixer, then fly-ash were placed with the mixture after
the activators were thoroughly mixed. Water was thenadded and mixed for 10 minutes, to which produced
the geopolymer paste. The mix of dry and wet
ingredients varies on the percentage of geopolymer tosoil.

Table 3. Geotechnical Properties of Dredged Soil
Description
Value
Specific Gravity, Gs
2.66
Liquid Limit, LL
None
Plasticity Index, PI
NP
Optimum Moisture Content (OMC, %)17.59
Max Dry Unit Weight (KN/m3)
17.23
Unsoaked CBR (%)
1.19
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SEE - Nagoya, Japan, Nov.12-14, 2018

Strength Tests
It can be observed that there was a significant
increase in the CBR strength when the geopolymer
was introduced to the dredged soil. It was shown thatfor a 10% geopolymer concentration, a minimum
value of 8.57 was generated and a general rating offair for subbase was obtained. A general rating of
good for base and subbase course resulted for the 20%
replacement while a general rating of excellent forbase course was obtained for the replacement of 30%
geopolymer on the dredged soil.

Figure 1. SEM photomicrographs of 10%(right),
20%(middle) and 30%(left) geopolymer mix at 2000x
There were no more spherical objects and moreof the white particles had appeared even forming
crystalline like structures. This indicates that thegeopolymer had fully formed. As the percent of thegeopolymer was increased the presence of thegeopolymer had become more evident. This would
explain why the 30 % geopolymer mix had the largest
increase in strength. Since the formation of thegeopolymer was more extensive compared to theother mixes.

The increase in the CBR Index follows apolynomial trend. The polynomial correlation waschosen to demonstrate the relationship between thepercentages and the CBR Index since it resulted togreatest regression value.
It shows that a pure dredged soil is not capable ofperforming unconfined compressive strength test
alone, but blending geopolymer with the soil allowed
to produce a confinement as little as 10%, following
a series of 20% and 30%. When soil was mixed witha geopolymer concentration of 10%, the value of thegained strength of 100.94 kPa belonged to typicalstrength of stiff soil (100-200 KPa). As thegeopolymer concentration increased to 20%, thegained strength value of 157 kPa still belonged to thetypical strength of stiff soil (100-200 KPa). A
significant increase can be observed when the soil
was mixed with a geopolymer concentration of 30%
since the grained strength of about 912.88 KPa
belonged to the typical strength of hard soil (>400
KPa).

CONCLUSIONSThe load bearing capacity of the dredged soil
stabilized with geopolymer through dry mixing
method showed that there is an increase in thestrength behavior of the sample. The dry mixing
method was able to improve the geotechnicalproperties of the dredged soil, but at the same time itis practical to use on site. The strength of thegeopolymer improved with time because of its
cementitious reaction. However, excess alkali
activator resulted as there in an increase ofgeopolymer to the sample, still, results showed an
exponential increase. The replacement of 30%
geopolymer on the dredged soil resulted to be bestused for Base course with a general rating of
excellent, according to the DPWH Standard. The 20%
replacement of geopolymer to the dredged soil
resulted to a general rating of fair for Base andSubbase course and the 10% replacement ofgeopolymer to the dredged soil was only rated goodas a subbase course.

The statistical analysis of the UnconfinedCompression Strength test results indicated that an
exponential relationship can be developed between
the varying geopolymer concentration and its average
UCS values. It can be seen that as the precentage of
geopolymer increases, the UCS values also tend toincrease and vice versa. This relationship was chosen
as the best measure since the regression value (R2)
resulted close to 1.

The dredged soil ran through series ofgeotechnical tests, and it was classified as a poorly
graded sand. The dredged soil moisture-density
relationship resulted to values of (OMC) and max dry
density (MDD) within the range of Poorly Graded
Sand which was (12% - 21%) and (15.71 KN/m^318.85 KN/m^3). Additionally, the unconfinedcompressive strength test on the dredged soil
produced an invalid strength, due to its dry andcrumbly characteristics that was not suitable for thestrength test.

Morphological Analysis
Since most of soils properties such as unit weightand strength are attributed to its microstructure.
Scanning Electron Microscope (SEM) was conductedon soil-geopolymer mix to clearly visualize theparticle angularity, assemblage and surface texture.
Figures show the SEM microphotographs of the 10%
20% and 30% geopolymer mix, shown on Figure 1. It
was found that the spherical particles, which
represents fly ash gradually decrease as more
geopolymer percentage was added on the soil.

The CBR value of 1.19 resulted for the dredged
soil alone. However, with the variation of mixes of
10%, 20% and 30%, it was found that CBR index
values increased with the further increase of281

SEE - Nagoya, Japan, Nov.12-14, 2018

geopolymer added to the dredged soil. The maximum
CBR value was obtained at 30% geopolymer
replacement on the soil, at a CBR value of 51.33%.
The minimum CBR value was obtained at 10%, witha CBR value of 8.57. The improvement of thedredged soil when replaced with geopolymer it
increased by 3.21 – 19.22 times the base CBR valueof the dredged soil alone.

skin infection.
Lastly, aside from strength, other factors such as
draining should be considered when dealing with roadembankments. That is why the researchers would also
recommend conducting permeability test (ASTM
D2434) to determine the hydraulic conductivity ofboth the untreated and treated soil. This would
determine its suitability to be used in roadembankments.

More so through the unconfined compressive
strength of the stabilized dredged soil had anincreasing trend as the mixed ration of geopolymer
increased. The 10% replaced geopolymer gained astrength value that is classified as strength of medium
soil at 100.94kPa. The 20% and 30% replacedgeopolymer gained a strength value that is classified
as strength of stiff at 157.0kPa and strength of hardsoil at 912.88kPa, respectively. It is evident that theunstabilized dredged soil, on the other hand, showeda significant improvement, due to the fact that sample
was too lose to stand by itself to begin with; it had nocoherent value.

REFERENCES[1] Zaliha, S., Mustafa AL Bakri, A.M., Kamarudin,
H., & Fauziah, A. (2015). Characterization ofSoils as Potential Raw Materials for Soil
Stabilization
Application
Using
Geopolymerization Method. Trans Tech
Publications, 8(03), pp. 135-143.
[2] Huang, Y., Zhu, W., Zhang, C., Wang, S. Zhang,
N. (2010). Experimental Study on Dredged
Material Improvement for Highway Subgradesoil. Pavement
Materials and Pavement
Analysis. 335-340.
[3] Roy, D.M. (1999). Alkali-activated cements
opportunities and challenges. Cement &Concrete Research, vol. 29, no.2 pp.249-254.
[4] Dungca, J.R., Jao, J.A.L. (2017). Strength andpermeability characteristics of road basematerials blended with fly ash and bottom ash.
International Journal of GEOMATE, 12 (31), pp.
9-15.
[5] Dungca, J., Galupino, J., Sy, C., Chiu, A.S.F.
(2018). Linear optimization of soil mixes in thedesign of vertical cut-off walls. International
Journal of GEOMATE, 14 (44), pp. 159-165.
[6] Dungca, J.R., Galupino, J.G., Alday, J.C.,
Barretto, M.A.F., Bauzon, M.K.G., Tolentino,
A.N.
(2018).
Hydraulicconductivity
characteristics of road base materials blended
with fly ash and bottom ash. International Journalof GEOMATE, 14 (44), pp. 121-127.
[7] Dungca, J.R., Galupino, J.G. (2017). Artificial
neural network permeability modeling of soil
blended with fly ash. International Journal of
GEOMATE, 12 (31), pp. 76-83.
[8] Dungca, J.R., Galupino, J.G. (2016). Modellingof permeability characteristics of soil-fly ashbentonite cut-off wall using response surface
method. International Journal of GEOMATE, 10(4), pp. 2018-2024.
[9] Galupino, J.G., Dungca, J.R. (2015).
Permeability characteristics of soil-fly ash mix.
ARPN Journal of Engineering and Applied
Sciences, 10 (15), pp. 6440-6447.
[10] Dungca, J.R., Codilla, E.E.T., II. (2018). Flyash-based geopolymer as stabilizer for silty sandembankment materials. International Journal ofPrevious studies have not performed theCalifornia Bearing Ratio test for soils that is to bestabilized with geopolymer; although, statisticalanalyses are provided. Comparing the results of the
CBR test with the results of the UCS test, it wasobserved that the behaviour of the increase in CBRvalue of the three geopolymer concentrations issimilar with the behaviour of the increase in strength
for the unconfined compression strength test results.
RECOMMENDATIONS
Due to time constraint and limited resources,
both the fly ash and dredged soil come from only one
coal-fired power plant source was used. However, it
is recommended to use samples from other power
plants and dredged soil across the country forverification of the results in order to avoid geographic
limitation on its widespread use. Moreover, only the
CBR (ASTM D1822) [14] and unconfinedcompression test (ASTM D2166) [15] wereconducted on the treated soil. Furthermore, other tests
such as particle size analysis (ASTM D422) [16],specific gravity (ASTM D854) [17], Atterberg’s limit(ASTM D4318) [18], standard proctor test (ASTM
D698) [19] to be conducted to on the treated soil todetermine its effect on the geotechnical otherproperties.
Moreover, from that additional test for different
curing period such as 7 days, 14 days and 28 days forboth the CBR and UCS test this is to observe thebehavior of the increase in strength of the soil andgeopolymer mix. It is also highly recommended towear protective gloves in mixing geopolymer to avoid

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GEOMATE, 14 (46), pp. 143-149.
[11] Davidovits, J. (1991). Geopolymers: Inorganic
Polymeric New Materials. Journal of Thermal
Analysis, 1633-1656.
[12] Davidovits, J., PROPERTIES, O. G. C. (1994).
Alkaline cements and concretes. Kiev State
Technical University, Ukraine, 131.
[13] Duxson, P., Fernandez - Jimenez, A., Proveis,
J.L.,
Lukey,
G.C.,
Palomo,A.
(2007)Geopolymer technology: the current stateof art. Journals of Material Science, 42(9), 29172933.
[14] American Society for Testing and Materials.
(2017). Standard Test Methods for California
Bearing Ratio. ASTM D1822.
[15] American Society for Testing and Materials.
(2017). Unconfined OCMpression Test. ASTM

D2166.
[16] American Society for Testing and Materials.
(2017). Standard Test Method for Particle-SizeAnalysis of Soils. ASTM D422.
[17] American Society for Testing and Materials.
(2017). Standard Test Methods for Specific
Gravity of Soil Solids by Water Pycnometer.
ASTM D854.
[18] American
Societyfor
TestingandMaterials.(n.d.). Standard Test Methods for
Liquid Limit, Plastic Limit, and Plasticity Index
of Soils. ASTM D4318.
[19] American Society for Testing and Materials.
(2017). Standard Proctor Test. ASTM 698.

283

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

RADIAL FLOW PERMEAMETER: A PROPOSED APPARATUS TO
MEASURE HORIZONTAL HYDRAULIC GRADIENT OF FLY-ASH
BASED GEOPOLYMER-SOIL MIX
Jonathan R. Dungca1, Winchell Dunley T. Lao2, Matthew Lim2, Wilson D. Lu2 and Juan Carlos P.
Redelicia2
Faculty, De La Salle University, Philippines; 2Graduate, De La Salle University, Philippines

1

ABSTRACT
Fly-ash based geopolymer has been proven by many scholars as a viable material to replace cement. Dueto its high compressive strength and abundance in industrial areas, it was advocated to partially replace theconventional material in constructing infrastructure, especially in road embankment. Merely consider the load
capacity or strength of the materials in designing a road embankment may overlook the durability of theinfrastructure. One vital parameter that leads to deterioration and failure of the road is the permeability of thematerials. Flow of water in the road structure comes in different direction but commonly runs in horizontal way
or longitudinal along the road. Neither ASTM nor AASHTO have established a standard procedure in
determination of the horizontal hydraulic gradient of the soil. Hence, a proposed radial flow permeameter was
adopted to determine the permeability of the fly-ash based geopolymer-soil mix. The mixes included dredged soil
with 10% (G10), 20% (G20), and 30% (G30) replaced by geopolymer in mass. The interpretation of the test isquantified using theoretical model and verified using graphical and statistical analysis. The computation was thenfurther verified through anisotropy factor ratio of kh/kv with the data that provided in a literature with similar
geopolymer-soil blend mix. The outcome of the model displayed the degree of the permeability of G10, G20, andG30 was ×10-4, ×10-6, and ×10- 7 in cm/s, respectively. Lastly, the proposed permeameter was found out to bepermissive in determining the horizontal permeability of specimen with low permeability having degree of 10-4 orlower.
Keywords: Horizontal Coefficient of the Permeability, Radial Flow Permeameter, geopolymer, flyash

manufacturers. In some studies, the set up for thehorizontal permeability test are custom made, which
is difficult to do. Another problem is that in this study,
geopolymer will be used as soil stabilizers which will
result to a low permeability soil. Most of the set up
for the horizontal permeability test are for highpermeability soils so it would be difficult for the
researchers to use the set ups proposed given thelimited time.
The objective of this study is to be able to identify
the horizontal permeability of the stabilized soil withfly ash based geopolymer. It also aims to propose a
new set up for getting the horizontal permeability thatwill give credible results.

INTRODUCTION
Engineers often overlook the drainage capacity ofroad embankments, which can lead floods in someareas in the Philippines. The Philippines often
experiences floods because it is in the typhoon belt.
The soil’s drainage property is important becausewith low performance of drainage can cause floods
when an insufficient surface drainage is provided. For
engineers, considering a good drainage is one of thefundamental design considerations for a road tominimize road maintenance costs and maximize theservice life-time of the road during operation [1].
In analyzing the permeability of roadembankments, both direction, vertical and horizontal,
should be considered because the water will flow not
only downward but also horizontally. To have a gooddrainage, horizontal permeability should beconsidered because the water entering the roadembankment should have an exit through the sides.
Most of the tests for the permeability are for verticalpermeability since it is easier to conduct compared tothe horizontal permeability because in getting thehorizontal permeability the flow of water should be
horizontal only. Most of the set up that are being usedin getting the horizontal permeability are rectangular[2-6], which is not common to some of the

METHODOLOGY
Neither ASTM nor AASHTO have established astandard apparatus and standard way in measuring thehorizontal permeability. Hence, a proposed new
permeameter set-up based from a well-concept(confined aquifer) incorporating with Darcy’s Law,
see Eq. 1, was used to measure the horizontal
permeameter.
Q= kiA

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SEE - Nagoya, Japan, Nov.12-14, 2018

The sample will be a hollow cylinder which is shownin Figure 1:

rw = interior radius of the wellbore (cm)h = height of the medium (cm)Pe = pressure head at the boundary radius (cm)Pw = pressure head at the wellbore radius (cm);use atmospheric pressure, Pw = 0
In figure 2, the graphical model of the newhorizontal permeameter was designed with thespecimen having a height of 65mm and a diameter of
60 mm in total including the PVC pipe. The new setup will also be using the same acrylic glass used invertical permeability test with a wooden base at thebottom that will keep the sample in place when being
poured and tamped. A space between the specimen
and acrylic glass was provided to allow the water toflow into the side and permeate horizontally. The
topmost part of the specimen was covered withsealant ensure that the water will enter the space at theside and will pass horizontally through the sample.
The permeameter was constructed with PVC pipe on
the center having a diameter of 20mm. The PVC pipe
was subjected to 4 holes within the height of thespecimen having a diameter of 8mm. The holes weremade at every quarter of the PVC pipe. On top of the
PVC pipe, the hole was wrap with sealant and left todry and solidify to prevent the water going into theholes. It was then glued to the base having a 10mm
thickness and 65mm diameter. The actual model ofthe proposed and actual set-up is seen figure ispresented in Fig. 3. The design was made with thehelp of Dr. Alfaro [8].

Fig. 1. Model for radial flow of fluids to the wellbore [7]As shown in Figure 1, an external boundary pressure,Pe, is located at the outer radius and an internalpressure, Pw, is located at the inner radius. The twopressures will give the general equation of Darcy’s
Law two boundary conditions. Given that there is aconstant change in pressure, the change in pressure
head along the horizontal direction can be expressedas,
i =dP/dr(2)
The area that will be considered in theformula is the area of the external radius which isexpressed as,
A = 𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐(3)

Substituting the area and hydraulic gradient
into Darcy’s Law will give,𝒅𝒅𝒅𝒅
𝐐𝐐 = 𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐
(4)
𝒅𝒅𝒅𝒅

Integrating the equation with the boundary
condition,
𝒓𝒓𝒓𝒓 𝒅𝒅𝒅𝒅
𝑷𝑷𝑷𝑷
𝐐𝐐 ∫𝒓𝒓𝒓𝒓= 𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐 ∫𝑷𝑷𝑷𝑷 𝒅𝒅𝒅𝒅
(5)
Which gives

𝒓𝒓

𝐐𝐐𝐐𝐐𝐐𝐐(𝐫𝐫𝐫𝐫/𝐫𝐫𝐫𝐫) = 𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐(𝐏𝐏𝐏𝐏 − 𝐏𝐏𝐏𝐏) (6)Rearranging the equation, the coefficient of
permeability can be solved by using the equation,
𝑸𝑸𝑸𝑸𝑸𝑸(

𝒓𝒓𝒓𝒓

)

𝒓𝒓𝒓𝒓
𝐤𝐤 = 𝟐𝟐𝟐𝟐𝟐𝟐(𝐏𝐏𝐏𝐏−𝐏𝐏𝐏𝐏)(7)
Fig. 2. Graphical Model of the New Horizontal
Permeameter

Where:
k = coefficient of permeability(cm/s)
Q = flowrate (cm3/s)
re = interior radius of the cell or boundary radius(cm)

For the preparation of the stabilized soil with fly
ash based geopolymer, in order to provide a standard
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SEE - Nagoya, Japan, Nov.12-14, 2018

uniformity between samples, the dredged soil and fly
ash was obtained only from a thermal power plant in
Mindanao. The dredged soils were sieved to have up
to the required maximum sizes, particularly sieve
number 4 or a nominal opening of 4.76mm followedby the removal of its moisture content thru ovendrying. The fly ash obtained was classified as Class F.
The index properties of the dredged soil was
determined by conforming to the ASTM procedures.
a. Specific Gravity of Soils (ASTM D854) [9]b. Particle Size Analysis (ASTM D422) [10]c. Standard Proctor Test (ASTM D698) [11]by making sure that side wall leakage will not affectthe results. One limitation of the set-up is that it can
only be used to low permeability samples such as
geopolymers. The set-up takes up less time comparedto the others because the passage way of the water ismuch shorter compared to the other proposed set-ups.
RESULTS AND DISCUSSIONS
Scanning Electron Microscopy (SEM) Results
In graphical analysis, scanning electron
microscopy (SEM) was used to evaluate themorphology of the specimen. It provided a highresolution image of the spaces formed between theparticles inside the specimen. Two levels ofmagnification, x500 (see Figure 3) and x5000 (seeFigure 3), were used in the analysis to fully
understand the bonds between the particles of thesample.
Figure 3 showed the microstructure of the three
blends under magnification of x500. As shown in the
Figure 3, the voids present in Figure 3 (a) were more
visible compared to the voids seen on Figures 3(b),and 3(c). This meant that G10 could be more
permeable as compared to the G20 and G30 because
the presence of spaces between the particles were thepath for the water to easily pass through. Furthermore,
it was observed that the void spaces presented in G20
and G30 were exiguous, making the microstructure of
the both blends indistinguishable under x500
magnification.

Conventional materials and blended samples
were individually subjected to microscopic testing inorder to evaluate the void spaces present using the
Scanning Electron Microscopy (SEM) [12-14].
The geopolymer based fly ash mix used wasbased on the mix design formulated by Ang, et al.
(2016) [15] which were used for the preparation ofsamples for the testing of strength and permeability
tests of each blends. The geopolymer mix design ispresented in Table 1:
Table 1. Geopolymer Mix [15]Geopolymer
Concentration(%)

Alkaline
Activator/
Fly AshSodiumSilicate/
SodiumHydroxide

NaOH
Concentration

10, 20, 30

0.4

2

14 M

The blended samples varies from 10%, 20% and
30% of partial replacement of geopolymer to the total
weight of dredged soil. The blended samples are
obtained by providing first the dredged soil to attainits maximum dry unit weight based from optimal
moisture content (OMC) that was determined throughthe Standard Proctor Test.
Constant Head Permeability Test were conducted
to evaluate the drainage characteristics of all theblends considering a relative compaction of 100%.
However, a relative compaction of 100% is somehow
unattainable due to tamping constraints, each samples
were just subjected to a constant of 25 blows per 3
layers using hand tamping.
There are some advantages in using the proposed
new set-up in getting the horizontal permeability.
According to the study of Dungca and Galupino(2015) [6], the horizontal permeability is expected tohave higher value because of the pressure that was
induced in their sample, but they were not able to take
into account the layers. In the new set-up, the layers
caused by the tampering was considered. Another setup that the researchers compared is the set-up madeby Baretto et. al. (2015) [3]. Their set-up was arectangularpermeameter,
unfortunately
theresearchers did not used their set-up due to the factthat their sample has properties similar to concrete
like shrinkage. The researcher designed their set-up

Figure 3. a) 10% b) 20% c) 30 % replacements withmagnification level of x500
To clearly distinguish the difference between G20
and G30 in terms of the void spaces, an increased
magnification level of x5000 was conducted. As canbe seen from the SEM photo (x5000) presented in
Figure 3, voids spaces were still present in bothblends that allowed water to pass through. Undermagnification of 5000, G20 was observed to havemore void spaces as compared to the G30; thus, theG20 replacement was more permeable than the G30.
In addition, there was great difference in the bonding
formations of the particles between G20 and G30.
Under G20, there still some particles of fly ash that
could be seen in the SEM photo. They were thespherical particles easily seen in Figure 2(a). Thoseparticles implied that the fly-ash did not completely
react with the alkaline activator. Unlike in G30, thesand and fly-ash particles in G30 were completely
reacted. The geopolymer in 30% replacement could
coat the sands particles and provided greater bonding

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SEE - Nagoya, Japan, Nov.12-14, 2018with the other sand particles, blocking thepassageway for the water.
From the microstructure of each blends, it could
forecast that as the percentage replacement increase
the permeability of that blend would decrease. Thisobservation would be later on proven throughexperimental result.

permeability tests, anisotropy ratio must be within thegiven range of Das (2008) [17]. The collected usual
ratio of horizontal and vertical permeability of soils
by Das (2008) [17] is with the range of 1.2-3.3, thus,
the data gathered must be within the range.
Vertical permeability of the soil-geopolymer mix
investigated [18] was utilized and tabulated in Table
4. From the value of the permeability, it shown thathorizontal permeability was slightly higher than thevertical permeability.

Horizontal Permeability
As stated, a proposed radial flow permeameter
was used in determining the horizontal permeabilityof the dredged soil stabilized with fly-ash based
geopolymer under 10, 20, and 30 percent replacement
in mass. Shown in Table 2, were the ranges ofpermeability value gathered from the proposedconstant head radial flow permeameter test. G10
produced an average of 2.72E-04 cm/s. G20 had an
average of 5.25E-06 cm/s. G30 produced an averageof 7.86E-07 cm/s. The lower the degree in the value
implied a slower flow of water through the voids ofthe specimen.

Table 4. Ranges of Vertical Permeability [18]Soil
MixtureMinimum
Kv, cm/s

Maximum
Kv, cm/s

AverageKv, cm/s

G10

1.14E-04

2.42E-04

1.60E-04G20

3.90E-06

4.98E-06

4.32E-06

G30

4.62E-07

7.55E-07

5.97E-07

Table 2. Ranges of Horizontal Permeability
Soil
MixtureMinimumKh, cm/s

MaximumKh, cm/s

AverageKh, cm/s

G10

1.66E-04

3.62E-04

2.72E-04

G20

4.89E-06

5.52E-06

5.25E-06

Computing the anisotropy ratio tabulate in Table
5, the ratio for all the blends ranges between 1.2-1.7,
thus, ratios are within Das’ desired range. The
proposed permeability was viable to obtain thehorizontal permeability of the soil.

G30

6.35E-07

9.27E-07

7.86E-07

Table 5. Anisotropy ratio of kh/kv

To determine the effect of the amount ofgeopolymer replaced in the soil, a box and whisker
plot was delineated, as shown in Figure 4. Box andwhisker plot provided the midspread values of eachreplacement. Using an IQR of 1.5, the obtainedcoefficient of permeability was fall in the ranges;
therefore, there is no outlier.
As expected from the SEM photo, it was observed
from Figure 4 that the permeability decreases as thepercentage replacement of geopolymer mixed to thesample increases. Due to the increased
geopolymerization took place in the blends, the void
spaces between the soil particles was coated andbonded with the geopolymer, hence, blocking thepassage of the water. Dungca & Jao (2016) [1] andGalupino (2015) [6] also result with a decrease of
permeability as fly ash increased in fly-ash-soil mix.
Classifying
the
blend
with
drainagecharacteristics defined by Casagrande and Fadum(1940) [16], G10 fall in poor drainage, meanwhile,
G20 and G30 fall under practically impervious. With
the classification, engineers must design with enoughdrainage system in road embankment to prevent water
ingress in the road pavement.

Soil
MixtureAverageKh,
cm/s

AverageKv, cm/s

Average
Kh/Kv

G10

2.72E-04

1.60E-04

1.70

G20

5.25E-06

4.32E-06

1.21

G30

7.86E-07

5.97E-07

1.32

CONCLUSIONSThe study investigated the effect of thegeopolymer on the soil, particularly on the drainage
characteristics. SEM analysis was conducted toprovide a better understanding on the formulation andconstruction of pores spaces on the mix. The SEM
showed a graphical progression of the effect of theamount of geopolymer on the soil. With theincreasing percentage replacement, the pore spaces
are being covered up. Consequently, the water will
have limited passageway to flow through, resulting toa lower permeability.
A proposed radial flow permeameter was used todetermine the horizontal coefficient permeability ofthe mix. The experiment obtained the degree of thepermeability of G10, G20, and G30 , the values were×10-4, ×10-6, and ×10- 7 in cm/s, respectively. As
expected from the SEM, the permeability decreases
along with the increase of geopolymer.

Anisotropy ratio, kh/kv
To further validate the results of the horizontal

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SEE - Nagoya, Japan, Nov.12-14, 2018

With the given set of data, the soil-geopolymer
mixes were classified with their respective drainage
characteristics. With the criteria provided by
Casagrande and Fadum (1940), G10 fall in poor
drainage, meanwhile, G20 and G30 fall underpractically impervious. Based from the evaluation,
the soil mixtures were concluded to be poor indrainage. However, it still can be used as anembankment material, given that the engineers mustdesign properly the drainage system to prevent
deterioration and failure of the road caused by the
ingress of water.
To validate the horizontal permeability,
anisotropy ratio of kh/kv must be fall in within Das’desired range (1.2 to 3.3). The computed ratios of all
mixtures were ranged from 1.2 to 1.7, hence, theobtained horizontal permeability was acceptable. In
addition, it was observed that horizontal permeability
is much higher than the vertical permeability whichmeans the flow of water in the horizontal direction ismuch faster compare to the vertical direction.
Lastly, with all the validation made, the proposed
permeameter is viable in determining the horizontal
permeability. However, the apparatus is only limited
to permeability having a degree of 10-4 or lower.

of GEOMATE, 14 (44), pp. 121-127.
[4] Dungca, J.R., Galupino, J.G. (2017). Artificial
neural network permeability modeling of soil
blended with fly ash. International Journal of
GEOMATE, 12 (31), pp. 76-83.
[5] Dungca, J.R., Galupino, J.G. (2016). Modellingof permeability characteristics of soil-fly ashbentonite cut-off wall using response surface
method. International Journal of GEOMATE, 10(4), pp. 2018-2024.
[6] Galupino, J.G., Dungca, J.R. (2015).
Permeability characteristics of soil-fly ash mix.
ARPN Journal of Engineering and Applied
Sciences, 10 (15), pp. 6440-6447.
[7] Engler, T. W. (2010). Fluid flow in porous media.
Retrievedfrom
http://infohost.nmt.edu/~petro/faculty/Engler52
4[8] De Guzman, E., Stafford, D., Alfaro, M., Dore,G., & Arenson, L. (2016). Large-Scale Direct
Shear Testing of Laboratory-Compacted Frozen
Soil Under Freezing and Thawing Conditions.
[9] American Society for Testing and Materials.
(2017). Standard Test Methods for Specific
Gravity of Soil Solids by Water Pycnometer.
ASTM D854.
[10] American Society for Testing and Materials.
(2017). Standard Test Method for Particle-SizeAnalysis of Soils. ASTM D422.
[11] American Society for Testing and Materials.
(2017). Standard Proctor Test. ASTM 698.
[12] Dungca, J.R., Codilla, E.E.T., II. (2018). Flyash-based geopolymer as stabilizer for silty sandembankment materials. International Journal of
GEOMATE, 14 (46), pp. 143-149.
[13] Tigue, A.A.S., Dungca, J.R., Hinode, H.,
Kurniawan, W., Promentilla, M.A.B. (2018).
Synthesis of a one-part geopolymer system forsoil stabilizer using fly ash and volcanic ash.
MATEC Web of Conferences, 156, art. no.
05017, .
[14] Dungca, J. R., & Dychangco, L. F. T. (2016).
Strength properties of road base materials
blended with waste limestones. International
Journal of GEOMATE, 11(3), 2493-2498.
[15] Ang, Isaac, Joven, & Sollano. (2016). Use of dry
mixing method in fly ash based geopolymer as astabilizer for dredged soil (Unpublishedundergraduate thesis). De La Salle University.
[16] Casagrande, A. and R.E. Fadum (1940). “Notes
on soil testing for engineering purposes,”
Harvard Univ. Grad. School of Engineering Publ.

ACKNOWLEDGEMENTS
They would like to thank their professors Dr.
Mary Ann Q. Adajar, Engr. Joenel G. Galupino, Engr.
Erica S. Uy, and Engr. Maria Emilia S. Miguel for
imparting to them their knowledge and helping themcomplete their study. They would also like to thankDr. Marolo C. Alfaro for sharing and imparting his
idea and knowledge for the formation of the newhorizontal permeameter set-up. They are also very
thankful to Mr. Manny Leuterio and Ms. Ghaye
Alegrio for providing them the dredged soil and fly
ash samples for their experiments. Their experiments
could not have been completed without theaccommodation of their patient laboratory technician,
Mr. Antonio Kalaw.
REFERENCES
Dungca, J.R., Jao, J.A.L. (2017). Strength andpermeability characteristics of road basematerials blended with fly ash and bottom ash.
International Journal of GEOMATE, 12 (31), pp.
9-15.
[2] Dungca, J., Galupino, J., Sy, C., Chiu, A.S.F.
(2018). Linear optimization of soil mixes in thedesign of vertical cut-off walls. International
Journal of GEOMATE, 14 (44), pp. 159-165.
[3] Dungca, J.R., Galupino, J.G., Alday, J.C.,
Barretto, M.A.F., Bauzon, M.K.G., Tolentino,
A.N.
(2018).
Hydraulicconductivity
characteristics of road base materials blended
with fly ash and bottom ash. International Journal
[1]

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SEE - Nagoya, Japan, Nov.12-14, 2018

characteristics of dredged soil stabilized with flyash based geopolymer for road embankment . De
La Salle University.

268, 74 pp.
[17] Das B. M. (2008). Advanced soil mechanics.
New York: Taylor & Francis.
[18] Dungca J., Lao W., Lim M., Lu W., andRedelicia
J.
C.
(2017).
Permeability289

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

VERTICAL PERMEABILITY OF DREDGED SOIL STABILIZED WITH
FLY-ASH BASED GEOPOLYMER FOR ROAD EMBANKMENT
Jonathan R. Dungca1, Winchell Dunley T. Lao2, Matthew Lim2, Wilson D. Lu2 and Juan Carlos P.
Redelicia2
1
Faculty, De La Salle University, Philippines; 2Graduate, De La Salle University, Philippines
ABSTRACTThis study presents the vertical permeability and strength relationship of dredged soil stabilized with flyash based geopolymer which is to be used for constructing road embankments. The fly-ash used for this study
was a low-calcium (Class F) fly-ash. The varying effects on both properties due to the different partial
replacements of geopolymer were studied. 10%, 20%, and 30% of the soil sample’s mass were used as partial
replacement. The samples were prepared using the dry-mix method and subjected to 28 days of air-dried curing.
Tests like the unconfined compressive strength test and the falling head permeability test were conducted. The
morphological features of the samples were investigated using the scanning electron microscopy (SEM). The test
results showed that as the percentage replacement of geopolymer increases, the samples become less permeable.
SEM analyses confirmed the results, showing that the geopolymer tend to cover up the pore spaces of the soil,
causing the water to have less passageways.
Keywords: Fly-ash, Geopolymer, Dredged soil, Permeability, Unconfined Compressive Strength

INTRODUCTION
One of the most common examples of CCP’s is flyash. It is a by-product of the coal-fired power plantand is posing a great threat to the environment.
When discharged by the power plants, it isimmediately considered as wastes. Only around halfof it are used for recycling. The rest are thrown out
into lands and bodies of water [2]. Some studies
have been made to utilize these ashes in different
fields. Some are used as embankment fill, cement
alternative and as soil stabilizer for roadembankments.
Since dredged soil possess weak strength, there isa need to stabilize it, for it to be usable forconstruction purposes. The soil for this study will bestabilized using geopolymer mixed with class F flyash. Geopolymer is synthesized through a natural
reactive property of aluminosilicate material whenmixed with an alkali-activator. It is an inorganic
polymer made up of covalently bonded molecules. It
undergoes polymerization which involves achemical reaction on Si-Al minerals under alkalinecondition forming series of sialate monomers likecement properties [9].
The aim of this study is to analyze therelationship between the strength and permeabilityof the blends and give recommendations based on
the results generated.

Road infrastructure is very essential todeveloping countries like the Philippines. Thesefacilitate the trade, communication, and travelling
purposes. The advancement of the economy isheavily reliant on these. Having bad and poorly
maintained roads causes inconvenience like roaddamages and flooding, which cause severe trafficand leads to slow progression of the economy.
Permeability is a very important parameter toconsider when designing road embankments. There
should be a compromise between the strength andthe permeability. Numerous studies have shown thatan increase in the strength of the soil leads to adecrease in its permeability. In a country like thePhilippines wherein heavy rains are very frequent, it
becomes a must for roads to exhibit good drainage.
When there is low permeability, water tends toaccumulate very fast and exert pore water pressure,causing ponding and the deterioration of theembankment.
The construction of roads embankments requires
different materials like aggregates, lime, and cement.
Unfortunately, the production of cement may impose
some harm to the environment, as it generates
greenhouse gases due to the emission of carbon
dioxide. The can constitute to the rising state ofglobal warming [1]. Numerous studies have shownthat coal combustion by-products, or morecommonly known as CCPs, have been found to be agood choice because it is very abundant in the
country and has a problem in disposal [2]-[8].
Furthermore, the use of these CCP’s can bringeconomic and environmental benefits.

METHODOLOGYTo provide a standard uniformity between
samples, the dredged soil and fly ash was obtained
only from a thermal power plant in Mindanao. The
dredged soils were sieved to have up to the required
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SEE - Nagoya, Japan, Nov.12-14, 2018

maximum sizes, particularly sieve number 4 or anominal opening of 4.76mm followed by theremoval of its moisture content thru oven-drying.
The fly ash obtained was classified as Class F.
The index properties of the dredged soil were
determined by conforming to the ASTM procedures.

RESULTS AND DISCUSSIONS
Scanning Electron Microscopy (SEM) Results
The scanning electron microscopy (SEM) is
commonly used for getting a high-resolution imageof the spaces between particles in the surface. Twolevels of magnification, x500 and x5000, were usedin the analysis to fully understand the bonds between
the particles of the sample.

a. Specific Gravity of Soils (ASTM D854)[10]b. Particle Size Analysis (ASTM D422)[11]
c. Standard Proctor Test (ASTM D698)[12]
Conventional materials and blended samples
were individually subjected to microscopic testing toevaluate the void spaces present using the ScanningElectron Microscopy (SEM).
The geopolymer based fly ash mix used wasbased on the mix design formulated by Ang, et al.
(2016) [9] which were used for the preparation ofsamples for the testing of strength and permeability
tests of each blends. The geopolymer mix design ispresented in Table 1.

Figure 2. a) 10% b) 20% c) 30 % replacements withmagnification level of x500
Comparing the voids seen on the SEM of eachblend as shown in figure 2, figures 2(b), and 2(c) are
observed to have almost no voids while figure 2(a)clearly shows the presence of spaces between theparticles where the water can easily pass through.
This means that the sample with 10% replacement ofgeopolymer could be more permeable, as comparedto the 20% and 30% replacements. Furthermore, theresearchers have observed that there is only a small
difference between the void spaces between 20%
and 30% replacement.

Table 1. Geopolymer Mix
Geopolymer
Concentration(%)

Alkaline
Activator/
Fly AshSodiumSilicate/
SodiumHydroxide

NaOH
Concentration

10, 20, 30

0.4

2

14 M

The blended samples vary from 10%, 20% and
30% of partial replacement of geopolymer to thetotal weight of dredged soil. The blended samples
are obtained by providing first the dredged soil toattain its maximum dry unit weight based from
optimal moisture content (OMC) that wasdetermined through the Standard Proctor Test.

AirWater
CylinderPump

Figure 3. a) 20% b) 30% replacements withmagnification level of x5000

Manometer

Permeameter

An increased magnification level by x5000 was
conducted to clearly distinguish the difference
between the 20% and 30% replacement in terms ofthe void spaces present. As can be seen from theSEM photo (x5000) presented in Figure 3, voids
spaces are still present that allows water to passthrough. The 20% replacement is observed to havemore void spaces as compared to the 30%
replacement; thus, the 20% replacement is more
permeable than the 30%, as expected by the group.
Also, the particles in 30% replacements arecompletely covered, as shown in figure 3(b). The
case is different with the 20% replacement, wherein
there can still be found some particles of fly ash that
did not react with the reactors which represented by
the spheres seen in figure 3(a). The geopolymer in
30% replacement was able to coat the sands andprovided greater bonding with the other sandparticles, blocking the passageway for the water.

Outflow
Collector

Figure 1. Experimental Set -up for Vertical
Permeability [3-7]
Falling Head Permeability Test (ASTM D5084)[13] were conducted to evaluate the drainage
characteristics of all the blends considering a relative
compaction of 100%. However, a relative
compaction of 100% is somehow unattainable due totamping constraints, each sample were just subjected
to a constant of 25 blows per 3 layers using handtamping. The acquired set-up for the permeability
test is shown on Figure 1.

291

SEE - Nagoya, Japan, Nov.12-14, 2018

determining the improvement of stabilized soils[14].
Given that the UCT cannot be done for puredredged soil, blending of geopolymer mix ofdifferent percentage was incorporated, specifically
10%, 20% and 30%. By observation, the addition ofgeopolymer mix with an inclusion of curing fortwenty-eight days showed that it was able to bind thesoil particles allowing the soil to stand firmly andform a cylindrical shape without confining pressure.
Based from observation, the geopolymer acts as thebinder for the soil in the form of stabilization. In
addition, the geopolymer mix exhibits cement-like
properties that similarities on its physical properties
are noticeable.
Table 3 presents the progression of thestabilized soil as more of the geopolymer is being
added. It is anticipated that the unconfinedcompressive strength of the mixture increases withthe continual addition of the geopolymer. As
observed, the incremental increase of strength isexponentially related to the percent replacement ofgeopolymer.

Gradation
The variation of particle size of the dredged soil
can be measured based on the parameters,
coefficient of uniformity and curvature, as shown in
Table 2. These coefficients define the grade of soil
which is based on ASTM D2487. As observed, thecoefficient of uniformity (Cu) of the dredged soil
was found to be having values less than 6. This
indicates that the soil contains particles having
uniform size. Moreover, the grain size distribution
curve (GSDC) of the 3 trials was observed to havesteep slopes which are almost vertical. Thus, thisverifies that the variation of particles sizes is withina narrow limit.
The coefficient of curvature (Cc) of the dredged
soil was found to be having an average of 2.97,
which is within the range 1-3. This signifies a wellgraded soil. Thus, the dredged soil could coveralmost all grain sizes. Also, observed from the
GSDC, there were no sudden changes of slope
which would signify the absence of certain grain
sizes. The dredged soil was found to be falling under
the classification of poorly graded soil since the Cu
was less than 6 (Cu>6, well-graded soil for sand) but
the Cc was between the range 1-3 (1-3, well-gradedsoil) though it was already at the limit’s boundary.

Table 3. Unconfined Compressive Strength of Mix
Geopolymer Mix
28 daysCuringTable 2. Uniformity and Curvature of Dredged Soil

10%

20%

30%

Unconfined Compressive Strength
(MPa)
Trial

Coefficient ofUniformity(Cu)

Coefficient ofCurvature
(CC)

1

4.06

3.01

2

4.35

2.96

3

4.26

2.93

Average

4.22

2.97

Trial 1

0.198

0.3217

1.309

Trial 20.22280.2868

1.550

Trial 30.17890.3265

1.432

Average

0.19990.31171.4306

A 10% partial replacement produced an average
unconfined compressive strength of 199.9kPa. Thiswas classified as a stiff soil, based on theclassification set by Liu and Evett, 2009 [15]. The
classification is shown below in Table 4. When thepercentage replacement was increased to 20%, on
the other hand, it resulted to an average unconfinedcompressive strength of 311.7kPa. This wasclassified as a very stiff soil. Lastly, 30% partial
replacement resulted to an average unconfinedcompressive strength of 1430.6kPa. This wasclassified as a hard soil.
The strength behavior brought about by thegeopolymer to the soil is because the geopolymer
possesses cementitious materials. These undergo
polymeric reactions, resulting in the formation ofaluminosilicate three-dimensional networks whose

Unconfined Compressive Strength
A dredged soil is mostly made up of sandy
particles which allows it to exhibit the property ofthe sand and not being able to provide confinement.
Thus, it is incapable of maintaining a firm stand andform a cylindrical shape even though there has been
no load being applied. Also, the dredged soil
obtained has been identified to manifest poor
geotechnical properties. As a result, geopolymer
would be added to enhance the geotechnicalproperties of the dredged soil. Consequently, for thatreason, the researchers are incapable to produce soil
samples made up of only pure dredged soil for theunconfined compression test (UCT). The unconfinedcompression strength test is commonly used for292

SEE - Nagoya, Japan, Nov.12-14, 2018

strength can be even higher to that of conventional
concrete [16].
The stress-strain diagram of each blends,
specifically 10%, 20% and 30%, with 3 different
trials were conducted. The illustrations presented are
the behavior of the soil mixture at different
percentages when subjected to loading. By analyzing
the graphs, the increase in the concentration ofgeopolymer had caused the mixture to become
brittle with the increase in strength. It exhibits thesame property with concrete wherein highcompressive strength concrete produces low strain
and suddenly fails.

are very important factors in the investigation of thepermeability. Much of this is governed by theamount of geopolymer applied to the sample. During
the process of increasing the strength of the soil
through stabilization, the sample undergoes throughgeopolymerization. The pozzolanic reaction causes
the particles to bind together. This then closes thepore spaces to increase the strength. Therefore, it
becomes more difficult for the water to flow throughthe sample.
Table 5. Coefficient of Permeability in the Vertical
Direction for Varying Replacement of GeopolymerSoil Mix (cm/s)

Table 4. Standard Relationship of Consistency andUnconfined Compressive Strength of Soil [15]Classification

UnconfinedCompressive
Strength (KPa)

Very Soft Soil

25

Soft Soil

25-50

Firm Soil

50-100

Stiff Soil

100-200

Very Stiff Soil

200-400

Hard Soil

>400

Trial
No.
1
2
3
4
5
Ave.

Pure

10%

20%

30%

9.85E-03
9.51E-03
1.01E-02
1.16E-02
1.06E-02
1.04E-02

2.42E-04
1.27E-04
1.18E-04
1.99E-04
1.14E-04
1.60E-04

3.90E-06
4.98E-06
3.94E-06
4.45E-06
4.34E-06
4.32E-06

4.77E-07
7.55E-07
4.62E-07
7.16E-07
5.73E-07
5.97E-07

Box and whisker plot provided the midspreadvalues of each replacement. Using an IQR of 1.5, theobtained coefficient of permeability was fall in therange between 25th and 75th percentile; therefore,
there is no outlier.
As discussed, there was a significant behaviour that
relates permeability with strength. It could beobserved that the permeability is inversely related tostrength. A related study conducted by Olivia andNikraz (2011) [19], also noticed and stated that there
is an inverse relationship between the strength andpermeability of the geopolymer mix. As the strength
increases, the permeability starts to decrease. They
compared their trend to the results of Cheena, et. al(2009) [20] where both researchers got similar trend
for the permeability and unconfined strength. The
researchers observed that their samples had the same
trend as Olivia and Nikraz’. The same trend can also
be found in the study of Wongpa et. al (2010) [21],stating that the permeability is indeed dependent on
the strength of the geopolymer mix. The reason
behind the trend is that as the percentage
replacement of geopolymer increases, the void
spaces decrease as seen from the SEM images which
resulted to the increase of strength and consequently,
the decrease of its permeability.
The difference between each mix’s void spaces
affected the permeability since more void spaces
means that water can easily flow and pass throughthe samples. Another observation that was madefrom the SEM analysis was the small difference ofvoid spaces between 20% and 30% replacement. It
can be seen from the graph that there is also a small
difference between the permeability of 20% and
30% compared to the 10%. The void spaces from the
10% mix can be clearly seen by the naked eyes

Vertical Permeability
Permeability is an important factor to consider
when increasing the strength of the soil. The effectof the polymerization is presented in Table 5,
wherein it shows the change in permeability between
dredged soils with and without geopolymer present.
The dredged soil alone was found to have an average
hydraulic conductivity of 1.04E-02 cm/s. A 10%
geopolymer replacement produced an average of
1.60E-04 cm/s. A 20% geopolymer replacement had
an average of 4.32E-06 cm/s. And the
30%replacement produced an average of 5.97E07cm/s.
The results were classified in accordance to thecriteria set by Casagrande and Fadum (1940) [17].
A 10% geopolymer replacement resulted inpoor permeability. The 20% and 30% replacements
were considered as practically impervious.
The trend shows that the additional replacementof the geopolymer further decreases thepermeability. According to Ma, Hu, and Ye (2012)[18], the pore size distribution and connectivity,
including the shape and volume of the pore spaces
293

SEE - Nagoya, Japan, Nov.12-14, 2018

while the void spaces of 20% and 30% mix can only
be seen through SEM.
By Regression Analysis, an empirical formula wasformulated to obtain the coefficient of permeability
with respect to percent replacement. The coefficientof permeability can be obtained from the formula:k = 𝐞𝐞(−𝟓𝟓.𝟎𝟎𝟎𝟎 −𝟎𝟎.𝟑𝟑𝟑𝟑𝟑𝟑𝟑𝟑)

Since the stabilized soil possess poor permeability,
Lovering and Cedergren (1962) [23] suggested that
there should be sufficient drainage outlets, for theembankments to be effective in draining. Theystrongly recommended that these drainage outlets
should also be maintained regularly so that they do
not become clogged and create a “bathtub” effect inthe drainage layer. Past studies have come toconclusions that the drainage layer alone cannot
guarantee an improved permeability performance.
The entire drainage system must have enoughcapacity and must also be working efficiently. Thus,
it is important to have the drainage layer, outlet
drains, and outlet pipes to be efficient for the
expected water infiltration during rainfall. Regular
maintenance must also be conducted. This is toensure that water infiltrated can be drained out as
quickly as possible before they get into theembankment [24].

(1)Where:
k = coefficient of permeability (cm/s)
G = percent replacement of fly-ash based
geopolymer
The regression was able to obtain a coefficientof correlation equal to 0.9744 which is almost equal
to 1, thus, makes the empirical formula acceptable.
The model or formula formulated allows engineer tohave the desired permeability characteristics for its
embankment based on the geopolymer replacement.
Also, it could allow engineers to approximate
permeability characteristics in order to design theappropriate drainage needed for the embankment
with respect to the replacement desired for the
project. However, the model provided is only limited
in providing the estimated hydraulic conductivity
value up to 30% replacement, thus, further study
must be conducted if greater geopolymer mix isneeded. Also, this study is only applicable for asingle compaction which was based from the Proctor
Test achieving a theoretical 100% relative
compaction.

CONCLUSIONS
A pure dredged soil, in its nature is capable ofdraining water at a good rate. However, it is very
weak and cannot be purely used for roadembankment purposes. Soil types such as thisneeded to be stabilized. A fly-ash based geopolymer
was found to be a very good stabilizer in enhancing
the strength of the soil mixture. A 10% partial
replacement by mass of the geopolymer resulted inan average unconfined compressive strength of
0.1999 MPa, and has been classified as a stiff soil. A
20% replacement produced an average unconfinedcompressive strength of 0.3117 MPa, and wasclassified as a very stiff soil. The researchers also
noticed that the 30% replacement has vastly
improved the strength of the soil. Its unconfinedcompressive strength reached an average of 1.432
MPa. This was classified under the hard soil
category. It is very evident that the strength
increases along with the additional amount ofgeopolymer being added. The soil mixtures wereobserved to have almost the same properties withthose of concrete.
The vertical permeability of the samples was also
investigated. As expected, there was an inverse
relationship between the strength and thepermeability of the samples. The permeability
decreases as the strength increases. Pure dredge soil
has an average hydraulic conductivity of 1.04E-02
cm/s. A 10% partial replacement results in an
average hydraulic conductivity of 1.60E-04 cm/s. A
20% partial replacement, on the other hand, results
in an average hydraulic conductivity of 4.32E-06
cm/s. Last, a 30% partial replacement results in an
average hydraulic conductivity of 5.97E-07 cm/s.
The 10% replacement was classified to have poor
permeability, and both the 20% and 30% wereconsidered practically impervious.

Recommendation on the Results
When using stabilized materials for constructing
road pavements, there will always be a compromise
between the strength and the permeability, The
American Concrete Pavement Association (1994)[22]. Even though the material possesses goodpermeability, it may be still possible to become
insufficient in supporting construction operations
and carrying loads, since the strength is not thathigh. When stabilized materials are used, a sacrifice
in its permeability comes along with the increase instrength.
This study was able to confirm that fly-ash based
geopolymers are indeed capable of enhancing thestrength of soil at a significant amount.
Unfortunately, it has also resulted in a drastic
decrease in its permeability, as discussed earlier.
This raises a big concern especially that this material
is to be used as road embankments in countries
which experience frequent heavy rain like thePhilippines. Another challenge arises on how toefficiently utilize such a material with good strength
but poor permeability for the construction of roadembankments.

294

SEE - Nagoya, Japan, Nov.12-14, 2018

The use of this material can be very helpful inconstructingroadembankments.
However,engineers must take precautions in using this since
the permeability is not that good. They must find away to be able to compromise both the strength andthe permeability in order to maximize the use of thismaterial. It is important to always remember that thedrainage of roads must not be relied solely on theroad embankments. There should always be proper
surface drainage systems installed. They must also
be working efficiently and frequently maintained.

2017.
[11] American Society for Testing and Materials.
Standard Test Method for Particle-Size Analysis
of Soils. ASTM D422, 2017.
[12] American Society for Testing and Materials.
Standard Proctor Test. ASTM 698, 2017.
[13] American Society for Testing and Materials.
Falling Head Permeability Test. ASTM D5084,
2017.
[14] Wong, L., Hashim, R., & Ali, F. Improved
strength and reduced permeability of stabilized
peat: Focus on application of kaolin as apozzolanic additive. Construction and Building
Materials 40, 2012, pp. 783-792.
[15] Liu, C., & Evett, J.. SOIL PROPERTIES:
Testing, Measurement, and Evaluation (6th ed.),2009.
[16] Mehta, A. and Siddique, R. Strength,
permeability,
andmicro-structuralcharacteristics of low-calcium fly ash based
geopolymers. Construction and Building
Materials 141 (2017), 2017, pp. 325-334.
[17] Casagrande, A. and R.E. Fadum. Notes on soil
testing for engineering purposes, Harvard Univ.
Grad. School of Engineering Publ. 268, 1940,
74 pp.
[18] Ma. Y., Hu. J., & Ye, G. (2012). The pore
structure and permeability of alkali-activated flyash. Fuel 104 (2013), 2012, pp. 771-780.
[19] Olivia, M., & Nikraz, H. R. (2011). Strength
and water penetrability of fly ash geopolymer
concrete . ARPN Journal of Engineering andApplied Sciences, Vol. 6 No. 7, 2011, pp. 70-78.
[20] Cheena D.S., Llyod N.A., and Rangan B.V.
Durability of geopolymer concrete box culvertsa green alternative. In: 34th conference on Our
World in Concrete and Structures. CiPremier,
Singapore, 2009.
[21] Wongpa, J., Kiattikomol K., Jaturapitakkul, C.,
Chindaprasirt C. Compressive strength,
modulus of elasticity, and water permeability of
inorganic polymer concrete. Materials andDesign, 31, 2010, pp. 4748–4754.
[22] American Concrete Pavement Association.
Cement-treated permeable base for heavy-traffic
concrete pavements. Concrete Information,
1994.
[23] Lovering, W. & Cedergren, H. Structural
section drainage. Proceedings, International
Conference on the Structural Design of Asphalt
Pavements, University of Michigan, Ann
Harbor, Mich., August 20-24, 1962, pp. 773784.
[24] Harvey, J., Tsai, B., Long, F., & Hung, D.
CAL/APT Program - Asphalt treated permeablebase. Laboratory Testing, Performance,
Predictions, and Evaluation of the Experience ofCaltrans and other Agencies, 1999.

REFERENCES[1] Roy,
D.M.,
Alkali-activatedcements
opportunities and challenges. Cement &Concrete Research, Vol. 29, No.2, 1999,
pp.249-254.
[2] Dungca, J.R., Jao, J.A.L. Strength andpermeability characteristics of road basematerials blended with fly ash and bottom ash.
International Journal of GEOMATE, 12 (31),2017, pp. 9-15.
[3] Dungca, J., Galupino, J., Sy, C., Chiu, A.S.F.
Linear optimization of soil mixes in the designof vertical cut-off walls. International Journal of
GEOMATE, 14 (44), 2018, pp. 159-165.
[4] Dungca, J.R., Galupino, J.G., Alday, J.C.,
Barretto, M.A.F., Bauzon, M.K.G., Tolentino,
A.N. Hydraulic conductivity characteristics ofroad base materials blended with fly ash andbottom ash. International Journal of GEOMATE,
14 (44), 2018, pp. 121-127.
[5] Dungca, J.R., Galupino, J.G. Artificial neuralnetwork permeability modeling of soil blended
with fly ash. International Journal of
GEOMATE, 12 (31), 2017, pp. 76-83.
[6] Dungca, J.R., Galupino, J.G. Modelling of
permeability characteristics of soil-fly ashbentonite cut-off wall using response surface
method. International Journal of GEOMATE,
10 (4), 2016, pp. 2018-2024.
[7] Galupino, J.G., Dungca, J.R. Permeability
characteristics of soil-fly ash mix. ARPN
Journal of Engineering and Applied Sciences,
10 (15), 2015, pp. 6440-6447.
[8] Dungca, J.R., Codilla, E.E.T., II. Fly-ash-based
geopolymer as stabilizer for silty sandembankment materials. International Journal of
GEOMATE, 14 (46), 2018, pp. 143-149.
[9] Ang, Isaac, Joven, & Sollano. Use of dry
mixing method in fly ash based geopolymer as astabilizer for dredged soil (Unpublishedundergraduate thesis). De La Salle University,
2016.
[10] American Society for Testing and Materials.
Standard Test Methods for Specific Gravity of
Soil Solids by Water Pycnometer. ASTM D854,

295

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PERFORMANCE OF SOIL SUBGRADE IMPROVEMENT USINGWASTE MATERIAL
Harnedi Maizir1, Reni Suryanita2, Ulfa Jusi3 and Raihan Arditama4
Faculty of Civil Engineering, Sekolah Tinggi Teknologi Pekanbaru, Indonesia;
2
Faculty of Engineering, University of Riau, Pekanbaru, Indonesia
4
Faculty of Engineering, University of Andalas, Padang, Indonesia

1,3

ABSTRACTThe last decades, many researchers present the paper regarding to the potential of using fly ash and bottom
ash as a waste material in order to improve the soil subgrade layer in road project. The fly ash and bottom ash
used in this study from one of power plant in pulp paper industry in Riau. The aim and objective of this study is
to determine the California Bearing Ratio (CBR) value for soil road subgrade mixed with some percentage of
waste material, especially from fly ash. The second objective is to determine the optimum of percentage using
fly ash mixed with the soil. The laboratory testing of the soil mixed with the fly ash on the CBR value for soaked
and un-soaked condition. The stabilized of the soil subgrade mixed with the waste material were compared to thecontrol sample of the road subgrade criteria accordingly to Indonesia Public Work Department (PUPR) fromStandard Specification for Road Works. According to the laboratory testing result shows, the improvement of
CBR value from two type of mixed of soil and fly ash, first is soil : fly ash = 60%:40% and the second is
50%:50%. The optimum percentage of fly ash used is the second mixed. The use of second mixed in order toimprove the soil subgrade of CBR value for soaked and un-soaked condition. However, the result of CBR value
for both condition were fulfil the requirement for road subgrade criteria from PUPR Indonesia for Standard
Specification for Road Works. These study shows, waste material like bottom ash could be used as an alternative
solution to mix with the soil to improve the CBR value.
Keywords: Waste material, Fly ash, California bearing ratio, Road subgrade

determined the California Bearing Ratio(CBR) value
for soaked and unsoaked condition to the use of fly
ash mixed to the soil subgrade layer of pavement.

INTRODUCTION
The last decades, most of researcher from othercountries focus to the coal as a fuel alternative forpower generation. Indonesia was introduced coal as
raw material for power generation since 1986.
Nowdays, there are two coal power plants in Riau
province namely, Riau Andalan Pulp and Paper(RAPP), Indah Kiat Pulp and Paper (IKPP).
Increasing in electricity consumption demand has
led to increase the coal consumption required andthus more produced, more waste products. Coal ash
mostly consists of fly ash and bottom ash. Wahab(2006) mentioned that, about 2500 ton/months of fly
ash was produced by RAPP as waste material. The
problems become worse to disposal of ash are
limited availability of land and this has a significant
problem to the environmental.
The previous studies showed that the engineering
properties of waste materials, such as fly ash andbottom ash were more effective to improve theperformance of subgrade layer of the pavement thanthose common pavement material. (Norazalan et al.,2011) and (Ferreira et al., 2003).
This study focuses on the alternatives for using
waste material from coal power plants, especiallyfrom fly ash and the potential as additives to theroad subgrade layer of pavement. This study was

MATERIALS AND METHODS
Waste Material (Fly ash)
The waste material used in this study consideredwere collected from RAPP Plant in Pangkalan
Kerinci – Riau Province. The waste materials arewaste product produced from combustion of coal forelectric power generation. A detail physicalproperties of waste material from plants was shownin Table 1.
Table 1 Physical properties of RAPP waste material
Properties
Spesific gravity
Particle size distribution:
Gravel (%)
Sand (%)
Fine/Silt (%)

Values
2,05
0
22,92
77,08

The result for chemical properties of the wastematerial test is shown in Table 2.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2. Chemical properties of RAPP Fly ash (FA)
Chemical properties
Silicaon Dioxide
Aluminium Trioxide
Fero Oxide
Calcium Oxide
Magnesium Oxide
Loss on Ignition

Preparation of sample
The testing used in this study is the California
Bearing Ratio (CBR) test. Two sets of sample wereprepared to determine the CBR value of this samples.
First sample is mixed with the soil 60% and wastematerial 40%. The second sample is mixed with thesoil 50% and waste material 50%. There are two
number of sample for each test to be prepared.

Chemical values
(%)
48,2
13,2
4,3
18,6
0,9
8,4

California Bearing Ratio (CBR) Test
The California Bearing Ratio(CBR) tests werecarried out to determine the CBR index value andthe test carried out based on standard procedure
given in ASTM D1883. CBR test method is used toevaluate the potential strength of the subgrade
material. CBR defined as the ratio of the loadsustained by the specimen at 2,5 or 5,0 mm
penetration to the load sustained by standard load
aggregate at corresponding penetration level.
The entire tests to determine CBR value were
performed in soaked and unsoaked condition. The
samples were prepared with its optimum moisture
content and were compacted at their maximum dry
density.

Based on the result of physical properties test, itshows that the RAPP fly ash (FA) classified as lightmaterials due to the specific gravity is about 2,05.
According to (Muhardi et al., 2010), the lower
specific gravity of fly ash due to the lower ferooxide content since the specific gravity related to thechemical composition. Based on Table 2shows that
the RAPP fly ash (FA) classified as class C fly ash
accordance to ASTM C618. RAPP fly ash (FA)consists of total combination composition of silicon
dioxide, aluminium dioxide and fero oxide morethan 50%.
Soil Road sub-grade.

RESULTS AND DISCUSSIONSThe properties of soil using in this study are given in
Table 3. As per Unified Soil Classification System(USCS), the soil is a MH soil.

The Laboratory result for CBR value for soaked
and unsoaked condition

Table 3. Soil properties
value
2,56
61,67
44,10
17,60

STRESS STRAIN CURVE

1000
900
800

1,27
38,25

700

Load (Lbs)

Description parameter
Specific Gravity
Atterberg Limits
LL
PLIP
Compaction Factor
γ (gr/cc)w (%)
Particle size distribution
Passing #200 (%)
Passing #4 (%)

Figure 1and Figure 2 shows the laboratories result
for CBR value of soil subgrade (50%) mixed with
waste material (50%) for soaked and unsoaked
condition.

97,33
100,00

600
500
400
300
200

Laboratory Testing100

The are some testing carried out in this study todetermine the index and engineering properties ofthe soil sub-grade. The testing method based on
ASTM standard for each test.(ASTM & D1883,
2014)

0

0

0,1

0,2

0,3

0,4

Penetration (inch)

Fig. 1 The laboratory result for CBR value soaked
50%-50%297

SEE - Nagoya, Japan, Nov.12-14, 2018

STRESS STRAIN CURVESTRESS STRAIN CURVE

1000

800

900

700

800

600
500

Load (Lbs)

Load (Lbs)

700
600
500
400

400
300

300

200
200

100

100
0

0

0

0,1

0,2

0,3

0,4

0

0,1

Penetration (inch)

0,2

0,3

0,4

Penetration (inch)

Fig. 2 The laboratory result for CBR value unsoaked
50%-50%

Fig 4 The laboratory result for CBR value unsoaked
60%-40%Figure 3 and Figure 4 shows the laboratories result
for CBR value of soil subgrade (60%) mixed with
waste material (60%) for soaked and unsoaked
condition.

The California Bearing Ratio (CBR) mixed with
waste material
Table 4 shows the CBR value versus percentage
of waste material from RAPP mixed with soil
subgrade for soaked and unsoaked condition. Its
shows that the CBR value for soaked condition
relatively lower than CBR value for unsoaked
condition. Its cause of saturated of soil for soaked
condition. It shows the CBR values increase 24,3%
for 60%-40% soil mixed for soaked and unsoaked
condition. For the 50%-50% mixed with the soil andwaste material, the CBR value increase 17,9% forsoaked and unsoaked condition

STRESS STRAIN CURVE

800
700

Load (Lbs)

600
500
400
300

Table 4 The CBR value for soaked and unsoaked
condition at every percantage of wastematerial

200
100
0

0

0,1

0,2

0,3

0,4

SamplePenetration (inch)

Fig 3 The laboratory result for CBR value soaked
60%-40%1
2

Soil:Wasteof material(%:%)
60 : 40
50 : 50

CBR
soaked
%
11,9
16,2

CBR
unsoaked
%
14,8
19,1

CONCLUSION
According to this study, waste material from
RAPP coal power plant (fly ash and bottom ash) aresuitable material to be used as additive for soil
subgrade. It was proved by laboratory experimental
result. By using the waste material (fly ash andbottom ash) as an additive material to the soil mixed
was improved the CBR value strength. The
percentage is suitable for soaked and unsoaked
condition accordingly to the CBR value index

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ACKNOWLEDGEMENTS
The authors would like to thank STT-Pekanbaru
for using the soil mechanic laboratory and
Kemenristekdikti-Indonesia for funding this research
year 2018.
REFERENCES[1] ASTM, & D1883. (2014). Standard test
method for California bearing ratio (CBR)of laboratory-compacted soils: ASTM
International West Conshohocken, PA.
[2] Ferreira, C., Ribeiro, A., & Ottosen, L.
(2003). Possible applications for municipal
solid waste fly ash. Journal of hazardous
materials, 96(2-3), 201-216.
[3] Muhardi, A., Khairul, A., Wei, L., & Lim,Y. (2010). Engineering Characteristics ofTanjung.
[4] Norazalan, Norbaya, & Fadzil, M. (2011).
The Potential of using Bottom Ash (BA)
Additives in Road Base. Paper presented attheInternational
Building
andInfrastructure
Technology
Penang,Malaysia.

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4th Int. Conf.on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

EFFECT OF GRADATION OF BOTTOM ASH AS FINE AGGREGATEON ENGINEERING PROPERTIES OF SHOTCRETE
Sattaya Chaiwithee1, Pitiwat Wattanachai1and Pisut Rodvinij1
1
Faculty of Engineering, Chiang Mai University, Thailand

ABSTRACTThis study focused on the effect of grain size distribution of bottom ash on the engineering properties of
shotcrete. Bottom ash was used as fine aggregate replaced fine sand in the mixture of shotcrete. Size distributionof aggregate that used in the test consists of upper boundary and lower boundary of gradation No.1 referencesfrom ASTM C33 and aggregates passed sieve No.4. The mixture of mortar was a combination of Portland
cement and fine aggregate is the ratio of 1:3. Water to cement ratio for a mortar is 0.6. The physicalcharacteristics of the bottom ash particles showed high porosity, very irregular and brittle. Therefore, thecompressive strength of bottom ash aggregate mortar was less than sand aggregate mortar approximately 45%.
The compressive strength of the samples mixed with bottom ash passed sieve No.4 gave the highest strength.
The compressive strength of the samples contains the maximum, minimum size distribution and aggregate
passed sieve No.4 were 7.7, 10.6 and 12.6 MPa respectively. The results of slump flow tests demonstrated theflow of mortar tends to increase with the reduction in the particle size of aggregate. Nevertheless, the setting
time tends to decrease with the reduction in the particle size of aggregate. In conclusion, bottom ash passed sieve
No. 4 was the most suitable to use as fine aggregate in the mixture of shotcrete.
Keywords: Bottom ash, Shotcrete, particle size and light weight
Claystone has been used as a backfill material tocounterweight and supported the potential mass.
However, claystone deteriorated when it has been
exposed to weather change was a cause of decreased
in a stability of backfill [3].
The literature review demonstrated claystone
protected from a weather change can maintainphysical properties of claystone and shear strengthof backfill [3]. Thus, shotcrete becomes the suitablestabilization method to maintain the stability ofclaystone backfill slopes. Due to shotcrete is often
used for temporary protection of exposed rocksurfaces that will deteriorate when exposed to air
and also used to permanently cover slopes or cut that
may erode in time or otherwise deteriorate [4].
Normally, the proportion of the shotcrete mixture
consists of cement, sand, and water and the unit
weight of normal shotcrete was approximately 2.2
T/m3 [5]. The external load that increases on abackfill due to the unit weight of shotcrete can leadto reducing the stability of slopes. Thus, thelightweight shotcrete became a good choice tostabilize the stability of backfill slope better than anormal shotcrete.
Therefore, this study focused on the lightweightshotcrete by using bottom ash, which is by-productmaterials from Mae-Moh power plant as fineaggregate in the mixture of shotcrete.
However, Aggregate of shotcrete mortar should
comply with the quality requirements of ASTM C
33. Table 1 shows acceptable grading limits.
Grading No. 1 should be used if a mortar mixture

INTRODUCTION
Area 4.1 located on the northeast side of the pit
wall in Mae Moh mine as shown in Fig. 1.
According to the mine plan, K and Q seams (green
layer and red layer in Fig.1) of lignite must be
excavated [1]. The cut and fill method become asuitable method was used to excavate lignite in thisarea. The area will be mined and partially undercut.
After completion of mining, backfilling will begin to
support the slope face and maintaining adequate
room for mining activities. The mining- backfilling
cycle is iterative until all the lignite in area 4.1 iscompletely mined out. It is necessary to fill thecurrent pit and cut the neighboring slope in a
subsequent procedure [1], [2].

Fig. 1

Cross section plot of area 4.1 [1].

300SEE - Nagoya, Japan, Nov.12-14, 2018

desired [4]. However, grading No.1 shown the lower
and upper limit of the aggregate. The different size
distribution of aggregate in the mixture of mortar
can be altered the properties of shotcrete mortar.
Thus, the investigation on the influence of thedifferent size distribution of fine aggregate in the
mixture can suggest a lower and upper limit
properties of shotcrete.

However, the particle size of bottom ash depends on
the source [6]. The density of mortar which
replacement of sand with bottom ash can be reduced
approximately 0.4 T/m3 due to a particle of bottom
ash has a high porosity [7].
Bottom ash fine aggregate has prepared byheating in an oven at 100 ºC for 24 hours. Then,bottom ash mixing with the water at moistureabsorption and curing them for 24 hours. Bottom ash,which passed this process has been used as fineaggregate in shotcrete mortar.

Table 1 Grading Limits for Aggregate [4]Sieve Size
¾ inch½ inch3/8 inch
0.19inch(No.4)
0.093inch(No.8)
0.046inch(No.16)
0.024inch(No.30)
0.012inch(No.50)
0.006inch(No.100)

Percent by Mass Passing
Individual Sieves
Grading Grading Grading
No.1
No.2
No.3
100
100
80-95
100
90-10070-9095-10070-85
50-7085-100
50-70
35-55
50-85
35-55
20-40
25-60
20-35
10-30
10-30
8-20
5-17
2-10
2-10
2-10

MATERIALS PREPARATION AND MIXPROPORTION OF SHOTCRETE
Wet mix shotcrete is predominantly used becauseof its homogeneity in quality and high work
efficiency [8]. The normal mixture proportion of
shotcrete consists of sand as fine aggregate, cement,
and water. However, the mixture proportion oflightweight shotcrete consists of bottom ash as fineaggregate, cement, and water.
Ordinary Portland cement type 1 is usedthroughout the experiments. Sand which passed
sieve No.4 is coming from the natural river sand.
Bottom ash obtained from a Mae Moh power plantin Lampang province of Thailand. Bottom ash,which used in this experiment should be passed
sieve opening No.4 to replaced as sand in mortar
mixture. Size distribution of sand was shown in
Fig.2. Size distribution of bottom ash was shown in
Fig.3. The three different size distribution of
aggregate consists of lower boundary, an upperboundary, and middle grade was used in this test.
Middle gradation of sand and bottom ash is theaggregate passed sieve No. 4.

BOTTOM ASH
Bottom ash (BA) is a solid waste from the
combustion of coal. The annual output of lignite
bottom ash in the Mae Moh power plant in the northof Thailand is around 0.8 million tons and is
disposed of a landfill near the power plant. Several
types of research on the utilization of coal bottom
ash for use as a cementitious material have been
conducted. The bottom ash has to be ground toincrease the pozzolanic activity and used to partiallyreplace Portland cement. The utilization of bottom
ash as a cementitious replacement material has not
yet been well received as it needs grading and only apartial replacement of cement is possible. Moreover,the bottom ash itself is porous and increase the waterrequirement of the mix. On the other hand, thegrinding of coal bottom ash results in a prolonged
setting time and causes a reduction in theworkability of the paste.
The as-received bottom ash particles wererelatively large and very irregular, showing
agglomeration of some spherical particles and otherfragments with observable pores. The chemicalcomposition of BA was 39.3 % SiO2, 21.3% Al2O3,
13.5% Fe2O3, 2.1% K2O, 16.5% CaO, 1.0% Na2O
and 1.4% loss of ignition [5].
Typically, the bottom ash contains assorted size
closer to the sand. The gradation 50-90 percent
passing sieve No.4, 10-60 percent passing sieve No.
40 and 0-10 percent passing sieve no.200. The
maximum particle size about 19.0-38.1 mm.

120

Percentange Passing (%)

100

Middle
Upper

80

Lower

60
40
20

0
10

1

0.1

Particle sizes (mm)Fig. 2

301

Size distribution of sand used as fineaggregate.

SEE - Nagoya, Japan, Nov.12-14, 2018

is dropped, it spreads out on the flow table.
Measured the diameter of the mortar along the fourlines. The flow is the average of the diameter ofmortar on the table.

120

Percentange Passing(%)

100

Middle
Upper

80

Lower

Setting time

60

This test method is intended to be used todetermine the initial setting time of mortar according
to ASTM C191. Vicat initial time of setting is
calculated as the time elapsed between the initial
contact of cement and water and the time when thepenetration is at 25 mm. The Vicat final time ofsetting is calculated as the time elapsed between
initial contact of cement and water and the time
when the needle does not sink visibly into a paste.

40
20
0
10

Fig. 3

1
Particle sizes(mm)0.1Size distribution of bottom ash used as fineaggregate.

Sagging and Build up thickness
The mix design of shotcrete mortar in this study
consist of a mixture used sand as fine aggregate anda mixture used bottom ash as fine aggregate. The
three difference size distribution of fine aggregate,according to Fig 3 and Fig 4 were used in the
mixture. The mixture of mortars was a combinationof Portland cement Type 1 and fine aggregate is in aratio of 1:3 by weight of cement. Water to cement
ratio for a mixture of mortar is 0.6. The six mix
proportion of shotcrete mortar as shown in Table 2.
Table 2
Mixture
code
SU
SM
SL
BU
BM
BL

This test method is intended to be used todetermine the build thickness of shotcrete mortar.
The build-up test consists of substrates with a build
thickness of framework at 300 mm. The surface of
substrates was claystone backfill. The trial mixes
will be plastered into an incline 300 x 300 mm byhand application to measure the build-up thicknessof mortar as shown in Fig 4. The inclination angle
that used in this test was 30, 45 and 60 degrees at the
thickness of the samples 5, 8 and 10 cm. The
sagging of mortar can be investigated by theincreasing thickness of mortar.

Mix proportion of shotcrete mortar
W/C

S/C,BA/C

0.6
0.6
0.6
0.6
0.6
0.6

3:1
3:1
3:1
3:1
3:1
3:1

Sand
(%)
100
100
100
0
0
0

BottomAsh(%)
0
0
0
100
100
100
Fig. 4

Sagging and Build-up thickness of mortar.

EXPERIMENTAL PROGRAM
Compressive strength
Shotcrete mortar mixed according to Table 2
were conducted to determine fresh properties andhardened properties. Fresh properties evaluationconsists of slump flow test, setting time and sagging
and build-up thickness. Hardened properties
evaluation consists of compressive strength.

This test method is intended to be used todetermine the compressive strength of mortar
according to ASTM C109. The specimen each mix
proportion cast in the mold of mortar at 50x50x50
mm cube specimens. Make three specimens ofmortar for each period of test or test age. The
specimens were cured in the water after the mortar
hardened. Test the specimens immediately after theirremoval from storage water after 3, 7, 14, 28 and 56
days. The Universal testing machine was used todetermine compressive strength.

Slump flow test
This test method is intended to be used todetermine the flow of mortars, according to ASTM
C 1437. Workability of mortar is its ease of use
measured by the flow of the mortar. The flow tableand flow mold were used to determine slump flow.
The mortar sample if placed on a flow table anddropped 25 times within 15 seconds. As the mortar
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SEE - Nagoya, Japan, Nov.12-14, 2018

respectively. A final setting time of SU and SM tend
to similar but a final setting time of SL was higher
than SU and SM approximately 45 minute.
Like, the initial setting time of mortar mixed
with bottom ash increased with the increase in thesize distribution of aggregate. Therefore, the initial
setting time of BL was higher than BM and BU
approximately 5 and 15 minutes respectively.
Moreover, a final setting time of BL was higher than
BU and BM approximately 60 minute and 45
minutes respectively.

FRESH PROPERTIES OF SHOTCRETE
The fresh properties of shotcrete mortar consistof slump flow test, setting time and sagging andbuild up thickness conducted on the samples mixed
according to Table 1.
The results of slump flow test
The slump flow of all mix proportions should be
225±10% mm. [8].
Table 3 and Fig.5 shown the test results of slump
flow on a fresh mortar. The flow of mortar mixed
with sand aggregate was approximately 20 cm -21
cm. However, The flow of mortar mixed withbottom ash aggregate was approximately 19.2 cm 20.6 cm. The results demonstrated the flow ofmortar tends to increase with the reduction in theparticle size of aggregate. This is due to a large
particle of bottom ash has a high porosity and highwater absorption[6].

Table 4 Setting time of shotcrete mortar
Mixture
code
SU
SM
SL
BU
BM
BL

Table 3 Results of flow ability

Final setting
time (minutes)
225
225
270
210
225
270

300

Slump Flow (cm)
21
20.5
20.0
20.6
20.4
19.2

Initial Setting Time
270
Final Setting Time

270

250

225

225

225
210

200

Time (Minutes)

Mixture code
SU
SM
SL
BU
BM
BL

Initial setting
time (minutes)
142
150
162
140
151
156

150

150

162

160

142

156
140

100
50

25

Slump Flow (CM)

21

20.6

20.5

sand
20.4

20

bottam ash
20

0
SM

19.2

SU

SL
BM
Mixture code

BU

BL

15

Fig. 6

10
5

Setting time of a various shotcrete mixture.

The results of sagging built-up thickness

0
SM-BM

SU-BU

SL-BL

The sagging and built-up thickness was
conducted on SM and BM samples. The trial mixes
plastered on the surface of backfill which paste in
the incline box by hand application. The inclination
angle was 30, 45 and 60 degrees at the thickness 5, 8
and 10 cm. The results of sagging built-up thicknessof shotcrete with different thickness and inclination
angle presented in Fig 7.
Sagging of SM was higher than BM at the same
thickness and inclination angle. This is due to theunit weight of SM was more than BM. The unit
weight of SM was 2.15 g/cm3 and the unit weight of
BM was 1.70 g/cm3. The maximum sagging ofmortar occurs with SM samples at a thickness 10 cm
and inclination angle of 60 degrees. The maximum
sagging of SM was approximately 10 cm. However,

Mixture CodeFig. 5Slump flow of a various shotcrete mixture.

The results of setting time
The setting time of shotcrete mortar with avarious size distribution of sand aggregate andbottom ash aggregate was presented in Table 4 andFig 6. The result showed an initial setting time of themortar mixed with sand aggregate increased with theincrease in the size distribution of aggregate.
Therefore, the initial setting time of SL was higher
than SM and SU approximately 10 and 20 minutes

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SEE - Nagoya, Japan, Nov.12-14, 2018

BM was not sagging at the inclination angle of 45
degrees and a thickness 8 cm but SM was sagging 3
cm. Thus, the result shown the lower unit weight ofthe mortar can be reduced sagging and increase thethickness of mortar.

Compressive strength (MPa)60

12Sagging (cm)1085 cm of sand8 cm of sand10 cm of sand5 cm of BA
8 cm of BA
10 cm of BA

50

SM1:3

SU1:3

SL1:3

BM1:3

BU1:3

BL1:3

40
30
20
10

0
0

10

20

30

40

50

60

Curing time (days)

6

Fig. 84The compressive strength of a various
shotcrete mixture.

2

CONCLUSION

0

Angle degree

Fig. 7

Based on the results which obtained from anexperimental study, it can be concluded that
The used bottom ash as an aggregate in the
mixture of shotcrete was reduced flowability
because a particle of bottom ash has a high porosityand high water absorption. However, a slump flowof shotcrete mixed with the upper boundary andmiddle gradation of bottom ash was in therequirement of slump flow of shotcrete.
. Sagging of shotcrete mortar mixed with sandaggregate was higher than shotcrete mortar mixed
with bottom ash aggregate at the same thickness andan inclination angle. This is because the unit weightof shotcrete mixed with sand aggregate was morethan shotcrete mixed with the bottom ash aggregate.
The compressive strength of a shotcrete mixed
with bottom aggregate was less than shotcrete mixed
with sand aggregate. Due to the particle of bottom
ash was weaker than sand particles and bottom ash
have a high porosity. The maximum strength of
shotcrete mixed with bottom ash was 13 MPa at acuring time 56 days. However, the compressive
strength of shotcrete mixed with bottom ash waspossible to use for protecting a backfill fromdeterioration. Thus, the all result shown thepossibility to use bottom ash as fine aggregate in
shotcrete mortar.

Sagging and Built up thickness of each
shotcrete mixture.

HARDENED PROPERTIES OF SHOTCRETE
This section presented the hardened properties of
shotcrete by a compressive strength test. All tests aredone in accordance with the American of Testingand Materials standard (ASTM).
The results of compressive strength
The compressive strength of all mixtures in thisstudy was presented in Fig.8. It obtained from acompressive strength test of shotcrete cubes in 3, 7,
14, 28, 56 days. Each reported value is the averageof three cube specimens.
The result shown the compressive strength ofSU, SM and SL were slightly different at 7 days.
The compressive strength of SL was the highest in
56 days. However, SU demonstrated the lowest
compressive strength in a shotcrete mixed with sandaggregate. In 56 days, the compressive strength of
SL was higher than SU and SM approximately 12
and 21 MPa, respectively.
The compressive strength of a shotcrete mixed
with bottom ash aggregate was slightly different
between BU, BM, and BL. However, thecompressive strength of BU was higher than BM
and BL, respectively in 56 days. This is due to alarge particle size of bottom ash is weak and it has ahigh porosity [6].
The comparison between the compressive of
shotcrete mixed with bottom ash and shotcrete
mixed with sand was shown the compressive
strength of BM was lower than SM approximately
26 MPa. This is because a particle strength ofbottom ash was weaker than sand.

ACKNOWLEDGEMENTS
The research work is done during the study at
Chiang Mai University, and also express anappreciation to the Graduate School, Chiang Mai
University for the financial support.

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REFERENCES[6] Moulton, “Properties of Pozzolan”, Chiang Mai
University, 1973
[7] Torkittikul P, and Nochaiya T, "Compressive
Strength, Density and Thermal Conductivity of
Mortar containing fly ash and Bottom ash,"
Proceeding the 7th National Science Research
Conference, 2015, pp. PY-O-029.
[8] Samaru Y, and Sugiyama K, "Slope
Stabilization Using the Shotcrete Grid Beam
System in Japan," Shotcrete Spring, 2005, pp.
36-40.
[9] American Society for Testing and Materials,“Standard Test Method for Compressive
Strength of Hydraulic Cement Mortars(Using 2in. or [50-mm] Cube Specimen)”, ASTM
C109M-16a,2011[10] American Society for Testing and Materials,“Standard Test Method for Time of Setting of
Hydraulic Cement by Vicat Needle”, ASTM
C191,2007[11] American Society for Testing and Materials,“Standard Test Method for Flow of Hydraulic
Cement Mortar”, ASTM C1437,2007[1] Leelasuksaree C, Mavong N, Khosravi M H,
Pipatpongsa T, "Physical and Numerical
Models of Undercut Slope Lying on Steeply
Inclined Bedding Plane", 17th National
Convention on Civil Engineering, 2012, pp.
GTE045-1 -GTE045-10.
[2] Mavong N, Tunkeaw S, Mungpayabal N,
Boonsritun N, "Mining Plan and Progressive
Excavation in Lowwall Area 4.1 of Mae Moh
Mine", International Symposium on Earthquake
Hazard Potential and Preparedness for Safety in
Coal Mining, 2011.
[3] Rodvinij P, and Wattanachai P,"Influence ofClaystone Deterioration on Shear Strength of
Backfill", International Journal of GEOMATE,
July 2017, Vol. 13, Issue 35, 54-59.
[4] US Army Corps of Engineers, Engineering and
Design Standard Practice for Shotcrete, 1993,
pp. 2-1 - 4-7.
[5] Sathonsaowaphak A, Chindaprasirt P, andPimraksa k, "Workability and strength of lignite
bottom ash geopolymer mortar," Journal ofHazardous Materials 168, 2009, pp. 44-50.

305

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

A STUDY OF THE QUALITY OF SOIL INFILTRATION AT THE
DOWNSTREAM OF KURANJI RIVER, PADANG CITY
Aprisal, Bambang Istijono*, Taufika Ophiyandri and Nurhamidah
Andalas University, Padang, Indonesia*Email: bistijono@eng.unand.ac.id; bistijono@gmail.com

ABSTRACTThe watershed at the downstream of Kuranji river often experience flooding. This is due the rainfall runoff
and the flat condition of the downstream area. Other factor might be due to low soil infiltration rate. The
objective of this research was to analyze the quality of soil infiltration at the downstream of Kuranji River’s
watershed. Research methodology that had been choosed was field survey. Soil infiltration rate was measured
using double ring infiltrometer. Location of soil sample was selected by purposive random sampling and wasanalyzed at the Department of Soil Science Andalas University. The data was analyzed using Horton formula toidentify the capacity and the cumulative soil infiltration rate. The result showed that the area which often
inundated and has high soil watertable had low infiltration rate. The results showed that the bulk density factor,
clay fraction and dust significantly affect the capacity of soil infiltration. Moreover, bulk density, clay fraction,and dust influence soil infiltration capacity. Areas that have high infiltration capacity are Gunung Sariek, Aie
Pacah, Ampang, Kurao Pagang, and Dadok Tunggul Hitam. Other sampling locations have low infiltration rate
due to high soil watertable.
Keywords: Infiltration capacity, Runoff, Watershed, Watertable

Kuranji river basin is often impaired due to rapidly
saturated soils. As a result, the city of Padang isoften flooded and inundated causing houses to be
flooded (Fig. 1). Factors causing the soil is saturated
rapidly due to high groundwater level, soil texture isvery smooth and layered consequently inhibit theentry of water into the soil. According to Asdak [4]when the rain falls on the surface of the groundsome of the water will be retained by the depressedpart of the soil, some of it into the soil and some into
the runoff. The rainwater that enters the soil fills thepores of the empty soil until the water reaches thefield capacity. Furthermore, the water will move
more deeply due to the force of gravity into
percolation of water to reach the saturated region.
Water in saturated regions can also movehorizontally due to plant root uptake and capillary
forces. Radke and Berry [5] stated that the verticalentry of water into the soil is closely related to thestructure or physical and biological characteristics ofthe soil. Further, other factors that affect water
infiltration is slope, soil texture, land use, land
processing, soil water content and soil organic chart.
The state of the soil surface and the number of soil
pores will determine the volume of water that canenter into the soil [6]. Soil pores that are numerous
and interlocked into the deeper soil will increase therate of infiltration. Includes pore holes made byroots and soil fauna.

INTRODUCTION
Water infiltrates the soil through the soil surface.
In the ground, water flows in the lateral direction as
the flow between (interflow) to springs, lakes andrivers; or vertically, known as percolation to theground water. The motion of water in the soil isaffected by the force of gravity and the capillary
force [1].
A technical report on Infiltration Characteristics
of Soils Under Forestry and Agriculture in the Upper
Waikato Catchment has been done due to increasingpressure for conversion of forest to agricultural land
within the upper Waikato catchment. The study
found that the conversion of forest to agriculturalland within the upper catchment area to increase
the accurance of flooding, both of peak andintensity of the flood, and also increase erosion
and sedimentation. [2]The special work for advanced study in theassessment of the maximum water storage capacityof soils under different land-use and landmanagement situations in a real river catchment has
been done [3]. The study is done by fieldmeasurements of infiltration under several land-use
and land-management situations. Then, adevelopment of modelling approach to estimate themaximum potential water storage capacity also
proposed. The study found that due to the change inland-use and land-management could reduce thestorage infiltration capacity by 17 %.
The rainwater absorption in the downstream
306

SEE - Nagoya, Japan, Nov.12-14, 2018of soil physical characteristics (BD / bulk density,
TRP/total pore space, organic C, permeability,
texture, etc.), and soil samples were disturbed forsoil organic C-analysis Infiltration measurements
were performed at each location of the soil sampling
point.
Data Calculation and Analysis
1. The soil texture parameters were analyzed byusing triangle texture to determine the soil
texture class.
2. Hydraulic conductivity set by using the Deboodt
method using Darcy's legal principle.
3. Establish infiltration capacity using double ring
infiltrometer, and data are analyzed using
Horton formula ie F = fc + (fo-fc) e-kt.
4. Analyze the result of soil physics characteristics
from laboratory in statistical analysis withcorrelation analysis and Principal Component
Analysis (PCA) or main component analysis
with Minitab 17 software. So it can be selected
main factor most determine infiltration capacity
at Kuranji downstream basin.

Fig. 1 Area Flooded at Gunung Pangilun,
Downstream of Kuranji Watershed.
The rate of infiltration decreases because of thechanging of soil porosity which blocked by fineparticles. The fine particles may come from spatteror from mud brought by flood. Dense soil surface
becomes water resist [4, 7]. This study aims to
examine the quality of soil absorption in thedownstream Kuranji river basin.
RESEARCH METHODOLOGY
Location and Time of ResearchThis research was conducted from March to
April 2018 at the downstream Kuranji watershed in
Padang City, West Sumatra, Indonesia. Based on thegeographical position of the study sites are at
00047'21 "to 00055'57" LS and 100020'31 "to100033'54" BT, with a height of 0 up to 1859 above
sea level. Research location are at Aie Pacah 1,
Kurao Pagang, Dadok Tunggul Hitam, Aie Pacah 2,
Gunung Sariek, Ampang, Gunung Pangilun, andKorong Gadang (1-8 locations).
Tools and Materials
The tool used in this study is a set of computerswith ArcView / ArcGIS program, Microsoft Excel,
Global Positioning System (GPS), infiltrometer.
Materials used in this study are Digital Elevation
Model (DEM) data in the form of Triangulated
Irregular Network (TIN), map of Kuranji watershedadministration, land use map, soil type map, andmonthly rainfall data.

Fig. 2 Research Location in the Downstream
Kuranji Watershed.
RESULT AND DISCUSSION

Data Collection

The main factors of soil physical characteristics that
affect the infiltration capacity

The data collected were 1) soil parameters(texture, soil structure, soil permeability, and soil
effectiveness), 2) infiltration capacity measured
directly in the field using double ring infiltrometer.
Soil sampling is done purposively (purposive
sampling), which is based on the consideration of
spatial distribution and areas that often get flooded
during the rain at 8 locations. The examples of soil
taken are examples of intact soils and disturbed soil
samples. The soil samples were used for the analysis

The results of principal of component analysis(PCA) [8] on soil physical characteristics, showedthat eigenvalue is greater than one ie PC1 (principal
component1) and PC2 (principal component2). On
the PC most variable values affect the infiltration
capacity is greater value on PC1 is bulk density(BD) 0.417, clay fraction 0.416. While on PC2 is
0.445 dust fraction. Based on this selected variable
hence can be made graph relation between variable
and infiltration capacity.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 This is the example for table formatting
Eigenvalue
Proportion
Cumulative
Variabel
BD
TRP
C Organik
Permeability
Sand
Dust
Clay

3.9644
0.566
0.566
PC1
0.417
-0.4170.056-0.349-0.4620.374
0.416

1.2777
0.183
0.749
PC2
-0.3700.370-0.648-0.238-0.2270.445-0.023Fig. 4 Correlation of infiltration capacity withpercentage of clay content in downstream
Kuranji watershed in Padang.

Based on PCA result analysis, asimple regression
relationship between infiltration capacity with soil
physical characteristics variable and sampling point
location was made.
The correlation of infiltration capacity to thelocation of flood affected areas
The infiltration capacity with some floodaffected sites has an exponential relationship (Figure2). The closeness of the relationship between theinfiltration capacity and the location of the flood isquite strong with the value of R2 equal to 0.9297. It
means that flood affected locations affect infiltration
capacity by 93 percent. This is because the locations
affected by the flood caused a change in thecharacteristics of soil physical characteristic that
affect the maximum ability of the soil in the water.
Floods generally carry a lot of sediment loads ofvery fine sand fractions, dust and clay. The results ofHuria [9] show that the Batang Kuranji river carries
the sediment 194,08 mg / l. The sediment material
comes from forest exploitation, mixed gardens,
shrubs, and settlements. The sediment material
carried to the floodplain will affect the physicalcharacteristics of the soil, especially the compositionof the fraction and the pores of the soil in the soil
layer.

Fig. 5 Correlation of infiltration capacity withpercentage of dust in downstream Kuranji
watershed in Padang.

Fig. 6 Correlation of cumulative infiltration withthe research location in the downstream
watershed in Padang.

The correlation of infiltration capacity with clay
fraction
The highest percentage of clay fraction is foundin Aie Pacah area, Gunung Sariek and Korong
Gadang. The clay content of the soil will increase
the soil micro pore from the micro pores. The
percentage of this pore affects the movement thatenters the soil. Based on the results of major
component analysis (PCA) clay fraction is one of thevariables that determine the infiltration capacity inthe lower Kuranji river basin. Based on simple

Fig. 3 Correlation of infiltration capacity withresearch location in downstream Kuranji
watershed of Padang.

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SEE - Nagoya, Japan, Nov.12-14, 2018

regression analysis of clay correlation with
infiltration capacity very closely with value R2 =0,8306 (Figure 4). This means that 83 percent
infiltration capacity is influenced by clay fraction. It
is also stated by Foth [10] that clay-textured soils
will be dominated by micro pores and unlike sandy
terraces will be dominated by micro pores. The
infiltration capacity is not determined by the micro
pores but is the macro pore. In macro pore theinfiltration capacity will be greater than slowmoving micro pores. Soil fraction or soil texture,also called soil grain, is one of the most important
properties of the soil. This is because soil fractions
are closely related to the movement of water andsolutes, air, heat movement, weight of soil volume,
specific surface area, compressibility, etc. [11].

absorption areas.
The difference in infiltration capacity between
the sample sites is due to the differences of soil
physical properties of the soil. Based on the analysisof PCA has sort out the variable of soil physics
properties that are very influential are BV, clay
fraction and dust fraction. The different of soil
properties on sampling locations caused by the
influence of the material cumulative floods (finefractions). This means that the location is often
inundated gradually so the nature of the soil will
experience changes, especially the bulk density
nature of the increasing tendon and reduce themovement of water into the soil. According toresearch results Mukhtar et al. [9] and Aprisal et al.
[15], finds the infiltration rate which tends to fall
due to the surface which always hit the raindrops
causing the soil to become slippery and smooth.

Correlation of infiltration capacity with dust
fraction

CONCLUSIONSThe correlation between the fraction of dust andthe infiltration capacity was strongly correlated, with
the R2 value of 0.8318 (figure 5). This means that
83% of the infiltration capacity is affected by dust
fraction. When compared to the size of the dust withclay, then illite is smoother than dust so there is adifference in relationship between infiltration
capacity between dust and clay.
According to Hardjowigeno [12], soil texture
shows the comparison of grains of sand (2mm-50 μ),
dust (50-2 μ) and clay (< 2 μ) in the soil. The soil
texture class is divided into 12 classes, namely:
sand, sand, sandy clay, clay, dusty clay, dust, clay,
sandy clay clay, dusty clay clay, sandy clay, dusty
clay, clay. Based on its size, the soil solid material isclassified into three particles of sand, dust, and clay.
Sandy soils are sand > 70%, low porosity (< 40%),
most of the pore space is large, resulting in good
aeration of rapid water conductivity, but the ability
to hold water and low nutrients. The soil is called
textured clay if the clay content is > 35%, theporosity is relatively high (60%), but most of it issmall pore, water conductivity is very slow and air
circulation is substandard [13]. In the sand soil
texture, the percolation rate will be very fast, in theclay soil texture the percolation rate is moderate tofast and in the clay texture the rate of percolation
will be slow [14].

Based on the research, it can be concluded, that;
1. The main factors affecting the capacity of
infiltration capacity in flooded areas are bulk
density, clay fraction, and dust.
2. The magnitude of infiltration capacity is
influenced by soil physical properties having
the first high correlation with clay fraction(R2 = 0,83) and dust has negative correlation(R2 = - 0,83).
3. Areas that have high water absorption or
cumulative rate of infiltration capacity are
Gunung Sariek, Aie Pacah, Ampang, Kurao
Pagang, and Dadok Tunggul Hitam.

ACKNOWLEDGEMENTS
This research was funded by Andalas University
under Research Grant No 43/UN.16.17/ PP.RGB/LPPM/ 2018 dated April 23, 2018.
REFERENCES[1] Bambang Triadmodjo 2008.
AppliedHydrology. Beta Ofset Yogyakarta. 380 pages.
[2] Taylor M., Mulholland M. and Thornburrow D.,
Infiltration Characteristics of Soils Under
Forestry and Agriculture in the Upper Waikato
Catchment, Environment Waikato Technical
Report 2009[3] Desoky M S., Dissertation: Impact of land-use
and land-management on the water infiltration
capacity of soils on a catchment scale, Fakultät
Architektur,
Bauingenieurwesen
undUmweltwissenschaftenderTechnischen
Universität Carolo-Wilhelmina, March 2011

Cumulative infiltration in frequently flooded area
Cumulative infiltration at various sampling sites
showed that the largest cumulative infiltration was
located at location 1, 5, and 6 (Fig. 6). It means thatthese locations have more ability to absorb water
than other locations. Areas that have larger
cumulative infiltration can be used as surface water309

SEE - Nagoya, Japan, Nov.12-14, 2018

[4] Asdak 1995. Hydrology and Watershed
Management. Revised Edition. Third Edition.
Gadjah Mada University Presss. Yogyakarta.
[5] Radke J.K. and Berry E.C. 1993. Infiltration asa tool for detecting soil changes due tocropping, tillage, and grazing livestock.
American Journal of Alternative Agriculture 8:
164–174.
[6] Mukhtar S., Baker J.L., Horton R. and Erbach
D.C. 1985. Soil water infiltration as affected by
the use of the paraplow. Transaction of ASAE
28: 1811–1816.
[7] Istijono.B. 2006. Watershed Conservation andFarmers Income: Studies on Watershed
Management Integration (Case Study: Sumani
Basin of Solok Regency / Solok City, West
Sumatera). PPs.Unand Dissertation.
[8] Jolliffe I.T. Principal Component Analysis,
Series: Springer Series in Statistics, 2nd ed.,Springer, NY, 2002
[9] Huria Teguh 2014. Prediction of erosion andsedimentation in Upper Kuranji Watershed.
Unand Graduate Tesis.
[10] Foth, H. D. and L. M. Turk.
1988.
Fundamentals of Soil Science. Fifth Edition.

Wiley international Edition. John Wiley andSons, Inc. 454p
[11] Purkait, B. 2010. The Use of Grain Size
Distribution Patterns to Elucidate Aeolian
Processes on a Transverse Dune of Thar Desert,
India. Earth Surface Processes Landforms. 35 :525-530.
[12] Hardjowigeno. 2008. Geology. PT. Mediyatama
Sarana Perkasa. Jakarta. 286 Pages[13] Utomo 2008. Sustainable Dry Land Raw
Material Management. University of Lampung.
Bandar Lampung. 25 pages.
[14] Sarief 2008. Physics-Chemistry AgriculturalLand. Publisher Pustaka Buana. Bandung. 220
pages.
[15] Aprisal, Adrinal dan Wulan Herman. 2017. The
Influence of Rice Husk Biochar Against
Infiltration Capacity on Ultisol. Proceeding of
National Seminar of Land of Suboptimal 2017,
Palembang 19-20 October 2017 “Developmentof Agricultural Science and Technology with
Local Farmers for Optimizing Suboptimal
Land”

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

MICROSTRUCTURE AND MECHANICAL PROPERTIES OF
CONCRETE WITH TREATED RECYCLED CONCRETE
AGGREGATESRichard De Jesus1, Anthony Tang2 and Alvin Cunanan2
1
Assistant Professor, De La Salle University (Manila)
2
Civil Engineering Undergraduate Students, De La Salle University (Manila), Philippines

ABSTRACT
Recycled concrete aggregates (RCA) are sourced from construction demolitions. Weaker concrete, however,often resulted when using RCA as partial or full replacement of coarse aggregates due to the presence of adhered(old) mortar. Several treatment methods for RCA target this old mortar to completely remove it, or enhance its
properties, to make RCA suitable for construction use. Three treatment methods were employed in this study: (1)sulfuric acid (SA), (2) silica fume impregnation (SF), and (3) the combination of both (SASF). Experimental
results showed improvement in the physical properties of RCA compared to untreated RCA, however, statisticaltests showed that these improvements are not significant. SA treatment was found to have a detrimental effect on
the surface of RCA, which developed a weaker layer of adhered mortar on the RCA surface resulting to a reductionin the mechanical strength of the concrete thus, its strength is lower compared to SF-treated RCA concrete. SF
treatment resulted in improved compressive strength in comparison to untreated RCA concrete, SA-treated RCA
concrete, and SASF-treated RCA concrete. It was also observed that 50% RCA replacement in all concrete mixes
with treated RCA resulted to highest obtained compressive strength.
Keywords: Recycled concrete aggregates, RCA treatment, Sulfuric acid, Silica fume, RCA concrete

they showed that cement has to be increased by 6%of cement mass for 50% RCA replacement, and 8.3%
increase for 100% RCA replacement to reach similar
compressive strength compared to normal concrete.
Also, the use of RCA brings about workability issue.
Salesa [6] showed that the workability of RCA
concrete is reduced due to adhered mortar and higher
absorption capacity of RCA.
The use of acid pre-soaking method has been
aimed toward removing adhered mortars. The study[7] used three kinds of acid solution (i.e. hydrochloric
acid, sulfuric acid and phosphoric acid) to treat RCA.
Results showed that the properties of RCA improvedin terms of water absorption, compression, andflexural strength. The rate of disintegration ofadhered mortars depend on the concentration andmolarity of the acid solution. Based on [8] & [9], thechange in molarities of acid solution enhanced thedensity, water absorption, and mechanical strength of
RCA. Akbarnezhad [7], employed various treatment
methods for RCA like mechanical, heating,microwave, and acid-soaking treatment and showedthat the quality of RCA depends on the quantity of theadhered mortars on its surface. Additionally, they
showed that acid-soaking treatment method removed
more adhered mortars than other treatment
approaches. Furthermore, [7] showed that for RCA
treated with weaker acid reduces water absorption
significantly and improved mechanical properties.
Kim [10] combined sulfuric (weak) acid treatment

INTRODUCTION
Raw materials used in producing concrete are notrenewable. Consumption of these raw materials, (e.g.
sand, gravel, and crushed rock) is at the rate of 10 to
11 billion tons per year [1]. Disposing of construction
and demolition wastes brings another environmental
issue as its disposal requires a lot of space. The total
amount of waste generated by construction anddemolition activities in the European Union in 2012
was 821 million tons, and is expected to increase
annually [2]. According to [3], 530 million tons ofconstruction and demolition debris were generated in
the United States in 2013. Since construction anddemolition debris have no reusable components otherthan steel reinforcement, they are often hauled andshipped to landfill.
Over the years, many studies were conducted on
the use of demolition and construction debris forvarious purposes. Several studies have proposed theidea of recycled aggregate concrete (RAC) whereconstruction debris and demolition wastes are used asfull or partial replacement of coarse aggregates in
concrete. However, the use of RCA in concrete often
results to a weaker concrete due to high water
absorption, lower concrete workability, and higher
drying shrinkage [4]. The strength of RAC with 100%
RCA results in a 20% to 25% reduction in strengthcompared to normal concrete and requires morecement to reach comparable strength [5]. Moreover,
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SEE - Nagoya, Japan, Nov.12-14, 2018with abrasion in treating RCA and demonstrated
improved qualities.
Concrete is prone to acid attack, and aggregates
react negatively to silica, thus, researchers devised analternative to treat RCA through silica impregnation.
Katz [11] investigated the use of impregnation ofsilica fume by soaking RCA for 24 hours in silica
fume solution. Results showed that silica fumetreatment resulted in an increase of 23 to 33%, and15%, in the compressive strength at ages 7 and 28
days, respectively. Cakir [12] showed that water
absorption of concrete with RCA treated with silica
fume decreased significantly especially at latter ages.
This effect is more significant in concrete with RCA
using higher amount of silica fume. However,compressive strength decreased with an increase in
the silica fume content in RCA treatment. Huoth [13]used 100% RCA replacement treated with varying
silica fume content of 5%, 10% and 15% and showedcomparable compressive strength results of RAC toconventional concrete.
This study explored three treatment methods for
RCA, namely; weak acid (sulfuric acid) treatment,
condensed silica fume impregnation, and the
combination of both. Moreover, the study
investigated the influence of these methods tophysical properties, in terms of water absorption, bulk
density, and abrasion resistance, and microstructureof RCA. Scanning electron microscopy (SEM) was
employedtoexplorethemicrostructure.
Additionally, the investigation was further extended
to compressive strength of concrete with untreated
and treated RCA, and varying amounts of treated
RCA.

combination of these two treatments (SA-SF
treatment).
Weak Acid Treatment using Sulfuric Acid (SAtreatment)This method of acid treatment was adapted from[7]. The recycled concrete aggregates were soaked in
0.5 molarity of sulfuric acid solution for 24 hours.
The RCA in the acid bath was shaken occasionally toensure efficient removal of bond between adheredmortar and aggregate. After soaking, RCA waswashed to remove acidic solvents. A final soaking inwater for 24 hours was done to ensure that no residue
from acid solvents remains on the aggregates.
Condensed Silica Fume Impregnation Treatment(SF-treatment)This method was adapted from [11], with little
modification, as condensed silica fume was usedinstead of raw silica fume. To create a silica fume
solution, 1 kg of condensed silica was mixed with 10
liters of water. RCA was then soaked in this solution
for 24 hours for silica fume impregnation to occur.
After soaking, the treated RCA was air-dried.
Combined Treatment Method (SA-SF treatment)
Combined treatment involved repetition ofprocedure for acid-soaking sulfuric acid treatment
followed by repetition of silica fume impregnation
method.
Physical and Microstructure Characterization of
RCA

MATERIALS AND METHODS

Several tests were conducted enable to compare
the physical properties and microstructure of treatedand untreated RCA. These tests are relative density(specific gravity) and water absorption as per ASTM
C127 [15], abrasion loss as per ASTM C131 [16],bulk density as per ASTM C29 [17], and surface
microstructure using Scanning Electron Microscopeas per ASTM C295 [18].

Sourcing and Preparation of RCA
RCA used in this study was obtained fromdemolished concrete pavements, which was mainlycomposed of cement mortar and aggregates.
Demolished concrete pavement was then crushed to a
maximum nominal size of 50 mm. The crushedrecycled concrete was then graded using sieve inaccordance to ASTM C136 [14]. Natural coarse andfine aggregates were used for the control concretemix, while parts of coarse aggregates were replaced
by RCA, by volume, in non-control concrete mixes.

Concrete Mix Design and Proportions
Mix design proportions are shown in Table 1.
Due to scarcity of Portland cement locally, this study
used Type 1P cement for all concrete samples. The
proportions used in the design mix was based on ACI
211.1 design mix procedure adopting a water tocement (w/c) ratio of 0.45 for all mixes. Concrete
samples were made with 100%, 75%, 50% and 25%
replacement of RCA by volume of coarse aggregates.

Treatment of RCA
RCA were treated prior to testing of its physicaland, strength properties after it has been incorporated
in concrete. In this study, the three methods oftreatment used were weak acid treatment using
sulfuric acid (SA-treatment), condensed silica fumeimpregnation treatment (SF-treatment), and theCompression Tests of Concrete with RCA

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SEE - Nagoya, Japan, Nov.12-14, 2018

All concrete specimens were made in accordancewith ASTM C192 [19]. Concrete cylinder sample ofsize 100mm x 200mm was used. For each mix type,8 samples were prepared, and cured in water for 7 and
28 days. Compressive strength tests were conducted
as per ASTM C39 [20].

can be observed that small particles were present
which were not observed in Fig 3a and 3b. This canbe attributed to the presence of micro silica that clings
to micro-surfaces around the RCA, thus filling voids
along the surface of the RCA.
Figure 1 shows a cross-sectional image of SAtreated RCA. It can be inferred from this image thatacid treatment created a layer of weakened mortar on
the RCA, implying that farther exposure to acid may
result to complete removal of this layer. Incomplete
removal, on the other hand, resulted to a weakeraggregate mortar interface which leads to weakermechanical strength.

RESULTS AND DISCUSSIONS
Physical Properties of Untreated and Treated
RCA
Bulk Density, Specific Gravity, Water Absorption and
Abrasion Loss

Compressive Strength of Concrete with RCA
Table 2 summarizes the average values both
untreated and treated RCA. Bulk density and specificgravity increased for all treated RCA. Water
absorption and abrasion loss decreased for treated
RCA. Combined treatment (SASF), however,exhibited an increase in water absorption compared tountreated RCAs. Except for bulk density, statistical ttests showed that changes in physical properties oftreated RCA compared to untreated RCA were notsignificant.

Except for concrete with 100% of coarse
aggregates replaced by treated RCA, all other RCA
replacement have higher compressive strength thanthat of concrete with untreated RCA. This wasobserved in both 7-day and 28-day, as seen in Fig. 4
and 5.
Comparison between concrete with RCA under
different treatment method

Surface Microstructure of RCA

For 7-day compressive strength, concrete
samples with SA-treated RCA and SF-treated gained
the higher strength for coarse aggregate replacementof 25% and 50% compared to concrete with SASFtreated RCA. Coarse aggregate replacement higher
than 50% (i.e. 75% and 100%) showed varying
results but samples with SF-treated RCA consistently
got the highest or next to highest compressive
strength.
Concrete with SF-treated RCA also gained thehighest for 28-day compressive strength consistently
for all. Concrete with SASF-treated RCA had thelowest strength except for mix with 75% RCA
replacement.
Comparison between concrete with SA-treated
RCA and with SF-treated RCA revealed that SFtreated RCA concrete had higher mechanical strengthfor both 7-day and 28-day strength. SASA-treated
RCA concrete performed better than SA-treated RCA
concrete in 7-day strength but not in 28-day strength.

Scanning electron microscope (SEM) ofuntreated RCA (Fig. 2a) showed noticeable porous
surface and covered with different impurities andloose crumbs of cement paste. This impurities andloose crumbs of cement paste can be observed betterwith higher magnification (x7500) in Figure 3a.
These observations were consistent with the study of[8] & [7]. SEM of SA-treated RCA shown in Figure
2b exhibited smaller pores and less jagged surface,
represented by dark spots and craggy formations.
Both SF-treated RCA and SASF treated RCA(Figures 2c and 2d) exhibited smoother, less porousand jagged surface.
The surface of the SF-treated, and SASF-treated
RCAs are shown in Figures 2c, and 2d, respectively.
Images showed that the porosity of RCA was reduced
significantly compared to untreated RCA and SAtreated RCA. The surface of SF-treated RCA
compared to SASF-treated RCA appeared with muchlarger irregular crags. Contrary to the effects ofsulfuric acid, which alters the surface topography of
RCA, silica fume coats the surface resulting tosmoother and less cragged surface.
SEM of treated and untreated RCAs with 7500x
magnification are shown in Figure 3. Untreated RCA(Fig. 3a) displayed a rougher surface compared to thatof SA-treated RCA (Fig. 3b) with smoothercrystalline-like structure. However, the surface
structure of the SA-treated RCA appeared moredisconnected, with broken strand formations andparticles around the sample. In Figures 3c and 3d, it

Fig. 1 Cross-sectional surface microstructure of SAtreated RCA
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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1. Mix Design for 1m3 concrete volume
CementFine Aggregates
Type of Mix
(kg)
(kg)
U-RCA
376
948
25SF
376
870
50SF
376
870
75SF
376
870
100SF
376
870
25SA
376
880
50SA
376
880
75SA
376
880
100SA
376
880
25SASF
376
877
50SASF
376
877
75SASF
376
877
100SASF
376
877

Water (kg)
169
169
169
169
169
169
169
169
169
169
169
169
169

Coarseaggregates (kg)
0
1167
779
389
0
1168
779
389
0
1171
781
390
0

RCA
(kg)
948
258
515
773
1030
255
510
765
1020
256
512
767
1023

SA-treated
1229
2.37
7.0
27

SASF-treated
1234
2.33
9.6
27

Table 2. Average physical properties of untreated and treated RCAs
RCA Physical Properties
Bulk density (kg/m3)
Specific gravity (SSD)
Water absorption (%)
Abrasion loss (%)

Untreated
1142
2.31
7.7
29

SF-treated
1223
2.41
6.6
27

Effects of varying amounts of RCA replacement

Compressive strength for 28-day showed moreconsistency with respect to trend in strength gain andloss (Fig. 4 & 5) than 7-day. SA-treated RCA
concrete, and SF-treated RCA concrete, both showed
increasing strength from 25% to 50% RCA
replacement then followed by decrease in strength for
75% up to 100% RCA replacement. For SASFtreated concrete, however, the strength increase wasobserved up to 75% RCA replacement then decrease
thereafter. This observation was similar to that of
SASF-treated concrete for 7-day strength.

For 7-day compressive strength, an increase wasobserved for SA-treated RCA concrete for 25% and
50% replacement while SF-treated RCA concrete did
not exhibit any strength increase until replacement
reached 75%. Concrete with SASF-treated RCA
exhibited rising strength pattern from 25% to 75%
RCA replacement then drop at 100% replacement.
SA-treated RCA concrete and SF-treated RCA
concrete exhibited a decrease in strength for morethan 50% RCA replacement.

Fig. 3 Surface microstructure of treated and untreated
RCA at 7500x magnification (a: Untreated RCA, b:
SA-treated, c: SF-treated, d: SASF treated)

Fig. 2 Surface microstructure of treated and untreated
RCA at 750x magnification (a: Untreated RCA, b: SAtreated, c: SF-treated, d: SASF treated)

314

20.0

Sulfuric
Acid
TreatedSilica fume
Treated

15.0
10.0
5.0

Compressive Strength, MPa

Compressive Strength, MPa

SEE - Nagoya, Japan, Nov.12-14, 2018

Combinati
on Treated

0.0
100%
RCA

75%
RCA

50%
RCA

25%
RCA

Untreated

RCA content

30.0
25.0
20.0
15.0
10.0
5.0
0.0

Sulfuric Acid
TreatedSilica fume
Treated
Combination
Treated
Untreated

100%
RCA

75%
RCA

50%
RCA

25%
RCA

RCA Content

Fig. 4. 7-day compressive strength of concrete withtreated and untreated RCA

Fig 5. 28-day compressive strength of concrete withtreated and untreated RCA

CONCLUSIONS[2] EU Waste statistics, 2015, Retrieved October 08,
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[6] Salesa, A., Perez-Denedicto, J. A., ColoradoAranguren, D., Lopez-Julian, P. L., Esteban, L.
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Determining the Mortar Content of Recycled
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There is a slight improvement on the physicalproperties, such as bulk density, water absorption,
abrasion loss and specific gravity, of RCA treated bysulfuric acid (SA), silica fume impregnation (SF), andthe combination of both (SASF). However, statisticalt-test showed that these improvements were notsignificant.
The microstructure surface of SA-treated RCA
was cleaner and free from loose particles compared tothe untreated RCA. However, the remaining adheredmortar on RCA that the sulfuric acid failed topenetrate became weak and affected the mechanicalstrength of concrete with SA-treated RCA. Thus,
compared to SF-treated RCA concrete, SA-treated
RCA concrete had lower mechanical strength.
The microstructure surface of the SF-RCA tends
to be smoother than the untreated RCA and SAtreated RCA validating the claim that silica fumeparticles occupy void spaces of RCA resulting tosmoothening of the rough microstructure surface of
RCA.
Treated RCA produced concrete with higher
compressive strength compared to concrete withuntreated RCA. Combination of SA and SF
treatments do not result in better strength compared
to concrete with RCA employing separate treatment.
While increase in percentage replacement
decreases compressive strength of RCA concrete, it
was observed that with treated RCA, the decrease instrength occurred at replacements higher than 50%.
Based on results, SF-treatment is the more effective
method of treating RCA.
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[13] Huoth, P., Suntharavadivel, T.G., and Duan, K.,
Effect of silica fume on recycled aggregate
concrete, Australasian Conference on the
Mechanics of Structures and Materials(ACMSM23), Vol. I, 2014, pp. 249-254, ISBN:9780994152008.
[14] ASTM C136, Standard Test Method for Sieve
Analysis of Fine and Coarse Aggregates andGrading, ASTM International, Conshohocken,
PA, 2016, www.astm.org.

[15] ASTM 27, Standard Test Method for Relative
Density and Absorption of Coarse Aggregates,
ASTM International, Conshohocken, PA, 2016,www.astm.org.
[16] ASTM C131, Standard Test Method for
Resistance to Degradation of small-size Coarse
Aggregate by Abrasion and Impact in the Los
Angeles Machine, ASTM International,
Conshohocken, PA, 2016, www.astm.org.
[17] ASTM 29, Standard Test Method for Bulk
Density and Voids in Aggregates, ASTM
International, Conshohocken, PA, 2016,www.astm.org.
[18] ASTM 295, Standard Guide for Petrographic
Examination of Aggregates for Concrete, ASTM
International, Conshohocken, PA, 2016,www.astm.org.
[19] ASTM C192, Standard Practice for Making andCuring of Concrete Test Specimens in the
Laboratory, ASTM International, Conshohocken
PA, 2016, www.astm.org.
[20] ASTM C39, Standard Testing Method forCompressive Strength of Cylindrical Concrete
Specimens, ASTM International, Conshohocken
PA, 2016, www.astm.org.

316

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

A COMPARATIVE STUDY ON VIBRATION SIGNALS OF A
MOTORCYCLE AT VARIOUS POSITIONSSuphattharachai Chomphan
Faculty of Engineering at Sriracha, Kasetsart University, Thailand

ABSTRACTThe motorcycle is becoming popular in the present days because of their swiftness and conveniences in thecrowded cities. It is considered the most popular choice in various aspects of transportation in the urban area. Whenstarting and accelerating the engine, it has been found that there was a vibration throughout all parts of the
motorcycle. If the driver perceives more vibration, he will feel more uncomfortable. Consequently, the researcher
conducted a study of the vibration signal sent through four core points which are the contacts between driver or
rider and the motorcycle body including motorcycle left hand, seat, left front footrest, and left rear footrest. The
specimen motorcycle in this research is Honda Wave 100s model. The comparison results have been performedby using two parameters of averaged peak and averaged energy of the vibrational signal. The results reveal thatthe left front footrest has the highest vibration level in both parameters, while the seat has the lowest vibrationlevel. All in all, it can be concluded that the mechanical structure of the motorcycle must be developed byconsidering the engine’s vibration sent through all parts especially the position of front footrest which has thehighest impact in order to increase the driver’s comfort.
Keywords: Engine vibration, Vibration signal, Averaged peak of vibration signal, Averaged energy of vibration
signalINTRODUCTION

to measure the vibration transmitted from its engine.
The engine is set to run at five different speeds of
2,000 rpm, 2,500 rpm, 3,000 rpm, 3,500 rpm and
4,000 rpm. The measurement of vibration signals has
been using an accelerometer passing through its
corresponding base station. Subsequently, themeasured signals are analyzed using some selectedsignal processing techniques. Two main parametersof averaged peak and averaged energy of thevibrational signal are calculated and discussed
afterward.

Nowadays, motorcycles play an important role in
the transportation in the modern and crowed towns
especially in the capital cities. Their swiftness andeconomical cost make a number of people turn to usethem more and more. One of the reasons to choose a
motorcycle of motorcyclist and stackers is its
convenience. The feelings of users to the motorcycle
seat, hands, and footrests are significant factors thatcannot be ignored. These interface positions areaffected from the vibrations of its engine and adjacentenvironments [1, 2].
Motorcycle vibration mainly occurs when theengine starts. The acceleration of the engine
reinforces the additional vibration to the motorcycle
body. The analysis of the vibration signal has beendeveloped for years in many fields of studies.
Distinguishing signal components and its major
attributions can be accurately accomplished.
Therefore, the concept of signal analysis technique isapplied to analyze the vibration of motorcycle atvarious positions in this paper [3, 4].
In the experiments, the HONDA WAVE 100s is
selected as an instance because of its popularity in
Thailand. The positions of left hand, seat cushion, left
front footrest, and left rear footrest are the four targets

BACKGROUNDThis section introduces some basic related
information of engine vibration, and corresponding
parameters used to indicate the condition of themachine.

Engine Vibration
Vibration is the phenomenon of moving back andforth of an object under force. The engine vibrations
are an integral sum of every mechanically moving
component on the motorcycle body [5-7]. These
vibrations in motorcycle engines are a result of
periodic and aperiodic oscillations caused about an

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SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

EXPERIMENTAL PROCEDURE

equilibrium point. These things are not wanted;
however, it cannot be avoided. Therefore, theappropriate thing to do is to limit the size of thesevibrations. The core amplitudes and frequencies ofthe vibration signals should be adequately andproperly analyzed.

Database of motorcycle
vibrations at various
positionsAveraged Power of Vibration Signal
The power of signal is defined as the amount ofenergy consumed per unit time. The signal attribute isvery meaningful to present the energy of the signal ina period of time. The energy of the engine-runningvibration signal often goes to infinity; in other words,
it can be assumed to be not-squarely-summable aslong as the engine does not stop running. The
calculation of power of signal is defined by using thesum of square of the signal samples [8, 9].
Mathematically, the averaged power of an aperiodic
sequence x[n] is defined as the following equation.
𝑃𝑥 = lim

1

𝐾→∞ 2𝐾+1

2∑𝐾
𝑛=−𝐾 |𝑥[𝑛]| ,Vibration atleft handVibration atseat

Vibration atleft front
footrest

Vibration atleft rearfootrest

Extraction of vibration’s
attributes

Analysis of vibration’s
attributes(1)

Conclusions

where K is the sequence half length which
extends its limit of number of samples to infinity.

Fig. 2Averaged Peak of Vibration Signal

Experimental Procedure.

The experimental procedure has been conducted
as depicted in Fig.2. The database of motorcycle
vibrations at various positions are implemented.
Subsequently, the distinction of motorcycle
vibrations at all four points is conducted. Thereafter,
the extraction of vibration’s attributes of averaged
power of vibration signal and averaged peak ofvibration signal as mentioned in the previous section
has been performed. An analysis of these vibration’s
attributes has been done comparatively. Finally theconclusions has been summarized.

In addition to the power of engine vibration signal
is described in the previous section. The averaged
peak of signal is defined as the averaging amountcalculated from a number of peak values of periodic
or semi-periodic signals existing in a unit of time.
Since the engine vibration is characterized as semiperiodic signal as depicted in Fig.1, the averaged peakof signal is selected in this study. This attribute is
calculated to compare with power of engine vibration
signal for all experimental conditions.

1

2

4

3
Fig. 1

Fig. 3

Experimental allocation of accelerometers
over the specimen motorcycle; (1) left hand,(2) seat, (3) left front footrest, and (4) left
rear footrest.
The specimen motorcycle in the experiment is

An example of motorcycle engine vibration
signal with semi-periodic waveform.

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SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

Honda Wave 100s model. The accelerometers areattached at four core points which are the contact
points between driver or rider and the motorcycle
body including motorcycle left hand, seat, left front
footrest, and left rear footrest as depicted in Fig.3.
These engine vibration signals are measured in theform of acceleration by these accelerometers andrecorded by the G-link microstrain serial base station
through a host computer. The vibration signal is in theform of an approximate periodic sequence which isassumed to be a power signal with a finite average
power [9-11]. Therefore, this equation has been
adapted with a specific length recorded in 10 iteration
samples for all five various levels of engine speeds of
2,000, 2,500, 3,000, 3,500, and 4,000 rpm,
respectively. The duration of each sample lasts 10
seconds at the sampling rate of 2,048 Hz.
From the measured values of vibration signals, theroot sum square of the accelerations of all three
directions is calculated. The equally-divided sectionsof the root sum square values are therefore provided
for all experiments. Subsequently, the extraction ofvibration’s attributes of averaged power of vibration
signal and averaged peak of vibration signal asmentioned earlier has been performed.
EXPERIMENTAL RESULTS
In the preliminary stage, the experimental resultsof the values of vibration signals is obtained from theaccelerometer measurement. A number of portions ofmotorcycle engine vibration signals at its left handwith the engine speed of 2,000 rpm are presented in
Fig.4. All experimental graphs insist the semiperiodicity which reflects from the working periodic
cycle of ignition inside the engine and thecorresponding effects of surrounding environments.
From these values of vibration signals, thevibration’s attributes of averaged power of vibration
signal and averaged peak of vibration signal are
extracted and plotted in comparative way withdifferent engine speeds as depicted in Figs. 5 and 6.
It can be seen from Figs. 5 and 6 that when theengine speed is increased, the averaged power ofvibration signal and averaged peak of vibration signal
are in upward trends for nearly most of the positionsof the accelerometers. When comparing among thepositions, both of the vibration’s attributes of the seat
are mostly lowest, meanwhile those of the left front
footrest are at the highest levels. Moreover, at thehigh engine speeds from 3000-4000 rpm, the second
highest is of that of left rear footrest, subsequently,
the third highest is of that of left hand.

Fig. 4319

Some examples of motorcycle engine
vibration signals at left hand with the engine
speed of 2,000 rpm.

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

Fig. 5This paper has studied the vibration of a
motorcycle at four different parts where the driver or
rider exposes to the motorcycle. This vibration has
been transferred from the working engine and all
surrounding environments. In this experiment, a
study of the vibration signal sent through four core
points has been performed. These points are thecontacts between driver or rider and the body of thespecimen motorcycle body including motorcycle left
hand, seat, left front footrest, and left rear footrest.
The selected motorcycle which is used in thisexperiment is Honda Wave 100s model. Calculationof two parameters of averaged peak and averagedenergy of the vibrational signal has been conducted in
a comparison way. The experimental results showedthat when the engine speed is increased, the averaged
power of vibration signal and averaged peak ofvibration signal are in upward trends for nearly mostof the positions of the accelerometers. By comparing
among all positions, both of the attributes of the seat
are mostly in the lowest levels, meanwhile those of
the left front footrest are at the highest levels. In
conclusion, it is obviously summarized that themechanical structure of the motorcycle should be
developed by considering the engine’s vibration sent
through all parts in order to improve the comfort forthe driver and rider.

Comparison of averaged peak of vibration
signal for four core contacting points
including motorcycle left hand, seat, left
front footrest, and left rear footrest at fivedifferent engine speeds from 2000-4000rpm.

ACKNOWLEDGEMENTS

Fig. 6

The research was partly sponsored by the Facultyof Engineering at Sriracha’s Fund. In addition, theauthor would like to express the gratitude to Mr.
Thapakorn Pankaew for some related experimental
data.

Comparison of averaged power of vibration
signal for four core contacting points
including motorcycle left hand, seat, left
front footrest, and left rear footrest at fivedifferent engine speeds from 2000-4000rpm.

REFERENCES[1] Yujun L., Peter W. T., Xin Y., Jianguo Y., EMDbased fault diagnosis for abnormal clearance
between contacting components in a diesel
engine, Mechanical Systems and Signal
Processing, Vol. 24, Issue 1, 2010, pp.193–210.
[2] Xia W., Changwen L., Fengrong B., Xiaoyang
B., Kang S., Fault diagnosis of diesel engine
based on adaptive wavelet packets and EEMDfractal dimension. Mechanical Systems andSignal Processing, Vol. 41, Issue 1-2, 2013, pp.
581–597.
[3] Binqiang C., Zhousuo Z., Chuang S., Bing L.,
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Systems and Signal Processing, Vol. 33, Issue 11,2012, pp. 275–298.

As for at the lower engine speeds from 2000-2500
rpm, the lowest is of that of left rear footrest, then thesecond lowest is of that of seat. It was obviously
observed that both of the attributes of left front footare at the highest levels. The core reason is that thisposition is closest to the motorcycle engine. The
vibration is sent directly through the body structure of
motorcycle with the shortest distance. On the other
hand, the attributes of the seat position are mostly
minimal. A concrete reason is that it is in furthest
distance from the engine. Moreover, a supporting
reason is that the sponge stuffed within the seat serves
as a vibration absorber.
CONCLUSIONS

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SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

spectrum and neural network analyses for
induction motor fault diagnosis. Mechanical
Systems and Signal Processing, Vol. 39, Issue 12, 2013, pp. 342–360.
[9] Akhand R., Upadhyay S. H., A review on signal
processing techniques utilized in the fault
diagnosis of rolling element bearings, Tribology
International, Vol. 96, Issue 4, 2016, pp. 289-306.
[10] Chomphan S., Chaimanatsakun A., Sakornsin R.,
Khumneungratavongsa S., Rattanarat K., A
Comparative Study of LPG-modified Engine andNormal Oil-usage Engine. in Proc. Int. Conf. On
Engineering and Applied Sciences, 2016, pp.
219-225.
[11] Carlucci A. P., Chiara F. F., Laforgia D.,
Analysis of the relation between injection
parameter variation and block vibration of aninternal combustion diesel engine. Journal ofSound and Vibration, Vol. 295, Issues 1–2, 2006,
pp. 141–164[4] Ahmad T. A., Barat G., Teymour T. H., Seyed
S.M., Vibration analysis of a diesel engine using
biodiesel and petro diesel fuel blends, Fuel, Vol.
102, Issue 12, 2012, pp. 414–422.
[5] Zunmin G, Jin C., Barry H., Analysis of engine
vibration and design of an applicable diagnosing
approach. International Journal of Mechanical
Sciences, Vol. 45, Issue 8, 2003, pp. 1391–1410.
[6] Xianhua L., Randall R. B., Jerome A., Blindseparation of internal combustion engine
vibration signals by a deflation method.
Mechanical Systems and Signal Processing, Vol.
22, Issue 5, 2008, pp.1082–1091.
[7] Xianhua L., Randall R. B., Blind source
separation of internal combustion engine pistonslap from other measured vibration signals.
Mechanical Systems and Signal Processing, Vol.
19, Issue 6, 2005, pp. 1196–1208.
[8] Liang B., Iwnicki S. D., Zhao Y., Application of
power spectrum, cepstrum, higher order321

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

FREQUENCY ANALYSIS OF THE ENGINE SUPPORT VIBRATIONWITH HYDROGEN-DIESEL DUAL-FUELING
Boonthum Wongchai, Poranat Visuwan, Sathaporn Chuepeng
Department of Mechanical Engineering, Faculty of Engineering at Sriracha,
Kasetsart University, 199, Sukhumvit Rd., Thungsukhla, Sriracha, Chonburi, 20230, Thailand

ABSTRACTIn the present days, diesel engines are mainly used in the transportation and the logistic systems. Hydrogen isused as an alternative energy in diesel engine called hydrogen-diesel dual fuel for saving diesel fuel and protecting
environment. Hydrogen adding affects diesel engine vibration and car seat vibration. This article presents the effectof hydrogen flow rate on the spectrum of the vibration of the engine support. The four stroke single cylinder diesel
engine is tested with hydrogen-diesel dual fuel by varying hydrogen flow rate. The vibration of the engine support
is measured at two constant speeds with three different loads. The fast Fourier transform of the engine support
vibration are calculated to analyze the vibration signals at the resonance frequency of the car seat vibration. The
fast Fourier transform spectrums in the experimental results show that the average peak acceleration of the first
three engine frequencies around 0 to 70 Hz tend to decrease by adding the hydrogen flow rate. The engine support
vibration and the car seat vibration at this frequency range can be reduced by adding the hydrogen flowrate.
Keywords: Hydrogen-diesel dual fuel, Fast Fourier transform, Frequency analysis, Vibration

INTRODUCTION

computed fromDiesel engines are nowadays widely used in
vehicles and stationary applications. Manny
researchers study effect of hydrogen addition ondiesel engine performance and pollution [1-5].
Hydrogen is sustainable, renewable, and carbon freeand can be produced from various procedures such as
waterelectrolysis,
steam
reforming,
anddehydrogenation of organic chemical hydrides.
Carbon and hydrocarbon emission can be reduced byadding hydrogen in a diesel engine. For the thermal
efficiency, hydrogen-diesel dual fuel operation showshigher thermal efficiency than a conventional diesel
operation at condition of relatively high engine load[6]. Adding of hydrogen affects cylinder pressure,noise, and also vibration of a diesel engine. Nguyen
and Mikami [7] studied the effect of hydrogen
addition to intake air on combustion noise. The results
showed that the combustion noise at late diesel fuelinjection greatly decreased by hydrogen addition of
10 vol% while the mean effective pressure wasalmost the same with or without hydrogen addition.
Uludamar et al. [8] reported that the Hydroxyl (themixture of hydrogen and oxygen gases) addition withdiesel-biodiesel blends decrease the engine vibration.
Engine block vibration is produced by thecylinder pressure. Pressure force pushes a piston andtransmits through connecting rod, crankshaft, engine
support and other components. For four stroke diesel
engine, diesel oil is injected and fires one time per two
revolutions of the crankshaft. The first main harmonicfrequency of an engine with i cylinders can be

N = 120 f / i ,(1)where N is the engine speed in RPM and f is thefirst main harmonic frequency in Hz [9]. Frequency
analysis are mainly used to analyze an engine
vibration and acoustic emission such as root meansquare value (RMS), fast Fourier transform (FFT),
power spectrum density (PSD), and short-time
Fourier transform (STFT) [10-13]. The FFT shows anamplitude of an engine vibration at any frequencies
and PSD is the power of FFT. The STFT is used toanalyze transient vibration signals such as valve
impact, injector-pulses, and prompt initial knock
detection. Taghizadeh-Alisaraei et al. [14-16] used
FFT and STFT to analyze the vibration of thecompression ignition engine (CI) with biodieseldiesel fuel blends and ethanol-diesel fuel blends. For
biodiesel-diesel fuel blends, the results showed that
D100 and B80 had lowest vibration and STFT can beused for the real-time knock detection and injection
control. In addition, the FFT, and STFT are used inengine noise and vibration analysis [17-19].
Engine support vibration can be separated into the
responses of excitation force and torque. The force atthe engine support has two components inlongitudinal and lateral direction of the piston travel.
The vibration at an engine support transmits
throughout the other car components and finally reachto car seats. The vertical and horizontal vibration of
the car seats causes of driver and passengers
discomfort with low resonance frequencies [20-21].
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SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

Qiu and Griffin [22] reported that the resonancefrequencies of the fore-aft vibration of the seat pan
and the backrest are below 50 Hz.
In this study, the engine support vibration of thehydrogen-diesel dual fuel engine with the variation ofhydrogen flow rate injected into the engine intake
port are investigated and discussed at two constant
speeds with three different loads. The FFT is used toanalyze the vibration signals. The obtained results
will be beneficial for vibration diagnostics ofhydrogen-diesel dual fuel engines.

The engine support acceleration data are stored
in on-board flash memory of G-Link accelerometerwith sampling rate of 2,048 samples per second andare transferred to computer after the tests arecompleted. G-Link accelerometers are controlled by
Node Commander software through WADA basestation. The accelerometer specification are listed inTable 2.

MATERIALS AND METHOD
Test engine and vibration measurement
The horizontal single cylinder Kubota RT100
Plus direct injection diesel engine as shown in Fig.1
is used in this study. The piston moves along x
direction with the connecting rod and the crankshaft
move on x-z plane. The engine is supported by four
springs. The specifications of the engine are listed inTable 1.

Fig. 2 Accelerometer
support (bottom view).

atengineTable 2 Accelerometer specification

Table 1 Engine specification
Model
Number ofcylinderBore × stroke
Cycle
Compression ratio
Maximum power
Maximum torque
Injection timing

installations

Instrumentation
G-LinkKubota RT100 plus
1
88 mm × 90 mm
4-stroke, water cooled
18:1
7.4 kW at 2,400 rpm
33.4 Nm at 1,600 rpm
Variable; 20 to 45 degrees
BTDC

WADA basestationCharacteristics
Sample rate: 2,048
samples per channel per
secondMeasuring acceleration:
X, Y and Z axes
Range: ±2 g or ±10 g
On-board flash memory:
2 MB
Power: USB
Frequency: 2.405 GHz
to 2.480 GHz

Experimental test program
The hydrogen-diesel dual fuel is use in this study.
Hydrogen is injected through the flow meter andmixes with air at the manifold with pressure at 1 bar.
Hydrogen-air mixture flow into the cylinder during
the intake stroke and the main diesel fuel is injected
before the piston reaching to TDC during thecompression stroke. The hydrogen volume flow rate
is varied at five levels of 0, 5, 10, 15 and 20 lpm withthe engine speed (N) and the engine load (T) are
shown in Table 3. The controlled engine loads are inpercentages of the maximum engine torque as
described in Table 1. The engine has been set to reacha steady state prior to collecting all data. The engine
base accelerations are acquired 100,000 data withsampling rate 2,048 samples per second.

Fig. 1 Test engine and accelerometer installations
at engine support (front view).
Five G-Link wireless triaxial accelerometers are
installed at the bottom of the engine support using hot
glue as shown in Figs. 1 and 2.
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SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

Fig. 30 to 70 Hz spectrum of the total acceleration at position 5; N = 1,600 rpm, T = 25%.

Fig. 40 to 70 Hz spectrum of the total acceleration at position 5; N = 2,000 rpm, T = 25%.

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SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

because the engine is the vibration source and addedhydrogen directly affects the engine vibration. For the
APA at positions 1 to 4, the results similar to the APAat position 5.

Table 3 Engine parameter
Test program1
2
3
4

N (rpm)
1,600
1,600
2,000
2,000

T (%)
15
25
25
50

All data are saved in cvs file format. After using
FFT, the vibration signals in frequency domain can beanalyzed in the frequency range from 0 to 1,024 Hz.
However, for the engine support vibration, thisfrequency range can be used.
RESULT AND DISCUSSION
For four stroke single piston diesel engine, theengine vibration is generated by the combustion of
the mixture vapor one time per two revolutions .The
engine frequency f in Hz can be calculated from
f = N / (120) and the harmonic frequencies aren × f where n are 1, 2, 3, 4, etc .The four stroke
engine with speed of 1600 rpm has the engine
frequencies of 13.33, 26.67, 53.33 Hz, etc .For theengine speed of 2,000 rpm, the engine frequencies are
16.67, 33.33, 66.67 Hz, etc.
Frequency analysis is used to analyze thevibration data from the accelerometers. Figures 3 to 4
show the FFT of the total acceleration of the engine
support at position 5 with the engine speed of 1,600
and 2,000 rpm at 25% engine load. The total
acceleration can be computed froma=ax2 + a y2 + az2 ,Fig. 5 Average peak of the total acceleration of thefirst three engine frequencies; N = 1,600 rpm.

(2)
Fig. 6 Average peak of the total acceleration of thefirst three engine frequencies; N = 2,000 rpm.

where ax, ay, and az are the acceleration in x, y,
and z axes.
The first three dominant engine frequencies
around 0 to 70 Hz affect resonance frequencies of the
car seat and cause discomfort of driver andpassengers. The average amplitude of the first three
engine frequencies around 0 to 70 Hz is define as theaverage peak acceleration (APA) and can becomputed from
APA = (APAf1 + APAf2 + APAf3)/3,

CONCLUSION
This paper present a frequency analysis of engine
support vibration, the hydrogen-diesel dual fuelengine is tested by varying hydrogen flow rate. The
vibration of the engine support is measured at two
different speeds and three different loads.
The FFT is used to analyze the signals of theengine support vibration at the resonance frequenciesof the car seat vibration. From the FFT spectrum, theadded hydrogen flow rate reduces the average peakacceleration of the first three engine frequency around
0 to 70 Hz. For this frequency range, the engine
support vibration and the car seat vibration can be
reduced by increasing the hydrogen flow rate.

(3)

where APAf1, APAf2, and APAf3 are theamplitudes at the first, the second, and the third
harmonic frequency of the engine vibration.
Figs. 5 and 6 show that the APA tend to reduce byincreasing the hydrogen flow rate. In addition, there
are other frequencies generated by other components
occur around 0 to 70 Hz. However, the present study
interests to discuss only the effect of added hydrogenon the vibration amplitude at the engine frequencies

ACKNOWLEDGMENTS
The study was conducted at Kasetsart University
Sritacha Campus. The authors would like to thank the325

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

Kasetsart University Research and Development
Institute (KURDI) for the provision of the research
grant to this project under the contract number VT(D)173.53. The Kasetsart University Center for
Advanced Studies in Industrial Technology under the
National Research University (NRU) project is also
acknowledged for the support to this study.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

ASSESSMENT OF OUT-OF-PLANE FAILURE OF NON-ENGINEEREDMASONRY WALL DUE TO TYPHOON HAIYAN-INDUCED STORMSURGES
Jenes P. Borais1, and Richard De Jesus2
Graduate Student, De La Salle University, Philippines;
2
Assistant Professor, De La Salle University, Philippines,
1

ABSTRACT
Typhoon Haiyan, in 2013, caused massive destruction central Visayan region in the Philippines. Failure(collapsed) of non-engineered masonry walls were the most common failure experienced by residential structuresin the area. This exposed the high vulnerability of non-engineered masonry walls of residential structures in rural
areas, against extreme events. Existing building codes for large reinforced concrete frame structures had performed
well, however, the masonry walls of low-rise structures along coastal areas have high vulnerability to out-of-plane
failures due to poor construction methodology and insufficient design considerations. On-site survey along thecoastal barangays of Tacloban City was conducted to determine the method of construction and design
consideration for masonry walls. The structural investigation utilized finite element modelling (elastic) and yieldline method (plastic). The estimated maximum pressure capacity using yield line method for the non-engineered
masonry walls and National Structural Code of the Philippines (NSCP 2015)/ACI 530-02 compliant design was
found to be inadequate. Thus, improved design was proposed and assessed against similar loads with consideration
about the cost and suitability for the local worker’s skills and techniques. Improvements in design includes
modification in spacing and size of steel reinforcements, increased in concrete hollow block thickness, andmodification on masonry wall dimensions. Based on the analytical results, it is concluded that the maximum
pressure capacity of the improved masonry design increased significantly by 2 to 3 times compared to the current
non-engineered masonry design. The new standard design could be used for new construction with potential
disaster risk reduction against out-of-plane collapse.
Keywords Storm surge, typhoon Haiyan, out-of-plane failure, masonry walls

non-engineered structures in coastal areas in
Tacloban City, Leyte. Structures had collapsed due tostrong winds, and extreme storm surge resulting toinjuries and casualties. Most of this structures are notdesigned to resist lateral forces caused by storm
surges. Non-engineered masonry walls are vulnerable
to out-of-plane failure since they are not designed tocarry lateral pressure. This type of structural failure
can lead to major injuries and even death to theoccupants. This natural catastrophic event motivated
the researcher to investigate the safety of the masonrywalls. An on-site survey was conducted to identified
the current construction method of the masonry wallsof low-rise residential/commercial structures along
the coastal barangays. Tacloban City was chosen forseveral reasons. First, it has the most number ofdamaged houses and number of casualties after thetyphoon. Second, there was a lack of measures forrisk reduction for coastal structures in Tacloban City.
Third, the strength of Typhoon Haiyan exceeded thescale of estimations of storm surge and hazard zones
and left tremendous devastation behind.
The survey objectives were to identify the methodof construction, material used, and the design process

INTRODUCTION
Super Typhoon Haiyan made landfall on the 7th
day of November, 2013 with estimated wind speeds
up to 314km/hr. in the Philippines and then five otherareas, including southern China and Vietnam.
However, the Philippines was one of the worst
affected. The typhoon caused excessive rainfall,landslides and flash floods throughout the region thatcaused casualties. The main cause of death is due todrowning, mainly caused by extreme storm surge.
Storm surge is caused by irregular rise of ocean water
caused by tropical cyclones. Rise in sea water levelis caused by high winds that push on the ocean’ssurface and the low pressure at the center of a storm
system [1].
The aftermath of the typhoon has recorded morethan 6,300 deaths, 28,688 injured and 1,062 are still
missing. [2]. Based on NDRRMC records, it is ranked
No.1 among the top 10 worst typhoons in terms ofdamage to properties amounting to Php 93B(infrastructure, production, social and cross-sectoral)[2]. Several structures had been severely damaged in
the path of Typhoon Haiyan more particularly to the328

SEE - Nagoya, Japan, Nov.12-14, 2018of the non-engineered masonry walls in order tounderstand the coastal damage condition and futurerisk assessments. Structural investigation was
performed using finite element modelling and yieldline method. A standard design for masonry walls wasestablished.

Around 58% out of the 380 houses surveyed arewithin the 40meter No Build Zone implemented by
the local government of Tacloban City. Almost 69%
of the houses within the No Build Zone areas are
single storey houses and the remaining 31% has thecapabilities to move on higher grounds since theirhouses were two storey structures. On the other hand,
65% of the total houses within 40-100metermeterfrom shoreline are considered as single storey
structures and the remaining 35% are two storey
structures.

INTERVIEW SURVEY
Based on the damage assessment of Tacloban
City after the Typhoon Haiyan, barangays along thecoastal areas were identified. On-site interview
survey was conducted on these areas to determine thenecessary information needed to assess the OOP
failure of masonry walls.

Figure 3: Number of houses within/beyond the No
Build Zone in the coastal areas of Tacloban City.
(survey conducted March, 2018)
CURRENT CONSTRUCTION METHOD AND
STRUCTURAL DETAILS
Based on the survey of the housing structures in
the coastal area, a typical house, named House E
shown in Fig. 4, is selected for investigating thecurrent construction method and structural details ofmasonry walls. House E is a 2 stories non-engineered
RC framed with masonry wall structure and isconstructed 2 years ago. The non-engineered designfor masonry walls was 10cm thick CHB, 10mmØ
(horizontal) every 4th CHB layer, 10mmØ (vertical)
every 80cm OC and partially grouted. These design
was based on the on-site survey conducted.

Figure 1: (a) On-site survey areas in coastal barangays
in Tacloban City, (b) Percentage of totally/partiallydamaged houses.
A total of 380 low-rise residential/commercial
houses were interviewed. This houses are locatedmostly at Brgy. 36, 37, 66, 67, 68, 69 and 70 in
Anibong, at Brgy. 30, 48-B, 52, 54, 58 and 60-A
along Esperas Avenue and Real St., at Brgy. 83 and85 at San Jose (see Fig. 1).
Almost 84% of the 380 houses were built without
the proper supervision of a licensed civil engineer or
professional architect (see Fig. 2). Since coastal areas
are the most vulnerable to high storm surges, around
79% of the houses surveyed were categorized as
totally damaged after Typhoon Haiyan (see Fig. 2).
The number of houses that were considered as totally
damaged is directly proportional to the number ofhouses that are totally flooded (see Fig. 1).

Figure 4: Actual photos of House E in Tacloban City.
ESTIMATION OF STORM SURGE PRESSURE
To estimate the pressure load imposed by thestorm surge during Typhoon Haiyan, different floodloads were calculated. Different flood loads includehydrostatic load, breaking wave load, hydrodynamic
load and debris impact load. A typical time series of
the complex combination of storm surge pressureloads is illustrated in Fig. 5. In this figure, a dashedline represents the actual capacity of the structure.
There is a decrease in capacity that can be attributed

Figure 2: (a)Percentage of houses per designer, (b)Percentage of totally/partially damaged houses after
Typhoon Haiyan (2013).
329

SEE - Nagoya, Japan, Nov.12-14, 2018

to the buoyancy force reducing the resistance of thestructure to global failure. In this research, it wasdifficult to calculate the exact pressure load on themasonry walls as a function of time, thus, theresearcher determined the estimated pressure ranges
or the possible minimum and maximum values ofpressure load.

surface area of obstruction normal to flow. Based on
the observed maximum velocity of floodwater in
Tacloban City, flow velocity ranges from 0.60 to 0.80m/s [4]. When the floodwater is in motion around thestructure, the hydrostatic condition no longer exists.
However, the deviation caused by the initial flow offloodwaters is mainly small in comparison with thehydrostatic state. Considering the range of observed
flow velocity, the estimated hydrodynamic pressure
ranges from 16.19 to 19.49 kPa.
Theoretically, debris impact forces can beevaluated with impulse-momentum principle. The
impact force when waterborne debris can be a causeof building damage. This can be estimated using Eq.
(4).
𝑭𝒊 = 𝟏. 𝟑 𝒖𝒎𝒂𝒙 √𝒌𝒎𝒅 (𝟏 + 𝒄)

where 𝑭𝒊 is the impact force, 1.3 is the importancecoefficient for Risk Category IV structures that is
specified by ASCE 7 Chapter 5 for debris impact,𝒖𝒎𝒂𝒙 is the maximum flow velocity carrying thedebris at the site ( the debris is conservatively
assumed to be moving at the same speed as the flow),
c is the hydrodynamic mass coefficient which
represents the effect of fluid in motion with thedebris, k is the effective net combined stiffness of the
impacting debris and the impacted structural elements
deformed by the impact, 𝒎𝒅 is the mass of the debris.
Based on the local condition of Tacloban City, debris
may include woods, garbage, stone, etc.
The debris damming forces are due to thejamming effect of debris on a structure, which
increases the hydrodynamic forces by increasing thesurface area exposed to the flow. This force follows
after the initial impact force of the debris. This can becalculated by replacing the width of the structure withthe width of the jammed debris, thus increasing theforce. The damming forces can be estimated using
Eq. 5.
𝟏(5)
𝑭𝒅𝒎 = 𝝆𝒔 𝑪𝒅 𝑩𝒅 (𝒉𝒖𝟐 )𝒎𝒂𝒙
𝟐

Figure 5: Typical time series of the complex
combination of storm surge pressure loads.
The hydrostatic pressure is a force under static
condition. Lateral hydrostatic loads are given by Eq.
(1). Note that 𝒇𝒔𝒕𝒂𝒕𝒊𝒄 is equivalent to the area of thepressure triangle and acts at a point equal to 2/3 𝒅𝒔
below the water surface.
𝑷𝒔𝒕𝒂𝒕𝒊𝒄 = 𝜸𝒘 𝒅𝒔(1)where 𝜸𝒘 is the specific weight of floodwater, 𝒅𝒔 isthe floodwater depth. Considering a flood depth
ranges from 2 to 3 meters high, the estimatedhydrostatic pressure on masonry wall was 9.81 to
14.72 kPa.
The impulsive force is caused by the impingementof a leading edge of initial surging floodwater onto
the structure. The impulsive force acts only on thefront side of the structure. Presently, there is noestablished and rational method available to predict
the force. Based on laboratory studies, the upper limitof the impulsive force is approximately 150% of thesubsequent maximum hydrodynamic force in a quasisteady flow, see Eq. (2).
𝑭𝒊𝒎𝒑 = 𝟏. 𝟓𝑭𝒅𝒚𝒏

where 𝝆𝒔 is the fluid density including sediments, 𝑪𝒅
is the drag coefficient, 𝑩𝒅 is the breadth of the debris
dam, 𝒉 is the flow depth, and u is the flow velocity
at the location of the structure. It is recommended thatthe drag coefficient be taken as 𝑪𝒅 = 𝟐. 𝟎

(2)The hydrodynamic pressure exists when thefloodwater under dynamic conditions. In the Coastal
Construction Manual of FEMA [3], the velocity offloodwater is assumed to be constant or steady-state
flow. Hydrodynamic loads can be calculated using
Eq. (3).
𝑭𝒅𝒚𝒏 =𝟏
𝑪 𝝆𝑽𝟐 𝑨
𝟐 𝒅

(4)

ESTIMATION OF LATERAL PRESSURECAPACITY OF MASONRY WALL
Masonry walls subject to lateral forces can sufferfrom instability and collapse laterally. For walls
which carry light gravity loads, out-of-plane loading
typically induces a stability failure where a wall
bursts outward or topples over.
The OOP behavior of masonry walls has not beenstudied as well as the corresponding in-plane(3)

where 𝑪𝒅 is the drag coefficient, 𝝆 is mass density offloodwater, V is velocity of floodwater, and A is the330SEE - Nagoya, Japan, Nov.12-14, 2018

behavior, however, some research has been carriedout on the OOP behavior. For example, Rivera,
Rivera, Macias, Baqueirro, & Moreno [5] constructed
six full scaled masonry walls tested against OOP
loading. Crack patterns are similar to those predictedby the yield line theory adapted from that for
reinforced concrete slabs. Steel reinforcements are
the main component that resist the tensile stresses inmasonry walls.
Yield line method is a well-established and ahighly effective method used in determining the load
bearing capacity of concrete slabs and plates. Yield
line method is considered as economical, simple andversatile design method. It is economical because it
considers features at the ultimate limit state [6]. The
similarity of the failure pattern in masonry walls andreinforced concrete slabs has been driven to apply
Johansen’s yield line method to laterally loaded
masonry walls. Yield line method requires thetechnical knowledge on how the masonry panels will
fail. Several crack patters have been observed basedon experimental studies conducted and based on
historical records for masonry failures. With these, allpossible failure mechanisms for any masonry wall
must be investigated to confirm the correct solutionthat will give the lowest failure load [7]. Some of themost common yield patterns was shown in Fig. 6.

and y direction respectively, a and b are the width andheight of the masonry walls. Nominal moment
capacity of the masonry walls, 𝑴𝒏𝒙 and 𝑴𝒏𝒚 wascalculated in accordance with the design procedurestated in the Building Code Requirements for
Masonry Structures [9]. The design strength for outof-plane wall loading was calculated in accordancewith Eq. (8).
𝒂𝑴𝒏 = (𝑨𝒔 𝒇𝒚 + 𝑷𝒖 ) (𝒅 − )𝟐(8)where 𝑨𝒔 is the area of steel reinforcement, 𝒇𝒚 is the
specified yield strength of steel reinforcement, 𝑷𝒖 is
the factored axial load, 𝒅 is the distance from extreme
compression fiber to centroid of tension
reinforcement, 𝒂 is the depth of an equivalent
compression zone at nominal strength, 𝒇′𝒎 is the
specified compressive strength of masonry, and 𝒃 is
the width of section. The width of section, 𝒃 in Eq.
(9) is the least value of the following: (1) center tocenter bar spacing, (2) six times the wall thickness,and (3) 72 inches or 1829mm.
𝒂=(𝑨𝒔 𝒇𝒚 + 𝑷𝒖 )𝟎. 𝟖𝟎𝒇′𝒎 𝒃(9)

In order to organize the difference between eachmasonry wall design. Design specifications werecategorized as: S-Category, C-Category, B-Category,and D-Category as shown in the Table 1.
P1

P2

P3

Table 1: Category per design of masonry wall.

Figure 6: Most common yield line pattern formasonry OOP failure (Wang, Salmon, &Pincheira, 2007.)
P1
P2
P3

𝑀𝑛𝑥 𝑎2=
𝑀𝑛𝑦 𝑏 2𝑀𝑛𝑥 𝑎2<
𝑀𝑛𝑦 𝑏 2𝑀𝑛𝑥 𝑎2>
𝑀𝑛𝑦 𝑏 2𝑤𝑢
𝑀𝑛𝑥 𝑀𝑛𝑦= 12 ( 2 + 2 )∅𝑎𝑏24𝑎(𝑀𝑛𝑥 + 𝑀𝑛𝑦 )𝑤𝑢= 2∅
2𝑏 𝑥 + 3𝑏 2 (𝑎 − 2𝑥)24𝑏(𝑀𝑛𝑥 + 𝑀𝑛𝑦 )𝑤𝑢= 2∅
2𝑎 𝑦 + 3𝑎2 (𝑏 − 2𝑦)

Spacingof Rebar
SCategory

CHB
Thickness
CCategory

Rebar
Diameter
BCategoryWall
Dimension
D-Category

S1(80cm)

C1(10cm)

B1(8mm)D1(3x3m)

S2(60cm)

C2(15cm)

B2(10mm)D2(3x4m)

S3(40cm)

C3(20cm)

B3(12mm)D3(3x2.5m)

(7a)
(7b)
(7c)

The analysis using virtual work method can beused to determine the relationship between theapplied loads and the resisting moments. Moments
and loads are in equilibrium when the yield line
pattern has formed, an infinitesimal increase in load
will cause the structure to deflect further. The external
work done by the loads to cause a small arbitrary
virtual deflection must equal the internal work done
as the masonry wall rotates at the yield lines toaccommodate this deflection.
The maximum
pressure for the most common yield pattern can be
estimated using Eq. 7a, 7b, and 7c [8] where 𝒘𝒖 is the
maximum pressure capacity, ∅ is reduction factor,
𝑴𝒏𝒙 and 𝑴𝒏𝒚 are the nominal moment strength in x

Based on the survey, most of the non-engineered
masonry walls are under S1 Category. This are
masonry walls whose horizontal reinforcement are
spaced every 4th CHB layer and whose verticalreinforcements are spaced at 80cm O.C. It is also
worth-mentioning that some masonry walls do nothave steel reinforcements mainly because of financial
incapability of the occupants. Some houses also used
40 x 20x 10cm thick CHB even if the desired
designed CHB thickness for exterior walls are 40 x 20
x 15cm CHB. This has been verified during thesurvey since around 65% of the 380 houses confirmedthat their house is not made of 6” CHB (40 x 20 x15cm). According to some construction hardware,
331

SEE - Nagoya, Japan, Nov.12-14, 2018

majority of the locals purchased/used 10mmØ for theconstruction of their houses. Based on House E, thedistance of the lateral supports or columns ranges
from 2.5m to 4m apart. In this research, nonengineered masonry walls are categorized as S1-C1B2. Using yield line analysis, the maximum pressure
capacity for S1-C1-B2 was 10.32 kPa, 7.97 kPa, and12.53 kPa for wall dimensions of 3 x 3m (pattern 1),
3 x 4m (pattern 2), and 2.5 x 3m (pattern 3)
respectively. For S1-C2-B2, the maximum pressure
capacity was 11.80 kPa, 9.12 kPa, and 14.34 kPa forwall dimensions of 3 x 3m (pattern 1), 3 x 4m (pattern2), and 2.5 x 3m (pattern 3) respectively. Maximum
pressure capacity of different masonry wall design
consideration is graphically represented as shown in
the Fig. 7.

The researcher conducted several attempts toimprove the lateral pressure capacity of the masonrywalls by: (1) Minimizing the on-center distance of thesteel reinforcements, (2) Increasing the CHB wall
thickness from 4” to 6” and 8” thick, (3) Providing alarger steel rebar diameter.
The lateral pressure capacity of the different
masonry walls with steel reinforcements under S2 andS3 category and CHB thickness under C2 and C3
category are also included in Fig. 7. Comparing all
the estimated lateral pressure capacity of eachmasonry wall design, the recommended design is S2C2-B3. The S2-C2-B3 is masonry design whose
vertical and horizontal reinforcements are 12mmØ
spaced @ 40cm, CHB thickness of 150mm or 6” andthe column distance is from 2.5 to 3meters. The S2C2-B3 has the estimated lateral pressure capacity thatis sufficient enough to resist impulsive forces. The
S3-C2-B3 can be upgraded to C3 category to improve
resistance to severe debris impact. The concept of
improvement is to reinforce the strength of themasonry walls with minimum cost increase. The
proposed improvements are listed in Table 2.

DEVELOPMENT OF IMPROVEMENT.
Considering the estimated maximum pressure
capacity of the non-engineered masonry walls, it isevident that the current non-engineered masonry wall
design has experienced difficulty in sustaining lateralpressure due to floodwater induced by storm surges.

50
Pattern 2

Pattern 1

Storm Surge Pressure

Lateral Pressure Capacity (kPa)

60

Pattern 3

40
30
20
10
0
C1 C2 C3 C1 C2 C3 C1 C2 C3 C1 C2 C3 C1 C2 C3 C1 C2 C3 C1 C2 C3 C1 C2 C3 C1 C2 C3
S1 S1 S1 S2 S2 S2 S3 S3 S3 S1 S1 S1 S2 S2 S2 S3 S3 S3 S1 S1 S1 S2 S2 S2 S3 S3 S3Non-engineered design

8mmØ
10mmØ
12mmØ
NSCP2015/ACI530-02 Compliant

Recommended design

Figure 7: Estimated lateral pressure capacity of different masonry walls per pattern using yield line analysis
Table 2: List of Improvements
Part
Horizontal
Reinforcement
Vert.
Reinforcement
Thickness of
CHB
Bar Size
Spacing ofSupport(Column)Non-engineered
designNSCP 2015

ACI 530-02

Recommended
design80cm O.C

Max. of 1.2meterMax. of 1.2meter

40cm O.C.

80cm O.C.

Max. of 1.2meterMax. of 1.2meter

40cm O.C.

10 cm Thick CHB(Table 411.3.1.1)
Min. of 10mmØl/t or h/t is 18 to
20 or 2.7 to
3meters

Minimum of 6" or 152mm( Sec. 5.6.2 )Min. of 10mmØ

10 cm
Max. of 10mmØ
Min of 3 m.

332

l/t or h/t is 18 to 20 or 2.7
to 3meters

15 cm-20cm
Min. of 12mmØ
2.5 to 3 meters

SEE - Nagoya, Japan, Nov.12-14, 2018

To estimate the cracking pressure and of masonrywalls, finite element analysis using Staad Pro V8.
Four models of 3 x 3m masonry walls weredeveloped, one for each design considerations asshown in Fig. 8. The masonry walls were modelled as
isotropic linear elastic using a structures mesh withsquare shell elements of 4 nodes and 6 degrees of
freedom per node, corresponding CHB thickness per
design consideration. Modulus of elasticity ofmasonry wall was 𝟓𝟓𝟎𝒇′𝒎 , where 𝒇′𝒎 was 6.89Mpa
based on the minimum compressive strength ofmasonry required. Modulus of elasticity and yieldstrength of steel reinforcement was 200 GPa and 275
Mpa, respectively. Poisson’s ratio was assumed
equal to 0.20. Hinge supports were located along theconfining elements to simulate the presence ofcolumns and ring beams. The endpoints of thereinforcements were considered fixed to consider theeffects of embedment to the supports, increasing
uniform lateral pressure was applied perpendicular to
the face of the masonry walls and the corresponding
maximum lateral displacement was determined (seeFig. 8).

Typhoon Haiyan, however, the current construction
method for masonry walls for coastal structures washigh vulnerability to OOP failures due to poor
construction methodology and used of poor quality
materials. No Build Zone Policy along coastal
barangays was not totally implemented due toeconomic and social considerations. A standard
design for masonry walls was established. Additional
improvements must be considered for structures withhigh exposure to heavy debris.
RECOMMENDATION
To achieve a much lower fatality count, there is aneed to strengthen the structures against natural
hazards. Building codes and hazard zoning may beenough for large structures, however additional safetymeasures must be implemented at the barangay leveland develop a culture of preparedness. Although thisis already embodied in our laws, its actual
implementation leaves must be desired.

(kPa)

REFERENCES[1]
National Geographic. (2017, March 24).
National Geographic. Retrieved fromhttp://www.nationalgeographic.org/encyclop
edia/storm-surge/[2]
NDRRMC. (2013). Final report of effects of
Typhoon "Yolanda" Haiyan. Quezon City:
National Disaster Risk Reduction andManagement Council.
[3]
FEMA. (2012). Guidelines for Design ofStructures for Vertical Evacuations fromTsunamis.
National
Oceanic
andAtmospheric Administration.
[4]
Takagi, H., Li, S., de Leon, M., Esteban, M.,
Mikami, T., & Matsumaru, R. (2015). Storm
surge and evacuation in urban areas during
peak of a storm. Coastal Engineering.
[5]

(mm)
Figure 8: Pressure-displacement curves for different
masonry wall design.
The results were graphically represented in Fig. 8.
Increasing the CHB wall thickness and reducing the
spacing of reinforcement significantly improves thelateral pressure capacity and reduce the lateraldisplacement of the masonry walls. The
recommended design can sustain lateral pressure 2 to
3 times of the non-engineered masonry walls
considering a 10mm lateral displacement.

[6]

[7]

[8]

CONCLUSION[9]Based on the field surveys and the corresponding
analytical results, the following conclusions andrecommendations are presented. Existing codes forlarge RC frame structures had performed well during
333

Rivera, J. V., Macias, D. N., Baqueirro, L. F.,& Moreno, E. I. (2011). Out-of-plane
behavior of confined masonry walls.
Engineering
Structures,
Engineering
Structures 33 (2011) 1734-1741.
Kennedy, G., & Goodchild, C. H. (2004).
Practical Yield Line Design. Camberley: The
Concrete Centre.
Nilson, A. H., Darwin, D., & Dolan, C. W.
(2003). Design of concrete structures.
Singapore: McGraw-Hill.
Wang, C.-K., Salmon, C. G., & Pincheira, J.
A. (2007). Reinforced concrete design 7th
Ed. United States of America: John Wiley &Sons, Inc.
Masonry Standards Joint Committee(MSJC).
(2005).
Building
Code
Requirements for Masonry Structures.
American Concrete Institute (ACI).

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

WALKABILITY AND RAIL NODES ALONG THE TRANSEUROPEAN TRANSPORT NETWORK: THE CASE OF GENOABRIGNOLE STATION
Noriko Otsuka1, Dirk Wittowsky1, and Marlene Damerau1
ILS – Research Institute for Regional and Urban Development, Germany

ABSTRACTThis paper discusses the walkability around railway stations along the Rhine-Alpine Corridor, which is one of
the nine Core Network Corridors under the Trans-European Transport Network (TEN-T) Regulations. Researchdraws upon an EU funded project, RAISE-IT (Rhine-Alpine Interregional Seamless and Integrated Travel Chain)
which consists of nine partners from the Netherlands, Germany and Italy. The project explores seamless rail
networks and intermodal connections at stations, and aims to improve passengers’ experience at six urban nodes
along the Rhine-Alpine Corridor connecting Rotterdam and Genoa through six European countries. The
accessibility of a rail node (i.e. station) has been examined at three levels of spatial contexts: 1) accessibility within
a node; 2) walkability of a node and its surrounding area within a radius of 800m from the node; and 3) accessibility
to and from a node at urban scale within the boundaries of the city. Research reported in this paper focuses on thesecond spatial level: the walkability around stations. With reference to existing benchmark indicators and urban
design parameters to assess the walkability (e.g. urban structure, design of the street, obstacles and traffic safety,
and personal impression), a tailor made methodology has been developed including field observation and map
analysis. Results from Genoa Brignole Station, one of the six case studies, have revealed the fact that the
walkability has been influenced by various factors, not only the quality of physical infrastructure, but also othersubjective aspects such as fear of crime and traffic safety, which are caused by structural constraints of the streets
and the maintenance and quality of public spaces.
Keywords: walkability, Tran-European Transport Network (TEN-T), accessibility, urban node
INTRODUCTION

Seamless Travel Chain), which is funded by theConnecting Europe Facility (CEF) programme. This
project focuses on the assessment of railway nodeaccessibility along the Rhine-Alpine Corridor that is
one of the nine Core Network Corridors (CNCs)
under the TEN-T Regulations [3]. This project
involved nine partners from the Netherlands,
Germany and Italy, and the consortium consists ofregional and local authorities within Interregional
Alliance for the Rhine-Alpine Corridor EuropeanGrouping of Territorial Corporation (EGTC), andalso three research institutions. To optimise accessand travel time within and to/from a railway station,
it is necessary to address a range of infrastructure andoperational aspects such as station facilities,
wayfinding for transferring passengers andinformation provision. Furthermore, the design andmanagement of station should be analysed in terms of
the integration of all the urban travel modes,
including walking, cycling, private car and public
transport as well as the spatial relationship with its
surrounding areas. In order to facilitate complex
intermodal connections, the urban node accessibility
should be discussed in a holistic way with reference
to different urban scales.

Background: RAISE-IT project
Railway stations have increasingly been expected
to play multifunctional roles beyond their traditionaltransportation functions. Their roles have extended
ranging from facilitating interchanges for multimodaltransport networks, to the creation of public spacesince various amenities (e.g. cafes, restaurants, andshops, etc.) are accommodated within the station
premise. Interchanges represent places where public
transport modes, and private or alternative forms oftravelling (e.g. walking, cycling, private car use, carsharing, and carpooling) all come together [1].
Furthermore, in the post-industrial era the role ofrailway has been rediscovered in providing a betterpedestrian access to the city centre and in acting as acatalyst for ‘urban renaissance’. The regeneration of
station and its surrounding area has been intensively
carried out in Europe that has contributed to the shift
from car-dependent lifestyle and the change of image
in urban centres [2].
This paper presents preliminary results of an EU
project, RAISE-IT (Rhine-Alpine Integrated and
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Objectives of this paperthat accessibility should be based on a structure ofeffects whose components consist of land use, thetransport system, the time resources and theindividual resources of a particular person [8]. Recent
work published by ITDP (2018), Pedestrians First,
discussed the framework for measuring the
walkability ranging from the most basic requirements
for walking to be possible (e.g passable, accessible
and safe), to factors adding extra benefits for pleasantwalking (e.g. convenient, comfortable and enjoyable)[9].

Within the framework of the RAISE-IT project, a
new methodology for assessing the urban nodeaccessibility has been developed with reference to six
railway stations along the Rhine-Alpine Corridor(Arnhem, Nijmegen, Düsseldorf, Frankfurt am Main,
Karlsruhe and Genoa). For this project, the term
‘urban node’ refers to an ‘urban area’ where therailway station is located, while ‘node’ means railway
station. ‘Urban area’ is concerned with area within themunicipality’s boundary of the studied city. The
following three levels of spatial contexts are
examined during the analysis: 1) accessibility within
a node; 2) walkability of a node and its surroundingarea within a radius of 800m from the node; and 3)
accessibility to and from a node at urban scale within
the boundaries of the city. In this paper, the second
spatial level (walkability) is focused. The rest of thepaper explains the methodology for the walkability
study and results from Genoa since it has illustrated
useful findings such as the importance of pedestrianfriendly streets and subjective aspects related to thestreet structure and environment.
METHODOLOGY
Target area and indicators for walkability study
The target area of the walkability study isconcerned with a node and its surrounding area, andtherefore we started with defining physical proximity
meant by ‘surrounding area’. The concept of Transit
Oriented Development (TOD) is used as a basis of ourdefinition since it refers to station area development
in terms of ‘a mixed use place, with a certain urban
density and high-quality walking environment
located within half-mile (800 m), i.e. 10 minutes’
walk of a transit stop [4]’. Previous research has
acknowledged the prominent role of TOD in
integrating mixed land use planning with multimodal
accessibility around a transit node which leads thecreation of pedestrian oriented urban environment[4[5][6]. This concept stemmed from the ‘node-placemodel’ which emphaises the strong link between thetransportation node and its urban surroundings byconsidering the node as the place of human activities[7]. This project considers an area within a radius of
800 m of a station (i.e. 10 minutes’ walk) as a basisof assessing physical proximity for pedestrians in the
walkability study (Fig 1).
In general, the walkability is examined in terms of
the objective capacity and subjective quality of thebuilt environment characteristics to support walking
for different purposes. In particular, the access to thetrain and the public transport system is regarded as
the central component. A wealth of previous literature
introduced numerous indicators for the walkability
study. For example, Geurs and van Wee maintained

Fig. 1: Target area of the walkability study in Genoa,
Source: Map by Commune di Genova (2017) and otheradded infomration by Otsuka

Methodology for the RAISE-IT walkability study
The walkability study in the present research hasaddressed both the objective environmental
characteristics and subjective aspects, which aregrouped into four key criteria: urban structure; designof the street; obstacles and traffic safety; and personal
impression, together with some backgroundinformation. A walkability checklist has beendeveloped using 21 indicators (Table 1).
A Likert scale (1 to 5) was used to assess eachindicator under the four criteria using the checklist.
Annotations were made on an OpenStreetMap (OSM),
and photographs have been taken for collecting visualevidence. Within the target area of a radius 800 m
around a railway station two or three zones weregenerally defined in collaboration with local project
partners of each node (Fig 1). Subsequently, therespective local partner suggested two or three major
walking routes per zone which are most frequently
used when people are walking to and from the station.
The authors and local partners walked all the selectedroutes between the ending point of the 800 m’s circle
line and the information centre of train operator
normally located in the middle of station building.
Firstly, the walking was carried out starting from335

SEE - Nagoya, Japan, Nov.12-14, 2018

the information centre towards the ending point of the
800 m circle, while filling in the checklist and taking
photographs. Then we walked straight back from theending point towards the information centre whiletime required for walking was measured.

interventions are possible when upgrading thestations for meeting modern standard of interchange
and multifunctional facilities. The two stations havegone through major refurbishment works over the last
15 years which have improved the both internal andexternal parts of the building and intermodal
connections. More than 60,000 passengers use eachof these stations per day.
The modal split of Genoa for daily trips (Fig.3)
indicates that there is a similar distribution in terms of
the use of sustainable modes of transport: 25% by
walking and 27% by public transport, while bicycle is
not used due to the difficult in cycling on steep hills.
Private means of transport represent 37% for car
drivers and 11% for others which consists of 9% formotorbikes and 2% for other vehicles such as light
duty vehicles. The share of private car is the highest
among the different transport modes (37%).

Table 1. Selected indicators for the walkability study,
Source: ILS, 2017.
Criteria

BACKGROUNDURBANSTRUCTURE

DESIGN OF
STREETOBSTACLE AND
TRAFFICSAFETYPERSONAL
IMPRESSION

Indicators
Condition of observation(date/time/ weather)
Name of streets along each route
Distance to travel (Measuring
time for walking the route)
Key characteristics of the street
Land use
Building type
Pedestrian walkway
Width of the streets
StreetscapeStreet furniture
Tree and vegetation
ShelterPavement material
Arts
Barrier free
Safe crossing roads and streets
Speed of cars and traffic calming
Waiting time for traffic light
Street parking
Street connectivity
Access for bikes
Comfortable in walking
Fear of crime
Cleanliness of streets
Pedestrian flow

The following sections explain results from the
Genoa node including background information of thecity and the walkability analysis.
CASE STUDY ON GENOA
General Information of the city of Genoa
The city of Genoa is situated in the region of
Liguria on the Mediterranean coast. It is the sixth
largest city in terms of the population of Italy(583.601) with an area of ca. 240 square kilometer[10]. The node of Genoa is located at the south end of
the Rhine-Alpine Corridor (Fig. 2) and plays a keyrole in transferring from/to land and to/from the sea.
The Genoa node is served by two main stations:
Piazza Principe and Brignole. The both stationbuildings were constructed during the second half ofthe 19th century and the two transport hubs are locatedbetween the historic centre and the 18th century partof the city centre. Due to Genova’s geographicalcharacteristics constrained by hills and theMediterranean Sea, it is difficult to apply major
infrastructure redevelopment in the city centre.
Furthermore, the protection of historic stationbuildings takes a priority and thus only small-scaleFig. 2: The location of Genoa on Rhine-Alpine Corridor,
Source: http://blog.interreg.de [3]
11%
25%

0%
37%
27%

Walking

Cycling

Public transport

Car driver

Car passenger

Other

Fig. 3: Genoa Modal Split (2016), Source: CDG - Città diGenoa.

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Results from the Walkability study

striking difference in the environmental quality
between three studied streets (Fig.4).
Two of the three routes in Zone 3 go throughmajor shopping districts of the Genoa node, and offer
comfortable pedestrianised streets (Fig. 5 and Fig. 6)
with a variety of shops, cafes and restaurants. In
particular, Via San Vincenzo was still lively evenduring the lunchtime (around 14:00 in Italy where
many people go home for lunch) when the study was
conducted (Fig, 6). Via Galata also offers a pedestrianfriendly and further wider street which allows theplacement of much street furniture such as benches
and plant boxes as well as tables and chairs by cafes
and restaurants (Fig.5). However, the end of the 800m circle on Via Galata (hospital, Mura delle
Capuccine) is situated at much higher level from thecity centre, and it is inevitable for pedestrians to walkup and down many stairs if they choose this short cut
to the city centre.
A striking difference from the two routes was apoor environmental quality found in Via Serra.
Despite the fact that this route recorded the shortest
walking time, narrow pedestrian walkway continues
along lengthy stone made walls without windows on
a long downhill (Fig.7). Furthermore, closer to theBrignole station, it was not pleasant to walk next toconcrete wall of multi-storey car parking.

The local partners in Genoa: the municipality of
Genoa (CDG) and a local research institution (IIC),
have decided to conduct the walkability analysis in
the Brignole station since more people are walking
around there because of its central location in theheart of business and retail districts. Three zones havebeen identified within the 800 m circle (Fig 1), andtwo or three walking routes have been selected perzone. The fieldwork was conducted on the 25th ofOctober 2017 and the weather was sunny and dry.
The study results were presented in walkability maps
which include a variety of quantitative and qualitative
data: walking routes, measured time per route,position of public transport stops and traffic lights, thenumber of car sharing and bike sharing, points ofinterests such as public squares and museums, spatialand social problems due to empty buildings, graffiti
and steep stairs (Fig.4).
Generally speaking, more people were walking inthe southern area of Brignole, and thus walking routes
appeared to be more visible being informed by theconstant flow of pedestrians (Zone 2 and 3),compared to the area in the north (Zone 1). In thispaper the walkability map of Zone 3 (San Vicenzo
and Carignano) is presented since it has revealed aFig. 4: Walkability map, Zone 3: San Vicenzo and Carignano, Source: CDG and ILS, 2017

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Using Likert scale scored by the researcher andthe local partners, radar graphs of the studied routes
have been created in respect of the four walkability
criteria (Fig. 5-7). Results from the radar graphs haveechoed to remarks from the walkability map analysis.
Via Galata and Via San Vincenzo presents the higherscores owing to pedestrianised streets and mixed land

use along the main shopping streets. Only drawback
is many steep stairs because of the difference in theland level on the Via Galata route, which resulted in
the low score of ‘obstacles and traffic safety’ (Fig. 5).
This is a typical example caused by geographicalconstraint of Genoa.

Fig. 5: Zone 3 Walkability results on Via Galata and pedestrianised street, Source: Otsuka, ILS, 2017

Fig, 6: Zone 3 Walkability results on Via San Vincenzo and pedestrianised shopping street, Source: Otsuka, ILS, 2017

Fig. 7: Zone 3 Walkability results on Via Serra and narrow downhill pedestrian walkway, Source: Otsuka, ILS, 2017

Via Serra has got the poorest scores due to narrowpedestrian walkways along the long stone made walls
and the multi-storey car parking (Fig. 7). The score of‘design of the street’ is the worst among the sevenstreets selected for the Genoa case study. Since Via
Serra has always been considered by the Genoese asa service road from Corvetto to Brignole, the designof the streets is rather road traffic oriented, whilepedestrians’ needs seem to be set aside. Although

there are a few historic palaces located along Via
Serra, their internal courtyards are not visible fromthe street and the massive stone walls and narrowsidewalk are main physical obstacles when
considering the future improvement of the walking
route to and from the station.
In Zone 3 ‘traffic safety’ has scored relatively low
in all the three routes (Fig. 7) since the access to andfrom the station square has to go through two traffic
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lights crossing the busy main access road to thestation. Although there is an official multi-storey car
parking right next to the station, people tend to use an
unofficial space for short-term parking and Kiss &Ride, and the entrance to that space clashes with thepedestrian flow.
Finally, there is a tunnel walkway connecting twosides of the city between Zone 1 and Zone 3 (Fig, 4),which was covered with a full of graffiti at the timeof the fieldwork. Local people know it is safe to walkthrough the tunnel, however, untidy graffiti and lessmaintained floor pavement tend to generate anegative image and make visitors feel uncomfortableand even a fear of crime.

of Istituto Internazionale delle Comunicazioni (IIC)
for their contributions to conducting the walkability
study in Genoa.
REFERENCES[1] Van der Hoeven F, van Nes A, van der Spek S,
Albecoa J, Skoniezki P, Berends H, Venema A,
van Hagen M, and Cré I, State of the Art(Deliverable 2.1 - Final). EU project: NODES,
2013.
[2] Peters D, and Novy J, “Rail Station MegaProjects: Overlooked Centrepieces in the
Complex Puzzle of Urban Restructuring inEurope”, Built Environment, Vol. 38(1), 2012,
pp. 5-12.
[3] European
Union,
TEN-T
Regulation.
REGULATION (EU) No 1315/2013 OF THE
EUROPEAN PARLIAMENT AND OF THE
COUNCIL of 11 December 2013, 2013.
[4] Vale D.S, “Transit-oriented development,
integration of land use and transport, andpedestrian accessibility: Combining node-placemodel with pedestrian shed ratio to evaluate andclassify station areas in Lisbon”, Journal ofTransport Geography, Vol. 45, 2015, pp.70-80.
[5] Papa E, and Bertolini L, “Accessibility andTransit-Oriented Development in European
metropolitan areas”, Journal of Transport
Geography, Vol. 47, 2015, pp. 70-83.
[6] Bertolini L, Curtis C, and Renne J, “Station Area
Projects in Europe and Beyond: Towards Transit
Oriented Development”, Built Environment, Vol.
38(1), 2012, pp.31-50.
[7] Bertolini L, “Nodes and places: complexities ofrailway station redevelopment”, European
Planning Studies, Vol. 4(3), 1996, pp. 331–345.
[8] Geurs KT, and Van Wee B, “Accessibility
Evaluation of Land-Use and Transport
Strategies: Review and Research Directions”,
Journal of Transport Geography, Vol.12, 2004,
pp. 127-140.
[9] ITDP (Institute for Transportation andDevelopment Policy), Pedestrians Frist, Tool for
Walkability City, First Edition, New York: ITDP,
2018[10] ISTAT - Italian National Institute of Statistics,
31/12/2016.
[11] Denscomb, M, The Good Research Guide: For
Small-Scale Social Research Projects, 6th Edition.
Maidenhead: Open University Press, 2017

CONCLUSIONSThis paper presented the methodology forassessing the walkability around railway stations withreference to the six urban nodes along the RhineAlpine Corridor. Results from the Genoa node
highlighted that the walkability has been affected byboth the objective environmental characteristics andsubjective aspects (e.g. traffic safety and fear ofcrime). These are caused by structural constraints ofthe streets and the maintenance and quality of public
spaces.
Data collection of the walkability study is basedon the field observation using a tailor made checklist,
and results can be influenced by subjective views of
the researchers and local partners. To overcome thisissue, findings from the fieldwork and the analysis of
the walkability maps and radar graphs have beencrosschecked by information gained through semistructured interview with the station manager and aseries of discussions with respective local partners.
The idea of methodological triangulation [11] hasbeen carefully integrated when the methodology was
designed.
Findings from each urban node have been used fora roundtable discussion by various stakeholders (e.g.
station manager, local authority planning officers,transport operations, user groups, etc.) who play a keyrole in developing, managing and using the station in
the respective case study location. The walkability
study aims to develop a tool for capturing andvisualising the current state of pedestrian accessibility
from and to the station building in order to present
tangible evidence to practitioners. The next step is to
explore the transferability of the methodologies toother urban nodes along CNCs beyond the RhineAlpine Corridor.
ACKNOWLEDGEMENTS
RAISE-IT is co-financed by the European Union's
Connecting Europe Facility [Grant number: 130E].
The authors would like to thank Paola Debandi ofCommue di Genova (CDG) and Sara Canevello339

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE COMPARISON OF DRAINED SHEAR STRENGTH BETWEENSINGLE STAGE AND MULTISTAGE OF KHON KAEN LOESS FROMTRIAXIAL TEST
1,2,3

S. Chatchawan 1, R. Nuntasarn2 and D. Hormdee3
Faculty of Engineering, Khon Kaen University, Thailand

ABSTRACTThis study was conducted to compare the drained shear strength of compacted Khon Kaen loess between
the single stage method and the multistage method by a consolidated drained triaxial test. The single stage
method is a conventional method of triaxial and direct shear test. At least three samples are used to determine theshear strength of soil. Meanwhile, only one sample is used to determine the shear strength of soil for a multistage
method. Therefore the multistage is a safe time for testing than the single method. The investigation of this two
method of this study will be checked the accuracy of the multistage method. A result of this study will help tomake a decision to choose between the single stage method and the multistage method for the studied of thedrained shear strength of compacted Khon Kaen loess. The result from the consolidated drained triaxial test by
the multistage method showed a quite well compared to single stage test results.
Keywords: single stage, multistage, drained shear strength, Khon Kaen Loess, Compacted soil

INTRODUCTIONMETHOLOGY
There are many reports of devastated buildings
at Khon Kaen University. The foundation of thesebuilding is a shallow foundation, which seats on
Khon Kaen loess. The structure of Khon Kaen loessis honeycomb which is instability. When the soil
moisture content is increased, the shear strength ofKhon Kaen loess is decreased and then suddenly
subsidence. Udomchoke [1] found that Khon Kaen
Loess is collapsible soil with a very server degree.
Moreover, [1] found that the shear strengthparameters (c and φ) are decreased with increasingof soil moisture content as shown in Figure 1and 2.

Preparation of Specimens
In this study, the size of soil specimen forconsolidation drained triaxial test is 50 mm indiameter 100 mm in height. The specimen was
statically compacted to achieve 90% wet side of
maximum dry density by modified compaction.
Three confining pressure of 100, 250 and 450 kPa
were used for a single method. Moreover, three
confining pressure of 60, 210 and 510 kPa were used
for the multistage.
Single Stage Testing

The objective of this project is to determine theeffect of matric suction on the shear strengthparameters. However, the conventional method of
triaxial test consumes the time for testing. Therefore,
this project is carried out using a multistage method
to reduce the time of testing. However, the test
results between the single stage and multistage haveto compare prior to the study. The scope of thispaper is to compare the test result from theconsolidated drained triaxial test of saturated andcompacted soil.

The shear strength testing of saturated soil by
the consolidated drained triaxial test can be divided
into 3 steps.
Step 1: Saturation, the specimen compacted
then set up a soil specimen into triaxial compression
apparatus and apply water pressure into specimen
until soil specimen saturated with a B value of 95%
by an equation for B value shown in Eq. (1).
B=

∆u
∆σ3

(1)

Where;For the multistage method, one specimen is
subjected to several confining pressures. Eachpressure, the specimen is not tested reach to theshear failure. The shear strength of Khon Kaen loessby the direct shear tests was carried out using themultistage technique and the results are quite wellcompared to those of traditional shear tests [2].

∆u = pore pressure change in the chamberpressure when drainage valves closed∆σ3 = isotropic change in the chamberPressure340

SEE - Nagoya, Japan, Nov.12-14, 2018

Where;

τ = shear stress
σ = total compressive stressc = apparent cohesion
φ = angle of internal friction
σ' = effective stress = σ − uw

c' = effective cohesion interceptφ́́' = effective internal friction angle
Table 1. Shear rate of single stage method
SampleNo.
123

Fig. 1 Variation of the cohesion of Khon Kaenloess with moisture content (Udomchoke 1991)

σc
(kPa)
100
250
450

t90
(min)
0.036
0.058
0.160

ε
(mm/min)
0.069
0.043
0.015

Table 2. Shear rate of multistage method
Sample
No.
1
2
3

σc
(kPa)
60
210
510

t90
(min)
0.040
0.073
0.160

ε
(mm/min)
0.062
0.034
0.016

Multistage TestingFig. 2 Variation of the friction angle of Khon Kaenloess with moisture content (Udomchoke 1991)

The multistage method is used only one
specimen to subject several confining pressures. The
specimen is not tested to reach the shear failure.
The steps are as follows: first, the specimen issaturated identical a single stage method when thesoil is saturated at B value of 95%. Second, thespecimen is consolidated at confining pressures as
determined (100 kPa). Third, the shearing stage, thespecimen is sheared at the shear rated as determining
from Eq (2) as shown in Table 2. The deviator
stress is applied until reaching a yield value and thenrelease load back to zero. Afterward, the second
confining pressure of 210 kPa was applied toconsolidate and then shear (repeat step 2 and 3). The
third confining pressure of 510 kPa is repeated step2
and 3. However, this confining pressure thespecimen had to shear until the specimen was failed
and can found strength parameter from MohrCoulomb shown in (3), (4).
A multistage method can found strengthparameter from one specimen which different fromsingle stage method that to use at least 3 specimens.
So, a multistage method it is a test the shear strengthof soil rapid than single stage method. However, [3]found multistage method testing affect structure ofsoil specimen and causing the loose shear strength
during the testing.

Step 2: Consolidation, consolidation byincreasing the confining pressure, according definedin this study and let the soil specimen drain until it
was equilibrium.
Step 3: Shearing, the shear rate or strain rate wasderived from the relationship of the graph between
volume change and square root time by using Eq. (2)as present in Table 1. The shear rate from Eq (2) wasused to shear the specimen until it reaches thefailure. Repeat step 1 to step 3 at least 3 specimens
to find out shear strength parameter from MohrCoulomb shown in Eq. (3), (4).
4%ε=
16t 90(2)

Where;
t90 = square root time derived from xin the relationship of graphintercept
between volume change and square roottime

τ = c + σ tan φ

τ= c '+ σ ' tan φ '

(3)
(4)

RESULTS AND DISCUSSION
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relationship indicated that the maximum deviator
stress from the single stage was 215, 556 and 970
kPa, respectively. Moreover, the relationshipbetween deviator stress and axial strain from thesingle stage testing showed a strain hardening
behavior, which is the behavior of dense sand. The
relationship between the volumetric strain and axial
strain showed the dilation behavior of three
specimens as illustrated in Figures 6, 7 and 8,
respectively. The dilation behavior is also thecharacteristic of dense soil.

Khon Kaen loess sample was collected as a
disturbed sample at a depth of 2 m. The index
properties and compaction characteristics are shownin Table.3.
Table 3 Properties of soil
Properties
Liquid limit (LL), %Plastic limit (PL), %Plasticity index (PI), %Specific gravity
Optimum moisture content (OMC), %Maximum dry density (ρd), t/m3
Sand (% )Silt (%)
Clay (%)
USCS classification

16.5
NP
2.65
9
2.0
55
30
15
SM

Fig.5 The testing result in single stage CD test at
confining pressure of 450 kPa.

Fig.3 The testing results in single stage CD test at
confining pressure of 100 kPa.

Fig.6 The relationship between volumetric strain andaxial strain in single stage testing at confiningpressure of 100 kPa
The multistage testing results at confiningpressure of 60, 210 and 510 kPa and a pore water of
20 kPa were applied to the specimen. The testing
results showed the relationship between deviator
stress and axial strain as shown in Figures 9, 10 and
11. The relationship indicated that the maximum
deviator stress from the multistage were 115, 389
and 1,037 kPa, respectively. In addition, therelationship between deviator stress and axial strain
from the multistage testing also showed a strain
hardening behavior at confining pressure of 60 and
510 kPa. However, the relationship between deviator
stress and axial strain at confining pressure of 210
kPa showed a strain softening behavior. The stress-

Fig.4 The testing results in single stage CD test at
confining pressure of 250 kPa.
Compacted and saturated Khon Kaen loess wastested for consolidated drained triaxial. Three
confining pressures of 100, 250 and 450 kPa wasused for single stage testing and pore water of 20
kPa was applied to samples. The testing results of
the relationship between deviator stress and the axial
strain were shown in Figures 3, 4 and 5. The
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SEE - Nagoya, Japan, Nov.12-14, 2018

multistage method as shown in Figures 13 and 14,
respectively. Table 4 showed the comparison of
total strength parameter between a single stage andmulti-stage. The Mohr circle of effective stressstrain curve was derived from various ensembles in
multistage testing shown in Figure 12.

showed that φ' = 31

๐and c' = 25 kPa in a single
๐stage method and φ' = 29.7 and c' = 20 kPa in a
multistage method as shown in Figures 15 and 16,
respectively. Table 5 showed the comparison ofeffective strength parameter between a single stage
and multi-stage.

Fig.7 The relationship between volumetric strain andaxial strain in single stage testing at confiningpressure of 250 kPa

Fig.10 Testing results in multistage CD test at
confining pressure of 210 kPa
Table 4. The comparison of total shear strengthparameters between a single stage and a multistagec(kPa)

Fig.8 The relationship between volumetric strain andaxial strain in single stage testing at confiningpressure of 450 kPa

Single stage
Multistage
Differential

0
0
0%

φ
(Degree)
31
27.9
4.2%

CONCLUSION
The stress-strain behavior of saturated andcompacted Khon Kaen loess showed a strain
hardening except to multistage testing at confiningpressure of 210 kPa, which showed a strain
softening. The relationship between the volumetricstrain and axial strain from single stage testing
results showed the dilation behavior. The
comparison of shear strength parameters between asingle stage and a multistage as shown in Table 4
and 5 indicated a small change. So, Khon Kaen loesscan be found shear strength by multistage method.
The multistage method is more simple and rapid
than single stage. The results showed that thestrength parameter of the test consolidated drained
triaxial test of Khon Kaen loess by multistage lessvaluable than single stage. Therefore, the shear
strength parameters from the multistage test result

Fig.9 Testing results in multistage CD test at
confining pressure of 60 kPa
The maximum stress value derived from therelationship between deviator stress and the axial
strain was drawn to the Mohr circle. The Mohr circle๐of total stress showed that φ = 31 and c = 0 kPa in a๐

single stage method and φ = 29.7 and c = 0 kPa in a
343

SEE - Nagoya, Japan, Nov.12-14, 2018

are appropriate forgeotechnical engineer.

conservative

designsin

ACKNOWLEDGEMENTS
Acknowledgement is given to Faculty ofEngineering, Khon Kaen University for the supportof this research. Grateful to Advisor Asst. Prof.
Ratamanee Nuntasarn for the suggestions andsolutions to the problems in this research. Thanks
other students at Department of Civil Engineering,
Khon Kaen University in preparing the soil samples
for the testing.

Table 5 The comparison of effective shear strengthparameters between a single stage and a multistage

c'
(kPa)
Single stage
Multistage
Differential

25
20
20%

φ'
(Degree)
31
27.9
4.2%

Fig.14 The Mohr circle of total stress from amultistage method

Fig.11 Testing results in multistage CD test at
confining pressure of 510 kPa

Fig.15 The Mohr circle of effective stress from asingle stage method
Fig.12 The stress– strain curve derived from various
ensemble in multistage testingFig.16 The Mohr circle of effective stress from amultistage method

Fig.13 The Mohr circle of total stress from a single
stage method344

SEE - Nagoya, Japan, Nov.12-14, 2018

REFERENCES[4] Wykeham Farrance. 2007. Triaxial test: Double
wallcell.http://www.wfi.co.uk/pdf/wf_catalogue_double_wall_triaxial_cell.pdf.
23
september 2007.
[5] Gan, J.K., Fredlund, D.G. and Rahardjo, H.,“Multistage direct shear testing of Unsaturated
Soil”, Geotechnical Testing Journal, GTJODJ,
Vol. 111, No. 2, June 1988, pp.132-138.
[6] Runtasarn and W. Wannakul,’” Drained Shear
Strength Of Compacted Khon Kaen Loess”,
International Journal of GEOMATE, 2017,
pp.28- 33.
[7] Terzaghi, Karl, Ralph B. Peck, and Gholamreza
Mesri. Soil mechanics in engineering practice.
John Wiley & Sons, 1996.

[1] Udomchoke, V. (1991). Origin and Engineering
Characteristics of the Problem Soil a in the
Khorat Basin, Northeastern Thailand. Ph.D.
dissertation Asian Institute of Technology
Bangkok Thailand.
[2] Hormdee D., Kaikeerati N., and Angsuwotai P.
“Evaluation on the Results of Multistage Shear
Test” , Int. J. of GEOMATE, 2012, pp. 140143Behaviour of Concrete Containing Waste
Carpet Fiber, International JournalofGEOMATE, Vol. 9, Issue 17, 2015, pp. 14411446.
[3] Ho, D. and Fredlund, D., "A Multistage Triaxial
Test for Unsaturated Soils," Geotechnical
Testing Journal,1988 , pp. 132-138.Author H., A
Book New York Publisher, Year, pp.1-200.

345

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

BEARING CAPACITY OF KHON KAEN LOESS BY PLATE BEARING
TEST

1,2,3

P. Thaowandee1, R Nuntasarn2 and P Punrattanasin3
Faculty of Engineering, Khon Kaen University, Thailand

ABSTRACTThe purpose of this study is to determine bearing capacity and settlement of Khon Kaen loess by plate bearing test.
Khon Kaen loess is classified as a collapsible soil, which is an unstable structure. According to USCS, Khon Kaenloess is classified as silty sand (SM). The structure of Khon Kaen loess is a honeycomb structure, which consistsof fine sand and silt. Moreover, clay particles and iron oxide is the binder. If the soil is wetting, the binder will be
washing. Therefore, the volume of soil decrease suddenly and the shear strength also decreases. In this study, thebearing capacity and the settlement of Khon Kaen loess will be compared between wet and dry condition. The
plate size 0.3x0.3 m will be seated at a depth of 0.4 m from the ground surface. The ultimate bearing capacity ofKhon Kaen loess at the moisture content of 9.76% is 12 t/m2. Moreover, the ultimate bearing of Khon Kaen loessafter soaked for 4 days (moisture content of 30%) is 8 t/m2.
Keywords: Khon Kaen loess, settlement, plate bearing,

the loaded behavior of collapsible soils and tomeasure its deformation at constant surcharge andground water infiltration rates [2]. Moreover, theplate bearing tests was used to studied the stabilized
collapsing soil by sand blended with coarse aggregate
of various sizes and proportions [3], compacted,
partial replacement by compacted sand/crushed stonelayers over the collapsible soil [4].

INTRODUCTION
Collapsible soil behavior is typical in Khon Kaen
province, in deposits of yellow or red Aeolian (windblown) silty sand (according to the Unified Soil
Classification System or USCS). The structure ofKhon Kaen loess is a honeycomb structure, which isan unstable structure. The majority of Khon Kaenloess consists of fine sand and silt. Whereas, clay
particles and iron oxide is the binder. If the soil iswetting, the binder will be washing. Therefore, thevolume of soil decrease suddenly and the shear
strength also decreases. The decreasing strength ofundisturbed Khon Kaen collapsing loess withincreasing moisture content was investigated byunconsolidated undrained (UU) triaxial testing as
shown in Figures 1 and 2 [1]. The apparent friction
angle decreased linearly with increasing moisture
content, but the dropping of apparent cohesion withincreasing moisture content was not linear. Moreover,the collapse index of Khon Kaen loess showed thesevere degree [1].
In the past, the engineering designed the spreadfootings, which seat on loess, for the building in Khon
Kaen University. Due to the strength of Khon Kaenloess is high on the dry season. Therefore, thestructure of these old buildings severe suffereddamage when the leaking of water to the foundation.
To determine the bearing capacity of spread footingin the filed, therefore a plate bearing test was used to
study in this project.
Plate bearing test was used to studied the
behavior of collapsible many projects. For example
collapsible soil at the United Arab Emirates wasstudied to develop a laboratory method of simulating

Fig. 1 Variation of the undrained friction angle ofKhon Kaen loess with moisture content [1]60

Cohesion (kPa)50

Red Loess40

Yellow Loess

30
20
10
0
0

5

10

15

20

Moisture Content (%)

Fig. 2 Variation of the undrained cohesion of Khon
Kaen loess with moisture content [1]346SEE - Nagoya, Japan, Nov.12-14, 2018

A design load for wet testing was a half of the
maximum load of dry testing. The maximum load ofdry testing was 12 t/m2. Therefore, the design load of
wet testing was 6 t/m2. Moreover, the increment ofloading was 0.5 t/m2 for the wet condition.
After loading, the settlement was recorded at 1,
2, 4, 8, 15, 30 and 60 min. The failure was defined as
the total settlement of 25 mm, or the rate of settlement
was over 0.2 mm/min.

However this project was also study the bearing
capacity of Khon Kaen loess in filed by plate bearing
and then compare with the calculation from thestandard penetration test (N-value) and the unconfine
compression test.

SCOPE
The soil profile of investigated site showed that
Khon Kaen loess is 0 to 1.5 m depth from the groundsurface and seat on the laterite. So that the plate sizeof 0.3x0.3 m was seated at a depth of 0.4 m from theground surface. The maximum pressure wascomputed from the load column of CB building,which is nearby the investigated site. The maximum
pressure of this project is 36 t/m2. Therefore theinterval load for the dry condition was 2 t/m2. The test
was determinate after the settlement rate of more than
0.2 mm/min or total settlement of more than 25 mm[5]. After testing at the dry condition, the maximum
pressure of wet condition was estimated at 50% of the
maximum pressure at the dry condition. Therefore theinterval load for the wet condition was 0.5 t/m2.
The testing pit between wet and dry condition was
farther of 5 times of plate size, which was 1.5 m [5].
Both sites were measured the matric suction andmoisture content during the testing.

Fig. 3 The installation of plate bearing test in a dry
pit

METHOD
Plate Bearing
According to the design pressure of 36 ton/m2 andplate size of 0.3x0.3 m, hence the allowable load was
4 tons. However, the factor of safety of 2 wasapplying therefor the ultimate load was 8 ton.
Therefore a nine piles was used as a dead load for thisproject. The capacity of hydraulic jack was 50 tons
with 10 ton of proving ring. Four dial gauges wereused to measure the settlement at the corner of theplate by attached with the reference beam. The
installation of apparatus was present in Fig 3.
The dry condition, the matric suction was measure
via KU-tensiometer as shown in Fig. 4 before
installation. The load was applied after the
installation was completed.
Water was applied in the testing pit for four days
as shown in Fig.4 for the wet condition. Then a water
was drained out from the testing pit before theapparatus was installed as shown in Fig. 6. The
moisture content of wet pit was 31%, which wasmeasured after testing. Both conditions wet and dry,were tested during the weather 25 to 35oc.
As a design load of 36 t/m2, therefore theincrement of loading was 2 t/m2 for the dry condition.

Fig. 4 Measurement matric suction by using KU
tensiometer
347

SEE - Nagoya, Japan, Nov.12-14, 2018

samples were used to determine the unconfinedcompressive strength. The shearing rate was 1
mm/min.

Fig. 7 Sampling block sample
Soil Water Characteristic Curve
The drying soil water characteristics curve (SWCC)
for the compacted Khon Kaen loess was determinedby pressure plate. According to [6], the pressure plate
method was used to establish SWCC for a suction
values between 1 to 1,500 kPa.

Fig. 5 Wetting pit (soaking for 4 days)

TEST RESULTThe properties of soil sample were shown in Table
1. Soil sample consisted of 60% sand and 40% siltclay with PI of 0.92%. Therefore the soil sample ofthis study was classified as silty sand (SM) according
to [7].

Fig. 6 The installation of plate bearing test in the wet
pit

Fig. 8 Frozen undisturbed sample

Unconfined Compressive Strength

Plate Bearing

The undisturbed soil sample was taken as a block
sample from the open pit as shown in Fig. 7. Then theblock sample was frozen before trim as shown in Fig.
8. The size of the sample was 50 mm diameter and
100 mm height as shown in Fig. 9. The proving ringof 3 kN and dial gauge was set up for testing. Three

The relationship between settlement and pressureof dry and wet condition as shown in Fig. 10 and 11,
respectively found that the ultimate pressure of dry
and wet condition was 12 and 8 t/m2, respectively.
The yield point of dry and wet condition was 4 and
348

SEE - Nagoya, Japan, Nov.12-14, 2018

1.5 t/m2, respectively. Moreover, the young modulus
of a dry condition is higher than the wet condition
about 12 times. The young modulus of dry and wet
condition was 20,000 and 1,730 kPa, respectively.
Fig. 10, 11 and 12 also presented the failure mode of
local shear failure, which is the characteristic of
medium dense sand. All test result represented inTable 2.
The differential settlement between wet and dry
condition was shown in Fig 13. The different
settlement at the applied pressure of 8 t/m2 showed asevere collapsing about 20% (Loess thickness of 1.1
m).

Fig. 11 The relationship between pressure andsettlement of wet condition

Fig. 9 Specimen after trimming
Fig. 12 Failure surface at field
Table 2 Plate bearing results
Table 1 Basic Properties of Khon Kaen loess
Properties
Liquid limit (LL), %Plastic limit (PL), %Plasticity index (PI), %Specific gravity
Natural moisture content, %Dry density (ρd), t/m3
Sand (% )Silt – Clay (%)
USCS classification

Yield Point (kPa)Young Modulus (kPa)Ultimate pressure (kPa)

14.3
13.21
0.92
2.65
10
1.6
60
40
SM

Wet
1.5
1,730
8

Dry
4
20,00012Moreover, the standard penetration test presented
the N-value of 2, which is also classified as very loose
sand. However, the dry density is 1.6 t/m3. The
tensiometer showed the matric suction was 28 kPa forthe dry condition, which is on the residual regime
according to SWCC as illustrated in Fig. 14.

Fig. 10 The relationship between pressure andsettlement of dry condition

349

SEE - Nagoya, Japan, Nov.12-14, 2018

t/m2, which was also underestimated.

=
q u 0.867c ' N c' + qN 'q + 0.4 γBN 'γ
Where
qu
c′
N′c, N′q, N′γqDfBFig. 14 Soil water characteristic curve of
undisturbed Khon Kaen loess(1)= ultimate bearing capacity= cohesion= codified bearing capacity factor= γ.Df= depth of foundation= width of foundation

Unconfined Compressive Strength
CONCLUSION
Three sample was studied. The initial moisture
content and the dry density was 7% and 1.6 t/m2,
respectively. The relationship between axial strain
and deviator stress was present in Fig. 15. The
average unconfined compressive strength is 2.5 t/m2.

The bearing capacity of Khon Kaen loess of a wet
condition was a slightly lower than a dry condition.
However Khon Kaen loess showed at a severe
collapsing at pressure of 8 t/m2. Moreover,unconfined compressive strength and N-value fromSPT give a lower the ultimate bearing capacity, which
was derived from Terzaghi’s equation for local shear
failure, from plate bearing test.

ACKNOWLEDGEMENTS
Acknowledgement is given to Faculty ofEngineering, Khon Kaen University for the supportof this research. Grateful to Advisor Asst. Prof.
Ratamanee Nuntasarn for the suggestions andsolutions to the problems in this research. Thanks
other students at Department of Civil Engineering,
Khon Kaen University in preparing the soil samples
for the testing.

Fig. 14 The stress-strain relationship of unconfinedcompression test

DISCUSSION

REFERENCES

The test result showed that the bearing capacityof dry condition was 1.5 times higher than the wet
condition. However, the young modulus of Khon
Kaen loess at dry condition is much higher than a wet
condition. The failure mode of bearing capacity wasa local shear failure, which is the characteristic of
medium dense soil. According to the matric suctionof dry condition, Khon Kaen loess was in the residual
regime.
According to Terzaghi’s equation for local shear
failure mode of square foundation as present in Eq.
(1). Also, the unconfined compressive strength ofundisturbed Khon Kaen loess of 2.5 t/m2 or theundrained shear strength of 1.25 t/m2 at a dry
condition. The ultimate bearing capacity of Khon
Kaen loess at a dry condition was 7 t/m2, which wasunderestimated almost 2 times.
According to SPT result, the friction angle was
26 deg [8]. The ultimate bearing capacity was 5.32

[1] Udomchoke, V. (1991), ‘Origin and Engineering
Characteristics of the Problem Soil a in the
Khorat Basin, Northeastern Thailand’, Ph.D.
dissertation, Asian Institute of Technology,
Bangkok, Thailand.
[2] Laboratory Simulation of Irrigation-Induced
Settlement of Collapsible Desert Soils Under
Constant Surcharge, Ramesh Vandanapu .
Joshua R. Omer . Mousa F. Attom Geotech Geol
Eng (2017) 35:2827–2840[3] Kesharwani R.S., Sahu A. K. and Khan N.U.,
2015, LOAD SETTLEMENT BEHAVIOUR OF
SANDY SOIL BLENDED WITH COARSEAGGREGATE, Journal of Asian Scientific
Research, 5(11): 499-512[4] Ali A. Naema, (2015), Performance of partiallyreplaced collapsible soil – Field study,

350

SEE - Nagoya, Japan, Nov.12-14, 2018

[7] ASTM - American Society for Testing Material.
2000. Standard Practice for Classification ofSoils for Engineering Purposes (Unified Soil
Classification System) (ASTM D 2487-00).
West Conshohocken. Pennsylvania.
[8] HATANAKA, M., and UCHIDA, A. (1996).
“Empirical Correlation between Penetration
Resistance and Internal Friction Angle of Sandy
Soils,” Soils and Foundations, Vol. 36, No. 4, pp.
1–10.

Alexandria Engineering Journal 54, 527–532[5] ASTM - American Society for Testing Material.
2000. Standard Practice for Bearing Capacity of
Soil for Static Load and Spread Footings (ASTM
D 1194-94). West Conshohocken. Pennsylvania[6] ASTM - American Society for Testing Material.
Standard Test Method for Capillary-Moisture
Relationships for Coarse- And MediumTextured Soils By Porous-Plate Apparatus(ASTM D2325-98). Ann Arbor. Michigan. 1998351

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DRAINED SHEAR STRENGTH PARAMETERS OF COMPACTEDKHON KAEN LOESS BY DIRECT SHEAR TEST
Atchariya Saengthongthip1, Ratamanee Nuntasarn2 and Chinawat Muktabhant3
1,2
Faculty of Engineering, Khon Kaen University, Thailand

ABSTRACTThis study aims to determine the relationship between drained shear strength and matric suction ofcompacted Khon Kaen loess soil. This soil samples were investigated shear strength parameters of compacted
Khon Kaen loess from CD method. A direct shear test determined these shear strength parameters. The initial dry
density of CD samples was 1.95 t/m3, which was 90% of maximum dry density by a modified method. The shear
rates of CD method was determined by consolidation. However, soil samples were tested for CD method undersaturated and unsaturated conditions. Unsaturated soil samples had been divided into three states by dry soil
samples in the air. 30, 60 and 90 minutes are times of dry soil samples in the air. The shear rate was 0.005 mm/min.
The results of a saturated consolidated drained direct shear test (CD Test) presented that a friction angle (φ´) anda cohesion (c) was 32.6 degree and 4 kPa, respectively. Moreover, the relationship between drained shear strengthand matric suction is linear. However, the slope of the graph or the φb value is not constant. It is varied with thevertical stress. The friction angle is constant with matric suction, but the cohesion increased with matric suction.

Keywords: Direct Shear, Saturated, Unsaturated, Consolidated Drained, Khon Kaen Loess, Compacted soil
And φb is an angle indicating the rate of increase in
shear strength relative to the soil suction at failure.

INTRODUCTION
In the present, there are many constructions inKhon Kaen province. Moreover, Khon Kaen soil wasused as construction material for landfill. Therefore
the engineering should know the shear strengthparameters for design the foundation. The shear
strength parameters can be evaluated by consolidated
drained method (CD). This method can test by triaxial
and direct shear test. This study used a direct shear
test to determine shear strength parameters of thismethod as mention previously.
In this study, Khon Kaen loess had been
investigated at compacted and saturated condition.
Soil samples for CD method were compacted at 90%
of maximum dry density by a modified method. The
unsaturated soil has three phases which are solid,
liquid and air. Therefore, the Terzaghi’s effective
stress law for saturated soil is not appropriate forunsaturated soil. Fredlund and Rahardjo [1]formulated the shear strength equation for an
unsaturated soil as given in Eq (1).

τff = c '+ (σn − u a ) tan φ '+ (u a − u w ) tan φbBASIC PROPERTIES
Khon Kaen loess, which was used in this study,
was classified as silty sand (SM) according to [2]. The
results of sieve and hydrometer analysis showed that
Khon Kaen loess consists of 55% sand, 30% silt, and
15% clay [2]. The majority of Khon Kaen sand size
was a fine grain as illustrated in Fig. 1. The naturaldensity of Khon Kaen loess was 1.65 t/m3, which is
the loosed sand. Atterberg’s limit results alsopresented a liquid limit was 16.5% and a non-plastic
limit. The specific gravity was 2.65. The basic
properties of Khon Kaen loess were present in Table1.
100
90

Percent Finer,%

80

(1)

70

Silt

Sand

60
50
40
30
20
10
0

Where τff is a shear stress at failure. c' is aneffective apparent cohesion, which is the shear
strength intercept when the effective stress is equal tozero. σf is total normal stress at failure. uaf is pore-airpressure at failure. uwf is pore-water pressure at
failure. φ' is an effective angle of internal friction.

10

1

0.1
Particle Size, mm

0.01

0.001

Fig. 1 Grain Size Distribution
Also, the modified compaction was decided to use
in this project because Khon Kaen loess was used inpavement construction rather than another352

SEE - Nagoya, Japan, Nov.12-14, 2018

hours before being consolidated for 24 hours. But theunsaturated specimen was air dry before
consolidating. Three series of air dry sample, whichare 30, 60 and 90 minutes, was studied in this project.
The shear rate of this method has to determine fromconsolidation stage as shown in Table 2. Threevertical stress of 200, 400 and 800 kPa was used to
study. The failure time of 200, 400, 800 kPa verticalload as shown in Table 2, 3, 4, 5, respectively.
However, the consolidation results found that thatpre-consolidation pressure (Pc) was 56 kPa and OCR
was 1.74, which was less than 2. Therefore the failure
time has to determine t50 or t90 as shown in Eq. [2]and 3, respectively. The shear rate was calculated
from the maximum value of the failure time as shownin Eq. [3]. The failure time, which was derived fromt50 was higher than t90. The shear rate of this study
equaled to 0.005 mm/min.

construction. The maximum dry density was 2 t/m3,
and the optimum moisture content was 9%.
Table 1 Basic Properties of Khon Kaen loess
Properties
Liquid limit (LL), %Plastic limit (PL), %Plasticity index (PI), %Specific gravity
Optimum moisture content (OMC), %Maximum dry density (ρd), t/m3
Sand (% )Silt (%)
Clay (%)
USCS classification
Pre-consolidation pressure (Pc)

16.5
NP
2.65
9
2.0
55
30
15
SM
56

DIRECT SHEAR

t f = 50 t 50

(2)

Soil samples were compacted at 90% of maximum
dry density at the wet side (moisture content of
11.85%) by a modified method. Soil samples were
trimmed by cutting ring and taken into direct shear
apparatus as shown in Fig 2 and 3, respectively.

t 50 = 11.6 t 90

(3)

df
tf

(4)

Rd =

Where df equal to 0.2 inches according [3] because
Khon Kaen loess was coarse grain soil. Moreover, tf
is a failure time, which equaled to 60 min.
Table 2 Failure time of CD saturated

Fig.2 Preparation specimen

VerticalStress(kPa)

t50(min)tf(min)t90(min)

tf
(min)

200

7.5

375

5.9

68.44

400

7.8

390

6.9

80.04

800

8

400

4.6

53.36

Table 3 Failure time of CD Unsaturated of air dry for
30 minutes

Fig. 3 Direct shear setup
Consolidated Drained Method
The saturated specimen had to be soaked for 24
353

VerticalStress(kPa)

t50(min)tf(min)t90(min)

tf
(min)

200

1.5

75

5.8

67.28

400

6.5

325

3.3

38.28

800

0.45

22.5

16

185.6

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 4 Failure time of CD Unsaturated dry 60
minutes
VerticalStress(kPa)

t50(min)tf(min)t90(min)

tf
(min)

200

1.357

67.5

3.5

40.6

400

0.857

42.85

8.5

98.6

800

0.55

27.5

9

104.4

The effective friction angle of saturated condition
was 2 degrees lower than an unsaturated condition.
The effective cohesion of unsaturated is 35 degree.
However, the cohesion was increased with decreasingof soil moisture dramatically.

Table 5 Failure time of CD Unsaturated dry 90
minutes
VerticalStress(kPa)

t50(min)tf(min)t90(min)

tf
(min)

200

1.07

83.5

3.5

40.6

400

0.85

42.5

2.5

29

800

1.71

85.5

8.6

99.76

Fig. 5 Drained shear strength of unsaturated sample
for 30 mins air dry

TEST RESULTThe test result was shown in Figure 4 to 7 forsaturated, air dry for 30, 60 and 90, respectively. The
summary test result present in Table 6.
The effective friction angle and cohesion ofsaturated soil was 32.6 degree and 4 kPa, respectively,
as shown in Fig. 4.
Fig. 6 Drained shear strength of unsaturated sample
for 60 mins air dry

Fig. 4 Drained shear strength of saturated soil sample

Table 6. The summaries of test result
Sampleφ'Saturated
32.6
Air dry for 30 min
34.8
Air dry for 60 min
35.2
Air dry for 90 min
34.7

Fig. 7 Drained shear strength of unsaturated sample
for 90 mins air dry
c'
3.6
13.3
22.9
25.6

The relationship between horizontal displacement
and shear stress of saturated sample and unsaturated
sample for 30 and 60 mins air dry showed the strain
hardening as shown in Fig. 8, 9 and 10, respectively.
But the relationship between horizontal displacement354

SEE - Nagoya, Japan, Nov.12-14, 2018

and shear stress of unsaturated sample for 90 min air
dry showed the strain softening as shown in Fig. 11.
Besides, the relationship between verticaldisplacement and horizontal displacement of bothconditions as present in Fig. 12 to 15 showed acompression behavior.
DISCUSSION
The relationship between matric suction andshear stress at initial state showed a quite linear
relationship. However, the slope of the graph or the
fb angles were not constant, but the φb angles werelinearly decreased with a vertical pressured from 200
to 800 kPa, as shown in Fig.16 and Table 7.

Fig. 10 The relationship between horizontal
displacement and shear stress of unsaturated sample
for 60 mins air dry

The relationship between matric suction andshear stress at a failure state as shown in Fig.16
showed a linear relationship with R2 of 0.87.
Moreover, the slope of the graph or the φb angles were
not also constant same as the initial state, but the φbangles were linearly increased with a verticalpressured as shown in Fig.17 and Table 7.
Finally, the relationship between matric suction
and shear stress at residual state showed that φb angles
were constant at a lower vertical pressured.
Nevertheless, that showed a quite linear at highest
vertical pressured, as shown in Fig.18 and Table 9.

Fig. 11 The relationship between horizontal
displacement and shear stress of unsaturated sample
for 90 mins air dry

Fig. 12 The relationship between verticaldisplacement and horizontal displacement ofsaturated sample
Fig. 8 The relationship between horizontal
displacement and shear stress of saturated sample

Fig. 9 The relationship between horizontal
displacement and shear stress of unsaturated sample
for 30 mins air dry

Fig. 13 The relationship between verticaldisplacement and horizontal displacement of
unsaturated sample for 30 mins air dry
355

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 16
the relationship between matric suction
and shear stress of direct shear at initial stateFig. 14 The relationship between verticaldisplacement and horizontal displacement of
unsaturated sample for 60 mins air dry
Table 7. The φb angle at initial state
VerticalShearmatricyload
stresssuctionintercept
kPa
kPa
kPa
200
2.99
98.00
0.55
103.8314.75
118.0316.83
135.9219.72
400
182.780.55
2.04
225.75
14.75
234.5016.83
207.6719.72
800
370.420.55
1.58
405.6114.75
423.5016.83
427.00
19.72

φb
(deg)
71.5

Fig. 17
the relationship between matric suction
and shear stress of direct shear at failure state

63.9

57.7

Fig. 18
the relationship between matric suction
and shear stress of direct shear at residual state
Table 8. The φb angle at failure state
VerticalShearmatricyload
stress suction intercept
kPa
kPa
kPa
200
98.00
0.55
5.66
103.833.89
118.033.89
135.927.25
400
182.780.55
7.73
225.75
6.63
234.505.42207.674.96
800
370.420.55
11.08
405.614.51
423.505.27
427.005.42

Fig. 15 The relationship between verticaldisplacement and horizontal displacement of
unsaturated sample for 90 mins air dry

356

φb
(deg)
80.0

82.6

84.8

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 9. The φb angle at residual state
VerticalShearmatricyload
stresssuctionintercept
kPa
kPa
kPa
200
97.22
0.55
1.93
97.22
8.16
107.338.16
131.258.16
400
178.890.55
0.29
200.083.44
194.44
8.46
179.288.46
800
331.720.55
13.44
405.614.51
412.616.03
392.005.88

φb

ACKNOWLEDGEMENTS

(deg)
62.7

Acknowledgement is given to Faculty ofEngineering, Khon Kaen University for the supportof this research.

16.5
REFERENCES[1] Fredlund, D.G. and Rahardjo, H. Soil Mechanics
for Unsaturated Soils. Wiley. New York. 1993
[2] ASTM - American Society for Testing Material.
2000. Standard Practice for Classification ofSoils for Engineering Purposes (Unified Soil
Classification System) (ASTM D 2487-00).
West Conshohocken. Pennsylvania.
[3] ASTM - American Society for Testing Material.
2011. Standard Test Method For Direct Shear
Test of Soils Under Consolidated Drained(ASTM D3080/D3080M). West Conshohocken.
Pennsylvania.

85.7

CONCLUSION
All test results were present in Table 6. The
different of the effective friction angle between
saturated and unsaturated are slight. However, thecohesion was increased dramatically with matricsuction. Moreover, the direct shear test showed alinear relationship between drained shear strength andmatric suction. However, the φb is not constant withthe vertical stress.

357

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ABSORPTION OF NI, CU AND ZN ON BENTONITE CLAYMIXED WITH POZZOLANIC MATERIALS
1Natta Orprasert, 2Pongsakorn Punrattanasin and 3Dolrerdee
Hormdee 1,2,3Faculty of Engineering, Khon Kean University,
Thailand

ABSTRACT
Clay is the main material used to absorb contaminants and heavy metals in treated ponds. It has a very large
specific surface area and its negative charge in the surface structure can bond well with heavy metals. Bentonite
mainly consists of montmorillonite, which is a type of clay mineral. This laboratory-based study experimented
with using sodium bentonite to adsorb Ni, Cu, and Zn. Bentonite was used and mixed with various pozzolanicmaterials, including (1) cement, (2) bottom ash, and (3) fly ash. Batch sorption tests were selected as the method
to evaluate sorption capacity. Factors controlled in this study were mixing time, temperature, and pH. The findings
from this experiment can be the capacity to describe adsorption potential and to find the best ratio of adsorbent to
be used in construction sites. In this study, sodium bentonite showed a very high Cu adsorption performance.
Mixing bentonite with cement resulted in a more effective performance relative to using pure bentonite.
Keywords: Adsorption, Bentonite clay, Pozzolanic materials, Batch adsorption test, Cement, Isotherm(XRF) are tabulated in Tables 1 to 2 [5]. Figures. 5 to
8 display the SEM photographs of samples withexpansion rate of 500 times.

INTRODUCTION
Thailand State of Pollution Report 2016
discovered that various water sources havecontaminated with heavy metals [1]. The main causes
were the waste water discharged from factories anddensely industrial estates [2]. Heavy metals cannot be
decomposed in natural processes and thenaccumulated in soil, water and organism [3]. In theremove of heavy metals from waste water, it can bedone by various methods such as ion exchange, foam
flotation, coagulation and chemical coagulation etc.
In these methods, adsorption with soil is an effective
and inexpensive solution. Therefore, the objective of
this study mainly focuses on the adsorption of heavy
metals including Ni, Cu and Zn on bentonite clay
mixed with cement, bottom ash and fly ash by batch
sorption test. The findings from this experiment canbe used to describe adsorption potential and to findthe best ratio of adsorbent to be used in construction
site.

Table 1 Chemical analysis of bentonite clay, bottom
ash and fly ash by XRF
Bentonite
Clay
Constituent
Wt.%
SiO2
56.80
Al2O3
15.10
Fe2O3
9.79
MgO
4.61
Na2O
2.01
CaO
2.81
SO3
K 2O
LOI
-

Bottom
Ash
Wt.%
47.45
20.32
10.92
2.60
1.03
13.16
1.16
-

Fly
Ash
Wt.%
41.16
22.30
1151
2.70
1.66
15.27
1.43
2.93
0.20

MATERIALS USEDThe adsorbent in this study is bentonite clay
(Fig.1) [4]. The Pozzolanic materials used to mix withthe bentonite for improve the adsorption capacity
consist of (1) cement (Fig.2), (2) bottom ash (Fig.3)and (3) fly ash (Fig.4). All of the Pozzolanic materials
were dry and were then sieved through sieve No. 16.
Most of Pozzolanic materials are by products andeasy to find. The composition of the mineralogicaland chemical of bentonite clay, bottom ash, fly ash
and cement determined by X-Ray Fluorescence

Table 2 Chemical analysis of cement by XRF
Constituent
SiO2
Al2O3
Fe2O3
MgO
CaO
358

Wt.%
20
5
3
1.1
60

SEE - Nagoya, Japan, Nov.12-14, 2018

SO3

2.4

Fig. 1

Fig. 5

Bentonite clay

Fig. 2

Fig. 3Fig. 4

SEM photograph of bentonite clay

Fig. 6

CementFig. 7

Bottom ash

Fig. 8

Fly ash359

SEM photograph of cement

SEM photograph of bottom ash

SEM photograph of fly ash

SEE - Nagoya, Japan, Nov.12-14, 2018

Copper (Cu), nickel (Ni), and zinc (Zn) were selected
to represent the range of the common heavy metals
and prepared in the form of the solution to be theadsorbates. The stock solutions of Cu (NO3)2, Ni(NO3)2, and Zn (NO3)2 were dissolved in thedeionized water to obtain the preferred initialconcentration of solution [6]. The chosen initialconcentration of the heavy metal solutions was
10,000 mg/L. The properties of heavy metal solutions
are presented in Table 3.

1, 3, 6, 12, 24, 36, 48, 72, 96 and 120 hours. The
bentonite clay replaced with the bottom ash, fly ash
and cement at the amount of only 10% by weight was
selected to find the equilibrium time. The amountadsorbed of Ni, Cu and Zn at any time (qt) was
illustrated in Figs. 10 to 12 for bentonite mixed withcement, bottom ash and fly ash, respectively. It canbe seen in Fig.9 that the adsorption took place rapidly
at the beginning of the reaction which theconcentration rapidly decreased at the period of
48 hours. Thereafter, the amount adsorbed was almost
constant for all Ni, Cu and Zn. This was due to theadsorption sites which interaced with the metal
decreased. Thus, the adsorption of Ni Cu and Zn bybentonite mixed with cement reached to equilibrium
within 48 hours. Unlike the others soils, theequilibrium occurs approximately only within 3 hours.
The same trend of results was also found when
performing the tests with bottom ash and fly ash.

Table 3 Properties of heavy materials solution
Property

Nickel(II)
NitrateCopper(II) Nitrate

Zinc (II)
NitrateFormulaMolecular(g/mal)Density(g/cm3)
Solubility(g/100cm3)

Ni(NO3)2
290.80Cu(NO3)2
241.60Zn(NO3)2
297.50

2.05

2.32

2.06

94.20

137.80184.30EXPERIMENTAL WORKThe bentonite clay was replaced with the bottom
ash, fly ash and cement at the amount of 0, 10, 20, 30,
40 and 50% by weight. In this study, batch adsorption
test was carried out to investigate the heavy metal
adsorption. The test processes can be performed bymixing a 2.5 g of sample with the Cu, Ni and Zn
solutions [6]. The initial concentration of Ni(NO3)2,
Cu(NO3)2, and Zn(NO3)2 was 10,000 mg/L and put it
in 120 mL plastic bottle. Then the mixture was shaken
by the horizontal shaker with a speed of 150 cycles
per minute for 1, 3, 6, 12, 24, 36, 48, 72, 96 and 120
hours [7]. After reaching equilibrium time, the soil
was separated from the heavy metal solution by using
a 0.45µm filter and diluted it into the solution [6].
Finally, concentration of the residual solution was
analyzed by using Atomic Adsorption Spectrometer(Fig.9) which repeat three samples in one experiment
set in order to find an average value [8]. Finally, theresults can then be evaluated the adsorption capacity,
equilibrium times and adsorption isotherm. Factors
controlled in this study were mixing time,
temperature, and pH.

Fig.9 Atomic Adsorption Spectrometer (AAS)100% Adsorption

80

60

40

Ni
Cu
Zn

20

0

RESULT AND DISCUSSION

0

15

30

45

60

75

90

105

120

Contact time (hr)Equilibrium Time Determination
The equilibrium time is time from start
adsorption until being to equilibrium state. Samples
were determining equilibrium time by batch test at

Fig. 10 Effect of contact time of Ni, Cu and Zn
adsorption on bentonite clay mixed withcement at 10% by weight.
360

SEE - Nagoya, Japan, Nov.12-14, 2018

of 0, 10, 20, 30, 40 and 50% by weight. The effects ofthe three additional Pozzolanic materials on theadsorption capacity of Cu, Ni and Zn are presented in
Figs.13 to 15. As presented in Figs.13 to 15,
additional material especially cement candramatically improve the adsorption capacity ofheavy metals. The adsorption capacity increased withincreasing amount of cement content. While using
20% of cement in the replacement, the results showed
the maximum adsorption capacity of Ni, Cu and Zn.
It was possible to conclude that the proper amount of
cement which should be used to replace the bentonite
clay was 20% for increasing the adsorption capacityof Ni, Cu and Zn. In Fig.15, the results show that theadsorption capacity of Ni and Cu increased linearlywith amount of fly ash. No change in adsorption
capacity was found in the case of Zn. Unlike cement
and bottom ash, the results of bottom ash was shownin Fig. 14. Increasing the amount of bottom ash can
reduce the sorption capacity for all Ni, Cu and Zn. It
can be concluded that bottom ash is not recommended
to replace in the bentonite.

100

Ni
Cu
Zn

% Adsorption

80

60

40

20

0
0

15

30

45

60

75

90

105

120

Contact time (hr)Fig. 11 Effect of contact time of Ni, Cu and Zn
adsorption on bentonite clay mixed withbottom ash at 10% by weight.

100
100

Ni
Cu
Zn

80

% Adsorption% Adsorption

80

60

60

40

40

Ni

20

Cu

20

Zn
0
0
0

10

20

30

40

50

Ratio of cement (%)
0

15

30

45

60

75

90

105

120

Contact time (hr)Fig. 13 Effect of ratio between bentonite withcementFig. 12 Effect of contact time of Ni, Cu and Zn
adsorption on bentonite clay mixed with fly
ash at 10% by weight.

The material surface characteristic is an
important factor affecting on the adsorption capacity.
Figures. 5 to 8 display the SEM photographs ofmaterial samples with expansion rate of 500 times. It
can be seen that bentonite clay and cement show highroughness of their surfaces, while Bottom ash and fly
ash show the lower roughness. High surface ofroughness results in high surface area, and vice versa.
Thus, adsorption capacity of bentonite with cement
were higher than that of bottom ash and fly ash. The

The Best Ratio of Adsorbent Determination
Because the bentonite has very high adsorption
capacity, this soil was chosen as a representative of
all soils to find the method of improvement of theadsorption capacity. The bentonite clay was replacedwith the cement, bottom ash and fly ash at the amount361

SEE - Nagoya, Japan, Nov.12-14, 2018

bentonite with bottom ash provided the lowest
adsorption capacity because the specific surface area
and roughness were the important factors which
affected on the adsorption.

CONCLUSIONSIn this study, the adsorption capacities of Cu,
Ni and Zn by bentonite clay was investigated.
Further, the new method was introduced to improve
the adsorption capacity of the bentonite clay by
mixing the soil with cement, bottom ash and fly ash.
The results indicated that the adsorptions of thesematerials reache the equilibrium time withinapproximately 48 hours and higher than that ofnormal soils. The adsorption capacity of samples wasin the order of cement>fly ash>bottom ash. The
bentonite with bottom ash provided the lowest
adsorption capacity because the specific surface area
and roughness were the important factors which
affected on the adsorption. From the improvement of
the adsorption capacity only cement and fly ash canincrease the adsorption capacity of the bentonite clay.
Cement showed the highest performance for
improvement of Cu, Zn and Ni adsorption. The
recommended contents of cement was 20% by weightof bentonite clay.

100

Ni
Cu
Zn

% Adsorption

80

60

40

20

0
0

10

20

30

40

50

ACKNOWLEDGEMENTS

Ratio of bottom ash (%)

This research was support by Department ofCivil Engineering, Faculty of Engineering, Khon
Kean University.

Fig. 14 Effect of ratio between bentonite withbottom ash
100

REFERENCES
Ni
Cu
Zn

% Adsorption

80[1] Pollution Control Department, Ministry of Natural Resources
and Environment, Thailand State of Pollution Report, 2016.
[2] Saad A. Aljlil and Fares D. Alsewailem, Adsorption of Cu &Ni on Bentonite Clay from Waste Water, Athens Journal of
Natural & Formal Sciences., Vol. 1, No. 1, 2014.
[3] A.Dube, R. Zbytniewski, T. Kawalkowski, E. Cukrowska, and
B. Buszewski, Adsorption and Migration of Heavy Metals in
Soil, Polish Journal of Environment Studies, Vol. 10, No. 1,
2001,
pp. 1-10.
[4] Mohammad Kashif Uddin., A review on the adsorption ofheavy metals by clay minerals, with special focus on the past
decade., Chemical Engineering Journal., Vol 308, 2017, pp
438-462.
[5] Arnun Chantaduang, Influence of Pozzolanic Materials in The
Adsorption of Heavy Metals on soils, 2017, pp. 14-47.
[6] Noppadol Sangiumsak and Pongsakorn Punrattanasin,
Adsorption Behavior of Heavy Metals on Various Soils, Polish
Journal of Environment Studies, Vol. 23, No. 3, 2014, pp. 853865.
[7] Pongsakorn Punrattanasin and Noppadol Sangiumsak, The
Effect of Clay, Lime and Rice Husk Ash Contents on theSorption Capacity of Cu, Ni and Zn by Soils, Conference
proceedings, in Proc. 1st Int. Conf. on GEOMATE, 2011, pp.
263-267.
[8] Arwut Yimtae, Pongsakorn Punrattanasin and Noppadol
Sangiumsak., The Sorption Capacity of Cu by SC-Soil from
Batch and Column Tests, Conference proceedings, in Proc. 1st
Int. Conf. on GEOMATE, 2011, pp. 203-207.

60

40

20

0
0

10

20

30

40

50

Ratio of fly ash (%)

Fig. 15 Effect of ratio between bentonite with fly ash

362

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ADSORPTION OF ZINC ON BENTONITE CLAY MIXED WITHPOZZOLANIC MATERIALS BY COLUMN LEACHING TEST
1Pittaya Satiman, 2Pongsakorn Punrattanasin and 3Chinawat

1,2,3Muktabhant Faculty of Engineering, Khon Kaen University,

Thailand

ABSTRACTThis research mainly focuses on the adsorption of zinc on bentonite clay when mixing with various Pozzolanicmaterials by column leaching test. The Pozzolanic materials in this study consist of 1) fly ash, 2) bottom ash, 3)rice husk ash, 4) blast furnace slag, 5) silica fume, 6) metakaolin, and 7) cement. Only zinc was selected as animportant heavy metal that was found around the vicinity area of industry. Cycles of loop in column leaching test
were systematically done. The main cycles consist of releasing heavy metal solution to the example model andthen releasing distilled water to the model with continuous flow. This two steps can simulate the actual conditionof the discharge of zinc in waste water into the soil and washed it by rain. Cycle 3 was then carried out to verify
the adsorption capability after the desorption process. The adsorption behavior in this study can be illustrated in
the breakthrough curves. The breakthrough curve is a relationship between the rates of absorption versus service
time. In this study, bentonite mixed with cement shows the highest zinc adsorption performance.
Keywords: Bentonite clay, Adsorption, Column leaching test, Pozzolanic materials, Breakthrough curve
INTRODUCTION

MATERIALS USED

Rapid growth of industries has led to increase theenvironmental problem. Every years, large amount ofwaste water has been discharged into river without
treatment. The waste water often contaminated withheavy metals. These heavy metals may cause damage
to mankind and animals. There are many methods forremove the heavy metals from the waste water suchas a reduction process, magnetic ferrites treatment,
ion exchange, reverse osmosis, chemical oxidation,
membrane separation, coagulation, flotation,
filtration, adsorption and evaporation [1], [2], [3].
Adsorption is one of the most common methods forheavy metal removal. It offers benefits in terms ofavailability, simplicity of operation. Soils, especiallyclay, have been widely used as the adsorbents for thewastewater treatment. Because high efficiency andinexpensive, it motivates many researchers to doresearch with soils in the adsorption study [4], [5].
Several soils were previously selected as theadsorbent of batch and column adsorption tests. The
adsorption capacity of bentonite, one type of clay,
were primarily studied by the batch technique. In
batch sorption test, the results show the beneficial
evidence on adsorption capacity of the heavy metalson the bentonite. To understand details ofcontaminate flow, column leaching test could provide
the most practical way and can simulate closer to thecircumstances than the batch adsorption experiment.
The objective of this study is to investigate theadsorption capability of bentonite clay mixed withvarious Pozzolanic materials by the small-scalecolumn test. The purpose of adding the Pozzolanicmaterials into the bentonite is to relatively evaluate
the enhancement of sorption capacity.

Bentonite clay was selected as an adsorbent inthis study. The Pozzolanic materials used to mix withthe bentonite consist of 1) bottom ash (BA), 2) ricehusk ash (RHA), 3) blast furnace slag (BFS), 4) silica
fume (SF), 5) metakaolin (MK), 6) cement (CE) and7) fly ash (FA). The bentonite was replaced with the
Pozzolanic materials at the only amount of 50% by
weight. The chemical contents of the bentonite clay
and the Pozzolanic materials were verified by X-ray
fluorescence (XRF) and then summarized in Table 1.
Figures 1 to 8 display the SEM photographs of all
samples with a magnification rate of 3,000 times.
Heavy metals chosen as adsorbate in this research
was zinc (Zn). The properties of Zn solutions areshown in Table 2. The chosen initial concentration of
the zinc was 10,000 mg/L and this concentration ishigher than that of the use in other soils before due toits high sorption capacity of the bentonite.
Table 1 Chemical analysis of bentonite clay and the
Pozzolanic materials by XRF
Constituent% by weight

1

2

3

4

5

6

7

SiO2
56.8 20 48 37 92 90 55
Al2O3
15.1
5
26 11 0.7 0.5 40
Fe2O3
9.8
3
10 0.3 1.2
2
0.5
CaO
2.8
60
5
40 0.5 0.5
MgO
4.6
1.1
2
7
0.2 0.2SO3
2.4 0.7 0.3
1.5
Lol.
2
3
4.7
Where: 1 = Bentonite, 2 = Cement, 3 = Fly and bottom ash,
4 = Blast furnace slag, 5 = Silica fume, 6 = Rice husk ash,
7 = Metakaolin.

363

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig.1 SEM photograph of bentonite

Fig.5 SEM photograph of silica fumeFig.2 SEM photograph of bottom ash

Fig.6 SEM photograph of metakaolin

Fig.3 SEM photograph of rice husk ash

Fig.7 SEM photograph of cement

Fig.4 SEM photograph of blast furnace slag

Fig.8 SEM photograph of fly ash
364

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Properties of zinc solution
Property
FormulaMolecular (g/mal)Density (g/cm3)
Solubility (g/100cm3)

Compaction of adsorbent m=20g

Zinc (II) NitrateZn(NO3)2
297.502.06
184.30The soils were satuarated by R.O.
water

Simulate the condition of thedischarge of zinc in waste water
into the soil

EXPERIMENTAL WORKThe components of the column adsorption
apparatus are schematically shown in Fig. 9. PVC
tube with an internal diameter and height of 2.54 cm
was used as a fixed-bed column. The adsorbent withthe mass of 20g were compacted in the column before
conducting the flowing process. Three cycles of loop
in column leaching test were systematically done.
Cycles 1 and 2 consist of releasing heavy metal
solution to the example model and then releasing
distilled water to the model with continuous flow.
This two steps can simulate the actual condition of thedischarge of zinc in waste water into the soil andwashed it by rain. The main purpose of cycle 2 was toevaluate the desorption behavior. Cycle 3 was thencarried out to verify the adsorption capability after thedesorption process. The procedure of the column
adsorption is described in Fig.10.

Cycle 1:
Flow of influent in soil column
C0 = 10,000 mg/L
Q = 1 mL/min

Simulate the condition of washedby it by rain

Cycle 2:
Flow of R.O.water
C0 = 0.00 mg/L
Q = 1 mL/min

Pressure pump
Influent

Adsorption capability after thedischarge process.
Soil column

Cycle 3:
Flow of influent in soil column
C0 = 10,000 mg/L
Q = 1 mL/min

Effluent

Fig. 9 Schematic drawing of column leaching test
The flowing processes of each cycle were atleast finalized until the exhaustion period of theadsorbent. The flow rate of the influent was
designated to be equal to 1.0 mL/min. The pressure
pump was used to drive the pressure into the PVC
tube and to set at a constant flow rate. A chronometer
was employed to measure the service time (t) at
different collections of effluent. The effluent was
diluted with 1% of nitric acid (HNO3). Atomic
Absorption Spectrometer was used to measure theconcentration of the effluent. The concentration of theeffluents (Ct) could finally be identified.

All of collected effluents weretaken to findthe concentration analysis by AAS
Fig. 10 Procedure of column adsorption test
RESULTS AND DISCUSSIONSThe breakthrough time and the shape of the
breakthrough curve were significant features todefine the operation response of an adsorption
column [1], [3]. The typical breakthrough curve is365

SEE - Nagoya, Japan, Nov.12-14, 2018

represented by plotting between the service time (t)and the ratio of Ceffluent to Cinfluent (C/C0). The
breakthrough point and the point of the exhaustion ofcolumn of the breakthrough curve wascorrespondingly selected to be the point at which
C/C0 =5% and the point at which C/C0 =95%,
respectively. Figures 11 to 17 demonstrate the scurves (t -C/C0) representing the adsorption processof zinc on bentonite (B) when mixing with bottom ash(BA), rice husk ash (RHA), blast furnace slag (BFS),
silica fume (SF), metakaolin (MK), cement (CE) andfly ash (FA), respectively. Three consecutive cycles
of adsorption, desorption, and adsorption were
continuously illustrated.

1.0

C/C0

0.8
0.6
0.4
0.2
0.0
0

1000
2000
3000
Time (min)
B+BFS Cycly 1
B+BFS Cycly 2
B+BFS Cycly 3

1.0

C/C0

0.8

Fig. 13 Breakthrough curve of Zn on B+BFS

0.6
1.0
0.4
0.8
C/C0

0.2
0.0
0

1000
2000
Time (min)B+BA Cycly 1

3000

0.6
0.4
0.2

B+BA Cycly 2

B+BA Cycly 3

0.0
0Fig. 11 Breakthrough curve of Zn on B+BA

B+SF Cycly 1
B+SF Cycly 3

1.0
0.8
C/C0

1000
2000
Time (min)3000

B+SF Cycly 2

Fig. 14 Breakthrough curve of Zn on B+SF

0.6
1.0
0.4
0.8
C/C0

0.2
0.0
0

1000
2000
Time (min)B+RHA Cycly 1
B+RHA Cycly 3

3000

0.6
0.4
0.2

B+RHA Cycly 2

0.0
0

1000
2000
3000
Time (min)B+MK Cycly 1
B+MK Cycly 2
B+MK Cycly 3

Fig. 12 Breakthrough curve of Zn on B+RHA

366

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 15 Breakthrough curve of Zn on B+MK

have a higher volume of adsorption than that of otherPozzolanic materials.
The concentration of the effluent samples incycle II at the beginning of the flowing period wasfound positive. The zinc solutions were observed in
the effluents in the cases of bottom ash, rich husk ash
and metakaolin. It means that zinc ions were
removed by water in cycle 2. This could be due to thereversible process or desorption process of the ionson the adsorbent surface during the flow of the water.
Comparing the results of materials than can sustain
the leaching by water, it can be ranked as follows: ricehusk ash < silica fume < bottom ash < fly ash <metakaolin < blast furnace slag. For cement, nodetection of zinc is in the effluent. The progression of
the concentrations of the effluents in cycle III was
similar to the cycle I. In cycle 3 of fig. 16, the valueof concentration of zinc shows the continuous insorption of zinc. Mixing bentonite with cement
resulted in a more effective performance relative tousing other materials.

1.0

C/C0

0.8
0.6
0.4
0.2
0.0
0

1000
2000
3000
Time (min)B+CE Cycly 1
B+CE Cycly 2
B+CE Cycly 3
Fig. 16 Breakthrough curve of Zn on B+CE
1.0

CONCLUSIONS

C/C0

0.8

The results in this research study show theadsorption capability of bentonite clay mixed withseven Pozzolanic materials by using a small-scalecolumn leaching apparatus. The purpose of adding
the Pozzolanic materials into the bentonite is toenhance the capacity of the bentonite. The resultsfrom column test can be illustrated by thebreakthrough curves. High adsorption occurred in the
beginning of Cycle 1 was observed for some samples.
Thereafter, the adsorption decreased until it reachedto the saturated point. The leaching of zinc by water
occurred with a fractional volume. The breakthroughcurves representing the adsorption process ultimately
identified the adsorption behaviors. The desorption
process in cycle II could not fully remove the zincions from the surface of the adsorption. Cement
depicted great adsorption capacity comparing to otherPozzolanic materials.

0.6
0.4
0.2
0.0
0

1000
2000
Time (min)B+FA Cycly 1
B+FA Cycly 3

3000

B+FA Cycly 2

Fig. 17 Breakthrough curve of Zn on B+FA
The breakthrough curves were found in thecycle I for all samples. The results showed that theconcentration of the effluent in cycle I of rice husk
ash, silica fume and fly ash increased sharply after thestarting point and then reached the point of theexhaustion of column or it implies that bentonite
mixed with these three materials reached the saturated
point of adsorption or its highest sorption capacity.
The adsorption occurred with high volume in the
Cycle 1. For other cases, especially cement, theadsorption continues to increase with service times
but not reached the saturated point of adsorption. It
was observed that the S-shaped curves of adsorption
by using bottom ash and cement show the beneficial
effect of adding them into the bentonite. This two
curves demonstrate that the bottom ash and cement

ACKNOWLEDGEMENTS
This research was support by Department of Civil
Engineering, Faculty of Engineering, Khon Kean
University.
REFERENCES[1] Punrattanasin P., Sariem P., Adsorption of
Copper, Zinc, and Nickel using Loess as
Adsorbent by Column Studies, Pol. J. Environ.
Stud. 24, (3) 2015, pp.1267-1275.
[2] Martins T, Leitão TE, Carvalho MR. 2017.
Assessment of Wastewater Contaminants
Retention for a Soil-aquifer Treatment System
367

SEE - Nagoya, Japan, Nov.12-14, 2018

Using Soil-column Experiments. Procedia Earthand Planetary Science. 17(15), pp. 332–335.
[3] E.D. de Freitas 614 et al. 2018. Continuous
adsorption of silver and copper by Verde-lodo
bentonite in a fixed bed flow-through column
Journal of Cleaner Production. 171, pp. 613-621.
[4] JV Smart, Bentonite, Mineral Information

Leatlet No. 1, Department of Mines and Energy,
1999.
[5] Tsiridis V, Petala M, Samaras P, Sakellaropoulos
GP. 2015. Evaluation of interactions between
soil and coal fly ash leachates using column
percolation tests. Waste Manag. 43, pp. 255–263.

368

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECT OF INITIAL CONCENTRATION OF HEAVY METALS ON
THE ADSORPTION CAPACITY OF BENTONIRE CLAYMIXED WITH PORTLAND CEMENT
1Anunt Sirisombunphatthana, 2Pongsakorn Punrattanasin and 3Ratamanee
1,2,3Nuntasarn Faculty of Engineering, Khon Kean University, Thailand

ABSTRACTThis research study examined the influence of initial concentration of heavy metals that affect theadsorption capacity of nickel (Ni), copper (Cu) and zinc (Zn) on bentonite clay. The bentonite clay was widelyused as a waterproofing material in hazardous waste landfill. An idea of mixing between bentonite clay andPortland cement can increase the adsorption capacity was adopted in this study. The laboratory results can beclearly proofed from a series of batch sorption test. A varieties of initial concentration of Ni, Cu and Zn wereprepared in the study. The results showed that increasing in the initial concentration of heavy metals can reduce
the adsorption efficiency of the soil. The Langmuir Isotherm model was able to efficiently explain the adsorption
behavior of the bentonite clay. Adsorption capacities were ranked as follows: Cu > Ni > Zn.
Keywords: Heavy metals, Adsorption, Isotherm, Bentonite clay, Cement, Batch test

(Cu(No3)2), Nickel Nitrate (Ni(No3)2) and Zinc
Nitrate (Zn(No3)2) in distilled water. The solutions
were varied with initial concentrations. Table 2
summarized properties of Cu, Ni and Zn. Selection
were based on heavy metals that commonly found inindustrial wastes.

INTRODUCTION
Rapid growth of industries during many decades
has led to increase the environmental problems. It was
found that a large amount of waste waters, especiallyheavy metals, has been directly discharged fromindustrial factories into river without carefully
treatment. There are various methods for remove theheavy metals from the waste water [1, 2, 3].
Adsorption is one of the most common methods forheavy metal removal. It was proven that adsorption
by soils is an effective and economical technique [4].
The objective of this study is to investigate the effectof initial concentration of heavy metals on theadsorption capacity of bentonite clay mixed with
Portland Cement Type1. Cement used is easy to findand cheap. An idea of mixing between bentonite clay
and cement can increase the adsorption capacity was
also adopted in this study. The adsorptions were done
at very high initial concentrations ranging from 7,000
to 10,000 ppm.

Table 1 Chemical analysis of the bentonite clay andPortland cement by XRF technique
Constituent
SiO2
Al2O3
Fe2O3
MgO
Na2O
CaO

Bentonite Clay
Wt%
56.8
15.1
9.79
4.61
2.01
2.81

Cement
Wt%
20
5
3
60
1.1
2.4

Table 2 Properties of heavy metal solutions

MATERIALS USED
Because clay has the highest adsorption capacity
relative to other soils, bentonite clay was then chosen
and used as an absorbent in this study. To increase theadsorption capability, Portland cement type I was
added into the bentonite clay with the amount of 5%
by weight. Chemical analysis of the bentonite clay
and cement by XRF was shown in Table1. Figures 1
and 2 graphically show the SEM photographs withmagnification rates of 50, 500, 1,000 and 3,000 timesof bentonite clay and cement, respectively. Three
heavy metals chosen as the adsorbed materials in thisstudy were copper (Cu), nickel (Ni) and zinc (Zn).
They were prepared by dissolving Copper Nitrate

Property
FormulaMolecular(g/mal)Density(g/cm3 )Solubility(g/100 cm3)

369

Copper(II) Nitrate

Nickel (II)
NitrateCu(NO3)2
241.60Ni(NO3)2
290.80Zinc(II)
NitrateZn(NO3)2
297.50

2.32

2.05

2.06

137.8

94.20

184.30SEE - Nagoya, Japan, Nov.12-14, 2018

Fig.1 SEM photograph of bentonite

Fig.2 SEM photograph of cement370

SEE - Nagoya, Japan, Nov.12-14, 2018

EXPERIMENTAL WORK

Adsorption Isotherm Determination

Batch Sorption Test

The adsorption isotherm is the relationshipbetween the concentrations of heavy metal solutions,at equilibrium Ceq, and the amounts of heavy metals
adsorbed by the soil (q). The value of q can becalculated as follows:

In this study, batch tests were carried out toevaluate the adsorption capacity of three heavy
metals. The batch test processes can be performed bymixing the bentonite clay with heavy metals. The
initial concentrations used in the pilot test wereranged from 500 to 6,000 ppm and put it in 120 mL
plastic bottle. Then the mixture was shaken by thehorizontal shaker with a speed of 150 cycles per
minute for 48 hours. After a particular period of thetime, the soil was separated from the heavy metal
solution by using a 0.45µm filter and diluted it into
the solution. Finally, concentration of the residual
solution was analyzed by using Atomic Adsorption
Spectrometer (Fig.3). From the step above, it can bemeasured the percentage of adsorption. The suitable
initial concentration of heavy metals for main test canbe evaluated.
To find an appropriate initial concentration to use
with bentonite mixed with cement, the next series ofbatch sorption test was then carried out. The
bentonite weight of 2.375 g is mixed with 0.125 g of
cement. After that, a 5 0 ml of heavy metal solution
was then added to the soil sample. The samples werediluted with nitric acid after shaking. The initialconcentrations of heavy metals chosen were 7,000,
8,000, 9,000 and 10,000 ppm.

q=

( C − C )V
0

eq

sol

Ms

(1)

Where: q is the amount of adsorption of heavy metals
per unit weight within soil (mg/g), C0 is the initialconcentration of heavy metal solution (mg/l), Ceq isthe equilibrium concentration of the solutions (mg/l),
Vsol is the volume of solution (cm3) and Ms is the massof soil (g).
Percentage of adsorption can be calculated bythis equation.

%adsorption =(C0 − Ceq )
Ceq

x100

(2)

The adsorption isotherm is relationship between
concentration of heavy metal solution (Ceq) and theamount of heavy metals adsorbed by adsorbent (q).
Langmuir's adsorption isotherm (eq.3).

q=αβ Ceq1 + α Ceq

(3)

Where: q is the amount of adsorbent absorbed at 1 g(mg/g), Ceq is the concentration of the absorbent inliquid at equilibrium (mg/g), β is the maximum
amount of metal solution adsorbed on the amount ofabsorbable soil. (mg/g) and α is the adsorption
constant of Langmuir (l/mg). Figure 4 shows therelationship between all Langmuir adsorption
isotherm parameters.

Fig.3 Atomic Absorption Spectrometer
Equilibrium Time Determination
The equilibrium time is the time adsorption takes
to reach an equilibrium state. To determine theequilibrium time, the batch method was performed atvarious lengths of time, i.e. 0.5, 1, 3, 6, 12, 24, 36, 48,
and 72 hours, with a concentration of heavy metal
solutions at 7,000 ppm. By employing this method,
the concentrations of solutions at any time were
known, and so the adsorption equilibrium time could
be established.

Fig.4 Langmuir isotherm parameters
RESULTS AND DISCUSSIONS
Suitable initial concentration
The results of percentage of adsorption of Cu, Ni
and Zn at a concentration of 500 ppm on sand, clay
and bentonite clay were illustrated in Fig.5. It was
371

SEE - Nagoya, Japan, Nov.12-14, 2018

shown that bentonite has the highest capacity
compared to sand and clay. The 100% of adsorption
demonstrates that an initial concentration of 500 ppm
of heavy metals is not enough to use. The next seriesof pilot test was then carried out with various initialconcentrations ranging from 500 to 6,000 ppm. This
series only pure bentonite was selected to identify thesuitable initial concentrations. It was shown in Fig. 6that pure bentonite can adsorb 100% of Cu up to an
initial concentration of 3,500 ppm. The suggestion
from these results is that for bentonite mixed withcement, the suitable initial concentration higher than
6,000 ppm is recommended.

to 85.7% at the initial concentrations of 7,000 and
10,000 ppm, respectively. The same tends of results
were found in cases of zinc and nickel. It means that
increasing the initial concentration of heavy metals
can reduce the adsorption efficiency of the bentonite
mixed with clay. Adsorption capacities were ranked
as follows: Cu > Ni > Zn.

% Adsorption

Clay

Bentonite80% Adsorption

Ni

80

100
Sand

Cu

100

60
40

60

20

40

0
500

1000 1500 2500 3500 4500 6000

Initial concentration (ppm)
Fig.6 Percentage of adsorption with different initialconcentration of pure bentonite

20
0
Cu

Ni

Zn

100

Fig.5 The comparison on performance of sand, clay
and bentonite in the adsorption capability at 500
ppm of heavy metals

80

Equilibrium time for bentonite mixed with cement

60

Zn

Ct (mg/L)Ni

To find the effects of contact times, theadsorptions in bentonite mixed with cement samples
were investigated at different times. Figure 7 shows
the remaining concentrations, Ct of Cu, Ni, and Zn
solutions at any elapsed time. It can be seen that theconcentrations of solutions decrease rapidly,
especially during the first periods of 0-3 hours. After
that, they decline slowly, until they reach a constantwithin 48-120 hours. After that, the samples weresaturated, as a result of the accumulation of the metalson the bentonite and cement surface. It can beconcluded that the equilibrium times of Cu, Ni, andZn adsorption, by all their samples, occurred within
48-120 hours.

Cu

40
20
0
0

50

100

150

Time (hr)Fig.7 Effect of contact time on Cu, Ni and Zn
adsorption by bentonite mixed with cement
Figure 9 shows the adsorption isotherm of Cu, Ni
and Zn. As shown in 9, the amount of adsorption (q)increased linearly with increasing equilibrium
concentration (Ceq). The adsorption isotherm can be
represented by Langmuir adsorption isotherm asshown in Figs 10 and 12. The Langmuir isotherm
parameters can be calculated from the relationshipbetween concentration at equilibrium (Ceq) and theratio of Ceq/q by referring Fig.4. The consistency of
the isotherm describes well that the surface of

Effect of initial concentrations and adsorption
isotherm
The results of adsorption capacity with different
initial concentrations of heavy metals were plottedand shown in Fig.8. The sorption capacities of Cu by
bentonite mixed with cement were found that thepercentage of adsorption staring from 91.0 and reduce
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SEE - Nagoya, Japan, Nov.12-14, 2018

samples was covered with monolayer of the heavy
metal particles. Langmuir parameters (β and α) andthe coefficient of correlation (R2) were thencalculated and summarized in Table 3. Very highcoefficient of correlation (R2) from this model
indicated that the adsorption of Cu, Ni and Zn bybentonite-cement sample favorable fit to Langmuiradsorption isotherm. The maximum value of theadsorbed metal solution on the amount of absorbablesoil is represented by β-value. This value indicatesthe maximum amount of bentonite mixed withcement can absorb heavy metals. β=181.8 means that
1g of bentonite mixed with cement (19: 1 ratio) canabsorb copper as much as 181.8 mg. Comparing βvalues in Table 3, it can be concluded that adsorption
capacities of bentonite clay when mixing with cement
were ranked as follows: Cu > Ni > Zn.

83.0
66.4

71.7

60

Ceq/q

6
4
y = 0.0055x + 1.3408
R² = 0.814

2
0
600

1100
Ceq

1600

Fig.10 Langmuir's adsorption isotherm of Cu

66.2

88.4

85.7

68.2

67.2

61.7

30

63.4

25
y = 0.0062x + 8.0588
R² = 0.9175

40
20

Ca
Ni

20

Zn

15
1800

0
7000

8000

9000

10000

Concentretion (ppm)
Fig.8 The effect of initial concentration on theadsorption capacity

30

Ceq/q

Ni
Zn

3800

y = 0.007x + 3.787
R² = 0.9292

20
15

120

10
1200 1700 2200 2700 3200 3700
Ceq

100
80
0

Fig.9

3300

25

Cu

140

2800
Ceq

35

180
160

2300

Fig.11 Langmuir's adsorption isotherm of Niq%Adsorption

80

8

Ceq/q

79.1

10

35

91.0

100

12

1000

2000
Ceq

3000

4000

Fig.12 Langmuir's adsorption isotherm of Zn

Adsorption isotherm of Cu, Ni and Zn
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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 3 Parameters of Langmuir adsorption isotherm

CopperNickelZinc

αβ0.00410.00070.0018181.80162.29142.86ACKNOWLEDGEMENTS
This research was support by Department ofCivil Engineering, Faculty of Engineering, Khon
Kean University.

R2
0.81400.91750.9292

REFERENCES[1] Aar M., Mclaughlin M.J., Kirby J.K., Stacey S.P.
Adsorption and desorption of copper and zinc in
tropical peat soils of Sarawak, Malaysia.
Geoderma. 175, 59, 2012.
[2] Ijagbemi C.O., Baek M.H., Kim D.S.
Montmorillonite surface properties and sorption
characteristics for heavy metal removal from
aqueous solutions. J. Hazard. Mater. 166, 538,
2009.
[3] Bulut Y., Tez Z. Removal of heavy metals from
aqueous solution by sawdust adsorption. J.
Environ. Sci. 19, 160, 2007.
[4] Meena A.K., Kadirvelu K., Mishra G.K.,
Rajagopal C., Nagar P.N. Adsorption removal ofheavy metals from aqueous solution by treatedsawdust (Acacia Arabica). J. Hazard. Mater. 150,
604, 2008.

CONCLUSIONSIn this study, the adsorption capacity of Cu, Ni
and Zn on bentonite clay mixed with cement wasinvestigated by performing batch sorption test. The
results from batch test indicated that the equilibriumtimes of Cu, Ni, and Zn adsorption occurred within
48-120 hours. The suitable initial concentration
higher than 6,000 ppm is recommended in the batch
test for bentonite-clay sample. The adsorption
capacity slightly decreased with increasing initialconcentration of heavy metals. Langmuir isotherm
model can favorable and well describe the adsorptionof this sample. It can be concluded from β-values that
adsorption capacities of bentonite clay when mixing
with cement were ranked as follows: Cu > Ni > Zn.

374

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ADSORPTION CAPACITY OF HEAVY METALS ON ILLITE, KAOLINITE
AND MONTMORILLONITE CLAYS FROM BATCH TEST
1Keatniyom Teerawattanaparpha, 2Pongsakorn Punrattanasin and 3Dolrerdee
1,2,3Hormdee Faculty of Engineering, Khon Kaen University, Thailand

ABSTRACTThis study investigated and compared the adsorption efficiency of the various types of clay by adsorb
heavy metals. Three types of adsorbents were used are kaolinite clay, illite clay and montmorillonite clay. The
heavy metals used are adsorbed is copper (Cu). The equilibrium times of Cu by montmorillonite clay is occurred
within 70 hours. The method that used to test the adsorption efficiency is batch sorption test. The initialconcentrations of copper solution used were 500, 1,000, 2,000, 4,000 and 6,000 ppm. The results of this study
demonstrate that montmorillonite clay have the best adsorption efficiency, followed by illite clay and kaolinite
clay. Langmuir and Freundlich isotherm models can favourable describe the adsorption behaviour of clays. The
montmorillonite provided the highest adsorption capacity because of large specific surface area and roughness
which affected on the adsorption.
Keywords: Illite clay, Kaolinite clay, Montmorillonite cay, Batch test, Copper, Adsorption efficiency
consists of a two layers of silica floor with alumina
layer and in each unit there is an ion of potassium
inserted.
Thechemicalcompositionis(KH3O)(AlMgFe)2(SiAl)4O10[(OH)2(H2O)].
The
specific gravity is 2.60. Montmorillonite clay, its
structure like an illite group, but in the structurallayer there is a water molecule inserted. Most of thecations are found to be calcium, magnesium, ironand sodium. This clay has the ability to swell inwater well [4]. Figures. 4 to 6 display the SEM
photographs of clays with expansion rate of 1,000The
chemicalcompositionistimes.
(Na,Ca)(Al,Mg)6(Si4O10)3(OH)6·nH2O.The specificgravity is 2.0. In this research, copper (Cu) was
selected to represent the range of the common
heavy metal and prepared in the form of thesolution to be the adsorbates. The stock solutions of
Cu (NO3)2 were dissolved in the deionized water toobtain the preferred initial concentration ofsolution. The chosen initial concentrations of theheavy metal solutions were 500, 1,000, 2,000,
4,000 and 6,000 ppm. The properties of thesolutions are presented in Table 2.

INTRODUCTION
Nowadays, industrial factories are expanding.
As a result, the amount of pollution generated fromthe production process is increasing. Most of thepollution from the factory is usually heavy metals.
The factory have to treat those wastes by putting in
the wastewater treatment pond before releasing toenvironment. The all ponds have to construct withmaterials that have adsorption efficiency such as
clay to prevent contamination of environment. This
research mainly focuses on investigate theadsorption capacity of copper on clays. Copper(Cu) will greatly affect the organism [1] whether it
is human beings, animals or plant. Direct impact,
such as human contact with copper directly, it can
get into the body and get sick or maybe to death.
Indirect impacts such as human consumption of fishcontaining copper residue may make sick or maybe
to death. This research investigated the adsorption
efficiency of the various types of clay which havedifferent clay mineral compositions. Three types ofadsorbents are kaolinite, illite and montmorillonite
clays [2][3]. The heavy metal used in this study is
only copper. The batch sorption technique was used
as a method to evaluate the adsorption capacity.

Table 1 Chemical Analysis by XRF Technique
Type
SiO2
Al2O3
TiO2
Fe2O3
Na2O
K2O
CaO
MgO
LOI

MATERIALS USED
Three types of adsorbents are kaolinite (Fig.1),
illite (Fig.2) and montmorillonite (Fig.3) clays.
Table 1 summarizes the chemical analysis of theseclays by XRF technique. Kaolin clay consists oflayers of silica arranged alternately with layers ofalumina.
Thechemicalcompositionis
Al2Si2O5(OH)4. The specific gravity is 2.42 and thechemical analysis is given in Table 1. Illite clay
375

Kaolinite
58.0
31.0
<0.10
<0.5
2.0
0.5
0.3
0.5
11.0

Illite
79.5
14.5
<0.10
0.6
0.65
5.0
0.1
<0.02
3.5

Montmorillonite
56.80
15.10
9.79
2.01
2.81
4.61
-

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Properties of copper solution
Property
FormulaMolecular (g/mal)Density (g/cm3)
Solubility (g/100cm3)

Copper (II) NitrateCu(NO3)2
241.602.32
137.80Fig. 4 SEM photograph of illite clay.

Fig. 1 Illite clay.

Fig. 5 SEM photograph of kaolinite clay.

Fig. 2 Kaolinite clay.

Fig. 6 SEM photograph of montmorillonite clay.

EXPERIMENTAL WORK
Batch Sorption Test
The procedures of the batch testing begin bymixing 2.5g of each clay with 50cm3 of copper
solution in bottles. Next, the mixtures were shaken
at a velocity rate of 130 cycles per minute using a

Fig. 3 Montmorillonite clay.
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SEE - Nagoya, Japan, Nov.12-14, 2018

horizontal shaker. After a defined time, soils werepercolated from the copper solution using a 0.45µm
filter. The solutions were then diluted by mixing
them with 1% nitric acid. These steps were
performed at a room temperature of 30oC. The
diluted solution concentrations were finallydetermined using an Atomic Absorption
Spectrometer (Fig.7). Batch tests were repeatedthree times in each experiment for high accuracy of
the results. The purposes of doing batch test are toto identify an equilibrium time and to evaluate theadsorption isotherm.

Adsorption Isotherm
When the data between Ceq and q are plotted,
one can obtain what is called the adsorption
isotherm. The most commonly used models are theLangmuir and Freundlich isotherms. The Langmuiradsorption isotherm has been widely applied tomany adsorption processes, specifically thoseassuming monolayer adsorption on the adsorption
surface. The Langmuir isotherm is defined as:
αβ Ceq(3)
q=
1 + αCeq
Where: α is the Langmuir constant, related to thebonding energy between the adsorbed ion and theadsorbent (L/mg) and β is the maximum
adsorption capacity (mg/g). Figure 8 shows therelationship between Ceq and Ceq/q values of theLangmuir isotherm.
The Freundlich isotherm is the most common
isotherm model, used to describe physicaladsorption in a solid-liquids system and is defined
as follows:(4)
qe = K (Ceq )1 / n
Where: qe is the amount of adsorbed heavy metal
per unit weight of soil at equilibrium (mg/g), K is
Freundlich constant (mg/g) and 1/n is theadsorption intensity (dimensionless). Figure 9shows the relationship between Log Ceq and Log q
values.

Fig 7. Atomic Adsorption Spectrometer.
Determine the Adsorption Equilibrium TimeThe equilibrium time is the time adsorption
takes to reach an equilibrium state. To determine
the equilibrium time, the batch method was
performed with only montmorillonite clay various
lengths of time, i.e. 3, 6, 12, 24, 48, 72 and 120
hours, with a concentrations of copper solution at
6,000 ppm. By employing this method, theconcentrations of solutions at any time were
known, and so the adsorption equilibrium time
could be established.

Ceq /qy = mx + c1/β1

Adsorption Capacity

1/αβ

The percentage of adsorption was calculated byusing equation (1).
(C0 − Ceq )(1)%adsorption =
x100

Ceq

Fig 8. The relationship between Ceq and Ceq/q
values of the Langmuir isotherm.

Ceq

Where: C0 and Ceq are the equilibrium
concentration of adsorbate in copper solution
before and after adsorption. The amount of copper
solution that adsorbed by the adsorbent wascalculated by equation (2).
(C0 − Ceq ) V(2)
q=

RESULTS AND DISCUSSIONS
Equilibrium TimeTo find the effect of contact times, the copper
adsorptions in montmorillonite clay were
investigated at different times. Figure 10 shows thepercentage of the adsorption of Cu solutions at any
elapsed time. It can be seen that the percentage ofadsorption increases rapidly, especially during thefirst periods of 20 hours. After that, it increases

M

Where: q is amount of copper solution that
adsorbed by the adsorbent, C0 and Ceq are theequilibrium concentration of adsorbate in copper
solution before and after adsorption, V is thevolume of copper solution and M is the volume of
clay.
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SEE - Nagoya, Japan, Nov.12-14, 2018

slowly, until reaching a constant within 70 hours.
After that, the montmorillonite clay were saturated,
as a result of the accumulation of the copper on thesurface. It can be concluded that the equilibriumtimes of Cu by montmorillonite clay, occurred at 70
hours.

100

Kaolinite% Adsorption

Log q

60

57.20
45.00

40

31.30
25.80
25.03
18.49 14.3018.70

20

y = mx + c

250

500

750

1000

2000

Initial concentration (ppm)n

Fig 11. Adsorption of copper solution withkaolinite and illite clays.

Log k

Log Ceq100

Fig 9. The relationship between Log Ceq and Log q
values of Freundlich isotherm.
Adsorption (%)

80
77.33 81.60

85.49

84.74

98.05

95.78

Montmorillonite
93.69

95

100

% Adsorption

11.20
7.41

0

1

60

Illite

80

90

87.52
84.17

85
80

55.61
75

40

500

36.14

1000

2000

4000

6000

concentration (ppm)

26.42
20
0

Fig 12. Adsorption of copper solution withmontmorillonite clay.

0.12
0

50

100

150

Adsorption Isotherm

Time (hr)Fig 10. Adsorption of copper solution withmontmorillonite clay at various times.

The amounts of adsorbed copper, q and theequilibrium concentrations, Ceq are plotted in Figs.
13 and 14. These called the adsorption isotherm. It
can be seen that the amount of adsorption increased
with equilibrium concentrations. The increasingrate of the amount adsorbed tends to gradually
decrease, and converge to the maximum value. The
Langmuir and Freundlich adsorption isotherms
were adopted to describe the isotherm. Figures 15
to 17 show the Langmuir isotherm and figs. 18 to
20 show the Freundlich isotherm of all clays.
Adapted from Figs. 8 and 9, the importantparameters of both models can be calculated.
Tables 3 and 4 show the parameters of theLangmuir and Freundlich isotherms. Higher valuesof R2 (almost all higher than 0.95) indicate thatboth models can accurately describe the adsorption
isotherm. The β-parameters of the Langmuir
isotherm represent the maximum adsorption
capacity of clays. It can clearly be seen in Table 3that the montmorillonite displayed the highest

Adsorption Capacity
The batch sorption test with illite, kaolinite
and montmorillonite clays were performed atvarious initial concentrations of 500, 1,000, 2,000,
2,000, 4,000 and 6,000 ppm. The relationshipbetween percentage of adsorption and initialconcentrations of are presented in Figs.11 and 12.
Montmorillonite clay shows the beneficial trend in
the adsorption capacity of heavy. At a particular
initial concentration, the adsorption capacity ofmontmorillonite is higher than illite and kaolinite
approximately 10 and 15 time, respectively. The
adsorption capacity of clays was in the order ofmontmorillonite> illite> kaolinite.

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SEE - Nagoya, Japan, Nov.12-14, 2018

adsorption capacity, while kaolinite provided thelowest adsorption capacity. The important factor
affecting the value of β was specific surface area of
illite, kaolinite and montmorillonite, which can beevaluated using SEM picture. Figures 4 to 6 display
photographs of samples using SEM at 1,000x
magnification. As shown in Fig. 6, the surfaces ofthe montmorillonite are rougher and larger thanillite and kaolinite.

Ceq/q (mg/g)

500

y = 0.2104x + 30.546
R² = 0.9919

400
300
200
100

Illite
0
0

500

1000

1500

2000

Ceq (mg/L)

5

Kaolinite

IlliteFig 16. Langmuir isotherm of illite clay.

4

10
3

Ceq/q (mg/g)

q (mg/g)

12

2
0

500

1000

1500

2000

y = 0.0086x + 1.8211
R² = 0.9513

8
6
4
2

Ceq (mg/L)

Montmorillonite00

Fig 13. Isotherm graph of kaolinite and illite clays.

200

400

600

800

1000

Ceq (mg/L)
120

Fig 17. Langmuir isotherm of montmorillonite
clay.

100

q (mg/g)80

Table 3 Parameters of Langmuir adsorption
isotherm
Clay
α
β
R2
-2
Kaolinite
1.69x103.06
0.999
Illite0.69x10-2
4.75
0.992
Montmorillonite 0.47x10-2 116.28
0.951

60
40

Montmorillonite
20
0
0

200

400

600

800

1000

Ceq (mg/L)
0.50

Log q (mg/g)

Fig 14. Isotherm graph of montmorillonite clay.

0.45

700

Ceq/q (mg/g)

600

y = 0.3273x + 19.363
R² = 0.9999

500

y = 0.1096x + 0.1267
R² = 0.9506

0.40

400

0.35

300

Kaolinite

200

0.30
2.00

100

2.50

3.00

Log Ceq (mg/L)

Kaolinite

0
0

500

1000

Ceq (mg/L)

1500

2000

Fig 18. Freundlich isotherm of kaolinite clay.

Fig 15. Langmuir isotherm of kaolinite clay.
379

3.50

SEE - Nagoya, Japan, Nov.12-14, 2018

were the important factors which affected on theadsorption. Montmorillonite clay can adsorb all ofcopper solution at 500, 1,000 and 2,000 ppm. But it
can adsorb 94.96% and 84.17% at 4,000 and 6,000
ppm.

0.70

Log q (mg/g)

0.65
0.60

y = 0.1617x + 0.1143
R² = 0.9332

0.55

ACKNOWLEDGEMENTS
0.50

This research was support by Department ofCivil Engineering, Faculty of Engineering, Khon
Kean University.

0.45

Illite
0.40
2.00

2.50

3.50

3.00

Log Ceq (mg/L)
REFERENCES
Fig 19. Freundlich isotherm of illite clay.

Log q (mg/g)

3

y = 0.5112x + 0.477
R² = 0.9979

2

1Montmorillonite
0
0

1

2

3

4

Log Ceq (mg/L)
Fig 20. Freundlich isotherm of montmorillonite
clay.
Table 4 Parameters of Freundlich adsorption
isotherm
Clay
Kaolinite
IlliteMontmorillonite

k
1.32
1.30
2.99

1/n
0.11
0.16
0.51

R2
0.951
0.933
0.998

CONCLUSIONSIn this study, the adsorption capacity of Cu on
three types of clay were investigated. Three typesof adsorbent were used are kaolinite clay, illite clay
and montmorillonite clay. The results indicated thatthe adsorption reaches the equilibrium time within
70 hours. The adsorption capacity increased withincreasing equilibrium concentration. Langmuir
and Freundlich isotherm models can favorable
describe the adsorption. Montmorillonite clays
have the best adsorption efficiency, followed byillite clay and kaolinite clay, respectively. The
kaolinite provided the lowest adsorption capacity
because the specific surface area and roughness
380[1] Zhiqiang W., Chen H., Yi X., Kang W., Yifei
L., Lihui F., and Silu M., Spatial distribution
and sources of heavy metals in natural pasturesoil around copper-molybdenum mine inNortheast
China.,
Ecotoxicology
andEnvironmental Safety., Vol 154., 2018, pp
329-336.
[2] Di L., Mansour E., and Luke B., Investigating
the settling behaviour of saline tailingsuspensions using kaolinite, bentonite, andillite clay minerals., Powder Technology., Vol
326., 2018, pp 228-236.
[3] Joanna M., Marta K., AnnaBiałk B., Wojciech
M., Jolanta K., Piotr S., Richard P., Oliver K.,
and Ute K., Column and batch tests ofsulfonamide leaching from different types ofsoil., Journal of Hazardous Materials., Vol
260, 2013, pp 468-474.
[4] Tetsuo Y., YukariImotoa K., Masayuki S.,
Kazuo H., Ute K., and Hirofumi S., Effects ofcolloidal particles on the results and reproducibility of batch leaching tests for heavy
metal contaminated soil ., Vol 57., Issue 5,2017, pp 861-871.

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ADSORPTION CAPACITIES OF HEAVY METALS TO SAND MIXEDWITH SODIUM BENTONITE USING BATCH SORPTION TESTS

1Yuttapong Chaipanha, 2Pongsakorn Punrattanasin, 3Dolrerdee Hormdee and 4Chinawat
1,2,3,4Muktabhant Faculty of Engineering, Khon Kaen University, Thailand.

ABSTRACT
Heavy metals are some of the most dangerous materials. A method to reduce the occurrence of heavy metals
involves the adsorption of materials by using absorbents. This research focused on the adsorption of copper, nickel,
and zinc to sand when mixed with different ratios of sodium bentonite. Batch sorption tests were performed toinvestigate adsorption behavior. The purpose of using batch tests was to find the adsorption capacities of the sandmixed with bentonite. The test results show that the adsorption of heavy metals to sand increases with the amountof sodium bentonite. Sand benefited from the bentonite. Adsorption capacities were ranked as follows: copper >nickel > zinc.
Keywords: Heavy metals, Sodium bentonite, Batch sorption testof 110o C for 48 hours and were sieved through sieve
No.16. It can be classified by the Unified Soil
Classification System (USCS) as Clayey Sand (SC).
Basic and engineering properties of the sand sample
are tabulated and shown in Table 1.

INTRODUCTION
Today's society is competitive and progressive inmany sides, both technology and economic growth.
As a result, the expansion and establishment ofindustrial plants are increased. The establishment of
more factories. These plants are the main cause ofpollution in various forms such as air, water, and soil,
especially waste water. When someone consumes acontaminated water source, a heavy metal solutionconsequently centers into the body that may cause ahealth problem. Therefore, the plant needs to protectthese heavy metals [1, 2]. One method to reduce theoccurrence of heavy metals is to use septic pond. In
the septic pond construction, absorbent materials areneeded to absorb heavy metals in the bottom of thepond. One needs to prevent the toxins moving out
from the wastewater into the groundwater below.
There are many recent research works [4] on theadsorption capacity of heavy metals by various soils.
It was shown that clay was the most efficientadsorption material. In this research, sodium
bentonite, one type of clay, is then selected and used
to mix with sand with various mixing ratios. The
main objective of this study is to evaluate thebeneficial effect of bentonite in the improvement of
the adsorption capacity to the sand.

Additional Materials
Because clay has the highest adsorption of heavy
metals, the additional material used to mix with thesand for improve the adsorption capacity in thisstudy was sodium bentonite, a one kind of clay. The
sodium bentonite was replaced with the sand at theamount of 0, 10, 20, 30 and 40% by weight. The
composition of the mineralogical and chemical ofsand and sodium bentonite determined by X-Ray
Fluorescence (XRF) are tabulated in Table 2.
Figures. 1 and 2 display the SEM photographs ofsand and the bentonite with expansion rate of 500
times, respectively.

Table 1 Properties of sand
Properties
Soil classification (USCS)
Specific gravity
Natural dry unit weight (kN/m3)
Natural water content (%)
Optimum moisture content (%)
Maximum dry unit weight (kN/m3)
Coefficient of Permeability (cm/s)
Specific surface area (SBET), m2/g
Micropore volume (VDR), cm3/g
Total pore volume (VT), cm3/g
Average pore diameter (DP), nm

MATERIALS USED
Adsorbent
The material used as an adsorbent was local
sand collected from Khon Kaen Province that is
located in the upper part of Northeastern region ofThailand. It was excavated at a depth of 50 cm fromthe soil surface. The sand was dried at a temperature
381

Sand
SC
2.62
16.30
5-12
10.0
19.1
1.46 x 10 -5
54
0.021
0.11
8

SEE - Nagoya, Japan, Nov.12-14, 2018

ppm. The purpose of varying the initialconcentrations is to obtain a suitable concentration
for sand and bentonite in the next series. Finally, thechosen initial concentration of the heavy metal
solutions in this study was 6,000 ppm. Table 3
summarized properties of heavy metals.

Table 2 Compound composition (% by weight)
Items
SilicaMagnesia
Alumina
Iron Oxide
Lime
Sodium

Sand
99.80
0.10
0.04
0.02
0.02
-

Bentonite
56.80
4.61
15.10
9.79
2.81
2.01

Table 3 Properties of heavy metal solutions
Property

Nickel(II)
NitrateCopper(II) Nitrate

Zinc (II)
NitrateFormulaMolecular(g/mal)Density(g/cm3)
Solubility(g/100cm3)

Ni(NO3)2
290.80Cu(NO3)2
241.60Zn(NO3)2
297.50

2.05

2.32

2.06

94.20

137.80184.30EXPERIMENTAL PROCEDURE
Batch sorption test
The procedures of the batch sorption testing
began by mixing 2.5 g of mixed sample with 50 cm3of heavy metal solutions in bottles. Next, themixtures were shaken at a velocity rate of 150 cycles
per minute using a horizontal shaker (Fig.3). After adefined time, solid particles were percolated fromthe heavy metal solutions by using a 0.45 μm filter.
Then the solutions were diluted by mixing them with
1% nitric acid (HNO3). These steps were performed
at a room temperature of 25 oC. Finally, the diluted
solution concentrations were determined using an
Atomic Absorption Spectrometer (AAS) with theflame method. Figure 4 shows the AAS machine.

Fig. 1 SEM photograph of sand

Equilibrium time of adsorption determination
The equilibrium time of adsorption is the time
adsorption takes to reach an equilibrium state. To
determine the equilibrium time, the batch sorption
method was performed at various lengths of time, i.e.
1, 3, 5, 12, 24, 48, 72, and 120 hours, withconcentrations of heavy metal solutions at 6,000
ppm. By employing this method, the concentrationsof solutions at any time were known, and then theadsorption equilibrium time could be established.

Fig. 2 SEM photograph of bentonite
Heavy metal solutions
Heavy metals chosen as the adsorbed materials
in this study were Cu, Ni and Zn. Selection of heavy
metals was based on its low toxicity, easily found in
all areas and commonly discharged from various
industries. They were prepared by dissolving Copper
Nitrate (Cu(No3)2), Nickel Nitrate (Ni(No3)2) andZinc Nitrate (Zn(No3)2) in distilled water. In pilot
tests, the solutions were varied with concentrationsof 500, 1,000, 1,500, 2,500, 3,500, 4,500 and 6,000

Volume adsorption determination.
Determination of adsorption capacity ofheavy metals is based on the amount of heavy metals
remaining in the solution. The remaining
concentration is then used to convert the percentageof adsorption by using eq.(1).

382

SEE - Nagoya, Japan, Nov.12-14, 2018

( C0 - Cr ) x100
% adsorption =were then shaken at 130 rpm for 48 hours by using ahorizontal shaking machine. After that, theexperiment was the same as batch adsorption test.

(1)
0
Where: C0 is an initial concentration and Cr is theremaining concentration in the solution.
C

RESULT AND DISCUSSION
Suitable initial concentration of heavy metals
Varieties of initial concentration of heavy metal
solutions were well prepared in laboratory. The
chosen initial concentrations of 500, 1,000, 1,500,
2,500, 3,500, 4,500 and 6,000 ppm were then tested.
The percentage of adsorption for all Cu, Ni and Zn
are summarized and shown in Table 4 and Fig.5. The
results show that the initial concentrations up to
3,500 ppm, Cu can completely adsorb by mixed
sample. An initial concentration of 6,000 ppm wasthen chosen for the next series of batch sorption test.

Table 4 the adsorption capacity at different initialconcentrations
InitialConcentration
(ppm)
500
1,000
1,500
2,500
3,500
4,500
6,000

Fig. 3 shaker

100% Adsorption
Cu

Ni

Zn

100.00100.00100.00100.00100.00
92.53
85.10

71.17
82.55
78.49
76.09
78.33
73.44
68.95

85.23
98.45
100.00100.00
90.66
91.38
86.03

Cu

Ni

Zn

% Adsorption

80

Fig. 4 Atomic Absorption Spectrophotometer
(AAS)

60
40
20
0

Effect of bentonite content on the adsorption
capacity of sand500 1,000 1,500 2,500 3,500 4,500 6,000
Initial concentration (ppm)

The sodium bentonite was mixed with sandwith different contents. The bentonite contents werestarting from 10% up to 40% by weight. Heavy
metals used in the experiment were the same as in
the previous section. A constant mass of oven soil
powder of 2.5g, percentage of bentonite by weight ofsand and 50 mg/L of metal solution were added into
a set of 120 ml plastic bottles. The soil solution ratios

Fig. 5 The comparison of adsorption capacity forheavy metals at different initial concentrations
Equilibrium time of adsorption
To find equilibrium time of adsorption, aseries of batch adsorption test in sand with sodium
bentonite were investigated at different times.
383

SEE - Nagoya, Japan, Nov.12-14, 2018

Figures 6 to 8 show the volume adsorption of Cu, Ni,
and Zn solutions at any elapsed time. It can be seenthat the volume adsorption increase rapidly,
especially during the first periods of time (0-5
hours). After that, they increase slowly. The
adsorption of Cu, Ni and Zn by sand mixed withbentonite finally reached to equilibrium at about 48
hours. Unlike the others soils, the equilibrium occurs
approximately only within 3 hours [4].

bentonite in the replacement, the results in Table 5
showed that the adsorption capacity of Cu, Ni and Zn
are 16%, 19% and 17%, respectively. In case of Cu,
the adsorption capacity of sand reached 46% ofadsorption when 40% of bentonite was used in thereplacement. The same tends of results were also
found with Ni and Zn. Table 6 summarizes thecalculated percentage of adsorption improvement
when adding the sodium bentonite to sand. It can beseen that all the heavy metals especially Zn and Cu
the adsorption capacity can improve up to 700%
compared to pure sand by only adding 40% ofbentonite to the sand. From Table 6 it can beconcluded that the percentage of adsorption
improvement when adding the bentonite to sandwere ranked as follows: zinc> copper > nickel.

25

15
25

10

20

5
% adsorption% adsorption

20

0
0

50

100

150

Time (hr)Fig. 6 the equilibrium time for Cu.

15
10
5
0

25

0

50

150

Time (hr)20% adsorption

100

Fig. 8 the equilibrium time for Zn.

15
10

46

50

5

40
0

50

100
Time (hr)% adsorption

0150

Fig. 7 the equilibrium time for Ni.

32
27

30
16

20
10 7

Effect of bentonite content on the adsorption
capacityy = 0.9352x + 6.9311
R² = 0.9871

0

The effect of the bentonite content on theadsorption capacity of Cu, Ni and Zn are presented
in Figs. 9 to 11, respectively. As presented in Figs.9
to 11,
bentonite can dramatically improve theadsorption capacity of sand. The adsorption capacity
increased linearly with increasing amount ofbentonite content. While using 10% of sodium

0

10
20
30
40
Sand-bentonite ratio (%)

Fig. 9 Percentage of adsorption for Cu.

384

50

SEE - Nagoya, Japan, Nov.12-14, 2018

replacement in cases of Cu, Ni and Zn, respectively.
Adsorption capacities were ranked as follows:
copper> nickel> zinc but the percentage ofadsorption improvement when adding the bentonite
to sand were ranked as follows: zinc> copper >nickel.

50% adsorption

40

34
28

30

29

19

20

Table 5 Percentage of adsorption for Cu, Ni and Zn

11

10

Sandbentonite
ratio
0
10
20
30
40

y = 0.5514x + 13.078
R² = 0.9397

0
0

10
20
30
40
Sand-bentonite ratio (%)

50

Fig. 10 Percentage of adsorption for Ni.

40% adsorption

Cu

Ni

Zn

7
16
27
32
46

11
19
28
29
34

4
17
25
28
32

Table 6 The percentage of adsorption improvement
when adding the bentonite to sand50

Sandbentonite
ratio
10
20
30
40

32
25

30

28

17

20
10

% Adsorption

Percentage of improvement
Cu

Ni

Zn

128.57285.71357.14557.1472.27
154.54163.63209.09325.00325.00525.00700.00y = 0.692x + 7.3188
R² = 0.9222

4

ACKNOWLEDGMENT

0
0

10
20
30
40
Sand-bentonite ratio (%)

50

This research was funded by Department of Civil
Engineering, Faculty of Engineering, Khon Kaen
University.

Fig. 11 Percentage of adsorption for Zn.
REFERENCES
CONCLUSIONS[1] Eveliina Repo, Jolanta K. Warchoł, Amit Bhatnagar,
and Mika Sillanpää, Heavy metals adsorption by
novel EDTA-modified chitosan–silica hybridmaterials, Journal of Colloid and Interface Science
358, 2011, pp. 261-267.
[2] Sariem Panha and Punrattanasin Pongsakorn.
Adsorption of Copper, Zinc, and Nickel Using Loessas Adsorbents. Polish Journal of Environmental
Studies No. 24, 2015, pp. 319-326.
[3] Shengtao Xing, Meiqing Zhao, and Zichuan Ma,
Removal of heavy metal ions from aqueous solution
using red loess as an adsorbent, Journal ofEnvironmental Sciences 23(9), 2011, pp. 1497-1502[4] Sangiumsak
NoppadolandPunrattanasin
Pongsakorn. Adsorption Behavior of Heavy Metals
on Various Soils. Polish Journal of Environmental
Studies No. 23, 2014, pp. 853-865.

This research presents the adsorption capacity ofheavy metals on sand which can be found in common
everywhere. A possible method of improving theadsorption to sand is proposed by adding and mixing
the sodium bentonite content into the original sand.
From batch sorption test, it was found that theadsorption reaches the equilibrium time at about 48
hours for the initial concentration of Cu, Ni and Znof 6,000 ppm. Unlike the others soils, theequilibrium occurs approximately only within 3
hours. The adsorption capacity increased linearlywith increasing bentonite content. The adsorption
capacity of sand reached 46%, 34% and 32% of
adsorption when 40% of bentonite was used in the385

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

OPTICAL RESPONSE ANALYSIS OF InGaAs HIGH-ELECTRONMOBILITY TRANSISTORS WITH A 1550-nm WAVELENGTH
FEMTOSECOND PULSE LASER
1Taiki Kozakai, 2Itsuki Takagi, 3Shun Nakajima, and 4Hirohisa Taguchi
1,2,3,4Department of Electrical and Electronic Engineering, School of Engineering, Chukyo University, 101-2

Yagoto Honmachi, Shouwa-Ku, Nagoya City, Aichi, Japan
ABSTRACTInGaAs is known as a material system with high electron mobility derived from InAs and can be formed by metalorganic chemical vapor deposition. The base material substrate is InP and is formed by controlling the composition
ratio of In and Ga to lattice match with this InP. The bandgap energy Eg of InGaAs is 0.87 eV, and photoelectric
conversion of 1550-nm light, which is a communication wavelength band, can be executed. Therefore, it is now
used as a detector material in optical communication technology. In this study, we investigated the photoresponsive
properties of InGaAs high-electron-mobility transistors (HEMTs) with simultaneous utilization of photoresponse
characteristics and high-frequency response characteristics of this InGaAs crystal. A 1550-nm wavelength
femtosecond pulse laser (with a pulse width of 100 fs and a period of 50 MHz) was coupled with DC light with awavelength of 1480 nm and irradiated from the InGaAs HEMT metal electrode surface. Laser light transmitted
through the side of the gate metal electrode into the device structure generates electron–hole pairs via thephotoelectric effect in the InGaAs layer, and it was confirmed that the maximum drain current of 0.4 mA was
reduced. A current response is detected inside the semiconductor by transporting electrons to the drain electrodeside and holes to the source electrode side. Because the laser used is pulsed light, the process of generation anddisappearance of electron–hole pairs was confirmed as photoresponsive properties. These results suggest that
InGaAs HEMTs may function not only as electronic response devices but also as photoresponsive devices.
Keywords: InGaAs HEMT, Photoresponsive property, Photoelectric effect, Hole accumulation effect
INTRODUCTION
GaAs is an indispensable material in our current
advanced information society [1]. It is used as a basematerial of key devices for transmitting and receiving
packet communications in mobile terminals. Because
GaAs is used for transmitting and receiving devices,
the operating frequency has been dramatically
expanded [2]. However, because of the demand forincreasing amounts of information, further increases
in transmission and reception speeds are required, andsituations where it is difficult to use GaAs areapproaching [3]. It is essential to develop newmaterial systems. InGaAs, a ternary material, hasbeen a subject of focus for a long time [4]. InGaAs is
known as a material system with high electron
mobility derived from InAs and can be to be formedby metal organic chemical vapor deposition [5]. Thebase material substrate is InP and is formed bycontrolling the composition ratio of In and Ga tolattice match with this InP. The bandgap energy Eg of
InGaAs is 0.87 eV, and photoelectric conversion of1550 nm light, which is a communication wavelengthband, can be executed [6]. Therefore, it is now used
as a detector material in optical communication
technology [7].
In this study, we investigated the photoresponsive
properties of InGaAs high-electron-mobility

transistors (HEMTs) with simultaneous utilization ofphotoresponse characteristics and high-frequency
response characteristics of this InGaAs crystal. A
1550-nm wavelength femtosecond pulse laser (with apulse width of 100 fs and a period of 50 MHz) was
coupled with a DC light with a wavelength of 1480
nm and irradiated from the InGaAs HEMT metalelectrode surface. Laser light transmitted through theside of the gate metal electrode into the device
structure generates electron–hole pairs by thephotoelectric effect in the InGaAs layer. The
significance of this research is the possibility of
HEMT which is an active device to be passive device.

Fig. 1 Schematic cross section of a HEMT.
386

SEE - Nagoya, Japan, Nov.12-14, 2018

DUT

0.02

VDS

Maxmam Gate Voltage: -0.1V
step:-0.1V

Infrared
Microscope
Beam Splitter

DUT Signal Line
Vector Network Analyzer
Anritsu MS4644B
Triger Line
Femto Second Pulse Laser

Optical Coupler

CW LaserPower Meter

Source-Drain Currnt, Ids [A]Bias Tee

h

0.015

0.01

0.005

Single Mode Fiber

0
0

0.2
0.4
0.6
0.8
Sourcs-Drain Voltage, Vds [V]1Fig. 2 Measurement block diagram.

Fig. 3 DC characteristic of an InGaAs HEMTA current response is detected inside thesemiconductor by transporting electrons to the drainelectrode side and holes to the source electrode side.
Because the laser used is pulsed light, the process ofgeneration and disappearance of electron–hole pairs
was confirmed as photoresponsive properties. These
results suggest that InGaAs HEMTs may function not
only as electronic response devices but also as
photoresponsive devices.

lasers were polymerized with an optical coupler, andthe light intensity was controlled by the direct lightintensity. The multiplexed light was split by the
optical splitter into an output of 10:90. The 10%
output was monitored with a light intensity meter andthe remaining 90% was converted to a parallel-platebeam via a drum lens. The incident light output waschanged by CW laser. The top of the InGaAs HEMTelectrode was irradiated via an aerial transition
process and the photoresponsive characteristics wereconfirmed. For the measurement, a network analyzer
at the 40-GHz level (Anritsu MS4664B) was used.
Single-mode fiber was used for the light transmission
path. For the high-frequency-response measurement,a 40-GHz-level adaptation system was used.

EXPERIMENTAL METHOD
Figure 1 shows the crystal structure cross sectionof the InGaAs-based HEMT used in this study. The
current frequency band of InGaAs is at the 12-GHzlevel, and it is intended for satellite communication.
Therefore, the mounting line was a micro split linewith a coplanar structure. Figure 2 shows themeasurement block diagram. An AF4B125 laser(Anritsu Corporation) was used as a direct current
laser. The femtosecond pulse laser (Karma
Corporation) had a pulse width of 100 fs, a period of
50 MHz, and an average output of 20 mW. These two

RESULTS AND DISCUSSION
DC Characteristics of InGaAs HEMTs
Figure 3 shows the DC current–voltage
characteristics (IV characteristics) of the InGaAs
HEMT used this time. As is clear from the IV
characteristics, the HEMT used in this study is of

1

1
0.8

0.6

Capacitance (pF)

0.8

Capacitance (pF)

0mW-|Cgd|
50mW-|Cgd|
72mW-|Cgd|
90mW-|Cgd|

0mW-|Cgs|
50mW-|Cgs|

0.4

72mW-|Cgs|
90mW-|Cgs|

0.1

0.4
0.2

0.2
0
0.01

0.6

1

Frequency (GHz)

0
0.01

10

0.1

1

10

Frecuency (GHz)

Fig. 4 Frequency dependence characteristics of the source–gate capacitance CGS (left) and the gate–drain
capacitance CDG (right).
387

SEE - Nagoya, Japan, Nov.12-14, 201850400mW-(h21)

35

50mW-dB(h21)3072mW-dB(h21)25

90mW-(h21)

20
15
10

Drain Conductances, Gd (S)45Gain, |h21| (dB)0.3

Vg=-0.3V, Vds=1.0V

5

0.25
0.2
0.15
0mW-Gd0.1

50mW-Gd
72mW-Gd

0.05

90mW-Gd

0
0.01

0.1

1

0
0.01

10

Frequency (GHz)

0.1

1

10

Frequency (GHz)
Fig. 6 Frequency dependence characteristic ofthe drain conductance Gd.

Fig. 5 Frequency dependence of the current gain
before and after light irradiation.
depletion type. Although a relatively good draincurrent rise is seen in the linear region, the current
does not exhibit a complete saturation state in thesaturated region but rather a slightly rising upward
characteristic. For this reason, the drain conductance
Gd has a certain value or more, but thetransconductance Gm has a good value of 100 S.

the h21 parameter.
Figure 6 shows the frequency dependence
characteristic of the drain conductance Gd. A clear
difference was confirmed for Gd depending on thepresence or absence of light irradiation. It was
confirmed that the drain conductance was lowered bylight irradiation. The reason for this will be discussed
below. It is known that the InGaAs layer originallyhas a hole accumulation effect [8]. At this time, holes
are accumulated in the InGaAs between the gate andthe source. The accumulated holes are recombinedwith a 2DEG, attenuating the amount of transferred
electrons, and this attenuation is a frequency
dispersion phenomenon of Gd. [9], [10]. Now, thelight incident to the InGaAs layer has almost the sameenergy as the bandgap energy of this crystal.
Electron–hole pairs are generated as photogenerated
carriers within the InGaAs layer by light irradiation.
At this time, electrons are transported together with a
2DEG toward the drain electrode, but holes aretransported toward the source electrode andaccumulate in the source–gate region. As a result, thehole surface density for recombination with the2DEG increases and the frequency dispersion effectof Gd increases, which is considered to be confirmedby the high-frequency measurement.

Confirmation and Analysis of Photoresponse
Characteristics
Clear optical response characteristics wereconfirmed in the IV characteristics of Fig. 3. At thestage when the coupling light entered the HEMT, thedrain current value was reduced by 0.4 mA at the
maximum. To clarify that this lowering phenomenon
is a photoresponsive characteristic, the S parameter
was measured by a vector network analyzer (Anritsu
MS4644B) and a parameter analysis was conducted.
Figure 4 shows the frequency dependence
characteristics of the source–gate capacitance CGS
and the gate–drain capacitance CDG. The light output
was controlled by CW laser output. The output
intensity was 50 mW, 72 mW, 90 mW. This is theincident light output on the top of InGaAs-HEMT. In
Fig. 4, the blue line shows the frequency dependence
before light irradiation and other lines show thefrequency dependency during light irradiation. Slightdecreases in both CGS and CGD induced by lightirradiation can be seen. Electron–hole pairs shouldhave been generated in the InGaAs layer by lightirradiation. Photogenerated electrons are transported
to the drain side together with a two-dimensional
electron gas (2DEG). Figure 5 shows the frequency
dependence of the current gain before and after lightirradiation. There is almost no difference before andafter. It is thought that the gain current was as weakas 0.4 mA at the maximum and was not reflected in

CONCLUSIONSA 1550-nm wavelength femtosecond pulse laser(with a pulse width of 100 fs and a period of 50 MHz)and DC light with a wavelength of 1480 nm were
coupled to an InGaAs HEMT and irradiated from thedevice metal electrode surface. Semiconductor laser
light penetrating into the device structure from theside surface of the gate metal electrode generated
electron–hole pairs by the photoelectric effect in the388

SEE - Nagoya, Japan, Nov.12-14, 2018

InGaAs layer, and it was confirmed that the
maximum drain current of 0.4 mA was reduced. Inelectron–hole pairs generated by incident light, holes
accumulated in the source region. It is clear from the
S parameter analysis that the hole accumulation effectis due to noticeable frequency dispersion of the drain
conductance. These results suggest that InGaAs
HEMTs may function not only as electronic response
devices but also as photoresponsive devices. From
now on, we will investigate system-on-chip ofphotoresponsive element and signal processing
element on InGaAs crystal.

Vol. 45, No. 11, 2006, pp. 8549–8555.
[5] K. Otsuki, Y. Kainuma, R. Miyashita, K.
Yamanaka, and H. Taguchi, DC and RF
Characteristics Fluctuation of InAlAs/InGaAs
HEMTs, International Journal of GEOMATE,
Vol. 12, Issue 34, 2017, pp. 28–31.
[6] T. Kawasaki, K. Sugawara, A. Dobroiu, H. Wako,
T. Watanabe, T. Suemitsu, V. Ryzhii, K.
Iwatsuki, S. Kuwano, J. Kani, J. Terada, and T.
Otsuji, InGaAs Channel HEMTs for Photonic
Frequency Double Mixing Conversion over the
Sub-THz Band, Proceedings of 2015 IEEE
MTT-S International Microwave Symposium(IMS).
[7] J. Zhang, M.A. Itzler, H. Zbinden, and J.-W. Pan,
Advances in InGaAs/InP Single-photon Detector
Systems for Quantum Communication, Light:
Science & Applications, Vol. 4, e286, 2015, pp.
1–15.
[8] H. Taguchi, M. Kawaguchi, M. Hayakawa, Y.
Nakamura, T. Iida, and Y. Takanashi, Frequency
Dependence of Drain Conductance due to Hole
Accumulation in InAlAs/InGaAs High Electron
Mobility Transistors, Japanese Journal ofApplied Physics, Vol. 45, Part 1, Number 6A,
2006, pp. 4960–4967.
[9] H. Taguchi, T. Sato, M. Oura, T. Iida, and Y.
Takanashi, Dependence of Carrier Lifetime of
InAlAs/InGaAs High Electron Mobility
Transistors on Gate-to-Source Voltage, Japanese
Journal of Applied Physics, Vol. 47, No. 4, 2008,
pp. 2858–2861.
[10] S. Nakano and H. Taguchi, Analysis of Intrinsic
Delay Time in InAlAs/InGaAs High-ElectronMobility Transistors at Cryogenic Temperature,
Proceedings of IEEE TENCON2017, pp. 1685–
1689.

ACKNOWLEDGMENTS
The authors are grateful to the Chukyo University
Research Found for financial assistance with thisresearch.
REFERENCES[1] M.S. Shur, Low Ballistic Mobility in Submicron
HEMTs, IEEE Electron Device Letters, Vol. 23,
Issue 9. 2002, pp. 511–513.
[2] J.T. Aberle, S.-H. Oh, D.T. Auckland, and S.D.
Rogers, Reconfigurable antennas for wirelessdevices, IEEE Antennas and Propagation
Magazine, Vol. 45, Issue, 6, 2003, pp. 148–154.
[3] Y. Yuan, Y. Fan, Z. Chen, L. Li, and Z. Yang,
Ku Band 2 Watt TR Chip for Phased Array
Based on GaAs Technology, IEICE Electronics
Express, Vol. 13, Issue 7, 2016, pp. 1–6.
[4] H. Taguchi, H. Murakami, M. Oura, T. Iida, and
Y. Takanashi, Analysis of Deviation ofThreshold Voltage from Hole Accumulation
Model, Japanese Journal of Applied Physics,389

4th Int. Conf. on Science, Engineering & Environment ( SEE) ,Nagoya, Japan, Nov. 12-14, 2018, ISBN: 978-4-909106018 C3051

VIBRATION AND SOUND SIGNAL ANALYSIS FOR A GASOLINEENGINE WITH LPG-INSTALLATION AND FAULT SIMULATIONS
1Suphattharachai Chomphan, 2Theerathan Kingrattanase and 3Saereephap

1,2,3Boonsit Faculty of Engineering at Sriracha, Kasetsart University, Thailand

ABSTRACT
Presently, number of vehicles and cost of gasoline have been tremendously risen, liquefied petroleum (LPG)
is a prominent alternative choice of fuel because of its popularity and economical cost. However, the LPGinstallation may cause some degradations of the engine efficiency. The important perceptions of the driver are theengine vibration and sound. Therefore, an analysis of vibration signals and sound signals to distinguish between
LPG-modified and normal oil-usage 2,200-cc engine is essentially inevitable. It has been reviewed in the firststage of this paper. The power of signal is applied for both engines at five different engine speeds. A ten-second
sample of signal has been measured with the sampling rate of 2,048 Hz. The experimental results of the analysis
of vibration signals show that the power of signals of the LPG-modified engine are mostly above those of thenormal oil-usage engine. As for the analysis of sound signals, the LPG-modified engine has higher power thanthat of normal oil-usage engine at low engine speed. Meanwhile, the normal oil-usage engine cause higher powerof signals when comparing with the LPG engine at the engine speed over 1,300 rpm. In the second stage, a studyof fault simulations has been reviewed. The fault simulations of butterfly valve and sparking plug have beenstudied. The experimental results show that the vibration of engine is directly proportional to the engine speed.
Moreover, the engine faults cause significant engine vibration at the speed above 1,500 rpm for both normal
gasoline and LPG modified engines. In conclusions, LPG-installation and engine faults cause degradations inengine efficiency which can be concretely evidenced by using the proposed signal processing technique.
Keywords: Engine vibration, Sound signal, Liquefied petroleum, Power of signal, Fault simulation

By investigating the reviews on detection anddiagnosis the faults in rotating machinery, thevibration-based techniques have been tremendously
and efficiently developed. These techniques are
seldom applied to gasoline or diesel engines. The
application of vibration-based techniques to theseengines are very burdensome due to the transient andnon-stationary nature [1]. The exploitation ofvibration signals of engines give much dynamic
information of mechanical system condition. Many
useful techniques of signal analysis have been applied
as the useful methods for fault diagnosis of theengines [2]. The power spectrum, cepstrum, higher
order spectrum and neural network analyses wereapplied in the specified induction motor fault
diagnosis [4]. Power of signal has been successfully
used in the previous work to compare the engine
sound of LPG-modified engine [5]. As for the fault
diagnosis, the discrete wavelet transform were
efficiently exploited with the vibration signal of thediesel engine and the gearbox [2, 3]. The power ofsignal analysis; one of the powerful techniques, hasbeen chosen to adaptively applied in the paper thanks
to its low complexity and minimal time consumption

INTRODUCTION
Alternative sources of energy are primary
importance to drive the current business and theongoing industrial sector. Supply preparation ofenergy in accordance with user’s need must be vitallyconsidered. Moreover, quality of energy such as
gasohol and biodiesel are very important for engine
in transportation system. Furthermore, renewableenergy are alternative way for the automotive
industrial. However the factors of economics and thedecrease of petroleum resources reinforce the current
research and development of energy made fromnatural gas considerably.
In general, natural energy can be divided into two
types. Compressed Natural Gas (CNG) which is
known as the Natural Gas for Vehicle (NGV) and
Liquefied Petroleum Gas (LPG) are both made fromhydrocarbons. Almost all demands in Thailand, the
LPG is however much more popular because its
installation cost is more economical [1-3]. The
number of service stations is also greater than that of
NGV. Therefore, the LPG-installation engine is aninteresting issue to be chosen to study in this paper.

390

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1,500 and 1,700 rpm. To measure the vibration andsound signals, a number of accelerometers andmicrophones have been installed. The positions ofthese sensors are partly allocated in Fig. 1. A wirelessreceiver which perceives the measured vibration andsound signals has been attached to a computer
notebook. The corresponding data are then recorded
in a specified file format.
Power of signal calculated for engine vibration orsound is mainly applied in this paper due to its
simplicity and fast calculation. The signal power is anamount of energy consumed per unit of time. Thisquantity is very useful to described the signal which
its energy goes to infinity where this engine vibrationand sound signal can be assumed to be not-squarelysummable as long as the engine does not stop running.
The calculation is developed by using the sum ofsquare of the signal samples [6, 10]. The average
power of an aperiodic sequence x[n] ismathematically defined as in Eq. (1).

[5, 6].
Modification of the engine and also the different
temperature of the combustion make the working
condition of the engine changed. The problems of
LPG-installation cause the engine vibration andsound both direct and indirect effects [7-10]. The
vibration and sound signals are therefore investigatedand analyzed to differentiate between the LPGmodified engine and the normal oil-usage engine [11,12], because they are ones of important measurable
attributes to indicate the causes or evidences ofirregular conditions of engines.
In the conventional engine diagnosis, theexpertise of the mechanic is used to find the cause of
the engine faults. To improve the conventional
approach, this research aims at discovering a suitable
technique to compare the signal power of vibrationand sound of the LPG-modified engine and thenormal oil-usage engine. At the first stage of thisstudy, two cases of basic normal engine and LPGmodified engine are focused. The study is limited at
the personal car with gasoline engine. We basically
apply the power of sound signal of speech analysis to
extract the power of engine vibration and sound. We
expected that these techniques are applicable that of
the engine vibration and sound.
In the second stage of this study, the simulation ofengine faults for both normal gasoline engine and
LPG modified engine has been performed to study thecharacteristics of them in all conditions. Finally, theconclusions of this study has been conducted.

𝑷𝑷𝑷𝑷 = 𝐥𝐥𝐥𝐥𝐥𝐥

𝟏𝟏

𝑲𝑲→∞ 𝟐𝟐𝑲𝑲+𝟏𝟏𝟐𝟐∑𝑲𝑲
𝒏𝒏=−𝑲𝑲 |𝒙𝒙[𝒏𝒏]| ,(1)

where K is the sequence half length which extends its
limit of number of samples to infinity.
The engine vibration and sound has been measured
by a number of accelerometers and microphones andrecorded by the G-link microstrain serial base station
and a number of softwares through a host computer
notebook. These infinite energy signals (called powersignal) in this research have been measured andrecorded with some approximately periodic
sequences. Therefore this equation has been adaptedwith a specific length which reflects the whole
vibration and sound sequences for both normal oilusage and LPG-modified engines. Therefore thisequation has been adapted with a specific length
recorded in a number of iteration samples for all fivevarious levels of engine speeds as explained earlier inprevious section.

MATERIAL AND METHODSIn the first stage of the study, the comparison
between two cases of basic normal engine and LPGmodified engine are introduced. The gasoline engine
with 2,200 cc piston has been used in the study. The
installation of alternative LPG system has been
conducted. There were two modes of fuel supply
including normal gasoline supply mode and LPG
supply mode. At the beginning of these modes, theengine has been started and waited until reaching thestable period of working engine. Five various levelsof engine speeds have been set at 900, 1,100, 1,300,

In the latter stage of the study, the simulation ofengine faults for both normal gasoline engine and
LPG modified engine has been conducted. In thisexperiment, the 1,500 cc gasoline engine has beenchosen as a specimen. The LPG installation has beenFig. 1 Sensor allocation design : the first stage

Fig. 2 Sensor allocation design : the second stage
391

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

implemented by using the European standard. The
LPG with injection system has been installed be an
experienced mechanics. To simulate [9] two faults ofworking conditions, the engine has been set up themechanics [10] as follows. Type I, the engine withbutterfly valve fault has been conducted by releasing
the corresponding valve out. Type II, the engine withsparking plug fault has been done by pulling the plugoff. These fault simulations have been performed
with both regular gasoline engine and LPG modified
engine. To measure the vibration from the engine, a
couple of accelerometers [1] are attached with theengine piston surface as allocated in Fig. 2.

Database of LPGmodified engine
vibration and soundNormalenginevibration

LPG-modified
engine vibrationand soundPower extraction ofvibration and soundComparison analysis anddiscussion
Conclusions

Fig. 3 Experimental procedure : the first stage

EXPERIMENTAL DESIGNSThe experiments in this paper has been organized
as two stages including the comparison of normal
gasoline engine and LPG-modified engine and thesimulation of engine faults. At the first stage, thestudy focused on the comparison between the normal
gasoline engine and the LPG-modified engine byconsidering the extracted parameters of engine
vibration and sound signals; averaged power, as
described in the previous section. Thereafter, thelatter study concentrated on two major engine faults(type I and type II) simulated by the experienced
mechanics. The averaged power of engine vibration
at various engine speeds has been investigated todifferentiate all condition of faults.

Database of LPGmodified engine
vibration

Normalenginevibrationwith fault

LPG-modified
enginevibration withfault simulation

Power extraction ofvibration

Comparison analysis
and discussion

Conclusions

Comparison of Normal Gasoline Engine and
LPG-Modified Engine

Fig. 4 Experimental procedure : the second stage
The experimental procedure for the first stage ofstudy has been implemented as depicted in Fig. 3 [5,13]. The accelerometers are attached at the pistons of
the engine. Meanwhile, the microphone with arecording software is applied to implement the
database of engine sound. The vibration and soundsignals are recorded in the form of connected samples
to attain the database of LPG modified engine’s
vibration and sound signals. The database consists ofthe vibration and sound signals of both conditions
including normal engine and LPG-modified engine.
A number of repetitions of signals were measured at
the engine speeds of 900, 1,100, 1,300, 1,500, and
1,700 rpm for both engine conditions. The duration ofeach sample lasts 10 seconds at the sampling rate of
2,048 Hz. Subsequently, the calculation of signal’s
power has been conducted as described in theprevious section. The signal powers, thereafter, wereanalyzed using comparative approach. The analysis
and discussion are presented in the next section. In the
final process, the conclusions have been performed.
In this study, five couples of linear plots of thevibration and sound signals at different samples havebeen presented. The overall presentation of theaveraged powers of vibration and sound signals at

various engine speeds is also summarized.
Simulation of Engine Faults
The experimental procedure for the second stageof study has been implemented as depicted in Fig. 4[14]. The accelerometers are attached at the pistons of
the engine. The vibration signal is recorded in theform of acceleration to attain the database of LPG
modified engine’s vibration signal [7]. The databaseconsists of the vibration signals of two conditions
including normal gasoline engine and LPG-modified
engine. A number of repetitions of vibration signals
were measured at the engine speeds at 700, 900, 1,100,
1,300, 1,500, 1,700, 1,900, and 2,100 rpm for six
engine conditions. The duration of each sample lasts
10 seconds at the sampling rate of 2,048 Hz.
Subsequently, the calculation of signal power has
been performed. The signal powers, thereafter, wereanalyzed using discrete signal formulation in Eq. (1)[8, 12]. Subsequently, the comparison analysis anddiscussion is presented. The overall presentation of
the averaged powers of vibration signal at different
engine speeds is finally concluded.
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SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

EXPERIMENTAL RESULTS

Comparison by Using Engine SoundThe experimental results consisted of two stages
including the comparison of normal gasoline engine
and LPG-modified engine and the simulation ofengine faults.

After measuring the sound signals through theprovided microphones, the normalized averaged
power of sound signals are calculated. A comparisonin power of sound signal of all engine’s conditions
including normal oil-usage engine and LPG-modified
engine is shown. Figure 6 summarily illustrates theconclusion of these experimental results. It can be
obviously observed that at the engine speeds of 900
and 1,100 rpm, LPG-modified engine has power ofsound signal more than that of normal engine with oil
supply. When the engine speed is increased above
1,300 rpm, the LPG-modified engine has power ofengine sound signal lower than that of normal engine
with oil supply.

Comparison Results of Normal Gasoline Engine
and LPG-Modified Engine
In the first stage of the study, the comparisons
between the normal gasoline engine and the LPGmodified engine are comprised of the comparison byusing engine vibration and the comparison by using
engine sound. Both of the comparisons utilize theaveraged power of the corresponding signals. The
experimental results are then explained, respectively.

2300
2250
2200
2150
2100
2050
2000
1950
1900
1850
1800
1750
1700
1650
1600
1550
1500

Comparison by Using Engine Vibration
The engine vibration is investigated in this section.
The normalized averaged powers of vibration signal
for both engine conditions including normal oil-usageengine and LPG-modified engine are calculated andthereafter comparatively plotted in different engine
speeds. All in all, figure 5 summarily presents theaveraged power of vibration signal at different engine
speeds. It can be noticeably concluded that thenormalized averaged power of vibration signals of the
LPG-modified engine are mostly above those of thenormal engine with oil supply except for the engine
speeds of 1,100 and 1,300 rpm.

Power of vibration signal

28.47
28.46
28.45

1300

1500

1700

Type I

1900

2100

Type II

Oil

28.44

2300

Gas

28.43

2250

28.42

2200

28.41

2150

28.40

2100
900

1100

1300

1500

2050

1700

2000
1950

Fig. 5 Normalized averaged power of vibration
signal at different engine speeds (rpm)

1900
1850
1800

0.18

1750

0.16
Power of sound signal

1100

Fig. 7 Absolute averaged power of vibration
signal for normal gasoline engine at different engine
speeds with 3 conditions (power of vibration signal vsengine speeds)

28.48

1700

0.14

1650

0.12

1600

0.1

1550

Oil

0.08

1500

Gas

0.06

700

900

1100
Normal

0.04
0.02
0

900

Normal

28.49

28.39

700

900

1100

1300

1500

1300

1500
Type I

1700

1900

2100

Type II

Fig. 8 Absolute averaged power of vibration
signal for LPG modified engine at different engine
speeds with 3 conditions (power of vibration signal vsengine speeds)

1700

Fig. 6 Normalized averaged power of sound signal
at different engine speeds (rpm)393

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

powers of vibration signal for these engine conditions
including normal oil-usage engine and LPG-modified
engine are calculated and comparatively plotted indifferent engine speeds. Figures 7-8 demonstrate theabsolute averaged power of vibration signal atdifferent samples at the engine speeds of 700 - 2,100rpm.
From Fig. 7, the absolute averaged power ofvibration signal for normal gasoline engine in three
engine’s conditions have been compared in thosedifferent engine speeds. When noticing at low engine
speeds, the powers of vibration signal of allconditions are closed to each other. When the engine
speed is increased above 1,500 rpm, the powers ofengine vibration signal with faults type I and type II
become significantly lying above than that of thenormal engine without faults.
From Fig. 8, the absolute averaged power ofvibration signal for LPG modified engine in three
engine’s conditions have been displayed in thosedifferent engine speeds. The experimental results arecorresponding to those of the normal gasoline engine
as demonstrated in Fig. 7. Last but not least, it can benoticeably seen from both figures that almost all of
the absolute averaged powers of vibration signal are
increasing from lower engine speeds to higher engine
speeds. Therefore it can be concluded that the
averaged power of the vibration signal are directly
proportional to the speed of the engine.
From Figs. 9-11, the absolute averaged power ofvibration signal for LPG modified engine in three
engine’s conditions have been displayed andcompared to those of normal gasoline engine indifferent engine speeds. These absolute averaged
powers of vibration signal are directly proportional tothe engine speeds. All of them have the similar
behaviors, the absolute averaged powers of vibration
signal at 1700 rpm and 1900 rpm fall slightly
compared to those of the previous engine speed of1500 rpm.

2000
1900
1800

LPG

1700

Gasoline

1600
1500

700 900 1100 1300 1500 1700 1900 2100

Fig. 9 Absolute averaged power of vibration
signal for normal gasoline engine vs LPG modified
engine at different engine speeds with normal
condition (power of vibration signal vs engine
speeds)
2300
2200
2100
2000
LPG

1900

Gasoline

1800
1700
1600
1500

700 900 1100 1300 1500 1700 1900 2100

Fig. 10 Absolute averaged power of vibration
signal for normal gasoline engine vs LPG modified
engine at different engine speeds with type I fault
condition (power of vibration signal vs engine
speeds)
2300
2200
2100
2000
LPG

1900

Gasoline

1800
1700
1600
1500

700 900 1100 1300 1500 1700 1900 2100

CONCLUSIONS

Fig. 11 Absolute averaged power of vibration
signal for normal gasoline engine vs LPG modified
engine at different engine speeds with type II fault
condition (power of vibration signal vs engine
speeds)This paper presents a study of vibration and soundsignal analysis for a gasoline engine with LPGinstallation and fault simulations. The paper isorganized as two stages including the comparison of
normal gasoline engine and LPG-modified engine
and the simulation of engine faults. In the first stage,
the study focused on the comparison between thenormal gasoline engine and the LPG-modified engine
by considering the averaged power extracted from theengine vibration and sound signals. From theexperimental results, it can be seen from the vibration
analysis that the power of vibration signals of the
LPG-modified engine are mostly above those of thenormal engine with oil supply except for the engine
speeds of 1,100 and 1,300 rpm. Moreover, it has beenconcluded from the sound analysis that at engine

Simulation Results of Engine Faults
In the second stage of the study, the main focus is
how the simulated engine faults affect the vibrationof the engine at different engine speeds. From the firststage, it can be noticed that both vibration and soundgive quite corresponding results. The vibration has
been therefore selected as the main signal to study forthe fault simulation in the second stage. The range ofengine speeds has been consequently broadened forinvestigating the vibration in deep. The averaged
394

SEE - USQ, Nagoya, Japan, Nov.12-14, 2018

speed at 900 and 1,100 rpm, LPG-modified engine
has lower power of sound signal more than that ofnormal engine with oil supply. At the engine speed of
1,500 and 1,700 rpm, LPG-modified engine has thepower of sound signal lower that of normal engine
with oil supply. In the second stage, the study
concentrated on two major engine faults. The
absolute averaged power of engine vibration at
various engine speeds has been investigated todifferentiate all conditions of faults. From theexperimental results, it can be summarized that thevibration of engine are directly proportional to the
speed of engine. Moreover, the engine faults causesignificant engine vibration at the speed above 1,500rpm for both normal gasoline and LPG modified
engines. In conclusions, LPG-installation and engine
faults cause degradations in engine efficiency which
can be concretely evidenced by using the proposed
signal processing technique. The expanded simulated
faults can be further studied, moreover the other typesof engines should be experimentally conducted in the
future.

2, 2013, pp. 342–360.
[5] Chomphan S., Chaimanatsakun A., Sakornsin R.,
Khumneungratavongsa S., Rattanarat K., A
Comparative Study of LPG-modified Engine andNormal Oil-usage Engine. in Proc. Int. Conf. On
Engineering and Applied Sciences, 2016, pp.
219-225.
[6] Akhand R., Upadhyay S. H., A review on signal
processing techniques utilized in the fault
diagnosis of rolling element bearings, Tribology
International, Vol. 96, Issue 4, 2016, pp. 289-306.
[7] Ahmad T. A., Barat G., Teymour T. H., Seyed
S.M., Vibration analysis of a diesel engine using
biodiesel and petro diesel fuel blends, Fuel, Vol.
102, Issue 12, 2012, pp. 414–422.
[8] Zunmin G, Jin C., Barry H., Analysis of engine
vibration and design of an applicable diagnosing
approach. International Journal of Mechanical
Sciences, Vol. 45, Issue 8, 2003, pp. 1391–1410.
[9] Xianhua L., Randall R. B., Jerome A., Blindseparation of internal combustion engine
vibration signals by a deflation method.
Mechanical Systems and Signal Processing, Vol.
22, Issue 5, 2008, pp.1082–1091.
[10] Xianhua L., Randall R. B., Blind source
separation of internal combustion engine pistonslap from other measured vibration signals.
Mechanical Systems and Signal Processing, Vol.
19, Issue 6, 2005, pp. 1196–1208.
[11] Zbigniew S., Jan W., Application of vibration
signals in the diagnosis of combustion engines –exploitation practices. Journal of KONES
Powertrain and Transport, Vol. 18, Issue 3, 2011,
pp. 405-412.
[12] Carlucci A. P., Chiara F. F., Laforgia D.,
Analysis of the relation between injection
parameter variation and block vibration of aninternal combustion diesel engine. Journal ofSound and Vibration, Vol. 295, Issues 1–2, 2006,
pp. 141–164[13] Kingrattanaset T., Chomphan S., Vibration
Signal Analysis for LPG-modified Engine andNormal Oil-usage Engine with Different Engine
Speeds. in Proc. Global Conference on
Engineering and Applied Science, 2016, pp. 312317.
[14] Boonsit S., Chomphan S., Vibration Signal
Analysis for LPG-modified Engine and Normal
Oil-usage Engine with Different Engine Speeds
and Faults. in Proc. International Congress on
Engineering and Information, 2017, pp. 102-107.

ACKNOWLEDGEMENTS
The research was partly sponsored by Kasetsart
University, Faculty of Engineering at Sriracha’s
Fund.
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between contacting components in a diesel
engine, Mechanical Systems and Signal
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[2] Xia W., Changwen L., Fengrong B., Xiaoyang
B., Kang S., Fault diagnosis of diesel engine
based on adaptive wavelet packets and EEMDfractal dimension. Mechanical Systems andSignal Processing, Vol. 41, Issue 1-2, 2013, pp.
581–597.
[3] Binqiang C., Zhousuo Z., Chuang S., Bing L.,
Yanyang Z., Zhengjia H., Fault feature extractionof gearbox by using over complete rational
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Systems and Signal Processing, Vol. 39, Issue 1-395

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

AN ARTIFICIAL NEURAL NETWORK MODEL FOR THE
CORROSION CURRENT DENSITY OF STEEL IN MORTAR MIXEDWITH SEAWATER
1,2

Cheryl Lyne C. Roxas1 and Bernardo A. Lejano2
Faculty, De La Salle University - Manila, Philippines

ABSTRACT
Corrosion is a very complicated phenomenon in the field of science and engineering. Over the years, several
numerical models have been developed to predict the damage caused by the corrosion process. The use of
artificial neural network in modelling corrosion has gained popularity in the recent years. Many of the factors
affecting corrosion are difficult to control. Thus, artificial neural network may be a better technique to consider
due to its ability to tolerate relatively imprecise, noisy or incomplete data, less vulnerability to outliers, filtering
capacity and adaptability. This study aims to generate a corrosion current density prediction model using theartificial neural network approach. Microcell corrosion current density is defined as the rate of corrosion
expressed in electric current per unit area of cross section. Several variables were considered as input variables
namely: age, water to cement ratio, cement content, compressive strength, type of mixing water, corrosion
potential, solution resistance and polarization resistance. These variables were entered into the neuralnetwork architecture and simulated in MATLAB. The feedforward backpropagation technique was used togenerate the best model for the corrosion current density. The best neural network architecture consists of 8
input variable, 8 neurons in the hidden layer and one output variable. The resulting neural network modelsatisfactorily predicted the corrosion current density with coefficient of correlation values of 0.96536, 0.80817,
and 0.7662 for training, validation and testing phases, respectively,
Keywords: Neural network, Corrosion current density, Seawater, Mortar

hand, probabilistic (stochastic) approaches presented
high-level statistics and other mathematical methods
in processing field data and were found to predict
local corrosion phenomena successfully [1].
Examples of modelling techniques are the multiple
linear regression, finite element method (FEM),
Bayesian updating and artificial neural network(ANN).
FEM has been applied in previous studies [2], [3][4], [5] and [6]; while a Bayesian updating approachof an existing steel loss model based on monitored
data was proposed in [7].
The use of ANN in modelling corrosion has
gained popularity in the recent years. The technique
can be applied to complex problems and isindependent of the physical processes involved but
rather the relationships present in a set of data [8].
Many of the factors affecting corrosion are difficult
to control. Thus, ANN may be a better technique toconsider due to its ability to tolerate relatively
imprecise, noisy or incomplete data, lessvulnerability to outliers, filtering capacity andadaptability.
Therefore, a model that can predict suchcorrosion behavior of steel reinforcement will help
design engineers in developing better design
practices for corrosion management, i.e., repair andrehabilitation procedures, thus extending the service
life of structures and saving costs. Modeling is a

INTRODUCTION
Concrete is probably the most-widely usedbuilding material in the world. It is a composite
material made of cement, aggregates, water andsome admixtures. The durability of concrete may becompromised through processes like alkaliaggregate reaction, sulfate attacks, freeze-thaw
cycles and corrosion, among others. Among all these,
corrosion of the reinforcing steel in concrete has
become a great concern as this may result to sudden
failure of structures. Thus, developments in thedesign, construction and maintenance of concrete
structures are encouraged to mitigate huge economic,
social, health, safety and environmental impacts.
Corrosion of steel is one of the main causes offailure in concrete structures. Theoretical andempirical models help determine its behavior overtime and therefore engineers can decide on
maintenance and repairs needed to prolong theservice life of a structure. Moreover, it is a very
complicated phenomenon in the field of science andengineering. Over the years, several numericalmodels have been developed to predict the damage
caused by the corrosion process. Numerical methods
can be classified as deterministic and probabilistic.
Deterministic models helped understand themechanisms of localized corrosion but were notreally practical for actual prediction [1]. On the other396

SEE - Nagoya, Japan, Nov.12-14, 2018useful tool in the quantitative understanding of key
elements in concrete and their interactions. This canbe accomplished by considering time-dependency oftransport properties of concrete, repair or
replacement of concrete cover, corrosion
propagation, chloride penetration mechanisms otherthan diffusion, structure geometry, environmental
humidity and temperature fluctuations and decay ofstructures under combined physical, chemical andmechanical deterioration processes as summarizedby [9]. Therefore, improvements on existing models
can be made to better simulate the corrosion
behavior of reinforced concrete structures, especiallythose mixed with non-conventional materials likeseawater and fly ash. Additionally, theirperformance on chloride-laden environment throughtime can be assessed.
This study aims to generate a corrosion current
density prediction model using the ANN approach.
Corrosion current density is defined as the rate ofcorrosion expressed in electric current per unit areaof cross section. Several variables were considered
as input variables namely: age, water to cement
ratio, cement content, compressive strength, type of
mixing water, corrosion potential, solution resistanceand polarization resistance.
This paper is organized as follows: The
introduction is followed by some literature on ANN
modelling of corrosion; followed by themethodology highlighting the data collection,
identification of the input and output variables, andbuilding the ANN models; and then results anddiscussion; finally, conclusions of the research arepresented.

Training is the method for setting the values of theweights. An activation function is applied to the sumof the weighted input signal. Typical activation
functions are unit step, linear, sigmoid andhyperbolic tangent. Neural networks are used to findthe solutions to constrained optimization problems
and can be applied for storing, recalling classifying
and mapping data or patterns [10].
Some ANN models related to measuring steel
corrosion in concrete are found in [8], [11], [12],[13], [14] and [15].
METHODOLOGY
Data Collection and Identification of Input
Variables
Input data were obtained from the experimental
quantities and equipment test results in [16].
Rectangular mortar prism specimens (40 mm x 40
mm x 160 mm) with steel reinforcements of 10 mm
in diameter and 100 mm length were cast. Ordinary
Portland cement (OPC) was the main binder used
and replaced with fly ash. The fly ash content in thespecimens was varied from 0% to 50% at 10%
interval, while the water to cement (w/c) ratios were
held at 0.35, 0.40, 0.45, 0.55, 0.65.
A 5 mm cover was applied from the top surfaceof the prism specimen. Insulated copper wires were
soldered at both ends of the steel and then covered
with epoxy. These wires were necessary for the
corrosion monitoring equipment (CT-7) inmeasuring the potential and polarization resistance.
In this study, several input variables as used inprevious literature were considered in determining
the best ANN model. A total of eight (8) input
variables were entered namely: age (days), w/c,
cement content (%), compressive strength (MPa),
type of mixing water (freshwater or seawater),corrosion potential (mV), solution resistance (Ω) andpolarization resistance (Ω). The corrosion potential,
solution resistance and polarization resistance were
measured from the corrosion monitoring equipment.
On the other hand, the output variable is the
microcell corrosion current density defined as therate of corrosion expressed in electric current perunit area of cross section.

ANN MODELING FOR CORROSION
With the development of new technology andcomputer softwares, mathematical modelling andcomputation became easier and faster. In this
proposed study, regression and artificial neuralnetwork (ANN) modelling are the initial modelling
techniques being considered.
ANNs mimic the learning process of the humanbrain. They generalize mathematical models byprocessing information at elements called neurons.
Signals are passed between neurons overconnections links. A weight is assigned on each link
which multiplies the signal transmitted. The output
is obtained by applying an activation function to the
net input. A neural network is characterized by its
architecture, training or learning algorithm andactivation function. A network architecture is thearrangement of neurons into layers and theconnection patterns within and between layers.
Neural networks are further classified as single ormultilayer, and are therefore feedforward networks.

Structuring the ANN Models
The Neural Network Toolbox in MATLAB
R2018a was used in constructing the ANN corrosion
current density model estimation. Data were divided
into three sets: 60% for training the neural network,
20% for validation and 20% for testing. These sets
were randomly selected in MATLAB. The
feedforward backpropagation technique was used togenerate the best model. This algorithm gradually
397

SEE - Nagoya, Japan, Nov.12-14, 2018

reduces the error between the model output and thetarget output by minimizing the mean square error(MSE) over a set of training set [17]. The MSE is agood overall measure of the success of the training
process [18], [19]. The weights and bias value, on
the other hand, were updated according to theLevenberg-Marquardt network training function.
This is often the fastest backpropagation algorithm
and highly recommended, though it requires morememory that other algorithms [20]. A two-layer
feed-forward network with sigmoid hidden neurons
and linear output neurons was used. This can fit
multi-dimensional mapping problems arbitrarily
well, given consistent data and enough neurons in its
hidden layer [20].

Fig. 1

ANN structure 8-8-1

Validation: R=0.80817

Training: R=0.96536
1.2
1.2

Data

Fit

1

0.8

Output ~= 0.94*Target + 0.077

Output ~= 0.93*Target + 0.026

Y=T

Trial ANN Model Architectures

0.6

0.4

0.2

Y=T

0.8

0.6

0.4

0.2

0

The best ANN model to estimate the microcell
corrosion current density was determined bydefining the number of neurons (nodes) in the input
and output layers, number of hidden layers and thenumber of neurons in each hidden layer. The model
generated utilized the 8 input variables. There is no
specific rule in determining the number of hidden
layers and the number of neurons in each hidden
layer [21]. In this study, one hidden layer was used
and the following rules were employed to determine
the optimum number of neurons: (a) a network with
n-input and m-output units requires a hidden layer
with at most 2n+1 units, (b) should be between the
average and the sum of nodes on the input andoutput layers; (c) seventy-five percent (75%) of the
input nodes [22]. Thus, simulation was done in therange of 5-17 neurons in the hidden layer.

Data

Fit

1

0
0

1

0.5

0

TargetAll: R=0.85983

Test: R=0.7662
Data

2

Data

2

Fit

Fit

Y=T

Y=T

Output ~= 0.9*Target + 0.051

Output ~= 0.85*Target + 0.084

1

0.5

Target

1.5

1

0.5

1.5

1

0.5

0
0.5

1

1.5

2

0

1

0.5

TargetFig. 2

1.5

2TargetRegression lines for ANN structure 8-8-1

Best Validation Performance is 0.047151 at epoch 13
10

1

Train
Validation
Test

RESULTS AND DISCUSSIONBest

Mean Squared Error (mse)

10 0After several simulations, ANN Structure 8-8-1(8-input variables, 8-nodes in the hidden layer, 1output) was found to be the best model to estimate
the microcell corrosion current density. Figure 1
shows the ANN Structure 8-8-1. ANN Structure 8-88 obtained a satisfactorily acceptable correlation
coefficient, R, values of 0.96536, 0.80817, and
0.7662 for training, validation and testing phases,
respectively. A correlation coefficient of 0.85983
was achieved considering all data points. Figure 2
presents the regression line while Fig. 3 shows thetraining performance for ANN Structure 8-8-1. The
resulting MSEs for each phase are seen in Table 1.

10

10

10

-1

-2

-3

0

2

4

6

8

10

12

14

16

18

19 Epochs

Fig. 3398

Training performance of ANN structure
8-8-1

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 MSE for different training phases
Phase
Training
Validation
Testing

Samples85
28
28

Element Model for Simulation of SteelCorrosion,
International
Journalof
Electrochemical Science, 2010, Vol. 5, pp. 314326.
[4] Lin, G., Liu, Y., & Xiang, Z., Numericalmodeling for predicting service life of
reinforced concrete structures exposed tochloride environments. Cement & Concrete
Composites, 2010, Vol. 32, pp. 571-579.
[5] Shekarchi, M., Ghods, P., Alizadeh, R., Chini,M., & Hoseini, M., DuraPGulf, A Local Service
Life Model for the Durability of Concrete
Structures in the Couth of Iran. The Arabian
Journal for Science and Engineering, 2008,
33(1B), pp. 77-88.
[6] Song, H.-W., Kim, H.-J., Saraswathy, V., &Kim, T.-H., A Micro-mechanics BasedCorrosion Model for Predicting the Service Lifeof Reinforced Concrete Structures. International
Journal of Electrochemical Science, 2007, 2, pp.
341-354.
[7] Faroz, S. A., Pujari, N. N., & Ghosh, S.,
Reliability of a corroded RC beam based on
Bayesian updating of the corrosion model.
Engineering Structures, 2016, 126, pp. 457468.
[8] Ukrainczyk, N., & Ukrainczyk, V., A neuralnetwork method for analyzing concrete
durability. Magazine of Concrete Research,
2008, 60(7), pp. 475-486.
[9] Shi, X., Xie, N., Fortune, K., & Gong, J.,
Durability of steel reinforced concrete inchloride
environments:An
overview.
Construction and Building Materials, 2012, 30,
pp. 125-138.
[10] Fausett, L., Fundamentals of Neural Networks:
Architectures, Algorithms, and Applications,
1994.
[11] Parthiban, T., Ravi, R., Parthiban, G.,
Srinivasan, S., Ramakrishnan, K., & Raghavan,M., Neural network analysis for corrosion ofsteel in concrete. Corrosion Science, 2005, 47 ,pp.1625-1642. doi:10.1016/j.corsci.2004.08.011[12] Shi, X., Tuan Anh Nguyen, P. K., & Liu, Y., A
phenomenological model for the chloride
threshold of pitting corrosion of steel insimulated concrete pore solutions. AntiCorrosion Methods and Materials, 2011, pp.
179-189. doi:10.1108/00035591111148894[13] Sadowski, L., & Nikoo, M.. Corrosion current
density prediction in reinforced concrete byimperialist competitive algorithm. NeuralComputing and Applications, 2014, 25 , pp.
1627-1638. doi:10.1007/s00521-014-1645-6[14] Hodhod, O., & Ahmed, H., Modeling thecorrosion initiation time of slag concrete using
the artificial neural network. HBRC Journal,
2014, 10, pp. 231-234.

MSE
0.0062789
0.0471508
0.1299260

CONCLUSION
This paper presents an artificial neural networkmodel for estimating the microcell current density ofsteel in mortar mixed with seawater. This value isnecessary in computing the corrosion rate of steel,which is one of the main causes of failure in
structures. Several input variables were considered
in constructing the ANN model namely: age, waterto cement ratio, cement content, compressive
strength, type of mixing water, corrosion potential,
solution resistance and polarization resistance.
From several trials, ANN Structure 8-8-1 waschosen as the best architecture having the highest
correlation coefficient values of 0.96536, 0.80817,
and 0.7662 for training, validation and testing
phases, respectively, in a range of 5-17 neurons in
the hidden layer. The resulting MSE in the training
phase is 0.0062789. The best validation performanceis 0.047151 and occurred at epoch 13. The test set
and validation set errors have relatively similar
characteristics.
Finally, it can be concluded that the neuralnetwork technique provided good predicting ability
despitethenon-uniform
distribution
andincompleteness of the data set. Expanded data set
may improve the results. Sensitivity analysis andrelative importance of the input variables can be
conducted to enhance the reliability and validity of
the results.
ACKNOWLEDGMENTS
The authors would like to thank their colleagues,
staff, technicians and former students of the Civil
Engineering Department, De La Salle University –Manila, especially Engr. Edrick Dan Lim.
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[2] Pan, T., & Wang, L., Finite-Element Analysis
of Chemical Transport and Reinforcement
Corrosion-Induced Cracking in Variably
Saturated Heterogeneous Concrete, Journal ofEngineering Mechanics, 2011, pp. 334-345.
[3] Dao, L. T., Dao, V. T., Kim, S.-H., & Ann, K.
Y., Modeling Steel Corrosion in Concrete
Structures - Part 2: A Unified Adaptive Finite
399

SEE - Nagoya, Japan, Nov.12-14, 2018[15] Guo-dong, L., Corrosion Evaluation Model ofReinforcement in Concrete Based on ANN. 8thInternational
ConferenceonIntelligent
Computation Technology and Automation,
2015, pp. 341-344. Nanchang, China : IEEE.
doi:10.1109/ICICTA.2015.92[16] Lim, E.D.P., Influence of Seawater on
Reinforced Mortars with Varying Fly Ash
Replacement Ratio, Water-Binder Ratio,
Curing Conditions and Type of Steel Bars,
Thesis, De La Salle University – Manila,
Philippines, 2012.
[17] Gunaydin, H. and Dogan, S., A neuralnetwork approach for early cost estimationofstructural
systemsofbuilding,
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[18] Al - Tabtabai, H., et.al., Preliminary costestimation of highway construction using neuralnetworks, Construction
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[19] Turochy,
et.al., Highway
projectcostestimating methods used in the planningstage of project development, Technical
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[20] MATLAB R2018a, Neural network toolbox.
[21] Shtub, A. and Versanob, R., Estimating the costof steel pipe bending, a comparison between
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[22] Oreta, A. Artificial neural networks: Multi layer feedforward networks using backpropagation, CIV578D Lecture Notes, 2012,
De La Salle University Manila.

400

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

IMPLEMENTATION OF CONNECTION SYSTEM OF WOODEN
PLATE AND WOODEN CLAMP ON JOINT MODEL OF BAMBOO
TRUSS STRUCTURES*Astuti Masdar1, Suprapto Siswosukarto2 Noviarti3 and Des Suryani42,

1,3Department of Civil Engineering, Sekolah Tinggi Teknologi Payakumbuh, Indonesia
Department of Civil and Environmental Engineering, Faculty of Engineering, Gadjah Mada University,
Indonesia
4
Department of Informatics, Faculty of Engineering , Universitas Islam Riau, Pekanbaru, Indonesia

ABSTRACTThe study of wooden plate bamboo connection system with the addition of wooden clamp was carried out
taking into account the variety the angle of the stems at the joint. The loading was preceded through theapplication of compressive force at the joint’s member under studied up to reaching the maximum load and theconnection was collapsed. It is known that the strength of bamboo not parallel to the direction of fiber is lower
than those parallel to fiber. Therefore, the strength of connection must be determined considering the strength ofbamboo not parallel to the fiber direction. The experiment was carried out under static loading on the bamboo
truss connections model with various angle of connection stems of 0o, 30o and 45o toward bamboo fiber
direction. From the test result, it was found that there is a decrease in the connection strength at stem angle of 30o
and 45o for about 16,80% and 12,21%, respectively, compared to the strength of the stem angle of 0o. The test
results also resulted the value of average elastic stiffness (Se) of the connection also indicates a decrease in the ofelastic stiffness value (Se) of the connection for the stem’s angle 30o and 45o for about 42,62% and 82,95%,
respectively, compared to stem angle of 0o. It can be concluded that there is a decrease in the strength andstiffness of the joints along with the increase in stem’s angle of the bamboo truss connection system using
wooden plate and clamp.
Keywords: Bamboo, Connection system, Wooden plate, Wooden clamp, Trussusing simple tools when employed in construction
practices. Bamboo culms is available in variety oflength and has high strength-weight ratio that makeit suitable to be used as structural material. As astructural material, bamboo can be used in a varietyof building components such as beams, columns,
partitions, floors or as a truss structure. In truss
structures, bamboo is commonly applied as
structural members in roof construction and bridge
structures.
High strength bamboo material cannot be
fully utilized due to the constraints of the connection
system. Researches to obtain a strong connection
system to overcome the problem of the weakness ofa connection have been widely done. Examples
include the connection system with connecting bolts
and filling cement mortar in internode of culm ofbamboo [3], the connection system with gusset plateof steel and devices connecting bolts [4], theconnection system with gusset plate of plywood
materials and devices connecting bolts [5] and theconnection system with gusset plate of plywood
materials or hard wooden planks and devices
connecting nails [6]. A connection system without
filler material on bamboo culms with wooden gusset

INTRODUCTION
Bamboo plants has been known as the plant of“source of lifehood”. As a source of life, bamboo
plants can produce a lot of oxygen. The roots ofplants can store water and strengthen the soil toprevent erosion, especially in the slope of a steep
cliff. For human life, the bamboo plant can be used
to basic human needs such as the need for food,clothing and housing.
Bamboo is highly an environmentally friendly
construction material that suitable to support green
building program as part of program to combat
global warming. Bamboo is very fast growth ofwhich can reach a maximum height of 15-18 cm in
4-6 weeks, while wood take year [1]. As aconstruction material, compared to wood, bamboo isa renewable material because of its rapid growth andfast growth as well as short period of planting ofabout 3 - 5 years, can used as a construction material[2].
Owing to its relatively high strength, stiffness
and lightweight characteristics, bamboo is apotential substitute for wood. It is also easily worked
401

SEE - Nagoya, Japan, Nov.12-14, 2018

plate and wooden clamps used to increase thecontribution to the shear at the connection has been
proposed by Masdar [7].

Woodenclamp

Need of the Study

90o

In the development of connection system onbamboo truss structure, the behavior aspects must be
considered, including the connections between
components of connection system. Futhermore, in
joint model of bamboo truss structure, behavior theconnection system for joint with variations of angle
between culm of bamboo need to known.

Woodengusset platet
bolt

bamboo(a)

The Objective of the Study
This paper addresses this subject, with theobjective of the study of: (i) knowing influence ofvariations of angle between culm of bamboo on joint
model againts strength and stiffness of bamboo truss
structure and (ii) experimentally, assessing theirstructural behaviour and performance under staticalloading.

(b)
Fig. 1DESCRIPTION OF CONNECTION SYSTEM

The proposed bamboo connection system[8], [9] (a) connection system on bamboo
truss structure (b) component of connection
system.
Woodenclamp

A connections systems that use of steel for gusset
plates and relatively heavy infill material has madethis connection system to be less desirable of thesignificant increase of structure weight andconstruction costs that make it uneconomical. A
bamboo connection system that possesses
lightweight nature but higher strength and lower cost
while keeping the form of the bamboo being
connected remains natural has been developed by
Masdar [7], [8], [9].
The proposed bamboo connection system
consists of bolts, wooden gusset plates and special
wooden clamps that have been adjusted with theshape and dimension of the bamboos being
connected as shown in Fig. 1. The wooden clamps
were placed between the bamboo and wooden gusset
plates make contact area that capable of mobilizing
its friction capacity to transfer the applied load forstronger and reliable connection as shown in Fig. 2.
The wooden clamp with ring angle of 90o wasdetermined to be optimal and thus recommended tobe applied to connections of bamboo truss structure[7]. Based on the results of previous research
conducted by Masdar [7], [8], [9] can be known thatthe strength of this bamboo connection system isinfluenced by several factors such as material
characteristics in the connection system, the angle ofwood clamps to the bamboo circumference and bolt
tightening force.

BambooBolt
Woodengussetplate(a)Fig. 2(b)Distribution of force on the bolt andwooden gusset plate to a bamboo culm(a) direct force into a bamboo culm(b) force through to a wooden clamps

EKSPERIMENTAL INVESTIGATIONThe study was conducted experimentally in twophases of testing. In the early stage of the research
preliminary testing on basic properties of thematerials used have been conducted. The second
phase of the research involved designing andfabricating several types of joint model of bamboo
truss structure with full scale sizes and tested
experimentally in the laboratory. The experiment
was carried out under static loading on the bamboo
truss connections model with various angle ofconnection stems of 0o, 30o and 45o toward bamboo
fiber direction
Test Set-up and material
Test Set-up
Tests on joint model of bamboo truss structure
are carried out in static loading. Static loading iscarried out until it reaches ultimate load and402

SEE - Nagoya, Japan, Nov.12-14, 2018

observation on deflection that occurs. In this test theload-displacement relationship is measured withload instrument in the form of load cell capacity 10
Ton and displacement with LVDT capacity of 50mm.
The testing method of basic material properties
was based on ISO N22157-2 [10] for bamboo and
ASTM D 143 for wood [11]. The testing method ofbearing strength of bamboo was adopted fromASTM D 5764 standard test method for evaluating
dowel bearing strength of wood and wood based
products [12]. Bearing strength test has been carriedout on bamboo and wood with deformed bolt
diameter of 12.2 mm.
The test set-up for joint models is shown in Fig.
3. The experiment was carried out under static
loading on joint model of bamboo truss structurewith various angle of connection stems toward
bamboo fiber direction is shown in Fig. 4. The test is
performed by giving compression test on bamboo
culm with three of varied of angle between bamboo
culm.

The connection system with three variation of joint
model on bamboo truss structure which are
distinguished by angle between bamboo culm, i.e.
0o, 30o and 45o, respectively. The result obtainedwith compression test on joint model of bamboo
truss structure is the strength, stiffness and behaviorof the connection by observing the amount of loadand deflection that occurred.
Material
The material used on the joint model of bamboo
truss structure is a natural material and a bolt madeof steel with a diameter of 12,2 mm. The type ofbamboo used as the main structural material in thisstudy was Gigantochloa atroviolacea. The gusset
platesware
madeof
Keruingwood(Dipterocarpaceae), while Mahoni wood (Swietenia
Mahagoni) was used for the clamps. The material
properties used on the joint model of bamboo truss
structure are shown in Tables 1, 2 and 3.
Table 1 Physical properties of material

Hidroulicjack
Load cell
Steel plate

Material

Densitygram/cm3

BambooWooden clamp
Wooden gusset plate

0,62
0,56
0,75

Moisture
Content%
12
12
12

Loading frame

Table 2 Mechanical properties of bamboo
Stress (MPa)Testingrange
averageCompressive
51 – 56
54
strength (σc)
Shear
7–8
7,8
strength (τ)
Bearing strength
33 – 41
37(fe)
Tensile strength
150 – 263
217
(σt)
Bending
55 – 79
58
strength (σt)
Tensile11219 – 18984
15450
MOE (Et)
Bending
12544 – 20620
16051
MOE (Eb)

LVDT

specimen
LVDT

Fig. 3Fig. 4

Test set-up for compression tests of thespecimen.

Table 3 Mechanical properties of wood
Stress (MPa)GrainMaterial
bearing shear Tensile
direction
(σ)
(σ)
(τ)
Wooden Parallel
46
6,2
clamp
Perpendicular 22
5,8
Wooden Parallel
62
8,4
gussetPerpendicular 26
4,1
plate

(b)
(c)
(a)
Specimen of compression test (a) bamboo
stem angle 0o (b) bamboo stem angle 30o(c) bamboo stem angle 45o

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SEE - Nagoya, Japan, Nov.12-14, 2018

force 45o toward the direction of bamboo fiber oneach specimen shows the maximum load ranged
from 1751 kg up to 1820 kg with displacemen
respectively is 38,2 mm and 29,58 mm.

Result and discussion
The strength and stiffness of the joints model
The relationship between load and displacement
obtained from the tests is shown in Fig. 5.
2500

α=0o
α= 30oα= 45o2000

Load (kg)

Table 4 The average maximum strength of theconnection on the compression test against
the bamboo stem angle on joint model ofbamboo truss structure
average
Averagemaximum
elastisNo.
Specimenstrength
stiffness (Se)
(kN)
N/mm
1.
MS (α= 0o)22,712051,522.
MS (α= 30o)
18,891176,933.
MS (α= 45o)
17,93
1121,33

1500
1000
500
0

0

10

20

30

40

50

Displacement (mm)Fig. 5

The relationship between load anddisplacement on joint model of bamboo
truss structure2500

Load (kg)

2000
1500
1000
500
0

0

5

10 15 20 25 30 35 40 45 50
bamboo stem angle (o)Fig. 6Graph of the relationship between the
maximum force average and bamboo stem
angle variation

There are nine joint specimens with three variationsof bamboo stem angle were tested undercompression as shown in Fig. 5. The result of testing
the connection model with the direction of force 0otoward the direction of bamboo fiber on eachspecimen shows the maximum load ranged from
2236 kg up to 2322 kg with displacemen
respectively is 32,24 mm and 25,05 mm. The resultof testing the connection model with the direction offorce 30o toward the direction of bamboo fiber oneach specimen shows the maximum load ranged
from 1802 kg up to 1967 kg with displacemen
respectively is 29,2 mm and 30,2 mm. The result of
testing the connection model with the direction of404

The compression test results shown that the
maximum strength on joint model of bamboo truss
structure is affected by the angle of a bamboo joint.
The greater the angle to the direction of bamboo
fiber on joint model of bamboo truss structure, thestrength and stiffness of the joints are smaller asshown in Fig. 6 and listed in Table 4.
Fig. 6 shown the relationship between the
maximum force average with various angle ofconnection stems of 0o, 30o and 45o toward bamboo
fiber direction, where the strength of the connection
decreases as the angle of force increases in theconnection system. The average maximum strengthon joint model of bamboo truss structure withbamboo stem angle of 0° 30° and 45° obtained fromthese compression tests were 22.71 kN, 18.89 kN
and 17.93 kN, respectively. From the test result, it
was found that there is a decrease in the connection
strength at stem angle of 30o and 45o for about
16,80% and 12,21%, respectively, compared to thestrength of the stem angle of 0o.
Similarly, the test results also resulted the valueof average elastic stiffness (Se) of the connection
also indicates a decrease in the of elastic stiffness
value (Se) of the connection for the stem’s angle 30o
and 45o for about 42,62% and 82,95%, respectively,
compared to stem angle of 0o.
The maximum loads and the loads that
correspond to the yielding of the connections weredifferent among variation of bamboo stem angle.
Based on the compression test results of theconnections depicted in Fig. 6 and listed in Table 4,
it can be concluded that the greater bamboo stem
angle, α, the lower the strength and stiffness of theconnection would be. It can be concluded that there
is a decrease in the strength and stiffness of thejoints along with the increase in stem’s angle of thebamboo truss connection system using wooden plateand clamp.

SEE - Nagoya, Japan, Nov.12-14, 2018

Failure modes of the joints model

In Fig. 7 can be seen the damage occurred on thebamboo is marked with a red line. In the specimentwith stems angle of 0o, 30o and 45o, the mostdamage occurs in bamboo, while the otherconnection system components damage is not so big
or just a small damage.

Failure modes of various angle of connection stems
are presented in Fig. 7.

The mechanical behavior of the components ofthe connection system of bamboo, wooden clamp,
wooden gusset plate and bolt connectors greatly
affect the strength of connection system on thebamboo truss structure. The mechanical behavior ofmaterial on connection system related to the strengthof the connection components need to be considered
to determine the strength of the connection. In thisresearch, analytical method considering failure modeand the strength of bamboo connection will beverified with result from experimental work. The
strength of connection of bamboo and the failuremode can be estimated from the formula which wasintroduced by Masdar [7], [8]. In Fig. 7, it appears
that the damage occurred is in the middle of theconnection system (bamboo). Failure mode I occurs
in the specimens. Failure mode I occurs when thebamboo bearing is reached. It can be concluded, The
component of the connection system determines thestrength of bamboo connections.

Bamboo bearing
damage(a)

CONCLUSION
Bamboo bearing
damageThis paper presented a study about
implemetation of connection system of wooden plate
and wooden clamp on joint model of bamboo truss
structure. The proposed connections system were
implementatied considering that information andreferences about joint model of bamboo truss
structure are very importanted. The following main
conclusions may be drawn from this study:
1. There is a decrease in the connection strength
at stem angle of 30o and 45o for about 16,80%
and 12,21%, respectively, compared to thestrength of the stem angle of 0o.
2. elastic stiffness (Se) of the connection also
indicates a decrease in the of elastic stiffness
value (Se) of the connection for the stem’s
angle 30o and 45o for about 42,62% and82,95%, respectively, compared to stem angleof 0o.
3. There is a decrease in the strength and stiffnessof the joints along with the increase in stem’s
angle of the bamboo truss connection systemusing wooden plate and clamp.
4. The mechanical properties of the basic material
influenced the overall connection behavior,namely the bearing strength, shear strength andtensile strength perpendicular of grain, wherein the proposed connection system failure
generally occurs in bamboo.

(b)

Bamboo bearing
damage(c)Fig. 7

Failure modes of the specimen (a) bamboo
stem angle 0o (b) bamboo stem angle 30o(c) bamboo stem angle 45o

405

SEE - Nagoya, Japan, Nov.12-14, 2018

Bambo Workshop, 1988. pp. 242-246.
[7] Masdar A., Suhendro B., Siswosukarto S. andSulistyo J., The Study of Wooden Clamp forStrengthening of Connection on Bamboo Truss
Structure.
JurnalTeknologi(Sciences
Engineering), Vol. 72, Issue 5, 2015, pp. 97-103.
[8] Masdar A., Suhendro B., Siswosukarto S. andSulistyo J., Development of Connection System
Bamboo Truss Structure, Proceedings of 4thInternational Confrence on Sustainable Future
fo Human Security, 2013, pp. 78-86.
[9] Masdar A., Suhendro B., Siswosukarto S. andSulistyo J., Influenced of bolt of tighening’s
force to The Strength of Connection System of
Bamboo Truss Structure With Wooden Clamp,
Procedia Engineering, 2017. Vol. 171. pp.
1370-1376.
[10] ISO N22157-2. Bamboo-Determination of
Physical and Mechanical Properties, Part 2,
Laboratory Manual, 2004.
[11] American Society for Testing and Materials.
2008. Annual Book of ASTM Standards 2008–
Section 4 Volume 04.10 Wood. American
Society for Testing and Materials.
[12] American Society of Mechanical Engineer,
ASTM D5764: Standard Test Method for
Evaluating Dowel-bearing Strength of Woodand Wood-based Products. Annual Book of
ASTM Standard, 2002. Vol. 04.10., WestConshohocken, PA, USA.

ACKNOWLEDGEMENTS
This study was conducted by using the researchfunding of Hibah Berbasis Kompetensi. It is funded
by DRPM DIKTI, Ministry of Research, Tecnology
and Higher Education of Indonesia, Ref. No.
065/K10/KONTRAK-PENELITIAN/2018(DIPA
Kopertis Wil X). The authors warmly thank all thesponsors and collaborators, especially all the bamboo
lovers.

REFERENCES[1] Akinlabi E. T., Fenin K.A., and Akwada D.R.,
Bamboo The Multi Purpose Plant, Spinger
International Publishing, 2017, pp. 1-3.
[2] Morisco, Rekayasa Bambu, Nafiri Offset, 2000,
pp. 1-87.
[3] Trujillo, D.J.A. Axially Loaded Connection in
Guadua Bamboo, Proceedings of the 11th
International Conference on Non-conventional
Materials and Technologies, 2009, pp 1-8[4] Morisco, Sambungan dengan Celah Pengisi.
Jurnal Forum Teknik, Vol. 24 No.1, 2000, pp.
99-109.
[5] Davies C., Bamboo Connections. The
Department of Architecture and Civil
Engineering. Bath: The University of Bath,2009, pp. 46-47.
[6] Misra, H. N. Know How of Bamboo House
Contruction, Proceedings of International406

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EXPERIMENTAL INVESTIGATION OF SEISMIC PERFORMANCEOF REINFORCED BRICK MASONRY INFILLED REINFORCED
CONCRETE FRAMES WITH A CENTRAL OPENING
Maidiawati1, Jafril Tanjung2, Yulia Hayati3 and Hamdeni Medriosa1
Civil Engineering and Planning Faculty, Padang Institute of Technology, Indonesia;
2
Engineering Faculty, Andalas University, Indonesia
3
Engineering Faculty, Syiah Kuala University, Indonesia

1

ABSTRACTThis paper discusses the experimental results of reinforced concrete (RC) frame with brick infills with acentral opening with and without rebar reinforcements on the opening interface to the masonry. 1/4 scale-downof single-story single-bay RC frame specimens were constructed. These specimens included one RC frame
without infill, one unreinforced brick masonry infilled frame, two unreinforced brick masonry infilled frameswith a central opening and two brick masonry infilled frames with a central opening with 2Ø6 steel
reinforcements embedded in infill above and below openings. The opening size to the panel area ratios were25% and 40%. All the specimens were subjected to in-plane reversed cyclic lateral loading. Consequently, theexperimental results show that the existence of the opening reduces the stiffness, the lateral strength, and energy
dissipation of the RC infilled frame system. However, the infilled frames with 25% and 40% openings showed
better performance compare to bare frame specimen. Although the strengthening by using embedded rebars does
not significantly increase the performance of the RC frame system, the brick infill with horizontal
reinforcements installed above and below the opening was verified to resist large deformation of masonry infill
in out of plane direction.
Keywords: Brick wall with opening, Lateral strength, Reinforced concrete frame, Reinforced masonry infill,
Stiffness.

concept. Consequently, the lateral force of infill canbe derived as a function of strut width [6]. The
proposed analytical model has been verified throughexperimental results of brick infilled frames.
All the past studies mentioned above are focused
only on the performance of RC frames with solid
brick infills and neglected the presence of infills
with openings assuming no contribution from infills
with openings on seismic performance of RC frame[7]. However, a lot of studies reported that masonry
infills with opening affect to reduce the lateralstrength and stiffness of infilled frame structure inwhich it depends on area and location of the opening
in panel wall [8]-[10]. This circumstance revealed
that the seismic behavior of the infilled frame with
opening still was not known well. Maidiawati [8]carried out an experimental study on brick infilled
frames with openings through monotonic lateral load
tests. The results disclosed that the openings inbrick-masonry infill control the failure mechanism,
the lateral strength and the stiffness of the overall
structure. Failure of infill occurred at the corners of
openings as the weakest part of the panel [8]. In thecurrent study, the behavior of RC frames with brick
infills with a central opening with steel
reinforcements placed above and below openings
was investigated through cyclic lateral load tests.

INTRODUCTION
Contributions of brick masonry infills have been
ignored for seismic design of buildings in many
countries.
It seems because of deficiency ofunderstanding on seismic performance of brick
infills under seismic loads. Several studies havebeen performed by researchers for evaluating theeffects of masonry infill on the seismic performanceof RC frame buildings [1]-[5].
The first author has also conducted a series ofpast studies related to RC frame structure with brickmasonry infills [4]-[6]. The first author investigatedthe earthquake-damage buildings after the 2007
Sumatra earthquake in Padang city and nearby asreported in [4]. It was found that brick infill
contributed to resist the seismic load in the RC
building, and it made the building can survive during
the earthquake. Further, the author performed aseries of experimental test on RC frames without
and with brick infill under reversed cyclic lateralloading. The test results revealed that brick infill
increases the lateral strength and stiffness of thewhole structure however it decreases ductility ofstructure [5]. Moreover, an analytical method was
proposed to calculate the lateral strength of infill inelastic range based on a diagonal compression strut
407

SEE - Nagoya, Japan, Nov.12-14, 2018

dimensions and detailing structure which
represented the first story of typical Indonesian lowrise RC buildings. The cross-sectional andreinforcement arrangement of frame elements areshown in Fig. 1(a). The figures 1(b) to 1(f) show thespecimens of IFSW, IFO-1, IFO-2, IFOR-1, and IFOR-2,
respectively. Table 1 summarized the specimens andtheir variance. Brick units of 1/4 scale clay bricks ofdimensions of 60 mm in length, 30 mm in width and
13 mm in height and mortar beds with thecomposition of cement: water = 1: 0.5 were used toconstruct the infills. The wall surfaces wereplastered with mortar of 5.0 mm in thickness.

EXPERIMENTAL PROGRAM
Test ModelSix of 1/4-scaled single bay and single story RC
frame specimens were constructed. The parametersstudied in this experimental evaluation were
influence of ratio of opening size to panel wall area,
α, of 25% and 40% and effects of 2Ø6 reinforcement
horizontally embedded at the below and above theopening. No shear connectors were used between
columns and infill. The elements of RC frame of all
specimens were constructed with identical
200

125

900

125

100 100

200
100 100

100

200

100

PVC 1"

200

PVC 1"

1550
900

125

125

Selimut Beton tb:15mm
6-50
4D13
200

200
PVC 1"

PVC 1"

200

200

4-25

200

200

4-25

4D10
4-50

1150 750

750

4-25

Selimut Beton tb:40mm
PVC 2"

4-25

PVC 2"

PVC 2"

200

200
1650
125

4D10

4D10

4-50

4-50
Selimut Beton tb:10mm

Selimut Beton tb:10mm

Pengekang pipa PVC O4

100

125

287.5

500
125

100

(b) IFSW specimen

287.5

700
100

6-50

700

500

6D13
Selimut Beton tb:40mm

100
250

50

250

125

450

450

900

50

125

250

(a) Bare frame specimen
200

500

200

200

200

200

350

350

500

200

Horizontal rebar 2

Horizontal rebar 2

200

6

6

200

(c) IFO-1 specimen
125

650

(d) IFOR-1 specimen

125

125

165

650

125

165
Horizontal rebar 2

420

420

165

165

Horizontal rebar 2(e) IFO-2 specimen

66(f) IFOR-2 specimen

Fig. 1 Detailed drawing of specimens.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1. Experimental parameters of the specimens
Specimens

ColumnBF

crosssection:
125x125
main bar:
4D10
hoop: 2Ø4-50

IFSW
IFO-1
IFOS-1
IFO-2
IFOS-2

residual drifts in each loading cycle.
Figure 3 shows the loading history of cyclicloading referred to [11]. The drift angel R used tocontrol the incremental lateral load applied on
specimens was an initial cycle to R=1/800 and thenfollowed by two cycles to R=1/400, 1/200, 1/100,
1/50, 1/25, 1/12.5 and 1/10. If the specimens failed
before the final cycles, the loading was stopped.

Brick infill
α (%) Reinforcement
0

-

0
25
25
40

2Ø6
-

40

2Ø6

TEST RESULTS AND DISCUSSION
Failure Process and Mechanism
Failure process and mechanism for all specimens
were investigated during experimental works. The
following compares the failure process of specimens.

Material Properties
The mechanical properties were the same for all
specimens which were obtained through material
samples tests. The compressive strengths of concreteand brick masonry prism were 49.9 N/mm2 and 13.0
N/mm2, respectively. The yield strengths ofreinforcements were 390.2 N/mm2, 346.8 N/mm2,
462.0 N/mm2, and 421,1 N/mm2 for rebars of Ø4,
Ø6, D10, and D13, respectively. The tensile
strengths of reinforcements were 598.3 N/mm2,
448.6 N/mm2, 619.7 N/mm2 and 582.4 N/mm2 forrebars of Ø4, Ø6, D10, and D13, respectively. The
average compressive strength of brick was 10.9
N/mm2.

BF specimen
The initial flexural crack was detected during thecycle of 1/400 at the top of the tensile column at thelateral displacement of 1.2 mm and initial shear
crack was during the cyclic 1/200 at 3.8 mm lateraldisplacement at the bottom of the compressive
column. The cracks developed during the next cycle
loading. During the cycle of 1/12.5, the compressive
column failed in shear at 58.8 mm lateraldisplacement. Soon after the shear failure of bothcolumns, the lateral strength significantly degraded.
Fig 4(a) shows the condition of BF specimen under
the cyclic loading to drift angle 1/50 rad.

Loading Method and Measurement
IFSW specimen
A separation crack was discovered between
column and wall at loading cycle of 1/800. Initial
flexural and shear cracks were found out at tensile
column during the cycle of 1/400 at the lateraldisplacements of 1.3 mm and 1.6 mm, respectively.
An initial diagonal shear crack was observed during
cycle 1/200 at 3.4 mm displacement at the center ofthe panel wall. Shear failure of brick wall occurred
during the cycle 1/50, and then the lateral strength
degraded significantly. After the failure of the brickwall in out of plane direction, the boundary column
failed in shear at the cycle of 1/12.5. Fig. 4(b) shows
the condition of the IFSW specimen by cycles to 1/50
rad.

The experimental tests were conducted at theStructural and Construction Material Lab. of Civil
Engineering Dept., Syiah Kuala University. The
specimens were subjected only by reversed cyclic
lateral loads as shown in the schematic of the test
setup and loading system in Fig. 2.
The horizontal and vertical displacements of thespecimens were measured with transducers
positioned on specimens. The applied loads, as well
as displacements, were monitored throughout the
tests. To identify the failure process and mechanismsof specimens, initiated cracks and crack propagation
were marked on the specimens at the peak andFig. 2 Schematic view of test setup

Fig. 3 Loading history.
409

SEE - Nagoya, Japan, Nov.12-14, 2018both columns and shear cracks at the bottom of thecompressive column were developed. Shear cracks
propagated in infill at the left and right sides of the
opening and below the opening. Shear failure oftensile column occurred at the cycle 1/12.5. Infill
failed in out of plane direction at the cycle 1/10. Fig.
4(e) shows the condition of IFOR-1 specimen bycycles to 1/50 rad.

IFO-1 specimen
Initial shear cracks in infill existed at the top left
corner of opening and the bottom right corner of
opening at a displacement of 0.45 mm during thecycle 1/800. Initial flexural crack at the tensile
column happened at 1.9 mm displacement during thecycle 1/400. Initial shear crack appeared at thetensile column at 3.5 mm displacement during thecycle 1/200. Infill wall failed in shear at the cornerof opening at the cycle 1/25 and column failed inshear at the cycle 1/12.5. Fig. 4(c) shows thecondition of IFO-1 specimen by cycles to1/50 rad.

IFOR-2 specimen
During the cycle 1/800, initial flexural and shear
cracks in infill were detected at the top left corner ofthe opening at 1.4 mm displacement. Initial flexural
crack at the top of the tensile column was observedat the displacement of 1.1 mm during the cycle
1/400. The initial shear crack appeared at the top of
the tensile column at the displacement of 2.9 mm. At
the subsequent cycles, propagation of flexural andshears cracks in both columns and development ofshear cracks at the left side was noticed. The top of
the tensile column failed in shear during the cycle
1/12.5. Moreover, brick infill failed in out of plane
direction at the cycle 1/10. Fig. 4(e) shows thecondition of IFOR-1 specimen by cycles to 1/50 rad.

IFO-2 specimen
During the cycle 1/800, it was found out theinitial flexural crack at the tensile column at 0.4 mm
displacement and the initial shear crack in infill at
the left top corner of opening at the displacement of
0.8 mm. During the cycle 1/200, initial shear crack
at the top of the tensile column was explored at 2.4
mm displacement. Shear failure of the bottom
compressive column occurred during the cycle
1/12.5 followed by failure of the wall in out of
direction. Fig. 4(d) shows the condition of IFO-2
specimen by cycles to 1/50 rad.

Comparison of Seismic Performance
IFOR-1 specimen
Initial shear crack at the left corner of the
opening and initial flexural crack above the openingof infill was observed at 0.75 mm displacement
during the cycle 1/800. Initial flexural crack took
place at the tensile column at the displacement of 1.7
mm during the cycle 1/400. An initial shear crack
appeared at the tensile column at the displacement of
3.8 mm during the cycle 1/200. During thesubsequent cycles, flexural cracks at along height of

Figure 5 shows the relationship between lateralforce and lateral displacement in hysteresis loops
and envelop curves to indicate the seismic
performance of specimens. The bare frame (BF) andsolid infilled frame (IFSW) specimens achieved the
maximum lateral strength of 51.3 kN and 127.7 kN
at the 57.8 mm and 7 mm displacements,
respectively.

(a) BF specimen(b) IFSW specimen(c) IFO-1 specimen(d) IFOR-1 specimen(e) IFO-2 specimen(f) IFOR-2 specimen

Fig. 4 Specimen at drift angle, R=1/50.
410

SEE - Nagoya, Japan, Nov.12-14, 2018

In the cases of infilled frames with opening
specimens, the maximum lateral strength of 74.1 kN,
76.1 kN, 61.5 and 60.4 kN at 14.0 mm, 14.8 mm,
14.9 and 13.9 mm lateral displacements for IFO-1,
IFOR-1, IFO-2, and IFOR-2, respectively. It revealed thatthe presence of a center opening reduces the lateralstrength and stiffness of the overall infilled frame
structure. The solid brick infill increased the lateralstrength of RC frame by about 2.5 times comparedto the bare frame. The opening of 25% and 40% in
infill decreased the lateral strength of solid brick
infilled frame to 0.59 times and 0.48 times,
respectively. However, the lateral strengths of infills
with openings of 25% and 40% were higher 1.4
times and 1.2 times than that of the bare frame,
respectively. Based on the Fig. 5, it seems that thehorizontal reinforcements installed at the bottom andabove opening were ineffective to increase thelateral strength of the overall structure, but they
contributed to preventing the failure of infill in outof plane direction, and they effectively controlled
the growth of the shear cracks at the corners of the
opening. The deformation capacities of structure
were a deformation as the lateral force degraded to
80% after the maximum of the force that wasreached at displacements of 63.0 mm for BF, 27.7mm for IFSW, 57.7 mm for IFO-1, 59.5 mm for IFOR-1,
69.6 mm for IFO-2 and IFOR-2 specimens. It indicatesthat the infilled frames with a central opening moreductile than the solid infilled frame. The reinforced
opening infills were not more ductile thanunreinforced opening infills.

(a) BF specimen(b) IFSW specimen(c) IFO-1 specimen(d) IFOR-1 specimen(c) IFO-2 specimen(d) IFOR-2 specimen

Fig. 5 Lateral strength-displacement relationship.
411

SEE - Nagoya, Japan, Nov.12-14, 2018

Masonry Infill in the Behavior of RC Frame
under Seismic Loading, Journal of Engineering
Structures, Vol. 165, 2018, pp. 599-621.
[2] Mynarz M. and Mynarzova L., Non-Linear
Approaches to the Response of Brick Masonry
Wall to Lateral Loading, International Journalof GEOMATE, Vol. 14, Issue 42, 2018, pp. 7682.
[3] Perrone D., Leone M., and Aiello M.A,
Evaluation of the Infill Influence on the Elastic
Period of Existing RC Frames, Journal ofEngineering Structures, Vol. 123, 2016, pp.
419-433.
[4] Maidiawati, Sanada Y., Investigation andAnalysis of Buildings Damaged during the
September
2007
Sumatra,Indonesia
Earthquakes, Journal of Asian Architecture andBuilding Engineering Vol.7, No.2, 2008, pp.
371-378.
[5] Maidiawati, Sanada Y., Sanada, Konishi D.,
and Tanjung J., Seismic Performance ofNonstructural Brick Walls Used in Indonesian
R/C Buildings, Journal of Asian Architecture
and Building Engineering, Vol.10, No.1, , 2011,
pp.203-210.
[6] Maidiawati and Sanada Y., R/C Frame-Infill
Interaction Model and Its Application toIndonesian Buildings, Earthquake Engineeringand Structural Dynamics, Vol.46, Issue 2, 2017,
pp. 221-241.
[7] Choi H., Nakano Y., and Sanada Y., Seismic
Performance and Crack Pattern of Concrete
Block Infilled Frames, In Bulletin of ERS,
No.38, 2005.
[8] Maidiawati, Tanjung J., and Medriosa H.,
Conference proceedings, in AIP Conf.
Proc.1892 of IGNITE-AICCE’17, 2017, pp.
020013-1-020013-8[9] Mondal G., and Jain, S., K., Lateral Stiffness of
Masonry Infilled Reinforced Concrete (RC)
Frames with Central Opening, Earthquake
Spectr., Earthquake Engineering ResearchInstitute (EERI), Vol.24, No.3, 2008, pp. 701723.
[10] Mohammadi M., and Nikfar F., Strength andStiffness of Masonry-Infilled Frames with
Central Openings Based on Experimental
Results. Journal of Structural Engineering,
Vol.139, 2013, pp.974-984.
[11] Interim Testing Protocols for Determining the
Seismic Performance
Characteristic of
Structural and Nonstructural Component,”
FEMA 461, pp. 21-25, 2007.
[12] Rodrigues H., Varum H., Arede A., and Costa
A., A Comparative Analysis of Energy
Dissipation and Equivalent Viscous Dampingof RC Columns Subjected to Uniaxial andBiaxial Loading, Journal of Engineering
Structures, Vol.35, 2012, pp.149-164.

Energy Dissipated
Energy on frame structure due to the seismic
force can be dissipated by response of hysteresis
loop without a significant reduction in strength ofstructure [12]. Therefore, the area enclosed byhysteresis loops indicated in Fig. 5 can be evaluatedto represent the energy dissipated of specimens. The
comparisons of cumulative energy dissipation of
specimens are presented in Fig. 6. The figure
exhibits that the dissipated energy of the infilled
frame decreased as opening existed in infill. Theenergy dissipation of the infilled frame with openingof 40% is the same with that of the bare frame. In
the case of infilled frames with embedded rebar
reinforcements, their energy dissipations wererelatively the same with that of unreinforced ones.

Fig. 6 Cumulative energy dissipated of specimens.
CONCLUSION
Experimental tests on brick infilled RC framewith a central opening and with/without
reinforcements in infills were carried out undercyclic lateral loading to assess their seismic
performance. As the results, a central opening
reduced the lateral strength and energy dissipation ofsolid infilled frame. Horizontal reinforcements
embedded in infill above and below the opening
were ineffective to increase the lateral strength andenergy dissipation, however, it verified to resist
large deformation of masonry infill in out of plane
direction.
ACKNOWLEDGEMENT
This paper reports the results of researchdeveloped under financially supported by the
Ministry of Research, Technology, (DIKTI)Indonesia,
withthereference
529/27.O10.4.2/PN/2017.
REFERENCES[1] Dautaj A.D., Kadiri Q., and Kabashi N,
Experimental Study on the Contribution of412

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE ANALISIS OF RIVER RUNOFF IN THE ABUKUMA RIVER
BASIN
Masanobu Taniguchi1, Hiroyuki Ii2Faculty of system engineering, Wakayama University, Japan 1,

1

ABSTRACTThe characteristic of the river runoff in the Abukuma River Basin has been not to clarify. The area of the
Abukuma River basin is 5,400 km². The flow path extension of the Abukuma River is 239km. There is thehydrophobic pass from the Inawashiro Lake. The water is used by some cities, so the water pass is complex,
therefore the analysis of river runoff is difficult. It is important that the river runoff in the each little basin forfloods estimation. The river cross section was surveyed, and the river flow rate is calculated. In the flood causedby the typhoon in August 1985 which recorded the largest flood after the war, it suffered a tremendous damage.
The research objective is clarify the ratio of river runoff of each little basin. The analysis will be basic information
for the analysis of pollutant load and movement of cesium.
Keywords: runoff, river flow,Abukuma River,precipitation quickly. [3]The precipitation data was imported fromdownloaded at government original data notconverted. The used data is Meteorological Agency
and Ministry of Land, Infrastructure and Transport(MLIT).[4] Moreover, the water level and flow rate
data is imported from government data, MLIT. The
analysis system can handle big data, and the datas
linked GIS data, the system can execute several
runoff analysis. The flow rate data was not measured
in few year, so the flow rate was estimated by thewater level data.
The river cross section was measured the distancefrom the bridge to riverbed between 5m length each.
In addition, river velocity is observed, velocity
decided the by average of three times measured. The
missing data of flow rate can be estimated used byrelation between water level and river cross section.

INTRODUCTION
The gradient of Abukuma River is gentle, so thecities in the basin was damaged from floods often in
past. So it is important to know the flow rate forfloods countermeasure, the river basin has lots of data
since 1930 in some observing station. The Typhoon
gave big damage often in 1938, 1941, 1943, 1947,
1948, 1950, 1958, 1966, 1971, 1981, 1982, 1986,
1991, 1998, and 2002. In other hand, the droughtdamage has also occurred in other years in the
Abukuma River Basin in 1967, 1973. 1978, 1987,
1997. The Abukuma Basin River history was old, theobserving station was constructed in early period in
1900’s. The first Dam, Shinobu Dam in the Abukuma
River Basin was constructed in 1939. The Basin has
problem of waterless in long period. The agriculture
water was send from the Inawashiro Lake by the
Asakasosui water pass in 1890 in first, the water pass
was connected to the larger rice field region in 1900’s.
The basin is researched in past about water quality
and floods.[1][2]Therefore, in the Abukuma River Basin, the water
moving was changing from 1938 to 2017, it isimportant to clear the relation between water runoffand precipitation. The research will be clarify the
relation between the rain runoff and river runoff ofbefore and after the construction of dams and land usechanges.

OVERVIEW OF RESEARCH AREA
N
Observing Station
Paddy
Orchard
ForestWaste Land
Building
Traffic
Other

RESEARCH METHODRiver or Lake
Beach

The water runoff analyze system is developed. The
system has database on the river structure made by
GIS data. Therefore, the system is able toautomatically calculated upper area, compared with

Sea
Golf course
0

413

10

20

30

40km

Atarume
YabukiNoji
Yomogita
Katasone
DoumekiYahataShiroishi
Atami
Nohonmatsu
Yunohara
Tuchiyu
TamogamiNiwasaka
Naganuma
Takidaira
Ohuchi
Ohtakine
TadanoIshikawa
Nasugawa
MafuneTokiwaFunahiki
Shitigasyuku Dam
Shiga
Yamakiya
Miharu Dam
Suzuriishi
Kukidate
Kohriyama
KumadoKanayama
IwanumaSeki
Nametsu
Dake
KakudaShionokura
Tohgatta
Kosugou

200

2009/12/1

2009/11/1

2009/10/1

2000

TyphoonDrought

2016/1/1

2013/1/1

2010/1/1

2007/1/1

2004/1/1

2001/1/1

1998/1/1

1995/1/1

1992/1/1

1989/1/1

1986/1/1

1983/1/1

1980/1/1

1977/1/1

1974/1/1

1971/1/1

1968/1/1

1965/1/1

1962/1/1

1959/1/1

1956/1/1

1953/1/1

1950/1/1

1947/1/1

1944/1/1

1941/1/1

0

1938/1/1

1000

1935/1/1

Precpitation (mm/year)

Fig.1 shows overview of Abukuma River Basin.
The area in Abukuma River basin is 5,400 km². The
flow path extension of the Abukuma River is
239km.[5] The length is 2nd long in Tohoku Area inJapan. The population is about 1.78 million people in
the Basin. The Abukuma River has 17 cities inFukushima Prefecture, has five cities in Miyagi
Prefecture. The Abukuma River is originated at
Asahidake in South - East of Fukushima. The land useof 56% in whole basin is forest, 16% is paddy, 14%
is orchard, and 6% is building. The water of theInawashiro lake inflows in the upper stream of
Abukuma River Basin shown in arrow in figure. The
sending water is mainly used for paddy. So it wasestimated that the sending water increases the amountof river basin water. However, in other side, Dams
control the river water, it is considered that theamount of water in the Basin does not necessarily
increase.

2009/9/1

2009/8/1

Fig.3 Time series of annual precipitation from 1935
to 2017 at Fukushima.
Fig.3 shows time series of annual precipitationfrom 1935 to 2017 at Fukushima. The annual
precipitation is constantly not changed and theaverage is 1143 mm/year. The max value is 1613
mm/year in 1991, and minimum is 652 mm/year in
1973.

RELATION BETWEEN WATER LEVEL AND
FLOW RATE

3000

2000

2016/1/1

2013/1/1

2010/1/1

2007/1/1

2004/1/1

2001/1/1

1998/1/1

1995/1/1

1992/1/1

1989/1/1

1986/1/1

1983/1/1

1980/1/1

1977/1/1

1974/1/1

1971/1/1

1968/1/1

1965/1/1

1962/1/1

1959/1/1

1956/1/1

1953/1/1

1947/1/1

1944/1/1

0

1941/1/1

1000

1938/1/1

Fig.2 shows time series of daily precipitation in2009. There are 40 observing station of precipitation
around the Abukuma Basin. Some observing station
did not have precipitation, and the distance between
stations is different. Since the basin area is too big,the max of precipitation is different place each event.
Therefore, it was necessary to calculate rain runoff
with each little basin. The precipitation in one event
is different with each places, so the sum of rain runoff
in the Abukuma River Basin needs to be calculated
by sum of multiply the precipitation and basin area.

計算値
流量1935/1/1

Flow rate (m3/sec)

4000

THE TIME SERIAS OF PRECIPITATION

1950/1/1

2009/7/1

2009/6/1

2009/5/1

2009/4/1

2009/3/1

0

2009/2/1

100

2009/1/1

precipitation(mm/hour)

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig.4 The time series of the flow rate from 1935 to2016 at Hongu

414

SEE - Nagoya, Japan, Nov.12-14, 20182010/1/1

2009/12/1

2009/11/1

2009/10/1

2009/9/1

2009/8/1

2009/6/1

2009/5/1

2009/4/1

2009/2/1

0

2009/3/1

1000

2009/7/1

Yahatarain runoff (m3 /sec)
Fukushima
Shirakawa
Ejiri
IwanumaTateyama
Akutsu2009/1/1

runoff (m3/sec)

2000

Fig.6 The time series of flow rate and rain runoff in 2009

Flow rate (m3/sec)

3000

amount of using water increased. Many water is used,
and the Basin has not enough Dams. Six Dam built in
the period, and two dams built in 2000’s. First Dam
built in 1938, so if it is considered the influence ofdam, it is need to estimate the flow data from thewater level for the comparing before 1938. Therefore,
as the flow rate has related to the water level, the flowrate was calculated from relation with the water level.

Calculeted flow rate
Flow rate (m3 /sec)

2000

1000

COMPARING WITH THE FLOW RATE AT EACH

0-0.1 1y=82.94x^1.80

2

3 4 5 6 7
Waterlevel (m)OBSERVING STATION

8

9
The flood flowing is not constant, so the velocity
cannot be measured easily. Therefore, the flow rate inflood time was not sometimes measured. So, the flowrate was calculated by the water level, the fit line
formula of constant was calculated. Table 1 shows thelist of the fit line formula of constant at eachobserving station.

Fig.5 The relation between the water level and theflow rate from 1935 to 2016.

Fig.4 shows the time series of the flow rate from1935 to 2016 at Hongu, middle stream of observing
station in the Abukuma River Basin. Fig.5 shows therelation between the water level and the flow ratefrom 1935 to 2016. The flow rate was measured from1942, so generally the flow rate is not measured
directly, thus the flow rate is calculated from waterlevel, and the calculated flow rate was compared withsurvey data sometimes measured. The dot line shows
calculated from the water level data. The calculated
flow rate data is fitting from the relation between thewater level and the flow rate statistically. [6][7]The fit line function is shown in formula (1).
𝒇𝒇(𝒙𝒙) = 𝟖𝟖𝟖𝟖. 𝟗𝟗𝟗𝟗𝒙𝒙𝟏𝟏.𝟖𝟖𝟖𝟖
3f(x):flow rate (m /sec)

Table.1 The calculated constant parameter

Observing station
AkutsuTateyama
Iwanuma
Ejiri
Kuroiwa
Shirakawa
Fukushima
Yahata(1)

constant a constant b
190.500
1.2
4.277.E-13
12581.486
1.05
0.016
5
59.9472.15
117.0072.15
345.145
1.26
f(𝑥𝑥) = a𝑥𝑥 𝑏𝑏

x:water level (m)Compare with the flow rate before 1960, the peakof flow rate was small after 1960. From 1967 to 1998,
drought occurred shouwn in Fig.3, moreover theperiod was the High Growth Period in Japan, so the

THE COMPARING OF THE FLOW RATE
Fig.6 shows the time series of flow rate and rain
runoff in 2009. Fig.7 shows the time series of rate of415

SEE - Nagoya, Japan, Nov.12-14, 2018

Shirakawa Rate
Fukushima Rate
Yahata Rate
Akutsu Rate
Tateyama Rate
Ejiri Rate
rain runoff (m3 /sec)

2

2010/1/1

2009/12/1

2009/11/1

2009/10/1

2009/9/1

2009/8/1

2009/7/1

2009/6/1

2009/5/1

2009/4/1

2009/3/1

0

2009/2/1

1

2009/1/1

runoff rate

3

Fig.7 The time series of runoff rate against the flow rate at Iwanuma in 2009
runoff against the flow rate at the lowest station of the
Abukuma Basin, Iwanuma in 2009. The change offlow rate tend to same change at each observing
station. The rate of each flow rate of observing station
against the lowest point was calculated. It is need toknow the rate of water runoff in the river basins, so t
the flow rate at the main stream was compared. The
observing station is lowest observing station of
Iwanuma, next Ejiri, Tateyama, Yahata, Fukushima,
Shiraskawa. Generally, the flow rate at lowest stationis biggest, however comparing with the flow rate at
Iwanuma and at Ejiri, the flow rate is sometimes
reversed in two station. There is another river basin
flow into at upper Iwanuma, however the flow rate do
not increased. So the riverbed is sand, it is estimatedthat the infiltration is occurred. Fig.7 shows the timeseries of runoff rate against the flow rate at Iwanuma
in 2009. The runoff rate was calculated by next
fowmula.
𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 =𝑒𝑒𝑒𝑒𝑒𝑒ℎ 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟
𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑎𝑎𝑎𝑎 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼

the runoff rate tend in middle July is same in fine days.
However, in rain time, the runoff rate is changeable,
and the runoff rate increased to about one at someobserving station. It was estimated that there is
rainfall is in mainly upper area, and so some basin has
no rain, it is necessary to calculate the amount ofrainwater by sum of the rainfall in whole basin.

rain runoff (m3/sec)

1000

2009/8/1

7/29

7/31

7/28

7/30

7/26

7/25

7/27

7/24

7/23

7/22

7/19

7/21

7/18

7/20

7/17

7/16

7/15

7/12

7/14

7/13

7/11

7/10

7/7

7/9

7/6

7/8

7/5

7/2

7/3

7/4

0

2009/7/1

rain runoff (m3 /sec)
Shirakawa
Kuroiwa
Fukushima
YahataAkutsuTateyama
Ejiri
Flow rate at Iwanuma

Fig.8 The time series of the water runoff in July 2009

Fig.8 shows the time series of the water runoff inJuly 2009. The peak of flow rate tend to be late than
1day of the peak of rain runoff. The flow rate tends tobe higher in 5 days after precipitation. Therefore, if
the water runoff of analysis was carried out, it isnecessary to calculate the 5 days of data at least. The
Abukuma River Basin has some dams, minimum
flow rate is promised. The rain runoff is 200m3/sec
from 1 July to 3 July, and the flow rate is same value
in the period. The flow rate and rain runoff isbalanced, the values is constant. The rain runoff isless from 11 July to 20 July, the flow rate change little.
The minimum flow rate is 115m3/sec, if the rain
runoff is higher than the flow rate, it is estimated thatthe flow rate increase.

(2)

If the runoff rate shows one, it shows that the flowrate was not changed. In addition, if he value is bigger
than one, it shows that the flow rate decreased. The
runoff rate at Ejiri shows almost more than one, therate increased in rain time shown by blue dot line in
Fig.7, and decreased in fine days. The runoff rate atanother observing station shows almost less than one.
The runoff rate average at Yahata is 0.64, the value at
Tateyama is 0.65, the value at Fukushima is 0.50 thevalue at Akutsu is 0.28, and the value at Shirakawa is
0.04. The upper basin area at Yahata is 4128km2,
Fukushima is 3304km2, and Akutsu is 1940km2. The
runoff rate was calculated less about 10% than basin
area rate against the whole basin.
In rain time, the flow rate is increased allobserving station, and the flow rate is seemed nearvalue at each stations in Fig. 6. The rate of flow rate
against the lowest station was compared. In middle
January, the runoff rate is constant in fine days, and
416

SEE - Nagoya, Japan, Nov.12-14, 2018

runoff was calculated by 50% of amount of the rain
runoff at each basin. The reason is that the all of the
precipitation do not flow out directly. The rain runoff
was adjusted to the flow rate value. The rain runoff at
Shirakawa observing station was 96 m3/sec, Akutsu
was 492m3/sec, Fukushima was 1023m3/sec, Ejiri
was 1577m3/sec and Iwanuma was 2018m3/sec.

All 20180708(解析)6におけるrain runoff (m3/sec)の変化

rain runoff (m3/sec)
Shirakawa
Kuroiwa
Fukushima
YahataAkutsuTateyama
Ejiri
Flow rate at Iwanuma

4000

3000

2000

8/31

8/30

2009/9/1

8/29

8/28

8/27

8/26

8/25

8/24

8/23

8/22

8/21

8/20

8/19

8/18

8/17

8/16

8/15

8/14

8/13

8/12

8/9

8/11

8/8

8/10

8/7

8/6

8/5

8/4

8/3

0

8/2

1000

2009/8/1

rain runoff (m3/sec)

5000

Table. 2 The list of flow rate and rain runoff at the
typhoon 9 in August 2009

Fig.9 The time series of the water runoff in August
2009

年月日 (m3/sec) Iwanuma Ejiri Tateyama Yahata Fukushima Akutsu Shirakawa rain runoff
2009/8/9
214 365
201
191
165
134
18
777
4095
2009/8/10
956 1192
1108
1182
1045
1021
109
2009/8/11
1553 1714
1188
1046
776
496
57
122

Table. 2 shows the list of flow rate and rain runoff
at the typhoon 9 in August 2009. The flow rate datashows observed data. The Shaded data was comparedwith the rain runoff. As the flow path extension of the
Abukuma River is 239 km, if the flow velocity is
2m/sec between 200 km distance, the reach time iscalculated about 1 day. The calculation is very rough,however the result shows important information. The
Shirakawa observing station has directly rain and theother stations is far from rain place.
Therefore, the rain runoff was compared with thenext day of flow rate, except the Shirakawa observing
station. The flow rate is same to 50% of amount of therain runoff at each basin, it is estimated that the runoff
rate is average 50%. The flow velocity was estimatedabout 2m/sec at the typhoon time.

CONCLUSION
The research will be clarify the relation between
the rain runoff and river runoff of before and after theconstruction of dams and land use changes. The waterrunoff analyze system is developed. The system has
database on the river structure made by GIS data.
Therefore, the system is able to automaticallycalculated upper area, compared with precipitation
quickly. The long-term flow rate is compared, it wasestimated that the flow rate is not effect from dams,
the cause of less flow rate is little precipitation in1990’s, and the max of flow rate did not decreased
dams construction before and after. The typhoon
influence was analyzed by the distribution of rain
runoff, the flood reach time was about 1day, and theflow velocity was estimated to 2m/sec.
.
REFERENCES

Fig.10 The distribution of integrated rain runoff fromupper stream at August 10, 2009
Fig.9 shows the time series of the water runoff inAugust 2009. In August 10, the rain runoff is
4000m3/sec.it is estimated that the peck of the rain
runoff is caused by the typhoon 9. West Japan is big
damaged by the typhoon 9. Compare with the peak ofrain runoff and the peak of flow rate, the peak of flowrate is tend delay one day except the Shirakawa
observing station. The Shirakawa observing station is
the most upstream observing station. The rain runoff
at Shirakawa observing station did not increased
compare with the other stations. It was estimated that
the Shirakawa observing station had no rain or a little.
Fig.10 shows the distribution of integrated rain runoff
from upper stream at August 10, 2009. The rain

[1] Tokuo KISHII, On the Flood Disaster in the
Abukuma River Basin at the End of August 1998,
Natural Disaster Research Report of the National
Research Institute for Earth Science and Disaster
Resilience 37 , pp. 91-105, 2001.
[2] Tsuyoshi KINOUCHI and Katumi MUSIAKE,
Water quality and nutrient loads in the abukuma
417

SEE - Nagoya, Japan, Nov.12-14, 2018[5] Digitalnational
land
information,
http://nlftp.mlit.go.jp/ksj/
Japan Meteorological Agency, http://www.jma.
go.jp/jma/index.html[6] Kazuyuki Mizumura, Hydrosphere hydrology,
1998.
[7] Isamu Kayane, Hydrology, Daimeido 1980.

watershed under normal flow condition, Water
Engineering paper, vol. 51, February 2007(inJapanese)[3] Ralia,https://www.wakayamau.ac.jp/~masa/profile/soft/index.html, 2018.
[4] Ministry of Land, Infrastructure and Transport,
Japan, Water information system, http://www1.
river.go.jp/418

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

INFLUENCE OF POZZOLANIC MATERIALS IN THE ADSORPTION
OF HEAVY METALS ON RED LOESS SOIL
1Pongsakorn Punrattanasin, 2Arnun Chantaduang and 3Chinawat

1,2,3Muktabhant Faculty of Engineering, Khon Kean University, Thailand

ABSTRACTThis study presents the results from laboratory in the adsorption of heavy metals on red loess when mixing
with Pozzolanic materials. The Pozzolanic materials consist of fly ash, bottom ash, rice husk ash, blast furnaceslag, silica fume, metakaolin, and Portland cement. Most of Pozzolanic materials are byproducts and easy to find.
Copper, nickel and zinc were selected as heavy metals and batch sorption test was selected as a method to evaluate
the sorption capacity. It was also found that the potential of Pozzolanic materials were ranged from Portland
cement, fly ash, bottom ash, blast furnace slag, rice husk ash, silica fume and metakaolin, respectively. The resultsfrom this experiment can be by identifying the adsorption isotherm model. The isotherm can describe and analyze
the adsorption potential. The Langmuir and Freundlich isotherm models were able to efficiently explain theadsorption behavior of the loess.
Keywords: Adsorption, Loess, Pozzolanic materials, Batch sorption test, Cement, Isotherm

the Unified Soil Classification System (USCS). The
Pozzolanic materials used to mix with the loess for
improve the adsorption capacity in this study (Fig.2)
consist of (1) fly ash (Fa), (2) bottom ash (Ba), (3)rice husk ash (Ra), (4) blast furnace slag (Bs), (5)silica fume (Sf), (6) metakaolin (Mk), and (7)Portland cement (Ce). All of the materials were dry
and were then sieved through sieve No. 16. Most ofPozzolanic materials are byproducts and easy to find.
The chemical analysis by X-ray fluorescence (XRF)
technique and the specific surface area of thematerials are summarized in Tables 2 and 3. In thisstudy, a 5% of Pozzolanic materials was mixed with
the 95% of loess by weight. This suggested ratio isfrom the previous study [2]. Copper (Cu), nickel (Ni),and zinc (Zn) were selected to represent the range ofthe common heavy metals and prepared in the formof the solution to be the adsorbates. The stock
solutions of Cu (NO3)2, Ni (NO3)2, and Zn (NO3)2
were dissolved in the deionized water to obtain thepreferred initial concentration of solution. The chosen
initial concentration of the heavy metal solutions
were 250, 500, 750 and 1000 mg/L. The properties ofheavy metal solutions are presented in Table 4.

INTRODUCTION
The Northeastern part of Thailand covers an areaof 170,000 km2. Approximately one-third ofThailand’s populations live in this region. The
general physiography is mainly undulated by highplateau. The top most soil layer found in these areas
is loess layer or wind-deposited soil (Fig.1). Loesscan be defined as a terrestrial clastic sediment, which
composed predominantly of silt-size particles
essentially formed by the accumulation of windblown dust [1]. This research aims as one method toinvestigate and study the effect of industrial
companies to the environmental issue of neighboring
community. Ground contamination due to a variety of
inorganic compounds can surely be occurred as aresult of leaks of hazardous chemicals. The sorption
value of contaminations such as heavy metals on
loess soil is investigated and a possible method of
improving the sorption capacity of contaminated flow
into this red loess is also proposed in this study byadding variety of Pozzolanic materials.
MATERIALS USEDRed loess (R) in the Northeastern part ofThailand were designated as the adsorbent of thisstudy. The samples were collected and dug at thedepth of 50 cm from its surfaces and were dried in theoven at 110 0C for 24 hours for bulk water elimination
purpose. The basic and engineering properties of theadsorbent are shown in Table 1. From the results ofthe sieve analysis, and Atterberg limits test, the soil
sample can be classified as silty sand (SM) by using

Table 1 Properties of Red Loess
Properties% Passing # 200 sieve% Passing # 4 sieve
Liquid Limit, LL (%)
Plasticity Index, PI (%)
Permeability, k (cm/s)

419

Red Loess
11.71
96.45
18.03
5.03
4.0 x 10-6

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 4 Properties of Heavy Metal Solutions

Table 2 Chemical analysis by XRF
Chemicalanalysis (%)
Red Loess
CementFly ashBottom ash
Blast furnace
Rice husk ash
Silica fume
Metakaolin

SiO2

Al2O3

Fe2O3

CaO

MgO

64.5
20
35
48
40
92
79.5
55

14
5
26
20
11
0.7
0.5
40

2.7
3
10
11
0.3
1
-

0.2
60
15
13
32
0.5
0.5
-

1.1
2
2
7
0.2
0.5
-

Properties
FormulaMolecular
weight(g/mol)Density(g/cm3)
Solubility(g/100ml)

CopperNitrateCu(NO3)2

Zinc
NitrateNi(NO3)2

NickelNitrateZn(NO3)2

241.60290.80297.50

2.32

2.05

2.06

137.8094.20

184.30(a) Portland cement

Fig. 1 Areas of loess deposits (stippled area) in Thailand(after Phien-wej et al. 1992).

(b) Fly ash

Table 3 Specific surface area of materials
SampleRed Loess
CementFly ashBottom ash
Blast furnace
Rice husk ash
Silica fume
Metakaolin

Specific surface area
(m2/g)
7.68
0.21
0.15
3.88
2.32
43.94
20.32
14.47

(b) Bottom ash
Fig. 2 The Pozzolanic materials

420

SEE - Nagoya, Japan, Nov.12-14, 2018

EXPERIMENTAL WORK
A series of batch sorption test was performed to
examine the adsorption behavior of Cu, Zn and Ni.
Adsorption is the process in which atoms or
molecules of a substance in one phase becomebonded to the surface of a second substance in adifferent phase [3]. The procedures of the batch test
can be done by mixing 2.5 g of soil sample with 50
cm3 of the heavy metal solution in the bottle. Thenshaking the mixture with a velocity of 130 cycles per
minute by the horizontal shaker until the desired timeis reached. Next, the soils were separated from theheavy metal solution by using a 0.45 µm filter. After
that, the solutions were diluted by mixing them with
1% Nitric Acid (HNO3) before taking to measure theconcentrations by the Atomic Adsorption
Spectrometer (AAS). The effect of the initialconcentration of heavy metal solution can be studied
by running the batch test with 250 to 1000 mg/L of
the heavy metal solutions. The concentrations ofsolutions at equilibrium were determined. Then,calculating the adsorption percentage at each initialconcentration by using Eq. 1.

(d) Blast furnace%adsorption =(C 0 − C eq )
C in

× 100

(1)

Where: C0 and Ceq are the initial and equilibrium
concentrations of heavy metal solution (mg/L),
respectively. There are many mathematical models
used to represent the adsorption isotherm, although
the two most commonly used models are theLangmuir and Freundlich isotherms. The Langmuiradsorption isotherm has been widely applied to many
adsorption processes, specifically those assuming
monolayer adsorption on the adsorption surface. The
Langmuir isotherm is defined as:(e) Rice husk ashq=αβ Ceq1 + αCeq(2)

Where: q is the amount of adsorption of heavy metals
per unit weight within soil (mg/g), α is theLangmuir constant, related to the bonding energy
between the adsorbed ion and the adsorbent (L/mg)(f) Silica fumeand β is the maximum adsorption capacity (mg/g).
The Freundlich isotherm is the most common
isotherm model, used to describe physical adsorption
in a solid-liquids system, and is defined as follows:(3)
qe = K (Ceq )1 / n

Where: qe is the amount of adsorbed heavy metal perunit weight of soil at equilibrium (mg/g), K is
Freundlich constant (mg/g) and 1/n is the adsorption
intensity (dimensionless) [4].
RESULT AND DISCUSSION(g) Metakaolin
By using the concentration of 250, 500, 750 and1000 mg/L, the adsorption percentage at eachFig. 2 The Pozzolanic materials
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SEE - Nagoya, Japan, Nov.12-14, 2018

From Langmuir model, the β-parameters summarizedin Table 5 is the maximum adsorption capacity of thesamples. It can be seen that loess mixed with cement(R+Ce) show the highest adsorption capacity, while
loess mixed with metakaolin (R+Mk) provided thelowest capacity. It was also found in Table 5 that thepotential of Pozzolanic materials were ranged from
Portland cement, fly ash, bottom ash, blast furnaceslag, rice husk ash, silica fume and metakaolin,
respectively. The adsorption capacity of Cu was
higher than the capacity of Ni and Zn for all samples.
Figure 9 shows the comparison of the maximum
adsorption capacity (β-parameter) of the loess mixed
with seven Pozzolanic materials.

concentration can be shown in Figs. 1 to 3. It can beseen that the adsorption percentage decreased with
the increasing initial concentration. This can be
explained by a reason of saturation on the soil surface
where the adsorption took place [5].
100
R+Ce
R+Fa
R+Ba
R+Bs
R+Ra
R+Mk
R+Sf

80

% Adsorption

60
40

100

R+Ce
R+Fa
R+Ba
R+Bs
R+Ra
R+Sf
R+Mk
R

20
% Adsorption

80

0
200

400
600
800 1000
Initial Concentration (mg/l)

1200

Fig. 1 Effect of initial concentration on Cu

40

20

100
R+Ce
R+Fa
R+Ba
R+Bs
R+Ra
R+Mk
R+Sf
R

80
% Adsorption

60

60
40

0
200

400

800

1000

1200

Initial Concentration (mg/l)
Fig.3 Effect of initial concentration on Zn

10

20

R+Ce
R+Ba
R+Ra
R+Mk

8

0
400 600 800 1000 1200
Initial Concentration (mg/l)

R+Fa
R+Bs
R+Sf
R

6
q (mg/g)200

600

Fig.2 Effect of initial concentration on Ni
The adsorption isotherm obtained from the tests
are shown in Figs. 4 to 6. It can be seen that theamount adsorbed increased with the equilibrium
concentration. This was due to the driving force of themetals toward active sites increased when theconcentration increased. Figures 7 and 8 show
examples of how to convert and calculate the datafrom Fig. 4 to 6 into the parameters for Langmuir andFreundlich adsorption isotherms in the case of Cu for
red loess mixed with cement. The adsorption
isotherm parameters of Langmuir and Freundlichmodels were summarized in Tables 5 and 6,
respectively. High values of R2 reveal that theadsorption isotherm was well fitted to both models.

4
2
0
0

200

400
600
800
Ceq (mg/L)
Fig. 4 Adsorption isotherm of Cu

1000

Table 7summarizes
thecalculated
percentage of adsorption improvement when adding
the Pozzolanic materials to the loess. It can be seenthat all the materials especially cement and fly ash can

422

SEE - Nagoya, Japan, Nov.12-14, 2018

dramatically improve the adsorption capacity of Cu,
Ni and Zn. The adsorption capacity can improve up
to 350% compared to pure loess by adding only 5%of cement to the loess.
log q (mg/g)

0.9

10
R+Ce
R+Ba
R+Ra

8

R+Fa
R+Bs
R+Sf

q (mg/g)6

y = 0.1546x + 0.4025
R² = 0.935

0.8

0.7

R+Ce
Cu

0.6
0

1
2
3
log Ceq (mg/L)
Fig.8 Freundlich adsorption isotherm of Cu
for R+Ce

4
2

Table 5 Parameters of Langmuir adsorption isotherm
0
0

200

400
600
Ceq (mg/L)

800

Sample1000

R+Ce

Fig. 5 Adsorption isotherm of Ni
10

R+Fa

R+Ce
R+Ba
R+Ra

q (mg/g)

8

R+Fa
R+Bs
R+Sf

R+Ba

6

R+Bs

4
R+Ra

2
R+Sf

0
0

200

400
600
800
Ceq (mg/L)
Fig. 6 Adsorption isotherm of Zn

1000

R+Mk

R

120

Ceq/q (g/L)

R+Ce
Cu

Table 6 Parameters
isotherm

80

Sample40

y = 0.1466x + 3.2523
R² = 1

R+Ce

0

R+Fa

0

Heavy
metals
Cu
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn

250
500
Ceq (mg/L)

750
R+Ba

Fig.7 Langmuir adsorption isotherm of Cu for R+Ce

R+Bs

423

Heavy
metals
Cu
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn
Cu

β
(mg/g)
6.82135.22474.39565.76706.02413.60104.70154.78013.7411
3.87903.81682.67243.04973.74391.67222.41252.34741.47472.02881.44991.18891.65081.16840.9823ofα(L/mg)
0.04510.01340.00760.02310.00470.00910.01420.00410.00410.01450.00540.00760.01050.00290.01020.01750.00410.00930.01420.00930.01250.01020.00410.0021

Freundlichk(mg/g)
2.52641.09570.51591.59150.33930.52571.08320.21580.18170.8738R2
1.00000.99950.99750.99950.9846
0.99820.99990.99620.99050.9986
0.99850.9881
0.9987
0.94681.00000.99960.98010.99960.9996
0.99660.99940.98450.96250.9747

adsorption

1/n

R2

0.15460.22600.30320.19350.40180.27380.21220.43020.41740.21620.93500.97970.96630.90280.95910.91990.97020.96250.93040.8892

SEE - Nagoya, Japan, Nov.12-14, 2018

Sample

R+Ra

R+Sf

R+Mk

R

Heavy
metals
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn
Cu
Ni
Zn

k
(mg/g)
0.28970.29900.60940.08190.39110.93480.18250.2996
0.68660.35430.38520.58470.24310.29551/n

R2

0.35950.31050.2272
0.52480.20100.1322
0.34170.22090.15000.19170.15440.17450.265400.13420.95920.82910.93460.87790.97090.99190.9641
0.94830.9936
0.98220.98680.91250.89740.9254

CONCLUSIONSThis research studied the behaviors of adsorptionof loess on seven kinds of Pozzolanic materials i.e.,
fly ash, bottom ash, rice husk ash, blast furnace slag,
silica fume, metakaolin, and Portland cement. The
adsorption capability and the adsorption isotherm
were investigated by the batch method. The
concentrations of the solution used in the batch test
were 250, 500, 750 and 1000 mg/L. The adsorption
capability decreased when the initial concentration
increased. The Langmuir and Freundlich isotherm
models were able to efficiently explain the adsorption
behavior of the loess mixed with all seven Pozzolanicmaterials. Mixing red loess with cement or fly ash
resulted in a more effective performance relative tousing pure loess. Adsorption capacities were ranked
as follows: Portland cement > fly ash> bottom ash>blast furnace slag> rice husk ash> silica fume>metakaolin.

8.0
7.0

Cu

Ni

Zn

6.0

ACKNOWLEDGEMENTS

β (mg/g)

5.0
4.0This research was support by Department of Civil
Engineering, Faculty of Engineering, Khon Kean
University.

3.0

REFERENCES[1] Phien-wej
N.,Pientong
T.,andBalasubramaniam, A.S., Collapse and strengthcharacteristics of loess in Thailand. Engineering
Geology, Vol.32, 1992, pp.59-72.
[2] Tongew N. and Punrattanasin P., Influence ofalternative materials in the adsorption of heavy
metals on loesses. in Proc. of the 21th National
Conference on Civil Engineering, 2016, pp. 11981203.
[3] Dube A., Zbytniewski R., Kowalkowski T.,
Cukrowska E., and Buszewski B., Adsorption
and migration of heavy metals in soil. Pol. J.
Environ. Stud. Vol.101, 2001, pp.1-10.
[4] Mohammad Kashif Uddin., A review on theadsorption of heavy metals by clay minerals, withspecial focus on the past decade, Chemical
Engineering Journal., Vol 308, 2017, pp 438-462.

2.0
1.0
0.0

Fig. 9 Maximum adsorption capacity of samples

Table 7 The percentage of adsorption improvement
when adding the materials to the loessSample
R+Ce
R+Fa
R+Ba
R+Bs
R+Ra
R+Sf
R+Mk

Percentage of Improvement
Cu
Ni
Zn
313.41350.41 348.53
249.52419.32 267.45
184.94312.08 281.74
135.09229.03 172.69
84.83
222.7570.63
46.21
102.36
50.48
22.96
24.99
20.60

[5] S. Veli, B. Alyuz, Adsorption of copper and zincfrom aqueous solutions by using natural clay, J.
Hazard. Mater. 149 (2007) 226-233.

424

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EXPERIMENTAL STUDY AND MODELLING OF STRESS-STRAIN
RELATIONSHIP OF RC COLUMNS STRENGTHENED BY BAMBOOREINFORCED CONCRETE JACKETS
Ari Wibowo1, Indradi Wijatmiko1 and Christin Remayanti Nainggolan1
Faculty of Engineering, Brawijaya University, Malang, Indonesia, 65145

1

ABSTRACT
Bamboo bars as replacement of steel reinforcement for structural concrete columns have gained increasing
interest due to the consideration of sustainability and green construction issues. Its application on concrete
jacketing method is being studied in this paper. In order to comprehensively understand the strength capacity andbehavior of such columns, the stress-strain relationship needs to be investigated. However, most available stressstrain model were developed for steel reinforced concrete columns as found in many papers and codes; but not forbamboo reinforced concrete columns. Therefore, experimental tests on axial load-deformation and the related
stress-strain curve of damaged concrete columns retrofitted with bamboo concrete jacket has been undertaken. The
parameters investigated in the test were longitudinal and transverse reinforcement ratios, spacing of the stirrups,
and the longitudinal bar configuration. The stress-strain model bamboo was then developed and in a reasonableagreement with the experimental data.
Keywords: Stress-strain formula, Bamboo reinforcement, Concrete column, Axial load test

INTRODUCTION
EXPERIMENTAL TEST SET-UP
Concrete jacketing techniques are well known forimproving the performance of structural elements. In
this research study, the focus was aimed on the
rehabilitation of damaged elements instead ofstrengthening weak structures. Weak elements arenormally caused by improper design or poor
construction method, whereas damaged elements are
resulted from the excessive load beyond the limit
strength capacity due to natural phenomenon such as
earthquake, soil settlement, flood, etc. Maindifference is the condition of the elements when the
retroffiting is applied i.e. under serviceability limit for
weak elements or experiencing failure stage close to
the collapse limit; which lead to different
approximation on strength analysis.
Concretejacketingmethodhas
beencomprehensively investigated [1-6] covering various
mechanism (axial, flexural, and shear behaviour) andvarious elements (beams and columns). However,those research projects mainly focused on the use ofregular reinforced concrete which depends largely on
the steel application. As the green material andsustainability issues are more prominent, it isnecessary to obtain alternative material to replacesteel. The common material to be used asreinforcement is bamboo which also has been studied
thoroughly [7-16]. Interestingly, very few of thosestudies studied about its application on retrofitting.
And therefore, this study aimed on the application ofbamboo as steel replacement on concrete jacket
method in retrofitting damaged concrete columns.

Three parameters varies were longitudinal
reinforcement ratio, configuration of main bars, andstirrups spacing which were aimed at investigating
the effectiveness of confinement of concrete jacket tothe damaged columns.
Four groups of specimen in the form of shortcolumns were axially loaded in two stages (originaland retrofitted columns). The dimension of originalcolumns were 12x12x30 cm, and were reinforced
with four φ6 mm steel bars (longitudinal
reinforcement ratio of 1.23%) as shown in Fig. 1.
A transverse reinforcement ratio of 0.81% wasused using φ6 stirrups spaced at 140mm. The
specified concrete compressive strength was 20 MPa,
whilst the yield strength for main rebars and stirrups
were 270 MPa and 170 MPa respectively.
The rehabilitation of damaged column after the
first axial load test were conducted using concrete
jacketing reinforced with bamboo bars as longitudinal
and transverse reinforcement (refer Table 1 and Fig.
2) as follows:• Two longitudinal reinforcement ratios used were1.23% and 2.47%, where each ratio wasrepresented by 4 and 8 square/rectangle bars
configuration, i.e., 4 bars 10x10 mm and 8 bars
10x5 mm (for the same ρv = 1.23%), and 4 bars
20x10 mm and 8 bars 10x10mm (for the sameρv = 2.47%). Petung bamboo (Dendrocalamus
asper) applied for longitudinal reinforcement
had yield strength of 190 MPa.
425

SEE - Nagoya, Japan, Nov.12-14, 2018•

For the transverse reinforcement, square bar
10x5 mm bamboo stirrups were set at about
7.5cm, 10 cm and 15 cm spacing corresponding
to transverse reinforcement ratios of 0.8%, 1.2%
and 1.6% respectively. Apus Bamboo(Gigantochloa apus) with yield strength of 120
MPa was used for stirrups fabrication since it wasless stiffer compared to the Petung Bamboo andhence relatively easier to be bent.

Table 1 Column set-up configuration
Columns

Original
A1R
A2R
A5R
B1R
B2R
B5R
C1R
C2R
C5R
D1R
D2R
D5R

Longitudinal
Reinforcement
Dimension
Ratio
(%)
1.40
4φ8
4 bamboobars
10x10 mm
8 bamboobars
10x5 mm
4 bamboobars
20x10 mm
8 bamboobars
10x10 mm

1.23

1.23

2.47

2.47

a. Set-up for columns with four bamboo main bars

Transverse
Reinforcement
Spacing
Ratio
(%)
0.81
φ6 - 140
10×5 – 100

1.21

10×5 – 150

0.81

10×5 – 75

1.61

10×5 – 100

1.21

10×5 – 150

0.81

10×5 – 75

1.61

10×5 – 100

1.21

10×5 – 150

0.81

10×5 – 75

1.61

10×5 – 100

1.21

10×5 – 150

0.81

10×5 – 75

1.61

b. Set-up for columns with eight bamboo main bars
Fig. 2

EXPERIMENTAL TEST RESULTS
The recorded axial loads and deformations for allcolumns are shown in Fig. 3-4 and Table 2 whichshowed interesting outcomes as follows:a. The average peak axial strength anddisplacement ductility ratio of original column
specimens were about 212 kN and 3.29
respectively.
b. Generally there were improvement of ductility
on all configuration of retrofitting compared tothe damaged columns as shown in Fig. 2. The
results also showed that the closer the stirrups
spacing, the higher the ductility ratio ofretrofitted columns.
c. At the same longitudinal reinforcement ratio, theuse of 8 smaller bar configuration exhibited
ductility ratio of about 30% higher than those ofcolumns with 4 larger bars. And hence it ispreferable to distribute the bars uniformly overthe column perimeter to obtain higher
confinement effectivity.
d. The increase rate of ductility when reducing thestirrups spacing from 150mm, 100mm to 75mm
was found higher on configuration of 4 main bars
longitudinal reinforcement rather than 8 bars
configurations. It is understandable since theapplication of 8 bars configuration has provided
greater ductility ratio at similar stirrups spacing.
e. The use of stirrups with spacing closer than thatof original columns seemed to increase the peak

Axial compression tests were conducted on
original columns until reaching 50% reduction ofpeak load. Then, the damaged columns wereretrofitted and further subjected to the second axial
load test until reaching failure. The axial load anddeformation were continuously measured using
compression testing machine and dial gauge as shownin Fig. 2.

Fig. 1

Typical retrofitting of damaged columns

Typical original columns

426

SEE - Nagoya, Japan, Nov.12-14, 2018300

load capacity of retrofitted columns; and viceversa for the wider stirrups spacing.
Axial Force (kN)350
Original Column

Axial Force (kN)

300

Column A1R
Column B1R

250

Column C1R

100

Original Column
A2R (Stirrups Spacing 15cm)
A1R (Stirrups Spacing 10cm)
A5R (Stirrups Spacing 7.5cm)

150

0

100

0

0

2

4

6

8

10

12

14

16

Deformation (mm)a. Columns with ρh=1.23% (4 main bars 10x10 mm)
0

2

4

6

8

10

12

14

300

16

Deformation (mm)Axial Force (kN)300
Original Column
Column A2R

250

Column B2R
Column C2R

200

Column B series
Original Column

250

a. Columns with stirrups spacing of 100mm

Axial Force (kN)

150

50

50

B2R (Stirrups Spacing 15cm)
B1R (Stirrups Spacing 10cm)

200

B5R (Stirrups Spacing 7.5cm)

150
100

Column D2R

50

150

0
100

0

0

2

4

6

8

10

12

14

4

6

8

10

12

300

16

14

16

Column C series

250

Axial Force (kN)b. Columns with stirrups spacing of 150mm
350
300
250

200
150
100

Original Column
C2R (Stirrups Spacing 15cm)

50

200
150

0

Original Column
Column A5R

100

Column D5R
2

4

6

8

10

12

14

C5R (Stirrups Spacing 7.5cm)
0

2

4

6

8

c. Columns with ρh=2.47% (4 main bars 20x10 mm)

Column C5R

0

C1R (Stirrups Spacing 10cm)

Deformation (mm)Column B5R

50

350

Column D series

16

300

Axial Force (kN)

Deformation (mm)c. Columns with stirrups spacing of 75mm
Fig. 32

b. Columns with ρh=1.23% (8 main bars 10x5 mm)
Deformation (mm)00Deformation (mm)50

Axial Force (kN)

200

Column D1R

200

Column A series

250

Comparison of longitudinal reinforcement
ratio effect

250
200
150

Original Column
D2R (Stirrups Spacing 15cm)

100

D1R (Stirrups spacing 10cm)

50
0

D5R (Stirrups Spacing 7.5cm)
0

2

4

6

8

10

12

14

16

Deformation (mm)d. Columns with ρh=2.47% (8 main bars 10x10 mm)
Fig. 4427

Comparison of the confinement effect due tovarious stirrups spacing.

SEE - Nagoya, Japan, Nov.12-14, 2018•

Table 2 Column set-up configuration
Col.

Ppeak
(kN)

P50
(kN)

∆y
(mm)

∆peak
(mm)

∆50
(mm)

µ

Original

229

104

1.60

2.40

5.25

3.28

A1R

231

118

2.00

2.81

10.88

5.44

A2R

204

100

2.00

4.20

7.24

3.62

A5R

278

173

1.60

1.30

14.40

9.00

B1R

243

106

2.20

4.40

14.90

6.77

B2R

163

76

1.80

3.60

10.60

5.89

B5R

257

156

1.80

4.40

14.20

7.89

C1R

253

133

1.60

3.00

7.00

4.38

C2R

216

120

1.50

2.20

4.80

3.20

C5R

280

140

1.00

2.30

7.30

7.30

D1R

305

151

1.70

2.00

7.00

4.12

D2R

250

124

1.60

2.60

6.90

4.31

D5R

288

190

1.70

3.80

14.20

8.35

Region BC (εc > 0.004K)
𝑓𝑓𝑐𝑐 = 𝐾𝐾𝑓𝑓𝑐𝑐′ [1 − 𝑍𝑍(𝜀𝜀𝑐𝑐 − 0.004𝐾𝐾)]
but not lesss than 0.2Kfc’where:
𝐾𝐾 = 1 + 𝜌𝜌ℎ

𝑍𝑍 =

𝑓𝑓𝑦𝑦ℎ
𝑓𝑓𝑐𝑐′

0.5

3+𝑓𝑓′𝑐𝑐3ℎ+ 𝜌𝜌 � 𝑠𝑠 −0.004𝐾𝐾
250𝑓𝑓′𝑐𝑐 −1000 4 ℎ 𝑠𝑠ℎfc’ = concrete strengthfyh = bamboo rupture strengthρh = volumetric transverse reinforcement ratio
sh = spacing of stirrups
bs = width of concrete core measured to outsideof stirrups.

The comparison of typical concrete stress-strain
curve of unconfined, steel confinement and bamboo
reinforced concrete jacket for concrete strength fc’ of
15 MPa and similar reinforcement configuration ispresented in Fig. 6. The application of the proposedmodel to the axial load-deformation prediction of thetested columns are shown in Fig. 7-9. The predicted
axial load-deformations took a more conservative
approach compared to the experimental results which
is suitable for preliminary design or nominal capacity
checking purposes.

STRESS-STRAIN MODEL
The simple stress-strain formula for damaged
concrete confined with bamboo reinforced concrete
jacket was developed based on Modified Kent-Parkmodel [17]. Since the bamboo stirrups had lower
yield strength and modulus of elasticity, theeffectiveness of confinement will be lower than thatprovided by steel stirrups; and hence, it was
reasonably assumed that the peak strength occurs at
0.004 concrete strain instead of 0.002 as the case ofsteel confinement. The model for predicting thestress-strain curve can be elaborated as follows (refer
Fig. 5):

Concrete Strength (MPa)1816

Unconfined

14

Confined

12

Retrofitted

10
8
6
4
2
0
0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

Concrete Strain

B
Concrete Stress, fc

Kfc’

𝒁𝒁 =

θ

Fig. 6

𝐭𝐭𝐭𝐭𝐭𝐭 𝜽𝜽
𝑲𝑲𝒇𝒇𝒄𝒄 ′Stress-strain curve comparison for 3 cases(unconfined, confined with steel, andconfined with bamboo).

300

C

Original Column
Column A1R
Column B1RTheoretical Model

A

Axial Force (kN)

250
200

0.004K

150

Concrete Strain, εc

100Fig. 5 Stress-strain model for bamboo reinforced
confinement on concrete jacket.
•

500Region AB (εc < 0.004K)
𝑓𝑓𝑐𝑐 = 𝐾𝐾𝑓𝑓𝑐𝑐′ �2𝜀𝜀𝑐𝑐0.004𝐾𝐾+�𝜀𝜀𝑐𝑐

0.004𝐾𝐾

0

2

4

6

8

10

12

14

16

Deformation (mm)2

� �

Fig. 7428

Comparison of the proposed model and theexperimental results

SEE - Nagoya, Japan, Nov.12-14, 2018

ACKNOWLEDGEMENTS
250

We acknowledge the support of Higher Education
Excellent Research Grant from Ministry of Research,
Technology and Higher Education of the Republic ofIndonesia.

Original Column
Column A2R
Column B2R
Theoretical Model

Axial Force (kN)

200
150
100

REFERENCES

50
0

0

2

4

6

8

10

12

14

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16

Deformation (mm)Fig. 8Comparison of the proposed model and theexperimental results

300

Axial Force (kN)

250
200
150
Original Column
Column A5R
Column B5R
Theoretical Model

100
50
0

0

2

4

6

8

10

12

14

16

Deformation (mm)Fig. 9Comparison of the proposed model and theexperimental results

CONCLUSION
Experimental test on four groups of short columns
retrofitted by bamboo reinforced concrete jacket has
been undertaken, with interesting outcomes asfollows:
a. Retrofitting using bamboo reinforced concrete
jacket were generally able to improve theductility ratio of damaged columns.
b. However, for reaching the similar nominal
strength of original columns, the stirrups spacingneeds to be set closer than that of damaged
columns.
c. It is It is preferable to distribute the bars
uniformly over the column perimeter to obtainhigher effectiveness of confinement.
Further, the simple model for predicting stressstrain of damaged columns retrofitted using bamboo
reinforced concrete jacket has been developed. The
analytical predictions showed a reasonable agreementwith the experimental test results with a moreconservative approach which is suitable for simple
checking or preliminary design purposes.

429

SEE - Nagoya, Japan, Nov.12-14, 2018[11] Bhavna Sharma, Ana Gatóo, Michael H.
Ramage, Effect of processing methods on themechanical properties of engineered bamboo,
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reinforcement in concrete, Construction and
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[13] Masakazu Terai, Koichi Minami, Fracture
Behavior and Mechanical Properties of Bamboo
Reinforced Concrete Members, Procedia
Engineering, Vol. 10, 2011, pp. 2967–2972.
[14] Abhijeet Dey, Nayanmoni Chetia, Experimental
study of Bamboo Reinforced Concrete beams
having various frictional properties, Materials
Today: Proceedings, Vol. 5, 2018, pp. 436–444.

[15] Ari Wibowo, Indradi Wijatmiko, Christin
Remayanti Nainggolan, Bamboo reinforced
concrete slab with styrofoam lamina filler assolution of lightweight concrete application,
MATEC Web of Conferences, Vol. 101, 2017,
Article number 05012.
[16] Ari Wibowo, Indradi Wijatmiko, Christin
Remayanti Nainggolan, Structural behavior oflightweight bamboo reinforced concrete slab
with EPS infill panel,
AIP Conference
Proceedings, Vol. 1887, 2017, Article
number 020024.
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430

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

STUDY OF MODULUS ELASTICITY OF PVC COATED WELDEDMESH FIBER CONCRETE
Christin Remayanti Nainggolan1, Indradi Wijatmiko1 and Ari Wibowo1
Faculty of Engineering, Brawijaya University, Malang, Indonesia, 65145

1

ABSTRACT
Modulus elasticity is an important parameter that show the ability of concrete to deform elastically. Data
analysis to obtain that value of modulus elasticity can be done with several empirical models. To compare someof these empirical models and to study the effect of fiber to the modulus elasticity of concrete, an experiment on
the addition of PVC coated welded wire mesh fiber to the concrete mixture has been conducted. The specimen inthis experiment was a cylindrical specimen with a diameter 150 mm and height 300 mm. There are 3 variations inthis experiment : (1) variations in fraction of percentage of wire fiber; (2) fiber’s length variation and (3) lengthinterlocking variation. Extensometer was installed onto the speciment to measure stress strain of concrete while
the compressive strength were conducted. The result of analysis showed that 1.5% of fiber fraction, 24mm of fiber
length and 0.6 mm of fiber interlocking length generated higher modulus elasticity compare to other variations.
However, PVC coated welded mesh fiber concrete has a less value of modulus elasticity when it compared withnormal concrete due to slip effect between fiber and concrete. Furthermore, there are some empirical models witha good agreement and some in different results depends on the country code and the parameters in the models.
Keywords: Fiber concrete, Modulus elasticity, Sress-strain, PVC coated welded wire meshshrinkage of the concrete. Ankur C. B. and Narendra
K. A. [5], used metalized plastic waste fibers wereshredded into 5 mm, 10 mm and 20 mm long fibers.
The fraction variation is from 0% to 2% of mix designvolume. The results of his research is that metalized
plastic waste fibers did not significantly affect thecompressive strength and flexural strength but it
increased tensile strength and ductility. From thesestudies, the results obtained that the addition of fiber
can increased tensile strength where the magnitude of
the increase is inflenced by the type of the fibers.
Swammy and Al-Noori (in Haryanto Y. W. andRecky S. G., pp.3 [6]) state that the shape of fibers
affects the bonding and the properties of the concrete.
Concrete using fibers with interlocking will increase
it bonding and structural properties rather than thefibers without interlocking.
The addition of fibers can increase tensile
strength wherein concrete generally has a low tensile
strength and has a brittle nature. Determining thetensile strength is important to determine the crackload where the crack is a form of tensile failure. To
have a better understanding about fibers concrete andit influence to tensile strength, it is necessary to know
the modulus elasticity of fibers concrete.
Modulus elasticity is one of the strengthparameter of a material, in which is to measure theresistance of an elastic deformation when the material
under the load. It can be said that modulus elasticity
is a measure of the stiffness of a material so that it canaffect the strength of a material. There are several
approaches used to obtain modulus elasticity of

INTRODUCTION
Fibers concrete is concrete made of cements,
aggregates, water and discerete fibers (steel fibers,
glass fibers, synthetic fibers, etc.). According to ACI
Comitte 544.1R-96 [1], the length and diameter of thefibers used for fibers concrete should not exceed 76
mm and 1 mm respectively. The addition of fiber tothe concrete has a purpose to fix the weakness of theconcrete that hasa low tensile strength.
There are a variety of fibers used for fibers
concrete. Iwan R. [2] used fibers made from wastecans with variation fraction and water cement ratio
0.45. The width, length and thickness of the fibers are
3 mm, 50 mm and 0.2 mm respectively. The result of
the research is that the addition of fiber with fraction
0.6% increased the compressive strength of 30.65%
and the tensile strength of 49.69%. Another researchdone by Kampa R. [3] use coca-cola can waste asfiber, the width and length of the waste tin fibers are
2 mm and 20 mm respectively.The fibers manually
twisted by 1800 to improve bondage between cement,
aggregates and fibers. The addition of waste tin fibers
shown insignificant change in compression andtensile strength. Waste carpet fibers with the length of
the fibers is 20 mm and the variaton of fraction are
between 0 – 1.25% were used by Hossein M,
Jamaludin M. Y., Abdul R. M. S. And A. S. M. Abdul
Awal [4] as a fibers concrete. In addition to used
waste carpet fibers, Hossein also added palms oil fuelash (POFA). The interaction between carpet fibers
and POFA subsequently led to the lower drying
431

SEE - Nagoya, Japan, Nov.12-14, 2018concrete. Emi M. [7] calculated modulus elasticity ofconcrete used the equation of Wang and Salmon.
Wang and Salmon predict the modulus elasticity
based on stress-strain of concrete. H. Z. Cui, TommyY. L., Shazim A. M., F. Xing and X. Shi [8] used
empirical model from ACI and institute of structuralto predicted the modulus elasticity of lightweight
concrete, which is influenced by compressive
strength and weight of concrete. Turhan B. [9] used
several empirical models such as Euro Code 2,
TS500, Norwegian Code, etc. , and used composite
material models such as Voigt model, Reuss model,
Popovics Model, etc. to predicted modulus elasticity
of high quality concrete.
Based on previous studies, this research used PVC
coated welded wire mesh fibers and investigated it
influence to modulus elasticity of fiber concrete. This
research also studied and compared the modulus
elasticity from several empirical models.

To prepare the materials, it is necessary to know
the density of wire mesh. After 3 experiments, thedensity of PVC coated welded wire mesh as shown at
Table 1.
Table 1. PVC coated welded wire mesh density
Density (gr/cm³)
0.373
0.351
0.388
0.371

Experiment A
Experiment B
Experiment C
Average

After knowing the density, then calculate the needfor each fraction. For example the calculation for one
cylinder with fraction 1%.
𝑊𝑊𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 𝑚𝑚𝑚𝑚𝑚𝑚ℎ= %𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑥𝑥 𝑉𝑉𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐 𝑥𝑥 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑤𝑤𝑤𝑤𝑤𝑤𝑤𝑤 𝑚𝑚𝑚𝑚𝑚𝑚ℎ= 1% x 5298.75 cm3 x 0.371 gr/cm³= 19.658 gr

EXPERIMENTAL INVESTIGATIONPVC coated wire is a modified type of wire bend.
It is also known as PVC coated welded wire mesh, isa high quality stainless steel wire with stainlessresistance much better than ordinary iron wire. Thiswire consists galvanized wire (diameter 0.8 mm)
coated by PVC (thickness 0.2 mm). The advantagesof this wire are high rust resistance, easy to get, greatsavings in time, effort and money.
The specimen in this research is a cylinder with adiameter 150 mm and height 300 mm with 3
variations :(1) Variation of fraction (0.5 %, 1 %, 1.5% of cylinder
volume) with fiber length 36 mm and interlocking
length 12 mm (Fig. 3.b)(2) Variation of fiber’s length (12 mm, 24 mm, 36mm) with fraction 1% and interlocking length 12
mm (Fig. 4)(3) Variation of fiber’s interlocking length (6 mm, 12mm, 18 mm) with fraction 1% and fiber length 36
mm (Fig. 5)
The specimen was tested with compressive test
machine and an extensometer to measure concrete
strain. (Fig.1)

(a)

(b)

12mm

12mm

12mm

Fig. 2. (a) PVC coated welded wire mesh, (b) PVC
coated welded mesh fiber

12mm

12mm

12mm

12mm

12mm

12mm

(a)

Fiber
lengthInterlocking
length(b)
Fig. 3. (a) PVC coated welded wire mesh before
cutted , (b) PVC coated welded wire mesh after cutted
Fig. 1. Test model with compressive test machine
432

SEE - Nagoya, Japan, Nov.12-14, 2018

MODELING APPROACH
Modulus elasticity is the ratio of the stress andstrain of the material as seen in the Eq.1.
PxL
σ
E= =
...................................................(1)ε A x ∆L
According to Wang and Salmon [11], modulus
elasticity depends on the age of the concrete,materials properties, the loading rate, the type andsize of the specimen. The empirical model used in thisresearch can be seen at Table 3. According to theoryof elasticity, the slope of the curve in the early stageillustrates the modulus elasticity of concrete (Fig.6).

18 mm

12 mm

36 mm

36 mm

36 mm

Fig. 4. Variation of fiber’s length

6 mmFig. 5. Variation of fiber’s interlocking length

Fig. 6. Stress-strain curve [12]Mix design in this research refers to SNI 03-28342000 [10]. From the calculation obtained ratio of
actual proportion (in kg).

Elastic proportional limits (ASTM C 469 andEurocode 2 - 1992) in predicting modulus areimportant because the nature of the concrete is aelasto plastic, where as a result of a fixed loading, thematerial exhibits the elastic ability of the material andalso exhibits permanent deformation. The modulus
elasticity based on the material resistance to thecompressive strength test (deformation) is called
modulus elasticity static. In addition there is also
empirical model of elastic modulus containing
concrete compressive strength factor (SNI 03-28472002 and TS 500).

Table 2. Ratio of mix design
Cement

Water

1.00

0.5

Fine
aggregate
1.18

Coarseaggregate
2.02

Table 3. Summary of empirical model to estimate the modulus elasticity
Empirical model

0.4 f ' c........(2)ε (0.4 f ' c)σ − σ1
E= 2...........(3)ε 2 − ε1E=

E = 0.043 x Wc1.5 x f c 0.5 ........(4)(1500 ≤ Wc ≤ 2500 kg/m3)

E = 4700 fc 0.5 ..............(5)(Wc ± 2300 kg/m3)(

E = 3250 x)

f ' c + 14000.........(6)Parameters
E is the modulus elasticity static (MPa), f’c iscompressive strength (MPa), ε is axial strain

Ref. source
Eurocode 2 - 1992

E is the modulus elasticity static (MPa), σ1 istegangan saat regangan 0.00005 , σ2 is tegangansaat 40% f’c, ε1 = 0.00005 , ε2 is regangan saat σ2
E is the modulus elasticity (MPa), Wc is unit
weight (kg/m3), f’c is compressive strength (MPa)ASTM C 469

E is the modulus elasticity (MPa), Wc is unit
weight (kg/m3), f’c is compressive strength (MPa)

SNI 03-2847-2002(IndonesianStandart)
TS 500 (Turkey
Standart)

E is the modulus elasticity (MPa), f’c iscompressive strength (MPa)433

SNI 03-2847-2002(IndonesianStandart)

SEE - Nagoya, Japan, Nov.12-14, 2018

RESULT AND DISCUSSIONIn Table 4, 5 and 6 are shown the results ofmodulus elasticity calculations using the empiricalmodel
contained
in
Table
3.
It can also be seen the percentage values of thedifference for each calculation method of modulus
elasticity. Eurocode 2 - 1992 (eq.2) and ASTM C
469 (eq.3) are similar to each other and the value ofmodulus elasticity also close to each other, they havethe smallest percentage of the diffence between

empiric formulas ( 2.3% - 2.6% ), this is because
both formulas consider the value of strain stress that
occurs in the concrete. If Eurocode 2 - 1992 (eq.2)
is compared with TS 500 (eq.6) and ASTM C 469(3) compared with SNI 2002 (eq.4), where as TS 500
and SNI 2002 related to compressive strength as theparameter of elastic modulus, then the percentage
difference is quite large (average more than 50%).

Table 4. Modulus elasticity of PVC coated welded mesh fiber concrete with variation of fiber’s fraction
No.

1
2
3
4
5
6
7

Specimen
code

N.A1
N.A2
F.0.5.A1
F.0.5.A2
F.1.A1F.1.A2F.1.5.A1

f’c
(MPa)

Modulus elasticity (MPa)
3
4
5
ASTM
SNI 2002
SNI 2002
C 469(1500 ≤ Wc
(Wc ±≤ 25002300
kg/m3)
kg/m3)
32.75
38158.5
37391
28326.8
26897.6
33.03
62778
58705
28448.8
27013.5
19.40
10924.5
10757
21672.3
20702.4
17.99
41827.4
42121
20493
19933.7
30.32
16970
16970
27581
25879.5
32.4141957.642121
26843.2
26757.931.6840600.738788
27360.2
26452.6
Average % difference between empiric model2
Eurocode2 – 1992

6
TS 50032599.4
32679.5
28315.527783.931895.4
32502.832291.7

difference between empiric formulas (%)
(2)
(3)
(4)
(2)
(4)
&
&
&
&
&
(3)
(4)
(5)
(6)
(6)

2.1
6.9
1.6
0.7
0.0
0.4
4.7
2.3

32
106
50
106
38
57
42
61.6

5.3
5.3
4.7
2.8
6.6
0.3
3.4
4.1

14.6
47.9
159.2
33.6
88
22.5
20.5
55.2

15.1
14.9
30.7
35.6
15.6
21.1
18
21.6

Table 5. Modulus elasticity of PVC coated welded mesh fiber concrete with variation of fiber’s length
No.

1
2
3
4
5
6
7
8

Specimen
code

N.A1
N.A2
L.1.2.A1
L.1.2.A2
L.2.4.A1
L.2.4.A2
L.3.6.A1
L.3.6.A2

f’c
(MPa)

Modulus elasticity (MPa)
3
4
5
ASTM
SNI 2002
SNI 2002
C 469(1500 ≤ Wc
(Wc ±≤ 25002300
kg/m3)
kg/m3)
32.75
38158.537391.028326.8
26897.6
33.03
62778
58705.028448.8
27013.5
28.91
13319.713346
26452.6
25268.8
30.60
56253.858645
27545.3
25987.7
22.91
18840.1
18683
23832.822495.8
23.4267726.1
63636
24096.2
22744.4
30.32
16970
16970
27581
25879.6
32.4141957.642121
26843.2
26757.9
Average % difference between empiric model2
Eurocode2 – 1992

6
TS 50032599.4
32679.5
31473.11
31978.71
29555.62
29727.51
31895.37
32503.04

difference between empiric formulas (%)
(2)
(3)
(4)
(2)
(4)
&
&
&
&
&
(3)
(4)
(5)
(6)
(6)

2.0
6.5
0.2
4.3
0.8
6.0
0.0
0.4
2.5

24.2
51.5
98.2
53.0
27.6
62.1
62.5
36.3
51.9

5.0
5.0
4.5
5.7
5.6
5.6
6.2
0.3
4.7

14.6
47.9
136.3
43.2
56.9
56.1
88.0
22.5
58.2

15.1
14.9
19.0
16.1
24.0
23.4
15.6
21.1
18.6

Table 6. Modulus elasticity of PVC coated welded mesh fiber concrete with variation of fiber’s length interlocking
No.

1
2
3
4
5
6
7
8

Specimen
code

N.A1
N.A2
I.0.6.A1
I.0.6.A2
I.1.2.A1
I.1.2.A.2
I.1.8.A1
I.1.8.A2

f’c
(MPa)

Modulus elasticity (MPa)
3
4
5
ASTM
SNI 2002
SNI 2002
C 469(1500 ≤ Wc
(Wc ±≤ 25002300
kg/m3)
kg/m3)
32.75
38158.537391928326.8
26897.6
33.03
62778.058705928448.8
27013.5
22.80
27402.6
26428
23632.522440.2
22.00
44146.4643217
23357.322047
30.32
16970616970
27581
25879.6
32.4141957.642121
26843.2
26757.9
30.21
18537.2
17755
27366.5
25831.2
32.07
23258.1
22810
27603.4
26617.4
Average % difference between empiric model2
Eurocode2 – 1992

434

6
TS 50032599.4
32679.5
29517.2
29245.3
31895.4
32502.7831862
32405.7

difference between empiric formulas (%)
(2)
(3)
(4)
(2)
(4)
&
&
&
&
&
(3)
(4)
(5)
(6)
(6)

2.0
6.5
3.6
2.1
0.0
0.4
4.2
1.9
2.6

24.2
51.5
10.6
46
62.5
36.3
54.1
21
38.3

5.0
5.0
5.0
5.6
6.2
0.3
5.6
3.6
4.6

14.6
47.9
7.7
33.8
88.0
22.5
71.9
39.3
40.7

15.1
14.9
24.9
25.2
15.6
21.1
16.4
17.4
18.8

SEE - Nagoya, Japan, Nov.12-14, 2018

70000
66000
62000
58000
54000
50000
46000
42000
38000
34000
30000
26000
22000
18000
14000
10000

Modulus Elasticity (MPa)Value of modulus elasticity from SNI 2002
formula for concrete weight ± 2300 kg / cm3(eq.5) and for concrete weight between 1500 s.d2500 kg / cm3 (eq.4) has not too much different(4.1% - 4.6%). This is because the normal
concrete and fiber concrete has a specific gravity
and compressive strength for each variation that
not too much different.

15

20

25

30

𝑓𝑓′𝑐𝑐 (MPa)35Eurocode 2

ASTM C-469

SK SNI T-15 1991 (1)SK SNI T-15 1991 (2)TS - 500

Linear (Eurocode 2)

Linear (ASTM C-469)

Linear (SK SNI T-15 1991 (1))

Linear (SK SNI T-15 1991 (2))

Linear (TS - 500)

Fig. 7. Regression of modulus elasticity of PVC
coated welded mesh fiber concrete with variation offiber’s fraction

Modulus Elasticity (MPa)Eurocode 2-1992 and ASTM C 469

Modulus Elasticity (MPa)Eurocode 2-1992 and ASTM C 469
50000

statement is similar with the theory of modulus
elasticity in Eq. 1.
In this paper, the effect of PVC coated welded meshfiber as a fiber in concrete will be analyzed based on
Eurocode 2-1992 and ASTM C-469. Experimental
result (Fiq.8) showed that the higher the fiber’s
fraction added to the concrete mixture, the greater themodulus elasticity resulted. However, PVC coatedwelded mesh fiber concrete has a less value ofmodulus elasticity when it compared with normal
concrete. The addition of PVC coated welded meshfiber did not give a positive effect to the compressive
strength or it can be said the compressive strength was
decreased (decreased by 19.4%.)
Based on previous research, fiber increase tensile
strength although it has little effect on compressive
strength. However in this study it can be seen that theaddition of PVC coated welded mesh fiber did notgive positive effect to modulus elasticity of concrete.
The wire coated by PVC and give slip effect, so thatbonding between concrete and fiber did not work
well. The addition of fibers are supposed to improve
the tensile strength, but the slip effect causes the fiber
did not give a good effect to tensile strength.
However, modulus elasticity of PVC coated weldedmesh fiber concrete increased as fiber’s volume
fraction increased, even though modulus elasticity offiber concrete less than normal concrete.

49258.1

45000

50000

42221.3

45000
40000

35391.1
35000

29504.6

30000
25000

40000

39694.4
20000

35000

0

29504.7
30000

26407.5

12

24

36

Length fiber (mm)

25000
20000
0.00%

0.50%

1.00%

1.50%

Fig. 9. Summary of modulus elasticity of PVC coatedwelded mesh fiber concrete with variation of fiber’s
length2.00%

Fraction (%)

Fig. 8. Summary of modulus elasticity of PVC coatedwelded mesh fiber concrete with variation of fiber’s
fractionFig. 10. Summary of modulus elasticity of PVC
coated welded mesh fiber concrete with variation offiber’s length interlocking
Figure 9 showed that PVC coated welded meshfiber concrete with variation of fiber’s length 24 mm
had the highest value of modulus elasticity. However
it decreased 14.29% from normal concrete.
The effect of PVC coated welded mesh fiber
concrete with variation of fiber’s length showed inFig. 10. The addition of fiber’s length interlocking
produced a decreasing effect on the modulus
elasticity. Compared with normal concrete, modulus

Figure 7 presented that the data regression ofEurocode 2-1992 and ASTM C-469 are coincide.
Both methods of SK SNI 2002 also produce linear
lines
that
are
mutually
coincide.
Although with different models and parameters, it canbe seen that compressive strength increased followedby the increased of modulus of elasticity. This

435

SEE - Nagoya, Japan, Nov.12-14, 2018

elasticity of PVC coated welded mesh fiber concretedecreased by 24%.

a fiber material is not effective in increasing themodulus elasticity of concrete.
REFERENCES[1] ACI 544.1R-96. State of The Art Report on Fiber
Reinforced Concrete[2] Iwan R. Utilization of Waste Can As Fibers To
Improve Concrete Characteristic. Teodolita,
Vol.14, No.2, 2013, pp.56-70. (in Indonesian)[3] Kampa R. Strength Characteristics of Coca-Cola
Tin Waste As Fibres in Concrete. IJARF, Vol.3,
Issue 2, 2016, pp.9-12.
[4] Hossein M., Jamaludin M. Y., Abdul R . M. S, A.
S. M. Abdul Awal. Journal of Cleaner Production,
144, 2017, pp.448 – 458.
[5] Ankur C. B, Narendra K. A. Construction and
Building Materials, 146, 2017, pp.455 – 463.
[6] Haryanto Y. W., Recky S. G. Effect of Wire
Fibers To Square Column Capacity. Jurnal Teknik
Sipil, Vol. 7, No. 1, 2006, pp.1 – 13. (inIndonesian)[7] Emi M. Review of Compressive Strength andModulus Elasticity For Diatomaceous As
Additives. Teras Jurnal, Vol. 6, No. 2, 2016, pp.
81 – 90. (in Indonesian)[8] H. Z. Cui, Tommy Y. L., Shazim A. M., F. Xing,
X. Shi. Analitycal Model for Compressive
Strength, Elastic Modulus and Peak Strain of
Structural Lightweight Aggregate Concrete.
Construction and Building Materials, 36, 2012,
pp.1036 – 1043.
[9] Turhan B. Investigation of Performance of Some
Empirical and Composite Models for Predicting
The Modulus of Elasticity of High Strength
Concretes Incorporating Ground Pumice andSilica Fume.
Construction and Building
Materials, 127, 2016, pp.850 – 860.
[10] SNI 03-2834-2000. Indonesian National
Standard. Procedures Mix Design For Normal
Concrete. (in Indonesian)[11] Chu-Kia Wang, Charles G. Salmon. Design ofReinforced Concrete. Vol.1, Fourth Edition.
Jakarta: Erlangga. 1994 (in Indonesian)[12] https://www.transtutors.com/
homework-help/civil-engineering/modulus-ofelasticity.aspx

Eurocode 2-1992 and ASTM C 469

Modulus Elasticity (MPa)

50000
45000
40000

35298.5

35000

29504.6

30000

20590.1

25000
20000
15000
0

0.6

1.2

1.8

Length interlocking (mm)

SUMMARY
1. Modulus elasticity calculated by Eurocode 2 1992 and ASTM C 469 are similar to each otherbecause both of the empirical models related tostress-strain relationship of fiber concrete. The
other empirical model such as SNI 2002 and TS500 also similar to each other and related tocompressive strength.
2. Although each of empiric models have a different
paramaters, however have the same pattern that is
an increase in compressive strength followed byan increase in modulus elasticity
3. Based on variation of fraction, PVC coatedwelded mesh fiber fraction of 1.5% produced thehighest modulus elasticity. However, compared tonormal non-fiber concrete, modulus elasticity
decreased by 19.4%.
4. Based on variation of fiber’s length, the modulus
elasticity produced the highest value on variationof fiber’s length 24 mm. However, compared tonormal non-fiber concrete, the elasticity modulus
value decreased by 14.29%.
5. Based on variation of fiber’s interlocking length,
fiber’s length interlocking of 0.6 mm produced thehighest modulus elasticity. However, compared tonormal non-fiber concrete, the elasticity modulus
value decreased by 24%.
6. Less bonding between fibers with concrete may
cause the use of PVC coated welded mesh fiber as436

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECT OF BRICK MASONRY INFILLS TO SEISMIC CAPACITY OF
INDONESIA MULTI-STORY RC BUILDING
Jafril Tanjung1, Maidiawati2 and Aditya Alfajri2
Engineering Faculty, Andalas University, INDONESIA; 2Padang Institute of Technology, INDONESIA

1

ABSTRACTThis paper discusses an analytical study on the effect of brick masonry infills to seismic capacity of the multistory reinforced concrete (RC) structures by using the finite element computer codes called STructural Earthquake
Response Analysis 3D (STERA 3D). A survived three-story RC building after the 2007 Sumatra earthquake wasconsidered as an analytical model. The building was located in Padang city, West Sumatera, Indonesia. The model
was analyzed for pushover and time history analyses. The pushover analysis was conducted followed UBC codeand the recorded ground acceleration of 2009 West Sumatra earthquake was applied as input motion in time history
analysis. The structural detail and material properties used in the analysis were collected from site investigatedbuilding after 2007 Sumatra earthquake. Two analytical RC building models were analyzed and compared in thisstudy, i.e. bare RC frame model and brick masonry infilled RC frame model. The results of the analytical study
were compared to the resume of the field observation after the earthquake for the considered building. The
analytical results are clearly shown that the brick masonry infills may significantly improve the seismic capacityof the RC building. The RC building could be survived to large ground motion even the building was designed byapplying the old Indonesia building code.
Keywords: RC building, Brick masonry, Seismic capacity, STERA 3D, Sumatra earthquake

buildings are shown as two red-boxes in Fig. 2. Thesebuildings were built in 1980. There was no detail
information about the structural design of these RC
building. However, it has been believed that thestructure of these RC buildings was not designed toresist the strong ground motion such as 2007 Sumatra
earthquake. The Suka Fajar building was used as a
car's showroom, while the Sutan Kasim building as acompany’s office and car’s tire dealer. Since Suka
Fajar was occupied as the car shown room, most of
the infills used tempered-glass. Contrast to Suka Fajarbuilding, Sutan Kasim building used brick masonry
as infills.

INTRODUCTION
The successive M8.5 and M7.9 earthquakes havestruck the south of Sumatra Island on September 12,
2007 (6:10 PM local time in Western Indonesia) and
September 13, 2007 (6:49 AM local time in Western
Indonesia) [1]. The epicenters of these earthquakes
are marked in yellow and red stars in Fig.1. A locationof the epicenter of the first event was approximately
30 kilometers off the coast southwest of Bengkulu
city at the depth of about 30 kilometers. The second
event was located about 225 kilometers off thenorthwest of the first event at the depth of 10
kilometers. These ground motions caused massive
damaged of thousand houses and hundreds of RC
building along the coastline in Bengkulu and West
Sumatra provinces and Mentawai Islands [2]. One of
the most affected city by the earthquakes was Padang
city, West-Sumatera province, located approximately
180 kilometers from the epicenter of the second event.
Post-earthquake investigation of the damaged RC
buildings caused by this 2007 Sumatra earthquake in
Padang city, has been conducted and well-reported by
Maidiawati and Sanada [3]. Their investigation has
shown the interesting results about the effects of thebrick masonry infills to the seismic capacity of the RC
multi-story building. They found that two adjacentcomparable tree-story RC buildings have differently
behaved due to ground motion of the 2007 Sumatra
earthquake. These RC buildings were Suka Fajar andSutan Kasim buildings. The locations of these RC

Fig. 1

Epicenters of the 2007 Sumatra Earthquake.

Due to the 2007 Sumatra earthquake, the Sutan
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SEE - Nagoya, Japan, Nov.12-14, 2018

Kasim building had survived, while the Suka Fajarbuilding collapsed. Maidiawati and Sanada [3] havealso evaluated the seismic capacity of these RC
buildings by using the Nakano’s method [4] and theJapanese standard [5]. They concluded that the brickmasonry infills has significantly contributed improve
the seismic capacity of Sutan Kasim RC building. In
their study, the seismic capacity was only considered
the first-story of the buildings. The presence of thebrick masonry infills in Sutan Kasim RC frame
structure helped the building survive during theearthquake. More detail of this field observation andevaluation works has been clearly summarized in [3].

Fig. 2analytical purpose, a survived Sutan Kasim building
has been considered. The computer codes called
STructural Earthquake Response Analysis 3D(STERA 3D) was used as an analytical tool [11,12].
These codes were developed by Professor Taiki Saito
from Toyohashi University of Technology, Japan.
THE MATERIAL AND METHODS
Figure 4. shows the typical floor plan for all floorsof the Sutan Kasim building according to detail sitemeasurement. The notation C and B which is shownin Fig. 4a denotes the column and beam of the RC
structure, respectively. The detail reinforcements
arrangements for these columns and beams are given
in Table 1 and Table 2, respectively. The location of
the masonry infill walls is notated by the bold line in
Fig.4b.

Location of Evaluated RC Buildings.

(a)

(a)

Fig. 3

Suka Fajar Building

Typical Floor Plan(b) Sutan Kasim Building

Photos of Evaluated RC Buildings.

Obviously, several researchers have been focusedon the investigation of effects and behaviors of themasonry infills to seismic performance, including theseismic capacity, of the RC structure. For instances,
Tanjung and Maidiawati [6,7]; Maidiawati et.al. [8];and Maidiawati and Sanada [9] have studied theseeffects through experimental works by testing thesingle-bay and single-story of RC frame structuressubjected to lateral static loads. Their works haveconcluded that the masonry infill increases the lateralstrength and stiffness of the RC frame structures, but
reduce the structure’s ductility. The comprehensive
discussion of this topic has also been explained byAsteris [9], Barnaure and Stoica [10] in their research
articles. They have discussed the failure modes andthe mathematical model for the masonry infills in
related to the seismic performance of the RC frame
structure.
In this paper, an analytical study for defining theeffects of brick masonry infills to the seismic capacityof the multi-story RC building is presented. For this(b)Fig. 4

The Location of Brick Masonry Infill

Floor Plan Used in the Analytical Model.

The compressive strength of the existing concreteused in the considered structure was about 26.7 MPa[9]. Its compressive strength was obtained byconducting the non-destructive Schmidt Hammer test
and the uniaxial compressive test on the cylinder
concrete specimens taken by the core drill machine.
All RC structures installed plain rebar with nominal
yield tensile stress about 307 MPa for the longitudinal
flexure and 240 MPa for shear reinforcements,
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SEE - Nagoya, Japan, Nov.12-14, 2018

respectively [3,9]. The compressive strength of thebrick masonry is 4 MPa.

5. As it mentioned above, two types of analysis were
performed on the models, i.e. the pushover and thetime history analyses. The pushover analysis was
conducted for maximum drift ratio 1/100 in X and Y
directions, respectively. For the time history analysis,
the input ground motions with a maximum
acceleration of about 320 gals for 60 seconds’
excitation was applied. The maximum acceleration of
320 gals was applied in according to the reported peakground motion on the coastline of Padang city causedby the 2007 Sumatra earthquake [1]. These input
ground motions were generated from the recorded
ground motion of 2009 West Sumatra earthquake
which was recorded by seismograph installed at
Singkarak Hydro Electric Power Plant [13]. The
works of the analytical study described in this paper
thus following an analytical matrix as is tabulated inTable 3.

Table 1 Reinforced Arrangements of ColumnsnColumnC1
C2
C3
BxD
350x350350x550Main
4φ22
1 rebar
8φ22
10φ22
4φ16
Hoop
2φ6@200
BxD
350x350350x550
Main
4φ22
4φ22
2 rebar
4φ16
6φ16
Hoop
2φ6@200
3 BxD
350x350350x550
Main
8φ16
rebar
Hoop
2φ6@200
Unit: mm; n: story number

C4
350x70018φ22
350x700
4φ22
14φ16
350x700
18φ16

Table 2 Reinforced Arrangements of Beams
N

Beam
BxD

B1
B2
B3
350 x 550
250 x 420
350 x 720
4φ16
10φ16
2 Main rebar
10φ12
4φ12
2φ12
Stirrup
2φ6@100 (middle: 2φ6@150)
BxD
300 x 450
250 x 420
350 x 720
4φ16
10φ16
Main
rebar
3
6φ22
4φ12
2φ12
Stirrup
2φ6@100 (middle: 2φ6@150)
R BxD
300 x 450
250 x 420
300 x 550
4φ16
4φ22Main rebar
4φ12
4φ12
Stirrup
2φ6@100 (middle: 2φ6@150)
Unit: mm; n: story number(a)

The STERA 3D computer codes were used tocreate the analytical models for the given floor plan
shown in Fig 4. The STERA 3D is the computercodes based on the nonlinear finite element method
which can be used to evaluate the seismic
performance of the RC and Steel buildings. The
STERA 3D computer codes have the capabilities toperforms the elastic modal analysis, the nonlinear
lateral static pushover and the nonlinear lateral static
cyclic analysis and the nonlinear earthquake
responses analyses. STERA 3D comes with thegraphic user interface to create and to analyze thebuilding model and then also to show the analysis
results. To make the analysis more reliable, the beam
is modeled as a line element with nonlinear bending
and shear springs. The column is also modeled as aline element, however, considering the nonlinear
interaction between axial force and bending moment.
The interaction is furthermore expressed by thenonlinear axial springs for concrete and nonlinear
multi springs for the reinforcements. The masonry
infill is defined as a line element with nonlinear shear
spring and vertical spring in the middle of the brickwall [11]. The final images of the analytical models
for the bare frame and the bare frame with brickmasonry infills models, respectively, are shown in Fig(b)Fig. 5

Bare Frame Model

Frame with Brick Masonry Infill Model

3D Analytical Models.

Table 3 Matrix of the Analytical Study
Analytical Works

Codes

Bare Frame Model
Pushover X-direction

PO-X-WO

Pushover Y-direction

PO-Y-WO

Time History Analysis

EQ-WO

Bare Frame with Infills Model

439

Pushover X-direction

PO-X-MWPushover Y-direction

PO-Y-MWTime History Analysis

EQ-MW

SEE - Nagoya, Japan, Nov.12-14, 2018

NUMERICAL RESULTS AND DISCUSSION
Figure 7. shows the comparison of the postimages of the analytical models between the RC
frame structure and RC frame structure with brickmasonry infills. In STERA 3D, the damages on the
structural components of the RC building is definedby the ductility of its structural components. Whenthe ductility in a range of one to five denotes its
structural components experience light to moderate
damage, while for ductility great than five denotes
severe damage. The comparison of these damage
structural components is tabulated in Table 4. The
presence of the brick masonry infill can reduce thedamage of the columns up to 17% and beam almost
50%. As we have been presumed, the analyticalresults show the presence of the brick masonry infill
can reduce the number of the damaged structuralcomponents.

(a)Fig. 7

X-direction(b)

Y-direction

Bare RC Frame.

Fig. 8(b)(a)

Comparison of the Base Shear.

The comparison of analytical results in the term ofbase shear of the models, including the comparison
with the requirement base shear design following
Indonesia RC building code SNI-1726-2012 [14], isshown in Fig. 8. Noting that for the time history
analysis, the North-South and East-West directions
coincide with X and Y directions of the building,respectively. The minimum requirement of the baseshear design was evaluated based on seismic siteparameters where the building was constructed.
These parameters are the soil specification is themedium soil; the maximum spectral response
acceleration at short periods SS is 1,35; the maximum
spectral acceleration at a period of 1 second S1 is
0,599; the acceleration-based site coefficient Fa is 1,0;
the velocity-based site coefficient Fv is 1,3; themaximum spectral acceleration at short periods
adjusted for site class SMS is 1,35; the maximum
spectral acceleration at a 1 second period adjusted forsite class SM1 is 0,779; the design spectral response
acceleration at short periods SDS is 0,9; and the design
spectral response acceleration at a period of 1 second

Bare RC Frame with Brick Masonry Infill.

Post-images of the Analytical Models.

Table 4 The Damage of Structural Components
Components

Percentage of Damage
Moderate
SevereBare RC Frame
Column
67%
0%
Beam
56%
18%
Bare RC Frame with Brick Masonry Infill
Column
40%
0%
Beam
8%
0%

440

SEE - Nagoya, Japan, Nov.12-14, 2018

SD1 is 0,519. The above seismic site parameters were
defined by Indonesia Seismic Design Map [15]. The
importance factor I is 1,0, and response modification
coefficient R is 8. These analytical results show thatthe presence of the brick masonry infills seems tohave given a significant contribution for increasing
the base shear, especially in Y-direction. Obviously,
all base shears of the analytical models greater thanminimum requirement by Indonesia code SNI-17262012 [14].

structures; see the comparison results for Y-directionin Fig. 9b.

Fig. 10 Comparison of the Seismic Capacity.

(a)

X- direction

(a)

(b)

Fig. 9X-direction

Y-direction

Comparison of the Inter-Story Drift.
Y-direction

The analytical results of the inter-story drift for
the analytical models are given in Fig. 9. Refer to
SNI-1726-2012 [14], in the case of RC frame
structure, with or without brick masonry infills, theinter-story drift is limited to 1% of the inter-floor
height and then divided by 1,3. All results of the
pushover analysis passed the limitation of the interstory drift of the current Indonesia code, while theresults of the time history analysis still adequate thecode. Again, the brick masonry infill shows it
superior to increase the seismic performance of the
RC structure by reducing the inter-story drifts ofFig. 11 Seismic Response of the Structure.
Comparison of seismic capacity which is plottedbased on the results of the pushover analyses of theanalytical models is shown in Fig. 10. These graphs
also clearly show the effect of the presence of thebrick masonry infills on the seismic capacity of theRC frame building, i.e. have significantly increased
the frame's seismic capacity. In this case, since thelocation of the brick masonry infills is parallel to theY-direction, the increased of the seismic capacity is
441

SEE - Nagoya, Japan, Nov.12-14, 2018

more observable in this direction.
A similar tendency regarding the effect of thebrick masonry to the seismic capacity of the RC
building is also shown by the graphs of the relation
between base shear and the lateral displacement of the
RC building as is shown in Fig 11. The lateraldisplacements in it figure were picked-up on the topof the building. The result of it comparison, again
especially in Y-direction, confirms the effect of brickmasonry infills can significantly improve the seismic
capacity of the RC building. The stiffness of the RC
frame is significantly raised due to the existence ofthe brick masonry infill, especially in Y-direction.

[4] Nakano Y., Maeda M. and Kuramoto H.,
Guidelinefor
Post-Earthquake
DamageEvaluation and Rehabilitation of RC Buildings inJapan. 13th World Conference on Earthquake
Engineering, 2004.
[5] The Japan Building Disaster Prevention
Association, English Version, 1st, Standard for
Seismic Evaluation of Existing Reinforced
Concrete Buildings, 2001, 2005.
[6] Tanjung J. and Maidiawati, Studi Eksperimental
tentang Pengaruh Dinding Bata Merah Terhadap
Ketahanan Lateral Struktur Beton Bertulang,
Jurnal Teknik Sipil ITB, Vol. 23 No. 2, 2016, pp.
99-106.
[7] Tanjung J. and Maidiawati, The Experimental
Investigation on Beneficial Effects of the Local
Brick Masonry Infills to Seismic Performance of
R/C Frame Structures in West Sumatera,International Journal of Civil Engineering andTechnology (IJCIET), Volume 8, Issue 10, 2017,
pp. 687–697.
[8] Maidiawati, Sanada Y., Konishi D. and TanjungJ., Seismic Performance of Nonstructural Brick
Walls Used in Indonesian R/C Buildings, Journalof Asian Architecture and Building Engineering(JAABE), Vol.10 No.1, 2011, pp. 203-210.
[9] Maidiawati and Sanada Y., R/C frame–infill
interaction model and its application to Indonesia
buildings, Earthquake Engng Struct. Dyn. 46,
2017, pp. 221–24.
[10] Asteris P.G., Kakaletsis D.J., Chrysostomou C.Z.
and Smyrou E.E., Failure Modes of In-filled
Frames, Electronic Journal of StructuralEngineering 11(1), 2011, pp. 11-20.
[11] Saito T., STructural Earthquake Response
Analysis 3D, Technical Manual Version 5.8,
Toyohashi University of Technology, 2017.
[12] Saito T., STructural Earthquake Response
Analysis 3D, User Manual Ver. 5.6, Toyohashi
University of Technology, 2017.
[13] Mangkoesoebroto S.P., Seminar dan Pameran
HAKI Perkembangan dan Kemajuan Konstruksi
Indonesia, 2010.
[14] SNI-1726-2012, Tata Cara Perencanaan Ketahanan Gempa Untuk Struktur Bangunan Gedungdan Non Gedung, BSN, 2012.
[15] http://puskim.pu.go.id/Aplikasi/desain_spektra_
indonesia_2011/

CONCLUSION
The analytical study to define the effects of brickmasonry infill on the seismic capacity of the multistory RC building by using computer code STERA
3D has been presented in this paper. The survived
tree-story RC building during the 2007 Sumatra
earthquake was evaluated as an analytical model. The
structural detail and the material properties used in
the analysis were collected after the earthquake fromthe building site. To the analytical model, thepushover and time history analyses were applied. The
pushover analysis followed the UBC method while
for the time history analysis, the input motion
generated from the 2009 West Sumatra earthquake
was used. From the analytical results are clearlyshown that the brick masonry infills may significantly
improve the seismic capacity of the RC building. The
evaluated RC building could be survived to large
ground motion even though the building was
designed by applying the old Indonesia building code.
ACKNOWLEDGMENTS
The authors sincerely acknowledge to Andalas
University for partially financial supporting to thisresearch works.
REFERENCES[1] https://earthquake.usgs.gov/earthquakes/eventpa
ge/official20070912111026830_34#executive[2] EERI, Observations on the Southern Sumatra
Earthquakes of September 12-13, 2007, EERISpecial Earthquake Report — November 2007.
[3] Maidiawati and Sanada Y., Investigation andAnalysis of Buildings Damaged during the
September 2007 Sumatra, Indonesia Earthquakes,
Journal of Asian Architecture and Building
Engineering (JAABE), Vol.7 No.2, 2008, pp.
371-378.

442

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

STRENGTH CHARACTERISTICS OF WASTED SOFT DRINKS CAN
AS FIBER REINFORCEMENT IN LIGHTWEIGHT CONCRETE
Indradi Wijatmiko1, Ari Wibowo1 and Christin Remayanti Nainggolan1
1
Faculty of Engineering, Brawijaya University, Indonesia 65145

ABSTRACT
Nowadays the problems of lightweight concrete flexural strength have been approached by adding fiber to the
mixture. Meanwhile waste materials are continuously produced as a result of modern industry. This paper aims toincrease the strength characteristic of both compressive and flexural lightweight concrete by introducing wasted
soft-drink cans as fiber reinforce. Comprehensive study has been conducted to investigate the optimal amount offiber fractions and the effect of fiber shape to the concrete mechanical strength. This study cleared the effect ofvarious fractions (10%, 15% and 20% by volume of concrete), followed by two types of fiber shape (hooked andclipped) to the lightweight concrete compressive and split tensile strength. The experimental results of cylindricallightweight concrete were compared to the normal lightweight concrete. The result showed that the introductionof 10% of fiber performed in higher tensile strength with the increase of 23%, while the hooked shape of fiber
increased the compressive strength by more than 40%. It can be concluded that the introduction of waste recycle
tin increased the mechanical properties of normal lightweight concrete, however further study can be performed
to effectively increase the strength characteristics.
Keywords: lightweight concrete, fiber reinforcement, waste materials, compressive strength, tensile strength

wasted is needed.
It has been known that 3R’s program (Reduce,
Reuse and Recycle) helps to preserve conserve
environment for sustainability purposes. However,
one of the environmental issue is the difficulty torecycling and bio-grade of steel waste material. In theother hand, steel waste material may provide higher
tensile characteristic increase the compressive andtensile strength in the concrete, especially lightweight
concrete[3][4][5].
Therefore, some study on the use of recycle orwaste material has been conducted to understand the
behavior of concrete strength. G.C. Behera concluded
that the use of soft drink bottle caps as a fiber with thefraction of 0.25%. 0.5% and 1.0% of the total weightincreased the compressive strength, split tensile andflexural strength especially in the case of 1.0% with
10-15% increment [6][7]. G. Murali et al studied that
introducing crumpled steel fiber concrete with aportion of 0.8% volume of concrete resulting tohigher compressive strength, split tensile and flexuralstrength compare to normal concrete [8]. The used ofpolyethylene terephthalate (PET) bottles fiber wasinvestigated as reinforcement of specimens [9][10].
The result showed a significant increase to indicate
the adherence between PET and concrete forstructural reinforcement [11].
This research study on the optimum fraction ofwasted soft drink can as fiber to improve compressive
and tensile strength, also to study the effectiveness ofinterlocking in the wasted soft drink can to reinforce
the lightweight concrete. Further, two types of

INTRODUCTION
Performance and durability become main
purposes in upgrading construction method andmaterial. One of the methods is by reducing theweight of dead load through applying lightweight
concrete materials. However, the common problem
related with lightweight concrete is the low
mechanical properties. Meanwhile fiber reinforced
concrete (FRC) is a composite material, which aims
to increase mechanical properties (i.e. compressive
and tensile strength), increase the toughness andimprove the energy absorption of concrete [1].
Various type of fiber has been researched, such as
glass, steel, synthetic and un-synthetic fiber [2].
Adding fibers into concrete create mixtures that are
more cohesive and less prone against segregation,
thus the interlock and entanglement around aggregate
particle tended to reduce the workability.
Inclusion of short fibers in a small fraction
improve mechanical performance of FRC by
reducing size and amount of defect in concrete. Oneof the benefit of FRC is providing resistance against
crack propagation, which may lead to pulled out andrupture. FRC has been known could reduce thebleeding of water that lead to plastic and drying
shrinkage cracking. However, each type of FRC has
different properties, advantages and limitations.
Steel fibers has been a common applied material
due to its significant improvement. However,producing steel fibers cost more than its benefit.
Therefore, an alternative material based on recycle or
443

SEE - Nagoya, Japan, Nov.12-14, 2018

interlocking are introduced to get clearer
understanding the mechanical properties of fiber
reinforce concrete.

top and bottom of can, the rectangular shapes of body
were washed thoroughly and dried. Body of can thenwas cut into several sizes depend on the interlocking
length and the type of interlocking (i.e. type A andtype B) as can be seen in in Fig. 2.

MATERIALS
Thirty sixth cylindrical specimens were casted inorder to have deep understanding on the use of softdrink can as fiber reinforce in lightweight concrete.
The component materials are described below.
CementAll specimens used locally manufactured
Pozzoland Portland Cement (PPC) type 1, which iscorrespondent with ASTM type 1.
Aggregates
Fine aggregates were obtained from river aroundLumajang residency, coarse aggregates wereobtained from Pasuruan city. Both places are known
as fine production of aggregates materials in EastJava provinces (Indonesia). In order to produce
lightweight concrete, pumice aggregates wereordered from Bali (Indonesia). Some of the part wererequired to be washed to improve the quality, while
the rest were in the good quality. A group of grain
pumice aggregates 8-16 mm were dipping into apolymer liquid in order to prevent excessive water
absorption, which would disturb water-cement ratio[12]. The coated pumice then dried 24 hours at theroom with the temperature of 25 ± 2°C. The
properties of aggregates can be seen in Table 1.
Table 1 Properties of aggregates
Aggregates

Wasted soft drink can as fiber reinforcement

Fig. 2

Sample of fiber with width of 2mm andlength 40mm without interlocking shape.

Water
3

Specific

Bulk density (kg/m )Watergravity

ASTM

absorption

Ovendry

Fig. 1

Shoveled

RoddedOvendry

Ovendry

Local tap water of the city of Malang, Indonesia
were used and measured for water-cement ratio andalso being used for the curing process of thelightweight concrete.

24hr (%)

Coarse Aggregates
GA

2.67

2696

2589

3.20

PA

1.85

-

-

14

CPA

1.79

-

-

10

2.60

2530

2693

3.22

METHODOLOGY
In this research, the concrete mix design was
aimed for 17MPa at 28 days. Referring to Indonesia
code (SNI 03-2834-2000), the concrete mix
proportion can be seen in Table 2 with the ratio ofwater-cement was 0.5.
In this research 36 cylindrical specimens were
casted with the height of 300mm and the diameter of
150mm. For the purposes of investigating the
optimum fraction of fiber, 24 cylindrical specimens
were casted with four different fraction of fiber’s i.e.
0%, 10%, 15% and 20% of volume, with 6 casted
specimens for each scenarios.

Fine Aggregates
River sandNote: GA (Gravel Aggregates), PA (Pumice
Aggregates), CPA (Coated Pumice Aggregates)
As seen in Table 1, coated pumice has lower
specific gravity and water absorption ability
compares to uncoated ones.
FibersFibers were constructed from metallic waste ofsoft drink can as shown in Fig.1. After removing the444

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Mix Design proportion
Materials

Bulk

RESULT AND DISCUSSIONS

Unit

Volumedensityweight3(kg/m3)(kg)

All specimens were subjected to compressive andtensile test at the day of 28, with the result that can be
described in term of the density and workability,
compressive strength and tensile strength.

Ratio

(m )

Cement

1350

363

0.268

1

Fine

1400

743

0.530

2

Density and Workability

1300

1069

0.822

3

1000

225

0.225

1

The purposes of coated pumice was to prevent thewater absorption, which has been indicated from thereduction of fiber pumice reinforce concrete density
compare to normal ones.

Aggregates
CoarseAggregate
Water

Fiber was made from aluminum soft drink canwith the dimension of 40mm length and 2mm widthwithout any particular interlocking shape. Coding ofspecimens and the attribute data are described inTable 3.

Table 4 Density and slump of specimens
Specimens
code

Table 3 Lightweight specimens properties
Specimens

AmountFiber’s fraction

Interlocking

code(specimens)(% vol)

type

Norm

6

0

No

Fr1

6

10

No

Fr2

6

15

No

Fr3

6

20

No

Il1

6

10

A

Il2

6

10

B

Density

Slump (cm)3(kg/cm )Norm

2250.4514.5

Fr12226.4214.5

Fr22183.3312Fr32215.308Il12213.849Il22232.71

14.5

Workability of mixture can be associated with theslump measurement. Table 4 shows the density andslump of specimens, which indicated that theinclusion of fiber have lower slump value. It has been
confirmed by many scholar and in ACI 213R-87 thatthe coated pumice and fiber inclusion produced lower
slump value due to the low weight as a consequenceof water absorption reduction. In order to avert the
segregation and to maintain the cohesive, a higher
slump value is demanded with the additional effort topreserve the ideal surface of specimens. In this study
the slump value can be keep between 7.5-15cm,
however the addition of waste soft drink can as fiber
caused reduction of slump value and resulting tominor porous on the surfaces as can be seen in Fig. 4.

Further, in order to investigate the effectiveness ofinterlocking, this study introduced two types ofinterlocking as can be seen in Fig. 3(a) and Fig. 3(b).

40 mm
Fig. 3(a) Fiber interlocking type A.

40 mm
Fig. 3(b) Fiber interlocking type B.
All types of specimens were subjected tocompressive tests (3 specimens) and tensile test (3specimens). Therefore, in total there were 18
specimens under the compressive tests and another 18
specimens under the tensile tests. An extensometerand stress-strain gauges were used during thecompressive tests to measure the stress strain abilities
and elastic modulus.

Fig. 4 Identified porous on the concrete surfaces.
445

SEE - Nagoya, Japan, Nov.12-14, 2018

Figure 6 shows the comparison of compressive
strength and deflection between normal concrete andconcrete with 15% of fiber inclusions, which can also
indicated the stiffness of specimens. The addition offiber not only increase the compressive strength, but
it tended to increase the stiffness as well. The stiffnessof specimens with 15% fiber’s volume were increased
14% compare to the normal ones.
The compressive strength of all various
interlocking system generated much stronger
compressive ability compare to the normal ones,
which can be seen in Fig. 7. Although the average ofinterlocking type B was the highest, interlocking type
A most likely produce higher compressive strengthfor each specimen.

Compressive Strength
Compressive strength tests were performed on
three cylindrical specimens for each fraction andinterlocking type. The dots on Fig. 5 shows thecompressive strength on various fractions (0%, 10%,15% and 20% respectively), while the continuous line
is used to connect the average value of each type.
Further, Fig. 5 indicated that though substitution ofstrong gravel aggregate by relatively weak pumice
aggregates might reduce the compressive strength,
however the inclusion of wasted soft drink can as
fiber tended to increase the compressive strengthcompare to normal ones.

20

Compressive Sterngth(MPa)

Compressive
Strength (MPa)

25

15
10
5
0

Norm
Fig. 5

Fr 1

Fr 2

Fr 3

20
15
10
5
0

Norm

Compressive strength of FRC with various
fiber fractions.

Fig. 7The coated pumice commonly reduce thecompressive strength due to the lack of clinker (C3S),
which may resulting on slow hydration and decrease
the heat development. However, the inclusion of thinaluminum can help to distribute the heat quicker andthe ongoing pozzolanic reactions lead to thecontinuous hydration phase. Though the FRC tended
to have higher compressive strength, the optimum
value can be taken from adding 15% volume of fiber.
An excessive fiber higher than 15% of volume lead tothe lack of workability and resulting to porous andmultiple fragmented parts.
Compressive Strength (kN)25Type A

Type B

Compressive strength of FRC with various
fiber interlocking.

Tensile Strength
Tensile tests were conducted on three specimens
for each type at the age of 28 days, as can be seen in
Fig. 8.

350
300
250
200
150
100
50
Norm

Fr2

0
0

Fig. 6

0.2

0.4

0.6

0.8

1

Deflections (mm)Compressive strength vs deflection of
normal and 15% volume of fiber fractions.

Fig. 8446

Tensile strength of FRC with various fiberinterlocking

SEE - Nagoya, Japan, Nov.12-14, 2018

Figure 9 shows the tensile strength of various fiber
fraction. As can be seen, the inclusion of waste softdrink can increase tensile strength compare to normal
ones. Further, the optimum result obtained from thefiber with 10% volume fraction. However, the smoothand slippery surface of soft drink can failed thehomogenous mix between concrete and fiber,
therefore the increasing of tensile strength wasconsidered mild (23% from the normal ones).

Compressive Strength(MPa)

Figure 11 shows the tensile strength result ofvarious interlocking. Despite the smooth and slippery
surface of fiber, the result indicate that interlocking
increase tensile strength. Interlocking createdstronger bound between fibers, which were effective
against tensile and strain effect.

Tensile Strength
(MPa)

2.5
2
1.5
1

2.5
2
1.5
1
0.5
0

Norm

0.5

Type A

Type B

0

Norm
Fig. 9

Fr 1

Fr 2

Fr 3

Fig. 11 Tensile strength of FRC with various fiberinterlocking

Tensile strength of FRC with various fiber
fractions.

The effectiveness of fiber on increasing tensile
strength can be observed visually on the failure
mechanism. In the case of normal concrete, the failure
mechanism occurred all of sudden followed by strong
sound indicate the failure phase achieved. Meanwhile,
the FRC based on the waste soft drink can begun the
failure mechanism with several cracks on the concretesurface, especially at the section where load applied.
The failure of specimen occurred without strong
sound, when the crack elongate from the upper
section into the bottom ones as can be seen in Fig. 8.
At the same time the load dial stopped, and started
showing the reverse number.
Figure 10 shows the sticking out of fiber at theconcrete surfaces in full-length size. This evidence
indicated the slip mechanism during tensile strength
due to the smooth and slippery surface of fiber can.

The tensile strength of fiber with interlocking
tended to increased as shown in Fig. 11. Theinterlocking type A has higher tensile due to the shapeof interlocking effectively bond each other during theload. However, the distribution of fiber also givesignificant impact as shown by specimen with type Ainterlocking code Il1.2 that had lower tensile strength
due to uneven distribution of fiber. Crack was
generated at the location without fiber, as it becomes
the weakest part against the tensile stress.
This research also give significant founding to theissue related to the fiber reinforce concrete by pumice.
It has been known that the low density of pumice keep
it difficult to distribute equally during the casting due
to floating pumice. However, the inclusion of fiberwith interlocking effectively keep pumice fromfloating and as a result pumice can be distributed
equally all around specimen.
Figure 12 shows the equal distribution of pumice
due to the existence of fiber.

Fig. 10 Fiber sticking out of concrete surfaces.

Fig. 12 Pumice distributions on the concrete withhigh fiber inclusions.
447

SEE - Nagoya, Japan, Nov.12-14, 2018

[3] Ismail, Z.Z., and Al-Hashmi, E.A., Validation ofUsing Mixed Iron and Plastic Wastes in Concrete,
Second International Conference on Sustainable
Construction Materials and technologies, 2011,
ISBN 978-1-4507-1490-7.
[4] RajPrasad, J., Anuradha, V., and Gridharan, P.,
Experimental Investigation on Fibre Reinforced
Concrete using Waste Materials, International
Journal of Engineering Trends and Technology(IJETT), Vol. 34, Number 3, 2016, pp.100-105.
[5] Balaguru, P., and Foden, A., Properties of fiber
reinforced structural lightweight concrete. ACIStructural Journal Vol. 93, issue 1, 1996, pp. 6278.
[6] Behera, G.C. and Behera, R.K., Increase inStrength of Concrete by Using Bottle Caps,
International Research Journal of Engineering andTechnology (IRJET), Vol. 02, Issue 03, 2015, pp.
1937-1942.
[7] Behera, D., Ahmed, A.E., and Chala, N.,
Innovative and Suistanable Application of Soft
Drink Bottle Caps as Fiber in Concrete Structures,Vol. 5, Issue 2, 2018, pp. 556-564[8] Murali, G., Vardhan, C. M. V., Sruthee, P., andCharmily, P., Influence of Steel Fibre on Concrete,
Journal of Engineering Research and Applications(IJERA), Vol. 2, Issue 3, 2012, pp. 075-078.
[9] Christian, S., Patel, K., Vasava, M., Vasava, P.,
and Purohit, S., Evaluating Strength of Concrete
Using Bottle Caps and PET, International
Journal of Advance Engineering and Research
Development, Vol. 04, Issue 3, 2017.
[10] Darshan N., Rajani V.A., and Sharath B.P.,
Experimental Study on the Hardened Properties
of Concrete by Using Soft Drink Bottle Caps asPartial Replacement for Coarse Aggregates,
International Journal of Emerging Trends inScience and Technology, Vol. 1, Issues 08, 2014,
pp. 1335-1341.
[11] Akhund, M.A., Sannd, A., Memon, U., andOad, S.J., Utilization of Soft Drink Tins as Fiber
Reinforcement in Concrete, Engineering Scienceand Technology International Research Journal,
Vol. 1, No. 2, 2017, pp. 47-52.
[12] Wijatmiko, I., Wibowo, A., Nainggolan, C.R.,
The effect of polymer-coated pumice to thestiffness and flexural strength of reinforce
concrete beam. MATEC Web Conf., SICEST
2016, 2017.

CONCLUSION
Thirty sixth lightweight fiber reinforce concrete
were investigated to have clear understanding theeffect of waste soft drink can as fiber and its
interlocking to the concrete mechanical properties.
Several outcomes can be observed as follows:
1. Waste soft drink can increase thecompressive strength of lightweight
concrete with the optimum volume fractionof fiber is 15%. Further, the interlocking
type generate higher compressive strength,
which is shown by interlocking type B. The
inclusion of fiber also increase the stiffnessof specimens as well as its deflection under
the axial load.
2. The addition of waste soft drink can giveadvantage on the tensile abilities of concrete
specimens, as it increase 5-23% from thenormal ones. The introduction of two typeof interlocking fiber slightly increase thetensile strength with the highest increasing
was in the interlocking type A.
3. The inclusion of fiber, especially withinterlocking, give additional advantages as
it help keeps pumice from floating to thesurfaces and hold pumice at the evenly
distributed places.
ACKNOWLEDGEMENTS
We acknowledge the support of Higher Education
Excellent Research Grant (Penelitian Unggulan
Perguruan Tinggi-PUPT) from Ministry of Research,
Technology and Higher Education of the Republic ofIndonesia.
REFERENCES[1] Blaszczynski, T., and Przybylska-Falek, M., Steelfiber reinforced concrete as a structural material,
Procedia Engineering Vol. 122, 2015, pp. 282289.
[2] Noaman, A.T., Abu Bakar, B.H., and MD. Akils,
H., Investigation on the Mechanical Properties of
Rubberized Steel Fiber Concrete, Engineering
Structures and Technologies, Vol. 9, Issue 2, 2017,
pp. 79-92.

448

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

OPTIMIZED PREPARATION OF RICE HUSK ASH (RHA) AS A
SUPPLEMENTARY CEMENTITIOUS MATERIAL*Carmela Denise C. Isberto1, Krystoffer Lloyd D. Labra1, Jan Marielle B. Landicho1, andRichard M. De Jesus2
1

Undergraduate Student of Civil Engineering in De La Salle University (Manila), Philippines
2
Faculty of Civil Engineering in De La Salle University (Manila), Philippines*Corresponding Author

ABSTRACTIn the last decade, supplementary cementitious materials (SCM) has been extensively used as an integral
component in the production of concrete. This practice has been motivated by the aspect of sustainability andreduced environmental impact by cutting down substantial amounts of greenhouse gas emission. Correspondingly,
the researchers intend to develop an appropriate method for the use of rice husk ash (RHA), a by-product of ricehusk (RH) which exists in ubiquitous amount in the Philippines, as a partial replacement to ordinary Portland
cement (OPC). Different studies have suggested optimal percentage replacement values of RHA, from 10% to20%, which demonstrated vast improvement in strength of the resulting blended concrete. These optimal values,
however, immensely depends on the burning preparation of RHA which adversely affects the amorphous silica
components, and therefore the pozzolanic activities of RHA in concrete. In this research, a potential approach toconvert RH into optimized and highly reactive RHA by controlled burning and grinding is provided. The effect of
RHA on concrete is investigated through the various proportions of 5, 10, 15, and 20% RHA by weight replacementof cement. Some of the findings are: (i) controlled combustion of RH with temperature ranging from 400 to 600
C and a slow method of cooling for 6 to 8 hours are some of the critical factors needed to produce high silica
content, (ii) concrete containing up to 10% RHA replacement is optimal in maximizing the strength of concrete,and (iii) the incorporation of RHA in concrete by 15% and 20% replacement by weight indicates a lower
workability of the concrete.
Keywords: Rice husk ash, Cementitious material, Incineration, High silica content, Optimized RHA

INTRODUCTION

improve the mechanical properties of concrete, due toits highly reactive silica content, which relatively
makes it a good pozzolanic material [5]. Commonlyand successfully established known SCMs in theconcrete industry include silica fume, fly ash, blast
furnace slag cement, etc. These SCMs indeed
essentially contribute to durability and strength
properties of concrete and generally help reduce CO2
emissions.
Countless significant researches have been carriedout and various explorations were done in search fora material that can pass as a cementitious material. A
popular candidate is RHA.
RH is one of the most common agricultural wastes
in the Philippines which serves as an outer coveringof the rice grain during its growth. According to [6],once the RH is detached from the grain during the rice
milling process, it usually ends up being dumped in
an open space making it worthless thus inducing
deterioration to land and environmental problems [7].
On the other hand, RH has its compelling usage; it has
been broadly employed as a fuel for boiler feed to
produce electricity for the power generation of rice

Clearly today, rapid urbanization and the massive
leap in industrialization create ever-increasing
demands for concrete. Concrete production has thenbeen castigated as it involves consumption of massive
amounts of natural resources and persistently
constitutes to several issues on carbon dioxide (CO2)emissions which pose huge threat on both the society
and environment. Waste management is anotherinterrelated issue that is constantly being addressedby environmentalists and many researchers. It isestablished that one of the solutions to lessen theadverse effects of CO2 emissions brought about by
the production of concrete is to build sustainable andenvironmentally sound cities. Most recent studies[1,2,3] leaned towards green technology andsustainability distinctly acknowledge utilization of
SCMs in concrete.
In evaluating SCMs, chemical analysis using any
appropriate methods as standardized by ASTM C114,
C311, and D4326 should be carried out [4]. One
notable characteristic of SCMs is its ability to449

SEE - Nagoya, Japan, Nov.12-14, 2018

mill. With this, voluminous amount of RHA is being
produced.
RHA is a natural carbon by-product obtained
from RH that is converted to ash during ignition
process [6]. The potential of RHA as a SCM has very
well been regarded since it contains high content ofsilica.
Several researches have been made concerning
the factors that affect the mechanical strength of theconcrete incorporated with RHA such as time ofincineration, temperature, time required for coolingprocess and fineness of the substance [8]. Nanoscale
analysis is being performed to verify the physical andchemical properties of RHA through different test
methods namely SEM, XRD, XRF-EDX [6,8,9].
Based on the analysis stated in the study of [7], results
show that RHA possesses amorphous SiO2 whengathered from a low temperature of 600°C [9]. Many
studies validated that generating RHA by controlledburning of RH between 550°C and 600°C
temperature converts the silica content into
amorphous phase [8,9,10]; and partially substituting
cement with 10% RHA by weight tends to improvethe compressive strength of Portland cement concrete[9].
In this study, an attempt to transform locallyavailable RH into high quality RHA that will exhibit
heightened pozzolanic activity to be suitable as a
cement replacement is done. To ascertain its quality,
chemical composition, physical properties andcharacterization of the produced RHA will be carriedout using X-Ray Fluorescence spectrometry (XRF),
X-Ray Diffraction spectrometry (XRD), andScanning Electron Microscopy (SEM). Also, further
investigation is carried out to determine the optimum
level of replacement of cement by the produced
optimized and highly reactive RHA.

(C-S-H) gel (previously referred to as tobermoritegel) which is the primary agent that binds the cement
and aggregate particles together in concrete. The
approximate hydration reactions of 𝐂𝟐 𝐒 and 𝐂𝟑 𝐒 are
illustrated using the following chemical equations:𝟐(𝟑𝑪𝒂𝑶 ∙ 𝑺𝒊𝑶𝟐 ) + 𝟔𝑯𝟐 𝑶 → 𝟑𝑪𝒂𝑶 ∙ 𝟐𝑺𝒊𝑶𝟐 ∙𝟑𝑯𝟐 𝑶 + 𝟑𝑪𝒂(𝑶𝑯)𝟐(1)
𝟐(𝟐𝑪𝒂𝑶 ∙ 𝑺𝒊𝑶𝟐 ) + 𝟒𝑯𝟐 𝑶 → 𝟑𝑪𝒂𝑶 ∙ 𝟐𝑺𝒊𝑶𝟐 ∙𝟑𝑯𝟐 𝑶 + 𝑪𝒂(𝑶𝑯)𝟐(2)
Chemical Contribution of RHA
High quality RHA which exhibits high pozzolanic
activity can be produced under controlled conditions.
From the study of [11], it was found that burning RH
at 600°C yields the highly pozzolanic RHA
consisting of amorphous silica. From Eq. (1) and (2),aside from the C-S-H gel produced, the hydration
reaction also yields a certain amount of 𝐂𝐚(𝐎𝐇)𝟐 .
This 𝐂𝐚(𝐎𝐇)𝟐 will further react with the amorphoussilica (SiO2) found in high quality RHA to form asecondary type of C-S-H gel. In a research by [12], acomprehensive study was conducted on the
pozzolanic effect of RHA on a cementitious systemand provides the following chemical reaction:
𝑺𝒊𝑶𝟐 + 𝟑𝑪𝒂(𝑶𝑯)𝟐 + 𝑯𝟐 𝑶 → 𝟐𝑪𝒂𝟏.𝟓 𝑺𝒊𝑶𝟑.𝟓 ∙
𝟐𝑯𝟐 𝑶
(3)
Physical Contribution of RHA
Grinding of RHA is usually done to reduce
particle size and improve surface area. Also, it isestablished that an inverse relationship exists between
particle size and pozzolanic activity of RHA.
However, this parameter does not significantly
change beyond 5.6𝛍𝐦. Habeeb & Mahmud (2010)
reported that concretes incorporated with finer RHA
resulted in denser concrete mix wherein the finerparticles acted as micro fillers to enhance the cement
paste pore structure contributing to the overall
strength development of the concrete.

THEORETICAL BACKGROUND
Hydration of Portland Cement
The hydration of cement is the result of mixing
between anhydrous cement with water involving aseries of exothermic reactions taking place both
simultaneously and successively. The main
compounds in cement are as follows: alite(𝐂𝐚𝟑 𝐒𝐢𝐎𝟓 , 𝐂𝐚𝟑 𝐒), belite (𝐂𝐚𝟑 𝐒𝐢𝐎𝟒 , 𝐂𝟐 𝐒), aluminate(𝐂𝐚𝟑 𝐀𝐥𝟐 𝐎𝟔 , 𝐂𝟑 𝐀),
and ferrite (𝐂𝐚𝟒 𝐀𝐥𝟐 𝐅𝐞𝟐 𝐎𝟏𝟎 ,𝐂𝟒 𝐀𝐅). A set controlling agent, such as gypsum, isusually added to prevent rapid setting brought about
by the high reaction rate of aluminate. However, thispaper only examines the chemical reactions involving
tri-calcium
silicate, 𝐂𝟑 𝐒, anddi-calcium
silicate, 𝐂𝟐 𝐒, since only these silicates produce thecalcium hydroxide (𝐂𝐚(𝐎𝐇)𝟐 ) needed for further
reaction with RHA.
The product of reaction of cement with water iscommonly referred to as Calcium-Silicate-Hydrated

METHODOLOGY
Preparation of RHA
A custom-built muffle furnace, with chimney andair inlet, was used to burn the RH. The interior
dimensions of the furnace are 1m wide, 1m height and
1m deep. The RHs were laid flat, measuring about 23cm in thickness, on 28 ceramic hearth plates. The
plates were stacked in multiple layers inside thefurnace using ceramic tubes as columns. About 12kgs
of RH could be loaded in the oven each burning and
450

SEE - Nagoya, Japan, Nov.12-14, 2018

only about 20% of which remains as high quality
RHA.
The muffle furnace utilizes burners (4pcs, 1 ineach corner) and is semi-controlled, that is, the fuel is
supplied from a propane tank and the main mode ofcontrol is through its pressure valve. When in
operation, the control of the temperature inside theoven is not absolute but fluctuates within a small
manageable range. The temperature is monitored
using a Benetech GM700 infrared thermometer
through the 4 holes (1 on each side and 2 in front) of
the furnace, temperature was strictly limited within
the range of 400-600⁰C. Since the temperature only
ranged below the exact optimal temperature ofburning (600C), the burning duration was prolonged
to 10 hours to make up for this temperature
deficiency. During burning, fresh air continuously
flows into the furnace through the 4 holes, thiscondition was defined as free air supply.
After the burning process, RHA is cooled to room
temperature by leaving the furnace door ajar. This
step usually takes 6-8 hours before RHA can be safely
recovered from the furnace.
Grinding of RHA was done using a Los Angeles
machine. About 2.4kgs of RHA is placed into the LA
machine for each batch; 12 pieces of 2” steel balls
were used for grinding. The machine had a rate of
36rpm and was operated for 2hrs in each grinding. To
avoid unwanted absorption of moisture, the RHA isstored in an airtight container every after burning andgrinding

Mix Proportion and Compressive Strength of
Cement Mortars with RHA

Table 1 Mix Proportion of Mortar Specimens

Table 2 Chemical Properties of OPC and RHA

Ordinary Portland Cement type I was used forthis study [13]. Ottawa sand passing through 1.18mm
sieve was used as fine aggregate [14].
RHA blended cement mortars were prepared byreplacing OPC with varying amounts of RHA (5%,10%, 15%, and 20% by weight of cement). The
cement mixes were designated as 05RHA-20RHA,
and 0RHA for the control mix. The mix proportions
are presented in Table 1.
The mortars were mixed using a planetary 4.8
liter-capacity mixer. Each RHA proportion was
produced in batches of 6 mortars and were mixed fora total of 2.5 min with a total of 1.75min rest in
between. Preparation and mixing of materials weredone in the following sequence: (i) water in mixer
bowl (ii) cement poured into bowl and then mixed(30s slow speed) (iii) sand slowly added while mixing(30s slow speed) (iv) further mixing (30s medium
speed) (v) resting cement mix (15s scraping + 90s)and (vi) final mixing (60s medium speed) [15]. Flow
tests were done following each mixing, after whichanother 15s of mixing were done before casting
cement mix into a mortar mold [16]. Compressive
strength of RHA blended cement mortars cubes of
5.08cm size were determined after 7 and 28 days ofmoisture curing, as prescribed by ASTM C 109:
Standard test method for compressive strength ofcement mortars hydraulics [17].

Material
(g)

0%
0
RHA

5%
05
RHA

10%
10
RHA

15%
15
RHA

20%
20
RHA

Oxide Composition (%)

OPC

RHA

Silicon dioxide (𝑺𝒊𝑶𝟐 )

19.6

93.47
0.92

500
0
1375
242

475
25
1375
242

450
50
1375
242

425
75
1375
242

400
100
1375
242

Aluminum oxide (𝑨𝒍𝟐 𝑶𝟑 )5.20

CementFerric oxide (𝑭𝒆𝟐 𝑶𝟑 )

3.20

1.08

Calcium oxide (𝑪𝒂𝑶)

64.8

0.87

Magnesium oxide (𝑴𝒈𝑶)

1.40

3.18

Sodium oxide (𝑵𝒂𝟐 𝑶)
Titanium oxide (𝑻𝒊𝑶𝟐 )

0.40
-

0.04

RHA
Sand
Water

Physical and Chemical Analysis of OPC and RHA
Chemical composition of OPC and RHA used in
the present investigation were determined using an
Olympus Delta Professional Handheld XRF.
Mineralogical analysis of RHA was done by X-ray
diffraction analysis using Shimadzu Maxima X 7000.
A JEOL 5300 scanning electron microscope(SEM) with the aid of a Gold Coater was used toobtain electron micrographs of the RHA sample andpowdered RHA blended mortars.

DATA, RESULTS AND ANALYSIS
Effects of Burning Conditions
Obtaining high quality RHA largely depends onburning techniques which include (but are not limitedto) the duration, and temperature of burning, type ofincinerator, method of combustion and others. The
process of layering the RH on each slab plate level
inside the furnace notably shows an effect on thecolor characteristic of RHA. As observed, laying the
RH thinly flat (less than 2 inches thick) on ceramichearth plates (Fig. 1a) resulted to a faint pink colored451

SEE - Nagoya, Japan, Nov.12-14, 2018

RHA after the incineration process (Fig. 2a). At same
duration, RH placed on the slabs in a triangular prismmanner (Fig. 1b), which was done in attempt tomaximize the area of the slabs and mass produce
RHA, appeared blackish in color (Fig. 2b). Accordingto [1], RHA exhibits a dark color due to its highcarbon content resulting from partial combustion
while a gray or pink-ish-white colored RHA indicateslower carbon content which is due to complete
combustion. Since complete combustion implies
better activity of the produced ash [18], the lattercolor appearance is more favourable. Furthermore, it
is reckoned that attaining such color of RHA is vitalas it substantially ascertains the degree to which RHA
can be suitable for use in concrete.

significantly smaller RHA particles is anticipated to
improve its pozzolanic activity.
XRD analysis was performed to identify themineralogical phase (amorphous or crystalline) of the
RHA produced. Figure 3 displays the XRD pattern ofthe produced RHA. The broad band on 2θ around 22°
represents the RHA as mainly amorphous in form.
Table 2 presents the chemical analysis of both OPC
and the produced RHA using XRF analysis. Thisparticular RHA consists of 93.47% silica. The
aforementioned results confirm that the burning
process was carried out properly and that the RHA
produced may be used as a SCM due to its potential
high pozzolanic activity.

(a)(b)
Fig. 1 Layering of RH on slab plates in two manners:(a) thinly flat (b) triangular prism

Fig. 3 The XRD Analysis of RHA
Fresh Concrete Properties
Workability is a property of fresh concrete
mixture used to assess the ease of mixing, placing,compacting and finishing of concrete. Flow tests were
performed on each proportion of RHA blended
cement mortars using a flow table to quantitatively
evaluate the effects of RHA on the property ofworkability.

(a)(b)
Fig. 2 Distinguished color of resulting RHA (a) faintpink (b) blackish
Experimentally, it was found out thatincinerating RH kept at a semi-controlled temperature
ranging from 400°C-600°C yields a predominantly
optimized pinkish-white RHA by-product. This
indicates that RH was burned to ash completely.
Since the burning process involves large amounts of
RHA, slow cooling method was done which, in turn,affected the chemical compositions of RHA.

Table 3 Flow Test Results

Properties of RHA
The microstructure of RHA and ground RHA
were observed through a scanning electron
microscope as shown in Fig. 4 (a-d). As these figuresshow, grinding RHA have broken down its cellular
structure; its microporous and multilayered particles
have become fine and uniformly sized particles. The% of RHA

Flow (mm)

0RHA
5RHA
10RHA
15RHA

175.30161.20141.33133.3320RHA-

The result of the flow table test indicates that theincorporation of RHA in concrete leads to a decreasein flow value, which is inversely proportional to the
RHA content as shown in Table 3. As listed in thetable, the 20RHA mix was so vicious that it had noflow reading. The large surface area of RHA particles
452

SEE - Nagoya, Japan, Nov.12-14, 2018attracts more water molecules to its surface, causing
the absorption of water by the RHA particles andconsequently reducing the flow value of a concretemix. Hence, the amount of water intended for thehydration of cement and fluidity of the mixture isdecreased so it is imperative that incorporation of
RHA increases the water demand of concrete.

(a)

(b)
Fig. 5 Comparison of compressive strengths obtainedfor 7 and 28 days of RHA blended cement concretemortars.

(c)

However, a substantial decrease in strength of
concrete was observed for concrete mortars
containing up to 15% and 20% of RHA. The decline
in strength indicates that there is too much silica
content in RHA blended concrete specimens wherein
the produced C-S-H during the hydration process
could not react anymore with the amount of silica
available in chemical reaction. Thus, an increase in
the replacement level of optimized and highly
siliceous RHA in supplementary mortar concrete
mixes would less likely enhance the strength
properties of concrete.

(d)Fig. 4 SEM Photographs (a) RHA (x200) (b) RHA(x2000) (c) ground RHA (x200) (d) ground RHA(x2000)Compressive Strength
Figure 5 demonstrates the development ofcompressive strength of cement concrete mortars
with varying mixture proportions of RHA. Becauseof the hydration process that took place during thecuring of the concrete mortars, result shows that thecompressive strength values at 28 days were higher
compared to 7 days except for concrete containing
20%RHA by weight. As presented in Fig. 5, thecompressive strength of the concrete comprising 10%
RHA at the age of 7 and 28 days were 33.972 MPaand 52.768 MPa, respectively. The results clearly
showed that the 10% incorporation of RHA to OPC
mix has significantly outweighed the compressive
strengths of other mix proportions as well as those of
the control OPC mix for 7 and 28 days which were
32.808 MPa and 40.228 MPa, respectively. Thus, it isdeduced that replacement level of 10% is the optimal
mixture proportion in maximizing the strength of
RHA blended concrete. This obtained strength can be
due to the high reactivity of the pozzolanic material
burned under controlled conditions [6, 8, 9, 10]. The
resulting high silica content of RHA validates thestatement reported by [6] in which RHA can beconsidered as a SCM in manufacturing concrete.

CONCLUSIONS AND RECOMMENDATION
Presently around the world, extensive andcontinuous researches are being initiated to alleviate
some of the most pressing issues of the environment,
among which is CO2 emissions brought about by
concrete production. Widespread use of SCMs haslong been recognized and firmly supported by many
significant studies as a result of a growing
environmental and sustainability awareness. As
shown in this study, RHA, an agro-waste byproduct,
was used as a partial replacement of cement. The
effects of RHA preparation and burning techniques
on enhancing its composition and pozzolanic
properties were discussed. Some of the substantial
conclusions drawn are as follows:
1.

2.

453

There are critical factors that need to beconsidered in attaining an optimized and highly
reactive RHA which includes correct and proper
burning conditions, controlled incineration
temperature, method of cooling, grinding, andthe type of incinerator or furnace used.
High quality RHA are produced by burning RH
at a semi-controlled temperature of 400°C-600°C

SEE - Nagoya, Japan, Nov.12-14, 2018

3.

4.

5.

6.

and by slowly cooling the resulting RHA for 6-8
hours.
A pinkish-white RHA indicates complete
combustion while a blackish colored one resultsfrom partial combustion. Hence, the former has
better reactivity.
As a result of subjecting RH under the specified
burning temperature, the silica content obtainedfor RHA is 93.47% which makes it highly
siliceous and most likely qualified as SCM.
Incorporation of RHA in concrete by 15 to 20%
leads to a significant low flow value making it
less workable concrete.
10% is the optimal replacement level inmaximizing the strength of concrete. Mortar
strength results show that incorporating
10%RHA into the mix greatly enhances thecompressive strength of concrete as compared to
OPC and other mix proportions.

[6] Aprianti, E., Bahri, S., Farahani, J., & Shafigh,P. (2015). Supplementary cementitious materials
origin from agricultural wastes – A review.
Construction and Building Materials, 74, 176187.
[7] Bakar, R., Gan, S., & Yahya, R. (2016).
Production of high purity amorphous silica fromrice husk. Procedia Chemistry, 19, 189-195.
[8] Alex, J., Ambedkar, B., & Dhanalakshmi, J.
(2016). Experimental investigation on rice husk
ash as cement replacement on concrete
production.
Construction
andBuilding
Materials, 127, 353-362.
[9] Bie, R., Chen, P., Ji, X., Liu, Q., & Song, X.
(2015). Studies on effects of burning conditions
and rice husk ash (RHA) blending amount on themechanical behavior of cement. Cement &Concrete Composites, 55, 162-168.
[10] Ganesan, T., Rajagopal, K., & Thangavel, K.
(2007). Rice husk ash blended cement:
Assessment of optimal level of replacement forstrength and permeability properties of concrete.
[11] Bie, R.X., Song, X.F., Liu, Q.Q., Ji, X.Y., Chen,
P. (2015). Studies on effects of burning
conditions and rice husk ash (RHA) blending
amount on the mechanical behavior of cement.
Cement and Concrete Composites, 55, 162-168.
[12] Jamil, M., Kasih, A.B.M.A., Raman, S.N., Zain,
M.F.M. (2013). Pozzolanic contribution of ricehusk ash in cementitious system. Construction
and Building Materials, 47, 588-593.
[13] ASTM C 150 (2018), Specification for Portland
Cement, ASTM International, PA, USA.
[14] ASTM C 778 (2017), Specification for Standard
Sand, ASTM International, PA, USA.
[15] ASTM C 305 (2014), Practice for Mechanical
Mixing of Hydraulic Cement Pastes and Mortarsof Plastic Consistency, ASTM International, PA,USA.
[16] ASTM C 1437 (2015), Test Method for Flow of
Hydraulic Cement Mortar, ASTM International,
PA, USA.
[17] ASTM C 109 (2016), Standard Test Method forCompressive Strength of Hydraulic Cement
Mortars (Using 2-in. or [50-mm] CubeSpecimens), ASTM International, PA, USA.
[18] Geetha, D., Ananthiand, A., & Ramesh, P.S.
(2016). Preparation and characterization of silica
material from rice husk ash –an economically
viable method. Research & Reviews: Journal ofPure and Applied Physics, 4, 3.

It is highly recommended for future researchers thatdifferent duration, burning temperature, and nominal
particle sizes of RHA be explored.
REFERENCES[1] Yang, W., Xue, Y., Wu, S., Xiao, Y. & Zhou, M.
(2016).
Performance
investigation
andenvironmental application of basic oxygen
furnace slag – Rice husk ash based composite
cementitious materials. Construction and
Building Materials, 123, 1-2.
[2] Thomas, B. (2017). Green concrete partiallycomprised of rice husk ash as a supplementary
cementitious material – A comprehensive
review. Renewable and Sustainability Energy
Reviews, 82, 1-2.
[3] Ahsan, M., & Hossain, Z. (2018). Supplemental
use of rice husk ash (RHA) as a cementitious
material in concrete industry. Construction and
Building Materials, 178, 1-2.
[4] American Society for Testing and Materials.
(n.d.). Standard Guide for Evaluation of
Alternative
Supplementary
Cementitious
Materials (ASCM) for Use in Concrete. ASTM
C1709-11.
[5] Saad, S., Nuruddin, M., Shafiq, N. & Maisarah, A.
(2016). The Effect of Incineration Temperature
to the Chemical and Physical Properties of
Ultrafine Treated Rice Husk Ash (UFTRHA) as
Supplementary Cementing Material (SCM). 4TH
International Conference on Process Engineeringand Advanced Materials, Kuala Lumpur,
Malaysia, August 15-17, 2016. Elsevier.

454

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

INVESTIGATION OF CHANGES IN INDOOR RADON
CONCENTRATIONS BEFORE AND AFTER SEISMIC ACTIVITIES IN
GYEONGJU AND POHANG, KOREA

1

Hanyoung Joo1, Jae Wook Kim1 and Joo Hyun Moon1
Department of Nuclear Energy System engineering, Dongguk University, Gyeongju; Republic of Korea

ABSTRACTThis paper made continuous measurement of the indoor radon concentrations at university building in
Gyeongju, Rep. of Korea, to check if there is any notable pattern between the indoor radon concentrations andseismic activities. On September 12, 2016, earthquakes with magnitude of 5.1 and 5.8 consecutively occurred in
Gyeongju. 14 months later, earthquake with magnitude of 5.5 occurred in Pohang, about 30 km away from
Gyeongju, on November 15, 2017. This study investigated the change in the indoor radon concentrations before
and after earthquakes to identify if there is any pattern between them, and found an interesting pattern. Prior toearthquakes, radon anomalies, which are radon concentration deviating by more than ±2σ from the seasonal
average, was usually identified. When 5.0 or greater magnitude earthquakes occurred, the indoor radon
concentrations decreased sharply a few days before them, and then continuously increased until the occurrenceof the earthquake.
Keywords: Earthquake, Gyeongju, Pohang, Indoor radon concentration, Radon abnormaly

occurrence of the earthquake [7]. Kumar et al
studied the correlation that the between tectonic
activities and abnormal measurements of radon
concentrations in the North-West Himalayan [8].
Kim et al studied prediction earthquake occurrence
by detecting radon radioactivity change[9]. Iovine etal have conducted and analyzed the 3 area, whereoccurred earthquake, radon concentration which
before/after
through
continuous
long-termmonitoring [10].
In contrast with the previous studies focusing on
the outdoor radon concentration, we have measured
and analyzed the indoor radon concentrations at auniversity building in Gyeongju, which is located 10
km away from the epicenter of the 5.1- and 5.8magnitude earthquakes in Gyeongju on September
12 2016, and 22 km away from the epicenter of the
5.5 magnitude earthquake in Pohang in November
15, 2017. Gyeongju and Pohang are known to be on
the same Yangsan Fault and share the geology
characteristic [11]. This study checked if there is any
notable pattern between the indoor radon
concentrations and earthquakes, and if the notable
pattern, if any, is repeated during the Gyeongju and
the Pohang earthquakes.

INTRODUCTION
Radon is a radioactive gas produced by uranium
and radium decaying naturally in soil, rock andwater. About 90% of indoor radon comes fromcracks on floor and wall, and the rest comes frombuilding material such as gypsum board, monazite,
and cement [1].
It is known that an elevated concentration ofradon in soil or groundwater could be a precursor ofearthquake. Several studies have investigated therelationship between the radon concentration andearthquake. Sac et al monitored the radon
concentration at an active tectonic zone in western
Turkey and, found that there was a linear correlation
between the radon emission rate and the seismic
activities in the area under investigation [2]. Arghaet al monitored soil radon concentration andanalyzed correlation earthquake precursor in india[3]. Wakita et al observed precursory changes in theradon concentration of groundwater prior to IzuOshima-kinkai earthquake of 7.0 magnitude 14
January 1978 [4]. Also Kuo et al observed
anomalous decrease in groundwater radon
concentration before earthquake of magnitude 6.4 in
Taiwan[5]. Omori et al observed anomalous
emanation of radon preceding large earthquakes andconsidered it to be linked to pre-seismic
electromagnetic phenomena such as great changes ofatmospheric electric field and ionosphericdisturbance [6]. Kim et al observed considerable
variations of radon concentrations before the

MATERIAALS AND METHODS
Radon measurement device and procedure
As shown in Fig. 1, a RAD7 detector was used tomeasure the indoor radon concentration. The RAD7455

SEE - Nagoya, Japan, Nov.12-14, 2018

can detect radon concentration in the range of 0.1
pCi/L to 20,000 pCi/L with the relative uncertainty
of ±5 % [12].
The RAD7 is able to make continuous
measurement. The measurements were made on thebasis of the U.S Environmental Protection Agency(U.S. EPA) protocols [13]. Before measurement,
Rad 7 was purged more than 10 minutes to evacuate
the remaining radon gas including thorium inside theRAD7. After purging, the air inlet nozzle of theRAD7 was positioned 1.5 m above the floor,
considering the breathing zone of a standard man.
The indoor radon concentration was continuously
measured every 30 minutes for each measurement.
The measurements were made at the corridor
neighboring the main entrance of the first floor in
the Energy Engineering Hall of Dongguk University
in Gyeongju. In the corridor, there was no forced airconditioning except natural ventilation through theentrance door opened and closed by visitors. The
measurement data were recorded and analyzed byusing the program embedded in RAD7.

Radon concentration could be affected by theambient temperature and humidity. Hence, the inlet
air temperature was measured by RAD7 upon eachmeasurement.

Fig. 2 Pohang earthquake epicenter andmeasurement spot.

Fig. 3 Gyeongju earthquake epicenter andmeasurement spot
Fig. 1 Structure of RAD7 detector
RESULTS AND CONCLUSION
Data analysis method
Measurement results
Gyeongju is located in the southeastern area ofthe Korean peninsula, approximately 360 km awayfrom Seoul. Pohang is located 22 km away from
Gyeongju. In Pohang on November 15, 2017, the5.5-magnitude earthquake occurred. Gyeongju andPohang are on the same Yangsan Fault [14].
The measurement point was 22 km and 10 km
away from the epicenter of 5.5-magnitude Pohang
earthquake and 5.1, 5.8-magnitude Gyeongju
earthquake as the crow flies, respectively, as shown
Fig. 2 and Fig. 3.

Indoor radon concentration variation over time
Fig. 4 and Table 1 show the monthly averageindoor radon concentrations from February 2017 to
February 2018, except for December 2017 when themeasurement was not made because of maintenanceof the RAD7.

Table 1 Monthly and seasonal indoor radon concentrations

SeasonMonth(measurement
period)WinterSpring2017.022017.03

Monthly averageindoor radon
concentration[𝐵𝐵𝐵𝐵/𝑚𝑚3 ]
18.4
15.5
456

Average air inlet
temperature
[℃]
11.0
13.5

Seasonal averageindoor radon
concentration[𝐵𝐵𝐵𝐵/𝑚𝑚3 ]18.4 ± 1.2
12.4 ± 0.9

SEE - Nagoya, Japan, Nov.12-14, 2018

SummerAutumnWinter2017.04
2017.052017.062017.072017.082017.092017.102017.112018.012018.02

10.5
10.6
10.0
10.6
9.0
12.2
11.4
15.3
19.8
18.8

18.7
22.3
24.4
28.4
27.9
23.9
20.4
14.3
10.8
9.9

9.9 ± 0.7

15.3 ± 0.9

19.4 ± 1.2

Fig. 4 Monthly average indoor radon concentrations
The curve of the monthly average indoor radon
concentrations is shaped like V-letter. Whiletemperatures in spring and summer are higher thanthose in fall and winter, the indoor radon
concentrations are vice versa. As shown in Fig. 4,
the annual average indoor radon concentration was
13.9 ± 1.2 Bq/m3. Table 1 shows the seasonal
average indoor radon concentrations in autumn andwinter period in 2017, 15.3 ± 0.9 and 19.4 ± 1.2
Bq/m3, respectively.
Previous studies showed that the radon
concentration could be impacted by temperature,pressure, humidity, rainfall, and wind. Using therainfall data obtained from the Korea Meteorological
Administration, we examined the rainfall’s effect on
the indoor radon concentration but did not find its
regular pattern between the two variables in our
measurements, as shown in Fig. 5 that shows radon
concentrations and rainfall data over the durationfrom July 10 to Nov 20, 2017. Because ourmeasurements were made inside building, wind had
virtually no impact on it.
We focused on temperature and humidity. The
temperature effects were analyzed by comparing theradon concentrations during the periods with thesimilar temperatures. Table 2 summarizes inlet
temperature, humidity, and the average radon
concentrations.
Examination of Table 2 and Fig. 5 let us find twointeresting facts. During the duration from July 10 toNovember 2, 2017, the average radon concentration
was 11.9 ± 0.9 Bq/𝑚𝑚3 , as shown in Fig. 5. The
indoor radon concentrations for the duration from
October 2 to October 16 were mostly less than the
average. After October 16, the indoor radon
concentration was much more than the average.
If the radon concentration deviates by more than
±2σ from the related seasonal value, it is possible
to say that radon anomalies are possibly caused byearthquake events and not by meteorologicalparameters [15]. We took closer look at the period of
September 25 to November 21 2017. During that
period, the average radon concentration was 14.80 ±1.0 Bq/𝑚𝑚3 and 2σ value was 20.01 Bq/𝑚𝑚3 . Overthe duration of November 2 to 17, 2017, the indoor
radon concentrations exceeded the average + 2σ,34.8 Bq/𝑚𝑚3 every day.
457

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 5 Radon and rainfall during July 10 to Nov 20
Table 2 Comparison of average radon concentration under similar temperature

Year

2017

Date
08/29
~ 09/1109/11~ 09/18
09/18~ 09/25
09/25~ 10/0205/10~ 05/1505/15~ 05/2105/21~ 05/31

Average

2017

10/02
~ 10/10
10/10~ 10/16
10/16~ 10/23
10/23~ 10/30

04/17~ 04/25
04/25~ 05/01
05/01~ 05/1005/10~ 05/1505/15~ 05/21

Average

2017

10/30
~ 11/06
11/06~ 11/13
11/13~ 11/20
11/20~ 11/27

03/14~ 03/2103/21~ 03/2703/27~ 04/06
04/06~ 04/17

Inlet airtemperature[℃]

Humidity[%]

Average radon
concentration[𝐵𝐵𝐵𝐵/𝑚𝑚3 ]

25.1

21.4

30.30

3.03

11.9

9.2

24.1

22.2

5.61

10.00

10.1

9.3

23.8

4.10
23.4

22.4

14.7
7.61

3.86

12.9
12.2

23.9

22.3

11.0

6.9

12.2

10.5

21.6

18.2

4.25

3.38

12.0

9.8

21.1

19.9

3.95

15.40

10.1

10.9

20.1

20.8

3.61

3.02

9.1

11.0

21.4
18.6

3.03
3.08

22.2

9.2
14.4

10.00

9.9

20.4

20.5

3.7

7.00

11.4

10.0

16.3

13.2

2.88

2.00

14.9

16.9

15.7

13.8

2.72

2.13

15.8

13.8

13.5

15.2

2.18

2.15

13.8

16.0

13.2

18.1

17.30

2.92

13.4

10.8

Average
14.7
15.1
6.3
2.3
14.5
14.4
Fig.6 showed the indoor radon concentrations before
and after the earthquake. On November 16, the458

SEE - Nagoya, Japan, Nov.12-14, 2018

over August of 2017 was 26.6 ± 24.69 Bq/𝑚𝑚3 [15].
One year later, August 10 to 16, 2017, the averageand peak indoor radon concentrations were 10.2 ±0.9 Bq/𝑚𝑚3 and 45.21 Bq/𝑚𝑚3 .
We examined the changes in the indoor radon
concentrations due to Pohang earthquake. The
average and peak radon concentrations overNovember 2017 were 17.0 ± 1.1 Bq/𝑚𝑚3 and79.05 Bq/𝑚𝑚3 , respectively. Over November 2016,
the average and peak concentrations were 14.4 ± 1.0
Bq/𝑚𝑚3 and 76.8 Bq/𝑚𝑚3 , respectively. Table 3
summarized the indoor radon concentrations in 2016
and those in 2017.
The peak indoor radon concentration overNovember 2017 was not much different that overNovember 2016. It was thought that because thedistance between the Pohang epicenter and themeasurement spot is two times longer than thatbetween the Gyeongju epicenter and themeasurement spot, the seismic activities had less
impact.

indoor radon concentration did not exceed theaverage + 2 σ , but on November 17, exceeded
average + 2σ again. Since 3.5- and 3.6-magnitude
earthquakes on November 19/20, respectively, theconcentration did not decrease but increases again.

Fig. 6 Radon concentration between Nov 14 to 17
Comparison with the Gyeongju Earthquake
Gyeongju earthquake occurred on September 12
2016. On August 10 2016, about 1 month earlier
than the earthquake, the peak indoor radon
concentration was 117.6 Bq/𝑚𝑚3 , and the average

Table 3 Comparison between the indoor radon concentrations in 2016 and those in 2017

Measurement
period2016.06.21~ 2016.06.23
2016.07.11~ 2016.07.31
2016.08.10~ 2016.08.18
2016. 10.19~ 2016.10.26
2016.11.01~ 2016.11.30
Concussion

Average indoor
radon
concentration[𝑩𝑩𝑩𝑩/𝒎𝒎𝟑𝟑 ]
8.4
11.0
26.6

9.8
14.4

Maximum
Average indoor
Maximumradon
Measurement
radon
radon
concentration
periodconcentration
concentration[𝑩𝑩𝑩𝑩/𝒎𝒎𝟑𝟑 ][𝑩𝑩𝑩𝑩/𝒎𝒎𝟑𝟑 ][𝑩𝑩𝑩𝑩/𝒎𝒎𝟑𝟑 ]Gyeongju earthquake (2016. 09.12)
2017.06.21
14.3~ 2017.06.23
2017.07.11
14.5
117.6
62.16
~ 2017.07.31
2017.08.10
10.2~ 2017.08.18
Pohang earthquake (2017. 11. 15)
2017. 10.19
15.0~ 2017.10.26
67.8
79.05
2017.11.01
17.0~ 2017.11.30
For earthquakes with magnitudes of 5.0 or
greater, radon anomalies, that is, the indoor radon
concentrations exceeding 2 σ above the seasonal
average, were observed even month earlier than theearthquakes. In some cases, there were noticeable
patterns between earthquakes and indoor radon
concentrations.
We hope that our study will be helpful in
identifying a clearer relationship between
earthquakes and indoor radon concentrations.

To check if there are any notable changes in theindoor radon concentration before and after theearthquake, we measured and analyzed the indoor
radon concentrations at one university building near
the epicenter of Gyeongju and Pohang.
As shown in Table 3, we compared the indoor
radon concentrations at the same periods in the yearof 2016 and 2017, to identify if the radon
concentration is influenced by any environmental
factor except for earthquake. No significant factor,
except for earthquake, was found, which hadsignificantly influenced on the indoor radon
concentration.

REFERENCES[1] M.K. Timothy, Geological Hazards:
Sourcebook, Greenwood Press, 2003.
459

A

SEE - Nagoya, Japan, Nov.12-14, 2018[2] M. M. Sac., C. Harmansh., B. Camgoz., H.
Sozbilir., Radon Monitoring as the Earthquake.
Ekoloji, Issue 79, 2011, pp.93-98[3] A. Deb., M. Gazi., J. Ghosh., S. Chowdhury.,
and C. Barman, Journal of Environmental
Radioactivity, Vol. 184-185, 2018, pp.63-70.
[4] H. Wakita., Y. Nakamura., H. Notsu., M.
Noguchi., and T. Asada., Radon Anomaly: A
Possible Precursor of the 1978 Izu-OshimaKinkai Earthquake. Science, Vol 207, Issue
4433, 1980, pp. 882-883.
[5] T. Kuo., W. Chen., and C. Ho: Anomalous
decrease in groundwater radon before 2016 M
6.4 Meinong earthquake and its application in
Taiwan, Vol. 136, 2018, pp.68-72.
[6] Y. Omori., Y. Yasuoka., and H. Nagahama., etal., Anomalous radon emanation linked topreseismic electromagnetic phenomena, Natural
hazards and earth system science, Vol 7, Issue 5,2007, pp. 629-635.
[7] Y.S. Kim., C.M. Lee., T. Lida., and K.
Yoshioka., A study of the prediction ofearthquake occurrence by detecting radon
radioactivity, Journal Environmental Science,Vol. 12, Issue 6, 2003, pp.677-688.
[8] A. Kumar., S. Singh., S. Mahajan., B. S. Bajwa.,
R. Kalia., and S. Dhar., Earthquake precursory
studies in Kangra valley of North West
Himalayas, India, with special emphasis onradon emission, Applied Radiation and Isotope,
Vol. 67, Issue 10, 2009, pp. 1904-1911.
[9] J. S. Kim., M. J. Kim., S. W. Kim., and H. M.
Lee., An Analysis of anomalous radon variation
caused by M 5.8 Gyenog-ju earthquake, The
KoreanSocietyof
EconomicandEnvironmental Geology, Vol. 51, Issue 1, 2018,
pp. 1-13.

[10] G. Iovine., I. Guagliardi., C. Bruno., R. Greco.,
A. Tallarico., G. Falcone., F. Luca., and G.
Buttafuoco: Soil-gas radon anomalies in three
study
areas
of
Central-Norhern
Calabria(Southern Italy), Natural Hazards, Vol.
91, 2018, pp. 193-219.
[11] K. H. Kim., T.S. Kang, Rhie. J., et al., The 12
September 2016 Gyeongju earthquakes: 2.
Temporary seismic network for monitoring
aftershocks, Geosciences Journal, Vol. 20, Issue
6, 2016, pp. 753-757.
[12] Durridge Company Inc, RAD7, Electronic
Radon Detector User Manual, 2009.
[13] U.S. Environmental Protection Agency (U.S.
EPA), Indoor Radon and Radon Decay ProductMeasurement Device Protocols, Office of Air
and Radiation, U.S. EPA Publication, 1992,
402-R-92-004.
[14] A. Gregoric., B. Zmazek., S. Dzeroski., D.
Torkar., J. Vaupotic., Radon as an Earthquake
Precursor – Methods for Detecting Anomalies,
Earthquake Research and Analysis Statistical
Studies, Observations and Planning, 2012.
[15] J. W. Kim., H.Y. Joo., R. Kim., J.H. Moon.,
Investigation of the relationship between
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a building in Gyeongju, Korea, Nuclear
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2018, pp. 512-518.

460

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

FIELD PERFORMANCE OF THE CAPILLARY WICKIRRIGATION (CAPILLARIGATION) SYSTEMFOR RICE-BASED CROPS*Ricardo F. Orge1 and Derose A. Sawey2
1

Scientist I and 2Science Research Specialist I, Philippine Rice Research Institute, Philippines
ABSTRACTThe Philippines is suffering from the devastating effect of climate change. During extreme drought periods
when it is already too risky to plant rice, farmers are advised to plant vegetables and other short duration crops
so as to maximize the use of limited water supply and have alternate source of income. This study evaluatedthe field performance of a locally developed irrigation system designed to be as efficient as possible so as tomaximize the use of limited supply of water during such conditions and as low cost as possible so that
smallholder farmers could afford to use it. The resulting prototype is a do-it-yourself type irrigation system
which is almost similar in layout as that of the drip irrigation system, except that, among other things, it makes
use of capillary wicks as drippers (hence called as capillarigation system) and maximizes the use of local andrecycled materials. Results of field tests consistently showed that the capillarigation system outperformed theexisting farmers’ irrigation practices (drip and hose) in terms of water productivity. In a field planted withgreen pepper (Capsicum annuum L.), the system yielded a higher water productivity of 36.6 g/L as comparedto the drip irrigation system (9.9 g/L). The same trend was observed when tested in another field planted with
eggplants (Solanum melongena esculentum). Being able to work with unfiltered water, with very low operatingpressure (15-20cm) and discharge rate (20-30mL/h), the capillarigation system offers some advantages whencompared with other existing irrigation methods. It however still needs more field tests so as to further evaluate
its performance under various crop, field, soil, and water conditions.
Keywords: Capillarigation, Capillary wick irrigation, Climate change, Drip irrigation, Drought

their farming activities through the Palayamanan,a highly diversified and integrated rice-based
farming system wherein farmers not only plant rice
but also other crops (vegetables, fruit trees, etc.) as
well as engage in other farming activities likemushroom production (utilizing the rice straws
generated from rice production as by-products),
poultry, livestock, and fresh water fish production,
among others, so as to maximize the use of farm
inputs and agricultural wastes, and provide farmers
additional sources of income [4]. During extreme
drought conditions, vegetables and other uplandcrops are usually planted by Palayamanan farmers
so as to maximize the use of limited supply of water.
While the commercially available drip
irrigation system (DIS) is proven efficient [5, 6], its
cost of acquisition is high and beyond the financial
capability of these small holder farmers. Thus,
PhilRice developed an irrigation system which was
designed to be as low cost and highly efficient as
possible. To lower down the cost and make itaffordable to small holder farmers, one of the basic
criteria in the design and development of the system
is to make the components easy to fabricate andinstall by the farmers themselves, maximizing theuse of recycled materials or those that can easily besourced out within their locality. This led to the

INTRODUCTION
The Philippines is suffering from the devastating
effect of climate change. Droughts, for instance,
have become more intense and frequent, causing
significant losses in crop production. These
extreme drought events are associated with El Niňowhich, as reported by Roberts et al. [1] is affecting
the country’s rice production both in irrigated andin rainfed areas. The 1998-1999 El Niňo inparticular, resulted to a significant reduction in the
paddy rice production, leaving most small holder
rice farmers in debt. Another strong El Niňo hit thecountry in 2015-2016 which, according to thedamaged report of the Philippine Department ofAgriculture as cited by the Food and Agriculture
Organization [2], ‘affected 16 of the country’s 18
regions and of which the impact was strongest in
Mindanao where 27 provinces were affected’. The
occurrence of these extreme drought events is
expected to continue in the future not only in thePhilippines but also in other Southeast Asian
countries, basing from the results of the study by theWorld Resources Institute [3].
To help enhance farmers’ resilience to climatechange, the Philippine Rice Research Institute(PhilRice) is encouraging the farmers to diversify

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SEE - Nagoya, Japan, Nov.12-14, 2018

soil is described as ‘heavy clay having poor
drainage characteristics, high shrink and swell
capacity upon wetting and drying, producing wide
cracks in the soil, hard when dry, and has very slow
permeability’.
Field trials of the prototype CS were establishedtogether with two existing irrigation methods: thehose irrigation (HI) which is commonly practiced
by small holder and resource-challenged farmers
when growing short duration crops, and the DIS
which is used mostly by advanced and financiallystable farmers. The experimental sites were within
500m radius from the PhilRice’s Agrometeorology
station. In all of the field test trials conducted, theobjective was to compare the performance of the CSwith the existing irrigation practices in terms of thetest crop’s performance (yield and agronomic
parameters) and the water productivity. Monitoringof the soil moisture content (MC) was done atdifferent growth stages of the crop, details of which
are described in each of the following test setup.

idea of using capillary wicks as means of dispensing
water. The use of capillary wicks in irrigating
plants was proven to efficiently work in nurseries,
saving water, time and labor in irrigation [7].
However, no advancements had been done yet inmaking use of the capillary wicks in field crop
production [8].
Our initial work proved that the use of capillary
wicks can feasibly be used in an irrigation systemthat is laid out in almost similar manner as that ofthe drip irrigation system. In this system, called as
capillarigation system (CS), capillary wicks serve
as substitute of the drippers following a setup
shown in Figure 1. From the tank (made of 200L
steel drum), water flows out of the float valve into
a container wherein its depth sets the system’s
operating depth, typically not more than 15 cm.
Because water seeks its own level, this level sets thelimit in all ‘risers’ where capillary wicks are placed.
Details on the design and construction of the wholesystem, including the results of the laboratory
studies conducted to identify appropriate wickmaterials and design parameters, was described in
our previous publication [9]. This paper presents
the results of our follow up studies conducted toevaluate the performance of the CS under actual
field conditions, together with the existing irrigation
methods/systems.

Capillarigation vs. hose irrigation (2015 dryseason)A 6m x 6.5m field, divided into six parallel 80
cm x 650 cm plots spaced 20cm apart, was prepared
for testing the performance of the CS side by sidewith the farmers’ practice of HI using green pepper(Capsicum annuum L.) as the test crop. Using
garden tools, each plot was tilled up to 15-20 cm
depth, pulverized, and applied with rice hull biochar
as soil amendment at 5 kg m-2 prior to final leveling.
In the setting up of the irrigation treatments, eachplot served as one replication. No randomization
was done on the assignment of the plots in order tosimplify the setting up of the CS. Thus, the first
three adjacent plots were used in the CS while theremaining three plots were used in the HI. In theCS, lateral pipes made from commercially available
25mm diameter flexible black Polyvinyl Chloride(PVC) plastic hose were laid out in the middle ofeach of the three plots. Risers were installed atevery 50cm length of the lateral. Each riser was
made from the same material (PVC hose) cut to15cm lengths and provided with a rubber seal at thebottom and a means for water from the lateral toflow into it. Final trimming of the risers was done
to maintain a freeboard of 2-3 cm. Two capillary
wicks were installed at each riser, providing ameans for dispensing water into the soil. Eachcapillary wick was made from 5mm (average
diameter) x 20cm long cotton strands extracted
from mop heads normally sold in local groceries orsupermarkets. To minimize mold accumulation as
well as water loss due to evaporation, plastic
drinking straw (6mm dia x 30mm length) were used
to cover each individual wick. Once the whole CS
was laid out, 2-week old green pepper seedlings

Fig.1 Schematic diagram of the capillarigation
system showing the various parts [9].
MATERIALS AND METHODSThis study was conducted at the Central
Experiment Station of the Philippine Rice ResearchInstitute (PhilRice-CES) in Muňoz Science City,
Nueva Ecija, Philippines (15.6712° N, 120.8908°
E) during the dry season of 2015 and of 2016. The
soil at PhilRice-CES, as reported by Javier et. al[10], was classified as Maligaya clay soil, which istypically fine and has a bulk density of 1.33 g cm-3.
In the PhilRice Soil Series Information System, this462

SEE - Nagoya, Japan, Nov.12-14, 2018

were transplanted in two rows for each plot, 60cm
apart and 60cm between hills, with the system’slateral pipe in between each pair of row (Fig. 2).
Wicks were then directed to each row, maintaining
a distance of 10cm from its tip to the nearest plant.
The tip of the wick was also positioned 5cm below
the ground surface. In the HI plot, the plants werewatered twice a day, one in the morning (8-9 AM)
and one in the afternoon (4-5 PM), at an application
rate of 0.5 liter per plant using a 20mm garden hose,simulating a backyard gardening practice.
Following the recommended nutrient management
practice [11], a commercially available complete
fertilizer (14-14-14) was applied in the second week
after transplanting (WAT) at 5g/hill followed by
Urea (46-0-0) and Muriate of Potash (0-0-60) eachat 4g/hill in the 4th and 6th WAT.

point where the float valve was installed (which
represents the sum of all the wicks’ flow rates) wasmonitored weekly.
Capillarigation vs. drip irrigation (2016 dryseason)The components for the drip irrigation system(DIS) used in the study were locally purchased,
comprising of 25mm flexible plastic pipe with builtin emitters (1.2 L h-1 discharge rate) spaced at 30cm,
cut-off valves, pipe connectors and water filters. A
1m3 plastic container was used as water tank which
was provided with a platform made from iron angle
bars to elevate it 1m from the ground.
Water application using the DIS was done by
opening the valve for a period of two hours daily inthe morning (8-9 AM) until harvest, simulating thetypical practice of the local users of the technology.
In the CS, the lateral which was made of flexible
PVC pipe in the previous setup, was replaced withtarpaulin sheet that had been cut to 30cm width,
folded longitudinally to form a U-shaped crosssection and then folded at the ends so that it
resembled a small channel to hold water (Fig. 3).
Bamboo sticks anchored on the ground were usedas stiffeners so that the sides of the tarpaulin would
stay vertical and be able to hold water. With thismodification, the installation of individual risers
along the length of the lateral was no longer needed,further reducing the cost of the system. Like in theprevious setup, the same freeboard of 2-3 cm wasmaintained. .

Fig. 2 A typical setup of a capillarigation systemshowing the placement of the lateral and the wicks
serving two rows of plants.
To determine the influence of each of the two
irrigation methods on the moisture of the soil within
the plants’ root zone, soil samples were taken using
a soil auger at 10 cm distance from the nearest plantand, in the case of the CS, not more than 10cm fromthe nearest wick. The time of getting of soil
samples was referenced from the time water wasapplied in the HI plot. The first sampling was done
one hour before (B) and the second one was six
hours after (A) irrigation water was applied in themorning. For the HI plot, the second sampling time(A) was done prior to the application of water in theafternoon. Each set of soil samples were taken at 0,
10, 20, 30, and 40cm depth and were oven-dried
following the standard laboratory procedures forsoil MC determination. For the whole crop growthduration, three sets of the soil samples were taken,
one at vegetative stage, another at flowering and at
fruiting stages of the crop.
To determine if the irrigation treatments havesome influence on weed population, occasional
weeding was done in all plots to keep them weedfree and the total air-dried weight of all of theremoved weeds were determined.
To check the consistency of the wicks to deliver
water as time passed by, the water flow rate at theFig. 3 The improved CS setup which made use of
the tarpaulin sheet for the lateral.
Two field setups were established to compare
the performance of the CS with that of the DIS. In
the first setup, eight 1m x 15m parallel plots weremade and planted with the same test crop (green
pepper) and management practices as in the 2015setup (CS vs HI). The first 4 plots were devoted to
the CS and the remaining four plots were for the
DIS. Soil samples were also collected in similarmanner as in the 2015 setup except for the depth
which was only up to 30cm. To measure the total
volume of water applied in each irrigation treatment
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SEE - Nagoya, Japan, Nov.12-14, 2018

(CS and DIS) throughout the whole period of crop
growth, a calibrated mechanical-type flow meterwith a resolution of 0.001 m3 was installed at themain line of each irrigation system.
In the second setup, the test crop used was
eggplant (Solanum melongena esculentum),transplanted at 14 days old and spaced at 60cm
between rows and hills. Urea (46-0-0) solution of
10g per 5L water was applied at a rate of 170 mL
hill-1 at 3, 5, and 9 WAT. On the other hand,
Muriate of Potash (0-0-60) solution (10g per 5L
water) was applied at 7 WAT at 170 mL hill-1
following
Inque
and
Agres
(2017)
recommendation.
Monitoring of soil MCs at different root zone
depths and crop stages were done only in the first
setup in the same manner as in the 2015 (CS vs HI)
setup. The time of getting of soil samples wasreferenced from the time water was applied in the
DIS, i.e. one hour before drip irrigation was done.
Each set of soil samples were taken at 0, 10, 20 and
30cm depth and were oven-dried following
standard laboratory procedures for MC
determination. For the whole crop growth duration,
three sets were taken, one at vegetative stage,
another at flowering and fruiting stages of the crop.

Volume of water applied (V)This was expressed in per plant and in per unit areabasis, using the formula,
𝑽𝑽 =

𝑽𝑽𝑽𝑽

`

𝒏𝒏

(2)

Where Vt = total accumulated volume of water
applied throughout the whole duration of crop
growth and n = number of plants
Yield
Yield data were taken from five randomly selected
inner plants in a selected row of an inner plot. An
average was taken to represent the average plant
yield in each irrigation treatment.
Water productivity (Ewu)This was computed following the standard formula:
Ewu =

𝑽𝑽𝑽𝑽
𝒀𝒀

(3)

Where Vt = total accumulated volume of water
applied throughout the whole duration of crop
growth and Y = total crop yield in the area covered

Data gathered

Labor requirement

Unless otherwise specified, the following data
were gathered in all of the field setups establishedunder this study:

This refers to the labor needed in the setting up andin the operation of each of the irrigation method.

Soil MC profile
Cost of irrigation
This was derived from the MC of the set of soil
samples taken during the three stages of the test
crop’s growth (vegetative, flowering, and fruiting).
Standard procedure for oven dry method was
followed and the MC was expressed in gravimetric
dry weight basis.

The cost of irrigation of each irrigation method wascomputed by taking note of the cost of establishingthe irrigation system (materials and labor) and thecost of operation.
Statistical analysis

Average soil MC maintained (aMC)
Whenever applicable, an analysis of variance(ANOVA) was done on the gathered data byconsidering the irrigation methods as treatments
following a Completely Randomized Design.

This parameter was used to evaluate theperformance of the irrigation method in terms ofsupplying water and maintaining soil MC
conducive for crop growth. The following formula
was used:𝑎𝑎𝑎𝑎𝑎𝑎 =(𝑑𝑑𝑑𝑑𝑑𝑑)+(𝑠𝑠𝑠𝑠𝑠𝑠)
𝑛𝑛𝑛𝑛+𝑛𝑛𝑛𝑛(1)

Where dMC = the sum of the MCs taken from therepresented soil depths, sMC = sum of the MCs
taken from the represented crop growth stages, nd =number of soil depths represented, and ns = numberof crop stages represented

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RESULTS AND DISCUSSION
Soil MC, %Vegetative (15DAT)

Capillarigation vs. hose irrigation
Effect on soil moisture content
Comparing the soil MCs at the two samplingtimes during the vegetative stage of the crop, it canbe observed from Figure 4 that there was anincrease in soil MCs from the first soil samplingtime (B) to the second sampling time (A) in the hose
irrigation method.
The difference is more
prominent at the ground surface than those beneath.
On the other hand, in the CS where water wasapplied all the time in small amounts, a reverse
trend was observed - the soil MC was higher in B
than in A, in all depths considered, with the largest
difference observed at the ground surface. This
could be explained by the fact that the second
sampling time occurred in the afternoon (2-3 PM)
and the decrease observed in the CS could be due towater evaporation. For the hose irrigation, higher
soil MC was observed at the second sampling time(A) since it occurred in the afternoon, just six hours
away from its most recent application of water (8-9AM, same day) while in the first sampling time (B),it occurred 23 hours away from its most recent
application of water. At 25 DAT and 35 DAT, there
was no remarkable difference observed in the soil
MC taken at the ground surface for the two
irrigation treatments. One of the reasons is because
the ground surface had already been covered by thecrop’s canopy during this time and water loss due tosurface evaporation was therefore minimized. As
shown also in Figure 4, the highest soil MC for the
CS was observed at 10cm depths particularly during
the sampling period of 15 and 25 DAT. This isbecause the tip of the wicks were buried close to thisdepth.
As shown in Figure 5, the CS maintains a higher
soil MC than the HI in all depths covered. Except
for the 10cm depth which is close to where the tipof the wick was buried (5cm), the soil MC in allother points are almost the same (~20%). In the HI,
on the other hand, the lowest MC was at the surface
which doubles at 10cm and then gradually increased
and stabilized at 20 up to 40cm depths. The marked
difference in the MC at the first 10cm depth
between the CS and the HI can be attributed to thefact that, in the CS, water in very small amount isconstantly delivered into the soil throughout thewhole duration of crop growth whereas in the HI,
soil dryness happened in between each applicationof water which was twice a day (morning andafternoon).

20
10
0
0cm

10cm
20cm
30cm
40cm
T1-B
T1-A
T2-B
T2-A

Soil MC, %40

Flowering (25DAT)

30
20
10
0
Surface

10cm

T1-B

Soil MC, %

30

20cm

T1-A

30cm

T2-B

40cm

T2-A

Fruiting (35DAT)

20
10
0
0cm

10cm

T1-B

20cm

T1-A

T2-B

30cm

40cm

T2-A

Fig. 4 A comparison of the soil MCs at different
soil depths between the hose irrigation (T1) andthe capillarigation system (T2) taken at two
sampling times (B=1h before and A= 6h after
water was applied in T1), during three stages ofgreen pepper growth.
30

Soil MC, %

25
20
15
10
Cap

5

Hose

0
0

10

20
30
Soil depth, cm

Fig. 5 Soil moisture content profiles of thecapillarigation and the hose irrigation.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Effect on crop performance and water use
As presented in Table 1, the CS maintained asignificantly higher average soil MC (20.49%) thanthe HI (14.54%) throughout the whole duration ofcrop (green pepper) growth. Although their yields
did not vary statistically, the yield difference isremarkable which may merit a deeper analysis. One
possible reason could be the assigning of the plots
which was not randomized, resulting in a highcoefficient of variance. Another could be the factthat in the CS-irrigated plants, the soil MC was
always maintained at field capacity while in the HI,
the soil underwent alternate drying and rewetting
which may have some beneficial effects. In spite ofthis however, the CS utilized water more efficiently
than the HI.
Table 1 A comparison of the average soil moisture
maintained, total amount of water applied and water
use efficiency of the two irrigation treatments.

Capillari-gation
Hose
Irrigation
ANOVA
CV

AverageYieldsoil MCper plant(g)maintained*

Water
applied(L
plant-1)

Water
productivity
(g/L)

20.49

68.67

29.07

1.61

14.54

86.00

51.00

1.25

*
8.51

ns
41.87

s
2.69

s
7.8

15 DAT

30
Soil MC, %Treatment

Fig. 6 The field setup of the capillarigation system
making use of tarpaulin sheets as laterals.

20

a

CS

DIS
a

a
ab

b

10
20
Soil depth, cm

30

ab

b
cd

10
0

0

Capillarigation vs. drip irrigation
Figure 6 shows the field setup of the CS and the
DIS wherein in the CS, tarpaulin sheets where usedas laterals, replacing the PVC hose. With thismodification, the labor requirement in the
installation of the laterals and the wicks had been
reduced as compared to that in the previous setup
which made use of the PVC hose as laterals andrisers.

25 DAT

Soil MC, %

30

CS

DIS

a

20

a
abc

10

b

b

a

b

d

0
0

Effect on soil moisture content
Soil MC, %40

As shown in Figure 7, the CS maintained asignificantly higher soil MC than the DIS especiallyin the first 10cm of the root depth, in all stages of
the test crop’s growth. The reason for the low soil
MC in the DIS especially at the soil surface isbecause sampling was done prior to the applicationof water, or 23 h from the most recent applicationof water. Thus, prior to sampling, the soil surface
had been exposed to the hottest period of the day.
In the CS, on the other hand, water was applied
continuously in small amounts throughout thewhole period of crop growth.

20
0

10
20
Soil depth, cm

30

35 DAT

CS

a
a
bcd

0

b

10

ab ab

b b

20

30

Soil depth, cm
Fig. 7 Moisture content (%) profile of the soil taken
during three stages of crop (green pepper) growthand 24h after water was applied in the drip-irrigatedplants. Means with the same letter do not varysignificantly

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SEE - Nagoya, Japan, Nov.12-14, 2018

On the average, combining all the soil samples
taken at different crop stages, the soil MC in CS
followed the same trend as that in the previous trial(CS vs HI) where the highest soil MC was at 10 cm
depth and slightly decreased at 30-40cm depths. On
the other hand, the soil MC in the DIS was lowest
at the ground surface and increases at increasing soil
depths and stabilizes at 20-30cm (Fig. 8).

Labor requirement
The CS requires labor in setting up its various
components which is significantly higher than thatof the DIS (Table 3). In the DIS, all the parts are
already available hence only the labor of setting up
was required. For the CS, on the other hand, around
70% of the labor is spent in the preparation(fabrication) of its various components. However,once the CS had been established, no effort is nolonger needed with regards to applying water to thecrops while in the DIS, there are cut-off valves toopen and close so as to ensure that the water isapplied just at the right amount. With regards to thehose irrigation, 100% of the labor needed were in
the application of water to the plants for the whole
duration (68 days) totaled to 22 labor-h for the 19.5
m2 area or an average of 1.13 labor-h per m2.

Soil MC, %

30
20
10
Cap

Drip

0
0

10

20
Soil depth, cm

30

Table 3 Labor requirement in the setting up
establishment of the two irrigation systems.

Figure 8. Soil moisture content profiles under thetwo irrigation methods, the capillarigation and thedrip irrigation system.

Irrigation
systemEffect on crop performance and water use
Capillarigation
Drip irrigation

There was no significant difference between thetwo irrigation methods in terms of the number ofdays from transplanting to flowering (22 DAT) andfruiting (30 DAT). In terms of yield, however, plots
irrigated with the DIS yielded a significantly higher
harvest than that in the CS (Table 2). However, likein the previous trials, the CS outperformed the DIS
in terms of water productivity.

Setup No. 2 (eggplant, 100 m2)
Yield
330.0
352.0
(g/plant)
Water
consumption
104.8
237.9
(L/plant)
Water
productivity
3.1
1.5
(g/L)

ANOVA

CV

ns

15.8

s

10.7

s

29.6

ns

28.8

ns

4.5

s

11.7

s

8.48

Averagelaborrequirement(labor-h m-2)
0.153
0.022

Material cost
As shown in Table 4, the cost of materials
needed in establishing the CS is computed at Php
14.58 m-2 while that of the DIS is Php 74.03 m-2, a
reduction of 80.31%. Among the reasons that
contributed to the reduced cost of materials in the
CS is its operating pressure that is much lower thanthat of the DIS such that an elevated tank is nolonger needed in the CS. Another reason is the factthat in the CS, a water filter is no longer necessary
since water is discharged through the capillary
wicks which does not necessarily require clean orfiltered water.

Table 2 Performance of the CS as compared to the
DIS (2016 trial).
Capillary
Drip
Setup No. 1 (green pepper, 60m2)
Yield
433.1
599.8
(g plant-1)
Water
consumption
11.8
60.6
(L plant-1)
Water
productivity
36.6
9.9(g L-1)
Weed density
29.2
32.2
(g m-2)

Labor required in
the establishment(labor-h)
60 m2
100 m2
9
15.5
1.5
2

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Table 4 Comparison between the materials used for, and cost of components of, the two irrigation systems
for a 100m2 irrigated area.
Major Component
Water supply tank
Water tank standWater filter andother accessories
prior to deliveryof waterSupply line
Lateral andcomponents fordispensing water

Fittings

Material Used
Drip
Capillarigation
1 m3 plastic tank
200L steel drum
Structure made from a 4mm no stand needed; thethick x 38mm x 38mm steel steel drum was directly
angle bar holding the tankplaced on the ground
1m above the ground
Superflow screen filter,
No filter needed
3m3/hour, 3/4" diameter, 1
1 pc plastic pail (10L)
pc @ Php 475/pc
1 pc plastic faucet¾” dia flexible PVC hose,
6m @ Php 8/m
Dripline, 11.8mm ID,
12.3mm OD with emitters(1.2 Lh-1 discharge) spaced
30 cm apart, 160m long at
Php7/mCost of Component (Php)*
Drip
Capillarigation
4,000
900
1,500
-

475

20
8

Quick start fitting, 48mm x20mm, 8pcs @ Php15/pc¾” dia flexible PVC
hose, 3m at Php 18/m
Flexible PVC hose,
12.5mm dia, 25m at Php
13/m
Cotton twine (from mopheads), 5mm dia x
100mm, 42 pcs at
Php2.33/pc
Plastic drinking straw,
60 pcs at Php 0.13/pc
PVC elbow, ½ x ¾”, 2
pcs at Php 15/pc

PVC tee, ¾”, 1 pc
@Php30/pc

PVC tee 3/4" x 1/2" x3/4", 1 pc at Php 15/pc

30

15

-

60

-

-

20

-

-

30

-

7,403
74.03

1,458
14.58

poly reducing tee, 16mm x
12mm x 16mm, 4 pcs at
Php15/pc
Tee, 16mm x 16mm x
16mm, 1 pc at Php20/pc
Elbow, 12mm x 16mm, 2
pcs at Php15/pc
Total cost
Cost per m2% Reduction

48

54

1,120

325

-

97.86

-

7.8

120

30

80.31

capillary wicks instead of the conventionaldrippers.
From the results of the study, thefollowing conclusions are drawn:
a. The use of capillary wicks is not only
applicable in nurseries but also in field crops
following a setup that is patterned from the drip
irrigation system.
In this system(capillarigation system), the capillary wicks
replace the emitters in drip irrigation systems asmeans for dispensing water to the plants andsome parts had been added to lower down thesystem’s operating pressure and provide somemeans to put up the individual wicks;
b. In all the field trials conducted, thecapillarigation system yielded the highest

SUMMARY AND CONCLUSION
With the advent of climate change, drought has
become more frequent and intense. Hence, it isimportant to consider how water is applied to theplants especially during the time when its supply isvery scarce. Drip irrigation systems which are
already commercially available had been proven tobe efficient however, for small holder farmers
especially in developing countries like thePhilippines, it is not widely used simply because of
its high cost of acquisition. This study presented
the field test results of the developed
capillarigation system which is a low cost variantof the drip irrigation system that makes use of468

SEE - Nagoya, Japan, Nov.12-14, 2018

water productivity when compared to the otherirrigation systems/practices tested;c. The material cost of the capillarigation system
is lower by up to 80% as compared to the drip
irrigation system.
More field tests however are still to be done toverify these results and to further evaluate theperformance of the system in wider areas andvarious field and crop conditions. In particular,
there is a need to further investigate the reason
why, in some trials, the yield of the wick-irrigatedcrops are lower than those in the drip-irrigatedcrops.

Journal of Crop Science, Volume 29, Issue 1,
2004, pp. 21-27.
[5] Goodwin, P.B., Murphy, M., Melville, P., &Yiasoumi, W. Efficiency of water and nutrient
use in containerized plants irrigated byoverhead, drip or capillary irrigation, Aust. J.
Exp. Agric., Volume 43, Issue 2, 2003, pp.
189–194.
[6] Weatherspoon, D.M., & Harrell, C.C. Evaluation of drip irrigation for container productionof woody landscape plants. HortScience,
Volume 15, Issue 4, 1980, pp. 488–489.

ACKNOWLEDGEMENTS[7] Nalliah, V. and Ranjan, R. Sri. Evaluationof a capillary-irrigation system for better yieldand quality of hot pepper (Capsicum annuum).
Appl. Eng. Agric., Volume 26, Issue 5,2010, pp.807-816

The authors acknowledge the assistance ofEngr. Lolita Leal, Science Research Analyst of the
Rice Engineering and Mechanization Division,
PhilRice, during the conduct of the study.
REFERENCES[8] Million, J., Yeager, T., & Larsen, C. Water use
and fertilizer response of Asalea using several
no-leach irrigation methods. Hortechnology,
Volume 17, Issue 1, 2007, pp. 21-25.

[1] Roberts, M.G., Dawe, D., Falcon, W.P., andNaylor, R. L. El Nino–Southern Oscillation
Impacts on Rice Production in Luzon, thePhilippines. Journal of Applied Meteorology
and Climatology, Volume 48, 2009, pp.17181724.

[9] Orge, R.F. and Sawey, D.A. Coping withwater scarcity in rice-based farms:
development of a capillary irrigation system
for small holder farmers in the Philippines,
Agricultural Research Updates, Volume 16,
Gorawala, P. and Mandhatri, S., Eds., Nova
Science Publishers, New York, 2017, pp. 191207.

[2] Food and Agriculture Organization of theUnited Nations. El Nino and La Nina in thePhilippines.
2017.
Retrieved fromhttp://www.fao.org/3/a-i6775e.pdf[3] Luo, T., Young, R., & Reig, P. Aqueduct
projected water stress country rankings.
World Resources Institute. 2015. Retrieved
from
http://www.wri.org/sites/default/files/aquedu
ct-water-stress-country-rankings-technicalnote.pdf.

[10]Javier, E.F., Marquez, J.M., Grospe, F.S.,
Mamucod, H.F., & Rodante E Tabien, R.E.
Three-year effect of organic fertilizer use on
paddy rice.
Philippine Journal of Crop
Science, Volume 27, Issue, 2002, pp.11-15.
[11]Inque, K. and Agres, E.P. Training guide for
Palayamanan
vegetable
production.
Philippine Rice Research Institute, 2007.

[4] Corales, R. G., Juliano, L. M., Capistrano, A.
O. V., Tobias, H. S., Dasalla, N. V., Cañete, S.
D., Casimero, M. C. & Sebastian, L.S.
Palayamanan: a rice-based farming systems
model for small-scale farmers, Philippine469

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

INTERNATIONAL WATER MODEL UNDER PRODUCTIVITY
CONDITIONS: THE CASE OF THE TIGRIS AND THE EUPHRATES
1

Abdulamir Hussein Qasim

1

Faculty of Engineering, Department of Civil Engineering, Kirkuk University, Iraq
ABSTRACT

Allocation of international water resources needs to play a vital role in the shared river basins. An
environmental and reliable framework involves not only the competing parties divided by geography andnational boundaries but also spatially - variable environmental parameters such as water productivity inagriculture. In international rivers, the inflow of turbid materials from the drainage basins of the upstream
definitely affects water quality at the downstream. Consequently, emerging global challenges, such as climatechange, water scarcity, and population growth have to meet rising demand over time. The Tigris andEuphrates (as a case study) give us a good example of the water system in a region politically unstable.
Although a number of studies on water resources allocation modeling, such as ITETRBM and WATERModel, have analyzed the geographic nature of basins, success in achieving sustainable development calls foran optimal water allocation model. Based on water productivity conditions, and to achieve stable, long-termcooperation among riparian countries and sustainable use of the water resources, international Water Model
Under Productivity Conditions (WMUPC) gives us an optimal solution. In order to show the impacts ofwater quality changes on downstream users, these results are presented via histogram. The significant finding,under previous conditions, is the water quantity available in downstream will be less than the quantity
required.
Keywords: International Water Resources, Spatial Equilibrium Analysis, The Tigris and the Euphrates

1. INTRODUCTION

2. NEEDS FOR NEW WATER MODEL

Freshwater is an indispensable resource forhuman life. It is used for different purposes:
irrigation, industry, energy production etc., but theintensity of its use varies according to climaticconditions, economic development, urbanization,etc. More than 286 international watercourses
cross the boundaries of two or more countries [1].
The Tigris and the Euphrates are the largest tworivers in the Middle East. Their basins span
notably three countries, Iraq, Turkey, and Syria,
including more than 126 million people, which
cover 1.4 million km2 and produce around 70 km3
of river discharges each year [2].
By water resource allocation, internationalrivers developments, including their basins withinvarious riparian, can obtain extremes ofcooperation or dispute. It is generally accepted thatconflicting demands over the Tigris and the
Euphrates will intensify. Yet, although theimportance of recent water allocation models, suchas ITETRBM and WATER-Model, the literature
on international water resources allocation anmodeling is still far from an encompassing
complex environment common factors. Therefore,
most of the rivers basins, in politically unstableregions, are not able to establish a long-termcooperative agreement between the riparian.

The appearance of international water disputes,
especially in unstable politically and economicallyregions, raises concerns for the future. The
disputes clearly stem from the mismatch between
demand and supply of water. The climate
challenge currently carries very serious issues
which call for a strategic focus on water resourcesmanagement. Due to low precipitation, Iraq
depends exclusively on the Tigris and the
Euphrates waters [2]. If climate change has played,and still, a role in reducing the water flow of these
two rivers, the dams which control the rivers flowin the upstream riparian also have negative impacts,
not only on the volume of the rivers’ waters but
also on their quality levels.
Inferior water quality will have a serious
impact on land and water productivity. The declineof water quality needs to be addressed and to be
included in any allocation model. Due toenvironmental concerns and the rising complexityof water demands, realize a water model under
productivity conditions needs to explain the basin's
real water availability and to confront population
growth and development.
3. WATER MODEL DESIGN
The linear water model WMUPC illustrates the470

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international Water Model Under Productivity
Conditions. In contrast to the other two precedingwater models, WMUPC model can be used toanalyze the reduction of water quantity as a reason
for quality fall. This model facilitates efficient
analysis of integrated water management among
the different riparian not only for the present but
also for the future. Its actual scope covers the
Tigris and the Euphrates basins. Moreover,
WMUPC has the ability to be developed to cover
not only other international watercourse but also to
add any other environment parameters on specificregions and countries.

ITETRBM, and from Water Allocation of the
Tigris and Euphrates Rivershed WATER-Model,
which developed by [3] and [4] respectively.
Without
considerationofwater
qualityrequirements, these models aim to allocate water
resources in the international rivers among TurkeySyria-Iraq through a network of supply anddemand nodes. However, due to water qualitychanges, ignoring these changes will increase
certainty the conflicts, and significantly reduces
the chance of successful negotiations along theinternational rivers. In an optimistic manner, the
WMUPC allocates all nodes of water demand andsupply by comprising water quality indicators.
A hydraulic network of supply and demandnodes was established and illustrated, as an
example of the case study, among Iraq, Syria, andTurkey. All of the variables pertaining to water
volume in various regions and sub-regions of the
Tigris and the Euphrates, such as the volume of
inflow, outflow, and water consumption for
agriculture, municipal and industrial, were
determined during a certain period of time. The
relationships between the unknown variables andthe given variables were expressed by a number offunctions of the given variables.
The mathematical details of the WMUPC arebased on quantitative outcome variables asfollows:

3.1 Boundary conditions
For the international basins, the optimal modelof water will depend on a mix of factors, includinghydrologic characteristics, quality of water
entering the basins, the water volume that willtravel down towards the downstream riparian andby taking into consideration the constant riparian
water rights. It is important to recognize that the
upstream country, Turkey in the case of the Tigris
and the Euphrates, will always have a different
agenda for the river that it shares with othercountries, Iraq and Syria. Thus Turkey will haveeasy access to better quality water sources.
The Tigris and the Euphrates take their sources
in Turkey, pass through Syria and enter Iraq fromthe north and north-west. The characteristics ofthese two rivers vary from upstream todownstream according to the zones crossed bythem. The variability of climatic conditions in eachriparian country, such as temperature andprecipitation, has played an important role inmodifying water resources qualitatively andquantitatively. Therefore, changes in water
properties by adding the agricultural drainage
water, particularly near the northern border of Iraq,
will seriously affect the water stress in this country.
For agriculture country, good quality of water
for irrigation is a prime requisite. There is acontinuous debate on whether the riparian have torespect water quality in an international
watercourse or just use any quantity of water
without taking into consideration the water
demands of downstream water users. Nevertheless,as long as the water of good purity helpfully
affects the productivity of the land, the poor
quality of the water negatively affects the
productivity of the land. This change can be
expressed mathematically by in the WMUPC
water model.

𝐷𝐷 = 𝜀𝜀 (∑𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 + ∑𝑄𝑄𝑄𝑄 +∑𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇)– 𝐸𝐸𝐸𝐸𝐸𝐸– ∑𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 − 𝐺𝐺𝐺𝐺𝑗𝑗 ∀ 𝑖𝑖, 𝑗𝑗 ∈ 𝑛𝑛 (1)Subject to:𝜎𝜎 = ∑𝑆𝑆𝑆𝑆 − ∑𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇/ ∑𝑆𝑆𝑆𝑆
𝜀𝜀 = 𝑘𝑘 − 𝜎𝜎

(2)
(3)

where D is the quantity of water Demand; TTW
refers to the Total Tributary Water; Q is the
Quantity of water inflow; TRW indicates to Total
Return Water; Ev expresses the loss of
Evaporation; TAMIW is the Total Agricultural,
Municipal and Industrial Water withdrawal; GF
assigns the Groundwater Feeding; i, is the demandand j is the supply nodes of the total nodes n; σrefers to the adjustability ratio of water resource;
SW is the Storage Water quantity; and ε ascribes
water's adeptness and its productivity, which
depends on a constant factor k =1 in this paper.
The water productivity term is used in a variety
of ways and there is no single definition that suits
all situations [5]. Therefore, the concept of waterproductivity has been used sometimes as ameasure of the ability of agricultural systems toconvert water into food, and sometimes used toevaluate the function of irrigation systems as theamount of crop per drop [6]. Consequently, the

3.2 Structure of WMUPC
The WMUPC is inspired from the InterTemporal Euphrates and Tigris River Basin Model
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SEE - Nagoya, Japan, Nov.12-14, 2018

water's adeptness quantitative symbol ε isdeveloped here to simulate the impacts ofirrigation on the water resources system, such as
the side effects of increasing the Total Dissolved
Solid TDS, the impact of biological oxygen
demand BOD, dissolved oxygen DO etc. of therivers.
The problem of estimating water productivity
could become more complex for large areas. The
discrepancy of the meaning of water productivity
between different users, especially in internationalriver basins, will complicate the model
considerably. To simplify this, the waterproductivity can be assessed by subtracting thevalue of water adjustability, which is demonstrated
here by the symbol ε. This step will help us toillustrate the reduction of productivity of the water
resource.

In order to be more confident of WMUPC
outcomes, the model should be calibrated andverified to a satisfactory accuracy. Thus, the model
details are improved and amended significantly inaccordance with the actual water nodes distribution
the main riparian countries in the Tigris and the
Euphrates basins.
The WMUPC model measures the relations
between the proposed demand and supply nodes of
two periods, both lasting for about six months.
Rainy period is ongoing from January till June,
while nearly no rainfall can be seen in the dry
season from July to December. The storage option
in the reservoirs enables the model to simulate
water amount for the included periods which could
satisfy the minimal demands. Water inflows
depend on tributary inflows in addition to
backflow water coming from upstream nodes.
While water outflows depend on evaporation
losses as well as agricultural, domestic andindustrial water withdrawal which are illustrated
by a number of supply nodes.
To indicate water productivity and quality
effectiveness at downstream nodes, at this stage of
research, there is a need for highlight water use invarious productive and consumptive activities.
Consequently, to find out the true figure of how
water quality is affecting its productivity at eachnode, further research needs to be conducted toassess that in more detail. It is clear, however, thehighest level of water use efficiency, reasonably
achievable by the upstream countries, Turkey and
Syria in this case. While water use efficiency in thedownstream countries, like Iraq, will be the lowest
level. To summarize and simplify the results, theindication of water productivity, across different
sections of the rivers, could hypothetically beequivalent to ε in the WMUPC model.

3.3 Model network applications
The WMUPC contains 63 demand and 45
supply nodes similar to the first version of the
figure, which is developed by [1]. The typicalallocations of these nodes are illustrated
schematically in Fig.1.

4. RESULTS AND DISCUSSION
In the simulation of WMUPC model, thesensitive parameters listed in this water model
were selected for the Tigris and the Euphrates
rivers among the riparian countries, in addition towater use for domestic, agricultural and industrial
purposes, including water quality indicator facing
water productivity.
The domestic and industrial sectors in Iraq,
Syria, and Turkey offer a large return rate of water
for irrigation purposes. So, in case of low waterflows in an arid zone as Iraq, only the minimum
agricultural water demands are met. Therefore, thecountry is suffering from a critical lack of water asshown in Fig.2.
In Iraq, the clear indication of the impact ofchanges in water quality on land, although a pretty
good amount of water, is the significant decrease

Fig.1 Network structure of the international Water
Model Under Productivity Conditions WMUPC of
the Euphrates and Tigris Rivers which is modified
from [1] with kind permission from the authors.
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SEE - Nagoya, Japan, Nov.12-14, 2018

in land productivity, for example, the number ofdate trees decreased from 33 to 13 million between
1950 and 2010; the number of sandstorm between
1951 and 1990 was about 24 days/year, while the
Ministry of the Environment in Iraq records 122
sandstorms and more than 280 dusty days from2000 to 2010 in addition to the prolonged droughtand desertification [2].

the water productivity is responsible for water
welfare, even though if this issue has a smallinterest in all riparian countries so far.
Highlighting the importance of these results andthe importance of water productivity, as mentioned
above, isn't in the sense that the water quantity isless important quality. The WMUPC is establishedhere to increase focus attention on both water
quality and quantity.
5. CONCLUSION
The asymmetries driven by population growth,
climate change, economic competition andagriculture evolution, over the last century,
highlight the importance of water efficiency
evaluation. The quantification of the lack or theabundance of international waters, due to changes
in water quality, is applicable by the modeling ofwater under productivity conditions WMUPC. So,
the calculations show the ability to reflect water
quality changes along any river to a valuableamount of water quality.
A shortcoming of this model is that the waterproductivity values do not cover the actual value ofthe nodes in this case study. However, the impact
of different water uses and effects of water qualitychanges has recently become more observable indownstream countries. Therefore, a comprehensive
database needs to be established in order toevaluate and analyze variations of waterproductivity. Furthermore, if the objective isfinding an effective international water allocation
tool, the WMUPC enables to represent analternative mechanism for fulfilling the dispute ofwater sharing among any riparian.

Fig.2 Water lack and abundance in Iraq.
While in the case of high water flows in ahumid zone as Turkey, the minimum agricultural
water demands almost are satisfied and will easily
meet the requirements of the irrigation. Thanks to
dam construction in the Euphrates and Tigris in the
upstream, however, increases the water welfare
and could thus foster water abstraction in that
region as shown in Fig.3 and 4.

6. REFERENCES[1] L. De Stefano, Jacob D. Petersen-Perlman, Eric
A. Sproles, Jim Eynard, Aaron T. Wolf.
Assessment of transboundary river basins forpotential hydro-political tensions, Global
Environmental Change, No. 45, April 2017,
pp. 35-46.
[2] Abdulamir H. Qasim. Impacts du changement
climatique sur les ressources en eau (quantité etqualité) dans les bassins du Tigre et del'Euphrate en Irak. Ph.D. Thesis, University ofPoitiers, France, 2017.
[3] Kucukmehmetoglu M., Sen Z., Özger M.
Coalition possibility of riparian countries via
game theory and fuzzy logic models, 2010,
Water Resour Res., Vol. 46, W12528, pp.1-20.
[4] Oei, P., Siehlow, M. WATER-Model: An
Optimal Allocation of Water Resources in
Turkey, Syria and Iraq, DIW Berlin Discussion
Paper No. 1381, Germany, 2014.

Fig.3 Water lack and abundance in Syria.

Fig.4 Water lack and abundance in Turkey.
Thus, the outcomes of the WMUPC show that473

SEE - Nagoya, Japan, Nov.12-14, 2018

[5] Randolph Barker, David Dawe, Arlene
Inocencio. Economics of Water Productivity inManaging Water for Agriculture. In: Kijne, J.
W. II. Barker, Randolph. III. Molden, D. J.
(Eds) 2003. Water productivity in agriculture:
limits and opportunities for improvement.
CABI international. Wallingford, Oxon, UK.

[6] Gichuki, F., H. Turral and S. Cook. Water
Productivity Assessment: Measuring and
Mapping Methodologies, 2007, Basin Focal
Project Working Paper No. 2. Colombo, Sri
Lanka, CGIAR Challenge Programme on
Water and Food.

474

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

UNDRAINED SHEAR STRENGTH OF SOFT CLAY REINFORCED
WITH SINGLE ENCAPSULATED LIME BOTTOM ASH COLUMN
Muzamir Hasan1,2,3 and Kwan Hui Yee2 and Fat-hi Muhamad1,2 and Masayuki Hyodo4
Centre for Earth Resources Research & Management, University Malaysia Pahang, Lebuhraya Tun Razak
26300 Gambang Kuantan Pahang Malaysia
2
Faculty of Civil Engineering & Earth Resources, University Malaysia Pahang, Lebuhraya Tun Razak
26300 Gambang Kuantan Pahang Malaysia
3
Earth Resources & Sustainability Centre, University Malaysia Pahang, Lebuhraya Tun Razak 26300
Gambang Kuantan Pahang Malaysia
4
Department of Civil and Environmental Engineering, Faculty of Engineering, Yamaguchi University, 2-161 Tokiwadai, Ube-shi, Yamaguchi 755-8611, Japan
1

ABSTRACTSoft clay soils are type of problematic soil that causes bearing capacity failure and excessive settlement, leading
to severe damage to buildings and foundation. In this study, bottom ash is used to replace the natural aggregate
while quicklime is used to increase the bonding between bottom ash particles. This research is aimed to investigate
the role of single encapsulated lime bottom ash column (LBAC) in improving the shear strength by using
laboratory scale model. Kaolin is being used as soil sample while lime bottom ash as the reinforced column andthe column is encapsulated with non-woven geotextile. Laboratory tests are conducted to determine the physicalproperties of bottom ash, kaolin clay, and quicklime sample. Unconfined Compression Test (UCT) also used totest the shear strength of the reinforced kaolin samples. There are 21 kaolin samples being tested in this study andthe dimension of the specimen used is 50mm in diameter and 100mm in height. However, there are two different
types of diameter of single lime bottom ash column being used which are 10mm and 16mm. The heights of thecolumn are 60mm, 80mm and 100mm. The improvement of shear strength of single encapsulated lime bottom ash
column with area replacement ratio of 4.00% (10mm column diameter) and 10.24% (16 mm column diameter) are
43.58%, 50.00%, 49.17% and 38.08%, 42.67%, 32.75% at sample penetration ratio, Hc/Hs of 0.6, 0.8 and 1.0
respectively. It can be concluded that the shear strength of soft clay could be improved by installation of single
encapsulated lime bottom ash column.
Keywords: sand column, sustainable construction, single encapsulated lime bottom ash column

INTRODUCTION
The use of stone columns as a ground
improvement technique in soft cohesive soils isincreasingly being extended to sites with poorer
conditions [3]. This is being achieved with the use ofgeosynthetic reinforcement which acts to provide
additional lateral support to columns, preventing
excessive bulging and column failure. Although theuse of geotextile encasement has been investigatedand implemented on numerous projects, research into
complex reinforced behavior is ongoing. In addition,
the concept of using other geosynthetic materials suchas geogrid for columns, small-scale laboratory testingof model sand columns was undertaken. In
conjunction with this, a numerical modelling study
was undertaken to further understand the interaction
between the geogrid, column material andsurrounding soil. Particular emphasis was placed oncomparing the behavior of partially encased columns
to fully encased columns. To simply modelling, theside wall friction in the cell was considered negligible

Soft clay soils are type of soil that composed ofvery fine particles and can impedes the flow of water.
Clay soils are commonly stiff in dry state but heavy
and sticky when saturated with water. The reduction
in strength and stiffness of soft clays causes bearing
capacity failure and excessive settlement, leading tosevere damage to buildings and foundation [1].
Therefore, deep mixing method is used to improve thepermeability, strength and deformation properties ofthe soil. This method mainly depends on increasing
the stiffness of natural soil by adding a strengthening
admixture material such as lime.
Granular columns are widely used to improve theperformance of weak deposits in order to reduce
foundation settlement and to increase load-bearing
capacity [2]. The performance of granular columns
depends entirely on the characteristics of thesurrounding material.
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SEE - Nagoya, Japan, Nov.12-14, 2018

and no resistance was applied to the model boundary.

Malaysia Pahang. Table 1 shows a list of tests andstandard used

The critical column length is the shortest column
which can carry the ultimate load regardless of
settlement [4]. [5] found from their model study thatthe load carrying capacity of the column increases up
to L/D = 4.1, beyond which there is no increase incolumn capacity. [6] suggested a minimum L/D ratioof 4.5, which is required to develop the full limiting
axial stress on the stone column. [7], [8] reported
from their experimental study that L/D ratio of
minimum 6 is required to develop the full limiting
axial stress on the column. [9] found out from theirmodel study that the critical length to be 4–5 D for
example beyond this length of stone column, no
significant increase in its capacity has been observed.
[10] supports the hypothesis of a critical column
length corresponding to about six column diameters.

Installation of Single Lime Bottom Ash Column
In preparing for the installation of Lime Bottom
Ash Column (LBAC) for the reinforced specimens,
the holes for the installation of LBAC were drilledusing drill bit of respective diameter with thespecimens still inside the mould to prevent it fromexpanding. The lime and bottom ash are installing in
the holes to achieve relative density of 13.31%.
To maintain a uniform density in each LBAC andmaintain the lime at 6%, the mass of bottom ash andlime used to fill the pre-drilled hole had been basedon the volume of pre-drilled hole. By referring to thismethod, the same density of 8.15×10−4g/mm3 hadbeen produced for every specimen in this study

Columns longer than critical length did not show
further increase in load-carrying capacity, however,longer columns may be needed to control thesettlements. Accordingly, rational decisions can betaken to tailor design of stone column installations toachieve maximum performance at optimum cost.
In this study, bottom ash not only used to improve
the soft soil strength as it also can reduce the need toquarry rock, since bottom ash is used as a substitutefor natural crushed rock. In addition, it can reduce theneed to dispose the product to landfill storage. Hence,using this material is more sustainable andenvironmentally friendly and avoids the use of natural
resources such as sand and gravel. However, lime isused as a binder to increase the bonding between thebottom ash which able to enhance the shear strengthof the soft soil. Lastly, the undrained shear strength ofsoft clay reinforced with single encapsulated lime
bottom ash column is determined in order to prove thefeasibility to implement lime bottom ash column inreal construction. Thus, varies type of laboratory tests
need to be conduct based on British Standard (BS) or
the American Society of Testing Material (ASTM).
The purpose of this study is to investigate theundrained strength of soft clay reinforced with single
encapsulated lime bottom ash column.

Figure 1. Arrangement of installed column in clay
specimen
Table 1. A list of tests and standard used
Materials

Tests
HydrometerStandards
BS 1377: Part 2
1990: 9.6

Standard

BS 1377: Part 4

Compaction

1990: 3.3

Falling Head
Permeability
Specific Gravity

ASTM D 2434
BS 1377: Part 2:
1990: 8.3

KaolinMETHODOLOGY
Few tests are conducted toward a small-scalemodel of the bottom ash as granular column andkaolin as the soft clay by adding some lime as binder.
Laboratory tests are conducted to determine thecharacteristics of lime, kaolin and bottom ash basedon British Standard and American Society of Testing
Material (ASTM). The model is 50mm in diameterand 100mm in height. All the experiments are carriedout at Soil and Geotechnical Laboratory of Universiti

Atterberg Limit

BS 1377: Part 2:

Liquid Limit

1990: 4.3

Plastic Limit

BS 1377: Part 2:
1990: 5.3

Lime

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Hydrometer

BS 1377: Part 2
1990: 9.6

SEE - Nagoya, Japan, Nov.12-14, 2018

Specific Gravity

BS 1377: Part 2:

Plastic
Index, 𝑰𝑰𝒑𝒑(%)
Optimum
Moisture
Content,
𝒘𝒘𝒐𝒐𝒐𝒐𝒐𝒐 (%)
MaximumDry
Density,𝝆𝝆𝒅𝒅(𝒎𝒎𝒎𝒎𝒎𝒎)(Mg/𝐦𝐦𝟑𝟑 )1990: 8.3

Atterberg Limit

BS 1377: Part 2:

Liquid Limit

1990: 4.3

Plastic Limit

BS 1377: Part 2:

Standard
Compaction

1990: 5.3
BS 1377: Part 2:

Dry Sieve

Specific Gravity
Bottom Ash

Small
Pycnometer

1990: 9.3
BS 1377: Part 2:

Standard

BS 1377: Part 4:
1990: 3.3

Constant Head
Permeability

Constant Head
Permeability

Standard

BS 1377: Part 4

with Lime

Compaction

1990: 3.3

Unconfined

Encapsulated

(UCT)

20.91

43.00

23.60

1.53

1.11

1.313

2.62

2.26

2.33

-

-

8.96
x𝟏𝟏𝟏𝟏−𝟏𝟏𝟏𝟏
-

-

5.03
x𝟏𝟏𝟏𝟏−𝟑𝟑

The shear strength of all the reinforced specimens
are proved to be higher than the control sample.
Meanwhile, the shear strength able to be improveafter installed the single encapsulate lime bottom ash
column. Table 3 shows the shear strength results andits improvement.

Clay

Compression Test-

Effect of Single Lime Bottom Ash Colum on Shear
StrengthSoft Kaolinwith Single

11

ASTM D 2434

Bottom Ash

Reinforced

CoefficientofPermeability, k (m/sec)
CoefficientofPermeability, k (m/sec)

Falling Head
Permeability

1990: 8.3

Compaction

Specific
Gravity, Gs

10

ASTM D 2166

Lime Bottom

Figure 2 and Figure 3 show the correlation line forsample shear strength and improvement shear
strength of single encapsulated lime bottom ash
column. From Figure 2 the value of correlationcohesion, R2 for diameter 10mm and 16mm are
0.9124 and 0.7443 respectively. Whereas, From
Figure 3 the value of correlation cohesion, R2 fordiameter 10mm and 16mm were 0.9255 and 0.6767
respectively. If the value of correlation cohesion, R2
nearer to 1, thus means the result is more accurate.

Ash Column

RESULTS AND DISCUSSIONS
Physical and Mechanical Characteristics of Kaolin,
Quicklime, and Bottom Ash
The physical properties of kaolin clay, quicklime,
and bottom ash have been summarized in Table 2.
The characteristic of kaolin is nearly same as soft clay
while bottom ash is almost similar to the natural
aggregate like sand and fine gravel. In this study,
quicklime able to increase the bonding between
bottom ash particles based on its fine particle
properties

Table 3. Shear strength results and its improvement

HeightPenetration Ratio,
𝑯𝑯𝒄𝒄 /𝑯𝑯𝒔𝒔

Table 2. Physical and mechanical properties ofkaolin, quicklime, and bottom ash
Test

Soil
Classification

Atterberg
Limit

Parameter

KaolinLime

BottomAsh

AASHTO

A-6

A-7-5

A-1-a
(0)

USCS
(Plasticity
Chart)MIMV-

Plastic
Limit, 𝒘𝒘𝒑𝒑(%)
LiquidLimit, 𝒘𝒘𝑳𝑳
(%)

26
36

72
61

Shear Strength, 𝑺𝑺𝒖𝒖
(kPa)
1

2

3

Average ShearStrength, 𝑺𝑺𝒖𝒖(kPa)

Improveme
nt of Shear
Strength,∆𝑺𝑺𝒖𝒖 (%)

Controlled Sample

0

11.5
9

12.4
3

11.9
8

12.00

-

Single Encapsulated Lime Bottom Ash Column (10mm)

0.6

17.3
3

16.2
8

18.0
7

17.23

43.58

0.8

18.2
7

17.0
8

18.6
6

18.00

50.00

1.0

17.9
3

17.1
0

18.6
6

17.90

49.17

-

477

SEE - Nagoya, Japan, Nov.12-14, 2018

Single Encapsulated Lime Bottom Ash Column (16mm)

0.6

17.4
2

16.7
4

15.5
4

16.57

38.08

0.8

17.0
8

17.5
4

16.7
4

17.12

42.67

1.0

16.3
5

15.9
4

15.5
0

15.93

32.75

Figure 4. Morphology images of lime bottom ash by
SEM at 10μm magnification

Figure 2. Correlation graph of shear strength withheight penetration ratio for single lime bottom ash
column with diameter 10mm and 16mm

Figure 5. Morphology images of lime bottom ash by
SEM at 100μm magnification
CONCLUSIONS
The major focus of this study is to check out whether
there is any improvement on undrained shear strengthof soft kaolin soil after reinforced with single
encapsulated lime bottom ash column with two
different column diameters and different length ofpenetration. Based on laboratory test results analysis,
the following conclusions can be made:Figure 3. Correlation graph of improvement shear
strength with height penetration ratio for single lime
bottom ash column with diameter 10mm and 16mm
Morphological Properties
From the Scanning Electron Microscope (SEM),
the particles of the lime bottom ash were greyish,
spherical and had rough, gritty surface textures. Someof the particles were spherical whereas there are also
popcorn type particles. The surfaces of the particles
are observed to have pores and dusty. The theappearance of the bottom ash particles is porous,
angular and irregular in shape and possesses a roughtexture by using microscope. Figure 4 And Figure 5
show Morphology images of lime bottom ash by
SEM at 10μm and 100 μm magnification. Based on
the figures, quicklime can enhance the bonding
between bottom ash particles

1.

478

Kaolin characterized as MI by referred to Unified
Soil Classification System (USCS) whichindicates that it was medium plasticity silts basedon its liquid limit (36%) and plasticity index(10%). The specific gravity of kaolin is 2.62 andit also classified as clayey soil, A-6, based on
AASHTO classification system. This is because
kaolin clay is well graded and its grain size is in
the range between clay to fine silt. From thecompaction test, the result show that maximum
dry density, ρd(max) for kaolin is 1.53Mg/m3
with the optimum moisture content of 20.91%.
Other than that, the permeability coefficient ofkaolin is 8.96 x 10−12m/s.

SEE - Nagoya, Japan, Nov.12-14, 2018

2

3

Tanjung Bin bottom ash that used in this study
was categorized as A-1-a group which consisting
predominantly of stone fragments or gravel,
either with or without a well-graded binder offine material. The maximum dry density ofbottom ash is 1.313Mg/m3 while its optimum
moisture content is 23.60% based on the result of
the compaction test. Its specific gravity is 2.33.
However, the permeability coefficient of bottom
ash is 5.03 x 10−3m/s which mean it has a gooddrainage characteristic that able to discharge
water.

area replacement ratio of 10.24%, it can improve
the shear strength up to 38.08%, 42.67% and32.75% at sample penetration ratio, Hc/Hs of 0.6,
0.8 and 1.0 respectively. This shows that the
improvement of shear strength does not fully relyon the column penetration ratio.
REFERENCES[1] Sakr et al, 2009. Utilization of Lime for
Stabilizing Soft Clay Soil of high organic content.
Curtin University of Technology: Civil
Engineering, pp.2.
[2] Sivakumar, V., Boyd, J. L., Black, J. A., McNeill,
J. A., Serridge, C. J., Slocombe, B. C., & Bell, A.
L. (2012). Discussion: Effects of granularcolumns in compacted fills. GeotechnicalEngineering - Proceedings of the ICE, 165(4),267–270. https://doi.org/10.1680/geng.11.00065[3] M. LEONI, M. KARSTUNEN and P. A.
VERMEER (2008), Géotechnique 58, No. 3,
215–226.
[4] Hughes, J. M. O. and Withers, N. J. (1974).
Reinforcing of Soft Cohesive Soils with Stone
Columns. Ground Engineering, 7, No. 3, 42–49.
[5] Hughes, J. M. O., Withers, N. J., and Greenwood,
D. A. (1975). A Field Trial of The Reinforcing
Effect of a Stone Column in Soil. Geotechnique,Vol. 25(1), 31–44.
[6] Mitra S, Chattopadhyay BC (1999) Stone
columns and designlimitations. In: Proceedings,
Indian geotechnical confer-ence, Calcutta, India,
pp 201–205[7] McKelvey, D., Sivakumar, V., Bell, A., &Graham, J. (2004). Modelling Vibrated Stone
Columns In Soft Clay. Geotechnical Engineering,Vol. 157, 137 -149.
[8] Black, J., Sivakumar, V., and McKinley, J. D.
(2007). Performance of Clay Samples
Reinforced with Vertical Granular Columns.
Canadian Geotechnics Journal, Vol.44, 89-95.
[9] Samadhiya NK, Maheswari P, Basu P, Kumar
MB (2008) Load-settlement characteristics ofgranular piles with randomlymixed fibres. Indian
Geotech J 38(3):345–354[10] Najjar, S. S., Sadek, S. and Makaroun, T. (2010).
Effect of Sand Columns on the Undrained Load
Response of Soft Clays. Journal of Geotechnicaland Geoenvironmental Engineering, Vol. 136,
No. 9, September 1, 2010. ASCE, 1263–1277.

For quicklime, it characterized as by referred to
the Unified Soil Classification System (USCS).
From the result, it shows that its liquid limit is
71% while its plasticity index is 10% thus
considered as low plasticity silt. Besides that, thespecific gravity of quicklime is 2.26. According
to the AASHTO classification system, this kaolin
to be classified as clayey soil, A-7-5 which
proved that it has moderate plasticity indexes inrelation to liquid limit and may be highly elastic
as well as subject to considerable volume change.
Moreover, the maximum dry density forquicklime is 1.11Mg/m3 with optimum moisture
content 43.00%.

4. Installation of single encapsulated lime bottom
ash column into kaolin soil can enhance the shear
strength of the soft soil. For the result, it showsthat with the installation of single encapsulated
lime bottom ash column of diameter 10mm withpenetration ratio Hc/Hs of 0.6, 0.8 and 1.0, it canincrease the shear strength from 12kPa up to
17.23kPa, 18.00kPa and 17.90kPa respectively.
However, for the single encapsulated lime bottom
ash column of diameter 16mm with penetration
ratio Hc/Hs of 0.6, 0.8 and 1.0, the shear strength
increase from 12kPa up to 16.57kPa, 17.12kPa
and 15.93kPa respectively.
5. In this study, the installation of single
encapsulated lime bottom ash column proved thatit able to improve the shear strength of kaolin soil.
Based on the test conducted, the installation of
10mm diameter of single encapsulated lime
bottom ash column with area replacement ratio of
4% can improve the shear strength of kaolin up to
43.58%, 50.00% and 49.17% at sample
penetration ratio, Hc/Hs of 0.6, 0.8 and 1.0
respectively. However, for the 16mm diameter ofsingle encapsulated lime bottom ash column with479

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

IMPROVEMENT OF ENZYMATIC CATALYSIS IN ORGANICSOLVENTS VIA IMMOBILIZATION ON BIOCHAR
Hidetaka Noritomi1, Jumpei Nishigami1, Nobuyuki Endo2, Satoru Kato1 and Shinsuke Takagi1
Department of Applied Chemistry for Environment, Tokyo Metropolitan University, Japan; 2EEN Co., Ltd.,
Japan

1

ABSTRACT
We have found that the adsorption immobilization of the serine protease α-chymotrypsin (α-CT) onto bamboo
charcoal powder (BCP), which is a kind of biochar, improves the transesterification rate of N-acetyl-L-tyrosine
ethyl ester (N-Ac-Tyr-OEt) with n-butanol (BuOH) in 9 organic solvents. Organic solvents strongly affected thecatalysis of BCP-adsorbed α-CT. The transesterification rate of BCP-adsorbed α-CT was much superior to that offree α-CT in every organic solvent. Especially, the transesterification rate of BCP-adsorbed α-CT was about 760
times higher than that of free α-CT in n-butyl acetate.
Keywords: Biochar, Adsorption, Enzymatic catalysis, Solvent effect

In order to apply biomass materials to enzyme
carriers, we have so far examined the adsorption of
enzymes onto biochar, which is derived from biomass
materials such as forestry residues. We have foundthat enzymes are effectively adsorbed onto biochar[12], [13], and biochar-adsorbed enzymes exhibit thehigh thermal stability in water [14]-[17]. Moreover,
we have reported that the adsorption of enzymes onto
biochar sufficiently improve the enzyme activity inacetonitrile [18], [19].
In our present work, we have assessed how thenature of organic solvents affects the catalysis of
enzymes adsorbed onto biochar in organic solvents.
We have used bovine pancreas α-chymotrypsin (αCT) as a model protein since it is well investigatedregarding its structure, functions, and properties [20].

INTRODUCTION
An enormous amount of greenhouse gas such as
CO2 has recently been emitted from industries, andthereby has caused serious global warming problems[1], [2]. Accordingly, the application of biomass
materials, which are carbon neutral, to energies andfunctional materials is crucial to reduce greenhousegas emissions [3], [4]. However, most of biomass
materials such as forestry residues have hardly beenutilized in the field of functional materials.
Accordingly, the development in the high valueadded application of biomass materials has been
desired to provide the multiple effective utilization
system of biomass materials.
Enzymes are biocatalysts, which exhibit theiroutstanding biological activity under mild conditions,and have widely been used in pharmacy,
biotechnology, and chemical industry [5]-[7]. Typicalapplications of enzymes are biotransformation,biosensor, biofuel cell, and so on. Enzymes are
generally stable in a cell. However, they are graduallydenatured and inactivated under various physical andchemical stresses such as heat, organic solvents, andso on [8]. In order to enhance the stability of enzymes
used in vitro, enzyme immobilization, where enzyme
molecules are attached to solid carriers, has widely
been used [9]-[11]. The main required features of
enzyme carriers are chemical stability, thermal
stability, insolubility under reaction conditions, highaffinity to enzymes, biocompatibility, presence ofreactive functional groups, availability, price,
regeneration, reusability, and so on. When enzymes
are immobilized onto carriers through adsorption, thecatalytic activity, specificity, and stability of enzymes
are influenced by the nature of carriers. Accordingly,
the performance of enzymes can be enhanced by
selecting an appropriate carrier.

MATERIALS AND METHODS
Materials
α-Chymotrypsin (EC 3.4.21.1 from bovinepancreas) (type II, 52 units/mg solid)( α-CT) was
purchased from Sigma-Aldrich Co. (St. Louis, USA).
N-Acetyl-L-tyrosine ethyl ester (N-Ac-Tyr-OEt) andN-acetyl-L-tyrosine (N-Ac-Tyr-OH) were also from
Sigma-Aldrich Co. (St. Louis, USA). Organic
solvents used in the present work were of guaranteed
grade, and were obtained from Kanto Chemical Co.
(Tokyo, Japan). All organic solvents were dried bystoring them over dry 0.3 nm molecular sieves (Wako
Chemical Co.) for at least 24 h prior to use.
Preparation of Bamboo Charcoal Powder
To prepare bamboo charcoal as a biochar, under
nitrogen atmosphere, bamboo waste was dried at
180 ℃ for 2 h, was pyrolyzed at 450 ℃ for 2 h, was480

SEE - Nagoya, Japan, Nov.12-14, 2018

adsorption from the amount of α-CT in the aqueous
solution before adsorption. The amount of α-CT was
measured at 280 nm by UV/vis spectrophotometer(UV-1800, Shimadzu Co. Ltd.).
Measurement of Catalytic Activity of α Chymotrypsin
The standard reaction for transesterification was
carried out as follows: Three milliliter of an organic
solvent containing 0.2%(v/v) water, 10 mM N-AcTyr-OEt, 1000 mM n-butanol, 1 mM acetanilide, andfree α-CT or BCP-adsorbed α-CT (30 μM) was placedin a 4 mL screw-cap vial, and was incubated at 120
rpm and 25 oC. The amounts of the reaction
components were periodically determined with
HPLC (Shimadzu LC-10A) (Shimadzu Co., Kyoto,
Japan) using a TSK-GEL ODS-80TM column (Tosoh
Co., Tokyo, Japan) eluted with water-acetonitrile (6:4
by volume) at 0.5 mL/min with detection at 270 nm.
Acetanilide was used as an internal standard.

Fig. 1 Pore size distribution of bamboo charcoal
powder (BCP).
carbonized at 350 ℃ for 3 h, and then was cooled at
100 ℃ for 1 h by pyrolyzer (EE21 Pyrolyzer, EEN
Co. Ltd., Japan) [19]. Bamboo charcoal powder(BCP) was obtained by grinding the resultant bamboo
charcoal with jet mill (100AS, Fuji Sangyo Co. Ltd.,
Japan).

Measurement of Fourier Transform Infrared(FTIR) Spectroscopy
FTIR measurements of free α-CT and BCPadsorbed α-CT were carried out using a Jasco FT/IR
spectrometer model FT/IR-4100. A KBr pellet
containing 0.5 mg of free α-CT or BCP-adsorbed αCT powder per 100 mg of KBr was prepared, andthe measurements were performed using 512 scans
under 4.0 cm-1 resolution.

Characterization of Bamboo Charcoal Powder
The SEM micrograph was obtained using ascanning electron microscope (JSM-7500FA, JEOL,Japan) operating at 15 kV. The sample for SEM was
prepared on a carbon tape without vapor deposition.
All samples were outgassed at 300oC for 8 hprior to the nitrogen adsorption measurements. The
specific surface area of BCP was obtained using a
micropore system (BELSORP-mini II, BEL
JAPAN, INC.), and the pore size distribution was
calculated with the use of the micropore analysis
method (MP method).
The surface of BCP was analyzed by X-ray
photoelectron spectroscopy (XPS) (Quantum-2000,
ULVAC-PHI Co. Ltd.) operating at an x-ray beam
size of 100 μm.

RESULTS AND DISCUSSION
Characterization of Bamboo Charcoal Powder
Bamboo charcoal has been prepared bypyrolyzing bamboo waste at low temperatures under
nitrogen atmosphere to produce functional groups,
which were used as a binding site for the adsorptionof enzymes. The resultant bamboo charcoal was
grinded by jet mill to obtain the fine bamboo charcoal
powder (BCP), whose diameter was about 7 μm.
The surface area of BCP was 294 m2/g, and was
similar to that of a conventional wood charcoal.
Figure 1 shows the pore size distribution of BCP. The
range of pore diameter was mainly from 0.6 nm to 1.2
nm, and was much smaller than the size of α-CT since
the size of α-CT is 5.1 x 4.0 x 4.0 nm [20]. This result
indicates that most of enzymes is adsorbed onto thesurface of BCP in direct contact with bulk organic
solvents during the enzymatic reaction in organic
solvents.
Figure 2 shows the scanning electron
micrograph of BCP. The surface of BCP looked likesmooth. As mentioned above, since the pore size of
BCP was the order of micropores, the pores on the

Adsorption of α-Chymotrypsin onto Bamboo
Charcoal Powder
As a typical procedure, 5 mL of 0.01 M
phosphate buffer solution at pH 7 containing 300 μM
α-CT and 3 g/L BCP was placed in a 10-mL test tube
with a screw cup, and was incubated at 25 ℃ and 120
rpm for 24 h. After adsorption, the mixture wasfiltrated with a membrane filter (pore size: 0.1 μm,
Millipore Co. Ltd.). The amount of α-CT adsorbed
onto BCP was calculated by subtracting the amountof α-CT included in the supernatant liquid after
481

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 3 Reaction scheme of α-CT-catalyzed
transesterification of N-acetyl-L-tyrosine ethyl
ester (N-Ac-Tyr-OEt) with n-butanol (BuOH)
to N-acetyl-L-tyrosine butyl ester (N-Ac-TyrOBu) and competing hydrolysis (N-Ac-TyrOH).

Fig. 2 SEM image of bamboo charcoal
powder (BCP).
Table 1 Waveform separation of C1s peaks.
Peak number

Band

Binding energy (eV)Atomic percentage (%)

1

C-C, C-H

284.78

63.87

2

C-O

286.12

10.93

3

O-C-O

287.1

3.29

4

C=O

288.48

2.57

5

COOH

289.480.03

Table 2 shows the ratio of the absorbance at 1650 cm1
to the absorbance at 1630 cm-1 (ABS1650/ABS1630) of
free α-CT and BCP-adsorbed α-CT after they were
immersed in organic solvents for 24 hr. The bands at
ca. 1650 and 1630 cm-1 are respectively assignable toα-helix and intramolecular β-sheet, which aresecondary structures of enzymes [23]. Before thesolvent
immersion,
theabsorbanceratio(ABS1650/ABS1630) of BCP-adsorbed α-CT was
greater than that of free α-CT. The absorbance ratio(ABS1650/ABS1630) of BCP-adsorbed α-CT after thesolvent immersion was different from that before thesolvent immersion. Likewise, the absorbance ratio(ABS1650/ABS1630) of free α-CT was altered by thesolvent immersion. Moreover, the absorbance ratio(ABS1650/ABS1630) of BCP-adsorbed α-CT after
acetonitrile immersion was almost similar to that after
n-octane immersion, while the absorbance ratio(ABS1650/ABS1630) of free α-CT after acetonitrile
immersion was smaller than that after n-octane
immersion. The α-helical structure of α-CT molecule
is more changeable than β-sheet, since the β-sheet
structure is the main backbone of α-CT molecule[20]. Consequently, the higher absorbance ratio
corresponds to the higher secondary structure. Those
results indicate that the conformation of BCPadsorbed α-CT is hardly influenced by the nature ofsolvents, compared to the case of free α-CT.

Table 2 Ratio of the absorbance at 1650 cm-1 to the absorbance at 1630 cm-1
(ABS1650/ABS1630) of free α-CT and BCP-adsorbed α-CT provided by the
FTIR measurement after the solvent immersion.
Solvent

ABS1650/ABS1630 (-)
Free α-CT

BCP-adsorbed α-CT

None

1.14

1.47

Acetonitrile

1.15

1.51

n-Octane

1.20

1.53

surface of BCP might not be observed under themagnification measured in the present work.
The chemical property of the surface of BCP has
been measured by X-ray photoelectron spectroscopy(XPS). The elemental composition and binding statefrom the surface to 3~5 nm depth can be detected by
XPS. As shown in Table 1, aromatics, aliphatics,
single C-O bond (alcohol, ether, phenol, C-OH of anenol-keto group), double bonded carbon oxygengroups, carbonyl, quinone, and carboxyl groups weremainly detected by waveform separation of C1 peaksof narrow scan spectrum.
The amount of α-CT adsorbed onto BCP was 9.8μmol/g. The charge of α-CT was positive in the buffer
solution at pH 7 since the isoelectric point of α-CT is
9.1 [20]. On the other hand, the ζ-potential of BCP
was negative at pH 7 in the buffer solution at pH 7[12]. These indicate that the electrostatic force
between the positively-charged α-CT molecules andthe negatively-charged surface of BCP mainly
contributes to the adsorption of α-CT onto BCP.

Solvent Dependence
Adsorbed α-CTof

Catalysis

of

BCP-

Figure 3 shows the α-CT -catalyzed reaction
scheme [24], [25]. When N-acetyl-L-tyrosine ethyl
ester (N-Ac-Tyr-OEt) is used as a substrate, theenzymatic reaction proceeds by the formation of
enzyme intermediates between the active site of
enzymes and the substrate. In water α-CT catalyzes
the hydrolysis reaction of N-acetyl-L-tyrosine ethyl

Solvent Dependence of Conformation of BCPAdsorbed α-CT
There have been some reports that the native
conformation of enzymes may be altered whenenzymes are immersed in organic solvents [21], [22].
482SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 4 Solvent dependence of transesterification
catalyzed by free α-CT (A) and BCP-adsorbed αCT (B). Free or BCP-adsorbed α-CT was placedin the organic solvent containing 0.2%(v/v)
water, 10 mM N-Ac-Tyr-OEt, 1000 mM BuOH,
and 1 mM acetanilide, and the resulting mixture
was shaken at 120 rpm and 25 oC.
ester (N-Ac-Tyr-OEt) with water to give N-acetyl-Ltyrosine (N-Ac-Tyr-OH). On the other hand, inorganic solvents α-CT mainly catalyzes thetransesterification reaction of N-acetyl-L-tyrosine
ethyl ester (N-Ac-Tyr-OEt) with another substrate, nbutanol (BuOH) to produce N-acetyl-L-tyrosine butyl
ester (N-Ac-Tyr-OBu). Thus α-CT, which ishydrolase, can beneficially catalyze the synthetic
reaction in organic solvents, although expensive
energy substances such as adenosine triphosphate(ATP) are needed to take place conventional synthetic
reactions by enzymes in water [24].
The catalysis of free α-CT and BCP-adsorbed αCT was markedly dependent upon the nature oforganic solvents as shown in Fig. 4. The catalytic
activity of BCP-adsorbed α-CT was much superior tothat of free α-CT in organic solvents. The
transesterification rate of free α-CT in n-octane
exhibited 813-fold, compared to that in n-butyl
acetate, while the transesterification rate of BCPadsorbed α-CT in n-octane was 1.3 times greater thanthat in n-butyl acetate.
Figure 5 shows the relation between the catalytic
activity and the hydrophobicity defined as log P
where P is a partition coefficient for a given solvent
between n-octanol and water [26]. The
transesterification rate of free α-CT and BCPadsorbed α-CT increased with an increase in theFig. 5 Relationship of log P of organic solventswith transesterification rate (A) or hydrolysis
rate (B) of free α-CT and BCP-adsorbed α-CT.
hydrophobicity of organic solvents. Likewise, thehydrolysis rate of free α-CT and BCP-adsorbed α-CTtended to increase with increasing the hydrophobicity
of organic solvents. The hydrophobicity contributes
to the partition of water between enzyme molecules
and the bulk organic phase in reaction systems [27],[28]. When a certain amount of water is added into
organic solvents, the amount of water associated withenzyme molecules increases in an increase in thehydrophobicity of organic solvents. Thereby, theflexibility of enzyme molecules, which is essential forcatalytic activity, is enhanced by the hydration of
enzyme molecules, and then the catalytic activity
increases. On the other hand, hydrolysis reaction is
promoted by water molecules around enzymes. As
483

SEE - Nagoya, Japan, Nov.12-14, 2018

shown in Fig.5, the transesterification rate of BCPadsorbed α-CT was much superior to that of free αCT at the low hydrophobicity. For instance, thetransesterification rate of BCP-adsorbed α-CT was
about 760 times higher than that of free α-CT in nbutyl acetate (log P = 1.7). Moreover, BCP-adsorbed
α-CT depicted the high transesterification rate inacetone and acetonitrile, compared to the case of free
α-CT. An enzymatic reaction in hydrophilic solvents
has the advantage of the solubility of a variety of
substrates including drug derivatives, which arepoorly soluble in hydrophobic solvents [29]. As
discussed above, since the native conformation of
BCP-adsorbed α-CT was maintained in hydrophilicorganic solvents, BCP-adsorbed α-CT could exhibit
the high catalytic activity, compared to the case of
free α-CT. On the other hand, no correlation between
the catalytic activity and the other parameter (e.g.
dielectric constant, hydrogen bonding parameter,solubility parameter, and viscosity) was shown.

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[13] Noritomi H, Hishinuma K, Kurihara S,
Nishigami J, Takemoto T, Endo N, Kato S,“Adsorption of α-chymotrypsin on plantbiomass charcoal”, J. Surface Eng. Materials
Adv. Technol., Vol. 3, 2013, pp. 269-274.
[14] Noritomi H, Kai R, Iwai D, Tanaka H, Kamila
R, Tanaka M, Muneki K, Kato S, “Increase inthermal stability of proteins adsorbed on
biomass charcoal powder prepared from plantbiomass wastes”, J. Biomedical Sci. Eng., Vol. 4,
2011, pp. 692-698.
[15] Noritomi H, Ishiyama R, Kai R, Iwai D, Tanaka
M, Kato S, “Immobilization of lysozyme on
biomass charcoal powder derived from plantbiomass
wastes”,
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onto biomass charcoal powder”, J. Biomaterials
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[17] Noritomi H, Kurihara S, Endo N, Kato S,
Uchiyama K, “Effect of adsorption condition on
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CONCLUSION
We have demonstrated that the nature of organic
solvents affects the catalysis of free α-CT and BCPadsorbed α-CT. BCP-adsorbed α-CT exhibited thehigh catalytic activity, compared to the case of free αCT in organic solvents. Especially, thetransesterification rate of BCP-adsorbed α-CT wasmuch superior to that of free α-CT in hydrophilicorganic solvents. The native conformation of BCPadsorbed α-CT did not change with the nature oforganic solvents, while that of free α-CT changed tosome extent.
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4th Int. Conf. on Science, Engineering & Environment ( SEE) ,Nagoya, Japan, Nov. 12-14, 2018, ISBN: 978-4-909106018 C3051

PROPERTIES OF LIGHTWEIGHT AERATED GEOPOLYMERSYNTHESIS FROM HIGH-CALCIUM FLY ASH AND ALUMINIUM
POWDER
Charoenchai Ridtirud1 and Prinya Chindaprasirt 2
Dept. of Civil Engineering, Faculty of Engineering, Rajamangala University of Technology Isan Khon
Kaen Campus, Khon Kaen, 40000, Thailand; 2 Sustainable Infrastructure Research and Development
Center, Dept. of Civil Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002,
Thailand1

ABSTRACTIn the present work, efforts to decrease unit weighs of the geopolymer mortar around 2,400 kilograms per cubic
meter to be lightweight aerated geopolymer which density lower than 1,800 kilograms per cubic meter and study
the properties of lightweight aerated geopolymer based on binders composed of high calcium fly ash, andaluminium powder was studied. Compressive strengths and densities of lightweight geopolymers with aluminium
powder contents of 0-0.20%wt, NaOH concentrations of 7.5-12.5 molars, liquid to fly ash ratios of 0.45-0.65,
Na2SiO3 to NaOH ratios of 0.33-1.5, sand to fly ash ratio of 0.6-1.4, curing temperatures of 25-100 degree Celsius,
and curing period of 1-24 hours. were tested. In addition, SEM and ultrasonic pulse velocity of lightweight aerated
geopolymer were determined. Results showed that the lightweight aerated geopolymer high calcium fly ash andaluminium powder with the 28-day compressive strength of 1.2-12.6 MPa and densities of 770-1,560 kilogram
per cubic meter, with satisfactory strength could be made.
Keywords Geopolymer, High Calcium fly ash, Aluminium powder, Lightweight aerated Geopolymer, Curing.

INTRODUCTION

Normal-weight concrete~2400

The unit weight of normal concrete is 2,300 2,500 kg/m3 which contributes a large dead load on
the building design. Lightweight concrete as shownin Table 1 has thus been invented to reduce the unit
weight and in effect reduce the dead weight of thestructure. Lightweight concrete with unit weight lessthan 1,800 kg/m3 [1] but still maintains the requiredcompressive strength for various tasks. For example,
lightweight structural concrete is defined as concretewith compressive strength more than 17.0 MPa and a
28- day air-dried unit weight not exceeding 1,850
kg/m3 [2]. Special structural lightweight concretewith a density of 1,725 kg/m3 and maximum
compressive strength of 60.0 MPa has been reported[3]. Lightweight concrete can be used in roof decks
and floors or lightweight concrete masonry block.

Heavyweight concrete>3200

Lightweight can be divided into three categories.
The first type is no-fine concrete (NFC) consisting of
cement, coarse aggregate, and water with no sand.
The cement paste is coated around the coarse
aggregate and provide point-to-point contact to leave
interstitial voids. The second type is lightweightaggregate consisting of both coarse and finelightweight aggregate for producing lesser unit
weight concrete. Lightweight aggregates were drawn
from 2 sources viz., natural materials such as pumicestone and burnt clay, and synthetic materials such asfoam and plastic. The last type is aerated and foamed
concrete with voids in the hardened cement paste or
mortar matrix causing low-density. This type ofconcrete can be divided into two main types; foam
concrete and aerated concrete. Foam concrete is
obtained by mixing cement paste or mortar withstabilized foam. After hardening, the foam cells form
concrete of a cellular structure [4]. Foam filling is
divided into two processes; the first drawing foamfrom foam machine and injecting into concrete formixing and second filling foaming agent into mortar

Table 1 Classification of concrete in accordance withunit weight [1]Unit Weight(kg/m3)
Classification
Ultra-lightweight concrete<1200

Lightweight concrete

1200 < UW < 1800
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composition of 64.3% of SiO2+Al2O3+Fe2O3 and
23% CaO indicate that it is a high calcium fly ash
according to ASTM C 618 [18]. From the XRD
analysis, it consists mainly of amorphous phase withsome peaks of crystalline phases of magnetite,magnesioferrite, dachiardite, and calcium aluminumoxide as shown in Fig. 1. This lot of fly ash was rather
fine with the Blaine fineness of 5,100 cm2/g. The fly
ash particles are spherical with a smooth surface asshown in Fig. 2. The aluminium powder with theminimum assay of 93.0 % is irregular in shape asshown in Fig.3. River sand passed sieve #50 (300 um)
and retained on sieve #100 (150um), with basic
properties as shown in Table 2 was used. The 7.5, 10,
and 12.5 molars (M) NaOH solutions and sodium
silicate (Na2SiO3) solution with 15.32% Na2O,
32.87% SiO2, and 51.8% water were used as alkali
activators.

admixture then mixing by the high shear mixer.
Aerated concrete mostly related with this study since
aerated or gas concrete can be mixed with or without
aggregates which fizz within concrete by a chemical
reaction between hydrate calcium oxide andaluminium following equation (1).
2Al+3Ca(OH)2+6H2O = 3CaO.Al2O3.6H2O+3H2 (1)However to obtain good quality aerated concrete, theproducts need autoclaving at a temperature of 175°C
and a pressure of 8 atm [4]. The manufacturing thus
requires high energy and also involves high budget in
the assembly line.
However, the essential material for autoclaved
aerated concrete is Portland cement which constitutes
the cost and environmental considerations. The
production of Portland cement in 2014 was around
4.3 billion tons [5] The production of 1 ton of cement
produces nearly 1 ton of CO2 emission [6].
Geopolymer is an alternative binder with lower
carbon dioxide emission than Portland cement withmany similar or better qualities such as heat-resistant,high performance and chemical-resistant [6]. Besides
good quality, a number of recycled waste materials
can be used for producing geopolymer [7] [8] [9] with
the implication that it is liable to be significant
cementing material in the future. It is synthesizedusing starting material rich in silica and alumina andactivated with a high alkali solution at normal room
temperature or higher temperatures of 40-80 oC [10][11].
In the alkaline environment of geopolymer,
aluminium powder can react and form hydrogen [12][13]. The reaction between NaOH and aluminium isused to produce lightweight aerated geopolymer [14][15] [16]. The present paper aims to produce
lightweight aerated high calcium fly ash-based
geopolymer mortars using aluminium powders. The
density, compressive strength, microstructure andspatial distribution of void were studied. With thedifferent amount of aluminium powder, NaOH
concentration, liquid/fly ash ratio, Na2SiO3/NaOH
ratio, sand/fly ash ratio, various curing temperaturesand curing periods.

D

0
A

D
C D
D

0

D

N
N

A

0
15

20

25

30

35

40

45

50

55

2-Theta

Fig. 1 XRD patterns of fly ash. A-Magnetite:
Fe3O4;C-Magnesioferrite:
Fe2MgO4;DDachiardite:Na1.1K.7Ca1.7Al5.2Si18.8O48(H2O)12.7; N-Calcium Aluminum Oxide:
CaAl2O4.

EXPERIMENTAL PROGRAM
Fig. 2 SEM micrograph of fly ash powder

Materials
The fly ash from Mae Moh power station in thenorth of Thailand was used as a starting material withbasic qualities as shown in Table 2 and the chemicalcomposition analyzed by X-ray fluorescence (XRF)
technique as shown in Table 3. The chemical

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were summarized in Table 4.

Materials

Fly ashSand

Specific gravity
Fineness by Blaine airpermeability (cm2/g)
Fineness modulus

2.49

-

5,166.00-

Table 4 Weight ratios of geopolymer lightweightmixes
Variant
Unit
Series
%AL 0.0(A),0.05(B),0.1(F),0.15(J),0.2(K)
7.5(E),10(F),12.5(G)NHM
0.45, 0.55(F),0.65
LA
3/2,3/3,2/3(F),1/3
SH
0.6(H),0.8,1.0(F),1.2,1.4(D)SAo
25(I),40(F),60,80,100('C)
CTC
1,3,6,12,24(F)
hr.
TC
DA
3,7,14,28
Day
Note:
AL: Percent of Aluminium powder by weight of fly
ash, NH: NaOH concentration, LA: Liquidalkaline/ash ratio, SH: Sodium silicate/NaOH ratio,
SA: Sand/ash ratio, CT: Curing temperature, CP:curing period, DA: Age of sample

-

1.00

Details of mixing

Density (kg/m3)

-

2.60

Water absorption (%)

-

3.63

Fig. 3 SEM micrograph of aluminium metal fine
powderTable 2 Physical properties of materials

The mixing process began with mixing fly ash andsodium hydroxide solution for three minutes. After
that, sand was added, and mixing was continued forminutes. Sodium silicate and aluminium powder werethen added and mixed for another 3 minutes. The
fresh mortar was placed into 50 mm cube molds. The
samples were left to expand for 30 minutes andleveled off the excess. The samples were left in acontrolled 25 °C room for 24 hr. Finally, thespecimens were demolded and wrapped with plastic
sheet and stored in a 25°C and 50% RH controlled
room.

Table 3 Chemical composition of Fly Ash (by weight)
Chemical composition Content (wt. %)
30.58
SiO2
22.81
CaO
17.10
Al2O3
16.60
Fe2O3
5.64
SO3
2.24
MgO
2.21
K2O
1.47
Na2O
0.53
TiO2
0.21
P2O5
0.15
BaO
0.14
SrO
0.12
MnO
L.O.I.
0.20

Details of test
The unit weight of aerated geopolymers wasdetermined as described in ASTM C 138/C138M-14[17]. The compressive strength was tested after theunit weight determination in accordance with ASTM
C109/C109M-13 [18]. The report results are theaverage of three samples. The test of ultrasonic pulse
velocity (UPV) was done in accordance with ASTM
C597 [19]. The microstructure of sample was studied
with SEM.

Mix proportion
Mix compositions
From the preliminary test, a mix with NaOH
concentration 10 molar, liquid to ash ratio (L/A) of
0.55, sodium silicate/ sodium hydroxy ratio (NS/NH)of 1.5, sand/ash ratio (S/A) of 1, curing temperatureof 40 C, curing period of 24 hr. and test age of 28days
was used as the standard mix. Eight series of mixes

RESULTS AND DISCUSSIONS
Fig.4 showed that Physical description oflightweight geopolymer when sample gets a hard
status that clearly when add more aluminium powder
there was more pore on the sample surface.
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Fig.6 SEM of sample A, B, F and J Order from left toright and top to bottom, respectively.
Fig.

4

Physical description of lightweightgeopolymer
Aluminium powder contents (Series AL)

NaOH Concentration (Series NH)
The results of the effects of NaOH solution
concentrations on density and compressive strengthsof lightweight aerated geopolymer are shown in Fig.
7. The increase in NaOH concentration resulted in the
reduction in density and compressive strength. For
normal high calcium fly ash geopolymer, the increasein NaOH concentration enhanced the dissolution of
fly ash [20], but the very high NaOH concentration
resulted in the increased viscosity of the mix and thepolycondensation was hindered [21]. The NaOH
concentration for optimum strength is around 10 M.
For the system with aluminium powder; the low 7.5
M NaOH resulted in high density and high strength
mixture. The relatively high density was a result of
the formation of a low amount of bubble. At low
NaOH concentration, the setting time of geopolymer
was rather fast due to the high calcium ion content.
The fast setting characteristic resulted in the
stiffening of the matrix and thus hindered theformation of a bubble. For the mix with high NaOH
concentrations of 10 and 12.5 M, the leaching out ofcalcium ions was suppressed and the setting time waslengthened. The matrix was thus less stiff than thatwith low 7.5 M NaOH mix and the formation of the
bubble could continue resulting in the lower density
geopolymer and lower strength as well. Afterconsidered SEM Fig.8 found that the texture ofsample E had most density but in sample G, thesurface of fly ash able to react but not much in density
like sample E and F

The results of density and compressive strength oflightweight aerated geopolymers with various
aluminium powder contents are shown in Fig. 5. The
density and compressive strength decreased with theincreasing aluminium powder contents as expected.
The density of geopolymer was in the range of 7501,950 kg/m3 with the corresponding strength range of
1.20-3.70 MPa. The 28-day compressive strength ofsamples with aluminium powder contents of 0, 0.05,
0.10, 0.15, and 2.0 % were 3.71, 2.84, 2.35, 1.73, and1.22 MPa, respectively. The increase in aluminium
powder contents increases the air bubbles [15] andthus reduce the strength of the sample which accord
with SEM analysis in Fig.6. Shows structure
deteriorated when more bubbles were added.

Fig. 5 Compressive strength and density at 7 and 28
days of lightweight geopolymer at various
aluminium powder contents (Series AL)

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Fig. 7 Compressive strength and density at 7 and 28
days of lightweight geopolymer at various
NaOH Concentration (Series NH)

Fig. 9 Compressive strength and density at 7 and 28
days of lightweight geopolymer at various
Liquid to Fly Ash Ratio (Series LA)
Na2SiO3 to NaOH (Series SH)
The result found that Na2SiO3 to NaOH
plentifully affected to compressive strength anddensity. Even though 28-day optimum compressive
strength that had 45 MPa was obtained with Na2SiO3
to NaOH ratios of 1.00 but density rate was over than
1,800kg/m3 and not regarded as lightweight aerated
concrete. If consider in density, we might realize that
Na2SiO3 to NaOH ratios reducing will cause lower
viscosity since sodium silicate was more viscous thansodium hydroxide. Therefore, Na2SiO3 can keep more
air bubbles [10] when Na2SiO3 to NaOH ratios
decreased which showed in Fig.10, Na2SiO3 to NaOH
ratios of 1/3, found that compressive strength was
reduced since the decreasing in strength in this rangeof Na2SiO3 to NaOH ratios was due to the silica
content of mixture reducing [22]. Moreover, high
NaOH did not cause higher SiO2 and Al2O3 leaching[20] since SiO2 and Al2O3 in Fly ash are limited but
NaOH solution exceed will reduce compressive
strength rate. A similar trend of the result wasreported for the normal weight high calcium fly ash
based- geopolymer mortars. The compressive
strengths of mortars with high Na2SiO3 to NaOH
ratios of 1.5 and 3.0 were reduced compared to thatwith Na2SiO3 to NaOH ratios of 1.0 [11] over OH
filling will fizz a large number of air bubbles andreduce density rate [13].

Fig.8 SEM of sample E and G Order from left to rightand top to bottom, respectively.
Liquid alkaline to fly ash ratio (Series LA)
The results of density and compressive strengthof lightweight aerated geopolymer with various liquidalkaline to fly ash ratios are shown in Fig. 9. The mix
with L/A ratio of 0.55 had the lowest density of 1,100
kg/ m3 and lowest compressive strength of 4. 6 MPa.
At low L/ A ratio of 0. 45, the workability of the
mixture was low due to the low liquid in the mix. The
formation of the bubble was hindered in this case as
the paste was too stiff resulting in high density andslightly high strength geopolymer. Increase in theliquid portion to L/ A ratio of 0. 55 resulted in a
mixture with adequate workability which allowed the
bubble to form and resulted in the geopolymer withrequired low density. Further increase in the liquid
portion to L/ A ratio of 0. 65 resulted in a highworkability mix with low ability to retain the formedgas resulted in a high- density geopolymer. It is thus
very important to use the proper amount of liquid toash ratio to obtain an optimum mix with required low
density with adequate strength.

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Fig. 11 Compressive strength and density at 7 and 28
days of lightweight geopolymer at various
Sand to Fly ash ratio (Series SA)

Fig.12 SEM of sample D and H Order from left toright, respectively.

Fig. 10 Compressive strength and density at 7 and 28
days of lightweight geopolymer at various
Na2SiO3 to NaOH (Series SH)

Curing temperature (Series CT)

Sand to Fly ash ratio (Series SA)

The results of compressive strength and density oflightweight aerated geopolymer with various curing
temperatures are shown in Fig.13. The optimum
curing temperatures was 60 °C and the strength of 3.3
MPa. An increase in curing temperatures from 25 °C
to 60 °C resulted to develop on compressive strength
accorded with several research works that studied
about an increase in temperature of curing to 60 °C
enhanced the geopolymerization and increased thecompressive strength [11], [23], [24], [25]. Even
though temperature curing increasing is the factor that
support geopolymerization method but when thetemperature reaches over 80 °C, the solution willrapidly evaporate, the reaction will not extremely
occur, the sample will be dry, shrink and become to
micro crack sample. In term of SEM analysis thatshowed in Fig.14, the compressive strength wasplentifully reduced from temperature curing at 60 °C
was 3.3 MPa to 1.8MPa at 80 °C decreasing as 45 %in order that temperature curing increasing will
reduce compressive strength as well. Moreover, thetemperature that higher than 80 °C restrained thedevelopment of compressive strength and thesample’s compressive strength tends to be reduced
based on the further ages. However, an increasing of
curing temperatures reduced density rate but notmuch effective since the high-temperature curing
caused watered solution lost their moistness morethan curing at a low temperature, so the sample
weight was decreased as well [11], [26]. Aninteresting aspect of lightweight aerated geopolymer
production is; autoclave treatment is not important for
producing, on the other hand, OPC concrete
production still needs autoclave [27], [28] that will
reduce the process, energy and production cost.

The results of the effects of sand to fly ash ratioon compressive strength and density of lightweightaerated geopolymer are shown in Fig. 11. Sand to Fly
ash ratio had an influence on the strength ofgeopolymer but the influence was rather small. The
result showed that after filled sand into thecompressive composition strength and density oflightweight aerated geopolymer rate will increase
because of sand replacing air bubbles. Afterconsidering the results, sand to fly ash ratio more than
1 will not be beneficial to compressive strength andincrease the sample density rate. From SEM Fig.12.
found that texture paste of the sample H had highest
homogeneous since air bubbles not kept within thesample. If we only applied the result from SEM, wemight not explain the result of the low compressive
strength of sample H, but after explained by SEM
displays, the results that accorded with compressive
strength were clearly showed. The sample that had
low rate of sand to fly ash ratio could not keep air
bubbles like sample H since most of the large bubbles
will rise up because sand is the factor that increases
sticky rate for fresh lightweight aerated geopolymer
and compresses the bubbles in order to stop their
floating as showed in Fig.6 and 12 (D, F, and H).

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curing period (Series CP)
Fig.16 showed that when the sample aged
compressive strength will continuously develop anddensity rate of the sample had a little change withaverage density rate as 1,058 kg/m3. However, in thistest the sample was cured with 40 °C and the result
accorded with Fernández-Jiménez 1999 research thatstudied about curing temperature of 45 °C [33] but
cannot find out that lightweight aerated geopolymer
will develop their compressive strength further agedin any cases. Since the relation of lightweight aerated
geopolymer compressive strength development has toconsider the main factor like curing temperature.
According to the research, curing in high temperature
will be beneficial to early compressive strength but it
will reduce along with its ages [30] Moreover, if
curing with relative humidity> 90%, the sample’scompressive strength will continuously develop [31].

Fig. 13 Compressive strength and density at 7 and 28
days of lightweight geopolymer at various
curing temperature (Series CT)

Fig.14 SEM of sample C and I Order from left toright, respectively.
Curing period (Series CP) and Age of the sample(Series DA)
The results of compressive strength and density oflightweight aerated geopolymer with various curing
period are shown in Fig.15. Density had changed
without significance with 1,055 Kg/m3 as its rate
signified that the curing period could not affect to air
bubbles fizzing or the sample evaporation when cured
with 40 °C. However, an increasing curing period will
increase compressive strength rate. The results
accorded with Görhan 2014 research which described,
when curing temperature of 65°C and increasing
curing period from 2, 5 and 24 hours geopolymer thatcompounded with NaOH 9 M’s compressive strength
will increase to 13, 16 and 21 MPa, respectively. [29].

Fig. 16 Compressive strength and density oflightweight geopolymer age (DA)CONCLUSION
Based on the obtained data, the following
conclusions can be drawn.
1. Suitable Liquid to Fly Ash Ratio for lightweightaerated geopolymer production, lowest density
should be 0.55.
2. An aluminium powder increasing increased H2
bubbles and reduced sample’s density and when thenumbers of void increased compressive strength andits development will be reduced.
3. An increasing of NaOH Concentration make
rapid and aggressive H2 bubbles on the other handhigh increasing NaOH Concentration generate large
air bubbles but density not much reduced.
4. Na2SiO3 to NaOH have a major effect on theviscous of fresh specimens If there are high quantities
the specimens will give a highly viscous, and also
affect the setting time, therefore, air bubbles

Fig. 15 Compressive strength and density at 7 and 28
days of lightweight geopolymer at various
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maintaining has to relate with setting time if setting
time is late, the bubbles will rise up to the surface anddensity rate will increase.
5. Sand to Fly ash ratio not much affect to density
rate and found that the suitable Sand to Fly ash ratiois 1.06. Curing temperature and curing period gave alittle effect to density rate but in compressive
strength, an increasing of curing temperature during
25- 60 °C will increase compressive strength on theother hand if curing with over 60 °C will harm tocompressive strength and its development tends to be
reduced.
7. The results showed that the lightweight aerated
geopolymer High- Ca fly ash and aluminium powder
with 28- day compressive strength of 1. 2- 12. 6 MPa
and densities of 770-1,560 kg/m3 could be made.

[8]

[9]

[10]

ACKNOWLEDGEMENTS
This research was supported by fund budget
revenue form Faculty of Engineering Rajamangala
University of Technology Isan Khon Kaen Campus.
We thank our colleagues Associate professor
Petcharakorn Hanpanich from Department ofradiology, Faculty of medicine, Khon Kaen
University who provided insight and expertise that
greatly assisted the research.

[11]

[12]

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

FLUIDIZED BED COAL-BARK FLY ASH GEOPOLYMER WITH
ADDITIVES CURED AT AMBIENT TEMPERATURE
Prinya Chindaprasirt1, Pornnapa Kasemsiri2, Suttipong Poomsrisa3 and Patcharapol Posi4*
1

Sustainable Infrastructure Research and Development Center, Department of Civil Engineering, Faculty ofEngineering, Khon Kaen University, Khon Kaen 40002, Thailand, and Academy of Science,
The Royal Society of Thailand, Dusit, Bangkok, Thailand 10300
2
Sustainable Infrastructure Research and Development Center, Department of Chemical Engineering,
Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand
3
Thai Paper Co., Ltd. 1 Siam Cement Rd., Bangsue, Bangkok 10800, Thailand
4
Department of Civil Engineering, Faculty of Engineering, Rajamangala University of Technology Isan
KhonKaen Campus, KhonKaen, 40000, Thailand

ABSTRACTIn this research, the properties of fluidized bed coal-bark fly ash geopolymer mortar containing additives viz.,
ordinary Portland Cement (OPC) and micro silica (MS) were studied. The fluidized bed coal-bark fly ash was a
waste from a power plant boiler in Khon Kaen, Thailand. The geopolymer mortar was made from fluidized bed
coal-bark fly ash, sand, sodium silicate solution, NaOH solution, and additives. The additives were used to replace
the fluidized bed coal-bark fly ash at the level of 0 - 15 % by weight. The mortars with liquid alkaline/ash ratios
of 0.9-1.4, sodium silicate/NaOH ratios of 0.33-3.00, NaOH concentrations of 5-15 molars, OPC and micro silica
contents of 0 - 15 % by weight of fly ash, and curing at ambient temperature were tested. The geopolymer mortars
with 28-day compressive strengths between 5.5 and 27.0 MPa and densities between 1970 and 2175 kg/m3 wereobtained. The addition of OPC and micro silica enhanced the strength development of geopolymer mortar with the
optimum OPC content of 10 % and micro silica content of 15 %. It is shown here that the fluidized bed coal-bark
fly ash geopolymer mortar containing OPC and micro silica as additives with ambient temperature curing
possesses sufficient strength. The use of this product can reduce the energy consumption in cement production andincreases the sustainability of construction industry.
Keywords: Coal-bark fly ash, Fluidized bed, OPC, Micro silica, Geopolymer

used for the production of precast concrete such as
pillars, beams, walls and finished flooring which aresuitable for work requiring high compressive strength
in a short time.
Today, the precast concrete is in high demand in
the market because it is convenient and fast to work.
However, heat curing also increase the cost of the
product. Curing at room temperature causes thegeopolymer to develop the strength slowly [4]. The
additive materials such as silica fume or micro silica
are used to help develop strengths. It helps to improvethe compressive strength of the geopolymer cured atroom temperature.
In addition, the production of geopolymer canutilize the waste from the manufacturing process in
the industrial sector. This includes agricultural
products such as rice husk ash, bagasse ash, and otherbiomass ash; the garbage industry, including wasteash, and the electricity industry, including fly ash andbottom ash.
In this research, fly ash was selected to use. The
fly ash was a waste from a power plant boiler in Khon
Kaen, Thailand. It used the wood scraps, which are

INTRODUCTION
Cement is the main material in construction. In the
cement production process, a large amount oflimestone is obtained from the limestone mountain. It
is processed through washing, grinding, baking andother processes and huge energy is thus used. The
temperature up to 1,400 degrees Celsius is needed anda large amount of carbon dioxide (CO2) is released
into the atmosphere. Every 1 ton of Portland cement
comes out of the furnace, about 1 ton of CO2 is
produced [1]. This results in an increase in thegreenhouse effect.
For this reason, the researches have been
conducted to develop alternative materials to
substitute cement to reduce the above-mentioned
problems. The potential binder to substitute Portland
cement is geopolymer materials. Geopolymer is anenvironmentally friendly binder with binding
capacity based on aluminosilicate [2, 3]. It provides
high strength in a short time when modulate heat is
applied. The temperature used is not very high around40-80 degrees Celsius [4]. The geopolymer can be
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SEE - Nagoya, Japan, Nov.12-14, 2018

the waste materials from the paper production
process. The factory has burned these wood scraps to
produce electricity together with the use of subbituminous coal in the Fluidized Bed Combustion(FBC).
The fluidized bed combustion uses small scale
pulverized coal mixed with limestone, and sprays into
the furnace with the hot air. The coal and limestone,
which are sprayed into the furnace, are suspended in
the hot air. It looks like a boiling liquid while the coalburns, the limestone acts as a sponge trapping sulfur
dioxide. This process can reduce the amount of sulfurthat is released by combustion by as much as 90% [5].
In addition, the combustion at temperatures below
1,000 ° C reduces the amount of pollution caused bynitrogen in the combustion system. However, the fly
ash obtained from this system is irregular in shapewith high crystallinity because the burnt temperature
is not very high. This fly ash can be used as apozzolanic material but It is not as good as the fly ash
obtained from the pulverized burning system. Also, it
has high calcium and sulfur content [6] to be used in
the work of geopolymer materials. The properties andeffects of ash will have to be investigated. The coburning of coal and biomass is now also practiced in
the other country [7, 8]. This co-burning of coal andbiomass has recently been applied and thus there is no
statistical report on this. In addition, the use of
fluidized bed coal-bark fly ash as a binder source is
not yet financially supported by the Thai government.
The support would promote the use of waste materials
and is an essence tool for future use of waste.
Therefore, this research has studied the propertiesof geopolymer with fluidized bed furnace system ashfrom burning sub-bituminous coal with wood derived
from the paper production at burning temperature
below 1,000 ° C. It has high calcium and sulfur
contents. The purpose is to recycle the waste from theindustry for maximum benefit. This is thedevelopment of materials for use in the construction
which is environmental friendly and sustainable.

in Fig. 1 and the morphology of FCB-FA by SEM as
shown in Fig. 2 indicated that the shape of FCB-FA
was irregular with some additional small pores.

3000

2000

MS

1000

0
0

20

40

60

80

2 Theta

a. MS
6000

5000

OPC

4000

3000

2000

1000

0
0

20

40

60

80

2 Thetab. OPC
Figure 1. The XRD of MS and OPC

EXPERIMENTAL PROGRAM
Materials
In this study, materials consisted of fluidized bed
coal-bark fly ash (FCB-FA) was a waste from a power
plant boiler in Khon Kaen, Thailand, ordinary
Portland cement (OPC) and micro silica (MS) of 0, 5,
10, and 15 % by weight of fly ash, sodium hydroxide(NaOH) of 5, 10, and 15 M, sodium silicate with
15.32% Na2O, 32.87% SiO2, and 51.8% water, andriver sand. the physical properties of materials areshown in Table 1. The specific gravity of FCB-FA
was 2.86 with median particle size of 23.9 µm. The
FCB-FA consisted of a high content of 21.14% SiO2,
8.02% Al2O3, 10.98% Fe2O3, and 35.8% CaO withthe loss on ignition (LOI) of 0.28% as shown in Table
2. It was, therefore, a class C in accordance which
ASTM C618 [9]. The XRD of MS and OPC as shown

Figure 2. The morphology of FCB-FA by SEM
Mix proportion
OPC and MS content
To study the effect of OPC and MS content, theOPC and MS contents of 0, 5, 10, and 15 % by weightof fly ash were used in one series. The compressive
strength and density of fluidized bed coal-bark fly ash
geopolymer were determined.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1. The physical properties of materials
Materials

MS

OPC

FCB-FA

Sand

Specific gravity
Median particle size (µm)
Fineness modulus
Unit weight (kg/m3)

2.16
13.8
460

3.15
18.7
1440

2.86
23.9
875

2.61
2.65
1360

-

-

-

1.17

Water absorption (%)

Table 2. Chamical composition of materials (byweight)Chemical
FCB-FAMS
OPC
compositions (%)
SiO2
21.14
92.4
20.8
Al2O3
8.02
4.7
Fe2O3
10.98
0.33
3.4
CaO
35.8
2.52
65.3
K2O
5.36
3.13
0.4
Na2O
0.33
0.1
SO3
11.56
0.96
2.7
LOI
0.28
0.21
0.9

Details of Mixing
All mixtures were made and cured at ambient
temperature. OPC and MS content of 0, 5, 10, and 15% by weight of FCB-FA, concentration of NaOH of
10, 12.5, and 15 molars, sodium silicate/NaOH ratios(NS/NaOH) of 0.67, 1.00, and 3.00, aggregate/ash
ratios of 2.50, 2.75, and 3.00. The mixing was donein a pan mixer with following step:- FCB-FA, OPC and MS were mixed for 5 min.
- NaOH was added and mixed for 5 min.
- Sand was added and mixed for 5 min.
- Sodium silicate was added and mixed for 5 min.
The fresh fluidized bed coal-bark fly ash
geopolymers were placed into 50 x 50 x 50 mm cubes
molds according to ASTM C109/C109M-16a [10].
The specimens were wrapped with plastic sheet andplaced in a 25 °C controlled room for 24 hours.
Finally, the specimens were demolded and stored in a
25 °C controlled room. The textures of fluidized bed
coal-bark fly ash geopolymer mortar containing
additives are shown in Fig. 3.

Mix compositions
In order to obtain adequate data, a number ofseries of mixes were tested as follows.
Series OPC: To study the effect of OPC content,
all mixtures used constant NaOH of 10 M, NS/NaOH
ratios of 1.00, aggregate (A)/FA of 2.75 cured atambient temperature. L/FA of 0.9, 1.0, 1.1, 1.2, and
1.3 and OPC content of 0, 5, 10, and 15 % by weight
were tested.
Series MS: To study the effect of MS content, all
mixtures used constant NaOH of 10 M, NS/NaOH
ratios of 1.00, A/FA of 2.75 cured at ambient
temperature. And varies L/FA of 0.9, 1.0, 1.1, 1.2,
and 1.3 and MS content of 0, 5, 10, and 15 % byweight were tested.
Series NS/NaOH: This series was used to study
the effect of sodium silicate/NaOH ratios. All
mixtures used constant NaOH of 10 M, OPC and MS
content of 10 % by weight, A/FA of 2.75 cured atambient temperature, and NS/NaOH ratios of 0.33,
0.67, 1.0, 1.5 and 3.0.
Series [NaOH]: All mixtures used constant OPC
and MS content of 10 % by weight, NS/NaOH ratiosof 1.00, A/FA of 2.75 cured at ambient temperature.
Three NaOH concentrations viz., 5, 10 and 15 molars
were used to study the effect of NaOH concentration.
Series A/FA: This series was used to study theeffect of aggregate/fly ash ratio. all mixture used
constant OPC and MS content of 10 % by weight,
NS/NaOH ratios of 1.00, NaOH of 10 M with cured
at ambient temperature. The A/FA of 2.50, 2.75, and3.00 were tested.

Figure 3. The sample of fluidized bed coal-bark fly
ash geopolymer mortar containing additives
Details of test
Compressive strength and density
The 50 x 50 x 50 mm cube specimens were tested
for density and compressive strength. The density
was determined at 28 days using the compressive
strength specimens as described in ASTM C
138/C138M-14 [11]. The compressive strength wasmeasured after the density determination. The cube
specimens were tested to determine the compressive
strength in accordance with ASTM C109/C109M16a [10]. The reported unit weight and compressive
strengths were the average of three samples.
RESULTS AND DISCUSSIONS
Compressive strength and density
Series OPC
The results of compressive strength of fluidized
bed coal-bark fly ash geopolymer with various L/FA
and OPC content are shown in Fig. 4. The
compressive strength of fluidized bed coal-bark fly
ash geopolymer with additives depended on both
L/FA and OPC contents. For the OPC content, thecompressive strength increased with increasing OPC
content from 0 to 10 % by weight of fluidized bed
coal-bark fly ash. This was due to the increased
497

SEE - Nagoya, Japan, Nov.12-14, 2018

amount of calcium from Portland cement. As a result,
the reaction form additional hydration products of CS-H and C-A-S-H which coexisted with normal
geopolymer products and improved compression [12,13]. For the high OPC replacement level of 15 %, theincrease in compressive strength started to cease andin some cases significant decreases were observed.
The high OPC content of 15 % resulted in somestrength reduction due mainly to the modifications of
microstructure of hydration products and the amountof cement is too high to make the mixture dry [14,15]. For example, the compressive strengths at 28
days of mixes with L/FA of 0.9 with volume of OPC
of 0, 5, 10, and 15 % by weight were 9.2, 16.8, 22.9,
and 22.0 MPa, respectively.
With regards to L/FA, the compressive strength
decreased with increasing L/FA. Due to the ratio of
liquid to fly ash is too high, the result was bleeding
and thus resulted in the reduction in compressive
strength [16, 17]. For example, the compressive
strengths at 28 days of 15 % OPC with L/FA of 0.9,
1.0, 1.1, 1.2, and 1.3 were 22.0, 20.4, 19.6, 18.4, and16.4 MPa, respectively.
OPC0%

Compressive strength (MPa)

25.0

OPC5%

OPC10%

Compressive strength (MPa)

30.0
25.0
20.0
15.0
10.0

0.9

1.0

1.1
L / FA

1.2

1.3

Figure 5. Compressive strength of series MS at 28
days
Series NS/NaOH
The results of compressive strength of fluidized
bed coal-bark fly ash geopolymer with various
sodium silicate/NaOH ratios and OPC, MS content of
10 % by weight are shown in Fig. 6. It was found thatthe optimum compressive strength was with sodium
silicate/NaOH ratios of 1.00. The increased insilicate/NaOH ratios affect to the pH value andincreased the compressive strength [19]. In contrast,
for the silicate/NaOH ratios above 1.00, the increasein sodium silicate content also increased the viscosityof mixture and this resulted in the difficulties incasting and adversely affect the compressive strength[20]. For example, the compressive strengths at 28
days of mixes with control and NS/NH of 0.67, 1.00,
and 3.00 were 6.7, 15.5, and 11.1 MPa, respectively.
When considering MS and OPC contents; the 10% MS gave mix with compressive strength higher
than 10 % OPC due to MS or micro silica is a very
reactive pozzolanic material because of its extreme
fineness and very high amorphous silicon dioxide
content [21]. For example, the compressive strengths
at 28 days of mixes with NS/NH of 0.67 of control,
10 % OPC and 10 % MS were 6.7, 9.3, and 15.4 MPa,
respectively.

OPC15%

5.0

0.0
1.2

MS15%

0.0

10.0

1.1
L / FA

MS10%

5.0

15.0

1.0

MS5%

35.0

20.0

0.9

MS0%

40.0

1.3

Figure 4. Compressive strength of series OPC at 28
days
Series MS
The results of compressive strength of fluidized
bed coal-bark fly ash geopolymer with various L/FA
and MS contents are shown in Fig. 5. For the MS
content, the compressive strength increased withincreasing MS content from 0 to 15 % by weight of
fluidized bed coal-bark fly ash. The particles of silica
fume were very small and highly amorphous phase
could react quite quickly [18]. For example, thecompressive strengths at 28 days of mixes with L/FA
of 0.9 with volume of MS of 0, 5, 10, and 15 % byweight were 9.8, 18.6, 24.5, and 34.5 MPa,
respectively.
With regards to L/FA, the compressive strength of
fluidized bed coal-bark fly ash geopolymer tended todecrease with increasing L/FA. For the example, thecompressive strengths at 28 days of 15 % OPC with
L/FA of 0.9, 1.0, 1.1, 1.2, and 1.3 were 34.5, 25.0,
30.5, 20.5, and 4.2 MPa, respectively.

ControlCompressive strength (MPa)25.0

OPC10%

MS10%

20.0

15.0

10.0

5.0

0.0
0.67

1.00
NS/NaOH

1.50

Figure 6. Compressive strength of series NS/NaOH
at 28 days
Series [NaOH]

498

SEE - Nagoya, Japan, Nov.12-14, 2018

The results of the compressive strength of
fluidized bed coal-bark fly ash geopolymer withvarious [NaOH] and OPC, MS content of 10 % byweight are shown in Fig. 7.
OPC10%

Compressive strength (MPa)Control

25.0

MS10%

20.0
Compressive strength (MPa)Control

25.0

15.0

OPC10%

MS10%

20.0

15.0

10.0

5.0

0.0
2.50

10.0

2.75
A/FA

3.00

5.0

Figure 8. Compressive strength of series A/FA at 28
days

0.0
10

12.5

15

NaOH

CONCLUSIONS
Figure 7. Compressive strength of series [NaOH] at
28 daysBased on the obtained data, the following
conclusions can be drawn:
1. When considering varies L/FA with OPC andMS contents; the compressive strength increased with
the increasing volume of OPC from 0 to 10 % byweight. In contrast, when the OPC increased from 10
to 15 % by weight, the compressive strength
decreased. For the volume of MS, the compressive
strength increased with the increasing of the volumeof MS from 0 to 15 % by weight.
2. For series NS/NaOH; the NS/NaOH of 1 gave
the highest compressive strength and apart from this,the strength of geopolymer started to drop. The 10 %MS gave compressive strength higher than 10 % OPC
due to MS is a very reactive pozzolanic material.
3. For the control and 10 % OPC samples of series[NaOH], the increase in NaOH from 10 M to 12.5 M
resulted in the increasing compressive strength. In
contrast, an increase in NaOH from 12.5 to 15 M
resulted in a decrease in the compressive strength. At
10 % MS, the increase in NaOH from 10 M to 15 M
resulted in the decreasing compressive strength
4. For series A/FA; the increase in A/FA resulted
in a slight decrease in compressive strength and thecompressive strength of 10 % MS was higher thanthat of 10 % OPC.
5. The results showed that the 28-day compressive
strengths between 5.5 and 27.0 MPa and densities
between 1970 and 2175 kg/m3 were obtained. The
addition of OPC and MS enhanced the strength
development of geopolymer mortars with the
optimum OPC content of 10 % and MS content of 15%. The use of this product can reduce the energy
consumption in cement production and increases thesustainability of construction industry.

The increased in NaOH from 10 M to 12.5 M
resulted in the increasing compressive strength. For
example, the compressive strengths at 28 days withthe volume of control with NaOH of 10, 12.5, and 15
M were 15.5, 15.8, and 10.3 MPa, respectively. The
low compressive strength with low NaOH due tosetting time of paste was short with low NaOH [22,23]. The NaOH influence the setting time of thegeopolymer. At low NaOH, the leaching out of silica
and alumina was low but high in Ca2+ and theamount of calcium was sufficient for the precipitation
and reacted to form calcium aluminate hydrate andcalcium silicate hydrate. Thus, the setting time ofgeopolymer was related to the amount of available
calcium [24, 25]. In contrast, an increased NaOH
from 12.5 to 15 M resulted in a decrease in thecompressive strength. At high concentration of
NaOH, the compressive strength decreased due to theexcessive hydroxide ions causing aluminosilicate gel
precipitation at the very early stages and resulting in
low compressive strength [13, 26, 27].
Series A/FA
The results of compressive strength of fluidized
bed coal-bark fly ash geopolymer with various
aggregate/fly ash ratio (A/FA) and OPC, MS contentsof 10 % by weight are shown in Fig. 8. The increasein aggregate/fly ash ratio resulted in a slightly
decrease in compressive strength due to the volume
of cementitious materials decreased.
When considering MS and OPC contents; at thesame Series NS/NaOH, the compressive strength of
10 % MS was higher than that of 10 % OPC due to
MS is a very reactive pozzolanic material.

ACKNOWLEDGEMENT
This work was financially supported by the
Phoenix Pulp & Paper Public Company Limited,
Khon Kaen, Thailand. The support of the Faculty of499

SEE - Nagoya, Japan, Nov.12-14, 2018

Engineering, Rajamangala University of Technology
Isan Khon Kaen Campus, and the Thailand Research
Fund (TRF) under the TRF Distinguished Research
Professor Grant No. DPG6180002 is gratefully
acknowledged here.

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Physicochemical and Engineering Aspects, Vol. 211,
Issue 2-3, 2002, pp. 115-26.
[27] Pimraksa K, Chindaprasirt P, Rungchet A, SagoeCrentsil K, Sato T. Lightweight geopolymer made ofhighly porous siliceous materials with various
Na2O/Al2O3 and SiO2/Al2O3 ratios. Materials Scienceand Engineering: A, Vol. 528, Issue 21, 2011, pp. 661623.

REFERENCES[1] Malhotra VM. Introduction: Sustainable Development
and Concrete Technology. ACI Concrete International,Vol. 24, Issue 7, 2002, pp. 7-22.
[2] Chindaprasirt P, Rattanasak U. Characterization of thehigh-calcium fly ash geopolymer mortar with hotweather curing systems for sustainable application.
Advanced Powder Technology, Vol. 28, Issue 9, 2017,
pp. 2317-24.
[3] Wongkvanklom A, Sata, V., Sanjayan, J., &Chindaprasirt, P. Setting time, compressive strengthand sulfuric acid resistance of a high calcium fly ash
geopolymer containing borax. Engineering and Applied
Science Research, Vol. 45, Issue 2, 2018, pp. 89-94.
[4] Chindaprasirt P, Rattanasak U. Improvement of
durability of cement pipe with high calcium fly ash
geopolymer covering. Construction and Building
Materials, (Supplement C), 2016, pp. 956-61.
[5] Chindaprasirt P, Rattanasak U. Utilization of blended
fluidized bed combustion (FBC) ash and pulverizedcoal combustion (PCC) fly ash in geopolymer. Waste
Management, Vol. 30, Issue 4, 2010, pp. 667-72.
[6] Chindaprasirt P, Rattanasak U, Jaturapitakkul C.
Utilization of fly ash blends from pulverized coal andfluidized bed combustions in geopolymeric materials.
Cement and Concrete Composites, Vol. 33, Issue 1,
2011, pp. 55-60.
[7] Kubacki ML, Ross AB, Jones JM, Williams A. Smallscale co-utilisation of coal and biomass. Fuel, Vol. 101,
2012, pp. 84-9.
[8] Ross AB, Jones JM, Chaiklangmuang S, PourkashanianM, Williams A, Kubica K, et al. Measurement andprediction of the emission of pollutants from the
combustion of coal and biomass in a fixed bed furnace.
Fuel. Vol. 81, Issue 5, 2002, pp. 571-82.
[9] ASTM C 618. Standard Specification for Coal Fly Ash
and Raw or Calcined Natural Pozzolan for Use inConcrete. Annual Book of ASTM Standard.
2012;Vol.04.01.
[10] ASTM C109/C109M-13. Standard Test Method ofCompressive Strength of Hydrualic Cement Mortars(using 2-in. or [50 mm] cube speciments). Annual Book
of ASTM Standard. 2013; Vol.04.01.
[11] ASTM C138/C138M-14. Standard test of method forunit weight of mortar. Annual Book of ASTM
Standard. 2014;Vol.04.01.
[12] Yip CK, Van Deventer JSJ. Microanalysis of calcium
silicate hydrate gel formed within a geopolymericbinder. Journal of Materials Science, Vol. 38, Issue 18,
2003, pp. 3851-60.
[13] Somna K, Jaturapitakkul C, Kajitvichyanukul P,
Chindaprasirt P. NaOH-activated ground fly ash
geopolymer cured at ambient temperature. Fuel, Vol.
90, Issue 6, 2018, pp. 2118-24.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

EFFECT OF CUTTING PARAMETER AND FIBER PULL-OUT ON
MACHINABALITY KENAF FIBER REINFORCED PLASTICCOMPOSITE MATERIALS USING DOE
Azmi Harun1, Che Hassan Che Haron2, Jaharah A. Ghani2, Yuzairi Abdul Rahim1, Roshaliza Hamidon1, Tan
Chye Lih1
School of Manufacturing Engineering, Universiti Malaysia Perlis, Malaysia,

1

Department of Mechanical and Materials Engineering, Faculty Engineering and Built Environment,
Universiti Kebangsaan Malaysia, Malaysia

2

ABSTRACTMilling surface quality normally depends on the value of surface roughness and delamination factor.
The milling parameters, which are cutting tool geometry and fiber pull-out, are the major factors affecting thevalue of surface roughness and delamination factor in milling kenaf fiber reinforced plastic composite. The
objectives of this research are to study the effects of milling parameters, to evaluate the fiber behavior, and to
determine the optimum conditions for a range of milling parameters in order to minimize surface roughness(Ra) and delamination factor (Fd) using response surface methodology (RSM). RSM with central composite
design (CCD) approach was used to conduct a non-sequential experiment and analyzed the data from themeasurements of surface roughness and delamination factor. This study focused on the investigation ofrelationship between the milling parameters and their effects on kenaf reinforced plastic composite materials
during cutting process. Kenaf composite panels were fabricated using vacuum assisted resin transfer molding(VARTM) method that was pressurized below 15 psi using a vacuum pressure. The results showed that the
optimum parameters for better surface roughness and delamination factor were cutting speed of 500 rpm, feed
rate of 200 mm/min, and depth of cut of 2.0 mm. The feed rate and cutting speed are expected to be thebiggest contributors to surface roughness and delamination factor. Finally, different cutting tool geometries
also influenced the fiber pull-out that affect surface roughness and delamination factor in milling kenaf fiber
reinforce plastic composite materials.
Keywords: Kenaf fiber, Surface roughness, Delamination factor, Response surface methodology

fiber is a biodegradable material. In other words, it isan environmentally friendly fiber that is not harmful
to the environment. Therefore, it can be used to
substitute non-biodegradable materials in productdevelopment.

INTRODUCTION
Natural fiber is a hairy-like raw material thatcomes from natural resources such as animal,
mineral, and plant fibers. Also, natural fiber issustainable as well as eco-efficient; therefore, it has
been used to replace glass fiber and other synthetic
polymer fibers that have various kinds ofapplications in engineering [1]. Natural fiber isfamous for its flexibility for processing because it isless delicate to health hazards and damage inmachine tools during manufacturing. Furthermore,natural fiber has a lot of beneficial characteristics, forexample considerably high tensile strength,
satisfying aspect ratio of fiber, and low density, but
due to the nature of the composite, machining ofcomposite materials becomes a major cause ofconcern in the industry [1]. Natural fiber is arenewable source; hence, its cost is very low
compared to man-made fibers. In addition, natural

Kenaf Fiber Composite
The main constituents of kenaf are cellulose (45–57wt.%), hemicelluloses (21.5 wt.%), lignin(8–13 wt.%), and pectin (3–5 wt.%) [2].
Wambua et al. claimed that poor mechanicalproperties could be the result of lack offirmness
betweenthepolymers(hydrophobic)
andthenaturalfiber(hydrophilic) [3]. Kenaf fiber offers betterinterfacial adhesion to matrix polymer than othernatural fibers [4]. Matrix polymer can support thefibers, transfer the stresses to fibers to bear mostof the load, prevent direct
501

SEE - Nagoya, Japan, Nov.12-14, 2018

Delamination of a natural fiber composite can be
described as the loss of adhesion between the layersthat can lead to critical damage of the reinforcement
layers (separation). Hocheng et al. believed thatdelamination can be worsened by increasing the feed
rate of milling parameters [15]. The damage of thecomposite is greater if the operation is conductedwith high cutting speed and high feed rate [14].
Furthermore, Hocheng et al. stated that delamination
can be worsened by increasing the feed rate and tool
life can be shortened by increasing the cutting speed
that causes higher torque [15]. Davim et al. studied
the effects of cutting speed and feed rate ondelamination of glass fiber reinforced plastic duringmachining with two different matrices [16]. The
damage of the composite is greater if operated withhigh cutting speed and high feed rate[14].

physical damage to fibers, and improve ductility andtoughness of the whole composite [5]. Epoxy
produces no toxic gases and offers high temperature
resistance that enables it to be used at hightemperature [6]. Hafizah et al. studied the tensile
behavior of kenaf fiber reinforced with several
polymer composites and concluded that kenaf
reinforced epoxy composite had the highest ultimate
tensile strength and the Young’s modulus [7].
Various research has been conducted and it has been
proven that machining parameters possess significant
effects on the performance and quality of natural
fiber composite [8], [9].

Milling Kenaf Fiber Composite
Erkan et al. claimed that increased spindle speed
worsened the damage factor and increased the plastic
deformation rate on an end-milled fiber reinforced
plastic composite [10]. Davim et al. claimed that feed
rate was expected to affect delamination rather thancutting speed for the machining of fiber reinforced
plastic [11]. Ramulu et al. studied the machining ofpolymer composite and stated that better surface
finish could be obtained with higher cutting speed[12]. The impact of depth of cut is not as important
as cutting speed and feed rate in composite
machining; however, it still gives a significant effecton machining process [13]. Besides, the milledsurface is getting smoother as the flute of the cutting
tool increases [10]. The end-mill cutter can be madeof either a high-speed steel or a carbide insert andusually has a straight shank or a tapered shank.
Normally, the cutter rotates on a workpiece in aperpendicular axis but it can still be tilted in order tomatch the need of producing a machine-tapered or
curved surface. However, milled composites always
tend to have surface roughness and delamination
problem that depends much on cutting parameters
and the composite’s characteristic [14]. Thus, an
optimum setting of these parameters is needed to findout in order to control the quality of a workpiece.
The advantages of a high-speed steel (HSS) cutting
tool over a carbide cutting tool are higher strength towithstand cutting forces and lower cost. However, acarbide insert cutting tool is better than an HSS tool
in metal cutting due to its great abrasion resistanceand high temperature resistance, which allows it to
be used in machining process at high speed without
the need to consider overheating situation. For
machining of natural fiber composites, an HSS
cutting tool is sufficient to meet this research’s
purpose.

METHODOLOGY
Materials Preparation
Kenaf reinforced epoxy composite materials
were prepared using vacuum-assisted resin transfer
molding (VARTM) method. The method was used totransfer resin to natural fiber in a vacuum condition
for molding with the assistance of a vacuum pump.
The kenaf fiber in mat form was cut into thedimensions of 300 mm × 300 mm × 5 mm(thickness). Two layers of kenaf fiber mat were used
and mixed with epoxy resin. The resin was preparedin the ratio of 4 (800 g epoxy) to 1 (200 g hardener).
The VARTM manufacturer recommended this ratio
for fabricating kenaf fiber reinforce plastic composite
materials. The VARTM method is gaining theinterest of manufacturers due to its ease of handlingand low preparation cost. Figure 2 shows the actual
setup of VARTM. The composite panels were thencut into small workpiece with the approximate
dimensions of 75 mm × 30 mm × (8–10 mm) for
milling process.

Milling Parameter
The milling parameters of this research werebased on the work by Babu et al. since they studied
the machining of natural fiber composite. The
parameter setting in this research was based on theprevious parameters used in the work by Babu et al.
[8]. Table 1 shows the parameters used in thisresearch in which all the units were converted to suitthe use of a computer numerical control (CNC)
milling machine. The three parameters used in thisresearch were spindle speed (rpm), feed rate (mm/min), and depth of cut (mm), with low and highDelamination Factor

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SEE - Nagoya, Japan, Nov.12-14, 2018

levels for each parameter. A two-level factorial
design of experiment was selected with eight
experiment runs designed using Design Expert 7.0
software. Four center points were added to seek forthe significance of the curvature and error testing. If
the curvature of the results is insignificant, a linear
modeling equation is sufficient to express the
optimization. If the curvature is significant, there is achance for applying RSM. In RSM, the CCD
approach was used to obtain a quadratic modeling
equation for parameter optimization. RSM was used
to develop a second-order modeling equation that has
better accuracy in expressing the optimization.
Table 1 Parameter setting for milling process.
Milling parameters

Low

Spindle speed (rpm)500

Feed rate (mm/min)
120
Depth of cut (mm)

200
1

Hig
h
100
0
0
3

Center point
700
750
2

Measurement of Delamination factor

Feed rate(mm/min)
1200

Depth ofcut (mm)
1

2

500

200

1

3

500

1200

1

4

750

700

2

5

750

700

2

6

1000

1200

3

7

750

700

2

8

1000

200

3

9

1000

200

1

10

750

700

2

11

500

1200

3

12

500

200

3

Fd
1.11
3
1.03
9
1.07
7
1.04
2
1.06
7
1.01
6
1.06
2
1.13
4
1.12
4
1.03
4
1.07
5
1.03
5

ANOVA analysis for screening process ofdelamination factor (Fd)The results of delamination factor wereobtained after milling processes. The
delamination factor (Fd) can be determinedusing (1).
Fd = Wmax / W

1

Spindlespeed (rpm)
1000

Run

The curvature is significant (see Table 3) and it
indicates that there is a chance for developing aquadratic modeling equation using RSM with CCD
approach. From the analysis of variance (ANOVA)
test for delamination factor (Fd), spindle speed was
the most significant factor (p value = 0.0068)
affecting delamination. The depth of cut was thesecond significant factor (p value = 0.0292) whereas
the feed rate was the least factor (p value = 0.2237).
In order to apply RSM, CCD (see Table 4) was
added to further investigate the parameters fordelamination by constructing a second-ordermodeling equation.

(1)

Where,
Fd = Factor of delamination
Wmax= maximum width of the delamination area
W = width of original cut

Results of delamination factor (Fd ) using Central
Composite Design (CCD)
Table 4 Result for delamination factor (Fd) using
Central Composite Design.

Fig. 1 Example measurement of delamination factor
(Fd)

Run
1
2
3
4
5

RESULTS AND DISCUSSION
Table 2 Result for delamination factor (Fd) using
screening parameter setting.

503

Spindle Speed(rpm)
1000.00
1000.00
500.00750.001000.00

Feed rate(mm/min)1200.00
200.001200.00
700.00200.00Depth of Cut
(mm)
1.00
1.00
3.00
2.00
3.00

Fd
1.075
1.134
1.077
1.062
1.113

SEE - Nagoya, Japan, Nov.12-14, 2018

6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

500.00750.00500.001000.00
750.00750.00500.001170.45750.00329.55750.00750.00750.00750.00750.00200.00700.001200.00
1200.00
700.00700.00200.00700.00-140.90700.00700.00700.001540.90700.00700.00

1.00
2.00
1.00
3.00
2.00
2.00
3.00
2.00
2.00
2.00
2.00
2.00
2.00
0.32
3.68

1.035
1.034
1.124
1.067
1.042
1.039
1.016
1.083
1.012
1.021
1.059
1.038
1.087
1.054
1.046

of lack of fit of the quadratic modeling equation asshown in Table 5. From Table 5, the main factors
significant to Fd were spindle speed with F value of
9.67 (0.72%), feed rate with F value of 4.86 (4.4%)
and the AB interaction with F value of 18.43(0.06%). The AB interaction (spindle speed and feedrate) had the largest effect on kenaf composite tolaminate, followed by A (spindle speed) and B (feedrate). The graphs of Fd versus A, B, and AB
interaction are plotted in Figure 2, Figure 3, andFigure 4, respectively.

Table 3 ANOVA result of delamination factor (Fd)using 2FI Design

0.012

Degree offreedom
4

A-spindle speed

2.319E-003

1

2.319E-003

16.27

B-feed rate
C-depth of cut
AB
Curvature

2.622E-004
1.157E-003
8.090E-003
3.456E-003

1
1
1
1

2.622E-004
1.157E-003
8.090E-003
3.456E-003

1.84
8.12
56.78
24.26

ResidualLack of Fit

8.549E-004
4.073E-004

63

1.425E-004
1.358E-004

0.91

Pure Error

4.476E-004

3

1.492E-004-

Mean square

F-value

0.0048

10.99

SourceModel

Sum of squares

ANOVA analysis using Central
Design of delamination factor (Fd )Mean square

F-value

2.957E-003

20.75

p-value
Prob>F0.0012significant
0.00680.22370.02920.00030.0026significant
0.5300Not significant-

Composite

Table 5 ANOVA result of delamination factor (Fd)using Central Composite Design
SourceSum of squares

Model

0.0145Degree offreedom3

A-Spindle speed
B-Feed rate
AB
ResidualLack of fit

0.00430.00210.00810.00660.0059

1
1
1
15
11

0.00430.00210.00810.00040.0005

9.67
4.86
18.43
3.21

Pure of error
Cor Total

0.00070.02274190.0002-After obtaining the experimental result using CCD,ANOVA test was conducted again to determine thesignificance of the three factors and the significance504

p-value
Prob>F
0.0005significant
0.00720.04350.00060.1357
Not significant-

SEE - Nagoya, Japan, Nov.12-14, 2018

and depth of cut of 2 mm. FD decreased for lower
spindle speed. This phenomenon is caused by thevibration of the cutting tool with high spindle speed
during milling process. With large vibration, high FD
is produced on top of the ductile composite materials
laminated. Besides, high feed rate (Figure 3)
produced high FD. Spindle speed and depth of cut
remained in the middle range.
In Figure 4, the depth of cut maintained at 2 mm,
where the red line indicates the high level of feed
rate (1,200 mm/min) and the black line indicatesthe low level of feed rate (200 mm/min). It can
be clearly observed that low feed rate (200 min/mm) with high spindle speed will produce theworst delamination factor. A good FD will be
produced using lower feed rate (200 mm/min)with lower spindle speed. Davim et al. shared thesame viewpoint that high cutting (spindle) speed
caused great damage on glass fiber reinforced plastic
composites during machining [19]. The non-linear
relationship between the feed rate and FD might
be caused by opposite milling to the orientation of
kenaf fiber. The results obtained might be lessaccurate if all the specimens are not milled in the
direction of orientation of fiber. In addition,
previous researchers concluded that low feed
rate causes small damage on composites [8], [15].

Fig. 2 Effect of A (Spindle speed) for
delamination factor (Fd)

Optimum parameter and modeling equation for
optimization of delamination factor
The second order modeling equation for
optimization of milling parameters on minimizing
delamination factor (Fd) is shown in (1).

Fig. 3 Effect of B (Feed rate) for delamination factor(Fd)

Fd = 0.85466 + 2.492 x 10-4 A + 2.163 x 10-4 B– 2.55 x 10-7 AB

Feed rate

(1)
Where
A= spindle speed (rpm)
B= feed rate (mm/min)
C= depth of cut (mm) in terms of actual value.
Table 6 Optimum parameter and conformation testfor delamination factor (Fd)Fig. 4 Effect of AB (Spindle speed and Feed rate)interaction for delamination factor (Fd)Figure 2 shows the effect of spindle speed on FD,
where FD increased slightly with the increaseof spindle speed at tfeed rate of 700 mm/min
505

Spindle
speed
(rpm)

Feed rate(mm/min)Depth
of cut(mm)

Calculated
Fd

Measured
Fd

Percentage
error (%)

530

310

2

1.012

1.032

1.93

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 6 shows the percentage error between
calculated (Fd) using the equation (1) and themeasured Fd. The measured (Fd) was located at
the prediction range (0.96 - 0.06) and thepercentage error was only 1.93% which proved
the modeling equation and the suggested
optimum parameters can be accepted.

[4] B. F. Yousif, A. Shalwan, C. W. Chin, and K. C.
Ming, “Flexural properties of treated anduntreated kenaf / epoxy composites,” vol. 40, pp.
378–385, 2012.
[5] S. R. Schmid and S. Kalpakjian, Manufacturing
Engineering and Technology, 6th ed. New Jersey:
Prentice Hall, 2009, pp. 172, 216–226, 662, 662–
668.

CONCLUSION[6] K. K. Chawla, Composite Materials. New York,
NY: Springer New York, 2012, pp. 81–83.

The suggested optimum milling parameters in thisresearch for the minimization of Fd were 530 rpm of
spindle speed, 310 mm/min of feed rate, and 2 mm ofdepth of cut. For the optimization of delamination,
the curvature shown in ANOVA after the 23 factorial
design of experiment was significant. This enabled
the utilization of RSM with CCD approach that
requires more experimental runs to collect data forconstructing a second-order modeling equation. CCD
approach was selected and eight additional
experimental runs were added. Low spindle speed
and low feed rate caused less delamination on milled
kenaf composites. In addition, with deeper depth ofcut, the possibility of delamination can be reduced.

[7] N. A. K. Hafizah, M. W. Hussin, M. Y.
Jamaludin, M. A. R. Bhutta, M. Ismail, and M.
Azman, “Tensile behaviour of kenaf fiber
reinforced polymer composites,” J. Teknol., vol.
3, pp. 11–15, 2014.
[8] G. D. Babu, K. S. Babu, and B. U. M. Gowd,“Effect of machining parameters on milled
natural fiber-reinforced plastic composites,” J.
Adv. Mech. Eng., pp. 1–12, 2013.
[9] N. Abilash and M. Sivapragash, “Optimizing thedelamination failure in bamboo fiber reinforced
polyester composite,” 2013.
[10] Ö. Erkan, I. Birhan, A. Çiçek, and F. Kara,“Prediction of Damage Factor in end Milling ofGlass Fibre Reinforced Plastic Composites Using
Artificial Neural Network,” 2012.

ACKNOWLEDGMENTS
Machine shop, laboratory facilities and their staff at
the Faculty of Engineering and Built Environment of
Universiti Kebangsaan Malaysia are gratefully
acknowledged. Thanks to the Ministry of Higher
Education Malaysia for supporting this project under
the grant LRGS/TD/2012/USM-UKM/PT/05.
.

[11] J. Davim, J. Rubio, and A. M. Abrao, “A novel
approach based on digital image analysis toevaluate the delamination factor after drillingcomposite laminates,” Compos. Sci. Technol.,vol. 67, no. 9, pp. 1939–1945, Jul. 2007.
[12] M. Ramulu, D. Arola, and K. Colligan,“Preliminary investigation on the surface
Integrity of fiber reinforced plastics,” Am. Soc.
Mech. Eng. Pet. Div., vol. 64, no. 2, pp. 93–101,
1994.

REFERENCES[1] Ho, M., J.H. Lee, C. Ho, K. Lau, J. Leng, D. Huiand H. Wang, 2012. “Critical factors on
manufacturing processes of natural fiber
composite,” Compos. Part B, 3549–3562.

[13] K. Palanikumar, “Modeling and analysis forsurface roughness in machining glass fibre
reinforced plastics using response surface
methodology,” Mater. Des., vol. 28, no. 10, pp.
2611–2618, Jan. 2007.

[2] R. M. Rowell, “A new generation of composite
materials from agro-based fiber,” in Proceedingsof the 3rd International Conference on frontiersof polymers and advanced materials, 1995, pp.
659–665.

[14] J. P. Davim, P. Reis, and C. Conceição
António, “A study on milling of glass fiber
reinforced plastics manufactured by hand-lay up
using statistical analysis ( ANOVA ),” Compos.
Struct., vol. 64, pp. 493–500, 2004.

[3] P. Wambua, J. Ivens, and I. Verpoest, “Natural
fibres : can they replace glass in fibre reinforced
plastics ?,” Compos. Sci. Technol., vol. 63, pp.
1259–1264, 2003.
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SEE - Nagoya, Japan, Nov.12-14, 2018[15] H. Hocheng, H. Y. Puw, and K. C. Yao,
“Experimental aspects of drilling of some fiberreinforced plastics,” in Proceedings of theMachining of Composites Materials Symposium,
1992, pp. 127–138.

analysis to evaluate the delamination factor
after
drilling
compositelaminates,”
Compos. Sci. Technol., vol. 67, no. 9, pp.
1939–1945, Jul. 2007.

[16] J. Davim, J. Rubio, and A.M. Abrao, “Anovel approach based on digital image507

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EMBEDDED INTELLIGENCE FOR QUALITY OF SERVICE-BASEDVERTICAL HANDOVER MANAGEMENT IN SEAMLESSWIRELESS NETWORKS
Sunisa Kunarak
Department of Electrical Engineering, Srinakharinwirot University, Nakhonnayok, Thailand 26120
Email: sunisaku@g.swu.ac.th
ABSTRACTThis paper presents the development and hardware implementation of the hybrid artificial neural networks thatis included learning vector quantization (LVQ) and radial basis function (RBF) for the vertical handover decisionalgorithm in order to keep the always best connected (ABC) ubiquitous wireless networks. The LVQ is
unsupervised learning and also the RBF is appropriate the non-linear data decision. The proposed approach isbased on the merit function as the received signal strength indicator, bandwidth requirement, mobile speed andmonetary cost of service to consider using field programmable gate arrays (FPGAs) logical architecture design.
Additional, the hybrid architecture describes in VLSI hardware description language (VHDL). WCDMA,
Advanced LTE and WLAN are cooperated topology in the experimental. The experimental results are depicted ahigh correlation with the hybrid artificial neural networks that is simulated by MATLAB and can increase thecomputation speed compared with the standard personal computer (PC) thus FPGA is suitable in the real world
situations as the non-real time and real time applications for the future wireless communication system.
Keywords: Embedded, Field Programmable Gate Array, Quality of Service, Vertical Handover, Wireless
Networks
service (QoS) parameters are the indicator of theeffective heterogeneous networks (HetNets),
respectively.
The remainder of this paper is structured as follow.
Section II, the hybrid artificial neural networks
approach based on FPGA for vertical handoverdecision is depicted. Finally, the experimentation
results and conclusion are discussed in Section III andIV, respectively.

INTRODUCTION
Artificial neural networks (ANNs) have beenstudied widely over many years. One of the mostpopular with ANNs is the radial basis function neuralnetwork (RBFNN) [1] that is suitable the non-linear
data but this algorithm does have to use the large
information. Additionally, the artificial neuralnetworks are the mathematical model that is inspired
the functioning of the human brain. It can be utilized
in classification, clustering, prediction, control
system, recognition problems and so on [2]-[5]. In
this paper, the hybrid artificial neural networks
includes the learning vector quantization (LVQ) andradial basis function (RBF) that is used for the verticalhandover decision since this algorithm is appropriate
the small to medium information and can support the
non-linear data that is proper the non-real time andreal time applications for the fifth generation (5G)
wireless networks as the future communications.
Nowadays the wireless mobile devices such as
smartphones or tablets need to access the internet at
anywhere and anytime. When the mobile terminals
can connect the same network is also known thehorizontal handover (HH) procedure; on the other
hand, the mobile terminals can connect the different
networks or technologies as the vertical handover(VH) procedure. The VH procedure is supported theincreasing complexing of the wireless networks inheterogeneous scenarios furthermore the quality of

HYBRID ARTIFICIAL NEURAL NETWORKS
APPROACH BASED ON FPGA FOR
VERTICAL HANDOVER DECISION
The hybrid artificial neural networks (HybridANNs) consist of the learning vector quantization(LVQ) that is based on the competitive layer and theradial basis function (RBF) layer i.e. the Gaussian
distribution function neural networks as shown in Fig.
1. The Kohonen presents the LVQ owing to theclassification method the same way as thecompetitive layer of cluster with Self-Organizing
Map (SOM) also known as unsupervised learning
while the RBF is the technique of training by descentgradient algorithm with updated the weights andcenters of learning. Firstly, the competitive layer isthe distance learning as follow [6]-[8]. The distancelearning is based on the Euclidean distance that ismeasured to adaptive during the training data sets i.e.
received signal strength indicator (RSSI), bandwidth
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SEE - Nagoya, Japan, Nov.12-14, 2018

Competitive Layer

Input

RSSI

Radial Basis Function Layer

IW

BW

ndist

MS

C

HandoverDecision
Criteria

LW

MC

Fig. 1

HandoverDecision

Hybrid artificial neural networks for vertical handover decision.

(BW), mobile speed (MS) and monetary cost (C)metrics as Eq. (1)Table 1 Pseudo-code of proposed algorithm
Hybrid Artificial Neural Networks Approachd  w , x   x  w T  x  w 

1: Collect the handover metrics: RSSI, BW, MS, C
2: Generates the initial hybrid artificial neural networks3: in order that the handover occurs or not?
4: if handover factor > 0.6 then5:
Handover initiation process ++6: else7:
Dropped call ++8: end if
9: Obtain the number of handover
10: Obtain the number of dropped call(1)

where x  x1 ,..., x D    D is the input samples
with D dimensional. Also, the yi  1,..., C ;i  1,..., N is the sample labels, and C is the numberof classes. The  is a full D  D matrix size andmust be the positive definite and the w i is defined as
the receptive field of training patterns as







i  x  X w  j  i   d  w , x   d  w , x .
R
j
i
j

communications, data processing, and etc [9]-[10].
The FPGAs consist of the three fundamental
components as the logic blocks, interconnection
resources and I/O cells in order to achieve
configurability. In this paper, the cmod A7-35T
breadboardable artix-7 FPGA module is used because
it is the same look like a mobile device. In addition,
there is a small and the breadboard friendly has 48pin DIP form factor board built around a Xilinx Artix7 FPGA. The board also includes a USB-JTAG
programming circuit, USB-UART bridge, clock
source, Pmod host connector, SRAM, Quad-SPI
Flash, and basic I/O devices. These components makeit a formidable, albeit compact, platform for digital
logic circuits and MicroBlaze embedded soft-coreprocessor designs using Xilinx's development
software as Vivado as shown in Fig. 2.

(2)
The arbitrary Euclidean distance in Eq. (1) is reduced
to Eq. (3) when the  is ignored to being diagonal
matrix and use instead with the Gaussian distributionfunction learning in the radial basis function neuralnetworks layerd   w, x  De x j w j 

2 2j

2

.

(3)

j 1

Hybrid Artificial Neural Networks for Vertical
Handover Decision
The hybrid ANN has been programmed in VLSI
hardware description language with the objective ofallowing its portability to any processing
environment for mobile device. In this case, it has
been successfully tested on an embedded processor
based on a small and low power FPGA device.
Additionally, the hybrid ANN is operated procedurethat is depicted in Table 1.

Fig. 2

Platform of cmod A7-35T breadboardable
artix-7 FPGA module.

EXPERIMENTAL RESULTS

Hardware Evaluation of Hybrid Artificial Neural
Networks

In the experimentation, the handover decision is
performed by a mobile terminal (MT) that is adopt themobile-controlled handover (MCHO) strategy.

Field programmable gate arrays (FPGAs) havebeen promoted in many applications such as wireless
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SEE - Nagoya, Japan, Nov.12-14, 2018

Moreover, this section is divided into 3 sub-sections
as experimental structure, experimental parametersand performance analysis, respectively.

distribution as demonstrated in Fig. 4. Also, thenumber of dropped call refers to the unsuccessful
handover call causes the mobile node to bedisconnected and is the fewest by using hybrid ANN
as illustrated in Fig. 5.

Experimental Structure
The heterogeneous wireless networks cooperatewith Wide-band Code Division Multiple Access(WCDMA), Long Term Evolution (LTE) and
Wireless Local Area Network (WLAN) as illustrated
in Fig. 3. The coverage areas of WCDMA, LTE and
WLANs are equal to 2,500 meters, 1,000 meters and
35 meters, respectively. The tightly and loosely
coupled are interworked in the seamless wirelesstopology. WLAN and LTE are connected to
WCDMA core network via radio access network intightly coupled type. In the other hand, the WLAN
and LTE can access the IP network without
connecting to WCDMA. Thus, the loosely coupled
type is introduced in the proposed algorithm since its
coupling provides a flexible and an independent
environment due that this scheme is based on mobile
IP (MIP) [11].
The user preferences and network characteristics
are different therefore the handover decision criteria
in the proposed approach is different together. Suchas, the real time applications (e.g. video conference),
handover should be performed as rapid as possible inorder to minimize the delay. On the contrary, theamount of data transmission is more important thanthe delay so that the handover criteria for non-realtime service is to attempt to connect WLAN/LTE aslong as possible due to higher data rate.

R=2500m
WCDMA

R=1000m
LTE

R=35m

R=35m
WiFi 1

Fig. 3

WiFi 2

Heterogeneous wireless networks structure.

Table 2 Summary of the experimental parameters
Parameters
Frequency (GHz)Coverage area (m)Transmission
power (w)
Bit rate (Mbps)
Latency (ms)
Mobile speed(m/s)
Bit error rate
(per 10^8)
Monetary cost rate

Experimental Parameters
The correspondent node (CN) generates theconstant bit rate (CBR) multimedia traffic using a 64byte packet size is sent every 0.1 second and user
datagram protocol (UDP) is the transport protocol
applied between the networks that includes thedetection of the new networks and the allocation of
new IP address. The experimental parameters of
WCDMA, LTE and WLAN are utilize as depicted inTable 2.

WCDMA

LTE

WLAN

2.1
5000
1.0

2.6
1000
0.5

2.4
100
0.1

0.384
35
80

35
25
130

54
3
5

50

100

200

0.8

0.7

0.4

In another experimental, the execution time
displays the time needed by the FPGA and PC
implementation as shown in Fig. 6. Figure 6 indicatesthe algorithm is nearly executed with the constantnumber of neurons when compares with the PC
although increases almost linearly as the number ofneurons in the approach increases.

Performance Analysis
The experimental, the average arrival rate of new
calls is fixed at 10 calls/sec and average call holding
time is equal to 180 sec. The user’s speed is a uniform
distribution as equal to 1-30 m/s and user movement
is modeled as the random waypoint mobility in 6,000
x 6,000 sq.m topology size for each speed. The hybrid
ANN can decrease the number of handover since this
proposed method brings the benefit of self-organizing
map and radial basis function that is suitable the nonlinear data communication namely the Gaussian

CONCLUSION
The hybrid artificial neural networks are used
the received signal strength indicator, bandwidth
requirements, mobile speed and monetary cost as themulti-criteria factors in order to the vertical handoverdecision. The experimental results indicate theproposed approach that outperforms another510

SEE - Nagoya, Japan, Nov.12-14, 2018

algorithm as reducing the unnecessary handover anddropping call, respectively. Correspondingly, theexecution time is independently the number ofneurons.

REFERENCES[1] Renteria-Cedano J. A., Aguilar-Lobo L. M., LooYau J. R. and Ortega-Cisneros S., Implementationof a NARX Neural Network in a FPGA for
Modeling the Inverse Characteristics of Power
Amplifiers, IEEE 57th International Midwest
Symposium on Circuits and Systems, 2014, pp.
209-212.
[2] Zamorano F. O., Jerez J. M., and Franco L., FPGA
Implementation of the C-Mantec Neural Network
Constructive Algorithm, IEEE Transactions on
Industrial Informatics, Vol. 24, No. 2, 2014, pp.
1154-1161.
[3] Gómez I., Franco, L. and Jerez J., Neural Network
Architecture Selection: Can Function Complexity
Help?, Neural Process. Letters, Vol. 30, Issue 2,
2009, pp. 71-87.
[4] Hunter D., Hao Y., Pukish, Kolbusz J. andWilamowski B., Selection of Proper Neural
Network
Sizes
andArchitectures—A
Comparative Study, IEEE Transactions on
Industrial Informatics, Vol. 8, No. 2, 2012, pp.
228-240.
[5] Lakshmi K. and Subadra M., A Survey on FPGA
based MLP Realization for On-Chip Learning,
International Journal of Scientific & Engineering
Research, Vol. 4, Issue 1, 2013, pp. 1-9.
[6] Nova D. and Estévez P. A., A Review of Learning
VectorQuantization
Classifiers,
NeuralComputing and Applications, Vol. 25, 2014, pp.
511-524.
[7] Yang W. A., Monitoring and Diagnosing of Mean
Shifts in Multivariate Manufacturing Processes
Using Two-Level Selective Ensemble of Learning
Vector Quantization Neural Networks, Journal ofIntelligent Manufacturing, Vol. 26, Issue 4, 2015,
pp. 769-783.
[8] Ortiz-Bayliss J. C., Terashima-Marin H. andConant-Pablos S. E., Learning Vector
Quantization for Variable Ordering in Constraint
Satisfaction Problems, Pattern Recognition
Letters, Vol. 34, Issue 4, 2013, pp. 423-432.
[9] Liu Q., Gao M. and Zhang Q., Knowledge-Based
Neural Network Model for FPGA Logical
Architecture Development, IEEE Transaction on
Very Large Scale Integration (VLSI) System, Vol.
24, No. 2, 2016, pp. 664-677.
[10] Tisan A. and Chin J., An End-User Platform for
FPGA-Based Design and Rapid Prototyping ofFeedforward Artificial Neural Networks with OnChip
Backpropagation
Learning,
IEEE
Transaction on Industrial Informatics, Vol. 12, No.
3, 2016, pp. 1124-1133.
[11] Nithyanandan L. and Parthiban I., Seamless
Vertical Handoff in Heterogeneous Networks
Using IMS Technology, IEEE International
Conference on Communications and Signal
Processing, 2012, pp. 32-35.

ACKNOWLEDGEMENTS
This research was supported by the research grant(No. 582/2559) from Srinakharinwirot University
revenue 2559, for the 2559 fiscal year.
90
Hybrid ANN
LVQNN

80
70
60
50
40
30
20
10
0

0

500

1000

1500

2000

2500

3000

3500

Number of Users

Fig. 4

Number of users and number of handovers.

200
Hybrid ANN
LVQNN

180
160
140
120
100
80
60
40
20
0

0

500

1000

1500

2000

2500

3000

3500

Number of Users

Fig. 5

Number of users and number of drop calls.
30
FPGA
PC

25

Time (s)

20

15

10

5

0
0

2

4

6

8

10

12

14

16

18

20

Number of Neuron

Fig. 6

Number of neuron and execution time.

511

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

GREEN CARGO MOVEMENT, LOCALITY: MEKONG
Leonard Johnstone1, Vatanavongs Ratanavaraha2
1,2

Suranaree University of Technology, 111 University Avenue, Suranaree Sub-district, Muang District,
NakhonRatchasima 30000, Thailand

Email for correspondence: vatanavongs@g.sut.ac.th
ABSTRACT
There is an issue in the identification of commonality across several localities associated with the problem ofcargo movement via modes of transport other than road. The approach in this paper considers movement from thelocality of the multi jurisdiction of the Mekong Region, an agglomeration of Myanmar, Thailand, Laos, Vietnam,
Cambodia and southern China. A mathematical approach was developed to analyze the impact of cargo movementaway from the road transport sector to greener alternative rail mode. The analytical appreciation is consideredfrom the review of large scale cargo movement across the region. Results from the data analysis are indicative ofan environmentally friendly or a green freight alternative. The mathematical model described in this paper is used
to consider freight modal shifts under various infrastructure development scenarios. The outcome from the analysis
results is the input into ongoing research to identify common mathematical functions across other jurisdictions.
The conclusion is that there is a likelihood that common mathematical procedures are applicable in several
localities.
Keywords: Mekong, GDP, Cargo, Mode

INTRODUCTIONIn France, the cargo modal share is eighty percent
increasing to eighty five percent in the United
Kingdom. Whilst the modal share in Italy is just overninety percent. Thus, even in the context of thedeveloped European Union cargo movement, roadtransport is the most significant mode. This
dominance of the road sector makes it difficult torealize the objective of the European Union to reducethe dependence on road transport.

The Mekong region in this context is defined toinclude seven localities namely the nation states ofMyanmar, Thailand, Lao People’s Democratic
Republic (PDR), Cambodia, Vietnam and the twosouthern provinces of Guangxi and Yunnan within
the People’s Republic of China (PRC). The extent of
the major infrastructure network is presented in Fig 1.
The focus of this paper is the modal analysis of cargoor freight movement throughout the Mekong.
Within the any region, the transport mode of cargotransport by road is an essential factor in economic
activity and has historically played a strong role in thedevelopment for many areas across the globe. In
many regions and countries with a single jurisdiction,
there is growing trend to develop strategies that moveaway from the dominance of cargo transport by roadtoward alternative environmental friendlier modes.
In a broader world context, almost all cargo
movements are dependent on road transport. In for
example, even in the European Union as reported inan earlier report [1], cargo movement in 2009 wasdominated by the road sector. The road modal sharefor any of the major country members did not fall
below sixty percent. This was true even in the case ofGermany where twelve percent of cargo moves via themode of inland water.

Fig. 1

512

The Mekong Region.

SEE - Nagoya, Japan, Nov.12-14, 2018

The Agenda 2020 of the European Union calls formember countries to reduce greenhouse gas
emissions. There is implicit in this agenda within theUnion the desirability of taxing fuels on road basedtransport, [2] thus encouraging by financial incentives
a modal shift away from the dominant road sector.
The Union is providing incentives towards a greener
movement of freight with consequently fewer
greenhouse emissions which in essence is to reduce
the road component of cargo movement following theParis Agreement on Climate Change [3] and [4] . Thisof course leads to the need of improving thealternatives to cargo movements by road.

period.
Population growth is seen as the higher in the twolarger population localities of Cambodia and Vietnam.
The Lao PDR has the highest historical population
growth albeit from a lower base.
The noted differential growth rates in the future
are likely to lead to changes in the distribution of GDP
Use at most three levels of headings that correspondto chapters, sections and subsections.
Table 1 Locality growth per annum 1998 - 2014
Locality
Cambodia
Guangxi, PRC
Yunnan, PRC
Lao PDR
MyanmarThailand
Viet Nam

THE REGIONAL SITUATION
There are two parts in the understanding ofregional cargo movement namely the movement
infrastructure, the transport supply and the actual
amount and nature of cargo movement on the
network, the demand side.
Within the framework of the regional transport
network for the Mekong assembled as part of thisresearch in the development of an analytical transportmodelling tool, the primary regional road network
identified as depicted in the earlier Fig. 1 is some
37,000 kilometers in length. The identified rail
network is of some 17,000 kilometers in length. The
length of the rail network is thus some 34% of the
major transport corridor by comparison in length.
There is a significant regional rail network although
there are some missing connections between theearlier defined seven localities within the Mekong.
In addition to the land transport network, there isa further 10,000 kilometers each of Inland Waterway
Transport(IWT) and Coastal Shipping or Sea Mode
included in the transport network. For the movementof people an extensive air transport network isincorporated into the overall network framework.
The cargo road mode of transport is often driven
by the lack of high quality alternatives. In theunderstanding of the cargo transport demand today
and that of the future, the key inputs are the macro
economic indicators. These indicators reflect theoverall development of each of the seven locality andthe propensity for cargo movement.

GDP
10.1%
12.4%
11.3%
9.7%
13.4%
6.3%
8.6%

Population
1.4%
0.1%
0.9%
2.1%
0.8%
0.7%
1.1%

Associated environmental concerns
The continued movement of cargo via the roadmode especially over long distances will also lead toa continued increase in emission gases. This is not inalignment with the overall Paris environmental
agreement. Whilst to some degree, such emissions
from within cities for personal mobility have been
contained. This is not the case for the movement ofcargo especially over long distances. Within thecontext of another large jurisdiction namely Egypt[5], the use of the road-based transport mode has
increased exponentially in the last few years.
Whilst this phenomenon has fulfilled a variety of
economic goals and expectations, unfettered growthis increasingly contributing to various negativeenvironmental impacts. This high level of usage in
Egypt is a historic consequence of pricing policies(such as the fuel subsidy), and “road focused” capital
works programs. There is a beginning of anunderstanding of the notion that a more balanced
approach to providing cargo mobility is desirable
especially in respect to the transportation of cargowithin the borders of Egypt.
For example, in another large country jurisdiction
such as Australia, over the period 1990 to 2006,
overall transport emissions grew by 27.4 per cent,however emissions from the movement of freightgrew by 40 per cent. Freight transport emissions now
contribute around four per cent of the nationalemissions total throughout the country and areforecast to more than treble to thirteen per cent by
2020 as reported in a recent freight transport review
paper [6].

Historical Activity Levels
Between 1998 and 2014, the Gross Domestic
Product (GDP), as measured in constant US dollars inthe base year of 2010 at market prices has grown at
an overall of 8.6% per annum. The regional
population has grown at 0.8% per annum. As depicted
in Table 1, there is differential growth by locality with
Myanmar registering the highest growth in GDP
closely following by the two Chinese provinces.
Thailand which is starting at a higher level of GDP
also registers significant economic growth over thisMETHODOLOGY
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SEE - Nagoya, Japan, Nov.12-14, 2018

Strategy Study[9]. Within the two provinces of China
there are 30 zones. In Myanmar, there are 40 zones
whilst Thailand has a total of 56 zones. There are 17
zones and 24 zones in Lao PDR and Cambodia
respectively. Finally, Viet Nam has 49 zones. Thus,
the model has a total of 216 internal zones. The total
number of zones is 254 including 38 external zonesof which 30 of the externals represent seaports.

The most commonly used tool for understanding
the movement of people or cargo throughout adefined geographical space is a transport model, [7]and [8]. A classic four step transport model isdeveloped as the analytical tool for the examinationof cargo movement through the region. The structure
for understanding movement within the Mekong isbuilt initially from the understanding the existingregional movement.
Of course, cargo movement does not happen in
isolation. The four-step procedure is followed bothfor the movement of cargo and people as depicted inFig. 2. In the final step, the network assignment
combines all movement across all transport network
infrastructure. In fact, the performance of the road
network is defined by both the movement of people
and cargo.

Fig. 2The Key Inputs – the Drivers of Future Demand
The two planning inputs, drivers of future cargo
movements are the regional GDP and the population.
The future economic and population projections are
based on trend data except for Thailand[10],Myanmar[11] and Vietnam[12]. In these three
localities, the economic and population projections
were derived from the national transport databases.
Regional GDP distribution
The Mekong wide GDP is projected to increase at
6.2% per annum until the year 2025 and estimated to
grow at 5% per annum thereafter until 2050. These
overall projected growth rates are in line with earlier
detailed historical growth rates[13] as well as thoseavailable from national transport databases. The key
important change in the future is the forecast
distribution balance of GDP. As earlier noted, thedifferential locality growth rates predict a change inregional economic distribution.
In 2015, as depicted in Fig 3., Thailand has nearly
40% of regional GDP. This is projected to decrease tounder 20% by 2050. This share of GDP is transferredto the two Chinese provinces and Myanmar by 2050.
By 2050, the two Chinese provinces are projected toincrease their share of overall GDP by 15% from an
initial 39% to 54% whereas Myanmar will increase
its share of regional GDP from 7% to 10%. The
remaining localities of Lao People’s Democratic
Republic (PDR), Cambodia, Vietnam are expected tomaintain approximately their existing share of GDP.

The regional model structure.

Data Preparation
The base input data are a collation of databases
available by locality held by the various responsible
agencies throughout the region. The master transport
network includes all known transport projects atpresent, both existing and proposed, that areincorporated into a master network with the potential
opening year of any new project provided as a
network parameter. At the same time the economic
and population datasets are prepared for the base time
horizon of 2015 and a future time horizon of 2050.
The data is prepared in detail at the level of traffic
analytical zone that correspond to administrative
boundaries with the amalgamation of smaller
administrative areas into a single traffic zone.
The zone system adopted for model is the same asthat for the earlier 2006 GMS Transport Sector
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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 3Distribution of GDP by locality.

The parameters in the equations vary by locality
and commodity group. The five commodity groups
were summarized based on the international
Harmonized System codes also referred to as simply
the HS codes. These codes are an internationallystandardized system of names and numbers to
identify an individual product. The code is an 8-digit
number but broad classifications are developed using
the first two digits of the code.
Broadly the five commodity categories innumerical order one through to five are agriculture,processed food, wood products, chemicals andmiscellaneous goods. The link of the five commodity
categories to the Harmonized System of coding ispresented in Table 2 which tabulates the first twodigits of the HS code against the commodity category.

Regional population Distribution
The regional population is projected to increase at
0.8% over the overall time horizon between 2015and
2050. Between 2015 and 2050, the regional
population is anticipated to grow from 340 million tosome 453 million people thus forming a potentiallysignificant trading block. The regional population
distribution is depicted in Fig 4.
40

Percentage

30

Yr:2015
Yr:2050

20

Table 2 Cargo commodity category

100Locality

Fig. 4

Category

Description

1
2
3
4
3
4
5

Agricultural
Processed Food
Chemical/Mineral
Wood/Skins
Chemical/Mineral
Wood/Skins
Miscellaneous

HS Code
Start
End
1
15
16
24
25
40
41
49
50
63
64
67
68
97

Distribution of Population by locality.
THE ANALYSIS

Unlike GDP, the population distribution isunlikely to change significantly. The regional
population share of Viet Nam increases from 28% to32%. The regional population share of Thailand
decreases by approximately three percent. Thechange in distribution in all other localities is less than2%.

The focus of this research as stated earlier is on
the modal allocation and the key input parametersnamely the population and GDP. However, prior tothe modal allocation step, there are the two earlier
steps associated with trip generation and distributionof cargo movement. Cargo movement generations are
estimated by traffic zone via a relationship linking
population and GDP per capita in a series of linear
regression equations derived for each locality
separately.
Cargo trip distribution used the Fratar growth
factor distribution method [14] that takes as a base an
existing distribution patterns sourced from an earlier
Mekong study [9]. The trip distribution is across all
localities so that there are not separate trip
distribution procedures via locality.
For the mode split step, the commodity
movement cost and travel times are the key inputs
into the freight mode split model. The mode split
structure for freight is a hierarchical three-level mode
split logit model as depicted in Fig 5. The total cargo
trips were distributed across four modes. At the firstlevel, coastal trips are separated while at the second
level, inland water transport trips are separated, withthe final level being the allocation of movement
between road and rail. In many cases, the mode
choices were limited to road and rail since there was

Impact of Distribution Change
The change in distribution between localities isimportant because such change will impact the likely
future pattern exchange of cargo movement between
the localities.
The Structure of Cargo Movement
For the analysis of cargo movements, the key
modes represented within the model are road, rail,
inland waterways transport and coastal shipping. The
model developed is known as the Mekong Regional
Transport Model henceforth referred to simply as the
MRTM.
Cargo movement is divided into 5 commodity
classifications. The MRTM was developed to
produce forecasts of passenger and 5 categories ofcargo movement by mode for the time horizons of thebase year of 2015 and two future horizons of 2025
and 2050.
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SEE - Nagoya, Japan, Nov.12-14, 2018

no logical route via other modes.
The MRTM’s master transport network includes
all known transport projects at present, both existingand proposed, that are incorporated into a master
network with the potential opening year of any new
project provided as a network parameter. In thismanner, there is an inbuilt flexibility as it is actual
possible to develop the network other than for the two
future time horizons of 2025 and 2050.
The structure of the binary logit equations isshown in Eq. 1.

road network except for access to the non-road
network (e.g. truck to rail).
In the case of truck trips there was also an impliedback loading factor to allow for trucks returning fromtheir destination without any load. The non-road trips
are then assigned to their respective networks such asrail. This results in a final network that representd
travel across all modes.
Table 4 Scale factors by commodity category
Category

Fig. 5

1
2
3
4
5
1
2
3
4
5
1
2
3
4
5

Modal Allocation Structure

The cost of travel on alternative modes is referred
to as the generalized cost of travel and is a function oftime and cost.

P1 =

expV1
expV1 + expV2

Equation
Level
1
1
1
1
1
2
2
2
2
2
3
3
3
3
3

Time

Cost

-0.2244-0.0004-0.0858-0.0355-0.0355-0.0194-0.0387-0.0732-0.0169-0.0173-0.3892-0.2078-0.176-0.5941-0.5891-0.0001-0.0004-0.0004-0.0004-0.0004-0.0001-0.0004-0.0006-0.0004-0.0001-0.0008-0.0003-0.0008-0.0034-0.0006(1)
Passenger vehicles and trucks share the road
networks. For the traffic movements assigned to theroad network, there is a feedback loop to adjust theroad traffic speed until there is equilibrium across the
network (i.e. that assumed input speeds match theactual output speeds after the traffic assignment). The
travel time on the road network impacts the mode
split of both person and cargo movement. All theassigned trips across all networks are combined intoa single output network following the equilibrium
procedure.
One potential bottleneck for the movement ofcargo between the different localities is both theformality and physical barriers at international bordercrossing points. This is currently being addressed byvarious cross regional organizations such as The
Greater Mekong Rail Association. In the distantfuture scenario, these are resolved to facilitate
economic prosperity.

Equation (1) defines the probability of using mode
1 as opposed to mode 2 whereas V1 and V2 are thegeneralized travel costs associated with modes 1 and
2 respectively.
The variables in the determination of generalized
travel cost namely travel time and the cost are
weighted by scale factors. These scale factors arepresented in Table 4 by commodity category for eachlevel of the modal analysis. The cost of travel by thevarious modes of travel was determined by locality.
The final step was the assignment or the allocationof the flow of people and freight to air, road, rail,
inland waterway and coastal shipping networks. The
final network travel times across the road network
were estimated following a capacity restrained
assignment.
In the case of the road network, the movement of
persons by car and bus were converted into equivalentpassenger car units together with the cargo-carrying
trucks on the network. The impact of person andcargo trips were combined in consideration of the
impact on the shared road network.
It was necessary to convert cargo movements
allocated to road network into vehicles via loadfactors. The remaining freight trips do not use the

The Model Validation
The validation of the model was undertaken fromdata sources not currently used as input data in themodel development. Two such comparisons are
discussed here. The base output from combined roadvehicle movement in 2015 was validated against
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SEE - Nagoya, Japan, Nov.12-14, 2018

screen line traffic counts in Thailand in the north-west
and south-east where such traffic has the potential to
be travelling to locality crossing points. The
screenline comparison of vehicle traffic was within
10%.
A Big Data comparison was made between themodel estimation of the overall trade between
Thailand and the two localities of Yunnan andGuangxi in China via a comparison of the two custom
databases. The estimation of trade between the two
Chinese localities and Thailand is 1,409 tonnes on
average per day in 2015 compared to an observed
volume of 1,400 tonnes per day. The comparison is
good.

50

2015
2050

Percentage

40
30
20
10
0

RESULTS AND CONCLUSIONS

LocalityIn the current situation incorporating all
infrastructure proposals, there is a small modal shift
in terms of tonne-kilometes of travel. However, this
implies that significant more effort is required toensure modal shift away from the road sector.

Fig. 6

Distribution of cargo travel by locality

In the current proposal incorporating all new rail
infrastructure proposals of the seven localities, there
is a small modal shift in the movement of cargo asreported in Table 5. Truck remains the dominantmode of transport across the region.
The modal share of the alternative non-roadmodes in combination increases nearly four times.
The modal share increases of rail alone increases bynearly 150%. There is in this case also an estimatedshift to IWT as a direct result of increased roadcongestion.

The Future Result
Cargo movement as measured in terms of tonnekilometeres of travel is estimated to grow at 4.9 %per annum between 2015 and 2025. However, as aresult of the changing interaction between theeconomic parameters, the differential distribution ofcargo across localities changes as depicted in Fig 6.
In 2015, Thailand has nearly 50% of regionalcargo movements. This is projected to decrease tounder 40% by 2050. This share of cargo is transferred
across all localities by 2050. By 2050, the two
Chinese provinces are projected to increase theirshare of overall cargo movements by 40% from an
initial 14% to 20% whereas Myanmar will decrease
its share of regional movement from 12% to 9%. The
localities of Lao People’s Democratic Republic(PDR) and Vietnam are expected to increase
approximately their share of cargo movement.

Table 5 Modal shift between 2015 and 2050
Mode
Truck
Rail
IWT
Sea

2015
98.43%
0.78%
0.18%
0.62%

2050
96.29%
1.30%
0.24%
2.17%

Another issue that arises from the continual
maintenance of the high cargo modal split towards
road movement is that by 2050, there is an estimatedsignificant change in the distribution of road traffic
across the region. As depicted in Fig. 7, by 2050, that
there is a dramatic shift in the sharing of regional road
space in terms of road movement as measured interms of passenger car units.
Today, trucks account 23% of all movements
across the regional road network, the model
developed in this research suggests that this will riseto 45% in a future scenario. This is a significant
change and is likely to have an impact on traffic
accidents.

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SEE - Nagoya, Japan, Nov.12-14, 201870

Yr:201560
Percentage

In this test case, the cost differential is changed
with an increase in the cost of cargo movement bytruck whilst at the same decreasing the cost of cargo
movement by rail. This suggests that there is apotential for the truck modal share of the movementof cargo across the Mekong to fall below the 90%
level.

Yr:2050

50
40
30
20

Feasibility of Green Cargo Shift10

When considering the development of new
infrastructure in the Mekong Region to assist in thetransfer to Green freight movement, the desired
modal split should be pursued in a realistic manner
taking the growth trend in road cargo into account.
Large increases in the sector capability of the nonroad sector are implementable but difficult from apractical and economic point of view.
The long-term forecast for the region
demographically in accordance with the various
locality economic forecasts demonstrates via
infrastructure development that it is possible to halt
the fact that the road sector for cargo movements wascontinuing to approach the one hundred percent mark.
Of course such movement away from the road sector
is not achievable overnight so that the mathematicalmodel considers a thirty five year time frame forintermodal shift[15].
The dilemma is the establishment of Green Cargo
Movement and the shifting of cargo movements fromthe dominant road mode to alternative modes. The
development of the mathematical model for cargo
movement has enabled the transport planner
practitioner to advance the understanding of cargo
movements and provide a numerical framework for
the understanding the impact of a green cargo modal

0
Car

Fig. 7

Bus
Mode

Truck

Road Usage (pcu-km of travel)

The Future Result-Ultimate Scenario
In the case of an ultimate rail scenario such as the
double tracking of the complete existing region rail
together with improved border crossings, there is in
this case an ultimate shift in cargo movement. Truckremains the dominant mode of transport across theregion. The modal share of the alternative modes incombination increases nearly seven times.
The modal share increase in rail alone is of theorder of five times higher as depicted in Table 6. The
transport model prepared as part of this research is ananalytical tool that is an initial starting point for
researchers to understand the mobility of cargothroughout the Mekong.
Table 6 Modal comparison – increase infrastructure
Mode
Truck
Rail
IWT
Sea

2015
98.43%
0.78%
0.18%
0.62%

2050
92.62%
5.09%
0.46%
1.83%

ACKNOWLEDGEMENTS
The authors acknowledge the support by thegovernment agencies within the Mekong and the
Asian Development Bank in the preparation ofexisting datasets and the development of theanalytical tools.
All ideas and views expressed in this paper are
those of the authors. They do not necessarily reflect
any of the sponsoring authorities of projects discussed
in this paper or any organizations associated with therespective authors.

If the localities of the Mekong are to consider
modal shift away from the road there will likely need
to be a change in the pricing structure of the
movement of cargo by road and rail. Such a change
in cost is reported in a test case in Table 7.
Table 7 Modal comparison – cost differential
Mode
Truck
Rail
IWT
Sea

2015
98.43%
0.78%
0.18%
0.62%

2050
89.48%
7.90%
0.45%
2.15%

REFERENCES[1]

Colliers International, European Internal
Demand Shifts, in European Logistics Report
2016.
[2] Bartocci, A. and M. Pisani, “Green” fuel tax onprivate transportation services and subsidies toelectric energy. A model-based assessment for
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SEE - Nagoya, Japan, Nov.12-14, 2018

[3]

[4]

[5]

[6]
[7]

[8]
[9]

the main European countries. Energy
Economics, 2013. 40: p. S32-S57.
Klein, D.R., et al., The Paris agreement on
climate change : analysis and commentary. 2017,
Oxford, United Kingdom: Oxford University
Press. xxxii, 435 pages.
Hossain, M., R. Hales, and T. Sarker, Pathways
to a sustainable economy : bridging the gap
between Paris climate change commitments andnet zero emissions. xviii, 225 pages.
Johnstone, L. and V. Ratanavaraha, Green
Freight Movement: The Dilemma of the
Shifting of Road Freight to Alternatives.
Transportation Research Procedia, 2017. 21: p.
154-168.
Eren, C., Freight Transport and Climate Change.
Total Environmental Centre Inc, 2008.
Johnstone, L.C. and N. Chancharoen Workshop& Lectures on Sustainable Multimodal
Transport & Urban Development: with
Evaluation of Transport Projects, Land Use Mix
and Supply Controls., 2010, Griffith University,
Australia.
Johnstone L. 2015. Transport Demand Modeling
Methods Training., Asian Development Bank.
Asian Development Bank., Greater Mekong
Subregion Transport Sector Study. 2006[10] Office of Transport and Traffic Policy andPlanning.,2014., Transport Data and Model
Integrated with Multimodal and Logistics(TDL2). 2014.
[11] JICA,2014., The Survey Program for the
National Transport Development Plan in the
Republic of the Union of Myanmar(2014).,
prepared by Japan International Cooperation
Agency(JICA).
[12] JICA, 2009., The Comprehensive Study on the
Sustainable Development of Transport System
in Vietnam (VITRANSS 2)., prepared by Japan
International Cooperation Agency(JICA).
[13] Asian Development Bank., Greater Mekong
Subregion Statistics on Growth, Infrastructure,
and Trade, 2nd. Edition, Editor. 2016. p. 5-25.
[14] Horowitz,
A., J., Origin Destination
Disaggregation Using Bipropotional Least
Squares Estimation for Truck Forecasting.
University of Wisconsin-Milwauke, 2009. 09(1).
[15] Li, L., R.R. Negenborn, and B. De Schutter,
Intermodal freight transport planning – A
recedinghorizoncontrol
approach.
Transportation Research Part C: Emerging
Technologies, 2015. 60: p. 77-95.

519

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECT OF FLY ASH FINENESS ON COMPRESSIVE, FLEXURALAND SHEAR STRENGTHS OF HIGH STRENGTH-HIGH VOLUMEFLY ASH JOINTING MORTAR
Patcharapol Posi1, Pornnapa Kasemsiri2, Surasit Lertnimoolchai3 and Prinya Chindaprasirt4*

1

Department of Civil Engineering, Faculty of Engineering, Rajamangala University of Technology Isan
Khon Kaen Campus, Khon Kaen, 40000, Thailand
2
Sustainable Infrastructure Research and Development Center Department of Chemical Engineering,
Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, Thailand.
3Managing Director, Concrete Precision Unique, Udornthani 41000, Thailand
4
Sustainable Infrastructure Research and Development Center Department of Civil Engineering, Faculty ofEngineering, Khon Kaen University, Khon Kaen, 40002, Thailand, and Academy of Science, the Royal
Society of Thailand, Dusit, Bangkok, Thailand 10300

ABSTRACTIn this research, the compressive, flexural, and shear bond strengths of high strength-high volume fly ash mortar
containing high calcium fly ash (HCFA) of various finenesses were studied. The mortars were made from ordinary
Portland cement (OPC), HCFA, sand, water, and Type D admixture. The HCFA was from Mae Moh power stationin the north of Thailand. Three types of HCFA fineness viz., as-received coarse fly ash (CF), medium fineness flyash (MF, passed sieved No. 100), and fine fly ash (FF, passed sieve No. 200) were used to replace OPC at thelevels of 0-70 % by weight of binder. The results showed that the high strength-high volume fly ash mortars withsatisfactory 28-day compressive strengths between 70.0 and 114.0 MPa, shear bond strengths between 7.2 and18.0 MPa, and flexural strengths between 15.9 and 27.6 MPa were obtained. Test results also indicated that theuse of FF gave significantly higher strengths than the use of CF and MF. Specifically, the compressive strength ofmortar containing 50%FF was very high at 110.0 MPa. The FF could thus be used to improve the strengths of highvolume fly ash mortar for uses in various architectural and structural works requiring high strength products.

Keywords: High calcium fly ash, Fly ash fineness, High volume fly ash, High strength mortar, Shear bond strength

the burning of calcareous material, the production of
cement thus produces a large amount of carbon
dioxide. For every ton of Portland cement coming outof the furnace, almost 1 ton of carbon dioxide (CO2)
was released into the atmosphere [2].

INTRODUCTION
Currently, the construction of wall in building
mainly uses ready-made concrete materials in theform of concrete blocks. In the past, the concrete
blocks for wall possesses low strength and thus theuse is relatively limited. For diverse usage, thestrength development is substantially improved suchthat it can be used in structural work as well [1].
One of the important use of the block is the
preformed wall for the housing units. The ready-madepreformed wall can be fabricated at the concrete plant
and transport to the construction site. This drasticallyreduces the time required for the construction ofbuilding or housing complex. This results in rapid
construction using concrete block panels as shown in
Fig. 1. The joining of the blocks in making preformed
wall required a high strength mortar such that the wall
can be transported to the site without damage.
To develop a sufficiently high strength mortar, itis necessary to use a high cement content and thisresults in high cost. In addition, the production of
cement is an energy intensive process. Coupled with

Figure 1. The rapid construction of wall using
preformed concrete blocks

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SEE - Nagoya, Japan, Nov.12-14, 2018

It is therefore important to reduce this greenhousegas emissions into the atmosphere by using theenvironmental friendly cementitious material
products [3] or alternatively use less cement with theuse of high volume pozzolanic material to replace
Portland cement. The available fly ash in large
quantity is the high calcium fly ash from Mae Moh
Power station in the north of Thailand which has beenshown to be a good pozzolan. This amount of calcium
is rather high and increases with the increasing depthof coal mining [4]. The use of this fly ash in concrete
increases the porosity, but the average pore size is
reduced [5, 6] and the interfacial zone between
aggregate and matrix is improved [7].
In order to utilize the fly ashes effectively, thecoarse portions of fly ashes have to be processed.
Grinding and classification can be used to increase
the fineness of the fly ash. It has been demonstrated
that the compressive strength of concrete with fly ash
can be improved by using finer fly ashes [8-13]. In
addition, the use of fine fly ash with spherical particle
and smooth surface result in some better mechanicalproperties i.e. to increase the strength and improve thedurability of mortar and concrete compared to thecoarse fly ash [8-10]. The shrinkage is also in reduced
compared to the control but slightly increased
compared to the use of coarser fly ash [14].
Therefore, in this study, the use of high calcium
fly ash with different finesses to improve the strengthof high volume fly ash jointing mortar is studied. The
as-received fly ash, the medium fineness fly ash
passed sieve No. 100 and the fine fly ash passed sieve
No. 200 were used to produce high strength mortar.
The results will enable the use of fly ash more
effectively through the classification and high volume
usage with ensured high strength.

amorphous content with relatively large hump around22-38 ᵒ2Ꝋ.
Table 1. The physical properties of materials
Materials

Sand

OPC

HCFA

Specific gravity
Median particle size (µm)
Fineness modulus

2.61
2.65

3.15
14.6
-

2.66
18.6
-

Unit weight (kg/m3)

1360

1440

-

Water absorption (%)

1.17

-

-

Figure 2. The morphology of HCFA by SEM

EXPERIMENTAL PROGRAM
Materials
Materials used in this research consisted ofordinary Portland cement (OPC), river sand, waterand high calcium fly ash (HCFA). The HCFA was theby-products from Mae Moh power station in
Lampang province, northern Thailand. It wasclassified to three lots of HCFA fineness viz., asreceived coarse fly ash (CF), medium fineness fly ash
passed sieved No. 100 (MF), and fine fly ash passed
sieve No. 200 (FF). The physical properties ofmaterials are shown in Table 1.
The morphology of HCFA by SEM as shown in
Fig. 2 indicated that the shape of HCFA was sphericalwith smooth surface. The chemical compositions of
HCFA are shown in Table 2. The specific gravity of
HCFA was 2.66 with median particle size of 18.6 µm.
The HCFA consisted of a high content of 36.20%
SiO2, 15.52% Al2O3, 14.25% Fe2O3, and 22.57% CaO
with the loss on ignition (LOI) of 0.88%. The XRD
of HCFA as shown in Fig. 3 indicated the highFigure 3. The XRD of HCFA. M-Maghemite: Fe2O3;
Fe3O4; H-Hematite; A-Anhydrite; C-Calcium Oxide;
Q-Quartz.
Table 2. Chemical composition of materials (byweight)Chemical
HCFA
OPC
compositions (%)
SiO2
36.20
20.8
Al2O3
15.52
4.7
Fe2O3
14.25
3.4
CaO
22.57
65.3
K2O
1.63
0.4
Na2O
0.33
0.1
SO3
8.9
2.7
LOI
0.88
0.9

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SEE - Nagoya, Japan, Nov.12-14, 2018

and mixed for 3 minutes to obtain a homogenous
mixture.
The fresh high strength mortar was placed into
50x50x50 mm cube molds, 75x75x150 mm and
75x75x300 mm prism molds. The specimens weredemolded at 1 day and stored in water.

Mix proportion
The HCFA contents
To study the effect of HCFA fineness, as-received
coarse fly ash (CF), medium fineness fly ash passed
sieved No. 100 (MF), and fine fly ash passed sieve
No. 200 (FF) were used to replace OPC at the levelsof 0-70 % by weight for the manufacturing of highstrength jointing mortars.
The compressive strength, flexural and shear bondstrengths of high volume fly ash-high strength mortar
were determined.

Details of test
Compressive strength and density
The cube specimens size 50x50x50 mm were
tested to determine the compressive strength inaccordance with ASTM C109/C109M-16a [15]. The
reported compressive strengths were the average ofthree samples.
Shear bond strength
The prism specimens size 75x75x150 mm were
tested to determine the shear bond strength inaccordance with ASTM C882/C822M [16]. The
reported shear bond strength was the average of threesamples. The sample bond strength of high volume
fly ash-high strength mortar with concrete by slant
shear are shown in Fig. 4. The 28 day-strength ofdummy concrete was 70.0 MPa. The contact surfaceof the dummy concrete was cut surface by diamondsaw.
Flexural strength
The prism specimens size 75x75x300 mm were
tested to determine the flexural strength in accordancewith ASTM C293-02 [17]. The reported flexuralstrength was the average of three samples.

a. Dummy Bottom Section

RESULTS AND DISCUSSIONS
Compressive strength
120.0

Compressive streng (MPa)

100.0
80.0
60.0
40.0
20.0
0.0
CF
MF
FF

0%
94.7
94.7
94.7

10%
100.3
103.6
104.1

20%
102.6
106.6
113.0

30%
103.3
105.3
114.0

40%
92.4
100.0
109.3

50%
96.2
93.0
110.6

60%
79.6
86.0
94.6

70%
74.0
83.2
91.6

b. testing of shear bond strength
Figure 5. Compressive strength of high volume fly
ash-high strength mortar at 28 days

Figure 4. The shear bond strength test of highvolume fly ash-high strength mortar

The results of compressive strength of highvolume fly ash-high strength mortar are shown in Fig.
5. The compressive strength increased withincreasing HCFA content from 0 to 30 % by weight.
The compressive strength development from all fly
ash was quite good, especially the fine fly ash. At low
replacement level, the compressive strengths of fly
ash mortar were higher than mortar without fly ash

Details of Mixing
All mixtures were made with binder to sand ratioof 1:0.33, superplasticizer (SP) of 0.50 % of binder
and water to binder ratio of 0.24. For mixing, OPC
and HCFA were firstly mixed together until the
mixture was homogenous. Next, sand was added andmixed for 5 min. Finally, water and SP were added

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SEE - Nagoya, Japan, Nov.12-14, 2018

due to the pozzolanic reaction of fly ash and thefilling effect [10]. In contrast, for the high volume
HCFA replacement, the strength started to decrease
with more than 30 % replacement. With more than
50% replacement the compressive strengths were lessthan that of the control. For example, the compressive
strengths at 28 days of mixes with CF with volume of
HCFA of 0, 10, 20, 30, 40, 50, 60, and 70 % by weight
were 94.7, 100.3, 102.6, 103.3, 92.4, 96.2, 79.6, and74.0 MPa, respectively.
With regards to types of HCFA fineness, thecompressive strength increased with increasing
HCFA fineness. The filling effect of fly ash
contribute to the relatively good compressive strength
development of the concrete containing HCFA. The
used of finer fly ash resulted in further enhancementof the compressive of concrete [8-10]. For example,
the compressive strengths at 28 days of 30 % fly ashwith HCFA fineness of CF, MF, and FF were 103.3,
105.3, and 114.0 MPa, respectively.

With regards to types of HCFA fineness, the shear
bond strength increased with increasing HCFA
fineness. For example, the shear bond strength at 28
days of 30 % fly ash with HCFA fineness of CF, MF,
and FF were 12.8, 15.1, and 16.9 MPa, respectively.
This is because the high fineness HCFA has highsurface area resulting in the high internal bondstrength of the cement paste [18] and thus resulted in
the high shear bond strength between high strengthmortar and old concrete substrate.

Shear bond strengtha. 10 % HCFA

b. 20 % HCFAc. 30 % HCFA

d. 40 % HCFA

e. 50 % HCFA

f. 70 % HCFA

20.0

Shear bond strength (MPa)

18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
CF
MF
FF

0%
8.2
8.2
8.2

10%
7.8
8.0
14.0

20%
10.6
12.4
14.2

30%
12.8
15.1
16.9

40%
10.1
13.3
17.6

50%
12.4
12.9
17.9

60%
9.8
12.2
10.6

70%
8.6
12.6
7.2

Figure 6. Shear bond strength of high volume fly ashhigh strength mortar at 28 days
The results of 30º slant shear bond strength test ofhigh volume fly ash-high strength mortar are shownin Fig. 6. For the mixes with CF and MF, the shear
bond strength increased with the increasing volumeof HCFA from 0-30 % fly ash. For example, the shear
bond strength at 28 days of mixes with MF withvolume of HCFA of 0, 10, 20, 30, 40, 50, 60, and 70% by weight were 8.2, 7.8, 10.6, 12.8, 10.2, 12.4, 9.8,
and 8.6 MPa, respectively. The increase in thereplacement levels resulted in a drop in the strengthof the samples. However, the results also indicatedthat the strength of the 70% fly ash mortar was stillcomparable to that of the control. For the fine fly ash,the shear bond strength of FF increased with theincreasing volume of HCFA from 0-50 %replacement levels. The increased shear bond strength
was due to increased compressive strength with theincrease in pozzolanic reaction of fly ash and thefilling effect of the fine fly ash particles [9].

Figure 7. The failure of shear bond strength
In addition, the fracture characteristics of slant
shear prisms are shown in Fig. 7. The slant shear bondprisms failed in the monolithic mode where cracks
were formed in both section of high strength mortar
and old concrete substrate [19] which indicated therelative high resistance to damage of high strengthmortar and high bonding between the two surfaces.
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SEE - Nagoya, Japan, Nov.12-14, 2018

optimum replacement level of fine FF was increased
to 50 % suggesting that a larger amount fly ash could
be incorporated providing that its particle was fine.
4. For the flexural strength, the trend of results
was similar to the improvements in compressive andshear bond strengths. The improvement with theincorporation of FF was more evident in the flexuralstrength. The improvement represented an average of
67 % from base line for the 10 % replacement level.
5. The results showed that high strength-highvolume fly ash mortars with satisfactory 28-daycompressive strengths of between 70 and 114 MPa,shear bond strength between 7.2 and 18.0 MPa, andflexural strength between 15.9 and 27.6 MPa wereobtained. Moreover, test results indicated that the useof FF gave significantly higher strengths than the useof CF and MF. The FF could thus be used to improve
the strengths of OPC mortar and used as an alternative
mortar for various architectural and structural works
requiring high strength products.

Flexural strengths
The results of flexural strength of high volume fly
ash-high strength mortar are shown in Fig. 8. For themixes with CF and MF, the flexural strengths
increased with the incorporation of the fly ash. For
example, the flexural strength at 28 days of mixes
with MF with volume of HCFA of 0, 10, 20, 30, 40,
50, 60, and 70 % by weight were 15.9, 21.1, 18.3,
18.9, 18.8, 18.4, 19.4, and 19.0 MPa, respectively.
Moreover, the flexural strength of FF were further
increased with the incorporation of FF especially at
the 10 – 30 % replacement levels. Normally, the trendof flexural strengths was similar to those ofcompressive strengths [20]. In this case, with theincorporation of fly ash, the flexural strengths were
improved slightly better than those of compressive
strengths.
With regards to types of HCFA fineness, theflexural strength of base line was 15.9 MPa and theflexural strength increased with increasing of HCFA
fineness. For example, the flexural strength at 28 daysof 10 % fly ash with HCFA fineness of CF, MF, andFF were 17.5, 21.1, and 26.6 MPa, respectively andrepresenting an average improvement of 67 % frombase line. The increasing of flexural strength was dueto the increase in the reaction products from increased
reaction of fine HCFA. This was associated with the
improvement of compressive strength and shear bondstrength of high strength mortar which led to overall
improvement in the flexural strength [19].

ACKNOWLEDGEMENT
This work was financially supported by theConcrete Precision Unique, Udornthani, Thailand.
The support of the Faculty of Engineering,
Rajamangala University of Technology Isan Khon
Kaen Campus, and the Thailand Research Fund
(TRF) under the TRF Distinguished Research
Professor Grant No. DPG6180002 is gratefully
acknowledged here.

30.0

REFERENCES

Flexural strength (MPa)

25.0
20.0

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15.0
10.0
5.0
0.0
CF
MF
FF

0%
15.9
15.9
15.9

10%
17.5
21.1
26.2

20%
17.8
18.3
25.7

30%
15.4
18.9
27.6

40%
18.0
18.8
20.7

50%
16.9
18.4
20.3

60%
19.1
19.4
25.4

70%
18.2
19.0
21.3

Figure 8. Flexural strengths of high volume fly ashhigh strength mortar at 28 days
CONCLUSIONS
Based on the obtained data, the following
conclusions can be drawn:
1. The increasing in HCFA fineness resulted in the
improvement of the compressive, shear bond andflexural strengths of mortar.
2. For compressive strength, the optimum volumeof HCFA was 30 % with substantial increase incompressive strength.
3. For shear bond strength, the behavior was
similar to that of compressive strength. However, the524

SEE - Nagoya, Japan, Nov.12-14, 2018

[6] Chindaprasirt P, Jaturapitakkul C, Sinsiri
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Cement and Concrete Research, Vol. 28,Issue 9,1998, pp. 1217-22.
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Homwuttiwong
S,
Sirivivatnanon V.,Influence of fly ash fineness on
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Sirivivatnanon V.,Influence of fly ash fineness on thechloride penetration of concrete. Construction and
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[11] Payá J, Monzó J, Borrachero MV, Peris E,
González-López E.,Mechanical treatments of fly
ashes. Part III: Studies on strength development ofground fly ashes (GFA) — Cement mortars. Cement
and Concrete Research, Vol. 27,Issue 9, 1997, pp.
1365-77.
[12] Kiattikomol K, Jaturapitakkul C, Songpiriyakij
S, Chutubtim S.,A study of ground coarse fly ashes
with different finenesses from various sources as
pozzolanic materials. Cement and Concrete
Composites, Vol. 23,Issue 4, 2001, pp. 335-43.
[13] Payá J, Monzó J, Borrachero MV, Peris-Mora E,
Amahjour F.,Mechanical treatment of fly ashes: Part
IV. Strength development of ground fly ash-cement
mortars cured at different temperatures. Cement andConcrete Research, Vol. 30,Issue 4, 2000, pp. 543-51.

[14] Vimonsatit V, Chindaprasirt P, Ruangsiriyakul
S, Sata V., Influence of fly ash fineness on waterrequirement and shrinkage of blended cement
mortars2015.
[15] ASTM C109/C109M-16a.Standard Test Methodof Compressive Strength of Hydrualic Cement
Mortars (using 2-in. or [50 mm] cube speciments).
Annual Book of ASTM Standard, Vol.
Vol.04.01,Issue, 2016, pp.
[16] ASTM C882/C882M.Standard Test Method forBond Strength of Epoxy-Resin System Used with
Concrete by Slant Shear. Annual Book of ASTM
Standard, Vol. vol. 04.02,Issue, 2005, pp.
[17] ASTM C293-02.Standard Test Method for
Fkexural Strength of Concrete (Using Simple Beamwith Center-Point Loading). Annual Book of ASTM
Standard, Vol. vol.04.02,Issue, 2002, pp.
[18] Husem M.,The effects of bond strengths between
lightweight
andordinary
aggregate-mortar,
aggregate-cement paste on the mechanical propertiesof concrete. Materials Science and Engineering: A,
Vol. 363,Issue 1–2, 2003, pp. 152-8.
[19] Phoo-ngernkham T, Sata V, Hanjitsuwan S,
Ridtirud C, Hatanaka S, Chindaprasirt P.,Highcalcium fly ash geopolymer mortar containing
Portland cement for use as repair material.
Construction and Building Materials, Vol. 98,Issue,
2015, pp. 482-8.
[20] Arif E, Clark MW, Lake N.,Sugar cane bagasseash from a high efficiency co-generation boiler:
Applications in cement and mortar production.
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2016, pp. 287-97.

525

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

THE USE OF BOTTOM ASH TO IMPROVE THE STRENGTH OF
POOR SUBBASE LATERITIC SOIL IN ROAD CONSTRUCTION
Chotikan Ratchakrom1
Faculty of Civil Engineering Technology, Valaya Alongkorn Rajabhat University under the Royal
Patronage, Thailand

1

ABSTRACTThis research investigates the use of bottom ash to improve the unconfined compressive strength of poor
subbase. Lateritic soil that used in test represented weak subbase soil in road construction. This research
performed on lateritic soil mixed with cement 1-1.5%, kaolin 0.5-1% and the different percentages of bottom ash
was between 2-8% by weight of soil. The unconfined compressive strength of the soil improvement tends toincrease with an increase in the amount of bottom ash. However, the unconfined compressive strength of thesamples slightly increased when the amount of bottom ash was exceeded 6%. The results demonstrated bottom
ash can develop the early strength of soil. As shown in the results of soil mixed with cement 1.5%, kaolin 1%,
and bottom ash 6-8% can be developed the strength near the soil mixed with cement 3% in 7 days. Moreover, theaddition 6% of bottom ash and 0.5% of kaolin in the soil samples mixed with cement 1.5% can be increased thecompressive strength 87% of the samples without bottom ash and kaolin. The required strength of subbase
improvement should more than 689 kPa at the curing time 7 days. The results demonstrated the strength of soil
mixed with 1.5% cement, 0.5% kaolin and 4-8% bottom ash was higher than the required strength. Therefore,bottom ash can develop the strength of poor subbase and reduced the utilized amount of cement to improve thestrength of soil.
Keywords: Lateritic soil, Bottom ash, Compressive strength, Kaolin, Subbase

Ash removed from the base of the furnace istermed bottom ash [3]. Bottom ash (BA) is a solid
waste available in Mae Moh power plant in the northof Thailand is about 0.8 million tons and is disposedof a landfill near the power plant [4]. It is coarser
than fly ash, ranging in size from fine sand to gravel[3]. Bottom ash is larger in size and very irregular,
containing pores and cavities [5]. Ground to a proper
fineness, bottom ash can be used as a pozzolan that
produces relative strength [6]. The chemicalcompositions of bottom ash were 39.3% SiO2,
21.3% Al2O3, Fe2O3, 2.1% K2O, 16.5% CaO, 1.0%
Na2O and 1.4% loss on ignition. The bottom ash has
increased pozzolanic activity and used to partiallyreplace Portland cement. The utilization of bottom
ash as a cementitious a partial replacement of
cement is possible [4].
Bottom ash serves well as structural fill andconstruction [3]. A variety of research on themobilization of coal bottom ash for use as the
cementitious material has been utilized. The bottom
ash has increased the pozzolanic activity [7], [8].
Therefore, many types of research have been used
the bottom ash as fine aggregate in concrete [9],asphaltic [10]. On the other hand, the bottom ash caninvolve clay minerals and increases the value of
supporting capacity of the clay and increasing thecompressive strength value [11].
This paper investigated the use of bottom ash

INTRODUCTION
The lateritic soil has been used in road
construction of Thailand and developing in the ruralarea. The subbase of road constructions wasconstructed by lateritic soil. However, it's become
the realize problem of lateritic soil. This is because
the poor lateritic soil is low compressive strengthand poor durability. Therefore, the bearing capacityof poor subbase was lower than the minimum
strength requirement for road construction.
Subsequently, the rain infiltration or the water
inundates the subbase can be causing the roaddamage. [1], [2]. This problem represents toemphasis for improvement in engineering propertiesof lateritic soil such as compressive strength,
durability, and permeability [2].
The most commonly used additive for soil
stabilization is ordinary Portland cement. To build a
subbase with cement stabilized ash alone is not yet
common, but this is one of the high volume ash
application being promoted by ash producers [3].
The use of ash or the pozzolanic materials combinedwith cement to improve the strength of soil can be
reduced the cost of the soil stabilization. Therefore,
this study investigated on the use of bottom ash,which is the by-product from Mae Moh power plant
to improve the strength of poor subbase.

526

SEE - Nagoya, Japan, Nov.12-14, 2018combined with cement which a partial replacementby kaolin to improve the strength of the poor qualityof soils. There are many of additive that has beentested the effect to develop the engineering
properties of lateritic soil. In order to reduce costs byreplacing some cementations stabilizers with noncementations additives [12, 13, 14]. Kaolin soil is amineral of soil, which some of these noncement
additives. In chemical terms, kaolin has many
cementing materials consists of SiO2, Al2O3, andFe2O3. These elements can improvement bonding,
durability and stabilization of soil. [15].
The objective of this paper is investigating theuse of bottom ash to improve the strength of poor
subbase. In order to increase the strength of subbase
higher than the required strength which suggested by
the Thailand Department of highways. The
unconfined compressive strength of the soil
improvement should be more than 689 kPa.

Fig.1

Bottom ash obtained from Mae Moh power
plant.

The soil samples mixed with cement, kaolin andbottom ash, according to Table 1 were conducted inmodified compaction tests and unconfinedcompression tests.
Table 1. The mixture ratio of admixture mixed withthe soil samples.

MATERIALS AND METHODS
MixtureCementKaolinBottomCode(%)(%)
Ash (%)
A1
1.5
A2
2
A3
3
B1
1
1
2
B2
1
1
4
B3
1
1
6
B4
1
1
8
C1
1.5
0.5
2
C2
1.5
0.5
4
C3
1.5
0.5
6
C4
1.5
0.5
8
Note: The amount of cement, kaolin and bottom ash
mixed with soil is percent by weight of soil.

The lateritic soil which has poor quality was usedin the experiment. The strength of the soil samples
was less than the required strength which suggestedby the Thailand department of highways. The soil
samples were conducted on Atterberg limits andsieve analysis test to determine the properties andclassification of the samples. Portland cement type 1,
kaolin and bottom ash were mixed in the soil
samples to improve the strength. Kaolin obtained
from Lampang province of Thailand. Bottom ash
obtained from Mae Moh power plant in Lampang
province of Thailand as shown in Fig. 1.
The maximum size of bottom ash mixed with thesoil samples was 4.75 mm. All admixture stored inplastic bags to maintain their dry condition. The soil
samples were mixed with cement, kaolin and bottom
ash in the ratio accordance with Table 1. The
mixture code in group A represented the soil
samples mixed with cement 1.5-3% by weight of thesoil samples. The mixture code in group B
represented the soil samples mixed with cement 1%,
kaolin 1% and the different percentages of bottom
ash 2-8% by weight of soil. The mixture code ingroup C represented the soil samples mixed withcement 1.5%, kaolin 0.5% and the different
percentages of bottom ash 2-8% by weight of soil.
The difference between the mixture in group B
and C is the percentage of Portland cement andkaolin. The combination of cement and kaolin in the
mixture of B and C samples was 2% by weight ofthe soil samples. However, the amount of cement in
the mixture group B was less than group C 0.5%.

The modified Proctor compaction tests on thesamples in each mixture were conducted inaccordance with AASHTO T180. This test isintended to be used to determine the maximum dry
density and optimum moisture content in each
mixture of the samples. The samples were manuallycompacted in five equal layers using the modified
compaction effort.
Unconfined compression tests are intended to be
used to determine the compressive strength of thesamples. Unconfined compression tests wereconducted in accordance with AASHTO T 208. The
soil samples mixed with cement, kaolin and bottom
ash in the ratio according to Table 1 were used inthis test. The samples mixed with water at the
optimum moisture content (OMC) for each mixture
which obtained the values from the modified
compaction tests. The samples were compacted infive equal layers using modified compaction effort.
After completing the compaction process, each
527

SEE - Nagoya, Japan, Nov.12-14, 2018

sample was extruded from the compaction mold andwas then cured in the plastic bag until tested. The
specimens were cured in the in the plastic bag for 3,
7 and 14 days. Following the curing process, thesamples were soaked in water for 2 hours and thencompressed the samples by the compression
machine. The results represented by the influence ofbottom ash on the strength of soil improvement.
However, the Thailand Department of highways
suggested that the unconfined compressive strengthof subbase improvement should be more than 689
kPa at the curing time 7 days. Therefore, theoptimum bottom ash content to improve the strengthof soil can be defined by the test results.

cement was slightly different from the samples
without cement. The maximum dry density of thesamples A1, A2 and A3 was 1957 kg/m3, 1959kg/m3, and 1946 kg/m3 respectively. The optimum
moisture content of the samples A1, A2 and A3
were 9.7%, 9.8%, and 10.2% respectively.
2000

Dry Density (kg/m 3 )

1950
1900
1850
1800
1750
1700
Soil

1650

A1

A2

A3

1600
6

8

7

9

RESULTS AND DISCUSSIONSThe Engineering Properties of Lateritic Soil

Fig. 3The soil samples were conducted on Atterberg
limits, sieve analysis test, and modified compaction
tests to determine the engineering properties of thesoil samples. Liquid limit, plastic limit, andplasticity index of the soil samples were 27%, 17%,and 10% respectively. Fig. 2 shows the particle size
distribution of the soil samples in this study.
However, according to the AASHTO classification
system, the soil samples were in A-2-4. The
gradation of soil samples is excellent to good for
subgrade materials when considered on the generalsubgrade rating of AASHTO. Moreover, the resultsof modified compaction tests demonstrated the
maximum dry density of the soil samples wasapproximately 1940 kg/m3 and optimum moisture
content was 9.9%.

Size Distribution of Soil Samples

80
Percent Finer (%)

70
60
50
40
30
20
10
0
0.01

0.1

1

11

12

13

Dry density and moisture content
relationship of the soil improvement bycement.

The results of soil samples mixed with cement,
kaolin and bottom ash shown in Fig. 4 and Fig. 5.
The results in Fig. 4 illustrates dry density andmoisture content of the samples in group B. The
maximum dry density of the samples B1, B2, B3 andB4 was 1945 kg/m3, 1961 kg/m3, 1954 kg/m3 and1966 kg/m3 respectively. The optimum moisture
content of the samples B1, B2, B3, and B4 was
9.8%, 9.9%, 9.9% and 11.1% respectively.
Dry density and moisture content of the samples
in group C illustrated in Fig. 5. The maximum dry
density of the samples C1, C2, C3 and C4 was 1960kg/m3, 1942 kg/m3, 1938 kg/m3 and 1940 kg/m3
respectively. The optimum moisture content of thesamples C1, C2, C3, and C4 was 9.8%, 10.4%,
10.0% and 10.0% respectively. The results
demonstrated a slight difference of maximum dry
density and optimum moisture content of thesamples for each mixture. The maximum dry densityof the samples in each mixture was between 19401960 kg/m3. Therefore, bottom ash adding in the soil
samples is less effect on the maximum dry density of
soil.

100
90

10

Moisture Content (%)

10

Particle Size (mm)

2000
1950

Particle size distribution of the soil samples
used in the test.

Dry Density (kg/m 3 )Fig. 2

Maximum Dry Density and Optimum Moisture
Content

1900
1850
1800
1750
1700
Soil

1650

B1

B2

B3

B4

1600

The modified compaction tests were conductedon soil samples mixed with cement, kaolin andbottom ash in a ratio accordance with Table 1. The
results of compacted soil samples mixed withcement 1.5%-3% as shown in Fig. 3. The results
showed the dry density of the samples mixed with

6

7

8

9

10

11

12

13

14

Moisture Content (%)

Fig. 4528

Dry density and moisture content
relationship of the soil improvement ingroup B.

SEE - Nagoya, Japan, Nov.12-14, 2018

demonstrated the strength of the samples in group C
which contained kaolin 0.5% and bottom ash 2%8% was higher than A1 samples. Moreover, thestrength of the samples tends to increase with anincrease in the amount of bottom ash. The
compressive strength of C3 and C4 samples wasnear in the curing time 3-14 days. The compressive
strength of the samples C3 and C4 increased
approximately 87% and 84% respectively of A1
samples in curing time 7 days. However, thestrength of C3 and C4 samples in curing time 14days was higher than A1 samples approximately
55%. Moreover, B2, B3, and B4 samples
represented the unconfined compressive strength
near A1 samples. Although, the samples in group B
contain the amount of cement was less than the A1
samples 0.5% by weight of soil. Therefore, thisresult demonstrated that bottom ash can be reduced
the utilized amount of cement to improve thestrength of soil. The influence of bottom ash on thecompressive strength of soil shown in Fig. 7 and Fig.
8.

2000

Dry Density (kg/m 3 )

1950
1900
1850
1800
1750
1700
Soil

1650

C1

C2

C3

C4

1600
6

7

8

9

10

11

12

13

14

Moisture Content (%)

Fig. 5

Dry density and moisture content
relationship of the soil improvement ingroup C.

Unconfined Compressive Strength
The average unconfined compressive strength
values of the soil improvement for each mixture are
as plotted in Fig. 6.

1200

A1

A2

A3

B1

B2

B3

B4

C1

C2

C3

C4

700

Unconfined Compressive Strength (kPa)

Unconfined Compressive Strength (kPa)

1400

1000
800
600
400
200
0
3

4

5

6

7

8

9

10

11

12

13

14

Curing Age (days)

600
500
400
300
200
B (14 days)

100

B (3 days)

B (7 days)

02

Fig. 6

4

Unconfined compressive strength of the soil
improvement for each mixture.

6

8

Bottom Ash (%)

Fig. 7

The results demonstrated the soil samples mixed
with 3% of cement gave the highest strength in 14
days. The strength of A3 samples was 1302 kPa in
curing time 14 days. The strength of C3 and C4
samples in the curing 14 days was lower than A3
approximately 415 kPa. However, the early strengthof C3 and C4 samples was near A3 in the curing
time 3 and 7 days. Although, C3 and C4 samples
contain Portland cement only 50% of A3. The
results can be suggested that bottom ash mixed withsoil developed the early compressive strength ofsoil. This is due to the composition of bottom ash
obtained from Mae Moh power plant were 21.3%
Al2O3 and 13.5% Fe2O3 [4] which Al2O3 and Fe2O3
in the bottom ash can be developed the earlystrength of the samples. However, the strength of A3
is more than C3 and C4 in the curing time14 days.
This is because the cement content in A3 samples
was higher than C3 and C4 and the later strength iscontrolled mainly by calcium silicate hydrate.
Consideration on A1 samples and the samples ingroup C which contain the same amount of cementin the samples at 1.5% by weight of soil. The results

The influence of bottom ash on thecompressive strength of soil mixed with theadmixture in group B.

Unconfined Compressive Strength (kPa)

1000
900
800
700
600
500
400
300
200
C (14 days)100

C (3 days)

C (7 days)

0
2

4

6

8

Bottom Ash (%)

Fig. 8The influence of bottom ash on thecompressive strength of soil mixed with theadmixture in group C.

The results demonstrated the strength of soil
improvement tends to increase with an increase in
529

SEE - Nagoya, Japan, Nov.12-14, 2018the amount of bottom ash. The unconfinedcompressive strength was rapidly increasing whenbottom ash contains in the samples 2 to 6%.
However, the samples which contain bottom ash 6%
and 8% shown the similar value of the unconfinedcompressive strength. Therefore, this result cansuggest the optimum content of bottom ash used to
improve the strength of soil.
Nevertheless, the soil samples mixed withcement 1%, kaolin 1% and bottom ash 2% in curing
time 3 days represented breakdown of the samples
after soaked in the water for 2 hours. This is because
the amount of cementitious materials is not enoughto react. However, the increased amount of cement
or bottom ash in the samples can increase thestrength of soil and durability of the samples.
The required unconfined compressive strength ofsubbase improvement which suggested by theThailand Department of highways should be morethan 689 kPa at the curing time 7 days. Fig.9
demonstrated the unconfined compressive strengthof soil mixed with an admixture of each mixture at
the curing time 7 days. The samples which passed
the minimum strength requirement consisted of thesamples A3, C2, C3, and C4. The unconfinedcompressive strength value of the samples A3, C2,
C3, and C4 was 889 kPa, 729 kPa, 854 kPa and 838
kPa respectively. Therefore, the samples mixed withcement at 1.5%, kaolin 0.5%, and bottom 4-8% candevelop the strength of poor subbase higher than theminimum required strength. However, the soil
samples mixed with admixture in group B cannot
develop the strength higher than the minimum
strength requirement. This is because the amount of
cement in the mixture is not enough to increase thestrength of soil.

strength of soil from the samples without bottom
ash. Therefore, bottom ash mixed with the soil
samples can be reduced the utilized amount of
cement to improve the strength of soil.
CONCLUSION
Based on the experimental test obtained in thisstudy, the following conclusion was made:1. Bottom ash can increase the unconfinedcompressive strength of poor subbase. The optimum
bottom ash content mixed in soil is 6% by weight ofsoil.
2. Bottom ash can develop the early strength ofsoil. The strength of the samples which containbottom ash was higher than the samples withoutbottom ash approximately 84% in curing time 7
days.
3. The strength requirement which suggested by
the Thailand Department of highways is 689 kPa in
curing time 7 days. The soil samples mixed withcement 1.5%, kaolin 0.5%, and bottom ash 4 to 8%
can be developed the unconfined compressive
strength more than the strength required.
4. The strength of soil mixed with cement 1.5%,
kaolin 0.5% and bottom ash 6 to 8% is equivalent tothe soil mixed with cement 3% in curing time 7
days. The unconfined compressive strength wasapproximately 850 kPa. Therefore, bottom ash
mixed in the soil samples can be reduced the utilized
amount of cement to improve the strength of soil.
REFERENCES[1] Kavitha S., Geetha D., Ramesh P.S., Synthesis
and characterizations of silver colloid
nanoparticles stabilized by dextran, J. Environ.
Nanotechnol. 4 (1), 2015, pp. 50–55.
[2] Onyelowe K.C., Duc B.V., Durability ofnanostructured biomasses ash (NBA) stabilized
expansive soils for pavement foundation, Int. J.
Geotech. Eng. , 2018, https://doiorg/10.1080/193
86362. 2017.1422909.[Online].
[3] Hausmann M.R., Modification by admixture,Engineering Principles of Ground Modification,
International Edition, McGraw-Hill Publishing
Company, 1990, pp. 302-324.
[4] Sathonsawaphak A., Chindaprasirt P., PimraksaK., “Workability and Strength of lignite bottom
ash geopolymer mortar”, Journal of Hazardous
Materials, 168, 2009, pp.44-50.
[5] Chindaprasirt P, Jaturapitakkul C, Chalee W,
Rattanasak U, "Comparative study on thecharacteristics of fly ash and bottom ash
geopolymers", Waste Management, 29, 2008,
pp.539-543.

Unconfined Compressive Strength (kPa)1000
Minimum Strength Requirement

900
800
700
600
500
400
300
200
100
0
A1

Fig. 9

A2

A3

B1

B2

B3

B4

C1

C2

C3

C4

Unconfined compressive strength of soil
mixed with an admixture for each mixture
in 7 days curing time

Although the A1 samples have the amount of
cement same as C2, C3, and C4, the A1 samples
cannot develop the strength of soil higher than theminimum required. However, C2, C3, and C4
samples can be developed the strength was higher
than the minimum requirement. This result can bedemonstrated that bottom ash can develop the530SEE - Nagoya, Japan, Nov.12-14, 2018[6] Juturapitakkul C, Cheerarot R, "Development ofbottom ash as pozzolanic material", Journal of
Materials in Civil Engineering, volume 15,
Issue 1, 2003.
[7] Cheerarot R., “Development of disposed fly
ashes and bottom ashes as pozzolanic material,
Master of Eng.
[8] Cheriaf M., Rocha J.C., P’era J., “Pozzolanic
properties of pulverized coal combustion bottom
ash, Cem.Concr.Res. 22, 1999, pp 1387-1391.
[9] Ghafoori N., and J. Bucholc., “Investigation oflignite-based bottom ash for structural concrete.”
J. Mater. Civ. Eng. 8(3), 1996, pp.295-301.
[10] Chorchill E. V., and Amirkhanian S.N, “Coalash utilization in asphalt concrete mixtures.”
J.Mater.Civ.Eng., 11(4), 1999, pp.128-13.
[11] Hastuty P. I., Roesyanto, and B. S. Jeriko., “Astudy of the effectiveness of the use of cement
and bottom ash toward the stability of clay interm of UCT value”. Procedia Engineering 171,2017, pp. 484-491[12] K.C. Onyelowe, B.V. Duc, Durability ofnanostructured biomasses ash (NBA) stabilized
expansive soils for pavement foundation, Int. J.
Geotech. Eng. (2018), https://doiorg/10.1080/
19386362.2017.1422909 [Online][13] K.J. Osinubi, V. Bafyau, A.O. Eberemu,
Bagasse Ash Stabilization of Lateritic Soil,
Springer Link Sciences and Business Media,
2009, pp. 271–280.
[14] K.C. Onyelowe, Nanosized palm bunch ash
stabilization of lateritic soils for construction
purposes, Int. J. Geotech. Eng. (2017), https://doiorg/10.1080/19386362.2017.1322797[Online].
[15] American Standard for Testing and Materials
ASTM C618, Standard Specification for
Pozzolan, ASTM, West Conshohocken, 2014,531

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DAMAGE LEVEL PREDICTION OF MULTI-STORY STEELSTRUCTURE IN SUMATRA USING BACKPROPAGATION NEURALNETWORK
1,3,4

Reni Suryanita1, Harnedi Maizir2, Ismeddiyanto3, Vindi Trisatria4 and Raihan Arditama5
Faculty of Engineering, Universitas Riau, Pekanbaru, Indonesia; 2Sekolah Tinggi Teknologi Pekanbaru,
Indonesia; 5Faculty of Engineering, Universitas Andalas, Padang, Indonesia.

ABSTRACT
Sumatra is one of the Indonesia islands that is prone to earthquakes both tectonic and volcanic. The researchaims to predict the damage level of a multi-story steel structure due to the earthquake in Sumatra Island using
the Backpropagation Neural Network (BPNN). The study used the steel structure building that received
earthquake loads from ten capital cities of the province on Sumatra Island. The structure analysis used the finite
element software while the BPNN method used the MATLAB Programming. The input data were the responsesof the structure such as displacement, velocity, and acceleration while the output was damage level of the steel
structure model. The model of BPNN has the potential accuracy to predict the damage level of steel structural
more than 95%. According to the simulation result, 98,5% data could be predicted correctly by the BPNN
method, and the best Mean Squared Error (MSE) is 0.028. These results have shown that BPNN can predict thedamage level of multi-story steel structure in all the capital cities of the province on Sumatra Island.
Keywords: Backpropagation Neural Networks, Damage Level, Earthquake Load, Mean Squared Error,
Response of Structure.

The construction of high rise buildings iscurrently overgrowing. When the building goeshigher, it tends to have a lower rigidity so that
deformation of the structure is higher if theearthquake load is active. This excessive
deformation can damage structural components.
Steel structure building is a construction made fromthe arrangement of steel rods. Each part of the steel
is connected using a joint such as bolts, nail or weld.
Steel frame structure has advantages compared toconcrete structures and wooden structures.
Therefore, the higher tensile strength of steel, thelighter steel and more flexible when compared withconcrete structures.
Therefore, the design of a building structure mustmeet the requirements written in the Design Codesand Standards and be well planned to minimize theoccurrence of errors. In the Indonesian National
Standards on Earthquake Resilience Procedures for
Building Constructions, the construction of abuilding structure can be well designed and take into
consideration earthquake loads that may occur. The
requirement of quantity is outlined in [4] which thenumber of the mode of modal shall be sufficient toobtain the modal participating mass ratio at least
90% of the actual mass in each mode. Through the
non-linear time history analysis, behavior andresponse of steel structure due to dynamic loading
can be known in detail [5]-[6]. However, thismethod takes a relatively long time to process thefinite element analysis compared with the static nonlinear method. It is necessary to develop a smart

INTRODUCTION
All the coastal areas of Sumatra are in the Pacific
Ring of Fire. Sumatra is one of the Indonesia islands
that is prone to earthquakes both tectonic andvolcanic. The characteristic of strong Indonesian
quakes as occurred in Aceh on December 26, 2004
(measured 9.3 on the Richter Scale) and in Padang
City on September 30, 2009 (with 7.9 on the Richter
Scale) is very dangerous to the structure of buildingson these areas [1]-[2]. The collapse due to thesudden release of energy from within that creates aseismic wave. Earthquakes often occur in thelocation areas that are close to volcanoes and also in
the regions that are surrounded by vast oceans.
When this wave reaches the surface of the earth, its
vibrations can be damaging or independent of source
power and focal distance, besides the quality of thebuilding and the quality of the soil in which it
stands. Ordinary earthquakes are caused by the
movement of the earth's crust (the earth's plates).
Base on [3] the scales are used to measure thestrength and magnitude of earthquakes is the Richter
Scale and MMI (Modified Mercalli Intensity.
However, in designing a structure, the necessary
earthquake record data is in the form of PeakGround Acceleration (PGA) units (g). The PGA isaccelerogram, that is, a graph of surface accelerationcomparison with time or duration during anearthquake. This accelerogram data will be an input
quake parameter for a design or structural analysis.

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SEE - Nagoya, Japan, Nov.12-14, 2018

learning process in predicting the damage level ofsteel structures in different quake locations rapidly.
For this reason, the study aims to identify damagelevel the steel structure due to earthquake load
quickly based on the time history of an earthquake
using Backpropagation Neural Network (BPNN).
According to FEMA 356 [7], the performancelevel of a building structure for primary members(P) and secondary members (S) must be at six levelsof structural performance as shown in Fig.1, whichare:
1. Immediate Occupancy (IO), that is, there is no
significant damage to the structure so that its
strength and stiffness are almost the same as
before the earthquake.
2. Damage Control, in these circumstances the
structure is at the safety level (safe limit) of thestructure.
3. Life Safety (LS), in this situation there is damage
to the structural components. The stiffness of thestructure is reduced but has not experienced
structural collapse. Structures that are in thisstate can still be used when the repair has beendone.
4. Limited Safety, in this case, the structure isdefined as being in the condition between theoccupant's safety structure and the prevention ofcollapse. In this situation, there is "muchstructural damage," because it is no longer safe
to be inhabited due to limited structural strength.
5. Collapse Prevention (CP), defined as a state ofpost-collapse damage. Damage occurs instructural and nonstructural components.
6. Structural Performance not Considered,buildings that have been damaged in their
nonstructural parts are classified at this level of
performance.

over time to earthquake vibrations. In general,
analysis using the time history of earthquake
requires a relatively long time duration. One solutionof rapid prediction is using the Backpropagation
Neural Network (BPNN). Based on previous
research, the BPNN method has been successfully
used in various fields of Civil Engineering formaking predictions such as [8], [9] and [10]. The
previous study has resulted in the BPNN accuracy
reaches 96% to 98% to predict the damage level ofdrift story of concrete building [11] and bridge
structure [12]. The study suggests that BPNN
deserves to be applied as a tool for predicting in the
Civil Engineering world. However, the number of
research that discusses the estimation of damage tostructures of multi-story steel buildings is still
relatively small. Therefore, this study aims to predict
the extent of damage to building structures that
occur due to earthquakes. Consequently, the matters
discussed in this study include the level of damage
to the multi-story steel portal that happens in abuilding model that has a height variation.
BACKPROPAGATION NEURAL NETWORKS
Knowledge of biological neuron cells in thebrain has inspired the development of a computing
system called Artificial Neural Network (ANN). The
artificial neural network is a system that has aworking system like the human brain. This system
can model a complicated thing between input andoutput to determine a particular pattern. The
architecture and operation of ANN can be describedin the form of mathematical and computationalmodels for data classification, clusters, and nonparametric regression or as simulations of biologicalneural models.
Backpropagation Neural Network (BPNN) is
one of the training methods on ANN, where thecharacteristics of this method are to minimize theerror on the output produced by the network. The
BPNN training is conducted to develop the ability ofmemorization and generalization in weights. The
strength of BPNN to memorize is the way toremember and take the learned pattern incorrectly.
What is meant by generalization capability is theability of BPNN to provide an acceptable response
from similar data and input patterns to a model
previously studied by the previous system. Most of
the training for feedforward networks use gradientsfrom the activation function to determine how tomanage the weights in minimizing performance. The
gradient is estimated by using a technique called
backpropagation. The advantage of using this BPNN
method is that it is possible to obtain informationfrom a complex set of data and solve problems thatare unstructured and difficult to define. The standard
backpropagation training algorithm will drive theweights with the negative gradient direction. The

Fig.1. Acceptance criteria of componen deformation
Currently, most of the earthquake-resistantbuildings are planned with procedures written in thebuilding codes. In this study, building structure wasanalyzed using a non-linear time history method tofind out the structure behavior due to earthquake
load. This time history analysis is a structural
analysis method that reviews the structure response

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SEE - Nagoya, Japan, Nov.12-14, 2018

fundamental principle of the backpropagation
algorithm is to fix network weights by making theactivation function go down quickly.
Backpropagation could be estimated errors
with gradient descent on each network located on
the architecture of the Artificial Neural Network.
BPNN consists of three layers; input, hidden and an
output layer. Each neuron in the hidden layer it will
receive information from the input layer neuron
multiplied by the weight of the tissue entering theneuron and summed.

RESEARCH METHODOLOGY
The models of the structure are three multistory steel building. The structure models refer to therequirements by SNI 1729-2015 Indonesian
specification for structural steel building [13]. The
dimensions of structural elements used are as
follows:
Fig 2. The steel structure model with various height.
1. Modulus of Elasticity
2. Shear Modulus
3. Poisson’s ratio
4. Steel density
5. Yield strength: 200.000 MPa: 80.000 MPa: 0.3: 7.850 Kg/m3: A36 - 240 MPa

Table 1 Properties of Steel Structure Model
Story of
Model
5
10
15

Beam

ColumnHeight (m)WF
300x150
WF
300x150
WF
300x150

H 350x350

18

H 350x350

35.5

H 350x350

53
Fig 3. The layout of the steel structure building

The structure of the building under observation
is a steel portal which has the same floorplan startingfrom the ground floor (base) to the roof (rooftop), as
shown in Fig 2. Elevation between floors is 4 meters
for the ground floor and 3.5 meters for the nextlevel. The regular building shape with X and Y
direction is not symmetrical as shown in Fig 3.
The earthquake load used is in the form of time
history response record. Adjustment of the scale
used is determined based on the planning standardsof seismic resistance of Indonesia SNI 1726-2012[4] with medium soil conditions. The earthquake
data in all provincial capitals on the island of
Sumatra in Table 2.

Table 2 PGA value of Capital City of Province in
Sumatra Island
No.
1
2
3
4
5
6
7
8
9
10
534

Capital City ofProvince
Banda Aceh
Medan
PadangPekanbaru
Tanjung Pinang
Jambi
Bengkulu
Palembang
Pangkal Pinang
Lampung

PGA
0,621g0,231g0,515g0,214g0,023g0,105g0,519g0,146g0,026g0,356g

SEE - Nagoya, Japan, Nov.12-14, 2018

Input layer consists of the height of the steel
structure building, displacement, velocity andacceleration of structural response in X and Y
direction. The output layer includes the building
condition after received earthquake load; Safe asindex 1, Immediate Occupancy as index 2, Life
Safety as index 3 and Collapse Prevention as index
4. The procedure of the study used the BPNN
method as shown in Fig 6.

The time history analysis of earthquake is doneby modeling the steel structure by the data that will
be used into the finite element software. Following
is the flowchart of the analysis steps with the finite
element software, as shown in Fig 4. Meanwhile, the
BPNN architecture model for this study is shown in
Fig. 5.

Fig 4. Flowchart of finite element method for thestudy

Fig 6. The BPNN method for the study

RESULTS AND DISCUSSION
Finite element analysis resulted in the time
history of displacement, velocity, and acceleration at
the top of the steel structure. Tthe most considerable
displacement value occurred in Banda Aceh City
was 0.102 meters in X-direction. Meanwhile, thedisplacement value of Y-direction was 0.112 meters.
The smallest displacement value happened in
Tanjung Pinang City was 0.006 m for the X
direction and 0.007 m for Y-direction.
The most considerable velocity value occurredin Banda Aceh City was 0.957 m/s for the Xdirection and 0.926 m/s for Y-direction. The
smallest velocity value happened in Tanjung Pinang

Fig 5. The BPNN architecture model
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SEE - Nagoya, Japan, Nov.12-14, 2018

City was 0.057 m/s for the X-direction and 0.055
m/s for Y-direction.
The most considerable acceleration value
occurred in Banda Aceh City was 13.832 m/s2 for Xdirection and 9,555 m/s2 for Y-direction. The
smallest acceleration value in Tanjung Pinang City
was 0.820 m /s2 for X-direction and 0.583 m/s2 forY-direction.
Backpropagation Neural Network (BPNN)
method was used with the following input
parameters: displacement, velocity, and accelerationin X and Y-direction. Whereas the predicted output
parameters are Safe as 1, Immediate Occupancy as
2, Life Safety as 3 and Collapse Prevention as 4 forthe label. The training process on the system wasdone as a whole to facilitate the learning process.
The learning process was delivered repeatedly andgradually with 21 hidden layers. After thecompletion of the training process, the total iteration(epoch) obtained was as much as 7675 epoch byusing Tan Sigmoid method. The best validation
performance of Mean Squared Error (MSE) is
0.028227 as shown in Fig 7.

Fig 8. The best performance of Regression (R)CONCLUSION
The displacement of a structure will increase theheight of the structure due to the earthquake. The
same is true for the velocity and acceleration which
will also increase with the height of the building
structure. Out of the ten provinces on the island of
Sumatra, Banda Aceh City shows the mostsignificant damage level due to the scaled
earthquake and has the most substantial
displacement is 0.102 m for the X-direction and
0.112 m for Y-directions in comparison to the otherprovinces. The smallest displacement values
occurred in the city of Tanjung Pinang with 0.006 m
for the X-direction and 0.007 m for the Y-direction.
Based on the average of Regression which is
0.95573, it can be concluded that the designed ANN
has a high correlation and accuracy.
Fig 7. The best performance of MSE (MSE)ACKNOWLEDGMENTS
The authors are grateful to The Indonesian
Government through the Ministry of Research,
Technology and Higher Education of Indonesia with
Contract No. 086/SP2H/LT/ DRPM/2017 forfunding this research.

Based on the above results, the trained BPNN
method has been able to predict the extent ofstructural damage very well. The result indicatedhow closely located the distribution of the target
points and the prediction to the diagonal line ofRegression (R) that is 0.98499. In other words, thepredicted results are close to 100 percent of theactual state as shown in Fig 8.

REFERENCES
[1]

536

T. Lay, H. Kanamori, C. J. Ammon, M.
Nettles, S. N. Ward, R. C. Aster, S. L. Beck,
S. L. Bilek, M. R. Brudzinski, and R. Butler,“The Great Sumatra-Andaman Earthquakeof 26 December 2004,” Science (80-. )., vol.

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[2]

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[5]

[6]

[7]

308, no. 5725, pp. 1127–1133, 2005.
C. Yang, “Study on Indonesian Seismic
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to High-rise Buildings in Jakarta,
Indonesia,” in Proceedings of World
Academy of Science: Engineering andTechnology, 2009, p. 50.
Y.-X. Hu, S.-C. Liu, and W. Dong,
Earthquake Engineering. CRC Press, 2014.
SNI-1726, The Seismic Resistance DesignStandard for Buildings (Indonesian National
Standard). 2012.
Y. Ding, X. Song, and H.-T. Zhu,
“Probabilistic Progressive Collapse Analysis
ofSteel-Concrete
Composite
Floor
Systems,” J. Constr. Steel Res., vol. 129, pp.
129–140, 2017.
J. Setiawan and S. Nakazawa, “Study on
Comparison of Special Moment Frame Steel
Structure (SMF) and Base Isolation Special
Moment Frame Steel Structure (BI-SMF) in
Indonesia,” in AIP Conference Proceedings,
2017, vol. 1892, no. 1, p. 20026.
FEMA356, “Prestandard and Commentary
for The Seismic Rehabilitation of
Buildings,” vol. FEMA 356. Federal
Emergency
Management
Agency,Washington, DC, 2000.

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Detection under Varying Temperature using
Artificial Neural Networks,” Struct. Control
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S.
Gholizadeh,“Performance-based
Optimum Seismic Design of Steel Structuresby a Modified Firefly Algorithm and a New
Neural Network,” Adv. Eng. Softw., vol. 81,
pp. 50–65, 2015.
M. Betti, L. Facchini, and P. Biagini,“Damage Detection on a Three-Storey SteelFrame using Artificial Neural Networks andGenetic Algorithms,” Meccanica, vol. 50,
no. 3, pp. 875–886, 2015.
R. Suryanita and H. Jingga, “Application of
Backpropagation Neural Networks in
Predicting Story Drift of Building,” in
Lecture Notes in Engineering and Computer
Science, 2017, vol. 2227.
R. Suryanita, Mardiyono, and A. Adnan,“Intelligent bridge seismic monitoring
system based on Neuro Genetic hybrid,”
Telkomnika (Telecommunication Comput.
Electron. Control., vol. 15, no. 4, 2017.
SNI-1729, “The Specification for Structural
Steel Building (Indonesian National
Standard),” 2015.

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

BRAIN TISSUE SWELLING DURING ISCHAEMIA-REPERFUSION:
2D FINITE ELEMENT ANALYSIS USING POROELASTICITY
Mohamed Mokhtarudin, M. J.1, Shabudin, A.2 and Payne, S. J.3
Faculty of Mechanical Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang
3
Institute of Biomedical Engineering, Department of Engineering Science, Old Road Campus Research
Building, University of Oxford, Headington, Oxford OX3 7DQ, UK
1,2

ABSTRACT
Brain vasogenic oedema is an injury that occurs after reperfusion treatment of ischaemic stroke patient. It can leadto brain tissue swelling consequently causing brain herniation that may affect brain functionality. In this paper, amathematical model describing this injury are developed using capillary filtration and poroelastic theory torepresent oedema formation and brain tissue swelling, respectively. An ideal 2D representation of human brain isdeveloped and the mathematical model of ischaemia-reperfusion injury is solved using finite element method. The
size and location of the ischaemic stroke infarct are varied and the movement of the midline that divides the
cerebrals is observed. The midline movement represents the level of herniation. Results show that herniation level
increases especially for large infarct size and for infarct located nearer to the brain ventricle. Further validation of
the model using MRI data and patient-specific representation is needed to estimate brain tissue swelling
subsequently predict the effectiveness of ischaemic stroke treatment.
Keywords: Poroelasticity, Finite Element Analysis, Cerebral Tissue Swelling, Ischaemia-Reperfusion Injury,
Vasogenic Oedema

In this paper, a mathematical model of brain
tissue swelling after a cerebral ischaemiareperfusion treatment is investigated using an ideal
2D brain geometry and solved using finite element
scheme of poroelastic model. The objective here isto observe the effect of infarct size and location
towards the formation and severity of brain
herniation. This will be a preliminary study before amore complete validation using MRI data ofischaemic stroke patient can be done.

INTRODUCTION
Brain oedema formation due to cerebral
ischaemia-reperfusion can be observed using
medical imaging modalities such as CT and MRI
scans by the movement of brain midline structures(also known as brain herniation) or by brain tissueswelling. Herniation usually results in thecompression of brain ventricle and cerebral
microvessels, which further results in the occurrenceof secondary ischaemia [1]. The presence ofherniation may indicate the rise in the intracranialpressure (ICP) and it may cause permanentneurological problems and even fatality [2]. Several
treatments are available for brain oedema such as
decompressive surgery and osmotherapy. However,
the effectiveness of these treatments remains
questionable due to the complicated nature of brain
oedema formation.
A mathematical model has been developed tofurther understand the formation of brain tissueswelling due to BBB breakdown using poroelastic
theory. Poroelasticity was initially used to study soil
mechanics [3] and has been extensively used to study
the mechanics of the pathological brain [4-6]. In thistheory, the brain tissue is assumed to behomogeneous, has linear elastic property, andcontain both water and blood, permeable in a solid
porous matrix structure. A comprehensive
mathematical framework of this theory can be foundin [7].

METHODOLOGY
Theoretical Background
During ischaemic stroke, the lack of oxygen andnutrient to the affected region creates a series ofbiochemical reactions that destroys the endothelial
cells surrounding the cerebral microvessels leading
to the blood-brain barrier (BBB) breakdown, which
increases the BBB permeability [8]. When bloodflow is restored after reperfusion treatment, ions andsome protein plasma can filtrate through thedamaged BBB creating osmotic pressure difference
between the capillary and interstitial space. This cancause the flux of water from the capillary andaccumulate in the tissue space and causes theformation of vasogenic oedema, eventually leading
to the formation of cerebral tissue swelling. Figure 1
illustrates the process of water accumulation into theinterstitial space after BBB breakdown.
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SEE - Nagoya, Japan, Nov.12-14, 2018pressure, which has been assumed constant. Lastly,
the term f represents the fraction of vessels thatremain open after the reperfusion and swelling
process at each point in space and time, and this canbe modelled using a Heaviside function.
The total stress,  ij , is linearly related to thestrain,  ij , using typical linear elasticity relation:

 ij  2G ij 

2Gv
 ii
1  2v(4)

where G , and v are the shear modulus andPoisson’s ratio of the brain tissue, respectively.
Fig. 1. Flux of water after BBB breakdown. Sbw

Numerical Procedure

represents the water movement from the cerebral
blood flow into the tissues via capillary filtration.

Brain Geometry and Meshing

POROELASTICITY MODEL

The brain geometry was drawn according to therealistic brain geometry as proposed by [9]. The
brain is modelled as a circle that consists of a circularcore in the middle that represents the brain ventricle.
The brain radius is about 65 to 67 mm [10], hence
the outer radius is taken here to be approximately as
80 mm. The circular core that represent the ventricle
has the radius of 24 mm, taken to be about 30% of
the brain radius [11]. The brain tissue is assumed tobe homogeneous, thus there is no difference between
the white and grey matter. The inner and outerboundaries of the brain geometry are named as theventricular layer and the subarachnoid layer,
respectively.

Mathematical Formulation
The formation of cerebral tissue swelling due tocapillary filtration has been modelled by [7] using
capillary filtration model and poroelastic theory. The
governing equations are given as:

 ij   wPw  0

(1)

1 Pw
 k w  2 Pw  Sbw  0
Qw t

(2)

where  ij is the total stress of the tissue, Pw is theinterstitial water pressure,  w is the Biot parameter
for water, Qw is the relative compressibility ofwater, k w is the permeability of water, t is time.
The term Sbw represents the water transferfrom the capillary space into the cerebral interstitialspace via capillary filtration, which occurs when
BBB broke down. This term can be described by [7]:S b w  2nb

Lp
Rc

f [( Pb  Pw )   b ](3)

Fig. 2. Idealized 2D brain geometry with an infarctof radius 7 mm located at 𝝋 = 135º.

where nb is the baseline volume fraction of theblood,

Lp is the hydraulic permeability of the

To model the effects of ischaemia, a small
infarcted region is drawn within the geometry. The
infarct size is varied in the range 7 mm to 28 mm
radius to study the effect of size on cerebral swelling.
The infarct is drawn as a circle which is locatedcapillary, Rc is the baseline value of capillaryradius,  is the reflection coefficient,  b is theosmotic pressure in the capillary and Pb is the blood
539

SEE - Nagoya, Japan, Nov.12-14, 2018

along the line that makes an angle 𝝋 = 135º, where
𝝋 is the angle measured counterclockwise from thex-axis, as shown in Fig. 2.
The infarcted region and region near it are
discretised using a finer mesh than the rest of the partof the geometry. The number of elements varies
depending on the sizes of the infarct of about 2000
to 5000 10-nodes tetradhedral elements. The
meshing is done using Gmsh.

Table 1. List of parameters and their baseline value
for the proposed model.
Parameter

Value
0.35
216.3 Pa

v

G
w
Qw
b

Pb

Boundary conditions
The boundary condition at the skull, R S is set as̅ . The tissue
stationary and pressure at baseline ICP, 𝑷
is assumed to initially static and the fluid pressure isat the baseline ICP.
Meanwhile, we consider two types of boundary
conditions at the ventricle, RV , which are: (1) theventricle is assumed fix and the pressure is at thebaseline ICP; and (2) the ventricle is free to move
during tissue swelling:13244 Pa2445 Pa
0.93
4389 Pa

nb

0.03

Lp

𝟑. 𝟎 × 𝟏𝟎−𝟏𝟏 m/s.PaRc

𝟓 × 𝟏𝟎−𝟔 m

P1330 PaRESULTS & DISCUSSION

 ij ( RV , t )  n   P n(5)

Fix Ventricle Boundary Condition

The simulations are solved using open-source
finite element analysis software ELMER and are
analysed using ParaView.

The brain tissue swelling during capillary
filtration was simulated for simulation time until 1
hour. Figure 3 shows the cerebral interstitial pressure

Model Parameters

Pw and tissue displacement u for various infarct
sizes for the case of fix ventricle boundary condition.
The tissue displacement starts to develop at theoutermost radius of the infarct before slowly
spreading to the inside and outside of the infarct.
Meanwhile, the pressure starts to rise within thecentre of the core and then spreads in the direction of

Table 1 below shows the parameters involved inthis model and their respective value. Details
regarding the parameters can be found in [7].

Fig. 3. 2D simulation results for various infarct sizes. (Top) Interstitial pressure. (Bottom) Tissue displacement.

540

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 4. Variation of the maximum brain tissue displacement and interstitial pressure with the infarct sizeand distance from the ventricle.
the infarct radius.
However, due to the boundary conditions
imposed at the subarachnoid and ventricular layers,
the displacement and pressure gradually decrease
near these layers. The tissue displacement pushes theother side of the cerebral tissue as indicated by the
deformation of the middle line to the right side. The
deformation of this line increases as the size of theinfarct becomes larger.
The changes in maximum displacement andmaximum pressure when the infarct distance fromthe ventricle is varied are shown in Fig. 4. The
maximum displacement increases when the distancefrom the ventricle increases except for the case of theinfarct radius at 7 mm. For this infarct size, there isa slight drop in the maximum displacement for theinfarct distance from 7 mm to 21 mm and the infarct
distance from 42 mm to 49 mm. Meanwhile, for the
maximum pressure, there is no substantial difference
when the distance is varied with the exception of thecase for a 7 mm infarct radius, although thedifference for this case is only about 25 Pa from theother case.
This difference is due to the ‘edge effect’, inwhich the infarct is located near the subarachnoid
and ventricle layer that have been fixed in terms ofdisplacement and pressure values. In reality, theventricle does not have a fixed shape and position
but it may move and be compressed during brain
tissue swelling. The compression of the ventricle isalso a good indicator of cerebral swelling in CT
images [12]. It is known that the existence of AQP4
at the interface of the ventricle and the cerebral space
can help in the clearance of oedematous fluid [13].
Thus, a further improvement to the model could bemade by incorporating a pressure gradient [14] andstress-free boundary conditions [15] at the ventricle
to see how the presence of this fluid cavity affects
the progression of cerebral swelling and fluidpressure development. However, for the sake ofmodel simplification, this assumption is applied
here.

Moving Ventricle Boundary Condition
For moving ventricle cases, we only consider two
different sizes of stroke infarct – 7 mm and 14 mm
radii. Then, we measure the displacement of two
points on the ventricle, namely point x1 and x2 as
illustrated in Fig. 5.

Fig. 5. Location of x1 and x2 for ventricle
displacement measurement.
Figure 6 shows the displacement of point x1 forstroke infarct of radius 7 mm and 14 mm at 7 and 5
different locations, respectively. The 0 mm and 42
mm lines referred to the stroke located nearest andfarthest from the ventricle, respectively.
It can be seen in Fig. 6 that the displacement ofpoint x1 increases as the simulation time increases
for all locations of the stroke. Stroke that is locatednearer to the ventricle results in larger displacementof point x1, whereas stroke located further shows
smaller displacement. The changes in displacement
for both 7 mm and 14 mm stroke shows similar
characteristic, where the displacement increase

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 6. Displacement of point x1 for infarct radius of 7 mm and 14 mm.

Fig. 7. Displacement of point x2 for infarct radius of 7 mm and 14 mm.
rapidly from time 0 to 2000 s. After time 2000 s, thedisplacement becomes almost constant. However,the displacement of point x1 is bigger for 14 mmcompared to 7 mm.
Meanwhile, Fig. 7 shows the displacement ofpoint x2 for infarct radius of 7 mm and 14 mm. It canbe seen here that the displacement of point x2
increases with time for all infarct locations, withexception for the case of infarct located 0 mm and 26
mm from the ventricle, for infarct radius of 7 mm
and 14 mm, respectively. It should be noted that thedisplacements of point x2 are much smaller
compared to point x1 because point x2 is relatively
farther from the stroke location than point x1.
It is important to measure the displacement of theventricle because brain swelling after stroke can beobserved by looking at the movement of ventricle in
MRI images. For example, ventricle enlargement has
been used as an objective measure of mild cognitive
impairment in Alzheimer’s disease [16]. To further
accurately measure ventricle movement will require
the integration of the finite element model with brain
images through image-model registration procedure,as has been done, for example, by [17].

cerebral structures. Meanwhile, the model developed
by Nagashima [19] used two different cerebral tissue
hydraulic conductivity values to account for theirdifferent properties. Therefore, incorporating thedifferent mechanical properties of the brain tissues
in the model could improve the brain tissue swelling
prediction.
Another aspect worth studying is the vasogenic
oedema resolution. The oedematous fluid will moveout into the ventricles and subarachnoid spaces via
glia limitans, into the capillary endothelium via theastrocytic foot or by metabolic degradation [20, 21].
The presence of aquaporin-4 (AQP4) channels in theglia limitans and astrocytic foot [21] facilitate theremoval of the oedematous fluid. However, AQP4
also plays a role in the formation of cytotoxic
oedema that causes intracellular swelling, which
does not result in an increase in ICP and brain tissueswelling [22]. The function of AQP4 has been
demonstrated by using a mathematical model [23].
Modification of the current model through theinclusion of the role of AQP4 might provide new
insight towards the occurrence of reperfusion injury.
CONCLUSION

FUTURE WORKS
From this study, it was found that the size andlocation of cerebral ischaemic infarct can affect thedegree of brain herniation. This is shown by thedeflection of the midline that divides the two
cerebrals. In addition, the maximum brain tissue
displacement and interstitial pressure are increase as
the infarct sizes increase. These findings indicatethat ischaemic infarct size plays an important role indetermining the severity of brain tissue swelling.
The results obtained here provide further useful
information such as: (1) the importance of making
the ventricle structure movable for better
quantification of the brain tissue swelling; and (2)It has been assumed in this study that the cerebral
tissue property is homogeneous throughout thegeometry. In reality, the cerebral tissue material
properties are different for those located in the whiteand grey matter of the cerebral space. Oedema is lesslikely to develop in the grey matter area due to its
twisted structure and it has a low tissue complianceas compared to white matter [18]. The study done by
Smillie [11] also assumed that the mechanicalproperties of white and grey matter are the same dueto the lack of data available. However, they use
different fluid permeability values within these two
542

SEE - Nagoya, Japan, Nov.12-14, 2018confirms the occurrence of herniation during brain
tissue swelling. This information is useful before themodels can be applied to the actual patient data forvalidation purposes.

11. Smillie, A., Sobey, I., and Molnar, Z., A
hydroelastic model of hydrocephalus. J. Fluid
Mech., 2005. 539: p. 417-443.
12. Zimmerman, R.A., Bilaniuk, L.T., Bruce, D.,
Dolinskas, C., Obrisi, W., et al., Computed
tomography of pediatric head trauma: Acutegeneral cerebral swelling. Radiology, 1978. 126:
p. 403-408.
13. Papadopoulos, M.C. and Verkman, A.S.,
Aquaporin water channels in the nervous system.
Nat. Neurosci., 2013. 14: p. 265-277.
14. Taylor, Z. and Miller, K., Reassessment of brain
elasticity for analysis of biomechanisms ofhydrocephalus. J. Biomech., 2004. 37: p. 12631269.
15. Liu, F., Lollis, S.S., Ji, S., Paulsen, K.D., Hartov,A., et al., Model-based estimation of ventricular
deformation in the cat brain. Med. Image.
Comput. Comput. Assist. Interv., 2009. 12(Pt 2):
p. 308-315.
16. Nestor, S.M., Rupsingh, R., Borrie, M., Smith,M., Accomazzi, V., et al., Ventricularenlargement as a possible measure of
Alzheimer's disease progression validated using
the Alzheimer's disease neuroimaging initiative
database. Brain, 2008. 131: p. 2443-2454.
17. Kyriacou, S.K., Davatzikos, C., Zinreich, S.J.,
and Bryan, R.N., Nonlinear elastic registrationof brain images with tumor pathology using abiomechanical model. IEEE Trans Med. Imag.,1999. 18(7): p. 580-592.
18. Kimelberg, H.K., Nestor, N.B., and Feustel, P.J.,
Inhibition of release of taurine and excitatory
amino acids in ischemia and neuroprotection.
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19. Nagashima, T., Shirakuni, T., and Rapoport, S.I.,
A two-dimensional, finite element analysis ofvasogenic brain edema. Neurol. Med. Chir.,1990. 30: p. 1-9.
20. Tourdias, T., Mori, N., Dragonu, I., Cassagno,N., Boiziau, C., et al., Differential aquaporin 4
expression during edema build-up and resolution
phases of brain inflammation. J. Neuroinflamm.,
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and Verkman, A.S., Aquaporin-4 facilitates
reabsorption of excess fluid in vasogenic brain
edema. FASEB J., 2004. 18: p. 1291-1293.
22. Donkin, J.J. and Vink, R., Mechanisms of
cerebral edema in traumatic brain injury:
Therapeutic developments. Curr. Opin. Neurol.,2010. 23: p. 293-299.
23. Mokhtarudin, M.J. and Payne, S.J., The study ofthe function of AQP4 in cerebral ischaemiareperfusion injury using poroelastic theory. Int J
Numer Method Biomed Eng, 2017. 33(1).

ACKNOWLEDGEMENTS
This study was supported by Universiti Malaysia
Pahang (UMP) Research Grant (RDU1703310) andTabung Persidangan Luar Negara UMP (TPLN).
REFERENCES
1. Abbott, N.J., Patabendige, A.A., Dolman, D.E.,
Yusof, S.R., and Begley, D.J., Structure andfunction of the blood-brain barrier. Neurobiol
Dis, 2010. 37(1): p. 13-25.
2. Donkin, J.J. and Vink, R., Mechanisms of
cerebral edema in traumatic brain injury:
therapeutic developments. Curr Opin Neurol,
2010. 23(3): p. 293-9.
3. Biot, M.A., General theory of three-dimensional
consolidation. J. Appl. Phys., 1941. 12(2): p.
155-164.
4. Taylor, Z. and Miller, K., Reassessment of brain
elasticity for analysis of biomechanisms ofhydrocephalus. Journal of Biomechanics, 2004.
37(8): p. 1263-1269.
5. Tully, B. and Ventikos, Y., Cerebral watertransport using multiple-network poroelastic
theory: application to normal pressurehydrocephalus. J. Fluid. Mech., 2011. 667: p.
188-215.
6. Vardakis, J.C., Tully, B.J., and Ventikos, Y.,
Exploring the Efficacy of Endoscopic
Ventriculostomy for Hydrocephalus Treatment
via a Multicompartmental Poroelastic Model of
CSF Transport: A Computational Perspective.
Plos One, 2013. 8(12).
7. Mohamed Mokhtarudin, M.J. and Payne, S.J.,
Mathematical model of the effect of ischemia–
reperfusion on brain capillary collapse andtissue swelling. Math. Biosci., 2015. 263: p. 111120.
8. Yang, Y. and Rosenberg, G.A., Blood-brain
barrier breakdown in acute and chronic
cerebrovascular disease. Stroke, 2011. 42(11):p. 3323-8.
9. Hakim, S., Venegas, J.G., and Burton, J., The
physics of the cranial cavity, hydrocephalus, andnormal pressure hydrocephalus: Mechanicalinterpretation and mathematical model. Surg.
Neurol., 1976. 5: p. 187-210.
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Psychiat., 2007. 62(8): p. 847-855.

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Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DESIGN OF BASE ISOLATED REINFORCED CONCRETE BUILDINGSUBJECTED EARTHQUAKE EXCITATION USING EC 8
Norliyati Mohd Amin1, Nabihan Ayub1 and Anizahyati Alisibramulisi1
Faculty of Civil Engineering, University Teknologi MARA, Selangor, Malaysia

1

ABSTRACT
From past earthquakes, it is proved that many of reinforced concrete (RC) structure are totally or partiallydamaged due to seismic load. However, new structures will soon have the capacity for better resistance toearthquakes with a design code for buildings to raise safety standards of structures. In this study, the RC structure
was modeled as bare frame of 10 storey building including ground floor using BS8110. The parameters used inthis research were taken based on the data provided by case study in the past literatures. The modeling was thendesigned with Eurocode seismic design guidelines. A study on RC structures behaviour with and without baseisolation was studied to observe the interstorey drift, lateral displacement and its base shear effect using response
spectrum analysis in STAADPRO software. Spring was defined to act as base isolation system for the reinforced
concrete structure. Based on the results, it was expected that the application of base isolation system significantly
contributes to reduction of storey drifts, lateral displacements and base shear as well as improvement of structure
behaviour as discussed throughout in this report.
Keywords: base isolation system, response spectrum, drift, displacement, base shear

Hassaballa et al. (2013) in which focusing in Central
Khartoum, Sudan. Therefore, the parameters used inthis research were taken based on the data provided
by the researchers themselves as well as thereferences used by them. Firstly, for the verification
purpose a comparison of drift displacement by story
were made. The design structure compliance with
BS8110:1985 / 1997 as constant structure. The mostimportant parameters governing the analysis of thisframe were both gravity loads which are (dead load
and live load) and seismic loads. Next, the modelingwas designed using Eurocode 2 with andimprovement of the structures were made withseismic design using Eurocode 8 principle whichusing base isolator as seismic resistant. Soil spring
foundation is defined as the base isolation system.
Response spectrum analysis was used to analyse thestructure behaviour. This study only focuses on the
result of storey drift, lateral displacement, and baseshear after subjected to earthquake excitation of thebuilding with and without base isolation system.

INTRODUCTION
The major challenge in the reinforced structure
designs process in which considering the seismic
action is to improve the poor seismic load resistance.
British Standard BS8110, do not consider seismic
loading and detailing such as at the beam-column
joint, bracing, bearing as base isolators or dampers.
As consequences, the current structure designs were
not capable to resist and withstand under field andlong distant seismic. Therefore, design reinforced
concrete structures using earthquake design standard
should be considered so that the effect of earthquake
damage in our neighboring countries can be
minimized. This study concentrated on the utilizationof spring base isolation system of a structure. Baseisolation is becoming alternative to the current
practice with regards to safety measures forearthquake design. The uncoupling of structure fromthe ground is accomplished by the use of speciallydesigned devices, set at the base of the structure, thatsimultaneously provide an increased capacity todissipate the energy input by the earthquakes andconfer an additional flexibility and a consequent
frequency shifting which usually causes a decrease in
the seismic forces.
This study concerns on analysis of reinforced
concrete frame only. The modeling of the wholebuilding is carried out using the computer program
STAADPRO. This study involves a theoretical 10
storey building including ground floor with normal
floor loading and no infill walls. This structure
modeling is conducted based on research made by

HISTORY OF SEISMIC ANALYSIS OF BASEDISOLATED RC BUILDINGS
Hassaballa et al. (2013) conducted a study on
seismic analysis of a multi-story reinforced concrete
frame in Central Khartoum, Sudan and it was
analyzed under moderate earthquake loads as anapplication of seismic hazard and in accordance withthe seismic provisions proposed for Sudan toinvestigate the performance of existing buildings if

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PROBABILISTICSEISMICASSESSMENT OF SUDAN

exposed to seismic loads. The results of the analysis
indicated that the frame suffered a maximum
horizontal displacement of 28.39 cm at its top level.
This represents about 0.94% of the frame total height.
These nodal displacements caused drifts in excess of
the allowable drifts. The result shown that the drift
reached up to 35 mm in some levels while theallowable drift in this frame should not be greater than
0.004 times the story height (12 mm). In other words,
the calculated drifts of the frame were about 2 to 3
times the allowable drifts.
Kamble et al. (2017) studied on 9 storey building
symmetric and asymmetric having fixed base andisolation of high damping rubber bearing (HDRB).
The results from the study shown that the time period
65% increases when building is isolated with HDRB
compared to fixed base, time period 67% increases
when building was isolated with LDRB compared to
fixed base. Besides that, 40% reduction in base shear
when building was isolated with HDRB compared to
fixed base. The results of frequency decreased by
67.70% when building was isolated with LDRB
compared to fixed base. Frequency 65.98% decreases
when building is isolated with HDRB compared to
fixed base and there were 43% reduction in base shear
when building was isolated with LDRB compared to
fixed base.
Santhosh et al. (2013) conducted a dynamic
analysis structural of six storey building under both
fixed supported and seismically isolated boundary
conditions was studied to demonstrate theeffectiveness of seismic isolation. The isolation
reduces the fundamental frequency of the structurefrom its fixed base frequency and thus shifts the
position of the structure in the spectrum from thepeak-plateau region to the lower regions. Also, itbrings additional damping due to the increased
damping introduced at the base level, and thus further
reduction in the spectral acceleration is achieved asshown in Fig. 1.

HAZARD

This section is focusing on response spectrum
parameters in Central Khartoum, Sudan as according
to Hassaballa et al. (2013), Mohamedzein et al.
(2004) and Abdalla et al. (2001), and further analysis
used for this research study.
Identification of Ground TypeThe soil at Central Khartoum can be reasonably
represented by curves for soils E and D. Thus, thevalue peak ground acceleration (PGH) of 0.214g
which in ductility class moderate (DCM) with type D
soil were considered.
Spectrum Type
Table 1 and Table 2 summarize the seismic source
region of Sudan and its vicinity and summary of peakground acceleration (PGA) occurs up 50, 100, 200
and 250 years span in Central Sudan.
As according to Hassaballa et al. (2013), theseismic analysis used horizontal input motion ofearthquake with moderate in which ranging of peakground acceleration (PGAH) between 0.2-0.39. Also,
they referred the design ground acceleration ofCentral Khartoum, Sudan according to the research
conducted by Mohamedzein et al. (2004). The
maximum acceleration at the ground surface in Sudan
varies over small range from 0.19 to 0.243g. And it
was stated by Mohamedzein et al. (2004) and Abdalla
et al. (2011) that for practical purposes an averagevalue of 0.214g can be adopted for Central Khartoum.
The recommended choice is the use of two types ofspectra: Type 1 is recommended to be adopted since
the earthquakes that contribute most to the seismic
hazard defined for the site for the purpose ofprobabilistic hazard assessment have a surface-wave
magnitude, Ms, greater than 5.5 (6.4) as according toTable 1.
Table 1 Seismic source region of Sudan and its
vicinity (Abdalla et al. (2001))

Fig.1 A graph of spectral acceleration against
natural period

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Table 2 PGA (in g) with 10% probability of being
exceeded in time span (Abdalla et al. (2001))

MODELLING
The objective of this study is to perform analysis
and design of RC structure building as well as
improvement by using base isolation.
Dimension of RC Frame Structure

Fig. 3 Side elevation

Table 3 shows the dimensions of cross section
details of 10 storey RC frame structure prepared in
STAADPRO.

The seismic isolators in the system are defined as
spring placed between the fixed base and thecolumns. The parameters selected to define theutilized isolators in STAADPRO is soil spring withstiffness, K=16000kN/m. As dynamic analysis
normally 5% damped response spectra areconsidered, so the 5% damped response spectrum andthe effective damping ratio of the isolation system, as
defined in Eurocode 8, does not exceed 30%. Thus,
for spring base isolation system the damping ratio
was assumed as 20%. The RC models are analyzed
using Response Spectrum in STAADPRO using
Eurocode 8.

Table 3 Cross-section details for RC structure model
Floor level

G-5th

Columns (mm)Typical beams(mm)Slab thickness(mm)
Support system

500 ×300
400 × 300

6th to7Th
400×300

8th toRoof
300×300

130
Fixed / Spring base support system

The beam and column sizes are kept same for both
fixed and isolated RC structure. Plan view and sideview on RC structure frame are as shown in Fig. 2 andFig. 3.

RESULTS AND DISCUSSIONInter-Storey Drift
Table 4 shows comparative study of inter-storey drift.
The results that has been observed using response
spectrum analysis that the story drift in spring baseisolated building is higher at the ground storey than
fixed base building and decreasing as the story getting
higher. It was expected that the drift of the baseisolated building would be less than that of the fixedbase building.
In case of fixed base structure, storey drift iscomparatively lower than spring base apart fromground floor which is 0.196% while spring baseisolation system is 0.312%. However, although thespring based isolated structures shown drastic
increased in story drift at the ground storey andreduced significantly up to roof level.

Fig. 2 Plan view of foundation

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Table 4: Comparative study of storey drift (mm) in X
direction
Storey

Roof
8
7
6
5
4
3
2
1
GroundStorey Drift
(mm)
Fixed
Spring Based
Support
Isolation
SystemSystem15.26512.44425.57416.03424.28115.40129.68617.18239.74020.58545.27322.41050.06424.15654.02626.25156.95231.82660.25495.254

Fig. 4 Storey against lateral displacement ratio in x
direction between fixed support and spring based
support system
Base Shear

Lateral Displacement

Table 6 shows the comparative study of base shear
without base isolators and with base isolation support
system while Figure 4 illustrates the base shear
against the direction of earthquake

Table 5 shows comparative study of percentage
drift without base isolators (fixed) and with baseisolators system (spring) while Figure 4 shows storey
against lateral displacement ratio between fixedsupport and spring based support system.

Table 6 Comparative study of base shear (kN)Study case

Table 5 Comparative study of percentage drift in X
direction
Storey

Roof
8
7
6
5
4
3
2
1
GroundFixed
Support
System1.315%
1.265%
1.181%
1.102%
1.004%
0.874%
0.726%
0.561%
0.384%
0.197%

Fixed Support
SystemSpring Based
Isolation System

Spring Based
Isolation
System
0.923%
0.882%
0.829%
0.779%
0.723%
0.655%
0.582%
0.502%
0.417%
0.312%

Base Shear (kN)
X direction
Z direction
5572.366400.912197.293384.36

The base shear value for fixed support system is5572.36kN and the base shear for spring baseisolation system is 2197.29kN for x direction
earthquake whereas 6400.91kN for fixed support
system and 3384.36kN for spring base isolation
support system in z direction earthquake. It has been
observed that the base shear for base isolated building
is reduced to average range of in x direction 60.57%
and 47.13% in z direction from the fixed basebuilding. Comparison is shown in Fig. 5.

The percentage of lateral displacement ratio at
ground storey to first storey of the reinforced concrete
structure in fixed based system is lower compared tospring based isolation system. At ground floor, theratio gives the smaller value of 0.139% for fixedsupport system and 0.312% for spring based isolation
system. However, the lateral displacement ratio has
been decreased at the spring base isolation systemcompared to fixed base systems as the storey getting
higher. The percentage of lateral displacement ratioof roof or top storey obtained in fixed support system
is 1.315% and spring based isolation system is0.923%.
The lateral displacement of spring based isolation
system building is expected to be less than that of the
fixed-base building. Spring base isolated structures
are likely to have larger displacement at lower level,
as they are separated from the ground. In other words,
base isolation lets the buildings to move over the
ground so that they have less frequency.

Fig. 5 Base shear against the direction of earthquake

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model was intentionally designed to limit theearthquake force transmitted to the structures.
Considerably, higher target period of isolation is
obtained using spring which can lead to a better
performance. Mode shapes of buildings depend on
overall geometry of building, geometric and material
properties of structural members, and connections
between the structural members and the ground at thebase of the building. The data was presented in graphof period against mode as in Figure 6 and Figure 7 forfrequency against mode.

Mode Shapes, Period and Frequency
Table 7 and Table 8 show the value of time period andfrequency for their respective modes that are obtainedby analysis of structure using response spectrum
method for building with fixed base and spring based
isolation system building.
Table 7 Comparative study of period in seconds
Mode

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

Period(second)
Fixed Support
Spring Based
SystemIsolation System
1.781842.51416
1.51689
1.93852
1.46657
1.89474
0.595240.75258
0.54349
0.64193
0.523990.61449
0.35886
0.398020.31198
0.394940.307110.36704
0.24816
0.34852
0.219630.340070.215220.335380.206890.31177
0.19432
0.296320.186270.26714

Percentage
different
(%)
41.10
27.80
29.20
26.43
18.11
17.27
10.91
26.59
19.51440.44
54.84
55.831
50.69
52.49
43.41

Fig. 6 A graph of period against mode

Table 8 Comparative study of frequency in cycle persecond
Mode

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15

Frequency(cycle/second)
Fixed Support
Spring Based
SystemIsolation
System
0.561
0.398
0.659
0.516
0.682
0.528
1.680
1.329
1.840
1.558
1.908
1.627
2.787
2.512
3.205
2.532
3.256
2.752
4.030
2.869
4.553
2.941
4.646
2.982
4.834
3.207
5.146
3.375
5.369
3.743

Percentage
different
(%)
29.06
21.70
22.58
20.9
15.32
14.73
9.87
21.00
15.48
28.8
35.41
35.82
33.66
34.41
30.28

Fig. 7 A graph of frequency against mode
Elastic Spectral Acceleration
Figure 8 shows graph of elastic spectrum
acceleration against period. The elastic spectral
acceleration for spring based isolation system issmaller compared to fixed support system. The baseisolation system reduces the frequency of thestructure from its fixed base frequency thus reduces
the structure in the higher spectrum to lower regions.

Period for both support system cases decreasingfrom first mode shape to fifteenth mode shape.
However, spring base isolation support system has
higher period compared to fixed base support system.
By referring with the frequency equation of the spring
based isolation system has smaller frequency fromfirst mode shape to fifteenth mode shape compared to
fixed support system.
Spring based isolation system has lower
frequency compared to fixed support system. The
period needs to be increased to reduce the frequency
in order for the structure to survive under theearthquake excitation. In this study, the base isolation

Fig. 8 Elastic spectral acceleration against period
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SEE - Nagoya, Japan, Nov.12-14, 2018

Spring base isolation system brought to large
reduction in the range of short periods and highfrequencies compared to fixed based system. The
damping causes high frequencies by increase intransmissibility at short period. Since the damping of
the isolated building (20%) is 4 times that of the fixedbase building (5%), the damping coefficient
contributes positive effect to the behaviour of thestructure flexibility. The spring based isolation
system structure reduces the response of the first
fixed base mode of the upper structure. A baseisolation system must be sufficiently flexible to cause
the fixed base excitation period (frequency) of theisolated structure to be significantly longer than first
fixed base system excitation period.

spectrum to lower regions. Besides that, it brings
additional damping due to the increased damping
from 5% to 20% introduction at base level, and thus
further reduction in the spectral acceleration isachieved.
REFERENCES[1] A. E. Hassaballa, Fathelrahman M. Adam., M. A.
I. Seismic Analysis of High-Rise Building by
Response Spectrum Method. International
Journal of Computational Engineering Research,
3(3), 2013, 272–279.
[2] Abdalla, J. A., Mohamedzein, Y. E., & Abdel
Wahab, A.. Probabilistic Seismic Hazard
Assessment of Sudan and Its Vicinity.pdf.
Earthquake Spectra, 17(3), 2001, 399–415.
[3] BS 8110-1:1997.. Structural use of concrete,(December), 2002, 160.
[4] Efiloglu, M. . Understanding the Concept of Base
Isolation, 1(July 2013).
[5] Eurocode 2: Design of concrete structures - Part
1-1 : General rules and rules for buildings.
British Standards Institution, 1(2004), 230.
[6] Eurocode 8 : Design of structures for earthquake
resistance —. (2011). Buildings, 3.
[7] Kamble, A. R., Khot, M. S., Kagale, H. K., &Magdum, S. S. Seismic Analysis Of Symmetric
Building With Base Isolation Technique.
International Journal of Recent Innovation in
Engineering and Research, 2 ( 3 March – 2017 (IJ R I ER)), 2017, 80–84.
[8] Mohamedzein, Y. E., Abdalla, J. A., &Abdelwahab, A. B. 13 th World Conference on
Earthquake Engineering Development of Design
Response Spectral For Central, 2004, 1508.
[9] Mohamedzein, Y. E., Abdalla, J. A., &Abdelwahab, A. B.Development of Design
Response Spectral for Central Khartoum, Sudan.
13th World Conference on Earthquake
Engineering, 2004, 1508.
[10] Mohamedzein, Y. E., Abdalla, J. A., Elsharief, A.
M., Abdelwahab, A. B., & Ahmed, E. O. (2001).
Seismic Microzonation of Central Khartoum ,Seismic Microzonation of Central Khartoum ,Sudan. Fourth International Conference on
Recent Advance Geotechnical Earthquake
Engineering and Soil Dynamics, (June 2016).
[11] Santhosh, H. P., Manjunath, K. S., & Kumar, K.
S. Seismic Analysis of Low To Medium Rise
Building for Base Isolation, 2013, 1–5.

CONCLUSIONSThe story drift for base isolated building withspring from response analysis was more compared to
fixed based building at ground level and reduced as
the height increases. The displacement of spring
based isolation system building was smaller
compared to the fixed base building due to provided
flexibility controlled by the base isolators. From theanalysis data, it can be summarize that base isolatedbuilding has more favorable behaviour compared to
fixed base building. The base isolation system
substantially increases the time period of the building
and reduces the base shear. A base isolation system
must also carry sufficient damping to suppress
possible large displacement of the upper structurecause by seismic excitation. Thus, the period needs toincrease to reduce the frequency in order for the
structure to survive under seismic load.
According to the analytical study following
conclusion were drawn:
1. Base isolated structures shown drastic
increased in story drift at the ground storey andreduced significantly up to roof level.
2. In case of fixed based structure displacement
was lesser only at lower storey of a structure but
increased significantly when the storey heightincreases compared to spring base isolation systemheight in which it has higher at ground level but lesser
at top storey.
3. The base shear for fixed base from response
spectrum analysis was 60% times of base isolated
structure. Therefore, the base shear value of baseisolated structure was smaller compared to fixed basestructure
4. The base isolated structure substantially
increases the time period of the building and hencecorrespondingly reduces the frequency.
5. The elastic spectral acceleration for spring
based isolation system is smaller compared to fixedsupport system. The base isolation system reduces thefrequency of the structure from its fixed basefrequency thus reduces the structure in the higher

549

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

STRENGTH AND BEHAVIORS OF DRY-JOINT RETAINIG NANOBLOCK
PoungchompuPongsagorn1*, Buyarat Tanakrit1, Bubpi Attaphol1
1

Rajamangala University of Technology Khonkaen Campus, Thailand

ABSTRACTThis research studied the strength and behaviors of dry-joint retaining walls built with nano blocks, a new
product made from wet-cast concrete of the size 20×40×18cm, with the weight of 15kg/block, and thecompressive strength of 94kg/cm². Construction of retaining walls with these dry-joint nano blocks–both forpermanent and temporary walls – is simple, convenient and fast without having to rely on skillful workers.
The research started from producing a prototype scale model of 1:12.5 for determining appropriate
experimentation. The structure of the retaining wall using 2.00×1.65×0.20meters dry-joint nano blocks
allowed distribution of lateral earth pressure through the sand in a semicircular-cut cylindrical mold of 15cm
radius and 1.60 meters height. Pressure was applied step by step all through the test. Gauging of bothhorizontal and vertical displacements was performed using a dial gauge. The testing program for the nanoblock retaining wall comprised 5 patterns of walls: half-block, half-block with 1.38kg-m steel reinforcement,
half-block with 2.77 kg-m steel reinforcement, half-block with 4.15kg-m steel reinforcement, and anchoredhalf-block with1.38kg-m steel reinforcement. Horizontal displacement was checked stepwise. Comparison of
the efficiency of the 5 patterns showed that the half-block nono-block retaining wall demonstrated the highest
horizontal displacement The retaining wall yielding the highest efficiency was the anchored half-block with
1.38kg-m steel reinforcement, with the least horizontal displacement of 2.90mm. It can be concluded thatsteel reinforcement and structural anchoring increases stability of nano-block retaining walls in terms oflateral compressive strength.
Keywords: Retaining wall, Nano blocks, steel reinforcement, Anchoredwall models because they will be useful for thosewanting to investigate further related topics [4, 5,
and 6].
The lateral pressure of soil exerting on
retaining wall can be categorized into 3 types:-At-rest condition or no movement-Active condition or movement away fromearth filling-Passive condition or movement toward earth
filling
Retaining wall failures are caused by two
major factors:-Internal instability, structural failures occur
because of the design strength which is not
sufficient to accommodate moment or shear force.
-External instability, retaining wall has externalstability when they do not slide, settle, or collapse
due to load on soil bearing under the foundation[7].
Combined structure means a structure that iscomposed of two or more materials adjoined
tightly until they function as one material. The
objective of a combined structure is to increase
strength to the structure by adding a high-strength
material to a low-strength material.
A combined structure behaves in such a waythat slides at the contact surface will not happen

INTRODUCTION
The present construction operations need totake into account the cost, ease, and convenienceof work as well as short project period.
Nevertheless, for some types of construction, soil
retaining walls have to be built before the main
structure. In engineering construction, retaining
walls are usually designed with reinforcement forstructural strength. The researchers are interested
in nanoblock concrete, which is an alternative andpromising material for constructing retention
walls. Nanoblocks are made from wet-cast
concrete that offers better engineering properties
than dry cast or compression. Wet concrete isstrong, durable, and locally available. Construction
can rely on local labor and can be done without theuse of bulky machinery. Nanoblocks, as aninnovative material, do not require a high cost oftransportation and are easy to remove without
skilled workers. [1, 2, 3].
There is to date little research on retaining wallmodels due to the complicated preparation of thesimulation
modelsthemselves.
Therefore,
information related to the movement behaviors ofretaining wall is not available. However, someresearchers are still interested to study retaining
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since shear force is sufficiently transferredhorizontally to the two materials. In a noncombined structure, the contact surfaces between
the structures slide, resulting in each individual
structure receiving moment separately [9].
MATERIALS AND METHODSThis research began from studying andproducing a small-scale prototype model(Fig.1),
compiling information, understanding all relevant
components including approaches, patterns, andthe possibility of the project before appropriately
planning work on material selection, designing thestudy format, planning experiments and variables
control. The retaining wall test cases installation
details as following-Testing retaining wall with half- nano block
Combined structure:-Exerting force of 10 pounds (1.38 kg-m)-Exerting force of 20 pounds (2.77 kg-m)-Exerting force of 30 pounds(4.15kg-m)-Testing retaining wall with half-bricks
interlocking bricks, reinforced bars and anchorage(1.50m*2.0m)-Exerting force at 10 pounds

Fig.2 Nano blocks
http//:www.thainanohouse.com-Rubber Sheet
The rubber sheets were used in the study toprevent sand flowing from the mold. The 10cm
wide and 2.0mm thick sheets were freshly madeand attached to the mold edges that contact two
retaining wall. The height was equal to theretaining wall.
-Vertical reinforcing steel
Sixteen 12 mm threaded steel studs wereused to reinforce the retaining wall structure. The
studs’ tensile strength was tested based on thestandard. These studs were as long as the retaining
wall and were 1.6m high. Both ends were bolted
and the force used for the bolt was set.
-Pound wrench
The pound wrench had the highest accelerationof 90 pounds. It was used to tighten the reinforcing
steel stud inserted into the retaining wall structureso that the tightening force was consistent.
-Test pond
The test pond measured 1.90x2.00x5.00m. It
consisted of a restraining bar set on top- Semi-circular iron moldThis is a cylindrical iron mold cut vertically inhalves with a radius of 1.5m, height of 1.60m and
8.0mm thickness. Its strength was increased byiron fins at every 0.50m distance. The iron molds
are simply used for dissipating lateral soil pressure.
-Iron plate
Iron plates that dissipate force have a radius of
0.15m and are 8.0mm thick. They have been
designed to fit the iron mold. These iron platesdissipate the pressure from hydraulic jacks tofilling sand.
-Hydraulic jacks
The hydraulic jacks under this study gave
external vertical pressure. This simulated an
external force exerting on filling sand and soil inthe model. The hydraulic jacks used were 30 tons.
- Dial gauge
Dial gauges with 0.01 fineness were used tocontrol vertical settlement of sand and gaugehorizontal movements of the retaining wall.
-Sling wires
Two sling wires were used between the 3
upper reaction beams and the anchor set toincrease their work efficiency by behaving
together.

Materials and Equipment used in the Tests- nano block as shown in Fig.2
measures20*40*18cm(width*length*height) andweighs roughly 15kg per block, compressive
strength of about 94 ksc per block .
-Sand
The sand used for filling here was Puttaisongsand. The weight was 1,495 kg/m3. Sand wasselected as a tested material for filling, which wasquite close to a research study by Liyan Wang[10]Fig.1 small-scale prototype model

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- Reinforced bars and restraining beam
Reinforced bars functioned like an iron anchor
enhancing stability to our retaining wall withinterlocking bricks. The 16 reinforcing steel studs
used had 12 mm threads all through their lengthand each was 1.60m long. One end of each stud
was joined at the upper end of the retaining walland the other was locked with steel plate and nut tothe C-shaped restraining beam so as to prevent
movement while being tested.
Retaining wall test set up
The retaining wall test installation details as
following (Fig.3, Fig.4, and Fig.5)
Number 1
A back supporting set to stopmovement of mold during the test
Number2
Two sling wires transferringforce to the test set below.
Number3
Iron mold 1.50m high, 8mm
thick with a radius of 15cm
Number4
One 30-ton hydraulic jack with araising capacity of 10cm
Number5
6 dial Gauges with 0.01mm
gradation, 2 installed at the tops of the test piles
and 2 each at the two-sided test anchorages
Number6
Three 4x4in cross-section, 6m
long steel rods
Number7
Test anchorages made fromreinforced concrete on the left and right sides of
the test piles
I-Beam 0.50m long strengthened
Number8
with 6mm steel plate welded at the center
and wings of I-Beam to prevent deformation
during the test
Number9
A 10-ton hydraulic jack with araising capacity of 10cm to transfer force fromLower beam to upper beam and prevent
deformation of lower beam during the test
Number10
9mm RB used to support lower
beam to remain at itslevel while other equipment
was installed
Number11
Threaded bolts to hold upper andlower beams so that they behaved similarly whenmoving during the test
Number12
Retaining wall 1.50m high, 2mwide made of interlocking bricks, with the bricksize of 12.50x25x10cm
Number13
Steel plate with a radius of 15cm
and thickness of 8mm
6 reaction beams or I-Beams 6m
Number14
long of the size HxB = 150x75, t1 = 5, t2 = 7,
r = 8, and cross-sectional area of 17.85cm2
Number15
Slings to tie between 3 upper
reaction beams and anchors to increase work
efficiency from co-behavior
Number16
6 square anchorage piles of thesize0.18x0.18x4.00m, 3 on each side bolted onto
the foundation of the pile test set

Fig.3 Pond Test (Top view)Fig.4 Pond Test (Side view)Fig.5 Test set up (Front view)

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The retaining wall test procedure detail asfollowing
2.3.1 Testing movements of retaining wall laidwith half-nano block, reinforced bars andanchorages (Fig.6 and Fig.7)-Prepare the reinforced barest set with sixteen
1.60m high, 12mm threaded studs, turn tightly
with pound wrench for accelerating internal force
of interlocking bricks-Weigh the sand and fill the unit weight was
1,495 kg/m3 until the last layer- Install steel studs and the anchorage set withthe vertical studs- Add 10-pound force to vertical studs andhorizontal studs, tighten the nut so that they adjoin
the restraining beams-Install hydraulic jacks and 2 dial gauges tomeasure sand vertical settlement-Install dial gauges to measure horizontal
movementsof7
retainingwall
at0.05,0.25,0.45,0.65,0.85,1.05 and 1.25m, with the
top position of retaining wall being 0.00m-Add load layer by layer, each at 1.00mm
settlement of filling sand and record results ofhorizontal movements of retaining wall
-Perform the testing until the settlement offilling sand reached 25mm; record the results ofhorizontal movements of retaining wall
-Repeat the tests in triplicate to obtain accurate
information of movement trends

Fig.6 Half nao block with reinforced bar andanchorage test set up (Front view)Fig.7 Half nano block with reinforced bar andanchorage test set up (Back view)

TEST RESULT AND DISCUSSIONS
When we were confident of the results from thestudy of the small-scale model, the large-scalemodel was constructed to study the behaviors ofeach type of retaining wall’ lateral pressure
resistance as shown in Fig.8. The five types ofretaining wall studied were: retaining wall laidwith half nano block (Fig.9); retaining wall laidwith half nano block and reinforced bars given
force of 10lb, 20lb and 30lb(Fig.10); retaining walllaid with half nano block, reinforced bars given
force of 10lb and anchorage (Fig.11); Tests weredone in triplicate to observe their tendency todeform. The results obtained were used to buildgraphs for comparing the data.

Fig.8Test results-The results of the five tests to compare theefficiency of horizontal movement of the retaining
wall showed that the control over filling sand was
at 25.00mm, which was the highest settlement
parameter. The greatest horizontal movement of
the retaining wall was studied; the most efficientretaining wall should move the least, which was
found to be the retaining wall laid in one layer with
10lb reinforced bars with anchorage.

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In order to find elastic modulus of the wall(Fig.12), strength or weakness of a combined
structure is its stiffness value which depends onthe elastic modulus (Etotal) and inertia moment (I)of the cross-section. The walls laid with half nano
block with no reinforcedbars showed uncombined
failure. Retaining wall strength depends merely on
weight over it and friction of material surface. Thisdiffers from a retaining wall with half nanoblockand reinforcedbars where failure will be partially
uncombined. Here, inertia moment values areequal showing that the strength of a retaining wallwith half nano block and reinforced bars depends
on elastic modulus (Table 1)

Fig.11 Half nano block test with reinforced bar
anchorage (Front view)

Table 1Composites elastic modulus

Fig.12 Composites elastic modulus test set up(Front view)
The analysis under this study was conducted bycomparing the costs of the construction material
against the maximum horizontal movement of the
5 types of retaining walls, namely: 1) halfnanoblock retaining wall, 2) half-nanoblock
retaining wall cast with a 1.38kg-m reinforced
sheet, 3) half-nanoblock retaining wall cast with a
2.77kg-m reinforced bar, 4) half-nanoblock
retaining wall cast with a 4.15kg-m reinforced bar,and 5) half-nanoblock anchored retaining wall castwith a 1.38kg-m reinforced bar. When consideringhorizontal movement of these structures, the halfnanoblock anchored retaining wall cast with a
1.38kg-m reinforced bar showed the greatest
strength because of its lowest movement value.
However, the cost of the half-nanoblock anchoredretaining wall cast with a 1.38kg-m reinforced bar
was the highest. The most appropriate structure,
considered by comparing the cost and horizontal
movement, was the half-nanoblock retaining wall
cast with a 4.15kg-m reinforced bar. Its cost was
1,062THB/m2 and its horizontal movement was
4.30mm.

Fig.9 Half nano block test set up (Front view)Fig.10 Half nano block test with reinforced bar(Front view)

The researchers investigated the behaviors of theretaining wall built with nanoblocks and anchorage.
The test was compared with the result of a relevant
study by Pongsagorn et al. (2018). The comparison
was performed between the 3 patterns ofhorizontal movement, the elastic modulus values,

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the cost per square meter, and the highest
horizontal slides of each retaining wall.
The horizontal slide of half-block interlockingbrick retaining wall under control of fill sandsettlement at 25 mm reached the maximum
movement at 8.48 mm in a curvilinear pattern.
The maximum horizontal movement of the
nanoblock retaining wall was less than theinterlocking-brick retaining wall with lesscurvilinear movement tendency.
Half-nanoblock retaining wall cast with a
4.15kg-m reinforced bar.The maximum horizontal
movement of the half-nanoblock retaining wall
cast with a 4.15kg-m reinforced bar was 4.40 mm
in an approximately linear pattern. The maximum
horizontal movement of the nanoblock retaining
wall was lower, but also in a linear pattern.
Half-nanoblock and anchored retaining wall
cast with a 1.38kg-m reinforced bar.The maximum
horizontal movement of the half-nanoblock
anchored retaining wall cast with a 1.38kg-m
reinforced sheet was 3.06 mm in an approximately
curvilinear pattern since the anchor at the very endof the wall decreased the horizontal movement.
The comparison showed that the maximum
horizontal movement of the nanoblock retaining
wall was much lower than the interlocking brickwall and was in a concave pattern, indicating theefficiency of the nanoblock retaining wall.
Comparison of the elastic modulus of retaining
walls.The elastic modulus of the nanoblock
retaining wall was higher than that of theinterlocking brick retaining wall, proving its
greater stability.
Comparison of reinforcement steel adhering
tools.The interlocking brick retaining wall wasconstructed by placing a washer before steel
reinforcing. The nanoblock retaining wall wasconstructed by using a steel plate to position thereinforcing steel. The plate was cut into a shapeequal to the nanoblock so that there was no
movement of reinforcing steel during the test.
Comparison of cost per square meter with the
maximum horizontal slides of retaining walls.The
cost of the interlocking brick retaining wall was
1,020 per m2.The cost of the nanobrick retaining
wall was slightly higher than the interlocking brickretaining wall. Therefore, nanoblock is analternative material for constructing a retaining
wall. The findings provide the information usefulfor those interested in building a retaining wallwith this material.
The half-nanoblock retaining wall cast withreinforcing steel at 20-30 pound reinforcement
range was found to be the most appropriate

Fig.13 Comparison efficiency

CONCLUSION
Based on bricks retaining wall model test
results, the following conclusions can be drawn:
The behavior of dry-retaining wall nanoblock
without reinforced bars shown uncombined failureand can support low pressure. With reinforced bar
and anchor showed partially uncombined.
The addition of reinforced bar to a significant
reduction of lateral deformation
The results of the four tests to compare theefficiency of horizontal movement of the retaining
wall showed that the control over filling sand was
at 25.00mm, which was the highest settlement
parameter. The greatest horizontal movement of
the retaining wall was studied; the most efficientretaining wall should move the least, which was
found to be the retaining wall laid in one layer with
10lb reinforced bars achorage.
ACKNOWLEDGEMENTS
The authors are grateful to the Khon Kaen
Campus of the Rajamangala University ofTechnology Isan for supporting the research.
.
REFERENCES[1] Villemus B., Morel J.C, Boutin C Experimental
assessment of dry stone retaining wall stability
on a rigid foundation. Engineering Structures,
Elsevier, 2007, 29 (9), pp.2124-2132; 2006
[2]Anne-Sophie Colas, Denis Garnier, JeanClaude Morel, Yield design modeling of dry
joint retaining structures. Construction and
Building Materials, Elsevier, 2013, 41, pp 912917; 2013[3] Morel J.C. Experimental assessment of dry
stone retaining wall stability on a rigid
foundation.availablefrom:www.elsevier.com/locate/engstruct.
25 August 2016.
[4]Morel J.C. Building houses with local
materials: Means to drastically reduce theenvironmental impact of construction. Building

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SEE - Nagoya, Japan, Nov.12-14, 2018and Environment, 2001
[5]Morel J.C. Full-scale field trials to assess drystone retaining wall stability.EngStruct, 2010.
[6]Poungchompu P., S. Hayashi, D. Suetsugu., andY. J. Du (2008), “Investigation into
performance of Raft & Pile supported
embankment on soft ground”. GeotechnicalEngineering Journal.Vol.39, No.4, pp.185-190.
[7]Bowles, J.W. (1988). Foundation Analysis andDesign. New York: McGraw Hill. pp. 589-693.
[8]Principle of foundation engineering handbook.
5th. Tomson brooks/Cole Publishing, USA, pp.
293-385.

[9] Poungchompu P., S. Hayashi, “Investigation on
Raft composites for construction”, The 4th
KKU International Engineering Conference
2012 (KKU-IENC 2012) “Driving together
towards ASEAN Economic Community”
Faculty ofEngineering, Khon Kaen
University, Thailand, May 10-12, 2012.
[10]Liyan Wang,Experimental study on seismic
response of geogrid reinforced rigid retaining
walls with saturated backfill sand.available
fromwww.elsevier.com/locate/geotexmem.25
August 2016.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ASSESSMENT OF STRENGTH PARAMETERS OF UNREINFORCED
MASONRY (URM) BLOCKS IN HERITAGE STRUCTURES IN THE
PHILIPPINES
Lessandro Estelito Garciano1, Darlene Clarice Campado2, Nitchell Andrei Castillo3, Mary Grace Odiamar4,
and Marcelino Tongco5, Jr.
1
Faculty of Civil Engineering, De La Salle University, Philippines; 2,3,4,5 De La Salle University, Philippines

ABSTRACT
Unreinforced masonry (URM) heritage structures, because of their rudimentary building techniques, arevulnerable during extreme environmental events, particularly earthquake. Limited literature involving thesestructures provide added challenge for establishing sound engineering solutions in their preservation, considering
their significance in a country’s history. Additional studies on the mechanical properties of masonry blocks –compressive, shear, flexural strengths, modulus of elasticity, etc., could provide an insight on the behavior ofstructural components subjected to excessive loading conditions, and establish parameters which can be used forseismic vulnerability assessments.
The blocks considered in this study are adobe, coralline limestone, and sandstone units. These samples are
acquired from selected heritage structures and subjected to lead tests. Customized setups for shear and flexure tests
were fabricated by the authors for the lack of standard test methods. Results show that response of earth masonry
to various loading setups was characterized by monolithic behavior, distinct lack of elasticity, and intense
deformability. Furthermore, strength values obtained from local samples of adobe and coralline limestone dictatethat they are best suitable only for single-story unreinforced structures, defined to be less than 13 m or wall area
not exceeding 12 m2. Sandstone, while stronger in performance, posed a very drastic failure mode in the form ofsudden shear and chipping off the member. Nevertheless, the masonry fabric proves to require further
strengthening measures in resisting forces, as shown by their strength parameters.
Furthermore, stress-strain properties of each sample show that sandstone, the type with the greatest material
strength, exhibited the smallest plastic deformation and abrupt failure, while adobe, with the least average strength,
exhibited the longest plastic deformation and gradual failure. Finally, a map is presented to show the spatial
diversifications of URM fabric as used on heritage structures per region in the Philippines, the most common ofwhich are coralline in Visayas and adobe and clay bricks in Luzon.
Keywords: Unreinforced masonry, Heritage structure assessment, Modulus of elasticity, Compressive strength
masonry, Shear strength masonry

INTRODUCTIONa strength parameter not commonly researched upon
unlike its compressive and flexural strength, but it isa factor that should not be neglected especially whenseismic forces are taken into consideration. A study
was conducted [2] wherein a masonry wall, when
loaded about the vertical axis, caused a splitting cycle
which generated vertical cracks in the upper part of
the wall. Furthermore, such kinds of shear failure arecommonly observed at vertical corner angles, or near
the corners of the wall [3].
Accounting for these detrimental effects, and withthe recent 2013 Bohol Earthquake, a multi-hazard
vulnerability assessment of heritage structures in thePhilippines was conducted using FAMIVE [4]. The
procedure consisted of setting up a reliable inventory
profile defining the exposure of heritage structures in
the region of interest. Identification of relevantbuilding features that affect the structural
performance was also considered, leading to aselection of specific case studies with performance-

Heritage structures in the Philippines are, at best,
representative of the country’s rich cultural diversity
and lineage, as exemplified by the many churches,chapels, convents, watch towers, bell towers, etc.
scattered throughout the archipelago. These
structures are also indicative of the state-of-the -artmaterials and construction methods at the time they
were erected, circa 15th to 19th century, utilizing
mostly unreinforced masonry (URM), timber, andother indigenous construction materials [1]. Overtime, the in-situ condition of the URM fabricdeteriorated, increasing the failure probability during
extreme environmental events. This failure variability
can be determined through analyzing the strengthparameters – compressive, shear, flexural strengths,
and modulus of elasticity, of individual blocks used
to create said fabric.
The shear strength of a masonry block, for one, is557

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based assessment framework introduced. From then,a quantitative approach for earthquake and typhoonassessment and safety conservation frameworks wereconsidered in said study. The absence of data for themechanical properties of URM was compensated bysaid research through assumptions of values utilizing
other studies from foreign literature.
The lack of local references for strengthparameters of commonly used URM blocks in the
country became the main objective of this paper: tofurther provide assessment of mechanical properties
of in-situ URM fabric used in selected heritage
structures and determine by experimentation therange of in-situ values of the most available andubiquitous URM materials locally – adobe, coralline
limestone, and sandstone, whose results can be used
for more in-depth assessment on vulnerability andmitigation measures in the country.

shear force over the shear area.
As for compressive testing, uniaxial compressive
force was applied perpendicular to the bed surface tosimulate compression loads experienced by themasonry block in-situ. The results that come from thecompressive strength test were also used for thedetermination of Modulus of Elasticity, computed as
the stress over strain or the slope of the linear graph,
the graph up to the yield point of the stress-strain
diagram for each masonry type. In this regard, adistance-amplifying instrument or a dial indicator
was installed on the UTM to measure thedisplacement of the top fiber during loading until
failure.

MATERIALS AND METHODOLOGYThe URM blocks used in the study were gatheredfrom specific regions in Luzon and Visayas where
heritage structures of distinct types of masonry are ofabundance – coralline limestone in Samar, Southern
Philippines; adobe in Intramuros, Manila, andsandstone in Pangasinan, north of Luzon. Fivesamples for each block were allotted for compression
testing; 3 samples for each block type were allottedfor shear, and another set of 3 samples each for
flexure testing. The acquisition of more samples wasconstrained by the availability of debris that werefrom the heritage structures themselves.
The block samples for compression and shear test
block have a minimum length-to-width ratio of 2, asprescribed by section 14.7.4.11 of the 2015 New
Mexico Earthen Building Materials Code used formasonry blocks in general testing [5] and theTechnical Standards in masonry specifications [6].
Using a diamond-brushed saw, the samples werepartitioned and cut into 4’’ x 4’’ x 8’’ blocks forcompression and shear tests, and 1.5’’ x 4’’ x 8’’ forflexure tests. To ensure even load distribution on theblock surface, rough surfaces were smoothened withplaster.

Fig. 1

Loading and instrument setup for shear test

The flexural strength of the blocks, on the other
hand, was obtained as the product of maximum
moment and distance of outermost fiber from theneutral axis experiencing the maximum stress, allover the moment of inertia computed from thetransverse cross-section of the block. The load rateapplied in the testing was at 0.01 MPa/s, withconsideration on the block dimensions and therigidity of the blocks. To obtain this parameter, acustomized flexure setup was fabricated as available
setups were either too large or too small for the
samples. A detailed flexure setup and 3D model withthe loading direction can be seen in Fig. 2.

Shear, Compressive, And Flexural Test Methods
For shear test, a customized shear setup was
fabricated to induce shear failure for each block. One
end of the block was constrained and the other half,
its free end, was subjected to an area load on the top
surface as shown in Fig. 1. Two fasteners held thefixed end on each side to prevent rotation. A steel
cube on top of the block transformed the concentrated
UTM load into an area load. Loads, including failureload, were recorded at various stages, and stored forpost-processing. The average shear stress was thencalculated by the general shear formula of applied

Fig. 2

Loading and instrument setup for flexure

To simulate flexural failure, blocks were madethin enough (1.5’’ x 4’’ x 8’’) to avoid compression
strut, an occurrence in which a block loaded on one
face develops compression along a diagonal from the
support to the applied load, as observed on deep
beams defined in 2010 National Structural Code of558

SEE - Nagoya, Japan, Nov.12-14, 2018

the Philippines provision 410.8.1 [7].

structural material for low-rise construction, based on
the assessment by the World Federation ofEngineering Organizations (WFEO) in 2011 [8],although their durability still depends on various
factors such as the manner of placement in wallconstruction and strength of interface between
adjacent blocks.
From Fig. 4, some adobe, coralline, andsandstone, were seen to take the shear failure and its
internal distribution along the midspan, althoughmore than one shear plane was observed in otheradobe and coralline samples. This failure can be most
likely attributed to the composition and density, as thetwo types had almost equal amount of denseness.
Sandstone, being the densest type among the three,yielded to the expected failure plane.

RESULTS AND DISCUSSION
Prior to shearing test, a shear preload was alreadyintroduced in the masonry block, based on the weightof the steel block (0.11625 kN) placed to initiate
distributed load on the unconfined half portion of themasonry block and added to the maximum load
indicated by the testing machine.
For the shear results shown in Fig. 3, adobe andcoralline limestone types from Manila and Visayas,
respectively, yielded almost the same strength,
resisting almost the same amount of forces
throughout the six tested specimens.

Fig. 4

Failure of masonry blocks due to shear

As for compressive strengths, adobe yielded thelowest mean of 7.488 MPa, the summary of which
can be seen in Fig. 5, with recorded values ranging
from 6.49 MPa to 8.95 MPa. The mean compressive
strength of coralline was not far off, with average of
7.77 MPa.

Fig. 3 Summarized shear strengths of masonry
samples
These values though, were inferior to the strengthof sandstone, yielding mean shear strength of 7.93
MPa or a little more than twice the combined mean
shear strengths of the first two masonry types. The
mean maximum load carried by the sandstone
samples was 64.716 kN. Theoretically, the shear
strength of a single block of sandstone surpasses eventhe combined material strengths of both adobe andcoralline. To fail an adobe brick, it would requirealmost the same loading and effort as failing acoralline limestone block, but sandstone would
require more than three times of the same loading toattain the same failure as that of the previous two
types.
These values mean that each individual block has
shear strength properties that make them suitable as

Fig. 5 Summarized
masonry samples
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The obtained compressive strength range ofadobe, coralline, and sandstone limits them to be used
only for single-story structures if they are to remain
unreinforced, as these blocks are inadequate alone insustaining greater degree of loads especially as
structural members or walls [8].
This data was in line with the specifications fromthe same assessment by WFEO, stating that in
unreinforced brick walls for single-story structure for
Asia [8], the compressive strength of brick must be atleast 30 kg/cm2 or 2.94 MPa, and wall area that thebricks would cover must not exceed 12 m2.
Furthermore, for earthquake-prone countries,
particularly in Japan, it requires that masonry units
should be applied only for walls not exceeding 10.8m,
with slenderness ratio between length and thickness
more than 1/12. Each masonry unit must haveallowable compressive strength of 1/3 of thesustained forces and 2/3 of the temporary forces
specified by their Code.
The flexural strengths of the masonry samples,
meanwhile, are summarized in Fig. 6.

Fig. 6long to fail in flexure, where an abrupt collapse after
reaching peak load was observed in all specimens,
coinciding with the expected output and in contrast to
the gradual failure induced by compression.
Experiment-wise, a single crack propagating fromthe bottom fiber of the specimens was generally
observed for all samples. These failures verify thehomogeneity as observed from similar studies [9].
The cracking patterns were generally the same foralmost all specimens, as shown in Fig. 7.

Fig. 7

Failure of masonry blocks due to flexure

Concerning the stress-strain curve, a long,continued shortening after the elastic limit wasobserved for adobe specimens in Fig. 8a, indicating
the less brittle property compared to other samples.
The elastic region and the elastic limit were identified
through the sudden plunge in the curve that signifies
the start of plastic deformation. The respective
equations on the elastic region take a general linear
form.
Values for slopes of the graphs ranged from721.27 MPa to 1058.9 MPa for adobe blocks. Mean
Modulus of Elasticity was then taken to be 869.78
MPa or 0.87 GPa. A low gradient of the straight line
at the elastic region means that at a low compressive
stress, a considerable amount of deformation wasapparent.
Sandstone samples, meanwhile, exhibited
smallest plastic deformation with stress-strain
diagrams propagating to rapid failure, as shown in
Fig. 8b. The slopes from the graphs of the elastic
regions were relatively higher compared to those of
adobe and coralline limestone, while the elastic
modulus yielded a mean of 5083.86 MPa or 5.83 GPa,from the range of 3.3-7.0 GPa. A higher elastic
modulus indicates that its stiffness is greatest among
the three types, especially when compared tocoralline limestone.
For the latter, a plunge was observed after the
samples have reached elastic limit as shown in Fig.
8c. At this point, the material could no longer resist
loads without permanent deformations. Elastic
modulus for coralline limestone yielded a mean of
816.33 MPa or 0.82 GPa from the range of 0.6-1.0
GPa.

Summarized flexural strengths of samples

Average flexural strengths of 0.3808 and 0.9116
MPa were observed for adobe and coralline limestone
samples, respectively, while sandstone still exhibitedthe most resistance of 2.5946 MPa. Adobe samples
were weakest in shear, compression, and flexure,
while coralline limestone remained to be an averagematerial for flexure.
From actual observations, specimens did not take

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 8(a)(b)(c)
Stress-strain curve for (a) adobe, (b) sandstone, and (c) coralline limestone masonry blocks

Distribution of URM Heritage Structures in thePhilippines

abundant in Luzon and has been commonly used inconstruction since the Spanish era [10], [11], asshown in Fig. 10 and Fig. 11, respectively.

To further complement the study, the distributionof masonry was illustrated using Quantum GIS in a
Philippine Map containing points that indicate thetypology and prevailing material per region ofinterest. Based on the available data gathered, it was
found out that the most common material wascoralline limestone found in Visayas, in some regions
in Luzon, and in northern Mindanao. Abundance of
said material was also confirmed by the Philippine
Statistics Authority, where limestone accounted for
39% non-metallic resources of the country, as shownin Fig. 9. Coralline limestone is also used for cladding
to rubble cores, most notable structures of which are:Bolioon Church and Carcar Church in Cebu; Loboc
Church, Loon Church, and Punta Cruz Church in
Bohol.

Fig. 10 Locations of clay brick masonry heritage
structures

Fig. 9 Locations of coralline limestone masonry
heritage structures

Fig. 11 Locations of adobe masonry heritage
structures

Clay brick, on the other hand, was the next
common masonry material found in all major islandgroups of the Philippines, next to adobe which is

Other types of masonry in abundance include
riverstone and sandstone, commonly found in Iloilo,
561

SEE - Nagoya, Japan, Nov.12-14, 2018

where notable churches made of such are Sta. Barbara
Church and Sto. Tomas de Villanueva Church.

queries and concerns related to the study.
REFERENCES

CONCLUSION[1] Klassen W., Architecture in the Philippines:
Filipino Building in a Cross-Cultural Context,
University of San Carlos Press, 1986, pp.173-175.
[2] Varum H., Tarque N., Silveira D., Camata G.,
Lobo B., Blondet M., Figueiredo A., Rafi M. M.,
Oliveira C., and Costa A., Structural Behavior andRetrofitting of Adobe Masonry Buildings,
Structural Rehabilitation of Old Buildings, Vol.2,
Springer-Verlag Berlin Heidelberg, 2014, pp. 3775.
[3] Aguilar R., Montesinos M., and Uceda S.,
Mechanical Characterization of the Structural
Componentsofpre-Columbian
EarthenMonuments: Analysis of Bricks and Mortar from
Huaca de la Luna in Peru. Case Studies inConstruction Materials, Vol. 6, 2016, pp.16-28.
[4] D’Ayala D., Barucco P., Zerrudo E., Galasso C.,
Jose R., Manalo M., Oreta A., Garciano L. E., Yu
K., Fadriguela C., Fanciullaci V., Bronzino C.,
and Putrino V., Multi-Hazard Vulnerability
Assessment Manual of Philippines Built Heritage,in Proc. 1st Int. Conf. on Natural Hazards andInfrastructure, 2016, Chania, Greece.
[5] New Mexico Administrative Code, Chapter 7:
Building Codes General, New Mexico Earthen
Building Materials Code, 2015, New Mexico,
USA.
[6] National Building Standards, Technical BuildingStandard NTE E. 080, SENCICO, 2000, Lima,
Peru.
[7] Association of Structural Engineers of thePhilippines, Chapter 4: Structural Concrete,
National Structural Code of the Philippines, 6th ed.
Vol. 1, ASEP Inc., 2010, pp. 61-66.
[8] World Federation of Engineering Organizations
Disaster Risk Management Committee, Current
Situation of Low-Rise Wall Type Structures PartI, 2011, Retrieved from http://www.wfeo.org/wpcontent/uploads/stc-disaster_risk/WFEOWall_Type_Structure-1.pdf[9] Illampas R., Ioannou I., and Charmpis D.C., A
study on the mechanical behavior of adobe
masonry, WIT Transactions on the Built
Environment, Vol. 118, 2011, pp. 485-496.
[10] Alarcon N., Philippine Architecture During the
Pre-Spanish and Spanish Period, UST Publishing
House, 1991, pp. 64-78.
[11] Valera-Turalba M.C., Philippine Heritage
Architecture before 1521 to the 1970s, Anvil
Publishing Inc., 2005, pp. 43-55.
[12] Silveira D., Varum H., Costa A., Martins T.,
Pereira H., and Almeida J., Mechanical Properties
of Adobe Bricks in Ancient Constructions,
Construction and Building Materials, Vol. 28, pp.
36-44.

From the experiments, a summary of results isprovided in Table 1.
Table 1 Material properties based from experiment
Strength
(MPa)
Shear

Adobe
1.711.73

Type
Limestone
1.25-1.65

Sandstone
7.21-8.55

Compressive

5.3210.56

6.1510.56

32.0640.33

Flexure0.2490.471

0.8830.954

2.42-2.89

Elastic
Modulus(GPa)
Density(kN/m3)0.721.06

0.640.989

3.33-7.01

12.514.52

12.1114.71

24-25.07

In the pilot study made, indications for thestrengths of the most commonly used masonrymaterials for heritage structures are highlighted. The
study has shown that in terms of strength, ascompared from various literature [6], [8], and [12],the masonry fabric may further be improved against
various risks of natural forces such as earthquake,
extreme wind, or fire. Strengthening measures may bebrought out towards heritage structures which, thoughaesthetically preserved, may have a rather
deteriorating structure and pose potential risk in thelong run for both multiple lives and the cultural
significance of said structures.
Typology mapping, on the other hand, addresses
the need for additional systematic assessment on
infrastructures and provides initial clustering which
can be further improved and then used for a costsaving, efficient, and objective prioritization for risk
mitigation of structures both modern and of antiquity.
ACKNOWLEDGMENTS
The researchers would like to thank Engr. Jainab
Altillero from the National Museum, and National
Historical Commission of the Philippines for theirguidance, support, and recommendations in thisresearch. Gratitude as well be to the DLSU Civil
Engineering Faculty for the accommodations in562

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECTS OF WATERSHED TOPOGRAPHY AND LAND USE ON
BASE FLOW HYDROLOGY IN EQUATORIAL REGION: A CASESTUDY IN UPPER KOMERING WATERSHED SOUTH SUMATERA,INDONESIA
1

Rosmalinda Permatasari1, Arwin Sabar2, Dantje Kardana Natakusumah3 , Hazairin Samaulah4
Faculty of Engineering, Palembang Tridinanti University, Indonesia; 2,3Bandung Institute of Technology,
Indonesia; 4 Palembang Tridinanti University, Indonesia

ABSTRACTThe characteristic hydrology of watershed is playing major role in ensuring water resource availability.
Rainfall and runoff responses in catchment area are part of the hydrology cycles. There are several factors todetermine the characteristic of hydrology at watershed, i.e. geological, region, soil and land cover. The existenceof water resources is very substantial for surroundings. The rapid development in various sectors lead to water
demands increase. Optimum utilization of water resources is needed in the sustainability of water resources or theneed for integrated water resources management. The consequence of development is land use change, resulting
in changes inflow characteristics, flood during wet season and drought or discharge decrease in the dry season.
Adaptation and mitigation efforts are required to anticipate changes in the flow characteristics. Base flow depends
on portion of stream flow and its sustained between precipitation and pathway watershed. The factors are key
controls on base flow through their influence on infiltration, catchment and subsurface storage properties. This
review underscores the need for more research that multiple aspects of the watershed system in explaining baseflow. The result of average base flow and total flow ratio during 40 years (1971-2010) is 0.296 and the class ofthe hydrologic function as a BF / TF ratio value which indicated very poorly hydrology function of Komering
watershed, although in certain hydrologic function was still in good category.
Keywords: Hydrology, base flow, catchment, watershed, climate, equatorial region

further stabilize availability of flow during the dry
season. Hydrological functions of an area isdetermined by several factors such as geologicalfactor, regional, soil type and land cover. The flow
and surface water quality produced can only beeffectively measured in a stream at the regional
watershed boundary [9]-[10].
Understanding of the groundwater to stream flows
is very important in planning of water resourcesmanagement. The direct flow is primely the direct
response of a rainfall event and includes the overland
flow (runoff) and the lateral flow in the soil profile
also known as interflow. The base flow is acomponent of the stream flow which is discharge
from the natural storage of aquifers [11].

INTRODUCTION
Change in land cover and land use influences therunoff characteristics of a drainage basin to a large
extent, which in turn, affects the surface andgroundwater availability of the area [1]-[2]-[3]-[4].
Water availability in an area depends very much on
how rainfall over the area is divided into various
components such as surface runoff, interflow,
groundwater recharge etc [5]-[6]-[7]. Stream flow
can be divided into quick flow and base flow. Quick
flow is normally from surface runoff, while base flow
is from shallow and deep groundwater. In equatorial
region, such as Upper Komering, South Sumatera,base flow becomes an important water source tosupport ecosystem and economic development in theregion. Typically, base flow is not very sensitive torainfall but more associated with the discharge fromgroundwater [8].
Degradation of hydrological function is caused by
exploitation of water and land resources exceeding
their bearing capacity. It is often associated with thedisaster in water resources, such as floods, landslides,
droughts and forest fires. A hydrologic function ofwatersheds is the role of the region in responding torainfall and its flow to surface. A watershed has
proper hydrologic function if its role in reducing
runoff surge fluctuations caused by rainfall can

MATERIALS AND METHODS
Study Area
The study was conducted in the upstream
Komering watershed, South Sumatera Province,
Indonesia. Water discharge data analyzed were
measured at The Perjaya (Martapura) headwork by
the Department of Central River Region VIII. The
upstream Komering watershed an area of about 4260
km2. The temperate humid climate 28.40 – 32.20 C,
humidity 80% and ratio sunshine 29%. An average
563

SEE - Nagoya, Japan, Nov.12-14, 2018

annual rainfall 2602.08 mm, wet season during
October-May and dry season during June-September[12]-[13]. The study of base flow variability required
data on the general condition of the upstream
Komering watershed. General conditions of data wascollected which associated to variability of base flow,
including land use, geology, water resources
infrastructure and watershed meteorologicalconditions. The area's climate is equatorial region andit’s present at Figure 1.

Q50 are taken as low flow rates [11]-[15]-[16]-[17][18].
Range value of base flow and total (BF/TF) ratio
as well as analysis of the physical condition ofKomering watershed can be used as a reference forclassification of hydrological functions. The baseflow index respectively, as follows [10]-[19]-[20][21]:𝑩𝑭

𝑩𝑭𝑰 = 𝑻𝑭

(3)

where,
BFI = Base flow index
BF = Base flow values
TF = Total flow values
RESULTS AND DISCUSSIONS
Study area falls under equatorial rain climate
region with the average rainfall 2,728.50 mm / year,
and the lowest rainfall occured in July. Water
resources at upstream watershed are original from
Muara Dua, the confluence of the Saka and SelabungRivers, with each catchment areas of 1,070 km2 and
1,230 km2. Selabung River upstream of Ranau Lakehas a catchment area of 508 km2 while at its
downstream there is Perjaya headwork. The total
catchment area of the upstream watershed is 5,169.74
Km2. Komering watershed is dominated by swamp
land systems, making it vulnerable to flooding [13].
River flow pattern is influenced by rock type andtopography of Komering watershed. Limestone andshale rocks are typical at the basin. The basin has two
different forms of flow patterns, moderate andmoderate-fine rectangular dendritics. The flow
pattern affects the efficiency of the drainage systemand hydrographic characteristics. Land use changes
are the factors that affect changes in the hydrologic
function [22]. Table 1 and Figure 2 are present land
use of study area.

Fig. 1 The location of study area
Data Processing
Variability of base flow values were calculated
from discharge rational model equation, as follow[14]:
Q = c (PA) + b(1)

where Q is discharge in m3/sec, c is runoff coefficient,
P is rainfall, A is area in Ha and b is base flow.

Table 1 Land use in upstream Komering (2005)

Frequency-duration analysis, known as flow
duration curve, was another method used to analyse
the characteristics of a stream flow. The flow duration
curve is constructed from flow data and is computed
as follow [11]-[15]-[16]-[17]-[18]:𝑚

𝑃(𝑋𝑚) = 𝑁+1(2)

where,
P = the probability of a given flow that will beequalled
m = the rank number when daily or monthly flows
are arranged in decending ordern = the total of number of observations

No.

Land use

1
2
3
4
5
6
7
8

Reeds
ThicketShrub
Lake
Denude forest
Village/settlement
Mixed farms
Smallholder
plantations
Swamp
Paddy field
Moor
Total

9
10
11

A stream discharge values at P = 50% (Q50) is taken
as the median stream flow. Stream flows greater than
564

Area
(Ha)
166,824.858
12,440.171
82,030.817
18,065.790
23,763.092
223,714.106
147,420.221
167,594.918
81,859.053
923,713.026

SEE - Nagoya, Japan, Nov.12-14, 2018

1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990

0.033
0.585
0.489
0.329
0.565
0.385
0.343
0.025
0.528
0.336
0.456

2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010

0.733
0.528
0.014
0.519
0.014
0.008
0.020
0.042
0.240
0.094
0.004

Range value of BF / TF ratio as well as analysisof the physical condition of Komering watershed canbe used as a reference for classification ofhydrological functions. The criteria explained thebearing capacity of Komering watershed as a water
reservoir and also as a reference to evaluatedegradation level or accomplishment of watershed
reservation. According Table 2 the result of averagebase flow and total flow ratio during 40 years (19712010) is 0.296. Table 3 described the class of thehydrologic function as a BF / TF ratio value whichindicated very poorly hydrology function ofKomering watershed, although in certain hydrologic
function was still in good category.
Fig. 2 The landuse of study area
Table 3 Hydrology function classification [23], [24]Land use particularly for agricultural. In upstreambasin at Belitang area is one of the largest agricultural
production in South Sumatera. In order to assist theprovincial government therefore irrigation project
development supported by the existences of Ranau
Lake Regulacy and Perjaya headwork was carriedout.
Ratio of base flow and total flow (BF/TF) is as one
indicator of the hydrologic functions of a watershedwhich is the role of the catch area responding tofalling rainfall and surface runoff . The watershedcategory includes a good classification when it can
reduce the surge in surface runoff fluctuations due torain fall, stabilize the flow rate and ensure thesustainabilty of water availability [5]-[9]-[10]. Table
2 is present base flow and total flow ratio in upstream
Komering.

Hydrology function classification
Very goodGood
Moderate
Poor
Very poorly

Furthermore, the determination of theclassification needs further analysis by reviewing thecarrying capacity of watersheds in water availability
and level of watershed damage. Land use change andwatershed management affect the occurrence oferosion, sedimentation and ultimately affect water
quality. In general, the occurrence of erosion isdetermined by climate factors, especially rain
intensity, topography, soil and rock characteristics,
vegetation cover and land use and on the system of
relationship between rain and surface flow is
considered the only factor change and other factors
can be as fixed variable [1]-[2]-[3]-[4]-[25]-[26].
Land cover is a fixed factor that is easily disturbed
by human activities. The occurrence of erosion occurs
due to changes in land use that lead to degradation ofwatershed quality. The distribution and classificationof erosion levels in the Komering DAS are presented
in Table 4 and Figure 3.

Table 2 Base flow and total flow (BF/TF) ratio instudy location during 1971-2010
Years
1971
1972
1973
1974
1975
1976
1977
1978
1979

BFI
0.160
0.089
0.399
0.651
0.301
0.205
0.318
0.274
0.244

Years
1991
1992
1993
1994
1995
1996
1997
1998
1999

BF/TF
>0,9
0,7-0,90,5-0,70,5-0,3
<0,3

BFI
0.456
0.315
0.447
0.182
0.483
0.386
0.159
0.158
0.306
565

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 4. Erosion classification
Area (Ha)(%)

Legend180,000,600

160,00140,00

0,500

8,487

SlightModerate
Serious194.559,7
209.321,7
292.690,4

21,166
22,772
31,842

Very
seriously
Total

144.623,0

15,734Light
yellow
Yellow
Gold
Light
brown
Brown

120,000,400

100,00

0,300

80,00
60,00

0,200

40,00
0,100

20,00

0,000

0,00

1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009

78.008,7

Value coeff.

Erotionclassification
Very slightly

0,700

Years

919.203,536

100
Fig. 4 Trend of runoff coeff. (C) and base flow
Upstream Komering Watershed
Land use has an effect on hydrological function ofwatershed especially affect on runoff and base flow
value. Base on Figure 2 land use due to humanactivities such as agricultural land (rice fields) andplantations contribute to large runoff.
CONCLUSIONS
Understanding land use and climate change willaffect base flow quantity, in the context of watershedgeomorphology, will aid watershed managers andstream in the protection of adequate water supply forhuman need and habitat availability in stream. The
responses of runoff and base flow to climactic factors
are different. Precipitation has a great impact onrunoff, whereas temperature has a great impact onbase flow. Land use changes has an impact on
reducing the absorption capacity, especially in viewof the proportion of changes in agricultural area in theUpper Komering Watershed and increasing the rateof surface runoff.
ACKNOWLEDGEMENTS
This research is supported by Ministry of
Research, Technology and Higher Education,
Indonesia. We appreciate comments provided andencouragement made by the reviewers, the editor andthe associate editor.

Fig. 3 Erosion classification in upstream Komering
The result of the distribution of erosion base on
Figure 3 the upstream Komering has been dominatedserious erosion classification. If associated with theresults of data processing increased runoff with anincrease in the value of runoff coefecient, the decline
in base flow value and the occurrence of discharge
extremity, it can be concluded there has been achange of hydrological regime. Figure 4 is presented
trend of runoff coefficient (C) and base flow
upstream Komering Watershed.

REFERENCES[1] N. Sajikumar, R.S. Remya. (2014). Impact ofland cover and land use change on runoff
characteristics. Journal of Environmental
Management, Elsevier, 1-9.
[2] Gustard A and Wesselink AJ . (1993). Impact ofland-use change on water-resources –Balquhidder catchments. Journal of Hydrology
145(3–4), 389–401.
[3] Githui, F., Mutua, F., Bauwens, W. (2009).
Estimating the impacts of land-cover change on
runoff using the soil and water assessment tool
566

SEE - Nagoya, Japan, Nov.12-14, 2018

(SWAT): case study of Nzoia catchment,
Kenya. Hydrol. Sci. J. 54 (5), 899-908.
[4] Alibuyog, N.R., Ella, V.B., Reyes, M.R.,
Srinivasan, R., Heatwole, C., Dillaha, T. (2009).
Predicting the efffects of land use change on
runoff and sediment yield in Manupali riversubwatersheds using the SWAT model. Int.
Agric. Eng. J. 18, 15-25.
[5] Raneesh, K.Y., Thampi, S.G. (2011). A study on
the impact of climate change on streamflow at
the watershed scale in the humid tropics.
Hydrol. Sci. J. 56 (6), 946-965.
[6] Chen, Y.N., Xu, C.C., Yang, Y.H., et al. (2009).
Hydrology and water resources variation and its
responses to regional climate change inXinjiang. Acta Geogr. Sinica 64, 1331–1341.
[7] Arnold JG, Muttiah RS, Srinivasan R, Allen
PM. (2000). Regional estimation of base flow
and groundwater recharge in the upper
Mississipi river basin. Journal of Hydrology ,227:21-40.
[8] Yuting Fan, Yaning Chen, Yongbo Liu,
Weihong Li. (2013). Variation of baseflows in
the headstreams of the Tarim River Basin during
1960–2007. Journal of Hydrology, Elsevier, 98–
108.
[9] Katie Price. (2011). Effects of watershed
topography, soils, land use, and climate on
baseflow hydrology in humid regions: A review.
Sage,Publications,DOI:10.1177/03091333114
02714.
[10] Chapman, T. (1999). A comparison ofalgorithms for stream flow recession and baseflow separation. Hydrological Process, 13:701714.
[11] W.A. Welderufael and Y.E. Woyessa. (2010).
Stream Flow Analysis an Comparison of Base
Flow Separation Methodes, Case Study of The
Modde River Basin in Central South Africa.
European Water Publications, 31:3-12,2010.
[12] Rusman, A. (2004). Simulasi Alokasi Air pada
Daerah Aliran Sungai Komering Bagian Hulu
dalam Pemenuhan Kebutuhan Air Tahun 2020.
Bandung: FTSL-ITB.

[19] Pertiwi, N.S., Sudradjat, A. (2009). Analysis ofBase Flow Variability at Nanjung StreamflowGauging Station on the Upper Part of Citarum
Watershed. FTSP-ITB.
[20] Eckhardt, K. (2008). A comparison of baseflow
indices, which were calculated with sevendifferent baseflow separation methods. Journalof Hydrology 352(1–2), 168–173.
[21] Tallaksen, L. (1995). A review of baseflow
recession analysis. Journal of Hydrology 165(1–4):, 349–370.
[22] Musi Watershed Center, (2009). Laporan
Kegiatan Identifikasi dan Inventarisasi
Karakteristik Sub DAS Komering.
[23] Djuwansah, M. (2006). Aliran Rendah Sebagai
Indikator Fungsi Hidrologi DAS. LIPI, 11-21.
[24] Suherman, Dadan, Djuwansa, dkk.,. (2006).
Unjuk Kerja Fungsi Hidrologi. Pusat Penelitian
Geoteknologi LIPI.
[25] Asdak, C. (2002). Hidrologi dan Pengolahan
Daerah Aliran Sungai (DAS). Yogyakarta:
Gadjah Mada University Press.
[26] Chow, V. (1964). Handbook of Applied
Hydrology. New York: McGraw-Hill, NY,USA.
[13] Balai Besar Sungai VIII (2010). Laporan
Hidrologi. Palembang[14] Arwin. (2009). Perubahan Iklim, Konversi
Lahan dan Ancaman Banjir dan Kekeringan.
Bandung: FTSL, ITB.
[15] Hughes DA, Hannart P, Watkins D. (2008).
Continous base flow separation rom time seriesof daily and monthly data. Water SA 29(1), 4348.
[16] Hadisusanto, N. (2011). Aplikasi Hidrologi.
Yogyakarta: Media Utama.
[17] Indarto. (2010). Dasar Teori dan Contoh
Aplikasi Model Hidrologi. Jakarta: Bumi
[18] Limantara, L. (2010). Hidrologi Praktis.
Bandung: Lubuk Agung.

567

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

TENSILE CREEP BEHAVIOR CONSIDERING YOUNG’S MODULUS
DEVELOPMENT OF FLY ASH CONCRETE AT EARLY AGE
Yuki Watanabe1, Yoichi Mimura2, Vanissorn Vimonsatit3, Isamu Yoshitake4 and Itaru Horiguchi5
Advanced Course, Project Design Engineering, National Institute of Technology, Kure College, Japan;
2,5Department of Civil Environmental Engineering, National Institute of Technology, Kure College, Japan;
3
Department of Civil Engineering, Curtin University, Australia;
4
Department of Civil and Environmental Engineering, Yamaguchi University, Japan;
1

ABSTRACT
Thermal cracks caused by volume changes due to hydration heat of cement affect the long-term durability ofconcrete structures. Fly ash (FA), which is coal ash discharged from coal-fired power plants, when used to partiallyreplace cement can reduce thermal stresses in concrete. Numerical analysis (FEM) is commonly used to predict
thermal stresses. The tensile creep characteristic of concrete at early age is one of the important input data for FEM.
The elastic strain for evaluation of creep behavior is generally assumed as constant. However, the Young’s
modulus development is remarkable at early age of concrete, therefore, it must be taken into consideration whenevaluating the elastic strain. In this study, two sets of tests were conducted. The first set of tests is direct tension
tests of dog-bone-shaped concrete specimens, which were conducted at the age of 3 days, and the loading stress
30% of the splitting tensile strength was sustained for 14 days. The other set of tests is splitting tensile strength
tests and compression tests which were conducted to obtain the mechanical properties development such as the
splitting tensile strength and the Young’s modulus. The test results indicate that mixing of FA has less effect on
the tensile creep behavior than considering the decrease of elastic strain at the early age.
Keywords: Early age concrete, Fly ash, Tensile creep, Young’s modulus, Elastic strain

period of time, so relaxation due to inelastic strain
such as creep strain occurs. Thus, if stress estimation
is made without considering the creep, thermal
stresses predicted by FEM may be excessively greaterthan an actual stress.
To obtain the tensile creep behavior, it isimportant to improve the accuracy of the initial crack
prediction. There are a few research reports on thetensile creep properties of FA concrete. Michimoto etal. [2] conducted direct creep tests under the loading
condition of stress-strength ratio of 30% for 14 daysin water. As a result, it is reported that the strain rateof FA concrete tended to be higher than that ofordinary concrete. However, in the previous report [2],the influence of Young's modulus development inearly age was not considered. It is known thatmechanical properties of concrete at early age(specifically the first two weeks after casting),
significantly develop. Therefore, it is considerednecessary to incorporate the development of Young's
modulus when evaluating concrete strains, because
the creep behavior evaluated by assuming constantelastic strain may not be appropriate [3].
Creep strain evaluation method is shown in Fig. 1.
In evaluation of general creep strain, elastic strain istreated as constant. However, the Young's modulus isremarkably developing at early age, so elastic strain
under constant stress is considered to gradually
decrease.

INTRODUCTION
Many concrete structures were constructed during
the period of high economic growth in Japan, andthermal cracks, one of the initial cracks, became aproblem [1]. Thermal cracks are caused by volume
change due to hydration reaction of cement. Thermal
cracks occur in approximately one or two weeks after
casting and affect durability of concrete structures.
Therefore, it is important to accurately predict
thermal cracks and take measures.
Measures against thermal cracks are roughlyclassified into a method of suppressing volume
change, a method of reducing constraint degree and amethod of controlling crack width. One of methods
for suppressing volume change of concrete is using of
fly ash (FA). FA is fine particles of coal ash fromcoal-fired power plant. By replacing FA with cement,
it can reduce the hydration heat that causes thermal
cracks.
Controlling thermal cracking requires an accurate
prediction of actual thermal stresses. Thermal stressanalysis is normally performed by FEM which needs
mechanical properties and volume change of concreteat early age, such as strength, Young's modulus andcreep for the analysis. This study focuses ondetermining the tensile creep behavior of concrete forpredicting accurate tensile thermal stress. Thermal
stress is usually sustained in concrete for a long
568

SEE - Nagoya, Japan, Nov.12-14, 2018

グラフ タイトル

50
creep strain
30
elastic strain
10(constant)
-10
time

strain

50
30
10
-10

0

5

Fig. 1

10

グラフ タイトル

Standards A 1113), and compression tests for
obtaining Young's modulus were carried out. The
dog-bone shaped specimen used for the direct tensile
creep test is shown in Fig. 2. A small mold strain
gauge having a temperature measurement function
and a length of 50 mm was embedded in the center ofthe cross section of the dog-bone shaped specimen. In
splitting tensile tests and compression tests, astandard 100 mm diameter, 200 mm long cylindrical
specimen was used. For the strain measurement incompression tests, a strain gauge of length of 60 mm
was attached at the center of both side faces of eachspecimen.
After casting, the specimens were carried into acuring room to be cured at a room temperature of 20± 1 oC for 24 hours before demolding. After that the
specimens were cured underwater in a water tank (16± 1 oC) installed in the curing room until load tests
were to be carried out at the age of 3 days.

early age
creep strain
elastic strain(decrease)05time 10Evaluation of creep strain

In this study, creep behaviors of FA concrete andordinary concrete with a consideration of thedevelopment of Young's modulus were investigatedand compared. In particular, it was aimed todetermine the influence of Young's modulus
development on concrete creep behaviors.
MATERIALS AND TEST PROGRAM

Method of Tensile Creep Test

Materials and Mixture Proportions

Figure 3 shows the loading apparatus used in the
direct tensile creep test in this study. Tensile creep
was loaded underwater, as shown in Fig. 3. The
loading apparatus was installed in the water tank in
the curing room with the temperature remained at 20± 1 oC and the temperature in the water tank remained
at 16 ± 1 oC. In this test, loading was carried out inwater to eliminate the effect of drying shrinkage.
Therefore, tensile creep in this study is targeted forbasic creep without moisture transfer.
The unloaded specimen was installed in the sameenvironment as the loaded specimen, and the strain of
the unloaded specimen was measured. By subtracting
the strain of the unloaded specimen from the strain of
the loaded specimen, strain caused by factors otherthan the loading, such as autogenous shrinkage andwet swelling, was eliminated. In this test, two loading
apparatuses and two water tanks and four dog-bone

Table 1 shows the materials used for concrete andmix proportion in this study. The mix IDs N and FA
represent ordinary concrete mixes and FA concrete
mixes, respectively, as shown in the table. The
targeted slump of each mix of ordinary concrete andFA concrete is 8 ± 2.5 cm, and the targeted air content
is 4.5 ± 1.5%. Because FA contains unburned carbon,
it reduces the effect of air-entraining and waterreducing admixture. Therefore, an air-entraining
agent for suppressing the influence of unburned
carbon was used in FA concrete mixes.

SpecimenIn this study, direct tensile creep tests, splitting
tensile strength tests (conform to Japan Industrial
Table 1

Materials and mix proportion

Property

Proportion
Ordinary concrete FA concreteN
FA

Materials

Mix ID

--a

---

55%

FA replacement ratio

---

0%

Water-binder ratio

55%

Water (W)
Tap water
165 kg/m
Cement (C)Ordinal Portland Cement
300 kg/m3
Fly ash (FA)Class II
0 kg/m3
Fine aggregate (S)Crushed rock sand
844 kg/m3
Coarse aggregate (G1)
Crushed rock (20-15 mm)
499 kg/m3
Coarse aggregate (G2)
Crushed rock (15-5 mm)
499 kg/m3
Admixture (Ad1) Air-entraining and water-reducing agent
3.00 kg/m3b
Admixture (Ad2)
Air entraining agent for FA
0 kg/m3abbinder = C + FA, diluted solution (diluted 100 times with water)
569

-----

20%
3

Density--3

165 kg/m
240 kg/m3
60 kg/m3
833 kg/m3
493 kg/m3
493 kg/m3
2.40 kg/m3
16.8 kg/m3

1.00 g/cm3
3.16 g/cm3
2.24 g/cm3
2.62 g/cm3
2.67 g/cm3
2.67 g/cm3
1.07 g/cm3
1.04 g/cm3

SEE - Nagoya, Japan, Nov.12-14, 2018

290

120

70

70

unit : mm
15

10, 14 and 17 days. In this test, three cylindrical
specimens were tested for each age.
RESULTS AND DISCUSSION

75

100

15

Table 2 shows the splitting tensile strength of thespecimens tested at the age of three days and theloading stress for tensile creep tests. Mix IDs No. 1 to
No.6 given in Table 2 are the specimens casted on
different dates due to a limitation in the casting molds.
Hence, the variation of the tensile strength results
could be due to the casting conditions at each day.
However, this difference does not affect the purposeof this study as the applied loading stress is specificfor each specimen.
The relationship between Young's modulus andsplitting tensile strength is shown in Fig. 4. In
addition, the regression results using Eq. (1) are
shown in Fig. 4. Equation (1) is obtained by changing
the parameter of the equation shown in Guidelines forControl of Cracking of Mass Concrete 2016 [1] fromcompressive strength to splitting tensile strength. In
this study, coefficients were evaluated by the using
least-squares method.

Strain gauge(50mm long)

Fig. 2

Dog-bone shaped specimen
Steel arm

Load

Water Unloaded
specimen
Loaded specimen

Fig. 3

Loading apparatus

shaped specimens were prepared. Therefore, one or
two of each of loading specimens and unloaded
specimens were used in one direct tensile creep test.
In the direct tensile creep test, the strain and thetemperature of loaded specimens and unloaded
specimens and the water temperature of each watertank were measured at one-hour intervals by using adata logger. The loading was started at the age ofthree days, and it was sustained for 14 days. The
loading at the age of three days was derived from theage of changing the temperature stress fromcompression to tension. In addition, the loading
period of 14 days was determined from theoccurrence of the initial cracks at approximately two
weeks after casting.
According to Davis-Granville's law, the creep
strain is roughly proportional to the loading stress if
the stress is less than the one-third of the concrete
strength. Therefore, the loading stress in this study
was set to 30% of the splitting tensile strength at theloading-start age (3 days).

E (t )  C1  f t (t )C2(1)

where E(t) is the Young’s modulus (GPa), ft(t) is
splitting tensile strength (MPa) and C1 and C2 are

Table 2

Splitting tensile strength and loading
stress of age three days

Mix ID

FA

N

No.1
No.2
No.3
No.4
No.5
No.6

Splitting tensile
Strength
(MPa)
1.32
1.51
1.53
1.22
2.09
2.38

Loading stress
(MPa)
0.397
0.454
0.458
0.365
0.628
0.713

Experiment Method of Young's Modulus
50
Young's modulus(GPa)Compression tests were conducted to obtain the
Young's modulus of concrete. In the compression test,
unloading was conducted at every increase of strainof 10 x 10-6. The strain and the load were recorded byusing a data logger during the loading and theunloading. In order to eliminate the influence of
inelastic strain in the evaluated Young's modulus asmuch as possible, strain and load were recorded until
the load reached the splitting tensile strength. The
relationship between strain and stress was linearly
regressed. The gradient of the regression line wastaken as Young's modulus. The compression test was
conducted at the age of 3, 5, 7, 10 and 17 days or 3, 7,

+15%

40
-15%
30

20
10

No.1
No.4

No.2
No.5

No.3
No.6

0

0
1
2
3
4
splitting tensile strength(MPa)Fig. 4570

Young’s modulus – splitting tensile
strength relationship

SEE - Nagoya, Japan, Nov.12-14, 2018

3

3

2

2

No.4
No.5
No.6

No.1
No.2 1
No.3

1

0

0

0

7 14 21age(days)age(days)

28 0

7 14 21age(days)age(days)28

strain(×10-6)N4strain(x10-6)

4

Fig. 5

Splitting tensile strength

45

45

FA

30

30

15

0
0

Fig. 6

No.115
No.2
No.3
0
7
14
21 0
age(days)age(days)Young’s modulus

40

loading
20

No.4
No.5
No.6
7
14
age(days)age(days)

20

non loading

0
loading

20

14

20

non loading
7

14time(days)
No.6(N)40

20

non loading

loading
non loading

00Fig. 7

7time(days)
No.5(N)loading

40

0
14
60 0

7
time(days)
No.3(FA)loading

40

21

14
60 0

non loading

0571

loading7time(days)
No.2(FA)40
20

No.4(N)40

non loading

0
60 0

N

60

No.1(FA)

0
60 0

-6

modulus(GPa)Young's modulus(GPa)

5

FA

-6
strain(x10strain(×10-6) )5

60

strain(×10 -6))
strain(x10strength(MPa)tensilesplittingstrength(MPa)tensilesplittingwhere ft (t) is splitting tensile strength (MPa), ft (28) is
splitting tensile strength at the age of 28 days (MPa),t is age (day) and A and B are coefficients.
The coefficients used for Eq. (2) in FA concrete,
A and B were 3.47 and 0.899, respectively. In
ordinary concrete, A was 4.14 and B was 0.871. The
splitting tensile strength of FA concrete at the age of
28 days was 3.08 MPa, and that of ordinary concrete

strain(×10-6)(2)

strain(×10-6)t
f t (28)A  Btft (t ) Was 4.14 MPa. The splitting tensile strength
development of FA concrete was more gradual thanthat of the ordinary concrete, as shown in Fig. 5. Thisis probably because pozzolanic reaction of FA is slow
and does not contribute to splitting tensile strength
development yet.
Time course of the Young's modulus is shown in
Fig. 6. In addition, the regression results are shown in
Fig. 6. The curves of FA mixes and the curves of N
mixes demonstrated in Fig. 6 were obtained from Eq.
(1) and Eq. (2). The development of the Young's
modulus was similar to that of the splitting tensile
strength, which shows that the Young’s modulus
development of FA concrete is slower than that of theordinary concrete.
The strain measured by the direct tensile creep
tests is shown in Fig. 7. The creep strain is obtainedby subtracting the elastic strain and the strain of
unloaded specimen from the strain of the loaded
specimen. The creep strain was evaluated by using
constant elastic strain. In addition, the elastic strain inconsideration of the Young's modulus development at
early age was also used for evaluating the creep
behavior. In other words, the elastic strain which
decreases when loading concrete at older ages wasevaluated. Using the regression result of the Young's
modulus shown in Fig. 6, the elastic strain can be
estimated by Eq. (3).

strain(×10-6)

coefficients.
C1 and C2 evaluated in this study was 23000 and
0.43, respectively. Kimura et al. [4] reported that thecompressive strength and Young's modulus showed a
fixed relationship regardless of FA replacement ratio
and age, and that mixing FA in concrete does notaffect the Young's modulus. In the present study, therelationship between the Young's modulus and thesplitting tensile strength shows a similar tendency inboth ordinary and FA mixes, as seen in Fig. 4.
Therefore, these results indicate that FA might notaffect the evaluation of the Young's modulus as in thecase of the previous report [4].
Figure 5 shows the time course of splitting tensile
strength. In addition, the regression results using Eq.
(2) are shown in Fig. 5. Equation (2) is obtained bychanging the parameter of the equation shown in
Guidelines for Control of Cracking of Mass Concrete2016 [1] from compressive strength to splitting
tensile strength. In this study, coefficients were
evaluated by using the least-squares method.

7time(days)time(days)

Measured strain

14 0

7time(days)time(days)14 e (t ) E (t0 )
 e (t0 )E (t )of specific creep of No. 4 to No. 6 ordinary concrete.
Figure 10(a) shows the graphs with constant elasticstrain, while 10(b) shows the graphs with decreased
elastic strain due to the development of the Young's
modulus. Yoshitake et al. [6] predicted the tensile
creep behavior of early age concrete using theviscoelastic rheological model and Eq. (4). It isreported that the regression accuracy of Eq. (4) is high.
The regression curves obtained by using Eq. (4) are
included in Fig. 10. In this study, the coefficients, a,b, c and d, were evaluated by using the least-squares
method.

(3)

FA

(4)

where J(t) is specific creep (x10-6/MPa), t is elapsed
time (day), a, b, c and d are coefficients.
The coefficients of Eq. (4) are shown in Table 3.
Regardless of the consideration of the Young's
modulus, the specific creep of FA concrete became
larger than that of the ordinary concrete, as shown in
Fig. 10.
The thermal stress depends on the specific creep rate
rather than its magnitude. The specific creep rate wasestimated by differentiating Eq. (4) with respect totime, and using coefficients given in Table 3 in order
to compare the behaviors of the specific creep. The
obtained specific creep rates are as shown in Fig. 11.
It can be seen that the specific creep rates decrease
monotonously in all cases.
Figure 12(a) shows the ratio of the specific creep
rate of FA concrete to that of ordinary concrete. As
shown in Fig. 12(a), the ratio of the specific creep

N

20
15

5

0
14 0 0time(days)

Fig. 8

No.1
No.2
No.3
7 7

40
No.4
No.530
No.6
20

No.4
No.1
No.5
No.2
No.6
No.3

載荷期間(日)time(days)time(days)

14 14 0714

載荷期間(日)time(days)

Reduction of elastic strain
specific creep(x10 /MPa)

載荷期間(日)N30

εe(decrease)

FA

N

20

10
εe(constant)εe(decrease)
0
7
14
7
14 0
time(days)time(days)time(days)time(days)εe(constant)00(a) constant(a) constant εe

8
6

40

N

10

10

(b) decrease(b) decrease εeFA

Fig. 10Specific creep (comparison of N and FA)

Table 3Specific creep regression result

420

coefficient0Fig. 9FA-6

10

specific creep(×10-6/MPa)725

J (t )  a t  b 1  exp(ct d )

specific creep(×10/MPa)
creep(x10-6/MPa)
specific-6)-6)
elastic
strain(x10strain(×10where εe(t) is the elastic strain at elapsed time t, εe(t0)is strain of the loaded specimen at the start of loading,E(t) is Young's modulus at elapsed time t (GPa) andE(t0) is Young’s modulus at the start of loading (GPa).
Reduction of elastic strain is shown in Fig. 8.
Elastic strain in FA concrete decreased byapproximately 24%. Elastic strain in ordinary
concrete decreased by approximately 28%. FA
concrete demonstrates a slow development of theYoung's modulus; the increase in the creep strain due
to the decrease in the elastic strain was approximately
4% smaller, as shown in Fig. 8. As mentioned earlier,creep strain is roughly proportional to loading stress,
so specific creep, which is the creep strain divided by
the loading stress, was evaluated. The increase in thespecific creep due to the decrease in the elastic strain
is shown in Fig. 9. The results shown in Fig. 9 are
obtained from using the decreased elastic strain (asseen in Fig. 8) divided by each loading stress. An
increase of the specific creep due to a decrease of theelastic strain of FA concrete was approximately 8%
smaller than ordinary concrete, as shown in Fig. 9.
The specific creep behaviors of FA concrete andordinary concrete are shown in Fig. 10. These graphs
are obtained from taking the average of the specificcreep of FA concrete No. 1 to No. 3 and the average

弾性ひずみの減少による
単位クリープ増分(×10-6/N/mm2-6)

0

SEE - Nagoya, Japan, Nov.12-14, 2018

7
time(days)

14

a
b
c
d

Increase in specific creep by decrease inelastic strain572

εe(constant)
FA
N
0.694
0.536
21.2
19.0
0.552
0.642
0.516
0.457

εe(decrease)
FA
N
0.674
0.405
31.5
34.6
0.450
0.414
0.592
0.533

SEE - Nagoya, Japan, Nov.12-14, 2018

specific creep
creep rate
specific
speed(×10-626/MPa/day)
(x10
/day)
/N/mm

4

εe(constant)creep. Compression tests were performed using
common cylindrical specimens to obtain the Young's
modulus. Based on the test results in this study, it canbe concluded as follows:εe (decrease)

3
FA

2

N
FA

1

(1) An increase of specific creep due to a decrease inelastic strain of FA concrete is about 8% smaller
than that of ordinary concrete.
(2) In ordinary concrete, the ratio of the specificcreep rate with decreased elastic strain to thatwith constant elastic strain ranges from 1.13 to
2.06. While in FA concrete, the range of this

N

0
0

7
time(days)time(days)

14 0

7

14

time(days)
載荷期間(日)弾性ひずみ（減少）

2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8

弾性ひずみ（一定）2.22.0εe(constant)
1.8
1.6
εe(decrease)
1.4
1.2
1.0
0.8
0
7
14 0
time(days)

7time(days)time(days)time(days)

specific creep speed ratio(FA/N)

specific creep rate ratio

specific creep speed ratio(FA/N)

Fig. 11 Specific creep rates(a) FA/N

ratio is smaller; the maximum ratio is 1.61.
(3) If the elastic strain is assumed constant, FA
concrete has greater specific creep rate thanordinary concrete. In the case of considerationof Young's modulus development during thecreep test, the specific creep rate of FA
concrete is almost equivalent to that ofordinary concrete.

NFA(4) Decreasing the elastic strain at early age has
more effect on the specific creep rate than the
mixing of FA.

14(b) decrease εe/constant εe

ACKNOWLEDGEMENTS

Fig. 12 Ratio of specific creep rates (FA/N)

The authors would like to thank Mr. Michimoto (aformer advanced course student of National Instituteof Technology, Kure College), members of Horiguchi
laboratory and the Chugoku Electric Power Co. Ltd.

rates in the case of constant elastic strain is more than
1.0 except for immediately after loading. This result
indicates that the specific creep rate of FA concrete is
greater than that of ordinary concrete. The ratio atloading period exceeded approximately one day isalmost constant at 1.2. However, the specific creep
speed rate in the case of the decreased elastic strain iswithin the range of ± 10% during the loading period.
Considering the decreased elastic strain (with thedevelopment of Young's modulus), the specific creep
rate of FA concrete is not always greater than that ofordinary concrete.
Figure 12(b) shows the ratio of the specific creep
rates with decreased elastic strain to that withconstant elastic strain. In ordinary concrete, thespecific creep rate with decreased elastic strain is 1.13
to 2.06 times that with constant elastic strain. In FA
concrete, the maximum ratio is 1.61. As shown in Fig.
12(a) and Fig. 12(b), the consideration of the decreasein the elastic strain at early age affected the specificcreep rate more than the FA mixing.

REFERENCES[1] Japan Concrete Institute, 2016, Guidelines forControl of Cracking of Mass Concrete 2016 (inJapanese).
[2] Michimoto S., Mimura Y., Horiguchi I. and
Yamada K., A Study on Stress Relaxation by
Creep of Fly Ash Concrete, Japan Society of Civil
Engineers 2017 Annual Meeting, V-413 ，pp.825-826，2017 (in Japanese).
[3] A. M. Neville., Properties of Concrete (5th edition),
Prentice Hall, 1963.
[4] Kimura M., Aikou Y., Ichinose T. and Yoshida T.,
On the Characteristic of the Concrete Using the
Fly Ash, Proceedings of the Japan Concrete
Institute, Vol.23，No.1，pp.301-306，2001 (inJapanese).
[5] Yoshitake I., Nakamura H., Nagai S. and Hamada
S., A Study on the Tension Creep Equation
During Hydration in the Early Age, Journal of
Materials, Concrete Structures and Pavements,
No.634/V-45，pp.43-53，1999.11 (in Japanese).

CONCLUSIONSThis paper presents an investigation of the tensile
creep behavior of FA concrete with a consideration of
the Young's modulus development in early ages ofconcrete. Direct tensile creep tests using dog-bone
shaped specimens were conducted to obtain tensile573

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

DATA BASE STRUCTURE MANAGEMENT INFORMATION SYSTEMLAND ALLOCATION IN SPATIAL PLANNING

1,2,3,4Sarino1, Dinar DA Putranto2, Agus Lestari Yuono3, and I.C. Juliana4
Faculty of Engineering, University of Sriwijaya, Km.32, Palembang-Inderalaya, Ogan Ilir District, South
Sumatera, Indonesia
ABSTRACT

Comprehensive data management systems are essential for watershed management. A large amount of
spatial data of the study area has been collected for the management study of the Palembang River Basin ofIndonesia. In this research will introduce database development to support the study of surface flow
management in spatial planning of city area and region. This database links the geographic information
system (GIS) with relational database management system (RDBMS) to facilitate the use of data in surface
flow management. The method used in this research is to develop an integrated GIS-RDBMS database using
the following steps: (1) to establish a database system that is easily accessible to all users; (2) developing
database format and structure; (3) establish a formula for data management procedures, including input,
update, conversion, QA / QC, and backup; and (4) the application of data queries and decision-making
techniques for users to search, display, print, or collect information. This study aims to develop the stages of
database compilation on the Jakabaring-based sub-watershed GIS-RDBMS. The process focuses on the studyof surface flow management of the Jakabaring Watershed, This research introduces a concept in modeling the
fuzzy geographic features in a watershed management system.
Keywords: GIS-RDBMS, run-off, fuzzy logic, DAS managementchanges in urban and regional land use, will help
urban planners and hydrologists in spatial planning.
The Land Allocation Management System[1] is awatershed analysis system (DAS) that will be
developed by utilizing GIS techniques using land
use change parameters, morphometrics andhydrometric watersheds. By using hydrodynamic
analysis and spatial analysis (1D / 2D), water levelin river and drainage channel, so it can get
information about the change of water level
distribution in sub watershed, due to land use change
done when determination of land allocation. Puddle
management involves the diagnosis of problems
within the watershed with emphasis on the causes ofrainwater runoff and tidal rivers causing flooding
and puddles, and optimizing land allocation toincrease water absorption into the soil to reducesurface or puddle flow.

INTRODUCTION
The Jakabaring watershed is one of the subwatersheds in the area across from the ulu,
Palembang City which was originally a flood plain,and some of its territory is a swamp and not widelyused for activities until 1995. To develop the area
across from Ulu, the government of South Sumatra
Province together with the government The city of
Palembang has reclaimed the swamp area andutilized for the implementation of Sports activities
such as the Asian Games 2018 in Indonesia, with all
facilities including residential areas, trade, offices
and other supporting facilities. The process ofdevelopment of the area of Seberang Ulu is done byhoarding the swamp area using the soil material
derived from the dredging of the Musi River and thesoil material taken from other areas.
The process of accumulating flood plains andswamps, of course, requires a water system inaccordance with the conditions of the sub watershed
Jakabaring that form the initial ecology of the area
opposite Ulu. In its development, some areas in thearea after the land conversion occurred, floods thatflooded some areas such as residential areas, evenrunoff flooded the surrounding residential areas.
This is one of the mistakes caused by the mismatch
between land use allocation in spatial arrangement
and the management of surface flow in a watershed.
Understanding of surface flow management with

METHODELand allocation management to reduce flood risk
can be divided into two parts: Flood risk analysis
and assessment on the one hand and risk mitigationon the other. Broadly speaking, the purpose of land
allocation management is the assessment of floodrisk to establish where the risk is very high, ie where
mitigation measures will be required. Risk
mitigation means proposing, evaluating, andproviding alternative solutions to mitigate risks inthe area. To map the risks and effects of flood risk
574

SEE - Nagoya, Japan, Nov.12-14, 2018

reduction due to land allocation, the utilization of
Geographic Information System (GIS) with its
ability to present spatial data is an appropriate tool
for processing spatial data in surface runoff analysis.
The approach presented in this paper is combining
MCAs with GIS.
The amount of runoff surface runoff in awatershed is the relationship between topographic
condition of the area, land use, soil type, drainage
channel condition and the amount of rainfall. The
smaller the area of infiltration, the greater runoff
occurs, if rainfall and channel capacity are reduced[2]. On that basis, it can be used to translate the levelof detail in the decomposition of the object class intoa derived class (specialization) of the required
database.
The Land Allocation Management System as
defined by Sharifi (2003) is a Geospatial

Information System classification, consisting of data
/ information (spatial and non spatial), models, andvisualization tools, especially developed to support
planning and decision-making processes. In
connection with the understanding as mentioned
above, the method that will be developed in the
manufacture of Spatial Spatial Allocation
Management Information System will be focused on
the planning phase, namely the preparation of
database structure related to Basic Geospatial
Information (IGD), such as topographic area,channel profile (river and drainage ), the width andshape of the watershed, land use, and rainfall
distribution. The overall architecture of the planningsupport system to be constructed is presented in
Figure 1.

Computer System and Selected software
BASE OFGEOSPATIALINFORMATION
Spatial Database
Management

Model of Land
Allocation Management

DATABASE
STRUCTUREDIALOG of LAND
ALLOCATIONMANAGEMENTTEMATIC of
GEOSPATIALINFORMATION

Fig. 1 Architecture Planning Dessicition Support System (DSS) in Land Allocation Management
The main components to be built in the Planning
Support System are as follows:(1) A database management system. This system
includes the preparation of database structure
which includes the design of conceptual data
model, identification of physical data collection+ Meta Data, E-R Diagram designed toaccommodate and organize spatial database andGeospatial Thematic information, and able toprovide facilities to analyze and manipulate data
(2) A Database Management System Model. The
system includes both quantitative and qualitativemodels that support surface flow analysis,
namely the assessment of potential surface flows
and spatial capacity at different levels of land
allocation management

interactions with topology, land use and soil
physical properties. Therefore, the use of
Geographic Information Systems (GIS) will bebetter than traditional techniques in thequantification of appropriate surface runoff bystoring and analyzing the underlying factors
affecting runoff. The estimation process becomes
more efficient, interactive and less complicatedwhen Geographic Information System (GIS) is used
to store, interpret and display the data required insurface runoff overlay techniques.
DATA BASE DESIGN
The design of the database in the Geographic
Information System (GIS) always starts from theanalysis of the appearance of geographic objects
from real-fact data sources adapted to the utilizationneeds to be made (Raper, 1992).

The hydrological response of the watershed leads
to the formation of surface runoff governed by

575

SEE - Nagoya, Japan, Nov.12-14, 2018that make up the watershed area of Palembang City,
part of the Musi River Basin, within theadministrative territory of South Sumatra Island,
Indonesia.

Study Area and Data Acquisition
Jakabaring sub-watershed with geographic
position 104o 44 '56 "- 104o 47' 45" BT and 02o 07'10 "- 02o 03' 50" is one of the 19 sub-watersheds

Sumatera Island

Jakabaring sub chatment, Palembang City
Fig. 2 Research Sites of Jakabaring Sub-watershed, Palembang City, Musi Watershed Area, Sumatera Island,
Indonesia{RESERVATION;
OFFICE;
INDUSTRY;EDUCATION; PUBLIC FACILITIES; TRADING;SOCIAL FACILITIES; HEALTH}. LHN_TBK
Subclass Class, is a generalization of the subclass of{SPECIAL FORESTS; GREEN OPEN SPACE;
WALKING ROAD; RIVER RIVER}. The HIDRO
Subclass, is a generalization of the sub class{RIVER; SWAMP; CHANNEL}. The sub-class ofroads, consisting of DAMIJA objects (Road Owned
Areas) having spatial structures of areas (polygons)
can be incorporated with PURAHAN sub-classes,
into LHN_TBGN Subclasses. The merger(association) is because between the sub-class ofwatershed boundaries and the space utilization subclass has many similarities in attributes andmethods, such as names, spatial and non spatial
relationships, widespread calculations and so on.
Figure 3. below shows a nail diagram illustrating
the hierarchy between the subspace class sub-district
visibility, for the watershed boundary subclass.
Identification of the data unit of the object thatcomposed the structure of the DAS Territorial
Layout for each subclass, can be fully detailed asfollows:(1) watershed area units used as observation limits
for flood or puddle analysis are used withinwatershed boundaries. To that end the subclassesof the watershed area contain the sub-watershed,

Object Description
The introduction of objects based on theappearance of land use objects is classified
according to the materials needed in river basin
management. Understanding land use here, is anobject that uses or requires space or land. To that
end, the objects of roads, rivers and waterways(swamps, lakes, canals) are also objects that use
space. Thus the sub class of road and river objects,
can be incorporated into one class, called sub classof space utilization or land use. Each space
utilization will be within the watershed area. For that
object space utilization can be incorporated in a subclass of objects called sub class space utilization andwatershed boundaries
A set of methods for calculating objects having
similar characteristics and shapes can beincorporated together with their attributes and calledclass definitions. The class hierarchy used is, thefirst class is called the base class, while the secondclass or sub-class, commonly called the derived
class. {LIMITS BOARD; LIMIT SUB; BATASSUB RIVER SYSTEM}, is a member of thewatershed sub-class sub-class. The space utilization
sub class is a form of "generalization" of the
subclass {P_LAHAN; LHN_HIDRO}. Sub ClassPURAHAN, is a generalization of sub Class

576

SEE - Nagoya, Japan, Nov.12-14, 2018

including the sub-sub-basins with the object
identification (primary key) in this class is theOID.
(2) spatial use specified by location and area of landfor each watershed boundary, identified as land
utilization subclass.
The relationship(subdivision) between the land utilization classand the level of detail will be indicated by thelevel of numbering in the OID. Geometric shapeand geometric spatial structure is represented bygeometric shape of polygon (area), consisting ofgeometric shape of boundary of utilization (ring)and the area of exposure (closure) and point
coordinates that indicate location andrelationship between geometric object based on
topology (face ) written in the form of nongeometric attributes

Sub Class Boundary Basin
Sub Class Land Use
Sub Class sub Basin
Sub Class Topography
Sub Class Hidrography
Sub Class Type of Soil

Fig. 3 Examples of specialization of DAS Basin class, Land Use sub-class and DAS sub-classes
diagram of Figure 3, is arranged in the form of a
spatially connected object diagram generalized bysubclass, with the following explanation: soil,
topography, and hydrographic elements are
unplanned Spatial Planning and is a watershed areaplanning area. The watershed area, divided into
observation boundaries, is called the sub-basinboundary. Within the watershed area boundary
which is an observation area, based on the planned
land allocation within each watershed boundary, it is
known that the run-off will occur in each watershed.
Thus, within each watershed boundary, there isspace utilization necessary to carry out activities thatare applied in space utilization zones, such as
settlement, education, trade, and so forth.
Any change of land use allocated within thewatershed limits will determine the value of C
(catchment coefficient) for each sub class of land
use object in the area, but will also determine theamount of runoff to be produced by each sub classof land use object, which will determine needs ofdrainage systems and retention ponds. The allocationof existing land use distribution to each subwatershed, will ultimately determine the need ofdrainage network system in the area. Thus there is aspatial relationship between the variables of land usechange within the watershed area with the amount of
runoff to be generated. The amount of land use
allocation to be able to serve the population
allocated to each sub-basin, will determine the

Attribute Data
Each object must have an attribute that describes
the property (property) of the object. Determination /selection of relevant attributes for an object isimportant in making the data model. Attribute data iscompiled based on the need of GIS utilization object
for watershed management. The attribute will
describe the contents of the geometric object
numerically (numbers) as well as spatially related toother geometric objects, which will produce thederived attributes. The subclass will inherit attributes
that are similar in character to the superclassattribute. Thus, there is no need to attribute that has
been defined in the "base class", redefined in the subclass, because it will only cause waste of storage inthe computer.
Connectivity among Object Class
Based on the relationship between spatial objects
that have been discussed earlier, then finally can bearranged a relationship diagram that explainsinterconnection (relation) between sub class of
spatial objects that make up the Spatial Area DAS.
Using the logic of relationships, such as
specialization, aggregation, generalization andassociation, each class is linked by describing it in a
spatial object linkage model diagram. Seen in FIG.
4, the logic of the relationship as illustrated in the577

SEE - Nagoya, Japan, Nov.12-14, 2018

amount of distribution needs of network system
Drainage (sub class utility object). Thus there is arelationship between the variables of land needs ineach sub-basin with the needs of the distribution ofdrainage system.
The attributes for each of these spatial use
objects are stored in tabular data, broken down byland use type, sub-class of land use, within each subwatershed. To obtain the amount of land utilizationin each sub-basin, simply add up the utilization ofland for each sub-basin boundary, and the utilizationof each sub-basin is summed up to obtain land use
throughout the basin. Connection diagram (E-R
Diagram) for data storage, can be seen in Figure 5.

Rainfall
PolygonGT

Soil
Adjacent

Sub-Chatment area

Chatment area
PolygonG

PolygonT

Polygon

G

G

G

LAND USE

contains

Polygon

T

T

G

T

G
Topography
Adjacent
Point

Drainage/River
PolygonG

G

T

Lake/Retention
T

T

G

PolygonFig. 5 Entity-Relationship Diagram for Run-off management at Chatment Area
sub-watersheds. The principle is commonly referred
to as inheritance (inheritance), polymorphism(Polymorphism) and encapsulation (encansulapted).
The design of the data structures for each object
classification used in the management of the Spatial
Planning can be seen in Table 1 below.

Data Structure
Each object will have at least one data attribute,which must be defined by the type of identifier(OID), the constructor type of each data column(interger, decimal, character, etc) and the value ofeach data column contained in the data attribute, the column that will be used to load the attributevalue.
The object set as the base class will be specified
as the key identifier, which will be represented as
the primary key (Primary Key). From the primary
key, then each object that belongs to the class, will
have an OID that follows the hierarchy of the
primary key of the class above it.
The method or commonly called function, isused to write commands to perform mathematical
calculations based on the analysis model used. In
determining the allocation of any required land use
and placed within each sub-basin boundary, a Runoff model is used. The mathematical function used
to calculate the probability of land use is directly
defined in the sub-class definition of sub-basinboundaries. Thus, to know the value of the total
infiltration coefficient that exists within the sub-subclass of sub-watershed or sub-basin, it is the sum of
the infiltration coefficient values present in each

Table 1 Structure Basis Data at Chatment Area

578

Object :Atribut :
Qcode
N_CA
NS_CA
Area_Ha
Perimeter
Center_L

Chatment Area
Data Type
Widh
Interger(10)
Character(25)
Character(25)
Decimal(15,3)
Decimal(15,3)
Decimal(10,3)

Object :Atribut
OID
L_Use
Class
Area_Ha
N_C
RDLand Use
Data TypeInterger
Character
Character
DecimalDecimalDecimal

Widh
(10)
(30)
(30)
(15,3)(5,3)(5,3)

SEE - Nagoya, Japan, Nov.12-14, 2018

ET_ETOA%P

DecimalDecimalDecimalObject :Atribut
OID
S_Height
Z (m)Topography
Data TypeInterger
Character
Decimal

Widh
(10)
(10)
(10,3)

Object :Atribut
OID
I_Countur
O_NameZ

Hydrometry
Data TypeInterger
Character
Character
Decimal

Widh
(10)
(10)
(15)
(10,3)

Object :Atribut
OID
Type_Soil
Area (Ha)Z_Organic
OM_Value
Moisture_Sc
BD
pH
K_Value

Soil
Data TypeInterger
Character
DecimalDecimalDecimalDecimalDecimalDecimalDecimal

Widh
(10)
(25)
(10,2)
(5,2)
(5,2)
(5,2)
(5,2)
(5,2)
(5,2)

Determination Peak Runoff Rate Using The
Modified Rational Formula

(5,3)
(5,3)
(5,3)

The rational method is described by the formula
1 (Brouwer, 2012)
Qp = 0.28∗C∗I∗A[1]

where,
Qp = Peak runoff rate [m3/sec].
C = Runoff coefficient.
I = Rainfall intensity [mm/hr].
A = Drainage area [km2].
In the modified version of the rational formula, astorage coefficient, Cs, is included
to account for a recession time > the time thehydrograph takes to rise. In theoriginal formula the recession time was assumed tobe equal to the time of rise.
The modified rational method is then describedby the formula 2.
Qp = 0.28∗Cs xC∗I∗A[2]

The rational method follows the assumptions that(1) the predicted peak discharge has the sameprobability of occurrence (return period) as theused rainfall intensity and(2) the runoff coefficient is constant during the rainstorm.
A rainfall with a steady uniform intensity applied
to the catchment will cause runoff that will reach its
maximum rate when all parts of the watershed arecontributing to the outflow. This will happen after
the elapsed time tc, the time of concentration. At thistime the runoff rate equals the excess rainfall rate.
There are a few well defined criteria for selectionof formulas or methods for determining the time ofconcentration. A number of formulas and methods
for determining tc exist. Only one of them will bepresented here:
Kirpich (Ramser) time of concentration equation.
Formula 3

The watershed class sub-class and space
utilization shall consist of sub-basin boundary tables,
which contain sub-basin objects and their attributes
containing {OID; N_CA; Area_Ha; Perimeter;
L_CA}, and chatment object with the same attribute,but the attribute value is the sum of all attributevalues of the sub-watershed that are its members.
Land utilization subclass will contain Tables
with attribute {OID; L_Use; Area_Ha; Koef_C;
Root_Depht}, which is connected to the sub-basinboundary based on the typical identifier number(OID), thus forming the sub-basin table relation{OID; Land Use}.
ANALYSIS MODEL INTER OBJECT DATAt = 0.0195∗L0.77∗S-0.385 (Kirpich/Ramser)

One method for analyzing flood peaks as a resultof land use change in a watershed is by analyzing
runoff. One important empirical formula for
determining the peak rate of runoff is the Rational
Formula. This formula is mostly used for designing
drainage facilities for small urban and rural
watersheds. It is characterized by (1) considerationof the entire drainage area as a single unit, (2)estimation of flow at the most downstream point,and (3) the assumption that rainfall is uniformly
distributed over the drainage area.

[3]

where,
tc = Time of concentration [min].
L = Length of main river [m].
S = Distance weighted channel slope [m/m].
CONCLUSION(1) There are 8 identifiable data objects with 7
relationships(2) The relationship between data objects isformulated by utilizing the SQL Select model bylinking Tables and columns based on rational
formulas579

SEE - Nagoya, Japan, Nov.12-14, 2018[12] Sarangi A, Bhattacharya AK, Singh AK,SambaihaA(2005b)
Performanceof
Geomorphologic Instantaneous Unit Hydrograph(GIUH) model for estimation of surface runoff.
In: International conference on recent advancesinwater
resourcesdevelopment
andmanagement, 23rd to 25th Nov 2005, IIT,
Roorkee, Uttaranchal, India, pp 569–581[13] SCS (1956) Hydrology, national engineering
handbook, supplement A, Section–4 Chapter 10,
Soil Conservation Service, USDA, Washington,
DC[14] Shrestha MN (2003) Spatially distributedhydrological modelling considering land-use
changes using remote sensing and GIS, Water
Resources, Map Asia Conference 2003, Map
Asia 2003. http://www. gisdevelopment.net[15] Singh AK, Bhattacharya AK (2006) Water
management and crop production, Handbook of
Agriculture, Directorate of information andpublication of agriculture. ICAR, New Delhi, pp
300–348[16] Socher M, Sieber HU, Mu¨ller G, Wundrak P(2006)
VerfahrenzurlandesweitenPriorisierungvon
Ho-chwassers
chutzmaßnahmenin
Sachsen.Hydrologie
undWasserbewirtschaftung50(3)[17]. Zade M, Ray SS, Dutta S, Panigrahy S (2005)
Analysis of runoff pattern for all major basins ofIndia derivedusing remote sensing data. Curr Sci
88(8):1301–1305[18] Sadiki, A., Faleh, A., Navas, A., Bouhlassa, S.,
2007. Assessing soil erosion and control factors
by the radiometric technique in the Boussouabcatchment, Eastern Rif, Morocco. CATENA 71,
13–20.
[19] Tyagi, J., Mishra, S., Singh, R., Singh, V.,
2008. Cscnbased timedistributed sediment yieldmodel. Journal of Hydrology 352, 388– 403.
[20] Zeynab Karimzadeh Motlagh, Mohammad
Husein Sayadi (2016). Siting MSW landfills
using MCE methodology in GIS environment(Case study: Birjand plain, Iran). Journal Waste
Management, Elsevier. Volume 46, Desember
2016, pages 322-377.
[21] Dinar DA Putranto, Sarino, Yuono, AL, 2015,
Model Medan Digital Untuk Analisis RainfallRunoff Sub DAS Musi Bagian Hulu-Hilir DAS
Musi, Laporan Penelitian, Hibah Strategis
Nasional.
[22] Dinar DA Putranto, Sarino, Yuono, AL, 2009,
Model 1D/2D Dalam Analisis Pemodelan Banjir
Kota Palembang, Laporan Penelitian, Hibah
Strategis Nasional.

ACKNOWLEDGEMENTS
Acknowledgments are submitted to the ResearchInstitute of Sriwijaya University, which has provided
a Competitive research fund for this activity.
REFERENCES[1] He C. Integration of geographic information
systems and simulation model for watershedmanagement. Environ Model Softw, 2003) 18(8–9):809–813[2] Mokarram, M., Hoyati, M., Using orderedweight averaging (OWA) aggregation for multicriteria soil fertility evaluation by GIS (casestudy: southeast Iran), Computers andElectronics in Agriculture, vol. 132 (2017) pp. 113 Published by Elsevier B.V.
[3] Dinar DA Putranto, Sarino, Yuono, AL., Sistem
Manajemen Alokasi Lahan (SIMAL) Sebagai
Dasar Dalam Melakukan Alokasi Ruang,
Proseding, FIT-ISI dan CGISE (2015)[4] Malczewski J, GIS- based multicriteria decision
analysis :a survey of the literature. Int J Geogr
Inf Sci 20 (7), 2007, :703–726[5] Malczewski J, Chapman T, Flegel C, Walters D,
Shrubsole D, Healy MA, GIS multicriteria
evaluation with ordered weight edaveraging(OWA) :case study of developing watershedmanagement strategies. Environ Plan A 35 (10),(2003): 1769–1784[6] Olivera F, Valenzuela M, Watershed and srteam
delineation
tool
interface.
http://cprofs.tamu.edu/folivera/GISTools/wsdt/
home.htm. Cited 26 June 2006[7]Sarangi A, Bhattacharya AK, Small watershed
runoff generation model. J Soil Water Conserv
43 (3&4), (1999) :176–188[8]Sumi Amarina Hamim, Model Pengendalian
Lingkungan sub Sistem Sungai Dalam
Manajemen Sistem Drainase Kota Palembang,
Disertasi, Program Doktor Ilmu Lingkungan,
Program Pascasarjana, UNSRI (2009)[9]Sarangi A, Bhattacharya AK, Comparison of
artificial neural network and regression models
for sediment loss prediction from Banha
watershed in India. Agric Water Manag, (2009),
78:195–208[10] Sarangi A, Madramootoo CA, Singh DK,
Development of ArcGIS assisted user interfaces
for estimation of watershed morphologic
parameters. J Soil Water Conserv, {2004) 3(3,4):139–149[11] Sarangi A, Madramootoo CA, Enright P,
Prasher SO, Patel RM (2005a) Performance
evaluation of ANN and geomorphology-basedmodels for runoff and sediment yield prediction
for a Canadian watershed. CurrSci, (2005)(12):2022–2033

580

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ANALYSIS OF TRAFFIC ENVIRONMENT
AND DYNAMIC BEHAVIOR OF BRIDGE GIRDERS
BASED ON IMAGE SENSING TECHNIQUES
1,4

Kouichi Takeya1, Koharu Ota2, Shiho Takagi3 and Junji Yoshida4
Faculty of Engineering, Graduate School, University of Yamanashi, Japan;
2,3Faculty of Engineering, University of Yamanashi, Japan.
ABSTRACTIn this study, image sensing techniques are focused to grasp the traffic environment and the dynamic behaviorof bridges simultaneously. The dynamic deflection of bridge girders and the traffic environment, such as speed
type of vehicles and weight, can be analyzed using the combination of the sampling moire method and optical flow
process. In this research, we attempted to construct a measuring method of traffic environment and dynamic
behavior of bridge girders based on these image sensing techniques.
As results of this fundamental study using a model bridge, first, a displacement measuring method was
examined and constructed based on the sampling moire method. The results were compared with measured
displacement by laser displacement sensors in the model experiments. It was demonstrated that the dynamic
deflection of the bridge girder can be calculated with high accuracy. Second, an analysis method of traffic
environment was constructed based on the optical flow process. It was demonstrated that the velocity and size ofmoving objects can be detected and monitored automatically.
Finally, by combining these two methods, an analysis system of the traffic weight using dynamic behavior ofbridges (known as Bridge Weigh-in-Motion or B-WIM) was proposed. Since these two measuring methods use
the same images taken by one camera, the proposed system can grasp the traffic environment and the dynamic
behavior of the model bridge simultaneously.
Keywords: Bridge deflection, Sampling moire method, Optical flow process, Traffic environment, B-WIM.
simultaneously grasping the dynamic behavior. The
dynamic deflection of bridge girders, when vehicles
are passing through, is aimed at analyzing thesampling moire method by photographing target grids
attached on bridges [3]-[5]. In this research, we
attempted to construct an analysis system to grasp theadvanced traffic environment such as the variablevelocity of the traffic, the vehicle type and weight byusing model experiments as a fundamental study.

INTRODUCTION
Aged deterioration of bridges is progressing due
to traffic vehicles, weather conditions, etc. Amongthem, heavy vehicles including overloaded vehicles
have a large influence on the deterioration of bridges.
Therefore, investigation of traffic environment on
bridges is highly required.
As a method to grasp the traffic environment ofheavy vehicles on bridges and estimate thedeterioration, Bridge Weigh-in-Motion (B-WIM) has
been focused for last several decades [1]. B-WIM isa method to estimate the traffic weight by sensing the
dynamic deflection or strain of the bridge members.
The influence line is mainly calculated based on the
dynamic strain measurement to estimate the traffic
weight.
To measure deflection of bridge members, such as
girders, direct measurements with contact ornoncontact displacement sensors exist. However,these are difficult to install, and the applicable bridge
is limited. On the other hand, a laser Doppler
velocimetry or accelerometers are other candidate.
However, there is a problem with integration
accuracy [2].
In this research, we focused on monitoring thetraffic environment using the camera and

DYNAMIC DISPLACEMENT MEASUREMENT
Model Bridge for ExperimentFig. 1 shows an image of the model bridge
experiment. The model bridge is made of ABS resin,
the span of the girder between two rubber supports is
800 mm, the width is 50 mm and the thickness is 4mm. Two rails are attached on the girder; four ironballs roll on the rails separately. The weights of thesteel balls are 16 g, 32 g, 64 g, and 126 g. Five targets
are attached on the both end and each quarter pointsof the girder. Three laser displacement meters(Keyence, LK-500) are also installed to evaluate thevertical displacement at the quarter points. A digital
camera (Canon, EOS 60D) was used for high-speed
consecutive shooting of JPEG images. The

581

SEE - Nagoya, Japan, Nov.12-14, 2018

specification of the equipment and targets are shownon the Table 1 and Table 2, respectively.
Target grids

Fourier transform (DFT)
Conversion of the phase difference to thedisplacement
First, the target position is selected manually andthe unnecessary images are cropped in each video
frame. The parameters to correct the inclination of theimage and the contrast are automatically determinedfrom the default image. Next, grid images are divided
in the vertical and horizontal directions and analyzed
separately. In this study, only the vertical direction
was focused. The blank columns (or rows) are
interpolated linearly and stripe pattern are created asshown in Fig. 3(A). Next, the image is sampled every
N pixel (N is named the sampling number) in verticaldirection and the blank pixels are interpolated linearlyusing the neighboring pixels. Through this sampling
process, N number of phase-shifted sampling moire
images are obtained (Fig. 3(B)).
As the sampling number N approaches the pixel
number of the pitch length in pixels, the phase periodof the phase distribution becomes longer. Therefore,
the resolution of the phase difference anddisplacement becomes higher. However, when thephase period is longer than half of the image length,
the phase difference cannot be calculated correctly
and error cases occur. Therefore, the largest sampling
number N is determined when the phase period is lessthan half of the image length, and it is iteratively
calculated and obtained automatically. Specifically,
for the vertical direction pixel v, the phase distribution ( N , v) [rad] averaged in the horizontal direction
pixel h is as follows.
4)5Model bridge
Digital camera(Canon EOS-60D)
 5184 3456 px
 5.3 fps

Laser displacement meter(LK-500 3)

Data logger(NR-600, HA-08)

Fig. 1 The model bridge and measurement
equipment of experiments
Table 1 Specification of the equipment
CameraLens
Sensors
LoggerCanon
5184×3456px
EOS 60D
Tamron, 28-78mm, F2.8
Keyence10μm
LK-500(accuracy)
Keyence±20mm
NR-60014bit
HA-08

5.3fpsanalog100Hz

Table 2 Target size and pitch length of grids

Millimeter
PixelsSize
25×25 mm(V)180  (H)180 px

Pitch length
2.031 mm18 px

 ( N , v) 1H

  ( N , v, h)h(1)Where, v = 1, 2, …, V [pixel] and h = 1, 2, …, H
[pixel]. The normalized autocorrelation functionR ( N ,  ) of the phase distribution are obtained

Sampling Moire Method
There are a lot of analysis methods of dynamic
displacement using images, such as image correlation
methods using the boundary or edge detection [6], [7],the sampling moire method [3]-[5]. Although bridges
are large-sized structures, their deflection is on theorder of a few millimeters, then the high resolution isrequired. Therefore, it is considered that the samplingmoire method is applicable for measuring thedeflection of bridge girders.
To calculate the vertical displacement or
deflection of the bridge girders, the procedure by the
sampling moire method is as follows.
1) Image preprocessing(contrast adjustment, noise
cancelling,correcting image size and inclination)2) Sampling every N pixel, shifting the sampling
points and the linear interpolation usingneighboring pixels(Creating phase-shifted sampling moire images)
3) Phase distribution calculated by the discretewith the sampling number N, where υ is in the range
between –V and +V [pixel]. The maximum sampling
number N is determined when peaks of thenormalized autocorrelation function Pk(N) are three (k= 1, 2, 3). In this study, the condition of the peaks was
set to 0.5 or more.
R ( N , )   ( N , v) ( N , v   )  ( N , v)v

Pk ( N ) | 1,2,3  0.5

2

(2)

v

(3)

The phase analysis by the discrete Fouriertransform (DFT) is carried out and one phase
distribution image is obtained (Fig. 3(C)). The phase
distribution image is calculated in each video frame(Fig. 3(D)). Fig. 4 shows an example of the phase
distribution with the optimized sampling number N =582

SEE - Nagoya, Japan, Nov.12-14, 201813.

absolute jumps between consecutive elements of (t ) are greater than π radians. The verticaldisplacement y(t) [mm] is finally calculated using thefollowing relationship.
y(t )  dy  (t )
2

(5)

Where dy is the pitch length of the vertical grid [mm].

Fig. 3 Phase analysis for two-dimensional grid(A) 2-D grid image to 1-D stripe pattern(B) Phase-shifted sampling moire images(C) Phase distribution analyzed by DFT(D) Iteration for each video flame
Fig. 5 Displacement analysis using phase analysis(E) Average phase difference in horizontal direction(F) Average phase difference in time domain
In Fig. 6, red dotted line shows the calculated
deflection by the sampling moire method when theiron ball passes through the model bridge. The blueline shows the actual value of displacement measured
by the laser displacement sensor (Keyence, LK-500).
The calculated deflection by sampling moire method
is matched with high precision with the actual values.

Fig. 4 Phase-shifted sampling moire images andphase distribution image with
optimized sampling number (N = 13)
As shown in Fig. 5(E), the phase difference Δφ(t,h) [rad] in each column (h = 1, 2, …, H) is calculated
between each moved phase distribution image at t =Tk (k = 1, 2, …, K) [sec] and the default phase
distribution image at t = T0. The average phasedifference  (t ) [rad] is calculated as follows (Fig.
5(F)).
1
 (t ) H  (t, h)hFig. 6 Vertical deflection of the center point of
the model bridge(4)

Next, four iron balls were traveled on the model
bridge around one hundred times in total. The peak
displacements calculated by the sampling moire
method and the actual values (the peak displacements

The average phase difference, between the moved
position image and the default position image, iscorrected in angles by adding multiples of ±2π when583

SEE - Nagoya, Japan, Nov.12-14, 2018measured with the laser displacement sensor) areplotted in Fig 7. The closer the plots are to the solid
black line, the higher the accuracy is. The black
dashed line shows the range of the ± 0.2 mm from theactual displacement, which can be considered as therequired accuracy for practical use of displacement
measurement at bridges.

Fig. 8 An example of the mask processing
Table 3 Parameters of the noise cancelling filters
Process
Structuring
elements
pixelsFig. 7 Distribution of the peak values ofdisplacement measured by sampling moire method
and the laser displacement sensor

Image
erosionLineshaped
15px(vertical)

Morphologicalclosing
opening
DiskDiskshaped
shaped100px
10px(radius)(radius)

Finally, the blob analysis was carried out tocalculate the size and velocity of the traffic. The
velocity of the traffic was calculated from the center
position of the blob in each video frame. An exampleof the analysis is shown in Fig. 9.
Fig. 10 shows the histogram of the velocity of thetraffic which pass through the model bridge. The
velocity of the traffic is not constant, therefore, theshown values in the histogram are the velocities when
the traffic pass through the center part of the bridge.

ESTIMATION OF TRAFFIC INFORMATION
Optical flow process
Considering and referring the many previous
studies [8]-[11], the optical flow process to analyze
the traffic on the bridges was constructed. The brief
process is shown as follows;
1) the foreground mask using the Gaussian mixture
model2) the noise cancelling filters(mask
processing,image
erosion,morphological image processing)3) the blob analysis (calculation of the size and thevelocity of traffic).
MATLAB 2016b was used for these analysis. The
figure was resized by 20 % (1037×692 pixels) to
reduce the computational load.
First, to determine whether individual pixels arepart of the background or the foreground, theforeground mask using the Gaussian mixture modelcompared a grayscale video frame to a backgroundmodel. In this mixture model, the number of Gaussianmodes was three, and the number of initial video
frame for training the background was five.
Next, four noise cancelling filters were used; amask processing, an image erosion, morphologicalimage closing and opening. The mask processing wasused for focusing only on the traffic (Fig. 8). The
image erosion and the morphological image
processing were used for eliminating the verticalmovement of the bridge girder. The parameters ofthese noise cancelling filters were tuned by try anderror (Table 3).

Fig. 9 An example of the noise cancelling process
and the detected velocity of the traffic

584

SEE - Nagoya, Japan, Nov.12-14, 2018

the relative deflection (black dotted line) from theinitial position was used.

Fig. 10 Histogram of the velocity of the traffic
Deflection Based Bridge Weigh-In-Motion

Fig. 12 Vertical displacement of the target

The traffic load is one of the most important
information of traffic environment. The method toestimate the traffic load using the dynamic structural
response of bridges is called Bridge Weigh-in-Motion(or B-WIM). Various B-WIM methods have beenstudied and proposed in the last decades, utilizingstrain, acceleration, and deflection. In thisfundamental study, a new analysis system of trafficload was proposed by using the maximum deflectionof the bridge girder measured by the sampling moire
method. This method can be applied only when the
single traffic passes through bridges. Therefore, theoptical flow process functions as a trigger for
distinguishing the single traffic condition, then the
single traffic load is analyzed. In addition, to reducethe calculation, the sampling moire method is carriedout only when the traffic is detected. The flow of the
proposed method is shown in Fig. 11.

Fig. 13 shows the relationship between the trafficload passing through the model bridge and therelative deflection. An approximate line passing
through the zero was determined by the least squared
method. As shown from the coefficient ofdetermination R 2 , the traffic load and the relative
deflection are linearly related. By using the obtained
linear equation (named the calibration function), it ispossible to estimate the traffic load from relative
deflection. The black dotted lines in Fig. 13 shows therange of traffic load ± 10 %, which is the practicallyrequired accuracy of B-WIM. Although there is atendency to underestimate when the traffic load issmall, it is not an important problem because it is only
heavy vehicles which influence the deterioration ofbridges.

Video frames

Sampling moire method

Trigger

Traffic information

Displacement

Relative deflection

Optical flow process

Existence (none / one or more)
TriggerNumber(alone /multiple)

VelocityType(size)

Deflection based B-WIM(calibrated transduce function)

WeightFig. 13 Vertical displacement of the target

Fig. 11 Proposed image processing flow chart

CONCLUSION

In actual bridges, the static vertical positionchanges mainly due to the temperature anddeterioration. Even in the model bridge of this study,
the initial position was not zero, it fluctuated slightly
during the measurement period (Fig. 12). Therefore,
instead of using the peak displacement (red circle),

In this study, we proposed the analysis system tograsp the traffic environment and dynamic behaviorof bridges. The following knowledge was obtained.
1) the displacement measuring method based on
the sampling moire method was constructed.
The analysis results were compared with the585

SEE - Nagoya, Japan, Nov.12-14, 2018

laser displacement sensor, and it was shown thatthe displacement can be calculated with highaccuracy.
2) To analyze the traffic environment, the opticalflow process based on the foreground detection
processing was constructed. Parameters of noise
cancelling filters were examined by try and error,
and it demonstrated that the velocity and size ofmoving objects can be obtained automatically inthe model experiments.
3) Combining displacement calculation by the
sampling moire method and the optical flow
process, the analysis system to estimate thetraffic load was proposed by focusing on therelative peak deflection.
It is possible to realize the advanced analysis, suchas estimation of the multiple traffic load, by utilizing
other information obtained in the image processing or
combining data from other sensors. In thisfundamental study, the noise cancelling process wasdetermined by trial and error, however, machinelearning techniques would be applied for practical useof the system.

2011, pp. 32-38.
[4] Ri S., Muramatsu T., Saka M., Nanba K., andKobayashi D., Accuracy of the Sampling Moiré
Method and its Application to Deflection
Measurements of Large-Scale Structures,
Experimental Mechanics, Vol. 52, Issue 4, 2012,
pp. 331-340.
[5] Zhang Q., Xie H., Liu Z., and Shi W., Sampling
moiré method and its application to determine
modulus of thermal barrier coatings underscanning electron microscope, Optics and Lasers
in Engineering, Vol. 107, 2018, pp. 315-324.
[6] Freitas J. D., Myers N. E., and Nobre A. C.,
Tracking the changing feature of a moving object,
Journal of Vision, Vol. 16, Issue 3, No. 22, 2016,
pp. 1-21.
[7] Shiiya K., Uchimura K., Izumida K., Sugita N.,
and Terada S., Moving Objects Detection basedon Presumption of the Amount of Edge
Displacement, Electric Engineering in Japan,
Vol. 125, No. 9, 2005, pp. 1455-1463.
[8] Stauffer, C. and W.E.L. Grimson. Adaptive
Background Mixture Models for Real-Time
Tracking, Computer Vision and Pattern
Recognition,
IEEE
ComputerSociety
Conference on, Vol. 2, 1999, pp. 246-252.
[9] Wang L., and Yung N. H. C., Extraction ofmoving objects from their background based on
multiple adaptive thresholds and boundary
evaluation, IEEE Transactions on Intelligent
Transportation Systems, Vol. 11, No. 1, 2010, pp.
40-51.
[10] Sobral A., and Vacavant A., A comprehensive
review of background subtraction algorithms
evaluated with synthetic and real videos,Computer Vision and Image Understanding, Vol.
122, 2013, pp. 4-21.
[11] Bouwmans T., Baf, F. E., and Vachon B.,
Background Modeling using Mixture ofGaussians for Foreground Detection - A Survey,
Recent Patents on Computer Science, Bentham
Science Publishers, 2008, Vol. 1, No. 3, 2008, pp.
219-237.

ACKNOWLEDGEMENTS
I would like to thank T. Ono and T. Ohata forassistance with the model experiments.
REFERENCES[1] Lydon M., Taylor S. E., Robinson D., Mufti A.,
and Brien E. J. O., Recent developments in bridge
weigh in motion (B-WIM), Journal of Civil
Structural Health Monitoring, Vol. 6, Issue 1,
2016, pp. 69-81.
[2] Sekiya H., Yokozeki K., Kimura K., Konishi T.,
and Miki C., Calculation method of bridge
displacement from acceleration record, Journal
Society of Civil Engineers (JSCE) A1, Vol. 72,
No. 1, 2016, pp 61-74.
[3] Morimoto Y., Fujigaki M., and Masaya A.,
Displacement
andStrainDistribution
Measurement by Sampling Moire Method,
Journal of the Vacuum Society of Japan, Vol.54,

586

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

NON-CONTACT ESTIMATION OF STRAIN PARAMETERTRIGGERING LIQUEFACTION
Erica Elice Saloma Uy1, Toshihiro Noda2, Kentaro Nakai3 and Jonathan Rivera Dungca4
Graduate Student, De La Salle University, Philippines; 2,3 Nagoya Univesity, Japan; 4De La Salle University,
Philippines

1

ABSTRACTThe strain parameter-triggering liquefaction is usually determined by implementing cyclic strain approachwith a corresponding laboratory experiment. These parameters are threshold shear strain, cyclic shear strain andcyclic shear strain that would trigger liquefaction. In this study, non-contact measurement technique was
implemented to estimate and monitor the development of the mentioned parameters. In this technique, amirrorless camera and Lucas and Kanade pyramidal optical flow algorithm were utilized to track the movementof the particles. The camera was first calibrated to eliminate the errors from the lens and the scene as well.
Furthermore, curvature correction was applied because the sample tested has a curved profile. The comparison
was made with the loose and medium dense conditions. The samples were tested under a consolidated undrained
cyclic triaxial test at 2.4, 1.6 and 0.8 mm strain amplitudes. The confining pressures used were 50, 100 and 200
kPa. Based on the results, non-contact measurement technique can estimate the parameters. A range of values
was established due to the non-homogeneous movement of the soil.
Keywords: Cyclic Loading, Non-Contact Measurement, Strain Parameter-Triggering Liquefaction, Curvature
Correctionof liquefaction. When γc exceeds the value of γcl this
implies that triggering of liquefaction had occurred.
Its typical value ranges from 0.4 to 3% [3]. The
minimum value of this parameter can also be seen in
Fig. 1. At this point, the pore water pressure ratio isalmost 0.95. The strain parameter-triggeringliquefaction is normally obtained from field tests orlaboratory tests such as cyclic simple shear test anddynamic triaxial test. In these tests, Linear Variable
Displacement Transducer (LVDT) is used todetermine these parameters. Kaddouri (1991)
installed the LVDT inside the triaxial cell in order toaddress the non-homogeneous deformations
measured by Dobry et al. (1981-1982) and Youd
(1972) [5]. This set-up can cause disturbances to thesample especially on how it is attached. It is also
susceptible to the tilting of the sample which canlead to errors in measurement. Furthermore, this setup cannot monitor the development of the strain
parameter-triggering liquefaction. A method that canbe implemented is non-contact measurement
technique. It utilizes cameras to estimate thedeformation of an object without causing any
disturbances [6]. Deformations are estimatedthrough image processing algorithms such as digital
image correlation (DIC), particle image velocimetry(PIV) and optical flow [6]-[8]. The technique canprovide local deformation, monitor the material’s
behavior during the experiment and assess the actual
test boundary condition. The technique was appliedin a cyclic triaxial test. Based on the results, thetechnique has the capacity to measure the

INTRODUCTION
Liquefaction assessment is performed todetermine the vulnerability of the soil to liquefy [1].
Assessment can be performed by cyclic stressapproach or cyclic strain approach. In theseapproaches, parameters needed are obtained from insitu testing techniques or laboratory testing [2]-[3].
The cyclic stress approach considers the build-up of
pore water pressure related to the cyclic shear stress(τc). Several studies pointed out that the results of
thisapproacharedependentontheoverconsolidation ratio (OCR), preshaking effect,
lateral earth pressure coefficient (K0), relative
density and method of sample preparation [2]-[3].
Due to this, researchers are focused on utilizing thecyclic strain approach. In this approach, the cyclic
shear strain is being correlated to the excess porewater pressure. Since it can characterize particle
rearrangement. The cyclic shear strain is associatedwith the deformation of the particles which is a
result of ground shaking [4]. This can produce
excess pore water pressure which can result inliquefaction. Strain parameter-triggering liquefaction
is used in the assessment. The parameters arethreshold shear strain (γtv), cyclic shear strain (γc)
and cyclic shear strain that would trigger
liquefaction (γcl). The γtv is the indicator of theinitiation of development of pore water pressure in acyclic test. This parameter is approximately 1x10-2%
existing for clean sand as seen in Fig. 1 [2]-[3].The
γcl is the parameter compared to γc on the triggering
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SEE - Nagoya, Japan, Nov.12-14, 2018

development of deformation [7]-[8]. In this study,
non-contact measurement technique was used toestimate and monitor the strain parameter-triggeringliquefaction. Two-dimensional image processing
was implemented. Lucas and Kanade pyramidal
optical flow algorithm was used to track the
deformation. A mirrorless camera was used because
it is more economical compared to a single lensreflex (SLR) camera or a high speed camera. Straincontrolled consolidated undrained test was
performed for a loose and medium dense condition.

factor. The values obtained were 0.7036 and 0.8579
for the x and y-directions, respectively. During thisphase, the camera settings and exact location of thecamera were determined. In order to ensure that theposition of the camera was fixed, it was placed at theback of the equipment. It was placed 42 cm from theequipment. In this location, the camera will not be
disturbed during the duration of the experiment.
Lighting was also controlled in order to avoid noisefrom uneven lighting. The area where uneven light
penetrated was covered with black paper.
Furthermore, a spot light was placed to improve the
distribution of light.

γcl
1
2
3
4

γtv

5
(a)
(b)
Fig.2 Calibration tools (a) calibration grid (b)straight edge block

Fig.1 Pore water pressure ratio plotted against γc [3]Table 1 Dimension of the targets

NON-CONTACT MEASUREMENT

Target1
2
3
45Calibration
The non-contact measurement was carried out by
using a mirrorless camera and optical flow
algorithm. The camera was initially calibrated and it
is divided into two phases. In the first phase, acalibration grid, as seen in Fig. 2a, with uniform
dimension and spacing, was used as a target to
extract the internal and external camera parameters.
These parameters were used to determine theposition of the points with respect to the camera
coordinate system. This was followed by applying
the polynomial distortion model to correct the
distortion from the lens. In the second phase, amagnification factor was determined. This was toeliminate the magnification from the triaxial cell andwater. Measurements were made using a straightedge block, Fig. 2b. It was carried out by placing thestraight edge block in the triaxial cell and it was
submerged with water. It can be seen thatrectangular targets were also placed on the block.
Different sizes were used to determine the amount ofmagnification encountered. The dimension of theblock is 10.0 cm x 7.0 cm. The dimensions of thetargets are tabulated in Table 1. A straight edged
block and rectangular targets were also used in orderto have an easy detection of the dimensions. Edge
detection was the image processing method used todetermine their dimensions. In order to determine
the magnification factor, the actual dimension wasplotted against the measurement from image
processing. The slope of the plot is the magnification

Dimension (LxH) (cm)0.7x1.0
0.7x1.0
0.7x0.7
0.7x2.0
0.7x0.5

Curvature Correction
The samples tested were in a cylindrical shape.
Since only 2D image processing was implemented in
the study the curvature effect needs to be corrected.
The images of the sample were corrected using thepolynomial model. This model is usually applied ina geometric correction since it can correct more
complicated types of distortion such as curved
surfaces [9]. The model is also known as nonlinear
transformation equation and it has the following
expression:𝐱𝐱 ′ = 𝐚𝐚𝟎𝟎 + 𝐚𝐚𝟏𝟏 𝐱𝐱 + 𝐚𝐚𝟐𝟐 𝐲𝐲 + 𝐚𝐚𝟑𝟑 𝐱𝐱 𝟐𝟐 + 𝐚𝐚𝟒𝟒 𝐱𝐱𝐱𝐱 + 𝐚𝐚𝟓𝟓 𝐲𝐲𝟐𝟐
𝐲𝐲 ′ = 𝐛𝐛𝟎𝟎 + 𝐛𝐛𝟏𝟏 𝐱𝐱 + 𝐛𝐛𝟐𝟐 𝐲𝐲 + 𝐛𝐛𝟑𝟑 𝐱𝐱 𝟐𝟐 + 𝐛𝐛𝟒𝟒 𝐱𝐱𝐱𝐱 + 𝐛𝐛𝟓𝟓 𝐲𝐲 𝟐𝟐

(1)
(2)

where x’ and y’ = corrected real-world coordinatesin x- and y-axis; x and y = original real-world
coordinates in x- and y-axis; a0 to a5 and b0 to b5 =polynomial correction parameters. The parameters
were obtained by least square error method for eachexperiment.
In order to validate the model applied, corrected
deformation readings were compared to the LVDT.
The target points chosen are shown in Fig. 3. These
points were chosen since it is independent of the soil
movement. The displacement of the soil based on
588

SEE - Nagoya, Japan, Nov.12-14, 2018

grayscale images. It is a type of feature based
approach where it assumes that brightness isconstant variable in the successive images. The
algorithm uses image patches together withwindowing methods. Least squares technique isimplemented to extract the changes in position [11].
The residual function ε is minimized to extract the�𝒅𝒅⃑ [10].

the results can be smaller or larger than the LVDT.
The typical results are shown in Figs. 4-5. It isnoticeable that the rightmost side experienced morecurvature than the leftmost side. It can be seen on
the extension loading of the rightmost side of thedisplacements from image processing (IP) were
smaller. Applying the curvature correction lessened
the errors from IP. The errors at the left target
lessened from 0.14 - 34.32% to 0.10 - 29.81%. For
the right target, it lessened from 0.133 -37.671% to
0.031 - 29.236%. Based on these results, thepolynomial model was adopted to correct thecurvature present in the sample. In addition to thecalibration
previously
discussed,
curvaturecorrection was always implemented prior todetermining the deformation and strain parametertriggering liquefaction. A correction was done withrespect to the height of the sample, location, andsection being monitored.

�⃑� = 𝜺𝜺�𝒅𝒅𝒙𝒙 , 𝒅𝒅𝒚𝒚 � =𝜺𝜺�𝒅𝒅𝒖𝒖𝒙𝒙 +𝝎𝝎𝒙𝒙

�

𝒖𝒖𝒚𝒚+𝝎𝝎𝒚𝒚�

𝒙𝒙=𝒖𝒖𝒙𝒙−𝝎𝝎𝒙𝒙 𝒙𝒙=𝒖𝒖𝒚𝒚 −𝝎𝝎𝒚𝒚[𝑰𝑰(𝒙𝒙, 𝒚𝒚)− 𝑱𝑱(𝒙𝒙 + 𝒅𝒅𝒅𝒅, 𝒚𝒚 + 𝒅𝒅𝒅𝒅)]𝟐𝟐(3)
where I(x, y) = First image with (x,y) pixel location;
J(x, y) = Second image with (x,y) pixel location; dx,
dy = image displacement and ωx, ωy = are arbitrary
numbers that ranges from 1, 2, 3 or more pixels.
CYCLIC TRIAXIAL TEST
Sample Preparation
Mikawa number 6 sand was used in the study. It
is an artificially produced shaved sample which has
high concentrations of silica. It can be considered assilica sand and can be classified as a coarse material.
This makes it susceptible to liquefaction. Samples
were prepared by air pluviation as specified in theJapanese Geotechnical Society (JGS) standard forsample preparation of coarse granular materials forthe triaxial test (JGS 0530-2009) [12]. Loose
condition (S1) and medium dense (S2) wereprepared to have 30% and 50% as the target relative
density, respectively.

Right
Target(RT)

Left
Target
(LT)

LVDT
IP

1

0

Displacement (mm)Displacement (mm)Fig.3 Monitored targets for curvature correction

-1
0

1000
2000
Time (sec)

LVDT
IP

1

0

-1
0

1000
Time (sec)

-1
0

2000

(a)

0

Displacement (mm)Displacement (mm)

(a)

LVDT
IP

1

1000
2000
Time (sec)(b)
Fig.4 Monitored LT (a) not corrected (b) corrected

0

-1
0

Optical Flow

LVDT
IP

1

1000
Time (sec)

2000

(b)
Fig.5 Monitored RT (a) not corrected (b) corrected

Lucas and Kanade pyramidal optical flow
algorithm were implemented to estimate monitor the
movement of the soil under cyclic loading. The�⃑) ofalgorithm determines the image displacement (𝒅𝒅the point of interest by tracking it in succeeding

Cyclic Triaxial Test
The strain-controlled consolidated undrained test
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SEE - Nagoya, Japan, Nov.12-14, 2018

was performed as specified in the JGS 0541-2009[12]. The confining pressure applied was 50, 100
and 200 kPa. The samples were cyclically loadedwith 2.4, 1.6 and 0.8 mm strain amplitudes (SA) for
10 cycles. In order to properly estimate the strain
parameter-triggering liquefaction, a slow frequency
was adopted. Furthermore, images were taken every
5 seconds.

between the LVDT and IP. For the internalmeasurements, the monitored sections are similar to
Fig. 6. It can be observed in Fig. 8 that there is anincreasing amount of deformation as the monitoredsection is closer to the top cap or where there is adirect contact with the applied load. Onceliquefaction occurred it was observed that larger
deformation was seen at the top section. The
measurement from IP shows that deformation trend
at different locations of the sample was not similar.
This implies that non-homogeneous deformation
exists during cyclic loading. The results of the strain
parameter-triggering liquefaction are tabulated inTables 2-5. Based on the results, a range of values
was estimated due to the non-homogeneous
movement observed from the locations and sections
monitored. The estimated γtv was observed to haveno consistent trend. It was observed that theminimum values estimated for both conditions are in
the vicinity of 10-2%. The results were compared tothe typical values. It is consistent with the findingsof Dobry and Abdoun (2011) that γtv in sands are in
the order of 10-2% or it is approximately 1x10-2%[2]-[3]. The maximum values, on the other hand, hadlarger results.
This can be caused by thehoneycombs present in the sample.

STRAIN PARAMETER-TRIGGERINGLIQUEFACTION
The strain parameter-triggering liquefaction was
estimated using the general engineering shear strain.
Equation 4 was used in the computation [13]. The γc
was first computed. The γtv and γcl were determinedin correlation with the pore water pressure ratio.
This is the ratio of the excess pore water pressure
with the confining pressure. The γtv has a pore waterpressure ratio close to zero or less than 0.1. At thispoint, there is no development of pore waterpressure. The γcl on the other hand has a value close
to 0.95. At this point, triggering of liquefaction isabout to occur. In order to apply Eqn 4, a 5 x 5-pixel
rectangular grid was used in the estimation.
1  ∂v ∂u +
2  ∂x ∂y 

γ= 

𝝏𝝏𝝏𝝏

(4)

Table 2 γtv for S1 (%) estimated from IP
S
A
2.4

𝝏𝝏𝝏𝝏

where 𝝏𝝏𝝏𝝏 , 𝝏𝝏𝝏𝝏 = displacement gradient.

The cyclic shear strain that would trigger
liquefaction was monitored at in three locations
namely, left (L), center (C) and right (R) location.
These locations are further subdivided into the top(T), middle (M) and bottom (B) section as seen in
Fig. 6. The parameter was monitored at different
locations and sections in order to investigate theoccurrence of non-homogeneous deformation. The
results estimated from IP were compared to the
LVDT. Shear strain from LVDT was computed
based on the following equation [14]:

1.6

0.8

L
o
c
T
M
B
T
M
B
T
M
B

Cell Pressure (kPa)
50

100

200

0.0144-0.2948
0.0265-0.3052
0.0037-0.5131
0.0053-0.7529
0.0008-0.8727
0.0005-0.4789
0.0033-0.6206
0.0014-0.8610
0.0349-0.8843

0.0076-0.4225
0.0020-1.0482
0.0014-1.6852
0.0072-0.4165
0.0324-0.6011
0.0172-0.6765
0.0011-0.4505
0.0015-0.5076
0.0004-0.3942

0.0555-0.2619
0.0066-0.6288
0.0102-0.4843
0.0005-0.2751
0.0001-0.2716
0.0001-0.2045
0.0110-0.6521
0.0077-0.5745
0.0053-0.3090

A similar trend was observed when the IP results
were compared with the LVDT results. The LVDT
results are tabulated in Table 6. For the γcl, the effectof varying the relative density, strain amplitude andconfining pressure was investigated. For the relative
density, S1 had larger results compared to S2 since it
has more voids present. Particle movement wasmore evident for S1. For the effect of strain
amplitude, γcl had larger values for 2.4 mm SA. On
the other hand, γcl decreased as the applied SA was
smaller. The variation in the results was due to thedifference in the applied amount of cyclic
deformation. For the effect of increasing theconfining pressure, the values for S1and S2 for all
sections and locations decreased as the confiningpressure was increased. As a whole, the estimated γclfrom IP was observed to be affected by the relative
density, strain amplitude and confining pressure.

(5)γ = εa(1+ν)
where εa = axial strain; ν = Poisson’s ratio. The
Poisson’s ratio for saturated sand can be assumed tobe 0.5.
RESULTS AND DISCUSSION
In order to verify the strain parameter-triggeringliquefaction from the mirrorless camera, its
measurements were compared with the LVDT. The
LVDT used in the experiment had a rated capacityof 20 mm, a sensitivity of 5 mV/V ±0.1 % andmeasurement uncertainty of within ±0.1 % of its
rated capacity. The comparison was made bychoosing a target on the cyclic triaxial equipment.
The target used was the top cap. Based on the results
as seen in Fig. 7, there was a good agreement590

SEE - Nagoya, Japan, Nov.12-14, 2018

S
A
2.4

1.6

0.8

L
o
c
T
M
B
T
M
B
T
M
B

Cell Pressure (kPa)
50

100

200

1.6099-2.8610
0.6910-4.5103
0.0039-1.8144
0.2668-2.4369
0.0567-1.8868
0.0064-3.7311
0.5851-1.9680
0.1452-1.6467
0.0493-3.2151

1.3085-2.9153
0.5722-2.8932
0.0178-1.8413
0.6478-2.3364
0.3210-1.8244
0.0150-0.7113
0.2442-0.9192
0.0163-3.0629
0.0011-0.6123

0.6401-1.6863
0.0047-0.9335
0.0114-0.6625
0.6681-1.7113
0.1803-1.4358
0.0054-0.4504
0.1156-1.2943
0.0187-0.6751
0.0096-0.4909

Table 4 γtv for S2 (%) estimated from IP
SA
2.4

1.6

0.8

L
o
c
T
M
B
T
M
B
T
M
B

Cell Pressure (kPa)
50

100

200

0.0049-0.4747
0.0147-0.8319
0.0310-0.7378
0.0019-0.6675
0.0042-1.6312
0.0038-0.9827
0.0011-0.3402
0.0023-0.8549
0.0019-0.5144

0.0282-0.9028
0.0216-0.8536
0.0522-0.9129
0.0087-1.1841
0.0011-1.0174
0.0019-0.5110
0.0034-0.5605
0.0019-1.5386
0.0008-0.9354

0.0197-0.3953
0.0072-0.7722
0.0076-0.3258
0.0057-0.5601
0.0045-0.4838
0.0083-0.5805
0.0030-0.5794
0.0008-0.5303
0.0045-0.4112

the maximum values are larger. The LVDT results,
as seen in Table 7, were also compared and a similar
trend was observed. The results were also comparedwith the range of pore water pressure responses forsands with different relative densities proposed by
Dobry (1985). The proposed range had an upperbound and lower bound curve as seen in Fig. 1.
These were overlayed to the results of IP toinvestigate the validity of its results. Typical results
are shown in Figs. 9-10. It can be seen that for S1
γc exceeds the boundary but for estimations prior toliquefaction. Once liquefaction had occurred theestimations are within the boundaries. For S2, moreestimation can be seen within the boundary. Moremovements were present for S1 since it has morevoids compared to S2. A difference can also be seen
for the results of LVDT when it was compared withthe proposed boundary. A smaller SA was used forthe proposed boundary. The SA used had amaximum value of approximately 0.675% while amaximum value of 2.4% was used for the study.
Pore water pressure ratio

Table 3 γcl for S1 (%) estimated from IP

Table 5 γcl for S1 (%) estimated from IP

1.6

0.8

50

100

200

0.2804-1.7204
0.0646-1.1497
0.0121-0.6603
0.0265-1.2563
0.0238-1.6607
0.0060-0.7540
0.02419-0.8761
0.00794-1.9839
0.00831-0.4566

0.0134-0.8547
0.0061-1.8240
0.0022-2.0432
0.0393-1.4275
0.0151-1.2854
0.0030-1.0280
0.0450-1.0730
0.0094-1.3992
0.0159-1.3005

0.1739-3.4617
0.2332-1.4612
0.0015-0.6380
0.0620-1.6479
0.0261-0.9577
0.0057-1.0473
0.0178-0.8338
0.0094-0.5083
0.0140-0.8141

Table 6 γtv and γcl for S1 (%) from LVDT
SA

2.4
1.6
0.8

γtv
Cell Pressure (kPa)
50
100
200
0.0009 0.0542 0.0828
0.0386 0.0359 0.0407
0.0360 0.0451 0.0372

γclCell Pressure (kPa)
50
100
200
1.7180 1.7070 1.5062
1.0876 1.1078 1.0769
0.4868 0.3800 0.0439

Table 7 γtv and γcl for S2 (%) from LVDT
SA

2.4
1.6
0.8

γtv
Cell Pressure (kPa)
50
100
200
0.0792 0.0892
0.054
0.0046 0.0394 0.0659
0.0184 0.0202 0.0315

γcl
Cell Pressure (kPa)
50
100
200
1.5288 1.0169 1.3872
0.5182 0.7583 0.9959
0.4737 0.4855 0.9959

In order to verify the results from IP, the typicalvalue of γcl was compared. The typical value ranges
from 0.4-3% [8]. The minimum values for all
conditions are within the range. On the other hand,

0.8
0.6
0.4
0.2
0

-2
-1
0
1
2
Cyclic shear strain (%)

Fig.8 Comparison of the γc from LVDT and IP
considering the sections monitored
Pore water pressure ratio

2.4

Cell Pressure (kPa)1

Dobry (1985)

0.8
0.6
0.4
0.2
0 -3
10

10-2
10-1
100
Cyclic Shear Strain (%)

50kPa (LVDT)
100kPa (LVDT)200kPa (LVDT)
50kPa (IP-T)
50kPa (IP-M)
50kPa (IP-B)
100kPa (IP-T)
100kPa (IP-M)
100kPa (IP-B)
200kPa (IP-T)
200kPa (IP-M)
200kPa (IP-B)

Fig.9 Comparison of the γc from LVDT and IP (S1)Pore water pressure ratio

SA

L
o
c
T
M
B
T
M
B
T
M
B

LVDT
IP (T)IP (M)IP (B)

1

1

Dobry (1985)

0.8
0.6
0.4
0.2
0 -3
10

10-2
10-1
100
Cyclic Shear Strain (%)

50kPa (LVDT)
100kPa (LVDT)200kPa (LVDT)
50kPa (IP-T)
50kPa (IP-M)
50kPa (IP-B)
100kPa (IP-T)
100kPa (IP-M)
100kPa (IP-B)
200kPa (IP-T)
200kPa (IP-M)
200kPa (IP-B)

Fig.10 Comparison of the γc from LVDT and IP (S2)CONCLUSION
Strain parameter-triggering liquefaction was
estimated using non-contact measurement technique.
Before applying the technique, calibration was

591

SEE - Nagoya, Japan, Nov.12-14, 2018

performed to eliminate the distortion from the lensand the scene. In addition to that, curvaturecorrection was implemented with respect to theheight of the sample, location, and section being
monitored. The curved profile of the soil surface wascorrected since it caused an error in themeasurement of the deformation. Curvaturecorrection can improve the monitoring of themirrorless camera. The capacity of the mirrorlesscamera to estimate the cyclic shear strain was also
investigated. The top cap was used as the target andit was compared with the LVDT. A good agreement
was observed. For the internal measurement, a nonhomogeneous deformation was observed. The values
increased from the bottom to the top location. For
the estimated γtv, no consistent trend was observed.
Minimum values are within the typical values of 102% or approximately 1x10-2%. Maximum values, on
the other hand, are larger. For the estimated γcl, therelative density, strain amplitude and confiningpressure. When the results are compared with theproposed boundary of Dobry (1985) it was also
observed that the results were greatly affected by thevalue of SA used. The non-contact measurement
technique implemented can still be extended tothree-dimensional monitoring. This can be beneficial
to understating the whole behavior of the soil as it
experiences liquefaction.

[4] Derakhshandi, M. et al. (2008). The effect ofplastic ﬁnes on the pore pressure generation
characteristics of saturated sands. Soil Dynamics
and Earthquake Engineering, 28, 376–386.
[5] Kaddouri, A., Mechanical characterization of thethresholdstraininsandliquefaction.
Proceedings: Second International Conference on
Recent Advances In Geotechnical Earthquake
Engineering and Soil Dynamics. 1991, pp.20112014.
[6] Uy E.E.S. and Boonyatee T., Image Processing
for Geotechnical Laboratory Measurements.
International Journal of GEOMATE, Vol. 10,
Issue 22, 2016, pp. 1964-1970.
[7] Longtan S., Song Y., Yong S., Chuan, H. andXiaoxia, G., Application of Digital Image
Processing Technology in Dynamic Triaxial Testof Soil Mechanics. Journal of Theoretical andApplied Information Technology, Vol. 48, Issue
3, 2013, pp.1358-1365.
[8] Koseki J., Hoshino R., Miyashita Y. and Sato T.,
Direct and Indirect Observations of Local
Properties of Saturated Sand Specimens in
Undrained Cyclic Triaxial Tests. The 6th JapanKorea Geotechnical Workshop, Vol. 4, Issue 1,
2016.
[9] Wahyudi S., Miyashita Y. and Koseki, J. Shear
Banding Characteristics of Sand in Torsional
Shear Test Evaluated By Means of Image
Analysis Technique, Bulletin of ERS, No.45,
2012, pp.1-8[10] Fernando W.S.P., Udawatta L. and Pathirana P.,
Identification of Moving Obstacles with
Pyramidal Lucas and Kanade Optical Flow andK Means Clustering. Proceedings on the Third
International Conference on Information andAutomation for Sustainability, 2007.
[11] Thota S.D., Vemulapalli K.S., Chintalapati K.
and Srinivas, P.S., Comparison Between the
Optical Flow Computational Techniques.
International Journal of Engineering Trends andTechnology, Vol. 4, Issue 10, 2013.
[12] The Japanese Geotechnical Society, Japanese
Geotechnical Society Standards: Laboratory
Testing Standards of Geomaterial. Issue 1, 2008.
[13] Sutton M.A., Orteu J.J. and Schreier H.W.,
Image Correlation for Shape, Motion andDeformation Measurements: Basic Concepts,
Theory and Applications: Springer, 2009.
Vol.25, No.3, 2011, pp.1460-1465.
[14] Dobry R. and Abdoun T., An Investigation into
Why Liquefaction Charts Work: A Necessary
Step Toward Integrating the States of Art andPractice. Proceedings of the Fifth International
Conference on Earthquake GeotechnicalEngineering,2011,
pp.13-45.

ACKNOWLEDGMENTS
The researcher would like to express her gratitude
to the Engineering Research and Development forTechnology, Civil Engineering Department of De La
Salle University and the Graduate School of Civil
and Environmental Engineering of Nagoya
University Geotechnical Engineering Division for
their support.
REFERENCES[1] Dungca, J.R., Kuwano, J., Takahashi, A,
Saruwatari, T., Izawa, J.,
Suzuki, H. andTokimatsu, K. Shaking table tests on the lateral
response of a pile buried in liquid sand. Soil
Dynamics and Earthquake Engineering, 2006,
Vol. 26, Issue 2-4, pp. 287-295[2] Dobry R. and Abdoun, T., Recent Findings on
Liquefaction Triggering in Clean and Silty Sands
during Earthquakes. Journal of Geotechnical andGeoenvironmental Engineering, Vol. 143, Issue
10, 2017, pp. 04017077-1-19.
[3] Dobry R. and Abdoun T., Cyclic Shear Strain
Needed for Liquefaction Triggering andAssessment of Overburden Pressure Factor Kσ.
ASCEJournalof
GeotechnicalandGeoenvironmental Engineering, 2015, pp. 1-18.

592

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

INFLUENCE OF DEVELOPMENT/DIMINISHING OF ANISOTROPY
ON THE MECHANICAL BEHAVIOR OF CLAYEY SPECIMEN.
Imran Khan1, Kentaro Nakai2, Toshihiro Noda3and Kota Mizukami4
1,2,4
Department of Civil Engineering, Nagoya University, Japan
3
Disaster Mitigation Research Center, Nagoya University, Japan

ABSTRACT
Anisotropy refers to the directional dependence of material properties. In order to know the true behavior ofnaturally deposited soil, the knowledge of development/diminishing of anisotropy are very important. The
anisotropy of clays and silty clay intimately connected with their structure, which depends on the environmental
conditions during which the soil is deposited as well as the stress changes subsequent to deposition. In this paper,
triaxial tests were carried out using the vertical and the horizontal extraction specimen of the reconstituted clay
and silty clay, for accumulating experimental facts of development of anisotropy during the preliminary
consolidation process and the influence of the anisotropy on the shear behavior. Pre-consolidation pressure of
200kPa applied to induced initial anisotropy. Undrained shear triaxial test was performed with different isotropic
stresses on clay and silty clay, isotopically consolidated for 24 hours and undrained shearing was carried out
under constant axial strain rate of 0.0056(mm/min). Vertical sample shows larger peak strength as compared tohorizontal, because of the development of anisotropy on the compression side. As the confining pressure
increases, the difference between peak strength of vertical and horizontal becomes smaller and smaller whichindicate that the anisotropy diminished and intensity ratio decreases. By comparing clay and silty clay, silty clay
materials lose their anisotropy at lower confining pressure as compared to clay materials. Therefore, the grain
sizes have significant effect on the developing and diminishing of anisotropy. Another important fact observed
was critical state index is decreasing and become constant as confining pressure increases.
Keywords: Anisotropy, Clay, Silty Clay, Undrained shear test and Critical state index.

depths showed different coefficients of anisotropy indifferent laboratory tests [2]. There have been somesimilar studies related to this research [3]-[5] andnumerous experimental studies on the effects ofanisotropy have been conducted focusing on theshear strength, however, there is not much to explain
how the anisotropy develops or disappears withongoing plastic deformation.
In this paper, triaxial compression tests werecarried out using the vertical and the horizontal
extraction specimen of the reconstituted clay andsilty clay sample, for accumulating experimental
facts of development of anisotropy during thepreliminary consolidation process and the influenceof the anisotropy on the shear behavior. Also thecomparison of clayey and silty clay and how thegrain size affects the development/diminishing of
anisotropy were discussed.

INTRODUCTION
Anisotropy refers to the directional dependenceof material properties. The anisotropy of clays andsilty clay intimately connected with their structure,
which depends on the environmental conditions
during which the soil is deposited as well as thestress changes subsequent to deposition. Neglecting
the anisotropy of soil behavior may lead to highly
inaccurate predictions of soil response underloading. In order to know the true behavior ofnaturally deposited soil, the knowledge ofdevelopment/diminishing of anisotropy are very
important.
Hoque et al. investigated the anisotropy in elastic
deformation of granular materials by measuringlocal strains in both vertical and horizontal direction
with static cyclic loading. He found that verticalyoung modulus is greater than horizontal young
modulus at isotropic stress level [1]. Islam et al.
investigated the strength anisotropy in both verticaland horizontal directions by trimming the specimens
at different angles so as to obtain the test samples ofdifferent orientations, compared to the depositional
direction and then subjected to UC and DS tests forboth the horizontal and vertical planes fromundisturbed clay masses. He concluded that the clay
samples collected from different places and different

EXPERIMENTAL WORK
Physical properties and grain size distribution of
the clay and silty clay used in the experiment are
shown in Table 1 and Figure 1 respectively. After
thorough stirring and degassing at a water content of
1.5 times the liquid limit, we applied preconsolidation pressure of 200kPa for one week forclay and two days for silty clay.
593

SEE - Nagoya, Japan, Nov.12-14, 2018

The method of extracting the sample from thepreliminary consolidation tank is the following;
specimen pulled out so that the axis was in thevertical direction is vertical specimen and thespecimen extracted so that the axis is in thehorizontal direction is horizontal specimen, shown
below in schematic figure 2.
By extracting the reconstituted sample fromdifferent directions, samples with different initial
anisotropy were prepared. Five (5) types of isotropic
stresses of 50, 100, 300, 600, 1800 kPa were appliedon clay and (3) three isotropic stressed of 50,300 and
600kPa were applied on silty clay. Both clay andsilty clay were isotopically consolidated for 24hours.
The saturation values (B) of each sample wereconfirmed to be 0.96 or higher. After isotropic
consolidation, undrained shearing was carried out
under constant axial strain rate of 0.0056(mm/min)for clay and 0.0112(mm/min) for silty clay. Theseaxial strain rate were considered to be slow enoughto maintain element behavior (the distribution ofexcess pore water pressure inside the specimen is
uniform) during shearing.

Development/Diminishing of Anisotropy in Clay
Figures 3 to 7 shows the stress-strain relationshipand effective stress path of vertical and horizontal
specimen with different confining pressures of clay,
50 to 1800kPa respectively. Fig 8 summarizes thedifference of shear strength in vertical and horizontal
direction at the time of axial strain was 5% and 10%(almost critical state). By comparing the shear/peakstrength of samples of clay, it was observed thatvertical sample shows larger peak strength ascompared to horizontal because of the developmentof anisotropy on the compression side. As theconfining pressure increases, the difference becomes
smaller and smaller which indicate that theanisotropy disappears/diminished and intensity ratio
decreases. However, even at 300, 600, and 1800kPa,
the same degree of strength difference remains. So it
was found that even if we have applied highisotropic consolidation pressure, anisotropy was notcompletely diminishedη=1.7

Table 1 Physical properties of Soil.
Description
Liquid Limit w (%)

Clay
81.4

Silty-Clay
45.82

Plastic Limit w (%)

43.7

25.37

Plasticity index I

37.7

20.44

2.65

2.65

L

p

p

Gs(g/cm3)

Fig.3

Confining pressure (Clay) 50kPa

Percent passing (%)

100

η=1.7

80
60
40
20
0
10-3

Fig.1

Clay
Silty clay
10-2
10-1
Grain size (mm)

100

Fig.4

Grain size distributions

Confining pressure (Clay) 100kPa
η=1.5
η=1.5

鉛直供試体

V

H

水平供試体

Fig.2

Extracting Vertical & Horizontal Specimen

Fig.5

594

Confining pressure (Clay) 300kPa

800

600

η=1.5
600

400

200

0
0

10

Shearstrain

Fig.6

20

400

200

0
0

εs (%)

200

400

Meaneffectivestress

600

800

Development/Diminishing of Anisotropy in Silty
Clayp′ (kPa)

Confining pressure (Clay) 600kPa
η=1.5

Fig.7

Figures 10 to 12 shows the stress-strain relationshipand effective stress path of vertical and horizontal
specimen with different confining pressures of silty
clay at 50 to 600 kPa respectively. Fig 13
summarizes the difference of shear strength invertical and horizontal direction at the time of axial
strain was 5% and 10%. By comparing theshear/peak strength of samples of clay, it wasobserved that vertical sample shows larger peakstrength as compared to horizontal because of thedevelopment of anisotropy on the compression side.
As the confining pressure increases, the difference
becomes smaller and smaller which indicate that theanisotropy disappears/diminished and intensity ratio
decreases. Moreover, the anisotropy almost
diminished at confining pressure of 600kPa. Figure
14 summarizes the silty clay samples that the criticalstate index is changing with increasing confiningpressure same as in clayey specimen.

V
H

Confining pressure (Clay) 1800kPa

1.6%Clay at 5%%Clay at 10%

1.4

200

1.2

1
0

300

600

900

Deviator stress q (kPa)

Devaitor Stress Ratio (qv/qH)

Figure 9 summarizes the clayey samples that thecritical state index (slope of critical state line) ischanging with increasing confining pressure. Also it
was observed that, critical state index is decreasing
and become constant as confining pressure
increases.

V
H

1200 1500 180

Mean Effective stress (kPa)

150
100
50

0

Fig.8
Difference in vertical and horizontal shear
strength of Clay

V-C
H-C

Fig.105

10
15
20
Axial strain εa (%)

25

200

Deviator stress q (kPa)800

Deviator stress q (kPa)

Deviator stress q (kPa)SEE - Nagoya, Japan, Nov.12-14, 2018

Critical state Index
V=1.31150H= 1.26
Avg. = 1.29

100
50

0

100
200
Mean effective stress p' (kPa)

Confining pressure (Silty Clay) 50kPa
Critical state Index
V=1.25H= 1.25
Avg. = 1.25

Fig.11
Fig.9

Difference in critical state index of clay

595

Confining pressure (Silty Clay) 300kPa

SEE - Nagoya, Japan, Nov.12-14, 2018

600
Critical state Index

V-C
H-C

500
400
300
200
100
5

0

10

15

20

V=1.14500

Deviator stress q (kPa)25

H= 1.14
Avg. = 1.14
400

300
200
100

Fig.12

400

600

800

Mean effective stress p' (kPa)

Confining pressure (Silty Clay) 600kPa

1.6

Silty Clay at 5%
Silty Clay at 10%

1.5
1.4

1.6

1.3

Devaitor Stress Ratio (qv/qH)

Devaitor Stress Ratio (qv/qH)

200

0

Axial strain εa (%)

1.2
1.1
1
0

300

600

900

1200 1500 180

Mean Effective stress (kPa)

Fig.13 Difference in vertical and horizontal shear
strength of Silty Clay

Critical State Index

1.4

1.2

1
0

300

600

900

1200 1500 180

Silty Clay

Fig.15 Difference in vertical and horizontal shear
strength

1.6

1.8

1.4
1.2
1
0

Clay
Silty Clay

Mean Effective stress (kPa)

1.8

300

600

900

1200 1500 180

Mean Effective Stress (kPa)

Fig.14Claysamples shows larger peak strength as compared tohorizontal because of the development of anisotropy
on the compression side. As the confining pressure
increases, the difference becomes smaller andsmaller which indicate that the anisotropy
disappears/diminished and intensity ratio decreases.
It was found that even if we have applied highisotropic consolidation pressure, anisotropy was notcompletely diminished specially in case of clay soil
but in case of silty clay they lose their anisotropy at
rapid rate as compared to clayey materials, atconfining pressure of 600kPa. So, it is concluded
that the grain size has significant effect on thediminishing of anisotropy, and silty material shows
rapid change in anisotropy compared with clay
material.

Critical State Index

Deviator stress q (kPa)

600

Clay
Silty Clay

1.6
1.4
1.2

Difference in Critical state Index of Silty

1
0

300

600

900

1200 1500 180

Mean Effective Stress (kPa)Comparison of Clay and Silty ClayFig 15 summarizes the clay and silty clay
samples, difference in vertical and horizontal shear
strength at 5%. Values were taken at 5% because, incase of silty clay sample, localized failure (sudden
decrease and discontinuous curve in stress-strain
relationship) can be observed after 5% especiallywithin high confining pressure and therefore, it isdifficult to recognize as element behavior
furthermore. As indicated above, both verticalFig.16

Difference in Critical state Index

Figure 16 summarizes the clay and silty clay
samples changing of critical state index withincreasing confining pressure. Comparing clay andsilty clay, critical state index is larger for clay
material. Another important fact observed that,critical state index is changing with different
confining pressure. To describe the effect of596

SEE - Nagoya, Japan, Nov.12-14, 2018

anisotropy, rotational hardening concept was often
used. However, when introducing the rotational
hardening concept directly to the original Cam clay
model that is so called as Sekiguchi-Ota model,
critical state index did not change even if theanisotropy develops and disappears. On the other
hand, when introducing the rotational hardening
concept to modified Cam clay model, critical stateindex changes according to the plastic deformation.
Figure 17 and 18 shows the schematic diagram of an
ordinary/ Sekiguchi-Ohata model and modified Camclay model with rotational hardening respectively.
From this viewpoint, modified Cam clay model ismore suitable to use as compared to the originalCam clay model.

CONCLUSION
From a series of experimental results, it isconcluded that anisotropy developed in the
preliminary consolidation process, and anisotropy
disappears due to isotropic consolidation.
Nevertheless, it does not completely disappear evenunder high confining pressure especially in case ofclay. However, if we compare clay and silty clay
soil, silty clay materials lose their anisotropy atlower confining pressure as compared to clay
materials. Therefore, the grain sizes have significant
effect on the developing and diminishing of
anisotropy.
Another important fact observed was that criticalstate index (slope of critical state line) is decreasing
and become constant as confining pressure
increases, however, when introducing the rotational
hardening concept directly to the original Cam clay
model that is so called as Sekiguchi-Ota model,
critical state index did not change even if theanisotropy develops and disappears. On the other
hand, when introducing the rotational hardening
concept to modified Cam clay model, critical stateindex changes according to the plastic deformation.
From this viewpoint, modified Cam clay model ismore suitable to use as compared to the originalCam clay model.
Further experiment will be performed to observe theeffect of cyclic shear test to evaluate thedevelopment/diminishing of anisotropy. In order tocheck the effect of an intermediate principle stressextension test will be performed.
Moreover, based on experimental facts, numericalsimulation will be performed in future to validate theexperimental results and the constitutive model andadd some improvement if necessary.

CSL is constant

Developmentof anisotropy

Fig.17

Sekiguchi-Ohata model

Increase of CSL
ACKNOWLEDGEMENTSq

This research work was supported by Ministry of
Education, Culture, Sports, Science and Technology(Japan).
Developmentof anisotropy

REFERENCES[1] Islam, M. S., and E. Haque., Strength
Anisotropy in Undisturbed Dhaka Clay. Journalof Geotechnical Engineering 1.1 2011, pp. 7-15.
[2] Hoque, E., and Tatsuoka, F., Anisotropy inelastic deformation of granular materials. Soils
and Foundations, 1998, 38(1), pp. 163-179.
[3] Sekiguchi, H. and Ohta H., Induced anisotropy
and time dependency in clays, Constitutive
Equations of Soils (Proc. 9th Int. Conf. Soil
Mech. Found. Eng., Spec. Session 9), Tokyo,
1977, pp.229-238.
[4] Hashiguchi, K. and Chen, Z.-P., Elastoplastic

Fig.18 Modified Cam-clay model with rotational
hardening

597

SEE - Nagoya, Japan, Nov.12-14, 2018

constitutive equations of soils with thesubloading surface and the rotational hardening,Int. J. Numer. Anal. Meth. Geomech., 22, 1998,
pp.197-227.
[5] Asaoka, A. Noda, T., Yamada, E. Kaneda, K.
and Nakano, M., An elasto-plastic descriptionof two distinct volume change mechanisms ofsoils, Soils and Foundations, 42(5), 2002,
pp.47-57.
[6] Karstunen, Minna, and Mirva Koskinen., Plastic
anisotropy of soft reconstituted clays. Canadian
Geotechnical Journal 45.3, 2008, pp 314-328.
[7] Liu, W., Shi, M., Miao, L., Xu, L., & Zhang, D.,Constitutive modeling of the destructuration andanisotropy of natural soft clay. Computers andGeotechnics, 51, 2013, pp 24-41.
[8] Duncan, J. M. and Seed, H. B., Anisotropy andstress reorientation in clay. Journal of Soil

Mechanics & Foundations Div., ASCE, Vol. No.
SM 6, 1966, pp. 81-103.
[9] Atkinson,
J.
H.,
Anisotropic
elastic
deformations in laboratory tests on undisturbed
London Clay. Geotechnique 25.2 1975, pp 357374.
[10] Hashiguchi, K., and Z‐P. Chen. Elastoplastic
constitutive equation of soils with thesubloading surface and the rotational hardening.
International journal for numerical andanalytical methods in geomechanics 22.3 1998,
pp 197-227.
[11] Graham, J., and G. T. Houlsby. Anisotropic
elasticity of natural clay. Géotechnique 33.2,
1983, pp 165-180.

598

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

FACTORS IMPACTING PRECAST UTILIZATION IN CAMBODIACONSTRUCTION

1Kaya Ting1, Phatsaphan Charnwasununth2*, Vachara Peansupap3 and Nobuyoshi Yabuki4
Faculty of Engineering, Khon Kaen University, Thailand; 2*Faculty of Engineering, Khon Kaen University,
Thailand; 3Faculty of Engineering, Chulalongkorn University, Thailand; 4Graduate School of Engineering,Osaka University, Japan

ABSTRACTPrecast construction has caught up the attention of construction practitioners since the end of World War II
and has been widely implemented in both developed and developing countries all around the world. However, it
has been noted that Cambodia has not enjoyed the benefit much from the use of precast method in construction
since it is still nascent. Hence, this research paper aims to identify the attributes having an influential impact on
precast industry and to investigate effects resulted from the demographic characteristics of precast users. Four
major processes are studied ranging from Design to Production, Transportation, and Installation. A closed-ended
questionnaire integrated with a Likert measurement scale was employed for the data collection after having
passed the reliability and validity test. The research finished with 47 respondents participated. Analytically, theresearch adopted Relative Importance Index and Analysis of Variance for data analysis based on the study’s
objectives. Consequently, top five factors in each process are found to have an influential impact on Cambodia
precast industry and three demographic characteristics are analyzed to have a significant effect on precast users
in Cambodia construction. Finally, a discussion is provided together with a suggestion for further researches.
Keywords: Cambodia construction, Demographic effects, Influential impacts, Precast implementation

capacity, the lack of sustainability approach, the lackof trained and skilled workers, the deprivation of
educational and technical course, the lack of labor
supply, the low productivity rate of local workforce,and the low workforce wage [1,5–7].
Throughout an intensive review of literatures,
precast construction method has been suggested toclose problematic gaps presenting in Cambodia
construction industry. However, the use of thismethod is still nascent, and many challenges are to
be faced upfront by the construction practitioners asa whole. Thus, this paper aims to close theknowledge gap by identifying the attributes having
an influential impact on precast industry andinvestigating effects resulted from the demographic
characteristics of precast users.

INTRODUCTION
Cambodia, one of the developing countries inSoutheast Asia, has been seeing a perpetual growthin economy with an exceeded 7 percent over the last
20 years and is transforming itself to be a lower
middle-income country. This improvement has beenbrought mainly by the contribution of several sectors
including agriculture, garment and footwear, tourism,
and construction [1].
Looking at Cambodia construction sector, there
have been many construction projects undergoingrecently that the investment in the construction hasreached beyond the country’s budget plan, totaling
at 36.4 percent of the total GDP by 2016 [1–3]. In
addition, the sector has seen an investment increaseof 22.32 percent amounting for 6.42 billion USD
with 3,052 approved construction projects on 10.74
million square meters and has contributed more than
92 million USD to the national revenue of Cambodia
by the end of 2017 [4].
However, with this surging investment trend into
construction, increasing concerns have been raised
upon how well the sector is prepared to take up thechallenges. As having been reported, it is facing thelagging of residential units’ supply, the cost andschedule overrun of projects, the large interprovincial development gap, the lack of technology
integration, the failure to lift up the income status of
the country, the failure to develop the human

LITERATURE REVIEWS
By definition, precast method is a contemporary
construction procedure where building structural andarchitectural components are casted inside highquality and environmental-controlled manufacturing
facility and transported to the construction site for
installation [8,9]. Globally, it has attracted theattention of construction practitioners due to its
benefits for all parties within the construction[10,11]. However, it also places drawbacks to theconstruction projects if it is not done in a proper
manner [12,13]. Following section lists the positive
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SEE - Nagoya, Japan, Nov.12-14, 2018

and negative reasons of using precast.

waste generated from construction activities andimprove buildability while Thailand shifted to thismethod owing to the shortage of construction laborin the industry [15,26]. In Eastern and Western
Europe, this technology caught on popularity afterWorld War II when there was a pressing andincreasing needs for immediate housing and during
the slum clearance in 1960s [8,13].

Precast Method’s Positive and Negative ReasonsBeneficially, precast construction has gained its
popularity over the last 50 years owing to its
advantages such as (F1) improving the productivity
and efficiency of the construction, (F2) saving theconstruction time, (F3) providing a high buildability,(F4) providing a high-quality control and assurance,(F5) saving the overall cost, (F6) promoting
affordability, (F7) embedding sustainability, (F8)minimizing waste, (F9) reducing carbon emissions,(F10) providing a clean construction site, (F11)
coping with labor shortage, (F12) reducing thedependency on labor, and (F13) improving theconstruction safety and health condition [8,11,13–
21].
However, these benefits also come along withthe challenges. Previous findings have mentioned 26
factors in which practitioners in different countries
have faced when precast is implemented such as(F14) design incapability, (F15) lack of government
promotion and incentives, (F16) lack of local policy
support and regulation, (F17) lack of manufacturing
capability, (F18) product quality problems, (F19)lack of standardization system, (F20) lack of skilledlabor, (F21) insufficient training and upskilling,(F22) incompetency of technology and equipment,(F23) lack of sufficient supply chain, (F24)monopoly dominance, (F25) poor coordination andcollaboration, (F26) higher initial cost, (F27) lack of
economy-of-scale production, (F28) economic risk,(F29) lack of uniform standards, guidelines, andcodes, (F30) resistance from customers andprofessionals, (F31) lack of expertise, (F32) lack ofmanagement, (F33) resistance to changes, (F34)
long lead-in time, (F35) lack of monotone
considerations, (F36) lack of standard components
manufacturer, (F37) lack of research anddevelopment, support service, and technology, (F38)lack of on-site cast yard and access, and (F39)transportation inefficiency [9,11–13,15,16,18,19,21–
24].

METHODOLOGY
Research methodology terminologically refers to
how the research is carried out in a systematic andscientific way in order to meet the objectives and tosolve the problem of the research [27–29]. Thus, thisresearch was designed using quantitative approachsince the objective was to evaluate numerically thelevel of influential impact on decision-making and toinvestigate the demographic characteristics whichplay a role in altering the method selection’s
consideration.
Data Collection Tools
In regards with the research’s data collection
tool, a closed-ended questionnaire using F1-F39
scientific-reviewed factors was distributed via an
online web survey mode, and the Likert 5-scalemeasurement was adopted [27,29]. Initially, thequestionnaire went through two critical tests whichwere validity and reliability tests. For the validity
test, 12 experienced precast practitioners with atleast 5-year working experience in Cambodia
precast industry were invited to rate the level of
relevance of the questionnaire items based on
Cambodia construction context. Analyzed using
Items of Objective Congruence (IOC) index, a list ofquestions was eliminated from the questionnaire as it
was rated as irrelevant with the IOC value of lessthan 0.5 [30,31]. Then, the questionnaire was revised
and went through the pilot test to check thereliability of the result. With this test, 30
respondents were invited to answer the questions,and upon finishing data analysis via SPSS Computer
Program, it was found out that the questionnaire
passed the test with the overall Cronbach’s Alphavalue of 0.861 which is over 0.70 as an acceptablevalue [7,32]. Thus, the questionnaire was treated as
appropriate for the mass data collection.

Adoption Approaches
Eventually, several countries have different
reasons for taking up this technology via various
approaches. For example, Malaysia brought in thistechnology to solve the growing needs for affordable
housing and housing shortage, deal with issues
related with foreign labor, and improve quality,
image and productivity of the construction industry
while China promoted this method so as to improve
the quality and productivity and to meet the urgent
demand for rapid and economically viable massproduced housing [13,25]. Looking at Hong Kong,
precast was adopted in order to reduce the amount ofSample Size and Sampling Method
Since precast industry was at an early stage ofintroduction to Cambodia construction industry,
there was no accurate information regarding thesampling frame or how many engineers were
working for precast projects in Cambodia [29,32]. In

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addition, the unit of analysis for this research was at
an engineer level due to the reason that the goal wasto study the industry prospect of precast construction
in Cambodia. Hence, the key informants were fromdesign, production, transportation, and installation
teams.
Due to the absence of the sampling frame, thisresearch study adopted non-random probability
sampling methods which were purposive andsnowball sampling methods. For the first one, thegoal was to select only the participants who had
experiences in precast works, but since precast
industry in Cambodia was still at an early stage, it
was needed to allow other engineers who had
precast knowledge to participate in this research
since their perspectives would also have an impact
on their decision. For the second one, theparticipants were asked for the networks so that the
researcher could enlarge the sample size selectively[29].

Production

Transportation

Installation

The data analysis tools of this research wereRelative Importance Index (RII) and Analysis of
Variance (ANOVA). For the first one, RII was
employed to evaluate the impact of each factor by
ranking it in ascending order [7,29,32,33]. For thesecond one, ANOVA was adopted in order toindicate the differences of participants in terms of
the responses so as to find out if the demographic
characteristics played a role in altering the decisions
making process of the practitioners in regards withprecast adoption in Cambodia construction industry[27,29,32].
RESULTS AND DISCUSSION
By the end of the data collection, a total of 47
respondents
participatedintheresearchquestionnaire. This section will show the results of
the research with an explanatory discussion of eachstudy’s objective.
Influential Impacting Attributes
Using Relative Importance Index (RII) toevaluate the influential impact of each factor which
affects the decision of the practitioners when using
precast, a total of 20 factors are presented in Table 1.
Table 1 Influential Impacting Attributes

DesignFactors

RII

Rank

F4
F11
F2

77.50%
76.25%
73.75%

1
2
3

72.50%
71.25%
90.00%
88.33%
86.67%
85.83%
85.56%
85.71%
82.86%
77.14%
74.29%
60.00%
83.33%
82.78%
81.11%
80.00%
79.44%

4
5
1
2
3
4
5
1
2
3
4
5
1
2
3
4
5

Based on the data shown in Table 1, 4 precast
processes are affected by a number of factors. To
begin with, top five factors were analyzed to have an
influential impact on the practitioners in Design
process. Firstly, the benefit that precast method canprovide a high-quality control and assurance drives
the practitioners to consider using precast for
construction projects with an influential impact of
77.50 percent. Secondly, the fact that precast cancope with the shortage of labor has been found to be
the second reason why Cambodia engineers choose
precast over the conventional method with an
influential impact of 76.25%. Thirdly, a number of
construction methods can help the practitioners tofinish the projects fast, and it is 73.75% confident
that precast method will be adopted. However, thelack of expertise has been rated as 72.50%
preventing the designers in Cambodia fromconsidering precast method while the lack of
uniform standards, guidelines, and codes has 71.25%
affected the decision makers not to use precast
method for the projects.
Looking at the data of Production process, top
five factors were notified to influence theconsideration of going for precast method. To start
with, the respondents agreed that precast can savethe overall cost and time of construction projects
with an impact of 90% and 88.33% respectively. In
addition, precast method is effective in providing aclean construction site which 86.67% influences thepractitioners to consider this method for usage. On
the contrary, the lack of government promotion andincentive and the production quality problems havehesitated Cambodia engineers from proposing
precast for projects with an influential impact of
85.83% and 85.56% each.
For the Transportation process, top five factors
have been analyzed to be influence the engineers
negatively in terms of precast adoption. That is, theAnalysis Tools

Group

F31
F29
F5
F2
F10
F15
F18
F32
F39
F35
F23
F28
F18
F2
F30
F4
F1

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SEE - Nagoya, Japan, Nov.12-14, 2018

lack of management has placed itself as the firstranked factor which 85.71% places difficulty to theprecast engineers in terms of transporting thecomponents thus dissatisfying the practitioners. In
addition, the inefficiency of transportation in
Cambodia has been considered as a barrier forprecast engineers from utilizing precast with an
influential impact of 82.86% while the lack ofmonotone consideration makes it difficult totransport the components as the panels cannot be
optimally stacked in which the impact is 77.14%.
Furthermore, the lack of sufficient supply chain does
not give the practitioners many options in terms ofdelivery assistive tools and thus 74.29% prevents the
successful transportation of precast components.
Moreover, the economic risk resulted from theinstability of precast usage in Cambodia has mademost practitioners to reconsider whenever precast
method is proposed with an influential impact of60%.
Last but not least, three driving and two
preventing factors have been founded in Installation
process. That is, the product quality problems havebeen consistently founded to happen while erecting
the components while most professionals andcustomers would be dissatisfied whenever precast
method is adopted as ranked first and third
respectively. However, the fact that precast method
can save the construction time has been affirmed byinstallers with 82.78% confidence, and it isconfirmed that precast can provide a better-quality
construction as compared to the conventional
method with 80% positive response. Finally, it has
been agreed that precast can improve theproductivity and efficiency of construction site with
79.44% influence.

Transportation

Installation

Demographic Characteristics
Using Analysis of Variance (ANOVA) toinvestigate the demographic characteristics whichcause the different responses from one respondent toanother, Table 2 lists each characteristic.

Years of
Experiences

DesignProduction
Transportation
Installation

Building
Heights

DesignProduction
Transportation
Installation

F32
F39
F39
F32
F25
F14
F22
F23
F36
F4
F8
F10
F12
F17
F18
F27
F2
F14
F25
F29
F17
F30
F33
F5
F13
F12
F1
F5
F2
F4
F8
F13
F7
F16
F21
F29
F32
F14
F17
F25
F31
F33
F35

Table 2 Affective Demographic Characteristics
Group
Academic
BackgroundType
DesignProduction

Based on the result illustrated in Table 2, there
are three demographic characteristics which affectthe response of each participant to be different. Firstof all, the academic background of each respondent
determines the choice of responses. Originally, four
academic choices were provided in the questionnairesuch as Higher Diploma, Bachelor Degree, Master
Degree, and Philosophical Doctoral Degree. As aresult, it was founded that 3 factors in Design
process, 9 factors in Production process, 7 factors inTransportation process, and 6 factors in Installation
process were significantly influenced by the

Factor
F5
F12
F14
F16
F19
F30
F25
F26
F33
F34
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SEE - Nagoya, Japan, Nov.12-14, 2018

different academic background of the respondents
who have graduated with Bachelor and Master
degree with the confidence interval of p<0.005.
Second of all, the number of years of working
experience was also confirmed to have an effect of
the respondents’ decision towards the adoption of
precast, mainly those who have the experiences fromless than 3 years to 12 years. That is, 1 factor in
Design process and 7 factors in Installation process
were founded to be significantly different in terms ofparticipants’ perception with the confidence intervalof p<0.005 while there was no significant differenceof responses in Production and Transportation
process.
Thirdly, the type of building as categorized by
the height also affects the respondents’ decision. The
questionnaire provided two choices in terms of thetype of building which were low-rise and high-risebuilding. As a result, 1 factor in Design process, 1
factor in Production process, and 18 factors in
Installation process were founded to result
differently depending on the experience of the
respondents in regards with the building type withthe confidence interval of p<0.005.

Kaen University for providing the grants to support
this research. In addition, the author would likesincerely thank the Environmental Design andInformation Technology Laboratory (Yabuki
Laboratory), Division of Sustainable Energy andEnvironmental Engineering, Graduate School ofEngineering, Osaka University, Japan for admitting
the researcher to be a special research student forstrengthening the research quality.
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CONCLUSION
Cambodia is a developing country and has been
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economy. By 2017, it has seen quite a robust
economic growth and has maintained at the rate ofexceeded 7% for 20 years. Construction sector is oneof the main role players in contributing to thisgrowth, but it has been reported as ineffective andinefficient. Thus, precast method is suggested tosolve the shortcomings in Cambodia construction
sector. However, the adoption of precast has neverbeen high since it is at an early stage of introduction,and many challenges are to face upfront. Upon
distributing the closed-ended questionnaire to anumber of respondents, two results have been foundsuch the factors which give influential impacts to thedecision making of the practitioners, and thecharacteristics of the practitioners themselves thatprevent them from using precast for construction
projects. In addition, each process is studied to havebeen affected by a number of factors. Further studies
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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DEVELOPMENT OF INTEGRATED SATELLITE-BASED DROUGHT
MODEL IN THAILAND USING MULTIPLE LINEAR REGRESSION
1Mongkol Raksapatcharawong and 2Watcharee Veerakachen

1,2Chulabhorn Satellite Receiving Station, Faculty of Engineering, Kasetsart University,

Thailand
ABSTRACT
Drought, due to climate change, has recently become more severe. Capability to monitor drought condition
and to assess drought risk is essential to a development of effective drought adaptation plan, especially for anagricultural country like Thailand. Current drought monitoring is provided by separate indices such as
Standardized Precipitation Index (SPI), Soil Moisture Index (SMI) and Moisture Available Index (MAI),
calculated from weather station datasets which are not easily comprehensible to users. This research develops acountrywide integrated satellite-based drought model consisting of three parameters: accumulated estimate rainfall
product from FY-2E satellite data, difference Land Surface Temperature (LST) and Normalized Difference
Vegetation Index (NDVI) products from MODIS. A simple drought hazard is introduced as multiple linear
regression model (R2=0.795) of these satellite products, calibrated with daily soil moisture measurement in 2015.
Consequently, drought conditions are represented by Drought Hazard Index (DHI) by assigning integer values,
from –3 (extremely drought) to +3 (extremely wet), according to the defined thresholds (presently at 0.05, 0.15,
0.30, 0.70, 0.80, and 0.95) of the cumulative distribution function (CDF) of drought hazard values. The model isvalidated with 426 countrywide drought situations announced by the Department of Disaster Prevention and
Mitigation (DDPM), during drought season 2016, yielding 0.96 probability of detection.
Since the model outputs are in georeferenced raster format, they can be processed with other relevant GIS datasuch as land use and irrigation to generate advanced thematic mapping called drought risk map. This map canbenefit not only policy makers but also farmers themselves.
Keywords: Drought Model, FY-2E, GIS, MODIS, Multiple Linear Regression

Therefore, practical drought monitoring and risk
assessment are essential to developing an effective
drought early warning and adaptation plan in which
potential victims are able to get involved leading to aproactive and effective drought management which
can actually reduce damaging impacts.
Traditional drought monitoring uses several
indices such as Standardized Precipitation Index(SPI), Soil Moisture Index (SMI) and Moisture
Available Index (MAI) each represents various
aspects of drought and has been widely used. The SPI
presents a rainfall anomaly as a normalized variableby probabilistically comparing accumulated rainfall
over a time period with historical rainfall period. The
SMI indicates soil water content and the MAI
determines the influence of water adequacy on yields.
However, the indices calculated from meteorologicalobservations are point-based and insufficient tomonitor drought at regional scale [6]. Consequently,
remote sensed satellite data has become a valuable
tool and taken significant role in drought monitoring
due to its grid-based feature providing spatial
information on drought even at global scale. Satellitebased data also has advantage comparing to groundbased observation in that consistent data records andproducts can be utilized in developing advanced
drought monitoring with multiple data sources.

INTRODUCTION
Drought is a major recurring natural disaster thatposes a concern in water and food security [1],environmental problems as well as economic risks,
especially for agricultural sector. Based on its impact,
droughts are classified into four types and usuallyoccur in a particular order which is meteorologicaldrought, agricultural drought, hydrological drought
and socioeconomic drought. Meteorological drought
caused by deficit in precipitation which subsequently
impacts on soil water content leading to agricultural
drought that resulting in plant water stress andreducing biomass and yield. Due to low recharge
from the soil to water features, hydrological drought
occurs when streamflow, reservoir storage andgroundwater level are in shortage. Eventually,socioeconomic drought will take place if thephenomena prolongs until water demand increased
and water stress intensified by human activities [2],[3], [4].
Drought monitoring and early warning are crucialcomponents for mitigation and adaptation plans [4].
Drought management typically responses to crisis
after impacts have occurred. Moreover, drought relief
providing to those affected decreases socioeconomic
capabilities in adaptation to drought disaster [5].
605SEE - Nagoya, Japan, Nov.12-14, 2018

Various satellite based drought indices have beendeveloped to monitor drought and can be categorized
into three perspectives. The first one provides
precipitation information which SPI is the mostwidely used. The computation requires satellite data
retrieval from Infrared (IR) sensors of Geostationary(GEO) satellite offering higher temporal resolution
and passive microwave (PWM) sensors of Low Earth
Orbit (LEO) satellite technically providing moreaccurate rainfall estimate. Several satellite-based
precipitation products are now available including
Precipitation Estimation from Remotely Sensed
Information using Artificial Neural Networks(PERSIANN) [7], Tropical Rainfall Measuring
Mission (TRMM) [8], CPC Morphing Technique(CMORPH) [9] and Global Satellite Mapping ofPrecipitation (GSMaP) [10]. However, these products
have relative short length of record which imposes alimitation in SPI calculation.
Another category of satellite-based indices are
based on Land Surface Temperature (LST) which
relate to soil water content, such as Temperature
Condition Index (TCI) and Normalized Difference
Temperature Index (NDTI) [11],[12]. The Last
category assess drought based on observed changes invegetation condition with indices typically derived
from the Normalized Difference Vegetation Index(NDVI) such as the Transformed Vegetation Index(TVI), the Standardized Vegetation Index (SVI), andthe Vegetation Condition Index (VCI) [13], [14], [15].
The combination of LST and NDVI has been
investigated in several works to provide more robust
characterization of drought phenomenon [16]. LSTNDVI based indices, such as Temperature Vegetation
Dryness Index (TVDI) and Vegetation Temperature
Condition Index, (VTCI) have been applied overdifferent landscapes with varying degrees of success[6], [17], [18] .
This work introduces a simple satellite-based
drought hazard index that combining all drought
related aspects including rainfall, soil moisture andvegetation health. The model inputs are derived fromsatellite products. Drought hazard values obtained
from the model were collected to generate aprobabilistic function. The function was defined toindicate levels of drought hazard index that can beshown on a map for easy interpretation.

The Study Region
Thailand is located in Southeast Asia on a latitude
of 5o N to 21o N and a longitude of 97o E to 106o E.
Climatologically, the country is classified as tropicalmonsoon and tropical savanna with 18-34o C averagetemperature and over 1,500 mm. average rainfall.
Drought season is ranging from November to January(winter) and February to April (summer). The study
region covers whole area of the country.
Satellite Datasets
Satellite images were received from Chulabhorn
Satellite Receiving Station (CSRS). The FY-2E data
is hourly received through DVB-S system while the
Terra/Aqua MODIS data is received from MODIS
direct broadcast receiving station at CSRS. There aretotally 100*1600 pixels for each image, covering
Thailand territory, at 1 km/pixel spatial resolution.
FY-2E Dekadal rain estimate
Satellite data received through DVB-S system isin a .VSR file format. Upon received, these data is
automatically transformed, using Equal-Lat-Longprojection, to numerical data (16-bit PNG). Only data
point within the country region is retrieved and stored
as a zip file every hour. Hourly satellite rain estimate
is calculated from IR1 data using Infrared Threshold
Rainfall with Probability Matching (ITRPM) model[19]. The model was adjusted to provide dekadal
rainfall by calibrating the satellite rain estimatesaccumulated in 10 days with co-located rain gauges
accumulated rainfall from http://www.thaiwater.net/
using dataset in 2016. Figure 1 shows an example ofthe dekadal rain estimate based on ITRPM model.

METHODOLOY
Satellite-based drought hazard model consists ofthree dekadal (10 days) satellite data products which
are accumulated rain estimate, difference LST, and
NDVI values. The relationship between these input
parameters and the drought hazard was investigatedusing multi-linear regression approach. Ground based
and reference datasets were collected to be used formodel calibration and comparison analysis.

Fig. 1

Example of FY-2E dekadal rain estimate.

MODIS different Land Surface Temperature
Land Surface Temperature (LST), MODIS level2 product with 1 km spatial resolution, is retrieve
twice a day at day– and night–time. The difference
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between day and night LST values relates to watercontent in the soil and therefore can indicate drought
condition. Figure 2 (left) shows an example of
MODIS LST product. Both day and night LST data
are filtered by cloud mask product. Every 10 days, themaximum values of day and night LST are selected.
This method is adopted from Maximum Value
Composite (MVC) technique which widely accepted
to improve analysis and reduce error resulting fromenvironment and atmosphere [20], [21]. The
difference between LST day and night called deltaTis then computed every 10 days becoming a dekadaldeltaT to be used as input parameter of droughthazard model.

Drought Hazard ModelIn this work, drought hazard is defined as acomposite drought assessment capturing three
indicators that are not fully correlated with each otherincluding dekadal rain estimate from FY-2E satellite,
deltaT and NDVI from MODIS sensors. These
dataset were used as input parameters of droughthazard model. Daily soil moisture in-situ
measurements collected throughout 2016 wereobtained from the University of Phayao experimental
site. Ten days-averaged soil moisture was used astarget for drought hazard model development bymeans of multiple linear regression approach yielding
R2 = 0.795. Figure 4 shows the structure of droughthazard model development. The drought hazard
model becomes
𝐷𝐻 = 11.643 + 0.356 ∗ 𝑅 − 0.297 ∗ 𝑑𝑒𝑙𝑡𝑎𝑇 +6.868 ∗ 𝑁𝐷𝑉𝐼
(1)
where 𝑅 is the FY-2E dekadal rain estimate, 𝑑𝑒𝑙𝑡𝑎𝑇is the decadal difference LST and 𝑁𝐷𝑉𝐼 is the
dekadal NDVI, both from MODIS. The lower the DH
implies worse drought condition. This model works
well during dry season. However, in rainy season,
MODIS satellite data may not be available due tothick clouds. In this case, the drought hazard model issimplified as

Fig. 2

Example of MODIS products (left) LST(right) NDVI.

𝐷𝐻 = 12.445 + 0.135 ∗ 𝑅(2)Since this model using only dekadal estimated rainfall,
the output of multiple linear regression yields R2 =0.371.

MODIS Normalized Difference Vegetation Index
Normalized Difference Vegetation Index (NDVI)
is also a level-2 MODIS product representing thewellness of vegetation. Figure 2 (right) shows anexample of MODIS NDVI product. The NDVI is also
processed by cloud masking and MVC technique, as
shown in Fig. 3, to compute dekadal NDVI to be usedas the last input parameter of drought hazard model.

Terra/Aqua MODIS data

NDVI
(10 days)Rain(10 days)deltaT(10 days)
Input

Gauge
accumulated
rainfallFY-2E IR1 data

In-situ soil
moisturemeasurement

Soil moisture(10 days)

Input

Multiple linear regression

TargetOutputTerra/Aqua MODIS data

Drought hazard

Drought hazard
index

Cloud mask

Fig. 4

Maximum value composite (MVC)(10 days)
LST_day(10 days)

NDVI(10 days)Fig. 3Drought Hazard Index
The cumulative distribution function (CDF) of
drought hazard is generated using sample values
computed from satellite datasets obtained in 2016.
The CDF is grouped into seven threshold levels(presently at 0.05, 0.15, 0.30, 0.70, 0.80, and 0.95) todefine the drought hazard index (DHI) which isrepresented by integer values ranging from –3

LST_night(10 days)+

Development of drought hazard model.

-deltaT(10 days)

Processing of dekadal NDVI and deltaT.
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(extremely drought) to +3 (extremely wet). The
thresholds corresponding to each DHI values areshown in Table 1. Drought hazard values are mappedto each DHI, representing severity of drought
condition, based on the drought hazard CDF as shownin Fig. 5.

announced by the Department of Disaster Prevention
and Mitigation, Ministry of Interior.
Comparison with Agrometeorological reports
Result validation was qualitatively performed bycomparison the drought hazard map with the TMD
agrometeorological reports in accordance to drought
event news. All TMD reports are calculated fromgauge station measurements and displayed in portable
document format (pdf) on TMD website. A severe
drought event was posted in the news at the beginningof January 2016 when there was drought crisis, withextremely low water level, at the Bhumibol andChaophraya dams located in the central part ofThailand. This event is clearly seen in the droughthazard map, Fig. 6 (a), showing severe to extreme
drought in central part of Thailand. This is confirmedby the accumulated rainfall, Fig. 6 (b), which exhibits
light rainfall in the area.

Table 1 Thresholds for Drought Hazard Index
Drought Hazard

Percentile

Less than
9.083156732[9.083156732 ,12.23415100)[12.23415100 ,12.97706809)[12.97706809 ,
19.66813821)[19.66813821 ,23.56635047)[23.56635047 ,29.14464206)
More than
29.14464206

0– 5Fig. 5

5 – 1515 – 30
30 – 70
70 – 85
85 – 95
95 – 100

Drought Hazard
index-3
Extremedrought-2
Severedrought-1Moderatedrought
0
Near
Normal1Moderatewet
2
Severewet
3Extreme
wet

(a)

(b)

(c)

(d)

Mapping between Drought Hazard CDF
thresholds and DHI.

RESULTS AND DISCUSSIONS
To generate drought hazard map every 10 days,
DHI for each pixel is calculated from drought hazard
model mapping with the CDF threshold. The droughthazard map is in georeferenced raster format and canbe displayed in geographic information system (GIS)
at 1 km spatial resolution. The results are qualitatively
validated by the news about drought events and byagrometeorological reports from TMD (accumulated
rainfall, MAI, and SMI). Quantitative validation of
the model is performed based on the probability ofdetection (POD) for drought events that are officiallyFig. 6Comparison of (a) drought hazard map, (b)accumulated rainfall, (c) moisture available
index (MAI), and (d) soil moisture index(SMI) maps, during January 110, 2016.

Note that there are inconsistencies among TMD
indices. For example, MAI map in Fig. 6 (c) indicates
extreme drought almost throughout Thailand whereas
accumulated rainfall map shows fair amount of608

SEE - Nagoya, Japan, Nov.12-14, 2018

rainfall in the Southern part. However, the droughthazard map shows near normal to moderate drought
conditions in that area which is consistent with bothaccumulated rainfall and SMI maps, in Fig. 6 (a) and(d). Another example is the report for the Eastern partthat shows slightly less than normal rainfall withmoderate drought in the MAI map but severe droughtin the SMI map. All this information was correctly
accounted in the drought hazard map with normal tomoderate drought in the Eastern area. Evidently, thedrought hazard map is useful in monitoring drought
condition coping with all three aspects including
rainfall, vegetation and soil condition. More
importantly, it is much easier to interpret and be
understandable to people in the area prone to drought
risk, thus effectively supporting the proactive droughtmanagement.

CONCLUSIONS
A new drought hazard index, integrating FY-2E
and Terra/Aqua satellite data, is proposed for droughtmonitoring. Multiple linear regression is applied todevelop drought hazard model with input parameters
including accumulated rainfall estimate from FY-2E
GEO-satellite retrieval and different LST and NDVI
derived from Terra/Aqua MODIS data. The model
input parameters represents precipitation information,soil water content and vegetation health respectively.
Drought hazard can be calculated every 10 days at 1km spatial resolution. The CDF of drought hazard
was then generated and used to assign drought hazard
index (DHI) by thresholding method. The results
were qualitatively validated with drought crisis news.
In comparison with the TMD agrometeorologicalreports, it is shown that drought hazard index is a
useful tool for drought monitoring in that it integrates
all three drought aspects into one easy-to-understandindex with consistent interpretation. Quantitatively,
the results were validated against DDPM drought
situation announcement with POD equals to 0.96,
higher than that of MAI. The drought hazard map is
automatically generated, published, distributed, andupdated in GIS format, every 10 days, at website
http://csrs.ku.ac.th/wegis/Product/KURDI. This isbeneficial to both government and farmer leading toproactive drought management.

Probability of Detection (POD) Analysis
During the dry season (January to April) of 2016,
the Department of Disaster Prevention and Mitigation(DDPM) had announced 426 drought situations
countrywide. Based on this information, theprobability of detection (POD) of drought hazard for
drought event is calculated. Since the drought
situation announcement is at the district level, the
DHI values (with 1-km resolution) at the time ofannouncement were averaged over the district area.
For each announcement, a hit event occurs if theaverage DHI is less than 0.5. The probability ofdetection is computed by
𝑃𝑂𝐷 =total number of hit events

ACKNOWLEDGEMENTS
This work is supported by Kasetsart University
Research and Development Institute (KURDI) under
the project “A Development of Drought Risk
Analysis Platform using Multiple Satellite Sensors”
and by Japan International Cooperation Agency(JICA) under the project “Advancing Co-Design ofIntegrated Strategies with Adaptation to Climate
Change in Thailand (ADAP-T)”.

(3)

total number of drought annoucement

The result was compared with the POD computedfrom the TMD report on MAI and SMI. The thresholdfor declaring drought by the MAI and SMI is 2.5.
Based on the level of MAI (0  4) and SMI (0  3),
the average value over the district area was computed.
If this value is less than 2.5, the hit event occurs. The
results are shown in Table 2. The POD of DHI is 0.96
which is higher than the POD of MAI (0.91) but lessthan that of SMI (1.00).

REFERENCES[1] AghaKouchak A., Farahmand A., Melton F.,
Teixeira J., Anderson M., Wardlow B., and Hain
C., Remote sensing of drought: Progress,
challenges and opportunities. NASA Publications,
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Y. C., Rowland J., and Verdin J. P., Drought

Table 2 The probability of detection for droughthazard index (DHI), Moisture available
index (MAI), and Soil moisture index (SMI).
Drought hit
Thresholds
DHI <  0.5
MAI < 2.5
SMI < 2.5

Number of hit
events
411
388
426

POD
0.96
0.91
1.00

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SEE - Nagoya, Japan, Nov.12-14, 2018

Monitoring and Assessment: Remote Sensing
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Mapping global patterns of drought risk: An
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Global Environmental Change, vol. 39, pp. 108124, 2016.
[6] Li X., Wang Y., Tang S., and Shen S., NDVILST Feature Space Based Drought Monitoring
using MERSI Data in Hunan Province of China.
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[7] Sorooshian S., Hsu K., Gao X., Gupta H., ImamB., and Braithwaite D., Evaluation of the
PERSIANN system satellite‐based estimates oftropical rainfall. Bulletin of the American
Meteorological Society, vol. 81, no. 9, p. 2035–
2046, 2000.
[8] Huffman G. J., Bolvin D. T., Nelkin E. J., and
Wolff D. B., The TRMM Multisatellite
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Multiyear, Combined-Sensor Precipitation
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[10] Kubota T., Shige S., Hashizume H., Aonashi K.,
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N., Nakagawa K., Iwanami K., Ushio T., Kachi
M., and Okamoto K., Global Precipitation Map
using Satelliteborne Microwave Radiometers by
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[12] Mc Vicar P.N. and Bierwirth R., Rapidly
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[13] Tucker C., Red and photographic infrared linear
combinations for monitoring vegetation. remotesensing of environment, vol. 8, no. 2, pp. 127150, 1979.
[14] Park J.S., Kim, K.T. and Choi, Y.S., Applicationof vegetation condition index and standardized
vegetation index for assessment of spring
drought in South Korea. Geoscience and Remote
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[15] Kogan F. and Sullivan J., Development of global
drought-watch system using NOAA/AVHRR
data. Advances in Space Research, vol. 13, no. 5,
pp. 219-222, 1993.
[16] Karnifli A., Agam N., Pinker T. R., Anderson M.,
Imhoff M.L., Gutman G.G., Panov N. andGoldberg A., Use of NDVI and land surface
temperature for drought assessment: Merits andLimitations. Journal of Climate, vol. 23, pp. 618633, 2010.
[17] Senay G B., Velpuri N M., Bohms S., Gudde M.,
Young C., Rowland J., and Verdin J. P., A
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Sensing of Environment, vol. 79, no. 2-3, pp.
213-224, 2002.
[18] Wang P.X., Wan Z.M., and Gong J.Y., Advances
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527-533, 2003.
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[20] Holben B., Characteristics of maximum-value
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[21] Liu H., Zhang A., Jiang T., Lu H., Liu X., andWang H., The Spatiotemporal Variation ofDroughtintheBeijing-Tianjin-Hebei
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Modified TVDI. Sustainability, vol. 8, pp. 1-15,
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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

COMPARATIVE ANALYSIS AND DESIGN OF TRANSVERSE BOX
GIRDER BRIDGE BETWEEN STAAD.PRO AND MIDAS CIVIL
SOFTWARES
Muhammad Naim Abdul Halim1,2, Anizahyati Alisibramulisi1,3, Mohammad Noor Abu Hassan4, Ahmad
Ramlan Abu Talib4, Noor Rita Ismail2, and Norliyati Mohd Amin1
1
Faculty of Civil Engineering, Universiti Teknologi MARA (UiTM), 40450, Selangor, Malaysia
2
Khairi Consult Sdn Bhd, 68100, Selangor, Malaysia
3
Institute for Infrastructure Engineering and Sustainable Management (IIESM), UiTM, 40450, Selangor,
Malaysia
4
Perunding ZAR Sdn Bhd, Civil & Structural Consulting Engineers, 40675, Selangor, Malaysia
ABSTRACTIn Malaysia, STAAD.Pro and MIDAS Civil software are commonly used by bridge engineer for the analysis
and design of bridge structure. MIDAS software which has an auto modeling generator is preferable by the users
as compared to STAAD.Pro software. However, STAAD.Pro software is much more user friendly. Therefore, inthis paper, a comparison study was carried out by modeling box girder bridge using STAAD.Pro and MIDAS.
The similarities, differences and limitations from these two software were investigated. Comparison of the
STAAD.Pro and MIDAS software showed that the result of analysis from this two software have significant
differences in live load cases as compared to permanent load cases. Whereas, for the design results, thereinforcement used was similar for cantilever part of the slab but different for other parts of the box girder segmentin which MIDAS Civil requires more reinforcement. The deviation of results between STAAD.Pro and MIDAS
software were most probably due to the fact that, both software have different configuration of wheel load on thebridge deck. Nevertheless, both software are recommended to be used in the analysis and design of box girder
bridge, as both software have proven to be effective as Computer Aided tools. Thus, any choices of software
depend on the needs and what to be solved. It is also evident from the results that there is a lack of establishedguidelines for modelling and verification. Such guidelines would simplify the work for engineers and set thefoundation for common working procedures within the industry.
Keywords: Transverse analysis, Transverse design, Box girder bridge, STAAD.Pro software, MIDAS Civil software

could analyse and design according to the requirementof code of practice, it is necessary to do an analysis ofresult comparison for the different software.

INTRODUCTION
In the modern bridge construction, Box Girder
Bridge is a significant type of bridge which has
capability of longer span and spiral or curved roadalignment. A safe bridge design requires a satisfied
input by engineers during site investigation, planning,
analysis and design. Besides that, an economic designis also desired for designing any structure without
neglecting the worst case of loading effect. The worst
case of loading effect was encouraged to be designed
for higher factor of safety value to avoid the failure ofstructure to occur. Therefore, box girder bridge which
has complex structural behaviour is needed to bemodelled accordingly in the software to give
appropriate result in both analysis and design.

In this paper, the main objective is to compare theanalysis and design of box girder bridge using
STAAD.Pro and MIDAS Civil software. This study
focuses only on the single component of Box Girder
Bridge which is the top slab where the analysis anddesign is only on transverse element. Furthermore, one
typical section has been used for the design stage. The
bridge configurations consisted of three (3) span
lengths of 95m, 160m and 95m respectively. The samebridge configuration was modelled in different
software for analysis and design. British Standard [1]and Design Manual for Roads and Bridges [2] wereused as a code of practice in this study together with
Design Verification of Balanced Cantilever Bridge asper BS Code [3]. Whereas, STAAD.Pro Reference
Manual [4] and MIDAS Reference Manual [5] wereused as guidance for the modelling part. The results ofmaximum moment and shear force obtained werecompared between the two software and the analysed
results were further used in the design stage.

Due to the rapid development of computational
methods, different program and analysis methods arebeing used nowadays. To name a few; STAAD.Pro,
MIDAS Civil, SAP2000 and LUSAS are the common
software used in Malaysia for bridge analysis anddesign. However, MIDAS Civil is much preferredamong bridge engineers for analysing box girder
bridge as compared to STAAD.Pro, eventhough it is
not fully utilized. Every software has its own
limitations in modelling and analysing the structures.
Hence, for any project, the result of analysis and designusing different software may not be consistent. In orderto determine the most appropriate software which

METHODOLOGY
Before the element was modelled using finite
element program, the element geometry must be
identified. For this study, the transverse model was

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Figure 2 and Figure 3 illustrate the section
properties defined in STAAD.Pro and MIDAS Civil
respectively.

performed for one segment only which is located at the
mid-span of the bridge. The geometry of the segment
is shown in Fig. 1.

Fig. 1: Geometry of the Box Girder Segment
Fig. 2: Section dialog box in STAAD.Pro

Structural Modelling and Analysis
General procedure to model the box girder bridgeis the same for both STAAD.Pro and MIDAS Civil
software. Both modeling started with assigningworking environment, defining section and material
properties, creating geometry of the model, assigning
section and material properties, defining and assigning
loading, and finally performing the analysis.
Working Environment
To perform structural modeling, the unit system are
set as kilo Newton (kN) and meter (m) for basic unit offorce and length respectively.
Material and Section Properties
The concrete properties adopted in the analysis anddesign of the segment are tabulated in Table 1. The
values in the Table are based on BS 5400-4:1990.

Fig. 3: Section dialog box in MIDAS Civil
Creating Geometry Model
Geometry modelling comprises combination ofnodes, beams, and plates element. For STAADPro,first node was assigned as coordinate (0,0,0) in X, Y,
and Z direction respectively. The nodes assignment are
based on the conceptual idea of elements. To complete
the structural element, nodes need to be connected byusing beam assignment. The geometric arching fromhaunches was considered in this model asrecommended by Abdullah Zaid [6]. Then, thematerials and section properties are assigned
accordingly to their respective members. The
completed STAADPro’s geometry model is shown in
Fig. 4.

Table 1: Concrete Properties
Cube Strength of Concrete
60 N/mm2
Modulus of Elasticity of
36 kN/mm2
Concrete
Poisson’s Ratio
0.2
Coefficient of Thermal
12 x 10-6/ oC
Expansion
Density
25 kN/m3
For the reinforcement properties, high yield
deformed type with yield strength value of 500 N/mm2
was used. As stated in BS 5400-4:1990, nominal coverrequirement and crack width limit for precast
superstructure external and internal faces of 30 mm and0.25 mm shall be used respectively.
The section properties of each beam are definedmanually as Tapered Section in STAAD.Pro. While in
MIDAS Civil, FCM Bridge Wizard was used for
defining the section. However, in order to use thiswizard, the section at both mid-span and support need
to be defined.

Fig. 4: 3D view of the model in STAAD.Pro

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In MIDAS, the geometry of model was definedusing Bridge Wizard Modelling. Firstly, thelongitudinal model must be defined in order for the
Bridge Wizard to automatically generate the transverse
model. The material properties and geometry were
specified in the model tab of Bridge Wizard, see Fig.
5. After completing longitudinal model, the transverse
model was generated using transverse model wizard bydefining the element’s number at the mid-span asshown in Fig. 6. The completed MIDAS’s geometry
model is shown in Fig. 7.

Design Loadings
For this study, the transverse model was loadedwith normal permanent load as uniformly distributedload to represent all self weight and superimposed deadload which represent 100 mm thick Asphaltic Concrete
Wearing Course with 22 kN/m3 density. For live trafficload, single axle of 45 unit of HB was applied on theslab from edge of parapet to another as inline moving
load of four (4) wheel load of 112.5 kN each.
In STAAD.Pro, the run load generator was used togenerate traffic loads. Vehicle load of HB45 with 1m
wheels spacing was defined as shown in Fig. 8.

Fig. 8: Input dialog for generating trafficloads in STAAD.Pro
In MIDAS, Moving Load Analysis feature wasused in generating traffic load on the bridge deck. It is
automatically done in finding the maximum andminimum cases by applying a unit load along thedefined traffic lanes. Figure 9 shows the input dialog
for defining the traffic load in MIDAS Civil.

Fig. 5: Model tab of Bridge Wizard in MidasFig. 6: Transverse model input in MidasFig. 7: 3D view of (a) Longitudinal modelTransverse modelFig. 9: Input dialog for generating trafficloads in MIDAS Civil

(b)

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According to Design Manual for Roads andBridges, BD 37/01, the analysis and design for deck
component of bridge shall satisfy the Serviceability
Limit State (SLS) and Ultimate Limit State (ULS)
under the following load combination: Partial loadfactor under SLS γfl for Dead Load, SIDL and 45 HB
are 1.00, 1.20 and 1.00 respectively, whereas Partial
load factor under ULS γfl for Dead Load, SIDL and 45
HB are 1.20, 1.75 and 1.30 respectively. Note that, allpartial load factor under ULS γfl to be multiplied by
γf3 1.10.

zfcu

is the lever arm �1 −

1.1𝑓𝑓𝑦𝑦 𝐴𝐴𝑠𝑠
𝑓𝑓𝑐𝑐𝑐𝑐 𝑏𝑏𝑏𝑏

� 𝑑𝑑 ;

is the characteristic strength of the concrete.

According to BS5400 Part 4, shear stress, v at any
cross section in solid slab is calculated from Eqn. 3

Where

Perform Analysis
According to Theryo [7], stresses at five (5) points
on bridge deck should be checked. However, in thisstudy, bending moment and shear force from the modelare extracted at three (3) specific points on the deck
section as shown in Fig. 10.

𝑣𝑣 =

𝑉𝑉

(3)

𝑏𝑏𝑏𝑏

V

is the shear force due to ultimate loads;bis the width of slab under consideration;dis the effective
reinforcement.

depth

to

tensionNo shear reinforcement is required when the stress, v,
is less than ξsvc×2d/av, but should not exceed
0.75(fcu)0.5 or 4.75 N/mm2, whichever is lesser.
(4)𝜉𝜉𝑠𝑠 = (500⁄𝑑𝑑 )1/4

The crack model for load effects to BS 5400 is anempirical model and it considers the effect of cover,reinforcement diameter, spacing and stress of thereinforcement. To ensure the structure remains in theelastic phase under loading, BS 5400 set the maximum
limits for stresses in the reinforcement and concrete.
The maximum surface crack width, w, for flexural iscalculated in BS 5400 using the following formula:
𝑤𝑤 =Fig. 10: Three (3) specific analysis point on thebridge deck3𝑎𝑎𝑐𝑐𝑐𝑐 𝜀𝜀𝑚𝑚(5)𝑎𝑎𝑐𝑐𝑐𝑐 − 𝑐𝑐𝑚𝑚𝑚𝑚𝑛𝑛
�
ℎ−𝑥𝑥

1+2�

The maximum crack width for tension is
calculated from the following expression:

Deck Slab Design
From the transverse model, the worst case oftransverse bending moment and shear force values
obtained from each load type being applied to the deck
were summarised and then adopted in the design. In
general, the design of reinforced concrete member iscontrolled by the ultimate limit state, whereas thelimitation on crack width is controlled by theserviceability limit state.

w = 3acr εm

(6)

where

According to BS5400 Part 4, for the slab section
which is without compression reinforcement, theultimate moment resistance shall be taken as the lesserof the values obtained from Eqn. 1 and Eqn. 2.

acr

is the distance from point (crack) considered
to the surface of the nearest bar which
controls the crack width;

cmin

is the required nominal cover to the outermost
reinforcement given;xis the depth of the concrete in compression (ifx = 0 the crack width should be calculatedusing Eqn. 6)

Mu = (0.87 fy ) Asz(1)his the overall depth of the section;

Mu = 0.15 fcu b d

(2)

εm

is the calculated strain at the level where
cracking is being considered, allowing for the
stiffening effect of the concrete in the tension
zone; a negative value of εm should beobtained from equation:

Where
Mu

is the ultimate resistance moment;As

is the area of tension reinforcement;bis the width of section;dis the effective depth to the tension
reinforcement;fy

is the characteristic
reinforcement;

strengthof

𝜀𝜀𝑚𝑚 = 𝜀𝜀1 − �

3.8 𝑏𝑏𝑡𝑡 ℎ�𝑎𝑎′ −𝑥𝑥�𝜀𝜀𝑠𝑠 𝐴𝐴𝑠𝑠 (ℎ−𝑥𝑥)� ��1 −

But not greater than ε1

the

614

𝑀𝑀𝑞𝑞

𝑀𝑀𝑔𝑔

� 10−9 �(7)SEE - Nagoya, Japan, Nov.12-14, 2018

Based on the summarized results in Table 3 andTable 4, the values of bending moments for cut section
A of its permanent load cases and shear force values
show only small differences between the two software
as compared to live load cases. But not for cut section
B and C, in which the value of shear force at section C
result from MIDAS Civil software is more than doubleof STAAD.Pro software. For the maximum case of
bending moments, STAAD.Pro analysis shows 26%
higher than MIDAS model at the center of web whileat the center of slab, MIDAS analysis shows 95.5%
higher than STAAD.Pro analysis. For the minimum
bending moment diagram, at center of web,
STAAD.Pro shows 26.5% higher than MIDAS Civil
which is same as case of maximum bending moment.
At cutting section B, Midas shows 129.6% higher
compared to STAAD.Pro. However, there is no
significant difference value at the mid span of slab
presented between this two software. The deviation of
results between STAAD.Pro and MIDAS software
were most probably due to the fact that, both software
has different configuration of wheel load on the bridgedeck. Figure 12 and Figure 13 shows the location ofwheels on the deck for maximum effect at section A
and B from STAAD.Pro and MIDAS Civil software
respectively.

RESULTS AND DISCUSSION
Transverse Analysis
The transverse analysis results obtained from both
STAAD.Pro and MIDAS software were summarizedin Table 2 and Table 3 and illustrated in Fig. 11.
Table 2: STAAD.Pro summary of beam end force
Structural
Element

Cut
SectionCantileverA

B
T op SlabC

Max. Moment

ULS
Envelope
985.835

Min. Moment-184.384

41.720-185.904

Max. Shear

545.650--

Max. Moment306.21015.386219.574

Min. Moment-100.581

15.385-93.341

Max. Shear

343.822--Max. Moment

85.571

3.015

63.117

Min. Moment-201.613

3.015-157.794

Max. Shear

134.854

-

-

Cases

SLS
Permanent Live Load74.226681.029*Moment (kNm) and Shear (kN)

Table 3: MIDAS Civil summary of beam end force
Structural
Element

Cut
SectionCantileverA

B
T op Slab
C

Cases

ULS
Envelope

SLS
Permanent Live Load

Max. Moment822.270

74.790554.653

Min. Moment-133.790

41.690-147.004

Max. Shear

545.500--

Max. Moment

320.040

17.480228.030-128.436

Min. Moment-156.600

17.480Max. Shear

362.920--

Max. Moment

172.600

6.630

114.257

Min. Moment-198.580

6.630-159.203

Max. Shear

297.400--*Moment (kNm) and Shear (kN)

Fig. 12: Location of wheels load on the deck
generated by STAAD.Pro software(a)Fig. 13: Location of wheels load on the deck
generated by MIDAS Civil software
As shown in Fig. 12 and Fig.13, the wheels locationof STAAD.Pro are able to run until the edge of slab
while in MIDAS Civil, it was restricted from running
until the edge of the slab. In the actual condition, theparapet was positioned at the edge of the parapet
whereby the wheel was restricted to run across it. Thisis due to the limitation of STAAD.Pro where in the runload generator input, only the starting point and(b)
Fig. 11: (a)Maximum bending moment diagramand (b) Maximum shear force diagram for envelope
live load case from STAAD.Pro and MIDAS Civil
software615

SEE - Nagoya, Japan, Nov.12-14, 2018

increment of distance were defined. While in MIDAS
Civil, the influence line of wheels load was determinedby the location of carriageway in which it was defined
during the input of barrier and pavement parameter.

developed more worst load case for live load intransverse analysis between the two software. The
deviation of results between STAAD.Pro and MIDAS
software were most probably due to the fact that, both
software have different configuration of wheel load on
the bridge deck. Nevertheless, both software arerecommended to be used in the analysis and design ofbox girder bridge, as both software have proven to beeffective as Computer Aided tools. Thus, it can beconcluded that, the choices of software depend on theneeds and what to be solved. As long as no errors in
the evaluation of the response, other parameters are
more important than the accuracy in the model,
namely; user friendliness, verification andinterpretation of results. It is also evident from theresults, that there is a lack of established guidelines formodelling and verification. Such guidelines would
simplify the work for engineers when establishing
structural analysis models and set the foundation forcommon working procedures within the bridge
engineering industry.

Transverse Design
The design results of transverse reinforcements(ULS) and crack width (SLS) were tabulated in Table
4 and Table 5.
Table 4: Area of reinforcement required based on
analysis from STAADPro software

Table 5: Area of reinforcement required based on
analysis from MIDAS software

ACKNOWLEDGMENT
The authors would like to acknowledge the financial
support for this work from Universiti Teknologi
MARA (UiTM) as well as the industrial supports from
Khairi Consult Sdn Bhd and Perunding ZAR Sdn Bhd.
The provided facilities, discussion and assistanceduring the modelling were gratefully appreciated.

Top reinforcement required for cantilever part ofbridge deck is similar for both envelope cases fromSTAAD.Pro and MIDAS software. However, thebottom reinforcement for that structural element
required by MIDAS Civil is lesser. This is due tomoment of live loads cases from MIDAS is smaller andthus, affect the crack width design. For both
reinforcement design at section B and C, shows thatanalysis from MIDAS Civil requires more
reinforcement as compared to STAAD.Pro. This is due
to shear resistance and serviceability check where theforces developed by MIDAS Civil software are higher
compared to STAAD.Pro.

REFERENCES[1] British Standard, BS 5400-4:1990 Steel, concrete andcomposite bridges. Part 4: Code of practice for designof concrete bridges.

[2] BD37/01, Design Manual for Roads and Bridges, Vol.
1, Highway Structures: General Design, Loads for
Highway Bridges, 2001.

[3] Jihoon Kang, Design Verification of Balanced
Cantilever Bridges as per BS Code, Midas IT, 2017.

[4] STAAD.Pro V8i, Technical Reference Manual, Bently
System Incorporated, 2012.

[5] MIDAS Technical Reference Manual, 2011.
[6] Abdullah Zaid, D. C., Transverse Assessment of a

CONCLUSION

Concrete Box Girder Bridge. Proceeding of theInstitution of Civil Engineers, 2016.

Comparison between STAAD.Pro and the MIDAS
software showed that the analysis result of the box
girder bridge from this two software have significant
difference in the live load cases as compared topermanent load cases. Whereas, for the design results,
the reinforcement used is similar for cantilever part ofthe slab but different for other parts of the box girder
segment, in which, the MIDAS Civil requires more
reinforcement. This shows that MIDAS Civil software[7] Theryo T.S., Segmental Concrete Bridges, Edited by
Wai-Fah Chen and Lian Duan, Bridge Engineering
Handbook 2nd Edition, Superstructure Design, Boca
Raton: Taylor & Francis Group, 2014, pp 91-169.

616

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE SPEED LIMIT FOR MOTORCYCLE: URBAN ARTERIAL ROADIN KHON KAEN CITY, THAILAND

1

Jetsada Kumphong1, Thaned Satiennam1 and Wichuda Satiennam1
Department of Civil Engineering, Faculty of Engineering, Khon Kaen University, Thailand.

ABSTRACTRoad traffic injuries tend to be more serious all over the world, as well as the number of road fatalities, serious
injuries and disabilities is also increasing. Since speeding is one of the top causes of death and injury, the speed of
motorcycle vehicles should be investigated in order to analyze the speed limit. The speed of motorcycle wereobserved at risk points on urban arterial road in Khon Kaen City. Then, the speed values were applied to determine
the speed limit of motorcycle. As the results, the road in the study area should stipulate the speed limit ofmotorcycle at 60-70 km/h. At present, Thai law has limited the speed in urban areas at 80 km/h. This information
will be valuable for the urban and transportation engineers and planners so as to forecast the speed limit ofmotorcycle vehicles in Khon Kaen city when a new road will be is designed in the future.
Keywords: Speed, Motorcycle, Safety, Traffic injuries

disclosed that the means peak-hour speed of vehicles
was 33.5 kilometers per hour, while the speed in
Amphur Muang or inner ring roads was lower at 19.7.
Based on the data of land use, the study also foundthat most of the areas were educational institutions.
Khon Kaen City is a province with huge areas
consisting also of government sectors and educational
institutions. With its mass number of educational
establishments, department stores and residences,
there is the daily extensive use of privatetransportation with the drivers’ use alcohol and use ofhigh speed frequently causing accidents. [12-13]
Although, There will be traffic measures (speed
camera, red-light running camera etc.). Therefore,
this study of motorcycle speed (before/after) witheffects of traffic measures on Mittraphap Road atKhon Kaen Urban to develop guidelines of speed
limit for motorcycle in Khon Kaen City.

INTRODUCTION
Traffic injuries tend to be increasingly serious allover the world, as well as the number of road fatalities
and disabilities that is becoming a problem.
According to Global Road Safety statistics of 2010,
approximately 1.27 million deaths worldwide werecaused by road accidents (3,479 people per day). If
old defensive measures were still used, within 20
years, road accidents could be the leading cause ofdeaths globally, and road safety problems are
predicted to expand dramatically. By 2030, the road
fatalities may rise up to 2.4 million deaths, inclusivewith a possible increase from injury rates. As a result,road accidents will become the major cause of deaths,
together with disabilities, and its rank will alsochanged from the 9th (in 1990) to the 3rd.[1]Thailand has the highest rate of traffic accident
fatalities, also highest rate of motorized 2-or 3wheelers deaths. [2-8] Speeding is one of the mostcommon causes of road accident in Thailand. [9]Prior to the speed study in Thailand, Bunjaweht andSutiwipakorn (2006) stated that traffic accidents
cause a mass of casualties and damage to citizens’
properties each year and can be considered as theunderlying causes of deaths. Among many factors of
traffic accidents was the speed of vehicles. Higher
speeds of vehicles increase the risks of accidents.
What is more? Fast speed intensifies the injuries anddamage. In a pedestrian versus car accident, if apedestrian is hit by a car at 64 kilometers per hour, thelikelihood of his/her death is 90%, while a hitting car
at 32 causes only a five-percent chance of the death.
As can be seen, the decrease of the vehicular speed by
1 can decrease the likelihood of deaths by 5%. The
study conducted by U-rod and Udomsri (2006)

Fig. 1 Traffic measures in Khon Kaen City
617

SEE - Nagoya, Japan, Nov.12-14, 2018

METHODOLOGY
Data Collection by Observation
In this study, there are 2 types of data sets. The
secondary data included the spot speed of motorcycle
riding on Mittraphap Road in Khon Kaen City in 2016
[14-16] (28 points), whereas the primary data wascollected from 1,555 motorcycle samples from the 28
points (S01-S28) in 2017 along the Mittraphap Road
(about 16 kilometers) in Khon Kaen city (as shown in
Fig. 2 and Fig. 3).The free flow speeds of vehicles
between 06.00 a.m. to 07.00 a.m. were collected byusing a radar gun as shown in Fig. 4.

N

Fig. 4 Observation by using a radar gun
Sample description
The spot speeds of motorcycle data in years 2016 –2017 are calculated into the means speed and 85th
percentile speed (MC85th: 85th percentile speed of
motorcycle (Km/h), MCm: means speed of
motorcycle (Km/h)). In addition, comparisons were
performed between the averages and the 85th
percentile of private cars in 2016 (PC85th: 85th
percentile speed of private cars (Km/h), PCm: means
speed of private cars (Km/h)) as shown in Tables 1,
2. Table 3 shows the physical characteristics ofMittraphap Road in Khon Kaen City. If the road’s
cross-sectional area is wider, the speed of vehicles
tends to increase. [15]Statistical Analysis
Fig. 2 Study area

Besides the descriptive statistics (means, 85th
percentile), t-test was conducted to find the differenceof data at 95% confidence level [17] by SPSS
program.
RESULTS AND DISCUSSION
From the speed study of motorcycles at 28 spots inKhon Kaen City, Thailand from 2016 to 2017, theresults showed that in 2016, the speed of 7.1% of
motorcyclists was over 59 Km/h whereas in 2017 nomotorcycle was found using speed of over 59 Km/h.
The majority of riders (92.90%) used a speed rangeof 50 – 59 Km/h (as shown in Table 4 and Fig. 5),
which is the speed range difference found in thestudies in Vientiane, Lao PDR. and Phnom Penh,
Cambodia where the means speed was 36 Km/h and
35 Km/h, respectively. [14-15]

Fig. 3 Example of a cross-sectional study area ofMittraphap Road in Khon Kaen City, Thailand

618

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Motorcycle and private car speed datain year 2016

Table 2 Motorcycle speed data in year 2017

No.

MC85thMCm
PC85thPCm(Km/h)(Km/h) (Km/h) (Km/h)
1
101
64
84
50
2
93
67
82
54
3
101
69
93
61
4
100
69
95
58
5
95
67
84
55
6
95
60
84
51
7
72
60
65
52
8
80
63
71
55
9
87
69
69
51
10
85
71
74
58
11
98
68
89
58
12
98
69
90
59
13
86
71
74
57
14
91
67
75
51
15
76
63
68
52
16
101
66
90
58
17
92
63
77
50
18
71
68
59
53
19
75
73
64
57
20
71
68
59
53
21
95
59
78
51
22
81
69
69
56
23
85
60
70
47
24
84
65
69
49
25
92
70
79
57
26
99
72
83
55
27
86
58
74
50
28
103
79
88
60
Note: Motorcycle speed data by Jetsada Kumphongin 2016

No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28

MC85th(Km/h)
64
69
64
68
67
64
63
65
64
63
66
66
65
65
65
65
61
65
60
60
58
60
65
66
66
68
62
66

MCm
(Km/h)
52
54
50
53
52
53
53
54
52
52
54
54
54
54
55
54
52
53
51
49
49
51
53
54
56
54
54
56

Table 3 Descriptive Statistics of physicalcharacteristics of Mittraphap Road
in Khon Kaen City

From Table 5, the comparison between motorcycle
speeds in 2016-2017 shows the difference of the
motorcycle speeds at 85 percentile at a significant
level (p < 0.05). However, the means speeds ofmotorcycles of the 2 years were not different. In
addition, the speed comparison between vehicles andmotorcycles indicates that the vehicle speed was
different from motorcycle speed at a significant level(p < 0.001), as shown in Table 6, the study of speed
differences between private car and motorcycle. The
difference of speed means of private car andmotorcycles in Vientiane, Lao PDR was 9 Km/h andin Phnom Penh, Cambodia it was 4 Km/h [14-15]. If
there is speed difference between vehicles, it is likelythat severe injuries from accidents may lead to death.
[14, 16]619

Independent Variables
Left safety strip width (m)Mean

Number of lanes

3.3

Lane width (m)3.8Roadway width (m)13Conflict point (per 1000 m)

3.5

Right safety strip width (m)

0.9

1.1

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 6 and Fig.7 illustrates the result of speed survey
at 85 percentile and vehicle speed means in 2017.
Based on the road line in the study area, the speed ofvehicle all through the route (S1-S28) is nearly
similar; at 85 percentile the speed range was 60-70
Km/h (accept at S21 spot) and the speed was 50-60
Km/h (accept at S20-S21 spot). If adhered toengineering principle and speed limit of vehicle at 85
percentile [18-19], the road in the study area should
stipulate the speed limit of motorcycle at 60-70 Km/h.
At present, Thai law has limited the speed in urban
areas at 80 Km/h, which is applied to motorcycles andprivate cars.

Table 4 Speeds of motorcycle in 2017 (N=1,555)
Speeds of motorcycle

Km/h

MC 85th

53

MC m.

65

<50 Km/h

50-59 Km/h

>59 Km/h(Km/h)
2 0 1 7 7.10%

92.90%

0%2 0 1 6 7.10%

85.70%

7.10%

80
70
60
50
40
30
20
10
0

S1
S2
S3
S4
S5
S6
S7
S8
S9
S10
S11
S12
S13
S14
S15
S16
S17
S18
S19
S20
S21
S22
S23
S24
S25
S26
S27
S28

Fig. 5 The result of motorcycle speed study
in 2016-2017
Table 5 Comparison between speeds of motorcycle in2016-2017

2016MC85th

Difference
Mean
S.D.
2.4
4.8

Fig. 6 The result of motorcycle speed survey at 85
percentile in 2017

t
2.6**

(Km/h)- 2017MC85th
1.1
3.9
1.7
2016MCm- 2017MCm
Note: *Significant at 90% confidence level,**Significant at 95% confidence level,***Significant at 99% confidence level.

60
50
40
30

Table 6 Speed differences between private car andmotorcycles

20

Difference
Mean
S.D.
22.4
10.2

0

10
S1
S2
S3
S4
S5
S6
S7
S8
S9
S10
S11
S12
S13
S14
S15
S16
S17
S18
S19
S20
S21
S22
S23
S24
S25
S26
S27
S28

t

11.6***
2016PC85th- 2016MC85th
22.8
8.8
13.7***
2016PCm- 2016MCm
24.8
9.2
14.2***
2016PC85th- 2017MC85th
36.1
9.8
19.5***
2016PCm- 2017MCm
Note: *Significant at 90% confidence level,**Significant at 95% confidence level,***Significant at 99% confidence level.

Fig. 7 The result of motorcycle speed survey atmeans in 2017
CONCLUSIONSThe statistical analysis in this study showedstatistically significant difference between the speedof cars and motorcycles at the confidence level of
0.95. The speed limit should be lowered to less than
80 Km/h, which is the current setting. The difference
between the speed and mass of the two vehicles in thecollision may lead to fatality of motorcyclists.
620

SEE - Nagoya, Japan, Nov.12-14, 2018

comparison of the Theory of Reasoned Action and theTheory of Planned Behavior. Conference proceedings,
in Proc. 12th Int. Conf. on the Eastern Asia Society forTransportation Studies, Vol. 11, 2017, pp. 1-14.
[9] Royal Thai Police. Injuries and Deaths Report 20062013.Thailand; 2013. (In Thai)[10] Bunjaweht P., Sutiwipakorn V., A study of the use of
traffic calming strategy in Thailand. Conference
proceedings, in Proc. 3rd the Nine National Transport
Conference Research (NTC3), Thailand, 2006. (InThai)[11] U-rod S., Udomsri R., The Applicationof Handheld
GPS in Speed and Travel Time Surveys. Conference
proceedings, in Proc. 3rd the Nine National Transport
Conference Research (NTC3), Thailand, 2006. (InThai)[12] Ichikawa M., Chadbunchachai W., Marui E., Effect of
the helmet act for motorcyclists in Thailand. Accident
Analysis and Prevention, Vol. 35, 2003, pp. 183-189.
[13] Nakahara S., Chadbunchachai W., Ichikawa M.,
Tipsuntornsak N., Wakai S., Temporal distribution of
motorcyclist injuries and risk of fatalities in relation toage, helmet use, and riding while intoxicated in Khon
Kaen, Thailand. Accident Analysis and Prevention,
Vol. 37, 2005, pp. 833-842.
[14] Kumphong J., A study of relations between speed ofvehicles with road characteristics and accident
severity. Master thesis in Department of Civil
Engineering, Faculty of Engineering, Khon Kaen
University, 2016. (In Thai)[15] Kumphong J., Satiennam T., Study of vehicle’s speedof cities in Greater Mekong Subregion. Conference
proceedings, in Proc. 8th Asian Transportation
Research Society (ATRANS) Symposium: Young
Researcher’s Forum, 2015. (In Thai)[16] Kumphong J., Satiennam T., Satiennam W., A studyof the relation between the speed of vehicles and traffic
accident and road Characteristics. Conference
proceedings, in Proc. 20th National Convention on
Civil Engineering (NCCE20), 2015. (In Thai)[17] Park H M., Comparing Group Means: The T-test andOne-way ANOVA Using STATA, SAS, and SPSS.
The Trustees of Indiana University, 2005.
(http://stat.smmu.edu.cn/DOWNLOAD/ebook/statisti
cs_course.pdf)[18] Abbas S K S., Adnan M A., Endut I R., Explorationof 85th Percentile Operating Speed Model on
Horizontal Curve: A Case Study for Two-Lane Rural
Highways. Conference proceedings, in Proc. 6th
International Symposium on Highway Capacity andQuality of Service, Stockholm, Sweden June 28 – July
1, 2011, pp.352-363.
[19] Federal Highway Administration & MUTCD. Setting
speed limits – The 85th percentile speed.
(https://lincoln.ne.gov/city/pworks/engine/traffic/pdf/
regulatory-speed-limits.pdf)[20] Mummuntree R., Klungboonkrong P., Determinationof the speed limits in Thailand. Conference
proceedings, in Proc. 19th National Convention on
Civil Engineering (NCCE19), 2014. (In Thai)

Additionally, the study of the motorcycles speed
in 2016-2017, conducted during the implementationof traffic control measures (RLR camera, speed
camera etc.) indicated no statistical difference
between the two years. This study indicated the
motorcycle speed limit at 85th percentile, which isbased on traffic engineering principle. This research
therefore proposes the use of a limit of 60 - 70 Km/h,so that the private car’s speed is reduced to approach
the motorcycle speed. It should be noted that the
speed limit for both motorcycles and private cars in
Thailand is similar. The results of this study will bepresented to those involved in this area for road trafficplanning and prevention.
RECOMMENDATION
The law of Thailand that governs urban speed
limits of cars and a motorcycle [20] is the same. As aresult, fatality among motorcyclists is more likely
than among motorists. In this regard, further studies
should be conducted to determine the appropriate
speed limit of each vehicle type for the relevantorganizations to take into account in developing
future policy or speed law enforcement.
ACKNOWLEDGEMENTS
This research received a Research Fund for
Supporting Lecturer to Admit High Potential Student
to Study and Research on his Expert Program Year2016, Graduate School, Khon Kaen University, Khon
Kaen, Thailand. Thanks are also extended to Khon
Kaen University Language Institute for editing thereport.
REFERENCES[1] Tanaboriboon Y., Satiennam T., Traffic accidents in
Thailand. IATSS RESEARCH, Vol. 29, No. 1, 2005,
pp. 88-100.
[2] World Health Organization. Helmets : A road safety
manual for decision-makers and practitioners. Geneva,
Switzerland, 2006.
[3] World Health Organization Global Status Report on
Road Safety 2009. Geneva, Switzerland, 2009.
[4] World Health Organization. Global Status Report on
Road Safety 2013. Geneva, Switzerland, 2013.
[5] World Health Organization. Global Status Report on
Road Safety 2015. Geneva, Switzerland, 2015.
[6] F.A.O. Fernandes R.J., Alves D.S., Motorcycle
helmets-A state of the art review. Accident Analysis
and Prevention 2013, Vol. 56, pp. 1-21.
[7] Kumphong J., Satiennam T., Satiennam W., A
correlation of traffic accident fatalities, speed
enforcement and the gross national income of Thailand
and its cross-border countries. International Journal ofTechnology, Vol. 7, 2016, pp. 1141-1146.
[8] Kumphong J., Satiennam T., Satiennam W., A Studyof Social Norms and Motorcycle Helmet Use
Intentions among Student Riders in University: A

621

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

MOTORCYCLE HELMET USE INTENTION WITH THE THEORY OF
TRAFFIC PSYCHOLOGY FOR BEHAVIOR CHANGE IN LAO PDR
Jetsada Kumphong1, Thaned Satiennam1, Wichuda Satiennam1 and Phongsavanh Inthavongsa2
1
Department of Civil Engineering, Faculty of Engineering, Khon Kaen University, Thailand.
2
Department of Road-Bridge and Transport Engineering, Faculty of Engineering,
National University of Laos, Lao PDR.

ABSTRACT
Recently, there has been growing interest in motorcycle safety in ASEAN countries. Laos has a high death of
motorcycle riders and helmet wearing rates remain big problem. The aim of the present study was to reduce theseverity of road accidents among student riders by studying the relationship between Lao students’ helmet use
intention and other psychological factors based on the Theory of Planned Behavior (TPB) and to study the
relationship between stages of change and processes of change among Lao students’ helmet use based on
Transtheoretical Model and Stages of Change (TTM) which is a traffic psychology module including. Data wascollected from 219 motorcyclists and analyzed using the Structural Equation Model (SEM), Theory of Planned
Behavior (TPB), which is a traffic psychology module including attitude (ATT), subjective norm (SN) andperceived behavioral control (PBC). Also, Transtheoretical Model and Stages of Change (TTM) to analyze by
Pearson Correlation. The results indicated that the TPB model and TTM, the actual behavior would be adapted bychanging their intentions. The TPB model showed that PBC were significant. The outcome of this study will bepresented to authority for planning road safety in Lao PDR.
Keywords: Helmet, Motorcycle, Safety, Traffic injuries

road users to conform to traffic rules. This research
investigated how to reduce the severity of roadaccidents among student riders by studying therelationship between students’ helmet use intention
and other psychological factors based on the Theory
of Planned Behavior (TPB), Transtheoretical Modeland Stages of Change (TTM).

INTRODUCTION
Motorcycles are used for transportation and sport
activities in ASEAN countries. The correlation
between high fatality rates, among motorcyclist, andlow helmet use illustrate the problem. [1-6]Japan has been successful in helmet law
enforcement with a high helmet wearing rate. Unlike
Japan, Laos has a high death rate from traffic
accidents per 100,000 population with low helmet
wearing rate and insufficient helmet law enforcement,
also highest rate of motorized 2-or 3-wheelers deaths
as shown in Fig. 1 and Fig. 2. [6]Vientiane City is a big city consisting of manyeducational establishments, hospitals, department
stores, and residences; there is thus an extensive useof motorcycle transportation on city. The average
number injury on the road is 1,734/year, the average
number severe injury on the road is 209/year, theaverage number breaths on the road is 161/year. [7]However, many riders do not wear helmets whiledriving (the helmet wearing rate is 60% [5]).
Vientiane City has been promoted that helmet use
campaign and distributing 1,000 helmets to student
rider on August 31, 2016. [8] The tow-wave panel
design was applied on city, with a 1-year interval
between waves. The first set of data were collected in2016 (before- helmet use campaign). The second
phase of data collection was done in 2017, under the
campaign for motorcyclists to wear helmets and forFig. 1 Trends in reported road traffic deathsin Lao PDR. [6]622SEE - Nagoya, Japan, Nov.12-14, 2018

Therefore, we employed the TPB to explain
intention of helmet use. Accordingly, we proposed
the following hypotheses:
H1: Attitude (ATT) variable is positively related tothe intention of helmet use.
H2: Subjective norm (SN) variable is positively
related to the intention of helmet use.
H3: Perceived behavioral control (PBC) variable ispositively related to the intention of helmet use.
H4: Intention (IN) variable is positively related to thehelmet use behavioral variable.
H5: Perceived behavioral control (PBC) variable ispositively related to the helmet use behavioral
variable.

Fig. 2 Deaths by road user category
in Lao PDR. [6]METHODOLOGY

Based on the aforementioned literature review,
following are our study models and hypotheses (Fig.
5).

Data Collection by Observation
The questionnaire survey (as show in Fig. 3)
which examined direct measurements followed theprinciples of TPB (Table 1.) [9-13], while TTM wasused for investigating states of chances (Fig.4; Table
2, 3 and 4). [14-15]

Fig. 5 Proposed study framework by TPB
Statistical Analysis
The analysis of the results was divided into threeparts adapted from Kumphong J. et al. (2017).
Overall, the model fit was evaluated against the
number of recommended fit statistics and fit indicesbased on Hair et al. (2010).The first analysis was afactor analysis on latent variables (attitude (ATT),
subjective (SN), perceived behavior control (PBC)
and intention (IN)) from the questionnaire. Reliabilityof the latent variables was analyzed by Cronbach’s
alpha. All variables were analyzed based on TPB byconfirmatory factor analysis (CFA). The second partused the Structural Equation Modeling (SEM) to
analyze all variables. Respondent’s factors (ATT, SN
and PBC) were positively related to the behavioral
intention of helmet use on campus. The final part was
the analysis of the results by TTM using Pearson
Correlation at 95% confidence level.

Fig. 3 Observation by questionnaireFig. 4 Proposed study framework by TTM

623

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 TPB concepts and scales
Item
Attitude (ATT)
ATT1 Wearing a helmet, it
would be
ATT2 Wearing a helmet, it
would be
ATT3 Wearing a helmet, it
would be
ATT4 Wearing a helmet, it
would beSubject norm (SN)
SN1 Most of my friends
wear a helmet whendriving...
SN2 Most of peoples wear ahelmet when driving...
Perceived Behavioral
Control (PBC)
PBC1 I believe I have theability to wear a helmet.
PBC2 I can wear a helmet
even if the other do not.
PBC3 I can wear a helmet
even if there is no police on
the street.
PBC4 I am confident that I
could wear a helmet.
Intention (IN)
IN1 Next 3 months, I will
wear a helmet whendriving......
IN2 Next 3 months, I want
wear a helmet whendriving...
IN3 Next 3 months, I intent
wear a helmet whendriving......
Self-report behavioral (B)B How often you wear ahelmet when riding...

Scoring
1 = Bad : 5 =Good
1 = Unsafe:
5 = Safe
1 = Harmful :5 = Beneficial
1 = Unlikely: 5 = likely

M

SD

4.71

0.73

4.72

0.73

4.62

0.81

4.68

0.78

1 = disagree: 5 = agree

4.18

1.05

1 = disagree: 5 = agree

4.12

1.02

4.65

0.66

4.50

0.84

1 = disagree: 5 = agree

4.48

0.90

1 = disagree: 5 = agree

4.52

0.74

1 = disagree: 5 = agree

4.46

1.05

1 = disagree: 5 = agree

4.56

0.86

1 = disagree: 5 = agree

4.39

1.03

1 = Never: 5 = Always

4.39

0.82

1 = disagree: 5 = agree
1 = disagree: 5 = agree

average age was 21 years old. 51% had a driver’s
license, and the average riding experience was 7
years. The interesting point founds were: the averageof 1 time of a crash of participants, 27% had notexperienced any accident, only 7% experienced
property loss and damage, and 56% were involved inminor injuries whereas only 10% had severe injuries.
Table 3 Processes of change concepts and scales
Processes of change
concepts
Experiential process
PC1-The activities letme know and learn
importance of wearing
PC2- The activities
make me feel that notwearing helmet is a risk
PC3- The activities
make me realize thatwearing helmet is an
important thing for me
PC4- The activities
make me realize thatwearing helmet is an
important thing to do in
the society
PC5- The activities
make me realize thatsocialnorm
issupporting
wearing
helmetBehavioral process
PC6- The activities
make me interested towear helmet
PC7- The activities
make me remembranceof wearing helmet whenriding motorcycle
PC8-The activities letme meeting those whoalways wear helmet
PC9-The activities
support me to wear
helmetPC10-The activities
make me feel thatwearing helmet isusefulTable 2 Stages of change concepts
Stages of change
Precontemplation
stage
Contemplation stage
Preparation stage

Action stage
Maintenance stage

Wearing helmet
Wearing helmet is not
an important behavior
Wearing helmet is an
important behavior
Wearing helmet is abehavior that I shoulddoI often ware helmet
I have been wearing
helmet more than a
year

RESULTS AND DISCUSSION

Item

M

SD

1 = disagree: 4 = agree

3.50

0.54

1 = disagree: 4 = agree

3.21

0.86

1 = disagree: 4 = agree

3.60

0.60

1 = disagree: 4 = agree

3.54

0.56

1 = disagree: 4 = agree

3.47

0.57

1 = disagree: 4 = agree

3.37

0.62

1 = disagree: 4 = agree

3.51

0.57

1 = disagree: 4 = agree

3.17

0.65

1 = disagree: 4 = agree

3.43

0.61

1 = disagree: 4 = agree

3.58

0.61

Validity of measurement TPB model

Demographic Data of the Sample

The results of reliability and validation estimation
were presented in Table 5. They show that all valuesof reliability and validation followed a good rule ofinternal consistency and rule of thumb, suggesting

The study of helmet wearing behavior change wasdone by the questionnaire survey from 219 student
motorcyclists (80% male and 20% female), whose624

SEE - Nagoya, Japan, Nov.12-14, 2018adequate convergence. In other words, Cronbach’s α,refers to consistent answers from identical group
questions (e.g., Items for SN measure) of the
respondents. The values threshold of 0.7 isacceptable. As a result, these values indicate latentvariables of TPB model, which are good reliable
representative values to explain the model. Table 6
shows that all latent variables (ATT SN and PBC)
correlated with the IN variable at 0.1% level ofsignificance.

Table 6 Reliability scales and correlation matrix TPB
model
No.
Factors
1
2
3
4
of items

1.ATT
2. SN
3. PBC
4. IN

4
3
3
3

1
0.234*
0.457**
0.257**

1
0.476**
0.196*

1
0.465**

1- Not relevant; ** Significant at 0.1% level; * Significant
at 5% level

Table 4 Decisional balance concepts and scales

Test of a structural TPB model

Decisional balance
concepts
Pros
P1-Increase safety

We present the indexes in Structural Equation
Model and factors influencing the indexes withstandardized path coefficients. The most often
indicated number of recommended statistics andindices in Tables 7 and 8 are fitted for the SEM basedon Hair Jr et al. (2010). Therefore, the model fits
between the theoretical constructs and observation
constructs. We carried out SEM for independent TPB
and extended TPB models.
Fig. 6 shows the result of structural models withstandardized path coefficients for TPB model. The
TPB model fit could pass a number of recommended
fit indices. TPB model could explain 22% of variancefor helmet use intentions and 26% of variance forhelmet use behavior. From the TPB model, PBC were
found to positively and significantly correlate withthe helmet use intention (IN). PBC was the mostsignificant and highly influential factor; it is theability to regulate behavior intention. In addition, the
TPB model indicated that PBC positively andsignificantly correlated with the helmet use behavior.

P2-Reducing accident
injuryP3-Sun/ dust/ insect
protection
P4-Police enforcement
Cons
C1-Reduce visibility

Item

1 = disagree: 5 = agree
1 = disagree: 5 = agree
1 = disagree: 5 = agree
1 = disagree: 5 = agree
1 = disagree: 5 = agree
1 = disagree: 5 = agree
1 = disagree: 5 = agree

C2-Prevent hearing
C3-Hot anduncomfortable

M

SD

4.73

0.59

4.68

0.64

4.69

0.61

4.69

0.63

3.56

1.06

3.60

1.04

3.06

1.34

Table 5 Exploratory factor analyses of model
TPB
items

1. ATT

2. SN
3. PBC

4. IN

Factors

α
ATT1
ATT2
ATT3
ATT4
SN1
SN2
PBC1
PBC2
PBC3
PBC4
IN1
IN2
IN3

1

2

3

4

0.914

0.675

0.767

0.756

Table 7 Explanatory power and fit index of models.
(N=219)

0.863
0.901

Model fit

Recommended
value

Model

χ2/df
GFI
CFI
RMSEA

< 3.0
> 0.90> 0.90< 0.08

1.97
0.917
0.945
0.067

0.864
0.869
0.861
0.824
0.715
0.745
0.782
0.700

Table 8 SEM results of model. (N=219)
0.799
Paths

0.812
0.801

ATT → IN (+)

Coefficients (β)

p-value

Hypothesis
Supported

0.005
0.953
No
-0.0370.715
NoPBC → IN (+)
0.488**<0.001Yes
IN → B (+)
0.528
0.201
No
PBC → B (+)
0.555**<0.001
Yes- Not relevant; ** Significant at 0.1% level; * Significant at
5% level- Not relevant; Factor loadings > 0.7; (KMO = 0.806, p <0.001)

SN → IN (+)

625

SEE - Nagoya, Japan, Nov.12-14, 2018

Vietnam. SN and PBC influenced the intention towear helmet since SN occurred from social pressure
while PBC occurred from oneself or one’s own
decision [9-10]. In our study, the attitude factor
affected helmet use intention at a statisticallysignificant level. This differs from previous research.
When considering TTM for investigated to helmet
wearing intentions, it was possible that measurestaken to encourage helmet use could increase
motorcyclists’ intention to wear helmet.

ATT1
ATT2

IN 2

IN 1

IN 3

ATT

ATT3

0.01

ATT4
*

0.23

**

-0.04

SN1

2

2

R = 0.26

0.51 R = 0.22

SN

-0.11

IN

SN2

B

**

0.56

**

PBC1

0.47

**

0.49

Table 9 Correlation between the stages of change andprocesses of change

PBC2
PBC3

PBC

*

**

p<0.05, p<0.001

PBC4

Factors
Fig. 6 Structure of TPB model of motorcyclists’helmet use on city

PC1
PC2
PC3
PC4
PC5
PC6
PC7
PC8
PC9
PC10

Test of a TTM structuralFig. 7 shows the percentages of helmet wearing
changes during the time measures were taken such as
helmet wearing campaign. The proportion of riders’helmet use was found to increase. Use of campaign
for support affected the rate of helmet wearing
intention more than other measures.
Table 9 shows that all processes of change
variables (PC1-PC10) correlated with the stages ofchange variable at 0.1%, 5% level of significance. In
addition, the result indicated that PC7 and PC8
positively and significantly correlated with the stagesof change. On the other hand, the result found thatpros and cons factors non-significant with the stagesof change variable.

AFTER- HELMETUSE CAMPAIGN

8.7 21.5

BEFORE- HELMET
11.0 25.6
USE CAMPAIGN

17.8

Sig.
0.304
0.450
0.695
0.059
0.979
0.109
0.019
0.012
0.494
0.071

- Not relevant; ** Significant at 0.1% level; * Significant
at 5% level

CONCLUSIONS
According to the TPB and TTM, the actual
behavior would be adapted by changing theirintentions. The result showed that PBC weresignificant factors for TPB, TTM. The traffic
psychological factors are consistent with intention towear helmet among student riders. Behavior change
could occur after helmet use campaign. The results ofthis study will be presented to those involved in thisarea for road traffic planning and prevention.
Motorcycle riders are required to follow the
instructions shown below, for suggest some concrete
transport measures based on this research output.
1) Implement city road safety action plan (Helmet
use 100%).
2) Set up the safe motorcycle riders in city areas.
3) Helmet law enforcement by CCTV camera 24 hr.
[17-18]52.0

25.0 11.0

PearsonCorrelation
0.070-0.051
0.027
0.128
0.002
0.108
0.158*
0.169*
0.046
0.122

27.4

1. Wearing helmet is not an important behavior.
2. Wearing helmet is an important behavior.
3.Wearing helmet is a behavior that I should do.
4. I usually wear helmet.
5. I have been wearing helmet more than time.

ACKNOWLEDGEMENTS
This research received a Research Fund for
Supporting Lecturer to Admit High Potential Student
to Study and Research on his Expert Program Year2016, Graduate School, Khon Kaen University, Khon
Kaen, Thailand. Thanks are also extended to Khon
Kaen University Language Institute for editing thereport.

Fig. 7 Percentages changes in helmet wearing
intentions
The results of this study agree with the previous
studies of helmet wearing behaviors among students
in Khon Kaen, Thailand and students in Ho Chi Minh,

626

SEE - Nagoya, Japan, Nov.12-14, 2018[11] Ajzen, I., Fishbein, M., Understanding
Attitudes and Predicting Social Behaviour.
Prentice-Hall, Inc., Englewood Cliffs, New
Jersey, 1980.
[12] Ajzen, I., Attitudes, Personality and behavior.
New York, USA, 2005.
[13] Fishbein, M., Ajzen, I., Predicting andchanging behavior: the reasoned action
approach. New York, 2010.
[14] Driving under the Influence of Drugs,
Alcohol and Medicines, Good Practice: InDepth Analysis on Recidivism Reasons &Analysis of Change Process and Components
in Driver Rehabilitation Courses Report,
2008.
[15] James O. Prochaska, Colleen A. Redding, andKerry E. Evers, HEALTH BEHAVIOR AND
HEALTH EDUCATION Theory, ResearchandPractice;
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5
THE
TRANSTHEORETICAL MODEL AND
STAGES OF CHANGE, pp. 97-117, 2008.
[16] Hair, J.F., Black, W.C., Babin, B.J., andAnderson, R.E., Multivariate Data Analysis a
global perspective 7th ed., New Jersey, 2010.
[17] Jantosut P, Kumphong J, Wonghabut P,
Satiennam W, Satiennam T, Ung-arunyawee R. ,The Evaluation of CCTV camera enforcement to
reduction of red-light running and increase of ahelmet use. 13th Thailand road safety seminar:
Invest for sustainable road safety 2017: 73–74.
(In Thai)[18] Wonghabut, P., Kumphong, J., Satiennam, T.,
Ung-arunyawee, R. & Leelapatra, W., Automatic
helmet-wearing detection for law enforcement
using CCTV cameras. IOP Conference Series:
Earth and Environmental Science, Vol.143,
2018.

REFERENCES[1] Kumphong, J., Satiennam, T., & Satiennam, W.,
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GEOMATE, Sept., 2018, Vol.15, Issue 49, pp. 72-77.
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International Journal of Technology, Vol. 7, 2016,
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Promotion
Foundation,
http://www.thaihealth.or.th/Content/32660รณรงค ์เยาวชนลาวใส่หมวกกันน็ อค.html (In Thai)[9] Kumphong, J., Satiennam, T., and Satiennam, W.,
Psychological models for development ofmotorcycle helmet use among students in
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[10] Kumphong J., Satiennam T., Satiennam W., A
Study of Social Norms and Motorcycle Helmet
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Int. Conf. on the Eastern Asia Society forTransportation Studies, Vol. 11, 2017, pp. 1-14.

627

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PSYCHOLOGICAL MOTIVATION OF ELDERLY’ INTENTION TO
USE PUBLIC TRANSIT: A CASE STUDY OF LIGHT RAIL TRANSITSYSTEM (LRT) IN KHON KAEN, THAILAND
Kawin Muenrit1, Wichuda Satiennam2
Department of Civil Engineering, Faculty of Engineering, Khon Kaen University, Thailand1,2

1,2

ABSTRACT
Elderly mobility is a challenging problem for the aging society in the developing countries and psychologicalfactors play a major role to understand their mode choice behavior. This paper proposes an integrated model
combining psychological factors according to the Theory of Planned Behavior (TPB) and Technology Acceptance
Model (TAM) to explain the elderly' intention of using the planned Light Rail Transit system (LRT) in Khon Kaencity, Thailand. A sample of 340 participants was administered a questionnaire survey that measured a series of aconstruct based on TPB and TAM. Structural equation models (SEM) technique is used to test causal structure of
the models. The results showed that attitude and subjective norm were all positively significant effect on elderly'
intention, an especially subjective norm. The recognition that the system is easy to use and beneficial to travelers
are important motivational factors behind. The implications of outcomes of this study help to understand elderly
mobility and some effective ways can trigger traveler' intention to use LRT are discussed. in developing countries
are discussed.
Keywords: Light Rail Transit system, Theory of Planned Behavior, Technology Acceptance Model, Elderly, Ageing
society.

The way to encourage public transit still based
policy goals of transportation management system.
To achieve this goal, one important step is tounderstand mode choice behavior of traveler. The
choice of transportation mode (private vehicle, public
transit) is an individual tendency that is considered
important in policy-making decisions. The recent
work in choice models has emphasized theimportance of the explicit treatment of psychologicalfactors affecting decision-making for example [4],[11]. A guiding philosophy in these developments isthat the incorporation of psychological factors leads
to a more behaviorally realistic representation of the
choice process, and consequently, better explanatory
power [3]. Many researchers have used various
techniques to explicitly capture psychological factors
in choice models. Psychological behavior theories inmodal choice are the Theory of Planned Behavior;
TPB, as in [1] and the Technology Acceptance
Model; TAM, as in [8]The theory of planned behavior (TPB) is a wellresearched model which is a social psychologicalmodel that has been successfully used to predict awide range of human intentions [1]. An individual’s
behavior can be predicted by the behavioral intention.
The constructs of theoretical include attitude toward
the behavior, based on perceptions of a favorable orunfavorable evaluation on the consequences ofaction, subjective norm, the belief about perceived
social approval for the action, and perceived
behavioral control, people’s perceptions of the ability
to perform a given behavior [1], [2]INTRODUCTION
Thailand is currently experiencing a rapid
increase in the aging population. In 2014, Thailand
had a high proportion of the elderly population,accounting for 14.9% of the total population [13].
According to a survey in 1994, the proportion of theelderly was 6.8% and increased to 9.4%. 10.7 and12.2 percent in 2002, 2007 and 2011, respectively,
due to the trend of population change. The elderly
population is an important group and needs to pay
attention and provide daily life support facilities.
The role of the elderly in the family today. Show
that most elderly also want to help their children or
family in various activities. As can be done especiallyin families with few members. these things play a rolein every family. In addition to playing a role in the
mission - responsible for family housework and also
plays a role in earning money. And a career as well.
Although they are very aged. The needs of the elderly
in depth is "I do not want to burden myself with myfamily".
Some elderly people rely on themselves for using
public transit for daily activities. Older people areexperiencing difficulties in using public transit
services that are not able to meet the needs of theelderly and obstructing the elderly in accessing
services. Due to there are no policies that focus on theprovision of public transit for the elderly. Therefore,
the purpose of this paper aims to study theconcept/factor of the elderly' intention to use public
transit.
628

SEE - Nagoya, Japan, Nov.12-14, 2018

The TAM introduced by [8] is "one of the mostreferred theoretical frameworks to predict theacceptance and use of new format of technology"[16]. A TAM construct includes, Perceived ease ofuse is defined as the degree that using a specifictechnology will be free from effort and Perceived
usefulness defined as the perceived degree to which
an individual believes that is using a specific service
or system will improve his or her task performance.
Additionally, perceived ease of use has an indirect
effect through perceived usefulness and attitude on
intention, Perceived usefulness directly influences
intention to use technology.
Both of TPB and TAM have been found toprovide consistently superior explanations andpredictions of human behavior [5], [6], [15], [16].
Besides, the combination of TPB and TAM canadequately define an individual’s behavior withregard to use new technology. For example, thecombined TAM and TPB model has been empiricallyapplied to examine switching intentions toward
public transit [5] and to examine factors affecting the
adoption of Internet banking in Tunisia [16].
This paper, therefore, proposes an integrated
model combining psychological factors according to
the Theory of Planned Behavior (TPB) andTechnology Acceptance Model (TAM) to examine
the effects of psychological factors to explain theelderly' intention of using the planned Light RailTransit system (LRT) in Khon Kaen city, Thailand. It
is a high expectation that understanding the factors
influencing traveler mode choice intentions will be
useful in designing effective strategies to promote theuse of LRT in the study area.

transit use are an issue of immense concern for mostcities around the world. In Khon Kaen city, Thailand,
the LRT is planned to operate to solve traffic
problems in the city. The LRT is a new public transit
system which has specific lanes, uses electric energythat will provide environmental friendly, convenientand standard service. According to the plan, there are
five LRT routes covering the urban area of the city.
In figure 2, the red line is the main transit route andhas 16 stations along the north-south of the mainhighway running through the city [14].

Fig. 2

Light Rail Transit system planning locationin Khon Kaen City.

Participants, Procedure and Measures
Participants are the people who travel and live incommunities near Mittraparb road-the main highway.
The target of study is to explore the opinion of
traveler about the LRT Project on the main route-the
Red Line. The introduction and presentation about theplanned LRT system are carried out before asking theparticipants to complete the questionnaires. Finally, a
total of 340 participants were completed. Participantsin the study were composed of 51% male and 49%
female. Majority of the respondents was between 51
and over years old, which was 62.5% of the total
respondents as shown in Table 1.

METHODOLOGY
Conceptual Framework
This study proposes an integrated model
combining TPB and TAM as shown in Figure 1. Thishypothesized model is based on theory and/or
previous analytic research.

Table 1 This is sample demographics
Frequency
GenderAgecareerFig. 1This is a theoretical framework of this study.

Study Area
Reducing private vehicle use and encouraging public
629

Male
FemaleUnder 40
41-50
51-60
61 and over
Government
officerHousewife
Entrepreneur
Unemployed

173
167
33
93
139
73
45

Percentage
(%)
51.0
49.0
10.0
27.5
41.0
21.5
13.0

108
95
92

32.0
28.0
27.0

SEE - Nagoya, Japan, Nov.12-14, 2018

Note: ** Is correlation is significantly at the 0.01
level (2-tailed)

The questionnaire contains two sections. The firstpart of the questionnaire asks the socioeconomic anddemographic characteristics were measured in termsof gender, age, income, and existing mode. The
second part consists of items for psychologicalmeasures according to TPB and TAM. All the items
are measured by using a five-point Likert scales
ranging from 1 (strongly disagree) to 5 (strongly
agree) that were used to examine participants
responded. The questionnaire with all the measures
under investigation was designed based on an
extensive review of the literature. The initial versionof the questionnaire was then refined through with afocus group. Based on group members' suggestions
on any confusing items in the questionnaire, someitems were moderately re-worded. The questionnaire
examined the variables according to TPB and TAM
as shown in Table 2. Descriptive statistics andCronbach alpha coefficients were calculated for all
measures in a model. Table 2. reports the number of
items, means, and standard deviations. All Cronbachalpha values are greater than 0.7 - suggested
minimum acceptable level of Cronbach alpha, as in[9] indicating that internal consistency is acceptable.

Data Analysis
According to the frameworks of this study, as shownin Figure 1, a measurement model is first estimatedusing Confirmatory Factor Analysis (CFA) to test
whether the data fit a hypothesized measurement
model. The Structural Equation Modeling (SEM)
technique is then utilized to examine the model fit andtest causal structure of the proposed model. This
study uses AMOS 22.0 to evaluate model fit and thesignificance of the hypothesized paths. The fit of theconceptual models to the empirical data is assessedwith the Chi-square ( χ 2 ) statistics, Degree of
freedom (df), The root means square residual (RMR),
Standardized Root Mean Square Residual (SRMR)
and the root mean square of approximation(RMSEA).
RESULTS AND DISCUSSION
Measurement Model

Table 2 This is psychological constructs and theirindicators

Constructs

No.
of
Item

Mean

SD

Cronbach's
alpha

Intention

3

4.30

0.71

0.87

According to the goodness-of-fit indices from the
CFA results, the measurement model was
parsimonious. The Chi-square statistic ( χ = 109.72,
df = 74) was significant. The GFI (0.95) was greaterthan the recommended value of 0.9. The root-meansquare error of approximation (RMSEA) was 0.043,
which is less than 0.08 (Hair et al., 2006).

Attitude

4

4.51

0.56

0.82

Structural Equation Models

3

4.30

0.72

0.86

3

4.34

0.58

0.70

3

4.46

0.60

0.77

3

4.33

0.66

0.77

2

Subjective
Norm
Perceived
Behavioral
Control
Perceived
Usefulness
Perceived
Ease of use

There are two SEM models developed in this study toreveal traveler intention to use LRT. The first SEM
model is guided by TPB (Model 1) and the second
models combine TPB and TAM (Model 2) as shownin Figure 3 and 4, respectively. The fit measuresindicate that the proposed model moderate to well fits
the observed data. The two models accounted for 6163 % of the variance of intention. The combining
model as shown in model 2 has a slightly increased
variance of mode choice intention from model 1. And
Notes that *p < 0.05, **p < 0.01, ***p < 0.001

As show in Table 3 illustrated intercorrelations for all
variables.
Table 3 This is a correlation among constructs

INT

INT
1

ATT

.64**

1

SN

.65

**

.66

**

1

.51

**

.58

**

.63

**

1

.37

**

.53

**

.57

**

.59

**

1

.47

**

.53

**

.56

**

.63

**

**

PBC
PU
PE

ATT

SN

PBC

PU

.52

PE

1

Fig. 3630

This is an estimated model 1.

SEE - Nagoya, Japan, Nov.12-14, 2018

underlying attitude has come from the perceived easeof use and usefulness. For example, if theaccessibility to LRT station (walkway, Parking) iseasy, the information board/Station name is easy tounderstand and clear vision, using the function ofticket system (ticket machine, ticket seller) is easy,
the traveler will have positive attitude to the system
and more likely intend to use the system. A plausible
explanation is that perceived ease of use andusefulness might often indicate its influence on theintention through the mediator of attitude. Therefore,
the LRT planner should take this information to raise
intention by focused on the subjective norm coupledwith attitude accounted when planning the LRT
system for elderly.
Fig. 4

CONCLUSIONS AND RECOMMENDATIONSThis is an estimated model 2.

This study has proposed an integrated mode
choice model consisting of the theory of planned
behavior and a technology acceptance model, toexamine elderly' intentions toward public transit in
the context of the introduction of a new transit system
in a study area. The results showed that the models
accounted for a significant part of the variance in theintention to use LRT. Combining TPB and TAM
model has a slightly increased variance of mode
choice intention from only TPB model. Subjective
norm and attitude are influential factors to LRT
choice intention. The perceived ease of use is the
motivation component underlying favorable attitude.
Since TAM is an important motivational factor
behind attitude and behavioral intention, someeffective ways can trigger traveler’ intention to taking
LRT are suggested. For example, a suitable electronic
ticket system - easy to use, easy to understand. Apartfrom that is service of staff, LRT schedule (service
frequency) and accessibility physical location of thestation (universal design) should focus on safety as
well.
The results from the LRT intention model of theelderly showed that in addition to the strategicplanning from the conceptual framework, in addition
to the focus on social strategy planning frompsychological factors have come out. Another issue
that should be considered is the provision of public
transit for the elderly. If we consider the real current
situation, it is found that elderly people haveproblems in using public transit services such asaccessibility, Security issues, Lack of facilities, noton time, a frequency of service, a problem of system
information, routes are not covered and not linked toother public transit systems [12].
However, the relevant government agencies do
not give priority to the policy of allocating public
transit to the elderly. The main reason is that Thailandis paying attention to other issues. The organization
responsible for managing public transit services

Figure 3. and 4. shows the estimated model in thisresearch. In model 1, the estimated value of thestandardized coefficients in model shows that attitude
and subjective norm have a positive influence on
Intention, but perceived behavioral control show the
opposite effect. Attitude (0.45) appears to be the mostinfluential factor of Intention followed by subjective
norm (0.44) and perceived behavioral control (-0.07).
The regression weight for PBC in the prediction of
intention is, however, not significantly different fromzero at the 0.05 level (two-tailed).
In model 2 the estimate's value of the standardized
coefficients in model shows that most variables from
TPB and TAM are positive and significant. The
results have changed from Model 1. According totheir strength, subjective norm (0.55) appears to be
the most influential factor of Intention followed byattitude (0.48) and perceived behavioral control (0.18) and the regression weight for PBC also notsignificantly. A perceived ease of use is found to besignificantly and positively associated with perceived
usefulness (0.63) and attitude toward LRT (0.40).
The results reveal that traveler intention is mainly
influenced by SN and ATT - especially subjective
norm. The positive relationship implies that the more
the traveler has a positive attitude toward LRT andthe more they perceived social pressure to use asystem, they are more likely intend to use LRT. The
result is confirmed with the studies by [5], [10] show
the subjective norm is the most influential factor on
traveler' intention to uses public transit. It is noticed
that in Asian countries, an age of traveler is involved
in intention. however, samples are mostly elderly, andthey focus on people who are important to themgreater than Self-determination. This result showsthat also consistent with the nature of Thai culture associalism elderly society.
Besides, this study also found that perceived easeof use and perceived usefulness appeared to have asignificant effect on attitude. In other words, belief

631

SEE - Nagoya, Japan, Nov.12-14, 2018

lacked understanding about the elderly. It is difficult
to push the elderly policy into concretely.

pp. 319–340.
[9] Hair JF, Black WC, Babin BJ, Anderson RE,
Tatham RL. Multivariate data analysis. 6th ed.
Upper Saddle River, New Jersey: Pearson
Prentice Hall; 2006.
[10] Kaewkluengklom,
R.,
Satiennam,
W.,
Jaensirisak, S. and Satiennam,T. Influence of
psychological factors on mode choice behaviors:
Case study of BRT in Khon Kaen City, Thailand,
Preparing to submit in Proceedings of the 14th
World Conference on Transport Research in
TRPRO, Shanghai, China; July 10-15, 2016.
[11] Koppelman, F. and J. Hauser (1979). Destination
Choice for Non-Grocery-Shopping Trips.
Transportation Research Record 673: pp. 157165.
[12] Kulachai W. (2015) Public Transportation
System for Aging People Is It a Neglected Policy.
Academic Resources, Prince of Songkla
University. Thailand.
[13] National Statistical Office. (2015). Preliminary
results of the elderly population survey inThailand 2014.
[14] Sustainable Infrastructure Research andDevelopment Center (SIRDC) (2016) The study
detailed design and impact on the environment ofpublic transport in Khon Kaen city. Khon Kaen
University, Thailand.
[15] Venkatesh, V., Morris, M.G., Davis, G.B., Davis,
F.D., 2003. User acceptance of information
technology: toward a unified view. MIS
Quarterly 27 (3), pp. 425–478.
[16] Wadie, Nasri., Lanouar Charfeddine. (2012)
Factors affecting the adoption of Internet
banking in Tunisia: An integration theory ofacceptance model and theory of planned

REFERENCES[1] Ajzen, I. (1991). A theory of planned behavior.
Organizational Behaviour and Human Decision
Processes, 50, pp. 179–211.
[2] Bamberg, S., & Schmidt, P. (2003). Incentives,
morality or habit? Predicting students’ car use
for university routes with the models of Ajzen,
Schwartz and Triandis. Environment andBehavior, 35, pp. 264–285.
[3] Ben-Akiva, Walker and Bernardino. (1997)
Integration of Choice and Latent Variable
Model, USA: MIT Press.
[4] Ben-Akiva, M. and B. Boccara (1987).
Integrated Framework for Travel Behavior
Analysis. IATBR Conference, Aix-en-Provence,France.
[5] Ching-Fu Chen and Wei-Hsiang Chao. (2011)
Using the theory of planned behavior,technology acceptance model and habit to
examine switching intentions toward public
transit. Transportation Research Part F; (14), pp.
128–137.
[6] Chun-Der Chen, J., Yi-wen Fan., Cheng-Kiang
Farn. (2007) Predicting electronic toll collection
service adoption An integration of thetechnology acceptance model and the theory ofplanned behavior. Transportation Research PartC, 15(2007), pp. 300-311.
[7] Chun-Hua Hsiao and Chyan Yang. (2010)
Predicting the travel intention to take HighSpeed
Rail
among
collegestudents.
Transportation Research Part C; (13), pp. 227287.
[8] Davis, F.D., 1989. Perceived usefulness,
perceived ease of use and user acceptance of
information technology. MIS Quarterly 13 (3),632

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov. 12-14, 2018, ISBN: 978-4-909106018 C3051

DEVELOPMENT OF A CRACK REPAIR METHODUSING YEAST-INDUCED CALCIUM CARBONATE PRECIPITATION
AND MODELING THE PRECIPITATION OF CALCIUM CARBONATE
USING GEOCHEMICAL SIMULATION
Yoko Sakakihara1, Shinichirou Okazaki2
Graduate school of engineering, Kagawa University, Japan;
2
Faculty of engineering and design, Kagawa University, Japan;
1

ABSTRACT
Many confirmed cases of water leakage occur from the gap between the high column and the floor slab of abridge. Although the gap is not classified as deterioration, some restoration for the gap is required. If the water
circulation from the leakage in the crack is insufficient, deterioration of the reinforced concrete becomes fasterthan expected. Even though this is not an urgent issue, an affordable countermeasure is needed. In this study, theapplicability of bio-grout using microbial metabolism for crack repairs was investigated. Bio-grout is a repair
material using microbial metabolism, mainly based on water. Therefore, bio-grout is expected to penetrate cracks
more easily due to a capillary tension that is quite different from conventional inorganic or organic grout.
Therefore, it is unnecessary to press fit the grout into cracks, and this grout is environmentally friendly. This study
examined the mixture proportion of the bio-grout used to produce a significant amount of calcium carbonate.
Further, the precipitation amount of calcium carbonate was investigated via sedimentation analysis using ageochemical code. The simulation model based on the geochemical code successfully reproduced, the precipitation
amount of calcium carbonate with reasonable precision.
Keywords: Grout, Calcium carbonate, Calcite, Microbial metabolism

The purpose of this research is to design a repair
model using a geochemical code to develop a more
optimal blending condition. [10]INTRODUCTION
In Japan, post-war reconstructed bridges are
currently in a state of deterioration, and restorationis required. However, the municipalities in Japan are
in severe financial straits; hence, allocating asufficient budget for repair expenses is difficult andthus, sufficient repair measures for all bridges areunattainable.
Although not classified as deterioration, many
reported cases of water leakage occur from the gap
between the high column and the floor slab of abridge; it is not a pressing matter, but restorationplans and action are required. Due to inadequate
water circulation in the crack, the deterioration of thereinforced concrete progresses faster than expected.
Therefore, some low-cost countermeasures are
required.
A conventional crack-repairing method is to fill
the crack with epoxy resin via press fitting, which islaborious and expensive, mainly due to the materialcost. It may also cause a leakage of the grout andproduce a pervasive smell. Therefore, a method of
repairing gaps and cracks using naturally derived
bio-grout is proposed herein. In previous studies,
calcium carbonate was precipitated from bio-grout,but that was not enough to repair the gaps. [1]-[9]MATERIALSAND

METHOD

Bio-grout formation comprises two reactions:biological and chemical. The former involves
microorganisms consuming nutrients and releasing
carbon dioxide, whereas the latter involves
producing calcium carbonate from the generated
carbon dioxide reacting with a calcium source. The
chemical reactions can be simulated using
PHREEQC, and they are outlined as follows:
C𝑂𝑂2 + 𝐻𝐻2 O ⇄ 𝐻𝐻2 𝐶𝐶𝑂𝑂3(1)

𝐻𝐻𝐻𝐻𝐻𝐻3− ⇄ 𝐶𝐶𝐶𝐶32− + 𝐻𝐻 +(3)

𝐻𝐻2 𝐶𝐶𝐶𝐶3 ⇄ 𝐻𝐻𝐶𝐶𝐶𝐶3− + 𝐻𝐻 +𝐶𝐶𝐶𝐶2− + 𝐶𝐶𝐶𝐶32− ⇄ 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶3

(2)

(4)

In producing bio-grout, we referred to thereaction condition as shown in Table 1. [1]The buffer is added here because of the633

SEE - Nagoya, Japan, Nov.12-14, 2018

precipitation of calcium carbonate is a reversible
reaction, and as the pH decreases, calcium carbonate
dissolves, as shown in Eq. (4). Therefore, tomaintain the production of calcium carbonate,Tris(hydroxymethyl) aminomethane (THAM) is
added to capture the released protons to induce morecarbonate ion (refer to Eq. (2) and (3)).

Following this, the mixture was kept at a constanttemperature. Finally, the pH and the amount ofcalcium carbonate thus produced were measured.
pH change and crystal appearance confirmed theprecipitation of calcium carbonate, and theprecipitation amount was measured. Further analysisof the obtained crystals was done via X-ray
diffraction (XRD) to examine the crystal structure.

Table 1 Formulation of bio-grout as reference.
Materials
Con.
Saccharomyces
9.0 g/L
Cerevisiae
Nutrient
D-glucose
0.10 M
Calcium
Calcium acetate
0.05 M
BufferTris(hydroxymethyl)
0.5 Maminomethane
Note: The pH was set to 9.0 and the experimental
temperature was 20°C.

RESULTSANDDISCUSSION

MicrobeExperimental Results
From Fig. 1 and Fig. 2, the pH remarkably
decreased over time in Cases 1, 2, and 4.
0h

24h

48h

72h

9
8

Experiments with Bio-grout

7

pH

In this study, the type of microbe and nutrient
used were fixed. The calcium source, bufferconcentration, pH adjuster of the buffer, and reaction
temperature were varied.
Table 2 shows the condition of the bio-grout.
Table 3 lists the conditions of the experiments.

6
5
4
3

Case 1Case 3

Case 5

Table 2 Proposed formulation of bio-grout.
Fig. 1
MicrobeNutrient
Calcium
BufferMaterials
Saccharomyces cerevisiae
D-glucose
Calcium lactate
Tris(hydroxymethyl)aminomethaneCon.
6.0 g/L
0.4 M
0.2 M
VariedpH change trends for different experimental
cases when the reaction was maintained at
25°C.

9
8
7

pH

Table 3 Different experimental conditions using thecomponents from Table 2.

65Case 1Case 2
Case 3
Case 4
Case 5
Case 6

Con. of THAM
0.3 M THAM
0.3 M THAM
0.75 M THAM
0.75 M THAM

Temp.
25°C
40°C
25°C
40°C
25°C
40°C

4
3

Fig. 2The experiment began by adding the pH adjuster
into the buffer solution to set a specific pH. 40 mLof the buffer solution was taken into a conical tube,
to which D-glucose and calcium source were added.
Next, baker’s yeast (S. cervisiae) was added.

Case 2

Case 4

Case 6

pH change trends for different experimental
cases when the reaction was maintained at
40°C.

Adding THAM resulted in a gentler pH change.
Figures 1 and 2 show that the higher theconcentration, the slower the pH change. For
example, when the temperature was 40°C, theconcentration of carbon dioxide increased and many
634

SEE - Nagoya, Japan, Nov.12-14, 2018

Peerecipitation (mol/liter)

protons were generated because the microbes
breathed more actively thereby producing morecarbon dioxide. Figure 2 shows that using only 0.3M
THAM resulted in a thin concentration andinsufficient effect. However, 0.75M THAM waseffective.
In Cases 1 and 2 where the buffer was not
introduced, calcite and aragonite, which are crystalsof calcium carbonate, did not precipitate (Figs. 3 and
4).
0h

0.08

24h

48h

aqueous, mineral, gas, solid-solution, surfacecomplexation, and ion-exchange equilibria;
specified mole transfers of reactants; kineticallycontrolled reactions; mixing of solutions; pressure
and temperature changes; inverse modeling.

Simulation Results Obtained via PHREEQC
In the simulation, besides the calcium ion
concentration, the pH value and the temperature
obtained from the experiment were used. THAM
was not found in the database of PHREEQC; hence,an assumed compound as a pseudo buffer was set
and used.
Similar to the experiment, precipitation of calcite
and aragonite was not observed in Cases 1 and 2(without buffer), and the change in pH wasremarkable (Fig. 5).
However, the addition of a pseudo buffer resulted
in a gentler pH drop, as depicted in Fig. 6, and theprecipitation amount of calcite, a crystal of calcium
carbonate, is shown in Fig. 7. Furthermore, noprecipitation of aragonite was observed in any of thecases.

72h

0.06
0.04
0.02
0

Fig. 3

Case 1Case 3

Case 5

Precipitation trend of calcium carbonate at
25°C

8.00

0.10

7.00

pH

Precipitation (mol/liter)

9.00
0.12

0.08

6.00
5.00

0.06

4.00

0.04

3.00

0.02
0.00

0.00

0.05

0.10

Case 20.15

0.20

Addition amount of gas carbon dioxide(mol/liter)
Case 2

Case 4

Case 6

Fig. 5
Fig. 4

Case 1

Precipitation trend of calcium carbonate at
40°C

pH change in Cases 1 and 2

9Case 3
Case 4
Case 5
Case 68pH

Further analysis of the precipitates via XRD
revealed that only calcite is a crystal of the produced
calcium carbonate.

765Geochemical Code: PHREEQC

40.00

PHREEQC [11] is a computer program written
in the C and C++ programming languages that isdesigned to perform various aqueous geochemical
calculations.
PHREEQC is capable of speciation andsaturation-index calculations; batch-reaction and
one-dimensional (1D) transport calculations withreversible and irreversible reactions, including

0.05

0.10

0.15

0.20

Addition amount of gas carbon dioxide(mol/liter)Fig. 6635

pH change in Cases 3-6

Precipitation amount of calcite(mol/liter)

SEE - Nagoya, Japan, Nov.12-14, 2018

0.12

Comparison
Between
Simulation Results

Case 6
Case 5
Case 4
Case 3

0.10
0.08

0.04
0.02
0.00

0.04

0.08

0.12

Addition amount of carbon dioxide(mol/liter)

Precipitation amount of calcite in Cases 3-6

Pripitation (mol/liter)(1) Comparison of Case 3(2) Comparison of Case 4

Simulation
Experiment

0.10
0.08
0.06
0.04
0.02
0.00

9

8

7

6

5

Preipitation (mol/liter)Fig. 7andComparing the experimental values with thesimulation values, where x-axis denotes pH and yaxis denotes the precipitation of calcite (Fig. 8), it
can be observed that the simulation values accurately
followed the experimental values.
Based on these results, the amount ofprecipitation produced from the bio-grout could be
predicted to some extent from the simulation. In
addition, Fig. 8 shows that maximum amount ofprecipitation was obtained between pH 6 and 7;
however, when the pH decreased to 6 or less, thecalcite dissolved, and the amount of precipitation
decreased.

0.06

0.00

Experimental

0.10
0.08
0.06
0.04
0.02
0.00

pH
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0

8

7

6

5

7

6

5

pH

(4) Comparison of Case 6
0.12

Precipitation(mol/liter)

Precipitation(mol/liter)(3) Comparison of Case 5

9

9

8.5

8

pH

7.5

0.10
0.08
0.06
0.04
0.02
0.00

7

9

8

pH

Fig. 8 Comparison of the precipitation amount between experimental and simulation results as a function of pH

A further study has been planned to test the crack
repair in concrete using the new bio-grout.

CONCLUSIONS
The results show that the simulation model
followed the same trend as the experimental
outcome. In conclusion, the simulation model could
be used to predict the amount of precipitation fromthe bio-grout to some extent.
The simulation also revealed that increasing the
precipitation amount of calcium carbonate by setting
a higher temperature and preventing the pH fromdecreasing is possible.

ACKNOWLEDGMENT
We would like to appreciate the great support forthis research provided by the JSPS Grant-In-Aid for
Scientific Research (B) task number 15h04025.

636

SEE - Nagoya, Japan, Nov.12-14, 2018of microbial metabolic processes to repair
concrete joint leakage, Advanced Material
Research, 845, 2013, pp. 158-162[6] Ujike I., Kubo F., Kawai K., and Okazaki S.,
Influencing factors affecting microbial
metabolic processes of bio materials used forleakage repairs, Concrete Solutions, 2014, pp.
127-133[7] Wiktor V. and Jonkers, H.M., Quantification of
crack healing concrete, Cement & Concrete
Composites, 33(7), 2010, pp. 763-770[8] Wiktor V. and Jonkers, H.M., Field
performance of Bacteria-based repair system;
Pilot study in a parking garage, Case Studies inConstruction Materials, 2, 2015, pp. 11-17[9] Wiktor V. and Jonkers H.M., Assessment of thefunctionality of bacteria-based repair system forconcrete through ESEM analysis, 15th Euro
Seminor of Microscopy Applied to Building
Materials, 2015, pp. 165-169[10] Akiyama M. and Kawasaki S., Application ofnumerical simulation of microbial reaction tobiogrout with ureolytic bacteria, Japanese
Geotechnical Journal, 12(3), 2017, pp. 337-349[11] Tokoro Chiharu, Introduction to reaction
analysis by PHREEQC for beginners, Tokyo, R& D support center, pp. 1-133

REFERENCES[1] Putri P. Y., Kawai K., Ujike I., and Yamamoto
S., Effect of temperature on precipitation rate of
calcium carbonate produced through microbial
metabolic process of bio materials, Civil
Engineering Dimension, 18(2), 2016, pp. 103108[2] Bang S. S, Galinat J. K, and Ramakrishnan V,
Calcite precipitation induced by polyurethaneimmobilized bacillus pasteurii, Enzyme andMicrobial Technology, Vol. 28, 2001, pp. 404409[3] Kawaai K., Ujike I., Putri P.Y., and Yamamoto
S., Some considerations on precipitation rate of
calcium carbonate in bio-based materials used
for concrete repair, Concrete Solutions 2016:
Proceeding of 6th International Conference on
Concrete Repair, Aristotle University ofThessaloniki, Greece, June 20-22, 2016, pp.
580-587[4] Kawasaki S., Muaro A., Hiroyoshi N.,
Taunekawa M., and Kaneko K., Fundamental
study on novel grout cementing due to microbial
metabolism, Journal of Japan Society ofEngineering Geology, 47(1), 2006, pp. 2-12
[5] Kubo K., Okazaki S., and Ujike I., Development637

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ELECTRET CONDENSER MICROPHONE AS SENSOR IN ARTERIALPULSE RECORDING DEVICE
Erni Yudaningtyas1, Waru Djuriatno1, Achsanul Khabib2 and Dionysius J.D.H. Santjojo3
1Department of Electrical Engineering, University of Brawijaya, Jl. M. T. Haryono 167, Malang, Indonesia
2Department of Electrical Engineering, State Polytechnic of Malang, Jl. Soekarno - Hatta 9, Malang-Indonesia
3Department of Physics, University of Brawijaya, Jl. Veteran, Malang-Indonesia

ABSTRACTAn Electret condenser microphone (ECM) was designed to pick up the signal from the human radial arterial
pulse. The ECM pick up system was equipped with an instrumental amplifier and a signal processing system.
The characteristic of the ECM was analyzed using a sixth order polynomial equation. The equation was used toreconstruct the signal which flattened the frequency response at the range of 0.5-4.5 Hz. The signal processing
consists of an FTT, a peak detection and a sixth order an anti-polynomial computational unit which are
implemented in the computer. The gain was one with the frequency response closed to 0 dB for the designatedfrequency range. The error reached the minimum of 0.21 % at 1.5 Hz. It is maximum at the lowest frequency of
0.5 Hz.
Keywords: Sensor, ECM, an Arterial pulse signal, Frequency response

INTRODUCTION
Pulses present in several parts of the body, one ofthem is located in the radial artery. The pulse signal
is a mechanical signal that has a frequency range of
0.5-4.5 Hz. A sensor is required to capture
mechanical signal is Electret Condenser Microphone(ECM). The ECM has a relatively flat frequency
response within the audio frequency range within thefrequency range of 50-20,000 Hz.
ECM has been long used as part of an
instrumentation. A study, compared the frequency
response of ECM which has different diameters, i.e.,½ inch and ¼ inch. The results show that the ½ inch
ECM has a sensitivity of ± 0.2 dB in range of 10Hz 17kHz. On the other hand, the ¼ inch ECM showed
the sensitivity within ± 0.3 dB from 100 Hz - 30 kHz.
[1]. It can be inferred that large dimensions cancapture a good signal.
Other factors which have to be considered are theeffects due to the acoustic and the air gap between
the diaphragm and the back plate. A novel design of
the ECM provides a number of the acoustic holes inthe diaphragm. The number of the holes, theirdistribution and the air gap determine the optimal
performance of the microphone. The sensitivity ofthe optimized structure was -41.6dB with a pull-in
voltage of 12V, and the frequency response was flatat 20Hz-20.6kHz [2].
In a preliminary study, the ECM has been used
to record the pulse in human radial arterial. The
results showed an expected pulse signal recording
similar to that of Shusaka Nomura [3]. Fig. 1 shows
the results of recording arterial pulse signals.

Fig. 1

ECM test arterial pulse of the human test.

At present, some researchers have proposed apulse signal measurement system using the ECM.
Eliminating noises and interferences is critical in theutilization of the ECM. One of the studies, use asoundproof sponge that is placed in a cylinder tube
as an intermediate medium to isolate the captured
pulse signals [4][5]. The model has advantages interms of low cost and simple. However, the design
has a large dimension because it should provide
enough air passage between the soundproof totransfer the acoustic wave. A smaller design can beby using a Micro Electro Mechanical System
Electret Condenser Microphone (MEMS-ECM) as asensor to detect the arterial pulse. The MEMS-ECM
is a type of microphone that has a small dimensionthat is 1.250 x 4720 x 3760 mm and has a frequency
response at about -35 dB [3].
In the pulse measurement system, the ECM
should have a frequency response at the range of
0.5-4.5 Hz to capture the mechanical signal
accurately. Further study was carried out to test theECM for its frequency response in the range of 0.54.5 Hz. Other researcher, tested the performance of638

SEE - Nagoya, Japan, Nov.12-14, 2018

the ECM in the extremely low-frequency region
using a computerized system. In this case, the ECM
captured signals at frequencies ranging from 0.5 to
20 Hz. Reasonably good frequency response wasachieved by removing the plastic cover and dust
filter of ECM [6]. However, the technique has
disadvantages, because the it reduced the signal tonoise ratio.
In this presents study, a new arterial pulse sensor
processing was added into the sensor design, where
the output flattened the amplitude of the ECM in therange frequency of 0.5-4.5 Hz.

rubber has an acoustic impedance of 1.4 MRayl
allowing the wave travels at the speed of 0.94
km/s[8]. Fig. 4 shows the placement of the soft
silicone rubber as the medium between the lowfrequency speakers and the ECM. The holder serves
as a support to keep the ECM in place.

METHODOLOGYThe ECM used in this study was KUC4023 fromHOSIDEN with the specification shown in Table 1[7]. The sensitivity of the ECM over the design
frequency which is from 50 Hz to 20 KHz is shownin Fig 2. A reduction of sensitivity is noticed in theband range of 5000-20000 Hz.

Fig. 2

Fig. 4

Photograph of low-frequency Speaker and
ECM

The signal from the ECM at the low frequency
was quite small, so we designed an instrumental
amplifier to amplify the small signal. Figure 5 shows
the schematic wiring of signal instrumental amplifierthat consists of 2 OP Amp. The function of thiscircuit is to eliminate low noise frequency andreducing the noise interference from the power
supplyECM Frequency response Fabrication [7].

However, for the pulse reading system, theresponse of the ECM at the range of 0.5-4.5 Hz has
to be determined. A testing system consisting of asignal generator, a low-frequency amplifier, a lowfrequency speaker as the mechanical vibration
source, an instrumental amplifier, and an
oscilloscope. The system is shown in Fig. 3.
Fig. 5

Fig. 3

Schematic wiring of the signal instrumental
amplifier

To obtain an accurate signal response, we select ahigh input impedance OP Amp which has a typicalslew rate to match the high impedance output of theECM. The selected OP Amp was TL 062 from
Texas Instrument with the specification: typicalsupply current: 200 μA (pre-amplifier), High Input
Impedance: JFET-Input Stage and high slew rate:
3.5 V/μs Typical. Some passive components required
such as R1 is 50 KΩ, R2 is 1 KΩ, R3 is 200 KΩ, R4
is 500 Ω, R5 is 500 Ω, and C1 is 1 µF.
Second setup of the study was connecting theamplified signal to a computer for digital signal
processing shown in Fig. 6.

Photograph of the setup of the ECM testing

The signal was amplified by a low-frequency
amplifier which drives the low frequency speaker.
The vibration from this speaker is sensed by the
ECM through a soft silicon rubber. The soft siliconrubber functioned as a wave medium between the
low-frequency speaker and the ECM. The Silicon
639

SEE - Nagoya, Japan, Nov.12-14, 2018

be interpreted in the polynomial equation. The
amplitude of the ECM decreased when thefrequency decreased. The smallest amplitude of theECM characteristic is 0.92 Vpp (peak to peak) andthe upper point amplitude 2.16 Vpp.
Mathematical Equation of ECM Characteristic

Fig. 6

Based on Fig. 7, we can approach the characterof the ECM into a polynomial equation. The
equation consists of sixth order polynomial equation
as given by the following equation:

Experimental setups of ECM test

6

5

y = 0.0093 x − 0.3226 x + 3.0306 x

Table 1 shows the test condition of theexperimental setup. The test condition consists ofspecifications of silicone rubber, laptop specification,
ECM specification and Digital storage oscilloscope.

3+ 2.9419 x − 192.06 x

4

2

(1)

+ 1081.7 x + 24.444

Table 1 Test condition of the experimental setup
Items
Specification
Signal Generator
K-Moon DDS Signal
Generator/Counter (Dual
Channel)Computer specifications
Intel core i5 CPU 2.30
GHz, 4 GB RAM
ECM
sensitivity: −45 dB,
impedance: 1.0 KΩ
PSU: 4.5 VDC
Current : 0.8 mA
Oscilloscope
Digital Storage
Oscilloscope Hantek
MSO5074F
4 Channel
70 MHz, 1 GSa/s

Signal Reconstruction
From Eq. (1), we reconstruct signal by the using
an anti-polynomial equation. The aim of the signal
reconstruction was obtaining consistency of
frequency response at the range frequency range of
0.5-4.5 Hz. Another goal of the anti-polynomial
equation is to convert the signal to digital mode, sothat it is suitable for the digital processing. The antipolynomial equation is formulated as follow:
6

5

3

2

y = 0.0001x − 0.0041x + 0.0576 x− 0.04274 x + 1.7692 x

4(2)− 3.9478 x + 4.9001
Based on Eq. 2, we can construct the anti
polynomial graph as follows:

Measurement of the ECM Signal
In Fig. 3, the output signal of the ECM wasmeasured by means of an oscilloscope. The
amplitude at different frequencies are displayed inFig. 7. The character of the ECM is critical for thedesign of a signal processing.

Fig. 8Anti polynomial graph at a frequency rangeof 0.5-4.5 Hz

Based on Eq. 1 and Eq. 2, we can design thesignal processing system. The general principle ofthe system is using a Fast Fourier Transform (FFT)
and an inverse Fast Fourier Transform (IFFT). The
FFT is a numerical computation which converts thetime domain periodic signals into frequency
domains data [9]. The FFT is performed forFig. 7

Characteristic graph ECM at a frequency
range of 0.5-4.5 Hz
Based on Fig. 7, the characteristic of ECM can
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SEE - Nagoya, Japan, Nov.12-14, 2018

application purpose in signal processing and data
manipulation embedded in a Digital Signal
Processing (DSP) or a microcontroller [10]. On theother hand, the IFFT is the inverse processing of the
FFT into the time domain. The implementation of
the IFFT on a DSP or microcontroller is carried out
using a convolution and a correlation [10],respectively. The FFT function is represent by
equation y(k) where x(k-i) is the input of the filter isthe unit pulse response of the filter. Then, x (k + i) is
the input signal and the pattern to be found in thesignal is represented by h(i).

RESULT AND DISCUSSION
The amplitude of ECM before and after
processing are tested and analyzed. The results showthat the proposed system has a good response as
given in Table 1. From the Table 1, we can definethat the amplitude before processing is decreased
when the frequency is reduced. On the other hand,the amplitude after processing is relatively constantat a range of 2 Volt.
Table 1 The amplitude of ECM before and after
processing
Frequency Amplitude before Amplitude after(Hz)
processing (V)processing (V)
0.5
0.92
2.000
1
1.48
2.057
1.5
1.8
2.080
2
1.94
2.093
2.5
2.04
2.100
3
2.08
2.102
3.5
2.14
2.108
4
2.16
2.117
4.5
2.1
2.102

M −1

y (k ) =∑ x(k − i) * h(i)

(3)

i =0

M −1

y (k ) =∑ x(k + i) * h(i)

(4)

i =0

Figure 9 describes the steps
implementation of equations 3 and 4.

Fig. 9forthe

From Table 1, we can calculate the gain value of
ECM amplitude. The Voltage gain is determining in
Av, where Vo is the output voltage and Vi is the
input voltage. We can obtain the Av by using theupper of the amplitude of ECM as Vi. In this case,the upper of amplitude is 2.16 Volt. To determining
the Voltage gain, we can calculate the value of Vo
and Vi by using the following equations:

Block diagram of General frequency
domain processing in DSP [10].

This processing system has a high efficiency
because it has the advantage of reducing signal
processing computing, increase signal processing
speed and reduce power consumption on DSP [11].
To get a flat response, the FFT must be multipliedby the sixth order anti polynomial equation andconverted to the time domain using IFFT. The
system of signal processing is shown in Fig. 9.

Fig. 9

Av =

Vo

(3)

Vi
Based on Eq. (3), the gain of the system can beshown at Fig. 10. The gain of the system after
processing is relatively flat in the range of 1.

System of signal processing

The Reconstructed Signal
The reconstructed signal of the system is shownand compare with the signal before processing in the
result and discussion below.

Fig. 10 Gain of before and after processing
The magnitude of the ECM frequency response
in decibel (dB) or ECM (dB) can be determined by
641

SEE - Nagoya, Japan, Nov.12-14, 2018using Eq. 4, where Vo is the output voltage and Vi is
the input voltage.

ECM (dB) = 20 log10

Vo
ViThe error value is determined in Eq. (5) as follows:

Error =

(4)ofbeforeandx100% (5)V average(after )Frequency response ECM (dB) at a frequency
range of 0.5-4.5 Hz is shown in Fig. 11. The
frequency response before processing was decreased.
However, after processing frequency response of
ECM (dB) is relatively flat at the range around 0 dB.

Fig. 11 Freq response
processing

V after − V average(after )Figure 13 is absolute error value from theexperiment. The error value from the system is about
0.21-4.05%. The error is caused by the input
character of the ECM and its sixth-order polynomial
representation. Furthermore, it also affected by thesignal manipulation process which is themultiplication of the sixth-order anti-polynomial andthe FFT output. The sixth order polynomial
representation is the approach to the original signal.
The error can be reduced by applying a higher orderpolynomial. In previous research [12] Yang Mei
applied an eighth-order polynomial implemented in
DSP TMS320C67x using 'C67x library functions
generates over 60% and up to 70.2% of total TI
library function cycles. So it can be concluded thatsixth order polynomial orders are capable of being
implemented in the DSP processor.

after

Based on Eq. (4), The output Voltage after
processing is shown in Fig. 12. The output Voltage
before processing is compared to output voltage
after processing. In this figure, the Voltage before
processing is decreased. However, the output
Voltage after processing is relatively flat in therange of 2.1 Volt.

Fig. 13 The error of signal processing
CONCLUSION
In this study, ECM has been used as a sensor torecord the signal of the human radial arterial pulse.
To improve the output voltage amplitude, a signal
reconstruction is required to obtain consistency of
frequency response at the range frequency range of
0.5-4.5 Hz. The output amplitude of the system isflat around 2.1 Volt in the range frequency of 0.54.5 Hz, the frequency response ECM is flat at 0 dB
and the system has error value is ranging from 0.214.05%
This device is able to provide a better choice forarterial pulse sensor because of several advantages,
such as simple, cheap, compact, portable and easy touse.
ACKNOWLEDGMENTS

Fig. 12 The output amplitude before and after
processing.

The research project was supported by
Department of Electrical Engineering, University ofBrawijaya Malang.

Base on Figure 12, the output voltage and input
voltage are compared to get an absolute error value.
642

SEE - Nagoya, Japan, Nov.12-14, 2018

frequency region of an electret condenser
microphone,” Sensors, vol. 11, no. 1, pp. 623–
637, 2011.
[7] E. C. Microphone, “Guide for Electret
Condenser Microphones,” Current.
[8] N. S. Inc, Acoustic Properties ofCommonMaterials. 2013. [Online]. Available:
http://www.ndtsystems.com/Ref. .
[9] E. Yudaningtyas, D. H. Santjojo, W. Djuriatno,
I. Siradjuddin, and M. R. Hidayatullah,“Identification of Pulse Frequency Spectrum ofChronic Kidney Disease Patients Measured at
TCM Points Using FFT Processing,” pp. 169–
172, 2017.
[10] W. W. S. and J. M. Smith, Handbook of RealTime Fast Fourier Transforms: Algorithms to
Product Testing. Wiley-IEEE Press, 1995.
[11] A. Fertner, “Computationally Efficient
Methods for Analysis and Synthesis of Real
Signals Using FFT and IFFT,” vol. 47, no. 4,
pp. 1061–1064, 1999.
[12] M. Yang, J. Wang, Y. Wang, and S. Q. Zheng,“Optimized Parallel Implementation of
Polynomial Approximation Math Functions on
a DSP Processor I-,” pp. 344–347, 2001.

REFERENCES
[1]

[2]

[3]

[4]

[5]

[6]

A. Ohyagi, D. Adachi, H. Kodama, and Y.
Yasuno, “Electret Condenser Microphones for
Measurement Instruments,” p. 185.
D. Zhang, Q. Fang, and X. He, “6 imulation
and Optimization of a Micro-machined Silicon
Condenser Microphone Using a Perforated
Diaphragm,” pp. 1682–1687, 2014.
S. Nomura, Y. Hanasaka, and H. Ogawa,“Multiple pulse wave measurement toward
estimating condition of human arteries,” Proc.
IADIS Int. Conf. e-Health 2013, EH 2013, Part
IADIS Multi Conf. Comput. Sci. Inf. Syst. 2013,MCCSIS 2013, vol. 11, no. 3, pp. 29–36, 2013.
Y. Y. Chen and R. S. Chang, “A study of new
pulse
auscultation
system,”Sensors(Switzerland), vol. 15, no. 4, pp. 8712–8731,
2015.
W.-M. Lue, Jiann-Hwa; Chang, Rong Seng;
Ko, Tai-Chuan; Su, Yu-Sheng; Cherng, Shen;
Cheng,“SimpleTwo-ChannelSound
Detectors Applying to Pulse Measurement,”
vol. 11, no. 4, pp. 3–5, 2014.
Y. N. Jeng, T. M. Yang, and S. Y. Lee,
“Response identification in the extremely low

6434th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EXPERIMENTAL INVESTIGATION OF HOLLOW BRICK
UNREINFORCED MASONRY BUILDING RETROFITTED BYFERROCEMENT LAYERS
Fauzan1, Abdul Hakam2, Febrin Anas Ismail3 and Jonathan Vincensius Osman4
1,2,3,4Engineering Faculty, University of Andalas, Indonesia.

ABSTRACTA retrofitting method to hollow brick unreinforced Masonry (URM) building has been developed using
ferrocement layers. In this method, the ferrocement layers were applied to the URM building with the bandage
system. An experimental study on hollow brick URM houses with and without ferrocement layers was
conducted. Two specimens of a quarter scale hollow brick house models consisted of four walls with size 104cm
x 110cm were constructed. The first model (B1) is the original hollow brick unreinforced masonry house without
mortar plaster, and the second model (B2) is the same masonry house retrofitted by providing bandage
ferrocement layers on both sides of the walls which are acting as sandwich structures. Both specimens were
tested by using a shaking table (304x190) cm2 with input motions from 0.3g to 0.6g. The test results show thatthe hollow brick URM house strengthened by using bandage ferrocement layers have excellent performance
without any damage up to input motion 0.6g. For the original URM house model, meanwhile, the damage wasinitially found near the door opening at input motion 0.3g and the applied additional uniform load of 200 kg on
the top of the specimen. Then, the cracks were developed and spread to the east side of the wall with the increaseof the uniform load and finally, the house model collapsed at input motion 0.6g. This results indicated that theferrocement layer significantly enhancement in ductility of hollow brick URM house model and effective inpreventing the collapse of the hollow brick masonry walls when the earthquakes occur.
Keywords: Unreinforced Masonry (URM) Building, Hollow Brick, Earthquake, Retrofit, Ferrocement Layers,
Bandage System.

INTRODUCTION
Unreinforced masonry (URM) is among the mostcommonly used building materials in many otherdeveloping countries including Indonesia. Most
URM buildings are built with little or no
consideration for seismic loading, and these are notcapable of resisting the expected seismic actions.
The major share of the loss of human lives andproperty during past earthquakes has been attributed
to poorly constructed URM buildings. [1]Earthquakes that often occur in West Sumatra
province of Indonesia, cause a lot of damage tobuildings, especially simple houses, ranging fromminor damage to heavy damage or uninhabitable. In
general, community houses are built with brick
URM masonry building, as shown in Fig. 1 [2].

The hollow brick house without reinforcement asshown in Fig. 1, is not strong against earthquake
load, because the house has no structural elements
such as beams and columns. The house only has
nonstructural components such as walls, roof, andceiling. The non-structural component of a simple
building is not part of the main load working on a
structure, but this component can be the main causeof the earthquake losses.
Hollow brick has a very heavy material because
it is made of mortar. The behavior of the hollow
brick material is brittle and has almost no ductility,
so the simple building of this brick wall has noresistance to horizontal load or earthquake load that
occurs. Therefore, when an earthquake occurs, thisbuilding can collapse unexpectedly (Fig. 2) [3].

Fig. 1 Hollow Brick Simple House [2]Fig. 2 Collapse of a hollow brick building [3]644SEE - Nagoya, Japan, Nov.12-14, 2018

A common method of seismic strengthening of
URM buildings is the use of horizontal and vertical
strips (known as bandages and splints, respectively)of ferrocement on both sides of walls. The horizontal‘bandages' are applied continuously on all the walls
at lintel, sill, ﬂoor, and roof levels, whereas thevertical ‘splints' are applied at corners and junctionsof walls and along the jambs of the openings [1], [4].
Fig. 3 shows the typical arrangement of splints andbandages in a retroﬁtted URM building. The
ferrocement strips consisting of welded wire mesh(WWM) reinforcement embedded in cement-sandmortar or micro-concrete have a composite action
with the URM resulting in signiﬁcantly enhanced
strength and ductility in shear, rocking and out-ofplane bending. The bandages provide the support to
the walls in out-of-plane action, whereas the splints
enhance the shear and rocking behaviour of the piers.

In previous studies, strengthening of clay brick
URM houses using ferrocement layers has been
conducted. Imai (2014) found that the significant
effect of retrofitting on the clay brick URMbuildings by using ferrocement overlay as bandaging
with galvanized was successfully demonstrated by
the shaking table test [7]. Strengthening a clay URM
house using full ferrocement layers on both sides of
the walls also has been conducted with the resultshow that the ferrocement layers can significantly
improve the performance of the clay brick URMbuilding [8].
In this study, the behavior of two mortar hollow
brick URM houses with and without bandage
ferrocement layers on both sides of the walls undershaking table test was investigated.
TEST SPECIMENS

Fig. 3. Retroﬁtting of a masonry building using
Ferro-cement splints and bandage [1]In the selection action for home improvement, itis certainly influenced by economic aspects. For thesake of the realization of a habitable home, some ofthe people who choose to build a simple house weredestroyed first and then rebuilt, but such a solution
will cost a lot. Another solution is that a simple
house made of hollow brick is reinforced in the formof woven wire mesh. Such a solution is very
efficient and effective because the price of wirelessis relatively cheap and the work can be done by alocal handyman. In addition, the reinforcement using
wire mesh or commonly called ferrocement layer
can be done also on houses that have been built
without reinforcement.
Ferrocement is a plastering layer (mortar) woven
with a wire mesh, so the ferrocement layer has atensile strength. This ferrocement layer is placed in
the position of the beam and column as a substitutefor the structural element or called the bandage
system. Boen introduced a retrofitting method for
non-engineering building using ferrocement withwire mesh as strengthening layers and usedsandwich construction analogy [5]-[6]. The
ferrocement layers consist of mortar and wire mesh,in which the wire mesh was encased in the mortar.
This retrofitting method uses ferrocement skin layers
on walls as bandaging or jacketing.

Fig. 4 Schematic drawings of the test specimen formodel B2, (a) back side wall, (b) left side wall, (c)front side wall, (d) right side wall and (e) detail
section of mortar brick wall with ferrocement layers

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SEE - Nagoya, Japan, Nov.12-14, 2018

There are two URM house models that built on
the shaking table in soil mechanical laboratory ofAndalas University. Both models have a 1:4 scale of
the actual building due to the limitation of theshaking table area. The first model (B1) is theoriginal of an unreinforced masonry building, andthe second (B2) is the same masonry structure
strengthened by providing bandage ferrocement
layers on both walls which are acting as sandwich
structures.
Each model consisted of four walls with size
1.04m x 1.1m. Fig. 4 shows the schematic drawingof masonry walls for model B2. The masonry walls
were made of hollow brick (100x50x25) mm, withthe ratio cement and sand was 1/5 by volume andbonded by using mortar joints with the ratio cement
and sand was 1/4 by volume. The thickness of themortar joints is 5 mm. The width of the ferrocement
bandage layer is 125 mm. The wire mesh wascovered by mortar plaster with the thickness of 5mm. The compressive strength of the hollow brick
was approximately 2.5 MPa and the compressive
strength of mortar to construct the Hollow Brickwall and ferrocement layer was 9.9 MPa. Fig. 5
shows the construction process of test specimens.

According to the National Standardization Agency
of Indonesia for Design Method of Earthquake
Resistance for Buildings and Other Structures (SNI
1729–2012), clause 7.5.3, the load was applied
separately in all two orthogonal directions. The mostcritical load effect due to the direction of earthquake
forces application to the structure is considered to be
fulfilled if the components and foundations aredesigned to carry the following set load
combinations: 100 percent force for one direction
plus 30 percent force for perpendicular directions[10]. Therefore, the slope of the specimens was set
up on 16˚ in the direction of the positive x-axis, as
shown in Fig. 6
TEST PROCEDURE
In this study, both specimens were tested byusing a horizontal uniaxial movement type ofshaking table in Soil Mechanic Laboratory ofAndalas University [9]. Table 1 show, the input
motions with varying the frequency of earthquake,such as the Medium earthquake (ME), and Strong
earthquake (SE), were used as input motions for thistest. The Input motion 0,6g is Peak GroundAcceleration (PGA) of Padang City based onIndonesia Earthquake Map 2017.
The excitation given to the specimens a = 2.94
m/s2, and 5.88 m/s2.
Table 1 Variation of the motions
Type of Input Motion

a m/s 2ME (0.3 g)

2.94

SE (0.6 g)

5.88

The specimens were tested in five stages. The
first stage (P1), both specimens were tested with ME(input motion 0.3g). For the second until forthstages (P2-P4), the specimens were tested with anadditional uniform load using sacks filled with sandon the top of specimens (Fig. 7), that is 200kg,
400kg, and 500 kg, respectively. All specimens on
P1 to P4 were tested with ME (input motion 0.3g).
In the last stage (P5), the specimens were tested
with 500 kg additional load and input motion 0.6g
until the specimen collapsed.

Fig. 5Construction Process of the Specimens B1 and
B2

Sand

G-TraceFig. 6Set-up of specimens on shaking table

Fig. 7 Specimen with additional uniform load using
sacks filled with sand (sandbags)
646

SEE - Nagoya, Japan, Nov.12-14, 2018

Test Specimens with 400 kg Additional Uniform
Load (P3)

RESULT & DISCUSSION
The experimental results are presented in thissection include the observed failure development
and accelerations response of the shaking table thatcause the crack on the specimens.

In this stage, the applied additional uniform load
was increased by 400 kg in both specimens while theapplied input motion was the the same those with theP1 and P2 Test (0.3g). As can be seen in Figs. 11
and 12, the cracks on Specimen B1 was developed
near the door opening and spread on the east side of
the wall (blue marker). Meanwhile, there is no
cracks was observed on Specimen B2.

Test Specimens without Additional Uniform
Load (P1)
The result of the first stage test with input
motion0.3g shows that there is no crack wasappeared on both specimens, as shown in Fig. 8.
From the analysis, the input motion is not strong
enough to damage the specimen.

Fig. 11The specimens with 400 kg additional
uniform loads (P3) at front side after testingFig. 8 The specimens without additional uniform
loads (P1) after testing
Test Specimens with 200 kg Additional Uniform
Load (P2)
In this test, both specimens were applied
additional uniform load of 200 kg on the top of thespecimens and tested with input motion 0.3g. The
result shows that cracks started to appear in the door
openings at front walls on specimen B1 (redmarker), while, Specimen B2 with bandage
ferrocement layers still survived without any
damage, as shown in Figs. 9 and 10.

Fig. 12 The specimens with 400 kg additional
uniform loads (P3) at east side after testing
Test Specimens with 500 kg Additional Uniform
Load (P4)
In this test, both specimens were applied 500 kg
uniform load with input motion 0.3g. In this phase,the cracks on Specimen B1 was developed on thesame location with the P3 test and other cracks wasobserved in the walls of the building, especially on
front and east sides walls (black marker). For
Specimen B2, on the other hand, it still survived
without any damage on the specimen, as shown in
Figs. 13 and 14.

Fig. 9 The specimens with 200 kg additional
uniform loads (P2) at front side after testingFig. 13 The specimens with 500 kg additional
uniform loads (P4) at front side after testingFig. 10 The specimens with 200 kg additional
uniform loads (P2) at east side after testing647

SEE - Nagoya, Japan, Nov.12-14, 2018

shaking table, while the red and green lines
represent the acceleration response of Specimen B1
and B2, respectively.
In the P1 test (without additional load), both
specimens (B1 and B2) have almost the same
behavior of the acceleration responses, as shown in
Fig. 17a. This might be due to the both specimens
still in elastic range without any crack.
The acceleration response on the P2 test showthat at t=10s, the initial crack occurs on specimen
B1 near the door openings with a max = -1,2g, asshown in Fig. 17b. In this stage, the max value ofacceleration (a) on the specimen B2 was 0.9g.
For P3 test, the response of Specimen B1 is alittle bit different with those in Specimen B due todevelopment of cracks and additional new cracks in
Specimen B1 that occurs on 2.5 seconds after
shaking. The specimen B1 has the maximum valueof a = - 0.7g, while the maximum value of a forSpecimen B2 is 0.85g, as shown in Fig. 17c.
Almost similar behavior with P3 test wasobserved on P4 test, as shown in Fig. 17d. At the P4
test, the crack appears on 25s after shaking. The
specimen B1 has the maximum value of a = 0.8 g,
while in Specimen B2, the a maximum is 0.82g.
The increase of input motion from 0.3 g to 0.6
causes the failure of Specimen B1 at t = 4.5 s with amaximum of -1,75g (Fig. 17e). Meanwhile, forSpecimen B2, with a maximum = 1.8g, there is no
crack was observed. From Fig. 17e, the collapse of
the specimen B1 can be seen at suddenly breaks of
the response at the beginning of the test.

Fig. 14 The specimens with 500 kg additional
uniform loads (P4) at east side after testing
Test Specimens with 500 kg Additional Uniform
Load and 0.6g input motions (P5)
In order to observe the failure mode of thespecimens, the applied input motion was increased
by 0.6g while the additional uniform load was thesame those in P4 test (500 kg). In this stage, thecollapse of Specimen B1 was observed (4.5 seconds
shaking), while on no cracks or damage was foundon Specimen B2, as shown in Figs. 15 and 16. This
indicates that the ferrocement layers enhance theseismic behavior (ductility) of the URM house andprevent the collapse of the hollow brick URMbuilding even at a big shakings.

Fig. 15 The specimens with 500 kg additional
uniform loads and 0.6g input motions (P5) at front
side after testing.

Fig. 16The specimens with 500 kg additional
uniform loads and 0.6g input motions (P5) at eastside after testing.
Acceleration Responses
The acceleration response is obtained from theG-trace in the form of an acceleration graph versus
time. Figs. 17a–e show the acceleration response ofboth specimens on P1–P5 test. In these graphs, theblue lines represent the acceleration response on theFig. 17a Acceleration response graph for Base plat,
Specimens B1 and B2 without additional uniform
loads (P1 Test)
648

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 17b Acceleration response graph for shaking
table plat (B), Specimens B1 and B2 with 200 kg
additional uniform loads (P2 Test)

Fig. 17e Acceleration response graph for shaking
table plat (B), Specimens B1 and B2 with 500 kg
additional uniform loads and 0.6g input motions.(P5Test, collapsed)
CONCLUSION
Based on the experimental result, it can beconcluded that:
1. There is no damage was observed for both
specimens on P1 tests because the input
motion is not strong enough to cause thecrack of the specimen.
2. In the second stage (P2 test), cracks begin toappear in the door openings and front walls
on specimen B1, while no crack wasappeared on Specimen B1
3. The crack was developed near opening andspread on the east side of the wall on P3 andP4 tests.
4. Specimen B1 collapsed with input motions
0.6g and 500 kg additional uniform load,
while no damage was observed on specimen
B2 at this stage.
5. The results of this study indicated that theferrocement layer significantly improve theseismic behavior of hollow brick URM housemodel and effective in preventing thecollapse of the hollow brick URM walls
when the earthquakes occur.

Fig. 17c Acceleration response graph for shaking
table plat (B), Specimens B1 and B2 with 400 kg
additional uniform loads (P3 Test)

ACKNOWLEDGEMENTS
The authors would like to acknowledge thefunding support provided by the Institute for
Research and Community Service (LPPM), Andalas
University, Padang, Indonesia.
REFERENCES[1] Kadam S.B, Singh Y, and Li B, Strengtheningof unreinforced masonry using welded wire
mesh and micro-concrete – Behaviour under in-

Fig. 17d Acceleration response graph for shaking
table plat (B), Specimens B1 and B2 with 500 kg
additional uniform loads (P4 Test)

649

SEE - Nagoya, Japan, Nov.12-14, 2018[7] Imai H., A Study of Disaster Mitigation for
Non-Engineered Construction in Developing
Countries: Bridging the Gap between
Experiment and Practice, Doctoral Dissertation,
2014.
[8] Fauzan, Ismail F. A., Hakam A, Zaidir, andAmalia S. H., Experimental Study on Masonry
Building Strengthened with Ferrocement
Layers, International Journal of GEOMATE,
May., 2018, Vol. 14, Issue 45, pp. 84-90[9] Hakam A, Ismail F. A., and Fauzan,
Liquefaction Potential Assessment Based on
Laboratory Test, International Journal of
GEOMATE, Oct., 2016, Vol. 11, Issue 26, pp.
2553-2557[10] National Standardization Agency, Earthquake
Resistance Planning Procedures for Building
Structure and Non-Building Structure (SNI
1726-2012), 2012, Jakarta.

plane action, Construction and Building
Materials, 2014, 54, 247-257[2] Boen T., Earthquake Resistant Design of NonEngineered Buildings In Indonesia. Kamakura,
2001.
[3] TEMPO., Using red brick, is more resistant toearthquakes. https://batamerahputih. wordpress.
com/category/rahasia-batu-bata-merah/.
Retrieved 10 May 2017.
[4] Boen T, et al., Retrofitting Simples Buildings
Damaged by Earthquake, 2nd ed., Jakarta,
Indonesia: WSSI, 2010.
[5] Boen T., Challenges and Potentials ofRetrofitting
Masonry
Non-Engineered
Construction in Indonesia, The University of
Kyoto, Ph.D. thesis, 2014.
[6] Boen T., Arya A. S., and Ishiyama Y.,
Guidelines For Repair, Restoration And Seismic
Retrofitting Of Masonry Buildings, JICA, 2012.

650

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

USING FUZZY MULTI ATTRIBUTE DECISION MAKING (FMADM)
APPROACH FOR RAILWAY TRACK REHABILITATION PLANNING:
A CASE STUDY IN THAILAND
Thawatchai Phanyakit 1 and Thaned Satiennam 2*
1

Department of civil engineering, Faculty of engineering, Khon Kaen University, Khon Kaen, 40002, Thailand

2

Department of civil engineering, Faculty of engineering, Khon Kaen University, Khon Kaen, 40002, Thailand

ABSTRACTRail transportation service from the past to present has been found that freight demand is higher than carrying
capacity. Thus, this is a great chance for rail transportation to be highly promoted. Previously, the State Railwayof Thailand (SRT) was not able to expand the rail transportation service to meet market growth because oflimitation of network and degradation of infrastructure. Therefore, it led to the degradation of infrastructure which
had an effect on service quality; in other words, rail freight transportation rate was considerably low i.e. only 2%[1]. As a result, railway track degradation has become a very interesting research topic for several organizations
to conduct seriously for the purposes of safety and high level of reliability in infrastructure. Degradation factor
was the main point of this study, so Fuzzy Multi Attribute Decision Making Method (FMADM) was used toanalyze railway track defect and degradation to select a rehabilitation plan on schedule. Related research andliterature were reviewed, and questionnaire was designed for asking opinions of the experts working for the State
Railway of Thailand (SRT) including related party in selecting the rehabilitation plan. The findings have revealed
that defect and degradation can lead to a high risk of derailment influenced by usability aspect. Defect code canbe classified into 4 types according to the International Union of Railways (UIC) using the pairwise comparison
method. Each type is different in the starting point and extension direction of railway track crack with contingency
index below 0.01. The experts have specified that the severity of transverse break defect without apparent origin
level of severity is the highest with relative weight of 0.396 followed by star-cracking of fish bolt holes withrelative weight of 0.275, and the least severity is horizontal cracking at web-head with relative weight of 0.142.
The analysis result based on FMADM has indicated that railway track structure replacement plan, considered by
the experts, was better than railway track rehabilitation plan with importance weight of 0 . 6 2 0 and 0 . 3 8 0 ,respectively.
Keywords :Rehabilitation, Fuzzy multi attribute decision making approach (FMADM)

Table 1 Assessment Result of Infrastructure Quality[3]

INTRODUCTION
Comparing the quality level of service between
Thailand and foreign countries, International
Institution for Management (IMD) World
Competitiveness Yearbook 2014 reported that railtransportation development in Thailand was ranked at
43rd place out of 60 countries including having 0.009
kilometer/square kilometer of track network density.
Also, service quality and safety were not satisfying,
and train operation was not punctual as well as train
speed was low i.e. 54 km/hr. and 26 km/hr. forpassenger train and freight train, respectively [2].
Moreover, track network in Thailand is more than 30
years old according to a report on infrastructure
quality by World Economic Forum 2013-2014[3], so
infrastructure quality of track in Thailand was ranked
at 72nd place which was worse than Singapore andMalaysia i.e. 10th and 18th place as shown in Table 1.

Country

Place of Infrastructure Quality
Assessment
Ove
Air
Road Train
Port
rall
port

Singapore

5

7

10

1

2

Malaysia
25
23
18
Thailand
61
52
72
Source: World Economic Forum [3]

21
34

24
56

Rail transportation of northeastern line ofThailand from Thanon Chira juntion to Nong Khaistation has single-track and ballasted-track
characteristic. Statistics of train and weight throughtrack according to the report of warehouse
department, State Railway of Thailand 2007-2016[4]can be seen in Fig. 1
651

SEE - Nagoya, Japan, Nov.12-14, 2018weights trough track
3.76

4.00
3.50
3.00
2.50

2.70
2.06

1.96

2.00

1.70

2.95

2.91
19.01

25.58
2.81
21.82

16.10
1.86

13.15

25.00
20.00
15.00

influencing track degradation as well as risk
prioritization of cracked or broken track based on thestandard of International Union of Railway (UIC) as
shown in Fig. 7 And Fig. 8 shows track rehabilitation
planning.

10.28

1.50

10.00

7.59
5.73

1.00
0.50

2.87

30.00

3.76

2.06

5.00
0.00

0.00
2007

2008

2009

2010

2011

MGT Per Year

2012

2013

2014

2015

2016

MGT Accumulation

Fig.1 Weight through Track of NE Line [4]Railway Track System
Railway track is generally divided into two mainparts: superstructure and substructure. The
superstructure consists of rails, fastening system, railpads, and sleepers. The substructure consists ofballast, sub-ballast, and subgrade. Figure 2 and 3
illustrate a design of ballasted railway track [5].

Area of Study
Northeast line of Thailand from Thanon Chira
juntion to Nong Khai station is the area of this study.
Related secondary data were gathered up bycollecting statistical data on defects of theNortheastern line from km.303+000 – km.623+900
between Thanon Chira juntion and Nong Khai station
with 320.900 km comprising 35 stations as shown in
Fig.4.

Fig.2 Track Design of Ballasted Track [5]Ballasted track is well known that it is constructed
to transport both freight and passengers with high costof approximately 70-200 million baht. Its structure
has at least 50 years of design service life cycle.
Considering the cost of track maintenance andmanagement, budget request for track construction is
not a difficult task compared to track maintenance.
The cost of track maintenance can vary based on
usability, so it is important to keep the track in goodcondition or prevent from degradation. [5].
Fig.4 Northeastern Line of Thailand Map

General Concept of Degradation
Track degradation process is complex, and its
mechanism is related to several variables such as axle
load, traffic speed, weather, rail quality, andgeography as shown in Figure 3.
Maintenance- Lubrication- Ballast cleaning- Tamping- Grinding- Inspection interval

Rail- Type/Quality- Wear- Age- Rail welding

Ballast- Type/Quality- Thickness- Age- Dust- Thickness

Environment- Temperature- Humidity- Corrosive
Environment- Thickness- Age

Condition

Track Geometry-Curvature-Elevation

Dynamic Load

Substructure

Sleeper- Type Quality

Superstructure
Track
Degradation- Type /quality

METHODOLOGYThis article aims at studying and analyzing factors
influencing track defects and degradation in Thailand
by applying FMADM to determine major and minor
factors for analyzing and making a decision on a planof track maintenance and renewal. The experts wereinterviewed to obtain knowledge about importanceweight of each factor by applying analytical hierarchy
process (AHP) as well as related secondary data werecollected. Criteria for considering the score of eachfactor were low, moderate, and high levels. Also,
fuzzy data were changed into the score by using fuzzyscoring method (FSM). Then total score wascalculated by using simple additive weighting(SAW). The analysis results of importance weightand score as mentioned above resulted in assessmentof major factors influencing track defect anddegradation to develop decision making on

Train- Type of Train- Traffic density- Axle load
/tonnage- SpeedStatic Load

Fig.3 Influencing Parameters Track Degradation [5]This research specifically focuses on factors
652

SEE - Nagoya, Japan, Nov.12-14, 2018

rehabilitation plan. Research methodology is shownin Fig.5. In this research, the experts had 15-35 yearsof track maintenance and rehabilitation experience inThailand.

Decomposition
Creating Hierarchy Structure

Reviewing literature and related research on major
factors influencing track defect and degradation
Pairwise comparison of importance of
decomposed factors on the same hierarchy

Collecting secondary
data on TQI andstatistics of broken andcracked track

Calculating the largest Eigen vector andEigen value

Inconsistent

Determining factors to analyze major factors
influencing track defect and degradation including
factors influencing broken and cracked track

Analytical Hierarchy
Process (AHP)

Determining criteria forconsidering score ofeach factor (low/moderate/high)Interviewing the experts
to calculate relative
weight of each factor

Changing considereddata into fuzzy number

Calculating relative
weight of expert groupfor each method by using
GMM

Calculating validity of decision making
Synthesis to investigate importance weightof factors
Consistent...n2
Expert 1

Combined decision making ofexperts using GMM
Calculating the largest Eigen
vector and Eigen value
Synthesis to investigate
importance of decision elementsfrom hierarchy structure

Summing up the score using Simple Additive
Weight (SAW) from calculating relative weightusing AHP and considered score using FSM fromanalyzing data to assess the factors influencing track
defect and degradation as well as severity of broken
and cracked track based on UIC Defect CodeFig. 6 Procedure of AHP [8]Defect from design

Prioritizing major factors influencing track defectand degradation of northeast line in Thailand

Defect from installation
Defect due to manufacturing materials of factory
Geological condition of track base

SystemSummarizing the analysis and selecting railway
track rehabilitation plan

Quality of track structure materials
Budget for maintenanceRadius of curvature of track for design
Gradient of track for design
Annual and accumulated weight through track

Fig. 5 Methodology Plan

Annual and accumulated number of trains

Usability

Analytical hierarchy process (AHP) developed by
Saaty (1988) is multi criteria decision making theory
which is widely used and highly accurate. AHP is theprocess simplifying decision on complicatedproblems because it imitates natural decision makingof human being. The procedure of AHP is presented
in Fig. 6.

Major factors
influencing track
defect anddegradation

Change of train operation
Increase of train speed
Wheel-track interaction
Track service life and dynamic limits

Track defect anddegradation

Dirty and weed-covered ballast
Frequency of track maintenanceTrack geometric condition adjustment

Track maintenance &rehabilitation

Wear of track
Degradation of sleeper and fastener
Degradation of ballast

Decomposition
Decision elements used in hierarchy structure
determined by a decision maker is important for
demonstrating the consistency of entire decision
elements from the highest hierarchy to the lowest one
as presented in Fig.7-8.

Frequency of annual check of track condition
Defect of track bed
Natural disaster

Externalfactors

Temperature
Humidity
Geographical features
Dangerous situation caused by train

Fig. 7 Hierarchy structure for prioritizing factors
influencing track defect and degradation
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SEE - Nagoya, Japan, Nov.12-14, 2018

Level 2Major Factors

Level 1
Goal

Level 3
Minor Factors

Level 4
(Alternatives)
Rehabilitation Plan

Disconnected junction
Straight/flat junction
Worn-out sleeper
Loose bolt

Code 1321: Horizontal
Crack at wet-headWorn-out fastener
Accumulated & Annual
Weight through Track

Code 135
Star-Cracking of Fishbolf
Holes
Prioritization of risks
influencing broken andcracked track

Track structure
rehabilitation plan

Limits of service life &dynamics
Corrugated rail head

Code 200
Transverse Break defectwith out apparent origin

Shaky wheel set
Fatigue of Thermit rail
welding
Fatigue of welded joint

Code 421
Transverse Cracking ofProfile Thermit Welding

Track structure
replacement

Non-vertical rail cutting
Natural settlement of Trackbed
Dirty ballast
Temperature

Fig. 8 Prioritization of Risks Influencing Break or Crack of Track

Table 2 Measuring Base Value Used for Decision
Making in Pairwise Comparison [8]Comparative
Importance
Score
1

Definition

Explanation

Equally
Important

Both factors show
equal result.

3

moderately
more
Important

5

Strongly
moreimportant7

VerystronglyMoreimportant

One factor ismoderately more
important than theother.
One factor isstrongly more
important than theother.
One factor is verystrongly more
important than theother.

9

Extremely
more
important

2,4,6,8Intermediate
judgment
value

This is fornarrowing gap incomparison
judgment andbeing not able toexplain withappropriate words.

Prioritization
Scores from 1 to 9 are used for pairwise
comparison where 1 indicates that both factors haveequal relative weight while 9 indicates that one factor
has extremely more relative weight than the other.
Using pairwise comparison for the decision
factors that are on the same hierarchy structure can beused for calculating the relative weights of decision
elements of each factor. Required data are obtained
from interviewing the experts. Measuring base value
used for decision making in pairwise comparison ispresented in Table 2.
Matrix of decision making obtained from pairwise
comparison is a pair of decision factor at the samehierarchy which corresponds to other factors on thenext upper hierarchy. Matrix is square value as shownin equation (1) where wi and wj represent relative
weight of factor i and j respectively.

There is anevidence
supporting
satisfaction with
one factor that isextremely more
important than theother.

654

SEE - Nagoya, Japan, Nov.12-14, 2018



W1 /W2 1
=AW  W2 /W1
1


 
 W /W W /W
 n 1 n 2







 
 
W1 /W    n W 
 W1 
 1
 W  n=
 W  nw
W2 /W =
n  2
 2 
 


W 
  W
 n
1   n 

1/ n
1/ n
 n

n  n



wi =  ∏ aij / ∑  ∏ akj 
k =1  j 1 (1) =
 j 1=


According to the theory of square matrix A, itsconsistency can be found when all elements ofcomparison are in the form of aik =aij x ajk and k 1 =,2 ,. , n. Principle right eigenvector for A is equal to n
(matrix sequence A). Therefore, it is very difficult for
matrix A to be completely consistent as equation (1).
Eigenvalue for A is not equal to n. Normally, righteigenvector (W) is represented by largest righteigenvalue (λmax) of matrix A as shown in equation(2).

AW = λ max W

λ max
=

(2)

CR =

(7)

where C [1, k] = global importance of elements for
decision making on hierarchy K which is consistent
with decision making on upper hierarchy.
Bi = ni- 1 Matrix of ni Matrix of row that iscontained for calculation.
n1 = numbers of factors used for decision making
on hierarchy structure i.
Fuzzy Multi Attribute Decision Making(FMADM)
FMADM was developed based on basic conceptof fuzzy set theory together with Multi Attribute
Decision Making (MADM). Chen and Hwang (1992)
hypothesizes that FMADM probably consists offuzzy data (words) and numeric data. Fuzzy data canbe represented by fuzzy number.

(3)

CI
RCI

(6)

k
C 1, k  = ∏ Bi
i =2

( λmax − n )
n −1

n  n

∑  ∑ a ×W 
ij i 
i =1  j =1
Synthesis
After obtaining the importance weight of eachfactor on each hierarchy structure, decision making
process using AHP is generally applied to “Principleof hierarchy composition” [7]. Calculated from theimportance weight of each factor value, global
relative importance that can be used for selecting an
optimal alternative is on the lowest position of thehierarchy structure chart as equation (7)Value of λmax is greater than or equal to n whenλmax is similar to n. Considered matrix A is consistentand reliable, so this is why λmax is used as an indicator
to express the validity of judging matrix A as
presented in equation (3). Consistency index (CI) is
developed from random square matrix test (500
samples) known as random consistency index (RCI)
presented in Table 3[7]. Ratio between CI and RCI iscalled consistency ratio (CR). CR will be allowable
when it is under 0.10, the value indicating theconsistency of decision making judgment as shown inequation (4).

C .I . =(5)(4)

Numberof factors

1

2

3

4

5

6

7

8

9

RCI

0.00

0.00

0.52

0.90

1.12

1.24

1.32

2.41

1.45

Table 3 Sample Consistency Index [7]Basic Concept of FMADM
In the criteria of alternative analysis for the basic
concept of FMADM, most of the decision-making
problems are composed of crisp fuzzy and numeric
data. Fuzzy data can be demonstrated in the form ofwords such as low, moderate, high, etc. or fuzzy
numbers.

There are so many ways used in calculating
principle right eigenvector (W) and largest
eigenvalue (λmax) for square A. This research used fornormalization of the geometric mean of the row(NGM) [8] as indicated in equation (5) and (6) toestimate principle right eigenvector (W) because it iseasy to calculate and understand largest eigenvalue(λmax) of square matrix A.

FSM

AHP

Fuzzy number

Pairwise Comparison

Crisp Score

Relative Weight

Simple Additive Weight (SAW)
Composite Score

Fig.9 Procedure of FMADM [8]655SEE - Nagoya, Japan, Nov.12-14, 2018

defects influencing break and crack can be divided
based on the International of Railway (UIC) using the
pairwise comparison method. Each type is different
in the starting point and extension direction of railway
track crack with contingency index below 0.01. The
experts specified the severity of code 200: transverse
break defect without apparent origin level of severity
is the highest with relative weight of 0.396 followedby code 135: star-cracking of fish bolt holes withrelative weight of 0.276, and the least severity is code
1321: horizontal cracking at web-head with relative
weight of 0.142 as presented in Table 4.

RESULT AND DISCUSSION
According to analysis of factors influencing track
quality particularly track degradation, rail isconsidered as the most significant element of track
structure because it gains the highest stress comparedto other elements; in other words, it directly connectswith wheels. From interviewing the experts, thenortheast line encounters the problem of broken andcracked track caused by degradation which exposes
to high risk of derailment influenced by usability
factor. Data collected from the report on broken andcracked track during 2007-2016 reveal that track
Table 4 Risk causing defects

Defect Code

Code
1321

Horizontal
Cracking

Code135

Star Cracking

Code
200

Transverse Break

Code
421

Transverse
Cracking ofProfile Thermit
Welding

Risk
Scoring%Prioritize
ImpactServerity

Prob.

ImpactFactors of cause

0.244

0.145
0.035

0.142

Disconnected junction

0.110

11.00%

4

Straight/flat junction

0.120

12.00%

3

0.265
0.069

0.276

Worn-out sleeper

0.150

15.00 %

2

Loose bolt

0.045

4.50%

10

0.244

0.405
0.099

0.396

Worn-out fastener

0.033

3.30%

11

0.252

0.185
0.047

0.187

Accumulated & Annual Weight
through Track

0.052

5.20%

9

Limits on service life &dynamics of Rail

0.200

20.00%

1

Corrugated rail head
Shaky wheel set

0.056
0.083

5.60%
8.30%

8
5

Fatigue of Thermit rail welding
Fatigue of welded joint

0.075

7.50%

6

Non-vertical rail cutting
Natural settlement of Track bed

0.066
0.004
0.002

6.60%
0.40%
0.20%

7
12
14

Dirty ballast
Temperature

0.001
0.003

0.10%
0.30%

15
13

Total

1.000

100 %

0.259

Table 5 Weight of criteria for decision making plan

According to analytic hierarchy process (AHP),
the result shows that track structure replacement plangets the highest score (0.575) while track structure
renewal plan gets lower score (0.425). As a result,track structure replacement should be selected for
conducting railway track rehabilitation because it is
optimal and highest consistent with all criteria. The
result indicates that track quality aspect is the mostimportant which has importance weight of 0.434
followed by return on investment aspect which has
importance weight of 0.303, and risk reduction of
defect aspect which has the lowest importance weightof 0. 263. The result from analyzing track
rehabilitation plan compared between track structure
rehabilitation plan and track structure replacement
plan in each criterion exhibits that each plan isdifferent in importance weight as presented in Table
5.

Criterion

Quality
Risk
Reduction
Return on
Investment

Track
Structure
Rehabilitation
0.38
0.32

Track
Structure
Replacem
ent
0.62
0.68

0.58

0.42

0.425

0.575

Weight

0.434
0.263
0.303

To further increase the competitiveness of railway
transport via quantity and quality of delivered service,improvements of track rehabilitation process are
required. This research has addressed vital aspects of656

SEE - Nagoya, Japan, Nov.12-14, 2018

track defects influencing break and crack that can bedivided based on the International of Railway (UIC)for the selection of rehabilitation plan. As a result,track structure replacement should be selected for
conducting railway track rehabilitation because it is
optimal and most consisting with all criteria.

economic and social development board.
[3] Report on infrastructure status in Thailand B.E.
2554, Office of the National Economics andSocial Development Board, 2011.
[4] Freight service department state railway ofThailand reprt on weight and train through therailway 2006-2016, SRT 2017.
[5] Lake M. Farreiera L., and Murray M., 2000,
Minimizing osts in scheduling railway track
maintenance, International Conference on
Computers in Railway No7, Bologne, Italy.
[6] Dahlberg, T. Railway track settlements – aliterature review, “Report for the EU projectSUPERTRACK”, Division of Solid Mechanics,
IKP, Linköping University, 2003.
[7] Saaty TL., The analytical hierarchy process,Priority setting, resource allocation, McGraw-hillinternational book company, 1980.
[8] Klungboonkrong P. and Faiboun N., Selection ofa suitable area for multimodal construction ofNong Khai bus terminal using fuzzy multi
attribute decision making method (FMADM),
The 20th National Convention on Civil
Engineering (NCCE20), 8-10 July 2015,
Chonburi, Thailand.

ACKNOWLEDGEMENTS
The researcher team would like to take thisopportunity to thank the Department of Civil
Engineering, Faculty of engineering, Khon Kaen
University as well as the experts from the State
Railway of Thailand (SRT) for giving useful data andopinions that contribute to the success of thisresearch.
REFERENCES[1] Project of analytic study on factors and effects formodal shift appropriate with road travel andtransportation
toward
rail
and
water
transportation, The Office of Transport andTraffic Policy and Planning (2009).
[2] Cited from journal of economy and society, vol.
52, No.2, April-June 2015, office of the national657

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

VEHICLE ACTUATED SIGNAL CONTROL FOR LOW CARBON
SOCIETY
1Thanapol Promraksa and 2Thaned Satiennam

Faculty of Engineering, Khon Kaen University, Thailand

ABSTRACTThe purpose of this study is to propose and evaluate the vehicle actuated signal control for coordinatedintersections to achieve the low carbon society. The study area is a group of 3 signalized intersections locating
along the national Highway No. 2 in Phol district of Khon Kean province, Thailand. This study proposed andevaluated the several signal control strategies to increase the effectiveness of these intersections. The proposed
strategies consist of i) fixed time control, ii) coordinated control, iii) semi actuated control, and iv) fully actuatedcontrol. This study applied the traffic microsimulation to evaluate the proposed strategies. The developed traffic
microsimulation model was calibrated by using the traffic data surveyed during morning peak. The study foundthat the fully vehicle actuated signal control was the best strategy to improve the level of service of intersections
and to reduce CO2 emission. The average max queue length, average travel time, delay, stop time delay, and CO2
emission of total systems decreased by 35%, 28%, 41%, 52% and 6%, when compared with existing fixed time
control. The fully vehicle actuate signal control could promote the low carbon society.
Keywords: Vehicle Actuated Signal Control, Traffic Simulation, Low Carbon Society, CO2 Emission

and evaluate the vehicle actuated signal control for
coordinated intersections to achieve the low carbon
society.
The study area is a group of 3 signalizedintersections, controlled by fixed time, along thenational Highway No. 2 in Phol district of Khon Keanprovince as displayed in Fig. 1. It is the four lane
divided highway. There is high number of traffic
volumes, 41,656 pcu/day, along main highway [7].
The roadside land use is the commercial andresidential areas which generated local traffic along
minor roads as well.

INTRODUCTION
Recently the global climate has become worse
because of Global Warming. This affects the averagetemperature of the Earth's atmosphere and oceans.
CO2 has increased by about 36% from 1973 to 2009[1]. Among human activities, the transport sector
emits a large proportion of CO2 emissions. The
amount of CO2 emissions has increased rapidly due
to the high level of motorization caused by economic
growth, particularly in developing Asian countries.
The international community has recognized the needto reduce greenhouse gas (GHG) emissions by 50%
by 2050 in order to keep global mean temperaturechange within 2 degrees Centigrade compared topreindustrial times [2]. To achieve this target, it isvery important to develop Low Carbon Societies(LCS) in Asia. This is due to developing Asian
countries accounting for more than half the global
population and GHG emissions. The CO2 emissions
from the transport sector will significantly increase
due to rapid economic growth and urban sprawl in thedeveloping countries of Asia.
To reduce emissions from the transport sector, theWorld Conference on Transport Research Society [3]proposed the CUTE matrix, introducing threestrategies, including AVOID, SHIFT and IMPROVE.
Many researchers have proposed measures according
to this matrix, including AVOID [4], SHIFT (e.g.,
shift to public transport [5]) and IMPROVE (e.g.,changing motorcycles to electric motorcycles [6]), for
Asian developing countries.
Therefore, the purpose of this study is to propose

Main rd.
Minor rd.
Intersection 1
350 m
Minor rd.
Intersection 2

700 m

Minor rd.
Intersection 3
Main rd.

658

SEE - Nagoya, Japan, Nov.12-14, 2018

Fully-actuated control
The fully-actuated control refers to intersections
for which all phases are actuated and hence, it
requires detection for all traffic demands and patterns
vary widely during the course of the day. There areseveral advantages of fully-actuated control. First, it
reduces delay relative to pre-timed control by being
highly responsive to traffic demand and to changes intraffic pattern. In addition, detection information
allows the cycle time to be efficiently allocated on acycle-by-cycle basis. Finally, it allows phases to be
skipped if there is no call for service, thereby
allowing the controller to reallocate the unused time
to a subsequent phase [8, 9].

Fig. 1 A group of 3 signalized intersections
RESEARCH METHODOLOGY
The research methodology is classified into four
steps: a proposal of signal control strategy, a surveyof road geometry and traffic data, the development ofa traffic microsimulation model and the evaluation of
the signal control strategies. Each approach in themodel development and application section will be
described in the following sub-sections.
Proposal of Signal Control Strategy
This study proposed four types of signal control
strategy, including a fixed time control, a coordinatedtraffic control, semi-actuated control and fullyactuated control, to achieve the low carbon society.
Their definitions and application were explained asfollows.

Survey of Road Geometry and Traffic data
The road geometry and traffic data were collected
for the development of a traffic simulation model.
The four vehicle types considered in this study weremotorcycles (MC), passenger cars (PC), pickup
trucks and vans (LT) and trucks and buses (HT). The
turning count data by vehicle type was collectedduring morning peak hours (7:00 – 8:00 am.) for adevelopment of OD matrices.

Fixed time control
The fixed time control is the pre-timed control
which its phasing and timing designed by the precounted traffic volume. Some fixed-time systems use
different preset time intervals for morning rush hour,
evening rush hour, and other busy times. But it cannot
compensate for unplanned fluctuations in traffic
flows. They give the most green time to the heaviest
traffic movement based on maximum information,
regardless of changes in traffic volumes. It is ideallysuited to closely spaced intersections where traffic
volumes and patterns are consistent on a daily or dayof-week basis. Such conditions are often found indowntown areas [8, 9].

Development of Traffic Microsimulation Model
This study selected the VISSIM software todevelop the traffic microsimulation model because
the VISSIM currently is only one of traffic simulation
software that has a function enabling to model lateralbehaviour of motorcycle when the motorcycle taking
over the slower or stopping other vehicles at
signalized intersection. Moreover, the VISSIM canmeasure the speed-time profile of individual vehicle
while it travels passing the signalized intersection.
The speed-time profile of individual vehicle, i.e.
instant speed and acceleration by every second, wasnecessary information as an input data for the CO2
emission models.
These OD matrices were input into VISSIM
through the function of turning movements by vehicle
type. The approaching, turning and crossing speeds atintersections by vehicle type were surveyed using the
spot speed method.
The study followed the guidelines proposed by
FHWA [10] for application in the traffic
microsimulation software. Before application of thetraffic microsimulation model, it was necessary tocalibrate the developed traffic microsimulation to be
as close to the real-world traffic conditions as
possible by adjusting the driving behavior parameters[11]. In the calibration process, this study simulated
the OD matrix on the developed network. The criteria
for traffic measures resulting from the simulation,
including traffic flow and the maximum queue length,were compared with the field. The differences andGEH statistics were compared with acceptance

Coordinated traffic control
The Coordinated traffic controls is to provide
smooth flow of traffic along streets and highways inorder to reduce travel times, stops and delay. A welltimed, coordinated system permits continuous
movement along an arterial. It is used in the case ofvery light side-street traffic [8, 9].
Semi-actuated control
The Semi-actuated control is used where a small
side street intersects with a major arterial or collector.
The detectors are placed only on the side street. The
green time is on the major street at all times unless a“call” on the side street is noted. It is used in the caseof very light side-street traffic, it reduces the delay
incurred by the major road through movements. On
the other hand, major road receives the green time
based on maximum traffic flow, regardless ofchanges in traffic volumes [8, 9].

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SEE - Nagoya, Japan, Nov.12-14, 2018

targets proposed by the Wisconsin Department ofTransport [12] and Ahmed [13]. The driving behavior
parameters were adjusted until the criteria for traffic
measures passed the acceptance targets.

k= 1= motorcycle, 2=passenger car, 3=pickup truckand van, and 4=truck and bus

Evaluation of Signal Control Strategies

This section presents the results of thedevelopment of the traffic microsimulation modeland the evaluation results of proposed signal control
strategies for Low Carbon Society.

RESULTS AND DISCUSSION

This study planned to propose the vehicle actuatedsignal control strategy for coordinated intersections toachieve the low carbon society. The conditions after
implementation of several proposed signal control
strategies were compared with the existing fixed time
control condition. The traffic microsimulation model
was applied to simulate the before and after traffic
conditions. The traffic Measure Of Effectiveness(MOEs) and CO2 emissions were considered as
evaluation criteria. The traffic MOEs consist of theaverage travel time, average delay and average queue
length of the total system. The CO2 emission of thetotal system was also evaluated.

Results of the Model Calibration
The result of the model calibration for traffic flow
is presented in Table 1. The difference between theobserved and modeled traffic flow and GEH of alllinks passed the acceptance target, proposed by the
Wisconsin Department of Transport [12]. This resultmeans that simulated traffic volume is close to traffic
volume in the field. The result of the model
calibration for a maximum queue length is presented
in Table 2. The difference between the observed andmodeled maximum queue length passed theacceptance target, proposed by Ahmed [13]. This
result means that maximum queue length of simulated
traffic flow is close to maximum queue length in thefield. In addition, the result of the model calibration
for traffic time is presented in Table 3. The difference
between the observed and modeled travel time of all
vehicles passed the acceptance target, proposed by
the Wisconsin Department of Transport [12]. These
results imply that the developed traffic
microsimulation model could closely simulate traffic
condition compared with real world conditions.

Calculation of CO2 Emission
This study applied the methodology and thedeveloped CO2 emission model of motorcycle for the
traffic microsimulation model, from the previous
study [14], to calculate CO2 emission of all vehicles.
This study also applied the emission data measured in
the Automotive Emissions Laboratory of the
Pollutant Control Department [15] to develop CO2
emission models according to fuel type, including
gasoline and diesel. The results from the traffic
microsimulation model, including the instantaneous
speed and acceleration of each individual vehicle,
were applied with the CO2 emission models to
calculate the CO2 emission.
CO2 emission rates (g/s) according to a
motorcycle, a gasoline vehicle and a diesel vehicle
were calculated by follow Eq. (1), (2) and (3):= 0.269 + 0.005u - 0.548a
LN (ERMC)
LN (ERGasoline) = -1.003 + 0.02u + 0.51a
LN (ERDiesel) = -0.239 + 0.028u + 0.193a

Evaluation Results of Signal Control Strategies
The evaluation results of the traffic flow measuresof effectiveness as well as the emissions and fuelconsumption are presented in Table 4. As expected,
all proposed signal control strategies could improve
max queue length, travel times, delays, stop timedelays and reduce CO2 emission in the selected study
intersections.
The updated fixed time control decreased theaverage delays, the average stopped delays, theaverage travel times, the maximum queue length, andCO2 emissions for the total systems by 9.1%, 12.1%,
7.6%, 2.1% and 0.4%, respectively. This result wascaused by the signal timing updated according to thecurrent traffic volume.
The coordinated control decreased the average
delays, the average stopped delays, the average travel
times, the maximum queue length, and CO2 emissions
for the total systems by 19.7%, 21.1%, 9.2%, 11.2%
and 1.2%, respectively. This result was caused by the
traffic along the major route could cross theintersections with less stop for the traffic signal.

(1)
(2)
(3)

where ER is the emission rate (g/s), u is the instant
speed (kph) and a is the instant acceleration (m/s2)
For each vehicle, its total emission was calculated
from a summary of instantaneous values at eachsecond. Finally, the total emission of all vehicles wascalculated using Eq. (4).
Total CO2 Emission =4mn� � � Instant Emission of a Vehicle
k

j

i

where
i= 1, 2, 3, ..., n (Number of time steps in second)
j= 1, 2, 3, …, m (Number of vehicles)

(4)

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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Results of model calibration of traffic flow
Diff.
Acceptance target
GEH
Pass/fail(veh/hr)Diff.*
GEH**
Intersection 1
SB-L
51
46
-5.0
0.72
Within 100
<5
Pass
SB-T
355
355
0.0
0.00
Within 100
<5
Pass
SB-R
100
108
8.0
0.78
Within 100
<5
Pass
NB-L
68
58
-10.0
1.26
Within 100
<5
Pass
NB-T
374
380
6.0
0.31
Within 100
<5
Pass
NB-R
63
67
4.0
0.50
Within 100
<5
Pass
WB-L
57
53
-4.0
0.54
Within 100
<5
Pass
WB-T
258
238
-20.0
1.27
Within 100
<5
Pass
WB-R
79
67
-12.0
1.40
Within 100
<5
Pass
EB-L
36
42
6.0
0.96
Within 100
<5
Pass
EB-T
217
206
-11.0
0.76
Within 100
<5
Pass
EB-R
252
233
-19.0
0.16
Within 100<5
PassIntersection 2
SB-L
52
54
2.0
0.27
Within 100
<5
Pass
SB-T
361
345
-16.0
0.85
Within 100
<5
Pass
SB-R
39
52
13.0
1.93
Within 100
<5
Pass
NB-L
185
205
20.0
1.43
Within 100
<5
Pass
NB-T
476
478
2.0
4.94
Within 100
<5
Pass
NB-R
86
107
21.0
2.14
Within 100
<5
Pass
WB-L
30
35
5.0
0.88
Within 100
<5
Pass
WB-T
252
250
-2.0
0.13
Within 100
<5
Pass
WB-R
30
36
6.0
1.04
Within 100
<5
Pass
EB-L
95
80
-15.0
1.60
Within 100
<5
Pass
EB-T
304
291
-13.0
0.75
Within 100
<5
Pass
EB-R
120
136
16.0
1.41
Within 100<5
PassIntersection 3
SB-L
12
22
10.0
2.43
Within 100
<5
Pass
SB-T
459
448
-11.0
4.43
Within 100
<5
Pass
SB-R
143
203
60.0
4.56
Within 100
<5
Pass
NB-L
217
215
-2.0
0.14
Within 100
<5
Pass
NB-T
525
539
14.0
0.61
Within 100
<5
Pass
NB-R
104
95
-9.0
0.90
Within 100
<5
Pass
WB-L
24
29
5.0
0.97
Within 100
<5
Pass
WB-T
85
81
-4.0
0.44
Within 100
<5
Pass
WB-R
33
21
-12.0
2.31
Within 100
<5
Pass
EB-L
85
102
17.0
1.76
Within 100
<5
Pass
EB-T
67
80
13.0
1.52
Within 100
<5
Pass
EB-R
252
233
-19.0
1.22
Within 100<5
Pass*Diff., hourly link flow of modeled versus observed within 100 veh/h, for flow < 700 veh/h, within 15% for 700veh/h < flow < 2,700 veh/h;**GEH statistics < 5; GEH =�(V − C)2/((V + C)/2) , where GEH is GEH statistic; V is simulated traffic flow; C is surveyed traffic flow;
[12].
Link

Modeled(veh/hr)Observed(veh/hr)Table 2 Results of the model calibration of the maximum queue length
Link

Modeled(m)Observed
(m)

SB
WB
NB
EB

52
59
102
50

54
72
126
48

SB
WB
NB
EB

96
63
112
77

96
66
96
72

SB
WB
NB
EB

158
21
129
64

162
18
126
72

Diff.
(%)
Intersection 1
3%
18%
19%
-5%
Intersection 2
0%
4%
-17%
-7%
Intersection 3
3%
-17%
-2%
11%

*Diff, maximum queue length of modeled versus observed within 20% [13].

661

Acceptance target (Diff.*)

Pass/failWithin 20%
Within 20%
Within 20%
Within 20%

Pass
Pass
Pass
Pass

Within 20%
Within 20%
Within 20%
Within 20%

Pass
Pass
Pass
Pass

Within 20%
Within 20%
Within 20%
Within 20%

Pass
Pass
Pass
Pass

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 3 Results of the model calibration of the travel time
Modeled
(s)
296
304

Link
NB
SB

Observed
(s)
265
302

Diff.
(%)
-12%
-1%

Acceptance target (Diff.*)

Pass/failWithin 15
Within 15

Pass
Pass

*Diff, travel time of modeled versus observed within 15% [12].

Table 4 Results of the effectiveness of traffic flow measures and CO2 emission reduction among scenarios
Parameters

Existing

Fixed time

CoordinatedSemi-actuatedFully-actuated

Delay (s/veh)

123

111 (-9.1%)

98 (-19.7%)

105 (-14.6%)

68 (-44.3%)

Stopped delay (s/veh)96

84 (-12.1%)

76 (-21.1%)

79 (-17.8%)

43 (-55.1%)

Travel time (s/veh)

1,141

1,075 (-7.6%)

1,060 (-9.2%)

1,059 (-6.3%)

876 (-28.1%)

Max queue length (m)1,203

1,037 (-2.1%)

740 (-11.2%)

832 (-4.1%)

808 (-29.2%)CO2 emission (kg/hr)

2,151

2,142 (-0.4%)

2,126 (-1.2%)

2,138 (-0.6%)

1,963 (-8.7%)

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SEE - Nagoya, Japan, Nov.12-14, 2018

Climate Policy Agenda - Recommendations
from WCTRS to COP18, Report, 2012.
[4] Klungboonkrong, P., Jaensirisak, S., Satiennam,T., Potential performance of urban land use andtransport strategies in reducing greenhouse gas
emissions: Khon Kaen case study, Thailand,International
Journalof
Sustainable
Transportation, Vol.11, No.1, 2017, pp.36-48.
[5] Satiennam, T., Jaensirisak, S., Natevongin, N.
and Kowtanapanich, W., Public Transport
Planning for a Motorcycle DominatedCommunity, Journal of the Eastern Asia Society
for Transportation Studies, Vol.9, 2011, pp.970985.
[6] Satiennam, T., Satiennam, W., Tankasem, P.,
Jantosut, P., Thengnamlee, J., & Khunpumphat,W., A Study of Potential Electric Motorcycle
Use to Support a Low Carbon Society: Case of a
Developing Asian City, Advanced Materials
Res., Vol. 931-932, 2014, pp. 541-545.
[7] Department Of Highway (DOH), 2015, Traffic
Volumes along Main National Highways in 2014<http://bhs.doh.go.th/download/traffic>.
[8] Roess P, Prassas S and McShance S. Traffic
Engineering Four Edition. [n.p.]: Transportationand System Engineering, 2010.
[9] Federal Highway Administration., Traffic
Signal Timing Manual chapter5, fromhttp://ops.fhwa.dot.gov/publications/fhwahop08
024/ chapter5.htm, 2015.
[10] Dowling R, Skabardonis A, and Alexiadis V.,
Traffic Analysis Toolbox Volume III: Guidelines
for Applying Traffic Microsimulation Software,
Report No. FHWA-HRT-04-040, Contract or
Grant No. DTFH61-01-C-00181, FHWA, 2004.
[11] Dowling R, Skabardonis A, Halkias J, McHale
G and Zammit G., Guidelines for Calibration of
Microsimulation Models Framework andApplications, In Transportation Research
Record: Journal of the Transportation Research
Board, No. 1876, TRB, National ResearchCouncil, Washington D.C, 2004, pp. 1–9.
[12] Freeway System Operational Assessment,
Paramics Calibration & Validation Guidelines,
Technical Report I-33 (Draft), Milwaukee, Wis,
USA, Wisconsin Department of Transportation,
2002.
[13] S. Ahmed, Calibration of Vissim to the Traffic
Conditions of Khobar and Dammam, Saudi
Arabia [Master, Thesis], King Fahd University ofPetroleum and Minerals, Saudi Arabia, 2016.

The semi-actuated control decreased the average
delays, the average stopped delays, the average travel
times, the maximum queue length, and CO2 emissions
for the total systems by 14.6%, 17.8%, 6.3%, 4.1%
and 0.6%, respectively. This result was caused by afacilitation of the traffic along minor routes
The fully-actuated control decreased the average
delays, the average stopped delays, the average travel
times, the maximum queue length, and CO2 emissions
for the total systems by 44.3%, 55.1%, 28.1%, 29.2%
and 8.7%, respectively. It caused that traffic along
major and minor routes could pass the intersections
with less stop.
Consequently, the fully vehicle actuated signal
control is the most efficient strategy among the
proposed strategies.
CONCLUSIONS AND RECOMMENDATIONSThis study proposed and evaluated the several
signal control strategies to increase the level ofservice of the intersections and decrease CO2
emission of total systems. The developed traffic
microsimulation model was applied to evaluate theproposed strategies. The study found that the fullyvehicle actuated signal control was the best strategy
to improve the level of service of intersections and to
reduce CO2 emission. It should be promoted toachieve the low carbon society.
As recommendations for further studies, the study
on providing advanced information regarding signal
phases and timing to vehicles travelling on asignalized corridor, extending from cars [16, 17] tomotorcycles with the vehicle actuated signal control
for developing countries, should to be evaluated on its
increasing intersection’s level of service andreduction on CO2 emission.
ACKNOWLEDGEMENTS
The authors would like to express theirappreciation to the Farm Engineering and AutomaticControl Technology Research Group (FEAT) at
Khon Kean University for a financial support on thisresearch.
REFERENCES[1] Intergovernmental Panel on Climate Change(IPCC). IPCC Guidelines for National
Greenhouse Gas Inventory, Volume 1, Revised,
Reporting Instructions, 2006.
[2] National Institute for Environmental Studies(NIES). Asian Low Carbon Society Research
Project. Report. National Institute forEnvironmental Studies. Japan, 2011.
[3] World Conference on Transport ResearchSociety (WCTRS), Putting Transport into

663

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Satiennam, W., Pasangtiyo, W, and Hashino, Y.,
Development of On-Road Exhaust Emission and
Fuel Consumption Models for Motorcycles andApplication through Traffic Microsimulation,
Journal of Advanced Transportation, Vol. 2017,2017.
[15] Office of Transport and Traffic Policy andPlanning (OTP), The Study to Develop Master
Plan for Sustainable Transport System and
Mitigation of Climate Change Impacts, Final
Report, Office of Transport and Traffic Policy
and Planning, Thailand, 2013.
[16] Barth, M., Mandava, S., Boriboonsomsin K., andXia H., Dynamic ECO-driving for arterial
corridors, in Proceedings of the IEEE Forum on
Integrated and Sustainable Transportation
Systems (FISTS ’11), pp. 182–188, Vienna,
Austria, June-July 2011.
[17] Xia, H., Boriboonsomsin, K., and Barth, M.,
Indirect networkwide energy/emissions benefits
from dynamic eco-driving on signalized
corridors, in Proceedings of the 14th IEEE
International Intelligent Transportation Systems
Conference(ITSC’11),pp.
329–334,
IEEE,Washington, DC, USA, October 2011.

664

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EXPERIMENTAL STUDY ON THE EFFECT OF STEEL FIBER WASTE
TYRE ON HIGH STRENGTH CONCRETE

1,2,3,4

Fauzan1, Rudy Kurniawan2, Oscar Fitrah N3, Claudia Lovina A. N4,
Engineering Faculty, AndalasUniversity, Padang, West Sumatera, Indonesia

ABSTRACTHigh strength concrete (HSC) is defined as concrete with a specified compressive strength of 40 MPa or
greater. Concrete with high strength is basically a brittle material, with low tensile strength. Another problem tonote is the incidence of cracks in HSC due to the tensile stress. One way to improve the brittle and weak concrete
properties towards tensile strength is by utilizing fiber. The utilization of steel fiber from waste tires (SFWT) in
high strength concrete can be used as an alternative to improve the mechanical properties of the concrete andalso has benefit to reduce the waste of used tires that are increasing every year. This research was conducted todetermine the effect of the addition of steel fiber waste tire on high strength concrete (HSC) and high strength
concrete containing silica fume (HSCSF). Steel fiber waste tyre is obtained from the extracting of used tires thatare cut into 4 cm long. The specimen used is a cylinder with a diameter 15 cm, height 30 cm and beam withdimension 10x10x50 cm. The content of silica fume on high strength concrete is 10% by replacing of the cement
weight. The addition of steel fiber waste tire in both HSC and HSCSF are 0%, 0.5%, 1.0%, 1.5%, and 2%.
Mechanical properties of concrete such as compressive strength, tensile strength and flexural strength are tested
at 28 days age. The results show that the addition of SFWT increases the compressive strength, tensile strengthand flexural strength of HSC and HSCSF. The increase of SFWT content results in the higher mechanicalproperties of the high strength concrete. In addition, the presence of SFWT in the high strength concrete delays
the crack width of the concrete and prevents the brittle collapse.
Keywords: High strength concrete, Steel fiber waste tire, Silica fume, Concrete properties

Also, the cracks of HSC will easily occur due to thetensile stress. One way to improve the brittle and weakconcrete tensile strength is by utilizing fiber. Fibers
help to improve the post-peak ductility performance,
pre-crack tensile strength, impact strength, fatigue
strength, and eliminate temperature and shrinkage
cracks [3]. Several studies have proved that theaddition of fiber in high strength concrete can improvethe mechanical properties of its concrete [4]-[8].
The utilization of special steel fiber from the usedtire (steel fiber waste tire) on high strength concrete
can be an alternative to produce HSC with high tensile
strength. The large number of waste tires production ispotential to be used to the improve the mechanicalproperties of HSC. This research focused on theinvestigation on the effect of steel fiber waste tire
addition on HSC and high strength concrete containing
silica fume (HSCSF).

INTRODUCTION
Concrete is the oldest and the most widely usedmaterial in the history of human development. In
general, the strength and performance of concrete
before the 20th century is still low and then, it isdeveloped to the high strength concrete (HSC). The
high strength concrete is concrete with compressive
strength implies 40 MPa or greater. The higher
compressive strength of concrete results reduction in
the size of structural elements such as columns andbeams [1].
HSC can be produced by reducing the watercement ratio of the concrete. The reduction of thewater-cement ratio results in a decrease in porosity andrefinement of capillary pores in the matrix so themechanical properties will increase. However, it willaffect the concrete workability. An alternative to make
HSC is by using pozzolanic admixtures such as silica
fume. Silica fume is a by product of producing silicon
metal or ferrosilicon alloys that is very reactive
pozzolan. It has been proved that the addition of silica
fume on HSC increase the compressive strength,
flexural strength and durability, in which the highest
increase was found with the replacement of 10% and
15% silica fume by cement weight [2].
High strength concrete is inherently a brittle
material, with low tensile strength and limited ductility.

MATERIALS AND METHODS
Materials Used
Cement
The cement that used in this research is Ordinary
Portland Cement (OPC) produced by Padang Cement
Factory, Indonesia.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fine Aggregate

Silica Fume

Locally available fine aggregate, with a maximum
size of 4.75 mm is used in this study. The properties ofthe fine aggregate such as specific gravity, absorption,fineness modulus, and water content of fine aggregate
can be seen in Table. 1

Silica fume that used in this research is Sika Fume
produced by Sika Factory. The added silica fumematerial used meets the technical requirements inaccordance with ASTM C 1240-00.
Superplasticizer

Table 1 Properties of fine aggregate
No

Property

Value

1
2
3
4

Specific gravity
Absorption
Fine Modulus(FM)Water content

2,44
3,6 %
3,4
0,94 %

Superplasticizer
usedisViscocrete-1003
manufactured by Sika Factory. The viscocrete-1003
additive material meets the technical requirements inaccordance with ASTM C 494-92 Type F.

Coarse Aggregate
The locally coarse aggregate is used with the size of
5-10 mm. The properties of the coarse aggregate suchas specific gravity, absorption, fineness modulus, andwater content can be seen in Table. 2
Table 2 Properties of coarse aggregate

Fig. 1 Waste tyres

No

Property

Value

1

Specific gravity

2,51

2

Absorption

2,8 %

3

Fine Modulus (FM)4,97 %

4

Water content

1,06 %

Water
Potable tap water which is free form acid andorganic substance is used in mix preparation and curingconcrete.

Fig. 2 Steel fibers extracted from waste tyres

Steel Fiber Waste Tyre
In this study, the steel fibers taken out from waste
tyres (Fig. 1) are used in the concrete mix to form acomposite fibrous material. Steel fibers waste tyres(SFWT) are extracted from chips of waste tyres by the
manual cutting process (Figs. 2 and 3) and cut to 4 cm
length (Fig. 4), and an average diameter of the fiber is
028 mm keeping aspect ratio 80. The steel fibers are
uniformly and randomly distributed in different
proportions from 0-2% with an increment of 0,5% by
the volume of concrete to prepare the different concrete
matrix. The geometric characteristics of SFWT can beseen in Table 3.

Fig. 3 The 4cm lenght of steel fiber extracted from waste tyre666

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 3 Properties of steel fiber waste tyre

Table 5. Mix proportions of HSCSF

Characteristics ofSteel fiber

Description

Material(Kg/m3)

SF
0

SF
0.5

SF
1.0

SF
1.5

SF
2.0

Form

Irregular, Sharp

505.3

505.3

505.3

505.3

Invisible

Cement(Kg/m3)505.3

Surface Texture
Size

Diameter 0.5 mm andlength 40 mm

Sand(Kg/m3)

638.7

638.7

638.7

638.7

638.7

Aspect Ratio

80

902.6

902.6

902.6

902.6

7850 Kg/m3

Split 5/10
(Kg/m3)902.6

DensityTensile strength

500-2000 N/mm2

Water(Kg/m3)

214.8

214.8

214.8

214.8

214.8

Steel Fiber
(%)

0.0

0.5

1.0

1.5

2.0

Silica Fume
(Kg/m3)

56.1

56.1

56.1

56.1

56.1

Viscocrete
1003
(%)

1.00

1.00

1.00

1.00

1.00

EXPERIMENTAL PROGRAM
Mix Proportions of High Strength Concrete
A high strength concrete mix design is calculated
according to the ACI (American Concrete Institute)method 211.4R-93. There are two variations of highstrength concrete namely, high strength concrete andhigh strength concrete containing silica fume. The rateof addition of silica fume in the concrete mixture is
10% of the cement weight, in which the silica fumeserves as a cement replacement material. The amountof steel fibers added in the concrete mixture is based on
the total volume of the commonly referred concrete
volume fraction. The mix proportions of high strength
concrete (HSC) and high strength concrete containing
silica fume (HSCSF) with the percentage of steel fiber
waste tire can be seen in Tables 4 and 5.

* SF : Steel Fiber
Casting of Specimens
There are 80 specimens were cast, consist of 60
cylinders specimens for compressive and splitting
tensile strength tests and 20 specimens for the flexuralstrength test. The number of test specimens can be seenin Table 6.
Table 6. Number of test specimens

Table 4. Mix proportions of HSC
Material(Kg/m3)

SF
0

SF
0.5
561.5

SF
1.0
561.5

SF
1.5

Cement(Kg/m3)

561.5

561.5

Sand
(Kg/m3)

638.7

638.7

638.7

638.7

638.7

Split 5/10
(Kg/m3)

902.6

902.6

902.6

902.6

902.6

Water
(Kg/m3)

214.8

214.8

214.8

214.8

214.8

Steel Fiber
(%)

0.0

0.5

1.0

1.5

2.0

Viscocrete1003 (%)

0.69

0.69

0.69

0.69

0.69

Number of Concrete specimens

Type of concrete

SF
2.0
561.5

compressive

TensileFlexuralHigh strength
concrete

15

15

10

High strength
concrete with Silica
Fume 10%

15

15

10

Total

30

30

20

Cylindrical moulds of 150 mm diameter and 300
mm length are used for casting the specimen forcompressive and splitting tensile strength tests,
respectively. For flexural strength test, beam specimen
with the size of 100 x 100 x 500 mm is cast. The
specimens are cast with 0%,0,5%,1%,1,5% and 2%
content of SFWT on concrete with and without silica
fume. All specimens were cured for 28 days.

* SF : Steel Fiber

Testing of Specimens
Testing of compressive strength and tensile strengthis carried out on cylindrical test specimens by using a
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SEE - Nagoya, Japan, Nov.12-14, 2018

compressive test apparatus at the Concrete Laboratoryof Semen Padang Factory (Figs. 4 and 5). Flexural
testing is carried out on beam specimens using aflexural testing machine in the concrete Laboratory of
Semen Padang Factory (Fig. 6). Compressive, splitting
tensile and flexural strengths of each specimen wasdetermined using SNI 03-1972-2011, SNI 2491: 2014,
and SNI 4154: 2014, respectively.

RESULTS AND DISCUSSION
Compressive Strength
The results of the compressive tests performed on
HSC and HSCSF with different percentage of steel
fibers tested on the 28th day is shown in Table 7 andFig. 7.
Table 7 Test result of compressive strength
No.

1
2
3
4
5

(%)

Compressive
Strength
HSC
HSCSF
(MPa)
(MPa)

Percentage ofIncrease
HSCSF
HSC
(%)
(%)

0
0.50
1.00
1.50
2.00

58.91
59.15
60.44
72.38
73.38

0.42
2.59
22.86
24.56

SFWT

69.87
73.41
74.36
77.00
78.54

5.08
6.43
10.21
12.42

As seen in Table 7, the compressive strength of
HSC and HSCSF containing SFWT increases with theincrease of SFWT content. In HSC, the percentage
increases in the compressive strength for the cylinder
with 0.5%, 1%, 1.5% and 2% SFWT addition are
0.42%; 2.59%; 22.86%; and 24.56%, respectively. The
highest value of compressive strength of 73,38 MPa
was observed on HSC with 2% SFWT addition.
For HSCSF, meanwhile, the highest value ofcompressive strength occurred in the addition of SFWT
by 2% that is 78.54 MPa, which is 12.4% increase incompressive strength compared to those without
SFWT. Percentage increase of compressive strengthwith 0.5%; 1.0%; 1.5%; and 2% SFWT addition are
5.08%; 6.43%; 10.21%; and 12.24%, respectively.
The comparison of compressive strength between
HSC and HSCSF with variation SFWT content isshown in Fig. 7.

Fig. 4 Compressive test on cylindrical specimen

Compressive Strength (MPa)Fig. 5 Splitting tensile test on cylindrical specimen
100
90
80
70
60
50
40
30
20
10
0

HSC

HSCSF

0.0

0.5

1.0

1.5

2.0

SFWT (%)

Fig. 7 Comparison of compressive strength between
HSC and HSCSF with different SFWT content
As can be seen in Fig. 7, the increase incompressive strength between HSC and HSCSF has
the different tendency. However, the compressive

Fig. 6 Flexural test on beam specimen
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SEE - Nagoya, Japan, Nov.12-14, 2018

strength of HSCSF was higher than those of HSC ineach SFWT content. This indicates that the presence ofSilica fume results in the higher concrete compressive
strength.

on tensile strength from 0.5% to 1% SFWT content. In
general, the tensile strength of HSCSF is higher thanthose of HSC at each SFWT content.
Flexural Strength

Tensile Strength
The results of the flexural strength tests performedon HSC and HSCSF at different percentage of SFWT
content is shown in Table 9 and Fig. 9.

Tensile strength test results on HSC and HSCSF
with different content of SFWT is shown in Table 8
and Fig. 8.

Table 9 Test results of flexural strength
Table 8 Test result of splitting tensile strength
No.
No.

1
2
3
4
5

SFWT

Tensile Strength

(%)

HSC
(MPa)

HSCSF
(MPa)

Percentage ofIncrease
HSC
HSCSF
(%)
(%)

0
0.50
1.00
1.50
2.00

3.85
4.77
4.87
7.61
8.27

5.61
5.65
6.10
7.75
9.14

23.87
26.32
97.55
114.69

(%)

HSC
(MPa)

HSCSF
(MPa)

Percentage ofIncrease
HSC
HSCSF
(%)
(%)

0
0.50
1.00
1.50
2.00

6.23
6.89
7.27
8.33
10.73

7.18
8.10
8.57
9.18
11.68

10.47
16.61
33.57
72.20

12.85
19.44
27.90
62.70

From Table 9, it can be seen that in general, there isan increase in flexural strength from the addition of
0.5%, 1%, 1.5% and 2% SFWT to both HSC and
HSCSF. Steel fiber in the concrete increases theflexural strength. The highest content of fibers gives
the maximum increase of the strength. The highest
percentage of increase in flexural strength wasobserved with the addition of 2%.SFWT content that is72.2% and 62.7% for HSC and HSCSF, respectively.
The maximum flexural strength on HSC and HSCSF
are 10.73 MPa and 11.68 MPa, respectively.
The tendency of increase in flexural strength isalmost similar for both HSC and HSCSF at each
SFWT content, as shown in Fig. 9.

14Flexural Strength (MPa)Tensile Strength (MPa)

Flexural Strength

1
2
3
4
5

0.76
8.83
38.27
62.99

The test results indicate that the tensile splitting
strength increases as the increase the SFWT content on
both HSC and HSCSF from 0% to 0.5%, 1%, 1.5%,
and 2%. This might be in consequence of the strong
mechanical interlocking force in the concrete due to thepresent SFWT.
For HSC, it is found that the maximum splitting
tensile strength by adding 2% SFWT is 8.27 MPa,
which is 114.69% increase as compared to HSC
without SFWT. In HSCSF, on the other hand, themaximum percentage increase of the tensile strength at
2% SFWT content is less than those in HSC, that is
62.99% (9.14 MPa).
Fig. 8 shows the comparison of tensile strength
between HSC and HSCSF with variation SFWT
content.

10
8

HSC

6

SFWT

12
10
8

HSC

6
4

HSCSF

2
0
0.0

4

1.0

1.5

2.0

SFWT (%)

HSCSF

2

0.5

0
0.0

0.5

1.0

1.5

2.0

Fig. 9 Comparison of Flexural Strength between HSC
and HSCSF with different SFWT content

SFWT (%)

Fig. 8 Comparison of Tensile Strength between HSC
and HSCSF with different SFWT content

The increases of the flexural strength with theaddition of steel fiber waste tire due to the influence ofhigh strength concrete bonds with added materials in
the form of SFWT. The fiber bonds on high strength
concrete can be seen in Figs. 10 and 11. The presenceof SFWT increases resistance to cracking, It is clearlyCompare to HSCSF, the increase of tensile strength
is more significant at each SFWT content. However,both HSC and HSCSF show almost similar increment
669

SEE - Nagoya, Japan, Nov.12-14, 2018

seen from Fig. 11 that the steel fiber from waste tyrebridges across the cracked matrix, which will provide
the higher bonding on the HSC.

3. For HSCSF, the replacement of 10% cement weightby silica fume results in higher of the concrete
strength compared with HSC at each SFWT
content. The maximum percentage increase of thecompressive, tensile and flexural strength wasobserved on 2% SFWT addition that are 12.4%;
73.0%; and 62.7%, respectively.
ACKNOWLEDGEMENTS
The authors acknowledge the staffs of theLaboratory of Material and Structure in Andalas
University and Concrete Laboratories of Padang
Cement Factory Padang, Indonesia for their support.

Fig. 10 Illustration of cracks in high strength concrete
without SFWTREFERENCES[1] Rashid, Mohammad Abdur, and Mohammad Abul
Mansur, “Considerations in producing highstrength concrete”, Journal of Civil Engineering(IEB), 37(1) (2009) 53-63[2] Amarkhail, Nasratullah., “Effects of Silica Fumeon Properties of High-Strength Concrete”,
International Journal of Technical Research andApplications e-ISSN: 2320-8163[3] Mhaske, Vijay M, Rahul D. Pandit and A. P.
Wadekar, “Study on Behavior on High Strength
Crimped Steel Fibre Reinforced Concrete for
Grade M90”, IJRET: International Journal of
Research in Engineering and Technology eISSN:
2319-1163, ISSN: 2321-7308[4] Zhao, Qingxin., et. al., “Effect of Fiber Types on
Creep Behavior of Concrete”, Construction and
Building Materials 105 (2016) 416–422[5] V, Raikar R., Karjinni V.V, and Gundakalle V. D,“Study on Strength Parameters of Steel Fiber
Reinforced High Strength Concrete”, Int. Journalof Applied Sciences and Engineering Research,
Vol. 1, Issue 4, 2012, ISSN 2277 – 9442
[6] Velayutham, G., and C. B. Cheah, “The Effects of
Steel Fibre on the Mechanical Strength andDurability of Steel Fibre Reinforced High Strength
Concrete (SFRHSC) Subjected to Normal andHygrothermal Curing”, MATEC Web ofConferences 10, 02004 (2014)[7] Ashwani., “To Study the Effect of Steel Fibers on
Strength of Concrete with Partially Replaced
Marble Dust”, International Journal of Science andResearch (IJSR), ISSN (Online): 2319-7064[8] Aydın, Serdar, “Effects of Fiber Strength on
Fracture Characteristics of Normal and HighStrength Concrete”, Rperiodica polytechnic, Civil
Engineering, Department of Civil Engineering,
DokuzEylül University, Buca 35160, Izmir,
Turkey.

Fig. 11 Illustration of cracks in high strength concretewith the addition of SFWTIn Figs. 10 and 11, cracks in high strength concrete
can pass through aggregates and matrix. This isbecause the mechanical properties of aggregates andmatrix in high strength concrete are very similar(equally strong).
High strength concrete bonds with steel fiber waste
tire can prevent the spreading of irregular small cracks
in the concrete caused by the added load when theconcrete is tested. So with the increase of steel fiber
waste tire on the concrete, the less likely theoccurrence of cracks (collapse) and test objects canreceive a greater load again. In addition, steel fiber
waste tire can also increase ductility, where steel fiber
is still able to bind cracks in the cracks, so it can
prevent the brittle collapse.
CONCLUSION
1. The addition of SFWT from 0.5% to 2% in HSC
and HSCSF increases the compressive strength,
tensile strength and bending strength. This is due tothe contribution of the fiber to bond the concrete,
reduce the cracks and prevent a brittle collapse.
2. In HSC, there is no significant increase ofcompressive strength with 2.0% SFWT addition,that is 24.56%, while, the significant increases oftensile and flexural strength are observed on
HSCSF that are 114.7% and 72.2%, respectively.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

AN ANALYTICAL INVESTIGATION OF EWECS COMPOSITECOLUMN WITH AND WITHOUT SHEAR STUD

1,2

Fauzan1, Ruddy Kurniawan2 and Zev Al Jauhari3
Civil Enginering Department, Andalas University, Indonesa; 3Bengkalis State Polythecnic, Indonesia

ABSTRACTThis paper explains about numerical analysis of EWECS (Engineering Wood Encased Concrete-Steel)column accompanied with shear stud connection under constant axial and lateral cyclic loads based on theprevious experiment. This is the new structure system contains concrete encased steel (CES) core with an
exterior wood panel. The experiment was performed in a variation of wood panel connection to the concrete. In
this study, the non-linear finite element (FE) analysis is performed by modeling the column with 3D solid
element and the friction devices of shear stud with two-node-link element. The hysteresis characteristics
comparison between experiment and numerical results show that the peak forces in the every last loops (story
drift) and hysteresis curves shape have similarity as well as on the main stiffness, ductility, and energy
dissipasion. The presence of shear studs on EWECS columns improved the ductility of the column and reduced
the damage of wood panel, but there was no much influence on maximum flexural strength of the column. With
shear studs, the wood panel contributed to flexural capacity until maximum story drift, R of 5%, although cracks
appeared at the column faces after R of 4%. Generaly, the analytical method can be used to predict accurately
the ultimate strength and behavior of EWECS columns.
Keywords: EWECS column, shear stud, cyclic load, numerical analysis

INTRODUCTION
To solve a problem on the story number
limitation for wood structures (unfireproof material)that limited to not more than three stories based on
the Building Standard Law of Japan [1], the type ofhybrid structural system that called as EWECS(engineering wood encased concrete-steel) structural
system has been developed by one of the authors inJapan. The proposed structural system consists of
EWECS columns and engineering wood encased
steel (EWES) beams, as shown in Figure 1. For the
first stage of the research program, composite
EWECS columns were investigated. The EWECS
column consists of an exterior wood panel withconcrete encased steel (CES) core (Figure 1).
In our previous studies [2], the seismic
perormance of EWECS column using double Hsection steel had been tested to apply to columns
subjected to bending moments and shear forces in
two directions, such as those in the structure offrame. The results show that the column had a stablespindle-shaped hysteresis curve without degradationof load-carrying capacity until large story drift, R of
5%. It was also found that the wood panel presenceon the EWECS column contributed to flexural
capacity by around 12% in peak of every loop.
Furthermore, EWECS columns using single Hsection steel, are being developed to apply tocolumns of one way moment frame connected withshear wall in the orthogonal directions [3].

Fig. 1

Schematic view of EWECS structural
system [2].

Composite action enhances structural efficiency
by combining the structural elements to create asingle composite section. The term “full shear
connection” relates to the case in which theconnection between the components is able to fully
resist the forces applied [4]. The component thatassures the shear transfer between the wood panel
671

SEE - Nagoya, Japan, Nov.12-14, 2018

and the concrete encased steel core in the composite
construction is the shear stud. The shear studs madefrom steel bolts were attached from the wood panel
to CES core along the column height for the column,
as shown in Figure 2. The purpose of the shear studs
is to enhance the bond between the CES core and thewood panel, thereby increasing the composite actionof the column. The effect of shear studs on the
behavior of EWECS columns can be examined bycomparing Models WC1 (without shear stud) andWC1-S (with shear stud). Both specimens have thesame column dimensions and configurations, and themain difference is only the presence of the studs.
The objective of this research is to develop afinite element model (FEM) using ANSYS APDL
14.0 [5] to predict the response and behavior of
EWECS composite column subjected to lateralcyclic loads. The developed model takes into
consideration the nonlinear behavior of concrete andcontact between surfaces. The results of the FEmodel were validated with experimental test resultsthat were conducted at Japan [2].

within the grid depends largely on the rate of changeof displacement in different directions. The total
number of elements used is 7810 elements which isan adequate refinement for the constructed 3D FE
model.

1600 mm

400 mmFig. 3

The 3D FE model of EWECS column.

Material Properties
The characteristics of the EWECS column modeland the real properties of materials are presented inTable 1. The materials properties of the section areincorporated to observe the realistic behavior.
(a)Fig. 2

Table 1 Material properites of EWECS column(b)Material
Concrete

Property
Value
Compressive strength fc’35(MPa)
Tensile strength ft (MPa)
3.1
Young’s modulus Ec (MPa)27800
Poisson’s ratio ʋ
0.2
Ultimate comp. strain
0.0025
Steel
Yield stress fsy (MPa)
313.3
(Web)
Poisson ratio ʋ
0.3
Young’s modulus Es (MPa) 156700
Steel
Yield stress fsy (MPa)293.6(Flange)
Poisson ratio ʋ
0.3
Young’s modulus Es (MPa) 146800
Wood*Compressive strength fcw’45
(MPa)
Tensile strength ftw (MPa)5Young’s modulus Ec (MPa)11500
Poisson’s ratio ʋ
0.34
Ultimate comp. strain
0.0025
Note: * the direction is parallel to axis of grain.

The dimension and cross section of (a)WC1 and (b) WC1-S spesimens [3].

ANALYTICAL WORK
Finite element analysis is a numerical method of
deconstructing a complex system into very small
pieces called elements. The software implements
equations that govern the behaviour of theseelements and solve them all, creating acomprehensive explanation of how the system act asa whole. These results then can be presented intabulated, or graphical forms.
The 3D Models Detail
All the model of column had 1600 mm heightand 400 x 400 mm2 cross-section. A composite
section is modelled with a single H-section steel of
300 x 220 x 10 x 15 mm and the thickness of thewood panel was 45 mm. The model of the column
composite is shown in Figure 3. FEM is the outlinesof the elements used to model the object of interest.
An important aspect of FE modeling that affects theanalysis is the aspect ratio of plane elements. The
aspect ratio describes the shape of the element in theassemblage. The optimal aspect ratio at any location

Element Types Adopted
For representation of concrete, an eight nodesolid element SOLID 65 was used. The solid
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SEE - Nagoya, Japan, Nov.12-14, 2018

element has eight nodes with three degree of
freedom at each node with translations in the nodal
x, y and z directions, as seen in Figure 4. The
element is capable of plastic deformations, cracking
in three orthogonal directions, and crushing. The
most important aspect of this element is thetreatment of non-linear properties.
The SOLID185 element is a 3D hexahedral
element defined by eight nodes as shown in Figure
5. The element has three translational degrees of
freedom at each node in the nodal x, y, and z
directions. The element has capability of plastic
deformation, hyperelasticity, stress stiffening, creep,large deflection, and large strain.

Fig. 4

concrete is based on William and Warnke
formulation [9].
An isotropic multi-linear compressive stress–
strain curve for concrete is used to define the plastic
behavior of concrete. The stress-strain relationshipin the rising region was designed on the model
developed by Saenz [7], which was built in the
program, as seen in Figure 6. To account for shear
stiffness reduction by shear crack deformation, shear
transfer model developed by Al-Mahaidi wasincluded in the analysis, with the use of modified
shear transfer coefficient, β, of 0.75 [8].

ANSYS Solid65 and Solid185 elements [5].

Two element types (CONTA174 and TARGE170)
are used for the contact and target surfaces since thecontact is between two different surfaces. Surfaces
with finer mesh were designated as contact surface
while surfaces with coarser meshes were consideredtarget surfaces. The contact element has eight nodes
as shown in Figure 5. Accordingly, FE analysis sets
the normal pressure to zero if separation occurs
between the surfaces in contact [6].

Fig. 6 Compressive stress-strain relationship for
concrete.
Steel
The steel element used in ANSYS was considered tobe perfectly elastic material and identical in tension
and compression. The constitutive model of the steel
encased inputed is shown in Figure 7.
Wood Panel

Fig. 5The constitutive model of wood in the paper isshown in Figure 8. Owing to the design to allow theforce to be applied in the direction parallel to theannual growth ring of the wood, some existing
concrete models built in the program by many
researchers might be used in the analysis with somemodifications. Stress-strain relationship in the risingregion was modeled with the linearly increasing(perfectly elastic - plastic criterion) model, andslightly reduced by 5% for the wood without shear
stud.
The fracture criterion of wood was adopted
following the rule of the five parameter model ofWilliam-Warnke [9] for concrete with the input ofwood material characteristic. To account for shear
stiffness reduction by shear crack deformation, theshear transfer model for concrete developed by AlMahaidi was included with the use of modified shear
transfer coefficient β of 0.35 for wood [8].
In this study, the material interface of the FEmodel between steel and concrete is considered

ANSYS Conta174 element [5].

Constitutive Model of Material
Concrete
Concrete is a quassi-brittle material and has different
behavior in tension and compression. In
compression, the stress - strain curve for concrete islinearly elastic up to 30 % of the maximum
compressive strength. The concrete constitutive
material model used here to define the failure of673

SEE - Nagoya, Japan, Nov.12-14, 2018

perfectly-bonded [11], while the material interface
between concrete and wood for WC1 is unbonded
performed by slightly reducing the stress-strain
relationship of wood. The material interface between
concrete and wood for WC1-S is assummed
perfectly bond [12].

against every possible movement, while applying theload was at the upper end. To duplicate such a
procedure, the bottom end (anchor plate/ stub
700.700.400 mm) of the simulated specimens was
fixed against all the degrees of freedom, as seen in
Figure 9. The load application was performed byapplying displacement to the upper end and the loadbearing capacity of the column was measured usinga reference point at the lower end [13].

(a)Restrained in ydirection

Cyclic lateral load
applied by displacement

Constant axial load
(red lines)(b)
Fig. 7 Tensile stress-strain relationship for (a) web
and (b) flange encased steel.

Restrained in x, y,
and z directions

Fig. 9 Boundary conditions of FE model
Loads

Fig. 8wood.

The loads are made to consider the experimental test
setup. The top-most columns were subjected to a
constant axial load of 1031 kN represented byapplying a point pressure of 1.4 kN on the stubelements with a total nodal of 717 in the FE model.
The horizontal displacements were provided tosimulate the cyclic load condition at the end of thecolumn. The lateral load cycles for the column were
controlled by story drift, R (the ratio between
horizontal to the column height) which is δ/h. The

Compresive stress-strain relationship for

Boundary Conditions
The experimental work has been done to test theaxial and lateral loads carrying capacity of EWECS
column were performed by fixing the bottom end
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SEE - Nagoya, Japan, Nov.12-14, 2018

lateral load sequence consisted of one cycles to each
R of 0.5, 1, 1.5, 2, 3, and 4%, followed by a halfcycle to R of 5%. Figure 10 shows the lateral cyclicload represented in the FE model.

gives contribution to flexural capacity by around
17% in maximum.

(a)Fig. 10 Lateral cyclic load (displacement)
RESULTS AND DISCUSSION
Hysteresis Characteristics
The load carrying capacity and stress distribution
are nearly same with minimum percentage of error.
The experimental hysteresis loops (shear force
versus story drift) for the WC1 and WC1-S arecompared with those obtained from the FE analysis
for the entire loading history, as shown in Figure 11.
The analytical results for hysteresis curve of the FEmodels show a good agreement with the test results.
Both the specimens and models show ductile andstable spindle-shaped hysteresis loops. Table 2 lists
the measured strength both EWECS columns at firstyield and at the maximum capacity.
From the FE model, the maximum lateral shear
force for WC1 column is 732 kN obtainedat last story drift 5%. This is approximately 3.1%
higher than the results obtained from theexperimental (709 kN). It is clear from Figure 12 (a)that the FE and experimental results arealmost the same behavior in each stage of cyclicloading. The average of different percentageof lateral shear force in each stage of loading cycles
between the FE analysis and the experimental results
is around 8.7%.
The maximum shear force for WC1-S is 804 kN
at R 5% from the FE analysis, which is 9.8% higher
than the experimentally obtained data (725 kN) at R
5%. The FE model behaved higher dissipated energy
in the each stage of loading cycles than theexperimental data, as seen in Figure 12 (b). The
average of different percentage of lateral shear
force in each stage of loading cycles between the FE
analysis and the experimental results is around 21%.
From the FE models, the presence of shear studs(b)Fig. 11 Comparison of hysteresis loops between
experimental and numerical results of (a) WC1 and(b) WC1-S.
Table 2 Measured strength
Model

Study

at Yielding

Qy
Exp.
367
Num.
373
WC1-S
Exp.
427
Num.
419
Note: Q (kN); and R (%).
WC1

Ry
0.55
0.50
0.70
0.74

at the Max.
Capacity
Qm
Rm
709
5
732
5
725
5
804
5

The difference between the FE and experimental
results at different stages of loading can be attributed
to mesh refinement, idealized boundary conditionsin the FE model, material nonlinearity, and thespecified coefficient of friction between contact
surfaces at the material interface of the columns.
Failure Mode and Principal Stress Distribution
The stress and strain in each of material element
is also analyzed to validate the FE models. A 0.002
principal strain is respectively reached in theencased steel of WC1 and WC1-S columns
models at story drift 0.51% and 1.1%, as indicated675SEE - Nagoya, Japan, Nov.12-14, 2018that the steel has first yield in oval shape in the
Figure 12. These results are almost similar with thetest data that the first yield in the corner region bothof top and bottom of the steel during experimental
are respectively at R 0.91% and 1.2%. In WC1
column model, the first crack in the concrete occurs
at R 0.4% in the strut zone of FE model, indicatedby maximum principal stresses (tensile) is greaterthan the tensile strength of concrete (3.1 MPa), as
shown inside the oval shape in Figure 13 (a). The
cracks occure spread on the strut area and propagate
along the horizontal direction.

(a)

(b)

Fig. 12 The principal strain at first yielding of the(a) WC1 and (b) WC1-S models.
Fig. 14 Comparison of failure mode of wood panelat (a) WC1-S and (b) WC-1 between experimental
and FE results.

(a)

The principal shear stress in the wood panel isshown inside the oval shape in Figure 14. The figure
shows that the crack occurred in the wood panels
assembled together by using wood glue at a shear
stress of approximately 7.24 MPa and 8.2 MPa(maximum principal shear stress) for WC1-S and
WC1, respectively. This corresponds to tangential
shear strength of normal wood at averaged 7.44 MPa
as suggested by Calderoni [14]. The crack occurs inthis location due to the weak shear strength of theconnection using wood glue during construction of
the specimen test. The cracks pattern are also formedat the opposite side. They propagate along a heightof the column.
Figure 15 shows the 1st principal normal stresson wood. The stress is concentrated on the edge
bottom and top of the wood, where sink (due tocompression) and uplift (due to tensile) occur. These
good comparative results confirmed the ability of the
proposed FE analysis to predict the maximum
strength and behavior of EWECS column underconstant axial and lateral loads reversals withacceptable accuracy.

(b)

Fig. 13 The principal stress at first crack and crush
in concrete core of the WC1 model.
Figure 13 (b) shows the minimum principal
stress (compressive) of concrete at last story drift,
where the value has exceeded the compressive
strength of concrete (49 MPa) that resulting in crush
on the top and bottom of the concrete.
676

SEE - Nagoya, Japan, Nov.12-14, 2018[3] H. Kuramoto, and Fauzan, “Feasibility study onengineering wood encased concrete-steel
composite columns”, Proceeding 11th Int.
Colloquium on Structural and GeotechnicalEngineering (11th ICSGE), Ain Shams
University, Cairo, Egypt, 2005.
[4] M. M. A. Kadhim, “Nonlinear FE analysis ofreinforced H.S. concrete continuous beamstrengthened with CFRP sheet”, Proceeding of
the ICASEIT, 2011, pp. 597 – 601.
[5] ANSYS Version 14. 2010. User’s and theoryreference manual.
[6] M. K. Hassan, M. F. M. Zain, and M. Jamil,“Finite element analysis of the effect of crack
depth and crack opening on the girder”,
Proceeding of the International Conference on
Advanced
Science,Engineering
andInformation Technology, 2011, pp. 646 – 651.
[7] L. P. Saenz, “Discussion of equation for the
stress-strain curve for concrete” Journal
American Concrete Institute, vol. 61(9), pp.
1229-1235, 1964.
[8] R. S. H. Al-Mahaidi, “Nonlinear finite element
analysis of reinforced concrete deep members”,
Rep. No. 79(1), Department of StructuralEngineering, Cornell University, Ithaca, New
York. 1979.
[9] K. L. Willam, and E. P. Warnke, “Constitutive
model for the triaxial behavior of concrete”,
Proc. International Association for Bridge andStructural Engineering (IABSE), vol. 19, Zurich,
Switzerland, 1975.
[10] H. Kuramoto, B. Li, K. Meas, and Fauzan,“Experimental and analytical performance
evaluation of engineering wood encased
concrete-steel beam-column joints”, Journal of
Structural Engineering ASCE, pp. 822-833,
2011.
[11] A. Leskes, and S. Grambicka, “Theoretical andexperimental studies on composite steelconcrete columns”, Proc. Eng. Science direct,
vol. 65, 2013, pp. 405-410.
[12] Fauzan,
andH.
Kuramoto,“Seismic
performance of EWECS composite columns in
new hybrid structural system”, Composite
Construction in Steel and Concrete, vol. 6, pp.
263–275, 2011.
[13] R. A. Hawileh, A. Rahman, and H. Tabatabai,“Nonlinier finite element analysis andmodelling of a precast hybrid beam-column
connection subjected to cyclic loads”, Journal
Applied Mathematical Modelling, vol. 34, pp.
2562-2583, 2010.
[14] C. Calderoni, G. D. Matteis, C. Giubileo, and F.
M. Mazolani, “Flexural and shear behavior ofancient wood beams: experimental andtheoretical evaluation”, Journal StructuralEngineering, vol. 28(5), pp. 729-744, 2006.

Fig. 15 Comparison of failure mode of wood panelin terms of sink and uplift of WC1 between
experimental and FE results.
CONCLUSION
Based on the analytical and experimental studies
presented here, the following conclusions can be
drawn:(1) EWECS columns using single H-section steel
had excellent structural performance without
severe damage, even at large story drift, R of 4%.
(2) The presence of shear studs on EWECS columns
improved the ductility of the column and reduced
the damage of wood panel, but there was no muchinfluence on maximum flexural strength of thecolumn.
(3) To modeling the slip behavior between concrete
and wood, it needs to reduce the strength of wood
about 5%. With shear studs, the woody panel
contributed to flexural capacity until large story
drift, R of 5%, although cracks appeared at thecolumn faces after R of 0.4 %.
(4) The calculated hysteresis loops using finite
element analysis showed a good agreement with theexperimental results, indicating that the analyticalmethod can be used to predict the ultimate strengthand behavior of EWECS columns.
REFERENCES[1] Ministry of Construction, Stipulation of criteriawith respect to structural calculations
performed to confirm the safety from the pointof view of structural capacity of wooden
columns. Building Standard Law of Japan
Notification No. 1349, May 23, 2000.
[2] Fauzan, H. Kuramoto, and K.H. Kim, “Seismic
performance of composite EWECS columns
using single H-steel”, Proceeding of JCI 27(2),2005, pp. 307-312.

677

WATER RESOURCES AND STORMWATER MANAGEMENTSTRATEGIES USING DUAL FUNCTION RAINWATER TANK INLABU RIVER BASIN MALAYSIA
Y.F. Huang1, Effie Nyanong1, K.F. Fung1
Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia

1

ABSTRACT
Rainwater harvesting is a water collection method that has gained more awareness, especially now that
there have been increasing water issues and flood problems around the world. A hydrologic-hydraulic model wasdeveloped to evaluate the potential and effectiveness of rainwater tanks for flood reduction in the Labu River
Basin. The feasibility of implementing rainwater tanks towards water supplement was then evaluated before theoptimum size of dual function rainwater tanks was determined by analyzing the effectiveness of rainwater tanks
in flood reduction, water supplement and also through economic analysis. The most appropriate tank size for bothflood mitigation and water supplement portions was 2m3. The 2m3 tank was found to be capable of reducing thepeak flow and maximum water level up to 14.29% and 1.57% respectively. Besides that, it also reduced the runoff
volume and flood period up to 100% while at the same time increased the time of concentration up to 66.04%.
The reliability ratios of the 2m3 tank when being simulated under the water usage of 250L and 750L for eachhouse per day was 82.5% and 45.3%, respectively.
Keywords: rainwater harvesting system, flood mitigation, water resources, Tangki NAHRIM
and administering sustainable drainage systems, plus it
is also applicable for the analysis, design and
Malaysia is blessed with sunshine and rain all year simulation of storm and wastewater systems and to
round with rain being one of the main sources of water. model flows in natural systems [19], [5], [10], [12]. By
However, it was not until a drought that occurred in incorporating a decentralized rainwater harvesting
1998 during El Nino that created a surge of interest in system, it is possible to reduce 20% of the peakrainwater harvesting by the Ministry of Housing and discharge [8], reduce the number of flooded areas
Local Government because the drought had brought within a river catchment [15] and increase the time ofunpleasant water supply disruptions for the Klang concentration [20], [15]. Tangki NAHRIM software on
Valley residents at the time. As of now, six states have the other hand is developed to ascertain the optimal size
gazetted the amendments to the Uniform Building By- of a rainwater storage tank system, the volume ofLaws 1984 to implement the Rainwater Harvesting and rainfall and rainwater distribution and also its reliability
Utilisation System (SPAH) at buildings and the states and efficiency [27], [6], [11]. It can also be used to
are Perak, Selangor, Johor, Melaka, Kelantan and Perlis. obtain rainfall data such as average monthly
SPAH had become very important because some states precipitations, average annual precipitations and also
were forced to carry out water rationing when the water the number of dry days [2]. In this paper, a duallevels in the dams dropped following a drought. function rainwater tank is proposed to be comprised of
Besides drought issues, there is also a growing water retention storage for water supplement and detention
demand due to the population growth and economic storage for flood reduction. The following section
development. Malaysia is faced with flood issues as covers the study of how the performance of eachwell, in which flooding is the most significant natural storage in water supplement and flood reduction
hazard in the country in terms of its effects to the respectively, can determine the optimum size of the
population, frequency, area extent, flood duration and dual-function rainwater tank which would minimizesocial economic damage.
space and maintain the best performance, at reasonable
In flood modelling, flood events are simulated to cost.
provide a better visualisation of flood events andunderstanding of flood risks. It usually involves both METHODOLOGYhydrologic and hydraulic modelling. Hydrologic
modelling involves the characterization of real Study Area
hydrologic features [3], [14] and some importantparameters that can affect flow in hydrologic modelling
The Labu River Basin was chosen mainly due to its
are inclusive of precipitation, hydrological loss rapid population growth and availability of its riverestimation and runoff estimation [4]. XPSWMM is a cross-section data. It is one of the basins within thecomprehensive software set for designing, modeling
INTRODUCTION

678

Langat River Basin and Labu River, the main river
within the basin, is the smallest tributary in Langat
River Basin. The location of Labu River Basin is asshown in Figure-1.
Due to its location, Labu River Basin has an
equatorial climate with annual average temperatures
between 20.5˚C and 36˚C [9]. The rainfall patterns areof moderately dry and moist and receive the lowest
yearly rainfall for Peninsular Malaysia [16], while themean monthly relative humidity range is from 80.6% to85.6% [18]. The types of soil within the study area aremainly (i) weathered Kenny Hill formation and (ii)quarternary alluvium that consists of unconsolidated tosemi-consolidated peat, clay, silt, sand and gravel [1].
There are a number of main land uses within the area
which include agricultural land, settlements, highways,
industry, forests, development projects, water bodies
and post landfill practices, in addition to having riverbanks that are wide and flat [9]. Furthermore, Labu
River is the main water source for the Salak Tinggi
treatment plant that caters for both Salak Tinggi and
Sepang areas [7].

Figure 1 Location of Labu River Basin in Langat River
Basin [21].
Flood Simulation
Design rainfall was used as the rainfall data for theflood simulation process and the calculations weredone based on the guidelines of the Urban Storm Water
Management [13] provided by Department of Irrigation
and Drainage Malaysia (DID). The formulas used are
as follow:
For overland flow,
to =107𝑛∗ 𝐿1/3
𝑆1/5

(1)

to = Overland sheet flow travel time
L = Overland sheet flow path lengthn* = Horton’s roughness value for the surface
S = Slope of overland surface
For drain flow,
td =𝑛𝐿
2/3 1/2

60𝑅

(2)

𝑆

td = Travel time in the drain
L = Length of reachn = Manning’s roughness coefficient679

S = Friction slope
R = Hydraulic radiusTime of concentration,
tc = t o + t d
Storm duration,td = c⁄60
Average rainfall intensity,
i =

𝜆𝑇к
𝜂
(𝑑+ 𝜃)

(3)
(4)
(5)

T = Average recurrence interval (ARI)d = Storm duration
λ, θ, η, к = Fitting constants
The storm duration obtained was used to determine
a set of temporal patterns from MSMA. These temporal
patterns were then utilized together with the rainfall
intensities to generate hyetographs in the XPSWMM
software which consequently fulfilled the rainfall datarequirement of the model.
For calibration and validation, the model was
simulated under the base scenario, a scenario in which
no rainwater tanks were installed at each house.
However, before simulations were done, the databasethat was developed in ArcGIS had to be imported into
the XPSWMM software first. The drainage system inLabu River Basin was drawn using the nodes and links
provided in the software.
After the base scenario was set up with all thenecessary information at both nodes and links in the
Runoff mode and Hydraulics mode, the model wascalibrated and validated. After that, another scenario
was added to the model, which was the rainwater tank
(RWT) scenario. The only difference between this
scenario and the base scenario was the presence ofrainwater tank in the former scenario. The Runoff mode
played a major part in this scenario, thus the adjustment
was mostly in the nodes of the Runoff mode. The
concept of the rainwater tank used for this research is
as shown in Figure-2. It is a dual tank that consists of adetention pond and also a retention pond. When
rainwater goes into the tank via the inlet, it will start tofill up the tank (assuming at the beginning the tank isempty). If the rain is heavy enough such that thedischarge at the inlet, Qin is the same as the discharge
at the first outlet, Qout_1 when the rainwater reaches thefirst outlet, it will discharge through the first outlet andinto the drain. In an extreme case such as long hours ofraining, the rainwater will surpass the retention pond
and proceed towards the detention pond instead ofdischarging through the first outlet because Qin > Qout_1.
Consequently, the rainwater will continue to rise until
it reaches the full capacity of the tank and excessive
rainwater will discharge through the second outlet.
After all the selected nodes were installed withrainwater tanks, the model was ready to be solved withboth base scenario and RWT scenarios being simulated
simultaneously. Three baseflows (¼, ½ and ¾), three
Average Recurrence Intervals or ARIs (5, 10 and 50
ARIs) and three tank sizes (2m3, 4m3 and 6m3) wereconsidered in the simulations and the results wererecorded and analyzed.

Figure 2 Rainwater tank concept used.
Water Supplement Simulation
The second main part of the methodology, the watersupplement simulation part, was executed to fulfill thesecond objective of the research; to evaluate thefeasibility of implementing rainwater tanks towards
water supplement and the software used was the Tangki
NAHRIM software. Before the simulations were done,
there were several inputs that had to be inserted into thesoftware first which include the rainfall station that will
supply rainfall data for the simulation, the roof
characteristics, the daily water usage and the size of thetank.
RESULTS AND DISCUSSION
Seven links were selected based on the percentage
of houses in their respective sub catchment for the
purposes of results compilation and discussion. An
additional link, Link 8, which was a representative of
the whole Labu catchment, was also included. The
percentage of roof area covered by all 8 links weretabulated in Table-1 and it was observed that Link 5 had
the biggest roof area coverage with 30.29%, followed
by Link 4 (17.3%), Link 3 (15.47%), Link 6 (8.9%),
Link 2 (8.81%), Link 1 (7.04%), Link 7 (1.99%) and
Link 8 (0.5%).
Table 1 Links and their respective percentage of roof
area coverage.
Link
1

Catchment Roof area
area (ha)(ha)
278.87
19.62

2

87.32

3
4
5
6

Percentage of roof area
coverage (%)
7.04%

7.69

8.81%

41.04

6.35

15.47%

77.85

13.47

17.30%

20.14

6.1

30.29%

25.50

2.27

8.90%

7

1252.73

24.96

1.99%

8

16669.46

83.38

0.50%

Overall, the results could be divided into two
categories; significant and less significant, based on thesignificance of peak flow, time of concentration andmaximum water level improvement from the basescenario to RWT scenario. Links 2, 3, 4, 5 and 6 hadsignificant improvement while Links 1, 7 and 8 had lesssignificant improvement. By taking Link 3 under 50
ARI as an example, its hydrographs comprising all tanksizes (2m3, 4m3 and 6m3) and baseflows (¼, ½ and ¾)
were presented in Figure-3 to Figure-11. For baseflow¼, in Figures 3, 4 and 5, it was observed that the valueof peak flow reduced from the base scenario to RWT
scenario in each hydrograph. The peak flow values inthe base scenario were discerned to be constant which
was 2.718m3/s. Meanwhile the values in RWT scenario
decreased, as tank size increased; from 2.652m3/s (2m3tanks) to 2.645m3/s (4m3 tanks), and further decreased
to 2.635m3/s (6m3 tanks). Thus the percentage of peakflow reduction for 2m3, 4m3 and 6m3 tanks scenarios
were 2.43%, 2.69% and 3.05% respectively, which
increased as tank size increased.
As for time of concentration, it could be seen from
Figures 3, 4 and 5 that the values of time ofconcentration increased from base scenario to RWT
scenario in each hydrograph. The time of concentration
values in Figures 3, 4 and 5 were also constant in thebase scenario, which was 3.433 hours. On the other
hand, the values in the RWT scenario increased as tanksize increased; from 5.65 hours (2m3 tanks) to 5.717
hours (4m3 tanks), and further increased to 5.85 hours(6m3 tanks). Hence the percentage of time ofconcentration increment for 2m3, 4m3 and 6m3 tanks
scenarios were 64.58%, 66.53% and 70.4%
respectively, which increased as tank size increased.

Figure 3 Flow hydrograph at Link 3 for 2m3 tank, 50
ARI and ¼ baseflow.

Figure 4 Flow hydrograph at Link 3 for 4m3 tank, 50
ARI and ¼ baseflow.

680

reduction in terms of other parameters were analysed at
the flood locations specifically instead, such as runoff
volume, flood period and maximum flood level, thoseparameters were observed to have more significant
results in comparison.

Figure 5 Flow hydrograph at Link 3 for 6m3 tank, 50
ARI and ¼ baseflow.
For the case of Link 3 under 50 ARI and ½ baseflow,
it could be seen that the value of peak flow reduced
from the base scenario to RWT scenario in eachhydrograph. The peak flow values in the base scenario
were observed to be constant which was 2.427m3/s.
Meanwhile the values in RWT scenario decreased, astank size increased; from 2.306m3/s (2m3 tanks) to
2.289m3/s (4m3 tanks), and further decreased to2.269m3/s (6m3 tanks). Thus the percentage of peakflow reduction for 2m3, 4m3 and 6m3 tanks scenarios
were 4.99%, 5.69% and 6.51% respectively, which
increased as tank size increased.
For the case of Link 3 under 50 ARI and ¾ baseflow,
it could be seen that the value of peak flow reduced
from the base scenario to RWT scenario in eachhydrograph. The peak flow values in the base scenario
were observed to be constant which was 2.255m3/s.
Meanwhile the values in RWT scenario decreased, astank size increased; from 2.105m3/s (2m3 tanks) to
2.083m3/s (4m3 tanks), and further decreased to
2.063m3/s (6m3 tanks). Thus the percentage of peakflow reduction for 2m3, 4m3 and 6m3 tanks scenarios
were 6.65%, 7.63% and 8.51% respectively, which
increased as tank size increased.
Overall, Link 3 under 50 ARI at all tank sizes (2m3,
4m3 and 6m3) and baseflows (¼, ½ and ¾) showed
positive improvement for both peak flow and time ofconcentration because as tank size increases, morewater can be stored into the tank, thus increases peakflow reduction and time of concentration increment.
Consequently, the percentage of maximum water level
reduction for Link 3 under 50 ARI also increased when
the tank size was increased, whereby the ranges were0.01%-0.5%, 0.02%-0.51% and 0.03%-0.55% for 2m3,
4m3 and 6m3 respectively. Similar results were also
observed for the rest of the scenarios under link 3 aswell as other links in the significant improvement
group.
During the simulations, there was flooding at several
locations in the model, thus those were considered as
flood events. The number of flood events decreased
with the installation of rainwater tanks in the rainwatertank scenario as shown in Figures 6, 7 and 8. When thetank size increased on the other hand, the number offlood events reduced was not significant because thepercentage of roof area coverage relative to thecatchment area was only 0.5%. However, when

Figure 6 Number of flood events under different
scenarios and ARIs for the case of baseflow ¼.

Figure 7 Number of flood events under different
scenarios and ARIs for the case of baseflow ½.

Figure 8 Number of flood events under different
scenarios and ARIs for the case of baseflow ¾.
Overall, the results for volume runoff, flood period
and maximum flood water level could be divided into
two categories based on the significance ofimprovement from base scenario to RWT scenario;
significant and less significant. Nodes E, H, J, K, L, M,
N and O were categorized as significant, while NodesA, B, C, D, F, G and I were categorized as lesssignificant. By taking node E as an example, thepercentage of volume runoff reduction and thepercentage of flood period reduction were both 100%,
under all tank sizes, baseflows and ARIs.

681

especially from 2m3 onwards, for both water usage
cases.

Table 2 Simulation results for water usage of 250L ineach house per day

CONCLUSION

Total rain
Rainwater
Tank size
volume Average per Reliability
captured(m3)
delivered day (m3)ratio (%)
3
(m )
(m3)
1

3939.54

1239.7

0.17

67.93

2

3939.541505.67

0.21

82.5

3

3939.54

1621.47

0.22

88.85

4

3939.541678.49

0.23

91.97

5

3939.54

1719.14

0.24

94.2

6

3939.541744.99

0.24

95.62

7

3939.54

1764.49

0.24

96.68

8

3939.54

1777.32

0.24

97.39

9

3939.541785.68

0.24

97.85

10

3939.54

1789.68

0.24

98.06

Table 3 Simulation results for water usage of 750L ineach house per day
Rainwater Total rain
Tank size
Average per Reliability
captured volume(m3)
day (m3) ratio (%)
delivered
3
(m )
3
(m )
1
3939.54
2093.99
0.29
38.25
2

3939.542480.89

0.34

45.31

3

3939.542746.91

0.38

50.17

4

3939.542969.85

0.41

54.24

5

3939.54

3100

0.42

56.62

6

3939.543199.63

0.44

58.44

7

3939.54

3286.09

0.45

60.02

8

3939.543350.91

0.46

61.2

9

3939.543403.83

0.47

62.17

10

3939.543455.79

0.47

63.12

The subsequent reliability ratio graphs based on the
two tables were plotted as shown in Figure-9 and it
could be seen that with each 1m3 increment, thereliability ratio difference was reduced insignificantly

Reliability ratio (%)

Consequently, the percentage of reduction of maximum
flood water level increased when the tank size
increased, whereby the ranges were 0.02%-0.18%,
0.18%- 0.92%, 0.56%-2.14% for 2m3, 4m3 and 6m3,
respectively. Similar results were also observed for the
rest of the nodes in the significant improvement group.
The results of water supplement simulation using
Tangki NAHRIM software were tabulated in Table-2
and Table-3 according to the daily household water
usage per house designated as 250L and 750L
respectively. It was observed from both tables that thereliability ratio increased as tank size increased.
However, for the same tank size, the 250L water usage
showed much higher reliability than the 750L water
usage. Thus it could be deduced that the higher thewater usage, the lower the reliability of the tanks.

120
100
80
60
40
20
0

250L
750L
0

5

10

15

Tank size (m^3)

Figure 9 Reliability ratio graphs for water usage of
250L and 750L

The incorporation of rainwater harvesting systems
in a catchment has the potential to reduce peak flow,
maximum water level, runoff volume, maximum flood
water level and number of flood events, while
simultaneously increase the time of concentration inwhich all these will subsequently assist in flood
mitigation works that would be very beneficial for thecountry in the future.
The 2m3 tank is the most suitable option among all
the tank sizes considered for water supplement
purposes (1m3, 2m3 and 3m3) and its setting up cost is
RM2038.18, which is the second highest of the three.
Despite not having the lowest setting up cost, itsreliability ratio is higher than the 1m3 tank that has thecheapest setting up cost (RM1703.90). When the 2m3
tank was simulated under the water usage of 250L per
day for each house, its reliability ratio was 82.5% ascompared to the reliability ratio of the 1m3 tank which
was 67.9%. Even when the water usage was increased
to 750L, the reliability ratio of the 2m3 tank remained
higher than the 1m3 tank, whereby the former was
45.3% as compared to the latter which was only 38.3%.
The reliability of a tank is a crucial factor in
determining the best tank size for any purpose but it isalso essential for the tank to have a moderate pricing,thus the 2m3 tank fulfils these criteria. The 3m3 tank has
the highest reliability ratio among the three (88.9% and50.2% under water usage of 250L and 750L
respectively) but consequently, its setting up cost is also
the most expensive (RM2611.50). Thus, 2m3 is anadequate tank size to fit the water supplement purposes
based on these reasons. Subsequently, between thethree tank sizes considered for the flood mitigation
portion (2m3, 4m3 and 6m3), 2m3 is the most suitabletank size considering that the consumption of either
4m3 or 6m3 tank will result in a rather unnecessarily
huge tank in total when it is added on to the watersupplement portion. All three tanks showedinsignificant difference when it comes to number offlood events reduced at the Labu River Basin (between
one to six flood events), thus a selection of any tanklarger than 2m3 for the flood reduction portion is rather

682

redundant. Furthermore, the 2m3 tank had shown anadequate overall reduction in the following parameters;
peak flow (reduction up to 14.29%), maximum waterlevel (reduction up to 1.57%), runoff volume (reduction
up to 100%) and flood period (reduction up to 100%).
Besides that, the increment of the time of concentrationby the 2m3 tank was satisfactory in general as well(increment up to 66.04%). Therefore, by taking allthese into account, it should be sufficient to deduce that
2m3 is also an appropriate tank size for the flood
mitigation purposes.
ACKNOWLEDGEMENT
The authors wish to express their sincere gratitude to
The Ministry of Science, Technology and Innovation(MOSTI), Malaysia, for the financial support.
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105-113.
[17] Shanahan, P., & Doyle, K. 2010. The impact offirst flush removal o rainwater quality andrainwater harvesting systems' reliability in rural
Rwanda. Proceedings of the World Environmental
and Water Resources Congress. ASCE.
[18] Sheriza, M. R., Ainuddin, N. A., Hazandy, A. H.
and Zulhaidi, M. S. H. 2011. Annual rainfall
estimation based on two different methods.
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[19] Toriman, M. E. et al., 2009. Integration of 1-dhydrodynamic model and GIS approach in flood
management study in Malaysia. Research Journalof Earth Sciences, 1 (1): 22-27.
[20] Wilkinson, M. E., Quinn, P. F. and Welton, P.
2010. Runoff management during the September
2008 floods in the Belford catchment,
Northumberland. Journal of Flood Risk
Management. 3 (4): 285-295.
[21] Zakaria, S. 2008. Management instruments for
Langat River Basin. Proceedings of the IWRMIHP Conference 2008 and 2nd Africa Regional
Meeting of the National Committees Of
UNESCO’s IHP, Cape Town ICC.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

A PRICE SETTING FOR AN EXCESS-BAGGAGE SERVICE AS A
FUNCTION OF FREIGHT PRICE
I.A. Shaban1, F.T.S. Chan*, and S.H. Chung
Faculty, University, Country; Company, Country1

ABSTRACT
According to IATA (International Air Transport Associate) reports in 2017, the uplift of passengers’
demand leads to the wide use of wide-bodied aircraft, in addition to the marked drop in the sea shipping
rates caused a clear decline in the air freight demand and overcapacity in the aircraft belly-hold. In this regard,
we discuss the aircraft overcapacity problem to fill the unused spaces in the belly-hold. Moreover, we confer
price setting for the new service with the reference to the freight price. For the sake of achieving this objective,
we adopted the multi-item newsvendor-based pricing model to derive a price formula for the excess-baggage
service as a function of freight price. Stochastic-Deterministic environment of excess-baggage and freight wasmodeled, respectively. The results showed that the optimal excess-baggage price can be determined as a functionof freight price in terms of base price plus the premium price. Finally, the model can be generalized to any two
products share common features and serve in the same market.
Keywords: Newsvendor model, Air freight, Combination airlines, Pricing.
Southeast Asia, the Middle east and Latin America
travelers are the major beneficiaries of the excess
baggage services, particularly they are the largest
users of wrapping services in the Southern Europe
airports[7]. Moreover, the free trade agreements
between the countries encourages the small
merchants to purchase products from the products’
country of origin [8] such as, the Hongkongers
travels to South Korea to bring the originalcosmetics. In this case, the larger the productamounts they buy from Korea, the higher the profit
they gain, and the heavier the luggage they carry to
the airport. Another significant example is thepeople who lives temporarily for long periods asforeigners, such as the post graduate students. The
minimum study period for PhD. is three years. Mostof these students during the study period buy many
properties but by the end of this period they need to
get them to their home countries. The expected
number of international PhD. students around theworld is 6.9 million by 2030[9]. therefore, they are
targeted to be excess-baggage customers.

INTRODUCTION
The air transportation is one of the mostprofitable markets beside the sea and rail freightshipping. According to IATA [1], the air freightshares over third of the world trade by value. Also,
Passengers is the second sector of the airtransportation business. Passenger sector is expected
to grow twice by 2035 [2]. The growth of passengers
leads to the wide use of the wide-bodied aircraft.
This trend causes an overcapacity problem in theaircraft belly-hold. However, the freight forecasts
refer to an increase, the unused space still larger[3].
In this research, we investigate the underutilized
aircraft belly-hold space. In this regard, we propose
and excess baggage pricing scheme to contribute in
attract more demand from the passenger’s excess
baggage. This excess baggage demand occupies
more space to fill the underutilized belly-hold space.
This research is motivated by the statistics of thecurrent excess baggage. For instance, the annual
charges which collected from British travelers forthe excess and overweighed bags exceeds £3.5
billion [4]. Also, the sum of profits of the american
airlines for the passengers’ excess baggage are morethan US$4 [5]. However, the numerical example
gives a sufficient proof that the excess baggage islarge enough, the passengers crooked method toaviod paying more charges for their excess bags andwieghts [6]A large segment of passengers might need forexcess baggage to carry the last-minute souvenir
purchases. For instance, the African, Gulf country,

Related Work
Recently, the capacity allocation problem hastaken a different direction than the last decades. In
the earlier years, the problem was treated such thatthe capacity less than the demand. Hellermann [10]designed an option contract between the single
airline and single forwarder. He induced thatpremium price policy is the best way to conduct thedeal instead of spot price reservations. The same
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excess baggage demand function, and 𝛿 is therandom variable of the demand function. The
demand variable is defined in range [𝐴, 𝐵].
Consider a single leg flight, where the aircraft
belly-hold is occupied by the passengers’ regularbags and excess baggage, and freights. Wong [8]designed the limits for the passengers’ regular bags
limits. Therefore, theoretically, the regular bags
occupy fixed space and they have the priority toallocation in the aircraft belly-hold. The rest of spaceis occupied by the combination of freight and theexcess baggage. The airline incurs operational costs
𝐶 for the combination of excess baggage and freight,
see Eq. (1):(1)
𝐶 = 𝑐𝑔 𝑥𝑔 + 𝑐𝑓 𝑥𝑓
Where 𝑥𝑔 , 𝑥𝑓 are the number of excess baggage,and freight units; 𝑐𝑔 , 𝑐𝑓 are the unit their unit costs.
Through the newsvendor setup the flight profit
𝜋 can be represented by Eq. (2)capacity options contract was updated to include
multiple forwarders using a Stackelberg game[11].
Usually the freight forwarder books the capacityin certain flight in advance. For the reason that theforwarder does not incur any penalties if they
cancelled part of their reserved capacity, the airline
sells the full capacity plus a buffer to avoid thecapacity shortage. Thus, Hellermann [12], added theoverbooking calculations to the option contracts.
Recently, the airlines have much space but they
do not have enough demand. This situation did notoccur suddenly, where the airlines update their fleet
in long while. So, the overcapacity takes place insome routes and some others stay overbooked whichmake imbalance between these routes [13].
In this research, we believe that the unused spacein the aircraft belly-hold can be filled by simplifying
and relaxing the excess baggage pricing schemes.
Considering two factors, the passengers’ regularbaggage limits which optimized by Wong [14], andusing the freight prices as a refence to calculate theexcess baggage new prices.
For the sake of formulating the excess baggage
price as a reference of freight price, the multi-item
newsvendor model was adopted.

Π(𝑝𝑔 , 𝑝𝑓 , 𝑥𝑔 𝑥𝑓 )𝑝𝑔 𝐷(𝑝𝑔 ) + 𝑝𝑓 𝑦(𝑝𝑓 ) − 𝐶 − 𝑂, 𝑖𝑓 𝐷(𝑝𝑔 ) + 𝑦(𝑝𝑓 ) ≤ 𝑥𝑔 + 𝑥𝑓={
𝑝𝑔 𝑥𝑔 + 𝑝𝑓 𝑥𝑓 − 𝐶 − 𝑆,𝑖𝑓 𝐷(𝑝𝑔 ) + 𝑦(𝑝𝑓 ) > 𝑥𝑔 + 𝑥𝑓

(2)

where, 𝑂 is the overbooking costs when the airline
offers spaces for excess baggage and freight morethan the expected market demand, and 𝑆 is theshortage costs when the offered space is less than theforecasted market demand. Eq. 3 and Eq. 4,

STOCASTIC - DETERMIMINSTIC MODEL

𝑂 = 𝑜𝑔 (𝑥𝑔 − 𝐷(𝑝𝑔 )) + 𝑜𝑓 (𝑥𝑓− 𝑦(𝑝𝑓 ))𝑆 = 𝑠𝑔 (𝐷(𝑝𝑔 ) − 𝑥𝑔 ) + 𝑠𝑓 (𝑦(𝑝𝑓 ) − 𝑥𝑓 )Consider an airline carries both passengers andfreights. let the freight service 𝑓 is sold at 𝑝𝑓 foreach freight unit, and the new excess baggage 𝑔price changes with the change of the freight price,suppose the new excess baggage price is 𝑝𝑔 pereach excess baggage unit. The airline need todetermine the optimal excess baggage price andquantity which maximizes its overall expected profit.
To formulate, we adopt the multi-item newsvendor
with price dependent demand function for bothexcess baggage, and freight services.
As the freight is a stable industry and there aremany demand forecasting models, we believe thatfreight demand can be modeled in a deterministic
form. Therefore, the demand can be represented by𝐷(𝑝𝑓 ) = 𝑦(𝑝𝑓 ) , where 𝑦(𝑝𝑓 ) = 𝑟1 − 𝑡1 𝑝𝑓 , asdiscussed in [15], and 𝑟1 , 𝑡1 are the additive demand
function coefficients.
On the other hand, the excess baggage, according
to the new price scheme, is not easy to predict. Thus,
it is better to be defined in a stochastic form. The
excess baggage may have a great variety because theits price must be controlled to keep the freight
demand stable specially in season. Hence, its
demand should be formulated in the iso-elastic form
which was discussed by Kocabıyıkoğlu [16]. So, theexcess baggage demand function is 𝐷(𝑝𝑔 ) =𝑦(𝑝𝑔 )𝛿 , and 𝑦(𝑝𝑔 ) = 𝑟2 𝑝𝑔 𝑡2 𝛿 , where 𝑟2 , 𝑡2 are thedemand function coefficients of the the iso-elastic

(3)
(4)

To make a linear relationship between the air
freight and the excess baggage, we assumed that the
combination of excess baggage and freight demands
equals to the aircraft belly-hold capacity 𝐺, and theproper form of the demand is 𝐷(𝑝𝑔 ) = 𝑟2 𝑝𝑔 𝑡2 𝛿, and𝐷(𝑝𝑓 ) = 𝐺 − 𝑦(𝑝𝑔 )𝛿 , define the 𝑤 value for theboth services by 𝑤𝑔 = 𝑥𝑔 /𝑦(𝑝𝑔 ), and 𝑤𝑓 = 𝑥𝑓 /(𝐺 −𝑦(𝑝𝑔 )𝛿). Thus, the excepted profit can be expressed
as in Eq. 5
𝐸[Π(𝑝𝑔 , 𝑝𝑓 , 𝑤𝑔 , 𝑤𝑓 )] = (𝑝𝑔 − 𝑐𝑔 −𝑝𝑔 + 𝑐𝑓 𝑤𝑓 )𝑦(𝑝𝑓 )𝜇 + (𝑝𝑓 − 𝑐𝑓 𝑤𝑓 )𝐺 −𝑤
(𝑐𝑔 + 𝑜𝑔 )𝑦(𝑝𝑔 ) ∫𝐴 𝑔(𝑤𝑔 −𝛿)𝑓(𝛿)𝑑𝛿 − 𝑜𝑐 𝐺(𝑤𝑓 −𝑤1) ∫𝐴 𝑔 𝑓(𝛿) 𝑑𝛿 + 𝑜𝑓 (𝑤𝑓 −𝑤(5)1)𝑦(𝑝𝑔 ) ∫𝐴 𝑔 𝛿 𝑓(𝛿)𝑑𝛿 − (𝑝𝑔 + 𝑠𝑔 −𝐵𝑐𝑔 )𝑦(𝑝𝑔 ) ∫𝑤 (𝛿 − 𝑤𝑔 ) 𝑓(𝛿)𝑑𝛿 −𝑔𝐵(𝑝𝑓 + 𝑠𝑓 )(1 − 𝑤𝑓 ) ∫𝑤 𝑓(𝛿) 𝑑𝛿 +𝑔(𝑝𝑓 − 𝑠𝑓 )(1 −𝐵

𝑤𝑓 )𝑦(𝑝𝑔 ) ∫𝑤 𝛿 𝑓(𝛿)𝑑𝛿.
𝑔

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SEE - Nagoya, Japan, Nov.12-14, 2018𝑤

𝐵−(𝑐𝑔 + ℎ𝑔 )𝑦(𝑝𝑔 )𝐹(𝑤𝑔 ) +(𝑝𝑔 + 𝑠𝑔 − 𝑐𝑔 )𝑦(𝑝𝑔 )[1 − 𝐹(𝑤𝑔 )].

Define ∫𝐴 𝑔 (𝑤𝑔 − 𝛿)𝑓(𝛿)𝑑𝛿 , ∫𝑤 (𝛿 − 𝑤𝑔 ) 𝑓(𝛿)𝑑𝛿 ,𝑔𝑤𝑔∫𝐴 𝑓(𝛿) 𝑑𝛿

,

and

𝐵

∫𝑤 𝛿 𝑓(𝛿)𝑑𝛿by𝑔

𝛬(𝑤𝑔 ), 𝛩(𝑤𝑔 ), 𝜛(𝑤𝑓 ), 𝜉(𝑤𝑓 ), respectively. Hence,the expected profit can be written in terms of theriskless profit and the expected losses as in Eq. (6)𝐸[Π(𝑞𝑔 , 𝑝𝑓 )] = 𝜓(𝑝𝑔 , 𝑝𝑓 ) − 𝐿(𝑞𝑔 , 𝑞𝑓 , 𝑝𝑔 , 𝑝𝑓 ), the maxima can be obtained if the second
derivative is less than zero,𝜕2 𝐸[Π(w𝑔 ,𝑝𝑔 )]

(6)

𝜕𝑤𝑔 2

Where
𝜓(𝑝𝑔 , 𝑝𝑓 ) = (𝑝𝑔 − 𝑐𝑔 − 𝑝𝑓 + 𝑐𝑓 𝑞𝑓 )𝑦(𝑝𝑔 )𝜇 +(𝑝𝑓 − 𝑐𝑓 𝑞𝑓 )𝐺.

(11)𝑐𝑔 )𝑦(𝑝𝑔 )𝑓(𝑤𝑔 ).

(7)

Equations (10) and (11) prove that the expected
profit function is concave in product 𝑔 quantity
when equation (10) is equal to zero. Similarly, theoverall expected profit is concave in both excessbaggage 𝑔 and freight 𝑓, Eq. (12).

, and𝐿(𝑤𝑔 , 𝑤𝑓 , 𝑝𝑔 , 𝑝𝑓 ) = (𝑐𝑔 + ℎ𝑔 )𝑦(𝑝𝑔 ) Λ(𝑞𝑔 ) +𝑤ℎ𝑓 𝐺(𝑞𝑓 − 1) ∫𝐴 𝑔 𝑓(𝛿) 𝑑𝛿 − ℎ𝑓 (𝑤𝑓 −1)𝑦(𝑝𝑔 ) 𝜛(𝑤𝑓 ) +(𝑝𝑔 + 𝑠𝑔 − 𝑐𝑔 )𝑦(𝑝𝑔 )Θ(𝑤𝑔 ) + (𝑝𝑓 + 𝑠𝑓 )(1 −= −[(𝑐𝑔 + 𝑜𝑔 ) + (𝑝𝑔 + 𝑠𝑔 −(8)𝐵𝑤𝑓 ) ∫𝑤 𝑓(𝛿) 𝑑𝛿 −𝑔𝜕𝐸[Π(w𝑔 , 𝑝𝑔 )]=0𝜕𝑝∗(𝑝𝑓 − 𝑠𝑓 )(1 − 𝑤𝑓 )𝑦(𝑝𝑔 )𝜉(𝑤𝑓 ).

Mills [15] defined the interpretation of the risklessprofit function, in equation (7), as a deterministic
profit value when replacing the uncertainty value ofthe product value 𝛿 by the mean value 𝜇 . In thismodel, the profit function holds excess-baggage andfreight and thus, the profit is a function of the twoitems prices. Also, Equation (8) is the loss function
according toSilver Edward and Peterson [17]definition, which evaluates the leftover cost
(𝑐𝑔 + 𝑜𝑔 ) for each value of Λ(𝑤𝑔 )𝑦(𝑝𝑔 ) of excessbaggage, and the expected leftover when too large
value of is selected; in addition to (𝑜𝑓 𝐺) for eachlikelihood of the leftover in excess-baggage minus
the mean value of 𝑜𝑓 in the range [𝐴, 𝑤𝑔 ]; moreover,
if the value of 𝑤𝑓 is chosen more than one, and theshortage costs for excess baggage is (𝑝𝑔 + 𝑠𝑔 + 𝑐𝑔 )for each Θ(𝑤𝑔 )𝑦(𝑝𝑔 ) expected shortages when too
small value of 𝑤𝑔 is selected. The shortage costs ofthe freight service are (𝑝𝑓 + 𝑠𝑓 ) for the likelihood ofexcess-baggage quantity minus (𝑝𝑓 − 𝑠𝑓 ) for
expected excess-baggage quantity; if the value of 𝑤𝑓
is chosen less than one. The expected profit isdepicted in (6), and the riskless profit occurs incertain selected demands with no uncertainty, andthe uncertainty factor in the model is added to the
expected penalties.
The objective of the model is to maximize theexpected profit in Eq. (7):Max𝑖𝑚𝑖𝑧𝑒 𝐸[(Π(𝑤𝑔 , 𝑝𝑔 )]𝑤𝑔 ,𝑝𝑔

Theory For fixed excess-baggage and freight
quantities, the optimal price of excess-baggage 𝑔 isdetermined uniquely as a function of the freight
service 𝑓 and the integrated quantities of the twoservices:
𝑝𝑔 ∗ =𝜇𝑝𝑔 0

𝜇−Θ(𝑤𝑔 )

𝜕𝑤𝑔

=

+

𝑏[(𝑐𝑔 +𝑜𝑔 )Λ(𝑤𝑔 )−𝑜𝑓 (𝑤𝑓 −1)𝜛(𝑤𝑔 )(𝑏−1)(𝜇−Θ(𝑤𝑔 ))

+

(13)

𝑏[(𝑠𝑔 −𝑐𝑔 )Θ(𝑤𝑔 )−(𝑝𝑓 −𝑠𝑓 )(1−𝑞𝑓 )𝜉(𝑤𝑔 )](𝑏−1)(𝜇−Θ(𝑤𝑔 )).

𝑏(𝑐𝑔 +𝑝 −𝑐 𝑞 )𝑓 𝑓 𝑓
where 𝑝𝑔 𝑜 =𝑏−1
Proof. for the multiplicative demand of excessbaggage, 𝑝𝑔 𝑜 is the optimal riskless price, which

maximizestheriskless

profit𝜓(𝑝𝑔 , 𝑝𝑓 ) =(𝑝𝑔 − 𝑐𝑔 − 𝑝𝑓 + 𝑐𝑓 𝑞𝑓 )𝑦(𝑝𝑔 )𝜇 + (𝑝𝑓 − 𝑐𝑓 𝑞𝑓 )𝐺,−𝑏where 𝑦(𝑝𝑔 ) = 𝑎𝑝𝑔 , by definition. The maximum
value of the riskless profit function can be obtained
when equating the first derivative w.r.t 𝑝𝑔 to zero,
Thus, letting:𝜕𝜓(𝑝𝑔 ,𝑝𝑓 )𝜕𝑝𝑔= (𝑝𝑔 − 𝑐𝑔 − 𝑝𝑓 + 𝑐𝑓 𝑞𝑓 )𝑦′(𝑝𝑔 )𝜇 +𝑦(𝑝𝑔 )𝜇;𝑎 𝜇 𝑝𝑔 −𝑏−1 [𝑏(𝑐𝑔 + 𝑝𝑓 − 𝑐𝑓 𝑞𝑓 ) − (𝑏 − 1)𝑝𝑔 𝑜 ] = 0.
therefore, the maximum value of 𝜓(𝑝𝑔 , 𝑝𝑓 ) is at(9)

𝑝𝑔 𝑜 =

The first and the second partial derivatives of𝐸[(Π(𝑤𝑔 , 𝑝𝑔 )] are taken with respect to 𝑤𝑔 and 𝑝𝑔
𝜕𝐸[(Π(𝑤𝑔 ,𝑝𝑔 )](12)𝑏(𝑐𝑔 +𝑝𝑓 −𝑐𝑓 𝑞𝑓 )𝑏−1,

Next, regarding the overall expected profit
function in equation (6), determine the optimal priceof excess-baggage as a function of the air freight,
and maximize the expected profit. We need to

(10)
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SEE - Nagoya, Japan, Nov.12-14, 2018

The excess-baggage price elasticity 𝒃 sets the
maxima of the excess-baggage riskless price, as
shown in Figure 2, where the riskless price of theexcess-baggage decreases exponentially withincrease of the excess-baggage price elasticity.
The Theory captures the optimal price of theexcess-baggage as a function of the freight price andmixed quantities of both services. The price equation
contains three terms; each term expresses animportant concern in order to set the price forexcess-baggage with reference to the freight price.
The theorem explains the main theme of the pricing
scheme which can be followed to set the price of theexcess-baggage with the aid of the freight price. Thismodel is inspired from Petruzzi and Dada [19]who’s model considers the use of single period
newsvendor model to set the price of a single
product.
The authors defined the optimal price of the
product as the sum of the base price and thepremium amount in the multiplicative demand
function, whereas our model uses product priceinformation to set a different
product price.
Theorem 1, defines the base as price equaling theriskless price of the excess-baggage multiplied by asafety factor and the premium value which is afunction of the overall expected shortage and theoverall expected leftover amount, and the expectedsales of the excess-baggage. Hence, the excessbaggage optimal price can be expressed by equation(13),
𝑝𝑔 ∗ =𝑝𝐵𝑔 +(13
𝑏[𝐸[𝑙𝑒𝑓𝑡𝑜𝑣𝑒𝑟 (𝑤𝑔 ,𝑝𝑔 )]+(𝑠𝑔 −𝑐𝑔 )𝐸[𝑠ℎ𝑜𝑟𝑡𝑎𝑔𝑒 (𝑤𝑔 ,𝑝𝑔 )]]−)(𝑏−1)𝐸[𝑠𝑎𝑙𝑒𝑠(𝑤𝑔 ,𝑝𝑔 )]equate the first differentiation of the (6) w.r.t 𝑝𝑔 tozero;𝜕𝐸[(Π(𝑤𝑔 ,𝑝𝑔 )]𝜕𝑝𝑔 ∗= (𝑝𝑔 − 𝑐𝑔 − 𝑝𝑓 + 𝑐𝑓 𝑤𝑓 )𝑦 ′ (𝑝𝑔 )𝜇 +𝑦(𝑝𝑔 )𝜇 − (𝑐𝑔 + 𝑜𝑔 )𝑦 ′ (𝑝𝑔 )Λ(𝑤𝑔 ) + 𝑜𝑓 (𝑤𝑓 −1)𝑦 ′ (𝑝𝑔 )𝜛(𝑤𝑔 ) − (𝑝𝑔 + 𝑠𝑔 − 𝑐𝑔 )𝑦 ′ (𝑝𝑔 )Θ(𝑤𝑔 ) −𝑦(𝑝𝑔 )Θ(𝑞𝑔 ) + (𝑝𝑓 + 𝑠𝑓 )(1 − 𝑞𝑓 )𝑦 ′ (𝑝𝑔 )𝜉(𝑤𝑔 ).
hence;−𝑎𝑏𝑝𝑔 −𝑏−1 (𝑝𝑔 ∗ − 𝑐𝑔 − 𝑝𝑓 + 𝑐𝑓 𝑞𝑓 )𝜇 + 𝑎𝑝𝑔 −𝑏 𝜇 +𝑎𝑏𝑝𝑔 −𝑏−1 (𝑐𝑔 + 𝑜𝑔 )Λ(𝑤𝑔 ) − 𝑎𝑏𝑝𝑔 −𝑏−1 𝑜𝑓 (𝑤𝑓 −1)𝜛(𝑤𝑔 ) + 𝑎𝑏𝑝𝑔 −𝑏−1 (𝑝𝑔 ∗ + 𝑠𝑔 − 𝑐𝑔 )Θ(𝑤𝑔 ) −𝑎𝑝𝑔 −𝑏−1 Θ(𝑤𝑔 ) − 𝑝𝑔 ∗ Θ(𝑞𝑔 ) − 𝑎𝑏 𝑝𝑔 −𝑏−1 (𝑝𝑓 +𝑠𝑓 )(1 − 𝑤𝑓 )𝜉(𝑤𝑔 ) = 0.
Thus,𝒑𝒊 ∗ =

𝝁𝒑𝒈 𝒐
𝝁−𝚯(𝒘𝒈 )+𝒃[(𝒄𝒈 +𝒐𝒈 )𝚲(𝒘𝒈 )−𝒐𝒇 (𝒘𝒇 −𝟏)𝝕(𝒘𝒈 )](𝒃−𝟏)(𝝁−𝚯(𝒘𝒈 ))𝒃[(𝒔𝒈 −𝒄𝒈 )𝚯(𝒘𝒈 )−(𝒑𝒇 −𝒔𝒇 )(𝟏−𝒘𝒇 )𝝃(𝒘𝒈 )(𝒃−𝟏)(𝝁−𝚯(𝒘𝒈 ))+.

The riskless price 𝒑𝒈 𝒐 is concave in the freight
price, where the excess-baggage riskless priceincreases with the increase of freight price until itreaches a turn down point then the excess-baggage
riskless price decreases. The airline can forecast
short-term market demand, andis most likely acombination of the Gamma and normal distributions
as mentioned by Swan [18]. Thus, the randomvariable is normally distributed in the application ofnumerical analysis with 𝜇 = 0.6, 𝑎𝑛𝑑 𝜎𝑔 = 0.2 .
See Figure 1.

Excess-baggage riskless
price𝒃[𝒐𝒇 [𝒐𝒗𝒆𝒓𝒂𝒈𝒆 𝒐𝒇 𝒘𝒇 ]+(𝒑𝒇 −𝒔𝒇 )𝑬[𝒔𝒉𝒐𝒓𝒕𝒂𝒈𝒆 𝒐𝒇 𝒘𝒇 ]](𝒃−𝟏)𝑬[𝒔𝒂𝒍𝒆𝒔(𝒘𝒈 ,𝒑𝒈 )].

Therefore, the interpretation of the base andpremium prices may be described next; the baseprice is obtainable from estimating the total costs ofthe excess-baggage service multiplied by the safety
factor “SF” which ensures that the riskless price is
not underestimated by dividing the mean demand
over the expected sales, where 𝑺𝑭 ≥ 𝟏 , The baseprice is also concave in the freight price, see Figure
3.
The base price concavity is flatter in the actual
range of freight prices, so we assumed a larger rangeof excess-baggage at freight prices to show the curve
behavior. The airline can manage the safety factor

Freight priceFig. 1
A plot of excess- baggage riskless price𝑝𝑔 0 as a function of freight price 𝑝𝑔 ranging from
0.5 to 10 in increment 0.025, the freight quantity is
assumed as 16000, a1=20000, b1=1.5, and b2=1.25.

687

SEE - Nagoya, Japan, Nov.12-14, 2018

Excess-baggage riskles priceby studying the demand average and the expectedshortage.
Moreover, the premium value in selling pricefor the excess-baggage is based on the formulawhich considers the overall expected leftover of theexcess-baggage,

This is because of the demand uncertainty in theexcess-baggage, thus the sum of the expectedpenalties of the 𝒇 freight service is subtracted fromthe expected penalties of the 𝒈 excess-baggage anddivided on the overall expected excess-baggage
sales.

30

CONCLUSION

25

In this paper, a new excess baggage and theoverweight scheme are identified and discussed as aservice combined with the freight in a combination
airline. The excess-baggage pricing scheme is
proposed as a solution for overcapacity resulting
from the extensive use of wide-bodied aircraft andthe reduction in the sea shipping rates. The excessbaggage is treated as a special freight service, andwe show that the excess-baggage can be considered
as a freight if the passenger acts as a shipper andsends luggage to a freight forwarder. The frieght
forwader inturn forwards them to the airline whichassign these luggage to the aircraft belly-hold, in
addition to permitted baggage.
The extra-baggage price can be set with reference
to the cargo prices, in terms of base price, andpremium value. The extra-baggage price is the sumof the base price and the estimated premium value.
The premium value is the expected penalties overthe expected sold capacity and can be either positiveor negative.

20
15
10
5
0
1

1.25

1.5

1.75

2

2.25

Excess-baggage price elsaticity

Fig. 2A plot of excess-baggage riskless price asa function of price elasticities, (a) Freight priceelasticity and, (b) Excess-baggage price elasticity.
, in addition to the overall expected shortage costs ofthe same service.
The result agrees` with Petruzzi’s results, but
this model holds a defined service, freight service,
which is the airline’s main service, so the freight
service affects the price of the new excess-baggage
service.

ACKNOWLEDGEMENTS
The work described in this paper was supported
by a grant from the Research Grants Council of theHong Kong Special Administrative Region, China(Project No. PolyU 15201414); a grant from The
Natural Science Foundation of China (Grant No.
71471158); and a grant from the ResearchCommittee of The Hong Kong Polytechnic
University under student account code RUMZ.

Excess-baggage base price

25

20

15

10

REFERENCES
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Freight priceFig. 3A plot of excess-baggage base price as afunction of freight prices.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

BOND STRENGTH PREDICTION MODEL OF CORRODED
REINFORCEMENT IN CONCRETE USING NEURAL NETWORK
1

Nolan C. Concha1,2 and Andres Winston C. Oreta3
PhD Student, De La Salle University, Philippines; 2Faculty, FEU-Institute of Tech., Philippines
3
Faculty, De La Salle University, Philippines

ABSTRACTThe expansion of corrosion products in steel-concrete interface offers radial tensile stress resulting todevelopment of cracks in reinforced concrete structures. This corrosion induced cracks promotes bond reduction
which involves intricate non-linear interactions. To deeply understand the underlying mechanisms involved in thebond strength of corroded rebars in concrete, a novel bond prediction model using artificial neural network (ANN)was developed. Accelerated corrosion was performed to 108 cube samples using 500 µA/cm2 current density. Steelbond strength after 35 and 70 days impressed corrosion exposure of concrete cube samples was measured using
single pull out test. The compressive strength, tensile strength, rebar diameter, embedment length, concrete cover,ultrasonic pulse velocity (UPV), crack severity, and corrosion level were the predictors in the ANN bond model.
Among all the bond strength models considered in this study, the proposed neural network model provided themost desirable bond estimates in good agreement with experimental results. The ANN model further showedsuperior prediction performance against the derived regression model.
Keywords: Bond strength, Corrosion, Crack severity, Impressed current
INTRODUCTION

enveloping concrete. The actual underlying bondbehavior of steel bars in concrete might not beadequately describe by these assumptions. In fact,
there has been an observed contradicting results
obtained between analytical and empirical equations
due to the uniform thick-walled cylinder analogy
adopted in the development of the models [3]–[4].
The formation of corrosion and its corresponding
effect on the bond between concrete and steel
involves complex interactions. One potential method
to model the dominant and complicatedinterrelationships among the variables of corrosion
and bond is artificial neural networks (ANNs). Recent
researchers have found the power of ANN to model
complex interactions and provide superior prediction
performance [5]–[6]. Through the set of input-output
data from a battery of tests conducted, ANN develops
a network of neurons that can be tuned up tosynthesize information and eventually learn.
A novel prediction model of bond behavior ofreinforcing steel bars in reinforced concrete due tocorrosion using artificial neural network will be
developed in this paper. Bond strength model using
multiple regression will be derived as well for further
comparison. Larger number of variables will beconsidered in the modeling including crack andcontinuity of concrete. The model will allow early
detection of the level of bond degradation between
concrete and steel in a simple and fast approach. Thisin turn leads to timely repair that can improve thesafety and prolong the service life of the structure.

Corrosion of steel reinforcements due to chloride
ingress is regarded as one vital structural healthconcerns in concrete structures. Embedded bars at
this rusting stage expand and develop radial stresses
in concrete resulting to cracking, bulging, andspalling of concrete. Corrosion also results to thebuckling, snapping, and ineffective bondcharacteristics of reinforcements due to continued
reduction in the effective bar size. When subjected toreinforcement corrosion, concrete structures
experience delamination in which the oxidized metal
requires greater space causing a wedge-like stress.
Surface and internal cracks tend to develop in
concrete and promote exposure of reinforcements tocorrosion. This in turn imparts excessive reduction in
the bond strength characterized by the adhesion andslippage resistance between steel and the enveloping
concrete. Ultimately the serviceability and durabilityof reinforced concrete are significantly reduced andpotentially results to structural collapse. Because ofthis, studies in developing bond strength andcorrosion resistance of reinforcing bars has remained
a popular research interest [1].
In the development of corrosion models
particularly in the numerical and analytical modelling,
several ideal assumptions were considered. The study
of El Maaddawy and Soudki [2] assumed that the
thickness of corrosion around the bar was uniformly
distributed and exerts a constant radial pressure in the690

SEE - Nagoya, Japan, Nov.12-14, 2018

cover of 60mm, 70mm, and 80mm were used.
Embedment lengths of 50mm, 75mm, and 100mm
were used to achieve an even bond stress distribution
within the entire embedment length of the rebar. The
properties of the materials were tested in compliancewith ASTM standards. The density and water
absorption of coarse aggregates were measured andfound to be 1572.028 kg/m3 and 0.402% respectively.
Similarly, for fine aggregates, the recorded values of1533.801 kg/m3, 3.2 %, and 2.673 for density, water
absorption, and fineness were respectively observed.
These results were used to proportion three design
mixes having target compressive strengths of 21 MPa,
28 MPa, and 35 MPa. Table 2 shows the material
proportions and average strengths corresponding toeach mixture using 0.68, 0.57, and 0.47 preliminary
ratios of water-cement, slump values from 25mm to100mm, and 2% entrapped air.

BOND STRENGTH MODELS OF CORRODEDSTEEL BARS IN REINFORCED CONCRETE
Impressed corrosion method was used by mostresearchers in the development of bond-corrosion
model. The effects of corrosion level in bond strength
loss and cracking of concrete using impressed method
were investigated by previous studies [7]–[9].
Monotonic pull out test was conducted on concrete
samples to develop bond strength models. Derived
models showed reasonable agreement between themeasured experimental results and empiricallyestimated values of bond strength. Unlike any otherstudies that focus on bond strength, the study of
Yaciner [1] model an equation for the ultimate bondstrength (tbu) using multiple linear regression. The
bond equation is dependent on concrete compressive
strength (f’c), cover (c) to bar diameter (D) ratio andcorrosion level (CL). Results showed that increase inconcrete compressive strength and concrete cover
improved the measured bond strength. Moreover, it
was found out that an increase in the compressive
strength with constant concrete protective cover
resulted to higher bond strength than a constantcompressive strength with increasing concrete
protective cover. Using ultra-high toughness
cementitious composite, Hou et al. [10] developed amodel to estimate the bond strength (tu) of a corroded
rebar as a function of rebar diameter (d), bond lengthlb, and corrosion ratio (ρc). The bond decreased up to
15% corrosion ratio but is almost the same with noncorroded samples. The prediction equation was able
to give acceptable results as compared withexperimental values recorded in the conduct of pullout tests of cylindrical samples. Table 1 shows thesummary of bond prediction models from various
literatures.

Table 2 Concrete design proportions and strengths
Design W
C
Mix kg/m3 kg/m3
1
189
301
2
189
359
3
190
436
Testing of Specimens
After curing for 28 days to gain strength, thesamples were immediately immersed in a 5% brine
solution as shown in fig. 1. A current density (i) of
500 µA/cm2 from a constant power source wasallowed to pass through the reinforcements embeddedin the concrete prism to accelerate the corrosion. A
total of 108 samples were subjected to accelerated
corrosion for 35 days and 70 days to generatesufficient corrosion products that will developinternal radial stress enough to cause internal andexternal cracks in the concrete.

Table 1 Bond strength models of rebars in concrete
CabreraLee and
WeyersChung et al.

CA
FA
f’c
ft
kg/m3 kg/m3 (MPa) (MPa)1018 866
22
2.081018 806
29
2.61
1018 726
36
3.14

fbo = 23.478 - 1.313C

t max = 0.34s b - 1.93 if D w < D wc
t max = 5.21e -0.0561Dw if D w ³ D wc
ub = 16.87 for Co £ 2.0
ub = 24.7Co-0.55 for Co >2.0

( )Yalciner et al.

t bu = 0.40551 f ' c - 0.25306 c D + 0.97926CL ( R 2 = 0.98)

Hou et al.

æd ö
t u = 0.335 éë-0.124rc2 + 1.183rc + 93.504ùû ç ÷
è lb ø

0.379

EXPERIMENTAL PROGRAM
Fig. 1

Materials and Specimens

Concrete cubes under accelerated corrosion

Likewise, the crack severity (CS) expressed as the
product of the crack length (L) and the representative
crack width (W) was determined. In order to measure
the opening of crack in each of the samples, several
polycarbonate reference points were attached to thesurface of the concrete. The development of the

The experiment in this study used 108 concrete
cube samples in total with sidelength 200 mm. Bar
diameters, concrete cover (cc) and embedment
lengths (Ld) were varied in the concrete cube samples.
Three deformed reinforcing bars of 16mm, 20mm,
and 25mm in diameters with corresponding concrete691

SEE - Nagoya, Japan, Nov.12-14, 2018

distance between the reference points were measured
using an electronic caliper. Using the measured
values in every crack line, the product of the length
and width was taken and the sum of all the results ineach specimen was used to represent the crack
severity of the sample. After which ultrasonic pulse
velocity test was performed to assess the quality ofconcrete samples after 35 days and 70 days impressedcurrent. The transducer and receiver of the UPV
apparatus was positioned in direct set up. The resultsof the test were used as input variable in the bondmodel representing the homogeneity andcompactness of concrete.
The bond strength of the rebar in concrete after
accelerated corrosion was measured using pull out
test in compliance with ASTM C234-91a. The pullout strength was determined by measuring the
maximum force required to pull the rebar from theconcrete sample. The bond strength (µ) was
calculated by taking the ratio of the maximum applied
force (P) and the surface area of the reinforcing steel
rebar in contact with concrete. Figure 2 shows thefractured concrete sample after performing single pullout test using the universal testing machine.

Fig. 2changes in the recorded values between uncracked
and cracked groups. Sudden drop in the UPV andbond strengths were obtained from almost all thesamples in the group. The average UPV of 4081 km/s
and average bond strength of 6.591 MPa for cracked
samples were substantially lower than the meanvalues from the uncracked samples. These reductions
were attributed to excessive amount of corrosion in
the reinforcement resulting to the development ofinternal and surface cracks in the samples. Moreover,corrosion level was even higher for samples in thecracked group with an average and maximum valuesof 1.015% and 3.254% respectively. Samples having
high corrosion levels in general correspond to highcrack severity. The maximum observed crack severity
was 215.492 mm2 and the average value in all thesamples was 77.791mm2. The dominant compressive
strength in the cracked group was 29 MPa while thediameter of the rebar was 25mm. Based on thestandard deviation and COV, higher variability wasobserved for UPV, corrosion level, crack severity,and bond strength of the samples.
Bond Strength Regression Model of Corroded
Reinforcement
The bond strength as a function of concrete
compressive strength, tensile strength, embedment
length, diameter, concrete cover, UPV, crack severity,and mass loss was developed using multiple linear
regression. The derived polynomial regression
equation with adjusted R square of 0.899 and standard
error of 3.262 is given in eq. (2). The embedment
length, rebar diameter, the root of the product ofcompressive strength and tensile strength of concrete,
and the crack severity offered reduction in bondstrength as described by the negative coefficients inthe model. For the other variables however, a direct
correlation with the bond strength were observed.
Among the variables considered in the model having
P values less than 0.05, the embedment length, rebar
diameter, UPV, and crack severity offered significant
effect on the bond strength. The observation was
reasonable since these parameters were interrelated
and dominated the behavior of bond. Substantialchange was observed in the experimental bond values
particularly on the vast number of samples in thecracked group attributed to the variation of theseparameters.

Concrete cube sample after pull out test

Prior to the casting of concrete in the mold,deformed bars were weighed to determine the initial
mass (Mo) before accelerated corrosion. After
performing the accelerated corrosion process and pullout testing of the samples, all pulled off bars werecleaned from corrosion products at the surface of therebar and weighed to record the final mass (Mf). The
actual percentage of mass loss or corrosion level (CL)of each bar was calculated using eq. (1).
CL =Mo - M f
Mo

x100%

(1)

EXPERIMENTAL RESULTS
Experimental Data Statistics

t = -0.106l d -0.236d + 0.009cc - 0.064 f ' c*ft
+0.006UPV - 0.040CS + 0.840C L

Among the 108 cube samples subjected toimpressed current method of accelerated corrosion,
74 of which or 69% were able to exhibit crack
formations due to the level of corrosion in thereinforcement. There were observed significant

The performance of the regression model inpredicting bond resistance of concrete is shown in fig.
3. Vast majority of points lied closely to the 45° line
indicating satisfactory prediction performance of themodel. The Pearson correlation coefficient of the
692

(2)

SEE - Nagoya, Japan, Nov.12-14, 2018

scatter plot was 0.831 showing good agreement
between experimental and predicted bond values. The
average prediction error was 31.81% with minimum
error of 0.61%. In all the predicted bond strengths,roughly 45% lied within ±20% error while 19% of thepredictions provided more than ±50% error.
Considering the fuzziness of the experimental bondstrengths, the bond regression model was able toprovide satisfactory prediction of the bond strength of
concrete.

Fig. 3The bond strength results obtained from shortterm pull out test of 100 samples was used in thedevelopment of the model. Seventy percent of thedata pairs was used in the training phase of the modeland the other 30 percent was used in the testing phase.
Carpenter and Barthelemy [11] suggested a minimum
number of training data pairs not greater than thenumber of weights and biases to achieve distinct
approximation. Further, an over determined data of
20-50% will yield satisfactory performance of the
ANN model [12]. Considering the neural networkarchitecture N 8-7-1 having seven nodes in the hidden
layer and using 20% overdetermined network, therequired minimum number of input-output data pairs
must be between 76 to 96. With this constraint, thedata used in the simulation was found sufficient toachieve the desired performance of the various ANN
models. In selecting the best performing ANN
architecture among the variations considered, meansquared error (MSE) and correlation coefficient (R)were used as performance metrics. The model having
the least MSE and closest R value to 1.0 will emerge
as the best ANN model. The result of simulations offour ANN models with their corresponding MSE and
R are shown in table 3. Apparently, the neuralnetwork model having 7 nodes in the hidden layer
provided the most desirable performance indicators.
N 8-7-1 model exhibited the least bond strength
prediction errors in good agreement withexperimental values. The model was able to achievelearning considering multiple predictors andfuzziness in the introduced data pairs. The MSE and
R of the derived model were 2.678 and 0.957
respectively. In contrast, N 8-5-1 model having 5
neurons was the least performing model.

Bond strength regression model predictions

NEURAL NETWORK MODELLING
Framework of the Neural Network Model
The input layer of the neural network model wascomposed of eight individual distinct nodes. Eachnode represents the predictors in the model which
includes the compressive strength (f’c), tensile
strength (ft), embedment length (ld), rebar diameter(f), concrete cover (cc), ultrasonic pulse velocity(UPV), corrosion level (CL), and crack severity ofconcrete (Cs). One hidden layer was used in the modeland the number of hidden nodes was varied between
5 to 8. The output layer was composed of one node
representing the bond strength output of the model.
Neural network model structure having 8 input nodes,
4 hidden layer neurons, and single node in the output
layer was denoted as N 8-4-1. In the development of
the model, the learning algorithm used was
feedforward backpropagation algorithm. The
hyperbolic
tangent
sigmoidfunctionf(n)=2/(1+e-2n)-1 was employed as neural activation
function which return values between -1 to 1 in the
output layer. An error tolerance of 0.001 andmaximum cycles of 100000 were used as thresholdcriteria to cease the simulation process. Early
stopping, validation phase in the development of themodel, and few number of hidden nodes wereconsidered to minimize the chance of overfitting andenhance the generalization of the ANN model.
ANN Model Experimental Data and Simulations

Table 3 Variation of ANN models
Model
N 8-5-1
N 8-6-1
N 8-7-1
N 8-8-1

Number of
hidden nodes
5678

Performance criteria
MSE
R
3.623
0.941
3.478
0.943
2.678
0.957
3.148
0.952

Connection Weights and Biases of N 8-7-1 Model
Table 4 shows the weights and biases of the
proposed neural network model. Each seven nodes in
the hidden layer was associated with connection
weights in the input and output layers. The relative
importance of each predictor in the model using thecausal inference procedure developed by Garson [13]was also reflected in the table. The ultrasonic pulse
velocity was found to be the most significant
predictor in the bond strength with a relative
importance of 20.11%. Associated to this variable
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SEE - Nagoya, Japan, Nov.12-14, 2018

were the crack severity and corrosion level having
relative importance of 13.01% and 15.63%
respectively. The results were reasonable since higher
corrosion levels offer immense radial tensile stress inthe samples resulting to excessive crack formations
and sudden fall in the UPV values. Measured bondstrengths in the pull-out test were significantly
affected by the change in values of these three

independent variables. The concrete compressive
strength was found to be the least significant predictor
having 8.08% relative importance. The strength of
concrete barely offered substantial effect on themeasured bond strength of the samples. Majority ofthe samples achieved internal and external crack
formations.

Table 4 Connection weights and biases of N 8-7-1 model
Hidden
Nodes
1
2
3
4
5
6
7
BiasesRel. Impt. (%)

Input Layer
f
cc

f’c

ft

Ld

1.71181.1845-0.6978-0.0326-1.0295

5.3538-0.2653 -2.4959

0.27930.43720.5614-1.4098

0.2691-3.4692-0.2920

2.4862 0.7990

0.0155-0.4544

1.14191.35580.37520.23382.9630-3.0908 3.2125

2.84762.4621

1.0616

3.12354.23680.5334-1.7865

1.3760 1.3494-0.2731-0.1467

1.55630.89800.71510.5034

1.87260.3141 -0.4767

0.93850.08870.81011.42310.33940.24692.5854-2.4950 2.5881-3.0964-2.2206-1.6088

1.4915-3.1291-1.3239

1.09830.3039 2.1818

0.3688-5.1069-0.6449

2.8476-0.1126

3.8667-0.0931-3.8237-0.7184

8.09

10.618

12.66

10.03

9.85

20.11

13.01

Prediction Performance of N 6-6-1 Model

UPV

Cs

CL

Output
Layer

15.63

the bond performance of the proposed ANN model
against the developed models of Yalciner et al. [1],Cabrera [10], Lee and Weyers [11], Chung et al. [12],Hou et al. [13], and the developed regression equation.
The experimental and predicted results of theenumerated models were plotted in fig. 5. The scatterplot diagram was so dispersed demonstrating large
deviations of the points from the 45° line. The models
developed by Cabrera [10], Chung et al. [12], andHou et al. [13] gave overestimated values of the bondstrength due to the limitations of the variablesconsidered. Most of the proposed models provided
significant errors in the prediction results. This can be
attributed to the inability of the models to capture
significant bond reduction in the presence of internaland surface cracks in the concrete. The proposed N 87-1 model on the other hand was able to exhibit
robustness in predicting the bond strength of thesamples. A close fit can be seen from the graph with
R value of 0.971. The limitation of the hidden nodes
and the early stopping adopted in the development of
the model worked so well to improve thegeneralization. The average observed error in theprediction results was 19.53% with maximum andminimum errors of 45.48% and 3.68% respectively.
The superiority of the proposed model was credited
to equally important variables such as UPV and crack
severity which were not considered in other models.

About 76% and 84% from training and test data
sets respectively were within the ±10% error. Though
there were few misfits of roughly 15% providing
more than 25% prediction errors, the model was able
to perform well in training and testing phases of thesimulation. The experimental and predicted values ofthe model for both phases were plotted as shown infig. 4. The model was able to perform better in thetesting phase giving an R value of 0.983 and average
error of 16.27%. The R value and average error in the
training phase of the model were 0.954 and 19.69%
respectively. Vast majority of samples with overall R
equal to 0.957 exhibited a close fit from the 45° line
showing desirable agreement between predicted andexperimental results. The average ratio ofexperimental to predicted values of 1.03 further
demonstrate robust performance of N 8-7-1 model inthe prediction of bond strength.
Comparison Between N 8-7-1 Model and Other
Bond Strength Models
Various bond prediction models available in theliterature were considered and compared to theperformance of the proposed N 8-7-1 model. Eightbond strength values from experimental data were notused in the calibration. This data set was used to test

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 4

Bond strength regression model predictions

Fig. 5

CONCLUSIONS

Bond predictions using different models[4] Alonso, C., Andrade, C., Rodriguez, J. and Diez,
J. M., Factors controlling cracking of concrete
affected by reinforcement corrosion,Materials andStructures, 31, August- Sept 1998, pp. 435-441[5] Yan, F., and Lin, Z., New strategy for anchorage
reliability assessment of GFRP bars to concrete
using hybrid artificial neural network with genetic
algorithm, Composites
Part
B:
Engineering, 2016, 92, 420-433.
[6] Rinchon, J. P. M., Concha, N. C., and Calilung, M.
G. V., Reinforced concrete ultimate bond strength
model using hybrid neural network-genetic
algorithm, 2017 IEEE 9th HNICEM (pp. 1-6).
IEEE.
[7] Cabrera, J. G., Deterioration of concrete due toreinforcement steel corrosion, Cement andconcrete composites, 1996, 18(1), 47-59.
[8] Lee, H. S., Noguchi, T., and Tomosawa, F.,
Evaluation of the bond properties between
concrete and reinforcement as a function of thedegree of reinforcement corrosion, Cement andConcrete research, 2002, 32(8), 1313-1318.
[9] Chung, L., Kim, J. H. J., and Yi, S. T., Bondstrength prediction for reinforced concrete
members with highly corroded reinforcing bars,
Cement and concrete composites, 2008, 30(7),603-611.
[10] Hou, L., Liu, H., Xu, S., Zhuang, N., and Chen,
D., Effect of corrosion on bond behaviors of
rebar embedded in ultra-high toughness
cementitious composite, Construction and
Building Materials, 2017, 138, 141-150.
[11] Carpenter, W. C., and Barthelemy, J., Common
misconceptions about neural networks as
approximators, J. Comput. Civ. Eng., 1994, 83 ,345 – 358.
[12] Carpenter, W. C., and Hoffman, M. E., Training
backprop neural networks, AI Expert, March
1995, 30–33.
[13] Garson, G. D., Interpreting neural-network
connection weights, AI expert, 1991,6(4), 46-51.

In the simulation of several neural networkarchitectures having eight input predictors and one
response variable, the N 8-7-1 model with sevennodes in the hidden layer emerged as the best
performing model. The proposed model provided
mean squared error and Pearson correlation
coefficient of 2.678 and 0.957 respectively indicating
robustness in estimating the pull-out resistance ofcorroded reinforcements in concrete. The model
further demonstrated superior prediction performanceand generalization among the bond models
considered in this study. Crack severity and ultrasonicpulse velocity predictors of the model in relation to
the formation of corrosion products in rebars offeredsignificant effects in the bond behavior. The
emergence of these two predictors were in agreementwith the results of causal inference procedureproviding respective high relative importance of
20.11% and 13.01%. With all the desirable attributesof the model, the proposed N 8-7-1 can be used toconveniently estimated the bond resistance ofcorroded steel in reinforced concrete.
REFERENCES[1] Yalciner, H., Eren, O., and Sensoy, S., An
experimental study on the bond strength between
reinforcement bars and concrete as a function of
concrete cover, strength and corrosion
level, Cement
andConcrete
Research,
2012, 42(5), 643-655.
[2] El Maaddawy, T., and Soudki, K., A model for
prediction of time from corrosion initiation tocorrosion cracking, Cement and concrete
composites, 2007, 29(3), 168-175.
[3] Rodríguez, J., Ortega, L., Casal, J. and Diez, J.,
Corrosion reinforcement and service life ofconcrete structures, Durab. Build. Mater.
Compon., 1996, 7 (1), pp. 117-126.

695

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DIFFERENTIAL SETTLEMENT OF SHORT PILED RAFT
FOUNDATION SYSTEM ON PEAT DURING LOADING TEST
Sajiharjo Marto Suro1, Adnan Zainorabidin2, Agus Sulaeman3 and Ismail Bakar2
1
STT-PLN, Indonesia; 2 UTHM, Malaysia; 3 ST-INTEN, Indonesia

ABSTRACTThis research observed the behavior of 3.0 m x 3.0 m large scale model of Short Piled Raft foundation systemon peat during loading test. The sequence of loading test consisted of loading - unloading - reloading - remain unloading, from 0 kN - 100 kN (100% design load) - 0 kN - 160 kN (160% design load) - remain for 24 hours - 0
kN, with increment or decrement of 20 kN, and had no failed. Five locations were observed, one at the centre andthe other four at each corner. After conducting the test, it was seemed that the maximum of total settlement ST(max)was 7.80 mm, 29.90 mm and 36.20 mm, occurred at the center [CR], while the maximum of difference in total
settlement between any two points ∆ST(max) was 1.95 mm ([SW] – [NE]), 10.30 mm ([SW] – [SE]) and 9.65 mm([SW] – [SE]), under the load of 100 kN, 160 kN and remain of 160 kN for 24 hours respectively. The ST(max)occurred at the centre was easily understood, because the load was acting on it. Differential settlement might occur,
because peat underneath the foundation was not homogeneous, thus, response of piles to contribute supporting
load might also be different, and finally produced differential settlement. It was also seemed that the piles could
function as stiffener of concrete slab effectively. The tolerable settlement is ST(max) < 50 mm and ∆ST(max) < 20 mm,
therefore it could be concluded that ST(max) and ∆ST(max) which occurred were tolerable.
Keywords: Differential settlement, Total settlement, Loading test, Short piled raftfoundation, with the pile length relatively shorter, andconsidered as a reinforced concrete slab resting on anumber of piles. The piling activity during
construction as shown in Fig. 1.

INTRODUCTION
With increasing in urbanization in last three
decades all over the world, and due to limited landavailable, many construction projects have penetrated
into the problematic soil area, with some of the
problems faced [1]. Completion of construction byusing a conventional foundation system such as pilefoundation system is still considered to be quite
expensive [2]. To overcome these problems, several
foundation systems have been developed, among
others, is a piled raft foundation, which the concept of
this system has received considerable attention inrecent years [3] and even proves to be more effective
on such conditions, increasingly recognized as afoundation more economical and effective on
problematic soil [4].
At the peat area, the construction method on peat
is different for the different depth of peat [5]. For peatwith depth less than 3 m, the removal andreplacement method are usually used. For the depth 3
m to 10 m, engineers normally used sand drain,lightweight fills and stone column. While for thedepth more than 10 m, the suitable method is deep
stabilization techniques such as pile and dynamic
compaction [6].
In this study, a Short Piled Raft foundation system
was introduced, built on peat which is known asproblematic soil. Short Piled Raft foundation system
is a modified piled raft foundation system, which is acombination between pile foundation and raft

Fig. 1
696

Adjusting pile verticality during piling

SEE - Nagoya, Japan, Nov.12-14, 2018

The basic concept of Short Piled Raft foundation
system considers passive soil pressure creating a stiff
condition of slab-pile system. This means that the thinconcrete slab floats on the supporting soil while thepiles serve as stiffeners slab concrete and also to
improve stability performance by reducing settlementof the foundation [7]. Figure 2 shows a phase of
construction before casting concrete slab.

METHODOLOGY
Loading test was conducted follows ASTM
Standard D 1143 - 81: Standard Test Method for Piles
under Static Axial Compressive Load. This test
method covers procedures for testing vertical or batter
piles individually or groups of vertical piles todetermine response of pile or pile group to a static
compressive load applied axially to the pile or piles
within the group, regardless of their method of
installation. There are three methods of applying load
as follows. Considering that peat is very soft soil, themost suitable was the method of Load Applied to Pileor Pile Group by Hydraulic Jack Acting against a
Weighted Box or Platform, although still needed to bemodified as shown in Fig. 3.

Fig. 3Fig. 2Modified method of applying load for
Loading Test

For conducting loading test, 16 concrete beams of
0.40 m x 0.40 m x 6.0 m were provided and laid on
an I profile steel beam. Figure 4 shows arranging of
concrete beam for loading test.

Reinforcement of concrete slab before
casting concrete slab

SCOPE, LIMITATION AND OBJECTIVE
The scope of this study was to observe thestability performance of a large scale model of Short
Piled Raft foundation system on peat during loading
test. The static load acted on the center of the concreteslab, as simulation of transmission line tower.
The limitation of this study was that the size of themodel to be 3.0 m x 3.0 m, with 0.15 m thickness ofconcrete slab, piled by 9 short piles of 3.0 m length,
outer diameter was 0.32 m and thickness of wall was
0.003 m. The pile was closed end galvanized steel
pipe, with the pile spacing of 1.00 m, as optimum
spacing [8] and constructed on peat with the layer
thickness of 3.5 m.
While the objective of the study was to evaluate
the differential settlement occurred at 5 points
observed on concrete slab during loading test, basedon the Recommendation of European Committee forStandardizationon
Differential
Settlement
Parameters.

Fig. 4 The last concrete beam would be laid as load
Loading was carried out by jacking the steel beamat the center point of concrete slab. Location of point
load and points observed shown in Fig. 5.

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SEE - Nagoya, Japan, Nov.12-14, 2018

The phase of loading test and its sequence asshown in Table 1.
Table 1 Sequence of Reading during Loading and
Unloading Test
PHASE

Location of Point Load and Point Observed

Loading Procedure
Unless failure occurs first, load the pile up to at least
160% of the group design the pile until the settlement
equals 15% of the pile diameter. Due to themagnitude of the decline could not be precisely
predicted, therefor constant time interval loading was
suitable procedure to be applied. Applying loadincrements of 20% of the design load with 1 hour
between load increments and unload with 1 hour
between load decrements.

For measuring movements, a leveling instrument(Sprinter) was used to measure some staff gauges that
installed at several certain observed points, as shownin Fig. 6.

Fig. 6

-

0

5
10
5
10
5
10
5
10
5
10
5
10
5
10
5
10
20
60
120

33.0
34.0
35.0
36.0
37.0
38.0
39.0
40.0

20
20
20
20
20
20
20
20

140
120
100
80
60
40
20
0

Final
Rebound

52.0

720

0

Remain160 kN

Procedure of Measuring Movements

Loading/Unloading
(kN)

0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
10.0
20.0
32.0

Loading
From 0 kN untill 160 kN
with icrement of 20 kN

Fig. 5Interval(minute)Unloading
From 140 kN until 0 kN
with decrement of 20 kN

InitialDuration
Cumul.
(hr)

20
40
60
80
100
120
140
160
160

During loading, provided that the test pile group
has not failed, additional readings should be taken andrecorded them at intervals 5 minutes during the first½ hour for each load increment. After the total load
has been applied, provided that the test pile group has
not failed, readings and record should be taken at theinterval of 20 minutes during the first 2 hours and 1
hour for the next 10 hours, and 2 hours for the next 12hours. If pile failure occurred, the readings should betaken immediately before removing the first loaddecrement. During unloading, readings and record
should be taken at intervals of 20 minutes. A final
rebound reading has been taken 12 hours after all load
has been removed.

(a)(b)
Leveling instrument, (a) Sprinter and (b)staff gauge.

Before testing, no-load reading should be taken for all
instruments, including staff gauge, and ground waterlevel meter. Taking the reading of time, load andmovement, and record them before and after theapplication of each load increment or the removal ofeach load decrement.
698

SEE - Nagoya, Japan, Nov.12-14, 2018

RESULTS AND DISCUSSIONS
Loading test was conducted until 160 kN or equal
to 160% of design load (100 kN) and the foundation
had no failed.
The data of settlement reading at the end of every
stage of loading, unloading, preloading and remain
were tabulated in Table 2.
Tabel 2 Relationship between load and settlement

FINAL
BOUND

UNLOADINGREMAIN

RE-LOADINNG

UNLOOADINGLOADING

Phase

Load
[kN]
0.00
20.00
40.00
60.00
80.00
100.00
80.00
60.00
40.00
20.00
0.00
0.00
20.00
40.00
60.00
80.00
100.00120.00140.00160.00160.00160.00160.00160.00160.00160.00140.00120.00100.00
80.00
60.00
40.00
20.00
0.00

SW
0.00
0.50
1.50
2.35
4.35
6.75
6.70
6.35
5.40
3.90
1.50
1.50
2.65
4.30
4.95
6.15
9.80
13.15
19.05
26.10
26.10
26.60
27.90
28.90
31.10
31.10
32.25
32.15
31.70
31.40
30.10
27.85
25.10
22.55

Settlement [mm]
NW
CR
SE
0.00
0.00
0.00
0.30
0.90
0.30
2.10
1.10
1.40
2.00
2.90
2.20
3.70
5.20
3.70
5.90
7.80
6.00
5.90
7.60
6.00
5.90
7.00
6.10
4.80
6.20
4.80
3.60
4.40
3.70
1.70
1.50
1.90
1.70
1.30
1.90
2.90
2.60
2.80
3.90
4.00
4.90
4.80
5.60
4.50
5.50
6.30
7.00
8.90
9.10
10.90
11.70
14.80
12.60
21.30
17.00
14.50
22.50
16.70
29.90
30.60
22.80
16.50
24.10
31.90
17.20
33.00
25.00
17.10
35.20
27.20
19.40
28.30
23.40
36.20
36.20
28.30
23.40
36.30
28.40
23.40
23.40
36.20
28.30
22.70
35.60
28.00
22.60
35.40
27.60
21.40
33.80
26.60
19.50
30.90
25.00
17.30
27.50
22.90
15.20
24.30
21.00

NE
0.00
0.70
1.80
2.30
4.00
5.70
5.90
5.50
4.90
3.50
1.70
1.70
2.80
4.40
5.10
7.00
10.00
12.60
16.50
19.50
19.90
21.00
21.60
24.20
24.50
24.50
24.40
24.60
24.50
24.40
23.70
22.80
21.10
19.00

0.00

22.30

15.10

18.50

24.10

20.70

Fig. 7

Relationship between load and settlement at
the center of concrete slab (CR)

From the data reading, settlement under the loadof 100 kN at each point observed were notsignificantly different, as shown in Fig. 8.

Fig. 8Relationship between loading up to 100 kN
and settlement at each point observed.

There were similar patterns of relationshipbetween load and settlement at every observed point,
it meant that the concrete slab moved down
simultaneously, indicated that the pile functioned as
stiffener of concrete slab effectively [7].
While at the SW point was 7.65 mm was relatively
larger than at the three point at another corners,
because under this part, the original soil was disturbed
due to for lifting remain big tree and filled back again
without any compaction. It means that heterogeneityof peat may influence immediate settlement of Short
Piled Raft foundation system.
The settlement under the load of 160 kN at eachpoint observed were presented graphically, as shownin Fig. 9.
There was a little bit strange data for curve line ofsettlement pattern of SE point from the load of 120
kN to 140 kN, that shown less settlement. But after
reached 160 kN, the curve back to similar condition.
Heterogeneity of peat might cause this phenomenon.
While the maximum of difference in total
settlement between any two points ∆ST(max) was 1.95
mm ([SW] – [NE]), 10.30 mm ([SW] – [SE]) and 9.65
mm ([SW] – [SE]), under the load of 100 kN, 160 kN
and remain of 160 kN for 24 hours respectively, lessthan 20 mm [9].

The data could also be presented graphically, as
an example, point at the center of concrete slab (CR)was taken as typical of settlement pattern, as shownin Fig. 7,
It can be seen that the patterns of relationshipbetween loading up to 100 kN and settlement weresimilar to relationship between loading up to 160 kN
and settlement. The maximum of total settlement
ST(max) occurred at the center (CR) of 7.80 mm under
the load of 100 kN, 29.90 mm under the load of 160
kN and 36,20 mm under the remain load of 160 kN
for 24 hours, less than 50 mm [9].

699SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 9[2]

Effendi, S., Cakar Ayam Soft Foundation
System Revisited. Soft Soil Engineering
International Conference 2013, Kuching,
Sarawak, Malaysia, 2013.

[3]

Prakoso, W. A. and Kulway, F. H., Contribution
To Piled Raft Foundation Design. Journal of
GeotechnicalandGeoenvironmental
Engineering, 2001, pp.17-24.

[4]

Srilakshmi, G. and Moudgalya, D., Analysis ofPiled Raft Foundation Using Finite Element
Method. International Journal of Engineering
Research and Science & Technology, Vol. 2,
No. 3, 2013, pp.89-96.

[5]

Bakar, I., Challenges in Peat Soil Research Malaysian Experiences. South East Asia
Conference on Soft Soils Engineering and
Ground Improvement, Bandung, 2014.

[6]

Huat, B. B. K., Prasad, A., Asadi, A. andKazemian, S., Geotechnics of Organic Soils
and Peat. CRC Press/Balkema, 2014.

[7]

Hardiyatmo, H. C., Analisis dan Perancangan
Fondasi II, Gadjah Mada University Press,
Edisi Ketiga, 2015, pp. 487-515.

[8]

Suro, S. M., Bakar, I. and Sulaeman, A., Pile
Spacing Optimization of Short Piled Raft
Foundation System for Obtaining Minimum
Settlement on Peat, IOP Conference Series:
Materials Science and Engineering, Volume
136, Conference 1, 2016.

[9]

Das, B. M., Principles of Foundation
Engineering, Seventh Edition, Cengage
Learning, 2011.

Relationship between loading up to 160 kN
and settlement at each point observed.

CONCLUSION
Based on the discussion, it can be concluded asfollows.
1. The loading test of Short Piled Raft foundation
system up to 160 kN or 160% of design load shownthat settlements at each point simultaneously moved
down with small differences. It means that beside assupporting the load, piles were also well functioning
as stiffener of concrete slab.
2. The maximum of total settlement ST(max) occurred
less than 50 mm and the maximum of difference intotal settlement between any two points ∆ST(max) lessthan 20 mm..
ACKNOWLEDGEMENTS
The research work reported in this paper was
funded by Contract Research Grant U260 ORICC,
Universiti Tun Hussein Onn Malaysia (UTHM).
The authors wish to express their gratitude to
RECESS - UTHM and Geomatic Engineering
Laboratory, FKAAS - UTHM in providing theequipments during carrying out this research.

[10] ASTM, Standard Test Method for Piles Under
Static Axial Compressive LOAD, Designation
D 1143 – 81 (Reapproved 1994).

REFERENCES[1]

Patil, J. D., Vasanvala, S. A., Solanki, C. H., A
Study on Piled Raft Foundation: State of Art,
International Journal of Engineering Research& Technology (IJERT), 2013, pp.1464-1470.

700

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

SETTLEMENT BEHAVIOR OF ROAD SURFACES CAUSED BY
DISSOLUTION OF SALT LAYERS
Siwadol Saenseela1, Pongsagorn Poungchompu2*, Gomin3
Chairatanangamdej Rajamangala University of Technology Khonkaen
address:
ppoungchomphu@gmail.com*Corresponding author; E-mailCampus,Thailand

ABSTRACTThis research was aimed at studying the settlement behavior of road surfaces caused by dissolution of salt
layers that in turn create cavities. The dissolution can happen naturally or occur from salt mining. The proposed
project’s site was Highway 2229 from km4 +066 to km 4+275, Kud Ruakham Sub-district, Ban Muang District,
Sakonnakhon Province. The 2015 soil layer drilling survey revealed layers of hard clay and compact soil or shalewith low plasticity. Cavities were found at the depth of 42 meters over sand stone layers. The analysis of roadsurface settlement was based on the Empirical Method and theories of Peck(1969(, O’Reilly and New(1982(, andRankin(1969( to determine the i and Vs parameters based on Smsx from the surveys of road surface settlementfrom 2013 to 2018. Using the survey results, the analysis by the theory of O’Reilly and New (1982( showed i at
21 m and Vs ranging from95 % to 102% of Vs. The analysis based on the survey data and Rankin’s theory(1969( showed i equal to 19.16m and Vs between 87% and93 % of Vs. The analysis of the surveyed data showed
end of surface settlement in 2016, which was consistent with the drilling survey in 2017 from which no cavities
were found on the sand stone layers.
Keywords: Settlement, Salt layer, Cavities, Empirical Method

unbreakable. Salt is able to flow from the edge of aglade towards the center or from top to bottom underpressure. Movement of salt is termed ‘salt tectonic’(Figure 2)]2[. The geological study of theMahasarakham rock group hierarchy as discoveredfrom the general drilled pits indicates 4
characteristics of the rock are as following.

INTRODUCTION
The Northeast of Thailand is principally
composed of mountains and glades. The two major
glades are Korat Glade and Sakonnakhon Glade; thesoil underneath of each contains layers ofMahasarakham rock group as shown in Figure 1,
with alternate layers of halite and clay]1[.

Fig.2 Structures of halite and potash classified under
Mahasarakham rock group ]2[-Three salt bed-Two salt bed-Potash-bearing one salt bed-Potash-barren one salt bed
Halite can be destroyed by water. When halite
under soil surface has continuously been destroyedby the water retained in the same layer, a cavity isformed. This cavity, if wide and if the soil-rocklayers above fail to bear the load, will collapse into a

Fig. 1 1999 Geological map of Korat high plain in
the Northeast containing Phu Tok andMahasarakham rock groups - scale 1:1,000,000]2[
The Mahasarakham rock group is mainlycomposed of halite, which, in a great amount and in
thick layers, naturally and physically becomesplastic, that is, deformable, flowable, and
701

SEE - Nagoya, Japan, Nov.12-14, 2018

sinkhole. The majority of sinkholes in Korat and
Sakonnakhon Glades have been found in areas
where saline water was pumped up for rock salt
mining purpose and also in areas adjacent to the rocksalt fields. Sinkholes in salt fields are usually notdisclosed. However, if they are in the areas nearby,
especially near communities or residential areas, thesinkholes will be reported on the news. Sinkholes
threaten lives and assets of people living in thevicinity ]3[.
Singh (1992) explained that such collapse takes
place as a result of interference from external stress.
Changes of stress affect the forms and movement ofrock and soil layers. The extent of settlement
depends on the degree of stress and the size of cavity
or pit hole which lead to instability. Therefore, soil
surface collapse or settlement is the function of soil
tectonic activity arising from a collapse of a cavity
underneath. Soil surface settlement in general resultsin vertical as well as lateral slides. Soil surface
settlement is caused by 3 factors, namely: 1) cracks,
splits, or different degrees of cracks, 2) sinkholes orholes, 3) water puddles or soil depressions ]4[.
Elashiry et al. (2008) conducted a study ofsurface soil settlement of a phosphate mine bycomparing the efficiency of the settlement equations
proposed by Bal, Peng, Knothe, and Peck. In sodoing, they compared the true measurement
parameters against the steepness, curve, andplasticity. The method proposed by Peck yielded theparameters closest to the reality, with the coefficientaccuracy over 0.9]5[.
This study was conducted on the settlement ofroad surface using the Empirical Method for the
analysis. The survey data of road surface settlementfrom 2015 until 2018 were analyzed along with thedata from soil survey by drilling in 2015 and 2017
comprising both vertical and horizontal soil
movement (Figure 3 and Figure 4).

Fig. 4 Horizontal movement (2017)
METHODOLOGY
The study site was Highway No. 2 2 2 9 from km
4+066 to km 4+275 I Kud Rua Kham Sub-District,
Wanonniwat District, Sakonnakhon Province. The
information retrieved showed that the highway wasconstructed before 1975 and the settlements weredetected in 2012. The aerial survey showed saline
water pumping from underground for a rock salt
mining purpose(Figure 5).
Chaiyan Hinthong and Adul Charoenprawat(1990) indicated that they found sinkholes in thearea of Ban Jampadong School in Khu Sakham SubDistrict, Wanonniwat District, Sakonnakhon
Province. There were detected sinkholes at Dinso
Brook and along the brook’s line. Sinkholes of 2-3
m size were also found at the school’s fence. Basedon the Nares Sattayarak’s tectonic movement
information, it is believed that the saline layer lies
within the 70 m level ]6[.
The drilling survey of soil layers in 2015 (Figure6) shows that the depth of 0-2 m is the road’s fill soil
layer. The depth of 2-10 m is a soft to rigid clay
layer, the depth of 10-11.50 m contains clay andtransformed wood, the depth of 10.50-39.50 m is
hard to very hard soil, the depth of 39.50-39.85
consists of cavities, and the depth of 39.85-42.00 m
consists of fine sand, assumed to result fromcollapse of the cavity walls above. The cavity height
was estimated at 2.50 m before the collapse.
Settlement data collection, the road surface
settlement data was obtained from the profile
leveling method done along the centerline of theroad, and the inflexion parameters were recorded as
per Figure 7, which were the data collected from2015-2018. The extent of settlements began fromkm 4+115 to km 4+245. The greatest settlement was
detected at km 4+180. All through the 4 years, thedata showed: 𝐒𝐒𝐦𝐦𝐦𝐦𝐦𝐦 = 1.24 m, 1.61 m, 1.75 m, and1.75 m, respectively. The road surface settlement
had a tendency to decrease and the settlement ceased
in 2017, which is consistent with the drilling surveyof soil layer in 2017 when no cavity over sandy rocklayer was found (Table 1).

Fig.3 Field investigations (2017)

702

SEE - Nagoya, Japan, Nov.12-14, 2018

𝐒𝐒𝐦𝐦𝐦𝐦𝐦𝐦 , and the depth measured from the soil surface
to the center of the cavity − 𝐙𝐙𝟎𝟎 . From the fieldsurvey, the distance from the center of the cavity tothe point where the curve 𝐢𝐢 changed could be
calculated in the case of clayey soil using themethod of O’Reilly and New and Rankin(Table2).
From the data Table2, it was possible to calculate
the settlement value according to Peck’s theory andcompare with the field data of 2015 to 2018. The
results showed settlement of the surface according to
Peck’s, which was consistent with the realparameters obtained in the fields at the beginning of
the route at km 4+115 – km 4+200. At the end of
the route at km 4+200 – km 4+445, the realparameter measured was lower than the surface
settlement based on Peck’s theory. This was due tothe non-equilibrium of the cavity which in turn, wascaused by the slope of halite layers or by the factthat the settlement data was obtained from theprofile leveling approach, and the curve at km 4+200– km 4+445 led to discrepancies of the horizontal
cross-section distance from the center of Cavity𝐱𝐱. (Figure 8, Figure 9, Figure 10 and Figure 11)
A comparison was done between calculation of
the road surface settlement parameter by the
Empirical ( 𝐕𝐕𝐕𝐕𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄 ) as per Equation 7 and theroad surface settlement parameter measured in thefield. The results showed that the settlement in 2015
differed from other years because the distance of 25
m between each data collection point was too longleading to the amount of field data related to soil
settlement being low. Therefore, we deleted the2015 parameters and were able to conclude theamount of soil settled per one meter unit using the
distance from the cavity center to the inflexion. In
the case of clayey soil, the method of O’Reilly andNew showed 𝐕𝐕𝐕𝐕𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄 at 83.25 – 85.14% of
𝐕𝐕𝐕𝐕𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒.
The
methodofRankinshowed 𝐕𝐕𝐕𝐕𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄𝐄 at 91.23 – 93.58% of
𝐕𝐕𝐕𝐕𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒 .(Table 3 and Figure 12).
When considering the determination coefficientfor more efficient method – with the value being
closer to 1 – to find the surface settlement using thewidth of settlement hole 𝐢𝐢 in the case of clayey soil
between the methods of O’Reilly and New andRankin; the results showed R2 = 0.96 from O’Reilly
and New method and R2 = 0.97 from Rankinmethod, which agreed with Flashily.
The analysis of horizontal slide based on the
Empirical Method by O’Reilly and New Theory(Figure 13), showed the horizontal surface slide. It
was assumed that the soil slid towards the center ofthe cavity. As seen in the Figure, the slide began at
km 4+115 and increased until the maximum at km
4+160 before it decreased again to zero at km
4+180, where the settlement point was the peak.
Then horizontal slide increased again to the
maximum at km.4+200 until it became 0 at km

Fig. 5 Position of road surface settlement

Fig. 6 soil profile (2015)

Fig. 7 road centreline elevations
Table 1 soil propertiesRESULTThe Result of the road surface settlement
estimation based on the Empirical Method A
comparison between the road surface settlement andthe scope of settlement was based on the Empirical
Method of Peck’s, the equation that compares thefield parameters using the maximum settlement 703

SEE - Nagoya, Japan, Nov.12-14, 2018

4+445. Figure 14 depicts horizontal slides that
resulted in cross-sectional cracks on the roadsurface. There were slides that coincided at the
maximum settlement point, which resulted inswelling.

Table3 road surface settlement

Table 2 inflexion (i)Fig. 8 road surface settlement (2015)
Fig. 12 volume of road surface settlement

Fig. 9 road surface settlement (2016)

Fig.13 horizontal movement

Fig. 10 road surface settlement (2017)

Fig. 11 road surface settlement (2018)
Fig. 14 crack due to horizontal movement704

SEE - Nagoya, Japan, Nov.12-14, 2018

outcrops on the Khorat PlateauKKU Res. J.
2012; 17(1):(58-70)[3] Peangta
Satarugsa
andSakornSangchumpoo,Comparison
of
Rates
for
Expansion of Surface and Subsurface Sinkholes:
a Case Study at Ban Bo Deang Amphoe Ban
Muang Changwat Sakon NakhonKKU Res J.
2011; 16(8): 993-1002[4] Chaiyan Hinthong and Adul Charoenprawat,
Report of Geological Study on Soil Settlement at
Ban Jampadong School in Khu Sakham SubDistrict, Wanonniwat District, Sakonnakhon
Province. Division of Geology, Department of
Geological Resources. American Railway
EngineeringandMaintenace-of-Way
Association. Manual of Railway Engineering
Volume 1 Track.AREMA, 2010.
[5] Singh, M.M., Mine subsidence, SME Mining
Engineering Handbook. Hartman, H.L. (ed).
Society for Mining Metallurgy and Exploration.
Inc. Littleton, Colorado, pp. 938–971, 1992
[6] Elashiry, A.A., Gomma, W.A. and Imbaby, S.S.
Surface subsidence prediction over working
longwall panel at abu-tartur phosphate mines.
Journal of Engineering Sciences. 36(3): 749758,2008[7] Fuenkajorn, K. and Archeeploha, S. Prediction of
cavern configurations from subsidence data.
Engineering Geology. 110: 21-29, 2009[8] Thongprapha, T., Fuenkajorn, K., and Daemen,
J.J.K.. Study of surface subsidenceabove an
underground opening using a trap door apparatus.
Tunnelling andUnderground Space Technology.
46: 94–103, 2015[9] Peck, R.B., Deep excavations and tunneling insoft ground, In: Proceedings of the 7thinternational conference on soil mechanics andfoundation engineering, State of the art volume,
ociedad exicana de ec nica de uelos, Mexico, pp.
225–290, 1969.
[10] O’Reilly MP, New BM ,Settlements abovetunnels in theUK-their magnitude and prediction.
Tunneling 82:173–181 ,1982[11] Rankin, W., Ground movements resulting fromurban tunneling, In: Prediction and effects,
proceedings of 23rd conference of theengineering group of the geological society,London Geological Society, pp. 79–92, 1988.

CONCLUSIONS
1. The settlement of road surface was caused bysolution of rock salt by water, which resulted incavities at the depth of 42 m from the surface to thecavity center 𝐙𝐙𝟎𝟎 .
2. The Empirical Method and Peck’s theory gave theconsistent road surface settlement value with thevalue measured in the field and coefficient ofdetermination R2 higher than 0.96.
3. The distance from cavity center to the inflexion in
the case of clayey soil measured by Rankin method
was 21 m. This means that the road surface
settlement according to Peck’s theory agreed withthe real value measured in the field more than themethod of O’Reilly and New. This was determinedfrom the coefficient of determination of Rankin
being R2 = 0.97, which was higher than that ofO’Reilly and New, where R2 = 0.96.
4.The amount of the road surface settlement by the
Empirical Method using the distance from the cavity
center to the inflexion 𝐢𝐢 by O’Reilly and New
method was 83.25 – 85.14% of 𝐕𝐕𝐕𝐕𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒 , whereas
Rankin’s calculation showed 91.23 – 93.58% of
𝐕𝐕𝐕𝐕𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒𝐒 .
5. The horizontal slide at the road surface led totension between km 1+115 – km 1+160 and km
4+200 – km 4+245, which in turn caused crosssection cracks on the road surface. From km 1+160
to km 1+200, compression occurred from horizontal
slides, causing swelling on the surface.
ACKNOWLEDGEMENT
The researchers are grateful to Buengkan
Highway Department and the Bridge Repair andConstruction Center 2 (Khon Kaen), Department ofHighway, for the information of the road surface
settlement at the study site, site history, soil layer
survey, and the assistance in the course of thisresearch study.
REFERENCES[1] Peangta Satarugsa,Boundary and Evolution 0f
Rock Salt in the Maha Sarakham Formation in
the Mortheast, Thailand KKU Res. J. 2005;
10(1):(65-78)[2] Parkorn Suwanich1,Geological Map of Phutok
Formation Improvement explored from Potash
and Rock Salt drilled holes, topography and705

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PRODUCTION OF ETHYL ESTER BIODIESEL FROM USEDCOOKING OIL WITH ETHANOL AND ITS QUICK GLYCEROLBIODIESEL LAYER SEPARATION USING PURE GLYCEROL
Mallika Tapanwong1, Vittaya Punsuvon1,2
Center of Excellence-Oil Palm Kasetsart University, Bangkok, 10900 Thailand
2
Department of Chemistry, Faculty of Science, Kasetsart University, Bangkok, 10900 Thailand
1

ABSTRACTIn this study, used cooking oil, ethanol and sodium hydroxide (NaOH) were used as raw material and catalyst
to produce biodiesel through transesterification reaction. The occurring emulsion from ethanol acts as a surfactant
in the reaction mixture make the separation of biodiesel from glycerol layer more difficult. This problem solving
was done by adding pure glycerol into the reaction mixture after complete reaction to make quick layer separation
between glycerol and biodiesel. The characterization of the produced biodiesel was performed by proton nuclear
magnetic resonance (1H-NMR) and gas chromatography (GC). The result showed that the optimum condition for
ethyl ester biodiesel production were 8:1 of ethanol to oil molar ratio, 0.75%w/w of NaOH amount, 45 min ofreaction time and 40 oC of reaction temperature. This condition gave 100% of fatty acid ethyl ester conversion that
determined by 1H-NMR. The result on the optimum condition for layer separation showed that the adding of 2.44%v/v of pure glycerol relation to the total volume of the reaction mixture took 14.38 min for glycerol-biodiesel layer
separation. In addition, ethyl ester biodiesel was further analyzed its fuel properties followed ASTM biodiesel
standard. The results showed the produced biodiesel met well with the standard.
Keywords: Biodiesel, Glycerol, Surfactant, Transesterification

three consecutive reversible reaction. The first step isthe conversion of triglycerides into diglycerides andfurther into monoglycerides in the second step. The
final step, monoglycerides converts into ester andglycerol molecule.
Short chain alcohol such as methanol and ethanol
are the most frequency employed. Methanol is highly
reaction and generates satisfactory yields at lower
temperatures and reaction time compared with otheralcohol [3]. However, methanol presents the
disadvantage of higher toxicity compared withethanol. In our work, ethanol is selected because
ethanol can be produced from agricultural renewable
resource such as sugarcane that result in total
independence from importing petroleum-based
alcohol like methanol [4]. However, as the synthesis
progresses through the transesterification reaction,
ethanol promotes a more stable dispersion between
the ethyl ester biodiesel and glycerol, impeding thelayer separation and thus increasing the time required
for the production process and lowering the quality ofthe obtained biodiesel [5]. Pure glycerol is usuallyused to disperse the layer of ethyl ester biodiesel andglycerol but the amount of adding and the waitingtime for separation is not known, so this is the firsttime to study.
The objective of this work is to determine theoptimum condition for the transesterification reaction
between used cooking oil with ethanol using NaOH
as alkali catalyst and pure glycerol as dispersing

INTRODUCTION
The limited fossil fuel resource along with theneed to reduce greenhouse gas emission were a major
impulse to the development of alternative fuels. As
one result, increased attention has been given to
biofuel, such as biodiesel, that can be used asalternative fuel to replace diesel fuel. Its production
from renewable resource, such as vegetable oil andanimal fat, makes it biodegradable and non-toxic
substance. In addition, biodiesel contributes to the
reduction of CO2 emission because it comprises a
closed carbon cycle [1]. The choice of vegetable oil
as feedstock for making biodiesel rely upon the costof production, reliability of supply and high yield.
Used cooking oil (UCO) was waste that obtained
from households, cafeteria and restaurants collection.
The UCO offers significant potential source as a low
cost raw material for biodiesel production. UCO
contained low free fatty acid content, thus it issuitable for making biodiesel via transterification
reaction without any problem caused by soap
formation. Furthermore from the waste management
viewpoint, using UCO in biodiesel production helps
to provide a cleaner way for disposing these wastes[2].
The most common way to produce biodiesel istransesterification reaction that triglycerides reactwith alcohol to form esters and glycerol as byproduct. Transesterification consists of a sequence of706

SEE - Nagoya, Japan, Nov.12-14, 2018

compound for biodiesel-glycerol layer separation.
The optimum condition in adding the amount of pureglycerol on the separation of biodiesel-glycerol layer
is also determined. Moreover, the purification ethyl
ester biodiesel is further characterized its fuelproperties compared with the methyl ester biodiesel
standard.

C=

AEE /2

Aα−CH2 /2

× 100

(1)

Where, C is the percentage of FAEE conversion,
AEE is the integration value of the protons of the ethyl
ester and Aα-CH2 is the integration value of themethylene protons. The 2 factor, which divides both
integration value s, is the normalization factor

MATERIALS AND METHODSRESULT

Material

Characterization of UCO

UCO in this research was obtained fromhousehold collection. The fatty acid composition
determined by gas chromatograph (GC) consisted of
0.857%w myristic acid, 36.030%w palmitic acid,
4.383%w stearic acid, 43.372%w oleic acid,
13.606%w linoleic acid. The calculated averagemolecular weight of UCO was 852 g/mol and its freefatty acid content was 0.18%w. Analytical grade
ethanol was purchased from Merck (Germany).
Methyl hepatadecanoate (C17) was obtained from
Fluka (Switzerland) and deuterated chloroform was
obtained from QReC (New Zealand).

The fatty acid composition of UCO that
determined by GC was revealed in Table 1.
Table 1 Fatty acid composition of UCO
Fatty acid
Octanoicacid
Decanoicacid
Lauric acid
Myristicacid
Palmiticacid
Palmitoleic
acid
Stearic acid
Oleic acid
Linoleic
acid
Linolenicacid
Arachidic
acid
Behenic acid

Trensesterification Reaction
The transesterification reaction was carried out ina laboratory scale setup using a three-necked 100 ml
flask equipped with a reflux condenser, athermometer and a magnetic stirrer. The reaction was
conducted with UCO that stirred constantly at 750
rpm with ethanol and NaOH catalyst. The reaction
were performed at diferent amount of NaOH catalyst(0.25-1.25%w), different molar ratio of oil to ethanol(4:1-12:1 mole) and different reaction time (15-120min) with keeping the constant temperature at 40 oC.
After the reaction was completed, the mixture wastransferred into separation funnel and 2.44%v/v ofpure glycerol was added into the mixture to separate
into two layers that the top layer was biodiesel and thebottom layer was glycerol. The biodiesel was further
purified with warm water and dried in an oven. The
obtained purified biodiesel was investigated for fatty
acid ethyl ester (%FAEE) conversion by 1H-NMR(varian, inova 400 mhz, usa).

Molecular
formular
C8H12O2

Molecular
weight144% AreaC10H20O2

172

0.019

C12H24O2
C14H28O2

200
288

0.320
0.857

C16H32O2

256

36.030

C16H30O2

254

0.305

C18H36O2
C18H34O2
C18H32O2

284
282
280

4.383
43.37213.606

C18H30O2

278

0.522

C20H40O2

312

0.365

C22H44O2

340

0.105

0.037

The fatty acid composition showed that oleic acid(43.372%) and palmitic acid (36.030%) are the two
major fatty acids, followed by linoleic acid(13.606%), stearic acid (4.383%). The minor fatty
acid are octanoic acid (0.037%), decanoic acid(0.019%), lauric acid (0.320%), myristic acid(0.857%), palmitoleic acid (0.305%), linolenic acid
(0.522%), arachidic acid (0.365%) and behenic acid(0.105%). The average molecular weight of UCO
calculated from the fatty acid composition is 852
g/mol. The UCO also contained 0.18%w/w of freefatty acid.

Determination of FAEE
The 1H-NMR spectra of UCO ethyl ester biodiesel
from the 1H-NMR analysis were obtained formonitoring the transesterification reaction in the formof percentage fatty acid ethyl ester (%FAEE)
conversion. The %FAEE conversion was analyzed
follow [6]. Breifly, the chemical shift at 4.15 ppm
represented the ethyl ester protons and at 3.30 ppm
represented the methylene proton (α-CH2). An
equation to calculate the %FAEE conversion isshown in Eq. (1).

1

H-NMR spectrum of ethyl ester biodiesel for%FAEE conversion calculation
The 1H-NMR spectrum of the UCO ethyl ester
biodiesel obtained after washing and drying is present
707

SEE - Nagoya, Japan, Nov.12-14, 2018

in Fig. 1.

Influence of molar ratio of ethanol to UCO on thepercentage of ethyl ester conversion (%FAEE)FAEE conversion(%)

The molar ratio of ethanol to UCO is one of themostimportantparameters
affectingthetransesterification conversion. Although thestoichiometric ratio requires three moles of ethanol
for each mole of UCO, in practice, the mole ratio
should higher to shift the equilibrium towards the
direction of the ethyl ester formation. Figure 3
describes the influence of mole ratio of ethanol to
UCO on the %FAEE conversion.
Fig. 1 1H-NMR spectra of UCO ethyl ester biodiesel.
The conversion of the triglyceride to monoalkyl
ester is clearly observed in the 1H-spectra by theappearance of the quartet at 4.15 ppm which related
to the ethyl ester CH2 group. From the chemical shift
at 4.15 ppm and at 2.30 ppm of the CH2 groupadjacented to the carbonyl group, both chemical shifts
were used to calculate the percentage conversion of
fatty acid ethyl ester (%FAEE) followed Equation 2.

4

6

8

10

12

14

Fig. 3 Influence of molar ratio of ethanol to UCO on%FAEE conversion. Transesterification
condition: reaction temperature = 40 oC,
amount of NaOH catalyat = 0.75%, reaction
time = 90 min at 750 rpm of constant stirring.
It can be found that the %FAEE conversion
increases rapidly from 4:1 to 6:1 of molar ratio afterthat the %FAEE increases gradually from 6:1 to 8:1
of molar ratio. The maximum of 100% FAEE
conversion obtained at 8:1 of molar ratio and further
increase in the molar ratio from 8:1 to 12:1 gave thesame %FAEE conversion.
Influence of reaction time on the percentage of ethyl
ester conversion (%FAEE)
The influence of reaction time on the %FAEE
conversion is studied and depicted in Figure 4.
FAEE conversion(%)

FAEE conversion(%)

90

Ethanol to oil molar ratio (mole)

The influence of the NaOH amount of catalyst on
the %FAEE conversion is examined in Figure 2. The
amount of NaOH catalyst varies from 0.25%w/w to
1.25%w/w. The %FAEE conversion using NaOH
catalyst increases rapidly from 0.25%w/w to 0.50
%w/w after that the %FAEE increases gradually from
0.50%w/w to 0.75%w/w The %FAEE conversion
reaches a maximum of 100% at 0.75%w/w. Further
increase in the amount of NaOH catalyst up to
1.25%w/w cannot promote the conversion. So, theselected optimum amount of NaOH catalyst was
0.75%w/w.
105
100
95
90

1.00

95

2

Influence of the amount of catalyst on the percentage
of fatty acid ethyl ester conversion (%FAEE)

0.50

100

85

Optimum Condition in Biodiesel Production by
Transesterification

85
0.00

105

102
100
98
96
94
0

1.50

30

60

90

120

150

Reaction time (min)Catalyst concentration (%w/w)

Fig. 4 Influence of reaction time on %FAEE
conversion. Transesterification condition:
reaction temperature = 40 oC, amount of
NaOH catalyat = 0.75%, molar ratio of ethanol
to UCO = 8:1 at 750 rpm of constant stirring.

Fig. 2 Influence of the amount of NaOH catalyst on%FAEE conversion. Transesterification
condition: reaction temperature = 40 oC, molar
ratio of ethanol to UCO = 10:1, reaction time
= 90 min at 750 rpm of constant stirring.
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SEE - Nagoya, Japan, Nov.12-14, 2018

It can be seen that %FAEE increased rapidly from15 min to 45 min after that the %FAEE becamealmost constant. The optimum time obtained from thestudy was 45 min that gave 100% of FAEE
conversion.

Table 2 Physico-chemical properties of ethyl ester
biodiesel

Influence of adding pure glycerol on the waiting time
for layer separation
The influence of pure glycerol addition
percentage on the waiting time for layer separation of
biodiesel and glycerol is shown in Figure 5. Pure
glycerol addition percentage varies from 2.44%,
4.76%, 6.98%, 9.09% and 11.11%v/v relatived to thetotal volume of the biodiesel and glycerol mixture.

Time (min)25

Physicchemical
properties

Test
methodEthyl
esterbiodiesel

Density at 15o
C (kg/m3)
Kinematic
viscosity at 40o
C (cSt)Acid Value(mg KOH/g)
Flash point
(oC)

ASTM
D1298
ASTM
D445

863

Methylester
biodiesel(ASTM)
860-900

4.94

1.9-6.0

0.36

0.50 max

216

120 min

ASTM
D664
ASTM
D93

CONCLUSION

20

In this study, the transesterification of UCO withethanol in the presence of NaOH catalyst shows afavorable reaction. A high FAEE conversion (100%)
was achieved by optimizing variable effects. The
optimum conditions on %FAEE determined by 1HNMR during transesterification was 0.75%w/w of
NaOH catalyst, 8:1 of molar ratio of UCO to ethanol,
45 min of reaction time, 40 oC of reaction
temperature, 750 rpm of stirring. The separation ofglycerol and biodiesel layer is optimized by adding
different amount of pure glycerol into the mixture ofglycerol and biodiesel product. The result showedthat 2.44%v/v of adding pure glycerol can accelerates
the waiting time for layer separation. It took 14.38
min for optimum time for separation. Additionally,
the physico-chemical properties of the ethyl ester
biodiesel met well with the ASTM methyl ester
biodiesel standard.

15
10
5
0

2

4

6

8

10

12

Pure glycerol addition percentage(%v/v)
Fig. 5 Influence of adding pure glycerol on thewaiting
time
for
layer
separation.
Transesterification
condition:
reaction
temperature = 40 oC, molar ratio of ethanol to
UCO = 8:1, reaction time = 45 min at 750 rpm
of constant stirring.
The result indicated that more pure glycerol
addition percentage from 2.44% to 11.11%v/v gave
the constant waiting time at 14.38 min for layer
separation. Therefore, the selected optimum amountof adding pure glycerol was considered 2.44%v/v.
The reason for adding a low quantity of pure glycerol
provokes a rapid separation of the two layer can beunderstood by the formation of hydrogen bonds
between ethanol and pure glycerol that are stronger
than the van der waals forces between ethanol andbiodiesel.
Physico-chemical
biodieselproperties

of

ethyl

ACKNOWLEDGEMENT
This work was supported by Center of
Excellence-Oil Palm, Kesetsart University andDepartment of chemistry, Faculty of science,
Kasetsart University.
REFERENCE[1] Anastopoulos G., Zannikou Y., Stournas S., andKalligeros S., Transesterification of Vegetable
Oils with Ethanol and Characterization of the
Key Fuel Properties of Ethyl Esters. Energies,
Vol. 2, Issue 2, 2009, pp.362-376.
[2] Diya’uddeen B.H., Abdul Aziz A.R., Daud
W.M., and Chakrabarti M.H., Performance
Evaluation of Biodiesel from Used Domestic
Waste Oils: A Review. Process Suf. Environ
Prot., Vol. 90, 2012, pp.164-179.
[3] Firdaus M., Yusoff M. , Xu X., and Guo Z.,
Comparison of Fatty Acid Methyl and Ethylester

The physico-chemical properties of ethyl ester
biodiesel were compared with the methyl ester
biodiesel standard that followed the USA (ASTM
standard). The results were exhibited in Table 2.
The result revealed that all physic-chemical
properties of the produced ethyl ester biodiesel meetwell with methyl ester biodiesel standard. In addition,
this result implied that ethyl alcohol can be replace
methyl alcohol for biodiesel production.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Esters as Biodiesel Base Stock: A Review on
Processing and Production Requirement. J Am
Oil Chem Soc, Vol. 91, Issue 4, 2014, pp. 525531.
[4] Namwong S., Punsuvon V., and Arirob W.,
Process Optimization of Ethyl Ester Biodiesel
Production from Used Vegetable Oil under
SodiumMethoxide Catalyst and its

Purification by Ion Exchange Resin. Applied
Mechanics and Material, Vol. 873, 2017, pp.9094.
[5] Silva W., Souza P., Shimato G.G., and TubinoM., Separation of The Glycerol –Biodiesel
Phase in An Ethyl Transesterification Synthetic
Route Using Water, J. Braz. Chem. Soc., Vol.
26, Issue 9, 2015, pp.1745-1750.

710

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

AN INTEGRATED APPROACH FOR SUSTAINABILITY IN THE
APPLICATION OF INDUSTRIALISED BUILDING SYSTEM (IBS)
Riduan Yunus1, Abdul Rahim Abdul Hamid2 and Siti Rahimah Mohd Noor1
Faculty of Civil & Environmental Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia;
2
Faculty of Civil Engineering, Universiti Teknologi Malaysia (UTM), Malaysia

1

ABSTRACT
Malaysia is committed to improve deliverables of construction industry especially in meeting the sustainableobjectives. Lack of systematic tools and poor collaboration between key stakeholders have been identified as themain barriers to meet the objectives. The purpose of this paper is to present an integrated approach that can be able
to assist designers, who are at the forefront in decision making, to select the best strategies that have been shown
to be effective in promoting sustainability for IBS application. Questionnaire survey and interviews of the local
practitioners were conducted to identify critical factors and provide recommendations on how to enhancesustainability by holistically addressing the identified issues during IBS design. SWOT (Strengths, Weaknesses,
Opportunities and Threats) analysis framework was used to help decision-makers maximise the opportunities byusing available strengths, avoid weaknesses, and diagnose possible threats in the examined issues. From thestatistical analysis, eighteen critical factors relevant to IBS sustainability have been ranked. The guidelines were
formulated based on the results from interviews to local practitioners and may be used as part of the project briefing
documents for IBS designers. Holistic design strategies expand “Triple Bottom Lines” considerations in achieving
sustainability. This study fills a current gap by responding to IBS project scenarios in developing countries. It also
provides a balanced view for designers to better understand sustainability potential and prioritize attentions tomanage sustainability issues in IBS applications.

Keywords: Sustainability, Prefabrication, Guidelines, SWOT Analysis, Designers

in ensuring faster and higher adoption of IBS
application in the local industry. Despite
acknowledging its benefits and the top-leveladvocacy, the local construction industry is still not
rapidly embracing IBS [2-4]. Arditi, Ergin andGunhan [5] highlighted that most of stakeholders do
not realize of the significant cost savings in the IBS
application through speedy erection and long term
investment. In addition, most of the developing
countries are depending on technology fromindustrialised countries [6]. It was highlighted that theeffective communication and higher financial capitalare required to accelerate technology transfer.
Currently, the implementation of IBS was lack ofcommunication and cooperation among the key
stakeholders [4-8]. Manufacturers and contractors
can only become involved after the design stage. The
separate functional discipline in the implementation
process is akin to the ‘over the wall’ syndrome [9].
This study aims to formulate sustainableguidelines from the perspective of the designer by
critically examining the relationship between
sustainability and IBS. Though other researchers havedeveloped decision tools in IBS application, no
previous studies in this field have considered thepotential threats and weaknesses of pursuingsustainability. This study explored perceptions

INTRODUCTION
Construction projects are become larger and more
complex. With systematic and innovative solutions,the industry players will be able to meet new andemerging challenges such as improving construction
efficiencies, integrating stakeholders’ management
and reducing environmental impacts. Industrialised
Building System (IBS) or prefabrication is recognised
as alternative methods to replace conventional
construction to enhance sustainable deliverables.
Building production in a controlled environment
offers many advantages such as reducing constructionwaste, minimising resources consumption, increasing
the quality of buildings and improving theoccupational safety and health [1-2]. In contrast,
conventional on-site methods have long been
criticised for being labour intensive, poor
workmanship quality, overwhelming management
control and excessive construction waste generation[3].
Understanding IBS benefits and its potentials, theMalaysian Government steering the local
construction industry to shift from traditional
practices to IBS based production. The Construction
Industry Transformation Programme (CITP) 20162020 is specifically highlight government strategies
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SEE - Nagoya, Japan, Nov.12-14, 2018

among the key stakeholders regarding both contexts
and provides easy-to-understand guidelines forpractitioners in developing countries such as
Malaysia. This study also presents unified views fromkey stakeholders instead of single professions, theconsideration of negatives instead of all “positives”,
and the justification to enforce a sustainability focus
in developing economies still grappling with finding
suitable solutions in local contexts.

from IBS will increase with the number of units
produced [3-16]. By implementing IBS, Malaysia ison the right track for moving forward to develop thecountry.
Chan, Qian and Lam [17] found that the economic
force and government interventions are the strong
forces to arouse interests in pursuing sustainability.
Their study highlighted that ‘‘rising energy costs’’
will present such an economic reality that people will
have to take part in sustainable development for theirown interest. The other economic attraction for all
stakeholders in construction industry to be involvedin achieving sustainability is “lower life-cycle”. Any
impact of the decisions for the long term, specificallyfor the demolition and deconstruction should needtaken into account in making effective decision. They
also stated that, it is important for a government tocreate mandatory regulation or building code toensure stakeholders are taking part in sustainable
efforts.
There have been several studies that integrate
factors that influence the sustainability for IBS
projects. Researchers have developed assessment
tools to help stakeholders overcome projectchallenges and use opportunities available in IBS
implementation [18-21]. The researchers argued thatthe measurement should also consider indirect
attributes, such as reducing the environmental impact.
While the proposed tools provide some assistance inthe selection of IBS, few are capable of providing
action plans on how to embed sustainability
deliverables in the selected options. Most of the tools
are focused solely on strategic level analysis and fails
to consider sustainable factors objectively withspecifics project requirement.
Current literature provides an understanding ofpotentials of IBS in improving sustainability. Despite
this awareness, academic research has not establishedholistic criteria in IBS selection. It is vital to consider
sustainability characteristics in improving IBS
implementation, specifically to developing countries,
such as Malaysia. The numbers of integral approachthat takes into account all of the environmental,
economic and social aspects is very small compare toapproach that focus on individual aspects [22-23].
Most of the stakeholders, such as contractors andmanufacturers
arestruggling tointegrate
sustainability in IBS implementation. This is due tounclear decision guidelines and the shortage of tools
regarding sustainability criteria selection. Local andregional characteristics and physical environment
plays a major role in measuring the level ofsustainability [24]. With the flexibility for adaption,issues studied in developed countries are unlikely to
be applicable or even relevant to developing countries[25]. Ofori and Kien [26] suggested that the
stakeholders in the construction industry should
initiate a strategy selecting the best solutions in theirdesign and building construction. The importance of

LITERATURE REVIEW
There are many factors that are internal andexternal to building projects that enhance thesustainable deliverables. Some commonly identified
factors include: energy use, transport, water
efficiency, ecology, land use, materials and resources,indoor environmental quality, heatlh and well-being,sustainable site and management, and innovation [1011]. A study of sustainable constructions aspects ofusing IBS in Hong Kong added to this body ofliterature by identifying factors that improvesustainable deliverables. Jailoon and Poon [12] foundthat IBS will be able to improved quality control,
improved environmental performance (reduction ofwaste, dust and noise), improved site safety, thereduction of labour demand and construction time. In
their case studies, on average, a reduction of 65% ofconstruction waste, 16% of labour requirement onsite, 15% of construction time and 63% lower than theindustry figure for the accident rate. In a similar study,
Lam, Chan, Poon, Chau and Chun [13] identify
principal factors leading to the success of preparing
green specifications in construction projects andidentified the following as the four major influencing
factors: (1) green technology and techniques, (2)reliability and quality of specification, (3) leadershipand responsibility, (4) stakeholder involvement, and(5) guide and benchmarking systems.
Pitt, Tucker, Riley and Longden [14] divided
three key areas towards sustainable construction: (1)environmental responsibility, (2) social awareness,and (3) economic profitability. They researchhighlighted that financial incentives and building
regulations were the two most important drivers thatwill be able to drive demand for sustainability
buildings. An effective working environment will beable to reduce absenteeism and supports staff
retention and recruitment. IBS promotes stableworking conditions and organised working
procedures. The local labourers have the opportunity
to develop their skills and knowledge and reduce thepossibility of being transferred to another region or
location. Currently, IBS is seen as more expensive,
especially as it involves high initial capital outlay, andhigher design, cranage and transport costs compared
to conventional construction [15]. Although thecritical investment in the initial process is very high,once the break-even point is reached, the benefits
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SEE - Nagoya, Japan, Nov.12-14, 2018

specifics actions assigned to particular stakeholders
in evaluate their decisions, including the selection of
raw materials to be used, energy consumed and thepollution and waste produced throughout the building
life cycle was highlighted. Therefore, the study
presented in this paper focuses on the holistic
approach in integrating potential factors to improvesustainability at the early stage of construction.

results covering perceptions of key stakeholders in asustainable IBS shall underpin the basis forestablishing the decision making process models forenhancing the feature of this innovative system.
Ultimately, as the final outcome of the study, theguidelines will help promote more integrated
approaches to decision making about theimplementation of sustainability strategies in thedesigning stage.

RESEARCH METHODS
The quantitative data were collected and analysed
to identify the level of significance of each potential
factor in improving sustainability for IBS application.
The critical factors were identified by using statisticaltest. Then, the qualitative interviews were conducted
to further explain the details of each critical factor andto formulate the action plans. Accordingly, theguidelines were developed based on in-depth
investigation on each issue using semi-structureinterviews. In responding to the negative and positive
contexts, the strategies on improving sustainability
were properly investigated.
The questionnaire survey involved seven sample
groups categorised by their organisation type, namely
1) designer/consultant companies, 2) manufacturer
companies, 3) user or facility management companies,
4) developers, 5) research/academic institutions, and
7) authority/government agencies. The respondents
were selected from professional databases of theConstruction and Industry Development Board,
Industrialised Building System Centre, and Green
Building Index Malaysia. The questionnaires were
distributed by post, online survey and face-to-faceconsultation. From 300 copies of questionnaire, 115
questionnaires were returned and can be used in theanalysis. Therefore, the response rate is 38 per cent.
Consequently, the factors were explored throughsemi-structured interviews to extract best practices of
how these factors can be dealt with. A semi-structured
interview form was used because it was flexible andit gave additional scope for the interviewees toprovide detailed information based on theirexperience and capability. It also allowed theresearchers to maintain focus on the research
objectives. Twenty respondents participated in theinterviews. They all have different backgrounds andvast experience in construction industry. This helps
researchers identify the perception of each type oforganisation in pursuing sustainability. As a result,the interviewees were able to provide more in-depth
and detailed answers and suggestions in their
responses to the questions. SWOT (strengths,
weaknesses, opportunities, and threats) analysis wasused to formulate a decision-making guideline.
In summary, the design of the proposed study is
including a literature review, survey, semi-structured
interview, and data analysis techniques (Figure 1).
With both quantitative and qualitative methods, theFig. 1: Research design

QUANTITATIVE ANALYSIS
The ranking of the sustainability factors was
carried out based on their mean values. In selecting
the critical factors, the cut-off mean value is 4.00
which represents “significant”. Out of the 62 factors
identified in the literature review, only 37 factors
were rated by the respondents as “significant” and“very significant” (mean ≥ 4.00). The standard
deviations in this analysis show uniformity with mostbelow 1, thus representing good data accuracy in thisstudy. Accordingly, a t-test was used to identify themost significant factors among the 37 factors. Thismethod was previously proven by several researchers
such as Ekanayake and Ofori [27] and Wong and Li[28] in related studies. In this study, the null
hypothesis (factors were neutral, insignificant, andvery insignificant) is accepted if the t-value is smaller
than 1.6583 (the critical t-value). As a result, there
were left with 18 critical factors, namely:“construction
time”,“production”,“wastegeneration”, “constructability”, “knowledge andskills”, “defects and damages”, “labour cost”, “waste
disposal”, “procurement system”, “durability”,“working conditions”, “standardisation”, “usage
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SEE - Nagoya, Japan, Nov.12-14, 2018

efficiency”,“labour
availability”,“materialconsumption”, “legislation”, “project control
guidelines” and “maintenance and operation costs”.
Kendall’s coefficient of concordance measures
the agreement of respondents on ranked factors. From
the analysis, the coefficient value for critical factors
is 0.104, which statistically shows that the
respondents have different preferences and evenconflicts in determining the most important factors.
To improve the common understanding of key
stakeholders in IBS construction, each group is to beassessed and analysed before the critical factors canbe finalised. It is important to note that Kendall’s
coefficient of concordance can identify the agreementlevels but it cannot investigate whether there are
significant differences in the stakeholders’ rankingsof the significance levels. To address this issue,
Kruskal-Wallis one-way ANOVA was used.
The Kruskal-Wallis one-way ANOVA test
revealed that there was no significant difference
between various stakeholder organisations for 13
sustainable factors. They have a consensus regarding
the perceptions and expectations in achieving
sustainability. On the other hand, five factors haveslight differences across the key stakeholders. They
are: (1) constructability, (2) defects and damages, (3)labour cost, (4) material consumption, and (5)legislation. It is interesting to note that although“constructability” is among the top five criticalfactors, the seven groups ranked it at different
significance levels.
Among these five factors, manufacturers andusers have a different agreement to other groups indetermining the significance level of “defects anddamages”,“labourcost”,
and“materialconsumption”. A possible reason may be that
manufacturers and users are only involved with theend product, which is contrary to other groups whichplay their roles in the briefing, design, andconstruction stages. Most of the decision-makers
consider available options or potential factors basedon their familiarity and personal preferences [30].
The Mann-Whitney test explores the differences
between two independent groups on a continuous
measure. The score on the continuous variable for thetwo comparable groups is converted to ranks in orderto evaluate whether the ranks differ significantly. It isnotable that the designer/consultant group has adifferent focus in improving IBS sustainability inregard to four factors, namely: 1) “constructability”,
2) “defects and damages”, 3) “labour cost” and 4)“material consumption”. The designer/consultant
group was found to have a different perception on thesignificance level of “defects and damages” and“labour cost” compared to the contractor,
manufacturer and user groups. For “legislation”,
differences were identified between the contractor
group and three other organisation groups(manufacturer, user and client). It is believed thatfrom the institutional perspective, these organisations
are more focused on the details in the legal
documentation and regulations. On the contrary, thecontractor group normally has a low level of concern
about these issues because they are more focused on
the physical activities.
The results showed that all the 18 factors can bestatistically considered as the most significant andrelevant in improving IBS sustainability. The
respondents and their organisations represent
different backgrounds and experiences which caneither affect or be affected in IBS projects. As key
stakeholders, their opinions and views are very
important to stimulate sustainability deliverables in
IBS construction. Therefore, the factors selected andranked as critical will provide a sound basis uponwhich decision-making guidelines for IBS
implementation can be based.
QUALITATIVE ANALYSIS
Knowing the critical factors is important. But
knowing how to deal with them requires appropriate
and effective strategies. Based on the results fromquantitative analysis, the logic and structure forprocessing critical factors was establish. The criticalfactors were grouped into 5 categories: ecological
performance; economic value; social equity andculture; technical quality; and implementation andenforcement.
The semi-structured interviews elicited insights
and points of view from the respondents that are
useful for the formulation of efficient decisionmaking guidelines. The remarks provided from therespondents for each critical sustainability factors
were produced from the reduction and transformation
process. This is important to ensure the information isreadily accessible, understandable, and to draw out
various themes and patterns [30]. Their remarks wereanalysed and grouped to form the action plans in
improving sustainability. The SWOT analysis was
adopted to evaluate simultaneously the internal andexternal factors by collecting all the possibilities andopportunities. It is important to note that the designers
require lots of information to guide them in making
appropriate decisions, especially when integrating
sustainability efforts [31-32]. Previous research has
proven that SWOT analysis can be used to evaluate
risks, to gain insight into the internationalisation of
construction companies in the global market and tomeasure the performance of construction firms indeveloping countries [33-35]. SWOT analysis is ideal
for analysing the situation each investigated factor
presents. The interrelated criteria also help to develop
potential strategies. Through such analysis, decisionmakers can exploit new opportunities by utilisingavailable strengths, avoiding weaknesses anddiagnosing any possible threats in the examined
issues.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Accordingly, the final guidelines were approvedby the respondents. It is agreed that the guidelines
will be able to provide a systematic decision support
tool for the stakeholders in encapsulating
sustainability. The importance of the stakeholders’participation and their full understanding of thisapproach were highlighted. These will increase thekey stakeholders’ interest in using the SWOT analysis
which provided in the guidelines.

Moreover, the clear responsibility of IBS participantsin regard to the sustainability deliverables can be
documented and potentially embedded in contracts.
Developers and designers alike will have a tool toassess the potential of IBS and to enhancesustainability.
While research findings are considered to be“representative”, as respondents covered a wide rangeof the construction industry stakeholders such as
contractors, consultants and manufacturers, thedelivered decision support guides are intended for thedesigners. These tools will be used in the design stageand early construction stage. Further research can
extend the findings to include appropriate decision
mechanism and preferences for other stakeholders.

DISCUSSION
The promotion of IBS usage in Malaysianconstruction industry is constantly faced with anumber of challenges to improve, meet market
demand, and overcome skills shortages. Literaturestudies suggest the general lack of research efforts toassess the full sustainability potential in IBS
applications. The few relevant research projects
attempted to deal with one aspect in Triple Bottom
Line (TBL) alone - such as economic or social
dimensions. A holistic approach that encompasses allimportant issues of the TBL and beyond is not yet
available. In Malaysia to date, IBS applications tend
to be linked with government projects primarily. As
such political scenarios and government support arevery important aspect. The quantitative methodology
adopted in this study has identified the 18 criticalfactors and interrelationships between these factors.
This study probes into the environmental, economicaland social aspects the IBS potential and extends themto include ‘technical quality’ and ‘implementationand enforcement’ aspects of the sustainability
assessment. Implementation and enforcement are thefactors that ensure that any planning will be carriedout accordingly. An effort from the authorities was
identified as a starting-point to integrate sustainability
for IBS applications in Malaysia. The technical issues
provide physically measurable attributes of IBS
construction and an opportunity to maximize the IBS
benefits in improving sustainability. These
considerations present a new level of thinking andknowledge paradigm in dealing with the IBS method.
Research findings noted that the adoption of
SWOT analysis will be able to provide the necessary
framework to understand the internal and external
conditions of each critical factor.
CONCLUSION
Considerations of both the positive and negative
aspects of pursuing sustainability can help “complete
the scenarios” when making the best selection. Sucha decision-making framework also includes actionplans to present information on what and how to
improve the sustainability of each critical factor.
Ideally, this would form part of the project briefing
documents against which sustainability solutions canbe considered and implemented by the designers.

ACKNOWLEDGEMENTS
The authors would like to thank Universiti of Tun
Hussein Onn, Malaysia and the Ministry of Higher
Education, Malaysia (FRGS vot. 1578) for theirgenerous sponsorship of this research.
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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PRODUCTION OF Cu MICROPARTICLESUTILIZING HIGH PURITY Cu DENDRITE CRYSTALSAND DEVELOPMENT OF CONDUCTIVE PAINTS
Junya Kuroda1, Risa Uda1, Honoka Tanabe1, Kimihiro Yamanaka1 and Hirohisa Taguchi1
1

Department of Electrical and Electronic Engineering, School of Engineering, Chukyo University
101-2 Yagoto Honmachi, Shouwa-Ku, Nagoya City, Aichi, JAPAN,
ABSTRACTIn recent years, metal microparticles made of Au or Ag have attracted attention as intermetallic bonding materials
and low resistance materials of fine interconnects. It is also known that the electron cloud localized on the finesurface of the fine particles has a catalytic effect, and researches on chemical reaction accelerators are being
advanced. However, Au and Ag have high material cost, not economical materials. Furthermore, Ag is extremely
easily oxidized, and there is a problem in durability of the catalytic effect in the solution. In this research, we
considered Cu microparticle formation by Cu three - dimensional tree structure (Cu dendrite). Cu has highelectrical conductivity and less oxidizable than Ag. It has an extremely high economic advantage compared with
Au. We have succeeded in making high purity Cu dendrites by our previous studies. This Cu dendrite was broken
in an aqueous solution using ultrasonic waves. As a result, Cu fine particles having a diameter of about 1 to 10 μm
were successfully formed. We also reported that this fine particle was impregnated into a water-soluble paint andsucceeded in forming a printer ink with electrical conductivity.
Keywords: microparticles, Cu dendrite crystal Conductive printer ink, electrical conductivity
INTRODUCTION

diameter and unify the particle shape [7]. Also, since
noble metals such as Au, Ag, Cu have extensibility,
physical fracture simultaneously promotes foil
formation.
In this study, physical grinding method of highpurity Cu dendrite crystal was investigated in order toform Cu fine particles with high industrial utilization
value in high yield and low cost. High purity Cu
dendrite crystals were formed by using copper sulfate
solution by the application of plating method. By themethod shown in this research, it was possible to forma purity of 99% or more for Cu dendrites, which wasa structure containing much impurities so far. Cu
dendrite crystals having a tree structure can beobtained. The Cu dendrite crystals can be easily
peeled off from the plated substrate. After peeling, Cu
dendrite crystals were subjected to ultrasonicvibration in ethanol. As a result, it was physicallypulverized to form fine particles with a particle sizeof 1 to 10 μm. Then we investigated the formation of
conductive ink by impregnating the fine particles into
the printer ink.

In recent years, metal microparticles made of Au or
Ag have attracted attention as intermetallic bonding
materials and low resistance materials of fineinterconnects [1]. It is also known that the electron
cloud localized on the fine surface of the fine particles
has a catalytic effect, and researches on chemical
reaction accelerators are being advanced [2]. The
mainstream of these metal fine particle production
methods is a chemical reduction method [3]. A metalsalt or a complex is synthesized, and a metal element
is precipitated using a reducing action. Finally, it is atechnique to obtain nano sized aggregates byclustering. Using this method, commercial metal
nanoparticles are already present. The disadvantageof the chemical reduction method is the precipitationof metallic elements [3]. The precipitated metalelement needs to be clustered. The particle diameter
formed in this way is the limit of about 1 μm. It fulfills
the purpose in utilizing the special surface catalytic
effect of metal nanoparticles [4]. However,considering the development of conductive paste andpaint, the yield of nanoparticles is important [5].
Chemical reduction forms a reliable metal
nanoparticles, but the yield is not high [6]. Anothermethod of forming fine metal particles is a physicalgeneration method from bulk metal. This is called apulverization method, and it is simply a method of
grinding a metal bulk to obtain fine particles. In thismethod, it is considered difficult to reduce the particle

EXPERIMENTAL METHODHigh purity Cu dendrite crystal formation method
Figure 1 shows the experimental system schematicused in this study. Basically, Cu plating method isused. In our previous study, it is known that Cu
plating on Zn/Al alloy in concentrated copper sulfate

717

SEE - Nagoya, Japan, Nov.12-14, 2018

solution forms Cu dendrite structure including Cu/Znalloy due to poor plating formation [8,9]. In thismethod, an oxygen free copper plate placed above thepart where Cu dendrite was formed. A gap of 0.4 mm
in thickness was formed in order to arrange an
oxygen-free copper plate. Since the concentrated
copper sulfate solution can penetrate into the gap of
0.4 mm, it is possible to form Cu dendrite by the interelectrode voltage.
Cu fine particle formation method
High purity Cu dendrite crystals formed by themethod is a structure entangled two-dimensional
growth surface and the three-dimensional growth
portion. Dynamically, it has strength enough to pickup a face with tweezers, but this is caused byentanglement of two-dimensional structure and threedimensional structure. Further, since the ZnO crystal
is present as a fragile structure on the surface of thegrowth substrate, it is possible to peel the Cu dendrite
crystal face from the substrate simultaneously andduring cleaning in the purified water. The peeled Cu
dendrite thin film was held in ethanol, and physicalpulverization was carried out using ultrasonic waves
of a frequency of 50 kHz and an output of 150 W.
After grinding, the water surface of the solution wasplaced in a dropper, and separation of Cu particles
and ethanol was carried out with a centrifuge at
20,000 rpm for 15 minutes. The separated Cu fineparticles were transferred to a petri dish, kept in anitrogen furnace at 80 ° C. for 20 minutes to evaporate
the ethanol, and particle shape observation was
carried out by SEM.

Figure 1. Schematic diagram of high purity Cu
dendrite crystal formation experiment system basedon Cu plating method.

Example of two-dimensional branch lobular crystals

Starting point ofThree-dimensional granular crystal growth
Figure 2. The SEM image showing simultaneous growthstate of two-dimensional crystal and three-dimensional
crystal in Cu dendrite.

(b)

(c)

(e)
(d)
(a)
Figure 3. The surface atomic distribution image and XDS spectrum.
(a) XRD spectrum (b) SEM image (c) Carbon surface distribution (d) Carbon surface distribution(d) Oxygen surface distribution (e) Cupper surface distribution
718

SEE - Nagoya, Japan, Nov.12-14, 2018

Conductive printer ink formation
It was investigated to develop a conductive ink aspractical application of Cu particles obtained in thisstudyCommercially available non-conductive printerink was impregnated with the Cu fine particles
indicated by the above method and dried on theinsulating sheet with this ink.
RESULTS AND DISCUSSIONHigh purity Cu dendrite crystal
It was placed oxygen-free copper plate directly above
the growth surface by Cu dendrite formation process.
This effect will be described below. The field effectof the free electron group in the oxygen-free copper
plate inhibited peeling of Zn fragments and upward
movement of Zn fragments occurring simultaneouslywith Cu plating growth. The electric field effect of
this oxygen free copper plate also affected Cu
dendrite structure formation. In the previous method,
it was three dimensional growth from the beginning.
In the early stage of Cu dendrite crystal growth by thismethod, two dimensional planar growth was carriedout, and a structure in which branches and leaves
extended laterally was formed. However, Cu plating
is stably formed at the Al site at the lower part of theplane growth surface, and longitudinal growth isperformed. The Cu dendrite structure shown in figure
2 was constructed according to the experimental chart
shown in figure 1. The experimental system shown infigure 1 was constructed in the supersaturated copper
sulfate solution. At the beginning, it was left for 5
minutes in the electroless state. It is an object of thesupersaturated copper sulfate solution be sufficiently
impregnated in the gap of 0.4 mm. After that, Cu
dendrite was constructed by fixing the inter-electrodecurrent at 40 mA and holding for 10 minutes. After
construction, it was washed with ultrapure water toremove sulfate ions. And dried at 80 °C. for 20
minutes in a heating furnace in an N2 atmosphere.
In figure 2, it shows an SEM image in which the twodimensional growth and the three-dimensional
growth surface are simultaneously grown. Althoughlateral growth of Cu dendrite crystals is confirmed on
almost the entire surface, longitudinal growth of
granular crystals is confirmed in the part. In the Cu
dendrite obtained by the above method, since thelongitudinal transport of Zn was inhibited, the Cu
concentration reached 99% level. Figure 3 shows thesurface atomic distribution image and XDS spectrum.
The Cu dendrite surface on which the XDS analysis
shown in figure. 3 was performed is the same as thatshown in figure 2. In the surface atomic distribution,
Cu or C is mainly observed. Since C and O ware acarbon tape for SEM observation, it means that mostof the observed substance was Cu. Both the XRD
spectrum and the Cu - kα line lay Cu - lα ray as themain and there were no other atoms other than C
observed. As a result, it can be said that the formationof high purity Cu dendrite crystals was successful.

(a)
(a)

(b)
Figure 4. The Cu fine particles obtained by
SEM observation(b)(a) Granular crystals and branched lobular
crystals(b) SEM image of branch lobe grains
Formation of fine Cu particles
The Cu fine particles obtained by SEM observation
are shown in figure 4. The particle shapes aredifferent, and the particle diameter also varies from 1
to 10 μm, but it was found that the particle formation
at μm level was successful. It was found that theshape of the fine particles differs from the granularshape or the plate shape. Basically, because it is amethod derived from the pulverization method, it was
confirmed that control of both particle size andparticle shape is difficult with this method [10].
However, in this method, since all of the obtained Cu
dendrite crystals are subjected to a pulverization
method, it is possible to atomize all of the Cu dendrite
crystals formed.
Conductive printer ink formation
In order to study the industrial application of Cu fineparticles prepared in this study, formation of
conductive ink was carried out. Printer ink
impregnated with fine Cu particles was measured bya four-terminal method to obtain electric resistivity.
Multiple samples were formed to obtain resistivity
4.22*10-5Ω-m. However, it was confirmed that theresistivity is about 10 times in some samples. This
719

SEE - Nagoya, Japan, Nov.12-14, 2018indicates that there is dispersion in Cu fine particles
that realizes conductivity. It is necessary to study inthe future to have good dispersion.

microparticles by solvent evaporationmethodwith double emulsion system usingfocused beam
reﬂectance measurement, Polymer International,Vol. 66, Iss. 11, 2017, pp.1448–1455[5] M. Inoue, Y. Itabashi, Y. Tada, Development ofbimodal electrically conductive pastes with Ag
micro- and nano-fillers for printing stretchable Etextile systems, Proc. of European Microelectronics Packaging Conference, 2015
[6] A. B. Dichiara, J. Yuan, S. Yao, A. Sylvestre, L.
Zimmer, and J. Bai, Effective synergistic effectof Al2O3 and SiC microparticles on the growthof carbon nanotubes and their application in highdielectric permittivity polymer composites,
Journal of Materials Chemistry A, No. 2, 2014,
pp.7980-7987[7] J. G. Lee D. Y. Kim, T. G. Kim, J. H. Lee, S.
S. A, Deyab, H. W. Lee, J. S. Kim, D. H. Yang,
A. L. Yarin, S. S. Yoon, Supersonically Sprayed
Copper–Nickel Microparticles as Flexible andPrintable Thin ‐ Film High ‐ Temperature
Heaters, Advance Materials Interfaces, No. 4,
2017, pp.1700075(1-8).
[8] Yong Xiao, Mingyu Li, Ling Wang, Shangyu
Huang, Xueming Du, Zhiquan Liu, Interfacial
reaction behavior and mechanical properties ofultrasonically brazed Cu/Zn–Al/Cu joints,
Materials and Design, NO. 74, 2015, pp. 42-49.
[9] Zhicheng Wu, Stefanie Sandlöbes, Liang Wu,
Weiping Hu, Günter Gottstein, Sandra KorteKerzel, Mechanical behaviour of Zn–Al–Cu–Mg
alloys: Deformation mechanisms of as-cast
microstructures,
Materials
ScienceandEngineering A, Volume 651, No,10, 2016, pp.
675-687[10] S. Richard, J. Selwin Rajadurai, V. Manikandan,
Influence of particle size and particle loading on
mechanical and dielectric properties of biochar
particulate-reinforced polymer nanocomposites,
International Journal of Polymer Analysis andCharacterization, Vol. 21, No. 6, 2016, pp.462–
477.

CONCLUSIONSIn this research, we got the following conclusion.
When placing an oxygen-free copper plate above the
Cu dendritic growth portion, upward movement of Zn
fragments derived from the Zn / Al substrate wasinhibited, and as a result it was found that high purity
Cu dendrite crystals could be formed. Next, byexecuting ultrasonic pulverization of this Cu dendrite
crystal in ethanol, it is possible to convert all of the
produced high purity Cu dendrite crystal into fineparticles having a particle size of about 1 to 10 μm.
Finally, by imprinting fine particles formed by thismethod into printer ink and executing printing,succeeded in forming printed matter with
conductivity although there was a deviation between
samples.
ACKNOWLEDGMENTS
The authors are grateful to the Chukyo University
Research Found for financial assistance with thisresearch.
REFERENCES[1] Carmen C. Garcia, Ayrat Murtazin,a SebastianGroh,a Vlasta Horvatica and Kay Niemaxa,
Characterization of single Au and SiO2 nanoand microparticles by ICP-OES using
monodisperse droplets of standard solutions forcalibration, Journal of Analytical Atomic
Spectrometry, NO. 25, 2010, pp.645-653.
[2] T. Kikuta, T. Uchino, N. Akao, Y. Akahoshi, T.
Koura, Procedia Engineering, No. 103, 2015, pp.
279-286[3] J. Giro-Paloma, M. Martínez, L. F.Cabeza, A.
Inés Fernández, Types, methods, techniques,
and applications for microencapsulated phasechange materials (MPCM): A review,
Renewable and Sustainable Energy Reviews,
Volume 53, 2016, pp.1059-1075[4] Muhaimin, and R. Bodmeierb. Eﬀect of solvent
type on preparation of ethylcellulose720

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THERMOGRAVIMETRIC ANALYSIS OF TREATED WASTE ABACAFOR FLY ASH-BASED GEOPOLYMER REINFORCEMENT
Janne Pauline S. Ngo1, Roy Alvin Malenab1 and Michael Angelo Promentilla1
1
Chemical Engineering, De La Salle University, Philippines

ABSTRACT
Natural fiber’s use in composites is gaining more attention for its eco-friendly advantage, low cost, lowdensity, good mechanical properties and other attractive features. In this study, enhancement of abaca fibergeopolymer matrix interaction by chemical treatments was investigated. The study assessed the effects ofsubjecting waste abaca fibers to (1)NaOH pretreatment and (2) aluminum sulfate treatment, in order to modify thefiber surface. Fibers’ tensile strengths were measured and were characterized using XRD and thermogravimetricanalyses (TGA) to analyze changes in composition and thermal stability. Untreated and treated fibers were
reinforced in geopolymer composites and withdrawn for thermogravimetric analysis to observe changes in fibermatrix interaction. The results show that the alkali treatment removes low strength, components in the fiber, which
resulted to lower fiber tensile strength. TGA results showed that treated fibers pulled out from geopolymer
composites were significantly more stable (43.3% by mass decomposition) than untreated fibers (76.0%).
Keywords: natural fiber, reinforcement, geopolymer, thermogravimetric analysis

INTRODUCTION

2016).
Treatments
andsurfacemodification
techniques have been explored in studies in order toimprove natural fibers’ suitability for geopolymer
reinforcement. One of the most studied chemicaltreatments is alkali treatment which involves
delignification and extraction of cellulose. Lignin,
hemicellulose and pectin which are hydrophilic,
amorphous and forms poor bonds with the matrix, arereduced in the fiber composition. In previous studies,
alkali treatment was observe to result in formation ofcorrugations or cause roughening of the fiber surface,enhancing the fiber-matrix adhesions. Natural fibers
also have the disadvantage of being biodegradable,
having the tendency to decay in alkali matrices andhigh temperature conditions, as observed in previous
study when used in concrete (Lima, 2007). In thisstudy, aluminum sulfate treatment was performed todeposit aluminum hydroxide precipitates on the fiber
surface, providing sites for geopolymer bond andgrowth. This in turn could allow protection of thefiber by geopolymer’s high thermal stability and fireresistant properties.
The thermogravimetric analysis (TGA)
involves measurement of sample’s mass loss withrespect to a gradual temperature increase. TGA is
typically done to analyze fiber treatments because thethermal degradation of plant fibers is dependent on its
compositional lignin, cellulose, hemicellulose, pectin
and other trace components (Alvarez & Vazquez,
2003; Izani, et al., 2013). Using TGA, the degradationof hemicellulose and lignin can be observed in thespecimen by observing the temperature ranges atwhich fractions of its mass degrade. This analysis isdone in reference to the standard decomposition

The Philippines is a leading producer of abaca.
Abaca is known for its high-strength fibers, which isincreasingly being used in advanced materials, and it
is broadening in application. The Philippines’ annual
output of abaca was reported as of 2015 is 70,400
metric tons (Philippine Statistics Authority, 2016).
The large volume of abaca produced in turn generates
a considerable amount of agricultural waste since
only its high grade fibers are valued and as much as
75% of the plant is discarded or left in the plantation
to rot (Araral, 2004). Abaca production has seencontinual growth, with export demands increasing
year after year. Meanwhile, researchers’ interest in
the utilization of raw abaca, and other natural plantfibers, has also become widespread due to its low costand abundance. This fiber has become essential inindustrial composite materials, such as in automotive
applications and in composite materials.
Combination of matrix and dispersed phase/s
and their proportions are the essent considerations indeveloping composite materials with the desired
properties (Balasubramanian, 2014). For fiberreinforced composites, the matrix is reinforced byfibers for load transfer, which enhances the overallcomposite strength. The interfacial bonding orinteraction that develops between the fiber and thecomposite matrix is crucial for the material’s strength,
which may often be poor for plant fiber-reinforced
composites. This is mainly because of the hydrophilictendency of plant fibers. Plant-based fibers such as
cotton, flax, jute, sisal, bagasse and hemp have been
adapted as reinforcing components in polymers andcement materials (Yan et al., 2016; Jabbar et al.,721

SEE - Nagoya, Japan, Nov.12-14, 2018stages of natural fibers, as presented in Table 1. TGA
is used to determine the thermal stability of cellulosic
material. Another test was performed on free treatedfibers and treated fibers that were used as geopolymer
reinforcement. The thermal decompositions observed
from these samples were used to assess if the seriesof treatments have aided in developing an interaction
between the geopolymer and the fiber surface, and if
geopolymer’s interaction with the fiber could
improve the fiber’s resistance to degradation.

mixture, washed with distilled water and air-dried for
24 hours before being stored in a desiccator. The
resulting treated fiber is shown in Figure 1c.

Table 1 Decomposition Temperatures of Natural
Fibers’ Components (Zhang et al., 2014)
Components Decomposition
Tmax, °C
Temp, °C
Moisture
30 – 10080
Hemicellulose 160 – 350
245 - 298
Cellulose
240 – 365
335
Lignin300 – 500
337

Figure 1 (a) raw abaca fiber, (b) alkali pretreatedabaca fiber and (c) alkali-Al2(SO4)3 treated abaca
fiber

MATERIALS & METHODOLOGY.

Tensile Strength

Preparation and Treatment of Abaca

Average tensile strengths of the abaca fibers(untreated and treated) were determined by taking
five strands from each bundle of 100 strands
randomly. Then each strand was cut to 5 cm andmounted to cardboard frames to be held by theuniversal testing machine (Instron model 3324) withgauge length of 3 cm. The universal testing machine(UTM) as shown in Figure 3 applies tensile load on
the fiber strand equivalent to an extension rate of 5mm per minute and recording the stress until it breaks.
Prior to fracture, each strand was placed under an
optical microscope (Amscope microscope) linked to
a computer to measure each of their diameters. Fiberstrands were assumed to have approximately circularcross-sectional areas and were computed accordingly.
Tensile strength of the fiber is defined as the
maximum stress it can withstand and is computed by
dividing the load at failure by the original crosssectional area per fiber. The five readings wereaveraged to obtain the final value recorded.

Waste abaca fibers were gathered from
Dumaguete City, Philippines. Abaca fibers wereextracted from the plant source by hand stripping thensegregated into various grades. Residual grade fibers
were collected and measured to have an average of 16
microns diameter. Sodium hydroxide micropearls (99wt%) and aluminum sulfate powders (99 wt%) wereobtained locally and were used as received.
Alkali Treatment
The fibers were segregated to one hundred strands
per sample and soaked in 6 wt% NaOH solution for
48 hours in a 500 mL beaker with constant agitation
at room temperature. Previous studies [11,12] showthat alkali treatment dissolve impurities and weakcomponents of the fiber resulting to a rougher fiber
surface. The fibers are drawn from the solution andwashed with distilled water several times. Alkali
treated fibers were then air dried for 24 h, as shownin Figure 1b.

X-ray Diffraction
Using XRD analysis, the surface modification
resulting from alkali treatment of waste abaca fibers
was evaluated. Crystallinity index (CI) calculatedusing XRD deconvolution method. XRD patterns
were collected on a Maxima XRD-7000 apparatus(Shimadzu, Tokyo, Japan) using Cu Kα radiation
source (40 kV; 30 mA) with wavelength of 1.54 Å toscan the surface of fibers laid on the sample holder
from 2θ of 3.00° to 70.00°. The amount of fibers wasenough to cover the sample holder. The resolution
was set at 0.020, with scan speed maintained at
2°/minute.

Aluminum Sulfate Treatment
Ten percent by weight (10wt%) Al2(SO4)3 solution(pH = 3.5) was used for the aluminum sulfate
treatment. Alkali-treated fibers were soaked in thesolution for 6.25 hours to allow the penetration ofions into the fiber. Gradual addition of 2 M NaOH
solution into the treatment resulted to increase in pH
and formation of white, aluminum hydroxide[Al(OH)3] precipitates. This was done until pH wasadjusted to 6. The fibers were allowed to soak for 24hours to allow further precipitation and deposition on
the fiber surface. Samples were then drawn from the722

SEE - Nagoya, Japan, Nov.12-14, 2018

Thermogravimetric Analysis
TGA was performed using a thermogravimetricanalyzer (TA Instruments TGA Q50, New Castle,
DE, USA). Samples were cut into small pieces(around 5 mm) of 20–25 mg and were placed on aplatinum pan, then heated from 30 to 900 °C at a rateof 10 °C per min under Argon gas at 40 mL per minpurge flow. Calculations of percentage mass loss andderivative plots were done using the TA Universal
Analysis software.

Table 3. Decomposition of Untreated Abaca and
Alkali-treated Abaca Fibers (Malenab et al., 2017)
Stage 1
Stage 2
Total %
mass lossp
Tmax% mass
Tmax
%
900°C
loss
mass
(°C)
(°C)
loss
Un62
8.9
345
78.2
87.1
treatedAlkali53
7.8
350
71.2
79.0
treatedRESULTS & DISCUSSION
Decomposition stage 1 which primarily
involves moisture loss was observed to be lesssignificant for the alkali-treated fiber. This indicates
reduction in hydrophilic components. Decompositionin stage 2 was also observed to be lower for alkalitreated fibers, indicating removal of components.
Overall, alkali-treated fibers were observed todecompose 79.0% of its total mass, whereas theuntreated fibers lost 87.1%, possibly indicating
improved stability.

Tensile Strength
The average ultimate tensile strengths measured fromthe treatments are summarized in Table 2. No
significant change in tensile strength was observed
from fibers treated with aluminum sulfate only. A
significant decline in tensile strength of was observed
when fibers were treated with alkali solution prior toaluminum sulfate solution. The decrease in strength
could be due to the delignification as caused by thealkali solution.

Untreated fibers and fully-treated fibers
reinforced in geopolymer were tested in TGA andcompared to confirm if geopolymer provides aprotective layer over the treated fiber surface
through the deposited inorganic precipitates.
Since geopolymers are known for its fireresistance and high thermal resistance, its
formation and interaction with the fiber could
form a protective layer. This was performed toevaluate the hypothesized effect of the aluminum
sulfate treatment. Fully-treated abaca fibers thatwere reinforced in geopolymer composites were
removed and subjected to TGA. The results werecompared to that of untreated fibers withdrawn froma geopolymer composite. The results, summarized inTable 4, show significant improvement in thermal
stability observed in treated fibers, which lost only
43.3% of its mass as opposed to untreated fibers
which lost a total of 76.0%. This entails that theAl(OH)3 deposits may have effectively served as sites
for geopolymer bond and growth, forming a highly
thermal resistant layer on the fiber surface.

Table 2 Average tensile strength of fibers under
different treatments
Treatment
Tensile Strength (MPa)Raw Abaca
432±141
Al2SO4-treated
420±144
Alkali-treated and296±82
Al2SO4-treated
X-ray Diffraction of Raw and Alkali-treatedFibers
The crystallinity indices measured for
untreated and alkali-treated fibers were 61.0% and78.8%, respectively. The observed increase in fiber
crystallinity after alkali pretreatment is due to theextraction or removal of its soluble amorphous
components including hemicelluloses, lignin andother non-cellulosic components. This process allows
the cellulosic fibers to adopt a more crystalline
structure. This also explains the decreased tensile
strength observed for alkali-treated fibers.
Thermogravimetric Analyses (TGA) of
Untreated and Treated Fibers
Thermal stability of the fibers was studied in terms ofpercent weight losses under argon atmosphere withrespect to a temperature ramp (100/min) from 300 C
to 9000 C. The value of Tmax represents thetemperature at which the maximum decomposition
rate was observed based from the differential
thermogravimetry (DTG) data. The effect of alkali
treatment on the rate of decomposition under thermal
stress was analyzed.
723

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 4 Decomposition of Untreated and Fullytreated Fiber Pulled out of Geopolymer (Malenab, etal., 2017)
Parameter
Tmax(°C)
Total %
mass loss
Max rate ofdecomposition(%/°C)

Untreated

Fully-Treated

320

287

76.0%

43.3%

1.2

0.2%

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Degradation of Cellulose Derivatives/Starch
Blends and Sisal Fibre Biocomposites. Polymer
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Grade Handicraft, 2004. Retrieved May 13,
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CONCLUSION
Lower tensile strength was observed for fibers
treated both with alkali and aluminum sulfate solution
as opposed to fibers treated exclusively withaluminum sulfate solution, whose tensile strength did
not deviate significantly from untreated samples. The
decrease in tensile strength caused by the alkali
treatment was expected since it involves dissolutionof the fiber components that hinder effective
interaction and bonding with the geopolymer matrix.
This was confirmed by the XRD results.
TGA was performed to analyze (1) the effect ofalkali treatment alone on the thermal stability of thefiber and (2) the effect of the series of treatments on
the fiber-geopolymer interaction. Results indicatethat alkali-treated fibers lost a smaller fraction of its
mass under thermal stress. This may signify reductionof weak fibers components after alkali treatment.
TGA results of untreated and treated pulled out ofgeopolymer composites show that treated fibers weresignificantly more thermally resistant. This signified
that the inorganic deposits on the fiber surface as aresult of treatment have aided in formation of bondwith geopolymer particles, thereby enhancing thefiber’s interaction with the geopolymer and acquiring
protection from it. Treated fibers that were pulled outof contact with geopolymer lost a total of 43.3% of its
mass whereas treated fibers that were not contactedwith geopolymer lost 76.0% of its mass in all.
ACKNOWLEDGEMENT
This research was financially supported by the
National Research Council of the Philippines (NRCP),
Philippine Council for Industry, Energy andEmerging Technology Research and Development(PCIEERD), Advanced Device and Materials Testing
Laboratory (ADMATEL) and Electronics ProductDevelopment Center (EPDC).

724

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

INTEGRATED MAINTENANCE SCHEDULING AND STAFFSCHEDULING FOR AN AIRCRAFT HANGAR MAINTENANCE
PROBLEM
Yichen QIN1, Felix T.S. CHAN2*, S.H. CHUNG3, B. NIU4, T. QU5
School of Electrical and Information Engineering, Jinan University (Zhuhai Campus), Zhuhai 519070,
China2
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hum,
Hong Kong
3
College of Management, Shenzhen University, Shenzhen, China
1

ABSTRACTIn this paper, an integrated aircraft parking layout planning and staff scheduling problem is studied. This
integrated problem is motivated by the heavy maintenance activities conducted in the aircraft hangar operated bymaintenance service providers, which consists of determining a maintenance schedule to meet the aircraft
maintenance requests from clients, a series of hangar parking plans and a staff schedule covering the entire
planning period. Instead of relying on inefficient manual handling, the concept of a mathematical model integrating
the interactions among the maintenance planning, aircraft parking arrangement and staff scheduling is discussed
to solve the maintenance problem. The development of geometric constraints is focused, as the number of aircraft
can be placed in the hangar varies according to the incoming maintenance requests to be maintained from time totime, and the blocking of aircraft during the rolling in and out path. Moreover, the maintenance scheduling andstaffing problem are further discussed in the development of mathematical models. This work is innovative indealing with such integrated maintenance problems for aircraft maintenance company providing hangar
maintenance service.
Keywords: staffing, scheduling, aircraft hangar maintenance, mixed-integer linear programming

connection, one feasible option is to outsource
airlines’ own heavy MRO operations to aircraft
maintenance service provider, as the airlines
company save its input in fixed assets related to heavy
maintenance. According to the estimation by
Marcontell [5], outsource of aircraft maintenanceactivities has risen 45 percent in the past over 20 years.
Many airlines have decided to distribute theirmaintenance activities to the maintenance company,
and therefore the airline company is able to focus on
their core business, such as flight planning, marketingand so on.
For aircraft maintenance companies, meeting theincreasing maintenance requests from different
airlines in a timely manner becomes challenging due
to different limit of resource, such as hangar spaceand licensed technician. In practice, many MRO tasks
for different incoming aircraft need to be undergone
at the same time under one hangar, and a maintenanceplan, including aircraft maintenance schedule,
personnel schedule and a series of hangar layout planfor the planning period, has to be carried out by theplanner. The objective of the planning is to minimize

INTRODUCTION
Aircraft maintenance ensures safety in aviation,and different types of aircraft Maintenance, Repair
and Overhaul (MRO) activities should be conductedupon specific flying hours. The expenditure on
aircraft maintenance activities consists around 9
percent of the overall cost within airlines annually [1].
Specifically, the maintenance cost can be classified asline maintenance and hangar maintenance, according
to the place where the maintenance activities are
conducted[2]. Usually, heavy maintenance activities
are referred as hangar maintenance, since thesemaintenance checks require more inputs (equipment,
licensed technicians, space and maintenance time)
and the maintenance activities are undergone inaircraft hangar. Nowadays, the high maintenancecosts and relevant capital input together with thefluctuations of passenger demand become themotivation to let airlines to switch their maintenancepractice, ensuring satisfying the operations safety
regulation and achieving a low maintenance cost andgood appropriate maintenance quality [3, 4]. In this725

SEE - Nagoya, Japan, Nov.12-14, 2018

The maintenance problem with the background of
aircraft heavy maintenance company is considered.
The maintenance planner come up with an aircraft
maintenance schedule, a personnel schedule, aligningwith a set of hangar layout for aircraft parking standarrangement across the planning period. As
mentioned above, the parking stands do not fix, andthe aircraft can be parked flexibly in the hangar.
Furthermore, workers have different skills and thespecific maintenance task for the aircraft can only be
conducted by the technician with license on thatparticular task. Therefore, such maintenance problem
is incorporated with a multi-skill personnel
scheduling problem. The mathematical model has thefollowing assumption: 1) each aircraft’s parking
position cannot be changed along the maintenanceperiod once the aircraft’s parking position isdetermined while rolling in; 2) aircraft cannot be
moved out before completing the maintenance tasks;
3) if blockage happen during the moving in or moving
out operations, the movement operation has tosuspend until the movement pathway is clear, orreconsider the other parking positions; 4) the path of
movement of any aircraft has to be a straight line andany turning movement should be avoided duringmoving in and out operation due to the safety
consideration; and 5) only licensed technician canconduct the designated maintenance task and themaintenance equipment is assumed to be sufficient in
the mathematical model.
Given a set of maintenance requests to be fulfilledby the hangar maintenance company, themaintenance planner need to come up with amaintenance schedule and personnel schedule thatalign with a series hangar layout for aircraft parking
in the hangar with minimize tardiness cost and laborcost. In particular, each maintenance request initiatedby the clients includes the aircraft type, required
maintenance checks, estimated time of arrival (ETA)
to the hangar and estimated time of departure (ETD)from the hangar. For the maintenance task of each
incoming aircraft, only licensed technician for aparticular maintenance task can conduct thecorresponding jobs. Generally, each technician has
multiple skill to conduct different maintenance tasks
for several types of aircraft model. In addition, thelegal constraints regarding the personnel schedulingshould be imposed. For example, the number ofworking hours each week must less than a prescribedhour.

the penalty cost related to delay in fulfilling the order,
as well as the labor cost. Given the situation that theaircraft to be maintained are received from different
airlines or customers, the hangar planner has toarrange these aircraft in different configuration with
their own maintenance request. In addition, safety
regulation need to be observed while making the
hangar layout plan for aircraft parking to reduce therisk of collision. In addition, labor is also a large cost
for an aircraft maintenance service provider, andtherefore an economic and proper scheduling of theworkforce is rather significant and an appropriate
personnel schedule should cover all flight with theavailable workers and their respective skill withminimal labor cost[6].
This paper mainly focuses on the aircraft heavy
maintenance activities taking place at themaintenance hangar operated by aircraft maintenancecompany, and the contents of this paper discusses theconcept of an integrated model assisting themaintenance scheduling problem, aircraft parking
position planning problem for the aircraft under thisproblem background. Blocking between aircraft andimproper arrangement of staff are two main causes
delays in maintenance activities. As different aircraft
have their own features and the specific problem
needs a particular skill, only licensed workers can be
assigned to maintain a specific aircraft in the hangar[6]. There are many papers studying personnel
scheduling problems from the perspective of line [69] while the research focusing on heavy maintenanceis limited [10]. This work is innovative inincorporating the geometric shape of aircraft in the
MILP model, together with personnel schedulingproblem, for the hangar maintenance problem. In
literature, the number of aircraft can be parked in themaintenance hangar is predetermined in the problem
setting of the mathematical model as a parameter, andthis assumption is appropriate under the case if themaintenance hangar is operated by a single airline
company given the situation that the parking positionof each aircraft have been predetermined while
designing the maintenance hangar since the numberof aircraft type operated by a single airline is limited.
However, such problem setting is inappropriate forthe independent aircraft hangar maintenancecompany as the combination of the incoming aircraft
and their size vary from day to day, making
predetermining the parking stand unchanged
impractical under such context.

CONCEPT
MODEL

OF

THE

MATHEMATICAL

The structure of the integrated maintenanceproblem is illustrated in Fig. 1, which consists of theaircraft parking and movement planning problem(Part A) and the personnel scheduling problem (PartPROBLEM DESCRIPTION
726

SEE - Nagoya, Japan, Nov.12-14, 2018

Integrated aircraft maintenance scheduling, parking stand assignment, and personnel
scheduling model with the objective of profit maximization
A. Modelling of aircraft parking standB. Modelling of integrated aircraft maintenanceassignment and scheduling problem
scheduling and personnel schedulingproblems
 Variance of hangar capacity and aircraft
parking assignment over planning period

 Integrating multi-skill licensed techniciansscheduling in maintenance scheduling problem

 Blockage between pair of aircraft during
movements

 Resource constraints

 Optimizing the maintenance schedule andseries of hangar layout plan for aircraft
parking
Fig. 1 Structure of the mathematical model
bij1

bij16

j

bij15

bij 3
i

bij14

( xi , yi )

bij 4
bij 5

bij13

bij12

bij 2

NFPij

bij 6

bij11

bij 7

bij10

bij 8
bij 9

Modelling of aircraft(a)

No-Fit Polygon for two aircraft
(b)

B738

i

A321

j

Safety Margin between aircraft(c)

Before imposing safety margin(d)

After imposing
safety margin(e)Fig. 2 Aircraft parking stand assignment problem

B). The following subsections describe thecomponent to be integrated in the mathematicalmodel.

of aircraft pi in two-dimensional space. No-Fit
Polygon (NFP) is adopted to prevent a pair of aircraftfrom overlapping in the mathematical model [11, 12].
In particular, for two of aircraft pi and p j , the NFPijCOMPONENTS IN MATHEMATICAL MODEL

refers to area where aircraft p j would collide with
Geometric constraints

aircraft pi if the coordinate of aircraft p j is locatedAircraft’s irregular in mathematical model can be
regarded as a polygon as shown in Fig. 2(a). Let thereference point determining the position of eachaircraft be the middle point of the bottom of thepolygon, and the coordinates ( xi , yi ) find the positionon the boundary or in the NFPij (Fig. 2(b)). The
proper region for parking aircraft p j preventing
overlaps with pi refers to the region outside NFPij .
The NFPij is obtianed by recoding the pathway of thecoordinates of p j while p j sliding around the727

SEE - Nagoya, Japan, Nov.12-14, 2018

Hangar Entrance

Staff 1
B
E
Arrival
E
E
A

Staff 2CD
E

Hangar Entrance

Staff 3C

A

Aircraft A - Check A
Aircraft B - Check B
Aircraft C - Check C

B
D

Roll in and Roll out blocking
Multi-skilled staff scheduling(a)(b)
Fig. 3 Maintenance and staff scheduling problem
Arranging the parking position for aircraft is an
important section in the maintenance problem as the
movement operations can be delayed by the improper
parking position arrangement, which may induce aseries of delay if the parking position is arranged
badly at the beginning of the planning period. In
addition, insufficient hangar space and overwhelming
maintenance requests during peak time can also causedelay and blocking (Fig. 3(a)) as mentioned earlier in[14]. For instance, the aircraft just arrive outside themaintenance hangar waiting for maintenance cannot
be moved into the hangar timely due to insufficientspace, or the aircraft finishing maintenance task isdelayed from moving out from the hangar before its
estimated time of departure, which are all due toimproper parking during the initial parking position
arrangement and the other aircraft undergoing
maintenance task blocks its movement way.

boundary of pi keep two polygons contact with eachother without overlapping. There have been a few
integer programming formulations that have adopted
the NFP concept. According to Alvarez-Valdes et al.
[13], each horizontal slice is defined by drawing one
or two horizontal line(s) outward from each vertex of
the NFP and they are then characterized by one or two
horizontal edge(s) as well as the part of boundary of
NFP as shown in Fig. 2(b). A set of variables bijk isassociated with each horizontal slice and thecoordinates of p j is located in the slice k if bijk = 1 .
Therefore, geometric constraint preventing overlaps
can be expressed as
α ijkf ( x j − xi ) + βijkf ( y j − yi ) ≤ qijk + M ⋅ (1 − bijk ),∀i, j ∈ P, i ≠ j , k =1,2,..., mij

where

α ijkf ( x j − xi ) + βijkf ( y j − yi ) =
qijk

is

the

expression of the line of the fth edge of the kth slicein NFPij and mij is the number of slices outside theBlockage of moving out from hangar

NFPij . To further incorporate the safety distanceIf the aircraft finishing its maintenance task isscheduled to moved out from the hangar, but blocked
by the other aircraft undergoing maintenanceactivities in the hangar, the departing aircraft’s moveout operation at current time is delayed until its
movement path is free with obstacles, i.e. wait for theaircraft that blocks its way to finish its maintenancetask and move out from the hangar together. As aresult, the maintenance schedule has to be adjusted
due to the impact of such the parking layout

between pair of aircraft, the original NFP is expanded(Fig. 2(c)) so as to separate two aircraft with aprescribed value. A comparison between before andafter imposing safety margins between each pair ofaircraft is presented in Fig. 2(d) and Fig. 2(e),showing that the empty space in the hangar has been
fully utilized.
Blockage of movement operations

Blockage of moving into hangar

728

SEE - Nagoya, Japan, Nov.12-14, 2018aircraft to be maintained has not arrived or not able toroll into hangar due to insufficient space or blocking.
The approach that reduces the domain time-related
decision variables is further enhanced by considering
the impact of personnel scheduling on themaintenance scheduling problem.

If the newly arrival aircraft received by the
maintenance company is scheduled to move in to its
designated parking position while the way of
movement to the designated parking stand is blocked
by the other aircraft undergoing maintenance task,
then the newly arrival aircraft cannot be moved in at
the scheduled time until its way of movement iscleared, i.e. wait for the aircraft blocking the pathway
to finish its maintenance task and move out, or
rearrange the parking position (Fig. 3(a)). Therefore,
if it is the case, the newly arrival aircraft’s moving inoperation is delayed at the current time to thedesignated parking stand, and hangar planner needreschedule the maintenance plan that aligns with the
hangar layout (if the designated stand for the newly
arrival aircraft remain unchanged), or rearrange a newparking stand for the newly arrival aircraft in order tomove in the aircraft in a timely manner if the buffer
time for such maintenance request is tight.
Integrating
maintenanceschedulingpersonnel scheduling problem

CONCLUSION
The concept of integrated maintenancescheduling, hangar layout planning for aircraft
parking and staff scheduling problem for aircraft
maintenance service company is discussed. Several
mathematical components to be incorporated in
Mixed-Integer Linear Programming (MILP)
formulation are proposed. It is believed that the
propose concept is able to assist aircraft maintenancecompanies to fully utilize their limited resource,
including hangar space and personnel, so as toachieve overall maximal profit. The irregular
geometric shape of aircraft has not been incorporated
in maintenance scheduling problem in literature,
together with multi-skill staff scheduling problem.
The model considers the variation of the number ofaircraft that maintenance hangar can accommodate
over the planning horizon to meet the real situation,
which aligns with the maintenance and staff
scheduling problems. The realization of suchmathematical model and efficient algorithms to tackle
the realistic large-size instance are our future research
direction. The mathematical model is expected tohave a larger number of binary variables deciding therelative position between each pair of aircraft in themodel, and therefore it is a feasible way to decompose
the original mathematical problem into several
subsections, then combine the sub-solution as acomplete one to tackle the complexity of the originalmodel while solving large-scale instances.

andAfter developing the aircraft maintenancescheduling model incorporating the parking standassignment problem with blocking consideration inphysical space, other resource constraints, i.e. multiskill workforce, shall be taken into consideration tocomplete the model (Fig. 3(b)). Different
maintenance checks on aircraft are performed bylicensed technicians with specific equipment in theaircraft hangar. Generally, each licensed technician
can perform different checks according to the license
they obtained, and the maintenance requests received
by the service company. Therefore, the multi-skilledworkforce scheduling problem with technicalequipment constraint is to be integrated with thescheduling problem. In this connection, thescheduling is confined by (1) hangar capacity; (2)multi-skilled workforce, which reflects thecomplexity in carrying out the aircraft maintenanceschedule. From the perspective of employee
scheduling, personnel wages consist a large part ofaircraft service company’s operational costs andtherefore the objective is to maximize the utilizationof total contracted hours so as to minimize overtime
assignment while satisfying the feasibility andlegality rules prescribed by government authorities.
The connection between the maintenance schedulingand personnel scheduling is established by the
maintenance requirements of a particular aircraft,
maintenance schedule and personnel schedule. As themaintenance scheduling and personnel scheduling are
carried out simultaneously, maintenance scheduleand workforce schedule might be adjusted recursively
to meet a series of feasibility constraints under theoccasions that the available workforce at specific time
is not able to meet the maintenance requirements; theACKNOWLEDGEMENTS
The work described in this paper was supported
by grants from The Natural Science Foundation ofChina (Grant Nos. 71471158, 71571120, 71271140);
The Research Committee of Hong Kong Polytechnic
University (Project Number G-UA4F); and The Hong
Kong Polytechnic University under student accountcode RUF1.
REFERENCES[1] ITAT. Airline Maintenance Cost Executive
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[2] Van den Bergh J, De Bruecker P, Belien J,
Peeters J. Aircraft maintenance operations: stateof the art. FEB@Brussel research paper. 2013.
729

SEE - Nagoya, Japan, Nov.12-14, 2018[3] Eriksson S, Steenhuis H. The Global Commercial
Aviation Industry. New York: Taylor & Francis;
2014.
[4] Knotts RMH. Civil aircraft maintenance andsupport fault diagnosis from a businessperspective. Journal of Quality in MaintenanceEngineering. 1999;5(4):335-48.
[5] Marcontell D. MRO's offshore edge shrinking.
Aviation Week & Space Technology.
2013;175(22):56.
[6] De Bruecker P, Belien J, Van den Bergh J,
Demeulemeester E. A three-stage mixed integer
programming approach for optimizing the skill
mix and training schedules for aircraft
maintenance. European Journal of Operational
Research. 2018;267(2):439-52.
[7] Belien J, Cardoen B, Demeulemeester E.
Improving Workforce Scheduling of Aircraft
Line Maintenance at Sabena Technics.
Interfaces. 2012;42(4):352-64.
[8] De Bruecker P, Van den Bergh J, Belien J,
Demeulemeester E. A model enhancement
heuristic for building robust aircraft maintenancepersonnel rosters with stochastic constraints.
European Journal of Operational Research.
2015;246(2):661-73.
[9] Belien J, Demeulemeester E, De Bruecker P, Van
den Bergh J, Cardoen B. Integrated staffing andscheduling for an aircraft line maintenanceproblem. Computers & Operations Research.
2013;40(4):1023-33.

[10] Chen G, He W, Leung LC, Lan T, Han Y.
Assigning licenced technicians to maintenancetasks at aircraft maintenance base: a bi-objective
approach and a Chinese airline application.
International Journal of Production Research.
2017:1-14.
[11] Burke EK, Hellier RSR, Kendall G, Whitwell
G. Complete and robust no-fit polygon
generation for the irregular stock cutting
problem. European Journal of Operational
Research. 2007;179(1):27-49.
[12] Bennell JA, Dowsland KA, Dowsland WB. The
irregular cutting-stock problem - a newprocedure for deriving the no-fit polygon.
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2001;28(3):271-87.
[13] Alvarez-Valdes R, Martinez A, Tamarit JM. A
branch & bound algorithm for cutting andpacking irregularly shaped pieces. International
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Production
Economics.
2013;145(2):463-77.
[14] Qin Y, Chan FTS, Chung SH, Qu T.
Development of MILP model for integrated
aircraft maintenance scheduling and multi-periodparking layout planning problems. 2017 4thInternational
ConferenceonIndustrial
Engineering and Applications, ICIEA 2017.
Nagoya, Japan: Institute of Electrical andElectronics Engineers Inc.; 2017. p. 197-203.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

SYNTHESIS OF ONE-PART GEOPOLYMER USING D-OPTIMALMIXTURE DESIGN FOR SOIL STABILIZATION
April Anne S. Tigue1, Jonathan R. Dungca2, and Michael Angelo B. Promentilla1
Chemical Engineering Department, De La Salle University, Manila 1004, Philippines
2
Civil Engineering Department, De La Salle University, Manila 1004, Philippines

1

ABSTRACT
Soil stabilization is a technique used to alter the natural properties of soil. Enhancing the strength and increasing
the stability of in-situ soil can either be done mechanically or chemically using conventional materials which areusually extracted through mining and quarrying and have been known to pose serious environmental impacts. In
addition, the production of these conventional materials, specifically cement, have a significant contribution to theglobal carbon dioxide emissions. Hence, waste materials such as coal fly ash and volcanic ash as substitute were
utilized in this study by employing the concept of geopolymer. Pertinent experimentations have already been
undertaken with the hopes of promoting geopolymer as construction material. However, less attention has been
given to its application as geopolymer soil stabilizer. One reason could be attributed to the applicability of the
traditional geopolymer synthesis in soil stabilization. Thus, a novel approach one-part geopolymer or ‘just add
water’ similar to ordinary Portland cement was employed and solid alkali activators such as sodium silicate,sodium hydroxide, and sodium aluminate were explored. Characterization technique such as X-ray fluorescence
was performed to examine the elemental composition of the raw materials. The effect of amount of soil, coal fly
ash, volcanic ash, and alkali activators on the unconfined compressive strength response after acid immersion were
investigated using D-Optimal mixture design.
Keywords: Geopolymer, Soil, Stabilizer, D-optimal, Mixture

INTRODUCTION

CO2-emission mitigation strategies [1]. With acement demand amounting to 24.4 million tons in2015 and considering the 20% public construction
growth rate, the forecast for cement may continue toincrease for the coming years [2]. Thus, several
approaches have been proposed to reduce the cement
consumption in the construction industry by using
pozzolanic materials such as coal fly ash and volcanicash.
Alternatively, the geotechnical and engineering
properties of soil may be improved with the process
called geopolymerization. With the presence of analkali activator, the precursor rich in alumina andsilica will react to form into aluminosilicate ions andwill turn into a hardened 3D molecule network uponpolycondensation [3]. Geopolymer precursor can be
any pozzolanic compound or source of silica andalumina that is readily dissolved in alkaline solution[4]. Industrial wastes such as fly ash, bottom ash, slag,
etc. have been utilized as a solid geopolymer
precursor for the application in making building
materials such as cement, concrete, bricks, foam,composite [5-7].
In this study, the potential utilization of wastematerials such as fly ash and volcanic ash that are
locally available in the Philippines as geopolymerbased soil stabilizer were explored. The mix
proportions and effect of amount of soil, precursors(fly ash and volcanic ash), and alkali activator on the

Soil Stabilization is a technique used to alter thenatural properties of soil. Most often, it is necessary
to enhance the strength and increase the stability of
in-situ soil to meet a requirement prior its intended
use. Other reason for using this technique is toimprove the stability by increasing the load bearing
capacity of the subgrade or subbase to support
pavements and structure. Commonly, stabilized soil
is used in structural fill, foundation, roadembankment, land reclamation, in constructing low
volume roadways, commercial sites, streets, and thelikes. Improving and enhancing the soil properties
may be performed by either mechanical or chemicalmeans. Mechanical soil stabilization alters thephysical properties of soil by blending materials toimprove the gradation of particle size to obtain amaterial meeting the required specification.
Conversely, chemical soil stabilization alters thechemical properties of soil by using an admixture.
Conventional materials utilized in chemical soil
stabilization are lime and cement through pozzolanic
hydration process. These materials are usually
extracted through mining and quarrying which havebeen known to pose serious environmental impacts.
In fact, the production of cement has a contribution of
about 5-8% to global anthropogenic carbon dioxide
emissions, which makes it a vital sector to be part of731

SEE - Nagoya, Japan, Nov.12-14, 2018

unconfined compressive strength (UCS) response
after subjecting in acidic environment were
investigated using D-Optimal mixture design.

resistance measured in terms of unconfinedcompressive strength (UCS). The factors consideredin the mixture design are categorized into two
mixtures. Mixture 1 consists of fly ash, volcanic ash
and soil while mixture 2 consists of the alkali
activators such as sodium silicate, sodium hydroxideand sodium aluminate. Dry mixing of materials(mixture of fly ash, volcanic ash, and alkali activator)
using 30% (w/w) alkaline activator were performed
according to the runs generated by the D-optimal
mixture design with parameter range as summarizedin Table 1 [9-11]. Water was added on the dry
formula followed by mixing for at least 5 minutes.
The geopolymer paste binder, a mixture of dry
formula and water, was completely mixed with soil.
After stabilization, geopolymer stabilized soil wascompacted in a cylindrical mold 50 mm diameter by
100 mm height for 3 layers of about 25 tamps per
layer. The molded specimen was sealed and cured for
28 days at ambient temperature.

MATERIALS AND METHODS
Sources of Raw Materials
The soil samples were obtained from a
construction area situated at the southern part ofManila, Philippines. Volcanic ash (VA) samples weregathered from central region of Luzon. Soil andvolcanic ash samples were immediately sieved using
Mesh No. 4. On the other hand, fly ash (FA) samples,collected from a thermal power plant located at thecentral region of Luzon, were used as received.
Analytical grade of sodium silicate (SS) withcomposition 44% SiO2, sodium hydroxide (SH)micropearls with 99% purity, sodium aluminate (SA)with 50-56% Al2O3/ 40-45% Na2O as alkali activatorsand sulfuric acid with 95% were purchased locally.

Table 1 Experimental factors and parameter range(%w/w)

Raw Material Characterization
Characterization such as chemical analysis,
particle size analysis, specific gravity, Atterberg limit,
and Unified Soil Classification System (USCS) weretaken into consideration. Chemical analysis of fly ash,volcanic ash, and soil were conducted using X-ray
fluorescence dispersive (XRF). Particle size analysis
was performed in accordance with ASTM D-422
using sieves to determine the particle size distributionof soil and volcanic ash. For particle size analysis of
fly ash, dynamic light scattering was considered.
Specific gravity and Atterberg limit, which includes
plastic limit and liquid limit, were performed inaccordance with ASTM D-854 and ASTM D-431.
The soil type was determined based on unified soil
classification system.

Factor
Mix 1

Mix 2

FA
VA
Soil
SS
SH
SA

Parameter Range
Unit
LH% of Total Ash 50% 100%% of Total Ash0%50%% of Mixture 1 75%
95%
Ratio
1
2.5
Ratio
1
1
Ratio
0
1.5

Acid Immersion Test
After curing for 28 days, the samples were
immersed in 5% (w/w) sulfuric acid solution[11],[12]. The unconfined compressive strength(UCS) was measured after 28 days of immersion foreach run.

D-Optimal Mix Design

RESULTS

D-optimal mix design methodology is a type ofcomputer generated design for optimizing mixture
with low and high-level constraints. The presence of
upper and lower bound constraints often leads to
oddly shaped region also known as a q-dimensional
convex polytope making the mixture design nonorthogonal compared to typical designs [8]. In
evaluating this kind of design, the forward selectionin Design Expert software is utilized. This design
generates points that are spread through the design
region of the given parameter range. For this study, doptimal design generated the best 21 design points
that will be used in the experiment. An additional 4
replicates were added to capture the error. A total of
25 runs were employed in this experiment. The
response variable considered in this experiment is thestrength response of stabilized soil to sulfuric acidRaw Material Characterization
The type of soil in this study is classified as SMbrown silty sand based on unified soil classification
system and has a specific gravity of 2.54. The
Atterberg limit showed that the fines are non-plastic.
The particle size distribution is shown in Fig. 1. Thisillustrates that the median diameter (D50) is 0.70 mm.
The elemental analysis of soil in oxides form is shownin Table 2. It is primarily composed of SiO2, Fe2O3,
Al2O3, and CaO. Fly ash utilized in this work is
primarily composed of SiO2, Fe2O3, CaO, and Al2O3
and has a specific gravity of 2.85. The median particle
size of fly ash as shown in Fig. 1 is 1.92 microns. The
result of the Atterberg limit showed that it has a liquid
limit of 12 and a plasticity index of 1. On the other732

SEE - Nagoya, Japan, Nov.12-14, 2018

hand, volcanic ash which also comprises SiO2, CaO,Al2O3, and Fe2O3 has a specific gravity of 2.80.
Based on the particle size analysis, 50% of theparticles has diameter of 0.33 mm. The Atterberg
limit showed that it comprises non-plastic particles.

Unconfined Compressive Strength
Figure 2 presents the measured unconfinedcompressive strength after immersion in 5% sulfuric
acid for 28 days of the geopolymer stabilized soil at
different mix proportions of raw materials and alkali
activator. The recorded unconfined compressive
strength ranges from 0.76 kPa to 2620 kPa. The
stabilized soil R22 (25% FA /75% soil and alkali
activator 50% SH/50% SS) has the highest value of
unconfined compressive strength making it the best
mix sample among other runs. The samples with ND
label, R6 (5% precursor/95% soil), R7(12.5%
precursor/87.5% soil), and R11 (5% precursor/95%
soil), were not able to withstand the acidic
environment resulting to breakage of sample priormeasurement of UCS. This may be due to the lowamount of geopolymer precursors (fly ash andvolcanic ash) and high amount of soil to be stabilized
in the mixture. The mix proportion with acompressive strength of at least 75 kPa can berecommended for structural fill application. This is inaccordance with the requirement of National
Structural Code of the Philippines [13].The stabilized
soil developed in this study has a compressive
strength comparable to soil stabilized with lime
and/or cement despite its exposure in aggressive
condition. Numerous studies have revealed that soil
treated with lime has a range of unconfinedcompressive strength of 14.2 kPa-3000 kPa [14-17].
Conversely, cement stabilized soil can range tounconfined compressive strength value of 100-900kPa [18-20].

Table 2 Chemical composition of raw materials
ChemicalCompound

Soil(Mass %)Fly Ash(Mass %)

SiO2
Fe2O3
Al2O3
CaO
TiO2
K2O
SO3
Others

38.87
34.06
12.53
6.82
3.09
1.87
2.76

24.65
44.63
8.55
16.04
1.32
1.18
1.63
2.00

Fig. 1

Volcanic
Ash(Mass %)
56.75
13.00
11.34
10.93
1.35
5.01
1.62

Particle size distribution of raw materials.

Fig. 2

Unconfined compressive strength at different mix proportions.

D-Optimal Mix Design Model(SS, SH and SA). The final model of the combined
mixture was chosen based on the highest orderpolynomial where the addition of terms is significant(p-value<0.05), model lack of fit is not significant(p>0.05) and the model is not aliased. Table 3 shows
the ANOVA of crossed mixture design. A p-value of0.1595 for lack of fit indicates that it is not significant
implying that the quadratic mixture crossed with

To statistically measure the effect of geopolymer
mix at different mix proportions, experimental data
were analyzed by fitting a model (linear or quadratic)
for the unconfined compressive strength response
which is dependent on different mix proportions ofsoil and precursors (FA and VA), and alkali activator
733

SEE - Nagoya, Japan, Nov.12-14, 2018

linear mixture model is fit. Quadratic mixture of soil
and precursors crossed with linear mixture alkali
activator was chosen having a p-value of 0.0002 and
0.0001 for mixture 1 and 2, respectively. The contour
plot of the model as presented in Fig. 3 shows theeffect and behavior of the various factors on themeasured unconfined compressive strength response.
The intensity of unconfined compressive strength canbe represented by red color which demonstrates highvalue of unconfined compressive strength to blue
having low value of unconfined compressive strength.

Table 3 ANOVA of chosen crossed mixture design model (A= Fly ash; B= Volcanic ash; C= Soil; D=Sodium
Silicate; E= Sodium Hydroxide; F= Sodium Aluminate)
SourceModelLinear x Linear Mixture
ABF
ACE
ACF
BCD
BCE
ResidualLack of Fit
Pure Error
Cor Total

Sum ofSquares
4902.30
4008.46220.23222.9845.02
281.19
51.86
42.08
35.17

df
13
8
1
1
1
1
1
11
7

6.91
4944.38

4
24

Mean
Square377.10501.06220.23222.9845.02
281.19
51.86
3.83
5.02

F Value
98.57
130.97
57.57
58.28
11.77
73.50
13.56

p-value(Prob > F)
< 0.0001< 0.0001< 0.0001< 0.0001
0.0056< 0.0001
0.00362.91

0.1595significant

notsignificant

1.73

Fig. 3 Contour plot for unconfined compressive response prediction model of mixture 1 (soil and precursor)
evaluated at each point of mixture 2 (alkali activator) design.
734

SEE - Nagoya, Japan, Nov.12-14, 2018

In terms of geopolymer precursor, it can beobserved that high strength geopolymer stabilized
soil can be produced as its nearing the apex of fly ash
component, which means that high amount of fly ash
could actually produce high strength geopolymer ascompared with volcanic ash. Conversely, as the
mixture nearing the apex of volcanic ash the strength
decreases. This could mean that greater proportion of
volcanic ash in the precursor relative to fly ash could
produce a low strength geopolymer stabilized soil.
This behavior may be attributed to the reactive natureof the precursor in terms of participation ingeopolymerization process. This also implies that not
all the alumina and silica content of the precursor canparticipate in geopolymerization [21]. The available
amorphous alumina and silica content of the
precursor are the only alumina and silica content
participating in geopolymerization process. It isbelieved that the amorphous content of alumina andsilica can easily be dissolved in the alkali activator
thereby producing gel networks of inorganic
geopolymer. The more available amorphous content
of alumina and silica in the raw material, the betterthe mechanical strength of geopolymer stabilized soil
[22].
The increase in compressive strength of thestabilized soil geopolymer have been remarkably
noticed in alkali activator containing 50%SS:50%SH,
47.5% SS:40.42% SH:12.08% SA and 33% SS:33%
SA:33% SA as the amount of soil decreases. It has
been observed that as the component reaches the apexof SA (less SA in the mixture) as illustrated in Fig. 3,
the strength increases. Presence of SS in greater
proportion in alkaline activator with considerationthat SH is also present in greater proportion, produces
a high strength geopolymer stabilized soil. The
presence of greater proportion of SH to produce highstrength geopolymer stabilized soil may be explainedby the initial step of geopolymerization. During thisprocess, dissolution of material rich in aluminosilica
occurs in the presence of an alkali activator such as
sodium hydroxide. This activator is responsible forincreasing the reactivity of the alumina silica material
by attacking the Si-O-Si/Si-O-Al bond of the starting
material with its OH-. This results in breaking downof Si-O-Si/ Si-O-Al bond thereby forming reactive
aluminates and silicates [23],[24]. High amount of SH
in the mixture could mean higher dissolution rate. A
higher dissolution rate may mean more material canbe broken down into its reactive form, hence morereactive aluminosilica source that could participate ingeopolymerization. The production of low strengthstabilized soil could be attributed to a lower
dissolution rate, less leaching of alumina and silica
ions from the precursor and lower value of
unconfined compressive strength [10].

synthesis using precursors such as fly and volcanic
ash and solid alkali activators such as sodium silicate,sodium hydroxide, and sodium aluminate with Doptimal mixture design. The unconfined compressive
strength (UCS) was evaluated after exposing to a 5%(w/w) sulfuric acid solution. The final model of the
combined mixture was quadratic mixture of soil andprecursors crossed with linear mixture alkali activator.
The mix proportion that yielded high value of
unconfined compressive strength was found to be theproportion mix having 25% fly ash/75% soil with analkali activator ratio of 50% sodium silicate/50%
sodium hydroxide having a strength of 2620 kPa. The
mix proportions having unconfined compressive
strength of at least 75 kPa can be recommended forstructural fill application. The geopolymer stabilized
soil developed in this study showed promising result
as potential acid-resistant material.
ACKNOWLEDGEMENTS
The authors would like to acknowledge theEngineering Research and Development forTechnology (ERDT), and URCO Research Project(IR 1TAY15-3TAY16) for the financial support. The
authors would also like to thank GeotechnicalLaboratory and Mechanical Engineering Laboratoryof De La Salle University for allowing them to use
their facilities.
REFERENCES[1] Worrell, E. , Price, L. , Martin, N. , Hendriks, C. ,and Ozawa, M. L. Carbon Dioxide Emissions
from the Global Cement Industry. Annual Review
of Energy and the Environment Vol. 26, Issue 1,
2001, pp. 303–329.
[2] Cement Manufacturers’ Association of thePhilippines Inc. (CeMAP) 2015 Annual Cement
Industry Report. (2015).
[3] Xie, J. and Kayali, O. Effect of Initial Water
Content and Curing Moisture Conditions on theDevelopment of Fly Ash-Based Geopolymers in
Heat and Ambient Temperature. Construction and
Building Materials Vol. 67, Part A, 2014, pp. 20–
28.
[4] Jaarsveld, J. G. S. Van and Deventer, J. S. J. Van
The Potential Use of Geopolymeric Materials to
Immobilise Toxic Metals Part I. Theory And
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for Geopolymer Research , in Australia Amazing
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10.
[5] Promentilla, M. A. , Thang, N. , Trung Kien, P. ,Hinode, H. , Bacani, F. , and Gallardo, S.
Optimizing Ternary-Blended Geopolymers with
Multi-Response Surface Analysis. Waste andBiomass Valorization Vol. 7, 2016[6] Kalaw, M. , Culaba, A. , Hinode, H. , Kurniawan,

CONCLUSION
This study has explored one part-geopolymer
735

SEE - Nagoya, Japan, Nov.12-14, 2018

W. , Gallardo, S. , and Promentilla, M. Optimizing
and Characterizing Geopolymers from Ternary
Blend of Philippine Coal Fly Ash, Coal Bottom
Ash and Rice Hull Ash. Materials Vol. 9, Issue 7,
2016, pp. 580.
[7] Malenab, R. A. J. , Ngo, J. P. S. , and Promentilla,
M. A. B. Chemical Treatment of Waste Abaca for
NaturalFiber-Reinforced
Geopolymer
Composite. Materials Vol. 10, Issue 6, 2017, pp.
579.
[8] Carlson, R. Design of Experiments, Principles andApplications, L. Eriksson, E. Johansson, N.
Kettaneh- Wold, C. Wikström and S. Wold,
Umetrics AB, Umeå Learnways AB, Stockholm,
2000, ISBN 91-973730-0-1, Xii + 329 Pp. Journalof Chemometrics Vol. 15, Issue 5, 2001, pp. 495–
496.
[9] Pavithra, P. , Reddy, M. S. , Dinakar, P. , Rao, B.
H. , Satpathy, B. K. , and Mohanty, A. N. A Mix
Design Procedure for Geopolymer Concrete with
Fly Ash. Journal of Cleaner Production Vol. 133,
2016, pp. 117–125.
[10] Phetchuay, C. , Horpibulsuk, S. , Arulrajah, A. ,Suksiripattanapong, C. , and Udomchai, A.
Strength Development in Soft Marine Clay
Stabilized by Fly Ash and Calcium Carbide
Residue Based Geopolymer. Applied Clay
Science Vol. 127–128, 2016, pp. 134–142.
[11] Djobo, J. N. Y. , Elimbi, A. , Tchakouté, H. K. ,and Kumar, S. Mechanical Properties andDurability of Volcanic Ash Based Geopolymer
Mortars. Construction and Building Materials
Vol. 124, 2016, pp. 606–614.
[12] Jin, M. , Zheng, Z. , Sun, Y. , Chen, L. , and Jin,
Z. Resistance of Metakaolin-MSWI Fly Ash
Based Geopolymer to Acid and Alkaline
Environments. Journal of Non-Crystalline Solids
Vol. 450, 2016, pp. 116–122.
[13] of Structural Engineers of the Philippines, A.
National Structural Code of the Philippines 2010:
Buildings, towers and other vertical structures.
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[14] Dash, S. and Hussain, M. Lime Stabilization ofSoils: Reappraisal. Journal of Materials in Civil
Engineering Vol. 24, 2012, pp. 707–714.

[15] Al-Mukhtar, M. , Khattab, S. , and Alcover, J.-F.
Microstructure and Geotechnical Properties ofLime-Treated
Expansive
ClayeySoil.
Engineering Geology Vol. 139, Issue
Supplement C, 2012, pp. 17–27.
[16] Ghobadi, M. H. , Abdilor, Y. , and Babazadeh,
R. Stabilization of Clay Soils Using Lime andEffect of PH Variations on Shear Strength
Parameters. Bulletin of Engineering Geology andthe Environment Vol. 73, Issue 2, 2014, pp. 611–
619.
[17] Dungca, J. R. and Dychangco, L. F. T. Strength
Properties of Road Base Materials Blended with
Waste Limestones. Vol. 11, 2016[18] Correia, A. A. S. and Rasteiro, M. G.
Nanotechnology Applied to Chemical Soil
Stabilization. Procedia Engineering Vol. 143,
Issue Supplement C, 2016, pp. 1252–1259.
[19] Ojuri, O. O. , Adavi, A. A. , and Oluwatuyi, O.
E. Geotechnical and Environmental Evaluationof Lime–cement Stabilized Soil–mine Tailing
Mixturesfor
Highway
Construction.
Transportation Geotechnics Vol. 10, Issue
Supplement C, 2017, pp. 1–12.
[20] Choobbasti, A. J. and Kutanaei, S. S.
Microstructure Characteristics of CementStabilized Sandy Soil Using Nanosilica. Journalof Rock Mechanics and GeotechnicalEngineering 2017[21] Tennakoon, C. , Silva, P. De , Sagoe-Crentsil, K.
, and Sanjayan, J. G. Influence and Role ofFeedstock Si and Al Content in Geopolymer
Synthesis. Journal of Sustainable Cement-BasedMaterials Vol. 4, Issue 2, 2015, pp. 129–139.
[22] Jaarsveld, J. G. S. van , Deventer, J. S. J. van ,and Lukey, G. C. The Characterisation of Source
Materials in Fly Ash-Based Geopolymers.
Materials Letters Vol. 57, Issue 7, 2003, pp.
1272–1280.
[23] Provis, J. L. 4 - Activating solution chemistry forgeopolymers. In Geopolymers; Provis, J. L.,
Deventer, J. S. J. van, Eds.; Woodhead
Publishing, 2009; pp. 50–71.
[24] Davidovits, J. Geopolymers. Journal of thermal
analysis Vol. 37, Issue 8, 1991, pp. 1633–1656.

736

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

FLOW INVESTIGATIONS WITHIN A CONCENTRIC CYLINDERS OFGAS SENSOR MODULE FOR I.C. ENGINES
1Tatsuya Kawaguchi, 2Yoona Jeong, 3Takushi Saito and 4Isao
1,2,3,4Satoh Tokyo institute of technology, Japan.

ABSTRACTThe study deal with the experimental investigation of the flow field around the inorganic sensors withconcentric double protectors with apertures such as the commercial gas sensor modules for passenger vehicles.
Transparent acrylic model was used in conjunction with the particle image velocimetry. The experimental result
demonstrated that the magnitude of velocity in the vicinity of the sensor rod is significantly lower than that of theexternal main flow. The velocity fluctuation through the opening apertures enhances the mass transfer between
the inside and outside of the protectors and contributes to the better response of the sensing module.
Keywords: Flow visualization, Gas sensor, Internal flow, Mixing process, Particle image velocimetryalignment of both concentric shrouds. Although theconcentration fluctuation of the exhaust gas must be
detected by the sensor, which is protected by theconcentric shrouds, the primary delay or time lag
occurs due to the off-axis alignment of the opening
apertures. Moreover, the frequency response of thesensor module decreased due to the aforementioned
delay effects. In order to understand thecharacteristics of the sensor and to improve theoverall performance of the gas sensor, the detailed
behavior of the fluid flow around the sensor core aswell as the flow between protectors must be clarified.
Especially, the airflow convection through themultiple opening apertures is the significant factor forthe evaluation of the mass transportation between
sensor core and external flow of protector.

INTRODUCTION
Regulation specifications of greenhouse gas
emission and fuel economy standards for passenger
vehicles or trucks were significantly progressed morethan a decade. Drastic reductions of the oxidizing
gases and the small particles in the exhaust gas fromthe I.C. engine have been required. Although only a
few country had introduced mandatory greenhousegas emission and/or fuel economy standards, many
countries including European Union were announced
their intention to introduce the greenhouse gas
emission standards. Further improvement of gas
emission sensing, monitoring and controlling for theinternal combustion engine of automobiles, marine
engines and power plants have been desired. Not only
the reduction of the particulate matter but also thecontrol of such emission gas as CO2, NO2 and SO2
were required that enable to improve total efficiencyof the thermal systems. In the recent engine system,
multiple inorganic gas sensor modules are equipped
to obtain the various kinds of gas concentration [1-3].
For example, precise measurement of O2
concentration difference between catalysts was used
for engine management system [4,5].
Figure 1 is the photograph of the actual engine
compartment of the passenger vehicle. The headsection of the exhaust gas sensor module forcommercial vehicles consists of the cylindrical rod of
Zirconium dioxide as a sensor core with heater anddual stainless cylindrical shrouds with multiple
openings or apertures. The shrouds prevent the sensor
core from the direct exposure to the high temperature
exhaust gas. Since the operation temperature of thesensor rod is significantly high, the penetration of theparticulate objects and liquids to the sensor core must
be avoided. Therefore, the most of all commercial
sensor module employ the apertures with off-axis

Fig 1 Gas sensors attached to the exhaust system fora passenger vehicle. Three rectangular indicate thesensor module. As the head of the module is plugged
into a pipe, neither sensor element nor protecting
shroud are visible.

737

SEE - Nagoya, Japan, Nov.12-14, 2018transparent channel with honeycomb and electricalfans. Both width and height of the channel were 240mm, length of the channel was 910 mm. In the present
experiments, velocity distribution at the channel
entrance was assumed to be homogeneous, mean
velocity of the airflow was 0.15 m/s. Continuouswave Nd:YAG laser was used in conjunction with thehigh-speed CMOS camera. Output power andwavelength of the laser light source was 2 W and 532
nm respectively. Maximum frame rate of the camera
was 800 fps, pixel dimension was 1920x1080 that
affected the resultant frame rate due to the bandwidthof the digital connection between camera head andthe computer. For the velocity vector map
determination, standard recursive cross correlation
calculation with the sub-pixel fitting estimation was
employed.
Figure 4 is a captured image of the model andtracer particles illuminated with the monochromatic
light source. As tracer particles, smoke from an
incense stick was used that has the good traceability
to the airflow. Mean diameter of the tracer particle
was a few μm,

QUANTITATIVE FLOW VISUALIZATION
For the industrial applications, gas or liquid flow
around the cylinder or rectangular obstacles is one of
the most important flow field. Especially the flow
analysis around a finite cylinder is the important
external flow; therefore, numerous experimental andnumerical investigations were reported that deal withthe detailed behavior of the flow around therectangular or cylindrical objects [6-10]. However,not so many investigations of the flow structure byusing the hollow cylinder or cylindrical object with
by-pass channels was reported [11,12]. In the present
study, we focused on the fluid flow visualization
within the gas sensor module for the automobile
applications.
Target model
A transparent acrylic model was designed andmanufactured by noting the Reynolds number of theactual flow field. Figure 2 shows the photograph ofthe concentric cylinders used in the experiments. The
model was divided into triple concentric cylinders,which consisted of outer protector, inner protector
and sensor core rod. In this experiment, the sensor is
replaced by the plastic solid cylinder instead of theZirconium sensor rod with a heater. External
diameter of the outer protector, inner protector andthe core were 100 mm, 70 mm and 40 mm
respectively. As shown in the figure, eight circular
apertures were prepared by 45 deg for the innercylindrical protectors. On the inner protector surface,in-line eight opening aperture were aligned. External
protector has dual-line eight apertures as well. On thecenter-top of the cylinders, the other aperture wasprepared. The diameter of each opening aperture was
20 mm.

(Top View)(Side view)Fig 2 Transparent acrylic model for the flow
visualization consisted of outer and inner hollow
cylinder (protectors) and inner solid cylinder (sensorrod). Diameters of cylinders were 100, 70 and 40 mm,
heights were 123, 98, and 61 mm, respectively. Bothprotectors have multiple opening apertures.

Flow field measurement by particle image
velocimetry
Figure 3 illustrated the experimental set up for the
optical flow visualization used in the following
experiments. Particle image velocimetry (PIV) [13]was used as a measurement method. PIV is one of the
optical flow measurement technique that can measure
the two dimensional two component velocity vectors
in the fluid flow by means of the thin laser sheet in
conjunction with the digital camera. The local
velocity vector is determined with the local particle
image’s displacement between two or moreconsecutive images of tracer particles in fluid flow. In
this study, normalized cross correlation function was
employed for the evaluation of the local particle
image similarity.
In this study, detailed airflow behavior in theconcentric protectors was investigated under thesteady flow. The model was installed in a rectangularFig 3 Experimental rig for the flow visualization bymeans of the particle image velocimetry.

738

SEE - Nagoya, Japan, Nov.12-14, 2018

respectively. By the comparison of the aperture phasedifferences, the effects of the offset angle of the
opening apertures was evaluated. Figure 6 compares
the spatially averaged velocity transition through the
opening apertures with the angles of (0, 0) deg.
Velocity transition under the other three alignment
were obtained with the same flow configuration. The
negative sign of the normal velocity component was
defined as the incoming flux to the sensor core. The
positive velocity, in contrast, indicates the outgoingflow to the external main flow. At the upwind
aperture, which was located at θ = 0 deg, the flow
through the aperture was stable and the magnitude of
the cross-sectional mean velocity was -2.0 mm/s
approximately. Since the opening aperture is present
at the upward stagnation point at θ = 0 deg in which
the relative pressure is higher than that of the otherapertures, mean inbound flow through thecorresponding aperture was observed. In contrast, thefluid velocity through the side aperture at θ = 90 deg
was significantly fluctuated. The mean velocity
through the side aperture was -6.7 mm/s, therefore thevolume flux through the side aperture was 2.1 cm3/sof incoming direction. Comparison of the velocity
fluctuations at the different alignment of theprotectors of (22.5, 22.5) deg resulted that both mean
velocities during the period were 2.5 mm/s and 6.3mm/s, volume fluxes were 0.79 cm3/s and 2.0 cm3/s
respectively. The comparison of the angularalignment of protectors demonstrated that theoutgoing flow is occurred even at the upstream
aperture.
In order to clarify the aforementioned flow pattern,angular distribution of mean velocity and velocity
fluctuation of each aperture position in terms of theoffset angles of the protectors were summarized. The
comparison of the mean velocity through theapertures demonstrated that the incoming andoutgoing flow were appeared at the downward andupward apertures respectively. The velocity
distribution indicated that the overall flow direction
within the inner protector was inverted to the external

Fig. 4

Snapshot of the captured image. Tracer
particles
wereilluminatedwith
continuous wave green laser sheet
RESULTS AND DISCUSSION
Figure 5 shows the calculated instantaneous
velocity vector map. From the visualization results ofthe velocity vector map around the sensor core rod,the magnitude of the velocity around the sensor core
was drastically decreased due to the complicatedstructure in the cavity and the multiple apertures.
Figure 5 also shows the comparison of the velocity
vector map in the vicinity of the opening aperture at
the different instance. Although the external flow wassteady and velocity was constant, the fluid behavior
within the protector is not steady and the orientation
as well as the magnitude of velocities weresignificantly fluctuated. To clarify the effects of theaperture positions, the location of the opening
apertures and the orientation of each protector werevaried as a parameter.
The parameter, θ, represents the angle from thedirection of upstream, i.e. the main flow is comingfrom the direction of θ = 0. The angular offset of bothouter and inner protectors were varied from (0, 0) deg,
(0, 22.5) deg, (22.5, 0) deg and (22.5, 22.5) deg

Fig. 5

Examples of the instantaneous velocity vector map near the opening aperture of the inner protector bymeans of the particle image velocimetry. The color of the arrows corresponds velocity magnitude, i.e.,
red arrow is the faster velocity magnitude. Both vector maps were obtained under the identical
di i
h fl
li
739

SEE - Nagoya, Japan, Nov.12-14, 2018

45 deg90 deg0 deg

Fig. 6135 deg

180 deg

Mean velocity through the opening apertures in terms of the angle. Each angle value in the figure represents
the angular position of the opening apertures under (0, 0) degree alignment of dual protector.

main flow. Consequently, the direction of volume
flux through the sensor core is opposed to the external
main stream. In contrast to the lower and stable mean
velocity distribution around the core rod, thesignificant velocity fluctuations were observed in thevicinity of the aperture located on the side of the innerprotector that enhancedthe convective mass transfer.

[2] Twigg M V, Progress and future challenges incontrolling automotive exhaust gas emissions,Applied Catalysis B: Environmental, Vol. 70, pp.
2-15, 2007
[3] Moos R, Izu N, Rettig F, Reiß S, Shin W andMatsubara I, Resistive Oxygen Gas Sensors for
Harsh Environments, Sensors(Basel), Vol. 11,
No. 4, pp. 3439-3465, 2011[4] Riegel J, Neumann H, Wiedenmann H M.
Exhaust gas sensors for automotive emission
control, Solid State Ionics. Vol.152-153, pp. 783800, 2002
[5] Salehi R, Alasti A, Vossoughi G and Boroushaki
M, Nonlinear Oxygen Sensor Output Voltage
Estimation in a Gasoline Engine Using NARX
Model, The Journal of Engine Research, Vol. 22,
pp.13-20, 2011
[6] Wang H F and Zhou Y, The finite-length squarecylinder near wake, J. Fld. Mech., Vol. 638, pp.
453-490, 2009.
[7] Pattenden R J, Turnock S R and Zhang X,
Measurements of the flow over a low-aspectratio cylinder mounted on a ground plane, Exp.
Fld., Vol. 39, pp. 10-21, 2005
[8] Rostamy N, Sumner D, Bergstrom D J and Bugg,
J D, Local flow field of a surface-mounted finite
circular cylinder, J. Fld and Structures, Vol. 34,
pp. 105-122, 2012[9] Igbalajobi A, McClean J F, Sumner D andBergstrom D J, The effect of a wake-mounted
splitter plate on the flow around a surfacemounted finite-height circular cylinder, J. Fld.

CONCLUSION
The flow field in the concentric triple cylinders
was investigated by means of a particle image
velocimetry. The transparent model was designed andused for the optical visualization. The geometricalshape was determined by considering the Re number
matching with the actual gas sensor for a passenger
vehicle. The quantitative visualization resulted thatthe flow direction within the inner protector was
inverted to the external main flow. The velocity
magnitude of the internal flow is significantly lower
than that of the main flow. The throughput of theconcentration modulation around the sensor could beenhanced by the velocity fluctuation around the side
apertures that contribute to the quick response of theentire sensor module.
REFERENCES[1] Szabo N, Lee C, Trimboli J, Figueroa O,
Ramamoorthy R, Midlam-Mohler S, Soliman A,
Verweij H, Dutta P and Akbar S, Ceramic-based
chemical sensors, probes and field-tests in
automobile engines, J. Materials Sci., Vol. 38,
21, pp. 4239-4245, 2003
740

SEE - Nagoya, Japan, Nov.12-14, 2018

Visualization of a finite wall-mounted cylinder
wake controlled by a horizontal or inclined hole,
J Visualization. https://doi.org/10.1007/s12650018-0482-6, 2018[13] Adrian R J, Particle-Imaging Techniques forExperimental Fluid Mechanics, Annu. Rev. Fld
Mech., Vol. 23, pp. 261-304, 1991

Structures, 37, pp. 185-200, 2013[10] Sumner D, Flow above the free end of a surfacemounted finite-height circular cylinder: A review,
J. Fld. Structures, 43, pp. 41-63, 2013[11] Rinoshika H, Rinoshika A and Fujimoto S,
Passive control on flow structure around a wallmounted low aspect ratio circular cylinder byusing an inclined hole, J. Fld. Sci. and Technol.,Vol., 12, No. 1, JFST0006, 2017[12] Rinoshika H, Rinoshika A and Fujimoto S,741

4th Int. Conf.on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

APPLICATION STATIC LOAD TEST (SLT) AND PILE INTEGRITYTESTING (PIT) OF PILES IN SEA PORT “PRORVA” (WEST
KAZAKHSTAN)

1,2,3

Askar Zhussupbekov1, Zhanbolat Shakhmov2and Gulshat Tleulenova3
Department of Civil Engineering, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan

ABSTRACTThis working plan has been developed for the production of driving operations of precast concrete piles withsection 400x400 mm on the project "Cargo Transportation Route for Facilities of The North-Eastern part of the
Caspian Sea. North Caspian Marine Channel with Berthing Facilities". This scope of work provides work on thegeodesic broken pile field, leader of drilling and precast reinforced concrete piles with 400x400mm section,
23.0m of length, 25.5m and 27.5m. Total amount of precast concrete piles 1100 pieces (23m of pile length - 714
pieces, 25.5m of length -368 pieces and with 27.5m length in the amount of 18 pieces). Precast concrete piles arecomposed of two segments: the bottom segment with length of 16.0m and upper segment length: 7.0m, 9.5m and11.5m. The following documents have been referenced for this method statement: Standard Test Method for
Low Strain Impact Integrity Testing of Deep Foundations use ASTM D 5882, Standard Test Methods for Deep
Foundations Under Static Axial Compressive Load use ASTM D 1143 in seasonally freezing soil ground. In
paper analyze bearing capacity of concrete pile foundations b/5, k/3. In SCLT testing, the test load on the pile isfor hold on 2 cycles. Loading and unloading was carried out in the following sequence: 0, 30, 60, 90, 125, 90,
60, 30, 0, 170, 210, 250, 210, 170, 125, 80, 40 and 0% of design. In the first cycle, the experimental pile was
loaded to 100% of the design value. In this paper presented results of piles of PIT methods in seasonally freezing
soil grounds.
Keywords: pile, load, settlement, standard

soil conditions.
The object of study are research bearing capacityof pile foundation in seasonally freezing soil ground..
The project "Cargo Transportation Route(CaTRo) for Facilities of The North-Eastern part of
the Caspian Sea. North Caspian Marine Channel
with Berthing Facilities" Seaport “Prorva” is one ofimportant Megaproject for Atyrau region West
Kazakhstan [27].
The construction Seaport “Prorva” presented byreinforced concrete structures. Totally construction
area is 154980 m2. The design life of this project is
assigned in accordance with SNiP RK 3.04-01-2008
is 50 years.

INTRODUCTION
Most of the territory of Kazakhstan ischaracterized by long winter periods. The thicknessof frozen soils was determined from the temperature
regimes. The temperature regime depends on
climate. The depth of freezing of soils varies within
0.5-2.5 meters.
Question the increasing the stability, reliability
and durability of structures studied by many
researches, both domestic and foreign. Most
experiences in these works are considered scientificfrom USA, Russia, South Korea.
Nevertheless, the problem seasonally freezing
soils such as change the mechanical and physicalproperties of frozen soils are dependent on
temperature, a moisture content of a soils and etc., isquite complex and poorly understood, and thepresent.
The issue of strength, stability and reliability ofthe designed structures in seasonally freezing soil
are not fully described in the standard [3]-[4].
In the problem under consideration to the usual
problems of designed pile foundation in seasonallyfreezing soil (the study of the geotechnicalproperties, moisture content of soils, temperatures,etc..) authors study the problem of stability,
reliability pile foundations in seasonally freezing

SEAPORT “PRORVA” DESCRIPTION
The construction site is dimensions of 205 x 756
m. The site in plan has a rectangular configuration.
The site used deep foundations.
This scope of work provides work on thegeodesic broken pile field, leader of drilling andprecast reinforced concrete piles with 400x400mm
section, 23.0m of length, 25.5m and 27.5m. Total
slaughter of precast concrete piles 1100 pieces (23mof pile length - 714 pieces, 25.5m of length -368
pieces and with 27.5m length in the amount of 18
pieces). Precast concrete piles are composed of two
742

SEE - Nagoya, Japan, Nov.12-14, 2018segments: the bottom segment with length of 16.0m
and upper segment length: 7.0m, 9.5m and 11.5m[5]-[21]. Geotechnical characteristics of soil groundon site “Prorva” [4]-[19].

Precast concrete pile with square cross section
400 x 400 mm were driving bypiling rigs: Junttan
PM25HD with hydraulic hammer HHK7/9A and
JunttanPM25 HD with hydraulic hammer HHK9A[5]-[25].
Each test pile consist of two pile sections withlength: first section – 16 m andsecond section11.5
m.Due to the fact that concrete pile is composed oftwo sections which areconnected with metal joint,
conduction integrity tests possible only for thesecond(top) section.Heads of piles were cleaned
from soil and suitable for testing. Threegraphreflectogramsfrom three blows for each pile
were accepted for further processing [2]-[24].
Fig. 1 presented procedure PIT of pilefoundations in construction site “Prorva”.
The acceleration signal is converted into
velocity and is represented on screen by the timefunction. All results are easily saved into thecomputer to be used in the processing.The time span
between the stroke and rebound is characteristic of
the location and its mechanical parameters: T =2L/C (T - stroke-return time, L – pile length, C wave propagation velocity (c=√Eρ), E – the Jung
modulus of concrete, ρ – density of concrete) [2][25].

Table 1 Engineering-geological elements

Soil type

𝝋𝝋

deg

C

Eoed

γnatural

Su

kPa

kPa

kN/m3

kPa

EGE-1
29,4 0.7
2,8
19.4
25
Fill sand(EGE-2)
29,4 0.7
2,75
19.3
15
Silt
(EGE-3)
31,5 2.7
30
19
Sand(EGE-7)24,7 20.8
2
19.1
80
Clay
(EGE-8)31,8 2.4
40
20
Sand(EGE-9)23,8 22.7
4
20.6
150
Clay
(EGE-10)
24,7
25
2
20.2
150
Clay
Eoed – Elastic unloading/reloading [kPa];
Su – undrained shear strength [kPa].
Table 1 illustrated physical and mechanicalproperties of soil ground in construction site “Prorva”[4]-[26].
METHODS OF PILE FIELD TESTS
The following documents have been referenced
for this method statement: Standard Test Method for
Low Strain Impact Integrity Testing of Deep
Foundations use ASTM D 5882, Standard Test
Methods for Deep Foundations Under Static Axial
Compressive Load use ASTM D 1143 in seasonallyfreezing soil ground [1]-[20].
Method pile integrity testing (PIT)

Fig.1 Procedure pile foundations of PITon
construction site “Prorva”.

At the construction site Seaport “Prorva” wascarried outthe integrity test (PIT) precast concrete
pile foundations from January to May 2017.
The purpose of the test is to check pile integrity.
Following works had been done:- Complex of low – strain dynamic testing of thepiles;- Proceeding and analyze results.
Integrity tests were performed by Pile Integrity
Tester (PIT) withSerial Number - SN #3557C.
Totally 161 precast concrete pile were tested at
this construction site.

The average velocity of wave distribution in theconcrete class B20÷25 – 3800m/s.
The accuracy of determining the length of thepile depends on the accuracy of the stress wave
velocity. When the pile length is known , the wave
propagation velocity can be matched to the known
length.
Pile: D2 – number of pile;
WS: 3900 м/с – velocity of wave distribution in theconcrete;
LE = 11,50 м– tested length of pile.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 2 presented graphs of PIT on construction site
“Prorva”.

− In the first cycle, the experimental pile was
loaded to 100% of the design value. Following eachapplication of an increment of load shall be held for
not less than the period or until the rate of settlement
is less than 0.25 mm/h and slowing down. The rateof settlement shall be calculated from the slope ofthe curve obtained by plotting values of settlement
versus time and drawing a smooth curve through thepoints [1]-[27].
Fig. 3 presented results graph of load-settlement
diagrams of piles k/3, b/5.
In Kazakhstan, a safety factor of SLT is 1.2.
According to SLT result of piles k/3, b/5 theload-settlement diagrams were illustrated in Fig. 3.
Bearing capacity of pile foundations k/3, b/5 is1639 kN.

RESULTS AND DISCUSSIONCONCLUSION

Results of Static Load Test (SLT)

According to the result of the SLT tests it can beconcluded.
Based on results of pile integrity testing (PIT) is
included at least 3 blows for each pile andproceeding on special program of PIT-W.
Totally 161 precast concrete pile were tested on
construction site seaport “Prorva”. All of the tested
piles do not have defects of integrity duringseasonally freezing soil ground.
Cracks and deformation in body of pilefoundation D/2 are not unascertained (Fig. 2).
According to the graphs (Fig. 3), analyze to theresults of SLT of driving concrete piles (40×40 cm
length 27.5 m) the bearing capacity of the pile b/5 is1639 kN, max settlement 16 cm.

Fig. 2Graph of velocity and length of D/2 pile.

The vertical load test shall be carry out to the
GOST 5686-94 “Soils. Field test methods by piles”
and with WBC134-3.SP.001.009 “Specification withprecast concrete piles”[1]-[25].
Static vertical loading test should be carry out
below sequences:− Pile testing begin not earlier than 6 day after
pile driving;− The vertical load creating with hydraulic jack
DG500G250 capacity 500 tons (for preliminary pile)and with hydraulic jack CLRG-2506 capacity 250
tons (Proof pile);− Load increment carried out proportional
stages (steps).
− In SCLT testing, the test load on the pile isfor hold on 2 cycles. Loading and unloading was
carried out in the following sequence: 0, 30, 60, 90,
125, 90, 60, 30, 0, 170, 210, 250, 210, 170, 125, 80,
40 and 0% of design.

Fig. 3

REFERENCES[1] Standard Test Methods for Deep Foundations
Under Static Axial Compressive Load D 1143-07,
ASTM, 2007.
[2] Standard Test Method for Low Strain Impact
Integrity Testing of Deep Foundations use
ASTM D 5882. ASTM, 2007.
[3] MSP 5/10-101-2003-Design and installation ofpile foundation, 2003, pp. 2-5.
[4] GOST 5686-94 Soils. Field test methods by piles.
M. Standard Publishing House, pp. 10-17.
[5] WBC134-3.SP.001.009 “Specification withprecast concrete piles”, Aktau.
[6] Zhussupbekov A, Omarov A., Moldazhanova A.,
Tulebekova A., Borgekova K. and Tleulenova
G., Investigations of the interaction of joint piles
with problematical soil ground in Kazakhstan.
Proc. of 7th Int. Conf. on GEOMATE, 2017, pp.
383-388.
[7] Das Braja M., Principles of Foundation
Engineering. 2nd PWS Publishing Company,
1984, pp. 360-380.
[8] Das Braja M., Soil Mechanics Laboratory

Load-settlement diagrams k/3, b/5 piles.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Manual, 2nd Ed., Department of Civil
Engineering. The University of Texas at EI Paso.
Engineering Press, pp. 41-59.
[9] Geotechnical Interpretation Report, WBCAS
134-3.TN.028.F01, Cargo Aktau, 2014.
[10] GOST 5686-94. Methods for field testing by
piles. Gersevanov Research Institute of Basesand Underground Structures (NIIOSP), Const.
Build., 1994, pp. 25-47.
[11] GOST 19912-2001. Soils. Field test methods bystatic and dynamic sounding. Gersevanov
Research Institute of Bases and Underground
Structures (NIIOSP), Const. Build., 2001, pp.
17-25.
[12] GOST 25358-2012. Soils. Field temperature
determination method, Const. Build., 2013, pp.
3-10.
[13] Karlov V.D., Soil-based and Foundations on
season freezing and swelling soil ground, Const.
Build., 2007, pp. 135-170.
[14] Nevzorov A.L., Foundations on seasonallyfrozen ground, Const. Build., 2000, pp. 30-46.
[15] Phukan Arvind, 1991, Foundations in cold
regions. Van Nostrand Reinhold, Const. Build.,
pp. 735-749.
[16] Shakhmov Zh., Influence of the freezing to soil
ground of foundation, PhD Thesis, 2013,
pp. 114-127.
[17] Shakhmov Zh., Assessment of the degree frost
heaving soil ground by different methods, Int.
Scient. Conf. of Young Scientists, 2014, pp.
4436-4443.
[18] SNiP RK 5.01-01-2002, “Soil basement andfoundations”, Const. Build., 2002, pp. 15-32.
[19] SNIP RK 5.01-03-2002.Pile foundations,
Committee for Construction of the Ministry ofIndustry and Trade of RK, 2002, pp. 25-84.
[20] Tsytovich N., Mechanics of Frozen soil ground,
Const. Build., 1973, pp. 125-148.
[21] Zhussupbekov A. Zh., Omarov A., Yergen A.,

Borgekova K. and Tleuenova G., Piling
Designing, Installation and Testing on
Problematical Soil Ground of Kazakhstan. Proc.
of the 50th Anniv. Symp. of the Southeast Asian
Geotech. Society, 2017, pp. 77-80.
[22] Zhussupbekov A., Shakhmov Zh. andTleulenova G., Geotechnical problems on
freezing ground soil and experimental
investigations in Kazakhstan. Science in cold
and arid regions. Vol. 9, Issue 3, 2017, pp. 331334[23] Zhussupbekov A., Shakhmov Zh., Lukpanov R.,
Tleulenova G. and Kudryavtsev S. Frost depth
monitoring of pavement and evaluation of frost
susceptibility at soil ground of Kazakhstan.
ICSMGE 2017-19th Int. Conf. on Soil Mech.
and Geo. Eng., 2017, pp. 1455-1458.
[24] Zhussupbekov A., Shin E. Ch., Shakhmov Zh.,
Tleulenova G., Estimation of the bearing
capacity of pile foundations in seasonallyfreezing soil ground. Proc. of the 2nd GeoInstitute-Kazakhstan Geotechnical. Society
Joint Workshop, Const. Build., 2018, pp. 6568.
[25] Shin E., Zhussupbekov A., Tleulenova G.,
Shakhmov Zh. Application of Static Load Testsof Model Piles in Seasonally Freezing Soils in
Kazakhstan. The 7th Techn. Conf. in Eastern
Asia on Geo-Natural Disasters, 2018, pp. 53-54.
[26] Zhussupbekov A., Shin E., Shakhmov Zh.,
Tleulenova G., Estimation of bearing capacityof model pile foundations in seasonally freezing
soil ground. Soil of Mechanics in Geotechnics.
Proc. of Int. Conf., 2018, pp. 83-94.
[27] Report PIT on construction site Seaport“Prorva”, 2017, pp. 2-20.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DAMAGE DETECTION OF TRUSS STRUCTURES BY APPLYINGMACHINE LEARNING ALGORITHMS

1,3

Koji Unno1, Atsushi Mikami2 and Masaki Shimizu3
Graduate Student, Tokai University, Japan; 2Professor, Tokai University

ABSTRACT
For the damage detection of truss structures, this study assumes to utilize vibration signals obtained fromsensors installed into the bridges. By preparing damaged and non-damaged bridge structures, large quantities of
response data are generated. AR (Auto Regressive) model is then applied to the time signals to extract structure’s
soundness characteristics. Here, AR coefficients are values in which damaged structural characteristics arereflected. Then, machine learning technique is applied to the AR coefficients to classify the structures into
damaged and non-damaged ones. Results showed that the machine learning method successfully detected thedamage of truss members. This kind of SHM (Structural Health Monitoring) technology is expected to contributeto early damage detection and preventive maintenance of bridges.
Keywords: Damage detection, Machine learning, AR model, Decision tree
INTRODUCTION
In Japan, infrastructures including bridges
constructed in the period of high economic growth are
getting older. Ministry of Land, Infrastructure andTransport and Tourism (MLIT) requires bridge
administrators to make short range visual observationof bridges more than once in every 5 years. Agedbridges tend to need more maintenance which
requires costs and human labors. However,maintenance engineers are insufficient in number
compared with the numbers of bridges. One solution
to resolve the problem is to use sensors and signal
processing techniques to detect damaged members
and their damage level of the structures.
Our research group is tackling the damage
detection problem of aged structures on theassumption of using sensor data.
Shimizu [1] conducted eigenvalue analysis to
fully utilize the sensor data, aiming to find optimum
sensor arrangement.
This study assumes to utilize vibration signals
obtained from sensors installed into the bridges.
Machine learning algorithm is applied to the sensor
data to detect damage. By preparing damaged andnon-damaged bridge structure models, large
quantities of response data are generated giving
random input motion at the base. AR model is thenapplied to the time signals to extract structure’s
characteristics. Here, AR coefficients are values inwhich damaged structural characteristics are reflected.
Then, the decision tree technique is applied to the AR
coefficients to classify those structures into damaged
and non-damaged ones.
This kind of SHM(Structural Health Monigoring) technology is
expected to contribute to early damage detection andpreventive maintenance of bridges [2].

Fig. 1 Hayakawa Bridge (Hakone Tozan
Railway)

1st mode 3.2065Hz.

2nd mode 10.493Hz

3rd mode 13.821Hz

4th mode 15.569Hz
Fig. 2

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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Parameters prescribing the Hayakawa Bridge truss members
Parameter
Unit

Breadth
400mm

Height
500mm

Sectional area
220000mm

Poisson’s ratio

Elastic modulus

0.3

206GPa(a) Input motion given to the bridge(b) Input motion(c) Example of Response(undamaged)(d) Example of Response(damaged)
Fig. 3 Input motion and Response
meters, constructed in 1888. The truss bridge istypical aged railway bridge in Japan. Wrought iron
was used for the material [3].

TRUSS BRIDGE TO BE ANALYZEDThe bridge structure we picked up in this study is
Hayakawa bridge administrated by Hakone Tozan
Railway Co. Ltd. shown in Fig.1. It is a double
Warren truss bridge which length is approximately 63

MODELING AND ANALYSIS
To model the structure, finite element method is
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SEE - Nagoya, Japan, Nov.12-14, 2018

used. The model was analyzed by two-dimensional
finite element method using the software, TDAPIII[4]. For the damage detection of structures, this study
assumes to utilize vibration signals obtained fromsensors installed into the bridges. By preparing
damaged and non-damaged truss bridges, large
quantities of response data are generated. Machinelearning algorithms is then applied. This study
referred MATLAB Web seminar for the applicationof machine learning algorithms [5], [6].
DYNAMIC ANALYSISSTRUCTURE

OF

THE

determined.
Fig.5 shows the AR coefficients by taking theorder of the coefficients (up to 10th mode) on thehorizontal axis. It seems that we may be able to findthe difference between damaged and non-damaged
cases by taking the AR coefficients as feature
quantities. Fig.6 shows the contributions of eachmode of AR coefficients. As the order of the modes
becomes higher, the contributions drasticallydecrease. Hence, this study focused on the only the
first and the second mode. Those determined AR
coefficients include non-significant coefficients,
hence, dimension reduction technique (PCA:
Principal Component Analysis) is utilized here.
Fig.7 represents the results of principal
component analysis (PCA) by looking at the first andthe second components. Clearly, we can divide thedata plots into two groups, therefore, the method iscapable of discriminating damaged cases from nondamaged ones. It is of importance for the efficientcomputation to conduct data compression as machinelearning tend to use enormous data. The dimensionof the data was reduced from 10 to 2 by PCA in thisstudy as shown in Fig.8. The total data is classified

TRUSS

Parameters that prescribe the Hayakawa bridge
model are shown in Table 1. Fig.2 shows 1st to 4thmode of the truss structure. 1st mode frequency is
3.2065Hz. 2nd mode frequency is 10.493Hz. 3rdmode frequency is 13.82Hz. 4th mode frequency is
15. 569Hz. Stationary random input motion is given
to the base of the prepared structures as shown in
Fig.3 (a), (b). The duration time is 60 second and timeincrement is 0.01 second, hence the input motion isconsisting of 6000 data. Acceleration responses frombottom chord member were calculated andaccumulated in the database. Both damaged and nondamaged structures were prepared, ranging thedamage level from 10% to 90% of the reduction ofelastic modulus. Examples of the responses fordamaged and non-damaged structures are shown in
Fig.3(c), (d), respectively.
AUTOREGRESSIVE MODEL
Autoregressive model (AR model) is then applied
to the accumulated signals in this study. As shown in
Eq (1), the model, depending on its own previous
values, regresses a value from the time signals. The
order of the AR model was set as 10th.
𝑋𝑋𝑋𝑋 = 𝑎𝑎0 + ∑𝑁𝑁
𝑖𝑖−1 𝑎𝑎𝑖𝑖 𝑋𝑋𝑛𝑛−𝑖𝑖 + 𝜀𝜀𝑡𝑡

Fig. 4 Example of inputs for an Autoregressive
Model

(1)

a0 is constant term. ai is parameter of model. 𝜀𝜀𝑡𝑡
is white noise. The responses include both fromdamaged and non-damaged truss structures. AR
coefficients were then calculated for both damaged
and non-damaged structures, then the coefficientswere saved for the machine learning process.

Parallel Coordinate Plot2damagedundamaged

1.5

1

FOR

THE

AR coefficients

PREPARATION OF DATAMACHINE LEARNINGAs an input wave, the portions regarded asstationary were extracted and used. As shown in
Fig.4, a total of 4000 data points out of 6000 data
points were extracted, and they are divided into 40
sections. Aforementioned AR model was thenapplied to the data that includes both damaged andnon-damaged cases. Then, AR coefficients were

0.5

0

-0.5

-1
1

2

3

4

5

6

Dimension

Fig. 5 Parallel coordinate plot
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7

8

9

10

SEE - Nagoya, Japan, Nov.12-14, 2018

into two groups: data to be studied by the machinelearning algorithms and data to test the performanceof the machine learning algorithm.

the algorithm. Based on the threshold number,calculated responses are classified into damaged andnon-damaged structures.
Table 2-4 shows results obtained by applying thedecision tree for upper chord, diagonal and bottom
chord members, respectively. Here, Table 3 is theresult corresponding to Fig.9. Fig.10 (a)-(c) shows theresults of the relation between the first and the second
principle components for upper chord, diagonal andbottom members, respectively. Blue dots stand fordamaged cases and red dots non-damaged cases. It
seems that we can distinguish the damaged structuresfrom non-damaged structures from these figures by
setting threshold values properly. The applied
decision tree method automatically determines thethreshold values.

MACHINE LEARNING
To discriminate damaged structures from nondamaged cases, machine learning algorithm isutilized. As a simple method to achieve the purpose,the decision tree method is applied to the data shownin Fig.8.
The series of analytical procedure including AR,
PCA, etc., leading to the machine learning iscommonly used procedures (e.g., [7]).
RESULTS
Detection of damage considering only damage to
one member
Shimizu [1] paid attention to the variation ofnatural frequency of the entire structure due to thedeterioration of a member. However, natural
frequencies are not always sensitive to the damage
considered [1], [8]. Hence, this study attempts toperform a different method, i.e., machine learning.
Fig.9 shows an example of result by the decision tree
method. The numbers are threshold determined by
Principal Component - Contribution Ratio
60

50

Contribution Ratio [%]

40

30

20

10

0
1

2

3

4

5

7

6

8

9

10

Principal Component

Fig. 8 An example of calculated AR coefficients

Fig. 6 Contribution rate
Distribution of features after dimensionality reduction
0.6

damagedundamaged

0.4

Second Principal Component

0.2

0

-0.2

-0.4

-0.6
-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

First Principal Component

Fig. 9 Decision Tree

Fig. 7 Dimensionality Reduction
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SEE - Nagoya, Japan, Nov.12-14, 2018

Distribution of features after dimensionality reduction
0.6

Table.3 Diagonal member

damagedundamaged

0.4

Items

Estimate_
damaged20
2Second Principal Component

0.2

damagedundamaged

0-0.2

Table.4 Bottom chord member

-0.4

Items

-0.6
-1

0

-0.5

0.5

Estimate_
damaged20
2First Principal Component

damagedundamaged(a) Upper chord member
Distribution of features after dimensionality reduction

Estimate_undamaged2
16

Principal component analysis of degree of damage
when specified on an upper chord member
Fig.11(a)-(c) show the results of principal
component analysis when degree of damage for an
upper chord member changed. Based on thesedamage, results were obtained as shown in Table 5-7.
Damage classification becomes difficult whendamage level decreases.

0.4

0.2

0

-0.2

Second Principal Component

Estimate_undamaged
2
16

-0.4

-0.6

-0.8

damaged-1

undamaged
Distribution of features after dimensionality reduction
0.3

-1.2
-1.2

-1

-0.8

-0.6

-0.4

0

-0.2

0.2

0.4

0.6

0.2

First Principal Component

0.1(b) Diagonal member0Second Principal Component-0.1

Distribution of features after dimensionality reduction
0.4
0.3
0.2
0.1

Second Principal Component

0

-0.2
-0.3
-0.4
-0.5

damaged-0.6

undamaged

-0.7

-0.1

-0.8

-0.6

-0.4

0

-0.2

0.2

0.4

0.6

First Principal Component

-0.2
-0.3
-0.4

(a) 10% damage

damagedundamaged-0.5

Distribution of features after dimensionality reduction

-0.6
-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.6

0.8

damagedFirst Principal Component

undamaged

0.4(c) Bottom chord member
Detection of
only damage

Second Principal Component

Fig. 10 Result ofconsidering
member0.2

damageto oneTable.2 Upper chord member

0

-0.2

-0.4

-0.6
-1.5

Items
damagedundamaged

Estimate_
damaged
19
0

-1

-0.5

First Principal Component

Estimate_undamaged
021(b) 50% damage

750

0

0.5

SEE - Nagoya, Japan, Nov.12-14, 2018

learning technique, decision tree method was applied
to the AR coefficients to classify the structures into
damaged and non-damaged ones. Results showedthat the decision tree method successfully detected
the damage of truss members. This method is
expected to contribute to automatically finddeterioration of a member for aged truss structureswith less costs and labors. To increase the accuracyof the damage detection is a future task.

Distribution of features after dimensionality reduction
0.6

damagedundamaged

0.4

Second Principal Component

0.2

0

-0.2

-0.4

ACKNOWLEDGMENTS
-0.6
-1.5

-1

-0.5

0

0.5

1

This study used TDAPIII developed by Ark
Information System.

First Principal Component(c) 90% damage

REFERENCES

Fig. 11 Principal component analysis of degreeof damage when specified on an upper
chord member[1] Shimizu, M., Mikami, A. and Unno, K., Damage
Detection of Truss Structures Based on Vibration
Characteristics, 4th International Conference on
Science, Engineering and Environment (SEE),
2018, (under review).
[2] MLIT, White Paper on Land Infrastructure,
Transport and Tourism in Japan, 2014.
[3] Sekino, M., Hakone Tozan Line Hayakawa
Bridge, Bridge and Foundation Engineering,Truss Bridge Feature, Kensetsutosho, Vol. 27,
No. 8, 1993, p. 167 (in Japanese).
[4] Ark Information Systems, INC., Users’ Manual,
2017 (in Japanese).
[5] MathWorks, Sensor data analysis and machinelearning - Error detection from vibration data web
seminar,2015(inJapanese),https://jp.mathworks.com/videos/sensor-dataanalysis-and-machine-learning-anomalydetection-using-vibration-data-100241.html(accessed on 2018-05-20).
[6] Figueiredo, E., Park, G., Figueiras, J., Farrar, C.
and Worden, K., Structural Health Monitoring
Algorithm Comparisons Using Standard Data
Sets, Los Alamos National Laboratory Report:
LA-14393, 2009.
[7] Goi, Y. and Kim, C-W., Damage Detection of a
Truss Bridge Utilizing a Damage Indicator from
Multivariate Autoregressive Model, Journal of
Civil Structural Health Monitoring, 7(12), 2017,
doi:10.1007/s13349-017-0222-y.
[8] Yoshioka, T., Harada, M., Yamaguchi, H. andItou, S., A Study on the Vibration Characteristics
Change of the Steel Truss Bridge by the Real
Damage of Diagonal Member, Journal of
Structural Engineering, Vol.54A, 2008, pp. 199208 (in Japanese).

Table.5 10% damage
Items
DamagedUndamaged

Estimate_
damaged16
8

Estimate_undamaged
4
12

Table.6 50% damage
Items
DamagedUndamaged

Estimate_
damaged21
0

Estimate_undamaged
019

Table.7 90% damage
Items
damagedundamaged

Estimate_
damaged24
0

Estimate_undamaged
0
16

CONCLUSIONSFor the damage detection of truss structures, thisstudy assumed to utilize vibration signals obtained
from sensors installed into the bridges. By preparing
damaged and non-damaged bridge structures, large
quantities of response data were generated. AR
model was then applied to the time signals to extract
structure's soundness characteristics. Here, AR
coefficients are values in which damaged structuralcharacteristics are reflected. Then, as a machine751

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DAMAGE DETECTION OF TRUSS STRUCTURES BASED ON
VIBRATION CHARACTERISTICS

1,3

Masaki Shimizu1, Atsushi Mikami2 and Koji Unno3
Graduate Students, Tokai University Japan, 2Professor, Tokai University

ABSTRACTThis study assumes to utilize vibration signals for the damage detection of the bridges. In the vibration-based
method, one key factor is natural frequency characteristics (natural frequency and natural vibration mode) of thestructure. Hence, representing the deterioration of the structural member by the reduction of the elastic modulus,
eigenvalue analysis is conducted to find out the basic idea that which member among many members is moresensitive to its natural frequency and natural vibration mode of the truss structures. Results show that structural
damage of upper and lower chord near the center of the structure is more influential for the first mode natural
frequency while damage to members near the vibration nodes are insensitive to natural frequencies for higher
modes. The knowledge obtained from this study is expected to contribute to the damage detection of structuresusing sensor data, i.e., to determine sensor locations.
Keywords: Damage detection, Truss bridge, Natural frequency, Vibration mode

INTRODUCTION
In Japan, infrastructures including bridges
constructed in the period of high economic growth are
getting older. Ministry of Land, Infrastructure andTransport and Tourism (MLIT) requires bridge
administrators to make short range visual observationof bridges more than once in 5 years. Although aged
bridges need maintenance, which requires costs andhuman labors, the problem of lack of engineers may
prevent aged bridges from sufficient maintenance [1].
One solution is to utilize sensors to identify thelocation and degree of damage. Referring someresearches related to vibration monitoring,
deterioration in rigidity due to damage may lead tochanges in the natural frequency of the truss. For
example, Yoshioka [2] studied how the vibration
characteristics of the steel truss bridge changed by thedamage to the member and showed that the modal
characteristics for in-plane direction was changed by
the partial damage to the diagonal member.
This study assumes to utilize vibration signals forthe damage detection of the truss bridges. In thevibration-based method, one key factor is natural
vibration characteristics (natural frequency andnatural vibration mode) of the structure. Hence,
representing the damage of the structure by the
reduction of the elastic modulus, eigenvalue analysis
is conducted to find out the idea that which member
is more sensitive to its natural frequency and natural
vibration mode of the truss structures that comprisemany members. The knowledge obtained from thisstudy is expected to contribute to the damage
detection of structures using sensor data, i.e., todetermine optimum sensor locations

Fig. 1 Hayakawa bridge side view
TRUSS BRIDGE TO BE ANALYZEDThe structure to be studied is named Hayakawa
bridge of Hakone Tozan Railway. Fig.1 is Hayakawa
bridge side view [3]. It is a double Warren truss
bridge, which is approximately 63 meters in length,
was constructed in 1888. The reason why this bridge
was picked up is that this truss structure is a typicalaged railway bridge in Japan. Wrought iron was used
for the material.
MODELING AND EIGENVALUE ANALYSISThis study paid attention to the change in thevibration characteristics when a member of the truss
structure is assumed to be damaged.
A structural analysis software TDAPIII [4] wasused in this study. Based on the Hayakawa bridge,
truss model was created by two dimensional finite

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Table 1 Parameter used for the analysis
Parameter
BreadthHeight Sectional area
Unit

500mm

500mm

Poisson’s
ratio
0.3

20000mm2

Elastic modulus

Mass density

206GPa7.8☓10-3

First mode 3.2065Hz.
Fig. 2 Finite element model of Hayakawa bridge

elements. The finite element model of Hayakawa
bridge is shown in Fig.2. The parameters used for the
analysis are shown Table 1. Truss members aretreated as 46 truss element and 24 nodes. Eigenvalue
analysis was carried out considering up to 4th
vibration mode.

Second mode 10.493Hz

RESULTS
Fundamental Vibration Characteristics
Third mode 13.821Hz
Natural vibration modes along with natural
vibration frequencies of the truss bridge are shown forfirst to fourth mode in Fig.3. In the second and thirdorder modes, nodes of vibration are seen near thecenter of the truss. In general, as higher modes are
susceptible to noise, this study focuses on the firstvibration mode.

Fourth mode 15.569Hz
Fig. 3 The first to fourth natural vibration modes

Effect of the Damage to one Member on the
Natural Frequency

Decrease rate of natural
frequency(%)

Eigenvalue analysis is performed when the elastic
modulus of a member from upper chord/ diagonal/
lower chord is assumed to be changed. The degree of
reduction of the elastic modulus is assumed to be 50%.
Upper chord
Fig.4 shows the decrease rate of the natural
frequency depending on the member location. The
vertical axis shows the ratio of reduction of natural
frequency to its natural frequency of non-damaged
structure. It seems that the central member has thebiggest effect on the decrease of the natural frequency.
Diagonal member
Fig.5 shows the decrease rate of the natural
frequency of the truss bridge. The end member has
the most significant effect on the decrease of thenatural frequency while other members have similar
minor effect. Near the center of the diagonal

4
3.5
3
2.5
2
1.5
1
0.5
0

Upper chord

0

2

4

6

8

10

Element number
Fig. 4753

Member position and decrease rate ofnatural frequency

SEE - Nagoya, Japan, Nov.12-14, 2018

members, the effect becomes almost zero, whichmeans that damage to the central member does notaffect the natural frequency.
Lower chord
Fig.6 shows the decrease rate of the natural
frequency. As similar to the upper chord case, thecentral member has the most significant effect on thenatural frequency.
From these results, the position of the truss
member that is the most influential is shown red in
Fig.7.

Fig. 7The members most influential to thenatural frequency of the structure

Analogy by Static Loading
The deformation shape of the 1st mode of the truss
structure is analogous to the static deflection whenlower chord is subjected to vertical loadings as shownin Fig.8. Hence, axial member forces are calculated
when lower chord is subjected to vertical loadings.
The obtained deformation shape is shown in Fig.9.
We can confirm that this shape is similar to the 1st
vibration mode shape.
Axial forces were shown in shown in Fig.10 for
upper and lower chord members, and Fig.11 fordiagonal members. It was found that the induced axial
forces became most severe at the members same as
those were most influential to the natural frequency
Diagonal

0.8

Decrease rate of natural
frequency(%)

Fig. 8 The deformation shape of the truss whensubjected to vertical loads

0.6

Fig.9 The deformation shape of the truss whensubjected to vertical loads

0.4
0.2
0

0

5
10
15
Element number

20

25

Fig. 5 Member position and decrease of natural
frequency

Decrease rate of natural
frequency(%)

Lower chord

Fig. 10 Induced axial forces of upper chord andlower chord members

4
3
2
1
0

0

2

4

6

8

Element number

10

12

Fig. 11 Induced axial forces of diagonal
members

Fig. 6 Member position and decrease of natural
frequency
754

SEE - Nagoya, Japan, Nov.12-14, 2018of the truss structure as shown in Fig.10 for upper andlower chord members, and Fig.11 for diagonal
members.

Lower chord
Decrease rate of natural
frequency(%)

14

Effect of Damage Degree of the Most Influential
Member on the Natural Frequency
Next, eigenvalue analysis was performed bylowering the stiffness ratios of the most influential
member (shown in red in Fig.7) by 20%, 50%, and80%. Fig.12 to Fig.14 show the results when therigidity ratio of the upper chord, diagonal member,lower chord has changed, respectively. The decrease
rate of the natural frequency is gradually increased by

12
10
8
6
4
2
0

0%

20%

40%

60%

80%

Decrease rate of raterigidity ratefrequency(%)

Decrease rate of natural

Upper chord
14

Fig. 1412108decreasing rigidity of the member. They seem to be
drastically changed at around 50% reduction oforiginal rigidity.

6
4
2
0

Changes in Natural Frequencies Accompanying
the Rigidity Ratio for Higher Modes
0%

20%

40%

60%

Decrease rate of rigidity rate80%

Up to here, we consider only the fundamental
vibration mode. However, the sensors installed on
the bridge would observe signals that consist ofvibration modes including higher modes. Hence, theeffect of higher modes is investigated next.

Fig. 12 Decrease rate of the natural frequency
when the stiffness ratio of the upper
chord material in Fig.7 is reduced by
0% to 80%Upper chord member
Figs.15 to 17 shows the rate of change in natural
frequency for the second mode to the 4th mode when
the rigidity ratio of one of the members from upper
chord is reduced to 50%. Looking at the second mode,the member 4 has almost zero effect while themember 8 is the most influential. Regarding 3rdmode, members 7 and 8 seems to have the most little
influence. 4th mode shows very complicated modeshape.
From the observations of the second and thirdmode, it seems that when the damaged members
locate on the vibration node of each mode, decrease
rates of the natural frequencies are insensitive to thedamage. Hence, sensors should not install adjacent to
the nodes if the system depends on higher mode
information.

Decrease rate of natural
frequency(%)

Diagonal
3
2.5
2
1.5
1
0.5
0

Decrease rate of the natural frequency
when the stiffness ratio by the upper
chord material in Fig.7 is reduced by 0%
to 80%

0%

20%

40%

60%

80%

Decrease rate of rigidity rate

Diagonal member
Figs.18 to 20 are rate of change from the second
mode to the 4th mode. Different from the upper chordmember, relation between locations of node and thedamaged member is not clear.

Fig. 13 Decrease rate of the natural frequency
when the stiffness ratio by the upper
chord material in Fig.7 is reduced by 0%
to 80%

755

SEE - Nagoya, Japan, Nov.12-14, 2018

Decrease rate of natural
frequency(%)

Second mode

Lower chord member
Figs.21 to 23 are rate of change of natural
frequency for the second mode to the fourth mode.
Looking at the second mode, if the location of thedamaged member is close to the vibration node (i.e.
member 7), natural frequency is insensitive to thedamage. For the third mode, when member 4 or 5 isthe damaged member, natural frequency is also
insensitive to the damage. However, the location of
the member is different from the position of vibration
node.

3.5
3
2.5
2
1.5
1
0.5
0

0

2

4

6

8

10

Element number

Third mode

6

Decrease rate of natural
frequency(%)

Decrease rate of natural
frequency(%)

Upper chord member position anddecrease of natural frequency

5

1
0.5
0

5
10
15
Element number

20

25

Fig. 18 Diagonal member position and decrease
rate of natural frequency

3
2
1
0

0

2

4

6

Element number

8

10

Fig. 16 Upper chord member position anddecrease of natural frequency

1.4

Third mode

3
2
1
0

Fourth mode

0

1.2
1
0.8
0.6
0.4
0.2
0

5

10

15

Element number

20

25

Fig. 19 Diagonal member position and decrease
rate of natural frequency

Decrease rate of natural
frequency(%)

Decrease rate of natural
frequency(%)

04Decrease rate of natural
frequency(%)

Fig. 15

Second mode

1.5

0

2

4

6

8

10

Elemnt number
Fig. 17 Upper chord member position anddecrease of natural frequency

Fourth mode

4
3
2
1
0

0

5

10
15
20
Element number

25

Fig. 20 Diagonal member position and decrease
rate of natural frequency

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SEE - Nagoya, Japan, Nov.12-14, 2018

Second mode

Dcrease of natural
frequency(%)

8

CONCLUSIONSFor the damage detection of aged truss structure
based on their vibration characteristics, this study
conducted eigenvalue analysis, assuming to utilize
sensor data (vibration signals). Deterioration of thestructural member was represented by the reductionof its elastic modulus. Results show that structural
damage of upper and lower chord near the center ofthe structure are the most influential members forthe first mode natural frequency while damage tomembers near the vibration nodes is insensitive tonatural frequencies for higher modes. These results
indicates that the effect of damage to a truss member
on the natural frequencies depends on vibration
modes. Hence, consideration of sensor locations
according to the focusing vibration mode may lead tobetter detection of damage to the truss member that issensitive to the corresponding vibration mode. In thisway, the knowledge obtained from this study is
expected to contribute to the damage detection of
structures using sensor data.

7
6
5
4
3
2
1
0

0

2

4

6

8

10

12

Elemnt number
Fig. 21 Lower chord member position anddecrease rate of natural frequency
Third mode
Dcrease of natural
frequency(%)

3.5
3
2.5

ACKNOWLEDGMENTS

2This study used the software developed
TDAPIII by Ark Information System.

1.5
1

REFERENCES

0.5
0

0

2

4

6

8

Element number

10[1] Ministry of Land, Infrastructure and Transport
and Tourism, Current situation of bridge aging,issues of measures against aging of bridges (inJapanese).
http://www.mlit.go.jp/road/sisaku/yobohozen/to
rikumi.pdf.
[2] Yoshioka, T., Harada, M., Yamaguchi, H. andItou, S., A Study on the Vibration Characteristics
Change of the Steel Truss Bridge by the Real
Damage of Diagonal Member, Journal of
Structural Engineering, Vol.54A, 2008, pp. 199208 (in Japanese).
[3] Sekino, M., Hakone Tozan line Hayakawa bridge,
Bridge and Foundation Engineering, Trussbridge feature, Kensetsutosyo, Vol. 27, No. 8,
1993, p. 167 (in Japanese).
[4] Ark Information System, TDAP III Manual,
2017 (in Japanese).

12Fig. 22 Lower chord member position anddecrease rate of natural frequency
Fourth mode
Dcrease of natural
frequency(%)

1.2
1
0.8
0.6
0.4
0.2
0

Fig. 23

0

2

4

6

Elemnt number

8

10

12

Lower chord member position anddecrease rate of natural frequency757

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

AN AGENT-BASED SUPPLY CHAIN NETWORK WITH QUALITY
AGENT MEDIATORS FOR QUALITY COORDINATION
C.Y. LAM
Graduate School of Engineering, Hiroshima University, Japan
ABSTRACT
A good quality coordination framework is necessary for a supply chain network if it is to achieve a competitive
advantage in terms of customer satisfaction. It can also help to ensure quality and prevent devastating quality
problems with the products or services that are delivered by the supply chain network. In this paper, an agentbased modeling approach is proposed for the development of a supply chain network, in which quality agents areused as mediators who monitor and control the input and output quality information that is generated from entities.
Hence, appropriate and suitable corrective actions can then be carried out to adjust any deviations in quality.
Agents need to address problems of autonomy and complexity that cause changes and disruptions with theirintelligence, so under the proposed agent-based modeling approach, a supply chain network with higher visibility
and better quality coordination can be constructed for the entities, and high quality can be assured in the supply
chain network. An agent-based modeling approach with three types of quality agents as mediators for the supply
chain network is proposed here.
Keywords: Agent Modeling, Multi-agent system, Quality coordination, Supply chain management, Supply Chain
Network
have increasingly turned to the frameworks that arederived from agent-based systems [21]-[26].
The Agent-based system is a distinctive modelingtechnique that emerged from a number of researchdisciplines including artificial intelligence, systemdesign and analysis using object-oriented
methodology and human interfaces [21], [27]-[32].
Throughout these research disciplines, the agentbased system has been defined as a usefulcomputational model for studying the coordination
issues arising from the interaction of the individual
behaviors of a collection of entities. The agents workthrough autonomous rule based reasoning in responseto their internal and external environment, they alsoorganize themselves to provide solutions bydetermining the structures, heterogeneity andhierarchy of the problems or environments in which
they are participating. Therefore, an agent-based
system represents and models agents as reasoning
autonomously, interacting with other agents, adapting
to environmental changes. They also pursue
advantages in a rational manner [33][34]. Moreover,agents autonomously operate without the directintervention of other humans. In full control of theiractions and objectives, agents possess problemsolving capabilities; they send and receive messages
concerning their current situations to agents in otherrelated or in the same-environment, and display“evolutionary” behaviors in response to changes [21][25] [27] [28] [32] [34].
In the research into supply chain networks, theframework of agent-based systems ranges in size and

INTRODUCTION
Supply chain management is the necessary
cornerstone of competitive strategy, increased market
share, and shareholder value, for most organizations.
Many organizations have directed significant
attention toward working more closely with supply
chain partners, including not only customers but also
various types of logistics entities in the supply chain
network, such as manufacturers, distributors, andretailers. The development of more meaningful“relationships” through the supply chain network canachieve better coordination and integration among theparticipating entities, so the value of the delivered
products or services from the supply chain network
can be maintained or increased [1]-[5].
According to the literature, many researchers havestudied the dynamic network relationship of the
supply chain network, and have characterized thecontemporary business situations and the internalfunctional structure of the supply chain network [6][10]. The importance of network relationships for thevalue of the delivered products or services can also befound in the literature [11]-[16].
In modeling the network relationships in the
supply chain network, most research papers solely
represent the supply chain network as a process flow
so as to capture the paths and tasks directly. However,a supply chain network is a complex adaptive system[17]-[20] that involves a certain degree of autonomy
among the entities that take part in it. Therefore, in m
odeling the supply chain network, researchers

758

SEE - Nagoya, Japan, Nov.12-14, 2018

complexity from simple diagrams of decision making
to complex entities’ behaviors and interactions. An
agent-based system captures the interaction of
independent and distributed entities as well as their
behaviors. Most researchers use the agent-based
system framework to represent the interactive
processes within supply chain networks, and someresearchers have extended the agent-based systemframework to address coordination problems at theenterprise level of supply chains. Moreover, someresearchers coordinate the behavior of the business
functions with agents’ decision making policy andprocesses [32]. These researchers develop agentbased systems for utilizing information into complex
architectures supporting multi-objective decision
making, rationalizing system design, and for reducing
uncertainty. All this research shows that theautonomy of the agent-based system is potentiallyvaluable in helping, realistically to capture andsimulate the dynamics of the complexity inherent in
the supply chain network.
Despite the recent growth of research interest in
using agent-based systems for modeling the supply
chain network, it is clear that research has yet been
unable to fully exploit the potential of the agent-based
system. This may due to the difficulties of fitting theagent-based system to practical disciplines, and many
practitioners have turned to modeling only for single
entity applications. In addition, there is relatively
little direct research that addresses the usage of agentbased modeling for quality coordination in the supply
chain network, and there is also relatively little
research that stresses the importance of mediating
agents in assisting supply chain coordination
activities.
In this paper, an agent-based modeling approachis proposed for the development of a supply chain
network, in which mediating agents are proposed andused as mediators to monitor and control the qualityof information from entities, and appropriate andsuitable actions will then be carried out to adjust thequality deviation, so a higher visibility and better
quality coordination can be achieved from the supply
chain network.

retailers, etc., and the quality information can beconsidered as the quality performance of the products
or services. This information is essential for a supply
chain network to produce and maintain high quality
products or services for customers.
Structure of Quality Agents in the Supply Chain
Network ENVironment (SCN-ENV)
A supply chain network is a network thatcomposes a parallel flow of products, materials,
services, and information from the suppliers throughvarious intermediate entities to the customers, where
all the entities are interrelated and connected together
for the efficient and effective flow of information
concerning the quality of the products or services in
the network. In the proposed agent-based modelingapproach, the quality agents respond and react to all
the series or parallel events performed by the entities
within the supply chain network, and these events canbe denoted as a set of events E, i.e.
(1)E  e0 , e1 , e2 ,, e where e is the element of events E, and the eventsin the supply chain network can be distributed orcontinuous. For each recorded event in the supply
chain network, there should be a related distinctive
action responding to the event. These actions can bedenoted as a set of actions ACT, i.e.
(2)
ACT   0 , 1 ,  2 ,,  
where α is the element of the actions ACT, andthe number of actions ACT are limited to the numberof events E in the supply chain network, i.e.
ACT  E . Each α in the set of actions α carries aseries of items of quality information from theprevious event as an input action for the next event;meanwhile each α in the set of actions ACT also
carries a series of items of quality information after
each event is completed, as an output action. Since
agents are used to monitor and control the actions inthe supply chain, the actions α are then adaptive tothe changes that occur in the events e.
In the proposed agent-based modeling approach,the supply chain network starts from an event e0 of anentity. Next, the quality agent will decide on a set ofactions α for the event e1 that leads to the next eventof the supply chain network. Quality agents will
decide on many appropriate actions for an event, but
only one suitable action will be executed. This willlead to the start of the next event. The agent willcontinually decide the appropriate actions for each
event in the supply chain network until the last eventis reached.
The quality agents all possess quality informationof different kinds. They will process this quality
information to decide on what action is appropriate
for the next event in the supply chain network. Due to

AGENT-BASED MODELIG IN A SUPPLYCHINA NETWORKAgents need to address problems of autonomy andcomplexity that cause changes and disrupt theirintelligence. Using the proposed agent-basedmodeling approach, a supply chain network withhigher visibility and better quality coordination canbe constructed among the entities. The major featureof the proposed modeling approach is the use ofquality agents as mediators to monitor and control the
input and output quality information from entities.
The quality information including the informationfrom the entities of manufacturers, distributers,

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SEE - Nagoya, Japan, Nov.12-14, 2018

autonomy and complexity that lead to changes anddisruptions with their intelligence, an agent
coefficient for the quality agent action is then also
added to each action to represent the agent action thatdeviates from the normal action, as well as the routing
adjustment. The set of agent-heuristic routings canfurther be illustrated as:(5)
R AG  r0AG , r1AG , r2AG ,, rAG

Fig. 1. The relationships and framework between thethree types of intelligence quality agents.
the dynamic variables in the supply chain network,
the amount of quality information input for an event
may be different from the output quality informationfrom previous events. The agent is responsible formonitoring and controlling these variations.
If the output quality information from an event isbetter than its input quality information, it means theperformance of this particular event was good, andquality problems may not exist in this particular event.
With this good quality information, the quality agent
will then decide on what action is appropriate for the
next event. In this way quality can be maintained
within the supply chain network.
On the other hand, if the initial input quality
information to an event is better than the output
information from it, it means quality problems may
exist in this particular event, and investigation or
corrective actions will be initiated by the quality
agent on this particular event or the quality agent will
decide what action is appropriate for the next event
so as to maintain the quality in the supply chain
network. Variation between the input and output
quality information can be determined by thefollowing algorithm:
 xi ei (3)Qei 1     Qei  yi ei 
where Q(ei+1) is the status of the quality
information for the event ei+1, Q(ei) is the status of thequality information of event prior to it ei. ∑ 𝑥 (𝑒 ) and∑ 𝑦 (𝑒 ) are the input and output quality informationof the event ei respectively. τ is an agent coefficientthat represents the investigation or corrective actionsof a quality agent in order to maintain the status of thequality information of an event.
For a supply chain network to be completed, a setof event-action routings R is involved. The set ofroutings R for the quality agent in the supply chain
network is induced by the interchanging sequence ofthe events and the executed actions, and a generalrouting can be illustrated as:
0

1

2

  1

r: e0  e1  e2    ewhere R0

AG

is the agent-heuristic routing, and
1

 2

 1r : e0  e1  e2    e . With the set ofAG

events E, action ACT, agent-heuristic routing RAG
and agent coefficient τ, the Supply Chain Network
ENVironment SCN-ENV for the agent can then be
defined as:
SCN-ENV = <E, ACT, RAG : 𝜏>
(6)
Therefore the quality agents that are involved in
the supply chain network environment SCN-ENV,
inherit the SCN-ENV properties but can make theirown action decisions.
Types of Quality Agents in the Supply Chain
NetworkIn the proposed agent-based modeling approachin the supply chain, three types of intelligence quality
agents are proposed, i.e. detection agent, decisionagent, and action agent. All these agents are subject
to the properties of the supply chain network
environment, i.e.
AGENT def <DETECTION_AGENT, DECISIONAGENT, ACTION AGENT>
s.t. SCN-ENV = <E, ACT, RAG : 𝜏>
(7)
The detection agent is the intelligence agent thatis responsible for the capturing and recording of thestatus of all the quality information within the supply
chain network. Therefore, to obtain the quality
information Q(ei) from an event ei, the detection agent
will capture and record the status of it as a set of
quality information in the supply chain network
environment SCN-ENV, i.e.
Qei   DETECTION _ AGENT : Qei  q0 , q1 , q2 ,, q 

(4)

(8)

After the quality information is captured andrecorded, the quality information will be processed by
the decision agent. The decision agent possess acertain level of skill and is knowledgeable about how
to process the designated quality information and has
considerable skill in handling scientific algorithms

where r is the element of routings R, i.e. R ={𝑟 , 𝑟 , 𝑟 , ⋯ , 𝑟 }, and R can be considered as all thepossible routings for each event and the appropriate
actions based on reliable quality information.
Since agents have to address problems of760

SEE - Nagoya, Japan, Nov.12-14, 2018mechanism is to modify deviation in the promissory
quality information. The forecasting-based learning
approach simulates the agents’ action and behavioral
patterns regarding unforeseen perturbations andchanges in the quality information from the events ofthe entities. By revealing these unpredictablebehaviors, the quality agents are then able to generate
appropriate agents’ action to correct any deviation in
the quality information.

and computations so as to determine any changes
needed in the quality information, i.e.

DETECTION_ AGENT : Qei   q0 , q1 , q 2 , , q 

(9)
 DECISION _ AGENT : Q * ei 
where Q*(ei) is the designated quality information
with 3 situations, i.e. Q*(ei) = 1: the output quality
information is better than the input quality
information; Q*(ei) =0: the output quality
information is the same as the input quality
information; and Q*(ei) = -1: the output quality
information is worse than the input quality
information
If changes occur in the quality information andhave been detected by the decision agent, a set of
appropriate actions will then be generated by theaction agent. Action agents are adaptable and cangenerate and store the appropriate actions for every
events, and will select one suitable action for the
event to execute, i.e.

Communication between AgentsIn the proposed agent-based modeling approach,agents communicate and interact to maximize
internal utility functions and maintain stability in the
supply chain network environment SCN-ENV. There
are two main kinds of communication information
between the agents, i.e. information about quality andinformation about action. Fig. 2 illustrates thecommunication cycle of a quality agent for an eventin the supply chain network.

DECISION _ AGENT : Q * ei   1; 0; 1  ACTION _AGENT : ACT

AG



 

AG
0

,

AG
1

,  2AG ,  ,  AG



(10)

AG

where ACT is the set of appropriate actions foran event, but only one suitable action 𝛼
will beexecuted by the action agent for the next event, i.e.
*
(11)
ACTION _ AGENT : ACT AG   iAG
 Qei 1 
1where 𝛼 is the most suitable action for the next
event, in which appropriate corrective action iscarried out to maintain the quality of the information
Q(ei+1) for the next event in the supply chain network.
The relationships and framework between the three
types of intelligence quality agents in the supply
chain network are illustrated in Fig. 1.

Fig. 2. The communication cycle of the quality agent
for an event in the supply chain network.
In agent communication, there are two rule-based
communication
methodsfortransmitting
communication signals, i.e. through publicbroadcasting or one-to-one communication. In
communication through public broadcasting, allagents in the supply chain network environment SCNENV can receive communication signals despite theposition of the event or of the entity in the supply
chain network, and then the target agents can respondto the signals. In one-to-one communication, thecommunication signal is sent to the target agents only.

Agent Adaptation and Learning in a Supply Chain
Network
Two adaptation and learning memory
mechanisms are adopted by the quality agents toenhance the monitoring and controlling of the quality
information so as to determine the appropriate actions
for the events. The two memory mechanisms are“explicit memory” and “implicit memory”. “Explicit
memory” allows the quality agent to learn from
historical agents’ actions so they can react quickly
and similarly to any significant changes in the quality
information, while “implicit memory” allows thequality agents to propagate the agents’ action in
response to changes of the quality information.
The “explicit memory” mechanism is based on the
distributed case-based learning approach that wasdeveloped from the former agents’ action andbehavioral patterns on quality information, and isstored in its knowledge base. Such knowledge is thenreused for future cases which possess similar quality
information. This knowledge is retrieved through an
extended case-based reasoning mechanism.
The main purpose of the “implicit memory”

A SIMULATION STUDY
For illustrating the proposed agent-basedmodeling approach in the SCN-ENV with agents’action and flow of quality information, a simulation
study on a supply chain network is conducted. The
simulation involves 3 manufacturers, 4 distributors,
and 7 retailers that are targeting 10 markets.
Since there are 3 manufacturers M = {1, 2, 3}, 4
distributors D = {1, 2, 3, 4}, 7 retailers R = {1, 2, …,
7}, and 10 markets M = {1, 2, …, 10}, there are totally
840 possible agent-heuristic routings with a minimumof 2520 agents, coefficient and corrective action foreach product. In this simulation, the data for the
optimization of the SCN-ENV are quantified by the761

SEE - Nagoya, Japan, Nov.12-14, 2018synthetic analytical methods so as the quantified data
can be used as the quality performance data. The
product demand, the quantified quality standard foreach entity, and the quantified quality informationfrom entity to entity are predefined in the agent
environment. For the quantified quality standard,
there are upper and lower limits for the data so thatflexibility can be induced for the agent coefficient 𝜏,
so for any deviation that occurs between the quality
information and quality standard, quality agents will
carry out the corrective action 𝛼 . The agent
coefficient 𝜏 and the corrective actions 𝛼 are agentheuristics that are determined by the quality agents inthe simulation. For this repeated monitoring andcontrolling of the quality information and the agents’actions, the optimizations of the proposed agentbased modeling approach in the SCN-ENV, withmaximum quality information in terms of the best
agent-heuristic routings with corrective actions, canbe simulated. The best agent-heuristic routings with(𝑒 ),case-based and forecasting-based set of 𝜏𝛼𝜏𝛼 (𝑒 ) , and 𝜏𝛼 (𝑒 ) are thus defined as𝑀  𝐷  𝑅  𝑁 , 𝑀  𝐷  𝑅  𝑁 , …,𝑀 𝐷  𝑅 𝑁 . The quality information andperformance within the supply chain network
environment SCN-ENV can also be maximized:
𝑄 ∗ = 490, 𝑄 ∗ = 114, and 𝑄 ∗ = 124). In addition,using the agent-based modeling approach, quality
agents can also identify the worst quality routings aswell as the entities with relatively poor quality
performance, i.e. the entities of Manufacturer M2,
Distributor D3, and Retailers R3, R6, R7 in the casestudy, therefore, the quality agents do not organize
any agent-heuristic routing through these entities, anddirect the agent-heuristic routings to other entities
within their ability. Therefore, by maximizing thequality information in the supply chain network
environment SCN-ENV with agents’ action, theentities can closely interact with each others andachieve higher visibility and better quality
coordination.

entities can closely interact with each other andachieve higher visibility and better quality
coordination; therefore, a higher customer
satisfaction can be achieved in the supply chain
network.
The modeling approach proposed in this paper canbe further improved in several ways. In the SCNENV, sub-agents can be used to assist with quality
coordination within the events of the entities so as toenhance the autonomy and adaptively of the supply
chain network. Moreover, for the quality agent, thedefinition of quality information can further be
elaborated and equipped with other elements, such as
the cost of taking corrective actions. To further
elaborate these elements, the agent-based modelingapproach can balance the objectives between thequality information and the operational cost of the
supply chain network. Therefore, if any quality
problem arises in the supply chain network, thecorrective action taken by the quality agents canmaximize the quality performance as well as
minimize the cost of the whole operation. In turn,customers can be satisfied by the quality of thedelivered products or services, the profit from the
supply chain network can be maintained and the loss
from taking corrective action can be controlled.
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[8] Surana, A., Kumara, S., Greaves, M. andRaghavan, U. N., Supply-chain networks: A

CONCLUSION
In this paper, an agent-based modeling approachis proposed for the development of a supply chain
network, in which quality agents are proposed as
mediators to monitor and control the input and output
quality information that is generated by the entities.
The major feature of this approach is that the model
adopts the features of agent for quality coordination.
Thus the proposed quality agents can autonomously
and adaptively act as mediators to generate
appropriate and suitable corrective actions foradjusting any deviation in quality. In this way quality
performance can be assured in the supply chain
network. Moreover, in optimizing the agent-basedmodeling approach, and by maximizing the quality
information in SCN-ENV with agents’ action, the762

SEE - Nagoya, Japan, Nov.12-14, 2018

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to distributed artificial intelligence, Harlow:
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763

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DESIGN, ANALYSIS, FABRICATION AND ANALYSIS OF SMALL WATERTURBINE
Gwo-Chung Tsai
Department of Mechanical and Electro-Mechanical Engineering National
Ilan University, I-Lan, Taiwan

ABSTRACTThis study designed different blades to make the small-impact water turbines. ANSYS / Fluent hydrodynamic
software is used to calculate the torque and power for different blade shapes. From which to find the mosteffective of blade shape, and in accordance with its blade design, the use of anti-corrosion glass fiber and resin
is to manufacture the composite blades. The amount of electricity produced by the turbine made ofanti-corrosion composite blades is compared with another group of unexplored wood blade turbines. As a result,
the turbine blades made of anti-corrosion composite blades can get a large amount of power.
Keywords: Turbine, ANSYS / Fluent, Anti-corrosion composite blade, Torque

INTRODUCTION
In recent years hydropower is quite popular green
energy [1]. Small hydroelectric power system its
advantages include the construction of small areas
can be integrated into the natural environment andpower generation area restrictions less ... and so on,
but to develop small hydropower system to consider
the main points include 1. In response to different
head height, 2 different water flow options, 3. Initialinvestment and follow-up maintenance should not be
too high. To sum up the conditions for the study is
the water turbine design should pay attention to the
problem [2 ~ 3]. From the literature [4 ~ 5] pointed
out that the impact of water turbine blades are
particularly suitable for high head low flow
conditions. Nakanishi [6] also carried out the impact
of water turbine blade simulation analysis andexperimental data were compared, the results showthat the values are similar between the two.
Therefore, it is proved that the simulation analysis
can effectively predict the various types of impact
water turbine blades. So this study carried out the
impact of the design of the form of water turbine
blades, and then designed to complete the water
turbine blades. And then use computational fluid
dynamics (CFD) for analysis and simulation to
obtain the optimum water turbine blades.
In order to increase the turbine power generation
efficiency, this paper uses ANSYS / Fluent analysis
to find the same boundary conditions, the maximum
power blade. In accordance with its blade design, theuse of glass fiber and resin is to produce theanti-corrosion composite blades. The

amount of electricity produced by the turbine madeof anti-corrosion composite blades is compared withanother group of unexplored wood blade turbines.

RESEARCH METHODOLOGYTHEORETICAL BACKGROUND
Turbine theory based on computational fluid
dynamics theory that is a calculation method for
ANSYS / Fluent software. In the case of finite
volume analysis, the flow field is divided into manyfine grids, using the momentum equation under the
microscopic condition, the mass conservation and themass conservation equation, and the fluid flow andthe heat transfer coefficient are integrated to performthe numerical analysis. That is, using a finite grid to
calculate the algebraic equations between field
variables to solve the approximation between theequations of the variables [7,8]. Fluent has been usedin all aspects of the application [9-11]. Many papers
had proposed the small scale hydropower
works[12-13]. The relevant hydrodynamic formula isas follows: (microscopic Renault transmission
equation):

Mass conservation equation::grad=

764

+

+

(1)

， :density

SEE - Nagoya, Japan, Nov.12-14, 2018

t:time:velocity
Fig. 1. Water velocity distribution

Momentum equation: Newtonian Fluid:
Navier-Stokes Equations:X-direction:(2)
Y-direction:(3)
Z-direction:

Fig. 2. Pressure distribution on blade
BLADE DESIGN(4)
ρ:density, t:time,, u:velocity

component in x-direction, v=velocity component in
y-direction, w=velocity component in z-direction,

μ:Viscosity coefficient.
ANALYTICAL PROCEDURES
After confirming that the tank size is 550 mm * 550
m * 200 mm, with its size reference, the drawing
software is used to plot the blades and water tank,and then ANSYS / Fluent is performed to do analysis
to find the maximum power turbine for production.
The flow field and rotor were represented by manysmall grid, the flow field and rotor material isassigned to be the mixture to perform a steady-state
analysis. The viscosity coefficient is realizable, andthe inlet flow rate for the pumping motor
specifications is 0.645kg / s, rotor speed is set tobe130rpm.Velocity distribution is shown in Figure 1,
the pressure distribution is shown in Figure 2. And
torque can be found to calculate the output power.

Figure 3 is the geometry of seven kinds of blades.
Table 1 is the calculated torque and power for theseblades. From the analysis results we can see that theblade design 7 pressure distribution is moreconcentrated. The pressure is also larger, as shown in
Figure 4a-b, and the larger the number and the size ofthe blade that can produce more power. The blade
design 7 uses the nozzle design 1 to produce
maximum power in these blade designs. Blade designreference Bellton type is a turbine blade similar tothe spoon-style blade that can absorb the impact ofwater. Drainage design in the blade will successfully
remove the impact of water that will not be retainedin the blades.
Manufacture of anti-corrosion composite blades
The reason why the glass fiber composite is selected
to make the blades that with high strength, lightweight, corrosion resistance and wear resistance andother characteristics. Their tensile strength of thestandard state is 6.3 ~ 6.9 g / d. Its tensile strength isstrong, and has the large elongation within the elastic
limit of the material. So It has the capability toabsorb the large impact energy, and has good water
resistance, it is very suitable for the
Table 1 the calculated torque and power
Blade number

Torque(Nm)Power(W)

Blade 1

1.02

13.9

Blade 2

1.69

22.97

Blade 3

2.22

30.22

Blade 48.39

114.19765

SEE - Nagoya, Japan, Nov.12-14, 2018

Blade 5

10.98

149.53

Blade 6

8.68

118.11

Blade 723.03

313.55

uses a glass fiber cut blanket, shown in Figure 5, 12
μm monofilament fiber diameter yarn stocks, evenly
distributed in the plane but no direction.
Monofilament diameter is thick, the product surface
will be rough, but there has better hardness.

Fig. 5. Glass fiber cutting blanket

Fig. 3 The geometry of seven kinds of bladesFig. 6a The upper moldFig. 6b The upper moldFig. 4a. Pressure distribution for blade design 1

In order to understand the impact of production
methods, two ways are used to make blades: closed
mold making blades and open mold making blades.
The use of 3D printing machine and the material is:
Pla Plate 3.0mm. Print out of the upper mold and thelower mold are shown in Figure. 6a-b.
CLOSED MOLD MAKING BLADES

Fig. 4b. Pressure distribution for blade design 7
production of impact turbine blades [3]. This study

The resin is mixed with the hardener in proportion.
Cut kraft paper, the size can be spread throughout themold. Use double-sided adhesive, paste the kraft
paper bag to the mold to help demoulding. Kraft
paper bag coated with wax oil or release agent, andthen put the glass fiber. At the same time a layer ofresin is painted once shown in Figure 7, a total ofthree layers of glass fiber is put. After the resin is
painted, cover the upper mold and the lock frame isused to fix the upper and lower molds. Then itis put
into the oven that heated to 100 Co and time for 55
minutes as shown in Figure 8. After the work piece is766

SEE - Nagoya, Japan, Nov.12-14, 2018

hardened, it will get the glass/epoxy blade after
demold and trim as shown in Figure 9-10.
OPEN MOLD MAKING BLADES

heating temperature of 60 ℃, time is 40 minutes,
wait two hours after cooling, then put it in room
temperature over one night and demolition the nextday.

Using the original lower mold to make open mold,add the bevels at the grooves of the two tripods, as
shown in Figure 11 that will be easily open the
demolding. The same method uses 3D printing
machine to print out the mold, as shown in Figure 12.
The production process is roughly the same as that of
the closed mold. After several tests andimprovements, the following best production
methods are obtained: The resin is mixed with thehardener in a ratio of 2: 1 to produce a group of
blades using about half can of the resin. In order toprevent the kraft paper rupture, leading to resin into
the mold surface, we put two layers of kraft paper on
the mold, and two layers of kraft paper withaluminum foil stickers together. The release agent
was changed to be butter. The shape of the glass fiber
can be cut into blades. Painted with resin, covered
with glass fiber, waiting for resin impregnated glass
fiber, and then painted with a layer of resin, a total of
3 layers of glass fiber are put. The mold put in the
furnace and set the heating temperature of 60 ℃,
time is 40 minutes, wait two hours after cooling, thenput it in room temperature over one night, anddemolition the next day.

Fig. 9 Demold

Fig.10 Glass/epoxy blade

Fig.7. Painting the resin
Fig. 11 Oblique angle diagram

Fig.8 The mold after heating
The shape of the glass fiber can be cut into blades.
Painted with resin, covered with glass fiber, waiting
for resin impregnated glass fiber, and then painted
with a layer of resin, a total of 3 layers of glass fiber
are put. The mold put in the furnace and set theFig. 12 Open mold for blade
Repeat to make the eight blades and use the sameprocess to make circular axles, and drill the axle, theuse of screw nut to lock the blade, that is, complete
767

SEE - Nagoya, Japan, Nov.12-14, 2018

the turbine blades shown in Figure 13.
THE OVERALL STRUCTURE OF THE
TURBINE AND EXPERIMENTAL TESTThe turbine will be locked into the tank, the output of
the axle will be accelerated with the speed increaserthat speed ratio of 1: 2 as shown in Figure 14. Using
the shrinkage jet to speed up the output water, water
pipe diameter is 25mm and nozzle diameter will
reduce to 15mm as shown in Figure 15. The overall
structure of the turbine after the overall combinationis shown in Figure 16. The generator is in series witha 3w bulb, and connect the mulimeters. The use ofpumping motor and long pipeline flushes the waterfrom ground, 2,3,4 floor into the water turbine torotate the turbine that makes the generator to
generate electricity. Record voltage and current arerecorded, and the tachometer is also used to measure
the rotaing speed that will be used in the hydrulic
analysis to calculate the output powe.

Fig. 16 The overall structure of the turbine

RESULTSDISCUSSIONSThe power produced from the turbine with theanti-corrosion composite blade and compared withthat fromthe turbine with the undesigned wood blade
shown in Figure 17. It is shown in Figure 18 that thedesigned blades have a higher power generationcompared to the wood blades. On the structure, we
use the speed increaser to make the generator to havea larger speed and output more torque to drive thegenerator.

Fig. 13 Turbine blade after assembly

Fig. 14 speed increaser

Fig. 17 Power get from two bladesFig. 18 Comparison between analysis results andtests

Fig. 15 water nozzle

768

SEE - Nagoya, Japan, Nov.12-14, 2018

It can be seen from Figure 18 that the higher the floor,
the lower the power generation efficiency. It is also
found that the test results are lower than that of thetheoretical data. Possible causes of this phenomenon
are the following: First, the phenomenon of water
pipe contraction, when the water washed down
through the hose under the floor, the high-speed flowof liquid low pressure caused by water pipe
contraction, so that the flow rate decreased, so thehigher flow the impact. The hose is soft, the next test
may change the material of hose. The second, thetheoretical power calculation using gravity equation
to calculate the flow rate, ignoring the waterviscosity and pipeline friction, coupled with theliquid as a continuum, the gravity equation to
calculate the flow rate will produce errors. Third, theblade surface is not smooth and may cause theturbulent in the water tank that will affect the overallturbine speed. Fourth, the blade weight is not evenresulting in rotation when shaking, affecting theefficiency of the turbine. In order to increase theefficiency, we can try to tighten the water pipe toreduce the contraction of the pipeline, the clay isused to smooth the uneven blade surface. The weightring is also used to adjust the center of gravity to theaxle center.
CONCLUSIONSThe use of engineering software for geometric shapedesign and the use of computational fluid dynamic
software to calculate the geometrics shape of a bladewith a higher torque can reduce the wrong design.
The results also show that the power get from thedesign of the blade will be higher than that of theunqualified design. Because the energy from theinjection water completely become the output powerin CFD calculation, but it is impossible in the real
design equipment. Therefore more reliable analyticalmethod must be considered.
In terms of the blade, the glass fiber hardness is good,
the user can make the blades thinner and lighter.
Glass fiber is more plastic than wood, it can design awide range of contact area with the water, and within
the elastic limit of the material, it has higher
elongation and higher tensile strength. The design ofthe spoon shape is more able to absorb the impact
energy of the water, plus the notch design will drain
the flow water that will not water in the tank, and can
reduce the generation of turbulence that will result in
sufficient drive torque.
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[1]Wang, J. H., Energy Industry SeminarHydropower,2015.
[2]Yamato, N. M., and Yamaichi, T. M., Hill hut
hydraulic power generation, Machinery, Vol.30,

769

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

FLEXURAL STRENGTH OF RIGID PAVEMENT USING RECYCLED
CONCRETE AGGREGATES IMPROVED BY POLYVINYL ALCOHOL
Suksun Horpibulsuk1; Teerasak Yaowarat2; Arul Arulrajah3; Mehdi Mirzababaei4;
and Ahmad Safuan A Rashid5
1
Center of Excellence in Innovation for Sustainable Infrastructure Development, Suranaree Univ. of Technology,
Thailand.
2
Suranaree Univ. of Technology, Thailand.
3
Swinburne Univ. of Technology, Australia.
4
Central Queensland Univ., Australia.
5Centre of Tropical Geoengineering (GEOTROPIK), Universiti Teknologi Malaysia, Malaysia.
ABSTRACT
Research on the utilization of recycled concrete aggregate (RCA) in civil engineering applications is gaining
popularity worldwide due to the increased efforts to promote the preservation of the environment and sustainable
development. Recycled concrete aggregate is, however, presently still limited to nonstructural applications.
Recycled concrete aggregate can still be considered as a rigid pavement material when its flexural strength isimproved adequately to sustain future traffic loads. In this study, polyvinyl alcohol (PVA), a water-soluble polymer,
was used to improve the flexural strength of RCA concrete. Polyvinyl alcohol was found to retard the hydration
process, resulting in the delay in initial and final setting times of cement-PVA paste, therefore reducing thecompressive strength of RCA-PVA concrete. For all the w/c ratios tested, the flexural strength increased withincreasing p/c ratios up to an optimum p/c ratio that provided the highest flexural strength, followed by asubsequent decrease beyond this peak value. The optimum p/c ratio tended to increase with an increase in w/c
ratio, being 0.5, 0.5, 1.0, and 1.5 for w/c ratios of 0.3, 0.4, 0.5, and 0.6, respectively. Based on the requirements of
the Department of Highways, Thailand, the p/c ≤ 1 at w/c ≤ 0.5 was found to be suitable for developing RCAPVA concrete for rigid pavements.
Keywords: Polyvinyl alcohol, Recycled concrete aggregate, Flexural strength, Compressive strength, Pavement.

shrinkage, large creep and low elastic modulus.
Nogchi [9] and Olorunsogo [10] indicated that thecompressive strength and durability against chloride
resistance of RCA concrete gradually decreased as
the amount of RCA increased. Silva et al (2014)
suggested that RCA concrete should only be used in
non-structural applications such as rigid pavement
and canal [4].
Several researchers have proposed methods toimprove the strength and durability of RCA concrete,such as by using the double mixing or two-stage
mixing (TSMA) approaches [8], [11].
Earlier studies on RCA concrete have focused on
the compressive strength properties, while researchon the essential flexural strength properties of RCA
concrete is limited to date. The flexural strength plays
a vital role in the stability of rigid pavement due to its
low tensile strength characteristics.
The flexural strength of concrete can be improvedby fiber reinforcement [12]. Water-soluble polymers
have been also reported to enhance the flexuralstrength as well as the durability of concrete [10]-[15].
Adding PVA into cement paste improves its chemical
resistance properties, such as preservation ofcompressive strength after exposure to chemical
attacks [14]. The flexural strength of concrete
specimens increases with increasing PVA-to-cement

INTRODUCTION
The utilization of waste materials and research on
new recycling techniques have been encouraged
world widely to promote sustainable practices toreduce the impact of civil engineering construction
activities on the environment. Recycled concrete
aggregate (RCA) is obtained from the demolition ofaged concrete buildings and essentially consists ofconstituents such as binding materials, water,
aggregates and admixtures. The major component is
the aggregates, which typically comprises 60–75% of
the total concrete volume [1]. Previous researches
have shown that RCA could be used sustainably as
unbound or stabilized pavement base/subbase
materials [2]-[3].
RCA can furthermore be used as coarse
aggregates in the production of concrete, which
would reduce waste concrete stockpiles at landfills
and would limit the need for natural aggregate
sources [4]. Reuse of waste materials from demolition
activities has numerous environmental and economic
benefits. However, the variable properties of RCA
remain the predominant barrier in using RCA for
concrete production. Several studies [5]-[8] reported
that RCA concrete often exhibited low compressive
strength, wide variability in quality, high drying
770

SEE - Nagoya, Japan, Nov.12-14, 2018100

Percentage passing (%)(by weight), p/c ratio due to the significant reductionof both total permeable pore volume and water
absorption of the specimens. PVA effectively packs
the concrete solid ingredients and results in a dense
matrix material [15].
To the authors’ knowledge, there has been noresearch undertaken to date on the application of PVA
for improving the flexural strength of RCA concrete,
which is the prime focus of this research. The RCA
concrete specimens were prepared by the TSMA
method in this study. The role of the water to cement(w/c) ratio and PVA/cement (p/c) ratio on thecompressive and flexural strengths of the RCA-PVA
concrete is also investigated in this study. The
flexural strength improvement of RCA-PVA concrete
specimens that meets the compressive strength
requirements of the Thailand national road authorities
is also reported in this study.

RCA.
Sand.
RCA + Sand
ASTM C33 .

80

60

40

20

0
.1

1

10

Diameter (mm)Fig. 1 Particle size distributions of sand, RCA andRCA+Sand.
Specimen Preparation

MATERIALS AND METHODS

RCA-PVA concrete specimens were prepared byvarying both w/c and p/c ratios. The PVA solution
was prepared in five different percentages withrespect to the cement weight, viz. 0, 0.5, 1, 1.5, 2.0,
representing low to high values for improving
workability and water retention abilities of theconcrete [17]. Four different w/c ratios including 0.3,
0.4, 0.5 and 0.6 were studied. The PVA solutions
were prepared by adding PVA powder at a target p/cratio into 2 liters of boiled water until the PVA wasentirely dissolved. The mixture was kept overnight inan open-air atmosphere for allowing to cool down toroom temperature before mixing it with cement slurry[14]. The 2 liters of water were removed for
producing normal concrete and replaced by 2 liters of
PVA solution.

Materials
Natural river sand with a fineness modulus of 3.74
was used as the fine aggregate for preparing the RCA
concrete. The river sand had a specific gravity in thesaturated surface dry state, water absorption, andpercent of voids of 2.58, 3.34%, and 42.5%,
respectively. The dry-rodded unit weight of the riversand was 14.7 kN/m3. Particle size distribution of theriver sand is shown in Fig. 1.
Recycled concrete aggregate (RCA) specimen had
particles with sizes ranging between 4.75 mm and 19
mm. The grain size distribution curve of RCA isshown in Fig. 1. RCA had a fineness modulus and a
specific gravity in saturated surface dry state of 1.34
and 2.67, respectively. Its dry-rodded unit weight was
12.1 kN/m3. The water absorption, percent of voids
and Los Angeles abrasion loss were, 5.5%, 54% and41%, respectively. Since the RCA was not scalped toremove the attached mortar. Consequently, the RCA
was weaker than the natural aggregate [16].
Ordinary Portland cement (OPC) was used tomake the RCA concrete specimens in this study. OPC
had a specific gravity and an average particle size of
3.15 and 14.7 µm, respectively. Chemicalcompositions of OPC are shown in Table 1.
Polyvinyl alcohol (PVA) was purchased from
Chemipan Corporation Co., Ltd, Thailand. It is asynthetic polymer that is achromatic, odorless andsoluble water (temperatures of 95～95 are generally
required for complete solution). PVA had a specificgravity, hydrolyzed, and molecular weight of 1.271.31, 87.83%, and 22,000, respectively.

Table 1 Chemical compositions of ordinary OPC(percentage by weight of cement, wt%).
SiO₂
20.9

SO₃
2.7

Fe₂O₃
3.32

Al₂O₃
4.7

CaO
65.4

MgO
2.54

LOI
0.9

The mixing proportions of the RCA concrete
specimens are summarized in Table 2. The RCA wasused to fully replace the natural coarse aggregate in
the mix proportion. The ratio of fine to coarse
aggregates was fixed at 45:55 by volume. The
gradation of aggregate (mixture of fine and coarse
aggregates) is shown in Fig. 1 and compared withupper and lower boundaries suggested by ASTM C33[18]. It is noted that the gradation of tested aggregatesis within the suggested boundary. The slump of the
fresh RCA-PVA concrete was controlled in theranges of 10-30, 20-50, 30-70 and 50-100 mm for w/c
ratios of 0.3, 0.4, 0.5 and 0.6,

Table 2 Mix proportions of concretes.
771

SEE - Nagoya, Japan, Nov.12-14, 2018

Mix Proportion (kg/m3)
Cement
PVA weight.
RCAa
Sand
W3PVA0
417.4
1193
890
W3PVA0.5
417.4
2.087
1189
873
W3PVA1
417.4
4.174
1191
874
W3PVA1.5
417.4
6.261
1182
867
W3PVA2
417.4
8.348
1179
864
W4PVA0
417.4
1189
873
W4PVA0.5
417.4
2.087
1194
877
W4PVA1
417.4
4.174
1186
870
W4PVA1.5
417.4
6.261
1173
860
W4PVA2
417.4
8.348
1164
852
W5PVA0
417.4
1174
860
W5PVA0.5
417.4
2.087
1187
871
W5PVA1
417.4
4.174
1190
873
W5PVA1.5
417.4
6.261
1176
862
W5PVA2
417.4
8.348
1185
869
W6PVA0
417.4
1168
855
W6PVA0.5
417.4
2.087
1195
878
W6PVA1
417.4
4.174
1181
866
W6PVA1.5
417.4
6.261
1166
854
W6PVA2
417.4
8.348
1172
859
a
Recycled coarse aggregate in the saturated surface dry (SSD) state.
bSuperplasticizer was assumed that it had water 50% by weight.
Mix

SPb
3.26
4.35
5.43
6.52
2.72
3.26
3.8
4.35
2.17
2.39
2.6
2.82
1.08
1.3
1.52
1.73

w/c
0.3
0.3
0.3
0.3
0.3
0.4
0.4
0.4
0.4
0.4
0.5
0.5
0.5
0.5
0.5
0.6
0.6
0.6
0.6
0.6

Slump
(mm)
10
15
10
15
20
30
30
35
35
40
45
50
45
50
55
85
80
85
85
80

respectively, by varying the amount of type F
superplasticizer.
In this study, the TSMA method [11] was chosen
to prepare the RCA-PVA concretes as this method
has been proved to reduce the porosity of RCA.

specimens was determined in accordance with ASTM
C 293 using the following equation:

Initial and Final setting times
The initial and final setting times were
investigated for all specimens to explain the effect of
PVA content on the hydration process of RCA-PVA
concrete specimens by using the Method A-Manual
Vicat Needle Apparatus in accordance with the
ASTM C191 [19]. The initial setting time is reachedwhen the penetration is 25 mm or less. Setting time
ended when the tip of the needle penetrated only 0.5
mm into the cement paste.

where P is the maximum applied load, L is thespan length, b and d are the average width and depthof the specimens respectively.
All the specimens were cast in steel molds andcompacted by a vibrating table. The cylindrical andprismatic concrete specimens were demolded after 24hours of curing at a room temperature, and then cured
in a water-curing tank at 27 ± 2 °C for the designed
curing age. The compressive and flexural strengths of
RCA concrete were investigated for the curing agesof 7 and 28 days.

Compressive and Flexural strengths

RESULTS

Based on ASTM C192 [20], all of the fresh
concrete mixtures were prepared using a rotary drum
mixer. For each concrete mix, Ø100×200 mm
cylinders and 100×100×500 mm prismatic specimens
were cast. The Ø100×200 mm cylinders were used todetermine the compressive strength according to the
ASTM C39 [21]. The 100×100 ×500 mm prismatic
specimens were prepared for the flexural strength testwith a center-point loading in accordance with the
ASTM C293 [22]. The flexural strength of theInitial and Final Setting Times

Flexural strength =𝟑𝟑𝟑𝟑𝟑𝟑𝟐𝟐𝟐𝟐𝟐𝟐²(1)

Figure 2 shows the initial and final setting timesof PVA-cement pastes at various w/c and p/c ratios.
The setting time was measured using Vicat apparatus
on two representative specimens for each set 15
minutes after preparation time. The PVA influences
the hydration process by delaying both initial andfinal setting times, as compared to the pure cement
paste (without PVA) at the same w/c ratios. For
772

SEE - Nagoya, Japan, Nov.12-14, 2018

instance, at a p/c ratio of 2 and w/c ratios of 0.3, 0.4,
0.5 and 0.6, the initial setting times were delayed byabout 44, 54, 43 and 53 minutes, respectively whencompared with those of the pure cement pastes. The
final setting times were 62, 51, 38 and 44 minutes,
respectively longer than those of the pure cement
plates, which is similar to the results reported byprevious researchers [13], [15]. It is noted that for thesame w/c ratio, the initial and final setting times are
longer for higher p/c ratios. For example, at w/c = 0.5,
the initial setting times are 215, 225, 229, 235 and 242
minutes for p/c = 0, 0.5, 1.0, 1.5 and 2.0, respectively
and the final setting times are 343, 349, 355, 362 and364 minutes for p/c = 0, 0.5, 1.0, 1.5 and 2.0,
respectively.

Compressive Strength (MPa)(a) 50w/c=0.3
w/c=0.4
w/c=0.5w/c=0.6

7 days of curing time.
40
30
20
10
0
0.0

.5

1.0

1.5

2.0

p/c (wt.%)
Compressive Strength (MPa)(b)5028 days of curing time.

40

w/c=0.3
w/c=0.4
w/c=0.5w/c=0.6

32 MPa

30
20
10
0
0.0

.5

1.0

1.5

2.0

p/c (wt.%)
Fig. 3 Compressive Strength of RCA-PVA concreteat (a) 7 days and (b) 28 days.

Fig. 2 Initial and final setting times of PVA-cement
paste.

Similarly, the maximum 28-day compressive
strengths were also found at p/c ratio = 0 and w/c =0.3. At p/c = 0, the 28-day compressive strength were
43.6, 41.1, 38.5 and 32.59 MPa for w/c ratios of 0.3,
0.4, 0.5 and 0.6, respectively (Fig. 3b).
It is evident from the test results that the additionof PVA to the concrete mix not only reduces thecompressive strength of the specimen at a particularcuring time but also the strength development withtime. This is in agreement with the test results ofsetting times in that the initial and final setting times
are longer with increasing of p/c ratio. For instance at
w/c = 0.3, 7-day and 28-day compressive strengths
are 29.5 and 43.5 MPa, respectively for p/c = 0; are24.5 and 35.6 MPa, respectively for p/c = 1.0 and are
20.6 and 27.4 MPa, respectively for p/c = 2.0.

Compressive Strength of RCA-PVA Concrete
The compressive strength of RCA-PVA concrete
specimens at 7 and 28 curing days and different w/cratios of 0.3, 0.4, 0.5 and 0.6 are shown in Fig. 3. The
highest 7-day compressive strength (Fig. 3a) was
found at p/c ratio = 0 where the maximum
compressive strengths are 29.5, 27.1, 24.7 and 21.2
MPa for w/c ratios of 0.3, 0.4, 0.5 and 0.6,
respectively while the minimum 7-day compressive
strengths were found at p/c = 2, including 20.6, 15.6,
14.1 and 12.3 MPa for w/c ratios of 0.3, 0.4, 0.5 and
0.6, respectively. This result indicates that thecompressive strength reduces with increasing of w/c
and p/c ratios. The additional water content(increasing of w/c ratio) leads to coarse pore
distribution in a concrete specimen and increases its
porosity and permeability, hence reduces its
compressive strength [23].

Flexural Strength of RCA-PVA Concrete
Figure 4 shows the flexural strength of thespecimen at various w/c ratios, p/c ratios, and curing
times. For low w/c ratios of 0.3 and 0.4, the maximum
flexural strength was found at approximately thesame p/c ratio of 0.5% at all curing times. The
maximum flexural strengths at w/c ratios of 0.3 and0.4 at 28 days of curing were found to be 6.7 and 5.8
MPa, respectively with an increase of 133% and773

SEE - Nagoya, Japan, Nov.12-14, 2018139% when compared to RCA concrete specimens at
the same w/c ratios. However, the addition of PVA
beyond p/c of 0.5% caused a reduction in the flexuralstrength.
The change in the flexural strength with p/c ratio
for higher w/c ratios of 0.5 and 0.6 is also similar tothat for w/c = 0.3 and 0.4, where the flexural strength
increases to the maximum value at the optimum p/cand then decreases as p/c increases. However, theoptimum p/c ratios providing the highest flexuralstrength are different from those of w/c = 0.3 and 0.4.
The optimum p/c ratios were found to be 1.0 and 1.5
for w/c = 0.5 and 0.6, respectively. In other words, theoptimum p/c increases with increasing of w/c ratio.
At the optimum p/c ratio, the 28-day flexuralstrengths were 5.35 MPa and 4.93 MPa for w/c = 0.5
and 0.6, respectively. The flexural strength increased
by 132% and 129% than those of RCA concrete at
the same w/c ratios of 0.5 and 0.6, respectively.
Compared with the strength requirement for the rigid
pavement by Department of Highways [24] (the 28day compressive strength > 32 MPa (see Fig. 3b), theRCA concrete (without PVA) meets the requirement
for all w/c ratios tested. With PVA, the RCA-PVA
concretes meet the requirement when w/c ≤ 0.5 andp/c ≤ 1.

Flexural Strength (MPa)

(a) 8
7

w/c=0.3
w/c=0.4
w/c=0.5w/c=0.6

7 days of curing time.

6
5
4
3
2
1
0

0.0

.5

1.0

1.5

2.0

p/c (wt.%)
Flexural Strength (MPa)(b) 8

CONCLUSIONS

7

28 days of curing time.

w/c=0.3
w/c=0.4
w/c=0.5w/c=0.6

6
5
4
3
2
1
0
0.0

This research investigates the feasibility of using
polyvinyl alcohol (PVA) to improve the flexuralstrength of recycled concrete aggregate (RCA)
concrete to be a sustainable rigid pavement material.
The following conclusions can be drawn from thisresearch study:
PVA prevents the water absorption for cement
hydration process. Hence, the higher the p/c ratio
results in the longer initial and final setting times of
RCA-cement paste and the lower the compressive
strength.
Even though PVA retards hydration, it contributes
to improving the tensile strength of the cement matrix
and hence results in an increased flexural strength.
The flexural strength of RCA-PVA concrete iscontributed from cementation bond and PVA film
strength. Due to the reduction in cementation bondstrength and the increase in tensile strength withincreasing of p/c ratio, the flexural strength increases
with increasing of p/c ratio up to the maximum value
at the optimum p/c ratio and then decreases withincreasing of p/c ratio.
The optimum p/c ratio is dependent upon w/c
ratio. The higher w/c ratio results in the higher p/cratio. The optimum p/c ratio was found to be 0.5, 0.5,
1.0 and 1.5 for w/c = 0.3, 0.4, 0.5 and 0.6,

.5

1.0

1.5

2.0

p/c (wt.%)
Fig. 4 Flexural Strength of RCA-PVA concrete at(a) 7 days and (b) 28 days.
respectively. Based on the national road authority(demanding a minimum 28-day compressive strengthof 32 MPa), the w/c ≤ 0.5 and p/c ≤1 was found to be
applicable for road construction. At the optimum p/cratio, the flexural strength of RCA-PVA wasapproximately 130% higher than that of the RCA
concrete.
The outcome of this research confirms theviability of using PVA to improve the flexuralstrength of RCA concrete to be used as an alternative
sustainable rigid pavement.
ACKNOWLEDGEMENTS
This work is financially supported from the Thailand
Research Fund under the TRF Senior Research
Scholar program Grant No. RTA5680002 and the
Ph.D. Royal Jubilee program Grant No.0143/2557,
Suranaree University of Technology. The first author
is grateful to the Thailand Research Fund for Ph.D.
study financial support under the Ph.D. Royal Jubilee
program.

774

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concrete produced from two-stage mixing
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Environment776

OPERATING CONDITIONS EFFECTS OF AN ELECTRODIALYSISMODULE ON HYDROCHLORIC ACID AND HYDROXIDEFORMATION FROM A SODIUM CHLORIDE MODEL SOLUTION
Medina Juan1, Diaz Zoila2 y Rojas Jorge3
Facultad Ingeniería Química, Universidad Nacional del Callao, Perú

ABSTRACTThe operating conditions effect on the formation of hydrochloric acid and sodium hydroxide from the sodium
chloride model solution has been studied using an electrodialysis module built at laboratory scale. In order toexperiment with the electrodialysis module, a laboratory scale discontinuous equipment was used, this equipment
contained two selective membranes, one cationic and one anionic (5 and 20 V) for a treatment time of 210 minutes.
Both the acid solution and the basic solution reached a 0,22 N and 0,25N concentration, respectively. To reach thebest operating condition a 15V tension was applied. Both the acid solution and the basic solution concentration was
0,05N and the model solution concentration 50g/L; the energy consumption of NaOH was 14,9 kWh / Kg, and andthe current efficiency 53.5%.
Keywords: electrodialysis, bipolar electrodialysis, electromembrane, hydrochloric acid, sodium hydroxide.
INTRODUCTION
Inorganic products such as hydrochloric acid, sulfuric
acid, phosphoric acid, nitric acid and sodiumhydroxide are indispensable in many industrial
processes, such as fertilizers, pickling, electroplating,steelmaking, water treatment etc. As the populationand the development of the industry increase, theconsumption of these chemicals must increase in the
future. The chlorine alkali industry produces chlorine,
sodium hydroxide and hydrogen by electrolysis of
NaCl aqueous solutions as indicated in the following
chemical equation

According to the diagram, sodium hydroxide is
produced at the electrolysis stage, however, to producehydrochloric acid other traditional operations areneeded, such as a combustion furnace and absorption
column. In these traditional processes, mercury andasbestos emissions occur. This has led to the search for
new alternatives to eliminate these stages of the
traditional process.
Electrodialysis is a process of separation of ionicspecies from aqueous solutions, based on the selective
migration of ions through ion exchange membranes
under the influence of a direct current electric field.
These processes generally contain two types of ion
exchange membranes; anionic membranes (MA)selectively permeable to anions and cationicmembranes (MC) which are selective to cations,placed alternately and separated by expansion joints
between two electrodes.

NaCl (ac) + H2 O(l) → Cl2(g) + NaOH (ac)+H2(g)……… (1)At present, the chlor-alkali process is mainly
represented by three technologies; mercury cell,
diaphragm and membrane cell. The main difference
between these technologies is cell configuration anduse of different materials. According to Fig. N ° 1, a
general scheme of the chlor-alkali process is shown.

When an electric potential is applied to the electrodes,
the migration of ions to the electrodes with opposite
charge begins. The cations penetrate the cationicmembranes, but these are blocked by the anionicmembrane. Similarly, the anions penetrate the anionicmembranes but the atonic membranes block theanions. The process at the end results in increasing theconcentration in one of the compartments and dilution
in another compartment. Inorganic and organic sales
found in effluents, such as sodium chloride, sodium
sulfate, sodium nitrate, sodium acetate, etc., can

Water
Chlorine

HydrogenElectrolysis

burnerSodiumchlorideabsorption

Hydrochloric
acid

Sodium hydroxideFig. N° 1 NaOH and HCl production

777

become its parameters and bases due to bipolarelectrodialysis.

Membrane Configuration
Figure N°2 shows the configuration of themembranes, one anionic and two cation exchange
membranes placed between the cathode and the anode

The ion exchange membranes can take different
possible configurations forming cells of two or morecompartments, each of these configurations can havevarious possible applications, such as desalination ofbrackish water, demineralization of wine, formation ofhydrochloric acid and sodium hydroxide, etc. The
purpose of this investigation is, first, to obtain NaOH
and HCl by electrodialysis instead of NaOH, Cl2, H2and second, to carry out a study of the influence of theoperation variables such as initial acid concentration,base concentration of sodium chloride and electric
potential on the final acid concentration and baseconcentration, in addition to the process efficiency andenergy consumption, the latter is fundamental tounderstand the process economy and scalability.

Fig. 2 Membrane Configuration

MATERIALS AND METHODSElectrialysis equipment

Materials

The cell built was a press filter type laboratory scalewith four compartments, It was built with acrylic
material on which three membranes were assembled
with their respective turbulence promoters, andsecured with 8 transverse bars with nuts to prevent any
type of leakage, mixed or spilled liquid. Two acrylic
plates with two inlets and two outlets at the end,
disposed for the flow of salt and hydrochloric acidsolutions. Two 1.5 cm thick acrylic frames, where twoelectrodes (of 100 cm2 effective area) are inserted,
made of steel and platinum titanium, each acrylic platecontains an inlet and outlet through which passes thesodium hydroxide solution and the diluted solution of
sulfuric acid. The dimension of each membrane is 10
cm × 9 cm. All experiments were performed in a batchmode at room temperature. The acid, base and salt
solutions were recirculated by pumps independently,
he flow rate was regulated by a step valve. The initial
volume of solutions in each compartment was 500 mL.
The voltage and current were recorded directly fromthe electrical source. the time used for each experimentwas 210 min.

Both analytical grade reagents such as Na2 SO4, NaCl,
NaOH y HCl and deionized water produced by EDI
equipment were used throughout the experience. The
acid and base solutions were generated using feedsolutions consisting of 0.01, 0.025 and 0.05 N ofhydrochloric acid and sodium hydroxide, 5.20 and 50
g / L NaCl and applied voltage of 5-15. Volts
maintaining a constant concentration of 0.05 M
H2SO4.
Membranes
Two commercial membrane clases were selected in thiswork, from the company FuMA-Tech GumbH, Germany.
Table 1 Membrane characteristics

MembraneCharacteristics- Electric
resistance(Ω/cm²)-Exchange
capacity (meq/g)-Thickness(mm)Cationic
Membrane(FTCM-E)

Anionic
Membrane(FTAM-E)

2,5- 3,5

2,5- 3,5

1,5 - 1,8

1,4 - 1,7

0,17 - 0,19

0,16 - 0,18

778

HCl, NaOH mol/L; VHCl, VNaOH (liters).

Efficiency electric current
The current efficiency (η) for a specific product is an
important critical parameter to assess the viability ofED since it determines the applied current fraction thatis effectively converted.
𝜂=𝑧𝐹(𝐶𝑓 −𝐶𝑖)𝑉𝑡𝑡

𝑁 ∫0 𝑖𝑑𝑡

𝑥 100% … …

(5)Fig. 3 Experimental equipament𝜂:current
efficiency:
Faraday
constant(96500A.s/mol), Cf y Ci - initial and final concentrationof HCl solution (mol/m3); i, electric current intensity(A) and N, number of cell pairs. Vt volume ofrecirculated HCl solution

Analytical methods
The concentrations of NaOH and HCl formed were
determined by titration with a standard concentrationof 0.01 mol / L of hydrochloric acid and sodiumhydroxide. The chloride ions by titration of 0.01N
silver nitrate. the conductivity was measured using an
ADWA AD 330 Conductimeter and the pH in the acidand base compartment was measured by a ADWA
Switzerland pH meter.

Energy consumption
The energy consumption was determinated by theequation (3)E=𝑉 ∫ 𝑖𝑑𝑡… … … … … . . (6)𝐶𝑡 𝑉𝑡 𝑃. 𝐹

Process indicators and electrodialysis
Where: E (Kwh/kg) is he required energy consumption
to form the acid and base, i (t) electric curren, V is thecell potential difference t: time Vt: volume (m3) as afunction of time, HCl solution final concentration
mol/m3.

Separation percentage
The separation percentage is evaluated by equation(1). The concentration or conductivity is measured at
the beginning and then at a certain time.

RESULTS ANALYSIS
𝑆=(

𝐶𝑡=0 − 𝐶𝑡=𝑡
) 𝑥100% … … … … (2)𝐶𝑡=0

pH evolution in the acid and base compartment
Figures 4 and 5 show the pH changes in thecompartments of both sodium hydroxide formationand hydrochloric acid, the graphs tendency is
explained in terms of the chemical reactions. In thebase compartment, water is decomposed by electric
current producing hydroxyl ions and hydrogen gas asindicated in the following equation.

Base acid concentration
Changes in the concentration of hydrochloric acidand sodium hydroxide were determined by titration
using phenolphthalein as an indicator. The
concentration is calculated using the following
equations (4)𝐻2𝑂(𝑙) → 𝐻2(𝑔) + 𝑂𝐻1− + 2𝑒 − …………(7)𝐶𝑁𝑎𝑂𝐻 𝑥𝑉𝑁𝑎𝑂𝐻
𝐶𝐻𝐶𝑙 =… … … . . (3)𝑉𝐻𝐶𝑙
𝐶𝐻𝐶𝑙 𝑥𝑉𝐻𝐶𝑙
𝐶𝑁𝑎𝑂𝐻 =
… … … … . (4)𝑉𝑁𝑎𝑂𝐻

The sodium ions of the sodium chloride compartment
are permeable to the cathode through the cationexchange membrane forming sodium hydroxide779

together with the oxydryl ions as indicated theequation.

Figure N°5 shows that pH decreases rapidly when avoltage of 15 volts is applied

𝑁𝑎1+ + 𝑂𝐻1− → 𝑁𝑎𝑂𝐻(𝑎𝑐) ……………..(8)Evolution of the acid and sodium hydroxide
concentration

The pH in this compartment increases over time dueto the formation of oxydryl ions, sodium ions andsodium hydroxide concentration formed as a functionof time. The figure 4 shows the pH increases more
quickly when a voltage of 15 volts is applied.
regardless of the initial concentration of NaOH in therange of 0.01 and 0.05 N.

Figure 6 and 7 show the increase in the acid and baseconcentration is more significant when a voltage of 15
V is applied and it is more significant for the acid when
the initial concentration is 0.05 N. The hydrochloric
acid concentration reached is 0.22 N and sodiumhydroxide 0.25 N for initial contractions of 0.05 N at
15 volts.

In the acid compartment, the hydronium ionsproduced at the anode are permeable by the cationicmembrane and combined with the chloride ions which
are permeable by the anionic membrane forminghydrochloric acid according to the following reaction.

HCl Concentration (mg/L)

10000

𝐻1+ + 𝐶𝑙1− → 𝐻𝐶𝑙(𝑎𝑐) … … … … … … … . (9)
12.6
12.4
12.2

6000
4000
2000
0

12

pH

8000

0

30

11.8

60

90

120 150 180 210

time (minutes)

11.6

0.01 N – 15V – 50 g/L

0.025N – 5V – 20 g/L

11.4

0.05 N – 15V – 5 g/L

0.05 N – 15V – 50 g/L

11.2
Fig.6 Changes of HCl (mg / L) concentration

11
30

60

90 120 150 180 210

0.01 N – 15V – 50 g/L

0.025N – 5V –20 g/L

0.05 N – 15V – 5 g/L

0.05 N – 15V – 50 g/L

NaOH concentration (mg/L)

0pH

Fig.4 pH dependence in the base compartment

2.3
2.1
1.9
1.7
1.5
1.3
1.1
0.9
0.7
0.5

12000
10000
8000
6000
4000
2000
0
1

2

3

4

5

6

7

8

time (minutes)

0

100

200

300

Time(MINUTES)
0.01 N – 15V – 50 g/L

0.025N – 5V – 20 g/L

0.05 N – 15V – 5 g/L

0.05 N – 15V – 50 g/L

0.01N - 15V -50 g/L

0.05N - 5V -20g/L

0.05N - 15V - 5g/L

0.05N -15V - 50 g/L

Fig.7 Changes of NaOH (mg / L) concentration

Fig.5 pH dependence in the acid compartment

780

Change in conductivity of base acid
Figure 10 shows that the conductivity of sodium
chloride decreases, and at equation (2) the separation
percentages have been evaluated at an applied voltageof 15 volts, obtaining 19.3% when the concentration of
sodium chloride is 50g / L and 95.28% when theconcentration of sodium chloride is 5g / L.

40
35
30

60

25

50

20
CONDUCTIVITYNaOH Conductivity (mS/cm)

Figures 8 and 9 show that the conductivity trend
grows over time for both the acid and the base, the acidconductivity grows faster than the base reaching 63.5
ms / cm, with a voltage of 15 volts for the base of 35.2
mS/cm

15
10
5
0
0

30 60 90 120 150 180 210

0.025N - 5V- 20 g/L

0.05N - 15V- 5 g/L

0.05N - 15V - 50 g/L

30
20
10
0

time (minutes)
0.01N - 15V - 50g/L

40

-10

0

100

200

300

TIME (MINUTES)

0.025N – 5V – 20 g/L

0.05 N – 15V – 5 g/L

0.05 N – 15V – 50 g/L

Fig.8 Change of NaOH Conductivity

Fig.10 Changes of NaCl Conductivity (mS/cm)

HCl conductivity (mS/cm)

80

Conductivity evolution of sulfuric acid60

In this compartment, water decomposes intohydronium ions and oxygen ions due to the action ofelectric current as indicated the equation40

𝐻2 𝑂(𝑙) → 𝑂2(𝑔) + 𝐻1+ ………….. (10)20

In the first ionization stage, the sulfuric acid inaqueous solution produces hydronium ions

0
0

30

60

90 120 150 180 210

time (minutes)
0.01 N – 15V – 50 g/L
0.05 N – 15V – 5 g/L

𝐻2 𝑆𝑂4(𝑎𝑐) → 𝐻1+ + (𝐻𝑆𝑂4 )1− ………(11)0.025N – 5V – 20 g/L
0.05 N – 15V – 50 g/L

Simultaneously hydronium ions are permeable by thecationic membrane to the acid compartment. As
expected, the conductivity and contraction of sulfuric
acid in this compartment varied slightly throughout theexperiment, as indicated in figure 11, due to theformation and disappearance of hydronium ions,
independently of the applied electrical voltaje.

Fig.9 Change of HCl Conductivity

Variation of conductivity of NaCl
In the sodium chloride compartment, a gradualdecrease in conductivity is observed as a function oftime, which is the result of the diffusion of sodium ionsby the cationic membrane and the chloride ions that arepermeable through the anionic membrane.

781

1.7
CONDUCTIVITY

1.6

Effect of applied electrical voltaje

1.5

Figure 6 and figure 7 show that, when the module
worked with a voltage of 15 volts, it was possible toobtain the highest concentration of acid (8030mg/L 0.22 N) and base (10000mg/L - 0.25 N) at initialconcentrations of HCl (1825 mg/L- 0,05 N) and NaOH
(2 000 mg/L -0,050 N) using 50 g / L of NaCl.

1.4
1.3
1.2
1.1
1
0

100

200

300

Equations 5 and 6 have evaluated the specific energy
consumption, obtaining 14.9 kWh / Kg of NaOH, andthe current efficiency was 53.5% at the most adequate
operating conditions of the electrodialysis equipment.

TIME (MINUTES)
0.01 N – 15V – 50 g/L
0.05 N – 15V – 50 g/L

Fig. 11 Changes of sulfuric acid (mS/cm) Conductivity

Effect of initial concentration of hydrochloric acidand sodium hydroxide

CONCLUSIONSElectrodialysis (ED) represents a method ofseparating chloride anions, sodium cations from a
sodium chloride model solution and simultaneously
obtaining aqueous solutions of hydrochloric acid andsodium hydroxide in different compartments.

To determinated the evolution of initialconcentrations of HCl and NaOH it was necessary
work with two inictial concentrations of NaCl (20g/L
and 50g/L) and two differetn electrical voltage (10v
and 15v). The acid and base initial concentrations were
0,01N, 0,02N and 0,05N.

ED with ionic membranes offers a clean technology,
compared to traditional processes for the production ofacid and base. In this study, it was shown that
according to the sodium chloride feed concentration,
the applied voltage and the initial concentration of theacid and base, the results show that when the applied
voltage is 15 volts, the initial concentration of the acidand base is 0.05N and 50 g/L of NaCl an acidconcentration 0.22N and 0.25N of sodium hydroxide
is reached.

Considering 50g/L of NaCl as initial concentration,
figure 12 shows the best result to 0,05N initialconcentration of acid when a voltage of 10v is applied
reached 0,14N and 0,22N when a voltage of 15v isapplied. At the same figure, NaOH initialconcentration is 0,05N and reached a final
concentration of 0,22N when a voltage of 10v is
applied, and 0,25N when a voltage of 15v is applied.

NORMALITY

0.3
0.25

ACKNOWLEDGEMENTS

0.2

We thank National University of Callao for thefinancial support that made posible the development of
this investigation.

0.15
0.1
0.05
0
Initial

10v

NaOH

15v

HCl

Fig.12 Evolution of normal concentration of HCl and
NaOH

782

REFERENCES[1] R. Ibáñez, A. Pérez-González, P. Gómez, A.M.

[8] Mohammadi, T. and Kaviani, A. (2005).

Urtiaga, I. Ortiz, Acid and base recovery fromsoftened reverse osmosis (RO) brines.
Experimental assessment using model
concentrates, Desalination 309 (2013) 165–
170.
[2] S. Koter, A. Warszawski Electromembrane
Processes in Environment Protection Polish
Journal of Environmental Studies Vol. 9, No.
1 (2000), 45-56[3] Jiangnan Shen, Zhendong Hou, Congjie Gao
Using bipolar membrane electrodialysis tosynthesize
di-quaternaryammoniumhydroxide and optimization design byresponse surface methodology[4] F. Schaffner a, P.-Y. Pontaher , V, Sanchez b,
F. Lutin ° Comparison of diester waste
treatment by conventional and bipolarelectrodialysis Desalination 170 (2004) 113121[5] Ochoa Gomez, J. (1996). “Electrosíntesis yElectrodiálisis” (Fundamentos, aplicaciones
tecnológicas y tendencias) (2a ed), Cap.7; Mc
Graw - Hill, Madrid, España, 199-237.
[6] Shaposhinik, V.A., Zubets, N.N and Mill, B.E.
(2001). Demineralization of wáter byelectrodialysis with ion-exchange membranes,
grains and nets, Desalination, 133, 211-214.
[7] Mohammadi, T. and Kaviani, A. (2003). Water
shortage and seawater desalination byelectrodialysis, Desalination, 158, 267-270.

Modeling of metal ion removal fromwastewater by electrodyalisis, Sep Purif.
Technol, 41, 73-82.
[9] Mohammadi, T. and Kaviani, A. (2007).
Separation of Different Ions from Wastewaterat Various Operating Conditions Using
Electrodialysis, Sep Purif. Technol, 54, 147156.
[10] Montalvo, A., Rodríguez Torres, L.G., Govea
Hernández, I., M., & Delgadillo Gómez, J.A(2002). Estudio de la densidad de corriente
límite en una celda de electrodiálisis en
función de la concentración y la velocidad.
Facultad de Ingeniería – Instituto de
Metalurgia Universidad Autónoma de San
Luis Potosí.

[11] Cowan, D.A., Brown, H.J. (1959). Efecto de laturbulencia en la corriente límite en las celdas
de electrodiálisis, Int Engng. Chem, 51, 1445.

[12] Lee, H. J., Strathmann, H. and Moon, S.H.
(2006). Desalination, 190, 43.

[13] Banasiak, L.J., and Kruttschnitt, T.W. (2007).
Desalination using electrodialysis as a functionof voltaje and salt concentration, Desalination,
205, 38-46.
[14] Sadrazadeh, M. and Mohammadi, T. (2008).
Sea water desalination using electrodialysis,
Desalination, 221, 440–447.

783

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

WOODY DEBRIS RECRUITMENT CAUSED BY DISASTERS
RELATED TO TROPICAL STROM NANMADOL (2017) IN
HEADWATER OF ASAKURA CITY, FUKUOKA, JAPAN1

Thapthai Chaithong1, Daisuke Komori2 and Yuto Sukegawa3
Graduate School of Environmental Studies, Tohoku University, Japan; 2,3 Graduate School of Engineering,Tohoku University, Japan

ABSTRACT
Woody debris is a natural component of the ecosystem. It is caused by trees that have fallen and been entrainedby natural disasters related to storms, such as shallow landslides, debris flow or floods, into streams or storage on
the hillslope. On 4 July 2017, Tropical Storm Nanmadol made landfall on the island of Kyushu, south of theJapanese mainland. It brought heavy rainfall, floods and shallow landslides to many cities on the island of Kyushu,
particularly the city of Asakura in Fukuoka Prefecture. The maximum hourly rainfall measured by the Japan
Meteorological Agency at the Asakura station was 106 mm on 5 July 2017 at 6:00 p.m., and the cumulative rainfall
between 4 and 6 July 2017 was approximately 590 mm. In this study, the post-disaster areas in the town of Asakura
were examined after the passage of Tropical Storm Nanmadol. From these observations, we found that a significant
cause of woody debris recruitment is shallow landslides, which cause the collapse of trees. The debris flow processacts as a conveyor that channels woody debris from the hillslope or origin of the landslide downward. Floods or
fluvial processes in the river entrain the woody debris downstream. The volume of woody debris recruitment
during this particular event was approximately 257,000 m3.
Keywords: Woody debris, Natural dam, Tropical storm, Disasters, Landslide, Flood, Debris flow

Nibutani Dam [4]. Moreover, enormous amounts ofwoody debris were generated by landslides, bankerosion and debris flows related to Typhoon Lionrockin 2016 [5]. Hence, precipitation plays a significant
role in the recruitment process of woody debris. In
2017, the Pacific typhoon season produced a total of
27 named storms. Tropical Storm Nanmadol is thethird name of tropical cyclone that it was Typhoon No.
1703. It hit the Island of Kyushu, to the south of theJapanese mainland, between 4 and 7 July 2017.
Enormous quantities of woody debris were
subsequently found in the city of Asakura in Fukuoka
Prefecture. A further 2,033 m3 of woody and otherdebris was removed from the Ariake Sea by the
Fukuoka Ariake Fishery Association, the Saga Ariake
Fishery Association and the Japanese Ministry ofLand, Infrastructure, Transport and Tourism [6].
The aims of this study are as follows: (1) topresent the results of the post-disaster investigation
related to woody debris recruitment in Asakura cityand 2) to examine the characteristics of woody debris
dam formation and woody debris transport processes.

INTRODUCTION
Woody debris can be defined as logs, branches,root wads and other wooden material. Such materials
play multiple roles in the ecosystem and human life.
On the positive side, they have an important role inthe carbon budget and nutrient cycle in forests,
including forming the river habitats of fishes andother aquatic organisms [1,2]. On the negative side,
they may increase the tendency of natural disasters todestroy infrastructure and housing in the event offlash floods, landslides and debris flow. Numerous
studies have reported that a lot of woody debris was
generated and set loose after the tropical storm madelandfall. Heavy rainfall caused by extreme storms canlead to an increase in the pore water pressure or
groundwater table in the soil slope and may increase
the river discharge. These processes are the cause oflandslides, debris flows and flash floods, as well as
stream bank erosion. In 2005, an extreme flood in
Switzerland entrained a volume of woody debris inexcess of 69,000 m3. In August 2009, approximately
603 m3 of woody debris flowed into the downstream
area of the Qijiawan catchment in Taiwan after
Typhoon Morakot [3].
An examination of the historical cases of woody
debris linked to heavy rainfall in Japan reveals several
past cases. For instance, when Typhoon Etau hit theisland of Hokkaido in 2003, approximately 50,000 m3
of woody debris was entrained by the flood into the

TROPICAL STORM NANMADOL (2017) AND
AFTERMATH
In Japan, Typhoon season runs from July to
October [7]. Tropical Strom Nanmadol made landfall
on Kyushu on 4 July 2017 with a wind speed of784

SEE - Nagoya, Japan, Nov.12-14, 2018

approximately 74 km/h (40 knots). At its peak, thestorm reached a wind speed of 101 km/h (55 knots)
and a minimum atmospheric pressure of 985 hPa. The
average wind speed was 81 km/h (44 knots). Figure 1
shows the path of the storm and the distribution of
cumulative rainfall on the island of Kyushu between
4 and 6 July 2017. The storm brought more than 140
mm of rainfall in 72 hours in Saga, Fukuoka, Oita,
Kumamoto and Nagasaki Prefectures. The maximum
rainfall in a single 24-hour period, 514 mm, wasrecorded at Asakura station in the city of Asakura.
This figure constitutes more than a quarter of thesite’s average annual rainfall of 1,918 mm (asmeasured from 1976 to 2017). The storm wascharacterised by the delivery of a high volume ofintense rainfall in a short period of time; in addition,

the pattern of rainfall was similar to an advanced
rainfall pattern.
The Kyushu Regional Development Bureau,
which forms part of the Ministry of Land,
Infrastructure, Transport and Tourism (MLIT) [6],reported that 266 houses were completely destroyed.
A further 850 sustained extensive damage, with 360
suffering substantial flooding above the floor, while
1,341 experienced less substantial immersion. A totalof 26 lives were lost and 14 people were injured
during the storm. A further five persons were declared
missing. Figure 2 shows the damage done to housesin the city of Asakura by Tropical Storm Nanmadol.
Figure 3 shows the river bank damage caused by thestorm.

Fig. 1(a) Path of Tropical Storm Nanmadol 2017 [8] and (b) cumulative rainfall from 4 to 6 July 2017.

Fig. 2

House damage caused by Tropical Storm
Nanmadol.

DESCRIPTION OF STUDY AREA, FIELDSURVEY AND CHARACTERISTICS OF
SHALLOW LANDSLIDESStudy area and field survey
The study area is the city of Asakura in Fukuoka
Prefecture, on the island of Kyushu, Japan. Asakura
suffered serious damage as a result of flooding,woody debris and landslides related to Tropical Storm

Fig. 3

River bank damage caused by Tropical
Storm Nanmadol.

Nanmadol. Eight sites in the city of Asakura were
investigated by our team after the passage of thestorm. The sites examined by our team are located at
the small headwaters in the city. Sugi, or Japanesecedar (Cryptomeria japonica), hinoki cypress(Chamaecyparis obtusa) and bamboo are the plants
most prevalent at the investigated sites. Our team also
used aerial photographs to investigate the location of
woody debris deposition in the river channel. In
addition, the woody debris that had flowed to the785

SEE - Nagoya, Japan, Nov.12-14, 2018

Terauchi and Egawa Dams was also measured. Figure
4 shows the location of the city of Asakura.
For the field survey, the diameter and age of trees
were measured for individual pieces of wood foundin the Terauchi and Egawa Dams. The team measured
the dimensions, such as the length, height, and width,

Fig. 4

as well as the latitude and longitude of the debris.
Moreover, the height and the diameter at breast height(BHD) were measured at the investigated sites. A
laser measuring device and measuring tape were themain instruments used to measure the dimensions.

Location of woody debris, landslides and dams in city of Asakura, Fukuoka, Japan.

Characteristic of shallow landslidesSc   Li  Lo  Qi / x  Qo / x  D  t

Figure 5 plots the number of shallow landslides,
landslide ratio and slope angle. A slope angle map
was extracted from a digital elevation model (DEM)
to determine the relationship between shallow
landslides and slope angles. Most landslide scars
were found on slopes ranging in angle from 20 to 30
degrees. These accounted for approximately 27% of
the total landslide scars. The landslide ratio is theratio between the landslide area and the total area ofthe city of Asakura. The maximum landslide ratio
occurred in slopes with angles ranging from 20 to 50
degrees. A review of the landslide areas reveals thatapproximately 90 per cent of landslides occurred inareas covered by trees. As a result, the landslides
produced a vast quantity of woody debris.

where  S c is a change in storage with a unit length(1)of stream x over time interval t . Li is lateralwoody material recruitment. Lo is the loss of woody
material caused by lateral deposition. Qi is the input
of woody segment caused by fluvial transport. Qo is
the output of woody segment caused by fluvial
transport. D is the in-situ decay of woody material.

CONCEPT OF WOODY DEBRIS BUDGETS
Woody debris budgets are mass budgets of woody
debris in streams that were developed with the aim of
explaining the recruitment, storage, transport anddecay of woody debris for the purposes ofquantitative analysis and prediction. Equation (1) isthe volumetric mass balance of woody debris in a unit
length of steam and is calculated based on the
differences in input, output and decay [9].

Fig. 5Landslide area and ratio of each slope in cityof Asakura, Fukuoka, Japan.

In this study, Eq. (1) is modified to a watershedsystem so that the modified woody debris budgets
concerned both natural processes and human activity.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Equation (2) is the volumetric mass balance of woody
debris in a watershed system and is a consequence ofdifferences in input, output and decay.

S   Ri  Qi  Qo  D  tequation [10]. The piece length is replaced by the treeheight and the cross-sectional area at the longitudinal
midpoint is replaced by the cross-sectional area of thetree at breast height.

(2)

Vt  H t  ABHD

where S is a change in the woody material storage
in the watershed over time interval t . Ri is the
woody material recruitment from the resources
caused by natural processes and human activities. Qi
is the input of woody material into the watershedsystem from other watershed systems, whereas Qo is
the loss of woody material out of the watershedsystem caused by natural processes and humanactivities. D is the in-situ decay of woody material.
Figure 6 provides an overview of the woody debris
budget in the watershed system.
In relation to woody debris storage in thewatershed, we draw a distinction between two main
locations: within the active stream channel andoutside of the active stream channel. The active
stream channel is the zone that is influenced by theflood or debris flow.
S  Sc  Sh

where Ht is the height of the tree and ABHD is the crosssectional area of the tree at breast-height. The decayof woody debris can be divided into five decay classes,
as shown in Table 1.
Table 1 Decay classes of woody debris [11]
Decay
class
1

2
3

(3)
4

where S c is the woody debris storage in the active
stream channel and S h is the woody debris storage
outside of the active stream channel, such as on thehillslope.
Woody debris recruitment to the watershedsystem represents several types of supply. In a
simplified calculation, woody debris recruitment isdivided into two principal sources: natural processes
and human activities.
Ri  Rn  Rm

5

Appearance of decaying fallen logs
No decay, Fine twigs remaining,
Bark completely remaining, No moss
Wood is clear, slightly stained.
Slightly decayed, No fine twigs,
Most bark present
Moderately decayed, but fallen log
could support itself, Branch stubs
remaining, Some bark present,
Sapwood and heartwood show strong
signs of decay
Fallen log could no longer support
itself,
All bark often absent,
Sapwood often absent and deep redbrown heartwood could be crumbled
manually
Wood resembles red powder with adisassembled structure,
The bark is completely absent,
The cross section of the bole is nolonger round, but elliptical(4)

where Rn is woody material recruitment by naturalprocesses such as landslides, debris flow, windstorms,
snow avalanches and fires and Rm is woody material
recruitment by human activities such as tree-felling.
In relation to the parameter Rn, we found thatlandslides play a significant role in the recruitment
process. Hence, we can calculate the woody debris
recruitment caused by landslide events using the areasof landslides and the properties of the forest, such astree density in the forest and the volume of individual
trees.

Rn,l  Al Vt  Dt

(6)

Fig. 6

Woody debris activities in the watershed.

RESULTS AND DISCUSSION(5)

Woody debris dam in the headwaters

where Rn,l is the woody debris recruitment bylandslide, Al is the area of the landslide, Dt is the tree
density in the forest and Vt is the volume of anindividual tree. In our case, the volume of anindividual tree is calculated based on Huberʼs

The site survey found the mean diameter of apiece of woody debris to be 24.9 ± 8.1 cm, whereas
the maximum diameter was 48.6 m. The mean age ofa piece of woody debris was 41.1 ± 16.3 years, with amaximum age of 69 years and a minimum age of 16
787

SEE - Nagoya, Japan, Nov.12-14, 2018

years. The mean length of a piece of woody debris
was 12.5 ± 7.2 m. Figure 7 plots the diameter and ageof pieces of woody debris. In terms of decay classes,
it was observed that approximately 87 per cent of thepieces of woody debris belonged to decay class 1,
with the vast majority of the remainder belonging todecay classes 2 and 3. Considering the relationshipbetween precipitation in the southern region of Japanand woody debris, stored pieces of woody debris
could be removed by typhoons and torrential rain,
since tropical cyclones frequently pass over southernand central Japan. Hence, most woody debris
recruited to streams falls into decay class 1 [12].
Using Eq. (5) and Eq. (6), we can estimate thepotential recruitment of woody debris. The total areaof landslide scars was extracted from aerial
photographs taken by the Geospatial Information
Authority of Japan after Tropical Storm Nanmadol
passed over the city of Asakura. The total area of thelandslide scars (Al) in the city of Asakura, as shownin Figure 1, is approximately 2.82 km2. Tree density
was measured at nine sites in the city of Asakura
during the field survey, giving a mean tree density(Dt) of 0.15 ± 0.1 trees/m2. The volume of woody
debris per piece was approximately 0.6 m3. Hence,the potential woody debris recruitment (Rn,l) causedby Tropical Storm Nanmadol is approximately
257,000 m3.

Fig. 7the Saga Ariake Fishery Association and the Japanese
Ministry of Land, Infrastructure, Transport andTourism removed approximately 2,000 m3 of woody
debris from the Ariake Sea, which is locateddownstream from Asakura. Hence, the minimum
amount of woody debris that flowed out of the city of
Asakura is 22,575 m3.

Fig. 8Driftwood flows to Terauchi Dam [13].

Fig. 9Driftwood flows to Egawa Dam [13].

In regard to the deposition of woody debris in theriver channel, we found 131 points at which woody
debris was deposited in the river channel in the cityof Asakura. Moreover, there were two main locationsof woody debris deposition: in the main river channel
and on the floodplain. Figure 10 shows the locationof woody debris deposition in the river.

Relationship between diameter and age ofwoody debris pieces.

In addition, an estimation of the woody debris thatflowed to the Egawa and Terauchi Dams revealed thatthe area of woody debris recruited to the Terauchi
Dam was 68,742 m2, with the Egawa Dam receiving
13,583 m2. By assuming that the depth of the woody
debris that flowed to the two dams was equal to themean diameter of the woody debris pieces, namely
approximately 0.25 m, we estimated the volume ofwoody debris recruitment to Terauchi Dam at
approximately 17,180 m3 and to Egawa Dam at
approximately 3,395 m3. The woody debris in the
Terauchi and Egawa Dams is outlined in yellow in
Figure 1. Figure 8 shows the driftwood above theTerauchi Dam, while Figure 9 shows the driftwood
above the Egawa Dam. As mentioned in the
introduction, the Fukuoka Ariake Fishery Association,

Fig. 10 Location of woody debris deposits in theriver.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Woody debris dams in the headwaters
In this study, we investigated eight sites in the cityof Asakura. All eight sites share steep gradientchannels, small stream channels, and first- or secondorder streams. Figure 11 plots the volume of thewoody debris dams for these eight sites. We
discovered a total of 31 woody debris dams at theseeight locations. The largest such dam was 953 m3 insize and was found at station 1. When reviewing theorigin of the woody debris, we found that landslides
and stream bank failures were the main sources of thewoody debris in the headwaters. Landslides can occur
in two locations: either above the stream channel ornear the stream channel. When the landslides
occurred and were mobilized down the slope
connected to the stream channel, the woody debris
was entrained by mass movement and deposited in
the stream valley. The woody debris thus deposited
created a dam in the stream channel. In contrast, inthe case of stream bank failure, this is theconsequence of erosion; here, the erosion process
may alter the soil mass of the stream bank, thereby
leading to the instability of the bank slope. Figure 12
shows the landslides and stream bank failure to
generate woody debris. Moreover, these sabo dams
play an important role in breaking the flow of woody
debris in the headwater streams; hence, we found that
additional woody debris was deposited on the sabodams, as shown in Figure 13.

Fig. 12 a) Stream bank failure; b) landslide
occurrence close to stream channel; and c)landslide occurrence above stream channel.
For five stations, the woody debris was classified
as decay class 1. For two stations, the decay wasclassified as decay class 4. At the final station, thewoody debris was classified as decay class 3. Figure
14 shows the state of decay of the woody debris dams
observed at each station.

Fig. 14 State of decay of woody debris dam.
CONCLUSION
Fig. 11 Volume of woody debris dam for eight sites.

The estimated amount of woody debris generated
by landslides related to Tropical Storm Nanmadol(2017) is approximately 257,000 m3. The majority of
the woody debris found in the city of Asakura wasfresh woody debris recruited by the landslides, debris
flow and stream bank failures caused by Tropical
Storm Nanmadol. We uncovered woody debris dams
(decay class 1) that are thought to have been newly
formed by the storm. Moreover, old woody debris
dams were also found at some stations, which are
believed to have formed before Tropical Storm
Nanmadol. Based on the concept of the woody debris
budget, woody debris storage is a common process innature. In headwater streams, landslides and stream
bank failures are the main sources of woody debris
recruitment. Woody debris was entrained
downstream by debris flows in the headwater stream
and floods in the large stream channel.

Fig. 13 Woody debris trapped at the sabo dam.

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SEE - Nagoya, Japan, Nov.12-14, 2018

GEOMATE, Vol. 14, Issue 44, pp. 109-114.
[6] Website:
http://www.qsr.mlit.go.jp/bousai_joho/H29hoku
bugouu.html[7] Abe K. and Ziemer R.R., Effect of Tree Roots on
Shallow-Seated Landslides, USDA Forest Service
Gen. Tech. Rep. PSW-GTR-130.1991, 1991, pp.
11-20.
[8] Website: http://www.jma.go.jp/jma/jma-eng/jmacenter/rsmc-hp-pub-eg/bstve_2017_m.html[9] Benda L.E., and Sias J.C., A Quantitative
Framework for Evaluating the Mass Balance of
In-stream Organic Debris, Forest Ecology andManagement, Vol. 172, 2013, pp. 1-16.
[10] Fraver S., Ringvall A., and Jonsson B.G.,
Refining Volume Estimates of Down Woody
Debris, Can. J. For. Res, Vol. 37, 2007, pp. 627633.
[11] Sakai Y., Ugawa S., Ishizuka S., Takahashi M.,
and Takenaka C., Wood Density and Carbon andNitrogen Concentrations in Deadwood of
Chamaecyparis obtuse and Crytomeria japonica,
Soil Science and Plant Nutrition, Vol. 58, 2012,
pp. 526-537.
[12] Seo J.I., Nakamura F., Nakano D., Ichiyanagi H.,
and Chun K.W., Factors Controlling the Fluvial
Export of Large Woody Debris, and its
Contribution to Organic Carbon Budgets at
Watershed Scales, WATER RESOURCESRESEARCH, Vol. 44, 2008, pp. 1-13.
[13] Website:
http://www.gsi.go.jp/BOUSAI/H29hukuoka_oo
ita-heavyrain.html

ACKNOWLEDGEMENTS
This study was supported by the Japan Society of
Civil Engineers, the Society for the Promotion ofConstruction Engineering, and the Social
Implementation Program on Climate Change
Adaptation Technology (SI-CAT). The authors are
grateful to the Japan Meteorological Agency for
rainfall data and the Geospatial Information
Authority of Japan for the aerial photographs oflandslides.
REFERENCES[1] Prescott C.E. and Laiho R., The Nutritional
Significant of Coarse Woody Debris in Three
Rocky Mountain Conniferous Forests, USDA
Forest Service Gen. Tech. Rep. PSW-GTR-181,
2002, pp. 381-392.
[2] Yan E., Wang X., and Huang j., Concept andClassification of Coarse Woody Debris in Forest
Ecosystems, Front. Biol. China, Vol. 1, 2006,
pp.76-84.
[3] Chen S.C., Chao Y.C., and Chan H.C., Typhoondominated Influence on Wood Debris
Distribution and Transportation in a High
Gradient Headwater Catchment, J. Mt. Sci, Vol 10,
Issue 4, 2013, pp. 509-521.
[4] Murakami Y., Shimizu O., Sato H., and Yamada
T., Sediment-related Disaster Caused by Typhoon
0310 (Etau) in Hidaka Region of Hokkaido, Japan.
International Journal of Erosion Control
Engineering, Vol. 1, 2008, pp. 30-37.
[5] Chaithong T., Komori D., Sukegawa Y., Touge Y.,
Mitobe Y., Anzai S., Landslides and Precipitation
Characteristics during the Typhoon Lionrock in
Iwate Prefecture, Japan. International Journal of790

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

REVERSIBLE JUMP MCMC METHOD FOR HIRARCHICALBAYESIAN MODEL SELECTION IN MA MODELS WITH
EXPONENTIAL NOISE
1

Suparman
Faculty of Teacher Training and Education, Ahmad Dahlan University, Indonesia

1

ABSTRACTThe noise in the moving average (MA) model is often assumed to be normally distributed. In applications it
is often found that the noise is exponentially distributed. MA model parameters include order, coefficient andnoise variance. This paper proposes a procedure to estimate MA model parameters containing exponential noise.
The estimatin of MA model parameters is done in a hierarchical Bayesian framework. But the posterior
distribution has a complex shape, the Bayes estimator cannot be determined exactly. The reversible jump Monte
Carlo Markov Chain (MCMC) method is proposed to determine the Bayes estimator of the MA model
parameters. The simulation result shows that this proposed method estimates MA model parameters well. As anapplication, MA model with exponential noise is used to model an environmental data.
Keywords: Bayesian, Moving Average, Exponential Noise, Reversible Jump MCMC

application it is often encountered that the data does
not meet the assumption of normality. The
estimation of MA models whose errors are
exponential distributions and whose order are notknown has not been investigated by researchers.
Reversible jump MCMC [7] has been applied inmany areas including in signal processing and intime series data analysis. The MCMC reversible
jump algorithm is used for model selection.
Punskaya [8] used the MCMC reversible jump
algorithm to select a piecewise AR model that has anormal distributed error. Grummer [9] used areversible jump for species selection. Pourhabib [10]used the MCMC reversible jump for the selection of
the number and locations of the pseudo points. Fox[11] used a reversible jump MCMC to select the
instrument calibration model. Newcombe [12] andKarakus [13] used a reversible jump MCMC for theselection of variables in regression. Steward [14]used a reversible jump MCMC to select non-linear
models in the volterra system.
This study proposes the reversible jump MCMC
method to estimate MA model parameters whose
error is exponential distributed where the order is
unknown. MA model parameters include order,
parameter coefficients, and error variance.

INTRODUCTION
The Autoregressive Model (AR) is a time seriesmodel used to model data in different areas of life.
AR models with normal distributed errors have been
extensively studied by various researchers. The AR
model with exponential error has been investigatedby various researchers. Shi [1] used a genetic
algorithm to estimate the exponential AR model of
AR. Sad [2] studied the AR model (1) whose error isexponential distributed. Larbi [3] used the Bayesianrobust method to obtain the optimal bayes estimatorfor AR models whose errors are exponentiallydistributed. In the above studies, the order of the AR
model is assumed to be known. Suparman [4]examined the AR model whose error is exponential
distributed but the model order is unknown. The AR
model was evaluated using MCMC reversible jump
algorithm.
Moving Average (MA) Model is a time seriesmodel that is similar to AR model. The MA model isalso used to model data in different areas of life.
Rossum [5] used the MA model as a continuous
quality control analysis for routine chemical tests.
The MA procedure is optimized using the MA bias
detection simulation procedure. Kordestani [6] used
an MA filter to accelerate the acceleration signal anddetermine the location of the damaged steel beam.
Although there are similarities between the AR
model and the MA model, the MA model estimation
is more difficult than the AR model estimation,
especially if the order of the order MA model is
unknown. In various studies, the MA model often
assumes that the error is normally distributed withmean 0 and the variance unknown. However, in the

METHOD
The parameter estimation is done in a bayesianframework. Bayesian estimation requires a priordustribution and likelihood function. The priordistribution and likelihood function are combined toobtain a posterior distribution. Under the quadratic
loss function, the bayes estimator is obtained by
791

SEE - Nagoya, Japan, Nov.12-14, 2018calculating the mean of the posterior distribution.
Because the posterior distribution has a complex
shape, the bayes estimator cannot be determined
analytically. MCMC is used to determine the bayes
estimator by creating a markov chain whose limit
distribution is close to the posterior distribution.
This markov chain is used to determine the bayes
estimator. In this study, the order of the MA modelis also a parameter that is estimated based on thedata. This makes the dimensions of the markov
chain a combination of several different
dimensioned spaces. So MCMC cannot be useddirectly. Therefore the Reversible Jump MCMC is
used to solve the problem.
The estimation procedure is as follows: First, thedetermination of the likelihood function, second theselection of prior distribution, third thedetermination of posterior distribution and the fourth
determination of the bayes estimator uses reversible
jump MCMC [7].

Let

the

Then MA(q) model is inversible if and onlyif ρ( q ) ∈ ]− 1,1 [q . Finally, the approximate likelihood
function of x can be written by:L( x q , ρ( r ) , λ )= λn − q exp− λ ∑ t = q +1 [ x t − ∑ j=1 G −1 (ρ j )z t − j ]nG −1 istheinverseof.
theBefore obtaining a posterior distribution, theprior distribution is selected.
Prior Distribution
The prior distribution is taken as follows. The
binomial distribution is chosen as the distribution forthe order q (q = 1, 2, ..., qmax)π(q µ) = Cqq max µq (1 − µ)1− q
Where qmax is the maximum for q and µ (0< µ <1) isa hyperparameter. The uniform distribution ischosen as the distribution for the vector coefficientρ( q )π(ρ( q ) q ) = U(−1,1)q

Where θ( q ) = (θ1 ,..., θq ) is the coefficient vector.

Also, the Jeffrey distribution is selected as the
distribution for parameter λRandom variable z t is the independent variable andπ(λ) ∝

the exponential distribution with parameter λ . The

1λThen, the hyperprior distribution for µ selected
uniform distribution at interval (0,1).
Let π(q, θ( q ) , λ, µ) be the prior distribution

probability function z t isf (z t λ) = λ exp− λz t
The variable transformation is used to transformfromvariablez
tovariablex.
Sofor (q, θ( q ) , λ, µ) . Since the conditional distribution

dz t
= 1.
dx t

of the parameter (q, θ( q ) , λ ) is given the hyper
parameter µ is π(q, θ( q ) , λ µ) =Therefore, the probability density function of x t isf ( x t λ) = λ exp− λ( x t − ∑ j=1 θ j z t − j )q.

π(q, θ( q ) , λ, µ)
π(µ)

, the

prior distribution for (q, θ( q ) , λ, µ) can be written as:Byπ(q, θ( q ) , λ, µ) = π(q, θ( q ) , λ µ)π(µ)

taking x1 = ... = x q = 0 , the likelihood function of

Posterior Distribution

x1 ,..., x n can be approximated by:

Let π(q, θ( q ) , λ, µ x ) be the posterior distribution

L ( x q , θ( q ) , λ )for (q, θ( q ) , λ, µ) . According to Bayes teorema, the= ∏ t = q +1 f ( x t λ)n=λtransformation

Bayesianqposterior distribution for (q, θ( q ) , λ, µ) is given as

exp− λ ∑ t = q +1 ( x t − ∑ j=1 θ j z t − j )nqtransformation G.

x t = ∑ j=1 θ j z t − j + z t ( t = 1,2,..., n )

n −q

and

q

Let x1 ,..., x n be n data following the following
MA (q) model:

x = ( x q+1 ,..., x n )regionG : θ( q ) ∈ Iq → ρ( q ) ∈ ]− 1,1 [Likelihood Function

Supposeinversibility

autocorrelation vector. By using transformation

The Bayesian method is used to estimate theparameters. Bayesian estimation requires a priority
possibility and distribution function.

z t = x t − ∑ j=1 θ j z t − j andbeρ( q ) = (ρ1 ,..., ρq ) is the sample inverse partial

RESULTS AND DISCUSSION

q

Iq

q

follows
792

SEE - Nagoya, Japan, Nov.12-14, 2018

π(q, θ( q ) , λ, µ x )ξ = (q, ρ( q ) ) be

Let

the

actualpoint(q )∝ L( x q, ρ( r ) , λ) π(q, θ , λ, µ)ξ* = (q + 1, ρ

∝ L( x q, ρ , λ) π(q, θ , λ µ)π(µ)

order from ξ = (q, ρ( q ) ) to ξ* = (q + 1, ρ

(q )

(r)

However, the Bayes estimator cannot be
determined analytically because the posterior
distribution of the θ parameter has a complex form.
To solve this problem, the reversible jump MCMC
algorithm [7] is used.

) is the new point. The birth of
(q* )

) is

Express q* = q + 1

defined in the following way.

and select random point v ~ U(−1,1) . Then, create a
new point ξ* = (q + 1, ρρREVERSIBLE JUMP MCMC

*

(q )

(q* )

) with= {ρ1* = ρ1 ,..., ρ*q(*) = ρq , ρ*q* = v}

Conversely, the transformation of the death oforder will change the MA coefficient, from q+1 to q.
Let ξ = (q + 1, ρ ( q +1) ) be the actual point andSuppose M = (q, θ , λ, µ) . The MCMC method(q )for simulating the distribution π(q, θ( q ) , λ, µ x ) is amethodthat
produceschain M1 ,..., M m which

(q* )

and

ξ* = (q, ρ( q ) ) is the new point. The death of order

ergodic
Markov
has a stationary

from ξ = (q + 1, ρ ( q +1) ) to ξ* = (q, ρ( q ) ) is defined in

distribution π(q, θ( q ) , λ, µ x ). The Markov chain

the following way. Express q* = q and create a new

M1 ,..., M m can be considered as a random variable

point ξ* = (q, ρ( q ) ) withhaving a distribution π(q, θ( q ) , λ, µ x ). Furthermore,ρMarkov chian M1 ,..., M m is used to estimate theparameter M. To realize this, the Gibbs algorithm isadopted.
The
simulationof
distribution(q )π(q, θ , λ, µ x ) consists of 3 steps : First,( q* )= {ρ1* = ρ1 ,..., ρ*q(*) = ρq }that ηn (ξ, ξ* )Supposeµ ~ B(q + 1, q max − q + 1)
Second, simulate λ ~ G (α, β) where α = n − q + 1

ηn (ξ, ξ* ) = min{1,and∑t = q +1

[ x t − ∑ j=1 G −1 (ρ j )z t − j ]Third, simulate π(q, ρ

q

(q )

(β* ) n − q
β

n − q +1

1q +1}
n − q q max − q

The acceptance probability for the death of orderis as follows:

1
n

are

respective the acceptance probability for the birth oforder and the acceptance probability for the death oforder. The acceptance probability for the birth oforder is as follows:

simulateβ=and ηd (ξ, ξ* )ηd (ξ, ξ* ) = min{1,x)

The distribution π(q, ρ( q ) x ) has a complex form
so that simulation of the distribution of π(q, ρ( q ) x )cannot be done exactly. Since the value of q is
unknown, the MCMC algorithm cannot be used tosimulate the distribution π(q, ρ( q ) x ) . Here, the
MCMC reversible jump algorithm (Green, 1995)
was adopted.
Let ξ = (q, ρ( q ) ) be the actual point of theMarkov chain. There are 3 types of transformation
used: order birth, order death and order change. Next,
let Nq be the probability of transformation from q to
q+1, let Dq be the probability of transformation fromq+1 to q, and let Cq be the probability of thetransformation from q to q.

(β* ) n − q +1
βn −q(n − q)q max − q}q +1

Change of Coefficient
Transformation of the change of coefficient will
not change the order. This transformation only willchange the MA coefficient. Let ξ = (q, ρ( q ) ) be theactual point and ξ* = (q* , ρThechangeto ξ* = (q* , ρof( p* )) is the new point.

coefficientfrom ξ = (q, ρ( q ) )) is defined in the following way.

Express q = q ,*( p* )

selectan

index

randomlyj∈ {1,..., q} , and select a point randomlyu ~ U(−1,1) . Then a new point ξ* = (q* , ρ
created withρ

Birth/Death of Order
The transformation of the birth of order willchange the MA model coefficient, from q to q + 1.

( q* )= {ρ1* = ρ1 ,..., ρ*j−1 = ρ j−1 , ρ*j = u ,ρ*j+1 = ρ j+1 ,..., ρ*q(*) = ρq }793

( p* )) isSEE - Nagoya, Japan, Nov.12-14, 2018

Let ηc (ξ, ξ* ) be the acceptance probability for

Average as Continuous Analytical Quality
Control Instrument Demonstrated for 24
Routine Chemistry Assays, Clinical Chemistry& Laboratory Medicine, Vol. 55, Issue. 8, p.
1142-1151.
[6] Kordestani, H., Xiang, Y-Q, Ye, X-W. (2018)
Output-Only Damage Detection of Steel Beam
Using Moving Average Filter. Shock &Vibration, Vol. 28, No. 1, p. 1-13.
[7] Green, P.J. (1995). Reversible Jump MCMC
Computation
andBayesian
Model
Determination. Biometrika, Vol. 82, p. 711-732.
[8] Punskaya, E., Andrieu, C., Doucet, A.,
Fitzgerald, W.J. (2002). Bayesian Curve Fitting
Using MCMC with Applications to Signal
Segmentation, IEEE Transactions on Signal
Processing, Vol. 50, No. 3, p. 747-758.
[9] Grummer, J.A., Bryson JR, R.W., Reeder, T.W.
(2014) Species Delimitation Using Bayes
Factors : Simulations and Application to the
Sceloporus Scalaris Species Group (Squamata:Phrynosomatidae). Syst. Biol, Vol. 63, No. 2, p.
119-133.
[10] Pourhabib, A., Liang, F., Ding, Y. (2014)
Bayesian Site Selection for Fast GaussianProcess Regression. IIE Transactions, Vol. 46, p.
543-555.
[11] Fox, M., Ickert, R.B. (2015) Model Selection
During Sample-Standard-Bracketing Using
Reversible Jump Markov Chain Monte Carlo,
Journal of Analytical Atomic Spectrometry, Vol.
30, Issue 10, p. 2208-2213.
[12] Newcombe, P.J., Ali, R.H., Blows, F.M.,
Provenzano, E., Pharoah, P.D., Caldas, C.,
Richardson, S. (2017) Weibull Regression with
Bayesian Variable Selection to Identify
Prognostic Tumour Markers of Breast Cancer
Survival, Statistical Methods in Medical
Research, Vol. 26, Issue. 1, p. 414-436.
[13] Steward, R.M., Rigdon, S.E. (2017) RiskAdjusted Monitoring of Healthcare Quality :Model Selection and Change-Point Estimation.
Quality & Reliability Engineering International,Vol. 33, Issue 5, p. 979-992.
[14] Karakus, O., Altinkaya, M.A., Kuruoglu, E.E.
(2017) Bayesian Volterra System Identification
Using Reversible Jump MCMC Algorithm,
Signal Processing, Vol. 141, p. 125-136.

the change of coefficient. The acceptance probability
for the change of coefficient is as follows:  β* α ηc (ξ, ξ ) = min 1,   β   *

CONCLUSION
This study proposes an estimation of MA
model parameters whose error is exponential
distribution and the order is unknown. Parameters
could not be estimated using the MCMC algorithm
because the order of the MA model is unknown.
The MCMC reversible jump algorithm was a
method that can be used to estimate the parametersof the MA model even though the order is unknown.
The advantages of this method are both the orderand the MA model coefficient that can be estimatedsimultaneously. In addition, the resulting MA modelis an MA model that satisfies an inversible condition.
ACKNOWLEDGEMENTS
The authors would like to thank Ahmad Dahlan
University in Yogyakarta Indonesia for the awarded
research grant. Acknowledgments are also given to
the Ministry of Research, Technology and Higher
Education of the Republic of Indonesia which hasprovided grants to attend seminar in Japan.
REFERENCES[1] Shi, Z. and Aoyama, H. (1997). Estimation of
the Exponential Autoregressive time seriesmodel by using the genetic algorithm, Journal ofSound and Vibration, Vol. 205(3), p. 309-321.
[2] Sad, N. (1999). On Exponential Autoregressive
Time Series Models, J. Math, Vol. 29(1), p. 97101.
[3] Larbi, L. and Fellag, H. (2016). Robust
Bayesian Analysis of an Autoregressive Modelwith Exponential Innovations, Afr. Stat., Vol.
11(1), p. 955-964.
[4] Suparman. (2017) New Estimation in AR
Models with Exponential White Noise by Using
Reversible
Jump
MCMC
Algorithm,
Proceeding of the Third International
Conference on Science, Engineering, andEnvironment, p. 103-106, Brisbane Australia.
[5] Rossum, H.H.V., Kemperman, H. (2017)
Implementation and Application of Moving794

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

GAP COMPETENCY ANALYSIS FOR EMPLOYEE OF ANIMAL FEED
WAREHOUSE DEPARTMENT

1,2,3,4

Siti Rochaeni1, Siska Nurita2, Eny Dwiningsih3 and Farahdita Soeyatno 4
Faculty of Science and Technology, Syarif Hidayatullah State Islamic University Jakarta, Indonesia

ABSTRACTPT Japfa Comfeed Indonesia Tbk is second with 24% market share. In order for Japfa to seize market sharein the first position, the management realize the need for competent human resources. By knowing the employeecompetency gaps in the Livestock Warehouse Department, the company can design a program to improve thequality of human resources for the achievement of better quality objectives. The purpose of this research is toanalyze the gap competency, find alternative solutions, and give the recommendation to upgrade competency ofthe employee. The data collected used Likert Scale, processed test data validation using Product Moment
Pearson correlation technique formula and analyze by gap analysis and importance performance analysis (IPA)
matrix. The value of competency gap is obtained by fulfilling importance level and capability level. Opinions
used are opinions by managers and employees. The highest negative importance gap for core competence is theability to anticipate, identify and solve the problem, while for field competence is mastering the way computer
operate. The highest negative capability gap value for core competence is the ability to reach the target forpermanent employees and ability to work with high spirits for outsourced employees, while for field competence
is mastering how to operate computer permanent employees and master the system of implementation of the sealof vehicle loading in accordance with work instructions for employees outsourcing.
Keywords: Core competency, Field competency, Gap, Importance, Capability

INTRODUCTIONMETHODS

The poultry feed market is dominated by four
players: PT Charoen Pokphand Indonesia Tbk, PT
Japfa Comfeed Indonesia Tbk, PT Malindo Feedmill
Tbk, and PT Wonokoyo Jaya Corporindo which has
a combined market share of about 80%. PT Charoen
Pokphand Tbk is a poultry feed company which
controls the market in the first rank with a market
share of 34%. PT Japfa Comfeed Indonesia Tbk issecond with 24% market share. In order for Japfa toseize market share in the first position, themanagement realize the need for competent humanresources. To improve the competence of humanresources, companies need to consider thecompetency gap or employee competency gap at thistime by looking at the extent to which employees
have the competence expected by the company,
especially employees of the Department of Animal
Feed Warehouse who handle the finished productand directly related to product damage that occurred.
The extent to which employees in this department
master the necessary skills and the extent to which
employees consider competence to be important intheir work. By knowing the employee competency
gaps in the Livestock Warehouse Department, thecompany can design a program to improve thequality of human resources for the achievement ofbetter quality objectives.

This research was conducted at PT Japfa
Comfeed Indonesia Tbk Tangerang Unit. for 3(three) months from July to September 2017. The
selection of research sites was conductedpurposively (deliberately) with the consideration thatPT Japfa Comfeed Indonesia Tbk needs
improvement in the quality of its human resources,
especially the Animal Warehouse Section. Primarydata was obtained directly using questionnaire.
Secondary data is obtained from documents andreports of PT Japfa Comfeed Indonesia Tbk
Tangerang Unit. Data collection was obtained bydirect interview using questionnaire.
Respondents in this research are employees of
PT Japfa Comfeed Indonesia Tbk Unit Tangerang
Department of Animal Feed Warehouse whichamounts to 60 people consisting of 20 employees
who work in five work units namely (1)administrators; (2) production handover; (3)implementing loading and unloading; (4) forklift
operators; (5) cleaners, and 40 outsourcing
employees who assist in the process of over sacking
and loading and unloading of feed.
The data collected consisted of data on
importance and data about the ability to use Likert
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Scale with range 1 to 5. Data of importance ranging
very unimportant to very important. data capabilities
ranging from very inadequate to very capable.
Before the data is processed test data validation
using Product Moment Pearson correlation
technique formula as follows:𝑟𝑟 =𝑛𝑛(Σ𝑥𝑥𝑥𝑥)−(Σ𝑥𝑥Σ𝑦𝑦)Competency Gap Analysis
The value of importance for each competency
required is as follows Setiarso (2009) in Chandra(2011: 27) :𝑁𝑁𝑁𝑁𝑁𝑁 =(1)�[(𝑛𝑛Σ𝑥𝑥 2 )−(Σ𝑥𝑥)2 )][(𝑛𝑛Σ𝑦𝑦 2 )−(Σ𝑦𝑦 2 )]Test reliability using Cronbach Alpha techniquewith formula as follows:
Σ𝜎𝜎𝑏𝑏 2

𝑟𝑟11 = �𝑘𝑘−1� �1 − 𝜎𝜎𝑡𝑡 2 �

𝑁𝑁𝑁𝑁𝑁𝑁 =

(2)

𝜎𝜎 =

(Σ𝑥𝑥)2𝑛𝑛

The tabulation form used for this study can beseen in table 1 below.
Table 1 Tabulation of Competency Gap Analysis

I
M
P
O
R
T
A
N
C
E

ComImportance

Capability

Gap

ce
Full-

1

2

3

4

5

Nki

1

2

3

4

5

Npi

=

time/

Nki-

out-

Npi

(5)

According to Tjiptono (2011), this technique was
first proposed by Martilla and James in 1977 in theirarticle entitled "Importance-Performance Analysis"(Oscar & Pambudi, 2014: 5. The IPA Matrix(Importance-Performance Analysis) is clearly anddetail presented in Fig. 1.

Where :
Σσ2 = Varietyx= Value of the selected scoren= Number of instances

peten-

𝑅𝑅

Importance Perfoemance Analysis (IPA)

(3)

𝑛𝑛

(𝑃𝑃1×1)+(𝑃𝑃2×2)+(𝑃𝑃3×3)+(𝑃𝑃4×4)+(𝑃𝑃5×5)

Where :
NPi = Values of competence i
P1 = Number of respondents with answer 1
P2 = Number of respondents with answer 2P3 = Number of respondents with answer 3
P4 = Number of respondents with answer 4
P5 = Number of respondents with answer 5

The formula to find the value of the variety is:Σ𝑥𝑥 2 −

(4)

The formula for calculating the value ofcapability for the knowledge required as follows:

Where :
r11
= Instrument reliabilityk= Many points of the statement
αt2= Total varianceΣ αb2 = The number of variance items

2

𝑅𝑅

Where :
Nki = Value of importance to competence i
K1 = Number of respondents with answer 1
K2 = Number of respondents with answer 2
K3 = Number of respondents with answer 3
K4 = Number of respondents with answer 4
K5 = Number of respondents with answer 5

Where:r= Coefficient of validity soughtn= Number of respondentsx= Scores of each statement xy= Score of each statement y𝑘𝑘(𝐾𝐾1×1)+(𝐾𝐾2×2)+(𝐾𝐾3×3)+(𝐾𝐾4×4)+(𝐾𝐾5×5)

sourcing

Kuadran I
Concentrate HereHigh Importance
Low Performance

Kuadran II
Keep Up Good WorkHigh ImportanceHigh Performance

Kuadran III
Low Priority
Low Importance
Low Performance

Kuadran IV
Possible Overkill
Low ImportanceHigh Performance

1.

PERFORMANCE

2.
3.

Fig. 2

4. etc796

Matrix IPA.

SEE - Nagoya, Japan, Nov.12-14, 2018

Outsourcing Employees
The core competency that has the highest
average value of interest is the ability to thinkcreatively, with an average value of 4.03.For corecompetencies that have the lowest average interest
compared to other core competencies is the ability tomake changes with an average rating of 3.53. The
core competencies that have a positive gap value are
creative thinking ability with a gap value of 0.03.
While other competencies have negative importancegaps. The core competencies that have the biggest
negative gap value is the ability to anticipate,
identify and solve the problem with the negative gapof 1.41.
There is no field competency that has an averagevalue of interest ≥ 4.00. The importance of thecompetence of the field of outsourcing employees all
has a negative gap value. Competency field that has
the value of the biggest negative interest gap is theway to operate the computer with negative value
1.41.

RESULTSThe value of competency gap is obtained byfulfilling importance level and capability level.
Opinions used are opinions by managers andemployees. The value of competency gap is obtainedby calculating the difference between the averagevalue importance level and capability level of theemployees with the value given by the manager.
Importance Level
The
assessedcompetencies
arecorecompetencies belonging to the Result Orientation,
Team Focus and Global View categories that break
down into 18 core competencies. In addition, there
are 10 field competencies required by the
Department of Animal Feed Warehouse. Assessment
using five Likert scales.
Permanent Employees
Six core competencies have an average value ≥4.00 that is the ability to work together; the ability tocomplete tasks in teams effectively; ability to respectcolleagues; the ability to think ahead; ability to workwith high spirits and ability to anticipate challenges.
The core competency that has the highest average
importance level is the ability to work together, withan average value of 4.50. The core competencies
that have the lowest average importance levelcompared to other core competencies are the ability
to make changes and the ability to express opinions
well, with an average importance level of 3.50. The
core competency that has the largest positive
importance gap is the ability to work with 0.50.
While the other 14 core competencies have anegative gap value.
Seven field competencies have an average
importance level ≥ 4.00, while the othercompetencies have an average importance level<4.00. Competence field that has the highest averagevalue of interest is mastering the system of feeding
identity in the warehouse in accordance with work
instructions and mastering the way of loading andunloading the feed in the warehouse in accordancewith work instructions with a value of 4.56.
Competence field that has the lowest average
importance level is mastered how to operate thecomputer, that is with the importance of 3.67. The
competence of the field that has the biggest negative
gap value is mastering how to operate the computer,that is with a negative value of 1.33.

Capability Level
The
assessedcompetencies
arecorecompetencies belonging to the Result Orientation,
Team Focus and Global View categories. In addition,
there are 10 field competencies required by the
Department of Animal Feed Warehouse. Assessment
using five Likert scales.
Permanent Employees
There is one core competency that has anaverage capability value of ≥ 4.00. The corecompetency that has the highest average value ofcapability is the ability to respect colleagues, with anaverage value of mastery of 4.22. The corecompetencies that have the lowest level of masteryare the ability to take advantage of opportunities, theability to think creatively and the ability to adjust tochange, with the average value of mastery of 3.39.
There are two core competencies that have morethan one gap value. Core competencies that have anegative gap value with a value of more than one
that is the ability to achieve targets and the ability towork with high spirits, effectively and definitely.
There is one competency field that has anaverage value of capability of ≥ 4.00. While thecompetence of other fields has an average value ofcapability value between 3.00 - 3.99. There is one
competency that has a value of less than one
capability gap. Competency field that has the biggest
negative gap value is mastering the way to operate
the computer, that is a negative gap of 1.67.

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Outsourcing Employees
The core competencies that have the highest
average value of capability are the ability toanticipate the challenge; have the nature of want tolearn, always try, add knowledge and new science;
ability to see problems in micro or macro with value
3,88. While the competence that has the lowest
average value of capability is the ability to thinkcreatively with an average value of mastery of 3.50.
Competence which has the biggest negative gap
value is the ability to work with a high spirit that iswith negative gap value 1.31.
Field competency that mainly mastered byoutsourcing employees is mastering the system ofhandling of food damaged/leaked in accordance withwork instructions that is with the average value ofmastery of 4.00. For the field competencies thathave the lowest average value of capability is tomaster the system of seal implementation vehicle fit
in accordance with work instructions that is with anaverage value of 3.53. Field competency that has thevalue of the biggest negative capability gap ismastering the system of the implementation of theseal of the vehicle loaded in accordance with work
instructions, that is with the negative gap 1.47.

The overall conformity for field competencies is90%. The field competency that has the highest levelof conformity is mastering how to drive a forklift inaccordance with work instructions with a value of
103%. The smallest level of conformity is owned bymastering the knowledge of the type of productstored in the warehouse with an 80% conformity
value.
Outsourcing Employees
The overall conformity for core competencies is
99.22%. The core competency that has the highest
level of conformity that is the nature of want tolearn, always trying to increase knowledge and newscience, that is with the value of 108%. The smallest
degree of conformity is shared by the corecompetency of creative thinking ability with an 87%
conformity score.
The overall conformity for field competencies is
99.00%. The field competency that has the highest
level of conformity is mastering the handling systemof damaged/leaked feed in accordance with work
instructions, with a value of 111%. The smallest
degree of conformity is owned by the competence ofthe field to control the system of the seal of theloaded vehicle in accordance with the work
instructions with 93% suitability value.

Conformity Level
The results of the assessment of importance level
and capability level will result in a calculation of thelevel of conformity between importance level andcapability level of core competence and fieldcompetence. The level of conformity is the result ofcomparison of the total score of capability with thenumber of importance scores. The results show how
far the employees capable the competence inaccordance with the importance of thesecompetencies to be mastered in their work.

DISCUSSIONS
The ratings of importance level, capability level,
and conformity level are used to determine
coordinate points. The coordinate points used fordrawing a cartesius diagram. There is four
placement in the cartesius diagram, which separated
by two perpendicular lines. The first quadrant (I) is
located to the upper left, the second quadrant (II) ison the upper right, the third quadrant (III) is on thelower left, and the fourth quadrant (IV) is on thelower right. The position of each core competency inthe four quadrants can be used as a tool in providing
alternative strategies to improve the level ofcompetence of employees.
Quadrant I shows competencies that areconsidered important by permanent employees but
have not demonstrated good mastery or
performance, so companies need to improve thecompetence controls included in this quadrant.
These competencies are a top priority for
improvement. Quadrant II shows competencies thatare considered important by permanent employees
and have been mastered well. The competencies inthis quadrant should be maintained by the company.
Quadrant III shows competencies that are consideredless important and less controlled by permanent
employees so that companies do not need toprioritize or give more attention to these

Permanent Employees
The average overall competence of corecompetence is 93.83%. The core competencies thathave the highest level of conformity are the ability toshare and appreciate the contribution of work andthe ability to make changes with the value of 103%.
There are four competencies that have a percentage
of less than 90%, there are ability to reach the target;
creative thinking ability; ability to work together andable to adjust to change. The smallest level ofconformity is owned by the core competence ofachieving the target value of 83%. The overall value
shows there are two core competencies
corresponding to the importance (conformity level ≥100%). While the other 16 core competencies havenot been in accordance with the importance (level ofconformity ≤ 100%).
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SEE - Nagoya, Japan, Nov.12-14, 2018

competencies. Quadrant IV indicates thatcompetence is considered less important but theemployees master it well so that companies better
allocate resources to increase the competence toother competencies that have a higher priority level.

of products stored in the warehouse. Competence
contained in quadrant II is mastering the lotting
system feed in the warehouse in accordance withwork instructions, mastering the system of feeding
identity in the warehouse in accordance with work
instructions, master the knowledge of the flow offeed in the warehouse in accordance with work
instructions, mastering knowledge of the groove of
feed warehouse in accordance with work
instructions, and master the way of loading andunloading the feed in the warehouse in accordancewith work instructions. Competence which is inquadrant III is mastering system implementation ofvehicle seal in accordance with work instructions
and mastered how to operate a computer.
Competencies that are in quadrant IV is Mastering
the handling system broken or leaking feed inaccordance with work instructions and Mastering
how to drive a forklift in accordance with work
instructions.
The field competencies of the outsourced
employees in quadrant I is to master the food lotting
system in the warehouse in accordance with work
instructions and master the knowledge about thetype of product stored in the warehouse. The fieldcompetencies in quadrant II is to master theknowledge of the groove of feed in the warehouse inaccordance with the work instructions, to master thesystem of feeding identity in the warehouse inaccordance with the work instructions, to master theloading and unloading of the warehouse inaccordance with the work instructions, feed from thewarehouse in accordance with work instructions,master the way to ride the forklift in accordance withwork instructions. The field competencies that is inquadrant III is to control the implementation of theseal of the loaded vehicle in accordance with thework instructions. The field competencies inquadrant IV is to master the handling system ofdamaged or leaked feed in accordance with the work
instructions and master the way to operate thecomputer.

Core competencies
The core competencies of permanent employees
in quadrant I is the ability to reach the target. The
competencies contained in quadrant II are the ability
to work in high spirits, the ability to effectively
complete the tasks of the team, the ability to work
together, the ability to respect colleagues, the ability
to anticipate challenges, and the ability to thinkahead. The competencies in quadrant III are theability to take advantage of opportunities, the ability
to think creatively, the ability to make changes, theability to convey a good opinion, the nature of thedesire to learn, always trying to increase knowledge
and new knowledge, the ability to adjust to change,
the ability to see problems from the scope of micro
and macro, and ability not limited to knowledge andskills in the field of work alone but be open to otherfields. The competencies in quadrant IV are theability to anticipate, identify and solve problems,
ability to share and appreciate work contribution,and competence of innovative thinking.
The core competencies of outsourced employees
in quadrant I are the ability to work with high spirits,
the ability to take advantage of opportunities, theability to think creatively, the ability to work
together, the ability to think innovatively, and theability not to limit themselves to knowledge andskills in the field of work but is open to the fieldothers. The competencies contained in quadrant II
are the ability to achieve the target, the ability torespect the co-workers, the ability to think ahead,
and the ability to see the problems of micro andmacro. The competencies in the quadrant III are theability to share and appreciate the contribution ofwork and the ability to make changes, the ability to
express opinions well. The competencies in thequadrant IV are the ability to anticipate, identify andsolve problems, the ability to effectively complete
the tasks of the team, the ability to anticipate
challenges, the ability to recognize and solve
problems outside the scope of work, have the natureof learning, always trying to increase knowledge andnew knowledge, and ability to adjust to change.

CONCLUSION
The conclusions that can be drawn from thisresearch are:
1. The highest negative importance gap for corecompetence is the ability to anticipate, identify
and solve the problem, while for fieldcompetence is mastering the way computer
operate.
2. The highest negative capability gap value forcore competence is the ability to reach thetarget for permanent employees and ability towork with high spirits for outsourced

Field Competencies
The field competencies of permanent employees
in quadrant I is to master the knowledge of the types
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employees, while for field competence ismastering how to operate computer permanent
employees and master the system of
implementation of the seal of vehicle loadingin accordance with work instructions for
employees outsourcing.

Pengetahuan (Knowledge Gap) Karyawan PT
Aneka Tambang Tbk Unit Geomin [Skripsi].
Bogor: Institut Pertanian Bogor, Fakultas
Ekonomi dan Manajemen; 2011.
[3] ICRA Indonesian Research. “Overview of theIndonesian Animal Feed Industry 2012”.
Desember 2012. Artikel diakses pada 19 Januari
2016 dari www.icraindonesia.com.
[4] Oscar O & Pambudi J. Analisis Kepuasan
Pelanggan dengan Important Performance
Analysis di SBU Laboratory Cibitung PT
Sucofindo. J@TI Undip, 2014;IX: 1.
[5] Ramadhan, MR, Yoanita Yniati & Sugih
Arijanto. Analisis Beban Kerja dan Pengukuran
Gap Kompetensi Teknisi Laboratorium Umum
dan Fakltas Z PTS XYZ. Reka Integra: Jurnal
Online Institut Teknologi Nasional, 2014; 02:384.
[6] Setiarso, B dkk. 2009. Penerapan Knowledge
Management pada Organisasi. (Yogyakarta:
Graha Ilmu, 2004).
[7] Spencer, Lyle dan Signe Spencer. Competence at
Work : Models for Superior Performance.
(Canada: Wiley, 1993)[8] Suroto,
Adi.
“Gap
Analysis(Analisa
Kesenjangan)”. 28 Juli 2015. Artikel diaksespada 2 Januari 2017 pukul 22.00 WIB dari
http://sis.binus.ac.id/2015/07/28/gap-analysisanalisa-kesenjangan/

RECOMMENDATION
Recommendations that can be given based on
this research for the company are:
1. Efforts that can be made in order to improvethe core competence of employees is to involve
employees
intargeting,compensation
improvement, and carry out training anddevelopment of human resources capabilities.
2. Efforts that can be done in order to improve thefield competencies of employees are training
methods of self-study.
REFERENCES[1] CPIN Company Presentation dalam Ben Santoso.
Indonesia’s Growing Appetite for Animal
Protein An Overview of Business Models,
Opportunities and Strategies. 2016. DBS Asian
Insights Sector Briefing 21.
[2] Chandra, Leily Purnama. Analisis Kesenjangan

800

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ENVIRONMENTAL REGENERATION AND MANAGEMENT IN
PARTNERSHIP IN THE NORTHWEST OF ENGLAND
Tomoko Miyagawa1, Clare Olver2, Noriko Otsuka3, and Hirokazu Abe4
Faculty of Systems Engineering, Wakayama University, Japan; 2The Mersey Forest, the UK;
3
ILS Institut für Landes- und Stadtentwicklungsforschung gGmbH, Germany;
4
Cyber Media Centre, Osaka University, Japan

1

ABSTRACT
Built environment and cultural heritage are important aspects to improve the quality of life in environmental
regeneration and management. This paper aims to compare two case studies to examine partnership forenvironmental regeneration and management in post-industrial landscapes in the northwest of England:conservation and interpretation of the salt heritage at Northwich Woodlands, and landscaping former coalfields
with artworks at Bold Forest Park, St.Helens. Study methods used are literature reviews and face-to-faceinterviews with representatives from partnership organisations, e.g. Mersey Forest, local authority officers, andFriends of Anderton and Marbury. From the results, characteristics of the two projects became apparent with
distinctive focuses: industrial heritage in Northwich Woodlands; and creating a focal point using collaborative
artworks in St. Helens. Similarities are also found in outcomes of environmental regeneration to create wildlife
areas with some statutory designations, and partnership patterns integrating sectors from public, private, and thecommunity. For both case studies, the overriding issue is being able to develop the resources and partnerships toenable the sites to be managed and thus cherished by their communities in the long term.
Keywords: Post-industrial landscapes; Industrial Heritage; Art Projects; Community Participationdifficult to be noticed [5]. In this way, landscape
improvements can be undertaken with approval of thecommunity and can empower the community to
become engaged in long-term landscape management[1]. Therefore, creating links between the landscapeand the people is inevitable for sustainability of thecommunity and the environment [6]. Furthermore,
the process can create opportunities to enhancecommunity empowerment through local enthusiasm[7]. Partnership for community scale GI has beenclassified into distinctive typology patterns bycharacteristic, governance, and activity focuses
which enables to analyse creation and management ofGI from local level to city-scale [8]. In terms of thepartnership capacity of the community, continuous
public sector support is also necessary in long-term
management in green space [9]. Therefore,
environmental regeneration and management in
partnership is becoming more recognised.
As a way of engaging with the community, art
in the landscape is found in many cases. Artworks
have been discussed to increase attractiveness forvisitors and being a touristic destination, as well as tohave an impact on regionally and nationally byattracting the media and the wider community which
can support with increasing revenue and future
funding opportunities [1].

INTRODUCTION
Participative Environmental Regeneration in
Creation of Post-industrial Landscapes in the UK
Post-industrial landscapes are brought by‘radical transformation by the industrial era’, i.e.,
mining, in European landscape, one of the first to be
faced with ‘the need to restore and give new purposes
to damaged industrial landscapes’ [1]. However, insuch damaged post-industrial landscapes, there areunused or underused lands, i.e., brownfields withunique flora and fauna, and industrial heritage insome cases [2]. In addition, in recent years, postindustrial landscapes are considered to be potentialsites for creating Green Infrastructure (GI) to improve‘the health and quality of life’ for the community byan ‘interconnected network’ with ecological process[3], [4] of blue (water) and green (open spaces)
systems [5].
In the UK, processes of environmental
regeneration in post-industrial landscapes arerecognised in parallel to community participation in
partnership with volunteer sectors and often with thecommunity, owing to the British Urban Policies tosupport physical regeneration with socio-economic
regeneration [1]. Because some of these sites are notalways recognised by the local community due to alack of infrastructure or its location they can be

Aims of the study and study methods
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SEE - Nagoya, Japan, Nov.12-14, 2018

This paper aims to compare two case studies to
examine the role of partnership for environmental
regeneration and management in post-industrial
landscapes as follows. It will focus on the
improvement of the built environment and cultural
heritage perspectives; conservation of industrial
heritage as a result of salt production at Northwich
Woodlands, and landscaping former coalfields with
an iconic artwork called ‘Dream’ at Bold Forest Park,
St. Helens. There has been little discussion about theenhancement of local distinctiveness and the qualityof life in brownfield land regeneration [6]. Study
methods used are literature reviews regarding on
environmental regeneration and cultural heritage andinterviews with four representatives of The Mersey
Forest, two local authority officers from St. Helens
Council, one officer from Cheshire West and Chester
Council, and one representative from the Community
Forest Trust, and two representatives from the
Friends of Anderton and Marbury.
Both projects consist of multiple land-uses andlandowners in the urban fringe in the Northwest of
England. Northwich Woodlands are located next to
the town centre of Northwich in Cheshire, and Bold

Colliers Moss
CommonKey
Forest Park Boundary
Green Belt
Recreation Hubs

Brickfields

Railway Station

Clock Face
Country Park
Sutton Manor
Mersey Valley Golf
and Country ClubKey Walking Routes
Rail Station Links
Preferred Road
Routes
Proposed
Bridleways
Development
Opportunity
Site
Cycle
Centre0
2,000
metresFig 3. A map of the Bold Forest Park [12] with someamendments
Forest Park is in the south of St. Helens inMerseyside, within the Liverpool City Region (Fig 13). Interestingly, these projects are also connected by
Sankey and St. Helens canals in St. Helens and theRiver Weaver in Northwich navigating to the River
Mersey for transporting salt and coal. These are key
projects of The Mersey Forest, one of two
Community Forests in the Northwest of Englandsince 1991.
The Mersey Forest has been leading apartnership with landowners and partners to manage
long-term landscape management for over twenty
years, and has ‘evolved from a governmental inspiredorganisation to a community empoweredorganisation’ [5]. It has supported the community to
set up friends groups for anyone to join to manage andundertaking range of activities and events on green
spaces since 1998 [13].

Fig.1 A map of case study areas by referencing [10]with some amendments

CASE STUDIES OF PARTNERSHIPS ON
ENVIRONMENTAL REGENERATION AND
MANAGEMENT

Budworth Mere
Trent and
Mersey Canal
MarburyCountry Park
Anderton
Lion Salt
Nature Park Hopyards
Works
Wood
Dairy House
Meadows
Anderton
Boat Lift
Uplands
Wood
Neumann’s
Flash
River
WeaverCarey Park
Ashton’s
Flash
Furey
Wood

Outlines of case studies
Both case studies are good practice examples ofpost-industrial environmental regeneration whichhave supported the change in landscape that have
improved the quality of the environment. Northwich
Woodlands have undergone ground condition
improvements to remediate past activities of saltmining, through brine extraction and subsequentdeposits of lime wastes (Table 1). Due to theexcessive mining and extraction in the past, sudden
historic subsidence has created several pools (known
locally as “flashes”) and altered the flow of water
courses. As a result, there are a variety of waterways
and wetland areas visited by people for bird watching
and recreation.
Northwich Woodlands is comprised of a variety

Northwich Town Centre

Fig. 2 A map of the Northwich Woodlands [11]802SEE - Nagoya, Japan, Nov.12-14, 2018

Lottery. It is managed by the ranger service from theCheshire West and Chester Council and supported by
the community and local Friends Group FoAM, it has
also received the Green Flag Award. This is thebenchmark national standard, which recognises andrewards the best green spaces in the country. Forprotection for wildlife and green space, a Site ofSpecial Scientific Interest (Carey Park) [14], seven
Local Wildlife Sites [14], and a Green Belt [14]-[16]for conserving undeveloped green fields by British
planning system have been designated.
Fig.6
illustrates Ashton’s Flashes, in fragile foundation bysubsidence [14] to limit accesses by fences around thesite. It is now used for grazing in dry seasons andbecoming a marshland in wet seasons [2].

of green spaces, including Marbury Country Park, aformer country estate with a formal landscape;grazing land at Ashton’s Flash; and community
woodlands owned by the Forestry Commission atUplands and Hopyards Woodland.
Northwich
Woodlands are located along the Trent and Mersey
Canal with the size of 315hectares, the total sum ofgreen spaces with some private lands (Fig. 2).
Lion Salt Works, recently completed
conservation works and opened as a museum in 2015
to disseminate local history and industry of saltmaking, and Anderton Boat Lift, constructed in 1875
for lifting about 15 meters high to connect the Trent
and Mersey Canal to the River Weaver which had aconservation work in 2002, along with thedevelopment of marinas to travel by waterways [2].
These conservation projects were mainly funded by
Northwest Regional Development Agency, agovernment organisation which promoted regional
development (abolished in 2012), and Heritage
Lottery Fund supported by the proceeds of National
Table 1 Outline of the Northwich Woodlands
Project name(size of sites)
Past industrial
activities
Landscapeschanges
Environmental
regenerationand types ofgreen space
Placesofinterestsofgreen space
Characteristicsof the projects
and statutory
designations
Fundings(main funders)Local
partnerships
and their roles
CommunitygroupsOther
localgroupsEventsandActivities on
sitesManagement
andresponsibleorganisations
Long
term
management
plans

The Northwich Woodlands (315ha)

Fig. 4 Lion Salt Works

Salt-mining, brine extraction, anddeposits of lime wastes
Subsidences to form pools andcreation of watercourses for saltmining and industrial activities
Pools and watercourses, undulating
landforms, and woodlands byenvironmental improvements andlandscaping
Bird watching places and to visit
industrial heritage (Lion Salt Works;
Anderton Boat Lift), travelling
waterways
Conservation of industrial heritage;
Green Flag Award, Site of Special
Scientific Interest (Witton Mill
Meadow)[14], 7 Sites of Biological
Importance[14], Green Belt[15], [16]Northwest Regional Developmente
Agency, Heritage Lottery Fund
Mersey Forest, Cheshire West andChester Council, local industries andbusinesses, landowners, residents, andcommunity and local groups
Friends of Anderton and Marbury

Fig.5 Anderton Boat Lift

Fig. 6 Ashton’s flash
Bold Forest Park was formerly a moss land withdiverse wildlife and nature. After coal-mining andquarrying activities during the 1950s to the 1980s, a
programme of environmental regeneration wasundertaken in the 1990s to create green spaces
through the reclamation of spoil heaps into
community woodland (Table 2). Bold Forest Parkalso includes privately owned agricultural land,
designated as a Green Belt [12], [17], [18] (Fig.3), as
well as protected areas for wildlife. This includes a
Local Nature Reserve (Colliers Moss Common
North) [12], and 11 Local Wildlife Sites [12] in the
project. The undulating landscapes created by spoil
heaps resulting from coal-mining activities (Fig.7)
and soil generated by housing development are now

SaltscapeCommunity
Forum;
Northwich Business Improvement
Districts; Lion Salt Works Trust;Cheshire Wildlife Trust; Canal andRiver Trust; Groundwork Cheshire,
Lancashire, Merseyside; Cheshire
West Archives; Northwest GeologicalSociety
Events by community and localgroups, Exhibition about Wildlife of
the Northwich Woodlands
Areawide management by rangers
with volunteers from community andlocal groups
Securing the budget for the rangers

803

SEE - Nagoya, Japan, Nov.12-14, 2018

becoming new landmarks with great views, such as
Sutton Manor.
Bold Forest Park consists of five green spaces,
320 hectares in total, such as Colliers Moss Common
with a variety of wildlife areas, as well as woodlands
and grassland owned by the Forestry Commission.
There is a private owned golf course, an area of 51.5
hectares, included in the Bold Forest Park Area
Action Plan and called to be ‘recreation hubs’ withgreen spaces [12]. Farmlands are located aroundgreen spaces with 63 percent of an area size of 1159
hectares of the park, also designated as Green Belt
(Fig. 3) [12].
The woodlands and marshlands of Colliers Moss
Common (North and South) are connected by apedestrian bridge over the railway line between
Manchester and Liverpool. Community Art has beenused on the site to engage with the local community,
such as “pit wheels” used for coal mining are featured
in the design of a pedestrian bridge which has become
a focal point of the Common (Fig.8).

There is also a Big Art Project called ‘Dream’
mainly funded by Northwest Regional Development
Agency and European Regional Development Fund[19]. The sculpture is the key output of collaborative
work of the artist and the member of the community
who worked in the coalmines, reflecting thecommunity’s wish to have something new andlooking to the future. The process of the collaborative
work was documented on a Channel 4 TV programme
and the project is widely known. It is located on thehighest point of Bold Forest Park, on the former
coalfield, Sutton Manor (Fig.9) and is an important
local focal point.

Table 2 Outline of the Bold Forest Park

Fig.7 Landscaping at Sutton Manor

Project
name(size of sites)
Past industrial
activities
Landscapeschanges
Environmental
regenerationand types ofgreen space
Placesinterests
green spaceofof

Characteristicsof the projects
andstatutory
designations
Fundings (mainfunders)
Local
partnerships andtheir roles
CommunitygroupsOther
localgroupsEventsandActivities
onsitesManagement
and responsibleorganisations
Long
term
management
plans
Project
name(size of sites)

The Bold Forest Park (320ha ofgreen spaces; 1808ha)
Coal-mining
Spoil heaps created from coalmining activities and a hill createdby soil constructed by a housingdevelopment
Reclamation of spoil heaps to form
hilly landscapes and tree planting;environmental improvements andlandscaping
surroundedbyagricultural lands
Big Art Project called the Dream,
Viewpoints to the surroundings, andgreen
spacescreatedbyenvironmental regeneration
Artworks with Big Art Project,environmental regeneration; Local
Nature Reserves (Colliers Moss
Common North)[12], 11 Local
Wildlife Sites[12], Green Belt[12],[17], [18]Northwest Regional Developmente
Agency, EU
Mersey Forest, St. Helens Council,
local industries and businesses,
landowners, residents, and acommunity group
Friends of Colliers Moss

Fig.8 A bridge at Colliers Moss Common

Fig. 9 A sculpture at Sutton Manor
Partnerships of case studies
Partnership of Northwich Woodlands
The Northwich Woodlands partnership includes
Cheshire West and Chester Council, the Mersey
Forest, Forestry Commission, Canal and River Trust,
local industries, businesses and community groups.
The well-established Friends of Anderton andMarbury (FoAM) and other local groups in the area
(Table 1) to undertake a programme of events.
FoAM was founded in 1999 and now has amembership of over 240; it continues to play an activerole to manage the sites. Area-wide management isundertaken by Cheshire West and Chester Council
and Forestry Commission rangers, supported byvolunteers from community and local businesses.

―
Events and management with thecommunity
Site based management by St.
Helens Council, Mersey Forest,
Forestry Commission, and private
landowners
Bold Forest Park Area Action Plan
(2017)The Bold Forest Park (320ha ofgreen spaces; 1808ha)

804SEE - Nagoya, Japan, Nov.12-14, 2018

Important tasks for the future are to secure the budget
to be able to continue to manage the habitats created.

(2012-2017) supported by the Heritage Lottery Fund[21] (Table 3). The importance of good access andconnections to Northwich town centre have been
discussed by developing Green Infrastructure in
Northwich Business Improvement District GreenInfrastructure Plan by Mersey Forest, since
Northwich Woodlands are closely located to the town
centre [22].
Northwich Woodlands has been identified inVale Royal Borough (reorganised into Cheshire West
and Chester Council) Local Plan (2006; saved
policies until 2015) [15]. However, a recently
published Local Plan (2015) by Cheshire West andChester Council mentions only selected sites but notentire Northwich Woodlands [16].
A planning timeline of Bold Forest Park has
been led by planning system, starting from strategies
in the 1980s and a development plan in the 1990s(Table 4). Forest Park has been identified in the
2000s, and it appeared in documents such as St.
Helens Town in the Forest Strategic Vision
Document (2006) [23], and City Growth Strategy(2008) [24]. In the 2010s, Bold Forest Park has been
identified in statutory documents as follows; St.
Helens Core strategy (2012) [25], and St. Helens
Local Plan (2016) [18], and the Bold Forest Park Area
Action Plan (2017) [12]. St. Helens Local Plan
(2016) is discussing about a release of Green Belt [18],which may also have effects to the future
development in the area, such as a development
opportunity site identified in the Fig. 3.

Partnership of Bold Forest Park
Partnership of Bold Forest Park includes St.
Helens Council, the Mersey Forest, Forestry
Commission, local industries and businesses,
landowners, residents, and a community group called
Friends of Colliers Moss. The Friends of Colliers
Moss was founded in 2016 to undertake events andmanagement on sites.
Table 3 A timeline of the Northwich Woodlands
1970’s1980’s1990’s2000’s2010's1975
Environmental improvements at
Marbury Country Park
1987 Environmental Regeneration at Furey
Wood
1989 Cheshire West and Chester Land
Regeneration
Unit to start environmental regeneration(2005)―
2006 Vale Royal Borough Local Plan (-2015)(Northwich Woodlands identified)2007 Supplementary Planning Document 5,
Landscape Character, Vale Royal BoroughCouncil2012 Saltscape Landscape Partnership (2017)2015
Local Plan (Part One, adopted),
Cheshire West and Chester Council
2016 Northwich Business Improvement
District Green Infrastructure Plan, Mersey
Forest (Northwich Woodlands identified)

Table 4 A timelines of the Bold Forest Park[20]1970’s1980’s1990’s2000’s2010'sCONCLUSIONS―
1986 Economic Strategy
1987 Ravenhead Renaissance established1989 Wasteland to Woodland (-1998)
1998 St. Helens Unitary Development Plan
1998 (-2013)2003 The First City Growth Strategy (Publicprivate partnership)2005 Forestry Commission District Valuer’s
Report2006 St. Helens Town in the Forest Strategic
Vision Document (Forest Park identified)2008 City Growth Strategy (-2018) (Forest
Park identified)
2012 St. Helens Core strategy (Bold Forest
Park identified)
2016 St. Helens Local Plan (2018-2033),
Scoping Consultation Document (Bold Forest
Park identified)
2017 Bold Forest park Area Action Plan

From the results, the two case studies present
good examples of environmental regeneration andmanagement creating community green spaces inpost-industrial landscapes. There are similarities inoutcomes of environmental regeneration creating
wildlife areas with some statutory designations, andpartnership with the public, private and community.
Moving forward there will be distinctive
focuses: most likely around industrial heritage inNorthwich Woodlands, and active recreation andcollaborative artwork in St. Helens. In both
Northwich Woodlands and Bold Forest Park thecommunity and local groups are actively participatingin running events and exhibitions, as well as assisting
to manage their green spaces.
For both case studies, the overriding issue isbeing able to develop the resources and partnerships
to enable the sites to be managed and cherished bytheir communities in the long term. The recently
published UK’s government’s ‘25 Year Plan for theEnvironment’ acknowledges that there needs to belong-term direction with flexibility to adapt to newevidence and circumstances: ‘the right mix of public
and private funding and financing for projects that
protect and enhance natural assets will be crucial.’

Planning timelines of case studies
A planning timeline of Northwich Woodlands
can be described as project based, starting fromenvironmental improvements at Marbury Country
Park in 1975, then Cheshire County Council Land
Regeneration Unit to take over environmental
regeneration during 1989 to 2005 [14], and more
recently through the Saltscape Landscape Partnership
805

SEE - Nagoya, Japan, Nov.12-14, 2018

Increasing pressures on local authority budgets has
meant the need to consider innovative funding andland holding mechanisms in order to realise thenatural capital benefits the two case studies provide.

2107, [Accessed 2017.8.22.].
[11] Northwich Woodlands, Map of the Park,<http://www.northwichwoodlands.org.uk/visit/index.shtml.>, undated, [Accessed 2017.8.22.].
[12] St.Helens Council, “Bold Forest Park Area
Action Plan”, 2017.
[13] Mersey Forest, “More from trees, The Mersey
Forest Plan”, 2014.
[14] Cheshire West and Chester Council, “Local Plan,
Planning
PolicyMapping2015,<http://maps.cheshire.gov.uk/cwac/localplan/>,undated, [Accessed 2018.7.26.].
[15] Vale Royal Borough Council, “Vale Royal
Borough Local Plan - Policies saved after 29 Jan2015”,<http://consult.cheshirewestandchester.go
v.uk/events/24925/2535161_accessible.pdf#searc
h=%27Vale+Royal+Borough+Local+Plan%27.>,
2006, [Accessed 2017.8.22.].
[16] Cheshire West and Chester Council, “Local Plan
(Part
One)
Strategic
Policies”,<http://consult.cheshirewestandchester.gov.uk/po
rtal/cwc_ldf/adopted_cwac_lp/lp_1_adopted?tab=files.>, 2015, [Accessed 2017.8.22.].
[17] St. Helens Council, “St. Helens Unitary
Development Plan”, <https://www.sthelens.gov.
uk/media/3391/sthelens-unitary-developmentplan-saved-policies-2013-addendum.pdf.>, 1998,[Accessed 2017.8.22.].
[18] St. Helens Council, “St. Helens Local Plan
Scoping
Consultation
Document”,<https://www.sthelens.gov.uk/localplan.>, 2016,[Accessed 2017.8.22.].
[19] St. Helens Council, “St. Helens, the heart of theNorthwest”, <http://www.dreamsthelens.com/
dream-facts-figures/.>, undated, [Accessed2017.8.22.].
[20] The Mersey Forest, provided materials, undated.
[21] Heritage Lottery Fund, “Saltscape secures
Heritage
LotteryFundinvestment”,<https://www.hlf.org.uk/about-us/mediacentre/press-releases/saltscape-secures-heritagelottery-fund-investment.>, 2014.8.22, [Accessed2017.9.4.].
[22] The Mersey Forest, “Northwich Business
Improvement District Green Infrastructure Plan”,
2016.
[23] St.Helens Council, “St. Helens Town in theForest Strategic Vision Document”, Gillespies,
2006.
[24] St.Helens Council, “City Growth Strategy”,
2008.
[25] St.Helens Council, “St. Helens Core strategy”,
2012.

ACKNOWLEDGEMENTS
The authors would like to express our gratitude
for the financial support provided by the Japan
Society for the Promotion of Science (no.17K06705).
REFERENCES[1] Davies C, “Old culture and damaged landscapes:
The new cultural landscapes of post-industrialsites in Britain”, in New cultural landscapes, Roeand Taylor, Ed., Abingdon: Routledge, 2014,
pp.41-58.
[2] Miyagawa T, Olver C, Otsuka N, Kurose T, and
Abe H, “The landuse changes and formation ofpartnerships
throughtheenvironmental
regeneration in Cheshire, the UK”, J. of theJapanese Institute of Landscape Architecture,
Vol.79(5), 2016, pp.555-558 (in Japanese).
[3] Williamson, K.S.,“Growing with GreenInfrastructure”, Heritage Conservancy, 2003,
pp.1-20.
[4] Handley, J, Pauleit, S and Gill, S, “Landscape,sustainability and the city”, in Landscape andSustainability, Benson andRoe, Ed.,
Abingdon: Routledge, 2007, pp.167-195.
[5] Miyagawa T, Olver C, Otsuka N, Kurose T, and
Abe H, “Lessons and achievements from the
Mersey Forest by networking partnership fortwenty years”, Proc. 7th Int. Conf. on GEOMATE,
2017, pp.564-570.
[6] Ling C, Handley J, and Rodwell J, “Restructuring
the Post-industrial Landscape: A Multifunctional
Approach”, Landscape Research, Vol. 32(3),2007, pp.285-309.
[7] Roe M, “Exploring future cultural landscapes, inNew cultural landscapes”, Roe and Taylor, Ed.,
Abingdon: Routledge, 2014, pp.241-269.
[8] Jerome G, Mell C, Shaw D, “Re-defining thecharacteristics of environmental volunteering:
Creating a typology of community-scale green
infrastructure”, Environmental Research, vol.158,
2017, pp.399-408.
[9] Mathers, A, Dempsey, N and Molin JF, “Placekeeping in action: Evaluating the capacity ofgreen space partnerships in England”, Landscapeand Urban Planning, vol.139, 2015, pp.126-136.
[10] Ordnance
SurveyMap,<http://www.osmaps.ordnancesurvey.co.uk/>,

806

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE INCORPORATION OF LEAN SIX-SIGMA INITIATIVES TO
REDUCE WATER FOOTPRINT OF A PUBLIC UNIVERSITY
Karin Kandananond
Faculty of Industrial Technology, Valaya Alongkorn Rajabhat University, Thailand

ABSTRACT
Water footprint is the amount of water use related to human activities. Currently, the water scarcity anduntreated water are the main problems many organizations have confronted with. In this study, the water
consumption activities of a public University are studied and assessed within the context of the three types of water
footprints. First of all, the water consumption of an organization in the form of the blue and green water footprints
are assessed and calculated. Secondly, the polluted water or gray water footprint is also included in the study.
Finally, the total water footprint of the organization is evaluated in term of liter per campus community member.
The second phase of the study focuses on the application of the lean six-sigma initiatives on the water consumption
activities of the University. The application will point out the most critical activity with the highest priority to
implement the water saving solution. This consequence will result in the significant reduction of the water footprintof the organization. Therefore, this incorporation will lead to the expedition of the environmental sustainability in
the University.
Keywords: Lean six sigma, Public University, Water footprint.

Bedal, Ulloa, and Grodek [3] show that the techniqueof lean six sigma and green is a potential tool toincrease the water efficiency in the industry. Parveen,
Kumar, and Rao [4] also applied the integrated
method of lean and green supply chain in the
manufacturing firms to reduce the water usage. The
study of the impact of lean and agile method on the
reduction of water footprint in the constructionindustry was conducted by Sertyesilisik [5].

INTRODUCTION
Water is the important resource for every aspectsof human’s life. However, the emerging problem isthe scarcity of water in many areas of the world andthe water conservation is the key to solve thisproblem. Although most people realize theimportance of the water saving, the crucial problem isthat they do not take it seriously. The study shows thatmost people might not get the whole picture of how
much water is spent on each process. As a result, if
water consumption of each product or process iscalculated and is attached to like a price tag. They willknow exactly the impact of their activities on theenvironment. According to the study, since theamount of water usage in the public sector is high, it
is important to implement the efficient method to
reduce the water consumption. Public University is apart of the public organizations. Therefore, if theappropriate intervention technique is applied to thecurrent activities of the University, it will result to thesignificant saving of the water consumption in theorganization.

SCENARIO
A public University in Thailand, Valaya Alongkorn
Rajabhat University, is selected to be a case. Valaya
Alongkorn Rajabhat University is a public University
established under the Rajabhat Unversity Act, B.E.
2547 (A.D. 2004), and the main campus is located in
Prathumthani province, Thailand as shown in Fig. 1.

REVIEWFor the success story in the industry, Sadraoui, Afef,and Fayza [1] utilized six sigma technique to reduceand optimize the water consumption at Coca Cola
Company. Moreover, Kaushik, and Khanduja [2]reported that the water consumption in the thermal
power plant was significantly reduced after the
implementation of six sigma method. Franchetti,

Fig. 1
807

University campus.

SEE - Nagoya, Japan, Nov.12-14, 2018

The University offers both undergraduate andgraduate degrees to part-time and full-time students
and it is operated daily from Monday to Sunday
except the national holidays. It is the medium-sized
University. There are about 10,000 students and 700
University personnel. There are many activities in theorganization that are related to water consumption.
This includes the transportation for official use,electricity use, and direct water consumption.

20 buildings. The unit of electricity measurement is
kWh (kilowatt-hour) and the life cycle analysis ofwater consumption on the electricity generation is
0.26 liter/MWh. As a result, the total amount of water
consumption according to the electricity use is shownin Table 1.
Table 1 Water consumption of the electricity use
Building
Office of Learning Promotion andProvision Academic Services
Language and Computer Center
Demonstration School 1
Demonstration School 2
Demonstration School 3
Green House
Plant Genetics Preservation
Student Affairs Division
Faculty of Science andTechnology (Office and lecture
hall/rooms)
Faculty of Science andTechnology (Home economics
lecture rooms/laboratory)
Faculty of Humanities and Social
Science (Office and lecture
hall/rooms)
Faculty of Humanities and Social
Science (Student government
office)Faculty of Industrial Technology
Faculty of Agriculture
Technology (Office and lecturerooms)
Faculty of Agriculture
Technology (Laboratories)
Faculty of Education 1
Faculty of Education 2
Faculty of Management Science 1
Faculty of Management Science 2
Faculty of Management Science 3
Total

RESEARCH PROCEDURES
The main research procedures are divided into two
sections. The first is to assess the amount of water
consumption regarding two major processes in theorganization, transportation and electricity use. The
second is the application of six sigma methodology to
reduce the water consumption.
The pathway to the reduction of water footprint isdifferentiated into five steps, i.e., define, measure,analyze, improve and control (DMAIC).
-DefineSince the main concept of problem defining is “vitalfew, trivial many”, the Pareto diagram was used to
identify the problem which contributed to the highest
amount of water consumption. According to thePareto chart in Fig. 2, the main source of water
footprint is the fuel consumption for thetransportation which holds the highest percentage ofwater consumption (88 percent) followed byelectricity, daily use water, and etc..

kWh66,116

Liter
17.19016

65,39265,920635
97,67532,200
2,182
1,596
3,200

17.00192
17.1392
0.165125.3955
8.372
0.56732
0.41496
0.832

66,44017.2744

6,600

1.716

59,69715.52122

39,20030,56010.192
7.945663,90916.61634

9,680
261,280
19,20014,9607,680
1,015,022

2.516867.9328
4.992
3.8896
1.9968263.9057

On the hand, the fuel consumption due to thetransportation activities is put into the accountFig. 2

Table 2 Water consumption of the fuel use

Pareto chart.

Therefore, it is interesting to note that the first priority
to reduce the water consumption should focus on the
reduction on the fuel use for the combustion in the
University car fleet.
-Measure
The water footprint are calculated by focusing on theactivities of the organization which lead to the water
consumption. The consumption is based on two main
activities, electricity use and fuel consumption on thetransportation.
The electricity use was measured from January to
April 2018 and the water footprint is calculated. The
measurement is done through the meter reading at
each building in the University. The total number is

Fuel

Density(kg/liter)

Gasoline
Diesel

0.77
0.832

Fuel
used
(liter)
24307
2640

Fuel
used
(kg)
18716
2196

(Liter/
kg)
857
690

Water
footprint(Liter)16,039,612
1,515,240
17,554,852

It is interesting to note that the major water
consumption is from the fuel consumption for thetransportation. Moreover, the detailed study showsthat gasoline use contributes to the highest water
consumption (16,039,612 liter). Therefore, the best
pathway leading to the water reduction is to decrease
the use of gasoline.
-Analyze
The major gasoline consumption is from the808

SEE - Nagoya, Japan, Nov.12-14, 2018

University vehicle fleet which is for official use.
Therefore, the only solution is to reduce theconsumption. As a result, the cause and effect or
Ishikawa diagram is utilized to analyze the causes ofthe effect, i.e., gasoline use reduction. Different
experts are interviewed and brainstormed, a potential
list of the causes is depicted in the form of cause andeffect diagram as shown in the following Fig. 3.
Materials

Methods

Natural Gas

Outsourced Transportation

Regular Maintenance

Machines

reduce the time spent in the traffic significantly.
-Methods
To reduce the official use of the fleet, the alternative
solution turns to the outsourced service. Although thetransportation activities will switch from the
University’s vehicle fleet.
-Identify
After all the options is identified, the experts havebrainstormed together and score the potential option
to practice. The results show that the utilization of
GPS might be the best option to practice. Because of
the advanced technology, GPS and its navigation
software is equipped in most smartphones. Therefore,
most drivers have access to the efficient and robustnavigation system. The sample of the navigation
through Google map is shown in Fig. 4.

GPS Tracking

Measurement

Fig. 3. Cause and effect diagram
According to Fig. 3, different categories of causes arelisted based on four main genres, i.e., materials,
methods, machines, and measurements.
-Materials
For materials, the commonly used fuel in the vehicle
fleet is gasoline. As a result, different type of fuel withless consumption of water, e.g., natural gas, should be
used instead of gasoline.
However, the engine system needs an upgrade so theeconomic analysis must be assessed. Moreover, since
the vehicle engine is originally designed for thegasoline used, the natural gas might affect thetribology of the engine. The engine might need more
frequent service in the long run.
-Machines
In this case, machine is the engine itself. To increase
the fuel saving rate, the regular maintenance might
help to increase the engine performance. Therefore,
this will lead to the significant saving of the fuel.
-Measurements
Since Bangkok is the capital of Thailand and her
traffic is among the worst in the world, the fuelconsumption is contributed to the traffic. Moreover,it also has the complex road network so it is easy to
get lost. As a result, the solution to this problem relieson the technology. Currently, the GPS tracking
system mostly come up with smart phones andGoogle map is the powerful software which will help
to find the fastest route to the destination. As a result,if all drivers use the GPS and its software, it will

Fig. 4. Navigation system-ControlThe solution to the problem is practice to ensure thatthe cause of the problem is solved. The measurement
has been done in order to validate the results.
RESULTS
After the efficient navigation system is introduced
and used in the University vehicle fleet for one
month, the result indicate that the average fuel saving
is approximately 5 percent for each trip (in the firstmonth after the implementation). Therefore, the total
amount of gasoline saving per month is about 300
liter/month or 197,967 liter of water consumption.
CONCLUSIONS AND DISCUSSIONS
The fuel used for the transportation in theorganization is the main concern which will lead tothe major saving of the water consumption. The leansix sigma method has been applied to reduce thewater use in the organization. The tool points out that809

SEE - Nagoya, Japan, Nov.12-14, 2018

the navigation system should be fully used in the
University vehicle fleet and this results in thesignificant saving in both the fuel and water
consumption. Besides the use of DMAIC, othermethods, e.g., 5S and Kaizen, might be used inaddition to the proposed method in order to reduce thewater usage.
REFERENCES[3] Franchtti M., Bedal K., Ulloa J., and Grodek S.,
Lean and Green: Industrial Engineering Methods
Are Natural Stepping Stones to Green
Engineering, Industrial Engineer, 2009, pp. 2434.
[4] Parveen C. M., Kumar A. R. P., and Rao T. V. V.
L. N., Integration of Lean and Green Supply
Chain - Impact on Manufacturing Firms in
Improving
Environmental
Efficiencies.
International Conference on Green Technology
and Environmental Conservation (GTEC 2011).
[5] Sertyesilisik B., Lean and Agile Construction
Project Management: As a Way of Reducing
Environmental Footprint of the Construction
Industry. Optimization and Control Methods in
Industrial Engineering and Construction, Vol.
72, 2014, pp. 179-196.

[1] Sadraoui T., Afef A., and Fayza J., Six Sigma:
A New Practice for Reducing Water
Consumption with Coca Cola Industry.
International Journal of Six Sigma andCompetitive Advantage, Vol. 9, Issue 2, 2012,
pp. 217-244.
[2] Kaushik P. and Khanduja D., Application of Six
Sigma DMAIC Methodology in Thermal Power
Plants: A Case Study. Total Quality Management& Business Excellence, Vol. 20, 2009, pp. 197207.

810

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PREPARATION OF GEOPOLYMER CEMENT FROM CRUSHEDSTONE BY-PRODUCT USING ALKALI FUSION
Kazuki Sakamoto1, Takaaki Wajima1
Department of Urban Environment Systems, Chiba University, Japan

1

ABSTRACTIn the crushed stone production process, crushed stone fines, such as dust and slurry cake, are generated as byproducts, and most of them are landfilled. Recently, it is becoming difficult to secure landfill sites, and effective
utilization of by-products is desired. On the other hand, geopolymer cement has attracted attention due to thehigher acid resistance than that of ordinary portland cement.
In this study, we attempted to prepare geopolymer cement from crushed stone by-products using alkali fusion.
In the experiment, crushed stone dust, discharged from one of the quarries in Japan, the fused dust, which preparedfrom the dust by heating at 500 oC with NaOH addition (weight ratio of addition is 1:1.6) for 0.5 h using rotarykiln, tap water and coal fly ash were used as raw materials. Crushed stone dust, fused dust, and tap water is mixed
on various mixed ratio, with or without addition of coal fly ash, heat at 30 oC or 80 oC for 24 h, and then stand atroom temperature, in air or distilled water to prepare geopolymer cement. Acid resistances for the obtained productand ordinary portland cement was also investigated. As a result, 7 g of mixture of crushed stone dust, water andfused dust (mix ratio is 1: 1: 2) with 3 g of coal fly ash, heated at 80 oC, and cured in water to obtain the geopolymer
cement with hard structure, and the obtained geopolymer cement indicates higher acid resistance than ordinary
portland cement.

Keywords: Crushed stone, Slurry cake, Coal fly ash, Alkali fusion, Geopolymer cement
sparked by metal ions, such as Al3+, Fe2+ and so on,which is similar to the reaction of zeolite synthesis[18] [19]. Therefore, there is a possibility to makegeopolymer cement using fused dust.
In this study, we attempted to prepare geopolymer
cement from crushed stone by-product using the dust
fused with alkali. The conditions, such as mixing ratio
and curing methods, to prepare the geopolymer
product with hard structure were investigated and theacid resistance of the prepared geopolymer cement
was evaluated.

INTRODUCTION
In the crushed stone industry, crushed stone dust /cake is generated as a by-product in large quantities
from crushing, cutting, polishing and cleaning
processes in the stone production process. Currently,
most of them are landfilled, but in recent years it is
becoming difficult to secure landfill sites, and further
development of effective utilization of by-products,
such as crushed stone dust and cakes, is desired bylaws in Japan [1].
Crushed stone dust is mainly composed of SiO2
and Al2O3, and the particle is fine and uniform. It isalso characterized as sparingly soluble. In previous
studies, we succeeded to convert sparingly soluble
crushed dust into highly soluble dust by alkali fusion
treatment to synthesize zeolitic materials [2] - [9].
Geopolymer cement is a cement produced frommixing sodium silicate, sodium hydroxide, water andsome industrial by-products, such as coal fly ash,blast furnace slag and so on [10] - [12]. Geopolymer
cement has attracted attention because it has less CO2
emissions in the manufacturing process than ordinary
Portland cement and has high acid resistance [10][13] - [17].
Ordinary Portland cement is mainly solidified by
the formation of needle-like calcium silicate hydrate(C-S-H), while geopolymer cement is mainly
solidified by the polymerization of silicate ions

EXPERIMENT
Samples
Crushed stone dust generated from one of thedomestic crushed stone companies in Japan was used
for the experiment. Coal fly ash used in this study wascommercially available fly ash type IV. The fused
dust was prepared by mixing crushed stone dust withsodium hydroxide at a weight ratio of 1: 1.6 andheating at 500 oC for 0.5 h using a rotary kiln [2].
Preparation of Geopolymer Cement from Dust
Crushed stone dust, tap water and the fused dust
were mixed so that total weight of the mixture is 7 g.
In addition, the mixture with or without coal fly ash
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SEE - Nagoya, Japan, Nov.12-14, 2018

was prepared to clarify the effect of coal fly ash
addition. The mixing ratio of the mixture is shown in
Table 1. The mixture was cured at room temperaturefor 1 day and 7 days, and 7 days passed and heated at
50 oC for 24 hours. The hardness of the product was
judged with a bamboo needle to insert into the
product.

were examined using atomic absorption spectrometer(AAnalyst 200, Perkin Elmer).
Acid resistance Test
Acid resistance test was conducted for the productin comparison with Portland cement. The sample wasprepared with a mold of φ 25 mm × 5 mm. The
product was formed by heating at 80 oC and standingin water for 24 hours. The Portland cement (Ordinary
Porto Portland Cement, N.C.C. Ltd.) was mixed at
50 % of water to cement ratio, poured into a mold,and stand at room temperature for 24 h. Each sample
was immersed in a 5% sulfuric acid solution (200 mL)
for 10 days, and the pH of the sulfuric acid solution
and the mass of the samples were measured every 24h.

Table 1 The mixing ratio of the mixture.

Dsut : Water

Fused dust : Water

Dsut : Water : Fused dust

The mixing ratio
1:1
1:2
2:1
1:1
1:2
2:1
1:1:1
2:1:1
1:1:2
1:2:1
1:2:2
2:2:1
2:1:2
3:1:1
1:1:3
1:3:1
3:1:2
2:1:3

3. RESULTS AND DISCUSSION
Formation of Geopolymer
The ternary diagrams of mixing condition forformation of hardened body (a) without coal fly ash
and (b) with coal fly ash are shown in Fig. 1. The plots
indicate the condition when hardened body wasconfirmed.
For the product without coal ash (Fig. 1(a)),
hardening could not be confirmed when the amountof water was large (above 40 %) and those of crushedstone dust and fused dust were small. With decreasing
the amount of water and increasing the amounts ofcrushed stone dust and fused dust, the number of days
used for hardening the product became shorter.
For the product with coal fly ash (Fig. 1),
hardening could not be also confirmed when theamount of water was large and those of crushed stone
dust and fused dust were small. In comparison withthe product without coal fly ash, the conditions for nohardening decrease, and the product becomes apowder when the amount of water is small and that of
the crushed stone dust is large. In addition, under thesame mixing condition, the time for hardening
becomes shorter. It is considered that the addition ofcoal fly ash accelerate the formation of geopolymer.
It is noted that the product added with coal fly ash was
harder than the product without coal fly ash added.

Next, 1 - 7 g of coal fly ash was added to 7 g of
the mixture (the mixed ratio of dust : water : fused
dust is 1 : 1 : 2). The mixture was knealed, and thecondition of the mixture was observed to obtain the
product precurser with high workability.
The raw materials and the products were observedwith a scanning electron microscope (SEM, JSM6510A, manufactured by JEOL).
Curing Experiment
The curing experiment was conducted to increase
the strength of the product.
The mixture (7 g) of dust, water and fused dust
(the ratio is 1 : 1 : 2) with 3 g of coal fly ash was used
for curing experiment. The mixture was filled andformed in a ring with a formwork of φ 25 mm × 5
mm. The ring stands for 24 h in a drying oven at 30o
C and 80 oC, and the product after 24 h was removed
from the ring to observe the condition. In addition, thering with the mixture was heated at 80 oC for 24 h,removed from the ring and then stand at room
temperature in air or in 200 mL of distilled water for
96 h. After 96 h, the product was picked up from thebeaker and the state was observed. For curing in water,
the elution amounts of Si, Al, Na and Ca to water812

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 2 Observation of the mixture with various
amount of coal fly ash.
The XRD patterns of the raw materials and the
product are shown in Fig. 3. The product was
obtained by adding 3 g of coal fly ash to the mixture(the mixed ratio is 1: 1: 2 of crushed stone dust, waterand fused dust). Crushed stone dust contains SiO2 andCaCO3 (Fig. 3(a)), and the fused dust consists ofalkali salts, such as Na2SiO3 and Na4SiO4 (Fig. 3(b)).
On the other hand, coal fly ash consists of SiO2,
Si2Al6O13 and amorphous glass (Fig. 3(c)). Peaks of
SiO2, CaCO3 and Si2Al6O13 remained, and Na2SiO3and Na4SiO4 disappeared in the product formed bymixing these raw materials (Fig. 3(d)). In addition,
hydrated sodalite (Na6Al6SiO6 ・ 8H2O) was
produced in the product.
Fig. 1 Ternary diagrams of mixing condition forformation of hardened body (a) without coal fly ash
and (b) with coal fly ash.
Figure 2 shows the condition after knealing the
mixture with varying amount of coal ash added. The
ratio of crushed stone dust, water, and fused dust is 1:
1: 2. The mixture after kneading was in liquid form
when the amount of coal ash added was 1 - 3 g, while
the mixtures with 5 g and 7 g of coal fly ash added
were semisolid and powder, respectively. The
viscosity increases as the amount of coal ash added
increases. Therefore, it is considered that the mixture
with 3 g of coal fly ash addition has a goodworkability to obtain the geopolymer cement product.

Fig. 3 XRD patterns of (a) crushed stone dust, (b)alkali fused dust, (c) coal fly ash and (d) product.
Raw materials were observed with SEM, as
shown in Fig. 4. Crushed stone dust has aggrogatesparticle of thin flake-like sticks with about 20 μm
diameter (Fig. 4(a)). The fused dust is the particles
with some small particles, alkaline salts, on thesurface (Fig. 3(b)). Coal fly ash was a sphericalparticle with a smooth surface having a particle
diameter of 5 to 10 μm.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 5 SEM image, (a) the product without coal
fly ash and (b) the product with coal fly ash.
Figure 6 shows the state of the sample after 24 hstanding at 30 oC and 80 oC. Although the sample at
30 oC is wet and brittle because chipping occurred atdemolding, the sample at 80 oC is hardened and nochipping occurred at demolding.

Fig. 4 SEM image, (a) dust, (b) fused dust and (c)coal fly ash.
The product prepared with or without coal fly ash
was observed with SEM, as shown in Fig. 5. The
product was prepared from the mixture with a ratio ofcrushed dust, water and fused dust of 1: 1 : 2 with orwithout addition of coal fly ash. For the productwithout coal fly ash, particles of crushed stone dust
were covered and solidified by gel-like materials. For
the product with coal fly ash, the product composedof many ball-like shapes, which would be coal fly ash
covered with some gel-like materials and sodalitelike crystals and crushed stone dust like particles
covered with gel-like materials. For the XRD patternof the product with coal fly ash, there was no change
in the crystal structure of the crushed stone dust andcoal fly ash. It is considered that crushed stone dusts
and coal fly ash were covered with the gels formed
from fused dust and water, and coal fly ash were more
impregnated in the product to be hardened.

Fig. 6 Sample state after standing at (a) 30 oC and(b) 80 oC for 24 h.
Figure 7 shows the state of the product after 72 hin air and water. For the product prepared in air, some
precipitates were observed on the surface. It is notedthat the product became fragile and cracked bywashing the precipitates on the surface with distilledwater. For the product prepared in water, nocomponent was precipitated on the surface, and thehard structure of the product was kept.

814

SEE - Nagoya, Japan, Nov.12-14, 2018

product is 90 % of the product before the test, whilethat of Portland cement is 20 % of the portland cement
before the test. It was found that the obtained producthas acid resistance of geopolymer cement.

Fig. 7 Observation of the product after 72 h in(a) air and (b) water.
Figure 8 shows the elution amounts of Si, Al, Ca
and Na into water. While Al and Ca were hardly
eluted, elution of Si and Na was confirmed. Elutionof Si and Na into water increased to 46 mg/g and 85
mg/g, and be constant after 48 h. The percentages ofNa and Si eluted from the product into water are about
60% and 25%, respectively. Therefore, the precipitateon the surface of the product prepared in air is caused
from excess amounts of Na and Si in the product, andthe product prepared in water has no precipitate on
the surface and hardened due to the removal of excess
Si and Na during the curing in water.

Fig. 8water.

Fig. 9 Observation of (a) product and (b) Portland
cement before and after immersion in sulfuric
solution.

Fig. 10 Mass change of the product and Portland
cement in sulfuric acid solution.

Elution amounts of Si, Al, Ca and Na into

CONCLUSION

Figure 9 shows the state of the sample before andafter acid resistance test. The shape and color ofPortland cement change to be small and the color
become white after the test, while the shape of the
product did not change after the test.
Figure 10 shows the mass changes of the productand Portland cement in sulfuric solution. It is notedthat the pH of the sulfuric acid solution was stable atbelow pH 1 during the immersion period. The massof portland cement decreases for 10 days, while thatof the product decreases in 2 days and be almost
constant after 2 days. After 10 days, the mass of the

We tried to prepare geopolymer cement fromcrushed dust, water, fused dust and coal fly ash. A
hardened geopolymer product was obtained byadding 3 g of coal ash to 7 g of the mixture with theratio of crushed stone dust: water: fused dust = 1: 1:
2. It was found that curing in water after heating at 80o
C was effective for producing stable geopolymer.
From the acid resistance test, it was found that the
prepared geopolymer cement has higher acidresistance than Portland cement.

815

SEE - Nagoya, Japan, Nov.12-14, 2018

REFERENCES

Characteristics of geopolymer and case examples
of construction, Construction and Building
Materials 156, 2017, pp. 9–18.
Nishimatsu Construction Technical Report Vol.
39 pp. 1 – 2.
[11] Hammad R. K., N.K. Lee, S.M. Park, N. Abba,
H.K. Lee, Synthesis of geopolymer-supported
zeolites via robust one-step method and theiradsorption potential, Journal of Hazardous
Materials 353, 2018, pp. 522–533.
[12] S. Moukannaa, M. Loutou, M. Benzaazoua, L.
Vitola, J. Alami and R. Hakkou, Recycling ofphosphate mine tailings for the production of
Geopolymers, Journal of Cleaner Production 185,2018, pp. 891-903.
[13] N.B. Singh, Foamed geopolymer concrete,
Materials Today, Proceedings 5, 2018, pp.
15243-15252.
[14] Part W. K., Mahyuddin R., Cheah C. B., An
overview on the influence of various factors on
the properties of geopolymer concrete derived
from industrial by-products, Construction and
Building Materials 77, 2015, pp. 370-395.
[15] Peng M.X., Wang Z.H., Shen S.H., Xiao Q.G.,
Li L.J., Tang Y.C., Hu L.L., Alkali fusion of
bentonite to synthesize one-part geopolymeric
cementscured at elevated temperature bycomparison with two-part ones, Construction
and Building Materials 130, 2017, pp. 103–112.
[16] Piotr R., Magdalena K. and Włodzimierz M.,
Spectroscopic studies of fly ash-based
geopolymers, Spectrochimica Acta Part A:
Molecular and Biomolecular Spectroscopy 198
2018, pp. 283–289.
[17] Ankur M., Rafat S., Sulfuric acid resistance of fly
ash based geopolymer concrete, Construction
and Building Materials 146, 2017, pp. 136–143.
[18] Melkon T., Gunther M., Stefan K. H., Relationof water adsorption capacities of zeolites with
their structural properties, Microporous andMesoporous Materials 264, 2018, pp. 70–75.
[19] Habbib G., Oliver S., Yvan M., Philippe K., The
Reconstruction of Natural Zeolites, book, pp. 15.

[1] Chugoku Bureau of Economy, Trade andIndustry, Market and business environment
survey for promoting new business · recycling
using rock resources and by-products, report,
2007, pp. 1-81.
[2] S. Onishi, T. Wajima, T. Imai, S. Susumu, Alkali
Fusion Process of Waste Stone Dust toSynthesize Faujasite Using Rotaky Kiln,
Mechanics, Materials Science & Engineering
Journal, Vol. 9, No. 1, 2017, pp. 287-292.
[3] T. Wajima, Alkali Fusion Synthesis of Zeolitic
Materials from Waste Dehydrated Cake
Discharged from Recycling of Construction
Waste Soil, Natural Resources, Vol. 8, 2017, pp.
300-305.
[4] T. Wajima, Synthesis of zeolite from blast
furnace slag using alkali fusion with addition of
EDTA, Advanced Materials Research, pp. 10441045, p.p. 124-127.
[5] T. Wajima, K. Munakata, Material conversion
from waste sandstone cake into cation exchanger
using alkali fusion, Ceramics International, Vol.
38, No. 2, 2012, pp. 1741–1744.
[6] T. Wajima, K. Munakata, Y. Ikegami,
Conversion of Waste Sandstone Cake into
Crystalline Zeolite X Using Alkali Fusion,Materials Transactions, Vol. 51, No. 5, 2010, pp.
849-854.
[7] T. Wajima, K. Yoshizuka, T. Hirai, Y. Ikegami,
Synthesis of Zeolite X from Waste Sandstone
Cake Using Alkali Fusion Method, Materials
Transactions, Vol. 49, No. 3, 2008, pp. 612-618.
[8] Lijalem A., Joaquín P.P., Yonas C., Isabel D.,
Conventional versus alkali fusion synthesis ofzeolite A from low grade kaolin, Applied Clay
Science 132–133, 2016, pp. 485–490.
[9] Jintang L., Xue Z., Xiaobing Y., Chaonan W.,
Xuetao L., Synthesis of pure sodalite with woolball morphology from alkali fusion kaolin,
Materials Letters 161, 2015, pp. 157–159.
[10] Liew Y.M., Heah C.Y., Long-yuan L., Nur A.J.,
Mohd M.A.B.A., Tan S.J., Kamarudin H.,816

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DESALINATION OF SEAWATER USING NATURAL ZEOLITE FORAGRICULTURAL UTILIZATION
Takaaki Wajima1
Graduate School of Engineering, Chiba University, Japan

1

ABSTRACT
We attempted to make agricultural cultivation solution from seawater with a simple process using naturalzeolite. In 21st century, the demand for food is increasing due to the global population growth, and securing
farmland is one of the most important factors in food production. Approximately 20 % of farmland in the world issalt-damaged soil with unsuitable properties for agriculture by high salinity water, and simple desalination methodsof high salinity water to improve salt-damaged soil is desired. Natural zeolite has a cation exchange ability, and isavailable in large quantities at low cost. In this study, desalination of seawater, as high salinity water, using
Japanese clinoptilolite zeolites with typical exchangeable cation, Na+, K+, NH4+, Mg2+ and Ca2+, were examined.
Ca2+-type zeolite indicates the highest reduction of NaCl from seawater among these ion-exchanged naturalzeolites. The column experiment using Ca2+-type natural zeolite shows that pH can be controlled to neutral andsalinity can be reduced by the reaction between Ca2+ in zeolite and other ions in seawater. Although Radish sprouts
did not grow in seawater, they could be grown in the solution treated with column process of Ca2+-type naturalzeolite.
Keywords: Seawater Desalination, Natural zeolite, Radish sprout growth, Ca-ion exchange

seawater.
The securing farmland is also one of the mostimportant factors in food production. Approximately
20 % of farmland in the world is salt-damaged soil
with unsuitable properties for agriculture by highsalinity water. Furthermore, the cultivated lands innortheast Japan were damaged by tsunami, andbecame salted soil not to use for agriculture.
Therefore, simple and inexpensive technique isdesirable for agricultural use to decrease salinity ofsaline water or salted soil.
Natural zeolite occurs in natural deposits,
generally associated with grassy volcanic rock, and isavailable in large quantities at low cost [4], especiallyJapan is volcanic country with abundant naturalzeolite deposits, such as clinoptilolite, mordenite andso on. Based on their high ion-exchange capacity,
absorptivity, water retention and low cost, naturalzeolites have been used in agronomy, horticulture andindustry [5]. Therefore, natural zeolite has possibility
to be used to reduce NaCl in saline water at low cost.
There are some papers for seawater desalination using
natural zeolites [6-8]. Little information is available,
however, on the treatment of saline water with naturalzeolite.
In this study, we investigated the ability of ionexchanged Japanese natural zeolite for seawater
desalination. Reduction of NaCl from seawater using
Japanese clinoptilolite-type zeolites with typicalexchangeable cation, Na+, K+, NH4+, Mg2+ and Ca2+,
were examined, and column test using ion-exchanged
natural zeolite was performed to produce the solution

INTRODUCTION
In the 21st century, global environmental issues
are very serious and effective utilization of energy
and mineral resource and securing food and water are
urgent problems. Production of a stable supply offood is essential to sustain human life. Securing
agricultural water is one of the most important factors
in food production. Due to the global population
growth, the demand for water is increasing. Many
countries of the Middle East and Africa are in achronic shortage of water, and it is expected that halfof the countries in the world will get into a water
shortage in 2025 [1].
One of the ways to supply water resources isseawater desalination because seawater is the mostabundant water resources on earth. The multi stage
flash (MSF) method and the reverse osmosis
membrane method (RO) are well known desalination
technologies [2], but these technologies are expensive
for agricultural use because they are producing highquality fresh water for domestic or industrial use.
However, the highest utilization of the fresh water inthe world is irrigation, and the percentage of irrigation
utilization is 70% of the total freshwater utilization[3]. Agricultural water should contain elements forcrops rather than be highly purified. Seawatercontains the essential elements needed for plant
growth, but its high concentration of NaCl causes salt
damage that precludes its direct use. Irrigation water
has no need to be high-quality fresh water and can beobtained by reducing high content of NaCl in
817

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

for agricultural utilization from seawater.

rate of 10 mL/min using a ceramic pump, and theeffluent was circulated to the column again for 2
hours. After circulation, distilled water (800 mL) was
passed through the column to remove the excess
Ca(NO3)2 in the column to prepare the Ca-exchanged
natural zeolite column. Four these columns wereprepared.
Seawater desalination experiment was done using
Ca-exchanged natural zeolite column. Seawater (40mL) was fed to the Ca-exchanged column frombottom to top at a flow rate of 4 mL/min using aceramic pump, and the effluent was circulated to thecolumn again for 2 hours. After circulation, thesolution was completely passed through the column
to collect the column treated seawater. This column
treated seawater was fed to the fresh Ca-exchanged
column, and done as the same procedure. This
operation was repeated 4 times.
The pH, salinity and the concentrations of mainelements, Na+, K+, Mg2+, Ca2+, Cl- and SO42-, in thesolution after passing through the column wasmeasured using pH meter (Horiba, F-72), salt meter(MK, YK-31SA) and ion chromatograph (Tosho, IC2010), respectively. The changes of each element oneach step represent as the ratio of measured
concentrations to the original concentrations inseawater (R) as follows;

MATERIALS AND METHOD
Samples
Seawater used in this study was collected from thesurface layer in Imari Bay, Saga Prefecture, Japan.
Japanese clinoptilolite-type natural zeolite, which
was obtained from the deposit of Koriyama,
Kagoshima prefecture, Japan, was used in zeolite
treatment.
Ion-exchanged Natural Zeolite Treatment
Five different ion-exchanged natural zeolites,
Na+-, K+-, NH4+-, Mg2+- and Ca2+-zeolite, wereprepared, and the NaCl reductions in seawater bythese ion-exchanged zeolites were compared. Before
the experiment, natural zeolites used in thisexperiment was grounded by mill, sieved under 500
μm, and dried in drying oven at 80 oC overnight.
Na+- and NH4+-zeolites were prepared using themethod reported in [9], and K+-, Mg2+- and Ca2+zeolites were prepared as follows. Na+-zeolite (100 g)
was put into 4 M KCl, 2 M MgCl2 or 2 M CaCl2
solution (500 mL) in 1 L vessel, and set in drying
oven at 80 oC overnight. Then, the slurry was filtrated,
and the solid was put into each fresh solution (500mL) again. This procedure was repeated 3 times, thenthe obtained solid was washed with 80 % EtOH, anddried at 80 oC overnight to obtain K+-, Mg2+- andCa2+-zeolite. It is noted that all exchangeable cationsites in natural zeolite was completely occupied by
the objective cations.
The reduction of NaCl in seawater using ionexchanged natural zeolites was examined as follows.
1.5 g of natural zeolite was added to 15 mL ofseawater, and stirred for 2 hours with a magnetic
stirrer. After stirring, the slurry was filtered, and thenfresh natural zeolite was added to the filtrate. This
procedure was repeated 5 times. The concentrationsof Na+, K+, Mg2+, Ca2+, Cl- and SO42- in seawater andthe filtrate after each times of zeolite treatments were
determined using ion chromatograph (DX-120,
Dionex).

RM =CM(M: Na+, K+, Mg2+, Ca2+, Cl-, SO42-) (1)C0

where C0 and CM are the initial concentration inoriginal seawater and the measured concentration in
the treated solution, respectively.
Growth Test
The solution after 4 times column treatment, tapwater and seawater were applied to growth test using
radish sprouts (Raphanus sativus). During this test,
cultivation was conducted for 10 days at room
temperature to investigate the possibility of using theobtained solutions for cultivation.
RESULTS AND DISCUSSION
Desalination Ability of Ion-exchanged Natural
ZeoliteFigure 1 shows the change of (a) Na+ and (b) Clconcentrations in seawater as a function of thenumber of zeolite treatment. Although Na+ content isalmost constant using Na+-type zeolite, other types
zeolites can decrease Na+ content in seawater. The
order of Na+ reduction is NH4+ ≒ K+ ≒ Ca2+ > Mg2+
> Na+ ≒ 0, which is good accordance with adsorption
affinity of clinoptilolite for cations [10]. On the other

Column Test using Ion-exchanged Natural Zeolite
Before the column test, Ca-exchanged naturalzeolite packed column was prepared. Natural zeolite
particles with the diameter of 1.0 mm (40 g) was
packed into the glass column tube (inner diameter: 14mm, height: 30 cm) sandwiched between layers ofquartz wool, 1 M Ca(NO3)2 solution (100 mL) was
then fed to the column from bottom to top at a flow
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SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

hands, Mg2+- and Ca2+-type zeolites, including
divalent cations, can decrease Cl- contents inseawater, while Cl- contents are almost constant using
Na+-, NH4+- and K+-type zeolites, including
monovalent cations.

+300

Mg -type+

Ca -type

42++

K -type
0

600

Na+
-NZ

4
2
3
1
Number of treatment

Na+

475

NH4+
K+
Mg2+

5

Ca2+

(b)

Cl500

400

Na -type

Mg -type+
NH -type4

Ca -type

0.0

0.0

0.3

0.9

59.8

5.7

3.1

51.
2
6.8

51.9

52.4

73.7

57.3

9.3

10.1

10.4

51.1

541

562

548

507

506

28.
0

27.6

27.5

27.2

27.1

0.0

10.
3
56.
0
11.
7
553
27.
8

K+NZ

406

Unit: mmol/L

2+

Desalination using Column

+

0

0.0

0.0

2+

K -type

300

66.5

477

SO42+

Ca2+
-NZ

415

Mg2
+
NZ
450

NH4
+
NZ
402

2+

Na -type
NH -type

SW

1
2
3
4
Number of treatment

The pH and salinity of the solution after naturalzeolite column treatment on each step are shown in
Fig. 2. The pH of seawater is 7.76, and those of thesolution after zeolite treatment are neutral (pH 6.5 7.5), which indicates the solution pH after naturalzeolite treatment is neutral to be used for cultivation.
The salinity of seawater is 3.40 %, and withincreasing the number of treatment to four times, thatof the solution gradually decreases to 0.66%, which
is approximately one-fifth of the original salinity ofseawater.

5

Change of (a) Na+ and (b) Cl- concentrations
in seawater as a function of the number ofzeolite treatment.

Table 1 shows the chemical compositions ofseawater and the solution after 5-times treatment with
ion-exchanged natural zeolites. It is noted thatoriginal seawater indicates typical chemicalcompositions of seawater [2], [11]. The cation
including in each type-zeolite is high content in eachsolution, and the contents of K+ and Ca2+, which are
the cations with high adsorption affinity ofclinoptilolite, decrease, except the solutions treatedwith K+- and Ca2+-type zeolite, respectively. It isconsidered that the exchangeable cations with highmobility (high affinity) can be exchanged with highcontent of Na+ in seawater. SO42- content is almost
constant using all types zeolites. It is unclear why
divalent-type zeolite can reduce only Cl- content inseawater. Anion removal using zeolite may depend
on surface adsorption because zeolite is cationexchanger. One of the reasons may be that the surface
properties of divalent-type zeolite are different tomonovalent-type, which indicates higher affinity for
Cl- than SO42-.

12

4
pH

10

Salinity (%)

3

pH

8
2
6
1

4

2

Fig. 2819

Salinity (%)

Na+ concentration (mg/L)

400

200

Cl- concentration (mM)

Table 1 Chemical compositions of seawater (SW)and the solution after 5-times treatment with
ion-exchanged natural zeolites (NZ).

(a)

500

Fig. 1

These results suggest that Ca2+-type naturalzeolite is the best for NaCl reduction from seawater.

0

1
2
3
4
Number of zeolite column treatment0

pH and salinity of the solution treated with
Ca-exchanged natural zeolite columns.

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

1.2

Contents(mg/L)
Na+
K+
Mg2+
Ca2+
ClSO42Salinity
(%)
pH

Mg2+

SO42-

K+

Cl-

Ca2+

10
8

0.6

6

0.4

4

0.2

2

0

1

2

3

4

Ratio of Ca2+ in seawater
to that in treated water

Na+

0.8

0

Table 2 Chemical compositions, salinity and pH ofseawater (SW) and the solution after 1-4
times treatment with Ca-exchanged naturalzeolite columns.

121
to those in treated solution

Ratios of Na+, K+, Mg2+, Cl- and SO42- in seawater

Changes of each element in the solution during thezeolite treatment are shown in Fig. 3. The contents of
Na+, K+, Mg2+, Cl- and SO42- drastically decreases on
first zeolite treatment and then gradually decrease
after second zeolite treatment, which isapproximately below one-fifth of the originalcontents of seawater, while that of Ca2+ drasticallyincreases and then be almost constant after second
zeolite treatment.
Therefore, the decrease of salinity mainly depends
on the decreases of all elements, except Ca2+.

1times2times3times4times

12191
682
1360
403
21891
2724
3.40

5027
140
592
2330
12409
1520
2.15

2501
74
330
3132
9643
1136
1.45

857
33
135
2644
6036
667
0.95

405
0
70
2466
4959
504
0.66

7.79

7.48

6.85

6.55

6.73

Figure 4 shows the growth test of radish sprouts
for 10 days at room temperature. Although we could
not observe the germination of radish sprouts using
seawater, we could confirm the growth of radish
sprouts using the treated solution like using distilledwater. These results suggested that it is possible toprepare the solution for agricultural cultivation fromseawater using Ca-type natural zeolite treatment.

0

Number of zeolite column treatment

Fig. 3SW

Ratios of Na+, K+, Mg2+, Ca2+, Cl- and SO42in seawater to those in the solution treatedwith Ca-exchanged natural zeolite column.

(a)Table 2 shows the chemical composition, salinity,and pH of seawater and the solutions after various
times of natural zeolite treatment. Although seawatercontains high amounts of Na+ (12191 mg/L), Cl(21891 mg/L) and other elements and indicates highsalinity (3.4 %) The solutions after zeolite treatment
contain lower amounts of Na+, Cl-, K+, Mg2+ andSO42- than seawater, except Ca2+, and indicates lower
salinity than seawater. It is noted that pH of thesolution is neutral to be used for cultivation. The
contents of Na+, Cl-, K+, Mg2+, SO42- and Ca2+ in thesolution after 4-times natural zeolite column
treatments are 405 mg/L, 4959 mg/L, 0 mg/L, 70
mg/L, 504 mg/L and 2466 mg/L, respectively, whichindicates that the solution contains low NaCl andminerals, Mg2+ and Ca2+, and indicates low salinity(0.66 %) for plant growth.

Fig. 4(b)(c)

Observation of Raphanus sativus after 10days growing using (a) tap water, (b)seawater, and (c) the solution after 4 times
zeolite treatment of seawater.

CONCLUSION
We investigated desalination behaviors fromseawater using Japanese clinoptilolite-type naturalzeolite in order to be used as desalination agent for
producing irrigation water from salty water. The
ability of ion-exchanged clinoptilolite zeolite for
NaCl reduction from seawater was examined. Amongtypical ion-exchanged zeolite, such as Na+-, K+,
NH4+, Mg2+- and Ca2+-type natural zeolites, Ca2+-typezeolite is the best for reduction of NaCl fromseawater. We could decrease the salinity of seawaterusing a simple Ca-exchanged natural zeolite column,
and can obtain the solution with neutral pH and low
salinity to be used for cultivation. Although radish
sprouts did not grow in seawater, they could be grownin the solution after zeolite treatment. These results
suggested that it is possible to prepare a solution for820

SEE - USQ, Brisbane, Australia, Nov.13-16, 2017

agricultural cultivation from seawater using a simple
Ca-exchanged natural zeolite treatment. I found that
Ca-natural zeolite can be desalinate seawater byremoving both cations and anions. In future, Caexchanged natural zeolite will be applied to improvesalted soil to cultivate craps.

1978.
[6] Wajima T., Ion exchange properties of Japanesenatural zeolites in seawater, Anal. Sci., Vol. 29,
2013, pp. 139-141.
[7] Wibowo E., Rokhmat M., Sutisna, Khairurrijal
and Abdullah M., Reduction of seawater salinity
by natural zeolite (Clinoptilolite): Adsorption
isotherms, thermodynamics and kinetics,
Desalination, Vol. 409, 2017, pp. 146-156.
[8] Okawa Y. and Wajima T., Desalination ofseawater using Ca-A zeolite for agriculturalutilization, Conference Proceedings, in Proc. 5thInt. Symp. Exhib. Aqua Sci. Water Resour., 2017,
pp.252-257.
[9] Ohmori Y. and Hosoi Y., The simple design
method for regeneration condition of ammonium
ion exchanged natural zeolite by saturated sodium
chloride solution, J. Jpn. Soc. Water Environ., Vol.
23, 2000, pp. 795-802.
[10] Akgü M., Karabakan A., Acar O. and Yürüm Y.,
Removal of silver (I) from aqueous solutions withclinoptilolite, Microporous and Mesoporous
Mater., Vol. 94, 2006, pp. 99-104.
[11] Nakajima T., Deep Seawater Utilization, Midori
Shobou, 2002.

ACKNOWLEDGEMENTS
This study was performed under Cooperative
Research Program of Institute of Ocean Energy, Saga
University (11002A).
REFERENCES[1] World Water Council (WWC), World Water
Vision. Making Water Everybody’s Bus.
Earthscan, 2002.
[2] Sea Water Society Japan and Salt Science
Foundation, Sea Water, its Property andTechnology. Tokai Daigaku Shuppan, 1994.
[3] Tilizer M.M., Conference Proceedings, in Proc.
the 2nd Autoanalyzer symposium in Osaka, 2006,
pp. 4-15.
[4] Tominaga H., Zeolite no Kagaku to Ouyou,
Kodansha, 2001.
[5] Barrer R.M., Zeolites and Clay minerals as
Sorbents and Molecular Sieves, Academic Press,821

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

COMPARISON OF COD AND TSS REMOVALS FROM ARTIFICIALRIVER WATER BY MUDBALLS MADE WITH ACTIVATED EM1 AND
EM4 SOLUTIONS
Fadjari Lucia Nugroho, Deni Rusmaya and Muthia Damayanti
Department of Environmental Engineering, Faculty of Engineering, Universitas Pasundan, Indonesia

ABSTRACTIn Indonesia surface waters are often polluted by domestic waste. The use of Effective Microorganisms (EM)mixed with rice bran and clay soil then shaped into mudballs has been suggested as a means to directly improvewater quality of polluted rivers. This study examined the removal of COD and TSS by 2.5 cm φ mudballs madewith two different kinds of activated EM solutions, i.e. EM1 and EM4. Batch experiments at 30°C wereconducted where artificial river water was treated with mudballs made from rice bran, and clay soil, which weremixed with either activated EM1 or EM4 solutions. Removal efficiencies of 120 mg/L COD by the mudballs
were respectively 60.3% with EM1 and 59.4% with EM4. Removal efficiencies of 100 mg/L TSS wererespectively 100% with EM1 and 97.9% with EM4. Statistical hypothetical testing of the experimental datasuggests that at α=0.05, there is no difference in removal efficiencies of COD and TSS by mudballs made witheither EM1 or EM4. COD and TSS removal efficiencies are correlated with mudballs’ diameter; where
increasing diameter results in better removal efficiencies. pH values of artificial river water after 5 days
treatment by mudballs mixed with EM1 and EM4 were respectively 6.2 and 4.8. TSS isotherm sorption by
mudballs with EM1 better fits the BET model, with qm= 32.4 mg/g, whereas that with EM4 better fits theLangmuir model, with Qm = 7.52 mg/g; KL = 0.0168 L/mg and RL = 0.373. It appears that EM1 would be thepreferred EM solution for direct treatment of polluted surface waters.
Keywords: Adsorption isotherms, Effective Microorganisms, Mudballs, River Water

by Professor Dr. Teruo Higa of the University of
Ryukus, Okinawa, Japan and have been applied foramongst others the treatment of water andwastewater, improvement of recycled water andsolving sanitary problems [4].
Nugroho et al. [2] reported that the removal
efficiencies of 120 mg/L COD and 100 mg/L TSSfrom artificial river water by 2.5 cm φ mudballs
made from rice bran, clay soil and EM4 activatedsolution at 30°C were 59.4% COD and 99.7% TSS
respectively.
However, the pH of artificial river water treatedby EM4 mudballs becomes acidic even when the pH
value of the artificial river water solution was
initially alkaline [5]. pH values in the acidic range
could potentially harm aquatic organisms, and infact based on statutory Indonesian regulations, pH ofIndonesian surface waterways must range between
6-9. EM4 is manufactured locally in Indonesia, andconsists of a mixed culture of Gram negative andGram positive rod-shaped bacteria, some of which
are spore-forming, as well as Mucor sp. and
Penicillium sp. fungi and actinomycetes [5].
In Malaysia, mudballs made from EM1 activatedsolution (EMS) have been used to clean up rivers,
including Sungai Kelian in the state of Perak whereEM-mudballs improved river water quality fromClass IV (suitable for irrigation) to Class III

INTRODUCTION
Urban rivers are major assets to communities as
they provide numerous benefits, including fresh
water, recreation, landscape amenity, habitat
provision and flood control [1]. However inIndonesia, surface waters are often polluted by both
domestic as well as industrial waste. For instance,
the average COD and TSS levels of CikapundungRiver, Bandung City, Indonesia in 2013 were 120
mg/L and 100 mg/L respectively; with maximum
levels at times reaching as high as 400 mg/L COD
and 350 mg/L TSS [2].
Althoughconventional
physical-biologicaltreatment methods can be applied to treat polluted
surface waters, they are often costly and not ecofriendly. Hence the use of Effective Microorganisms(EM) that are mixed with clay soil and shaped into
balls, - known as “EM mudballs”, - has been
proposed as an alternative means to directly improvewater quality of polluted rivers [3]. These so-called“EM-mudballs” are capable of reducing suspended
solids, turbidity, as well as COD content of thepolluted river; which would also improve the river’s
DO content.
The concept of EM, which is a mixed culture ofnaturally occurring effective, beneficial, nonpathogenic microorganisms was first promulgated822

SEE - Nagoya, Japan, Nov.12-14, 2018

(suitable for water supply with extensive treatment)[3]. EM1 is the original Effective Microorganisms
solution developed by Dr. Higa in the 1980s, madeup of a mixed culture of microorganisms including
lactic acid bacteria, photosynthetic bacteria,
actinomycetes, yeasts and fermenting fungi.
As artificial river water treated with EM4
mudballs produces an acidic pH value [5], theobjective of this current study was therefore todiscern whether EM1 mudballs also produce similar
results. The removal efficiencies of COD and TSS in
artificial river water by mudballs made with either
EM1 or EM4 solutions were therefore compared.
Parameters analyzed included COD and TSS
removal efficiencies, change in pH values of thetreated artificial river water, correlation between
removal efficiencies and mudballs’ diameter as well
as TSS isotherm adsorption model.

in a shaker water bath at 30°C. The COD, TSS andpH values of the treated river water solutions were
measured daily.
TSS adsorption experiments
The TSS adsorption experiments were carriedout in 250 ml Erlenmeyer flasks containing 200 ml
tap water mixed with kaolin powder producing a
TSS concentration of 100 mg/L. Varying quantities
of EM1-MB or EM4-MB (1 - 10 g) were then added
into the TSS solution and the flasks placed in a
shaker water bath adjusted to 30°C. The TSS was
measured after 3 days of shaking.
Calculation of adsorption isotherms
Adsorption isotherms describe the equilibrium
relationships between adsorbent and adsorbate [6].
The isotherm equations used to determine the TSS
adsorption model were the Freundlich, Langmuir
and Brunauer-Emmett-Teller (BET) isotherm
equations. The Freundlich isotherm is an exponential
equation that assumes that as the adsorbate
concentration increases so too does theconcentration of the adsorbate on the adsorbent
surface [7]. This isotherm can be used for non-ideal
sorption that involves heterogeneous surface energy
systems, hence not restricted to the formation of amonolayer. The mathematical expression of theFreundlich isotherm is as follows:

METHODSAll experiments were conducted as batch
experiments. COD was measured by close reflux
titrimetry, TSS was measured by gravimetry
methods and pH was measured using Lutron pH-208
pH-meter.
Materials
EM1 solution used in the experiments is a
registered trademark of EMRO and was procured
from Seikatsu, Japan. Whereas, the EM4 solution
used in the experiments was manufactured by
Songgo Langit Persada and procured locally in
Bandung, Indonesia. The EM solutions are sold in adormant state and hence had to be activated.
Activation of the dormant EM solutions was
performed by diluting 5% EM solution with distilledwater and leaving the mixture to ferment for a day atroom temperature [5].
The mudballs (MB) were prepared by mixing
20% rice bran and 80% dry clay soil with 40%
activated EM solutions (v/w), shaped into 2.5 cm φballs, which were then left to ferment in coveredbaskets for 7 days at room temperature.
Artificial river water with a COD content of 120
mg/L and TSS content of 100 mg/L was prepared byadding glucose and 60 mesh sieved kaolin powder
into tap water [5].

𝑋𝑋

𝑀𝑀

1

= 𝐾𝐾𝐹𝐹 𝐶𝐶𝑒𝑒 𝑛𝑛

(1)

𝑿𝑿

where is the amount of adsorbate adsorbed by the𝑴𝑴adsorbent (mg/g), KF is a rough indicator of theadsorption capacity (mg/g), 1/n is the adsorption
intensity and Ce is the equilibrium liquid-phase
concentration of the adsorbate (mg/L).
The Langmuir isotherm equation is based on theassumption of monolayer coverage (the layer is one
molecule thick) of adsorbate over a homogenous
adsorbent and that when equilibrium is attained nofurther adsorption can take place. Adsorption isassumed to take place at specific homogenous sites
in the adsorbent and the adsorption of each moleculehas equal adsorption energy [8]. The theoretical
Langmuir isotherm equation is as follows:𝑿𝑿

Experiments

𝑴𝑴

Batch experiments with artificial river water=

𝑸𝑸𝒎𝒎 𝑲𝑲𝑳𝑳 𝑪𝑪𝒆𝒆
𝟏𝟏+𝑲𝑲𝑳𝑳 𝑪𝑪𝒆𝒆(2)where Qm is the maximum amount of adsorption
corresponding to complete monolayer coverage on
the surface (mg/g); and KL is the Langmuir constantrelated to the energy of adsorption (L/mg).
The Brunauer-Emmett-Teller (BET) adsorption
isotherm is a theoretical equation that was developedin order to describe multilayer adsorption systems

The batch experiments were carried out in 250
mL Erlenmeyer flasks. Mudballs (MB) made witheither EM1 (EM1-MB) or EM4 (EM4-MB)
activated solutions were mixed with 200 mL
artificial river water. The flasks were then incubated823

SEE - Nagoya, Japan, Nov.12-14, 2018

[9]. The model assumes that a number of layers ofadsorbate accumulate at the surface and each layer
follows the Langmuir isotherm model. As such, thethe BET isotherm equation is as follows:
𝒒𝒒

𝒒𝒒𝒎𝒎

𝒃𝒃𝒃𝒃

= (𝑪𝑪

MB are different, statistical hypothetical testing
against the COD and TSS experimental data was
performed. The results are presented in Table 2
Table 1 Changes in pH, COD and TSS values ofartificial river water treated with EM1-MB
and EM4-MB at 30° C(3)

𝒔𝒔 −𝟏𝟏)[𝟏𝟏+(𝒃𝒃−𝟏𝟏)𝑪𝑪⁄𝑪𝑪𝒔𝒔 ]where C is the aqueous concentration of adsorbate(mg/L), Cs is the saturation concentrations foradsorbate in solution and qm is maximum capacity ofadsorbent for adsorbate (mg/g)

Day
0
1
2
3
4
5
6

RESULTS AND DISCUSSIONS
COD and TSS Removal Efficiency
Figure 1 show the results obtained regarding
COD and TSS removal efficiencies by 2.5 cm φ MB
made with either EM1 or EM4 activated solutions(EM1-MB and EM4-MB). Whereas, Table 1 shows
the changes in pH, COD and TSS values over timein artificial river water treated with EM1-MB and
EM4-MB.
120

Removal efficiency (%)

100
80

77

60
47 48.7

40

36.9
31.2

48.9
43.3

82.7

56.8
53.1

60.3

ɑ
Hypothesis
Results of t
testing
Conclusion

59.4

44.8
41.4

Fig. 1

1

2

Day

3

4

TSS (mg/L)
EM1 EM4
100
100
53.3 51.3
22.3 17.3
0
0.67
0
0.67

% COD removal
0.05
H0 :µEM1=µEM4
H1:µEM1>µEM4
tcalculated < ttable% TSS removal
0.05
H0 :µEM1=µEM4
H1:µEM1>µEM4
tcalculated < ttable% COD removal
by EM1 = COD
removal by EM4% TSS removal
by EM1 = TSS
removal by EM4

The results presented in Table 2 show that at ɑ =0.05, COD and TSS removal efficiencies by
mudballs made with either EM1 or EM4 activatedsolutions are the same. COD removal is attributed toboth physical (sorption) and biodegradation
processes, whereas TSS removal is attributed tophysico-sorption processes alone [2].
With regard to changes in pH values (Table 1),
after 5 days the pH value of artificial river water
treated with EM4-MB was pH<5, whereas thattreated with EM1-MB was pH>6. Accordingly, thepH of artificial river water treated with EM1-MB
meets Indonesian statutory regulations, while thattreated with EM4-MB does not meet statutory
Indonesian regulations. The differences in pH values
are attributed to differences in the types of
microorganisms present in EM1-MB and EM4-MB.
EM4 solution includes mixed cultures of Gram
negative and Gram positive rod-shaped bacteria,some of which are spore-forming, as well as
actinomycetes and fungi of the Mucor and
Penicillium genera [5], whilst the EM1 used in thisstudy contains amongst others Bacillus sp. as well as

20
0

COD(mg/L)
EM1 EM4120
120
75.7 82.6
68.1 61.3
70.3 66.2
51.9 56.3
47.6 48.7
47.6 48.7

Table 2 Statistical hypothetical testing of COD and
TSS removal efficiencies by EM1 and EM4
Mudballs

COD EM1
COD EM4TSS EM1TSS EM4

100
99.7

pH
EM1 EM4
5.1
4.1
5.5
4.65
5.5
4.48
5.7
4.6
6
4.76
6.2
4.82
6.2
4.82

5

COD and TSS removal efficiencies (%) ofartificial river water by EM1-MB and EM4MB at 30° C

The results presented in both Fig. 1 and Table 1
show that maximum COD and TSS removals wereattained after 5 and 3 days incubation respectively at
30°C. COD removal efficiencies by EM1-MB and
EM4-MB were respectively 60.3% and 59.4%;
hence it initially appeared that slightly better COD
removal was obtained with EM1-MB. Likewiseslightly better TSS removal efficiency was obtainedwith EM1-MB as TSS removal efficiency with
EM1-MB was 100%, while that of EM4-MB was
99.7%. Accordingly, to confirm whether COD and
TSS removal efficiencies by EM1-MB and EM4824

SEE - Nagoya, Japan, Nov.12-14, 2018

Gram negative rod shaped non-spore forming
bacteria, as well as fungi such as Mucor sp.and
Bipoloris sp. [10]. Both Bacillus sp. and Gram
negative rod-shaped non-spore forming bacteria are
not categorized as lactic acid bacteria given that bydefinition lactic acid bacteria are Gram-positive,
non-sporeforming cocci, coccobacilli or rods thatferment glucose to lactic acid or to lactic acid, CO2
and ethanol. Therefore different types of microbialconsortia present in the EM solutions would attributeto differences in the abilities of the EM1 and EM4
microorganisms to produce organic acids that in turnwould affect the pH values. In comparison,
Namsivayam et al. [11] reported that after 5 days
domestic sewage treated with EM solution
composed of Lactobacillus planetarium (lactic acidbacteria), Candida utilis (yeast), Streptomyces albus(actinomycetes) and Aspergillus oryzae (fungi) had a
pH of 8.4 and 14% reduction in COD. The SS, DO,
COD, BOD and pH values of Kelian River,Malaysia improved after being treated with mudballs
made from EM1 activated solution [3]. On the other
hand, after 12 days of incubation at room
temperature the pH of produced water treated with
EM solution composed of Lactobacillus plantarum,
Aspergillus sp. and Penicillium italicum decreased
from 8.03 to 3.71 and had a COD reduction of 60%[12].

0.9633 and 0.9705 for EM1-MB and EM4-MB
respectively. Whereas, the correlation coefficient (R)for COD removal efficiency versus mudballs’
diameter is 0.9549 and 0.9675 for EM1-MB and
EM4-MB respectively. These values indicate asignificant correlation between TSS as well as COD
removals against mudballs’ diameter, where
increasing mudball diameter results in better
removal efficiencies of COD and TSS. This isunderstandable as COD removal is attributed to both
physical (sorption) and biodegradation processes,
whereas TSS removal is attributed to physicosorption processes alone [2]. Hence larger mudball
diameters would provide more sorption sites that
adsorbed the organic material and suspended solids
contained in the artificial river water, resulting in
better removal efficiencies.
100% COD EM1-MB% COD EM4-MB

90% COD removal

80
70
60

y= 47.08x -24.98
R2 = 0.912
R = 0.9549

50
40
30
20

y = 31.67x - 15.63
R² = 0.936
R = 0.9675

10
0

90

y = 39.94 x - 6.799
R2 = 0.942
R = 0.9705

80% TSS removal

70

Fig. 3

50
40
30

1

1.5

2

2.5

Correlation between COD removal
efficiency and mudballs’ diameter

Adsorption of TSS20

y = 40.53x - 11.65
R2 = 0.928
R= 0.9633% TSS EM1-MB% TSS EM4-MB

10
0

0.5

1

1.5

2

Figure 4 depicts the TSS adsorption (mg/g) bydifferent quantities of EM1-MB and EM4-MB after
3 days of incubation at 30°C.
As shown in Fig. 4, TSS adsorptions by both
EM1-MB and EM4-MB are higher at lower
quantities of mudballs. Given that adsorption of the
TSS involves migration by pore diffusion of the TSS
from the surface into the interior of the porous
adsorbent, it is understandable that more TSS canmove into the smaller sized less compacted mudballsin comparison to the larger sized, dense and heavier
mudballs [2]. However, as indicated in Fig. 2
removal efficiency is greater with larger sizedmudballs, given that the adsorption mechanism for
TSS removal by the mudballs entails a surface
phenomenon and larger diameters will provide more
sorption sites.

2.5

Φ Mudballs (cm)Fig. 20.5

Φ Mudballs (cm)

60

0

0

Correlation
betweenTSS
removalefficiency and mudballs’ diameter

Figures 2 and 3 respectively depict correlation
between removal efficiencies of TSS and COD withmudballs’ diameter. As shown in Fig. 2 and Fig. 3
the determination coefficient (R2) and the correlation
coefficient (R) indicate a high correlation between
TSS as well as COD removal efficiencies against
mudballs’ diameter, whether this is with EM1 or
EM4. The correlation coefficient (R) for TSS
removal efficiency against mudball diameter is825

SEE - Nagoya, Japan, Nov.12-14, 2018

follows [13]:
9
8

8.05
7.48

X/M (mg/g) EM1-MB
X/M (mg/g) EM4-MB

7
6
X/M (mg/g)

𝑹𝑹𝑳𝑳 =

5

4.47
3.36

3

3.51
2.66
2.19

2

2

2.12

2.29
2.2

5

6

2.05 2.14

1.85
1.83
1.78
1.61.68
1.75

1
0

1

2

3

4

7

8

9

10

CONCLUSION

gr MudballFig. 4

Batch experiments were conducted at 30°C tostudy differences in removal efficiencies of 120
mg/L COD and 100 mg/L TSS in artificial riverwater by 2.5 cm Φ mudballs made from rice bran
and clay soil that were inoculated with two different
types of activated effective microorganisms (EM)solutions, these being either EM1 which is theoriginal EM solution developed by Dr. Higa in the
1980s or EM4 solution, which is a local EM solution
fabricated in Indonesia. Statistical hypothetical
testing at ɑ = 0.05 indicates that there is nodifference in removal efficiencies of COD and TSS
by mudballs made with either EM1 or EM4
activated solutions. However measurements of pH
values show that whereas the final pH value of
EM4-MB treated artificial river water is in the acidic
range (i.e. pH = 4.8), that treated with EM1-MB has
a pH value of 6.2 which is within the pH range
required by statutory Indonesian regulations forsurface water, this being 6-9. The differences in pH
values produced by EM1-MB and EM4-MB are
attributed to differences in microbial consortia
present in EM1 and EM4 solutions. The adsorption
mechanism of TSS by EM1-MB is better describedby the BET isotherm, which is an extension of theLangmuir isotherm that indicates adsorption bymultiple layers of adsorbate, with the Langmuir
isotherm applying to each layer of adsorbate. The qm
value of TSS adsorbed by EM1-MB is 32.42 mg/g.
With regards to EM4-MB, the results indicate that
adsorption mechanism of TSS by EM4-MB appear
to better fit the Langmuir isotherm, which is basedon monolayer coverage on a homogenous material.
The Langmuir parameters obtained for EM4-MB
were Qm = 7.52 mg/g; KL = 0.0168 L/mg and RL =0.373. This latter RL value indicates favorable
adsorption. The results of this study also show thatmudball diameter affects removal efficiencies of
COD and TSS where increasing diameters produce
better removal efficiencies. The correlation
coefficient (R) for COD removal efficiency against
mudball diameter was 0.9548 and 0.9675 for EM1MB and EM4-MB respectively. The correlation
coefficient (R) for TSS removal efficiency against

Adsorption of TSS (mg/g) by different
quantities of EM1-MB and EM4-MB at
30°C, C0 = 100 mg/L

The experimental data were plotted against theFreundlich, Langmuir and BET isotherm models inorder to describe TSS adsorption by the mudballs.
Table 3 presents the results obtained from thisexercise.
Table 3 Calculated isotherm parameters andregression coefficients (R) for TSS
adsorption by EM1-MB and EM4-MB
Isotherm
Freundlich

Langmuir

BET

EM1-MBn = 1.373
KF = 18.509
R=0.7714
Qm = 0.1041
KL = 67.32
R =0.8231
qm = 32.42
R = 0.8394(4)

where KL is the Langmuir constant (L/mg) and Co is
the initial concentration of the adsorbate (mg/L).
Lower RL values indicate that the adsorption isfavorable, with the shape of the isotherm being
either irreversible (RL=0), favourable (0<RL<1),linear (RL=1), or unfavourable (RL>1) [13]. Hencethe RL = 0.373 indicates that adsorption of TSS by
EM4-MB is indeed favorable.

4

4

𝟏𝟏

𝟏𝟏+𝑲𝑲𝑳𝑳 𝑪𝑪𝒐𝒐

EM4-MBn = 1.212
KF = 14.26
R =0.8240
Qm = 7.52
KL = 0.0168
R = 0.8619
RL = 0.373
qm = 2.19
R =0.7211

The regression coefficients (R) presented inTable 3 suggest that TSS adsorption by EM1
mudballs better fits the BET isotherm adsorption
model, with qm=32.42mg/g, Whereas, that with EM4
mudballs better fits the Langmuir isotherm
adsorption model, with Qm= 7.52 mg/g and KL =0.0168 L/mg. The BET isotherm is an extension of
the Langmuir isotherm that accounts for adsorption
by multiple layers of adsorbate, which appears to be
the case of EM1 mudballs as the mudballs
themselves consisted of a mixture of rice bran andclay soil. The Langmuir isotherm accordingly
applies to each layer of adsorbate. In the case of theLangmuir isotherm, its’ essential feature is adimensionless parameter known as the separation
factor or equilibrium parameter, RL, defined as

826

SEE - Nagoya, Japan, Nov.12-14, 2018

mudball diameter was 0.9633 and 0.9705 for EM1MB and EM4-MB respectively. Based on the above
results, it can be surmised that EM1 activatedsolution would be the preferred EM solution for the
direct treatment of polluted surface water, as pH
value of the treated surface water would still meetstatutory Indonesian regulations. The mudballs’
diameter should also be adjusted to obtain optimum
results.

Quality Using Mudballs Made From EM4, Rice
Bran and Clay Soil, Conference proceedings, in
Proc. 5th Environmental and Management Conf.
on Green Technology Towards Sustainable
Environment, 2015, pp. OP/AE/002-1 OP/AE/002-8.
[6] Hossain MA, Ngo HH, Guo WS, Nguyen TV,
Removal Copper from Water by Adsorption onto
Banana Peel as Bioadsorbent, International
Journal of GEOMATE, Vol. 2, No. 2, (SI. No. 4),
2012. pp. 227-234.
[7] Freundlich H, Adsorption in Solution, Chemie,
57, 1906, pp. 384-410.
[8] Langmuir I, Adsorption of Gases on Plane
Surfaces of Glass, Mica and Platinum, J. Am.
Chem. Soc. 40, 1918, pp. 1361-1403.
[9] Foo KY, Hameed BH, Insights Into theModeling of Adsorption Isotherm Systems,
Chem. Eng. J. 156, 2010, pp. 2-10.
[10] Nugroho FL, Rusmaya D, Damayanti M,
Identifikasi Mikroorganisme Pada EM1 dan
Mudball (Dedak Padi, Tanah Liat dan EM1)
Yang Digunakan Dalam Penjernihan Air Sungai
Buatan, Infomatek, Vol. 19, No. 2, 2017, pp 91100.
[11] Namsivayam SKR, Narendrakumar G, Kumar
JA, Evaluation of Effective Microorganism(EM) for treatment of domestic sewage, Journalof Experimental Sciences, Vol. 2, Issue 7, 2011,
pp. 30-32.
[12] Stanley HO, Ekoh PE, Impact of Effective
Microorganisms on the Microbiological andPhysicochemical Parameters of Produced Water,
International Annals of Science, Vol.3, Issue 1,
2017, pp. 6-12.
[13] Hall KR, Eagleton LC, Acrivos A, Vermeulen T,
Pore and Solid Diffusion Kinetics in Fixed Bed
Adsorption Under Constant Pattern Conditions,Ind. Eng. Chem. Fundamentals, Vol. 5, No. 2,
1966, pp. 212-223.

ACKNOWLEDGEMENTS
The works were financially supported by theIndonesian Ministry of Technological Research andHigher Education.
REFERENCES[1] Covarrubia JC, Rayburg S, Neave M, The
Influence of Local Land use on the Water
Quality of Urban Rivers, International Journal of
GEOMATE, Vol. 11, Issue 23, 2016, pp. 21552161.
[2] Nugroho FL, Rusmaya D, Yustiani YM, Hafiz FI.
and Putri RBT, Effect of Temperature on
Removal of COD and TSS From Artificial River
Water by Mudballs Made From EM4, Rice Bran
and Clay, International Journal of GEOMATE,
Vol. 12, Issue 33, 2017, pp. 91-95.
[3] Zakaria Z, Gairola S, Shariff N, Effective
Microorganisms (EM) Technology for Water
Quality Restoration and Potential for Sustainable
Water Resources and Management, Conference
proceedings, in Proc. International Congress on
Environmental
Modelling
andSoftwareModelling for Environment's Sake, Fifth
Biennial Meeting, Ottawa, Canada, 2010, p.
S.0.04.
[4] Higa T, Parr JF, Beneficial and Effective
Microorganisms For A Sustainable Agriculture
and Environment, International Nature Farming
Research Center, Atami Japan, 1994, p. 4
[5] Rusmaya D, Nugroho FL, Yustiani YM, Hafiz
FI, Putri RBT, Improving Artificial River Water827

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE ESTIMATION OF THE LAKE COLAC WATER BALANCE USINGISOTOPIC RATIO OF WATER, AMOUNT OF PRECIPITATION AND
EVAPORATION VALUES IN VICTORIA, AUSTRALIA
Hiroki Kitagawa1, Peter G Dahlhaus2 Hiroyuki Ii3
Graduate School of Systems Engineering, Wakayama University, Japan2
Principal Research Fellow Centre for eResearch and Digital Innovation, Federation University, Australia
3
Faculty of Systems Engineering, Wakayama University, Japan
1

ABSTRACTThe Lake Colac and creek waters were sampled in both winter and summer, August 2017 to April 2018 and
pH, ORP, EC, temperature, dissolved ions and oxygen isotopic ratios for sampled waters were measured. Water
level of the Lake Colac and pan water level beside the Lake Colac were also measured. There was much
precipitation in winter and surface water flowed into the lake, therefore, the lake and pan water levels increased.
The creek water with low soluble substances was connected with south of the Lake Colac. EC value in the northof lake decreased gradually after precipitation because creek water did not flow into the lake. There was little
precipitation in summer and pan water level was only dropped and pan water dried up, however, the lake water
was not dried up because creek water flowed into the lake sufficiently even in summer. Groundwater was believed
to be a main water source at the north of Lake Colac, however groundwater did not flow into the Lake Colacbecause HCO3- values of lake waters were lower than those of groundwater and close to those of creek water. As
the result of EC record from March 2006, EC value did not increase even after the lake dried up. It was revealed
that the lake water flowed out underground because there is no flowing-out from the lake to creek. Evaporation
rate in the Lake Colac in sampling period was estimated 37.9% (approximately 9028500m3) by using oxygenisotopic ratio.
Keywords: Precipitation, Evaporation, stable isotopic ratio, dissolved ions

INTRODUCTION
The Lake Colac is one of the biggest fresh waterlakes in Victoria. Many farmers use groundwater for
agriculture and dairy farming, however, evcess
pumping up groundwater for agriculture and dairy
farming changes supply of surface water and undergroundwater flows into lakes [1], [2]. and then forprotecting water quality and quantity of the lake, it’s
important to understand relation between
groundwater and surface water for the Lake Colac,
therefore the purpose of this research reveals that theamount of groundwater and evaporation in the Lake
Colac to assess groundwater and surface waterinteraction. The Lake Colac has been studied formany years [1][2], however these studies have nofrequency for sampling and it is difficult to reveal theimpact from groundwater, precipitation andevaporation in the Lake Colac. This research has
much more data than previous ones and it can berevealed that hydrological cycle as groundwater,
surface water and evaporation in the Lake Colac.

Fig.1 The location map showing the Lake Colacin Corangamite in Victoria.
Colac in Corangamite region in Victoria. There are a
lot of lakes or wetlands in Corangamite area and thoselakes including the Lake Colac are recognized as
being of international ecological value and registeredas Ramsar Convention.
The Lake Colac is in Western plains between

STUDY AREA
Fig.1 shows the location map showing the Lake
828

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig.2 Sampling
pointsthe Lake
Colac. and theCentralHighlands
andforOtway
Rangesregional groundwater moves from Central Highlands
and Otway Ranges [3]. The Lake Colac is connectedwith Barrongarock Creek and the creek water always
flows into the Lake Colac. The amount of annual
rainfall is 600mm~700mm and there is no
precipitation in summer.

Fig.3 pH values and amount of precipitation for
the Lake Colac in both winter and summer.

METHODFig.2 shows sampling points for the Lake Colac.
Sampling of the lake and creek waters were
performed from August to September 2017 and fromFebruary to April 2018. EC, pH, ORP andtemperature were measured by using a calibrated fieldkit. Sampled waters were measured main dissolved
ions and oxygen stable isotopic ratios.
Fig.3 shows the way of measuring water level for theLake Colac. An iron stick with a brick was put at No.1
sampling point shown in Fig.2 in the Lake Colac andthe length from the top of brick to water level wasmeasured. For estimating of evaporation pan was also
put at the garden without shade near No.2 sampling
point in the Lake Colac and both the lake and panwaters were compared.
Stable oxygen isotopic ratios were measured bymass spectrometer (Sercon Geo Wet System) withdual inlet and equilibrium with CO2 and H2 gas
method. This isotope ratio is useful tracer forclarifying the origin for groundwater or evaporation
rate. Oxygen isotope ratio is generally expressed δ18O.
It is presented as per mil (‰) of the standard average
seawater (SMOW: Standard Mean Ocean Water).
The formulas are shown in equation (1). δ18O of

Fig.4 EC values and precipitation for the Lake
Colac in both winter and summer.
SMOW is denoted as (D/H) SMOW, (18O/16O)
SMOW and δ18O of the sample is denoted as (D/H)
Sample, (18O/16O). Measurement error ofmeasurement error of δ18O is ±0.2‰.

829

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig.5 Relationship between HCO3- and Cl- forthe Lake Colac and Creek waters, groundwaterand seawater.
δ 18O = [(18O/16O)Sample/(18O/16O)SMOW1]×1000: (1)Water level of the Lake Colac and pan water levelbeside the Lake Colac were also measured. The levelof pan water is measured close to No.2 on the map. A
stick and block are set up on No.1 and water level wasmeasured from the top of block in the lake water.

The Lake Colac in winterThe Lake Colac in summer

Groundwater

Creek

Pan water1

SeawaterFig.6 Hexa Diagram for the Lake Colac and creek
waters in both winter and summer, groundwater,
pan water and seawater.

RESULTFig.3 shows that pH values for the Lake Colac inboth winter and summer. The pH value for the lakewater ranged from 8 to 9 and its for creek water werefrom 7 to 8 in winter. Both the Lake Colac and creek
water reacts with rocks such as limestone, pH values
will become higher. Therefore, both waters did notreact with limestone. On the other hand, pH values for
the Lake Colac are from 8.5 to 9 because there is lessprecipitation in summer. pH values for the Lake
Colac and creek waters in winter are lower than thosein summer
Fig.3 shows EC values for the Lake Colac and creek
water in both winter and summer. No.3 sampling
point is close to creek and water at No.3 is mixed withcreek water, therefore EC values for No.3 sampling
point were lower than any other sampling points
when it rained. No.1 and No.4 sampling points are far
from creek and water for these sampling points are
hardly mixed with creek water. EC values for theLake Colac and creek water are increasing constantly
in summer, however those for creek water shifted
constantly without precipitation.

Fig.7 δ18O values for the Lake Colac and creek
waters in both winter and summer, pan water,
groundwater and seawater.

Main dissolved ionsFig.5 shows relationship between HCO3-/Cl- and Clfor the Lake Colac and creek waters and groundwaterin both winter and summer. The values of HCO3- forgroundwater are generally higher than those forsurface water because generally groundwater reacts

with carbonate rocks for long term. If groundwaterflows into the Lake Colac, the values of HCO3-/Cl- forthe Lake Colac are changed, however the values of830

SEE - Nagoya, Japan, Nov.12-14, 2018

GW divides

GW Pathlines

1m GW contours

Fig.9 Groundwater path lines around the Lake
Colac.

Fig.8 Water level for the Lake Colac and panwaters in both winter and summer and amount ofprecipitation.
HCO3-/Cl- for the Lake Colac were uniformed,
therefore it is thought that groundwater did not flow
into the Lake Colac.
Fig.6 show Hexa diagram of lake water, groundwaterand creek water for the Lake Colac area in bith winterand summer. The lake water in winter was sampled
21st September and that in summer was sampled 24th
March.
Chemical compositions for the Lake Colac waters inboth winter and summer and creek water, pan water
were similar to that for modern seawater and Na+ and
Cl- are higher than any other dissolved ions because
aerosol such as Na+ or Cl- in precipitation from thesea has been concentrated as evaporation in summer.
Chemical composition for groundwater is different
from other water because groundwater is reacted withrocks or soil underground. Ions composition for Pan
water 1 is the same as seawater. Pan water was watertaken at No.1 sampling point in the Lake Colac 16th
February and only evaporated in pan. The value of
HCO3- for pan water was relatively lower than that for
the Lake Colac and creek. The lake and creek waters
are contacted with soil included carbonated minerals,
however pan water is contacted without soil andHCO3- is decomposed in pan therefore the value of
HCO3- for pan water was relatively lower. It isthought that only surface water flows into the Lake
Colac and evaporated in summer

Fig.10 EC values for the Lake Colac between
March 2006 and April 2018.

Fig.11 Relationship between Cl- and δ18O for theLake Colac and creek waters, pan water andgroundwater.
Fig.7 shows the values of δ18O for the Lake Colacand creek water, precipitation, groundwater. Those
for Pan water 1 and 2 were also measured. δ18O values
for creek water and precipitation ranged from -3‰ to-6 ‰ and those for groundwater were -4 ‰ . It isthought that creek water and groundwater derived
from precipitation and those water was notevaporated. Those for the Lake Colac in winterIsotopic Ratio

831

SEE - Nagoya, Japan, Nov.12-14, 2018

ranged from 0‰ to -2‰ and those in summer ranged
from +3‰ to +5‰.
δ18O values for Pan 1 water were taken from No.1
sampling point in the Lake (then +5.6 ‰ ) andincreased to +9.1‰ and those for Pan 2 water werealso taken from No.1 sampling point in the Lake (then+5.2‰) and were increased to +8.2‰.
The Lake Colac water is thought to be much
evaporated, however creek water flows into the lake,
therefore δ18O values for the Lake Colac are nothigher than those for pan water.
Water Level
Fig.8 shows water level for the Lake Colac and panwaters, the amount of precipitation in both winter andsummer. There is much precipitation in winter,
therefore water level for both the Lake Colac andcreek waters increased. Although water level for theLake Colac increased after 19th September, that for
pan water decreased. It is thought that it took a timethat surface water flowed into the lake and water level
for the Lake Colac still increased.
There is less precipitation in summer, therefore
water level for both the Lake Colac and creek water
decreased. Pan water 1 was almost dried out 9 th
March, therefore another pan (pan water 2) was set
close the Lake Colac.
In summer water level for the Lake Colac changed
much in a few days. It is thought that depth of theLake Colac is shallow and then the water level is easy
to be affected by wind speed and direction.

Fig.12 Relationship between the amount ofchange the δ18O per unit the amount of change of
evaporation (‰/%) and evaporation (%).
Average in winterLake Colac No.4
Creek

Average in summer

Cl (mEq/L)

37.43

δ¹⁸O (‰)

-0.08

5.15

Cl

12.69

12.89

δ¹⁸O

-4.15

-4.10

55.85

Table 1 Average of δ18O and Cl- values for theLake Colac and creek waters both winter andsummer.
increase, however those values decreased after driedup.
Fig.11 shows relationship between Cl- and δ18O for
the Lake Colac and creek water, pan water,
groundwater and precipitation. Those for the lake andcreek water are in a proportion. Cl- ion is generally
stable in environment, therefore the value is not easy
to be changed and used as index for evaporation. This
result also reveals that the lake water was evaporated,
therefore evaporation rate for the Lake Colac can be
estimated.
Miyahara and Ii estimated evaporation rates of water
for the Lake Inawashiro in Japan by using oxygenisotopic ratio [4]. Fig.12 shows variation of theamount of change of the δ18O per unit the amount ofchange of evaporation rate about humidity from 20%
to 80%. Table1 shows the change of δ18O for the Lake
Colac and creek waters. No.4 in the Lake Colac is far
from creek, therefore it is most reliable value in thelake. The average humidity in Colac from September
2017 to March 2018 is approximately 60%. The
amount of change of δ18O and 0.14‰/%, the amountof change of the δ18O per unit the amount of changeof evaporation rate shown in expression (2).

CONSIDERATION
Fig.9 shows groundwater path lines around the Lake
Colac. It was thought that groundwater came from
Wallion Hill to the Lake Colac [3], however, as
shown in Fig.5, HCO3- values for the lake were notsmaller than those for groundwater but creek water,
therefore groundwater doesn’t flow into the Lake
Colac in both winter and summer and the Lake Colacis dominated only surface water.
Fig.10 shows EC values for the Lake Colac between
March 2006 and April 2018. EC values of the lakewater between March 2006 and February 2008 were
measured by Tweed [3]. EC values of the lake
between August 2017 and April 2018 were measured
in this study. In the summer of 2008 to 2009 the Lake
Colac water dried up completely, however the lakepartially refilled for only one year. Before dried up
EC values ranged 1000 mS/m to 3000 mS/m andAfter dried out those values were under 1000 mS/min this study, therefore it is revealed that the lakewater has been flowing out to underground. Because
if the Lake Colac is only destination for the creek,
dissolved ions especially Na+ or Cl- were precipitatedin the lake and even precipitation and creek waterflow into the lake, EC values for the lake water

5.3 (‰) / 0.14 (‰/%) ≒37.9 (%)

832

(2)

SEE - Nagoya, Japan, Nov.12-14, 2018

Area of the Lake Colac is 2778hec (27,780,000 m3)
and the depth is 2.5m and then the volume of the lake
is estimated 23,150,000 m3. Therefore, amount of
evaporation in the Lake Colac from September 2017
to March 2018 was estimated 9,000,000 m3.

REFERENCES[1] Annette B.Barton., Andrew L. Herczeg., Peter G.
Dahlhaus. And Lames W. Cox., A geochemical
approach to determining the hydrological regime
of wetlands in a volcanic plain, south-eastern
Australia, Groundwater and Ecosystems, Chapter
7, 2013, pp. 69-79.
[2] Sarah. Tweed., Marc. Leblanc. and Ian.
Cartwright.,
Groundwater-surface
waterinteraction and the impact of a multi-year droughton lakes conditions in South-East Australia,
Journal of hydrology, 379, 2009, pp. 41-53.
[3] Russell. Crosbie., Andy. Herczeg., Jim. Cox.,Peter. Dahlhaus., Phil Davies and John. Dighton.,
Defining Groundwater Flow Systems on the
Volcanic Plains to Accurately Assess the Risks ofSalinity and Impacts of Changed Landuse, 2007,
pp. 1-55.
[4] Sarah. Tweed., Mike. Grace., Marc. Leblanc., Ian
Cartwright and Donna. Smithyman., The
individual response of saline lakes to a severe
drought, Science of the total environment, 409,
2011, pp. 3919-3933.
[5] Miyahara S and Ii H., Proposal of simple
Measurement Method for Evaporation Rate by
Using Oxygen Isotopic Ratio, International
Journal of GEOMATE, Vol. 3, No.1, 2012, pp.
318-324.

CONCLUSION
It was thought that the Lake Colac was composed bygroundwater and surface water, however this study
revealed that groundwater does not flow into the Lake
Colac in August 2017 to April 2018 because
groundwater level is lower than the Lake Colac insummer and even its level increases in winter, waterlevel for the Lake Colac is high in winter, therefore
groundwater does not flow into the lake as pressureof the lake water.
Moreover, the lake water is thought to flow out tounderground because if the Lake Colac is destination
for creek without flow-out, dissolved ions (especially
Cl-) increase every year, however EC value did notincrease even after the lake had dried out.
It was revealed that 37.9% (approximately
9,000,000 m3) of the Lake Colac water was
evaporated in September 2017 to March 2018 byusing oxygen isotopic ratio.

833

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECT OF 17α-METHYLTESTOSTERONE ON SEX REVERSAL OF
RED TILAPIA (OREOCHROMIS NILOTICUS X OREOCHROMISMOSSAMBICUS) IN FREE-SWIMMING STAGE
Supamas Sriwongpuk1
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi, Thailand

1

ABSTRACTThe effect of 17α-Methyltestosterone (MT) on sex reversal of Red tilapia (Oreochromis niloticus x
Oreochromis mossambicus) in free-swimming stage by immersion and feeding technique were carried out at
Department of fisheries, Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi,
Pathumthani Province during April to July 2017. The experimental design was a factorial experiment in CRD
studied on two factors: 1) sex reversal by immersion treatment of 17α-MT (0, 150 and 300 µg/l) for 3 hours (T1,
T2 and T3) and 2) sex reversal by feeding treatment of 17α-MT (40, 60 and 80 mg/kg) for 28 days (F1, F2 and F3).
Results from these studies indicated that free-swimming stage that undergone immersion treatment of 17α-MT in
300 µg/l for 3 hours (T3) was the highest in growth rate about weight, total length (28 days), ADG, FCR andsurvival rate (0.731 g, 3.340 cm, 0.024 g/d, 0.627 and 95.443 % respectively). The immersion treatment of 17αMT in 150 µg/l for 3 hours (T2) was medial growth rate among other factors. The immersion treatment of 17α-MT
in 0 µg/l for 3 hours (T1) was the minimal growth rate but had the highest sex ratio of male (8 3 . 8 8 9 %). Sex
reversal by feeding treatment of 17α-MT in 60 mg/kg for 28 days (F2) was the highest in growth rate about weight,
ADG and FCR (0.644 g, 0.022 g/d and 0.714 respectively). Sex reversal by feeding treatment of 17α-MT in 80
mg/kg for 28 days (F3) was a medial growth rate and the highest of survival rate (95.037 %) and sex ratio of male(85.667 %). Sex reversal by feeding treatment of 17α-MT in 40 mg/kg for 28 days (F1) has a good growth rate but
the other factors were minimal.
Keywords: 17α-Methyltestosterone, sex reversal, Red tilapia (Oreochromis niloticus x Oreochromis
mossambicus), free-swimming stage

then introduced in different countries during the1970s but problems including inbreeding, insufficient
fish seed supply, stagnant production and poor fish
growth hindered small scale aquaculture production.
Large scale genetic improvement programs have been
established for O. niloticus in Asia [6] and genetic
methodologies to control sex have now resulted in thereliable production of all male fry to help overcome
the problem associated with excessive fry production
in culture ponds [7].
The Genetic Improvement in Farmed Tilapia(GIFT) project in the Philippines created strains of O.
niloticus that grew up to 60% faster than theirrelatives [8]. The benefits of the GIFT strain include
significantly faster growth rates than other farmed
strains, improved survival in polluted waters and thatthey can be raised in extensive systems without theneed for commercial feeds. The development ofhormonal sex-reversal techniques in the 1970s
represented a major breakthrough that allowed malemonosex populations to be raised to uniform,
marketable sizes. Although several species of tilapia
are cultured commercially, research on nutrition andculture systems, along with market development andprocessing including value addition in Nile tilapia
made the species as the predominant cultured species
worldwide. The species matures at a larger size and is

INTRODUCTION
Tilapia are freshwater fish belonging to the family
Cichlidae. They are native to Africa, but wereintroduced into many tropical, subtropical andtemperate regions of the world during the second halfof the 20th century [1]. Tilapia is a worldwide fish ofgreat commercial importance and it is recognized as
one of the most important aquaculture species of the
21st century. Tilapia is currently ranked second only
to carps in global production [2]. The world’s total
tilapia production in 2012 was 4.2 million tones.
Tilapia aquaculture is rapidly expanding with a global
production of about 2.8 million metric tons in 2008[3] and estimated to increase to 8.89 million metrictonnes by the year 2020 [4].
This rapid global production of tilapia is due to theintroduction of improved strains of Nile tilapia(Oreochromis niloticus) which is the major farmed
tilapia species. The important aquaculture species are
the nile tilapia (O. niloticus), blue tilapia (O. aureus),Java tilapia (O. mossambicus) and Zanzibar tilapia(O. hornorum). The red tilapia (O. hybrids)
developed from crosses of the main Oreochromis
culture species also has become popular in recent
years. Other tilapia species are cultured only bysmall-scale farmers in Africa [5]. Nile tilapia was834

SEE - Nagoya, Japan, Nov.12-14, 2018less fecund and thus less prone to overpopulation.
Today, tilapia are often farmed with multiple species
in the same pond, such as shrimp and milkfish. Thisnot only optimizes the financial return if space islimited, but also helps to prevent the growth ofharmful bacteria and serves to remove excess organic
matter in the water [9].
Initially, GIFT trials were conducted in
Bangladesh, China, Thailand and Vietnam, as well as
in the Philippines. Today, 13 countries in Asia havereceived GIFT to develop national breeding anddissemination programmes and GIFT's fast growthand high yield have encouraged many rural families
to take up environmentally friendly aquaculture
across the region. As many new fish farmers are
women, this empowers them as it improves local
supplies of high-quality, affordable protein andbenefits the nutrition of the household. The "GIFT
Fish" was the result of this carefully conductedgenetic selection and improvement programme basedon broodfish collected from four African countries(Egypt, Ghana, Kenya and Senegal) and fourcommercial O. niloticus strains (from Israel,
Singapore, Taiwan, Province of China and Thailand)
used in the Philippines [10]. In the initial phase of theresearch, it was evident that the gain in growth andsurvival through crossbreeding were less than
expected. This was followed by a pure breeding
strategy among the best performing purebred andcrossbred groups that led to the build-up of agenetically-mixed base population. This population
formed the basis for the final selection program
through a combined family and with in family
selection strategy [11]. Subsequent selection resulted
in the emergence of the GIFT strain, which is
purported to have an 85 percent cumulative genetic
gain compared to the base population [6].
Hormonal sex reversal has been extensively used
for sex determination and producing monosex fish foraquaculture purposes. Steroid hormones or hormone
analogues as well as non-steroid compounds arecommonly used for producing monosex tilapia. The
hormones are generally incorporated into larval feeds
and administered to undifferentiated larvae at very
early larval stages (preferably at first feeding) for
sufficient time to enable sex reversal. The use ofhormones has been under increasing public criticism
due to their possible health and environmental
impacts. As a result, the use of hormones for sex
reversal of tilapia is either licensed (in USA) or
banned (in Europe) [12]. Androgens are steroid
hormones derived from cholesterol synthesized
naturally by the adrenal cortex. Steroids are group of
lipids with several unique properties affecting growthand development. Steroids are called androgens, if
they are able to induce male characteristics andestrogens, if they induce female characteristics. The
hormone testosterone is ineffective as an androgen
when given orally and has a short duration of action

when administrated parenterally because of rapid
hepatic metabolism [13].
"Aquatic Animals" is a healthy diet that rich inprotein, high quality fat and many types of fatty acids.
Especially tilapia (O. niloticus), which is consideredgood protein and cheap. All people around the world
can be accessed. Tilapia is a good source of fat
contains all kinds of essential fatty acids and lower
cholesterol when compared to other meat or aquatic
animals together. In addition, the texture of tilapia
meat is white when cooked to make a colorful
appetizing and very delicious. It can be cooked in avariety of menus. For this reason, Tilapia is popularamong consumers both in Thailand and abroad. Sex
reversal by immersion and feeding may lessen the
duration of treatment and lower the cost of hormone
used. The present study aims to investigate thepotentiality different doses of 17α-MT with respect tothe determination of the optimum dose.
METHODOLOGY
The experiment was conducted at the laboratoryof Tilapia Hatchery, Division of Fisheries, Faculty ofAgricultural technology, Rajamangala University ofTechnology Thanyaburi (RMUTT).
1. Experimental Design
This study was designed as a factorial experimentin CRD. The experiment was divided into 9
treatments with 3 replications per trail and carried out
in a 50 liters glass cabinet filled with 30 liters volume
of water (total of 27 experimental units) for 28 days.
The experiments in this study was conducted toinvestigate two factors: immersion and feeding. Thereare 3 concentration levels of 17α-Methyltestosterone(MT): 0, 150 and 300 micrograms per liter (T1, T2 andT3) in the first factor (immersion) and 3
concentrations levels of 17α-MT of 40, 60 and 80
milligrams per kilogram feed (F1, F2 and F3) in thesecondary factor (feeding).
2. Preparing of 17α-MT for immersion
Free-swimming stage or fry (3 days old) whose
yolk sac have been absorbed were collected from thehatchery between 1,600-1,700 hours and weretransferred to the laboratory. Four thousand and fifty
free-swimming stages were immersed in different
concentrations of 17α-MT hormone concentrations of0, 150 and 300 µg l-1 for three hours. Immersion was
done using plastic containers (1.5 liter capacity each)
which were suspended in aquarium measuring 24 cm
x 50 cm x 30 cm. Aerators were provided in eachcontainer to facilitate the continuous movement of
Free-swimming stage in the water column.

835

SEE - Nagoya, Japan, Nov.12-14, 2018

3. Preparing of 17α-MT for feedingof fingerlings (male female, intersex) were identified
by gonad squash technique [15].

Hormone treated feed was prepared as described[14]. The 17α-MT was the hormone used. A stock
solution was made by dissolving hormone in 50 ml of
95% ethanol. Treatments were made by taking theaccurate amount of the hormone from the stock
solution and different doses were prepared viz. 60 mg
and 80 mg 17α-MT kg-1. This solution was evenly
sprayed over 500 g of shrimp starter feed containing
40% protein and mixed thoroughly. The feed-alcoholhormone mixture was mixed again and again toensure an equal distribution of the 17α-MT
throughout the feed. Treated diets were dried at room
temperature for 24 hours and then kept in airtightcontainers since androgens will breakdown when
exposed to sunlight or high temperature. The
prepared diets were stored at 4°C in refrigerator
before fed to fry of red tilapia. The diets containing
17α-MT were characterized as follows:
T1: diet + 40 mg 17α-MT kg-1 of dietT2: diet + 60 mg 17α-MT kg-1 of dietT3: diet + 80 mg 17α-MT kg-1 of diet

6. Statistical analysis
In order to calculate the statistical significancebetween the growth of the groups treated withdifferent doses of 17α-MT, a comparison of thedifferent parameters were described according to[16]. T-test was used to find out the statisticalsignificance in term of growth parameter, survival
rates and sex ratio.
RESULTS AND DISCUSSION
Effect of dietary 17α-Methyltestosterone on sex
reversal of red tilapia (O. niloticus x O. mossambicus)
in free-swimming stage by immersion and feeding
technique. The experimental design was a factorial
experiment in CRD studied on two factors: 1) sex
reversal by immersion treatment of 17α-MT (0, 150
and 300 µg/l) for 3 hours (T1, T2 and T3) and 2) sex
reversal by feeding treatment of 17α-MT (40, 60 and
80 mg kg-1) for 28 days (F1, F2 and F3). The two
factors are not combined. The results are as follows(Table 1).

4. Rearing
Sex reversal of tilapia free-swimming stage or fry
whose yolk sac have been absorbed was done by oral
administration of 17α-MT through feed. After threedays of hatching, the fry was shifted to nine glass
aquaria. Three replicates for each treatments having
30 liters of water each, containing 300 nos of fry forsex reversal treatment. Free swimming stage wasadministrated orally 17α-MT mixed feed containing
40% crude protein at three different dose rates viz.
40 (T1); 60 (T2) and 80 (T3) mg 17α-MT kg-1 offeed. The feeding was supplied to 6 times (7.00 9.00
11.00 13.00 15.00 and 17.00 am) daily during the day
light hours for 28 days.
During the rearing period, water quality
parameters (temperature, pH, dissolved oxygen (DO),Total Ammonia and Nitrite) in the net enclosures
were measured weekly up to the end of theexperiment. Temperature and DO concentration were
measured by YSI DO meter Model 55 while pH by apen-type HANNA pH meter. Total Ammonia andNitrite by titration. The mean length, weight andsurvival rate of the fish in each treatment wererecorded. After twenty eight days, the percentage ofmale and females were recorded.

1. Growth parameters and survival rate
1.1 average weight and length
After twenty eighty days of 17α-MT treatment
with three concentration of 0, 150, 300 mg l-1 in freeswimming stage of red tilapia by immersion
technique. The experiment was carried out in alaboratory at 30 fish density per liter with average
weight of 0.482, 0.698 and 0.731 grams, respectively
and with average length of 3,156, 3,331 and 3,340
centimeters respectively. The results show that theimmersion of 17α-MT with a concentration of 300 mg
l-1 were the heaviest weight and length and followedby concentration of 150 and 0 mg l-1. Feeding of 40,
60 and 80 mg kg-1: the average weight was 0.624,
0.644 and 0.642 grams, respectively, and an average
length of 3.292, 3.282 and 3.252 centimeters,
respectively. It was found that feeding hormone of 60
mg kg-1 was the highest weight and followed by 80
and 40 mg kg-1. And length by feeding of 40 mg kg-1
was the longest and followed by 60 and 80 mg kg-1
(Table 1). This was better than the results of [17] thatwas conducted to produce sex reversal tilapia (O.
niloticus) seed in fiberglass tanks in recirculating
systems with different densities for 21 days. He foundthat 10 densities l-1: the final weight was 0.066 ± 0.03
grams and the mean length was 1.00 ± 0.36
centimeters. This may be in this experiment fed thefish by ad-libitum technique. This method will feed
little by little until the fish filled. Each time it takes

5. Specifying of sex rates
To find out how sexual development after twenty
eight days of treatment, the sex was determined
depending on the secondary sexual characters. All
surviving fish were placed in iced box and
immediately dissected for sex differentiation. Sexes

836

SEE - Nagoya, Japan, Nov.12-14, 2018about 30 minutes for the fish to get food fully then theweight and length are considered in good standing.
Table 1 Effect of 17α-MT on sex reversal of red tilapia (O. niloticus x O. mossambicus) in free-swimming stage
by immersion and feeding technique.
Factor

WeightWeightLengthIncreased
ADG
FCR
on 28
gain
on 28
length(g d-1)day (g)(g)day (cm)(cm)
Hormone Concentration (immersion)
T1
0.428b
0.472b
3.156b
3.066b0.018b
0.928a
a
a
a
a
ab
T2
0.698
0.688
3.331
3.241
0.021
0.646b
a
a
a
a
a
T3
0.731
0.721
3.340
3.243
0.024
0.627bHormone Concentration (feeding)
F1
0.624a0.614a3.292a3.2.2a0.022a0.742a
a
a
a
a
a
F2
0.644
0.634
3.282
3.315
0.022
0.714aF3
0.642a0.632a3.252a3.192a0.019a0.743aNote: Different English letters in the vertical mean significantly different (P <0.05).
T1 = Hormone concentration 0 μg l-1 used for immersion
T2 = Hormone concentration 150 μg l-1 used for immersion
T3 = Hormone concentration 300 μg l-1 used for immersion
F1 = Hormone concentration 40 mg 17α-MT kg-1 used for feeding
F2 = Hormone concentration 40 mg 17α-MT kg-1 used for feeding
F3 = Hormone concentration 40 mg 17α-MT kg-1 used for feeding

Survival
rate
(%)

Male
ratio
(%)

94.852ab93.222b95.443a83.889a82.111a82.222a94.110a94.370a95.037a80.667a81.889a85.667aTable 2 Water quality parameters observed in the glass tank of red tilapia
Water Quality Parameters
Man-MaxpH
8.38 ± 0.00-9.31 ± 0.59
DO (mg l-1)
3.38 ± 0.01-5.91 ± 0.02
Temperature (°c)
27.00 ± 0.00-29.00 ± 0.10
Total Ammonia (mg l-1)
0.01 ± 0.01-0.36 ± 0.04
Nitrite (mg l-1)
0.00 ± 0.00-0.02 ± 0.02
Note: *The standard of water quality for fish farmingStandard value*
6.59-.0≥3
32.00-25.00
≤ 0.5
≤ 0.1

3 concentrations (40, 60 and 80 mg kg-1) were 0.742,
0.714 and 0.743, respectively. It was found thatfeeding at 60 mg kg-1 were the best FCR and followed
by 40 and 80 mg kg-1. This was better than the resultsof [17] that was conducted to produce sex reversal
tilapia (O. niloticus) seed in fiberglass tanks inrecirculating systems with different densities for 21
days. He found that FCR of Red Tilapia was 2.860.
This may be due to feeding by ad-libitum technique
has less food loss than other methods, resulting inlower FCR values.

1.2 Average Daily Grain (ADG)
The ADG of the free-swimming stage at 3
concentrations (0, 150 and 300 µg l-1) by immersion
were 0.018, 0.021 and 0.024 g d-1, respectively. It was
found that at 300 µg l-1 was the best growth rate andfollowed by 150 and 0 µg l-1. The ADG by feeding at
3 concentrations (40, 60 and 80 mg kg-1) were 0.022,
0.022 and 0.019 g d-1, respectively. It was found thatfeeding at 40 and 60 mg kg-1 were the best growth rate
and followed by 80 mg kg-1. There is the experiment
about the level of 17α-MT concentration on sex
reversal of three strain of Nile Tilapia in Thailand. It
found that the growth rate of Red Tilapia was 0.023 g
d-1.Which is close to the present experiment and showthat red tilapia have the best daily growth rate. [18].

1.4 Survival rate
The survival rate of the free-swimming stage at 3
concentrations (0, 150 and 300 µg l-1) by immersion
were 94.852, 93.222 and 95.443 %, respectively. It
was found that at 300 µg l-1 was the best survival rate
and followed by 0 and 150 µg l-1. The survival rate byfeeding at 3 concentrations (40, 60 and 80 mg kg-1)
were 94.110, 94.370 and 95.037 %, respectively. It
was found that feeding at 80 mg kg-1 were the best
survival rate and followed by 60 and 40 mg kg-1. Thiswas better than the results of the experimental of 17α-

1.3 Feed Conversion Ratio ((FCR)The FCR of the free-swimming stage at 3
concentrations (0, 150 and 300 µg l-1) by immersion
were 0.928, 0.646 and 0.627, respectively. It was
found that at 300 µg l-1 was the best FCR andfollowed by 150 and 0 µg l-1. The FCR by feeding at
837

SEE - Nagoya, Japan, Nov.12-14, 2018

MT on sex reversal of Nile Tilapia (O. nilotica) by
immersion of 300 µg l-1 and feeding of 60 mg kg-1.
The result of the survival rate were 8 3 . 8 ±7 . 1 ,77.3±13.1, 78.0±5.7, 74.4±5.1, 79.9± 12.5 และ
66.1±10.9 %, respectively. This may be due to thispresent study, the factors were controlled in all
experiments, especially water quality and theenvironment. The fish do not stress, feeding regularly
making good health and good growth. It has a higher
survival rate [19].

treatment of 17α-MT in 0 µg l-1 (T1) was the minimal
growth rate but had the highest sex ratio of male.
Sex reversal by feeding treatment of 17α-MT in 60
mg kg-1 (F2) was the highest in growth rate about
weight, ADG and FCR. Sex reversal by feeding
treatment of 17α-MT in 80 mg kg-1 (F3) was a medial
growth rate and the highest of survival rate and sex
ratio of male. Sex reversal by feeding treatment of
17α-MT in 40 mg kg-1 for 28 days (F1) has a good
growth rate but the other factors were minimal.

2. Sex ratio

ACKNOWLEDGEMENTS

The sex ratio of of the free-swimming stage at 3
concentrations (0, 150 and 300 µg l-1) by immersion
were 83.889, 82.111 and 82.222 %, respectively. It
was found that at 0 µg l-1 was the best male ratio andfollowed by 300 and 150 µg l-1. The sex ratio by
feeding at 3 concentrations (40, 60 and 80 mg kg-1)
were 80.6667, 81.889 and 85.667 %, respectively. It
was found that feeding at 80 mg kg-1 were the bestmale ratio and followed by 60 and 40 mg kg-1. The
experimental of 17α-MT on sex reversal of Nile
Tilapia (O. nilotica) by immersion of 300 µg l-1 andfeeding of 60 mg kg-1 for 45 days. The result of thesex ratio was 100 % and higher than this present study.
This may be due to the longer duration of hormone
exposure. The third level headings [19].

The author would like to express sincere
appreciation to the Faculty of Agricultural
Technology and the Institute of Research andDevelopment,
Rajamangala
UniversityofTechnology Thanyaburi (RMUTT), for their financial
support.
REFERENCES[1] Pillay T.V.R., Aquaculture: Principle andPractices, Fishing Book News, London, 1990,
pp. 1-575 pp.
[2] Ridha M.T., Comparative study of growth
performance of three strains of Nile tilapia,(Oreochromis niloticus L.) at two stocking
densities, Aquaculture Research, Vol. 37, 2006,
pp. 172-179.
[3] FAO, FAOSTAT. Food and Agriculture
Organization of the United Nations, 2010.
[4] Tacon, A.G.J., Metian M., Global overview on
the use of fish meal and fish oil in industriallycompounded aquafeeds: Trends and future
prospects, Aquaculture, Vol. 285, 2008, pp.
146-158.
[5] Teichert-Coddington, D.R., Green B., Boyd C.E.,
Harvin J.L., Rodriguez R., Martinez D., andRamírez E., Effect of diet protein on foodconversion and nitrogen discharge during semiintensive production of Penaeus vannamei during
the wet season. In: D. Burke, B. Goetze, D. Clair,and H. Egna (Editors), Fourteenth Annual
Technical Report, Pond Dynamics/Aquaculture
CRSP, Office of International Research andDevelopment, Oregon State University,
Corvallis, Oregon, 1997, pp. 71-77.
[6] Eknath, A.E., Tayamen M.M., Palada de Vera
M.S., Danting J.C., Reyes R.A., Dionisio E.E,
Gjedrem J.B. and Pullin R.S.V., Genetic
improvement of farmed tilapias: the growth
performance of eight strains of Oreochromis
niloticus tested in eleven different
environments. Aquaculture, Vol. 111, 1993, pp.
171-188.
[7] Mair, G.C., Abucay, J.S., Beardmore, J.A. andSkibinski, D.O.F., Growth performance trails ofgenetically male tilapia (GMT) derived from

3. Water quality
Hormonal feeding of red tilapia with different
methods and concentrations for a period of 28 days.
Daily water quality check every day throughout thetrial period. It was found that pH were 8.38 ± 0.009.31 ± 0.59, Dissolved Oxygen (DO) were 3.38 ±0.01-5.91 ± 0.02 mg l-1, Water temperature were27.00 ± 0.00-29.00 ± 0.10 ° C, Total Ammonia were0.01 ± 0.01-0.36 ± 0.04 mg l-1 and Nitrites were 0.00
± 0.00-0.02 ± 0.02 mg l-1. (Table 2) Found that thewater quality in this present study were satisfactorymanner [20]. Due to the quality control of the water
throughout the duration of the experiment. The fish
do not stress and has a higher survival rate.
CONCLUSION
According to study the effect of 17α-MT on sex
reversal in free-swimming stage of Red Tilapia (O.
niloticus x O. mossambicus) by immersion (0, 150
and 300 µg/l) for 3 hours and feeding (40, 60 and 80
mg/kg) for 28 days. It has been found that freeswimming stage that undergone immersion treatmentof 17α- MT in 300 µg l-1 (T3) was the highest in
growth rate about weight, total length (28 days),
ADG, FCR and survival rate. The immersion
treatment of 17α-MT in 150 µg l-1 (T2) was medial
growth rate among other factors. The immersion

838

SEE - Nagoya, Japan, Nov.12-14, 2018

YY-males in Oreochromis niloticus L.: on
station comparisons and mixed-sex and sex
reversed male populations, Aquaculture, Vol.
137, 1995, pp. 313-322.
[8] Eknath A.E. and Acosta B.O., Genetic
Improvement of Farmed Tilapias (GIFT)
Project Final Report, March 1998 to December
1997. ICLARM, Makati City, Philippines, 1998,
pp. 21-22.
[9] Troell M., Joyce A., Chopin, T., Neori, A.,
Buschmann, A. H., Fang, J-G., Ecologicalengineering in aquaculture-Potential for
integrated multi-trophic aquaculture (IMTA) in
marine offshore systems. Aquaculture, Vol.
297(1-4), 2009, pp.1-9.
[10] Day, M.M. and Gupta, M.V., Socio-economic
aspects of disseminating improved tilapia in
Asia: an introduction. Aquacult. Econ. And
Manage, Vol. 4(1&2), 2000, pp. 5-12.
[11] Eknath, A.E., Managing aquatic genetic
resources. Management Example 4: The Nile
Tilapia, in Thorpe J (ed.), Conservation of Fish
and Shellfish Resources: Managings Diversity,
London, Academic Press, 1995, pp. 176-94.
[12] Penman, D.J. and B.J. McAndrew, Genetics forthe management and improvement of cultured
tilapias. In: M.C.M. Beveridge and B.J.
McAndrew (Editors), Tilapia: Biology andExploitation. Kluwer Academic Publishers, The
Netherlands, 2000, pp. 227–266.
[13] Brueggemeier, R.W, Androgens, anabolics andantiandrogens. In: M.Verderame, (Ed.).
Handbook of Hormones, Vitamins, andRadiopaques. CRC Press, Inc., Boca Raton, FL,
USA, 1986. pp. 1-49.
[14] Killian H. S. and Kohler C.C., Influence of 17αmethyltestosterone on red tilapia under two
thermal regimes. J. World Aqua. Soc., Vol. 22,
1991, pp. 83-94.
[15] Guerrero R.D. and W.L. Shelton, An acetocarmine squash method for sexing juvenile
fishes. Progressive Fish Culturist, Vol. 35,
1974, p. 56.
[16] Fisher R.A., Statistical Methods for research,
Workers, 11th ed. Oliver and Boyd, London,
1950, pp. 1-354.
[17] Thongchai Y., Tharaphand W., Juthamas C. andSoontorn K., Seed Production of Sex Reversalof Nile Tilapia, Oreochromis niloticus(Linnaeus, 1758), in Fiberglass Tanks Using
Water Circulation System at Different Stocking
Densities. Technical Paper No. 21, 2011.
[18] Kriangsak M.A., Arnuparp W., Rogelio C. andYuthana S., The Concentration Level of 17αMethyltestosterone Hormone for Three Stainedof Tilapia Sex Reversal, Fisheries Conference
2006, pp 306-315.
[19] Nuanmani P., Saifon S. and Chintana N.,
Effects of androgens on sex reversal of niletilapia, Thai Fisheries Gazette (Thailand),Vol.57, No.3,2004 pp. 251-259.
[20] Boyd C.E., Water Quality in Warm water Fish
Ponds, Auburn University, 1979, pp. 1-39.

839

4th Int. Conf. on Science, Engineering & Environment ( SEE) ,Nagoya, Japan, Nov. 12-14, 2018, ISBN: 978-4-909106018 C3051

SEASONAL VARIATION AND SOURCE ANALYSIS
OF MONITORING PM10 DATA IN NORTHERN THAILAND
Pantitcha Outapa* and Katiya Ivanovitch
Faculty of Public Health, Thammasat University, Lampang, Thailand
ABSTRACTThis study examines emission sources and meteorological data affecting ambient concentrations ofpollution haze in Northern Thailand on the basis of particulate matter (PM10) concentrations monitored andcollected by Thailand’s Pollution Control Department over a three-year period at thirteen stations in eightprovinces. Increasing pollution and its major emission sources have been analyzed to reflect the seasonal variationof meteorological data over the periods of dry and rainy seasons. The results show that daily PM10 concentrations
were at their highest levels during the dry season from January to April. In the course of a three-year time span,from 2015 to 2017, almost all monitoring stations recorded average PM10 concentration levels that wereapproximately 1 to 3 times higher than the Thailand’s daily ambient air quality standard (120 µg/m3). It was also
observed that the average PM10 concentrations in areas under study were significantly higher than the average air
quality recorded during the rainy season. The meteorological data, including temperature and winds blowing fromthe southerly and southeasterly directions, were significantly related to the increase of average PM10
concentrations. By contrast, the relative humidity and the wind speed were significantly related with the decreaseof average PM10 concentrations. Forest fires and agricultural waste burning have been identified as the major
sources of PM10 concentration in each site.
Keywords: Particulate matter, Haze, Seasonal variation, Thailand

emission sources are analyzed on the basis of themeteorological data and haze pollution during dry andrainy seasons in Thailand’s 8 Northern provinces.
The
relationshipbetweenaverage
PM10
concentrations and the meteorological data has been
investigated at 13 monitoring stations, located in 8
Northern provinces and operated by Thailand’s
Pollution Control Department (PCD).

INTRODUCTION
For more than fifteen years, the haze pollution has
been a serious problem during dry seasons inNorthern Thailand [1], [7]. Emission sources areforest fires, biomass burning, motor vehicles, solid
waste burning and some industries [2]. The hazepollution has adverse effects on transportation bycausing visibility problems for air travel. More
importantly, the haze pollution also damages thehuman respiratory systems by high concentrations ofairborne particulates below 10 microns (PM10) [3],[8]. Likewise, a significantly negative impact ofPM10 depositions is observed on fruits, vegetables
and vegetation in general [3].
In 2016, Thailand’s pollution reports showed thatthe 24-hour average of repairable suspended
particulate matter (RSPM or PM10) in Northern
Thailand exceeded on many days the country’s
ambient air quality standard of 120 micrograms per
cubic meter (µg/m3), reaching the peak concentration
at 317 ug/m3 during the dry season from January to
April [9]. Forest fires alone accounted for 70% ofobserved PM10 concentrations [10]. Other factors
affecting PM10 concentrations included geography,
seasonal weather variations and meteorologicalconditions [1], [2], [4], [8].
In this study, average PM10 concentrations and

MATERIALS AND METHODS
Description of the study area and monitoring
stations
The area selected for this study covered thefollowing provinces in Northern Thailand: Chiang
Mai (20,107 km2), Mae Hong Son (12,681 km2),
Lampang (12,534 km2), Chiang Rai (11,678 km2),
Nan (11,472 km2), Phrae (6,539 km2) Phayao (6,335
km2) and Lamphun (4,506 km2). Most of the study
area is located in valleys surrounded by mountain
ranges. The area has thirteen air monitoring stations
managed by Thailand’s Pollution Control
Department (PCD). The map of the geographicalposition of the sites within the study areas is shown in
Fig. 1. The coordinates and the description ofmonitoring stations are presented in Table 1.

840

SEE Nagoya, Japan, Nov.12-14, 2018

Fig. 1 Study area and monitoring stations.

Table1. Coordinates of study sites and monitoring stations.
Province

Monitoring Station (Code)

LatitudeLongitude

Wiang Muang (WM)

19° 54' 33'' N

99° 49' 24'' E

Wiang Phang Kham (WPK)

20° 25' 38'' N

99° 53' 2'' E

Chang Phueak (CP)18° 50' 26'' N

98° 58' 11'' E

Si Phum (S)

18° 47' 27 '' N

98° 59' 24'' E

Phra Bat (PB)

18° 16' 42'' N

99° 30' 24'' E

Sop Pat (SP)18° 15' 3'' N

99° 45' 50'' E

Ban Dong (BD)18° 25' 37 '' N

99° 45' 27'' E

Mae Mo (MM)18° 16' 57 '' N

99° 39' 35'' E

LamphunNai Muang (NM)18° 34' 3'' N

99° 0' 29'' E

Mae Hong Son

Chong Kham (CK)

19° 18' 16'' N

97° 58' 18'' E

Nan

Nai Wiang (NW)

99° 0' 29'' N

100° 46' 35'' E

Phrea

Na Chak (NC)18° 7' 42'' N

100° 9' 45'' E

PhayaoWiang (W)19° 10' 0'' N

99° 53' 49'' E

Chiang Rai

Chiang Mai

Lampang

841

Characteristics
Suburban, 5 m
distance to the road.
Suburban, 5 m
distance to the mainroad.
Suburban, 150 m
distance to the road.
Urban, close to abusy road.
Suburban, 300 m
distance to the road,close to the airport.
Rural, 5 m distanceto the quiet road, apark surrounding.
Rural, a park
surrounding.
Rural, a park
surrounding.
Suburban, 100 m
distance to the road.
Suburban, a park
surrounding, close
to the airport.
Suburban, 100 m
distance to the road.
Suburban, 100 m
distance to the road,a park surrounding.
Suburban, 100 m
distance to the road.

SEE Nagoya, Japan, Nov.12-14, 2018

The PM10 concentration averages in dry andrainy seasons are presented in Figure 4. A three-year
peak of the average PM10 concentration is shown at
the CK monitoring station (210 ug/m3).
According to the selected areas of the study,
Lampang province showed the highest of 30% exceed
the average standard of Thai ambient PM 10 24-hour,
follow by Chiang Rai (23%), Mae Hong Son (18%),
Prae (12%), Chiangmai (9%), Phayao (6%) and Nan
province (2%), respectively.
In terms of seasonal variations, average PM10
concentrations during the dry season weresignificantly higher than during the rainy season(P<0.001, t-test). The standard deviations (SD) of
average PM10 concentrations during dry and rainyseasons were 73.38±13.05 and 20.05±5.32,
respectively. Results of the test are shown in Table 1.
Relationships
betweenaverage
PM10
concentrations and meteorological data, including
wind speed, wind direction, temperature and relative
humidity, were examined using datasets of the BD
monitoring station in the Lampang Province. That iswhere the highest average of PM10 concentrations
was found. The correlation coefficients of PM10
concentrations and meteorological data were thehighest for relative humidity (P<0.001), followed bywind speed (P=0.048), temperature (P=0.034) andwind direction from south (P=0.001) and southeast(P=0.01). The linear equation model of these
relationships is shown as Eq. (1).

PM10 concentration and meteorological data
analysisHourly PM10 concentrations at the 13 monitoring
stations were obtained from the PCD monitoring
system during the January-April dry season and theJune-September rainy season from 2015 to 2017.
Methods of Beta Ray attenuation and Tapered
Element Oscillating Microbalance (TEOM) wereused for measuring PM10 concentrations at themonitoring stations. That has made it possible toobtain differences of average PM10 concentrations
during dry and rainy seasons.
The daily meteorological data, including windspeed, wind direction, temperature and relative
humidity, were obtained from the PCD’s air
monitoring stations.
Source analysis
Data on burnt areas were obtained from the GeoInformatics and Space Technology Development
Agency (Public Organization), or GISTDA, ofThailand’s Ministry of Natural Resources andEnvironment. A linear regression analysis is used toinvestigate the relationship between average PM10
concentrations and burnt areas. That relationship is
also examined on the basis of fire hotspots data,obtained from Thailand’s Forest Fire Control
Division.

𝑌𝑌𝑃𝑃𝑃𝑃10𝑐𝑐𝑐𝑐𝑐𝑐. = 159.457 − 1.723𝑋𝑋𝑅𝑅𝑅𝑅 − 13.644𝑋𝑋𝑤𝑤𝑤𝑤 +0.868𝑋𝑋𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 + 9.538𝑋𝑋𝑤𝑤𝑤𝑤5 + 6.861𝑋𝑋𝑤𝑤𝑤𝑤4

RESULTS
Concentration and seasonal variation of PM10

(1)

Where YPM10con. is PM10 concentration in ug/m3;
XRH is relative humidity (%); Xws is wind speed inm/s; XTemp is temperature in Celsius degrees; Xwd5 is
wind direction from the south; Xwd4 is wind direction
from the southeast. The values of y-intercepts inabove equations could be interpreted as a relationshipbetween average PM10 concentrations andmeteorological data. The relative humidity and windspeed show a significantly inverse relationship withaverage PM10 concentrations (P<0.05), while theaverage PM10 concentrations are positively related tochanges in temperature and southerly and southeasterly winds (P<0.05).

Figure 2 shows average annual PM10
concentrations during dry and rainy seasons inThailand’s 8 Northern provinces from 2015 to 2017.
That evidence indicates that the Thai ambient PM10
annual standard of 50 micrograms per cubic meter(ug/m3) was not exceeded. However, during those
three years, the annual averages of PM10
concentrations were higher in dry seasons than inrainy seasons. In addition, Figure 3 shows that the
proportion of days (%) when PM10 concentrations (in24-hour averages) exceeded the Thai ambient PM1024-hour average standard (<120 µg/m3) in eachmonitoring station was approximately in the range of
8-19% for 2015, 6-30% for 2016 and 0-19% for 2017.

Table 1. Results of t-test comparing average PM10 concentrations in dry and rainy seasons.
Parameter
PM10 inDry season
PM 10 inRainy season

Mean

Std. Deviation

73.3829

13.05008

20.0520tdf

p-value

24.52238

0.001

5.31829842

SEE Nagoya, Japan, Nov.12-14, 2018

100
90
80

PM10 (µg/m3)

70
60
50
40
30
20
10
0
Dry 2015

Wet 2015

Chiang Rai
Lamphun
Phrea

Annual 2015

Dry 2016

Wet 2016

Chiang Mai
Mae Hong Son
PhayaoAnnual 2016

Dry 2017

Wet 2017

Annual 2017

Lampang
Nan
8 Provinces averageFig. 2 Average annual PM10 concentrations in Northern Thailand.

Fig. 3 Percentage by which daily average PM10 concentration exceeded standard in 13 monitoring stations.

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SEE Nagoya, Japan, Nov.12-14, 2018240
WET SEASONDRY SEASON

PM10 concentration (µg/m3)

180

120

60

0

day
WM

WPK

CP

S

PB

SP

BD

MM

CK

NW

NM

NC

W

Fig. 4 Daily average of PM10 concentration during dry and rainy seasons at 13 monitoring stationsin Northern Thailand
Source analysis of PM10 concentration

Year

Most forest fires in Northern Thailand areobserved during the dry season. The data collected by
the Department of Forestry in 2017 showed that the
major emission sources of haze pollution were forest
fires during the harvesting of non-timber products(75.21%), followed by hunting (7.76%) andagricultural burning (4.04%). Other factors accounted
for 12.99% of haze pollution.

2017

Table 2. Amount of fire hotspots in Northern Thailand(unit: point).

Year

2015

2016

Study area Agricultural Forest
Chiang Rai
74714
Chiang Mai
178
1,833
Lampang192
606
Lamphun57309
Mae Hong
168
2,142
Son
Nan
120
1,201
Phrea
110
319
Phayao36
177
Chiang Rai
127
1,235
Chiang Mai
134
758
Lampang155660
Lamphun39
204
Mae Hong
87
1,252
Son
Nan
66
977
Phrea
118
606

Study area Agricultural Forest
Phayao82
312
Chiang Rai
38
115
Chiang Mai
186
1,782
Lampang189465
Lamphun49
276
Mae Hong
48
1,114
Son
Nan
60
478
Phrea
55
244
Phayao
19
82

Total

5,200

Total
In addition, the information of the burnt areas,
detected by the Landsat 8 satellite images andpresented by the GISTDA, showed increasing PM10
concentrations during the dry season. The Pearson
correlation analysis found a significant relationshipbetween average PM10 concentrations and burnt
areas in 8 provinces over the period from 2015 to2017 (P<0.05). That was confirmed by the linear
regression analysis showing that burnt areas weresignificantly and positively related to PM10
concentrations (P<0.001). The equation estimatingthat relationships is shown as Eq. (2).

8,236

𝑌𝑌𝑃𝑃𝑃𝑃10𝑐𝑐𝑐𝑐𝑐𝑐. = 0.04𝑋𝑋𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 + 65.108(2)

Where YPM10con. is PM10 concentration in ug/m3
and Xarea is burnt area in km2. The values of yintercept in the equation above could be taken to
represent the PM10 concentration in burnt areas.

6,812

844

SEE Nagoya, Japan, Nov.12-14, 2018

The data in Table 2, obtained from Thailand’s
Forest Fire Control Division, show fire hotspots (inpoints) in the study area from 2015 to 2017,indicating that forest fires and the agricultural wasteburning remain the major sources of pollution. In
particular, as Eq. 3 shows, increasing average PM10
concentrations are significantly and positively related
to fire hotspots in each area (P<0.05).
𝑌𝑌𝑃𝑃𝑃𝑃10𝑐𝑐𝑐𝑐𝑐𝑐. = 0.049𝑋𝑋𝐻𝐻 + 62.289

Wangkarn
S.,
Tengcharoenkul
U.,
RayanakornEnviron M. Seasonal variation, risk
assessment and source estimation of PM 10 and
PM10-bound PAHs in the ambient air of Chiang
Mai and Lamphun, Thailand. Environmental
Monitoring and Assessment. Vol. 154, 2009, pp.
197-218.
[2] Oanh N.T.K., Leelasakultum K. Analysis ofmeteorology and emission in haze episodeprevalence over mountain-bounded region forearly warning. Science of the Total Environment
Vol. 409, 2011, pp. 2261–2271.
[3] Sooktawee S., Humphries U., Patpai A.,
Kongsong R., Boonyapitak S., Piemyai N.
Visualization and Interpretation of PM10
Monitoring Data Related to Causes of Haze
Episodes in Northern Thailand. Vol. 37, Issue 2,
2015, pp. 33-48[4] Pimonsree S. Seasonal variation of PM10
Concentrations in Northern Technology andInnovation for Sustainable Development.
International Conference (TISD2010) Faculty ofEngineering, Khon Kaen University, Thailand,
4-6 March 2010[5] Pardthaisong L., Sin-ampol P., Suwanprasit C.,
Charoenpanyanet A. Haze Pollution in Chiang
Mai, Thailand: A Road to Resilience. Procedia
Engineering Vol. 212, 2018, pp. 85–92.
[6] Pongpiachan S., Choochuay C., Chalachol J.,
Kanchai P., Phonpiboon T., Wongsuesat S.,
Chomkhae K., Kittikoon I., Hiranyatrakul P.,
Cao J., Thamrongthanyawong S. Chemical
characterisation of organic functional groupcompositions in PM2.5 collected at nineadministrative provinces in northern Thailand
during the Haze Episode in 2013. Asian Pacific
Journal of Cancer Prevention Vol. 14 , Issue 6,2013, pp. 3653-3661.
[7] Sirimongkonlertkul N., Upayokhin P., Phonekeo
V. Multi-Temporal Analysis of Haze Problem inNorthern Thailand: A Case Study in Chiang Rai
Province. Kasetsart Journal (Natural Science)Vol. 47, Issue 5, pp. 768-780.
[8] Li M., Zhang L. Haze in China: Current andfuture challenges Environmental Pollution. Vol.
189, 2014, pp. 85-86.
[9] Pollution Control Department (PCD). Thailand
state pollution 2017. Bangkok, Thailand, 2018.
ISBN 978-616-316-391-2.
[10] Kreasuwun J., Chotamornsak C., RatchiranukulP., Wiranvejayan O. Weather analysis and air
pollution warning. The Thailand Research
Fund. Bangkok, Thailand, 2008.

(3)

Where YPM10con. is PM10 concentration in µg/m3
and XH is the amount (in points) of fire hotspots.
CONCLUSION
This study is based on a 3-year dataset from2015 to 2017, collected at 13 monitoring stations inNorthern Thailand, to evaluate the sources and theseasonal variation of average PM10 concentrations.
The results show that the average PM10
concentrations are significantly and positively related
to burnt areas and the amount of fire hotspots in eachlocation covered by this analysis. The highest level ofPM10 concentration -- at 210 µg/m3 --during those
three years was found in the period of dry season.
Average dry season PM10 concentrations weresignificantly higher than those observed during therainy season (P<0.001, t-test).
The increasing average PM10 concentrations
were significantly related to meteorological data,such as temperature, southerly and southeasterly
winds. On the other hand, relative humidity and windspeed were found to have a significantly inverse
relationship with average PM10 concentrations.
Average PM10 concentrations were significantly andpositively related to increasing fire hotspots (P<0.05).
The main sources of PM10 concentrations in the areas
covered by this study were forest fires andagricultural waste burning.
The meteorological data indicate that seasonalchanges and PM10 emission sources have to be taken
together to investigate major causes of haze pollution.
ACKNOWLEDGEMENTS
The authors sincerely thank the Pollution
Control Department and the Forest Fire Control
Division of Thailand’s Ministry of Natural Resources
and Environment for providing the data used in thisanalysis. This study was partially supported for
publication by Thammasat University, Thailand.
REFERENCES[1] Pengchai P., Chantara S., Sopajaree K.,845

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

SPATIAL ANALYSIS OF COMMUNITY’S ACCEPTANCE FOR SUDSAPPLICATIONS IN NHIEU LOC – THI NGHE SUB-BASIN, HO CHIMINH CITY, VIETNAM

Nguyen Hoang My Lan1,2, Vo Le Phu2 and Le Van Trung2
Faculty of Urban Studies, Ho Chi Minh City University of Social Sciences and Humanities, VNU-HCM,
Viet Nam; 2 Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology,
VNU-HCM, Viet Nam
1

ABSTRACTWith the purpose of imitating the nature drainage process at the site before development, Sustainable Urban
Drainage System (SUDS) – a widely recognized solution to urban drainage and flood mitigation – is one of themost sustainable approaches to reduce the effect on the quality and quantity of run-off from urban developmentareas. Moreover, SUDS can improve the conditions of living environment for the communities, which defines thecommunity amenity and social benefit. The concept of community’s acceptance was used in this study to identify
the social benefit of SUDS techniques in Nhieu Loc – Thi Nghe sub-basin where flooded areas have increased inquantity, frequency and level of severity. The purpose of this paper, firstly, is to examine the relationship between
variables and the community’s acceptance of proposed SUDS techniques in Nhieu Loc – Thi Nghe sub-basin, Ho
Chi Minh City, including Rainwater Harvesting, Green Roof, Green Open Space, Pervious Pavement, and Pervious
Parking Lot. Then, the public acceptance data obtained from the survey from November 2016 to March 2017 wasadjusted and converted into GIS data layer. By correlation test in SPSS, there is a statistically significant
relationship between the community’s acceptance of SUDS techniques and both the understanding of SUDS
techniques and the living places of respondents in Nhieu Loc – Thi Nghe sub-basin. Through Hot Spot Analysis
in GIS, most of the acceptability hot-spots located in the extent of standard deviation ellipse of floods from 2007
to 2017 which lied entirely in the lowest elevation of the sub-basin. Therefore, the City government should increase
the community perception of SUDS as well as its benefits in flooding management before planning to improvecurrent drainage system.
Keywords: Sustainable Urban Drainage System, Spatial statistics, Community’s acceptance, Urban flooding
A perfect SUDS scheme or treatment train shouldhave a series of drainage techniques ranging fromprevention, source control, site control and regional
management, respectively. Through the SUDS
scheme, wherever possible, storm-water and run-off
should be managed and infiltrated into the ground bylandscape features, such as rain garden, swale, pond,
rather than being conveyed to and stored in large
conventional pipelines and treatment stations.
Building an ideal treatment train with a full range of
SUDS components is more practical for new
development than existing dense urban areas due tothe limitation of available spaces for complete
installation [33]. Hence, retrofitting existing stormwater management measures and turn them into
sustainable infrastructures are the most satisfactory
approach for flooding control in rapidly urbanizedareas, like Ho Chi Minh City where the built-up area
has increased over time. In SUDS treatment train or
management train, techniques in prevention andsource control stage should be preferred to others insite and regional control, which can be feasible andcost-effective in developed areas. According to

INTRODUCTION
The conventional drainage systems are designed
to collect and transport stormwater run-off fromurban areas as quickly as possible via sewer networks
and water treatment facilities to nearby receiving
water bodies [11]. Also, these systems are notplanned for either water quality improvement or
amenity making. On the contrary, Sustainable Urban
Drainage System – SUDS, introduced in the 1990s
and commonly applied in developed countries, isconsidered as one of the sustainable approaches todeal with urban flooding. According to The
Construction Industry Research and Information
Association – CIRIA (2007), SUDS is designed tominimize the impacts from the development on thequantity and quality of the runoff and maximize
amenity and biodiversity opportunities [22]. These
objectives should all have equal standing, and theideal solution will achieve benefits in all three
categories, although the extent to which this ispossible will depend on site characteristics andconstraints.
846

SEE - Nagoya, Japan, Nov.12-14, 2018

Lamond et. al (2014), the most appropriate SUDS
features for retrofit within dense central business
district (CBD) are green roofs, pervious paving,rainwater gardens and small treatment trains [44].
In term of social benefits, the most common
notion used to assess SUDS sustainability is thecommunity’s acceptability or acceptance [55, 6].
Chui and Ngai (2016) found that despite not having astrong understanding of SUDS or SUDS benefits, thecity dwellers in Hongkong were willing to pay for
SUDS retrofitting in public places and private
properties equal to 8.8% of the current government
spending on storm-water management and 1.8% of
the property price, respectively [55]. Also, theresidents in Dundee, Scotland, UK were willing to
pay more for their properties near the green spaces
provided by SUDS features; and the more they knew
about SUDS functions, the more they paid for
retrofitting SUDS [66].
Therefore, the objective of this paper is to answer
the question “Is there any significant relationshipbetween the community’s acceptance to SUDS
techniques and other variables, including thedemographic information, the knowledge of SUDS,
the places of living, and the spatial distribution ofinundations in Nhieu Loc – Thi Nghe sub-basin?”.

TN sub-basin has the lowest elevation which createsthe most frequently and seriously flooded routes.
From 2010-2017, this sub-basin has challenged
the annual average of twenty inundated locations
including the deepest and the most spreading in thewhole city. In this study, after collected from Ho Chi
Minh City’s Steering Center for Flood Control,
flooding data were analyzed and converted into GIS
layer for spatial pattern and trend analysis.
A face-to-face interview by questionnaire wasconducted from November 2016 to March 2017 with
238 households which distributed randomly in the
NL-TN sub-basin extend. Over 60% of the
respondents located around the NL-TN canal and in
the Eastern of the sub-basin where flooding has
occurred more frequently (Fig. 1). The number ofinterviewees in the Western was otherwise the lowest
because of limited accessibility. The 5-Likert scale
was used to quantify the answer to whether the
residents were willing to accept to install proposed
SUDS techniques in their properties or surrounding
areas. 1 in 5-Likert scale represents for Strongly
disagree and 5 represents for Strongly agree.
Moreover, the coordinate of households was collected
and then geocoded in ArcMap for further spatial
analysis.

STUDY AREA AND METHODOLOGY
Study area and data collection
Ho Chi Minh City, Vietnam is one of the Top 20
coastal cities with the greatest rate of the population
exposed to flooding in the 2070s (including bothclimate change and socioeconomic change) [77]. In
recent years, flooding has become the mostsignificant issue to affect the city’s growth and create
the economic loss, as well. Ho Chi Minh City
(HCMC) has considerably been flooded, especiallyduring the rainy season from June to November andduring flood-tide between September and December.
According to the Ministry of Natural Resources andEnvironment [88], with the worst case scenario ofclimate change, the average temperature andprecipitation in HCMC up to 2100 are projected toincrease 1 – 3.5oC and 14.7 – 23.4%, respectively.
Moreover, 17.8% of the city area will be flooded
when the sea level rises 100cm, in which Binh Thanh
is the most inundated district with more than 80% of
its area.
Based on the Master Plan of Drainage System in
HCMC to 2020 issued in 2001, Nhieu Loc – Thi Nghe
(NL-TN) sub-basin with the area of 33.2km2 is one of
the central drainage catchments in HCMC andcomprises whole or part of seven districts including 1,
3, 10, Phu Nhuan, Tan Binh, Go Vap, and Binh Thanh.
Land elevation in NL-TN sub-basin ranges from 0.5m
to 10.6m and ascends from the NL-TN canal toward
the Northern and the Southern. The Eastern of NL-

Fig. 1

Respondents’ distribution in Nhieu Loc –Thi Nghe sub-basin

The Statistical Package for the Social Sciences(SPSS) software (Version 23) was used for statisticalanalysis, including descriptive statistics andcorrelation tests between observed variables. In thisstudy, the Chi-square test and Kendal correlation test
were used to examine the relationship between
acceptability and other observed variables. The null
hypothesis was that the two or more than two sets ofmeasures were similar, used in Chi-square test andthat there was no correlation between two variables,used in Kendall correlation test. The significant value(p-value) of 0.05 or 95 percent confident was used toretain or reject the null hypothesis. Phi and Spearman
rank (Spearman’s rho) correlation coefficient werethen used to measure the strength of the relationshipbetween two variables after claiming that therelationship existed significantly. Both Phi and
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SEE - Nagoya, Japan, Nov.12-14, 2018

Spearman’s rho vary from -1 to 1 where positive
value indicates a direct relationship and negative
denotes an inverse correlation. The higher coefficientis, the stronger relationship exists between tested
variables.

𝑆𝑆𝑆𝑆𝑆𝑆𝑥𝑥 = � 𝑖𝑖=1

𝑛𝑛

Geotis-Ord Spatial Statistic

𝑆𝑆𝑆𝑆𝑆𝑆𝑦𝑦 = � 𝑖𝑖=1

𝑛𝑛

Hot Spot Analysis – one of the spatial statistic
tools in ArcMap (Version 10.4) is used to create amap of statistically significant hot and cold spots
based on Getis-Ord Gi* or Gi* statistic. This statistic
measures the degree of association that results fromthe concentration of points and all other points
included within a certain radius of distance from theoriginal point [99].

Where xi and yi are the coordinates for feature i,
� , 𝒀𝒀� } represents the Mean Center for the features,{𝑿𝑿and n is equal to the total number of features.
The rotation of the long axis measured clockwisefrom noon is calculated as:tan 𝜃𝜃 =𝐺𝐺𝑖𝑖∗ =

� 𝑛𝑛
∑𝑛𝑛
𝑗𝑗=1 𝑤𝑤𝑖𝑖,𝑗𝑗 𝑥𝑥𝑗𝑗 −𝑋𝑋 ∑𝑗𝑗=1 𝑤𝑤𝑖𝑖,𝑗𝑗𝑛𝑛
22𝑆𝑆�𝑛𝑛 ∑𝑛𝑛
𝑗𝑗=1 𝑤𝑤𝑖𝑖,𝑗𝑗 −(∑𝑗𝑗=1 𝑤𝑤𝑖𝑖,𝑗𝑗 )∑𝑛𝑛
𝑗𝑗=1 𝑥𝑥𝑗𝑗
𝑛𝑛∑𝑛𝑛

𝑆𝑆 = � 𝑗𝑗=1
𝑛𝑛

𝑥𝑥𝑗𝑗2

∑𝑛𝑛 (𝑦𝑦𝑖𝑖 −𝑌𝑌�)2

(5)

𝐴𝐴+𝐵𝐵
𝐶𝐶

(6)

𝐵𝐵 = �(∑𝑛𝑛𝑖𝑖=1 𝑥𝑥�𝑖𝑖2 − ∑𝑛𝑛𝑖𝑖=1 𝑦𝑦�𝑖𝑖2 )2 + 4(∑𝑛𝑛𝑖𝑖=1 𝑥𝑥�𝑖𝑖 𝑦𝑦�𝑖𝑖 )2(1)

𝐶𝐶 = 2 ∑𝑛𝑛𝑖𝑖=1 𝑥𝑥�𝑖𝑖 𝑦𝑦�𝑖𝑖

Where 𝑥𝑥� i and 𝑦𝑦� i are the deviations of the xycoordinates from the Mean Center. When the features
have a spatially normal distribution in which they aredensest in the center and become increasingly lessdense toward the periphery, one standard deviation iscreated to encompass approximately 68% of the input
features centroids.
In this study, two SDEs were created from the dataof flooding in 2017 and 2010-2017. The SDE of 2017
was calculated based on the hypothesis thatexperiences with flooding in the most recent year
would affect the community's acceptability toproposed SUDS techniques. After that, these SDEs
could be used to observe the spatial relationship of thecommunity’s acceptance to SUDS techniques andflooding situation or trend.

(2)− (𝑋𝑋� )2(4)

𝐴𝐴 = (∑𝑛𝑛𝑖𝑖=1 𝑥𝑥�𝑖𝑖2 − ∑𝑛𝑛𝑖𝑖=1 𝑦𝑦�𝑖𝑖2 )Where xj is the attribute value for feature j, wi,j isthe spatial weight between feature i and j, and n isequal to the total number of features. 𝑋𝑋� – the mean of
attribute x and S are calculated by the following
equations.
𝑋𝑋� =∑𝑛𝑛 (𝑥𝑥𝑖𝑖 −𝑋𝑋� )2(3)

The Gi* returned for each feature in the dataset isa z-score which, together with p-value, tells whether
the null hypothesis of the spatial concentration can berejected or not. A close-to-zero Gi* value implies
random distribution of the observed spatial events.
Conversely, positive and negative Gi* statistics withhigh absolute values correspond to the clusters ofhigh- and low-valued events, respectively [1010].
Hot Spot Analysis tool creates a new feature classwith a z-score, p-value and confidence level bin(Gi_Bin) for each feature in the input dataset. The
Gi_Bin field identifies statistically significant hot(high value) and cold (low value) spots, assigned
values of +/- 1, +/-2, and +/-3 reflecting the 99%,95%, and 90% of confidence level, respectively.
While features with 0 for Gi_Bin field are notstatistically significant clustering.

RESULTS AND DISCUSSIONS
The result of flooding data analysis shows thatflood occurred 167 times from 2007 to 2017 andconcentrated on roads in NL-TN sub-basin, with thetotal flooded route over 65,000 km. Submerged sites
mostly located in Binh Thanh district where is NLTN canal and Sai Gon river intersection and has thelowest elevation in sub-basin. Therefore, the Standard
Deviation Ellipse of floods in 2007-2017 (SDE-1)
lied mostly in Binh Thanh district with the long axes
doubled the short one and the rotation was more than
87 degrees. Particularly, based on directional trend
analysis, the SDE of floods in 2017 (SDE-2) covered
the NL-TN canal entirely as well as below 5m land
(Fig. 2) and had the area of 20km2, twice as much as
SDE-1. The trend of both SDE-1 and SDE-2 had thesame direction which was along the NL-TN canal andmostly parallel with the east-west axis of sub-basin.

Standard Deviational Ellipse
The Standard Deviational Ellipse (SDE) tool iscommonly used to measure the trend for a set offeatures. The output ellipse is shaped by the x- and ydirections from the mean center of the input dataset.
The SDE is given as:

848

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 2

Statistically significant Cold and Hot spots location of the community acceptance of SUDS techniques in
NL-TN sub-basin: (A) Rainwater Harvesting, (B) Green Roof, (C) Green Open Space, (D) Pervious
Pavement, and (E) Pervious Parking Lot

Table 1 Correlation efficient between acceptability to SUDS techniques and other observed variables

Acceptability to
SUDS techniques

Agea

Sexa

Incomeb

Rainwater Harvesting-0.104-0.067

Green Roof

-0.0210.221*
0.131

Knowledge ofcorresponding
techniquesa
0.428**

0.052

Green Open Space

0.156*

0.061

Pervious Pavement-0.068Pervious Parking Lot
Phi correlation efficientb
Spearman’s rho efficient*p = 0.05, **p = 0.01

-0.096

Districta

Flood frequencyb

0.475**

0.099

0.464**

0.454**-0.0240.046

0.530**

0.325

0.137*

0.083-0.0320.479**

0.408*

0.158*

0.162-0.106

0.388**

0.455**

0.133*a849

SEE - Nagoya, Japan, Nov.12-14, 2018

Rainwater Harvesting refers to the collection ofwater from surfaces on which rain falls andsubsequently storing this water for later use [1111].
Furthermore,domestic
householdrainwater
harvesting has the potential to groundwater recharge,
resulting reduction in the rate of land subsidence.
There is, however, still much concern about thequality of rooftop, stored rainwater, including
chemical and microbiological factors [1111], andavailable spaces for storage installation.
Green Roofs are the systems which cover abuilding’s roof with vegetation and designed toincrease localized infiltration, attenuation and/or
detention of storm-water [1212]. GR is one of the
SUDS components which can meet all the three goalsof sustainability: water quality, water quantity, andamenity [1313]. Most of the respondents showed theiranxieties for these two techniques because of theirdifficulties in both operation and maintenance.
Generally, pervious surfaces, such as Pervious
Pavement, Green Open Space and Pervious Parking
Lot, allow rainwater to infiltrate through the surface
into an underlying storage layer, where water is stored
before infiltration to the ground, reuse or release into
surface water [22]. Permeable pavements could be thepromising performance of the SUDS to provide
storage capacity for extreme rainfall and water quality
control to meet the good status required byenvironmental agencies [11]. However, that theoperation and maintenance of pervious surface may
be costly and need new skills [1414] is the reason for
those who totally disagree to install these methods (63of 124 comments).
In NL-TN sub-basin, the proposed SUDS
techniques are accepted more in Binh Thanh and Go
Vap, where inundation occurred more frequently andseverely than in district 1, 3 and 10 because of thelimitation of available spaces for construction. Basedon the results of correlation tests (Table 1), thesedifferences of acceptability by places are statisticallysignificant, except for GOS, and these associations
are from moderate to strong relationships (0.3 < Phicoefficient < 0.4). Besides, the understanding of
SUDS technique is the factor to make strong positive
relationships with SUDS acceptability, thus the City
government should increase the community
perception of SUDS as well as its benefits in flooding
management before planning to improve current
drainage system.
Figure 3 shows that NL-TN sub-basin has
experienced the annual average of twenty inundated
locations from 2010 to October 2017. In NL-TN subbasin, Nguyen Huu Canh street, passing the meancenter of SDE-1 (Fig. 2), possesses the deepest andthe most spreading flooded points in the whole city.
It is easily found that almost the hot spots of thecommunity's acceptance of five SUDS techniques

concentrated in the extent of SDE-1 and SDE-2. It
indicates that experiences with floods in recent years
have prompted respondents to adopt new and moresustainable drainage techniques. Moreover, these hot
spots also appeared in the North of sub-basin withhigher elevation and fewer flooded locations, except
for GOS. Respondents living along NL-TN canalpreferred to GOS because they wanted to not only
improve aesthetics but also manage floods for their
better living conditions.

Fig. 3

Number of flooded locations in Nhieu Loc –Thi Nghe sub-basin from 2010 to October
2017

CONCLUSIONSIn this study, the characteristics of thecommunity’s acceptance of five proposed SUDS
techniques were explored by collecting survey data,
statistical analysis, and correlation tests. Interestingly,
most of the respondents would be willing to adopt the
new and sustainable drainage techniques for better
living conditions. Among the significant influent
factors to the acceptability, how the respondents
know SUDS techniques and where they live are themost strongly positive ones. The research result
showed that, however, the residents in NL-TN subbasin favored the drainage techniques which areconstructed in public or surrounding areas rather thanthose retrofitted with their properties.
Regarding spatial pattern, spatial analysis andstatistics were used to only detect the community's
acceptance in the relationship to directional trend offloods in NL-TN sub-basin. Most of the acceptability
hot-spots located in the extent of standard deviation
ellipse of floods from 2007 to 2017 which lied
entirely in the lowest part of the sub-basin. For further
improvement, there is a need to increase the observed
samples to represent the whole sub-basinsignificantly and explore the spatial characteristics incorrelation to land-use data, especially the impervious
surface data.
REFERENCES[1] Zhou, Q., A Review of Sustainable Urban
Drainage Systems Considering the Climate

850

SEE - Nagoya, Japan, Nov.12-14, 2018

Change and Urbanization Impacts, Water, 6 (4)(2014) pp. 976-992.
[2] Woods-Ballard, B., Kellagher, R., Martin, P.,
Jefferies, C., Bray, R., and Shaffer, P., The SUDS
manual. Vol. 697. CIRIA, London, 2007.
[3] Mguni, P., Herslund, L. and Jensen, M. B.,
Sustainable urban drainage systems: examining
the potential for green infrastructure-basedstormwater management for Sub-Saharan cities,
Natural Hazards, 82 (2) (2016) pp. 241-257.
[4] Lamond, J., Wilkinson, S., Rose, C., and Proverbs,
D., Sustainable urban drainage: retrofitting for
improved flood mitigation in city centres. 2014.
[5] Chui, T. F. M. and Ngai, W. Y., Willingness topay for sustainable drainage systems in a highly
urbanised city: a contingent valuation study inHong Kong, Water and Environment Journal, 30(1-2) (2016) pp. 62-69.
[6] Jose, R., Wade, R. and Jefferies, C., Smart SUDS:
recognising the multiple-benefit potential ofsustainable surface water management systems,
Water Science and Technology, 71 (2) (2015) pp.
245-251.
[7] Hanson, S., Nicholls, R., Ranger, N., Hallegatte,
S., Corfee-Morlot, J., Herweijer, C., and Chateau,J., A global ranking of port cities with highexposure to climate extremes, Climatic change,
104 (1) (2011) pp. 89-111.
[8] Ministry of Natural Resources & Environment MONRE, Climate change and sea level rise

scenarios for Vietnam: summary for policymakers.
Ha Noi, 2016.
[9] Getis, A., Spatial filtering in a regression
framework: examples using data on urban crime,
regional inequality, and government expenditures,in Perspectives on spatial data analysis. 2010,
Springer. p. 191-202.
[10] Songchitruksa, P. and Zeng, X., Getis-Ord
spatial statistics to identify hot spots by using
incident management data, Transportation
Research Record: Journal of the Transportation
Research Board, (2165) (2010) pp. 42-51.
[11] Vo Le Phu and Bui, T. D., Rainwater harvesting:the new direction for Ho Chi Minh City, Vietnam,
Journal of Science & Technology, 50 (1C) (2012)
pp. 188-198.
[12] Ossa-Moreno, J., Smith, K. M. and Mijic, A.,
Economic analysis of wider benefits to facilitate
SuDS uptake in London, UK, Sustainable Cities
and Society, 28 (2017) pp. 411-419.
[13] Uzomah, V., Rapid decision support tool basedon novel ecosystem service variables for
retrofitting sustainable drainage systems in thepresence of trees. University of Salford, 2016.
[14] Malulu, I. C., Opportunities for integrating
sustainable urban drainage systems (SuDS) in
informal settlements as part of stormwater
management.
Stellenbosch: Stellenbosch
University, 2016.

851

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DEVELOPING FINE PARTICLE FILTERING SYSTEM FOR
MOTORCYCLE EXHAUST USING COCO FIBERS
Arinto Y.P. Wardoyo1, Firdy Yuana1, and Selly Y. A. Elbasari1
Faculty of Mathematics and Natural Science, Brawijaya University, Indonesia

1

ABSTRACT
Fine particles from motor vehicle exhaust emissions become a major problem for the environment andhuman health. This burden requires a new technology of filtering system with a high efficiency. However, thefiltering system for motorcycle exhaust is still limited. Thus, we developed a new filtration system using cocofibers mixed to tapioca glues with the variation ratio such as 50:50 (Filter 1); 60:40 (Filter 2); 70:30 (Filter 3);
and 80:20 (Filter 4). The efficiency is calculated by the ratio of the fine particle concentration in the exhaustemission before and after passing through the filter. The fine particle concentration was measured using a Digital
Dust Monitor (Kanomax, Model 3443) when the motorcycle was operating in the idle condition. The fineparticle concentration was measured for twenty sampling time. The filter efficiency was tested using threedifferent motorcycles (M1, M2, and M3). The result showed that the filter efficiency was found between 12%
and 33% depending on the filter thickness, density, and composition of the coco fiber and the glue.
Keywords: Fine particles, Coco fiber filter, Motorcycle, Exhaust emission, Efficiency

blood pressure alteration [5]. Many epidemiologic
studies have been conducted to investigate thepulmonary responses to the exposure to fineparticles in a mice model [6]. The previous studies
have confirmed that fine particles have anassociation with coronary artery disease [7]. They
are able to induce oxidative stress and to cause
inflammatory cytokines gene expression andsecretion [8].
Several studies have been conducted to improve
the filtration technology in the motor vehicle exhaustsystem. A diesel particulate filter (DPF) of theheavy-duty diesel trucks has been investigatedrecently [9]. The previous study confirmed the latest
filtration technology using an electrostatic force toreduce the concentrations of ionic ultrafine particles[10]. Even, the thermal energy generated from the
motorcycle muffler has been utilized to reduce theconcentration of fine particles [11].
In other sides, the data about a porosity-based
filter developed from the coconut fiber has not been
available. Meanwhile, the reference of the biomass
particulate filter for the motorcycle exhaust systemis still limited. In this study, four variations ofbiomass fine particle filters were tested in alaboratory test bench. The study included three
motorcycle samples in different manufacturers andengine types that selected randomly. The aim of thisresearch was to provide the detail information about
the performance of the particulate filter in reducing
the concentrations of fine particles emitted by
motorcycle, including the factors that related to thefilter efficiency.

INTRODUCTION
The population of a motor vehicle in the world
has been increasing from year to year. Some factorsthat influence the growth rate of the motor vehicles
are the increased population and the economic
growth [1]. The growth rate of motor vehicles was
also related to the urbanization [2]. From manykinds of motor vehicles, the motorcycle is widelyused as the common vehicle due to its highefficiency, low fuel consumption, long durability,and easy of use. Thus, the motor vehicle population
growth can be linked to the emission of motor
vehicles (particulate matter and gaseous emissions)that influence the air quality level.
Particulate matter (PM) is a key component of air
pollution in which motorcycle is one of the source.
Thus, PMs become a major problem for theenvironment. The size of PMs ranges fromnanometers (submicron) to microns in the diameter
size. Generally, they are classified into PM0.1(ultrafine particles), PM2.5 (fine particles), and PM10
(coarse particles).
Especially for the particulate matters with thediameter less than 2.5 µm, PM2.5 consists of major
and minor elements, inorganic ions, elemental
carbons, and some organic compounds [3]. The
accumulation concentrations of PM2.5 in the ambient
air, whether the indoor or outdoor environment, may
affect ecological balance and does have an impact
on human health. In an indoor environment, fineparticle toxicity was influenced by its deposition
velocity onto human body surfaces [4]. A long-term
exposure to fine particles was associated with the852

SEE - Nagoya, Japan, Nov.12-14, 2018room temperature and fine particle concentration
during ambient monitoring (Tambient = 27 – 28oC).
The location of the measurement was also greaterthan 1000 m from the nearest public roadway. The
particle measurement set-up (filter test bench) isrepresented in Fig. 1.

MATERIALS AND METHODS
Motorcycle Samples
The study included three different motorcycle
samples preferred randomly in Malang, Indonesia.
The description of the vehicle samples is presented
in Table 1. The names of the motorcycle samples are
replaced by the letter code of M1-M3.
Table 1 Motorcycle samples classification
Motor
Engine Capacity
Model
Samples
(cm3)
Years
M1
150
2013
M2
150
2013
M3
150
2013
Note: Each motorcycle sample was purchased fromrandom user in a standard engine condition (4-stroke
engine, manual transmission) with the same gasoline
type and octane number.

Fig. 1

Schematic of the bench-scale fine particle
filters test system.

Fine Particle Filters
Each filter was installed individually on theoutlet of the motorcycle muffler using a filter
converter kit (diameter: 76.2 mm). The motorcycle
engine was turned on for 1 minute for a warming up
process, with a constant condition (idling state at
1000 RPM). A Digital Dust Monitor (Kanomax Inc.,
Model 3443) was used to measure the fine particles
concentration. The pressure drop of the exhaust flowrate after treatment (vout) was monitored by an
Anemomaster (Kanomax Inc., Model A031). The
inlet (Tin) and outlet temperatures (Td) were
measured with digital thermometers. The ambient
temperature (Tambient), relative humidity, and gaseousemissions (CO and CO2) were reported from a QTrak (TSI, Model 8554). These measurements wereconducted before (Cin) and after (Cout) applying thefilter to the motorcycle muffler in every 10 seconds
as the interval time of the measurement. All
measurements were repeated three times.

The coco fibers were purchased from the local
market around Brawijaya University, Malang,Indonesia. The coco fibers were chopped up andnaturally air-dried in order to reduce the moisture
content. When the fibers were dry (moisture content< 15%), the coconut fibers were grinded to become
the fine-grained powder. The powder was mixed
with the tapioca glue in four different variation
ratios in order to generate four different filters: F1,
F2, F3, and F4. The filter cake was mixed with thedilution water. When it came blended, it was pressedon a metal screen with a constant pressure in orderto generate a filter sheet with the specific thickness(Table 2). The filter sheet was naturally air-dried.
Table 2 Specifications of the fine particle filters
Parameter
Coco Fiber :Glue (Ratio)
Diameter [cm]Thickness [cm]Density[g/cm3]
Dilution Water
[cm3]

F1
50:50

F2
60:40

F3
70:30

F4
80:20

7.620
0.154
0.232

7.620
0.178
0.215

7.620
0.205
0.201

7.620
0.241
0.195

500

500

500

500

Statistical Analysis
The recorded fine particle concentrations wereanalyzed using Eq. (1) in order to determine thefilter efficiency (Ef) [10].
Ef = [(Cin - Cout) / (Cin)] x 100%

(1)

The filter efficiency was interpreted as the mean
± SD from all motorcycle samples. The difference
between filter was determined using a Student’s ttest, in which the p-values of less than 0.05 wereconsidered to be statistically significant [6]. The
statistical analysis was carried out using Microsoft
Excel 2016.

Particle Measurement
Particle measurement was conducted at theLaboratory of Air Quality and Astro Imaging
Physics Department, Brawijaya University, Malang,Indonesia. The measurement was conducted in anindoor room (laboratory test bench), with a constant
853

SEE - Nagoya, Japan, Nov.12-14, 2018

RESULTS
Fine Particles Concentration
In order to understand the filtration behavior on
the fine particles reduction, the concentrations offine particles were measured before and after
applying the filter. Fig. 2 shows the effects of theinstalled filters with a constant condition. Comparedto the Cin, all filters could decrease theconcentrations of fine particle emissions (p < 0.05).

Fig. 3Filter performance on fine particle
concentrations, p < 0.05 (mean ± SD fromthree repeated measurements in threedifferent motorcycle samples).

Figure 3 shows the efficienccy of the four
different filters with the different thickness level.
Based on the filter thickness, F4 had the highest
efficiency when applied in M1 (33%), whereas thelowest efficiency was obtained at F1 applied in M1(12%). The similar results were found in M2 and M3.
In the sample of M2, F1, F2, F3, and F4 generated
16%, 20%, 28%, and 32% of the filter efficiencies,
respectively. Similarly, F1 and F2 generated 13%
and 18% of the filter efficiencies when applied in
M3. On the other hands, the efficiencies of the filters
F3 and F4 in M3 were 28% and 32%, whereas theF4 generated the highest efficiency. The value wassignificantly higher than the efficiency of F1 (up to
19% higher). Among three different motorcycle
samples, F4 has the highest efficiency. This result
was consistent with the result obtained from theprevious study [12].
DISCUSSION

Fig. 2

Figure 3 depicts the mean efficiency, in which
the filter efficiency is influenced by the thicknessesof the filters. This tendency is proven in this study,as the thickness variation of the filter wasinvestigated to determine the efficiency. According
to the results, the increase in the filter thickness has
better ability in reducing fine particles showing to
the higher efficiency. In order to get a better
understanding, Fig. 4 below interprets thecorrelation between the filter thickness and the filter
efficiency.

Fine particle concentrations of F0 (Cin) and
Cout from Filter 1 (F1) - Filter 4 (F4) for all
motorcycle samples: (A) M1; (B) M2; and(C) M3.

Filter Efficiency
Filtration test was conducted to determine thefilter efficiency in reducing fine particles. Figure 3
below represents the filter performances (mean ± SD,
for all motorcycle samples, n = 3), as calculatedusing Eq. (1) .
854

SEE - Nagoya, Japan, Nov.12-14, 2018

had measured the level of pressure drop related to
the flow rate of the emission. The results showedthat F1 had the most pressure drop (58%).
Meanwhile, the lowest pressure drop level wasreferred to F4, as the most porous filter (22%).
Based on the flow rate measurements of the outlet,
the values of vout was 0.09 m/s, 0.10 m/s, 0.11 m/s,
and 0.16 m/s for F1, F2, F3, and F4 respectively. In
other sides, the vin was 0.21 m/s. There was nodifference between Tin and Td.

Fig. 4The correlation between filter thickness andfilter efficiency.

Based on Fig. 4, the linear regression analysis
shows an extreme positive correlation between thefilter thickness and the filter efficiency, since the R2
value is 0.98 (≈1). The correlation is interpreted as alinear function with the approximation equation y =22.27x – 20.56. This trendline indicates that there isa strong correlation between the filter thickness andthe filter efficiency.
The different efficiency level Ef of the filters
might be related to the filter porosity. In this state,
the porosities across the substrate of the coconut
fibers might influence the filter efficiency. As
confirmed in the previous study, the porosity
distribution of the filter, including the pore size
distribution, can represent the performance of aparticulate filter [13]. The porosity level of a filter
has a correlation with the filter thickness and density.
According to the results, F4 had the highest filter
efficiency. Interestingly, the thickness of F4 was thehighest, 0.24 cm. In contrast, the density of the filter
F4 was only 0.195 g/cm3. Although F4 was the
thickest filter, F4 had the lowest density level. These
results indicated that F4 had the most porosity level
due to their lowest density level.
As shown in Table 2, F4 is the thickest filter(0.36 – 0.87 mm thicker than other filters) with thelowest porosity level. Thus, as expected F4 has thehighest efficiency level, related to the filter
thickness. As the thickest filter, F4 might have more
fibroin content due to its high coco fiber ratio (80%).
The coco fiber ratio of F4 was up to 10% higher thanF3, F2, and F1. These different coco fiber ratio
might influence the porosity of the filters since thefluid flow through porous media is related to themedia porosity [14]. Since the filter density is not
only the influencer factor, the filter efficiency ismuch more influenced by the filter thickness.
The density and porosity might indicate theexistence of pressure drop that reflected filter
performance [15]. As interpreted below (Fig. 5), we

Fig. 5a). Filter thickness vs pressure drop, R2 =0.89; b). Filter density vs pressure drop, R2= 0.66.

These results reflect the correlation (linear
regression functions) between the filter density –filter thickness and pressure drop, together with thefilter performance Ef. The thickness of the fibrous
media structures influences the permeability and theairflow [16]. The more porous filter had moretapioca glue. The more concentration of coco fiber
increased the filter efficiency, together with thedecreasing amount of the pressure drop. These
results indicated that the thickest filter F4, with thehighest coco fiber ratio, could decrease the most fineparticles concentration though it had the lowest
density level.
CONCLUSION
We have developed the filter using coco fibers formotorcycle fine particles with the efficiency in therange of 12 to 33% depending on the filter thickness,
855

SEE - Nagoya, Japan, Nov.12-14, 2018

density, and the composition ratio between cocofibers and tapioca glue.

[8] Cachon B. F., Firmin S., Verdin A., Ayi-fanou
L., Billet S., Cazier F., Martin P. J., Aissi F.,
Courcot D., Sanni A., and Shirali P.,
Proinflammatory effects and oxidative stresswithin human bronchial epithelial cells
exposed to atmospheric particulate matter(PM2.5 and PM>2.5) collected from Cotonou,
Benin, Environ. Pollut., Vol. 185, 2014, pp.
340–351.
[9] Quiros D. C., Yoon S., Dwyer H. A., Collins J.
F., Zhu Y., and Huai T., Measuring particulatematter emissions during parked active diesel
particulate filter regeneration of heavy-duty
diesel trucks, J. Aerosol Sci., Vol. 73, 2014, pp.
48–62.
[10] Wardoyo A. Y. P., Budianto A., andAbdurrouf, Filtration of submicron particles
from motorcycle emission using a DC low
electrostatic filter, Int. J. Appl. Eng. Res., Vol.
12, No.8, 2017, pp. 1725–1728.
[11] Wardoyo A. Y. P., Nuriyah L., and Darmawan
H. A., Developing Reheated Filter ofMotorcycle Exhaust for Reducing PM2.5
Emissions, in Proc. Int. Semin. Sensor,
Instrumentation, Meas. Metrol., 2017, pp. 42–
45.
[12] Wardoyo A. Y. P., Juswono U. P., and Riyanto
S., Developing particulate thin filter using
coconut fiber for motor vehicle emission, in
Proc. AIP Conf. Proc. 1719, 2016, pp. 0300431-030043-4.
[13] Gong J., Stewart M. L., Zelenyuk A., Strzelec
A., Viswanathan S., Rothamer D. A., Foster D.
E., and Rutland C. J., Importance of filter’s
microstructure in dynamic filtration modelingof gasoline particulate filters (GPFs):
Inhomogeneous porosity and pore size
distribution, Chem. Eng. J., Vol. 338, 2018, pp.
15–26.
[14] Tien C. and Ramarao B. V., Can filter cakeporosity be estimated based on the KozenyCarman equation?, Powder Technol., Vol. 237,
2013, pp. 233–240.
[15] Rapagnà S., Gallucci K., and Foscolo P. U.,
Olivine, dolomite and ceramic filters in one
vessel to produce clean gas from biomass,
Waste Manag., Vol. 71, 2018, pp. 792–800.
[16] Gervais P., Bémer D., Bourrous S., andRicciardi L., Airflow and particle transport
simulations for predicting permeability andaerosol filtration efficiency in fibrous media,
Chem. Eng. Sci., Vol. 165, 2017, pp. 154–164.

ACKNOWLEDGEMENTS
The authors wish to acknowledge Arif Budianto,
Mia A. Pawestri., Ayu Wenda I. Putri., Rudi Andika,and Renado Anggara for their excellent technicalassistance.
REFERENCES[1] Dayal Sharma R., Jain S., and Singh K.,
Growth rate of Motor Vehicles in India Impact of Demographic and Economic
Development, J. Econ. Soc. Stud., Vol. 1, No.
2, 2011, pp. 137–154.
[2] Riley K., Motor Vehicles in China: The Impactof Demographic and Economic Changes,
Popul. Environ., Vol. 23, Issue 5, 2002, pp.
479–494.
[3] Minguillón M. C., Rivas I., Moreno T.,
Alastuey A., Font O., Córdoba P., ÁlvarezPedrerol M., Sunyer J., and Querol X., Road
traffic and sandy playground influence on
ambient pollutants in schools, Atmos. Environ.,Vol. 111, 2015, pp. 94–102.
[4] Shi S., Li Y., and Zhao B., Deposition velocity
of fine and ultrafine particles onto manikin
surfaces in indoor environment of different
facial air speeds, Build. Environ., Vol. 81,
2014, pp. 388–395.
[5] Chan S. H., Van Hee V. C., Bergen S., Szpiro
A. A., DeRoo L. A., London S. J., Marshall J.
D., Kaufman J. D., and Sandler D. P., Longterm air pollution exposure and blood pressurein the sister study, Environ. Health Perspect.,Vol. 123, No.10, 2015, pp. 951–958.
[6] Bai R., Zhang L., Liu Y., Meng L., Wang L.,
Wu Y., Li W., Ge C., Le Guyader L., and Chen
C., Pulmonary responses to printer tonerparticles in mice after intratracheal instillation,
Toxicol. Lett., Vol. 199, 2010, pp. 288–300.
[7] McGuinn L. A., Ward-Caviness C., Neas L.
M., Schneider A., Di Q., Chudnovsky A.,
Schwartz J., Koutrakis P., Russell A. G.,
Garcia V., Kraus W. E., Hauser E. R., CascioW., Diaz-Sanchez D., and Devlin R. B., Fine
particulate matter and cardiovascular disease:
Comparison of assessment methods for longterm exposure, Environ. Res., Vol. 159, 2017,
pp. 16–23.

856

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

POLYETHYLENETEREPHTHALATE-BASED ACTIVATED CARBONPRODUCTION: PRELIMINARY STUDY ON KOH ACTIVATIONWITH MICROWAVE ASSIST
Sirasit Meesiri1, Nattawut Seayang1, Weeraphong Homnan1, Navadol Laosiripojana2, and Anusorn Boonpoke1
1
School of Energy and Environment, University of Phayao, Thailand
2
The Joint Graduate School of Energy and Environment,
King Mongkut's University of Technology Thonburi, Thailand

ABSTRACT
Since the beginning of the plastic age, drinking bottle waste has been increasing worldwide. Petroleum plastic
waste is composed mainly of Polyethyleneterephthalate (PET), which is durable and can remain in the environment
for a long period, thereby causing significant harm to humans, flora, and fauna. Waste recycling is one of thepromising mitigation strategies being used to reduce the amount of final disposal. This research, a preliminary
investigation of activated carbon production conditions from PET bottle waste, was carried out using fractional
factorial design (FFD) with 95% confidence level. Starter material PET waste was obtained from a local recycling
factory. Crusted and sieved PET was carbonized at 700 oC for 1 h., then impregnated with potassium hydroxide(KOH) and heated in a microwave. The production factors included char:KOH ratio (1 to 3 by weight), microwave
power (540 to 900 watt), and microwave heating time (10 to 30 min). PET-based activated carbon (PET-AC)
showed high iodine adsorption capacity ranging from 759.38–1,125.34 mg/g. It was found that all production
factors were significant contributors to the characteristics of PET-AC. The highest iodine adsorption capacity was
found at the condition of 3 by weight, 900 watt, and 30 min for ratio, microwave power, and heating time,
respectively. This research confirmed that PET bottle waste could be converted to a highly valuable nanoporous
adsorbent. However, the optimum production conditions for PET-AC will be carried out using a more detailed
describable design of experiment (DOE).
Keywords: Activated carbon, Polyethyleneterephthalate, Design of experiment, Microwave

using CO2 and steam provided a surface area of 1,000
m2/g [11, 18, 19] while chemical activation gave
1,000–3,200 m2/g [6, 14, 16]. Convection furnace has
been used as activation reactor at high temperature in
the activation process with a long time period andhigh energy consumption, with the resulting nonuniform porosity and surface of activated carbon [4,20]. Recently, microwave irradiation has been
performed because it has a shorter activation time andreduces the non-uniform problem. The microwave
heating is different from convection or conduction
heating; it heating within the molecular level by
dipole rotation and ionic conduction [21, 22].
Microwave heating consumes less energy thanelectrical furnace heating [23].
This research aimed to investigate the optimum
production condition of PET-based activated carbon
using chemical activation and microwave heating.

INTRODUCTION
Activated carbon (AC) is a black material withhigh surface area and high porosity. It have been
widely used in various applications such as
separation/purification of gas and liquids, removal ofcolor and toxic substances in water [1-4]. The
activated carbon could be made from various raw
materials that contain low ash content, high fixed
carbon, and low cost [5], such as coal [6], coconut andpalm shell [7], wood [8], agricultural residual [9],pipe (PVC) [10], and PET bottle waste [11, 12]. PET
is one of the most abundant municipal, industrial, andocean wastes. It takes approximately 180 years todegrade. To lessen the problem of PET waste, it could
be used as the starter material for activated carbon
production due to its low organic content and a highpercent of carbon yield post the carbonization process[13].
Activated carbon preparation can be made by two
different methods: physical activation using CO2 andsteam for increased surface area and porosity, andchemical activation by chemical agents such as KOH[14], ZnCl2 [15], HNO3, and NaOH [16, 17].
Typically, the surface area in chemical activation ishigher than in physical activation. Physical activation

METHODOLOGY
PET-char Preparation
The PET bottle waste was washed and crushed to
1–3 mm. and dried at 80oC for 24 h. PET wasconverted to char to remove volatile matter and
857

SEE - Nagoya, Japan, Nov.12-14, 2018

increase carbon content before activation. Twenty
grams of sieved PET was carbonized at 700oC with a
10oC/min heating rate under nitrogen atmospheres for
1 h., and then it was cooled at room temperature. The
remaining black solid material was called char.

RESULTS AND DISCUSSIONPET Activated Carbon Characteristics
The N2 adsorption isotherms of the produced
PET-AC indicated type IV with hysteresis loop (Fig.
1) based on the classification isotherm of IUPAC
classification [24, 25]. It was indicated that PET-AC
was composed mainly of mesoporous materials [11,24, 25].
The pore size distribution of PET-AC was shownin Fig. 2. The number of pores in microporous andmesoporous rang with an average pore size of 2.03
nm. The BET surface area for the PET-AC was 1,345
m2/g with a total pore volume of 0.68 cm3/g. The
obtained PET-AC had a relatively high surface area
compared to previous reports, as shown in Table 1.

PET-AC Preparation
The mixture of char and KOH at designed ratios(1:1 and 1:3 by wt.) were placed in a quartz tube
container with 32 mm diameter and heated in a
microwave oven (Samsung model ME711K) under anitrogen flow rate of 200 ml/min at given power (540and 900 watt) and time (10 and 30 min). Then, theactivated char was rinsed with 10% hydrochloric acidand washed with hot distilled water until the pHreached neutral. The solid adsorbent was dried at
105oC overnight. The resulting activated char wasthen called PET-based activated carbon (PET-AC).
PET-AC Characterization
Iodine number was determined using Standard
Detection Method (ASTM Designation: D4607-86).
The surface area, pore volume and pore size
distribution of PET-AC were analyzed by using N2
adsorption/desorption isotherms at 77 K (Micro
Active for ASAP 2460, Norcross, USA). The surface
area was calculated with the Brunauer Emmett Teller(BET) theory. Pore volume and pore size distribution
were calculated by non-negative regularization. The
surface morphology of PET-AC was taken byscanning electron microscopy (SU8030, Hitachi,
Tokyo, Japan). The carbon, hydrogen, nitrogen, andsulfur contents were determined by elemental
analyzer (LECO CHN628 Series Sulfur, USA) andapproximate analysis was used to determine themoisture. Volatile organic carbon, fixed carbon, andash was carried out according to the ASTM D 758210.

Fig. 1 N2 adsorption/desorption isotherm of PET-AC
obtained from the optimum production condition

Experimental Design
This is the design of the experiment using
fractional factorial design (FFD) to determine theoptimum conditions for the preparation of PET-AC.
The investigation factors char:KOH ratio (by wt.),
microwave power (watt), and microwave heatingtime (min) were selected in the model. The FFD wasdone for three factors, two levels, and three replicates,with a total of 12 experiments.

Fig. 2 Pore size distributions of PET-AC

Table 1 Comparison of the pore structure of activated carbon from different method
Raw material
PET
PET
PET
PET
PET

Activating agent
KOH
CO2
CO2
CO2
Steam

Heating method
Microwave
furnacefurnacefurnacefurnace

858

SBET (m2/g)
1,345
1,117
790
1,110
1,170

VT (cm3/g)
0.68
0.44
0.43
0.39
0.63

Ref.
This work
[18]
[11]
[26]
[19]

SEE - Nagoya, Japan, Nov.12-14, 2018

pore volumes of the high and low carbon content
activated carbon, it can be seen that the activatedcarbon with high carbon content has surface area andpore volume higher than activated carbon with low
carbon content.

Scanning Electron Microscopy (SEM)
The SEM morphologies of the PET-char and PETAC are showed in Fig. 4. From the SEM images, it
was observed that PET-AC exhibits a higher pores
distribution than PET-char after being carbonized bychemical activation and microwave heating process.

Optimum PET-AC Production Conditions
The predicted optimal values for the independent
factor were as follows: 3 by weight, 900 watt, and 30
min for ratio, microwave power, and heating time,
respectively. This work, the preparation conditions of
PET-AC using FFD are generated by Design Expert
software. The various conditions and levels are given
in Table 3. The analysis of variance (ANOVA) of
iodine adsorption capacity are shown in Table 4. It
was indicated that all observed factors, A (char:KOH
ratio), B (microwave power), and C (microwave
heating time) are significant (p-value less than 0.05).
A regression equation is developed by FFD for iodine
adsorption are shown in Eq. (1).
Iodine adsorption = + 888.06 + 52.66 A + 105.41B+ 71.67C(1)

Table 3 Factors and levels
Factors

Fig. 4 SEM images of PET-char and PET-AC

Code

Level
-1

+1

Char:KOH ratio

A

1

3

Microwave power (watt)

B

540

900

Microwave heating time
(min)

C

10

30

Elemental Analysis
The suitability of the model equation was
evaluated by 0.9918 and 0.9866 of adjusted R2 andpredicted R2, respectively. The fact that the adjusted
R2 and the predicted R2 are high indicates that there isa good equation in this model between the experiment
data and the model prediction [5, 9, 22, 28]

The elemental analyses of PET-char and PET-AC
are showed in Table 2. It was found that the PET-AC
shows a higher carbon content than the PET-char due
to the elimination of some oxygen from the carbon
surface [27]. If we compare the surface areas and total
Table 2 Elemental analyses of PET-char and PET-AC

C

H

O

N

S

SBET
(m3/g)PET-Char

55.76

1.43

42.55

0.26

-

-

-

This work

PET-AC

80.08

1.45

17.94

0.52

-

1,345

0.680

This work

PET-50S2

96.49

0.42

2.97

0.08

-

1,524

0.607

[18]

PET-50C3
97.31
0.42
2.21
dry basis2
PET-based activated carbon steam activation3
PET-based activated carbon CO2 activation

0.02

-

1,850

0.743

[18]

SampleUltimate analysis (%)1

1

859

VT
(cm3/g)Ref.

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 4 Analysis of variance (ANOVA) for fractional factorial design
SourceModel
A
BC
Pure error
Cor total

Sum ofsquares
2.282E+05
33271.64
1.333E+05
61643.37
1366.78
2.296E+05

Df

Mean square

F-valueP-value

3
1
1
1
8
11

76082.71
33271.64
1.333E+05
61643.37
170.85445.33194.74780.42360.81< 0.0001< 0.0001< 0.0001< 0.0001

The predicted versus actual plots for iodine
adsorption capacity are shown in Fig. 5. The actual
iodine adsorption capacity was the real experimental
data while the predicted iodine adsorption capacity
represented adsorption capacity by using
optimization (Eq. (1)). It was shown that the predictedvalues agreed well with the actual indicating highmodel ability [22, 29].

watt, and 30 min for ratio, microwave power, andheating time, respectively. The highest iodine
adsorption capacity was 1,117.8 mg/g. The BET
surface area for PET-AC was 1,345 m2/g.

(A) Microwave power versus char:KOH ratio

Fig. 5 Plot of actual response versus predicted
response for iodine adsorption capacity
The response surface of combined effect ofoverall factors in this work (char:KOH ratio,
microwave power and microwave heating time) are
shown in Fig. 6. The iodine adsorption capacity of
PET-AC increases with the increase in all factors dueto the improvement in the porosity of the activatedcarbon.
CONCLUSION
The PET-based activated carbon was successfully
produced by KOH activation heating by microwave
radiation. The optimum condition for the preparationof PET-based activated carbon were 3 by weight, 900(B) Microwave heating time versus char:KOH

860

SEE - Nagoya, Japan, Nov.12-14, 2018[7]Su, W., L. Zhou, and Y. Zhou, Preparation of
Microporous Activated Carbon from Raw
Coconut Shell by Two-step Procedure1
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Foundation of China (No.20336020). Chinese
Journal of Chemical Engineering, 2006. 14(2): p.
266-269.
[8]Wang, T., S. Tan, and C. Liang, Preparation andcharacterization of activated carbon from wood
via microwave-induced ZnCl2 activation. Carbon,
2009. 47(7): p. 1880-1883.
[9]Xin-hui, D., et al., Regeneration of microwave
assisted spent activated carbon: Processoptimization, adsorption isotherms and kinetics.
Chemical Engineering and Processing: Process
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Preparation and evaluation of activated carbons
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2012. 43(4): p. 631-637.
[12]Mendoza-Carrasco, R., et al., Preparation ofhigh-quality
activatedcarbonfrompolyethyleneterephthalate (PET) bottle waste. Its
use in the removal of pollutants in aqueous
solution. Journal of Environmental Management,
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[13] László, K., Adsorption from aqueous phenol andaniline solutions on activated carbons withdifferent surface chemistry. Colloids andSurfaces A: Physicochemical and Engineering
Aspects, 2005. 265(1): p. 32-39.
[14] Otowa, T., Y. Nojima, and T. Miyazaki,
Development of KOH activated high surface areacarbon and its application to drinking water
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[15] Xiao, X., et al., Preparation of activated carbon
from Xinjiang region coal by microwave
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(C) Microwave heating time versus microwave
power
Fig. 6 3D response surface graph for Iodine
adsorption capacity.
Acknowledgements
This study was financially supported by the
National Research Council of Thailand (NRCT),
University of Phayao (RD60054) and the Thailand
Graduate Institute of Science and Technology(TGIST: SCA-CO-2560-4588-TH).
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862

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECT OF SUSPENDING TRAFFIC ON A HIGHWAY IN A
MOUNTAINOUS REGION IN CENTRAL JAPANON THE SUCCESSION OF SLOPE VEGETATION
Teruo Arase1, Akane Nishio1, Tetsuo Okano1 and Taizo Uchida2
1
Faculty of Agriculture, Shinshu University, Japan;
2
Faculty of Engineering, Kyushu Sangyo University, Japan

ABSTRACT
Gonbei Highway, a winding road in a mountainous region in central Japan, was damaged by typhoons in theautumn of 2004, and a 9-km stretch of the highway has remained closed (without being restored). We established11 survey sites to examine slope vegetation along Gonbei Highway in the summer of 2004 (just before the area
was damaged by typhoons), and we conducted surveys again in 2016 (12 years after the damage), including at 5
survey sites along the closed section of the road. At each survey site, a quadrat (2 m × 5 m) was established on
the mountain side and the valley side of the road. The deterioration of the road surface was also observed. Here,
we examine the effects of suspending traffic on roadside vegetation and road surface deterioration. Our results
showed that succession to arboreal vegetation was not observed at the roadside sites along the closed section of
the road: vegetation coverage increased significantly along the closed section with increasing coverage of shrubs(mainly bamboo grass). In contrast, tree seedlings increased in the passable sections. Thus, the suspension of
traffic and the subsequent long-term absence of roadside vegetation management allowed bamboo grass toincrease, and the community of bamboo grass prevented invasion and growth of tree seedlings. Obvious
deterioration of the road surface was not observed, excepting sparse cracks and weed invasion. Consequently,
the dominance of bamboo grass may be one of the criteria by which to judge the necessity of vegetation
management along roads closed to traffic.
Keywords: Roadside Slope, Road surface, Vegetational succession, Suspension of traffic, Gonbei Hyghway

be surveyed 10 to 12 years after traffic is suspended.
Gonbei Highway, an asphalt mountain road in
Nagano Prefecture in central Japan, has fulfilled an
important role in joining the two regions (Kami-ina
and Kiso regions) on either side of the Kiso
Mountains. This highway is a winding mountainroad that crosses the Gonbei Pass at an elevation of1550 m and was designated as a national highway(Route 361). In the autumn of 2004, rainfall andwinds from several typhoons passing over the area
(Fig. 1) damaged the highway, and a 9 km section
located on Mt. Kyogatake was closed [6]. In 2006, a
new and less winding highway (bypass of Route361) traversing the newly constructed ‘Gonbei
tunnel’ was opened to traffic [6]. This road
construction was undertaken in order to improveaccess to medical services for residents in the Kiso
region, where there are no general hospitals.
Subsequently, Old Route 361 was closed without
being restored following the disaster in 2004 and thedesignation as a national highway was removed (Fig.
2). Despite the change in designation, this roadremains important: the area along this road is aJapanese larch (Larix kaempferi) forest, and someradio facilities are located there. Further, if traffic on
the new Route 361 is suspended, the Old Gonbei
Highway will be the only road joining these two

INTRODUCTION
Recently, fewer winding roads with tunnels or
elevated bridges have been newly built as highway
construction has focused on roads with higher traffic
volume and improved safety. While the necessity ofmaintaining old highways is reduced in this strategy,
abandoning these highways may lead to disasters
such as landslides: since roads placed on hillsides
can disrupt the natural flows of surface water andground water unless they are properly engineered [1],lack of maintenance will spoil the road and roadsideslopes by uncontrolled water and sediment flows.
Plant growth prevents erosion on roadside slopes[2]: leaves mitigate the direct impact of raindrops on
the soil surface, roots retain soil, and transpiration
reduces excessive soil water in the ground. To
maintain these functions, it is necessary to monitor
and manage the roadside slope vegetation.
Inadequate management leads to undesirable
vegetation on roadside slopes, narrowed fields ofview, and even damage to the road by fallen trees orlandslides [3]. There are few reports on thevegetation succession along old or closed roads todate. Since the lifespan of asphalted road is usuallyplanned to be around 10 years in Japan [4],vegetation succession on roadside slopes should also863

SEE - Nagoya, Japan, Nov.12-14, 2018

In the present study, we surveyed roadside slope
vegetation in the summer of 2004 (just before thearea was damaged by typhoons) and again in 2016(12 years after the damage) to examine the effect ofsuspending traffic on roadside vegetation. The
original survey was designed to evaluate wild
herbaceous plants for utilization in vegetation
technology [7], but the sites were damaged by thepassing typhoons soon after the vegetation survey in
2004, and the subsequent follow-up study describedhere was planned. Based on analyses of the changes
in vegetation based on coverage percentage andspecies composition, we discussed how and when to
manage roadside slope vegetation along closed roads.

regions. Due to infrequent access, it is difficult tomonitor and maintain this road and the surrounding
roadside slopes.

METHODS
Vegetation Survey

Fig. 1

The research area is the roadside area along Old
Gonbei Highway in Nagano Prefecture, central
Japan. This winding highway joined Ina City (Kamiina region) and Shiojiri City (Kiso region), but a 9km length of this highway has been closed since theautumn of 2004.
In July 2004, eleven sites (labeled A to K) were
established at approximately regular intervals along
the road for a vegetation survey. Each site iscomprised of two plots of roadside slopes (2 m × 5
m per plot, mountain side and valley side). The
section of road closed in autumn 2004 included 5sites (labeled E to I) out of the 11 sites. The
elevation and slope direction at each site aredescribed in Table 1.

Paths of typhoons that produced heavy
rains and strong winds in the research areain 2004. Figure is based on original dataand graphs reported in [5].

Fig. 2

Old Route 361 (Gonbei Highway) and newly constructed Route 361
Arrows indicate the placement of gates for closing the road to traffic.
864

SEE - Nagoya, Japan, Nov.12-14, 2018

100%, was reported as being 87.5%). The change incoverage percentage (∆ = coverage percentage in2016 - coverage percentage in 2014) was calculated
for each slope and was considered for combinationsof two factors (section: passable or closed, slope:mountain side or valley side). Significant differencesamong coverage percentages were detected byanalyses of variance and Tukey’s HSD test.
Because of the large dominance in the herb layer
in 2016, we additionally noted of the dormancy form
[8] for each plant species. Each plant species was
categorized into a corresponding dormancy form,
and the total coverage percentage by form wascalculated. The composition differences ofdormancy forms were analyzed by the analysis ofvariance (F-test). Dormancy forms were categorized
in the present study as follows:A, annual or biennial herb;
P, perennial herb with dormant bud close to theground;N, shrub with dormant bud 0.3 to 2 m above theground (includes bamboo grass);
M, tree with dormant bud 2 to 8 m above theground; andMM, large tree with dormant bud over 8 m above
the ground.
In this analysis, if a small seedling of an MM species
was detected in the herb layer, the coverage data of
the species was categorized as ‘MM’. Therefore, thecomposition of the dormancy form can be used toevaluate the potential progression of vegetation
succession.

Table 1 Vegetation survey sites
No.
A
B
C
D

Elevation
(m)
955
1150
1110
1180

Slope
direction
SW
SW
SW
E

E
F
G
H
I

1260
1330
1419
1530
1550

SE
S
S
E
S

Closed

J
K

1390
1235

SW
S

Passable

Condition

Location

Passable

Ina City↑↓
ShiojiriCity

In 2004 (just before the area was damaged bytyphoons) and in 2016 (after the damage), coverageof each plant species in each plot was measured ineach of the tree, shrub and herb layers. Plant
coverage was ranked using the classes of the BraunBlanquet scale as follows:+, sparse vegetation with coverage by area of lessthan 1% over the total plot area;
1, vegetation coverage between 1% and 10% of total
plot area;
2, vegetation coverage between 10% and 25% of
total plot area;
3, vegetation coverage between 25% and 50% of
total plot area;
4, vegetation coverage between 50% and 75% of
total plot area;
5, vegetation coverage of more than 75% of total
plot area.

RESULTS
Roadside Slope Vegetation

Observation of Road Surface

Table 2 shows the changes in vegetation
coverage percentage (∆) in each layer after 12 years.
In the tree layer, the effect of section (passable roador closed road), slope direction, and their interaction
were not significant, and the change trend was notapparent (ranged from -15% to +20%). In the shrub
layer, the effect of section was significant (F-test, p<0.05). The coverage percentage increased byaround +50% in the passable section, and it
increased by less than +20% in the closed section. In
the herb layer, the effect of section was alsosignificant (F-test, p <0.02); coverage percentage
decreased in the passable section, with a notabledecrease of around -40% on the valley side, whereas
it increased by around +30% in the closed section.
Fig. 3 shows the change of the composition of
dormancy forms of plants in the herb layer. The
effects of year (2004 or 2016), section (passable orclosed) and slope (mountain side or valley side)
were significant (F-test, p <0.0001, 0.02, 0.005,
respectively). The effect of interaction of year ×
section was also significant (F-test, p <0.005),

To conduct the 2016 vegetation survey, we
accessed sites in the closed section of the road bywalking in from the gate closing the road.
Consequently, we explored the entire closed sectionof Gonbei Highway while conducting the vegetation
survey.
Since there was no current information regarding
the condition of the road in the closed section, we
observed the road surface for parameters including
the presence or absence of cracks, dips,
accumulation of fallen branches or leaves, andinvasion of weeds to gather preliminary informationin the investigation of the deterioration of the roadsurface in the survey area.
Data Analysis
To compare the total vegetation coverage
percentage, each coverage class was reported as asingle medium percentage (e.g., class 5, which hadcoverage percentages ranging between 75% and865

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Change in vegetation coverage percentage in each layer
Section
Passable
(n=6)

Slope
Mountainside
Valleyside

Closed(n=5)

Mountain
Side
Valley
side

year
2004
2016
∆
2004
2016
∆
2004
2016
∆
2004
2016
∆

Tree
31.8
10.4
-21.3
38.1
23.4
-14.7
12.5
7.5
-5.0
23.6
37.5
13.9

a

a

a

a

Layer
Shrub
8.8
54.9
46.2 ab
19.1
70.3
51.2 a
23.6
32.5
8.9 c
16.7
35.8
19.1 bc

Herb
52.3
48.2
-4.2 ab
54.3
16.6-37.8 b52.9
81.9
29.0 a29.3
55.4
26.1 aEach value denotes the average percentage obtained from plots.
Different letters in columns denote significantly different means as
determined by Tukey’s HSD test (p <0.05).
N, Sasa spp. (Poaceae), Rubus spp. (Rosaceae);
M, Lindera praecox (Lauraceae), Deutzia crenata(Hydrangeaceae); andMM, Quercus spp. (Fagaceae), Alnus hirsuta(Betulaceae).
Of the N (shrub) in the herb layer, bamboo grass(Sasa spp.: S. borealis, S. sikokiana and S.
senanensis) comprised the majority of the species.
Although the coverage percentage was sparse in
2004, it increased to rank 4 (50% to 75%) or 5 (75%
to 100%) in 2016 in some plots in the closed sectionof the highway.
To examine the relationship between the shrub
layer and herb layer, the correlation of coverage
percentages between these layers was determined.
As a result, the correlation coefficient was not
significant in the passable section (r = 0.223; F-test,ns), but it was significant (r = -0.542; F-test, p<0.02) in the closed section.

indicating that the change in composition of
dormancy forms after 12 years differed between thepassable and closed sections.

Road Surface
Fig. 3

Changes of composition of dormancy formsof plants as the total coverage percentage inthe herb layer

In the section of closed road, obvious dips ordifferences in level were not observed. However,mash-like or linear cracks were sparsely observed(Fig. 4). The former is caused by deterioration ofasphalt and the latter seems to occur where paving
different construction was conducted.
Accumulation of fallen branches and leaves was
especially observed on the shoulder of the road, andfine fallen leaves (e.g., needle-like leaves ofJapanese larch) accumulated on linear cracks (Fig.
4).
Weeds growing in the road surface were
scattered and were concentrated where fine leaves
accumulated in cracks in the road. The number ofweed species was as small as 0 to 5 per site, and notree seedlings were observed. Representative species
were Plantago asiatica (Plantaginaceae), Erigeron

In 2004, each slope was primarily dominated by
P (perennial herbs) and around 5% to 15% of A
(annual or biennial herbs). At 12 years later, A(annual or biennial herbs) decreased on each slope,and M or MM (tree seedlings) markedly increased in
the passable section. In contrast, the dominance of N
(shrub) became obvious in the closed section. The
following representative plant species werecategorized into each dormancy form in the survey
plots:A, Amphicarpaea bracteata ssp. edgeworthii(Fabaceae), Oplismenus undulatifolius (Poaceae);
P, Artemisia indica var. maximowiczii (Asteraceae),
Miscanthus sinensis (Poaceae);866

SEE - Nagoya, Japan, Nov.12-14, 2018

preventing the growth of trees in the management ofroadside slope vegetation. The colonization of asedge (Carex oxyandra: Cyperaceae) has also beenreported to suppress tree seedlings [9] [10] andmight be preferable over bamboo grass in the
management of roadside slope vegetation.
The road surface of Gonbei Highway in theclosed section was not deteriorated or heavily
invaded by weeds, probably due to the asphalt
coverage and its location in a cool climate at highelevation. In contrast, there is a report of an unpaved
working path for forestry becoming almost covered
with plants, including tree seedlings, after only 3
years [11]. In that case, the road surface is not
usually paved, and the rapid development ofvegetation is desirable to reduce the risk of erosion[12]. Compared to unpaved working paths, the roadsurface of Gonbei Highway seems to be wellmaintained, even in the closed section after 12 years.
The weeds on the road surface included a small
number of species that had little relation to thespecies found in the slope vegetation, suggestingthat unique vegetation, though in an early stage, wasextending along the closed highway. This vegetation
succession, even in a mountain area, shows
similarities to vegetation growing in cracks in roads
in urban areas [13]. The seeds of weeds might havebeen gradually introduced in the area by water, windor wild animals and birds from outside the area since
there has been little automobile or human traffic
after the suspension.

annuus (Asteraceae) and Juncus tenuis (Juncaceae).
Most of the species growing in the road surface were
not present in the adjacent roadside slope vegetation:in the road surface, on average only 0.6 (0 to 2)
species per site were observed out of 13.4 (6 to 20)
species growing on the adjacent roadside slope
vegetation.

Fig. 4

Deterioration of road surface in the closed
section of Gonbei Highway
Cracks, accumulated fallen leaves, andscattered invading weeds can be observed.
Length of the red and white striped pole = 2
m.

DISCUSSIONCONCLUSION

In the closed section of Gonbei Highway, we
found that tree and shrub layer coverage percentages
did not increase markedly (Table 2), despite thelong-term suspension of traffic creating a
disturbance-free environment. In other words, thecomposition of tree seedlings (M and MM)
occupying the herb layer was larger in the passable
section than in closed section (Fig. 3), suggesting theadvanced progression of vegetation succession
occurred in the passable section. These unexpected
results are due to the presence or absence of N
(especially bamboo grass) in the herb layer, since
there is a negative correlation between the coverage
percentages of shrub layer and herb layer in theclosed section.
Colonization of bamboo grass has been reported
to suppress the establishment of tree seedlings (e.g.,[9] [10]). In the present study, it is considered thatthe disturbance due to vegetation management in thepassable section prevented colonization of bamboo
grass, allowing tree seedlings to grow. However, inthe disturbance-free environment of the closed
section, the colonization of bamboo grass was
accelerated, suppressing the recruitment and growthof tree seedlings. It is generally considered that thegrowth of bamboo grass should be controlled inforestry practice, but it can also be useful for

In the present study, we surveyed Gonbei
Highway, a winding road in a mountainous region incentral Japan. It was damaged by typhoons in theautumn of 2004, and a 9 km stretch of the highway
has remained closed. We established 11 survey sites
to examine slope vegetation along Gonbei Highway
in the summer of 2004 (just before the area wasdamaged by typhoons), and we conducted surveys
again in 2016 (12 years after the damage), including
at 5 survey sites along the closed section of the road.
Our results were as follows:(1) On the roadside slopes, succession to arboreal
vegetation was not observed at the sites along theclosed section of the road. In herb layer, vegetation
coverage increased significantly along the closed
section with increasing coverage of shrub species(mainly bamboo grass). In contrast, tree seedlings
increased in the passable sections.
(2) On the road surface in the section of closed road,obvious deterioration was not observed, excepting
mash-like or linear cracks. The road surface
vegetation was seemed to be just in the early stageof succession: weeds growing in the road surface
were scattered and were concentrated where fineleaves accumulated in cracks in the road. No tree
867

SEE - Nagoya, Japan, Nov.12-14, 2018seedlings were observed, and most of the species
growing in the road surface were not present in theadjacent roadside slope vegetation.
The suspension of traffic and the subsequent
long-term absence of roadside vegetation
management allowed bamboo grass to increase, andthe community of bamboo grass prevented invasion
and growth of tree seedlings. Bamboo grass mightalso be useful to prevent the invasion of weeds,
especially non-native species, through the road into
roadside slope vegetation. Consequently, thedominance of bamboo grass in roadside slope
vegetation may be one of the criteria by which tojudge the necessity of vegetation management alongroads closed to traffic.

index.htm.>, referred in Feb. 2nd , 2017[7] Fujii, M., Studies on the Revegetation using
Wild Fabaceae Species Growing on the Roadside
Slopes along Gonbei Highway, Graduation
Thesis of Shinshu University, 2004, pp. 1-21 (inJapanese)[8] Numata, M and Yoshizawa, M. eds., Weed
Flora of Japan –Illustrated by Colour (a New
Publication), Zenkoku Noson Kyouiku Kyokai
Publishing Co. Ltd., 1978, pp. 8-22.
[9] Arase, T., Okano, T. and Shirota, T.,
Colonization and Morphological Changes of a
Sedge Restricting Regeneration after Wind
Damage in a Natural Forest,
International
Journal of GEOMATE, Vol. 12, Issue 31, 2017,
pp. 100-104.
[10] Arase, T., Okano, T. and Shirota, T., Methodsof Suppressing Colonizing Sedge to Help toEstablish Tree Seedlings in a Natural Forest,
International Journal of GEOMATE, Vol. 12,
Issue 32, 2017, pp. 19-24[11] Ogura, A., Suzuki, H., Usuda, T., Yamaguchi,T., Tanaka, Y. and Umeda, S., A Case ofvegetation Recovery on a Working Path, Bulletinof the Ishikawa Agriculture and Forestry
Research Center Forestry Experimental Station,
Vol. 44, 2012, pp. 42-43. (in Japanese)[12] Sato, H., Effective Forest Management toReduce Fine Sediment Production and Delivery,
The Journal of the Japanese Forest Society, Vol.
88, Issue 1, 2006, pp. 50-59.
[13] Uchida, T., Xue, J.H., Hayasaka, D., Arase, T.,
Haller, W.T. and Gettys, L.A., The Relation
between Road Crack Vegetation and Plant
Biodiversity in Urban landscape, International
Journal of GEOMATE, Vol. 6, Issue 12, 2014,
pp. 885-891

REFERENCES[1] Jones, J.A., Swanson, F.J., Wenple, B.C. and
Snyder, K.U., Effects of Roads on hydrology,
Geomorphology, and Disturbance Patches in
Stream Networks, Conservation Biology, Vol. 14,
2000, pp. 76-85.
[2] Togari, A., A Guide to Vegetation Construction–Fundamental Knowledge of Vegetation, The
Journal of Japan Railway Civil Engineering
Association, Vol. 36, Issue 10, 1998, pp.798-801.
(in Japanese)[3] Kawanishi, Y., Ozaka, K., Kobayashi, T.,
Ueshima, K. and Sudou, S., The Ideal State of
the Vegetation on the Expressway Slopes, and Its
Management Plan, Journal of the JapaneseSociety of Revegetation Technology, Vol. 42,
Issue 1, 2016, pp.208-211 (in Japansese)[4] Road conservation technology Center ed., RoadManagement Technology Handbook, Kajima
Publishing Co., 2010, pp. 1-111 (In Japanese)[5] Japan Meteorological Agency, Various Kindsof Data and Report HP, <www.jma.go.jp/
jma/menu/menureport.html>, referred in Feb.
2nd , 2017[6] Ina Construction Office of Nagano Prefecture,
Traffic
Restrictions
InformationHP<http://yassy.asystem-a.org/xdoboku/inakenn/868

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ISOTOPIC RATIOS AND CHEMICAL COMPOSITION OF
PRECIPITATION BETWEEN FOOT OF THE BUILDING AND TOP OF
THE BUILDING IN OSAKA CITY AND WAKAYAMA CITY,
JAPAN
Toshiki Ueda1 and Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan
2
Faculty of Systems Engineering, Wakayama University, Japan

1

ABSTRACT
Amount of precipitation and soluble substances may depend on altitude because raindrop evaporates andcondensates during the falling process from cloud to ground and then to clarify altitude effect is important. To
compare mountain areas with plain areas does not only contain altitude effect but also the distance effect from thesea or the other mountain. Therefore, in this study, comparing precipitation sampled at the top of the high building
with precipitation sampled at the foot of the high building, influence of difference of altitude on isotope or soluble
substances was clarified. The high altitude sampling point at the Abenoharukasu building in Osaka City is 295m
tall. Another high sampling point at Systems Engineering Building in Wakayama University is 112m tall.
Precipitation on the ground at both buildings was sampled. As a result of comparing these precipitations, isotope
values of precipitation sampled at high altitude were lower than those sampled at low altitude for the same caseand both values were the same for the other cases. The difference was thought to be caused by evaporation because
stable isotope values change with evaporation and then the humidity of air before precipitation is thought to beimportant. Low altitude precipitation contained high Ca2+ and HCO3- and high altitude precipitation contained highCl-.
Keywords: altitude effect, precipitation, soluble substances, stable isotope，humidity

precipitation event[4]. However, it has not beenclarified how much these factors contribute to altitude
effect.
Regarding the chemical composition, it wasreported that acid rain affected the decline of forest
and acidification of lakes in Europe and North
America from the 1960s to the1970s, and the cause ofacid rain has been investigated worldwide [5][6].
However, change of soluble substances ofprecipitation with altitude has not been clarified.
In this study, we assumed that the altitude effect
was a phenomenon peculiar to the mountains. And
precipitation was collected at high buildings where
updraft was unlikely to occur and the straight distance
between water sampling points was short. The
purpose of this study is to clarify the relation ofoxygen stable isotopic ratios or soluble substanceswith altitude for precipitation using the high building.

INTRODUCTION
It is important to clarify evaporation and reactionof raindrop until raindrop reaches the ground for
estimating chemical composition and isotope valuesof precipitation. Stable isotopic ratios of precipitation
are influenced by regional characteristics due tometeorological and spatial conditions such as theamount of precipitation, temperature and altitude. For
example, Waseda, Nakai, 1983[1]; Asai, Tsujimura,
Wilson Yetoh FANTONG, 2014[2] have beenreported that isotope ratios at low altitudes are higher
than high altitudes in the mountain. This feature iscalled the altitude effect, and there are two main
factors that cause the altitude effect. The first factor isthe difference in the amount of evaporation during
precipitation falling. Precipitation arrived at low
altitude point travelled longer distance relative toprecipitation at high altitude point. Amount of
evaporation relates to travelling distance. Then, theamount of evaporation of precipitation arrived at low
altitude was high. In particular, under the low humid
condition, the evaporation rate is high and then theisotope difference is large [3]. The second factor isthat isotopic ratios of early precipitation often
includes heavier than that of late precipitation due tothe condensation process of Rayleigh during a

METHOD
Sampling and Analysis
Fig.1 shows survey points. Precipitation samplingin this study was performed in Tennoji-ku, Osaka Cityand Sakaedani, Wakayama City. Fig.2 shows the
sampling points of Tennoji-ku, Osaka City. One

869

SEE - Nagoya, Japan, Nov.12-14, 2018

precipitation sampling point is near the roof of
Abenoharukasu (= OH«Osaka high») whose altitude
is about 306m, and another point is Tenshiba (=OL«Osaka Low») whose altitude is about 11 m. The
difference in altitude and the straight distance
between both points is about 295 m and about 410 m.
Fig.3 shows the sampling points of Sakaedani,
Wakayama City. One precipitation sampling point is
rooftop of building B, Wakayama University whose
altitude is about 112 m and another point is Green
Planet House Parking whose altitude is about 70 m.
The difference in altitude and the straight distance
between both points at Wakayama is about 42 m andabout 650 m.
Sampling was performed from September toDecember 2017 in Osaka City and from June to
December 2017 in Wakayama City. The stable
isotopic ratios were expressed as δ values ‰, and an
isotope mass analyzer (Geo Wet System, Sercon Co.)was used for analysis. δ values ‰ represented byfollowing equation.

Fig.2 Sampling points of Tennoji-ku, Osaka city.

δ = (Rsample/(Rv − smow) − 1) × 1000 ‰ (1)R; 18O/16O, V-SMOW: Vienna-Standard Mean Ocean
Water.
Measurement error of δ18O was within ±0.1‰.

Osaka

Fig.3 Sampling points of Sakaedani, Wakayama city

RESULT AND DISCUSSION
δ18O value in each event

Wakayama

Fig.4 shows time series of δ18O values ofprecipitation sampled at both high and low altitudes
in Osaka and Wakayama Cities. From this result, in
Osaka city, δ18O values of OL sampling point were 3 to -14 ‰ and δ18O values of OH sampling point
were -3 to -13 ‰. In Wakayama City, δ18O values of
WL sampling point were -2 to -12 ‰ and δ18O valuesof WH sampling point were -2 to -12 ‰. δ18O valuesof each precipitation at all points changed with eachrainfall event In Osaka City, the δ18O values at OL
and OH were almost the same until October 18th andafter October 24th the difference of δ18O value at
between OH and OL sampling points were -1.04 to 1.47 ‰.
On the other hand, in Wakayama City, the altitudedifference of δ18O values at both points was hardly
found, and then the values of WL and WH were
almost the same. When precipitation evaporation
occurs, light isotope selectively evaporates rather
than heavy isotope by Rayleigh process, as a result,

100㎞

Fig.1 Survey points in this study

870

SEE - Nagoya, Japan, Nov.12-14, 20182

δ18O value of precipitation at the low altitude
becomes high.
The altitude effect of the oxygen isotopic ratios ofprecipitation is from -0.2 to -0.3 ‰ / 100 m in various
places in Japan according to [7]. The oxygen isotopic
ratios per altitude in Osaka City were -0.35 to -0.49 ‰/ 100 m which were in agreement with previous
results. In Wakayama City, the δ18O values of WL andWH were about the same, then precipitation does notevaporate during fall and isotope values keep uniform
values.

1.5

δ¹⁸O (‰)

1
0.5
0

-0.5
-1
-1.5
50

0

WL

WH

OL

OH

-2

δ18O(‰)

70

Humidity(%)

80

90

Fig.5 The relationship of the difference (OL – OH) of
the δ18O values at between high and low
sampling points and the humidity in Osaka City

-4
-6

1

-8

0.5

-12

0

δ¹⁸O(‰)-10

2017/7/3
2017/8/6
2017/8/7
2017/8/15
2017/9/22
2017/9/29
2017/9/30
2017/10/4
2017/10/8
2017/10/10
2017/10/18
2017/10/24
2017/10/30
2017/11/2
2017/11/11
2017/11/14
2017/11/17
2017/11/23

-14
-16

60

-0.5
-1
-1.5
-2
50

Fig.4. Time series of δ18O values of precipitation
sampled at both high and low altitudes in
Osaka and Wakayama Cities

60

70

80

Humidity(%)

90

100

Fig.6 The relationship of the difference (WL – WH)of the δ18O values at between high and low
sampling points and the humidity inWakayama City

Characteristics of the large difference of δ18O
values between the foot of the building and top of
the building

As unsaturated air rises adiabatically, atmosphericpressure does not only decrease but also temperature,
water vapor pressure, and dew point. Finallyunsaturated air reaches the dew point altitude where
the air is saturated with water.

Fig.5 shows the relationship of the difference (OL– OH) of the δ18O values between high and low
sampling points and the humidity in Osaka City. The
humidity values for each precipitation event in Fig.5
show the beginning of precipitation. When humidity
was low, about 70 %, the difference of isotope values
for precipitation between low and high sampling
points was plus and altitude effect was recognized.
Therefore, under low humidity condition, isotope
values easily increase during precipitation falling
because water is eager to evaporate.
Fig.6 shows the relationship of the difference (WL– WH) of the δ18O values between high and low
sampling points and the humidity in Wakayama City.
In Wakayama City the difference for δ18O of
precipitation increased with the decrease of humidity.

𝐇𝐇 = 𝟏𝟏𝟏𝟏𝟏𝟏 × (𝐓𝐓₀ − 𝛕𝛕₀)

(2)

H ; Altitude at dew point, T₀ ; Surface temperature,𝛕𝛕₀ ; Dew point. Surface temperature and vapor
pressure are used from Japan Meteorological Agency
at Osaka and Wakayama.

From a dew point altitude it is possible to estimate
an altitude for bottom of cloud bottom altitude andthen a dew point altitude, and indicate the distance
between the cloud and the ground. Therefore, it isimportant to estimate changes of the dew point
altitude for calculating falling distance. And then, we
focused on relationship between δ18O values
difference and dew point altitude. Fig.7 shows therelationship of the difference (OL - OH) of the δ18O
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SEE - Nagoya, Japan, Nov.12-14, 2018

values at between high and low sampling points andthe dew point altitude in Osaka City. The dew point
altitude increased with the difference of isotope
values for precipitation at between low and highsampling points.
Fig.8 shows the relationship of the difference (WL– WH) of the δ18O values at between high and low
sampling points and the dew point altitude in
Wakayama City. In Wakayama City the differencefor δ18O of precipitation increased with the increaseof dew point altitude.

Characteristics of chemical composition between
foot of the building and top of the building
Fig.9 shows the change in the average content ofchemical components for precipitation at between
high and low sampling points in Osaka City. In Osaka
City, Ca2+ and HCO3- concentrations at low sampling
points were high, however, Cl- and NO3concentrations of precipitation at high sampling
points were high.
Fig.10 shows the change in the average content ofchemical components for precipitation at between
high and low sampling points in Wakayama City. In
Wakayama City, Ca2+ and HCO3- concentrations ofprecipitation at low altitude sampling points werehigh, however, Cl- and SO42- concentrations ofprecipitation at high altitude sampling points werehigh.
From these results, Cl- concentrations at highaltitude in both Osaka City and Wakayama City werehigh, however, Ca2+ and HCO3- concentrations ofprecipitation at high altitude sampling points werehigh.
At the low altitude sampling point, high Ca2+ andHCO3- was thought to be caused by asphalt dust
contained CaCO3 [8].
As generally Cl- source in precipitation was sea salt,
the difference between both altitudes was not high.
Then, little high Cl- concentration at high sampling
points in both cities was thought to be influenced sea
salt because both cities are near the sea and rising sea
salt from sea surface directly is mixed precipitation.

2
1.5

δ¹⁸O(‰)

1
0.5
0

-0.5
-1
-1.5

400

600

800

1000

1200

Dew point altitude(m)Fig.7 The relationship of the difference (OL – OH) of
the δ18O values at between high and low
sampling points and the dew point altitude in
Osaka City.
1
0.5

-0.5

Content(meq/l)δ¹⁸O(‰)

0

-1
-1.5
-2

150

650

Na⁺

NH₄⁺

Mg²⁺

Ca²⁺

K⁺

0.35

0.35

0.3

0.3

0.25

0.25

0.2

0.2

0.15

0.15

0.1

0.1

0.05

0.05

NO₃⁻

SO₄²⁻

HCO₃⁻

0

0

1150

Cl⁻

OH

OL

OH

OL

Dew point altitude(m)Fig.9 The change in the average content of chemicalcomponents for precipitation at between highand low sampling points in Osaka City

Fig.8 The relationship of the difference (WL – WH)of the δ18O values at between high and low
sampling points and the dew point altitude in
Wakayama City.

872

SEE - Nagoya, Japan, Nov.12-14, 2018

Na⁺

NH₄⁺

Mg²⁺

Ca²⁺

0.01

K⁺

Cl⁻

NO₃⁻

0.005

SO₄²⁻

HCO₃⁻

0

Cl⁻ (meq/l)Content(meq/l)

0.015-0.005

0.3

0.3

0.25

0.25

0.2

0.2

0.15

0.15

0.1

0.1

-0.03

0.05

0.05

-0.035

0

0

WH

WL

-0.01
-0.015-0.02-0.025

WH

-0.5

0

0.5

1

1.5

2

δ¹⁸O(‰)

WL

Fig.11 The relationship between the difference (OLOH) of Cl- and the difference (OL-OH) ofδ18O values in Osaka city

Fig.10 The change in the average content of chemicalcomponents for precipitation at between highand low sampling points in Wakayama City

0.05
0

-

Relationship between Cl and evaporation-0.05

Cl⁻(meq/l)

During precipitation falling, when raindrop
evaporates, soluble substances such as Cl- of
precipitation increase. Then, Fig.11 shows therelationship between the difference (OL-OH) of Cland the difference (OL-OH) of δ18O values in Osaka
City. Cl- concentration differences between low andhigh sampling points increased with δ18O value
differences (0 to 1.5‰). Then evaporation was
thought to occur during precipitation falling processfrom top of the building to ground in Osaka City.
Fig.12 shows the relationship between the
difference (WL-WH) of Cl- and the difference (WLWH) of δ18O values in Wakayama City. Clconcentrations at both low and high sampling points
were the about same excluding one data under various
differences (-0.4 to 0.4 ‰) of δ18O values between the
top of building and ground in Wakayama City. In
Wakayama City, the difference of δ18O values
between the top of the building and ground was notalways plus and evaporation was not clear. Therefore
Cl- concentration was thought to be uniform at both
high and low altitude points.

-0.1
-0.15
-0.2
-0.25
-0.3
-0.35
-0.4

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

δ¹⁸O(‰)
Fig.12 The relationship between the difference (WLWH) of Cl- and the difference (WL-WH) ofδ18O values in Wakayama city
CONCLUSION
Amount of precipitation and soluble substances
may depend on altitude because raindrop evaporates
and condensates during the falling process from cloudto ground and then to clarify altitude effect isimportant.
Then the purpose of this study is to clarify the
relation of oxygen stable isotopic ratios or soluble
substances with altitude for precipitation using thehigh building.
The δ18O values at ground and top of the building
were almost the same until October 18th and after
October 24th the difference of δ18O value at between
ground and top of the building were -1.04 to -1.47 ‰.
On the other hand, in Wakayama City, the altitude
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SEE - Nagoya, Japan, Nov.12-14, 2018

difference of δ18O values at both points was hardly
found, and then the values of ground and top of thebuilding were almost the same.
And then, differences of isotope and humidity
between the high altitude point and the low altitude
point in Osaka City and Wakayama City were studied.
When humidity was low in the precipitation event, thedifference of isotope was large. Therefore, humidity
was thought to be largely influenced by precipitation
evaporation due to difference in altitude. The dew
point altitude increased with the difference of isotope
values for precipitation at between low and highsampling points.
Regarding chemical composition, in Osaka City,
low altitude precipitation contained high Ca2+ andHCO3- and high altitude precipitation contained highCl- and NO3-. On the other hand, in Wakayama City,
low altitude precipitation contained high Ca2+ andHCO3-, and high altitude precipitation contained highCl- and SO42-. From these results, Cl- concentrations athigh altitude in both Osaka City and Wakayama City
were high, however, Ca2+ and HCO3- concentrationsof precipitation at high altitude sampling points were
high. At the low altitude sampling point, high Ca2+and HCO3- was thought to be caused by asphalt dust
contained CaCO3.
Cl- concentration differences between low and highsampling points in Osaka City increased with δ18O
value differences (0 to 1.5 ‰). Then evaporation was
thought to occur during precipitation falling processfrom top of the building to ground in Osaka City.
In Wakayama City, the difference of δ18O values
between top of the building and ground was notalways plus and evaporation was not clear. Therefore
Cl- concentration was thought to be uniform at both
high and low altitude points.

[5] Hisao Sakai, Takeshi Morisawa, Tetsuya
Sengoku “Characteristics of pH, EC values andionic components in rain and snow for 7 years at
Mt. Ontake, Central Japan” Jpn. J. For.
Environment 45 [1], 21-27 2003
[6] Hiroshi HARA “Precipitation Chemistry inJapan” The Chemical Society of Japan 1997,
No.11[7] Shiho YABUSAKI, Norio TASE, Maki
TSUJIMURA and HAYASHI “Characteristicsof Stable Isotopes in precipitation at South
Slope of Mt. Tsukuba” Tsukuba University
Terrestrial Environment Research Center Report
No.9, 15-23, 2008[8] Norio Fukusaki “Chemical characteristics ofconstituents in precipitation collected on Mt.
Tanigawa” Niigata Prefecture Sanitary and Eco
Institute Annual Report vol.9 1993

REFFERENCES[1] Amane WASEDA, Nobuyuki NAKAI “Isotopiv
compositions of meteoric and surface waters inCentral and Northeast Japan” Earth science 17,
83-91 1983
[2] Kazuyoshi ASAI, Maki TSUJIMURA,Wilson
Yetoh FANTONG “Temporal variation of stable
isotope ratios in precipitation on Chubumountainous areas : a case study of Mt.Ontake,Japan” Journal of Japan Hydroculture Vol.44,
No.2, 67-77 2014[3] Satoshi Miyahara, Hiroyuki Ii “Proposal of
Measurement for Evaporation Rate by Using
Oxygen Isotopic Ratio” Int. j .of GEOMATE,
Sept, 2012, Vol. 3, No.1(Sl.No.5), pp.318-324[4] YABUSAKI Shiho “Characteristics of Stable
Isotopes in Precipitation at Kumagaya City,
Saitama Prefecture” Global environment
research, Vol.12 (2010)874

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

REGENERATION FOR SOCIO ECOLOGICAL PRODUCTIONLANDSCAPE IN SERIOUSLY ENVIRONMENTAL DAMAGEDRURAL AREA

1

Takato Azegami1, Hirokazu Abe2, Noriko Otsuka3 and Tomoko Miyagawa4
Graduate School of Engineering, Osaka University, Japan; 2 Cyber Media Centre, Osaka University, Japan;
3
ILS Institut für Landes- und Stadtentwicklungsforschung gGmbH, Germany; 4 Faculty of Systems
Engineering, Wakayama University, Japan

ABSTRACTThis research aims to explore the regeneration for socio ecological production landscape in seriously
environmental damaged rural area through the field survey of prior efforts around the area. In Fukushima, six years
have passed since the nuclear accident, and evacuation orders for about 32,000 people living in Namie, Iitate,
Tomioka and Yamakiya District of Kawamata, haves been lifted by April 2017. However, since the socioecological production landscape has lost, the lifting of this evacuation order will not lead directly to the returnhome of residents. The challenge is how to restore people’s former life which was based on agriculture and forestry
and this research looks into the ways of regenerating the socio ecological production landscape, using interview
with local community representatives and field observation. The case study has revealed that the decontaminationof forest is still in a trial stage and the key obstacle is the fact that there are still a few people who wish to return
because the future concrete outlook is still not visible. However, a new community has been gradually generatingby the approach which a part of farmers resume farming with external researchers and volunteers with interest. It
seems to lead to the potential for regeneration of the socio-ecological production landscape.
Keywords: Socio-ecological Production Landscape; Serious Environmental Damage; Fukushima; Community
Participation

INTRODUCTION

agriculture and forestry and this research looks into
the ways of regenerating the socio ecologicalproduction landscape, using interview with local
community representatives and field observation. The
case study has revealed that the decontamination offorest is still in a trial stage and the key obstacle is thefact that there are still a few people who wish to return
because the future concrete outlook is still not visible.
However, a new community has been gradually
generating through an approach which some farmers
resume farming with external researchers andvolunteers who are interested in the regeneration. It
seems to be lead to the potential for regeneration of
the socio-ecological production landscape.
This research will explore the regeneration for socioecological production landscape in seriously
environmental damaged rural area of Fukushima
through the field survey of prior efforts around thearea.

Background of This Research
Recently a number of mountainous rural areas arefacing the difficulty in maintaining villages due to therapid depopulation and aging society. In these areas,
it is also difficult to maintain the functions of thevillage community and the socio ecologicalproduction landscape which have been managed by
the villagers. Some villages have been undertaking
regeneration of socio ecological production
landscape affected by serious environmental damage
which requires a strict risk management against
various stigmas as well as the burden of restoring theenvironment. Especially in Fukushima, six years havepassed since the nuclear accident, and evacuation
orders for about 32,000 people living in Namie, Iitate,
Tomioka and Yamakiya District of Kawamata, haves
been lifted by April 2017. However, since the socioecological production landscape has lost, the liftingof this evacuation order will not lead directly to thereturn home of residents. The challenge is how to
restore people’s former life that was based on
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Fukushima Daiichi Accident and Residency
Restriction

To tackle this catastrophic event, the Special Measure
Act for Radioactive Pollution came into force 2012.
Two types of areas were designated in the Act whichare Intensive Contamination Survey Areas (ISA) andSpecial Decontamination Areas (SDA). Figure.1
shows a part of map of ISA and SDA. ISA (under 20
mSv/y) shows yellow color in the map, in whichmunicipalities were obliged to implement
decontamination. SDA (over 20 mSv/y) shows redcolor in the map, in which the national government
carries out decontamination. Left side map of Fig.2
shows the SDA, within Red dot line, where residency
is restricted or prohibited by the national government
in 2012. Red color shows the zones (over 50mSv/y)where residency is prohibited for an extended period.
Yellow color shows the zones (from more than
20mSv/y to less than 50mSv/y) where residency is
restricted. Green color shows the zones (20mSv/y)where residents will be allowed to return after
decontamination
After six years from the disaster, decontamination
work has progressed. On April 2017, residency
restriction of 12 areas was lifted. They are shown as
green color areas in Right side map of Fig.2. The
range of residency prohibit area (within Red dot line)
has decreased to one-third of the initial area. Also, thedecontamination of the living area of human being(areas within only 20 meter from the settlements) had
been completed, and the residents of these areas could
return to home. From now on, it is necessary toresume farming and to ensure security against
radioactive contamination.

The Great East Japan earthquake had occurred on
March 11, 2011. Tsunami hit the Fukushima Daiichi
Nuclear Power Plant (FDNPP) and it exploded. The
radioactive pollutant from FDNPP had diffused
widely in the surrounding area. 332,691 residents
were forced to evacuate.
Intensive survey areas
Special decontamination areas

Fig.1 Designated areas in Special Measure Act forRadioactive Pollution in 2012 [1] (Courtesy Ministryof Environment)

Yamakiya
Towa

Areas where restrictionof residence wascanceled

AIMS
ANDtheSTUDY
METHODS
Fig.2 Changes of SDA /left: Jan. 2012/ right: April 2017 (author
editedSDA map
Ministry of environment
[2])
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This paper aims to explore the regeneration for socioecological production landscape in seriously
environmentally damaged rural area of Fukushima
through the field survey of prior efforts around thearea.
It will focus on two areas; the Yamakiya area and the
Towa areas which are neighbouring villages (SeeFig.2). Yamakiya Area was located within the SDA.
On the other hand, the Towa Area was located outside
the SDA. Then, residents in Towa Area were allowed
to return home and restarted agriculture soon after the
nuclear disaster.
This paper will investigate leading activities in the
Towa Area that have taken countermeasures against
various social problems aiming for reconstruction
which was located outsides SDA despite the actual
damage of radioactive contamination. We also aim to
obtain knowledge for the regeneration of socioecological production landscapes in other rural areas.
Study methods used in this research are literature
reviews and field survey regarding on current
condition of the two villages and interviews with five
representatives and young farmers of Towa area andYamakiya area.

Nihonmatsu City from 2000 to 2016 are shown in
Fig.6. It was maintaining a gradual rate of descentfrom before the earthquake in Towa area. This is acommon phenomenon in many mountainous areas inJapan. It can be seen that no significant population
decline has occurred before and after the disaster.
Also, because Towa area was out of the evacuation
instruction area, it can be inferred that the community
maintenance of the agricultural field were achieved inspite of the contamination. In the following resultsfrom the four interviews are presented.
Interview of a Young Farmer; Representative of
Kibounotane Company
Interviewee M is the representative of Kibounotane
Company. She is also one of the young farmers who
decided to return to the TOWA area to continue
parents' farming by organic cultivation. When she
graduated from a university in Tokyo, the Great East
Japan Earthquake occurred. She said that the Towa
area was in a difficult situation, there were harmful
rumour damage, and the workers were aging.

RESULTS AND DISCUSSIONS

It is necessary to increase the number of people
involved in the town, and to continue to increase
the people who can work in the community
maintenance of the town, by conveying the current
situation to many people. And I believe that it isimportant what to produce a diversity of thenumber of people.

This research investigated priori attempts incontaminated areas. We conducted an interview
survey on representative people in the both Areas. In
fact, it appeared to be a gap of in their reconstructionin the two areas. Here, we show some noteworthy
activities and initiatives in the Yamakiya area and the
Towa area.
Towa Area
Current Condition

Fig.7 Agricultural Experience and Famer Tour(Courtesy Kibounotane Company [4])Therefore, she established the Kibounotane Company.
This company aims to get many people to be
informed the current situation of Fukushima throughengaging in agricultural experience and farmer tour
around the Towa area. Also this company promotes
organic cultivation of rice and vegetables, and web
sales etc.
She talked about the green tourism of the post

Fig.6
Changes in Population of the Towa in
Nihonmatsu City/ 2000-2017 (Data of Nihonmatsu
City [3])The changes in the population of Towa in
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SEE - Nagoya, Japan, Nov.12-14, 2018

disaster;

local farmers who felt a sense of crisis when being
marginalized during the ‘Municipal Merger’ by
government Policy. After the disaster, the group was
entrusted to the operation of the road station 'Michino-Eki' from the city and acted as a base of activities
on reconstruction. Local residents of this group havecomprehensively undertaken various activities suchas branding of local agricultural products, sixth
industrialization(agricultural
diversification),
support of new farmers, and exchange with cities andgreen tourism etc.

I would like to focus on not only agriculture but
also career building and education in the area. And,I would like to not only engage in the framework ofdisaster reconstruction but also expand activities
with people outside the region from now on.
Also, she talked about agriculture,
Although general agriculture has resumed, there
are still harmful rumours regarding theradioactive contamination. The number of farmers
resumed is very small. Moreover they are almost
over 65 years old. Then, they can only last ten to
twenty years if young farmers don't return.

The interview respondent talked about the roadstation Fukushima Towa in his book published in2012 [6].
We are positioning the station of road as a base for
local production and local consumption by smallquantity multipurpose agriculture centring mainly
on vegetables and upland field creation.
We also open a variety of events, and the office of
NPO YSTA is also installed.
It is not only a function to sell products but also aplace for joint activities in the area and a place totackle the issue of community development..

Furthermore, she said about the future of the Towa
area
Even now, there is no change in the severe
situation, but increasing the number of people
involved in the town and communicating thesituation of the town will be a solution to the
problem. How many key person can connect local
person and the person who wish to immigrate
here?
And I want to increase the number of people who
can be active and create diversity.

'Satoyama Rebuilding Project' started from 2009 withthe goal of regenerating local communities, farmlands
and forests.
As an extension of the project, in August 2011 after
the earthquake, 'Yuuki no Sato Towa Satoyama
Rebirth Plan / Disaster Reconstruction Program'started. It was notable that the efforts of such aframework after the earthquake disaster and therestoration with a long-term perspective were carriedout at an early stage.
He talked about the difference between the Towa area
and the Yamakiya area.

Interview of Representative of Fukushima Organic
Agricultural Network
Interviewee S is the representative of Fukushima
Organic Agricultural Network and Director of NPO
Yuuki no Sato Towa Association (YSTA). He is alsoa person who is familiar with the process ofreconstruction and promotion for agriculture in Towa
Area

There is a big difference between the Yamakiya
area and the Towa area. One of them is aneighbouring town guarantee system-being
responsibility by Tokyo Electric Power Company.
There was compensation of 100,000 yen per personin the Yamakiya area what is located inside the
SDA, but no compensation was offered in the Towa
area since it was outside of SDA.
The famers in Towa had to start soon after the disasterwithout the compensation after the disaster in spite ofunder decontamination process.

Fig.8 NPO Yuuki no Sato Towa Association [5]NPO YSTA was established in 2005 which has
members of approximately 250 households, including
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Summary of the Towa Area

Interview of Young Farmer, member of Abukuma
Cut Flower GroupThe findings in this section are summarised asfollows.
1. It is necessary for the regeneration ofenvironmentally damaged rural area to increase thenumber of people involved in the town, and tocontinue to increase the people who can work in thecommunity maintenance of the town, by conveying
the current situation to many people.

Interviewee H is also one of the few young farmers
who decided to return to the Yamakiya area. He
would like to keep the community of Yamakiya bycultivating Turkey bellflower. And he is devoted tocontinuing the Abukuma Cut Flower Group. People
in the Yamakiya area were forced to evacuate due tothe disaster, cultivation was cancelled in 2011 and2012.
After that, by utilizing the 'Fukushima Prefecture
Farming Resumption Support Project' in 2013, we
tried to demonstrate a good example of the cultivationof Turkey bellflower in the evacuation area,
decontaminated agricultural land beforehand andcarried out test cultivation.
After completing the trail of cultivation, they planted
seedlings in 2014, and 9450 bottles of flowers
shipped.
Overcoming the blank for three years, they areshipping high quality Turkish bellflower

2. In the Towa area there is a framework called NPO
YSTA, this organization played a great role incomprehensively connecting people and towns.
3. It was notable that the efforts of such a framework
after the earthquake disaster and the restoration witha long-term perspective by utilizing the government
measures such as "Reconstruction Plan / Disaster
Recovery Plan”, were carried out at an early stage.

Yamakiya Area
Current Condition
The changes in population of Yamakiya district in
Kawamayta Town from 1995 to 2018 are shown in
Fig.9. It was maintaining a gradual rate of descentfrom before the earthquake in the Yamakiya area.
This is the same as Towa.
However, from 2011 (after the disaster) to 2017 (until
the lifting of the evacuation order), there were noresident.
Even after the evacuation direction was cancelled thenumber of residents were 100 in 2017, 300 in 2018,
and only about 20% of the total residents had returned,
and the number of evacuees still remains high in
Yamakiya.

Fig.10 Abukuma Cut Flower Group [7]The interview respondent
Community development.

talkedabout

theFirst of all, it is important that you can make astable living as a farmer in the Yamakiya area. And
I think that we can increase the number of membersof this group.
In addition, he suggested about a matter of the
Yamakiya Area.
I heard that the number of people who are thinkingof returning to Yamakiya will increase little bylittle.
However, the Yamakiya area originally had manyelderly people, and from now on, it is predicted thatFig.9 Changes in Population of Yamakiya/ 20002017 (Data of Town Council of Kawamata [6])879SEE - Nagoya, Japan, Nov.12-14, 2018

Yamakiya work in Kawamata Town andFukushima City.
Six years have passed since we evacuated, butmany people still do not come back to the Yamakiya
area. I hope that Yamakiya will become a place
where they can come back any time, even if I do notlive in the Yamakiya area,
And, unless the Great East Japan Earthquake
happens, there is a connection that was not born.
Many people have supported me, so I believe that I
can give back them.

the population of the town will decrease more, so
the survival of local community maintenance likethe association of neighbourhood is a problem.
Also, I think that it is better to encourage
revitalization as a commercial facility for "Tanyano Sato" as a reconstruction base facility.

Interview of Chairperson of the Neighbourhood
Community Association of Yamakiya
Interviewee G is Vice Chairman of the Yamakiya
Farm Association. He is a person who participatedwidely in activities, such as events, dialogues, etc. asa face of the town, in various situations as well as
agriculture since the disaster.
He talked about the community.
Fig. 11 Tonya no Sato (Author’s photo)
There was a place point of time I was almost
giving up as it is a disaster, but with thecancellation of the evacuation order in the
Yamakiya area, I had to think about what to do in
the town. I tried to resume the living of the old
Yamakiya area, but I could not see anything of the
future vision. And I noticed that there was no
human connection in this current area.

Tonya no Sato, one of the ‘Michi-no-Eki’, is to be
developed as a symbolic facility of reconstruction
based on ‘Plan for promoting commercialization of
the Yamakiya area restoration base (March 2015)’. It
has been planned to contribute to the living support ofpeople who returned home from evacuation, as a
facility for people to gather and create bustling, andto revitalize local communities scattered by
evacuation.
He talked about the decontamination

Furthermore, he raised a concern about the Yamakiya
Area.
Although there is strong belief among the people
who have returned to the Yamakiya area now, there
are many elderly people who do not have physicalstrength or energy and the problem is that the
young generation does not return. There is asystem of the central government that supports
agriculture, but it is necessary to plan things ahead
for years and there is anxiety as to whether or not
to continue.
I think that it is good to create places other thanagriculture where we can do what we can doRadioactive contamination in Yamakiya area is notworrying too much, since there are some higher
points of air dose rate in the Towa area outside of
SDA higher than Yamakiya inside of SDA.
The grace of the mountains such as wild vegetables
and mushrooms was familiar to people in the
Yamakiya area long ago, but decontamination of
Satoyama is a serious task, so I think that I do nothave to force it.
Interview of Young Musician, Chairperson of theperformance group ‘Yamakiya Taiko’Summary of the Yamakiya area

Interviewee E is the leader of the performance groupcalled Yamakiya taiko. This group was formed in2001 to raise reputation of the region with traditional
drums that have been played for a long time at thesummer festival in the Yamakiya Area.
He suggested about a matter of Yamakiya Area.

The findings in this section are summarized asfollows.
1. Various activities and efforts at Yamakiya have a
big role for reconstruction. Each activity contains astrong intention for the revitalization of the town.
However, in the current Yamakiya area, there is noorganizational structure that strongly connects

The Yamakiya area is rich in nature, but theclimate in winter is severe. Many people from880

SEE - Nagoya, Japan, Nov.12-14, 2018residents, each of which remains independent
activities.

We would like to thank the interviewees for this paper
for their helpful comments.
Our thanks are also owed to Dr Tetsuo Yasutaka of
AIST for his helpful supports on this research. Also
our thanks go to Grants-in-Aid for Scientific
Research of Japan Society for the Promotion of
Science (18k18602) and the Obayashi Foundation.

2. The current situation of Yamakiya and the Towa
areas which are neighbouring towns presented a big
difference by the division caused by administrative
boundary of inside or outside SDA. This contrasting
recovery process was a negative effect on community
revitalization because this is a typical administrative
division caused by the central government’s policy. It
seems that a more flexible approach to designating
SDA is needed.

REFERENCES[1] Framework of Decontamination, Ministry of theEnvironment Government of Japan, Jan, 2012(http://josen.env.go.jp/en/)[2] Special decontamination Area, Ministry of theEnvironment Government of Japan, Jan, 2012
[3] Resident population by district (census) of
Nihonmatsu City, Fukushima(http://www.city.nihonmatsu.lg.jp/page/dir0026
02.html) in Japanese[4] Kibounotane Company(http://kibounotane.jp/aboutus/index.html) in
Japanese[5] Masatoshi Sugeno, Hiroshi Hasegawa,‘Agricultural activity overcome radioactivity’,Commons Publishing, 2012 in Japanese[6] Resident population by district (census) of
Kawamata Town, Fukushima,(http://www.town.kawamata.lg.jp/site/sinsaisaigai/Yamakiyatikukyojyuujyoukyou.html) in
Japanese[7] Fukushima Prefectural Government,
Agriculture, Forestry and Fishery Case Studies(https://www.pref.fukushima.lg.jp/site/fffsyoku-furusato/jireisyu.html) in Japanese

CONCLUSIONSIn this research we examined the activities in twocontrasting areas in Fukushima. Results are as
follows.
1. Various activities and efforts at Yamakiya playeda critical role in reconstruction. Each activity contains
a strong intention for revitalization of the town.
However, In the Yamakiya area, there is no publicorganization system that strongly connects residents,and each follows currently an independent activity.
On the other hand, in the Towa area there is aframework called NPO YSTA which gives aframework for comprehensively connecting people
and towns.
2. The current situation of the Yamakiya and theneighboring Towa area had a big difference caused byadministrative division by the government’s policy
on evacuation order. This contrasting recovery
process was a negative effect on the community
redevelopment. It seems that a more flexible
approach for designating SDA is needed.
3. It is necessary for the Yamakiya Area to increase
the number of people involved in the rebuilding of thetown, and to continue to support the people who canwork in the community maintenance of the town, bydisseminating the current situation to many people.
The role of rural tourism is important as in the Towa
Area important.
4. It should be noted that the efforts in anticipation ofsuch a framework after the earthquake disaster andthe restoration with a long-term perspective by
utilizing the government measures such as"Reconstruction Plan / Disaster Recovery Plan”, werecarried out at an early stage in the Towa Area.
ACKNOWLEDGEMENTS

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

HOLISTIC LANDSCAPE PLANNING`S VALUE FOR NATURALDISASTER RECONSTRUCTION: WILLINGNESS TO PAY FOR NEW
RESIDENCE IN DIFFERENT RECONSTRUCTION PLANNING
APPROACHES
1Misato Uehara
Graduate School of Science and Technology, Shinshu University, Japan

1

ABSTRACT
Practical evidence demonstrating the effectiveness of holistic landscape planning is limited, because
comprehensive decision-making is misunderstood as depriving individual sectors' authority and budgets. Author
compared the difference of recovery speed from disaster and the quality of relocation housing in the twomunicipalities in contrasting planing process from the Japan Earthquake and Tsunami (2011) disaster. Shinch
town has recovered by bottom up planning process and author's site-analysis which based on 1969's McHarg's
landscape planning principle and 1980's Japan Land Agency's environmental database. Whereas, Soma city has
recovered by top-down planning process, which was the same method as other municipalities affected bytsunami. In this test, 263 students evaluated relocation houses’ prices. Author analyzed subjects' attribute datathat could potentially affect their evaluation: evaluator's sex, environment in childhood, and demand for futureenvironment. T-test and multiple regression analysis were performed to analyze the concurrent effects of holisticplanning process. Welch 's t-test found that the mean of relocation residential WTP price ($). Shinchi town'shouse (mean=$185400) was significantly higher than that of Soma city (mean=$157680. t=15.9, p<2.2e-16 (twotailed), d.f.=3622.1), $1=￥100). A multiple linear regression was calculated to predict [WTP], based on [USP：
Under Shinchi town planning process] and [VDD：Volunteer or donation to a disaster area]. (Predicted WTP isequal to [150200] + [+27700] ([USP]) + [+8176] ([VDD]). [USP] is coded as [Shinchi:1 or Soma:0], and [VDD]
is coded as [Yes:1, No:0].). These findings could help us in recovery planning from disasters.
Keywords: Land use planning process,2011 Tohoku disaster, Reconstruction. Cost-benefit, Climate-change

On the other hand, in 1969 Ian L. McHarg [3]compared the cost effectiveness of uncontrolled
growth and controlled growth with comprehensive
land use planning in Baltimore County, Maryland.
On that basis, he showed that it is possible toincrease development income by comprehensive
land use plan. George Hundt Jr [4] analyzed theactual Baltimore 's regional development. He
indicated that although McHarg's master plan was
extremely effective for the restriction development,
it did not achieved housing development. Melissa
Wagner [5] and Yang, B. [6] pointed out that
McHarg's original analysis for land suitability in
New York Staten Island and The Woodlands, Texas
were effective to avoid disasters respectively.
In such circumstances the following has not beenclarified. Can the comprehensive planning processcontribute to not only the avoidance of disasters but
also the development of the housing which has
higher value?
This present study aimed toevaluation of the real value of reconstructed housingwith holistic land use planning approach in 2011
Tohoku earthquake and tsunami disaster area.

INTRODUCTION
Amendola [1] indicated that between 1984 and2003, more than 4 billion people were affected byextreme natural events, and that between 1990 and
1999, the cost of natural disasters was more than 15
times higher than during 1950-1959 [2]. The
research noticed that the standard planningapproaches to disasters were too reactive, although
there had been some progress toward integrated andproactive risk management for disasters in many
countries. Moreover, in most countries there has
been little integration among the relevant
responsibilities. For example, disaster prevention
generally has nothing to do with land use planning.
Formerly, many Japanese people believed thatmodern technology could prevent damage from any
natural disasters, but this belief is proved to be afault, by the 2011 Earthquake and Tsunami Disasterin Japan. Thus, we should change the fragmentary
approach to a new holistic approach with citizen’s
participation. In fact, the disasters which attack oursociety are becoming more and more frequent andunpredictable.
Unfortunately, many relocation sites after thedisasters are still based on fragmentary approaches.

METHOD882

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Study Area Selection
The author analyzed the two towns’
reconstruction process until the completion of
housing; this section compares each town's
development achievement rate, from the candidate
site selection (2012) to close -out of recovery andreconstruction (2015).

In this research, we focused on the twomunicipalities’ redeveloped houses for the tsunami
damage area, which were planned by contrastingprocess in Fukushima prefecture. Shinchi town
provided the residents with many reconstruction
sites by bottom up planning process and our site
suitability analysis using the Ian McHarg's landscapeprinciple and 1980's Japan Land Agency's historic
data [3], [7]. Shinchi town’s process involved citizen
and public co-determination, whereas Soma city
only determined a quick-fix solution without
renewed planning. Unfortunately, most areas which
are affected by this disaster carried out theirreconstruction, using the method which is similar toSoma city's one.
The land evaluation of the Shinchi town’splanning process is important for the following
reasons. Ryuzo Eda operated the Shinchi town’sreconstruction planning. He was a graduate of the
Hokkaido University’s Dr. Hidetsugu Kobayashi
laboratory, which had incorporated McHarg's theory
into education early.
In addition, this town utilized author’s land
suitability analysis for bottom-up planning with
Tadayoshi Inoue 's support, which was the resultsof Land suitability analysis with McHarg's landevaluation process and historical environmental dataof the Japan Land Agency in author’s laboratory.
This 1980's data was a historically importantachievement that has been saved miraculously in theauthor’s university's laboratory. This is the first
application of Ian McHarg's ecological planning for
Asian country. While the database was being
constructed, there was cooperation among landscapearchitects, politicians, architects and bureaucrats inJapan and the United States. This non-digitizedpaper data (maps and index tables) were digitized by
the author. After that, the disaster risks at Shinchi
town's relocated residential site and the place being
considered for a new factory were verified by thisdata and ecological planning process in 2012,2015.
. However, the other tsunami disaster areas
which are bigger than Shinchi town have difficultyin making a holistic relocation planning with victims
without the author's land suitability analysis andMcHarg's planning approach.

Reconstruction Housing Evaluation by WTP
Based on the photographs of each reconstruction
residential area taken in 2015, author conducted aquestionnaire survey of CVM to 263 students. Its
purpose was to investigate how much we would liketo pay for 14 site houses (Shinch town’s 7 sites,
Soma city’s 7 site). The hedonic approach deals withactual sales volume. It is difficult to obtainappropriate price data, because the rebuild relocation
housing construction used subsidies. Therefore, theauthor decided to carry out a CVM (WTP) approach,using the virtual evaluation method instead of thehouses’ actual prices. The author also considered a
web questionnaire which surveyed actual victims,
but there is a bias to evaluate their own housing andregion samples highly. Furthermore, in actual
disaster areas, the young generation’s outflow to theother big city is a serious problem. So the author
used university’s students as subjects. In the CVM
virtual evaluation method, generally a two-step
selection method is selected, to avoid a decrease of
the number of samples due to an answer of 0 yen.
However, in order to have 14 sites of reconstruction
houses evaluated, this research required to present
the average sales price (20 million yen) of thereconstructed housing at coastal region of
Fukushima and required to have students answer theevaluation price by free description (Open -end
method).
Photographing and Processing
Reconstruction Houses

Completed

Photos of each relocation houses were taken toreflect each types of houses and the surrounding
environment. In addition, each photo was processed
to minimize temporal effects such as sky’s
brightness. Regarding actual price evaluation of
CVM, in order to eliminate the influence of theevaluation order, this CVM test showed the subjects
the photos of Shinchi town and of Soma city
mutually.
Statistical Processing

Monitoring Until the Housing Relocation Is
Completed

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Photo 1 Difference in progress of housing relocation between Shinchi town and Soma city

Photo 2 Shinchi town’s real relocation houses in 7 sites

Photo 3 Soma city’s real relocation houses in 7 sites
Wilcoxon 's t-test and multiple regression
Shinichi town decided the policy to purchase theanalysis were performed to analyze the concurrent
tsunami inundation residential area by consultation
effects of holistic environmental planning process. A
with government, which is decided fastest in thelogit model including both planning style (Shinch ordisaster areas. Tadayoshi Inoue helped the initial
Soma) tested the significance of the related variable.
direct negotiation between Shinch town andUnderlying the results is the contribution of adding
government, but the other municipalities had noteach variable stepwise procedure.
tried contact with the government. Shinchi town
could start to decide the suitable site to rebuild
houses by consultation with its residents from the
RESULT
whole town smoothly. On the other hand, Soma Cityand many other municipalities basically used the
Study Area Selection
remaining place of the residential zone, which had
884

SEE - Nagoya, Japan, Nov.12-14, 2018

been planned already as the relocation’s destination.
These site planning was determined before thedisaster in 2011. Shinchi town’s reconstruction
process with residents’ participation required a lot oftime and effort, but the Soma city’s process did not.
But Soma city’s victims might have to build housesin the areas which is not suitable for development,
because the planned residential zone had alreadybeen taken up in proper land [8].
The author evaluated a natural disaster’s risk ofrelocation housing candidate site of Shinchi town
and Soma city, using Japan Land Agency’s data in
1980 and McHarg's land suitability analysis in 2011.
Shinch town’s housing candidate sites were decided
by many workshops with its residents and theadminister. Interestingly, these sites coincide withthe areas which judged to be safe by author's
comprehensive land suitability analysis. On theother hand, Soma city’s sites were evaluated danger
than Shinch’s sites.
On the other hand, Soma city’s sites were
evaluated more dangerous than Shinch town’s sites.
The result of disaster risk assessment by theauthor was also referred by Shinch town, and theydecided the 7 relocation places in 2012. Since 2011,
700 billion dollars was used as the reconstruction
budget in the tsunami disaster areas. But 100
thousand victims moved to another big city from theaffected area until 2015, although building
infrastructure and housing was promoted. In suchcircumstances Shinchi town is a successful modelthat restored the population, except for big cities.
The other big cities whose population has recovered
are Minami-Soma and Iwaki, which had temporary
workers at Fukushima nuclear power plant andradioactive decontamination work, and Sendai,
where is the biggest city in the Tohoku region.

renewedSoma city’sestimates
relocation
houses are
Table 1planning.
Willingness-to-pay($1=¥100)
willingness-to-pay estimate

the meanstandard deviation
95% confidence intervals(1$ = \100)
Shinchi town's
new house(Ecological Planning)
185400.3
56314.2

Welch t-test

Soma city's
new house157680.449591.488165.4 282635.2

47263.9 268096.9

Test satisrics
15.85

probability
p < 2.2e-16

Table 2 Evaluation result of relocation house's WTP
by multiple regression analysis
All data

VariableIntercept

Model1
Estimate
154330t value30.038

Pr(>|t|)< 2e-16 ***ME：Major of Education

5035-1.7790.075247 .

MF：Major of Fiber Science
MLE： Major oflaw and economy
ML：Major of literature

7046

1.764

0.077752 .

6200

2.066

0.038928 *

6484

2.224

0.026180 *MM：Major of Medical-2342-0.3110.756

MS：Major of Science

9236

2.403

0.016322 *ME：Major of Engineering-4937-1.5880.112

USP：Under Shinchi town planning process

27720

16.157< 2e-16 ***GUS：Grow up in the suburbs-786-0.301

0.764

GUU：Grow up in the urban
GUC：Grow up in the
countryside
GUA：Grow up in theapartment
GUD：Grow up in the
detached house
DSL：Desire ofsuburb living
DUL：Desire of urban living
DCL：Desire ofcountryside living
DAL：Desire ofapartment living
DDL：Desire of detached house living
TTD：Traveling to a disaster area
VDD：Volunteer or donation to a disaster area

-8956

-2.3570.018454 *

2678

0.844

0.399

3503

0.802

0.423

-5975

-1.9790.047883 *-3595-1.3700.171-25314-6.6603.16e-11 ***

11544

0.387

0.699

13253

2.478

0.013248 *

8176
-8980
6346

2.309
-2.8633.339

0.020986 *0.004216 **0.000849 ***built in paddy field, wetland and so on, which is notsuitable for development, because the land which isproper for residential zone had already been used.
Evaluation of two municipalities’ WTP differencesby t-test
The difference between the mean WTP of the
Shinchi town and Soma city was 27720 $ / house(Table 1). In addition to using Welch t-tests, we
compared the two municipalities’ average of
relocation house price. As a result, it was clearedthat Shinchi town's WTP is higher than that of Soma
city.

Monitoring Until the Housing Relocation Is
Completed
Photo 1 shows the difference of two
municipalities’ development achievement rate. The
Shinchi town's completion rate of relocation houses
has been 100% (7/7 sites) until 2015. On the other
hand, that of Soma city has been 77% (7/9 sites)
until 2015. Moreover, the occupancy rate of Soma
city's completed relocated houses is also low.

Evaluation of relocation house's WTP by multiple
regression analysis
This section examines the relationship among
the evaluation (WTP) to the relocation housing after
2011 Tohoku earthquake disaster, the difference ofplanning process (Shinch’s way or Soma’s way),
and the respondent attribute by multiple regression
analysis (Table2).
Since the obtained WTP scores follows anormal distribution, analysis using that value wascarried out. 269 individuals were interviewed and263 of that were valid responses. Table 2 shows theRelocated Housing Evaluation by WTP
Sinchi town's and Soma city's relocation houses ineach 7 sites
Photo 2,3 show each relocation houses’ types
and surrounding environments. Comparing thecompleted reconstruction houses of the twomunicipalities, Shinchi town’s process involved
citizen and public co-determination, whereas Soma
city only determined a quick-fix solution without
885

SEE - Nagoya, Japan, Nov.12-14, 2018

analysis result of the contribution of adding eachvariable falling a stepwise procedure. The author did
not inform the subjects of the difference of two
towns’ planning process and these photos’ location.
This table shows the largest positive contribution to
explaining variation in WTP is USP (Under Shinchi
town's planning process). The VDD (Volunteer or
donation to a disaster area) also has positive
contribution to explaining variation in WTP.

accomplish the relocation, but the author’s method
can help save time. The realization of this process
might be difficult without the planning supports
above because the selection of residence areas
requires detailed discussion between the town and its
residents.
Next, the author found that Shinchi town's
relocation house's WTP is higher than Soma city's
WTP statistically. In addition, multiple linear
regression analysis indicates that USP (Under
Shinchi town's planning process) and VDD(Volunteer or donation to a disaster area) are
positive contribution. This result means Shinchi
town’s process increased value of relocation houses’
value (27,719 $ / house).
These findings extend research result of
McHarg[3], George Hundt Jr. [4], Wagner [5], andYang, B. [6]. ; The analysis of holistic land
suitability and planning process are useful for
selection of reconstruction site and development ofvaluable new residence for victims in 2011 Tohoku
earthquake and Tsunami disaster field.
In other words, this WTP comparison indicates thecomprehensive planning process contribute to not
only avoidance of disasters but also development ofreconstructed housing with higher value after
disaster.
Most notably, this is the first study on theknowledge to investigate the effectiveness of holistic
land suitability analysis and planning process forreconstruction housing from natural disaster.
Tohoku Earthquake and Tsunami disaster hadserious social damage: Magnitude-9 earthquake,
Tsunami disaster area 561km2, Dead 15,894 people,
missing 2,500 people, Destroyed buildings 120,000,
Half-destroyed buildings 278,000. This disaster’s
direct financial damage is $199 billion dollars. The
damage due to the radiation effect is estimated tocost approximately 641 million dollars in Fukushima
prefecture [16]. In addition, although 700 billion
dollars of reconstruction expenses had been used,
100 thousand victims moved to other big cities fromrestoring home towns. So it is very important thatthe houses which based on holistic land use planning
get higher evaluation than the house by top-downplanning process in Tohoku disaster areas.
However, although our hypotheses were
supported statistically, there is limitation that the
sample were students, not actual victims. Therefore,
the work in the future should include follow-up
work designed to evaluate by actual young victims
who leaved home town.

CONCLUSION
Prior works documented the existence of
farmland and green space's value [9] [11]; forexample, Mbolatiana Rambonilaza [10] reports thatmost of visitors were willing to pay for the use ofwooded recreation areas. Furthermore, approximate
half of the respondents were willing to pay toprevent the conversion of forested parks to anotherland use for quality of thir housing environment.
Yan Song [12], Fanhua Kong [13], Hee Jin Yang[14], Shabana, Ghaffar Ali [15] and value, planning
process and time change from the planannouncement. For example, Fanhua Kong [13]reported that proximate urban green space (the sizedistance index of forest park, accessibility to parks
and green spaces) has a positive impact on houses’
prices.
In addition, Ian L. McHarg [3] compared thecost effectiveness of an uncontrolled land use
development with that of a comprehensively
controlled land use development, in Baltimore
County, Maryland. This simulation showed thepossibility to increase development revenue. George
Hundt Jr [4] indicated that McHarg's Baltimore
master plan did not achieve houses’ development,
although it was effective for the controlled
development.
Melissa Wagner [5], and Yang, B. [6] proved theusability of the original McHarg's land use plan for
natural disasters. But, actual development deviatedfrom original McHarg's land use planning. Then, thepurpose of this present study is to clarify that thecomprehensive planning process contributes to not
only avoidance of disaster impact but also
development of higher value housing."
As a result, the author found that in this virtualcase, the candidate sites selected by Shinch town's
careful bottom-up planning process correspond withthe safer sites (low natural disaster risk) which was
judged by author's evaluation with 1980's Japan
Land Agency's data and McHarg's land analysis /planning process. This result indicates that there is apossibility that larger municipalities also can selectsuitable land for relocation site easily using the
1980's environmental assessment data and McHarg's
planning process. If large municipalities could use
them, they could select the proper relocation sites inshorter time. Shinchi town needed a lot of time to

ACKNOWLEDGEMENTS
This work was supported by JSPS KAKENHI
Grant Number 15K21039 and Research Institute for
Humanity and Nature (RIHN: a constituent memberof NIHU) Project No 14200103. The author886

SEE - Nagoya, Japan, Nov.12-14, 2018

experiment method?,Landscape and Urban
Planning,Vol.83, Issue 4, 2007, p318-326[11] Liisa Tyrväinen, Hannu Väänänen ,The
economic value of urban forest amenities: anapplication of the contingent valuation method,
Landscape and Urban Planning, Vol.43, ,1998
pp. 105-118[12] Yan Song, Gerrit-Jan Knaap, New urbanism andhousing values: a disaggregate assessment,
Journal of Urban Economics, Vol.54, Issue 2,
2003, pp218-238[13] Fanhua Kong, Haiwei Yin, Nobukazu
Nakagoshi, Using GIS and landscape metrics in
the hedonic price modeling of the amenity valueof urban green space: A case study in Jinan City,
China, Landscape and Urban Planning, Vol.79,
2007, pp.240–252[14] Hee Jin Yang, Jihoon Song, Mack Joong Choi,
Measuring the Externality Effects ofCommercial Land Use on Residential Land
Value: A Case Study of Seoul, ,Sustainability,
MDPI, Open Access Journal, vol. 8(5),2016,pp1-15[15] Shabana, Ghaffar Ali, Muhammad Khalid
Bashir, Hassan Ali, Housing valuation ofdifferent towns using the hedonic model: A caseof Faisalabad city, Pakistan, Habitat International
Vol.50, 2015, pp240-249[16] Kenta Tanaka, Shunshuke Managi,Impact of aDisaster on Land Price: Evidence from
Fukushima Nuclear Power Plant Accident,The
Singapore Economic Review,Vol.61(1),2016,
pp.1-15

gratefully acknowledges the help of Makoto Fujii
and Yuka Utsugi.
REFERENCES[1] AnielloAmendola,Joanne
LinneroothBayer,Norio Okada,Peijun Shi, Towards
integrated disaster risk management: casestudies and trends from Asia- Natural Hazards,
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[2] Parker, Ronald Steven, Hazards of nature, risks
to development: an IEG evaluation of WorldBank assistance for natural disasters, The World
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[3] Ian L. McHarg, Design with Nature.,Garden
City: American Museum of Natural History,
1969,pp.1- 197[4] George Hundt Jr, Thomas L. Daniels,The Planfor the Valleys Assessing the Vision of Ian
McHarg and David Wallace, Journal ofPlanning History, Vol 17, Issue 1, 2018,pp3-19[5] Melissa Wagner, Joanna Merson, Elizabeth
A.Wentz, Design with Nature: Key lessons from
McHarg's intrinsic suitability in the wake of
Hurricane Sandy, Landscape and Urban
Planning,Vol.155, 2016, pp33-46[6] Yang, B., & Li, M. H. Assessing planningapproaches by watershedstreamflow modeling:
Case study of The Woodlands; Texas. Landscapeand Urban Planning, Vol.99 (1), 2011.,pp 9-22.
[7] Japan land agency, Evaluation method of land
use suitability by ecological planning - Survey
report,1980,Regional
planning
team,
inJapanese[8] Misato Uehara, Tadayoshi Inoue, Gen
Shintaku,The Favorable Settlement Relocation
Process After the 2011 Earthquake and Tsunami
Disaster in Japan by Evaluating Site
Environments and Accessibility, International
Review for Spatial Planning and Sustainable
Development,Vol.3,Issue1,2015,pp119-130[9] John M. Halstead, M.S., Measuring theNonmarket Valoe of Massachusetts Agricultural
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preferences: What can we learn from choice887

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE ADSORPTION OF HEAVY METALS FROM INDUSTRIAL
WASTEWATER USING SARGASSUM CRASSIFOLIUM
Lily Surayya Eka Putri1 and Eka Syafiqa1
1

Faculty of Science and Technology, State Islamic University Syarif Hidayatullah Jakarta, Indonesia
ABSTRACT

Sargassum crassifolium is the origin strains of macroalgae from Indonesia which was the most effectively
adsorb heavy metals from liquid solution and it was investigated the adsorptive capability of heavy metals inindustrial wastewater. The macroalgae were collected at Kotok Besar Island, Seribu Island, North Jakarta,
Indonesia and were treated with the variety of pH 2, 3, 4, 5 and 9 for 60 minutes oscillation, in duplicate
assessment. The macroalgae was selectively effective for removal of Cd, Hg, and Pb compared with other heavy
metals, achieving 75-99.05% adsorption efficiency, mostly in acidic condition for 60 minutes oscillation, except
Hg. The selectivity order for other metal ion uptake by S. crassifolium was Cu>Fe>Co>Ni>Cr with percentage
removal below 56%. Due to the low cost, availability and significantly high adsorption capability, the brownmacroalgae S. crassifolium is able to be used for selective removal of heavy metals from industrial wastewater
effectively in acidic pH range.
Keywords: Adsorption, Heavy metals, Industrial wastewater, Sargassum crassifolium

it has the various functional groups involved
including: (1) alginic acid, with carboxyl groups
and sulfated polysaccharides, as well as sulfonicacid, in brown algae matrix [15, 16, 17]; (2)sulfated galactans in red algae [15, 18, 19]; and (3)an external capsule composed of proteins and/or
polysaccharides in green algae [20].
Algal materials have been broadly observed forheavy metal adsorption, particularly the potential ofmarine algae, including macroalgae which has been
widely investigated. Non-living seaweed or dried
seaweed can be used as an alternative to the lowcost adsorbents [14] compared to other methods
such as more expensive physicochemical processes.
In Indonesia, the studies of macroalgae as heavy
metal adsorbents are limited in an aqueous solution,such as the study of adsorption of Cu(II) on
Sargassum crassifolium [21], Cr(III) on Euchemaspinosum [22] and Pb(II) on Sargassum duplicatum[23], S. crassifolium, Euchema spinosum andPadina minor [24]. The study of heavy metals
removal from industrial wastewater, however, has
not been widely conducted.
An inexpensive material such as marine
macroalgae is suitable for removing the heavy
metals from industrial wastewater [15, 16, 18-20,25]. In the present study, the industrial wastewater
was used as a medium to test the ability of S.
crassifolium to adsorb the heavy metals and as acontinuation of the previous study that conducted
testing with an aqueous solution. Sargassum
crassifolium is a genuine strain of Indonesian
seaweed that grows abundantly in Indonesian

INTRODUCTION
An increase in human population leads to asignificant enhancement in waste production.
Nowadays, the most notable wastes are the heavy
metals because of the high toxicity to living
creatures [1]. Along with the development ofscience and technology, the use of heavy metals,
especially in industries is increasing and causing
many environmental problems [2]. Heavy metals
wastes are discharged into the environment fromvarious industries working on electroplating,leather tanning, water cooling, pulp, and ore andpetroleum processing industries that are suspected
to be highly toxic to ecology and human health [3],and can also contaminate the environment
persistently [4, 5]. In Indonesia, Government
Regulation of Republic of Indonesia No. 82/2001
on Water Quality Treatment and Water Pollution
Control [6] is used to monitor the heavy metals
concentrations commonly generated by industries.
The removal of heavy metals from theenvironment is the urgent action to conserve nature
in a sustainable and further to protect human health.
The biological agent is one of the most efficientmethods used to reduce the pollution of heavy
metals in water including macroalgae [7, 8, 9],microalgae [10, 11, 12], mushroom [13], andagriculture waste [14]. The ion exchange and theformation of complex compounds are the heavy
metal adsorption schemes that occur within thewalls of algal cells. The structure of the cell wall
produces a high seaweed binding capacity because

888

SEE - Nagoya, Japan, Nov.12-14, 2018

waters. Therefore, it is appropriate to use S.
crassifolium as an adsorbent in this study whichaims to analyze its efficiency to adsorb the heavy
metals from the industrial wastewater. The resultsof this study can be applied in the industrial
wastewater treatment and subsequently contributeto reducing the pollution in the aquatic
environment.

to determine the metals concentration at 543 nm
wavelength.
Metals uptake and removal were calculated as
the difference in the metal concentration(s) before
and after sorption [26], according to Eq. (1).
q = (𝑪𝒊 − 𝑪𝒇 ) x
R=

MATERIALS AND METHODS

𝑪𝒊 − 𝑪𝒇
𝑪𝒊

𝑽

(1)

𝑴

x 100%(2)

Where q =metal adsorption (mg/g); M = dry
biomass (g); V= volume of the initial lead solution(L); Ci= initial concentration of lead in aquatic
solution (mg/L); Cf = final concentration of lead in
the aquatic solution (mg/L) at given time (t; min); R= removal percentage (%).

This study was conducted in the Integrated
Laboratory Center of the Faculty of Science andTechnology, State Islamic University Syarif
Hidayatullah Jakarta, including preparation of thesamples. The biomass samples of macroalgae S.
crassifolium were collected from the water
surrounding Kotok Besar Island, Seribu Islands,
North Jakarta, Indonesia. The samples were used in
the dried form. For wastewater sample, it was
obtained from the company of hazardous wastes
treatment located in Cileungsi region, Indonesia.

RESULT AND DISCUSSION
The preliminary research of the present study
had been conducted in an aqueous solution onvarious types of macroalgae, Euchema spinosum,
Padina minor and Sargassum crassifolium on Pb
and Cr adsorption using various initialconcentrations of 200, 300, 400, 500, 750, and 1000
mg/L and 7 variations of contact time, namely 10,
20, 30, 45, 60, 90, and 120 minutes [24] at pH 5[9]. Based on the study, S. crassifolium achieved
97-98% (Fig. 1) as the highest adsorption of Pb at
60 minutes contact time (Fig. 2). This was higher
and relatively faster than the study of Sweetly et al[9] which achieved 89.75% removal. This is due tothe high availability of active sites to bindadsorbent such as -COOH, -OH and -NH2 [27].
The ability of heavy metal adsorption by S.
crassifolium tends to decrease after 60 minutes
oscillation because the metal binding on the active
site has already saturated.
The highest Cr adsorption by S. crassifolium
was 99% achieved at 30 minutes contact time.

Preparation of Adsorbent
All sediments or small organisms which weretrapped in the macroalgae samples were washedwith the seawater and put in the zipped plastic bag,then brought to the laboratory. In the laboratory, allsamples were washed and rinsed again using
distilled water and then dried in an oven at 50 C for
24 hours to get the stable weight. The driedsamples were pounded with a mortar and pestle andsieved to the size 250-500 µm. The powder ofadsorbent was ready to use and kept it at room
temperature.
Adsorption Test
The experimental design used was Completely
Randomized Design with two (2) replications. The
eight heavy metals, including Cd, Co, Cr, Cu, Fe,
Hg, Ni, and Pb, and 5 variations of pH, namely 2, 3,
4, 5, and 9 which were oscillated for 60 minutes(refer the result from the previous study). The
correlation between pH and adsorption efficiency
was analyzed using one-way ANOVA.
The characteristic of Industrial wastewaterobtained from the company was measured using
ICP (Inductively Coupled Plasma), including pH,
chemical oxygen demand (COD), Total Dissolved
Solids (TSS), NH3, and initial concentration ofheavy metals. Furthermore, 0.5 g of dried S.
crassifolium was put into 50 mL wastewater andstirred for 60 minutes using a magnetic stirrer at
200 rpm. The solution pH was adjusted to 2, 3, 4, 5
and 9 with HCl (0.1 M) and NaOH (0.1 M). Then,the solution were filtered with Whatman paper
BF/C code and the filtrate was analyzed using ICP

100

%R

98

96
94
92
90
200

300

400

500

750 1000Ci (mg/L)
E. spinosum
S. crassifoilium

P. minor

Fig. 1 Adsorption percentage of heavy metal in an
aqueous solution at different initialconcentration [24]889SEE - Nagoya, Japan, Nov.12-14, 2018

The pH value is one of the most importantparameters in an experiment on a biosorption.
Various studies have been conducted but using
different biomass, such as Sweetly et al [9] using
Sargassum, while Vimala and Das [13] using
mushrooms as an adsorbent. The concentration ofhydrogen ions in adsorption is one of the importantparameters affecting the ionization rate of theadsorbent during the reaction and the replacementof positive ions in the active site [22].
The industrial wastewater used was assumed
containing a high concentration of heavy metals as
end-product of the industrial process. The
wastewater samples obtained from the company ofhazardous wastes treatment in Indonesia is a
mixture of wastewater solution from various
industrial companies. Thus, it absolutely contains a
lot of heavy metals which have specificbiochemistry characteristics and should be given
serious attention from all stakeholders.
The types of heavy metals contained in theindustrial wastewater were Cd, Co, Cr, Cu, Fe, Hg,
Ni, and Pb with initial pH 7.91. Several parameters,
including pH, COD, TDS, NH3, and heavy metals
from the industrial wastewater were also analyzed
using standard methods (APHA-AWWA) [28]. The
initial concentration of the various parameters forthe untreated industrial wastewater is exhibited inTable 2. The untreated concentration was thencompared to the treated industrial wastewater with
S. crassifolium is presented in Table 3. In order todetermine the safe limit of wastewater discharged
into the environment, the Government Regulationof the Republic of Indonesia No. 82/2001 [6] isused as a guideline.
Based on the regulation, most of theconcentration of the heavy metals from the sample
of industrial wastewater in various pH were above
the threshold limit, but not too far away, except Cd,

100

%R

95
90
85
10

20

30 45 60 90
time (minute)E. spinosum
P. minorS.crassifolium

120

Fig. 2 Adsorption percentage of heavy metal inaqueous solution at various contact time
[24]
Sargassum crassifolium showed the fastest time toreach the highest adsorption percentage than E.
spinosum and P. minor, due to the high number ofactive sites (carboxyl, amine, and hydroxyl) on thesurface of the S. crassifolium’s epidermis.
Therefore, of the previous study‟ results, S.
crassifolium belonging to Phaeophyta division
could be claimed as the most suitable adsorbent forlead supported by a stronger form of the cell wall,
predominantly alginic acid or alginate, compared toE. spinosum (Rhodophyta) and P. minor.
Macroalgae S. crassifolium was able to adsorp 9798% of lead (Fig. 1) and capacity of adsorption
55.56 mg/g fit Freundlich model (Tabel 1). This
was assumed S. crassifolium had high adsorption
capacity on heavy metal. Other studies have also
supported by these findings [8, 9, 15,17, 21, 23,
25].
The observation was continued using industrial
wastewater to analyze the capability of macroalgae
S. crassifolium on heavy metals adsorption, invarious pH, 2, 3, 4, 5 and 9 for 60 minutes
oscillation as the optimal contact time refer to theprevious study.

Table 2 Characterization of the untreated industrial
wastewater
Parameter

Table 1 Constant Value of Langmuir & Freundlich
Isotherm
Adsorbent
E. spinosum
P. minorS. crassifolium

E. spinosum
P. minorS. crassifolium
Source: [24]

a
32.26
40.00
55.56
k
3.322
4.846
2.453

Langmuirb
0.00460.00260.0008
Freundlich
n
2.841
1.390
1.379

pH
COD
TDS
NH3
Heavy metals:
Cd
Co
Cr
Cu
Fe
Hg
Ni
Pb

R2
0.984
0.934
0.882
R2
0.892
0.862
0.976

890

Initial Concentration(mg/L)
7.91
8160
18890
656
0.10
0.0505
0.41
0.102
2.69
0.27
1.11250.04

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 3 Concentration of heavy metals after treatedby S. crassifolium
Met.
Cd
Co
Cr
Cu
Fe
Hg
Ni
Pb

TH
(mg/L)
0.01
0.2
0.05
0.02
0.3
0.001
0.003
0.03

pH 2
0.001
0.026
0.252
0.044
2.608
0.008
0.62
0.033

pH 3
0.001
0.027
0.269
0.045
1.546
0.00720.619
0.01

Cf (mg/L)
pH 4
pH 5
0.001
0.001
0.031
0.036
0.35
0.412
0.088
0.481
1.3
1.186
0.006 0.0065
0.69
0.805
0.026
0.031

70%), especially in dried brown algal biomass [30].
Thus, the adsorption efficiency of the brown algae
displays at pHs near the apparent dissociation
constant of carboxylic acids as the majority ofmetals of interest (i.e. Cd, Co, Cu, Fe, Ni, Pb) [15],which is similar to this study result.
The optimum removal of those metals from theindustrial wastewater was completely achieved at
60 minutes contact time which was contrary to thereview by Davis et al [15] in red and brownmacroalgae which were achieved in 180 minutes,
although the adsorption efficiency was almost thesame. The contact time did not show significantly
correlated, as reported by Putri [24], however, it hasa very significant effect on the cost of the industry
for the processing of waste, including electricity
and tools use. Besides, the metal hydrolysis
constants, the ion size (ionic radius) andelectronegativity have to be considered for theaffinity of the adsorbent for adsorbing heavy metals[31].
Each type of heavy metal has the ability tobind with the cationic group on different
macroalgae active sites depending on the chemical
properties of the heavy metal and is highly
dependent on the acidity (pH) conditions. The
highest adsorption capability of S. crassifolium wasachieved at range pH 2-5 for Cd, Co, Cr, Cu, Ni,
and Pb, which similar to Sudiarta and Diantariani[22] and Susanti [32], except for Hg and Fe which
was removed as much as 98.81% and 53.48 fromthe solution at pH 9. This is similar to the study
reported by Cossich et al [33] for Cr, Latinwo [29]for Cr and Fe, and Davis et al [15] for Cd, Pb, Ni,
and Cu. However, the affinity of the adsorbent for
adsorbing Hg from industrial wastewater is quiterare studied. Huang and Lin [8] studied Hgadsorption by Sargassum in an aqueous solution
which found pH 8-10 was the optimum adsorption
capability with 70% removal of heavy metals.
Another study was reported for red algae which
could adsorb 99% Hg at pH 7-10 [34]. Similar tothis study, the adsorption efficiency of Hg by S.
crassifolium had almost reached 98% removal fromindustrial wastewater at pH 9.
The studies reported above were tested in the
aqueous solution which was differed from thisstudy trialed in industrial wastewater. In this study,
several heavy metals were removed from industrial
wastewater below 56.86%, only Cd, Co, Hg, and Pb
with 75-99.05% removal. Nevertheless, all theheavy metals were safely discharged to theenvironment because the concentrations were still
below the threshold limit in accordance with theregulation [6]. The different adsorption capacity
was due to the affinity of adsorbent to adsorb heavy
metal which was related to the cationic binding
system. At acidic pH (pH<5), it had positive surface
charge and electrostatic repulsion from a number of

pH 9
0.01
0.043
0.403
0.058
1.169
0.002
0.916
0.046

Note: TH: threshold limit based on Government
Regulation of Republic Indonesia no 82/2001%R

Co, Hg, and Pb were safely to be discharged to theenvironment (Table 3). Although the final
concentration on those metals was still above theregulated threshold limit, the adsorption efficiencyof those metals was quite good reaching 37.7856.86% removal (Cu>Fe>Ni>Cr). However, interms of environment quality, this condition is notgood and needs a serious attention especially on
treatment process, including pH, type of adsorbent,
and contact time to get an optimum heavy metals
adsorption by the adsorbent.
Regarding the adsorption capability of heavy
metals by S. crassifolium, the percentage removalof Cd, Hg, and Pb from industrial wastewater was
the highest, reaching 75-99.05%, mostly in acidic
pH range, except Hg were in alkaline pH, as shownin Fig. 3. It further was followed by
Cu>Fe>Co>Ni>Cr was found 37.78-56.86%
removal in acidic pH range, as similar as reported
by Davis et al [15]. It is was assumed due to thedissolution of some cytoplasmic components orions, such as carbonates released into the solution
and anion types, similar to the study by Latinwo etal [29] for chromium uptake.
The carboxylic groups in the brown algae are
generally the most abundant acidic functionalgroup, such as in S. crassifolium. They constitutethe highest percentage of binding sites (more than
120
100
80
60
40
20
0
Cd Co
pH 2

pH 3

Cr

Cu

Fe Hg Ni

metals
pH 4
pH 5

Pb

pH 9

Fig. 3 Removal percentage of heavy metal on
industrial wastewater891

SEE - Nagoya, Japan, Nov.12-14, 2018

H+ ions and cationic species caused a lower
attachment of metal ions. On the contrary, theadsorbent‟s sites carried negative charges atalkaline pH (pH>5) which favoring metal cationiccomplexes attachment.
Thus, it can be confirmed that this experimentconsiders selective removal of heavy metals fromindustrial wastewater, in suitable pH (p<0.05) andcontact time, in order to reach the optimum removal
percentage. The safe concentration of heavy metals
discharged into the environment, especially into thewaters, is an important point because it caninterfere with the life of living organisms andultimately lead to death. That is why theinternational institutions develop standardization
for food consumption that could expose throughfood to human through the food chain in nature.
Those international institutions are the World
Health Organization (WHO), Food and Agriculture
Organization (FAO), European Medicine Agency(EMA) and Joint Expert Committee on Food
Additives (JECFA) providing the guidelines oftolerable daily intake on exposure of heavy metals
for the human being based on body weight (Table
4).

aquatic ecosystem which further has a serious
impact on human health. The regulations set by thegovernment have to be obeyed by all industry
stakeholders and prioritize law enforcement for
those who violate.
CONCLUSION
Sargassum crassifolium from the Phaeophyta
division showed the best ability to selectively
adsorb 37.78-99.05% of heavy metals fromindustrial wastewater at pH 2-3 or 9 and contact
time of 60 minutes. The highest adsorption
capability was 75-99.05% for Cd, Hg, and Pb. Mostof the heavy metals are still above the standard,
both by the Government Regulation of the Republicof Indonesia No. 82/2001 and TDI standard,
however, it exhibits high adsorption efficiency.
This finding is useful for the industries which
produce hazardous wastewater in the production
process. This study is able to reduce the cost andtime of wastewater treatment efficiently, although
the selectivity of the heavy metals adsorption is oneof the limitations of this study. However, theslightest reduction of a pollutant from industrial
wastewater is very influential on environment
condition and will give a significant contribution to
the conservation of living organisms in theecosystem sustainably.

Table 4 Tolerable Daily Intake (TDI) for heavy
metals

Metals
Cd
Co
Cr
Cu
Fe
Hg
Ni
Pb

TDI (mg/50-60kg bw)
WHO/FAO
EMA
JECFA
[35]
[36]
[37]
0.06
1
0.05-0.2
0.3
3
0.05
0.8
0.26
0.8
0.005
1
1.4
0.3
0.214
2

ACKNOWLEDGEMENTS
Authors would like to thank State Islamic
University (UIN) Syarif Hidayatullah Jakarta which
had given financial support for this research. We
thank the hazardous waste treatment company forthe technical support in research material and dataassessment. We also thank students and laboratory
staffs of Biology Department, Faculty of Scienceand Technology UIN Syarif Hidayatullah Jakarta
for field and laboratory work‟s support.

The concentration of heavy metals in food is
the important information that has to be obeyed by
all stakeholders in the industries. Foods from thefishery products are mostly exposed to pollutants inthe waters, which are mainly derived fromindustrial wastewater. Many studies reported
contamination of heavy metals in the organism [38,39, 40], in sediments and waters [40, 41]. They
reported that industrial wastes contribute to thewater pollution and is responsible for solving thatproblem.
In connection with the results of this study, thefinal concentration of heavy metals in thewastewater after the treatment by S. crassifolium
was relatively safe for Cd, Cu, Hg, Ni, and Pb in
accordance with TDI guideline, except for Cr and
Fe. Therefore, the treatment of the industrial
wastewater is the important process to conserve the

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

MEDICAL WASTE MANAGEMENT IN PRIVATE CLINICS IN
SURABAYA AND FACTORS AFFECTING IT
1

Susi A Wilujeng1, Enri Damanhuri2 and Mochammad Chaerul2
Environmental Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
2
Environmental Engineering Department, Institut Teknologi Bandung, Bandung, Indonesia

ABSTRACT
Health care services generate solid wastes that impose environmental risk if not properly managed, especiallythe one categorized as hazardous. The compliance of those facilities to the regulation regarding waste
management—from the source by waste reduction, segregation, storage, transportation, treatment, and burial—
is important to be investigated to identified whether it has been conducted properly. This study was conducted in
17 representative clinics by sampling their solid waste for five consecutive days, observing whether theoperation of their solid waste management is conforming the related regulations, and performing logistic
regression analysis to develop the correlation between independent variables (sanitary officer that specifically
responsible for managing waste; routine budget allocated for waste management; standard operational procedure(SOP) for waste management; and waste management training for staffs) and dependent variables (color-coded
waste containment; symbol assignment on waste container; and waste storage location). The results show thatthe medical waste generation rate was 0.070 kg/patient/day. Composition of the waste from clinics comprised of
21% sharps, 42% infectious, and 37% general waste. The process of solid waste segregation, collection, andstorage has not complied with the standard regulated by the government. Logistic regression analysis shows thatfor implementation of color-coded container the affecting factors are budget and SOP; for the availability of
waste storage is staff training; while for symbol assignment there seem to be no significant factors affecting it.
Keywords: binary logistics regression, health care clinics, medical waste, solid waste management,
Surabaya City

level standards and regulations leads to ineffective
control and an inability to impose legal penalties on
those who neglect their waste management duties[5]. Several developing countries, including Jordan,Iran, Brazil, India, Cameroon, Botswana, Vietnam,
and Nepal, to name a few, have already
implemented ministerial-level medical waste
management regulations [6]. Indonesia also has
comparable regulations. Environment and Forestry
Ministry Regulation number 56, regulate themanagement of hazardous waste from health carefacilities. This regulation has been adopted by
Ministry of Health to regulate and monitor clinics by
issuing Ministry of Health Regulation no 27 2017,
Guidelines for Infection Prevention and Control at
Health Service Facilities. This regulation
standardises the management of hazardous waste at
the point of origin by regulating waste reduction,
segregation, containment, transportation outside thefacility of origin, treatment and burial [7].
Unfortunately, many healthcare facilities fail tocomply with these regulations, continuing to
improperly dispose of their waste without
punishment [8]. These facilities dispose of theiruntreated medical waste mixed with general waste inopen areas [9]. The limited availability of waste

INTRODUCTION
Healthcare solid waste is waste generated from
activities in healthcare facilities such as hospitals,
clinics, research centres, and laboratories related to
medical procedures. Of this waste, 75–95% consistsof non-hazardous, domestic-like waste that poses nohealth or environmental risks, and 10–25% iscomposed of hazardous waste that poses health andenvironmental risks [1]. Due to its infectious nature,
this waste must be well managed to prevent it fromspreading diseases [2,3]. Infectious diseases such as
cholera, dysentery, skin infections and hepatitis canbe epidemically spread by improper medical solid
waste management [4]. Inadequate waste treatment
and disposal can also cause indirect health risks.
Waste landfill, when not properly managed, may
release pathogens, toxic pollutants, and odours to theenvironment. It can also expedite the growth of
insects, rodents, and worms that lead to the spread of
diseases. Improperly operated waste incineration
may emit dangerous gases to the environment [1].
The difficulties faced by developing countries inmanaging their medical solid waste is caused by alack of financial investment, awareness on the partof administrators, trained staff, and appropriatetechnologies. Furthermore, the absence of national895

SEE - Nagoya, Japan, Nov.12-14, 2018

collection facilities, including the use of unsafe
containers and the absence of colour-coding for
medical waste, also posed obstacles to proper waste
segregation [8]. The segregation of waste inaccordance with its type, waste containment, as well
as storage that complies with standards, is key to thecontrol of risk at the origin of waste. The owners or
operators of healthcare clinics play a crucial role inthis process. Segregation is the key to minimizing
waste. It can reduced the amount of medical waste to
be treated up to 70.1% thus reduce significant
amount of cost [10]. Mistakes in segregating waste
at the source or placing the waste in the wrong
container occurred in small hospitals and clinics[11]. The well-executed waste segregation at thesource by providing good containers is the earlysteps of a good waste management that areimportant to do.
Logistic regression model is one of regression
methods used to find out the correlation of
categorized response variable with one or more
independent variable as category or continue. The
research objectives were to investigate themanagement of medical solid waste in clinics in
Surabaya, and to determine the factors that influence
the implementation of waste containment andstorage using logistics regression.

Table 1. Variables used for logistic regression model
Variable
CodingNo
Independent
1 = Present
1 Sanitary officer (X1)
0 = Absent
Waste management
1 = Present2routine budget (X2)
0 = Absent
Waste management SOP
1 = Present
3(X3)
0 = Absent
Waste management
1 = Present
4training (X4)
0 = Absent
Dependent
Colour-coded container
1 = Present
1(Y1)
0 = Absent
Symbol assignment on
1 = Present
2
container (Y2)
0 = Absent
Waste storage location
1 = Present
3(Y3)
0 = Absent
Modelling analysis was conducted using IBM
SPSS 20 software. Three models resulted: colourcoded container model, symbol assignment model,
and waste storage model. The logistic regression
model follows equation (1).

p (Y ) =METHODS

exp( β 0 + β 1 x1 +  + β k x k )1 + exp( β 0 + β 1 x1 +  + β k x k )(1)

where β0 is constant, βj is the regression coefficientand j is the number of predictor (independent)
variables.
The logistic regression model requires predictor
variables to have no multicollinearity. By calculating
VIF, the multicollinearity can be determined. If VIF
is less than 10 or the tolerance is more than 0.1, thenthe variables are free of multicollinearity. Table 2
presents the results of the multicollinearity test,
which shows that the dependent variables used inthis study fit the requirement.

This research is a descriptive study of solid waste
management in clinics in Surabaya City that took
place in 2017. Out of 285 clinics, the study was
conducted in 17 clinics, spread across the city, thatwere willing to issue a formal permit. Waste
generation sampling was performed over fiveconsecutive working days by weighing the waste
and recording the number of outpatients. To
investigate the clinics’ compliance with the waste
management regulations set out in Ministry ofEnvironment and Forestry Regulation No. 56, 2015,
observation and survey questionnaires were also
conducted.
The clinics’ waste management practices wereanalysed using binary logistics regression. Four
independent variables were determined for thisanalysis: a sanitary officer specifically responsible
for managing waste (X1), routine budget allocatedfor waste management (X2), standard operatingprocedure (SOP) for waste management displayed in
the clinic (X3), and waste management training forstaff (X4). The dependent variables being observed
were: colour-coded waste containment (Y1), symbol
assignment on waste containers (Y2), and waste
storage location (Y3). The absence of any of thesevariables was coded ‘0’ and its presence was coded‘1’ [12]. The complete set of variables used for thelogistic regression model is presented in Table 1.

Table 2. Multicollinearity test
Variables
Tolerance
Sanitary officer (X1)
0.362
Waste
management
0.881
routine budget (X2)
Wastemanagement
0.283
SOP (X3)
Waste
management
0.178
training (X4)

VIF
2.765
1.135
3.532
5.603

RESULT AND DISCUSSION
Surabaya City is the capital city of East Java
Province, a metropolis with 2,95 million inhabitants
covering an area of 33.306 Ha. Healthcare facilities
in the city comprise 61 hospitals offering various
classes and types of services, 63 community healthcentres, and 285 clinics [13].
The clinics observed in this study are privately
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SEE - Nagoya, Japan, Nov.12-14, 2018

owned. The establishment of a clinic is subject togovernment permission and the clinic owner mustobtain an operational permit. Subsequently, thegovernment will guide and supervise its operation.
Clinics must comply with regulatory requirements
governing their location, buildings, rooms,
infrastructure, equipment and staffing. One of theserequirements is to have waste management facilities[14].

activities are limited.
The waste generation survey results show thegeneration of 0.07 kg/patient/day of medical waste
and 0.040 kg/patient/day of non-medical waste. The
patients visiting clinics are solely to get treatment
and no other activities, therefore the genaration ofnon medical waste is low. The rate at which clinics
in this study generated medical waste is similar to
the rates in Pakistan (0.06 kg/patient/day), South
Africa (0.07 kg/patient/day) and Tanzania (0.01kg/patient/day) [1]. Surabaya City Health
Department recorded 256,143 patients per day,giving a waste generation figure of approximately 18
tonnes/year—a sizeable number that must be given
serious attention.
Non-medical waste does not require special
treatment; thus, it is directly transferred to thenearest temporary waste storage site to await
transportation to the government-owned landfill in
Benowo. In contrast, medical waste requires special
treatment. None of the clinics studied treat their own
waste. They must therefore subcontract this activity
to another party who has permission to transport andtreat hazardous waste. Unfortunately, not all clinics
were able to produce a manifest to prove that theirsubcontractors had the proper permits. The small
volume of waste generated by the clinics means thatdaily transportation by the third party is impractical.
Therefore, clinics must provide a waste storage area.
This area must be protected with an impermeable
floor and must be free of rodents and other animals.
The maximum storage time is two days; if storage
exceeds this timeframe, the waste must be kept at or
below 0° Celsius. The survey shows that only 41.2%
of clinics provide a special safe room, without acooler, for storing their medical waste. The rest of
the clinics keep their medical waste in a standard
storage area or other unspecified space within theclinic, without posting any signs.
The success of solid waste management depends
on the organisational capabilities of the clinic’s
management, such as the presence of operations
staff, operational guidance and adequate budget, as
well as the clinic’s staff’s knowledge regarding how
to properly manage the waste. The survey shows that
only 11.8% of clinics have a dedicated sanitary
manager, while the rest allocate responsibility for
waste management to administrative staff. Only
47.1% of clinics allocate a routine budget for waste
management. Moreover, only 23.5% of clinics havestandard
operatingprocedures
for
waste
management, while a mere 17.6% of clinics havestaff that have been trained in waste management.
These low numbers show the lack of awareness ofclinic management of the importance of medical
waste management. On the other hand, the absenceof routine government control mechanisms toenforce clinics’ compliance with regulations
worsens the situation. For better medical waste

Waste management in clinics
All clinics studied already separate their medical andnon-medical (domestic-like) waste. Medical waste is
further separated into sharps and infectious waste,
which are contained in different containers.
Government-owned community health centres in
Surabaya separate their waste in a similar manner[15].
According to the regulations, medical waste
containers must be equipped with lids or covers
made of a puncture- and leak-resistant material.
They must be lined with yellow plastic bags andmust feature a proper identifying symbol according
to the nature of the waste they contain. The survey
results show that the containers in use are equippedwith hard plastic lids, but only 41.2% of clinics use
yellow containers, and only 29.4% of clinics haveaffixed infectious symbols on containers. The sharps
symbol has been used because sharps are containedin special containers made of thick cardboard.
Figure 1 shows the typical containers used to containmedical waste in clinics.

Fig. 1 Containment of medical waste, sharps andnon-medical waste
The five-day waste generation sampling shows thatthe waste generated by clinics consisted of 21%
sharps, 42% infectious waste, and 37% generalwaste. This composition differs from thecomposition of hospital solid waste in otherdeveloping countries. In Tripoli, Libya, thecomposition of sharps, infectious waste and generalwaste is 4%, 21%, and 74%, respectively. In Dhaka,Bangladesh, the composition is 2.8%, 18.4% and78.7%, respectively, while in Gujranwala, Pakistan,
the composition is 0.87%, 25.8% and 73.8%,
respectively [6]. This discrepancy arises becauseclinics only provide outpatient services; as a result,
the waste generation from patients and staff
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SEE - Nagoya, Japan, Nov.12-14, 2018

management, Surabaya Government needs to makean effort to increase awareness, provide readily
applied guidance or SOPs, and—if needed—
stimulant funding for clinics to manage their medical
waste. Provision of a good waste management
facility as an example for clinics may also be useful.
The correlation between the presence ofdedicated sanitary staff, operational procedures,budget and training, on the one hand, and colourcoded containment, symbol assignment and storage
area provision, on the other, is analysed using
logistic regression.

Based on Table 4, it can be concluded thatbudget and SOP significantly affect theimplementation of colour-coded containers, as
shown by sig. being smaller than α = 15%, whichmeans that H0 is rejected. The resulting simultant
logistic model is expressed as equation (2):g ( x) = −1,99 + 2,10 Routine_budget (1) + 2,32 SOP(1) + e

with a probability function fit expressed by equation(3):

Logistic regression model for colour-coded waste
container
The first step in creating a logistic regression model
is to perform a univariate test model between thedependent variables with each independent variable.
The test on βj will show whether a predictor variable
can feasibly fit into the model. Each feasible
variable will be modelled for the colour-coded
container. The hypothesis is as follows:π ( x) =Table 3. Univariate logistic regression test on
colour-coded container
Independent
B
Wald
Sig.
Variable
Var Dep.: colour-coded container (present vsabsent)Sanitarian (X1)
21.89
0.00
0.99
Routine Budget (X2) 1.76
2.64
0.10*
SOP (X3)
1.91
2.15
0.14*
Training (X4)
1.28
0.91
0.34
Note: α = 15%

Table 5. Univariate logistic regression test on
symbol assignment on waste container
Independent
B
Wald
Sig.
Variable
Var Dep.: symbol assignment (vs absent)
Sanitarian (X1)
1.01 0.44
0.51
Routine Budget (X2) 2.08 2.66
0.10*
SOP (X3)
2.80 4.08
0.04*
Training (X4)
1.99 2.06
0.15
Note : α = 15%

Based on Table 3, when α = 15%, theindependent variables routine budget and SOP
significantly affect the implementation of a colourcoded container for medical waste, showed by a sig.
value of less than α = 15%; therefore, H0 is rejected.
A value of α = 15% was applied because of thisstudy’s small sample size (n = 17), giving a verysmall error tolerance. Subsequently, a parametersignificance test was performed with themultivariate model, as shown in Table 4.

Table 6. Multivariate logistic regression test on
symbol assignment on waste container
Independent
B
Wald
Sig.
Variable
Var Dep.: symbol assignment (vs absent)
Routine Budget (X2)
-0.29
SOP (X3)
1.25
Note : α = 15%; R2 = 0.642

Table 4. Multivariate logistic regression test on
colour-coded container
Independent
B
Wald
Sig.
Variable
Var Dep.: colour coded container (vs absent)
3.36
2.64
2.15

exp(-1.99 + 2.10 Routine_Budget(1) + 2.32 SOP(1) )1 + exp(-1.99 + 2.10 Routine_Budget(1) + 2.32 SOP(1) ) (3)Logistic regression model for symbol assignmenton the waste container
Table 5 shows that the independent variables with asig. of less than α = 15% are budget and SOP, whichmeans that both variables significantly affect symbol
assignment. Subsequent multivariate analysis, as
shown in Table 6, demonstrates that those variables
did not simultaneously affect the implementation ofsymbol assignment on the waste container, as
indicated by the sig. value exceeding α = 15%.
Therefore, for this model, only a univariate model
results; we were unable to produce simultaneous
probability using a multivariate model.

H0 : βj = 0 (no partial effect)
H1 : βj ≠ 0, (has partial effect)
where j = 1, 2, 3, 4

Constant-1.99
Routine Budget (X2) 2.10
SOP (X3)
2.32
Note: α = 15%; R2 = 0.387

(2)

0.15
1.04

0.70
0.31

Logistic regression model for waste storage area
The third model generated is a logistic regression
with waste storage area as the dependent variable.
Table 7 shows that the independent variables with asig. of less than α = 15% are SOP and training. Thismeans that both of these variables significantly
affect whether clinics provide storage for their

0.07*
0.10*
0.14*

898

SEE - Nagoya, Japan, Nov.12-14, 2018

medical waste or not.

and 37% general waste. Waste generation survey
results show that medical waste generation was
0.070 kg/patient/day, and non-medical was 0.040
kg/patient/day.
The segregation of solid waste into nonhazardous and hazardous categories is being
undertaken by all clinics. Nevertheless, waste
containment is not compliant with the regulations
governing the proper management of hazardous
medical waste. Clinics subcontract the treatment of
their medical waste to third parties; therefore, theyrequire temporary storage for their waste prior to its
transportation to treatment facilities. Not all clinics
have an appropriate storage area. Moreover, not allclinic operators have special sanitary staff, routine
budgets, SOPs, and training for their staff.
The performance of a logistic regression
analysis demonstrated that the factors thatsignificantly affect the implementation of colourcoded waste containers in clinics are the presence ofa routine budget and SOPs for medical waste
management. A multivariate logistic analysis
modelling the assignment of the symbol on waste
containers yielded no significant variable. Thus, themodel is based only on a univariate analysis. As forappropriate waste storage areas, the most significant
factor affecting their presence is the waste
management training provided to the clinic’s staff.
This results show that assistance and supervision
to clinics by Ministry of Health as the one who issue
the operational permit must be improved. This is toensure that the solid waste generated does not harm
environment and health. Future research need to be
conducted to further study the routine budget
provided by clinics, as well as how good the staffs incharge knowledge of medical waste management.

Table 7. Univariate logistic regression test on waste
storage area
Independent
B
Wald
Sig.
Variable
Var Dep.: storage area (vs absent)
Sanitarian (X1)
-0.69
1.60
0.21
Routine Budget (X2) -0.69
0.96
0.33
SOP (X3)
-1.20
3.34
0.07*
Training (X4)
-0.92
2.39
0.12*
Note : α = 15%
The subsequent multivariate logistic regression
test (Table 8) on independent variables found tohave an effect in the univariate modelling (X3 andX4) resulted in the emergence of one significant
independent variable: training. The sig. of variable
X4 which is staff training, is less than α = 15%; thus,
H0 is rejected. Therefore, the only variable that has asignificant effect on the clinic’s provision of a waste
storage area is whether or not any training isprovided for their staff. The resulting model isexpressed as equation (4):g ( x) = −1,204 Training (1) + e(4)with the probability function expressed as equation(5):
π ( x) =exp(−1,204 Training (1) )1 + exp(−1,204 Training (1) )(5)

Table 8. Multivariate logistic regression test on
waste storage area
Independent
B
Wald
Sig.
Variable
Var Dep.: storage area ( vs absent)
SOP (X3)
21.61 0.00
0.99
Training (X4)
-1.20
3.34
0.07*
Note : α = 15%; R2 = 0.642

REFERENCES[1] Chartier, Y., Emmanuel, J., Pieper, U.,
Rushbrook, P., Stringer, R., Townend, W.,
Wilburn, S., Zghondi, R., Safe management ofwastes from health-care activities, World HealthOrganization, 2014, pp. 3-21.
[2] El-Salam, M.M. A, Hospital waste managementin El-Beheira Governorate, Egypt, Journal
Environmental Management, Volume 91, Issue
3, 2010, pp. 618–629.
[3] Al-Khatib, I.A., Sato, C., Solid health carewaste management status at health care centersin the West Bank-Palestinian Territory, Waste
Management, Volume 29, Issue 8, 2009, pp.
2398–403.
[4] Coker, A., Sangodoyin, A., Sridhar, M., Booth,C., Olomolaiye, P., Hammond, F., Medical
waste management in Ibadan, Nigeria: obstacles
and prospects, Waste Management, Volume 29,
Issue 2, 2009, pp. 804–11.

The R2 of the model was 57.2% indicating that
two independent variables, SOP and trianing, canpartially explain Y3 variable which is medical waste
storage. While the remaining 42.8% is described byother variables outside the model.
Based on the probability function developed,
clinics that arrange medical waste training (X4 = 1)
has the probability to provide medical waste storageof 0.230.
CONCLUSION
This study successfully obtained data on thegeneration and composition of solid waste fromclinics in Surabaya. Composition of waste fromm
clinics comprised of 21% sharps, 42% infectious,
899

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[5] Liu, H.C., You, J.X., Lu, C., Shan, M.M.,
Application of interval 2-tuple linguistic
MULTIMOORA method for health-care waste
treatment technology evaluation and selection,
Waste Management, Volume 34, Issue 11,2014, pp 2355–2364.
[6] Ali, M., Wang, W., Chaudhry. N., Geng, Y.,
Hospital Waste Management in Developing
Countries: A Mini Review, Waste Management
Research, Volume 35, Issue 6, 2017, pp.1-12[7] Ministry of Environment and Forestry
Indonesia, No. 56 The Year 2015, Technical
Procedures and Requirements Management ofHazardous and Toxic Waste Material from
Healt Care Service Facilities.
[8] Irianti, S., Heart, S, Prasetyoputra, P.,
Determinant of Hospital Waste Management inIndonesia: Focusing on the importance ofSegregation at Souerce and Color Coded
Collection System, Journal of Applied Sciencein Environmental Sanitation, Volume 8, Issue 2,
2013, pp. 135-144.
[9] Chaerul, M., Tanaka, M., Shekdar, A.V., A
system dynamics approach for hospital waste
management, Waste Management, Volume 8,
Issue 2, 2008, pp. 442–449.

[10] Taghipour,H.,
Mosaferi,M.,
2009.
Characterization of medical waste from
hospitals in Tabriz, Iran, Science Total
Environment, Issue 407, 2009, pp. 1527–1535.
[11] Zhang, H.J., Zhang, Y.H., Wang, Y., Yang,
Y.H., Zhang, J., Wang, Y.L., Wang, J.L., 2013.
Investigation of medical waste management in
Gansu Province, China, Waste Management &Research, Volume 31, Issue 6, 2013, pp. 655–
659.
[12] Agresti, A. An Introduction to Categorical Data
Analysis, John Wiley and Son, Second Edition,
2007, pp. 99-121.
[13] Wilujeng, S., Damanhuri, E., Distribution
Pattern of Solid Health Care Waste in Surabaya,
Conference Proceedings, in Proceeding
International Seminar on Environmental Healthand Sustainable Tourism, Udayana University,
Bali Indonesia, 2016, pp.242-254.
[14] Wilujeng, S., Damanhuri, E., Chaerul, M.,
Management of Solid Waste from Community
Health care Facility in Surabaya City,
Conference Proceedings, in Proceeding
International Conference on Green Agro
Industri
andBioeconomy,
Universitas
Brawijaya, Malang Indonesia, 2017, pp.115119.

900

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PUBLIC HEARING WITHIN THE ENVIRONMENTAL AND HEALTH
IMPACT ASSESSMENT SYSTEM: A CASE STUDY FORM THAILAND
Chutarat Chompunth
National Institute of Development Administration, THAILAND

ABSTRACTThe integration of public participation in Environmental and Health Impact Assessment (EHIA) isvery significant in terms of its implication for sound decision-making and the sustainability of development
activities. In this regard, the Thai EHIA system provides for a participation of stakeholders in an implementationof mega development projects. This is carried out through a number of techniques, particularly the holding of
public hearings. In public hearings within the Thai EHIA context, shareholders are brought together in a forum toexpress their ideas and offer recommendations on a proposed project in order to guidance the decision-making
process. Frequently, this forum leads to violent conflict among stakeholders. This study is aimed to state theimportance of public participation in the Thai EHIA system and to evaluate the current practice of public hearing
in development of a coal-fired power station. The case study, the Krabi coal-fired power plant project waspremeditated and examined. The study revealed that the requirements for public hearing in the EHIA system havebeen promoted remarkably by both the 2007 and 2017 Constitutions. It concludes that public participation, in formof public hearing, in the EHIA process is essential and could bring gigantic benefits to all stakeholders including
project owner, local communities, project proponent, and the nation as a whole. Thus, Thai citizens request greater
participation in the decision-making processes concerning controversial matters. Where public participation isdisregarded, environmental conflicts and difficulties may be created for project development execution andsustainability.
Keywords: public hearing, public participation, environmental and health impact assessment, stakeholders

government formulated a new Enhancement andConservation of National Environmental Quality Act
B.E. 2535 (1992) [3].
The EIA is a systematic process which aims topredict, determine, and evaluate the significant
environmental impacts of development projects inadvance. It is also regarded as a useful analyticalmechanism by providing this useful information to
the decision maker to manage the decision process
more systematically, timely and effectively [4].
Currently, in Thailand there are both the EIA andEHIA system, which concerns health impact,
processes are compulsory system of procedural
control mechanisms under the NEQA 1992 and the2017 Thai Constitution. Regarding the NEQA 1992,
the EIA procedures are described in sections 46 to 48
that the projects or activities that might causesignificant impacts to the environment must have anassessment of environmental impacts before theprojects or activities are implemented. The projects oractivities that are obligated by law to obtain
permission prior to construction or operation are
required to prepare an EIA report and submit it to thepermitting authority [[2], [3]].
In practice, the Thai EIA/EHIA process is largely
controlled by the government. An expert review
committee has been established for the EIA/EHIA
system. The expert review committee comprises ofexpert members who are qualified and specialized in

INTRODUCTION
The Thailand was one of the very first countries inSoutheast Asia that implemented EIA [1]. The first
institutionalization of the EIA process in Thailand
began with the proclamation of the ENQA 1975.
Section 17 of this act authorized the ministers, withthe approval of the NEB, to specify notification for
the type and size of projects or activities requiring
EIA. In July 1981, the first notification specifying
types and sizes of projects and activities requiring an
EIA was announced. This notification applied toeither public or private projects. In the early stages of
implementation, the contribution from political andeconomic institutions to the promotion ofenvironmental impact assessment was low, andenvironmental institutions usually had less power
than economic agencies. The ONEB was perceived as
not having sufficient authority. The EIA process was
also criticized as being a closed process, it was
primarily conducted by the project proponent, andwas not available for the public unless the project
proponent was willing to involve them [2].
Until present, a mass of environmental problems
and conflicts has occurred throughout Thailand.
These controversies have dramatically increased
public awareness of the deteriorating state of theenvironment and also the lack of an approach to deal
with the country’s natural resources. Thus, the901

SEE - Nagoya, Japan, Nov.12-14, 2018various fields of related disciplines and the legal
authority competent to grant permission for the
project including: the secretariat of the OEPP as achair, the head of the licensing agency, the head ofinvolved governmental agencies, a maximum ofseven environmental experts who are appointed by
the ONEB, and an OEPP officer as a secretary [5].
Between the years 2007-2017, more than 100
EHIA were conducted in Thailand and all of thesewere the subject of public hearing. This paper
attempts to explore where many development
projects were subjected to public hearings, what are
the objectives and purposes, form and outcomes ofpublic hearings. In practically, the problems
concerning to the public hearing practice areinvestigate in order to find out alternative approach to
improve the practice.

cannot stop the unrest, and was always too late tosolve conflicts [6]. The important cases of public
hearings in Thailand, which were perceived as
unsuccessful, include the Yadana gas pipeline project,
the Kao Hin Son Coal-fired power plant project and,particularly, the Krabi power plant project [3].
The principles and processes for conducting
public hearings are still unsystematic andcomplicated [[5], [6]]. There must be publicity
processes concerning this activity. All basic
information, such as, the appointment of committees,
topics for the public hearing, summary of proposals
by all related organizations, time of activity andregistration period, venues for registration, how toprovide information to the committees, and thecharacteristics of people that can register to join theactivity has to be officially announced and widely
notified to ensure that all related persons and parties
are informed. Moreover, during the hearing process
all relevant information, evidence and opinions fromstakeholders and interested parties must be heard andbe open to the public in order to avoid any influenceor bias [7].
Because of these weak points of the directive,
some have argued that the public hearing regulation
should be reviewed, and reenacted as a parliamentaryact.

PUBLIC HEARING PRACTICE IN THE EHIASYSTEM IN THAILAND
Public hearing is a form of participation in whichstakeholders and proponents are brought together in aforum to express their opinions and offer suggestions
on a proposed undertaking in order to influence thedecision-making process. The purpose of this activity
is to collect useful information from stakeholders forgovernment decision-making so that a decision can bemade on the foundation of objective facts. Moreover,
it is a significant provision prescribing the detailed
procedure on how the citizen can be involved in an
administrative decision-making process. Thai law
provides that citizens have the right to object to a
project, and to participate in the hearing to articulate
their views and evidence [5]. Since 1992, many
public hearing activities have been arranged; many ofthem relating to huge development projects withpotential effects on the quality of people's lives andthe environment. In practice, however, the procedures
have still been obstructed by some difficulties, forexample, an unclear authority of the administrators;
limitations on the project that can have a public
hearing; and, unsystematic procedures [[2], [5]]. In
practice, most public hearings last for a period of
about three to five hours and are well attended. In aparticular case, as many as 100-500 people attended
the meeting. These included community’s leaders,
community representatives, government officials, theproject proponents and the project opponents.
In Thai experience, many public hearings werecarried out, and most of these hearings were carriedout because of strong requests and pressure from thepublic. They did not take place on the initiative of thegovernment. In addition, they were organized after
the decisions about the development project or
activities were already made. As a result, the public
hearing in Thailand is perceived as a process thatRESEARCH METHODOLOGY
Qualitative research was conducted utilizing acase study strategy of inquiry. A case study
methodology is chosen as a key strategy to explain
and conduct an in-depth study of a public hearing
practice.
The data collection methods included semistructured interviews, non-participant observation,and documental review. A total of 29 semi-structured
interviews were conducted with 17 community
members, including community leaders and menbers,
who participated in public hearing of the case study
and 12 government officials, NGOs and EHIA
practitioners who were key players in the public
participation processes. Community participants
were sought out using a snowball sampling approachstarting with community leaders identified in EHIA
reports and meetings with practitioners. Theinterviews took place in the participants' hometown
and workplace.
All interviews and field notes were transcribed andcoded into thematic categories. The data collected isoften represented by quotes in the text below. These
have been selected to highlight the intent and voice ofour participants.
RESULT AND DISCUSSION
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SEE - Nagoya, Japan, Nov.12-14, 2018•
BACKGROUD INFORMATION OF THE CASESTUDY: The Krabi coal-fired power plant
The Krabi coal-fired power plant project is one ofa large-scale project in the south of Thailand whichhaving significant environmental problems, inparticular air pollutions. The project is located in
Krabi province. According to the 2007 Thai
Constitution, power plant projects that have a
production capacity exceeding 100 megawatts perday, must conduct and Environmental and HealthImpact Assessment (EHIA) study and submit this
EHIA report before getting an approval from the
Authority. Thus, the Krabi power plant project was
required by law to conduct an EHIA study.
Accordingly, the Krabi coal-fired power plant issuitable to be examined how public participation
process through public hearing practice in managing
environmental pollution control did not succeed since
the project is having conflicts with a high level ofcontroversy among stakeholders.

•

to offer the affected and interested parties, aswell as other stakeholders, the opportunity to
express their opinions on any issues consideredoutstanding; andto promote effective public participation andensure confidence in the Thai EHIA process aswell as support for the proposed undertaking.

RESEARCH FININGS
Noticeably, public participation techniques
employed in this case study were varied and could
range from traditional public participation methods
on an education and information provision level, to amore interactive approach such as public meetings.
However, the majority of participation techniques
were traditional. Thus, the public did not have more
opportunities to discuss the issue and there was no
appropriate means to manipulate the decision. Many
affected villagers were frustrated with theparticipation process and their government because
they felt that the process was not a participation
process in which they could make any change to thedecision or create appropriate dialogue. It seemed tobe just a public relations activity to convince them toaccept the project already approved. Clearly, in thiscase, traditional participation techniques had been
unsuccessful in developing collaboration between
stakeholders.

RATIONALS FOR PUBLIC HEARINGS IN
THAILAND
Typically, the Thai EHIA Procedure requires the
project developer to hold a public hearing as public
participation practice in EHIA system where:• the expected environmental and health impacts
are considered extensive and far reaching:• there is great adverse public reaction to a
proposal; and• there will be relocation or dislocation ofcommunities.
In practice, the Thai regulations have accounted
for the holding of public hearings on 35 types ofdevelopment projects for EIA and on 12 types ofmage-development projects. This can be attributed to
the need to relocate or resettle affected communities
as well as the strong public concerns expressed about
the overall impacts of these projects.

This tallies with other finding [8] that traditional
methods, in particular public hearings or meetings,
was always held in a fixed place or location and at a
fixed time, often during office hours. Thus, many
people were not available to attend. These activities
could be dominated by minority groups and are often
difficult for the lay people to understand since thewhole process often involves highly technicalinformation. Importantly, these meetings could leadto confrontation among stakeholders.
Although there were many arguments expressing
dissatisfaction with the implementation ofparticipation methods, many participants enjoyed thedeveloper’s activities such as seminars, site tour andsports activities. One local villager highlighted that:OBJECTIVES AND PURPOSE OF PUBLICHEARING
The main objectives for organizing these public
hearings as part of the EHIA review process are:• to provide a forum for the proponent to informthe entire community of the outcome of theEnvironmental Assessment of proposed
undertakings;• to verify the accuracy of the EHIA findings inrelation to the situation on the ground;• to confirm that all the affected parties andstakeholders have been adequately consulted
and have been part of the various decisionmaking processes;“I liked the multiple types of their participation
approaches. They provided more benefits to us. I liketheir creative activities in particular the social
activity. They made people share ideas, do more
activities together. It benefits the whole society.
Whenever we wanted to make input or learn more
information about the power plant, we had a variety
of ways to do that. They set up an open exhibition attheir site for more than a month, and they also
provided staff to answer our questions. They invited
students and teachers to our communities to run theirseminars. They did give us the information we wanted
903

SEE - Nagoya, Japan, Nov.12-14, 2018

to know” (Villager 6).

mechanism because it is a method for all stakeholders
and interested parties to meet with one another anddiscuss together to find out agreements anddisagreements. In the public hearing, there were agreat number of the representatives from different
stakeholders for instance; central government
officers, local government officers, the developers,
and local villagers. Different opinions were presented
appropriately. I thought that was a pretty good mix ofopinions. Although this vehicle did not work for thiscase, I think this was a good approach that had tohappen” (Local government officer 4).

Frequently, traditional public participation
techniques have been criticized as ineffective
approaches to engage the public, Daniels and Walker[9] pointed out that, although traditional methods
were being widely applied to provide the public with
an opportunity to communicate their concerns withthe authority and receiving feedback, they focused
one-way transmission of information from thedeveloper or the authority to the public and the public
had less opportunity to input into an early stage of thedecision-making
processes.
Importantly,ameaningful public input is not guaranteed. The
citizens do not know how their input will be used andwhether it will influence the decision.

On the other hand, many participants felt that the
public hearing was not effectively arranged and,
importantly, caused more conflicts. One academic
researcher pointed out one weak point associated withlarge public hearings whereby too many participantsin the hearing made it impractical for the organizers
to allow every participant to present their ideas, so theorganizers could not accurately ascertain the
representative public views (Academic 1).
Obviously, in this case, the public hearing seemed not
to be an effective technique to engage the public, or
to solve the conflict among stakeholders.

Although, there were many participation
activities, in particular meetings or seminars,
conducted by both sides [7], only supporters for eachgroup attended these events. The project supporters
joined in the forums conducted by the developers,
while the project opponents always refused toparticipate in the activities organized by the project
proponent or even the government. At the same time
the local villagers set up their own activities to
educate themselves on the issues. They conducted
regular meetings in their location every week andmost of them were supplied with information byNGOs and academics. One villager stated that: “Infact, we wanted to discuss or debate with the project
owners; but when we set up the seminar with NGOsor other academics, they did not come. We wanted
them to be in the forum to clarify our enquiries”(Villager 11). Another villager argued that:“Basically, the public hearing aimed to bringeverybody’s input into one forum. However, you
could have too many difficulties if the participants did
not sit down together, discuss based on reason, listen
to other voices, and try to accept the views of
everybody. Many different ideas were raised. How tomanage this complex issue was still problematic.
Moreover, how to make everyone pleased and accept
the forum was more difficult” (Academic 1).

“Although I did join in some of their programs,
most of the participants were their supporters. The
developers invited only their supporters. Most of the
impacted villagers did not participate. We did not
believe what they tried to convince us. Their
information was not correct” (Villager 4).

A public hearing is a classic example of aparticipation technique grounded in a traditional
approach, and perhaps it is the oldest and most widelyused technique for citizens to participate ingovernmental decision making at the local, national,
and international level. Frequently, the public hearingis the only main approach in the public participation
program. In the Thai experience, a public hearing was
a common technique which the government usuallyadopted to solve conflict problems in construction
projects in a non-violent way [10]. However, it was
clear that frequently this technique was not successful
in solving the conflict in Thai society [11].

In the Krabi case, at the beginning of the conflict
escalation process, the protestors called for a public
hearing to make their voice heard. However, thegovernment paid no attention to their requests.
Finally, the public hearing was conducted lather but
it could not solve the problem since it was too late andthe conflict was too complicated to solve. Although
the public hearing was not the only techniqueemployed to solve the problem, it seemed to be themost recognized mechanism to engage the public andsolve the conflicts. There were a great number of theresearch interviewees who experienced this event.
Some of them gave their perspectives on the positiveside of the public hearing as follows.

On the equality issue, a public hearing hardly everallows people to participate equally in the processwith government officers and experts. This isbecause, normally, in the hearing, the authorities
define the agenda, set up the format, and provide theinformation and analytical resources. Petts andHalvorsen [12] stated that the structure of the public
hearing process could lead to expert bias and by
nature of the public hearing, participants may not“From my point of view, it was a useful
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SEE - Nagoya, Japan, Nov.12-14, 2018

truly the representatives of the public. In the public
hearing of the Krabi power plant, a number ofvillagers claimed that the hearing committees were
not neutral enough since some of them worked for,and had a close relationship with, the project
proponent. Many participants agreed that public
hearing committees should be neutral and allocate
time fairly and give an opportunity for all participants
to express their ideas, both negative and positives(Academic 1 and Local leader 2).

the Minister of Environment, Science andTechnology, the appropriate sector Minister, theappropriate District Authority, and relevant
government departments.
It is important to the government that the findingsof public hearings have had considerable influence on
the EHIA study. In some cases certain aspects of the
project proposal had to be altered, additional
mitigation proposals and commitments were madeand final decision on projects delayed until
substantive issues were addressed. For instance in thiscase study, the public hearing showed that an
important group was not represented on thecommunity and therefore were creating problems forthe power plant in its concerns.

Moreover, more than two-thirds of theparticipants from local villages claimed that the seatsand the presentation time were distributed unequally
between the participants. They explained that almost
all of the participants in the hearing event were
supporters. This made the villagers who wanted to be
involved in the process feel that the hearing process
was unequal and unfair. Thus, they boycotted theforum. The protestors sent only their representatives
into the hearing. As one villager explained:

CONCLUSION
Evidently, in the Thai EHIA’s system, public
hearings are mandated by law; however, they can leadto troublesome rather than productive participation. It
allows not only for the diffusion of antagonism, butalso the assuaging of public opinions. This isespecially the case if hearings are held late in theplanning process, and there were no, or few, previous
attempts to engage the public. As clearly presented inthis case study, when the public hearing was held too
late, it could not resolve conflict among stakeholders,
and the situation became more controversial. This
statement was supported by one key informant fromeducational section that:“It was unacceptable from the beginning of thehearing process. The stage could carry less than twohundred participants. The number of impacted
villagers who wanted to participate in the forum wasvast and they could not all be registered. Only themembers of central and local governments, theproject owner, academia, and the villagers who
supported the project were booked on the stage. On
that day, we went there but we were excluded. We
could not get in. We were all around the hall. The
seats were limited and not enough for us.
Furthermore, the process was not neutral, we did notwant join them. We sent our representatives to present
our concerns” (Local leader 5).

“In the Thai’s experience, we hardly found a
successful public hearing. Indeed, Thai citizen
ordinarily preferred to avoid controversy. However,in this case when people’s voices were not heard, they
started to oppose the project. Public hearings could
easily lead to confrontation among stakeholders.
Importantly, the lay people were more likely not tolisten to others’ concerns. Confrontation might workin a strong democratic country but not in Thailand.
We were different. In my opinion, the public hearing
was not suitable with the Thai context”.

One leader of the protestors, who joined in the
hearing process, stated that there were limitations ofpresentation time for the protestors in the hearing andthat the participants from the supporters and thedeveloper had more chances to speak. She said that:“We wanted to express our perspectives, our concerns
but we had very limited time. The representatives
from the project owners and their supporters spent a
lot of time talking. They had more opportunities to
speak. I thought the process was offensive” (Local
leader 2).

In summary, it could be argued that development
projects, either initiated by the government or private
sector which may cause significant impacts to theenvironment, must conduct a public participation
process in form of public hearing in Thailand. In
accordance with this finding, as stated by many
academic and researchers [[7], [12], [13]], although
the public hearing is a forum for discussions, it isoften superficial and causes conflict over the
exploration of the common ground. Evidently, had
public hearings has earlier distinguished as a weakmechanism for public involvement in many context.
It could be said that the hearing could intimidate and

OUTCOMES OF PUBLIC HEARINGSAt the end of any public hearing the panel submits
a report making its findings and recommendations to
the decision-maker or the authorities as an input to the
EIA/EHIA review process. The authorities, to make a
final decision, will determine all these concerns andrecommendations. When the final decision is madeon the project EIS, the Agency notifies the proponent,
905

SEE - Nagoya, Japan, Nov.12-14, 2018

Planning Power Plant Project in Thailand,
Thammasat International 9(1), pp. 67-73, 2004.
[7] Chutarat Chompunth (2017). “Role of Public
ParticipationinEnvironmental
ImpactAssessment in Thailand.” International Journalof GEOMATE. Vol. 12(33): 109-113.
[8] Vantanen, A. and M. Marttunen, Public
Involvement in Multi-Objective Water Level
Regulation Development Projects-Evaluating theApplicability of Public Involvement Methods,
Environmental Impact Assessment Review,25(3), pp. 281-304, 2005.
[9] Daniels, S. E. and G. B. Walker (2001). Working
Through
Environmental
Conflict:
The
Collaborative Learning Approach. Westport,
Praeger Publishers.
[10] Petts, J. (2003). "Barriers to Deliberative
Participation in EIA." Journal of Environmental
Assessment Policy and Management 5(3): 269293.
[11] Gunes, Y. and A. A. Coskun (2005). "Legal
Structureof
PublicParticipationinEnvironmental Issues in Turkey." Journal ofEnvironmental
Assessment
PolicyandManagement 7(3): 543-568.
[12] Halvorsen, K. E. (2001). "Assessing Public
Participation
Techniquesfor
Comfort,Convenience, Satisfaction, and Deliberation."
Environmental Management 28(2): 179-186.

be prone to adversarial confrontation. In many
development project in Thailand, a public hearing is
not the most appropriate means of engaging the
public. Thus, there is a keen need to find out the mostappropriate participation technique to engage thepublic in the decision-making process. The key lessonis that public participation in EHIA study is essential
and may lead to substantial benefits for both the
project’s proponent and affected community. Where
it is ignored it leads to conflicts and problems forevery
development
project
implementation,
acceptability and sustainability.

REFERENCES[1] Chesoh, S., Environmental Impact Assessmentof Power Development Project: Lessons fromThailand Experiences, Asian Social Science,
7(9), pp 119-123, 2011.
[2] Chompunth, C., Public Participation in
Environmental Management in Constitutionaland Legal Frameworks, American Journal ofApplied Science, 10 (1), pp. 73-80, 2013.
[3] Ogunlana, S. O., T. Yotsinsak and S. Yisa, An
Assessment of People's Satisfaction with the
Public Hearing on the Yadana Natural Gas
Pipeline Project, Environmental Monitoring andAssessment, 72(2), pp. 207-225, 2001.
[4] Creighton, J. L., The Public Participation
Handbook: Making Better Decisions ThroughCitizen Involvement, San Francisco, Jossey
Bass, 2005.
[5] Manowong, E. and S. O. Ogunlana (2006).
"Public Hearings in Thailand's Infrastructure
Projects: Effective Participations?" Engineering,
Construction and Architectural Management
13(4): 343-363.
[6] Chaisomphob, T., J. Sanguanmanasak and K.
Swangjang, Role of Public Participation in[13] Almer, H. L. and T. M. Koontz (2004). "Public
Hearings for EIAs in Post-Communist Bulgaria:
Do They Work?" Environmental Impact
Assessment Review 24(5): 473-493,

906

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

SEMI–ARTIFICIAL SLUDGE PRODUCTION BY UTILIZINGINORGANIC MATTERS OBTAINED FROM NATURAL "HEDORO"
Hirosuke Hirano1,*, Davin H. E. Setiamarga2,3,4
1

Department of Civil Engineering, National Institute of Technology, Wakayama College, Japan
Department of Applied Chemistry and Biochemistry, National Institute of Technology, Wakayama College,Japan
3
Department of Ecosystem Engineering, Faculty of Advance Engineering, National Institute of Technology,
Wakayama College, Japan
4
The University Museum, The University of Tokyo, Japan* Corresponding Authors; email: hirano@wakayama-nct.ac.jp

2

ABSTRACT
Studies focusing on the utilization of physical and chemical properties of sludge have been hampered by thedifficulties of sample preservation while maintaining the desirable original physical and chemical properties.
Meanwhile, re-obtaining samples with similar characteristics from nature is almost impossible. Previously, we
reported the creation of an artificial sludge mimicking the general properties of the natural sea floor sludge of the
Funabashi in Chiba. However, although useful for recreating sludge with high organic content (Funabashi =23.61%), the method was not useful for recreating sludge with low organic content (e.g. Hidaka in Wakayama =5.58%), because one of the ingredients, zeolite, has a high organic content (7.79%). In this study, we focused on
the creation of a semi-artificial sludge using inorganic matters obtained from natural sea sludge. Sludge from
Hidaka Port was cryopreserved in 4ºC, 0ºC, and –20ºC for a week, and changes in properties such as watercontent, of the 0ºC and –20ºC samples, were confirmed. We then recollected sludge samples from Hidaka, andremoved their organic content by burning at 600ºC. Artificial organic materials were then added to the obtained
inorganic matters, following the method described in our previous study. The resulting semi-artificial sludge
mimics the properties of original. Thus in this study, we are successful in adjusting our previously proposed
method, by recreating low organic content sludge by utilizing inorganic matters collected from natural samples.
Future studies involving changing production and preservation conditions will be conducted to increase therobustness of our result reported here.
Keywords: Artificial Sludge, Sea Sludge, Inorganic Content, Cryopreservation, Hidaka Port

hydrogensulfidebyoxygen[2],
anddecontamination by decomposing organic matter [3].
However, in such studies, it is crucial to obtainand to collect hedoro every time for the clean sludge
research, because hedoro is only available in nature.
However, the condition of the natural environment(e.g. weather and seasonal changes) during sampling
affects the characteristics of the hedoro,.It is
impossible to set all environmental conditions to be
the same for all samples. For example, we haveshown that the organic contents in Hidaka Port inWakayama in Japan changes each month, [4].
We proposed the production of an artificial
sludge useful for research requiring sludge with its
early values constant. By hedoro’s chemical analysis,
we found that we were able to produce artificial
sludge by using dry yeast as the source of organic
matter, zeolite for inorganic matter, and sodium
sulfide nonahydrate (Na2S ・ 9H2O) to recreate
sulfide content. In this experiment, we succeeded toreproduce hedoro collected from the Funabashi port

1. INTRODUCTION
1.1 Report of our previous studies
Hedoro, which is a Japanese word for sludge
collected from aquatic environment floor, is known
to bring unwanted environmental effect in closed
water environment (e.g. is lake, pond, and harbor).
In a previous study, hedoro is composed of inorganic
matter such as mud or sand, organic matter fromnutrient salt or protein, and sulfide as the cause of
the “rotten egg” smell [1]. Hedoro is also known tobring malicious environmental effects such as
eutrophication causing bacterial and otherorganismic blooms, bad smell caused by hydrogensulfide, and captured radioactive cesium.
Accordingly, in order to purify water environment,
methods have been devised to clean the hedoro fromthe aquatic environment, such as decontamination.
Some decontamination methods have been reported
by previou studies, for example decomposing
907

SEE - Nagoya, Japan, Nov.12-14, 2018

To test the possibility that zeolite capture organic
matter from the air, we then burned the zeolite in
600 ºC to get rid all of possibly contained organic
matter (the incinerating temperature of organic
matter), and put the obtained sample in the open air
in the lab. The organic content was then measured
by TG once a day, and we found the organic content
6.91% as the maximum value after putting thesamples for four days (Fig. 2). From this result, we
can conclude that zeolite has the possibility to obtainorganic matter during preservation. Accordingly,
when such preserved zeolite was used to produce anartificial sludge, it is impossible to reproduce anartificial sludge with the organic content lower thanthe organic content of the zeolite itself.

in Chiba, Japan [5]. We also showed that dry yeast,as the source of organic matter in artificial sludge,
has the ability of capturing cesium, and thus similar
to natural hedoro [6] [7].
1.2 Artificial sludge weaknesses
During our previous experiment to produce theartificial sludge, we first made the “artificial sludgebase” by mixing dry yeast and Na2S・9H2O. Next,
we added zeolite with the sludge base: basecomposition equals to 0:100, 41.7:58.3, and83.3:16.7. We calculated the calibration curve of theheat-weight loss analysis (TG; Thermo-Gravity
analysis) (Fig. 1) by primary equation and quadratic
equation, and use average value as best addition rateof the sludge base to produce the artificial sludge.
However, when we measure the 0:100 sample,
despite the lack of organic content addition, we
found out that it has the organic contents of 7.79%.
The main ingredient zeolite, being made of only
inorganic matter (silicon and aluminium), is
supposed to content no organic material. We
considered that the ingredient zeolite probably
captured microorganisms and water in the air, andthus obtained its organic content.

2. CHANGES OF HEDORO PROPERTIESDURING STORAGE
In this study, we proposed one way of long-term
storage of natural hedoro, because it is difficult toreproduce low organic content by our present
artificial sludge. Some have suggested to store thesamples at low temperature: freezing at –20 ºC to –18 ºC, cold storage at 0 ºC, and refrigeration at 2 ºC
to 6 ºC. For this experiment, we put our samples in afreezer for the –20 ºC treatment, ice pack for the 0ºC treatment (Fig. 3), and in a fridge for the 2 ºC–
6ºC treatment. Change of the hedoro samples’organic contents and moisture contents were
measured daily after one week. Samples werecollected in Hidaka port in 22th February 2018 and30th March 2018. The organic contents of thesamples were 2.00% in February and 1.16% in
March.
We measured the organic contents twice for eachsample. Both measurement results showed only
slight differences as shown in Table 1 (-0.01%/day
to 0.00%/day). We also checked the possibility ofthe same slight differences in other hedoro samples
collected from a channel in Gobo city at Wakayama,.
The organic contents of the channel’s hedoro
samples were 16.40% and 4.69%. Interestingly, ourorganic content measurement showed that both

Organic contents [%]

70

60
50
40
30
20
10
0
0

20
40
60
Added value of origin [%]80

Fig. 1: Calibration curve in artificial sludge

Organic contents [%]

8
6
4
2
0
0

1

2
Time [day]3

4
Fig. 3: Ice petri dishFig. 2: Change of zeolite by time series
908

SEE - Nagoya, Japan, Nov.12-14, 2018

samples had an organic content increase of +1.93%
to +2.30% daily (Table 2). Standard deviation, it was
shown results as Table 3. Values were under 3.8%(n=3) in all, so we understood that has no problem inpresent results of organic contents. On the otherhands, in our present study, we are unable topinpoint with confidence the reason of the daily
increase, because the samples were put in airtightziplock bags to prevent outside contamination. Somepossibilities could be related to temperature changes[8] - [13] and possible microbial contaminations andproliferations [4] [14] [15].
Based on this observation, although refrigeration(2 ºC to 6 ºC) seemed to be probably the better way
of storage (as shown by the slight increase; Table 2),
it still could not prevent the changes of organic
content.
In the previous sections, we have discussed that it isalmost impossible to store natural hedoro with its
original physical and chemical conditions kept
unchanged. The organic content of a hedoro sample
changes, even only days after sample collection. For
example, hedoro in Hidaka port collected in April 30
was measured on the next day to have an organic
content of 12.54%, but after 11 days, the valuechanged to 1.38%, and after 13 days, 1.61%, allsamples kept at room temperature.
We also measured the changes of the moisture
content in the sludge during preservation. We havepreviously mentioned that when a hedoro was frozen,
its moisture content expanded during the ice crystal
formations, causing component materials of hedoro
to be broken. The structure and physical properties
of such samples, when thawed, changed to be likethose of tundra soil thawed samples; materials
became spongy, with increased but leaky moisture
content. We measured the changes of moisture
contents of our samples by TG analysis. First, weheated the samples at 100ºC for five minutes tosterilize possible contaminations. After that, we start
our first measurement, and subsequently repeat
measurements
every
five
minutes,while
continuously heating the samples at 100ºC. Our
samples were the hedoro collected from the Hidaka
port (organic contents: 2.00% and 1.16%), hedoro
from a channel in Gobo City (organic contents:
16.40% and 4.69%), and artificial sludge samples(organic contents: 20.64% and 28.01%). The results
are shown in Fig. 4 to Fig. 9 (●: Refrigeration, ▲:Freezing, □: cold storage in ice).

Table 1: Change of organic contents in storage (1)Time[days]

Organic
contents[%]

Originalorganic
contents[%]

Change
[%]

7

1.75

2.00

-0.25

7

1.38

1.16

0.22

7

1.70

2.00

-0.30

7

1.35

1.16

0.19

7

1.64

2.00

-0.36

7

1.41

1.16

0.25

Changeofaverageby time[%/day]

Way
of
save

0.00

Free
zing

-0.01

-0.01

Save
in
ice
Refri
gera
tion

Table 2: Change of organic contents in storage (2)Time[days]

Organic
contents[%]

Originalorganic
contents[%]

Change
[%]

7

31.09

16.40

14.69

8

24.69

4.69

20.00

7

27.14

16.40

10.75

8

28.83

4.69

24.14

8

21.31

16.40

14.31

8

20.82

4.69

16.62

Changeofaverageby time[%/day]

Way
of
save

2.30

Free
zing

2.28

1.93

Save
in
ice
Refri
gera
tion

Table 3: Results of standard deviation to changeorganic contents in storage
Standard deviationin organic contents
n
Free
Save
Refrigezing
in iceration[%][%][%]Channel’s
hedoro in
Gobo city

3

0.22

0.47

0.32

3

0.21

0.18

0.20

3

1.13

3.73

1.47

3

1.16

1.89

3.46

Moisture content [%]Naturalhedoro in
Hidaka
port

40
30
20
10
0
5

10

15
20
Time [min]25

30

Fig. 4: Change of moisture content in hedoro (1)909SEE - Nagoya, Japan, Nov.12-14, 2018

30
20

20
10
0
5

10

15
20
Time [min]

25

15
20
Time [min]25

30

Fig. 8: Change of moisture content in artificial (1)

10

15
20
Time [min]

25

40

30

Fig. 5: Change of moisture content in hedoro (2)

40

30
20

30
20
10
0
5

10

10

30

Fig. 9: Change of moisture content in artificial (2)

0
5

10

15
20
Time [min]25

Table 4: Significant difference in moisture content
Significant differencen● and ▲ ▲ and □ ● and □30

Fig. 6: Change of moisture content in channels (1)Moisture content [%]

30

10
0
5

Moisture content [%]40

Moisture content [%]Moisture content [%]40

refrigeration; Fig. 7).
Our r esult fo r the ar tificial slud ge wer e
inconclusive (Fig. 8 and 9; organic contents were set
to 20.64% for the first sample, and 28.01%for thesecond sample). This result, however, emphasize thedifficulties of maintaining both the moisture andorganic content of samples during preservations,

Moisture content [%]Our result indicates that for the hedoro collectedfrom Hidaka port, the lowest values of released
moisture content were 2.81% (first sample; organic
content: 2.00%; preservation method: cold storage in
ice; Fig. 4) and 8.28% (second sample; organic
content: 1.16%; preservation method: cold storage in
ice; Fig. 5). For hedoro samples from the Gobo City
channel, the values were 17.51% (first sample;
organic content: 16.40%; preservation method: cold
storage in ice; Fig. 6) and 13.24% (second sample;
organic content: 4.69%; preservation method:

40

Natural3
hedoro (1)p = 0.495

p = 0.498

p = 0.497

30

Natural3
hedoro (2)p = 0.367

p = 0.446

p = 0.421

20

Channel’s
3
hedoro (1)p = 0.498

p = 0.363

p = 0.469

10

Channel’s
3
hedoro (2)p = 0.498

p = 0.498

p = 0.498

Artificial
3
sludge (1)p = 0.498

p = 0.498

p = 0.496

Artificial
3
sludge (2)p = 0.494

p = 0.496

p = 0.496

0
5

10

15
20
Time [min]25

30

Fig. 7: Change of moisture content in channels (2)910

SEE - Nagoya, Japan, Nov.12-14, 2018

contents and moisture content; we thought result of
freezing is standard as 1, and changed values inothers than freezing. Result was Fig. 10, it was
shown relationship. But it was wrong that shown
values under 0, so we regulated two conditions inrelationship; maximum value was nearly 2, andminimum value was over 0. As a result, we guessed
formulas in relation with organic contents (X) andmoisture content (Y) (Fig. 11).

Moisture content[Measured value / Result of save in ice]

regardless of the method utilized, and we can show
this difficulties from results that is no significant
difference (Table 4). Without doubt, such changes
also will affect the physical and chemical propertiesof the samples. The artificial sludge production
method follows our previous report [5].
Then, we considered relation with organic3

Y ≓ 0.0053X3 - 0.3435X2 + 7.0758X - 45.062(13.65 ≤ X < 29.53) (1)2Y ≓ 0.0053X3 - 0.5967X2 + 22.0250X - 265.740(29.53 ≤ X < 45.43) (2)10

Y ≓ 0.0053X3 - 0.8498X2 + 45.0240X - 788.110(45.43 ≤ X < 61.33) (3)-1Y ≓ 0.0053X3 - 1.1030X2 + 76.0730X - 1740.200(61.33 ≤ X < 77.23) (4)

-2
-3
0

10
20
Organic contents [%]30

Y ≓ 0.0053X3 - 1.3561X2 + 115.1700X - 3249.900(77.23 ≤ X < 93.13) (5)Fig. 10: Relation with organic matter and water (1)Moisture content[Measured value / Result of save in ice]

X = 1.7 + 7.95*n2

methods follow our previous report of artificial
sludge [5].
3. SEMI–ARTIFICIAL SLUDGE

1

3.1 The production of semi-artificial sludge using
inorganic matter extracted from natural hedoro
In our present study, inorganic matter from twohedoro samples collected from the Hidaka port
(February 2018 and May 2018) were extracted by
combustion at 600 ºC to completely burn organic
materials from the samples. Then, we made three
types of artificial sludge with differing organic
contents, by using the leftover inorganic mattersfrom the burnt samples. The organic content were
calibrated using the previously mentioned "artificial
sludge base" (= sludge base). The three types ofsamples are as follow: sludge base/natural sludge
inorganic matter = 0/100, 41.7/58.3, and 83.3/16.7.
We then created a calibration curve to analyze theorganic/inorganic ratio. These compositional ratios
enabled us to recreate samples mimicking the natural
hedoro collected in February (organic content =1.30%; Fig. 13), and in May (organic content =1.50%; Fig. 14). Based on or analysis using thehedoro were 3.10% to recreate February sample, andcalibration curve, the best value of sludge basepowder addition/inorganic material from the natural
0.73% for May sample. We were successful infollowing the recipe, with the margin error during
addition between 0.13% – 0.14%.

0
15

30

45
60
75
Organic contents [%]90

Fig. 11: Relation with organic matter and water (2)40
Moisture content [%](n: Constant) (6)

30
20
10
0

10

20
Time [min]30

Fig. 12: Change of moisture contents by times(●:7 days, ▲:15 days, □: 30 days)
911SEE - Nagoya, Japan, Nov.12-14, 2018

method presented here.
However, despite some weaknesses, we weresuccessful in further improving the weaknesses of
our artificial sludge production methods reported
previously [5]. For example, in a previous section(2.1), we mentioned that it was impossible torecreate natural hedoro with low organic contents(less than 6.91%). However with our method
presented here, although future research for
improvement is still needed, we were successful with certain limitations- to recreate low organic
contents hedoro, such as those from the Hidaka port,
and we need to resolve reproducibility, consider
from p value in significant difference (Table 6). As
these results, we understood that higher
reproducibility in first experiment (Table 4) by
0.181 than second experiment (Table 5) by 0.499.
But we couldn’t show p value under 0.05 in thisstudy.

3.2 Results
The resulting semi-artificial hedoro, interestingly,
showed different organic content ratio than what waspredicted by the calibration curve. For the February
sample recreation, the expected organic content was
1.22%, and for May was 1.58%. However, theactual observation value we obtained were 1.31%(Table 4) and 2.86% (Table 5), respectively.
Therefore, the February sample-mimicking semiartifical hedoro had +0.09% than the expected value,
while the May one showed +1.28% than expectedvalue.
The result indicated that we were unable torecreate the May sample, because the margin oferror was bigger than 1.0%. This is probably
because it is difficult to add the sludge base powder
less 1.0% of the total organic/inorganic mix, since inthis experiment we only made ca. 1 gram of semiartificial sludge.
When we looked at the calibration curve, someinorganic content values were too high (more than
98.94% = organic content values were under 1.06%),
causing the ideal values of sludge base needed in themix, in effort to reproduce such samples, to be lessthan 0.0%. This indicates also that there are someplaces we still need to improve in the present

4. CONCLUSION
In our present study, we were successful inimproving our previously reported method torecreate natural hedoro with low organic content(high inorganic content) by utilizing inorganic
matter extracted from the original natural hedoro.
Inorganic matter storage is much easier and more

70
Table 4: Result of reproduction (1)Organic contents [%]22th Feb., 2018
0.92
Average as
Natural
1.43
1.30
1.53
1.09
Semi-artificial
Average as(Added 2.96%
1.37
1.31
of A. S. powder)
1.47

Measured value [%]

60
50
40
30
20
10
0
0

20

40
60
80
Organic contents [%]Table 5: Result of reproduction (2)25th May, 2018
Organic contents [%]1.40
Average as
Natural
1.77
1.50
1.33
2.80
Semi-artificial
Average as(Added 0.86%
3.17
2.86
of A. S. powder)
2.61

100

Fig. 13: Calibration curve (1)70Measured value [%]

60
50
40

Table 6: Standard deviation and significant
difference in semi-artificial hedoroStandard
significant
deviationdifference
Natural (1)0.268
p = 0.181
Semi-artificial (1)0.161Natural (2)0.196
p = 0.499
Semi-artificial (2)
0.232

30
20
10
0
0

20

40
60
80
Organic contents [%]100

Fig. 14: Calibration curve (2)912SEE - Nagoya, Japan, Nov.12-14, 2018

adsorbed cesium by organic matter from sea
sludge. 50th Annual Conference of Japan
Society on Water Environment, 2016, pp. 622.
[7] Hirano H., Sakamoto K., and Semura D.,
Comparison of adsorbed ability for cesium, byinorganic matter and sea sludge Part2: changing
decontaminate ability by values of Cs in sample.
51th Annual Conference of Japan Society on
Water Environment, 2017, pp. 404.
[8] Tamamura S, Sakai T, Shimizu S, Ishijima Y,
Igarashi T, Variation in inorganic nitrogen andorganic carbon concentrations in groundwater
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Journal of Groundwater Hydrology, Vol. 54,
Issue 2, 2012, pp.107–116.
[9] Ide T., Kawasaki K., Yamashiro H., andMatsuda A., Conditioning of excess activatedsludge by freezing and thawing process - thechange of physical chemical properties ofsludge with half-freezing and extended freezing-. Suishitsuodakukenkyu, Vol. 10, No. 10, 1987,
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Conditioning of excess activated sludge by
freezing and thawing process - the change ofsettling characteristics of sludge floc -.
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pp. 16–22. (Japanese)[11] Fujita M., Sludge dewatering by freezing.
Japanese Journal of Freezing and Drying, Vol.
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Pathogen reduction capabilities of freeze.thaw
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Science & Technology, Vol. 1, No. 3, 2004, pp.
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Wanga, and W. Qiu, Conditioning ofwastewater sludge using freezing and thawing:Role of curing. Water Research, Vol. 45, issue18, 2011, pp. 5969–5976.
[15] Noda S., Koyama K., Takakuwa T., and Akutsu
T., Experimental studies on dewatering ofdigested sludge by freezing thawing andfiltration method. Eiseseikougaku, Vol. 9, 1964,
pp. 41–53. (in Japanese)[16] Sato A., Nakamura D., Suzuki T., andNishimoto S., Change of moisture content of
unsuitable soil through freezing and thawing
process appeared in natural cold climate.
Japanese Goetechnical Journal, Vol. 4, No. 2,
2009, pp. 205–214. (in Japanese)reliable, since organic matters changes drasticallyduring storage, causing changes to the properties of
the hedoro samples. Therefore, the recreation of asemi-artificial sludge using preserved inorganic
materials extracted from the original natural samples
would allow successful recreations of the originalnatural hedoro.
To summarize:(1) If use zeolite in artificial sludge like previous
study, it is difficult to mimic under 6.91% byconditions.
(2) About to storage hedoro for experiment, organic
contents were changed under freezing. So it isimportant to keep under refrigeration whenstorage organic matter.
(3) Moisture contents were changed by many
elements; way of storage, time of storage, andorganic contents.
(4) It is impossible to keep hedoro same as natural
conditions.
In the future, we will try to improve our method
to recreate natural hedoro with low organic content,
or high inorganic content. We will also consider andtest other possible source of organic matter besides
yeast extract, and inorganic matter besides zeolite.
REFERENCES[1] Yoshida T., About generation and the removalof the sludge - In bottom sampler examinationof the Gulf of Minamata, HEDORO, No. 1,
1974, pp.11–27.
[2] Okamoto K., Toyama T., and Komoriya T.,
Ocean Decontamination: High Ability Removal
Method to Radioactive Cesium from Ocean
Sludge by Using Micro Bubbles and Activating
Microorganisms. International Journal of
GEOMATE, Vol. 12, Issue 32, 2017, pp.57–62.
[3] Hirano H., Toyama T., Nishimiya N., andOkamoto K.., Removal of Cesium from Sea
Sludge through Decomposition of Organic
Matter with Aqueous Hydrogen Peroxide.
International Journal of GEOMATE, Vol. 8,
Issue 1, 2015, pp.1203–1206.
[4] Hirano H., Semura D., Sakamoto K., Toyama T.,
and D. H. E. Setiamarga, A Dynamic changes oforganic content over time in the sea sludge
collected from the Gobo/Hidaka coastal area inWakayama, southwest Japan. IOP Conference
Series: Earth and Environmental Science,(Accepted).
[5] Hirano H., Toyama T., Nishimiya N., D. H. E.
Setiamarga., Morita S., Uragaki Y., andOkamoto K., Artificial Sludge Based on
Compositional Information of a Natural Sea
Sludge. International Journal of GEOMATE,
Vol. 12, Issue 31, 2017, pp.95–99.
[6] Uragaki Y, Morita S, Hirano H, Ability of913

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

EFFECTIVENESS OF USING CICADA SHELL AND RIVER
BRYOPHYTE AS AN INDEX OF AVAILABLE CU, ZN, PB, AS, NI AND
CR CONTAMINATION
Hiroyuki Ii1
Faculty of Systems Engineering, Wakayama University, Japan

1

ABSTRACT
Cicada shells, mainly Black Cicada, were analyzed in metropolitan parks in Wakayama and Osaka
prefectures. Cu, Pb, Cr, Zn, and Ni concentrations of black cicada shell at parks which were developed on former
factory land were 10 to 100 times or 10 times higher than those at normal metropolitan parks. Therefore, high Pb,
Cr, Zn, and Ni concentrations of black cicada shells were thought to have been caused by soil metal
concentration. Cu, Pb, Zn and As concentrations of large brown, small and evening cicada and anotogastersieboldii shells at metal mines were high and their high concentration was influenced by soil contamination
caused by tailings. Cr and Ni concentrations of small, evening and robust cicada shells at serpentinite areas were
10 times higher than those of other normal cicada shells. Therefore, high Cr and Ni concentration was also
thought to be caused by serpentinite soil metal concentration. As a result, metal concentration of cicada shell wasthought to be influenced by soil metal condition. For Pb Zn, Cu Cr, Ni, and As, metal concentrations of adultcicada were lower than those of cicada shell. Metal concentration of river bryophyte was influenced by mine
activity such as waste water from tailings and geological condition. The maximum differences for Pb Zn, Cu Cr,
Ni, and As concentrations between contaminated areas and non-contaminated areas were very high, 80,000,
1,000, 20,000, 5,000, 2,000, and 2,000 times. Therefore, river bryophyte was influenced by river metal
contamination and was also clarified to be an index of river contamination. .
Keywords: Cicada shell, Metal, Bryophyte, Contamination
concentration along streams is useful for estimating
river metal contamination, geological condition andmetal waste water in river catchment around living
place [3], [4]. The purpose of this study was
therefore to clarify the effectiveness of using cicada
shell as an index of soil metal contamination andriver bryophyte as an index of river metal
contamination.

INTRODUCTION
Heavy metal concentration for soil is not uniform
and it is difficult to measure available heavy metal
concentration for terrestrial organisms because
available heavy metal for terrestrial organisms
depends on chemical form. Cicada shell andbryophyte are studied as an index of available heavy
metal concentration for terrestrial organisms. Cicada
larva lives in soil over several years and gets
nutrition from the roots of trees. Heavy metal isaccumulated in cicada larva through a bioconcentration process. Some kinds of heavy metal
for cicada shell are concentrated from cicada
comparing concentrations between cicada and cicada
shell. As cicada shell can be sampled on tree andleaves, cicada shell is easier than adult cicada to
determine living place. Therefore the metal
concentration of cicada shell is thought to indicate
the available metal concentration of soil around theliving place [1], [2].
Heavy metal concentration for river water is verychangeable and river metal contamination is thought
to be cause by river water and river sediments.
Consequently, it is difficult to measure the available
heavy metal of river water. River bryophyte grows
slowly and heavy metal concentration is relatively
high in normal plants by a high bio-concentration
process. Therefore, bryophyte heavy metal

METHOD
Cicada shells and river bryophytes were sampledfrom 2015 to 2017 and 2015 to 2018 respectively.
Sampling points were widely selected for covering
metal contaminated and non-contaminated places. In
particular, the Adelaide mine area with a large
production of crocoite (CrPbO4) was selected forbryophyte sampling expecting Pb and Cr
contamination [5]. The Waidani, Ikuno and Tada
mines were also selected as Pb, As, Cu and Zn
contamination places [6], [7].
The sampling points of black cicada shell were
Nishikino metal wire factory (NMF) in the south of
Osaka prefecture, Wakayama University (WUI) on
the Mesozoic sedimentary rock (Izumi Formation) at
the north of Kinokawa River, Akiba mountain(AMG) and Wakayama Castle (WCG) on
914

SEE - Nagoya, Japan, Nov.12-14, 2018

black cicada at OCF is also little high, 10 ppm.
Excluding NMF, OCF and SuTA, Pb concentrationof black cicada were 1 to 10 ppm. As NMF is metal
wire factory, SuTA is shrine and OCF is past closed
factory, therefore these soils were thought to becontaminated. Pb concentration of the evening andsmall cicada at IKM was high, 10 to 200 ppm andthose of large brown at TGM were several tens ppm,
over 10 times higher than those at THS althoughdistance between both places was 10 km. Pb
concentration of anotogaster shell at WVM was over
10 ppm.
Fig.2 shows Zn concentration of cicada shell.
The Zn concentration of black cicada varied lessthan 10 to 1,000 ppm. Those at WUI and AMG were
low, 10 too ppm and at the other places 100 to 1,000
ppm. Zn concentrations of small cicada at IKM werehigh, 100 to 10,000 ppm. Zn concentrations ofevening and large brown cicada were 10 to 100 ppm.
Zn concentration of small cicada at IKM was high,
10 to 200 ppm and those of large brown at TGM
were over 10 times higher than those at THS
although distance between both places was 10 km.
Zn concentration at WVM was 500 to 700 ppm.
Fig.3 shows Cu concentration of cicada shell.
The Cu concentrations of black cicada were uniform,
several to several tens ppm and difference between
locations was less than 10 times. Cu concentration ofsmall cicada at IKM was high, several tens to 2,000

Sanbagawa Green schist, Wakaura and Saigasaki
park (WSP) on Sanbagawa pelitic schist at the southof Kinokawa River in Wakayama Prefecture [8],Shirasagi Park (SIA), Suminoe Park (SuNA),
Sumiyoshi Park (SuYA), and Sumiyoshitaisya(SuTA) on alluvial sediment in the Osaka plain,
Nagai Park (NPP) on the plateau sediment, andOsaka Castle Park (OCF) which was developed after
closing a military factory in Osaka prefecture. Otherkinds of cicada shell were sampled at Ikuno
polymetal mines (IKM), Tada Ginzan silver andcopper mine (TGM), Tada housing site (THS) near
Tada mine, south of Nakase mine (NSS), north ofNakase mine (NNS) on serpentinite in Hyogo
prefecture [7]. Shell of anotogaster sieboldii was
sampled at Waidani polymetal mine (WVM) in
Okayama prefecture.
The sampling points of Australian bryophyte
were the Adelaide mine shaft and entrance (ADM),
Adelaide mine tailing (ADO) and creek near
Adelaide mine (ADC), Dundas Extended mine pond
(DEP) and tailing (DET), Stitchtite Hill (SHS) on
serepentinite [5], Queen River from copper mine
waste (QER) in the west of Tasmania Island andCosterfield mine Sb mine (CFA) and Dayslesford
gold mine (DFG) in Victoria state [9]. Dundas
extended mine and Adelaide mine produce a lot of
Pb and Cr mineral. The sampling points of Canadianbryophyte were the Vermilion copper and nickel
mine (VMP) and Crown reserve cobalt and silvermine (CCR) in Ontario Province. The sampling
points of bryophyte of Japan were IKM, TGM,
Nishinomaki arsenic mine (NSA), WVM, Mineoka
serpentinite (MNS), Kongo granite mountain (KGG),
Yoshino granite plateau, Ningyotouge granite
mountain (NGG), and Okayama granite area (OKG).
Sampled cicada shell and bryophyte were dried
after ultrasonic cleaning then dissolved withconcentrated nitric acid solution. The solution after
filtration with 0.45 micrometer and stream water
sample were analyzed for metal concentration by
ICP-AES (Inductively Coupled Plasma Atomic
Emission Spectroscopy, SPS1700HVR ; Seiko
Instruments Inc.).

Pb ppm dr y wei ght

1000
100

Bl ackEveni ng
Lar ge br own
smal lRobustAdul tAnot ogast er

10
1
0. 1

0. 01

N W A W W S Su Su Su N O I T T N N W
MU M C S I N Y T P C M M H S N V
FI R R P A A A A PF MM S S SM

Fig.1 Pb concentration of cicada shell
104
1000
Zn ppm dr y wei ght

RESULTS
Metal Concentration of Cicada Shell
Fig.1 shows Pb concentration of cicada shell.
The Pb concentration of black cicada varied lessthan 0.01 to 600 ppm. NMF reached 600 ppm.
Although the distance between SuNA, SuYA and
SuTA is less than several km and under samegeological condition, Pb concentration of SuTA
shrine is, several tens ppm, 10 times higher thanthose of SuNA and SuYA parks. Pb concentration of

100
10
1
0. 1

Bl ackEveni ng
Lar ge Br own
Smal lRobustAdul tAnot ogast er

N W A W W S Su Su Su N O I T T N N W
MU M C S I N Y T PCM M H S NVF I R R P A A A A PF MM S S SM

Fig.2 Zn concentration of cicada shell
915

SEE - Nagoya, Japan, Nov.12-14, 2018104

Cu ppm dr y wei ght

1000
100

ppm and those of large brown at TGM reached 700
ppm, over 10 times higher than those at THS
although distance between both places was 10 km.
Cu concentration at WVM was over 100 ppm. Cu
concentrations of evening cicada were very low, 1 to
10 ppm at Nakase areas (NSS and NNS).
Fig.4 shows the Cr concentration of cicada shell.
The Cr concentration of black cicada varied lessthan 1 to 60 ppm. NMF reached 60 ppm. Cr
concentrations of black cicada at NPP were also alittle high, 10 ppm. Excluding NMF and NPP, Cr
concentration of black cicada were 1 to 10 ppm. Cr
concentration of small cicada at IKM was variable,
several 0.1 to 10 ppm and those of large brown at
TGM were less than 1 ppm. Cr concentration at
WVM was less than several ppm. Cr concentrationsof evening cicada at NSS and NNS were several toseveral tens ppm.
Fig.5 shows Ni concentration of cicada shell.
The Ni concentration of black cicada varied lessthan 0.1 to 20 ppm. NMF were high and reached 20
ppm. Ni concentrations of black cicada at SuTA are
little low, less than 1 ppm. Excluding NMF and
SuTA, Ni concentration of black cicada were about
1 ppm. Ni concentration of small cicada at IKM was
1 to 10 ppm and those of large brown at TGM wereless than 1 ppm. Ni concentration at WVM wasseveral ppm. On the other, Ni concentrations ofsmall and evening cicada at NNS were also 10 to
100 ppm.
Fig.6 shows the As concentration of cicada shell.
The As concentration of black cicada varied 0.1 to
10 ppm. NMF were low 0.1 to 1 ppm although othermetal was relative to high. As concentrations ofevening and small cicada at IKM were high, 1 to 200
ppm. As concentration of anotogaster shell at WVM
was high, 200 ppm. As concentrations of large
brown cicada were 1 to 10 ppm.
Adults at IKM are small cicada and adults at
NNS and NSS are robust cicada. Comparing cicada
shell with adults, Pb, As, Cr and Ni concentrationsof small and robust cicada adults were smaller thanthose of shells excluding Ni concentrations at NNS.
For Ni concentrations robust cicada at NNS, cicada
shell is lower than those of adult. Zn and Cu
concentrations of robust cicada adult were higher
than those of shells however those of small cicada
shells and adults were the same. Totally, adult metal
concentrations were lower than those of shell.

Bl ackEveni ng
Lar ge Br own
Smal lRobustAdul tAnot ogast er

10
1
0. 1

N W A W W S Su Su Su N O I T T N N W
MU M C S I N Y T P CM M H S NVF I R R P A A A A PF MM S S SM

Fig.3 Cu concentration of cicada shell

Cr ppm dr y wei ght

100

10

1

0. 1

0. 01

Bl ackEveni ng
Lar ge Br own
Smal lRobustAdul tAnot ogast er

N W A W W S Su Su Su N O I T T N N W
MU M C S I N Y T P C M M H S N V
F I R R P A A A A PF MM S S SM

Fig.4 Cr concentration of cicada shell

Ni ppm dr y wei ght

1000
Bl ackEveni ng
Lar ge br own
Smal lRobustAdl utAnot ogast er Si ebol di i

100
10
1
0. 1

0. 01

N W A W W S Su Su Su N O I T T N N W
M U M C S I N Y T PCMM H S N V
F I R R P A A A A PF MM S SS M

Fig.5 Ni concentration of cicada shellAs ppm dr y wei ght

1000
100
10

Bl ackEveni ng
Lar ge Br own
Smal lRobustAdul tAnot ogast er

Metal Concentration of Bryophyte

1

Fig.7 shows Pb concentration for river
bryophyte. Pb concentrations at the Adelaide minearea (ADM, ADO, ADC, DEP, DET) were
extremely high, over 1,000 ppm and reached 80,000
ppm and reached also over 3,000 ppm at Japanese
metal mines (IKM and TGM). Those at WVM wereabout 100. Those at non-contaminated area (MNS,

0. 1
0. 01

N W A W W S Su Su Su N O I T T N N W
M U M C S I N Y T PCMM H S NVF I R R P A A A A PF MM S S SM

Fig.6 As concentration of cicada shell
916

SEE - Nagoya, Japan, Nov.12-14, 2018

105

Cr ppm dr y wei ght

Pb ppm dr y wei ght

105
104

104

1000

1000
100
10

100
10
1

1

0. 1

0. 1

A A A D DS Q CDV CI T N WMKY N O
D D D E E H E F F M C K G S V N GS G K
M O C P T S R A G P R M M A M S GG G G

A A A D DS Q CDV CI T N W MKY N O
D D D E E H E F F M C K G S V N GS G K
M O C P T S R A G P R M M A M S GG G GCu concentrations at WVM reached 20,000 ppm

KGG, YSG, NGG

104

Ni ppm dr y wei ght

Zn ppm dr y wei ght

105
104

1000

1000
100
10

100
10
1

1
0. 1
A A A D DS Q CDV CI T N WMKY N O
D D D E E H E F F M C K G S V N GS G K
M O C P T S R A G P R M M A M S GG G G

0. 1
A A A D DS Q CDV CI T N WMKY N O
D D D E E H E F F M C K G S V N GS G K
M O C P T S R A G P R M M A M S GG G G

Fig.10 Cr concentration for river bryophyte.

Fig.7 Pb concentration for river bryophyte.
104

As ppm dr y wei ght

Cu ppm dr y wei ght

105

1000

104

1000
100
10

100
10
1

1

0. 1

0. 1

A A A D DS Q CDV CI T N WMKY N O
D D D E E H E F F M C K G S V N GS G K
M O C P T S R A G P R M M A M S GG G G

A A A D DS Q CDV CI T N WMKY N O
D D D E E H E F F M C K G S V N GS G K
M O C P T S R A G P R M M A M S GG G G

Fig.8 Zn concentration for river bryophyte.
Fig.9 Cu concentration for river bryophyte.

Fig.11 Ni concentration for river bryophyte.
Fig.12 As concentration for river bryophyte.

and OKG) were 1 to 10 ppm. Those at the otherareas (SHS, QER, CFA, DFG, VMP and CCR) were
1 to 100 ppm.
Fig.8 shows Zn concentration for river bryophyte.
Zn concentrations at Adelaide mine area (ADM,
ADO, ADC, DEP, DET) were high, 100 to several
1,000 ppm and reached 7, 000 ppm and reached also
over 10,000 ppm at Japanese metal mines (IKM and
WVM). Those at TGM were about 1000 ppm. Thoseat non-contaminated area (MNS, KGG, YSG, NGG
and OKG) were 10 to 100 ppm. Those at the otherareas (SHS, QER, CFA, VMP and NSA) were 10 to
100 ppm.
Fig.9 shows Cu concentration for river bryophyte.

those at VMP, IKM and TGM were also high values,
several 1,000 ppm. Those at Adelaide mine area
(ADM, ADO, ADC, DEP, DET) were 10 to 1,000
ppm. Those at non-contaminated area (MNS, KGG,
YSG, NGG and OKG) were 1 to several tens ppm.
Those at the other areas were 10 to 100 ppm.
Fig.10 shows Cr concentration for river
bryophyte. Cr concentrations at Adelaide mine area
(ADM, ADO and DET) were extremely high, 10
ppm to 5,000 ppm. Those at serpetinite (SHS and
MNS) were high, 100 ppm. Those at noncontaminated area (KGG, YSG, NGG and OKG)
were 1 to 10 ppm. Cr concentration at high Cu
sampling points, QER, VMP and WVM were less917

SEE - Nagoya, Japan, Nov.12-14, 2018

than 10 ppm.
Fig.11 shows Ni concentration for river
bryophyte. Ni concentrations at Adelaide mine area
(ADM, DET), Vermilion mine (VMP), Cobalt(CCR) in Canada and serpentinite area (SHS and
MNS) reached extremely high, 2,000 ppm. Those at
non-contaminated area (KGG, YSG, NGG and
OKG) were less than 1 to several tens ppm. Ni
concentration at high Cu sampling points, IKM,
TGM, QER, and WVM were less than several tens
ppm.
Fig.12 shows As concentration for river
bryophyte. As concentrations at WVM reachedextremely high, 2,000 ppm and those at ADM, CCR,IKM and NSA also reached 500 ppm. Those at noncontaminated area (KGG, YSG, NGG and OKG)
were less than 1 to several tens ppm. As
concentration at high Cu sampling points, TGM,
QER, and VMP were less than several tens ppm assame as Non-contaminated area.

and copper mine those tailing contains Zn(sphalerite
ZnS), Cu(chalcopyrite CuFeS2), and Pb(galena PbS)
minerals [7]. Although shell specie were different,
Cu, Pb, Zn and As concentrations of small andevening cicada and anotogaster shells at IKM andWVM were high and their high concentration was
influenced on soil contamination caused by tailings
as well as high Pb, Cu and Zn concentration forlarge brown at TGM mine.
Cr and Ni concentrations of small, evening androbust cicada shells at NSS and NNS were 10 times
higher than those of other normal cicada shells.
Generally Ni and Cr concentration of serpentinite
such as ultrabasic rock is high relative to other rocks.
Therefore, high Cr and Ni concentration was also
thought to be caused by soil metal concentration.
As a result, metal concentration of cicada shell
was thought to be influenced by soil metal condition.
The maximum values of each metal for black,evening, small and large brown cicada shell were
600, 200, 200 and several tens ppm for Pb, 1,000,
100, 10,000, and 100 ppm for Zn, 60, 10, 2,000 and
700 for Cu, 60, several tens, 10 and several ppm for
Cr, 20, 100, 100 and 1 ppm for Ni, and 10, 200, 200
and 10 ppm for As.
High Pb concentration river bryophyte was foundat metal mine areas (ADM, ADO, ADC, DEP, DET,
IKM, TGM and WVM) and the maximum value was
80,000 ppm. On the other hand, those at noncontaminated area were 1 to several ppm and thenPb concentration of river bryophyte was influenced
by mine activity such as waste water from tailings.
The maximum difference between contaminatedarea and non-contaminated area was 80,000 times.
High Zn concentration river bryophyte was found at
metal mine areas (ADM, ADO, ADC, DEP, DET,
IKM, TGM and WVM) and the maximum value was
10,000 ppm. On the other hand, those in noncontaminated areas were 10 to 100 ppm so the Zn
concentration of river bryophyte was deemed
influenced by mine activity such as waste waterfrom tailings. The maximum difference between
contaminated area and non-contaminated area was
1,000 times. High Cu concentration river bryophyte
was found at metal mine areas (ADM, ADO, ADC,
DEP, DET, IKM, TGM and WVM) and the
maximum value was 20,000 ppm. On the other hand,those at non-contaminated area were 1 to several
tens ppm and then Cu concentration of river
bryophyte was influenced by mine activity such aswaste water from tailings. The maximum difference
between contaminated area and non-contaminatedarea was 20,000 times. High Cr concentration river
bryophyte was found at Adelaide mine areas (ADM,
ADO, and DET) and serpentinite areas (SHS and
MNS) and the maximum value was 5,000 ppm. TheDISCUSSION
Mainly, black cicada shells were analyzed in
metropolitan parks in Wakayama and Osaka
Prefecture because large amounts of cicada shellsamples were easily obtained in metropolitan parks.
On the other hand, in forests, cicada shells arescattered and it is difficult to get a lot of cicada
shells in a narrow area. Cicada shell was very
limited in forests and it is important to find trees
concentrated with cicada shells. Then, if thecontaminated area located in the forest, sampled
cicada is not always expected species in the forestand cicada shell is not always found in contaminatedareas. In the forest, large brown, evening, small or
robust cicada shells were found in Kansai district.
NMF is a steel wire factory and Pb, Cr, Zn, andNi concentrations of black cicada shell at NMF were
10 to 100 times or 10times higher than those at otherpoints. In particular, the factory uses stainless (Niand Cr alloy) and Ni and Cr contamination for soil isestimated and Pb or Zn was also thought to be used
for producing steal wire. Therefore, high Pb, Cr, Zn,
and Ni concentrations of black cicada shells were
thought to be caused by soil metal concentration.
OCF is a metropolitan park but was a military
factory in former times. Cr, Pb, and Cu
concentrations of black cicada shell were relatively
high, 10 times higher than those of black cicada. Cr,
Pb, and Cu concentrations of Cicada shell were
thought to be influenced by soil metal concentration
after the military factory.
IKM and WVM are closed polymetal mines andtheir tailing contains
Zn(sphalerite
ZnS),
Cu(chalcopyrite CuFeS2), As(arsenopyrite FeAsS),
and Pb(galena PbS) minerals and TGM is a silver

918

SEE - Nagoya, Japan, Nov.12-14, 2018

Adelaide mine area is accompanied with serpentinite.
On the other hand, those at non-contaminatedarea excluding serpentinite area were 1 to 10 ppm so
the Cr concentration of river bryophyte was deemed
influenced by mine activity such as waste waterfrom tailings and geological condition. The
maximum difference between contaminated areasand non-contaminated areas was 5,000 times. HighNi concentration river bryophyte was found at
Adelaide mine area (ADM, DET), Vermilion mine(VMP), Cobalt (CCR) in Canada and serpentinite
area (SHS and MNS) and the maximum value was
2,000 ppm. On the other hand, those at noncontaminated area excluding serpentinite area were
1 to several tens ppm and then Ni concentration ofriver bryophyte was influenced by mine activity
such as waste water from tailings and geologicalcondition. The maximum difference between
contaminated area and non-contaminated area was
2,000 times. High As concentration river bryophyte
was found at WVM, ADM, CCR, IKM and NSA
and the maximum value was 2,000 ppm. Ore
mineral at CCR and NSA was arsenic cobalt mineraland arsenic Sulphur mineral. On the other hand,those in the non-contaminated area were 1 to several
tens ppm therefore As concentration of river
bryophyte was influenced by mine activity such aswaste water from tailings. The maximum difference
between contaminated area and non-contaminatedarea was 2,000 times.

thought to be caused by soil metal concentration. For
Pb Zn, Cu Cr, Ni, and As, metal concentrations ofadult cicada were lower than those of cicada shell.
Metal concentration of river bryophyte was
influenced by mine activity such as waste waterfrom tailings and geological condition. The
maximum differences for Pb Zn, Cu Cr, Ni, and As
concentrations between contaminated area and noncontaminated area were very high, 80,000, 1,000,
20,000, 5,000, 2,000, and 2,000 times. Therefore,
river bryophyte was influenced by river metal
contamination and was also clarified to be an index
of river contamination.
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Hyogo Prefecture, Humans and Nature, No. 6,
September 1995, pp.197- 243.
[8] Wakayama City Children’s Science Museum,
http://www.city.wakayama.wakayama.jp/kodo
mo/sassi/ganseki/chizu/wakayama.htm[9] Department of Energy and Minerals, Government ofVictoria,
Australia,
MineralsofVictoria(1:1,000,000), 1992.

CONCLUSION
Mainly, black cicada shells were analyzed in
metropolitan parks in Wakayama and Osaka
prefecture. In forests, large brown, evening, small or
robust were found in the Kansai district. Pb, Cr, Zn,
and Ni concentrations of black cicada shell at steel
wire factory were 10 to 100 times or 10times higher
than those at other points. Cr, Pb, and Cu
concentrations of black cicada shell at a
metropolitan park after military factory wererelatively high, 10 times higher than those of black
cicada. Therefore, high Pb, Cr, Zn, and Ni
concentrations of black cicada shells were thought tohave been caused by soil metal concentration.
Cu, Pb, Zn and As concentrations of small andevening cicada and anotogaster shells at polymetal
mines were over 10 times higher than those at nonmetal mine area and then their high concentration
was influenced on soil contamination caused bytailings. Cr and Ni concentrations of small, evening
and robust cicada shells at serpentinite areas were 10
times higher than those of other normal cicada shells.
Generally Ni and Cr concentration of serpentinite
such as ultrabasic rock is high relative to other rocks.
Therefore, high Cr and Ni concentration was also919

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

STUDY ON REMOVAL OF CONTAMINATED SOIL ON FORESTSLOPE FOCUSING ON DIFFERENCE IN DENSITY OF SUBSURFACEGROUND
Keiichiro Shibata1, Hidenori Yoshida2, Daisuke Matsumori3, Matsumoto Naomichi4 and Kazushi Moriki5
1, 5
Graduate school of engineering, Kagawa university, 2 Faculty of engineering and design, Kagawa
university, Japan; 3 Penta-ocean construction, Japan; 4 Technical staff, Kagawa university, Japan

ABSTRACTA large amount of radioactive cesium was released from the Fukushima Daiichi nuclear power station.
Decontamination in living area has been almost completed for seven years. However, decontamination has notprogressed much in forests where people do not enter. The decontamination of soil on forest slope cannot be doneusing heavy machinery unlike that on flatland. The effective decontamination method for the forest slope isdesired. Therefore, in this study, the collecting method of slope surface soil through flushing water and the soil
separation method focusing on difference in density of minerals were proposed and examined. In the proposed
method, it is expected to reduce the volume of contaminated soil through the separation of contaminated part andnon-contaminated one. In this study, the laboratory test is conducted to evaluate the usefulness of the proposed
method. In the test, a device of simulating the slope and a device to flush the soil by flowing water are produced.
When an actual soil is utilized for experiment, it is difficult to ensure the experimental repeatability due to soil
variability. Therefore, simulated soil is consisted of Toyoura standard sand and vermiculite. To simulate soil
contaminated with cesium, cesium standard solution is added into the simulated soil. The soil is set on the slope,and the test is conducted to flush and collect the soil by running water from upside to downside. As a result, it isclarified that only the soil containing cesium can be removed by separating the soil after flushing.
Keywords: Radioactive cesium, Forest slope, Vermiculite, Contaminated soil

uncompleted in forests away from the living
environment of residents. The completion ratio of
decontamination of forests in the area where thecountry implements the decontamination is shown in
Table 1. Also, from this table, there is a difference inthe completion ratio of the decontamination
depending on geographical features. Some forests inthe area such as Iitate village and Kawamata town are
scarcely decontaminated. Although the air dose rateof forest decreases year by year due to thedecontamination work and half-life, it is still higher
than that in living area. The decontamination inforests is difficult because it is hard to enter heavymachinery to remove the top soil. The
decontamination of contaminated soils on flatgrounds is primarily done by removing the top soil.
Furthermore,onforestslopes,carefuldecontamination work is required as excessive
removal of top soil can cause landslides.
For radioactive cesium in the forest soil, aremoval method using wood chips is devised by
Kaneko et al. at Yokohama National University as in[2]. The method utilizes the property that fungi absorb
radioactive cesium. The wood chip is placed in the
bag and radioactive cesium is adsorbed into thecellulose body contained in the wood chip. After that,the decontamination is completed by collecting thebag. This method is inexpensive. However, it takes

INTRODUCTION
The Great East Japan Earthquake, which is themost powerful earthquake on record, occurred in
Sanriku offshore on March 11, 2011. The Fukushima
Daiichi nuclear energy plant of the Tokyo ElectricPower Company (1F) was hit by the great Tsunami
several times after an hour of the earthquake. The
power facilities were widely destroyed, and thebasement room and the shaft were inundated with the
Tsunami. Major quantity of radioactive materials
were discharged from the 1F. The radioactive
materials is spread to atmosphere, which is fallen
down mountain, river and marine by rain breeze. Also,
the radioactive materials that have fallen into themountains are firmly bonded to the cray minerals inthe soil. Especially, the cesium-137 has been
extensively detected in Fukushima prefecture
because the cesium-137 has been vigorously
discharged and long half period. The radioactive
cesium has been decontaminated by removing the top
soil because it has settled in the surface layer of thesoil after being absorbed by atmospheric dust as in [1].
The decontamination around the living environmentof the resident is almost completed due to a harddecontamination work since the accident. On theother hand, there are places where thedecontamination is completed and decontamination is920

SEE - Nagoya, Japan, Nov.12-14, 2018

time because it can be removed only by the power offungi. Alternatively, the previous studies are
conducted by the faculty of engineering, Ibaraki
University in order to control the moving of cesiumon the forestry slope, and it has two features as in [3].
One is that the bentonite is spread onto the leaf moldin the forest so as to control the resorption of theradioactive cesium to plants. The other is that themoving of the bentonite including the radioactive
cesium is controlled by polyion-complex (PIC) of
excess positive charge and negative charge. The
radioactive cesium in the air and solution is adsorbed
into the bentonite. The resorption to the plant is
controlled by the absorption performance of thebentonite. Alternatively, the forest ecosystem is not
destroyed because the elements such as the flow ofrainwater are used in this method. Furthermore, the
PIC is harmless because the raw material of PIC iscommonly used as the thickener of ice-creams as in[4]. The moving of cesium is controlled, but thecontaminated soil is not reduced in this method.
Besides, it takes time to complete the work due to theuse of rainfall. Based on these points, in previous
study, the simple decontamination method is
proposed in order to decontaminate the contaminatedsoil on the slope by flowing water as in [5]. From thisstudy, it was clarified that it was possible to remove
about 50% of cesium by running water fromsimulated contaminated soil and stirring after
recovery of running water. On the other hand, it was
mentioned as a problem that the variability occurredin the flowing water time and the flowing wateramount in the produced equipment. Thus, in thisstudy, the reproducibility of the test is improved by
improving the equipment. Then, the method ofrecovering only soil containing cesium is proposed byusing the difference in the specific gravity of the soil
after collection. In this method, only clay mineral thatspecifically adsorbs cesium such as vermiculite isrecovered from mixed sand and separated.
Furthermore, other cesium is recovered by washing
thorough stirring, which leads to volume reduction ofcontaminated soil.

released by the accident in the 1F. The radioactive
cesium has harmful long-term effects due to its long
half-life. The volume of spreading strontium-90 iscomparatively small, despite its long half-life. The
cesium exists as the monovalent cation in the soil, and
it is absorbed into the soil particle having a negative
charge. Especially, the cesium is selectively absorbed
into the small clay particle. The cesium is adhered tothe soil due to the 2:1 types of lamellar silicate. Whenthe part of silicon or aluminum substitute for anotherelement having a few positive charges in the silicontetrahedron sheet or aluminum octahedron sheet, thenegative charge is expressed with the shortage of
positive charge in the sheet. Moreover, the cation isabsorbed in order to neutralize the intercalation. The
charge in this intercalation shows a high selectivity
for the cesium ion. That is because the six-memberedring is nearly equal to the ion radius of the cesium ion
in the basal seat of the silicon tetrahedron sheet.
Alternatively, the bonding strength with the sixmembered ring becomes larger as the hydrationenergy is smaller, and the bonding strength of cesium
ion is the highest. Generally, the six-membered ringis occupied by the potassium ion because theabundance of potassium ion predominantly is major
in the soil (see Fig. 1 of top part). The terminal of thelayer in the cray mineral is swelled by thedisintegration, and the potassium ion is discharged.
Thus, the empty space that another cation gains entry
is formed. This space is called the frayed edge (seeFig. 1 of bottom part), and the extraction of cesium
ion from the frayed edge is very difficult. It is almost
impossible to extract the cesium in the frayed edge
only by flowing water. Thus, in this study, it isconsidered that the contaminated surface soil can becollected with the flowing water by utilizing thestrong fixation.

Table 1 Decontaminated situation of forest in town
and village
Cities
Tamura city
Kawauchi village
Iitate village
Kawamata town
Katsurao village
Okuma town

Decontamination
completion ratio (%)
100
74
3
12
67
44

CESIUM IN THE SOIL
Fig. 1 Top part of 2:1 types of lamellar silicate andbottom part of Frayed edge

A large number of radioactive materials was
921

SEE - Nagoya, Japan, Nov.12-14, 2018

0, 7, 14 and 28 days. After curing, the mixed sand is
set on the slope of the equipment. The assumed soil iscollected by flushing water from the rolling pipe atthe upper part of the slope. The water and assumed
contaminated soil are collected from the slit byflushing water. The cesium concentration in the
supernatant of the solution is analyzed by an AAS(Atomic Absorption Spectrometer). In the second
step, the recovered the assumed contaminated soil isclassified by sieving. From some trials of sieving at
an early stage, it is found that the sieving of the sandis difficult under the moisture condition of the sand.
Therefore, the assumed contaminated soil is dried for
24 hours in an oven dryer set at 110 °C. The using
sieve size is 425, 250 and 106 μm. After classification,
the assumed contaminated soil remaining in eachsieve is stirred, and the cesium concentration isanalyzed by the AAS (Atomic Absorption
Spectrometer) to calculate the extraction ratio for soilthat remained in each sieve. As the screwing method,
200.0 mL of pure water is poured into the collectedsoil, and the sample is screwed with 300 rpm for 10
minutes by the stirrer. The calculation formula of theextraction ratio is shown below.

METHODThe simulated soil used in the test and the test
method are explained, respectively. Alternatively, inthis study, all of the tests are conducted three times
under the same conditions to ensure the repeatabilityof the tests.
Assumed contaminated soil
In this study, the Toyoura standard sand,vermiculite or their mixed sand is used as the assumed
contaminated soil to which the cesium is added. The
Toyoura standard sand consists of uniform grain size.
The vermiculite contains the silicate mineral thatmainly consists of the oxidized silicon, magnesia andaluminum oxide. The vermiculite has a highadsorption performance for cesium as in [6], and themechanism of absorption has been clarified as in [7].
The vermiculite is widely distributed to Fukushima
soil, and the vermiculite constitutes barriers to thedecontamination of cesium in a soil. Based on the past
study as in [5], 9.5 g of the standard sand and 0.5 g ofvermiculite is mixed in order to make the assumed
contaminated soil.

𝐄𝐱𝐭𝐫𝐚𝐜𝐭𝐢𝐨𝐧 𝐫𝐚𝐭𝐢𝐨 (%) =𝐞𝐱𝐭𝐫𝐚𝐜𝐭𝐞𝐝 𝐚𝐦𝐨𝐮𝐧𝐭 (𝐦𝐠)/𝐚𝐝𝐝𝐞𝐝 𝐚𝐦𝐨𝐮𝐧𝐭 (𝐦𝐠) × 𝟏𝟎𝟎(𝟏)

Test and analysis method
In order to imitate the real behavior of cesium inthe soil slope, the slope device is produced (see Fig.
2). The slope device consists of two equipment: oneis the slope section and another is the flowing watersection. A 3D making device is used to produce theslope section (20.0 cm x 20.0 cm x 6.5 cm). The slit
is set at the bottom of slope section in order to collectthe water and soil which contain cesium. Althoughdetails will be described below, the assumed soil falls
into this slit by flushing water from the upper part ofthe slope of the equipment. Also, the slope angle isset to about 9 degrees to avoid the flow disruption.
The flowing water section is made by the polyvinyl
chloride (PVC) pipe having the spiral holes. The
rotating shaft is set on the top of the slope, and the
PVC pipe and the rotating shaft are connected. The
PVC pipe is rolled at 10 rpm, and the water is evenly
flowed out from each hole by rolling the PVC pipe.
The test is divided into two steps. In the first step,
the mixed sand containing cesium on the slope isrecovered by running water, and the cesium isseparated from soil by stirring. Specifically, 1 ml of acesium chloride solution (about 3.3 ppm of initialconcentration) is added to the mixed sand and thecuring of mixed sand is conducted. It is known thatthe time required for adsorption of cesium to clay
minerals is long. Also, a long period has elapsed sinceradioactive cesium deposited in the soil of Fukushima.
Based on these points, a curing period is establishedto investigate the influence of passage of time on theabsorption of cesium in the soil. The curing period isFig. 2 Slope device
TEST RESULTS
The results of test in the each step are shown anddiscussed, respectively. The each result is shown
thorough the graph. The value in the graph is the922

SEE - Nagoya, Japan, Nov.12-14, 2018average one of the test of the three times.

by stirring is shown in Fig. 4. The extraction ratio of
cesium and the curing period of cesium are shown inthe vertical and horizontal axes, respectively. The
lower the extraction ratio is, the longer the curing
period is getting. It is considered that the cesium isadsorbed into the frayed edge in vermiculite by curing
as the reason. Moreover, the cesium tend to be
extracted easily from the soil that remained in 106 μmof the sieve. As this reason, it is presumed that mostof the soil remaining in 106 μm of the sieve is thestandard sand. From these facts, it is suggested thatthe concentration of cesium can be reduced byscrewing the soil except frayed edges such as thestandard sand. Also, the amount of contaminated soil
may be reduced by separating the vermiculitecontaining a lot of cesium from the soil.

Test result of first stepIn the first step, the assumed contaminated soil isrecovered by flushing water, and the concentration ofcesium in the supernatant of the recovered sample isanalyzed by AAS. The results are shown in Fig. 3.
The extraction ratio of cesium and the curing periodof cesium are shown in the vertical and horizontal
axes, respectively. In the specimens without thecuring period, the extraction ratio of cesium is about
7%, and over 90% of cesium remained in the assumed
mixed soil. The extraction ratio of cesium is low inthe case of setting on curing period of cesiumcompared to case of the specimen without curing
period. The extraction ratio hardly change even if thecuring period is prolonged. It is found that theextracting of cesium from contaminated soil in a realsituation is difficult by only flushing water regardlessof the length of curing period.

Table 2 Mass of soil remaining in each sieve

Sieve mesh
(μm)
425
250
106
Bottom
Total

80

0.46
1.09
8.40
0.03
9.99

Curing period (days)
7
14
0.45
1.35
8.13
0.03
9.97

0.44
1.38
8.13
0.03
9.98

28
0.48
1.93
7.53
0.02
9.96

60
100
40
20

6.67

4.22

4.51

Extraction ratio (%)

Extraction ratio (%)

100

0

3.93

0
0

7
14
Curing period (days)

28

Fig. 3 Extraction ratio of cesium after flushingwater

106 μm

250 μm425 μm

80
60
40
20

Test result of second stepIn the second step, the recovered soil in the firststep is dried, and classified by sieving. The amount ofrecovered soil is measured. After measuring, thesieved soil is washed out by stirring, and theconcentration of cesium in the solution which is usedduring the stirring is analyzed by the AAS.
First, the mass of the assumed soil remaining ineach sieve is shown in Table 2. The mass of theassumed soil before the test is 10 g, which means that
almost all assumed soil is recovered by flushing water.
It is suggested that the flushing water is effective forcollecting of the contaminated soil on the slope.
Alternatively, all of the soil remaining in 425 μm ofthe sieve are the vermiculite because all standard sandpass through 425 μm of the sieve.
Secondly, the extraction ratio of cesium extracted

Bottom

0

1.20
14.32
10.86
10.68
1

2.75
16.02

1.07
13.77

8.68
6.97

5.34
5.05

7
14
Curing period (days)

2.33
13.18
2.75
4.08
28

Fig. 4 Extraction ratio of cesium after sieving andscrewing
CONCLUSIONSIn this study, the test equipment assuming theforest slope is made and the recovering test of theassumed contaminated soil by flushing water isconducted in order to establish a new
decontamination method for the soil of the forest
slope where the decontamination work is hard. The
standard sand and the vermiculite are mixed to model
923

SEE - Nagoya, Japan, Nov.12-14, 2018the assumed contaminated soil. The contaminatedpart of the soil can be reduced by separating andrecovering the soil because the their adsorption
property of minerals involved in the soil for cesium isgreatly difference. Therefore, the recovered
contaminated soil is classified according to theminerals by the mesh control with sieve. Afterclassification, washing out by stirring is attempted toreduce the concentration of cesium in the assumed
contaminated soil by separating the main part inwhich cesium is mainly involved. As a result of thetest, the assumed soil is recovered with only flushingwater. Furthermore, the standard sand and thevermiculite are separated by the mesh control withsieve. In other words, it is suggested that only
vermiculite adsorbing cesium strongly should berecovered to reduce the contaminated soil. The
extracting cesium from the separated standard sandwith stirring may also lead to the reduction of theconcentration of cesium in the contaminated soil.
From the above results, it is considered that the
proposed method has usefulness for removing thecontaminated soil on the forest slope and for the
reduction of the contaminated soil by separating thesoil part in which cesium is mainly involved. On theother hand, the assumed contaminated soil in this test
is different from actual complicated soil. Therefore,
the universal knowledge is not necessarily obtained
only by this experiment. For example, the soil suchas the decomposed granite soil has the complicatedsoil structure and contains a large amount of clay. The
clay may have a frayed edge, and a lot of cesium may
be adsorbed into the frayed edge. In near future, it isnecessary to examine whether the decontaminationand the volume reduction by the proposed method are
possible for the soil such as the decomposed granite
soil.

[1] Ministry of Agriculture, Forestry and Fisheries,
Technical document on measures against
decontamination of agricultural land, part 2 ofconstruction, 2013, pp. 31-33.
[2] B. Rafferty, et al., Decomposition in two pine
forest: The mobilisation of 137Cs and K fromforest litter, Soil Biol. Biochem, Vol. 29, No.
11/12, 1997, pp. 1673-1681.
[3] Ibaraki University, KUMAGAI GUMI CO.,LTD. and Japan Atomic energy Agency, “Newtechnology to control the removal of radioactive
cesium from forest to living area”, May 2016, pp.
1-4.
[4] Naganawa H, Kumazawa N, Saitoh H, Yanase N,
Mitamura H, Nagano T, Kashima K, Fukuda T,
Yoshida Z and Tanaka S,
Removal ofRadioactive Cesium from Surface Soils Solidified
Using Polyion Complex Rapid Communication
for Decontamination Test at Iitate-mura in
Fukushima Prefecture, Transactions of theAtomic Energy Society of Japan, Vol. 10, 2011,
No. 4, pp. 227-234.
[5] Awal A.S.M.A, Hosseini H. and Hossain M.Z.,
Strength, Modulus of Elasticity and Shrinkage
Behaviour of Concrete Containing Waste Carpet
Fiber, International Journal of GEOMATE, Vol.
9, Issue 17, 2015, pp. 1441-1446.
[6] Shibata K, Yoshida H and Matsumoto N, Studyon removal method of cesium from slope soil
using simple slusher, International Journal of
GEOMATE, Vol. 14, Issue. 45, 2018, pp. 136143.
[7] Suzuki N, Amano Y, Ochi K and Toshiyuki C,“Cesium uptake with the natural raw vermiculite.
~Concerning the grain size to adsorbability, andits application to the column method~”, Journalof Ion Exchange, Vol. 26, 2015, Issue. 3, pp. 2933.
[8] Motokawa R, Endo H, Yokoyama S, Nishitsuji
S, Kobayashi T, Suzuki S and Yaita T,“Collective Structural Changes in Vermiculite
Clay Suspensions Induced by Cesium Ions”,
Scientific Reports (online), Vol. 4, Jun 2014,
article number 6585 (online)

ACKNOWLEDGEMENT
The part of this work was supported by Japan
Society for the Promotion of Science, the Grants-inAid for Scientific Research (C) (Grant number:
18J12343).
REFERENCES

924

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

MAPPING STABLE ISOTOPIC RATIOS OF STREAM WATER AND
CU, ZN, PB AND AS CONCENTRATIONS OF BRYOPHYTE ALONGSTREAMS IN THE EAST OF OKAYAMA AND TOTTORIPREFECTURES, JAPAN

1

Hiroyuki Ii1 and Masahito Yoshimura2
Faculty of Systems Engineering, Wakayama University, Japan; 2,DOWA Holdings Co., Ltd., Japan

ABSTRACTThe stable isotopic ratio of precipitation is useful for estimating both the recharge area and resource ofgroundwater as well as for mapping of precipitation. Stream water is representative of precipitation for small
river catchment so stream water was sampled and analyzed. A distribution map of oxygen and hydrogen stable
isotopic stream water values along the Yoshiikawa and Tenjinkawa rivers show that isotope values decreased
with distance from the Inland Sea implying that southward wind or cloud was mainly controled isotope values
and that the influence of the Japan Sea on isotope of precipitation was low.
Bryophyte grows slowly and accumulates heavy metals relative to other life by a high bio-concentration
process. Therefore, bryophyte heavy metal concentration along streams is deemed useful for estimating river
metal contamination, geological condition and metal waste water in the river catchment. Bryophyte along
streams was also sampled at the same time of stream water sampling. A map for Zn, Cu, As, and Pb
concentrations of bryophyte shows that metal concentrations of stream bryophyte around the watershed area
were low whereas metal concentrations around Tsuyama Basin and Yanahara mine, were medium relative tothose of the other areas excluding the Waidani mine area. In the Waidani mine area, Zn, Cu, As, and Pb
concentrations of bryophyte were extremely high as well as high Zn, Cu, As, and Pb concentrations of stream
water and high bio-concentration factor for bryophyte was maintained.
Keywords: Oxygen isotope, hydrogen isotope, bryophyte, river waterbryophyte along streams which excluded sewage
and agric ultural seepa ge, data for me tal
contaminations of bryophyte and stable isotope
values of precipitation were accumulated andmapped. In particular, in the eastern part of
Okayama and Tottori Prefectures connecting theJapan Sea with the Inland Sea, it is possible toanalyze the influence of the Japan Sea on isotope ofprecipitation [2], [3]. The area also includes the
Ningyotouge uranium mine [9], the Yanahara pyrite
mine [10] and the Waidani copper mine [11] so it
was selected as a study area shown in Fig.1.

INTRODUCTION
Oxygen and hydrogen stable isotopic ratios ofprecipitation change with their distance from the sea,
altitude, latitude, amount of precipitation andtemperature [1], [2], [3]. The stable isotopic ratio of
precipitation is useful for estimating recharge area
and groundwater resources such as spring water andgeothermal water and is important to the mapping of
precipitation. Although the stable isotopic ratios ofprecipitation change with each precipitation event,stable isotopic ratios of river water are uniform
values relative to those of precipitation because of
the homogenization for precipitation. Stream water
is a representative of precipitation for small rivercatchment [4], [5].
Bryophyte grows slowly and accumulates heavy
metals relative to other life by a high bioconcentration process. Therefore, bryophyte heavy
metal concentration along streams is deemed usefulfor estimating river metal contamination, geologicalcondition and metal waste water in river catchment[6], [7], [8].
Streams are upper catchment and are generally
not influenced by human activity. Therefore, neither
sewage water nor agricultural seepage flows into
streams. Then, in this study, using stream water or

METHOD
Stream water and bryophyte along streams were
sampled from 2012 to 2016. Measurement of δD andδ18O for sampled water was carried out using an
isotopic ratio measurement system (Sercon Geo Wet
System). δD and δ18O are presented in per mil (‰)
of the standard average seawater (SMOW: Standard
Mean Ocean Water). The formulas are shown inequation (1) and (2). δD and δ18O of SMOW aredenoted as (D/H) SMOW, (18O/16O) SMOW and δDand δ18O of sample are denoted as (D/H) Sample,
925

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig.2 distributions of oxygen stable isotopic valuesof stream water.

Fig.1 distributions of hydrogen stable isotopic valuesof stream water

RESULTS AND DISCUSSION

-30
-35
-40

δD( ‰)

IsotopeδD=8×δ18O+10

Fig.2 and 3 show the distributions of oxygen andhydrogen stable isotopic values of stream waters
along the Yoshiikawa and Tenjinkawa rivers. Bothresults show the minimum values around thewatershed (W line as shown in Fig 2 and 3), between
the Yoshiikawa River and Tenjinkawa River in thenorth of map, were found and isotope values
increased gradually, apart from the mountain peak.
In particular, maximum values were found aroundthe Inland Sea. There are many small mountains
between the Inland Sea and the watershed as well asvery complicated topographic features. Point B was
Tsuyama Basin and its altitude was low relative tothe areas. Fig.4 shows the relation between oxygenand hydrogen isotopic ratios. From Fig.4, isotopic
values were distributed between the meteoric line (δD = 8×δ18O +10) and δD = 8×δ18O +20 andthe distribution had common values [2], [3].
Generally, the oxygen and hydrogen stable
isotopic ratios of precipitation changes with theirdistance from the sea and altitude [1], [2], [3], [5].
Although complicated features and a basin were
found, both isotope values decreased with distancefrom the Inland Sea. Southward wind or cloud was
mainly thought to control isotope values and as aresult, the influence of the Japan Sea on isotopes ofprecipitation was low. Southward wind or cloudmust pass across Shikoku Island before it passes
across the study area, therefore isotopic values were
thought to be low relative to Wakayama and thesame as Nara area [4].

-45
-50
-55
-60
-65
-70
-10

-9

-8

-7

-6

-5

δ18O( ‰)
Fig.3 Relation between oxygen and hydrogenisotopic ratios(18O/16O) Sample. Measurement error of δD is±1.0 ‰ and measurement error of δ18O is ±0.1 ‰.
δD = [(D/H) Sample/(D/H) SMOW-1] ×1000: (1)δ 18O = [(18O/16O) Sample/ (18O/16O) SMOW-1]
×1000:(2)
Sampled bryophyte were dried then dissolved
with concentrated nitric acid solution. The solution,
after filtration with 0.45 micrometer and stream
water sample, were analyzed for metal concentration
by ICP-AES (Inductively Coupled Plasma Atomic
Emission Spectroscopy, SPS1700HVR ; Seiko
Instruments Inc.).

926

SEE - Nagoya, Japan, Nov.12-14, 2018

Zn ppmdry weightAs ppmdry weight51~100101~200
501~1000
1001~5000

Y

Zn

Waidani

5001~
10000
10001~

bryophyte

Cu ppmdry weightPb ppmdry weight

1~20

0
1~10
11~20

21~200201~500
501~1000
1001~
5000
5001~
10000
10001~

21~50
51~
100
101~
200

201~
300

bryophyteAs201~500

B

bryophyte

Fig.4 distribution of Zn, Cu,
concentrations for river f bryophyte

1~50

N

0~5
6~10
11~30
31~50
51~100
101~
500
501~

and

bryophytePb

concentrations of river bryophyte around thewatershed area were low, less than 20 ppm. Aroundthe Tsuyama Basin and the Yanahara mine, Znconcentrations were 20 to 500 ppm. In contrast, Cu
concentrations of river bryophyte around the
Waidani mine area were over 500 ppm and the
maximum value reached over 10,000 ppm.
As concentrations of river bryophyte around thewatershed area (Ningyotouge uranium mine) were
low, less than 10 ppm and less than 30 ppm aroundthe Tsuyama Basin and the Yanahara mine
excluding the Waidani mine area. However, Asconcentrations of river bryophyte around the
Waidani mine area were over 50 ppm and the
maximum value reached over 500 ppm.
Pb concentrations of river bryophyte around thewatershed area were low, less than 20 ppm andfound to be from 20 to 100 ppm around the Tsuyama

Metal concentration of bryophyte
Fig.4 shows distributions of Zn, Cu, As and Pb
concentration for river bryophyte. Excluding the
Waidani mine area in the southeast of the study area,
Zn concentrations were 1 to 200 ppm. In particular,
Zn concentrations of river bryophyte around thewatershed area (Ningyotouge uranium mine, N)
were low, less than 100 ppm. Around the Tsuyama
Basin, (B) and the Yanahara mine (Y), Zn
concentrations were 200 to 500 ppm. On the other
hand, Zn concentrations of river bryophyte around
the Waidani mine area were over 500 ppm and the
maximum value reached over 10,000 ppm.
Excluding the Waidani mine area, Cu
concentrations were 1 to 200 ppm. In particular, Cu
927

SEE - Nagoya, Japan, Nov.12-14, 2018

100000

Cu ppm Pl ant

Waidani mine area
There are some small scale closed copper minesin the Waidani Valley at the northeast of Wake
which were operated until 70 years ago. Tailings
containing ores and slag which were disposed ofalong the top of a local valley with no protection.
Pyrite FeS2, sphalerite ZnS, chalcopyrite CuFeS2 andarsenopyrite FeAsS and galena PbS were found in
the tailings and Zn, Cu, Pb, and As contamination
was suspected. River water originated from thetailings seepage [11].
At the top of the valley, there are large tailingplaces from which the south and north rivers
originated. The upstream, middle and downstream ofthe south river are WSU, WSM and WSD and thelength was 4 km. The sampling points from the
upstream to downstream of the north river are WNT,
WNH, WNU, WNM and WND and the length was 3
km. WNT is spring from the tailing. WNH is head ofriver with no tailing and WNU is a stream after
100000

10000

1

1000

0. 1

100
W
N
T

W
N
H

W
N
U

W
N
M

W
N
D

W
S
U

W
S
M

W
S
D

1

0. 1

0. 1

0. 01
W
N
T

W
N
H

W
N
U

W
N
M

W
N
D

W
S
U

W
S
M

W
S
D

W
N
H

W
N
U

W
N
M

W
S
M

W
S
U

W
N
D

W
S
D

0. 001

Cu Fi l t er ed ( mg/l )Tot al Cu ( mg/L)

1
Fi l t er

0. 1

0. 1

0. 01

0. 01

0. 001
W
N
T

W
N
H

W
N
U

W
N
M

W
N
D

W
S
U

W
S
M

W
S
D

0. 001

Fig.8 total and soluble Cu concentration of river
river with no tailing and WNU is a stream after
WNT and WNH streams join [11].
Fig.5 shows Zn concentration for river
bryophyte and river water at the the Waidani area.
Zn concentration for river bryophyte was over 500
ppm and in particular reached 10,000 ppm besidetailings. Zn concentration for river bryophyte
decreased with downstream and 1,000 ppm at 3 km
and 900 ppm at 4 km from the tailing. Total Zn
concentration of river water also decreased fromabout 2 mg/l to 0.03 mg/l with down the stream
which exceeded the Japanese Environment Standard
for rivers (0.03 mg/l) [11]. Therefore, Znconcentration for river bryophyte changed with total
Zn concentration of river water.
Fig.6 shows total and soluble Zn concentrationsof river water at the Waidani area. Soluble
concentration was filtered with a 0.45 micrometer.
Both concentrations were almost the same so Zn
migrated in soluble style while river bryophyte
directly is thought to have absorbed Zn from riverwater. Therefore, the Zn concentration of river
bryophyte changed with the Zn concentration ofriver water. The bio-concentration factor for Zn is10,000 from Zn concentration of river bryophyte andriver water at the Waidani area assuming 1 L = 1kg.

Tot al Zn ( mg/L)

Zn Fi l t er ed ( mg/l )

1

0. 01

Tot al10
Fi l t er

1000

1

Fig.5 Zn concentration for bryophyte and river water
Tot al

0. 1

Fig.7 Cu concentration for bryophyte and river water

0. 01

10

10000

W
N
T

Tot al Zn ( mg/L)

Zn ppm Pl ant

Ri verRi ver100

10
Pl ant1
Pl antTot al Cu ( mg/L)

Basin, the Yanahara mine and the Inland Sea
excluding the Waidani mine area. However, Pb
concentrations of river bryophyte around the
Waidani mine area were over 59 ppm and the
maximum value reached 300 ppm.

0. 01

Fig.6 total and soluble Zn concentration of river
928

SEE - Nagoya, Japan, Nov.12-14, 2018

100

0. 01

10

0. 001

W
N
U

W
N
M

W
N
D

W
S
U

W
S
M

W
S
D

Tot al

0. 05

0. 05

0. 04

0. 04

0. 03

0. 03

0. 02

0. 02

0. 01

0. 01

0
W
N
M

W
N
D

W
S
U

W
S
M

W
S
D

W
N
M

W
N
U

W
S
D

W
S
M

W
S
U

W
N
D

0

Fig.11 Pb concentration for bryophyte and river
water
1

1
Tot alAs Fi l t er ed ( mg/l )

0. 06

W
N
H

W
N
T

0. 07

0. 06

W
N
U

0. 05

100

0

0. 08
Fi l t er

W
N
H

150

0. 0001

Tot al Pb ( mg/L)

Pb Fi l t er ed ( mg/l )

0. 08

W
N
T

0. 1

Ri ver50

Fig.9 As concentration for bryophyte and river water

0. 07

200

Fi l t er

0. 1

0. 1

0. 01

0. 01

0. 0010

Tot al As ( mg/L)

1
W
N
H

Pl antRi verPl antW
N
T

250

Tot al Pb ( mg/L)

0. 1

Pb ppm Pl ant

1000

0. 15

300

Tot al As ( mg/L)

1

As ppm Pl ant

10000

W
N
T

W
N
H

W
N
U

W
N
M

W
N
D

W
S
U

W
S
M

W
S
D

0. 001

Fig.12 total and soluble Pb concentration of riverFig.10 total and soluble As concentration of riverof river bryophyte changed with total or soluble Cu
concentration. The bio-concentration factor for Cu is
10,000 from Cu concentration of river bryophyte
and river water at the Waidani area assuming 1 L =
1kg [7]. Excluding the Waidani area, Cu
concentration of river water was very low, less thandetection limit, 0.001 mg/l and then the bioconcentration factor for Cu excluding the Waidani
area could not be calculated.
Fig.9 shows As concentration for river bryophyte
and river water at the Waidani area. As
concentration for river bryophyte was over several
tens ppm and in particular reached 1,000 ppm besidetailings. As concentrations for river bryophyte
decreased going downstream from 1,000 ppm to 10
ppm at 3 km and 4 km from the tailing. Total As
concentration of river water did not clearly decrease
going downstream and ranged from 0.001 to 0.2
mg/l which was over the Japanese Effluent Standard
for river (0.1 mg/l) [11].
Fig.10 shows total and soluble As concentrationsof river water at Waidani area. Both concentrations
were almost the same, so it is thought that As
migrated in soluble style and river bryophyte isthought to have directly absorbed As from riverwater. Therefore, As concentration of river
bryophyte changed with As concentration of riverExcluding the Waidani area, the Zn concentration ofriver water was very low, less than 0.005 mg/l andZn concentration of river bryophyte were 1 to 200
ppm. The bio-concentration factor for Zn excluding
the Waidani area ranges from 200 to 40,000
however almost it coincided with the calculated
values at the Waidani area.
Fig.7 shows Cu concentration for river bryophyte
and river water at the Waidani area. Cu
concentration for river bryophyte was over several
hundred ppm and in particular reached 10,000 ppm
beside tailings. Cu concentration for river bryophyte
decreased with downstream and 600 to 1,000 ppm
at 3 km and 200 to 800 ppm at 4 km from the tailing.
Total Cu concentration of river water also decreased
from about 0.2 mg/l to less than 0.01 mg/l down thestream. Although these values were less than theJapanese Effluent Standard (3 mg/l) [11], Cu
concentration for river bryophyte changed with total
Cu concentration of river water.
Fig.8 shows total and soluble Cu concentrationsof river water at the Waidani area. Bothconcentrations were not always the same and total
Cu concentration was often higher than soluble Cu
concentration. Cu migrated by soluble and particle
style down the steam. Therefore, Cu concentration
929

SEE - Nagoya, Japan, Nov.12-14, 2018

water. The bio-concentration factor for As is 1,000
to 10,000 from As concentration of river bryophyte
and river water at the Waidani area assuming 1 L =1kg. Excluding the Waidani area, the Asconcentration of river water was very low, less thanthe detection limit, 0.001 mg/l and then the bioconcentration factor for As excluding the Waidani
area could not be calculated.
Fig.11 shows Pb concentration for river
bryophyte and river water at the Waidani area. Pb
concentration for river bryophyte was over several
tens ppm and in particular reached 50 to 300 ppm
around tailings. Pb concentration for river bryophyte
decreased going downstream to 50 ppm ~ 100 ppm
at 3 km and less than 50 ppm at 4 km from thetailing. Total Pb concentration of river water did not
clearly decrease going downstream and ranged fromless than 0.001, detection limit to 0.07 mg/l which
was less than the Japanese Effluent Standard forriver (0.1 mg/l).
Fig.12 shows total and soluble Pb concentrationsof river water at the Waidani area. Bothconcentrations were not always the same and total
Pb concentration was often higher than soluble Pb
concentration. Pb migrated in soluble and particle
style down the steam. Therefore, Pb concentration ofriver bryophyte changed with total or soluble Pb
concentration. The bio-concentration factor for Pb isvariable, 20,000 to 40,000 at the Waidani area
assuming 1 L = 1kg [7]. Excluding the Waidani area,
Pb concentration of river water was very low, lessthan the detection limit, 0.001 mg/l therefore thebio-concentration factor for Pb excluding Waidani
area could not be calculated.

concentrations of bryophyte were extremely high aswell as high Zn, Cu, As, and Pb concentrations ofstream water and high bio-concentration factor forbryophyte was maintained [7].
REFERENCES[1] Sakai H. and Matsihisa Y., Stable Isotope
Geochemistry, University of Tokyo Press. 1996. PP.
93-100.
[2] Mizota C. and Kusakabe M., Spatial distribution ofδD-δ18O values of surface and shallow groundwatersfrom Japan, south Korea and east China,
Geochemical Journal, Vol.28, 1994, pp.387-410.
[3] Machida I. and Kondo A., Stable Isotope Ratios of
Natural Water in Japan, J. Japan Soc. Hydrol. &Water Resour. Vol. 16 No.5, 2003, pp.556-569.
[4] Ishizuka M., Sone Y., Ii H. and Hirata T., Effect ofenriched early dropped rainwater on mesoscaleisotopic distribution in surface water on the Kii
Peninsula, Japan, Water Resources Research, Vol.42,
W12410, 2006, pp.1-16.
[5] Clark I. and Fritz P, Environmental Isotopes inHydrogeology. New York: Lewis Publisher, 1999, ch.
1, 2, 3 and 4.
[6] Debéna S., Aboala J.R., Carballeiraa A., Cesab M.
and Fernándeza J.A., Monitoring river water quality
with transplanted bryophytes: A methodologicalreview, Ecological Indicators 81 (2017) 461–470.
[7] Kubohara T and H. Ii, “Evaluation of metal
contamination for river using bryophyte in the
Kinokawa River catchment”, International Journal of
GEOMATE, Vol. 13, Issue 37, Sep., 2017, pp. 108115..
[8] Satake K., Shibata K. and et al., “Copper
accumulation and location in the moss Scopelophila
cataractae”, Journal of Bryology, Vol.15, Issue 2,
1988, pp.353-376.
[9] The Geological Survey of Japan and Atomic Fuel
Corporation, Prospecting and development of
Uranium Deposits of Ningyo-touge Uranium Field inJapan, Mining Geology, Vol.14, No.63, 1964, pp.110.
[10] Mitsuno C. Nureki T. Sugita M. and Asami M.,
Geology and Modes of Occurrence of Iron Sulfide
Deposits in the Yanahara Mining District, Mining
Geology, Vol.25, No.5, 1975, pp.331-345.
[11] Ii H. and Nishida A., Effectiveness of using river
insect larvae as index of Cu, Zn, and As
contaminations in rivers, Japan, International Journalof GEOMATE, Vol. 12, Issue 33, May, 2017, pp.
153-159.

CONCLUSION
Stream water is representative of precipitation
for small river catchment so stream water was
sampled and analyzed. A distribution map of oxygenand hydrogen stable isotopic stream water values
along the Yoshiikawa and Tenjinkawa rivers showthat isotope values decreased with distance from theInland Sea implying that southward wind or cloud
was mainly controlled isotope values and that the
influence of the Japan Sea on isotope ofprecipitation was low.
Bryophyte along streams was also sampled at thesame time of stream water sampling. A map for Zn,
Cu, As, and Pb concentrations of bryophyte showsthat metal concentrations of stream bryophytearound the watershed area (Ningyotouge uraniummine, N) were low and around the Tsuyama Basin,(B) and the Yanahara mine (Y), metal
concentrations were medium relative to those of theother areas excluding the Waidani mine area. In the
Waidani mine area, Zn, Cu, As and Pb

930

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

REDUCTION OF NUTRIENTS IN PUBLIC MARKET WASTEWATER
BY PHYCOREMEDIATIONRadin Maya Saphira Radin Mohamed1*, Alfituri Ibrahim Abdullah Abuala2, Najeeha Mohd. Apandi3, Adel AlGheethi4 , Aisha A. Amhimmid Alqantosh5 and Amir Hashim Mohd. Kassim6
1,2,3,4,5,6

Micro-pollutant Research Centre (MPRC), Department of Water and Environmental Engineering, Facultyof Civil & Environmental Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat,
Johor, Malaysia.

ABSTRACT
Phycoremediation using microalgae has high potential for reducing nutrient load in public market wastewater(PMW). However, the reduction efficiency depends on the initial concentrations of microalgae and PMW. In thepresent study, the reduction of total nitrogen (TN), total phosphorus (TP), and total organic carbon (TOC) in
PMW using Scenedesmus sp., was investigated as a function of different PMW concentrations. Scenedesmus sp.
was inoculated with 106 cell/mL into 500 ml of PMW and incubated outdoors under full sunlight for 19 days.
The results revealed that higher microalgae growth was recorded in PMW than in Bold’s basal medium (BBM).
The maximum reduction values of nutrients were 91.51% for TN, 92.67% for TP, and 90.2% for TOC wereachieved by 50% of PMW. The findings indicated that phycoremediation with Scenedesmus sp. can successfully
reduce the nutrient load of PMW.
Keywords: Public Market Wastewater, Scenedesmus sp., Phycoremediation,
Besides, the microalgae biomass generated
during the phycoremediation process has several
applications as biofuel, biodiesel, fish feed,
fertilizer, pharmaceuticals, and cosmetic ingredients[8]. Furthermore, phycoremediation with masscultured microalgae is cheaper than conventional
aerobic wastewater treatment systems because of its
low energy input, initial capital cost, and operational
cost [9]. Wastewater from the dairy industry andmunicipal waste, and industrial wastewater havebeen previously used as a microalgae production
medium [7], [10], [11]. In this research, the growthof Scenedesmus sp. and nutrient reduction indifferent concentrations of PMW were investigated.

INTRODUCTION
Wastewater is a general term that refers tovarious types of liquid wastes generated throughactivities that utilize massive volumes of water [1].
The source of wastewater determines the final
characteristics of wastewater [2]. For instance,
public market wastewater (PMW) contains highlevels of organic matter (> 600 mg/L of biochemical
oxygen demand [BOD]) and solids derived fromfish, meat, poultry, vegetable, and fruit residues;
PMW is thus classified as highly polluted
wastewater [3]. Fresh foodstuff, poultry waste
scraps, and fish entrails contain high concentrationsof total nitrogen (TN), total organic carbon (TOC),
and total phosphorus (TP) which contribute
effectively to the contamination of PMW [4]. TP and
TN concentrations in PMW reached up to 25 mg/L
and 61 mg/L, respectively, as a result ofcontamination with blood residues from meat, fish,and poultry processing [5]. Therefore, the directdischarge of PMW into natural water bodies
contributes in the water pollution and promotes
eutrophication [5]. Hence, PMW must be treated forthe removal of organic matter, nutrients, pathogens,and heavy metals prior to its final discharge into theenvironment.
Amongseveralwastewater
treatment
technologies, phycoremediation is one of the mostefficient techniques for PMW because the highnutrient load of PMW supports microalga growth
rates and thus improve nutrient uptake [6], [7].

MATERIALS AND METHODSPMW Collection
PMW was collected at Pasar Awam Rengit,
Jalan Kampung Rengit Laut, Rengit, 83100 Rengit,
Johor, Malaysia (1.67757, 103.14563). The pH,
BOD, chemical oxygen demand (COD), totalsoluble solids (TSS) TN, TP, and TOC of the PMW
samples were determined according to APHA
(2005).
Scenedesmus sp. Culturing
Scenedesmus sp. was refreshed by sub-culturing
in autoclaved Bold’s Basal Medium (BMM),(Bischoff and Bold, 2003). The culture medium was
931

SEE - Nagoya, Japan, Nov.12-14, 2018

COD
TN
TP
TOC

incubated at room temperature for 8 days prior for
use in phycoremediation.
Experimental Setup

3432
968
178
1798

50
5
-

100
10
-

Note: (−) Not detectable. All parameters, except for
pH, are expressed in mg/L.

The experiment was set up in a 1 L Erlenmeyer
flask containing 500 mL of PMW. BBM was used as
the control medium. PMW samples were filtered anddiluted with distilled water to produce five different
concentrations (10%, 25%, 50%, 75%, and 100%).
Scenedesmus sp. was inoculated with 106 cell/mL.
The phycoremediation process was conducted
outdoors under full sunlight for 19 days. Each flask
was shaken twice a day to prevent sedimentation.

It can be noted that raw PMW with 10%, 25%,
50%, 75% and 100% dilutions have high BOD and
COD levels of 222–1208 and 443–3432 mg/L,
respectively, while TN and TP were 968 and 178
mg/L, respectively. These values are higher than
BOD levels of 85.39–92.62 and 71–122 mg/L
reported by previous studies [17], [18]. The highconcentrations of COD and BOD might be related tothe presence of organic materials in PMW which
differ seasonally and geographically [19].

Scenedesmus sp. Growth
The growth of Scenedesmus sp. was estimated by theharvesting of cell biomass from the culture medium
using centrifugation at 4000 rpm for 5 minutes. The
supernatant was discarded while the algal pellets
were suspended in 45 mL of autoclaved and filtersterilized Gillard's F\2 solution. A fixed volume of
10 mL aliquots was taken from the suspended
solution and transferred to cuvettes. The opticaldensity of the Scenedesmus sp. growth wasestimated at 650 nm (OD650) in a DR 6000
spectrophotometer (Janway, USA). Gillard's F\2solution was used as the blank [15], [16].

Growth of Scenedesmus sp.
The growth of Scenedesmus sp. in different
concentrations (10%, 25%, 50%, 75% and 100%) of
PMW is depicted in Fig. 1.

Nutrient Removal
The reduction of TP, TN, and TOC wasdetermined according to Eq. 1 [12,13,14].
��������� (%)

�� − ��
)��× ��� %=(RESULTS AND DISCUSSION

Fig. 1: Growth of Scenedesmus sp. in PMW during
phycoremediation(�)The highest growth rate was recorded in 50%
PMW on day 14 of phycoremediation. OD650
increased from 0.112 to 0.2923 from day 1 day to
day 14 and decreased to 0.228 on the 19th day ofphycoremediation. The results of the present
research corresponded with those reported by Chen[3], who indicated that optimum Chlorella growth
was observed in 50% piggery wastewater.
Meanwhile, the microalga growth in 25% and
75% PMW reached the maximum values of 0.266
and 0.271 on day 11 and day 14 ofphytoremediation, respectively, and decreased
thereafter. In contrast, microalga growth rates in
10% and 100% PMW were 0.182 and 0.169,
respectively, and decreased after day 11 and day 6 ofphycoremediation, respectively. This behavior may
be attributed to the low nutrient content of 10%
PMW or to the excessive nutrient content of 100%
PMW, as shown in Table 1. These results indicate

PMW Characteristics
Seven parameters were tested to characterize
PMW samples. These parameters were selectedaccording to the Environmental Quality Act (1974),
Regulation 2009). The characterization data of
PMW are shown in Table 1.
Table 1: Characteristics of public market wastewater(PMW) in comparison with effluent
standards and previously reported values.
Parameter

PMW conc.

pH
BOD

7.5
1208

Effluent standard (Environmental
Quality Act, 1974)
Standard A
Standard B
6.0–9.0
5.5–9.02050

932

SEE - Nagoya, Japan, Nov.12-14, 2018that the PMW had high nutrient loads and should be
subjected to the dilution process before thephycoremediation process. Furthermore, microalga
growth rates in BMM, the control medium, were0.112 and 0.228 on day 0 and day 19 of cultivation.
The maximum value of microalga growth in BBM
was 0.234 which was observed on day 13 ofcultivation. Therefore, microalga can be successfully
cultured in different concentrations of PMW.

In this study, the removal rates of TN, TOC, andTP were used as indices of nutrient removal by
Scenedesmus sp.. Table 2 shows that in 50% PMW,
TN
levelsdecreasedby
91.51%
after
phycoremediation
with
Scenedesmus
sp.
Accordingly, TN levels dropped from 613 mg/L to
52 mg/L in 50% PMW. By contrast, TN levels in thecontrol decreased by 14.68% from 613 mg/L to
523.01 mg/L in the control samples. TN removal
rates in 10%, 25%, and 75% PMW were 85.3%,
88.6% and 70.7% respectively. The lowest TN
removal rate was 57.49% which was observed in
100% PMW. This result may be attributed to thenegative growth rate of the alga. However, TP
removal rates in 50% PMW was 92.67%.
Specifically, TP levels decreased from 111.84 mg/L
to 8.19 mg/L after phycoremediation. TP removal
rates in the control, 10%, 25%, 75%, and 100%
PMW were approximately 22.01%, 75.6%, 91.16%,
79.34%, and 62.92% respectively. In 50% PMW,
TOC decreased from 1022.03 mg/L to 100.08 mg/L.
This decrement is equivalent to a reduction of 90.2%(11.14 ± 0.96% in the control). Meanwhile, TOC
removal rates in 10%, 25%, and 75% PMW were
80.97%, 86.51%, and 77.91% respectively. The
lowest TOC removal rate was observed in 100%
PMW, in which TOC levels decreased from 1798.22
mg/L to 897.23 mg/L (50.10%). These phenomena
may be attributed to the different nutrient loads
associated with different PMW concentrations.
Overall, phycoremediation using Scenedesmus
sp. successfully removed TN, TP, and TOC from
PMW. In a previous study, Jais [17] found that
Scenedesmus sp. was able to remove TN, TP, and
TOC from PMW at the rates of 73.01%, 76.77%,
and 71.73%, respectively

F. conc.
(mg/L)

10 %
25 %
50 %
75 %
100 %

223
396
613
758
968

TN
32.76
45.13
52
222.07411.43

Removalpercentage(%)

Control
(%)

85.30
88.60
91.51
70.703
57.49

14.14
19.69
14.68
15.39
12.39

10 %
25 %
50 %
75 %
100 %

389
697
1022.03
1458
1798.22

TP
8.07
5.20
8.19
32.64
66
TOC
74
94.02
100.08322.01897.2375.60
91.169
92.67
79.34
62.92

21.58
17.65
22.01
22.70
11.59

80.97
86.51
90.20
77.91
50.10

23.33
15.50
11.14
24.48
20.92

CONCLUSION
The present study demonstrated that different
PMW concentrations affect the efficacy of nutrient
removal from wastewater using phycoremediation
with Scenedesmus sp. The highest nutrient removal
rates were observed in 50% PMW. Therefore, thePMW concentration must not exceed 50% tofacilitate phycoremediation effectively. Furthermore
TN, TOC, and TP removal rates in 50% PMW were
91.51%, 90.20%, and 92.67%, respectively. To
conclude, phycoremediation with microalgae
represents the best biological wastewater treatment
process given its low cost.
ACKNOWLEDGEMENTS
The authors wish to thank the Ministry of Science,
Technology and Innovation (MOSTI) for funded
this research through the E-Science Fund S029 (0201-13-SF0135). They are also immensely grateful to
the Research Management Centre (RMC), UTHM
through the IGSP U682 grant.
REFERENCES[1] Pahazri, Nor Fadzilah, R. M. S. R. Mohamed, A.
A. Al-Gheethi, and Amir Hashim Mohd Kassim.,
Production and harvesting of microalgae biomass
from wastewater, Environmental Technology
Reviews, Vol. 5, Issue 1, 2016, pp. 39-56.
[2] Eriksson, Eva, Karina Auffarth, Mogens Henze,
and Anna Ledin., Characteristics of grey
wastewater. Urban water, Vol. 4, Issue 1, 2002,
pp. 85-104.
[3] Chen, Zhuo, Huu Hao Ngo, and Wenshan Guo.,
A critical review on the end uses of recycledwater. Critical reviews in environmental scienceand technology, Vol. 43, Issue 14, 2013, pp.
1446-1516.
[4] Apandi, Wan Mohamad, Wan Asma, and Hazel
Monica Matias Peralta., Removal of nutrientsand selected heavy metals in wet market
wastewater by using microalgae scenedesmus sp.
In Applied Mechanics and Materials, vol. 773,

Table 2: Nutrient removal efficiency as a function of
PMW concentration
Int. conc.
(mg/L)

33.08
58.96
111.84158.03178

Note: Int. conc.: initial concentration and F. conc.:
final concentration.

Nutrient Removal Efficiency of Scenedesmus sp.

PMW
Concentration

10 %
25 %
50 %
75 %
100 %

933

SEE - Nagoya, Japan, Nov.12-14, 2018

Trans Tech Publications, Vol. 773-774, 2015, pp.
1210-1214.
[5] Jais, Noor Maisara, R. M. S. R. Mohamed, A. A.
Al-Gheethi, and MK Amir Hashim., The dual
roles of phycoremediation of wet market
wastewater for nutrients and heavy metals
removal and microalgae biomass production.
Clean Technologies and Environmental Policy,
Vol. 19, Issue 1, 2017, pp.37-52.
[6] Rawat, I., R. Ranjith Kumar, T. Mutanda, and F.
Bux., Dual role of microalgae: phycoremediationof domestic wastewater and biomass production
for sustainable biofuels production. Applied
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[7] Gani, Paran, N. M. Sunar, H. Matias-Peralta,
Abdul AA Latiff, and A. R. A. Razak., Influenceof initial cell concentrations on the growth rate
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[8] Eloka-Eboka, Andrew C., and Freddie L.
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[10] Chokshi, Kaumeel, Imran Pancha, Arup Ghosh,and Sandhya Mishra., Microalgal biomass
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towards
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[11] Umamaheswari, J., and S. Shanthakumar.,
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[12] Malla, Fayaz A., Shakeel A. Khan, Gulshan K.
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934

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

AMOUNT OF PRECIPITATION ON TOPOGRAPHY FROM OSAKAPLAIN TO NARA BASIN ACROSS IKOMA MOUNTAINS, JAPANHiroki Nishiwaki1 and Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan
2
Faculty of Systems Engineering, Wakayama University, Japan

1

ABSTRACT
Water vapor content is important parameter for high precipitation phenomenon in around mountain andmountain shadow area. When rain cloud with rich vapor or wet air met the mountain, new rain cloud occurs andgrows around the mountain. Grown rain cloud cross mountain and goes to mountain shadow area. Grown cloud
did not disappear quickly and dropped a lot of rain to mountain shadow. As a result, in the mountain and mountainshadow area, amount of precipitation is higher than that around the area. Therefore, amount of precipitation in theslope of Ikoam Mountains increased with topography that collected a lot of water vapor where high slope ofmountain or recessed to the east side. When rain cloud or air comes from western where clouds do not meet anothermountain before the Ikoma Mountains during from April to June, amount of precipitation increased from the Ikoma
Mountains to Nara Basin because rain cloud or air was wet.
Keywords: Precipitation, Water vapor content, Mountain, Mountain shadow area.

occurred around the Rokko Mountain and there
localized heavy rain in Kyoto City, 50 km from the
Rokko Mountain [5]. Such localized heavy rain
occurs most of region in Japan [6]. Then, it isnecessary to clearly influence of cloud grown aroundthe mountain that amount of precipitation behind themountain. Therefore, in this study, the purpose is toclarify the relation between amount of precipitationand topography and then rain sample was sampledfrom the Osaka Plain to the Nara Basin across the
Ikoma Mountains covering big topography change.

INTRODUCTION
It is known that amount of precipitation increased
with altitude in mountain [1]. Increase in precipitation
is different for each mountain. In Nagano andYamanashi prefecture, Japan, amount of precipitation
every event increased from 5 to10 per cent with 100
m in higher [2] and in Yamagata and Fukushima
prefecture, Japan, increased from several per cent to20 per cent with 100 m in higher [3]. When air or
cloud crosses mountains in land, updraft brings out at
the mountain and new cloud occurs and rain cloud
grows. Grown rain cloud drops lot of rain aroundmountain. In other hand, amount of precipitation in
the Owase, Japan didn’t increase in mountain [4].
Thus, relationship topography and precipitation has
not been clarified because topography of mountain iscomplicated. Grown cloud drops to region far fromthe mountain. On 15th October, 1998, Liner rain band

METHOD
Topography of Osaka Plain, Ikoma Mountains
and Nara Basin and Analysis
Fig. 1 shows location of study area. This study
area was between from the Osaka Plain to the Nara
Basin cross the Ikoma Mountains in Osaka prefecture
and Nara prefecture, Japan. The Osaka Plain is the
topography among sea and three mountains. The
Ikoma Mountains is located in the north-south
direction on the border of Osaka and Nara prefecture
and the altitude of many mountain peaks is 300 m to
400 m. The Nara Basin is located at the east of the
Ikoma Mountains and is surrounded by mountains all
direction. Fig.2 shows location of sampling point andobservation stations for Japan Weather Association.
In this study, two types of data were used for amountof precipitation. First type of data was sampling data
and there were 25 rain gauged points from the eastern
Osaka to the Nara Basin cross the Ikoma Mountains.
There were 4 sampling points north of 34°41′

Fig. 1 Location of study area

935

SEE - Nagoya, Japan, Nov.12-14, 2018

north longitudes are called North-1 to North-4 inorder from west. There were 11 sampling points from34 ° 39 ′ to 34 ° 41 north longitudes are called
Center-1 to Center-11 in order from west. There were
10 sampling points south of 34 ° 39 ′ northlongitudes are South-1 to South-10 in order fromwest. Rain sampling was performed 24 times by every
precipitation from January to June in 2018. Sampler
was 500 ml bottle. Wide mouth of sampler, 61.0 mm
in diameter. Amount of precipitation was measured
by the following equation.
)2

P = (W⁄ρ)⁄((C⁄2There 10 points South-1 to South-10 were called
South Line.
Data of wind direction and wind speed wereobtained from JMA at Ikoma. Wind direction of each
event was obtained and was shown as 8 directions.
Cloud direction was estimate by weather chart. Cloud
direction was shown as 8 directions. Weather chart
was announced by JMA.
RESULTS AND DISCUSSION
Precipitation ratio for each sampling area× π)

In this study, precipitation ratio was used tocompare topography change. Precipitation ratio isamount of precipitation on each sampling point
divided by amount of precipitation on base point in
the Osaka Plain for comparing amounts ofprecipitation between the Osaka Plain to Nara basin.
Fig. 3 shows precipitation ratios and altitude in
North, Center and South Line. In North and Center
Line, base point was assumed Center-1. In SouthP: Amount of precipitation (mm), W: Weight (g),ρ: Density of water (10⁻³ g/mm³), C: Caliber ofSampler (61.0 mm). Second type was data observed
by JMA (Japan Weather Association) and data of
Ikoma, Nara and Yao observation stations were also
used for analysis. There 4 points North-1 to North-4
were called North Line. There 13 points Center-1 toCenter-11, Ikoma and Nara were called Center Line.

Fig. 2 Location of sampling point. Open triangles
are points observed by JMA. Open circles areNorth Line. Double circles are Center Line. Closed
circles are South Line.

Fig. 3a Precipitation ratios for North Line

Fig. 3b Precipitation ratios for Center Line

Fig. 3c Precipitation ratios for South Line
936

SEE - Nagoya, Japan, Nov.12-14, 2018of precipitation in east slope of the Ikoma Mountains
decreased with distance form peek of mountain. Six
points North-4, Center-11and from South-6 to South9 are located in the west side of Nara basin. In westside of the Nara Basin, most of precipitation ratios
showed 0.8 or more and average showed 1.2. Amountof precipitation on the east side of the Nara Basin
were about the same and higher than amount ofprecipitation on flat are of the Osaka Plain.
There 2 points Nara and South-10 are located in
the east side of Nara basin. In west side of the Nara
Basin, most of precipitation ratios for each sampling
points showed 1.0 or more and average showed 1.3
and 1.5. Amount of precipitation on east side of the
Nara Basin were higher than amount of precipitation
on west side of the Nara Basin and flat area of the east
Osaka Plain. In general, amount of precipitation
decreases with increase of distance from the sea
because vapor is not supplied to clouds from land.
Fig. 5 shows monthly precipitation from JMA
data from 2003 to 2017. Monthly precipitation on
Ikoma was the largest precipitation on other two
points and amount of precipitation on Nara werehigher than Yao where are located on the east Osaka
Plain. These results are in agreement with results ofFig. 3 and Fig. 4. Thus, from both observation andsampling data it found that amount of precipitation on
the Nara Basin were concluded to be large than thoseof the east Osaka Plain.

Fig. 4 Average of precipitation ratios for eachsampling points and altitude of topography

Relationship between precipitation ratios from
Osaka Plain to west slope of the Ikoma
Mountains and altitude
From Fig.3 and Fig.4, amount of precipitation in
the west slope of Ikoma Mountains increased withaltitude and amount of precipitation in the Nara Basinwas higher than the Osaka Plain. Thus, first, highprecipitation phenomenon in the west slope of Ikoma
Mountains was examined.
Fig.6 shows relationship between precipitation
ratio for flat area and west slope every event andaltitude. In Fig. 6, Base point was assumed to beCenter-1. Most of precipitation ratio for each point
were varied from Y = 5.7 × 10-4x +0.6 to Y = 5.7 ×
10-4x +1.2 (Y: precipitation ratio, x: Altitude) andrange of precipitation ratios was 0.6, large variety.
Amount of precipitation on the west slope of Ikoma
Mountains increased with 5.7 % per 100 m in height.
Amount of precipitation increased with altitude
because high altitude slope collects a lot of water
vapor.
On South-3 & South-4, precipitation ratios varied
from 0.9 to 1.4 and amount of precipitation were aslarge as those at the sampling points on about 400 m
in height. When air meets slope, air rises along slope.
Air temperature decreases with elevation by adiabatic
expansion and then saturated vapor pressure
decreases. When air vapor pressure is over the

Fig. 5 Average of precipitation observation by JMA
every month from 2003 to 2017
Line, base point was assumed South-1. Fig. 4 shows
average precipitation ratio for each sampling points.
Average precipitation ratios were calculated by thedata of 95% of confidence interval. Center-1 andSouth-1 points are located in flat area of the east
Osaka plain and their precipitation ratios wereassumed 1.0. There are 3 points North-3, Ikoma,
South-5 was mountain peak. Precipitation ratio inmountain peak were always 1.0 or more and average
were the highest ratio on those Line. 11 points from
North-1 to North-2 in North Line, from Center-2 toCenter-7 in Center Line and from South-2 to South-4
in South Line are called west slope of the Ikoma
Mountains. In the west slope of the Ikoma Mountains,most of precipitation ratios showed 1.0 or more andaverage showed from 1.1 to 1.4. Amount ofprecipitation in west slope increased with altitude.
Three points from Center-8 to Center-10 are locatedin east slope of the Ikoma Mountains. In the east
slope, most of precipitation ratios showed 0.9 or more
and average about 1.3. Precipitation ratios for the east
slope were less than those of mountain peak. Amount937

SEE - Nagoya, Japan, Nov.12-14, 2018

air is dry or wet.
Table. 1 Weather conditions of events when
precipitation ratio based on Center-1 for Ikoma was
1.5 or more
Date

Amount of Precipitation
AirWind
precipitation ratio on peak temperature Direction
(mm)

(℃)

Wind
speed

Cloud
Direction(m/s)

Center-1

Ikoma

Ikoma

Ikoma

Ikoma

Apr 6th

13.0

2.0

10.7

W

4.1

W
SW & WMay 2nd

7.6

1.6

16.8

W

3.5

May 18th

8.4

1.6

18.1

W

5.2

W

May 23th

8.5

1.7

14.8

NE

1.9

W

Jun 5th

44.6

1.7

15.5

E

3.0

W

Jun 6th

10.6

2.4

18.5

W

3.6

W

Jun 14th

1.8

3.4

15.8

E

2.7

SW

Many winds for high precipitation ratio event
were west and some wind directions were east andnortheast. Then, wind direction is not absoluteparameter to determine whether high or low
precipitation ratios. However, western wind caneasily come up the Ikoma Mountains slope because
the mountain direction is south to north and most of
events was thought to depend on wind direction.
On May 5th, cloud direction varied west andsouthwest because low pressure was near the study
area. For 14 events between April and June excluding
May 2nd, 6 cloud directions were southwest and 8
cloud directions were west. Most cloud directions
were west. If rain clouds come from west, rain clouds
move from the Osaka Bay to the Ikoma Mountains
across the Osaka Plain. Rain clouds go up along theslope and amount of precipitation increases aroundthe mountain area. If rain clouds come fromsouthwest, rain clouds cross the Izumikasturagi
Mountains or the Kii Mountains before the Osaka
Plain. When rain clouds cross the Izumikasturagi
Mountains and the Kii Mountains, mounts ofprecipitation increase around those mountains. After
passing through those mountains, some clouds
disappear and wet air is dried. Then, cloud direction
is one important parameter because decide whether
the cloud or air is dry or wet.
Topography that collects a lot of water vapor isimportant for high precipitation phenomenon.
Seasonal condition and cloud direction wereparameter decide whether the cloud or air is dry or
wet. Wet air makes new cloud in the slope. Therefore,high precipitation phenomenon in slope of mountain
was concluded to be caused by water vapor content.

Fig. 6 Relationship between precipitation ratio forflat area and west slope every event and altitude.
Upper broken line is Y = 5.7 × 10-4x +1.2 andLower broken line is Y = 5.7 × 10-4x +1.2.
saturated vapor pressure, raindrops occur and makerain cloud. Topography around South-3 and South-4
are recessed to the east side. When air meets recessed
topography, a lot of air vapor is gathered to center andrise along slope. A lot of air vapor makes a lot of rain
cloud. Thus, topography that collects a lot of water
vapor is important for high precipitation
phenomenon.
Relationship between high precipitation on peekof mountain and cloud direction
From Fig.6, amount of precipitation on the west
slope of Ikoma Mountains increased with altitude.
However, amount of precipitation always did notincrease because precipitation ratios had large
variety. Weather conditions of events was examinedwhen precipitation ratio for peak of mountains washigh. Therefore, in detail weather condition was
analyzed for clarifying variety of precipitation ratios.
Table 1 shows weather conditions when precipitation
ratio on Ikoma observation station was 1.5 or more.
When precipitation ratio on South-5 was high,precipitation ratio on Ikoma observation station was
also high and season of high precipitation ratio was
only from April to June. From Fig.6, differences ofmonthly precipitation between Yao and Ikoma
observation stations from March to July were higher
than those from January to March. In japan,
temperature from March to July is higher than thosefrom January to March. High temperature air has a lotof vapor and many rain drops and clouds occur on theslope of Ikoma Mountains. Seasonal condition is one
important parameter for high precipitation
phenomenon because determine whether the cloud or

Relationship between high precipitation on Nara
Basin and mountain
High precipitation phenomenon in the slope of
Ikoma Mountains was concluded to be caused bywater vapor content. Second, high precipitation
phenomenon in the Nara Basin was examined.

938

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 7 shows precipitation ratios in the CenterLine when precipitation ratio on Nara observation
station was 1.5 or more. Precipitation ratios on Naraobservation station were 1.5 or more and precipitation
ratios on Ikoma observation station were 1.5 or more
were the same day. When precipitation ratio on Ikoma
observation station was high, precipitation ratio on
Nara observation station was also high. Especially,
precipitation ratio on Nara observation station on
June 9th and June 14th was very high. Then,
relationship between cloud direction and highprecipitation phenomenon for Nara Basin was
examined. Fig. 8 shows move of rain cloud on June
14th and June 9th. High precipitation phenomenon for
the Nara Basin had two types. First type was that rain
cloud grew around mountains located on the westernof Nara and grown cloud made rain in the Nara Basin
like June 9th.
On June 9th, small size rain cloud came from west
to Nara cross the Ikoma Mountains. From 2:10 to
2:20, rain cloud met the Ikoma Mountains and rain

Fig. 7 Precipitation ratios of events when
precipitation ratio for Center Line based on Center-1
for Nara was 1.5 or more.

Fig. 8 Move of rain cloud on June 14th and June 9th. High precipitation phenomenon for the Nara Basin had
Two types
939

SEE - Nagoya, Japan, Nov.12-14, 2018

cloud grew. Grown cloud passed through Nara from2:25 to 3:00.
Second type was that strong rain cloud come fromthe eastern Nara Basin like a June 15th. On June 15th,
many big rain clouds moved from southwest tonorthwest and some small size and strong rain cloudcame from east to west. At 7:10, small size cloudgrew around the Kasatori Mountain located in theeastern Nara basin and moved to the Nara Basin.
From 8:10 to 10:10, rain cloud made a lot of rain in
the Nara Basin. After passing though the Nara Basin,
rain cloud become weak and made rain to the Ikoma
Mountains and the Osaka Plain from 10:10 to 10:40.
Both first and second type, the Nara Basin was
located as a mountain shadow. When air with richvapor met the mountain, rain cloud grew around themountain and cross mountain. Grown cloud did notdisappear quickly and made a lot of rain behind
mountain shadow. Then, water vapor content was
important parameter of high precipitation
phenomenon for mountain and mountain shadow
area.

wet. Most cloud directions were west. when
precipitation was high for mountain peak. If rain
clouds come from northwest or west, rain clouds
move from the Osaka Bay to the Ikoma Mountains
across the Osaka Plain. Amount of precipitation
increases around the mountain area. If rain clouds
come from southwest, rain clouds cross the
Izumikasturagi Mountains and the Kii Mountains
before the Osaka Plain. After passing through the
Izumikasturagi Mountains and the Kii Mountains,some clouds disappear and wet air is dried because ofrain around those mountains. Then, cloud direction is
one important parameter because decide whether the
cloud or air is dry or wet. Topography that collects a
lot of water vapor is important for high precipitation
phenomenon. Seasonal condition and cloud direction
were parameter decide whether the cloud or air is dryor wet. Wet air makes new cloud in the slope.
Therefore, high precipitation phenomenon in slope ofmountain was concluded to be caused by water vapor
content.
Second, high precipitation phenomenon in the
Nara Basin was examined. When precipitation ratio
for Ikoma was high, precipitation ratio for Nara washigh. Then, relationship between cloud direction andhigh precipitation phenomenon for Nara Basin was
examined. The Nara Basin was located mountainshadow. When rain cloud with rich vapor met themountain, rain cloud grew around the mountain andcross mountain. Grown cloud did not disappear
quickly and dropped a lot of rain to mountain shadow.
Then, water vapor content was important parameterof high precipitation phenomenon for mountain andmountain shadow area.

CONCLUSION
The purpose of study is to clarify the relation
between amount of precipitation and topography.
Then rain sample was sampled from the Osaka Plainto Nara Basin cross the Ikoma Mountains covering
big topography change.
Amount of precipitation for the Nara Basin werehigher than Osaka Plain. amount of precipitation in
the west slope of Ikoma Mountains increased withaltitude and amount of precipitation in the Nara Basinwas higher than the Osaka Plain. Thus, first, highprecipitation phenomenon in the west slope of Ikoma
Mountains was examined. Amount of precipitation on
the west slope of Ikoma Mountains increased with 5.7% per 100 m in height. Especially, amount ofprecipitation in topography recessed to the east side
were very high. High altitude slope collects a lot ofwater vapor. When air meets recessed topography, a
lot of air vapor is gathered to center and rise alongslope. Thus, Topography that collects a lot of water
vapor is important for high precipitation
phenomenon.
Amount of precipitation always did not increase
because precipitation ratios had large variety.
Weather conditions were examined when
precipitation ratio for peak of mountains was high.
Deference of monthly precipitation between flat areaand mountain peak from March to July were high. In
Japan, temperature from March to July is high andHigh temperature air has a lot of vapor and many rain
drops and clouds occur on the slope of Ikoma
Mountains. Seasonal condition is important one
parameter for high precipitation phenomenon
because determine whether the cloud or air is dry or

REFERENCES[1] Yabusaki S., Kono T., “Characteristics of stable
isotopes in precipitation at Kyoto basin”, Bulletin of
geo-environmental science, Vol. 14, 2010, pp. 23-30.
[2] Suzuki H., Nakakita E., “Analysis of Dependence of
Heavy Rainfall on Elevation Using Data Observedat Railway Stations and Meteorological Stations”,
Annual journal of Hydraulic Engineering, Vol.51,
2007, pp. 283-288.
[3] Suzuki H., Nakakita, E., “Dependence of Heavy
Rainfall on Elevation Along Railroad in Mountainous
Area”, Annual journal of Hydraulic Engineering,
Vol.54, 2010, pp .337-342.
[4] Yamada T, Hibino T, Araki T, “Statistical
Characteristics of Rainfall in Mountainous Basins”
Journal of Japan Society of Civil Engineers, No. 527,
1995, pp 1-13.
[5] Higashi K. and Fuji T., A Case Study on Local Heavy
Rainfall Observed in Kyoto City on 15 October 1998,
Kyoto Sangyo University essays. Social science series,
Vol.33, 2004, pp.86-103.
[6] Tsuguti H. and Kato T., Objective Extraction of Heavy
Rainfall Events and Statistical Analysis on theirCharacteristic Features, Tenki, Vol.61, No.6, 2014,
pp.455-469.

940

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

STUDY ON ADSORPTION PERFORMANCE OF FOOD WASTES FORVARIOUS HEAVY METALS
Keiichiro Shibata1, Hidenori Yoshida2, Tsumugi Inoue3, Matsumoto Naomichi2 and Yoshihiro Suenaga2
1
Graduate school of engineering, Kagawa university, Japan; 2Kagawa university, Japan; 3Okayama city,
Japan

ABSTRACTThe harmful materials are came to a head through the redevelopment in empty lots in recent years. The soil
and groundwater contaminations are often caused by the heavy metals and the volatile organic compounds. The
cleaning treatment water for the excavated soil and the contaminated water pumping is generated by digging andwashing the contaminated soil. The adsorption disposal by the activated carbon is conducted as the disposal method
for both contaminated water and pumped groundwater after the aeration disposal. However, the activated carbon
has a low adsorption performance for inorganic substances such as the heavy metals. Thus, in this study, the ricehusk and fish bones which are an industrial waste are focused on. The material cost is saved by using the industrial
waste. The product process of the fish bone is only burning and the rice husk is not manufactured. It is examined
whether both materials can be used as the adsorbent for the heavy metals. As the results of examinations, it isclarified that some heavy metals such as Zn2+ and Cd2+ are well adsorbed into both materials and both materials
are useful as the recycling materials.
Keywords: Soil and groundwater contamination, Fish bone absorber, Rice husk, Heavy metals

Therefore, there are many cases of groundwatercontamination by hexavalent chromium and arsenic
among heavy metals.
The cleaning treatment water for the excavatedsoil and the contaminated water pumping is generated
by digging and washing the contaminated soil. The
adsorption disposal by the activated carbon isconducted as the disposal method for bothcontaminated water and pumped groundwater after
the aeration disposal. The activated carbon is mostfrequently used as an adsorbent, it is inexpensive
compared to other adsorbents, and has an advantageof having a high specific surface area. Especially, it is
known that the activated carbon has a high adsorption
performance for organic substances such as a VOC.
However, the activated carbon has a low adsorption
performance for inorganic substances such as theheavy metals. For this reason, adsorbents such as thezeolite and the silica are used for inorganic substances,
but they have the disadvantage that the manufacturing
cost is higher than that of activated carbon. It is
predicted that the number of soil and groundwatercontamination increases with redevelopment etc. in
the future. Therefore, the adsorbent which can be
manufactured at low cost is required. Thus, in thisstudy, the rice husk and fish bones which are anindustrial waste are focused on. The material cost is
saved by using the industrial waste. The unprocessed
rice husk and only burned fish bone are used as anadsorbent in order to reduce the manufacturing cost.
Also, the adsorption performance of the rice husk andfish bone for heavy metals are examined whether both

INTRODUCTION
In recent years, the soil contamination andgroundwater contamination because harmful
materials are came to a head through theredevelopment in empty lots. According to the reportsof each prefecture's soil pollution case andgroundwater pollution case released by the Ministryof the Environment as in [1], [2], the number of bathcases has increased since 1991, when the soil
environmental standards were enacted. In particular,
the number of both cases has rapidly increased in
2002 by executing the Soil Contamination
Countermeasures Act, and the cases have increased
again in 2010 when executing the revision Soil
Contamination Countermeasures Act. The researchedcumulative number of cases is 19,927, and thecumulative number of cases that exceeds theenvironmental standard value is among 9,733 in thecase of soil contamination cases grasped by
prefectures by the end of 2014. The soil andgroundwater contaminations are often caused by theheavy metals and the volatile organic compounds(VOC). The VOC has the characteristics that it isdifficult to dissolve in water and its viscosity is low.
Thus, the VOC moves in the soil and easily reaches
the groundwater surface. On the other hand, the soil
pollution by heavy metals is difficult to spread deeply
because most of heavy metals are easily adsorbed byminerals in soil. However, the certain heavy metals
such as hexavalent chromium and arsenic are highly
soluble in groundwater, and have high mobility in soil.
941

SEE - Nagoya, Japan, Nov.12-14, 2018

materials can be used as a new adsorbent.

generated when the burning temperature falls below
400 °C. Practical realization has not progressed muchdue to the difficulty of such processing. In order topropose a new method of utilizing raw rice husk andto reduce the cost of processing, in this study, anadsorption performance of dried rice husk for heavy
metals without processing is examined (see Fig. 1).

MATERIALS AND METHODSIn this study, the rice husk and fish bone, foodwaste, are adopted as an adsorbent for the heavy
metals as has noted above. Their material properties
are explained below.
Rice husk
The rice husk is the shell of berry taken from the
spike of rice. The rice husk is covered with a wax
component which protects the surface of the organism
called the cuticle. The rice husk is hard to decompose
since the wax component shed the water. The ricehusk is shown in Fig. 1, and has the feature that about
20 percent of silica is contained. Bamboo is also said
to have a lot of silica, but even it is less than 0.1% in
the case of raw bamboo. The silica is the silicon
dioxide or the generic name of substances whichconstituted by silicon dioxide. The rice husk is very
hard and difficult to process due to the properties ofsilicic acid which is the raw material of glass
contained in chaff. The amount of rice husk emissions
is about 2 million tons annually nationwide, and mostof them are discarded as the industrial waste since theusage of unprocessed rice husk is limited. The
unprocessed rice husk has been used for packing or
seedling cover materials, but the usage as plastics
material has been increasing in recent years.
Although it is considered that the optimum processing
and utilization method of unprocessed rice husk arefew, the rice husk ash made by burning rice husk has
been studied for many uses. In Thailand, the rice husk
is used as a heat source to generate steam and power.
The rice husk ash given off from these generation isused for material of cement. As a similar technology,
the researches for making building materials forhouses from rice husk, which were developed by the
National Institute of Advanced Industrial Science andTechnology
KyushuIndustrial
Technology
Laboratory (now Kyushu Center for Industrial
Science and Technology) is conducted. After using
rice husk as a heat source, the rice husk ash, caustic
lime and glass fiber are mixed and solidified to
produce boards that can be widely used as lightweightbuilding materials for general houses such as
insulation materials. Furthermore, a study that the ricehusk ash is mixed in concrete are also conducted as in[3]. In addition, it is confirmed by the studies ofNakanoku University of Chukyo University that ricehusk ash has high adsorption rate for radioactive
materials such as the cesium and strontium.
As noted above, various usage methods arestudied for the rice husk ash, but it is necessary tocontrol the temperature at 400 ~ 600 °C and burn inorder to produce the high quality rice husk ash as in[4]. Crystallized silicic acid and dioxin may be

Fig. 1 Dried rice husk
FbA (Fishbone Absorber)
Hydroxyapatite is the basic calcium phosphate,and its chemical formula is Ca10(PO4)6(OH)2.
Hydroxyapatite is excellent in biocompatibility andused for materials such as artificial bone and implants
because it is a major constituent of teeth and bones.
In addition, hydroxyapatite has many functions suchas high adsorptive property (especially amino acids,
proteins, lipids, sugars, etc.), ion exchange properties,
catalytic properties, and ionic conduction properties
as in [5], [6], [7]. It is artificially synthesized by manymethods and it is used in various fields including thebiomaterials. According to study of Nishiyama et al.,it is already known that hydroxyapatite has adsorption
properties not only for heavy metals but also forstrontium as in [8]. Some hydroxyapatite is derived
from cattle bones and pig bones, but in this study, theadsorbent based on hydroxyapatite derived from fishbones (Fishbone Absorber, hereinafter referred to as
FbA and, see Fig. 2) is used for various tests. The sizeof the piece is approximately 1 cm square and its
weight is approximately 0.6 g. The FbA is producedby burning fish bone discarded at a fishing port.

Fig. 2 FbA

942

SEE - Nagoya, Japan, Nov.12-14, 2018

three times in order to ensure reproducibility, and thetest results are shown by their average values.
Test results
The test results using the rice husk and the FbA as
the adsorbent are shown graphically. The adsorption
ratio of heavy metal and heavy metal are shown in thevertical and horizontal axes, respectively. The
numerical value written on the top of the bar graph isthe pH value which is measured immediately after
taking out the adsorbent. Table 1 shows the pH
values of each test specimen before adding theadsorbent. The pH of all test specimens indicatesfrom weak acid to strong acid before adding
adsorbent because the standard solution is an acidic
solution.

Fig. 3 Removal method for heavy metals ion in
the solution
RESULTS AND DISSCUSSION
Among various materials which are harmful tothe environment and the human body, and in thisstudy, 9 types of Cr6+，Cr3+，Mn2+，Ni2+，Zn2+，
As3+，Se4+，Cd2+，Hg2+ are selected. The materials
section is based on the harmful substances specified
by the uniform effluent standards of the Ministry of
the Environment. Se4+ is the cation in the solution
though Se4+ is a nonmetallic element. Furthermore,
Se4+ is targeted in the test because Se4+ iscomprehended in the harmful material and the cationin the solution. For chromium, trivalent andhexavalent samples are prepared because their waste
water standards are different depending on thevalence. The test conditions are set and adsorption
tests for each heavy metal are conducted in order toexamine the basic adsorption performance of the ricehusk and the FbA for heavy metals. First, 300 mL ofpure water is put in a cylindrical container, and astandard solution of each heavy metal (analyticalreagent adjusted to 1000 mg / L) is added. The
standard solution of 1mL and 5 mL (about 3.3 and16.4 ppm of initial concentration, respectively) is
added in order to ascertain the adsorption amount perunit mass of the adsorbent for each heavy metal ion.
Secondly, the adsorbent is put in the filter bag and it
is immersed in the solution assuming collection ofadsorbent after the end of the test. The adsorbent istaken out after immersing in a thermostat set at 25 °C
for 168 hours, and the concentration of each heavy
metal ion in the solution is analyzed by an ICPS
emission spectrometer. The adsorption performanceof each adsorbent is evaluated by the adsorption ratio
derived from the residual concentration of each ion in
the solution to the initial concentration at the time ofaddition of standard solutions. All tests are conducted
Table 1

1 mL
5 mL

Cr3+
3.4
2.8

Cr6+
4.6
3.5

Mn2+
3.5
2.8

Adsorption test of rice husk
First, the results of the adsorption test using therice husk as an adsorbent for each heavy metal are
shown in Figs. 4 and 5, which correspond to theadsorption tests to 1 mL (initial concentration is about
3.3 ppm) and 5 mL (initial concentration is about 16.4ppm) additions of heavy metal standard solution,
respectively. The mass of rice husk is 0.6 g, and thismass is almost equal to the mass of FbA single piece.
As shown in Fig. 4, 80 percent or more of Zn2+,2+
Cd , and Hg2+ are adsorbed to rice husk when 1 mLof the sample was added. On the other hand, Cr6+ andAs3+ are not adsorbed at all. All three types of ionswith high adsorption ratio are group 12 elements. The
Group 12 elements are also called zinc groupelements. They are metal elements, and classified as
typical elements. The Group 12 elements are
considered to be closer to the adsorption mechanismof alkaline earth metal than other heavy metals
classified as transition elements because the zincgroup elements are divalent cation. According to
Shannon's ionic radius table, the ionic radius of thethree zinc group elements are relatively close (seeTable 2). The high adsorption rate for ions whoseionic radii are close suggests that rice husk may
adsorb the ions by physical adsorption rather thanchemically adsorbed. It is necessary to clarify
adsorption mechanism in near future. Alternatively,
Mn2+ and Ni2+ is the divalent cations in solution
similarly to Zn2+, Cd2+, and Hg2+ with high adsorption
ratio to the absorbent. However, the adsorption ratio
remains around 50 percent. From these facts, it isconsidered that not only the ion valence but also thepH value before adding adsorbent
Ni2+
3.5
2.7

Zn2+
3.4
2.8
943

As3+
5.8
4.8

Se4+
3.6
2.6

Cd2+
3.4
2.8

Hg2+
3.5
2.8

SEE - Nagoya, Japan, Nov.12-14, 2018ionic radius are related to the adsorption performance.
On the other hand, there are exceptions such as Cr3+,
and other factors also need to be examined in near
future. Focusing on pH, the pH value of Cr6+and As3+
are higher than that of the other specimens and show
neutrality. It is a possibility that the adsorption ratio
may be improved by adjusting the pH value of thesolution to a low value and making an acidic
environment.

Adsorption ratio (%)

100

6.1 4.7

100
Adsorption ratio (%)

adjusting the pH value in order to clarify the influenceof the pH value on the adsorption of each heavy metal
ion, and the test in which the addition amount isminutely set is conducted in order to ascertain theadsorption limit amount of rice husk.

5.8
80
60

6.0

5.0

5.2

5.9

80
2.9

60
3.0

40

2.9
3.0

20

2.9

2.9
5.5

3.0
7.2

0

40
20
6.6

7.0

0

Fig. 5 Adsorption perfomance of rice husk (adding
amount of 5 mL)
Adsorption test of FbA

Fig. 4 Adsorption performance of rice husk
(adding amount of 1 mL)

First, the results of the adsorption test using the
FbA as an adsorbent for each heavy metal are shownin Figs. 6 and 7 which correspond to the adsorption
test to 1 mL (initial concentration is about 3.3 ppm)
and 5 mL (initial concentration is about 16.4 ppm)
additions of heavy metal standard solution,
respectively . The 1 piece of FbA (about 0.6 g) is usedin the test.
As shown in Fig. 6, the adsorption ratio for Hg2+
is the highest all of samples and 90% or more of Hg2+
is adsorbed to the FbA when 1 mL of the sample isadded. Subsequently, the adsorption ratio of Zn2+ andCd2+ is high, and the results are similar to those of thetest using rice husk. On the other hand, the adsorption
ratio to Cr6+ and As3+ is low, and the result is alsosimilar to the case using the rice husk, while theadsorption ratio for Mn2+ is higher than that of thecase using rice husk. The adsorption ratio of Mn2+ isabout 50% when the rice husk is used. However, it
exceeded 70% in the case using the FbA. It isconsidered that Mn2+ has a property to promote thecalcification of bone in increasing the adsorption ratioof the FbA to Mn2+. Mn2+ is a necessary mineral forthe calcification of bone and is more easily absorbed
into bone than other ions. It is presumed that Mn2+ isadsorbed to the FbA rather than rice husk because the
FbA is derived from fish bone. Additionally, theadsorption ratio of Cr3+ is slightly higher than that of
the case using the rice husk. A slight precipitate isconfirmed when the specimen of Cr3+ using the FbA

As shown in Fig. 5, the adsorption ratio decreases
in most of the specimens to compare with using 1mlof sample when 5 ml of the sample is added. It isconsidered that the amount capacity of adsorbing
each ion of 0.6 g of rice husk may be clarified byincreasing the amount of sample added. Although theadsorption ratio decreases as the most of samples, thedivalent cations, Mn2+, Ni2+, Zn2+, Cd2+, and Hg2+
tend to be relatively adsorbed. Especially, the ricehusk for Hg2+ has a relatively high adsorption ratio
even if the addition amount is increased five times.
The fact that 50% of the added amount is adsorbed
suggests the adsorption amount increases. Almost allof Hg2+ is adsorbed in the 1 mL of addition amountand about half adsorption in 5 mL, and there is apossibility that the adsorption limit amount for Hg2+
is between 1 and 5 mL. These results shows that theadsorption limit amount for Hg2+ may be between 1
and 5 mL. The reason why the adsorption ratio
decreases in most samples is considered to depend on
the difference in the initial pH value (see Table 1).
The heavy metal ion is easily adsorbed in the lower
initial pH value. On the other hand, among all
specimens, the adsorption ratio in the only specimenof As3+ is high and the pH values after the test isalmost the same regardless of the amount of addition.
In near future, the test should be conducted by

Table2
Cr3+
0.62

Cr6+
0.44

Mn2+
0.67

Ni2+
0.69

Ionic radius (Å) (Shannon)

Zn2+
0.74

As3+
0.58
944

Se4+
0.50

Cd2+
0.95

Hg2+
1.02

Si4+
0.40

Ca2+
1.00

SEE - Nagoya, Japan, Nov.12-14, 2018

is observed. It is widely known that heavy metal ionsmight precipitate hydroxides by increasing the pH
value as in [9], [10]. The value varies depending on
the heavy metal ion and the element coexisting in thesolution, and the specimen of Cr3+ generates aprecipitate due to this property. As a result, theadsorption ratio increases by decreasing the ion
concentration in the solution. Even in the specimens
except the test specimen to which Cr3+ is added, thepH value is changed from weak acid to neutral in thecase of using the rice husk. On the other hand, it
increased to weak alkalinity in some specimen when
the FbA is used. The adsorption performance of ricehusk and FbA are very similar, but their effects on pH
value in solution are different. As this reason, the FbA
is fired while the rice husk is not burned. The ricehusk ash is often used as a conditioner for soil toneutralize acidic soils as in [11]. It is clarified that therice husk and FbA can be used not only as anadsorbent for heavy metals but also as a pH value
adjustment material by controlling the used amount in
the case of using both materials as contaminatedwater on site.
7.6
7.4

6.6

7.6

6.7

100

60

6.6

7.2

Adsorption ratio (%)

Adsorption ratio (%)

100
80

for divalent cations, in particular, Group 12 elements,
in both cases of addition amount of 1 ml and 5 ml. As
shown in Table 2, the ionic radius of the three kindsof ions which belong to group 12, are close to theionic radius of Ca2+. This result suggests that the FbA
may remove heavy metal ions from solution byphysical adsorption. The heavy metal ions areadsorbed to the FbA and Ca2+ is released instead, sothat the adsorption performance may be higher forheavy metal ions with a close ionic radius. If theadsorption mechanism of FbA is physical adsorption,
heavy metals adsorbed to the FbA can be taken out.
In addition, both the FbA and heavy metals can bereused. Therefore, the adsorption mechanism may be
examined in near future.
The adsorption performance of FbA is higher thanthat of rice husk in the case of adding 5 mL of most
sample through all the test results. The rice husk has
a high adsorption performance when additive amountis as small as 1 mL. On the other hand, the FbA is
more useful than the rice husk when the content ofheavy metal ion in the solution exceeds a certain
amount. Additionally, the adsorption performance of
FbA is higher than that of rice husk in the case ofadding 5 mL of sample. It is assumed that the FbA
has more marginal adsorption than rice husk.

40
20

7.5

7.8

0

80
4.5 4.5
60

4.2

4.7
4.3

40

4.4
4.3

20
7.3

7.3

0

Fig. 6 Adsorption performance of FbA (adding
amount of 1 mL )As shown in Fig. 7, the adsorption ratio for Cd2+
and Hg2+ is relatively high when 5 mL of the sample
is added, and the values exceed 60%. For Hg2+, it ispresumed that the adsorption limit amount is between
1 and 5 mL as in the case of adding the rice husk. The
amount of adsorption for Cd2+ increases as the added
amount increases. The solution is acidic because thepH value is low when 5 ml is added. It is consideredthat the pH value is low and the solution is acidic in
the case of adding 5 ml. It is necessary to adjust the
pH and conduct additional tests in order to clarify theconsideration. The adsorption ratio for other samples
is lower than that of adding 1 mL, and the results
show a similar tendency of those of 1 mL addition ofheavy metals. Some samples increase the amounts ofadsorption such as Hg2+ and Mn2+, and it is needed toinvestigate each sample of adsorption limit amount indetail. It is revealed that adsorption ability is higher

Fig. 7 Adsorption performance of FbA (adding
amount of 5 mL )CONCLUSIONSIn this study, the hydroxyapatite (FbA) derived
from fish bones and rice husk which are known as
industrial waste were focused. The possibility as a
new adsorbent was investigated by elucidating thefundamental adsorption performance for harmful
substances and the principle of these materials. In thetests, the adsorption effect of rice husk and FbA onnine kinds of heavy metals which have harmful
effects to the ecosystem was examined. The test was
conducted preparing the addition amount of the heavy
metals to 1 mL, 5 mL in order to ascertain theadsorption amount per unit mass of the adsorbent. As
945

SEE - Nagoya, Japan, Nov.12-14, 2018a result, it is confirmed that more than 40% ofadditive amount of all metals except As3+ and Cr6+
can be absorbed by the both adsorbents. In particular,
both adsorbents had high adsorption ratio for Group12 elements such as Hg2+, Cd2+, Zn2+. The rice husk
and FbA have similar property of adsorption for 9
metals, and both adsorbents had powerful adsorption
effect on divalent cations. Alternatively, it ispresumed that other factors such as ionization
tendency, ionic radius and specific gravity are related
to ion adsorption as well as ionic valence. As shownin Table 1, in case of the FbA, the ionic radius of welladsorbed heavy metal ions is close to the ionic radiusof the main component Ca2+ of the FbA. It isnecessary to examine the influence of these factors on
adsorption and the reason why the rice hulls and FbA
have similar adsorption performance to heavy metals
should be discussed in more detail.
For the pH, the FbA tends to change the pH of
solution to alkaline more than the rice husk. It isconsidered to be caused by whether or not thecalcination process is carried out. Depending on thefiring temperature, organic acids is thermallydecomposed or released as carbon dioxide in theprocess of burning substances including organic
substances. Therefore, alkali metals and alkaline
earth metals such as sodium, potassium and calcium
remain on the surface of the material as oxides,
carbonates and hydroxides. The pH value rises in thesolution because these pyrolysis residue elutes. As aresult, it is necessary to consider the influence of thepH value when the FbA is adopted as the adsorbent.
For As3+ and Cr6+, the adsorption ratio may alsochange by adjusting the pH value. Therefore, it isnecessary to adjust the pH value and conduct the same
test. The each limit amount of adsorption for FbA andrice husk were different for heavy metal ion tocompare the adsorption ratio according to the additive
amount of sample. The adsorption ratio of rice husk
is high in the case of using 1mL, and that of FbA ishigh in the case of using 5 mL. It is suggested that the
FbA has a higher adsorption limit than the rice husk.
Additionally, the adsorption performance of rice husk
may be improved by adjusting low concentration ofheavy metal ion, and that of FbA by adjusting highconcentration. In near future, it is necessary to
examine the adsorption performance by drasticallydecreasing or increasing the additive amount of heavy
metal ion and widening the range of concentration.

Ltd. provided FbA. We express our gratitude here.

REFERENCES[1] Ministry of the Environment, Ministry of Water
and Atmospheric Environment, Research resultson the construction situation of the soil
contamination countermeasure law and the case ofsoil pollution surveys and measures in 2014, 2016,
pp. 1-33.
[2] Ministry of the Environment, Ministry of Water
and Atmospheric Environment, Measurement
results of groundwater in 2014, 2015, pp. 2-55.
[3] Norihiro K, Takumi U and Kazuhide S,
Fundamental study of fresh and hardening
property of concrete with non-crushed rice husk
ash, Concrete Research and Technology, Vol. 28,
2017, pp. 1-13.
[4] Kozo I and Naomichi H, Thermal treatment andcharacteristics of rice husk ash, The Society ofInorganic Materials, Vol. 3, No. 263, 1996, pp.
312-318.
[5] Moritsugu H and Takeshi N, Inorganic
components of bones of fish and their advanced
utilization, The Journal of Shimonoseki
University of Fisheries, Vol. 43, No. 4, 1995, pp.
185-194.
[6] Aoki H, Tatsuhiko Y and Toshiyuki K, Apatite asa marvelous biomaterial and the surface
technology, Surface Technology, Vol. 58. No. 12,
2007, pp. 744- 750.
[7] Hironori S, Toshiyuki E and Tatsuya S,
Development of a medical grinding toolconsidering material properties of wet bone forminimally invasive surgery, The Japan Society of
Mechanical Engineers, Vol. 79, No. 804, 2013, pp.
254-265.
[8] Yuichi N, Tadashi H, Jun Y, Yoko Y and Toshiro
O, Adsorption and removal of strontium inaqueous solution by synthetic hydroxyapatite,
Journal of Radioanalytical and Nuclear Chemistry,
Vol. 307, Issue. 2, 2016, pp. 1279-1285.
[9] Konen Y and Masakatsu S, Heavy metal
contamination and its new countermeasuremethod, Society of Environmental Conservation
Engineering, Vol. 3, No. 4, 1974, pp. 235-242.
[10] Naoki K, The relationship between pH and theconcentration of heavy metal ions, The Chemical
Society of Japan, Vol. 46, No. 12, 1998, pp. 806807[11] Yaren b, Kazuo H, Makoto H, Shizuko I, Shohei
A and Motoyasu K, Processing and utilization ofrice husk charcoal, Journal of the JapaneseSociety of Agricultural Machinery, Vol. 62, No.
Supplement, 2000, pp. 185-186.

ACKNOWLEDGEMENTS
This work was supported by Japan Society for the
Promotion of Science, the Grants-in-Aid for
Scientific Research (C) (Grant number: 18J12343).
Also, in carrying out this study, Nihon Kogyo Co.,946

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE ACUTE EFFECT OF TRADITIONAL THAI MASSAGE ONRECOVERY FROM FATIGUE IN BASKETBALL PLAYERS
Nopparak Kaesaman1,3 and Wichai Eungpinichpong2,3
Graduate School, Khon Kaen University, Thailand
2
Faculty of Associated Medical Sciences, Khon Kaen University, Thailand
3
Research and Training Center for Enhancing Quality of Life of Working-Age People,
Khon Kaen University, Thailand
1

ABSTRACT
Massage has been used as an alternative treatment for professional athletes for decades. However, it has
hardly been used for rapid recovery on the sport field that always needs rapid recovery during half-time brake ofcompetition such as basketball. This study aims to investigate the acute effects of Traditional Thai Massage onrecovery in basketball players as indicated by heart rate variability (HRV) and physical fitness. A cross-overdesign was administered. Sixteen basketball players were randomly allocated into two groups: intervened with
Traditional Thai Massage (TTM) and Control (C). Each period, the participants underwent 20 minutes ofbasketball-playing simulation after which they were assessed on HRV and physical fitness. Then they received
either 10-minute TTM intervention or 10-minute rest, and were assessed again immediately after theinterventions with 3 days washout period. The results showed that HRV and physical fitness were significantly
increased (P< 0.05) in both groups after the interventions. There was no significant difference of LF/HF ratio(LF/HF ratio) in the control group. Mean changes in Grip strength test (GST) and High Frequency (HF) were
found to be higher in the TTM than the control on between-group comparison (P<0.05). Both TTM and passive
rest could enhance recovery after strenuous basketball playing. However, the TTM showed superior
improvement from fatigue than passive rest as indicated by HRV and GST.
Keywords: Traditional Thai Massage (TTM), Heart Rate Variability (HRV), Basketball Players, Fatigue,
Recovery

Furthermore, manual massage could provide anincrease of skin temperature which helps stimulating
the blood flow [3]-[5], and reduces the muscle
soreness [6]. In most cases, massage are used torecover the fatigued muscle, stretch the affectedmuscle, and improve the mood states during andafter the competition [7].
Traditional Thai Massage (TTM) is a deep-tissue
type of manual massage which mainly use forpromote relaxation and wellbeing. In addition, it has
been modified to use with athletes to facilitate
recovery of fatigued muscles after the competitions
such as Thai boxing, and football. The applied Thai
massage used for athletes’ muscle recovery consistsof the massage techniques of rubbing, rolling,pressing, squeezing with fingers and palm, gently
chopping with hand to stretch the joints throughout
the body, including all major muscle bundles ofarms, legs, and abdomen. The applied massage also
focuses on stretching the ten nerve lines of Thai
massage. Previous studies have shown the empiricalevidence that massage arouses the temperature on
the skin that can increase the blood flow [3]-[5]. In
addition, massage can minimize soreness [2] [8],enhance flexibility [2], reduce sympathetic nervous
system while increasing parasympathetic nervous

INTRODUCTION
Recovery is one of the basic principles in athletic
training methodology [1]. Fast recovery from muscle
fatigue is vital in sport events especially whenathletes require maximum energy for better
performance during competition. Frequently, aninterval between matches in each competition could
be varied depends on the local competition rules.
Thus, it is crucial for athletes to be provided with asufficient treatment that has an immediate effect on
the muscle recovery after the highly vigorous muscle
activities. The appropriate muscle recovery process
must quickly reduce the fatigue. If the impropermuscle treatment is applied to the athletes, it may
lead to reduced physical performance, increased riskof injury, or even emotional stress during
competition.
Several methods of muscle recovery have beensuggested for professional athletes, including the useof hot/cold therapies, stretching techniques, andsport massage. Among various muscle recovery
strategies, manual massage is considered as the mostnatural technique that be gently and directly applied
to the injured areas to enhance the elasticity ofmuscle and joints while relaxing the tendons [2].
947SEE - Nagoya, Japan, Nov.12-14, 2018

system [2], [9], [10].
Basketball is one of the most popular sports inthe world. It requires the players’ use of strenuous
energy as well as ultimate strength of the muscle andmobility skills throughout the game. In general,basketball players move approximately 4,500-5,000
meters in 40 minutes [11]. Every two minute, theplayers run, walk, spin, jump, slide, etc [12]. Fifteen
percent of each game is considered as highly intense
exercise [13]. Due to the heavy physical movement,
the injuries often occur [14]. However, thebasketball players are given with limited time off toobtain the recovery during the intervals. Thus, it isessential for the basketball players to meet theseneeds in order to compete at full strength andrecover quickly during and after the competition.
Yet, no studies have reported the effect oftraditional Thai massage on the recovery by using
HRV or other parameters to determine its efficiency
in the context of intense sport, particularly
Basketball. Hence, it is important to examine theacute effect of traditional Thai massage on therecovery of basketball players. The results of thestudy are expected to provide evidence for further
sport performance improvement, and enhance theunderstanding in the extent of sport and sportscience.
The purposes of this study are to examine theacute effects of traditional Thai Massage onrecovery in basketball players during thecompetition, and compare the acute effects oftraditional Thai Massage and passive rest on
recovery in basketball players during thecompetition.

study. The participants will divide into two groups.
The first group was intervened by traditional Thai
massage (TTM), receiving massage for ten minutes.
The second group is controlled group (C), allowed togain passive rest for ten minutes. This research is acrossover randomized controlled trial. All
participants were examined for two times. That is,
an individual participant would receive traditional
Thai massage; then passive rest.

Figure 1 Diagram of study protocol and variablemeasured. TTM and C group: 10 minute foreach protocols, 1 trial per protocol, wash out 3
day. TTM: Traditional Thai Massage.
Heart Rate Variability (HRV)The participants sat on a comfortable chair with abackrest, with eyes opened. HRV parameters were
measured three minutes by using the device, called
Ubio macpa, Korean version. The values of HR,
RMSSD, SDNN, HF, LF, and LF / HF ratio wereused to evaluate HRV.
Physical Fitness
Sit and reach test (SRT) was measured as
described by [15]. Subjects sit with the soles of theirfeet against the box, and with their hips flexed toabout 90˚ to assume an upright sitting position. And
then subjects flex their hip joints and vertebral
column (with possible contributions from shoulder
joint flexion and scapular elevation) to reachforward as far as possible. A centimeter scale isprinted on the top surface of the box.
Grip strength test (GST) was measured using a
Grip dynamometer (TKK 5401, Japan). The
participants griped the dynamometer with four
fingers, except the thumb, and controlled the widthof the handle. The arms were naturally lowered.
Maximum strength was applied to the dynamometer
without touching the body. [16].
Back strength test (BST) back strength of theparticipants was measured using a Back-leg-chest
dynamometer. The participant was positioned withbody erect and knees bent so that the grasping handrests at proper height. Then, by straightening theknees and lifting the chain of the dynamometer,pulling force was applied on the handle. The body
would be inclined forward at an angle of 60 degrees
for the measurement of back strength [17].
Leg strength test (LST) leg strength was alsomeasured using a back-leg-chest dynamometer. The

METHODS
Study design and participantsThis study was a crossover randomized
controlled trial, approved by the ethics committee ofKhon Kaen University, Thailand (HE602113). The
included participants were 16 males (mean age
20.13 ± 1.31 years), with a mean age of 20.13 ± 1.31
years, average of 72.69 ± 11.25 kilograms, average
body mass index of 177 ± 6.68 cm, and average
body mass index of 24.05 ± 5.79 kg/m2. They were
3-year experienced basketball players with nohistory of serious disease. Before participating inthis study, the participants were advised to refrainfrom eating, drinking alcohol, smoking, andconsuming caffeine for at least 2 hours.
Procedure and protocol
The participants were basketball players of
Sakon Nakhon Rajabhat University. They were
provided with orientation to understand the criteriaof the research and consent to participate in the948

SEE - Nagoya, Japan, Nov.12-14, 2018

participant was asked to stand erect with knees bent
so that the grasping hand rests at proper height. The
individual then lifted the handle of the dynamometer,
bending his legs, and then straightened the legs [17].

However, the LF/HF ratio increased significantly (P<0.05) only in the TTM group. HF values weresignificantly different (P <0.05) and no significant
differences in the comparison of results between
groups is presented in Table 2.

Traditional Thai massage (TTM) and Passive rest
DISCUSSION
The participants in Traditional Thai Massage
group are given 10 minutes of massage whereas thecontrolled group are given 10 minutes to rest. In theroom, the temperature is controlled at 25-26 °C. In
the TTM group, Thai traditional and Effleurage
massage techniques are applied throughout the bodyof the participants including biceps and triceps(arms), deltoid (shoulders), latissimus dorsi, thoracolumdar fascia, trapezius (back), and stretchingmuscles which consist of hamstrings, rectusfemoris,
arms, and back. In the C group, the participants areprovided with a regular passive rest (half time).

The result showed that Thai traditional massage
has acute effect on recovery from fatigue inbasketball players in both groups. According to the
HRV and physical fitness results, the average
recovery level in the Thai traditional massage group
was higher than in the non-Thai traditional massage
group that received only passive rest. The positive
result on recovery in the group treated by Thai
traditional massage was considered as the processthat body systematically reacts to the massage,
including the biochemical processes in cellular,
tissue and organ level.
It was found that body relaxation contributes tolower blood pressure because the stimulation ofparasympathetic from the massage [18]. In thisstudy, the basketball players significantly noticed themental and muscle tension, refreshment and power
boost to play more effectively in another half of thegame. This result was consistent with the previous
studies that stated that massage can increase HRV[2], reduce sympathetic activity, and increaseparasympathetic activity [19], [20]. Even with thedifferent types of massage, the result showed thedecrease of HR and increase of SDNN, RMSSD, LF,
HF, and LF-HF Ratio. Thus, the results indicatedthat Thai traditional massage can reduce sympathetic
activity and increase parasympathetic activity which
contribute to the greater recovery rate in basketball

Statistical analysis
The data were presented as mean ± SD. ShapiroWilk test was used to verify normality of data.
Crossover study design analysis was employed. The
paired t-test statistic was used to compare the mean
between the groups. The independent sample t-test
statistic was used to compare mean between groups.
Statistical significance value was set at p <0.05.
RESULT
Table 1 shows the comparison of the statistic
values in each group. The results of RMSSD, SDNN,
HF, LF, SRT, GST, BST, and LST, weresignificantly increased (P<0.05). whereas HR, wassignificantly decreased (p<0.05) in two group.
Table 1 Comparison of the results in each group
Results
RMSSD(ms)SDNN (ms)HR (bpm)
HF (ms2)
LF (ms2)
LF-HF ratio
SRT (cm)
GST (kg)
BST (kg)
LST (kg)

TTM group (n=16)
BeforeAfter
12.08±3.221.49±3.63*
38.83±13.15
46.43±13*130.53±10.54
98.86±6.95*
6.56±0.76
7.95±0.77*
7.86±0.98.84±0.78*
1.18±0.04
1.25±0.08*
11.56±5.05
13.13±5.06*
39.66±4.96
40.6±5.46*
127.94±18.65
143.47±20.12*
150.41±26.97
162.63±27.22*

Controlled group (n=16)
BeforeAfter
12.23±2.65
18.46±4.02*
41.56±9.47
46.08±11.44*
134.74±8.12104.6±8.04*
6.34±0.84
7.57±0.67*
7.86±19.2±0.86*
1.17±0.05
1.19±0.11
12.19±5.02
12.13±5.03*
39.28±6.58
38.74±6.25*
131.72±25.06
138.42±22.21*
154.59±34.33
161.36±31.71*

Data are expressed as mean ±SD. TTM – traditional Thai massage; RMSSD – the square root of the meansquared differences of successive normal R-R intervals; SDNN – the standard deviation of the normal-tonormal intervals; HR – heart rate; HF – high frequency; LF – low frequency; LF/HF ratio – low frequency perhigh frequency ratio; SRT - Sit and reach test; GST - Grip strength test; BST - Back strength test; LST - Legstrength test. Significant change within group, * p<0.05
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Table 2 Comparison of the results between two groups

Results
RMSSD (ms)SDNN (ms)HR – heart rate (bpm)
HF – high frequency (ms2)
LF – low frequency (ms2)
LF/HF ratio – low frequency
per high frequency ratio
SRT - Sit and reach test (cm)
GST - Grip strength test (kg)
BST - Back strength test (kg)
LST - Leg strength test (kg)Compared before
TTM –Traditional
Passive rest
Thai massage(n=16)(n=16)
12.08±3.2
12.23±2.65
38.83±13..15
45.31±12.32
130.53±10.54
134.74±8.12
6.56±0.76
6.34±0.84
7.86±0.97.86±1Compared after
TTM –Traditional
Passive rest
Thai massage(n=16)(n=16)
21.49±3.63
18.46±4.02
30.24±8.78
25.58±8.86
98.86±6.95
104.6±8.04
7.95±0.77*
7.57±0.67
8.84±0.78
9.2±0.86

1.18±0.04

1.17±0.05

1.25±0.08

1.19±0.11

11.56±5.05
39.66±4.96127.94±18.65
150.4±26.97

12.19±5.02
39.28±6.58131.72±25.06
154.59±34.33

13.13±5.06
40.6±5.46
143.47±20.12
162.63±27.22

12.13±5.03
38.74±6.25
138.42±22.21
161.36±31.73

Table 3 Comparison of the mean change scores (pre–post) of HRV and physical fitness tests between the(TTM) and control groups
Results
RMSSD (ms)SDNN (ms)HR – heart rate (bpm)
HF – high frequency (ms2)
LF – low frequency (ms2)
LF/HF ratio – low frequency
per high frequency ratio
SRT - Sit and reach test (cm)
GST - Grip strength test (kg)
BST - Back strength test (kg)
LST - Leg strength test (kg)TTM – Traditional
Thai massage (n=16)9.41±2.74
7.61±5.87-31.68±8.05
1.39±0.95
0.98±1.06

Passive rest
(n=16)
6.23±2.69
4.51±5.87-30.14±5.79
1.23±0.77
1.34±1.22

Different(95% CI)-3.18(-5.56 to -0.80)
3.1(-1.14 to 7.33)-1.54(-3.53 to 6.60)-0.16(-0.79 to 0.45)-0.36(-1.18 to 0.47)

0.08±0.1

0.03±0.1

0.05(-0.02 to 0.12)

1.56±0.96
0.94±2.07
15.53±16.79
12.22±10.32-0.06±1.61-0.54±4.44
6.7±13.04
6.76±13.21

1.62(0.67 to 2.58)
1.48(-1.01 to 3.99) *8.83(-2.02 to 19.69)
5.46(-3.10 to 14.02)

For Thai traditional massage, the mechanicalpressure is used by pressing on the muscle tissues toincrease muscle flexibility for several benefits: toreduce the tension at the joints and muscle, andincrease the degree of movement and elasticity [24].
The mechanism of massage has an effect on
autonomic nervous system resulting in better mental
relaxation because the massage can reduce theprocess of sympathetic activity while increasing
parasympathetic activity [25]. This reduces thecortisol level, which in turn, lowers anxiety,eventually leading to relaxation [24], [26]. This
result was in accordance with the previous studies of[2] and [27] indicating that massage helps reduce theanxiety. Likewise, [5] revealed that massage
alleviates muscle tightness and heals the sore muscle
after intense exercise.

players.
Thai traditional massage dilates the blood vessels[4], [5], [21], which helps remove oxygenated blood
and waste from the muscle e.g. lactic acid; as aconsequence, the acidity in muscles is diminished.
This leads phosphofructokinase - an enzyme that
controls process of glycolysis - to generate theenergy to the muscles, and improves the binding ofprotein myosin and actin in muscle contraction; as aresult, the muscles work effectively [22]. Moreover,Thai traditional massage helps the blood vessels totransport oxygen to the muscles so that the muscles
can perform better. In additional, Thai traditional
massage at the arms, legs, and back helps tissues
around these organs improve flexibility, especiallywhen they contract [23]. All these effects of massage
may contribute to improve overall performance ofthe basketball players.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Physical Therapy in Sport.
[7] Cafarelli, E., F. Flint. (1992). The role ofmassage in preparation for and recovery fromexercise. An overview. Sport Med, 14,1-9.
[8] Corrie A. Mancinelli, D. Scott Davis, Leila
Aboulhosn, Misty Brady, Justin Eisenhofer,
Stephanie Foutty. (2006). The effects of massage
on delayed onset muscle soreness and physicalperformance in female collegiate athletes.
Physical Therapy in Sport, 7, 5–13.
[9] Lindgren, L., Rundgren, S., Winsö, O., Lehtipalo,S., Wiklund, U., & Karlsson, M. et al. (2010).
Physiological responses to touch massage inhealthy volunteers. Autonomic Neuroscience:
Basic and Clinical, 158(1-2), 105–110.
[10] Pishbin, T., Firoozabadi, S.M.P., Jafarnia
Dabanloo, N., Mohammadi, F. & Koozehgari, S.
(2010) Effect of physical contact (hand-holding)on heart rate variability. International Journal ofAdvanced Computer Science, 2(12), 452-456.
[11] Goran Vučković, Brane Dežman,Nic James,
Frane Erčul, (2010). Analysis of the movement
intensity of national level basketball guards andcentres in defence and offence- A case study.
Kinesiologia Slovenica, 16(3), 66–76.
[12] Crisafulli A, Melis F, Tocco F, Laconi P, Lai C,
Concu A. (2002). External mechanical work
versus oxidative energy consumption ratio
during a basketball field test. J Sports Med Phys
Fitness, 42, 409–417.
[13] McInnes, S.E., Carlson, J.S., Jones, C.J., &McKenna, M.J. (1995). The physiological load
imposed on basketball players during
competition. Journal of Sports Sciences, 13,
387–397.
[14] Lakomy, J. and D.T. Hayton. (2004). The effectof enforce, rapid deceleration on performance ina multiple sprint test. J Strength Con Res,
18,579-583.
[15] Wells, K. F., & Dillon, E. K. (1952). The Sit
and Reach—A Test of Back and Leg Flexibility.
Research Quarterly. American Association for
Health, Physical Education and Recreation, 23(1),
115–118.
[16] You Sun Ko, Sung Eun You (2015).
Comparisons of physical fitness and bodycomposition among Sasang types with andwithout body mass index as a covariate,
Integrative Medicine Research, 4, 41–47.
[17] Shyamal Koley, Aseem Khajuria, and Sheri
Melton. (2010). The correlation between backstrength and leg strength among indian interuniversity male cricketers. Physical Educationand Sport, 8(2), 125 – 132.
[18] Wichai Eungpinichpong. Therapeutic Thai
Massage. Bangkok. Suweriyasarn publishing,2008; 54-8.
[19] Lindgren, L., Rundgren, S., Winsö, O.,
Lehtipalo, S., Wiklund, U., & Karlsson, M. et al.

CONCLUSION
The results of this study showed that Thai
traditional massage has more acute effect on therecovery of basketball players than the passive rest.
Hence, Thai traditional massage is an effective
approach for muscle recovery since it improves theperformance of basketball players during thecompetition. This method of Thai traditional
massage could be applied to the basketball players
during the breaks of the game, or even to other typesof sports that are held with the breaks during thecompetition e.g. football, Sepak takraw, volleyball,etc. Therefore, sport massage as an alternative
recovery method for athletes, trainers or interested
parties could be applied in sports for greater
performance and success.
ACKNOWLEDGMENTS
The authors would like to thank the volunteers
who participated in this study. The study was
supported by the Research and Training Center for
Enhancing Quality of Life of Working-Age People
at Khon Kaen University, and we would like tothank the Sakon Nakhon Rajabhat University fordata collection.
REFERENCES[1] Rushall, B. S., & Pyke, F. S. (1990). Training for
sports and fitness. Melbourne, Australia:
Macmillan Educational.
[2] Buttagat, V., Eungpinichpong, W., Chatchawan,
U. &Kharmwan, S. (2011). The immediate
effects of traditional Thai massage on heart ratevariability and stress-related parameters inpatients with back pain associated withmyofascial trigger points. Journal of Bodywork
and Movement Therapies, 15(1), 15-23.
[3] Zhang, W., Takahashi, S., Miki, T., Fujieda, H.,& Ishida, T. (2010). A pilot study exploring theeffects of reflexology on cold intolerance.
Journal of Acupuncture and Meridian Studies,3(1), 43-48.
[4] Hinds, T., Mcewan, I., Perkes, J., Dawson, E.,
Ball, D., & George, K. (2004). Effects ofmassage on limb and skin blood flow after
quadriceps exercise. Medicine and science.
[5] Mori, H., Ohsawa, H., Tanaka, T. H., Taniwaki,
E., Leisman, G., & Nishijo, K. (2004). Effect ofmassage on blood flow and muscle fatigue
following isometric lumbar exercise. Medical
Science Monitor, 10(5), CR173-178.
[6] Corrie A Mancinelli, D. Scott Davis, Leila
Aboulhosn, Misty Brady, Justin Eisenhofer.
Stephanie Foutty. (2006). The effects of massage
on delayed onset muscle soreness and physicalperformance in female collegiate athletes.
951

SEE - Nagoya, Japan, Nov.12-14, 2018(2010). Physiological responses to touchmassage in healthy volunteers. Autonomic
Neuroscience: Basic and Clinical, 158(1-2), 105–110.
[20] Pishbin, T., Firoozabadi, S.M.P., Jafarnia
Dabanloo, N., Mohammadi, F. & Koozehgari, S.
(2010) Effect of physical contact (hand-holding)on heart rate variability. International Journal ofAdvanced Computer Science, 2(12), 452-456.
[21] Monedero J, Donne B. Effect of recovery
interventions on lactate removal and subsequent
performance. Int J Sports Med 2000; 21: 593-7.
[22] Frayn KN. Metabolic regulation. A humanperspective. Portland Press, London 1996; p.182.
[23] Wilmore JH, Costill DL. Physiology of sportand exercise. Human Kinetics. Champaign,
IL1994; 524-5.

[24] Weerapong, P., Hume, P.A., & Kolt, G.S.
(2005). The mechanisms of massage and effects
on performance, muscle recovery and injury
prevention. Sports Medicine, 35(3), 235-256.
[25] Lee, Y.H., Park, B.N., & Kim, S.H. (2011). The
effects of heat and massage application on
autonomic nervous system. Yonsei Medical
Journal, 52(6), 982-989.
[26] Sripongngam Thanarat, (2015). Immediate
Effects of Traditional Thai Massage on
Psychological Stress as Indicated by Salivary
Alpha-Amylase Levels in Healthy Persons.
Medicine and science, 21: 216-221.
[27] Kunikata, H., Watanabe, K., Miyoshi, M., &Tanioka, T. (2012). The effects measurement ofhand massage by the autonomic activity andpsychological indicators. The Journal of Medical
Investigation, 59(1-2), 206-212.

952

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE POTENTIAL OF TROPICAL MICROALGAE AS FLOCCULANTIN HARVESTING PROCESS
Astri Rinanti1*, Ronny Purwadi2
1

Environmental Engineering Department, Faculty of Landscape Architecture and Environmental Technology,
Universitas Trisakti, Jakarta, Indonesia
2
Chemical Engineering Department, Faculty of Industrial Technology, Institut Teknologi Bandung, Bandung,Indonesia

ABSTRACTThis environmental biotechnology research aims to obtain a diversity of freshwater tropical microalgae which
has the ability to form a floc naturally to be utilized as bioflocculants in the process of harvesting other tropicalmicroalgae biomass that does not have such ability. The microalgae Chlorella vulgaris, Chlorella sorokiniana,
Chlorococcum sp., Closterium sp., Oscilatoria sp., Monorapidhium sp, Ankistrodesmus sp and Scenedesmus
obliquus are cultivated in batch culture and their environmental condition are controlled at 25°C, fed with 5% pure
CO2 with flow rate of 5 L/min. To determine the ability of microalgae strain as microalgae flocculant or not, it isnecessary to calculate recovery efficiency. The addition of Scenedesmus obliquus and Ankistrodesmus sp as
flocculant microalgae followed by slow mixing allows better interaction between flocculant microalgae and nonflocculant microalgae, so the floc size increases. Scenedesmus obliquus and Ankistrodesmus sp can be used as
flocculant species because the value of settling for both types of microalgae is more than 50% for 60 minutes whileother microalgae species can be categorized as non-flocculant microalgae since within 60 minutes settles less than
50%. The study also proved that no greenhouse gas was formed during the bioflocculation process. Thus themethod of bioflocculation with Scenedesmus obliquus and Ankistrodesmus sp is feasible to be applied to harvest
microalgae biomass on an industrial scale.
Keywords: Bioflocculation, Tropical microalgae, Flocs, Harvesting, Diversity

INTRODUCTION

reach up to 20% of total solids when using
centrifugation [1]. However, centrifugation is atechnique with high capital, energy and operationalcosts [5].
In addition, this process allows the components inthe cell to be damaged [3], [6]. Another technique thatis commonly used is sedimentation, but this technique
is inefficient with time and requires space to build astorage pond. Harvesting of microalgae using
filtration techniques can only be done to harvest
microalgae which larger than 100 μm and havefilamentous or colonized cell shape, such as Spirulina
sp. and Micractinium sp [7].
Harvesting of microalgae biomass using chemical
flocculants and biofalms has been done by previous
researchers. mentions that flocculation is ideal for
harvesting microalgae smaller than 100 μm and notcolonizing. Flocculation using chemicals can also
lead to nutrient degradation, changes in temperatureand dissolved O2 [8]. Chemical flocculants may
contaminate the water used as microalgae culture
medium. Water remaining after harvesting when
disposed directly into the environment must beprocessed first to meet the required quality standards.
The process requires a lot of money and energy. The

In a series of microalgae biomass production
systems, the harvesting stage must be through first
before entering any processing stage of the
microalgae, such as to be bioenergy raw materials,
foodstuffs, raw materials of drugs and cosmetics. In
order to obtain high biomass production, it isnecessary to do research on harvesting with the rightmethod without causing new problems. Since
microalgae biomass concentrations are often very low
with size only a few micrometers (1 to 30 μm ), thenharvesting of microalgae becomes difficult [1] andexpensive [2]. The cost of harvesting can be reduced
significantly by choosing a more efficient andeconomical harvesting technique. Although someharvesting techniques have currently known, the main
disadvantage of such of them is requiring expensive
operational costs due to high energy dependence andless environmentally friendly.
Centrifugation is one of the most commonly usedharvesting techniques because its ability to produce
80-90% harvested biomass from cultivation results inonly one stage thus increasing efficiency in theharvesting stage [3], [4]. Harvested microalgae can
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addition of chemical compounds can also causechanges in the composition of microalgae cells [9],[10].
Bioflocculation is a technique of harvesting
microalgae whose principle is similar to flocculation,
which is the difference is the flocculant material used.
Bioflocculation uses living things such as bacteria,
fungi, or microalgae as flocculants. Flocculation
using bacteria [11] and fungi [12] are alternatives toreplace chemical flocculants, so the effects ofchemical pollution on culture media can be reduced.
However, the use of fungi and bacteria as flocculants
requires additional special media as a source ofenergy for its growth. In addition, bacteria and fungi
can contaminate microalgae [11], [13].
The use of microalgae as flocculants does not
require different growth media so it reduces
additional costs. In addition, it will prevent bacterial
contamination of the microalgae to be harvested [13].
Most importantly, bioflocculation by utilizing
microalgae is more environmentally friendly because
residual water harvesting that not contain chemicals
can be reused or can be disposed of without require
special treats with high cost.
In addition, microalgae flocculants can reduce
dependence on energy used in the harvesting processuntil microalgae processing becomes a usefulproduct. Thus, the problems to be studied include thefastest and most stable microalgae floc formulation
test by taking into account the gradient criteria of floc
forming speed. In addition, optimal flocculant
microalgae ratios of non-flocculant microalgae need
to be determined to obtain maximum yield. To findout how far the bioflocculation technique gives aneffect of efficiency in harvesting, it will be extracted
to obtain by products, such as lipids and starch.
By studying the floc forming speed gradient, it
is particularly expected to provide information on thediversity of microalgae as the flocculant agent thatgives the highest biomass yield. In general, thisresearch is expected to provide scientific contribution
to the development of microalgae biomass production
technology that is more economical, efficient andenvironmentally friendly.

Fig. 1 Scheme of Microalge Cultivation in Batch
Culture, not to scale(1) aerator, (2) regulator to regulate aeration rate, (3)silicone hose for aeration channel, (4) bottle ofculture, (5) fluorescent lamps
The Study of Flocculation (%) of Microalgae by
Flocculants and Fioflocculants
The precipitation of non flocculating microalgae withbioflocculant is obtained from the calculation of
OD750 (Optical Density) data using equation 1 [13].
𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 (%) =𝑂𝑂𝑂𝑂750 (𝑡𝑡0 )− 𝑂𝑂𝑂𝑂750 (𝑡𝑡)
𝑂𝑂𝑂𝑂750 (𝑡𝑡0 )

. 100

(1)

OD750(t0) is the turbidity of sample taken at time zeroand ODa750 (t) is the turbidity of the sample taken attime t.
To determine the ability of microalgae strain as
microalgae flocculant or non-flocculant microalgae,
it is necessary to calculate recovery efficiency, i.e.
recovery by non-flocculant microalgae toflocculating microalgae divided by non-flocculant
microalgae recovery without presence of flocculant
microalgae [13].
𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑒𝑒𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 (%)= �1 −RESEARCH METHODOLOGY
Cultivation of Flocculant and Non Flocculant
Microalgae

𝑂𝑂𝑂𝑂𝑎𝑎750(𝑡𝑡)
𝑂𝑂𝑂𝑂𝑎𝑎750 (𝑡𝑡0 )𝑂𝑂𝑂𝑂𝑏𝑏750 (𝑡𝑡)
𝑂𝑂𝑂𝑂𝑏𝑏750 (𝑡𝑡0 )� . 100(2)

ODa750(t0) and ODa750(t) are the turbidities ofsamples of non-flocculating microalga withflocculating microalga taken at time zero and at timet, respectively. ODb750(t0)is the turbidity of sample ofnon-flocculating microalga taken at time zero
andODb750 (t) is the turbidity of the same sample taken
at time t (Fig. 2)

Microalgae were cultivated using an artificial
growth medium of Provasoli Haematococcus Media(PHM). Microalgae that grow in light and climate arecontrolled 25 °C in temperature, fed with 5% pure
CO2 with a flow rate of 5 L⋅min-1, illuminated byfluorescent lamps (4000 lux)) with 16/8 hour
light/dark cycle [14]. All microalgas were tested on
its ability to improve the recovery efficiency.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 2 Determination of Recovery Efficiency
RESULT AND DISSCUSION
Flocculation tests have been performed on 8
types of microalgae identified morphologically, as
shown in Figure 3. The 6 of 8 microalge were
Chlorellavulgaris,
Chlorellasorokiniana,
Chlorococcum sp., Closterium sp., Oscillatoria sp.,and Monorapidhium sp. (Fig. 3 a, b, c, d, e, f) in thefirst 1 to 6 hours visual observation remained
unflocculated and sedimentated, while the other 2
species were Scenedesmus obliquus, Ankistrodesmus
sp. (Fig. 3g, h) experienced floc formation followed
by a settling time of less than 60 minutes ofobservation.
The experimental results have shown that theadditionof
Scenedesmus
obliquus
andAnkistrodesmus sp as flocculant microalgae followed
by slow mixing allows better interaction between
flocculant microalgae and non-flocculant microalgae,
so the floc size increases.
Settling time depends greatly on flock size. The
larger the size of the floc that is formed, the fastersettling time. Flocculation efficiencies is influenced
by several factors, i.e
pH [14], dosage ofbiofloccurrent [11], [15] and proper mixing [12] .
Initial pH values of culture can be adjusted to improveflocculation efficiency [14]. Incorrect doses may
decrease flocculation efficiency. Mixing is necessary
to increase the contact between microalgae cells so as
to facilitate the formation of large flocs in a shortertime than without adequate mixing [12].

Fig. 3 Non flocculant microalgae: a) Chlorella
vulgaris, b) Chlorella sorokiniana, c) Chlorococcumsp., d) Closterium sp., e) Oscilatoria sp., f)
Monorapidhium sp. Flocculant microalgae: g)
Scenedesmus obliquus, h) Ankistrodesmus sp.
Flocculant formation occurring in the flocculant
microalgae can be seen in Fig. 4, while the microalgae
flocculation capability and ability within 60 minutesof observation can be seen in Fig. 5. Figure 5 showsthat the addition of Scenedesmus obliquus into culture
followed by slow mixing allows
increasing
interaction between the flocculant microalgae cells
and the non-flocculant microalgae so that theflocculation performance is efficient.

Fig. 4 The formation of floc on Scenedesmus obliquus
within 60 minutes of observation

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This indicates that Scenedesmus obliquus andAnkistrodesmus sp can be used as flocculant species
because the value of settling for both types of
microalgae is more than 50% for 60 minutes whileother microalgae species can be categorized as nonflocculant microalgae since within 60 minutes settles
less than 50% (Table 1). The fastest of settling occurs
in the ratio of flocculant and non-flocculant
microalgae is 4: 4 compared to 1: 4, 2: 4 and 3: 4
ratios. This suggests that the addition of more
flocculant species may increase theprecipitation
percentage. Salim et al. [13] suggest that the additionof flocculant species with higher concentrations inharvesting will increase the settling percentage.
The results of this study also show that thedifference of settling rate (%) among non-flocculant
microalgae species is affected by the size of each kindof microalgae. The size of non-flocculant microalgae
ofChlorella sp. is measuring 2.0-10.0 μm,
Monorapidhium sp. is 2-11 μm., Chlorococcum sp. is
5.0-12.0 μm, Closterium sp. is 10-15 μm, Oscilatoria
sp. is 10-150 μm with filament 2-20 μm while
Scenedesmus and Ankistrodesmus have sizes of 1520 μm and 12-14 μm respectively. According to [10]the rate of particle precipitation is influenced by thesize of the particle, the larger the size of a particle theeasier the settling.
Sathe [19] mentions that bioflocculation is aspontaneous flocculation of microalgae cells
occurring as a result of extracellular polymeric
substances (EPS) secretion when the microalgae areunder stress conditions. Lack of nutrients is a major
factor causing microalgae cells to overexpress thesubstance of the extracellular polymer [20]. The
substance of the extracellular polymer produced by
the microalgae will trigger the formation of cellclumps, which then will form a precipitated biomass
The results of bioflocculation observations undera microscope with 10x magnification showed
microalgae forming large networks connected to eachother. At the beginning of mixing (t=0) visible cells
flocculant and non-flocculant microalgae are stillseparated and not bounded at all. Gradually thebinding process begins to occur as the cells begin toexperience stress due to decreased nutrition andtrigger the microalgae to secrete the extracellularpolymer. The resulting extracellular polymer createsbonds between microalgae cells. The bond between
the flocculant and non-flocculant microalgae cells at
5th hour has begun to appear with the bond formation
betweenthemicroalgae
species.
Moremicroscopically bonds begin to appear at 12th hours,
when non-flocculant species are bound to flocculant
species and form larger batches of biomass, causing
the flocs cells to settle.

Fig. 5. The ability of microalgae flocculation within
60 minutes of observation: a) Chlorella vulgaris, b)
Scenedesmus obliquus c) Chlorella sorokiniana, d)
Chlorococcum sp., e) Closterium sp., f) Oscilatoriasp., g) Monorapidhium sp.
On a laboratory scale, the effectiveness ofdewatering technology in relation to the process of
harvesting of many microalgae biomass has beenreported to have achieved significant efficiencies, but
increasing to a larger scale still make problems, i.eless economically viable if harvesting implemented to
produce products such as biofuel [5], [16]. In
contrary, bioflocculation harvesting is anenvironmentally friendly method, consuming lessenergy, can take place relatively quickly (withinminutes).
The flocculant and non-flocculant microalgae
species were determined from the settling percentage(%) calculated on the basis of the OD750nm value ofeach microalgae (Eq. 1). The value of OD750nm for
S.obliquus and Ankistrodesmus sp. initially 0.20 ±7.16x10-3 and 0.18 ± 9.17x10-3 respectively andsubsequently decreased rapidly after the first hour to
0.09 ± 4.13x10-3 and 0.095 ± 3.89x10-3, thendecreased slowly until the 12th hour became 0.04 ±6.16x10-3 and 0.05 ± 3.38x10-3. Salim et al. [13] statesthat species potentially made as microalgae
flocculants are microalgae with a settling value (%)
of 50 or more within 60 minutes.
Table 1. Percentage of the settling value in the first 60
minutes
Tropical microalgae
Settling value
Flocculant microalgae
1. Scenedesmus
55.1% + 1.24
52.3% + 3.71
obliquus
2. Ankistrodesmus sp
Non flocculant microalgae
1. Chlorella vulgaris
17.3% + 0.88
16.7% + 1.13
2. Chlorella
21.5% + 1.19
sorokiniana
25.1% + 1.36
3. Chlorococcum sp.
27.3% + 2.11
4. Closterium sp.
17.8% + 1.89
5. Oscilatoria sp.
6. Monorapidhium sp.

956

SEE - Nagoya, Japan, Nov.12-14, 2018

[4] Chen, C., Yeh, K., Aisyah, R., Lee, D,. Chang,J., Cultivation, Photobioreactor Design andHarvesting of Microalgae for Biodiesel
Production: A Critical Review, Bioresource
Technology, Vol.102, No.1, 2011, pp. 71-81,
ISSN 0960-8524[5] Wijffels, R.H., Barbosa, M., An Outlook on
Microalgal Biofuels, J Science, 2010,
doi:10.1126/science. 1189003[6] Li, Y., Wan, C., Algae for Biofuel,Departement of Food, Agricultural andBiological Engineering,The Ohio State
University. 3, 2011.
[7] Gouveia, L. and Oliveira, A. N., Microalgae as
A Raw Material for Biofuels Production, J. Ind
Microbiol Biotechnol, Vol. 36, 2009, pp. 269–
274.
[8] Mata, T. M., Martins, A. A., Caetano, N.S.,
Microalgae for Biodiesel Production and Other
Applications: A Review, Renewable andSustainable Energy Reviews, Vol. 14, 2010, pp.
217-232.
[9] Papazi A., Makridis P., Divanach P., Harvesting
Chlorella minutissima Using Cell Coagulants, J
Appl Phycol. Vol. 22, 2010, pp. 349–355.

The study also proved that no greenhouse gas
was formed during the bioflocculation process. Thus
the method of bioflocculation with Scenedesmus
obliquus and Ankistrodesmus sp is feasible to be
applied to harvest microalgae biomass on anindustrial scale.
Conclusion
It is work examined the flocculation performance ofthe 6 freshwater microalgae i.e Chlorella vulgaris,
Chlorellasorokiniana,
Chlorococcum
sp.,
Closterium sp., Oscilatoria sp., Monorapidhium sp
induced by the bioflocculant Ankistrodesmus sp and
Scenedesmus obliquus. This research is an advanced
research as an effort to obtain the technique of cheap
harvesting and environmentally friendly, so that
economic feasibility in microalgae biomass
production can be improved. Thus biofloculation canbe industrialized. Furthermore, further research isneeded to analyze the biochemical composition of
microalgae harvested by bioflocculation to produce
biofuel. Further information on energy consumption
and process costs should also be further investigated
for the development of commercialization of
microalgae based products[10] Pillai J, Flocculants and Coagulants: The Keys
to Water and Waste Management in Aggregate
Production: Nalco Company, 1997.
[11] Ndikubwimana T., Zeng X., Liu Y., Chang J.S.,Lu Y., Harvesting of Microalgae Desmodesmus
sp. F51 by Bioflocculation with Bacterial
Bioflocculant, Algal Res, Vol. 6, 2014, pp.
186–93.
[12] Li X. Y., Yang S.F., Influence of Loosely Bound
Extracellular Polymeric Substances (EPS) on
The
Flocculation,
Sedimentation
andDewaterability of Activated Sludge, Water
Reserch, Vol. 41, 2007, pp. 1022-10340.
doi:10.1016/j.watres.2006.06.037.
[13] Salim S., Bosman R., Vermue M.H., Wijffels
R.H., Harvesting of Microalgae by Bioflocculation, J Appl Phycol, Vol. 23, 2011, pp.
849-855. doi: 10.1007/s10811- 010-9591-x.
[14] Rinanti, A., Dewi, K., Astuti, D.I., Kardena, E.,
Improvement of Carbon dioxide Removal
through Artificial Light Intensity andTemperature by Constructed Green Microalgae
Consortium in A Vertical Bubble Column
Photobioreactor,
Malaysian
JournalofMicrobiology, Vol.10, No.1, 2014, pp. 29-37.
[15] Rinanti, A., Purwadi, R., Bioflocculation
Activityin
Harvesting
System:A
Biotechnology Approach for Microalgae
Biomass, Aceh International Journal of Scienceand Technology, Aceh International Journal of
Science and Technology, Vol.7, No.1, 2018, pp.

ACKNOWLEDGEMENTS
The authors would like to thank Directorate for
Research and Community Services as well as
Directorate General for Strengthening Research andDevelopment at the Ministry of Research,
Technology, and Higher Education of Indonesia forfunding this study through the scheme of “Hibah
Penelitian Pasca Doktor (Post-Doctoral Research
Grant) 2018”.
REFERENCES[1] Sim T. S., Goh A., Becker E.W.,1988.
Comparison of Centrifugation, Dissolved Air
Flotation and Filtration Technique for
Harvesting Sewage-grown Algae, Biomass,Vol.16,
1988,
pp.
51-62,
doi:01444565/88/$03.50[2] Lee A.K., Lewis D.M., Ashman P.J., Microbial
Flocculation,
A
Potentially
Low-Cost
Harvesting Technique For Marine Microalgae
for The Production of Biodiesel, J Apply Phycol,
Vol. 21, pp. 559–56, 2009, doi 10.1007/s10811008-9391-8[3] Thompson R. W., D’Elia L., Keyser A., Young
C., Algae Biodiesel. Faculty Worcester
Polytechnic Institute. An Interactive Qualifying
Project Report, 47, 2010.

957

SEE - Nagoya, Japan, Nov.12-14, 2018

111-121.
[19] Sathe S., Culturing and Harvesting Microalgae
for The Large-scale Production of Biodiesel,
Microbial Engineerring Research Group. 97,
2010.
[20] Lee A.K., Lewis D.M., Ashman P.J., Microbial
Flocculation:
A
Potentially
Low-Cost
Harvesting Technique for Marine Microalgae
for The Production of Biodiesel, J Apply Phycol.
Vol.
21,
2009,
pp.
559–567,doi
10.1007/s10811-008-9391-8[16] Zheng H., Gao Z., Yin J., Tang X., Ji X., Huang
H., Harvesting of Microalgae by Flocculation
with Poly (γ-Glutamic Acid).,Bioresour
Technol, Vol. 112, 2012, pp. 212–20.
[17] Coward T., Lee J.G.,
Caldwell G.S.,
Development of A Foam Flotation System for
Harvesting Microalgae Biomass, Algal Res,
Vol. 2, No. 2, 2013, pp. 135–44.
[18] Barsanti L., Gualtieri P., Algae: Anatomy,
Biochemistry, and Biotechnology, Taylor &Francis, Boca Raton, 2006.

.

958

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

UTILIZATION OF WATER QUALITY MODELING TO DETERMINEMAXIMUM BOD LOAD OF UPSTREAM CITARUM RIVER
Yonik Meilawati Yustiani*, Sri Wahyuni and Syarifah Nur Fitria Dewi
Faculty of Engineering, Universitas Pasundan, Indonesia

ABSTRACT
Citarum River as the largest river in West Java gives an important role for the life of the community either
directly or indirectly. However the pollution that occurs on the Citarum River is very high that its tributary watercannot be used properly. One of the efforts to rehabilitate the quality of the Citarum River is by utilizing thewater quality modeling. The purpose of this study was to obtain the maximum BOD values that can be acceptedby the Citarum River for the rehabilitation purpose. The modeling prepared in this research was using StreeterPhelps equation. The data analyzed in this study is derived from the West Java Province Government monitoring
sampling in 2013, 2014 and 2015. Sampling area covers Dayeuhkolot area to Nanjung. The calculation result
using Streeter Phelps equation provides the concentration value of deficit oxygen and BOD load. The deficit
oxygen calculated by the model show its concentration was ranging between 3.20 mg/L and 3.68 mg/L, while
the maximum BOD load concentration is ranging between 8.06 mg/L and 23.83 mg/L. Using this value, thegovernment can create a strategy for managing the Citarum River so that its water quality can be returned inaccordance with its designation.
Keywords: Deficit oxygen, BOD, Upstream Citarum River, Water quality modelingthe modeling. Modeling is a more time-saving effort,
effort and cost compared to direct measurement. The
purpose of this research is to analyze the water
quality of Upper Citarum River by modelingdissolved oxygen (DO) and biochemical oxygen
demand (BOD) with Streeter Phelps method as theeffort to determine the maximum organic pollutant
load that can be discharged to water body. The
maximum load will contribute to regulate
wastewater discharge of industries and otheractivities along upstream region of Citarum River.

INTRODUCTION
Citarum River is the main river and one of thelargest river in West Java with a length of ± 297 km,
and the watershed area of 6.614 km2. Citarum Riverat Wayang Mountain located in District Kertasari
Bandung Regency at an altitude of 2182 m above
sea level and empties into the Java Sea. Citarum
River crosses 7 districts and 2 cities of Bandung,
Sumedang, Cianjur, Bogor, Purwakarta, Karawang,
Bekasi, Bandung and Cimahi. The Citarum rivers
amount to ± 36 tributaries. The Citarum River andits tributaries are utilized for various needs such as
agricultural irrigation, industrial activities, raw water
sources [1a], water sources for fisheries and ashydroelectric power plants.
Environmental damage in the upper part of the
Citarum river can be seen from the community's
behavior such as dumping garbage directly into theriver, resulting in the accumulation of garbage, thedecrease of land conservation areas, the density of
population settlements, river pollution by domestic
and industrial waste, and others causing floods,
drought, and landslides often occur in the upper
reaches of the Citarum River. This indicates that thequality decline has already begun in the upstream
area of Citarum [2].
Monitoring is the important aspect that needs tobeconducted
properlyinstakeholder’s
responsibilities, authorities and resources [3]. One
effort to monitor and control river water pollution is
to analyze the water quality data of the river using

METHODOLOGY
Research Location
This location the research takes place on theupper region of Citarum River with segments from
Dayeuhkolot to Nanjung. Some of the problems of
the Upper Citarum Watershed especially for the
Dayeuhkolot area to Nanjung are the development ofsettlements around river banks. The housing weredeveloped without good planning. There are many
daily activities of people who throw garbage directly
into the river, the remnants of fertilizers or pesticides
from agricultural areas, hospital waste, and cattle
manure waste. There are also development of the
textile industry and dispose of its waste into theriver, so that the river becomes the final disposal
without first processing. Figure 1 shows the Citarum
watershed as well as the research sites on the
upstream. The figure also gives information of959

SEE - Nagoya, Japan, Nov.12-14, 2018

watershed performance of Citarum River, where thelight brown shaded indicates a rather poor
performance area and the yellow shaded indicates
poor
performancearea,
considering
theenvironmental quality.

represent the level of pollution caused by activity ofindustry, agriculture and domestic and can represent
condition of incoming creek discharge. Figure 3
shows the schematic diagram of the research
segment for the purposes of calculating water quality
and pollutant load. Samplings were conductedduring dry season.

Figure 3. Diagram of domain segmentation.
Laboratory Analysis
Laboratory analysis was conducted using
Standard Methods [5]. The BOD measurements
consist of sample dilution, incubation for 5 days at
20°C and dissolved oxygen measurements before
and
after
incubation.
Dissolved
oxygenconcentration was measured using electrochemical
method. The method of determining dissolved
oxygen by electrochemical method is a direct way todetermine dissolved oxygen by means of DO meter.

Figure 1. Citarum Watershed [4] and research
location.

EquationsFigure 2 shows the location of the samplingstation on the upstream Citarum River.

Some of the equations used in the calculation ofwater quality and pollutant load in this study areequations for calculating ultimate BOD (Eq. 1)[6],[7], Streeter Phelps’ oxygen deficit (Eq. 2)[7] andmaximum pollutant load (Eq. 3). The maximum
pollutant load equation was modification of classic
Streeter Phelps equation which focusing in theremaining capacity of river water in receiving
pollutant.
k− dx

La = L0 e u(1)Where:
La = concentration of BOD ultimate (mg/L)
L0=concentration of BOD5 at initial position (mg/L)
Kd = deoxygenation rate coefficient (1/day)
x = distance from initial position (m)u = flowrate (m/s)

Figure 2. Sampling station points.
There are 5 points along the upper Citarum River
sampled. The sampling points have the following
coordinates:
6°59'29.8"S107°37'47.5"E,
6°59'21.3"S107°37'28.7"E,
6°59'07.3"S107°33'46.7"E,
6°58'41.5"S107°33'06.3"E,
6°56'50.8"S 107°32'05.1"E respectively for Stations
1, 2, 3, 4 and 5. While along the segment is divided
into sub-segment as the area of pollution load
calculation. Determination of sampling point is withthe consideration that the point can represent thewater quality condition of Upper Citarum River, can

D = D0 e

k
− ax
u

k
k
− ax
K d .La  − ud x
e
− e u  ( 2)+K a − K d Where:
D = deficit oxygen concentration ( mg/L)
ka = reaeration rate coefficient (1/day)
960

SEE - Nagoya, Japan, Nov.12-14, 2018

La = concentration of BOD ultimate (mg/L)
D0= concentration dissolved oxygen in x=0 (mg/L)

segmentation between Dayeuhkolot and Nanjung
area.
Table 1 shows the result of sample river water
analysis for the parameter of temperature, pH, DO
and BOD.

log La = log Dall
0.418


kd 
D0 

 log k a (3)

1 −
+ 1+


ka − kd Dall kd


Table 1. Laboratory analysis result
Sampling Location (Station No.)
Parameter

Where:
Dall : allowed oxygen deficit (mg/L)

Temperature

RESULT AND DISCUSSION
According to the water quality monitoring, theDO concentrations measured were under thegovernment standard. Figure 4 shows theconcentration of DO in the upstream Citarum Riverof the year 2013, 2014 and 2015. Figure 5 display
the concentration of BOD of Citarum River in theyear of 2013, 2014 and 2015.

2014

BOD concentration (mg/L)onormal

C

1

2

3

4

5

23.8

24.9

26.5

25.3

24.1

pH

-

5-9

6.61

6.15

6.51

6.41

6.41

DO

mg/L

≥6

3.2

4.6

3.3

6.1

3.4

BOD

mg/L

6

0.5

10.5

5.5

16

2.5

DO concentrations of almost all sampling points
do not meet the B class standard. 39 of 2000 except
only point 4 that meets the predetermined quality
standard of 6.1 mg/L. B class of the standard that
regulate the water quality for the purpose of raw
water for drinking water. BOD concentrations thatmeet the quality standard of Group B of Governor's
Decree no. 39 of 2000 are at point 1, 3 and 5. At thatpoint, there is already a pollutant input fromdomestic and non domestic waste, but still within thestandard limit. Calculations using the Streeter Phelps
model use DO and BOD data as the basis fordetermining pollution profiles. The Phelps Streeter
model links the rate of change in oxygen deficit with
distance to deoxygenation rate (oxygen depletion)and deoxygenation or reaeration (addition of oxygenin water).
In order to calculate the oxygen deficit and actual
DO, the value of saturated DO is necessary. The
saturated DO concentrations were obtained based on
actual temperature of river water. Table 2 displays
the saturated dissolved oxygen in the samplingstations.

maximum BOD concentration = 6 mg/L

2013

Standard**) Standard of West Java Province, Governor
Decree no.39, year 2000

Figure 4. DO concentration in the upstream Citarum
River.
200
180
160
140
120
100
80
60
40
20
0

Unit

Table 2. Saturated DO
Sampling
Temp
Station
(oC)
1
23.8
2
24.9
3
26.5
4
25.3
5
24.1

2015

Figure 5. BOD concentratioin in the upstream
Citarum River.
The monitoring of BOD concentrations were also
indicated that pollution has been occurred in the
recent year. Almost all BOD concentration wererecorded above the maximum allowed standard.
High concentration of BOD can be indicated as thepollution activities from the domestic andagricultural area.
Based on the monitoring results, primary
samplings were conducted in the more detail

Saturated DO(mg/L)
8.47
8.30
8.06
8.24
8.43

In every tributary point, the concentration of DO,
BOD and temperature after mixing were calculatedusing the mass balance equation considering eachwater discharge, then Eq. 1 was used to calculate theultimate BOD. The deoxygenation constant used is
the range kd for the Cikapundung River flow
between 0.10 - 0.37 [8], where Cikapundung River
961

SEE - Nagoya, Japan, Nov.12-14, 2018

The calculation of maximum load of BOD isused Eq. 3. The maximum load is affected by theactual BOD load and the deoxygenation rate.
Maximum load values can be viewed in Figure 8.

DO concentration (mg/L)

BOD ultimate (mg/L)

is one of the tributaries Citarum. This value issimilar and in the range of urban rivers in Indonesia
deoxygenation rate coefficient, i.e Citepus River,Rangkui River, Cimanuk River [9]-[11]. The
ultimate BOD value can be seen in Figure 6.
35
30
25
20
15
10
5

15
10
5
0
0

0
0

5

10

15

20

25

The modeling results show that the maximum
pollutant loads in the middle part of the research
segment are low. The lowest BOD load is 8.06 mg/L
located at km 12.51, whereas the highest BOD load
is 18.47 mg/L at km 19.03. In the middle section, thepollution has already high and the river capacity toperform self purification restricts any additional
pollutant to enter the water body.
CONCLUSION
Several important findings can be summarizedfrom this research, i.e.:• The pollutant source for Upstream Citarum River
comes from domestic waste, agricultural waste
and industrial waste.
• The sample measurement data shows for DO
parameters that almost all points did not meet thequality standard of Group B of Governor's
Decree No. 39 Year 2000.
• BOD concentration of the sample water also
show pollution in several points.
• The calculation result with Streeter Phelps
method shows that the DO concentration range is
as low as 3.20 mg/L to 3.68 mg/L. BOD
maximum load value of 8.06 mg/L to 23.83
mg/L.
• Based on the research results, the water qualityof the Upper Citarum River shows that they do
not meet the quality standard.
Based on the results, it is recommended a major
rehabilitation on the river water quality of Citarum
River, both in the pollution sources and in the river.

5
4
3
2
1
0
10

15

Figure 8. Maximum BOD load.

At km 0 to km 12.51 before mixing the BOD
value still meet the quality standard that is less than
6 mg/L. At km 12.51 after mixing up to km 16.23
before mixing the BOD value increases and exceeds
the quality standard that is more than 6 mg/L due tothe influent of domestic waste into the river. Highconcentrations of BOD occurred due to influent ofwaste from plastic factories and other industries
entering the river and densely populated areas. At
km 16.23 after mixing up to km 19.03 BOD
decreases which is usually due to the occurrence ofdilution by rain water.
The value of dissolved oxygen concentration canbe seen in Figure 7.

5

10Distance (km)Figure 6. BOD ultimate

0

5

20

Distance (km)DO concentration (mg/L)

20

15

20

Distance (km)Figure 7. Concentration of Dissolved Oxygen(mg/L)For DO concentrations ranging from km 0 to km
19.03 up and down and did not meet the quality
standard of Group B Governor's Decree no. 39 of2000 is less than 6 mg/L, due to the large number ofdomestic waste due to the density of the populationand industrial waste due to the existence of someindustries around the location of observation anddispose of its waste directly to the river andprocessing first.

REFERENCES[1] Afiatun E., Notodarmodjo, S., Effendi, A.J.,
Sidarto, K.A. Cost minimization of raw water
sources by integrated water supply systems (Acase study for Bandung, Indonesia). International
Journal of Geomate, June, 2018, Vol. 14, Issue
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SEE - Nagoya, Japan, Nov.12-14, 201846, pp. 32-39. DOI: 10.21660/2018.46.9 813[2] Fulazzaky M.A. Water quality evaluation system
to assess the status and the suitability of the
Citarum river water to different uses. Environ.
Monit. Assess, 168, 2010, pp. 669-684.
[3] Ginkel, C.H. Water Quality in Upper Citarum
River Basin: towards a better understanding of aheavilypollutedcatchment.
Student
Undergraduate Researach e-Journal, Vol 2, 2016,
pp.
[4] Ministry of Environment and Forestry. Citarum
Watershed (Map). http://sipdas.menlhk.go.id/
documents/ 170, access June 8, 2018.
[5] American Public Health Association-APHA;
American Water Works Association-AWWA;
Water Environment Federation-WEF. Standard
Methods for the Examination of Water andWastewater. 22nd edition. Washington. 2012.
[6] Ajayi,A.A., Peter-Albert,C.F., Ajojesu, T.P.,
Bishop, S.A., Olasehinde, G.I., Siyanbola, T.O.
Biochemical Oxygen Demand and Carbonaceous
Oxygen Demand of the Covenant University
Sewage Oxidation Pond. Covenant Journal of
Physical and Life Sciences (CJPL), Vol 4 no. 1,
2016, pp. 11-19.

[7] Chapra, S.C. Surface Water – Quality Modeling.
McGraw-Hill International Editions, 1997, p.391[8] Yustiani, Y.M., Nurkanti, M., Suliasih, N.,
Novantri, A. Influencing Parameter of Self
Purification Processes in the Urban Area of
Cikapundung River, Indonesia. International
Journal of Geomate, Vol. 14, Issue 43, 2018, pp.
50-54. DOI:10.21660/2018.43.3546[9] Yustiani, Y.M., Mulyatna, L., Pranata, F. The
Deoxygenation Rate Determination Based on
Physical Condition of River Body, Case Study ofCitepus River. Padjadjaran International Physics
Symposium 2013, AIP Conf. Proc. 1554, pp.
281-284. DOI: 10.1063/1.4820340[10] Yustiani, Y.M., Pradiko, H., Amrullah, R.H.
The study of deoxygenation rate of Rangkui
River water during dry season. International
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164-169. DOI: 10.21660/2018.47. 28822[11] Yustiani, Y.M., Wahyuni, S., Alfian, M.R.
Investigation on the deoxygenation rate of waterof Cimanuk River, Indamayu, Indonesia.
Rasayan J.Chem, vol. 11, no. 2, 2018, pp. 475481. DOI: 10.7324/RJC.2018.1121892

963

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

TURBIDITY REDUCTION OF THE RAW DRINKING WATER FORPILOT SCALE ELECTROCOAGULATION DEVELOPMENT*E. Afiatun1, H. Pradiko1 and E. Fabian1
Faculty of Engineering, Universitas Pasundan, Indonesia*Corresponding author

1

Abstract
A preliminary study to reduce the turbidity of drinking water by electrocoagulation method has beenpreviously investigated. Subsequent studies were then conducted with various turbidity and initial precipitation
treatments. Cikapundung River and Cisangkuy River are the main drinking water sources in Bandung with very
fluctuating turbidity. In the water supply system, turbidity is one of the important factors to be observed due toseveral reasons such as aesthetic, consideration of load to filtration, and disinfection process. This study aims toapplying the electrocoagulation process to reduce turbidity as an alternative to conventional coagulation system
by utilizing Poly Aluminum Chloride (PAC). Electrocoagulation is one method of water treatment by combining
the process of coagulation, flotation and electrochemistry. In this work, the electrocoagulation experiments were
set up by varying the current density from 10-30 volts with 5-30 minutes detention time so that the turbidity
variation could be created in a range of 25 Nelphelometric Turbidity Unit (NTU) up to 400 NTU. In addition, theexperiments were carried out by a precipitation process prior to the electrocoagulation process. The optimum
conditions of the electrocoagulation process with both initial and non-precipitated depositions occurred at an
initial turbidity of 400 NTU with electrocoagulation time and with a 100 RPM fast stirring for 10 minutes tohave a turbidity reduction of 99.52% and 98.28 %. The optimum current density for non-precipitating conditions
was 21.33 A / m2, whereas it is with precipitating of 46.22 A / m2. This optimum condition is useful for a pilot
scale development.
Keywords: electrocoagulation, optimum conditions, precipitation, raw water, turbidity

INTRODUCTION
Electrocoagulation is one method of water
treatment by combining the process of coagulation,
flotation
andelectrochemistry.
Theelectrocoagulation mechanism follows the basic
principle used in the electrolysis cell system, where
the anode and cathode are the site of the reductionoxidation reaction. The electrical energy applied tothe anode dissolves the aluminum into the solution
which then reacts with the hydroxy ion from thecathode to form aluminum hydroxy. Hydroxy
coagulates and flocculates suspended particles
resulting in a removal of solids from treated water[7]
The research that has been done on 100 NTU
turbidity concentration, obtain optimal condition ofremoval process under conditions with stirring,
optimum detention time 10 minutes, optimum
voltage 10 Volt, and optimal current density 21.33 A/ m2 [8]. In this research, the raw water treatment
process by electrocoagulation method is used to set
aside the variation of turbidity concentration at the
optimum condition of previous research. In thisstudy also tested the initial precipitation process
before the electrocoagulation process, as an effort toeliminate suspended particles.
The aim of this research is to analyze theefficiency of the electrocoagulation process using

Drinking water sources of Bandung City comefrom surface water that are Cikapundung River andCisangkuy River [1] – [3]. These raw water sources
are affected by upstream conditions, pollution along
the stream, as well as the climate and weather that
result in this surface water quality changing overtime. Water quality in Cikapundung river also
influenced by hydrological and land cover factors[4]. Such conditions lead to the need for raw water
treatment before being utilized. Turbidity is one ofpollutant parameters that is of primary concern as it
often exceeds the quality standard. According
Sawyer (2003) in the system of drinking watersupply turbidity is one important factor for several
reasons including aesthetic factors, filterability, thenumber of harmful organisms that affect thedisinfection process [5].
Raw water treatment process of Bandung City
generally use Poly Aluminum Chloride (PAC) as
coagulant to bind turbidity. The use of PAC
increasingly large due to the condition of the quality.
of raw water is getting more and more decreased [6].
The large use of PAC leads to a large and dangerous
sludge of processing waste. In this regard, more
efficient raw water treatment alternatives are needed
and produce less sludge.
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SEE - Nagoya, Japan, Nov.12-14, 2018

aluminum plate electrode to decrease theconcentration of turbidity parameters in Cisangkuy
River and Cikapundung River, which further
become the reference in pilot scale research.
RESEARCH METHODS
Tools and Materials
The tool components consist of: batch scale
reactor made of glass with dimensions of 12 cm x 9
cm x 12 cm with a working volume of 1 liter
equipped with 100 RPM magnetic stirrer, andfloculator with a speed of 60 RPM. The dimensionof the submerged aluminum plate is 7.5 cm x 7.5 cm
x 0.15 cm. The dc power supply used is with an
output voltage of 0 - 30 volts. Artificial turbidity ismade from mud samples originating from
Cikapundung and Cisangkuy Rivers.
Fig 2. Electrocoagulation reactor design [8].

Methods
The research was conducted on each current
density at each variation of turbidity with the
influence of the initial deposition process andwithout the influence of the initial deposition
process.
The research flow diagram can be seen in Figure1

Overall, the reactor design to be operated is asfollows:
Table 1. Reactor operation
Electrode TypeDistance between
Electrodes
Optimal Voltage
Optimal Detention
Time
Number of Electrodes
The submerged platearea
Rapid mixing
Slow mixing
Variety of turbidity
Time of precipitation
after electrocoagulation
process
The height of the platefrom the bottom of thereactorFig. 1 Flow Chart of Research
Reactor Design
The sketch of electrocoagulation reactor design
can be seen at Figure 2.

Aluminum Plate
1,5 cm10 Volts
10 minutes
One pair
7,5 cm x 7,5 cm
100 rpm, during
electrocoagulation
process
10 minutes 60 rpm
25, 50, 100, 200, 300,
and 400 NTU
15 minutes

2,5 cmData Collection
Samplig
Samples are taken at a height of ½ - ⅔ from thebottom of the reactor and approximately 5 cm fromthe edge of the reactor using a pipette.
Sample Turbidity Test
Testing of sample turbidity by using Lutron
turbidimeter model TU-2016.
Electrical Conductivity Test (DHL)965

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The sample was tested for conductivity by using
conductivity / TDS meter of Lutron model Yk-22CtNomodel.

Current
Density(A/m²)

Turbidity
afterProcessing(NTU)

Efficiency
(%)

67.56

1.79

96.42

21.33

1.74

98.26

46.22

0.94

99.06

67.56

0.42

99.58

21.33

0.37

99.82

46.22

0.00

100.00

67.56

0.00

100.00

21.33

0.90

99.70

46.22

0.49

99.84

15

67.56

0.00

100.00

16

21.33

0.66

99.84

46.22

0.21

99.95

67.56

0.00

100.006
Data Analysis
Turbidity of samples that have been treated with 7
electrocoagulation method then compared with8
initial turbidity. Electrocoagulation performance canbe known from the efficiency percentage in reducing 9
the turbidity level to meet the drinking water quality 10
standard of Indonesian Ministry of Health11
Regulation No. 492 / MENKES / PER / IV / 2010.
Meanwhile, the effectiveness of pollutant removal 12
can be calculated by the formula [9].
13
R% = (Cin − Cef)/Cinx 100%
Where :
R = Removal efficiency (%)
C in = Influent concentrations (NTU)
C ef = Effluent concentrations (NTU)

(1)

14

17
18

RESULT AND DISCUSSION
The research was conducted based on optimum
condition of preliminary research that has been
done. The research was conducted using
electrocoagulation process which was equipped with
fast stirring using magnetic stirrer at 100 RPM for
10 minutes, followed by slow stirring using
floculator with speed 60 RPM for 10 minutes.
Precipitation is done for 15 minutes.
The research was conducted on several variationsof turbidity, ie 25 NTU - 400 NTU. In addition, a
study was conducted by combining theelectrocoagulation process with the initial
precipitation process to see how much the effect of
the initial precipitation on turbidity removal.

No

1
2

25

10

3
4
5

50

10

Current
Density(A/m²)

Turbidity
afterProcessing(NTU)

Efficiency
(%)

21.33

2.07

91.72

46.22

1.92

92.32

67.56

1.57

93.72

21.33

3.38

93.24

46.22

2.56

94.88

200

300

400

10

10

10

10

25 NTU

50 NTU

100 NTU

200 NTU

300
300 NTU
NTU

400 NTU

Standard

Table 2. Electrocoagulation efficiency for eachvariation turbidity
DetentionTime(minutes)

100

DetentionTime(minutes)

Turbidity value through electrocoagulation
process on each variation of turbidity and current
density already meet the applicable quality standard.
Graphically, the turbidity removal on each variationof turbidity and current density can be seen in theFig. 3

Electrocoagulation Process in Each Variation of
Turbidity
The turbidity variations used in the study were25, 50, 100, 200, 300, and 400 NTU. Each turbidity
variation was treated using any variation of current
density resulting from 10, 20, and 30 Volt voltages
with a detention time of 10 minutes. The results
were then compared with drinking water quality
standards. The results were obtained as follows:

InitialTurbidity(NTU)

InitialTurbidity(NTU)

Fig.3 Turbidity removal at each variety ofCurrent Density
Based on Fig. 3, it can be seen that the final
turbidity value of the processing result is better
along with the increasing of current density used.
The higher the initial turbidity value the higher theeffluent value produced by the treatment, although
there is no significant difference.
Processing using the lowest current density to thehighest, all of which already meet the applicabledrinking water quality standards. Percentage of966

SEE - Nagoya, Japan, Nov.12-14, 2018

processing efficiency can be seen in Fig.4.
N
o

9
1
0
1
1
1
2

25 NTU

50 NTU

100 NTU

200 NTU

300 NTU

400 NTU

Electrocoagulation
Process
with
InitialPrecipitation
Further experiments were carried out by
combining the initial precipitation process withelectrocoagulation. The turbidity variations used inthis experiments were 25, 50, 100, 200, 300, and 400
NTU. Turbidity is then processed by using thecurrent density generated by a voltage of 10 and 20
volts. After the experiments, the results obtained asfollows :

1

50

26,27

5,62

78,60

3

100

34,96

5,66

83,80

4

200

41,06

5,55

86,49

5

300

6

400

55,00

7,05

87,19

62,67

6,90

88,99

7

25

19,27

3,57

81,47

8

50

26,27

3,29

87,48

21,33

46,22

200

41,06

2,79

93,20

300

55,00

2,23

95,95

400

62,67

1,93

96,92

Turbidity AfterProcessing(NTU)

Efficie
ncy
(%)

2,98

91,47

Standard
Fig. 5 Decrease of turbidity with initial
precipitation and electrocoagulation

Table 3. Efficiency of turbidity removal withinitial precipitation and electrocoagulation
Turbidity Curre
Turbidiafter
nt
Initialty After Efficie
InitialDens
TurbidProcessncy
Precipita
ity
ity
ing
(%)
tion
(A/m
(NTU)
(NTU)
(NTU)
²)
25
19,27
5,23
72,86

2

Curre
nt
Dens
ity
(A/m
²)

At a current density of 21.33 A / m², the turbidity
value after the initial precipitation andelectrocoagulation on each turbidity variation has
not been able to meet the applicable quality
standards, while at the current density of 46.22 A /m² the effluent obtained is able to meet theapplicable quality standards. The turbidity removal
by electrocoagulation and the initial precipitation ineach turbidity variation can be seen in Fig. 5.

Fig 4. Processing efficiency at any variety of
turbidity
From Fig. 4 it can be seen that the processing
efficiency has been very high, up to exceed 91%
although using the lowest current density. The
higher the current density given the higher theprocessing efficiency.

N
o

100

Turbidity
after
InitialPrecipita
tion
(NTU)
34,96

InitialTurbidity(NTU)

Based on Fig. 5 it can be seen that at a current
density of 21.33 A / m2 the final turbidity value
increases with increasing initial turbidity of thesample. However, at a current density of 46.22 A /m² the value of the final turbidity decreases with theincreasing initial turbidity. The processing efficiency
can be seen in Fig. 6.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig 6. Efficiency of turbidity removal with initial
precipitation and electrocoagulation

Fig. 8 Decrease of turbidity at current density
46.22 A / m²

From Fig. 6 it can be seen that the efficiency of
the turbidity removal at the initial precipitation
followed by the electrocoagulation process gives
better results at a current density of 46.22 A / m2.

Based on Fig. 8, it can be seen that the final
turbidity value of the processing with and without
the initial precipitation already meet the quality
standard. The processing efficiency with and without
initial precipitation at a current density 21.33 A / m²
can be seen in Fig. 9.

Comparison of Electrocoagulation With andWithout Initial Precipitation
Turbidity removal with electrocoagulation andwith or without initial precipitation at current densityof 21.33 A / m2 can be seen in Fig. 7.

Fig. 9 Efficiency of turbidity removal at current
density 21.33 A / m²
From Fig. 9 it can be seen that the efficiency ofelectrocoagulation
process
without
initialprecipitation gives higher yield than using the initial
precipitation. In each variation of turbidity there is asignificant difference in efficiency when using
current density 21.33 A / m2. The processing
efficiency with and without initial deposition at acurrent density 46.22 A / m² can be seen in Fig. 10.

Fig. 7 Decrease of turbidity at current density
21.33 A / m²

Based on Fig. 7, it can be seen that the final
turbidity value of the processing with the initial
precipitation still can not meet the quality standard,
while for the processing without the initial
precipitation can meet the quality standard. The
removal of turbidity with electrocoagulation withand without precipitation at a current density of
46.22 A / m2 can be seen in Fig. 8.

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SEE - Nagoya, Japan, Nov.12-14, 2018

[1] Afiatun, E., Notodarmojo, S., Effendi., A.J.,
Sidarto, K.A., Cost Minimization of Raw Water
Source by Integrated Water Supply Systems (a
Case
Study
for
Bandung,indonesia),
International Journal of GEOMATE, Vol. 14
Issue 46, 2018, pp. 32-39.
[2] Yustiani Y.M., Lidya L., Towards an
Information System of Modeling andMonitoring of Cikapundung River, Bandung,Indonesia, Procedia Engineering 154, 2016, pp.
353-360.
[3] Yustiani, Y.M., Lidya, L., Matsumoto, T.,
Rachman, I., Komariah, I. Formulation of theInformation System of River Water Quality in
the Cikapundung River, Bandung, Indonesia.
International Journal ofEngineering andTechnology. 2017, Vol 9 No. 1, pp: 137-142.
DOI: 10.21817/ijet/2017/v9i1/170901416[4] Pradiko, H., Arwin, Soewondo, P., Suryadi,
Y.,The Change of Hydrological Regime in Upper
Cikapundung Watershed, West Java Indonesia,
Procedia Engineering 125, 2015, pp.229-235[5] Sawyer, C.N., McCarty, P.L., Chemistry for
Environmental Engineering, 4th ed., McGrawHill, New York, 2003
[6] Afiatun, E., Pradiko, H., Prayoga, H., A
Turbidity Removal Strategy From The Water
Resources of Bandung City, Indonesia,
International Journal of GEOMATE, Vol. 12
Issue 34, 2017, pp. 57-61.
[7] Kuokkanen, V. Kuokkanen, T. Rämö, J. &Lassi, U. 2013. Recent Applications ofElectrocoagulation Treatment of Water andWasterwater. Green and sustainable Chemistry.
89-121.
[8] Pradiko, H., Afiatun, E., Fabian, E., Influence of
Mixing and Detention Time in Electro
Coagulation Process to Treat Raw Water at
Badak Singa Water Treatment Plant, Indonesian
Journal of Urban and Environmental Technology,
Vol 1, Number 2, 2018, pp. 137-150.
[9] Nasrullah, M. Singh, L. & Wahid, Z.A. ,Treatment of Sewage by Electro Coagulation andthe Effect of High Curent Density. Energy andEnvironmental Journal. Vol. 1, 2012.

Fig. 10 Efficiency of turbidity removal at current
density 46.22 A / m²
From Fig. 10 it can be seen that the efficiency ofelectrocoagulation
process
without
initialprecipitation gives higher yield than using the initial
precipitation. At initial turbidity of 25 NTU there issignificantly difference in efficiency, whereas forother initial turbidity variation there is no
significantly difference. The large number ofparticles causes the distance between the particles
closer, resulting in faster flocculation, larger floc
size and more particle bonding. While at the time ofinitial deposition, large particles have precipitated inadvance so that floc is more difficult to form
CONCLUSION•••At the current density 21.33 A/m2 the final
turbidity value of the electrocoagulation processwith the initial precipitation still can not meet thequality standard, while for the processing
without the initial precipitation can meet thequality standard.
At the curent density 46.22 A/m2 the final
turbidity value of the electrocoagulation processwith and without the initial precipitation alreadymeet the quality standard.
The results in this study became the basis ofsubsequent research on a pilot scale

REFERENCES

969

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

GEOSPATIAL MODEL OF PHYSICAL AND SOCIAL
VULNERABILITY FOR TSUNAMI RISK ANALYSIS
Abu Bakar Sambah12, F. Miura3, Guntur1, Sunardi1, and A. F. Febriana1
Faculty of Fisheries and Marine Science, University of Brawijaya, Indonesia; 2Marine Resources
Exploration and Management Research Group, University of Brawijaya, Indonesia, 3Faculty of Engineering,
Yamaguchi University, Japan
1

ABSTRACTTsunami risk assessment is required to support preparedness activities and effective disaster reduction. In thisstudy, the analysis of physical and social vulnerability for tsunami risk assessment was applied for tsunami
mitigation activities in coastal areas. The analysis was applied in the southern coastal area of East Java,
Indonesia. The application of Geographical Information System (GIS) was used to capture, store, manipulate,analyze, manage, and visualize geographic data that used for tsunami risk analysis. GIS make possible inintegrating a complex layer of geographic phenomenon and the parameter of tsunami vulnerability. In this case,the spatial overlay of physical and social vulnerability was done using spatial multi-criteria approach. Physicalvulnerability parameters analyzed in this study were elevation, slope, land use, and distance from the coast.
While the social vulnerability parameters include number of population, age distribution, number of women, andpeople with disabilities. The results described the visualization of possible damage and loss areas that may result
from tsunami attack. The analysis illustrated that the most vulnerable areas of the tsunami were areas with low
elevation, very sloping slopes, areas that close enough to the coastline and the land use type of residential class.
The areas with high vulnerability class also illustrated by social vulnerability parameters especially population
density. The estimates of affected areas due to tsunamis can help the decision-makers in mitigating the possible
consequences of tsunamis, managing the emergency response related to tsunami disaster, and developing plans
for recovery and reconstruction after the tsunami event.
Keywords: Geospatial, Tsunami, Vulnerability, Risk

aspects and dimensions [7].
The negative impact of tsunami occurrence incoastal areas is not a recent phenomenon, but modelof study for assessing the impact damage,vulnerability, and risk is a relatively new trend [8].
The project of Coastal Risk Analysis for Tsunamis
and Environmental Remediation (CRATER) has
been applied for assessing tsunami vulnerability incoastal area using the parameters of infrastructural,geomorphological,
andecologicalfeatures,elevation, coastal proximity, and parameters of landuse [9]. Moreover, the Papathoma Tsunami
Vulnerability Assessment (PTVA) model has been
applied also for providing initial assessments ofbuilding vulnerability [10]–[11]–[12].
Indian Ocean includes South area of East Java
Indonesia is located at one of the most active
geological subduction zones. During December
2004 and July 2006 most recent seaquakes followedby huge tsunamis and it is expected to occur also in
the near future [7]. Highly destructive tsunamis havebeen recorded at a number of locations in South
Java, Indonesia (East Java in June 1994, Cilacap andPangandaran in July 2006) [13]–[14]. It affected
almost every sector of economy, including
agriculture, fishery, tourism, transportation, housing,

INTRODUCTION
The tsunami disaster has been considered amajor disaster such that many researches have been
done to assess both its vulnerability and risk forcoastal areas. Tsunami risk assessment has been
done to quantify the potential damage and losses
area due to tsunami [1]–[2]. Tsunami risk
assessment needs an integrated analysis ofgeospatial data related to the tsunami hazard and theelement of risk [3]. In order to assess tsunami risk,
the assessment of vulnerability is necessary. In
common, risk assessment implies two dimensions;the assessment of hazard (external part), and theassessment of vulnerability (internal) [4]. Tsunami
vulnerability is analyzed after the evaluation oftsunami potential and probability. It depends on how
close the communities are to the hazard source, andtheir social and economic characteristics [5].
Vulnerability also defines as “The conditions
determined by physical, social, economic, andenvironmental factors or processes, which increase
the susceptibility of a community to the impact ofhazards”[6]. Vulnerability is trans-disciplinary andmulti-dimensional, which covers social, economic,
physical, political, engineering and ecological
970

SEE - Nagoya, Japan, Nov.12-14, 2018and health [15].
In order to construct better disaster mitigation
due to tsunami, appropriate analysis related to thetsunami vulnerability and risk assessment isnecessary. The application of geospatial analysis fortsunami vulnerability and risk assessment has also
applied using remote sensed dataset [12]–[16]–[17]–[18]–[19]. Another geospatial approaches has also
applied soil type, urban form and social dataset forassessing potential natural hazard [20] and has
determined the tsunami-vulnerable area bycomparing the map tsunami-affected area and the
topography data, which is related to land elevation,
land use class, and the distance from the coast [21].
This study tried to assess the potential of affectedarea as the impact of tsunami, in which tsunami
vulnerability areas will be calculated using both
physical and social vulnerability parameters.

DatasetMETHODS

In order to create tsunami vulnerability map ofresearch area, the parameter of both physical andsocial vulnerability was collected. Physicalvulnerability parameter includes elevation, slope,land use, and coastal proximity. Moreover, social
vulnerability parameter consists of population
density, gender, age, and disabilities. The elevationand slope data was created from The ASTER Global
Digital Elevation Model (ASTER GDEM) version 2.
ASTER
GDEM
was
collected
fromhttps://gdex.cr.usgs.gov/gdex/. The analysis ofLandsat 8 OLI satellite image was applied to create
land use map. Landsat image was collected fromhttps://earthexplorer.usgs.gov/. In addition toprepare coastal proximity, digital vector map of theresearch area was applied. Social vulnerability data
was collected from Indonesia Central Bureau of
Statistics.

Research Area

GEOSPATIAL ANALYSIS

Tsunami vulnerability mapping using physicaland social vulnerability parameter was applied in the
coastal area of Blitar district, East Java, Indonesia(Fig. 1). This area is bordered by District of Malang,
East Java on the East part. It also directly faces the
Indian Ocean on south part.
Geographically, Blitar district is located at thesouthern of East Java with a height of 167 meters
above sea level, at coordinates of 111° 40 '- 112° 10'
East longitude and 7° 58 '- 8° 9' 51 "South latitude.
Blitar district has a 45 km-long coastline with
26,100 hectares of 4 nautical miles areas, and 63,330
hectares of 12 nautical miles.

Data analysis was done through geospatial
analysis. The analysis consists of four steps (Fig. 2).
It starts with data acquisition, pre-processing,geospatial analysis, and result. Data consist of two
data type, raster and vector dataset. ASTER GDEM
was applied for elevation and slope data as one ofphysical vulnerability data. Moreover, Landsat 8
OLI satellite image as raster data was applied inorder to create land use map.

Fig. 1

Research area.

Fig. 2

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Vector data includes base map of research area,
and it was applied for creating costal proximity, thedistance from coast line to the hinterland. All
parameters were classified in five classes based on
the physical tsunami vulnerability. Social
vulnerability data was taken from Indonesia Central
Bureau of Statistics. Data were classified and scoredbased on the criteria of social tsunami vulnerability.
It consists of population density, gender, age, anddisabilities.
Data analysis for creating tsunami vulnerability
map, as a combination of physical and social
tsunami vulnerability, was done using cell-basedmodelling in the term of geographical information
system. All parameter applied in the model wereconverted to raster dataset. This data consist of amatrix of cell and were classified in different weight.
Weighted overlay is a type of suitability analysis
that helps in analyzing geographic data based on
multiple criteria. Weighted overlay allows the user
to combine weight of several different types of
information and visualize it, in which multiple
factors can be evaluated at once [22]–[23]. The
illustration as described in Fig. 3.

1=low, 2=slightly low, 3=medium, 4=slightly high and
5=high vulnerabilitysocial vulnerability*weight

Weighted spatial overlay

physical vulnerability*weight

Table 1 Physical vulnerability classes and weight[12]–[24]–[25]–[26]Fig. 3

Vulnerability classes

Fig. 4

1

2

3

Tsunami vulnerability
physical parameter

4

5

map

based

on

Figure 4 describes tsunami vulnerability map incoastal area of Blitar district based on physicalparameters. Diverse elevation of research area
causes the different level of vulnerability. In somecoastal areas close to the ocean covered by highcliffs and it described low class of tsunami
vulnerability. The area of high vulnerability is foundonly in areas with elevations close to 0 or less than 5
meters. This area identified as bay area with somesettlement

Illustration of weighted overlay throughcell-based modelling.

Physical Vulnerability

Social Vulnerability

Four physical vulnerability parameters wereconverted to raster cell type and analyzed using
weighted overlay to create map of tsunami
vulnerability. Raster cells of all parameters wereclassified based on its value to five classes ofvulnerabilities represent low, slightly low, medium,slightly high and high vulnerability. The
vulnerability classes and its weight as described inTable 1, and tsunami vulnerability map as describedin Fig. 4.

Social vulnerability can be defined as the
exposure of groups or individuals to unexpectedchanges and disruption to livelihoods [27]. Social
vulnerability also can be measured as a result ofsocial and place inequalities [28].
Moreover, it defined also as the limitation of acommunity to the impact of natural disasters that
influence its ability or resilience in order to mitigate,recover, and preparedness from the impacts. [29].
Social vulnerability map was created using four972

SEE - Nagoya, Japan, Nov.12-14, 2018

parameters and weighted equally. The calculation
was based on the criteria as described in Table 2.
Social vulnerability map as described in Fig. 5.
Table 2

Total vulnerability illustrated the vulnerability area
due to tsunami in which four parameters of physicalvulnerability and four parameter of social
vulnerability were combined (spatial overlay) as
described in Fig. 6.

Social vulnerability criteria and weight[3]* determine the factor of each village divided by number
per sub-district** the same value for all places on all the social variables*** number of elderly and children
Vulnerability classes

Fig. 6

1

2

3

4

5

Tsunami vulnerability map

Table 3 Total vulnerability area

Vulnerability classes

Fig. 51

2

3

4

Vulnerability classes

Area (Ha)

1
2
3
4
5

low
slightly low
mediumslightly highhigh

50,3204
176,5883
824,6320
383,9447
4,2357

Vulnerability maps as described in Fig. 6
includes the information of total area pervulnerability classes (Table 3) may be good forcommunication tool for disaster preparedness [32].
The information of the map also plays an importantrole for effective early warning system. People often
do not understand their risk; the social vulnerability
map provides information on village or sub-districts
with relatively high vulnerability. By integrating thephysical and social vulnerability in the early warning
system, coastal communities will be aware of theirrisks. As consequent, it will enhance community’s
preparedness for tsunami.

5

Tsunami vulnerability map based on social
parameter

DISCUSSION
Vulnerability represents the susceptibility of agiven population to damaging effects from exposure
to hazardous events [30]–[31]. The combination ofphysical and social parameters for assessing tsunami
vulnerability area using cell-based modelling is oneof the approaches in order to support risk analysis.
Cell-based modelling calculated every single pixelof the parameter based on its score and weight. The
analysis follows arithmetic logic as below.
Vulnerability = ∑ Wi Xi
Total vulnerability =∑ (physical vulnerability*weight)+(social
vulnerability*weight)

No

CONCLUSION
Geospatial model followed by the weighted cellbased processing described good result in assessing
tsunami vulnerability area. The combination ofphysical and social vulnerability parameters inmodel also described good approaches in order tocreate tsunami vulnerability map. The map isimportant in determining the possibility area that
could be affected by tsunami wave. The result
illustrated important information in many

(1)

(2)

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SEE - Nagoya, Japan, Nov.12-14, 2018

applications to support disaster risk management andmitigation strategies. Furthermore, in order to obtainan accurate tsunami vulnerability map andinundation map, this method can be applied byadding other vulnerability parameter such as coastal
ecology (coral reef), barrier island, coastal type, andalso tsunami direction.

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Method) for Assessing Tsunami Vulnerability
at The Regional Scale Using ASTER Imagery,
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2, 2010, pp. 55-74.
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Tsunami Vulnerability Assessment And Its
Implications For Coastal Hazard Analysis And
Disaster Management Planning, Gulf ofCorinth, Greece, Natural Hazards and Earth
System Sciences, Vol. 3 No. 6, 2003, pp. 733747.
[11] Papathoma, M., Dominey-Howes, D., Zong, Y.
andSmith,D.
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TsunamiVulnerability, An Example from Herakleio,
Crete”, Nat. Hazards Earth Syst. Sci., Vol. 3
No. 5, 2003, pp. 377-389.
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Sensing and Spatial Multi-Criteria Analysis for
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Prevention and Management, Vol. 23 Issue 3,
2014, pp. 271 – 295.
[13] Synolakis C., Imamura F., Tsuji Y., Matsutomi
H., Tinti S., Cook B., Chandram Y.P., andUsman M., Damage, Condition of East Java
Tsunami of 1994 Analyzed. Eos, Transactions,
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June 27, 1995, pp. 257, 261-262.
[14] Reese, S., Cousins, W,J., Power, W.L., Palmer,
N. G., Tejakusuma, I. G. and Nugrahadi, S.,
Tsunami Vulnerability of Buildings and People
In South Java–Field Observation After the July
2006 Java Tsunami. Natural Hazards and Earth
System Science, Vol. 7, 2007, pp. 573-589.
[15] Levy, J.K. and Gopalakrishnan, C., Promoting
Disaster-Resilient Communities: The Great
Sumatra-Andaman Earthquake of 26 Deceber
2004 And The Resulting Indian Ocean
Tsunami. Water Resources Development, Vol.
21, 2005, pp. 543-559.
[16] Sinaga, T.P., Adhi, N., Yang-Won, L. andYongcheol, S., GIS Mapping of Tsunami
Vulnerability: Case Study of the Jembrana
Regency in Bali, Indonesia, KSCE Journal of
Civil Engineering, Vol. 15, No. 3, 2011, pp.
537-543.
[17] Karen, E., K. C. Joyce, S. Wright, V.
Samsonov, and V. G. Ambrosia, Remote
Sensing and the Disaster Management Cycle,
In Advances in Geoscience and Remote
Sensing, edited by G. Jedlovec. Croatia:
InTech, 2009.
[18] Yamazaki, F., K. Kouchi, and M. Matsuoka,
Tsunami Damage Detection Using ModerateResolution Satellite Imagery, Proceeding of the

ACKNOWLEDGEMENTS
The research is a part of tsunami risk mapping
project in coastal area of East Java funding by
Ministry of Research, Technology and Higher
Education Republic of Indonesia. Authors arethankful too to METI and NASA for the ASTER
GDEM products, USGS for Landsat 8 OLI image,and Geospatial Information Agency of Indonesia(BIG) for providing the basic map of the study area.
We also thank to Laboratory of Disaster Prevention
System, Yamaguchi University, Japan andLaboratory of Marine Resources Exploration,
Brawijaya University Indonesia.
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Cutter, S.L., Mitchell, J. T. and Scott, M.S.,
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Geneva, 2004.
Post J., Zosseder K., Strunz G., Birkmann J.,
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and Roberts, S., Quantifying Social
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8th U.S. National Conference on Earthquake
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Fuad, and Defrian Marza Arisandi. Assessing
Tsunami Vulnerability Areas Using Satellite
Imagery and Weighted Cell-Based Analysis.
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[24] Van Zuidam R.A., Guide To GeomorphologicAerial Photographic Interpretation and
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Enschede, 1983, The Netherlands.
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Level Mapping in Sikka, East Nusa Tenggara,

Journal of Tropical Marine Science andTechnology, Vo. 1, No. 1, June 2009, pp 48-61,(Indonesia edition).
[26] Iida K., Magnitude, Energy And Generation
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[27] Adger W.N., Social Vulnerability to Climate
Change and Extremes In Coastal Vietnam.
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Catastrophe: The Changing Face ofVulnerability Along The Hurricane Coast. Ann
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HYDROLOGICAL AND NITRATE LOADING MODELING IN LAM
TAKLONG WATERSHED, THAILAND

1Chau Ngoc Tran1,2, *Chatpet Yossapol1
School of Environmental Engineering, Institute of Engineering, Suranaree University of Technology,
Thailand2
Faculty of Engineering-Technology-Enviroment, An Giang University, Vietnam
ABSTRACT

Water pollution is largely associated with the growth of agriculture, urbanization, and industrialization. By theyear 2016, the quality of significant surface water sources in Thailand has been evaluated and categorized as 34%
good quality, 46% fair quality and 20% poor quality. According to the Pollution Control Department of Thailand,
the lower Lam Taklong river, one of the critical watersheds of Thailand, is considered to have a poor water quality.
In Lam Taklong watershed, non-point sources area approximately covered 89% of the total area, those sources
became the significant contributors of water pollutants, particularly nutrients to the Lam Taklong watershed. Plus,water quality researches of the watershed were carried out with many different watershed models, but SWAT
model has not been applied to allot the pollutant loading from diffuse sources. Therefore, the main objective of
this study is to apply the SWAT model to simulate flow and nitrate from 2007 to 2013, and allocate NO3- loading
in upstream is lower than downstrem of the Lam Taklong watershed. The results of the study can be a useful tool
for the management of surface water resources in the Lam Taklong watershed.
Keywords: SWAT, Lam Taklong watershed, Nitrate, Diffuse source
SWAT model could be a useful tool for water
resources managements in Lam Takong River basin.
The water flow change at the outlet of Kosynthos
river watershed affected the nutrient loads [3].
Previous studies in Lam Taklong basin have notestimated relationship between flow and nitrate in
LTW.
In this study, ArcGIS integrated with the SWAT
model, which can realistically represent the spatial
variability of watershed characteristics, will be used
to study upstream and downstrem areas in Lam
Taklong River basin. SWAT model is selected for thisstudy because it is included channel degradation
routine with detail appropriate for watershedmanagement [4]. The results could be a useful tool forwater resources planning in LTW.

1. INTRODUCTION
Lam Taklong watershed (LTW) is one of thecritical watersheds of Thailand. It is a part of the Mun
river watershed, in the Northeastern region ofThailand. In addition, it has a role of drainage,
recreation, and environmental conservations. LTW
was covered with extended large forests in the past.
At the present, most areas have been invaded,
deforested and converted into communities,
farmland, orchards and deserted areas and others tokeep up with local progress.
Lam Taklong watershed has a high economic
growth rate but is still facing water scarcity.
Wijitkosum [1] analyzed the water situation in the
Watershed which was subject to the economic plan of
the government. LTW was on the brink of a water
shortage and this problem was at the peak during the
maximum water usage and minimum water asset. As
result of the economic value, it is necessary to
conduct a hydrological and water quality modelingresearch in Lam Taklong watershed. The results show
the accuracy of the flow simulation, helping planners
to come up with a reasonable flow and water quality
management.
Netnapa [2] applied Soil and Water Assessment
Tool (SWAT) model for evaluations streamflow,
sediment, nutrient loading simulations in Lam
Takong River basin. That author demonstrated that

2. MATERIALS AND METHODOLOGY
2.1. Study Area
Lam Taklong River basin is a part of the Munwatershed in Northeastern region of Thailand, is also
a sub-basin of the great Mekong river. The length of
the river is 220 km, originated from Khao Yai
National Park, has an area of 3,518 km2 covering six
districts in Nakhon Ratchasima province and more
880,000 population reside [5] (Fig. 1).

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SWAT-CUP. Automatic calibration and uncertainty
analysis capability is directly incorporated in
SWAT2012 via the SWAT-CUP software developed
by Swiss Federal Institute of Aquatic Science andTechnology [7] and R2 [8] will be selected as theefficiency criterion. SWAT-CUP includes automatedas well as the semi-automated program SUFI2 formodel calibration.
The sensitive parameters from the sensitivity
analysis results will be considered in the calibration
process. The following parameters will be included in
the calibration CN2, ALPHA_BF, GW_DELAY,GWQMN.
Fig. 1 Lam Taklong watershed.
(Wijitkosum, 2010)

2.3 Input Data
The main input data for simulating thehydrological processes in ArcSWAT are the base mapdata, meteorological data and observed data. The
necessary data is showed in Table 1.

LTW is under the influence of southwest andnortheast monsoon. From May to October, thesouthwest monsoon brings moisture from the Indian
Ocean causing rain, peaking in August and
September. The average amount of rainfall is 1,454
mm (2010).

Table 1 Model input data sources for the Lam
Taklong watershed

2.2 Model Description
ArcGIS 10.1 software is integrated theSWAT2012 (Soil and Water Assessment Tool) model
to calculate the flow in Lam Taklong watershed.
SWAT model was selected for this study due to awide variety and with proper testing [6].
The subwatershed discretization of SWAT
divides the watershed into 29 subbasins. Then,
subbasins continue to be partitioned into 309 multiplehydrologic response units (HRUs) based on soil andland use distribution of the watershed. For each HRU,
the land phase of the hydrological cycle is modeled,and flow from each HRU are calculated. Then flowfrom HRUs within a subbasin are summed to get flowfrom this subbasin.
For a subbasin located downstream of anothersubbasin, flow from land phase are added at the outletof the upstream subbasin and then continue to berouted through the channel.
The necessary data is collected for simulation offlow in the Lam Taklong river. The main input data
for simulating the hydrological processes in Arc
SWAT are the base map data, meteorological dataand observed flow data.
The ArcSWAT2012 interface is used to delineate
the Lam Taklong basin based on an automatic
procedure using Digital Elevation Model (DEM)
data. A DEM grid map with a 30m spatial resolution
was available. Moreover, a mask map which
identifies the focused area for delineation to reduce
the processing time and a burn-in river map whichhelps to accurately predict the location of the stream
network was also input.
Calibration is used autocalibration tools in

Data type

SourceDetailTopography(DEM)
30mx30m

Land Development
Department

Elevation, slope

Soil
Land use
Weatherstations
Flow ofwater
Water
quality

Land Development
Department
Land Development
Department
Thai Meteorological
Department
Lam TaKlong Water
Supply &Maintenance
Project
Regional Environment
Office 11

Spatial soil variability
Soil types and properties
Land cover classificationand spatial representation
Daily precipitation
Temperature
Relative humidity
Wind speed
Solar radiation
M89 and M164 stations(m3day-1)
Sediment (mgl-1)
Nitrate nitrogen (mgl-1)

The base map data is overlayed by land use andsoil data. Climate data input consists of temperature,
relative humidity, wind speed, solar radiation; theweather data and the rainfall data. Observed dataconsists of concentration of sediment and nitrate
nitrogen.
3. RESULT AND DISCUSSION
The Lam Taklong watershed is delineated into
sub-basins using the digital elevation map (30m) and
it is divided in 29 subbasins outlet of Lam Taklong
River (Fig 2).

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ALPHA_BF (0.287), GW_DELAY (51.42),
GWQMN (1.89) from initial default conditions.
The sensitive parameters were replace SWAT
model to simulate flow and nitrate loading. The
simulated flow was compared to observed flow in
upstream LTW.
25.00

15.00
10.00

Fig. 2 Subbasins of lam taklong watershed.

5.00
0.00

Land use data are required for pollution
assessment because of activities that we do on land
can affect on generate the pollutants. The digital landuse data were obtained from Land Development
Department (LDD) in the year 2011.
The U.S. Natural Resource Conservation Service(NRCS) classifies soils into 4 hydrologic groups
based on infiltration characteristics of the soils
including group A (high infiltration rate), group B(moderate infiltration rate), group C (slow infiltrationrate) and group D (very slow infiltration rate). Soil
data was obtained from LDD including fourteen soil
series with soil texture class and quantitative particle
size distribution analysis by LDD were transformed
to hydrologic soil group.
The delineated sub-basin map, land use, and soil
map will be overlaid. SWAT simulate different land
use in each sub-basin. Lam Taklong River
watershed’s DEM, land use and soil data areintegrated to accumulate flow direction, and stream
network in Lam Taklong River (Fig 3).

Jan-07
May-07
Sep-07
Jan-08May-08
Sep-08Jan-09
May-09Sep-09Jan-10May-10
Sep-10Jan-11
May-11
Sep-11
Jan-12
May-12
Sep-12
Jan-13May-13
Sep-13

Flow (cms)20.00

Flow_upstream (cms)
Observed Flow_upstream (cms)Fig. 4 Simulated monthly flow and observed
monthly flow at upstream of LTW
The simulated flow values are compatible withminimum observed flow values in lower LTW from
0.4 to 1.8 m3/s (Fig. 4). Similarly, simulated flow
values in upper LTW from 1.6 to 2.7 m3/s is close to
the average observed flow value. The simulated flow
at subbasin outlet of LTK is shown Fig. 5 during 7
years.
25
15
10
5
0

Jan-07
May-07
Sep-07
Jan-08May-08
Sep-08Jan-09
May-09Sep-09Jan-10May-10
Sep-10Jan-11
May-11
Sep-11
Jan-12
May-12
Sep-12
Jan-13May-13
Sep-13

Flow (cms)20

Flow_downstream (cms)
Observed Flow_downstream (cms)Fig. 5 Simulated monthly flow and observed
monthly flow at downstream of LTW
The average monthly observed and simulated
flow from 2007 to 2014 for an outlet of LTW ispresented in Fig. 5. SWAT has simulated during atime period when the average daily precipitation is
input date. The model was validated for an averagetime period from January 2007 to July 2014. Test
results show that with the modified values for themodel SWAT, the Nash-Sutcliffe R2 for monthly total
flows was 0.66.
Results obtained by using the model’s modified
values for simulating flow accentuate the critical needfor model calibration in order to ensure thathydrologic processes are well represented on awatershed.

Fig. 3 Stream network of Lam Taklong watershed
3.1 Simulated monthly flow in Lam Taklong
Watershed
Calibration is conducted in lower LTW by
adjusting input four parameter values CN2 (-0.1516),

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In contrast to upstream, downstream flow values areinversely proportional to nitrate loading values. They
are showed in Fig. 8.

Jul-12

Jan-13

Jul-11

Jan-12

Jul-10Jan-11

Jul-09Jan-10Jul-08Jan-09Jul-07

Jan-08

Jul-13

4. CONCLUSION
For this study, calibration process was conductedwith four parameters CN2, ALPHA_BF,
GW_DELAY, GWQMN. The R2 value 0.66 iscompared to the results from Zhao et al [9] theregression coefficient of measured value andsimulation value was 0.63 and it shows that thecorrelation between observed and simulated monthly
runoff is good. This means that the SWAT model issuitable for fluid flow and nitrate. Determination of
accurate parameters in calibration when modelingwatersheds are vital for simulating streamflow data
corresponding to measured values.
The simulated flow and nitrate loading values in
LTW upstream have a proportional relationship,
oppositely in downstrem they have inverse ratio from
May to October.

3.3 The influence of the flow on nitrate nitrogenloading
3.3.1 Upstream area
The simulated results of flow and nitrate loading in
upstream of LTW showed that they have a
proportional relationship (Fig. 7).
2.00

0.40

1.00

0.20

Flow (cms)

3.00

0.60

0

As the flow rate increases, nitrate loading values tend
to decrease from May to October. However, from
November to January flow and nitrate loading value
have the same downtrend.

However, the upper area has the high nitrate loadingfrom July to September and from March to June in thelower area. In contrast, both of two areas had the low
nitrate loading is from december to January. This
result is consistent with Netnapa’s study [2] that
September was the month with the highest NO3-N
while January and December were the lowest months.

0.80

1

0.20

Fig. 8 Relationship of flow and nitrate loading indownstream of LTW.

Fig. 6 Simulated nitrate loading in upstream anddownstream of LTW.

NO3 Loading (kg/ha)

0.40

NO3_downstream (kg/ha)
Flow_downstream (cms)NO3_upstream (kg/ha)
NO3_downstream (kg/ha)

1.00

2

0.60

0.00

0.20

Sep-13May-13Jan-13

Sep-12

May-12

Jan-12

Sep-11

May-11

Jan-11

Sep-10May-10Jan-100.00

0.80

Jan-10
Apr-10Jul-10
Oct-10Jan-11
Apr-11
Jul-11
Oct-11
Jan-12
Apr-12
Jul-12Oct-12
Jan-13Apr-13
Jul-13Oct-13

Loading (kg/ha)

0.40

0.00

3

1.00

0.60

Jan-07

Nitrate Loading (kg/ha)

Sediment and nitrate was calibrated after flow
calibration. Simulated nitrate values in downstream ishigher upstream.

Flow (cms)

3.2 Nitrate loading simulation in Lam Taklong
Watershed

ACKNOWLEDGEMENTS

0.00

The author thanks anonymous reviews for theircomments and suggestions; Dr. Chatpet for his huge
contribution in improving the paper; the Land
Development Department, Regional Environmental
Office 11, the Royal Irrigation Department, the Thai
Meteorology Department, Lam Ta Klong Water
Supply and Maintenance Project for providing data
and results from SWAT model; and the SUT-PhD
scholarship for ASEAN countries for financial
support in Suranaree University of Technology inThailand.

NO3_upstream (kg/ha)
Flow_upstream (cms)Fig. 7 Relationship of flow and nitrate loading
in upstream of LTW
Both of flow and nitrate loading value in LTW
upstream have the lowest value in January and thehighest in September.
3.3.2 Downstream area

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REFERENCES[1] S. Wijitkosum and T. Sriburi, “Evaluation of
Water Resource Management In Lam Ta Kong
Watershed : The Water Scarcity Area ofThailand,” vol. 4, no. 4, pp. 1047–1057, 2010.
[2] N. Pongpetch, P. Suwanwaree, C. Yossapol, S.
Dasananda, and T. Kongjun, “Using SWAT toassess the critical areas and nonpoint source
pollution reduction best management practices in
Lam
Takongriver
basin,
Thailand,”EnvironmentAsia, 2015.
[3] V. Pisinaras, C. Petalas, G. D. Gikas, A. Gemitzi,
and V. A. Tsihrintzis, “Hydrological and water
quality modeling in a medium-sized basin using
the Soil and Water Assessment Tool (SWAT),”
Desalination, vol. 250, no. 1, pp. 274–286, 2010.
[4] N. A. Staley, T. Wynn, D. Ph, B. Benham, G.
Yagow, and V. Tech, “Modeling Channel
Erosion at the Watershed Scale : Model Review
and Case Study,” no. March, 2006.

[5] N. Pongpetch, P. Suwanwaree, C. Yossapol, S.
Dasananda, and T. Kongjun, “Sediment andNutrient Load Environmental Factors of Lam
Takong River Basin, Thailand,” Adv. Mater.
Res., vol. 1030–1032, pp. 594–597, 2014.
[6] J. G. Arnold, J. R. Kiniry, R. Srinivasan, J. R.
Williams, E. B. Haney, and S. L. Neitsch, “Soil& Water Assessment Tool: Input/output
documentation. version 2012,” Texas Water
Resour. Institute, TR-439, pp. 207–208, 2013.
[7] Swiss Federal Institute of Aquatic Science andTechnology (Eawag), Usermanual SWATCUP.
2015.
[8] P. Krause, D. P. Boyle, and F. Bäse,“Comparison of different efficiency criteria forhydrological model assessment,” Adv. Geosci.,
vol. 5, pp. 89–97, 2005.
[9] W. J. Zhao, W. Sun, Z. L. Li, Y. W. Fan, J. S.
Song, and L. R. Wang, “A Review on SWAT
Model for Stream Flow Simulation,” Adv. Mater.
Res., vol. 726–731, pp. 3792–3798, 2013.

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WATER QUALITY ASSESSMENT BASED ON THE WATER QUALITYINDEX (WQI) APPROACH USING GEOSPATIAL ANALYSIS
Rina Febrina1 and Abu Bakar Sambah23
Faculty of Engineering, Malahayati University, Indonesia.2Faculty of Fisheries and Marine Science,
University of Brawijaya, Indonesia;3Marine Resources Exploration and Management Research Group,
University of Brawijaya, Indonesia.
1

ABSTRACT
Water quality refers to the chemical, physical, or biological characteristics of water, in which assessing thecondition of water relative to the requirements of biotic species or to any human purposes. The aim of this study
was to analyze the water quality of the Way Kuripan River based on the Water Quality Index (WQI) calculation
method. Water samples were taken from five different areas (WK01, WK02, WK03, WK04 and WK05). WQI
was calculated on the basis of six parameters; dissolved oxygen (DO), biochemical oxygen demand (BOD),
chemical oxygen demand (COD), pH, total suspended solid (TSS) and ammoniac-nitrogen (NH3-N). The
calculation started by identifying the equation of the Sub-Index (SI) based on the parameter value, calculating
the Sub-Index (SI) of each parameter, and calculating the Water Quality Index. The results show that WK01 and
WK04 have WQI values of 70.3 and 70.11. Those values show that water quality of the Way Kuripan River was
in class III or slightly polluted. WK02 (WQI = 55.8) and WK03 (WQI=53.8) were highly polluted. The lowest
WQI of the Way Kuripan River was in WK05 = 38.3, and classified as Class V (highly polluted). Moreover,Geospatial analysis was done to identify the distribution of water quality geographically. It shows that homeindustry and human activities, were spread along the river flow, and it caused the fluctuation of water quality.
The results of this study can be used as a reference by the local government for water resources management.
Keywords:Water quality index, Way Kuripan River, Chemical, physical, and biological characteristics
In Southeast Asia regions, the most recognized
WQI is DOE WQI. The WQI was developed by the
Department of Environment of Malaysia [15]. DOE
WQI calculation has been used as standard
calculation for water quality in Water Quality
Monitoring Program in Malaysia [7].
In this study, DOE-WQI method [9] was applied
to analyze the water quality of Way Kuripan River.
Way Kuripan River is one of the largest rivers in
Bandar Lampung city, Indonesia. Along the river,there are landfill, industrial, residential andagriculture. The water body of the river practicallyreceives, industrial waste, liquid waste from landfill,domestic wastes and drainage water from theresidential area. The river were utilize for some
purposes such as cleaning and sanitizing by thepeople living in surrounding areas. To identify the
distribution of water quality in the Way Kuripan
River some approach is needed. The integrated
analysis of geospatial and water quality index
calculation will describe the distribution of water
quality along the river and determine the class ofpolluted water.

INTRODUCTION
Water pollution increases day by day in many
places in the world. On the other hand theavailability of water supply decreases continuously.
Based on the circumstance, water quality in many
parts in the world is dropped continuously. Water
quality is always an important and interesting topic
to discuss.
Water quality is one of the most importantfactors that must be considered when evaluating thesustainable development of region [1]. The mostuseful tool to monitor and assess the water quality is
by using the water Quality Index (WQI) which is asingle number like a grade explains the total water
quality at a certain area and time based on several
water quality parameters [2]. It also assesses thesuitability of the quality of the water for a variety
uses such as agriculture, aquaculture, and domesticuse [3]. WQI was first proposed by Horton 1965,
later, numerous of indices have been developed allover the world such as Weight Arithmetic (WA),National Sanitation Foundation (NSF), CanadianCouncil of Ministers of the Environment (CCME),
British Columbia, Oregon etc [4]-[5]-[6]-[7]. Overthe years, many researchers have been conducted tomonitor and study water quality [8]-[9]-[10]-[11][12]-[13]-[14].

METHOD
Study Area

981

SEE, Nagoya, Japan, Nov.12-14, 2018

The analysis applied in the area of Way
Kuripan River, Bandar Lampung city. In general,
Lampung can be described as hilly to mountainous
terrain, and characteristic of steep slopes with aslope of more than 25% and an average altitude of
300 meters above sea level. Way Kuripan River was
created by the confluence of Way Simpang Kiri
River and Way Simpang Kanan River. The lengthand the catchment area of the Way Kuripan River
were 9.6 km and 60.81 km2. Research location as
described on Fig. 1.

Biological Oxygen Demand (BOD), Chemical
Oxygen Demand (COD), Dissolve Oxygen (DO),Ammoniac Nitrogen (NH3-N), Total Suspended
Solid (TSS).

Fig.2 Sampling point
The surface water sample was collected about ahalf of the river depth due to the velocity of waterflow less than 5m3/s [16]. Water samples from eachstation were stored in one liter polyethylene bottles
for analysis of selected parameters included: pH,
Biological Oxygen Demand (BOD), Chemical
Oxygen Demand (COD), Dissolve Oxygen (DO),Ammoniac Nitrogen (NH3-N), Total Suspended
Solid (TSS).
Data Analysis
The algorithm applied for calculating WQI wasdeveloped by the Department of Environment of
Malaysia. The algorithm was described as follows:

Fig.1 Research location
Data Collection

WQI  0.22SIDO  0.19SIBOD  0.16SICOD (0,15SIAN )  (0.12SIpH )The water samples consist of 5 points and weretaken during January 2017. Each sampling site waspositioned by Global Positioning System (GPS), as
illustrated in Table 1 and Fig. 2.

Where, WQI = Water Quality Index, SIDO = Subindex DO, SIBOD = Sub-index BOD, SICOD = Subindex COD, SIAN = Sub-index AN, SISS= Sub-index
TSS, SIpH= Sub-index pH.

Table 1 Sampling point coordinate
ID
WK01
WK02
WK03
WK04
WK05

Latitude (S)05˚26.458’
05˚26.712’
05˚26.910’
05˚26.194’
05˚26.212’(1)

Every sub-index was calculated based on theequation in certain condition which is:Longitude (E)105˚15.026’
105˚15.169’
105˚15.387’
105˚15.461’
105˚15.778’

SIDO; SIDO = 0 for x ≤ 8; SIDO = 100 for x ≥ 92;
SIDO = -0.395 + 0.030 x2 - 0.00020x3 for 8 < x <92.
SIBOD; SIBOD = 100.4 – 4.23x for ≤ 5; SIBOD =108* exp (-0.055x) – 0.1x for x >5. SICOD; SICOD= -1.33x + 99.1 for x ≤ 20; SICOD = 103*exp (0,0157x) – 0.04x for x > 20. SIAN; SIAN = 100.5 –105x for x ≤ 0.3; SIAN = 94*exp (-0.573x) – 5*│x 2│ for 0.3 < x <4; SIAN = 0 for x ≥ 4. SISS; SISS =97.5* exp (-0.00676x) + 0.05x for x ≤ 100; SISS =The surface water sample was collected about ahalf of the river depth due to the velocity of waterflow less than 5m3/s [16]. Water samples from eachstation were stored in one liter polyethylene bottles
for analysis of selected parameters included: pH,982

SEE, Nagoya, Japan, Nov.12-14, 2018

71*exp (-0.0061x) – 0.015 for x < 1000; SISS = 0
for x ≥ 1000. SIpH; SIpH = 17.2 – 17.2x + 5.02x2
for x < 5.5; SIpH = -242 + 95.5x – 6.67x2 for 5.5 ≤x < 7; SIpH = -181 + 82.4x - 6.05x2 for 7 ≤ x <8.75; SIpH = 536 – 77x + 2.76x2 for x ≥ 8.75.
(2)Management of Water Quality and Control of Water
Pollution [17].
Table 2 Analysis result

General rating scale for the DOE WQI was
between 0 and 100. The interpretation of the value
applied in some water resources development
purposes is described below:

No
1
2
3
4
5
6

 For general use of water: 0≤x<60 = high polluted
water; 60≤x<80 = slightly polluted water; x>80 =clean water. For classification of water: 0≤x<40 =Class V; 40≤x<50 = Class IV; 60≤x<80 = Class
III; 80≤x<90 = Class II; x>90 = Class I.
 For public water supply: 0≤x<40 = notacceptable for public water supply; 40≤x<50 =doubtful for public water supply; 60≤x<80 = needs
expensive treatment for public water supply;
80≤x<90 = needs minor purification for public
water supply; x > 90 = no need treatment for
public water supply.
 For recreation water: 0≤x<20 = not acceptable
for recreation; 20≤x<30 = obvious pollution
appearing, still not acceptable for all recreation;
30≤x<40 = only for boating; 40≤x<50 = doubtful
for water contact; 50≤x<70 = acceptable for watercontact but needs bacteria count; x>70= acceptable
for all water sport.
 For fisheries: 0≤x<30 = not acceptable forfisheries; 30≤x<40 = only for coarse fish; 40≤x<50= only for handy fish; 50≤x<60 = doubtful forsensitive fish; 60≤x<70 = marginal for trout; x>70
= acceptable for all fish.
 For navigation: 0≤x<30 = not acceptable fornavigation; 30≤x<40 = obvious pollution
appearing; x>50 = acceptable for all navigation.
 For water transportation: 0≤x<10 = notacceptable for water transportation; x>10 =acceptable for water transportation.

Para
Meters(mg/l)
DO
BOD
COD
AN
SS
pH

WK
01
3.69
2
6
0.03
1
7.56

Analysis Result
WK WK WK
0203
04
3.56 4.04 1.45
30
29
4
9
32
6
0.03 0.12 0.16
11
1
7.36 7.20 7.47

WK
05
3.05
131
468
0.03
1
7.61

Table 3 Goverment regulation of the Republic ofIndonesia No. 82, year of 2001

Class I
(mg/l)
6
2
10
0.5
50
6-9

Quality Standard
Class IIClass III
(mg/l)(mg/l)
4
3
3
6
25
50
400
400
6-9
6-9

Class IV
(mg/l)
0
12
100
400
5-9

Table 2 shows the value of Dissolved Oxygen(DO) at sample points of WK01, WK02, WK05
were 3.69 mg/l; 3.56 mg/l and 3.05 mg/l, and it
included in water quality standard of class III [17].
While at the sample points WK03 and WK04 have
DO value of 4.04 mg/l (Class II) and 1.45 mg/l
(almost close to Class IV). DO is one of theimportant parameters in water quality analysis. The
DO value indicates the amount of oxygen available
in a body of water. The greater the DO value onwater, indicating the water has good quality.
Conversely, if DO value is low, it can be seen thatthe water has been contaminated. The value of DO
also shows the extent to which the water body isable to accommodate water biota such as fish andmicroorganisms. The results shows that the value of
DO increasingly smaller the downstream. As for the
BOD value there was an increase from upstream todownstream. The increasing of BOD value wasabove the standard of the class IV water quality, andthis occurred at sample points of WK02, WK03 andWK05; 30 mg/l, 29 mg/l and 131 mg/l, respectively.
The highest BOD value occurred in thedownstream area (WK05=131mg/l) while theupstream of the river had a low BOD value of 2
mg/l, and included in class I. The BOD value
indicates the amount of oxygen required by
microorganisms to decompose dissolved organic
substance and some of the organic substancessuspended in water. The greater the value of BOD

RESULT AND DISCUSSION
Water Sample Analysis
Water samples were analysis at Health
Laboratory
of
UPTD/Local
technical
implementation unit includes five parameters;
Dissolved Oxygen (DO), Biological Oxygen
Demand (BOD), Chemical Oxygen Demand (COD),
Ammonia (AN), Suspended Solid (SS) and Degreeof Acidity (pH). The result of analysis as describedin Table 2.
The value as shown in Table 2 were comparedwith the water quality standard in accordance with
Government Regulation of the Republic ofIndonesia No. 82, year of 2001 (Table 3) on the983

SEE, Nagoya, Japan, Nov.12-14, 2018means the process of decomposition of organic
substance occurs in large quantities and will absorb
oxygen in water thereby reducing the amount ofdissolved oxygen (DO). The increase in BOD value
from upstream to downstream indicates the qualityof river water has decreased. This is because thesource of pollutants is not only from the previous
water flow but also from the surrounding settlementsthat dispose of domestic waste directly into the river.
In addition, the activities of ships entering theestuary by disposing of waste from ships such asengine oil and others also increase the source ofpollutan to downstream areas.
In addition, COD value at sample point of
WK01, WK02, WK04 were 6 mg/l, 9 mg/l and 6
mg/l, and included in the standard of water quality
class I. COD value at sample point of WK03 was 32
mg/l, and it almost close to the standard of water
quality class III. While the COD value for thedownstream area (WK05) was very high, equal to468 mg/l, far exceeds the water quality standard
required by the government.
The downstream region requires the greatest
amount of oxygen compared to other regions forchemical reaction processes to decompose thecontaminants. Level of ammonia (AN) at sample
point of WK 02 to WK 04 has increased withhighest AN concentration occurring at sample pointof WK 04 (0.16 mg/l). It did not exceeding
recommended quality standard based on Goverment
regulation No. 82, 2001 (equal to 0.5 mg/l). In thisarea the dominant activity is the settlements whose
effluents are directly discharged into river bodies
and poor sanitation of the people. This is inaccordance with the statement of Effendi (2003)
which states that high ammonia level is an indicationof the contamination of organic materials derived
from domestic waste, industries and run-off
agricultural fertilizers [16].
SS (Suspended Solid) parameter of Way Kuripan
River at sample point of WK01 up to WK05 has thesame value (1 mg/l). Concentrations of SS fromupstream to downstream described the water quality
standard of class I and Class II based on
Government Regulation, so that SS content of riverwater of Way Kuripan did not affect to the allocationof raw water, facilities/infrastructure of recreational
water, animal husbandry and fishery interests.
Although SS was not a toxic but with the increasing
value of SS means increasingly penetration of lightobstructed into the river.
Moreover, pH was classified as normal, and it
indicated that life of aquatic biota still in goodenough condition. The overall analysis of water
quality of Way River Kuripan illustrated that somethe result did not meet the criteria of quality standard
according to Government Regulation of Republic ofIndonesia No. 82, year of 2001 on the Managementof Water Quality and Control of Water Pollution[17].
Analysis of DOE - Water Quality Index (DOEWQI)
Based on the analysis of Way Kuripan River
water samples (Table 2), it can be calculated thesub-index value of each parameter. The analysis ofwater quality used DOE-WQI method applying theequation (1). The results of DOE-WQI calculations
are presented in Table 4.
Table 4 WQI Value of Way Kuripan River
No.
1
2
3
4
5

SampleLocation
WK01
WK02
WK03
WK04
WK05

WQI

Class

70.3
55.8
53.8
70.11
38.3

III (Slightly Polluted)
IV (Polluted)
IV (Polluted)
III (Slightly Polluted)
V (Highly Polluted)

The analysis of WQI described the decreasing
value of water quality from upstream todownstream; it is related to the contamination level.
At the sample point of WK01 the WQI value was
70.3, it means that the water quality in upper riverarea is slightly polluted. Based on the investigationof pollution source in upstream area occured due toerosion of vacant land and residential area.
Upstream water can be used for drinking waterneeds, although it requires processing first. It also
safe for fisheries activities and suitable for all types
of water sports, shipping and water transportation.
The areas between upstream and downstream at the
sample points of WK02, WK03, WK04 have WQI
values of 55.8, 53.8 and 70.11. The source ofpollution was dominated by domestic and household
wastes generated from the contribution of Karang
City urban village with dense population Village(see land use map on Fig 3).
The water quality at the sample points of
WK02 and WK03 were worse compared to WK04,
due to the existence of SABO DAM between sample
points WK03 and WK04. The high concentration ofcontaminants from the previous water flow (WK02
and WK03) became lower when through SABO
DAM due to an increase in water discharge. Water
discharge gives a significant influence on the
improvement of water quality level. Water quality
on WK02 and WK03 were doubtful for drinking
water use because the pollution level was higher
than WK01. The class category of this area wasClass IV (polluted). It needs routine bacterial control
if apply for sport in contact with water. While forfisheries only allowed for fish that are cultivated but
still doubtful for more sensitive fish but permitted
for shipping and water transportation.
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SEE, Nagoya, Japan, Nov.12-14, 2018

WK04 has a value approaching WK01. Whilethe downstream of Way Kuripan River (WK05) has
a WQI value of 38.3, including in the highly
polluted category (Class V). The source of pollution
was caused by market or shops (Purwata and Karang
City urban village), home industry, temporary
shelter which is widely located along the river flow,
the flow of in and out of traditional fishing boats andfrom dense settlements in Purwata. River water inthe downstream area can not be used for drinking
water, whereas for fisheries only fish can live inpermissible dirty water. Sailing and watertransportation were permitted even though there wasstill polluted. Overall the Way Kuripan Rivercondition from upstream to downstream has been
contaminated with varying levels of pollution.

As described in laboratory test of water
quality, the sampling point of WK02 and WK03
illustrated highly polluted water. This area consist of
two different sub-district in both side of the river, inwhich mostly covered by urban area.
Mapping the water quality parameters using
spatial analysis, a Geographical Information Systemapproach, can be useful for taking quick decisions asgraphical representation. It would be easy tofacilitate government or policy maker in taking adecision especially in water resources management.
The analysis specially designed for handling ageographical data. The advantage of using ageospatial analysis is handling attribute data inconjunction with spatial features.

Geospatial Analysis

CONCLUSION

Spatial analysis describes an approach whichstudy entities using geographic properties. It also
defined as an approach to applying statisticalanalysis and other analytic techniques to georeference dataset [18]. All sampling points and resultof measurement were plotted based on its
geographical information on thematic map. The
maps showed not only the information of water
quality value, but also illustrated the relationshipbetween water quality distribution and surrounding
land use.
Sampling point of Way Kuripan River spatiallyspread from coastal line to the hinterland in around2.8 km of length. The land use surrounding sampling
point illustrated urban or settlement area (Fig. 3), in
which the forest area found at north and west part of
the area.

In general, the water quality of Way Kuripan
River is in contaminated status with varying level ofpollution. The results of the analysis show that
WK01 and WK04 have WQI values of 70.3 and70.11, with the category of river water quality ofclass III (slightly contaminated). At the sample
points of WK02 and WK03 have WQI values of
55.8 and 53.8. The water quality at the sample points
is included in polluted category (Class IV). The
value of WQI at the sample point of WK05 is 38.3
with the status of highly polluted water quality(Class V). The results of this study can be used as areference by the local government to overcome thecontamination of Way Kuripan River water withwater pollution control strategy, utilization,
monitoring and maintenance of water resources in
Way Kuripan watershed.

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Fig.3 Land use map
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986

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE AWARENESS OF ENVIRONMENT CONSERVATION BASED ON
OPINION DATA MINING FROM SOCIAL MEDIA
Kunyanuth Kularbphettong 1
Faculty of Science and Technology, Suan Sunandha Rajabhat University, Thailand

1

ABSTRACTSocial media have become an important role in society and people widely use social media platforms toexpress and criticize their opinion. With the previous studies, there is much of research to develop and harvest
information and knowledge from social media data for decision making and prediction. The awareness ofenvironment conservation has become a significant issue nowadays and building and raising environment
awareness is to conserve and protect the nature for the benefits of humans. Opinion mining is one of text mining
approaches to assess the attitude in a given subject and the attitude may be positive or negative opinion. The
paper proposes to conduct social media opinion mining in case of the awareness of environment conservation ofThai people. This study shows that social media effects to build and raise the awareness of environment
protection and furthermore this research can apply to other fields and industries aspects as well. .
Keywords: Sentiment analysis, opinion mining, awareness, environment conservation, social media

Live, Periscope, Vimeo). Social media becomes avital part of everyday life and the number of social
users has rapidly increased to reach 3.196 billion, up
13 percent year-on-year [2]. Therefore, the use ofsocial media to disseminate information is a newphenomenon of Thai social life and it has an
influence in people’s behavior and decision making
in various fields.
Also, the trend of using online media is likely at
a rapid pace and the influence of user generatecontent plays an increasingly important role toimpact on people’s behavior because user generatecontent is more reliable and generates faster andstronger streams. The power of social movement
through online media acts as the communication
mechanisms to interact and integrate online
community for driving the purpose of social issuesin Thai society.
Opinion mining is one of text mining approaches
to assess the attitude in a given subject and theattitude may be positive or negative opinion andsentiment analysis is the analysis of emotions andfeelings from the text to express the feelings ofpeople such as positive feelings or negative feeling.
The information of people think has always been a
crucial part to influence on decision making. Social
media sentiment helps to understand the perceived
positive or negative mood what people post onsocial media This research proposes to conductsocial media opinion mining in case of theawareness of environment conservation of Thai
people to understand and perceive the feeling of theawareness of environment conservation of Thai
people.

INTRODUCTION
Urban growth in all regions of the world isundeniable, especially in capital cities or economy
cities, and the growth of the city means the
movement of a large group of people who cometogether to pursue a career and live. This situation
causes enormous consumption and environmental
degradation. Environmental crisis is one of the
major problems in the world that affects the viabilityof the most biological systems in the future.
Therefore, the requirement to quickly resolve
environmental degradation problem is an essential tocultivate good moral traits in environmental
awareness. The Environment awareness is thefoundation of the psychology to acknowledge thehuman actions that cause to deteriorate environment
and the result will get back to destroy human life.
Nowadays, social media are increasingly used todisseminate information and express everyone’s
opinion to an online society where users cancommunicate and convey their attitude throughsocial network. Social media has become a new
digital medium that has played a significant role in
the rapidly changing society in terms of being part ofthe current news media process. When the internet
technology is growing by leaps and bounds, social
media takes an action to be a channel for news
media and affects to the digital economy of thecountry. There are many kinds of social media
platforms according to the purpose of using asfollowing [1]: social networking (Facebook,
Linkedln, Google+), microblogging (Twitter,
Tumblr), photo sharing (Instagram, Snapchat,
Pinterest), and video sharing (YouTube, Facebook
987

SEE - Nagoya, Japan, Nov.12-14, 2018

RELATED WORKSRESEARCH METHODOLOGIES

A literature reviews of relevant researches for
exploration and adaptation information shows that
sentiment analysis is the instrument to understandwhat people think and what feeling they are. It
amalgamates with many other fields like natural
language processing, statistics, and text analysis to
extract the emotional feeling from text. According to
M. Baykara and U. Gürtürk [3], tweets from twitter
were analyzed to classify users' categorization innews, politics, and culture. Bollen et al. [4]investigated the tweets posted on Dow Jones
Industrial Average (DJIA) to measure positive vs.
negative mood and Google-Profile of Mood States(GPOMS) by using Self-Organizing and Fuzzy
Neural Network and the result shown that the moodstates will directly affect investment decisions andstock market. Facebook posts were performed on
sentiment analysis to measure data available topublic domain [5]. The comments of fan page
Facebook and tweet of Twitter were classified intosome categories, positive, negative, and neutral
sentiment by using TF-IDF in Indonesia; Gojek,
Grab, and Uber and the results indicates that thecomments on social media are evaluated theperformance of these business transport online [6].
Barbosa et al. [7] propose a method to identify
sentiments from tweets and the data sources wasprovided by labels to solve different bias. The social
media analytics engine, by employed fuzzy
similarity-based classification method, was proposed
to automatically classify text into sentimentcategories (positive, negative, neutral and mixed)
and it is able to collect, filter, classify, and analyzesocial media text data and describes and predicts
analytic information on dashboard [8]. Also,
explained extends six emotions on new smart
services over mobile devices, the approach is used
emotional dictionaries and considers linguistic
parameters to identify results [9].
There are several approaches proposed to extract
information from social media and it can beclassified to 2 main techniques as follows: statisticaltechnique and machine learning technique. Linear
discriminant analysis (LDA), one of the statisticaltechnique, was applied to explore relationshipbetween Facebook fan pages and visitor
engagements of the exhibitions [11] and logistic
regression was used to analyze textual data fromsocial [12]. Machine Learning was applied to extract
information from text data and for example, Gurkhe
et al. [10] implemented the machine extracted thepolarity (positive, negative or neutral) of social
media data set by using naive Bayesian technique.
With the advance technologies, the enhancement of
this research is continually move forward towidespread in various other fields.

This section describes how to conduct thisresearch and the methodologies applied in thisproject as follows: Data preparation; Feature
extraction; Model Building and Testing and
Evaluation.
Data Preparation
In the first stage, data were collected form social
media and internet web sites and it was posted toexpress the opinion about environment conservation.
Tweepy API [13] is used to retrieve the tweets anddata, like twitterID, hashtag, date of created tweet,
tweet text, and retweet count, was stored in the
database. Some selected Thai hashtags were
presented in Table 1. The second type of data sourceis news and related web sites related to the conceptof environment conservation. Data is the text format
that requires to be preprocessing to clean andmanage data before analyzing text mining.
Preprocessing step of the data set is following:
removing URLs, hashtags, username, and symbols;
replacing the emotion icons and correcting thespelling words.
Table 1 Example of selected Thai hashtags#รัก โลก #รัก ษ์ โลก #โลกร้อน #ประหยัดไฟ
#พกถุงผ้า#ป ลู ก ต้ น ไม้ #ใช้ จ ัก รยาน #ป ระห ยัด นํ้ า#คัดแยกขยะ#ง ด ถุ ง พ ล า ส ติ ก #รั ก ษ า สิ่ ง แ ว ด ล้ อ ม#ขยะรีไซเคิล#ข ย ะ ย่ อ ย ส ล า ย #อ นุ รั ก ษ์ พ ลั ง ง า น#ลดเลิกเพือ่ ช่วยโลก
#ปลู ก ป่ าช่ ว ยชาติ #รัก ษาป่ าไม้ #ลดมลพิ ษ#อนุ รกั ษ์ สงิ่ แวดล้อมและป่ าไม้ #วันรักต้นไม้
#พื้ น ที่ สี เ ขี ย ว #รัก ษ าผื น ป่ า #ปลู ก ต้ น ไม้#ล ด เ มื อ ง ร้ อ น ด้ ว ย มื อ เ ร า#ปลู ก ฝังจิต สํานึ ก รัก ษ์ โ ลก #การจัด การขยะ#ป ลู ก ป่ า เ ทิ ด พ ร ะ เ กี ย ร ติ#ป ร ะ ห ยั ด พ ลั ง ง า น ไ ฟ ฟ้ า #จิ ต อ า ส า#ทดแทนคุณแผ่นดิน #ปลูกเพือ่ ให้
However, Thai language is different from English
because it’s no marks or symbols to indicate thescope of each word or sentence.
The figure 1 was shown the system overview anddata was collected from tweeter and related websites. LEXiTRON Corpus was used to analyze
words and meaning of words [14]. This research was
specified related domains collected from similar
related information.

988

SEE - Nagoya, Japan, Nov.12-14, 2018

documents in the training data set (Training Set) and|DF (f)| is the number of documents that feature (f)appears. IDF(f) is inverse document frequency used
to identify positive , negative or neural. Unlike
TFIDF mentioned above, this study divides data into
two parts, one for positive data, and one fornegative. Furthermore, according to K. Ghag, K.
Shah [15], SentiTFIDF was applied to this project toclassify the positive, negative and neutral emotional
mood and then the set of emotional words werestored in database to be further next process.

Fig. 1Model Building
To build model, Naïve Bayes and Support Vector
Machine (SVM) were used to build a sentimentclassifier. The data were divided to be 2 sets:
training and testing sets with the ratio 70:30.
Naive Bayes classifier, based on Bayes' theorem, is
one of the crucial techniques in machine learning
used to many fields like customer segmentation or
sentiment analysis.

The System Overview.

Feature Selection
Feature Selection is the reduction of data size by
reducing the original data size and losing key
features using the selection technique. This process
of extracting comments is to pull out the feature of
the comment to determine what features use thisproject. Thai stop word is removed the insignificant
words without meaning change. For example, thesentence is “ร ้ า น ก า แ ฟ ห ล า ย ร ้ า นถ ้ า พ ก แ ก ้ ว ไ ด ้ ส่ ว น ล ด ด ้ ว ย ค่ ะช่ ว ย ลด โลก ร อ้ น แล ะป ระห ยั ด ตั ง ” and the result waspresented in figure 2.

𝑷𝑷(𝒄𝒄|𝒙𝒙) =|𝑫𝑫||𝑫𝑫𝑫𝑫(𝐟𝐟) |(3)

Testing and Evaluation
Accuracy, recall, precision and F-measure were used
to evaluate the performance of text models.

For instance, the word “ค่ ะ ” is a non-significant
word and in the feature selection process, the feature
will be cut off. Thai segmentation technique isapplied to extract data and data extraction stage isthe process to extract data and labels the training set,
annotated positive, negative or neutral, to identify
the category of text by hand. The data consists of
2,964 sets and assigned weight each set as a positive,
negative and neutral review. Labels were used as 1
for a positive review, 0 for a neutral review and -1
for a negative review. TF-IDF (Term FrequencyInverse Document Frequency) was applied todetermine indexing for using for training process.

𝑰𝑰𝑰𝑰𝑰𝑰(𝐟𝐟) = 𝒍𝒍𝒍𝒍𝒍𝒍

𝑷𝑷(𝒙𝒙)

P (c|x) is the posterior probability of the attribute X
that has set the label of class C. P (x|c) is thelikelihood that the data in class C contains attribute
X. P(c) is prior probability of class C. P (x) is thepredictor prior probability.
Support Vector Machine is the significant
supervised algorithm that can solve a classification
problem and the concept of SVM is to define data in
the feature space and create hyperplane to separate
different class labels.

Fig. 2. Example Sentence.

𝑾𝑾(𝐟𝐟,𝐝𝐝) = 𝑻𝑻𝑻𝑻(𝐟𝐟,𝐝𝐝) × 𝑰𝑰𝑰𝑰𝑰𝑰(𝐟𝐟)𝑷𝑷(𝒙𝒙|𝒄𝒄)𝑷𝑷(𝒄𝒄)

𝑻𝑻𝑻𝑻𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑𝒑 =𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓𝒓 =𝑻𝑻𝑻𝑻+𝑭𝑭𝑭𝑭

𝑻𝑻𝑻𝑻

𝑻𝑻𝑻𝑻+𝑭𝑭𝑭𝑭𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨 =(5)
𝑻𝑻𝑻𝑻+𝑻𝑻𝑻𝑻(6)

𝟐𝟐×𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩×𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑(7)

𝑻𝑻𝑻𝑻+𝑭𝑭𝑭𝑭+𝑭𝑭𝑭𝑭+𝑻𝑻𝑻𝑻

𝑭𝑭 − 𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎𝒎 =

(1)

(4)

𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩𝐩+𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑𝐑

Where TP represents the number of correctlyclassified documents (True Positive), FP is all
documents retrieved (False Positive) and accuracy is
the percentage of documents correctly classified,recall is the percentage of relevant documents
correctly retrieved (TP) with respect to all relevant
documents (TP + FN) and F-Measure is consisted ofa single measure Precision (P) and Recall (R).

(2)

Where TF (f, d) presents the frequency of the feature(f) in documents (d) and W (f, d) shows the weightof a feature (f) in (d). |D| explains the number of989

SEE - Nagoya, Japan, Nov.12-14, 2018

research can apply to other fields and industries
aspects as well. However, there are some errors withword wrapping and comment extraction because of
the typing error and occurring of new social words.

EXPERIMENTAL RESULTS
After preprocessing data, to label data with polarity
words from the comments were applied to set train
data of extracted words. Then, sentiment analysis
was used to label each comment to three groups ofsimilar comments: positive, negative and neutral
based on their polarity scores. The result gained
from the experiment by using Naïve Bayesclassification and SVM algorithms as shown in table
2. The data from this project was collected fromsocial network and accuracy, precision and Fmeasure was used to evaluate the effective ofclassification models.
Table 2 classification performance
Accuracy Precision Recall
SVM 80.5
82.5
85.7Naïve 72.6
79.7
76.8
bay

ACKNOWLEDGEMENTS
The authors gratefully acknowledge the financial
subsidy provided by Suan Sunandha Rajabhat
University.
REFERENCES[1] Warren Jolly. (2018). “The 6 Most Effective
Types of Social Media Advertising in 2018”,
ECOMMERCE MARKETING. Available:
http://www.bigcommerce.com/blog/socialmedia-advertising/[2] Dave Chaffey. (Mar, 2018). “Global social
media research summary 2018”,Available :https://www.smartinsights.com/social-mediamarketing/social-media-strategy/new-globalsocial-media-research/[3] Muhammet Baykara and Uğur Gürtürk,“Classification of social media shares using
sentiment analysis”, proceeding of International
Conference on Computer Science andEngineering(UBMK,
2017)
DOI:
10.1109/UBMK.2017.8093536[4] Bollen, J., Mao, H., and Zeng, X.-J., “Twittermood predicts the stock market”, Journal ofComputational Science vol. 2(1):1–8, 2010.
[5] Federico Neri, Carlo Aliprandi, Federico Capeci,
Monstserrat Cuadros, Tomas, "Sentiment
Analysis on social media", IEEE/ACM
International conference on Advances in Social
Networks analysis and mining, pp. 919-926,
2012.
[6] M. H. Saragih and A. S. Girsang, “Sentiment
Analysis of Customer Engagement on Social
Media in Transport Online,” in International
Conference on Sustainable Information
Engineering and Technology (SIET), pp. 24–29,
2017.
[7] L. Barbosa, J. Feng. “Robust Sentiment
Detection on Twitter from Biased and Noisy
Data". COLING 2010 Poster vol, pp. 3644.2010.
[8] Wang, Z., Chong, C. S., Lan, L., Yang, Y., Ho,
S. B., & Tong, J. C., “Fine-grained sentiment
analysis of social media with emotion sensing”,
Presented at the Future Technologies
Conference, San Francisco, CA, USA. Dec.
2016, doi:10.1109/FTC.2016.7821783

F-score83
74.2

The SVM classification model is better thanNaïve bay with accuracy of 80.5, precision of 82.5,
recall of 85.7 and f-measure of 83 as displayed in fig
3. The result when using the model shows that themodel can use to detect the concept of environment
conservation and the positive awareness is more theother awareness in the number of words and theaverage length of Tweet’s on data set.
90
85
80
75
70
65

SVM
Naïve bay

Fig. 3.The Results of Classification Performance.

CONCLUSION
The awareness of environment conservation has
currently become an important topic and to educate
and implant environment awareness social media
has influenced in society and people. Therefore, thesentiment analysis is the powerful approach toidentify opinion, to extract opinion’s feature, toclassify sentiment, and to display the results invisualization and summarization. This research
describes the methods to conduct social media
opinion mining in case of the awareness ofenvironment conservation of Thai people. Thisapproach collected data from twitter and related websites and then it shows how to preprocess andextraction the results. The results show that social
media effects to build and raise the awareness ofenvironmental protection and furthermore this990

SEE - Nagoya, Japan, Nov.12-14, 2018

“Effective Sentiment Analysis of Social Media
Datasets using Naive Bayesian Classification”,
International Journal of Computer Applications(0975 8887) vol. 99 - No. 13, August 2014[13] Tweetpy
API,
Avaliable:
http://www.tweepy.org/[14] LEXITRON,Available:
https://www.nstda.or.th/th/nstdaknowledge/11180-lexitron[15] K. Ghag, K. Shah, "SentiTFIDF-Sentimentclassification using relative Term Frequency
Inverse Document Frequency", International
Journal of Advanced Computer Science andApplications, vol. 05, no. 02, pp. 36-43, 2014.

[9] Athena Vakali, Despoina Chatzakou, Vassiliki
Koutsonikola and Georgios Andreadis, “Social
data sentiment analysis in smart environments
extending dual polarities for crowd pulse
capturing”,
2013,Available:
https://pdfs.semanticscholar.org/1b2c/374cae2ee5c57965211bb5b715b4b45d31c3.pdf[10] Lee, T., Shia, B., & Huh, C., “Social Media
Sentimental Analysis in Exhibition’s Visitor
Engagement Prediction”, American Journal ofIndustrial and Business Management, 06(03),pp. 392-400, 2016.
[11] Virgile Landeiro , Aron Culotta, “Robust textclassification in the presence of confoundingbias”, Proceedings of the Thirtieth AAAI
Conference on Artificial Intelligence, , Phoenix,
Arizona, Feb 2016.
[12] Dhiraj Gurkhe, Niraj Pal and Rishit Bhatia,991

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

LIFE CYCLE IMPACT ASSESSMENT OF NEW GROUND MATERIALAND EMBANKMENT CONSTRUCTION METHODS CONSIDERINGRECYCLING

1,3

Hideyuki Ito1, Kento Aimono2 and Takahiro Fujii3
College of Science and Technology, Nihon University, Japan; 2Taisei Corporation, Japan

ABSTRACTIn Japan, the conventional cut-and-fill method is often used in banking construction methods. However, thisconstruction method is pointed out that it causes land subsidence and/or landslide in soft ground. For solving these
problems, various new construction methods using the ground materials such as EPS (styrofoam), recycled foamed
waste glass and expanded polystyrene beads have been developed as new lightweight and workable composite
geomaterials. These new construction methods are believed to be effective for construction on soft ground andlandslide-prone areas. In existing researches of this field, they aimed to identify areas for improvement and the
problems associated with the use of these new ground materials. However, there are few researches that focusedon negative impacts to land use, by exhausting air pollution and GHGs (Green House Gases) with recycling fromthe perspective of environmental economics field. Thus, in this research, we compared conventional cut-and-fillmethod and some new ground materials such as the expanded polystyrol construction method using the new EPS
geomaterial, the lightweight embankment construction method with EPS beads and the foamed waste glass
construction method using embankment material with recycled waste by analyzing the negative impacts to land
use considered ecosystem services and life cycle cost (LCC) including external cost by emissions of GHGs andair pollutants such as SOx and NOx using life cycle impact assessment analysis.
Keywords: Life Cycle Assessment, Life Cycle Impact Assessment, Life Cycle Cost, New Ground Material

ground materials on land use including air-pollution
substances, global greenhouse gas (GHGs) andecosystem services are comprehensively assessed asexternal costs.
Thus, the purpose of this research is to do acomparative analysis by life cycle impact assessment(LCIA) for each kind of embankment construction
methods using new ground materials. Specifically,
this research performs, while taking account of thepresence or absence of the recycling of wastes, acomprehensive assessment of external costs
converted to a currency for the respective
embankment construction methods including theexternal costs attributable to the emission of airpollution substances and GHGs and those resulting
from the land use at every lifecycle stage.

INTRODUCTION
In Japan, social assets including roads that wereconstructed from the postwar period to the highgrowth period are facing a renewal period. In thiscontext, it will be important from now on forestablishing a circulation-type society that include thereuse of materials recycled from wastes and theselection of environmentally friendly construction
methods. Currently, the conventional cut-and-fillmethod is most widely used among embankment
construction methods. The conventional cut-and-fillmethod is considered to have a chance of causing
ground sinking and/or landslide at soft grounds andthe areas likely to experience landslide, construction
methods that take advantage of new ground materials
like expanded polystyrene (EPS) are believed to beeffective for the construction on soft grounds and theareas likely to experience landslide because of theirlightweight properties and construction properties,
etc.
While there are previous researches such as acomparative analysis done by Ito et al. [1] on theinfluences and costs caused to environments by thevarious construction methods and a study performedby Ochiai et al. [2] in which the potential of mixed
ground materials made from wastes is discussed.
However, no research has ever been conducted
where the impacts made by new recycling-friendly

LITERTURE REVIEWIn the previous researches about the lifecycle
assessment (LCA) that pay attention to new groundmaterials and the presence or absence of the recyclingof wastes, Ito et al. [1] revealed that environmental
burdens and lifecycle costs could be reduced in eachkind of embankment construction methods utilizing
new ground materials (EPS) and wastes (expandedbeads and expanded waste glass) if recycling would
be done while considering lifecycle stages. However,992

SEE - Nagoya, Japan, Nov.12-14, 2018

addition to environmental assessments, LCAs using
environmental accounting methods, social andenvironmental efficiency and cost calculation
utilizing the Monte Carlo simulation. However, thisresearch dealt with construction polluted mud and its
impact assessment of land use was not enough.
Kamemura et al. [6] implemented a research withregard to the lifecycle cost assessment of civilengineering structures with considering the risk.
Specifically, it showed the size and characteristics ofrisks as well as the effects of objects by optimizing
cost statistics regarding the construction costs forstructures and their operation/maintenance costs
while they are in use. However, this research only
made an assessment on the lifecycle cost.
Omine et al. [7], after organizing the additional
values, physical natures and the grouping of
constitutional materials of various mixed groundmaterials, estimated the CO2 emission at the
production stage of cement stabilization soil, bubble
mixed lightweight soil, fluidization disposal soil, clay
mixed calcination fixation agent and tire chip mixed
soil, although they didn’t assess impacts resulting
from polluted substances other than CO2.
While Minegishi et al. [8] explained about thestrength and impacts of repeated stress ratios made on
the deformational characteristics of EPS mixed
lightweight soil, Kagawa [9] analyzed thecharacteristics and physical strengths as earth fill of
the EPS civil engineering method as well as the
durability, weather resistance, environment in soil
and drug resistance of EPS. Such previous researchanalyzed the strength, etc. of EPS but didn’t make its
lifecycle assessment.
Onitsuka et al. [10] demonstrated the potential of
expanded waste glass materials as new materials by
doing an experiment for improving the engineer
characteristics of expanded waste glass materials andfundamental road bases, although they didn’t
implement an environmental assessment with the
LCA method.
It is concluded from the above that no research has
ever, while focusing attention on respective
construction methods using new ground materials,
conducted a comprehensive assessment in terms ofexternal costs resulting from the emission of airpollution substances and GHGs as well as those dueto the land use including ecosystem services.

any external cost was not considered in this research.
Ochiai et al. [2] organized additional values,
physical natures and the grouping of constitutional
materials of various mixed ground materials in theirprevious researches regarding the materials
constituting mixed ground materials, which reported
more than one research result on mixed groundmaterials. In addition, they assessed environmental
burdens and the recycling efficiency of mixed groundmaterials made from wastes. However, since theseresearches figured out environmental burdens only
from the production process of embankment
materials, environmental burdens were not analyzed
through the entire lifecycle.
Amano et al. [3] visualized the potential ofrecycled materials in paving roads. More specifically,
they revealed that environmental burdens could be
reduced to a maximum by around 40% with the useof recycled materials at both the stages of
construction and maintenance/repair, by totaling theenvironmental burdens and costs associated with theconstruction
of
paved
roads
and
their
maintenance/repair for respective stages of initialconstruction and maintenance/repair and by
evaluating the lifecycle of paved roads from both thesides of environmental burdens and costs. Both of theenvironmental burdens and costs for asphaltic
pavement at the stage of its maintenance/repair
accounted for 40 to 50% of those at its entire stages.
This research, however, didn’t deal with an impact onroad structures and surrounding environments in theentire lifecycle.
In their previous research that employed LCA andenvironmental economy assessment methods, Ito et al.
[4] performed an LCIA of biodiversity and ecosystemservices based on the extinction risk of living things
while focusing on the construction of wooden
residences and steel residences. Then, this researchassessed an impact on biological ecosystems andecosystem services that would disappear due to thealteration and occupation of land occurring in theentire lifecycle. However, this research only made anassessment of residence construction, not new groundmaterials.
Inazumi et al. [5] previously conducted anassessment research of social and environmental
efficiency regarding the recycling of construction
polluted mud as a ground material. Specifically, they
discussed an evaluation method of social andenvironmental efficiency assessing the recycling ofwastes from a social perspective by internalizing
environmental burdens as an environmental cost, in

METHOD AND SYSTEM DETAILSIn this research, the Mineoka area in mountainous
roads located in the southern part of Chiba prefecture993

SEE - Nagoya, Japan, Nov.12-14, 2018

Estimation Method for External
Attributable to Air Pollution and GHGs

was selected as case study area as well as in theprevious research [1], and then compared above 4
construction methods. The summary of eachembankment construction method using new groundmaterials is shown in Table 1.
We also set a same functional unit that provides alogical basis for comparing the environmental
performance of alternatives for applying LCA tothese four construction methods based on theprevious research [1]. We defined the target roadcondition (2 lanes, 7 m wide and 1m long) as afunctional unit and then, it was hypothesized that the
inclined a the angle between the mountain and theroad is 35°.

Costs

The impacts made including on environments,
human health and social assets by air-pollution
substances and GHGs that are emitted in road
construction throughout the overall lifecycle areintegrated in terms of a currency. In this research, a
LCIA was performed utilizing the values representing
the emission amounts of air-pollution substances and
GHGs estimated in the research by Ito et al. [1]External costs were estimated in a way to integratethem by multiplying the total amounts of air-pollution
substances and GHGs that are emitted in all lifecycle
stages by the original unit for external costs per unit
emission amount in respective environmental impact
fields used in the Life-cycle Impact assessment
Method based on Endpoint modeling (LIME2)
environmental impact integration software [11].

Setting of Recycle Method in Each Construction
MethodFor the purpose of analyzing recycled
embankment materials and environmental burdens,
this research conducted a survey on how to recycle
embankment materials by doing a questionnaire
survey and an interview survey with ten construction
companies and then set a recycling method based on
the results of such surveys. In order to take account ofrecycling, this research based on the presumption
established from the results of the research by Ito etal. [1] that roads would be reconstructed in 100 years
from the start of their service, assumed thatembankment construction work would be done fourtimes in total as well as the system boundary.
In addition, since the interview survey had foundthat recycling was difficult in the EPS construction
method, it was assumed that roads would bereconstructed every 100 years with virgin materials.
This research aims to identify future tasks andimprovement plans through the calculation of thetotal environmental burdens and costs generated
depending on the presence or absence of recycling.

Estimation Method for External Costs Caused by
Influences on Land Use
The impacts made on land use by the alterationand occupation of land in the entire lifecycle aresubstantial. In this respect, the impacts given on
ecosystem services from the perspective of land use
are assessed in term of a currency with classifying
land use into four categories such as forests, tidelands,
waters and desserts. Regarding the analysis method,
the influenced area is calculated by land use
classification for respective construction methods andthen the external costs resulting from the loss of
ecosystem services are estimated.
First, the recycling methods and the utilization
amounts of materials per unit area for respective
construction methods that were set in the previous
researches are shown in Table 2 and Table 3. Then,the setting of land use classification is illustrated inTable 1 Summary of each embankment construction method using new ground materials
Expanded Polystyrol
Construction Method

EPS blocks are stacked as embankment materials and are integrated by dedicated clamps.
When stacked, these ultra-lightweight embankments have advantages of their compressive
resistance, durability, and independent stack design.

Lighter soil is used, comprising EPS beads mixed with soil and sand. This method isLightweight EPS Bead effective for use in soil fills on soft ground and in landslide-prone areas due to its
Mixture Method
capability of reducing the applied load on the ground more effectively than ordinary soil
and sand.

Foamed Waste
Glass Method

Foamed waste glass is a porous embankment material manufactured by pulverizing,burning, and foaming recycled waste glass. The specific gravity and degree of water
absorption can be controlled during manufacturing according to the requirements of specificapplications. Hence, foamed waste glass is used in a wide range of applications including
civil engineering, greening of slopes and rooftops, agriculture, water purification, and heatinsulation. This material is lightweight, water permeable, water retentive, fire resistant, anda good thermal insulator.

994

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 4 and the conversion factors for calculating
impacted area by fuel/energy consumption in eachlifecycle based on JEMAI-LCA database [12],existing research [4] and the hearing survey toconstruction companies are shown in Table 5.
The estimated results of influenced land area perunit amount are obtained by figuring out the
influenced area per functional unit based on theultimate recoverable reserves of materials used in
respective construction methods and such area. Table
6 shows the estimated/calculated results of impactedarea by land use classification for respective
construction methods.

Table 5 Conversion factors for calculating impactedarea by fuel/energy consumption

Table 2 Recycling methods
Construction method

Recyle (first time)

Recyle (from second time)

Used banking material mixed with
Virgin material is used for first time
cement is reused from second time

Cut & Fill (R)No resycle because EPS block cannot be recycled

EPS (V)

Used banking material mixed with
Lightweight EPS
Virgin material is used for first time
cement is reused from second time
bead mixture method (V)EPS beads is removed from
Lightweight EPS
After used styrofoam was blasted,
demolished banking material and thenbead mixture method (R) it is used by mixing soil and cement
recycle the styrofoam
Foamed waste
glass method (R)Virgin material is used for first time

Demolished banking material isrecycled

Table 3 Utilization amounts of materials per unit area
for respective construction methods
EPS
Block

Aluminum Zinc

3

2

EPS
beads

Foamed Clamping
waste glass materials

Soil

Cement

2

kg/m

2

kg/m

m /m

kg/m

kg/m

kg/m

kg/m2

Cut & Fill (R)15,750

645

-

-

-

-

-

-

EPS (V)--367.08

2.15

1.70

-

-

734.17

Lightweight EPS
bead mixture method (V)19,250

1,790

-

-

-

161.22--

Lightweight EPS
bead mixture method (R)19,250

1,790

-

-

-

161.22--

Foamed waste
glass method (V)

-

-

-

-

-

-

5,250

-

Foamed waste
glass method (R)

-

-

-

-

-

-

5,250

-

Unit

2

2

2

kg/m2

Table 4 Land use classification of impacted area
EnergyCrude OilElectricity

Natural Gas

Coal

Country

Saudi Arabia

Japan

Australia

Australia

Type ofLand UseOil field
Desert area

TidelandSea area

Mine

ImpactImpact byoil field
development

Impact to tidelandby reclamation for
constructing thermal
power station

Impact by
Impact by
developing
coal minenatural gas field development

Estimation Item
Conversion Factor
Impacted area by
4.00E-04 ㎡/kg
obtaining aggregate
Impacted area Impacted area by
1.10E-03 ㎡/kg
by obtaining
obtaining lime
construction
Impacted area by
6.88E-05 ㎡/kg
materials
obtaining aluminum
Impacted area by
3.63E-03 ㎡/kg
obtaining zinc
Impacted area by
4.02E-03 ㎡/kg
constructing andoperating refinery
Impacted area by
constructing and3.57E-02 ㎡/kg
operating zincrefineryImpacted area by
constructing and7.90E-07 ㎡/kg
operating cement
Impacted area at
works
production phase
Impacted area by
constructing and2.92E-05 ㎡/kg
operating manufacturing
plant of EPS block
Impacted area by
manufacturing clamping 4.0.E-05 ㎡/kg
materials
Impacted area by
manufacturing
2.92E-05 ㎡/kg
expandable beads
Impacted area by
constructing and1.10E-02 ㎡/kg
operating recycling
factory of waste glass
Impacted area by
constructing and1.54E-04 ㎡/kg
operating recycling
Impacted area byfactory of styrofoam
recycle facility
Impacted area by
constructing and6.20E-02 ㎡/kg
operating recycling
factory of steel
Impacted area byreclaiming waste
1.39E-01 ㎡/㎥
material
Impacted area by
2.00E-04 ㎡/kg
extracting crude oil
Impacted area by
2.60E-07 ㎡/kWh
Impacted area by generating electric power
extracting energy Impacted area by
4.70E-01 ㎡/kg
extracting natural gas
Impacted area
7.50E-04 ㎡/kg
by mining coalconstruction method were the smallest as shown in
Figure 1. Also, it was found that the emission of SOX
being a cause for air pollution would make substantial
impacts on the increase in external costs, that thebiggest external costs were those for the expanded
waste glass materials construction method, and thatthe said external costs would be in the same range as
those for the expanded beads lightweight soil
construction method if taking account of recycling.

RESULTS AND DISCUSSION
Estimated Results of External Costs Due to
Emission of Air-Pollution Substances and GHGs
The estimated result of external costs attributable tothe emission of polluted air substances and GHGs
demonstrated that the external costs for the EPS
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Table 6 Impacted area by land use classification for each construction method
Total Impacted Area of each Land Use for 300 Years
Total Impacted Area（㎡）Impact to Land

EnergyTotal

Material
ForestForestTidelandTidelandSea area

ForestTidelandSea area

Cut & Fill
①V②-④R

36.8

1.0

2189.33.8.E-05

037.8

2189.3

0

EPS
①－④V

0

1.0

1.4

1.5.E-04

0.4

1.0

1.4

0.4

Lightweight EPS bead mixture
①－④V

38.7

1.0

10703.1

1.8.E-04039.7

10703.1

0Lightweight EPS bead mixture
①－④R

38.7

1.0

2675.9

1.1.E-04

039.7

2675.90

Foamed waste glass
①－④V

0

1.0

3150.01.3.E-03

178.1

1.0

3150.0

178.1

Foamed waste glass①V②－④R

0

1.0

787.5

3.4.E-04

44.5

1.0

787.5

44.5

Construction Method

Figure 1 Estimated results of external costs of emission of air-pollution substances and GHGs
were calculated, then by summing up which
influenced areas the influenced areas by land use
classification for respective construction methods
were figured out. Lastly, external costs were
estimated by multiplying the estimated influenced
areas by land use classification for respective
construction methods by the economic value of
ecological services per unit area which was estimatedin the previous research.
Consequently, the external costs for the EPS
construction method were found to be the smallest as
shown in Figure 2 because the estimation was madeon the presumption that crude oil being the raw
material for EPS blocks would be produced in thedesert areas of Saudi Arabia and therefore its impact
on ecological services was considered to be small.
The external costs for the expanded waste glassmaterials construction method V which causes a
considerable impact on tidelands by occupying theland were estimated to be the biggest. Further, it was
shown that external costs would be substantiallyinfluenced depending on the presence or absence ofrecycling.

Estimated Results of External Costs Caused by
Impacts on Land Use
The impacts made on land use by the alterationand occupation of land in the entire lifecycle aresubstantial and therefore there is a need to assess theimpacts on ecological services from the perspectivesof land use such as forests, tidelands and waters. In
this context, the influenced area was calculated byland use classification for respective construction
methods and then the external costs resulting from theloss of ecology services were estimated.
First, the total amounts of fuels and energies perfunctional unit were estimated according to the
JLCA-LCA database [12] and also the interview
survey and the total amounts of all raw materials to
be used in respective database were calculated. Then,the influenced area by each land use was figured out
by multiplying such amounts by respective
influenced areas per estimated unit amount. Also, theareas influenced by the collection of construction
materials and respective fuels/energies as well as byeach land use such as the occupation of factories, etc.
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SEE - Nagoya, Japan, Nov.12-14, 2018

Figure 2 External costs caused by impacts on land use

Figure 3 Total external costs of each construction method
Estimated Results of Total External Costs

CONCLUSION

Figure 3 shows the total external costs by summingup the life cycle cost estimated by existing research[1] and all external costs by emission of GHGs, airpollution and impacts on land use.
As the result, the total external costs were increasedin the order of EPS, cut & fill, foamed waste glass
method (R), lightweight EPS bead mixture method(R), lightweight EPS bead mixture method (V) andfoamed waste glass method (V).
In addition, it was shown that total external costs
would be substantially influenced depending on thepresence or absence of recycling. In terms of foamed
waste glass method (V), since the external cost of
GHGs and air pollution at extraction of raw materials
phase was very big, the technical improvement for
reducing those emissions is necessary.

This research, while paying attention to thepresence or absence of recycling, made acomprehensive LCIA including of external costs
generated by land use as well as by air-pollution
substances and GHGs in addition to market prices.
External costs by life stage for respective construction
methods were clarified through such effort andaccordingly future tasks for reducing the externalcosts were presented.
From now on, there is a need to identify futuretasks including the elaboration of original units forexternal
costs
withconsidering
regional
characteristics.
REFERENCES[1] H. Ito, K. Yamanaka, H. Noguchi, T. Fujii and K.
Minegishi, Comparative Analysis of New
Geomaterials and Embankment Construction
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SEE - Nagoya, Japan, Nov.12-14, 2018

Methods Considering Recycling, International
Journal of GEOMATE, Vol.13(35), 2017,
pp.114-119.
[2] H. Ochiai and K. Omine, Evaluation ofenvironmental impact and development of mixed
composite materials with new additional value.
The Foundation Engineering & Equipment, Vol.
32, Aug. 2004, pp. 9-11.
[3] K. Amano and K. Makita, Life Cycle
Evaluation of the Environmental Loading andConstruction Cost in Paving Process, Journal ofJapan Society of Civil Engineers, Vol.657,
2000, pp. 57-64.
[4] H. Ito and K. Hayashi, Assessment of
Biodiversity and Ecosystem Services Utilized
Life-Cycle Assessment and Environmental
Economic Valuation -Case Study of Wooden
and Steel Framed House, Sociotechnica, Vol.12,
2015, pp. 34-42.
[5] S. Inazumi, H. Otsu, T. Isoda, and Y.
Shigematsu, “Evaluation of social
environmental efficiency on recycling of
construction sludges as ground materials”,
Journal of Geological Engineering, Vol. 68,
March 2012, pp. 163-174.
[6] K. Kamemura, M. Hori, K. Murata and S.
Konishi, Life Cycle Cost of Civil Structures
Considering Risks, Soil mechanics andfoundation engineering, Vol.51(10), 2004, pp.
30-32.
[7] K. Omine and H. Ochiai, Evaluation ofEnvironmental Impact and Recycling Efficiency
for Composite Geomaterials Using Wastes,
Symposium of Environmental GeotechnicalEngineering, Vol.6 2005, pp. 203-208.
[8] K. Minegishi, K. Makiuchi and R. Takahashi,Strength and Deformation Properties ofLightweight Geomaterials Mixed with EPS
Beads, 2001 Annual Meeting of Japan Society of
Civil Engineering, 2001, pp. 426-427.
[9] M. Kagawa, Lecture. New Materials for Soil
Improvement. 4. Method with ExpandedPolystyrene, Material, Vol.40 (449), pp. 242-248.
[10] Onitsuka K, Yokoo M, Hara Y, and Yoshitake
S, Engineering Properties of Foaming Wasteglass Material and an Example of its Utilization,
Journal of Soils & Foundations, Vol. 47 (4),1999, pp. 19-22.
[11] N. Itsubo and A. Inaba, Environmental Impact
Assessment Method for Supporting Decision
Making, Japan Environmental Management
Association for Industry, 700pp, 2010.
[12] Japan Environmental Management Association
for Industry, Option Data Pack for JEMAI-LCA
PRO, Database for JLCA-LCA provided by
Japan Environmental Management Association
for Industry, 2009.

998

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

TRACE ELEMENTS CONCENTRATIONS OF SEAWEED BESIDEMANY CLOSED COPPER MINES IN SADAMISAKI PENINSULA

1Erika Ueno1 and Hiroyuki Ii2
Graduate School of Systems Engineering, Wakayama University, Japan;
2
Faculty of Systems Engineering, Wakayama University, Japan

ABSTRACT
About 66 copper mines operated in Sadamisaki Peninsula from middle Meiji to Taisho era although at
present all the mines closed. From the previous study, seaweed metal concentration sampled around the Takaura
mine was clarified to be high. Metal concentrations of seaweed are generally high compared to metal
concentrations of seawater because of bio-concentration process and depend on long term living undersurrounding condition. Then, seaweeds were sampled at both copper mine area and non-copper mine area. The
mine area is around Sadamisaki Peninsula and the surrounding non copper mine areas are Yashiro Island in
Yamaguchi prefecture and Kada in Wakayama prefecture. Copper, iron, manganese, lead, zinc, calcium,magnesium and arsenic concentrations of seaweeds were measured and their concentrations were studied withsampling location, seaweed type and sampling season. As a result, copper, iron and manganese concentrations ofgreen seaweed were 334, 8195 and 1109 mg/kg high, high, arsenic concentration of brown seaweed was 0.6 to
196 mg/kg, high and magnesium concentration in Ulvales was higher than Sargassum fusiforme. Iron andmagnesium concentrations in Oshima were high. Oshima is a geology that contains a lot of iron and magnesium.
It was found that the concentration of trace elements in seaweed was greatly affected by the surrounding
environment and the geology of the growing place.
Keywords: Trace element, Mine, seaweed, Ulvales, Geology
Sadamisaki Peninsula can be assumed as seaweed inmetal contamination sea. Then, seaweed in the
Sadamisaki Peninsula and the other areas of the Seto
Inland Sea are sampled and their trace element
concentrations are measured and the influence fromthe surrounding environment is evaluated.

INTRODUCTION
Seaweed contains many kinds of trace elements,
because sea water contains various kinds of elements.
The elements are in indispensable for human beingsand marine creatures [1]. Seaweed gets nutrition andheavy metal by taken in seawater. Then, seaweed
stores nutrition and the heavy metals such as arsenicin the body for long term. This characteristic isbioconcentration. It is clear that heavy metal
concentration in seaweed is higher than that inseawater by bioconcentration. In previous studies,characteristics of trace element concentration in eachregion were studied [2]-[6].
The one of the study area is the Sadamisaki
Peninsula located in the western part of Ehime
prefecture and the area is famous for many closed
copper mines operated in Taisho to beginning ofShowa era [7]. And development of mines was
actively carried out in Taisho era.
Figure.1 shows points of mining trace in the
Sadamisaki Peninsula. There were 66 mine traces
operated during the heyday. Although at present allmines closed, waste water from some closed mines
and from tailings of mines still flows into sea. As themost area of the Sadamisaki Peninsula ismountainous and its coast is steep slope and cliff,
waste water directly flows into sea.
Therefore, seaweed sampled around theFig.1 Points of mining trace
at the Sadamisaki Peninsula

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Table 1: Study area name and geology

Fig.2 Study area
METHOD AND STUDY AREARESULTS

Fig.2 shows study area, and Table 1 shows study
area name and geology. Sanbagawa metamorphic
belt mainly composed of green rocks (basaltic rocks
metamorphosed) and granodiorite are rich for ironand magnesium.

The trace element concentrations in seaweed at
the 7 study areas

Izumi
Mue
ikatagoshi
Ashinari

KojimaOoe
Futami

Mekkomisaki

MyojinOoku

Yobokori

UchinouraLight house

NatoriTakauraInouraIn the previous study, heavy metal concentrationin seaweed at the Kii Peninsula was measured andheavy metal concentration pattern for each seaweed
species was also clarified. It’s known that Cu and Fe
concentrations in green seaweed were higher thanthose in brown and red seaweed and that there wasno clear difference of Pb and Zn concentrations
among green, brown and red seaweeds and that As
concentration in brown seaweed was higher thanthose in green and red seaweed. In this research, toclarify the tendency for study area.
First, to compare elements such as copper, leadand arsenic that will adversely affect the humanbody.
Cu concentrations in seaweed

Fig.3 Sampling points at Sadamisaki PeninsulaFig.3 shows sampling points at Sadamisaki
Peninsula.
8 sampling points along the Seto Inland Sea are
Lighthouse, Yobokori, Myoujin, Kojima, Ooe,
Ikatagoshi, Mue and Izumi. 7 sampling points along
the Seto Inland Sea are Uchinoura, Takaura, Inoura,
Natori, Ooku, Futami, Mekkomisaki.
The seaweeds for survey have been collected at
the time of the ebb tide.The collected seaweeds weredried after water washing and the dried samples
were dissolved with concentrated nitric acid. Heavy
metal concentration of solution after filtration with
0.45 micro meter filter was measured by ICP-AES.
Trace element concentration in seaweed was
calculated according to equation (1)㎎ ㎏㎎ ㎏

Fig.4.1 Cu concentrations in seaweed…(1)
Fig.4.1 shows Cu concentration in seaweed forstudy area. Green seaweed, brown seaweed, and red
1000

SEE - Nagoya, Japan, Nov.12-14, 2018seaweed are shown as circle, square and triangle. Cu
concentrations in green seaweed were plotted at 1 to
334 mg/kg, and among them, those in Ulvales at
Takaura was high. Cu concentrations in brownseaweed, it was plotted at 0.2 to 89 mg/kg, andamong them, those in Scytosiphon lomentaria at
Takaura was high. Cu concentration in red seaweed
were plotted at 0.8 to 14 mg/kg, and among them,those in Gloiopeltis furcata at Takaura was high. In
most study points, Cu concentrations in green
seaweed were higher than those in brown and red
seaweed.

Fig.5 shows Mn concentrations in seaweed. Mnconcentrations in green seaweed were plotted at 5 to1109 mg/kg, and among them, those in Ulvales at
Yashiro Island was high. Mn concentrations inbrown seaweed were plotted at 1 to 239 mg/kg, andamong them, those in Sargassum siliquastrum at
Shimonoseki was high. Mn concentrations in red
seaweed were plotted at 4 to 50 mg/kg, and among
them, those in Chondrus ocellatus Holmes at Kada
was high. There is no difference in Mn concentrationfor each seaweed. And regardless of the study points,
there were no difference.
Pb concentrations in seaweed

Fig.4.2 Cu concentrations in green seaweed
Fig.4.2 shows Cu concentrations in green
seaweed. Cu concentration in Ulvales at Takaura
was 121 to 334 mg/kg, and Cu concentrations inUlvales at the other study points were 1 to 27 mg/kg.
Therefore, Cu concentrations in Ulvales at Takaura
were higher than those at the other area.
Mn concentrations in seaweed

Fig.6 Pb concentrations in seaweed
Fig.6 shows Pb concentrations in seaweed. Pb
concentrations in green seaweed were plotted at 0.4
to 50 mg/kg, and among them, those in Cladophora
at Mekkomisaki was high. Pb concentrations inbrown seaweed were plotted at 0.05 to 15 mg/kg,
and among them, those in Sargassum muticum at
Uchinoura was high. Pb concentrations in red
seaweed were plotted at 0.9 to 78 mg/kg, and among
them, those in Gloiopeltis furcata at Mekkomisaki
was high. Therefore, there was no difference in Pb
concentration for each seaweed. Comparing thesampling site, Pb concentrations at Uchinoura,
Takaura and Mekkomisaki were higher than those at
the other study points.
As concentrations in seaweed

Fig.5 Mn concentrations in seaweed

Fig 7.1 shows As concentrations in seaweed. As
concentrations in green seaweed were plotted at 0.4
to 19 mg/kg, and among them, those in Codium
fragile at Shimonoseki were high. As concentrationsin brown seaweed were plotted at 0.6 to 196 mg/kg,
and among them, those in Sargassum macrocarpum
at Yashiro Island were high. As concentrations in
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SEE - Nagoya, Japan, Nov.12-14, 2018

red seaweed were plotted at 0.8 to 19 mg/kg, andamong them, those in Grateloupia turuturu at
Kojima were high. As concentrations in brownseaweed were higher than those in green and red
seaweed. But there was no difference by region.

the human body
Fe concentrations in seaweed

Fig.8.1 Fe concentrations in seaweed
Fig.7.1 As concentrations in seaweed

Fig.8.1 shows Fe concentrations in seaweed. At
most points, Fe concentrations in green seaweed are
higher than those in brown and red seaweed.
Fe concentrations in green seaweed were plottedat 19 to 8195 mg/kg, among them, those in Ulvales
at Takaura was high. Fe concentrations in brownseaweed were plotted at 27 to 1675 mg/kg, among
them, those in Scytosiphon lomentaria at Izumi washigh. Fe concentrations in red seaweed were plotted
36 to 905 mg/kg, among them, those in Lomentaria
catenata at Yashiro Island was high. Therefore,
green seaweed is considered suitable for comparisonof Fe concentration.

As
SaganosekiLighthouse
Uchinoura
Yobokori
InouraTakaura
MyojinNatoriOoku
KojimaOoe
Futami
Mekkomisaki
Ikatagoshi
Mue
Mue・Izumi
Izumi
SuzawaShinomoseki
YashiroBaishinji
Shiraishi
Innoshima1
Oshima
Kada
0

50

100

150

200

As concentrations (㎎/㎏)
Sargassum
horneri

Eiseniabicyclis

IshigeokamuraeCassiope
lycopodioides

Scytosiphon
lomentaria

Ecklonia
kuromeMyagropsis
myagroides

Sargassum
muticum

Padinaarborescens
HolmesSargassum
fusiforme

Sargassum
thunbergii

Undaria
pinnatifida

Fig.7.2 As concentrations in brown seaweed
Fig.7.2 shows As concentrations in brownseaweed. It separates symbols for each kind ofbrown seaweed. Sargassum fusiforme andSargassum thunbergii could be collected at mostpoints. As concentrations in Sargassum fusiforme
were plotted at 29 to 103 mg/kg. As concentrationsin Sargassum thunbergii were plotted at 57 to 150
mg/kg. Because it can be sampled easily and there
are differences in concentrations, it is consideredthat these two seaweeds are suitable for comparisonof As concentration.
Next, to compare elements such as iron, zinc,calcium and magnesium that will be nourishing for

Fig.8.2 Fe concentrations in green seaweed
Fig 8.2 shows Fe concentrations in green
seaweed. Fe concentrations in Ulvales were plotted
1002

SEE - Nagoya, Japan, Nov.12-14, 2018at 19 to 8195 mg/kg, those in other green seaweed
were plotted at 250 to 2580 mg/kg. Therefore, Feconcentrations in Ulvales were higher than those in
the other green seaweed.
Zn concentrations in seaweed

concentration of Ulvales, and the dotted line is thestandard component concentration of Sargassum
fusiforme. This standard component concentration
was quoted from the Ministry of Education, Culture,
Sports, Science and Technology [8].
Ca concentrations in Ulvales were plotted 4300
to 93000 mg/kg, and standard component
concentration was 4900 mg/kg. Ca concentrations inSargassum fusiforme were distributed 6500 to 37000
mg/kg, and standard component concentration was
10000 mg/kg.

Mg
Ulvales

SaganosekiLighthouse
Yobokori
TakauraOoku
KojimaOoe
Ashinari
Mekkomisaki
Ikatagoshi
Mue
Izumi
SuzawaShimonoseki
Baishinji
Shiraishi
Innoshima1
Innoshima2
Innoshima3
Ooshima
Saikasaki

Fig.9 Zn concentrations in seaweed0

Fig.9 shows Zn concentrations in seaweed. Zn
concentrations in most seaweed were plotted 10 to
100 mg/kg at most sampling points. Therefore, there
is no difference in Zn concentration for eachseaweed, and there was no difference for each region.
Ca and Mg concentrations in the two seaweeds

Ca
Ulvales

SaganosekiLighthouse
Yobokori
TakauraOoku
KojimaOoe
Ashinari
Mekkomisaki
Ikatagoshi
Mue
Izumi
SuzawaShimonoseki
Baishinji
Shiraishi
Innoshima1
Innoshima2
Innoshima3
Ooshima
Saikasaki
0

Sargassum
fusiforme

Sargassum
fusiforme

10000

20000

30000

40000

Mg concentrations(㎎/㎏)

50000

Fig.11 Mg concentrations in the two seaweeds
Fig 11 shows Mg concentrations in Ulvales andSargassum fusiforme. Mg concentrations in Ulvales
were distributed 9700 to 47000 mg/kg, and standard
component concentration was 32000 mg/kg. Mg
concentrations in Sargassum fusiforme were
distributed 2900 to 15000 mg/kg, and standard
component concentration was 6400 mg/kg.
Ca and Mg concentrations in Sargassum
fusiforme were no clear difference for each study
point. But these concentrations in Ulvales weredifference in each study points. Especially, Caconcentrations in Ulvales at Lighthouse andInnoshima2 were higher than those at the other study
points.
DISCUSSION

50000

Ca concentrations(㎎/㎏)

100000

Fig.10 Ca concentrations in the two seaweeds
Fig.10 shows Ca concentrations in Ulvales andSargassum fusiforme. A solid filled circle indicates
Ulvales, and a square outline indicates Sargassum
fusiforme. The solid line is the standard component

At Takaura there is a large copper mine trace,and there is a drainage groove continuing from themine trace. So, at Takaura it seems that the influence
from the mining site extends to seaweed.
When comparing study points, Fe concentrationsin Ulvales at Sadamisaki Peninsula, innoshima andOoshima were higher than those at the other study
area. As a factor, it is conceivable that the geologyof the three points contains a lot of iron.
The Sadamisaki Peninsula is a peninsula made ofcupriferous iron sulfide deposit. Therefore, about 66
copper mines operated in Sadamisaki Peninsula
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SEE - Nagoya, Japan, Nov.12-14, 2018from middle Meiji to Taisho era although at present
all the mines closed. The mine is composed of FeS 2
and CuFeS2, and waste water contains copper andiron. Among them, the Takaura mine becomes alarge scale mine trace in the Sadamisaki Peninsula.
Takaura faces Takaura Bay, and there is little
influence from ocean current.
At Oshima which is similar to Sadamisaki
Peninsula, Fe and Mg concentrations in Ulvales
were higher than those at the other study area. As afactor, the influence from geology is considered. The
main geological features of the Sadamisaki
Peninsula and Oshima with high Fe and Mg
concentrations are composed of mafic rocks
containing a lot of Fe and Mg minerals.
As a factor that Fe and Mg concentrations inUlvales were higher than those in the other seaweeds,
it is thought that Chloroplasts in the body of theUlvales are involved. The chloroplast contains
chlorophyll. Mg is a core element for chlorophyll.
Takaura is considered to be the possibility ofcopper contamination comparing normal area suchas the Kada and Yashiro Island areas. In addition,
seaweed growing in a part of Sadamisaki Peninsula
including Takaura and Oshima is considered to berich in Fe and Mg concentrations due to geologicalinfluences.
CONCLUSION
Cu concentration in Ulvales at Takaura washigher than those at the other study area. Pb
concentration in seaweed at Uchinoura, Takaura andMekkomisaki were higher than those at the otherstudy area. As concentrations in brown seaweed
were higher than those in the other seaweed.
Especially, As concentrations in Sargassum such as
Sargassum muticum and Sargassum fusiforme werehigher than those in the other brown seaweed. Fe
concentrations in Ulvales at Takaura, Kojima andOshima were higher than those at the other study
area. Zn concentrations of seaweed at all sampling
points were uniform and Zn concentration deference
between each species was not found. Mg
concentrations in Ulvales were 3 times higher thanthose in Sargassum fusiforme.
Ulvales can be collected easily at each point, andCu, Fe and Mg concentration range is wide.
Therefore, it is considered that Ulvales is suitable forconcentration comparison. Takaura is considered tobe the possibility of copper contaminationcomparing normal area such as the Kada andYashiro Island areas. In addition, seaweed growing
in a part of Sadamisaki Peninsula including Takaura
and Oshima is considered to be rich in Fe and Mg
concentrations due to geological influences

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Bookstore, 1933.
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and Kudo T, “PIXE analysis of trace heavy
metal elements concentrated in seaweed”
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CONCENTRATIONS OF SEAWEED AT THE
KII PENINSULA, JAPAN” International
Journal of GEOMATE, June, 2016, Vol. 10,
Issue 22, pp. 2036-2042.
[4] Ii H, “CU, ZN AND AS CONTAMINATION
OF SEAWEED BESIDE SHIZUKI AND
KANAYAMA METAL MINES IN JAPAN”
Int. J. of GEOMATE, Sept., 2015, Vol. 9, No. 1(Sl. No. 17), pp. 1411-1417.
[5] Yamamoto T, and Ishibasi M, “The Content ofTrace Elements in Seaweeds”, in Proc. 7th Int.
Seaweed Symposium, 1971, pp. 511-514.
[6] Yamamoto T, “Chemical Studies on the
Seaweeds (27) The relations between
Concentration Factor in Seaweeds andResidence Time of Some Elements in Sea
Water”, Records of Oceanographic Works inJapan., Vol. 11, No.2, March. 1972, pp. 65-72.
[7] Fujioka K, Human geography of the Cape
Peninsula - Ehime Prefecture Sadamisaki
Peninsula Scientific Research Report -:Taimeido, 1966.
[8] MINISTAY OF EDUCATION, CULTURE,
SPORTS, SCIENCE AND TECHNOLOGYJAPAN, “Japan Food Standards Ingredients
Table”, 2015.
[9] Kimura T and Kobayashi K, “Report on copper
sulfide iron ore floor survey in the western partof Ehime prefecture” Geological Surveyor
Monthly Report, 1954, 5(10) pp.505-528.
[10] Ken’ichi Hanaoka, Shinnji Miyamoto andmasakatsu Usui, “Effect of hot water washingand soaking on the arsenic content of the brownagla Akamoku, Sargassum horneri” Journal of
National Fisheries University 61(1) 23-26(2012).
[11] Masayuki KATAYAMA, Motohiro KASAMA
and
Yohko
SUGAWA-KATAYAMA“Accumulation of iron and magnesium ingrowing Hijiki(Sargussum fusiforme) plants.”
Trace Nutrients Research, 2012, 29:100-105.
[12] JL Smith, G Summers & R Wong, “Nutrientand heavy metal content of edible seaweeds in
New Zealand” new Zealand Journal of Crop andHorticultural science,38:1,19-28.
[13] G. N. Saenko, M. D. koryakova, V. F.
Makienko and I. G. Dobrosmyslova,“Concentration of Polyvalent Metals bySeaweeds in Vostok Bay,Sea of Japan”, Marine
Biology
1976,
34,
169-176.
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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

HEATING VALUE ENHANCEMENT BY BIOGAS PURIFICATIONUSING NATURAL ZEOLITE AND RICE STRAW-BASED BIOCHAR
Ambar Pertiwiningrum1,2, Margaretha Arnita Wuri3, Andang Widi Harto4, Rachmawan Budiarto4 and Misri
Gozan4
1
Faculty of Animal Science, Universitas Gadjah Mada, Indonesia; 2Agrotechnology Innovation Center,
Universitas Gadjah Mada, Indonesia; 3Faculty of Engineering, Christian University of Surakarta, Indonesia;
4
Faculty of Engineering, Universitas Gadjah Mada, Indonesia; 5Faculty of Engineering, Universitas
Indonesia, Indonesia

ABSTRACT
Biogas has many incentives to replace firewood and crop straw for cooking in rural area. However, to accesssustained adoption of clean, carbon neutral and eco-friendly household fuels, raw biogas needs to be purified
before used. Beside methane (CH4), raw biogas contains trace components adversely affecting appliances or enduser. For example, carbon dioxide (CO2), the greatest impurities in biogas, affect the decrease of heating value.
In some literature, the adsorption for CO2 was claimed to be cheap, simple and adoptable for CO2 removal. This
study aims to investigate utilization rice straw-based biochar as partial substitute adsorbent for CO2 removal.
Carbon dioxide removal using rice straw-based biochar combined with natural zeolite (Z-RB) at room
temperature and gas pressure range of 5-7 bar. Carbon dioxide removal using Z-RB increased the theoreticaland empirical heating value of biogas from 1214.48 kJ to 1766.34 kJ and from 276 kJ to 288.55 kJ respectively.
From this observation, the blue flame that appeared from the combustion of purified biogas using Z-RB went out
for longer than using natural zeolite only (Z-Z).
Keywords:Heating value, Biogas purification,CO2 removal, Rice straw-based biochar, Methane
encourage government to promote biogas
technology as a way to combat global warming andhealth hazards from the traditional biomass energy
combustion. In some developing countries, biogas
dissemination has some obstacle, such as
Indonesian’s policy, public lack of skill and lack ofbiogas related research [8]. On the other hand, inIndonesia the existence of raw material of biogas,
the natural resources of biomass-based livestock andagriculture sector, is abundant [9]. Biogas contains
methane (CH4), a flammable gas with a heating
value of 21-24 MJ/m3 [10]-[11]. A lower heating
value of biogas is due to the considerable carbon
dioxide (CO2) composition in the biogas content, so
to increase the biogas heating value the removal ofcarbon dioxide (CO2) by biogas purification
technology is required [10]-[13].
According to some references, adsorption is acheap, simple and adoptable method for CO2
removal [14]-[15]. Carbon dioxide removal using
the biomass waste-based adsorbent, such as biochar
and activated carbon, has been developed [14], [16][18]. However, the application of rice straw based
biochar for CO2 removal in biogas purification israre. This study aims to investigate the influence ofrice straw-based biochar application as a naturalzeolite partial substitute as adsorbent in biogas
purification system. Because it is known that naturalzeolite has the best ability to eliminate CO2 [15].

INTRODUCTION
In Indonesia, 96% of national energy needs aresupplied from fossil fuels based energy such as
petroleum, natural gas and coal [1]. The constantly
increasing demand for energy led to a long-term
dependency on coal and other fossil fuels [2].
Nevertheless, the traditional biomass energy such as
crop straw and firewood are still dominant in ruralarea [3]. The traditional biomass energy is burnt
directly for domestic utilization such as cooking,heating and lighting. Unfortunately, combustion ofthese fuels leads to high level of health damaging air
pollution from particulate matter (PM), carbon
monoxide (CO), nitrous oxide (NO2) and polyaromatic hydrocarbons (PAHs) [4]. People in rural
areas waste too much of their time to collect crop
straw or firewood for cooking, moreover, theybreath polluted air from the traditional biomassenergy combustion that can threatens their life.
Whereas the availability of clean, low cost andhigh efficient fuel could significantly improve theliving quality, economic sector [5] and public healthin rural area. Biogas is a clean and smokeless fuel,which can be an excellent substitute for these
traditional biomass energies. H Pathak [6] andAmanda [7] claimed that biogas technology is anattempt of greenhouse gases (GHGs) mitigation. The
multiple benefits of biogas technology should

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SEE - Nagoya, Japan, Nov.12-14, 2018

METHODOLOGY

CodeMaterials

Z-Z

Rice straws were prepared to produce biochar as
partial substitute of natural zeolite for CO2 removal.
Agrotechnology Innovation Center of Universitas
Gadjah Mada provided the biogas that will be
purified. Biogas was generated from anaerobic
digestion of cow manure. Aquadest, thermometerand biogas stove were prepared to calculate theheating value needed for boiling water.

Z-RB

Column 1(40:40 grams)
Natural zeolite :natural zeolite
Natural zeolite :rice straw-based
biocharColumn 2(40:40 grams)
Natural zeolite :natural zeolite
Natural zeolite : ricestraw-basesd
biocharCalculation the heating value of biogas
The heating value of the purified biogas samples
was then calculated. Amanda stated that the heating
value of biogas is correlated linearly with thecontent of CH4 dissolved therein [7]. The calculationof the biogas heating value was derived from thepercentage of CH4 content, so theoretically heating
value calculation can be written as follows:

Experimental
Rice straw-based biochar production

Ebiogas = LHVx n CH 4

Rice straws were collected from rice fields andchopped into 10-15 cm size. Rice straw-based
biochar was produced through pyrolysis process.
Before converted to biochar, rice straws were dried
under direct sunlight to evaporate the water content.
Pyrolysis was carried out at 500oC and was then heldfor 4 hours straight when a temperature was reached.
The biochar-based rice straw was then characterizedusing infrared (IR) spectroscopy instruments to
identify the surface functional groups.

(1)

Equation (1), Ebiogas shows the heating value inbiogas tank (kJ). LHV represents the lower heating
value of CH4 (kJ/mol) and n CH 4 represent the CH4content in biogas (mol). The heating value of raw
biogas and purified biogas were then compared toinvestigate the CO2 removal effect on the heating
value enhancement.
Calculation the heating value needed to boil water

Biogas purification through removing CO2
Carbon dioxide removal in biogas purification aims
was to increase the biogas heating value. Stainlesssteel was used to make the adsorption column with
40 mm diameter and 200 mm length. The detailed
scheme of biogas purification unit was illustrated inFig. 1 and the adsorbents formulations were
formulated in Table 1. CO2 adsorption was carriedout at room temperature and gas pressure ranged
between 5-7 bar. The CH4 contents of before andafter adsorption biogas samples then analyzed withgas chromatography (GC) instrument.

The purified biogas then packed into a four bar
pressure tank. In this study, the purified biogas thenused to boiling water using a biogas stove. Each1000 ml is prepared and boiled with a biogas stove.
The temperature rises and boiling time wererecorded every 30 seconds until the water boiled.
The needed heating value for boiling water was
calculated with the formulation in Equation (2):=Q mxcx∆T(2)

Q represents the needed heating value for boilingwater (kJ), m is mass of water (kg), c is specificheat of water (kJ/kg K) and ∆T is the difference
between initial and final water temperature (K).
RESULTS AND DISCUSSION
Characteristic functional groups of rice strawbased biochar
Rice straw-based biochar characterized using IR
spectroscopy to determine functional group on
biochar surface. IR spectroscopy sample wasprepared using KBr pellets and analyzed with wave
number ranges in between 400-4000 cm-1. The result

Fig. 1 Details scheme of CO2 adsorption unit

Table 1. Adsorbents for CO2 adsorption in biogas

1006

SEE - Nagoya, Japan, Nov.12-14, 2018of IR spectroscopy analysis showed in Fig. 2. The IR
spectra in Fig. 2 confirmed the typical bands ofbiochar’s functional groups were similar to theprevious studies. The bands at 3503 cm-1
corresponds to the hydroxyl groups vibration of thebiochar [17]-[18]. The absorption at 1110 cm-1 also
confirmed the C-O bonds vibration of phenol,
alcohol or carboxylic group on biochar’s surface[17], [19]. The C=C aromatic carbons was
confirmed from the absorption at 1609 cm-1 [17]-[19]justified.

Natural zeolite used in this study is similar to naturalzeolite used by Margaretha et al. [19] with specificsurface area of 27.9 m2/g. And biochar, according to, has specific surface area about 200-300 m2/g [20].
It means that biochar has better capability of CO2
removal than natural zeolite.

Fig. 3 Methane content of raw and purified biogas
The linear relationship between CH4 content andthe biogas heating value was also shown in this Fig.
4. The increase of biogas CH4 content wasrepresented by the increase of the heating value.
Before the CO2 removal using Z-Z, raw biogas had
1513.65 kJ heating value per tank. There was anincrease of 1534.31 kJ per tank in heating value after
the CO2 removal. The higher increase in CH4 content
was performed by Z-RB from 1214.48 to 1766.34 kJ
per tank. The results support that the higher heating
value depend on the CH4 content in the biogas. The
same phenomenon of the heating value increased
after biogas purification has also been reported byprevious researcher [10]-[13]. Adalberto [10]reported that the raw biogas heating value is 50
MJ/kg has increased to 45 MJ/kg (90% CH4 content)
after purifying.

Fig. 2 IR spectra of rice straw-biochar
The Biogas Heating Value Enhancement after
CO2 Removal
Carbon dioxide
removal process using
adsorbents aims to enhance the biogas heating value
through the increase in CH4 content. Methane played
an important role in generating energy by biogas
combustion [10]-[11]. The linear relationshipbetween CH4 content and the biogas heating value
was investigated in this paper. The comparison ofCH4 content in raw and purified biogas after CO2
removal using adsorbents according to Table 1. isshown in Fig. 3. Fig. 3 showed that raw biogas(biogas before the CO2 removal) has a lower CH4
content compared with purified biogas. This means
the biogas purification using CO2 removal has been
done successfully. Natural zeolite and rice strawbased biochar are able to capture and trap CO2
molecules on their cavities [15]-[16].
The greatest increase of CH4 content is shown by
purified biogas with Z-RB adsorbent of 44.85%
compared to Z-Z adsorbent of only 1.4%. It can beconcluded that CO2 adsorption by rice-based
biochar is greater than natural zeolite. Yu-Fong et al.
[17] reported that the higher specific surface area ofrice straw-based biochar play an important role incapturing CO2 molecules, well compared to Z-Z.
Ambar et al. [18] and Margaretha et al. [19] also
reported that the higher CO2 removal performed by
combination of natural zeolite and livestock waste
based-biochar compared to natural zeolite only.

Fig. 4 The heating value of raw and purified biogas
Since purified biogas were prepared for domestic
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SEE - Nagoya, Japan, Nov.12-14, 2018

utilization as combustion energy for cooking,combustion test are also necessary. Biogas
combustion test was conducted by observation ofboiling water with biogas. The biogas heating value
was calculated from the energy it needed to boiled
water. The empirical biogas heating value was thencompared with the theoretical biogas heating value.
The results of the needed energy to boiled water
showed in Table 2. It was concluded that biogas
purification using Z-RB were greater compared to ZZ. From the observation, the blue flame rose fromthe purified biogas combustion using Z-RB arise
longer than the purified biogas combustion using ZZ. This is because the purified biogas using Z-RB
adsorbent has a greater CH4 content that act as afuel. The difference between empirical andtheoretical heating values on the results of this study
is due to the correction energy factors lost due to theuse of biogas stoves (biogas stoves have an
efficiency of 15-25%).

and empirical biogas heating value after CO2
removal increased from 1214.48 to 1766.34 kJ andfrom 276 to 288.55 kJ respectively. In other words,
the CO2 removal in biogas could enhance the biogas
heating value. Based on results in this study, theeffort on quality upgrading by biogas purification
through CO2 removal would encourage biogas
technology adoption in rural areas.
ACKNOWLEDGEMENTS
This research was supported by Grant Programfrom Universitas Gadjah Mada, Indonesia (Number
1849/UN1/DITLIT/DIT-LIT/LT/2018). The authors
also would like to thank Universitas Gadjah Mada
and USAID through Sustainable Higher Education
Research Alliances (SHERA) program for helpful.
REFERENCES[1] National Energy Council, Outlook Energy 2014,
Indonesia, Ministry of Energy and Mineral
Resources, 2014.
[2] Qiu C. and Tianbiao, Biogas System in Rural
China: Upgrading from Decentralized toCentralized?, Renewable and Sustainable Energy
Reviews, Vol. 78, 2017, pp.933-944.
[3] International Energy Agency, World Energy
Outlook 2006, Paris, International Energy
Agency, 2006.
[4] The World Bank, Household Cookstoves,Environment, Health, and Climate Change: A
New at An Old Problem, Washington, The
World Bank, 2011.
[5] Zhang P., Yang Y., Tian Y., Yang X., Zhang Y.,
Zheng Y. and Wang L., Bioenergy Industries
Development In China: Dilemma and Solution,
Renewable and Sustainable Energy Reviews, Vol.
13, Issue 9, 2009, pp.571-2579.
[6] H. Pathak, N. Jain, A. Bhatia, S. Mohanty andNavindu G., Global Warming Mitigation
Potential of Biogas Plants in India,
Environmental Monitoring and Assessment, Vol.
157, 2009, pp.407-418.
[7] Amanda D.C. and Michael E.W, Cow Power:
The Energy and Emissions Benefits ofConverting Manure to Biogas, Environmental
Research Letters, Vol. 3, 2008, pp.1-8.
[8] Agabu S., Shabbir H.G. and Seveliano P., Rural
Domestic Biogas Supply Model for Zambia,
Renewable and Sustainable Energy Reviews, Vol.
78, 2017, pp.683-697.
[9] Chandra, W.P. and Ambar P., Novel Design ofTunnel Type Biodigester, in Proceeding 14thISSAT International Conference on Reliability
and Quality in Design, 2008, pp. 289-292.
[10]Adalberto N, Juan M.M. and Jorge E.L.,
Treatment of Biogas Produced in Anaerobic
Reactors for Domestic Wastewater: Odor
Control and Energy/Resource Recovery,

Table 2. The empirical heating value of raw andpurified biogas
Code

Raw
biogas
(kJ)

Z-Z
Z-RB

239.44276

end-pointtime ofblue
flame(seconds)
140
540

Purifiedbiogas(kJ)

249.44288.55

end-point
time
of
blue
flame
(seconds)
270
600

From the findings showed that there wasassociation between CO2 removal for enhancing
heating value of biogas. The increase in heating
value after biogas purification through CO2 removalusing natural zeolite and biochar would encouragerural communities to use biogas energy for cooking.
The higher efficiency energy of biogas has impact
on the increasing types of cooking fuel that would beselected by rural communities. Although the use of
biogas not fully replaces other fuels for cooking, it
can be used as an environmentally friendly and clean
alternative fuel for cooking in rural area. Cahyono etal. [21] also claimed that biogas purification is agood approach to sustainable bio-energy.

CONCLUSION
From this study result, concluded that rice strawbased biochar can be used as alternative adsorbent
for CO2 removal in biogas purification process. In
addition, the use of natural zeolite combined withrice straw-based biochar gave greatest impact ofincreasing the biogas heating value. The theoretical
1008

SEE - Nagoya, Japan, Nov.12-14, 2018[16]Anne E.C., Bin G. and Ming Z., Carbon Dioxide
Capture using Biochar Produced from Sugarcane
Bagasse and Hickory Wood, Chemical
Engineering Journal, Vol. 249, 2014, pp.174-179.
[17]Yu-Fong H., Pei-Te C., Chun-Hao S., ShangLien L., Liping S., Yuan Z., and Chungsheng Q.,
Microwave Pyrolysis of Rice Straw to Produce
Biochar as An Adsorbents for CO2 Capture,
Energy, Vol. 84, 2015, pp.75-82.
[18]Ambar P., Margaretha A.W. and Rachmawan B.
Evaluation The Calorific Value of Biogas After
Carbon Dioxide Adsorption using Natural
Zeolite and Biochar, Unpublished Work but
Accepted, 2018.
[19]Margaretha A.W., Ambar P. and Rachmawan B.,
Methane Enrichment by Carbon Dioxide
Adsorption on Natural Zeolite and Biochar
Derived from Chicken Manure, in Proc. The 9thInternational Graduate Students and Scholars’
Conf. in Indonesia, 2017, pp.911-918.
[20]Zhang Z., Zhang S., Yang H., Shi T. and ChenY., Influence of NH3/CO2 Modification on The
Characteristic of Biochar and The CO2 Capture,
Bioenergy, Vol. 6(4), 2003, pp. 1147-1153.
[21]Cahyono, A., Bambang H.S., Bambang S.,
Ambar P., Wiranti, Iwan S. and Dibyo P.,
Integrated Bio-cycles Farming System for
Production of Bio-gas through GAMADIGESTER, GAMA PURIFICATION and
GAMA COMPRESSING, Journal of the Japan
Institute of Energy, Vol. 90, 2011, pp. 1085-1089.

Reviews in Environmental Science and
Bio/Technology, Vol. 5, 2006, pp.93-114.
[11]Olumide W.A., Yaqian Z., Ange N., Doan P.M.
and Nathalie L., A review of Biogas Utilisation,
Purification and Upgrading Technologies, Waste
Biomass Valorization, Vol. 8, 2017, pp.267-283.
[12]Qie S., Hailong L., Jinying Y., Longcheng L.,
Zhixin Y. and Xinhai Y., Selection ofAppropriate Biogas Upgrading Technology – A
Review of Biogas Cleaning, Upgrading andUtilisation, Renewable and Sustainable Energy
Reviews, Vol. 51, 2015, pp.521-532.
[13]Wojciech M.B., A Review of Potential
Innovations for Production, Conditioning andUtilization of Biogas with Multiple-criteria
Assessment, Renewable and Sustainable Energy
Reviews, Vol. 54, 2016, pp.476-481.
[14]Muhammad
R.A.M.,
Mohammad
R.K.,
Mohammed M.R., Abdullah M.A. and Shuichi T.,
Methane Enrichment of Biogas by Carbon
Dioxide Fixation with Calcium Hydroxide andActivated Carbon, Journal of the Taiwan
Institute of Chemical Engineers, Vol. 58, 2016,
pp. 476-481.
[15]A. Alonso-Vicaro, Jose R.O., S. Gill-Rio, O.
Gomez-Jimenez-Aberasturi, C.A. RamirezLopez, J. Torrecilla-Soria and A. Dominguez,
Purification and Upgrading of Biogas byPressure Swing Adsorption on Synthetic andNatural Zeolites, Microporous and Mesoporous
Materials, Vol. 134, 2010, pp.100-107.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE POTENTIAL IMPROVEMENT OF PUBLIC TRANSPORT IN
MINIMIZING AIR POLLUTION
Lasmini Ambarwati1, and Amelia K. Indriastuti2
Faculty of Engineering, Brawijaya University, Malang, Indonesia;2Faculty of Engineering, Diponegoro
University, Semarang, Indonesia

1

ABSTRACT
Improvement of public transport is an essential effort to encourage mobility. Declining mobility occurs due toincreasing travel length for most people in big cities as consequence from urban development. Urban developmentwith the phenomenon of urban sprawl has been a big issue since the beginning of 20th century which has effects on
increasing traffic congestion, demand for mobility and air pollution. Research has addressed improvement of public
transport, monorail system in minimizing air pollution cost due to urban sprawl. Air pollution cost is imposed onroad users. Current research is insufficient to reveal the effects of urban sprawl on cost build-up caused by emissionof air pollution. This paper examines the extent to which the improvement of monorail system is able to increase
accessibility, reduce air pollution as well air pollution cost due to housing development in the suburbs. Comparative
analysis was conducted to assess the influences of design of monorail system and existing public transport on
differences of air pollution cost. The results show that design of monorail system has significant effect on the
reduction of air pollution concentration and cost compared to the existing condition. The reduction of light vehicles
due to the design of monorail shows a better accessibility and air quality of residents in the western regionsofSurabaya City as case study area in the morning peak hour.
Keywords:Air pollution, Monorail system, Urban sprawl, Emission parameter, Mode choice

INTRODUCTION
Urban development with the phenomenon of urban
sprawl occurs in many cities the world-wide. The
phenomenon of urban sprawl influences living condition
due to the change of complex pattern of land use,transportation pattern, and socio economic development.
Urban sprawl is a pattern of land use in urban area that
illustrates low levels of some dimensions such as
density, continuity, concentration, compactness,
centrality, diversity and proximity [1]. Urban sprawl
represents a rapid expansion of residential area at theoutskirt of the town, causing a spatial mismatch of jobs
and residential dwellings, further causing imbalance intransport with high dependence on automobile [2].
Some consequences of this phenomenon are theincrease of personal mobility and automobile
dependence, and associated with health hazards such as
air pollution, vehicles accidents, and pedestrian injuries
and fatalities [3].
Improvement of public transport were held in
Georgia in order to capture transport issues [4].
Costabile and Allegrini [5] explained that the impacts ofimprovement of transport technology in the reduction ofvehicles pollution could be integrated with ‘‘intelligent’’transport management system. The integrated system

was designed for the real case of Beijing in assessing
the real-time traffic-related air pollution. They
recommended further research to understand themechanisms leading to air pollution impacts fromtransport emissions, to reduce the uncertainty in ourability to quantify the relationships between all
emissions and all impacts, especially for NO2 andparticles.
The vehicle fleet is the largest single source of
global air pollution. The fastestgrowing source ofcarbon dioxide emissions is exhausted from road traffic,
having huge environmental problems with US$93
billion worth of damage to health and environmental
quality each year in the US [6].
The phenomenon of urban sprawl has been
identified in most Indonesian cities since the beginningof the 20th century. A pattern of urban developmentwith increasing settlement growth in the suburbs wasreflected this phenomenon. The phenomenon occurs in
the city of Surabaya as case study area, arecharacterized by an estimated 38% of the population
lives in the suburbs [7]; most of them commute every
day to work in the central urban area. This condition has
significant consequences for mobility, increasing traffic
congestion. It has strongly increased since the late
1990s; predominantly due to increasing numbers of

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SEE - Nagoya, Japan, Nov.12-14, 2018

motorcycles and private cars. Current mode choice byresidents in the city of Surabaya: private car (30%),
motorcycle (62%), and other vehicle types (8%, mostly
minibuses). This situation results in significant increaseof time, cost and productivity losses, and an increase in
air pollution. Improvement of public transport is
expected to change modal split from private vehicles topublic transport, to reduce the amount of air pollution
from motorized vehicles, and to lessen air pollution cost
imposed to road users, as wellto decrease travel timeand distance. Currently, a substantial sourceof
environmental pollution and traffic congestion in urban
areas due to private road transports.

Numerous studies in transport strategies have been
conducted such as transport demand management(TDM) withthe aims of reducing the air pollution frommotor vehicles. Mitchell [8] explained that there was asignificant level of environmental inequality in Leeds,inthe UK. Briefly, environmental inequality was reduced
by an analysis of transport strategies with natural fleet
renewaland road-user charges. Another transport
strategy has been conducted by two demand
management measures, i.e. roadpricing and the vehicle
quota scheme (VQS), revealed as effective instrumental
in controlling both congestion and automobileownership[9]. These studies on transport strategies, such as TDM
and the promotion of technology to control emission,found that those strategies were insufficient to control
the phenomenon of urban sprawl.
An insufficient number of studies have considered
improvement public transport related to minimize theimpacts of the phenomenon of urban sprawl andopportunity to reduce air pollution concentration andcost. Here with, this research focuses on improvementof public transport, i.e. monorail system related to
impactassessment,
particularly air
pollution
concentration in the existing condition and the condition
with a design of monorail system. This study will assess
air pollution cost imposed to road users with expansionof housing development in western region of the city ofSurabaya.
An extensive survey was conducted to estimate themode choice of residents due to the design of monorailsystem. The results of this study are expected to informan effectiveness of design of monorail system in orderto minimize the phenomenon of urban sprawl and toassist in policy making with regard to addressing air
pollution as part of the control of urban sprawl.
This paper is structured as follows: data collection
and methodology are elaborated in Section ‘‘Methods”
consisting of background information on the existing
public transport and improvement of public transport inthe city of Surabaya. Section ‘‘Results” details asimulation analysis of transport, measurement of air
pollution values, procedure to assess change of transport
modal split and air pollution cost and concentration.
This section discusses the estimation of emission
parameters and compares the impacts of each emission
parameter as well air pollution cost for each parameter.
Section ‘‘Conclusions and recommendations” presents
conclusions and recommendations for further research.

METHODS
The city of Surabaya is a case study area, the second
biggest city in Indonesia. Surabaya City, the capital cityof East Java Province, comprises 31districts and 163
villages (Fig.1), the total area of 327 km², and is locatedat an altitude of 3-6 m above mean sea level.
The city has a population of 2,765,908 [7]. The
population density in 2011 was estimated more than
11,000 people per km². A major problem related tosettlement development occurs in the city. In the central
urban area, several informal settlement areas are built,
having a high density (45% built-up area). This situationis contrary to suburban, low density. Data was collected
for each village (called desa) within the urbanized areaof Surabaya City.

Fig.1 The study area (Surabaya City), located in EastJava Province, Indonesia
Currently, Surabaya public transport network
comprises minibus/paratransit and busses. There are 68
available paratransit routes, and 22 bus routes. The
Local Government has planned to improve transport
infrastructures such as monorail and tram system as
seen in Fig.2.
The data was collected by 2010 Census data,secondary data from the Department of theEnvironment. Primary data was collected by distributing
questionnaires to 163 villages (approximately 554
respondents). The questions consisted of three parts:socio-economic background, trip characteristic,transport mode choice. Traffic counting, speed study

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SEE - Nagoya, Japan, Nov.12-14, 2018

and road geometric inventory were investigated on theseveral road-sections of Surabaya City (31 roads).
Vehicle emission values were determined based on
traffic volume and speed.

Fig. 2 The monorail routes
Monorail accommodates the passengers in thewestern and eastern regions, as seen in Fig. 2. The
assessment of the effect of monorail operation on thedecrease of air pollution concentration and cost is
conducted.
The research framework consists of the backgroundcondition of public transport system and further plan of
public transport development. The result is expected toreduce the use of private vehicles and air pollution, toincrease the beneficial received from improvement ofpublic transport as illustrated in Fig. 3.
Improvement of Public Transport (PT) Systems
The existing public transport consists of minibusses(paratransits) with 68 routes and busses in 22 available
routes (minibus accommodates 8–12 passengers, while
bus has 50–55 seats). The frequency of minibusses andbusses are approximately 20–25 veh/h and 5–6 veh/h
respectively.
Anon-board
surveyforbus
andminibus/paratransit was conducted in order tounderstand the current performance ofpublic transportand monorail systems planned, such as capacity, quality,and efficiency. Each region of the city is served byapproximately 26 minibus routes, except the southern
region of the city, which is accommodated by 10
minibus routes.
The Government of Surabaya City plans a monorailsystem in order to decrease the amount of traffic
congestion, to provide alternative options of public
transport that are safe, comfortable and scheduled [10].
The properties of the proposed monorail system are: aticketprice of approximately $0.82, stop spacing of 0.5–
2 km, seat capacity of 177 seats. The improvements topublic transport are expected to encourage the users ofcars and motorcycles to shift their transport mode.

Fig. 3 The research framework
Assessment of Emission Load
The assessment was conducted in two analysis, i.e.
the current public transport condition and the design ofmonorail system.
The analysis of the motorized vehicle emissions
were classified based on vehicle types and air pollutant
substances. Subsequently, the values of pollutant can becalculated based on traffic volume and traffic
composition [11], as follows:
Air pollutant (gr) =traffic flow of each vehicle
class (veh) x emission value for each parameter foreach type of vehicles (g/veh.mile) x road length mile (1)Unit emission loads (g/veh km) are vary for different
modes and different speeds. Relevant emission
substances are CO, CO2, NOx, SOx, and HC. The
number of passengers was based on the average vehicle
occupancy, i.e. automobiles/private cars, minibuses,
medium buses, large buses, trucks and motorcycles
accommodate 3 passengers, 8 passengers, 30
passengers, 55 passengers, 2 passengers, and 2
passengers respectively. The standard value ofmotorized vehicle emissions based on traffic volume
and traffic composition isshown in Table 1.

1012

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1. The standard value of motorized vehicle
emissions in Peak Hours (gr/pas-mile)
Mode
HC
CO
NOx
SOx
Automobile
2.42 18.13 1.47
0.05
Car Pool
0.88 6.55
0.53
0.02
Diesel Bus
0.06 0.81
0.36
0.05(medium or largebus, truck)
Source:[11] .

take over from users other modes. The increase ofpassengers in the monorail system reduces the use ofprivate motorized vehicles, is expected to decline
emission parameters.

Calculation of Air Pollution Cost
The comparative analysis is conducted based on theexisting condition and design of monorail system
condition. According to [12], air pollution cost for urban
road is calculated by using the following:
Air pollution cost ($) =air pollution cost
constant ($/veh-mile) x peak hour traffic
volume (veh) x road length (mile)(2)
The air pollution cost constant is shown in Table 2.
Table 2. Air pollution cost content ($/veh-mile)
HC

CO

NOx

Value of Air Pollution ParameterThree cases are proposed in order to understandreduction of traffic volume because some private
vehicle users change to use the monorail system.
The loads of emissions based on specific weighted
emission parameters regarding air quality for the city ofSurabaya roads are required. The weighted emission
parameters refer to air quality data containing theweighted emission values per vehicle kilometer (gr/vehkm) and depend on average speed standard of eachvehicle class for each road type (motorway, urban, andrural).The weighted parameters, such as CO, NOx, SOx,and HC are estimated. The values were analyzed for thecurrent base 2010 according to [12], the procedure fordetermining air pollutants at micro level due to traffic,
as explained as follows:(3)
qCO = 867.92. Uv-0.8648

SOx

qNOx= 0.0005. Uv2-0.0656. Uv + 3.6586 (4)7.20
120.60 – 8.40
0.01 – 0.36
Source: [11].
Note : the value will convert from USD into IDR

where Uv is average speed standard for each vehicle
class for each road type in km/hr.

RESULTSThis section explains the assessment of modal split on
existing condition and improvement of public transport
situation, emission parameter concentration and cost
imposed to road users.
Modal Split
The comparative analysis is conducted in order toknow the change of modal split for each vehicle classbased on the existing condition and design of monorailsystem condition. Three cases are simulated by
OmniTRANS model, consisting of estimation oftransport model parameters for each condition andemission parameters. Simulation model has been donein previous research [13].
The following the results of previous research as
follows:
a. The design of monorail systems (C3) encourages
the use of public transport up to 37% from thecurrent trend.
b. The number of cyclists in C3 also increases six
times compared to the current trend 2030. Thisfinding means that this case can influence the loadof traffic flow and air quality on the roadcorridors.
Briefly, provision of sufficient PT is necessary to

The emission load for each parameter has been
computed by simulation of the OmniTRANS model,
based on the simulated flows on the transport network,for various cases; the results are presented in Table 4.
Improvement of the PT system with the design ofmonorail system (C3) has an effect on decreasing theload of private vehicles (cars and motorcycles), as
reflected in 30% (cars) and 50% (motorcycles) reducing
CO emission compared to C2 as explained in Table 3.
Table 3Weight emission for CO for each caseTransport
mode
Cars
Motorcycles
PT
Total (allvehicles)Concentration of CO
Case
(C1)
(C2)
(C3)
Current
Current
MonorailBasetrendsystem
22.8
65.3
21.2
53.4
124
60.3
84.3
45.1
20
160.5
234.4
101.5

Comparative analysis of emission parameter fordifferent road corridor
The operation of monorail in western part ofSurabaya areas can reduce the air pollutant
concentration. A great benefit for the community due toan increase of air quality and air pollution cost is1013

SEE - Nagoya, Japan, Nov.12-14, 2018

obtained. A significant difference of emission
concentration and cost occurs on Lontar St. and
Sungkono St. as described in Table 4.
Reducing CO concentration is amounted 71% byassumption of ticket price of monorail 2,500 IDR morethan the price of existing public transport (minibus andbus). It can be concluded that monorail operation can
reduce the amount of CO pollutant, because of thedecrease of user of motorized vehicle on the roads andincrease of monorail user.
The air pollution costs on each street can becalculated after the value of air pollutant on Lontar St.
and Sungkono St. were identified, using the Equation(2, and converted into IDR (1 USD = 13,500 IDR).
Table 4 The value of emission parameter on Lontar
St.(gr) and Sungkono St
VehicleType

Traf. Vol.
(veh/h)

HC

CO

NOX

SO2

Automobile

929

9,639

72,213

5,855

199

Car Pool

22

332

2,471

200

8

9

125

56

8

47,434

113,841

57,414

188,650

6,111

215

Diesel Bus*)
Motorcycle

3,319

Total
Private car

4,108

410,451,825

684,086,376

256,532,391

10,831,368

Publictransit78

7,793,389

12,988,982

4,870,868

205,659Bus

1

99,915

166,525

62,447

2,637

Truck

17

1,698,559

2,830,932

1,061,599

44,823Motorcycle

9,607

959,885,756

1,599,809,594

599,928,598

25,330,319

Total

4,578,682,562

Table 5 Prediction of vehicle emissions on Lontar St.
and Sungkono St. with Monorail Operation (gr)Peak Hour(Average of Morning, Noon and Afternoon)
Sce.

I

II

III

Mode

Lontar St.
CO

NOX

Automobi
le1,570

11,763954

Car Pool

42

311

SO

SO

HC

CO

NOX

33

8007

59,983

4,864

165

25

1

221

1,659

134

4

X

X

DieselBus
MotorcycleAutomobi
le

221

1,658

134

5

266

1,995

162

6

7,191

53,877

4,369

149

21,524

161,25

13,074445

4,628

34,6682,811

95

23,581

176,66

14,324487

Car Pool

194

1,451

118

4

983

7,359

597

20

DieselBus
MotorcycleAutomobi
le

230

1,727

140

5

355

2,660

215

7

10,24776,7656,224

212

30,673229,7918,632634

6,637

49,722

4,032

137

33,814

253,33

20,540699

Car Pool

443

3,317

269

9

2,380

17,827

1,445

49

248

1857

150

5

522

3,912

317

11

13,124

98,322

7,972

271

39,282294,2923,862

812

DieselBus
MotorcycleTable 6. Prediction of Air Pollution on Lontar St. and
Sungkono St. with Monorail Operation (IDR)

VehicleType

Sungkono St.

HC

From the results of change of mode split, the traffic
volume reduction can be obtained as shown before, thus
the air pollutant reduction can be calculated using
Equation 1, as seen in Table 5. Three scenarios ofmonorail systems with the change of ticket price are set
in order to know the different concentration of air
pollution parameterfor each vehicle type. First scenario
is condition with monorail ticket 2,5000 IDR less cheap
than the existing public transport. Second scenario iscondition which is monorail ticket similar to the existing
public transport. The third scenario is done by monorailticket 2,5000 IDR more expensive than the existing
public transport.
Table 5 explains that CO is the major component of
the motorized vehicle emission. Thus, motorcycle gives
the largest contribution in air pollution, followed byautomobile.As amount ofair pollution is influencedby
the characteristics ofvehicle engine.
Scenario 1 is the condition with monorail ticket ischeaper than the existing modes, the monorail
passengers increase, thus the amount of emission is thelowest concentration. Meanwhile, scenario 3 is thehighest emission concentration for each parameter due
to less reduction of use of private vehicles. Scenario 3
has the effect on reduction of 26% HC, 23% CO, and
24% NOx. Scenario 2 has impacts on reduction of HC
and CO up to 44% and NOx up to 47%. Meanwhile,
scenario 1 has significant decreasing HC up to 66%, CO
up to 71%, and NOx up to 82%.
The difference of cost due to CO emission between
road with business places and with residential areas inroad corridors is approximately 3 billion IDR as seen in
Table 6.

Peak Hour(Average of Morning, Noon and Afternoon)
CO

Total

CO

Total

542.706.304

Private car

106.520.753

Publictransit1.776.271

Bus-

388.559

Truck

5.273.305

5.883.898

Motorcycle

315.954.207

945.697.792

9.547.457
855.111.763

2.994.659.300

There were a significant reduction between existing
condition of air pollution cost (with no monorail) andthe condition with monorail. By applying Scenario 3,
the community can save about 26% of the air pollution
cost, while applying Scenario 2 can save 44%. Scenario
1 can reduce air pollution cost from 5.19 trillion IDR to
1.71 trillion, or save about 67%. So, it can be concluded
1014

SEE - Nagoya, Japan, Nov.12-14, 2018that the investment of monorail will delivered asignificant benefit in the savings of air pollution cost as
illustrated in Fig. 4.

Air Pollution Cost (in trillion IDR)
5.19

existing

1.71

2.89

3.85

Scen.1

Scen.2

Scen.3Fig. 4 Total of Air Pollution Cost on Lontar St. and
Sungkono St. due to Monorail Operation

CONCLUSIONS AND RECOMMENDATIONS
Conclusions
This study demonstrated that improvement of public
transport with the design of monorail system isnecessary to address the mobility and emission
problems in fast growing urban areas and the associatedeffects of urban sprawl. Consideration on air quality, i.e.
i.e. HC, CO, NOx, SOx concentration is an importantfactor in urban transport planning with analysis of threecases.
The case (C3) with improved PT systems such asmonorail system was characterized by the smallest
emissions rates of each parameter. This case (C3) also
can reduce the use of private vehicles (cars andmotorcycles) and decrease 30-50% of emission
parameter compared to the existing public transport.
Scenario 1 of monorail operation will decline HC up
to 66%, CO up to 71%, and NOx up to 82% total on
both streets. Thus the air pollution cost will decline up
to 67%. Scenario 2 can reduce HC and CO up to 44%
and NOx up to 47%, and the total air pollution of bothstreets on peak time is reduced about 44%. Scenario 3
only lessened 26% HC, 23% CO, and 24% NOx, andthe total air pollution of both streets on peak is saved
26%.
The highest air pollutant cost occur on road corridors
as business places. The difference cost of CO emission
between road corridor with business places and withresidential areas is high cost about 3 billion IDR.
Recommendations
An integration of spatial-transport strategies as wellan environmental assessment would provide moresophisticated and long-term advantages when designing
improvements of public transport systems related tohousing planning. The integrated approach should also
be based on residents' preferences as regards the impact
of such new developments.

The further research for air pollutant cost assessment
should be conducted in order to estimate the air
pollutant suitable with the Indonesian road environment
and the change of monorail tariff.

REFERENCES[1] Bekele, H., Urbanization and urban sprawl. Masterof Science Thesis-Department of Infrastructure
Section of Building and Real Estate Economics
Kungliga Tekniska Högskolan, 2005.
[2] Duncan, J. E., Frank, J., The search for efficienturban growth patterns. Tallahassee, FL: Florida
Department of Community Affairs, 1989.
[3] Frumkin, H., Urban Sprawl and Public Health.
Public Health Reports 117, 201, 2002.
[4] Karanadze, L., The Main Aspects of Sustainable
and Healthy Urban Transport Development
inGeorgia, Ministry of Environment of Georgia,
2006.
[5] Costabile, F., Allegrini, I., A new approach to linktransport emissions and air quality: an intelligent
transport system based on the control of traffic air
pollution. Environ. Model. Software. 23, 2008,
pp.258–267.
[6] Carley, M., & Christie, I., Managing sustainable
development. Routledge, 2017.
[7] Statistic Bureau of Surabaya, The Figures ofSurabaya City in 2010 (in Indonesian).
[8] Mitchell, G., Forecasting environmental equity: air
quality responses to road user charging in Leeds,
UK. J. Environ. Manage. 77, 2005, pp. 212–226.
[9] Chin, A.T., Containing air pollution and traffic
congestion: transport policy and the environment in
Singapore. Atmos. Environ. 30, 1996, pp. 787–801.
[10] Department of Transport of Surabaya City,
Surabaya
MRT:Surabaya
Mass
Rapid
Transportation (SMART). Technical Report.
Surabaya, Indonesia, 2013.
[11] Litman, T., Transportation Cost Analysis. Victoria,
1995.
[12] The Ministry of General Works, Law no.
017/T/BM/1999, Procedure for prediction of air
pollution in micro scale from traffic‖ (inIndonesian), Jakarta, 1999.
[13] Ambarwati , L., Verhaeghe, R.J., Pel, A.J., Arem,
B. van, The influence of integrated space–transport
development strategies on air pollution in urban
areas, Transportation Research Part D 44, 2016, pp.
134–1461015

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PURIFICATION EXPERIMENTS ON THE PASIG RIVER,PHILIPPINES USING A CIRCULATION-TYPE PURIFICATIONSYSTEM
Okamoto Kyoichi1, Komoriya Tomoe2, Toyama Takeshi1, Hirano Hirosuke3,
Garcia, Teodinis4, Baccay, Melito4, Macasilhig Marjun4, Fortaleza Benedicto4
1
Professor, CST, Nihon University, Japan; 2CIT, Nihon University, Japan; 3National College of Technology,
Wakayama College, Japan; 4Technological University of the Philippines, Philippines

ABSTRACT
Polluted sludge from the Pasig River, which connects Laguna de Bay to Manila Bay in the Philippines, exerts
a very large environmental load on the surrounding area. The river used to be a good route for transportation and
an important source of water for the old Spanish Manila. However, the river is now very polluted due to humannegligence and industrial development, and biologists consider it unable to sustain aquatic life. Many researchers
have investigated the purification of the Pasig River, without satisfactory results. Here, we investigate fine-bubble
technology for purification of polluted sludge. The critical point in this technique is the activation of bacteria
existing in the area using fine bubbles. Sludge is decomposed and purified by activating aerobic bacteria after
creating an aerobic state. In this study, our objective is to test the performance of the purification system on thesludge and water in the Pasig River by comparing the results to a case study in Funabashi Port, Japan. We achieved
good results, with a significant decrease in total nitrogen in both the Pasig River and Funabashi Port samples. The
system is an effective purification system for treating sludge from the Pasig.
Keywords: Fine bubbles, Purification of Sludge, Circulation-Type Purification System, Pasig River, Aerobic
Bacteria
developed by one of the authors of this paper to treat
ocean sludge, as described in [3]. This system has
already been shown to be efficient for purification [3].
In this study, our objective is to demonstrate theeffectiveness and efficiency of the circulation-type
purification system for treatment of the Pasig River.

INTRODUCTION
The Pasig River in the Philippines connects
Laguna Lake to Manila Bay and divides thePhilippine capital Manila into a northern and southern
part. The Pasig River is a tidal estuary and the flow
direction depends on the difference in water level
between Manila Bay and Laguna Lake. The Pasig
River was historically used as a very importanttransportation route and water source. The river is
now very polluted due to a human negligence andindustrial development, as in [1]. There are many
research papers as in [2], [3] investigating the river,
but no study has made considerable progress from thepoint of view of purification. One author investigatedthe COD (chemical oxygen demand) at about 15
points along the river [2]. We measured the current
COD in the river and found that the value has almost
doubled since the year 2000.
In general, polluted matter in solid form elutes inwater and polluted matter in water settles to theriverbed when pollution is severe. It is best to treat
both pollution sources without a distinction between
solids and water. In addition, the treatment must be
effective for both freshwater and seawater, since theriver flows into the sea and is tidally influenced.
Here, it is considered that the best treatment
method is a decomposition purification system using
the circulation of fine bubbles to activate naturally
occurring aerobic bacteria. The system was

EXPERIMENTAL SYSTEM
Experimental Devices
The experimental device consisted of two parts,
shown in Fig. 1. The water circulates through twotanks. In one tank, fine bubbles are generated, using asystem based on [5]. The fine bubbles have microsize diameters and high solubility. This means thatwater with a high concentration of dissolved oxygen(DO) circulates through the tanks.

Fine-Bubble Generator

Experimental Tank

Fig. 1 Schematic Representation of the Experimental
Apparatus
1016

SEE - Nagoya, Japan, Nov.12-14, 2018

The second part of the device is the experimental
tank. Here, sample water and sludge are treated. Thisapparatus was set up in one of the laboratories of theIntegrated Research and Training Center (IRTC) of
the Technological University of the Philippines(TUP), Manila.

Sampling Points for Sludge and Water
Sedimentary sludge samples were collected using
an Ekman-Berge bottom sampler at the Ayala Bridgeon the Pasig River as shown in Fig. 3 and Fig. 4.
Water samples were collected at wharf near sludge
sampling point in [3].
Samples from Funabashi Port, Japan shown in Fig. 5
were used to compare the efficiency and effectivenessof the purification system for the Pasig.
Tokyo

Yokohama

Fig. 2 Picture of the Experimental Apparatus

Fig.5 Sampling Point at Funabashi Port in Japan
Catching sludge
Ayala Bridge

Experimental Procedure
Catching water

The dimensions of the experimental device areshown in Table 1. A sedimentary sludge sample of
0.417 (kg) and 25(L) of river water were collected.
The samples were then put in the experimental tanks.
The quality of the samples was measured from themoment the fine bubble generator started. After six
hours of fine bubble generation, a microorganism
activator was added in liquid form. The main
component of the activator was kelp with somenutrients and enzymes. The microbial activator wasadded in a 100 (mg/L) concentration. The measured
sample quality parameters were water temperature,
pH, DO, ammonia nitrogen (NH4-N), nitrite nitrogen(NO2-N), nitrate nitrogen (NO3-N), total nitrogen (TN), and COD. Measurement of these parameters was
conducted 24, 48, 60, and 72 hours from the time thefine-bubble generator started. Water temperature andDO were measured using a multi-parameter water
quality meter (portable fluorescent dissolved oxygen
meter). A digital water analyzer; Digital Pack Test
(Kyoritsu Chemical-Check Lab., Corp.) was used tomeasure NH4-N, NO2-N, NO3-N, and T-N.

Pasig R iver

FunabashiPortin Tokyo Bay

Manilain Philippines

Fig.3 Sludge (Circle) and Water (Star) Sampling
Points at the Ayala Bridge on the Pasig River, Manila

Table 1 Dimension of the Experimental Devices
Water = 25 L, Sludge= 0.417 kg
Size of Water Tank = 200x270x370 mm
Flow Rate for Fine Bubble Generator = 43 L/min
Flow Rate for Circulation Water Pump = 10 L/min
Microbial Activator = 100 mg/L

Fig.4 Sampling Sludge and Water in the Pasig River

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SEE - Nagoya, Japan, Nov.12-14, 2018

RESULTS AND CONSIDERATIONS

Comparison of the Purification Results for T-N
with Funabashi Port in Japan

Water Temperature, pH and Dissolved Oxygen
To compare the results of Funabashi Port and the
Pasig River, we carried out experiments to understandthe effect of the ratio of sludge and water. The
experimental conditions, with variable amounts ofwater and sludge, are shown in Table 2. The usualparameters used at Funabashi Port in Japan are 1 kgof sludge and 30 L of water and the total experimental
time is 120 hours. Case 1 was treated as the standard
ratio of sludge, Case 2 was half the standard sludge
ratio, and Case 3 tested a lower volume of water.
These sludge and water are from Funabashi Port.
Figure 8 shows the results of T-N for the threecases. We estimated that purification of the samples
in Case 2 in Fig.8 is completed in half the time ofCase 1 according to the ratio of sludge. However,there was no change in the performance due to thedifference in water volume between Case 2 and 3.
According to the above, Fig. 9 presents the resultsof Case 1 in half the run time, i.e. 60 hours instead of
120 hours. Therefore we can get assuming linear
relation. Here, the y-axis shows the normalized
expression.
Figure 10 shows a comparison of the results of TN between Funabashi Port and the Pasig River. From
the results, the circulation-type purification system
indicates the same tendency and good purification
performance. The tendency of the purification results
is almost the same.

Measured results of water temperature, pH, andDO are shown in Fig. 6. The water temperaturestabilized at 30 degree Celsius, pH was constant ataround 8.0, and the DO stabilized around 6.0 mg/L.
The water temperature, pH, and DO are the basic
environmental conditions of the experiment andshould be kept constant as much as possible forproper interpretation of the other measured
parameters.

Fig. 6 Changes in Water Temperature, pH, andDissolved Oxygen during the Experiment

Results of DIN (Dissolved Inorganic Nitrogen)and T-N in the Pasig RiverThe DIN is the totality of NH4-N, NO2-N, andNO3-N. Figure 7 shows the results of measured DIN
and T-N. There was a significant decrease in DIN
from hour after 24 to until 72. DIN decreased a little
at about 6 hours, but decrease rapidly after 24 hours.
Therefore, it seems that bacterial denitrification
occurred in the system.
The measured T-N showed that the quality of thesample improved. The temporary increase in T-N atabout six hours may have been due to a slight delayin the inclusion of the microbial activator. After
inclusion of the activator, T-N decreased significantly
to 72 hours. The purification system performed very
well since the concentration of T-N after 72 hours was
about 50% of the starting value.

Table 2 Experimental Condition for Comparison of
the Sludge Ratio
Case1: Water = 25L, Sludge = 0.84kg ; Standard
Case2: Water = 25L, Sludge = 0.42kg ;1/2

Case3: Water = 20L, Sludge = 0.42kg ;1/2

Fig.8 Comparison of T-N with Different Sludge
RatiosFig. 7 Changes in DIN and T-N in the Psig River

1018

SEE - Nagoya, Japan, Nov.12-14, 2018

T-N (normalized) ((mg/L)/(mg/L))

Comparison of the Solid Results for the Pasig
River and Funabashi Port
Comparison of EDX (Energy Dispersion Type X-ray
Analysis Device) Results between the Pasig River andFunabashi Port
Figure 12 shows a comparison of the EDX resultsfrom the Pasig River and Funabashi Port. Comparing
the beginning and the end of the experiments, S(sulfur) decreased but Na (sodium) increased slightly.
The change in Si (silica) differed between the two
locations; no change was observed in the Pasig River
sample however the proportion of Si in the Funabashi
Port sample decreased. It seems the Si (silica) ratio in
Funabashi Port sample decreased a little by the
relatively increase of Al and Fe. The other results
showed the same tendency for both locations.

T-N (normalized) ((mg/L)/(mg/L))

Fig. 9 Normalized T-N in Samples with Different
Sludge Ratio

100%

P, 0.6

P, 0.5Fe, 11.9

Ca, 4.7
Na, 2.5

Fe, 10.9

Fe, 9.0

Ca, 2.3

Ca, 2.3

Na, 5.0Na, 8.2

S, 5.2S, 0.9S, 2.0P, 1.2

P, 0.9Ca, 5.2
Na, 4.7

Al, 20.7

Al, 20.0

Al, 20.7

Si, 57.8

Si, 57.8

Si, 56.9

Pasig River 0h

Pasig River 72h

Funabashi Port 0h

Fe, 10.9

S, 3.3

Al, 23.6

50%

Si, 50.5

0%Funabashi Port 120hFig. 12 EDX Results from the Pasig River andFunabashi Port

Fig. 10 Comparison of T-N in the Pasig River with
Funabashi Port

Comparison of SEM (Scanning Electron Microscope)
Results for the Pasig River and Funabashi Port
Visualization of Results
Figure 13 shows a comparison of the SEM resultsfrom the Pasig River and Funabashi Port, at amagnification of 1000 times. Comparing the
beginning and the end of the experiments, no change
was observed for the Pasig River samples.

Figure 11 shows the experimental visual scene at
0, 24, 48, and 72 hours. Changes to the water color in
the tank can be clearly seen, which demonstrates the
purification effects.

0h

24h

48h

72h

Fig. 11 Photos of the Experimental Tank with Time

(Pasig River; 0 h)

(Pasig River; 72 h)(Funabashi; 0 h)

(Funabashi; 120 h)Fig. 13 SEM Results from the Pasig River andFunabashi Port

1019

SEE - Nagoya, Japan, Nov.12-14, 2018

The diameter of the sludge particles from the Pasig
River is relatively large so they are resistant toabrasion. On the other hand, the diameter of thesludge particles from the Funabashi Port is relatively
small, so that the diameter decreased after treatment.

REFERENCES[1] Gorme et al, The Water Quality of the Pasig
River in the City of Manila, Philippines: Current
Status, Management and Future Recovery, 2010.
[2] Urase T., Nadaoka K., Yagi H., Iwasa1 T.,
Suzuki T., Siringan F., Garcia T.P. and Thao T.
T., Effect of urban emissions on the horizontal
distribution of metal concentration in sedimentsin the vicinity of Asian large cities, Journal of
Water and Environment Technology, Vol.4,
No.1, 2006.
[3] Okamoto K., Hotta K., Toyama T. and Kohno H.,
Purification System of Ocean Sludge by
Activating
Microorganisms,
International
Journal of GEOMATE (Geotec, Const. Mat. &Env.), Vol.6, No.1, March, 2014, pp.791-795.
[4] Matsuo K., Maeda K., Ohnari H., Tsunami Y.
and Ohnari H., Water Purification of a Dam Lake
Using Micro Bubble Technology, Progress inMultiphase Flow Research I, 2006, pp.279-286.
[5] Okamoto K. and Hotta K., Purification System of
Ocean Sludge by Using Coagulants andActivating
Microorganisms,
International
Journal of GEOMATE (Geotec, Const. Mat. &Env.), Vol.4, No.2, June, 2013, pp.574-579.
[6] Sone T, Yamashita K and Okamoto K,
Identification of Microorganism in Purification
Process for Ocean Sludge by using Purification
System with Circulation Type, Japan
Association for Coastal Zone Studies, July 2014.
[7] Okamoto K and Toyama T, Ocean
Decontamination: High Efficiency Removal
Method of Radioactive Cesium from Ocean
Sludge by Using Microbubbles and Activating
Microorganisms, The Japan Society of Naval
Architects and Ocean Engineers, May, 2016.
[8] Okamoto K. and Toyama T.,
Ocean
Decontamination: Removal Efficiency ofRadioactive Cesium from Ocean Sludge by using
Microbubbles and Activating Microorganisms,
International Journal of GEOMATE (Geotec.,
Const. Mat. & Env), Vol. 10, Issue 21, May,
2016, pp. 1924-1928.
[9] Komoriya T., Okamoto K. and Toyama, T.,
Removal of Radioactive cesium from Ocean
sludge by the bacterium using Purification
System of Circulation Type, International
Journal of GEOMATE, Vol.15, Issue 47, July,
2018, pp.53-57.

CONCLUSION
The effectiveness and efficiency of treatment of
the Pasig River using the circulation-type purification
system were determined.
1) The purification efficiency was good as
demonstrated by the decrease in DIN and T-Nconcentrations.
We carried out three experiments to determine theeffect of a variable ratio of sludge and water. From
the results, an interpolation factor was determined. Bychanging the time axis using the factor, we comparedT-N in the Pasig River and Funabashi Port and a very
good purification tendency was obtained for both
locations. From the results:
2) The purification performance was very good,as shown by the decrease in T-N in both the Pasig
River and Funabashi Port samples.
3) The water color in the tanks over time alsovisually demonstrated very good purification results.
From the results of EDX, the weight ratio of thematter in the solid dry sludge was calculated.
From the results of SEM, the change in diameterof the sludge particles was identified.
4) From all the above, it appears this system cantreat both polluted sludge and water which is very
useful in application to the Pasig River.

ACKNOWLEDGEMENTS
The authors would like to express sincere thanks
for executing the experiments to Mr. Nogawa,
Daisuke, a graduate student, Mr. Tateishi, Shotaro, a
student of Nihon University, Prof. Reynaldo, Baarde,
Head of Construction Engineering and management
Department of TUP, and also help for writing paperto Ogawa, Ma.Richie C., a staff of Nihon University.
This work was supported by a KAKENHI(Grant-in-Aid for Scientific Research (C-17K06969)).

1020

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PERFORMANCE OF A CIRCULATION TYPE PURIFICATIONSYSTEM DURING THE TREATMENT OF SLUDGE
FROM MANILA BAY AND TWO PORTS IN JAPANKomoriya Tomoe 1, Okamoto Kyoichi 2, Toyama Takeshi2, Hirano Hirosuke3,
Garcia, Teodinis4, Baccay, Melito4, Macasilhig Marjun4, Fortaleza Benedicto4
1
CIT, Nihon University, Japan; 2CST, Nihon University, Japan; 3National College of Technology,
Wakayama College, Japan; 4Technological University of the Philippines, Philippines

ABSTRACT
Ocean sludge can have negative effects on local marine ecosystems. Here, the use of fine-bubble technology
was investigated for applications involving the purification of sludge. The principle of this technology is thatbacteria that can degrade sludge are activated by the aerobic conditions induced by the fine-bubbles. One of theauthors has developed a fine-bubble decomposition system for ocean sludge that is of the circulation type. Here,
we tested the performance of this system during the treatment of sludge from Manila Bay and two ports in Japan.
The results showed that the system performed well when treating the sludge. Potentially beneficial bacteria isolated
from the Manila Bay sludge experiments were identified by 16S rRNA gene sequence analyses.
Keywords: Fine-bubbles, Purification of Sludge, Circulation Type Purification System, Manila Bay

countries. Because of the high levels of humanactivity and industrialization around Manila Bay, thewater quality within the bay is degraded [4].

INTRODUCTION
It is very important to reduce the amount of
sedimentary sludge in the ocean. Plans to reduce suchsludge are usually based on dredging or sand covers.
Dredging is a simple method whereby the sludge isphysically removed. However, the dredged sludge
needs to be treated after removal, which takes timeand money. Sand covers, in general, reduce
contamination from ocean sludge, but they too canstress living organisms and ecological systems andare not ideal in places where navigation is a concern.
Hence, better sludge management options are needed.
Here, we explore the use of fine-bubble
technology to promote sludge degradation. Finebubbles can change conditions from an anaerobic
state into an aerobic state. One of the authors hasdeveloped a method for decomposing sludge by using
microorganisms activated by the aerobic state
induced by micro-bubbles. Subsequently, very goodresults were achieved with this method [1–3]; forexample, the method enabled the treatment time to be
reduced to 5 days. Here, the purification system wasused to treat sludge from the following three areas:
Funabashi Port in Tokyo Bay, Japan, Hidaka Port inWakayama Prefecture, Japan, and Manila Bay,
Philippines. The main objective of this study was toassess the performance of the purification system.
The ports of Funabashi and Hidaka are important
ports in Japan. Manila Bay is a natural harbor that is
located in the capital city of the Philippines. It has
served as a key area for socio-economic developmentin the country and has helped to facilitate commerce
and trade between the Philippines and nearby

EXPERIMENTAL SYSTEM
Experimental Devices
The experimental devices consisted of two parts,
as shown in Fig. 1. Specifically, the water circulates
through two tanks in the purification system. In one
tank, fine-bubbles are generated. These fine-bubbles
have a micro-sized diameter and high solubility. This
allows water with high concentrations of dissolved
oxygen to circulate readily through the tanks. The
fine-bubble generator was based on earlier work [56]. The other tank is the experimental tank. In thistank, sea water and sludge were combined.
This apparatus was set up in one of thelaboratories of the Integrated Research and Training
Center (IRTC) of the Technological University of thePhilippines (TUP), Manila, Philippines.

Fine-Bubble Generator

Experimental Tank

Fig. 1 Purification System of the Circulation Type

1021

SEE - Nagoya, Japan, Nov.12-14, 2018

Collection Points for Sludge and Sea Water

Funabashi Portin Tokyo Bay

To investigate the efficiency of the purification
system, sea water and sedimentary sludge samples
were collected from Manila Bay in the Philippines atthe site indicated by the red circle in Fig. 2. Other
samples were collected from the ports of Funabashi
and Hidaka at the sites indicated by the red circles in
Figs. 3 and 4, respectively.

Manila Bay
in Philippines

Experimental Procedure

Hidaka Portin Wakayama

Sedimentary sludge was collected by using thesediment sampler, shown in Fig. 5. The collected
samples were then placed into the tanks (Fig. 6). The
time that the fine-bubble generator was started wasused as the start time for sample measurements. After
6 hours of generating fine-bubbles, a microbialactivator was added, which consisted of kelp withsome nutrients and enzymes; it was in liquid form.
The amount of microbial activator added was 100
mg/L. The water quality was assessed by taking
measurements of the water temperature, chemical
oxygen demand (COD), and concentrations of
dissolved oxygen (DO), ammonia nitrogen (NH4-N),
nitrite nitrogen (NO2-N), nitrate nitrogen (NO3-N),and total nitrogen (T-N). Measurements wereconducted after 24, 48, 60, and 72 hours from the start
time, i.e., the time that the micro-bubble generator
was started. Dissolved oxygen and water temperature
were measured with a multi-parameter water quality
meter (portable fluorescent dissolved oxygen meter).
Ammonia nitrogen, nitrite nitrogen, nitrite nitrogen,and total nitrogen concentrations were measured byusing a Digital Pack Test (Kyoritsu Chemical-Check
Lab, Corp.). Additional specifications of theexperimental devices are given in Table 1.

Fig 2. Locations of the study sites in Manila Bay,
Philippines, and Funabashi and Hidaka, JapanTokyo

Yokohama

Fig.3 Sampling Point at Funabashi Port in Japan

Osaka

Wakayama

Hidaka-Port

Fig.4 Sampling Point at Hidaka Port in Japan
Fig. 6 Photograph of the Actual Experiment
Table 1 Specifications of the Experimental Devices
Water = 25 L, Sludge= 0.1875 kg
Size of Water Tank = 200x270x370 mm
Flow Rate for Fine Bubble Generator = 43 L/min
Flow Rate for Circulation Water Pump = 10 L/min

Fig. 5 Sediment Sampler

Microbial Activator = 100 mg/L

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SEE - Nagoya, Japan, Nov.12-14, 2018

EXPERIMENTAL RESULTS
Water Temperature and Dissolved Oxygen
The measured water temperature and dissolved
oxygen results are shown in Fig. 7. The watertemperature stabilized at 30 degrees C, and the DOstabilized at around 7.5 mg/L. The stable watertemperatures and DO concentrations were desirable
because this facilitated proper interpretation of theresults for the other parameters that were measured.
The above data also demonstrate that aerobic
conditions were present in the experiments.

Fig.7 Changes in Water Temperature and Dissolved
Oxygen (DO)Dissolved Inorganic Nitrogen, Total Nitrogen andChemical Oxygen Demand
The level of dissolved inorganic nitrogen (DIN)
represents the total amount of ammonia nitrogen(NH4-N), nitrite nitrogen (NO2-N), and nitrate
nitrogen (NO3-N). Figure 8 shows the results for the
DIN. The DIN concentrations abruptly decreased
within 24 hours and thereafter remained at almost
undetectable levels for the 48 hour and 72 hour time
points. These data indicate that denitrifying bacteria
were present in the system.
The T-N results are shown in Fig. 9. The T-Nconcentrations first decreased and then slightly
increased by about 20% within the first 48 hours.
However, after 72 hours, T-N was not detected in thesystem, which implies that the purification system
performed well. The temporary increase of T-N
between 24 hours and 48 hours may have been due todelayed effects from the addition of the microbialactivator.
The results for the COD are shown in Fig. 10. The
COD remained constant at 20 mg/L for 24 hours andthen increased to 25 mg/L at 48 hours possibly
because of the microbial activator. Then, the COD
returned to 20 mg/L at 72 hours. These results
confirm the efficiency of the system.

Fig.8 Changes in Dissolved Inorganic Nitrogen(DIN)

Fig.9 Changes in Total Nitrogen (T-N)

Comparison of the Purification Results for Total
Nitrogen in Manila Bay Samples with Those fromthe Ports of Funabashi and Hidaka in Japan
Figure 11 shows the results for the T-Nconcentrations versus time for the three experiments
conducted with sludge from three places, namely,
Manila Bay and the ports of Funabashi and Hidaka.
The T-N concentrations decreased dramatically in all
three experiments. The T-N concentrations reachedundetectable levels within 72 hours for the samples
from Manila Bay and Hidaka, whereas the T-Nconcentrations only reached undetectable levels after
120 hours for the samples from Funabashi. According
to these results, the purification system of thecirculation type showed good purification
performance.

Fig.10 Changes in the Chemical Oxygen Demand
(COD)

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SEE - Nagoya, Japan, Nov.12-14, 2018

T-N (normalized) ((mg/L)/(mg/L))

The following six species of bacteria were identified
from sludge at 0 and 24 h: Rhodococcus sp., Bacillus
sp., Exiguobacterium sp., Serratia sp., Pseudomonassp., and Marinobacter sp. (Table 3).
We
concludedthat
Rhodococcus
sp.,
Exiguobacterium sp., and Marinobacter sp. wereuniquely valuable for breaking down the sludge.
Previous studies have shown that Rhodococcus sp.
have the ability to participate in fossil fuelbiodesulfurization reactions, and Exiguobacterium sp.
have been detected in unique environments withtemperatures ranging from -12 to 55 degrees C [8].
Marinobacter sp. can degrade hydrocarbons, as
discussed in [9].
Table 3 Sequence Analysis Results for the Six
Isolated Stains

Fig. 11 Comparison of the Total Nitrogen (T-N)
Results for Manila Bay Samples with Those from thePorts of Funabashi and Hidaka

Comparison of the Purification Results for
Elemental Compositions in Manila Bay Samples
with Those for Funabashi and Hidaka Port inJapan
Figure 12 shows comparisons of the EDX (Energy
Dispersion type X-ray analysis device) results forsamples from Manila Bay and the ports of Hidaka andFunabashi.
Compared with the beginning and the end of theexperiments, S (sulfur) decreased in each treatment.
Interestingly, Na (sodium) increased by a small
amount only at Funabashi. The other components
showed similar tendencies. The largest decrease in Si(silica) occurred in the Funabashi samples.
100%

P, 0.6

P, 0.4P, 0.2

P, 0.9P, 1.2

Ca, 14.2

Ca, 14.2

Ca, 1.0

Ca, 1.0

Ca, 2.3

Ca, 2.3

Na, 5.5

Na, 2.4

Na, 2.7

Na, 5.0Na, 8.2

S, 5.2S, 3.3Fe, 9.0

Fe, 10.9

S, 1.6S, 0.9Fe, 10.1

Fe, 9.9

Al, 17.4

Al, 17.8

Si, 50.5

Si, 51.6

Manila Bay 0h

Manila Bay 72h

Al, 20.8

S, 2.4

Al, 21.7

S, 1.5
Fe, 6.0

Fe, 5.7

Al, 20.7

Al, 23.6

50%

Si, 67.1

0%

Hidaka Port 0h

Si, 66.4

Hidaka Port 120h

Si, 56.9

Funabashi Port 0h

Length (bp)% similarity

1

1624

98 % Rhodococcus sp.

2

1005

95 % Bacillus sp.

3

1075

92 % Exiguobacterium sp.

4593

93 % Serratia sp.

5453

79 % Pseudomonas sp.

6

1509

97 % Marinobacter sp.

CONCLUSION

Na, 5.8

P, 0.7

Strain No.

Si, 50.5

Funabashi Port 120hFig. 12 Results from the EDX (Energy Dispersion
Type X-ray Analysis Device) for Manila Bay and thePorts of Hidaka and Funabashi

Experiments were carried out to assess theperformance of a circulation type purification system
during the degradation of sludge samples from
Manila Bay in the Philippines and the ports ofFunabashi and Hidaka in Japan. According to theresults for several measured parameters, namely,
water temperature, dissolved oxygen, dissolved
inorganic nitrogen (DIN), total nitrogen (TN), andchemical oxygen demand (COD), the performance ofthe purification system was very good. In particular,
DIN and TN concentrations decreased markedly
during the treatments within a short period of time,
which were reflective of improvements in the water
quality of the samples. Six species of bacteria wereisolated from the sludge from Manila Bay.
Pseudomonas sp. was identified as the same bacteria
found in [7].

Microbial Analyses

ACKNOWLEDGEMENTS

Microbial analyses were performed to identify theuseful bacteria in the fine-bubble treatment of Manila
Bay sludge. Bacteria were isolated from the sludge
experiments and identified by 16S rRNA genesequence analyses according to methods described inearlier work [7].

The authors would like to express sincere thanks
to Mr. Nogawa, Daisuke, a graduate student, Mr.
Tateishi, Shotaro, a student of Nihon University, andProf. Reynaldo, Baarde, Head of the Construction
Engineering and Management Department of TUP

1024

SEE - Nagoya, Japan, Nov.12-14, 2018[5] Matsuo, K., Maeda, K., Ohnari, H., Tsunami, Y.,
and Ohnari, H., Water Purification of a Dam
Lake Using Micro Bubble Technology, Progressin Multiphase Flow Research, Vol. 1, 2006, pp.
279–286.
[6] Okamoto, K., Hotta, K., Toyama, T., and Kohno,
H., Purification System of Ocean Sludge by
Activating
Microorganisms,
International
Journalof
GEOMATE(Geotechnique,
Construction Materials and Environment), Vol. 6,
No. 1, 2014, pp. 791–795.
[7] Komoriya, T., Okamoto, K., and Toyama, T.,
Effect of Adding of Bacteria on the Removal ofRadioactive Cesium from Ocean Sludge in a
Circulation
Type
Purification
System,International
Journalof
GEOMATE(Geotechnique, Construction Materials andEnvironment), Vol. 12, 2017, pp. 121–126.
[8] Vishnivetskaya, T.A., Kathariou, S., and Tiedje,
J.M., The Exiguobacterium Genus: Biodiversity
and Biogeography, Extremophiles, Vol. 13, 2009,
pp. 514–555.
[9] Brito, E.M.S., Guyoneaud, R., Goñi-Urriza, M.,
Ranchou-Peyruse, A., Verbaere, A., Crapez,
M.A.C., Wasserman, J.C.A., and Duran, R.,
CharacterizationofHydrocarbonoclastic
Bacterial Communities from Mangrove
Sediments in Guanabara Bay, Brazil, Research in
Microbiology, Vol. 157, 2006, pp. 752–762.

for executing the experiments; we are also grateful to
Ogawa, Ma.Richie C., staff of Nihon University, forassistance with writing the paper.
This work was supported by a KAKENHI Grantin-Aid for Scientific Research (C-17K06969).
REFERENCES[1] Okamoto, K., Komoriya, T., and Toyama, T.,
Comparison of Purification Performance against
Ocean Sludge in Two Sea-Area by Using
Purification System of Circulation Type,
Proceedings of the 6th International Conferenceon Civil Engineering, 2017.
[2] Okamoto, K., and Hotta, K., Purification
Experiments on Sedimentary Sludge byMicroorganism Activation, Recent Advances inMarine Science and Technology 2010 – PACON
International, 2010, pp. 151–166.
[3] Okamoto, K., Hotta, K., Toyama, T., and Kohno,
H., Experiments on Purification of Ocean Sludge
by Activating Microorganisms, The International
Offshore (Ocean) and Polar Engineering
Conference, 2011.
[4] Jacinto, G.S., Azanza, R.V., Velasquez, I.B., andSiringan, F.P., Manila Bay: Environmental
Challenges and Opportunities, In Wolanski, E.
(Ed.), The Environment in Asia Pacific Harbors,
2006, Springer, pp. 309–328.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ESTIMATION OF GROUNDWATER RECHARGE AND
SALINIZATION IN A COASTAL ALLUVIAL PLAIN AND OSAKAMEGACITY, JAPAN, USING δ18O, δD, AND Cl−
1Yusuke Tomozawa1, Shin-ichi Onodera1, Mitsuyo Saito2
Graduate School of Integrated Arts and Sciences, Hiroshima University;
2
Graduate School of Environmental and Life Science, Okayama University

ABSTRACTSeawater intrusion and salinization are the most common problems of water pollution in coastal groundwater.
To clarify the process of groundwater salinization in a coastal alluvial plain, we estimated the groundwater
recharge and salinization process in Osaka coastal groundwater using δ 18O, δD, and Cl−. Water samples werecollected at 14 boreholes of 9 plots with depth of −5 to −60 m amsl in March 2015. The δ18O values and Cl−
concentrations of the groundwater varied spatially from −6.4 ‰ to −4.7 ‰ and 17 mg/L to 5193 mg/L,
respectively. Based on Cl− concentrations, the maximum mixing ratio of seawater with the concentration of 1800
mg/L into groundwater was estimated to be 29% about 3 km inland from the shoreline at the depth of about −40
m. The relationship between δ18O and Cl− of groundwater and seawater indicated three types of end members:
seawater with high Cl− and δ18O, a groundwater source with lower Cl− and lower δ18O (−5.6 ‰), and a groundwater
source with lower Cl− and the lowest δ18O (−7.2 ‰). According to the relationship between the altitude ofgroundwater recharge and δ18O established by previous research, two types of groundwater recharge and sourceareas were estimated to be coastal lowland and upland with altitudes <10 m amsl and surrounding hill 18 km inlandfrom the shoreline with altitudes of 100 m amsl.
Keywords: Coastal groundwater, Stable isotope, Chloride, Seawater intrusion

1. INTRODUCTION
The resource value of groundwater has beenrecognized again in recent years and consideredwidely, such as for water use in an emergency andheat for renewable energy. Within the Big Movementin Japan, the "Basic Law on the Water Cycle" wasestablished in March 2014. It requires efforts tounderstand water circulation throughout the basins ofJapan, including the groundwater recharge zone.
For the use of groundwater as a sustainable water
resource, water quality is important from theviewpoint of safety, and it is necessary to maintainand manage water quality [1-3].
Seawater intrusion is the most common water
quality problem for coastal groundwater. The main
factors of seawater intrusion are disturbance of thewater balance in an aquifer caused by excess pumping(a human factor) and influences such as topography,
geology, sediment, etc. (natural factors). It is
important to understand the degree of influence ofeach of these factors to manage seawater intrusion.
Since 1940, ground settlement has been a problem
in the Osaka Plain because seawater intrusion has
occurred correspondingly. However, groundwater
intake restrictions have been strengthened to recover
the groundwater level, so the level has been almost
stable in recent years. Although several studies
concerning water quality [4-11] have been conducted,
this research was not sufficient to elucidate in detailFig. 1 Study area
the groundwater recharge/flow in the entire Osaka
Plain. Therefore, the aims of this study were to1026

SEE - Nagoya, Japan, Nov.12-14, 2018

2. STUDY AREA AND METHOD

Fig. 2 Topography / Geology（Modified after KG-NET, Kansai Area Ground Work
Meeting (2007) [13] ）Osaka St.
Fukanominami
Osaka bay
Shin-Osaka

Alluvium(aquifer)

Ma13(aquiclude)

Tg1(aquifer)

Ma12(aquiclude)

Topsoilclay

GravelSee cell

Sand
Fresh water
cell

Silt
Mismatc

Number = 14Cage B.P. O.P.±0m=Tokyo pell -1.30m

Fig. 3 Geologic columnar section（modified after Ichihara et al. [12] ）confirm the situation of seawater intrusion into thecoastal groundwater and estimate the recharge
process of the water by measuring the concentrationsof chloride ion (Cl−) and stable hydrogen and oxygenisotopes as well as analyzing the isotopic ratios (δ18O,
δD) and comparing them with the existing values in
the literature.

The research was conducted in the Osaka Plain.
The locations of observation wells are shown in Fig.
1, and the geological features of the region are shownin Fig. 2 and Fig. 3 [12][13].
The flat area is covered with alluvial deposits.
The geological column from soil surface can besummarized as (example from Osaka Bay) top soil (a),sand (b), silt (c), clay (d), sand and mixed silt (e), silt(f), sand (g), and gravel (h). Aquifers are assumed to
be located in sand layer (b), gravel layer (h), alluvium,
the 1st Hongan laminated gravel layer (Tg1), and the
2nd volcanic gravel layer (Tg2) near the deeper G.L60m aquiclude (Ma13–Ma11), which is locatedbetween each aquifer [9][14].
Nine observation wells on the coast of Osaka Bay
were the target of our research. Five observation wells(N1 to N5) were under the jurisdiction of the
Research Council of Groundwater Environment. Two
observation wells (S3 and S4) were under thejurisdiction of the Ministry of Land, Infrastructure
and Transport, and the other two wells (S1 and S2)
were under the authority of Osaka Prefecture (Fig. 1).
The assumed aquifer and depth (G.L-m) of eachobservation well follow:
 Alluvium: S1/6.70 m, S3/10.50 m, S4/10.20 m, N3AS/22.00 m.
 The 1st Hongu laminated gravel layer (Tg1):
S2/25.00 m, N1-Tg1/37.50 m, N2-Tg1/31.60 m,
N3-Tg1/40.50 m, N4-Tg1/40.20 m, N5-Tg1/ 39.30
m.
 The 2nd Huang layered gravel layer (Tg2): N1Tg2/56.25 m, N2-Tg2/56.80 m, N4-Tg2/61.70 m,
N5-Tg2/59.75 m
The strainer length of N1 to N5 is 4.0 m, and thoseof S1 to S4 are 3.7 m, 3.0 m, 7.6 m, and 8.0 m,
respectively. The groundwater level measurement
and sample collection were carried out in March 2015.
The observation wells were drained before sampling.
The electrical conductivity, pH, and dissolved oxygen
concentration of the sample water were measured onsite. Cl− concentration and stable hydrogen andoxygen isotopes were analyzed in the laboratory. The
Cl− concentration was analyzed by ion
chromatography (Shimadzu Corporation, CL-VP),
and the stable isotope ratios (δD, δ18O) were
calculated with the WS-CRDS method (PicarroCompany, L2120-i).

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 4 δ diagram（× refers to analysis values by Nakaya et al. [14],the same below）
3. SITUATION OF SEAWATER INTRUSION
Fig. 4 shows a δ diagram with data of thegroundwater and the meteoric water line (δD = 8δ18O+ 10) around the Osaka Plain by Nakaya et al. [14]for comparison. The data plotted along the meteoric
water line with a slope of roughly 8, indicating thatthe water was derived from rainwater. Some dataplotted near the mixing line of modern sea water (δD:0‰, δ18O: 0.0‰) and the lower limit of groundwater.
It is suggested that the mixing of groundwater and sea
water shifted isotopic values to heavier ones.
Fig. 5 and Fig. 6 show the correlation between
δ18O and Cl−. The concentrations of Cl− at N5-Tg1
and N4-Tg1 were 5193 mg/L and 4813 mg/L,
respectively. These concentrations were particularly
high, indicating saltification. Given the values ofmodern seawater of δ18O: 0.0 ‰, Cl−: 18000 mg/L,
seawater intrusion occurs when the mixing ratio of
sea water is 0.1 to 28.9 %. At the other points, Cl−concentration was 500 to 1000 mg/L, which
confirmed the occurrence of seawater intrusion.
Intrusion of seawater is stronger in the Yodo River
Basin (N1–N5, S4) than in the Yamato River Basin(S1–S3).
The intersection of the vertical line with the highmixing line and the low mixing line was −7.2 to−5.6 ‰ (Fig. 5). These values were included in the
freshwater side data. We assume that groundwaterand modern seawater are mixed in the aquifer.
4. δ18O AND Cl− DISTRIBUTION
CHARACTERISTICS IN CROSS SECTION
AA'
Fig. 7 shows the distribution of (a) Cl– and (b)Fig. 5

δ18O–Cl−

Fig. 6 δ18O–Cl−（Inside the dotted rectangle in Fig. 5)
δ18O at cross section AA'. N5-Tg1 and N4-Tg1 occur
in the vicinity of about −40 m at the center in the
figure and have especially high seawater intrusion.
The cross-sectional distribution of Cl− shows that
N4-Tg1 and N5-Tg1 have high concentrations of Cl−.
Wells N4 and N5 have low groundwater level, andgroundwater samples were collected from thesurroundings. We assume that seawater intrusion had
already occurred at the sampling period. The Tg2
layer has moderate depth compared to the Tg1 layer.
The upper layers of S4 and N3-AS show acontrasting condition with N5-Tg1 and N4-Tg1. The
Cl− concentrations are low and there is fresh water on
top of salt water.
The distributions of δ18O show heavy values(−4.8 ‰, −5.1 ‰) at the points where Cl−
concentrations are high (N4-Tg1, N5-Tg1). Other
points have values ranging from −5.4 ‰ to −6.4 ‰1028

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 7 Distribution of (a) Cl− and (b) δ18O in cross section A–A' in Fig. 1

and show an ambiguous distribution feature.
Therefore, each value is considered to be a value
generated by mixing with modern seawater.
Freshwater δ18O before mixing corresponds to theintersection of the mixing line (the line connecting theplot of each value and the plot of the value of modern
seawater) in Figs. 5 and 6 with the ordinate. Also, themixing ratio of sea water was calculated with the Cl−
concentration of modern seawater as 100%. As aresult, the δ18O of fresh water before mixing with theheaviest point (N5-Tg1) was −7.2 ‰, and the salt
water mixing ratio was 29%.
In addition, the rought altitude of the study of
Nakaya et al. [14] was obtained from the δ18O resultsof surface water in the recharge zone of the Osaka
Plain groundwater. The altitude effect characteristic
is a decrease of the δ18O of precipitation from low-

altitude areas to high-altitude areas. This feature canbe used to obtain the groundwater recharge elevation.
In the Osaka Plain, a δ18O of water value of −7.2 ‰corresponds to water recharged at 100 m altitude. The
light water is considered to be recharged in themountainous area, while the heavy water is presumed
to be recharged on the hill/plateau area at less than
100 m elevation.
The calculation result for δ18O at N5-Tg1 and N3Tg1 was −7.2 ‰. These points are located in the 1st
volcanic gravel layer. This location can be inferred as
representing water recharged in the mountainous
areas. Shallow groundwater on the sea side of point
N5 cannot reach light water from the mountains andis considered to be heavy water (δ18O: −7.1 ‰ ormore) recharged on the plateaus and flat ground.
Particularly, there was some heavy water at N31029

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 8 Distribution of freshwater δ18O before mixing in cross section A–A' in Fig. 1
AS (−5.7 ‰) and N4-Tg2 (−5.6 ‰). These locations
have a different type of aquifer. The water recharged
at the 0 m altitude area estimated from the altitude
effect is δ18O: −6.9 ‰. Thus, these heavy waters
cannot be explained by the altitude effect. One
possible reason for the heavy water is thatprecipitation accumulates in reservoirs, rice fields,
waterways, etc., evaporates, and isotopic
fractionation occurs. Other unknown factors such as
contamination of sewer water into groundwater,
influences from underground structures, and someothers are also conceivable. However, data explaining
these waters are currently lacking.
Discussion of the constant altitude effect used inthis case is necessary. For example, δ18O of
precipitation is known to change seasonally [15], andthere is the possibility that one-time sampling is not
sufficient.
Even if heavy water factors are revealed, theprocess of heavy water invading each aquifer is still
difficult to explain. Therefore, various approaches
using other tracers are considerably necessary.

with altitudes of 100 m or more, (ii) recharge in hilly
areas and plateaus with altitudes less than 100, and(iii) modern seawater.
However, some heavy water cannot be explainedby the altitude effect. Therefore, it is necessary to
clarify the factors causing the generation of this water.
The restoration process from seawater intrusion may
be captured in the future by sampling water regularly.
6. ACKNOWLEDGEMENTS
This research was partially supported by the
Research Council on the Groundwater Ground
Environment FY2008. We thank the Kinki Regional
Development
Bureau,MinistryofLand,
Infrastructure and Transport, Osaka Prefectural
Environmental Agriculture, Forestry and Fisheries
Department, and Osaka City Environment Bureau for
their cooperation during this investigation. We also
thank our colleagues Ms. Hiroko Ito and Mr. Yutaka
Maruyama (former graduate student of Hiroshima
University) from the Geo-Research Institute for theirgreat help in collecting the samples.

5. CONCLUSIONREFERENCES
In this study, Cl− concentration was measured to
trace seawater intrusion, and δ18O and δD were
measured to estimate the water recharge process.
The results showed that seawater intrusion with amaximum mixing rate of seawater of 29 % was
confirmed in groundwater collected in 2015. The
groundwater is considered to be derived fromprecipitation.
We suggested that the groundwater is formed
from three sources: (i) recharge in mountainous areas[1] Masuda H., The Future of Urban Water Resourcesand Groundwater, Kyoto University Academic Press,
2010, p 249.
[2] Taniguchi M., Importance of groundwater as security,
Journal of Groundwater Hydrogy, Vol. 55, 2013, pp
5-11.
[3] Taniguchi M., Asia's Underground Environment–
Remaining Global Environmental Issues, Gakuhosha,
2010.
[4] Tsurumaki M., Summary of groundwater quality

1030

SEE - Nagoya, Japan, Nov.12-14, 2018

water research committee activities, Symposium on
groundwater ground environment 2003 released
papers, 2003, pp 81-90.
[5] Tsukamoto T. and Tsurumaki M., About abnormal
water quality, found in "Chronology of groundwater
quality water quality", Symposium on groundwater
ground environment 2003 released papers, 2003, pp
99-106.
[6] Aoki K., Tsurumaki M. and Nishida M., Salt water
phenomenon in southern part of Sennan area andoptimum water volume, Symposium on groundwater
ground environment 2003 released papers, 2003, pp
91-98.
[7] Tsukamoto T., Characteristics of water quality ofgroundwater observation well in Osaka area,
Symposium on groundwater ground environment
2010 released papers, 2010, pp 87-94.
[8] Onodera S., Shimizu Y., Ito H., Tsukamoto T., Oki T.
and Aoki K., Influence of nitrogen changes on Osaka
Plain and its groundwater quality, Kansai GeoSymposium 2013 Paper Collection, 2013, pp 27-30.
[9] Ito H., Onodera S., Saito M., Maruyama Y., Jin K.
and Katsumi T., About the inclusion status of heavy
metals etc. in groundwater in Osaka plain and its
surrounding area, Kansai Geo-Symposium 2015
Paper collection, 2015, pp 91-96.
[10] Saito M., Onodera S., Ito H., Maruyama Y.,
Taniguchi M., Jin K. and Katsumi T., On theinteraction between groundwater and sewerage along

the coast of Osaka Bay–Looking at nutrient salts,
Kansai Geo-Symposium 2015 Paper Collection,
2015, pp 87-90.
[11] Onodera S., Saito M. and Shimizu Y., On thetendency of water quality contamination ofgroundwater in coastal giant cities, Kansai GeoSymposium 2016 Paper Collection, 2016, pp 3-4.
[12] Ichihara M., Fujino Y., Mori K., Nakakose K.,
Kusaka M. and Murota A., Osaka Group and Osaka
Plain, URBAN KUBOTA, NO.16, 1975, pp 2-11.
[13] KG-NET and Kansai Gio-informatics ResearchCommittee, Osaka Bay from Osaka Plain of ShinKansai Earthquake, KG-NET and Kansai Gioinformatics Research Committee, 2007, p 354.
[14] Nakaya S., Mitamura M., Masuda H., Uesugi K.,
Motodatge Y., Kusakabe M., Iida T., and Muraoka K.,
Recharge sources and flow system of groundwatersin Osaka Basin, estimated from environmental
isotopes and water chemistry, Journal of
Groundwater Hydrogy, Vol. 51-1, 2009, pp 15-41,[15] Tanoue M., Ichiyanagi K. and Shimada J., Seasonalvariation and spatial distribution of stable isotopes inprecipitation over Japan, Journal of Japanese
Association of Hydrological Sciences, Vol. 43-3,
2013, pp 73-91.

1031

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov. 12-14, 2018, ISBN: 978-4-909106018 C3051

ANALYSIS OF STATISTICAL METHODS FOR WATER-LEVELFORECASTS OF NIGER INNER DELTA IN MALI
*Barry Kassambara1, Homayoon Ganji1 and Takamitsu Kajisa1
1

Graduate School of Bioresources, Mie University, Japan
ABSTRACTThe Niger Inner Delta (NID), a wetland that was selected as an International Important Wetland under theRamsar Convention (on February 1st, 2004) still can be considered a hotspot of biodiversity in the Sahel. The
Niger River as the main source of water for the NID is also used for urban life and irrigation. Therefore, thesustainable use of water to ensure the environmental flow in the NID is under discussion. In this paper, we evaluate
the performance of different models established with empirical (Artificial Neural Network and Regressions) or
Conceptual Variable Source Area (Water Balance Method WBM) approaches. The result of evaluation andvalidation based on determination coefficient (R2), Root Mean Squared Error (RMSE) and Nash-Sutcliffe
Efficiency (NSE) show that all the models have good results however the Levenberg Marquardt Artificial Neural
Network has the best fitting for validation and testing periods.

Key words: Niger Inner Delta, water-level, wetland, simulation model
INTRODUCTION

Statistical/stochastic and Conceptual/Physical models

For many decades, water shortage has been a direfor Niger Inner Delta water level forecasting and makeproblem for millions of people living along the

a comparison between these different models. The

southern fringe of the Sahara Desert [1]evaluation and forecasting of water-level fluctuation

The Niger river has its source in the Fouta Djallon(WLF) is increasingly important for the NID owing to

Mountains in the South of Guinea (West Africa), it

its close relation to human living and production, andflows northeast through the Upper Niger basin andsocio-economically and environmentally sustainable

enters the Niger Inland Delta (NID) in Mali with adevelopment.

large floodplain ranging from 30,000 to 40,000 km2
along the Niger River in Mali [2] (See Fig 1).TheSTUDY AREA AND DATA SOURCES

annual flooding of large alluvial plains is a vital
resource for many ecosystem services, including

Beyond the town of Ségou, the Niger River forms

agriculture, livestock, groundwater recharge, anda vast inland delta with an area of 41,800 km² (Fig. 1&

biodiversity (see Fig 2). The rapid expansion of2); it joins with its main tributary, the Bani, at Mopti

irrigation upstream, by the diversion dams on theand then forms several lakes. The watershed area of

Niger river and its subsidiary (Bani), have athis Inner Delta covers 130,000 km² [3]. The NID issignificant impact on the Water-Level (WL) in theextremely flat and contains many lakes and streams of

NID downstream [3].

varying morphology. The altitude of the river bed

The main objective of this study is to develop

decreases by only approximately 10 m over the 350

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SEE - Nagoya, Japan, Nov.12-14, 2018

km between the entry and exit of the delta [4]. For thisAkka are from the Malian Government Hydraulicstudy the data are from different sources (Table 1):

Service, the meteorological data are from Mali-Meteo

The Niger river flow at Mopti and the Water Level at& Atmospheric Science Data Center (NASA)

Table 1: Data type and data sources
Station

Mopti Station

3

4

Date

Malian Government Hydraulic Service

1
2

SourceMalian Meteorological Service
Atmospheric Science Data Center (NASA)

Akka Station

Malian Government Hydraulic Service

Fig. 1 The Niger Inner Delta in MaliMETHODS

Data Type
Water flow

1960-2015

No

RainfallTemperature, wind velocity,
Solar Insolation
NID Water-Level

Fig. 2 NID during dry season (Source Google)

Artificial Neural Network (ANN)The most common methods for river flow and WL
forecasting are physical, conceptual and/or statisticalrainfall-rainoff methods [5], [4], [6]. In recent years
Artificial Intelligence (AI) as a modern approach fordata series analysis has received a great deal ofattention for hydrology modeling, including Artificial
Neural Network (ANN), and Adaptive Neuro-Fuzzy
Inference System (ANFIS) [5], [7], [8], [9], [10], [11],[12], [13],. For our study we have implemented six(06) different models based on empirical andstochastic approaches.

An artificial neural network (ANN) is a non-linear
black box statistical/stochastic approach [11]; themain objective is to find the optimum architecture ofan ANN that can model the relationship between input
and output variables. In this study we use the Matlab
Neural Network tool to train the different models. For
each of the following ANN algorithms, the monthly
rainfall, evapotranspiration and the river discharge at
Mopti station were designated as predictors and thewater level at Akka station as the predictant.

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SEE - Nagoya, Japan, Nov.12-14, 2018

The most commonly used ANN structure is thetraining aims to reduce the sum of squared errors 𝐸𝐷

feed-forward multilayer perceptron (MLP). It is aand the regularization adds an additional term 𝐸𝑊

network formed by simple neurons called perceptron.

[17]. The objective term becomes 𝐹 = 𝛽𝐸𝐷 + 𝛼𝐸𝑤

The perceptron computes a single output from(3)

multiple real-valued inputs by forming combinations

whereof linear relationships according to input weights andparameters.

𝛽

and

𝛼

are the objective function

even nonlinear transfer functions [5].
Mathematically, the MLP can be express as:

Scaled Conjugate Gradient Algorithm

𝒚 = 𝒇( ∑𝒏𝒊=𝟏 𝒘𝒊 𝒑𝒊 + 𝒃)
(1)

The Scaled Conjugate Gradient (SCG) method, as

Previous studies indicated that the Levenberg-

most of the feedforward neural networks, is based on

Marquardt algorithm produces reasonable results forthe gradient descent algorithm well known inmost ANN applications [14], [5]. For the present study

optimization theory [18]. The SCG avoids the line

we considered the three algorithms available insearch per learning iteration by using a LM approach

Matlab:in order to scale the step size.

Levenberg-Marquardt(LM),

Bayesian

Regularization (BR) and Scaled Conjugate Gradient(SCG) algorithms.

Gaussian Process Regression (GPR) Model with
Matlab Regression Learner

Levenberg-Marquardt Algorithm
Gaussian process regression (GPR) models are
Levenberg-Marquardt (LM) is the most popular

kermel-based probabilistic models [19].

alternative to Gauss-Newton method for finding the

A linear regression model is of the form:

minimum of the function 𝑭(𝒙) that is a sum of:1[𝑓 (𝑥)]2
𝐹(𝑥) = ∑𝑚
2 𝑖=1 𝑖[15]

(2)

Let the Jacobian of 𝑓𝑖 (𝑥) be denoted 𝐽𝑖 (𝑥), thenthe LM method searches in the direction given by thesolution 𝑝 of the equation (𝐽𝑘 𝑇 𝐽𝑘 + λ𝑘 𝐼)𝑝𝑘 =−𝐽𝑘 𝑇 𝑓𝑘𝒚 = 𝒙𝑻 𝜷 + 𝜺(2)Where λ𝑘 are nonnegative scalars and 𝐼 is theidentity matrix.

Bayesian Regularization Algorithm( 4)
Where ε~𝑁(0, 𝜎 2 ) . The error variance 𝜎 2 and thecoefficient β are estimated from the data. A GPR
model explains the response by introducing the latentvariable, 𝑓(𝑥𝑖 ), 𝑖 = 1,2, … 𝑛 , from a GaussianProcess (GP), and explicit basis functions, hWater Balance Model (WBM)

The water depth in the NID may be obtained using

This algorithm uses David MacKay’s Bayesian
techniques to optimize regularization which requires
the computation of the Hessian matrix [16]. Typically,

the Variable Source Area (VSA) model as follows:
𝑯𝒊+𝟏 = 𝑴𝒂𝒙(𝑯𝒊 + (𝑸𝒊+𝟏 − 𝑸𝒐𝒖𝒕 )

1034

𝑫
𝑨𝟏

+ (𝑹𝒊+𝟏 −SEE - Nagoya, Japan, Nov.12-14, 2018

𝑬𝑻𝟎 𝒊+𝟏 𝑫)(𝑨𝟏 +𝑨𝟐 )𝑨𝟏estimate the monthly maximum water level of the NID,𝜸 )will be as:

(5)
The

outflow

𝑯𝒎𝒂𝒙 = 𝜷𝟎 + 𝜷𝟏 𝑬𝑻𝟎 + 𝜷𝟐 𝑹𝒂𝒊𝒏 + 𝜷𝟑 𝑸𝒎𝒂𝒙
𝑄𝑜𝑢𝑡

is

𝑄𝑜𝑢𝑡 = 𝛽𝑀𝑎𝑥(𝐻𝑖 , 0)𝛼

(9)

(6)
The wet soil area is given as

𝐴2 = 𝛿√𝐴1

RESULTS
The monthly data from 1960 to 2010 were used

(7)
Time, monthly maximum inflow from Mopti

for the model validations, and the monthly data fromstation upstream (𝑄𝑖 ), monthly rainfall (𝑅) the daily

2011 to 2015 for testing. To validate and evaluate thepotential Evapotranspiration (𝐸𝑇0 ), the number day ofmodels, Correlation Coefficient (CC), squared R (R2),each month (𝐷 ), and pond water surface (𝐴1 ) data

Root Mean Squared Error (RMSE) and Nash-Sutcliffe

were fed into the spreadsheet. To estimate theEfficiency (NSE) were used (Table 2). The plots of the

maximum water level (𝐻𝑖 ) at various time steps using

monthly maximum WL (Hmax) variation for different

the equation 6 based on the parameters 𝛼, 𝛽, 𝛾 andmodels are shown in Fig 3.
The Nash-Sutcliffe Efficiency (NSE) is a

𝛿 . The Generalized Reduced Gradient (GRG)

normalized statistic that determines the relative

nonlinear solving method was used.

Multiple Linear Regression (MLR)

magnitudeof thecompared

with

the

residual variancemeasureddata(“noise”)
variance(“information”). The NSE indicates how well the plots
As opposed to simple linear regression models,
which describe the linear functional relationshipof observed versus simulated data fit [21].
The NSE is computed as shown below:
𝟐

between a single explanatory variable 𝑋 (inflow,
Rainfall, 𝐸𝑇0 ) and the response variable 𝑌 (NID

𝒐𝒃𝒔
𝒔𝒊𝒎
∑𝒏
𝒊=𝟏(𝒀𝒊 −𝒀𝒊 )𝑵𝑺𝑬 = 𝟏 − [ 𝒏𝒎𝒆𝒂𝒏 )∑𝒊=𝟏(𝒀𝒐𝒃𝒔𝒊 −𝒀variables for describing the behavior of 𝑌 [20]. In
formal terms 𝑦 = 𝛽0 + ∑𝑘𝑗=1 𝛽𝑗 𝑥𝑖𝑗(8)Parameter estimation in multiple linear regression is

]

(10)

Water-Level), multiple linear regression models
comprise the use of a collection of explanatory

𝟐

Where 𝑌𝑖𝑜𝑏𝑠 is the ith observation WL, 𝑌𝑖𝑠𝑖𝑚 is the ith
simulated value of WL, 𝑌 𝑚𝑒𝑎𝑛 is the mean ofobserved WL, and n is the total number ofobservations.

based on the least squares methods. The equation to1035

SEE - Nagoya, Japan, Nov.12-14, 2018(a)ANN LM(b)ANN BR

PeriodHmax_Obs(m)Hmax_LM(d)GPR Regression

PeriodHmax_Obs(m)Hmax_BR(e)WBM

1000
800
600
400
200
0

(f)MLR

1960
1964
1968
1972
1977
1981
1985
1989
1994
1998
2002
2006

1960
1964
1968
1972
1977
1981
1985
1989
1994
1998
2002
2006

1960
1964
1968
1972
1977
1981
1985
1989
1994
1998
2002
2006

Hmax

PeriodHmax_Obs(m)Hmax_SCG

Hmax

1000
800
600
400
200
0

Hmax

1000
800
600
400
200
0

1960
1964
1968
1972
1977
1981
1985
1989
1994
1998
2002
2006

1960
1964
1968
1972
1977
1981
1985
1989
1994
1998
2002
2006

1960
1964
1968
1972
1976
1980
1984
1988
1992
1996
2000
2004
2008

Hmax

PeriodHmax_Obs(m)(c)ANN SCG

1000
800
600
400
200
0

Hmax

1000
800
600
400
200
0

Hmax

1000
800
600
400
200
0

Hmax_GPR

PeriodHmax_Obs(m)Hmax_WBM

PeriodHmax_Obs(m)Hmax_RegFig. 3 Validation scatter plots of observed versus modelled water level. (a) Levenberg-Marquardt ANN, (b)Bayesian Regularization ANN (c) Scaled Conjugated ANN, (d) Gaussian Process Regression, (e) Water Balance
Model (WBM), (f) Multilinear Regression model.
Table 2: Model validation and Evaluation statistics
Validation (1960-2010)

N

Model

CC

R2

RMSE(cm)

Evaluation (2011-2015)

NSE

CC

R2

RMSE(cm)

Parameters
AlgorithmaHmax_LM

0.97

0.94

41.47

0.9477

0.97

0.95

38.36

Algorithmb

Hmax_BR

0.97

0.89

59.00

0.9450

0.97

0.95

38.20

AlgorithmcHmax_SCG

0.96

0.92

52.05

0.9141

0.96

0.92

46.99

AlgorithmdHmax_Mat_GPR

0.97

0.93

46.88

0.9141

0.97

0.95

37.51

Hmax_WBM

0.95

0.91

60.00

0.8415

0.96

0.93

39.88

e

α=1.29,β=228.73,δ
=59.19,γ=0.32
𝛽0 = 1070.2, 𝛽1

f

Hmax_MLR(exc
el

0.93

0.87

65.02

0.8532

0.96

0.92

46.68

= −156.65, 𝛽2= −1.14, 𝛽3= 0.12DISCUSSION

perform much better for each of the algorithms,
2

The models' performance from R , RMSE and NS

followed by Gaussian Process Regression; the Water

are given in table 2 and fig 4. It can be seen from theBalance Model and theresults of validation that the ANN (LM, BR and SCG)

Multilinear Regression Model have the worst

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SEE - Nagoya, Japan, Nov.12-14, 2018

performance. For all the models the NSE values of

however ANN Levenberg-Marquardt algorithm has

validation are close to 1, which is in the range ofthe best result for each performance index.

acceptable levels (between 0 and 1 where 1 is the
optimal value) according to Moriasi et al. [21],0Hmax_Cal(cm)Hmax_Cal(cm)Hmax_MatReg_GPR(cm)y = 0.9803x
R² = 0.9427

y = 0.9832x
R² = 0.9459

600
500
400
300
200
100
0

(a) Water Balance Model
600
500
400
300
200
100
0

100 200 300 400 500 600
Hmax_Obs(cm)y = 0.8923x
R² = 0.8943

0 100 200 300 400 500 600
Hmax_Obs(cm)y = 0.9744x
R² = 0.9162

0 100 200 300 400 500 600
Hmax_Obs(cm)0 100 200 300 400 500 600
Hmax_Obs(cm)(b) Hmax_MLR
Hmax_Cal(cm)Hmax_Cal(cm)

600
500
400
300
200
100
0

600
500
400
300
200
100
0

100 200 300 400 500 600
Hmax_Obs(cm)Hmax_Cal(cm)Hmax_Cal(cm)y = 0.9852x
R² = 0.94550(e) Hmax_SCG(d) Hmax_BR(c) Hmax_LM
600
500
400
300
200
100
0

600
500
400
300
200
100
0

y = 0.9603x
R² = 0.8614

0 100 200 300 400 500 600
Hmax_Obs(cm)Fig. 4 (a) Levenberg-Marquardt ANN, (b) Bayesian Regularization ANN (c) Scaled Conjugated ANN, (d)Gaussian Process Regression, (e) Water Balance Model (WBM), (f) Multilinear Regression model(MLR).

CONCLUSION

data. Thanks to the Laboratory of Water Resources
Engineering of Mie University for their help.

The accuracy of different models for forecasting the
maximum monthly water level of the Niger River
Inner

Delta

was

investigated

using

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[11] A. MohammadKalteh, "Monthly riverflow forecasting using[22] Z. Yu, G. Lei, Z. Jiang and F. Liu, "ARIMA Modelling and Forecasting

artificial neural network and support vector regression modelsof Water Level in the Middle Reach of the Yangtze River," in ICTIS,

coupled with wavelet transform," ELSEVIER, vol. 54, pp. 1-8,

Banff(CANADA), 2017.

2013.

1038

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov. 12-14, 2018, ISBN: 978-4-909106018 C3051

ENHANCEMENT OF BIOMETHANE PRODUCTION POTENTIALFROM THE ALKALINE PRETREATED POLY (LACTIC ACID)
WASTE BY THE CO-DIGESTION PROCESS
Sutisa Samitthiwetcharong1,2 and Orathai Chavalparit1,2,3
1

Department of Environmental Engineering, Chulalongkorn University, Bangkok 10330, Thailand
2

Research Unit of Environmental Management and Sustainable Industry, Faculty of Engineering,
Chulalongkorn University, Bangkok 10330, Thailand

3

Research Program: Sustainable management of industrial and agricultural wastes for transitioning to acircular economy, Center of Excellence on Hazardous Substance Management (HSM), Bangkok 10330,
Thailand

ABSTRACTThe objective of this research was to evaluate the yield of biomethane production from anaerobic co-digestion
process and biodegradation potential of post-consumer Polylactic acid (PLA) plastic waste. PLA waste waspretreated with sodium hydroxide (NaOH) and then utilized as co-digestion substrate along with organic waste.
The potential of alkaline pretreatment and co-digestion of PLA on food waste and market waste for methane
production was investigated. The CSTR batch carried out different samples in laboratory scale. Results from the
CSTR tests showed that the utilization of pretreated PLA as a single substrate was able to produce 148 L/kgVSaddedof biomethane. The co-digestion of pretreated PLA and market waste was able to enhance the yield of biomethane
production as much as 282.7 L/kgVSadded. Whilst biomethane produced by co-digestion of pretreated PLA andfood waste was 211.6 L/kgVSadded, which was 1.6 times more than that produced by utilizing only food waste.
Keywords: Polylactic acid (PLA), Thermal-alkaline pretreatment, Co-digestion, Methane production

option for PLA waste disposal. Theoretically, PLA is
produced by polymerization reaction of lactic acid.
Accordingly, landfilling could disrupt biological andchemical degradation mechanism significantly. As aresult, PLA might be unable to be broken down andconsumed directly by cells as effectively as lactic acidcould be. Moreover, PLA has highly crystalline
structures which are not easy to degrade underaerobic and anaerobic mesophilic conditions [4]. Sin[5] stated that the degradation of PLA was initiatedthrough hydrolysis process, followed by enzymatic or
microorganism digestion. Such degradation leads to
PLA fragmentation and ultimately transforms PLA
into harmless substances. Massardier-Nageotte [4]reported that PLA showed some mass loss whenaerobic conditions were applied. However, the massloss was insignificant in anaerobic conditions. The
explanation is that the biodegradation of PLA is very
slow, because of a lack of microorganism
colonization on the sample’s surface. Kale [6]reported that PLA under composting plant
disappeared within 30 days, while landfill required 6
months for a major fragmentation to occur, and 15
months for significant amount of mass loss. For biodigester condition, the fermentation of PLA underanaerobic biodegradation at 37 °C took 100 days tocomplete the degradation process [7]. Furthermore,

INTRODUCTION
Bioplastics are eco-friendly biodegradable
plastics which can degrade under appropriate
environmental conditions. Nowadays, bioplastics arewidely used in many countries in order to reduce theconsumption of petroleum-based plastics [1]. It is
expected that the growth of biopolymers andbioplastics worldwide could increase as high as 12%
annually. In 2018, the global production capacity of
bioplastics is 6.6 million tons. Among the various
types of bioplastics, Polylactic acid (PLA) is thesecond most consumed bioplastics [2]. Generally,
PLA is derived from renewable resources such as
corn starch, tapioca roots, chips, starch and sugarcane.
PLA is available commercially for various
applications, including films, bags, packaging,electronic parts, and medical plastics. However, themost common use of PLA as biodegradable polymer
is in medical and food packaging. Despite PLA’s
utility for various applications, there are some
limitation, e.g. PLA’s slow degradation rate, and its
low affinity to the cells whose degradation processdepends on pH and temperature [3]. As a result,finding an appropriate method for PLA
recycling/recovery can be a challenging task.
Generally, landfilling is considered the best1039

SEE - Nagoya, Japan, Nov.12-14, 2018

contained 2% of the VS and a different variation of
conditions as shown in Table 2. Different batches ofbiomass mixtures and fractions were prepared inorder to investigate biogas production andperformance of co-digestion process. For each reactor,
the ratio of substrate to inocula was maintained at 3
L: 2 L, that is preparing 3 L of the 2% VS substrateand 2 L of the 2.5% inocula. Flowchart of biomethane
production experiment is shown in Fig. 1.

thermophilic condition can increase the efficiency of
PLA biodegradation as well. The experiment provedthat using 1.5 L reactor at 55 °C was able to result in
91% degradation of PLA within 75 days, along with
53.8% production of methane [8].
Currently, there are a few researches that focus on
methane production by anaerobic fermentation assource of renewable energy. Samitthiwetcharong [9]observed that biogas production from pretreated PLA
with 0.5 M NaOH at 60 °C could obtain 215
ml/gVSadded, which was 3.7 times higher than thatobtained from non-pretreated PLA. Vasmara [10]also stated that biogas production from biochemicalmethane potential (BMP) at 55°C from PLA could
obtain biogas for 282 mL CH4 g-1 VS. When PLA
was utilized along with pig slurry in co-digestion
process, Mmax was achieved at 12% which was higher
than in theory. Methane ratio during PLA degradation
at 35oC and 55 oC ranges from 50% to 60% [8]. As forthis research, the main focus was the precursor of
PLA for biogas production. The aim of this study wasto enhance biogas yield achieved from anaerobic codigestion process of organic food waste/market waste
and alkaline pretreated PLA, whose pretreatment
process was done by soaking PLA in NaOH.

The amount of substrate fractions with an initial 3
L of 2% VS was added to CSTR. 3 g/L of NaHCO3
was added to the reactor to provide buffer capacity.
The ratio of substrate and its chemical characteristics
in each reactor is shown in Table 2. The volume ofbiogas production in each reactor was recorded on adaily basis. The experimental batches were incubateduntil no further gas was produced (60 days). For 3
times a week, a 50 ml sample from each reactor was
taken and analyzed for TS, VS, and sCOD. A
methane gas composition analyzer was used tomeasure methane content by using Gas
Chromatography and Thermal Conductivity Detector(TCD).

MATERIALS AND METHODS

Table 1 Characteristics of substrates and inocula

Substrate and Raw Materials

Substrate

A commercial PLA film with 80 µm thickness
was used in this experiment. The PLA film was cut
into 1-2 mm pieces using grinder. The alkaline
pretreatment condition was done by soaking the cut
PLA film in 0.5 M sodium hydroxide solution (w/v)
in the ratio of 1 g of PLA to 10 ml of NaOH, for 2.5
days at ambient temperature. Biochemical methane
potential (BMP) experiments were used to determine
an optimum pretreatment condition of PLA [9].
Food waste and market waste were collected from
Chulalongkorn University’s cafeteria and freshmarkets in Bangkok. Major components of the foodwaste were rice and vegetables, while most of themarkets’ organic waste components were various
kinds of vegetables such as Chinese cabbage,
cauliflower, cabbage, Chinese kale, and lettuce. The
vegetable waste was grinded to be used for theexperiment.
Inoccula used in CSTR reactor were obtained
from mesophilic anaerobic digester from a biogas
production plant of a soft drink company. The inocula
were analyzed by using the standard methods todetermine the total solids (TS) and volatile solids(VS) as shown in Table 1.

Food
waste
Marketwaste
PLA
InoculaOperation Scheme

TS
(%)
35.29

VS
(%)
33.83

COD
(mg/L)
148,732

pH
4.95

C/N
ratio
31.15

49.38

45.85

41,239

5.68

11.01

99.78
-

99.78
2.5%

-

-

8.51

Fig. 1 Flowchart of biomethane production fromalkali pretreatment PLA with food waste.
RESULTS AND DISCUSSION
Effect of NaOH Pretreatment on PLA

Experimental Procedure

The PLA was pretreated by soaking in 0.5 M NaOH
solution (w/v) for 60 hours prior to its use as
feedstock for anaerobic digestion in CSTR.

Four reactors were used in this study. Each reactor
1040

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 2 Experimental setup: number of substrates in each batch reactor and chemical characteristics
ReactorSubstrate

TVS(%)TVS (%)%C%N

C/N ratio

1
2

PLA
PLA pretreated with 5 M NaOH
for 48 h (pretreated PLA)
Co-digestion of pretreat PLA andfood waste with ratio 1:1(pretreated PLA: FW = 1:1)
Co-digestion of pretreat PLA andmarket waste with ratio 1:1(pretreated PLA:MW= 1:1)

2

2.0

33.56

-

-

2

2.56

39.98

-

-

2

2.65

36.77

1.08

34.13

2

2.54

30.01

1.43

21.02

3

4

The NaOH solution used for PLA pretreatment was
analyzed for lactic acid. The result showed that theconcentration of lactic acid was 18,200 mg/l. Gorrasi[11] reported that hydroxide ion (OH-) from NaOH
could increase reaction rate of hydrolysis byminimizing PLA’s structures in which the PLA wasdegraded into lactic acid form. The detection of
Lactic acid might confirm that the hydrolyzed PLA
was transformed into lactic acid, which would
convert into acetic acid whose methanogens could
enable biogas production [3], [12]-[13]. As a result,pretreatment with alkaline solution proved to beeffective for PLA to be utilized along with organic
food waste or other biomass for anaerobic digestion
or co-digestion process for biomethane recovery.

PLA. In co-digestion process, it was observed that theratio of 1 pretreated PLA to 1 food waste could
achieve the highest biogas production, i.e., 627.4
L/kgVSadded.

Biomethane Production(a) Biogas yield

Co-digestion of alkaline pretreated PLA andorganic waste could increase methane content in theobtained biogas. The biogas and methane yieldedfrom the pretreated PLA film substrate were 230 and
148.3 L/kgVSadded, respectively (Fig. 2). It wasobserved that the percentage of methane in biogas
was as high as 64.5%. This resulted from hydrolysis
and defragmentation of the PLA into lactic acidaccording to the pretreatment process. Consequently,
the microorganism that produced acid could directlytransform the lactic acid into acetic acid in whichmethanogens could transform the acetic acid intomethane. However, the methane generation since thestaring of the system operation until the biologicalreaction was completed in 27 days.
The results from co-digestion experiment showed
higher amount of biogas and methane yield than theyield from the reactor which utilized only pretreated(b) Methane yieldFig. 2

Cumulative
biogasandmethaneproductivity of pretreated PLA and codigestion of pretreated PLA with organic
waste.

Table 3 pH, temperature and VFA/ALK ratio from co-digestion of pretreated PLA and organic waste
Reactor12
3
4

substrate
PLA
Pretreated PLA
Pretreated PLA: FW = 1:1
Pretreated PLA: MW =1:1

pH

Temp (OC)6.50 – 7.95
6.65 – 7.94
6.78 – 7.82
6.90 – 7.96

29.9 – 34.9
30.7 – 34.6
29.7 – 34.7
30.7 – 34.9

1041

VFA/ALK
ratio
0.07-0.33
0.07-0.39
0.05-0.37

SCOD remove
(%)
88.37
94.32
90.51

SEE - Nagoya, Japan, Nov.12-14, 2018

Scanning Electron Microscopy (SEM) Study
The reactor that utilized the ratio of 1 pretreated PLA
to 1 market waste was the second highest biogas
production, which was approximately 500.4
L/kgVSadded. However, methane content in the biogas
obtained from pretreated PLA and market waste wassignificantly higher than that obtained frompretreated PLA and food waste. As a result, the codigestion of pretreated PLA and food waste achieved
the highest methane yield at 282.7 L/kgVSadded, while
the methane yield achieved from co-digestion of
pretreated PLA and food waste was 211.6
L/kgVSadded. Theoretically, lactic acid is the primary
reactant for biogas production process. This might
explain why biogas production increased.
Furthermore, co-digestion of bioplastic and organic
waste could also increase biomethane production.
Wang [12] found that organic waste could increasedegradation rate of PLA in an anaerobic condition
with proper temperature, pressure and ammonia
content derived from protein in food waste.
In addition, the co-digestion of pretreated PLA
and market waste obtained 1.9 times higher amountof methane than that obtained from using pretreated
PLA as a single substrate as shown in Fig. 3. Also, theexperiment of the co-digestion of pretreated PLA andfood waste could increase methane production
capacity for 1.43 times higher than that of the reactor
which utilized only pretreated PLA. Drawing fromthe results, it might be concluded that co-digestion of
pretreated PLA and organic waste could enhancemethane production in co-digestion anaerobic
process.

Topological study of the pretreated PLA films
was done by using the Scanning Electron Microscopy(SEM) with magnification of 2000 times (as shown in
Fig. 5-8). Four sets of PLA films and pretreated PLA
films were used for the topological studies, i.e., 1)
PLA film obtained from non-pretreated PLA
digestion, 2) pretreated PLA digestion, 3) Codigestion of pretreated PLA: FW, and 4) Co-digestionof pretreated PLA: MW. For the pretreated PLA
films, high density of pores was observed for only 15
days of operation. The density of pores was further
increased after 60 days of operation.

Fig. 3

Biogas and methane productivity
pretreated PLA and co-digestion
pretreated PLA with organic waste.

ofof

Digester Performance
Table 3 shows pH and alkalinity ratios(VFA/ALK) of the effluents during the 60-day
incubation period of various substrates. The results
showed that all of the CSTR experimental batches
had VFA/ALK ratio within the range of 0.05-0.39(Fig 4). Alkalinity result of each batch also accounted
for higher than 2,500 mg as CaCO3/l which showed
great buffer capacity of the overall systems. These
results might indicate a high stability of the system inwhich the VFA/ALK should be below 0.4.
Result from soluble COD removal efficiency(Table 3) showed that normal, non-pretreated, PLA
could not be biologically degraded within 65 days inan anaerobic condition, while alkaline pretreated PLA
could be biologically degraded by anaerobic bacteria.
Consequently, alkaline pretreatment could help
promote the degradation of PLA and turn it into lactic
acid by increasing the rate of hydrolysis. Lactic acidcan be transformed into biogas later on [9]. The
results also showed that the COD removal efficiencyof the pretreated PLA was at the same rate as themarket waste.

(a) pretreated PLA:FW = 1:1

Fig. 41042(b) pretreated PLA: MW =1:1
The performance of an anaerobic digester ofco-digestion.

SEE - Nagoya, Japan, Nov.12-14, 2018

production. Furthermore, co-digestion of alkaline
pretreated PLA with market waste and food waste
could achieve more biomethane yield than that
achieved by utilizing only PLA. As a result, PLA
waste could be used as a substrate for anaerobic codigestion process. In addition, alkaline pretreatmentof PLA could help promote biomethane yield as well.
Fig. 5ACKNOWLEDGEMENTS

Surface of non-pretreated PLA films fromsingle substrate digestion

This research was financially supported by
the authors thank the Office of Higher
Education Commission (OHEC) and the S&T
Postgraduate Education and Research Development
Office (PERDO) for the financial supportof the Research Program and the 90th
Anniversary of Chulalongkorn University Fund
(Ratchadapiseksomphot Endowment Fund).
Fig. 6

Surface of alkaline pretreated PLA films

Fig. 7

Surface of pretreated PLA films from codigestion with food waste.

Fig. 8

Surface of pretreated PLA films from codigestion with market waste.

REFERENCES[1] Borrisuttanakul S., Thai Bioplastics Industry
Association (TBIA), International BusinessDirectory for Innovative Bio-based Plastics andComposites, 2012, pp. 119.
[2] Chaisu K., Bioplastic Industry from Agricultural
Waste in Thailand. Journal of Advanced
Agricultural Technologies, Vol. 3, No. 4, 2016.
[3] Elsawy M.A., Kim K.H., Park J.W. and Deep A.,
Hydrolytic Degradation of Polylactic Acid
(PLA) and Its Composites. Renewable andSustainable Energy Reviews, Vol. 79, 2017, pp.
1346-1352.
[4] Massardier-Nageotte V., Pestre C., CruardPradet T. and Bayard R., Aerobic and Anaerobic
Biodegradability of Polymer Films and Physicochemical Characterization. Polymer Degradationand Stability, Vol. 91, Issue 3, 2006, pp. 620-627.
[5] Sin L.T., Rahmat A.R. and Rahman W.A.W.A.,
Degradation and Stability of Poly (lactic Acid).
Polylactic Acid, 2013, pp. 247-299.
[6] Kale G., Auras R., Singh S.P. and Narayan R.,
Biodegradability of Polylctide Bottles in Realand Simulated Composting Conditions. Polymer
Testing, Vol. 26, Issue 8, 2007, pp. 1049-1061.
[7] Itävaara M., Karjomaa S. and Selin J.F.,
Biodegradation of Polylactide in Aerobic andAnaerobic
Thermophilic
Conditions.
Chemosphere, Vol. 46, Issue 6, 2002, pp. 879885.
[8] Yagi H., Ninomiya F., Funabashi M. andKunioka M., Anaerobic Biodegradation Tests of
Poly (lactic acid) and Polycaprolactone Using
New Evaluation System for Methane
Fermentation in Anaerobic Sludge. Polymer
Degradation and Stability, Vol. 94, Issue 9, 2009,
pp. 1397-1404.
[9] Samitthiwetcharong S., Kullavanijaya P. andChavalparit O., Anaerobic Biodegradation ofThis result indicates that NAOH could enhanceporosity of PLA film which would increase
biodegradation process and bioavailability for
microorganism and enzyme to function more
effectively. Results from fig. 6 and 7 emphasized theenhancement of biogas production due to codigestion of pretreated PLA. It was shown that using
pretreated PLA with organic waste, from single
substrate digestion, could promote biogas production,
which is a result of PLA’s high porosity.
CONCLUSION
Pretreatment of PLA film with NaOH at pH 13(NaOH 0.5 M) for 60 hours could promote PLA
degradation, which would turn PLA into lactic acidand the lactic acid would further transform into acetic
acid which is the primary substrate of biogas
1043

SEE - Nagoya, Japan, Nov.12-14, 2018

Poly (lactic acid) Under Mesophilic Condition
Using Thermal-alkaline pretreatment. IOP
Conference Series: Materials Science andEngineering, Vol. 222, 2017.
[10] Vasmara C. and Marchetti R., Biogas Production
from Biodegradable Bioplastics. Environmental
Engineering and Management Journal, Vol. 15,
No. 9, 2016, pp. 2041-2048.
[11] Gorrasi G. and Pantani R., Effect of PLA Gradesand Morphologies on Hydrolytic Degradation at
Composting Temperature: Assessment ofStructural Modification and Kinetic Parameters.

Polymer Degradation and Stability, Vol. 98,
Issue 5, 2013, pp. 1006-1014.
[12] Wang F., Hidaka T., Tsuno H. and Tsubota J.,
Co-digestion of Polylactide and Kitchen Garbage
in Hyperthermophilic and Thermophilic
Continuous Anaerobic Process. Bioresource
Technology, Vol. 112, 2012, pp. 67-74.
[13] Kim M.S., Na J.G., Lee M.K., Ryu H., Chang
Y.K., Triolo J.M., Yun Y.M. and Kim D.H.,
More Value from Food Waste: Lactic Acid andBiogas Recovery. Water Research, Vol. 96, 2016,
pp. 208-216.

1044

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

PERFORMANCE OF AIR CONDITIONING SYSTEM INEDUCATIONAL BUILDING FOR ENERGY CONSERVATION
Nantamol Limphitakphong1, Nuttasate Chaikatetham2, Therdthai Khaimook2, and Orathai Chavalparit1,2
1
Research Unit of Environmental Management and Sustainable Industry, Faculty of Engineering,
Chulalongkorn University, Bangkok, 10330, Thailand
2
Department of Environmental Engineering, Faculty of Engineering, Chulalongkorn University,
Bangkok, 10330, Thailand

ABSTRACT
Building sector plays an important role in energy consumption globally. In tropical countries like Thailand,
more than half of all energy is usually supplied for cooling systems. The objective of this study, therefore, is toinvestigate the environmental performance of an air-conditioning (AC) system for an educational building and to
propose strategies for mitigating GHG through energy efficiency measures toward a campus-wide sustainableenergy policy. According to data collected, the results demonstrate that the existing AC system consumes about
70% of total energy consumption. The existing system’s low energy efficiency caused the whole building’s
performance to fall below the building energy code standard stipulated by the Thailand’s Ministry of Energy. To
improve the building’s performance, replacement of the current AC system with a highly efficient AC system isneeded. This, however, would be costly. Alternative energy conservation measures, including changing windowpanes, walls, and roof tile materials and installing thermal insulation were proposed to quantify the amount ofenergy savings as well as GHG emissions reductions. The findings will be useful for building owners, architects
and policy makers as a guide about whether to use existing materials or new materials when planning to for abuilding’s energy-efficiency.
Keywords: Environmental performance, Energy efficiency measure, Air-conditioning system, Educationalbuilding

total national consumption and its consumption has
increased rapidly with growth rate of 82% over thelast two decades [10]. To cope with a concern ofsupplying energy for such a huge demand sufficiently,
the Thailand’s Ministry of Energy has issued
Ministerial Regulation stipulating the type and size ofbuildings and standards criteria and methods ofdesigning energy conservation building, B.E. 2552
(2009) and provided for the monitoring of designatedcommercial buildings which consume more thantwenty-million megajoules of power energy
equivalent annually [11]. Among the six categories ofdesignated commercial building, data obtained from
Department of Alternative Energy Department andEfficiency (DEDE) demonstrated that the educational
institution building stock accounted for 9% andconsumed around 15% of total energy demand forbuildings [12]. Consequently, research on ways toimprove the energy efficiency of this type of building
would definitely contribute significant positive
impacts on energy security. Chavalparit andLimphitakphong [13] have evaluated the energy
efficiency and environmental performance ofbuildings in Bangkok and emphasized that most of
the energy use in educational building was attributed
to electricity consumption for HVAC system,
resulting in the greatest portion of GHG emission as

INTRODUCTION
Due to increasing global concern about climatechange, energy efficiency and environmental
remediation have broadly become main areas ofresearch. One of the main issues concerning the effort
to limit global temperature rise to only 2 degrees
Celsius above pre-industrial levels is the building
sector, since it consumes a huge amount of energy
and resources and emits a large amount of greenhousegas (GHG) [1]-[2]. In tropical countries, increased
use of air conditioning to maintain thermal comfort inbuildings is a main factor causing an increasing ofenergy demand whereas increased use of heater is a
key pressure for the temperate countries [3]-[5].
Accordingly, it could be implied that high potentialsof either energy saving or GHG emission reduction
can be achieved through energy improvement optionsfor Heating, Ventilating, and Air Conditioning(HVAC) system of buildings. Recently, numerous
studies have validated that advanced cleaner
technologies and higher energy efficiency equipment
coupled with changing occupant habits will saveabout 30-50% of total energy consumption for both
new and existing buildings [6]-[9].
In Thailand, the final energy consumption of thedomestic building sector accounted for 22% of the1045

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 The basic parameters ofeducational building

a consequence. Thaipradit [14] has provided
evidence demonstrating that building insulationmaterials have a significant impact on the energy andenvironmental performance of educational buildingsin Thailand. Chaiyat [15] has applied the concept ofusing phase change material for improving thecooling efficiency of an air conditioner and found thatthe modified air-conditioner could decrease theannual electrical consumption by about 1.13 MWh
while having a payback period for modifying
equipment of 4.15 years.
In addition, since the Thai Ministry of Energy has
pledged to reduce around GHG emissions by 20-25%
by 2030 in the 21st conference of the parties,
commercial buildings have become a major
contributor in reducing such number of reductions
through energy efficiency measures [16]. This study,
therefore, was aimed at investigating theenvironmental performance of existing airconditioning (AC) system for educational building
and to propose strategies for mitigating GHG throughenergy efficiency measures toward a campus-wide
sustainable energy policy. Besides applying advanced
technology and higher energy efficiency equipment
replacement, changing building envelopes were also
evaluated to identify alternative options for
improving existing buildings, based on either anenvironmental or economic performances perspective.
The information provided from the findings of thisstudy can be useful for policy makers and building
planners in determining strategies for either reducing
energy demand and GHG emission or saving
expenditures of educational institutions in tropicalcountries like Thailand.

Building parameters
FloorsGross floor area
Air-conditioned area
Structure
Envelope
Glass
Roof

case

study

Specifications
5 floors above ground1,862.28 m2
1,195.43 m2
Concrete
Brick and curtain wall
combination
Clear flat glass
Flat roof, concrete slab

CP is used for validating results of actual cooling
performance with the idle to assure its accuracy.
Whereas the results of COP and EER were testified
in accordance with Thai industrial standard of AC
system (TIS2134:2553).
𝐶𝐶𝐶𝐶 = 𝑊𝑊𝑊𝑊 ⁄𝐶𝐶𝐶𝐶(1)

𝐶𝐶𝐶𝐶𝐶𝐶 = ∆ℎ𝑜𝑜𝑜𝑜𝑜𝑜 ⁄∆ℎ𝑖𝑖𝑖𝑖(3)

𝐶𝐶𝐶𝐶 = 5.707 𝑥𝑥 10−3 𝑥𝑥 𝐴𝐴 𝑥𝑥 𝑉𝑉 𝑥𝑥 60 𝑥𝑥 (𝐻𝐻𝑟𝑟 − 𝐻𝐻𝑠𝑠 )𝐸𝐸𝐸𝐸𝐸𝐸 = 𝐶𝐶𝐶𝐶𝐶𝐶 𝑥𝑥 3.412

(2)

(4)

WI = Watt input (kW), inspecting at
condensing unit by power meter
CL = Cooling load (TR), inspecting at fan coilunit
A = Cross-sectional area (m2)V = Velocity (m/s)
Hr = Enthalpy Return (kJ/kg dry air), referring
to psychometric chart
Hs = Enthalpy Supply (kJ/kg dry air),referring to psychometric chart∆hout = Difference of enthalpy at fan coil unit(kJ/kg)∆hin = Difference of enthalpy at condensing
unit (kJ/kg)

MATERIALS AND METHODS
Building Description
This research was performed using a 5-storey
educational building at Chulalongkorn University asa case study. The case study building, as described inTable 1, is located in the heart of Bangkok at 13.92
latitude and 100.6 longitude with a range of dry-bulb
temperature of 19.0 – 37.2๐C and humidity ratio of
11.2 – 28.7 gw/kgda throughout the year [17].

Energy Simulation
To identify the potential of alternative options for
improving building’s energy efficiency, Building
Energy Code (BEC) software version 1.0.6 developedby DEDE in accordance with the Ministerial
Regulation on type or size of buildings and standards
criteria and methods of designing energy
conservation buildings B.E. 2552 (2009), was used inthis study to estimate the amount of energy savings
compared with the current consumption. Data input
in the program are classified into 6 categories,
including building envelope, lighting system, AC
system, photovoltaic (PV) system, hot water (HW)system, and other equipment. However, since there

Evaluation of the Energy Efficiency of the Air
Conditioning System
To evaluate the efficiency of electricalconsumption in air conditioning (AC) system, threeparameters involving cooling performance (CP),coefficient of performance (COP), and energy
efficiency ratio (EER) were investigated following
Eq. (1) – (4).

1046

SEE - Nagoya, Japan, Nov.12-14, 2018

study as demonstrated in Eq. (6) to assess the
economic performance of each energy efficiency
improvement measure. A trade-off between
investment cost and energy expenditure savings will
help signify and prioritize the possible measures for
implementation. When the total investment cost is
paid by the saving of energy cost, it is a point ofbreak-even, which thereafter entails no monetary loss
from implementation.

are no PV and HW systems in this building case study
and lighting system and others equipment share alittle portion of energy consumption, this study
therefore only focused on the AC system andenvelope materials that are related to heat transfer
through building envelope and building’s energy
demand. Furthermore, four options for improving
energy efficiency of the building were examined tosignify a key building material resulting in betterbuilding performance as presented its properties inTable 2 - 3.

𝑷𝑷𝑷𝑷 (𝒚𝒚𝒚𝒚) =𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰𝑰 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄 (𝑼𝑼𝑼𝑼𝑼𝑼)𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄 𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔𝒔 ((6)

𝑼𝑼𝑼𝑼𝑼𝑼)𝒚𝒚𝒚𝒚

Environmental Performance Analysis

RESULTS AND DISCUSSIONS

Due to global concern about climate change, theenvironmental impact of energy consumption wasdemonstrated in terms of CO2 emission through thefollowing equation (Eq. 5);

Energy Consumption of Educational Building: A
Case Study

𝑬𝑬𝑬𝑬 = (𝑩𝑩𝑩𝑩𝑬𝑬𝑬𝑬 − 𝑷𝑷𝑷𝑷𝑬𝑬𝑬𝑬 ) × 𝑬𝑬𝑬𝑬𝑮𝑮𝑮𝑮𝑮𝑮𝑮𝑮

Through 12 months of data collection, the casestudy building consumed about 127,489 kW ofelectricity, approximately 71% of this total power
consumption was attributed to the AC system. Such a
portion is quite high compared with the averageenergy consumption proportion of educationalbuildings (59%) presented by Phupadthong [9]. This
indicates that the efficiency of AC system in this casestudy is probably low, resulting in consuming higher
amount of energy than the typical case. An energy
efficiency evaluation of AC system also emphasizedthat among all the AC equipment, only two of themcomply with the Thai industrial standards aspresented in Table 4.

(5)

Where ER is mission reduction of each measures(kgCO2/yr). BEEC refers baseline energy consumption(kWh/yr) and PEEC represents project energy
consumption (kWh/yr). EFGRID stands for emission
factor of electricity production, which isapproximately 0.6093 kgCO2/kWh for Thai gridproduction [18].
Economic Performance Assessment
A payback period (PB) analysis was used in thisTable 2 Properties of opaque materials
Type
Ceiling
Insulation
Materials
Wall
Materials
Roof Tile
Materials

PVC Gypsum
Aluminum Foil Gypsum
Polyurethane
Glass Wool (Stay Cool)
Autoclaved Aerated Concrete
Concrete BlockConcrete Profile Tiles
Asbestos Cement Corrugated

Thermal Conductivity(W/mK)
0.211
0.322
0.023
0.039
0.476
0.546
0.993
0.395

Density(kg/m3)
684
745
24
12
1,280
2,210
2,400
2,000

Specific Heat(kJ/kgK)
1.09
1.09
1.59
0.96
0.84
0.92
0.79
1.00

Table 3 Properties of transparent materials
Glass
Type
TintedGlass
Solartag(TS560)Thicknessm

Visible Ray

Solar Energy

U-value
w/m2

SH
GC

ReflectanceTransmittance

ReflectanceTransmittance

Absorption

0.006

7.0

0.760

5.0

49.0

46.0

5.74

0.6

0.006

5.2

0.361

4.8

21.9

73.3

5.35

0.4

1047

SEE - Nagoya, Japan, Nov.12-14, 2018

In addition, DEDE building regulations define asuitable level of overall thermal transfer value(OTTV) and residential thermal transfer value(RTTV) at 50 and 15 watt/m2 for an educationalbuilding. The low energy efficiency of the existing
AC system in this study, apparently, lead the wholebuilding performance to fall below the standard ofthis regulation.

consumption by about 25,886 kWh a year, or ifconverted to GHG emissions, it equates to a reductionof 15,772 kgCO2e/yr. The break-even point of each
AC capacity types, as illustrated in Fig.1, will be 6.3,
6.6, 21.1 and 30 yrs. for 12000 Btu, 18,000 Btu,
30,000 Btu and 36,000 Btu, respectively.

High Efficiency of Air Conditioning System
Replacement
Because the current AC system plays such animportant role in the building’s energy demands andseemingly caused the building to fall below standard
a high efficiency AC replacement. Based on theassumption that every AC equipment that have has
become obsolete or declines in performance will be
replaced with a high efficiency AC at the same
capacity, the result demonstrated that such
implementation requires an investment of 39,224
USD. This investment will reduce energy

Fig 1

Economic assessment for air conditioning
system replacement

Table 4 Energy performance of air conditioning system in building case study
Actual AC Efficiency
Capacity
Ideal Performance*
Comply with TIS**(Btu)(kW/TR)
CP
COP
EER
1
12000
1.17
1.66
2.13
7.25
FAIL
2
36000
1.13
2.89
1.22
4.15
FAIL
3
12000
1.17
1.70
2.07
7.05
FAIL
4
48000
1.13
1.23
2.86
9.76
PASS
5
30000
1.16
5.44
0.65
2.20
FAIL
6
12000
1.20
3.94
0.89
3.05
FAIL
7
36000
1.13
2.77
1.27
4.33
FAIL
8
38000
1.14
1.22
2.90
9.87
PASS
9
30000
1.16
9.15
0.38
1.31
FAIL
10
18000
1.25
2.14
1.65
5.62
FAIL
11
30000
1.16
1.62
2.18
7.42
FAIL
12
36000
1.13
2.05
1.72
5.87
FAIL
13
12000
1.10
2.07
1.70
5.78
FAIL
14
12000
1.17
6.00
0.59
2.00
FAIL
*
To validate the measurement, CP value of actual AC efficiency shall higher than ideal performance.
**
COP and EER should not less than 2.82 and 9.60 respectively to pass the Thai industrial standard [19].
No.

Table 5 Performance of improving existing building through envelope materials
Investment
Energy Saving
Cost
Quantity
Expenditure(USD)(kWh/yr.)(USD/yr.)
Tinted Glass
801.74
5,138.6
688.22
Polyurethane
3,607.41
11,108.2
743.87
Autoclaved Aerated Concrete
2,934.87
9,951.6733.06
Concrete Profile Tile
1,665.75
2,125.2
59.07
Total
6,845.32
22,762,2
1,676.72
Note: Electricity charge is about 0.147 USD/kWh
Material Type

1048

Payback
Period
(yr.)
1.1
2.2
2.0
5.3
2.0

GHG
reduction(kgCO2e/yr.)
3,131
6,768
6,064
1,295
13,869

SEE - Nagoya, Japan, Nov.12-14, 2018

Fig 2(a) Ceiling Insulation Materials(c) Roof Tile Materials(b) Wall Materials(d) Glass Materials

Economic assessment for improving building envelope materials
CONCLUSION

Options for Improving the Energy Efficiency of
Buildings

A large portion of final energy is attributed to thebuilding sector and its demand is going to increase in
the near future abruptly. Audits to monitor and help
manage buildings’ energy performance is vital. The
performance of the case building at Chulalongkorn
University was investigated to identify hotspots andto propose strategies for mitigating GHG. The
findings revealed that the efficiency of the air
conditioning system was poor as most equipment
failed to meet the Thai industrial standards. Either ahighly efficient air conditioner replacement or
improving building envelope should be implemented
to amend this. The initiatives on considering
performance-based energy efficiency measures cancontribute to a campus-wide sustainable energy
policy. Further actions on monitoring energy
performance and its improvement and future researchon other factors influencing energy consumption and
GHG emission from this and other buildings areneeded, otherwise this small-scale energy assessment
will have little positive effect on Thailand’s
environmental sustainability.

Besides changing the AC system, which requires
a payback period of more than 6 years, alternative
options for improving energy efficiency of a building
should be examined. Figure 2 illustrated the payback
period for implementing each measure of the fourenergy efficiency improvement options described inTable 2-3. It was found that the option with theshortest payback period consists of installing
polyurethane insulation above the ceiling, using
autoclaved aerated concrete instead of bricks, roofingwith concrete profile tiles, and installing tinted glass.
The best 4 measures, therefore, were integrated to reinvestigate the maximum level of energy demand
reduction as well as GHG reduction through envelopematerials improvement. The result as presented inTable 5 revealed that more than 22 MW/yr. ofelectricity will be saved and about 13,869 kgCO2e/yr.
will be reduced if these four measures are
implemented together. Moreover, it will help increase
the building’s performance to meet the code ofdesignated building regulation eventually.

1049

SEE - Nagoya, Japan, Nov.12-14, 2018sector: impacts of energy efficiency plan, Energy
procedia, Vol. 138, 2017, pp. 847-852.
[9] Phupadtong
A.,
Limphitakphong
N.,
Kanchanapiya P., Tantisattayakul T. andChavalparit O., The assessment of theenvironmental and economic performances for
improving existing educational building: a casestudy of Bangkok, Thailand, International
Journal of Sustainable Energy Development,
2018, In press.
[10] Department of Alternative Energy Department
and Efficiency (DEDE), Thailand, Final energy
consumption by economic sectors, 2018[11] Ministry of energy (MoE), The ministerial
regulation type or size of buildings and standards
criteria and methods of designing energy
conservation building B.E. 2552, 2009[12] Department of Alternative Energy Development
and Efficiency (DEDE), Thailand, Lists ofdesignated buildings, 2018.
[13] Chavalparit O. and Limphitakphong N.,
Pathways to level up net zero carbon building
towards smart cities. Unisearch Journal, Vol. 5,
Issue 1, 2018, pp. 16-22.
[14] Thaipradit
P.,
Limphitakphong
N.,
Kanchanapiya P., Tantisattayakul T. andChavalparit O., The influence of building
envelop materials on its life cycle performance:a case study of educational building in Thailand,
Key Engineering Materials, 2018, In press.
[15] Chaiyat N., Energy and economic analysis of abuilding air-conditioner with a phase changematerial (PCM), Energy Conversion andManagement, 2015, Vol. 94, pp. 150-158.
[16] Limphitakphong N. and Chavalparit O.,
Potential of greenhouse gas emissions reductionin Thailand, Thailand’s Second Assessment
Report on Climate Change 2016, Thailand
Research Fund. Bangkok, 2016, pp. 456–497.
[17] EnergyPlus, Weather data, 2018, https://www.
energyplus.net/weather[18] Electricity Generating Authority of Thailand(EGAT), Thailand, Thailand grid mix electricity
life cycle inventory database, 2009.
[19] Thai Industrial Standards Institute (TISI), Room
air conditioners: energy efficiency, 2013

ACKNOWLEDGEMENTS
This research was funded by the Ratchadapisek
Sompoch Endowment Fund (2016), Chulalongkorn
University (CU-59-002-IC).
REFERENCES[1] Intergovernmental Panel on Climate Change(IPCC), Climate Change 2014: Synthesis Report,
Contribution of Working Groups I, II and III to
the Fifth Assessment Report of theIntergovernmental Panel on Climate Change,
Geneva, Switzerland, 2014, 151 pp.
[2] United Nations Framework Convention on
Climate Change (UNFCCC), Decision 1/CP.21:
Adoption of the Paris Agreement, Paris Climate
Change Conference, 2015.
[3] Agdas D., Srinivasan R.S., Frost K. and Masters
F.J., Energy use assessment of educationalbuildings: Toward a campus-wide sustainableenergy policy, Sustainable Cities and Society,Vol. 17, 2015, pp. 15-21.
[4] Zanni D., Righi A., Mora T.D., Peron F. andRomagnoni P., The energy improvement ofschool buildings: analysis and proposals foraction, Energy procedia, Vol. 82, 2015, pp. 526532.
[5] Varun, Sharma A., Shree V. and Nautiyal H.,
Life cycle environmental assessment of an
educational building in Northern India: a casestudy, Sustainable Cities and Society, 2012, Vol.
4, pp. 22-28.
[6] Salvalai G., Malighetti L.E., Luchini L. andGirola S., Analysis of different energy
conservation strategies on existing schoolbuildings in a Pre-Alpine Region, Energy andbuilding, Vol. 145, 2017, pp. 92-106.
[7] Rospi G., Cardinale N., Intini F. and Negro E.,
Analysis of the energy performance strategies ofschool buildings site in the Mediterranean
climate: A case study the schools of Matera city,
Energy and building, Vol. 152, 2017, pp. 52-60.
[8] Chaichaloempreecha A., Winyuchakrit P. andLimmeechokchai B., Long-term energy savingsand GHG mitigations in Thailand’s building1050

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

WILLINGNESS TO PAY (WTP) BY CONTINGENT VALUATIONMETHOD(CASE STUDY: WASTE MANAGEMENT SERVICES)
1

1,2

Marselina, 2Ria Virsa
Economic and Business Faculty, Lampung University, Indonesia

ABSTRACTThis study aims to estimate the household WTP on the tariff of waste management service with theContingent Valuation Method and to investigate the relationship between respondent characteristics with their
WTP. Questioners are designed with 8 options of waste management services with some more reasonabletariff. The sample consists of 200 households selected randomly in Bandar Lampung city, Indonesia. The result
indicates that household's WTP for waste management services is 200% higher than before, if services are
upgraded. Other results indicate that the level of education, number of family, job, income, knowledge andsatisfaction of respondents to waste management services are positively correlated with WTP.Government has toreview the tariff policy to obtain a more awareness tariff that encourage the sense of responsibility of thecommunity to protect the environment.
Keyword: Willingness to pay, Waste management services, Tariff, Contingent valuation method

1.

Banga, M (2011) also suggested to used WTP to
avoid the problem of free-riders in thedetermination of tariffs for public goods services.

INTRODUCTION

Waste issues are becoming an important issueof the environment in Indonesia. This problem isgetting worse along with the population growth andthe bad attitude of households disposing their
rubbish without being responsible. This habit isdriven by the low cost of waste management
service which is set by government. As a public
good, waste management services is non market
because no one can express their preference, so thetariff of its cannot be determined by market
mechanism. So that way, this tariff does not reflect
the actual cost, includes environment damaging.
Based on local regulation in Bandar
Lampung city, one of Indonesia provinces, theaverage of tariff of waste management service isbetween is 20,000 IDR to 30.000 IDR per monthThis tariff is only operational costs such as fuelprices for waste transport vehicle, labor, andvehicle maintenance and has not taken into
consideration of environmental damage. According
to Hagos (2012), the tariff must also be includes
the cost of recycling and composting. This low
tariff encourage people to easily dispose of waste
regardless environment damage and this attitude
will undermine environmental conditions.
Based on this background, it is needed tohave a technique for estimating of tariff thatencourage environmental awareness. One of
methods to estimate it, is Willingness To Pay(WTP). WTP is a technique to know thewillingness of individuals to pay for public goods
benefit in which the price of its can not be
determined by market mechanism. WTP is anindividual valuation technique on natural resourcesin order to improve the quality of the environment.

WTP is based on the user's perception of s ofthe public service. To get user perception, it canbe used Contingent Valuation Method (CVM).
CVM is a method of measuring someone's
preference (FontaWM, 2008). CVM is measuring
WTP by eliciting stated user preferences throughdirect surveys. User are directly asked about their
WTP
by
using
open-ended
questions(Makkonen.M,et all, 2011). In this surveys, user are
offered some alternative services or condition withvarying attributes. WTP is inferred indirectly fromtheir ranking or ratings of these alternative services.
CVM is can be used to determine the price of
tourism services, apartment tariffs, utilizing
wildlife, environmental quality.
In Indonesia, there is still miss interpretation, in
which all the public service and procurement
services including waste management services aregovernment duties and it should be free of charge.
In order to have a common point in determining thetariff, it should involve the participation of thehousehold. Afroz (2011) found the same point, inwhich households do not care about waste
management. According to Tansatrisna (2014), theparticipation of households in waste management
services can be indirect participation, namely the
involvement of households in financial matters.
This participation in waste management is reflectedby making payment of user tariff for garbage.
According Manurung (2008), one form ofparticipation on waste management can be seenfrom the willingness to pay for the improvement of1051

SEE - Nagoya, Japan, Nov.12-14, 2018

waste management facilities so that cleanliness andenvironmental quality can be maintained.
Public participation is essential and may lead toenormous benefits for sustainability development(Chutarat C: 2017). Teddy (2017) also agree thatwaste management services are facilitated by thegovernment but managed by the community
which requires active community involvement.
Involvement, participation and some characteristicof household determines their choices in WTP.
Brahim, Djemaci (2015) and James, K Boyce(2003) found that some characteristics of householdsuch as education level, gender, age, lines of class,race, ethnicity, house type, house distance, income
and service quality, awareness, perception andhousehold satisfaction level toward the benefits ofpublic goods in correlating with WTP. Effects on
WTP is high when they are interactions eachothers. Age tends to increase income and higher
income has higher opportunities to get higheducation and high education tends to increase
their awareness of environment (Makonenn,2011).
The more aged, the more
knowledge andexperience of environmental benefits and the moreconcern for the environment. This relationshipincrease the WTP. Family members will add
family members' information about environmental
issues because in Indonesia, environmental issues
become the curriculum taught in schools.
Community awareness of the environmentis influenced by the level of education andknowledge about environment (Finger,1994).
According to Mustafa.U (2014), household
concerning will affect WTP and it increase alongwith improving the quality of services. Survey
conducted by Gregory O. Thomas, et al (2018) also
found that having children may change people’s
individual environmental attitudes and behaviour,and the results indicate that having a new child is
associated with a small decrease in the frequency ofa few environmental behaviour. According toJames, K Boyce (2003) income inequalities caninfluence environmental degradation. Inequalities
may affect the overall extent of environmental
quality, so that the higher income the higher WTP.
High level of awareness and knowledge andpositive attitude will increases the environmental
protection(Aminrad,Z:2013).

policy of setting, in particular the
management services.

of waste

3.CITATION AND REFERENCE LISTWTP is an individual valuation techniqueon natural resources in order to improve the qualityof the environment. Some experts also define WTP
is the maximum price a benefitersi willing to pay
for a given quantity of product or services(Wartenbroch and Skiera,2002). WTP as a way of
calculating the ability of each individual on an
aggregate basis to pay in order to improve
environmental conditions to conform to desired
standards. Economic valuation is an attempt toprovide quantitative value to goods and services
produced by natural resources and environment
regardless of whether market value is available ornot (Susilowati, 2002). CVM is done by asking
directly to benefiters about the value of benefits ofpublic goods includes resources and environment.
Indramawan (2014) asks to 120
respondents in Semarang Barat and he found that
almost 85% of respondents are willing to pay
higher tariff. He also found that the level of
education and family income has a positive effecton the size of WTP. Huntari (2015) found that the
average WTP of consumers on waste treatment
services is higher than the tariffs paid. Yunis(2012) found the average of household WTP in
Tampan Pekanbaru is IDR 10.330 per month.
Banga et al (2011) in Uganda, found that WTP canbe increased by improving the service quality.
Contingent Valuation Method (CVM) is amethod for valuing natural resources and theenvironment. This approach is done to measure theeconomic value of goods that cannot be determinedbecause non market price. According to Fonta WM(2008), CVM is a technique to analyze thevaluation function that can provide qualitative
information that is difficult to identify using otherconventional valuation techniques. CVM is done
because household is unable to express its
preference for economic . CVM is also practiced byFried (1995) to find out WTP hunters for tourism
hunting services Cervus Elaphus in Oregon
National Park - Latin America, obtained WTP for$1,063 for each hunt. Afroz (2010) saw household
WTP for garbage dumping tariffs in Kuala Lumpur.
Ragens (1991) conducted a study of household
WTP to control pollution through counter measuresagainst water pollution in coastal areas of Kristians
and Fjord - Norway. Fried (1998) used CVM toresearch hunting tourism services. Brahim, D(2015), Nasir (2009)

2.OBJECTIVE
This study aims (1) to calculate thewillingness to pay of household to waste
management service in order to get the tariff whichis resulting which can arouse the awareness ofhouseholds to be more responsible, (2) toinvestigate the relationship between respondent’s
characteristic with their WTP. This study is
expected to provide inputs to the government's

4.RESEARCH METHODOLOGYThis research is field study with survey
technique. Data were obtained from questionnaires
1052

SEE - Nagoya, Japan, Nov.12-14, 2018

given to households located in densely populated
housing with the highest volume of waste.
Determination 200 household respondent usedjudgment random sampling technique. in Sukabumi
district whose waste is managed by city waste
management service of Bandar Lampung,Indonesia value of waste management service. One
way to know benefit from public goods is to use
CVM s by asking the ability of household pay for
waste management service.
It begins by designing a questionnaire that
describes some of the preferred bids from theimproved conditions of waste management services
at a reasonable tariff that follows. The initialconditions of service and of management services
at the study sites are taken as start points. Start
point condition of waste management service ismanaged 3 times a week in the afternoon, withgarbage cart, with tariff IDR 20.000 / bulan. The
average waste per day disposed of every householdin the study site was 3 plastics or 90 plastic/ month.
It means the value of waste management during
this per pack of garbage IDR 222.22 / plastic. Then
7 scenarios of waste management services werecreated by raising the per stage of service IDR
10.000/stage, in which IDR 10.000 is considered onhousehold ability.Designed questioner asked torespondent. If most respondents answer one
scenario selected, then this scenario is the actual
WTP desiredelements, namely the number of family members,
the level of education, the type of work, the level ofincome, the level of service satisfaction and thelevel of knowledge of the dangers of unmanaged
solid waste.The hypothesis developed as follows:
Ha (1): Numbers of Family is a significant andpositive correlation with WTP.
Ha (2): Level of education has positive correlation
with WTP.
Ha (3):The type of work of respondents has
positive relationship with WTP.
Ha (4): Level of income level has positive
relationship with WTP.
Ha (5):The level of satisfaction of respondents has
positive relationship with WTP.
Ha (6):The level of knowledge has positive
relationship with the WTP.
5.RESULTThe starting point if this study is based on
tariff paid by household of IDR 222/plastic or IDR
20.000/month with 3 times a week it collected andtransported in the afternoon. Garbage is mannedwith slower waggle wagon and taking 3 times aweek caused smell is not good.
Based on the survey results, most of
responden are dominantly choose scenario G, by
37% . They desired the waste management
services working every day or 7 times a week,
managed in the morning by garbage truck and theyagree to pay normal tariffd as IDR 555/ plastic or
IDR 50.000 /month. This WTP increase 200% if
compare to they paid before. 20% of respondents
choos the same condition, 19% of respondents arewilling to pay IDR 388,00 /plastic or scenario Dthat is garbage managed four times a week,
managed in the morning by garbage truck. The restor 36% of respondents chose to spread among
scenarios A, B, C, E, F. The result of the
respondent's choice is shown in Table 2 below.

Table 1: Scenarios, Services and Tariff
Scenario Services
Tariff
Scenario A
Garbage is managed 2x a 166
Starting
Point
Scenario B

Scenario C

week, in the afternoon
with a garbage car
Garbage is managed 3x aweek, in the afternoon
with a garbage car
Garbage is managed 3x aweek, in the morning,with garbage cart
Garbage is managed 4x aweek, late afternoon, bytruck
Garbage is managed 4x a
week. morning withgarbage truck
Garbage is managed 5x aweek, early morning withgarbage truck
Garbage is managed 6x aweek, morning withgarbage truck
Garbage is managed 7x aweek, morning withgarbage truck

222
277
333

Hypothesis Development

Table2. WTP of Waste Management Services Per
Plastic
WTP
Percent
Valid
166
3.0
222
10.0
277
13.0
333
7.0
388
19.0
444
2.0
500
9.0
555
37.0

Meanwhile, to obtain the second objectiveof the relationship between the characteristics ofthe respondent with the WTP he selected, thecorrelation and crosstab analysis techniques areused. The respondent's characteristic consists of 6

The result indicates that most of household's
WTP of waste management service is IDR
555/plastic or IDR 50.000/month if the services is
upgraded. The desired services is garbage collected
and transported everyday, in the morning so

Scenario D

Scenario E

Scenario F

Scenario G

388
444
500
555

1053

SEE - Nagoya, Japan, Nov.12-14, 2018

garbage is not decomposed yet and make air
pollution in the afternoon. It’s mean, WTP of thecommunity can be pushed to increase if theirsatisfaction of public services is increased.

correlation equal to 78,6%. The higher level of
education that has been taken has influenced the
respondents' mindset of environmental quality sothat their WTP increases. With higher levels of
education respondents tend to better understandabout the effect of waste on environment. Higher
knowledge raises awareness for a healthy
environment. Level of income is also correlatewith WTP with 73,3%. It means that if thehousehold has more income, they have higher

Correlation Between the Characteristics Of
Respondents with Their WTP
Relationship of some characteristics of
respondents with WTP used Pearson ProductMoment Test. Characteristics of respondents
consists of 6 elements, namely the number offamily members, the amount of income, the level of
education, the type of work, the level of satisfaction
on waste management services and the level ofknowledge of respondents about the importance ofprocessing waste and maintaining the environment.
Of the six characteristics of the household
respondents, only the type of work has nocorrelation with WTP, while five characteristics
have a positive correlation. Their effects on WTP
whenthey areinteractions each others(Makkonenn,2011). The result of the test as
follows.

paying capacity. By adding WTP to IDR
555/plastic, it doesn't matter. This finding is
supported by Feitosa et al (2017), that the
respondents' income, age and duration of school
determine WTP of waste management service. He
recommend that communities be encouraged toparticipate in waste management to safeguard theenvironment, economics, institutions and social
sustainability. Type of work is not significant
correlation with WTP. This finding is also
supported by consumption theory by Keynes, inwhich the current consumption depends on thedisposable income of household. Consumer income
will affect consumer decisions in consuming
certain goods or services. The higher the income,the higher the ability to buy goods or services. The
higher income will increase demand for better
environmental quality. Others finding, that there ispositive correlation between the satisfaction levelof waste management services with WTP. Level ofsatisfaction of respondents to waste management
services in Sukabumi, Bandar Lampung with WTP
for example, provision of public goods and services
will provide benefits for households. Guritno(2003) states theoretically, the provision of public
goods and services will be optimal if thesatisfaction obtained by households is similar to thedissatisfaction that households get by taxes/s. The
increase in the services provided is expected tohave an impact on the satisfaction of households in
Sukabumi households will increaseWTP. The
satisfaction of the household increase due to theincreasing of the quality of waste management
service. Household will pay higher for theservices. According to Hagos (2012) more services
that should be provided and enhanced by thegovernment include collection services, waste isdisposed of properly, and recycling and composting
features are added, more WTP increase. Banga et al(2011) also supports this finding that WTP for
waste management service in Kampala City,
Uganda can be improved by improving the qualityof waste services.
The knowledge level of the respondents
about the impact on the environment is correlatedwith the WTP with coefficient correlation of
56.8%. The more knowledge about environmental,
the higher their WTP. According to Ladiyance etal (2014), respondents who have good knowledge
about the benefits and damage of environment,

Table 3. Correlation Between Characteristics ofRespondents with Their WTP
Characteristiccoefficient Sign
Respondent
The of family
0,593
0,000*
memberLevel
0,786
0,000*
Education
Type of Work

0,155

0,125

Level
of
Income
LevelofSatisfaction
LevelofKnowledge*) sign on 95%

0,733

0.000*

0,740

0.000*

0,568

0.000*

There is a positive correlation between the numberof family member and WTP, with coefficientcorrelation of 59.3%. The more family number,, themore increase WTP. The effects on WTP when
they are interactions each others. While family
members become bigger, it will add family
members' information about environmental issues
because in Indonesia,environmental issues is one of
the curriculum taught in schools. This awarenesswill encourage their WTP.
Age tends to increase income and higher income
has higher opportunities to get high education andhigh education tends to increase their awarenessof environment (Makkonenn,2011). It means theawareness is also supported by education. The
result find that there is positive correlation between
level of education with WTP, with coefficient1054

SEE - Nagoya, Japan, Nov.12-14, 2018[7] Fonta.W.Metall .2008.Using A Contingent
Valuation Approach for Improved Solid Waste
Management Facility:Evidence from Enugu
State Nigeria.Journal of African Economics.
[8] Ghanem Samar Khairy. 2018.The Relationship
Between Population and The Environment and
Its Impact on Sustainable Development in
Egypt Using a Multi Equation Model
Environment,
Development
andSustainability, Volume 20, Issue 1, pp 305-340[9] Gregory O. Thomas,
Rose Fisher,
Lorraine Whitmarsh, Taciano L.
Milfont,
WouterPoortinga.2018. The impact ofparenthood on environmental attitudes andbehaviour a longitudinal investigation of thelegacyhypothesis.
Population
andEnvironment. Volume 39, Issue 3, pp 261–276[10] Hagos et all. 2012.Households Willingness To
Pay for Improved Urban Waste Management in
Mekelle City,Ethiopia. Discussion Paper
Series.nEfDDP 12-06[11] Huntari,D. 2015.
Willingness to Pay ofHousehold Analysis On Waste Management
Case Study:Rajabasa Raya, City, Indonesia.
Paper. Lampung University.
[12] Indramawan, Dandy P. 2014. WTP Analysis
Integrate tariffd Waste Management at
Kecamatan West Smarang. Diponegoro
University.Paper.
[13] James K. Boyce, 2003.Inequality andEnvironmental Protection. Paper. Political
Economy Research Institute. MIT.
[14] Ladiyance,S danYuliana, L. 2014.Variable
Effected Willingness To Pay Household at
Bidaracina Jatinegara, East Jakarta.Widya
Journal.Vol 2.No 2.
[15] Manurung R. 2008. Persepsi dan partisipasi
siswa sekolah dasar dalam pengelolaan
sampah di lingkungan sekolah. Jurnal
Pendidikan Penabur.
[16] Makkonen. M, Halttunen. V, Frank L.2011.The
Effects of Gender, Age, and Income on theWillingness to Pay for Music Downloads.
BLED Proceedings. AIS Electronic Library(AISeL)[17] Muniarti,Eindah.2017.Willingness To Pay(WTP) Analysis For The Rent of Subsided
Apartment at Keteguhan West Teluk Betung
Barat, Bandar Lampung City Of Indonesia.
Paper.
[18] Mustafa,U.et all. 2014.Capturing WTP
dan Its Determinant for Improved Solid
Waste Managemen. Pide working Paper.
No 110, Pakistan.
[19] Tansatrisna, D. 2014. Persepsi dan
Partisipasi
Rumahtanggadalam
Pengelolaan Sampah Rumah Tangga.
[20] Yunis,M, 2012. WTP Analysisi of
Houishold on Cleanness in Tampan
Pekanbaru, Riau, Universitas Riau

they will tend to be more likely to be willing topay. Finger (1994) also find that environment
experienceis
positively
correlatedwithenvironmental awareness.People who haveenvironmental experiences are willing to pay
higher. Respondents have more knowledge
respondents will do activities that are notenvironmentally damaging and are likely to bewilling to make conservation efforts environment.
5.CONCLUSIONWTP of households for waste management
services can be increased up to 200 % if the service
is upgraded. There is a positive correlation between
characteristic of respondents such as, the level of
education, the level of satisfaction, income, level ofsatisfaction, and knowledge of respondents to their
WTP except type of work,. Local government
needs to review the local regulation concerning
WTP and better services. It is neccesary forgovernment of Indonesia to review local regulationof waste services by paying attention to WTP .
Government should be
upgraded the public
services and training for household to processing
rubbish by sorting, selecting, utilizing and dispose
waste wisely.
REFERENCES[1] Afroz,R.2011.UsingaContingent
Valuation
Aproach for Improved Solid Waste
Management Facility.Journal Elsevier
Waste
Management, Vol.31.800-808.
[1] Aminrad,Z, Sharifah ZB, Sayed ZASH,
MahyarSakari.2013. Relationship Between
Awareness, Knowledge and Attitudes
Towards Environmental Education Among
Secondary School Students in Malaysia.
World Applied Sciences Journal 22 (9):1326-1333.
[2] Banga, Margaret. 2011. Households
Willingness to Pay for Improved Solid
KampalaWaste Collection Services in
City, Uganda. The Journal of Environmentand Development.
[3] Brahim, Djemaci. 2015. Using a Contingent
Valuation Approach for Improved Household
Solid Waste Management in Algeria. Munich
Personal.
[4] Chutarat Chompunth. 2017. Role of Public
Participationin
Environemnetal
ImpactAssasement in Thailand. International Jurnalof GEOMATE. Volume 12. Issue 33.
[5] Feitosa, Anny K.2017. Economic Valuation of
Urban Solid Waste: A Review. Revista
Spacious.Vol 38 No14.pp1[6] Finger, M. 1994. From Knowledge to Action?
Exploring
The
Relationship
BetweenEnvironmental Eperiences, Learning, andBehavior. Journal of Social Issues 50 (3),141160.

1055

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

BIOETHANOL PRODUCTION FROM AGRICULTURAL PRODUCTS
AND FRUITS OF BANGLADESH
Md. Abul Kalam Azad*1 and Nilufa Yesmin2
1,2Institute of Environmental Science, University of Rajshahi, Rajshahi-6205, Bangladesh

ABSTRACT
Bangladesh is an energy deficient country. Petroleum is the main energy source of Bangladesh imported from
the Middle East spending a huge amount of foreign currency. However, the sub-tropical climate of Bangladesh isfavorable for cultivation of different agricultural products and fruits. This research was carried out to find out thepotentiality of bioethanol production from different agricultural products and fruits of Bangladesh. In 100 gm ofagri-products (boiled) and fruits (ripen), 300 ml of distilled water was added and blended and then sterilized.
Alpha-amylase enzyme (1750 unit) was added to degrade the starch into simple sugar compound. For alcoholic
fermentation, 200 ml yeast (Saccharomyces cerevisiae CCD) was added to make the total volume 500 ml andincubated at 31oC for 6-days. From the fermentation of agri-products (potato, sweet potato, corn, pumpkin andcarrot), a highest bioethanol production was observed in sweet potato. Bioethanol production capacity of four
fruits (orange, banana, papaya and sofeda) was also assessed. A high yield of bioethanol was found from a local
variety of banana called Sagor Kola. The purity of bioethanol in single distillation for banana and sweet potato
was 40% and 35%, respectively. This research proved that Bangladesh has a good prospect of bioethanol
production from banana and sweet potato.
Key words: Bioethanol, Agricultural products, Fruits and Fermentationagri-products and ripen fruits such as bananas,
papaya, orange and sofeda were studied.

INTRODUCTION
Bioethanol is considered to be the most optimistic
biofuel. Ethanol fermented from renewable sources
for fuel or fuel additives is known as bioethanol.
Bioethanol, unlike petroleum, is a form of renewableenergy source that can be produced from agricultural
feedstocks [1]. The first generation of ethanol
production used corn as a substrate, later corn wasconsidered as a feedstock lead to the second
generation of production of ethanol which usedmicroorganisms and different wastes as a substrates[2]. The cheapest and easily available source for the
production of bioethanol is fruit wastes. It is apotential energy source, from which ethanol can beobtained. Fruit waste which is thrown away has very
good antimicrobial and antioxidant potential.

The objective of this study is to determine theproduction efficiency of bioethanol from different
agri-products and ripen fruits of Bangladesh.
MTERIALS AND METHODS
Raw Material Collection
The agri-products (potato, sweet potato, corn,
pumpkin and carrot) and fruits (orange, banana,
papaya and sofeda) were collected from the local
market of Rajshahi city, Bangladesh.
Yeast Strain and Culture Media
Yeast strain (Saccharomyces cerevisiae CCD) wascollected from the Spirit Section of Carew and Co.,
Darsana, Bangladesh. For yeast culture, modified
YMPD (Yeast-Malt-Peptone-Dextrose) broth culture
media was used. The YMPD media was preparedwith yeast extract (3.0 g), malt extract (3.0 g),
peptone (5.0 g) and dextrose (10.0 g). All of these
ingredients were dissolved in 1000 ml of water andadjusted to pH 6.0.

Rapid increase of population and exponential growth
on industrialization load on fossil fuel resources andthe resources are being depleted very fast. Therefore,
it is required to discover alternative cheaper sourcesof fuel for fulfillment of worldwide demand. The
main task is to develop easier techniques by using
cheaper source for the production of bioethanol sothat the common people can also produce it bythemselves. For this purpose fruit wastes were taken
as a substrate for the ethanol production with use ofyeast Saccharomyces cerevisiae [3]. In this study,
comparison of bioethanol production from different

1056

SEE - Nagoya, Japan, Nov.12-14, 2018

large amount (95 ml) of bioethanol with 35 % (v/v)
purity and after fermentation the sugar concentration
was reduced to 5.9 mmol/L from 14.9 mmol/L. The
lowest amount of bioethanol was produced frompumpkin with purity of 6% (Table 1).

Production of Bioethanol from different AgriProducts
About 100g of agri-products (potato, sweet potato,corn, pumpkin and carrot) was boiled blended in 300
ml distilled water. About 1750 unit of α-amylase
enzyme and 200 ml of 2-days old yeast were added
to each treatment and adjusted to pH 6.0, andincubated at 31˚C for 6-days. After incubation
period, turbidity of solution and produced ethanol
were measured.

Table 1 Bioethanol production from different agriproducts
Name ofAgriproducts

Bioethanol Production from different Ripen
FruitsPotatoSweet
PotatoCorn
Pumpkin
CarrotDifferent ripen fruits like banana, orange, papaya
and sofeda pulps were extracted by blending withblender machine. The fruits fresh or blanched weremashed. Then it was used as raw materials forbioethanol production. For optimum bioethanol
production 200 ml of 2-days old yeast was added in
300 ml fruit pulp solution (20%), adjusted to pH 6.0,
and incubated at 31˚C. After 6 days of fermentation
the crude fermented fruit solution was firstcentrifuged at 12,000 rpm to remove the unused
starch and yeast cell. Then, the clear solution was
taken into rotary evaporator for separation of ethanol
at 78.5˚C for five minutes.

Volumeafter
fermentation
(ml)
465
487

Volumeafter
distillation
(ml)
67
95

Purity of
Bioethanol% (v/v)

449
466
459

82
64
70

15
6
10

18
35

Ethanol production from spoiled starch richvegetables by sequential batch fermentation wasstudied by Satish [4], Kumar et al. [5] used sweet
potato as raw material for the production of ethanol
and the production was only 0.15%. This vast
variation may due to the larger amounts offermentable sugars are present in agri-products.

Estimation of Total Sugar before and after
Fermentation

Bioethanol Production from different Ripen
FruitsTotal sugar content was determined by sugar
measurement machine named "On Call Plus". Sugar
concentration before and after fermentation were
measured.

The study of bioethanol production from ripen fruits
like orange, banana, papaya and sofeda has not bedone widely,so the present investigation was
carried out for the production of ethanol with ripen
fruits. The productions of bioethanol from four
different ripen fruit pulps (orange, banana, papaya,
sofeda) were assessed during this study. Sugar
content in banana (27.9 mmol/L) was higher thanother three fruits and it produces a large amount (97ml) of bioethanol with 40 % (v/v) purity and after
fermentation, sugar concentration is reduced to 12.8mmol/L from 27.9 mmol/L . The lowest amount of
ethanol was produced from sofeda (Table 2).

Distillation Process
Distillation was carried out using a distillation
apparatus. Heating of fermented materials was
carried out at 78.5°C.
Measurement of Purity of Produced Alcohol
The percent of purity of produced bioethanol fromagri-products and fruits was measured by using an
alcohol meter (Jiujingnongduji, China). This metercan measure the alcohol purity from 0-100%.

Table 2 Bioethanol production from different ripen
fruitsRESULTS AND DISCUSSION

Nameof
Fruits

Production of Bioethanol from different AgriProducts

OrangeBananaPapayaSofedaBioethanol production from five different agriproducts (potato, sweet potato, corn, pumpkin,carrot) were assessed. It was found that sugar
content in sweet potato (14.9 mmol/L) is higher thanother four agri-products. Sweet potato produces a1057

Volumeafter
fermentation
(ml)
482
493
460
445

Volumeafter
distillation
(ml)
87
97
83
81

Purity of
Bioethanol% (v/v)
30
40
20
18

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 3 Bioethanol production
varieties of banana

This result is quite similar with some studies ofbanana waste [6]. The amount of produced ethanol
in present study is higher compare to the studies of
Hossain et al. [7] and Kumar et al. [5]. Hossain etal. [7] reported that rotten pineapple produces 8.7%
ethanol.

BananaVarieties

Sagor
Sabri
Chinichampa
Bichikola

Bioethanol Production from different Varieties ofBananaThe bioethanol production from four different
varieties of banana (sagor, sabri, chinichampa andbitchi kola) was assessed. It was shown that thesugar content in sagor kola (27.9 mmol/L) is higher
than other three varieties of banana and it produces alarge amount (97 ml) of bioethanol with 40 %(v/v)
purity and after fermentation the amount of total
sugar was reduced to 13.8 mmol/L from 27.9mmol/L. The lowest amount (81 ml) of ethanol was
produced from bitchi kola with purity of 20% (Table
3).

from

different

Volumeafter
fermentation
(ml)
493
486
460

Volumeafter
distillation
(ml)
97
87
83

Purity of
Bioethanol% (v/v)
40
30
35

445

81

20

CONCLUSIONS
From this study we conclude that sweet potato andbanana are the good and cheaper sources forbioethanol production. These sources can be used
for small and large scale production of bioethanol
because sweet potato and banana are available
everywhere in Bangladesh.

According to Hossain et al. [7], 900g of rotten
banana with 35% distilled water adding 3g/L yeast
and adjusted pH at 5.8 was incubated at 35oC for 3
days and found the bioethanol purity only 7.1%(v/v).

The production of ethanol from the agri-products
and fruits can be improved further by using
genetically engineered yeast strains that are capableof converting multiple sugars in to ethanol and usingof proper distillation process for increasing thepercentage of purity of produced bioethanol.

Janani et al. [8] observed the rate of ethanol
production through fermentation of apple, grapes,
papaya and banana waste by Saccharomyces
cerevisiae at pH 5.4 and temperature 30oC,
bioethanol and observed the yields 4.73%, 6.21%,
4.19% and 5.4%, respectively.

REFRENCES[1]

Singh, A., and Jain, V.K., Batch fermentationof cane molasses for ethanol production by
Zymomonas mobilis. Journal of Indian
Chemical Engineering, Vol. 37, 1995, pp.8094.

Kumoro et al. [9] used jackfruit juice and theethanol production was 12.13%. Ethanol yield in
fruit pulps varied significantly between the fruit[2] Grassi, M., Modern Bioenergy in the European
samples and the highest yield was 35.86% in theUnion. Renewable Energy, Vol. 16, 1999,
mixed fruit pulps sample, followed by 28.45% in
pp.985-990.
banana pulp and the lowest yield was 26.5% inmango pulp. The fermentation of enzymatic G [3]Gohel, H.R., Ghosh, S.K. and Braganza, V.J.,
hydrolysis of acid pretreated mixed fruit pulps
Yeast as viable and prolonged feedstock for(banana and mango) by yeast showed an incubation
biodiesel production. International Journal of
period of 48 h as optimum for maximum ethanol of
Renewable Energy Research, Vol. 3(1), 2013,35.86% corresponding to a fermentation efficiency
pp. 126-131.
of 70.33%. In peels samples, the maximum yield[4] Satish, B., Ethanol production fromwas 13.84% in banana and 9.68% in mango at 42 h
spoiled starch rich vegetables by sequential
of incubation. The results of present ethanol yieldbatch fermentation. International Journal ofare similar to the observations of Sirkar et al. [10] in
Biotechnology & Biochemistry, Vol. 3, 2010,
the case of banana. This observation is consistentp. 351.
with the report of Akin-Osanaiye et al. [11], whichindicated that the amount of yeast influenced ethanol[5] Kumar, A., Kumar, N., Baredar, P. and Sukla,
production in agro wastes. The current observations
A., A review on biomass energy resources,
are in good agreement with similar results reported
potential, conversion and policy in India
by Pramanik and Rao [12] for grape waste.
Renew. Sustain. Energy Rev. Vol. 45, 2015,
pp. 530-539.
1058

SEE - Nagoya, Japan, Nov.12-14, 2018[10] Sirkar, A., Das, R., Chowdhury, S. and Sahu,
S.J., An experimental study and mathematicalmodeling of ethanol production from banana
peels by hydrolysis and fermentation.
International Journal of Science and Research,
Vol. 88, 2008, pp. 4-10.

[6] Snehal R. Patil and Gaurav A. Zope., Productionof Biofuel from Banana waste. International
Journal of Innovative Research in Science,
Engineering and Technology, Vol. 6, 2017, pp.
551-554.
[7] Hossain, A.B.M.S. and Fazliny A.R., Creation ofalternative energy by bioethanol production
from pineapple waste and the usage of its
properties for engine), Afr. J. Microbial. Res.
Vol. 4(9), 2010, pp.813-819.
[8][11] Akin-Osanaiye, B.C., Nzelibe, H.C. andAgbaji,A.S., Production of ethanol from(papaw) agro waste: effect of saccharificationand different treatments on ethanol yield.
African Journal of Biotechnology, Vol. 4 (7),2005, pp.657-6 59.

Janani, K., Ketzi, M., Megavathi, S.,
Vinothkumar, D. and Ramesh, B.N.G.,
Comparative studies of ethanol production fromdifferent fruit wastes using Sacchromyces
cerevisiae. International Journal of Innovative
Research in Science, Engineering andTechnology, Vol. 2, 2013, pp. 7161-7167.

[12] Pramanik, K. and Rao, D.E., Kinetic study on
ethanol fermentation of grape waste using
Saccharomyces cerevisiae yeast isolated fromtoddy. IE (I) Journal, Vol. 85, 2005, pp.53-58.

[9] Kumoro A.C., Rianasari D., Pinandita A.P.P.,
Retnowati,
D.S.
and
Budiyati,
C.S.,
Preparation of Wine from Jackfruit (Artocarpus
heterophyllus lam) Juice using beaker yeast:
Effect of yeast and initial sugar concentrations.
World Applied Sciences Journal, Vol. 16, 2012,
pp. 1262-1268.

1059

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ISOLATION OF STRESS TOLERANCE YEAST STRAIN FROMPAPAYA WASTES
Gemilang Lara Utama1,2, Dwi Wahyudha Wira3 and Roostita L. Balia3
Faculty of Agro-Industrial Technology, Universitas Padjadjaran, Indonesia;
2
Center for Environment and Sustainability Science, Universitas Padjajaran, Indonesia;
3
Faculty of Veterinary Medicine, Universitas Padjajaran, Indonesia
1

ABSTRACT
Papaya wastes is naturally fermented and potentially overgrown by microorganisms such yeasts. The researchaims to determine the presence of ethanol-fermenting yeasts on papaya wastes which has the ability to toleratehigh glucose and ethanol contents. Yeasts isolated from papaya wastes with using Potato Dextrose Agar/PDA
which modified with 3% yeast extract/YE and 10 ppm Amoxicillin, then incubated for 48h at room temperature.
The isolates were identified macroscopic and microscopically then the yeast-like isolates cultured on Nutrient
Broth/NB with the addition of 3% YE, 10 ppm Amoxicillin and 30% glucose or alcohol to be tested for thetolerance ability towards high glucose and alcohol. Yeasts presence on high glucose and alcohol media wasdetermine by UV-Vis spectrophotometer by measuring optical density (OD) for UV absorbance at λ=600nm. The
isolate with highest OD at glucose and alcohol media grown at papaya wastes for 72h and the ethanol contents
measured by chromium dichromate oxidation methods every 24h. Species identification performed using sequence
analysis of the rRNA gene internal transcribed spacer (ITS) region with using primers ITS1 (5′TCCGTAGGTGAACCTGCGG-3′) and ITS4 (5′-TCCTCCGCTTATTGATATGC-3′), the sequences comparedwith the GenBank database using Basic Local Alignment Search Tools/BLAST algorithm. The results showed thatthree yeast-like isolates found from papaya wastes, with Y1 isolate identified as best isolate with the OD of 0.4699
at 30% glucose media and OD of 0.0960 at 30% alcohol media, with the highest ethanol fermented at 48h was
4.34%. The rate of isolate identification by sequence analysis resulted 96.20% (531/552) identical with Pichia sp.
strain AQGWD 7.
Keywords: Papaya, Wastes, Yeasts, Stress, Tolerance
isolated from papaya wastes is still rarely revealed
especially for the ability in ethanol production.
Kowser, et al. [8] has been isolated the potential
acetic acid bacteria from rotten papaya that potential
in utilizing ethanol for producing acetic acid. The
latest research has been isolated yeast from various
agriculture wastes including papaya that has xyloseutilizing ability in producing ethanol [9].
Yeasts has been known as the best
microorganisms for ethanol producing activity,
however yeasts with the ability in tolerating stresswhen the ethanol production occurs still hard to find[10] [11].
High sugar and ethanol stress was the common
inhibitor when the ethanol fermentation occurs [12][13] [14]. Both conditions could influence theosmotic pressure or membrane fluidity which disturbs
yeasts growth and ethanol fermentation process [15].
Thusly, indigenous yeasts with the ability to toleratehigh sugar and ethanol in ethanol fermentation stillneed to discover.

INTRODUCTION
Papaya (Carica papaya) waste is the second
highest fruit wastes found in wet market particularly
in West Java, Indonesia. As one of the featured
product of West Java, papaya is constantly available
in every season. However, the number ofunderutilized papaya wastes had demonstrated thepotential usage or unsettling influence that can become about.
The plenitude of papaya waste has been raising anapproach to increase its economic value. Papaya
waste commonly utilized for livestock feed or crudematerial of compost [1] [2]. Others started to create
papaya as a biomass of crude materials for the makingof sustainable power sources such biogas [3] [4].
Other sustainable power source that can be createdfrom papaya biomass is ethanol [5] [6].
Papaya wastes contain high complex saccharide
in a form of lignocelluloses which could behydrolyzed into D-glucose and D-xylose thenconverted furthermore into ethanol by microorganism[7]. However, papaya wastes potential in ethanol
fermentation is not just resulted from its complexcellulose compound yet in addition from thebiological aspect that represented by the existence ofindigenous microorganisms which naturally
fermenting ethanol when the putrefaction occurs [8].
The potential of indigenous microorganisms

MATERIALS AND METHODS
Indigenous Yeasts Isolation from Papaya Waste
Papaya waste was randomly collected from thelocal market in Bandung City, Indonesia, blended
aseptically then transferred into containers and stored
in the refrigerator. Using Potato Dextrose Agar/PDA
1060

SEE - Nagoya, Japan, Nov.12-14, 2018

(Oxoid Ltd.) which modified with 3% yeast
extract/YE (Kraft Inc.) and 10 ppm Amoxicillin,indigenous yeasts isolated from papaya wastes thenincubated at room temperature for 48h. The
morphological characteristics of indigenous yeasts
was identified macroscopic and microscopically [15][16].

best isolates that shown OD of 0.4699 and 0.4656
respectively while Y3 reach OD of 0.4034.

Stress Tolerance Tests
To determine indigenous yeasts tolerance ability
towards stress caused by high glucose and ethanol
contents, 30% glucose or alcohol added into Nutrient
Broth/NB (Oxoid Ltd.) modified with 3% yeast
extract/YE (Kraft Inc.), 10 ppm Amoxicillin.
Spectrophotometer UV-Vis used for measuring
optical density (OD) at λ=600nm to determine yeastspresence on high glucose and alcohol media [15].
Ethanol Fermentation
Papaya waste weighed and blended asepticallywith the dilution ratio of 1:1.5. Indigenous yeast withstress tolerance, cultured at papaya wastes in room
temperature for 72h. The ethanol that resulted wasmeasured by chromium dichromate oxidation
methods every 24h [15] [16].

Fig. 1

Indigenous Yeast Species IdentificationrRNA gene internal transcribed spacer (ITS)
region was used to identify indigenous yeast species,
using sequence analysis of the with using primers
ITS1 (5′-TCCGTAGGTGAACCTGCGG-3′) and
ITS4 (5′-TCCTCCGCTTATTGATATGC-3′). The
gene sequencing has been done by Macrogen Inc., thesequence results then compared with the database of
GenBankusing
BLAST
algorithm(https://blast.ncbi.nlm.nih.gov/Blast.cgi) [17].

Y1 (a)

Y1 (b)

Y2 (a)

Y2 (b)

Y3 (a)

Y3 (b)(a) macro and (b) microscopic (1000x
magnification) morphology of indigenous
yeasts colony (Y1, Y2, Y3)
0.70

Optical Density

0.60
0.50
0.40
0.30
0.20
0.10
0.00
Y1

RESULTS AND DISCUSSIONS

Y2

Y3

Isolates of yeasts

Morphological Characteristic of Papaya
Indigenous Yeasts
Indigenous yeasts isolation results showed thatthree yeast-like colonies have been identified frompapaya wastes (Fig. 1). According to morphologicalcharacteristics, the three isolates could be categorized
as yeast. The isolates has cell length of 1-5 µm up to
20-50 µm, width of 1-10 µm also has unicellularcolonies, round, ouval, long shaped with theestablishment of pseudomycelium [18]. The results
also in accordance with the characteristic of yeasts
strain that isolated from papaya which has smoothsurface, spherical or ouval shape, creamy white color
and presence of pseudomycelium [16].

Fig. 2

Yeast optical density on high glucose media

Determination of glucose-tolerance was done todecide the capability of indigenous yeast isolated
from papaya waste in generating ethanol on highosmotic pressure condition [19]. Mostly yeast growth
was inhibited by the osmotic pressure that resulted
from high contents of sugar up to 30 % [20] [16].
However, higher ethanol also could be resulted
from high sugar available because ethanol generated
from sugar fermentation by microorganism [21]. The
rate of ethanol generation was also influenced bysugar concentration [19]. Therefore, the ability intolerating high glucose contents was important inresulting high ethanol.
At the beginning of fermentation, yeasts with theability to tolerate osmotic pressure could consume
glucose, doing glycerol synthesis and producing low

Yeasts Tolerance towards High Glucose
High glucose tolerance test results (Fig. 2) showedthat all of the indigenous yeasts can be survived at
30% of glucose content media with Y1 and Y2 as the1061

SEE - Nagoya, Japan, Nov.12-14, 2018

% Ethanol Contentsacid [22]. High glucose osmotic stress can becombated by efficient glycerol transport into inside
the yeasts cell [23]. Assimilation succinic and acetic
acid by several non-Saccharomyces yeasts could help
in surviving the osmotic stress condition [22] [24].
Yeasts Tolerance towards High Ethanol
Figure 3 has been shown all the indigenous yeast
isolates had tolerance ability towards high ethanol up
to 30% which determined by optical density of
isolates Y1 (0.096), Y2 (0.075), and Y3 (0.070). The
yeast presence on high ethanol environment due tonormally papaya waste contains high sugar and theethanol was accidentally generated when theputrefaction occurs.
High ethanol contents could delay the growth ofyeasts [25]. Ethanol interrupt the permeability ofyeast cell wall then the sorting and signaling function
will be disturbed so that the growth, fermentation andviability of yeasts cell also decrease [26]. Therefore,
ethanol tolerance test was performed to find out theindigenous yeast capability in tolerating stressresulting from high ethanol.

Optical Density

2.0

0

24

48

72

Hours

Fig. 4

Ethanol fermentation

After the growth end, non-Saccharomyces yeasts
have respiro-fermentative regulatory mechanism thatcan decrease ethanol contents [31]. Carbon source
available is consumed for respiration so that theethanol decreases [32] [33].
Yeast Identification
Gene sequencing results (Table 1) showed that the
ITS1 primer gained 725 of 756 (95.90%) sequences
identical with Pichia sp. stains QAUPK01(KT987926.1) and the nearest phylogenetic relatives
which shown by the tree (Fig. 6). Meanwhile, theresults of ITS 4 primer had shown higher identicalsequences with 531 of 552 (96.20%) identical with
Pichia sp. stains AQGWD7 (KP721590.1) with thenearest phylogenetic relatives shown by Fig. 7. The
indigenous yeast isolate has close relatives with
Pichia kudriavzevii, Candida xylopsoci, andIssatchenkia sp.

0.120
0.100
0.080
0.060
0.040
0.020
0.000
Y2

3.0

1.0

0.140

Y1

4.0

Y3

Isolates of yeasts

Table 1 Results of Yeast Identification
Fig. 3

Yeast optical density on high ethanol media

PrimerIdentities
Percent Identities
Nearest phylogenic relative
StrainAccession number

Ethanol fermentation
Indigenous yeast isolate of Y1 chosen as bestisolate with the ability in tolerating glucose andethanol up to 30% then used to ferment the papaya
waste for resulting ethanol. The results (Fig. 4)
showed that the ethanol contents tend to increase until
48h with the contents of 4.34±0.086 %, then decreaseat 72h (1.28±0.001 %).
Natural ethanolic fermentation usually occurs anddominated by non-Saccharomyces yeasts at the earlystages of fermentation [27]. The dominance will lastfor 2-3 days and affect the ethanol contents until 5%then decrease [28].
Early fermentation has shown the high rate ofyeasts growth by utilizing amino acids and vitamins
for continuing the ethanol fermentation [29]. Organic
acids, esters, and ethanol dominated the early stage
fermentation which resulted from β-glucosidase, βxylosidase and some proteases enzyme [20].

ITS1725/756
95.90
Pichia sp.
QAUPK01
KT987926.1

ITS4
531/552
96.20
Pichia sp.
AQGWD 7
KP721590.1

Pichia kudriavzevii previously known as
Issatchenkia orientalis has been isolated from various
natural sources and used for ethanol production.
Some other strain of Pichia kudriavzevii also shown
tolerance towards acid, ethanol, thermal and salt
stress with higher thermotolerant activity thanconventionally used ethanol-fermenting yeasts i.e.
S.cerevisiae [34]. Pichia kudriavzevii is acidophilic
yeasts which grow better under acidic conditions (pHof 4-6) that could lead the intracellular enzymes for
optimal sugar conversion to ethanol and the otherstudy mentioned that the yeast presenting ethanol
tolerance ability[35] [36].
The ability of indigenous non-Saccharomyces
yeasts in naturally grown and producing ethanol atroom temperature has been escalated since the1062

SEE - Nagoya, Japan, Nov.12-14, 2018ethanol-tolerance ability characterized [37]. Gidado,
et al. [36] found that indigenous yeast species withidentical sequence of 97-98% to Pichia kudriavzevii
has the ability to grow and ferment ethanol up to 20%

v/v. Pichia kudriavzevii strains GY1 was the mostadaptive, efficient and effective in various sugas(fructose, galactose, glucose, lactose and sucrose)
utilization for ethanol production [38].
Y1_ITS1

Fig. 6

ITS1 Phylogenetic Tree
Y1_ITS4

Fig. 7

ITS4 Phylogenetic Tree

CONCLUSION
Three yeast-like colonies isolated from papaya
wastes. Isolate Y1 chosen as best isolate in toleratingstress from glucose and ethanol contents up to 30%
with the OD of 0.4699 and 0.0960 respectively. The
chosen indigenous yeast isolates fermenting
4.34±0.086% v/v ethanol from papaya waste for 48h.
Gene identification gained 96.20% (531/552)
sequence identical with Pichia sp. strain AQGWD 7.

ACKNOWLEDGEMENTS
Author would like to thank Rector of Universitas
Padjadjaran for the Research Fundamental Grant ofHibah Internal Unpad and Travel Award 2018. Also
thanked the Student Research Group, Vivi Fadila
Sari, Isfari Dinika and Syarah Virgina who helped in
the laboratory.

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Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

MOBILE DEVICES: ITS IMPACT TO ACADEMIC PERFORMANCE

1

Charito G. Ong1, Cipriana P. Flores2
University Registrar, University of Science and Technology of Southern Philippines, Cagayan De Oro City
2
Senior Faculty, San Isidro College, Malaybalay City

ABSTRACT
Notwithstanding the step up in educational indicators like college attendees, noteworthy challenges linger
concerning the delivery of quality education in both public and private institutions. To ably find feasible
resolutions to these challenges, a large amount of hope is placed in new information and communication
technologies (ICTs), mobile phones being one example(Ramos,2008). This paper evaluated the crucial role ofmobile phone-facilitated learning to enhance educational outcomes in Capitol University by investigating theresults of mobile learning intervention. Specifically, this research examined the impact of mobile phones toCollege English performance in two specific ways: 1) its influence to language ratings, and 2) in promoting
communicative competence. Analysis of the language classrooms through classroom observation indicated that
there is relevant evidence of mobile phones facilitating students’ communicative competence in their English
language classes. Mobile learning, or mLearning, in this paper takes advantage of opportunities offered byportable technologies. The term covers: learning with portable technologies, where the focus is on thetechnology which could be in a fixed location, such as a classroom; learning across contexts, where the focus
is on the mobility of the learner, interacting with portable or fixed technology; and learning in a mobile society,with a focus on how society and its institutions can accommodate and support the learning of an increasingly
mobile population (Atkinson, 2007). The concept of mobile learning understood as learning facilitated bymobile devices in this paper gains toehold in the academic society. Findings of the rising number of mLearningassociated by the development of students’ communicative competence earned focus here as well. With theescalating interest now being given to the function of mobiles in the educational sector of the academe, there
is a need at this point in time to take stock of the available evidence of the educational benefits that mobile
phones provide towards students’ language competencies. Thus, this paper explores the results of observing
mLearning-abled-students that took place in Capitol University in relation to their Language performance intheir English classes. In exploring how mobile phone-facilitated mLearning contributes to improved language
competencies, this paper earned two specific issue-results: 1) the influence of mobiles in English Language
performance was declared highly significant based on findings, and 2) the role of mobiles in promoting
students’ communicative competence was rated highly exceptional. Of note, the classes observed mostly usedmobile phones in their language classes. The formation of this paper flows as follows. After the introduction,
the paper slots in with the literature that discusses how mobile technology can address interrelationship with
communicative competencies. The paper then examines college English classes that involved the use of mobile
phones as a teaching methodology. The paper wraps up with a discussion of the potential of mobile phonefacilitated mLearning in improving language skills as well as with indications for possible future areas ofresearch.
Keywords: Mobile phones, mobile learning, communicative competence, information and communication
technologies, language ratings
the workplace outside the office (21%), outdoors(5%), in a friend's house (2%), or at places ofleisure (6%). Other locations reported (14%)
included places of worship, the doctor's.

INTRODUCTION

Mobile learning is considered special compared toother types of learning activity. An essential casein point is that learners are continually on themove; hence a proof. A study by Vavoula (2005)
of everyday adult learning found that 51% of thereported learning episodes took place at home or in
the learner's own office at the workplace, i.e. at thelearner's usual environment. The rest occurred in

In the context of language education, this reality
exists outside the formal learning environment.
The history of simulations in language education
goes back to the time when language learning wasformulated as "communicative competence".

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SEE - Nagoya, Japan, Nov.12-14, 2018

Language education operationalized this insight inthe concept of "task" (Prahbu, 1987). Where tasks,
so to speak, involved simple hypotheses aboutcommunicative functions, simulations represented
a more sophisticated way to "orchestrate" the quest
for communicative competence. A wide range of
exciting simulations were invented and tested
through role play, reflecting real authentic
linguistic situations.

means of helping people to acquire foreign orsecond language skills (Crookall & Oxford 1990,
Baltra 1990, Li & Topolewsky 2002, GarciaCarbonell, Rising, Montero and Watts 2001).
In the recent years until today, learning comes incoexistence with mobile devices used by themillennial-learners. Though educators haverecently voiced concern about the detrimental
effect that text messaging is having on teenagers’
vocabulary; it is still mostly utilized in extending
students’ vocabulary.

From a recent review in languages, technology andlearning (Milton 2006) posited that learning alanguage is different from any other subject in the
curriculum. It combines explicit learning of
vocabulary and language rules with unconscious
skills development in the fluent application of boththese things. For language learners, this implies
that they should be able to master both
grammatical knowledge and fluency, the latterbeing often difficult to provide in classrooms
where a couple of lessons a week may fail toprovide the meaningful exposure to the foreign
language required for learning. Games andsimulations have been part of second and foreign
language education for decades (Crookall 2007, Li& Topolewski 2002). Simulation/gaming
techniques proved to be an extremely powerful

Simulations

Figure 1 below illustrates in schematic form thetheoretical components of this research showing
the relationship between the different elements ofthe study model.
The students’ language performance takes themain role in the model. In the academe, thestudents are considered as the core in the process.
To meet the objectives for them to learn, different
strategies are employed. Teachers make use ofsimulations, games, language guides, mobile
phones, and web-chat. The end all specificallycontribute to the development of students’language competence and academic rating.

Games

Mobile City andLanguage Guides

Students’ Language
Performance

Text-Based Web Chat

Mobile Phones in
Vocabulary Learning
Language ratingsand competence

Fig.1

The theoretical framework of the research

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SEE - Nagoya, Japan, Nov.12-14, 2018
METHODOLOGY

their mobile devices. The students
identified challenges related to theworkings of the mlearning system.

This research was done using teacher and student
questionnaires, students’ reflective diaries,
impromptu feedback from students and teacherswhich were gathered in the school through a focus
group discussion. Observation of classes was
likewise employed for two weeks with an hour
daily session.

4.

In the focus group discussion, students
made suggestions for improvements tothe system should the mlearning be
extended. They wanted more experiencesof it in their other classes; not only inEnglish subject. Moreover, teacherscommented positively on the shift from
more teacher-led learning to student-led
learning that mlearning allowed.
Teachers noticed increased motivationand student interest for using English.
They stated that students found using thetechnologies more interesting and funcompared with the traditional learning
methods.

5.

Teachers also observed as manifested in
the questionnaire answer that students
learned certain topics faster when using
the technologies. Teachers’ perspectives
on the technology impact were also
positive. They reported enjoying the shift
from providing feedback in a traditionalmanner using ‘a red pen’ to more modern
ways via feedback sheet. They alsocommented favorably on their increased
ability to hear more from those students
who are usually shy in the classroom
therebypromotingstudents’communicative competencies. Teacherscommented on the success of the textmessage delivery of English vocabulary –to such an extent that students requested
that they could receive vocabulary during
their summer break to their personal
mobile phones. Likewise, teacherscommented that for the entire term,
students’ language ratings improved.

6.

Though some students switched phones
and others dropped out without advising
their teachers, it was observed in theclassroom observation done by the
researchers that students were given
enough time to communicate. They were
excited to share their experiences using
the mobile phone as a tool. Most of thestudents were confident and revealed
communicative competence as theyphased on with the activities.

The questionnaire content focused on how students
fair in their classes with the aid of mobile phones.
Similar topic was sought for in the students’reflective diary, impromptu feedback and focus
group discussion. Moreover, in the classroom
observation, the researchers took notes of thestudents’ speaking engagement time.
FINDINGS

The following findings were found out in the
conduct of the study:
1.

Both students and teachers stated thatstudents had made progress in speaking
English as a result of being immersedwith the learning. Students remarked onprogress made in comprehension,competence, grammar and vocabulary.
Students regarded the integrated
technologies as a positive move from
more traditional methods of learning
English. They embraced the ‘new age’technology and it proved to break down
barriers to students’ learning andspeaking of English. 95% of respondents
reported that they had ‘enjoyed’ using thetechnology for teaching and learning
English.

2.

Students also reported a reduced amountof pressure in communicating throughEnglish using the integrated technologies
than they usually experienced in face-toface settings in the classroom. Students’abilities tolearn autonomously wereenhanced – the technologies facilitatedlearning at any time, in any place and at
the students’ own pace. 93% of students
recommended that other students should
also be given the opportunity to use thetechnologies for learning and practicing
English.

3.

In the reflective notes, 35 respondents
commented that they, as mobile learners
began to expect and demand the ability to
seamlessly manage and synchronize
assignment access, delivery, review andcompletion between their desktop PC andCONCLUSIONSThe subsequent conclusions were drawn from thefindings of this study:

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SEE - Nagoya, Japan, Nov.12-14, 20181.

Keegan (2003) says mobile learning will
provide the future of learning. This
statement was proven true for thisresearch and has provided an insight into
the role mobile learning could play in the
future of the English language. The
ability of teachers and students alike toembrace the change is vital. The students’
self-esteem were boosted through the useof mobile phone as a tool for learning.
Learning was fun for them, not a chore.

2.

The respondents that followed the SMS
modules indicated that the modules
enabled them to pursue their school work
according to their own schedule.
Obviously, the mobile learning systemenabled these students to have higher
ratings and communicate effectively inEnglish. Some students even pointed tothe added benefit of being able to do theirlessons during breaks.

3.

Overall, the students’ expressed interestin following modules covering theirEnglish subject areas was an amazing
edge.
They
likewise
expressed
excitement regarding the use of mobiles
for learning. Hence, mobile learning must
be considered as a must for use in thetertiary level in the Philippine school
system.

Languageacquisition, The Modern
Language[2] Journal, Volume 86, Issue 4, Date: December
2002, Pages: 525-545[3] Baltra, A. (1990) Language Learning ThroughComputer Adventure Games. Simulation &Gaming 21, 4.
[4] Bo-Kristensen, M., Ankerstjerne, N.,
Neutzsky-Wulff, C. & Schelde H. (2008)
Mobile City and Language Guides: New
Links Between Formal and Informal Learning
Environments,in:Remenyi,D.
(ed.)
Proceedings of the 7th European[5] Conference on eLearning. Reading, UK:
Academic Conferences Limited[6] Crookall, D. & Oxford, R.L. (1990)
Simulation, Gaming, and Language Learning.
Newbury House Publishers[7] Crookall, D., Oxford, R.L. & Saunders, D.
(1987) Towards a Reconceptualisation ofsimulation: From representation toreality. Simulation/Games for learning, 17[8] Garcia-Carbonell, A., Rising, B., Montero, B.,
Watts, F. (2001) Simulation/gaming and theacquisition of communicative competence inanother language. Simulation and gaming 32,4
[9] Hymes, D. 1972. On Communicative
Competence. In: Pride P.A. & J. Holmes (eds.)
Sociolinguistics. Harmondsworth:[10] Penguin Books, s. 269-293[11] Keegan, Desmond. (2003). Learning in a
Mobile Age.Academia.edu.follow research.
[12] Kukulska-Hulme, A. & Shield, L. (2007)
Overview of Mobile Assisted Language
Learning: Can mobile devices support
collaborative practice in speaking andlistening?
(Paperretrievedathttp://vsportal2007.googlepages.com/,last accessed January 26, 2009)[13] Li, R-C, Topolewski, D. (2002) ZIP &TERRY: a new attempt at designing language
learning simulation. Simulation and gaming
33, 2.
[14] Milton, J. (2006) Literature review inlanguages, technology and learning. Futurelab
Series. Can be downloaded fromRECOMMENDATIONS
As a result of the aforesaid findings and conclusions, thefollowing items are recommended:1.

Another study can be done in this same topic
covering other subject areas such as Filipino
and Mathematics. These are considereddifficult subjects in the Philippines as more
exposure of students are English based.

2.

Communicative teaching coupled with mobile
learning should be tried out in the tertiarylevel. After all, this is but the goal of teaching,for students to be able to communicate.

3.

Maintaining the student-centered approach
among classes is further recommended as apossible avenue for research. This is to be tied
up with modules that promote student
competence.

[15] www.futurelab.org.uk/research/lit_revie
ws.htm[16] Vavoula, P. M Sharples (2005) Report 11:
Literature Review in Mobile Technologies
and Learning. Nesta Future Lab[17] Prahbu, N.S. 1987. Second language
Pedagogy. Oxford University Press.
[18] Ramos (2008). Using Mobile Phones to
Improved Educational Outcomes.IRRODL.
[19] Vetter, Jeannot, L., and A. Chanier, T. (2006)
Cambridge Journals Online - Abstract.
Copyright © 2006 Cambridge University
Press.

REFERENCES[1] Atkinson,

D.

Sociocognitive(2007)

approach

Towardato second1069

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

GEOPOLYMER BEADS FROM COAL FLY ASH AND
WASTE PEN SHELLS
Kimmie Dela Cerna1, Jose Isagani Janairo2 Roy Alvin Malenab3 and Michael Angelo Promentilla
1
Chemical Engineering Department, Gokongwei College of Engineering, De La Salle University;
2
Biology Department, College of Science, De La Salle University

ABSTRACTThis paper presents our exploratory study on the development of a nanomaterial-enhanced inorganic polymerbased composite that can be used for environmental application. Geopolymer, also known as a kind of alkaliactivated material, is an inorganic polymer binder formed from chemical reactions of alumino-silicate oxides oralkaline activation of reactive alumino-silicate materials resulting in two- or three-dimensional polymeric
network of Si-O-Al bond. This material has been recently gaining attention as an alternative binder for Ordinary
Portland cement (OPC) due to its waste valorization opportunities, lower embodied energy and CO2 footprint.
However, the geopolymer technology is not the “cure-all” for material selection problem. Geopolymers would
have a wide range of properties depending on the raw materials and process conditions. This paper thus present
the recent results from our experimental studies in the Philippines using coal fly ash and waste pen shell to
produce geopolymer beads, wherein the porous matrix are functionalized and enhanced with nanomaterials suchas nanosilver.
Keywords: fly ash, geopolymer, alkali-activated material, nanomaterial, waste pen shells
and tested for its antimicrobial activity against E.
coli in water.

INTRODUCTION
The term geopolymer was first coined by JosephDavidovits back in the 1970’s, pertaining to a classof material whose molecular structure consists of anamorphous to semi-crystalline inorganic network ofmineral molecules [1]. The mechanical properties ofgeopolymers, such as its compressive strength anddensity, are generally comparable to that of Ordinary
Portland Cement (OPC). They are also reportedly
more resistant to chemical attacks, such as exposure
to acidic environments, as well as fire damage.
Because of these specific properties, plenty of
researches today focus on the use of geopolymers asa more environmentally-friendly construction
material.
Recent studies on geopolymers have started toinvestigate its applications for other industries,
particularly in refractory materials [2,3], in
solidification/stabilization of heavy metals lining for
cement pipes to increase their durability [6], and intreating contaminated water [7].
In this study, a new potential application ofgeopolymers will be explored. They will be formed
into bead shapes about 4-5mm in diameter and usedas matrices for nanosilver attachment. Foaming
agents were also used to increase the porosity of thebeads. These beads were then coated with nanosilver

MATERIALS AND METHOD
Materials
Coal Fly Ash (CFA) from Central Luzon,
Philippines and waste pen shells from thesouthernmost part of Luzon were used as the solid
raw materials. On the other hand, NaOH micropearls
and water glass solution were used as activating
solution. Hydrogen peroxide (50% solution) andSodium Lauryl Sulfate (SLS) were used to adjust thedensity of the geopolymer paste and provide added
porosity to the beads. AgNO3 and NaBH4 was used
for the nanosilver coating of the beads.
Synthesis of Geopolymer Beads
Geopolymer beads were synthesized using amodified method described in [8,9]. The waste pen
shells were first washed, dried, and crushed to small
pieces. Then, they were calcined in a furnace for twohours at 700oC. The calcined shells were finallycrushed with a mortar and pestle, and sieved to mesh#200. Figure 1 shows the waste pen shells before
and after calcination.

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 1

Waste Pen Shells Before
Calcination

andfresh AgNO3 of the same concentration was added.
This ensures the entire surface of the geopolymer,
including all accessible pores, have been covered
with the silver ions. This was left for another 2 hours,
then decanted off. Lastly, 20mL of 1M NaBH4 wasadded into the silver-ion-coated geopolymer. This
rapidly reduced the attached silver ions on thegeopolymer surface into nanosilver. The NaBH4 wasleft for two hours, then again decanted off. The
resulting nanosilver-coated geopolymer was thenallowed to dry in a laboratory oven at 60oC before
storing for future use.

After

The fly ash and the calcined shells were firstcombined at a total weight of 80g to form the solid
precursor. An amount of 7.47g of a 12M NaOH
solution was added with 29.87g of WGS to form thealkali activator solution. The solid precursor wasthen added to the alkali activator and stirred by handfor 1 minute. 1.7mL of water was also added, thenhand-stirring was done for another 2 minutes.
Finally, varying masses of a 50% H2O2 solution was
dropped in, ranging from 0.15% to 0.35% of themass of the geopolymer. This was stirred thoroughly
for another 2 minutes. The resulting paste wasbrown and had a thick consistency.
The geopolymer paste was then loaded into asyringe and dropped into a hot PEG-600 solution at
90oC. The dropwise addition of the paste, coupledwith the high temperature of the medium, allows thepaste to rapidly solidify into 4-5mm beads shown in
Fig. 2. The formed beads were left in the PEG for
about 20 minutes in order to fully harden, thentransferred, rinsed thoroughly, and left to cure in alaboratory oven at 90oC for 24 hours.

Fig. 2

Antimicrobial Activity Test of Geopolymer Beads
A 105 cfu/mL inoculum was first prepared using
a culture of E. coli made 24 hours prior to theexperiment. The 30mL of this inoculum was placedin a beaker containing 20 nanosilver-coated beads.
The beaker was then agitated in an orbital shaker set
at 300rpm. Exactly 1.5mL of 5% (wt) solution of
sodium thiosulfate was added 30 minutes after. This
immediately halts the antimicrobial activity of thesilver ions. Then, 1mL of the liquid from eachsample and their serial dilutions (up to 10-3) wereplated in agar and left to incubate at 37oC for 24hours.
RESULTS AND DISCUSSION
Surface Morphology
SEM-EDX analysis was done on the uncoatedbeads to examine their surface morphology. Figure 3
shows the SEM images of the geopolymer bead. The
porous surface of the geopolymer is evident fromthese images.

Geopolymer Beads

Nanosilver Coating of the Geopolymer Beads
An in-situ reduction process of AgNO3 into
nanosilver was done with the beads. Exactly 20mL
of AgNO3 with a concentration of ranging from
0.1M to 0.5M was introduced to a beaker containing
20 geopolymer beads. This allows the silver ions in
the AgNO3 to be attached to the geopolymer. The
beads in AgNO3 solution was left for 2 hours. After,
the AgNO3 was decanted off, and another 20mL of

Fig. 31071

SEM Image of Porous Uncoated Beads

SEE - Nagoya, Japan, Nov.12-14, 2018

cm-1 are attributed to the asymmetric vibrations of
the Si-O/Al-O bonds in the SiO4 and AlO4 groups[11], while the peak at ~700 cm-1 may be frombending vibrations from the Si-O-Si and Si-O-Al gel[10].
Nanosilver-coated geopolymer
Figure 6 shows the surface morphology of thenanosilver-coated beads. It can be seen that a fine,
powdery substance is predominant on the surface.
EDX analysis shows this substance is mostly silver,with smaller amounts of oxygen and carbon.

Fig. 4

SEM-EDX of Uncoated Beads

On the other hand, Fig. 4 shows the EDX
analysis. It can be seen from the elemental analysis
that C and O are the main constituents on thegeopolymer surface. This is attributed to theformation of Na2CO3 and CaCO3, from thecarbonation of NaOH and Ca(OH)2, respectively[10]. FTIR analysis was also done on the beads
before and after washing them. It is expected thatwashing will remove some of the carbonate species
from the geopolymer, particularly Na2CO3. Figure 5
shows the FTIR spectrum.

Figure 6.

SEM Image of Nanosilver-Coated Beads

Figure 7.

SEM-EDX of Nanosilver-Coated Beads

Fig. 5 FTIR Spectrum of Washed and UnwashedBeads
The broad peak between 3400cm-1 and 3500cm-1
correspond to the OH stretching vibrations and in
the hydration products of the geopolymer. On theother hand, the sharp peak at ~1400cm-1 is attributed
to the asymmetric stretching vibrations from the OC-O bonds in the carbonate groups. This is present
in both of the samples. A peak at ~880cm-1 is also
indicative of the presence of calcite species [10]. For
both of these peaks, a difference in intensity wasobserved for the washed samples, an indication thatindeed some of the carbonates have been removed
from washing. On the other hand, the peaks at ~1050

Antimicrobial activity of the geopolymer beads
Equation 1 was used to compute for the
antimicrobial efficiency, AE.
𝐴𝐴𝐴𝐴 =

𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐−𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐
𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐

× 100%(1)

Table 1 summarizes the results from the antimicrobial test of the beads. Using statistical analysis
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SEE - Nagoya, Japan, Nov.12-14, 2018

via ANOVA, it was inferred that the amount of H2O2,
the concentration of AgNO3, and the interaction
between these two factors are significant. The
resulting regression model is also shown in Eq. 2. It
is evident from the results that majority of the trials
were successful in eliminating at least 95% of the E.
coli in the water sample.
Table 1
%H2O2
0.25
0.15
0.25
0.25
0.35
0.15
0.35
0.35
0.25
0.15
0.25
0.25
0.25

Antimicrobial Efficiencies
AgNO3 (M)AE (%)
0.3
95.46
0.3
93.58
0.3
97.97
0.5
95.94
0.1
99.56
0.1
98.7
0.5
97.61
0.3
98.88
0.3
97.79
0.5
87.68
0.3
98.65
0.3
99.94
0.1
99.94

Figure 8. Interaction Plot between %H2O2 andAgNO3 Concentration

𝑨𝑨𝑨𝑨 = 𝟏𝟏𝟏𝟏𝟏𝟏. 𝟏𝟏 − 𝟕𝟕. 𝟐𝟐𝑯𝑯𝟐𝟐 𝑶𝑶𝟐𝟐 − 𝟒𝟒𝟒𝟒. 𝟓𝟓𝟓𝟓𝟓𝟓𝟓𝟓𝑶𝑶𝟑𝟑 +(2)𝟏𝟏𝟏𝟏𝟏𝟏. 𝟒𝟒𝑯𝑯𝟐𝟐 𝑶𝑶𝟐𝟐 ∗ 𝑨𝑨𝑨𝑨𝑨𝑨𝑶𝑶𝟑𝟑

From the interaction plot (between the amount of
H2O2 added and the concentration of AgNO3 used)shown in Fig. 8, it is evident that overall, increased
H2O2 had a positive effect on the antimicrobial
efficiency. This was as expected, as increasing H2O2
amounts increases the porosity of the geopolymer
beads, and thus increases the available space fornanosilver attachment. However, notable from theinteraction plot is that the positive effect of H2O2 ismagnified at high levels of AgNO3 (0.5M). Thismay be an indication that at low concentration of
AgNO3, majority of the silver ions have alreadyattached to the pore spaces; thus, increase inavailable space (brought about by introducing more
H2O2) no longer increases antimicrobial efficiency.
Figure 9 above shows the contour plot for
antimicrobial efficiency. It is evident that generally,
lower concentrations of AgNO3 produced the mostantimicrobial beads. This may be because the use ofhigher concentrations of AgNO3 produces coarser
nanosilver particles, thus having reduced contact
surface with the water sample. Similar results havebeen obtained by [13], where they found that
increasing AgNO3 concentration from 1mM to 4mM
led to increase in particle size and decrease in
sedimentation activation energy.

Figure 9. Contour Plot for AE

CONCLUSION
This study demonstrates the potential of
producing porous geopolymer beads from fly ash
and waste pen shells. Indication also suggests thatnanosilver-coated geopolymers beads were effective
in killing E. coli in a water sample, with results ashigh as 99.9% removal. Increased porosity of thegeopolymer beads and lower concentrations of
AgNO3 thus enhanced antimicrobial activity of thebeads. Future work will investigate further theamount of silver loading and leachability in thebeads.

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[7] Catauro, M., Bollino, F., Papale, F., & Lamanna,
G. (2014). Investigation of the sample
preparation and curing treatment effects onmechanical properties and bioactivity of silica
rich metakaolin geopolymer. Materials Science& Engineering. C, Materials for BiologicalApplications, 36, 20–24.

ACKNOWLEDGEMENTS
The authors would like to acknowledge the financial
supportfrom
Engineering
ResearchandDevelopment for Technology (ERDT), PCIEERDADMATEL grant, and URCO Research Project.
REFERENCES[8] Tang, Q., Ge, Y.-Y., Wang, K.-T., He, Y., &Cui, X.-M. (2015). Preparation of porous P-typezeolite spheres with suspension solidification
method. Materials Letters, 161, 558–560.
[9] Xia, Y., Jiang, X., Zhang, J., Lin, M., Tang, X.,
Zhang, J., & Liu, H. (2017). Synthesis andcharacterizationofantimicrobial
nanosilver/diatomite nanocomposites and its
water treatment application. Applied Surface
Science, 396, 1760–1764.
[10] Pasupathy, K., Berndt, M., Castel, A., Sanjayan,J., & Pathmanathan, R. (2016). Carbonation of ablended slag-fly ash geopolymer concrete in field
conditions after 8years. Construction and
Building
Materials,
125,661-669.
doi:10.1016/j.conbuildmat.2016.08.078[11] Ahmari, S., & Zhang, L. (2013). Utilization of
cement kiln dust (CKD) to enhance minetailings-based geopolymer bricks. Construction
and Building Materials, 40, 1002-1011.
doi:10.1016/j.conbuildmat.2012.11.069[12] Zhang, X., & Shi, B. (2015). Preparation of ananosilver composite plant medium with
antimicrobial capability through a nontoxic
method. Nanomaterials and Nanotechnology, 5,
21. doi:10.5772/60913[1] Davidovits, J. (1991). Geopolymers. Journal of
Thermal Analysis, 37(8), 1633–1656.
[2] Temuujin, J., Rickard, W., Lee, M., & vanRiessen, A. (2011). Preparation and thermal
properties of fire resistant metakaolin-based
geopolymer-type coatings. Journal of NonCrystalline Solids, 357(5), 1399–1404.
[3] Villaquirán-Caicedo, M. A., de Gutiérrez, R. M.,
Sulekar, S., Davis, C., & Nino, J. C. (2015).
Thermal properties of novel binary geopolymers
based on metakaolin and alternative silica
sources. Applied Clay Science, 118, 276–282.
[4] Dermatas, D., & Meng, X. (2003). Utilization of
fly ash for stabilization/solidification of heavy
metal contaminated soils. Engineering Geology,70(3-4), 377–394.
[5] Van Jaarsveld, J. G. S., Van Deventer, J. S. J., &Lorenzen, L. (1997). The potential use ofgeopolymeric materials to immobilise toxic
metals: Part I. Theory and applications. Minerals
Engineering, 10(7), 659–669.
[6] Chindaprasirt, P., & Rattanasak, U. (2016).
Improvement of durability of cement pipe withhigh calcium fly ash geopolymer covering.
Construction and Building Materials, 112, 956961. doi:10.1016/j.conbuildmat.2016.03.023

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

DIFFUSION OF MERCURY FROM ARTISANAL SMALL-SCALEGOLD MINING (ASGM) SITES IN MYANMAR
Tomonori Kawakami1, Misa Konishi1, Yuki Imai1 and Pyae Sone Soe2
1

Faculty of Engineering, Toyama Prefectural University, Japan; 2 Graduate School of Agriculture Kyoto
University, Japan

ABSTRACTIn some developing countries, such as Myanmar, mercury used for gold refining in artisanal small-scale
gold mining (ASGM) is emitted into the atmosphere and water, causing environmental pollution. In this study,
the diffusion of mercury from ASGM in Thabeikkyin Township, Mandalay Division, Myanmar wasinvestigated. Air samples, water samples and hair were collected from the ASGM sites. The mercury
concentration in the atmosphere in the gold mining area reached 74,000 ng/m3 at the maximum concentration,
which exceeded WHO guideline of 1,000 ng/m3. The mercury concentration in the Ayeyarwady River and thegroundwater pumped from the gold mining tunnel was 4.6 ng/l and 29-35 ng/l, respectively. The limit of
mercury in hair is considered to be 50 μg/g, at which concentration nervous symptoms may appear, while 11
μg/g is the concentration at which adverse effects on fetuses could take place. The average mercury
concentration in hair was 1.5 μg/g for ASGM workers, while it was 1.1 μg/g for nonworkers. An analysis of
hair indicated that the mercury was not at a level that would adversely affect human health, so far.
Keywords: Mercury, Myanmar, Hair, Water, Atmosphere

anthropogenic emissions and releases of mercury
and mercury compounds.”
The importance of artisanal and small-scale
gold mining (ASGM) on rural development hascaused debate among policy makers. However, theMinamata Convention includes a mix of provisions
to control and reduce the major sources of mercury,including mercury use in ASGM. For example, thedevelopment of national action plans (NAPs) for
ASGM is an obligation under Article 7. The best
available technology and best environmental
practices (BAT/BEP) must be utilized to protect
against the sources of air pollution as organized by
the convention. The NAP for ASGM is required toregulate the informal sector of ASGM and intends
to accomplish this through requirements forcountries. Key to such an NAP is the developmentof mercury inventories and baselines of the ASGM
sector in order to monitor improvements and toestablish regulatory standards for reduction [3].
On September 24 - 29, 2017, the first
Conference of the Parties (COP1) was held in
Geneva, Switzerland, to initiate enforcement of theconvention.

INTRODUCTION
Minamata Disease
Organic mercury compounds, such as
methylmercury (Me-Hg), which is more intensely
toxic than inorganic compounds, could cause
neurological symptoms when they are taken into thehuman body. Minamata disease, a mercury-relateddisease, occurred in 1950-1960 in Japan. A
bioaccumulation took place in the fish and shellfish
in Minamata Bay, where industrial effluent
contaminated with Me-Hg was discharged. People
who ingested such polluted fish and shellfish
developed Minamata disease, resulting in loss of
consciousness and even, sometimes, death [1].
The Minamata Convention
The Minamata Convention is a multilateralenvironmental agreement that obligates parties toreduce or control sources of mercury pollution inorder to protect human health and the environment.
Since mercury is easily transported across nationalboundaries [2], international cooperation was
required for its control. The Minamata Convention
on Mercury, adopted on October 10, 2013, andsigned by 128 countries, is a legally binding
international agreement that was designed
specifically to address global mercury pollution [3].
The objective of the Convention is “to protect
human health and the environment from

ASGM in Myanmar
The government of Myanmar, had not yet
signed the Minamata Convention when it wasclosed to signatures on October 9, 2014. However,
the government of Myanmar is preparing to ratify
the Convention, as stated in a letter addressed to UN
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Environment and the Global Environment Facility(GEF) on June 30, 2015. During that period,
Myanmar participated in the Asia and the PacificRegional Workshop to support the ratification andeffective implementation of the Minamata
Convention on Mercury from March 17 to 18, 2015,
in Jakarta, Indonesia [4].
The GEF and the government of Myanmar haveinitiatedthe collaboration project titled“Development of Minamata Initial Assessment andNational Action Plan for Artisanal and Small Scale
Gold Mining in Myanmar.” The project aims at theratification and early implementation of the
Minamata Convention by providing key national
stakeholders in Myanmar with the scientific andtechnical knowledge and tools needed for that
purpose [4].
Implementation of the Minamata Convention
will require a series of international obligations on
the part of the government of Myanmar to reduce
the use of mercury and to control the transport andimport/export of mercury. These requirements
should give the ASGM sector and responsive policy
makers a better understanding as to how to improvetheir environment.

ore is mined underground 20-30 m below thesurface by digging a level after making a verticaltunnel (Fig. 1). A large amount of groundwater
comes out of the tunnel and is pumped to theresidential house in the village near the ASGM fordaily life (Fig. 2).
The purification process in ASGM is as follows:
Gold ore taken from the mine underground is firstdried up and crushed by a powdering machine (Fig.
3). The powder is then put in a pan with water toseparate gold particles by gravity. In the bottom of
the pan, gold particles are collected with some sand.
Mercury is added to the pan to extract mercury by
the formation of a gold-mercury amalgam. The
gold-mercury amalgam is squeezed through a cloth
to remove liquid mercury, which remains without
reacting to the gold (Fig. 4). Finally, an operator
vaporizes the mercury in the gold-mercury
amalgam using a burner to obtain purified gold. The
vaporized mercury is emitted into the atmospherewithout any treatment, not only polluting theenvironment but harming human health, especiallythe health of workers.
In this study, the diffusion of mercury from
ASGM in the Thabeikkyin Township, Mandalay
Division of Myanmar was investigated to better
understand the environment as related to mercury
emissions from ASGM.

Mercury Use in ASGM
The mercury in the atmosphere includes bothnatural and anthropogenic emissions. According to
the United Nations Environment Program (UNEP),
1960 tons of the mercury emitted in 2010 camefrom anthropogenic activities such as ASGM, theburning of fossil fuels, and the production of
cement. ASGM is the largest source of mercury
emissions. In ASGM, mercury is used to produce agold-mercury amalgam to extract gold from goldore. Mercury is vaporized by burning the goldmercury amalgam to separate gold from theamalgam. This process has been adopted in many
developing countries such as Myanmar andIndonesia, since it is an easy and cheap process for
purifying gold [6]. It is reported that in thewatershed of the Amazon river in Brazil, inorganic
mercury turns into organic mercury to bioaccumulate through the food chain after a large
amount of mercury has been used for ASGM andreleased into the environment [5]. The number ofworkers engaged in ASGM is estimated to be 20
million in more than 50 developing countries.
Among them are 650,000 females and 1-1.5 million
children [7]. It is concerning that the workers,
including children, aspirate gaseous mercury, andthe residents around ASGM eat polluted fish.

Fig. 1 Vertical gold mine tunnel

Mercury Emissions from ASGM in Myanmar
ASGM is operating in the ThabeikkyinTownship, Mandalay Division of Myanmar. Gold

Fig. 2 Groundwater leaked form the tunnel
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Fig. 3 Machine that powders gold ore
Fig. 5 ASGM sites in Mandalay Division of
MyanmarFig. 4 Squeezing the gold-mercury amalgam
Fig. 6 Enlarged map of ASGM sites
MATERIALS AND METHODS
Measurement of the Mercury Concentration in
the Atmosphere

Site Descriptions
In this study, the diffusion of mercury from
ASGM in the Thabeikkyin Township, Mandalay
Division of Myanmar was investigated to evaluate
the effect of ASGM on the environment. Figures 5
and 6 show Mandalay of Myanmar and the sitewhere ASGM is operating heavily. At the ASGM
site, five ASGMs were operating (Sites 1-5 in Fig.
6). The atmospheric mercury concentration wasmeasured at Site 5 to elucidate the spatial
distribution. At Site 5, the mercury concentration of
the groundwater leaked from the gold mining tunnel,
which was pumped to residents, was measured. The
groundwater from Sites 1-4 was sampled. The
mercury content in human hair was measured forboth ASGM workers and nonworkers at Sites 1-5.
In addition, the mercury concentrations of the
Ayeyarwady River, which flows through Mandalay,
were measured.

Mercury exists in the atmosphere as gaseous
mercury and particulate mercury. The total mercury
is the sum of the gaseous and particulate mercury.
The major forms of mercury in the atmosphere aregaseous elemental mercury (GEM, Hg(0)), reactive
gaseous mercury (RGM, Hg(II)), and total
particulate mercury (TPM, Hg(p)) [8]. Since Hg (0)is hard to dissolve in water, it has a long retention
time in the atmosphere, and it contributes 95% of
the total mercury in the atmosphere. Hg(p), which
adheres to particle matter suspended in theatmosphere contributes several percentage points ingeneral, except near the emission source [9].
Accordingly, the total mercury in the atmospherecan be estimated by measuring the gaseous mercury.
Atmospheric samples were collected by passive
samplers and active samplers at the same time. An
active sampler system, which collects gaseous andparticulate mercury separately, is shown in Fig. 7

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SEE - Nagoya, Japan, Nov.12-14, 2018[10]. GEM was collected in a tube (M-160, Nippon
Instruments Corp., Ltd.) with an air pump (MP-Σ30,
Shibata Science). To capture Hg(p), a quartz fiber
filter with a pore size of 0.3 µm was attached at the
intake nozzle. The air was aspirated at a rate of 0.5
L min-1. The total volume of aspirated air wasrecorded in the pump system, and the atmosphericmercury concentrations were then calculated fromthe air volume and the amount of mercury absorbed.
Passive samplers were also used to measure thespatial distribution of mercury [11]. The passive
sampler had the same dimensions as the Ogawa
passive sampler for sulfur dioxide, which is
cylindrical with a diameter of 2 cmφ and a length of
3 cm. Diffuse plates with a thickness of 2mm and22 holes were placed at both ends of the cylinder.
As an absorber, a quartz fiber filter coated with gold
was set inside the diffuse plate (Fig. 8). The main
body and the diffuse plates were made of fluorine
resin, which allows the sampler to be cleaned inacidic solution. The mercury absorbed on the quartz
fiber filters was converted proportionally to theatmospheric concentrations by using theatmospheric concentrations obtained by the active
sampler system.
Two and three active samplers and 13 and 17
passive samplers were placed at various locations
around the ASGM for the first survey from March
2 to 3, 2017, and for the second survey from
October 19 to 20, respectively. The passive sampler
was set under the roof of ASGM facilities andresidential houses and attached to trees. It wascovered with a cup so as not to get wet from rainwhen it is attached to trees. Active and passive
sampling continued for 24 hours. Gaseous andparticulate mercury collected by the active andpassive samplers was measured using a heatvaporizing atomic absorption method (MA-2,
Nippon Instruments) after taking them to Japan.
The instrument has a detection limit of 0.03 ng.
When a passive sampler is used, the absorbed
mercury on the quartz fiber filters cannot be
converted directly into the mercury concentration in
the atmosphere. To obtain the ratio between theatmospheric mercury concentration and the amountof mercury adsorbed into the filter, both active andpassive samplers were operated simultaneously at
two or three points in the same location. Assumingthat the amount of mercury measured by a passive
sampler is proportional to the atmospheric mercury
concentration measured by an active sampler, theamount of mercury obtained by a passive sampler
was converted into the atmospheric mercury
concentration based on the proportion [11].

Fig. 7 Active sampler system operated with a dry
battery

30mm

20mm

Fig. 8 Passive sampler. Quartz fiber filters coatedwith gold are placed inside the diffuse plates.

Measurement of Mercury in Water Samples
Bromine chloride solution, prepared by mixing
1.08 g of KBr and 1.52 g of KBrO3 into 100 mL ofhydrochloric acid, was used for cleaning thesampling bottles and the degradation of the organic
matter in the sample water. Samples collected in
Myanmar were kept in Teflon bottles washed by abromine chloride solution and pure water. Ten mLof 0.1% L-cysteine solution was added to every 1 Lof sample solution to prevent the vaporization of
mercury and the adherence of mercury to the wallsof bottles. After adding L-cysteine solution,
samples were taken to Japan for analyses. The
reduction vaporization method was applied foranalysis. Five mL of bromine chloride solution wasadded to every 1 L of the water samples one day
before analysis to degrade organic matter. On thefollowing day, 200 mL of the samples and 2 w/v%
of hydroxylammonium chloride solution weremixed in a reduction bottle to deactivate thebromine chloride. After 10 mL of 50 v/v% sulfuric
acid solution and 10 mL of 10 w/v% tin(II) chloride
were added, mercury vaporized by bubbling wasanalyzed by a gold amalgam method using amercury analyzer (MA-2, Nippon instruments)[12].
Two well water samples were collected at eachsite shown in Fig. 6: Site1 (Kapani village), Site2
1078

SEE - Nagoya, Japan, Nov.12-14, 2018

(Khwin Village), Site3 (Latpanpyant village), Site4(Wattay village and Phatshae village), and Site5(Chaungyi village). Groundwater leaked from thegold mine tunnel was collected at Site 5.
Ayeyarwady River water was collected at the center
flow of the river in the city of Mandalay, which islocated downstream of the ASGM sites.
Ayeyarwady River water upstream of the ASGM
siteswas also collected.

mercury indicated that the burning process was also
taking place in the gold shop outside the ASGM. In
fact, residents of the village dug tunnels in theirbackyards to obtain gold ore, and they do goldmercury amalgamation in their house as part of theireveryday activities. This is the reason for the highconcentration of mercury that prevailed throughout
the entire village. The high concentrations ofgaseous mercury of 10-1461 ng/m3 were reported
outside the ASGM area in Central Sulawesi,
Indonesia which was one of the largest ASGM sites
in Indonesia with 760 ASGM plants [16]. The usageof mercury outside the ASGM may be the reason
why higher level of gaseous mercury was observed
in Myanmar than that in Central Sulawesi.

Measurement of Mercury in Human Hair
The mercury content in hair samples taken from39 ASGM workers and 11 nonworkers (age:18-57)
from Sites 1-5 was measured by the heatvaporization method with the mercury analyzer(MA-2, Nippon instruments). Hair samples weretaken in accordance with the protocol permitted by
the ethics committee of Toyama Prefectural
University, permission number H29-6 on the effectof the use of mercury in ASGM in Myanmar on
human health.

RESULTS AND DISCUSSION
Atmospheric Mercury around the ASGM in
MyanmarIn Fig. 9, the distribution of the gaseous mercury
concentration from the first survey is shown as bars.
The highest concentration of 10,900 ng/m3 wasobserved near a small house where the burning
process took place at the ASGM site. It was morethan ten times of the WHO guidelines of 1,000
ng/m3 [13]. Even in the residential area outside theASGM, the lowest concentration measured 130
ng/m3 which is a much higher level than the 0.9 -1.5
ng/m3 in non-polluted areas [14,15].
In Fig. 10, the distribution of the gaseous
mercury concentration from the second survey isshown as bars. The highest concentration of 74,000
ng/m3 was observed in the same place where thehighest concentration was observed in the firstsurvey, even though there was no burning during
the 24-hour sampling. ASGM workers should
aspirate higher concentrations of mercury during
the vaporization of mercury at the small house. In
the main office of ASGM, 5,300 ng/m3 of mercury
concentration was measured. Even in the residential
area outside the ASGM, generally higher
concentrations, with a maximum concentration of
1,600 ng/m3, were observed. The highest
concentration was observed in front of the so-called
gold shop, where the gold-mercury amalgam
brought by the village people was burnt, and thegold shop bought the resultant purified gold. The
gold shop sold mercury and goods needed for
ASGM, such as pans. The highest concentration ofFig. 9 Spatial distribution of Hg(0) observed in thefirst survey( unit: ng/m3)

Fig. 10 Spatial distribution of Hg(0) observed in the1079

SEE - Nagoya, Japan, Nov.12-14, 2018

μg/g [18]. Nonworkers seemed to have lower levels;
however, based on to t-test, there were no
significant differences between the two groups. The
lower mercury level in hair may be due to lessindexicality of hair for mercury vapor [18].

second survey( unit: ng/m3)
Table 1 Mercury concentration in water samples
collected in Myanmar

Site 1Site 2Site 3Site 4Site 5
Ayeyarwady
river

Type
Ground water
Ground water
Ground water
Ground water
Ground water
Ground water
Ground waterRiver water
Leaked water
Leaked water
Water to the village
Upper
Lower

Hg
(ng/L)
20.9
12.1
0.0
2.0
1.2
0.0
20.1
12.9
29.3
34.5
27.1
3.8
4.6

Hg content (µg/g)

SiteMedian-Median-25%ile
25%ile75%ile-MedianWorkers

Nonworkers

Fig. 11 Mercury content in the hair of ASGM
workers and nonworkers

Mercury Concentration in Water

CONCLUSION

Table 1 shows the mercury concentration inwater samples. The sample taken at the center of the
Ayeyarwady River in Mandalay located downflowof the ASGM showed 4.6 ng/L. Even the sample
taken from upper flow of the Ayeyarwady River
showed 3.8 ng/L. Comparing these concentrations
with the typical mercury concentration in lakes andrivers, 1-3 ng/L [17], the mercury concentration in
the Ayeyarwady River was slightly higher but not
exceptionally so.
Groundwater leaked from the ASGM tunnel
was 29.3 ng/L and 34.5 ng/L in the first and second
surveys, respectively. The groundwater at Site1 andSite 4 also had concentrations higher than 20 ng/L.
Although none of the samples exceeded WHO
guidelines for drinking water, 500 ng/L [18], the useof mercury in ASGM could affect the mercury
concentration in groundwater, since most of themercury in groundwater is derived fromatmospheric sources [19].

The government of Myanmar has initiated acollaborative project called “Development of
Minamata Initial Assessment and National Action
Plan for Artisanal and Small Scale Gold Mining in
Myanmar”. The project’s goal was the ratificationand early implementation of the Minamata
Convention by providing key national stakeholders
in Myanmar with scientific and technicalknowledge and tools needed for that purpose.
In this study, mercury concentrations in theatmosphere, water, and human hair were measured
in two surveys in ASGM areas in the ThabeikkyinTownship, Mandalay Division of Myanmar
performed in March and October, 2017.
The first and second surveys revealed that thehighest concentrations of mercury in theatmosphere of ASGM sites reached 10,900 ng/m3
and 74,000 ng/m3, respectively. Even in the village
outside the ASGM, concentrations higher than the
WHO guidelines of 1,000 ng/m3 were observed.
This was caused by the use of mercury for gold
mining in village households and by the burning
process taking place at the gold shop.
In the ASGM site, groundwater, especially thegroundwater leaked from the gold mining tunnel,
had elevated concentrations of mercury, indicatingthat ASGM had contaminated the groundwater withmercury. Although the mercury concentration wasmuch lower than the WHO guidelines, the mercury
concentration in the Ayeyarwady River could be
affected by ASGM as well.
An analysis of hair indicated that the averagelevels of mercury content in the ASGM workers andthe nonworkers, 1.5 μg/g and 1.1 μg/g, respectively,
were within the normal level of 1-2 μg/g. Based on

Mercury Content in Hair
Hair mercury is a biomarker for Me-Hg, and isoften used to characterize Me-Hg exposures [20].
The lowest limits of mercury considered to poserisks of neurosis and health concerns to unbornbabies are 50 μg/g and 11 μg/g, respectively [21].
Figure 11 shows the mercury content in the hair of
ASGM workers and nonworkers. The maximum
levels of the ASGM workers and the nonworkers
were 5.7 μg/g and 2.9 μg/g, respectively. The
average levels of mercury content in the ASGM
workers and the nonworkers, 1.5 μg/g and 1.1 μg/g,
respectively, were within the normal level of 1-2
1080

SEE - Nagoya, Japan, Nov.12-14, 2018

to t-test, there were no significant differences
between the two groups. To this point, the mercury
is not at a level that would adversely affect humanhealth.

[10] Kagaya, S., Amatani, M., Nagai, T., Tohda, K.
and Kawakami, T., A Simple Method for
Determination of Gaseous and Particulate
Mercury in Atmosphere, Journal of
Ecotechnology Research, 13, 2007, pp.241.
[11] Kuniki, R., Kawakami, T., Kagaya, S., Inoue,T., Rosana, E. and Nagafuchi, O.; Measurementof gaseous mercury concentration in theatmosphere - Development of a passive sampler-, Environmental Engineering Research, 46,2009, pp.355-359.
[12] EPA, Method 1631, Revision E:Mercury in
Water by Oxidation, Purge and Trap, and Cold
Vapor Atomic Fluorescence Spectrometry,
http://www.caslab.com/EPAMethods/PDF/EPA-Method-1631.pdf.
[13] WHO/Europe, Chapter 6.9 Mercury
http://www.euro.who.int/__data/assets/pdf_fil
e/0004/123079/AQG2ndEd_6_9Mercury.PD
F.
[14] Lin C-J., S. O. Pehkonen, The chemistry of
atmospheric mercury: a review, Atmospheric
Environment, 33, 1999, pp.2067-2079.
[15] Shannon J. D., E. C. Voldner, Modelingatmospheric concentrations of mercury anddeposition to the great lakes, Atmospheric
Environment, 29, 1995, pp.1649-1661.
[16] Yuka Serikawa, Tomonori Kawakami, Basir
Cyio, Isrun Nur, Rosana Elvince andTakanobu Inoue, Emission and dispersion of
gaseous mercury from Artisanal Small Scale
Gold Mining plants in Palu City, Central
Sulawesi, Indonesia, Environmental Science,24(4), 2011, pp.269-274.
[17] Fan, Anna M.. “Mercury.” In Lawrence
Fishbein, Arthur Furst, and Myron A.
Mehlman, eds., Genotoxic and Carcinogenic
Metals: Environmental and Occupational
Occurrence and Exposure. Advances inModern Environmental Toxicology, Vol. 11.
Princeton, N. J., Princeton Scientific
Publishing, 1987.
[18] WHO, Guidelines for drinking-water quality,
fourth edition, 2011.
[19] Grace M. Vandal, Robert P. Mason, William F.
Fitzgerald, Cycling of volatile
mercury in temperate lakes. Water, Air, andSoil Pollution, 56, 1991, pp.791–803.
[20] WHO/UNEP DTIE Chemicals Branch,
Guidance for Identifying Populations at
Risk from Mercury Exposure, 2008.
[21] National Institute of Minamata Disease,
Mercuryandhealth,http://www.nimd.go.jp/english/kenkyu/docs/
Mercury_and_health.pdf.

REFERENCES[1] Harada, M., Minamata disease: methylmercury
poisoning in Japan caused by environmental
pollution, Critical Reviews in Toxicology. 25(1),1995, pp.1-24.
[2] David C. Evers, Susan Egan Keane, NiladriBasu, David Buck, Evaluating the effectivenessof the Minamata Convention on Mercury:
Principles and recommendations for next steps,
Science of the Total Environment, 888-903,
2016, pp.569-570.
[3] United Nations Environment Programme,
Minamata Convention on Mercury, 2013.
[4] Global Environmental Facility, Request for
Chemicals and Wastes Enabling Activity,
Development of Minamata Initial Assessment
and National Action Plan for Artisanal andSmall Scale Gold Mining in Myanmar, GEF
Project ID-9805, 2017,https://www.thegef.org/project/developmentminamata-initial-assessment-and-nationalaction-plan-artisanal-and-small-scale-4.
[5] United Nations Environment Programme,
Global Mercury Assessment 2013 Sources,
Emissions, Releases and Environmental
Transport, 2013.
[6] Minoru Yoshida and Hirokatsu Akagi,
Environmental pollution of mercury use ingold mining in developing countries,
Environmental Science, 17(3), 2004, pp.181189.
[7] The World Bank, CASM's holistic approach tosmall-scale mining aims to transform thisactivity from a source of conflict and poverty
into a catalyst for economic growth andsustainable
development,
Communities,
Artisanal and Small-Scale Mining (CASM),
2008, pp.1-4.
[8] Munthe J., I. Wängberg, N. Pirrone, Å. Iverfeldt,
R. Ferrara, R. Ebinghaus, X. Feng, K. Gårdfeldt,
G. Keeler, E. Lanzillotta, S. E. Lindberg, J. Lu,
Y. Mamane, E. Prestbo, S. Schmolke, W. H.
Schroeder, J. Sommar, F. Sprovieri, R. K.
Stevens, W. Stratton, G. Tuncel, A.U rba,
Intercomparison of methods for sampling andanalysis of atmospheric mercury species,
Atmospheric Environment, 35, 2001, pp.30073017.
[9] Kouji Marumoto and Masahiro Sakata, Review
of recent studies on mercury in the atmosphere,
Chikyukagaku(Geochemistry) 34, 2000, pp.5975.

1081

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

REMOVING ARSENIC AND FLUORIDE FROM HOT SPRINGWATER BY ELECTROLYSIS
Yuki Imai1, Misa Konishi1, and Tomonori Kawakami1
1

Faculty of Engineering, Toyama Prefectural University, Japan

ABSTRACT
Currently in Japan, there are many hot springs containing fluoride and arsenic with high concentration.
Although the national minimum effluent standard for arsenic and fluoride is 100 µg/L and 8 mg/L,
respectively, they are not applied to the hotels with hot spring since no appropriate treatment techniques areavailable. The objective of this research is to reduce fluoride and arsenic in hot spring wastewater by using
electrolysis technique to meet the national minimum effluent standards.
The electrolysis system with an anode bath and a cathode bath separated by a diaphragm was adopted.
Fluoride and arsenic co-precipitate with magnesium hydroxide formed in the cathode bath in which pH value
increases as the electrolysis progresses. The Gero hot spring containing fluoride and arsenic as 17 mg/L and120 µg/L, respectively, was used as a model effluent.
Since Gero hot spring water contains almost no magnesium, magnesium chloride was added as a magnesium
source. The addition of 100-200 mg/L could reduce the fluoride concentration to less than 8 mg/L. The
arsenic concentration decreased to less than 10 μg/L. 1040 C/L of electricity was required for the operation.
The electrolysis system successfully reduce the fluoride and arsenic concentrations below the national
minimum effluent standards.
Keywords: hot spring waste water, arsenic, fluoride, electrolysis, national minimum effluent standard
INTRODUCTION
Intake of drinking water containing highconcentrations of fluoride for a long term could
cause fluorosis, such as dental fluorosis and skeletal
fluorosis. In order to prevent human health fromfluorosis, the standard for drinking water and thenational minimum standards were set as 0.8 mg/L
and 8 mg/L, respectively. Currently in Japan,
however, there are many hot springs containing
fluoride in excess of the national minimum effluent
standards. A temporal standard is applied to hotels
with hot springs since no appropriate treatment
techniques are available. Adsorption, ion exchange
and reverse osmosis (RO) techniques can be used
for removing fluoride from drinking water, however,co-existing contaminants in hot springs degrade
their effectiveness [1,2]. In addition, RO is notavailable for wastewater treatment due to rejectedwater with concentrated contaminants [3]. Even
though the Japanese Ministry of Environment
invited private companies to compete for thetreatment technique for the wastewater, no effective
technology has been developed yet [4]. Accordingly,
the ministry decided to extend the term of validityof the temporal provisional standard for 2001 after
reviewing the regulation in 2016 [5].
On the other hand, long-term exposure toarsenic from drinking water and food could cause
cancer and skin lesions. Arsenic is naturally present
at high levels in the groundwater of a number ofcountries, and it is highly toxic in its inorganic form.
The national minimum effluent standards of arsenic
have been set at 100 μg/L. In Japan, many hot
springs contain arsenic exceeding the national
minimum effluent standard such as Kusatsu hot
spring (250–1260 μg/L) [6], Gero hot spring (140μg/L) [7], and Yudanaka hot spring (1240 μg/L) [8].
Hot spring inns are exempted from arsenic
regulations. This is also due to the lack of effective
technologies to remove arsenic.
The authors have been developing technologies
to remove fluoride from drinking water indeveloping countries. In developing countries,
inexpensive and easy-to-operate equipment isrequired. Fluoride removal by an electrolysis
system is one of the technologies applicable to hot
spring waste water. The electrolysis system consistsof electrolysis baths separated by a diaphragm.
Whenelectrolysis
progresses,
magnesium
contained in well water in a cathode bath
precipitates as a form of magnesium hydroxide as
the pH increases, and fluoride co-precipitates withmagnesium hydroxide [9,10]. Moreover, arsenic
was found to be removed efficiently by thiselectrolysis method. With this electrolysis method,
fluoride and arsenic can be removed simultaneously.
In drinking water, it is rare that fluorine and arsenic
exist at the same time in high concentrations;however, the waters of both Kusatsu and Gero hot
springs have higher concentrations of fluoride andarsenic than the minimum effluent standards. It is1082

SEE - Nagoya, Japan, Nov.12-14, 2018preferable that they should be treated and removed.
The objective of this research was to remove
fluoride and arsenic simultaneously from hot spring
wastewater using an electrolysis system to meet thenational minimum effluent standards.

MATERIALS AND METHODSFor the simultaneous removal of fluoride andarsenic, an electrolysis system was used. The
electrolysis system consists of an anode bath and acathode bath separated by a diaphragm. When watercontaining magnesium is electrolyzed in theelectrolysis system, magnesium precipitates as aform of magnesium hydroxide by increasing the pH
value of the cathode bath. Fluoride and arsenic coprecipitate with magnesium hydroxide when theelectrolysis progresses.
Experiments were carried out in a continuous
flow system. Fig.1 (a) shows the flow diagram of
the continuous electrolysis system, and Fig.1 (b)shows a photo of the electrolysis system used in theexperiment. The diaphragm of the electrolysis
shown in Fig.1 (b) is made of an uncalcined plate.
An aeration bath is added to the electrolysis system.
The sizes of the anode and cathode baths were 7 cm
(H) × 40 cm (L) × 1 cm (W) and 7 cm (H) × 40 cm(L) × 2 cm (W), respectively. The volumes of theanode and cathode baths were 280 mL and 560 mL,
respectively. As shown in Fig.1 (a), a constriction
plate to restrict the mixing of the solution before andafter was provided in the flow in the anode andcathode tanks. A plastic (PVC) plate 0.5 mm thick
was used as the constriction plate. The constriction
plate provided an open area 1 cm deep from thebottom. In this study, the compartments in theanode bath were named the “+1 cell” and the “+2cell” from upstream to downstream. The
compartments in the cathode bath were named the“-1 cell” and the “-2 cell” from upstream todownstream. A platinum wire (purity 99.99%,
diameter 0.6 mmφ, length 1 m) was used as theelectrode for the anode, and a stainless steel wire
(SUS 304, diameter 1.0 mmφ, length 1 m) was used
for the cathode.
Table 1 shows the water quality of the Gero hot
spring. The Gero hot spring, which contains
fluoride and arsenic, was used as a model effluent.
Since Gero hot spring water contains almost no
magnesium, magnesium chloride was added as amagnesium source when electrolysis was carriedout.

In the laboratory, the water taken from the Gero
hot spring was put in a bucket, and magnesium
chloride was added to adjust the magnesium
concentration. The hot spring water (Mg added)
was introduced into the anode bath and the aeration
bath of the electrolysis cell. Carbonate andbicarbonate, which interfere with the formation ofmagnesium hydroxide, were removed from the raw
water by introducing the effluent water from theanode bath with low pH into the aeration bath. The
size of the aeration bath was 6.5 cm (H) x 6.5 cm(L) x 6.5 cm (W), and the volume was 275 mL. The
generated carbon dioxide was expelled to theatmosphere by aeration. As the operating condition,
the treatment capacity was 10 L/day. The residence
time in the cathode bath was 80 minutes.
Electrolysis was carried out at a constant current byusing a constant current power supply(TAKASAGO ZX–400 M).
We investigated the effect of the flow rate ratio,
which is the ratio of the flow rate to the anode bath(a):aeration bath (b), magnesium concentration, andcurrent on the removal of fluoride and arsenic.

Fig.1 (a) Schematic diagram of the sequential flow
reactorFig.1 (b) The electrolytic equipment used for theexperiment1083

SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1 Water quality of the Gero hot spring

9.5

Na+
(mg/l)
108.9

K+(mg/l)
1.2

Mg2+(mg/l)
0Ca2+(mg/l)
1.9

F(mg/l)16.5

Cl(mg/l)75

SO42(mg/l)
10.9

As(mg/l)
140

Alkalinity(µeq/l)
-

9.2

105.2

0.6

0

0

16.9

75

11.4

114

1329

pH
Literature[11]Measuredvalue

Effect of The Flow Rate Ratio

RESULTS AND DISCUSSION

The flow rate ratio of the hot spring watersupplied to the anode bath (a) and the aeration bath(b) was varied—a:b=10:0, 5:5, 2:8, or 0.6:9.4—
under conditions in which the magnesium
concentration and the current were set at 100 mg/L
and 120 mA, respectively.

Effect of The Flow Rate Ratio

Effect of The Magnesium Concentration
The magnesium concentration was varied—0,
50, 100, or 200 mg/L—under conditions in which
the flow rate ratio and the current were set at
a:b=0.6:9.4 and 120 mA, respectively.

Effect of The Electrolysis Current
The current was varied—80, 120, or 200 mA—
under conditions in which the flow rate ratio and themagnesium concentration were set at a:b=0.6:9.4
and 100 mg/L, respectively.

Analyses
Sampling was conducted at the raw water exit,+1 cell, +2 cell, aeration bath, -1 cell, and -2 cell
after continuing to operate for 24 hours or more forstabilizing.
The concentration of As was analyzed by ICPMS (Agilent 7700 Series).
The ionic component concentrations of F-, Cl-,
NO3-, SO42-, PO43-, Na+, K+, NH4+, Mg2+, and Ca2+
were analyzed by ion chromatographs.
(Cation: Thermo ICS 1500, separation column
IonPac CS 12A, eluent methanesulfonic acid 30
mmol/L, suppressor CERS 500)
(Anion: Thermo ICS 2000, separation column
IonPac AS 18, eluent KOH 23–40 mmol/L(gradient), suppressor AERS 500)
The pH was measured by a glass electrode methodwith a BECKMAN ∅ 32 pH Meter (electrode:
BECKMAN 511070).

Fig.3.1 (a) shows the effect of the flow ratio on
the removal rate of fluorine and arsenic. When theanode side had a small flow rate, a higher removal
rate was observed. The fluoride concentrations ineach cell with various flow rate ratios are shown in
Fig.3.1 (b), and the arsenic concentrations areshown in Fig.3.1 (c). When the flow rate ratio was
a:b=10:0, the entire amount of raw water was
supplied to the anode. On the other hand, whena:b=0.6:9.4, the majority was supplied to the mixed
aeration tank.
When the flow rate ratio a:b=10:0, no significant
change in fluorine concentration was observed ineach cell. On the other hand, in the case of
a:b=0.6:9.4, the fluoride concentration increasedslightly due to the Coulomb force in the +1 cell andthe +2 cell; however, the fluoride concentration wasclose to that of the raw water in the aeration bath towhich the majority of the raw water was supplied.
Thereafter, the fluoride concentration rapidly
decreased in -1 and -2 cells. For arsenic, even when
the flow rate ratio was a:b=10:0, the arsenic
concentration decreased in the -1 and -2 cells. The
highest removal ratio of arsenic was also recorded
when the flow rate ratio was a:b=0.6:9.4.
The pH and magnesium concentrations in eachcell at various flow rate ratios are shown in Fig.3.1(d) and Fig.3.1 (e), respectively. The pH in theaeration bath was less than 4 irrespective of the flowrate ratio, indicating that carbonate and bicarbonate
had been removed. When the flow rate ratio was
a:b=10:0 and a:b=0.6:9.4, there was a difference in
pH in the -1 and -2 cells. In the former case, the pH
in the -2 cell was 8.10, while in the latter case, it
was 10.05. When taking the solubility ofmagnesium as 16.6 × 10-5 mol/L [12]. the solubility
product is calculated to be Ksp=[Mg2+][OH-]2 =[16.6 × 10 ][33.2 × 10 ] = 1.83 × 10.
When the same solubility product is assumed, amagnesium concentration of 35 mg/L in thesolution is obtained at pH=10.01, which almost
coincides with the measured value of 34 mg/L. At
pH 8.10, if the same solubility product ofmagnesium hydroxide is assumed, the solubility is(10(10.05 –8.10))2=7900 times higher than that at
pH=10.05, indicating that theoretically no1084

SEE - Nagoya, Japan, Nov.12-14, 2018

precipitation occurs. In fact, slight precipitation was
found only in the vicinity of the electrode.
Consequently, the magnesium concentration did notdecrease greatly, as shown in Fig.3.1 (e). The
difference in the pH value in the -2 cell affects theformation of Mg(OH)2 and the removal of arsenic
and fluoride.

Fig.3.1 (d) Change in the pH in each cell

Fig.3.1 (a) Effect of the flow rate ratio on theremoval rates of fluoride and arsenic

Fig.3.1 (e) Change in the Mg concentration in eachcellFig.3.1 (b) Change in the fluoride concentration ineach cell

Fig.3.1 (c) Change in the arsenic concentration ineach cell

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SEE - Nagoya, Japan, Nov.12-14, 2018

Effect of The Magnesium Concentration
Fig.3.2 (a) shows the influence of fluoride andarsenic on the removal rate when the magnesium
concentration in the raw water was varied. The
higher the magnesium concentration, the higher theremoval rate of fluoride and arsenic. However,when the magnesium concentration was 50 mg/L or
more, the removal rate of arsenic stayed within 90
to 100%.
Fig.3.2 (b) and (c) show the fluoride
concentration and the arsenic concentration,
respectively, in each cell when the magnesium
concentration was varied. In the legend of the
figures, Mg 0, Mg 50, Mg 100, and Mg 200 indicate
when the magnesium concentration in the raw water
was 0 mg/L, 50 mg/L, 100 mg/L, and 200 mg/L,
respectively. When the magnesium concentration
was varied between 100 and 200 mg/L, 8 mg/L
(removal rate 53%) of the fluoride concentration in
the treated water (-2 cell) was obtained. The arsenic
concentration in treated water (-2 cell) was less than
10 μg/L when the magnesium concentration was 50
mg/L or more.
Fig.3.2 (d) and (e) show the pH and themagnesium concentration, respectively, in each cellwhen the magnesium concentration was varied.
When 200 mg/L of magnesium was added, about
100 mg/L of magnesium remained in the treatedwater (-2 cell). The reason is that the pH did notincrease sufficiently. However, the magnesium
reduction from the raw water in treated water (-2cell) was largest when 200 mg/L of magnesium wasadded, leading to the highest removal of fluoride.

Fig.3.2 (b) Fluoride concentration for different Mg
concentrations

Fig.3.2 (c) Arsenic concentration for different Mg
concentrations

Fig.3.2 (d) pH for different Mg concentrations

Fig.3.2 (a) Effect of the magnesium concentrationon the removal rates of fluoride andarsenic

Fig.3.2 (e) Magnesium concentration for different
Mg concentrations

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Effect of The Electrolysis Current
Fig.3.3 (a) shows the influence of the current on
the removal rates of fluoride and arsenic. Fig.3.3 (b)and (c) show the fluorine concentration and thearsenic concentration, respectively, when theelectrolysis currents were varied. Electrolysis
currents larger than 120 mA did not increase
fluoride removal but did increase arsenic removal.
As shown in Fig.3.3 (c), when the current was 120
mA or more, an arsenic concentration of less than
10 μg/L was obtained. The pH and magnesium ofeach cell are shown in Fig.3.3 (d) and Fig.3.3 (e),respectively. Changes in pH due to different
currents were hardly observed; however,differences in magnesium concentrations wereobserved in each cell. With a current of 80 mA,
magnesium was not sufficiently precipitated, which
could be the cause of the low removal rates offluorine and arsenic.
When the current was 120 mA, the fluoride
removal rate was the highest, and the fluoride
concentration met the national minimum effluent
standard. The arsenic concentration was also lessthan 10 μg/L.
The amount of electricity per day with a currentof 120 mA was calculated to be 10400 C/day. Since
the flow rate was 10 L/day, the electricity required
per 1 L was 1040 C/L.

Fig.3.3 (b) Fluoride concentrations in different
currents

Fig.3.3 (c) Arsenic concentrations in different
currents

Fig.3.3 (d) pH in different currents
Fig.3.3 (a) Effect of the current on removal rates offluoride and arsenic

Fig.3.3 (e) Magnesium concentrations in different
currents

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CONCLUSION
An electrolysis system was operated with theaim of simultaneously removing fluorine andarsenic from hot spring wastewater. The electrolysis
system consisted of electrolytic cells separated by adiaphragm made of an uncalcined plate. The
electrolysis system was used to remove arsenic andfluoride by the co-precipitation of magnesiumhydroxide on the cathode side with fluoride orarsenic.
The wastewater of the Gero hot spring was used
as a model. Since the Gero hot spring did notcontain magnesium, magnesium was added
externally. The addition of 100–200 mg/L could
reduce the fluorine concentration in raw water from
16.9 mg/L to 8 mg/L or less. Simultaneously, thearsenic concentration could be reduced from 114
μg/L to 10 μg/L or less.
ACKNOWLEDGEMENTS
This research was partly supported by JSPS
KAKENHI Grant Number 17K18910.
REFERENCES[1] Maurice S. Onyango and Hitoki Matsuda,
Fluoride Removal from Water Using
Adsorption Technique
Fluoride andthe environment, Vol. 2, 2006.
[2] Paripurnanda Loganathan, Saravanamuthu
Vigneswaran, Jaya Kandasamy, Ravi Naidu,
Defluoridation of drinking water using
adsorption processes, Journal of Hazardous
Materials, Vol. 248-249, 2013, pp. 1-19.
[3] Stéphane Nicolas, Laurence Guihard, Alain
Marchand, Bernard Bariou, Abdeltif Amrane,
Ali Mazighi, Nabil Mameri, Azzeddine El
Midaoui, Defluoridation of brackish northern
Sahara groundwater - Activity productcalculations in order to optimize pretreatment
before reverse osmosis, Desalination, Vol. 256,

Issue 1-3, 2010, pp. 9-15.
[4] Ministry of the Environment Government ofJapan, Exploration into development anddissemination of technology for wastewater
treatment from hot spring,
http://www.env.go.jp/water/onsenhaisui/tech.html, 2018.6.9.
[5] Ministry of the Environment Government ofJapan，Notification, No.1606161, Review of
the temporal minimum effluent standard forboron, fluoride, ammonium, nitrite and nitrate,
2016.
[6] Yukiko Sakai and Tsuneo Takishima, Arsenic
Content in the Hot Spring Waters in Gunma
Prefectur, Hot Spring Sciences, Vol. 26, No. 1,
1975, pp. 13-25.
[7] Gifu Research Center for Public Health, Hot
spring analysis data, 2013.
[8] Kimio Noguchi, Chemical Components of the
Hot Spring Waters in Nagano Prefecture，Hot
Spring Sciences, Vol. 18, No. 2, 1967, pp. 4764.
[9] Tomonori Kawakami, Hikaru Miyazaki, Yuki
Imai, Misa Konishi，Fluoride Removal from
Groundwater by an Electrolysis System ，Journal of Arid Land Studies, Vol. 27, Issue 1,
2017, pp. 41-47.
[10] Yuki Imai, Shiori Yanagawa, Misa Konishi,
and Tomonori Kawakami, Removing
Fluoride from a Hot Spring Using an
Electrolysis System, International Journal of
GEOMATE, Vol. 12, Issue 32, 2017, pp.
101-106.
[11] Gifu Research Center for Public Health，Hot
spring analysis data, 13B04774, No. 125,2013.
[12] Kagaku Binran Basic edition Ⅱ, rev. 5, The
chemical society of Japan, 2004.

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4th Int. Conf.on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018C3051

A DEVELOPMENT OF WASTE MANAGEMENT MODEL: A CASESTUDY OF SI MUM MUANG MARKET IN THAILAND
Anucha Jaisai and Chutarat Chompunth*
School of Environmental Development Administration,
National Institution of Development Administration, Thailand

ABSTRACTThe objectives of this research are to 1) study waste management in Si Mum Muang Market, PathumThani
Province, Thailand, 2) to study factors affecting waste management and 3) to find out a developmental guidelinein waste management. According to waste problem of the case study, there are 240 tons of wastes per day, waste
disposal fee is 30 million baht per year, and landfill site may not enough in the future. This problem also causes
pollution and environmental impact to local communities. This study employed qualitative researchmethodology. Data were collected through in-depth interviews and participatory observation, and action research
was conducted. SWOT Analysis was conducted to analyze data. The study showed that Waste management of
the Si Mum Muang Market is under control of Donmuang Pattana Co., Ltd. The company encourages its
supervisory staffs to invent waste management’s innovation namely “One to Three innovation”. This techniquecontributes value benefits as follows, reducing waste disposal fee, increasing value, create an organic waste
product and lead to sustainable environmental business. Internal factors affecting success in waste management
include vision of management executives, systemic thinking, empirical practice, and high level of having
experience and proficient on waste management. External factors are public awareness on environment,
government sector and environmental organization in supporting the development of waste management at Si
Mum Muang Market. Finally, for effective waste administration, the organization should provide more
opportunities for the public to participate in waste management activities and determine carefully on any impact
to public health and environment.
Keywords: Waste Management, SWOT Analysis, One to Three Innovation, Environmental Business

INTRODUCTIONRESEARH RATIONAL
The pollution problems of Thailand are
numerous including a variety of aspects from theindustry, the agriculture, community, tourist
attractions and the market that produces
environmental impacts to the environment. The
environmental pollution that is the priority issues
including, water pollution, air pollution, noise
pollution and waste pollution and waste. The causeof the increasing the environmental pollution
problems are 2 mains reasons. The first one is thatthe average population increase of the global
population tend much higher even if campaign aboutfamily planning succeed but the amount of increaseof population growth is still like exponential
population which is a multiplier increasing, whenmore people want to consume more resources on all
sides, food, housing, energy and others, Secondly,
the expansion of economic and technologicalprogress resulting in an economic expansion makes
a high living standard. The consumption of natural
resources is over the basic necessities of life [1]. So,
it is necessary to use more energy as well. At thesame time, the technological progress is supported tobring the natural resources to use easier and more.

One problem that important to all sector suchas industry, agricultural community, tourist
attraction places and the market is the pollution
problems caused by community waste and solid
waste. Accumulated solid waste may result in
dirtiness and environmental nuisances including
odors, flies, and blowing litter that directly causes anaesthetic problem. In the long-term effects, solid
waste can also contaminate the environment by solid
waste disposal that transfers harmful substances tothe air, water and soil, which may destroy theenvironment and pose human health problems. The
situation of waste from 2010 to 2017 is massive,
there was the volume of waste up to 26.77 million
tons and it was appropriately managed only 7.2
million tons. The rest is under inappropriate
managed and from the academic research, inThailand, community waste can be recycled only 5.1
million tons, this problem causes environmental
problems and affect to people's health [2]. Thailand
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people in the community to cooperate effectively
and with the health care of the cleanliness follow thesanitation principles, provided to the sellers in themarket. It is an approach working of a successfulorganization and should be taken as an example ofan effective environmental management.

has an increasing production of municipal solid
waste that, allied to the current un-effective waste
management system, makes the search foralternatives of waste management essential.
MarketMarket is the exchange of goods as a centerof community in life along in the Thai culture for along time. The main product is all kind of foodespecially fresh food and according to its position as
a gathering source of food. Frequently, it was foundthat the market is the source of wide spread diseases
causing from food infective disease. These problems
are caused by the environmental un-sanitation of themarket such as waterlogged, waste residues, smelly
etc. In order to control the market to be compliedwith hygiene standard, the market is necessary tosegregation their waste and properly manage them.
The developer must improve the market hygiene byfollowing guidelines under the Public Health Act
2535. Moreover, there are many authorities
controlling and supporting the whole sale market tocomply with Thai laws and regulations including,
Local governments, Provincial Health Office,Department of Health and so on. Thus, it isimportant for the developer to search forappropriately alternatives of manage municipal solid
waste from the hole sale market. One to Three
Innovation as an innovative waste management of Si
Mum Muang market is investigated and suggested asa practice to other wholesale market in Thailand.

Research methodology and Data analysis
This research is an action research with theinvention of innovative waste management of Si
Mum Muang Market, KhuKhot subdistrict, Lam
LukKa District, Pathum Thani province. The
researcher used the questionnaire to collect data anddescriptive data analysis by using the technicalenvironment analysis (SWOT Analysis) to analyze
in order to understand the operations of all waste
management of Si Mum Muang Market with One tothree innovation and factors in the operation of Si
Mum Muang Market. Collect data by interviewing
someone that involved in waste management of Si
Mum Muang Market. More details, step by step are
as follows:
1. Explore the basics information about waste
management of Si Mum Muang Market, Pathum
Thani Province by seeking information fromliterature sources. Use documentary research that
related to waste management, reducing the amountof waste, waste management in community, factorsthat makes accomplish and case studies in various
areas as well as other documents related to theobjecives of the study.
2. The study of waste management of Si Mum
Muang Market to understand the guideline of waste
management as policy and study the successful in
implementing the waste management in the market.
3. Data were collected by interview the executiveof the market and the traders involved which areimportant people up to 29 key informants. The
details are as follows: 5 of the executive of themarket, 1 of the environmental manager who is
responsible for waste recycle and management of Si
Mum Muang Market, 5 of the waste management
staff workers of Si Mum Muang Market, 2 waste
collector, 9 of merchants, 4 of the officeenvironment in Pathum Thani province, 3 authorities
from department of environmental policy.
4. The data collected by observation method suchas, observing the work of the officers involved.
Practice of traders and the participation of customers
in the market.
5. Processing, summarize and presentation of theresults of the study by bring the data from the study
in the target area, the process of exchange,
brainstorming of study group, analyze format andfind the factors leading to the success along withguidelines to add more in order to expand the resultof the waste management that appropriate with Si

Si Mum Muang wholesale market
Si Mum Muang is a wholesale market which
is known as leader for wholesale fruits andvegetables in Thailand. The market is operated in thenorth part of Bangkok more than 33 years. The
market’s vision is as “the market is clean,convenient, and peace which are a basic structure
together with the participation in the management
chain, product quality, efficiency and social
responsibility”. Although consumer’s demand iscontinued to be increased by the circumstances ofthe economic expansion, Si Mum Muang Market
still committed to be an honest trader in order tomaintain leadership of the fruit and vegetable tradecenter by planning the future to be market in newera. The market focuses on building good
relationships and engages in improving the qualityof life of the society. The market also focus on thecustomer‘s convenient from sellers to customers bydeveloping the trade area and a project for a lot ofcars to come in the area of the market, Manage
Transportation, Transfer goods services both productrelease and effective delivery. The waste
management from activities with a daily average of
200 tons by managing waste from the source, also,
the campaign for the seller, worker, customer and
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SEE - Nagoya, Japan, Nov.12-14, 2018

Mum Muang Market to achieve the most effective
environmental management and report the results.

and blue bins are placed at every stall and shop.
Yellow garbage bins are set near every block of thecommercial zone.
Since 2012, the principals of the Market havebeen implementing and developing customized
recycling programs of all types and sizes of solid
waste in the market. Si Mum Muang Market
provides Sustainability Reports for each of its
customers to demonstrate its site by site what type ofwastes are being recycled and the quantity of thewaste, allowing its stakeholders to see theimpact/success of their recycling efforts in a morequantifiable manner. Benefits of recycling are as
follows; to reduce waste to landfills which spares theland and reduces pollution/contamination; and, toreduce waste removal costs as recyclables are
removed from solid waste procedures. Most
importantly, Si Muang Market is now effectively
connected to all local, and municipal governments toensure that its operations and practices meet all laws
and regulations.
In this market, composting is gaining asubstantial amount of push. As composting is theprocess of recycling organic material which
typically includes food production scraps and crop
growing waste. Its practices are environmentallysensitive and lower their garbage collection costs byremoving food waste from the garbage stream whichroutinely be transferred to landfills.
The results also showed that the merchants whoare better informed about solid waste management
information likely have better solid waste
management behavior. The reason could also bebecause merchants who are regularly informed about
appropriate solid waste management may understandthe method to minimize the solid waste generation
rate and the ways to separate solid waste into
recyclable and non-recyclable items to reuse or
recycle solid waste again. Regularly provided
information is a key factor that can give theinformation to the merchants, and better information
might increase the participation in solid waste
management. With regard to the sources of
information, a survey study done in many place [5]mentioned that most recyclers are more likely tohave one or more sources of information, forexample newspapers and television. Various sourcesof recycling knowledge coming from public
education and information through public campaigns
showed a positive correlation with recycling rates.
The case study analysis by techniqueenvironment analysis (SWOT Analysis are presented
as follows.
Within the business organization has twodimensions including, the dimension of the strengths
that leaders are visionaries, work in a systematic
approach by encourages staff to develop theirpotential in the field of waste management. So, staff
try to invent new innovations in waste management

Results and Discussion
Case study background
This study was undertaken in Si Mum Muang
Market, Thailand. It is located in Pathum Thani
province, which is about thirty kilometers from thenorth of Bangkok, Thailand. It is one of the largest
wholesale agricultural products markets in Thailand,
and a trading point for farmers, sellers and buyers of
the large quantities of both locally produced andimported food products. There are more than 30,000
customers daily and approximately 10,000 metrictons of goods are traded daily. The primary productcategories traded at this market were fruits,
vegetables, meat and fish, rice and crops, flowers,
pet supplies, and plants.
The study concluded that affecting factors to Si
Mum Muang Market of effective waste management
is an innovative “One to three” which leads tobusiness sustainable environment.
In this study, proposed solid waste management
options for Si Mum Muang Market, Thailand were
designed to minimize the initial generation ofcommunity waste through source reduction, thenthrough reuse and recycle to further reduce thevolume of material being sent to dispose of atlandfills or being disposed of by other alternatives.
Options development of solid waste management forthe market is focused on (1) solid waste generation,(2) solid waste handling and separation and storage,and (3) solid waste collection. Solid waste in thiscase study can be classified into many groups
including organic waste, plastic, food waste, wood,
paper, glass, clothes, metal, and miscellaneous.
In-depth interviews were conducted in thisstudy to interview the environmental manager andstakeholders regarding solid waste management. The
results showed that Si Mum Muang Market officers
who work in the solid waste management
department mentioned that solid waste managementin the market is efficient in terms of solid waste
disposal. They can transform the organic waste to
make useful products, they can still handle thecollection of a large amount of solid waste well, as
they can collect the solid waste from the market
space properly and provide coverage to all zones ofthe market. Execution of a solid waste management
system is crucial to deal with the solid waste
generation as economically and safely as possible. It
is vital that all solid waste are professionally as
possible collected from all sources, and disposed ofin controlled disposal facilities. All collected waste
are stored separately in three types of garbage bins
including; green, yellow and blue. Green garbage
bins are used to store organic waste, yellow garbage
bins are used to store recyclable waste and blue
garbage bins are used to stock general waste. Green
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SEE - Nagoya, Japan, Nov.12-14, 2018as 1 of waste management will get 3 benefits and it
was called innovative “One to three” to reduce wastefrom source in order to save the cost of waste
disposal, adding value to solid waste and create
products from organic waste this concept leads theorganization to achieve environmentally sustainablebusiness. This is consistent with the results of astudy of Poboon, etc. [3] studied the local authorities
practice to overcome the global warming crisis: A
case study of municipal district Klang city. It was
found that a municipal district Klang city focus on adevelopment of personnel skill and people
awareness in all sectors. It also improved theworkflows, applies applicable technologies, andimplement many activities to reduce global warmingin the municipality. The Municipal also giving
priorities on development of staffs skill and it will
boost staff’s knowledgeable and competence on thefield of waste management even more and more.
The staff can use their knowledge and expertise todevelop and improve the organization's operations
practices more efficient.
For weakness dimension, it was found that Si
Mum Muang Market was a wholesale market ofvegetables, fruits and raw materials. There are large
amounts of merchants and affect to amount of wasteof 240 tons per day. Thus, there is a large amount ofwaste and the budget of waste disposal is quite high.
The market still has no unblemished guidelines forplanning waste management and no clear guideline
for the operators to perform the operation practiceeffectively.
The external business organization has twodimensions including the dimension of a chance
which is a chance to discover that there is a
Government and environmental organizations in
supporting the development of waste management's
Si Mum Muang Market to be effective. From theinterviews of Si Mum Muang market executives said
that "In the past had the local authorities and theeducation authorities that gave priority and support
to Si Mum Muang Market such as KhuKhot
Municipal supported and educated about waste
management to the market staff of waste
management department. Kasetsart University camein to support staff on controlling and training
procedures how to make the biological fermentation
as well as support staff for biological fermentation.
While Khonkean University do many research on
bringing the fruits and vegetables in Si Mum Muang
market for cattle feeding and supported theinformation on fruit and vegetable scrap to makeefficiently cattle feeding product" (Personal
interview, May 15, 2561), This finding corresponds
to many research [4], [5] that participation isbeneficial to an implementation of waste
management policies and a development for various
projects which concerning an conservation of natural
resources and the environment. This might because

all stakeholder can monitor for surveillance andwarning particularly any projects or activities that
affect public health, social and environmental
quality. Importantly, waste management programs of
Si Mum Muang market focus on public participation
practice which strongly benefit to the public,
surrounding communities and the public as a whole.
However, for the threat dimension, it was found that
Si Mum Muang market as a large-scale market, so
there are communities living around the market a lot,causes many complaints from people surrounding
areas, as presented in the interviews of market staffs
that “In the past, there were a lot of complaints frompeople around the market. They were mainly about
the environmental problems because of Si Mum
Muang market is so large and has a lot of solid waste
which may cause environmental and health impact
to the community as well as disturbing people living
surrounding the markets. That is why Si Mum
Muang market need to find approaches and means todeal with these significant issues” whichcorresponds to many researches [2], [6], [7] that theorganization should be accountable and open to thecommunities. There must be a good criterion or
terms include the success of the mission together
with the efficiency of operation and cost-effective
use of resources in the environmental managementof local government agencies that need to use thelocal resources is critical to reducing operationalcosts. So it can be concluded that Si Mum Muang
market has a social responsibility in environmental
management and solution of environmental issues
from the complaints of the people living around the
project site.
Conclusion and recommendations from the study
To be successful in waste management practiceas a case study, it should be an integration between
the educational program and the providing ofappropriate solid waste management. In accordancewith the educational program, it aims to increase theawareness of merchants by educating them in terms
of proper solid waste management. A solid waste
management system is also important to deal withthe solid waste generation to ensure that all solid
waste are appropriately transferred and disposal [8].
To make the operation of waste management
more broadly effective, business organization should
spread the innovation of waste management to otherfunction in order to expand broader efficiency andsustainability approaches by suggestions as follows:
1) Recruiting enough workers with direct
knowledge in waste management
2) Increase public relations to the rightknowledge to the traders in the area such as posters,
pamphlets and etc.
3) In order to prevent waste from outside to
inside the market. There should be a point of waste
disposal so that the person can be drop properly.
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SEE - Nagoya, Japan, Nov.12-14, 2018

4) Bio-compost should be more introduced, inorder to help the communities in wastewater
treatment. The market should be encouraged to build
on or sold to third parties in order to increase
revenue to the market.
5) Add more channel in order to promote themarket for the customers to be more environmental
friendly practice.

[3] Peeraya. V, Chamlong. P,andChutarat. C. 2014.
Local Authority’s Solid Waste Management: A
Case Study of Muangklang Municipality,
Rayong Province. Journal of Environmental
Management. Vol. 10, Issues 2, 71-81.
[4] Lamboglia R., Raffaele F., Mancini D. and S.
Garzella, 2018. From a waste crisis tosustainability strategies: The case study of
Naples’ waste collection firm, Journal of
Cleaner Production, Vol. 186, Issue 10 , pp.
726-735.
[5] Lee W. H. and J. Morris Chang, 2004, A waste
collection policy based on empirical behavior,
Information Sciences, Vol. 167, Issue 1-4, pp.
129-146.
[6] Kinnaman T. C. and D. Fullerton, 2000. Waste
and Recycling with Endogenous Local Policy,
Journal of Urban Economics, Vol. 48, Issue 3,
pp. 419-442.
[7] Fujita S. and H. Tamura,. 2004. Life Cycle
Management for Selecting the Way of
Disposing Domestic Kitchen Waste, IFAC
Proceedings Volumes, Vol. 37, Issue 11, pp.
109-114.
[8] Putters K., 2005, HIA, The next step: Defining
models and roles, Environmental Impact
Assessment Review, Vol. 25, Issues 7-8, 2005,
pp. 693-701.

Finally, it could be summed that people’s
participation is the one of significant factor toachieve the successful solid waste management of
this case study. The recommendation is that aknowledge and information project is needed toeducate the customers. The motivating broadcasts
might help people to understand more and havebetter environmental friendly behavior. As a study
found that better information can make separation
and recycling behavior easier.
REFERENCES[1] Chesoh, S. 2011. Environmental Impact
Assessment of Power Development Project:
Lessons from Thailand Experiences, AsianSocial Science, Vol. 7, Issues 9, pp 119-123.
[2] Chompunth, C. 2017, Role of Public
ParticipationinEnvironmental
ImpactAssessment in Thailand. International Journal of
GEOMATE, May, Vol.12, Issue 33, pp.109-113.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

MECHANICAL PERFORMANCE OF ABACA-GEOPOLYMERCOMPOSITE EXPOSED TO ELEVATED TEMPERATURES

1

Roy Alvin J. Malenab1 and Michael Angelo B. Promentilla1,2
Gokongwei College of Engineering, De La Salle University, Philippines; 2National Research Council of thePhilippines, Philippines

ABSTRACT
Geopolymer binders are the most promising green alternative to ordinary Portland cement due to theirdemonstrated “good to superior” mechanical and thermal properties, chemical and fire resistance, among others.
However, the use of geopolymer in several applications is being limited because of its brittle nature. In this study,
samples of fly ash based geopolymer reinforced with fixed dose of chemically modified waste abaca fibers cured
at different temperatures were synthesized and characterized in terms of compressive and flexural strengths. Thenexperimental short-term thermal endurance of select composites was employed. Composites gained compressive
strength after exposure to 200°C while retained its room-temperature compressive strength when exposed further
up to 600°C. Furthermore, results indicated that flexural strength decreases with increasing exposure temperature.
Scanning electron microscopy analyses were also performed to examine the microstructure of the geopolymer
matrix and to investigate the failure mechanism in the fiber-geopolymer composite before and after exposure toelevated temperatures.
Keywords: Geopolymer, Natural fiber, composite

density, good mechanical properties, nontoxicity, etc.
[11],[12],[12],[13].
In general, geopolymers are known to performbetter than the conventional concretes made with
OPC in fire, due to their ceramic-like properties[14],[15] that led to its applications as fire resistance,
refractory in the glass industry, thermal insulation andother uses requiring good performance at hightemperatures [16]. Although geopolymer as binderand its composites have been well studied, there arelimited published research assessing the effect ofdesign parameters on the performance of thesematerials in terms of its fire resistance and responses
to elevated temperatures [16],[17].
In this study, mechanical performance ofgeopolymer reinforced with untreated abaca fiber wasassessed after exposure to different elevatedtemperatures. Structural and morphological changes
in the composites were also studied.

INTRODUCTION
Geopolymer is a new class of ceramic-like
inorganic polymer material composed primarily oftetrahedral silica and alumina which are formed
through the reaction of aluminosilicate ions under thepresence of an alkali activator resulting into hardened
3-D molecule networks [1]. These materials are more
ecologically friendly compared to ordinary Portland
cement (OPC) since geopolymerization of precursors
from natural source or industrial solid residues does
not release carbon dioxide during the low temperature
reaction [2]. In addition, geopolymer binders exhibit
rapid development of good to excellent mechanicalstrength and superior resistance to heat, fire and acid[3],[4],[5],[6]. Furthermore, the abundance ofaluminosilicate raw materials makes geopolymer alow cost option as main component of many building
materials [7].
Similar to conventional OPC-based construction
materials, however, geopolymer exhibits brittle
behavior with low tensile strength and is sensitive to
cracking that impose constraints in structural design
and affects the long-term durability of structures[8],[9]. To overcome these limitations, different
fibers have been used to reinforce geopolymer
cementitious materials [10] ranging from high cost,high strength metal oxide or silicon carbide fibers to
low cost, abundant and renewable natural fibers [7].
Recently, plant or cellulosic fibers are becoming
more attractive reinforcement than synthetic fibers
because of their natural abundance, low cost, low

MATERIALS AND METHODOLOGY
Materials
For the preparation of geopolymer matrix, fly ash
from a coal-fired power plant in Bataan, Philippines
was used as aluminosilcate source. Chemicalcomposition of the fly ash, as determined by X-ray
fluorescence (XRF) analysis, is given in Table 1.
Based on ASTM specification, the coal fly ash is aclass F fly ash or low-calcium fly ash having a total
SiO2, Al2O3, and Fe2O3 of 89.2% (more than 70%).
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SEE - Nagoya, Japan, Nov.12-14, 2018

As-received sodium hydroxide (NaOH) micropearls
to prepare 12M NaOH solution and commercial waterglass solution (modulus = 2.5, 34.1% SiO2, 14.7%
Na2O and 51.2% water by weight) were used toprepare the alkaline activator.
Residual abaca fibers used in this study werecollected from abaca farms in Dumaguete City,
Philippines. These were by-products of fiber
extraction from plant source followed by segregation
into commercial grades based on color and texture.
Residual fibers are usually disposed as waste.

After that, the furnace was turned off while thespecimens were allowed to cool down inside thefurnace to room temperature.
Characterization
Compressive and flexural strengths of control
specimen and those exposed to elevated temperatures
were determined. For compressive strength testing,
cured cubic samples were subjected to a constantstress rate of 0.25 MPa/s until failure. Flexuralstrengths or modulus of rupture of samples wereobtained by three-point bending test at a constantstress rate of 0.25 MPa/s.
Fourier transform infrared (FTIR) spectroscopy
and Scanning electron microscopy (SEM) analyses
were also performed to examine the changes instructural and morphological characteristics ofsamples before and after exposure to hightemperatures.

Table 1 Chemical composition of fly ash
Components
Fe2O3
SiO2
CaO
Al2O3
OthersLoss on ignition

wt %
20.8
43.2
4.5
25.2
5.8
2.5

RESULTS AND DISCUSSION
Mechanical Properties

Synthesis of Abaca Fiber Reinforced Geopolymer
Composite Materials

Compressive and flexural strength results before
and after temperature exposure of pristine and fiberreinforced geopolymer specimens are summarized inFig. 1 and Fig. 2, respectively. Figure 1 shows thesimilarity in compressive strength progression
between the pristine and fiber-reinforced
geopolymers. Prior to thermal exposure, compressive
strength of pristine geopolymer (45.2 ± 7.6 MPa) ishigher than that of fiber-reinforced (28.0 ± 2.9 MPa).
After exposure to 200°C, both pristine and reinforced
samples gained up to 23 MPa and 15 MPa increase incompressive strength, respectively. However, both
samples decreased in compressive strength after
exposure to 400°C while almost no further strength
losses when exposed at 800°C were observed for both
samples.

First, fly ash and abaca fibers (99:1 by weight)
was dry-mixed to ensure uniform fiber distribution.
For every 1kg of fly ash–fiber mixture, 400g ofalkaline activator, well-mixed 80g of water glass
solution and 320g of 12 M NaOH solution [18], wasrequired. The overall mass ratio of solids (fly ash andfiber) to activator was based from a previous study[19] to achieve a mixture with considerable
compressive strength and good workability.
To prepare the composite, alkaline activator waspoured into a bucket then fly ash and fibers were
gradually added with mixing in between using alaboratory motorized hand-held mixer. Mixing wascontinued for about 15 minutes or until the mixture
become homogenous. Water was added to attain thedesired consistency. Then, the mixture was poured
into 5 cm × 5 cm × 5 cm cube molds (for compressive
strength test) and 5 cm × 5 cm × 18 cm bar molds (forflexural strength test). After 24 hours, samples weredemolded and cured in the oven at 75°C for 46 hours.
Then, samples were cured at ambient conditions inresealable plastic bags for 28 days before subjecting
to various testing. Pristine geopolymer samples, i.e.,with no abaca fiber reinforcement were prepared toserve as the reference material.
Exposure to Elevated TemperatureSpecimens at age of 28 days at ambient conditions
were exposed to different temperatures (200°C,
400°C and 600°C). The specimens were placed in a
furnace and heated at constant heating rate of
10°C/min up to a desired temperature for two hours.

Fig. 1

Compressive strength of pristine and abaca
fiber reinforced geopolymer.
As presented in Fig. 2, pristine and fiber-

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SEE - Nagoya, Japan, Nov.12-14, 2018

reinforced geopolymer samples showed slightly
different tendency in flexural strength evolution after
exposure to elevated temperatures. Roomtemperature flexural strength of fiber-reinforced
geopolymer (3.7 ± 0.4 MPa) is higher when compared
to unreinforced samples (2.0 ± 0.2 MPa). After
exposure to 200°C, flexural strength of fiberreinforced geopolymer decreased to 2.1 ± 0.4 MPa.
Further flexural strength loss (1.1 ± 0.6 MPa) was
observed after exposure to 400°C while lesspronounced decrease (0.5 ± 0.3 MPa) was detected
after thermal exposure to 600°C.
Flexural strength of pristine geopolymer also
decreased from 2.1 ± 0.2 MPa to 0.9 ± 0.4 MPa after
exposure to 200°C. No changes in flexural strength
were detected after subjecting the samples to higher
temperatures up to 600°C. It can be observed thatflexural strength of pristine and fiber reinforced
geopolymers are almost the same after exposure to
400°C and 600°C.

Fig. 2This could be explained by further geopolymerizationof unreacted fly ashes and/or sintering process [20].
FTIR analysis can provide important informationon the geopolymerization from solid precursors
involving complicated chemical processes. Figure 3
shows the spectra of fly ash and geopolymer samples
exposed to elevated temperatures. The major IR
characteristic bands of geopolymeric specimens fromvarious systematic investigations are given in Table
2. The spectrum of fly ash shows broad peaks (1,100
and 1,015 cm-1) due to glassy or amorphous natureand heterogeneity of fly ash [24]. Significant spectral
differences can be observed between the fly ash andgeopolymer samples. The Si-O-T (T is either Si or Al)
at 1,100 cm-1 of the fly ash shifted to a lower
wavenumber (1,070 cm-1) in the different geopolymer
samples indicating alkali activation or reaction
products of fly ash and alkali activator were formed.
Reduction in shoulder due to increasing intensity ofthis peak was also observed and most noticeable forgeopolymer exposed at 400°C (inset of Fig. 3) whilebecame flatter at 600°C. For the other peak at
1,015cm-1, shifting to a lower wavenumber was notobserved however compared to fly ash, the peak
becomes sharper in the control or unexposed to hightemperature sample. Its intensity decreased with
exposure temperature. New peaks at 795 cm-1, 690
cm-1 and 615 cm-1 appeared corresponding to other
Si-O, Al-O and ring vibrations.

Flexural strength of pristine and abaca fiber
reinforced geopolymer.

Strength losses can be associated to thedegradation of the geopolymer matrix. Similar to
OPC-based materials, geopolymer degradation
mechanism can be categorized into three: 1) thermal
incompatibility, 2) pore pressure effect and 3) phasetransformation [20]. These could explain the decreasein compressive strength of pristine and fiberreinforced geopolymers when exposure temperaturefrom 200°C to 400°C and decrease in flexuralstrength after exposure to 200°C. Degradation of thefiber in the geopolymer composite could also
contributed to the observed strength losses within thetemperature range of exposure. Based onthermogravimetric studies, thermal degradations of
the different components of plant fiber such as abaca
range from 160°C to 500°C [18],[21],[22].
Increase in strength of geopolymers after thermal
exposure are reported in literature [20],[23]. In thisstudy, pristine and fiber-reinforced geopolymer
gained compressive strength after exposure to 200°C.

Fig. 3FTIR spectra of unexposed (control) andafter exposure to elevated temperature
geopolymer samples.

The good to excellent compressive strength ofgeopolymer is due to its 3D aluminosilcate structure
as already pointed in numerous studies [25],[26],[27].
The observed gain in compressive strength of samples
exposed at a certain temperature (200°C) can be
explained by further geopolymerization of partiallypolymerized aluminosilicate species [28]. It is also
possible that as water molecules were evaporated
from the geopolymer matrix, dissolved species
exceeded its solubility limit, thus further precipitation
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SEE - Nagoya, Japan, Nov.12-14, 2018

happened that resulted to increase in strength [29].
These are supported by the changes in IR spectra from
1,070 cm-1 to 1,015 cm-1 wavenumber for further
geopolymerization and at around 1,640 cm-1
wavenumber for the water evaporation. In addition,sintering of geopolymer at elevated could also
contributed to strength gain [20]. In contrary,
exposure to higher temperature could destroy
geopolymer backbone due to thermal incompatibility
resulting to decline in strength. The overall
compressive strength progression observed in thisstudy could be due to combined effects of the theseprocesses [20].

followed by degradation as result of the thermal
contact experienced by the matrix based on FTIR
analysis. The observed improvement in flexuralstrength between control pristine and reinforced
geopolymers was associated to good adhesion
between the fibers and geopolymer matrix. However
due to excessive removal of water from the composite
and thermal degradation of fiber, flexural strength
declined continuously after exposure from 200°C to
600°C. Chemical treatment of matrix and/or fiber
may delay or prevent this phenomenon to sustain thereinforcing objective of the synthesized composite.

Table 2 IR characteristic band of geopolymers.
Wavenumber
cm-1
1,640
1,425
1,070-1,015
795

Assignment

Referenceswater
sodium carbonate
Si-O-T asymmetricstretching vibration
Si-O-Si vibration[30][31],[32]Fig. 4[24],[29],[32][29]AlO4 stretching

[30]

690

3-unit ring vibration

[33]

615

6-unit ring vibration[33]

SEM images of a) control and b) exposed to
400°C fiber reinforced geopolymer
composites.

ACKNOWLEDGEMENTS
This research was financially supported by the
National Research Council of the Philippines (NRCP),
Philippine Council for Industry, Energy andEmerging Technology Research and Development(PCIEERD), Advanced Device and Materials Testing
Laboratory (ADMATEL) and Electronics ProductDevelopment Center (EPDC). The authors would liketo acknowledge the following for their contribution tothis study: Ms. Patricia Isabel K. Bravo, Antonio L.
Kalaw, Bernardo B. Bernardo, Zachary Cole L. Ang,
Don Angelo V. Joson1, Gian Dominic C. Mercado,
Ramon Tirso Manuel A. Santillan and Jedwig
Siegfrid S. Tan.

Scanning electron images of fractured control (notexposed to elevated temperature) and exposed to
400°C are shown in Fig. 4. The enhancement of
flexural strength of fiber reinforced geopolymer
composite is due to good interaction between thematrix and fiber as shown in the SEM image (Fig. 4a).
In fact, some geopolymeric particles were depositedon the fiber surface. Fiber pullout and fiber fracture
possibly control the failure mechanism of thecomposite. Compared to the fiber in the control
sample, after exposure to 400°C, damages to fibers
were observed as shown in Fig. 4b. This could explain
the decrease in flexural strength of the fiber
reinforced geopolymers exposed up 600°C. In fact at
400°C and 600°C exposure, flexural strength ofpristine and fiber reinforced specimens are almost thesame, thus, fibers are no longer functioning as
reinforcements.

REFERENCES[1] Davidovits, J. Geopolymer Chemistry andApplications. Vol. 171, 2008[2] Turner, L. K. and Collins, F. G. Carbon Dioxide
Equivalent (CO2-e) Emissions: A Comparison
between Geopolymer and OPC Cement
Concrete. Construction and Building Materials
Vol. 43, 2013, pp. 125–130.
[3] Jaarsveld, J. G. S. Van , Deventer, J. S. J. Van ,and Lorenzen, L. The Potential Use of
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Minerals Engineering Vol. 10, Issue 7, 1997, pp.
659–669.
[4] Zhang, T. , Gao, P. , Gao, P. , Wei, J. , and Yu, Q.
Effectiveness of Novel and Traditional Methods
to Incorporate Industrial Wastes in Cementitious

CONCLUSION
This study evaluated the compressive andflexural strengths of fiber reinforced geopolymer
composites before and after exposure to elevatedtemperature up to 600°C. The pristine and fiber
reinforced samples gained compressive strength after
exposure to 200°C and eventually returned to its
original strength when exposed up to 600°C. This wasdue to combined effect of further geopolymerization

1097

SEE - Nagoya, Japan, Nov.12-14, 2018Materials - An Overview. Resources,
Conservation and Recycling Vol. 74, 2013, pp.
134–143.
[5] Rios, S. , Ramos, C. , Fonseca, A. V. Da , Cruz,
N. , and Rodrigues, C. Colombian Soil Stabilizedwith Geopolymers for Low Cost Roads. Procedia
Engineering Vol. 143, Issue Ictg, 2016, pp.
1392–1400.
[6] Yankwa Djobo, J. N. , Elimbi, A. , Kouamo
Tchakouté, H. , and Kumar, S. Mechanical
Properties and Durability of Volcanic Ash BasedGeopolymer Mortars. Construction and Building
Materials Vol. 124, 2016, pp. 606–614.
[7] Musil, S. S. , Keane, P. F. , and Kriven, W. M.
Green Composite: Sodium-Based Geopolymer
Reinforced with Chemically Extracted Corn
Husk Fibers. Developments in Strategic
Materials and Computational Design IV 2013,
pp. 123–133.
[8] Sakulich, A. R. Reinforced Geopolymer
Composites for Enhanced Material Greenness
and Durability. Sustainable Cities and SocietyVol. 1, Issue 4, 2011, pp. 195–210.
[9] Yang, T. , Han, E. , Wang, X. , and Wu, D. Surface
Decoration of Polyimide Fiber with Carbon
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Enhancement of Phosphoric Acid-BasedGeopolymers. Applied Surface Science Vol. 416,
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[10] Chen, H. Biotechnology of lignocellulose:
Theory and practice. 2014.
[11] Mohammed, L. , Ansari, M. N. M. , Pua, G. ,Jawaid, M. , and Islam, M. S. A Review on
Natural Fiber Reinforced Polymer Composite
and Its Applications. International Journal of
Polymer Science Vol. 2015, 2015, pp. 1–15.
[12] Yan, L. , Kasal, B. , and Huang, L. A Review of
Recent Research on the Use of Cellulosic Fibres,
Their Fibre Fabric Reinforced Cementitious,
Geo-Polymer and Polymer Composites in Civil
Engineering. Composites Part B: Engineering
Vol. 92, 2016, pp. 94–132.
[13] Reinforced Geopolymer Composites: A criticalreview.
[14] Bakharev, T. Geopolymeric Materials Prepared
Using Class F Fly Ash and Elevated Temperature
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[15] Ahmed, S. F. U. Fibre-reinforced geopolymer
composites (FRGCs) for structural applications.
Woodhead Publishing Limited: 2014.
[16] Bernal, S. A. , Bejarano, J. , Garzón, C. ,Gutiérrez, R. M. De , Delvasto, S. , andRodríguez, E. D. Composites : Part B
Performance of Refractory Aluminosilicate
Particle / Fiber-Reinforced Geopolymer
Composites. Composites Part B Vol. 43, Issue 4,2012, pp. 1919–1928.
[17] Kong, D. L. Y. and Sanjayan, J. G. Damage

Behavior of Geopolymer Composites Exposed to
Elevated Temperatures. Cement and Concrete
Composites Vol. 30, Issue 10, 2008, pp. 986–
991.
[18] Malenab, R. , Ngo, J. , and Promentilla, M.
Chemical Treatment of Waste Abaca for Natural
Fiber-Reinforced
Geopolymer
Composite.
Materials Vol. 10, Issue 6, 2017, pp. 579.
[19] Kalaw, M. E. , Culaba, A. , Hinode, H. ,Kurniawan, W. , Gallardo, S. , and Promentilla,
M. A. Optimizing and Characterizing
Geopolymers from Ternary Blend of Philippine
Coal Fly Ash, Coal Bottom Ash and Rice Hull
Ash. Materials Vol. 9, Issue 7, 2016[20] Pan, Z. , Sanjayan, J. G. , and Rangan, B. V. An
Investigation of the Mechanisms for Strength
Gain or Loss of Geopolymer Mortar after
Exposure to Elevated Temperature. Journal of
Materials Science Vol. 44, Issue 7, 2009, pp.
1873–1880.
[21] Jabbar, A. , Militký, J. , Wiener, J. , Javaid, M.
U. , and Rwawiire, S. Tensile, Surface andThermal Characterization of Jute Fibres after
Novel Treatments. Indian Journal of Fibre andTextile Research Vol. 41, Issue 3, 2016, pp. 249–
254.
[22] Zhang, J. , Feng, L. , Wang, D. , Zhang, R. , Liu,
G. , and Cheng, G. Thermogravimetric Analysis
of Lignocellulosic Biomass with Ionic Liquid
Pretreatment. Bioresource Technology Vol. 153,
2014, pp. 379–382.
[23] Kong, D. L. Y. and Sanjayan, J. G. Effect ofElevated Temperatures on Geopolymer Paste,
Mortar and Concrete. Cement and Concrete
Research Vol. 40, Issue 2, 2010, pp. 334–339.
[24] Rees, C. A. , Provis, J. L. , Lukey, G. C. , andDeventer, J. S. J. Van In Situ ATR-FTIR Studyof the Early Stages of Fly Ash Geopolymer Gel
Formation. Langmuir Vol. 23, Issue 17, 2007,
pp. 9076–9082.
[25] Davidovits, P. J. 30 Years of Successes andFailures in Geopolymer Applications . Market
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Geopolymer 2002 Conference 2002, pp. 1–16.
[26] Duxson, P. , Fernández-Jiménez, A. , Provis, J.
L. , Lukey, G. C. , Palomo, A. , and Deventer, J.
S. J. Van Geopolymer Technology: The Current
State of the Art. Journal of Materials ScienceVol. 42, Issue 9, 2007, pp. 2917–2933.
[27] Provis, J. L. and Deventer, J. S. J. van Alkali
Activated Materials. 2014.
[28] Pan, Z. and Sanjayan, Æ. J. G. An Investigationof the Mechanisms for Strength Gain or Loss ofGeopolymer Mortar after Exposure to ElevatedTemperature. 2009, pp. 1873–1880.
[29] Lee, W. K. W. and Deventer, J. S. J. Van Use of
InfraredSpectroscopy
toStudy
Geopolymerizationof
Heterogeneous
Amorphous Aluminosilicates. Langmuir Vol. 19,
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Issue 21, 2003, pp. 8726–8734.
[30] Palomo, A. , Grutzeck, M. W. , and Blanco, M.
T. Alkali-Activated Fly Ashes: A Cement for the
Future. Cement and Concrete Research Vol. 29,
Issue 8, 1999, pp. 1323–1329.
[31] Barbosa, V. F. F. , MacKenzie, K. J. D. , andThaumaturgo, C. Synthesis and Characterisationof Materials Based on Inorganic Polymers of
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Polymers. International Journal of Inorganic
Materials Vol. 2, Issue 4, 2000, pp. 309–317.

[32] Fernández-Jiménez, A. , Palomo, A. , andCriado, M. Microstructure Development of
Alkali-Activated Fly Ash Cement: A Descriptive
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[33] Criado, M. , Fernández-Jiménez, A. , Palomo,
A. , Sobrados, I. , and Sanz, J. Effect of the
SiO2/Na2O Ratio on the Alkali Activation of Fly
Ash. Part II:29Si MAS-NMR Survey.
Microporous and Mesoporous Materials Vol.
109, Issue 1–3, 2008, pp. 525–534.

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4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ON THE IMAGE BASED ON SMART PHONE USERS IN PUBLIC
SPACE
1Yuki Ogimoto and 2Kazunari Tanaka
1Engineering, Osaka Institute of Technology, Japan; 2Engineering, Osaka Institute of Technology, Japan

ABSTRACTThe purpose of this study is to find the relationship between the characteristics of space and pedestrian features,grasp the relationship between the place of daily, everyday actions, including mobile phone usage action and theimage of the surrounding space. It is ultimately to design by taking human behavior into consideration humanbehavior. The authors extract external factors that appear to be affecting people. Furthermore, the authors willcalculate specific figures and analysis them. Analysis is made on the relationship between the elements of thespatial shape extracted by the physical survey, by the image analysis as well as human attributes. The survey was
conducted in the open space around Osaka station. The author found that the mobile phone operation position isdifferent depending on the state at the time of usage. Currently, we chose a place where smartphones are easy touse. And it is the where people are trying to capture the future visually. Future developments will capture changes
in the field of vision. From there, is to select a place where there is a high necessity for maintenance.
Keywords: mobile phone, pavement, open space, public space

INTRODUCTION

analysis that finds how space design affects
pedestrian influence, while acquiring a large amountof pedestrian behavior data. In order to grasp andexpress the influence of the spatial shape and theinfluence range. The authors extract external factorsthat are appear to be affecting people. Furthermore,
the authors will specific figures and analyze them,
Analysis is made on the relationship between theelements of the spatial shape extracted by the survey
and human attributes.

The purpose of this research is to design pavementtaking pedestrians into consideration, especially theelderly, which is the fastest growing age group. In
recent years, It is considered that the walking path ofpeople is changing due to the design of sidewalks andthe walking environment. By analyzing the elementsof the spatial shape, The authors believe that theauthors can utilize this for urban planning, byclarifying the route according to individual’s age. In
previous studies, walkability tests and analysis were
performed for each type of pavement. There are few
studies on public spaces. If it is possible to grasp therespective walking route by attributes such as age
group, then this can lead to improve functional design
universally. Designers are trying to create space thatvarious people can use easily. However, there are
actually various aspects to consider for design.

POINT OF INTEREST
In conducting this research, the author focuses onmobile phones and public spaces. Currently, mobile
phones are spreading globally. With the advent ofsmartphones from 2010, it became indispensable toour daily lives. The graph shows the penetration rateof communication terminals in Japan (Figure 1).
However, due to mobile phones accidents are also
occurring.

PURPOSE AND METHOD OF RESEARCH
The authors find the relationship between thecharacteristics of space shape and pedestrian features,grasp the relationship with the place of each action
and the shape of the surrounding space. It is
ultimately best to propose a design taking into
consideration human behavior.
In this research, the authors will quantitatively
find the influence of invisible design, utilizing
physical and pedestrian behavior data obtained froma field survey.
Ultimately, the authors will refine it to detailed
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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 1

Japanese communication
Penetration
TARGET AREA

terminal

purpose, we photo shooting at the target location.

of

INVESTIGATION (1)For the target area, the authors wanted to use aspace that had various features common in public
places such as; pillars, walls, stairs, monuments etc.
Osaka is one of the central urban areas in Japan.
The number of tourists is the highest every year,
centered on Osaka, many tourist attractions are
adjacent. Therefore , it was targeted around Umeda ,which is considered to be one of the center areas in
Osaka (Figure 2,3).
In this research, the authors will cover a spaceused mainly by pedestrians. A preliminary survey
was conducted in the open space around Osaka
station, and a place considered to be similar was set
as the target site. In addition, this survey is a placewith many railway stations.

Fig. 2First, the authors took the photos to capture thelocation and constituent elements of the people
standing around, then plotted this on GIS (Figure 4,5).
The one shown in the figure shows the operator of
the smartphone and the non-operator of thesmartphone. The shooting point is indicated by a 60
degree cone. The survey summary is shown in thetable (Table 1).
Table 1 Survey summary
Schedule
Time frame
weather
Target area
Method2017 August 30 (Wednesday),
September 1 (Friday)
8: 20 - 9: 00
Cloudy weather
osaka station around in osaka
photo shooting

People flow at the osaka station

Fig. 4
Position of people focusing on theoperation of mobile phones (crosswalk)

Fig. 3

Target Area

INVESTIGATION AND ANALYSIS
In this research, I can know the usage situation byfind places where mobile phones are used. For that

Fig. 5
Position of people focusing on theoperation of mobile phones (Bus Rotary)
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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig. 7phone

operates without walking the mobile

RESULT (1)Next, from the obtained results, we calculated
where people concentrate (Figure 6). The method ofanalysis was done by density estimation. The red partshows a high numerical value. This method can
reduce the error in the case of representing theconcentrated part of the person. This has been provedby a previous study [3].
In addition, there were two types of behavior for
people who operate mobile phones. The first one isoperates without walking the mobile phone. The
second is operating a mobile phone while walking .

Fig. 8operating a mobile phone while walking

CONSIDERATIONThe results commonly showed that the place ofthe pedestrian crossing was high. Therefore, theauthor considers it necessary to investigate thelocation of the pedestrian crossing in detail.
INVESTIGATION (2)Fig. 6

The purpose of this survey is for detailed analysis
of pedestrian crossings.
The outline of the survey is shown in the table(Table 2). The survey method is movie shooting at
people. The shooting time was 1 minute and 40
seconds. It is 1 minute 30 seconds between the redsignal and 10 seconds of the blue signal.
Also, the author did this survey three times.

This is the example for figure formatting

ANALYSIS (1)Based on the above result, we analyzed the twokinds of behavior of the person who operates themobile phone separately. The method was carried out
at the same point density as before.
The place which shows the high numerical valueof the first graph is in front of the pedestrian crossing(Figure 7). Also, the place which shows the highnumerical value of the second graph is also thepedestrian crossing (Figure 8).

Table 2 Survey summary
Schedule
Time frame
weather
Target area
Method2017 August 23 (Wednesday)
8: 30 - 9: 00
Cloudy weather
crosswalkMovie shooting

RESULTS (2)The results are shown in the figure. In this figure,the authors pointed to the person who operates themobile phone and the person who does not operate
the mobile phone (Figure 9)[2].
The author will compile those results.

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CONCLUSION
In this research, the authors focused attention onpedestrians in public spaces in the city and observed
and analyzed them. From the survey, we were able tograsp those who used cell phones in public spaces.
In addition, analysis clarified where it
concentrates. When touching a mobile phone at apedestrian crossing, 46.2% of the people found thatthey used the mobile phone while walking, The above
results were discussed.
Fig. 9People flow at the osaka station

REFERENCES

Table 3 Operators of mobile phones in crosswalks
Contents
Operator of mobile phone
Non-operator of mobile phone
Total number of two[1] Maeda K., Higa K., Tanaka K. and Yosikawa S
Civil Engineering Association Kansai Branch
Annual Scientific Lecture Summary IV-19 2015[2] Yanobe T., Tanaka K and Yoshikawa S, STUDYDOWNTOWNSTVANGERTOTHE
PEDESTRIAN SPACE 25.A-3-3(CD)[3] Sato T. and Maruyama T., Analyzing Visitors’
Activity Area in Downtown Kumamoto using
Smartphone-based Travel-Survey Date Journal of
the City Planning Institute of Japan, Vol.50 No.3
2015 October .
[4] Yogo Y., Hayashida K. and Watanabe H.,
Spatial usage behavior by age in station concourse
2012 pp651 ~ pp652[5] E.FUNABIKI N.MATUMOTO I.KATAYAMA
elationship between visitor behaviour at“EkiNaka Squares” and spatial composition. ―Comparison of JR Tokyo Station Marunouchi
North Exit Concourse and JR Sapporo Station
West Concourse―[6] Kabata A., Oonishi R. and Yamaguchi K.,
Migration characteristics of rental cycle in Kyoto
city sightseeing using GPS log data - For foreign
tourists – Proceeding of city planning No16 2018p37-40[7] AIHARA K., Grasping dynamism of tourist
behavior and thoughts through big data analysis
JOHO KANRI Vol.59 No11 February 2017

Number ofpeople145
370
515

ANALYSIS (2)From the calculated result, the proportion ofpeople who operate mobile phones while walking was
calculated (Table 4). All proportions were calculated
based on the number of pedestrians caught in thevicinity of the pedestrian crossings. The purpose ofthis analysis is to clarify, as manipulation of mobile
phones while walking is becoming a social problem.
Table 4 Percentage of operators of mobile phones atpedestrian crossingsContents
Operator of mobile phone (515)
People who start to operate
mobile phones while
walking(515)Percentage of mobile phone
operators walking smashing (145)

Proportion(%)
28.2
13.0

46.2

DISCUSSION
The place to operate the smartphone is a place toforcibly stop walking.
Therefore, it is considered to be a place where
pedestrians make time to operate mobile phones.
At the present stage, I studied weekday.
However, the attributes of people change on holidays.
Therefore, if you investigate holidays as well, you candesign suitable for the city.

1103

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

IMAGE ANALYSIS ON NIGHT SEQUENTIAL IMAGES
Hiroki Komai1 and Kazunari Tanaka2
Engineering, Osaka Institute of Technology, Japan; 2

1

ABSTRACTNight scape has a beauty that attracts people. In recent years, due to the spread of cameras and SNS, there aremany new trends and new popular spots. As a byproduct, this seems to attract tourist. In this research, thecharacteristics of the night scape were analyzed using the photos and post contents from SNS. As a result, by the
analysis to evaluate a part of the values, the examples: the perseverance, the painfulness and the merriment areappeared of the night scape.
Keywords: Image analysis, Night scape, SNS

INTRODUCTION
N Night scape attracts a lot of people regardlessof race, gender, generation. It is a visual stimulus thatbrings healing to modern people who have various
stresses in modern society. The night scape has anability to allow one to collect themselves. In recent
years, popularization of smartphones and digitizationof cameras has progressed, giving many people easy
access to cameras that are now high performance. At
the same time, information exchange platforms ofSNS (social network service) have become popular.
It became possible to “share” one’s information or“moments” with unspecified numbers of people. SNS
leads trends and when people shoot a night scape with
their camera and post it to SNS the post receives a lotof attention and that location becomes a popular night
scenic spot. That popular night scenic spot is thensought after by tourists which leads to increased
regional revitalization. It is indispensable to focus
attention on people’s consciousness to find acharacteristic night scape.

PURPOSE AND METHOD
In this research, we aim to grasp what kind of
emotion people feel from a night view. This insight
into emotion should become a clue for thecharacteristics of an optimal night view.
For the research method, we collected lyrics fromsongs related to nightscape photos and night scenes.
After
that,
analyzeclassification
andcharacteristics of nightscape photograph and analyze
the lyrics.
Next, we retrieve words obtained by analysis ofcollected lyrics and classify them.
Finally, from the relationship between theanalysis result of the night scape photograph and thewords obtained by the lyrics analysis, we analyze theimage of the nightscape picture and make conclusions.
HOW TO COLLECT PICTURES
Flickr is a photo posting site from overseas
boasting the most photos posted in the world. In
Flickr, registered users can freely classify photos in
Flickr with keywords called "tags". In addition, eachuser has a function to create a "set" in which
thumbnails of a plurality of photos are arranged in thesame title on their respective top page. The sets here
are more flexible than the traditional file sorting
method, it is possible to put one picture in multiple
sets or not in any set. In this way, it is easy to classify
and search pictures, as the relationship between
pictures and words has an SNS-like aspect.
Furthermore, Flickr has released its own API(Application Programming Interface), allowing
applications to "mash up" with SNS.
In this research, we selected Flickr as a photocollection site.

Fig. 1 Night scape1104

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COLLECTION OF LYRICS
In this research, we use lyrics to analyze
nightscape pictures. The lyrics to be used were forsongs in which words related to night were included
in lyrics out of a total of 280 songs by the ranking ofsales each year from 1989 to 2016.
ANALYSIS OF LYRICS
In this research, text mining was used for lyrics
analysis. Text mining is a method for discovering
useful information from sentences.
It uses a method of natural language processing to
extract bits from sentences by dividing sentences intowords and phrases and statistically analyzing theoccurrence frequency of words and the relationshipbetween words. Therefore, text mining is considered
to be an effective means for realizing the objective ofanalyzing a large amount of text data efficiently andobjectively.
It can be divided into parts that categorize
sentences by natural language processing andstatistical analysis of categorized data. Therefore, inorder to implement it, software that executes natural
language analysis to separate sentences into words
and software to perform statistical analysis are
required. In the case of text mining software, there issoftware capable of performing both of thesefunctions, and software only capable of categorizing
the former sentences.
In this research, we analyzed lyrics using "IBMSPSS Text Analytics for Surveys" which categorizes
sentences.
For lyrics of extracted songs, we extracted words
expressing night scenes and adjectives and adverbs
that psychologically evaluate them. Examples areshown in Table 1 and Table 2.

Fig. 2 Examples of pictures collected using Flicker
COLLECTING NIGHT SCAPE PICTURESIn this research, we analyzed images of night
scenery searching photos with “night view” tags.
However, there are enormous amounts ofphotographs taken from countless nightscape spots
making it difficult to analyze all of them. Therefore,
in this research, we selected nightscape spots andtargeted nightscape photographs taken within them.
Night scene spots were targeted at 26 places withreference to the website. After that, we collected
photographs of the target night scenic spots andsorted out pictures other than night scenes. Then, sixtarget night spot spots where the ratio of the total
number of searches and night view photos exceeded
30% were taken as the target of this study.
Table 1 Percentage of target spot and night view
photo
place
Mount Hiei driveway

Mount Oiwa view place
Mount Mandoro observatory
Abeno harukasu
Seaside cosmos
Umeda sky building
Orix Honmachi building
Mount Satsuki driveway

Izumiotsu parking area
Jusou Pass observatory
Kanku outlook hall
Hannan sky town
Mount Maya
Rokkou garden terrace
Mount Rokkou observatory
Mount Nadamaru park
Maiko park
Kobe port tower
Venus village
Port Island north park
Itami sky park
Yamatedai north park
Awaji service area
Mount Wakakusa
Shigi Ikoma sky line
Saisyogamine view place

percentage(%)
7.6
0.0
100.0
13.8
23.1
11.2
15.2
56.1
7.6
50.0
33.6
6.5
27.3
6.5
7.8
37.8
66.0
4.1
0.4
5.9
2.2
25.0
-

Table 2 Extraction of night scenery and psychology
Night scape word
city
light
sky
night sky

Psychological words
get over(norikoeru),miracle(kiseki),Painful(tsurai),etc…
To watch over(mimamoru),To succeed(setsunaku),etc…
happiness(siawase),break down(kowasu),To die(kareru),etc...
Important thing(taisetsunamono),Goodbye(sayonara)

Table 3 Extraction of night scenery and psychology
Night scape word
street light
light
sky
night skybridgesea

1105

Psychological words
severely
To watch over(mimamoru),To succeed(setsunaku),etc…
happiness(siawase),break down(kowasu),To die(kareru),etc...
Important thing(taisetsunamono),Goodbye(sayonara)
To be sunny(hareru),My chest hurts(munegaitamu)
break down(kowasu),to hug(dakisimeru),To die(kareru)etc…

SEE - Nagoya, Japan, Nov.12-14, 2018

EVALUATION OF NIGHT SCAPE PHOTOS
THROUGH LYRICS
In this study, we have grasped the image of thenight view photograph from the relationship between
the constituent elements and lyrics expressing thepsychology associated with the extracted night viewphoto. Here, the constituent elements of night scenes
are taken out, and words of psychology evaluation arearranged in parallel for each.
RESULTS AND DISCUSSION
Analysis of nightscape photos and lyrics revealed
that various emotions can be obtained from the nightview. The results found that night scenery attracts
people with its beauty, but also that a possibility that
simply feeling that it is beautiful is only part of thesurface layer. Table 2 and Fig. 3, and Table 3 and Fig.
4 correspond to each other. Starting with Table 2 andFig. 3, it can be expressed that "a hardship must be
overcome". With Table 3 and Fig. 4, it can be
expressed as "I hope to focus on important things".
From these analyzes and considerations, it turned outthat people have various emotions, regardless of theirconsciousness, when looking at night views. There
was also a tendency that positive and negative
emotions coexisted with the photographs targeted thistime. These provide suggestions on how to draw out
the charm of the night view attracting people.

Fig. 4 Example 2 of analysis and consideration
CONCLUSION
In this research, we tried grasping emotions andimages obtained from night scenes using night viewphotos and lyrics. As a result, we think that we found
one evaluation method of a characteristic night timelandscape. Moreover, it was revealed that various
emotions are obtained from the space constituent
elements of night views. From this result, I think that
we could grasp a part of the charm of the night view.
I think that discovering the attractiveness ofnight views using new indicators and methods will besignificant in the future nightscape analysis.
Moreover, we think that this could lead to thepossibility of contributing to the creation of acharacteristic night view.
REFERENCES[1] Hiroki T, Kazunari T, Shin Y , Boundary
focusing on light environment in urban space ,Civil Engineering Association Kansai Branch
Annual Scientific Lecture Concert Summary, IV14, 2013.
[2] Yuji O, Kazunari T, Shin Y , Analysis and
Evaluation of Landscape Based on Tourist
Behavior, Geographical Information System
Conference Presentation Proceedings, Vol. 26,
2017,C-1-2(CD).

Fig. 3 Example 1 of analysis and consideration1106

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

ON THE SPATIAL ELEMENTS FROM A BIRD’S-EYE VIEW SCAPE

1

Nobuaki Tanaka1, Kazunari Tanaka 2
Osaka Institute of Technology, University;2,Japan

ABSTRACT
When it comes to landscapes, beautiful landscapes are formed from local climates such as history and customs
by elements such as varying nature and demographic structures. A feature that creates these beautiful landscapesis the linear landscape element. This linear element is characterized as being beautiful because landscape elementsthat can be continuously viewed form a beautiful landscape such as a building that looks continuous due to theshape and color, in addition to linear landscape elements such as rivers and roads. Hypotheses concerning
continuity and image are present not only in urban landscapes, but also in the landscape of rural areas andmountainous regions. Therefore, in this research, focusing on a bird's eye view from high vantage points, we aim
to examine urban landscapes by analyzing their elements, shape, view and area. As for the examination method,
we analyzed and expressed the continuity of streets, rivers, green roads, etc., using image analysis and GIS. From
the results, we extract and consider the relationship between the position and shape of elements with regards tocontinuity and the beauty of urban landscapes.
Keywords: High-rise building, Bird's eye view, Landscape, Continuity, Visibility analysis

INTRODUCTIONPURPOSEIn Japan, there are various climates. There areplaces to enjoy beautiful scenery, such as views froma natural observation point such as a mountain, or aview from man-made point such as a bridge. Theview from a mountain or high-rise building etc.,
provides a majestic landscape that people cannot see
much in everyday life. The landscape from thisaltitude is called an “overhead view”, which isimportant when viewing landscapes(Fig. 1).
Meanwhile, in recent years, various techniques
have been used to capture attractive urban landscapes.
A combination of elements such as arrangement andshape of buildings and trees etc., that is continuous iswhat forms a beautiful landscape. Sexuality is also
one of the elements that directs the appeal of thelandscape, for example, a sprawling grassland, thescenery of a city from the top of a mountain or theroof of a building, the continuous light in a night view,etc., all feel beautiful. Such continuity is important informing a beautiful landscape because it is possible toview from various places and angles. We believe that
future landscape design can be done by grasping therelationship between the continuity of the city, andthe overlooking landscape.

There are many places where we can see the urban
landscape, for this research we focused on high-risebuildings. In Japan there are more than 500 buildings
over 100m tall. Offices and condominiums are
becoming taller, and it is becoming more common forpeople to view the urban landscape from a bird's eye
view.
Also, beautiful urban landscapes are related toshapes and colors that are continuous. Hypotheses
about continuity and image are established not onlyin the city, but also in the landscape of rural areas andmountainous areas. However, in general high-risebuildings are concentrated in big cities, and therefore,
in some cases the buildings obstruct the view.
Therefore, for this research it is crucial to be able toobserve the unobstructed urban landscape from abird's-eye view from a high-rise building in Osaka
city, and subsequently examining the urban landscapeby analyzing elements and shapes, view and areas.

Fig. 1METHODFirst of all, a questionnaire survey was conducted
to grasp the relationship between the overhead viewand the landscape elements in a linear direction. From
the results, when looking at the city from a bird's-eye
view, it was more attractive when the roads, rivers,
and greens were linear as landscape elements. Taking
this into account, we will discover where we can see
many elements when looking at a target area. By
analyzing the depression angle from the test building,we grasp how much we can see continuously from a

Picture of bird's eye view
1107

SEE - Nagoya, Japan, Nov.12-14, 2018

bird's-eye view.
INVESTIGATIONA questionnaire survey was conducted using thepaired comparison method for the influence ofcontinuity from an overhead view(Table 1). This
investigation is a method of choosing which one isperceived as more attractive by showing two images.
This time, we collected 10 pictures randomly takenfrom a high-rise building. From these images, we
altered them by removing linear roads, rivers, andgreens (Fig. 2~3). We had 20 of these images
randomly arranged. The questionnaire date and time
and target number of people are as shown in Table 1.
The average of the questionnaire results was graphed(Fig. 2). Results showed that overall the landscape
was considered more attractive when the linear
elements exist. However, in the case of 1 and 8, theimage without the linear landscape elements wasmore attractive. The reason for this is that in the caseof 1, we believe that shadows affected the outcome.
In the original image, the difference between light anddark is small, and in the created image, the createdimage is better because the light and dark areas areclear. In the case of 8, we thought that the
miscellaneous townscape looked beautiful, thus
making the created image more attractive.

0.8
0.6
0.4
0.2
0
1

Date and time
MethodFig. 2

Fig. 32

3

4

5The original image

Fig. 46

7

8 9 10
Photo number

Created image

Average value of the questionnaire result

In order to ascertain the validity of this result, a ttest was performed (Table 2). By conducting this test,
it can be confirmed as to whether or not the given
results were by chance. Since the absolute value ofthe t value is larger than the absolute value of theboundary value of the t value from the table, and thevalue of the p value is smaller than 0.05 even from thep value, there is some statistically significancebetween the two variables. This means that thedifference between the average values cannot be said
to be 0. Therefore, from this result it can be said thatthe more continuous the road, river, greenery etc., themore statistically significant and attractive thelandscape. However, there were some results that did
not have significance.

Table 1 Outline of questionnaire survey
TargetGraph on average

Score
1

Osaka Institute of Technology
students 78 people
9-May-18
Questionnaire survey by paircomparison

Table 2 Result of t test of 1 and 11
name
Average
Variance
Observed number
Pearson correlation
Difference fromhypothesized
averagedegree of freedom
t-ratioP(T<=t) One sidet Boundary value
One sideP(T<=t) both sides
t Boundary value
on both sides

Original image

Create image
1108

10.51282051
0.25308025
78
0.76777190
077-3.36504523
0.00059788
1.66488454
0.00119575
1.99125440

110.64102564
0.23310023
78

SEE - Nagoya, Japan, Nov.12-14, 2018

INVESTIGATION
The target area of this research is Osaka city.
Osaka city has rivers that are wide and winding withrich greenery and parks along the banks, along withnumerous buildings and structures. In addition, largescale roads are stretched in a lattice pattern, and thelandscape is formed taking into consideration thecontinuity of buildings and harmony between theroads and buildings (Fig. 3).

Fig. 5
Skylinedistribution [1]possibility

appearance

DEPRESSION ANALYSIS

Fig. 5

Depression angle analysis was conducted inorder to grasp the area that would be visible from abird's-eye view from the selected building. The
depression angle analysis was carried out using the
DSM to grasp the overhead view that can be seenfrom each viewpoint, and the position of the point
was set at a height of the observation platform (at1.5m). As for the depression angle, we also verified
the bird's-eye view from existing research andobtained quantitative analysis results (Figure 3).
From this result it is possible to analyze at the lower
limit of the depression angle of 30 °or more.

Target area

SELECTION OF VIEWPOINT
We selected high-rise buildings as viewpoints.
To do the selection, we use skyline possibility
analysis from existing research[1]. The reason forusing this analysis is that this analysis identifies theareas where you can see the skyline from various
places. The area where the frequency of occurrenceof skyline possibility is high is a boundary line that
separates the ground from the sky, which can be said
to be an obstacle or a noticeable object. On thecontrary, when viewed from the building, you can see
a wide range of landscapes. From this relationshipyou can see the area where urban space is regarded asa wide area landscape. To do this analysis, we created
a 250m mesh DSM (Digital Surface Model) fromexisting research; Osaka city, which is the target area,
has a generation range of about 20km square. Using
this DSM, we identified a place where you can see awide area overlooking the city of Osaka. The darker
the blue color, the easier it is to view the skyline. As
a result, it came out that the Osaka stationneighborhood and Tennoji station would be highvisibility. Narrowed further, Ebuchi Harukasu, aplace with public nature was selected as an optimal
location.

Fig. 6 Hypothetical number of Bird's eye view
scape[2]Table 3 Hypothetical number of Bird's eye view
scape[2]Angle
Viewpoint height（
Distance（DH））
5.7H~7.1H
Visual axis（- 8〜-10°Central vision）
Depression general
-30°
1.7H
lower limit
Minimum-45°
Hdepression angle
lower limit
Hypersurface
19H~29H-2〜-3°
general upper limit

1109

SEE - Nagoya, Japan, Nov.12-14, 2018

The analysis results from the observatory of
Abeno Harukasu is shown in Figure 6. From theresults, it was possible to grasp the area that can beviewed from a bird's eye view from the viewpoint.
Specifically, there were many areas in the southernpart of Osaka city which are in the good visible
region. However, the scope of view in Umeda islimited because there are many high-rise buildings.

color difference, we also want to represent thecontinuity of the landscape component quantitatively.
REFERENCES[1] Okabe Y, Yoshikawa S and Tanaka K.,
Landscape Analysis of Skyline in Building
Group and Mountains, Conference ofGeographical Information Systems Conference
Presentation Papers, Vol. 25, D-4-4.
[2] Shinohara O, Higuchi D., Natural terrain andlandscape, Civil Society year Science Lecture
IV,1971.
[3] Sato T, Yoshikawa S and Tanaka K., Modelingof Nightscape, Conference of Geographical
Information Systems Conference Presentation
Papers, Vol. 18, pp.275-278.
[4] Masuno T, Yoshikawa S and Tanaka K., The
Quantitative Description of the Continuity on
Cityscape, Conference of Geographical
Information Systems Conference Presentation
Papers, Vol. 17, pp. 583- 586.

High

Low
Fig. 6

Result of declination analysis

RESULTS AND DISCUSSION SECTION
We grasp the area where we can see the target areafrom the result. Also, I can see various things such as
roads and buildings. However, in this analysis, wehave not been able to grasp areas with continuity.
Therefore, we think that it is necessary to classify it
as buildings, roads, etc. and find continuity as anoverlooking landscape.
CONCLUSION
In this research, we analyzed the overhead viewand continuity. At first, when looking at the bird's-eye
view, we investigated whether it is more attractive tohave linear landscape elements such as roads andrivers. As a result, it was concluded that it is better tohave linear elements. From this, we analyzed Osaka
city. From the perspective of the skyline appearance,
we found a viewpoint with a nice view which one cansee the various landscape components in Osaka citysuch as concrete, declination analysis, continuously
as an overlooking landscape.
As a future prospect, we analyzed the depression
angle only from a close-up view, but since theviewable display area changes according to the height,
analysis including the distant view area is necessary.
Moreover, by visualizing the boundary between the1110

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE EFFICIENCY OF FLY ASH AND CEMENT SLAG TO
DEVELOPMENT BUILDING
Ranti Hidayawanti1, Supriadi Legino2 , Iriansyah Sangadji3,Rony Panca Adi Widodo4
1,2,3
Sekolah Tinggi Teknik PLN, 4Adhimix Precast Indonesia
ABSTRACTIn the world of construction, concrete is the most important element in which in the concrete there is a collectionof natural mineral aggregates or granules that can be separated by mechanical means if the aggregate is stirred inwater. A large amount of raw material is used in the manufacture of concrete, it is commonly known that Fly ash
and cement slag can be used as cement replacement materials.. This is due to the difficulty of the availability of
cement in the market and the impact of rising prices for cement which continues to soar up, so that waste can berecycled for making concrete. This paper investigates the ratio of fly ash and 50% cement slag and waste
management used. To produce lightweight concrete with environmentally friendly structure utilized coal waste in
Suralaya such as fly ash, cement slag as a good soil stabilization material in the construction of high rise buildings.
This research has analytical compressive strength at the age of 1,3,7 and 28 days, the need for water for the same
workability. From experimental data obtained the same quality using Cement Slag using a smaller number of
average 70 kg / m³ and Initial setting time of Cement Slag 50% on average 36 minutes faster than FA 50%. Besides
that the utilization of fly ash and cement slag can minimize waste and with the use of the mixture can reduce
production costs. From a financial standpoint, the application of this system can prevent companies frompotentially losing billions / year.
Keywords: Fly ash, cement slag, concrete, compressive strength, production cost.
I. INTRODUCTION
The construction of high-rise buildings currently
demands good quality materials, almost 70% of theuse of materials from the building is concrete so thatto meet the construction of high-rise buildings will be
demanded high-quality concrete[1]. It has beencommonly known that the use of fly ash can be used
for mixed use of concrete but what about the slag
concrete in which both components are hazardous
waste?. The results show that significantly improved
workability and strength development are obtained at
an increased admixture content [2]. Many researchhas been done to review the effect of added
ingredients on improving the quality of concrete. Oneof the added ingredients that is often to be used in
mixed concrete mix is fly ash and cement slag. Dueto their good performance and environmental
friendliness, fly ash-based construction materials
have great [3]. Fly-ash which is the remnants of coal
combustion, flowed from the combustion chamber
through the kettle in the form of smoke bursts, which
is formed of fine particles and is an inorganic material
formed from the change of mineral materials due tothe combustion process of the coal combustion
process on the generating unit steam (boiler) will
form two kinds of ash that is fly ash (fly ash) andbottom ash (bottom ash). In Indonesia, the use of
toxic hazardous waste such as cement slag, Fly Ash,bottom ash cannot be used directly but there must bea waste management. Fly Ash-Bottom Ash isclassified as hazardous waste so that any management
in storage, transport, collection, utilization,
management and stockpiling must be recorded andtraceable as evidenced by the manifest document andeach of the actors shall have a valid license andappropriate with designated it. Disposal of fly ash
from coal-fired power plants causes economic andenvironmental problems. Violations of the provisionsof hazardous waste management regulations result in
administrative sanctions up to criminal sanctions in
the form of prison confinement 1-5 years and a fineof 1-5 billion as stipulated in the Law of Indonesia
No. 32 of 2009 on the management and protection of
the environment. The purpose and objectives of thispaper Innovation are as follows :- Making Effective Management System whichfacilitate the process of data collection of coal ash
in and out every day (First In First Out).
‐ Knowing the quality of Fly Ash and Cement Slag
‐ Determine standard of cement use for concrete
mix when using fly ash and cement slag withcomparison 50%‐ Knowing the level of efficiency of using fly ash
waste and cement slag waste.
II. LITERATURE REVIEWThe production process of electricity of Coal
Steam Power Plant produced side products which are
1111

SEE - Nagoya, Japan, Nov.12-14, 2018

Fly ash and bottom ash. Fly ash is a solid waste
produced from coal-fired power plants[4] The
product are kept in big stack with size of particles
grains smooth[5]. From the waste can be used as
mixture of cement replacement for high rise building.
According [6] to form an economical aggregate sandsubstitute to be used as a concrete filler product. Fly
ash can be used for concrete mixed.. In utilization ofwaste can be compared to the other waste such as
cement slag. Cement slag is a chemical reaction as
one of popular activation methode which isconsidered to fix hydrolic characteristic of the slag[7]. This work presents chemical activation of blastfurnace slag-blended Portland cement. According to[8] a partial replacement of Portland cement (PC) by
ground granulated blast furnace slag (GGBFS)is aneffective method to improve the durability of concretedue to its lower diffusivity and higher chemical
resistance compared to PC. Both media will react todecrease production cost because the usage of cement
is relatively increase in every years. The productionof cement, the primary ingredient in concrete [9] The
production cost pressed in order to get the highest
advantage but still considered the quality without
relieve the ingredients which cause bad quality in thedevelopment of high rise building.
For concrete calculations in finding correlationgraph w/c (cement water factor) to compressive
strength used exponential regression formula and in
the calculation used MS Excell program.
Y= aebx...........................................................1)a = compressive strength (kg/cm2)
b = w/ce = exponential (2,718)
R = Coefficient (if close to 1 then the value is good)
As for determining the water requirement against w/c
used the formula :Y = a+bx .............................................................2)a = water requirement (ltr/m3)
b = w/cIII. RESEARCH METHODOLOGY
In this research the methodology is used as follows :Fig.1 Flowchart Methodology
Starting from the management waste, it will becheck through the manifest. During theexperiment, it get observed and test such as
workability (slump), the need of water for thesame workability to seek the correlation graph ofw/c toward tensile pressed at the age of 1,3,7 and
28 days and determined the need of cement, waterand price for concrete which is using fly ash andcement slag.
IV. EXPERIMENTAL SETUP
The experiments performed on a laboratory scale
include mortar cube experiments and concrete
experiments using a small mixer.
Materials used in this experiment are as follow :‐ Cement : Type I (OPC) Ex. PT. Indocement
Tunggal Perkasa‐ Fly Ash 50% : Ex. Pelabuhan Ratu
‐ Source Fly ash taken from this research including
Fly ash ex. Suralaya Factory, Fly ash ex. Pindodeli
and Fly ash ex. Indhobarat, Fly ash ex. Pelabuhan
Ratu. Most of the usage of fly ash using fly ash ex.
Suralaya 96%, the use of fly ash ex. Pindodeli 2%
while Fly ash Indobarat 1%, therefore it is needed
another source as alternative pozzolan as mineral
add material in order to get appropriate quality andcost. Other fly ash alternatives are obtained fromvarious sources that produce Fly ash, for example
the Jakarta cement slag.
‐ Cement Slag 50% : Ex. Semen Jakarta‐ Split : Split Ex. BCA Suplier Bangun Jaya
‐ Sand : Natural Sand Ex. Belitung‐ Water : Well Plant Precast Cibitung

V. RESULT AND DISCUSSION
5.1 Transportation of Hazardous waste

1112

SEE - Nagoya, Japan, Nov.12-14, 2018

Fly ash and bottom ash are the dominant hazardous
waste generated from Power Generation activities in
PLTU Suralaya. Not all waste can be used for
concrete mixes for construction buildings, but forcoal waste can be used as well. The amount of ash
produced depends on ash content in coal. Here is thehazardous Waste Distribution Flow.

5.3 Concrete Experimental Result
Concrete experiments were performed with thecomposition of Fly Ash 50% and 50% cement slag
are as follows :Table 1. Test Result Data of Fly Ash Test with
Cement Slag
2

Compressive Strength (kg/cm ) a age
w/c 0,5 FA 50
1 day
104
3 day
219
7 day
330
Percentage of comparison
1 day
1,00
3 day
1,00
7 day
1,00
28 day1,00
Realitation Trial Mix
Realitation w/c
0,500
1,000

w/c 0,5 SJ 50
101
229
353
0,97
1,05
1,07
1,07
0,500
1,000

3

0
0
Change of water (ltr/m )change of water (%)
1,000
1,000
Initial seting time
hours:minutes
05.40
05.04
Delta
00.36
Slump (cm)Slump Plain
10
5
Slump After 30'
Developing Compressive strength
Age of day% Compressive Strength after 28 days
1
0,45
0,41
3
0,95
0,94
7
1,44
1,44
28
1,00
1,00

Fig.2 Process Flow of Hazardous Waste Manifest
Distribution
The Manifest document consists of 7 sheets, withthe final holder of the manifest for the 3rd and 7th
sheets hold by the sender (producer), sheet 1 is holdby the carrier, the 2nd and 5th sheets are hold by the
Ministry of the Environment, the 4th sheet is hold by
the recipient, the 6th sheet is hold by the governor
which is delivered by the carrier.

In order to know the quality of Fly Ash and Cement
Slag, and viewed from Mortar and concrete
experiment then it is got the combination as follows:

5.2 Mortar Experiment Result

Compressive strength
Fig.4 The relation of compressive strength against
W/C.

Fig.3 Laboratory Test Result on Mortar Fly Ash
Comparison with Cement Slag

The above graph shows a compressive strength
relationship to w / c, where the compressive strengthof cement slag is relatively the same as that of fly ash.
From the analysis of the exponential linear regression
graph above can be seen near the scatter point or
coefficient value R = 1.

Fly ash and slag cement have been treated sustainable
materials for the use of cement products for
wastewater infrastructure due to their capabilities ofcorrosion resistance[10] .

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SEE - Nagoya, Japan, Nov.12-14, 2018

Fig.5 The relation of water requirement with w/c
From the above linear regression graph analysis canbe seen the value of R = 1 means good and can beused.

develop construction technology ranging fromconstruction materials to technology used in theconstruction itself. The development of these
construction materials can be seen from the many
types of added materials used as additives in thenormal concrete mortar. These added ingredients aim
to improve the quality of concrete to be better andenviromentally friendly. Alkali-activated fly ash-slag(AAFS) concrete is a new blended alkali-activatedconcrete that has been increasingly studied over the
past decades because of its environmental benefits
and superior engineering properties. [10] To know thequality of cement against fly ash, and evaluated frommortar and concrete experiment, it is got combination
as follows :Table 2 Comparison of composition for efficiency
w/c
Quality K Goal kg/m3

Fig.6 Distribution of Molen Truck for High Rise
Building foundry with Fly Ash and Cement Slag
Nowadays, concrete is a material widely used tomake high-rise buildings. Thus to meet theconstruction of high-rise buildings will be demanded
high-grade concrete. But along with the increasing
human need for better infrastructure, then theconcrete with high quality is much needed, forexample for high rise buildings.

Fig.7 Floor and column concrete with concrete
containing FA and cement slag
The development of construction in Indonesia
occurred so fast, this research has been done towater (ltr/m3)

Cementius

Price (IDR)

FA 50

Slag
cement 50

FA 50

Slag
Cement 50

FA 50

Slag
cement 50

FA 50

Slag
Cement 50

100

149

0,670

0,754

163

166

243

221

395.940

400.190

200

249

0,554

0,630

171

174

308

277

413.879

417.701

300

349

0,458

0,526

178

182

389

346

438.197441.215

400

449

0,379

0,439

186

190

492

432

470.279471.946

500

549

0,313

0,367

194

198

620

539

511.874

511.418

600

649

0,259

0,307

202

206

780

671

565.181561.524

700

749

0,214

0,256

210

214

979

834

632.950624.607

From the table above with the comparison of thecomposition between Fly Ash and Cement Slag 50%
for high rise building, for example taken K300 with
FA 438.197 (IDR) and cement slag 441.215 (IDR)
whereas for normal production cost without the use
both materials with the same quality is about 470
million, so the diffence is about 30 million (IDR). If
the production cost per year, for example 1 billion/m3
than the efficiency can be generated is 1 billion x 30
million = 30 billion, so with utilization of fly as andcement slag it can avoid the company from potental
loss of billions/ year. The cost of production is theamount of costs incurred by an industry to process
raw materials into finished goods. By optimizing theavailable production factors optimally in order toproduce optimal output.
IV. CONCLUSION
With the implementation of Innovation the use of
Fly Ash and Cement Slag and by experimental
method, it can be concluded that :1. The use of Fly Ash and cement Slag semen isneeded to replace the role of cement and sand.
2. With the same w/c of compressive strength
cement slag 50% bigger than Fly Ash that is equal
to 23%.
3. In order to get the same workability the water
usage of cement slag 50% is larger with averages
4 liters / m3
4. The bigger usage of fly ash and cement slag
materials made smaller production cost which canhelp the need of the development in the future.
1114

SEE - Nagoya, Japan, Nov.12-14, 2018

ACKNOWLEDGEMENTS
The authors acknowledge to Leaders of STT PLN
who have provided good support morale material andconcrete labolatory civil engineering of adhimix also
committee of Science, Engineering & Environtment.
REFERENCES[1] R. Hidayawanti, S. Legino, and D. Harjanto,“OPTIMIZINGTHEUTILIZATIONCEMENT SLAG AND FLY ASH
O F , ” n o . March, pp. 14–18, 2018.
[2] A. Keulen, Q. L. Yu, S. Zhang, and S.
Grünewald, “Effect of admixture on the pore
structurerefinement
andenhancedperformance of alkali-activated fly ash-slag
concrete,” Constr. Build. Mater., vol. 162, pp.
27–36, 2018.
[3] G. Xu and X. Shi, “Characteristics andapplications of fly ash as a sustainable
construction material: A state-of-the-art
review,” Resour. Conserv. Recycl., vol. 136,
no. August 2017, pp. 95–109, 2018.
[4]
X. Tan, F. Han, and F. Zhao, “Preparationof Autoclaved Foamed Concrete Block
from
Fly
Ash
and
C a r b i d e S l a g , ” v o l . 02006,
pp. 1–6, 2018.
[5]

[6]

[7]

[8]

[9]

[10]

L. Nguyen, A. J. Moseson, Y. Farnam, and

1115

S. Spatari, “Effects of composition andtransportation logistics on environmental,
energy and cost metrics for the productionof alternative cementitious binders.,” J.
Clean. Prod., vol. 185, pp. 628–645, 2018.
R. N. Lieberman et al., “Environmental
impact and potential use of coal fly ash andsub-economical quarry fine aggregates in
concrete,” J. Hazard. Mater., vol. 344, pp.
1043–1056, 2018.
A. Allahverdi, A. Maleki, and M.
Mahinroosta, “Chemical activation of slagblended Portland cement,” J. Build. Eng.,
vol. 18, pp. 76–83, 2018.
E. Yogarajah, T. Nawa, and T. Igarashi,“Physical, chemical, and mineralogicalcharacteristics of blast furnace slag on
durability of concrete,” MATEC Web
Conf., vol. 147, p. 01007, 2018.
L. C. Chao and C. P. Kuo, “Ternary
Blends of High Aluminate Cement, Fly ash andBlast-furnace slag for Sewerage Lining
Mortar,” IOP Conf. Ser. Mater. Sci. Eng.,
vol. 303, no. 1, 2018.
G. Fang, W. K. Ho, W. Tu, and M. Zhang,“Workability and mechanical properties ofalkali-activated fly ash-slag concrete cured
at ambient temperature,” Constr. Build.
Mater., vol. 172, pp. 476–487, 2018.

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

GEOSPATIAL PREDICTION OF SOIL EROSION USING MODIFIED
BIVARIATE FREQUENCY RATIO TECHNIQUE
Abdulkadir Taofeeq Sholagberu1, Muhammad Raza Ul Mustafa1,2, Khamaruzaman Wan Yusof1, Ahmad Mustafa
Hashim1, Muhammad Waris A. Khan3
1
Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS, 32610 Seri
Iskandar, Perak, Malaysia
2
Centre for Urban Resource Sustainability, Institute of Self-Sustainable Building, Universiti Teknologi
PETRONAS, 32610 Seri Iskandar, Perak, Malaysia
3
Faculty of Industrial Management, Universiti Malaysia Pahang, 26300 Gambang, Pahang, Malaysia

ABSTRACT
Erosion is one of the most serious environmental problems with adverse effects on agricultural productivity
and hydrological systems. Prediction of erodible locations is very crucial for sustainable watershed management.
This study is aimed at predicting geospatial distribution of erosion under the influence of causative factors (CFs)using modified bivariate frequency ratio, GIS and remote sensing techniques. The study considered dynamic CFs
which often ignored in previous studies together with static CFs for erosion susceptibility analysis. Essential
factors such as drainage density, lineament density (LD) and length-slope (LS) were selected as static factors, andland surface temperature (LST), soil moisture index (SMI), normalized difference vegetation index (NDVI) andrainfall erosivity as dynamic factors. Spatial correlations between classes of each CFs and occurrence of erosion
were evaluated. The results showed that most erosion occurred in the class of 150.81 - 282.75, 0.337 - 0.369
km/km2, 1.174 - 1.255, 24.20 - 32.64 oC and 1.250 - 1.358 for LS-factor, LD, NDVI, LST and SMI respectively.
Analysis of prediction rates for each CFs indicates that LS-factor, SMI and LST were the most prominent factors
triggering erosion in Cameron Highlands. The accuracy of developed susceptibility map from CFs’ prediction
rates was 68.6%. This suggests that the map was acceptable for watershed management, optimal land-use planningand prevention of erosion.
Keywords: Soil erosion, dynamic causative factors, susceptibility, frequency ratioof relative probability of occurrence of soil erosion ina particular location within watershed under the
influence of causative factors (CFs). This predicts
geospatial distribution of occurrence of soil erosion
within the watershed and classifies areas into zones
of different degrees of susceptibility to erosion [5].
The analysis could be accomplished by using two
approaches: qualitative or quantitative approach. The
former is subjective as the analysis rest largely on theexperts’ opinion and less accurate while the latter isobjective and more accurate because it is statisticaland probabilistic in nature [6]. The quantitative
approach is categorized into bivariate andmultivariate techniques to analyze numerical data andstatistics in order to express the relationship between
erosion and its CFs [7]. These two techniques analyze
the historical linkage between CFs of a given erosive
process and the distribution of the erosional
landforms [8]. The target of this analysis is toestablish, evaluate and visualize susceptibility,
hazard and risk associated with natural events [5]. In
bivariate technique, CFs maps are combined witherosional distribution map based on weighting values
estimated for each factor. Some examples of bivariatetechniques reported in literatures are frequency ratio(FR), statistical index and weight of evidence.
In the analysis of erosion susceptibility, selection

INTRODUCTION
Erosion is one of the most serious environmental
problems that degrade land and threatens agricultural
productivity and hydrologic systems in a watershed[1]. Human activities in the watershed such asincreasing agricultural practice, massive land clearing
for development, deforestation, etc cause drasticchanges in land-use and land-cover patterns which
enhances erosion phenomenon. Soil erosion process
is modified basically by some biophysical factors of
the watershed such as soil, climate, terraincharacteristics and land-cover [2]. Hence, area
specific studies are often applied for erosion
assessment. These factors interact in a complex
manner that makes erosion prediction ormeasurement difficult. Vijith, et al. [3] reported that
Asia, Africa and South America have very higherosion rate with average value of 30-40 ton/ha/year.
The ecological related issues of soil erosion havenecessitated the development of sustainable erosion
control measures. Substantial efforts have been spenton the development of soil erosion models [4]. Soilloss estimation and identification of critical zones arevery crucial for the implementation of best
management practice [2].
Susceptibility analysis is used for the assessment
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SEE - Nagoya, Japan, Nov.12-14, 2018

of appropriate CFs is the starting point [9]. Previous
studies showed that majority of CFs considered were
static factors such as slope angle, length-slope, plancurvature, stream power index, slope aspect andtopographic wetness index, normalized difference
vegetation index (NDVI), landuse/landcover,lithology, lineament, soil erodibility (k-factor), etc.
These factors remain unchanged for a relatively long
period of time. Furthermore, many of these are
redundant that should not be simultaneously used as
it often lead to overweighting of the results [9].
However, there are some important dynamic CFs
such as land surface temperature (LST), soil moistureindex (SMI) and rainfall erosivity (R-factor) whose
impacts on erosion susceptibility results have notbeen investigated. Some literatures have indicatedthat these factors are crucial in triggering erosion but
often neglected in many susceptibility analyses due todata unavailability [9-11]. Therefore, the aim of thisstudy is to predict geospatial distribution of soil
erosion in Cameron Highlands, Malaysia using
modified bivariate FR technique. The study considers
both non-redundant static and dynamic CFs for
erosion susceptibility analysis of complex watershed
where there is increasing rate of erosion due to theincreased human-environment interactions.

assess their significance in erosion susceptibility
analysis.
After preparation of all the CFs, modified
bivariate frequency ratio (FR) technique was adopted
to estimate the probabilistic relationship between
response (i.e., erosion) and predictor variables (i.e.,
erosion CFs) [18]. This method was chosen owing to
its simplicity in application and understanding of theresults. It evaluates the ratio of area of erosion
occurred pixels to the total study area and the ratio of
erosion occurrence probability to the non-occurrence
for a given attribute [19]. FR application forsusceptibility analysis commenced by reclassifying
all the CFs into ten (10) classes and the number oftraining points (erosion occurred points) within eachclass were evaluated. FR for each causative factor
were evaluated by finding the ratio of percentage
target occurrence in each subcategory to percentage
category of CFs in question as given in Equation 1.
The relative frequency (RF), prediction rate (PR) andsusceptibility index (SI) respectively defined asshown in Equations 2, 3, and 4 were evaluated. The
PR and SI are used to define the mutual relationshipamong the CFs and occurrence of soil erosion. The
expressions were applied and the results of theanalyses are presented.

MATERIALS AND METHODSFR =Soil erosion susceptibility analysis start with theidentification of erosion affected spots in the area
under study. In Cameron Highlands, a total of 159
erosion affected spots were identified as shown in
Figure 1a. Based on this, erosion CFs required for the
analysis were prepared and evaluated (see Figures
1b-1h) using ArcGIS 10.1, ENVI 5.0 and Geomatica
2016 software. These factors were extracted fromvarious sources having different scales andgeneralization. The non-redundant static factors:
drainage density (DD), LS-factor, lineament density(LD) were extracted from digital elevation model(DEM 5m spatial resolution) and dynamic CFs:
NDVI, SMI and LST were derived from Landsat-8
image obtained from USGS database. R-factor wasderived from monthly rainfall data (2006-2016)
obtained from Malaysian Department of Irrigation
and Drainage. The detailed procedures for the
extraction of LST and SMI described by Abdulkadir,et al. [12] were used. All these CFs were considered
due to their roles in triggering erosion and theirprevious implementation by many earliest
researchers in erosion susceptibility analysis. For
instance, some of non-redundant static CFs
considered are DD [3, 6, 13], length-slope [14, 15],
LD [1, 3] whose detailed descriptions could be foundin the aforementioned literatures. Similarly, dynamic(multi-temporal) CFs such as R-factor [9, 16], LST[10], SMI [17] have been highlighted by researchers
to influence erosion. Hence, they were introduced to% target occurence in each subcategory

RF = ∑PR =% category of an indepedent factor

factor class FR(2)factor classes FR(RFmax −RFmin )MIN. totat of (RFmax −RFmin )SI =∑(RF∗PR)

MAX.(RF∗PR)

(1)

∗ 100

(3)
(4)

RESULTS AND DISCUSSION

This section discusses the results obtained for thesusceptibility analysis for geospatial prediction of soil
erosion in Cameron Highlands watershed. The results
are presented in Tables 1(a-g) for each factor. These
Tables showed the correlations between classes ofeach CFs and occurrence of soil erosion in thewatershed. In the case of correlation between soil
erosion and SMI, erosion mostly occurred in the SMI
classes of 0.852-1.032 and 1.152-1.358 because theirrespective ratios were greater than 1.0. The SMI classof 1.250-1.358 had the highest frequency ratio value
as shown in Table 1a. Locations within the watershedwith very low SMI were relatively dried compared toother locations. The results of SMI analysis withrespect to soil erosion suggest that the drier locations
were more prone to erosion than wet locations [17].
This is because drier soils are loose and could easily
be detached and moved by runoff in the event of
rainfall. The LST range of values where most of soil
erosion took place was 24.20-32.64 0C as shown in
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SEE - Nagoya, Japan, Nov.12-14, 2018

Table 1b. The locations with these highest LST values
are the hottest regions in the study area. These
locations have relatively low SMI values [11, 20]
because solar radiations reduce the soil moisture
content. Thus, erosion occurrence was prominent inthose locations. Regions with NDVI values ranges
between 1.174-1.494 and 1.623-1.759 are locations

where most erosion occurred with highest
experienced at NDVI range of 1.174-1.255 as shownin Table 1c. This region with relatively low NDVI
indicates lesser vegetation abundance. Therefore,
there is very high tendency to have erosion occurringin such locations as experienced in the study [21].

Tables 1(a-h). Frequency ratio and prediction rates for soil erosion CFsa) Factor classes(SMI)b) Factor
classes (LST)

Ratio

RF

22.105
0.766
0.597
0.200
0.202
0.378
1.114
3.572
7.826
13.843

0.437
0.015
0.012
0.004
0.004
0.007
0.022
0.071
0.155
0.274

RF

15.95 - 19.87
19.88 - 21.80
21.81 - 22.23
22.34 - 22.88
22.89 - 23.47
23.48 - 24.19
24.20 - 25.04
25.04 - 26.09
27.60 - 27.60
27.61 - 32.64e) Factor
classes (LD)

Ratio

RF

0.000
0.000
0.000
0.000
0.000
0.001
0.064
0.144
0.195
0.597

0.09 - 0.134
0.135 - 0.170
0.171 - 0.207
0.208 - 0.242
0.243 - 0.275
0.276 - 0.307
0.308 - 0.336
0.337 - 0.369
0.370 - 0.407
0.408 - 0.477c) Factor classes(NDVI)

Ratio

RF

0.852 - 0.993
0.994 - 1.032
1.033 - 1.060
1.061 - 1.082
1.083 - 1.104
1.105 - 1.126
1.127 - 1.151
1.152 - 1.189
1.190 - 1.249
1.250 - 1.358d) Factor classes
(LS)

4.153
1.730
0.962
0.988
0.751
0.395
0.523
1.041
3.004
30.210

0.095
0.040
0.022
0.023
0.017
0.009
0.012
0.024
0.069
0.690

Ratio

0 - 2.22
2.23 - 7.76
7.77 - 14.42
14.43 - 21.07
21.08 - 28.83
28.84 - 38.81
38.82 - 53.22
53.23 - 80.94
80.95 - 150.80
150.81 - 282.75g) Factor classes
R-factor

0.000
0.000
0.000
0.000
0.000
3.356
264.315596.648808.169
878.384
Ratio

RF2015.22 - 2086.83

1.309

0.136

CFs

Min

Max

[Max-Min]

2086.84 -2146.89
2146.90 - 2200.02
2200.03 - 2248.54
2248.55 - 2292.43
2292.44 - 2334.01
2334.02 - 2382.52
2382.53 - 2440.27
2440.28 - 2500.34
2500.35 - 2604.29

1.959
0.933
0.000
0.190
1.087
0.906
1.336
1.923
0.000

0.203
0.097
0.000
0.020
0.113
0.094
0.139
0.199
0.000

SMI
NDVI
LST
DD
LS-Factor
LD
R-Factor

0.009
0.000
0.004
0.000
0.000
0.012
0.000

0.690
0.285
0.437
0.230
0.597
0.203
0.203

0.681
0.285
0.433
0.230
0.597
0.191
0.203

The results for LS-factor in Table 1d showed thatthe highest ratio occurred in the region with highest
value (i.e., 150.81-282.75). This underscores theinfluence of slope-length on occurrence of soil
erosion as highlighted by many researchers [22].
Higher LD regions suggest high geological faults(i.e., presence of fractured and weathered terrain) in
the watershed that could enhance soil erosion. Thiswas experienced in the study area as depicted in Table

Ratio

RF

0.984 - 1.173
1.174 - 1.255
1.256 - 1.327
1.328 - 1.391
1.392 - 1.449
1.450 - 1.494
1.495 - 1.534
1.535 - 1.573
1.574 - 1.622
1.623 - 1.759f) Factor classes
(DD)

0.000
6.882
4.965
5.778
3.616
1.114
0.079
0.172
0.157
1.405

0.000
0.285
0.205
0.239
0.150
0.046
0.003
0.007
0.006
0.058

Ratio

RF

0.116 0.012
13 - 18279
0.447 0.048
18280 - 40203
0.772 0.083
40204 - 62789
1.180 0.127
62790 - 86690
0.946 0.102
86691 - 110931
1.206 0.129 110932 - 138357
0.987 0.106 138358 - 170221
1.593 0.171 170222 - 205077
1.892 0.203 205078 - 244898
0.298 0.032
244899 -319504(h) Model prediction rates

0.037
0.520
1.614
1.033
1.313
0.864
1.386
2.644
2.064
0.000

0.003
0.045
0.141
0.090
0.114
0.075
0.121
0.230
0.180
0.000

Min
tot.
0.191

PR
3.576
1.494
2.272
1.209
3.133
1.000
1.066

1e and conformed to description made by Barrow, etal. [23]. The results for the remaining CFs such as DD
and R-factor are presented in Tables 1f and 1g
respectively. The prediction rates were evaluated foreach factor by finding the minimum RF, maximum
RF and the differences between both as shown in
Table 1h. The obtained values were used to evaluate
contribution of each factor. The analysis showed that
all the CFs contributed significantly to the occurrence
1118

SEE - Nagoya, Japan, Nov.12-14, 2018of erosion. SMI had the highest impact on soil erosion
followed by LS-factor and the least was LD as shownin Table 1h. The prediction rate values for each factor
was then applied in ArcGIS 10.1 for the developmentof erosion susceptibility maps as shown in Figure 2.
This predicts the potential locations where erosion
could occur based on the CFs.

a

b

c

d

e

f

h

g

2604.292015 22

Figure 1. Maps for erosion locations and CFs (a) Training points (b) DD (c) LS-factor (d) LD (e) NDVI (f) LST(g) SMI (h) R-factor

1119

SEE - Nagoya, Japan, Nov.12-14, 2018

map. The accuracy of model was assessed using areaunder-curve method and was estimated to be 68.6%
accurate. This suggests that the map is valid forgeospatial erosion prediction and acceptable for
optimal land-use and sustainable management of thewatershed against erosion and it related hazards.
ACKNOWLEDGEMENTS
This study was supported by the Universiti
Teknologi PETRONAS Malaysia under University
Research Internal Fund-URIF 2016 Grant (0153AAG04) and Graduate Assistance Scheme. Authors also
acknowledged Malaysian Department of Irrigation
and Drainage for the provision of rainfall data.

Figure 2. Erosion susceptibility map
Accuracy of the soil erosion susceptibility map
obtained was evaluated by using area-under-curve(AUC) technique. An AUC “measures the quality ofprobabilistic model describing its ability to reliably
predict the occurrence or non-occurrence of events”[24]. Its values often range between 0 and 1 in whichcloser to 1 indicate perfect prediction and close to 0.5
indicates that the model is inaccurate [25]. It is widely
accepted and adopted by researchers for evaluation ofsusceptibility mapping accuracy [26]. The AUC value
was estimated to be 68.6%. This indicates that FR
method performed fairly well in erosion susceptibility
assessment and the map could be used for sustainable
management of the watershed. Susceptibility map
produced was classified into five classes using natural
break approach as in Figure 2. Most northeast andcentral regions of the study area were mostly
identified as “very low” susceptible zones while“high” susceptible zones are distributed across thewestern region. The percentage area occupied byregions with very low, low, moderate, high and very
high susceptible zones to soil erosion are 42.3, 36.9,
16.4, 3.8 and 0.5% respectively.

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CONCLUSION
This present study applied modified bivariate FR
technique for geospatial prediction of soil erosion in
Cameron Highlands. The study considered some
important CFs which often neglected in manysusceptibility analyses along with other nonredundant CFs. As a result, DD, LD and LS wereselected as static factors, and LST, SMI, NDVI and
R-factor as dynamic factors. Correlations between
subclasses of each CFs and occurrence of soil erosion
were evaluated. The results showed that most erosion
took place in the subclasses of 150.81 - 282.75, 0.337- 0.369 km/km2, 1.174 - 1.255, and 1.250 - 1.358 for
LS, LD, NDVI, and SMI respectively. The analysis
of prediction rates for all the factors showed that
contributed significantly to the occurrence of erosion
with the SMI having the highest value followed by
LS. The results of prediction rates for the CFs wereapplied for the development of erosion susceptibility
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SEE - Nagoya, Japan, Nov.12-14, 2018

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[21] W. J. D. Van Leeuwen and G. Sammons,"Vegetation dynamics and erosion modelingusing remotely sensed data (MODIS) and GIS,"
presented at the 10th Biennial USDA Forest
service remote sensing applications, U.S., 2005.
[22] B. Liu, M. Nearing, P. Shi, and Z. Jia, "Slopelength effects on soil loss for steep slopes," Soil
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bivariate and multivariate statistical analyses,"Engineering Geology, vol. 110, pp. 11-20, 2010.
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Computers & Geosciences, vol. 44, pp. 120-135,
2012.

1121

NONLINEAR BEHAVIOR AND THERMAL DAMAGE OF THERMALLAGGING IN CONCENTRIC LIVING TISSUES SUBJECTED TO
GAUSSIAN DISTRIBUTION SOURCE
Hamdy M. Youssef 1, 2, Najat A. Al-Ghamdi3
Alexandria University, Dept. of Mathematics, Faculty of Education, Alexandria, Egypt
2
Umm Al-Qura University, Dept. of Mechanics, Faculty of Engineering, Makkah, KSA
3
Umm Al-Qura University, Dept. of Mathematics, Faculty of Science, Makkah, KSA

1

ABSTRACTThe effects of thermal lagging with high-order became essential to describe non-equilibrium heating in tissues.
Our paper studies the temperature rise behavior in living tissues theoretically during the treatment by magnetic tumor
hyperthermia based on the non-linear form of the dual-phase-lag model. Experimentally, it was found that theconcentration of magnetic particles is in Gaussian distribution through the radial direction when magnetic fluid is
injected into the living tissue space. Hence, the governing partial differential equation in concentric spherical space issolved in the Laplace transform domain. Some comparisons between the non-linear and linear effects of phase-lag
time’s parameters on bio-heat transfer have been studied and discussed. The thermal damage quantity for the tumor
has been calculated with different values of the phase-lag times. The results show that the non-linear and linear
effects of phase-lag times on bio-heat transfer have significant effects on the tumor, the tissue, and the thermal
damage quantity.
Keywords: Nonlinear Behavior; Thermal Lagging; Thermal Damage; Living Tissue; Gaussian distribution Source
transport and heat distribution stimulated bycommercially available magnetic nanoparticles
injected into the extracellular area of biological tissue
using agarose gel with porous structures alike tohuman tissue.
Pennes model [13] describedtemperature distribution in the living biologicaltissues. The connection between [14] arterial bloodand the heat transfer in a living tissue are taken. The
model known as the bioheat equation remains used
today. Pennes inserted a medium response term to thebasic heat equation that accounts for the mitigating
effect of blood flow. This convective term depicts
heat transport by means other than propagation.
Wissler [15] explicated the validity of Pennes’ model
connected to normal thermal distribution in living
tissue. supposed mixed boundary conditions in restingtissue, Pennes’ model strictly describes the decay of
temperature from the core of the body to the surface[14]. The Pennes bio-heat transfer equation (PBT) isbased on the classical Fourier’s law, taken into
account a blood perfusion term, which is
proportionate to the volumetric rate of blood
perfusion and the difference between the averagearterial blood and tissue temperatures. Pennes bioheat model is true only if when the venous bloodflows from the capillary bed to the main supply vein,
its temperature remains the same as the tissue
temperature disregard the size of the vessel and theflow rate. Youssef modified the theory of heat
conduction in deformable bodies which have been

INTRODUCTION
Hyperthermia (also called thermal therapy orthermotherapy) is a kind of medical treatment incancer therapy; it is elevated body temperature to 40–
44 C. Hyperthermia is used with radiation therapy
and chemotherapy to treat cancer [1]. Cells in theseareas are often cell cycle arrest and so most resistantto growth prohibiting drugs. It remains unclear
whether these cells are sensitive to heat damage;moreover, heat can motivate vascularization andincrease oxygenation of the tissue, thermotherapy
make cancer cells more motivate to radiation or harm
other cancer cells that radiation cannot damage [2, 3].
These studies have been certain in a number ofclinical studies [4, 5] which indicate that elevation of
the temperature within a tumor has a cytotoxic
influence on radio resistant cells when heated totemperatures above 42 C. There is a variety oftechniques [3, 6] to increase the temperature within
the human body. Hyperthermia for the processing ofcancer is under study, including all body
hyperthermia, partial or regional hyperthermia, andlocal hyperthermia. In several biologists studying the
behavior of bio-heat transfer in tissues during
magnetic fluid hyperthermia management, thedistribution of the magnetic particles was always
regarded as homogenous in a limited spherical
domain [7-11]. Furthermore, Salloum et al. [12]experimentally evaluated magnetic nan-ofluid

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SEE - Nagoya, Japan, Nov.12-14, 2018

investigated by Chen and Gurtin, which depends
upon two distinct temperatures, the conductive
temperature and the thermodynamic temperature [16].
For time-independent situations, the difference
between these two temperatures is proportional to theheat supply, and in the absence of any heat supply,
the two temperatures are identical. Youssef
considered the non-Fourier’s heat conduction basedon one relaxation time. Youssef applies the twotemperature heat conduction in many applications[17-21]. In this work, two-temperature bio-heattransfer equations based on second-order effects inthermal lagging was introduced and used to discuss
the variation of temperature in a laser-irradiatedbiological tissue.

ρi Ci

The term

Ti

1, 2 .
β ∇ T ( r, t ) , i =( r, t ) − T ( r, t ) =
2

i

i

C

i

(2)

Where
=
i 1 for 0 ≤ r ≤ R and=i 2 for R ≤ r < h ,β i is a non-negative parameter which is called twotemperatureparameter,

Ti c

is

the

= −∇ ⋅ qi ( r , t ) − wbi Cb ρ p (Ti D ( r , t ) − T0 ) +

.

(3)

1, 2
( q ( r, t ) + q ( r, t )) , i =w C (T ( r , t ) − T ) expresses the heat
ri

D

bi

b

i

0

caused by convection within the tissue per unit massof the tissue and it is considered to be homogenous
and T0 = 37 o C is the reference temperature of thetissue and the tumor.
The second order Taylor series of the DPL model canbe rewritten as2∂ τ qi ∂ 2 
1 + τ qi +
 q ( r, t ) =∂t 2 ∂t 2 (4)∂ τ 2 ∂2 
1, 2
− K i 1 + τ Ti + Ti 2  ∇Ti c ( r , t ) , i =∂t 2 ∂t Consequently, it gives2∂ τ qi ∂ 2 
1
+
τ
+

 ∇ ⋅ q ( r, t ) =qi∂t 2 ∂t 2 In a magnetic fluid hyperthermia, magnetic
particles are injected into at the center of tumor
surrounded by the normal tissue and radially diffuse
from the injected point in Gaussian distribution [12].
For excitation of an alternating magnetic field,
magnetic particles become the space-dependent
heating sources in the tissue. For t > 0 , the heat istransferring in the radius direction symmetrically. The
small tumor is regarded as a solid sphere with theradius R [7-11]. The temperature distribution in thetumor 0 ≤ r ≤ R and normal R ≤ r < h tissues is thefunction of the distance r from the center of thesphere and time t.
Youssef proposed the two-temperature model todifferentiate between the conductive temperature andthe dynamical temperature as:qi ( r , t + τ qi ) =− K i ∇Ti c ( r , t + τ Ti ) , i =1, 2 ,
(1)
D

∂t

mi

FORMULATION OF THE PROBLEMC∂Ti D ( r , t )(5)∂ τ Ti2 ∂ 2  2 c− K i 1 + τ Ti +1, 2
 ∇ Ti ( r , t ) , i =∂t 2 ∂t 2 A high order differential equation of bio-heat transfer
is obtained from equation (3) as:τ 2 ∂ 2  1 ∂  2 ∂Ti C ( r , t ) ∂K i 1 + τ Ti + A Ti 2  2
r
=
∂t
∂r
2 ∂t  r ∂r ∂Ti D ( r , t )


(6)
−
 ρi Ci∂tτ qi2 ∂ 2  

∂
D
1, 2.
1 + τ qi + B  wbi ρb Cb (T0 − Ti ( r , t ) )  , i =∂t
2 ∂t 2   −qmi ( r , t ) − qri ( r , t ) where the values of the coefficients α1 and α 2 arefor DPL type I equation,
α=
α=
0.0
1
2
=
α1 1.0,=
α 2 0.0 for DPL type II equation, andfor DPL type III equation.
α=
α
=
1.0
1
2
Consider the following functions:θ i ( r=, t ) r (Ti C ( r , t ) − T0 )=, i 1, 2conductiveD

temperature, Ti is the dynamical temperature, K theheat conductivity, q the heat flux, and t is the time,τ q ,τ T are the phase-lag time parameters of the heatϕi ( r=, t ) r (Ti D ( r , t ) − T0 )=, i 1, 2.

(7)

Hence, we have from equations (6) and (7) thatflux and the temperature gradient, respectively. In
general, the relaxation times τ q ,τ T take a minimalτ 2 ∂ 2   ∂ 2ϕi ( r , t ) ∂K i  1 + τ Ti + α1 Ti 2  =∂t
2 ∂t   ∂r 2 value, while in the biological materials this parameteris more significant.
The energy conservation equation of bio-heat transfer
is described in the context of the two-temperaturemodel as:∂θ i ( r , t )


(8)
+
 ρi Ci

∂
t
2


τ


∂
∂
1, 2.
1 + τ qi + α 2
  wbi ρb Cbθ i ( r , t ) −  , i =
∂
2
∂
t
t2 


 rqmi ( r , t ) − rqri ( r , t ) 




2
qi

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SEE - Nagoya, Japan, Nov.12-14, 2018

θ i ( r , t ) =−ϕi ( r , t ) β i∂ 2ϕi ( r , t ), i=
1, 2 .

∂r
Assume the following spatial heating source
qri ( r , t ) = q0 H ( t ) e − ( r / r ) ,
2

2
i 0

−λ1 K1e − λ R c11 + λ1 K1eλ R c12 + λ2 K 2 e − λ R c21
1

(9)

2

(10)

2

(11)

where we will use the following initial conditions:∂ϕi ( r , t )∂θ i ( r , t )ϕ=r , t ) t 0=
θ=r, t ) t 0== 0 .(12)
i (
i (
=
∂t

=t 0 =t 0

hqi ( ρi Ci s + wbi Cb ρ p )K i hTi + β i hqi ( ρi Ci s + wbi Cb ρ p )(13),

qmi + hqi qrifi =, K i hTi + β i hqi ( ρi Ci s + wbi Cb ρ p ) s 2τ qi2 s 2τ 2 hTi =1 + sτ Ti + α1 Ti  , hqi =1 + sτ qi + α 2
,
2 
2 


q
q
qri ( r , s ) = 0 e − ( r / r ) , qmi = mi .
ss
The general solution of the differential equation (13)takes the formfs ) c11e − λ r + c12 eλ r + 12 r , 0 ≤ r ≤ R,
ϕ1 ( r ,=
(14)
λ1
and
f
ϕ2 ( r=, s ) c21e − λ r + c22 eλ r + 22 r , R ≤ r < h .
(15)
λ2
Apply the boundary conditions=
ϕ1 ( r , s ) r =0 0,=
ϕ1 ( R, s ) ϕ2 ( R, s ) ,
2
i 0

1

1

2

2

exposure time t at a given absolute temperature T.
The measure of thermal damage Ω was introduced,
and its rate κ (T ) were postulated to satisfy:dΩ E /η ,(21)= A exp  − a
dt
T 

which leads tot E /η (22)=Ω A∫ exp  − a
dt ,
T 
0

where A is a material parameter (frequency factor);
Ea is the activation energy; η is the universal gas
constant. Equation (37) indicates that a reaction
proceeds faster with larger values of T or A for thesame Ea , or with smaller values of Ea for the same

κ (=
T)

.(16)
K1 ∂ϕ1 ( r , s )K 2 ∂ϕ 2 ( r , s ), ϕ 2 ( r , s ) r =h 0
=
=
∂r
∂r
r
r
=r R=r R

value of A. The constants A and Ea are usuallyobtained experimentally. After the pioneering work ofHenriques and Moritz, many researchers have also
proposed some other models, but most of them have asimilar format. There are only differences in thecoefficients used in the burn damage integral, which
are mainly due to the different experimental databases
used to define the models and the different emphasis

We get the following system of linear equations:(17)
c11 + c12 =
0,

 f
f 
e − λ R c11 + eλ R c12 − e − λ R c21 − eλ R c22 = 22 − 12  R , (18)
λ
λ
 2
1 
1

1

2

(20)

The Arrhenius burn integration induced byHenriques and Moritz is widely used. Their results
showed that progressively decreasing temperatures
could produce a burn injury of standard thresholdseverity as the thermal insult period is logarithmicallyincreased. They conducted two different experiments,
which involved boundary conditions of constanttemperature and constant heat flux in computing thetime-temperature relationship at the dermal-epidermal
junction. They worked out the solution of the Fourier
heat conduction equation for a semi-infinite body tomodel the transfer of heat through the skin. Based on
their observation, Moritz and Henriques proposed thatskin damage could be represented as a chemical rate
process, which is calculated by using a first order
Arrhenius rate equation. Whereby damage is related
to the rate of protein denaturation κ (T ) and0

where λi2 =λ2THE THERMAL DAMAGE∞

Thus, we get∂ 2ϕi− λi2ϕi =− fi r , i =1, 2 ,
∂ r2

2

(19)

We solve equations (17-20), we complete the solution
in the Laplace transform domain.

Applying Laplace transform for equation (8) and (10)defined as:

∂t

2

 f2
f1  ,− λ2 K 2 eλ R c22 = 2 − 2 R λ2 λ1 fc21e − λ h + c22 eλ h =− 22 h .

where r0 is a parameter which determines how far the
diffusion of the injected magnetic particles occurs andq0 determines the maximum strength of the spatial
heating source at the injection site. The function
H ( t ) is Heaviside unit step functionf ( s ) = ∫ f ( t ) e − st dt ,

1

2

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SEE - Nagoya, Japan, Nov.12-14, 2018

when

analyzing

Ti C ( 0 C ) =

ϕi
r

the

burn

processof tissue =R 0.005 ≤ r ≤=h 0.02 at the instant timeand τ T 5.0
t = 20 s==s, τ q 15.0 s . DPL type I, II, III

where+ T0 + 237 .

for the one-temperature and two-temperature model,
respectively, have been represented in this figure to
discuss the effect of the two temperature parameteron the conductive temperature increment. The twotemperature parameter β has significant effect where
the conductive temperature increment decreases in
the context of the two-temperature model for thethree DPL types. The non-linear effects of τ T2 , τ q2 are

NUMERICAL INVERSION OF THE LAPLACE
TRANSFORM
To determine the distribution ϕi ( r , t ) of eachlayer, we will use a Riemann-sum approximation
method to obtain the numerical results in which, any
function in Laplace domain can be inverted to thetime domain as:
Neκ t  1
i nπ  
n

(23)
Z=
(t )
 ,
 Z ( ε ) + Re ∑ ( −1) Z  ε +
t 2



n =1

very significant. The heat conduction temperature
increment is greater in the context of DPL type III
than DPL type I and Type II. The non-linear term ofτ q2 plays a vital role to increase the heat conductiont 

where Re is the real part and i is imaginary number
unit. For faster convergence, numerous numericalexperiments have shown that the value of ε satisfies
ϕ ( r, t )the relation ε t ≈ 4.7 Tzou. The value of 1
atr
r = 0 is undefined value and it must be replaced byϕ ( r, t )its limit as Lim 1
and by using L’Hôpital’s rule
r →0
r
as:
ϕ1 ( r , t )ϕ1 ( r , t ) dϕ1 ( r , t )
.
(24)
=
=
Lim
r →0
r
r
dr
r 0 =r 0

temperature increment in the context of the onetemperature model and the two-temperature model. In
the tumor space, the heat conduction temperature
increment in the context of DPL type III is greaterthan DPL type I and DPL type I is greater than DPL
type II. In the tissue space, the three types are muchclosed based on one-temperature parameter while
they are coinciding based on the two-temperaturemodel. The difference values of the heat conduction
increment in the context of the one-temperaturemodel and the two-temperature model are greater inthe tumor space than its values in the tissue spacebecause the positions 0 ≤ r ≤ R are in the range ofthe heating source. Figures 2-4 show the heat
conduction increment of DPL type I, II, and III,
respectively, in the context of the one-temperaturemodel and two-temperature model, respectively. The
non-linear effects of τ T2 , τ q2 are significant. The heat

NUMERICAL RESULTS AND DISCUSSION
To simulate the thermal response within a small
spherical tumor of radius R = 0.005 m and its
surround tissue, the thermal material properties of thetumor and the tissue are provided in Table1. The
volumetricheat
capacity
of
blood
is
ρb=
Cb 4.18 × 106 J / m3 / K and the spatial heating
sourceisspecified

q0 6.15 × 106 W / m3 ,with==
r0 0.75 × R and=h 4.0 × R .
Table1: Properties of Tumor-Tissue Model
Parameter
Unit
Tumor
Tissue
W
/
m
K
0.778
0.642
K

ρ

kg / m3

1660

1000

C

J / kg K

2540

3720

wb

m3 / s / m3

0.00640.0064

37

37

T0
qm
x

o

C

conduction temperature increment is greater in thecontext of the one-temperature model than the twotemperature model. The non-linear term of τ q2 plays avital role to increase the heat conduction temperature
increment in the context of the one-temperaturemodel while it has a limited role in the context of the
two-temperature model. In the tumor space, the heat
conduction
temperature
increments
whenisgreaterwhen==s, τ q 30.0 s
τ T 15.0
then τ T 5.0=s, τ q 10.0 s ,=τ T 10.0=s, τ q 20.0 s , and =while the three cases are coinciding in the context ofthe two-temperature model. In the tissue space, thethree types are much closed based on one-temperatureparameter while they are coinciding based on the
two-temperature model. The difference values of theheat conduction increment in the context of the onetemperature model and the two-temperature model
are greater in the tumor space than its values in thetissue space because the positions 0 ≤ r ≤ R are in

3

29000
450
W /m
m
0.005
0.02
β
0.000001
0.000001
m −2
Figure 1 shows the heat conduction increment along
the distance range of tumor 0.0 ≤ r ≤ R =0.005 and
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SEE - Nagoya, Japan, Nov.12-14, 2018

the range of the heating source. Figures 5-7 show theheat conduction increment of DPL type I, II, and III,
respectively, in the context of the one-temperaturemodel and two-temperature model, respectively. The
non-linear effects of τ T2 , τ q2 are significant. The heat
conduction temperature increment is greater in thecontext of the one-temperature model than the twotemperature model. The non-linear term of τ q2 andthe time t are playing vital roles to increase the heat
conduction temperature increment in the context ofthe two models. The difference values of the heat
conduction increment in the context of the onetemperature model and the two-temperature model
are greater in the tumor space than its values in thetissue space because the positions 0 ≤ r ≤ R are in
the range of the heating source. Figures 8-10 shows
the thermal damage of DPL type I, II, and III,
respectively, in the context of the one-temperaturemodel and two-temperature model, respectively. Theline passing through the damage Ω =1.0 separates
between the irreversible damage above and thereversible damage below. The non-linear effects ofτ T2 , τ q2 are significant. The thermal damage is greater

Figure 2: The heat conduction increment of DPL
type I

Figure 3: The heat conduction increment of DPL
type IIin the context of the one-temperature model than the
two-temperature model. The non-linear term of τ q2
and the position r are playing vital roles to increase or
decrease the heat thermal damage in the context ofthe two models. The only one case that has
irreversible damage occurred when τ q > τ T for the
one-temperature model and the two-temperaturemodel and all the other cases when τ q < τ T andτ q = τ T has reversible damage to the two models.
The one-temperature model offers irreversible
damage quantity more than the two-temperatureparameter. The DPL type III offer irreversible
damage quantity more than the DPL type I and thenthe DPL type II offers the smallest irreversible
damage quantity.

Figure 4: The heat conduction increment of DPL
type III

Figure 5: The heat conduction increment of DPL
type I at a different time and various r

Figure 1: The heat conduction increment withdifferent DPL types
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SEE - Nagoya, Japan, Nov.12-14, 2018

Figure 6: The heat conduction increment of DPL
type II at a different time and various r

Figure 10: The thermal damage quantity of DPL typeIII of the tumor

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Figure 9: The thermal damage quantity of DPL type
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SEE - Nagoya, Japan, Nov.12-14, 2018

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[21]H. M. Youssef and A. El-Bary, "Two-temperature
generalized thermo-elastic medium thermally
excited by time exponentially decaying laser
pulse," International Journal of Structural
Stability and Dynamics, vol. 16, p. 1450102,
2016.

1128

4th Int. Conf. on Science, Engineering & Environment (SEE),
Nagoya, Japan, Nov.12-14, 2018, ISBN: 978-4-909106018 C3051

THE COMPLEX OF FIELD PILING STATIC LOADING TESTS ON
AKSAI, NORTHWEST KAZAKHSTAN
Askar Zhussupbekov1, Iwasaki Yoshinori2, Abdulla Omarov3, Karlygash Borgekova4 and Sungat
Akhazhanov5
1,3,4,5
Department of Civil Engineering, L.N. Gumilyov Eurasian National University, Kazakhstan;2
Geo-Research Institute, Japan

ABSTRACTThis paper presents the complex analysis of diverse field loading tests of ten large diameter deep bored piles
in Aksai of the northwest Kazakhstan. Overall ten field tests on bored piles with diameter 600 mm, depth 15.51
m and 21.85 m were performed correspondingly. Two static lateral, four static tensions and four static
compression pile loading tests were carried out on the construction site of KPC Gas Debottlenecking Project.
Static loading tests applied load to a deep-foundation element gradually for measuring foundation settlement.
Applied load and head movement are measured for static axial compression and tension load tests. Applied loads
are determined using a load cell and hydraulic jack pressure. The foundation’s head movement can be measured
using digital or mechanical dial gages, a number of types of displacement transducers, string potentiometers, or a
combination of these devices. The applied load and head movement is plotted and interpreted to define thefoundation’s geotechnical load. The static loading tests were performed on axial compression by ASTM D1143,
axial tension by ASTM D3689 and lateral by ASTM D3966. The load-settlement and the load-displacement
curves were obtained from field tests. These curves were analyzed to identify the bearing capacity. Comparisonof bearing capacity of bored piles with different length in problematic soil conditions of West Kazakhstan werediscussed in this paper. The analysis showed that the bearing capacity of bored piles with different lengths
corresponds to the design requirements.
Keywords: Pile test, PLT, STPLT, SCPLT, SLPLTINTRODUCTION
The Karachaganak field is one of the world’s
largest oil and gas condensate fields located innorthwest Kazakhstan and covering an area of morethan two hundred eighty square kilometers. The
Karachaganak field is located in a remote andchallenging working environment with the ambient
temperature ranging from minus forty degrees
Celsius in winter to plus forty degrees in summer.
The field, the top of which is located at a depth ofaround three thousand five hundred meters, is some
one thousand six hundred meter thick and very
complex and unique. Karachaganak Field is a gas
condensate field in Kazakhstan. It is located about
twenty three kilometers east of Aksai (Aksai) in thenorthwest of Kazakhstan. The field was once a
massive Permian and Carboniferous reef complex
covering an area thirty by fifteen square kilometers.
ENGINEERING-GEOLOGICAL CONDITIONS
OF THE CONSTRUCTION SITE AKSAI, IN
NORTHWEST KAZAKHSTANThe Karachaganak Field is one of the world's
largest gas condensate fields. It is located in the PreCaspian Basin, which extends from the southeastern

margin of the Russian Platform down to the northerncoast of the Caspian Sea. The North Caspian is a
pericratonic depression of Late Proterozoic-Early
Paleozoic age (see Figure 1).

Fig. 1 The
geological
Karachaganak field.

structureoftheSediments in the five hundred thousand square
km basin are up to twenty two km thick in places.
The basin is subdivided into numerous zones bylarge salt domes, and the primary salt layer, thePermian Kungurian salt, separates strata verticallyinto subsalt and suprasalt layers. The basin isbounded to the east by the Hercynian Ural
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SEE - Nagoya, Japan, Nov.12-14, 2018

Mountains and to the southeast and south by otherorogenic belts. In the north, the basin lies on theflank of the Voronezh Massif in the west and theVolga-Ural Platform in the north. Numerous oil andgas fields have been discovered in this region in
addition to Karachaganak, such as Astrakhan,
Tengiz and Zhanazhol Fields [1].
The depositional setting of the field is also
varied. On the basis of core sample analysis andseismic studies the following depositional settings
have been identified: limestone, talus, normal
marine, shallow marine, inner reef lagoon, reef core,
relatively deep water, slope, and anhydrite (seeFigure 2).
In geological structures of a site of researches
take part: EGE-1: Loam-heavy, dusty, yellowishbrown, brown color, lumpy, weakly wet, from solid
to semisolid consistence, setting; EGE-2: Clay-light,
brownish black, yellowish-brown and brown color,
lumpy, weakly wet, from solid to semisolid plastic
consistence, setting; EGE-4: Clay-light, dusty,
brown and light brown color, lumpy, weakly wet,from solid to tough plastic consistence; EGE-5: Clay
reddish-brown, dark brown color with black freedeigns, solid weakly wet, from solid to tough plastic
consistence; EGE-6: Clay-light, dusty, greyishbrown, dun color with free designs of grey color,
average density, weakly wet, wet, from semisolid totough plastic; EGE-7: Clay-light, dusty, dun, grey,
dark grey color, average density, wet, tough plastic.

Table 1 Standard and design values of physical andmechanical characteristics of soils
N
E
G
E

1

2

4

5

6

7

S
O
I
L

L
O
A
M
C
L
A
Y
C
L
A
Y
C
L
A
Y
C
L
A
Y
C
L
A
Y

Soil
Consist
ency
g/cm3

Speci
fic
cohe
sion
MPa

Mod
ulus
of
defor
ma
tion

De
sign
resis
tance
kPa

c
0.006

Ang
le of
inter
nal
fric
tion,
deg.
ϕ
20

ρ
1.73
1.96

E
9.34
4.4

R0
400
200

1.77
1.97

0.008

19

7.39
4.78

400
200

1.92
2.03

0.015

19

8.08
7.10

400
250

1.94
2.01

0.029
-

17
-

7.59
-

250
-

1.96
2.01

0.026
-

18
-

8.09
-

250
-

1.98
2.03

0.020
-

19
-

8.33
-

250
-

Field testing of soils by cone penetration test was
executed for more detailed partition of soils anddetermination of bearing capacity of piles on soils.
Soil Field Tests PLT (Plate Load Test)

Fig. 2 Location of earthquake epicenters to thenorthern coast of the Caspian Sea.
Results of physic-mechanical properties of soil
the bases of construction site are resulted from top to
down in Table 1.

Plate Load Test is a field test for determining theultimate bearing capacity of soil and the likely
settlement under a given load. The Plate Load Test
basically consists of loading a steel plate placed at
the foundation level and recording the settlements
corresponding to each load increment. The test load
is gradually increased till the plate starts to sink at a
rapid rate. The total value of load on the plate insuch a stage divided by the area of the steel plategives the value of the ultimate bearing capacity ofsoil. The ultimate bearing capacity of soil is divided
by suitable factor of safety to arrive at the value ofsafe bearing capacity of soil. PLT tests by loading aplate with a diameter of 300 mm are made inaccordance with requirement GOST20276 (1999) or
ASTM D 1194. The plate loading test (further PLT)
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SEE - Nagoya, Japan, Nov.12-14, 2018

was carried out in the workings at a depth of 1.2 m
while maintaining the natural addition of soil, with aflat die 300 mm in diameter, to determine the elastic
modulus of deformation (see Figure 4) [2-3].

Fig. 4 Plate load test: (a) Photo field test and (b)nature of load-settlement curve (PLT-1, PLT-2 and
PLT-3).
Testing with a flat stamp consisted in the factthat the stamp was placed on the bottom of the pit,on the previously cleaned and leveled surface of theground, after which a step-by-step loading was
performed on the stamp. The subsequent stage ofloading was carried out after the decay of the deposit
from the previous loading. As a support, beams
fixed on both sides on the anchor piles were used.
Totally three tests one test in Plate Load Test 1(further PLT-1), second test in Plate Load Test 2(further PLT-2) a depth of 1.2 m had been made.
The load intensity and settlement observation of theplate load test are plotted. The figure shown below
shows a set of typical load settlement curves. Figure
4 shown the results the pressure-settlement diagramsof Plate load tests of PLT–1, PLT–2 and PLT-3.
Modulus of deformation of soils in PLT–1 –108.8 MPa, PLT–2 – 86.1 MPa and PLT-3 - 61.7 adepth of 1.2 m.

recommendation for new pile design. CFA pile is a
type of drilled foundation in which the pile is drilled
to the final depth in one continuous process using acontinuous flight auger. The use of the continuous
flight auger rig avoids many of the problems ofdrilling and concreting piles experienced when using
conventional power augers. The new CFA
equipment can perform piles in most type of soils(including sand, gravel, silt, clay, chalk and weak
weathered rock) with diameters up to 1200 mm andlengths down to 35-40 meters. So, with proper
planning and design, performing equipment andskilled personnel, high production rates and highquality product can be achieved, Klosinski &Rychlewski (2003). Installation of CFA pile consistof following steps: placing the boring machine to theboring place; boring the pile hole to the design level;
removing the screw with simultaneous concrete
filling under the high pressure and replace the boringmachine, installation of steel anchor into the pile
body with preparation of pile head. In modern CFA
technology the systematic employment of devices
auto-recording the drilling data represent a real
breakthrough considering that in the past the CFA
method was not accurate, and relied on theoperator’s ability: now such devices guarantee thecontrol and recording of the data during the wholeconstruction process. The recorded working data areusually drilling/withdrawal speed, rotation speed,
depth, concrete pressure and delivery rate perincrement of auger lift during casting. The CFA
construction sequence is comprised of five stages in
Figure 5.
Stage 1. The digging tip of the auger is fittedwith an expendable ca);
Stage 2. The auger is drilled into the ground to
the required depth;
Stage 3. Concrete is pumped through the hollow
stem, blowing off the expendable cap underpressure;Stage 4. Maintaining positive concrete pressure,the auger is withdrawn all the way to the surface;
Stage 5. Reinforcement is placed into the pile up
to the required depth.

The pile installation through technology CFA
Modern geoengineering face with engineers anddesigners modern requirements, therefore traditional
technologies were replaced by resent economically,
ecologically and energy-efficient technologies,
including pile foundation. Pile foundation is a
widespread type of foundations on construction sitesof Kazakhstan. Expediency of pile foundation is
explained by high value of bearing capacity of highrise buildings. At the same time settled designStandards is not corresponding with new emerged
technologies,
becauseofabsenceanyFig. 51131

The CFA construction sequence.

SEE - Nagoya, Japan, Nov.12-14, 2018

Static Pile Loading Test
Static Compression Pile Loading Test
In this article loading tests used for deep drilling
piles in KPC Gas Debottlenecking Project near
Aksai, Kazakhstan. Bored piles which have diameter
600 mm and from 15.53 to 21.85 m depths havebeen executed at the Caspian Sea for more
shipments platforms construction site. Some of therequirements of the designer of piled foundations
and to what extent the accessible testing methods
comply with these requirements are considered.
Finally, some recommendations are made for testing
methods suitable for problematical groundconditions of Kazakhstan are introduced.
Static Compression Pile Loading Test (further
SCPLT) one of the more reliable field tests inanalyzing pile bearing capacity. SCPLTs carried out
for four piles on the construction site (see Figure 6).
The measured relationships between the pile headload, L, and the head settlement, S, of the test piles
are shown in Figure 7.
It is seen from Figure 7 that the load-settlement
curves of four piles SCPLT-1,-2, -3 and SCPLT-4
are almost identical, having an ultimate shaft
capacity of 1050 kN (SCPLT-3 and SCPLT-4),1310
kN (SCPLT-2) and 1975kN (SCPLT-1).
Standard – SNiP RK 5.01-03-2002 – ultimate
value of settlement of the tested pile is determined as
and depending on category of construction is equal
to 16 or 24 mm. The last argument shows
conditional character of SLT method [4-6].
According to Kazakhstan Standard 1% ofconstructed piles on construction site must be tested
by SCPLT, but at least 2 SCPLTs in a site must be
done.
According to SCPLT results, the load-settlement
diagrams were drawing (see Figure 7). The pressurein the jack was created with the help of manualelectro-hydraulic pump station NER -1,6A40T1 withpower distribution, the moving of concrete piles was
fixed by caving in measurers MA100BU100, whichwere positioned on center of unmovable bearings
with the benchmark system. For reference beams
using two H-beams with h=20 cm and length 5.3 m
which bolted with clamp to screw piles BAU
114*4*2000 drilled in soil with depth 1.5 m.
Testing platform presented itself system fromsteel, which consists of metallic beam and 2
platforms located on equidistant distances from thecentre main beams (see Figure 6a). Most of the static
pile load tests are performed using reaction systems(see Figure 6b). SCPLT is a highly accurate androbust system that enables you to monitor static pile
tests whilst also ensuring the safety of site
operatives.
This test is used to measure the axial deflectionof a vertical deep foundation when loaded in static
axial compression. This vertical compression pile

maintained load test is usually carried out to ensure
the structural and geotechnical soundness of the pileand also to predict settlement of other piles.

Fig. 6 Field pile test by SCPLT method a)platform b) anchors pile.
The usual procedure is to increase the load instages until the proposed working load and a certain
factor of safety is reached and then to unload and toleave the load off until the rise or reboundsubstantially ceases, the test in standardized by
ASTM D1143 [7]. Vertical static loading of piles
using the SCPLT method is one of the most widelyused field test methods for soil used to analyze pile
bearing capacity. The pile may be tested in two
standards cycles:- The 1st cycle tests the pile to its 150% of the
Design Load.
- The 2nd cycle tests the pile to its 200% of the
Design Load.

Fig. 7 Results of Static Compression Pile Load
Test (piles SCPLT-1, -2, -3 and SCPLT-4).
Static compression pile loading tests were
performed on bored piles No. SCPLT-1,-2, -3 and
SCPLT-4, which are with depth from 15.53 and21.85. In SCPLT testing, the test load on the pile is1132

SEE - Nagoya, Japan, Nov.12-14, 2018

specified for one and two cycles (one 1050 kN(SCPLT-3,-4) and two cycles from 786 kN to 1310
kN (SCPLT-2) and from 1185kN to1975kN(SCPLT-1), respectively). Loading and unloading
was carried out in the following sequence (SCPLT1): 0, 25, 50, 75, 100, 125, 150, 100, 50, 0, 25, 50,
100, 125, 150, 175, 200, 225, 250, 200, 150, 100, 50
and 0% of design. In the first cycle, the experimental
pile was loaded to 150% of the design value (1185kN); during the second cycle, to 200% (1975 kN).
The hold time while loading was 60 min; while
unloading −15 min. It took 300 min, respectively, toattain peak load [7].

following sequence (for STPLT): 0, 25, 50, 75, 100,
125, 150, 100, 50, 0, 25, 50, 100, 125, 150, 175, 200,
225, 250, 200, 150, 100, 50 and 0% of design. In thefirst cycle, the experimental pile was loaded to 360
kN of the design value; during the second cycle, to
600 kN. According to STPLT results, the load settlement diagrams were drawing (see Figure 9) [7].

Static Tensile Pile Loading Test
Static tensile loading test do not apply concreteand composite piles, prestressed reinforced concrete
piles without transverse reinforcement bored piles
with enlarged base and screw piles. It is allowed touse the piles with the help of which the soil test wastested with static top down load. The depth of thepile subsidence during test conducted for the
purpose of determination of the negative friction in
subsiding soils, apply equal to the distance from thesurface of the soil to the depth where the soil
additive from its own weight during soaking equal
the maximum permissible draft for the plannedbuilding or structure. For the criterion of conditional
stabilization deformation take the exit velocity of thepile from soil on each stage of the application tensile
load must be no more than 0.1 mm in the last 1 hourof observation or pile foundations of buildings andstructures (except bridges), and pile foundations forbridge piers - no more than 0.1 mm in the last hourof observation. Load at the control pile test withtensile load during construction should not exceed
the design tensile load on pile indicated in
calculation of the pile foundation.
In this paper static tensile loading tests used fordeep CFA bored piles in construction site Aksai (seeFigure 8). Bored piles which have diameter 600 mm
and from 15.51 to 21.71 m depths have been
executed at the Caspian Sea for more shipments
platforms construction site.

Fig. 9 Results of Static Tension Pile Load Test
(piles SCPLT-1,-2,-3 and SCPLT-4).
Static Lateral Pile Loading Test
This test method covers procedures for testingvertical and batter piles either individually or ingroups to determine the load‐deflection relationshipwhen subjected to lateral loading. It is applicable toall deep foundation units regardless of their size or
method the actual lateral load capacity of the pile‐soil system can best be determined by lateral testing.
Such testing measures the response of the pile‐soil
system to lateral loads and may provide data forresearch and development, engineering design,quality control, and acceptance or rejection under
specifications. Under the iterative elastic method ofanalysis that considers the nonlinear response of thesoils, lateral testing combined with proper
instrumentation can be used to determine soil
properties necessary for the structural design of thepile to resist the lateral load to be applied.

Fig. 10 Static Lateral Pile Loading Test.

Fig. 8 Static Tension Pile Loading Test.
Loading and unloading was carried out in the

In this article static Lateral loading tests used fordeep CFA bored piles in construction site Aksai (seeFigure 10). Bored piles which have diameter 600
mm and from 15.51 to 20.50 m depths have been1133

SEE - Nagoya, Japan, Nov.12-14, 2018

executed at the Caspian Sea for more shipments
platforms construction site.
Loading and unloading was carried out in thefollowing sequence (for SLPLT): 0, 25, 50, 75, 100,
125, 150, 100, 50, 0, 25, 50, 100, 125, 150, 175, 200,
225, 250, 200, 150, 100, 50 and 0% of design. In thefirst cycle, the experimental pile was loaded to 150%of the design value (120 kN); during the second
cycle, to 250% (200 kN) [7]. According to SLPLT
result, the load - displacement diagrams weredrawing (see Figure 11).
Table 2 presents a comparative analysis of the
bearing capacity of piles, obtained by different
methods in this research.
Table 2 Results of complex of field piling static
loading tests
#

1
2
3
4
1
2
3
4
1
2

Pile #

L, m

D, mm

Load,
kN
Static Compression Pile Loading Test
SCPLT-1 20.50
600
1975
SCPLT-2 15.53
600
1310
SCPLT-3 21.85
600
1050
SCPLT-4 21.72
600
1050
Static Tension Pile Loading Test
STPLT-1
20.50
600
600
STPLT-2
15.51
600
600
STPLT-3
21.71
600
360
STPLT-4
21.69
600
360
Static Lateral Pile Load Test
SLPLT-1
15.51
600
200
SLPLT-2
20.50
600
200

S,
mm
2.14
1.48
0.94
1.08

The results of the axial compression and tension
loading tests performed in soft to firm or stiff clays
demonstrated the suitability of CFA bored pilefoundations. The results of the loading testing
program confirmed that the CFA bored pile is a
viable deep foundation option for construction Oiland Gas in remote areas West Kazakhstan anddemonstrated their advantages.
Static pile loading test is the most reliable
method to obtain the load-settlement relation ofpiles. Most of the static pile load tests are performed
using reaction systems. The number of pile load tests
in construction site is limited to 2 piles in usual of
construction site in Kazakhstan.
The results of the full-scale load tests are also
used to validate the theoretical model used for CFA
bored pile design installed in soft and problematicalsoils of northwest of Kazakhstan.
The bearing capacity of CFA boring piles
according to the results of shown table 5 amounted
to be maximal load 1975 kN, settlement from 0.94
mm to 2.14 mm. These investigations are importantfor understanding of behavior of piles on
problematical soil ground of Aksai, northwest of
Kazakhstan.
REFERENCES

0.41
0.32
0.16
0.33
6.19
7.27

Fig. 11 Results of Static Lateral Pile Load Test
(SLPLT-1 and SLPLT-2).
CONCLUSION
Existing pile foundation standards practiced in
Kazakhstan are out-of-date and are in urgent needfor modernization. This paper presented very short
descriptions of coming changes to the concept of
Kazakhstan pile foundation design.

[1] Zhussupbekov, A., Omarov, A., Zhukenova, G.,
Tanyrbergenova, G. (2017). Pile Foundations ofMega Projects: New Railway Station and LRTin Problematical Soil Ground of Astana.
Procedia Engineering, Vol. 189, Pages 511-518.
[2] GOST 20276-99 (1999). Soils. Field methods
for determining the strength and strain
characteristics.
[3] ASTM D 1194. Standard Test Method for
Bearing Capacity of Soil for Static Load andSpread Footings.
[4] Zhussupbekov A.Zh., Lukpanov R.E., Omarov
A.R. (2016). Experience in Applying Pile Static
Testing Methods at the Expo 2017 Construction
Site. Journal of Soil Mechanics and Foundation
Engineering. Volume 53, Issue 4, Pages 251256.
[5] Zhussupbekov A., Omarov A. (2016). Modern
Advances in the Field Geotechnical Testing
Investigations of Pile Foundations. Procedia
Engineering, Vol. 165, Pages 88-95.
[6] Zhussupbekov, A.Z., Lukpanov, R.E., Omarov,
A.R. (2016). Bi-directional Static Load testing.
Fourth Geo-China International Conference(Geotechnical Special Publication). Shandong,
China. Pages 35-42.
[7] ASTM D1143 / D1143M - 07(2013) Standard
Test Methods for Deep Foundations Under
StaticAxial
Compressive
Load.

1134