ISBN: 978-4-909106032 C3051

Proceedings

EDITED BY
Zakaria Hossain
Suksun Horpibulsuk
Jim Shiau

November 11 – 13, 2019
Swissotel Le Concorde, Bangkok, Thailand

SEE 2019, BANGKOK, THAILAND
SCIENCE, ENGINEERING AND ENVIRONMENTiPROCEEDINGS OF FIFTH INTERNATIONAL CONFERENCE – SEE 2019SCIENCE, ENGINEERING & ENVIRONMENT BANGKOK, THAILAND
11-13 NOVEMBER, 2019

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

Prof. Suksun HorpibulsukCenter of Excellence in Innovation for Sustainable Infrastructure Development
School of Civil Engineering Suranaree University of Technology, Thailand

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

THE GEOMATE INTERNATIONAL SOCIETYii

Copyright @ 2019 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: 978-4-909106032 C3051

iii

Fifth International Conference on Science, Engineering & Environment,
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

Table of Contents

ID

Prefacexii

Organization

xiii

Keynote Papers

1

1k

A CONCRETE WALL ELEMENT TEST TO EVALUATE COM-PRESSIVE FRACTURE ENERGY
Tetsuya Ohmura, Kyouhei Iwasaki and Hiroaki Matsufuji

2k

LANDSLIDES: BEHAVIOR AND MITIGATION APPROACH
Avirut Chinkulkijniwat, Somjai Yubonchit

2

8

21

Technical Papers
ID

Science

225508

DIFFERENT RATIOS OF OKRA JUICE AND PANDAN LEAF JUICE ON SPORT DRINK
Wattana Wirivutthikorn

23

5513

ESTIMATING PEOPLE'S TRAVEL BEHAVIOR TOWARDS TRANSIT-ORIENTED DEVELOPMENT INDUKUH ATAS, DKI JAKARTA PROVINCE
Gemala Pritha Ryzki Rynjani, Chotib

29

5533

ABOUT KARST (CHEMICAL) DENUDATION IN ZEMO IMERETI PLATEAU. GEORGIA,CAUCASUS
Zaza Lezhava, Lasha Asanidze, Kukuri Tsikarishvili, Nino Chikhradze, Lela Gadrani

35

5536

RESEARCH AND DEVELOPMENT OF PILLOW FOR HEALTH IN THAI PEOPLE: A PILOT STUDY
Panida Chaiming, and Wichai Eungpinichpong

41

5540

THE IMPACT OF URBANIZATION ON THE WATER QUALITY OF UTTARA LAKE, DHAKA – CASESTUDY.
Shama Emy Haque and Farhana Aktar

47

5542

THE EFFECTS OF COMBINED ELECTRICAL STIMULATION WITH SHORT FOOT EXERCISE ON
MEDIAL LONGITUDINAL ARCH AND INTRINSIC FOOT MUSCLE SIZE: A PILOT STUDY
Juntip Namsawang, Ratana Vichiansiri, Wichai Eungpinichpong, and Somchai Rattanathongkom

53

5543

EFFECT OF LAND MANAGEMENT OF HORTICULTURAL TO SOIL ERODIBILITY AT THE
UPSTREAM OF SUMANI WATERSHED
Aprisal, Bambang Istijono and Indradwipa

58

5544

A NEW REPORT OF ARGULUS INDICUS (CRUSTACEA: BRANCHIURA) INFESTATION IN RED TILAPIA(OREOCHROMIS NILOTICUS X OREOCHROMIS MOSSAMBICUS) IN THAILAND
Supamas Sriwongpuk

64

5545

IMMEDIATE EFFECTS OF ARM SWING EXERCISE THERAPY ON THE RANGE OF SHOULDERMOTION AND STAND POSTURE: A PILOT STUDY IN YOUNG ADULTS
Zhen Xiao, Wichai Eungpinichpong, Xingze Wang, and Uraiwan Chatchawan

70

iv

5559

COMPARISON OF INTRAOCULAR PRESSURE CHANGES AFTER VIEWING LAPTOP COMPUTER AND
TABLET COMPUTER: A PILOT STUDY
Pattrawan Pattaranit, Tanapat Ratanapakorn, Rungthip Puntumetakul, Orawan Buranruk, andWichai Eungpinichpong

76

5562

THE CRUDE TANNIN EXTRACTION FROM WOOD SCRAP WASTES FOR PROLONGING THE SHELF LIFE
OF LITCHI FRUITS
Pornanan Boonkorn, Angkhana Chuajedton and Weeranuch Karuehanon

81

5566

EXTRACTION OF PECTIN FROM PEANUT SHELL WASTE WITH HEATING IN COMBINATIONWITH ULTRASONIC-ASSISTED EXTRACTION
Chuajedton, A., Karuehanon W. and Boonkorn, P.

87

5567

5602

5612

5618

EFFECT OF COMBINATION MICROWAVE AND OVEN DRYING ON THE CHEMICAL PROPERTIES
OF CRUDE PALM OIL OBTAINED FROM DIFFERENT OIL PALM FRUIT RIPENESS
Mallika Tapanwong, Rayakorn Nokkaew and Vittaya Punsuvon
EFFECTS OF CHLORINE DIOXIDE DIPPING ON PERICARP BROWNING REDUCTION OF LONGAN FRUIT
Suttinee Likhittragulrung, Tanachai Pankasemsuk, Kanda Whangchai,
Wittaya Apai and Wanwarang Patanapoh
SPATIAL DISTRIBUTION OF RESTAURANT POPULARITY INDEX BASED ON CONSUMER REVIEWWEBSITE IN JAKARTA
Dewi Susiloningtyas, Alexander Tio, Supriatna and Sidiq, IPA
EFFECT OF ELECTROLYZED REDUCING WATER ON CARBENDAZIM SOLUTION AND RESIDUESDEGRADATION OF CHERRY TOMATO (Solanum lycopersicum L. var. cerasiforme)
Wanwarang Pattanapo, Kanda Whangchai, Jamnong Uthaibutra, Tanachai Pankasemsuk
and Usawdee Chanasut

93

98

104

110

5619

EFFECT OF FRUIT BAGGING ON QUALITIES OF PUMMELO CV. KAO NAM PHEUNG AND KAO YAI
Yaowarat Wongsrisakulkaew, Chanpen Chaimongkol and Niyom Buaban

116

5624

EFFECT OF ELECTROLYZED OXIDIZING WATER AND ULTRASONICATION ON PATHOGENIC CONTROLOF FRESH TUMERIC (Curcuma longa L.)
Santirote Keatsirirote, Angkhana Chuajedton, Jamnong Uthaibutra and Kanda Whangchai

120

5629

EXTRACTED OF THE ANTHOCYANINS FROM Clitoria ternatea FOR STAINED PROTOZOA AND
ANTIAMOEBIC ACTIVITY
Chanyapat Sangsuwon

5636

EFFECT OF TRADITIONAL THAI MASSAGE ON MUSCLE OXYGEN SATURATION IN LOW BACK PAIN
PATIENTS: A PRELIMINARILY STUDY
Ketsarakon Oatyimprai, Wichai Eungpinichpong, Orawan Buranruk and Kurusart Konharn

5640

PROBIOTICS ENCAPSULATED FRUIT JUICE PEARLS AS FUNCTIONAL FOOD PRODUCTPalida Tanganurat, Intira Lichanporn,Nunchanok Nanthachai and Charoen Charoenchai

5642

EFFECT OF ENVIRONMENTAL FLUCTUATIONS ON INCIDENCE OF MYCOFLORA
H. N. P. Singh, Sunita Kumarii and M.M. Prasad

126

131

138
144

5656

EFFECT OF KNEADING AND FERMENTATION TIME ON CHEMICAL QUALITY OF HERBAL TEA FROMMANGO PEEL
Nunchanok Nanthachai, Intira Lichanporn, Palida Tanganurat and Pradit Kumnongphai
FORMULATION, ANTIOXIDANT AND ANTIBACTERIA ACTIVITIES OF PEEL-OFF GEL MASK, ENRICHEDWITH BIDARA LEAF (ZIZIPHUS SPINA-CHRISTI L.) EXTRACT
Hendrawati, Aziza, La Ode Sumarlin, Yulyani Nur Azizah

5659

A STUDY ON ELECTRICAL IMPEDANCE IN RIPENING AMBON-BANANAS (MUSA PARADISIACA
VAR. SAPIENTUM) PROCESSES STIMULATED BY ETHREL (2-CHLOROETHYL PHOSPHONIC ACID)
Chomsin S Widodo, Didik Rahadi Santosa, Wahyu Sugianto, Arinto Yudi P Wardoyo

162

5660

DNA EXTRACTION METHODS FOR FIN OF MACKERELS IN THAILAND
Walaiporn Makkapan, Patcharaporn Narkthewan and Kaewalee Viboonkit

168

5654

v

148

155

5678

ANGIOTENSION CONVERTING ENZYME (ACE) INHIBITORY ACTIVITY OF PROTEIN EXTRACTOF MUNG BEANS (Vigna radiata L.) TEMPEH FERMENTED BY Rhizopus sp.
Sri Yadial Chalid, Siti Nurbayti, Zelda Zein Zunaedi

173

5680

ESTIMATION OF PROPENSITY SCORE USING LOGISTIC REGRESSION (CASE STUDY: BREASTFEEDINGDATA IN SELOPURO SUB-DISTRICT BLITAR REGENCY)
Hilwin Nisa’, Maria Bernadetha Theresia Mitakda, and Suci Astutik
THE MORPHOLOGY AND PHENOLOGY OF YELLOW COMMON BEAN (F7) AS OFFSPRING OF
INTRODUCED AND LOCAL VARIETY CROSSING
Fathiyyah, Sumeru Ashari and Andy Soegianto

5690

FORWARD MODELING FOR SUBSURFACE SYNTHETIC SEISMOGRAM
Wasis Wasis, Adi Susilo, Musthofa Nuh

187

5693

THE PERFORMANCE OF INDONESIAN AGRICULTURAL EXTENSION WORKER
Siti Rochaeni, Muchlis R. Luddin, Mansyur Ramly, and Dewi Susita

191

5695

DETERMINATION OF HISTAMINE-FORMING BACTERIA, TOTAL COLIFORM AND ESCHERICHIA COLI IN
FERMENTED FOODSPatcharaporn Narkthewan and Walaiporn Makkapan

196

5679

5696

5710

5716

5727

5749

5780

VITAMIN AND MINERAL CONTENT OF SIX NATIVE VARIETIES OF RICE IN THAILAND
Intira Lichanporn, Nanchanok Nantachai, Palida Tunganurat, Unchalin Singkhum, Nowapor
Lapsongphon, Anchalee Sawatthum, Ratchata Tonwitowat, Tongmee Mosom and Purin
Akkarakultron
AFM VISUALIZATION OF PHYTOPLASMA DNA IMMOBILIZATION AND HYBRIDIZATION EVENT ON
CHITOSAN MODIFIED SPCE SURFACE
Porntip Wongkaew, Buddhapala Wongkaew
IMPROVEMENT THE PROPERTIES OF POLY(L-LACTIDE) FILMS WITH CELLULOSE FIBER FROM RICESTRAW WASTE IN AGRICULTURAL PRODUCTS
Chutima Banthao, Patcharin Kumpolsan, Yodthong Baimark, Sujitra Wongkasemjit, and Kansiri
Pakkethati
SUSTAINABLE AQUACULTURE MANAGEMENT OF VANAMEI SHRIMP (Liptopenaeus vannamei) IN
BATUKARAS VILLAGE, PANGANDARAN, INDONESIA
Andrian Achmad, Dewi Susiloningtyas and Tuty Handayani
EVALUATION OF THE TOXIC EFFECTS OF SMOKELESS TOBACCO CHEWING MIXTURES BASED ON
BIOLUMINESCENCE TESTING USING THE EXAMPLE OF NASWAR
Dianna B. Kosyan, Olga V. Kvan, Elena A. Rusakova, Inara E. Larjushina, Elena V. Kiyaeva, Galimzhan
K. Duskaev
THE MODIFIED DECOMPOSITION METHOD FOR SOLVING VOLTERRA FREDHOLM
INTEGRO-DIFFERENTIAL EQUATIONS USING MAPLE
Dalal Adnan Maturi

179

183

201

205

211

217

222

229

5785

STUDY OF ELECTRON FLUXES IN IONOSPHERE-PLASMASPHERE COUPLING FROM WHISTLERSOBSERVED AT LOW LATITUDE GROUND STATION JAMMU L= 1.17
M. Altaf

233

5789

METAL PLASTICITY AND PERIODIC TABLE
Lev B. Zuev, Svetlana A. Barannikova and Albina M. Zharmukhambetova

240

ID

Engineering

246

5506

ECONOMICAL ANALYSIS OF THE GEOGRID REINFORCED RAILWAY TRACK
ASaad Farhan Ibrahim, Ali Jabbar Kadhim and Harith Basim Khalaf

247

5507

A STOCHASTIC MODEL OF THE MRO SPARE PARTS PROCUREMENT PLANNING PROBLEM FOR
AIRCRAFT MAINTENANCE SERVICE PROVIDER
Yichen QIN, Felix T.S. CHAN, S.H. CHUNG and T. QU

252

vi

5510

COMPUTING PROGRAM FOR EVALUATING RESSUREMETER TEST RESULTS OF CLAY
Radhi Alzubaidi and Athra Al-Kanim

256

5516

ANALYSIS OF PROBLEMS AND SOLUTIONS IN THE HEAT INSULATING GLASS MANUFACTURING
INDUSTRY USING FMEA
Natsuda Paiboon,Nipalai Inplaeng, Wisitsree Wiyaratn and Anucha Watanapa

261

5519

APPLICATION OF DEAGGREATION OF SPATIAL PROBABILISTIC SEISMIC HAZARD TO DISASTERPREPAREDNESS
Takayuki Hayashi and Harumi Yashiro

267

5521

A CONCRETE WALL ELEMENT TEST TO EVALUATE COM-PRESSIVE FRACTURE ENERGY
Tetsuya Ohmura, Kyouhei Iwasaki and Hiroaki Matsufuji

273

5525

THE EFFECTS OF BATANG KANDIS RIVER FLOOD CONTROL IN PADANG CITY-PALAPAMETROPOLITAN AREA
Benny Hidayat, Bambang Istijono, Irwan Irwan, Taufika Ophiyandri and Akhmad Junaidi

279

5527

FATIGUE STRENGTH OF HEADED STUDS WELDED WITH IMPROVED FERRULE IN CONCRETE UNDERUNIDIRECTIONAL CYCLIC LOADING
Hiroshi Higashiyama, Kenji Yoshida, Satoshi Banba and Shigeyuki Matsui

285

5528

DESIGN AND ANALYSIS OF FORMULA SPACE FRAME CHASSISWITH SIDE IMPACT
Boonthum Wongchai

291

5529

PUBLIC TRANSPORT INITIATIVES IN WEST AFRICA, A CASE STUDY OF ABIDJAN
Leonard Johnstone and Vatanavongs Ratanavaraha

297

5530

PRELIMINARY RESULTS OF SITE-SPECIFIC GROUND RESPONSE ANALYSIS
Bambang Setiawan, Taufiq Saidi and Mark B. Jaksa

305

5531

STUDY OF SEEPAGE THROUGH AN EARTH DAM CASE STUDY (AJDABIYA RESERVOIR)
Prof. Salem Al- Sanusi, Mervat J. M. Alarosh

311

5532

ANALYSIS OF SLOPE STABILITY (AJDABIYA RESERVOIR)
Prof. Salem Al- Sanusi, Abier J. M. Alarosh

315

5534

PREDICTION OF FLEXURAL STRESS IN UNBONDED POST-TENSIONED STEEL AT DIFFERENT LOADING
STAGES
Nazar Oukaili and Iqbal Peera

320

5539

5541

5549

5553

THE DURABILITY OF LIME STABILIZED EXPANSIVE SOIL
Yulvi Zaika, Eko Andi Suryo
DURABILITY OF CONCRETE CONTAINING RECYCLED ASPHALTIC CONCRETE AGGREGATE AND HIGHCALCIUM FLY ASH
Prinya Chindaprasirt, Pornnapa Kasemsiri, Sompron Leekongbub3 and Patcharapol Posi
WALKING AUTHENTICATION BASED ON POWER SPECTRUM DENSITY OF ACCELERATION AT LUMBERPART
Masahiro Yoneda
EFFECT OF SALT CONTENTS ON COMPRESSIVE STRENGTH OF DMM IN SALINITY CLAY SOFT SOILSFOUNDATION IN VIETNAM
Tran Thi Nguyen Hao, Tran Thi Thanh and Vo Phan

326

332

339

344

5554

CORRELATION BETWEEN VIBRATION SIGNALS AND SOUND SIGNALS OF A PERSONAL CAR WITHGASOLINE ENGINESuphattharachai Chomphan, Boonthum Wongchai

349

5558

STRESS ANALYSIS OF EMBANKMENT DUE TO DIFFERENT IN CONSTRUCTION CONDITIONS
Shin-ichi Kanazawa and Satoe Suzuki

355

vii

5560

5561

5563

INVESTIGATION OF OPTIMAL CONTACT TYPE ULTRASONIC COLLECTING DEVICE FOR MEASURINGROUGHNESS USING AERIAL ULTRASONIC SENSOR
Seiya Nagaoka, Kenji Okajima, Mohammad Raihanul Islam, Ryoei Ito and Ken Watanabe
Experimental Investigation of Multi-axial Mechanical Behavior of Rubber Materials for BaseIsolated Bridges
Hiromichi Narita, Junji Yoshida, and Kouichi Takeya
HIGHLY ACCURATE ESTIMATION OF DAILY SUSPENDED SEDIMENT LOAD USINGMULTIVARIATE HYDROLOGICAL
Phakawat Lamchuan, Adichai Pornprommin, Jiramate Changklom

361

367

372

5569

FATIGUE STRENGTH OF HEADED STUDS UNDER ROTATIONAL SHEAR LOADING FOCUSING ON
WEIGHT REDUCTION OF STEEL-CONCRETE COMPOSITE BRIDGE DECK
Kenji Yoshida, Hiroshi Higashiyama, Hideki Ogomori and Shigeyuki Matsui

378

5582

LABORATORY EXPERIMENT OF CHANNEL HEAD BIFURCATION BY RADIAL OVERLAND FLOW
Adichai Pornprommin, Ravicha Thaisiam and Wandee Thaisiam

384

5583

IDENTIFICATION OF DRAINAGE SYSTEMS CAPACITY USING EPA-SWMM 5.1 VERSION MODELING INGUNUNG PANGILUN OF PADANG CITY-PALAPA METROPOLITAN AREA
Taufika Ophiyandri, Bambang Istijono, Milania, Benny Hidayat, and Aprisal

390

5584

SIMULATION OF THE COLLAPSE PROCESS OF INFRASTRUCTURE USING GENERAL-PURPOSE PHYSICSENGINE
Yoshihiro Kabeyama, Sunao Fujimura and Shinichiro Okazaki

396

5587

MOTORCYCLE-RELATED DEATHS AND HELMET USAGE SITUATION IN THAILAND
Jetsada Kumphong, Thaned Satiennam and Wichuda Satiennam

402

5589

5593

5594

5604

STUDY ON SEISMIC LOAD ON BUILDINGS CONSIDERING RESIDUAL RISK
Sei’ichiro Fukushima, Takayuki Hayashi and Mitsuo Tsuzuki

408

CONSTRUCTION OF DAMAGE FUNCTION FOR AN ANALYSIS OF THE ECONOMIC DAMAGE BY
EARTHQUAKES WITH A FOCUS ON THE RECONSTRUCTION OF SHARED HOUSING
Norikazu Sakaba, Yashiro Harumi

414

GROUND SURVEY BASED ON THE DISTRIBUTION OF SURFACE WAVE VELOCITY AND ELECTRICALRESISTIBILITY
Katsuyuki Kawai, Ryosuke Hamada and Koji Nakashima
BASIC STUDY ON BRIDGE WEIGH-IN-MOTION USING OPTICAL FLOW ANALYSIS
Kouichi Takeya, Junji Yoshida

420

426

5609

EFFECT OF REINFORCEMENT STIFFNESS ARRANGEMENT ON SEISMIC PERFORMCANCE OF GEOGRID
REINFORCED SOIL WALLS
Albano Acacio Ajuda, Jiro Kuwano and Kosuke Hoshina

432

5611

THE IMPACT AGGREGATE QUALITY MATERIAL AS A LINEAR REGRESSION STUDY ON MIXTURE
CONCRETE
Ranti Hidayawanti, Dicki Dian Purnama , Tommy Iduwin, Supriadi Legino and Fahdun Ibnu Wachid

439

5616

DEVELOPMENT OF A MICROBIAL-BASED GROUTING MATERIAL WITH CALCIUMCARBONATE PRECIPITATESYoko Sakakihara, Yoshihiro Kabeyama and Shinichiro Okazaki

446

5620

EVALUATION OF LARGE DIAMETER JET GROUTING TECHNIQUE USED FOR TUNNEL CONSTRUCTION IN
BANGKOK
Kuo Chieh Chao, Ph.D., P.E., Sasirada Seepim, Ricky K. N. Wong, Takeshi Iwakubo, and Morris Wang

452

5623

STRUCTURAL BEHAVIOR OF NON-DUCTILE REINFORCED CONCRETE COLUMNS
Ari Wibowo, Rizki Amalia Tri Cahyani

458

5628

STATISTICAL ANALYSIS OF THE INFLUENCE OF TRAFFIC AND ENVIRONMENTAL DISTURBANCES ONDAMPING IN A BRIDGE
Koharu Ota, Kouichi Takeya, Junji Yoshida

465

viii

5631

REDUCTION IN BEARING CAPACITY OF GYPSEOUS SOILS WITH CAVITIES
Ahmed A. Al-Obaidi and Reem S. Najim

471

5634

A STUDY OF THE EFFECTS OF THE FLOOD IN 2554 ON AGRICULTURAL MACHINERY USE IN RICEPADDY FIELDS IN PATHUMTHANI PROVINCE
Dowroong Watcharinrat

478

5637

DESIGN AND IMPLEMENT A MONITORING SYSTEM OF TRAFFIC SIGNAL USING MICROCONTROLLER
DEVICES
Aleksander Purba, Rahayu Sulistyorini, Agung Ilhami and Ageng Sadnowo Repelianto

484

5645

ENHANCING THE ROLE OF BENT-UP BARS IN SHEAR BEYOND THE CODE REQUIREMENTS BY USINGPLANE-CRACK INTERCEPTOR-CROSS DIAGONAL FORM
Ms. Naim Asha

490

5650

EFFECT OF EXCESS PORE WATER PRESSURE IN SATURATED SANDY SOIL FOR EVALUATING
LIQUEFACTION POTENTIAL DURING EARTHQUAKE DURATION
Hua Thanh Than, Nguyen Ngoc Phuc and Tran Thi Thanh

5653

PREDICTION OF GROUNDWATER LEVEL USING A DISCRETE SPACE-STATE MODEL AS AN
ALTERNATIVE TO PHYSICALLY BASED GROUNDWATER MODELLING
Dilip Kumar Roy, Sujit Kumar Biswas and Khandakar Faisal Ibn Murad

506

5661

EXPERIMENTAL INVESTIGATION OF RESPONSE OF SEGMENT LINING DUE TO ADJACENT PILE UNDERLOADING
Pattanasak Chaipanna, Kisada Trakoonjannak and Pornkasem Jongpradist

512

5663

THE STUDY ON EFFECT OF LIGHTWEIGHT CONCRETE BLOCK BY WATER HYACINTH ADDING
Prang Subpa-Asa, Laemthong Laokongthavorn, Shigeyuki Date

516

5669

STUDY ON THE PROPERTIES OF CEMENT MILK ADDED WITH BAKING SODA -COMPRESSIONSTRENGTH ESTIMATION FROM BLEEDING REDUCTION AND INITIAL ELECTRICAL RESISTIVITY
Yasuhide Mochida, Joshua O. Ogunbiyi ,Makoto Minemoto,and Keisuke Funato

523

5761

SHEAR STRENGTH AND PERMEABILITY ANALYSIS OF GEOTEXTILE FROM PINEAPPLE LEAVES AND
LUFFA
INZ Baharuddin, Hairin Taha, RC Omar, R.Roslan and S.Nadirah

529

5673

5674

5681

5682

APPLICATION OF WASTE WATER AND GREEN ALGAETO STRENGTHEN SOIL
R.Roslan, RC Omar, INZ Baharuddin, Hairin Taha and M.Syafiq
QUANTITATIVE INTERPRETATION OF LANDSLIDE OCCURRENCE SITE BY AI TECHNOLOGY OF IMAGE
CLASSIFICATION AND TOPOGRAPHICAL ANALYSIS MAP CREATED BY AERIAL LASER DATA
Koki Sakita, Satoshi Nishiyama, Teruyuki Kikuchi, Junsheng Song and Yuzo Ohnishi

497

535

541

LIQUEFACTION MAPPING PROCEDURE DEVELOPMENT: DENSITY AND MEAN GRAIN SIZEFORMULATIONS
Abdul Hakam, Bayu Martanto Adji and Junaidi

547

COMPARISON STUDY ON DAMAGE PATTERN OF TWO STORIES BUILDING: SIMULATION VS
FIELD RECORD
Febrin Anas Ismail, Abdul Hakam, Hendri Gusti Putra, M Maisaquddus Hape, M Sofian
Asmirza

553

5700

LIQUEFACTION POTENTIAL MAPPING OF THE CITY OF VALENZUELA, PHILIPPINESAngelo S. Enoria, Jr., Sophia Joy Q. San Juan, Hiyasmin F. Ubaldo

558

5702

THE PROPERTIES OF POROUS CONCRETE PAVING BLOCKS
Nurul Rezuana Buyung and Abdul Naser Abdul Ghani

562

5703

CONSTRUCTING AN ARTIFICIAL INTELLIGENCE MODEL FOR WATER ENVIRONMENT EVALUATION
Shengping Zhang and Jie Qi

568

ix

5705

5706

5707

INFLUENCE OF ERRORS THAT RESULT FROM CONSIDERATION OF WATER IN-FLOW DIMENSIONDIFFERENCES BASED ON OBSERVATION METHOD FOR MOUNTAIN TUNNEL CONSTRUCTION
Yasuyuki Kubota, Moritada Mori, Toru Yasuda, Satoshi Nishiyama
THE USE OF SAWDUST WASTE ON PHYSICAL PROPERTIES AND THERMAL CONDUCTIVITY OF FIRED
CLAY BRICK PRODUCTION
Nonthaphong Phonphuak, Anuwat Srisuwan, Must Srila, Siriwan Artbumrung and Panuwat
Ruenruangrit
THE VERIFICATION OF DIFFERENCE ANALYSIS IN THE HIGH PRECISION INSPECTION TECHNOLOGYFOR SLOPE SURFACE, USING MOBILE MAPPING SYSTEM
Naoto Samori, Satoshi Nishiyama, Koki Sakita, Michinari Fuziki, Naoya Ono and Junsheng Song

575

581

587

5709

LESSON LEARNED IN MAINTAINING THE PRECAST CONCRETE BUILDINGS
Zul-Atfi Ismail

593

5720

ON THE SEASONAL COLORS AND SMELLS ANALYZING SOCIAL NETWORKING SERVICE
Tatsuya Matsuura, Momoko Tanaka, Hayate Deguchi and Kazunari Tanaka

599

5724

PROPOSED ANGAT RIVER WATER IMPOUNDING AND FLOOD MITIGATION PROJECTBon Ryan P. Aniban, Roniel C. Naungayan, Sheina R. Pallega

602

5732

A RISK ASSESSMENT FRAMEWORK FOR HIGH-RISE SCHOOL BUILDING PROJECT IN METRO MANILA,
PHILIPPINES
Michael V. Almeida and Andres Winston C. Oreta
ASSESSMENT OF DEBRIS FLOW VELOCITY USING A SIMPLE LUMPED MASS MODEL FOR DEBRIS FLOWMOBILIZATION
Thapthai Chaithong

5739

DYNAMIC ANALYSIS OF NAILED SLOPE
Srinivas Ch, Padmavathi M and Sanjeeva P

5741

SETTLEMENT OF SILTY SOIL UNDER SATURATION USING MICRO SYNTHETIC FIBERS
Padmavathi, V. and Rao, P. N.

5728

5743
5745

GROUND IMPROVEMENT USING GEOSYNTHETICS ~ A LITERATURE REVIEW
Mohamed Eltaher, Zakaria Hossain, Jim Shiau, and Hajime Takami
STATICAL MODEL OF THE PIEZOELECTRIC SELF-ADJUSTINGGYROSCOPE-ACCELEROMETER
Arif Pashayev, Anvar Hazarkhanov, Toghrul Karimli,Vasif Neymatov

608

616

621

627
632
640

5758

PROPORTION AND PROPERTY SPECIFICATIONS AND STRENGTH BEHAVIOR OF MORTAR USINGWOOD ASH AS PARTIAL REPLACEMENT OF LIME
Robert Michael Tampus, Janine R. Lardizabal, Dennise Linoel M. Acena, Michaela Angelica M. Uy,
and Kenneth Vance R. Arcenal
IMPACTS OF WEATHER VARIABLES ON URBAN WATER DEMAND AT MULTIPLE TEMPORAL SCALES
Chinnapan Makpiboon, Adichai Pornprommin and Surachai Lipiwattanakarn

5760

GROUNDWATER LEVEL RISE IN MUSCAT AIRPORT AREA AND WAYS OF MANAGING THE ISSUE
Luminda Gunawardhana, Mahad Baawain and Ahmed Sana

659

5767

LIGHTWEIGHT FOAMED CONCRETE INTERLOCKING BLOCK UTILISING UNGROUND OIL PALM ASH
Hanizam Awang, Mohammed Zuhear Al-Mulali and Wenny Arminda

665

5757

647

653

5768

FINANCIAL AND INSTITUTIONAL ASPECT FOR APPLICATION OF A CENTRALIZED DOMESTIC WASTEWATERMANAGEMENT SYSTEM IN SUKOLILO DISTRICT, SURABAYA, INDONESIA
Dwi Agustiang Ningsih, Eddy Setiadi Soedjono and Nurina Fitriani

671

5772

ANALYSIS OF CHANGES IN SHEAR STRENGHT AND STIFFNESS OF HO CHI MINH CITY’ SOFT SOIL
UNDER THE UNLOADING STRESS PATHS FOR DEEP EXCAVATIONS CALCULATION
Trung Ngo Duc, Phan Vo and Thanh Tran Thi

677

x

5773

SELF-SUPPORT SHELTER AS AN ALTERNATIVE SOLUTION IN THE TSUNAMI-PRONE AREA
Anas Febrin Ismail, Taufika Ophiyandri, Abdul Hakam, Afdilla Yofianda, Dicky Kurnia Adha, Tria Yuli
Anggraini

683

5774

GREEN CONCRETE HOLLOW BLOCKS UTILIZINGBASIC OXYGEN FURNACE STEEL SLAG
Santiago, Karen Joyce B. and Juan, Jose Arnel P.

689

5776

RESPONSE OF A SINGLE PILE LOCATED ON SLOPING GROUND UNDER DYNAMIC LOADING
Deendayal Rathod, D. Nigitha and Krishnanunni K T

695

5777

BIM-BASED SIMPLIFIED APPROACH TO AUTOMATICALLY ESTIMATE BUILDING COSTS FOR PROJECTSIN THAILAND
Suon Tokla, and Kumpon Subsomboon

701

5779

EMOTIONAL QUOTIENT ASSESSMENT PROGRAM FOR STUDENTS
Nualsawat Hiransakolwong

707

5781

ELECTROMAGNETIC SWITCHING TRANSIENTS IN TRANSMISSION LINE COOPERATING WITH
THE LOCAL SUBSYSTEM
Pawel Sowa, Daria Macha

714

5784

SAFETY, CONNECTIVITY, AND COMFORTABILITY AS INDICATORS TO IMPROVE WALKABILITY TO THE
BUS STOPS IN PENANG ISLAND
Nur Sabahiah Abdul Sukor and Siti Fadhlina Muhammad Fisal

720

5787

APPLICATION OF CONDITIONAL CULTURE ALGORITHM AND SIMULATION FOR OPTIMAL RESERVOIRRULE CURVES PROJECTS
Anujit Phumiphan and Anongrit Kangrang

729

5791

A STUDY OF FLOOD FORECASTING AND MAPPING FOR THE ATTANAGALU OYA
W.C.P. Wickramarachchi, N.K. Gunasekara, W.C.D.K. Fernando and S.S. Wickramasuriya

735

5793

LAO KHAM’S VARISCITE PROPERTIES AND APPLICATION IN CHEMICALLY BONDED PHOSPHATECEMENT
Watcharagon Wongkamjan and Thanawat Jumepaeng

5794

PERFORMANCE EVALUATION OF CONCRETE WITH RECYCLED WASTE POLYPROPYLENE
N. Haque, M.J Islam, A. Tahsin & T. Mehdi

746

5809

LIFE CYCLE COST ANALYSIS FOR REINFORCED GEOGRID RAILWAY TRACK
Saad Farhan Ibrahim Alabdullah, Ali Jabbar Kadhim and Harith Basim Khalaf

751

5810

CHARACTERIZATION OF NEW TYPES OF GEOSYNTHETICS EMBEDDED IN SOIL USING CALIFORNIABEARING RATIO TEST
Mohamed Eltaher, Zakaria Hossain, Jim Shiau, and Hajime Takami

756

ID

Environment

763

5514

A STUDY ON HUMAN DAMAGE IN EVACUATION FROM TSUNAMICONSIDERING STREET-BLOCKADESCAUSED BY DESTROY OF BUILDINGS
Ken-ichi Fujita, Harumi Yashiro

764

5518

DEVELOPING AGE-FRIENDLY CITY: CASE STUDY FROM DEPOK
Fatmah Fatmah

741

770

5537

BIOMONITORING OF WATER POLLUTION IN LAKE CHEBARKUL BY THE CONTENT OF HEAVY METALSIN MACROPHYTE ORGANS, RUSSIA
I.V. Mashkova, A.M. Kostryukova , E.E. Schelkanova, V.V. Trofimenko and A.I.
Slavnaya

781

5538

GROUND REACTION FORCE OF STEP MARCHING: A PILOT STUDYPairaya Sitthiracha, Wichai Eungpinichpong

787

xi

5546

5548

5551

THE EFFECTS OF WATERING RATES USING THE DRIP IRRIGATION METHOD ON THE ROOT MASSGROWTH OF BIRD’S NEST FERNS
Sawat Pimsuwan and Dowroong Watcharinrat
THE INFLUENCES OF HEAVY METALS AND MAJOR IONS IN STREAM WATERS, RUNNING IN
SERPENTINE, LIMESTONE, AND CLOSED-MINE AREAS, ON MACROINVERTEBRATECOMMUNITIES, KINKI AND CHUGOKU, JAPANAkio Nishida and Hiroyuki Ii
LANDSCAPE OPPORTUNITIES AND PREFERENCES FOR CHOOSING RECREATIONAL PLACES OFMEGALOPOLIS RESIDENTS (ON EXAMPLE OF ST. PETERSBURG)
Pogodina V., Matveevskaya A., Filippova I., Evseeva L. and Evseev V.

791

796

802

5557

ANALYSING THE INFLUENCE OF COGNITIVE, AFFECTIVE, CONATIVE AND MOTIVATION ASPECTS ON
TRAIN PASSENGER’S DEVIANT BEHAVIOUR: COMMUTER LINE, INDONESIA
Ahmad Zubair, Chotib

809

5565

IMMEDIATE EFFECTS OF THAI MASSAGE ON GAIT SPEEDS AND BALANCE PARAMETERS
IN ELDERLY
Nutthanun Tatchananusorn, and Wichai Eungpinichpong

815

5570

A COMPARISON STUDY BETWEEN CHEMICAL COAGULATION AND ELECTRO-COAGULATIONPROCESSES FOR THE TREATMENT OF WASTEWATER CONTAINING REACTIVE BLUE DYENidaa AdiL Jasim, Tamara Kawther Hussein

821

5572

INDOOR PLANT SPECIES SURVIVAL UNDER DIFFERENT ENVIRONMENT IN INDOOR VERTICALGARDEN
Sukanya Chaipong

827

5573

THE CONSIDERATIONS FOR URBAN DESIGN REGARDING THE PRESENCE OF ONLINE TAXI BIKE
Heidy Octaviani Rachman, Chotib and Kemas Ridwan Kurniawan

831

5575

SERVICE QUALITY GAP ANALYSIS OF WATER SUPPLY IN URBAN AREAS: WATER SUPPLYCOMPANY, KABUPATEN BOGOR
Armeinita Octavia and Chotib

837

5576

ISOLATION OF HEAVY METAL DEGRADABLE HALOPHILIC BACTERIA FROM SOIL IN SAMUTSAKHON PROVINCE, THAILAND
Jaruwan Chutrtong and Waradoon Chutrtong

847

5579

FACTORS AFFECTING COMMUNITY PERCEPTION AROUND BETAWI CULTURE TOURISM ACTIVITIESSETU BABAKAN JAKARTA SELATAN
Dwinanto and Chotib

852

5591

QUALITY OF VERMICOMPOST BY Pheretima peguana On Different Organic Wastes
Pornpailin Boonna, Nipapun Kungskulniti, Rochana Tangkoonboribun, Naowarut Charoenca

858

5592

5597

5599
5610

EVALUATION OF METHANE AND CARBON DIOXIDE EMISSIONS FROM LIVESTOCK WASTE,COMPOST, AND BIOGAS SLUDGE
Ambar Pertiwiningrum, Margaretha Arnita Wuri, Dina Setiyana, Benito Heru Purwanto, Andang
Widi Harto and Misri Gozan
STUDY ON ELUTION REDUCTION OF HEXAVALENT CHROMIUMFROM RECYCLED BASE COURSE
MATERIAL USING WASTE SYRUP
Keiichiro Shibata, Hidenori Yoshida, Hiroki Yokoyama, Shinichiro Okazaki and Matsumoto
Naomichi
GEOINFORMATICS OF TUBERCULOSIS (TB) DISEASE IN JAKARTA CITY YEAR 2017
Titin Siswantining, NPC Purwandani, MHD Susilowati, and Adi Wibowo
SPATIAL AND TEMPORAL PATTERN OF SOIL CONSERVATION IN MOUNTAIN ECOSYSTEM: CASESTUDY OF PATUHA MOUNTAIN, WEST JAVA – INDONESIA
Satia Nisa Firdhauzi, Astrid Damayanti, Jarot Mulyo Semedi, Muhammad Dimyati

xii

863

868

874
879

5621

SPATIO-TEMPORAL RICE PHENOLOGY USING UAV IN PARAKAN SALAK, SUKABUMI REGENCY,
INDONESIA
Rokhmatuloh, Supriatna, Adi Wibowo and Iqbal Putut Ash Shidiq

885

5622

RICE PRODUCTIVITY ESTIMATION BY SENTINEL-2A IMAGERY IN KARAWANG REGENCY, WEST
JAVA, INDONESIASuprianta, Rokhmatuloh, Adi ibowo and Iqbal Putut Ash Shidiq

889

5625

EFFECTS OF OZONE SPARGING ON GROUNDWATER PHYSICALCHEMICAL PARAMETERS DURING
IN SITU REMEDIATION OF A SITE CONTAMINATED WITH CHLORIDES
Erica Kotani Caram and Maria Eugênia Gimenez Boscov

893

5641

DAIRY WASTEWATER TREATMENT BY VERMI-BIOFILTRATION
Rabee Rustum, Shebin Akbar K and Adebayo J. Adeloye

899

5643

System Dynamic Modelling for Sword and White Pomfret Fish Resources at Depok Coast, Bantul
Regency
Dewi Susiloningtyas, Hengki Tasman, Tuty Handayani and Arti Aulia

904

5651

FRESH PROPERTIES PERFORMANCE OF ALKALINE ACTIVATED PALM OIL PASTE
Aidan N, Nuradila Izzaty H, Muhd Norhasri M.S, Sharifah A

909

5652

ANALYSIS OF THE PERFORMANCE AND ELEMENTAL ANALYSIS ON LIME ACTIVATOR POFA
Nuradila Izzaty H, Aidan N, Muhd Norhasri M.S, Sharifah A

914

5658

PHYSICAL AND CHEMICAL PROPERTIES OF WATER: CASE OF TAAL LAKE, PHILIPPINES
Merlita C. Medallon, Ed.D. & Enrico Garcia

918

5672

DURABILITY STUDY OF MALAYSIA ROCK MASS FOR TUNNELLING CONSTRUCTION
RC Omar, R.Roslan, INZ Baharuddin, Hairin Taha and Vigneswaran V

926

5675

H2 PRODUCTION FROM LACTIC ACID RICH MEDIUM AND CASSAVA STARCH WASTEWATER BY
Klebsiella pneumoniae subsp. Pneumonia
Piyawadee Saraphirom, Napapach Chainamom, Piyarat Namsena

931

5676

OPTIMIZATION OF PARAQUAT DEGRADATION WITH MICROBIAL CONSORTIUM FROMCONTAMINATED SOIL USING STATISTIC METHOD
Mullika Teerakun Alissara Reungsang Monrodee Chaowarat and Piyawadee Saraphirom

937

5683

CRAFTING A THEORETICAL FRAMEWORK ON WASTE MANAGEMENT: A CASE FOR SUSTAINABLE
CITIES
Jennie Lagman-Bautista

943

5689

HUMAN BEHAVIOUR AND WORKPLACE SAFETYOF READY-MADE GARMENT FACTORIES IN DHAKA
DURING FIRE: A CURRENT SCENARIOA S M Fahad Hossain, Ishraq Tasnim Hossain and Prof. Dr. Mehedi Ahmed Ansary

948

5698

ULTRAFINE PARTICLE FILTER DESIGN FOR MOTORCYCLE EMISSION EXHAUST SYSTEM: A HIGH
VOLTAGE ELECTROSTATIC-BASED SYSTEM
Arinto Y. P. Wardoyo, Hari A. Dharmawan, Muhammad Nurhuda, and Arif Budianto

954

5711

EXPERIMENTAL STUDY ON SOIL IMPROVEMENT OF COHESIVE SOIL FOR CONSTRUCTION FIELD
Shoji Kamao

960

5721

ANALYSIS OF HABITAT AREA FOR ENDANGERED SPECIES USING MAXENT BY ROAD
CONSTRUCTION AND HOUSING LAND DEVELOPMENT IN CHIBA, JAPAN
Hideyuki Ito, Koji Hayakawa, Makoto Ooba and Takahiro Fujii

964

xiii

5726

SOLID WASTE GENERATION IN THE PHILIPPINES: A CORRELATIONAL ANALYSIS ON ECONOMIC
AND SOCIAL METRICS
Jennie Lagman-Bautista

970

5742

ANALYSIS ON SPATIAL USE AND LAND USE IN NORTH JAKARTA ADMINISTRATIVE CITY
Galih Jati Utomo, Hafid Setiadi, Rudy P. Tambunan and Komara Djaja

976

5744

THE PATHWAY TO THE ORGANIZATION SUSTAINABILITY THROUGH THE LAND FOOTPRINTMETHOD
Karin Kandananond

986

5748

DESIGN AND ASSESSMENT OF A BATTERY OPERATED ROTARY TYPE LOW COST WEEDER FOR
NON-CHEMICAL UP-LAND CROP MANAGEMENT
Mohammad Ashrafuzzaman Gulandaz, Dr. Md. Israil Hossain, Dr. Md. Ayub Hossain

990

5761

SHEAR STRENGTH AND PERMEABILITY ANALYSIS OF GEOTEXTILE FROM PINEAPPLE LEAVES AND
LUFFA
INZ Baharuddin, Hairin Taha, RC Omar, R.Roslan and S.Nadirah

998

5762

PARTICIPATION IN WASTE MANAGEMENT BY UNDERGRADUATE STUDENTS OF RAJAMANGALAUNIVERSITY OF TECHNOLOGY THANYABURI
Korntouch Kosidphokin

1004

5763

ENVIRONMENTAL MANAGEMENT FOR GREEN UNIVERSITY BASED ON THE UI GREEN METRIC OF
UNIVERSITY SUCCEED
Korntouch Kosidphokin

1008

5764

INVESTIGATING OZONE LEVELS IN MUSCAT AREA, OMAN BY USING ARTIFICIAL NEURALNETWORKS
Mahad Baawain, Hasina Al-Hinai and Abdullah Almamun

1014

5769

STUDY ON MUSRENBANG MECHANISM IN INDONESIA TO PROMOTE SANITATION
Eddy Soedjono , Wahyu Wijaya and Nurina Fitriani

1019

5770

THE IMPACT OF EXPOSURE TO AEROSOL MOSQUITOES REPELLENT RELATED TO FREE RADICALSON THE ORGANS OF MALE RATS
Unggul P. Juswono, Arinto Y. P. Wardoyo, Chomsin S. Widodo, Johan A. E. Noor, and Didik R.
Santoso

1024

5782

VARIATIONS IN WATER QUALITY ALONG ACIDIC RIVERS IN VOLCANIC AREAS OF EASTERN JAPANTakeshi Saito and Naoki Watanabe

1030

5792

WATER FOOTPRINT OF RICE IN MYAUNGMYA TOWNSHIP, MYANMAR
May Myo Han

1035

5797

THE EFFECT OF INSIDE CIRCUMSTANCE OF THE HAZARDOUS WASTE LANDFILL ON THE LEACHING
BEHAVIOR OF HARMFUL HEAVY METALS
Yasumasa Tojo, Taira Ikeda, Takayuki Matsuo and Toshihiko Matsuto

1040

5798

5804

5805

COSTS AND BENEFITS OF USING PARABOLIC GREENHOUSE SOLAR DRYERS FOR DRIED HERBPRODUCTS IN THAILAND
Samatcha Krungkaew, Kanokwan Kingphadung, Suphaphat Kwonpongsagoon, Busarakorn
Mahayothee
AIR POLLUTION CONCENTRATION AND COST FOR THE DIFFERENT ROAD CORRIDORS
LasminiAmbarwati, Amelia K. Indriastuti

MICROBIOLOGICAL AND CHEMICAL PROPERTIES OF THE CHI RIVER, MAHA SARAKHAM PROVICE,THAILAND
Yuwadee Insumran, Jackaphan Sriwongsa, Panuwat Ruenruangrit and Supattra Chinakool

xiv

1045

1051

1057

5807

EFFECTS OF CLIMATE CHANGE ON MILK YIELD AND MILK COMPOSITION IN THAI CROSSBREDHOLSTEIN COWS
Doungnapa Promket, Wootichai Kenchaiwong, and Khanitta Ruangwittayanusorn

1062

5671

STEADY STATE GROUNDWATER FLOW MODEL OF WADI SAMAIL CATCHMENT
Sharifa AL-Hashmi, Luminda Hewawasam, Ahmed Sana and Mahad Baawain

1067

xv

Fifth International Conference on Science, Engineering & Environment,
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

PrefaceOn behalf of the SEE 2019 Organizing Committee, it is our great pleasure to welcome you to the Fifth
International Conference on Science, Engineering & Environment (SEE2019) will be held in Bangkok on Nov.
11-13, 2019, Thailand in conjunction with Suranaree University of Technology, Mie University ResearchCenter for Environmental Load Reduction, The GEOMATE International Society, Useful Plant SpreadSociety, Glorious International, AOI Engineering, 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 2019. 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
Prof. Dr. Suksun Horpibulsuk, Conference Chairman
Dr. Jim Shiau, USQ, Australia (Assistant to Chairman)xvii

Fifth International Conference on Science, Engineering & Environment,
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

Organization
Scientific Committees:
Honorary Chairman: Dr. Sohji Inoue, E/Prof. Mie University, Japan
Dr. Suksun Horpibulsuk, Prof. Suranaree University of Tech., Thailand (Program)
Dr. Zakaria Hossain, Prof. Mie University, Japan (General)
Assistant to Chairman Dr. Jim Shiau, University of Southern Queensland, Australia
Conference Organizing Committee:
Dr. Suksun Horpibulsuk, Prof. Suranaree Uni of Tech (Chair)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 Dad 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. Hj. Ramli Bin Hj. Nazir, A/Prof., UTM, Malaysia
Dr. M.S. Hossain, Prof., International Islamic Univ. Bangladesh
Dr. Md. Ariful Islam, A/Prof. Dhaka University, Bangladesh
Dr. Md. Nurul Amin, Prof. Dhaka University, Bangladesh

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
A/Prof. Mohamed Ramadan, University of Hail, Saudi Arabia
A/Prof. Najam Hasan, Dhofar University, Oman
A/Prof. Nosina Krishna Chaitanya, Jawaharlal Nehru Technological University, India
A/Prof. Nurbek Saparkhojayev, Almaty Management University, Kazakhstan
A/Prof. Pandian Vasant, Universiti Teknologi Petronas, Malaysia
A/Prof. Teodor Lucian Grigorie, University of Craiova, Romania
A/Prof. Zawawi Daud, Universiti Tun Hussein Onn Malaysia
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
A/Prof. Edgar Allan Mendoza, University of the Philippines
A/Prof. Lakhveer Singh, Universiti Malaysia Pahang (UMP) Malaysia, Malaysia
A/Prof. Lidia Sas Paszt, Research Institute of Pomology, Poland
A/Prof. Mahmood Barbooti, University of Yechnology, Iraq
A/Prof. Majid Mirzaei, Universiti Tunku Abdul Rahman, Malaysia
A/Prof. Najeh Lakhoua, University of Carthage, Tunisia
A/Prof. Ryan Joseph Calinao, Lyceum of the Philippines University-Laguna
A/Prof. Sarawut Thepanondh, Mahidol University, Thailand
A/Prof. Yasir Al Hussein, Jerash University, Faculty of Engineering, Jordan
A/Prof. Grigorie Teodor Lucian, University of Craiova, Romania
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
Dr. Cazacu Gabriela, S.C. Geotech Dobrogea, Romania
Dr. Chengen Yang, Intel Corporation, United States
Dr. Dayang Norulfairuz Abang Zaidel, Universiti Teknologi Malaysia
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
Dr. Mohd Hairy Ibrahim, Sultan Idris Education University, Malaysia
Dr. Mostafa Khater, Egypt - El sharqia - Zagazig, Egypt
Dr. Najam Hasan, Dhofar University, Oman
Dr. Namir Alkawaaz, University of Almustansiriyah, Iraq
Dr. Nashrul Fazli Mohd Nasir, Universiti Malaysia Perlis, Malaysia
Dr. NaufaL Mansor Kampus Uniciti Alam, Universiti Malaysia Perlis (UniMAP), Malaysia
Dr. Obed Majeed Ali, Northern Technical University, Iraq
Dr. Piyapong Janmaimool, King Mongkhut' University of Technology, Thailand
Dr. Po-Sheng Chiu, National Cheng Kung University, Taiwan
Dr. Prabu Mohandas, Adhiyamaan College of Engineering, India
Dr. Raman Kumar, D A V Institute of Engineering and Technology, India
Dr. Riccardo Colella, University of Salento, Italy
Dr. Rolando Javellonar, Romblon State University, Philippines
Dr. Shikha Agrawal, Rajeev Gandhi Technical University, India
Dr. Stefania Tomasiello CORISA, University of Salerno, Italy
Dr. Sumiyyah Sabar, Universiti Sains Malaysia, Malaysia
Dr. Suphaphat Kwonpongsagoon, Mahidol University, Thailand
Dr. Wei Hong Tan, Universiti Malaysia Perlis, Malaysia
Dr. Yoshiro Fujii, Shin Kobe Dental Clinic, Japan
Dr. Yuk Feng Huang, Universiti Tunku Abdul Rahman (UTAR), Malaysia
Dr. Zongyan Zhou, Monsh University, Australia
Dr. Purnanand Savoikar, Goa Engineering College, India
Dr. Ahmed Toaha Mobashsher, University of Queensland, Australia
Dr. Chupong Pakpum, Maejo University
Dr. Emanuele Quaranta, Politecnico di Torino, Italy
Dr. Jiangling Yin, Apple Inc., Cupertino, CA, United States
Dr. Khor Shing Fhan, Universiti Malaysia Perlis, Malaysia
Dr. Mario Chauca, Ricardo Palma University, Peru
Dr. Santosh Gaikwad, Model College, Ghansawangi, India
Dr. Tse Guan Tan, Universiti Malaysia Kelantan
Dr. Vikas Panthi, National Institute of Technology, India
Dr. Watoo Phrompittayarat, Naresuan University, ThailandxxDr. Hamidreza Namazi, Nanyang Technological University, Singapore
Dr. Parichat Phumkhachorn, Ubon Ratchathani University, Thailand
Dr. Subhasis Roy, University of Calcutta, India
Conference Correspondence:Prof. Dr. Zakaria Hossain (Director)
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. Jamie Ovia
Engr. Mohamed Mahmoud Ahmed EltaherxxiKeynote Papers

15th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

A CONCRETE WALL ELEMENT TEST TO EVALUATE COMPRESSIVE FRACTURE ENERGY
Tetsuya Ohmura1, Kyouhei Iwasaki1 and Hiroaki Matsufuji1
1
Faculty of Architecture, Tokyo City University, Japan;

ABSTRACT
Concrete walls are significantly effective seismic elements to resist lateral force due to an earthquake, because
they have much stiffness and strength. A building with a number of concrete walls would be generally designed
for just the strength. On the other hand, a building with a few of concrete walls would be designed for not only thestrength but also the ductility. In other words, the ductility of a concrete wall is the key thing considering thesurvey reports of concrete walls damaged by an earthquake. Generally speaking, the ductility of a concrete building
depends on the ductility of the concrete with rebar. According to some previous studies, the fracture energy was
focused to evaluate the ductility. However, their test specimen were cylindrical columns, not to target for a concretewall. In this paper, the ductility of a concrete wall is focused and test the specimen of a concrete wall element. The
fracture energy of a concrete wall element was examined, the thickness of a wall and the amount of their rebar
were evaluated.
Keywords: Concrete wall, Ductility, Element test, Concrete strain
Rots [1] defined the effective band width with integrated point of 4 was two times of root of the element area.
Nishiyama and Watanabe et al. [2] examined therelationship between stress and strain of the axial andtransverse for the concrete cylinder with 135mm ofdiameter in the concrete strength of 25 to 83 N/mm2.
Priestley and Park [3] suggested the model withstrain softening for a concrete cylinder and a cuboid
with enough transverse rebar under one-way cyclicloading.
Higai and Nakamura [4] suggested the compressive fracture energy was 8.8 times of concretes
strength and the compressive fracture zone length of
1,300 divided by the root of the concrete strength
based on the test data of cylinder with no transverse
rebar, concrete strength of 11 to 52 N/mm2 and thediameter of 100 to 150mm and height of 100 to
600mm.
Niwa et al. [5] suggested the equation of the fracture zone length and compressive fracture energy
based on the test data of cylinder with no transverse
rebar, concrete strength of 26 to 48N/mm2 and the diameter of 100mm, the height of 200 to 800mm.
Koshikawa et al. [6] suggested compressive zone
length and compressive fracture energy based on thetest data of cylinder with no transverse rebar, concrete
strength of 29 to 36N/mm2 and diameter of 100 to
200mm, height of 200 to 600mm.
Their specimen shape mentioned above were cylinder and cuboid for making not a wall but a column
concrete model. The fracture energy and fracturezone length of wall in former studies haven’t been referred and they are not obvious.

INTRODUCTION
Lateral strength and ductility significantly dependon the property of the concrete strain softening. It is
well-known that the stress decreasing is controlledeven in the post peak in the confined concrete withrebar. The column well-confined by rebar has great
ductility and hardly collapsed even after a maximum
considered earthquake (MCE). The strength of thegirder well-confined by rebar is not decreased as well.
Those are based on a number of technical reports, andthe amount of the rebar is estimated due to the Japanese code.
The depth of the concrete wall is much larger
than one of the concrete column. Therefore, the concrete strain at the end of the compressive area at thepeak is significantly large, and the compressive area
would be developed at the post peak.
The accurate concrete model considered thestrain softening is needed to estimate the lateralstrength and the ductility of a concrete wall, and theway to estimate the rest of the lateral and axial
strength after MCE is expected.
FE analysis is often used to simulate the lateralstrength, damage and ductility under an earthquake
loading, and to easily have the data that is hard tomeasure at the test. In addition, parametric analyses
could be performed after being verified.
Not to mention, the concrete model is consequence in a FE analysis and sufficient verificationmust be needed for the material property with compressive fracture energy
For example, Drucker Prager fracture criterionand Mohr-Coulomb fracture criterion were wellknown to estimate their maximum compressive stress.
2

SEE - Bangkok, Thailand, Nov.11-13, 2019

Moreover, the confined effect of the transverse rebar in their cylinders might be definitely different
from the one of the vertical and horizontal rebar in awall.
In this paper, several wall element tests were performed for a concrete wall. The concrete strain softening property was examined and the fracture energy
was focused for a wall element with vertical and horizontal rebar.

Specimen
Specimen are shown in Table 1. The number of allof specimen was four. The common factors are concrete material, the width and depth. The parameters
are the wall thickness and the rebar ratio (pw). The
wall thickness is 150 or 180mm. The rebar is locatedsingle or double. pw is 0.24 to 1.11 percent. The diameter of rebar is #3 to #5.
Specimen geometrics are shown in Fig. 1. The
wall consists of the confined area (Focused area), theextra area and stab. The concrete was cast from top.

TEST

Table 1 Specimen#Namet (mm)

1

150-21-024

150

2

180-21-039

f 'c(N/mm2)p w (%)

Rebar

0.24

#3(D10)@200-S

0.39#3(D10)@200-D

0.71#4(D13)@200-D

1.11#5(D16)@200-D

20.7
3

180-21-071

4

180-21-111

180

Note: S and D indicate single and double rebar respectively.

t: Thickness

a-a'

a-a'

b-b'
(a) No.1b-b'(b) No.2 to 4
Fig. 1 Specimen geometrics
Table 2 The material propertyb) Rebara) Concrete
f 'c

Young
modulas(N/mm2)

Strain at f ' c
(%)

Wall

20.7

0.1955

20.9

Stub

43.4

0.1982

29.4

Yield stressTensilestrength(kN/mm2)(N/mm2 )(N/mm2 )#3 (D10)362

0.2123170

495#4 (D13)352

0.1998176

481#5 (D16)351

0.2056171

501(kN/mm2)

3

Young
modulasYield strain
(%)

Rebar

SEE - Bangkok, Thailand, Nov.11-13, 2019

cell and the displacement gage, respectively. The
acrylic column with the strain gages was located at
the center of the specimen. The strain gages were
measured via a data logger as the same strain of theconcrete, because of the ruggedness shape of theacrylic column.

Material property
The material property of concrete and rebar isshown in Table 2. The compressive strength of thecylinder with 100mm of the diameter and 200mm ofthe height (f ’c) was 20.7 N/mm2 for the wall and
43.4N/mm2 for the stub.

TEST RESULTS

Loading

Load and displacement

Repeated compressive load was applied via therigid body of the top and bottom of the specimen by
2,000kN amsler testing machine.
Loading plan is shown in Fig. 2. The repeatedcompressive load was unloaded at the one-third andtwo-third of the f ’c on the material test. Next, it was
unloaded at every 10% decreased load after the maximum load.

The enveloped curve of the relationship between
the compressive load and the displacement are shownin Fig. 4. The compressive displacement (δ) of thespecimen was defined as the two time of the displacement at the center without the elastic displacement of
the rigid body.
The comparison of the enveloped curve between
No.1 and 2 are shown in Fig. 4(a). The displacement
at the maximum load (Pmax) of No.1 with 150mm
thickness and single rebar was larger than one of No.2
with 180mm thickness and double rebar.
For No.1, the displacement of 2.1mm was meas-

Measurement
The measurement plan is shown in Fig. 3. The
compressive load (P) and the vertical displacement at
the center of the specimen were measured by the load

σ

3000

0.9

2700

0.8
0.7
0.6
0.5
0.4

2400

2100

1800

1500

1200

𝜹
𝟐

0.3

900

0.2×

600

300

0

0

0

350

700

1050

1400

1750

2100

2450

2800

3150

Displacement

Fig. 2 Loading plan

Fig. 3 The measurement(1.0, 924) No.2 180-21-039

・・ (2.1, 833) No.1 150-21-024

1000

Load(kN)

Load(kN)

1000(1.0, 924) No.2 180-21-039(δ, Pmax) Specimen name

500

・

・
・
・

(1.7, 965) No.3 180-21-071(0.7, 844) No.4 180-21-111(δ, Pmax) Specimen name500

・

: Pmax: Pmax

0

0
0

5

10

15

0

20

5

10

Disp.(mm)Disp.(mm)Disp.(mm)(a) No.1, 2(b) No.2 to 4

Disp.(mm)Fig. 4 The enveloped curve of the relationship between the compressive load and the displacement
4

15

20

SEE - Bangkok, Thailand, Nov.11-13, 2019ured at the Pmax of 833kN and the crack width developed and the eccentricity of damage was observed at
the displacement of 10.7 and load of 286kN, and then
the test was stopped.
For No.2, the displacement of 1.0mm was measured at the Pmax of 924kN and the significant damage
was observed with 82 % of the decreased load, andthen the test was stopped. The eccentricity of damage
as well as No.1 was not observed and stable comparedwith No.1.
The enveloped curves of No2 to 4 are shown in
Fig. 4(b). Their wall thickness was 180mm with double rebar of the pw of 0.39 to 1.11%.
For No.3 and 4, the displacement of 1.7 and 0.7mm at the Pmax of 965 and 844kN were observed, respectively. The eccentricity of damage was not observed as well as No.2.
The enveloped curve of the load of the concrete
resisted (cP) and δ is shown in Fig. 5. cP was definedas the P without the load of rebar resisted (sP). And
then the relative load was defined as cP divided bycPmax.
The strain of the vertical and horizontal rebar
showed approximately yield at around cPmax in all
specimens.
The displacement at the yield was defined as theminimum displacement at the cPmax or 0.01 time of theelastic stiffness.
The same tendency was shown in Fig. 4 and 5, andthe concrete confined effect was not observed even in
the specimen with the rebar ratio of 0.71%.
Damage and Cracking
The final crack behavior was shown in Fig. 6. For
all specimen, about 0.2mm of the crack width was observed before Pmax, the crack was developed and thecrack width was increased following increase of thedisplacement.
Crack was hardly observed in the extra area andstub.
For No.1 with the wall thickness 150mm and single rebar, the crack width surrounded by dashed ellipse shown in Fig. 6(a) was significantly developed
and the eccentricity of the rebar strain and crack damage were observed, then the fragile behavior was
shown.
For No.2 to 4 with the wall thickness 180mm anddouble rebar, the difference of the crack behavior was
not observed independent of the rebar ratio.
Concrete Strain Distribution(1.0, 1.0) No.2 180-21-039(0.7, 1.0) No.4 180-21-111(2.1, 1.0) No.1 150-21-024

1.0
cP/cPmax

cP/cPmax

1.0(δy, cP/cPmax) Specimen name

0.5
: δy

(1. 0,1.0) No.2 180-21-039(1.7, 1.0) No.3 180-21-071(δy, cP/cPmax) Specimen name

0.5

: δy

0.0

0.0
0

5

10
Disp.(mm)

15

0

20

5

10

15

20

Disp. (mm)(a) No.1, 2(b) No.2 to 4

Fig. 5 The enveloped curve of the relationship between the compressive relative load and the displacement
Significant damage
C1
C2
C3
C4
C5
C6

(a) No.1(b) No.2(c) No.3

Note: C1 to C6 indicate the gauge location.
Fig. 6 The final crack behavior
5(d) No.4

SEE - Bangkok, Thailand, Nov.11-13, 2019

The concrete strain distribution was shown in Fig.
7. The strain gages location number of C1 to C6 wereindicated the location in Fig. 6(b). For all specimen,
it was assessed that up to 2 % of the concrete strain

was appropriate. The amount of over 2% of the stain
was estimated as 2% over.
The concrete strain at the center of the wall was
200

Gauge location

×𝛅𝒚
0.3𝑷𝒎𝒂𝒙

C1

𝑷𝒎𝒂𝒙
2.2

Gauge Location

C4

160

C5

0.6𝑷𝒎𝒂𝒙

4.5~
~

4.5

120

8.3~

80

0.6Pmax
Pmax

1.9.

40 0.7𝑷𝒎𝒂𝒙

0.9Pmax

2.8~

0.8Pmax

2.3.

00.7Pmax

2.8~

𝑷𝒎𝒂𝒙

1.6 1

2

Strain(%)

80

40

0.6Pmax

2.3~

2.8~

0

0
0.0

0.5

1.0
1.5
Strain (%)

0.0

2.0

0.5

(a) No.1

×𝛅𝒚

4.7~8.8

200
3.2

4.9~
0.6𝑷𝒎𝒂𝒙
80

1.9
2.4~

120

3.2~4.9

40

1.7

3.9~
3.9

2.4

120

𝑷𝒎𝒂𝒙

160

2.5

Gauge Location

𝑷𝒎𝒂𝒙

160

2.0

0.4𝑷𝒎𝒂𝒙

1.9~3.9

200

1.0
1.5
Strain (%)(b) No.2×𝛅𝒚

0.3𝑷𝒎𝒂𝒙

Gauge Location

0.3Pmax

80

120 0

40

C6

2.3~3.4

160

Gauge Location

C2

C3

8.3~

5.9

×𝛅𝒚

0.3𝑷𝒎𝒂𝒙

120
200

3.2

200

160

6.6~
4.7

0.7𝑷𝒎𝒂𝒙

6.6~
6.6

80
8.8
40

0

0
0.0

0.5

1.0

1.5

0.0

2.0

0.5

1.0
1.5
Strain (%)

Strain (%)(c) No.3

2.0(d) No.4

Note: ×→ indicates 2% or more.

No.2 180-21-039

No.3 180-21-071
No.4 180-21-111

No.2 180-21-039

t=150
Gfc (N/mm)

No.1 150-21-024

2
cσ (N/mm )2cσ (N/mm )Fig. 7 The concrete strain distribution

t=180

200
100
0
0.0

Disp.(mm)Disp.(mm)(a) No.1，2(b) No.2 to 4

Fig. 8 The envelopment curve between the stress and the displacement
6

0.4

0.8
pw (%)

1.2

Fig. 9 The relationship between Gfc,
wall thickness, and pw

SEE - Bangkok, Thailand, Nov.11-13, 2019

larger than one of the top and bottom due to the concrete confined effect by rebar.

Table 3Compressive Fracture Zone Length
As mention above, the eccentricity of the concrete
strain distribution was not shown along the wallheight due to concrete confined effect by the wall rebar. In addition, the all concrete strain in all specimens was the strain at the f ’c or more at the Pmax,
therefore the compressive fracture zone length in thispaper was defined as 200mm.

#

P max
(kN)

c P max(kN)δ atc P max
(mm)

δy
(mm)

(cm2 )

eb p
(mm)

No.1

833

807

2.1

1.2

389

260

No.2

924

898

1.0

433

241

No.3

965

889

1.7

429

238

No.4

844

747

361

200

Note: Pmax
c PmaxδδyA'
ebp

Compressive Fracture Energy

The test result

:
:
:
:
:
:

0.7

0.6

A'

Maximum load
Maximum load of concrete
Displacement
Displacement at Minimum (Pmax or 0.01·K0)
c Pmax divided by f 'c
A' divided by thickness

strain and crack damage were observed, then the fragile behavior was shown. For specimen with the wall
thickness 180mm and double rebar, the difference ofthe crack behavior was not observed independent of
the rebar ratio.
2) The concrete strain at the center of the wall waslarger than one of the top and bottom due to the concrete confined effect by rebar.
3) For all test specimens the compressive fracturezone length was defined as 200mm.
4) For the specimen with the pw of 0.71% more in
No.4, Gfc was slightly increased, because the concrete
strain was gradually increased.
5) ebp was decreased following increasing of pw.

The envelopment curve between the concrete
stress and the displacement is shown in Fig. 8. The
concrete stress was the cP divided by the wall thickness and 250mm. The compressive fracture energy(Gfc) [6] was estimated as the area.
The relationship between Gfc, wall thickness, andpw is shown in Fig. 9.
The displacement for Gfc (δconf) was calculated as
the displacement of the focused area i.e. confined area
as below.
ℎ𝑐𝑜𝑛𝑓
𝛿𝑐𝑜𝑛𝑓 =
∙𝛿ℎWhere h is the wall height 200mm, hconf is focusedarea i.e. confined area 200mm.
For the specimen with the wall thickness of
180mm and double rebar in No.2 to 4, Gfc was increased following increasing of the pw and the confined effect.
However, for the specimen with the pw of 0.71%
more in No.4, Gfc was slightly increased, because theconcrete strain was gradually increased.
For the specimen with the wall thickness of
150mm and single rebar in No.1, the Gfc of No.1 waslargest. It should be examined in our future study.

REFERENCES[1] ROTS, J. G.: Computational Modeling of Concrete Fracture, PhD thesis, Delft University of Technology, 1988.
[2] Naoki Takamori, Benny Benni Assa, Minehiro
Nishiyama, Fumio Watanabe : Confined Stress concrete - Strain Relationship formulation Fundamental Study, Proceedings of the Japan Concrete Institute, Vol.18, No.3, pp.395-400, 1996.
[3] J. B. Mander, M. J. N. Priestley, R. Park, Fellow,
ASCE : Theoretical Stress-strain Model for Confined Concrete, J. Struct. Eng, Vol.114, Issue.8, pp
1804-1826, Sep.1998.
[4] Hikaru Nakamura, Takeshi Higai : Compressive
Fracture Energy and Fracture Zone Length of Concrete, JCI-C51E Seminor on Post-Peak Behavior of
RC Structures Subjected to Seismic Loads, Vol.2,
pp.259-272, 1999.10.
[5] Ken Watanabe, Junichiro Niwa, Hiroshi Yokota,
Mitsuyasu Iwanami : Formulation of Stress-strain
Relationship of Concrete Considering The Localized Compressive Failure Zone, Journal of JSCE,
Vol.58, No.725, pp 197-211, 2003.2.
[6] Shinya Muramatsu, Koshikawa Takeaki, Takanori Saito, Takuya Hasegawa : Quantitative Evaluation of Strain Softening Characteristics of Concrete Subjected to Uniaxial Compression, Architectural Institute of Japan Hokkaido Branch research report, No.83, pp.81-84, 2010.

Equivalent Compressive Fracture Zone Width
The test result is shown in Table 3. The equivalent
compressive fracture zone width (ebp) was defined as
Pmax divided by the wall thickness and f ’c.
cP was decreased following increasing of pw, because the sP was increased.
In other word, ebp was decreased following increasing of pw.
CONCLUSION
Basic concrete walls with rebar test was performed applying compressive stress to estimate theircompressive fracture energy for a concrete wall element model with rebar.
We reached several conclusions as below.
1) For the specimen with the wall thickness of
150mm and single rebar, the eccentricity of the rebar
75th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

LANDSLIDES: BEHAVIOR AND MITIGATION APPROACH
1

2

Avirut Chinkulkijniwat , Somjai Yubonchit
1Suranaree University of Technology, Thailand
2
Rajamangala University of Technology Isan, Thailand
ABSTRACT
Assessment of rainfall-induced shallow slope failures is very important to reduce damages of infrastructuresand lives of people living close to hazardous areas. Understanding the hydrological and physical responses ofshallow slopes, subject to rainfall events is vital for the efficiency of a warning system setup. A series ofexperiments were undertaken to evaluate the hydrological responses of shallow slopes of varying steepness andwhen subjected to varying intensities, periods, and inter- storm periods of rainfall. The hydrological and physicalresponses were characterized to infiltration and saturation phases. During the infiltration phase, the maximum
magnitude of water content was found behind the wetting front, termed as the water content behind the wetting
front (w). For a certain soil type, the magnitude of wb was found to be dependent on the magnitude of rainfall
intensity, regardless of the slope gradient and initial water content. This knowledge was further extended tocharacterize the stability of shallow landslides. Numerical experiments were also conducted to perform parametricstudy on the most common used tool for land sliding mitigation: the rainfall intensity-duration thresholds (IDthreshold). It was found that the slope angle and antecedent rainfall play role on instability of the shallow slope.
They control the initial stability of slope, which results in the different linear relationship of ID thresholds. In
addition, the slope angle might accelerate the rate of rain water infiltration, and hence it reflects the slope of the
ID thresholds.
Keywords: Rainfall-induced landslides; Physically-based warning system; ID thresholds; Rainfall infiltration
triggering the initiation of rainfall-induced
landslides, in which it has been empiricallyrecognized as the cumulative rainfall of 100-300 mm
in a day (the Department of Mineral Resources,
2004). The real-time rainfall data of 50-65%, 6580%, and >80% of the critical rainfall are consideredas immunity, caution and evacuation levels of thedisaster risk, respectively.
The advantage of using critical rainfall thresholds
as a part of early warning is its ease for fast
assessment of rainfall-induced landslides. However,
the rainfall thresholds have been empiricallyobtained by analyzing historical data of thelandslides. Several factors such as soil’s hydraulicproperties (Pradel and Raad, 1993; Rahimi et al.,2010; Ma et al., 2011; Li et al., 2013), slope
geometries (Rahardjo et al., 2007; Cho, 2009; Ali etal., 2014a) and antecedent rainfall conditions(Rahardjo et al., 2001; Rahimi et al., 2011; Cuomo
and Della Sala, 2013) that affect hydro-mechanicalinteractions and hence landslide characteristics are
neglected. Previous literatures also reveal that other
instrumentations (i.e., moisture sensor, tensiometors
and inclinometer) can be effectively used in warning
system (e.g., Tohari et al., 2007; Gallage andUchimura, 2010; Greco et al. 2010), in which
warning levels can be directly interpreted via realtime responses from those devices. Nevertheless,prior to install those devices, a suitable location formonitoring of rainfall-induced landslides needs to be
examined.

INTRODUCTION
Rainfall-induced shallow landslides frequently
result in natural disasters in many countries. One of
the worst natural disasters in Thailand due to failureof slope was in 1988. Extremely rainfall in thesouthern part of Thailand in 1988 resulted inwidespread slope failures and caused more than
240 deaths, as well as the destruction of 1560
bridges and 5694 km of roads (Oh et al., 2008).
Another great tragedy in Thailand was due to a slope
failure on 10 August 2001 in Phetchabun province
when a rainfall intensity of 100 mm/day induced
hundreds of slope failure and sequential mudflows
resulting in 136 deaths as well as economic damagesof more than 15 million USD (Yumuang, 2006).
An early warning system represents effective tool
widely used to manage rainfall-induced disasters,
including landslides, floods, and debris flows(Brand et al., 1984; Keefer et al., 1987; Wilson et al.,
1993; Sirangelo and Braca, 2004). In Thailand,
1,052 early warning stations has been establishedby the Department of Water Resources since in
2004, which covers all 3,207 hazardous villages inThailand. Monitoring devices including automatic
thermometer, rain gauge and soil moisture sensor
have been installed at warning stations to collectreal-time temperature, rainfall and soil water content.
The real-time rainfall data are typically evaluatedthrough the risk thresholds to interpret the disasterrisk. The risk thresholds are usually critical rainfall
8SEE - Bangkok, Thailand, Nov.11-13, 2019

This paper presents recent research regarding toboth empirical and physical landslides waningsystems. Efforts had been devoted to examine thefactors influencing landslide characteristics and thecritical rainfall thresholds which will provide
comprehensive understanding of rainfall-induced
shallow landslide mechanisms and subsequently aguideline for building up powerful warning system
based on monitoring device installations.

Moisture Responses During Rainfall Infiltration
Physical slope model and experimental program

To investigate moisture responses during rainfall,a local sandy soil was used in this study to prepare thehomogeneous soil slope. The soil was classified as
poorly-graded sand (SP) according to Unified Soil
Classification System. A schematic diagram of thephysical model is shown in Fig. 1. The model consistsof four components including the rainfall simulator,
the experiment box, the box supports, and the chain
pulley system. The box supports are pin and roller
type supports such that the experiment box can beraised one side to a prescribed inclined angle by thechain pulley.
Fig. 2 shows details of the experiment box. The
dimensions of this box are 1550 mm length, 1000 mm
high, and 200 mm width. The sides and bottom baseof the box were made from impervious acrylic platesof 15 mm thick. Five of 5 mm diameter holes werevertically drilled at mid of the side boundary to insert
the moisture sensor probes (Decagon 5TE, Decagon
Devices Inc. (2007-2010)). Three of 9 mm diameterholes were drilled at bottom of the experiment box at
distances of 375 mm (downslope), 750 mm (middle
slope), and 1125 mm (upslope). These holes wereused to insert the piezometers. To reduce entrapped
air that might be affecting to measurement of thevolumetric moisture content (w), three other holes
were drilled nearby the piezometer holes to install the
opening valves. At downslope, permeable porous
concrete overlaid by geotextile was placed to allow
free water outflow at nearly saturated state, and toprevent the clogged soil in porous concrete.

PHYSICAL-BASED WARNING APPROACH
Previous studies (Tohari et al., 2007; Gallage andUchimura, 2010; Greco et al., 2010; Eichenberger etal., 2013) revealed that the physically-based
prediction can be used to build up an early warning
system, interestingly. In the method, the warninglevels are evaluated via the real-time hydraulicresponses read from a set of monitoring devices. The
common monitoring devices are moisture sensors,piezometers and tensiometers. Location of
instrumentation is vital for early warning systems tobe effective. Few attempts have been made to date on
the study of suitable instrumentation locations for
effective early warning systems. This part of researchis systematically divided into two parts: 1) laboratory
experiments and 2) stability analysis of the slope. A
physical slope model was constructed to evaluate thehydrological responses on various steepness of soil
slopes when subject to various rainfall intensities andperiods. Subsequently, a series of infinite slope
analysis was conducted to develop a fundamental
understanding of the characteristics of failure planes
in shallow slopes when subjected to varying rainfall
conditions.

Fig. 1. Schematic diagram of the physical slope model
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Fig.2 Details of the experiment box (a) side view (b) top viewThree set of laboratory experiments wereconducted as shown in Table 1. In total, 13 tests werecarried out. Each test, rainfall was continuously
applied until the arrival of the steady state which isindicated by the rate of water outflow at slope toe
equals to the rainfall intensity. The magnitudes ofrainfall intensity assigned to each test were lower than
the soil’ saturated permeability (= 1.54x10-4 m/sec =554.4 mm/hr). Monitored data were recorded during
the test until the steady state (end of each test) was
achieved. s k
The variation of rainfall intensity was conductedin test series I. The rainfall intensities of 45, 70, 100,
130, 160 mm/hr were applied to the model at slope
angle (β) of 20˚. The variation of slope angle wasconducted in the test series II. The slope angles (β) of
5˚, 10˚, 20˚ and 30˚ were assigned to the model
subjected to rainfall intensity of 100 mm/hr. Theinter-storm rainfall period was assigned to the modelin the test series III. This test is to study the effect ofantecedent water content from the previous rainfall,
which might affect the hydrological responses. The
two rainfall events of 100 mm/hr each were applied
to the model at slope angle (β) of 20˚ with the interstorm period of 4, 7 and 14 days

Tested results

The volumetric water contents (w) read from themoisture sensors B1, B2, B3, B4, and B5, located at
a vertical distance from the impervious surface of 100
mm, 200 mm, 300 mm, 400 mm, and 500 mm,
respectively (see Fig. 2a).
Fig. 3, 4 and 5 present developments of w profilein the soil subjected to rainfall experiment series I, II,
and III, respectively. The developments of w profile
of all experimental series look similar to10

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Table 1 Experimental programs conducted in this study
Series rainfall
intensity, i(mm/hr)

I

II

III

(deg)Inter-storm
rainfallperiodtb (day)

45
70
100
130
160

20

-

100

5
10
20
30

-

20

4
7
14
-

100

Slope angle

Rainfall sequenceeach other. The general characters of w profile
development were determined as follows:
1) The development of w profile begins since therainwater starts infiltrating into the soil. During the
rainwater infiltration process termed as theinfiltration phase, the volumetric water content
increases from its initial value (wi) to a volumetricmoisture content of wb, named the volumetric watercontent behind the wetting front. The wb presents a
possible maximum magnitude w of taking place
during the infiltration phase.
2) After reaching the impervious boundary of thewetting front, an upward movement of water tablebegins. This process is called saturation phase. At thisphase, w increases from the wb to the magnitude ofw that closes to sat.
The characters of w development summarized
above are in accordance with those reported byprevious studies (Tohari et al., 2007; Huang et al.,2008; Huang and Yuin, 2010; Sharma and Nakagawa,
2010; Phi et al., 2013).
Fig. 3(a) – (e) present the variation of volumetricwater content in shallow slope of the experimental
series I for rainfall intensity of 45, 70, 100, 130 and
160 mm/hr, respectively. The results show that the w
profile development in the infiltration phase clearly
depends on the magnitudes of rainfall intensity. The
higher rainfall intensity results in the faster move ofwetting front, and hence the deeper development of a
wetting front. In addition, the results show that themagnitude of wb increases with the magnitude of
rainfall intensity. These findings are similar to thosereported by Lee et al., 2011.
The rainfall intensity also affects the w profile
development in the saturation phase. In the plots, therise of water table is indicated at the magnitude wherew reaches sat. The level of water table is indicatedby the point where the w profile in the saturation
phase deviates from sat. It is found that the greaterrainfall intensity causes the faster rise of water table.
In addition, the final level of water table at the steadystate also depend on the rainfall intensity and thegreater rainfall intensity yields the higher level ofwater table at steady state.

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Fig. 3. Volumetric water content profiles for the test series I: (a) i/ks = 0.081, (b) i/ks =0.126, (c) i/ks = 0.180, (d) i/ks = 0.234, and i/ks = 0.289

12SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 4. Volumetric water content profiles for the test series II: (a)  = 5˚, (b)  = 10˚, (c)  = 20˚, and(d)  = 30˚Fig. 5 Volumetric water content profiles for the test series III: (a) tb =4 days, (b) tb = 7 days, (c) tb = 14 days and (d)continuous storm tb =0 days
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magnitudes of stability index (tan'/ tan ) for thisdemonstrated case. The vertical distance measured
from the slope surface to the failure plane is called
the critical depth ( Z wf ), while the thickness of theshallow slope is denoted as Z t . For a certain soil, thecritical depth decreases with an increasing rainfall
intensity. In the other words, the shallower depth of
failure plane is encountered in the slope subjected to
the greater magnitude of rainfall intensity.
Fig. 6 shows that the depth of failure plane isvery sensitive to the change of rainfall intensity forthe stability index ranged from 0.9 to 1.0. The depthof failure plane can occur at any depth dependingon the magnitudes of the infiltration and stability
indices. However, the depth of failure plane is inert
to the change of rainfall intensity for the stability
index of lower than 0.9. In addition, in this case thedepth of failure plane might take place at very
shallow depth ( Zwf / Zt< 0.2).

Fig. 4(a)-(d) present variation of volumetric watercontent in shallow slope of the experimental series II
for the slope angle ( ) of 5˚, 10˚, 20˚ and 30˚,
respectively. The w development and the magnitudeof wb in the infiltration phase are not dependent on
the slope angle. In other words, within the  range
conducted in this study, the magnitude of slope angle
 do not affect the hydrological response. It is dueto the vertical seepage flow plays important role tothe hydrological responses in isotropic shallow slope
soil during rainwater infiltration process. Thisfinding is similar to thatfound by Lee et al., 2011 who conducted two setsof laboratory seepage flow tests: one-dimensionalsoil column and 18o tilted slope model. The slope
angle, however, affects the w profile developmentin the saturation phase. Figures 4 (a)-(d) clearly showthat the rise of water table depends on the slope angle,
the faster water table development is found at mild
slope angle. This results may naturally be attributed
to a dominant role of lateral flow along theimpervious layer at the soil saturated state. The
higher slope angle provides the higher hydraulicgradient and the faster lateral flow, and thus the lessaccumulated rain water at the impervious boundary.
Fig. 5 presents variation of volumetric watercontent in shallow slope of the experimental series
III for a continuous storm, and for the different
inter-storm period (tb ) of 4, 7, 14 days, respectively.
The w development in the infiltration phase depends
on the magnitude of tb as it affects the magnitude of
an initial w of the subsequent rainfall (wi); theshorter tb results in the higher magnitude of wi. The
speed of the wetting front advancement is more
rapid for the shorter tb. Although the variation oftb significantly affects the wetting front development,
it does not affect the magnitude of the volumetricmoisture content behind the wetting front ( wb). In
the other word, the magnitude of wb is independentof the magnitude of tb .

Fig.6. Critical depth chart
Categorization of the Slope Failures
Once the critical depth chart is available, thethreshold value can be assigned to the slope based on
personal judgment. The threshold is the stability
number at which the critical depth is slightly
sensitive to rainfall intensity, i.e. the thresholdvalue used in the illustrated case is 0.9 which isthe stability index at which an infiltration index (i/k)
to a normalized critical depth (Z wf /Zt ) ratio is no
greater than 0.2.
Based on the relative depth of the failure plane,
possible modes of slope failure are: 1) along theimpervious layer mode, 2) shallow depth mode
which occurs very close to the slope surface, and 3)
transitional mode which occurs at any depth fromthe impervious layer to the slope surface. These
modes are governed by the stability index (tan'/tan) as depicted in Fig. 7 and summarized below:
1. For the mild slope (tan'/tan  1.0), the failuremode is the along the impervious layer mode

Analysis of Failure Plane
Location where failure plane takes place is vital forassessment of the slope failure. In this study, an
infinite slope analysis was used to assess the failure
plane based on the moisture responses characterizedby physical slope model test. For the shallow slope
failure taken place during the saturation phase, thefailure plane always takes place at the interfacial
between the soil and the impervious layers. However,the location of failure plane taken place during theinfiltration phase might vary from the depth to depth
depending on many factors. Fig. 6 presents therelationships between the normalized critical depth(Zwf/ Zt) and the infiltration index (i/k s ) for various
14

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which is triggered by an increment of positive porewater pressure taking place during the saturation
phase.
2. For the steep slope (tan'/ tan  1.0), the failure
is triggered by the loss of matric suction during theinfiltration phase. With the assistance of thecritical depth chart, the failure mode ischaracterized according to the magnitude oftan'/tan  ratio.

thresholds developed from the above mentioned
literatures. From these thresholds, a mathematic
expression for ID thresholds can be expressed as:
I f a cT rfm(1)

where a, c and m are the ID thresholds parameterswhich represent the curvature, intercept and gradientof ID thresholds, respectively.

If the slope’s stability number (tan 'tan ) is
lower than the threshold (for the illustrated
case, the tan'/tan ratio is lower than 0.9),
the failure mode is the shallow depth mode
which occurs closed to the slope surface.
 If the slope angle is within a small range
between the soil frictional angle and an angleof slightly greater than the soil frictional angle(for the illustrated case shown in the study, thetan'/tan ratio ranges from 0.90 to 1.0), thefailure mode is the transitional model. The
depth of the failure plane can occur at any depth
in the soil layer depending on the magnitude of
infiltration index. A greater tan'/tan ratio
results in a more sensitive depth of failure
plane relative to the infiltration index.
According to the failure modes shown in Fig.
7, instrumentations on a specific slope can becharacterized by its stability index. In the mild slope(tan'/tan  1.0), slope failure will be triggered
during the saturation phase. The end of infiltration
phase, which is notified by the arrival of wb at nearinterface layer, may be set as the first warning point.
For the very steep slope (tan'/tan ≤ threshold), themode of failure is a shallow depth slope failure. Timeto reach the failure might occur shortly after a rainfall
event. Warning systems might not be suitable for thistype of slope. The area and the vicinities should beclassified as a sensitive area, in which humanactivities are prohibited. For an intermediate steep
slope (1.0>tan'/tan> threshold), the failure plane
can occur at various depths depending on thestability and infiltration indices. Intensive
instrumentation to monitor the rainfall intensity andthe development of wetting front must be assigned
to this area.
Fig. 7 Modes of failure in shallow slope classified
by the stability number
Numerical Modelling
Slope geometry, boundary conditions and fixity
used in this study are shown in Figure 9. The slopemodel is divided into two layers. The bedrock isoverlaid by a uniform shallow soil layer withthickness of 3 meters(d = 3 m.), which gives the ratioof slope length (L) to soil depth (d) of about 31, 29
and 26 for the slope angle of 20˚, 30˚ and 40˚,
respectively. These L/d ratios are greater than 20
which is far enough to avoid boundary effects in
calculation of safety factor (Griffiths et al., 2011;
Tiwari et al., 2014).

RAINFALL
INTENSITY-DURATIONTHRESHOLDS (ID THRESHOLDS)
The rainfall intensity-duration thresholds for
initiation of slope failure (ID thresholds) which is arelationship between the rainfall intensity (I f) andrainfall period (Trf ) to trigger slope failure is widelyused to simply assess the stability of shallow slope(Caine, 1980; Calcaterra et al., 2000; Corominas,
2000; Crosta and Frattini, 2001; Aleotti, 2004;
Cannon and Gartner, 2005; Chien et al., 2005;
Guzzetti et al., 2007). Fig. 8 shows a set of ID

Fig. 8 ID thresholds for initiation of shallow slope
failures proposed by previous researchers
Standard fixities were prescribed to allow only
vertical movement along the boundary sides, while
15

SEE - Bangkok, Thailand, Nov.11-13, 2019

lateral and vertical movements were fixed at bottom
boundary. 15-node triangular finite element mesh is
assigned in the problem. The finer elements weregenerated at the soil layer, and the finest mesh was
generated along the soil slope where the failure tends
to occur.
A prescribed flux, which relates to the desired
intensity of rainfall, was assigned along the slope
surface BC. Along the slope surface BC, a range ofpore water pressure between -0.05 m and 0.05 m wasprescribed. By this maximum pore water pressureof 0.05 m, the ponding water due to the excess of
rainfall intensity over the infiltration capacity at soil
saturation state could be developed up to 5 cm. overthe slope surface. While the minimum pore waterpressure of -0.05 m was used to represent a depth ofnegative flux due to evaporation. The boundaries AB
and CD were assigned as no flux boundaries, while
the boundaries AHG, DEF and GF were prescribed
as impervious boundaries. The initial conditions
were prescribed by variation of initial pore waterpressure (uwi) ranges from -50 kPa to -80 kPa fromsoil-bedrock interface to soil surface to represent
ground conditions prior to rainfall season. The
volumetric water content at field capacity ( fc ) andthe residual water content ( res ) were used as
references to prescribe the range of  i , and hence
uwi. The fc is known as the content of water, on amass or volume basis, remaining in a soil 2 or 3 days
after having been wetted with water and after freedrainage is negligible (Soil Science Glossary Terms
Committee, 2008; Meyer and Gee, 1999). It
corresponds to the pore water pressure of -34 kPa(Dingman, 2002) for any soil type. If no additionwater added into the soil for 2-3 days after rainfall,
the water content might further decrease due toevaporation and plant root uptake. As such, a rangeof  i might possibly be between fc and res .
According to the soil water characteristic assigned
to the model the variation of pore water pressure
range from -80 kPa to -50 kPa is presented by thevariation of volumetric water content of 20% to 22%
as shown in Fig. 9.
Table 2 summarizes the material properties
categorized into three categories; strengthparameters, hydraulic related parameters, anddeformation parameters. Mohr-Coulomb model wasused to explain the mechanical behavior of soil andbedrock layers. Van Genuchten and van GenuchtenMualem models were used to explain the hydraulicbehavior of the soil layer, while the bedrock layer
was assumed as an impermeable non-porous
material.

Three series called series I, series II and series III
were conducted in this study to evaluate stability andtime to failures of the shallow slope under various
conditions of the influence factors, including rainfall
intensity; slope angle; and antecedent rainfall. As
shown in Table 3, the numerical experiment includes
156 cases of the simulation run. The simulations
include 78 cases of rainfall period of 24 hours and78 cases of continuous rainfall until the arrival of
slope failure.

Fig.9 Slope geometry and boundary conditions
For series I, 21 cases of continuous rainfall until
the arrival of slope failure were conducted. For eachsoil type, a constant rainfall intensity was assigned
in a range from 0.36 to 360 mm/hr depending on thesaturated permeability of each soil type. In addition,
an extreme rainfall condition (EXT) is assigned toevery soil types. This condition may occur once
the rainfall intensity is much higher than thedrainage capacity of soil at saturation ( i ksat ) andthe infiltration excess might exist since the start of
rainfall. In this study, the extreme rainfall conditionis assumed to generate a ponding rain water heightof 5 cm for a whole period of the simulation. In
PLAXIS, this condition can be simulated by aprescribed maximum pressure head ( max ) of 5 cm.
The effect of slope angle on the stability andtime to failure were evaluated in series II. 39 casesof simulation run were conducted by varying theslope angle from 20° to 40°. Three types of soil withthree or four rainfall intensities were assigned to eachslope angle in this series.
Finally, 18 cases of simulation run wereconducted in series III to evaluate the effect ofantecedent rainfall. The antecedent rainfall imitates
the periodical rainfall in real field. The previous
rainfall affects the initial conditions of the soil
subjected to the sequential rainfall, and hence theinitial stability of the slope. The simulation started
with an antecedence rainfall of certain rainfall
intensity for 24 hours. Subsequently, the rainfall
was terminated for a certain period (antecedentcondition) prior to an arrival of another rainfall event.
In series III, two antecedent conditions of rainfall of
48 and 168 hours (2 days and 7 days) were prescribedto the simulations.

Experimental Program

16

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Table 2 Soil parameters required for Mohr-Coulomb modelParameter

SymbolSoil layer

Bedrock layer

Unit

Model

Mohr-Coulomb

Mohr-Coulomb

-

Type

Undrained A

Non-porous-

Cohesion

6.74

25a*

kPa

Friction angle

33.62

50a*

deg

Van Genuchten--

Material models
Mechanical modelType of material behavior

Hydraulic model

Model
-

A

B

C

-

-

1x10-6

1x10-5

1x10-4

-

m/sec

1.564

-

-

0.162

-

kPa-1

50000

100000

kPa

0.33

0.2

-

Dry unit weight

17.36

23a*

kN/m

Total unit weight

17.36

23a*

3

Soil type
Saturated permeability of soil

Deformation parameters
Effective modulus of elasticity
Effective Poisson´s ratio

a*
a*

kN/m
3

a* is assumed values.

The magnitudes of rainfall intensity, rainfall
duration, and period of the antecedent condition usedin this case series are summarized Table 3. For sakeof simplicity, the effects of evaporation is neglectedin this study. The slope instability triggered rainfall
is typically taken place during rainfall period having
high relative humidity, and hence evaporation is
negligible.

saturation, the final rate of infiltrated rainwater isequal to the infiltration capacity at the soil saturation
state. And the infiltration excess of rainwater isformed as the surface runoff. In the other words, theTrf decreases with increasing the rainfall intensity if
the rainfall intensity is not greater than the infiltration
capacity of the soil at saturation. Therefore, themaximum rainfall intensity, which the relationshipbetween If and Trf obeys the ID thresholds, isgoverned by soil types in term of their saturated
permeability.

Numerical Results
Fig. 10 shows the ID thresholds for various typeof soils (in term of their saturated permeability) withthe slope angle of 30o. The coordinates (If, Trf) lay on
a single linear line on log-log scale regardless of themagnitude of saturated permeability. The Trf
decreases with increasing the rainfall intensity.
However, the Trf does not decrease if rainfall
intensity increases beyond the infiltration capacity atsaturated state of the corresponding soils (shown as
black star symbols for the rainfall intensity of greaterthan the infiltration capacity at soil saturated state andas vertical dashed line for the extreme rainfall
condition). According to the Green and Ampt model(Green and Ampt, 1911), if rainfall intensity isgreater than the infiltration capacity of the soil at

Fig. 10 ID thresholds based on Soil A, B, C withvarying rainfall intensities, β=30°, non-stop rainfall.
17

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 12 presents the effect of antecedent rainfall on
the ID thresholds. Prior to the continuous rainfall R3,
the slope is subjected to 24 hours of the rainfall R1
followed by between-storm period t b of 2 days or 7
days. The ID thresholds parameter m remains almost
constant regardless the magnitude of t b, but theparameter c increases with increasing the magnitude
of tb. The drop of the ID threshold parameter c withdecreasing tb is due to the lower of initial FS for the
shorter tb. As shown in Figure 4.9 that the shorter t b
results in the lower initial FS prior to the subsequent
rainfall. Under the same rainfall intensity, the Trf
decreases with decreasing t b from that of 7 days to thatof 2 days. In the other word, the faster slope failure isfound for the slope subjected to the shorter betweenstorm period t b.

Fig.11. ID thresholds based on slope angle 20, 30
and 400 with varying rainfall intensities, Soil A, B,
C, non-stop rainfall.

CONCLUSIONSThis paper presents two main parts. First part is toobtain comprehensive understanding of hydromechanical responses within shallow slope leading
to primary framework for quantifying criticallocations, which is useful for early warning system
based on monitoring device installations. A series ofexperiments were undertaken in this part to evaluate
the hydrological responses of shallow slopes ofvarying steepness and when subjected to varying
intensities, periods, and inter-storm periods ofrainfall. A series of analysis of infinite slopes was
also
undertaken to develop a fundamental
understanding of rainfall-induced shallow landslidecharacteristics. Thereafter, factors influencing
rainfall-induced shallow landslides and the criticalrainfall thresholds (ID thresholds) were investigatedthrough a series of numerical experiment. The
conclusions can be deducted as following:

Fig. 12. ID thresholds based on 2 types of antecedent
rainfall (tb=2 and 7 days) with varying rainfall
intensities, β=30°, Soil A, B and C
Fig. 11 presents the effect of slope angle on thetime-intensity of rainfall at the failures state. The
absolute value of ID thresholds parameter m slightly
increases with increasing slope angle. In the other
word, the steepness of the ID thresholds increases
with increasing slope angle. Moreover, the ID
threshold parameter, c, which represents the rainfall
intensity required to trigger the slope failure at a unit
time of rainfall, clearly decreases with increasing
slope angle. The drop of the ID threshold parameter cwith increasing slope angle is due to the lower initial
FS for the greater slope angle. The increment of the
ID threshold parameter m with increasing slope angle
implies that the time to failure is faster for the steeper
slope. Chinkulkijniwat et al., 2016 investigated thedepth of failure plane in cohesionless soil slope
subjected to continuous rainfall. For the soil slope ofgreater than the soil frictional angle itself, they foundthat the greater slope angle results in the shallower
depth of failure plane, and hence the faster the time to
failure. In total, the time to slope failure is accelerated
by the slope angle. Under a specific rainfall intensity,
the higher slope angle results in the shorter Trf.

Physically-based Warning Approach
The experimental results showed that thehydrological and physical responses within shallow
slope subjected to rainfall were characterized in theinfiltration and saturation phases.
During theinfiltration phase, the maximum magnitude of watercontent was found behind the wetting front, termed
as the water content behind the wetting front (θwb).
For a certain soil type, the magnitude of θwb was
found to be dependent on the magnitude of rainfall
intensity, regardless of the slope gradient and initialwater content. Based on the relative depth of the
failure plane, the failure can be categorized by three
prime modes: 1) along the impervious layer mode, 2)
shallow depth mode, and 3) transitional mode. These
modes can be characterized by the magnitude of astability index termed as tan'/tan  ratio. An
infiltration index, termed as i/ks ratio, was found toplay a role in the depth of failure plane only for thetransitional mode.
18

SEE - Bangkok, Thailand, Nov.11-13, 2019[6] Cannon SH, and Gartner JE. 2005. Wildfirerelated debris flow from a hazards perspective. In:
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Rainfall Intensity-duration Thresholds approach
The critical rainfall thresholds (ID thresholds)
were examined via finite element method. The
numerical results showed that the rate of reduction
in safety factor (FS) increases with an increasing
the intensity of rainfall, only in a range of lower
than the infiltration capacity at soil saturated state.
As such the saturated permeability of the soil, whichis equal to the infiltration capacity at soil saturated
state, plays an important role in the shallow slope
failure. The saturated permeability was found also togovern a range of applicability of ID thresholds. If
the rainfall intensity is not greater than the infiltration
capacity at soil saturated state, the rainfall duration
to failure (Trf) can be read from the ID thresholds.
Slope angle and antecedent rainfall were found toplay significant roles on instability of shallow slopes,
as they control the initial stability of slope, which
results in the different linear relationship of ID
thresholds. In addition, the slope angle might
accelerate the rate of rain water infiltration, andhence it reflects the slope of the ID thresholds.
ACKNOWLEDGEMENTS
This work was supported by the Thailand
Research Fund under the TRF Senior Research
Scholar program grant No. RTA5680002, Suranaree
University of Technology, and the Office of Higher
Education Commission under NRU project ofThailand.
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[4] Caine N. 1980. The rainfall intensity-duration
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deposits of Campania. Proc. 8th Int. Symp. on
Landslides, (Bromhead E, Dixon N, Ibsen ML,eds) Cardiff: AA Balkema 1:209-214.
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in model slopes for shallow flowslides early
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[20] Guzzetti F, Peruccacci S, Rossi M, and Stark CP.
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20

Technical Papers

21

Science

22

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DIFFERENT RATIOS OF OKRA JUICE AND PANDAN LEAF JUICEON SPORT DRINK
Wattana Wirivutthikorn1
1

Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi (RMUTT)
2 Phaholyothin 87 Soi 2 Phaholyothin Road Thanyaburi Pathum Thani 12130 Thailand
ABSTRACTThe major advantage is that there are good bioactive ingredients and antioxidants that are beneficial to thebody are possible when used as a sport drink. There were possibility to produce sport drink by using Thai herb as
raw materials. The objective of this research was to study the optimum ratios of okra juice and pandan leaf juicewith vitamin C supplementation of mixed juice. Four ratios of okra juice and pandan leaf juice were performed
into 4 experiments. Experiment 1: (control formula) okra juice 100 ratio, Experiment 2: blended okra juice andpandan leaf 70:30 ratio, Experiment 3: blended okra juice and pandan leaf 60:40 ratio and Experiment 4:
blended okra juice and pandan leaf 50:50 ratio were obtained. The results from physical measurement (L,-a*,b*and percent of transmittance) were significantly different (P<0.05). The study chemical of measurements, i.e.
pH, percentage of acidity and total soluble solid were performed. The results showed that Experiment 4 had thelowest pH and gave the highest percentage of acidity values of 3.15 and 0.28, respectively. The microbiologicalproperties revealed that amount of microorganism in each treatment was not found. The sensory evaluation on
overall acceptability by using 9-point hedonic scale revealed that panelists accepted with the highest scores of
7.13 on okra juice (control). From the information obtained, the formulation of sport drink produced from Thai
herbs can be developed to be accepted by consumers, which has increased steadily and expanded in the large
future level in beverage industry.
Keywords: Okra, Pandan leaf, Juice, Sport, Drink
quality or standards as announced by the Thai
Ministry of Public Health. Especially minerals
controlled in 1 liter sport drink containing theseminerals: sodium not less than 20 meq, glucose notless than 2 percent of weight or sucrose not less than
4 percent of weight, potassium not more than 5 meq(if any) and bicarbonate or citrate not more than 15
meq. In addition to previous components may use
minerals other than 3 and 4 or other sugars to beapproved by the Food and Drug Administration [3].
Chloride is one of the minerals that is controlled in
sport drinks. The reason for having to control theamount of salt in food or chloride in sport drinks, if
there is too much salt, it may be a major cause ofhigh blood pressure. Chloride is the most important
negative ion in the body. Most of the body gets it in
the form of sodium salt. Chloride acts to balance thepH of the body and a component of hydrochloric
acid in the stomach. If the body is absent, will vomit.
In general, the body gets chloride along together
with sodium [4]. The utilization possibility of okra
to be processed into sport drinks for those who lacknutrients and exercise Because, it is rich in nutrientsthat are nutritious, such as carbohydrates as fiber,
protein, folate, calcium, phosphorus, potassium,magnesium, iron, vitamin A, vitamin B1, vitamin B2
and vitamin C in sufficient quantities. Because okra
is highly nutritious, in addition to food and the drink
also has properties for the treatment of diseases suchas fresh okra with high amounts of ginseng and

INTRODUCTION
At present, Thai society has seen the importanceand pay attention to exercise more sports. In order tohave a healthy, healthy body without disease,athletes must pay attention to their health care.
Health supplement products have become more
actives. Especially the use of vitamins and minerals
to enhance health and fitness [1]. Sport drinks,
called electrolyte drinks, refer to beverages that
contain minerals as the main ingredients. Includes
dry mineral drinks as well is a liquid replacement
drink that is lost during exercise or sport. The lost
fluid is the loss of sweat. The sweat contains asmuch as 99 percent water and contains 1 percent
more minerals. Drinking of sodium-containing
solutions during exercise and recovery may help
maintain the condition and normalize the amount ofblood and also help maintain the water in the space
between cells. But still have thirst, while drinking
clean water will help suppress appetite [2]. The
major components of sport drink according to the
FDA requirements are that they should containsodium chloride minerals and magnesium inquantities not exceeding 25 g / l. If the concentrationof minerals and sugar is high, will slow down theabsorption, so drinking mineral drinks or otherbeverages need to be diluted before. To allow theabsorption of water to replace sweat quickly. Sportdrink are a specific control food. It must have
23

SEE - Bangkok, Thailand, Nov.11-13, 2019

pectin. Several compounds such as gum and pectinin high amounts cause mucus, which will help
reduce the symptoms of gastroenteritis, prevent
atherosclerosis, maintaining normal blood pressure,nourishing the brain and also being a good laxative[5]. Pandan leaf has a fragrant aroma of essential
oils. The aroma of pandan leaf is very much fromthe chemical called 2-acetyl-1-pyrroline, which isthe same smell that can be found in jasmine rice,white bread and flowers. Pandan leaf contains
proteins, carbohydrates, fiber, calcium, phosphorus,
iron, essential oils (containing linalil acetate, benzyl
acetate, linoleol and ethyl vanillin, geranium, andkumarin fragrance). It contains chlorophyll pigment,
making it green with -carotene, which is theessence that is beneficial to the body, helps inexcretion and can resist cancer as well [6]. There isresearch related to comparison of chloride
determination in 10 commercially available sport
drinks by using titration method and sedimentation
method for silver chloride analysis. The results
showed that the values obtained in both methods arehighly correlated (r2 = 0.9582) and when analyzing
results were tested with t-test. It was found that bothmethods were not statistically different. Whencalculating the cost of chemicals used, it was foundthat the method of precipitation in silver chloride
required a cost of 1.3 times higher than the titration
method. The cost of chemicals is 7.1455 and 5.5424
baht, respectively. In addition to, the titration
method took 15 minutes per sample, whereas thesettling silver chloride method took approximately 9hours per sample [7]. But there was no information
about the formulation of okra mixed with pandanleaf. For this reason, of okra and pandan leaf
benefits, the researchers mentioned the importanceof producing water-based okra and pandan leaf withthe healthy sport drink by studying appropriate
amounts of okra and pandan leaf ratios on thephysical, chemistry quality and sensory acceptanceof the consumer towards the product in order toobtain the taste that is acceptable to the consumer,
which help with the quenching of thirst and help
relax or make the body. The data obtained from thisresearch was an alternative to apply by making sport
drink containing both of okra and pandan leaf as raw
materials to improve the nutritional quality and good
health. Sport drink that has benefits and suitable forpeople who love to exercise, love health and also
solve the problems of bringing agricultural productsthat are processed with higher values.

were purchased from Rangsit Market which locatedin Pathum Thani Province Thailand.
Dried Okra Preparation
The okra was washed and cut into thin small
pieces. Then 5 kg of dried okra was dried at 75c for3 hrs. Stored products that were packed in plastic
zipper bags with desiccants [8].
Pandan Leaf Preparation
The pandan leaf was washed and cut into thinsmall pieces. Then 100 g of broken pandan leaf wasdried at 75c for 2 hrs. Stored products that were
packed in plastic zipper bags with desiccants
adapted from [8].
Production of Blended Dried Okra Juice andPandan
Leaf
Juice
with
VitaminC
Supplementation
Okra Juice Preparation
Weigh 50 g of dried okra was placed in astainless steel pot containing 1,000 ml of water andheated to 100°C. Then, put pandan leaf to reduce thegreen odor of okra. The aliquot was filtered througha cloth until there was no sediment and then stored
its in the refrigerator [8].
Pandan Leaf Preparation
Weigh 10 g of dried pandan leaf was placedin a stainless steel pot containing 1,000 ml of waterand heated to 100°C. Then, put pandan leaf toreduce the green odor of okra. The aliquot was
filtered through a cloth until there was no sedimentand then stored its in the refrigerator adapted from
[8].
Blended Okra Juice and Pandan Leaf Juice
Preparation
This research was performed as four
experiments (three replications): 1) okra juice(control); 2) blended okra juice and pandan leaf
juice 70:30; 3) blended okra juice and pandan leaf
juice 60:40 and 4) blended okra juice and pandanleaf juice 50:50. Bring the okra juice mixed withpandan leaf juice to be homogeneous and add otheringredients as shown in Table 1.

METHODOLOGY
The research was carried out at the Division ofFood Science and Technology, Faculty ofAgricultural Technology, Rajamangala University ofTechnology Thanyaburi. (RMUTT) Pathum Thani
Province Thailand. The samples used in this study

Production of Blended Okra Juice and Pandan
Leaf Juice with Vitamin C Supplementation
Weigh 50 g of dried okra was placed in astainless steel pot containing 1,000 ml of water and
24

SEE - Bangkok, Thailand, Nov.11-13, 2019heated to 100°C for 5 minutes. The aliquot was
filtered through a cloth until there was no sediment.
Bring okra juice blended with pandan leaf juice.
Addition of some detailed ingredients as shown(Table 1). (65 g of sucrose, 1.2 g of citric acid, 8g of
sodium chloride and 0.5 g of vitamin C), thencooling and heated to 70°C for 15 minutes. The
blended aliquots were placed in 250 ml of sterilize
colored glass bottles by means of coolingimmediately and storage at 4C adapted from [9].

[12].
Sensory Evaluation
The sensory evaluation was carried out by 30
untrained panelists in Rajamangala University ofTechnology Thanyaburi (RMUTT) , Thailand.
Panelists were asked to analyze their level ofpreference for each treatment by using a 9-point
hedonic scale test based on the attributes of color,
odor, taste, clarify and overall acceptability. 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 [13].

Recording of Data
Collect and record numerical data fromexperiments (three replications) and calculate dataand statistical analysis. The Experimental design for
physical and chemical quality analysis were
evaluated by using a completely randomized design(CRD). A randomized complete block design(RCBD) for sensory evaluation was used withanalysis of variance. Analysis of the meandifferences of experiments was performed using
Duncan’s new multiple range test [10].

RESULTS AND DISCUSSION
Physical appearances of okra juice and passion
leaf
Figure 1, The characteristics of sport drink
products, okra juice was mixed with pandan leaf
juice and vitamin C supplementation. Whenconsidering the appearance, it was found that theExperiment 1 and 2 had a lot of suspended
sediments of okra. The Experiment 3 showed that
there was a little suspended okra and Experiment 4
was found that there was no sediment of okra. Whenconsidering the color, it was found that theExperiment 1 had a light brown color, but theExperiment 2 had an orange-brown color, whereas
the Experiment 3 was yellowish brown, the last theExperiment 4 had a clear yellow color. The results
revealed that the Experiment 1, 2 and 3 were brownin color from the okra juice in a ratio greater thanpandan leaf [14]. Possible reason was that okra
contains a soluble fiber pigment such as pectin andmucilage caused by acetyated acidic polysaccharide
compounds and galactulonic caid. The Experiment 4
had a clear yellow color due to the ratio of okra juice
and pandan leaf juice in the same ratio. Whenconsidering the smell, it was found that the smellvaries according to the amount of okra juice that was
reduced and the amount of pandan leaf juice wasincreased. Compared to the control sample, when
considering the taste, it revealed that all experiments
had a slightly sour, sweet, salty taste due to flavoringwith sucrose at the equal amount of sodium chloride
and citric acid in all experiments [15].

Physical Measurement
Observation by eyes
Observation of the external appearance ofmineral drink products, okra juice, mixed withpandan leaf juice, vitamin C supplementation in all 4
experiments [11].
Measurement by using instrument
Color brightness (L* ), color as green (-a* ) andyellow (+b* ) were measured by using Minolta CR10 and recorded as values adapted from [11]. The
sedimentation was detected by using Visible
Spectrophotometer Metertech Model SP830 and thesedimentation value was recorded as values adaptedfrom were recorded as percent of transmittancevalues (% T) adapted from [11].
Chemical Measurement
The pH, total soluble solid (TSS) and percentage
of total acidity (calculated as citric acid) were
measured by using pH meter OHAUS ST3100-F,
using hand refractometer (measured as Brix andtitration
with
0.1N
sodiumhydroxide(phenolphthalein as indicatorasvalues),respectively adapted from [12].

Physical measurement
Table 2, The results revealed that all of (L*),(a*),(b*) and percent of transmittance values andphysical appearance depending on different ratios of
okra juice and pandan leaf juice. The results showedthat all values were different (P <0.05). The physicalcharacteristics of blended okra juice and pandan

Microbiological Measurement
The total microbiology was measured as total
plate count by using plate count agar adapted from25

SEE - Bangkok, Thailand, Nov.11-13, 2019leaf juice products with vitamin C supplementation,comparing the differences between the experimentsof color values (L*), (-a*), (b*) and percent oftransmittance. The results revealed that thebrightness value (L*) were of 27.61, 28.48, 29.78
and 29.58, respectively. The color values (-a*) and(b*) were -3.00, -2.67, -6.35 and -10.08, 10.59,
12.13, 12.51 and 13.55, respectively. The percentageof transmittance from all treatments with value of
77.09, 74.02, 83.63 and 87.50, respectively [15].
This may be caused by the ratios between okra juice
and pandan leaf juice with different amounts due toeach experiment to have different values. The
experiment with a large amount of pandan leaf ratio
had a darker color and more brightness than theexperiment with ratio of the less amount of okra
juice. One possible reason was both okra and pandanleaf have a chlorophyll (as green pigment), but
increasing the amount of pandan leaf juice results in
an increasing trend of all values [16],[17].

that the sensory scores on color, smell, taste, texture
fromcomparison
ofdifferences
betweenexperimental items were not statistically significant
difference (p> 0.05) in which each experiment had
not different on preference scores [22],[23],[24].
The experiment with the highest liking scores was
the Experiment 1. For one possible reason was theratios of okra juice and pandan leaf juice were notsignificantly different, resulting in the consumer's
acceptability for color, odor, taste and clarity [25].
The other reason, may be amount of vitamin C that
was added to each experiment may be too little,
therefore almost panelists could not to clearly
distinguished in each experiment. For overall
acceptability, panelists preferred the Experiment 1
than compared to the other experiments, since there
was only okra juice. From the results of thisresearch, it indicated that increasing the proportionof pandan leaf juice was likely to cause consumers
to dislike it, possibly due to the pandan leaf smellthat is too strong [26],[27].

Chemical Measurement
Table 3, The results indicated that the pH, totalsoluble solid and percentage of total acidity in okra
juice products with pandan leaf juice, depended on
the different ratios (Table 3) [18]. The result was
found that the measured values were statisticallysignificant differences (P < 0.05), while total soluble
solid was not statistically different. This value
depends on the increasing okra juice and pandan leaf
juice ratio, resulting in lower pH values (moreacidity). The results indicated a tendency for thepercent of total acidity did not decrease low values
in comparison with the control samples. The values
analyzed were consistent with the percentage of total
acid content in the form of citric acid that was higher
with the increase in vitamin C. The total soluble
solid was not significantly different (p> 0.05) due tothe amount of solid ingredients added in all
experiments [19],[20].

E1

E2

E3

E4

E1: Okra juice )Control)
E2:Blended okra juice and pandan leaf juice
70:30
E3:Blended okra juice and pandan leaf juice
60:40
E4:Blended okra juice and pandan leaf juice
50:50

Microbiological Measurement
Based on the analysis of total microbial counts
by using the total plate count method in blended
okra juice, and pandan leaf juice with vitamin C
supplementation. The results showed thatmicroorganisms were not found in all experiments.
One reason possibility was due to the pasteurization
process of sport drink before packaging. This
processing is a thermal processing method with themain purpose to destroy pathogenic microorganisms,
including microorganisms and related enzymes thatcause food degradation [21].

Table 1 Different ratios of blended okra juice andpandan leaf with vitamin C supplementation
IngredientSensory Evaluation
Table 4, The sensory characteristics It was found26

Experiment
1

2

3

4

okra juice )ml(

1000

700

600

500

pandan leaf )ml(

0

300

400

500

sucrose )g(

65

65

65

65

citric acid )g(

1.2

1.2

1.2

1.2

sodium chloride )g(

8

8

8

8

SEE - Bangkok, Thailand, Nov.11-13, 2019vitamin C )g(

0.5

0.5

0.5

6.. Based on this research, researchers will beable to launch new sport drink products in the futureby selecting the appropriate Thai local vegetables
and fruits that are beneficial for antioxidants, an
option for health-conscious consumers.

0.5

Table 2 Physical measurement of blended okra juice
and pandan leaf juice products with vitamin C
supplementation
Experiment

physical values*
L*
-a*
b*
%T
1
27.61b-3.00a10.59c77.09c2
28.48b
-2.67a12.13b74.02d
a
b
ab
3
29.78
-6.35
12.51
83.63b
a
c
a
4
29.58
-10.0813.55
87.50aNote: *a-d The different letters in the same column
mean significant difference (P < 0.05)
Table 3 Chemical measurement of blended okra
juice and pandan leaf juice products with vitamin C
Experiment

ACKNOWLEDGMENTS
The researchers would like to thank the 4 thegrade students and officials of the Division of Food
Science and Technology, the Faculty of Agricultural
Technology Rajamangala University of Technology
Thanyaburi (RMUTT), Pathum Thani Thailand that
contributed some parts in the research. The Facultyof Agricultural Technology provided support
facilities and budgets for the research.

chemical values
TSS (Brix)ns

pH*

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1
4.01b
9.00
0.13b
2
4.08a
9.10
0.21a
3
3.65d
9.08
0.23a
4
3.71c
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0.14b
Note: *a-d The different letters in the same column
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Table 4 Mean score of preference for sensory
properties of blended okra juice and pandan leaf
juice products with vitamin C supplementation
Experimentscorescolornsodornstastens

clarifyns

overall
acceptability*

1
7.03 6.77 6.63
6.83
7.13a
2
7.30 6.57 5.91
6.57
6.77ab3
7.13 6.37 5.80
6.31
6.57b
4
6.77 6.30 6.17
6.42
6.63b
Note: *a-d The different letters in the same column
mean significant difference (P < 0.05) and ns non
significant difference (P>0.05)
CONCLUSION
1. The uses of different ratios of raw material
preparation had effects on the quality of mixed okra
juice and. pandan leaf juice.
2. The results of the physical properties analysis
showed that all values were statistically significant
differences (P<0.05).
3. The results of the chemical analysis showedthat percent of total acidity (except pH and tota
lsoluble solid) were significantly different (P<0.05).
4. Blended okra juice )control) gave the most
overall acceptability of 7.13 values from thepanelists.
5. The results of total plate count indicated thatno microorganism in each experiment was not found.
27

SEE - Bangkok, Thailand, Nov.11-13, 2019

tangerine Juice, Faculty of Agricultural
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Rajamangala
UniversityofTechnology Thanyaburi, Pathum Thani; 2009.
[19] Rebecca, L. J., et al., Extraction and purificationof carotenoids from vegetables, Journal ofChemical and Pharmaceutical Research, Vol. 6,
2014, pp. 594-598.

[20] Wirivutthikorn, W., Effect of passion fruit Juiceand sugarcane juice ratios on blended passion
fruit juice and sugarcane juice production,
Agricultural Sci. J. 49, No.3 (Suppl), 2018: pp.
229-235.
[21] Ciuffreda, E. et al., Alicyclobacillus spp.: New
insights on ecology and preserving food quality
through new approaches, Microrganisms, Vol 3,
2015, pp. 625–640.
[22] Obasi, B.C., Whong C.M.Z. and Ameh, J.B.,
Nutritional
andsensory
qualitiesofcommercially and laboratory prepared orange
juice, African Journal of Food Science, Vol. 11,
2017, pp. 189-199.
[23] Wirivutthikorn, W., Effects of types andquantities of sweeteners on development of
blended lotus root juice and goji berry product
In: Proc. the 6th Academic Science andTechnology
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2018. p. AS176-AS180.
[24] Intakul, N., Product development of passion
fruit product. Research report. Division of Food
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[26] Wirivutthikorn W., Appropriate ratios ofproducing riceberry blended with gac fruit androselle beverage. In Proc 3rd National andInternational Research Conference 2019 :NIRC III 2019
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28

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ESTIMATING PEOPLE'S TRAVEL BEHAVIOR TOWARDS
TRANSIT-ORIENTED DEVELOPMENT IN DUKUH ATAS, DKI
JAKARTA PROVINCE
1

Gemala Pritha Ryzki Rynjani1, Chotib2
Faculty of Economics and Business, Universitas Indonesia, Indonesia; 2Faculty of Economics and Business,
Universitas Indonesia, Indonesia
ABSTRACT

Increasing resident activity in Jabodetabek has highlighted that increased traffic flow and transportationneeds could cause congestion and environmental problems. To address these possible transportation problems,
a transit-oriented development (TOD) policy is soon to be implemented in Dukuh Atas, Jakarta. Therefore, theresearch objective was to examine resident travel behavior based on socioeconomic characteristics and land
use based on the TOD policy in Dukuh Atas. A model was developed to more closely examine the travel
behavior influencing factors in the Dukuh Atas TOD area. Questionnaires were distributed to 300 respondents(150 inhabitants near the transit station and 150 commuters), and the data analyzed using structural equation
modeling (SEM). It was found that the travel behavior in Dukuh Atas TOD was more influenced bysocioeconomic status than land use in the TOD area. In general, the income, transportation costs, andeducational background variables were found to be the most influential socioeconomic variables. Moreover,
respondent travel behavior was not found to be unduly influenced by transit area facilities.
Keywords: Travel Behavior, Transit-Oriented Development, Structural Equation Modeling

426,000 vehicles per day from Depok and Bogor,
and 38% or 571,000 vehicles per day from Bekasi.
The increase in population density has begun toaffect the urban transportation facilities in Jakarta.
Because of the urban sprawl, the government is
expected to implement technical instruments andplanning regulations,especially forthetransportation sector.
Jakarta's urban problems are a government
concern as it is the government’s responsibility toprovide quality urban infrastructure facilities thatare capable of accommodating large numbers ofcommuters. With the rising commuter loads fromBODETABEK, multimodal transport systems andnetworks and convenient public transport services
are needed. Therefore, the government needs to“force” people to switch to public transportation
rather than using private transport.
Transit-oriented development (TOD) is aconcept that supports smart growth, increases
economic growth, is able to change market demandand lifestyle preferences (Cervero, 2004), also
minimizes human and vehicle movements.
Therefore, the TOD concept could be the answer toensuring sustainable economic, social andenvironmental
urban
development.
TOD
concentrates urban activities in one transit point
through mixed land use (mixed-use) and compact
development (Calthrope et al., 2004). Whichmeans, placing commercial centers, housing,offices, parks and public facilities within walking
distance of transit stops. To support the

INTRODUCTION
As cities drive economic growth anddevelopment, urbanization has been seen as a policy
tool to drive city development and improve thequality of life of the residents. According to theWorld Bank (2007), by 2025, approximately 67.5%
of Indonesia’s population are expected to be living
in urban areas. In recent years, due to an increase in
infrastructure facilities and qualified jobs, Jakarta
has been growing rapidly, with an estimatedincrease in population of 269 people a day.
Until 2017, the population density in Jakarta was
15,234 people / km2.
According to Statistics Indonesia, the average
population growth rate in Jakarta was 1.09 since
2000. However, after 2010, the number of migrants
to Jakarta city started to decline, with many
migrants preferring to move to the Jakarta
hinterland to Bogor, Depok, Tangerang, and Bekasi(JABODETABEK) possibly because the land
prices were lower than in Jakarta.
JABODETABEK commuter survey in 2014
found out that the 28 million JABODETABEK
residents, 13% or  3.5 million people werecommuterresidents.
Data
from
the
JABODETABEK Transportation Management
Agency (BPTJ) also found that the volume ofvehicles per day in Jakarta was 940,000, the tollroad load per day for four-wheeled vehicles heading
to Jakarta was 31% or 423,000 vehicles per day
from Tangerang and South Tangerang, 31% or29

SEE - Bangkok, Thailand, Nov.11-13, 2019transportation system development, the government
through the Minister of ATR / BPN in Indonesia is
responsible for developing policies for TOD.
Basically, the regulation reviews the basis andpurpose for TOD areas to support urban
transportation systems that are pro-commuter andare aligned with the socioeconomic carrying
capacity of the community in the TOD area as wellas the residents living in the transit area vicinity.
Because the policy has now been drafted, it isexpected that there will be several TOD areas
announced for Jakarta. These areas need to be able
to accommodate at least two modes of public
transportation, one of which should be rail-based
and located downtown; therefore, the Jakarta TOD
is to be centralized in the Dukuh Atas area. Several
rules for the Jakarta TOD have been made tocomply with Governor Regulation No. 44 of 2017
concerning the Development of Oriented
Development Areas. The existing conditions in
Dukuh Atas are basically in accordance with therequirements for TOD areas. Data from the PT
MRT Jakarta (2018) show that Dukuh Atas isalready an intermodal mass transportation area withconnections to Sudirman KRL Station, the Airport
Train Station, Jakarta MRT Station, Dukuh AtasLRT Station and the Transjakarta Bus Stop. Dukuh
Atas also has many commercial and residential
activities such as offices, retail stores, hotels, andapartments. Therefore, developing this area as the
key transportation node and the center of economic
development in Jakarta has many challenges
because of the current inadequate environmental,social and economic quality, flood risks, urban
congestion problems, and poorly functioning
pedestrian (pedestrian) and bicycle road network.
For this reason, this development requires theimplementation of regional principles that arefocused on land use with mixed functions that allow
for high density development and ensure increased
connectivity, an improved quality of life, social
justice, environmental sustainability, infrastructure
resilience, and economic regeneration.
As well as the aim to streamline public transport
services in TOD areas, the TOD can also increasesocial capital by improving the kinship between thelocal communities or neighbors (Nallari, Griffith, &Yusuf, 2012), which could overcome the main
problems associated with urbanization; the lack ofstrong social bonds. However, TOD have beenfound to increase the social capital for people living
closer to the station. TOD research in China in
Beijing and Shenzhen, found that accommodating
the development of multimodal transportation wasable to improve ecological, economic and social
sustainability in these rapidly growing cities (Xie,
2017).
Although
TOD
implementation
development indicators have shown that it can be
successfully applied, each city has varying

development needs. Therefore, this paper examines
travel behavior around the Transit-Oriented
Development in Dukuh Atas in terms of thesocioeconomic characteristics and land use
development policy and develops a model that
explains the influencing factors for travel behavior
in the Dukuh Atas TOD area.
METHODSThis research was conducted in the transitoriented area Dukuh Atas located on Jalan Juana,
Jalan Kendal, to Jalan Blora, Kelurahan Menteng,
Kecamatan Menteng, City of Central Jakarta. In the
DKI Jakarta Provincial Spatial Plan for 2012 - 2030
and the DKI Jakarta Province Spatial Detail Plan for2014 –2019, the Dukuh Atas area was identified asa priority area for the primary TOD activity. Dukuh
Atas is a large scale, high density residential,commercial and business area in the SudirmanThamrin area and has significant potential as acentral transit-oriented area. The focus of theresearch was the TOD area and the surrounding
areas that would be affected by the TOD. The buffer
Map (Figure 1) shows the 800 meters transit point
area that is to be affected by the TOD.

Fig. 1 Buffer Area for the Dukuh Atas TOD
The research took a stratified random sampling
approach, which is considered suitable for
proportional and heterogeneous populations(Margono, 2004; Sugiyono, 2001; Meng, 2013).
Stratified random sampling was also used because
the sampling could be done in all survey locations
and because the estimates have been found to be
more accurate for each section of the population.
Sample collection was conducted on people in thearea around the TOD Dukuh Atas. The
determination of the number of respondents to beapproached in this study was according to Joreskog& Sorbom (1996) based on the number of researchvariables. In this research, as there were 22
variables, the sample was determined based on thefollowing formula:

30

SEE - Bangkok, Thailand, Nov.11-13, 2019

(X212), and livability (X213). The latent travel
behavior construct (Y) was explained using thefollowing observation variables; distance (Y1),choice of public transportation mode (Y2), trip (Y3),and time (Y4). The results of the model are shownin Figure 2.

(1)
k = number of variables
The estimation of the minimum study
population using the Joreskog & Sorbom’s (1996)
formula was 210 local residents and commuters;
because of a possible sampling error of 5%, theresearch sample was rounded to 300 respondents;
150 resident respondents and 150 commuterrespondents. The commuters were identified as
people who were travelling across districts andcities to carry out their daily activities and theresidents were people who had been living within aradius of 800 meters around the Dukuh Atas TOD
area transit point for at least 6 months or not up to 6
months but with the intention to stay. The occupantdata was obtained using a questionnaire that
required the respondent to systematically answer
the study questions. The household questionnaire
was designed to capture the characteristics of the
housingenvironmentandsocioeconomic
characteristics of the household (e.g., car ownershipand household income) (Van Acker,Witlox, & Van
Wee, 2007).
The resident and commuter travel behavior
model in the TOD area was developed using thestructural equation modeling (SEM) approach,which is a multivariate analysis technique used tobuild and test a statistical model and develop a
causal model (Golob, 2001; Hairulsyah, 2013).
SEM is a hybrid statistical modeling technique that
includes confirmatory aspects from the factor, path,and regression analyses, and has cross-sectional,
linear and general properties. The SEM analysis in
this study was processed using SmartPLS software,
which is used for structural equation modeling andincludes formative indicators to make predictions
through relationship testing between each variable
construct (Soo, 2016).
This research examined government policies on
the development of the TOD area regarding the
behavior of public transportation users in the Dukuh
Atas TOD area and the population around Dukuh
Atas.
The analysis included three latent variables. The
latentconstructpredictor
variablewassocioeconomic (X1), the observation variables were
gender (X11), age (X12), occupation (X13),
education (X14), income (X15), and transportation
costs (X16), and the mediator variables were theTOD (X2) simultaneous variables; walkability
predictor variables (X21), walking distance (X22),
walking time (X23), alternative mode (X24), cycle(X25), cycling access (X26), connect (X27),
signage (X28), pedestrian access (X29), one-stop
center (X210), parking (X211), park and ride

RESULTS AND DISCUSSION
To identify the characteristics of each of the
inhabitant and commuter respondents, aquestionnaire was distributed to 150 residents in thevicinity of the Dukuh Atas TOD area and 150
commuter
respondents.
The
respondents’socioeconomic quantitative data is shown in Table
1.
Table 1 Respondent Characteristics
SocialEconomics

Frequency (%)
Inhabitants

Commuters

Male

58%

52,7%

Female

42%

47,3%

15–25

32.0%

38.7%

26–35

28.7%

34.0%

36–45

20.7%

16.7%

46–55

8.7%

10.7%

56–65

4.0%

0.0%

66–80

6.0%

0.0%

Employee

32%

60.7%

Entrepreneurship

12,7%

21.3%

GenderAge

Job

Merchant

7.3%

1,3%

Housewife &Student

39.3%

14.7%

Others8.7%

2%

Education

31

Not Graduated

0.7%

0.0%

Graduated fromelementary
school2.0%

4.0%

Graduated fromjunior highschool /equivalent

9.3%

4.7%

Graduated fromhigh school /equivalent

59.3%

26.0%

Graduated from
Diploma

10.7%

23.3%

SEE - Bangkok, Thailand, Nov.11-13, 2019SocialEconomics

Frequency (%)
Inhabitants

Commuters

Graduated (S1)

18.0%

40.0%

Graduated (S2)

0.0%

2.0%

SocialEconomics

Income/month<=3,5 million

36%

34%

3,51 - 5 million

41.3%

34%

>= 5,1 million

22.7%

32%

The Jakarta urban sprawl has had an impact on
the many daily commuters to Jakarta. As shown in
Table I, the majority of people commute for
employment purposes, with the others attending
school or involved in activities around the Dukuh
Atas transit area. The survey revealed that 60.7% ofcommuters came to Jakarta for work, and 39.3% of
local residents were either housewives or students.
Around 40% of commuters had graduated fromcollege (40%), but the majority of local residents
had only graduated from high school (59.3%). In
terms of income, however, 41.3% of residents
earned 3.51–5 million and 36% earned up to 3.5
million, whereas 34% of commuters earned below
3.5 million, 34% earned between 3.51 to 5 million,
and 32% earned more than 5.1 million, whichmeans that one-third of commuters were in theupper middle category based on the World Bank
calculations. Previous studies have found that
populations around transit areas are generally lowincome households without cars (Cervero, 2004),
which was also found in this study.

00 - 0.4 km

70.0%

76.7%

0.41 - 1 km

26.7%

13.3%

1.1 - 4 km

2.7%

9.3%

4.1 - 7 km

0.7%

0.7%

68.0%

73.3%

Distance (km)2.1 - 7 minutes

2.0%

5.3%

7.1 - 15 minutes

26.0%

18.0%

15 - 30 minutes

4.0%

3.3%

6.0%

1.3%

46%

2 times

18.0%

46%

More than 3
times

15.3%

6.7%

Never

15.3%

8.0%

Sometimes (<5times a week)

50.0%

43.3%

Often (5–10
times a week)

21.3%

14.0%

Yes, always (>10 times a week)

13.3%

34.7%

Not Using Public
Transport

20%

17.3%

KRL / Commuter
line

38%

49.3%

Transjakarta bus

30.7%

32.7%

Public vehicles
with routes(Metromini,
Kopaja,Mayasari Bakti,
etc.)

8.7%

0.7%

BuswayIntegrated Border
Transportation(APTB)

2.0%

0%

Pick-up public
transportation

0.7%

0%

MRT

81.3%

79.3%

LRT

6.0%

18.7%

Airport Train

7.3%

0.7%

Others4.0%

1.3%

In terms of the land use in the TOD area, the railand non-rail mass public transportation, thepedestrian and bicycle lane transit functions arevery important. Moreover, to reduce the use of
personal vehicles, walking or cycling provisions areneeded. Table 2 shows the resident and commuter
travel behavior, from which it can be seen that mostresidents (70%) and commuters (76.7%) travelled
00 - 0.4 km from the transit point from their placeof residence to the place of their activities. Morelocal residents (26.75) walked 0.41 - 1 km to theirplace of activity than commuters (13.3%), but morecommuters (9.3%) walked 1- 4 km to their place of

Trip
Walking

60.7%

Source: Primary Data, processed with SPSS, 2018

Time (min)<= 0 - 2 minutes

1 timeFuture Mode
ChoiceFrequency (%)
Commuters

Commuters

Mode Choice

Table 2 Travel Behavior Characteristics

Inhabitants

Inhabitants

PublicTransport
Usage

Source: Primary Data, processed with SPSS, 2018

SocialEconomics

Frequency (%)

32

SEE - Bangkok, Thailand, Nov.11-13, 2019activity than local residents (2.7%). However, very
few commuters or residents walked 4.1 - 7 km
(0.7%).
To improve the quality of Jakarta’s
development, the government plans to operate
sustainable transportation; the Mass Rapid Transit(MRT) and Light Rapid Transit (LRT). The railbased Mass Public Transport System (SAUM) was
put into operation to complement the integration of
the intermodal transportation in Dukuh Atas,
following the opening of the airport fast train,
Transjakarta, and the Busway Integrated Border
Transportation (APTB). If it were alreadyoperating, most respondents claimed that theywould switch to the MRT; 81.3% of residents and79.3% of commuters. However, the propose used of
the LRT mode was much lower at only 18.75 ofcommuters and 6% of residents.

Source: Primary Data, processed with SmartPLS,
2018
SEM research proposes that a normed fit index(NFI) be the first measurement after the calculationof the Chi-Square value (Bentler & Bonett, 1980).
NFI values are between 0 and 1; the closer to thevalue is to 1 or when it is above 0.90, the model isseen to have acceptable compatibility. The NFIvalue in Table 3 was found to be 0.533, and as thisvalue was between 0 and 1, the model was judged
to be of average acceptability. The standardized
root mean square residual (SRMR) value is used asa measure of goodness of fit to avoid
misspecification in the model (Dijkstra & Henseler,2015). From the SRMR value of 0.092 or <0.08
shown in Table III, it was concluded that there wasno model misspecification. From Table III, it canalso be seen that the model form was not goodenough because the indicator variables in the model
were not significant to each other.

Analysis of Structural Equation Modeling

Table 4 Average Variance Extracted (AVE)The travel behavior resident and commuter
TOD area model was then analyzed using a SEM
approach.

Origi
nal
Samp
le (O)

Sam
ple
Mea
n
(M)

T
Statistics(|O/STD
EV|)

P
Valu
es

0.358

Standard
Deviati
on
(STDE
V)
0.017

Socioecono
mics

0.359

21.135

0.123

0.131

0.014

9.044

0.530

0.532

0.015

34.528

0.00
0
0.00
0
0.00
0

TOD Forms
TravelBehavior

Source: Primary Data, processed with SmartPLS,
2018
Hypotheses test are used to assess theprobability value of each variable if the value of P
<0.05. When the value of P > 0.05, this indicatesthat there is no correlation between the variables. As
shown in Table IV, the AVE was found to have acorrelation with all formative indicators <0.05, withall socioeconomic variables, TOD forms, and travel
behavior being 0.000, clearly indicating that there
was a significant effect between the independent
variables and the dependent variables. As the tstatistic value for the formative indicator had avalue higher than 1.96, the null hypothesis was
rejected, which meant that all the formative
indicators were in accordance with the study
hypotheses.
Therefore, it was found that the travel behaviorof Dukuh Atas TOD users was influenced more bysocioeconomic status (0.431) than TOD land use(0.251). In general, income, transportation costs,
and educational background had the most influenceon the socioeconomics of the respondents. The
choice of the place of residence was also influenced
by the social status of the respondent, whichindirectly affected travel behavior (Van Acker et al.,2007). That is, indirectly, the respondents who hadhigher transportation costs and travelled further fora longer time used several modes of transport to get

Fig. 2 SEM Result
Source: Primary Data, processed with SmartPLS, 2018

The SEM model analysis in Figure 3 revealed
that the model fit was in accordance with previous
research. The model test obtained a Chi-Square of
586.122.
Table 3 Model Fit
ThresholdEvaluation

SRMR

Saturated
Model
0.092

<0.08

-

Chi-Square

586.122

Small

-

NFI

0.533

-

Prob.

0.000

Between 0
to 1
>0.05

Good

33

SEE - Bangkok, Thailand, Nov.11-13, 2019

to their place of activity before transiting in the
Dukuh Atas TOD area.
The behavior related to the respondents’ travel
was not found to be influenced by the transit area
facilities, which was in disagreement with researchin San Diego, in which it was found that this type ofland use greatly influenced travel behavior (Boarnet& Crane, 2001). The difference between thesefindings was possible because of the marked
differences between the socioeconomic status of the
respondents and the urban facilities in Jakarta andthose in San Diego.
The model analysis indicated that even though
respondents were not satisfied with the service
facilities in the transit area, the highly educated andhighincomes
respondents
usedpublictransportation because they lived quite far away andthe travel time was quite long; however,socioeconomic status was not found to affectrespondent activities in Dukuh Atas (0.189).
Although in general the respondents were notsatisfied with the infrastructure services at Dukuh
Atas, the travel behavior was more influenced bysocial status, with respondents having a higher
social status travelling longer distances for a longer
time and taking more trips per day. Travel behavior
was found to be less complex in respondents who
had fewer household responsibilities and thoseliving in urban environments.

ACKNOWLEDGEMENT
The authors wish to acknowledge that thisresearch was supported by Publications Grant for
Thesis and Dissertation of Universitas Indonesia(PITTA UI Grant).
REFERENCES[1] Bentler, P. M., & Bonett, D. G. (1980).
Significance tests and goodness-of-fit in theanalysis of covariance structures. Psychological
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Design. Oxford, UK: Oxford University Press.
[3] Calthrope, Peter. (1993). The Next American
Metropolis–Ecology,
Community,
and
TheAmerican Dream. Canada: Princeton
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(2004).
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development in the United States: Experiences,
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participation on sustainable transportation andregional development in Medan. Medan: UGM.
[8] Nallari, R., Griffith, B., & Yusuf, S. (2012).
Geography of growth: Spatial economics andcompetitiveness. Washington, DC: The WorldBank.
[9] Soo, Kim Gye. (2016). Partial Least Squares
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CONCLUSION
Based on the analysis results, the following
conclusions were made.
The commuter and resident trip behavior aroundthe transit area were somewhat similar. Most
respondents did not see public transportation as themain means for their daily activities. In addition,
both the commuters and residents were less willing
if they had to walk and/or use bicycles to conduct
their activities in the transit area.
The income, transportation costs, andeducational background variables were found to be
the most influential socioeconomic variables, andthe respondent travel behavior was not found to be
influenced by the transit area facilities.
Respondents’ socioeconomic backgrounds were
found to have a greater influence on travel behavior
than the land use in the TOD area. In contrast to
many previous studies, in which it was found thatcompact land use significantly affected walking andpublic transportation use travel behavior, this was
not found in this study, possibly because most
respondents expressed a degree of dissatisfaction
with the Dukuh Atas land use infrastructure quality.

34

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ABOUT KARST (CHEMICAL) DENUDATION IN ZEMO IMERETI
PLATEAU. GEORGIA, CAUCASUS
Zaza Lezhava1, Lasha Asanidze1, Kukuri Tsikarishvili1, Nino Chikhradze2, Lela Gadrani1
1
Vakhushti Bagrationi Institute of Geography, TSU. Tbilisi, Georgia
2
School of Natural Sciences and Engineering, Ilia State University. Tbilisi, Georgia

ABSTRACTOne of the discussion issues of karstological studies is the identification of karst denudation intensity; it means
the quantitative evaluation of the intensity of this process, which, in turn, allows to predict the karst development.
The problem of karst denudation is developed insufficiently today, which can be explained by the complexity of
the issue and at the same time, the methods used to assess the intensity of denudation are not yet refined. The
intensity of denudation and its general regularities in the Zemo Imereti Plateau can be judged based on the materials
available at our disposal today, which were obtained based on field, experimental and laboratory multi-year
studies. Based on the materials obtained by comprehensive research conducted by us, we have studied andcalculated the intensity of karst denudation in the Zemo Imereti Plateau. Studies have identified that the karst
denunadation intensity (surface - 64.2-190.6 m3/km2 ; underground - 1.5-117 m3/km2 a year) in the Zemo Imereti
Plateau significantly exceeds the similar indices of Apkhazeti (values of surface and underground karst denudationin high karst strip is equal to 75-108 and 30-45 m3/km2 a year respectively, and in the foothills - 38-58 and 5-12m3/km2 a year respectively) and Askhi karst massifs (59 m3/km2 a year), which is a result of impact of technogenic
factor.
Keywords: Karst, Plateau, Massif, Technogenic factor, Denudation intensity
where: Ru – is the ion runoff, t/year; Q – stream
discharge, m3/sec; and C – is the concentration ofions, mg/l.
Different modifications of this (1) formula areused in assessing chemical denunciation in
karstology. Mostly they are based on the amount of
runoff and the calcium content in it. The intensity ofkarst denudation in the study area has been calculated
by us according to the formulas of A. Kruber [1], Zh.
Korbel [2] and M. Pulina [3].
A. Kruber (2) was one of the first who calculated
karst denudation. The mentioned author and Zh.
Korbel [2] identify the amount of chemical
denunciation by the amount of dissolved calcium
carbonate. Their formulas have the following look:
Q=31.54·103·n·a (2),where Q – is a leaked CaCO3 mass in kg/year; n –discharge, l/s; and a – CaCO3 content, gr/l.
X= 4ET
100 (3),where x- – is karst denudation value, m3/km2 peryear or mm/millennium; E– the height of runoff layer,dm; T – content of calcium carbonate in water, mg/l;

INTRODUCTION
Definition of kart denudation intensity that allows
predicting karst development is one of the discussing
problems of karstological studies.
Karst denudation problem is weakly developed ingeneral, which can be explained by the problem
complexity. Modern methods to assess denudation
intensity are not finally developed so far. For thispurpose, it is necessary to identify the rivers’
topographic and underground basins areas trueboundaries, as well as indices of rainfall amount,runoff and evaporation, to take into account themineralogical and chemical features of karstified
rocks, etc. In addition, it is difficult to get a full
picture of the real indicators of the denudation withsingle or episodic observations. Such conclusions on
the karst rivers and karst sources should be based on
seasonal observations if not on annual ones.
The intensity of denudation in the Zemo Imereti
Plateau and their general regularities can be judged
based on the materials available at our disposal today,
which have been obtained on the basis of multiannual field, experimental and laboratory studies.
The amount of ion runoff determines the rockdestruction and distribution of rock destruction
product:

4100– is the coefficient of transfer of theweight units into the volume units.

Somewhat different formula is offered by M.
Pulina (4). It has the following look:

Ru=31.54 QC (1),35

SEE - Bangkok, Thailand, Nov.11-13, 2019

D=0.0126·V·ΔT (4)where: D – is the speed of karst denudation in
m3/km2 per year or mm/millennium, ΔT- themineralization of karst waters (ΔT = T1-Ta, whereT1– is the karst waters mineralization, Ta –atmospheric precipitations mineralization), and V –runoff module from l / sec.km2.
From the results obtained from theabovementioned three methods, we believe that tothis actual situation is most fitted the results obtainedby the karst- hydrometeorological method offered by
M. Pulina, as it considers the mineralization of
atmospheric precipitations, ignoring of which gives
8-12% of error. It is also calculated not only the
number of ions in water but also the overallmineralization (mg/l). Therefore, during the analysis,
we mainlydepend on the results obtained by theformula of M. Pulina [3]. A number of papers werededicated to karst denudation in Georgia [4]-[10]. In
this respect, there is no such investigation has been
conducted in the karst region of Zemo Imereti.

Zemo Imereti Plateau includes the easternmost
part of western Georgia’s limestone strip,
characterized by its peculiar natural conditions (relief,
tectonics, climate, surface and underground waters)
and is the only region of the platform karst in Georgia[11]-[14].
The main morphological peculiarity of the study
area is determined by geological structure. The
boundary of the Zemo Imereti Plateau’s karst region
coincides with the surface of the surface contact of
the Cretaceous limestones with the older formations(Bajocian porphyritic suite in the north and east andthe Middle Paleozoic granitoids in the south andwest), which is the geological substrate of the karst.
The existence of a solid Hercynian platform
stipulated the character of layout of the MesoCenozoic suites (subhhorizontal or slightly inclined),
which is represented mainly by the ValanginianHauterivian, Barremian and Turonian-Danianlimestones, Tertiary clays and sandstones. Platform
construction of the plateau has played an importantrole in the genesis and development of surface andunderground karst forms and underground karst
streams developed here (Fig. 1, 2).

STUDY AREA

Fig. 1 Geological map of the Zemo Imereti Plateau [15].

36SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 2 Geological sections of the folded system of the southern slope of the Greater Caucasus
and the Georgian block [16].
As it is known, the intensity of the karst
processes greatly depends on the physicalgeographic and geological conditions of the region.
The amount of atmospheric precipitations and arunoff module along increase according with theincrease in altitude of the karst massifs of Georgiathat stipulate activation of karst processes. Korbel[2] and later M. Pulina’s [3] observations confirmed
this opinion by the case study of the karst regions of
the moderate and subtropical regions of theEurasian continent. Indeed, with the increase inprecipitation and runoff by altitude, the speed ofkarst denudation increases gradually. Namely,
intensity of karst denudation increases up to 4
m3/km2 in foothills and up to 8 m3/km2 – in high kart
per year when the amount of annual precipitations
increases by100 mm [3].
What is the situation on the Zemo Imereti(Chiatura) Plateau? Based on the comparison ofamount of atmospheric precipitations and theevaporability data, it may be noted that the balanceof the annual runoff is everywhere positive within
the karst strip of the study area [17], [18], whichleads to the activity of karst processes throughout
the year, especially in the cold period of the year.
Apparently, in the abovementioned trend, there may
be made corrections by technogenic factors andplay stimulating role in the activation of karst
processes that are confirmed by our studies.

The chemical composition and hydro-chemical
regime of karst waters (namely, surface streams,
karst sources and cave streams) were determined bystationary
observations
andlaboratory
investigations.
RESULTS
Based on the materials obtained by our
researches, first time was studied (calculated) the
intensity of karst denudation on the Zemo Imereti
Plateau, the results of which are given in the Table
1. The obtained data is partially based on episodic
observations, though the chemical analysis ofvaucluse sources and surface streams have been
carried out once again several times in the different
seasons of the year. In addition, detailedhydrochemical studies of karst waters were carriedout, as well as regime observations on karst sources.
Laboratory and experimental methods haveidentified the true boundaries of the areas of
topographic and underground riverbasins. At thesame time, for solution of a number of issues(substances migration, formation of composition ofunderground karst waters is formed, and etc.) the
chemical (namely, macro and micro elements ofsurface streams, karst springs and cave streams)
composition and hydrodynamic regime have been
identified by stationary observations and laboratory
studies [19], [11].
As it is known, the feature of the atmosphericprecipitation, the fissureness of karstified rocks, thelithology and others have a considerable impact on
the intensity of karst denudation. Based on the
results obtained by us, we can discuss some of thetrends that is characteristic of the karst massif ofZemo Imereti Plateau. In particular, there is a close
relation between runoff and karst denudation,
which means that karst denudation increases with
the increase of runoff (Table 1).

RESEARCH METHODS
Field, experimental and laboratory researchmethods were used in the study. Cartographic
methods were used for determination of surface
water catchment basins, and the method of painted
water tracing with special paints (indicators) todetermine the boundaries of underground basins.
The available climatic and hydrological data andthe results of our long-term observations have beenused to determine the amount of atmosphericprecipitation, runoff and evaporation indicators.
37

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 Karst denudation intensity in the Zemo Imereti Plateau.

Distribution of karst denudation by heights is
also interesting. In particular, in the study area, theincrease of karst denunal intensity is observed with
the increase of absolute height. For example, in theunderground stream (570 m above sea level) basinof the Namdzleviklde Cave, thy karst denudation
value is 1.5 m3/km2 per year, in the undergroundstream of the Shvilobisa Cave (612 m above sea
level) – 24 m3/km2 per year, in the undergroundstream of the Shekiladzeebi cave (860 m above sea
level) – 84 m3/km2 per year, and in the undergroundstream basin of the Karianiklde Cave (1300 m
above sea level – 117 m3/km2 per year.
The intensity of karst denudation is different forthe different limestone stratigraphic horizons.
Relatively low rate of denudation (1.5-5.6 m3/km2)
was observed in the areas built by Middle Miocene
limestones and marls, the average values (9.0-60.8
m3/km2) – in the areas built by Upper Cretaceous
limestones, and the highest rates (84-117 m3/km2)
in the areas built with by Barremian limestones.

It means that the intensity of karst denudation
increases more, the more pure the limestones are.
Surface streams are also distinguished by highintensity of denudation (Nekrisa River - 190.6
m3/km2 per year, Rganisghele River – 64.2 m3/km2
per year).
As hydrochemical studies of karst waters havebeen identified, the mineralization of undergroundkarst waters of the research area is 1.5-3 times
higher than the analog indicators of neighboring
karst regions. The reason for this is not only thecomplex lithological-stratigraphic structure of theregion but also the wide distribution of open pits ofmanganese ore (Fig. 3). In open pit areas (especiallyduring rainfalls) intensive washing of substancesfrom loose rocks take place [20], [21].

38SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 3 Karst relief of the Zemo Imereti Plateau transformed under the anthropogenic impact.

Due to the above reason, mineralization of karst
waters in the areas of distribution of open quarries
on the Zemo Imereti Plateau varies between 500712 mg.l-1 and occasionally reaches the anomalous
high values (Σ¡ 1052-2290 mg.l-1) [19], [11].
The sharp increase in the overall mineralizationof sources also leads to increased intensity of karst
denudation. That is why a number of deviations areobserved in the above mentioned trend. For
example, the underground water discharge of theOrmoebi Cave is the lowest among the streams wehave studied, but with the karst denudation rate
(19.1 m3/km2 per year) it exceeds the sources withexcess discharge that can be explained with a highrate of total mineralization of the undergroundstream of the Ormoebi Cave (Σ¡ = 1932 mg/l)(Table 1). By the same reason is explained the highkarst denudation rate (190.6 m3/km2 per year) of the
Nekrisa River, which is fed with highmineralization karst springs and cave streams (Σ¡1052-2290 mg.l-1 accordingly). Such high rates ofmineralization are mainly because of thewidespread of manganese open pits in theunderground karst waters feeding basins. The
influence of high mineralization is noticeable in the
distribution of karst denudation according to theheight above sea level.

CONCLUSION
Based on the research material available at our
disposal, it is possible to note that the Zemo Imereti
Plateau exceeds the Apkhazeti (in the high karst
strip the surface and underground karst denudation
values are correspondingly 75 - 108 and 30 - 45, andin the foothills – 38-58 and 5-12 m3/km2 per year)
and Askhi (59 m3/km2 per year) karst massifs with
the indices of karst denudation (surface – 64.2190.6; underground - 1.5-117.0 m3/km2) [7], [4]. In
our opinion, the higher indicators of chemical
denunciation intensity in the Zemo Imereti karst
region are related to the technogenic factors(especially the open mining of manganese): theoverall increase of water aggression, the highmineralization (mineralization of karst waters of themanganese areas is 1.5-3 times higher than the same
indices of the karst regions of Georgia) andintensive washting of substances.
In order to avoid adverse consequences during
agricultural use of karst massifs of the study area,
we consider it necessary to consider and predict
karst denudation.

39

SEE - Bangkok, Thailand, Nov.11-13, 2019[13] Asanidze L., Chikhradze N., Lezhava Z.,
Tsikarishvili K., Polk J., Chartolani G.
Sedimentological Study of Caves in the Zemo
Imereti Plateau, Georgia, Caucasus Region.
Open Journal of Geology. Scientific Research.
7. 2017a. p. 465-477.
[14] Asanidze L, Lezhava Z, Tsikarishvili K,
Chikhradze N, Polk J. Karst morphologicalprocesses and evolution of the limestone massifof Georgia from depositional, sedimentary, andstructural investigations in Muradi Cave.
Proceedings of 17th international congress ofspeleology. 2017b. Sydney, Australia.
[15] Gudjabidze GE. Geological map of Georgia,
Scale 1:500 000. (Editor: Gamkrelidze et al.).
Georgian State Department of Geology andNational Oil Company Saqnavtobi. Tbilisi,
Georgia. 2003. (in Georgian).
[16] Gamkredidze PD. The structure anddevelopment of the western part of the southernslope of the Greater Caucasus and the Georgian
block. Geotectonics, № 4. Tbilisi. 1969. (inRussian).
[17] Kordzakhia M. Climate of Georgia. 1961.
Tbilisi.
[18] Kordzakhia M. Javakhishvilisi Sh.
Evaporability in the territory of Georgia. Worksof the Vakhushti Institute of Geography, vol. 17.
1962. Tbilisi.
[19] Supatashvili G. D., Lezhava Z. I., Tintilozov Z.
K., Shioshvili L. Sh. Hydrochemical
characteristics of the karst regions of Zemo
Imereti. Bulletin of the Academy of Sciences ofGeorgia. 1990. 140, pp. 345-348.
[20] Lezhava Z., Tsikarishvili K., Asanidze L.,
Bolashvili N., Chikhradze N., Chartolani G.
Ecological Investigation of karst water in thecentral part of Georgia. Lap Lambert Academic
Publishing. Saarbrucken. 2017. ISBN: 978-6202-02210-1.
[21] Lezhava Z., Tintilozov Z., Jamrishvili A.
Technogenic factor and karst genesis on
Chiatura
structural
plateau.
Vakhushti
Bagrationi Institute of Geography, Summary
Session. 1991. Tbilisi.

ACKNOWLEDGEMENTS
This work was supported by Shota Rustaveli
National Science Foundation of Georgia(SRNSFG), grant number: №YS-18-096.
REFERENCES[1] Kruber A.A. Karst region of the mountain
Crimea. 1915.
[2] Korbel J. Annales de geographie. № 336. 1959.
LXIII, Mars-Avril.
[3] Pulina M. Geogr. Polon. №14. 1968.
[4] Jishkariani V. M. On karst denudation in thebasin of the r. Tsachkhuri (Askhi massif,
western Georgia). Bulletin of the Academy of
Sciences of Georgia, 60, №2. 1970. Tb.
[5] Abashidze E. M. Intensity of leaching of rocksof the thicket of the Shaori reservoir. Collection"Caves of Georgia". 1973. T. U, Tb.
[6] Gabechava D. Sh. Ion current and denudative
action of the karst waters of western Georgia. In
the book “Problems of hydrogeology andengineer-geology of mountainous-folded area”,№ 8. 1978.Tb.
[7] Kiknadze T. Z. Geology, hydrogeology andlimestone karst activity (case sturdy of
Abkhazia). 1979. Tb.
[8] Kochetov N. I. K. On comparative assessmentof the intensity of karst denudation of somelimestone massifs of the Western Caucasus.
Geomorphology, №2. 1983.
[9] Tintilozov Z. K. Karst caves of Georgia(morphological analysis). 1976. Tb.
[10] Tintilozov Z. The karst and cave of Bzipi
massive. Metsniereba. 1988. Tbilisi.
[11] Lezhava Z. The Karst of Zemo Imereti Plateau
and Its Surrounding Areas. Publishing House
Universali, Tbilisi. 2015. (In Georgian)[12] Lezhava Z., Bolashvili N., Tsikarishvili K.,
Asanidze L., Chikhradze N. Hydrological andHydrogeological Characteristics of the Platform
Karst (Zemo Imereti Plateau, Georgia). 14th
Multidisciplinary Conference on Sinkholes andthe Engineering and Environmental Impacts of
Karst. pp. 93-100. 2015. Rochester, USA.

40

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

RESEARCH AND DEVELOPMENT OF PILLOW FOR HEALTH IN
THAI PEOPLE: A PILOT STUDY
Panida Chaiming1, and Wichai Eungpinichpong2*
1

Ph.D candidate, Exercise and Sport Science, Faculty of Graduated School, Khon Kaen University, Thailand
2
BNOJPH Research Center, Faculty of Associated Medical Sciences, Khon Kaen University, Thailand*Corresponding author, E-mail: wiceun@yahoo.com

ABSTRACT
Proper size of pillow is an important factor in promoting quality and quantity of sleep. However, the most of
pillows available in the market are built according to the curve of the cervical spine of the people in the west which
may not be suitable for Thai people. We preliminarily determine the proper pillow size by verifying the effect of
8 cm, 10 cm, and 12 cm based on the perception of comfort, the ability to produce force of the wrist flexor muscles,
electromyography (EMG) signals of the upper trapezius muscle and wrist flexor muscle, and skin temperature ofneck. In addition, we studied on the correlation between the body height and the preferred pillow size. Thirty
healthy individuals aged 20-80 years participated. The participants underwent baseline tests. After 5 minutes, theparticipants performed the post-tests and rated on perception of comfort as they rested in the supine position with
their heads supported on three different heights of an adjustable pillow. Descriptive analysis and Spearman rank
test were used to evaluate for pillow size preference. Most of the participants preferred the 8 cm. pillow heights.
However, most of the force and EMG of the wrist flexor muscle were greatest when they rested on the 10 cm, and12 cm of pillow heights. EMG of the upper trapezius muscle and the temperature of the neck were not staticallysignificant among resting on the three of pillows. There was no correlation between the body height and thepreferred pillow size. The three pillow heights could be suitable for sleeping in Thai people.
Keywords: Pillow, Healthy, Comfortable, Thai people

neck pain, stiff neck, headache, scapula and arm pain.
They could provide the feeling of comfortable sleep,and better sleep quality when compared to pillows
made from polyester, foam, and feather [2,3,4,]. It
was possible that when people were lying on the sideon the pillows made from latex, the curvature of thecervical spine did not change much [4]. This may be
due to the properties of the latex with moderate tensile
strength, high elasticity, and good tear resistance.
In addition to the type of material used to makethe pillows, it is important to sleep on a proper
dimension of the pillow. The size, height and lengthof the pillows according to the cervical spine are also
important for sleeping. If the pillows are not suitablefor head support while sleeping, it can make thesleeper feel unwell, and neck pain. This could reflexly
result in the inhibition of arm muscle function [11].
Therefore, pillows with proper height, and fully
support the cervical spine could help increase arm
muscle strength [12].
Commonly used pillows by Thai people currently
have a variety of forms such as squares, sphericaldiscs, and wedge-shaped pillows. To prevent neckpain or help the cervical spine to be in a naturalalignment, a pillow that has a convex section fitted tothe curvature of the cervical spine and fully support
the head is needed. Most of the pillows available in

INTRODUCTION
In daily life, people need to sleep for at least 8hours, which is one third in daily life. Having good
sleep results in a better immune system of the body[1]. After a good sleep, people can work efficiently
during the day. On the other hand, insomnia or
insufficient sleep can lead to negative effects on the
body and mind such as colds, stress, other infections,metabolic syndrome, reduced performance of work,
and wrong decision [7].
To have a good sleep, proper pillow size andshape is essential for supporting the head and neck.
Prolonged use of improper pillow size and shape maylead to neck strain, headache, and chronic cervicalspine disorders. The optimal pillow size and shaperequire that the sleeper feels comfortable, relax theneck muscles, reduce core temperature of the body,and allow the cervical spine being in neutral position
during sleep. Previous studies reported that, reducingof the core temperature could decrease resting heartrate, provide deep sleep, and increase sleep quality[2,4,5,6]
Many materials, such as polyester, foam, feather,and latex, have been used to make pillows since they
could restrain the head and neck during sleep. Proper
pillows made from latex have been found to reduce
41

SEE - Bangkok, Thailand, Nov.11-13, 2019the markets are replicated from the Western countries
where the curves of the cervical spine of people aredifferent from of the Thai or Asian people withsimilar physical structure. Therefore, the researchers
are interested in developing proper pillows to suit
Thai or Asian people where physical stature, socialand cultural context is different from those in theWestern countries. Specifically, purpose of this study
was to evaluate the three levels pillow height on the
feeling of comfort, electromyography of upper
trapezius and the wrist flexor muscles of dominantlimb, skin temperature of neck while lying on thepillow, and hand grip strength. We also verify the
relationship between anthropometry of the body andthe pillow height that provide the most comfortable
sleep.

apex of the cervical lordosis curve to the wall. The
occiput-wall distance (OWD) was measured from theseventh cervical spinous process to the wall (Fig. 1).

Fig.1 The occiput-wall distance (OWD) test.
The comfortable

METHOD

Comfortable was measured by using the Visual
analog scale. Visual analog scale is a straight line of
10 cm. The left end of the scale represents the value
0, or the most comfort. The right end of the scale
represents the value of 10, or the less comfortable. All
participants were asked to rest on supine lying
position on a pillow with three height levels including
8 cm., 10 cm., and 12 cm. for 5 minutes, and marked
on this line to show comfort and values was recordedin centimeters with 2 decimals from 0-10 (Fig.2).

ParticipantsThis preliminary underwent on 30 participants.
They were healthy Thai people, aged between 20 -80
years old, and were randomly allocated in threedifferent age groups of 10 20-35 years, 36-60 years,
and61- 80 years respectively. The participants
were excluded if they had a cervicothoracic spine
injury or accident within 6 months, the dominant
upper limb injury within 6 months, cervical vertigo,
and muscle weakness of the dominant upper limb.

8 cm.

Experimental Procedure
The study was approved by the Institutional
Review Board of the Khon Kaen University Ethics
Committee in Human Research (HE592390). All
participants were received informed consent. This
study was a cross sectional study. All participants
were asked to test the anthropometry, comfort levelof each pillow height, and the electromyography ofupper Trapezius muscle and the wrist flexor muscleof the dominant upper limb, hand grip strength andskin temperature, respectively.

10 cm.

12 cm.

Fig. 2 A pillow, three height levels as 8 cm., 10 cm.,and 12 cm.

Measurements

The Electromyography (EMG)

The anthropometry
A researcher attached electrodes to both sides ofupper trapezius muscles, and the wrist flexor musclesof the dominant upper limb. The participants wereasked to rest in the supine lying on the pillows withthree height levels for 5 minutes/level. The EMG test
was repeated three times with 1-minute rest intervals
between the trials. Cometa Wave Plus Device(Cometa®, Bareggio, Italy) was used as surfaced
EMG in this study. The mean value of the three trials

The anthropometry of the neck in this study
included neck length, neck thickness, and the occiputwall distance (OWD). The neck measurements were
tested the participant's neck position in the neutral
while standing erectly. Neck length was measured
from the external occipital protuberance to theseventh cervical spinous process. Neck thickness wasmeasured while the participant standing erectlyagainst the wall, by measuring the length from the42

SEE - Bangkok, Thailand, Nov.11-13, 2019the relationship between the anthropometry and theheight of the pillow that was most comfortable. The
statistically significant level is p < 0.05. SPSS version
17 was used to analyze data in this study.

was used (Fig. 3).

RESULT
Thirty individuals participated in the study.
Demographic and clinical characteristics of theparticipants are presented in Table 1.
Table 1 Demographics
andmeasurements of the participants.

anthropometric20-35 (y)36-60 (y)61-80 (y)Age (y)26±3.745±7.969.9±5.3
Sex (M/F)
3:7
3:7
0:10
Body length
1.6±0.1
1.6±0.1
1.5±0.1(m)
Body
65.1±18.1 66.2±11.2 56.09±5.5weight (kg)BMI
24.3±5.1
25.7±2.923.5±2.6(kg/m2)
Neck length10.8±1.3
10.6±1.6
8.9±1.1(cm)
Neck
6.6±1.3
7.2±1.1
6.9±1.4
thickness(cm)
OWD (cm)5.2±1.55.4±1.85.3±1.5
Data are presented as n or mean ± standard deviation.
BMI = body mass index; F = female; M = male.
The occiput-wall distance = OWD

Fig. 3 Electrodes on the upper trapezius muscles bothsides, and the wrist flexor muscles of the dominant
upper limb
The hand grip strength
All participants were asked to rest on the supine
lying on the pillows with three level heights andmeasured the hand grip strength for three times with
1-minute rest intervals between the trials. The meanvalue of three repetitions was used (Fig. 4).

The Effectiveness of Health Pillows for Thai
People Aged 20-80 Years
Fig. 4 The hand grip strength test

Age 20-35 years group

The skin temperature
The distribution of skin temperature wasmeasured every 2 minutes with the Thermograph at
pillow after rest supine lying on three pillows. The
mean value was recorded.

The comfortable, the EMG of the upper
trapezius muscle and the wrist flexor muscle of thedominant upper limb, the hand grip strength, and theskin temperature were not significantly different
between the three-pillows (p > 0.05) in Table 2.

Statistical Analysis

Age 36-60 years group

Descriptive statistics were used to determine theclinical characteristics and anthropometric data of theparticipants. The one-way repeated measures analysis
of variance (ANOVA) statistics was used todetermine the effects of pillow height on theanthropometry, comfortable, EMG, hand grip
strength, and skin thermometer with mean, standard
deviation or percentage data. The Spearman Rank
Correlation Coefficient statistics were used to analyze

The pillow height at 8 cm. was the most
comfortable (p < 0.05). On the other hand, the EMG
of the upper trapezius muscle and the wrist flexor
muscle of the dominant upper limb, the hand grip
strength, and the skin temperature were not

43

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 The Effectiveness of Health Pillows for Thai People Aged 20-80 Years.
Age (y)The pillow
height (cm)20-35 group36-60 group61-80 group

8

10

12

8

10

12

8

10

12

Comfortable
(cm)

2.27
±1.35

2.19
±2.05

2.56
±1.84

1.59
±1.66*

2.56
±2.41

3.74
±2.41

2.39
±1.71

2.4
±1.63

2.55
±2.06

EMG of Rt.
upper
trapezius m.
(µV)

2.2
±0.63

2.2
±0.42

2.2
±0.63

2.1
±0.31

2.4
±0.70

2
±0.00

2.2
±0.42

2.3
±0.48

2.3
±0.68

EMG of Lt.
upper
trapezius m.
(µV)

3
±0.67

3
±0.67

2.9
±0.99

3.2
±1.48

3.8
±1.03

3.5
±0.71

3.5
±1.65

3.8
±1.03

3.5
±1.72

EMG ofwrist flexor
m. (µV)

74.6±30.02

68.3±20.8773.8±30.2063.7±20.02

67.9±16.31

63.7±18.6769.2±26.14

66.3±26.12

62.7±20.48Forces ofwrist flexorm. (kg)26.05±10.45

24.99
±8.01

25.42
±11.17

27.91
±8.76

28.77
±8.37

26.34
±9.67

20.72
±3.46

21.18
±4.09

20.88
±3.96

Skin
temp.(oc)

35.11
±0.97

34.94
±0.88

35.19
±0.70

34.92
±0.87

34.84
±0.84

34.82
±0.80

33.82
±1.24

34.4
±1.10

34.56
±1.03

Data are presented as n or mean ± standard deviation.
* between group sig. p < 0.05
DISCUSSION

significantly different between the three-pillows (p >0.05) in Table 2.

This research aimed to study and develop healthpillows for Thai people with a physical structure andThai social and cultural context. The objectives wereto test the health pillows for three level heights on the
comfortable, EMG, hand grip strength, skintemperature, and the relationship between theanthropometry and the pillow height that the most
comfortable.

Age 61-80 years group
The comfortable, the EMG of the upper
trapezius muscle and the wrist flexor muscle of thedominant upper limb, the hand grip strength, and theskin temperature were not significantly different
between the three-pillows (p > 0.05) in Table 2.

The Pillow Heights on The Comfortable
The Relationship Between the Anthropometry
and The Height of The Pillow That the Most
Comfortable

The height level of pillows that the participants
feel the most comfortable was 8 centimeters, which
was consistent with Wang JC et al [12]. They
conducted by asking participants to rest in the supine
lying on 11 pillows of different height, and thenchoose the pillow that feels the most comfortable.
They found a pillow height at 8 cm. was the most
comfortable. Inconsistent with Sacco IC et al [9],studied the participants by lying on three pillow
height 5 cm. 10 cm. and 14 cm. They measured the
comfortable while lying on the pillow for 5
min/pillow height. They found the participants lying

There is no relationship between theanthropometry (neck length, neck thickness, andoccipital to the wall) and the height of the pillow thatwas most comfortable of the three age groups (p >0.05).

44

SEE - Bangkok, Thailand, Nov.11-13, 2019

on a pillow height 10 cm. feel the most comfortable
when comparing the height of other two pillows. The
length of the cervical spine of the participants tended
to decrease by their. The pillows with a height of 8
cm. were the height that could be recommended forThai people to sleep for health.

inducing relaxation and the heart rate to slow down.
Therefore, it did not affect the temperature reductionof the head while lying on the most comfortablepillow.
The Relationship Between the Anthropometry
and The Pillow Height That the Most Comfortable

The Pillow Heights On EMG
The three age groups had no relationship between
the anthropometry (neck length, neck thickness, andoccipital to the wall) and the height of the pillow thatwas most comfortable. It corresponded to Wang JC,
et al [12], which allowed the participants to rest on 11
pillows of various heights and chose the pillows thatthe most comfortable. They found that theanthropometry had the relationship with the most
comfortable pillow. However, this study found thatthe anthropometry was not related to the pillow thatfeels comfortable.

The EMG of the upper trapezius muscle, and thewrist flexor muscle of the dominant upper limb were
not significantly different between the three pillows
which is consistent with Sacco IC et al [9]. They
studied the EMG signal of the sternocleidomastoid
muscle, and upper trapezius muscle; the EMG was
not significantly different between lying on the threepillows. However, Sacco IC et al [9] found that the
EMG of the middle trapezius muscle was reduced
when lying on the pillow with the height that feels
most comfortable. On the other hand, Wang JC, et al[12] found that the pillows that the most comfortable
had the highest EMG signal in wrist extensor muscle.
However, EMG signal of the wrist flexor muscle alsotended to increase in the pillow height level that themost comfortable in participants age 61-80 years
group of this study had.

CONCLUSIONSThe three pillow heights could be suitable forsleeping in Thai or Asian people who have similar
physical stature . Study in the future should be doneon a larger sample size to get a clearer answer.

The Pillow Heights on The Hand Grip Strength

ACKNOWLEDGMENTS

The pillow height could affect the cervical spine
causing uncomfortable sleep and resulting reflex-type
muscle inhibition of the upper extremity. Inhibition
has been frequently in muscles that cross the joints
owing to joint pathology [8]. However, previous
studies demonstrated that muscle inhibition due tospinal dysfunction can occur in muscle groups thatare not directly connected to the spine. Suboptimal
cervical alignment due to an uncomfortable pillow
may produce sensory inputs and therefore affect thenormal function to the muscles of the upper extremity[10,11]. In this study, muscle forces of the hand grip
strength were not different between the pillow
heights. Inconsistent with Wang JC, et al [12] foundthat the pillows that the most comfortable effected tothe highest forces in wrist extensor muscle. Due to thesmall sample size of this study, the results may beobserved with only some degree of difference of wrist
flexor muscle forces between the pillow heights.

This work was supported by the Research Fundfor Supporting Lecturer to Admit High Potential
Student to Study and Research on His Expert
Program Year 2017, graduate school of Khon Kaen
University, THAILAND.
REFERENCES[1] Faraut Brice., Boudjeltia Karim Zouaou.,
Vanhamme Luc., Kerkhofs Myriam., Immune,inﬂammatory and cardiovascular consequencesofsleep
restriction
andrecovery,
Sleep Medicine Reviews, Vol. 16, Issue 2, 2012,
pp. 137-149.
[2] Gordon Susan J., Grimmer-Somers Karen.,Trott Patricia., Pillow use:
The behaviour of cervical pain, sleep quality and pillow comfort in side sleepers. Manual
Therapy, Vol. 14, Issue 6, 2009, pp. 671-678.
[3] Gordon Susan J., Karen A Grimmer-Somers.,
Patricia H Trott., Pillow use: the behavior of
cervical stiffness, headache and scapular/arm
pain. Journal of Pain Reseasrch. Vol. 3, 2010,
pp. 137–145.
[4] Gordon. Susan J., Karen A Grimmer-Somers.,
Patricia H Trott., A randomized, comparative
trial: does pillow type alter cervicothoracic
spinal posture when side lying?. Journal of

The Pillow Heights on The Skin Temperature
The skin temperature of the three-pillow height
was not different which is not consistent with Jeon etal. [6]. Jeon et al. found that proper pillow must be
reduced the temperature of the head or body coretemperature and causing the heart rate to slow down
and sleep deeper. Due to this study asked theparticipants to lying 5 minutes/pillow height, it might
be that experimental period was not long enough for
45

SEE - Bangkok, Thailand, Nov.11-13, 2019

[5]

[6]

[7]

[8]

Multidisciplinary Healthcare, Vol. 4, 2011, pp.
321–327.
Gordon, Susan J., Grimmer-Somers, K., Your
Pillow May Not Guarantee a Good Night’s
Sleepor
Symptom-Free
Waking. PHYSIOTHERAPY CANADA; SPR,
Vol. 63, Issue 2, 2011, pp. 183-190.
Jeon, MY., Jeong, H., Lee, SW., Choi, W., Park,
JH., Tak, SJ., Choi, DH., Yim, J.,
Improving the Quality of Sleep withan Optimal Pillow:
A
Randomized,
Comparative Study. TOHOKU JOURNAL OF
EXPERIMENTAL MEDICINE, Vol. 233, Issue
3, 2014, pp. 183-188.
Kyle, Simon D., Morgan, Kevin., Espie, Colin
A., Insomnia and health-related quality of life.
Sleep Medicine Reviews, Vol. 14, Issue 1, 2010,
pp. 69-82.
Rice DA., McNair PJ., Quadriceps arthrogenic
muscle inhibition: neural mechanisms andtreatment perspectives. Seminars in Arthritis

Height on Muscle Activity of The Neck And
Mid-Upper Back and Patient Perception of
Comfort. Journal of Manipulative &Physiological Therapeutics. Vol. 38, Issue 6,2015, pp. 375-381.
[10] Suter E., Lindsay D., Back muscle fatigability is
associated with knee extensor inhibition in
subjects with low back pain. Spine, Vol. 26,
Issue 16, 2001, pp. 361-366.
[11] Suter, E., McMorland, G., Decrease in elbow
flexorinhibition
after cervicalspine
manipulation in patients with chronic neck
pain. CLINICAL BIOMECHANICS, Vol. 17,
Issue 7, 2002, pp. 541-544.

[12] Wang, Jia-Chi., Chan, Rai-Chi., Wu, HanLin., Lai, Chih-Jou., Effect of pillow size
preference on extensor digitorum communis
muscle strength and electromyographic
activity during maximal contraction in
healthy individuals: A pilot study. Journal of
the Chinese Medical Association, Vol. 78,
Issue 3, 2015, pp. 182-187.

and Rheumatism, Vol. 40, Issue 3, 2010, pp.
250-266.
[9] Sacco Ic., Pereira Il., Dinato Rc., Silva Vc.,
Friso B., Viterbo Sf., The Effect of Pillow

46

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE IMPACT OF URBANIZATION ON THE WATER QUALITY OFUTTARA LAKE, DHAKA – CASE STUDY.
1*Shama Emy Haque1 and Farhana Aktar2
Associate professor, North South University, Bangladesh;
2
North South University, Bangladesh

ABSTRACTThis study evaluates the water quality of Uttara Lake in Dhaka to understand the impacts of urban
environment in a developing country. In recent years, the lake has suffered episodes of fish kills, which havebeen described by the local media and residents as cases of intentional poisoning of the water body. To
evaluate Uttara Lake’s water quality, a series of water samples were collected and analyzed for various water
quality parameters (e.g., temperature, pH, conductivity, alkalinity, turbidity, total dissolved solids, dissolved
oxygen, chemical oxygen demand and biochemical oxygen demand, concentrations of dissolved phosphateand nitrate). The results indicate that the majority of the water samples exceed the Bangladesh Environment
Conservation Rules (1997) standards for various water quality parameters. Here, the water quality data arepresented to determine the possible mechanisms responsible for the reported fish kills and determine whether
the water quality is suitable for its intended uses.
Keywords: Urbanization, Lake, Surface Water, Water Quality, Eutrophicationof Uttara Lake, which is located in Uttara Model
Town, a northern sub-administrative district and a
suburb of Dhaka (Fig. 1). Uttara Lake is one of themain lakes in the City. Until the 1990s, Uttara
Model Town was considered a generally quiet
neighborhood. However, in recent years, it has
been transformed into a densely populated
neighborhood to accommodate the increasing
influx of people moving in from the city. Currently,
the neighborhood accommodates high-riseapartment buildings along with hospitals, shopping
complexes, garment factories, and educational
institution [18].
Over the years, fish farming or pisciculture hascontinued in Uttara Lake at various capacities.
Initially, the local Ministry of Fisheries permitted
fish farming in the lake water; however after the
recent fish kill episodes, the permission was
revoked. In recent years, episode of fish kills havebeen reported by local residents and also throughthe local media [19]-[21]. The term ‘fish kill’refers to any sudden and unexpected massmortality of wild or cultured fish over a shortperiod of time [22]. The most recent fish kill
episode has been explained by the local media andresidents as alleged ‘poisoning’ of the lake water
resulting from dispute related to lease of the lake
for fish cultivation. During field investigation, it
was noted that numerous effluent channels drain
into the lake carrying contaminated water. Basedon observation and discussion with local fishermen,
it is our understanding that illegal fish farming still
continues throughout the lake.

INTRODUCTION
The total population of Bangladesh is estimatedat 159 million and its population is growing
annually at 1.37% [1]. A large portion of the
population is migrating to Dhaka, the capital of
Bangladesh for better employment and investment
opportunities [2]. The trend towards urbanization
along with encroachment of water bodies, rapid
industrial expansion, overloaded infrastructure andineffective
enforcementofenvironmental
regulations have all taken their toll on the water
quality of the city’s hydrographic network [3]-[4].
Nine industrial areas (Tongi, Tejgaon, Hazaribagh,
Tarabo, Narayanganj, Savar, Ghorashal, Gazipur,
and Dhaka export processing zone) neighboring
the city have been identified to be the primarycontributors to river pollution [5]. Locally, 10% of
the industries discharge treated effluent whereas
the remainder of the industries discharges effluent
into the water bodies without any treatment or withminimal treatment [6]. Due to insufficient sewage
treatment facilities 72% of sewage generated alongwith storms-drainage is discharged to theenvironment and make their way into the Dhaka’s
surface water bodies untreated and eventuallyleach into the groundwater system [7]-[9].
In the past few decades, the surface water-bodyareas in and around Dhaka has significantly
reduced and has also been polluted due to rapid
urbanization [10]-[12]. Well documented cases ofpollution of surface water bodies by domestic,
industrial and agricultural effluent are reported
from various parts of the city [13]-[17].
This contribution focuses on the water quality
47

SEE - Bangkok, Thailand, Nov.11-13, 2019

Jasimuddin Avenue and by Ashulia, a suburban
area, respectively (Fig. 2). The length and averagewidth of the lake is 2.35 km and 62 m, respectively,
and the mean depth of the lake is 4.1 m [21].
Originally, the lake was designed to prevent water
logging of the area during the wet months of theyear. However, over the years, encroachers havefilled up a portion of lake near the southeasternpart near Sector-3.
The first water sample was collected fromsampling location 1, which is located 0.25 km
north from Jasimuddin Avenue (Fig. 2). Seven
additional water samples were collected from thelake in a general northerly direction towards theTurag River. Specifically, sampling locations, 2, 3,
4, 5, 6, 7 and 8 are located at ~0.53 km, 0.82 km,
1.13 km, 1.36 km, 1.55 km, 1.77 km and 1.90 km,
respectively, northwards commencing from
Jasimuddin Avenue (Fig. 2). Following sampling
location 8, the lake curves and turns towards thewest. Two additional samples were collected fromsampling locations 9 and 10 that are located in thewesterly portion of the lake at 2.13 km and 2.31
km, respectively from Jasimuddin Avenue (Fig. 2).

Fig. 1 Map of Bangladesh showing location of
Dhaka (modified from [4] and Google Maps).
In the past, the Department of Environment(DoE), Dhaka measured the dissolved oxygen(DO) and biochemical oxygen demand (BOD)
values of Uttara Lake water, which were reported
to be 0.6 mg/L and 15.07 mg/L, respectively [21].
To the best of our knowledge there is no further
information available about the lake’s hydrogeochemistry and the lake’s residence time.
The study aims to investigate, examine andevaluate the water quality of the lake anddetermine the possible circumstances for fish kill.
To achieve the goal, a series of surface water
samples were collected and analyzed for various
water quality parameters such as temperature, pH,
conductivity, alkalinity, turbidity, total dissolved
solids (TDS), DO, chemical oxygen demand(COD) and BOD5 along with concentrations of
dissolved phosphate (PO4) and nitrate (NO3).
Measurements of these water quality parameters
are expected to determine whether the quality of
the water is suitable for the health of the naturalenvironment and the uses for which the water isrequired [23]. The results of the study are expected
to provide the foundation for further research on
the water quality of the lake. The results are
expected to serve as a reference to assist relevant
agencies to take positive steps to improve thelake’s water quality and to restore the environment.

Fig. 2 Uttara Lake water sampling locations(modified from RAJUK and Google Maps).

STUDY AREASAMPLING TECHNIQUES

Uttara Model Town is a planned square grid
residential suburb, geographically elevated fromsouthern Dhaka and is divided into several‘sectors’. The suburb is planned by Rajdhani
Unnayan Kartripakkha (RAJUK), which is the
Capital Development Authority of the Governmentof Bangladesh, and divided into 14 sectors (sector
1 to sector 14). The peripheral areas of the lake aresectors 3, 5, 7, 9, 11 and 13 (Fig. 2). At thesouthern and northern ends, the lake is bordered by

The sampling event took place in February of
2018, which falls during the dry months of theyear (November to May). During the wet season,
influx of rainwater into the lake causes dilution ofwater. Thus, sampling was done during the dry
season that is the yearly period of low rainfall. Ten
water samples were collected from midstream andfew centimeters below the surface using clean 1 L
polyethylene bottles. For each sample, the bottle
48

SEE - Bangkok, Thailand, Nov.11-13, 2019was rinsed three times with lake water. Afterrinsing, the bottle was submerged below the waterlevel to allow it to fill completely to the top withminimum disturbance. All sample bottles werestored in the dark and ‘on ice’ at ~4◦C [24]-[25],and were transferred to the DoE Laboratory for
immediate chemical analysis.

in mg/L (Table 1), with a mean value of 276 mg/L.
The mean alkalinity value of the lake water
samples are below the Bangladesh (1997)
guidelines of 50-300 mg/L for fisheries.
Table 1 Uttara Lake’s water quality data: pH,
Conductivity (Cond), Alkalinity (Alk; expressed as
CaCO3 in mg/L), Turbidity (Turb), Total
Dissolved Solids (TDS).

ANALYTICAL TECHNIQUESA HACH HQ40D portable multi-meter wasused to determine temperature, pH, EC and TDS.
The Winkler test method was employed todetermine the DO levels. To determine theturbidity a Hanna HI 83414 turbidity meter was
employed. Biochemical oxygen demand and COD
were measured using a Lovibond incubator(incubation at 20◦C) and a HACH DRB200 COD
reactor, respectively. Dissolved PO4 and NO3levels were determined using a HACH DR 2700
portable spectrophotometer. Analytical instruments
were calibrated in accordance with the
manufacturer instructions prior to sample analysis.

Sample

pH

1
2
3
4
5
6
7
8
9
10

7.14
7.20
7.02
7.20
6.92
6.60
6.98
7.06
6.58
6.61

RESULTS AND DISCUSSION

The turbidity values range from 18.2 to 118
NTU, with a mean value of 46.6 NTU. The ECR1997 does not list a turbidity standard for inland
waters for fish farming. However, others havesuggested that turbidity should be <50 NTU forlakes for aquatic life [27]. The water sample
collected at location 6 is characterized with thelowest pH value of 6.60 and highest turbidity valueof 118 NTU (Table 1). Here, domestic waste water
is directly discharged into the lake water through adrainage pipe and field observation indicatesvisible algal bloom. Increased growth in algae cancause an increase in the turbidity of water and cancreate odors problems [29], both of which wereobserved in the collected samples.
The TDS values range from 240 to 364 mg/L,
with a mean of 305 mg/L. There is no ECR (1997)
standard available for TDS for fisheries [26],however according to WHO (1996; [30]), theacceptable range for TDS for fisheries is 0-1000
mg/L. In general, The TDS values appear toincrease after sampling location 5 and towards toTurag River. At location 6, the TDS value is at
maximum. Here, the direct discharge of domestic
waste water into the lake likely plays a key role in
the increase in TDS values. Total dissolved solid
values have strong positive correlation with EC (r= 0.99) and turbidity (r = 0.78).
Oxygen parameters were determined to assess
the biological and industrial pollution of Uttara
Lake. The DO values range from 0.00 to 7.10
mg/L, with mean value of 2.98 mg/L. Dissolved
oxygen levels were below detection at locations 6

The temperatures of the water samples range
between 21.7 and 22.1◦C, with a mean value of
21.9◦C. The variations in water temperature wererelatively small from one site to another. It is wellestablished that the water temperature influences
the amount of DO present; less O2 dissolves inwarm water than cold water. Water temperature is
an important parameter of water quality (especiallyfor DO) for the survival of aquatic organisms
especially fish are sensitive to temperature changes
in the water.
The sampled waters are near-neutral, with pH
values ranging from 6.58 to 7.20 (Table 1), with amean value of 6.93. More specifically, pH exhibits
an initial increase from 7.14 to 7.20 in the first
0.53 km, before decreasing to pH <6.58 at 2.13
km. The pH values fall within the Environment
Conservation Rules (ECR, 1997) of Bangladesh
standards for pH range of 6.5 to 8.5 for inlandsurface water.
Electrical conductivity values range from 465
to 698 μS/cm (Table 1), with a mean value of 587
μS/cm. The EC values of all water samples arewell below the Bangladesh standard (800-1000
μS/cm) for pisciculture [27]. Note that EC of mostnatural water generally ranges from about 50 to1500 μS/cm [28].
In almost all natural waters, alkalinity is due tothe presence of certain ions: carbonates,
bicarbonates, and hydroxides in water. Alkalinity
is important for aquatic life as it protects themagainst rapid changes in pH. Alkalinity values
range from 204 to 348 mg/L expressed as CaCO3
49

Cond
μS/cm
497
490
465
465
575
698
680
670
658
673

Alk
mg/L
206
216
204
208
264
330
348
312
338
332

Turb
NTU
23.1
18.2
18.2
22.1
29.2
118
48.0
34.0
73.4
84.5

TDS
mg/L
258
253
240
240
299
364
354
349
342
349

SEE - Bangkok, Thailand, Nov.11-13, 2019

and 10 (Table 2), which is indicative of anexcessive demand on the DO in the water. At
location 2, the measured DO value is 7.1 mg/L,
which is significantly higher than that of at theother locations (Table 2). Note that compared to
the remainder of the sampling locations, thisportion of the lake water appeared to relatively
clear and garbage free. The ECR (1997) standardsof DO for inland surface water bodies suggest aminimum DO requirement of 5 mg/l for different
purposes including fish farming [26]. As
mentioned earlier, in recent years, the lake has
suffered from episodes of fish kills. In overenriched lakes ‘algal blooms’ can occur, which aresurface accumulations of free-floating or attachedeukaryotic algae or cyanobacteria [31]. As themasses of algae decay, they can disturb the DO
regime of the lake water. As algae carry out
photosynthesis they consume CO2 and release O2
to the water body. During night, however, thealgae respire and consume DO and the DO levels
may become low enough to cause fish mortality.
The reduced DO values are likely to have negative
influence on the aquatic life of the lake.
The COD values of the lake water range from44.0 and 439 mg/L. There is no ERC (1997) COD
standard for fisheries but the ECR (1997) COD
standard for waste from industrial units is 200
mg/L [26], which is lower than the mean BOD
value of 207.9 mg/L, which gives an indication of
the levels of organic pollution. The results show
positive correlation parameters between COD and
BOD5 values (r = 0.66), and COD and turbidity
values (r = 0.86). The maximum COD value of
439 mg/L was measured at location 10 (Table 2).

project that aims to determine the water andsanitation condition of Uttara Lake slum. In the
bigger project, analysis of total and fecal coliform
bacteria (i.e., the primary indicator of potability ofwater) is currently being carried out. Near location
9, a hospital dumps medical waste into the lake.
Moreover, there are numerous hidden drainage
pipes that are illegally discharging untreated waste
water into the lake [21]. At location 10, waste
water is directly discharged into the lake through adomestic sewage pipe and the lake water appeared
to be black with a denser consistency.
The BOD5 values range from 23 mg/L to 68
mg/L (Table 1), with mean of 45.2 mg/L. The
BOD5 values of all water samples are significantly
higher than the Bangladesh standard for
pisciculture (<6 mg/L) and recreation (3 mg/L;[26]. In general, the lake water is characterized byrelatively low DO levels and elevated levels of
BOD5, which indicate significant organic
pollution. A negative correlated parameter was
found between BOD5 and DO values (r = -0.38).
The BOD5 value is the highest at location 9 andthe DO values are low in these waters (Table 2).
The waste disposal activities of slum dwellers arelikely a major factor dictating the observed trend inthese water quality parameters. The consequencesof elevated levels of BOD are the same as those forlow DO: aquatic organisms become stressed,
suffocate, and eventually die [28]. The sampled
water from locations 1, 5 and 7 have relatively low
DO values against relatively low BOD values.
Currently, there is no physical evidence available
for this observation.
Concentrations of PO4 range from 29.1 to 54.4
mg/L (Table 2), with a mean value of 41.7 mg/L.
The highest PO4 level was found in water sample
collected from location 10. The source of PO4 in
surface water can be natural or anthropogenic
depending on the activities occurring in theneighboring area [32]. In nature, phosphorus (P)occurs in rocks and mineral deposits and during
the natural weathering processes the rocks release
the P as PO4 ions. Dissolved PO4 can also be
introduced into water bodies due to usage of PO4
based detergents, septic tank failure, fertilizer
runoff and improperly treated waste-water. The
ECR (1997) does not list a standard for PO4 in
inland surface water [26], however others haveindicated that a value of >10 μg/l of PO4-P isindicative of eutrophication [33] and the PO4 levelsof Uttara Lake are well above this level. Elevated
PO4 levels in surface water have been linked toaccelerated rates of plant growth, changes in
species composition and proliferation ofplanktonic, epiphytic and epibenthic algae [34]-Table 2 Uttara Lake water quality data: Values ofoxygen parameters and dissolved PO4 and NO3.
Sample

DO
mg/L

COD
mg/L

BOD5
mg/L

1
2
3
4
5
6
7
8
9
10

2.30
7.10
6.80
6.30
0.70
0.00
0.30
6.10
0.20
0.00

130
44.0
191
108
152
351
206
196
262
439

30.0
27.0
23.0
56.0
38.0
65.0
24.0
54.0
68.0
67.0

PO4
mg/L
29.1
30.8
30.7
43.8
43.1
48.2
44.0
48.1
44.8
54.4

NO3
mg/L
4.00
7.10
5.50
2.90
4.70
8.20
8.10
6.80
7.90
8.70

The residents of slums located between
sampling locations 8 and 9 dispose of theirhousehold waste along with human wastes into
these water. Note that this study is part of a bigger

50

SEE - Bangkok, Thailand, Nov.11-13, 2019[35]. The bacteria responsible for decompositionof the dead algal mass can use up and deplete DO
to such levels that it can result in fish kills [32].
The levels of NO3 range from 2.90 to 8.70
mg/L, with a mean value of 6.39 mg/L. Numerous
past studies have indicated that in surface waters,
the NO3 levels remain generally low, ranging from0 to 18 mg/L [36]-[37]. Note that NO3-N levels>1.5 mg/L indicate a hyper-eutrophic condition[32], [38]. The mean value of NO3 is of 6.39 mg/L
indicates that the lake waters are hyper-eutrophic,
which suggests that due to excessive nutrients, thewater body is able to support an abundance ofaquatic plants or algae. Dissolved NO3 levels canbe elevated due to runoff of agrochemicals, sewage
leak, refuse dump runoff, runoff from animal
manure storage areas [32], [37]. There are several
nurseries located along the lake that uses inorganicand organic fertilizers along with agrochemicals.
Data analyses indicate that dissolved PO4 wasmore concentrated than NO3 (Table 2). A possible
explanation
underlying
theconcentrationdifferential is likely the unique behavior of P inshallow waters. In general, lakes have relatively
long retention times and store large amounts of P
in their bottom sediments. When a lake becomeseutrophic, the waters at the lake bottom are more
likely to become anoxic during the growing
season. In turn this process tends to rapidly
regenerate the soluble PO4 from the bottom
sediments and this dissolved P is then released tothe surface waters in shallow lakes [39].

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[3] Bodrud-Doza M., Islam A.R.M.T., Ahmed F.,
Das S., Saha, N., and Rahman M.S.,
Characterization of groundwater quality using
water evaluation indices, multivariate statistics
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[4] Haque S.E., An Overview of Groundwater in
Bangladesh, Mukherjee, A. (ed) Groundwaterof South Asia, Springer Publishing Company,
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[5] Kibria M.G., Kadir M.N., and Alam S.,
Buriganga River Pollution: Its causes andimpacts, International conference on recent
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CONCLUSION
The analyzed water quality data indicate that
Uttara Lake is hyper-eutrophic and the water is notsuitable for pisciculture. The results suggest thatthe majority of the samples exceed the Bangladesh
ECR (1997) standards for various water quality
parameters. The results indicate that unplanned
urbanization and improper disposal of untreatedwaste from various sources is contributing to thedegradation of the water quality of lake’s water.
ACKNOWLEDGMENTS
We acknowledge Mr. Md. Enamul Quadir,
Project Manager of Uttara Lake Development
Project, for his support. The authors thank Mr. MD.
Raisul Mondal for assistance with sample analyses.
The authors sincerely appreciate Mr. Mahbub
Haque for his valuable guidance. The authors
thank Mr Ashrful Alam for his help with editing.
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52

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE EFFECTS OF COMBINED ELECTRICAL STIMULATION WITH SHORTFOOT EXERCISE ON MEDIAL LONGITUDINAL ARCH AND INTRINSIC FOOTMUSCLE SIZE: A PILOT STUDY
Juntip Namsawang 1, Ratana Vichiansiri 2, Wichai Eungpinichpong 3, and Somchai Rattanathongkom1
1
Faculty of associated medical sciences, KhonKaen University, Thailand;2
Faculty of medicine, KhonKaen University, Thailand;
3
BNOJPH Research Center, Faculty of associated medical sciences, KhonKaen University, Thailand
ABSTRACTThe important function of the intrinsic foot muscles is the dynamic stabilization of the medial longitudinal arch
(MLA). Several studies have reported that implementing strengthening exercises amid the intrinsic foot muscles
may increase MLA height. Functional electrical stimulation may also enhance muscle strength. Nevertheless, theeffect of electrical stimulation (ES) in combination with short foot exercise (SFE) as an exercise method amid
intrinsic foot strengthening has to date, not been shown. Hence, the aim of this study was to compare the effectsof combined ES and SFE versus SFE alone on navicular drop (ND), in addition to the cross-sectional area (CSA)of the abductor hallucis (AbdH) muscle. Ten healthy female subjects were randomly assigned to undergo combined
ES with SFE (n=5) or SFE with sham ES (n=5). Both groups performed 30 repetitions of SFE followed by 20
minutes of ES per day, 3 days a week, for 4 weeks. ND and the CSA of the AbdH muscle were assessed before
and after intervention. The results showed that combined ES with the SFE group significantly decreased in ND
after training (p<0.05). However, there were no significant differences between the two groups. The CSA of the
AbdH muscle in both groups was increased (ES with SFE=10.93 mm2and SFE=7.44 mm2; p<0.05) but without
significant differences between the groups. These results demonstrated that ES with SFE and SFE alone could
improve intrinsic foot muscle size. Nevertheless, combined ES with SFE tended to increase MLA more than SFE
alone. Hence, ES in combination with SFE may be used as an alternative treatment to increase MLA and intrinsic
foot muscle size.
Keywords: electrical stimulation, short foot exercise, medial longitudinal arch, intrinsic foot muscles

navicular drop (ND). The height of the navicular boneserves as the key to the MLA. Moreover, previous
studies demonstrated that muscle strength hadsignificant correlation with cross-sectional area
(CSA) [9]. IFM weakness and atrophy commonly
result in several conditions such as plantar fasciitis[10], hallux valgus, and pes planus [11]. Pes planus,
in particular, is associated with heel eversion andforefoot abduction. In the long term, these changes
may be a cause of overuse injuries [12], functional
limitation, and disability [13]. Therefore, therehabilitation and prevention of these problems are
resultant of necessarily reinforcing IFM strength
aimed at improving MLA.
Several studies have reported the beneficial
effects of IFM training, especially short foot exercise(SFE) on navicular drop [10] and the cross-sectional
area of the abductor hallucis muscle (AbdH) [12].
Jung et al. reported that SFE can improve IFM
activity and prevent the fall of MLA [14].
Today, functional electrical stimulation is analternative method for the rehabilitation of aparalyzed muscle as well as strength promotion [15]because this treatment has the ability to isolate
contraction of the desired muscle group [16]. A study
by Fourchet et al. [17] found that neuromuscularelectrical stimulation of the abductor hallucis (AbdH)

INTRODUCTION
The foot is an importantly complex structure
which serves as the propulsive organ and supporting
pedestal during weight bearing throughout
locomotion [1]. Foot function efficiency depends on
the integrity of the medial longitudinal arch (MLA)[2].
The MLA is the primary structure responsible forstability and resiliency of the foot load [3]. Archconfiguration can be maintained via passive andactive support. The most significant static
contributors are the plantar fascia, the long and shortplantar ligaments, and the spring ligament. Whereas,
the intrinsic and extrinsic foot muscles play a role indynamic contributors [4]. However, recent evidence
has suggested that the intrinsic foot muscles (IFM)
play a crucial role in supporting MLA [5]-[6]. What’smore, it is believed that the intrinsic foot muscles
have their origins and insertions within the foot.
These muscles act as local stabilizers, and thus, they
serve primarily to stabilize the arch [6].
Previous studies have confirmed the function of
the IFM. A study by Fiolkowski et al. [7] and Headlee
et al. [8] demonstrated the inhibition of the tibial
nerve amid the IFM in addition to exercise until IFM
fatigue increased significantly enough to render a53

SEE - Bangkok, Thailand, Nov.11-13, 2019muscle decreased ND post training. Moreover,electrical stimulation (ES) significantly increased
CSA of the vastus lateralis, vastus medialis, andvastus intermedius muscles post training [18].
Conversely, some evidence suggests thatcombined ES in addition to exercise training is more
effective for strengthening the muscles than exercise
alone [19]-[21]. Nevertheless, the short-term effect of
ES in combination with SFE as an intrinsic footstrengthening exercise method has to date not been
discussed. Therefore, the purpose of this study was tocompare the effects of combined ES and SFE versus
SFE alone on ND and CSA of the AbdH muscle.

distributed between both legs. The knees wereextended and feet relaxed. Navicular tuberosity
height was then measured again. The test was
performed three times with the mean value of threemeasurements calculated. Consequently, naviculardrop was calculated by subtracting navicular heightstanding measurement from the sitting measurement.
Cross-sectional area of abductor hallucis
An ultrasound machine (M5 series, Shenzhen
Mindray Bio-Medical Electronics Co., China) with
7.5 MHz linear array probe was applied to render animage of the AbdH muscle. Subjects lie down in thesupine position with a 15 degree knee flexion with theankle in the neutral position. An ultrasound probewith a sufficient amount of gel was placed
perpendicularly to the AbdH muscle. The anterior
margin of the ultrasound probe should be positioned
1cm posteriorly to the navicular tuberosity. The
image of the AbdH muscle was taken with only
minimal pressure applied to the ultrasound probe.
CSA mean was calculated from three separate images
using software Image J version 1.52b (NIH,
Bethesda, MD, USA). The CSA measures the desired
area by tracing the muscle border [22].

METHOD
Design and setting
A double-blinded randomized controlled trial wasused in this study. Subjects were recruited from
Muang district, Chonburi province, Thailand. This
present study was approved by the Khon Kaen
University Ethics Committee in Human Research. All
subjects were randomly assigned to undergo
combined ES with the SFE group (experimentalgroup) or SFE with sham ES group (control group).
Numbered lots (1, control; 2, experimental) wereplaced in sealed opaque envelopes by physiotherapist
1. The subjects were then allocated and assigned forintervention by physiotherapist 2. The investigatorsin this study were blinded.

Procedure
Subjects in the experimental group received ESwith SFE, whereas the control group received SFE
with sham ES.
ES training was performed using an electricalstimulator (Endomed 482, Enraf-Nonius Co.,
Netherlands) with two electrodes. The passive
electrode was placed behind the head of the firstmetatarsal bone. Meanwhile, the active electrode wasplaced over the motor point of the AbdH muscle.
Each individual was trained at 85 Hz frequency, 5seconds pulse duration, and 6 seconds pause durationfor 20 minutes each session, once daily covering 3
sessions weekly for a period of 4 weeks. Intensity was
adjusted to each subject’s maximum tolerance
without pain and discomfort. Subjects in the control
group were administered with sham ES according to
the same location, using the same ES device andtraining protocol, but without the releasing ofintensity.
Subjects in both groups received SFE post ES
performed in the sitting position. Subjects were asked
to place their feet on the ground. Then, they attempted
to pull the head of metatarsal bones toward the heel
without flexing the toes, nor lifting the forefoot andheel from the ground. Exercise training was
performed for 30 repetitions per day, 3 days per week,
for 4 weeks. Each repetition required a contraction of
5 seconds. Throughout the 4 weeks, subjects were notallowed to participate in any other exercise.

Participants
Ten healthy females between 18 and 40 years ofage volunteered to participate. All subjects reported
good health, no contraindication of ES, and no historyof lower extremity orthopedic or neurologic disorders
within the previous 6 months.
Outcome measures
The measurements of outcome in this study wereassessed at the site of both feet prior to and 4 weeks
succeeding training intervention by the sameinvestigators.
Navicular drop
The differences in distances between navicular
tuberosity and the floor while sitting and standing aredefined as the navicular drop. Subjects sat on a chairwith the hips, knees, and ankles at a 90 degree angle.
Each subject was marked for their navicular
tuberosity using a permanent marker. The
investigator measured navicular tuberosity height
utilizing a digital vernier caliper (CD-20AX,
Mitutoyo, Kawasaki, Japan). Then, subjects were
instructed to stand with their weight equally
54

SEE - Bangkok, Thailand, Nov.11-13, 2019differences between groups in terms of baseline andclinical (navicular drop, ND and cross-sectional area,
CSA) characteristics.

DATA ANALYSIS
All data were analyzed using SPSS version 19.
Descriptive data was expressed as mean with standard
deviation. The student t-test was implemented tocompare demographic characteristics. Changes to ND
and CSA in the AbdH muscle between the two groups
at baseline and 4 weeks post-intervention werecompared utilizing the student t-test. A p-value of lessthan 0.05 was considered statistically significant. Alldata are presented as mean ± standard deviation.

Navicular drop and cross-sectional area
After 4 weeks, the results showed a significant
decrease in navicular drop (ND) in ES amid the SFE
group subsequent to training, whereas the SFE groupalone revealed no statistically significant decrease in
ND from baseline. However, there were no
significant differences between groups (Table 2).
The cross-sectional area (CSA) of the AbdH
muscle in both groups was increased (ES with
SFE=10.93 mm2and SFE=7.44 mm2 ; p<0.05) but
without significant differences between groups.

RESULTS
Demographic Characteristics
Subjects’ demographic and clinical characteristics
are shown in Table 1. There were no significant

Table 1 Baseline characteristics of each subject group.
Characteristic
Age (years)
Height (cm)Weight (kg)Body mass index (kg/m2)
ND (mm)
CSA (mm2)

ES with SFE(n=5)
20.60±0.89
158.40±7.30
50.40±6.89
19.80±1.56
6.28±1.50
191.25±35.43

SFE
(n=5)
20.40±0.55
158.20±6.4253.50±4.72
21.59±1.137.47±2.31
190.24±25.33

P
0.22
0.98
0.20
0.40
0.36
0.96

Table 2 ND and CSA comparison of AbdH muscle between both groups.
Parameter

ND (mm)
CSA (mm2)

ES with SFE (n=5)
Baseline
4 weeks6.28±1.50
191.25±35.43

4.77±1.50
202.18±38.05

P

SFE (n=5)
Baseline
4 weeks

0.03
0.003

7.47±2.31
190.24±25.33

6.45±1.07
197.68±21.19

P

0.40
0.04

P
(betweengroups)0.08
0.82

exercise alone [24].
Moreover, the results in this study incorporated
measured muscle size measurement which isconsidered to be one of the preeminent determinantsof muscle strength [11]. A previous study reported
that the cases of IFM weakness presented asignificant reduction in CSA [11],[25]. Recent studies
on the uses of SFE or ES to treat flatfoot suggest thatboth methods tend to improve plantar intrinsic footmuscle strength [26].
In a similar way, the results of this study support
a previous finding in that ES with SFE and SFE tends
to increase muscle size. Furthermore, the present
study demonstrates that the increase to CSA changed
more rapidly than in the previous study. CSA wassignificantly increased after 4 weeks of intervention.
In addition, the previous study demonstrated that
CSA may increase after 5 to 12 weeks of strength
training [27]. Gondin et al. [18] found the CSA of thequadricep muscles increased after 8 weeks of electrostimulation. Jung et al. [12] demonstrated that AbdH
muscle CSA significantly increased after 8 weeks of

DISCUSSION
The purpose of the current study was to compare
the effects of combined ES and SFE versus SFE alone
on ND and CSA amid the AbdH muscle. Hence, ourresults demonstrate that 4 weeks of ES with SFE tend
to increase MLA height more than SFE alone. Morerecently, a study conducted by Kaur et al. [22]showed the use of ES in flexible flatfoot significantly
decreased navicular drop after 3 weeks of therapy.
This is consistent with a study by Fourchet et al. [17]which revealed that stimulation of the AbdH muscles
in healthy young adults significantly caused naviculardrop to decrease after 3 weeks of training.
The possible mechanism was the ES involved in
the reverse motor unit recruitment in the skeletal
muscles. Large fibers have a lower threshold forstimulation, thus large type II fibers are recruited
preferentially, resulting in a greater potential formuscle force production [23]. Therefore, ES canfacilitate muscle strength to gain more rapidly than55

SEE - Bangkok, Thailand, Nov.11-13, 2019

SFE. On the other hand, a recent study incorporating
8 weeks of plantar intrinsic foot muscles strength
training in a small group of healthy subjects revealed
no significant difference in CSA among an NMES
group [28].
The finding in terms of increased CSA of the
AbdH muscle CSA may be described by the proper
intensity and duration of strength training. An
increase in muscle size using NMES with exercise
and exercise alone rendered the enlargement ofmuscle fibers due to the resistance training
mechanism [29]. ES with SFE and SFE is effective in
producing hypertrophy of type I and II muscle fibers
by increasing protein synthesis within muscle fibers,
resulting in an increase in the physiologic crosssectional area of the whole [3].
This pilot study has some limitations. Firstly, thesample size was small. Secondly, subjects wereyoung. Thus, the result cannot be generalized to fit
the general population. Lastly, we selected subjects
without muscle weakness. In the future, the study will
be conducted among participants with intrinsic footmuscle weakness in order to examine the effects of
SFE or ES with SFE after training.

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CONCLUSION
These results demonstrate that ES with SFE andSFE alone, can improve intrinsic foot muscle size. An
increase in AbdH muscle size is one factor relating to
IFM strength. Hence, combined ES with SFE tended
to increase MLA over SFE alone. Consequently, ES
in combination with SFE may be recommended as analternative treatment to increase MLA.
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Journal of Physiology, Vol. 15, 2001, pp. 613-623.

57

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF LAND MANAGEMENT OF HORTICULTURAL TO
SOIL ERODIBILITY AT THE UPSTREAM OF SUMANIWATERSHED*

Aprisal, Bambang Istijono and Indradwipa
Andalas University, Padang Indonesia

ABSTRACT
Upstream watersheds (DAS) in Sumani, is a large horticulture farming area widely cultivated by vegetables,such as cabbage, onions, potatoes etc. Due to intensive farming business activities, which tend to have an impact
on the level of erodibility inherent soils, a large portion of land is destroyed by rain leading to erosion. The
purpose of this study therefore is to determine the erosion level and determining erodibility factor on farm landson the upstream of Sumani Watershed. The research method adopted, is the purposive random sampling.
Furthermore, soil samples were taken in order to analyze its physical properties (texture, organic matter,
structure, permeability) at a depth of 0-20 cm. The samples were analyzed in the soil Department laboratory at
Faculty of Agriculture Andalas University. Data analysis was processed using the soil erodibility equation and to
determine the factors, the principal component analysis (PCA) was utilized. The results of the analysis showed
the value of soil erodibility against rainfall which was determined by using its organic matter, structure andpermeability. The soil was also prepared by applying the conservation method. The resh organic material of theharvest is capable of improving its durability damaged by rainfall.
Keyword; watersheds soil, horticultural, erodibility, rainfall

which includes physique, chemical, biology, andmineralogy capable of influencing the land. [4] Thisis also related to the combination actions fromrainfall, run-off, and land infiltration. K factor is theeffect of land and its profile reduction features. [5]Nowadays, it has been considered as erosion indicator
due to its detachment sensitivity and particle
transporttation [6].
Land erosion has become a reduction problem at
farming soil regions, especially at sulfur regions suchas the upstream watersheds in Sumani (DAS).
Furthermore, this research aims to review the landerodibility value of horticulture farming.

INTRODUCTION
The use of various poor farming management
activities leads to land damage. Agricultural ventures,
which fail to implement the conservation rule, tend to
make the land susceptible by rainfall thereby, leading
to erosion. Furthermore, this is influenced by several
factors which is dependent on the soil’s
characteristics, precipitation, land management, andits cover vegetation.
To determine the eroticism factor and predict themisplaced land, the researcher used the USLE
method, therefore, the lost soil’s arbiter factor was
analyzed. According to some researchers, erosion issometimes in the form of land resistance owing toheavy rainfall. The K factor is an integrated effectfrom rainfall precipitation and land resistance to thedetachment particle and transportation. This process
is influenced by soil characteristics such as particle
size distribution, structural stability, organic material
content, land chemistry, loam mineralogy, and watertransmission characteristic. Therefore, erodibility is acombined influence of land attributes with very
powerful conditions used to arrange the power which
can refuse the debris potency from rainfall erosivity[1] .
To appraise and decide the land misplaced acrossthe globe, the researcher used soil erodibility. [2] The
research proved that there is a strong relation between
the soil erodibility value and proved-lost land. [3]Furthermore, it consists of several land characteristics

MATERIALS AND METHODThe Research Setting
The research is located in the upstream
watersheds Sumani (DAS). Andisol and Inseptisol aredominant materials found in volcanic ash. The
rainfall precipitation in this area is 2.333 mm/year.
The research is agriculturally grouped into A, B, C
and D. Group A cultivates radish, potato, and tomato,
B consists of chili, radish, and tomato, while C
comprises of onion, chili, and potato, and group D(chili, radish, and tomato). Therefore, it is the centerof horticulture production.
The Derivation of Rainfall Precipitation Data
The rainfall precipitation data is taken fromsuppressor station in Alahan Panjang, to determine
58

SEE - Bangkok, Thailand, Nov.11-13, 2019

soil erosivity. This was calculated using the Lenvain
1989 formula as follows; R = 2,21 P 1, 36 in which R
represents rain erosivity and P the monthly average
rainfall precipitation in the research setting [7].

abc= organic matter content (% c x 1,724)= soil structure= soil permeability

To determine the land susceptibility, its erodibility
value is obtained comparing the formula with thecriteria in table 1.

Management Area
The land is cultivated by hacking it twice in each
agriculture season conventionally. The hacking
location is made different in line with its gradient.
Furthermore, the land surface is refined and clear
from organic material residue. Afterwards, group B
returned the harvest residue and used it in cultivating
the land.

Table 1. The criteria of land erodibility value
CriteriaNoClass
0,00 – 0,10
1
Very slow
0,11 – 0,20
2
Slow
0,21 – 0,32
3
Average
0,33 – 0,43
4Slightly high0,44 – 0,55
5High
0,56 – 0,64
6
Very high

The Taking of Soil Sample
A total of 12 sample points were randomly takenby the researcher using the purposive technique in thehorticulture area (Figure 1). These are indicated inchart 1 at four agriculture groups. Group A was atpoints 1, 2, and 3, B at 4, 5, and 6, C at 7, 8, and 9,
while D was at points 10, 11, and 12. The researcher
took the land sample at depth of 0-20 cm, with theagitated land sample for four fractions of texture
analysis, and organic materials. While the unagitatedland is examined by permeability analysis and soil
structure. To determine the land sample and analysis,
the Soil Department, Faculty of Agriculture, Andalas
University’s laboratory was utilized

The Main Component Analysis of Land
Characteristic to the Erodibility
The Principal Component Analysis (PCA), is used
to ascertain the land’s deteriorating ability as a resultof heavy rainfall. The researcher also uses thismethod to decide the main factor which influences its
value using a PC with an eigen value ≥1 as its
independent variable. Therefore, it consists of thehighest correlated independent value in PC, [9]. The
researcher also uses Minitab 17 to analyze.
RESULT AND DISCUSSION
Rainfall Erosivity
Approximately 2333 mm/year of rainfall data was
obtained for ten years from Kembar lake climate. Fromthese numbers of precipitations, the erosivity energy
capable of running the structure became fragmented,
thereby, leading to smooth particles which later floated
off the surface. The calculation using the Lenvain
formula results in rainfall erosivity energy of 1535, 99.
Its energy is big huge enough to destroy the land
structure on surface area. Furthermore, it causes
erosion velocity on the horticulture region to often open
when cultivated.

Figure 1. location of research area
Deciding the Land Erodibility Value
Furthermore, the researcher also made use of thenomograph formula to decide the land erodibility
value using factors such as texture, structure, organic
substance, and land permeability [8]. The equation is
as follows:
100 K = 1,292 [2,1 M1,14 (10-4) (12-a)] + 3,25 (b2) + 2,5 (c-3)
that:Land Erodibility Value at Upstream of Sumani
Watersheds (DAS)The erodibility land result taken at 12 sample
points in the horticulture region ranges from low tohigh, with the highest value at 0,33. Furthermore, thisis drawn from the susceptible and precipitation oferosivity, with a higher value. Some factors liketexture, structure, organic material, and soil
permeability influences its value. However, these
these factors are also influenced by land management.
In the horticulture region, the cultivation management
and plant types have a high impact on soil erosivity
precipitation. The plants which cover the land
surface, also reduces the rain erosivity. According to

K = soil erodibility
M = the percentage of the very fine sand andsilt (diameter 0,1 – 0,05 and 0,05 – 0,02mm) x (100 – % cay)
59

SEE - Bangkok, Thailand, Nov.11-13, 2019

Santos et al. 2003, vegetation or plant has the ability
to push rain energy and increase the infiltration rate
into the land.
The land surface closure by plants tend to reduce
rainfall kinetic energy and in turn, it the land can be
pushed, thereby lowering its erodibility. The

percentage increase in content, improves theinfiltration rate while decreasing its flow rate [10].
Therefore, the loamy fraction content helps to reduce
the particle thereby, lowering its erodibility value.

Table 1. The land erodibility value in research setting.
SamplePasir halus

debu

liat

a

b

c

M

K

1

8.3

29.0

29.5

6.9

3.0

5.0

2630.7

0.21

2

10.1

16.4

33.3

8.6

3.0

5.0

1767.5

0.16

3

9.8

28.9

22.0

6.9

2.0

6.0

3017.8

0.18

4

1.0

24.5

70.6

8.1

2.0

5.0

750.4

0.13

5

0.8

81.4

14.4

2.2

2.0

6.0

7039.7

0.30

6

6.4

60.9

7.1

3.4

2.0

5.0

6253.9

0.26

7

11.8

40.8

0.3

1.7

3.0

3.0

5245.1

0.32

8

6.3

13.7

54.9

2.9

3.0

5.0

899.5

0.31

9

8.6

43.8

13.4

6.9

3.0

6.0

4539.2

0.22

10

10.6

42.7

4.1

3.4

3.0

6.0

5116.0

0.31

11

11.8

36.9

4.3

3.4

3.0

3.0

4658.5

0.27

12

10.5

21.4

25.9

2.9

3.0

6.0

2367.10.33

Note; a = organic material, b = structure, c = permeability, M = the percentage of the very fine sandand silt (diameter 0,1 – 0,05 and 0,05 – 0,02 mm) x (100 – loam percentage), K = soil erodibility

The Analysis of Main Component
Erodibility Value in Horticulture Area.

shows that in eigen value the two PCA pools havescores above 1 which is the most influencing landerodibility value. The biggest value in PCA1 aresmooth sand variable and dust.

(PCA)

The dominant factors influencing the erodibility
value, is determined by analyzing the principal
component (PCA). The analysis result on table 2

Table 2. The land variable analysis result with PCA
Eigenvalue
2.78292.02480.90030.27430.01760

Proportion

0.464

0.337

0.15

0.046

0.003

0

Cumulative

0.464

0.801

0.951

0.997

1

1

Variable

PC1

PC2

PC3

PC4

PC5

PC6

K

0.54

0.04

0.443

0.02

0.714

0

Very Fine sand

0.288

-0.542-0.371

0.433

0.031

-0.545

Silt

0.261

0.575

-0.317-0.431-0.021-0.561Clay-0.487-0.044

0.611

0.009

-0.009-0.622a-0.518-0.185-0.412-0.289

0.666

0

b

0.229

-0.5810.149-0.737-0.212060

SEE - Bangkok, Thailand, Nov.11-13, 2019

The land erodibility (table 1) is also has thehighest value found in sand content and dust whichplays an essential role in determining the landerodibility value.
The Texture Relation with Land Erodibility
The land texture is very relevant with its
erodibility. For instance, in Figure 2, there is polymial
relation between its texture using a coefficient valueof R2 = 0,92. It means that in each loam improvement,
about 1 % value land erodibility reduction value of
0,005 at 0,34 with a credibility of 91 % is obtained. .

Figure 3. The relation of silt fraction with theland erodibility.

0.4
0.4

Soil Erodibility

0.3
0.3
0.2
y = 0.4278e-0.12x
R² = 0.9229

0.2
0.1

Figure 2. The relation of loamy fraction withthe land erodibility.

0.1
0.0
0.0

In addition, the relationship between silt and landerodibility also has a negative relation withdetermination R2 having a value of 0,89. Figure 3
shows that the improvement of 1% leads to a
reduction of about 0.003 and a credibility level of
89% at 0.37.
The land fraction or texture is an importantcharacteristic owing to its ability to retain water
movement rate through the land matric. Furthermore,
the land texture influences the soil fertility and thecultivation rate. While the relation of silt fraction withland erodibility is linear in relation with R2 = 0.89.
This means, that each dust improves by 1% with areduction rate of 0.003 while the soil erodibility value
0,37 has a credibility level of 0,92%.

2.0

4.0

6.0

8.0

10.0

Persentase Organic Mater

Figure 4. The organic matter relation withthe land erodibility

Dust is a smooth fraction with no capacity andincapable of making ligament without adhesivecontent therefore, it will be easy for erosion to occur
on the surface flow [11]. In addition, the loamy
fraction has capacity and capable of creating aligament. Therefore, this fraction will be harddifficult to undergo erosion compared to the dusty
fraction. The land which is dominant by loamy
fraction will be very cohesive and hard to get ruined.
The Organic Substance relation with erodibility

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SEE - Bangkok, Thailand, Nov.11-13, 2019

CONCLUSION
0.4

From the result, the following conclusions wheremade as follows:
1. The land erodibility at the flow of Sumani river
hilt is highest with average criteria.
2. Based on the PCA analysis, the dusty fraction
content and smooth sand are the main factors
which improve the value in this region.
3. In addition, there are other factors that indicatesthe relationship between the land erodibility withloamy content, organic matter and soil
permeability which also influences it.
4. The other environmental factor which influences
this value is horticulture management enterpriseby the farmer..

Soil Erodibilty

0.4
0.3
0.3
0.2

y = 0.064ln(x) + 0.0403
R² = 0.8811

0.2
0.1
0.1
0.0
0.0

50.0

100.0

150.0

Permeability rate cm/h

ACKNOWLEDGMENTS
Figure 5. Permeability relation withsoil erodibility

The researcher is wishes to express his profoundgratitude to the rector of Andalas University for the
support and providing all the facilities needed to carryout this study. Furthermore, the researcher is also
grateful to all students who participated in the field
and laboratory activities. Hopefully, this paper will
enhance students literation.

The organic substance seems to influence the landerodibility (figure 4) with power relation between it
and the organic substance using a coefficient R2 valueof 0,92. This means that each improvement inaccordance to the organic material degree of 1%
influences the land erodibility by 0,43 with credibility
level of 92%. According to [12], the positive effectof organic carbon is for aggregate stabilization andthe land structure, while [13] stated that organic
material functions as layer and loamy fraction inincreasing the land aggregate stability, thereby
reducing its degradation. Previously [14], people
argue that aggregation improves land endurance
towards the rainfall boundary, thereby, reducing its
fall

REFERENCES[1] Lal, R., research method of 1994 erosion. Land.
3rd edition. Land and Water Conservation Society(Aukeny), & St. Lucie Press (Delray Beach),
United States, 352 p.
[2] Zhang ZG, Fan BE, Bai WJ, Jiao JY, J. Tanah.
Air. Conserv. 5 (2007) 7-13.
[3] Tejada M., Gonzalez JL, Tanah. Sampai. Res. 91(2006) 186-198.
[4] Veihe A., Geoderma. 106 (2002) 101-120.
[6] Manyiwa T., Dikinya O., Afr. J. Agric. Res. 8(2013) 4170-4178.
[7] Asdak, Chay. 2010. Hydrology and river basin
management. Yogyakarta: Gadjah Mada
University Press.
[8] Wischmeier, W., Johnson, C., Cross, B., 1971.
Sebuah tanah erodibilitas nomograph untuk lahanpertanian dan konstruksi situs. Jurnal Konservasi
Tanah dan Air 26 (3): 189-193[9] Andrews, SS, Carroll, CR, 2001. Merancang alatpenilaian kualitas tanah untuk manajemen agroekosistem yang berkelanjutan. Aplikasi ekologi 11(6): 1573-1585.
[10] Santos, FL, Reis, JL, Martins, OC, Castanheira,
NL, Serralheiro, RP 2003 penilaian Perbandingan
infiltrasi, limpasan dan erosi sprinkler irigasi
tanah. Biosystem Teknik 86 (3): 355-364.
[11] Dariah, A., F. Agus, S. Aryad, Sudarsono, andMaswar. 2003. The relationship between soil

The Relation of Permeability with Erodibility
The land erodibility has a logarithm
relation(figure 5) with determinant R2 of about 0,88.
It means that each land permeability increases by 1
cm/hour which reduces the land erodibility reduction
by 0,06 cm/hour an erodibility of 0,04, and acredibility level of 88%.
Its permeability lead to the drop of rainfall in the land
surface therefore it is capable of reducing stagnant
water. According to [15], the soil permeability rate is
influenced by the total amount of land pore withmacro pore being the primary factor. According to[16] the soil which has a high infiltration andpercolation rate, has low relative value.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

characteristics and erosion rate of coffee based
farming area in Sumberjaya, West Lampung.
Journal of Land and Climate No. 21/2003, soil
Research Hall. Bogor. 78-86 things.
[12] Emami, H., Astaraei, AR, 2012. Pengaruh
amandemen organik dan anorganik padaparameter dari kurva retensi air, bulk density dan
diameter agregat dari tanah salin-sodik. Jurnal
Ilmu Pertanian dan Teknologi 14: 1625-1636.
[13] Kodešová, R., Rohošková, M., Žigová, A. 2009.
Perbandingan stabilitas agregat dalam waktu
enam profil tanah di bawah pengolahan tanah
konvensional menggunakan berbagai tes
laboratorium. Biologia 64 (3): 550-554.
[14] Baldock, JA, Skjemstad, JO, 2000. Peran matriks
tanah dan mineral dalam melindungi bahanorganik alami terhadap serangan biologis.
Organik Geokimia 31 (7-8): 697-710.
[15] Aprisal, Rusman. B. Dwipa. I., Refdinal. Erlina,
R., Fajriwandi 2016. The dynamics of some of thephysical properties of soil under conservation
farming. On the critical land of Aripan in DTA
Singkarak. Journal of Land Suboptimal: 5 (2) 137144.
[16] Irma. F., Saka., Arief. 2008. Agricultural land
Erosion analysis and economic parameters using
nail (net agricultural income loss) method basedon geographic information system in Hulu Das
Jeneberang.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

A NEW REPORT OF ARGULUS INDICUS (CRUSTACEA:
BRANCHIURA) INFESTATION IN RED TILAPIA (OREOCHROMISNILOTICUS X OREOCHROMIS MOSSAMBICUS) IN THAILAND

1Supamas Sriwongpuk1
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi, Thailand
ABSTRACT

Argulus indicus (Crustacea: Branchiura), or the fish louse, is an external parasite in Phylum Arthropoda foundon the skin, fin or gills of freshwater fish species. It is very flat with an oval or rounded carapace, two compoundeyes, sucking mouthparts with a piercing stylet, and two suction cups it uses to attach to its host. Clinical signs ininfected fishes include scratching on aquarium walls, erratic swimming and poor growth. It causes pathologicalchanges due to direct tissue damage and secondary infections. In the present study, red tilapia (Oreochromis
niloticus x Oreochromis mossambicus), with symptoms such as abnormal swimming or scratches on their skin,were collected from a cage culture at Klong Rapee-Phat, Nong-Seau District, Pathum-Thani Province in Thailand.
The parasites collected from the skin and fins of infected red tilapia were identified as Argulus indicus. This is thefirst report of infection with A. indicus of red tilapia (O. niloticus x O. mossambicus) in Thailand.
Keywords: Argulus indicus, Fish louse, Red tilapia, Oreochromis niloticus x Oreochromis mosambicus, Thailand

intermediate host for many parasites which can cause
mass mortality thereby reducing the food value offishes [11]. Tilapia species are freshwater fishes
belonging to the family of Cichlidae which areconsidered to be more resistant as compared to otherspecies of cultured fishes [12]. Crustaceans constituteone of the four recent subphyla of phylum Arthropoda
which includes 1,242,040 species [13].
Tilapia is a freshwater fish belonging to the family
Cichlidae. It is native to Africa, but was introduced
into many tropical, subtropical and temperate regionsof the world during the second half of the 20th century[14]. Tilapia is a worldwide fish of great commercial
importance and it is recognized as one of the mostimportant aquaculture species of the 21st century.
Tilapia is currently ranked second only to carp inglobal production [15]. The world’s total tilapia
production in 2012 was 4.2 million tonnes. Tilapia
aquaculture is rapidly expanding with a global
production of about 2.8 million metric tonnes in 2008[16] and estimated to increase to 8.89 million metrictonnes by the year 2020 [17]. The red tilapia(Oreochromis hybrids or O. niloticus x O.
mossambicus) developed from crosses of the main
Oreochromis culture species has also become popular
in recent years [18].
The parasites use the fish for their shelter and foodand destruct more or less each and every organ
resulting in pathogenic effects [19]. Crustacean is an
important disease producing parasites of freshwater
fishes. Argulus is one of a serious pathogen of fish innatural and intensive fish cultures. Many problems
associated with argulid infections are a reduced rateof growth and impact on the aesthetic value of the fish
host which results in economic losses in fisheries

INTRODUCTION
Among crustaceans, more than 1,500 species ofcopepods are parasitic on fishes. Argulus Müller,
1785 is one genera belonging to the class Branchiura,
most commonly known as fish lice or fish louse, aclass of crustacean arthropods [1] that are membersof a large group of branchiuran parasites related to
crabs, lobsters and shrimp [2]. The genus Argulus(Crustacea: Branchiura), or fish louse, is a common
parasite of freshwater fishes [3]. Nearly 15 species arefound in freshwater fishes and several of the species
are parasitic on marine fishes [4]. Fish louse
belonging to the Argulidae family are skin parasites.
About one hundred known species have worldwide
distribution [5] and cause damage to skin epithleumby their feeding activity. The wounds bleed slowly
and become the sites of secondary infections by
pathogens [6]. The injury to tissue manifests as
inflammation and secondary infections by microbes.
If the infection is high, these parasites can cause greatdamage to populations of fishes in pond culture andcage culture systems [7].
Parasitic crustaceans are among the most harmful
pests for fishes. Certain species cause massinfestation and mortality in fish cultures, sometimes
even in nature, resulting in considerable economic
losses. Fish cultures now include raising fishes not
only in man-made ponds and tanks, but also in cages
and pens built or suspended in large bodies of watersuch as reservoirs, lakes, and even marine coastal
areas [8]. Fishes serve as a potential source of animal
protein for humans [9]. About 40% of the protein dietof 2/3 of the entire global population comes fromfishes [10]. The majority of fishes serve as an
64

SEE - Bangkok, Thailand, Nov.11-13, 2019[20]. This is the first report of infection with A.
indicus of red tilapia (O. niloticus x O. mossambicus)
in Thailand. As such, the present study aims to makea survey to elucidate the morphologicalcharacteristics of A. indicus.

The systematic position of the genus Argulus is asfollows:
Class: Crustacea
Subclass: Branchiuran
Order: Arguloidea
Family: Argulidae
Genus: Argulus
Argulus indicus Weber, 1892

MATERIALS AND METHODSIn March 2017, thirty red tilapias were collectedusing gill nets from a cage culture at Klong RapeePhat, Nong-Seau District, Pathum-Thani Province inThailand. These fishes were examined for ectoparasites. Twenty four fishes were found to be
infected with copepod parasites. Argulus were foundattached to the bodies on scales and fins. The
parasites were carefully removed with the help of aneedle and a soft brush. The specimens of Argulus
collected from the body surface of the red tilapias
were preserved in 70% ethyl-alcohol and thentransferred to 2% formalin for detailed study. Using acompound light microscope at x10 and x40
magnifications, the fishes were dissected andexamined. The Argulus parasites were fixed in 70%
ethyl-alcohol and then transferred to the laboratory.
The
identificationofthemorphometriccharacteristics of this parasite was carried out asdescribed previously [5, 21, 22, 23 and 24].

The morphological description of Argulus indicus
can be expressed as follows (Figure 1 to 3); a wide,
oval body, dorso-ventrally flattened and 2 complex
faceted eyes. The cephalothorax is covered with awide convex scutum and its posterior margin isindented. First maxillae are usually modified as
powerful suctorial organs, which are clearly visible atthe ventral surface. The second maxilla or suction cup,posterior to the sucker, has 5 segments. Four pairs ofthoracic legs are modified for swimming. Eachthoracic segment bears a single pair of biramous
swimming legs (thoracopods), the first 2 pairs ofwhich in both sexes have a backwardly projecting
process or flabellum. The urosome with rounded
lobes is covered marginally with small spines. The
anterior end of the cephalothorax forms a broad
protrusion and is delimited laterally by shallow
grooves. The posterior incisures of the urosome do
not reach into the center.

RESULTS AND DISCUSSION
Specimens of fish louse were collected in March2017 of the body surfaces (scales, skin and fins) of
red tilapias in a cage culture at Klong Rapee-Phat,
together with the number of infestation values are
given in table 1.

1
2
3

4

Table 1 Infestation values of Argulus indicus on Red
Tilapia caught from Klong Rapee-Phat
Infestation values
Number of fish investigatedNumber of fish infested
Prevalence (%)
Number on 1 fish
Total number of Argulus indicus

Number
30
24
80
1-28
736

6

7

5

Twenty four red tilapias were found to be heavily
infested with A. indicus. Acute haemorrhagic
septicemia inflamed skin wounds, an increased
production of mucosal material, loss of scales andcorrosion of fins were observed in these red tilapias.
Fish louse causes damage to the skin epithelium by
their feeding activity. The wounds bleed slowly andbecome the site of secondary infection by pathogens[6]. The small lesions and collagen of the dermis weresecondarily infected by bacteria and fungi leading tofurther degeneration of the epidermal layer anddisruption of the basal membrane [25].

8
9

1 mm

Fig.1 Ventral view of A. indicus (female) (scale = 1mm), where 1=1st antenna, 2=2nd antenna, 3=eye,
4=1st maxilla or suction cup, 5=respiratory area,
6=thorax, 7=thoracic appendage, 8=spermathecal,
9=abdomen (urosome or caudal fin)

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SEE - Bangkok, Thailand, Nov.11-13, 2019

The carapace is almost as broad as it is long witha deep posterior sinus. The lateral lobes of thecarapace convex overlap all the swimming legs. The
dorsal paired ridges of the carapace curve outward
beyond the paired eyes anteriorly and discontinue
posteriorly with the posterior straight pieces ending
near the posterior transverse groove of the cephalicregion (Figure 3).
The minute anterior respiratory area just anterior
to the very large and oblong posterior one (Figure 1
and Fifgure 4); the ribs of the suction cup with 3 rods
and not of the imbricate plates (Figure 5); the second
maxilla slender, basal plate with three large teeth.

1
3

2

4

5

7
6

1 mm

Fig.2 Ventral view of A. indicus (male) (scale = 1mm), where 1=1st antenna, 2=2nd antenna, 3=eye,
4=1st maxilla or suction cup, 5= thoracic appendage,
6= abdomen (urosome or caudal fin), 7=testes

1

3

0.5 mm2

Figure 4 The respiratory area of A. indicus (arrow)(scale = 0.5 mm)

The species of the fish louse Argulus (Crustacea:
Branchiura) are found distributed throughout theworld and 143 species in the genus have been
described, although it is likely that many of these aresynonymous [6]. Species of Argulus are characterized
by a depressed ovoid and broad body. The head isfused with the thoracic segment forming a
cephalothorax covered by a dorsal, broad, flat shield(carapace) with posterolateral lobes. Two pair ofmaxillae are present, the first maxillae in the genus
Argulus is highly modified to form cup-like suckers
with strongly reinforced walls [26].
This genus is distributed worldwide in bothmarine and freshwater habitats [5]. The genus
Argulus causes problems in many types of aquatic
systems throughout the world. Although there is aconsiderable literature available on the group ofparasites, most is concerned with the taxonomy,

4
5
1 mm

Figure 3 Dorsal view of A. indicus (Male) (scale = 1mm), where 1= carapace, 2=ridges, 3=eye, 4=testes,
5=swimming leg

66

SEE - Bangkok, Thailand, Nov.11-13, 2019

morphology and development of the parasite, about
which aspects are fairly well understood. There ismuch less reliable information available on otheraspects of the biology of Argulus; in particular there
is a need for quantitative and experimentally based
studies. A. indicus was found on Ophiocephalus
punctatus from West Bebgal [27], Ophiocephalus
micropeltes from Tasik Temengor, Parak fromMalasia [28] and on Major carps from Hyderabadfrom Pakistan [29]. There are four species of Argulus
reported in Thailand such as A. foliaceus, A. indicus,
A. siamensis and A. alosae [21]. A. indicus was foundon the skin of Siam fighting fish (Betta splendens
Regan, 1910) from Bangkok, Thailand [30]. If it isphysically possible the best control method for
Argulus-infected waters is to empty them of fish andallow a fallow period before re-stocking. This would
have to be long enough to allow for the hatching of
eggs and the death of resulting parasites.
Alternatively lakes could be drained and left empty
for sufficient time for eggs to be killed by desiccation
or frost [31].

valuable information given the widespread local
consumption of the fish and its significance as themain source of protein .In the study, a total of thirty
red tilapia fish samples were examined and thefindings revealed the existence of fish louse or A.
indicus (Crustacea: Branchiura). The external
copepod parasitic species were found on the scales,
skin and fins with the highest prevalence of parasitic
infection (80%( (Table 1) with the characteristic of
the anterior respiratory area minute just anterior to thevery large and oblong posterior one; ribs of suction
cup with three rods and not of imbricate plates. All ofparasites from this study were fish louse in genus
Argulus and were identified as A. indicus. This is thefirst report of infection with A. indicus of red tilapia(O. niloticus x O. mossambicus) in Thailand.

ACKNOWLEDGMENTS
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.
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Tilapia, Oreochromis niloticus L. Cultured inPhillipines. In Diseases in Asian Aquaculture III

0.5 mmFigure 5 Ribs of the suction cup with 3 rods (arrow)(scale = 0.5 mm)

CONCLUSIONSThis research has identified and characterized theparasites residing in the red tilapia (O. niloticus x O.
mossambicus) from Klong Rapee-Phat, Nong-Seau
District, Pathum-Thani Province in Thailand. This is67

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(Flagel T.W. and Mac Rae I.H. eds.), As. Fish.
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Bay and Environs. PCARRD Book Series, No. 49,
Los Baños, Laguna, 1988, pp.7-14.
[9] Abdel-Gaber R., Abdel-Ghaffar F., Bashtar A.R.,
Morsy K. and Saleh R., Interaction between theIntestinal Cestode Polyonchobothrium clarias(Cestode: Ptychobothriidae) from the African
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Metal Pollutants in an Aquatic Environment in
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[10] Abdel-Ghaffar F., Abdel-Gaber R., Bashtar A.R.,
Morsy K., Al Quraishy S., Saleh R. and Mehlhorn
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priacanthi(Digenea:
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from the Red Sea, Egypt, Parasitol. Res., Vol. 114,
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[11] Bunkley-Williams L, Williams E.H. andBashirullah A.K.M., Isopods (Isopoda: Aegidae,
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3), 2006, pp. 175-188.
[12] Akoll P., Konecny R., Mwanja W.W., Nattabi
J.K., Agoe C. and Schiemer F, Parasite Fauna ofFarmed Nile Tilapia (Oreochromis niloticus) and
African Catfish (Clarias gariepinus) in Uganda,
Parasitol. Res., Vol. 110, Issue 1, 2012, pp. 315323.
[13] Zhang Z.Q., Animal Biodiversity: an Outline ofHigher-Level Classification and Survey of
Taxonomic Richness, Zootaxa, Vol. 3148, 2011,
pp. 1–237.
[14] Pillay T.V.R., Aquaculture: Principle andPractices, Fishing Book News, London, 1990, pp.
1-575.
[15] 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, Issue 2,
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[16] FAO, FAOSTAT. Food and Agriculture
Organization of the United Nations, 2010.
[17] Tacon, A.G.J. and Metian, M., Global Overview
on the Use of Fish Meal and Fish Oil in
Industrially Compounded Aquafeeds: Trends andFuture Prospects, Aquaculture, Vol. 285, No. 1-4,
2008, pp. 146-158.
[18] Teichert-Coddington, D.R., Green B., Boyd C.E.,
Harvin J.L., Rodriguez R., Martinez D., andRamírez E., Effect of Diet Protein on Food
Conversion and Nitrogen Discharge During SemiIntensive Production of Penaeus vannamei

During the Wet Season. In Burke D., Goetze B.,
Clair D. and Egna H. (Editors), Fourteenth
AnnualTechnical
Report,Pond
Dynamics/Aquaculture CRSP,
Office ofInternational Research and Development, Oregon
State University, Corvallis, Oregon, 1997, pp. 7177.
[19] Lilley, J.H., Philips, M.J. and Thongutai, K., A
Review of Epizootic Ulcerative Syndrome (EUS)in Asia. Publ. Aquatic Animal Health ResearchInstitute and Network of Aquaculture Center in
Asia-Pacific, Bangkok, Thailand, 1992, pp.1-73.
[20] Taylor N.G.H., Sommerville C. and Wootten R.,
The Epidemiology of Argulus spp. (Crustacea:
Branchiura) Infections in Stillwater Trout
Fisheries, Journal of Fish Diseases, Vol. 29, Issue
4, 2006, pp 193-200.
[21] Sirikanchana P., Parasites of Aquatic Animal,
Sky Word Advertising Partnership Ltd., Bangkok,
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[22] Bykhoskaya-pavlovskaya I.E., Gusev A.V.,
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and Epstein V.M., Key to Parasites of Freshwater
Fish of USSR, Israeli Program for Scientific
Translation, Jerusalem, 1964, pp. 1-694.
[23] Hoffman G.L., Argulus, a Branchuiran Parasite
of Freshwater Fishes, U.S. Fish and Wildlife
Service. Fish Disease Leaflet 49, 1977, pp. 1-9.
[24] Thomas M.M. and Devaraj M., Two New
Species of Argulus Müller (Crustacea:
Branchiura) from River Cauvery with a Key toIndian Species, Central Marine Fisheries
Research Inst., Regional Centre, MandapamCamp (India), 1977, pp 215-220.
[25] Bauer O.N., Musselius V.A. and Strelkov Y.A.,
Disease of Pond Fishes, Israel Program for
Scientific Translations, Jerusalem, 1973, pp 152.
[26] Richard H., Other Ectoparasites Infesting Fish;
Copepods, Branchiurans, Isopods, Mites andBivalves, Aquaculture Magazine November/
December, 2003, pp. 1-7.
[27] Ramakrishna G., Note on the Indian Species of
the Genus Argulus Müller (Crustacea, Copepoda)
Parasitic on Fishes, Indian Museum Calcutta
Records, Vol. 49, Issue 2, 1951, pp. 207-215.
[28] Seng L.T., Two Ectoparasitic Crustaceans
Belonging to the Family Argulidae (Crustacea:
Branchiura) in Malaysian Freshwater Fishes,
Malayan Nature Journal, Vol. 39, 1986, pp. 157164.
[29] Jafri S.I.H. and Ahmed S.S., A New Record of
Ectoparasitic
Crustaceans(Branchiura:
Argulidae) from Major Carps in Sindh, Pakistan,
Pakistan Journal of Zoology, Vol.17, Issue 1,
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[30] Wilson C.B., A Copepod (Argulus indicus)
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[31] Tonguthai69

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

IMMEDIATE EFFECTS OF ARM SWING EXERCISE THERAPY ON
THE RANGE OF SHOULDER MOTION AND STAND POSTURE:
A PILOT STUDY IN YOUNG ADULTS
1

Zhen Xiao1,3, Wichai Eungpinichpong1,2,3*, Xingze Wang4, and Uraiwan Chatchawan2,3
Division of Physical Therapy, Faculty of Associated Medical Sciences, Khon Kaen University, Thailand;
2Back, Neck and Other Joints Pain and Human Performance (BNOJPH), Thailand;3
Research and Training Center for Enhancing Quality of Life of Working-Age People, Thailand;
4
School of Physical Education and Training, Shanghai University of Sport, Shanghai, China
ABSTRACT

People who work in offices for a long time tend to have poor posture and a decreased range of motion throughout the body. This could lead to chronic neck and shoulder pain if not corrected. Shuai Shou Gong, a version of
Arm Swing Exercise (ASE), has been developed and practiced by some Chinese people for over one thousand
years to maintain physical well-being. Its beneficial effects on posture and range of motion have not yet beenverified. Thus, the purpose of this study was to preliminarily examine the immediate effects of ASE on shoulder
range of motion (ROM) and occiput-wall distance (OWD) in young adults. The before-after study design was usedin fifteen healthy office workers (6 males, 9 females), aged 20-40 years, who participated in the study. The shoulder
ROM and OWD of the participants were measured before and immediately after a 10-minute session of supervised
ASE. A paired-sample t-test was used to estimate the mean changes in the outcome. Results in this study revealed
that shoulder ROM was increased in all directions (P < 0.05) while the OWD was decreased (P < 0.05) after the
10-minute session. However, a postural assessment method using a mobile application (PostureScreen) could notdemonstrate a significant improvement. In conclusion, ASE may provide immediate improvements on shoulder
ROM and forward head posture as indicated by a decreased OWD. Further research using a randomized controlled
trial is needed.
Keywords: Arm Swing Exercise, Shoulder Range of Motion, Occiput-wall Distance, Posturejoints, muscles, ligaments, activation reflection, andproprioception circuit, improves the sensory functionof upper limbs and promotes neuromuscular recovery[7], ASE is conducive to the accurate coordination of
space and time between sensory center and muscle
proprioception [8] then it may facilitate having goodstanding posture.
Theoretically, repeatedly swinging the arms may
stimulate the nerves, tendons and muscles surrounding the shoulder joint [9]. When the arms are swinging, the latissimus dorsi muscle and the gluteus maximus that are connected by the superficial layer of thelumbar fascia, can transfer the forces and rotate thetorso [9]. In previous studies, ASE training has showna protective effect on vascular complications by improving blood glucose control and improving oxidative stress through exercise [11]. Exercise capacityand oxygen consumption in overweight and normal
weight sedentary young adults are improved throughASE [11]. ASE was also found to improve the pulmonary functions in type 2 diabetes mellitus (T2DM) patients [12].
Nowadays, there is an increase in the number ofpeople who work in offices for an extended time. Thiscan lead to poor posture and a decreased range of motion throughout the body because of tiredness andmuscle tightness resulting in chronic neck and shoulder pain. Since the effects of ASE on improving the

INTRODUCTION
Arm Swing Exercise (ASE) is a type of traditional
Chinese QiGong which has been practiced by Chinese people for ages to maintain both physical andmental wellbeing. ASE first appeared in the book of
Dharma Yi Jin Jing more than a thousand years ago[1]. The performance of ASE consists of a series ofrhythmic arm swinging and body swaying back-andforth plus on the fifth swing, the participants slightly
bent their knees and dipped down twice. ASE normally lasts for 5-15 minutes depending upon thehealth conditions of the performers. It has been classified as a low-intensity exercise, based on approximately 23% of the maximum VO2 and 45％ of the
maximum HR (HR Max) during the exercise [2].
Based on traditional Chinese medicine, ASE may facilitate the circulation of Qi, the internal energy [3],throughout the whole body, since Qi nourishes the internal organs and helps recovery from illnesses andprovide positive effects for health [4].
Performing ASE training quickly and repeatedly
stimulates the muscles, improves the transmission
rate of nerve transmissions across synapses, improves
tonic reflexes that causes the muscle to contract andincreases muscular activity [5]. ASE is beneficial forincreasing muscle strength and balance stability [6].
Since rapid vibration stimulates the receptors in the70

SEE - Bangkok, Thailand, Nov.11-13, 2019shoulder range of motion and standing posture has notbeen verified, this study aims to preliminarily examine the immediate effects of ASE on shoulder rangeof motion (ROM) and occiput-wall distance (OWD)
in these office-working people.

The participants stood with their feet apart about
shoulder width. The arms were actively raised toshoulder-height with comfortably straightened fingers. While their trunk and neck were kept upright,
their arms swung back and forth, naturally following
the preset tempo of the metronome. Breathing
through their nose, they breathed in during the upswing and breathed out on the down swing. Each setof ASE consisted of five arm-swings, where the action from 1 to 4 was the same. However, on the fifthswing, the participants slightly bent their knees anddipped down twice (Figure 2). The participants wereencouraged to swing their arms rhythmically in a relaxed manner [4].

METHODOLOGY
Study design and participantsThis pilot study employed a before-after research
design. Healthy people aged between 20-40 years
who met the inclusion criteria were recruited. Exclusion criteria was based on reviewing past medical records. Participants with a pre-existing medical condition with contra-indication to exercise were excluded.
Before and immediately after the experimental intervention, the evaluation parameters of the young
adults were investigated to explore an immediate effect of ASE on posture and on active range of motionof the shoulder joints. The whole process of the study
is presented in the following flowchart (Figure 1).
Assessed for eligibility (n = 18)
Excluded (n = 3):
Not met inclusion
criterion (n = 1),other reasons (n =2).

Fig. 2 Single set of ASE performance. Consisted of
the first four swings (A) with knees extended and thefifth swing (B) with slightly bent knees.

Received ASE therapy (n=15)

OUTCOME MEASURES

Completion of the research protocol (n = 15)

Shoulder Range of Motion (ROM)
Data analysis (n = 15)
Fig. 1

Active shoulder ROM is defined as the range of
motion where participants could move their shoulders
to the end of each of the cardinal plane while maintaining a neutral thorax (no compensatory movementof the trunk) [13]. A standard goniometry of shoulder
joint ROM was measured by a licensed physical therapist (the examiner). The examiner asked the participants to lay supine on a massage bed to measure ROM
in order to minimize the compensatory movement of
the thorax during the measurement [14]. Movements
in shoulder flexion, abduction, medial (internal) rotation, lateral (external) rotation and extension were
measured bilaterally [15]. The first four directions
were measured in the supine lying position. Only theshoulder extension was measured when the participants were in the prone lying position. Three consecutive measurements were made on each direction, after which the average was used.

Flowchart of study process (n=15)

Arm Swing Exercise Intervention
The ASE training was performed in a researchroom with proper light and ventilation where theroom temperature was set at 25°C. Participants weretold to wear suitable cotton T-shirt and shorts. The
ASE protocol consisted of a 3-minute period ofwarm-up and active stretching of the main muscle
groups of the body. Then the participants performed
a 10-minute session of ASE as guided by a prerecorded video tape. Finally, the session ended with a3-minute cool-down. All of the procedures of ASE
were guided by an exercise coach using a metronome
to control the rhythm.

Occiput-Wall Distance (OWD)
Arm Swing Exercise protocol

71

SEE - Bangkok, Thailand, Nov.11-13, 2019

The distance between occiput and wall (OWD) instanding position was measured by the examiner.
OWD has been used to determine the amount of kyphosis [16]. The flexed posture defined by OWD isalso associated with increased posterior chest convexity [16]. OWD has been widely used in epidemiological studies, although it cannot replace the clinicalmeasures of highly accurate kyphosis deformity suchas Cobb’s Angle [17]. However, it could be used as
screening tool for early detection of forward neckposture and possible weakness of posterior neck muscles in non-disabled elderly people [18]. The examiner used a ruler to measure the distance between the
protuberance of the 7th cervical spinous process andthe wall as the participants stood up erect where theheels, sacrum, and upper back were positioned
against the wall [19].

RESULT
Fifteen participants (6 males, 9 females), aged
28.8 ±7.03 years, were included. Their mean height,
weight, and BMI (Body Mass Index) were 162.62±7.08cm, 65.95±14.72 kg, 25.07 ±4.52 kg/m2, respectively.
Shoulder ROM
Shoulder ROM was increased in all directions
when participants finished 10-minutes of ASE. Basedon changes from baseline to intervention, the significant improvement was shown in shoulder flexion, abduction, medial rotation, lateral rotation and extension measurements in all participants (P < 0.05) (Table 1).

PostureThe posture can be defined as the rotation andstraight position of adjacent body segments and its direction relative to gravity [20]. The proper alignmentof the body’s segments so that the least amount of energy is required to maintain a desired position is theideal posture. The examiner used the PostureScreen
Mobile APP to take the participants’ photos in front
view, right side view, back view, and left side view[21]. Through the taken photos of the standing body,the average of lateral postural displacements was determined. Previous studies have shown that this mobile APP has high reliability and validity. Inter-rater
reliability was good to excellent for all translations
and a range of 0.71 to 0.99 for the intra-rater reliability [18].

Table 1. Pre-ASE and Post-ASE values of the shoulder range of motion

Heart Rate
Note: Values are means ± standard deviation, P value(2-tailed); Pre-ASE means pre-Arm Swing Exercise;
Post-ASE means post-Arm Swing Exercise.

HR was measured to monitor the exercise intensity of the participants while doing the ASE. The examiner used the Jumper JPD-500A pulse oximeter tomeasure the heart rate of participants. The heart rate
was measured: before exercise, during exercise (at 5minute mark), and immediately after exercise.

Figures 3, 4 are shoulder flexion, abduction measurements presented in box plot format. The results
showed the positively skewed distribution. According
to the results, there was significant improvement inshoulder range of motion after ASE. When the arm isswinging back and forth, the arm swings forward to
90 degrees and backward swing to 45 degrees. Increased shoulder range of motion can be achieved byrepeatedly stimulating shoulder muscles and joints[33].

Data collection
The trained examiner measured all before and after exercise data in the laboratory where the intervention occurred in the same sequence. Data from shoulder ROM, OWD and posture were collected twice,whereas heart rate was collected three times.
Data Analysis
SPSS 20.0 was used to process and analyze alldata. Paired-sample T test was used to compare themeans of before and after the intervention. The levelof significance was set at p < 0.05.
72

SEE - Bangkok, Thailand, Nov.11-13, 2019side view, back view, left view. Through PostureScreen

Figure. 3 Shoulder flexion
Note: SFLt.1 means Shoulder flexion before exercise (left); SFLt.2 means Shoulder flexion after
exercise (left); SFRt.1 means Shoulder flexion
before exercise (right); SFRt.2 means Shoulder
flexion after exercise (right))
Fig 5

Occiput-wall distance between Pre-ASE

and Post-ASE
analysis, average lateral postural displacements ofparticipants were measured. The results showed nosignificant improvement in average lateral postural
displacements of participants (P >0.05), however, theresults of this study may be due to the short time ofintervention of ASE, the usual training period being
eight weeks or more to improve posture significantly.
DISCUSSION

Fig. 4
Shoulder abduction
Note: SALt.1 means Shoulder abduction before
exercise(left); SALt.2 means Shoulder abduction
after exercise (left); SARt.1 means Shoulder abduction before exercise (right); SARt.2 means
Shoulder abduction after exercise (right)

This study was to preliminarily examine the immediate effects of ASE on shoulder range of motion(ROM): after 10 minutes of ASE, shoulder ROM wasincreased in all directions. Based on changes frombaseline to intervention, all participants showed improvement in shoulder flexion, abduction, medial rotation, lateral rotation and extension measurements.
Short-term exercise can effectively increase theshoulder range of motion. These results are in linewith other previous studies using different types of
exercise. One study reported that regular exercise is
an important factor in maintaining the shoulder rangeof motion of older women. Women between the agesof 50 and 71 who participate in regular exercise(twice a week) can improve and/or maintain a shoulder range of motion [24]. Pilates exercises are effective in improving shoulder abduction and external rotation ROM [25]. Traditional Chinese Qigong training among breast cancer patients effectively increased shoulder muscle strength, shoulder range of
motion and was associated with better functional
wellbeing [26].
In this study, however, after one session of practicing traditional Chinese ASE training, the range of
motion of shoulders was significantly improved.
Probably the manner of ASE directly affects the muscles around the shoulder joints. Clinical observations
have shown that posterior shoulder tightness leads to

Occiput-wall distance (OWD)
The median measurement of OWD before theASE was 4.93cm and after the ASE median measurement was 3.63cm (Figure 5). OWD was decreased by
1.3cm after the ASE (P < 0.05). This decreased in
OWD indicated that the kyphotic posture of the participants has been decreased.
Heart Rate (HR)Before ASE the mean HR was 79 bpm (beats per
minute), during exercise (at 5-minute mark) the mean
HR was 93 bpm and after ASE, the mean HR was 103
bpm. ASE is a low-intensity traditional Chinese
QiGong [19]. The result from the HR monitoring has
confirmed that the intensity of this observed ASE waslow.
PostureThis study used the PostureScreen mobile application to take participants photos: front view, right73

SEE - Bangkok, Thailand, Nov.11-13, 2019a variety of kinematic changes, such as decreased
shoulder rotation, horizontal adduction, abduction,
flexion, and increased external rotation. During ASE,
the posterior shoulder, acromioclavicular joints, biceps, trapezius and deltoid were fully mobilized [33].
This may be one reason to increase the range of shoulder movement.
The results of this study also demonstrate that
ASE therapy may provide immediate improvements
on OWD in young adults as indicated by a significant
decrease OWD after ASE. OWD is a quick and simple method for the evaluation of kyphosis and also aneffective way to assess posture [28]. Long-term ASE
training in the future may improve OWD more effectively and decrease kyphotic posture.
During ASE the body was in a straight line; headand shoulders move back, chest moved forward, feetshoulder-width apart, which allows the entire coremuscles to be activated. If ASE is done correctly, it
can improve the participant’s core muscle control, effectively promoting the participant’s core strength,core endurance, and it can mobilize the spinal joint[29]. Therefore, it provides benefits to the participant’s posture (decrease in OWD). It may help activate many major core and limb muscles, for example,
splenius capitis and splenius cervicis, deltoids, triceps, brachialis, biceps and core muscles, such as
erector spinae, multifidus, gluteus maximus and rectus femoris [30].
A 10-minute training did not significantly improve participants’ standing posture as detected by
the Postural Screen application program. Probably thechanges in whole-body posture have been compensated by many axial joints and core muscles. It may
require long-term and regular ASE training to affectthe improvement in posture. In addition, the participants in this pilot study were healthy young adults
having no significant posture problems such that nochanges could be observed after a single session ofASE.
A targeted exercise program (10-week trial) was
found to improve posture adjustments associated withforward head posture. [30] The formation of humanposture is a long-term development, so correcting aperson’s established posture or posture may also require a long process [32], [33]. In order to detect asignificantly change in posture, a randomized controlled trial on the effect of ASE on posture is neededin future studies.
We acknowledge that our research design has
some limitations. Firstly, the physiological mechanism of ASE in this study cannot be fully explained,
nor did it fully explain the physiological mechanismof ASE on the shoulder ROM, OWD and Posture.
Secondly, the power of statistical analysis of thisstudy was limited due to the small sample size yetthere was no control group for comparison. In the future, an improved randomized controlled trial will be
more appropriate.

CONCLUSIONSASE may provide immediate improvements onshoulder ROM and forward head posture as indicatedby a decreased OWD. A 10-minute training did not
significantly improve participants’ standing posture.
Long-term and regular ASE training is required tomaximize its benefits including improvement in posture. Further research using a randomized controlled
trial is needed.
ACKNOWLEDGMENTS
We would like to thank the Faculty of Associated Medical Sciences, the research center in Back
Neck and Other Joint Pain Research Group, Research
and Training Center for Enhancing Quality of Life ofWorking-Age People and the Khon Kaen University
for financially supporting this project.
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75

5th Int. Conf.on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

COMPARISON OF INTRAOCULAR PRESSURE CHANGES AFTERVIEWING LAPTOP COMPUTER AND TABLET COMPUTER: A
PILOT STUDY
Pattrawan Pattaranit1, Tanapat Ratanapakorn2, Rungthip Puntumetakul3, Orawan Buranruk3, and* Wichai Eungpinichpong3
1
Faculty of associated medical sciences, Khon Kaen University, Thailand;2
Faculty of medicine, Khon Kaen University, Thailand;3
Research and Training Center for Enhancing Quality of Life of Working Age People, Khon Kaen University,
Thailand

ABSTRACT
Prolonged computer use has been reported to be associated with elevated intraocular pressure and anincreased risk of Computer Vision Syndrome. However, this issue has been one of controversy. The aim of thisstudy was to preliminarily investigate the effect of using a laptop computer and tablet computer in terms ofchanges to intraocular pressure (IOP) in healthy young participants. Ten healthy participants (aged 29±6.36
years; male: female = 3:7) participated and were randomly allocated into one of the two groups (laptop computer
users and tablet computer users). Each subject was requested to work on either a laptop or tablet for 60 minutes.
IOP was subsequently measured via a non-contact tonometer in both eyes at 15, 30, 45, and 60 minute intervals.
Pre-intervention IOP and IOP changes were compared within and between groups. The results showed that themean IOP at each time point was not significantly different when compared among pre-intervention at different
time points in both eyes. Mean IOP in the laptop computer group was slightly higher than that of the tablet
computer group, yet there was no significant difference. The results of this study demonstrate that laptop andtablet usage for 60 minutes may have no effect on IOP levels in healthy volunteers. Hence, further research
involving a larger sample size and longer exposure time to computer screens is needed.
Keywords: Intraocular pressure, Laptop computer, Tablet computer, Computer vision syndrome

intraocular pressure (IOP) [7], [8]. Elevated IOP is
one of the major risk factors in relation todegenerative eye disease and glaucoma: one of theleading causes of preventable blindness worldwide[9]-[12]. This ocular disease, if untreated, may leadto optic nerve degeneration and possibly result invisual impairment and blindness [13]. IOP isconsidered to be normal between the ranges of 9 and
21 mmHg [14], [15]. The risk of developing
glaucoma may increase if IOP rises above 21 mmHg[15]. There is a significant increase in the risk ofdeveloping visual field loss (even with only a small
increase in IOP), especially once IOP rises above 26
mmHg to 30 mmHg [16], [17]. Therefore, almost all
current treatment options for glaucoma are aimed atlowering or preventing a rise in IOP [18]. Body
posture is believed to be one factor which influences
IOP fluctuation [19]. A previous study found that
there was a significant increase in IOP during neckflexion when measured in a sitting position among
healthy participants [21]. Furthermore, due to theportability of and ability to carry computer devices,many individuals tend to spend several hours a day

INTRODUCTION
Nowadays, computers have a great deal of
impact in almost every aspect of our daily lives.
Moreover, they have been developed to be easily
carried in the form of portable computers including
laptop computers, tablet computers and smartphones[1]. These devices are employed worldwide due totheir convenience and efficiency with regards toaccessinginformation,
writing
articles,communicating with others, and watching videos[2]. Consequently, many individuals spend asignificant amount of time utilizing digital devices.
With the rapid growth of digital device usage, there
has been an increase in the development of
numerous computer-related visual symptoms.
Symptoms reported include headaches, eye strain,
blurred vision, and eye irritation with symptom
severity rising with the number of hours spent on
devices [3]-[5]. Collectively, these disorders are
known as computer vision syndrome (CVS) [6].
Many studies have recently suggested that longexposure to computer screens can cause elevated76SEE - Bangkok, Thailand, Nov.11-13, 2019using a laptop or tablet computer in a poor anddamaging posture. A prolonged poor-posturecoupled with staring at a computer screen for long
periods may cause more severe elevation of IOP,
and subsequently appear to put users at an increased
risk of developing glaucoma. One study
demonstrated that the use of smartphones rendered agreater head flexion when compared to utilizing
desktop computers [20].
As noted previously, some studies have reported
that the range of head flexion among users is related
to different types of computer tasks and computerdevices [20], [22]. Another study highlighted thatvisual fatigue and discomfort were significantly
induced by tablet computer screen viewing, [23] andanother recent study was focused on using
smartphones in daylight and low-light conditions interms of alterations to IOP.
To date, no definite conclusion has been
mentioned in terms of the effects of prolonged usageof portable computers incorporating different
degrees of head flexion on IOP in healthy
participants. Hence, this study aimed topreliminarily explore the effect of two different head
positions while viewing a computer screen. The
study also compared IOP values between laptop andcomputer users, and tablet computer users at
difference time points.

prior, and they were requested to sleep for at least 68 hours the night before determination of IOP.
Materials and Procedures
In this preliminary study, participants wererandomly divided into two groups of 5 (10eyes/group). They were grouped as follows:
Group 1 (laptop computer user group): firstly,
participants were seated quietly in an examination
chair with an adjusted backrest angle of 90° for 5
minutes. Subsequent to resting, participants wereassessed for IOP as a pre-intervention value. Then,they were asked to watch a laptop computer screen(LENOVOTM Ideapad 310, Lenovo Group Ltd.,
China, 14-inch screen, 141 PPI) with brightness set
at 188 cd/m2. Viewing distance was approximately
50 cm. IOPs were subsequently, measured at 15, 30,
45 and 60 minutes after exposure to the laptop
screen.
Group 2 (tablet computer user group): in thisgroup, tablet computer (iPad® Pro 3rd Generation,
Apple Inc., California, USA, 12.9-inch screen, 264
PPI) with brightness set at 600 cd/m2 was employed.
After a resting period of 5 minutes, a tablet wasplaced on a participant’s lap at a distance of 30-40
cm from the eyes. IOPs were measured before
viewing and at 15, 30, 45, 60 minutes post viewing.
Each participant was requested to maintain a headposture with the neck at a 40°-60° flexion while
viewing the tablet for 15 minutes. IOP was thenevaluated in the upright position. All IOP
measurements were taken within 30 seconds in a 90°
upright sitting posture with the right eye always
measured first. Three consecutive IOP readings wereobtained with the same non-contact tonometer(NCT; Nidek Co., Ltd., Aichi, Japan) and the meansof readings were recorded for further statisticalanalysis. During laptop computer and tablet
computer usage, participants were requested tocontinuously maintain the same head posture anddistance from the screen.
Data was collected in the research laboratory
which was set up and located in the Faculty of
Associated Medical Sciences, Khon Kaen University,
Thailand. The experiments were performed in anexperimental room incorporating an illuminationlevel of 300 lux and a room temperature of 25°C.
To avoid possible
diurnal IOP
variation,allmeasurements were scheduled between 08:00-10:00
in the morning.

METHOD
Participants
The participants in this study were students andemployees of Khon Kaen University, Thailand aged
20-40 years. This study followed the Declaration of
Helsinki and was approved by the Khon Kaen
University Ethics Committee for Human Research.
All participants were given details of experimental
procedures before the study, and they gave theirconsent to participate. They were then requested tocomplete a questionnaire on computer usage amid
their daily lives. Participants who spent more than 4hours a day viewing a computer or tablet wereselected to participate. Moreover, participants were
included if they presented no signs or symptoms ofglaucoma, crossed eyes, narrow angles, corneal
infection or ulcer, corneal scarring, uveitis, retinal
tear or detachment. The IOP of each of the recruitedparticipants was less than or equal to 22 mmHg inthe sitting position with refractive error at between-4.00 and +2.00 diopters. Participants were excluded
if 1. They had received β–blockers or steroids prior
to the IOP measurements, and 2. They were unable
to maintain the head in the neck flexion or neckextension position for at least 15 minutes. In order toavoid IOP disturbance, participants were asked not
to drink caffeinated products or alcohol 12 hours

Statistical Analysis
Statistical analysis was done using SPSS
software version 23.0 for Windows (SPSS Inc.,
Chicago, IL). All values were presented as mean ±standard deviation. Comparison of mean values
between pre-intervention and different time points
77

SEE - Bangkok, Thailand, Nov.11-13, 2019within each group was analyzed by applying apaired-sample t-test, while the independent-sample
t-test was used to compare between groups. For all
tests, P-values less than 0.05 were considered
statistically significant.

group. IOP values at 4 check-out points (15, 30, 45
and 60 minutes) were compared to pre-intervention
IOP values. Accordingly, it was discovered that
there was no significant difference in IOP at
different time points. The mean IOP value at preintervention in the right eye among laptop users was
slightly lower than IOP at 60 minutes, yet thisdifference was not statistically significant.
Table 3 shows mean IOP between both laptop
computer user and tablet computer user groups.
When comparing IOP values between the 2 groups,
the mean value of eyes in the laptop group was
higher than in the tablet user group at every timecheck-point. However, no significant difference intheir IOP value was observed between the groups in
the right eye as well as in all left eye IOP
measurements.

RESULTSA total of 10 healthy participants (20 eyes) were
included (7 female and 3 male) into this preliminary
study with a mean age of 29±6.36 (range 23-39)
years. Five of the 10 individuals were assigned towatch a laptop computer screen while the remaining
participants were assigned to watch a tablet
computer screen. Participants’ demographic data aresummarized in Table 1.
Table 2 shows the IOP measurements obtained inboth the right and left eyes of both the laptop
computer user group and the tablet computer user
Table 1 Participant demographic data.
Group
Laptop users
Tablet users
Table

2

N
5
5

Within-groupGroup
Laptopcomputeruser
Tabletcomputeruser

comparison

Age (years)
29.80±7.98
28.2±5.07
of

IOP

value

(mmHg)

changes

Gender (male/female)
2/3
1/4
among

study

participants.

Side

Pre-intervention

15 min30 min45 min60 minRight
P-value*Left
P-valueRight
P-valueLeft
P-value

14.52±1.91

15.12±2.01
0.325
14.74±2.05
0.191
13.52±1.91
0.696
12.72±1.86
0.834

14.94±4.39
0.787
14.32±2.80
0.716
12.38±1.98
0.473
12.26±2.18
0.717

15.14±2.51
0.176
14.14±2.37
0.828
12.86±2.32
0.757
12.46±2.32
1.000

15.32±2.15
0.20313.20±1.62
0.465
12.92±1.770.808
12.26±1.96
0.618

14.00±2.41
13.14±1.66
12.46±1.86

Table 3 Between-group comparison of IOP value (mmHg) changes at different checkout points among laptop
computer and tablet computer user groups.
Group Side
Laptop user
Tablet user
P-value*

Pre-intervention
Right
Left
14.52
14.00
±1.91
±2.42
13.14± 12.46
1.66
±1.86
0.26
0.29

15 minRight
Left
15.12 14.74±2.01 ±2.06
13.52 12.72±1.91 ±1.86
0.23
0.14

DISCUSSION
Prolonged viewing of a computer screen cancause IOP elevation which is a major risk inrelation to developing glaucoma [8], [25]. The
underlying mechanism of ocular dynamics inregards these IOP changes during prolonged workin front of a computer screen is not yet fully

30 min45 min60 min
Right
Left
Right
Left
Right
Left
14.94 14.32 15.14 14.14 15.32 13.20±4.39 ±2.80 ±2.51 ±2.37 ±2.15 ±1.6212.38 12.26 12.86 12.46 12.92 12.26±1.98 ±2.18 ±2.32 ±2.32 ±1.77 ±1.96
0.27
0.23
0.17
0.29
0.09
0.43
understood. Available evidence has suggested that
IOP alterations are supposed to be involved during
theoccurrenceofaccommodation
andconvergence when the eyes attempt to focus on
images in close proximity.
Moreover, the researchers assume further studies
are needed to confirm that dry eyes and neckflexion posture due to extended periods of78

SEE - Bangkok, Thailand, Nov.11-13, 2019

electronic display usage can cause IOP elevation.
In addition, psychophysiological stress isreportedly associated with fluctuations in IOP [8].
In this study, we examined the changes to IOP at
different time junctures using 2 types of computer
screen in different head flexion angles.
Studies in normal participants have revealed
that numerous factors affect IOP. IOP
measurements were taken when sitting with theneck in the neutral position. Whereas, all otherhead positions including flexion, extension andsupine body positions result in IOP elevation. [21].
Additionally, a study revealed that participants
maintained a head flexion of 33°-45° from verticalwhen using a smartphone [20]. Similarly, anotherstudy showed that head and neck flexion angles
during tablet use were higher than when utilizing
desktop and notebook computers [22]. Ha [8]reported that IOP was significantly increased
immediately after 5 minutes and continued to beelevated throughout 25 minutes post smartphone
use under lowlight conditions. Another researchshowed that 4 hours of computer work resulted insignificant IOP elevation among healthy young
participants [7]. Based on the aforementioned
information, it would be reasonable to suggest thata forward head and neck flexion posture whenusing a mobile computer may cause IOP
fluctuation.
To the best of our knowledge, the current study
is the first research to investigate IOP changes
induced by viewing both laptop and tablet screens.
Nonetheless, our findings did not support any ofthe earlier findings because the results did notshow any significant changes to IOP amid preintervention compared with different check-time
points in both groups. In addition, IOP among
participants who used a laptop computer for a
prolonged duration did not demonstrate statisticalsignificant difference when compared withparticipants who used a tablet computer at any
time point.
This preliminary study has several limitations
that require consideration. First, the present study
was limited in terms of the small number ofparticipants. Thus, further studies are needed to be
carried out among larger populations. Anotherlimitation is that IOP value was collected for only
a short time. Hence, a study employing a longer
duration of computer usage will be considered.
Lastly, IOP measurement utilizing a reliable
method is necessary. Goldmann applanation
tonometry (GAT) is regarded as the gold standard
and thus ought to be applied amid further studies.

healthy participants. However, further studies areneeded in order to clarify whether or not posturalchanges associated with prolonged use of laptop
computers or tablet computers cause IOP
fluctuation.
ACKNOWLEDGEMENTS
This study was granted by the Research andTraining Center for Enhancing Quality of Life ofWorking Age People, Khon Kaen University,
Thailand.
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80

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE CRUDE TANNIN EXTRACTION FROM WOOD SCRAP WASTESFOR PROLONGING THE SHELF LIFE OF LITCHI FRUITS
Pornanan Boonkorn, Angkhana Chuajedton and Weeranuch Karuehanon
Science Faculty, Lampang Rajabhat University, Lampang, Thailand

ABSTRACT
Waste from wood scrap is an important problem in areas of wood handicraft performed. The purposes of thisresearch was to study the optimum condition for crude tannin extraction from those wastes and usage them forprolonging shelf life of litchi fruits. Various chemicals used for the extraction included distilled water, 95%
ethanol, 8% sodium carbonate and their combinations. The proportion between wood scrap per solvent were 1:10
or 1:20 g.mL-1 and extraction temperature were 70, 80 or 90°C. The basic chemical characteristics of the extracted
tannin were tested. Quantification of tannin was performed by spectrophotometry. The results found that optimum
solvent was 95% ethanol with proportion at 1:10 g.mL-1 and 80°C extracted temperature, which gave the maximum
amount of tannin (12.34 mg.g-1 dry weight). Then, crude tannin was tested for the in vitro fungicidal effect topathogenic fungi isolated from litchi fruits. The PDA medium containing crude tannin at different concentrations
including; 0, 0.1, 0.2 and 0.4 % were tested in comparing to 0.1 % benomyl fungicide. The result was found that
PDA containing 0.2 and 0.4 % of extracted tannin significantly (P0.05) inhibited growth of fungal mycelium
better than 0 and 0.1 % but still lower than benomyl fungicide. The in vivo test with litchi fruits by soaking the
fruits in various concentrations of crude tannin; 0, 0.1, 0.2 and 0.4%, compared to 0.1% benomyl fungicide wasfound that 0.2% tannin could extend the shelf life of litchi fruits better than other concentrations but its efficiency
was still lower than benomyl fungicide.
Keywords: Tannin, Wood scrap, Shelf life, Litchi

decay. The high incidence of postharvest disease inlitchi is primarily caused by green mold, P. digitatum.
The fungus preferentially penetrate through wounds
that occur during harvesting and postharvest
handling. Fungicide is widely used to reduce
pathogenic fungi and extend shelf life of litchi fruits.
However it is becoming less effective because ofpathogenic resistance, along with consumer concerns
about possible risk associated with the use ofchemicals. Among a number of new strategies being
investigated to control postharvest decay, natural
plant extract may be an alternative to traditional
postharvest fungicide practices. The purposes of thisresearch was to study the optimum condition for
crude tannin extraction from wood scrap wastes andusage them as an antifungal agent for prolonging
shelf life of litchi fruits.

INTRODUCTION
Tannins are polyphenolic compounds found inalmost plants. The compounds are widely used intanning leather industries, clarifying wine and beer,or used as mordant in dyeing and astringents inmedicine. Mangrove is well known as tannin
resources [1]. The increasing demand for the raw
material in extracting natural tannin along with theconservation of mangrove as a coastal protection andcultivated area for various marine lives, newresources of tannin are needed. Wooden handicraft,such as carvings, mortars and mobiles, is one of animportant products of Northern Thailand. Wastes
from wood scrap is a problem in the area. Villagers
re-use them as mushroom cultivation medium andcharcoal briquette. Tannin extracted from these wood
scraps is one of an interesting way in reducing
wooden waste. There are several studies on
antimicrobial effects of tannin extracts from various
plants such as rain tree pods [2], coconut mesocarp[3], guava leaves [4] or chestnut and quabracho [5].
A number of tannin extraction solvents andconditions have also been tested and reported.
Litchi (Litchi chinensis Sonn. cv. Hong Huay) is
an economically important fruit of Thailand.
Postharvest loss of the fruit is a big problem for both
domestic and foreign markets. Postharvest
deterioration of the fruit is mainly due to fungal

MATERIALS AND METHODS
Wood scrap waste was collected from Look
village, Lampang province, Thailand in May, 2018. It
was dried, cut into small pieces and milled to a fined
powder. Tannin extraction was conducted withvarious solvents included distilled water, 95%
ethanol, 8% sodium carbonate, 95% ethanol : distilledwater (1:1 v/v) and 8% sodium carbonate : distilledwater (1:1 v/v). The proportion between wood scrap
per solvent were 1:10 or 1:20 g.mL-1 and extraction
81

SEE - Bangkok, Thailand, Nov.11-13, 2019

temperature were 70, 80 or 90°C. Each experiment
was performed in triplicate.
Wood scrap and solvent at the tested ratio wereadded into a 1000-ml flask and then incubated in awater bath at the tested temperature with the shaking
speed of 100 rpm for 2 hours. Crude extracted tanninfrom all treatments were then evaporated to dryness
in hot air oven at 50°C to constant weight.
Quantification of tannin was performed byspectrophotometry at 700 nm, serial dilutions ofstandard tannic acid were used to obtain thecalibration curve [2]. The basic chemical
characteristics of the extracted tannin were tested
comparing to standard tannic acid by the interaction
with ferric chloride (1% FeCl3), 1% gelatin, and lead
acetate (1% Pb(C2H3O2)2) followed the methods of
Moosophin et al. [6] and Elgailani and Ishak [7].

in May, 2018. Before any commercial postharvest
treatment was applied, the fruits were selected byhand and transported to the laboratory at Lampang
Rajabhat University within 5 hours. The uniform andnon-damage fruits were selected. The pedicels of
the fruit were cut, 0.5 mm left intact on fruit, anddivided into 5 groups. Crude extracted tannin was
suspended in distilled water to make a concentrationof 0 , 0.1, 0 . 2 and 0.4 percent. Positive control was
0.1% benomyl fungicide. All the fruits were thensoaked in the prepared tannin treatment suspensions
or fungicide suspension for 20 minutes with softly
shaking fruits in the suspensions every 2 minutes.
After soaking, fruits were dried at 25oC for 1 hour andthen kept in foam tray, 10 fruits per tray, and wrappedwith polyvinylchloride plastic. All treatments werestored at 15+1oC, samples were taken every 2 days.
Fruit samples in each treatment, three replicates of ten
fruits, were inspected for disease incidence. Fruits
showing white mycelium on the peels wereconsidered as infected fruits. Disease incidence wasexpressed as percentage of infected fruits from three
replicates of ten fruits. Shelf life of the fruits wereconsidered acceptable only if disease incidence
was less than 50%.

In vitro and in vivo antifungal activity screeningtest
A 7-day-old of Penicillium digitatum on potato
dextrose agar (PDA) plate, obtained from the
Department of Biology, Faculty of Science, Lampang
Rajabhat University, Lampang, Thailand, was used
for the study.
For the in vitro test, crude extracted tannin withthe optimum extraction condition from the previous
experiment was used. The crude extract wassuspended in a newly prepared PDA medium, before
the agar hardened, to make a concentration of 0 , 0.1,
0 . 2 and 0.4 percent. Positive control was 0.1%
benomyl. Mycelium discs of P. digitatum were cut
with a sterile cork-borer (0.4 cm diameter) and each
one was placed on the surface of a treatment PDA
plate, 5 plates per treatment. All the dishes were thenincubated at 25oC. Mycelium diameter was measured
after 72 hours of the incubation
For the in vivo test, ‘Hong Huay’ litchi fruits thatgrown under standard cultural practices were
harvested at commercial maturity stage from an
orchard in Amphoe Mae-rim, Chiang Mai, Thailand

Statistical analysis
All analyses were run in triplicate or more. Data
analysis was done by One-Way ANOVA and meandifferences were analyzed by least significant
differences at P  0.05.
RESULTS
Wood scrap waste sample of rain tree (Samanea
saman (Jacq.) Merr.), from mortars handicraft, wascollected from Look village, Lampang province,
Thailand in May, 2018 as shown in Fig. 1. Woods ofrain tree were left outdoor until making mortars andleft a lot of wood scrap waste under the machine.

Fig. 1 Woods of rain tree and their scrap waste from mortars handicraft82

SEE - Bangkok, Thailand, Nov.11-13, 2019

Maceration method was used for tannin
extraction in this study. It is a simple extraction
method, done by immersing plant sample in an
organic solvent. Organic solvents will penetrate thecell wall into the cavity of the cell that contains theactive substances so the active substances will
dissolve [4]. In this study, the appropriate condition
in extracting tannin from wood waste was 95%
ethanol with a proportion of wood scrap per solventat 1:10 or 1:20 g.mL-1, 80 or 90°C extracted
temperature, which gave the maximum amount oftannin (Table 1). The color of all crude extracts were
present in Fig.2 which shown that the color of theextract were not accordance to tannin content.
Various researchers tried to find an appropriate
solvents in extracting tannin from plants. Various
results of that were found, such as acetone for
Galium tunetanum extraction [8], acetone-water
mixtures for grape skin extraction [9], 8% sodium
carbonate for Pinus oocarpa extraction [10], mixtureof water and 95% ethanol for mangosteen peel
extraction [6] and n-hexane for pods of rain tree
extraction [2]. These different results may comefrom the different in plant species, part of the plants
or conditions and methods of the extraction. In thisstudy, we found that extraction ratio of wood scrap
per solvent at 1:10 or 1:20 and extraction
temperature at 80 oC or 90 oC gave the similar content
of crude tannin (not statistically difference at P0.05). So, for an economically reason, the low
solvent and temperature usage would be an ideal
extraction procedure for feasible usage. As a reason,
the ratio at 1:10 and temperature at 80 oC weresuitable in tannin extraction in this study. Dried
brownish crude extract from the optimum extraction
condition was shown in Fig. 3.
Tannin extracted from wood scrap of rain treewith 95% ethanol at 80oC extraction temperature and1:10 g.mL-1 proportion of wood scrap per solventswas then tested for antifungal effect against
mycelium disc of Penicillium digitatum, which is an
important pathogenic fungi of litchi fruits after
harvest, and the ability for prolonged the storage lifeof litchi fruits at 15+1oC. The basic chemical
characteristics of the crude tannin extract incomparison with standard tannin was shown in Table
2. The ability to interact with metal ions such as
FeCl3 and Pb(C2H3O2)2 and the ability to precipitate
protein such as gelatin in comparison to standard
tannin indicated the presence of tannin in the crude
extract as described by Moosophin et al. [6] andElgailani and Ishak [7].

with various conditions

Solvents

Distilledwater

Extraction
ratio(g.mL-1)

Extraction
temperature
(oC)

1:10

70
80
90
70
80
90
70
80
90
70
80
90
70
80
90
70
80
90
70
80
90
70
80
90
70
80
90
70
80
90

1:20

95%
ethanol

1:10

1:20

8% sodiumcarbonate

1:10

1:20

95%
ethanol :distilled
water

1:10

8% sodiumcarbonate :distilled
water

1:10

1:20

1:20

Tannincontent
(mg.
g-1)
2.05c
2.46c
2.54c
2.18c
2.62c
2.76c
7.26b
12.34a12.55a7.65b12.12a12.47a
4.06b
5.11b
6.03b
4.51b
6.14b
7.03b
5.11b
6.10b
6.55b
6.02b
6.54b
7.11b
2.06c
2.63c
2.65c
2.42c
2.47c
2.83c

Fig. 2 Color of the crude extract after extraction withvarious solvents

Table 1 Tannin content from wood scrap extracted
83

SEE - Bangkok, Thailand, Nov.11-13, 2019with the development of mass white mycelia andpowdery masses of olive green spores. The disease
incidence increased to 100, 100, 73.33, 100 and
46.66% in 0, 0.1, 0.2 and 0.4% tannin or 0.1%
benomyl, respectively after 14 days of storage at
15+1oC (Table 4 and Fig. 5).
The 0.1% benomyl and 0.2% tannin treatments
could delay the disease incidence after storage.
Interestingly that litchi fruits in 0.4% tannin
treatment had more severely disease incidence thanthe 0.2% treated fruits. The fruit peel damage from
acidic suspension of 0.4% tannin may be the reason
for this situation, because pH of the 0.4% tannin
suspension were 3.21 (data not shown) which may
destroy litchi fruit peel compared to the 0.2% tannin
treatment which had higher pH value (4.56).
Damage on fruit peel led the fungal easily penetrated
through wounds and growth rapidly.
Although 0.2% tannin and fungicide treatment
could delay disease incidence on litchi fruits,
however, it should be noted that the treatments did
not totally control the fruit decay at the end ofstorage period. The inability of tannin and fungicide
to control final incidence of mold may be attributed
to the growth of survival fungal spores after
treatments or fungal spores in ambient air penetrated
into natural micro-cracking on the fruit peel tissues
as described by Underhill and Critchley [11].

Fig. 3 Crude extract of tannin extracted with 95%
ethanol, 80°C at 1:10 g.mL-1 proportion
Table 2 Test of basic chemical characteristics of theextracted tannin from wood scrap in comparison
with standard tannin
Tannintype
Standard
tannicacid
Extracted
tannin*1% FeCl3
Black
precipitate

Chemical tests
1% gelatin 1%
Pb(C2H3O2)2
White
Dark
red
precipitate precipitate

Greenish
White
Dark
red
black
precipitate precipitate
precipitate
Note: *Tannin was extracted with an optimum
extraction condition (95% ethanol, 80oC and 1:10
g.mL-1 proportion)
Tannin treatment in vitro resulted in significantly
reduced mycelium disc diameter of P. digitatum
when compared to control (Table 3 and Fig.4). The
mycelium growth inhibition was numerically but notsignificantly (P<0.05) enhanced with increasingtannin concentration from 0.1 to 0.4 percent. The
mycelium diameter after growth on PDA with tannin
at concentrations 0, 0.1, 0.2 and 0.4% for 72 hours
were 9.00, 3.18, 2.68 and 2.66 cm, respectively. The
results confirm with the findings of Mailoa et al. [4]who found a significant inhibition of five different
pathogen microbial growth after treated with tannin
extracted from guava leaves with 30% ethanol. They
estimated that tannin in an extract can inhibit thesynthesis of 1,3 β-glucan, the main component of thefungal cell wall, by inhibiting the enzyme
responsible for building that polymer. Althoughtannin treatment could obviously suppressed themycelium growth when compared to the control, but
the efficacy was less than 0.1% benomyl fungicide.
Hoque et al. [5] also found that Chestnut tannin andQuabracho tannin did not show satisfactory
inhibition of mycelium growth of six fungal
pathogens when compared to fungicides.
The incidence of disease from in vivo test on
litchi fruit peels first appeared on the 8th day ofstorage at 15+1oC in all groups, except for the 0.2%
tannin and 0.1%benomyl treatment (data not shown).
Symptoms of fungal attack first appeared with white
mycelium on fruit peel (which was judged as
infected fruit). Severity increased with storage time

Table 3 Mycelium disc diameter of P. digitatum after
placed on PDA plate with various concentrations oftannin or 0.1% benomyl fungicide for 72 hours
Treatment
Diameter (cm)Control
9.00 a
0.1% tannin
3.18 b
0.2% tannin
2.68 b
0.4% tannin
2.66 b
0.1% benomyl
0.00* cNote: *The fungal was died after 48 hours of the
incubation in PDA with benomyl fungicide
Table 4 Percent of disease incidence of litchi fruits
after soaked in various concentrations of tannin or
0.1% benomyl fungicide and then kept at 15+1oC for
14 days
Treatment
Control
0.1% tannin
0.2% tannin
0.4% tannin
0.1% benomyl

84

Percent of disease
incidence (%)
100.00 a
100.00 a
73.33 b100.00 a
46.66 c

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 4 Mycelium diameter of P. digitatum after placed on PDA plate with various concentrations of tannin or 0.1%
benomyl fungicide for 72 hours

Fig. 5 Disease incidence of litchi fruits after soaked in various concentrations of tannin or 0.1% benomyl fungicide
and then kept at 15+1oC for 14 days
[2] Ukoha, P.O., Cemaluk, E.A.C., Nnamdi, O.L.,and Madus, E.P., Tannins and Other
Phytochemical of The Samanea saman Pods andTheir Antimicrobial Activities. African Journalof Pure and Applied Chemistry, Vol.5, Issue 8,
2011, pp. 237-244.
[3] Ramirez, M.G.L., Ruiz, H.G.O., Arzate, F.N.,
Gallegos, M.A.C., and Enriques, S.G.,
Evaluation of Fungi Toxic Activity of Tannins
and a Tannin-copper Complex From the
Mesocarp of Cocos nucifera Linn. Wood andFiber Science, Vol.44, Issue 4, 2012, pp. 357-364.
[4] Mailoa, M.N., Mahendradatta, M., Laga, A., andDjide, N., Antimicrobial Activities of Tannins
Extract from Guava Leaves (Psidium guajava L.)
on Pathogens Microbial. International Journal of
Scientific and Technology Research, Vol. 3,
Issue 1, 2014, pp. 236-241.
[5] Hoque, M.Z., Akanda, A.M., Miah, M.I.H.,
Bhuiyan, M.K.A., Miah, M.G., and Begum, F.,
In vitro Screening of Fungicides and Tannins
Against Fungal Pathogens of Jujube Fruits.
Progressive Agriculture, Vol. 27, Issue 2, 2016,
pp.154-161.
[6] Moosophin, K., Wetthaisong, T., Seeratchakot,
L., and Kokluecha, W., Tannin Extraction from
Mangosteen Peel for Protein Precipitation in
Wine. Khon Kaen University Research Journal,
Vol. 15, Issue 5, 2010, pp. 337-385.
[7] Elgailani, I.E.H., and lshak, C.Y., Methods for
Extraction and Characterization of Tannins fromCONCLUSIONS
1. The optimum solvent to obtain tannin extract ofwood scrap waste of rain tree was 95% ethanol withproportion of samples per solvent at 1:10 g.mL-1 and
80°C extracted temperature, which gave themaximum amount of tannin at 12.34 mg.g-1 dryweight
2. Tannin extract from wood scrap waste of rain tree
had antifungal activity against Penicillium digitatum(in vitro) and could prolonged the storage life oflitchi fruits
ACKNOWLEDGMENTS
I would like to thank the Faculty of Sciences,Lampang Rajabhat University, Lampang, Thailand,for supporting grant of the study. And I would liketo thanks all villagers in Look village, Lampang
province, Thailand for supporting wood scrap wastes
for this study.
REFERENCES[1] Hardoko, Sasmito, B.B., and Puspitasari, Y.E.,
Antidiabetic and Antioxidant Activities ofTannin Extract of Rhizophora mucronata leaves.
Journal of Chemical and Pharmaceutical
Research, Vol.8, Issue 3, 2016, pp. 143-148.
85

SEE - Bangkok, Thailand, Nov.11-13, 2019some Acacia Species of Sudan. Pakistan Journalof Analytical and Environmental Chemistry,
Vol.17, Issue 1, 2016, pp. 43-49.
[8] Gaamoune, S., Harzallah, D., Kada, S., andDahamna, S., The Comparison of Two Tannin
Extraction Methods from Galium tunetanum
Poiret and Their Antioxidant Capacities. Der
Pharmacia Lettre, Vol. 6, Issue 1, 2014, pp. 114119.
[9] Downey, M.O., and Hanlin, R.L., Comparison of
Ethanol and Acetone Mixtures for Extraction ofCondensed Tannin from Grape Skin. South
African Journal for Enology and Viticulture, Vol.

31, Issue 2, 2010, pp. 154-159.
[10] Vieira, M.C., Lelis, R.C.C., da Silva, B.C., andOliveira, G.L., Tannin Extraction from the
Bark of Pinus oocarpa var. oocarpa with
Sodium Carbonate and Sodium Bisulfite.
Floresta e Ambiente Vol. 18, Issue 1, 2011, pp.
1-8.
[11] Underhill, S.J.R., and Critchley, C.,
Physiological Biochemical and Anatomical
Changes in Lychee (Litchi chinensis Sonn.)
Pericarp
duringStorage.
JournalofHorticultural Science, Vol. 68, Issue 3, 1993,
pp. 327-335.

86

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EXTRACTION OF PECTIN FROM PEANUT SHELL WASTE
WITH HEATING IN COMBINATION WITHULTRASONIC-ASSISTED EXTRACTION
Chuajedton, A.1 , Karuehanon W.2 and Boonkorn, P.1
Department of Biology, Faculty of Science, Lampang Rajabhat University, Thailand
2
Department of Chemistry, Faculty of Science, Lampang Rajabhat University, Thailand
1

ABSTRACTThe extraction of pectin from peanut shell waste with heating in combination with ultrasonic-assisted
extraction (UAE) was studied. Powder of peanut shell was extracted at a temperature of 70, 80 and 90 °C for 2
hr. It was shown that the pectin extraction at 80 °C had the highest amount of pectin at 1.56±0.07 %, comparedto other treatments and the chemical characteristics of the extracted pectin were similar to commercial pectin.
Then, the pectin extraction condition at 80 °C for 2 hr was combined with UAE at 40kHz/1500W for 10, 20, and30 min. Results shown that pectin extraction at 80 °C for 2 hr in combination with UAE at 40kHz/1500W for 10
min had the highest amount of extracted pectin at 1.61±0.04 % with 88.64± 2.69 % degree of esterification,
52.12±1.46 % galacturonic acid, 9.40 % moisture and 13.50 % ash which were the most similar properties tocommercial pectin compared to other treatments. Therefore, pectin extraction with heating in combination with
UAE method appeared to be an increasing pectin extraction when compared to the conventional method.
Keywords: extraction, peanut shell, pectin, ultrasonicagricultural residues. Pectin is one of the mostimportant and widely used in the food industry. It is
used as a gelling, stabilizing, encapsulating agents,
and a thickening agent such as jellies and jams [8].
The pectin content has resulted in different
extraction methods. It depended on the raw material,
the extraction methods, and further chemical
purification treatments. The conventional extraction
technique was a regular solvent extraction based on
stirring and heating. It was extracted by acidic
solvent at high temperature [6]., microwave-assisted
extraction (MAE), ultrasound-assisted extraction(UAE), and enzymatic extraction. Moreover, theextracted pectin investigated the combination of two
or more techniques.
UAE is a process that highly efficient in terms ofacoustic energy and solvents to extract compounds
from various plant matrices. It can be relatively shorttimes and obtain the yield quantity and high purity[9]. The mechanism of UAE based on the interactionof the ultrasonic waves and molecules of the solvent
allowing cavitation and cell disruption by ultrasonicwaves may enhance the mass transfer across the cell
membranes [6]. The increasing extraction yield isfragmentation mechanisms that result in reducing
particle size and increasing the surface area of themass transfer [10]. The standard frequencies ofultrasonic waves comprised between 20 kHz and
100 kHz.
Furthermore, the high ultrasonic power induces
the greater shorten that results in the fragmentationof material [11]. High efficiencies recently reported

INTRODUCTION
Peanut (Arachis hypogaea L.) is an important oiland protein crop in the world. It belongs to
Leguminosae. Peanut crops used for oil production,
roasted peanut and snack product, etc. [1] However,
the amount of waste is generated in the process of
harvest or oil extraction which is only a few wastes
of peanut is used as animal feed and treated as afertilizer. It regarded as agriculture waste. Peanut
shell waste derived from the harvested groundnut
such as the kernels is used to roasted snack peanuts
and peanut oil, which generated a shelled peanutkernel. Sobolev and Cole [2] reported that a little
peanut shell makes the cattle feed or extract ofphenolic compounds. So, the more efficientutilization of peanut shell as a renewable raw
material can provide for the extraction ofcompounds.
Pectin is a polysaccharide in the primary cell
walls and middle lamellae of many plants and fruits
and associated with cellulose, hemicellulose, andlignin structures [3]. Pectin forms the most complex
of polysaccharides, which pectin backbone
composed of (1 → 4)- α -D-galacturonic acidmolecules [4], [5]. For example, plants of Lupinus
genus had pectin contents around 1.5%–7% or peach(Persica vulgaris L.) had pectin contents up to 10%.
[6]. As well as from the agricultural and foodindustries to obtain pectin contents with over 15%
on dry basis by-products [7]. The extraction method
for pectin is a new trend for the revalorization of87

SEE - Bangkok, Thailand, Nov.11-13, 2019

for the UAE of pectin from several agricultural
wastes, such as pomegranate peel [12], passion fruit
peel [13] and Opuntia ficus indica cladodes [14].
However, this study about the peanut shell waste fora renewable raw material can provide for the
extraction of pectin. Thus, this research was todetermine the extraction of pectin from peanut shell
waste with heating in combination with ultrasonicassisted extraction (UAE).

temperature for 120 minutes and adjusted to 2.0
using 0.25 M HCl. Then, the solution was filteredwith a white cloth, and then the solution was
precipitated using 95% ethanol (solution/ethanol
ratio 1:3). And then, the precipitate was filteredusing vacuum filtration. The precipitate was later
rinsed three times using 70% ethanol. Subsequently,
it was dried at 40°C using an oven until constantweight. The extraction yield was calculated

MATERIALS AND METHODS
Physiochemical analyses of the extracted pectin
Degree of esterification
The degree of esterification (DE) of pectin wasdetermined by Rangana [16]. A dried sample ofpectin (0.5 g) was solubilized in 100 ml of water
without CO2 with 2 ml of ethanol. After the sample
completely dissolved, five drops of phenolphthalein
were added. The solution was titrated with 0.5
NaOH, and the volume of NaOH dissolved wasrecorded as the initial titer. Then, 10 ml of 0.5
NaOH was added and allowed to stand for 15
minutes. And then, 10 ml of 0.5 HCl was added, andthe sample was shaken until the pink color
disappeared. Five phenolphthalein was added andtitrated with 0.5 NaOH to pink color, and the volume
of NaOH dissolved was recorded as the final titer.
The DE was calculated from the following equation:

The plant materials
Peanut shell (Arachis hypogaea L.) collectedfrom peanut farm in Mae-Tha, Lampang Province,
Thailand and transported to the Laboratory at
Lampang Rajabhat University. The peanut shell was
immersed in hot air oven at 55°C for 24 hr and thendried peanut shell were ground until obtaining a fine
powder using a grinding machine and stored at room
temperature until use.
Determination of heating for pectin extraction
The extraction process was performed using thefollowing condition by Pagan [15]. The powder of
peanut shell 33 g added to 100 ml of distilled water
after that, pH of solution was adjusted to 2.0 using
0.25 M HCl. The extraction by using thethermostatic bath at three different temperatures (70,80, and 90°C) for 120 minutes and stir every 30
minutes. After heating, each treatment filtered with awhite cloth, and then the solution was precipitatedusing 95% ethanol (solution/ethanol ratio 1:3). And
then, the precipitate was filtered using vacuum
filtration. The precipitate was later rinsed three times
using 70% ethanol. Subsequently, it was dried at
40°C using an oven until constant weight. The
extraction yield was calculated as follows:

DE% =final titerinitial titer + final titer

X 100

Galacturonic acid
Galacturonic acid (GA) was determined by
Rangana [16]. A dried sample of pectin (0.01 g) was
solubilized in 100 ml of 0.05 N NaOH and allowed
stand for 25 minutes. The sample 2 ml was diluted
with 100 ml of distilled water and then sampling 2
ml immersed into the test tube with 1 ml of 0.1%
carbazole. Then, 12 ml of 98% H2SO4 was added
and allowed stand for 25 minutes, and absorbancewas measured at 525 nm with UV-VIS
spectrophotometer. The GA content was expressed
as GA% (w/w), obtained from a calibration curve of
galacturonic acid standard solutions (Fig. 1).

Extraction yield (%) = Pectin weight (g) X 100
Sample weight (g)Determination of heating in combination withultrasonic-assisted
extractionforpectinextraction
The powders of peanut shells were extractedwith the optimal condition determined fromconventional heating. The powder of peanut shell 33
g was added to 100 ml of distilled water and pH 2.0(0.25 M HCl). The pectin extraction condition at
80 °C for 2 hr was combined with UAE [14] at thefrequency of 40 kHz and the power of intensity of1500 W for 10, 20 and 30 min. After the time
extraction, each treatment was cooled at room

Determination of moisture content and ash content
The moisture content and ash content were
determined by the standard test method (ASTM
D3173-95). For moisture content, a dried sample ofpectin (1 g) was immersed into the crucible, closewith a cover and inserted into the furnace chamber
which maintained the temperature at 150 for 3 hr
until constant weight. The moisture content wascalculated as follows:88SEE - Bangkok, Thailand, Nov.11-13, 2019

Moisture (% wb) = A-BA

fruit preservatives and juices and jellies [20]. While
GA content of all treatments was similar tocommercial pectin, which is related to thecharacteristic of the ability of pectin to form gels.
Moisture contents were similar to all treatments andash content had significantly, and at 80°C had thehighest when compared to all treatments.

X 100

where: A = weight of sample used (g)B = weight of sample after heating (g)For ash content, a dried sample of pectin (1 g)
was immersed into the crucible, close with a coverand inserted into the furnace chamber which
maintained the temperature at 650 for 3 hr until
constant weight. The ash content was calculated asfollows:

Determination of heating in combination withultrasonic-assisted
extractionforpectinextraction
Pectin extraction with heating in combination
with UAE represented Fig. 3 and Fig. 4. The yield of
pectin extraction showed the highest yield at 80°C in
combination with UAE for 10 minutes of 1.67
yield% (w/w) while, UAE for 20 minutes UAE for
30 minutes had the yield of 1.37 and 1.21 yield%(w/w), respectively. Xu [21] found that the longer
time of extraction occurred the yield slightly
decreased. The extraction with heating in
combination with UAE could result in the enhanced
ability of pectin extraction. Wang [9] reported thatthe pectin extraction of grapefruit peel obtained the
optimum time was 29.95 minutes at the power
intensity of 12.56W and the temperature at 66.71°C,
as well as Moorthy [12], found that the maximum
extraction yields of pomegranate peel were
determined at 61.9 °C for 28.3 minutes resulting inyield extraction of 24.2%. The extraction
temperature and sonication time are essential for
UAE. In the other hand, the extraction conditions ofsisal fibers showed the optimal extraction condition
was 61 W for 26 min and temperature at 50 °C
resulting in pectin yield of 29.3% [22]. Therefore,
UAE destructed the cell wall by allowing cavitationand enhance the mass transfer across the cell
membranes [6]. The characteristic of pectin as
represented in Table 2. The result showed that theamount of DE and GA significantly obtained thehighest DE% at UAE 10 minutes gave the amount of
DE of 88.64 %, which was high DM. And GA% in
UAE 30 minutes was similar to UAE 10 and 20
minutes. Moisture contents were similar to alltreatments and ash content had significantly, andUAE 20 minutes had the highest when compared to
all treatments.

Ash (% wb) = weight of sample used (g)X 100weight of sample after heating (g)Statistical analysis
All experiments were replicated three times andevaluated with the regression procedure using SPSS
version 17. Differences among treatments performed
using Duncan's Multiple Range test (P ≤ 0.05).
RESULTS AND DISCUSSION

Absorbance (525 nm)

Determination of heating for pectin extraction
The yield of pectin extraction revealed in Fig. 2.
The result showed that the amount of pectin
extracted significantly obtained the highest yield at
80°C of 1.56 yield% (w/w). Meanwhile, thetemperature at 70°C and 90°C had a yield of 1.19
and 0.72 yield% (w/w), respectively. The highextraction yields were obtained at high temperaturesand low pH values due to the separating of pectin,
and other cell wall materials. As well as Oliveira[17] reported that the extraction of banana fruit had
been considered an excellent source of pectin which
was used to determine the effect of pH 2.0–4.5 andthe temperature between 70–90 °C for 120–240
minutes under stirring at 150 rpm. In the same way,
Korish [18] reported that Citrullus lanatus var.
Colocynthoides watermelon obtained the optimum
yield (16.7%) with acidic water solution (HCl, pH
2.0) at 85 °C for 60 min. In the other agriculturalresidues, peels of yellow passion fruit and dragon
fruit gave pectin yield of 14.2% and 12.6% at pH
2.4 and the extraction times for 58 and 65 min,respectively [19]. Physiochemical analysis ofheating for the extracted pectin as represented inTable 1. The result showed that DE and GA content
of pectin extraction had non-significant whencompared to commercial pectin. DE content at 80°C
obtained the highest amount of DE of 70.41 %,which the degree of methyl-esterification containing
up to 50% was pectin with high DM. It was used asa gelling component in heat-resistant bakery jams,

0.8

y = 0.0075x - 0.0044
R² = 0.9917

0.6
0.4
0.2
0
0

20

40

60

80

Concentration of galacturonic acid (µg/ml)

Fig. 1 Standard curve of galacturonic acid

89

100

SEE - Bangkok, Thailand, Nov.11-13, 2019

1.8

aExtraction Yield (%w/w)

Extraction Yield (%w/w)

2
b
1.5

a
1

0.5

a

1.6

b

b

UAE 20 min

UAE 30 min

1.4
1.2
1
0.8

0.6
0.4
0.2
0
UAE 10 min

0
70 C

80 C

90 C

Treatments

Temperature (°C)

Fig. 3Fig. 2 Yield of pectin extracted at different
temperatures. The result followed by error
bar represented standard deviations. Values
with the same letter on the same color bars
represented no significance differences(*P≤0.05)

Yield of pectin extracted with heating at
80°C and UAE. The result followed byerror bar represented standard deviations.
Values with the same letter on the samecolor bars represented no significancedifferences (*P≤0.05)

Table 1 Characteristics of pectin extracted at different temperatures.
Characteristics
Commercial pectin
70 °C
80 °C
90 °C
a
a
b
83.10±4.63
DE%70.41±9.23
66.37±10.15a
29.35±4.82aaaGA (% w/w)
30.36±8.33
24.85±0.5424.18±0.38
24.18±0.69aaaa
Moisture (%wb)
9.10 ±0.55
7.00±0.32
8.00±0.87
8.30±0.52aaac
Ash (% wb)
8.70±0.19
13.00±0.72
28.20±0.13
20.10±0.46b*mean value followed by different superscript in the same row differs significantly by Duncan’s new multiple
range test (P≤0.05).
Table 2 Characteristics of pectin extracted with heating at 80°C and UAE at different times.
Characteristics
Commercial pectin
UAE 10 min
UAE 20 min
UAE 30 minaab
83.10±4.63
DE%88.64±2.69
79.35±5.21a62.25±5.82aabGA(% w/w)
57.12±1.4656.96±4.1458.58±0.87a
30.36±8.33aaa
Moisture(%wb)
9.10±0.03
9.40±0.119.30±0.1212.70±0.55aaabAsh(% wb)
8.70±0.32
13.50±0.72
27.80±0.13
24.10±0.55b*mean value followed by different superscript in the same row differs significantly by Duncan’s new multiple
range test (P≤0.05).

aFig. 4bcdPectin extracted from peanut shell waste with heating at 80°C and UAE at different times (a) UAE 10
min (b) UAE 10 min (c) UAE 10 min (d) commercial pectin.

90

SEE - Bangkok, Thailand, Nov.11-13, 2019

Grapefruit peel: Optimization and Comparison
with the Conventional Method. Food Chem.,
Vol, 178, 2015, pp. 106–114.
[10] Chamet F., Huma Z. and Khan M. K.
Application of Ultrasoundin Food
Technology : Processing Preservation and
Extraction, Ultrasonics Sonochemistry, Vol.
18. Issue 4, 2011, pp. 813-835.
[11] Bermudez D. A., Mobbs T. and Barbosa C. G.
Ultrasound Application in Food Processing. In
H. Feng G., Barbosa C. and Weiss J. (Eds.)
Ultrasound Technologies for Food andBioprocessing , New York Springer, 2011, pp.
65-105.
[12] Moorthy I. G., Maran J. P., Surya S. M.,
Naganyashree S. andShivamathi C. S.
Response Surface Optimization of UltrasoundAssisted
ExtractionofPectinfrom
Pomegranate Peel. Int. J. Biol. Macromol. Vol.
72, 2015, pp. 1323–1328.
[13] Cibele F. O., Giordani D. Lutckemeier R.
Gurak P. D. Olivera F. C. and Markczak L. D
.F. Extraction of Pectin from Passion Fruit Peel
Assisted by Ultrasound. LWT- Food Scienceand Technology, Vol. 71, 2016, pp. 110-115.
[14] Bayar N., Bouallegue T. Achour M. Kriaa M.
and Bougatef A. Ultrasonic Extraction of
Pectin from Opuntia ficus indica Cladodes
after Mucilage removeal: Optimization ofExperimental Condition and Evaluation ofChemical and Functional Propoties.Food
Chemistry, Vol. 235, 2017, pp. 275-282.
[15] Pagan J., IbarzA., Lorca M., Pagan A. andBarboza-Canovas G. V. Extraction andCharacterization of Pectin for stored peachpomace.
Food Researc
International,Vol. 24, 2001, pp.605-612.
[16] Rangana S. Manual of Analysis of Fruit andVegetable Products. Tata Mc. Graw Hill Pulblishing Company Limited. 1977.
[17] Oliveira T. Í. S., Rosa M. F., Cavalcante F. L.,
Pereira P. H. F., Moates G. K., Wellner N.,
Mazzetto S. E., Waldron K.W. and Azeredo H.
M. C. Optimization of Pectin Extraction from
Banana Peels with Citric acid by Using
Response Surface Methodology. Food Chem.
2015, in press.
[18] Korish M. Potential Utilization of Citrullus
lanatus var. Colocynthoides Waste as a Novel
Source of Pectin. J. Food Sci. Technol. Vol. 52,
2015, pp. 2401–2407.
[19] Liew S. Q., Chin N. L.; Yusof Y. A. andCheok C. Y. Citric acid Extraction of Pectinfrom Tropical Fruit Peels of Passion fruit,
Dragon fruit and Soursop. J. Food Agric.
Environ. Vol. 13, 2015, pp. 45–51.
[20] Valdes A. Burgos N. Jimenez A. andGarriogos
M.
C.
NaurakPectinPolysaccharides as Edible Coatings. Coating,

CONCLUSIONSThe extraction of pectin from peanut shell wastewith heating in combination with ultrasonicassisted extraction (UAE) appeared to be anincreasing pectin extraction. The pectin extraction
at 80 °C had optimal condition and the pectin
extraction condition at 80 °C for 2 hr was combinedwith UAE at 40kHz/1500W for 10 min had theamount of extracted pectin, degree of esterification,
galacturonic acid, moisture and ash content whichwere the most similar properties to commercial
pectin compared to other treatments.
ACKNOWLEDGMENTS
This work has been supported by Department of
Biology, Faculty of Science, Lampang Rajabhat
University.
REFERENCES[1] Rustom I. Y. S., Lopez-Leiva M. H. and Nair
B. M. Nutritional, Sensory and Physiochemical
Properties of Peanut Beverage Sterilized under
Two Different UHT Condition. Food
Chemistry, Vol. 56, 1996, pp. 45-53.
[2] Sobolev V. S. and Cole R. J. Note on
Utilization of Peanut Seed Test. J. Sci. Food.
Agric, Vol 84, 2003, pp. 4295-4302.
[3] Anuradha K., Padma P.N., Venkateshwar S.
and Reddy G. Fungal Isolates from Natural
Pectic Substrates for Polygalacturonase andMultienzyme Production. Indian J. Microbiol.,Vol. 50, 2010, pp. 339–344.
[4] Pedrolli D.B., Monteiro A.C., Gomes E. andCarmona
E.C. Pectin and Pectinases:
Production, Characterization and Industrial
Application of Microbial Pectinolytic Enzymes.
Open Biotechnol. J., Vol. 3, 2009, pp.9–18.
[5] Caffall K.H. and Mohnen D. The Sructure,
Function, and Biosynthesis of Plant Cell Wall
Pectic Polysaccharides. Carbohydr. Res. Vol.
344, 2009, pp. 1879–1900.
[6] Ovodov Y.S. Current Views on Pectin
Substances. Russ. J. Bioorg. Chem., Vol. 35,
2009, pp. 269–284.
[7] Giovanetti M.H., Nogueira A., de Oliveira, C.L.
and Wosiacki G. Chromatography—The Most
Versatile Method of Chemical Analysis
InTech: Rijeka, Croatia, 2012.
[8] Thakur B. R. and Handa A. K. Chemistry andUse of Pectin- a Review. Critical Reviews inFood Science and Nutrition, Vol. 37, Issue 1,
199, pp. 47-73.
[9] Wang W., Ma X., Xu Y., Cao Y., Jiang Z.,
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[21] Xu Y. Zhang L. Bailina Y., Ge Z. and Ye T.
Effect of Ultrasound and/or heating on the
Extraction of Pectin from Grapefruit Peel.

Journal of Food Engineering, Vol. 126, 2014,
pp. 72-81.
[22] Maran J. P. and Priya B. Ultrasound-assisted
Extraction of Pectin from Sisal Waste.
Carbohyd. Polym.Vol. 115, 2015, pp. 732–738.

925th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF COMBINATION MICROWAVE AND OVEN DRYING ON
THE CHEMICAL PROPERTIES OF CRUDE PALM OIL OBTAINEDFROM DIFFERENT OIL PALM FRUIT RIPENESS
1

Mallika Tapanwong1, Rayakorn Nokkaew2 and Vittaya Punsuvon1,2
Faculty of Science, Kasetsart University, Thailand; 2Center of Excellence-Oil Palm
Kasetsart University, Thailand

ABSTRACT
Small crude palm oil mill in Thailand produced the low quality of crude palm oil by using oven drying to dry
palm fruits for 14-16 hours. So, the aim of this study is to replace oven drying by using the combined microwave
and oven drying to dry palm fruits at different ripeness for 3-4 hours. The effects of combined methods on thechemical properties of crude palm oil are evaluated and compared the properties with premium crude palm oil.
The experiments of study follow this details. The raw materials were 18, 20, 22 and 24% of oil content consistedin oil palm bunch. In experiment, 1 kg of each sample was heated at 750 watt for 10 minutes in microwave followed
oven drying for 3 hours. Heated palm fruits were further separated the mesocarp from kernel seed. The mesocarp
was further pressed by hydraulic presser to obtain crude palm oil. The oil was analyzed the chemical properties interm of free fatty acid (FFA), deterioration of bleachability (DOBI), carotene content, vitamin E content, fatty acidcomposition, iodine value (IV) and peroxide value (PV). The results showed that all of oil palm fruits ripeness can
produce a grade A crude palm oil with low free fatty acid content and high DOBI value.
Keywords: Microwave, Oven, Oil palm fruit, Ripenessfruit follow these details. Cheng [4] found that thequality of the crude palm oil produced by microwave
pretreatment followed with solvent extraction was
superior compared to that produced by using
conventional means in terms of lower acidity, lower
moisture content, higher carotene content and higher
vitamin E content. Tan [5] studied the combined
process of microwave pretreatment and solvent
extraction in the laboratory scale and found that thisprocess gave high yield of palm oil, low free fatty acidcontent, low peroxide value, low anisidine value andhigh carotene content of the obtained palm oil. Chow[6] studied the detachment of palm fruits from wholebunches and spikelets using microwave heating. The
result showed that microwave heating had highsufficiently detached the palm fruits from both wholebunches and spikelets in the easy way by using aslight push of the finger. Sarah [2] studied the effectof sterilization time and temperature on fatty acids
composition, carotene and vitamin E content of oil
extracted from palm fruit that irradiated by
microwave energy. The results showed that fatty
acids composition and vitamin E content were notinfluenced by time and temperature increment but
carotene content greatly influenced by temperature
increment.
Our studied replaced the drying palm fruit by hot
air into microwave for sterilization of palm fruit and
we found that microwave drying can inactivated thelipase enzyme activity that result in decreasing of thefree fatty acid in crude palm oil. In addition, the

INTRODUCTION
At the present, large and medium scale palm oil
mills in Thailand were used a steam sterilization
process which has pressurized the palm bunches of
15-45 psi for 90 min at a temperature more than 100
oC. Palm oil from this process has a good quality.
Nevertheless, effective steam sterilization process has
produce many waste water because of the large
amount water used in the process. Thus, the high costof discharge treatment was necessary to rigorous
environmental standard [1]. Most small scale mills in
Thailand do not have more ability to generate steam
for sterilization. Therefore, non-steam sterilization of
the bunch such as drying by hot air is alternative
process. But the disadvantage of this process isgetting lower quality of crude palm oil due toexcessive temperature and drying time of operation.
Microwave is electromagnetic waves withwavelengths ranging from 1 nm to 1 m, or frequencies
between 0.3 GHz to 300 GHz. Industry utilizes
microwave energy as a source of energy for heating
and sterilization [2]. The mechanism of heatgeneration in the palm oil fruit at a microscopic levelis due to the re-orientation of water molecules in thepalm fruit to follow electric field direction andinteract among themselves which creates friction andheat. The temperature rises of oil palm fruit thatexceed 47 oC enhance reduction or inhibition of lipase
enzyme activity [3]. Several studies reported theutilization of microwave to heat and sterilize oil palm

93

SEE - Bangkok, Thailand, Nov.11-13, 2019

deterioration of bleachability index (DOBI) value,
carotene content in crude palm oil can increase after
microwave drying of palm fruit, too. However, thedrying by microwave is not enough to decrease themoisture content in palm fruit to less than 10 %w/w
that is suitable for screw pressing. Thus, the palm fruitobtained after microwave drying need to decrease themoisture content by drying again with hot air in ovendrying for a few hour.
The aim of this research is to determine the effectof palm fruit maturity on the quality that obtained
after drying by microwave combined with ovendrying. Quality in term of chemical properties
measured were free fatty acid content (FFA), DOBI,
peroxide value (PV). Iodine value (IV), carotene
content and tocopherol content. All of these term arecompared significant differences or similarity
between different ripeness of palm fruit bunches
using statistical analysis.

FFA (%) =(S − B) × N × 25.6
W

(1)

Where, S is the volume of sodium hydroxide used
for oil titration, B is the volume of sodium hydroxideused for blank titration, N is the concentration of
sodium hydroxide, W is the weight of oil.
Determination of peroxide value (PV)A 5 g oil sample was dissolved in a 30 ml mixtureof acetic acid and chloroform which was further
reacted with 0.5 ml of saturated potassium iodine
solution. After one minute of shaking, 30 ml of water
were added and the contents were shaken vigorously
to liberate iodine from the organic to aqueous layer.
Iodine was titrated with a 0.1 N sodium thiosulphate
solution using a starch indicator. A blankdetermination was made using the same procedure
without the oil sample. PV was calculated using theEq. (2) (AOCS official method cd 8-53, 1997)

MATERIAL AND METHOD
Material

PV =(S − B) × N × 1000
W

(2)

Fresh palm fruit bunch at the different ripeness of
18, 20, 22 and 24% based on oil content of bunch
were collected from local oil palm plantation in
Pangnga province, Thailand. Fresh fruit bunches
were chopped into fruit spikelets and 1 kg of eachpiece was weighed for microwave drying.

Where, S is the volume of sodium thiosulphateused to titrate with oil sample, B is the volume ofsodium thiosulphate used to titrate with blank, N isthe concentration of sodium thiosulphate, W is theweight of oil.

Microwave and Oven Drying Experiments

Determination of iodine value (IV)

1 kg of fruit spikelet was weighed before
undergoing microwave drying (microwave ovensharp model with maximum power output of 850 W
at 2,450 MHz) for 10 minute intervals time until
100% stripping reach. The fruit at the spikelets weredetached with a slight push of a finger until the fruits
were completely detached from the spikelet. The
detached palm fruit were kept at room temperature for
one night after that they were dried in oven at 70-75o
C for 3 hours. After the drying process, the mesocarpof the fruit was peeled and the seeds were removed.
The peeled mesocarp was pressed using hydraulicpresser to extract the oil and the oil was collected for
its chemical analysis

IV was determined followed AOCS official
method cd 1-25. Briefly explained, 0.2 g of oil sample
was weight into 250 ml of iodine flask. Then, 10 mlof chloroform and 25 ml of wijs reagent was added tointo a flak, respectively. The analytical flask was
shaken vigorously and stored in a dark place for 2
hours. After that, the flask was added with 20 ml ofpotassium iodide followed with 15 ml of distillated
water. The sample solution was titrated immediately
with 0.1 N sodium thiosulphate until yellow color
almost disappears. A starch indicator was added into
sample and titrated continuously until the blue starchiodine color disappeared. In addition, a blank wasmade in the same manner. The IV value is calculated
followed Eq. (3)Chemical Analysis(B − S) × N × 12.69
W

Determination of free fatty acid content (FFA)IV =The FFA content of the oil sample was measure
by dissolving oil in 95% ethanol and titrated with 0.1
N sodium hydroxide solution using a phenolphthalein
indicator. A blank determination was also made withthe sample procedure without the oil sample. The
percentage of FFA content was calculated using thisEq. (1)

Where, B is the volume of sodium thiosulphateused to titrate with blank, S is the volume of sodium
thiosulphate used to titrate with oil sample, N is theconcentration of sodium thiosulphate, W is the weightof oil.
Determination of carotene content

94

(3)

SEE - Bangkok, Thailand, Nov.11-13, 2019

Carotene content were carried using MPOB test
method (2004). Briefly explained, 0.1 g of oil sample
was dissolved in n-hexane in a 25 ml volumetric flask.
The absorbance reading of the solution at 446 nm wastaken using UV-VIS spectrophotometer. The
carotene content is calculated as Eq. (4).
Total carotene content (ppm) =383(A)(V)
100(W)

Effect of Drying Process on FFA Content
A FFA content of each sample is shown in Table
1.
Table 1 The relationship of FFA on the ripeness ofoil palm fruit at different condition ofexperiment(4)

Ripeness
Average FFA (%w/w)
based
Raw
MW*
Left
After
on %oilmaterialfor 1
oven
content
night
drying1828.80a4.69b 2.21b
1.08b
a
b
b
20
28.41
3.26
1.25
1.28b
a
b
b
22
30.76
4.17
1.69
1.63b
24
28.43a2.87b 1.64b
1.65b*
MW means after microwave drying
a-b
Denotes statistically significant in a same row(P<0.05)

Where, A is the absorbance at 446 nm, V is thevolume of oil solution (25 ml) and W is the weight ingram of oil sample.
Determination of deterioration of bleachability index(DOBI)
DOBI was determined followed MPOB test
method (2004). DOBI is defines as the ratio of thespectrometric absorbance at 446 nm to 269 nm.
Briefly explained, 0.1 g of oil sample was weighed
into 25 ml of volumetric flask and dissolved with nhexane. The sample solution was measured
absorbance at 269 and 446 nm using UV-VIS
spectrophotometer. The value of DOBI is calculated
followed Eq. (5)DOBI =

Absorbance at 446 nm
Absorbance at 269 nm

It indicates that the microwave drying can reduce
the FFA content of all ripeness. Due to the lipase
enzyme which induces the hydrolysis reaction of
triglyceride to generate the FFA is inactivated by
microwave. The results showed that the drying
process affected to reduce the FFA content while thedifferent ripeness at the same drying step was notaffected. The statistical analysis showed that the FFA
content was not significant difference in all
experiment. In addition, the FFA content after ovendrying was 1.08-1.65 %w/w in all ripeness of palm
fruit.

(5)

Determination of α-tocopherol and γ-tocotrienol by
HPLC
A 20 µl of oil sample (obtained by solubilizing
250 mg of oil in 25 ml of n-hexane) was directly
injected to a HPLC column 15cm x 4.6 mm ID(Unison UK-Silica UK505, Imtakt, USA) at a flowrate of 1 ml/min and 292 nm of wavelength. The
HPLC system for α-tocopherol and γ-tocotrienol
content analysis consisted of Yonglin-HPLC
equipped UV detector. Standard solution of αtocopherol and γ-tocotrienol were used at 0-150 pm
concentration for quantification. The mobile phase
was 99.5% n-hexane and 0.5% isopropanol which
was HPLC grade.

Effect of Drying Process on Carotene Content and
DOBI
The total carotene content is shown in Table 2.
The result showed that the carotene content increase
after microwave drying. The carotene content wasslightly decreased after left for one night and afteroven drying. The obtained carotene content in all
ripeness of palm fruit was 554.7-731.5 ppm.
Table 2 The relationship of total carotene content on
the ripeness of oil palm fruit at different
condition of experiment

Statistical Analysis
All independent parameter were carried out in
triplicated and the result were expressed as the meanvalue. Data were statistically analyzed by analysis ofvariance (ANOVA) followed by Duncan test. The
significant level of difference between chemical
properties from different ripeness of oil palm bunch
were accessed. The level of significance is p<0.05.

Ripeness Average total carotene content (ppm)
based
Raw
MW*
Left
After
on %oilmaterialfor 1
oven
content
night
drying18396.2
610.2 598.4
554.7
20
411.8
682.3 755.3
639.2
22
599.0
689.4 714.8
646.0
24
699.7
742.7 704.0
731.5*
MW means after microwave drying
The statistical analysis showed that the carotene
content was not significant different in all experiment

RESULTS AND DISCUSSION

95

SEE - Bangkok, Thailand, Nov.11-13, 2019of different ripeness of oil palm fruit.

content. The peroxide value increased when thesample was treated by microwave. Due to themicrowave can induce the peroxide species on
unsaturated fatty acid molecule in palm oil. In ovendrying, the peroxide value increased when the
ripeness was increased.

Table 3 The relationship of DOBI on the ripeness ofoil palm fruit at different condition ofexperiment
Ripeness
Average DOBI
based
Raw
MW*
Left
After
on %oilmaterialfor 1
oven
content
night
drying
18
1.05b
4.07a
4.10a
3.89a
b
a
a
20
1.74
4.49
4.83
4.61a
b
a
a
22
2.05
4.75
4.78
4.18a
b
a
a
24
2.17
4.31
4.29
4.00a
*
MW means after microwave drying
a-b
Denotes statistically significant in a same row(P<0.05)

Effect of Drying Process on Iodine Value
The iodine value represents the number ofunsaturated species. Table 5 indicated that the drying
process wasn’t affected on iodine value for all
ripeness.
Table 5 The relationship of iodine value on the
ripeness of oil palm fruit at different
condition of experiment
Ripeness Average iodine value (g I2/100 g oil)
based
Raw
MW*
Left
After
on %oilmaterialfor 1
oven
content
night
drying
18
53.5
54.0
54.0
52.0B
20
56.9
56.2
56.8
55.9A
22
53.5
54.5
53.7
52.8B
24
54.0
54.2
53.8
53.3B
*
MW means after microwave drying
A-B
Denotes statistically significant in a same column(P<0.05)

In addition, The DOBI of oil after treatment wasaffected by drying process (Table 3). The results
indicated that DOBI value of all maturity increased
when the sample was treated by microwave and kept
constant though left for one night or oven drying. The
statistical analysis showed that DOBI value was not
significant different in all experiment of different
ripeness of oil palm fruit. The obtained DOBI afteroven drying was 3.89-4.61.
Effect of Drying Process on Peroxide Value
The peroxide value which represents the firstoxidation reaction is shown in Table 4.

However, the statistical analysis showedsignificant difference of iodine value on different
ripeness. For palm oil after oven drying, the highest
iodine value was 20% of oil content because of highoriginated amount. The obtained iodine value afteroven drying was 52.0-55.9.

Table 4 The relationship of peroxide value on the
ripeness of oil palm fruit at different
condition of experiment

Effect of Drying Process on α-tocopherol content

Ripeness
based
on %oilcontent

Average peroxide value(meq O2/kg oil)
Raw
MW*
Left
After
material
for 1
oven
night
drying
18
5.5a
1.5b
1.7b
0.4b,C
b
a
a
20
0.2
0.7
0.6
0.8a,BC
22
1.2
0.9
1.8
1.4B
24
3.8
2.3
2.7
2.5A
*
MW means after microwave drying
a-b
Denotes statistically significant in a same row(P<0.05)
A-C
Denotes statistically significant in a same column(P<0.05)

Crude palm oil is the one of vitamin E resources
which contained about 600-1000 ppm. A vitamin E inpalm oil consists of both tocopherol (21.3%) andtocotrienol (78.7%) [7]. A beneficial of vitamin E isantioxidant characterization that prevents theoxidation reaction of oil. In this study, the vitamin E
in form of α-tocopherol was study and shown in Table
6. The α-tocopherol content of sample after drying
process indicated that the microwave had affected toreduce the amount of α-tocopherol content. In the
ripeness comparison, the 18% of oil content gave thehighest α-tocopherol content and decreased when theoil content was increased. For γ-tocotrienol, the result
gave the same trend of α-tocopherol (Table 7). The γtocotrienol decreased when the sample was treated by
microwave but the ripeness was insignificant
difference.

In comparison of drying process, the statisticalanalysis investigated that the microwave drying had
affected on peroxide value at 18 and 20% of oilcontent while the other was not. The peroxide valueof palm oil after microwave treatment was decreased
from raw material at 18% of oil content. In 20% of oilcontent, the result was contrast with 18% of oil

Table 6 The relationship of α-tocopherol content on
the ripeness of oil palm fruit at different
96SEE - Bangkok, Thailand, Nov.11-13, 2019condition of experiment

beneficial for small palm oil mill to produce thepremium crude palm oil using the oil palm fruit
ripeness from 18-24% as raw materials.

Ripeness Average α-tocopherol content (ppm)
based
Raw
MW*
Left
After
on %oilmaterialfor 1
oven
content
night
drying18
1,248a,A 920b,A 967b,A 911b,A
20
933a,B
781b,B 784b,B 798b,B
22
811B
744B
739B
715BC
24
803B
722B
737B
740C
*
MW means after microwave drying
a-b
Denotes statistically significant in a same row(P<0.05)
A-C
Denotes statistically significant in a same column(P<0.05)

ACKNOWLEDGMENTS
This research was supported by Tech Enterprise
Service Network (TESNet), Center of Excellence-Oil
Palm, Kasetsart University and Department ofChemistry, Faculty of Science, Kasetsart University.
REFERENCES[1] Umudee
I.,
Chongcheawchamnan
M.,
Kaitweerasakul M. and Tongurai C., Sterilizationof Oil Palm Fresh Fruit Using Microwave
Technique, International Journal of Chemical
Engineering and Applications, Vol. 4, Issue 3,
2013, pp.111-113.
[2] Sarah M., Ramadhan M.R. and Zahra A., Effectof Sterilization Time and Temperature on Fatty
Acids, Carotenoids and Vitamin E of Oil
Extracted from Palm Fruit Irradiated byMicrowave Energy, Proceedings of the 4thInternational Symposium on Applied Chemistry,
2018, pp.020068-1 – 020068-8.
[3] Sarah M., Widyastuti S. and Ningsih D., Red
Palm Oil Production by Microwave Irradiation,
IOP Conference Series: Materials Science andEngineering, Vol. 309, 2018, pp.1-5.
[4] Cheng S.F., Mohd N.L. and Chuah C.H.,
Microwave Pretreatment: A Clean and Dry
Method for Palm Oil Production, Industrial Crops
and Products, Vol. 34, 2011, pp.967-971.
[5] Tan J. CX., Chuah C.H. and Cheng S.F., A
Combined Microwave Pretreatment/Solvent
Extraction Process for the Production of Oil from
Palm Fruit: Optimisation, Oil Quality and Effectof Prolonged Exposure. Journal of the Science ofFood and Agriculture, Vol. 97, 2017, pp.17841789.
[6] Chow M.C. and Ma A.N., Processing of Fresh
Palm Fruits Using Microwaves, Journal of
Microwave Power and Electromagnetic Energy,Vol. 40, Issue 3, 2007, pp.165-173.
[7] Kua Y.L., Gan S., Morris A. and Ng H.K.,
Optimization of Simultaneous Carotenes andVitamin E (Tocols) Extraction from Crude Palm
Olein Using Response Surface Methodology,
Chemical Engineering Communications, Vol. 205,
Issue 5, 2018, pp.596-609.
[8] Erkan, N., Ayranci G. and Ayranci, E., A Kinetic
Study of Oxidation Development in Sunflower
Oil under Microwave Heating: Effect of Natural
Antioxidant, Food Research International, Vol. 42,
Issue 5, 2009, pp. 1171-1177.

Table 7 The relationship of γ-tocotrienol content on
the ripeness of oil palm fruit at different
condition of experiment
Ripeness Average γ-tocotrienol content (ppm)
based
Raw
MW*
Left
After
on %oilmaterialfor 1
oven
content
night
drying
18
719a
64b
27b
a
b
20
474
32
24b,c
13c
22
727a
41b
8b
20b
a
b
b
24
809
17
12
19b
*
MW means after microwave drying
a-b
Denotes statistically significant in a same row(P<0.05)
However, γ-tocotrienol was more decreased bydrying treatment than α-tocopherol. The almost 90%of γ-tocotrienol was destructed by microwave
whereas α-tocopherol was lost about 15-30% in thisprocess. The reason might be molecular structuraldifference between both forms. The structure of both
vitamin E forms have the same chromanol ring but it
differ at the position of the side chain. The
unsaturated side chain of γ-tocotrienol is moresensitive to microwave heating than α-tocopherol
consisting saturated side chain. Thus, γ-tocotrienol
are easily destroy.
CONCLUSIONS
Microwave is one of several technique to improve
the quality of crude palm oil but this techniqueconsumes the high production cost. Thus, thecombination between microwave and oven drying are
the better choice for crude palm oil production. The
studied shows that the combined microwave and ovendrying can reduce the FFA content to less than 3%
and increase DOBI value to excess 3.5 which is thestandard of premium crude palm oil. This process is97

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECTS OF CHLORINE DIOXIDE DIPPING ON PERICARPBROWNING REDUCTION OF LONGAN FRUIT
Suttinee Likhittragulrung1,6 Tanachai Pankasemsuk2,3,4 Kanda Whangchai4,5
Wittaya Apai6 and Wanwarang Patanapoh1
1
Postharvest Technology Research Center, Faculty of Agriculture, Chiang Mai University,
Chiang Mai 50200, Thailand
2
Department of Plant and Soil Sciences, Faculty of Agriculture, Chiang Mai University,
Chiang Mai 50200, Thailand;
3International College of Digital Innovation, Faculty of Agriculture, Chiang Mai University,
Chiang Mai 50200, Thailand
4
Postharvest Technology Innovation Center, Office of the Higher Education Commission,
Bangkok 10400, Thailand
5
Department of Biology, Faculty of Science, Chiang Mai University,
Chiang Mai 50200, Thailand
6
Office of Agricultural Research and Development region 1, Chiang Mai 50100, Thailand

ABSTRACT
Pericarp browning is the main factor to reduce the storage life and marketability of longan fruit. In thepresent study evaluated chlorine dioxide (ClO2) dipping on reducing pericarp browning. Fresh longan fruit wasdipped in 1%, 1.25% and 1.5% ClO2 for 5 min and stored at 5±2 oC, 85±5% RH for 42 days, investigated every 7
days. Evaluation by browning index (BI) as pericarp browning, outer pericarp color by a chromameter expressedas L*and b* value and hue angle, disease incidence, ClO2 residue and sensory acceptance was determined. The
result showed that dipping in 1%, 1.25% and 1.5% ClO2 could reduce pericarp browning (lower BI, higher L*and b* value and hue angle). However, they showed no significant differences with commercial SO2 fumigation
but they were significant differences with untreated fruit. ClO 2 treatments could reduce disease incidence andlow ClO2 residue in flesh. The sensory acceptance such as outer pericarp color, flesh and flavor treated with
1.5% ClO2 had shown great potential. The results suggested that 1.5% ClO 2 dipping could reduce pericarp
browning of longan fruit as same as the commercial SO 2 fumigation.
Keywords: Longan fruit, Chlorine dioxide, Pericarp browning, and Sulfur dioxide(FDA) for dip or spray treatment of food items,
including fresh and fresh-cut fruits and vegetables,
and has shown a strong ability to control pathogen[4]. ASC is mixture of sodium chlorite (SC) and an
acid. Sodium chlorite, the major component of ASC,
also had strong anti-microbial ability against humanpathogenic bacteria. SC was strongly inhibited
enzymatic browning on fresh-cut apples. Because ofits dual role in browning inhibition and pathogen
inactivation, the anti-browning property of SC could
be attributed to two modes of action, i.e., direct
inactivation of polyphenol oxidase (PPO) activity
and oxidative degradation of the phenolic substrates[5] It could be combined with a substance for
improving better good quality that hydrochloric acid(HCl) mixed with SC produced chlorine dioxide(ClO2). It is one of the disinfectants has been used tocontrol microbial contamination. ClO2 solution
offers several advantages for food sanitizing,
especially for processing vegetables and fruits. The
used of ClO2 to reduce microorganism have beenreported in apple, carrot, lettuce, cabbage, tomato

INTRODUCTION
Longan (Dimocarpus longan Lour.) is nonclimacteric fruit, widely cultivated in many countries
especially in China, Vietnam and Thailand. In
Thailand cv. Daw is an important economic
exported fruit. It was very short postharvest life for
3-4 days under ambient temperatures. The main
factors reduce storage life and marketability of
longan fruit are pericarp browning, fungal andmicrobial decay [1], [2]. Sulfur dioxide (SO2)fumigation is commercially to extend shelf life of
fresh longan at least 45 days at low temperature [3].
It is the most popular commercial means forprevention of fruit decay and browning because it
was effective and inexpensive [1]. However, SO2
fumigation leaves SO2 residues and toxic ingredientsthat may have adverse effects on human health.
Therefore, a replacement of SO2 or improve processwith the safer for consumer are required.
Acidified sodium chlorite (ASC) is a sanitizing
agent approved by Food and Drug Administration
98

SEE - Bangkok, Thailand, Nov.11-13, 2019and blueberries [6]-[8]. In addition to the studies of
ClO2 has been used to reduce enzymatic andmaintain quality such as fresh-cut lotus roots, fleshcut asparagus lettuce and litchi fruit [9]-[11]. In
longan, the use of gaseous ClO2 concentration 10
mg/L for 10 min. was effective to reduce pericarp
browning during storage at 25 ํ C for 7 days [12].
Although gaseous form has greater penetration
ability and leave behind less residue [13] but theaqueous ClO2 form to reduce pericarp browning inlongan had still lack enough data. Therefore theobjective of this study was the effects of fruit
dipping in various concentration of ClO2 solution on
pericarp browning control and fruit quality of longan
fruit during cold storage.

Pericarp color was measured by chromameter(Model CR400, Minolta Japan). The results wereexpressed as L*, b* value and hue angle. L* value
indicated lightness of color wheel, ranged fromblack = 0 to white = 100, b* value = (-) blue toyellow (+) and hue angle was true color. Two spots
on opposite sides of the fruit were measured and themean of the two measurements considered as one
reading. The results were expressed as a mean value
from three replications of the 5 measured samples.
Flesh discoloration
The following scale was used: 1 = normal(excellent quality); 2 = slight flesh discolored; 3 =less than 25% discolored of the total surface; 4 = 2550% discolored; and 5 = 50% discolored (poorquality). A flesh discoloration index was calculatedusing the following formula: ∑ (discolor scale x
number of fruit in each class)/Total fruit. Fruits flesh
having a discolor score above 3.0 were rated as
unacceptable.

MATERIAL AND METHOD
Plant Material and ClO2 Treatment
Mature longan fruits (Daw) for export weretransported from packing house in Lamphunprovince, Thailand. They were placed in 11.5 kg
commercial perforated plastic basket, 15 baskets (9baskets for ClO2 treated , 3 baskets SO2 fumigatedand 3 baskets not treated) were transferred tolaboratory 1 day before testing and stored overnightat 5oC with 80-90% relative humidity (RH). Next
day, longan fruits were selected with uniformity
shape, color size and without disease or insect
infected and divided into 3 treatments for dipping in
ClO2 solution. Before treating each basket werecleaned with tap water, after that each treatment (3basket/treatment) were dipped in ClO2 solutions at
different concentration of 1%, 1.25% and 1.5% for 5
min which tested in only a fume hood for safer andallowed to air dry for 2 h and then stored at 5oC with
80-90% (RH) for 42 days. The samples were taken
every 7 days for quality evaluation as browningindex, pericarp color, disease incidence, sensory
evaluation and ClO2 residue and storage life until
day 42.

Disease incidence (DI) and sensory evaluation
Disease incidence was visually assessed bycounting the fruits that showed lesions of mycelium
or rot on the fruit surface. Sensory evaluation was
evaluated during cold storage every 7 days. The inhouse trained panel consisting of 10 members
assessed the samples. The acceptability of pericarp
color, flesh quality, taste and overall quality using afive-point hedonic scale where 5 = like extremely, 3= neither like nor dislike and 1 = dislike extremely.
Chlorine dioxide residues and storage life
ClO2 residues was evaluated by using DPD
method [15].The samples (100 g) of whole fruit(ClO2 residue on pericarp) and just a flesh (ClO2
residue on flesh) were rinsed with 100 ml distilledwater shaken at 160 rpm for 10 min. Ten millilitersof rinsed water were collected for analyze ClO2
residues [12]. The ClO2 residue in fruits was
expressed as mg/kg. Storage life was determinedfrom 3 parameters as browning index below 3.0score( Jiang and Li, 2001, disease incidence (%)
below 25% and sensory evaluation above 5.0 [16],[17]. Analysis of variance (ANOVA) and the test ofmean comparison according to least significant
difference (LSD) were applied with a significancelevel of 0.05.

Fruit Quality Evaluation
Browning index
Browning index was assessed visually the total ofbrown area on fruit surface by following scale: 1=
no browning, 2= slight browning, 3= less than 25%
browning of the total surface, 4= 25-50% browningand 5= >50% browning. The browning index was
calculated by (browning scale  percentage of fruitin each scale). A browning index scale over 3.0 was
considered as unacceptable marketability [14].
Pericarp color

99

SEE - Bangkok, Thailand, Nov.11-13, 2019

incidence (DI) at 6.7% at 42 day. Whereas theuntreated fruit had DI over than 25% in 28 days ofstorage at 5 ºC (Fig. 4) due to fruit rotting frommany diseases. The result found that high ClO2
concentration more than 1.25% increased highefficiency in preventing DI because ClO2 act asoxidizing agent could kill many pathogens. This
result was likely of Wu et al.[11] who observed
dipped litchi in ClO2 solution concentration at 80
mg/l and 120 mg/l were significantly to reduce
postharvest disease. On the other ClO2 treatment
were reduced microflora in mulberry fruit [21].
Saengnil et al.[12] was fumigated longan with 10
and 25 mg/l ClO2 could delay and reduced disease.
Due to ClO2 is the strong oxidizing and sanitizing
agents [simpson2005] possible to kill endospores,
virus, algae, fungi and some common bacillus [22].
Furthermore the various observations indicated thatthe increase BI is associated with DI development[11],[23] and also susceptible to various pathogen[2].

RESULT AND DISCUSSION
Pericarp Browning, Pericarp Color and Flesh
discoloration
In preliminary test was studied the effect ofdifferent ASC (HCl+NaClO2) concentration on
longan pericarp browning and extended shelf life. It
was found that fruits were dipped in HCl or NaClO2
alone did not reduced pericarp browning, the used ofHCl 9% combined with NaClO2 7.5% could
produced ClO2 2% (maximum concentration) was
the effective treatment to reduce pericarp browningand had storage life for 35 day at 5oC. In this study
was investigated in the effect of difference
concentration of ClO2 (1.0%, 1.25% and 1.5%) on
reducing pericarp browning. Pericarp browning wasshown as browning index (BI) and pericarp color.
Fruits dipping in all ClO2 concentration at 1.0%,
1.25% and 1.5% for 5 min could prevent pericarp
browning for 28 day (BI below 3.0) at 5 ºC (Fig. 1).
Whereas untreated fruit, pericarp became browningby 7 days at 5oC which indicated by BI above 3.0
due to chilling injury occurrence. For flesh
discoloration, all treatment was increased withstorage time increased but scores showed less thanlimit of acceptance (less than 3.0) throughout periodof time (Fig.2). BI was corresponded with pericarp
color as shown in L* ,b* value and hue angle, alltreatment of ClO2 were higher than the control after
treated and were maintained color for during 42 day
storage (Fig. 3a-c). This study was found that high
ClO2 concentration from 1 to 1.5% increased highbleaching effects in controlling pericarp browningwhich was contrasted that of Wu et al.[8] who
found that litchi were dipped in ClO2 at low
concentration of 120 mg/l was significantly lower BIthan the control after 5 day of harvest and the sameas Saengnil et al.[12] who use 10 and 25 mg/l ClO2
fumigation on longan fruit found that they weremaintained marketing quality of fruit at room
temperature for 5 day and delayed the decrease in L*
and b* value and hue angle. This could be explainedthat pericarp browning of longan fruit is primarily
attributed to oxidation of phenolic compounds by
PPO and POD [12],[18],[19] and possible that ClO2
might discolor longan pericarp by oxidation of lignin
as lignin oxidation in pulp bleaching [20]. ClO2
treatment significantly delayed the decrease in total
phenolic content which was accompanied with adecrease in activity of PPO and POD, leading to alower BI of longan pericarp [12].

ClO2 1.0%
SO2

Browning Index

6

ClO2 1.25%
untreated

ClO2 1.5%

5
4
3
2
1
0
1

7

14
21
28
Storage time (days)

35

42

Fig.1 Effect of ClO2 dipping on browning index oflongan pericarp during store at 5oC for 42 days (Dotline represents limit of acceptance).

Flesh discoloration

2.5
2
1.5
1
0.5
0
1

7

14

21

28

35

42

Storage time (days)

Fig.2 Effect of ClO2 dipping on flesh dicoloration of
longan during store at 5oC for 42 days (Dot line
represents limit of acceptance).
.

Disease Incidence (%)
In this study found that the treated treatment with1.25% and 1.5% of ClO2 showed no sign of diseasedeveloped during 42 day storage as same as SO2
treatment but ClO2 1.0% treated found disease100SEE - Bangkok, Thailand, Nov.11-13, 2019(a) 70

ClO2 1.0%
SO2

ClO2 1.25%
untreated

ClO2 1.5%

Sensory Evaluation

L* values

60

Pericarp color acceptance of longan fruit weretreated with 1.0%, 1.25% and 1.5% ClO2 were
acceptable for 42 days during storage. Whereas
untreated fruit was accepted for 1 day (Fig. 5a).
Flesh color and tasty acceptance, treated with ClO2
were accepted for 35 days showed no significant
difference with SO2, but untreated fruit was accepted
at 21 days and 35 days, respectively (fig. 5b,c). The
overall acceptance, dipped in 1.0%, 1.25%, 1.5%
ClO2 and SO2 fumigation were high acceptance ascompared with untreated fruit at 42 day, whereas
untreated fruit acceptable at 28 day (fig. 5c). The
result of this study are relate with Saengnil et al. [12]which longan fruit treated with 2.5-10 mg/l ClO2 10
min maintained higher sensory quality scores thanthose of the control. Furthermore sensory quality
evaluation just likely an overall visual quality(OVQ) of Du et al. [9] study found that 100 mg/l
ClO2 treatment 10 min generated high OVQ values
during storage time.

50
40
30
20
10
0

(b)

1

7

1

7

14
21
28
Storage time (days)

35

42

35

42

50

b* values

40
30
20
10
0

14

21

28

Storage time (days)(c)

ClO2 1.0%
SO2

84

ClO2 1.25%
untreated

Chlorine Dioxide Residues

ClO2 1.5%

hue angle

82

ClO2 can participate in series of oxidation
reactions and subsequently degrade to chlorite,
chlorate and chloride, they are the principal residues
from chlorine dioxide gas interaction with food [6],[15]. The Environmental Protection Agency (EPA)
and The National Institute for occupational Safety
and Health have established residual acceptancelevels as 0.8 mg/L for chlorine dioxide and 1.0 mg/L
for chlorite in drinking water [24]. Although it iswell known that a major benefit of ClO2 fordisinfecting drinking water is the lack of organochlorine compounds, the residues from the direct
treatment of fruits and vegetables have not been wellestablished [15]. In this study ClO2 residues on
longan pericarp was detected every 7 days duringstorage time after treated with 1.0%, 1.25% and1.5% ClO2 solution, the levels of ClO2 residues wasin ranking 0-0.12 mg/Kg, 0.07-0.22 mg/Kg and0.04-0.17 mg/Kg, respectively. Furthermore, ClO2
residues on fruit flesh was evaluated as pericarp,
there were 0-0.02 mg/Kg, 0-0.02 mg/Kg and 0-0.03
mg/Kg, respectively (data not shown). The levels of
ClO2 residues on pericarp and flesh of all treatment
were very low. The results are consistent with
Saengnil [12] who reported that ClO2 residues on
longan fruit were less than 0.014 mg/kg and notdetected in flesh. For this study is indicating that thephysiological of pericarp is different, ClO2 solution
can absorbed into flesh easily, but ClO2 residues
level on flesh was very low and less than 3 mg/kg
that limitation imposed by the FDA [FDA1998].

80
78
76
74
72
70
1

7

14
21
28
Storage time (days)

35

42

Fig.3 Effect of ClO2 dipping on L*(a), b*(b) valueand hue angle (c) of longan pericarp during store at
5oC for 42 days.
ClO2 1.0%
SO2

Disease Incidence (%)

120

ClO2 1.25%
untreated

ClO2 1.5%

100
80
60
40
20
0
1

7

14
21
28
Storage time (days)

35

42

Fig.4 Effect of ClO2 dipping on disease incidence(%) of longan during store at 5oC for 42 days (Dotline represents limit of acceptance).
.

101

SEE - Bangkok, Thailand, Nov.11-13, 2019

pericarp color acceptance(score)(a)
ClO2 1.0%
SO2

6

ClO2 1.25%
untreated

CONCLUSIONClO2 1.5%

5

The results showed that dipping in 1.0%, 1.25%
and 1.5% ClO2 for 5 min were effective to reduce
pericarp browning, postharvest decay and extended
storage time for 42 days at 5oC. Therefore, dippingin 1.5% ClO2 solution could be used to reduce
pericarp browning and further study more. It will be
one of alternative to replace SO2 in the future.

4
3
2
1
0
1

7

14
21
28
Storage time (days)

35

42

ACKNOWLEDGMENTS

flesh color acceptance(score)(b)
6This work was funded in part by grants from theAgricultural Research Development Agency,
Thailand through Postharvest Technology ResearchCenter, Faculty of Agriculture, Chiang Mai
University. The authors wish to thank all the staff ofresearchers in the Laboratory of OARD1,
Department of Agriculture.

5
4
3
2
1
0

1

7

14

21

28

35

42

Storage time (days)

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.

Tasty acceptance (score)(c)
ClO2 1.0%
SO2

6

ClO2 1.25%
untreated

ClO2 1.5%

5
4
3
2
1
0
1

7

1

7

Overall acceptamce (score)

(d)

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21
28
Storage time (days)

35

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42

6
5

4
3
2
1
0
21

28

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Storage time (days)

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pericarp during store at 5oC for 42 days (Dot line
represents limit of acceptance).

102

SEE - Bangkok, Thailand, Nov.11-13, 2019

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[15] Trinetta, V., N. Vaidya, R. Linton and M.
Morgan., Evaluation of chlorine dioxide
gas residues on selected food produce.
Journal of Food Science,76, 2011, pp. T11T15.
[16] Lawless, H.T. and Heymann, H., Sensory
Evaluation of
Food: Principles andPractices. Chapman and Hall. New York,
1998, pp. 848.
[17] Apai, W., Klongdee, H., Sukhvibul, N.,
Noppakoonwong, U., Lim, S.S., Luk, C.S.,
Tan, S.C.A., Neo, S.Y., Hoon, K.G., Lee,
C.A., Amareok, S., Rattanakam, S. andSardsud, V., Study on the Feasibility of Useof Hydrochloric Acid as an Alternative to
Sulphur Dioxide for Preserving Longan.
Food and Applied Bioscience Journal 3,2015, pp 193–205.
[18] Khunpon, B., J. Uthaibutra, B. Faiyue andK.
Saengnil. Reduction of enzymaticbrowning of harvested'Daw' longan
exocarp by sodium chlorite. Science Asia.
37, 2011, pp. 234-239.
[19] Chomkititichai,W.,
Faiyue,B.,
Rachtanapun, P., Uthaibutra, J., Saengnil,K., Enhancement of the antioxidant
defense system of post-harvested ‘Daw’
longan fruit by chlorine dioxide fumigation.
J. of Scientia Horticulture, 178, 2014
pp.138-144.
[20] Tarvo, V., Modeling chlorine dioxide
bleaching of chemical pulp. (Ph.D. Thesis
in Chemical Engineering). School of
Science and Technology, Aalto University.
2010.
[21] Chen, Z., Zhu, C. and Han, Z., Effects ofaqueous chlorine dioxide treatment on
nutritional components and shelf-life of
mulberry fruit (Morus alba L.). J. Biosci.
Bioeng, 111, 2011, pp 675-681.
[22] Du, J.H., Fu, M.R., Li, M.M. and Xia, W.,
Effects of chlorine dioxide gas on
postharvest physiology and storage qualityof green bell pepper (Capsicum frutescens
L. var. Longrum). Agric. Sci. China 6,
2007, pp. 214-219.
[23] Li, X., Liu, A.Y. and Chen, W., Studies ondevelopment and control of anthracnose oflychee fruit before and after harvest. Acta
Hortic, 665, 2005, pp. 409-413.
[24] EPA, Environmental Protection Agency,
IRIS,. Information on chlorine dioxide.
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DC, USA. 1998.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SPATIAL DISTRIBUTION OF RESTAURANT POPULARITY INDEXBASED ON CONSUMER REVIEW WEBSITE IN JAKARTA
Dewi Susiloningtyas1, Alexander Tio2, Supriatna3 and Sidiq, IPA4
Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Indonesia

ABSTRACT
Nowdays there has been a remarkable surge in the usage of social media specially in urban area in choosing
restaurant that they want to visit. This surge becoming new phenomenon that change people lifestyle and behavior
in urban area and that is include how people receive information from word of mouth (WoM) recommendation forrestaurant and becoming electronic-word of mouth information. Consumer review websites (CRW) are e-word of
mouth (e-WoM) information that using people information as main database for restaurant recommendation.
Zomato are one of the CRW that have around 4032 database for DKI Jakarta and that include popularity index.
Each restaurant divided by 3 classification of popularity group: high popularity, middle popularity, and low
popularity. First by using Nearest Neighbor Analysis (NNA) and second Kernel Dencity Analysis (KDA) that eachclasification have different spatial distribution and high popularity group are cluster and high dencity with 59
restaurant/km2 in Center and South Jakarta, middle popularity with cluster and mid dencity (29 restaurant/km2) inCenter, South, and North Jakarta and low popularity are cluster too but with very low dencity up to 4 restaurant/km2
in East and South Jakarta. Factor that effect for each classification popularity are shopping mall, hotel 4 & 5 star
and Central Bussines Distric (CBD) then by using proximity for each classification that high popularity restaurantgroup are close to urban functional unit and CBD. Low popularity are more likely place in outside of town andhave far distance from urban fungtional unit.
Keywords: Spatial distribution, Consumer review website, Popularity index, Zomato

be visualized based on their rating and geographic
information [6].

INTRODUCTION
Rising of social media users have a lot of impact
in surge of Electronic word of mouth or E-WoM. This
becoming valuable infromation in moderen era for
helping someone to buy from internet [1]. This
information from social media users have become EWoM that can be affect others people decition
whether or not they have to buy or use that service [1].
Consumer review website or CRW are platform for
consumers in catering and tourism industry that use
social media users as participant in giving theiropinion on service or product [2]. This platform gaveeasy access for consumers connected to each otherand give rating or review for product or service basedon their experience [3]. People in urban district using
more and more consumer review website as theirreliable information for choosing what restaurant theywant to eat because people behavior for service or
product depend on other online review [4].
Zomato is one of consumer review websites thathave restaurant database for Jakarta based on people
rating and review. Zomato also have foodie index or
popularity index for each restaurant in their database.
Rating system is process of subjectif scoring fromconsumer based on restaurant food, service, price,
location and environment [5]. This scoring become
popualrity index for each restaurant and based on thisresearch that use zomato as main database, score foreach restaurant vary from 1 to 5. Popularity index can

VARIABEL
Popularity Index
Zomato have foodie index that become popularity
index in this research. Each restaurant have their own
rating and this rating from user will be calculated
based on Zomato algorythma and become popularity
index. This popularity index then classified to 3
different group based on their rating which is highpopularity, mid popularity and low popularity
Table 1 Classification group for popularity index
Group
RatingTotal
Restaurant
Restaurant
RestaurantHigh
4.0 – 5.0
1494
Popularity
Middle3.0 – 3.9
1970
Popularity
Low
1.0 – 2.9
568
Popularity*Rating is based on zomato scoring for restaurant
Urban Functional Unit

104

SEE - Bangkok, Thailand, Nov.11-13, 2019Urban functional unit are all unit that support all
the activity in city [7] this unit typicaly consist ofgrocery store, hospital, mall, bank, office, school etc.
Restaurants that close to urban functional unit are
more likely have higher popularity and restaurantsthat far from urban functional are more likely have
low popularity [6].

METHOD
Study Area
Jakarta is the capital city of the Republic ofIndonesia that located on the northwest coast Java.
Jakarta has an area of 662 km2 and total population of
10 million people as of 2014. Jakarta also the growthcenter fo economic, cultural, and social in Indonesia.
Jakarta divided by 5 adminitration region which isWest, Center, South, East, and North. Jakarta
becoming growth center for food industry andtourism and also Zomato have the most data for
popularity index in Jakarta.

Shopping Mall
Shopping mall have impact on popularity index
based on their distance with restaurant [6]. thisresearch include 90 mall from all Jakarta.
Hotel
Beside shopping mall, hotel also one of urban
functional unit that have impact on popularity index[6]. This research include 150 hotel across all regionin Jakarta .
Mall dan Hotel
150

90
62

57
29

15

CenterFig. 1

15 16

18 13

East

West

North

Mall

Hotel

13

South

2

Total

Shopping mall and hotel in Jakarta
Fig. 2Central Bussines District (CBD)
Central bussines distric or CBD is one of the focal
point that have economic impact in city. Jakarta has 6
main roads that include in CBD: Thamrin, Rasuna
Said, Mega Kuningan, Gatot Subroto, and Satrio.

Jakarta the Capital City of the Republic ofIndonesia

Spatial Distribution
Spatial distribution for each restaurant in Jakarta
based on popularity index was analyzed using two
method: Nearest neighbor analysis (NNA) and Kernel
dencity analysis (KDA). Using NNA we can see how
distribution each restaurant in Jakarta based on its
popularity whether its cluster, random or spread in all
region across Jakarta.
Then by using KDA we can confirm NNA anlysis
and see how each class have different dencity that
affect each class spatial distributin across all region in
Jakarta. This two method will strengthen spatial
distributin analysis in each class and see what region
that have each classification restaurant based on their
popularity index. KDA and NNA in Spatial
distribution analysis using Arc-GIS software.

Accessibility
Accessibility in this research were using 2 type ofroad based on closest distace to each restaurant whichis arterial and collector
Land Use (LU)
Land use or LU were using in this research to see
every type of LU that effect index popularity in eachrestaurant. Land use that include in this research:business, settlement, religion, social-cultural, andother.
105

SEE - Bangkok, Thailand, Nov.11-13, 2019

Jakarta.
Statistical Analysis

Restaurant Distirbution In Jakarta

Before using statistical method, popularity group
was divide to 5 group this is done to see how
popularity group for high and low have significant
interval rating number:
RegionTotal

Table 2 Popularity group divided to 5 group
Popularity
Group

High
Middle
Low

North

859

East

313

South

1404

H-TestPopularity

Rating

Group

4032

Center

758

West

698

Very High

4,5 – 5,0High

4,0 – 4,4

Middle3,0 – 3,9Fig. 4Low

2,6 – 2,9Popularity Distribution

Very Low

1,0 – 2,5

Restaurant

Distribution for 4032 restaurant in Jakarta*Rating is based on zomato scoring for restaurant
Statistical analysis that this research used was
kruskall-wallis test or H-test based on each restaurant
distance to 3 urban functional unit; mall, hotel and
CBD. H-test was conduct on 3 classification group;
high, mid, and low in SPSS program [8]. Then using
distance for each restaurant to analyzed accessibility
and land use for each class by using proximity
distance in Arc-GIS.
RESULTS AND DISCUSSIONS
Restaurant Distribution

Fig. 5Popularity group of restaurant in Jakarta

4.2.1 High Popularity

Fig. 3High restaurant was located in center and south of
Jakarta as seen in fig. 5. Using NNA as seen in figure
6 NNA that classify cluster this mean that restaurantwith high popularity is cluster in Jakarta.
With KDA result as seen in fig. 7 we can see that
dencity of high popularity group were between 0 tohigh as 59 restaurant/km2. Based on this analysis mostof high popularity group were located in central andsouth with few in north and west Jakarta.

Location of 4032 restaurant in Jakarta

Distribution for 4032 restaurant in Jakarta basedon Zomato as seen in figure 3 and 4 that mostrestaurant was located in south, north, and central
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SEE - Bangkok, Thailand, Nov.11-13, 2019west with 0 to 28 restaurant/km2. North region also
have dencity around 0 to 19 restaurant/km2 and east
region have the lowest dencity with 0 to 14
restaurant/km2.

Fig. 6 NNA result for high popularity group in
Jakarta

Fig. 8 NNA result for middle popularity group in
Jakarta

Fig. 7 KDA result for high popularity group in
Jakarta
Middle Popularity
Mid popularity was located in center, south, north,west and very few in east Jakarta. Based on NNA
result in fig 8 we can see that like high popularity
group, mid popularity also had cluster classification.
This mean that mid popularity restoran was cluster inJakarta.
Based on NNA, that mid popularity group wascluster in Jakarta to see which region it was clusteredthen using KDA result in fig 9 we can see that dencity
for mid popualrity was cluster in south, center, andFig. 9 KDA result for middle popularity group in
Jakarta
Low Popularity
Low popularity restaurant was located spread
across region in Jakarta. Based on NNA result in fig
10 we can see that low popularity restaurant also
cluster in Jakarta but to analyzed this more deep by107

SEE - Bangkok, Thailand, Nov.11-13, 2019using KDA as seen in fig 11 and the result was
dencity for restaurant with low popularity group were
0 to 4 restaurant/km2. Although NNA result werecluster but with KDA results were very low dencity.
This means that low popularity group actually
spread across all region in Jakarta and NNA result
were to sensitive with how large the area.

functional unit, accessibility, and land use. Urban
functional unit include shopping mall, hotel and CBD.
Using statistical analysis, H-test or kruskall-wallis
test in table 3 using spss software we can see thatbetween 5 group popularity that distance for eachrestaurant to 3 urban functional unit was not the sameor there is connection/relations between popularity
group with their distance to urban functional unit.
Table 3 H-Test or Kruskal-Wallis test between
popularity group with urban fuctional unit

Connection between this variable were restaurantthat closer to urban functional have more highpopularity and the more far away from urban
fuctional unit is more likely to have low popularity as
seen in table 4. Interval 2 group that has been divided
show that there is significant different but only in highpopularity group.

Fig. 10 NNA result for low popularity group in
Jakarta

Table 4 Rank H-Test based on their distance (meter)

Fig. 11 KDA result for low popularity group in
JakartaPopularity Index Factor

Accessibility for each restaurant can have andimpact on how popular that restaurant. By usingarterial and collector road to see how distance

Factor that affect popularity index; urban
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SEE - Bangkok, Thailand, Nov.11-13, 2019

between 2 road with popularity for each restaurant we
can see that affect the road to restaurant popularity.

it have high chance to have high popularity andgetting further it from this factor are more likely
having low popularity restaurant.

Table 5 Accessibility for popularity group
ACKNOWLEDGEMENTS

Popularity

Arterial

High

Collector

909

585

Mean

Mean

Distance

Distancetoto

Arterial

Collector

178.82471.71

Meter

Meter
413.87

Middle982

988

505.08
Meter

Meter

Low

283

285

583.95413.67

Meter

Meter

We would like to thank to Hibah PITTA 2019
(NKB-0626/UN2.R3.1/HKP.05.00/2019)
have supported in funding of this research.
REFERENCES[1] Su Jung Kim , Ewa Maslowska & Edward C.
Malthouse. 2017. Understanding The Effects Of
Different Review Features On Purchase
Probability. International Journal of Advertising.
Vol. 37, Issue 1, 29-53.
[2] Liu, C., Su, C., Gan, B., & Chou, S. 2014.
Effective Restaurant Rating Scale Development
And A Mystery Shopper Evaluation Approach.
International Journal of Hospitality Management.
43[3] Laurell, C., & Sandström, C. 2013. Value
Creation And Appropriation In Social Media The Case Of Fashion Bloggers In Sweden. In Int.
J. of Technology Management (Vol. 61)[4] Chevalier, J. A., & Mayzlin, D. 2006. The Effectof Word of Mouth on Sales: Online Book Reviews.
Journal of Marketing Research, 43(3), 345–354[5] Zhang, Z., Zhang, Z., & Law, R. (2014). Positive
And Negative Word Of Mouth About
Restaurants: Exploring The Asymmetric Impact
Of The Performance Of Attributes. Asia Pacific
Journal of Tourism Research, 19, 162-180[6] Zhai, Shixioa. Xu, Xiaolin. Yang, Lanrong. Zhou,
Min. Zhang, Lu. 2015. Mapping The Popularity
of Urban Restaurants Using Social Media Data.
Applied geography, 63, 113-120[7] Myint, S. W. 2008. An Exploration of Spatial
Dispersion, Pattern, And Association of Socio
Economic Functional Units In An Urban System.
Applied Geography, 28, 168-188[8] Silverman, B. W. 1998. Density Estimation For
Statistics and Data Analysis (p. 48). London:
Chapman & Hall/CRC

Based on table 5 that high popularity are mostly
close to arterial and low popularity closer to collcetorroad. The last factor that affect popularity index wasland use.
Table 6 Land use for popularity group
SocialPopularity

Business

Setlement

Religion

High

1237

209

5

21

22

Mid

1456

349

5

41

51

Low

394

140

2

11

21

Cultural

Other

Based on table 6 that 75% restaurant regarding
their popularity were in bussines, and few were insettlement.
CONCLUSIONS
Spatial distribution for popularity index restaurant
in Jakarta for high popularity were cluster in centeradn south with high dencity up to 59 restaurant/km2
and 28 restaurant/km2 for mid in center, south andwest. Low popularity restoran were spread across all
region in Jakarta with low dencity up to 4
restaurant/km2. Factor that affect popularity index areurban functional unit, accessbility and land use forbussines. The closer restaurant to this factor making

109

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF ELECTROLYZED REDUCING WATER ON
CARBENDAZIM SOLUTION AND RESIDUES DEGRADATION OF
CHERRY TOMATO (Solanum lycopersicum L. var. cerasiforme)
Wanwarang Pattanapo1,2 Kanda Whangchai1,2,3 Jamnong Uthaibutra1,2,3 Tanachai Pankasemsuk 1,2,4,5
and Usawdee Chanasut 1,2,3
1
Postharvest Technology Research Center, Faculty of Agriculture, Chiang Mai University,
Chiang Mai 50200, Thailand
2
Postharvest Technology Innovation Center, Office of the Higher Education Commission,
Bangkok 10400, Thailand
3
Department of Biology, Faculty of Science, Chiang Mai University,
Chiang Mai 50200, Thailand
4
Department of Plant and Soil Sciences, Faculty of Agriculture, Chiang Mai University,
Chiang Mai 50200, Thailand;
5International College of Digital Innovation, Faculty of Agriculture, Chiang Mai University,
Chiang Mai 50200, Thailand

ABSTRACTThe effect of electrolyzed reducing water (ER) on a degradation of carbendazim residues degradation of cherry
tomato (Solanum lycopersicum L. var. cerasiforme) was investigated. Electrolyzed water was generated byelectrolysis from 5% NaCl solution. The cherry tomato samples were washed in ER water at different
concentrations (100, 250, 500 and 1000 mg/L) and in distilled water (control). The standard carbendazim solution(5 mg/L) was treated with the previous concentrations of ER. Reduction of residual carbendazim was determinedby high performance liquid chromatography (HPLC) while liquid chromatography-quadrupole-time-of-flight mass
spectrometer (Agilent, LC-6545 Q-TOF/MS) was used to determine the concentration of anions as majordegradation products. It was found that all concentration of ER water significantly reduced carbendazim solution,compared to control. The ER water at 250 mg/L could effectively remove carbendazim residues from cherry
tomato, most of the degradation occurred within 30 min. Residue of carbendazim on cherry tomato were reduced
by 60.36%, 80.49%, 67.32%, and 64.68% after 30 min washing in ER 100 mg/L, 250 mg/L, 500 mg/L, and1000
mg/L, respectively.
Keywords: Electrolyzed reducing water, Carbendazim degradation and Cherry tomato
effective, so it is used extensively in each harvestingseason to control fungal diseases. For example, it isused to prevent Sclerotinia stem rot (caused by
Sclerotinia sclerotiorum) in various fruits, vegetables,
and other plants [2]-[4]. Carbendazim is classed as apossible human carcinogen [5], [6]. It is persistentand very toxic and has been banned in Australia, USA
and most European Union countries [7,8]. The MRLs
for carbendazim in tomato is 0.5 mg/kg. The
carbendazim residues in vegetables affects on thehealth of customers and causes huge downside forThai clients and exporters. The residue problem
comes from the inefficient processes of planting andcleaning raw materials. The most common practicefor reducing contamination is using a sanitizer.
Finding the appropriate process to eliminate chemical
contaminant which has the least impact on humanhealth and environment would be an ideal
requirement. In the past, the researchers applieddifferent techniques to reduce the pesticide residues
such as washing with tap water or strong oxidizing
agent e.g. ozone and chlorine dioxide.

INTRODUCTION
Cherry tomato (Solanum lycopersicum L. var.
cerasiforme) is one of the popular tomato varieties inThailand which is locally consumed and exported. It
is a small tomato with high nutritional value and canbe consumed as fresh or processed tomato. The cherry
tomato growers usually apply fungicides andinsecticides many times until the fruit were harvested.
As a result, there are excessive amounts of various ofpesticides left on the fruits. The pesticide residue isan important problem and becomes seriously related
to human health problems and hazardous to theenvironment. One of the serious problems of
harvested tomato is pesticide residue over the
Maximum Residues Limits (MRLs). Thai Pesticide
Alert Network [1] also reported that 11.11% of
tomato samples in Bangkok, Chiang Mai and Ubon
Ratchathani province were contaminated with thepesticide residues over the MRLs. It was shown that
pesticide residue mostly found in tomato wascarbendazim. Carbendazim is a very active systemic
broad spectrum fungicide. It is very cheap and
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Nowadays, the advanced oxidation processes(AOPs) have been proposed for removing pesticide
residues from fruits and vegetables such as
electrolyzed water. Various studies on the applicationof AOPs for the pesticide residue reduction have beenreported electrolyzed water is a chlorine based
solution produced by electrolyzing a diluted salt(usually NaCl) solution in an electrolytic chamberwith anode and cathode. ER water is generated fromthe cathode side. It may also be able to reduce theresidues through alkaline hydrolysis. Moreover, it
was found that electrolyzed water is an effective
treatment to degrade the insecticide residues on
agricultural products. For example, Qi [9] suggested
that ER water was effective in degrading phosmet andthe longer treatment time resulted in the higher
reductions of diazinon, cyprodinil, and phosmet.
Jianxiong et al. [10] also found that using ER waterin fresh spinach for 30 mins reduced acephate by 86%,
omethoate by 75% and DDVP by 46%. In addition,
Tamjapo et al. [11] indicated that chlopyrifos
residues in yard long bean could be degraded using
ER water for 30 min. Furthermore, Al-taher et al. [12]reported the effect of various washing treatments witha combination of the ultrasonication on acephate,
malathion, carbaryl, bifenthrin, cypermethrin,
permethrin,
cyhalothrin,
chlorothalonil,andimidacloprid removal from tomatoes. They found thatremoving of pesticides from tomato surface depended
on the washing treatments e.g. washed with water,
sodium hypochlorite, peroxyacetic acid, or Tween 20
with and without sonication.
Therefore, this study focused on the effect of ER
water on the carbendazim fungicide removal fromcherry tomato fruit.

Fig. 1 Structure of carbendazim
Electrolyzed Water Preparation
The ER water was generated by electrolyzing 5%
NaCl solution by mixing 500 g NaCl in10 liters of
distilled water in an electrolytic chamber with anodeand catthode. The electrodes were then subjected to a
direct current of 8 A and 8 V using DC power sourcefor 1 hour. The ER water was in the cathode side. The
pH and Oxidation Reduction Potential (ORP) were
measured using pH/ion meter. The properties of ER
water were determined immediately after preparation.
The physical and chemical parameters of ER water
were pH 11.5, ORP 260 mV. The concentrations of
ER water used in this study, were 100, 250, 500 and1000 mg/L. Ten milliliters of standard carbendazim
solution (5 mg/L) was added to 20 mL of ER water at
the concentrations previously mentioned and distilledwater (control). The removal percentages of eachstandard carbendazim fungicide sample were
determinedbyhighperformanceliquidchromatography (HPLC).

Washing Treatments
One kilogram of cherry tomato was divided into 5groups of 200 g each group were spiked with 5 mg/L
carbendazim and 1% tween20 then air dried at room
temperature. After that, the fruits were left to soak indifferent concentrations of ER water (100, 250, 500
and 1000 mg/L) and distilled water (control) for 30
min (without shaking). After treatment, all samples
were air dried at room temperature for 1 hour before
fungicide extraction.

MATERIALS AND METHODS
Plant Material
Organic cherry tomato fruit at a commercial
harvesting stage was obtained from a local market,
Chiang Mai Province, Thailand and was transported
to the Postharvest Technology Research Center,
Faculty of Agriculture, Chiang Mai University. It was
carefully selected for uniformity in shape, color andsize, and insect bites, blemished or diseased fruit was
discarded.

Analytical Method
The carbendazim residue in cherry tomato was
extracted with the QuEChERS extraction kit (Agilent
Quick, USA.) and homogenized according toAnastassiades et al. [13]. Tomato sample (15 g) was
cut into small pieces and extracted with 15 mL
acetronitrile in a 50 mL Teflon centrifuge tube. The
Q-sep QuEChERS Extraction Salt was added,
immediately shaken on a vortex mixer for 2 min.
Then centrifuged at 4,000 rpm for 5 min.
Additionally, a clean-up step was conducted in the
optimization procedure. After centrifugation step, thesupernatant (about 5 ml) was transferred into a
QuEChERS Dispersive SPE 15 mL. After shaking for

Chemicals Preparation
Standard carbendazim fungicide was purchasedfrom Ehrenstorfer™ with 99.0% purity. Stocksolution (1000 mg/L) for the residue analysis was
prepared in acetone. The solution was diluted with
distilled water to appropriate working concentration(5 mg/L).

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SEE - Bangkok, Thailand, Nov.11-13, 2019

2 min and centrifugation at 8,000 rpm for 12 min, 1
mL of the supernatant was taken, filtered through a0.45 μm nylon filter and injected into the LC–MS/MS
system. The samples were analyzed with LC-6545 QTOF/MS, each analysis was done with 5 replicates.
For the LC analysis, an Agilent 1260 infinity II
with a Poroshell 120 EC-C18 analytical column of 2.1
mm x 100 mm and 2.7 μm particle size was used. The
mobile phases, A and B, were H2O + 5 mM NH4formate + 0.1% formic acid and MeOH + 5 mM NH4formate + 0.1% formic acid, respectively. The
gradient program started with 95% of A for 1.5 min,changed to 5% (10 min) then followed by a return tothe initial conditions within 5 min.
A liquid chromatography-quadrupole-time-offlight mass spectrometer (Agilent, LC-6545 QTOF/MS) was used to analyze the mass spectrometry.
The electrospray ionization (ESI) source wasoperated in positive ionization mode and its
parameters were as follows: temperature: 150ºC, gas
flow of 10 L/min, nebulizer gas: 45 psig, capillary
voltage: 3500 V. Nitrogen was served as the nebulizer
and collision gas. The multiple reaction monitoring(MRM) was used, with a delta time of 1.0 min foreach analyte.

Fig. 2 Removal percentage of standard carbendazim
solution and carbendazim in cherry tomato
after ER water treatment at different
concentrations

Table 1 Degradation
productofStandardcarbendazim after treatment of ER water
Treatments

Compound namemeasured mass
(m/z)

dibutyl succinate

253

ER100

dibutyl succinate

253

ER250

-

-

DW
(control)Statistical Analysis
The data were analyzed by SPSS 16.0, Significant
difference was considered at p<0.05.
RESULTS AND DISCUSSION
It was found that the removal percentage ofstandard carbendazim was significantly increased at
all concentration of ER applied, compared to control.
ER water at 250 mg/L was the most effective
concentration for removing carbendazim residues, theremoval was 52.80%. Washing cherry tomato with
ER water was more effective than washing with
distilled water. Residue of carbendazim on cherry
tomato were reduced by 60.36%, 80.49%, 67.32%,
and 64.68% after 30 min washing in ER 100 mg/L,
250 mg/L, 500 mg/L, and1000 mg/L, respectively(Fig. 2). Similary, Tamjapo et al. [11] reported thattreatment of yard long bean with ER water 250 mg/L
for 30 min could degrade chlopyrifos residues. It wasalso found that the ER water could be used as acleaning solution to reduce pesticide residues in fruits
and vegetables; for example, cabbage, leek [10],beans, grapes [14], and cowpea [15].

atrazineER500

desisopropyl-2-

173

OH

dibutyl succinate

253

atrazineER1000

desisopropyl-2OH

112

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SEE - Bangkok, Thailand, Nov.11-13, 2019

the ion trap MS/MS analysis of the m/z 192 resulted
in a m/z 160 ion with a loss of methanol. This loss is
consistent with the structure of carbendazim andwhich the accurate mass neutral loss from m/z 192 to160. There are carbendazim-methanol (160 m/z),
buprofezin (306 m/z), buprofezin fracgment ion(201m/z), thiophanate methyl (343 m/z), thiophanate
methyl minus methanol (311 m/z) and basic
thiophanate fragmention (151 m/z). But in this study,
there found dibutyl succinate (253 m/z), atrazinedesisopropyl-2-OH (173 m/z) and butopyronoxyl(244 m/z) were detected.

(a)

(b)
Fig.3 Structure of dibutyl succinate (a) and atrazinedesisopropyl-2-OH (b)Carbendazim
192.0773 m/z

Fig.5 Mass spectrum of dibutyl succinate after
treatment of carbendazim with distilledwater (DW)

Fig.6 Mass spectrum of dibutyl succinate after
treatment of carbendazim with ER water 100
mg/L (ER100)
Fig.4 Mass spectrum of carbendazim(a)

The degradation products that found in eachtreatment of standard carbendazim were dibutyl
succinate and atrazine-desisopropyl-2-OH (Table 1
and Fig.3). The fragment ion at m/z 192 was frommolecular ions of carbendazim (Fig.4). After
treatment with the various concentrations of ER
water, the fragment ion at m/z 192 was loss. It founddibutyl succinate after washing in distilled water, ER
100 mg/L and ER 500 mg/L, but it could not found in
ER 1000 mg/L. However, after washing in ER 1000
mg/L and ER 500 mg/L found atrazine-desisopropyl2-OH. Anywise, in ER 100 mg/L could not found thedegradation product. The fragment ion from the 2degradation product are shown in Table 1 and Figs.58. In Michale et al. [16] studied in skin of tomato thatwash with methanol for remove the white powder,found the ion trap MS/MS analysis in carbendazim
was m/z 192 as in these studied. They mentioned that(b)

Fig.7 Mass spectrum of atrazine-desisopropyl-2-OH(a) and dibutyl succinate (b) after treatment ofcarbendazim with ER water 500 mg/L (ER500)
113

SEE - Bangkok, Thailand, Nov.11-13, 2019[4] Devi, P. A., Paramasivam, M., and Prakasam, V.
Degradation pattern and risk assessment ofcarbendazim and mancozeb in mango fruits.
Environmental Monitoring and Assessment, Vol.
187, 2015, pp. 1-6.
[5] Goodson, W. H., Lowe, L., Carpenter, D. O.,
Gilbertson, M., Ali, A. M., de Cerain Salsamendi,
A. L. Assessing the carcinogenic potential of lowdose exposures to chemical mixtures in theenvironment:The
challenge
ahead.
Carcinogenesis, Vol. 36(1), 2015, pp. 254-296[6] Selmanoglu, G., Barlas, N., Songür, S., andKoçkaya,E.
A.
Carbendazim-induced
haematological,
biochemical
andhistopathological changes to the liver and kidneyof male rats. Human and Experimental
Toxicology, Vol. 20(12), 2001, pp. 625.
[7] Huan, Z., Luo, J., Xu, Z., & Xie, D. Acute toxicity
and genotoxicity of carbendazim, main impurities
and metabolite to earthworms (eisenia foetida).
Bulletin of Environmental Contamination and
Toxicology, Vol. 96(1), 2016, pp. 62-69.
[8] Zhang, X., Huang, Y., Harvey, P. R., Li, H., Ren,
Y., Li, J., Wang, J. and Hetong Y. Isolation andcharacterizationofcarbendazim-degrading
Rhodococcus erythropolis djl-11. PLoS One, Vol.
8(10), 2013, pp. e74810.
[9] Qi, H. Efficacy of electrolyzed water in degrading
and removing pesticide residues on fresh produce.
M.S. Thesis. Faculty of the University of Georgia,
Georgia, 2015, 122 pp.
[10] Jianxiong H., Wuyundalai, H. Liu, T. Chen, Y.
Zhou, Y. Su, and Lite L. reduction of pesticide
residues on fresh vegetables with electrolyzed
water treatment. Journal of Food Science Vol. 76,
Nr. 4, 2011, C520- C524.
[11] Tamjapo, A., J. Uthaibutra, and K. Whangchai.
Effect of electrolyzed oxidizing and reducing
water on the reduction of pesticide residue andmicrobial contamination in yardlong bean.
Agricultural Science Journal, Vol.47 (3) (Suppl),
2016, pp. 39-42.
[12] Al-taher, F., C. Yang, W. Philip and C. Jack.
Reduction of pesticide residues in tomatoes andother produce. Journal of Food Protection, Vol.
76(3), 2013, pp. 510-515.
[13] Anastassiades, M., S.J. Lehotay, D. Stajnbaher
and F.J Schenck. Fast and easy multiresidue
methodemployingacetonitrile
extraction/partitioning and “dispersive solidphase extraction for determination of pesticide
residue in produce. Journal of AOAC
International, Vol. 86(2), 2003, pp. 412-431.
[14] Qi, H., Q. Huang, and Hung Y.C. Effectivenessof electrolyzed oxidizing water treatment inremoving pesticide residues and its effect on
produce quality, Food Chemistry, Vol. 239, 2018,561–568.
[15] Han, Y., L. Song, Q. An, and Pan C. Removal of

Fig.8 Mass spectrum of atrazine-desisopropyl-2-OH
after treatment of carbendazim with distilledwater, ER water 100 mg/L, 250 mg/L, 500
mg/L and 1000 mg/L (ER1000)
CONCLUSIONSER water at 250 mg/L could effectively remove
carbendazim residues from cherry tomato, most of thedegradation occurred within 30 min. This study
demonstrated the ER water could be used to reduced
cabendazim residues on tomato and have a positive
impact on ensuring safety of tomatoes for
consumption. Further studies are also needed toinvestigate the degradation mechanism and possible
disinfection of by-products after ER washing.
ACKNOWLEDGMENTS
We would like to thank the Postharvest
Technology Research Center and Department ofPlant and Soil Sciences, Faculty of Agriculture,
Chaing Mai University; Department of Biology,
Faculty of Science, Chiang Mai University and The
Graduate School Chiang Mai University, Chiang
Mai, Thailand for providing research facilities;
Postharvest Technology Innovation Center, Office ofthe Higher Education Commission, Bangkok,
Thailand for a research fund.
REFERENCES[1] Thai Pesticide Alert Network. 2016. Surveillanceof pesticide residues in fruits and vegetables on
2016.
[Online].
Avaliable:
http://www.thaipan.org/sites/default/files/file/pes
ticide_doc24_press_4_5_2559.pdf (15 May
2018).
[2] Ma, H. X., Yu, C., Wang, J. X., Yu, W. Y., Tang,Z. H., Chen, C. J. Activity of carbendazim,
dimethachlon, iprodione, procymidone andboscalid against sclerotinia stem rot in jiangsu
province of China. Phytoparasitica, Vol. 37(5),2009, pp.421-429.
[3] Tortella, G. R., Mella-Herrera, R. A., Sousa, D.
Z., Rubilar, O., Briceno, G., Parra, L.
Carbendazim dissipation in the biomixture of onfarm biopurification systems and its effect on
microbial communities. Chemosphere, Vol.
93(6), 2013, pp.1084-1093
114

SEE - Bangkok, Thailand, Nov.11-13, 2019

six pesticide residues in cowpea with alkaline
electrolyzed water, Journal of the Science of Foodand Agriculture, Vol. 97, 2017, pp. 2333–2338.
[16] Michael E. T, I. Ferrer, Amadeo R. F. Matching
unknown empirical formulas to chemical

structure using LC/MS TOF axxurate mass anddatabase searching: example of unknown
pesticides on tomato skins, Journal of
Chromatography A, Vol. 1067, 2005, pp.127-134

115

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF FRUIT BAGGING ON QUALITIES OF PUMMELO CV.
KAO NAM PHEUNG AND KAO YAI
Yaowarat Wongsrisakulkaew, Chanpen Chaimongkol and Niyom Buaban
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi, Thailand
ABSTRACTThe effect of fruit bagging on qualities of pummelo cv. Kao Nam Pheung and Kao Yai. The aim of this work
was to study fresh weight, circumference of fruit, peel thickness, the color value (L*, a*, b*) of peel and internal
qualities. The experimental design was CRD (Completely Randomized Design) with 5 treatments and 4
replications include newspaper bags, commercial bags, nylon bags and plastic bags compared with non-bagging
treatment. This experiment was conducted in farmer’s orchard at Sam Phran, Nakhon Pathom province andAmphawa, Samut Songkham province, Thailand. The results showed that the bagging in both cultivar had noeffect on color value of peel at harvesting stage. The bagging in pummelo cv. Kao Nam Pheung had effect on the
total soluble solids (TSS). Also, there was not difference on fresh weight, circumference and peel thickness. The
bagging could be improved the peel quality of pummelo fruit for export.
Keywords: Pummelo, Bagging, Fruit Quality, Kao Nam Pheung, Kao Yaibagged by black paper could change the peel colorand had influence on TSS/TTA ratio [14].

INTRODUCTION
Pummelo (Citrus maxima L. Osbeck) is referred toa type of giant citrus fruit and parent of many citrus
fruits such as grapefruits and tangelos and belongs to
the family Rutaceae [1]. It is native of southern Asia
and Malaysia [2] although, [3] reported that pummelo
is a native of Asia especially in China (primary centreof origin), southern Japan, Vietnam, Malaysia,
Indonesia and Thailand (secondary centre)[3],[4].
Pummelo has been regarded as one of the ancestral
species as well as important commercial fruit tree
under the genus Citrus [5]. Pummelo is one of thefavorite fruits of the many people because of its
delicious taste and high nutritional value. The fruit isa good source of vitamins C, B1, B2 and B12 andprotein as well as an excellent source of water, fat,carbohydrates, vitamin A, and niacin [6]-[8]. It is also
excellent source of antioxidant flavonoids, potassium,
phosphorus, folic acid, citric acid, etc. [9],[10]. Manyof the outstanding cultivars from Thailand have been
introduced to other countries, commonly with theterms “Siamese” and “Bangkok” attached to theirnames. Some common cultivars are the ‘Tongdee’(brilliant gold pomelo), ‘Kao Nam Pueng’ (whitehoney pomelo) [11]. ‘Khao Paen’, ‘Khao Phuang’,‘Khao Yai’, ‘Khao Taengkwa’, and ‘Tha Khoi’ [12].
It has good market potential and of low perishability
allowing for distant transport to overseas consumers.
The problem of pummelo fruit is not only
assimilate requirement for fruit growth but also thefruit external and internal quality. The most importantof external quality improvement is fruit appearance.
One of the technique to improve the fruit appearance
is bagging. Bagging could reduced pests attack andimproved fruit quality on guava [13]. Grapefruit

OBJECTIVE
The aims of this research were to evaluate effectof fruit bagging and their relationship on quality ofpummelo fruit for export.
METHODOLOGY
The 5 years old of pummelo cv. Kao Nam Pheung
and Kao Yai tree grown at Sam Phran, Nakhon
Pathom province and Amphawa, Samut Songkham
province, Thailand was used for the experiment.
Laboratory analysis has been conducted at theDivision of Crop Production, Faculty of Agricultural
Technology, Rajamangala University of Technology
Thanyaburi.

Time of Bagging
Bagging was done during the 3rd months of fruit
pummelo.

Experimental Design
This study used a Completely Randomized
Design with 5 treatments and 4 replications include
newspaper bags, commercial bags, nylon bags andplastic bags compared with non-bagging treatment.
The experimental data were analyzed using analysis
of variance at level α = 5%, followed by Duncan
Multiple Range Test (DMRT) at level α = 5%

116

SEE - Bangkok, Thailand, Nov.11-13, 2019

monitoring was regularly done on weekly basis.
Observation on the occurrence of other insect pests
was also undertaken.

Table 2 The quality of pummelo fruit cv. Kao Nam
Pheung.
Diameter (cm)

TSS )ºBrix)

Control

14.35 b12.70

Newspaper bags

15.25 ab

12.00

Plastic bags

15.10 ab

12.80

Commercial bags

16.68 a12.63

Nylon bags

15.38 a13.40

F-test**ns

CV (%)

5.44

10.26

Treatment

Harvesting and Evaluation
Fruits were harvested at 160-170 days from fruit
set. The following were recorded and evaluated:
1) The quality of fruit: fruit weight,
circumference, diameter, peel thickness and totalsoluble solids (TSS)
2) Pigments and color of fruit peel

RESULTS AND DISCUSSION
Kao Nam Pheung Pummelo
Means followed by the same letter at the same column were not significantly
different at the 5% level by DMRT.
** = significantly different at P < 0.01
ns = not significantly

Observations on pummelo fruit in the field showedthat the bagging in pummelo cv. Kao Nam Pheung
was not difference on circumference and peel
thickness and the total soluble solids (TSS)(Table 1).
The bagging in pummelo cv. Kao Nam Pheung had
effect on diameter and fruit weight (Table 2). Fruit
peel color indicated by the lightness (L) and color
value of peel. The bagging in pummelo cv. Kao Nam
Pheung had no effect on color value of peel at
harvesting stage (Table 3). However, comparison of
the lightness among five treatments found that the
maximum average of the lightness was the bagging
commercial bags.

Table 3 The color value (L, a, b) of fruit peel
Treatment

Table 1 The quality of pummelo fruit cv. Kao Nam
Pheung.
Treatment

Fruit weight Circumference Peel thickness
(kg)
(cm)
(cm)

Control

1.32 ab

46.93

1.53

Newspaperbags

1.23 b

47.50

1.53

Plastic bags

1.30 ab

48.20

1.70

Commercial
bags

1.63 a

52.03

1.88

Nylon bags

1.30 ab

47.85

1.88

F-test**nsns

CV (%)

11.34

4.65

21.85

L

a

b

Control

54.26

-9.67

67.20

Newspaper bags

52.96

-10.12

59.90

Plastic bags

53.84

-8.95

60.59

Commercial bags

56.73

-9.33

59.08

Nylon bags

56.72

-7.02

58.37

F-testnsnsns

CV (%)

8.58

29.22

12.49

Fig. 1 The peel quality of pummelo fruit cv. Kao
Nam Pheung.
Kao Yai Pheung Pummelo

Means followed by the same letter at the same column were not significantly
different at the 5% level by DMRT.
** = significantly different at P < 0.01
ns = not significantly

Fruit quality consist of the external and internal
quality. External quality fruit include fruit weight,
circumference, peel thickness and diameter. Internal
quality include juice content and TSS.The bagging inpummelo cv. Kao Yai was not difference on fruit
117

SEE - Bangkok, Thailand, Nov.11-13, 2019weight, circumference and peel thickness (Table 4).
Sweetness of fruit indicated by TSS, it was notaffected by the bagging there was not difference on
diameter and TSS (Table 5). The results showed thatthe bagging in both cultivar had no effect on color
value of peel at harvesting stage (Table 6). The
bagging could be improved the peel quality ofpummelo fruit cv. Kao Yai (Fig 2).

Table 4 The quality of pummelo fruit cv. Kao Yai
Treatment

Fruit weight(kg)

Fig. 2 The peel quality of pummelo fruit cv. Kao Yai.

Circumference Peel thickness
(cm)
(cm)

Control

1.71

54.20

1.86

Newspaperbags
Plastic bags

1.43

48.80

1.58

1.61

50.80

1.68

Commercial
bags
Nylon bags

1.74

51.60

1.60

1.47

49.60

1.70

F-testnsnsns

CV (%)

16.82

5.97

17.25

Fruit peel color indicated by the lightness (L) andcolor value of peel. (Table 3 and 6). The color valueof peel showed the reflection color of fruit peel. The
bagging bag treatment have no significant effect on
the lightness of the peel (L) but effect on the color
value of peel. Interaction between L a and b wassignificantly affected by carotenoid content and peelcolor. Insect pests were also observed in control fruits(without bagging treatment) (Figure 1 and 2). Scale
insect infestation was observed in all bagged
treatments. Fruitfly infestation was not observed on
fruits bagged with newspaper, commercial bag andplastic bag. Mealybug infested the fruits bagged withnylon bag. Bagging could reduced pests attack andimproved fruit quality similar result was reported on
guava [13].

Table 5 The quality of pummelo fruit cv. Kao Yai
Treatment

Diameter(cm)

TSS(ºBrix)Control

16.34

12.26

Newspaper bags

15.44

11.36

Plastic bags

16.04

12.40

Commercial bags

14.46

12.24

Nylon bags

15.38

11.94

F-testnsns

CV (%)

12.96

8.90

CONCLUSIONS
Bagging could be improved the peel quality ofpummelo fruit cv. Kao Nam Pheung and Kao Yai forexport. Insect pests can be controlled by bagging at
pre-bloom stage because it is in this stage that the said
pest starts infestation. It is recommended to bag
pummelo fruits to prevent or minimize the use ofpesticides for the control of insect pests infestation
thereby enhances production of good quality andpesticide-free pummelo fruits at reduced cost.
Pesticide free fruits also can command premium
price. However, the use of bagging material is limited
to a smaller scale of pummelo plantings.

Table 6 The color value (L, a, b) of fruit peel
TreatmentLabControl

54.08-11.7759.67

Newspaper bags

55.72

-8.68

54.72

Plastic bags

55.08

-9.53

56.00

Commercial bags

55.30

-8.81

48.58

Nylon bags

51.31

-8.82

54.63

F-testnsnsns

CV (%)

6.43

18.88

14.64

ACKNOWLEDGMENTS
The author would like express thanks to RMUTT
for providing the research fund.
REFERENCES[1] Scora R.W. 1975. On the history and origin of
citrus. Bull. Torrey Bot. Club. 102: 369-375.
[2] Purseglove J.W. 1968. Tropical Crops.
Dicotyledons. 502 p.

118

SEE - Bangkok, Thailand, Nov.11-13, 2019[3] Burana-osota J., Soonthornchareonnonb N.,
Chaidedgumjorna A., Hosoyamac S., Toidac T.
2010. Determination of galacturonic acid frompomelo pectin in term of galactose by HPAEC
with fluorescence detection. Carbo. Poly. 81:
461-465.
[4] Min Y.Y. 1997. Study on the diverse centre oforigin of pummelo germplasms. China Citrus.
26(1): 3-5.
[5] Verdi A. 1988. Application of recent
taxonomical approaches and new techniques tocitrus breeding, Balaban Publishers.
[6] Rahman M.M., Rabbani M.G., Khan
A.S.M.M.R., Ara N., Rahman M.O. 2003.
Study on physio- morphological characteristics
of different local pummelo accessions. Pakistan
J. Bio. Sci. 6(16): 1430- 1434.
[7] Xu G., Liu D., Chen J., Ye X., Ma Y., Shi J.
2008. Juice components and antioxidant
capacity of citrus varieties cultivated in China.
Food Chem. 106: 545-551.
[8] Gopalan C.B., Sastri B.V.R., Balasubramanium
S.C. 2000. Nutritional value of Indian food.
National Institute of Nutrition, Indian Council ofMedical Research, Hyderabad, India.
[9] Tsai H.L., Chang S.K.C., Chang S.J. 2007.
Antioxidant content and free radical scavenging
ability of fresh red pummelo (Citrus grandis (L.)
Osbeck) juice and freeze-dried products. J. Agri.
Food Chem. 55: 2867-2872.

[10] Igual M., Martinez E.G., Camacho M.M.,
Navarrete N.M. 2010. Effect of Thermal
Treatment and Storage on the Stability ofOrganic acids and the Functional value of
Grapefruit juice. Food Chem. 118: 291-299[11] Tongdee, S.C. n.d. Impact on farming practices
of producing pummelos under the Nakornchaisri
geographical indication. Retrieved October 26,
2010 from http://www.foodquality-origin.org/
documents/ Nakhonchaisri.pdf.
[12] Chomchalow, N., Somsri, S. and P.N. Songkhla.
n.d. Market trends and export of Thai fruits.
Retrieved October 26, 2010 fromhttp://www.itfnet.org/gfruit/Slides/Session%201/Market%20Trends%20and%20Export%20of%
20Thai%20Fruits.pdf[13] Harach, S. and K. Wanichkul, 2006. Influencesof bagging methods on fruit quality of guava(Psidium guajava L.) cv. Yen Song.
Kamphaengsaen Acad. J., 4: 41-47.
[14] Hwang, A.S., K.L. Huang and S.H. Hsu, 2004.
Effect of bagging with black paper on colorationand fruit quality of Ruby grapefruit. J. Agric. Res.
China, 53: 229-238.

119

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF ELECTROLYZED OXIDIZING WATER ANDULTRASONICATION ON PATHOGENIC CONTROL OF FRESH
TUMERIC (Curcuma longa L.)
Santirote Keatsirirote1,2 Angkhana Chuajedton4 Jamnong Uthaibutra1,2,3 and Kanda Whangchai1,2,3
1
Postharvest Technology Research Center, Faculty of Agriculture,
Chiang Mai University, Chiang Mai 50200, Thailand
2
Postharvest Technology Innovation Center, Office of the Higher Education Commission,
Bangkok 10400, Thailand
3
Department of Biology, Faculty of Science, Chiang Mai University, Chiang Mai 50200, Thailand
4
Department of Biology, Faculty of Science, Lampang Rajabhat University, Lampang 52100, Thailand

ABSTRACT
Effect of electrolyzed oxidizing water (EO) and ultrasonic (US) waves on a pathogenic control of fresh
turmeric (Curcuma longa L.) were studied. Electrolyzed water was generated by electrolysis from 5% NaClsolution, which produced the EO water. The fresh turmeric samples were washed with EO solution at different
concentrations (0, 100, 200, 300 and 400 mg/L residual chlorine) and ultrasonic waves (43 and 1000 kHz.). The
percentage of redact of total bacteria, yeast and mold and Escherichia coli was counted with the determined bycompact dry plate. It was found that pathogenic control of fresh turmeric increased with EO all concentrations
and ultrasonication.
Keywords: Electrolyzed oxidizing water, Pathogenic control, Turmeric and ultrasonic wave

pathogenic bacteria [8]. Electrolyzed water ispowerful bactericidal effects and is applied in a wide
range of fields, including aquaculture, agriculture
and food industry [9,10]. Buck [11] reported thatelectrolyzed water used to treat 22 fungal species
significantly reduced growth of the thin-walled
species (e.g., Botrytis and Monilinia) within 30
seconds. Additionally, it significantly reduces
growth of the thicker- walled, pigmented
fungi,Curvularia and Helminthosporium within 2
minutes or less. In addition, Deza [12] found thattomato peel treated with electrolyzed water resulted
in a decline of bacteria such as Escherichia coli
0157:H7, Salmonella enteritidis and Listeria
monocytogenes, without any effect on theenvironment. Hung [13] reported that electrolyzed
water treatment on strawberries and broccoli
significantly reduced E. coli 0157:H7. Paola [14]found that washing lettuce with electrolyzed waterfor 5 minutes significantly inhibited the growth of L.
monocytogenes. Guentzel [15] also found thatspraying electrolyzed water at the surfaces of foodservice areas on spinach and lettuce reduced thegrowth of microbial. Whangchai [16] found thatelectrolyzed water treatment on tangerine cv. Sai
Nam Pung at a free chlorine concentration of 215
ppm for 120 and 240 seconds completely inhibitedthe growth and development of Penicillium
digitatum. In addition, Whangchai [17] found thatwashing orange with electrolyzed water andexposure to ozone gas for 2 hours per day
significantly controlled P. digitatum. Ultrasonic

INTRODUCTION
Turmeric (Curcuma longa L.) is an edible andmedicinal plant is the family Zingiberaceae, known
as Indian saffron. Turmeric rhizome when dry andground provides a yellow and flavorful powder, used
for natural coloring agent in food, cosmetic andtextile. Also flavoring compounds as insect repellent
and medicine. Recently, it has been valued
worldwide as a functional food, due to its healthpromoting properties. Turmeric has been used as
antioxidant,
digestive,
anti-microbial,
antiinflammatory and anti-carcinogen [1].
Thailand is one of the turmeric major exporter
country. [2,3]. However, the major problem of fresh
turmeric is the microbial contamination during
harvest [4]. Naruemon and Dariwan [5] reported
that the contamination of turmeric was due to mold
40.45% and Escherichia coli 62.34%. Postharvest
disease control can be done with many methods,
such as chemical disinfection, hot water treatment or
washing with clean water. Washing fresh turmericwith hot water is recommended in many countries,
such as India [6]. In Thailand, the harvested
turmeric distributed in markets are washed withclean water only. Normally, fungi and bacteriapresent in the packing-house and in the field after
harvest. Moreira [7] reported that the symptoms ofrot ginger (Zingiber officinale Roscoe) rhizomes in
Brazil was caused from Fusarium oxysporum 74% .
Recently, electrolyzed water (EO) has been reported
to have strong anti-bacterial effects on most120

SEE - Bangkok, Thailand, Nov.11-13, 2019

(US) waves have been used in postharvest treatment
to reduce decay incidence and maintain the qualityof fruits and vegetables. The high power ultrasoundwash water decontamination process in the fruits andvegetable industry is effective to decrease of
foodborne outbreaks [18].
Ultrasound treatment
has been reported to be effective in food processing
and preservation, such as cleans surfaces,
inactivation of microorganisms and enzymes,
disruption of cells [19]. Thus, the objective of thisresearch was to determine the effect of electrolyzed
oxidizing water with ultrasonication on pathogenic
control of fresh turmeric.

Preparation of ultrasonication
Ultrasonic wave (US) devices with the input
power of 3 watts and 2 frequencies of 43 and 1000
kHz, (Honda Electronics Company, Toyohashi,
Aichi, Japan) were utilized for 3 replications. A
polyethylene cylinder reactor, 10 cm in diameter,
equipped with a transducer at the lower part wasused.
Effect of electrolyzed water on microbial growth
inhibition
The fresh turmeric (50g of each replication) was
immersed into 450 ml of electrolyzed water at
different concentrations (0, 100, 200, 300 and 400
mg/L residual chlorine) for 10 minutes and then thesamples were subjected to microbiologicallyanalyzed by putting 25g fresh turmeric into 225ml
sterile 0.1% peptone and homogenizing in a
stomacher blender for 2 min and 30 second forgravitation. Serial ten-fold dilution of thehomogenate was down in 0.1% peptone. One
milliliter of each dilution was dropped onto compact
dry plate (R-Biopharm AG Company, Darmstadt,
Germany) All the plates were incubated at 37°C for
24 hr for total plate counts, and E. coli andincubated at room temperature 28±2°C for 72 hr for
yeast and mold.

MATERIALS AND METHODS
The plant materials
Fresh turmeric (Curcuma Longa L.) wascollected from a commercial turmeric farm in MaeTang, Chiang Mai Province, Thailand andtransported to the Postharvest Physiology ResearchLaboratory at Chiang Mai University within 3 hrs.
Fresh turmeric rhizomes (50 gram) were sampled foreach replicates. All experiments were designed as aCompletely Randomized Design (CRD) and eachtreatment was done in triplicate.
Preparation of electrolyzed water

Effect of electrolyzed water and ultrasonic wave
on microbial growth inhibition

Electrolyzed water (EO) generated byelectrolysis in a cell with positively and negatively
charged titanium electrodes separated by apolypropylene membrane. The electrodes were
subjected to a direct current of 8 volts. A 5% NaClsolution was added into the above system (Fig. 1).
The pH of EO water was recorded with pH/ion
meter. Free–chlorine concentration was determinedby using N,N-diethyl-P-phenylene diamine (DPD)
test and oxidation-reduction potential (ORP) was
measured by pH/ ORP meter.

The fresh turmeric (50g) was immersed into 450
ml of electrolyzed water at different concentrations(0, 100 and 200 mg/L residual chlorine) combinedwith ultrasonic wave 43 and 1000 kHz for 10
minutes the samples were microbiologicallyanalyzed fresh turmeric. 25g from each treatment
was put into 225ml sterile 0.1% peptone andhomogenized in a stomacher blender for 2 min. and
30 second for gravitation. Serial ten-fold dilution of
the homogenate was down in 0.1% peptone. One
milliliter of each dilution was dropped onto compact
dry plate (R-Biopharm AG Company, Darmstadt,
Germany) which incubated at 37°C for 24 hr for
total plate counts, and E. coli and incubated at room
temperature 28±2°C for 72 hr for yeast and mold.
Statistical analysis
All the experiments were replicated three times
and evaluated with regression procedure using SPSS
version 17. Differences among treatments were
performed using Duncan’s Multiple Range test (P >0.05).

Fig. 1 Schematics of electrolyzed water generator.
(Huang [20] )121

SEE - Bangkok, Thailand, Nov.11-13, 20191000 kHz and EO 200 +US 1000 kHz could inhibit
the growth at 0.93, 0.35 and 0.63 log CFU/g,
respectively. The combined treatment was able toinhibit the growth of E. coli. Hung [13] reported thata combination of EO water and US wave resulted ina greater reduction of the bacterial contamination ofbroccoli. For total plate count, EO 100 + US 43 kHz
gave the best result in log reduction by 2.14 log
CFU/g. For Yeast & Mold, EO 200 + US 43 kHz
obtained the best result in log reduction by 1.27 log
CFU/g. The efficiency of EO and US combined
showed a significant enhanced control of microbial
cells. US wave destroyed microorganism by thephysical forces of cavitation which is the mechanicaleffect responsible for the destruction of fungal cells[23]. In the same way, Cao [24] used ultrasoundtreatment on strawberries at 0, 25, 28, 40 or 59 kHz
at 20°C for 10 min, and then stored at 5°C for 8 days.
Hypochlorous acid damages the microbial cell byoxidizing nucleic acids and proteins, causing lethal
damage [25]. Scouten and Beuchat [26] reported
that combined treatments of chemical, heat, andultrasound were effective at killing Salmonella andE. coli O157:H7 on alfalfa seeds. The result of thisresearch also suggested that the application of EO
water combined with US wave could pathogenic
control of fresh turmeric.

RESULTS AND DISCUSSION
Effect of electrolyzed water on microbial growth
inhibition
The reduction in microbial cells is shown in Fig.
2. EO water significantly inhibited the cell growth at
100 mg/L and EO water at 300 and 400 mg/L
obtained the best result in the reduction of E. coli by
1.80 and 1.84 log CFU/g, respectively (Fig. 3). The
total plate count, also showed that EO water at 300
mg/L significantly inhibited the cell growth by 1.47
log CFU/g when compared with the control. EO
water was effective against bacteria. Tomás-Callejas[21] reported that washing fresh-cut baby mizuna
leaves with EO water showed an inhibitory effect onnatural microflora. In the another report, IssaZacharia [22] demonstrated that EO water treatment
significantly reduced the total aerobic mesophilic
bacteria from Chinese celery, lettuce and daikon
sprouts by ≥ 2.5 log CFU/g. E.coli and Salmonella
spp. were also significantly reduced by ≥ 2.7 log
CFU/g and ≥ 2.9 log CFU/g, respectively. EO water
has a strong oxidation potential and bactericidal
effect that can be used as a disinfectant. Electrolyzed
oxidizing water (pH < 2.7, ORP > 1100 mV) and thepresence of hypochlorous acid were produced at theanode side. This solution has a strong oxidation
potential in which oxidation-reduction potential(ORP) was measured for the oxidation reaction of alltreatments at EO water as represented in Table 1.
The highest value of ORP occurred in EO treatment
at 400 mg/L. The ORP showed more oxidation
efficiency which promoted the rising of oxidation
efficiency by the concentrations. Suslow [18]reported that an ORP had the activity to eliminate
the pathogens that promoted the rising of ORP. An
ORP at 650-700 mV reduced the sterilization time ofEscherichia coli, Salmonella sp. and Listeria sp.
when comparatively with the ORP lower than 485
mV.

Table 1 Effect of Electrolyzed water on pH, and
ORP (mV)
Treatments
No washed (NW)
Distilled water (DW)EO 100 mg/L
EO 200 mg/L
EO 300 mg/L
EO 400 mg/L

Parameters
pH
ORP (mV)

2.64
2.51
2.50
2.39

224
238
246
250

Effect of electrolyzed water and ultrasonic wave
on microbial growth inhibition
Combination of electrolyzed water and ultrasonicwave inhibited the bacterial growth which alltreatments were presented the value of log reduction.
The high value of log reduction occurred in EO
300+US 43 kHz, EO 300 +US 1000 kHz, EO
400+US 43 kHz and EO 400 +US 1000 kHz (datanot shown). Combination of electrolyzed water andultrasonic wave significantly inhibited bacterial
growth a Fig. 4. Treatments showed of log reductionof E. coli after treated with EO 0 +US 43 kHz, EO
100 +US 43 kHz and EO 200 +US 43 kHz by 1.19,
1.15 and 1.00 log CFU/g, respectively (Fig. 5)
meanwhile EO 200 +US 1000 kHz, EO 100 +US

Fig. 2122

Effect of electrolyzed water on microbial
growth inhibition after incubated at 37 °C
for 24 h. *Error bar represented standard
deviations. Values with the same letter on
the same color bars represented nosignificant differences (*P>0.05)

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 3

Effect of electrolyzed water (A) control (nowashed: NW) (B) distilled water: DW (C)EO 100 ppm (D) EO 200 ppm (E) EO 300
ppm (F) EO 400 ppm on growth inhibitionof E. coli after incubation at 37 °C for 24 hr.

Fig. 5

Effect of electrolyzed water and ultrasonicwave (A) control (no washed: NW) (B)distilled water: DW (C) EO 0+US 43 kHz(D) EO 0+US 1000 kHz (E) EO 100+US 43
kHz (F) EO 100+US 1000 kHz (G) EO
200+US 43 kHz (H) EO 200+US 1000 kHz
on growth inhibition of E. coli after
incubation at 37 °C for 24 hr.

CONCLUSIONS

Fig. 4

EO water significantly inhibited the cell growth
and the application of EO water combined with US
wave gave the best inhibition of microbial cells (E.
coli, total plate count and yeast and mold). Therefore,
EO water and US wave could enhance pathogenic
control of fresh turmeric.

Effect of electrolyzed water and ultrasonicwave on microbial growth inhibition after
incubation at 37 °C for 24 h. *Error bar
represented standard deviations. Values
with the same letter on the same color bars
represented no significant differences(*P>0.05)

ACKNOWLEDGMENTS
This work was supported by Postharvest
Technology Research Center, Faculty of Agriculture,
Chiang Mai University, Chiang Mai and
Postharvest
technology
Innovation
Center,Commission on Higher Education, Bangkok,
Thailand.
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1255th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EXTRACTED OF THE ANTHOCYANINS FROM Clitoria
ternatea FOR STAINED PROTOZOA AND ANTIAMOEBIC ACTIVITY
Chanyapat Sangsuwon
Department of Science and Technology, Suan Sunandha Rajabhat University, Bangkok,Thailand
ABSTRACT
Clitoria ternatea L. (CT) is family Fabaceae, commonly known as Butterfly pea and a popularly plant
consumed for blue color. A wide range of medicinal compounds are including triterpenoids, flavonol glycosides,
anthocyanins and steroids has been isolated from CT. Dried flowers were 30g extracted individually with water,water: ethanol in ratio1:1 and 1:2 gave F1, F2 and F3 respectively. The maceration gave F1(1.8g), F2(2.2g) andF3(3.5g), respectively.F1-F3 were monitoring with Thin layer chromatography (TLC) were showedanthocyanins(ATN) components. TLC showed clearly of the anthocyanins chemical constituents in F2.
Acanthamoeba keratitis (AK) is pathogens of human eyes which the causative by Acanthamoeba protozoa. It is
the free living protozoa in the environment which are opportunistic diseases. Antiamoebic therapy by chemical
drug of biguanides chlorhexidine (BCH) or polyhexamethylene biguanide (PHMB) which were not effective enough tokill Acanthamoeba cysts. CT plant has bioactivities in anti-inflammatory and analgesic properties. Which wereinteresting of studied CT for antiamoebic by anthocyanins which has vivid blue color. Extracted of F2 has
Anthocyanin which stained Acanthamoeba cysts cells and damaged morphological and changed structural of
Acanthamoeba cysts, detected by anthocyanins staining are shown under the light microscope.Anthocyanins of
F2 in concentration (250, 125, 62.5, and 31.25 µg/ml) showed dead of cysts by 50% were antiamoebic effect for
24, 48 and 72h were 140.4, 113.3 and 90µg/ml, respectively.
Keywords: Acanthamoeba, Antiamoebic, Clitoria ternatea, Extracted, Stained.

Ternatins are blue anthocyanins agylcone whichsoluble in water gave vivid blue and found in thepetals of CT [7].

INTRODUCTION
Clitoria ternatea L. (CT) (Family: Fabaceae)
commonly known as Butterfly pea, a traditional
Ayurvedic medicine, has been used for centuries as amemory enhancer, antistress, anxiolytic,antidepressant, anticonvulsant[1], root, seed and flower of CT
have long been widely used as a brain tonic and isbelieved to promote memory and intelligence[2]. CT
flowers are used for cosmetics as ATN was smear onbrows for black and shiny. The anthocya- nins is
deep violet which was the natural dye for cotton andenhanced by Ultrasonic assistance [4]. The phenolicand ATN compounds of the flowers suggest thatthey may have antioxidant activity [5].The common
ATN based on delphinidin and derivatives (Fig1)[6].

Fig. 2 Anthocyanin aglycone of (1) and theirderivatives (2-4) isolated from C. ternatea
The flowers of CT was isolated the chemical
constituents are flavonoids such as kaempferol andkaempferol
glycosides
kaempferol
3-neo
hesperidoside, kaempferol 3-rutinoside, kaempferol
3-glucoside, quercetin, quercetin glycoside. The
phenolic compounds of the flowers suggest that they
may have antioxidant activity (Fig3) [8]. ATN is thepolar components which can dissolves in the waterand deep blue color which absorbed by UV
spectrometer at 275 nm and 520 nm, respectively[9].

Fig.1 The most common ATN distributed in
the plants. Dephinidin(1), Cayanidin(2),Malvidin(3), Peonidin(4) and Pelargonidin(5).
126SEE - Bangkok, Thailand, Nov.11-13, 2019

antho cyanin by 10% H2SO4-ethanol spray reagent
and flavonoids intense fluorescence is producted in
UV365 nm by NP/PEG (NP=diphenylboryloxyethylamine, PEG: polyethylene glycol-4000), authentic
standard were anthocyanin and quercetin. Concentra
tions of anthocyanin measurement by UV spectro
meter by preparing standart curve of 1-100µg/ml ofanthocyanin at max 530 nm. F1-F3 were preparedin concentration 1mg/1 ml for measurement
quantitative of ATN.
Fig. 3 Quercetin aglycone and their derivatives
isolated from CT.

DPPH Radical Assay
Determination of antioxidant activity using 2, 2diphenyl-1picrylhydrazyl(DPPH)
radicalscavenging method by repared 0.2 mM of DPPH in
MeOH. F1 was crude extracted by ether of CT
flowers was prepared of serial concentration as 10,
20, 30, 40, 50, 100, 250, 500 and 1000 ppm.
Pipettes 1ml each of concentration of sample andadded 1ml of DPPH to each well. Mixtures werevariously shaken and left for 30 min in the dark.
Absorbance was measured at 515 nm using MeOH
as blank. Percentage of radical scavenging was
calculated using the equation: S(%) = A0-As /A0x100,
which A0 is the absorbance of the control (0.2mM of
DPPH, 2 ml), and As is the absorbance of the tested
sample. The half maximal inhibitory concentration(IC50) value represented the concentration of thesamples which have the antioxidant activity. Results
were compared with of L-ascorbic acid. The results
were expressed in percentage of inhibition as meanof three replicates. Repeated were testing with thecrudes fraction F2-F3.

Acanthamoeba spp. is protozoa and found in
virtually every environment. The life cycle wastrophozoite and cyst [10]. Trophozoites feed on
bacteria and other microorganism that retained
viable bacteria. Unfavorable conditions become cyst
form capable of surviving up to many year, isresistant to high temperature and in acid or basecondition. Acanthamoeba-resistant are known to bereservoirs of bacterial pathogens such as Ligionella
pneumophila,Mycobacterinum avium. This diseaseis known as granulatomatous amoebic encephalitis(GAE) [11]. Further, Acanthamoeba is the causative
agents of AK, a painful eye infection mainly
associated with contact lens use [12]. The chemicaldrugs for therapy of AK included biocides such as
biguanide chlohexidine and polyhexamethylene
biguanides (PHMB) were not effective enough tokill cysts [13]. Recently, the antiamoebic drug wason the way of improvement. The disinfecting solution
used included Povidone-Iodine and Virkon® which
damaged Acanthamoeba cyst [14]. The alternative useof medicinal plants is another interest as plants canhave low toxicity than chemicals. P. pellucida wasstudied the ability to kill Acanthamoeba cyst in
vitro .P. pellucida is a plant in the family ofPiperaceae [15]. Reported, CT was extracted withwater by ultrasonic and were used ultrafilter forsterilized anthocyanin for antibacterial ingredient ineye drop drug [16].

Antiamoebic Test
Acanthamoeba cysts were isolated from an
immune suppressed patient at Siriraj Hospital was
designated. Acanthamoeba were cultured in normal
saline solution seeded with E. coli heat-killed(NNA-E.coli) in 24 well plate incubated at 37C for
7 days. The cysts were harvested, washed withnormal saline solution, and adjusted to a final
concentration of 104 cells/ml. Pipetted 50l of
Acanthamoeba cysts (1x104 cells/ml) in each of the
1st to 4th well of 96 well plate. Dissolves
Anthocyanin of F2(5 mg) in 1 ml of Tween 20. Add
100l of F2 in the 1st well with 100l of Tween 20,
then pipette 50l from the 1st to the 2nd well withanother 100l of Tween 20, and the serial dilution
were done to the fourth well. Prepare theAcanthamoeba cysts in normal saline solution at theconcentration of 1x104 cells/ml. The Acanthamoeba
cysts solution were pipetted 50l (1x104 cells/ml)
and added into each well of 96 wells plate,incubated at 37°C for 24 h. The procedures wererepeated for 48 and 72 h.The Acanthmoeba protozoa
cysts were stained by toluidine blue were reference.
Acanthamoeba cysts and were checked by underlight microscope and the percentage of dead cysts

METHODOLOGY
Plant Material
CT flowers bought at Rajchaburi province,
Thailand in February 2018.The dried flower plant of
CT was powdered in a blender and then 30g, it
extracted individually with water(200 ml), water:
ethanol in ratio 1:1 (100:100 ) and 1:2 (70:130 ml)
gave F1, F2, and F3 respectively. The solvents were
removed by rotary evaporate at 120C.
Phytochemical screening by TLC
F1- F3 fractions are monitored the chemical
constituent by Si gel TLC Kieselgel 60F254 (Merck).
The solvent system was used n-butanol: acetic acid:
H2O (4: 2: 2), TLC screening was examined the127SEE - Bangkok, Thailand, Nov.11-13, 2019calculated by dead cysts x 100/total cysts. The 50 %inhibitory concentration values were calculated by alinear equation curve. The activities corresponding
to each fraction evaluated in the vitro assay.

TLC showed extracted of F2 was extracted ATN
components clearly and F3 have flavonoids whichhave polarity more than quercetin.
Antioxidant Activity

RESULTS AND DISCUSSION
F1 F2 and F3 were extracted with the order ofpolarity, water gave the polar compounds as
glycosides. The mixed organic reagents by ethanol
which is the polar organic reagent and could
extracted the organic compounds. Results, F2 wasextracted anthocyanin is the high yields and IC50
was the active in 13.40 (µg/ml). F1-F3. These results
are in agreement of F1-F3 were tested antioxidant
activity used DPPH reagent, and were IC50 of F1-F3
were 34.66, 13.40 and 28.77µg/ml, respectively(Table 2).

Phytochemical Scanning by TLC
The dried flower of CT were extracted water (200ml), water: ethanol in ratio 1:1 (100:100 ml) and 1:2(70:130 ml) gave F1, F2, and F3 respectively. TLC
showed the phytochemical components of
Anthocyanin by 10% H2SO4 in ethanol using sprayreagent and heat at 110C were red. In planar
chromatography in particular, the retardation
factor Rf is defined, retardation value calculated byformula:𝐦𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐝𝐢𝐬𝐭𝐚𝐧𝐜𝐞 𝐨𝐟 𝐬𝐮𝐛𝐬𝐭𝐚𝐧𝐜𝐞(𝐜𝐦)Rf = 𝒎𝒊𝒈𝒓𝒂𝒕𝒊𝒐𝒏 𝒐𝒇 𝒅𝒊𝒔𝒕𝒂𝒏𝒄𝒆 𝒐𝒇 𝒔𝒐𝒍𝒗𝒆𝒏𝒕 𝒇𝒓𝒐𝒏𝒕

Table 2 IC50 of inhibited DPPH radical scavenging
on F1-F3 of CT flower.

NP/PEG spray reagent was activated flavonoids
under ultraviolet spectrometer at 366 nm. The
authentic standard were anthocyanin and quercetin.
TLC screening the chemical constituents of CT
flowers in F1-F3 were summarized in Table 1.

Extracted
F1 :
water
F2 :
water:ethanol
(1:1)
F3 :
water:ethanol(1:2)

Table 1 ATN of flower of CT in F1-F3 detected by
TLC screening and UV spectrometer
Extracted
fraction(200ml)F1 : water
F2:
water:ethanol
(1:1)
F3:
water:ethanol
(1:2)

Weigh
of dried
crude (g)
1.8
2.2

%
yield
18
22

Rf
of
ATN
0.67
0.67

Concentrationof ATN(mg/ml)
9
15

3.5

35

0.67

5

50% Inhibited of
DPPH radical
scavenging (µg/ml)

average

S.D.

IC50(µg/ml)

1

2

3

34

35

35

34.66

0.06

34.66
±0.06

13.2

13.6

13.4

13.4

020

13.40
±0.02

28.6

28.5

29.5

28.87

0.06

28.77
±0.06

F2 prepared in serial concentration; 1:2, 1:4, 1:8, and1:16 (250, 125, 62.5 and 31.25 µg/ml) were treated on
the Acanthamoeba cyst. Preparing Acanthamoeba cyst
in concentrated 1x104 cells/ml of normal saline solution.
Pipette 50 l of cysts solution in serial concentration of
F2, incubated at 37°C for 24 h. After that studied themorphological changed of Acanthamoeba cyst by
Anthocyanin dyne staining and counted the dead cyst
under light microscopy. The studied of Acanthamoeba
cyst were treated with F2 for 48 and 72 h. Toluidine
dyne stained living Acanthamoeba cyst for reference(Fig 5).

Fig 4 Chemical constituents of F1-F3 detected by
UV spectrometer at 256, 366 nm and reagentof NP/PEG detected flavonoids and
10% H2SO4/ethanol detected ATN.

Fig 5 Living Acanthamoeba cyst detected by
A.Toluidine dyne
B. Anthocyanins components
The morphological and structural changes of the
Acanthamoeba cysts after treated with F2 the minimum
128

SEE - Bangkok, Thailand, Nov.11-13, 2019

cysticidal concentration of 1:16 (31.25µg/ml) areinvestigated. The double cyst walls compose of thewrinkled ectocyst and damaged endocyst walls.
Most cysts showed the shrinkage of cytoplasm withthe cytoplasmic clumps, while no typical cysts arevisible. Some cysts showed the empty content within
the double-walls cyst with wrinkled ectocyst andenlarged endocyst (Fig 6).

for inflammatory and immunotherapy can killcancer. CT flowers have deep blue color of
Anthocyanins and selected for stained the cell of
Acanthamoeba cysts which have activity for
antiamobic test. The research aimed to natural color
for stained and used the Anthocyanin components
for eye drop drug for Acanthamoeba keratitis.
Repored, used ATN for ingredient in eye drop drug
for antibacterial. The study showed Anthocyanin cankill the Acanthamoeba cyst by IC50 90µg/ml in 72 h
in vitro. CT is studying in the other conditions forantiamoebic test.
ACKNOWLEDGMENTS
I am grateful for Assist.Prof. Kosol Roongruangchai
Department of Parasitology Mahidol University
Bangkok Thailand for providing the Acanthamoeba
spp. for antiamoebic test

Fig. 6 The dead Acanthamoeba cyst showedmorphological and structural changes by
the double cyst walls compose of the wrinkledectocyst and damaged endocyst walls whichstained by ATN under light microscope.

Conflicts of Interest
The authors declare that they do not haveconflict of interest

Anthocyanins extracted from F2 in concentration(250, 125, 62.5, and 31.25 µg/ml) killed the cysts
higher than 50% were antiamoebic. The experiment
treated Anthocyanins compounds and incubated for
24, 48 and 72h which were actived in 140.4, 113.3
and 90µg/ml, respectively. F2 in 72h was the active
for antiamoebic showed IC50 90.0± 0.03 % (Fig 7).

[1] Morris J. Characterization of butterfly pea(Clitoria ternatea L.) accessions formorphology phenology, reproduction andpotential nutraceutical, pharmaceutical trait
utilization. Genetic Resources and Crop
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EFFECT OF TRADITIONAL THAI MASSAGE ON MUSCLE OXYGENSATURATION IN LOW BACK PAIN PATIENTS: A PRELIMINARILY
STUDY
Ketsarakon Oatyimprai1, Wichai Eungpinichpong2, Orawan Buranruk3 and Kurusart Konharn4
Research center in Back Neck Other Joint Pain & Human Performance (BNOJPH), Thailand
2,3,4
Faculty of Associated Medical Sciences, Khon Kaen University, Thailand

1,2,3,4

ABSTRACT
Low Back Pain (LBP) is common disease found in every age that affects daily life. LBP may cause poor postureof lumbar spine, and decrease muscle performance which lead to muscle fatigue, reduce blood circulation andreduce muscle oxygen saturation. Traditional Thai Massage (TTM) has been used to treat patients with LBP forlong time with some evidence that it could increase muscle flexibility, improve blood circulation and decrease
pain. However, its effect on muscle oxygen saturation has not been explored. This study uses one group pretestposttest design to preliminary determine this effect. Twenty-three subjects (6 males and 17 females) who had nonspecific LBP participated. Each of them was measured on muscle oxygen saturation, perceived muscle fatigue,visual analog scale (VAS) and Sorensen’s test before and immediately after having a 15-minute session of TTM.
These measures were compared before and after those of 15-minute rest period. The results showed significantly
increase in muscle oxygen saturation (p < 0.01), decrease VAS (3.45±1.87) (p < 0.01) and increase endurance ofback extension (p < 0.05) in the TTM group. In conclusion, TTM could improve muscle oxygen saturation level,
decrease pain scale and increase duration of hold while performing back muscle endurance test.
Keywords: Low Back Pain (LBP), Traditional Thai Massage (TTM), muscle oxygen saturationeach working process. Oxygen is transported inhemoglobin and myoglobin. Therefore, oxygen
saturation separated two type as arterial oxygen
saturation and muscle oxygen saturation. Fromprevious study, Murthy, G. [13] reported thatimportance of muscle oxygen saturation when muscle
ischemia that affect to decrease blood volume andmuscle oxygenation, it causes of muscle fatigue. The
study of Bengtsson, A. [14] reported that “hypoxia in
combination with muscle work causes pain as well as
energy depletion” and when oxygen is raising, it candelay onset of muscle fatigue [15].
At the present, there are several studies that show
therapeutic evidence base about traditional Thai
massage, but none of the studies has provide the levelof muscle oxygen saturation of TTM on lower backmuscle. Thus, TTM still need more evidences tosupport the beneficial effects such as treatment
guidelines. Therefore, this study will preliminarily
determine effects of traditional Thai massage on levelof muscle oxygen saturation and muscle endurance oflower back muscles in low back pain patients.

INTRODUCTION
Lower back muscles are the part of body structurethat used to stabilize the body in upright position
where the main muscle that acts in this position iserector spinae (ES) muscle. ES muscle is responsible
for thoracic and lumbar flexion from the uprightposition since its acts as antagonists to the gravity [1].
Low back pain (LBP) is one common disease
resulting from disorder of lower back muscle andlumbar spine [2]. LBP has high prevalence in adult
population (70-85 %), especially rate of incidence infemales was higher than males in all age group[3][4][5].
The individual with LBP which effects on daily
life can developed chronic low back pain (CLBP) [6].
LBP could be divided into two types as specific andnon- specific base on pathology where most of thecases are non-specific LBP [7][8]. CLBP can affectpoor posture of lumbar spine, poor balance in sitting
position. Causes of LBP may induce inefficientmuscular stabilization of spine, psychological distressand prolong workload is promoting muscle fatigue,
reduce blood flow and reduce muscle oxygenation[9][10][11][12] Nowadays, many kinds of treatments
have been suggested to treat low back pain such as
massage, stretching exercise, strengthening exercise,etc., because they could improve muscle flexibility,
muscle activity, blood circulation and oxygen
saturation.
Oxygen are the most important to body work in

METHODOLOGYThis study used one group pretest-posttest design,
conducted in the department of Physical therapy,
faculty of Associated Medical Sciences, Khon Kaen
university, Khon Kaen Province, Thailand. This
study was approved by Ethics Committee of Khon
Kaen university.
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Participants
Recruited eligibility subjects

Male and female participants with LBP age
between 20 – 45 years old were recruited by usingbulletin boards and oral requests. They werescreening by researcher according to the inclusion
criteria; subacute (3 weeks to 3 months) or chronic
low back pain of non-specific low back pain (> 3months), body mass index (BMI) = 18.5-24.9 kg/m2[16], visual analog scale ≥ 3/10, good communicationand cooperation, no contraindication to either TTM,
no fracture, non-smoking [17] and adipose tissue
thickness (ATT) ≤ 6.7 mm. All participants mustrefrain from drinks containing alcohol and caffeine
before attending in 24 hours.
Twenty-three participants (26.70 ± 6.18 years ofage; height 1.63 ± 0.09 m.; weight 56.14 ± 8.99 kg.;
BMI 20.88 ± 1.71 kg/m2; ATT 4.37 ± 1.49 mm.) weresigned inform consent before joining in this study.

v

Baseline assessmentsv

Traditional Thai Massage (TTM)
15 minutes
Post-test assessmentsv

Data analysisv

Fig.1 Overview of study design

Procedure
Twenty-three participants were measured
physical examination (e.g. heart rate, blood pressure,severity of pain and level of exhausted at that time),anxiety level by STAI-Y1, Visual analog scale (VAS),
muscle oxygen saturation (SmO2) and endurance ofback extension by Sorensen’s test for baseline. Afterthat they received TTM for 15 minutes per session on
lower back muscle in prone position. The participants
rest 15 minute before receive TTM.
Massage points including 2 lines and in this study
performed along energy lines or Sen-sib which is call
“Ping-kha-la” or “Ei-tha” [18] depends on pain side.
The massage therapist was measure 2 fingers basefrom spine and pressed at T1 to S1 to apply gentle,
gradually increasing, pressure through the massage
therapists thumb or palmar. Pressure applied until theparticipants begin to feel slight uncomfortable thenhold 5-10 seconds per time. The massage therapist
applied in several times until 15 minutes [19]. The
participants can request to stop the massage therapists
or researcher at any time if they feel pain. And remeasured in same baseline after finished TTM (Fig.1).

Fig.2 The location of Moxy monitor placed on low
back muscle
Endurance of back extension using Sorensen’s test
The participants were prone by lower part of bodyon bed and anterior superior iliac spine place on edgeof bed after that the researcher strapped to the threepoint: level of greater trochanter of the femur, knee
creases and level of lateral [22]. The chair placed in
front of participant for support upper part of body andparticipant placed both hand on the chair for starting
position. Beginning the participant lift the upper partand hand from the chair and both arms crossed on thechest. The upper part of body was horizontal to thebed. They hold horizontal position until fatigue or the
body can’t lift to horizontal (Fig.3). The researcher
measured the time by stopwatch. [23] [22] [24].
Validity of Biering-Sorensen test has 0.77 [22]. This
assessment time was 5 minutes approximately.

Measurements
Muscle oxygen saturation (SmO2) using MOXY
Muscle oxygen saturation choose as a primary
outcome measure in this study and used MOXY formeasure muscle oxygen saturation. The participants
were lying in prone position; the researcher clean up
on lower back at L1 to L5. Then the researcher
palpated L3 for place MOXY monitor on the centerof erector spinae [20] (Fig.2). The data recorded inperipedal (software of MOXY) and exported in
Microsoft excel. Validity of this tool are considerablystrong (ICC; r = 0.773–0.992) [21]. The researcher
has intra-class correlation coefficient at 0.98.

Fig.3 Sorensen’s test
Pain intensity using Visual analog scale (VAS)
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Pain intensity was assessed by 10 cm. visual
analog scale. Range 0-10 which 0 is “no pain” and 10
is “most pain”. The participants were mark on thescale of pain intensity.

oxygen saturation was decreasing again andincreasing after resting 15 minutes. In the same resultof Soren1 in Soren2 but the muscle oxygen saturation
decreased lower than Soren1. The last recovery
period was increasing more than all period andsignificant increasing after received the treatment.

Anxiety level by STAI-Y1 (Thai version)
The participants requested to state trait anxiety
inventory Y1 has 20 item State anxiety items include:‘Not at all; I fell a little bit; I fell quite a lot” and I fellvery so much’. Higher scores mean greater anxiety.
Score of STAI-Y1 separate to 3 level of anxiety, there
are including; 20-39 scores: Low anxiety, 40-59
scores: Moderate anxiety and 60-80 scores: Highanxiety.
Statistical analysis
Data analysis was using by SPSS version 23 inthis study. Descriptive data of continuous data suchas age, weight, etc., are presented in terms of meanand standard deviation. The categorical data such as
gender, occupation, etc., are presented in proportionand percentages. Demographic data are presented asmean ± standard deviations (SD) and percentage.
Mean and standard deviations of the values were
calculated for each variable. This study aimed toanalyze each outcome in the period before and after
treatment, the difference times by immediate effect ofeach outcome. Paired t-test and Wilcoxon used tocompare outcome variables at baseline with outcome
variables after received treatment immediately withingroup. Friedman’s 2-way ANOVA used to compare
the change of outcome measure in difference times
within group. This study estimates the adjusted meandifference and the 95 percentages confidence interval
for each outcome measure.

Fig.4 The change of muscle oxygen saturation(SmO2) baseline until recovery.
Endurance of back extension muscle
Endurance of back extension was 0.015,
significantly improved at p value < 0.05.
Endurance of back extension muscle hassignificantly increasing after received TTM and it’s
not normal distribution because some participants had
decreasing of time when doing Sorensen test 2(Fig.5).

RESULTS
Muscle oxygen saturation
Table 1 showed that the immediately after
received TTM had significantly increasing between
Soren1-Recovery, TTM-Recovery and Base5MRecovery (p value < 0.001). In addition, there arethree pairs that have significantly different at p value< 0.05: Rest1-Recovery, Soren2-Recovery and
Rest2-Recovery.
Muscle oxygen saturation represented the data oftwenty-three participants. SmO2 showed changes ofmuscle oxygen saturation in each period with thefollow changes: In Soren1 when the participant
extend back in Sorensen’s test, the muscle oxygen
saturation was decreasing from baseline andincreasing after resting 15 minutes. Next, the massage
therapist applied massage on affected side, the muscle

Fig.5 The change after received TTM of endurance ofback extension

Pain intensity and anxiety level
Pain intensity was significantly decreased at pvalue < 0.001 and anxiety level was significantly
improving at p value < 0.001 after received TTM
from baseline.

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Table 2 Comparison outcome of pain intensity andanxiety levelcausing the blood vessels to gradually relaxed andincreased blood circulation. Then, the participants
were resting 15 minutes showed the SmO2 level was
higher than baseline, causing muscle relaxation that
improved blood circulation and improved
oxygenation. In Sorensen’s test 2 showed the SmO2
level had decreased while doing back extension but
it’s decreasing less than Sorensen’s 1.
The last recovery period showed that the SmO2
level had significantly increased with each period.
Since, there were both relaxing massage andincreasing the strength of isometric back extensionthat effect of the possible mechanism might bepromoted parasympathetic to relaxation, improvevasodilation to good blood circulation and exchanges
deoxygenation

DISCUSSIONSThis study was preliminarily determining theimmediate effects of traditional Thai massage (TTM)
on level of the muscle oxygen saturation (SmO 2),
Visual analog scale (VAS), State trait anxiety Y1(STAI-Y1) and muscle endurance of lower backmuscle in low back pain (LBP) patients. The results
showed that SmO2, muscle endurance, VAS and
STAI-Y1 had significant increasing. The result
showed the traditional Thai massage can increaselevel of the muscle oxygen saturation and muscle
endurance of lower back muscles in low back pain
patients in immediately after received treatment.
Beside pain scale and anxiety level have improve inthe same way.

Immediate effect on improving endurance of backextension
This study found that endurance of back extension
was significantly improved after received TTM
according to massage could be decreased muscle
spasm, muscle tension and improved flexibility,
causing there were improved blood flow [25] [29] andimproved oxygen saturation. In addition, Sorensen’s
test was isometric exercise of back extension, it could
be improved strengthening cause of participants
could be hold the upper body longer from baseline.

Immediate effect on increasing muscle oxygen
saturation level
Previous study [25] presented the occlusion
technique in TTM could improve blood flow and [26]
Swedish massage on calf muscle could improve tissue
blood flow. In normally contracting skeletal muscle
has increasing of blood flow and oxygen extraction,
the oxygen also binds with hemoglobin andmyoglobin in blood. It’s may cause of increasing ofmuscle oxygen saturation. [27]This study showed that changes in real time ofmuscle oxygen level in 7 periods (Base5m, Soren1,
Rest1, TTM, Rest2, Soren2 and recovery), findingthat in each period there were different changes. First
baseline measurement was measured 5 minutes andthe SmO2 level was high or low depending on themuscle tension and blood flow on lower back in each
person. According to previous study, who had
myofascial trigger point or muscle spasm often had
vasoconstriction that affect to poor blood circulation,
poor oxygenation and fatigue easily [28].
Next, Sorensen’s test 1 showed SmO2 wasdecreasing for baseline because they had muscle
contraction when performed back extension, causing
the vessels were occluded. So, the SmO2 level wasincreasing after resting 15 minutes in period 1.
Afterthought, the massage therapist applied thepressure and while doing massage had changes of
SmO2 rise and fall because when she applied thepressure, had compress to vessel in the muscle andthen the massage therapist slowly released pressure,

Immediate effect on reducing pain intensity
This study showed that the level of pain intensity
was significant decreased after the treatment.
Previous study, Study of Chatchawan [18] showedthat participants received TTM had decreased pain
intensity after treatment 3 weeks and one monthfollow up. There might be explained by gate control
theory. The touch sense could decrease pain
sensitivity by inhibition of small fiber, so that lead toblock the signal to the brain [30]. In addition, TTM
promoted vasodilation, exchanges oxygen anddecreased lactic acid cause of fatigue
Immediate effect on improving state trait anxiety Y1level
The study found that after the participantsreceived the massage, there was a better anxiety
condition before received massage. In previous study,
Buttagat, V. found that the immediately of TTM onback muscle 30 minutes could improve pain intensity
and improve level of anxiety which accordance withthis study. TTM were promote relaxation, activatedparasympathetic and decreased sympathetic.
Moreover, [31] massage whole body in pregnancy
could increase serotonin (5HIAA), increased
dopamine, decreased cortisal that might be explained
about improving of anxiety.
The researcher was followed up the participants
about pain intensity and adverse effect after received
the treatment 1 day. This study didn’t found any
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participants who had side effects from treatment.
This study has some limitations. First, this study
has small sample size because there usedpreliminarily study and non-control group forcompare with treatment. Second limitation was noblind for the assessor and patients. Third limitationfrom muscle oxygen monitor was when doing
activities that were moving or sweating. Sometimes
the device can’t read oxygen saturation in muscle. In
some participants who sweat easily, there is aproblem while doing Sorensen’s test, causing theinformation to be lost and can’t be analyzed. The last
limitation was duration of treatment because thisstudy was measuring immediate effect. Although, thisstudy measures immediate effect and in the future
study may use randomize control trial (RCT) or
crossover design for long term effect of TTM on pain
scale and anxiety except for SmO2 and muscle
endurance.

Table1 Participants outcome of Muscle oxygen
saturation (SmO2)

CONCLUSIONS
TTM on lower back muscle in LBP patients for 15
minutes could improve level of SmO2, decrease pain
scale, decrease anxiety and increase duration of holdwhile performing back muscle endurance test.
Treatment technique in this study has no side effectand provide relaxation of anxiety. Consequently, thisTTM for 15 minutes on pain area can serve as analternative treatment of LBP patients.

ACKNOWLEDGMENTS
Financial support in this research were authorized
by the Research and Training Center for Enhancing
Quality of life of working Age People and the
Research Center in Back Neck Other Joint Pain and
Human Performance (BNOJPH). Location support inthis research has been approved by the ResearchCenter in Back Neck Other Joint Pain and Human
Performance (BNOJPH) at the research room 5th floor,
Faculty of Associated Medical Sciences, Khon Kaen
University, Thailand.

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PROBIOTICS ENCAPSULATED FRUIT JUICE PEARLS AS
FUNCTIONAL FOOD PRODUCT
1Palida Tanganurat 1, Intira Lichanporn1,Nunchanok Nanthachai1 and Charoen Charoenchai
Department of Food Science and Technology, Faculty of Agricultural Technology, Rajamangala University ofTechnology Thanyaburi, Pathum Thani, 12130, Thailand
ABSTRACTThis experimental research investigates encapsulation of Pediococcus pentosaceus ARG-MG12 in pure orange
juice pearls. In the study, four tropical fruit juices: guava, watermelon, pineapple, and orange, were first evaluatedin terms of sensory characteristics: color, odor, flavor, texture, overall acceptance, using a 9-point hedonic scale;and orange juice whose sensory scores were statistically highest was selected for further development into
probiotic fruit pearls. The physicochemical properties of probiotic orange pearls were examined and the sensory
evaluation undertaken. Furthermore, the probiotic pearls were subjected to gastric juice (pH 2.0) and bile salt
(0.6% w/v) environment for 3 h to simulate human gastrointestinal tract and to variable storage durations (0, 3, 5,
7, 14 days) at 6 oC to assess cell viability. The findings showed that the probiotic orange pearls had 390.71 g/secof stiffness, DPPH radical-scavenging activity of 294 g ascorbic acid eq./ml, and L-ascorbic acid content of 0.095
mg/ml. Meanwhile, the survival rates of bacterial cells in low pH environment and bile salt were 83.27% and94.24%, respectively. At day 14, the remaining bacteria were above 8 log CFU/g, given that the minimum
concentrations of probiotics are 106–107 CFU/ml at the end of product’s shelf life. Moreover, sensory testing
panelists were unable to differentiate between non-probiotic and probiotic orange pearls.
Keywords: Probiotic, Encapsulation, Fruit pearl
compounds [7],[8].
Despite widespread encapsulation of probiotics ina variety of food products, research on probiotics
encapsulation for fruit juice pearls is limited and rare.
Thus, this research aims to develop fruit pearls
containing probiotics encapsulated with sodium
alginate as functional food product. In the study, four
tropical fruit juices: guava, watermelon, pineapple,
and orange, were first evaluated in terms of sensory
features (i.e., color, odor, flavor, texture, overall
acceptance) using a 9-point hedonic scale and thefruit juice with statistically highest scores selected forfurther development into probiotic fruit pearls. The
physicochemical properties of the probiotic fruit
pearls were then characterized in terms of size,
texture, antioxidant activity, and L-ascorbic acidcontent; and the sensory evaluation undertaken incomparison with commercially non-probiotic fruit
pearls. In addition, the probiotic fruit pearls were
subjected to simulated human gastrointestinal tract
and variable storage durations at 6 oC to determine thecell viability.

INTRODUCTIONFirst invented in Taiwan in the 1980s [1], bubble
tea is a trendy drink popular among teenagers. The
colorful beverage is concocted from green or black
tea mixed with milk and fruit syrup. As a marketing
gimmick, the drink contains small spherical tapioca
starch balls of 10 -15 mm in diameter (also known asbubbles, pearls, or boba), and is served with a wide
colorful straw through which the bubbles are suckedup [2].
Encapsulation involves the entrapment of active
substance within another substance acting as coating
material. The encapsulation technology is commonlyused by the food industry for preservation anddelivery of flavors, dyes, stabilizers, antioxidants,
enzymes, probiotics, lipids, mineral salts, andvitamins [3]. For probiotics, encapsulation protects
microorganisms against environmental stresses.
Specifically, microcapsules creates an anaerobic
environment conducive to probiotics growth andprovide protection against harsh environment,
including acidic fruit juice, freezing, and gastricconditions, thereby mitigating cell injury [4,5].
Of particular interest is the survival of probiotics
in food products given that significant proportions ofcells deteriorate during processing and storage.
According to the International Dairy Federation, theminimum concentrations of probiotics should be 10 6–
107 CFU/ml at the end of product’s shelf life [6]. The
health benefits of probiotics include, for example,
bio-availability of macro- and micro-nutrients,
antioxidant activity, and production of anti-microbial

MATERIALS AND METHODS
Preparation of Fruit Pearls
Fresh tropical fruits were acquired from a local
fresh market in Thailand’s Pathum Thani province,
consisting of 10 kg each of guava, watermelon,pineapple, and orange. The fruits were washed,peeled, and ground by a blender for 5 min at
maximum speed (Philips, HR-2118). The slurry was138

SEE - Bangkok, Thailand, Nov.11-13, 2019

manually squeezed through a muslin cloth for juice,and pH values were measured by pH meter (Sartorius
PB-20, Germany) and titratable acidity determined[9].
In this research, the encapsulation followed
Krasaekoopt and Kitsawad [11] whereby 1% sodium
alginate (w/w) was mixed with 1000 ml fruit juice andheated at 70 °C for 10 min. The mixture was extruded
dropwise through 8-mm needle into sterile 0.1 M
CaCl2 as hardening solution and left for 10 min. The
fruit juice pearls were cleaned by potable water andparticle sizes measured using Vernier caliper.
The sensory attributes (color, odor, flavor, texture,overall acceptance) of pearls of four fruit juices:guava, watermelon, pineapple, and orange, were
evaluated by a team of 30 untrained panelists using a
9-point hedonic scale, where 1 denotes extremely
dislike and 9 extremely like. Randomized complete
block design was utilized to select the fruit juice withstatistically highest sensory scores (p≤0.05) for
subsequent experiment [10].

fruit juice, and bacterial culture (log CFU/ml).
Texture Profile Analysis
Texture profile analysis of fruit pearls was carriedout using Texture Analyser (Model TA. XT. Plus,
Make: Stable Micro Systems, UK) equipped with 10
kg load cell. The data from the texture profile (forcetime) curve was used to determine chewiness (g),energy to chew (g.%), and stiffness (g/sec) [12].
Antioxidant Activity and L-Ascorbic Acid
The antioxidant activity of probiotic fruit pearls
was determined according to [13] using free radical
2,2-diphenyl-1-picrylhydrazil (DPPH), whereby 0.2
ml of the suspension (containing sodium alginate,
fruit juice, and bacterial culture) and 3.8 ml of 0.1
mM DPPH in ethanol were briefly mixed in test tube,
and retained in darkness for 30 min. The absorbancewas measured at 517 nm by visible light
spectrophotometer (772s, Precision and Scientific
Instrument Co., Shanghai, China). L-ascorbic acidwas used as standard and ethanol as blank. The
antioxidant activity was expressed in μg of ascorbic
acid eq./ml. Meanwhile, the Association of Official
Agricultural Chemists (AOAC)’s titrimetric method
was used to determine L-ascorbic acid content [9].

Preparation of Inoculum
Pediococcus pentosaceus ARG-MG12 wascultured in 10 ml de Man, Rogosa and Sharpe (MRS)
broth (Merck, Darmstadt, Germany), followed byovernight incubation at 37 °C. The culture wastransferred to 100 mL MRS broth and incubatedovernight at 37 °C. Cultures were harvested bycentrifugation at 3000 g at 25 °C for 10 min andwashed with sterile saline, and the procedure wasrepeated prior to the collection of cultures.

Tolerance of Probiotic Fruit Pearls to Simulated
Human Gastrointestinal Tract
In this research, the tolerance of probiotic fruit
pearls was characterized under simulated gastric juice(pH 2.0) and bile salt (0.6% w/v) conditions. The
simulated gastric and intestinal juices were to mimic
human gastrointestinal (GI) tract [14]. In theexperiment, fruit pearls were introduced into thesimulated gastric juice and incubated at 37 °C for 3 h.
Afterward, 10 g of fruit pearls was mixed with 90 mlof sterile phosphate buffer and broken up by thestomacher for 1 min at room temperature. The
mixture was diluted and the number of viable cells
determined by pour plate count (log CFU/ml) in MRS
agar after incubation at 37 °C for 48 h [15]. The
survival rate (%) was then determined.
For bile salt tolerance, the probiotic pearls were
submerged in the bile salt (Sigma, USA) andincubated at 37 °C for 3 h. Afterward, 10 g of thesample was mixed with 90 ml of sterile phosphatebuffer and disintegrated for 1 min at room
temperature using the stomacher. The mixture wasdiluted and the number of viable cells determined bypour plate count (log CFU/ml) in MRS agar after
incubation at 37 °C for 48 h [15]. The survival rate(%) was then determined.

Encapsulation of Ped. pentosaceus
In encapsulation, Ped. pentosaceus ARG-MG12
bacterial cultures (1011 CFU/ml) were asepticallysuspended in the selected sodium alginate-mixed fruit
juice (i.e., the fruit juice with statistically highest
sensory scores). The suspensions were extruded
dropwise through 8 mm needle into sterile 0.1 M
CaCl2 as hardening solution and left for 10 min. The
probiotic fruit pearls were then washed by potablewater.
To determine the bacterial survival, 10 g of the
probiotic fruit pearls was mixed with 90 ml of sterile
phosphate buffer in mixer bag and broken up bystomacher (Seward, UK) at room temperature for 1
min. The mixture was diluted and the number of
viable cells determined by pour plate count (log
CFU/ml) in MRS agar after incubation at 37 °C for
48 h. The survival rate (%) was then calculated using
Eq. (1):
Survival rate (%) = (N/N0) x 100(1)
where N is the number of viable cells in the fruit
pearl (log CFU/ml) and N0 is the number of freeviable cells in suspension containing sodium alginate,

Sensory Evaluation
Color, odor, flavor,
139

texture,andoverallSEE - Bangkok, Thailand, Nov.11-13, 2019

acceptance of probiotic fruit pearls were evaluated bya team of 30 untrained panelists. Two sets of fruit
pearls, i.e. commercially non-probiotic (Ding Fong
Foods, Thailand) and probiotic fruit pearls, wereserved to the panelists who subsequently scored on
the sensory features (color, odor, flavor, texture, andoverall acceptance) using a 9-point hedonic scale,where 1 denotes extremely dislike and 9 extremely
like. Randomized complete block design was used toassess the statistical difference between the nonprobiotic and probiotic fruit pearls (p≤0.05) [10].

RESULTS AND DISCUSSION
Comparison of Fruit Pearls
Table 1 tabulates the pH and total acidity of four
fruit juices (guava, watermelon, pineapple, andorange) mixed with sodium alginate.
Table 1 pH and total acidity of fruit juices
Fruit pearls

Titratable
acidity (%)
Guava
4.31±0.02b
0.70±0.07caWatermelon
5.73±0.04
0.62±0.15cdPineapple
4.12±0.02
1.65±0.80a
Orange4.23±0.03c
1.23±0.10b
The experiments were carried out in triplicate, and theresults are expressed as mean ± standard deviation.
Different superscripts in the same column indicate
significant difference (p≤0.05).

Statistical Analysis

pH

All the experiments were carried out in triplicate
and the results expressed as mean ± standard
deviation and average percentage for the survival rate.
Analysis of variance (ANOVA) was used to analyze
the data and Duncan’s multiple-range test to comparemeans. Statistical significance was based on the 5%
significance level (p≤0.05).
Use at most three levels of headings that
correspond to chapters, sections and subsections. The
According to Gandomi, Abbaszadeh, Misaghi,
first level headings for chapter titles should be in 10pt,
Bokaieand Noori [16], formulating probiotic fruit
bold, justified, and upper case font. Leave one blankjuicespresents
greater challenges than dairy productsline before and after the first level headings,
respectively.
Table 2 Sensory evaluation of four experimental fruit pearls
Fruit pearls

Sensory evaluation
Color
Odor
FlavorTexturens
Overall acceptance
c
c
c
Guava
5.56±1.38
4.43±1.71
4.63±1.62
5.76±1.13
5.33±1.53bbcbb
Watermelon
6.86±1.47
5.23±1.52
5.36±1.40
5.93±1.17
5.80±1.32bbaa
Pineapple
6.40±1.49
6.46±1.65
6.13±1.54
6.03±1.62
6.46±1.61aaaaOrange7.40±1.42
7.13±1.45
6.46±1.35
5.93±1.38
6.90±1.44a
The experiments were carried out in triplicate, and the results are expressed as mean ± standard deviation. Different
superscripts in the same column indicate significant difference (p≤0.05). ns denotes not significant (p>0.05).
because fruit juices normally have low pH (3.0-4.5),
which affects the stability of probiotics. In Table 1,
pH of fruit juices, except watermelon, were below 4.5,
which is unconducive to bacterial viability.
Sensory features of fruit pearls are also importantin formulating probiotic food products. Table 2
presents the sensory evaluation of the four fruit pearlson color, odor, flavor, texture, and overall acceptance.
The results indicated that the evaluation scores oforange pearls were statistically highest in nearly all
sensory characteristics (p≤0.05). Orange fruit juice(i.e., 100% genuine orange juice) was thus selected
for subsequent development into probiotic fruit pearls.

extrusion method [18]. In addition, the beads were
spherical in shape given that sphericity plays a crucialrole in preventing cell overgrowth in encapsulated
beads [18].
Table 3 Characteristics of probiotic orange pearls
Characteristics
Size (mm)TextureChewiness (g)Energy to chew (g.%)
Stiffness (g/sec)
L-ascorbic acid (mg/ml)
DPPH radical-scavenging
activity (g ascorbic acideq./ml)Characteristics of Probiotic Orange Pearls
Table 3 tabulates the average size, texture profile,L-ascorbic acid, and antioxidant activity of probiotic
orange pearls. The average size of probiotic pearls
was 11.4±0.05 mm, as opposed to 0.5-3 mm forconventionally probiotics-encapsulated beads using
140

Value
11.4±0.05
220.03±26.02
3,400.57±421.92
390.71±25.66
0.095±0.01
294±22.13

SEE - Bangkok, Thailand, Nov.11-13, 2019

The experiments were carried out in triplicate, andthe results are expressed as mean ± standard
deviation.

Encapsulation of probiotics in hydrocolloid beads
protects the bacterial cells against damage caused byexternal environment and during gastrointestinal
transition [18]. In Table 4, the bacterial stability
decreased in both stimulated gastric juice (8.96±0.06
log CFU/g) and bile salt (10.14±0.04 log CFU/g), visà-vis the control (10.76±0.12 log CFU/g), with thecorresponding survival rates of 83.27% and 94.24%.
In comparison, unencapsulated Ped. pentosaceus
strains in the simulated gastric juice suffered a
reduction in the bacterial stability by two logarithmic
cycles after 1h incubation [21].

Based on the bead/pearl size, encapsulation isclassified into two categories: macroencapsulation(mm to cm) and microencapsulation (1-1000 µm)[8],[17]. The probiotic fruit pearls of thisexperimental research belong to the macroencapsulation group. Figure 1 illustrates theexperimental probiotic orange fruit pearls.

Table 4 Viability and survival rate of probiotics
under simulated gastrointestinal conditions
Conditions

Viability(logCFU/g)
10.76±0.12a
8.96±0.06c

Survival
rate (%)
100.00a83.27cControlStimulated gastricjuice (pH 2.0)
Bile salt (0.6%)
10.14±0.04b
94.24bThe experiments were carried out in triplicate, and theresults are expressed as mean ± standard deviation.
Different superscripts in the same column indicate
significant difference (p≤0.05).

1 cm

Figure 1 The experimental probiotic orange pearls
Table 3 also presents the texture of probiotic
orange pearls, including chewiness, energy to chew,
and stiffness. The texture of fruit pearls was
positively correlated with sodium alginate
concentrations.
Elevated
sodiumalginate
concentrations induced a higher degree of crosslinkage between gel networks, resulting in denser andmore rigid gel structure. Specifically, sodium alginate
gelation developed as Ca2+ gelling ions crosslinked
with sodium alginate whose optimal concentrations
for probiotics encapsulation were 0.5 - 4% (w/v).
Sodium alginate is preferable for probiotics
encapsulation due to ease of use, biocompatibility,
economy, non-toxicity, rapid gel matrix formation
around bacterial cells, and mild processing [18]. In
Table 3, the DPPH antioxidant activity and Lascorbic acid content indicated adequate antioxidant
capacity of the probiotic orange pearls.

In this research, 83.27% of Ped. pentosaceus
ARG-MG12 survived after 3 h in low pH
environment, a time period sufficient for the
probiotics to reach their action site in the intestine[20]. In addition, 94.24% of the bacteria were capableof surviving high bile salt concentration (0.6% w/v).
In [21], unencapsulated Ped. pentosaceus strains
exhibited abundant growth at 0.5% concentration ofbile salt but poor growth rates at 1-2% concentrations,suggesting that encapsulation contributes to theenhanced viability of probiotics in gastrointestinal
tract.
In Storage Cell Survival and Sensory Evaluation
Table 5 tabulates the viability and survival rates
of Ped. pentosaceus stored at 6 °C for 0, 3, 5, 7, and14 days. The cell viability decreased with extended
storage time (p≤0.05). According to Ding and Shah[22], encapsulated Ped. pentosaceus could survive inorange and apple juices for six weeks in refrigerated
storage (4 °C), whereas free cells (unencapsulated)
lost their viability within five weeks.

Viability of Probiotics in Fruit Pearls under
Simulated Gastrointestinal Condition
For health benefits, probiotics must be able tosurvive during gastrointestinal transition and exist inhigh proportions in the intestines (106 - 108 CFU/g ofintestinal content) [19]. In this research, the viabilityof Ped. pentosaceus ARG-MG12 encapsulated inorange pearls was investigated in the simulated
gastric juice (pH 2.0) and bile salt (0.6% w/v)
environments for 3 h each. Table 4 tabulates the assay
results, where control denotes the initial condition at
0 h.

Table 5 Viability and survival rate of probiotics
during storage at 6 °C
Storage(days)
03
141

Viability(logCFU/g)
11.38±0.05a
9.02±0.04b

Survival rate(%)
100.00a79.26b

SEE - Bangkok, Thailand, Nov.11-13, 20195714

9.12±0.02b
9.11±0.02b
8.58±0.20c

The experiments were carried out in triplicate, and theresults are expressed as mean ± standard deviation.
Different superscripts in the same column indicate
significant difference (p≤0.05).

80.14b80.05b75.40cTable 6 Sensory evaluation of commercial (non-probiotic) and probiotic orange pearls
Fruit pearls
Colorns

Odor

Sensory evaluation
Flavorns
Texturens

Overall
acceptancens
Commercial orange pearls
7.77±1.13
6.53±1.87b
7.23±1.59
7.60±1.35
7.40±1.27
Probiotic orange pearls
7.57±1.04
7.67±1.26a
7.20±1.62
7.13±1.47
7.50±1.13
The experiments were carried out in triplicate, and the results are expressed as mean ± standard deviation. Different
superscripts in the same column indicate significant difference (p≤0.05). ns denotes not significant (p>0.05).
The authors would like to extend deep gratitude to
In Table 5, the viability of probiotics in the orange
the Faculty of Agricultural Technology, Rajamangala
pearls steadily declined from day 0 through toUniversity of Technology Thanyaburi, for thetermination (day 14). At termination, the remaining
research grant.
bacteria in the probiotic orange pearls were still above
8 log CFU/g, given that the minimum concentrations
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143

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF ENVIRONMENTAL FLUCTUATIONS ON
INCIDENCE OF MYCOFLORA
H.N.P. Singh, Sunita Kumari and M.M. Prasad
Post Graduate Department of Biotechnology
T.M.Bhagalpur Universit y, Bhagalpur-812007, Bihar, (India)

ABSTRACTThe value of medicinal plants on great extent depends on their potential ability to cure diseases. Usuallythese are collected from the forest or from the natural habitats by the local people of that area and are storedin gunny bags or dumped on the floor of kaccha store house. The faulty storage techniques makes the plants
or plant parts victim of several micro-organisms which in turn results in the deterioration of’ their
therapeutic value. Keeping this in view four drug plants viz. Ricinus communis (Andi), Carthamus
tinctorius (Kusum), Datura alba (Safed datura) and Solanum xanthocarpum (Kateli) was undertaken fromfield, storage centres and markets of Bhagalpur (Bihar) and its suburbs to record their fungal flora. The
results revealed that composition of storage fungi fluctuated on account of the change in the atmosphericcondition and the hosts. The fungi was maximum during rainy season due to high humidity, suitabletemperature and heavy rainfall. However less incidence of fungi was recorded during winter season when
the temperature, R.H. and rainfall was minimum. A large number of fungi was also observed in summer.
But in winter; fungal incidence was noted minimum as compared to summer season.
Keywords: Effect, Environment, Incidence, of, Mycoflora.
INTRODUCTION
Rheumatism is a serious problem of Indianmass. Early literature reveals that a large numberof plants and plant parts, like seed, leaf and roots
are used for the treatment of this disease. Someof the most important ones are Ricinus
communis, Carthamus tinctorius, Solanum
xanthocarpum and Datura alba. The traditional
method of using these plants, plant parts, seeds
as well as fruits as antirheumatic diseases has
been practiced since long in the tribal areas. The
unscientific collection, storage, handling andmarketing of these drug plants by the unskilled
people could not establish their efficacy against
diseases. So, that present investigation deals withthe effect of Environmental Fluctuations on
Incidence of Mycoflora associated with various
medicinal plants.

rheumatism by the local practiceners andHakims. Those are colleted from natural habitats
markets and store houses of Bhagalpur and its
adjoing area. The samples were brought to thelaboratory in separate polyethylene bags fordetailed study.
Mycoflora associated with the collected
samples were isolated following the standard
technique recommended by International Seed.
Testing Association (1966) after sterilizing thesamples by 2% sodium hypochloride (NaOCl)solution.
Blotter Test
Sterilized seeds/leaves of approrimately equal
size were placed aseptically on moistened
blotters by the sterilized distilled water in petri
plates .The plates were incubated for 7days atroom temperature (25  20C). The moisture levelof the blotters was maintained by addingsterilized distilled water. Samples were
examined regularly from 4th days onward under
microscope .The fungi appeared on the samples

MATERIALS & METHODS
Different parts of four medicinal plants i.e.
Ricinus communis (seed), Carthamus tinctorius(seed), Solanum xanthocarpum (leaf) and Daturaalba (leaf) which are commonly used against
144

SEE - Bangkok, Thailand, Nov.11-13, 2019were isolated and purified and maintained on
Potato Dextrose Agar (PDA) as well as Asthanaand Hawker agar solid slants. The identificationof fungi were also done regularly.

DISCUSSION
The above findings reveal that the medicinal
plants/ parts are highly colonized by a large
number of fungi. A. flavus, A. niger, Fusasiummoniliforme, F. oxysporum, Pencillium citrinum,
Rhizopus stolonifer, Chaetomium cochloides, C.
globossum, Alternaria alternata, Curvularia
lunata were regularly recorded on almost all thehosts throughout the year.
A comparative review of Table-1 indicatesthat composition of storage fungi fluctuated on
account of the change in the atmosphericcondition and was found maximum during therainy season. Lesser incidence of fungi wasrecorded during winter when the temperature,
RH and rainfall were minimum. However in thesummer season minimum number of fungi wasobserved in comparison to winter season where
maximum number of fungi was noted. Roy et. al.
(1987), Dutta (1988), Chourasia (1990), Chavan
et. al. (1995) and Singh et. al. (2012) have also
observed the similar trend when they worked
with various hosts.
The variation in the fungal incidence indifferent seasons was obviously due to theirdifferent level of tolerance to grow undervariable environmental conditions. Singh (1992),
Prasad et. al. (1995) observed that maximum
number of fungi was found during July to
September when temperature, humidity and
Rainfall was maximum when they worked withdifferent host. Kadians (1989) observed
maximum disease incidence during the rainyseason while working on urad bean.
The early literature also shows that higher
level of relative humidity favored the luxuriant
fungal growth on stored commodities(Christensene 1973 and Wallace et. Al. 1976).
The view was also supported by Bhatt andChauhan (1985), Kumari and Roy (1990) andSingh (1992) who worked on environmental
conditions.

RESULTS
A comparative accounts of plants/parts with
their therapeutic value as well as fungi associatedwith them during different seasonal variation has
been presented in Table 1.
A perusal of Table illustrates that Aspergillus
candidus, A.flavus, A niger, Fusarium
oxysporum, Pencillium sps, Chaetomium –globossum C. cristatum C. cochloides,
Curvularia lunata Alternaria alternata and
Colltotrichum sp. were common fungal flora on
all the samples during winter season (November
to February) when the temperature and RH
ranged from 7.5 to 23.6 0C and 50-97%
respectively, the rainfall ranged between 1.4 to
8.0 mm. Besides above listed fungi Papulospora
sp. and Rhizopus stolonifer were listed from C.
tinctorius seed while
Helminthosporium
spiciferum was recorded from S. xanthocsrpum
leaves.
The nature and number of fungi varied withthe changes in the temperature (10.5-37.2 0C
Humidity (31-83% RH) and rainfall (0-0.77mm)
during the summer season (March to June).
Presence of Aspergillus flavus A. niger A.
candidus A. ochraceus, Rhizopus stolonifer
Chaetomium cochloides, C. globossum, Fusarum
moniliforme, F. oxysporum, Penicillium,
citrinum, Curvularia lunata, Alternarita,
alternata,
Helminthosporium
spiciferum,
Colletotrichum dematium and Botryodiplodia
theobromae were recorded on all the selected
samples. Besides, these Rhizopus nigricans was
isolated from the seeds of C. tinctorius while
Papulospora sps, was recorded on Ricinus
communis seeds.
During rainy season i.e. July to October theenvironmental temperature, humidity and rainfall
ranged between 21.5-24.50C, 71-91% and 30.533.2 mm respectively. It was also noted that the
number of myoflora was maximum during therainy season. Aspergillus flavus, A. niger A.
candidus, Fusarium moniliforme F.equiseti,
Chaetomium cochloides, C. cristatum, C.
globossum, Penicillum citrinum, Colletotuchum
dematium
Cercospora
sps.
Cladospora
cladosporiodes, Rhizopus stolonifer, Curvulasia
lunata and Botryodiplodia theobromae wereisolated from all the selected samples.

CONCLUSION
Preliminary survey of field, store houses andmarkets have revealed that drug plants, plantparts and seeds were contaminated by a numberof fungi of different groups. However, the natureof mycoflora varied with the chemicalcomposition of the hosts as well as withcondition of storage.
The seasonal variations like temperature,humidity and rainfall plays major role on theincidence of fungi (Awasthi and Kolte 1994).
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1: Mycoflora Associated with Drug Plants/Parts

Name of the
Plant/Family

Winter Season(November-February)

Summer Season(March-June)

Rainy Season(July-October)

RicinusCobbunis(Euphorbiaceae)

Aspergillus flavus
A. nigerA. candidus
Chaetomium globossum

A. flavus
A. candidus
A. ochraceus
Chaetomium cochloides

A. flavus
A. nioger
A. candidus

C. cochloides

C. cristatus

Curbuloaria sp.

Rhizopus stolonifer
Botryodiplodia
theobrolae
F. monilfrome
F. equiseti
Papulospora sp.
Penicillium citrinum
A. flavus
A. ochraceus
Curvularia lunata
Chaetomium
globossum
C. cochloides
Collettrichum
damatjum
F. monilifromeF. oxyspotus
Penicillium citrinum
A. alternate
A. flavus
Chaetomium cochloides
C. globossum
Colletotrichum
dematium
Curvularia lunata
Fusarium monliforme
F. oxysporum
H. spiciferum

C. luntea

Colletotrichum sp.
Fusarium oxysporum
Penicillium sp.

Carthamus
Tinctorius(Coapositae)

A. flavus
A. nigerC. lunata
F. soniliforme
F. equiseti
Papulospora sp.
Alternaria alternate
Rhizopus stolonifer

Solanum
Xnthocarpum(Solanaceae)

Actinospora sp.
Alternaria alternate
Aspergillus flavus
Chaetomium glodoffuf

B. theobromae

Colletotrichum sp.
Fusarium oxysporum
Helminthosporium
Speciferum

Datura alba
(Solanaceae)

Fusarium equiseti
Curvularia lunata
Altermaria alternata
Aspergillus flavus

C. globossum

A. niger

Fusarium oxysporum
E. equiseti
Curvularia lunata
Altaermaria alternate
Colletotrichum
dematium
Cladosporius
Cladosporoides
Aspergillus flavus

A. candidus

146

A. nidulans
Chaetomiaum
globussum
Colletotrichum sp.

Fusarim equiseti
F. oxysporum
F.oxysporum
Penicellium citrinum
A. nidulans
A. flavus
A. nigerA. candidus
C. globssum
C. cochaloides
C. indicum
F. noniliforae
F. equiseti
Actinospora sp.
A. flavus
A. nigerA. candidus

Chaetomium globossum
C. cochloides
Fusarium moniliforme
F. eqeiseti
Nigrosporaoryzae
Papulospora sp.
Hieminthosporium sp.
Aspergillus sp.
A. flavus
Colletotrichus sps.
Chaetomium indicum

C. cohliides
Cercosporors sp.
Botryodiploidia sp.

SEE - Bangkok, Thailand, Nov.11-13, 2019

A. niger
However, periodical observation and survey ofthe samples showed that Aspergillus flavus, A.
niger, Fusarium monliforme, Rhizopus stolniferand Alternaria alternata were most common
fungal flora on all the samples throughout theyear whereas Curvularia lunata, Chaetomium
globossum, Fusarium oxysporum and Pencillium
citrinum remained confined to specific seasons.
Some of the fungi like A.candidus, F.
semitectum, H. spiciferum Papulospora sps.
Cercospora sps. Nigrospora sps. were rare on
all the samples. The maximum incidence offungi was noted between July and October whenatmospheric temperature, humidity and rainfall
are quite suitable for the presence of fungal
incidence. While minimum incidence noted
between November to February. These periods
are safest for the storage of medicinal plants/
parts as well as seeds due to minimum
temperature, humidity and scanty rainfall.

Papulospo sp.

22/91(RBB-1) pp. 33-56.
[6] Roy, A.K., Chourasia, H.K. and and Kumari
N. Seasonal Variation in mycoflora
associate with store medicinal fruits andseeds Biol. Bull. India 1987, Vol. 9 No. 2,
pp. 111-116.
[7] Gutta, G.R. and Roy A.K. Mycoflora
associate with strychnos seeds anddeterioration of their active principles understorage Ind. Phytopathi 1987, Vol. 40 No. 4,
pp. 520-524.
[8] Chourasia,
H.K.
PathologicalandBiochemical investigation of some common
drug plants with special reference to
Mycotoxin eleaboration. Ph.D. Thesis,
Bhagalpur University, 1990.
[9] Chavan, S.B., Khandge, S.V., Varshneya,
M.C. and Patil, J.D. Influence of weather
parameters on conidia formation in powdery
mildew of grope. 1995 Indian phytopath
Vol. 48. No. 01 pp. 40-44.
[10] Kadian, O.P. Effect of environment on
incidence and development of leaf crinkle
disease in urid seed. 1989 Indian phytopath
42(2) pp. 273.
[11] Bhatt,
J.C.
and
Chauhan,V.S.
Epidemological studies on neck blast of ricein U.P. hills. Indian Phytopath 1985, Vol. 38
No. 1 pp. 126-130.
[12] Kumari, V. and Roy, A.K. Biodeteriorationof Embelia ribes seeds under the influenceof different relative humidity. 1990 National
Academy Science Letters. Vol. 13 No. 05
pp. 167-169.
[13] Christensen, C.M., Loss of viability instorage microflora. 1973 Seed Science andTechnology 1:547-562.
[14] Wallace, H.A.H., Sinha, R.N. and Mills, J.J.
Fungi associated with small wheat bulks
during prolonged storage in Manitoba. 1976.
Chad. J. Bot. 54(12) 1332-1343.
[15] Awasthi, R.P. and Kolte. Epidemologicalfactors in relation to development &prediction of Alternasia blight of repeseed &mustard 1994. Indian. Phytopath 47(4) pp.
395-39.

REFERENCES[1] Singh, H.N.P., Studies on disease of
Banana: A pathodogical and Biochemical
approach Ph.D. Thesis, 1992, pp. 26-32, 3343.
[2] Singh, H.N.P., Kumari, S. and Prasad, M.M.
Influence of Meteorological conditions on
diseases development of Banana fruits. 2012
Proceeding volume, Glimpses of Phythology
for sustainable Agriculture, A.B. Publication
New Delhi, Edited Dr. H.K. Chaurasia, Dr.
A.K. Roy & Dr. Usha Kumari pp. 227-232.
[3] Geetika and Ahmad, Mushtaq. Influence of
abiotic factors on the bio-control efficacy oftrichoderma against Fusarium proliferatum
under in vitro. Journal of Mycology & plant
pathology. 2018, Vol. 48 No. 3 pp. 348-356.
[4] Singh, H.N.P. and Prasad M.M. Effect oftemperature and humidity on fungal spoilageof two varieties of banana Indian Botanical
Reporter. 1992, Vol. 6(1) pp. 85-86.
[5] Prasad, M.M., Singh, H.N.P. Roy, A.K. andSinha, R.K. Microbial spoilage of silk
cocoons in storage centres of Bihar and theircontrol 1995, Final Technical Report U.G.C.
Govt. of India, New Delhi, Code No. F 3-

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF KNEADING AND FERMENTATION TIME ON
CHEMICAL QUALITY OF HERBAL TEA FROM MANGO PEEL
1

Nunchanok Nanthachai1, Intira Lichanporn 1, Palida Tanganurat1 and Pradit Kumnongphai1
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi , Thailand

ABSTRACTThis research aimed to develop herbal tea from agricultural by-product such as mango peel. The
study was conducted using a 3x3 Factorial in completely randomized design. Two factors were investigated; thekneading time of mango peel at 10, 20 and 30 minutes and the fermentation time of mango peel at 15, 30 and 45
minutes. The result showed that total phenolic content and antioxidant activity of the unripe mango peel were
8.48 mg/g and 18.34%, respectively. And those contents were significantly higher than that ripen mango (p 0.05). The kneading and fermentation time were affected on total phenolic content and antioxidant activity of thepeel. Mango peel kneaded for 20 minutes had 20.83 – 28.50% antioxidant activity which significantly higher
than that kneaded for 10 and 30 minutes (p  0.05). And mango peel fermented for 15 minutes had 21.96 –23.01 mg/g total phenolic compounds that significantly higher than fermentation time at 30 and 45 minutes (p 0.05). Sensory evaluation showed that the score of color, flavor and taste of tea from mango peel kneaded andfermented for 10 and 15 minutes, respectively significantly higher than other kneading and fermentation times (p 0.05).
Keywords: Mango, Herbal tea, Total phenolic compounds, Antioxidant activity[8]. Mango is normally used for direct consumption,
as well as for the processing of dried fruit, fruit juice
and etc [9]. During mango processing, the peel is
one of the most important by-products, whichconstitutes about 15-20 g/100g of the fresh fruit
weight [10]. In fact, mango peel has various
nutrients, including dietary ﬁber, protein, fat, andphytochemicals like polyphenols, carotenoids,
tocopherols and ascorbic acid etc. [11] - [14].
Bioactive compounds such as polyphenols,
carotenoids and anthocyanins present in fruits andvegetables are receiving increased attention becauseof their potential antioxidant activity. Therefore,
mango peel is a potential healthy food ingredientthat could be used to improve the functional
properties of food [9]. The application of mango
peel powder has been reported in biscuits, bread andmacaroni etc., and the products showed elevatedpolyphenol and dietary ﬁber contents, as well as
improved antioxidant ability [15], [16]. However,mango peel has not been applied in beverages. In
this study, mango peel was imitated the process ofmaking tea. Kneading and fermentation of themango peel probably increase phenolic compounds
and flavor. Thus, the objective of this research was
to develop herbal tea from mango peel by
investigated the optimization of kneading andfermentation times of the peel.

INTRODUCTION
Tea is an aromatic beverage prepared by pouring
hot water over leaves of the Camellia sinensis. Tea
is a popular beverage, consumed by people
worldwide. It is rich in polysaccharides, caffeine,
polyphenols and amino acids, as well as
antioxidants, which are beneﬁcial for human health[1]. Herbal teas also called tisanes are deﬁned aswater-based infusions prepared with herbal
ingredients other than Camellia sinensis. Such teas
are popular amongst health-conscious people as they
are rich in minerals and antioxidants [2], [3]. Tisanes
are caffeine free and can be served hot or cold.
Tisanes were drunk for both enjoyment andmedicinal purposes. Plant phenolic, also called
polyphenols, are a class of chemical compounds thatconsist of one or more hydroxyl groups (OH)bonded to one or more benzene rings. In recent
years, quantifying the phenolic content andevaluating its contribution to the antioxidant
capacity have become important [4]. Phenolic
compounds are produced through the secondary
metabolism of plants and are essential for their
growth. This group of biologically active molecules
has been extensively studied due to their multiple
biological eﬀects, such as anti-inﬂammatory,
antimicrobial and antioxidant activity [5].
Mango (Mangifera indica L.) is one of the mostpopular and best known tropical fruits due to its
production and consumer acceptance [6]. Mango is ahighly prized fruit due to its attractive color andflavor, delicious taste and high nutritional value [7],MATERIALS AND METHODS
Experimental Materials

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SEE - Bangkok, Thailand, Nov.11-13, 2019

In this research, unripe (immature) and ripe
(mature) mangos were of Numdokmai variety andacquired from a local fresh market in Thailand.
Harvesting index of unripe and ripe mango were 70– 90 and 95 – 105 days after fruiting, respectively[17]. Unripe and ripe mangos were presented in Fig.
1. The fruits were first washed with tap water andthen rinsed with distilled water before left to dry andpeels removed.

(a)sensory characteristics included color, aroma, andtaste.
Characterization of chemical properties
In this research, total phenolic content wasdetermined using Folin-Ciocalteu method [18] withminor modifications. In the analysis, 0.3 millilitersof tea infusion was first mixed with 2.25 millilitersof 10% Folin-Ciocalteu reagent dissolved in distilledwater, and with 2.25 milliliter of 6% sodium
carbonate solution. The mixture was then incubated
for 90 minutes at room temperature. The absorbancewas measured at 725 nanometers using aspectrophotometer, and total phenolic content
expressed as milligram/gram (mg/g).
Antioxidant activity was determined by (1,1diphenyl-2-picrylhydrazyl)
radicalscavenging
activity [19] with minor modiﬁcations, whereby 0.1
milliliter of tea infusion was added to 1.9 milliliterof 0.1 milliliter 1,1-diphenyl-2-picrylhydrazyl
solution dissolved in ethanol, shaken and incubatedin the dark for 30 minutes at room temperature. The
absorbance was measured at 517 nanometers usingthespectrophotometer.
The
1,1-diphenyl-2picrylhydrazyl scavenging activity was calculated by(b)

Figure 1 Physical appearance of: (a) unripe and (b)ripe mango

Experimental Methodology
Mango peel drying process
The mango peels were cut into smaller pieces (1x 3 cm) and kneaded by a kneader mixer (EMS200LP, Japan) at a moderate speed for 10 minutes.
The kneaded peels were transferred to stainless steel
containers and covered with straining cloth toferment for 10 minutes at room temperature. The
fermented peels were then oven-dried at 60oC for 3
hours (BINDER GmbH, Germany). The dried unripe
and ripe mango-peel tea products were retained in aconcealed airtight container at room temperature.

Antioxidant activity (%)

Acontrol  Asample
Acontrolx100

where Acontrol and Asample are the absorbances ofreference and tea infusion sample, respectively.
Sensory evaluation of mango peel tea
The sensory evaluation of dried mango peel tea
infusions was carried out using a 9-point hedonic
scale, where 1 denotes extremely unfavorable and 9
extremely favorable. The dried mango peel tea (3grams) was brewed in 200 milliliters hot water (8090oC) for 5 minutes. Then, 20 milliliter of the tea
infusions was transferred to tea cups for sensory test
where a group of 30 untrained panelists evaluatedthe tea solution samples on color, aroma, taste, andoverall acceptance, based on 9-point hedonic scale.

Optimization of kneading and fermentation times
Prior to optimization, total phenolic content andantioxidant activity of unripe and ripe dried mangopeel tea products were characterized and compared.
The tea product possessing higher total phenoliccontent and antioxidant activity was selected for
subsequent experiment.
The kneading and fermentation durations ofchosen dried mango peel tea product were optimized
with regard to the chemical properties and sensory
characteristics using a 3x3 factorial design, giving
rise to 9 experimental runs (i.e., nine dried mango
peel tea products). The kneading time was varied
between 10, 20, and 30 minutes; and thefermentation time between 15, 30, and 45 minutes.
The chemical properties of interest were total
phenolic content and antioxidant activity and theStatistical analysis
All experiments were carried out in triplicate andthe results expressed as mean ± standard deviation.
Analysis of variance (ANOVA) was used to analyze
the data and Duncan’s multiple range test tocompare means. Statistical significance was basedon the 5% significance level (p ≤ 0.05).
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SEE - Bangkok, Thailand, Nov.11-13, 2019

experiment.

RESULTS AND DISCUSSION
Chemical qualities of tea from unripe and ripemango peel

Table 1 Chlorophyll and carotenoid of tea from
unripe and ripe mango peel.

Figures 2 (a)-(d) respectively illustrate thephysical appearance of unripe and ripe dried mango
peel tea products and their respective tea infusions.
By comparison, unripe mango peel tea possessed adarker color and stronger scent than ripe mango peeltea.

Tea product

Chlorophyll
Carotenoid(mg/g)(mg/g)nsa
Unripe mango peel
3.33
12.24
Ripe mango peel
0.12b
12.80
Mean of the same column with different superscripts
indicating significantly differences (p ≤ 0.05).
ns mean not significant
Table 2 Total phenolic content and antioxidant
activity of tea from unripe and ripe mango peel.
Tea product(a)

Total phenolic Antioxidant
content (mg/g) activity (%)
Unripe mango peel
8.48a
18.34ab
Ripe mango peel
5.85
11.00bMean of the same column with different superscripts
indicating significantly differences (p ≤ 0.05).

(b)

Optimization of kneading and fermentation times(c)Kneading and fermentation probably did notaffect chlorophyll of mango peel tea (Table 3).
Although, chlorophyll of processed mango peel was
lower than unprocessed, this might be due tochlorophyll damaged while drying in hightemperature. The central Mg atom is replaced byhydrogen ions. This affects the energy levels within
the molecule, causing its absorbance spectrum toalter. Thus processed mango peel changed color,becoming a paler, insipid yellowy green. Carotenoid
trended to increase after the process (Table 3).

(d)Figure 2 Physical appearance of: (a) unripe and (b)ripe dried mango peel tea products, (c) unripe and(d) ripe mango peel tea infusions

Chlorophyll and carotenoid of mango peel tea
were shown in Table 1. Total phenolic content andantioxidant activity of tea from unripe mango peel
were 8.48 mg/g and 18.34%, respectively (Table 2).
And those contents were significantly higher thanthat ripe mango (p  0.05). The total phenoliccontent and antioxidant activity of mango peel var.
Raspuri and Badami have been reported. The total
polyphenols content in 80% acetone extract of raw
mango peels ranged from 90 to 110 mg/g peel,
whereas it ranged from 55 to 100 mg/g in ripe peels
depending on the variety [20]. In the present study,
the phenolic content and antioxidant activity werelower than those reported previously; a possible
reason could be that the peel was diluted into readyto-drink-solution before the measurements. However,in this present study also found that total phenoliccontent and antioxidant activity of the solution from
unripe peel higher than product from ripe peel. Thus,
the unripe mango peel was selected for the next

Table 3 Chlorophyll and carotenoid of unripe mango
peel teas.
Kneading &Chlorophyll
Carotenoid
Fermentation(mg/g)ns(mg/g)(minutes)
10 & 150.09
16.22bc
10 & 30
0.08
15.90cd
10 & 450.11
14.35de20 & 150.10
19.44a20 & 30
0.09
18.94a20 & 450.09
17.56ab30 & 150.05
16.26bc
30 & 30
0.12
13.25e30 & 450.08
15.14dMean of the same column with different superscripts
indicating significantly differences (p ≤ 0.05).
ns mean not significant
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SEE - Bangkok, Thailand, Nov.11-13, 2019

In Table 4, total phenolic of unripe mango peeltea were positively correlated with the fermentation
time, and the antioxidant activity initially rose withincrease in the kneading time and declined beyond
20 minutes. Specifically, the moderate kneading
time (20 minutes), for all fermentation durations (15,30, 45 minutes), achieved significantly higher
antioxidant activity (20.83 – 28.50%), comparedwith short (10 minutes; 16.65 – 19.20%) and long
(30 minutes; 15.93 – 18.70%) kneading time (p ≤0.05). Meanwhile, the short fermentation time (15minutes) yielded significantly higher total phenolic
compounds (21.96 – 22.62 mg/g), vis-à-vis moderate(30 minutes; 17.34 – 20.01 mg/g) and long (45minutes; 17.35 – 19.78 mg/g) fermentation times (p≤ 0.05). Generally, total phenolic contents of herbal
teas were between 0.08 - 28.97 g/100g dry weight,
averaging 4.52 g/100g dry weight [21].

the fermentation process probably induced thephytochemical compounds and enzymes in mango
peel broken down, and its antioxidants are released
or transformed. Oxidation is highly important in theformation of many taste and aroma compounds,
which give a tea has specific color, strength, andbriskness.
The correlation between the total phenoliccontent and antioxidant property of mango peel teas
were calculated as shown in Figure 3. There was no
significant correlations detected between the total
phenolic compounds and antioxidant activity (r2 =0.31). Many studies indicated that total phenolic
compounds were highly positively correlated withantioxidant activity [24]-[26]. However, the resultin this study was difference from other studies; thepossible reasons could be that this result was basedon the determination and statistical analysis of asmall number of samples. Meanwhile, thecorrelation between the carotenoid content andantioxidant property of mango peel teas showed thestrongly relation (r2 = 0.87). Carotenoids also haveantioxidant properties. The antioxidant activity ofthese compounds can shift into a prooxidant effect,
depending on such factors as oxygen tension or
carotenoid concentration. Mixtures of carotenoids
alone or in association with others antioxidants canincrease their activity against lipid peroxidation [27].

Table 4 The total phenolic content and antioxidant
activity of unripe mango peel teas.
Kneading &Phenolic
Antioxidant
Fermentation(mg/g)
activity (%)(minutes)
10 & 15
21.96a19.20bc
10 & 30
18.13
17.30bc
10 & 45
17.35
16.65ca
20 & 15
22.21
28.50ab
20 & 30
20.01
25.80ac
20 & 45
19.78
20.83aa30 & 15
22.62
18.43bc
30 & 30
17.34
15.93cc
30 & 45
18.25
18.70bMean of the same column with different superscripts
indicating significantly differences (p ≤ 0.05).

It was obvious that processed mango peel had
phenolic
content
andantioxidant
activity
significantly higher than mango peel without any
process (p ≤ 0.05). The results in this study wereconsistent with the previous study [22]. They foundthat Japanese-style-green-tea-process-young (JGTPY) coﬀee leaves and black-tea-process-mature(BTP-M) coﬀee leaves exhibited antioxidant andanti-inﬂammatory activities that reﬂected both thephenolic concentration and speciﬁc composition.
Tea fermentation is usually referred as theatmospheric oxidation of catechins (ﬂavanols)
catalyzed by the tea leaf endogenous enzymes,
which produces polyphenol pigments [23].
The process of mango peel tea in this study was
modified from oolong tea processing since it usedshort oxidation period. The kneading action ofmango peel probably caused some of the sap,
essential oils, and juices inside the skin to ooze out,
which further enhances the taste of the tea. And in

Figure 3 The regression and correlation between the
total phenolic compounds and antioxidant activity ofthe mango peel tea product.

Color of mango peel tea and the infusions wereshown in Figure 4 and 5, respectively. Color of
infusions of mango peel kneaded for 10 minutes andfermented for 10 and 30 minutes were slightly
darker than other treatments. The aroma and taste ofinfusions were green and a bit astringent. The
hedonic test on parameters such as color, flavor,
taste and overall acceptance of mango peel tea
infusion were presented in Table 3. Sensory
evaluation showed that the score of color, flavor andtaste of tea from mango peel kneaded and fermented
for 10 and 15 minutes, respectively significantly
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SEE - Bangkok, Thailand, Nov.11-13, 2019higher than other kneading and fermentation times(p  0.05).

Table 5 Sensory attributes evaluation such as color,flavor, taste and overall acceptance of mango peeltea infusion.
Kneading &Sensory evaluation
Fermentation Color Flavor Taste
Overall(minutes)
acceptance
10 & 15
6.70a
6.73a
6.67a
6.67a
b
b
b
10 & 30
5.70
5.97
5.90
6.00b
b
b
b
10 & 45
5.77
5.97
5.77
5.87b
b
b
b
20 & 15
6.00
5.70
5.70
5.97b
b
b
b
20 & 30
6.10
5.67
5.73
5.90b
b
b
b
20 & 45
5.93
5.77
5.93
5.90b
b
b
b
30 & 15
6.03
5.73
5.90
5.90b
b
b
b
30 & 30
5.87
5.90
5.90
5.93b
b
b
b
30 & 45
6.10
5.90
5.67
5.87b
Mean of the same column with different superscripts
indicating significantly differences (p ≤ 0.05).

Figure 5 Color of mango peel tea infusions. Mango
peels were kneaded and fermented at different time:(a) 10 and 15 minutes (b) 10 and 30 minutes (c) 10
and 45 minutes (d) 20 and 15 minutes (e) 20 and 30
minutes (f) 20 and 45 minutes (g) 30 and 15 minutes(h) 30 and 30 minutes and (i) 30 and 45 minutes.

CONCLUSION
Total phenolic content and antioxidant activity oftea from unripe mango peel were significantly
higher than that ripe mango (p  0.05). Kneading
time had effect on antioxidant activity of the tea
product, while, fermentation time had effect on total
phenolic content of the tea. The result showed thatmango peel kneaded for 20 minutes had antioxidant
activity significantly higher than kneading time at 10
and 30 minutes (p  0.05). And mango peelfermented for 15 minutes had total phenolic
compounds significantly higher than fermentation
time at 30 and 45 minutes (p  0.05). Sensory
evaluation showed that the score of color, flavor
taste and overall acceptance of the infusion frommango peel tea kneaded and fermented for 10 and 15
minutes, respectively significantly higher than otherkneading and fermentation times (p  0.05).
Figure 4 Physical appearance of mango peel tea thatkneaded and fermented at different time: (a) 10 and
15 minutes (b) 10 and 30 minutes (c) 10 and 45
minutes (d) 20 and 15 minutes (e) 20 and 30 minutes(f) 20 and 45 minutes (g) 30 and 15 minutes (h) 30
and 30 minutes and (i) 30 and 45 minutes.

ACKNOWLEDGEMENTS
This work was supported by National ResearchCouncil of Thailand (NRCT) and Faculty ofAgricultural Technology, Rajamangala University ofTechnology Thanyaburi (RMUTT).

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SEE - Bangkok, Thailand, Nov.11-13, 2019

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

FORMULATION, ANTIOXIDANT AND ANTIBACTERIA ACTIVITIESOF PEEL-OFF GEL MASK, ENRICHED WITH BIDARA LEAF(ZIZIPHUS SPINA-CHRISTI L.) EXTRACT
Hendrawati1, Aziza1, La Ode Sumarlin1, Yulyani Nur Azizah1
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

ABSTRACT
Bidara Leaves (Ziziphus spina-christi L.) is the one of the herbs that already known by people to repair the
broken cell and acne’s problem. The bidara leaves extract can be formulated into a peel-off gel mask for facialskin. The objective of this research is to formulate the peel-off gel mask from ethanol extract of bidara leaves. The
peel-off gel mask expected effective in reducing the adverse effects of free radicals and inhibits the growth ofacne-causing bacteria on the face. Identification of bioactive compounds in bidara leaves extract withphytochemical test and Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) instrument.
Antioxidant activity test using 1,1-diphenyl-2-picrylhydrazil (DPPH) method and IC50 value determination.
Testing of antibacterial activity of ethanol extract of bidara leaf against Propionibacterium acne bacteria bydiffusion method. Preparation of gel mask peel-off using variation of concentration 15, 25 and 35%. Peel-off gel
mask characterization by organoleptic test, physical appearance, pH value, homogeneity test, dispersion test,
drying time test and microbial contamination. Ethanol extract of bidara leaves has very strong antioxidant activity
with IC50 23,382 ppm and antibacterial activity with inhibition of bacteria P. acne at a concentration ≥ 0.25 g/mL.
The results of LC-MS/MS analysis showed that there were routine compounds at retention time of 5.13 which
had the potential as antioxidants and antibacterial. Peel-off gel masks obtained have antioxidant and antibacterial
activity and are included in the quality requirements category of SNI 16-6070-1999 and SNI 16-4380-1996.
Keywords: antibacterial, antioxidant, bidara leaves, peel-off gel mask

INTRODUCTION

alternative medicine for self- purify and to cure fever,pain, dandruff, wound, inflammation, asthma, andsore eyes [2]. In traditional medicines, all parts ofbidara, namely root, leaf, fruit, seed, and stem wereused to cure [3]. Bidara leaf extract has been
analyzed by using LC-MS instrument. Soleh Putri,2017 obtained the highest concentration of two
suspected rutin compounds, which classified as oneof the active flavonoid compounds [4]. Kusriani et al.
(2015) stated that bidara leaf extract contained
phenolic compounds, in total 7,192% ± 0,0198 [5].
Meanwhile, the ethanol extract of bidara leaves
showed antioxidant activities with IC50 value 127,87
ppm [6].
Research conducted by Haeria et al. (2016)
suggested that the ethanol extract of bidara leaves
contained high concentration of antioxidant, withflavonoid compounds 1,5312% in total and IC50 value
90,9584 ppm [7]. Ali et al.(2015) revealed that bidara
leaf extract shows antibacterial activities to prevent
pathogen-bacteria growth, i.e. Proteus vulgaris,
Escherichia coli, Bacillus subtilis, Staphylococcus
aureus, and Pseudomonas aeruginosa that can be

The utilization of natural substances as
antioxidant and antibacterial agents for health productand personal care has been increasingly developed tosupport human basic needs. Plants as natural
substances have been considerable used for health,
medicine, and beauty products. In global health’s
context, natural source and its outcome prove that allplants contain compounds, which are clinically
proven beneficial for health [1]. Bidara is one of theplants that is beneficial for human health. According
to hadith by Bukhari and Muslim, Rasullullah
presented the commendable deed to utilize bidara
leaves in performing Islamic ritual ablution andpurification on a dead body. This ritual performance
gives basic knowledge to human that bidara leaf has
beneficial effects to purify.
Bidara leaf extract has been utilized in medicines
development in addition to pharmacology activities in
Middle East, South East, and East Asia. Bidara leaf
is believed to have medicinal properties to curevarious diseases. Bidara has been used as an

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SEE - Bangkok, Thailand, Nov.11-13, 2019potentially added into the active substances in facialcosmetic product [8].
Facial cosmetic can be produced in various forms.
One of those forms is peel-off mask, which ispractically used and easy to clean [6]. Ariani and
Wigati (2019) used the formulation of peel-off mask
as acne cream with Polyvinyl alcohol (PVA) as themain formula of gelling agent; hydroxypropyl
methylcellulose (HPMC) as viscosity-increasing
agents; and propylene glycol (PG) as humectant agent[9]. The formulation of peel-off gel mask withselected basis substances, i.e. PVA with higher
concentration than HPMC, did produce the mostexcellent characteristic of peel-off gel mask [10].
Therefore, a research on peel-off gel mask, enrichedwith ethanol extract of bidara leaf (Z. spina-christi
L.) with various concentrations, is supposed to
conduct. This new formula is expected to increase
antioxidant and antibacterial activities of peel-off gel
mask.

extract to examine steroid/triterpenoid, flavonoid,
alkaloid, phenolic, tannin, and saponin compounds,
was conducted by using proper reagents.
Identification of Active Compounds of Ethanol
Extract of Bidara Leaves using LCMS/MS Method
Ethanol extract of bidara leaves (1 mg) was
weighed and diluted in methanol. Leaf samples (10μL) were taken and injected to LCMS/MS throughcolumn C-18 (2 x 150 mm) with the flow rate 0,2
mL/min. Chromatography analysis and mass
spectrophotometry were observed by using a software
program, MassLynx (Version 4.1), to identify thesuspected chemical structures.
Formulation of Peel-Off Gel Mask
Polyvinyl alcohol (PVA) was added with aquades
four times and heated until the PVA was transparent
and homogenous. Hydroxypropyl methylcellulose(HPMC) was grown with aquades for 30 min. PVA
and HPMC were mixed in a mortar and grinded until
the mixture was homogenous. The mixture was addedwith proplylene glycol, gradually diluted with ethanol
and odour, and then homogenized. The peel-off gel
mask was formulated with varied concentration ofbidara leaf extract, 25, 30, and 35% (b/v).

RESEARCH METHOD
Materials and Equipments
Bidara leaves used in this research(approximately 1 kg), were obtained from bidara
farm in Sumenep, East Java and identified in
Herbarium Bogoriense, LIPI Bogor. A solvent used
was 96% technical grade ethanol. Bacterial isolate of
P. acne was obtained from Laboratorium Biologi,
Universitas
Indonesia(Biology
Laboratory,
University of Indonesia). Tryptic Soy Agar was used
as a medium to culture antibacterial compounds.
DPPH was used to analyze antioxidant activities.
PVA, HPMC, propylene glycol, and aquades, as wellas commercial product to compare, were used to form
peel-off gel mask. The equipments used in thisresearch were Spectrophotometer UV Vis, LCMS/MS, analytical weighing balance, laboratory
glassware, pH meter, oven, vacuum rotary evaporator,
incubator, and autoclave.

Antioxidant Activity TestingA 2 mL sample was put into a culture tube, thenadded with 2 mL of DPPH 0,002%. The mixture washomogenized then incubated in a dark room, at room
temperature for 30 min. The absorbance wasmeasured by using UV-Vis Spectrophotometry andobtained wavelength 516 nm. A percentage inhibition
was calculated and equated into a linear regression
analysis to obtain IC50 value.
Antibacterial Activity Testing
Antibacterial activity testing of bidara leaves was
conducted by performing preliminary test on ethanol
extract of bidara leaves, with the following steps: (i)TSA medium (25 mL) was inserted into petri dish; (ii)
added with bacterial suspension (0,25 mL); (iii)homogenized until the medium was solid and firm.
Furthermore, holes were made in medium and appliedwith 100 µL extract, then incubated at 37oC for
24 h. Ethanol extract testing of bidara leaves was
conducted on thick extract, with extract concentration
1; 0,5 ;0,25; 0,125g/mL. Inhibition zone formed wasobserved; diameter of inhibition zone was measured.

Extraction and Phytochemical Analysis of Bidara
LeavesBidara leaves (Z. spina-christi L.) were grinded,weighed and put into a container to be macerated.
Afterwards, the macerated bidara leaves were addedwith 96% ethanol until the leaves were completely
soaked. After the soaking procedure, the soakedbidara leaves were stirred for 30 min. The container
was covered and kept for 24 h at room temperature.
The filtration of bidara leaf extract was collected andcondensed in a vacuum rotary evaporator. The
solvent was further evaporated to obtain thick-ethanol
extract of bidara leaves. Afterwards, the ethanol
extract of bidara leaves were ready to use as the test
samples. Phytochemical analysis on bidara leaf

Characterization of Peel-Off Gel Mask
The analysis of formulation result from ethanol
extract of peel-off gel mask of bidara leaves includes:
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SEE - Bangkok, Thailand, Nov.11-13, 2019organoleptic test or testing on panellist’s preference,physical appearance, pH value, dispersion test,
drying-time test, viscosity test, and microbial
pollution test to identify the gel mask quality.

ethanol extract compounds from bidara leaves. The
m/z value 611,1687 was fragmented to be m/z
303,0536 at retention time 5,15. Ionization used inthis research was [M+H]+ to determine the real m/z
value 610,1687. The prediction of compoundmolecular formula was C27H30O16. Compared with
online database Mass Bank, the findings showedsome similarities of mass spectra as a result from rutin
mass spectra measurement, i.e. m/z 611; 465; 303.
Phytochemical screening test showed flavonoid
compounds. Thus, the compound appeared at
retention time 5,15 was suspected as flavonoid
compound, namely rutin.

RESULT AND DISCUSSION

Bidara leaves were grinded and extracted by using
maceration method with 96% ethanol, resulted thickand dark green extract (Figure 1); yield percentage
19%. Phytochemical screening test of ethanol extractof bidara leaves showed positive results on the six
reagents with colour change when added withreagents, proved that bidara leaf extract contains
steroid, flavonoid, alkaloid, tannin, phenolic, andsaponin compounds (Table 1). Ethanol extract ofbidara leaves was expected to have potential
antioxidant and antibacterial activities.
Table 1. Phytochemical screening test

% Intensity

Extraction and Phytochemical Analysis on Bidara
LeavesClass of
Compounds

Reagent

ColourChangeConclusion

Steroid

Lieberman
Burchard

Green+

Flavonoid

Mg+HClOrange+Alkaloid

WagnerPrecipitated
Brown

+

Mass (m/z)

Phenolat

Akuades +FeCl3 1%Black+

Figure 2. Chromatogram of ethanol extract

TanninFeCl3 1%

BlackishGreen+

SaponinAquades

Foamed+Extract of bidara leaves
Rutin is a derivative compound from flavonoid,
i.e. flavonol. Rutin is a condensation result between
quercetin and glycone rutinoside. Quercetin-3-Orutinoside and quercetin have antioxidant activities[11]. Flavonoid prevents free radicals through free
radical scavenger process by donating hydrogen atom
to alter radicals being inactive [12]. According toPelczar dan Chan (2006), quercetin may also act as
antibacterial because its phenolic group performs
protein denaturation and damage microbial cell
membranes [13]. Quercetine and its derivative
compounds were first reported to have antivirus
activities [14].

Figure 1. Ethanol extract of bidara leaves

Identification of Active Compounds in Ethanol
Extract of Bidara Leaves using LCMS/MS Method

Antioxidant Activity of Ethanol Extract on Bidara
Leaves

The analysis of the suspected compounds was
carried out by comparing the similarity of mass
spectra samples and mass spectra compounds, using
online database Mass Bank, The Human Metabolome
Database, and Mass Bank of North America.
Chromatogram in figure 2 illustrated some peaks of

Ascorbic acid was used to observe antioxidant
activities. Research found that ascorbic acid showedstrong antioxidant activity, with IC50 value 3,606
ppm. Antioxidant activity of bidara leaf extract (Z.
spina-christi L.) also classified into highly-strong
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SEE - Bangkok, Thailand, Nov.11-13, 2019

antioxidant activity, with IC50 value 23,382.
However, antioxidant activity of ethanol extract ofbidara leaves is lower than ascorbic acid.

zone with negative control; proved that leaf extract atthat concentration did not show inhibition activities
against P. acne bacteria. Concentration extract of
0,25 g/mL showed diameter of clear zone 14,40 mm;
Concentration 0,5 g/mL resulted inhibition diameter
15,90 mm; Concentration 1 g/mL resulted inhibition
diameter 17,50 mm and thick extract without dilution
process 18,85 mm. Bidara leaf extract (Z. spinachristi L.) showed inhibition activities against P. acneat concentration ≥ 0,25 g/mL. Results obtained from
responses of substances in diffusion holes, marked by
the area clearness or diameter of inhibition zone ateach concentration.

Table 2. Antioxidant activity test on ethanol extractof bidara leaves
Concentrarion
Of bidara
(ppm)

Ads

%
Inhibition

0

0,264

0

2,5

0,185

29,92 ± 0,0042

LinearRegressi

50,172

35,04 ± 0,0007

10

0,156

40,90 ± 0,0014

20

0,134

49,43 ± 0,0007

40

0,093

64,96 ± 0,0007

80

0,018

93,37 ± 0,0007

y=0,7921 x
31,479R2 =0,9911

IC50(ppm)

Formulation of Peel-Off Gel Mask of Ethanol
Extract of Bidara Leaves
The homogenized substances of peel-off gel mask
was added with extract concentration, 0,25, 30, and35%, respectively. The concentration was taken fromthe results of antibacterial activity test on bidara leaf
extract, which showed inhibition power atconcentration ≥ 0,25 g/mL.

23,382

Note: Means ± Standard Deviation (SD)

Antibacterial Activity of Ethanol Extract ofBidara Leaves
Antibacterial test was conducted on thick extract
without dilution process and some varied
concentrations, i.e. concentration 1; 0,5; 0,25, and0,125g/mL, respectively. Positive control was
antibiotic, generated inhibition zone 37,80 mm.
Negative control was sterilized aquades, generated
inhibition zone 8 mm.
Table 3. Antibacterial activity test on ethanol extractof bidara leaves
Figure 3. Formulation of peel-off gel mask
Concentration of
Bidara (g/mL)

Inhibition Diameter (mm)

0,125

8±0

0,250

14,40 ± 1,56

0,500

15,90 ± 1,98

0,100

17,50 ± 1,70

Pekat

18,85 ± 2,76

Kontrol (+)

37,80 ± 1,56

Kontrol (-)

8±0

The peel-off gel mask obtained was F0 with extract
concentration 0%, resulted transparent or clear cream;F1 with 25% extract concentration in faded green
colour; F2 with 30% extract concentration in lightgreen colour; F3 with 35% extract concentration indark green colour (Figure 3). The green colour inpeel-off gel mask was resulted from bidara leaf
extract. The thickness of green colour in peel-off gel
mask increased equally with the adding of bidara leaf
extract.
Antioxidant Activity of Peel-off Gel Mask ofBidara Leaf Ethanol Extract
Based on the results of antioxidant activity test on
peel-off gel mask, the higher amount ethanol extractof bidara leaves (Z. spina-christi L.) added into thepeel-off gel mask, the higher antioxidant activities
performed. It was in accordance with the increasing
inhibition percentage value of peel-off gel mask andNote: Means of inhibition diameter ± Standard
Deviation; Control (+) is tetracycline and Control (–)
is sterilized aquades
Results of antibacterial test of bidara leaf extract atconcentration 0,125 g/mL showed the same inhibition
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SEE - Bangkok, Thailand, Nov.11-13, 2019

the increasing ethanol extract concentration of bidara
leaves. The inhibition percentage was lower
compared with the ethanol extract of bidara leaves.
The smaller amount of extract concentration than theamount of peel-off gel mask used in this research led
to low percentage of inhibition. The decrease of
inhibition percentage might be caused by the amountof ethanol extract of bidara leaves that was not
sufficient or less, hence the active compounds did not
optimally work. However, the peel-off gel mask
showed high antioxidant potentials, compared withcommercial product with the lowest inhibition value.

inhibition zone 9,10 mm. The sample with thesmallest width of inhibition zone was commercial
peel-off gel mask, with inhibition zone 6 mm, samewith peel-off gel mask without additional extract as
the negative control. Antibacterial activity test
showed that peel-off gel mask formula added withethanol extract of bidara leaves performed
antibacterial activities against P. acne. The result was
relatively small compared with the inhibition zone ofethanol extract of bidara leaves before formulated inpeel-off gel mask. The low inhibition zone in peel-off
gel mask was found to be caused by high viscosity,
led to a lower antibacterial activities. The bond
between gel bases and high viscosity was tighter,hence the active compounds were more difficult todiffuse [15].

Table 4. Antioxidant activity test of peel-off gel
mask
SampleInhibition percentage(%)

Commercial (F0)18,389 ± 0,737(Sample without additional
extract)

3,163 ± 0,847(Sample added with 25% extract)
F2

Table 5. Antibacterial test on peel-off gel mask

Formulation

Commercial
6±0F1
7,65 ± 0,49
F2
8,50 ± 1,13
F3
9,10 ± 0,85
Control (+)
32,30 ± 0,42
Control (–)
6±0Note: Means of inhibition diameter ± standard
deviation; Control (+) is t tetracycline and Control
negative (–) is peel-off gel mask without additional
extract.

50,862 ± 1,219(Sample added with 30% extract)F365,743 ± 3,227(Sample added with 35% extract)
Thick extract of bidara leaves
Ascorbic acid

Inhibition Diameter (mm)38,638 ± 3,876

80,823 ± 3,823
94,568 ± 0,415

Note: Means of inhibition percentage ± standard
deviation

Characterization of Gel Mask and Hedonic Test
on Panellists
Antibacterial Activity of Peel-off Gel Mask of
Ethanol Extract of Bidara Leaves

Characterization on formula of peel-off gel maskof ethanol extract of bidara leaves includes physicalappearance, pH value, viscosity test, dispersion test,
drying-time test, and microbial pollution test to study
the characteristic of each peel-off gel mask sample.
Characterization test showed that all samples havefulfilled the requirements of SNI 16-6070-1999,
concerning facial-mask quality and SNI 16-43801996, concerning facial-cleanser product.
Furthermore, statistical hedonic test on panellist
preference showed peel-off gel mask formula F1
indicated the highest level of preference, with theaverage value 3,87. Commercial peel-off gel mask
showed the same subset-class, with the preference
level 3,84. Peel-off gel mask formula F0 showed
preference value 3,78 on second subset-class. Peeloff gel mask formula F2 and F3 were on first sub-set
with preference value 3,02 and 2,64. These values
were significantly different with second subset-class,suspected it was due to the colour change, odour, andtexture [16].

Antibacterial activity test on peel-off gel mask ofethanol extract of bidara leaves showed results thatthe higher concentration the ethanol extract of bidara
leaves added into the peel-off gel mask, the larger the
inhibition activities against P. Acne performed.
Results were obtained from responses of substancesin diffusion holes, marked by the area clearness ordiameter of inhibition zone. The difference of extract
concentration added to each samples led to different
clear zones. The higher extract concentration ofbidara leaves added, the larger amount antibacterial
compounds contained. The larger amountantibacterial compounds obtained from bidara leaf
extract, the larger amount P. acne bacteria damaged,
either the structure or metabolic system. Researchfound bacteria interrupted by antibacterial
compounds were killed or inhibited. Findings showedthat formulation with the largest width of inhibitionzone was peel-off gel mask of bidara leaf extract,
formula F3 added with 35% extract, which showed
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 6. Activity and charateristic of peel-off gel
mask
Characteristic
PhysicalpH
Value
Dispersion(cm)
DryingTime(min)
Viscosity (cP)
Microbial
Pollution(coloni/gram)

Comm
ercialHomog
enous,
steriliz
ed

F0

F1

F2

F3

Homog
enous,
sterilized

Homogenous,
sterilized

Homogenous,
sterilized

Homogenous,
steriliz
ed

6,56

6,62

5,62

5,53

5,43

5,3

5,5

5,25

4,765

4,53

25

29

26

24

22,5

6020

8141

12039

13367

16653

N/A

N/A

N/A

N/A

N/A

CONCLUSION
Ethanol extract of bidara leaves was expected
to contain (i) rutin compounds, (ii) IC50 value 23,382
ppm, and (iii) antibacterial activity of P. acne against
ethanol extract of bidara leaves (Z. spina-christi L.)
at concentration ≥ 0,25 g/mL. Based on organoleptic
test, the best formulation of peel-off gel mask ofethanol extract of bidara leaves was formula F1 with
25% extract addition. The formulation, which showedantioxidant activity 38,638% and inhibition zone
against P. acne 7,65 mm, has fulfilled the quality
requirement of SNI 16-6070-1999 and SNI 16-43801996.

[4]

Putri RAZ. 2017. [Testing Anticancer Activityof Arabic Bidara Leaves in Colony Cells(WiDr) through MIT Method and Identification
Active Compounds using LC-MS Method][Skripsi]. Malang: Universitas Islam Negeri
Maulana Malik Ibrahim Malang.

[6]

Vieira RP, Fernandes AR, Kaneko TM,
Consiglieri VO, Pinto CASDO, Pereira
CSC,Velasco MVR. 2009. Physical andphysicochemical stability evaluation of
cosmetic formulations containing soybean
extract fermented by Bifidobacterium animalis.
Brazilian Journal of Pharmaceutical Sciences,3(45),
515–525.
doi.org/10.1590/S198482502009000300018.

[7]

Haeria, Hermawati, Dg. PineATU. 2016.
[Determination of Total Flavonoid Content andAntioxidant Activity and Ethanol Extract ofBidara Leaves]. Pharmascience, 1(2), 57–61.

[8] Ali AB, Almagboul AZ, Mohammed OM. 2015.
Antimicrobial Activity of Fruits, Leaves, Seeds
and Stems Extracts of Ziziphus spina-christi L.
Arabian Journal of Medicinal and Aromatic
Plants, 1(2), 94–107[9]

Ariani LW, Wigati D. 2009. [Formulation of
Peel-off Gel Mask of Ethanol Extract of Sweet
Orange Skin as Acne Cream]. Media Farmasi
Indonesia, 11(2), 1084–1092.

[10] Syarifah RS, MulyantiD, Gadri, A. 2015.
[Formulation of Peel-off Gel Mask of Papaya
Leaves as Antiacne and Efficacy Test against
Propionibacterium Acne]. Prosiding Penelitian
SPeSIA Unisba 2015, 1(1), 662–670.

REFERENCES[2]

Dragland
SM,
Senoo
H,
WakeK,
HolteK,Blomhoff R. 2003. Antioxidant activityof terpenoids. Journal Nutrition, 1(1), 133.

[5] Kusriani RH, Nawawi A, Machter E. 2015.
[Determination of Total Phenolic Content andAntioxidant Activity of Bidara Leaf, Fruit, and
Seed
Extract].
Prosiding
SNaPP2015
Kesehatan.

The panellists preferred white colour andfresh odour. However, moderate addition of extract informula F1 (25%) still could be accepted by thepanellists because the green colour was not very
thick; the odour was not too sour; and the thickness
texture was sufficient. Therefore, based onorganoleptic test, formula F1 was chosen as the bestformulation.

[1]

[3]

Thalbah, H. 2009. Ensiklopedia Mukjizat AlQur’an dan Hadist [Encyclopedia of Miracles
in Al-Qur’an and Hadith]. Jakarta: Perpustakan
Nasional.

[11] Aderogba MA, Ogundaini AO, Eloff JN. 2006.
Isolation of Two Flavonoids FromBauhinia
monandra(Kruz)
Leavesandtheir
Antioxidative Effects. Afr.J.Tradisional CAM,
3 (4): 59 - 65.

AsgarpanahJ,
Haghighat
E.
2012.
Phytochemistry and pharmacologic properties
of Ziziphus spina christi (L.) Willd. African
Journal of Pharmacy and Pharmacology,
6(31),
2332-2339.
doi.org/10.5897/
AJPP12.509.

[12] Burda S, Oleszek W. 2001. Antioxidant andAntiradical Activities of Flavonoids. Journal of160

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Agric Food Chemistry, 49(1), 2774-2779.
[13] Pelczar MJ, Chan ECS. 2006.Dasar-Dasar
Mikrobiologi 2 [Basic Principles ofMicrobiology 2]. Jakarta : UI Press

Cahyana M, EkaprasadaT,HerryA.2002.
[Isolation of Antioxidant Compounds of
Cinnamon Bark Skin]. Jurnal Indonesia, 3(1),50–58.

[16] NingsihW,
Nofiandi D, DeviarnyC,
RoselinDR. 2017. [Formulation andAntibacterial Effect of Peel-off Gel Mask of
Dewa Leaf Extract Against Staphylococcus
epidermidis] . Scientia, 7(1), 61–66.

[14] Santos, Alda E, KusterRM., YamamotoKA,
SallesTS, CamposR., Meneses, Marcelo DF,
SoaresMR, Ferreira D. 2014. Quercetin andQuercetin 3-O-glycosides from Bauhinia
longifolia (Bong.) Steud. Show Anti-mayora
Virus Activity. Parasites and Vectors, 7(1),130.doi: 10.1186/1756-3305-7-130.

161

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

A STUDY ON ELECTRICAL IMPEDANCE IN RIPENING AMBONBANANAS (MUSA PARADISIACA VAR. SAPIENTUM) PROCESSESSTIMULATED BY ETHREL (2-CHLOROETHYL PHOSPHONIC ACID)
Chomsin S Widodo1, Didik Rahadi Santosa1, Wahyu Sugianto1, Arinto Yudi P Wardoyo 1
1
Faculty of Mathematics and Natural Science, Brawijaya University, Malang, Indonesia

ABSTRACTThe use of ethrel (2-chloroethyl phosphonic acid) is faster fruit maturity. Excessive use of ethrel in the ripeningof bananas causes damage to the fruit and people who consume it. The principle of measurement based on electrical
impedance spectroscopy can detect changes that occur in biological material. This paper discusses the comparisonof the electrical impedance values of the ripeness of bananas, which marinated using various ethrel concentrations
and natural maturity. The electrical impedance measurement system uses four needle electrodes made of puresilver, which are supported by the use of the V to I module and signal generator from PICOSCOPE 5244B. The
system injects a current of one mA into the sample. The sample consisted of bananas through the ripening processusing three ethrel concentrations of 1000 ppm and 2000 ppm. Observation of changes in fruit and impedance
measurements in the range of 1 Hz to 1 MHz carried out every two days for nine days. The impedance value that
correlates with the maturity of the banana well observed in the frequency range between one to 100 kHz. Increasing
the impedance value describes the fruit maturity, which indicated by increasing the acidic until peak-phase andincreasing sugar content until the fruit rot. The maturation process using ethrel provides the effect of shifting thepeak impedance value. The higher the ethrel concentrations that used the electrical impedance value of the banana
will be higher.
Keywords: Electrical Impedance, Bananas, Ethrel,

food ingredients identify the concentration of salt
solutions [6, 15–18]. Until now, various forms andquantities of EIS electrodes have been developed [4,19].
The study aimed to apply EIS to Ambon banana
with a ripening process using various concentrationsof ethrel. Electrical parameters obtained frommeasurements clarified with maturity observed fromchanges in skin color

INTRODUCTION
Consumer attention to healthy food products isstill a concern until now, while food producers aretrying to find a profit that is as big as possible.
Processing products that are faster and cheaper is still
the choice of producers, although it has the potential
to harm consumers in terms of health. One of theprocesses used by traders is to speed up the ripeningof bananas using ethrel (2-chloroethyl phosphonicacid).
Some studies use ethrel in the process ofaccelerating fruit with observations based on
physiological changes in the fruit. The ethrel mango
ripening at a dose of 1000 ppm, gives a good taste andis still acceptable to the market [9], etrel spray effecton postharvest mango with a different concentrationof 600 ppm accelerates uniform maturation in 4 days[7], at maturation of Guava [5], maturity of wintertomato fruit harvested [10]. Physiological changes inbiological media (e.g., fruits) indicate a difference inthe properties of these materials. Changes in theproperties of compositions that affect the electricalproperties observed using a system of electrical
impedance spectroscopy (EIS).
The EIS-based study has been applied to various
fields, for example, observing changes inphysiological properties in fruits: apples, mango,
bananas, and avocado [1, 2, 8, 12, 13]. Also, the EIS
application used to detect additives, or additional

MATERIAL AND METHODS
Samples of Bananas Ambon
Ambon banana (Musa paradisiaca var.
Sapientum) obtained from the local market. The
selection of bananas based on its size and the banana
fruit washed thoroughly.
Banana fruit includes climacteric fruit, which has
a different sudden period where during this process, aseries of biological changes occur, beginning with theformation of ethylene [11], as shown in Fig. 1. The
ripening process starts with the occurrence of cell
metabolism that develops towards the beginning of
the ripening process (Climacteric Respiration
Minimum phase). At that time, acid formation
dominated the banana starch. After going through theminimum Climateric Respiration phase, thetransformation of starch into sugar occurs, thetransformation of tanin compounds which can
162

SEE - Bangkok, Thailand, Nov.11-13, 2019

dissolve into insoluble forms, a significant reductionin the amount of acid, softening of woody tissue andincreasing fluid levels.
The grouping of Ambon Banana used as a sample
based on the treatment group and labeled. The
treatment on bananas using ethrel carried out on day
0 for each concentration at room temperature, bydipping the banana into a container containing ethrelsolution for 30 seconds then remove it and stored
without cover for nine days. Physiologicalobservation of banana skin carried out on the first,
third, fifth, seventh, and ninth days.

Fig. 1tissues, does not contain any inductive components
but consists of the resistive and capacitive elements[2], as shown in Fig. 3.

Generalized patterns of growth andrespiration during development, maturation,and senescence of climacteric fruits.

Fig. 2

Systemof
Measurements

Electrical

Impedance

Fig. 3Equivalent circuit model based on cell tissue
according to the modified Hayden Model,
Cm is Capacitance of the membrane, Recf isthe resistance of apoplectic fluids, and Ricf isintracellular resistance [3, 14].

Analysis of the effect of frequency on impedance
by application Bode plot to determine the extent of
the impact of phase difference on real value andimaginary impedance to frequency. Effect of ethrel
treatment by applying the Nyquist curve, as shown in
Fig 4.

Electrical Impedance Measurements
The EIS system consists of four silver needle
electrodes with a diameter of 1 mm ((length of 10mm), two electrodes used to inject current (3.6 mm
apart) and two others used for measuring the output
voltage (8 mm distance). Picoscope type 5244B
supports the system as an AC voltage generator, andthe injection of 1 mA sinusoidal current in a banana
sample uses a V to I converter circuit, as shown in Fig
2.
Measurement of electrical impedance in thefrequency range of 1 Hz to 1 MHz using needle
electrodes by plugging all parts of the needle
electrode into the middle part of the banana.
Impedance measurements carried out in room
conditions (temperature, humidity, and atmosphericpressure). The data obtained is the value of the output
voltage. Calculation of the impedance value by
dividing the number of tops and bottom peakvoltages, and then the results divided by a current of
1 mA. Calculation of phase difference from input andoutput voltages by measuring the difference in peakvoltage displacement from input and output.
The research subject in the form of biologicalmaterial is usually analogous to an electrical circuit,which consists of resistors and conductors, and there
can be inductors depending on the content. The
electrical impedance of banana like any other plantFig. 4

Nyquist plot analysis for the modified
Hayden Model

RESULTS AND DISCUSSIONS
Ethrel Effect on Banana Skin Color
Ripening of bananas using ethrel affects the maturityof bananas. Observations on the physiologicalproperties of color, it appears that the yellow color of
the fruit skin shows the level of sophistication, thefaster it forms in the immersion of 2000-ppm ethrel,
as shown in Fig. 5. Control banana (natural ripening
process) in 9 days still shows greenish-colored skin,and different results occurred in bananas with aconcentration of 1000-ppm ethrel, which was yellow
on the fifth day, while an ethrel concentration of 2000
ppm caused a more yellow color to occur on the third
day.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

The characteristic of the maturity of a banana isthat the skin color of the fruit changes from green toturn yellow with the increasing formation of ethylenegas. During the ripening process of bananas, there isan increase in sugar levels and a decrease in flourcontent or softening of banana meat. This condition
causes by an insoluble remodeling of the protopectinto become soluble. These substances are derivativesof Polygalacturonic acid and are present in the formof protopectin, pectin, pectinic acid, and pectic acid.

When the fruit ripens, the soluble pectate andpectinate content increases, while the total amount ofpectate decreases. In the change in pectin, the fruit's
toughness decreases, so the fruit becomes soft.
Hydrolysis Amylum is perfect by acids or specificenzymes on polysaccharides producing monosaccharides or their derivative compounds, and there
is a slight increase in sucrose, glucose, and fructose
during maturation.

Fig. 5

Display of banana color for all days at various ethrel concentrations.

Fig. 6

Plot Graph of electrical impedance measurements at a frequency of 100 Hz in various concentrations, theresults compared with climacteric fruit charts.

The results showed a similar pattern, where theimpedance value suddenly decreased with increasing
time, as shown in Fig. 6. The maturation process inthe control sample until the ninth day passes throughthe minimum climacteric maturation phase and willlead to the formation of sugar. The measurement
results show a decreasing impedance value until theminimum climacteric respiration phase.
The formation of sugar in the ripening process
will increase the impedance value of the banana [18].
The 1,000 ppm ethrel concentration shifted the timeof sugar formation compared to the control, where on
the third day, the maximum maturity level occurred,
and this also happened at a concentration of 2000
ppm. After the peak phase, the process will enter thehydrolysis phase, where this phase will reduce theimpedance value. The interesting thing happens isthat at a concentration of 2000 ppm there is a sharper
decline compared to 1000 ppm, the hydrolysis
process occurs more so that the banana decomposes
more quickly.
Fig. 7 shows the Bode plots for all treatment,
where at low frequencies (up to 100 Hz), all graphs
show a relatively constant phase angle, and theimpedance value shows a linear relationship.
Dispersion occurs at a frequency of 1000 Hz andabove. At that time, the impedance value more
influenced by the presence of resistive and capacitive
properties of the material. Plotting Nyquist curves
show apparent differences between treatments for all
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SEE - Bangkok, Thailand, Nov.11-13, 2019

days. Suitability between extractions results for eachelement obtained with the model used is very high, asshown in Fig. 8. The measurement on the first day

proved a shift in the imaginary-value and real valueof electrical impedance as the concentration of ethrel
increased and at 2000 ppm shifted further.

Fig. 7

An analysis of Bode-plots results for real and imaginary of impedance values in all treatments.

Fig. 8The results of the Nyquist plot analysis for all treatments.
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Table 1 The simulation results using EIS Spectrum
Analyzer Freeware [20] for the equivalentcircuit in Fig. 3, with the fitting of the
Nyquist plot results in Fig. 8.
Day

Element

Control

1000

2000

1

Ricf ()Error (%)

1

C (nF)
Error (%)

1

Recf ()Error (%)

50.57
18.20
3.22
3.58
2986.90
2.30

50.93
16.63
3.07
3.58
2914.00
1.52

50.64
21.70
2.11
11.00
3307.60
1.24

3

Ricf ()Error (%)

50.19

50.21

50.55

3

C (nF)
Error (%)

3

Recf ()Error (%)

6.78
3.30
3.01
2756.50
2.13

10.19
3.72
3.43
2015.40
3.30

5.33
3.33
16.06
2470.30
1.94

5

Ricf ()Error (%)

5

C (nF)
Error (%)

50.77
10.06
3.72

50.77
7.18
3.72

50.21
6.86
3.69

3.84
2323.60
10.99

19.04
2323.60
2.80

9.48
3078.20
3.07

50.02
7.98
3.79
14.77

50.09
7.23
3.86
5.81

5

Recf ()Error (%)

7

Ricf ()Error (%)

7

C (nF)
Error (%)

50.68
7.09
3.83
9.80

7

Recf ()Error (%)

1367.00
3.52

1802.00
2.29

1289.30
3.52

9

Ricf ()Error (%)

9

C (nF)
Error (%)

50.69
8.51
3.84
18.96

50.76
14.96
3.73
6.01

50.76
14.96
3.73
6.01

9

Recf ()Error (%)

1353.80

1624.50

1624.50

2.46

1.48

1.48

Fig. 9The value of Recf obtained by the Nyquist
curve at various concentrations from Table
1.

The value of C is relatively constant at around 3.5
nF, and similar results obtained for the Ricf, which isapproximately 50.5 Ohm. On the other hand, Recf
results of the curve tend to follow the maturation levelof bananas, as shown in Fig 9. The extraction results
for all elements in all treatments turned out to be
similar to the curves of the measured electrical
impedance values, as shown in Fig, 6. Changes in thecomposition of ingredients in the ripening process ofbananas, for example, sugar content, acid content,
salt, amount of liquid due to hydrolysis affect theresistivity level of the material.
CONCLUSIONS
Ethrel stimulation accelerates the ripening processof Ambon banana fruit. On the fifth day, bananas with
ethrel have reached the maximum climatic respiration
phase, while natural fruit ripening is still in theminimum climacteric respiration phase. Impendence
spectroscopic system can detect banana ripening
process, where on a fifth day of maturation due to2000 ppm ethrel has a maximum impedance value of3101.83  higher than 1000 ppm with an impedancevalue of 2297.67 . The electrical impedance value
during the ripening process of bananas is more
influenced by the nature of extra cell fluid resistancedue to the formation of sugar solution which has
resistive properties, with resistance values at thematurity peak of 3078.60  and 2323.6  for 2000
ppm and 1000 ppm respectively.

On the third day, a noticeable change occurred inbananas with an ethrel concentration of 2000 ppm,
where there was a shift in the real and imaginary
values of electrical impedances. Whereas, the result
for a 1000 ppm shifts only its imaginary-value. As
shown in Table 1, the error is around 7.5% for all
elements in all treatments, where the lowest error is
1.24%, and the biggest is 21.70%.

ACKNOWLEDGMENTS
This research funded by the PTUPT-Grant 2019 from
Directorate of Research and Community Service,
Directorate General for Research and Development at
the Ministry of Research Indonesia, Technology andHigher Education with contract number 332.
45/UN10.C10/PN/2019.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

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and the ubiquity of ethylene—An overview, J.
Food Sci. Technol., Vol. 49, 2012, pp. 1–21.
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Pear Tissues, Food Bioprocess Technol., Vol. 11,
2018, pp. 2125–2129.
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Electrical Impedance Measurement of Solution
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[1] Chowdhury A., Datta S., Bera T.K., Ghoshal D.,
and Chakraborty B., Design and development of
microcontroller based instrumentation forstudying complex bioelectrical impedance offruits using electrical impedance spectroscopy, J.
Food Process Eng., Vol. 41, 2018, pp. e12640.
[2] Chowdhury A., Kanti Bera T., Ghoshal D., andChakraborty B., Electrical Impedance Variations
in Banana Ripening: An Analytical Study with
Electrical Impedance Spectroscopy, J. Food
Process Eng., Vol. 40, 2017, pp. e12387.
[3] Chowdhury A., Singh P., Bera T.K., Ghoshal D.,
and Chakraborty B., Electrical impedance
spectroscopic study of mandarin orange during
ripening, J. Food Meas. Charact., Vol. 11, 2017,
pp. 1654–1664.
[4] Chung J., Chen Y., and Kim S.-J., High-density
impedance-sensing array on complementary
metal-oxide-semiconductor circuitry assisted bynegative dielectrophoresis for single-cellresolution measurement, Sensors Actuators B
Chem., Vol. 266, 2018, pp. 106–114.
[5] Elkashif M.E., Hamdoun E.A., Elamin O.M., andMahmoud H.I., Effects of Ethrel, packaging andwaxing on quality and shelf life of guava(Psidium guajava L.) fruits, Gezira J. Agric. Sci.,
Vol. 14, 2016.
[6] Gowry B., Shahriman A.B., and Paulraj M.,
Electrical bio-impedance as a promisingprognostic alternative in detecting breast cancer:
A review, IEEE, 2015, pp. 1–6 с.
[7] Gurjar P.S., Verma A.K., Dikshit A., and Shukla
D.K., Effect of ethrel spray on the ripening
behaviour of mango (Mangifera indica L.) variety'Dashehari', J. Appl. Nat. Sci., Vol. 9, 2017, pp.
1619–1623.
[8] Islam M., Wahid K., and Dinh A., Assessment of
Ripening Degree of Avocado by Electrical
Impedance Spectroscopy and Support Vector
Machine, J. Food Qual., Vol. 2018, 2018, pp. 1–9.
[9] Kaur S., Effect of different treatments of ethrel on
ripening behaviour and post- harvest quality ofmango (Mangiferaindica L.) during storage, J.
Appl. Nat. Sci., Vol. 9, 2017, pp. 85–93.
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on ripening and quality of winter tomato fruit167

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DNA EXTRACTION METHODS FOR FIN OF MACKERELSIN THAILAND*Walaiporn Makkapan, Patcharaporn Narkthewan and Kaewalee Viboonkit
King Mongkut’s Institute of Technology Ladkrabang Prince of Chumphon Campus,
Pathiu, Chumphon, Thailand

ABSTRACTThe quality and quantity of DNA are crucial aspects for fish studies based on the molecular techniques.
Extraction method of genomic DNA is depended on tissue types and organism species. This research aimed to
identify an appropriate extraction method for gDNA from fin of three popular mackerel species in Thailand;
short-bodied mackerel (Rastrelliger brachysoma), island mackerel (R. faughni) and Indian mackerel(R. kanagurta). Four different methods for gDNA extraction were compared based on time, quality and quantityof extractable gDNA for PCR technique. Method III showed the highest quantity of gDNA in R. brachysoma andR. kanagurta. Nevertheless, the highest purity of gDNA for both species was obtained by method II and IV,
respectively. The gDNA from method IV was successful to amplify the intense band of β-actin fragment. The
highest concentration and purity of gDNA from R. faughni were received using method II. However, β-actin
gene fragment amplified from gDNA of method IV showed intense bands. These results indicated thatmethod IV was suitable for gDNA extraction from fin of three mackerel species because of fastest, high quality
and quantity for PCR amplification.
Keywords: DNA extraction, Fin, Mackerel, Fish

Thailand.
Caudal fin was
isolated andsubjected for gDNA extraction using four different
methods composed of method I-V.
Method I was modified from urea treatment
method [6]. Fin tissue (20 mg) was mixed with
300 µl of extraction buffer (10 mM Tris-HCl pH 8.0,
10 mM EDTA, 0.5% SDS, 4 M Urea) with 5 µlof RNase (10 mg/ml). The mixture washomogenized and incubated at 42°C with shaking
at 200 rpm. After incubation for 1 h, the mixture
was gently mixed with 10 µl of Proteinase K(10 mg/ml) and then incubated at 42°C with shaking
at 200 rpm for 16-18 h. Equal volume ofphenol:chloroform:isoamyl alcohol (25:24:1) was
then added into the mixture and inverted for several
times. The mixture was centrifuged at 11,000 rpm
for 15 min. The upper phase was collected to the
new tube, and mixed with 1 M NaCl and equalvolume of absolute ethanol. The mixture wascentrifuge at 11,000 rpm for 15 min. The
supernatant was discarded. The 70% ethanol wasadded to DNA pellet and then centrifuged at 11,000rpm for 5 min. The DNA pellet was air-dried andre-suspended in sterile water.
Method II was modified from report of [1].
Fin tissue (20 mg) was homogenized in 300 µlof extraction buffer (50 mM Tris-HCl pH 8.0,
100 mM NaCl, 50 mM EDTA, 1% SDS) with
7.5 µl of Proteinase K (10 mg/ml). The mixture
was incubated in the shaking incubatorat 55°C for 16-18 h with oscillation of

INTRODUCTION
Extraction of genomic DNA is an important
step of fish studies based on the moleculartechniques. Several reports related DNA extraction
from various fish suggested quality and quantityof extracted gDNA were depended on fish species,
tissues types and extraction methods [1]-[5].
Nowadays, attempt to extract gDNA from fishtissue without or less invasive sampling method
was investigated in many fish. Several reports
demonstrated the different protocols of DNA
extraction from the external organs of fish, such as
fins [1], [5], and scales [3]. There is little
information related molecular studies in three
popular mackerel species in Thailand, including
R. brachysoma, R. faughni and R. kanagurta.
Therefore, the objective of this study was to identify
an appropriate method for gDNA extraction from finof three mackerel species for PCR-based techniques.
The result data will be as a beneficial knowledge
for further mackerel research such as genomic
analysis, biomarker study and genetic species
identification, etc.
MATERIALS AND METHODSFish Sample and Extraction Methods
R. brachysoma, R. faughni and R. kanagurta
were obtained from port in Chumphon Province,
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SEE - Bangkok, Thailand, Nov.11-13, 2019

200 rpm. Subsequently, 300 µl of 5 M NaCl was
mixed with the mixture and centrifuged at
11,000 rpm for 10 min. The supernatant wascollected and inversely mixed with equalvolume of phenol:chloroform:isoamyl alcohol(25:24:1). The mixture was then centrifuged at
11,000 rpm for 10 min. The upper phase wascollected and mixed with equal volume of absoluteethanol for DNA precipitation. The mixture wascentrifuge at 11,000 rpm for 15 min. The
supernatant was discarded. The 70% ethanol wasadded to DNA pellet and then centrifuged at
11,000 rpm for 5 min. The DNA pellet was
air-dried and re-suspended in sterile water.
Method III was followed by Rapid MT method[4]. The fish fin (20 mg) was homogenizedin 660 µl of extraction buffer (100 mM Tris-HCl
pH 8.0, 5 mM EDTA, 0.2% SDS, 200 mM NaCl)and then 1 µl of Proteinase K (10 mg/ml) was
added. The mixture was incubated in the shaking
incubator at 55°C for 24 h with oscillationof 200 rpm. After incubation, the sample wascentrifuged at 12,000xg for 15 min. The supernatant
was taken in the new tube and inversely mixed
with equal volume of phenol:chloroform:isoamyl
alcohol (25:24:1). After centrifugation at 12,000xg
for 10 min, the upper phase was collected andmixed with equal volume of isopropanol, andthen centrifuged at 12,000xg for 10 min. The
supernatant was decanted and the DNA pellet
was washed with 70% ethanol. The DNA pellet was
air-dried and re-suspended in sterile water.
Method IV was modified from report of [5],[7]. Fin sample (20 mg) was homogenized in 400 µlof extraction buffer (200 mM Tris-HCl pH 8.0,
100 mM EDTA, 250 mM NaCl, 1.2% SDS,
200 µg/ml Proteinase K) and incubated in
the shaking incubator at 48°C for 3 h. Equal volumeof phenol:chloroform:isoamyl alcohol (25:24:1)
was added into the mixture and mix byinversion for several time. After centrifugation at
11,000 rpm for 15 min, the upper layer
was taken into new tube. Equal volume ofisopropanol and 0.2 volume of 10 M ammonium
acetate was added and mixed. The sample wascentrifuged at 11,000 rpm for 15 min. The
supernatant was removed and the DNA pellet waswashedin 70%
ethanol,
air-driedandre-suspended in sterile water.

spectrophotometer with absorbance of 260 and
260/280 nm, respectively. The data was presented asa mean ± standard deviation (mean±SD; n=5).
The statistical significance was examined using the
One-Way Analysis of Variance followed bya Tukey's HSD test at a significance level of ≤ 0.05.
Polymerase Chain Reaction
The quality of gDNA was further confirmed byamplification in conserved region of β-actin gene,consisting of 1244 bp, using specific primers:
Forward 5’ ATGAAATCGCCGCACTGG 3’ andReverse 5’ TGGATGGCAACGTACATGGC 3’.
PCR reaction was performed in total volume of
50 µl mixture consisting of 100 ng of gDNA,
1X Standard Taq Reaction buffer, 1 mM MgCl2,
0.2 mM dNTPs mixture, 0.4 µM of forward andreverse specific primers, and 1.25 U Taq DNA
polymerase. Amplification conditions were 95°C for
3 min followed by 30 cycles at 95°C for 30 s, 53°C
for 30 s, 72°C for 30 s and then subjected to a final
extension of 72°C for 3 min. The amplified products
were analyzed through 1.5% agarose gel stainedwith SYBR Safe DNA Gel Stain.

RESULTS AND DISCUSSION
This study identified the appropriate extraction
method for gDNA from fin tissue of three popularspecies mackerels in Thailand based on extraction
time, quality and quantity of gDNA. The gDNA
extraction method should be rapid and efficient forachieving the high quantity and quality of gDNA[8], [9]. The fin gDNA was extracted from four
different methods: method I-IV. For the extraction
time, the method I-III needed more than 20 h forwhole process, whilst the time requirement formethod IV was not more than 6 h. Extraction bufferof all methods was generally used SDS andproteinase K as a detergent for tissue digestion
process, which was varied the concentration of
those. Moreover, urea and RNase were added into
extraction buffer of method I for protein and RNA
denaturation [5], [6], respectively. The extraction
buffer of method II-IV was additionally mixed
with NaCl used for extracting protein [4].
The temperature in tissue lysis step in all
methods was carried out at 42-55°C. Subsequently,
phenol: chloroform: isoamyl alcohol was required toremove the proteins and DNA was precipitated byeither absolute ethanol or isopropanol. Interestingly,
DNA precipitation step of all did not take additionaltimes.
The quantity and quality of gDNA fromfin of Rastrelliger sp. obtained from different
four methods was summarized in Table 1.

Quality and Quantity of gDNA Analysis
The quality and quantity of gDNA from eachmethod were determined by agarose gelelectrophoresis and spectrophotometer. The DNA
sample was visualized in 1% agarose gel stainedwith SYBR Safe DNA Gel Stain. The concentrationand purity were evaluated using UV/visible

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Table 1 Quantity and quality of extracted DNA from different extraction methods
R. brachysoma
Extraction
MethodR. faughni

R. kanagurta

Concentration(µg/µl)Purity(A260/A280)

Concentration(µg/µl)Purity(A260/A280)

Concentration(µg/µl)Purity(A260/A280)

Method I

0.45±0.18a

1.48±0.03a

0.62±0.08a

1.49±0.07a

0.49±0.03a

1.67±0.08a

Method II

0.64±0.12a,b1.61±0.07b

1.10±0.07b

1.77±0.05b

0.70±0.08b

1.75±0.06a,b

Method III

0.98±0.10c

1.54±0.02a,b

0.94±0.12b

1.66±0.09b

0.84±0.07c

1.70±0.02a

Method IV

0.74±0.10b

1.59±0.03b

1.05±0.14b

1.74±0.08b

0.70±0.07b

1.83±0.04b

Note: Concentration and purity were represented as mean±SD (n=5). The different letters indicated the significant
difference between extraction methods within same species. The significant difference was analyzed by Tukey's
HSD at P<0.05.
The extractable gDNA concentration from different
methods varied in each species. The concentrationof gDNA from R. brachysoma was shown
in range of 0.45-0.98 µg/µl. The highest
concentration of gDNA from R. brachysoma
was found from method III (0.98±0.10 µg/µl),followed by method IV (0.74±0.10 µg/µl), method II(0.64±0.12 µg/µl), and method I (0.45±0.18 µg/µl),
respectively. The concentration of gDNA of
R. faughni was obtained in range of 0.62-1.10µg/µl. The gDNA of R. faughni was shown
the highest concentration obtained from method II(1.10±0.07 µg/µl). This was followed by method IV(1.05±0.14 µg/µl), method III (0.94±0.12 µg/µl),
and method I (0.62±0.08 µg/µl), respectively.
The concentration of gDNA of R. kanagurta
was extractable in range 0.49-0.84 µg/µl.
The highest concentration of gDNA from
R. kanagurta was found in method III (0.84±0.07µg/µl), followed by method IV (0.70±0.07 µg/µl)
and method II (0.70±0.08 µg/µl). The lowest
concentration of extracted gDNA was observed
from method I (0.49±0.03 µg/µl). This study
found the significantly lower values wereattained from method I supplemented with urea
in extraction buffer, suggesting this method did notsuitable for DNA extraction from fin of threemackerel species.
The quality of the gDNA was indicated by
A260/A280 ratio. The purity of extracted DNA isgenerally accepted a yield of A260/A280 ratio in
range of 1.8-2.0 [10]. The gDNA of R. brachysoma
from all extraction methods expressed a low purity,
which had a value in range of 1.48-1.61. The highest
purity in this species was exhibited in the extracted
DNA obtained by method II (1.61±0.07). This wasfollowed by the gDNA attained from method IV(1.59±0.03), method III (1.54±0.02), and method I(1.48±0.03), respectively. The gDNA of R. faughni
showed the purity values in range of 1.49-1.77. The

gDNA obtained from method II showed the highest
purity for R. faughni (1.77±0.05), following
by method IV (1.74±0.08), method III (1.66±0.09),
and method I (1.49±0.07), repectively. Meanwhile,
the gDNA of R. kanagurta showed the purity
values in range of 1.67-1.83. The highest purity
in this species was shown in the extracted
DNA obtained by method IV (1.83±0.04), following
by method II (1.75±0.06), method III (1.70±0.02),
and method I (1.67±0.08), respectively. These
results suggested the method II produced
the highest quality of gDNA for R. brachysoma
and R. faughni compared to other methods.
The method IV was able to extract the highest
quality of gDNA for R. kanagurta. Corresponding
with quantity result, the quality of gDNA
extracted from method I was lowest for all
species. Report of [1] revealed the purity of
fin DNA extracted from modified salt method
showed in range of 1.83-2.19. These results ofshowed the similar results of reports from [4], [5]demonstrated the purity of fish DNA was in rangeof 1.6-2.0.
Subsequently, the quality of gDNA wasconsidered by using as a template for PCR
amplification of β-actin gene fragment. The
amplified products of β-actin gene analyzed
by 1.5% agarose gel electrophoresis were shownin Fig. 1. The PCR products in R. brachysoma as
well as R. kanagurta were achieved from gDNA
obtained from all methods. The intense band of PCR
products was represented from the gDNA obtained
from method I and IV. Whereas, some of
gDNA obtained from method II and III showed
the light band of the amplified PCR fragment.
The PCR amplification in R. faughni was attained byusing gDNA extracted from all mehods. The PCR
products of gDNA from method IV showed
the intense band. The gDNA from method I, II and
III were amplified the PCR products with light band.
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Fig. 1 β-Actin fragments amplified from gDNA extracted from fin of a) R. brachysoma, b) R. faughni, andc) R. kanagurta by using different methods (method I-IV). M = 100 bp DNA ladder marker and
N = negative control.

[3] Li Y., Gul Y., Cui L., Cao X., and Wang, W.,
Comparative Analysis of Different Protocol
for Extraction of DNA from Fish Scalesof Cyprinus carpio. Indian Journal of
Biotechnology, Vol. 14, Issue 3, 2015, pp. 382387.
[4] Chowdhury M. M., Rahman A. S. M. S., Nahar
L., Rahman M., Reza H. A., and Ahmed Md. S.,
Efficiency of Different DNA Extraction
Methods for Fish Tissues: A Comparative
Analysis. IOSR Journal of Pharmacy andBiological Sciences, Vol. 11, Issue 3, 2016,
pp. 11-15.
[5] Muhammad H., Iqbal Z., Iqbal M. U., Younas
T., and Bashir Q., An Efficient Method for
DNA Isolation from Fish Fin. Pakistan Journalof Agricultural Sciences, Vol. 53, Issue 4, 2016,
pp. 843-850.
[6] Wasko A. P., Martins C., Oliveira C., andForesti F., Non-destructive Genetic Samplingin Fish. An Improved Method for DNA
Extraction from Fish Fins and Scales.
Hereditas, Vol. 138, Issue 3, 2003, pp.161-165.
[7] Kumar R., Singh P. J., Nagpure N. S.,
Kushwaha B., Srivastava S. K., and Lakra,
W. S., A Non-invasive Technique for Rapid
Extraction of DNA from Fish Scales. Indian
Journal of Experimental Biology, Vol. 45,
Issue 11, 2007, pp. 992-997.
[8] Sika K. C., Kefela T., Adoukonou-Sagbadja
H., Ahoton L., Saidou A., Baba-Moussa
L., Baptiste L. J., Kotconi S. O., andCONCLUSIONSThe quality and quantity of gDNA from fin
varied according to fish species and extraction
methods. The method IV was the appropriate
method for DNA extraction from fin of threemackerel species in Thailand. It indicated that theadvantage of method IV was rapid, good quantityand quality of gDNA for PCR amplification.
ACKNOWLEDGMENTS
This work was financially supported by National
Research Council of Thailand. The facilities
were supported by King Mongkut’s Institute ofTechnology Ladkrabang Prince of Chumphon
Campus, Thailand.
REFERENCES[1] Lopera-Barrero N. M., Povh J. A., Ribeiro R. P.,
Gomes P. C., Jacometo C. B., and Lopes, T. S.,
Comparison of DNA Extraction Protocolsof Fish Fin and Larvae Samples: Modified
Salt (NaCl) Extraction. Ciencia e Investigación
Agraria, Vol. 35, Issue 1, 2008, pp.65-74.
[2] Mukhopadhyay T., and Bhattacharjee, S.,
Standardization of Genomic DNA Isolationfrom Minute Quantities of Fish Scales and Fins
Amenable to RAPD-PCR. Proceedings of the
Zoological Society, Vol. 67, Issue 1, 2014,
pp.28-32.
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Gachomo E. W., A Simple and Efficient
Genomic DNA Extraction Protocol for Large
Scale Genetic Analyses of Plant Biological
Systems. Plant Gene, Vol. 1, 2015, pp. 43-45.
[9] Shafi N., Rauf A., Akhtar T., Minhas R. A.,
Ulfat, and Bibi S., Comparative Isolation and
Amplification of Cytochrome oxidase 1 DNA
from Oncorhynchus mykiss (Rainbow Trout)of Azad Jammu & Kashmir. International
Journal of Fisheries and Aquatic Studies, Vol. 4,
Issue 6, 2016, pp. 196-199.
[10] Boesenberg-Smith K. A., Pessarakli M. M.,
and Wolk D. M., Assessment of DNA Yield
and Purity: an Overlooked Detail of
PCR Troubleshooting. Clinical Microbiology
Newsletter, Vol. 34, Issue 1, 2012, pp. 1, 3-6.

172

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ANGIOTENSION CONVERTING ENZYME (ACE) INHIBITORYACTIVITY OF PROTEIN EXTRACT OF MUNG BEANS(Vigna radiata L.) TEMPEH FERMENTED BY Rhizopus sp.

1,2,3

Sri Yadial Chalid1, Siti Nurbayti2, Zelda Zein Zunaedi3
Chemistry dept. Faculty of Science and Technology, Islamic State University Syarif Hidayatullah,
Jakarta, Indonesia

ABSTRACTOne of the roles of Angiotensin Converting Enzyme (ACE) is as a narrowing factor of blood vessels bychanging angiotensin I to angiotensin II. Prevention of narrowing of arteries can be done by inhibiting ACE work.
ACE inhibitorys are derived from synthetic drugs, proteins and active ingredients in food ingredients. Protein-richfermented foods and bioactive peptides can be used to inhibit ACE and protein tempeh is one of the foods that caninhibit ACE. Mung beans (Vigna radiata L.) were fermented with Rhizopus sp to produce tempeh. The amount of
Rhizopus sp used was 0.2 and 0.4% (w/w) with various time variations of 6 hours interval, namely 0, 6, 12, 18, 24,
30, 36 and 42 hours. The physical properties of tempeh were analyzed including the growth of mycelium, color
and aroma according to the Indonesian National Standard (SNI). Protein tempeh was extracted by the precipitation
method at the isoelectric point, the dissolved protein was measured, and the ability of the protease to hydrolyze
the protein into peptide was determined by the degree of hydrolysis (DH). The activity of tempeh protein extract
in ACE inhibitory was measured based on the amount of hypuric acid produced in the reaction between hippurylhisdidyl-leucine (HHL) and ACE enzyme. The best ACE inhibitory activity was obtained by mung beans tempeh
fermented for 24 hours with a yeast amount of 0.4% and dissolved protein content of 351 mg/mL. The results of
the SDS-PAGE analysis showed the presence of proteins with molecular weights of 12, 54, 98 and 125 kDa. The
degree of hydrolysis produced was 18.68% and ACE inhibitory activity was 75%. Therefore, mung beans tempeh
has the potential to be developed to be functional antihypertensive foods.
Keywords: Protein extract, Mung beans tempeh, Functional food, Antihypertensive

hypertension therapy should be done to avoid the side
effects mentioned above.
Some components of food have antihypertensivefunctional properties such as fermented foods.
Tempeh is one of the fermented foods that is widely
developed in Indonesia. Consumption of food orfunctional foods as ACE inhibitorys stimulates thesecretion of bradykinin hormones which vasodilate
blood vessels thereby reducing blood pressure [8].
Consumption of soybeans tempeh can reduce bloodpressure in humans [9].
The objective of the study was to produce mungbeans tempeh as a new breakthrough in functional
antihypertensive foods. Mung beans was fermented
using Rhizopus sp [10], the protein was extracted at
isoelectric point [11], dissolved protein content [12],hydrolysis degree [13], protein characteristics using
sodium dodecyl sulfate polyacrylamide gelelectrophoresis (SDS-PAGE) [14] were measured,and angiotensin converting enzyme (ACE) inhibitory
activity was tested based on the amount of release of
hipuric acid from substrathippuryl-L-histidyl-Lleucine [15, [16].

INTRODUCTION
Angiotensin-converting enzyme (ACE) is zincmetallopeptidase which plays a role in changes inangiotensin I to angiotensin II. Angiotensin II is an
octapeptide capable of stimulating aldosterone
secretion resulting in retention of extracellularsodium and stimulating the secretion of Anti-Deuretic
Hormone (ADH) which plays a role in decreasing theamount of urine excreted from the body. Thiscondition causes blood to become thick [1], [2].
Formation of angiotensin II is one of the mechanismsof the cause of hypertension [3]. Some treatments thatcan be done as therapy and prevention of
hypertension are medical treatment, regulating
lifestyle, losing weight, consuming foods rich inpotassium and calcium, low sodium, rich in fiber, andfruits, doing physical activities, and not consuming
alcohol. This balanced lifestyle is according to DASH
(diet dietary approaches to stop hypertension) [4].
Medical drugs classified as ACE inhibitorys
include katopril, enalapril, and lisinopril [5], yet thesesynthetic drugs have side effects such as nausea,
headache, diarrhea, dry cough, no appetite and kidney
problems [6] and allergy [7]. Thus, non-medical

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SEE - Bangkok, Thailand, Nov.11-13, 2019precipitated nitrogen was analyzed using the Kjeldahl
method [13] and the degree of hydrolysis wascalculated using the formula:

METHOD
Preparation of Mung beans Tempeh

DH (%) = 𝐃𝐢𝐬𝐬𝐨𝐥𝐯𝐞𝐝 𝐧𝐢𝐭𝐫𝐨𝐠𝐞𝐧 𝐢𝐧 𝟏𝟎% 𝐓𝐂𝐀
Total nitrogen of sample

A total of 400 g of mung beans were peeled andsoaked for 2 hours with an acid solution (pH 4) byadding vinegar, then steamed for ±8 minutes, drained
and cooled. Dried mung beans were inoculated with
Rhizopus sp. inoculum with a concentration of 0.2%(w/w) and stirred evenly. The amount of yeast of
0.2% (w/w) used is based on the amount of yeast to
ferment soybeans. A total of 50 grams of mung beans
were put into clean propylene plastic bags measuring
5 cm in width and 10 cm in length. These plastic bags
had been given several small holes first.
Mung beans fermentation was carried out at room
tempehrature with a 6 hour interval of 0, 6, 12, 18, 24,
30, 36, and 42 hours. Every 6 hours, fermentation was
stopped and an organoleptic test was carried out
including physical properties, mycelium growth,aroma, color, texture and growth of mycelium [10].

Characterization of Protein Profiles of Mungbeans Tempeh using SDS-PAGE Analysis
The profile of protein extract of mung beans
tempeh was analyzed by electrophoresis using
acrylamide gel. The gel consists of two parts, namely
stacking gel and separating gel. The acrylamide
concentration on stacking gel was 5% and separating
gel was 12%. The injected sample volume was 40 μL
and the marker was 5μL as a standard, namely thePrecision Plus Protein TM Dual Color Standard
marker. Running was carried out at a constant voltageof 90 volts for 150 minutes. The gel was stained withcoomasie brilliant blue G-250 and color removal was
carried out by destaining solution [14]. The protein
molecular weight was analyzed using the Gel
Analyzer 2010a software.

Protein Extraction of Mung Beans Tempeh
A total of 50 gram mung beans tempeh was
mashed using a blender with the addition of distilledwater (1:10 w/v). The suspension was added with 1M
NaOH until it reached pH 9.8 while stirring using astirrer for 1 hour. The suspension was centrifuged at
6,000 x g for 20 minutes at 4°C. Supernatant wasadded with 1M HCl solution gradually while stirring
until it reached pH 4.5 (isoelectric point). The
solution was centrifuged again at 6,000x g for 20
minutes at 4°C. The resulting deposits are called
tempeh protein extracts and were stored in a freezer
with a tempehrature of -20°C or preservated by freeze
drying [11].

Analysis of Angiotensin Converting Enzyme
Inhibitory Activity
Enzyme activity was determined using Hip-HisLeu (HHL) synthetic peptide as a substrate based on
the method developed [15], [16]. A total of 15 µl of aprotein extract solution was added with 125 µL of a
100 mM sodium borate solution (pH 8.3) containing
7.6 mM Hip-His-Leu and 608 mM NaCl, and waspreincubated for 5 minutes at 37°C. The reaction
begins with the addition of 50 µL ACE enzyme which
are dissolved in distilled water. The mixture wasincubated for 30 minutes at 37oC. A total of 50 µL of
aquades were used as blanks.
The reaction was stopped with the addition of 125µL HCl 1N. The hypuric acid released by ACE wasextracted by adding 750 µL of ethyl acetate to the
mixture and shaken using the vortex immediately.
The mixture was centrifuged at 13,760 x g for 10
minutes, 500 µL of the top layer of the supernatant
was collected and dried at 90oC for 30 minutes. Thenhypuric acid was dissolved in 1 mL distilled waterand the absorbance was measured by aspectrophotometer at a wavelength of 228 nm.

Dissolved Protein Content Analysis
A total of 0.1 gram of tempeh protein extract fromeach time of fermentation was homogenized with 2
mL of distilled water while rotating with vortex. The
protein extract suspension was centrifuged at a speedof 12,000 x g at a tempehrature of 4°C for 20 minutes.
Supernatant protein content was determined by
Bradford [12] and bovine serum albumine (BSA)
methods as standard.

% ACE Inhibitory Activity = [(C-A)/ (C-B)] x 100%
Degree of Hydrolysis Analysis (DH)

Where A is absorbance of the sample, B isabsorbance of the blank and C is absorbance of thecontrol (sample replaced with aquades).

A total of 2 mg of tempeh extract of mung beans
were added with a 20% TCA solution (b/v) of 2 mL
while stirring to obtain a dissolved and non-soluble
fraction in 10% (w/v) TCA. The mixture was left tostand for 30 minutes to precipitate, then centrifuged
at a speed of 7,800 x g with a tempehrature of 4°C for
15 minutes. The nitrogen content of supernatant and

RESULTS AND DISCUSSION
Characteristics of Mung Beans Tempeh

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Mung beans were fermented at intervals of 6hours namely 0, 6, 12, 18, 24, 30, 36 and 42 hours
with yeast concentrations of 0.2% (w/w). The
fermentation time was determined by observing thephysical properties of tempeh including the texture,aroma and growth of mycelium in accordance withIndonesian National standards. The best fermentation
time for mung beans with a yeast concentration of
0.2% (w/w) was 24 hours, where the characteristics
of tempeh are in accordance with the Indonesian
National Standard (Fig. 1).
The growth of fungi was evenly distributed on thesurface of tempeh, sporulation has not occurred or
black spores on the surface of tempeh have not yet
appeared. The texture of mung beans tempeh wascompact and it had a distinctive aroma of tempeh. The
distinctive aroma of tempeh is determined by theactivity of molds which break down macro molecules
into simpler and volatile compounds such as
ammonia, aldehyde and ketones [17].
Mung beans fermented less than 24 hours
produced tempeh that does not meet Indonesianstandards where the growth of mycelium had not been
flat, the texture was not compact (crushed when cut)and did not have the distinctive aroma of tempeh. The
characteristics of mung beans tempeh are similar tothe characteristics of soybeans tempeh [10]. “[18]states that the optimum time and ideal conditions for
producing good mung beans tempeh are 24-36 hours
at 30 °C”. In this study, mung beans fermented for 36
and 42 hours produced tempeh that began to rot where
the mycelium began to blacken on the surface of thetempeh (Fig. 1). In this study, mung beans fermented
for 36 and 42 hours produced tempeh that began to rot
where the mycelium began to blacken on the surfaceof the tempeh (Fig. 1).

Control

6H

12 H

tempeh is shown in Figure 2. The optimum amount ofyeasts was not determined from the analysis of thephysical properties of tempeh but from themeasurement of inhibitory activity on optimum ACE(Table 2), namely fermented mung beans with a yeast
concentration of 0.4% (w/w).
Physical observations for mung beans tempeh
generally showed that the mycelium growth was
almost evenly distributed in all tempeh, the presenceof distinctive aroma of tempeh with a compact texture,
yellow-colored and had almost the same color as
soybeans tempeh. Fermented mung beans with a yeast
concentration of 0.1% (w/w) showed uneven growthof mycelium on the surface and tempeh crushed whencut. Miselum growth of the mold was spread evenly
on the surface of tempeh with a yeast concentration of
0.2% (w/w) yet the texture is not compact when cut.
The same was found in tempeh with yeast
concentrations of 0.3% and 0.4% (w/w) (Fig. 2).

0.1 %

0.2 %

0.3 %
0.4 %
Fig 2. Optimization of yeast concentration of mungbeans tempeh (% w/w)
The further parameters measured are the degree ofhydrolysis (DH) and dissolved protein content. DH isa parameter that shows the ability of proteases tohydrolyze proteins into peptides and amino acids. The
protease in this study derived from Rhizopus sp. andthe ability of proteases to hydrolyze proteins wasdetermined from DH values. The amount orconcentration of tempeh protein extracted by water
was determined by the Bradford method [12]. The
results of the calculation of DH and dissolved protein
are shown in Table 1.

18 H

24 H
30 H
36 H
42 H
Fig 1. The physical appearance of mung beans
tempeh with varying fermentation times (H)

Table 1. Degree of hydrolysis and protein content ofMung beans tempeh with varying yeast
concentrations

After obtaining the optimum fermentation time,
which is 24 hours, the fermentation of mung beans
was continued by varying the concentration of yeast
which was 0.1; 0.2; 0.3; and 0.4% (w/w). Each mungbeans with varying amounts of yeast was incubatedfor 24 hours at room tempehrature. The resulting% (w/w)

0.1
0.2
175

Degree ofHydrolysis(%)
18.680.23
11.270.30

ProteinConcentration(mg/L)
62.810.31
85.530.07

SEE - Bangkok, Thailand, Nov.11-13, 2019

0.3
0.4

8.510.28
9.020.19

soybeans with a yeast amount of 0.2% (w/w) had
ACE inhibitory activity of 67.43% [20].
Organoleptic tests (data are not shown) of fermented
tempeh with a yeast concentration of 0.4% (w/w)
showed that the tempeh was not suitable for
consumption because the aroma of tempeh was highly
strong so that it was not liked by panelists yet it had ahigh ACE inhibitory activity in vitro. In contrast,
panelists preferred fermented mung beans tempeh
with a yeast concentration of 0.1% (w/w) but ACE
inhibitory activity was lower.

144.190.20
351.000.00

Fermented mung beans with a yeast concentrationof 0.1% (w/w) were the most optimum treatment inhydrolyzing proteins with a hydrolysis degree valueof 18.68%. Some of the enzymes produced by
Rhizopus oligosporus are lipase, amylase andprotease, and the most active enzyme is protease [19].
Enzymatic hydrolysis is better than chemicalhydrolysis because enzymatic hydrolysis can produce
free amino acids and varied short chain peptides thathave functional activities.

Table 2. ACE Inhibitory Activity of Protein Extractof Mung Beans Tempeh
No Yeast Concentration
ACE Inhibitory% (w/w)
Activity (%)
1
Without yeast
50.000.36
2
0.1
68.850.21
3
0.4
75.000.08
4
Catopril80.000.02

Protein Profile of Mung Beans Tempeh
The profile and molecular weight of protein
extract of mung beans tempeh was determined by
SDS PAGE electrophoresis. In unfermented mungbeans, 10 protein bands were found with molecularweights of 148, 140, 103, 84, 80, 60, 34, 28, 21 and 9
kDa. The same amount of protein bands and protein
molecular weight was also found in 6 hours fermented
mung beans. The data showed that in 6 hours
fermentation, protease enzyme has not been released
into the mung beans media or there is a possibility that
other protease enzymes have not been active. The 12hours fermentation of mung beans showed that thehydrolysis reaction had occurred of which the numberof protein bands was reduced into 7 bands with amolecular weight of 148, 140, 60, 34, 28, 21 and 9
kDa. Whereas proteins with molecular weights 103
and 84 kD did not appear in 12 hours fermentation.
The fermentation of mung beans for 18 hours
obtained only 4 protein bands with molecular weights
84, 71.41 and 10 kDa. Whereas fermentation for 36,
42 and 48 hours obtained only 1 protein band with amolecular weight of 9 kDa. This data shows that
proteases have a high activity to degrade large
molecules into smaller molecules so that several
small molecules are not detected in theelectrophoresis gel. Large molecules no longer appear(electrophotogram is not shown).

Fermented mung beans had ACE inhibitory
activity of 50%. The data show that consumption ofmung beans is good for body health for people withhypertension because it can inhibit ACE activity.
Some grains have ACE inhibitory activity, such as
Mucuna pruriens Linn seeds which traditionallycould control high blood pressure with ACE
inhibitory activity of 38.44% [21]. Melinjo fruit
extracted using water had ACE inhibitory activity of
89.90% [22].
The further analysis was an analysis of thechemical content of mung beans and mung beans
tempeh through the highest ACE inhibitory activity,
namely mung beans fermented for 24 hours using ayeast concentration of 0.4%. The results of theanalysis are shown in Table 3.
Table 3. Chemical characteristics of mung beans andmung beans tempeh
Parameter(%)

ACE Inhibitory Activity of Protein Extract ofMung Beans Tempeh
Measurements of ACE inhibitory activity werecarried out on the extracts of mung beans tempeh withvariations in yeast concentrations of 0.2% (w/w) and
0.4% (w/w) which fermented for 24 hours. The resultsof the analysis are shown in Table 2. The highest ACE
inhibitory activity of protein extract was 75% formung beans fermented with a yeast concentration of
0.4% (w/w). Fermented tempeh with yeast
concentration of 0.1% (w/w) was 68%. Several
studies have shown that fermentation increases ACE
inhibitory activity, wherein in this study fermented

Water
Ash
Fat

Type of Sample
Mung
Mung
Beans
Beans
Tempeh9.360.41 46.660.16
4.110.26 2.610.36
3.070.08 2.540.42

Quality of
TempehRequirements*(%)
At most 65
At most 1.5
At most 7

Protein

20,370.19 19.850.18

At most 15* Indonesian National Standard for soybeans tempeh
The standard used in this study is the Indonesian
National standard for soybeans tempeh because
Indonesia does not yet have a reference for tempeh
from seeds other than soybeans
Fermentation decreased the ash content and the fat
content of tempeh yet increases the water content.
The moisture content of mung beans tempeh in thisstudy meets Indonesian national standards. The
176

SEE - Bangkok, Thailand, Nov.11-13, 2019

increase in water content derived from soaking andboiling process during tempeh preparation. Similar
results were also obtained [23] wherein fat content
was 1.2g, protein content was 22.2g and carbohydratecontent was 62.9g each in 100 grams of mung beans.
[24]” stated that the fermentation of beans produces
tempeh with protein content of 28.85%, fat content of
28.85%, and ash content of 2.10%.
The nutritional content of tempeh made from a
mixture of mung beans and jackfruit seed was
13.77%, 0.66% and 2.18% for protein, ash and fat
content [25], respectively. Cowpea tempeh contained
ash content of 0.83%, protein content of 16.04% andfatean content of 1.37%, while gude beans tempeh
contained ash content of 1.19%, protein content of
16.04% and fat contentof 0.96% [26]. The fat content
of mung beans tempeh (2.54%) in this study was
lower than that of mung beans (3.07%), thus it can beconcluded that the lipase enzyme actively hydrolyzes
the fat in mung beans. The fat content of mung beansobtained was 2.61% [27]. The fat content of mungbeans and germinated mung beans obtained was 1.3%
and 0.6%, respectively [28]. The fat content of mungbeans tempeh in this study was low so that tempeh isfree from bad odor due to the degradation of fatty
acids into low chain fatty acids.
Mung beans protein content (20.37%) in thisstudy was higher than the protein content of mungbeans tempeh (19.85%). The decrease in protein
content of mung beans tempeh is suspected becausesome of the decreased protein is used by Rhrizopus asa nutrient source for its growth. The mung beans
protein content obtained was 23.25% [27], this value
did not differ greatly from the content of mung beans
protein in this study.

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Chemistry,Vol. 211, pp. 423–430.
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CONCLUSION
Mung bean is a type of beans that can be used as
raw material for soybeans tempeh preparation and has
ACE inhibitory activity. Mung beans fermented for
24 hours with 0.4% yeast concentration had the best
ACE inhibitory activity. ACE inhibitory activity ofprotein extract of mung beans tempeh was 75% sothat mung beans tempeh has the potential to be
developed into functional antihypertensive foods.
ACKNOWLEDGMENTS
The authors thank the Rector of Syarif
Hidayatullah Islamic State University Jakarta,
Indonesia, for the assistance of research funding.
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SEE - Bangkok, Thailand, Nov.11-13, 2019[22] Mun’im A., Munadhil M. A., Puspitasari N. andYanuarA. A., Angiotensin converting enzyme
inhibitory activity of Melinjo (Gnetum gnemon
L.) seed extracts and molecular docking of its
stilbene constituents. Vol. 10, Issue 3, 2017,
pp.1-6.
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sifat organoleptik, dan kandungan gizi padaproduk tempeh dari kacang non-kedelai. Jurnal
aplikasi teknologi pangan, Vol 5 Issue1. 2016, pp
16 – 20.
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from chickpea seeds. Journal of American
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[25] Hutagalung T. Y., Nainggolan R. J. andNurminah M. The Effect of Ratio of GerminatedMung beans and Jackfruit’s Seed andConcentration of Tempeh Inoculum on the
Quality of Tempeh. Jurnal Rekayasa Pangan dan
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nutrient value and antioxidant activities of
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tempeh (Vigna unguiculata) with variations offermentation time. Biofarmasi, Vol. 2, Issue 2,
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G., Carvalho V., and Silva K.. CholesterolLowering and Liver-Protective Effects of Cooked
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[19] Karmini M.and Sutopo D., Aktivitas Enzim
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litbang. depkes. go. id. 2007, pp 94-102.
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Activity of the Soybeans Tempeh Protein as
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178

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ESTIMATION OF PROPENSITY SCORE USING LOGISTIC
REGRESSION (CASE STUDY: BREASTFEEDING DATA INSELOPURO SUB-DISTRICT BLITAR REGENCY)

1

Hilwin Nisa’1, Maria Bernadetha Theresia Mitakda2, and Suci Astutik3
Faculty of Math and Science, Brawijaya University, Indonesia; 2,3 Brawijaya University, Indonesia

ABSTRACT
Propensity score is a method to estimate the effect of receiving treatment when subjects cannot be treatedrandomly. Propensity score can be estimated using logistic regression or Classification and Regression Tree
Analysis (CART). Logistic regression is the most common method to estimate propensity score. Generally, there
are four methods of propensity score, they are matching, stratification, weighting, and regression adjustment. In abreastfeeding case study, random assignments to mothers as subjects are not feasible. So, it will be difficult toestimate the effect of receiving treatment. In Selopuro Sub-District Blitar Regency, many mothers still do not give
exclusive breastfeeding for their babies [1]. It is important to know what is factor causes exclusive breastfeeding.
Propensity score can help us to estimate the effect of receiving treatment in this breastfeeding case. Before weanalyze the propensity score, we need to estimate the propensity score. In this paper, we will estimate thepropensity score of breastfeeding data in Selopuro Sub-District Blitar Regency using logistic regression.
Keywords: Propensity score, Logistic regression, Random, and Exclusive breastfeeding.

choose the treatment that we will evaluate the effect.
The treatment which we will use in this research is a
confounding variable. We use Chi-Square test to
know the confounding variable. Then, we will
estimate the propensity score using logistic regression.
Propensity score can be analyzed after being
estimated using logistic regression.

INTRODUCTION
In conducting research, sometimes the examples
which we used cannot be taken randomly. It can befound in observational and non-experimental studies.
This condition can cause bias when we evaluate theeffects of treatment given. To reduce bias in thesekinds of research, we can use propensity score
method. Propensity score can help to evaluate theeffects of treatment given [2].
No randomization in observational study causes
different group on confounding variable. It
potentially has signifficant effect on result [3].
Propensity score helps to make groups more similar.
So that, it will reduce bias of estimating treatment
effect in observational study.
Research to know factors of exclusive
breastfeeding can be conducted by observation. In
Selopuro Sub-District Blitar Regency, many mothers
still do not give exclusive breastfeeding to theirbabies. In other side, we know how important
exclusive breastfeeding for baby is. World HealthOrganization (WHO) suspected 53% of acutepneumonia cases and 55% of infant deaths fromdiarrhea are caused by poor feeding in the first six
months of birth [4].
Propensity score can be estimated by several
methods. Generally, the methods are Classification
and Regression Tree Analysis (CART) and logistic
regression. The most familiar method is logistic
regression [5]. By logistic regression, we can also
predict the probability of an event [6].
Before estimating propensity score, we need to

METHODSTo estimate the propensity score, we use logistic
regression. Thus, the function of propensity score is[6]:(1)𝑒(𝑋𝑖 ) = 𝑃(𝑧𝑖 = 1|𝑋𝑖 )exp(𝛽0 + 𝛽1 𝑥1 + ⋯ + 𝛽𝑘 𝑥𝑘 )=1 + exp(𝛽0 + 𝛽1 𝑥1 + ⋯ + 𝛽𝑘 𝑥𝑘 )The breastfeeding data which we use is data
primer. The data is gotten by conducting survey inMarch 2019 and the respondents are mothers in
Selopuro Sub-District Blitar Regency who have six
months until eleven months baby.
In Selopuro Sub-District Blitar Regency, there are
195 mothers who have six-eleven months babies.
Using this formula:𝑁(2)𝑛=[ 1 + 𝑁 (𝑒 )2 ]195=
1 + 195(0.05)2= 131.092 = 131
we can determine the number of samples. To makethe research more valid, we add the number ofsamples in this research. We use 188 samples in this179

SEE - Bangkok, Thailand, Nov.11-13, 2019research.
Independent variable (𝑌) in this research is
exclusive breastfeeding graduation status (Yes/No)
and there are ten dependent variables, they are:
𝑋1 = mother’s age
𝑋2 = the last education of mother
𝑋3 = mother’s job
𝑋4 = where the mother gives birth
𝑋5 = practice of early breastfeeding initiation
𝑋6 = when the mother starts breastfeeding
𝑋7 = whether the first breastfeeding is collostrum
𝑋8 = mother’s knowledge about breastfeeding
𝑋9 = mother’s attitude about breastfeeding
𝑋10 = mother’s reason in first time gives her baby
besides breast milk.

Source: Processed using SPSS
Table 3 shows the capability independent variable
explain dependent variable. The value of Nagelkerke
R Square is 0.729, it means independent variables can
explain 72.9% dependent variable and 27.1% of
dependent variable is explained by other variable
whisch is not in the model.
Then, the treatment which we use in this researchis confounding variable. Confounding variable can befound by Chi-Square test. Based on Chi-Square test,
confounding variable is 𝑋5 (practice of earlybreastfeeding initiation).
The result of Chi-Square test can be seen in thisfollowing table.
Table 4 Test of correlation between 𝑋5 and othervariables

RESULT AND DISCUSSION

Variable P-Value
Decision
0.905
Accept 𝐻0
𝑋5 ∗ 𝑋1
0.076
Accept 𝐻0
𝑋5 ∗ 𝑋2
0.96
Accept 𝐻0
𝑋5 ∗ 𝑋3
0.000
Reject 𝐻0
𝑋5 ∗ 𝑋4
0.000
Reject 𝐻0
𝑋5 ∗ 𝑋6
0.358
Accept 𝐻0
𝑋5 ∗ 𝑋7
𝑋5 ∗ 𝑋8
0.641
Accept𝐻0
𝑋5 ∗ 𝑋9
0.256
Accept 𝐻0
𝑋5 ∗ 𝑋10
Source: Processed using SPSS
where, hypothesis of this test is:
𝐻0 : there is no correlation between 𝑋5 and anothervariable, versus
𝐻1 : there is a correlation between 𝑋5 and anothercorrelation.
Based on the test, variable which has the mostcorrelation with other variables is 𝑋5 . So, we can saythat confounding variable is 𝑋5 . Confounding
variable 𝑋5 devides the data become two groups,
control and treatment. Control group is a group ofmothers who do not practice early breastfeeding
initiation and treatment group is a group of mothers
who practice early breastfeeding initiation.
Then, we can estimate the propensity score by thefunction at Eq. (1). There are two groups ofpropensity score estimation, one is for control groupand other for treatment group.

Breastfeeding data in Selopuro Sub-District Blitar
Regency shows that 105 mothers do not give theirbabies exclusive breastfeeding and 83 mothers give
their babies exclusive breastfeeding. Mothers whogive exclusive breastfeeding is 55.9% from 188
respondents. It can be seen in this following table.
Table 1 Classification table
Predicted
Y
Percentage
Unsuccess SuccessCorrect
105
0
100.0
83
0
.0
55.9

Observed
Y Unsuccess
Success
Overall
Percentage
Source: Processed using SPSS

Table 2 Model Fitting Information
Model Fitting
Criteria

ModelIntercept

Likelihood Ratio Tests-2 LogChi-

Likelihood

Squaredf

Sig.

147.685 10.000

258.043

Only
Final

110.358

Table 5 Variables in the equation of control group

Source: Processed using SPSS
Table 2 shows the result when independent variables
have not been in the model.
X1
X2
X3
X4

Table 3 Pseudo R-Square
Cox and Snell.544

Nagelkerke.729

McFadden

.572

X6

180

B
.048
-.149
-.030
1.998
-.661

S.E.
.101
.849
.485
1.00
4
.651

Wald df.229 1.031 1.004 1
3.959 1
1.032

Sig. Exp(B)
.632
1.049
.861
.862
.951
.971
.047
.136

1 .310.516

SEE - Bangkok, Thailand, Nov.11-13, 2019

X7.149 2121.000 1 1.00
1.161
0.06
0
3
X9
21.21 9313
.000 1 .998 1634994
5 .514733.532
X10.656 .270 5.910 1 .015
1.928
Const
- 1905.000 1 .999
.000
ant
21.99 5.84
1
6
Source: Processed using SPSS
Based on Table 5, we can obtain model to estimate
propensity score for control group. The model is(3)
𝑒(𝑋𝑖 )= 𝑃(𝑧𝑖 = 1|𝑋𝑖 )exp(−21.991 + 0.048𝑥1 + ⋯ + 0.656𝑥10 )=.
1 + exp(−21.991 + 0.048𝑥1 + ⋯ + 0.656𝑥10 )40.97038⋮⋮58
0.9194259
0.00482
Source: Processed using SPSS
Table 8 Estimation of propensity score for treatment
group
Respondent
𝐸 (𝑦|𝑧 = 1)
10.791242
0.4089230.2442140.88427⋮⋮128
0.83864129
0.48296
Source: Processed using SPSS

Table 6 Variables in the equation of treatment group
B

S.E.

Wald

df

Sig.

Exp(B)

X1

.030

.054

.312

1 .577

1.031

X2

.302

.316

.914

1 .339

1.353

X3

-.507

.178 8.067

1 .005

.602

X4

-.197

.333

.351

1 .554

.821

X6

.251

.488

.264

1 .6071.285

X7-.843 26284.

.000

1 1.00

.430

863
X9

21.81 6855.7
8

X10

.522

Based on Table 7 and Table 8, we can know thatprobability mother give exclusive breastfeeding oftreatment group is bigger than control group.
Then, the value of propensity score estimation canbe analyzed based on one of four methods propensity
score, like matching, weighting, stratification andssregression adjustment.
CONCLUSION AND RECOMMENDATION
Propensity score of breastfeeding data in Selopuro
sub-district Blitar regency can be estimated using
logistic regression by Eq. (3) for control group andEq. (4) for treatment group. For the next research cananalyze propensity score using one of propensity
score methods.

0.000

1 .997 2989682

66

111.448.135 14.99

1 .0001.686

1 .999

.000

6
Con
stant

- 25375.
26.10

.000

ACKNOWLEDGMENTS
This work would not have done well without thefinancial support of LPDP (Lembaga Pengelola Dana
Pendidikan - Indonesia Endowment Fund for
Education) who has given me scholarship in mymaster degree. I am grateful to my lecturers, Dr. Ir.
Maria Bernadetha Theresia Mitakda and Dr. Suci
Astutik, S. Si., M. Si., who have supported and guided
me. I would like to thank my parents and my beloved
family whose love and prayers are always for me. Allof my friends who always supported me, I am sothankful.

035

2
Source: Processed using SPSS
Based on Table 6, we can obtain model to estimate
propensity score for treatment group. The model is(4)𝑒(𝑋𝑖 )= 𝑃(𝑧𝑖 = 1|𝑋𝑖 )exp(−26.102 + 0.03𝑥1 + ⋯ + 0.522𝑥10 )=.
1 + exp(−26.102 + 0.03𝑥1 + ⋯ + 0.522𝑥10 )Then, Eq. (2) and Eq. (3) are used to calculate
estimation of propensity score like in the following
tables.

REFERENCES[1] Arum D. N. A., Interviewed by Researcher, inJanuary 2019, Selopuro Health Center.
[2] Daniel F. M. C., Greg R., and Andrew R. M.,
Propensity Score Estimation with Boosted
Regression for Evaluating Causal Effects in
Observational Studies, Psychological Methods,
Vol. 9, Issue 4, 2004, pp. 403-425.

Table 7 Estimation of propensity score for control
group
Respondent1
2
3

𝐸 (𝑦|𝑧 = 0)0.005380.00000
0.94420181

SEE - Bangkok, Thailand, Nov.11-13, 2019[3] Reeve, B. B., Smith, A. W., Arora, N. K., andHays, R. D., Reducing Bias in Cancer Research:
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69-80.
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[5] Shenyang G. and Mark W. F., Propensity Score
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SAGE, 2010, pp. 127-210.
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31-43.
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for Accommodating Estimation Errors of
Propensity Scores, BMC Medical Research
Metthodology, Vol. 5, Issue 1, pp. 1-9.

182

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE MORPHOLOGY AND PHENOLOGY OF YELLOW COMMON
BEAN (F7) AS OFFSPRING OF INTRODUCED AND LOCAL VARIETY
CROSSING

1,2,3

Fathiyyah1, Sumeru Ashari2 and Andy Soegianto3
Agriculture Faculty, Brawijaya University, Indonesia

ABSTRACT
Common beans (Phaseolus vulgaris L.) are plants from legumes or Fabaceace family that are very popularwithin the society. Crossing between varieties is a method to produce desired trait or produce new trait in the
improvement of a plant character. One of them is crossing introduced varieties and local varieties. Some common
bean varieties in Indonesia are introduced varieties and crosses between introduced and local Indonesian varieties.
Offspring from introduced (Cherokee sun) and local Indonesian varieties (Gogo kuning) in the F6 generation haveshown good adaptation to the medium plain. Morphological and phenology studies on the accession of plant
breeding results are needed to determine the similarity of offspring's appearance to its parents. The two accessions
obtained have the character of yellow pod having a different type of growth which is dwarf and climbing. Bothparents have several differences in morphological and phenological characters. Type of growth, colour (leaves,stems, flowers, and pods), flowering time, the initial appearance of pods is a character observed in six plants ateach accession. The yellow character of the pod on the two accessions is a new appeal for consumers. Yellow
pigment in plants as an identification of the carotene content in these plants.
Keywords: Morphology, Phenology, Common Bean, Offspring, Introduced and local variety

INTRODUCTIONMETHOD
Common bean (Phaseolus vulgaris L.) is a speciesof Fabaceae family that is preferred for consumption.
The content of protein and minerals such as K, Ca,
Mg, Zn, Cu, P, Fe, vitamin B6, folic acid, thiamine,riboflavin, niacin, and essential amino add value tothe feasibility of consuming Common beans [1]. Highnutrition is also an added value for Common beans
and is recommended as an alternative food for diet[2].
Common bean is not only developed in Indonesia
but also in various other countries. Common Beandelivered by different countries has different
characters and become an advantage for Commonbeans themselves. Hybridization is the crossing of
two individuals of the same species or which has aclose relationship [3]. Plant crossing can be one way
to combine the two superior traits of each parent into
one offspring that has a superior trait or more fromboth parents. The crossing can be done one of themby hybridizing between introduced varieties and local
varieties.
Cherokee Sun variety is introduced variety from
Hawaii which has superior yellow pod trait. Gogo
Kuning is a local variety of Surakarta Indonesia
which has a high yield. The results of both crosses canbe seen through morphological and phenology studies
on the accession of the results of the crossing of thetwo parents on the appearance of the offspring.

Two parents are introduced varieties (Cherokee
Sun) and local varieties from Surakarta (Gogo
Kuning). The crossing is done on two parents which
are then selected to get the yellow pod character.
Furthermore, several selected lines in the F7
generation were cultivated in green houses located in
Tegal Weru village, Dau sub-district, Malang
Regency, East Java, at latitude 7°56'32"S112°33'51"E with an altitude of 722. Every 6 plantsof the parent (Cherokee sun) and 2 accessions of theoffspring are planted to determine the differences andsimilarities between them. Observations were madevisually to find out the all appearance of the accession
to continue the next selection stage. Morphology
observation is done on the colour of leaves, stems,
and flowers. Observation of phenology is carried out
on the initial character of flowering and pods
appearing. The colour of pods and seeds become
interesting characters which are then also observed.
RESULT AND DISCUSSION
The selection of parent is an important aspect for
the initiation of plant breeding programs [4]. Crossing
between varieties of introduced and local varieties
can be good genetic material to change a plant trait.
Local common bean varieties display an important
183

SEE - Bangkok, Thailand, Nov.11-13, 2019variety of potential characters related to productivity
such as the number of pods per plant [5]. The
presence of Cherokee sun as introduced varieties andGogo Kuning as local varieties are expected to beparents that can inherit and improve the character ofcommon beans through crossing both and the results
can be seen on the offspring.
In this breeding program Cherokee Sun varieties
as female parents and Gogo Kuning local varieties asmale parents. The aim of this program is to produce
new common bean varieties with high yielding
yellow pods [6]. After selection up to F6, a number oflines have been found that have known yellow pod
trait. Morphological and phenology studies on thelines resulting from the crossing of both were carriedout to determine the desired trait appearance for the
next selection process.
The colour of leaves and stems between parent(Cherokee sun) and two offspring (CSxGK 1 and 2)
both have the green. CSxGK 1 is dwarf bean while
CSxGK 2 is climbing bean. Flowers of all them arealso purple and white as in Fig.1. Flower initiation in
CsxGk 1 and 2 appears early than its parents. Early
flower in Cherokee sun appeared on 32 DAP (Days
After Planting) and CsxGk 1 and 2 respectively 2628 and 28-31 DAP. Early pods appeared on the
Cherokee sun 37-40 DAP and at CsxGk 1 and 2
respectively 33-35 and 35-37 DAP. Each phenotype
in an individual affects the expression of a trait in its
offspring. Even in flower phenology, the maternal
effect is very influential. Phenology in reproduction
is one example of a character from a parent that
influences its intergeneration. The effect of maternal
reproduction on phenology will influence the time ofoffspring germination if there is a relationshipbetween flowering time and fruit cooking time [7].
abFig. 1are one of the goals of the initiation program. The
pigment determines the colour and shows the visualappearance of parts of the plant. The colour of fresh
vegetables or fruit is one of the people's assessments
for consuming these foods [8]. Green in vegetables,
yellow to orange and red in tomatoes, white to yellow,
orange, red and purple is a pigment that identifies thecontent of carotene, betalain, and anthocyanin.
Yellow pods are one of the goals of this preliminary
program. The yellow colour of the pod is indicated by
the carotene content of the pod. Cherokee sun has aweak degree of curvature and CSxGK 1 and 2 has amedium and strong degree of curvature.
Seed colour on both offspring and parent is Dark
brown to black (Fig 4). Dark coloured seeds contain
3.8% ash, 0.1-1.1% fat, 0.5-17.7% protein, 77.4%
carbohydrates, 3.4-21.5% fiber [9]. The maternal
effects are also a form of phenotypic plasticity acrossgenerations, caused by the maternal environment[10]. The direct maternal effects can physicallychange the appearance of phenotypic offspring as it
develops as in the effects of cytoplasmic and seed size
[11].
a

c

b

c

Fig. 2a) Pod of Cherokee Sun, b) Pod of CSxGK
1, and c) Pod of CSxGK 2

Fig. 3

Curvature Degree of Pod Base on UPOV
Assessment TG/12/9 Rev.2.

a) Flower of Cherokee Sun, b) Flower of
CSxGK 1, and c) Flower of CSxGK 2.

Table 1 Flowering Time and Pod Initiation of
Cherokee Sun and The Offspring
Flowering
Pod InitiationLines
time (DAP)(DAP)
Cherokee Sun

32

±39

CsxGk 1

±28

±34

CsxGk 2±30

±36

CsxGK 1 and 2 has yellow pods as seen in Fig.2.
The content and composition of pigments in plants
184

SEE - Bangkok, Thailand, Nov.11-13, 2019ablight absorbed by plants. Light becomes one of thefactors that stimulate carotene content in plants [17].

c

CONCLUSION

Fig. 4

The two lines in the F7 generation have amorphologically similar appearance to their female
parent. This shows the success of a character's decline
from the female parent in its derivatives. The
presence of yellow pod in common beans can be a
new variation in the genetic diversity of commonbeans. Furthermore, it is necessary to conduct
selection and fulfillment the requirements forregistration and varieties release of yellow podcommon beans in order to be widely commercialized.

a) Seed of Cherokee Sun, b) Seed of CSxGK
1, and c) Seed of CSxGK 2

F1 crosses with parent (Backcross) in thebreeding process are considered successful in
displaying yellow pod characters. The backcrossmethod is a crossing generation of F1 with one of theparents. The benefit of the backcross method is tomaintain all the positive traits found in the parent
variety. This method is part of the convergent
breeding method. Where convergent breeding is amethod of crossing that is carried out if there are only
one or two traits which want to be repaired and will
be gathered into existing superior varieties. The
results of this method are important traits in superiorvarieties can still be preserved [12]. Yellow pod trait
as a trait from female parent and high yields as a traitfrom Gogo Kuning which.
Yellow-orange vegetables and fruits as major
dietary source of carotene also providing most of the
β-carotene and the α-carotene [13]. One of them iscarrots which have Beta and high Alpha carotene, it’scaused by two major locus, namely Y and Y2 which
are dominant and capable of expressing carotene
accumulation. Another case is tomatoes. the Beta andDelta content of tomatoes is controlled by CYC-b andthe overexpressed LCY-e allele during fruit ripening[14]. Carotene content and carotenogenic expressionof the gene as a control response to biotic and abiotic
stress such as during growth, photomorphogenesis,
photosynthesis, flowering time and fruit ripening [15].
Yellow, orange and red are expressions ofchromoplast which depend on the combination of
carotene and xanthophyll content. The color appearson the differentiated chromoplast which is depositedin plastoglobules. when chromoplast development,
carotenoid accumulation in color plastoglobules
confers in fruits and flowers. The development ofchromoplast is accompanied by the induction of
enzymes that catalyze carotene biosynthesis.
although inactive, the enzyme is found in the stroma,active forms occur in plastids which have lipophilic(carotene precursors). Biosynthesis and ability of
Carotenoid accumulation in some fruits is controlled
by genetic influences, suggesting some rate-limiting
carotenogenic step as responsible for the carotenoid
accumulation during fruit ripening. Carotenoids werealways present in higher quantities than chlorophylls
in the flesh of both yellow and red skinned [16]. Coloris also influenced by the high quantity and quality of

ACKNOWLEDGMENT
I am enormously grateful to LPDP (Lembaga
Pengelola Dana Pendidikan-Indonesia Endowment
Fund for Education) for continuous encouragement
on my study and funding to participate in thisconference. I am thankful for all my lecturer forkindly advices throughout my study.
REFERENCES[1] Tugce C., Hatice S.D., Huseyin C., Duygu S.,
Alper A.I.D., Tuba E. and Cengiz T., The
Nutritional Content of Common Bean
(Phaseolus vulgaris L.) Landraces in
Comparison to Modern Varieties, J.Agron,Volume.8, No.166, pp.1-9.
[2] Romero A.O., Damian H.M.A., Rivera T.J.A.,
Baez S.A., Huerta L.M. and Cabrera H.E., The
Nutritional value of Beans (Phaseolus vulgaris
L.) and its importance for Feeding of Rural
communities
in
Puebla-Mexico.
Int.Res.J.Biological Sci, Vol.2, No.8, 2013,
pp.59-65.
[3] Acquaah G., Principles of Plant Genetics andBreeding, Wiley Blackwell US, pp.132-134.
[4] Correa A.M., De Souza L.A.R., Braga D.C.,
Ceccon G., Teodoro P.E., Da Silva J.C.A. and Da
Silva F.A., Agronomic performance and genetic
variability among common bean genotypes insavanna/pantanal ecotone. J. Agron, Vol.14,
2015, pp.175–179.
[5] Daria S., Fernando R., Juan J.R., Rosa R. andGiandomenico C, Morphological and genetic
diversity among and within common bean
(Phaseolus vulgaris L.) landraces from theCampania region (Southern Italy), Scientia
Horticulturae, Vol.180, 2014, pp.72-78.
[6] Soegianto A., and Sri L.P., Perakitan Varietas
Tanaman Buncis (Phaseolus vulgaris L.)
Berdaya Hasil Tinngi Dengan Sifat Warna
Polong Ungu dan Kuning. Seminar Nasional
PERIPI 2014, p.1-8.
185

SEE - Bangkok, Thailand, Nov.11-13, 2019[7] Galloway L.F, The effect of maternal phenology
on offspring characters in the herbaceous plantCampanula Americana, J. of Eco, Vol.9, 2002,
pp. 851-858[8] Barrett D.M., Beaulieu J.C. and Shewfelt R.,
Color, flavor, texture, and nutritional quality offresh-cut fruits and vegetables: desirable levels,
instrumental and sensory measurement, and theeffects of processing, Crit.Rev.in Food Sci andNut. Vol.50, No.5, 2010, pp.369–389.
[9] Francine G.B.L., Aca C.A.F.Z., Jose P.W.,
Alessandro N. and Ivo M.D, Beans (Phaseolus
vulgaris L.): whole seeds with complex
chemical composition, Review Current Opinion
in Food Science 2018, Vol.19, 2018, pp.63–71.
[10] Wolf J.B. and Wade M.J, What are maternal
effects (and what are they not)?,
Philos.Trans.R.Soc.B-Biol.Sci Vol.364, 2009,
pp.1107–1115[11] Roach D.A. and Wulff R.D., Maternal effects inplants, Annu.Rev.Ecol.Syst, Vol.18, 1987,
pp.209–235[12] Syukur M., Sujiprihati S. and Yunianti R.,
Teknik Pemuliaan Tanaman. Jakarta:Penebar
Swadaya, 2012, pp. 96-102[13] Amorim K.T., Cepeda A., Fente C. and Regal
R, Review of Methods fo analysis ofcarotenoids. 2014 Trends in analyticalchemistry, No.56, 2014, pp.49-73.
[14] Giuliano G., Provitamin A biofotification of
Crop plants: a gold rush with many miners,
Current Opinion in Biotechnology, No.44,
2017, pp.269-180[15] Hannoufa A., and Hossain Z, Regulation ofcaretonoid accumulation in plants, Biocatalysis
and agricultural Biotechnology, 2012, pp.198202[16] Delgado-Pelayo R., Guerrero L.G., and Mendez
D.M., Chlorophyll and carotenoid pigments inthe peel and flesh of commercial apple fruit
varieties, Article, Food Research International,
2014, pp.1-10[17] Rodrigo, M.J. Alquezar B. Alos E. Lado J.
Zacarias L., Biochemical bases and molecularregulation of pigmentation in the peel of Citrus
fruit. Sci. Hortic, 2013, pp.1-17

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

FORWARD MODELING FOR SUBSURFACESYNTHETIC SEISMOGRAM

1

Wasis Wasis1, Adi Susilo1, Musthofa Nuh1.
Faculty of Mathematics and Natural Sciences, Brawijaya University, Malang, Indonesia

ABSTRACTThe relationship between the subsurface geological model and the synthetic seismogram record, could be
identified visually. One of the method to identify seismic response is seismic forward modeling that makes seismic
survey more efficient. This study is to identify subsurface synthetic seismogram characteristics based on theconfiguration, frequency, and velocity. Data used in this study are synthetic, including depth, distance/offset,
velocity, density, and ricker wavelet. The configurations are Off-end spread and Split spread. Ricker wavelet’s
frequencies are 20 Hz and 40 Hz. Forward modeling method applied by convoluting the wavelet and the reflection
coefficient to gain a synthetic seismogram that represent subsurface structure. Based on the model, the seismic
responses were obtained 8 synthetic seismograms with the different responses, which is obtained by variation ofconfiguration, frequency, and velocity. Five reflectors with a different reflection coefficient were obtained. The
results show that the largest value is fourth reflector, because of the high contrast of acoustic impedance between
sandstone and limestone. Beside that, variation of configuration, frequency, and velocity resulting different
synthetic seismograms (wiggles) especially in wave response and arrival time.
Keywords: Subsurface structure, Forward modeling, Synthetic seismogram, Reflector.

simultaneously in an area. The synthetic seismic
generated from the entire acquisition process will becompleted faster and the acquisition parameters thatwill be used in the actual measurements can be
immediately determined so that it can save costs.
Synthetic seismic are only predictions to identify
what might be beneath the surface. However,acquisitions directly in the field must still be carriedout. Synthetic seismic will never be able to replaces
actual seismic, but only helps understand it [4].
One form of model that can be made as an initial
prediction is the modeling of subsurface synthetic
seismograms. This modeling utilizes the convolution
process between seismic source wavelets andreflection coefficients (RC) from rock layers. Thismodel can later also be used as an ideal model that isuseful for assisting understanding of seismic wave
propagation before conducting data acquisition in thefield.

INTRODUCTION
Seismic forward modeling is a method of
applying seismic waves to actual geological models[1]. The two main components in seismic modelingare the making of numerical and computational
geological models of seismic responses. The
modeling illustrates the process of propagating
seismic waves from the source to the subsurface andreturn to the receiver. Models can be made based on
actual field conditions and can be either 1D, 2D or 3D[2]. Advanced seismic reflection modeling is acomputational process in the subsurface geologicalmodel (with parameters: horizontal distance, verticaldepth, acoustic impedance) which is transformed into
synthetic seismic recordings. Vertical depth isconverted to two-way travel time. Acoustic
impedance contrast (the result of speed and density)
is converted into a reflection coefficient. Often, therelationship between geological models and synthetic
seismic recordings can be inferred through visualobservation [3].
One method that is useful for identifying seismic
responses is forward modeling (seismic forward
modeling). The reason why advanced modeling isused in seismic surveys is because it can save timeand money. If this work is done by a computer, it canmake savings rather than using a seismic survey
vessel. A seismic ship must conduct a new survey foreach target area, while a computer has the ability to
carry
out
different
acquisition
processes

METHODS
Input Data
As an initial step, data is collected from related
references. This data is in the form of depth, distance( offset ), velocity, density, and wavelet . Data on
depth, distance ( offset ), and velocity are used for
calculation of travel time, while data on velocity anddensity are used for calculation of reflection
coefficients. The results of the reflection coefficient187

SEE - Bangkok, Thailand, Nov.11-13, 2019are convoluted with the wavelet so that the data is in
the form of a synthetic seismogram. This synthetic
seismogram is displayed on a graph of shot gather
between time and distance .
Geology Model
This geological model is based on thepredetermined density and velocity data. This modelis an approach model to the actual conditions in thefield. In this study, two geometry of seismic sourceswere used, namely Off-end and Split spread.
This geological model will later provide a general
picture of subsurface lithology and its interactions
with seismic waves so that they can produce asynthetic seismograms.

Fig. 2. Split-spread geology model
Making of Synthetic Seismograms
The synthetic seismogram in this study was
carried out by the convolution process between
wavelets and reflection coefficients.𝑺(𝒕) = 𝑾(𝒕) ∗ 𝒓(𝒕)(4)Ricker Wavelet
Ricker wavelets have frequency values of 20 Hz and
40 Hz. in the time domain. The x axis is a timeparameter in second, and the y axis is an amplitude
parameter.
Data Plotting

Fig. 1. Off-end spread geology model

The result of this data plotting is a shot gather graphthat describes subsurface synthetic seismograms. The
synthetic seismogram in the form of a plot curve
between distance (offset) as the x axis and time as they axis.

Travel Time Calculation
The travel time calculation phase starts from theprocess of entering the required data into MATLAB
software. Data needed include depth, distance(offset), and velocity.
𝒙𝟐

𝒙𝟐

𝟒𝒉𝟐

𝟏

𝟏

𝟏

𝒕(𝒙)𝟐 = 𝒗𝟐 + 𝒕𝟐𝟎 = 𝒗𝟐 + 𝒗𝟐𝟏

RESULTS AND DISCUSSION
Research Results(1)

The results obtained from this study are a modelof subsurface synthetic seismograms. This synthetic
seismogram is obtained from the convolution process
between the earth reflection coefficient (RC) and theseismic source wavelet [5].
The value of the velocity and density of eachrock layer will produce an acoustic impedance (AI).
The greater the velocity and density value, the greater
the acoustic impedance value. Comparison of AI
values between two rock layers will produce areflection coefficient (RC) which is located in theboundary plane between layers, and have a value

Reflection Coefficient Calculation
The reflection coefficient was obtained from theresults of the AI calculation. Based on the calculation,
the RC value will be found in the range between -1
and +1. This value is related to the contrast value ofAI. The bigger the AI value, the greater the RC value(close to +1), and vice versa.
𝑨𝑰 = 𝝆 𝒗(2)

𝑨𝑰 − 𝑨𝑰

𝝆 𝒗 −𝝆 𝒗

𝑹𝑪 = 𝑨𝑰𝟐 + 𝑨𝑰 𝟏 = 𝝆𝟐 𝒗𝟐 + 𝝆𝟏𝒗𝟏
𝟐

𝟏

𝟐 𝟐

𝟏 𝟏

(3)
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SEE - Bangkok, Thailand, Nov.11-13, 2019

between -1 and +1. This RC value is convoluted (*)
with wavelets using Matlab.
Discussion.
Analysis of RC

Reflector 1

The reflection coefficient was obtained from thecontrast of AI in each layer.

Reflector 2
Reflector 3
Reflector 4
Reflector 5

Table 1. Reflection Coefficient on each reflector
No.
1
2
3
4
5

Reflector
Reflector 1
Reflector 2
Reflector 3
Reflector 4
Reflector 5

Value of RC
0.0553
0.0981
0.09750.24290.2264

Fig. 3 Synthetic Seismogram (Off-end spread,
f=20 Hz, velocity=Data 1).

Reflector 1

Analysis of Synthetic Seismograms

Reflector 2This synthetic seismogram was obtained fromthe results of convolution between wavelets andreflection coefficients (RC). Red line or known as
wiggle, is the amplitude produced by the convolution
process. In seismic fields, the amplitude of this wave
is often called a reflector. A strong and brightreflector can be interpreted that the reflector consistsof large amplitudes. In the picture you can see there
are 6 lines that have different shapes. The red line thatis located at the top is interpreted not as a reflector,
but the amplitude generated from direct waves.
Meanwhile, the other five lines are seismic reflectors,
where each of these reflectors has different shapes
and amplitude values.
Figure 3 is the result of synthetic seismograms
resulting from the Off-end spread configuration
geological model and the ricker wavelet frequency of
20 Hz. This off-end spread configuration has a
distance / offset ranging from 0 m - 1500 m withseismic sources at the end (zero offset). The fivereflectors have different RC values as in Table 1.
Figure 4 is a synthetic seismogram that is producedon the same configuration with a different frequency,
which is 40 Hz. When observed, both have asignificant difference in the waveform. On synthetic
seismograms with a frequency of 20 Hz, the resulting
waves are larger and wider than those on synthetic
seismograms with a frequency of 40 Hz.
On synthetic seismograms with a frequency of 20
Hz, the resulting waves are larger and wider thanthose on synthetic seismograms with a frequency of
40 Hz. This is also based on the reason for thedifference in the location of the wave peak at afrequency of 20 Hz and 40 Hz.

Reflector 3
Reflector 4
Reflector 5

Fig. 4 Synthetic Seismogram (Off-end spread,
f=40 Hz, velocity=Data 1).

Fig. 5 Synthetic Seismogram (Split spread;frequency= 20 Hz, velocity= Data 1).

Fig 6 Synthetic Seismogram (Split spread;frequency= 40 Hz, velocity= Data 1).

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Figure 5 and Figure 6 are the results of synthetic
seismograms resulting from the geological model ofthe Split spread configuration and the ricker wavelet
frequency of 20 Hz and 40 Hz. Both also have asignificant difference in the waveform. On synthetic
seismograms with a frequency of 20 Hz, the resulting
waves are larger and wider than those on synthetic
seismograms with a frequency of 40 Hz. This is also
based on the reason for the difference in the locationof the wave peak at a frequency of 20 Hz and 40 Hz.
The difference in the Split spread configuration withthe previous configuration (Off-end spread) is where
the seismic source is located. In this configuration,
the source is located right in the middle so that thesynthetic seismogram produced is also different.
In general, split spread configuration is more
often used in data acquisition in the field, because thesynthetic seismograms produced are better than the
results of the off-end spread configuration. This isbased on the reason that seismic sources that are in
the middle of the range of receivers can better
distribute their energy to the near offset and far offset,
because the distance traveled by the wave is only half
the part. Meanwhile in the off-end configuration
spread, the energy must be distributed to all parts of
the offset with a distance of 2 times, because theseismic source is at the end. Generally this will resultin the farthest distance or far offset not getting enoughwave energy distribution so that the resolution of thesynthetic seismogram produced is not good enough.
Therefore, choosing the right configuration greatly
affects the results of synthetic seismograms.

from the reflector which has the greatest amplitude
value, that is in the result of the reflection coefficientin Table 1. The reflection coefficient that approaches
the +1 value has the highest amplitude value.
This can be proven from the type of layer in thegeological model. Layers 1 through 6 are rock types
that have different velocity and density values, where
both parameters increase with increasing depth.
The fifth reflector has a deviation in the form of awave peak, where the amplitude of the wave will bea peak if the AI value in the lower layer is greater thanthe layer above it.

All forms of synthetic seismograms produced
from frequency variations (20 Hz and 40 Hz) haveadvantages and disadvantages. The frequency valueof 20 Hz will produce a larger and wider waveform,
but if a layer has a low thickness (thin), this frequency
is less suitable for use. At that moment, a higher
frequency (40 Hz) is needed, because the smaller
waveforms can show and separate thin layers thatcannot be done by a frequency of 20 Hz. Therefore,
the right frequency selection must be considered.
If the RC value is different for each layer, then the
wave amplitude will be different from the seismic
cross section. This will apply to actual seismic dataobtained from measurements directly in the field. But
in this study, where the data used is synthetic data(without making direct measurements) and only anapproach model, the amplitude produced will appear
to have the same value in each layer. Because the RC
value cannot be known directly from a synthetic
seismogram, to find out the difference it can be seen

REFERENCES

CONCLUSIONS
1.

2.




From the results of synthetic seismogram
forward modeling, obtained five reflectors.
Reflector 4 has the highest value of thereflection coefficient (0.2429) because of thehigh acoustic impedance contrast between
sandstone and limestone.
Configuration change, frequency, and velocity
show significant difference on the synthetic
seismogram form.
Configuration change from Off-end spread to
Split spread yields a better synthetic
seismogram resolution.
Frequency change from 20 Hz to 40 Hz gives athinner and smaller wiggle.
Velocity change from data 1 to data 2 yields a
shorter wave travel time on the near offset part.

[1] Fagin, S. W. 1991. Seismic Modeling of
Geologic Structures: Applications to Exploration
Problems (Geophysical Development series, 2ed.). Society of Exploration Geophysicists.
[2] Ellison, A. 1993. Modeling, Philosophy and
Limitation.
Computing&ControlEngineering(4), 190-192.
[3] Anderson, N., & Cardimona, S. 2002. Forward
Seismic Modeling: The Key to UnderstandReflection Seismic and Ground Penetrating
Radar (GPR) Techniques. Rolla: University ofMissouri-Rolla.
[4] Sæther, O.-P. 2013) Seismic Forward Modelingof Deltaic Sequences. Trondheim: Norwegian
University of Science and Technology.
[5] Lillie, R. J. 1999. Whole Earth Geophysics: An
Introduction Textbook for Geologist andGeophysics. Prentice-Hall: USA.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE PERFORMANCE OF INDONESIAN AGRICULTURALEXTENSION WORKER

1

Siti Rochaeni1, Muchlis R. Luddin2, Mansyur Ramly3, and Dewi Susita4
Faculty of Science and Technology, State Islamic University Syarif Hidayatullah Jakarta, Indonesia
2,3,4State University of Jakarta, Indonesia

ABSTRACTThe purpose of this study was to determine whether there were a positive direct impact of (1) variations oftasks to rewards, (2) career promotion to rewards, (3) variations of tasks to performance, (4) career promotion to
performance, (5) rewards to performance for agricultural extension worker in Banten Province. The research
design used is a structural equation model of factors that influence the performance of agricultural extension
workers. The collected data were analyzed by using reliability test using Cronbach Alpha coefficient, and thenanalyzed using Structural Equation Model with the help of Smart PLS software version 3.2.7. The results
showed that: (1) there is a significant positive direct impact on the variable variation of the task to reward, (2)there is a significant positive direct impact on the variable of career promotion to rewards (3) there is asignificant positive direct impact on the variable variation of the task to performance, (4) there is a positive direct
impact not significant variable career promotion to performance, (5) there is a significant positive direct impact
on rewards to performance.
Keywords: Task variety, Career promotion, Rewards, Performance, Agricultural extension worker

agricultural extension worker can get a promotion toa higher level position if the minimum cumulative
credit point is acquired. The performance of the
agricultural extension worker is determined by the
conformity of the job description and the actual
work. The work should be reported as a proof of
accountability for the organization. The purpose ofthis study was to determine whether there were apositive direct impact of (1) task variety to rewards,(2) career promotion to rewards, (3) task variety toperformance, (4) career promotion to performance,(5) rewards to performance for agriculturalextension worker in Banten Province.

INTRODUCTION
The agricultural extension worker has a wide
range of task variety, especially as a development
agent. The wide range of task variety should bemanaged altogether at the same time by the
agricultural extension worker. Task variety refers to
the degree to which a job requires employees toperform a wide range of task on the job [1]. Task
variety refers to the number and frequency of
exceptional, unexpected, or novel events that occur
in the task. With high variety, employees typicallyhave difficulty predicting problems or activities inadvance. Task analyzability refers to the extended towhich a task can be broken into small, well definedcomponents and is concerned with how employees
respond to problems that occur. Typically, withhighly analyzable tasks, employees follow an
objective, well defined procedure to solve problems,and are more likely to pursue knowledge in aformalized and written form. Significant correlations
were found between work-life balance and task
variety and task autonomy. The employees with hightask variety showed lesser interference of work withpersonal life, lesser personal life interference withwork and higher overall work-life balance than theemployees with low or average task variety. The
employees with high task autonomy also showed
higher work-life balance [2].
Self-development for the agricultural extension
worker has become the important aspect to make abetter agricultural extension management. The

METHODS
Use at most three levels of headings that
correspond to chapters, sections and subsections.
The first level headings for chapter titles should bein 10pt, bold, justified, and upper case font. Leave
one blank line before and after the first level
headings, respectively.
This research conducted in Banten Province,
Indonesia, that consisted of five districts: Serang,
Serang City, Tangerang, Pandeglang, and Lebak forfour months from 2018 February to June. In thisresearch, the variables were: (1) Performance (Y) as
endogenous variable; and (2) Task Variety (X1),
Career Promotion (X2), and Reward (X3) as
exogenous variable.
The design of the research used structural
equation model of factors that influence the191SEE - Bangkok, Thailand, Nov.11-13, 2019

performance of agricultural extension worker. The
construct validity used to test the validity of thequestionnaire through determined the conceptual
framework, constructed the operational standard,determined the indicators of each variable, and thefield test of the instrument. The reliability of datacollected was tested with Cronbach alpha.
The data was analyzed using model Structural
Equation Models (SEM). The data processing wasdone with software Smart PLS 3.2.7 ver. The
research variable consisted of observer variable andunobserved variable – a variable that cannot bemeasured directly but the score could be obtained
through observed variable. Based on the relationshipdirection, there were endogenous variable(influenced by other variable) and exogenous
variable (influences other variable). In this research,
the variables were: (1) Performance (Y) as
endogenous variable; and (2) Task Variety (X1),
Career Promotion (X2), and Reward (X3) as
exogenous variable. The causality relationshipbetween those four variables could be explained by
Figure 1.
The number of samples was determined withSlovin formulation, using simple random samplingtechnique with 10% of error level. The population ofagricultural extension worker in Banten Province
was 643 people, so in 10% of error level, the numberof sample obtained was 87 people. For a better data
distribution, the sample taken was increased to 100
people.
Performance (Y) indicators consisted of: (1)Preparation of agricultural assistance, consisted of 4
parameters; (2) Implementation of agriculturalassistance, consisted of 9 parameters; (3) Evaluation
and reporting, consisted of 3 parameters. For every
parameter, there were 5 answer choices available
from a to e. The scoring criteria for every choices
was as follow: select “yes” for a,b,c,d = 5 points;
select “yes” for b and d = 4 points; select “yes” forand d = 3 points; select “yes” for a and d = 2 points;
select “yes” for d = 1 point. Those parameters wereadopted from Republic of Indonesia’s Agricultural
Ministry Regulation (Peraturan Menteri Pertanian
RI) No.91 in 2013.
Task Variety (X1) indicators consisted of: (1)Integrate various skills at the same time, consisted of
3 parameters; (2) Do various different tasks,
consisted of 4 parameters; (3) Do a large scope task,
consisted of 4 parameters; (4) Do various tasks at thedifferent times, consisted of 4 parameters. The
scoring criteria used Likert scale from 1 to 5 asfollow: 1 = never; 2 = rarely; 3 = sometimes; 4 =often; 5 = always. The indicators and parameters
were constructed and developed based on Morgeson
and Humphrey (2006).
Career Promotion (X2) indicators weredeveloped based on Gaol (2014) [3]. In other hand,
Reward (X3) indicators consisted of: (1) Salary,consisted of 4 parameters; (2) Allowance, consistedof 4 parameters; (3) Appreciation, consisted of 4
parameters; (4) Retirement guarantee, consisted of 4
parameters. The scoring criteria used Likert scalefrom 1 to 5 as follow: 1 = strongly disagree; 2 =disagree; 3 = doubt; 4 = agree; 5 = strongly agree.
The indicators of Reward were developed based on
Malik et al. (2015) [4].
RESULTS AND DISCUSSIONS
Result of Parametric Estimation Revised Model
Below is the path diagram of Structural Equation
Models (SEM) along with the estimation parametersof the initial model with Partial Least Square (PLS)
estimation method which describes the relationshipbetween indicators with their latent variables and theeffect of exogenous latent variables task variety andendogenous latent variables career promotion andperformance.

Fig. 1

Path Diagram Result of
Estimation Revised Model.

Parametric

The Direct Impact and Indirect Impact of Task
variety (X1) to Reward (X3)
The table below showed that the direct impact of
Task variety (X1) to Reward (X3) was 36.84%. On
the other hand, the indirect impact of Task variety(X1) to Reward (X3) through Career Promotion(X2) was 18.52%. The total value of the impact of
Task variety (X1) to Reward (X3) was 55.36%.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 The Direct Impact and Indirect Impact of
Task variety (X1) to Reward (X3)

Table 2 The Direct Impact and Indirect Impact ofCareer Promotion (X2) to Reward (X3)

Task variety (X1) to Reward (X3)
CalculaVariable
Weighted %
tion
Task
(0.607)*
Directvariety
0.3684 36.84(0.607)(X1)
Career
(0.607)*
Indirect
Promotion (0.916)* 0.1852 18.52
through(X2)(0.333)
Total impact of Task variety (X1)
0.5536 55.36
to Reward (X3)

Career Promotion (X2) to Reward (X3)
CalculaVariable
Weighted %tionCareer(0.333)* 0.1109 11.09
DirectPromotion (0.333)
(X2)
Task
(0.333)* 0.1852 18.52
Indirect
variety(0.916)*through(X1)(0.607)
Total Direct Impact and Indirect 0.2961 29.61
Impact of Career Promotion(X2) to Reward (X3)

ImpactImpactTask variety of agricultural extension worker
was the degree when the workers need somevariations of activity. The high degree of variationneeded the use of different skill and talent, that is toencourage the farmers to learn about how toinnovate, also to listen to their complaints, thenobserving farmer’s needs, lastly to analyze and takethe right steps according to the farmers problem inthe same time or different locations. Besides,
agricultural extension worker needs to mastered inseveral aspects, that is (1) crop and livestock
production, (2) agriculture as a business, (3)agriculture development process, (4) farmers andtheir learning style, (5) rural society. Agriculturalextension worker had to mastering these aspects all
at once in educating process.
While they had a complex tasks to complete,agricultural extension workers are also a social beingthat need reward for their work. The reward could be
attained in form of wage, appreciation, and pension
guarantee. The reward would motivate to do a better
work. So when we expect someone to do tasks withdifferent variations, we also need to concern about
the reward. The reward should be decided alongwith the sacrifice of tasks delivery.

According to table above, the direct impact ofCareer Promotion (X2) to Reward (X3) was 11.09%,
while the indirect impact of Career Promotion (X2)
to Reward (X3) was 18.52%.The total impact ofCareer Promotion (X2) to Reward (X3) was 29.61%.
Self-improvement of agricultural extension worker
was an important element in the agriculturalextension changing process. In carrying out the moreparticipative process, the changes in contents andmethod of staff improvement were needed, both intraining and leadership style that inclined to selfimprovement of agricultural extension worker. Selfimprovement was not only in skill, but also incharacter development that can be applied in work.
The Direct Impact and Indirect Impact of Task
Variety (X1) to Performance (Y)The Direct Impact and Indirect Impact of Task
Variety (X1) to Performance (Y) can be seen in tablebelow:
Table 3 The Direct Impact and Indirect Impact of
Task Variety (X1) to Performance (Y)The Direct Impact and Indirect Impact of Career
Promotion (X2) to Reward (X3)

Task Variety (X1) to Performance (Y)CalculaVariable
Weighted %
tion
Task
(0.459)*DirectVariety0.210721.07(0.459)(X1)
Career
(0.459)*Promotion (0.916)* 0.0744
7.44(0.177)
Indirect (X2)
through(0.459)*Reward
(0.911)* 0.1325
13.25
(X3)
(0.317)
Total Impact of Task Variety
0.4176
41.76(X1) to Performance (Y)Impact

The Direct Impact and Indirect Impact of Career
Promotion (X2) to Reward (X3) showed in this tablebelow.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

The table above showed that the direct impact of
Task Variety (X1) to Performance (Y) was 21.07%.
The indirect impact of Task Variety (X1) to
Performance (Y) through Career Promotion (X2)
was 7.44%, and the indirect impact of Task Variety(X1) to Performance (Y) through Reward (X3) was
13.25%. The total value of the impact of Task
Variety (X1) to Performance (Y) was 41.76%.
Task Variety is a level where tasks needvariation in each different activity. The higher
variation in worker tasks would require the use ofdifferent skill and talent. The application of different
skill and talent would help to increase theproductivity of workers. When productivity
increased, it was hoped to give impact to reward
accepted, so the performance would also increase.
Task Variety had a positive impact to worker’s
performance. This means that if there is a positivechange in Task Variety, then the performance will
also increase.

Agricultural extension worker got the promotion
opportunity if they could fulfill the required ofminimum cumulative credit point. Career promotion
refers to things related planned work that carried out
to achieve mastering in skill, knowledge, andattitude of the worker. The improvement was
focused more on decision making skill. Career
promotion had a direct and positive impact toperformance. It means that if there was positivechange in career, then the performance will also
increase.
The Direct and Indirect Impact of Reward (X3)
to Performance (Y)The direct influence and indirect effect of the
Rewards (X3) variable on the Performance variable(Y) in detail is presented in table 5 below.
Table 5 The Direct and Indirect Impact of Reward(X3) to Performance (Y)The direct impact and indirect impact of Career
Promotion (X2) to Performance (Y)Reward (X3) to Performance (Y)CalculaVariable
Weighted %tion(0.317)*
DirectReward (X3)
0.100510.05(0.317)(0.317)*
Task Variety(0.911)* 0.1326
13.26
(X1)
(0.459)Indirect
through Career(0.317)*
Promotion(0.888)* 0.0498
4.98
(X2)
(0.177)
Total Impact of Reward (X3) to0.282928.29
Performance (Y)Impact

The direct impact and indirect impact of Career
Promotion (X2) to Performance (Y) could be seen intable below.
Table 4 The Direct Impact and Indirect Impact ofCareer Promotion (X2) to Performance (Y)Career Promotion (X2) to Performance (Y)CalculaVariable
Weighted %tionCareer
(0.177)*
DirectPromotion
0.03133.13(0.177)(X2)
Task Variety (0.177)*(X1)(0.916)* 0.0744
7.44(0.459)Indirect
through Reward (X3) (0.177)*(0.888)* 0.0498
4.98(0.317)
Total Impact of Career Promotion 0.1555
15.55(X2) to Performance (Y)ImpactFrom table 5 above it can be seen that the direct
impact of the Rewards (X3) variable on the
Performance variable (Y) is 0.1005 or 10.05%,
while the indirect impact of the Rewards variable(X3) on the Performance variable (Y) through the
Task Variety variable (X1) is 0.1326 or 13.26%, andindirect impact through Career Promotion variables(X2) is equal to 0.0498 or 4.98%. So that the total
impact is given by the Rewards variable (X3) on the
Performance variable (Y) is 0.2829 or equal to28.29%.
The level of income is the amount of rupiah
value of income earned on the outlays of agriculturalextension workers and their families in one month.
The income of the agricultural extension worker is
not only used for daily basic needs but if possible,
can still be used for secondary purposes. Thus theincome of an agricultural extension worker
influences the ability to carry out basic tasks so thatthe higher the incoming level of an agriculturalextension worker, the higher his ability to carry out

The table above showed that the direct impact ofCareer Promotion (X2) to Performance (Y) was
3.13%. The indirect impact of Career Promotion(X2) to Performance (Y) through Task Variety (X1)
was 7.44%, and the indirect impact of Career
Promotion (X2) to Performance (Y) through Reward(X3) was 4.98%. The total value of the impact ofCareer Promotion (X2) to Performance (Y) was
15.55%.
Promotion was an advance level position to ahigher salary, responsibilities, organization level,
usually as appreciation for the performance.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

basic tasks properly. Rewards for agriculturalextension worker have a direct positive impact on
the performance of agricultural extension workers.
This means that if there are positive changes in the
rewards of agricultural extension workers, it willlead to an increase in the performance of agriculturalextension workers.

Province, meaning that if there is a positivechange in rewards, then it results in an increasein the performance of agricultural extension
workers.

REFERENCES[1] Morgeson, F. P. & Humphrey, S. E.. The work
design questionnaire (WDQ): Developing andvalidating a comprehensive measure forassessing job design and the nature of work.
Journal of Applied Psychology, 2006. 91:
1321-1339.
[2] Walia, Parminder. “Work-Life Balance in
Relation to Task Variety and Task Autonomy:
A Study of Bank Employees,” Journal ofStrategic Human Resource Management.
http://www.publishingindia.com/jshrm/32/work-life-balance-in-relation-to-task-variety-andtask-autonomy-a-study-of-bankemployees/283/2073/[3] Gaol, J. L. A to Z Human Capital, 2014, PT.
Gramedia Widiasarana Indonesia, Jakarta:
Indonesia.
[4] Malik, M. A. R., Butt, A. N., & Choi, J. N.
Rewards and employee creative performance:
Moderating effects of creative self-efficacy,
reward importance, and locus of control.
Journal of Organizational Behaviour, 2015. 36:
p. 59-74.
[5] Lee, S. Y. & Ohtake, F. The effect of
personality traits and behavioral characteristics
on schooling, earnings and career promotion.
Journal of Behavioral Economics and Finance,
2012. 5: p. 231-238.
[6] Morgeson, F. P. & Humphrey, S. E. The work
design questionnaire (WDQ): Developing andvalidating a comprehensive measure forassessing job design and the nature of work.
Journal of Applied Psychology, 2006. 91:
1321-1339.

CONCLUSIONS
Based on the results of data analysis in thisstudy, it can be concluded as follows:
1. There is a significant positive direct impact on
the variable task variety of the agriculturalextension worker in Banten Province, meaningthat if there is a positive change in the task
variety of agricultural extension worker, it results
in an increase in the agricultural extension
service.
2. There is a significant positive direct impact on
career promotion variables on the rewards ofagricultural extension workers in Banten
Province, meaning that if there is a positivechange in the rewards of agricultural extension
worker, it will result in an increase in the rewardsof agricultural extension worker.
3. There is a significant positive direct impact on
the variable of task variety on the performance ofagricultural extension workers in Banten
Province, meaning that if there is a positivechange in the task variety of the agriculturalextension worker, it will lead to an increase in
the performance of agricultural extension
workers.
4. There is a positive direct impact not significant
on career promotion variables on theperformance of agricultural extension workers in
Banten Province, meaning that if there is apositive change in the agricultural extension
career promotion, it does not result in an increasein the performance of agricultural extension
workers.
5. There is a significant positive direct impact of
reward variables on the performance ofagricultural extension workers in Banten

1955th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DETERMINATION OF HISTAMINE-FORMING BACTERIA, TOTAL
COLIFORM AND ESCHERICHIA COLI IN FERMENTED FOODSPatcharaporn Narkthewan1 and Walaiporn Makkapan1
Food and Agricultural Biotechnology Program, Department of General Science and Liberal Arts,
King Mongkut’s Institute of Technology Ladkrabang Prince of Chumphon Campus, Thailand

1

ABSTRACT
Fermented fishery food products have been generally sold in the local market, Thailand. These products were
frequently contaminated with various microorganisms due to raw material and unhygienic production process.
Determination of microbial contamination of fermented food products helps to assure safety for consumers.
Therefore, the aims of the study were to determine total bacteria, total coliform, Escherichia coli and histamine
producing bacteria from fermented fishery food products commercially distributed in several regions of Chumphon
and Surat Thani provinces. Twenty-two samples of fermented fishery food products were randomly collected forbacterial contamination assay. All samples revealed the levels of pH and salt content in range of 3.67-7.46 and8.46%-29.69%, respectively. The bacterial contamination of the samples was tested by total plate count method.
Determination of coliform bacteria and E. coli was examined by multiple-tube fermentation technique. Total
bacteria, total coliform and E. coli of all samples were in the range of 2.15-7.54 log CFU/g, <3-460 MPN/g and<3-93 MPN/g, respectively. In addition, thirteen histamine-forming bacteria were found on histamine-forming
bacteria isolation agar after incubation at 37°C for 4 days. Five isolates of histamine-forming bacteria named M1,
M3, M9, M11 and M13 were selected to identify by molecular techniques. M1 and M3 were obtained from shrimp
paste (Kapi) and M11 was obtained from fermented fish (Pla Pang Dang). They were identified asEnterobacter sp. M9 and M13 isolated from fermented fish (Pla Som and Pla Ra) were identified as Citrobacter
farmeri and Staphylococcus kloosii, respectively.
Keywords: Fermented food, Histamine, Enterobacter sp., Citrobacter farmeri, Staphylococcus kloosii

INTRODUCTION

decarboxylases produced by many bacterial strains.
Histamine-forming bacteria were found in fermented
food products such as Bacillus coagulans [9],B. megaterium [9], [11], B. subtilis, Staphylococcus
pasteuri [4], [5], S. capitis [4], [5], Enterobacter sp.
[14].
The high amounts of biogenic amine (mainly
histamine) and pathogenic bacteria in fermented
foods also increase consideration on food safety.
However, a few reports have been presented inhistamine-forming bacteria and pathogenic bacteria
in fermented fishery food products in Thailand. The
objective of this research was, therefore, toextensively determine the contamination of bacterial
pathogens in traditional fermented food fisheryproducts sold in the local market of southern areas(Chumphon and Surat Thani provinces).

Fermented fishery food products such as
fermented fish products (Pla Som, Pla Pang Dang and
Pla Ra), fermented fish entrails, fermented molluscs
and shrimp pastes are the Thai traditional fermented
products. Fermented fish entrails and shrimp pastes(Kapi) are mainly consumed in southern parts ofThailand. However, Pla Ra is normally consumed in
the northeastern regions of Thailand.
Biogenic amines are formed mainly through thedecarboxylation of specific amino acids. They arebasic nitrogenous compounds occurring in foods,
especially fermented foods such as kimchi [1],mustard pickle products [2], fermented soybean
products (miso, douchi, natto and soybean paste)[3]-[6], fermented meat [7], and fermented seafood
products [8]-[11]. The quantity and types of biogenic
amines formed in fermented food products arestrongly influenced by the food composition,
microflora and by other factors which allow bacterial
growth during food processing and storage [12].
Histamine, a biogenic amine is causative toxin of
scombroid (a food-borne chemical agent). Scombroid
poisoning causes of a variety of symptoms including
rash, urticeria, nausea, vomiting, diarrhea, flushingand itching of the skin [13]. Free amino acid, histidine
was catalyzed to histamine through by exogenous

MATERIALS AND METHODS
Sample Collection
Twenty-two samples of fermented fishery foodproducts, including 8 shrimp pastes (Kapi),
1 fermented shrimp, 8 fermented fish (1 Pla Som,
2 Pla Pang Dang and 5 Pla Ra), 2 fermented green
mussel and 2 fermented fish entrails (Tai Pla) werepurchased from the local market in Chumphon and
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SEE - Bangkok, Thailand, Nov.11-13, 2019Surat Thani provinces, Thailand. After purchase, they
were immediately transported to the laboratory forchemical and microbiological analysis.

broth (TSB) and incubated at 37°C for 16-24 h. Afterincubation, the culture was centrifuged at 11,000 rpm
for 10 min. The cell pellet was mixed with 1 ml of
TE buffer (10 mM Tris-HCl; 1 M EDTA; pH 8.0) andlysozyme. The mixture was incubated at 37°C for
90 min. Then, 200 µl of 10% (w/v) sodium dodecyl
sulphate (SDS) was added into the mixture and thereaction was incubated at 60°C for 30 min. The 20 µlof Proteinase K was added into the mixture andincubated at 37°C for 30 min. The equal volume ofphenol: chloroform: isoamyl alcohol was mixed withthe mixture and centrifuged at 11,000 rpm for 10 min.
The supernatant was collected and mixed with the
2 volumes of isopropanol to precipitate the genomic
DNA at -20°C for 30 min. The mixture was thecentrifuged at 11,000 rpm for 10 min. The DNA pellet
was washed with 200 µl of 70% ethanol. The air-dried
DNA pellet was resuspended in 100 µl of the sterilewater. The quality and quantity of extracted DNA
were analyzed by measuring the absorbance at 260
and 280 nm and using agarose gel electrophoresis.
The PCR reaction was performed by using 10 ng
of extracted DNA in a reaction volume of 25 µl,
containing a final concentration of 0.2 µM of eachprimer, 1X TE buffer, 10 µM of each dNTP, and one
unit of Taq DNA polymerase. Amplification
conditions were 98°C for 3 min followed by 30 cycles
at 98°C for 10 s, 55°C for 10 s, 72°C for 30 s, andthen subjected to a final concentration of 72°C for
5 min. The PCR products were then analyzed with anautomatic sequencing system (Apical Scientific Sdn
Bhd, Malaysia). Sequence homology was aligned
using the BLAST tool (NCBI). Phylogenetic tree wasconducted by MEGA 7.0 using neighbor-joining
method.

Determination of pH Measurement and Salt
Content
Each fermented food product (10 g) was
homogenized in 10 ml of distilled water with thesterile blender to make the slurry product. The pH ofslurry product was measured using pH meter. Salt
content of each sample was investigated according to
the AOAC method [15]. Two grams of samples were
homogenized in 18 ml of distilled water. Then, thehomogenate was titrated with 0.1 M silver nitrate(AgNO3) using 10% w/v potassium dichromate(K2CrO4) solution as an indicator
Microbial Analysis and Isolation of Histamineforming bacteria
Twenty-five grams of fermented food products
were added into 225 ml of 0.05 M potassium
phosphate buffer (pH 7.0) and homogenized withsterile blender for 2 min. The homogenates wereserially diluted (1:10) with a sterile potassium
phosphate buffer (pH 7.0) in triplicate. The
suspension (1 ml) was poured onto Petri dishes (9 cm
diameter). Then, 15-20 ml of plate count agar (PCA)
containing 0.5% NaCl was added and gently mixed.
After solidification of agar plate at room temperature,
total bacterial colonies were determined after theplates were incubated at 37C for 48 h. The bacterial
numbers were then expressed as logarithm of colony
forming unit per gram (log CFU/g). Total coliformand E. coli in fermented food samples were
performed using the three-tube most probable number(MPN) method [16].
For histamine-forming bacteria isolation, 0.1 mlof the diluted sample was spread on histamineforming bacterium isolation agar (HBI agar)
supplemented with L-histidine according the methodof [17]. After 4 days of incubation at 37C, colonies
with blue or purple color on the plates were pickedand further streaked on trypticase soy agar (TSA) toobtain pure colonies.

RESULTS AND DISCUSSION
Twenty-two fermented fishery food products
were categorized into 2 groups (salty taste and salty
and sour taste) based on the taste of fermented foodproducts. The fermented food products with salty
taste were Kapi, Pla Ra and Tai Pla. The productswith salty and sour taste were Pla Som, Pla Pang
Dang, fermented shrimp and fermented green mussel.
The levels of pH, salt content, total bacteria, total
coliform and E. coli in all products were in the range
from 3.67-7.46, 8.46%-29.69%, 2.15-7.54 log CFU/g,<3-460 MPN/g, and <3-93 MPN/g, respectively as
shown in Table 1.
The average pH value (6.03) and the average saltcontent (24.40%) of the fermented food products withsalty taste was higher than the average pH value(4.27) and the average salt content (15.39%) of the
products with salty and sour taste. However, pH value
and salt content of fermented food products did not
relate with the quantity of total bacteria, total coliformand E. coli. Thai Community Product Standards are
requirement of quality that makes the reliable andMolecular Identification of Histamine-forming
isolates
The identity of the presumptive histamineforming isolates was carried out by amplifying andsequencing approximately 1400 bp of 16S ribosomal
DNA (rDNA). The 16S rDNA gene was amplified
withtheuniversal
primers:
F27(5’
AGAGTTTGATC(A/C)TGGCTCAG3’) and R1492(5’TACGG(C/T)TACCTTGTTACGACTT3’) [18].
The selected presumptive histamine-forming
isolates were inoculated into 2 ml of trypticase soy
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 Values of pH and salt content of fermented fishery food products, total bacteria, total coliform andE. coliCategory of fermented food samples

No. ofSamples

pH

Salt content(%)

Salty taste- Shrimp paste (Kapi)- Fermented fish (Pla Ra)- Fermented fish entrails

15

4.49-7.46(6.03)

18.02-29.69(24.4)

Salty and sour taste- Fermented fish (Pla Som)
- Fermented shrimp- Fermented fish (Pla Pang Dang)- Fermented green mussel

73.67-4.76(4.27)

27.14-8.46(15.39)Total
bacteria(log CFU/g)
2.15-7.54

Total
coliform(MPN/g)< 3-460

E. coli(MPN/g)2.79-7.52< 3-53< 3-93< 3-43

Note: the value in the parenthesis is the average value of each data.
acceptable community products and increases theconfidence to consumers. The standard regulation ofsome fermented food products according to Thai
Community Product Standards reveals that the pH
value of Pla Som and fermented shrimp must notexceed 4.6. In addition, the salt content of Kapi, Tai
Pla and Pla Ra are not lower than 12%. The results of
pH value and salt content in this study were similarity
with the several previous reports. Values of pH andsalt content in fish sauce, fish paste and shrimp paste
were 4.8-6.5 and 16.2%-45.3%, respectively [9]. The

traditional fermented products (soybean and black
bean douchi products) had the pH values and saltcontents of 4.7-5.9 and 4.4%-14.0%, respectively [4].
The level of pH and salt content in fish sauces werein the range of 4.8-5.7 and 15.6%-25.7%, respectively[19]. The traditional soybean pastes of Doenjang had
the pH values in the range of 4.8-6.0 [6]. The
traditional Rihaakuru (fish paste) from the Maldives
had the pH values of 5.62-6.18, whereas salt content
of 1.4%-1.6% was lower than this study [10]. The pH
values and salt contents in salted seafood products

Fig. 1 Phylogenetic analysis of M1, M3 and M11 was constructed based on 16S rDNA sequences using theneighbor-joining method in the MEGA 7.0. The numbers in the phylogramnodes indicated the bootstrap value (%).
198

SEE - Bangkok, Thailand, Nov.11-13, 2019were in the range from 3.58-7.47 and 2.34%-21.51%,

Pla Ra, respectively. The M1, M3 and M11 isolate
were identified as Enterobacter sp. (Fig. 1). The M9
isolate was highly homologous to Citrobacter farmeri(Fig. 2). The M13 isolate had a homology with
Staphylococcus kloosii (Fig. 3). The Enterobacter sp.
was identified as histamine former isolated from tuna
dumpling [14]. E. cloacae isolated from salted
mackerel were found to be weak histamine former[8]. E. cloacae were also identified as weak histamine
former isolated from mustard pickle products [2].
Staphylococcus sp. was mostly found as histamine
formers in fermented foods. S. capitis and S. pasteuri
were found as a histamine former in the mustard
pickle products [2] and douchi [4].

Fig. 2 Phylogenetic analysis of M9 was constructedbased on 16S rDNA sequences using the neighborjoining method in the MEGA 7.0. The numbers in thephylogramnodes indicated the bootstrap value (%).
respectively [11]. The pH is an important factor for
fermentation and formation of biogenic amines
because amino acid decarboxylase activity remains
stronger in an acidic condition [20].
The quantity of total bacteria was 2.15-7.54
log CFU/g obtained from fermented food products inthis study. However, the standard regulation of total
bacteria in fermented food is not reported in Thai
Community Product Standards. Several previous
studies determined aerobic plate count (APC) in
fermented food products. Fermented fish products
were obtained 1.0-4.2 log CFU/g of APC [9].
Soybean douchi and black bean douchi showed
6.6 log CFU/g of APC and 7.5 log CFU/g of APC,
respectively [4]. Moreover, salted seafood products
had 1.08-7.2 log CFU/g of APC) [11].
Total coliform and E. coli in all tested samples
were <3-460 MPN/g and 3-93 MPN/g, respectively
as shown in Table 1. Twelve fermented food samples
was found <3 MPN/g of total coliform and E. coli.
The quantities of E. coli in the fermented foods
according to Thai regulatory level must be <3 MPN/g
whereas the quantity of total coliform in theseproducts is not reported. Comparison with fermented
food products in the previous studies such as mustard
pickle products, soybean douchi products, salted
seafood products, none of these products contained
total coliform and E. coli [2], [4], [11]. The results ofthe study indicated that the bacterial contamination of
fermented fishery food products may be caused frombacterial flora in the raw materials and the bacterial
contamination during fermentation process.
From twenty-two fermented fishery food samples,
thirteen histamine-forming bacteria were obtained
after incubation at 37C for 4 day. Five bacterial
isolates (M1, M3, M9, M11 and M13) were selected
to identify by the universal primers targeted to the
16S rDNA gene. The 1400-bp amplicons obtained
from each isolate were analyzed and compared withother reference strains from GenBank using the
BLAST tool. Bacterial isolates (M1 and M3) wereisolated from Kapi. The other isolates (M9, M11 andM13) were isolated from Pla Som, Pla Pang Dang and

Fig. 3 Phylogenetic analysis of M13 was constructedbased on 16S rDNA sequences using the neighborjoining method in the MEGA 7.0. The numbers in thephylogramnodes indicated the bootstrap value (%).
CONCLUSIONS
Total bacteria, total coliform, E. coli andhistamine forming bacteria were determined infermented fishery food products. The presence ofE. coli found in some products were out of Thai
regulatory level (<3 MPN/g). Moreover, the study of
the research demonstrated the incidence of histamineforming bacteria (Enterobacter sp., C. farmeri and
S. kloosii) in fermented fishery food products.
Therefore, further studies are to determine thequantity of histamine contents in fermented fisheryfood products for food safety assessment.
ACKNOWLEDGMENTS
The authors greatly appreciate Biotechnology
Laboratory, King Mongkut’s Institute of Technology
Ladkrabang Prince of Chumphon Campus forprovidingthelaboratory
facilities
andMiss Suwanan Sangthong for assisting the research.
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Cheng S.H., Wei C.I., and Hwang D.F.,
Occurrence of Histamine and HistamineForming Bacteria in Kimchi Products in Taiwan.
Food Chemistry, Vol. 90, 2005b, pp. 635-641.
199

SEE - Bangkok, Thailand, Nov.11-13, 2019[2] Kung H.F., Lee Y.H., Teng D.F., Hsieh P.C.,
Wei C.I., and Tsai Y.H., Histamine Formation by
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200

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

VITAMIN AND MINERAL CONTENT OF SIX NATIVE VARIETIES OF
RICE IN THAILAND
Intira Lichanporn1, Nanchanok Nantachai1, Palida Tunganurat 1, Unchalin Singkhum1, Nowapor
Lapsongphon1, Anchalee Sawatthum1, Ratchata Tonwitowat 1, Tongmee Mosom1 and Purin Akkarakultron
1
Faculty of Agriculture and Technology, Rajamangala University of Technology Thanyaburi, Phathumthani
12130

ABSTRACTThe objective of this research was to examine the vitamin and mineral contents present of the native varieties
of six rice varieties (Sangyod, Khaw kin, Mali nil surin, Khaw heniyw lump haw, Khaw kla heniyw andThabthim chumphae) in Thailand. Results showed that Mali nil surin had the highest vitamin E content (0.25mg/100 g) and Khaw kin had higher iron (5.08 mg/100g) than that other rice. Khaw kla heniyw had the highfolic acid content (88 mcg/100g) and niacin content (4.12 mg/100g). Folic acid and niacin of Khaw heniyw lum
phaw had the lowest (9 mcg/100g and 3.11 mg/100g) while, Khaw kin and Khaw kla heniyw had the lowest
vitamin E and iron (0.09 and 0.30 mg/100g). Therefore, rice is a good candidate for natural sources ofnutritional and medicinal properties and may hold the potential for the development of rice-based beauty
products, functional foods, drugs, and natural food preservatives.
Keywords: Native varieties of rice, folic acid, ironmetabolically active forms in the human body [10].
The synthetic form of folic acid is the folate found insupplements and fortified foods. This is the morestable form and occurs unusually in foods or thehuman body [8]. The aim of the research was to
examine the vitamin and mineral contents present of
the native varieties of six rice varieties (Sangyod,
Khaw kin, Mali nil surin, Khaw heniyw lump haw,
Khaw kla heniyw, and Thabthim chumphae) in
Thailand, they’re a good candidate for natural
sources of nutritional and medicinal properties.

INTRODUCTION
Rice (Oryza sativa), is known as the grain of life
and is similar to food for Asians [1]. Over 2 billion
people in Asia alone arise 80% of their energy needsfrom rice, which contains 80% carbohydrates, 7-8%
protein, 3% fat, and 3% fibre [2]. Paddy rice is agood specialist of thiamine (vitamin B1), niacin(vitamin B3), and vitamin B6 [3]. The B-complex
vitamins, especially thiamin, riboflavin and niacinpresented by natural brown rice promote youthfulenergy and nourishment to skin and blood vessels[1]. Rice bran also holds beneficial anti-oxidations
like tocopherols and tocotrienols (of the Vitamin E
family) and oryzanols [4]. Red and black rice arefull in iron (Fe), zinc (Zn) and minerals [5]. Zinc andiron are required by the human body for enzymatic
processes and haemoglobin production, respectively[1]. Iron is a considerable factor affecting its
absorption and hence affects iron status. In cereal
foods, phytate is the most important absorption
inhibitor, binding nonheme iron, zinc, and calcium
in an insoluble complex in the intestine, making it
unavailable for absorption [6][7]. Folates are an
essential nutrition component (an important B
vitamin) in the human diet, concerned in many
metabolic pathways, mainly in carbon transfer
reactions such as purine and pyrimidine biosynthesis
and amino acid inter-conversions [8]. Folates
survive as vitamers (one carbon folate derivatives)that are polyglutamate with varying oxidation statesand substituents [9]. Folates survive in two formsNaturally occurring folates are found in foods and

EXPERIMENTAL METHODS
1. Preparation of Paddy
Rice, six varieties of Sangyod, Khaw kin, Mali
nil surin, Khaw heniyw lump haw, Khaw kla heniyw,
and Thabthim chumphae, Thailand were used. Ricegrains were ground by the mortar and pestle andanalyzed according to the technique described above.
2.

Vitamin E
The following vitamin E was measured byhigh performance liquid chromatographic methods.
Vitamins E (a-tocopherol) were determined after
alkaline saponification [11].
3. IronIron content was measured by the method
described by AOAC, 2016. 984.27 [12]4.

201

Folic acid
Folic acid was determined by In house

SEE - Bangkok, Thailand, Nov.11-13, 2019

method based on AOAC 2016. 960.46 [13].
5. Niacin (Vitamin B3)
Niacin was determined by the colorimetricmethod (AOAC 2016. 961.14) [14].

hence affects iron status [1]. For rice levels ofphytate informed in the literature range from 0.87 to
3.7 mg/g of dry matter, which equals 0.09-0.37%[18] [19] [20]. In table 1, the iron of Khaw kin was
highest as 5.08 mg/100g, while Khaw kla heniyw
was lower than the other samples as 0.30 mg/100 g.
Iron is demanded by the human body for enzymatic
processes and hemoglobin production, respectively[1].

RESULTS AND DISCUSSION
The color of the varieties is deep red (Sangyod),light red (Khaw kin), purple rice (Mali nil surin andKhaw heniyw lum phaw), red and purple (Khaw kla
heniyw) and light red (Thabthim chum phae) (Figure
1A-F). The deep red and purple colors of varieties
are comparable more nutritious. The red/purple or
brown unpolished rice is a healthy food because it
provides with rice bran, thin brown coating between
rice kernel and protective hull provides mankind
greatest nutritional needs [15]. In Chhattisgarh of
India, Layacha variety is effectively used to cureboil caused on scalpel of the newly born child. The
mother of the child eats cooked rice of the variety,useful to heal the boil of the child who consumes
mother milk. Cooked grains of Layacha variety isbeneficial for pregnant women to prevent unborn
children from contracting Laicha disease (skininfection) [15].

Table 1. Vitamin E and Iron of six native varieties ofrice
Native varieties of Vitamin E
Iron
rice
(mg/100g)(mg/100g)
Sangyod
Khaw kin
Mali nil surin
Khaw heniyw lum
phaw
Khaw kla heniyw
Thabthim chumphae

0.11
0.09
0.25
0.18

0.99
5.08
0.78
1.31

0.14
0.11

0.30
0.51

Khaw kla heniyw had highest folic acid,compared with Sangyod, Khaw kin Mali nil surin,
Khaw heniyw lump haw and Thabthim chumphae(Table 2). Folic acid is to prevent neural tube defects(NTDs), which are an important cause of perinatal
mortality and infantile paralysis worldwide [21].
Table 2. Folic acid and Niacin of six native varietiesof rice
Native varieties of
Folic acid
Niacinrice(mcg/100g)(mg/100g)

Figure 1. Characterizes of paddy in Pathum Thani
Rice Province; Sangyod (A), Khaw kin (B), Mali nil
surin (C), Khaw heniyw lum phaw (D), Khaw kla
heniyw (E) and Thabthim chumphae (F).

Sangyod
Khaw kin
Mali nil surin
Khaw heniyw lum
phaw
Khaw kla heniyw
Thabthimchumphae

The rice Mali nil surin had the highest vitamin E
content (0.25 mg/100g) and Khaw kin had thelowest vitamin E content (0.09 mg/100g) (Table 1).
Studies have confirmed beneficial qualities such as
the high biological value of vitamin E in brown rice(0.90-2.50 mg/100g) and milled rice (0.75-3.00 mg/100 g) [2]. Rice also holds beneficial anti-oxidants
like tocopherols and tocotrienols (of the “Vitamin E
family) and oryzanols [4]. Researchers have
explored the anti-cancer activities of tocopherols[16]. While the color of red and purple rice is full inanthocyanin and tannins which possess antioxidant
and anti-inflammatory properties [1]. Mali nil surinof the varieties is purple color and high richantioxidant of anthocyanin. Khonkaen rice seedcenter [17] have also found that antioxidants andanthocyanins of Mali nil surin were at 117 mg/kg
sample and 219.03 mg/kg. Bioavailability of iron isa considerable factor affecting its absorption and

31
32
44
9

4.18
3.71
3.95
3.11

88
41

4.12
3.19

Niacin of Sangyod and Khaw kla heniyw had
4.18 and 4.12 mg/100g, while Khaw kin, Mali nil
surin, Khaw heniyw lump haw, and Thabthinchumphae had 3.71, 3.95, 3.11 and 3.19 mg/100 g,
respectively. Niacin is the vitamin B3 and has basicroles as part of reduction/oxidation coenzymes
involved in energy metabolism, amino acidmetabolism, and detoxification reactions for drugs
and other substances. Niacin comes from in any
forms: (1) nicotinic acid (pyridine-3- carboxylicacid) [22], (2) nicotinamide (nicotinic acid amide),and (3) other derivatives (e.g., inositol
hexanicotinate) “that exhibit the biological activityof nicotinamide” [23].

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Lampi, A.M., Shmelev, A., Salovaara, H., et al.,Production of folate by bacteria isolated fromoat bran, International Journal of Food
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41-47.
[10] Food and Nutrition Board, Institute of Medicine,
Folate, 1998, pp. 196-305[11] Speek A.J., Schrijver J., and Schreurs W.H.P.,
Vitamin E composition of some seed oils as
determined by high-performanceliquidchromatography with fluorometric detection,
Journal of Food Science, Vol. 50, 1985, pp.
121-124.
[12] AOAC., AOAC Official Method 984.27
Calcium, Copper, Iron, Magnesium, Manganese,
Phosphorus, Potassium, Sodium, and Zinc in
Infant Formula Inductively Coupled Plasma
Emission Spectroscopic Method. AOAC
Official Methods of Analysis. 20th ed. AOAC
International. Gaithersburg. MD.2016.
[13] AOAC., AOAC Official Method 960.46
Vitamin assays, Microbiological Method.
AOAC Official Methods of Analysis. 20th ed.
AOAC International. Gaithersburg. MD.2016.
[14] AOAC., AOAC Official Method 961.14 Niacin
and niacinamide in drugs, foods and feeds. The
colorimetric method, Final action 1962, in theofficial. AOAC Official Methods of Analysis.
20th ed. AOAC International. Gaithersburg.
MD. 2016.
[15] Rahman S., Sharma M.P., and Sahai S.,
Nutritional and medicinal values of someindigenous rice varieties, Indian Journal of
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pp. 454-458.
[16] Kline K., Yu W., and Sanders B.G., Vitamin E
and Breast Cancer, The Journal of Nutrition,
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[18] Prynne C.J., McCarron A., Wadsworth M.E.J.,and Stephen A.M., Dietary fibre and phytate; abalancing act. Results from 3-time points in a
British birth cohort. British Journal of Nutrition,
Vol. 103, 2010, pp. 274–280.
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I.S., The decreased molar ration of phytate:zinc
improved zinc nutriture in SouthKoreans for the
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malnourished children 6 months to 5 years ofage, Food and Nutrition Bulletin. Vol. 30, 2009,
pp. S434–S405.

CONCLUSIONS
Thailand is many rice varieties that havemedicinal properties and Khaw kla heniyw had
higher the folic acid and niacin than other verity
rice. While, Khaw kin was high the rich of iron anda much of vitamin E as Mali nil surin.
ACKNOWLEDGMENTS
Financial support for this work was provided thePlant Genetic Conservation Project under the Royal
Initiative of Her Royal Highness Princess Maha
Chakri Sirindhorn, Thailand. We thank the Facultyof Agricultural Technology and Institute of Researchand Development, Rajamangala University ofTechnology Thanyaburi. Finally, we would like tothank Pathumthani Rice Research Center for thenative varieties of rice in Pathum Thani Province.
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[23] Institute of Medicine (IOM), Dietary Reference
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204

5thInt. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

AFM VISUALIZATION OF PHYTOPLASMA DNA IMMOBILIZATION
AND HYBRIDIZATION EVENT ON CHITOSAN MODIFIED SPCESURFACE1

Porntip Wongkaew1, Buddhapala Wongkaew2
Faculty of Agriculture, KhonKaen University, Thailand,
2
Metropolitan Waterworks Authority,

ABSTRACTThe evidence of DNA immobilization and hybridization on a functional surface is demonstrated in thispresentation following the high resolution atomic force microscopic (AFM) direct observation. A planarfunctional surface was fabricated by self-assembly of a biopolymer chitosan onto screen-printed carbon electrode(SPCE) concerning to its excellent covalent bonding binding of biomolecules. The target DNA molecules wereextracted from important phytoplasma diseased plants such as sugarcane white leaf (SCWL), burmuda grass
white leaf (BGWL) and sesame phyllody (SP). The real image in actual posture of long chain natural DNA andthe well-known structure of the DNA double helix were obviously visualized following the DNA immobilizationand subsequent transitional hybridization with their complementary DNA. The coordinate quantitative
parameters of AFM images such as line profile analysis, surface roughness, power spectrum density (PSD)
algorithm and fractal dimension were also determined. The width size of double stranded DNA and the specifichybrid DNA were apparently almost 2 folds bigger than their single stranded DNA. Whereas an aggregation andgrowth mechanism of those DNAs on chitosan modified SPCE surfaces were mainly stacked in vertical direction
and grown beyond a diffusion limited model as indicated by their fractal dimension values around 2 to 3. Thisphenomenon is hence valuable for the verification and the efficient development of diagnostic DNA-based
devices.
Keywords: Atomic force microscope, Chitosan modified SPCE, DNA immobilization and hybridization,
Realactual image[5]. Therefore immobilization and hybridization of
the DNA on transducer surface is exactly critical for
desirable sensitivity and specificity including overallmeasurable electronic signal generation of thebiosensor.
A direct physical anchor of DNA on the capture
molecules at a basal electrode surface is one of themost common immobilization approaches. This
procedure involves the simple electrostatic selfassembled layer by layer technique [1], [2], [5].
Selection of a proper working platform is crucial forthis type of DNA immobilization and fabrication of
the DNA sensor. Previous studies on theestablishment of high conductivity and bioaffinity
modified electrodes using the versatile chitosan
biomaterial have been sequentially reported [1]-[5],[7], [8]. However, a study in more criteria details
both quantitatively and morphologically is stillneeded to elucidate the reality of hybridization
dynamics especially the classical double helix
forming postulated by Watson and Crick [10] that noone could actually see it ever.
With reference to those excellent advantages of
the chitosan modified electrodes previously reports,
this current study was further motivated using three
genomic DNA, each, from phytoplasma pathogens
that cause important plant diseases in Thailand [11]such as sugarcane (Saccharum officinarum L.) white

INTRODUCTION
At present, biosensing technology has perceived
a profound attention due to human life necessity for
accurate, specific, ultrasensitive and speedy
automatic point of care diagnostic tools. Ubiquitous
applications including healthcare monitoring of
human, animal husbandry, plant production, foodand environment security are growing adopted [1][4]. For decades, researches on coupling
biomolecules with electronic detection devices havebeen pursued for effective sensing application.
Several biological elements and molecules such as
cells, antibodies, enzymes, receptor proteins, lectins,
and nucleic acids are considerately competent.
Among these, DNA (Deoxyribonucleic acid) has
attracted intensive focus according to its structural
versatility and genetic functionality that makes a top
capacity for target discrimination. Typically, DNA
based biosensing system is manipulated throughfunctional surface sensor containing the selected
single stranded DNA molecule attached onto anelectroactive transducer. The target detection issubsequently operated on the most selective
reactions in nature basis of nucleic acidhybridization that allows several readout strategies
such as colorimetry, spectroscopy, electrophoresisand especially the electrochemical signalling [1], [2],205SEE - Bangkok, Thailand, Nov.11-13, 2019leaf (SCWL), burmuda grass (Cynodon dactylon L.)
white leaf (BGWL) and sesame (Sesamum indicumL.) phyllody (SP) as representative illustrations for aclose investigation of the actual hybridization event.
The AFM was employed for the intensive
speculation due to its superb efficiency in imaging at
micro and nanoscale over than other devices at thismoment. This microscopy not only offers thecapacity to visualize nanometric features in two andthree dimensions but also the physicochemical
characteristics including its spatial distribution
mapping of surfaces at different stages of themolecular assembly. Moreover, observation can bedirectly performed without any special preparation
requirement [3], [4], [7], [8], [12]. In a while,
successful direct visual evidence of DNA
immobilization and hybridization phenomena could
be captured and ascertained by the AFM imaging
andcorresponding
quantitative
topographic
parameters. The first real image of the being tie inhelical posture of the complementary DNA couple
during a hybridization event could also be validated
in this article.

Preparation of Chitosan modified electrodeplatform
Chitosan solution (1%, w/v) was done bydissolving 1 g chitosan in 100mL of 1% (v/v) acetic
acid solvent and the solution was filtered to remove
insoluble materials. A self-assembled monolayer ofchitosan was formed on carbon working spot of
screen-printed carbon electrode (SPCE) by applying
a 3.0 μl drop of chitosan solution and naturally dried
up at room temperature. The modified working
surface was then fixed with a 10μl drop of 0.1 M
NaOH for 30 min and left it dried again prior to use.
Nucleic Acid Extraction
The phytoplasma DNA from diseased SCWL,
BGWL and SP, each was extracted following the
CTAB-phenol-chloroform method [13] from midribof the leaves, the plant sieve elements where most
phytoplasma cells are colonized [11]. The extracted
DNA was purified by repeating this procedure again
to get at least the purity index of 1.8 at A260/A280
ratio for a suitable direct use in the immobilizationand hybridization trials. Its concentration was thenquantified spectrophotometrically from the value
measured at A260. The Challenging target nucleic
acid from healthy plants was also extracted frommidrib of the leaves by similar method. Stocksolution of each nucleic acid sample was maintainedin 10 mMTris HCL pH 8.0 containing 1 mM
Sodium EDTA (TE buffer) and kept frozen. The
ssDNA was achieved by denaturing its native
dsDNA in 100˚C water bath for 10 min and followedby rapid cooling in ice bath. This type of ssDNA
was also prompted for subsequently used as probe to
its complementary DNA hybridization.

MATERIALS AND METHODS

Materials
Screen printed carbon electrode (SPCE) model
DRP-150 consisting of 4 mm spot carbon as
working electrode surrounded with a counterelectrode platinum line and a reference electrodesilver line was provided by DropSens, S.L. Llanera(Asturias) Spain. Chitosan at 85% degree ofdeacetylation with a molecular weight of 0.28 kDa
was obtained from Bioline Lab, Co., Thailand.
Analytical graded chemicals for reagent preparation
were purchased from Sigma-Aldrich Co. LLC, USA
and Ajax Finechem Pty, Ltd., Australia. High purity
deionized water of 18.2 MΩ from Milli-Q RG
system (Millipore Corporation, MA, USA) was usedin all solutions. The diseased samples, sugarcane
white leaf (SCWL) , burmuda grass white leaf
(BGWL), and sesame phyllody (SP) from collection
maintained in the insect proof disease nursery of
Plant Pathology Division of the Faculty ofAgriculture, KhonKaen University, were used for apure source of each causal phytoplasma DNA
extraction . Healthy sugarcane, burmuda grass andsesame maintaining far apart in another insect proof
nursery were brought as the challenge controls.
Preliminary confirmation for the absence orexistence of each causal phytoplasma was done by
PCR with a set of specific primer pair of both the
16S rDNA and 16-23S rDNA reported earlier [9].

Immobilization of DNA
The chitosan modified SPCE surface was
employed as working platform for every challenging
DNA immobilization experiments. Each DNA
sample was immobilized by dropping 2 μl of its 10
μM inTE buffer onto the chitosan-modified SPCE
platform and allowed to incubate overnight at room
temperature. This functionalized surface was rinsed
with 0.1% SDS phosphate buffer (pH 7.0) threetimes to remove the unbound DNA and dried atroom temperature prior for the next manipulation.
DNA hybridization
Hybridization, a reaction that is commonly
recommended as an indication for specificrecognition of the complementary DNA strand wasdue in this investigation. The reaction was
performed by overspreading the ssDNA probe206

SEE - Bangkok, Thailand, Nov.11-13, 2019

functionalized spot surface of chitosan modified
SPCE with a 3 μl droplet of 2 × SSC solvent
containing 10 ng/μl challenging target ssDNA andkept incubating at 42˚C for 40 min. Afterward it wasrinsed three times with 0.1% SDS phosphate buffer(pH 7.0). The testing hybridization performance wasthen ready for inspection after a minute of natural
drying in air at room temperature.

on the working surface of chitosan modified SPCE
which adequately allowed stable and good quality
AFM image without any complicate treatment. It isindeed due to an excellent affinity of the naturalchitosan polymer consisting of polycation function
compatible for biological molecules including
proteins, enzymes and DNA [1]-[5], [7], [8]. This
multiple cation site chitosan matrix has been proved
highly effective for immobilization of the DNA
molecule in our previous experiments [1], [2], [5].
Its electrochemical capability has also beensubsequently approved [7]. Affirmation on the DNA
incident on the platform surface was proceed by theline analysis of AFM image using power spectral
density (PSD) function of the waveguide algorithm.
The PSD outcome is as illustrated in Fig. 2 that thedensity peak size of each DNA strand type could be
obviously differentiated, the biggest PSD wave from
dsDNA and the smaller two PSD waves from theother two ssDNA.

AFM imaging and analysis
A nanoscale
imaging
for the DNA
immobilization and progressive hybridization event
was carried out by an atomic force microscopemodel XE-70 (Park Systems Corp., Suwon, Korea)
through a true non-contact mode. The observation
was done under ambient conditions with standard
PPP-NCHR silicon cantilever consisting of a < 10
nm tip radius (Nanosensors TM, Neuchâtel,Switzerland) with a spring constant of 42 N/m force
constant and resonant frequency of 320 kHz. An x-y
accessible 1×1up to 5×5 μm area with a Z scanner at
0.5 Hz scan rate was inspected with XEP softwarefor data acquisition and XEI software for image
processing and quantitative analysis of the surface
topography. Relevant parameters such as line profile,
an average roughness Ra (nm), standard deviation of
the height value Rq (nm), skewness (Rsk), kurtosis(Sku), power spectrum density (PSD) algorithm, andfractal dimension were then successively identified.

RESULTS AND DISCUSSION
AFM image and characterization of the dsDNA
and ssDNA immobilized on chitosan modified
SPCE

Fig. 1 Three-dimensional AFM image at 11 mscan size revealing surface morphology of dsDNA
and the two ssDNA strands splitting from thedsDNA.

A striking atomic force microscopy image of theintact double-stranded DNA (dsDNA) and its
correlative two Single-stranded DNA (ssDNA)
during the DNA strand separation consequence isperfectly manifested in Fig.1. This picture, in themean time, declares a fiduciary distinguishingfeature between the dsDNA and ssDNA molecules.
Observation in all cases of the phytoplasma DNA
from SCWL, BGWL and SP similarly andconsistently presented the duplex dsDNA andssDNA profiles as well (data not shown). In general,
differentiation in UV light absorption measurement
is the only technique for notifying the separation of
the DNA strands [14]. The attained AFM image
could thus be considered as the first direct visualevidence revealing a DNA separating posture
simultaneously after the common denaturation
process by heating. An important prerequisite one
for this successful imaging is on account of a steadyimmobilization strategy. In our investigation, a DNA
containing TE buffer droplet was simply deposited

Fig. 2 Power spectral density (PSD) function of
the waveguide analyzed along a line in the AFM
image of dsDNA and the two ssDNA strands
splitting from the dsDNA at 11 mscan size.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

AFM image revealing the conformation ofcomplementary DNA strands upon hybridization
The hybridization scheme was performed on
chitosan modified SPCE working surface. This
presentation represents a generous process gained
from SCWL, BGWL and SP phytoplasma genomic
DNA. The ssDNA recognition probe was firmly
immobilized and subsequently hybridized with its
complementary ssDNA target to form complete
dsDNA molecule thatcan be detected
simultaneously by an appropriate read-out systems
such as the electrochemical voltammetry and the
AFM in our cases [1], [2], [5], [7], [9]. By means of
the non contact mode AFM observation, thehybridization incidence was directly visualizedshowing the duplex helical DNA tile forming clearly(Fig. 3). This AFM image indicates a dynamic of
DNA hybridization since the beginning of the wellknown Watson-Crick double helix state. The twocomplementary nucleotide strands were being tie toeach other like a two ply rope with a right handappearance. Herein, to our knowledge this captured
image should also be the first direct visible double
helix structure forming during the DNA
hybridization. Successful direct imaging of the DNA
hybridization in this simple technique was obtainedby no harm or any damage to the DNA specimen
which probably due to an excellent bioaffinity andprotective effect of chitosan scaffold. Acceleration
in DNA hybridization rate by two orders throughfacilitation of a nucleation step; a major rate
determining step of hybridization was previously
demonstrated in cationic polymer such as poly(Llysine)-graft-dextran
copolymer
employingfluorescence-based assay [15]. The multiple cationicnature of chitosan polymer was therefore assumed to
be an important factor accelerating the DNA
hybridization which was found almost complete
within 45 min in our observation. Meanwhile the
combination trials of phytoplasma ssDNA with
ssDNA from their healthy sugarcane, burmuda grassand sesame plants yielded no sign of couple pairing
or tying frame, hence referring to a mismatching
nature of these non complementary strands.

Fig. 3The tying complementary ssDNA strands into
two-ply strand of the renowned double helix DNA
captured image by AFM at 11 m scan size.

The DNA statures appeared in AFM images were
estimated by their x, y and A values fromdifferent cross sections lines to define a
differentiation between the dsDNA and ssDNA
including the tying hybrid ssDNA pair. These values
were remarkably 1.4 to 1.75 fold higher in dsDNA
and the hybridized DNA than that of the ssDNA.
The PSD values gained from dsDNA and hybridized
DNA were also higher by 2 to 3 folds. Therefore theform of double stranded DNA is apparently bigger
than ssDNA by at least 1.4 orders. The fractal
dimension parameter values obtained as 2.37 of thedsDNA and 2.47 of the hybridized DNA explicitedtheir bigger size in comparison to 2.26 of the ssDNA.
On the other hand, the fractal dimension values on
the surface between 2 and 3 are the values
suggesting a top up aggregation of deposit molecule
following a 3D diffusion limited model [16]. In thecourse of roughness profiles Ra and Rq, values
gained from the dsDNA and the hybrid DNA
immobilized surfaces were about 1.34 - 1.73 folds
rougher than the ssDNA. A negative Rsk acquired in
the hill top cases represents a good bearing
platykurtoic surface of the DNA while a morenegative value from the whole platforms indicatesdominant valley surface underneath the DNA tile.
The Rku values at the DNA hill top cases were allless than 3.00 which imply for a gradually varying
feature of the surface. Whereas the values over than
3.00 were from Rku of the whole immobilized
platform and thus explicate an evidence of a highDNA hill laid over the basal surfaces.
The results in this direct visual observation
substantiate a success on steady immobilization andsubsequent progressive hybridization of the long
chain genomic DNA along with their measurable
geographical characteristics. The non contact mode
AFM has delivered considerably excellent resolution

AFM surface parameters concerning the DNAmorphological configuration
To determine the morphological configuration of
the DNA, interpretation of the measured data was
performed with reference to our previous reports [7],[8]. Important amplitude features were resolved byrelevant statistical parameters as shown in Table 1.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

showing both the distinction between two types of
DNA strands and the dynamic of complementary
hybridization event. Although a bit limitation on an
exact assessment was existed owning to the confine
performance of a 10 nm radius standard AFM tip
available at present-day which probably makeinevitable over estimate in the DNA width that has
been formerly reported to be about 2 nm according
to crystallographic X-ray diffraction analysis [17].
More sophisticate AFM techniques were suggested
for better scaling of DNA configuration such as theminiaturization of AFM cantilevers [18]; the use of
frequency modulation AFM [19] and the use of peakforce tapping mode including a typical tapping mode[20]. These techniques were found suitably operated
with DNA aqueous solution samples. However theprocedure of direct non contact mode AFM imaging
in air is generally preferred still due to its simplicity
and non-invasiveness, improvement concerning thenon contact mode hardware including appropriatecantilever and its software combination is thus
necessary. Notwithstanding the confinement of asimplest AFM model used in our investigation, avirtual image of the DNA and its differentiation isclearly demonstrated and sufficiently verified a real
hybridization event empowering the effective of
DNA biosensor performance.

Table 1 Surface profile analyzed from AFM
nanographs of the dsDNA, ssDNA and completely
hybridized DNA at 1x1 m scan size on chitosan
modified SPCE platform.
Parameters

HybridizedDNAx (nm)121.2
87.6
112.67± 11.96± 11.93± 6.43y (nm)
9.33
6.4
11.19
± 2.08± 2.41± 2.45
A
27.7
16.56
28.74
± 3.23± 1.02± 0.72
PSD (nm3) 1 0.033
0.01
0.007
± 0.01±0.001± 0.0012
0.015± 0.008
Fractal
2.37
2.26
2.47
dimension± 0.12± 0.05±0.06
Ra (nm)
9.11
5.26
7.74
± 1.3
± 0.14±0.04
Rq (nm)
9.92
6.71
8.96
± 1.26± 0.17±0.86
Rsk hill
-0.39
-0.75
-0.77
surface± 0.15± 0.085± 0.06
Rskwhole
-0.88
-0.94
-1.05
surface± 0.15± 0.62± 0.09Rku hill
2.21
2.06
2.24
surface± 0.05± 0.042± 0.13
Rku whole
3.48
3.28
3.99
surface± 0.05± 0.3±0.04
Note: A = angle degree of a hill slope, x =horizontal distance y = vertical distance, PSD =power spectral density, Ra = roughness average,
Rq= root mean square roughness, Rsk = skewness,
Rku = kurtosis.

CONCLUSIONSThe present work shows the first image
capturing a striking posture of dsDNA separationand hybridization dynamic through a common noncontact mode AFM observation. A well known
double helix forming state between twocomplementary ssDNA strands could be seen
directly following hybridization process. All thetrials with SCWL, BGWL and SP phytoplasma
genomic DNA yielded similar performance from avery simple immobilization protocol employing theself assembled mechanism of the DNA containing 3µl droplet onto chitosan modified SPCE basal
surface. This successful direct imaging of the DNA
dynamics was simply obtained in air at room
temperature without any deteriorate effects to theobserving DNA. The apparent size of dsDNA andhybridized one seemed to be almost 2 folds wider
than ssDNA. Their aggregation and growthmechanism on the basal platform surface weremainly directed vertically beyond a diffusion limited
model according to the line analysis results. By
virtue of this finding, the reality of DNA
immobilization and hybridization occurring event
empowering an efficacy of the DNA biosensor caneasily be verified and encouraged further
development of real practicable diagnostic devices.

Ds DNAssDNA

ACKNOWLEDGMENTS
The authors gratefully acknowledge KhonKaen
University’s Division of Research and Technology
Transfer Affair for partial funding and the KKU
Research Instrument Center for instrumental
facilitation. We also thank Mr. SupatrChuaymee and
Mr. VorrayuthMekarkat for their AFM technicalassistances.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

IMPROVEMENT THE PROPERTIES OF POLY(L-LACTIDE) FILMS
WITH CELLULOSE FIBER FROM RICE STRAW WASTE INAGRICULTURAL PRODUCTS
Chutima Banthao1, Patcharin Kumpolsan1, Yodthong Baimark1, Sujitra Wongkasemjit2, and Kansiri
Pakkethati1
1
Department of chemistry, Faculty of Science, Mahasarakham University, Mahasarakham 44150, Thailand;
2
The Petroleum and Petrochemical College and the National Center of Excellence for Petroleum,
Petrochemicals and Advanced Materials, Chulalongkorn University, Bangkok 10330 Thailand
ABSTRACTThe poly(L-lactide) films properties were improved by using cellulose from rice straw. The cellulose was
extracted by hydrolysis method and that was confirmed the property by using Fourier transforms infrared
spectroscopy (FT-IR). The sample films were prepared by mixing poly(L-lactide) with cellulose at different weightratios (100/0, 98/2, 96/4, 94/6, 92/8, 90/10). Physical, mechanical and thermal properties of the films were analyzed
by X-Ray diffraction (XRD), Scanning Electron Microscope (SEM), Thermogravimetric Analysis (TGA) andTensile testing. It was found that after increasing the concentration of the cellulose to 2 %wt, the tensile strength
increase from 24.949 to 37.108 MPa and Young's Modulus slightly increase from 0.111 to 0.119 GPa. The thermal
stability of the sample films increased slightly. These results showed that cellulose from rice straw was enhanced
to develop the thermal and mechanical properties of poly(L-lactide) film. The water uptake increased with theaddition of cellulose.
Keywords: Poly(L-lactide), Cellulose fiber, Rice straw
and a problematic fuel source due to high ash
generation, exploring more viable options to utilize
rice straw is pressing, particularly as anenvironmental concern. The composition of ricestraw is cellulose (38.3%), hemicellulose (31.6%),
lignin (11.8%) and silica (18.3%)[15]. In this work
reducing the problems of the environment and adding
value to the rice straw was studied. Improvement themechanical properties and thermal properties of thepoly(l-lactide) films with cellulose fiber from ricestraw was studied in different ratios (0%, 2%, 4%, 6%,
8% and 10% of cellulose fiber).

INTRODUCTION
Nowadays, polymers are used in the daily life of
human which used mostly from petroleum. Because
the polymers are lightweight, inexpensive and highstrength but it is hard to be degradable. Therefore, thebiodegradable polymer is one choice to substitutepolymer from fossil fuel. The biodegradable
polymers are classified according to their origin into
two groups which are natural polymers for example
chitosan[1], chitin[2], starch[3] and silk fibroin[4]and synthetic biodegradable polymers such aspoly(glycolic acid)[5], poly(caprolactone)[6] andpoly(l-lactide). In the decade the researchers areinterested in poly(l-lactide) due to nearby properties
with the petrochemical origin. The outstanding
properties of poly(l-lactide) are renewable[7],biodegrading[8], transparent properties[8]. However,poly(l-lactide) is very brittle[9] and low toughness,
which limits in applications that need plastic
deformation under high stress[10]. Thus, thedisadvantages of poly(l-lactide) were improved bycomposite with bamboo charcoal[11], cotton gin
waste [12], oil palm [13] and cellulose fiber[14].
Thailand is one of rice country so there is a lot of
leftover rice straw after the harvest of rice. Although
the straw is useful for animal feeding or used as amaterial for cultivation of straw mushroom however
the quantity of rice straw is still rested a lot. Therefore,
farmers need to get rid of rice straw by burning, which
resulted in the environmental impact. As rice straw is
a marginal feed compared to other cereal grain straw

MATERIALS AND METHODS
Materials
The poly(l-lactide) (PLLA, molecular weight =100,000), used in this study was supplied by Assoc.
Prof. Dr. Yodthong Baimark. Sodium hydroxide(NaOH, AR grade, Ajax Finechem), hydrogen
peroxide (H2O2, 30-32%, ANaPURE), sulfuric acid
(H2SO4, 98%, ANaPURE) and Chloroform (CHCl3,
AR grade, LLC) were used as received.
Preparation of cellulose from rice straw
Rice straw from agriculture was cut in the lengthof 1-2 cm, washed 3-4 times with tap water for
removing dust and dried at 100 ˚C for 24 hours.
NaOH (2M) was added to rice straw (1 g/NaOH 20ml) and boiled under constant stirring at 80 ˚C for 1
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SEE - Bangkok, Thailand, Nov.11-13, 2019

hour. After that, it was washed with distilled water.
Fibers were bleached with 18.5% H2O2 (v / v) for 3
hours, then washed with distilled water. The cellulose
fibers were hydrolyzed using 50% H2SO4 (v/v) at
45˚C for 1 hour under constant stirring as a previously
reported method [7]. After hydrolysis, it was diluted
with cold water to stop the hydrolysis reaction. Thenthe samples were washed with water until neutral pH
to remove the excess sulfuric acid. The suspension
was sonicated [7] at 45 ˚C for 30 minutes andevaporated in an oven at 100 ˚C for 12 hours. Then, it
was ground into a powder, the powdered cellulose
fibers were selected in the size 150-250 μm before
stored in a desiccator.

from water and weighed. The water uptake wasdetermined using this equation

where M1 is the weight of the dry film before
immersion and M2 is the weight of the film after
immersion.
RESULTS AND DISCUSSION
The extracted cellulose was filtered with thesieves and the size of cellulose was 150-250 μm. The
result was showed in Fig 1. The result of FT-IR waspresented in Fig 2, the 3500-3000 cm-1 range
characterized by a broad spectrum and high intensityof OH stretching and 1650 cm-1 was OH bending
showed at a lower range than adsorbed water. At
1450-1420 cm-1 was C-H stretching and the range of1382-1375 cm-1 was CH bending. At 902-893 cm-1
was associated with cellulosic β-glycosidic linkages,
at 1155 cm-1 was C-C ring stretching, and C-O-C at
953 cm-1 was glycosidic ether. The results weresimilar to Ping Lu's et al [17] results.

Fabrication of poly(l-lactide)/cellulose composite
filmAdding the chloroform 15 ml into poly(l-lactide)and stirred until 1 hour. Then it was mixed withcellulose for 30 minutes. It was poured into the petri
dish and dried in an oven at 50˚C for 1 hour. After
that, it was also deeply dried in a vacuum oven at
50˚C for 24 hours and then it was stored in a
desiccator. The ratio of poly(l-lactide)/cellulose was
100/0, 98/2, 96/4, 94/6, 92/8 and 90/10 (w/w).
Characterization
composite filmofpoly(l-lactide)/cellulose

FT-IR spectra were obtained using Fourier
Transform Infrared Spectroscopy; FTIR (Perkin
Elmer model Spectrum GX). The measurements were
scanned in the range 400 - 4000 cm-1. X-ray
diffraction; XRD was widely used for theidentification of unknown crystalline materials andmeasured by the machine models D8 ADVANCE(Bruker). The crystallinity of cellulose was extracted
from rice straw, films sample were scanned byscattering 2 angles from 5-40 degree with a rate of 0.2
sec/degrees. Scanning Electron Microscope; SEM(JEOL, JSM-64606V) was used to study surface andmorphology (shape, pattern, size) of the samples. The
cellulose powder samples were prepared into thecarbon tape on the stub and coated with gold. The film
samples were prepared by immersion in liquid
nitrogen before it was broken to study the crosssection morphology. The film pieces were also
mounted on the stub to study morphology.
Thermogravimetric Analysis; TGA samples were
heated from 40 to 800 ◦C at a rate of 10 ◦C/min under
nitrogen atmosphere. Tensile testing of the film
samples was studied on a universal testing machine(LLOD INSTRUMENTS, AS500) at room
temperature. The film samples were cut 1 × 8 cm.
(repeat 5-10 times). The water uptake capacity [16]ofeach film was studied by cut the film to size 1 x 1 cm
and was immersed into distilled water at room
temperature for 90 minutes. Then it was taken off

Fig. 1 Rice straw cellulose powder

Fig. 2 FT-IR spectrum of rice straw cellulose
The XRD results (Fig. 3) showed that the
crystalline peaks of cellulose were at 15.3o, 22.5o, and34.5o. It could be asserted that the extraction ofcellulose could be accomplished by hydrolysis.
Lignin and hemicellulose were amorphous structure.
The crystalline peaks are found in the same area as
the research by Anuj Kumar et al [18]. It was also
found that when the improved chemical wasincreased the crystallization was also increased due to212

SEE - Bangkok, Thailand, Nov.11-13, 2019the amorphous removal. Fig 4 shows that theappearance of cellulose powder was small anduncertain shape may be due to the hydrolysis process.

was C-H stretching, which was found in poly(llactide) and cellulose. As 950 cm-1 was a C-O-C
glycosidic ether that is prominent in cellulose. The
results of FT-IR can be confirmed that the sample
film (b-f) were contained cellulose. [17]Fig. 3 XRD spectrum of rice straw cellulose

Fig. 5 Physical characteristics of films

Fig. 4 Morphology of rice straw cellulose powder
from SEM 500X (a) and 1000X (b)Characterization of poly(l-lactide) films mixed
with rice straw cellulose fiber
The physical appearance of the poly(l-lactide)films (Fig. 5) was smooth and clear. The best
cellulose distribution compared to other ratios was
PLLA98/CS2. When adding more cellulose, the film
became darker and the cellulose was clumped due tothe polarity of the cellulose. The results obtained by
FT-IR analysis (Fig. 6) show that (a) was a 100%
cellulose spectrum. The dominant function of the3500-3000 cm-1 spectrum was broad spectrum andhigh intensity of OH stretching. The range of 14501420 cm-1 was C-H stretching and at 950 cm-1 was CO-C glycosidic ether and (g) was the spectrum ofpoly(l-lactide) film. The 1750 cm-1 function group
was a function of C=O and the range of 1450-1420
cm-1 was C-H stretching. The (b-f) spectrum waspoly(l-lactide) film mixed with cellulose. The rangeof 3500 - 3000 cm-1 was OH stretching. It has broadspectrum and high intensity compared to poly(Llactide) film (spectra g). As a result, there was a large
number of hydroxyl groups (OH) in cellulose. The
1750 cm-1 was a function of carbonyl (C=O), which
was prominent in poly(l-lactide). C-H stretching was
a common group of poly(lactic acid) and cellulose(950 cm-1). C-O-C was a glycosidic ether that wasprominent in cellulose. The range of 1450-1420 cm-1

Fig. 6 FT-IR spectra of the film in various ratios (a)CS100, (b) PLLA98 / CS2, (c) PLLA96 / CS4, (d)PLLA94 / CS6, (e) PLLA92 / CS8 (f) PLLA90 / CS10
and (g) PLLA 100.
The crystallinity of polylactide film at 16.7 ◦ and22.6◦ was shown in Fig. 7. According to Ping Lu et al.
[18], 2θ values of cellulose were found at 15.3◦ 22.5◦
and 34.5◦. When the cellulose was mixed into thepoly(l-lactide), it was observed that the crystallinityof the film was increased and the highest increase wasthe PLLA98 / CS2 ratio film. Surface characteristics
of films were shown in Fig.8. It was found that thesurface appearance of poly (l-lactide) film wassmooth and less rough which was different to thefilms that mixed with cellulose, which were more
213

SEE - Bangkok, Thailand, Nov.11-13, 2019

roughly textured, the ratio of cellulose increases.
However, PLLA98/CS2 was a good dispersion of thecellulose, making the least rugged surface film whencompared to the others. The poorly distributed
cellulose, resulting in a rough surface. The crosssection of ratio each film were investigated. It was
found that the poly(l-lactide) contains rough surface
texture somewhat less than film mixed with cellulose.
The results were in the same direction as the surface
characteristics of the film, as shown in Fig. 9. The
cellulose was inserted into the films. It was known
that poly(l-lactide) and cellulose were nothomogeneous because non-polar properties of poly(llactide) and that the cellulose was polar properties. So
it was less homogeneous. But it can be seen that thecellulose can be inserted into the poly(l-lactide) as aresult of adhesion. It could be said that cellulose hasa rough surface when poly(l-lactide) melts into aliquid and could be inserted into the gap in theroughness of the cellulose when the poly(l-lactide)solidifies it causes adhesion. It also described theadhesion of the chemical bonding. Many hydroxyl
groups of cellulose could build up hydrogen bond
between molecules of cellulose and poly(l-lactide)[19], [20]Fig. 8 The surface of PLLA, PLLA98 / CS2,
PLLA96 / CS4, PLLA94 / CS6, PLLA92 / CS8 andPLLA90 / CS10 500X

Fig.9 The cross section of PLLA, PLLA98 / CS2,
PLLA96 / CS4, PLLA94 / CS6, PLLA92 / CS8 andPLLA90 / CS10 2000X

Fig. 7 XRD spectra of the film in various ratios (a)CS100, (b) PLLA98 / CS2, (c) PLLA96 / CS4, (d)PLLA94 / CS6, (e) PLLA92 / CS8 (f) PLLA90 /CS10 and (g) PLLA 100.
Fig. 10 TG thermograms (a) and DTG thermograms(b) of PLLA100, PLLA98 / CS2, PLLA96 / CS4,
PLLA94 / CS6, PLLA92 / CS8, PLLA90 / CS10 and
CS100.

Thermogram analysis was shown in Fig.10. The
decomposition of poly(l-lactide) at 320 ˚C andcellulose decomposition showed at 360 ° C, so it was
showed only one component. Decomposition ofhemicellulose (250 ˚C) and lignin (365 °C) were notfound. The results were similar to the article of SuHwa Jung[21]. When the cellulose was mixed into thepoly(l-lactide), the degradation was 1 stage at 300400 °C. The decomposition of each ratio varies. It wasnoted that when the cellulose content increases, thetemperature of the decomposition of the film
increases slightly as shown in Table 1

Tensile testing of poly(l-lactide) film andcellulose mixed films in various ratios were foundthat cellulose affects the mechanical properties ofpoly(l-lactide) films. When mixing the cellulose in
the poly(l-lactide) films, the tensile strength,
elongation at break and Young's modulus of films
were increased. These values indicated the strength of
the film (The results are shown in Table 2). However,214

SEE - Bangkok, Thailand, Nov.11-13, 2019the highest test values were from PLLA98/CS2 film.
This may be due to the amount and dispersion ofcellulose in the film, which affected the strength. The
results of this study were consistent with the findingsof Sanyang ML et al. [16] and also consistent with
SEM results. The good dispersion of cellulose
resulted in a stronger film. Due to the uniform
dispersion, the mixed film was very strong adhesion.
Thus the mixed films were better tensile properties
than the poly(l-lactide) film without cellulose blends.
However, when the amount of cellulose mixture wasincreased at more than 2% the films were reduced
strength. Because the more cellulose, the formation ofcellulose was poor dispersion and less adhesion
between poly(l-lactide) and cellulose.

The water absorption results were present in Fig.
11. The poly(l-lactide) film was the lowest water
absorption while the water absorption of mixed films
was increased because of the hydroxyl groups ofcellulose. The water absorption increased with anincreasing amount of cellulose. When comparing
PLLA with PLLA98/CS2, the values were slightly
different[16].
CONCLUSIONS
The rice straw cellulose was mixed in poly(llactide) by the solvent method. The ratio of poly(llactide)/cellulose was 100/0, 98/2, 96/4, 94/6, 92/8
and 90/10. Physical characteristics of the film were
darker color when cellulose content was increased.
The surface fracture of the films was more unevensurface as the ratio of cellulose increased. The
thermal stability of the films was slightly increased
with the addition of cellulose blends. The cellulose
content increased also increasing the tensile strength,
Elongation at break, and Young's Modulus. However,when the amount of cellulose is increased, theformation of cellulose results in poor distribution andless adhesion between the poly(l-lactide) and thecellulose. It could be concluded that the cellulose
extracted from rice straw was used as a reinforcement
to increase the thermal and mechanical properties ofpoly(l-lactide). The film with 2% cellulose blend was
the best thermal and mechanical properties due to theaddition of ingredients in the right proportion andwell dispersed in the poly(l-lactide) of cellulose.

Table 1 Temperature decomposition of cellulose andfilms
SampleCS100
PLLA
PLLA98/CS2
PLLA96/CS4
PLLA94/CS6
PLLA92/CS8
PLLA90/CS10

Td (max) (˚C)
360
320
340
340
330
330
330

Table 2 Tensile testing of the films
SamplePLLA100
PLLA98/
CS2
PLLA96/
CS4
PLLA94/
CS6
PLLA92/
CS8
PLLA90/CS10

Tensilestrength
(MPa)
24.95
±3.95
37.92
± 1.03
35.46
±1.12
34.31
±1.51
30.60
±1.09
29.98
±1.39

Elongation
at break
(MPa)
6.47
±1.36
13.55
±3.45
10.70
±2.04
10.31
±1.22
10.31
±0.96
7.12
±2.06

Young's
Modulus(MPa)
1112.99±38.311198.47± 45.28
1184.18± 77.58
1141.26± 61.271023.97± 88.79
1154.50± 94.63

ACKNOWLEDGEMENTS
This research was supported by the Department ofChemistry Faculty of Science Mahasarakham
University and was financially supported by Thailand
Reserch Fund (Senior Research Scholar).

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SUSTAINABLE AQUACULTURE MANAGEMENT OF VANAMEISHRIMP (Liptopenaeus vannamei) IN BATUKARAS VILLAGE,PANGANDARAN, INDONESIA
1Andrian Achmad1, Dewi Susiloningtyas2 and Tuty Handayani3
Marine Sciences FMIPA Universitas Indonesia, 2 Universitas Indonesia; 3 Universitas Indonesia, Indonesia
ABSTRACT

Vaname shrimp is a superior commodity in aquaculture which continues to increase in demand. The farmingof vaname shrimp in Batukaras Village, Cijulang Subdistrict, Pangandaran Regency is carried out with semiintensive technology, the application of this technology is not sustainable due to lack of supporting facilities. This
study aims to analyze the physical aspects and the quality of production and the sustainability status also determine
the priority strategy for sustainable management of vaname shrimp. Analysis of sustainability status is carried out
by surveys and interviews with farmers then processed using the RAPFISH method (The Rapid Appraisal of The
Status Fisheries), for physical aspects measurement of water quality is carried out in situ and testing in thelaboratory with measured parameters, namely temperature, salinity, DO, pH, nitrite and ammonia. While thepreparation of priority programs is processed using the AHP (Analytical Hierarchy Process) method using Expert
Choice software. The results of the research are water quality parameter values for temperature, salinity, pH, DO
and nitrite and the quality of shrimp according to standard values, but ammonia parameters are far from normal
limits. The multidimensional sustainability level of vaname shrimp management in Batukaras Village has asustainability index of 60.00 which means it is quite sustainable. The choice of the main priority program for thesustainability of vaname shrimp cultivation is the rehabilitation program for fishpond infrastructure with a value
ratio of 0.29.
Keywords: AHP, aquaculture, Pangandaran, Rapfish, vaname shrimp.
gourami commodities, 30 tons of tilapia, 15 tons of
catfish, 15 tons of carp, 10 tons of tawes, 5 tons ofprawns and 5 tons of other fish. From theachievements of production in 2016, Freshwater
farming achieved a production realization of 110.79
tons or equal to 92.32% of the production target.
Whereas for brackish water farming, the production
target is set at 101.5 tons consisting of 70 tons ofvaname shrimp, 10 tons of black shrimp, 10 tons ofmilkfish, 5 tons of crab, grouper of 1 ton, whitesnapper and other types of fish of 0.5 tons and 5 tons.
The achievement of brackish water farming has
succeeded in getting production in 2016 of 122.31
tons or equal to 120.5% of the achievement of the
production target. For the main commodity ofbrackish water farming is vaname shrimp from thetarget set at 70 tons which exceeded the target bysuccessfully obtaining a production of 110.43 tons.
The purpose of this study is to determine thesuitability of general water parameters and the qualityof production, know the sustainability status ofaquaculture in terms of ecological, social, economic,
technological and institutional dimensions anddetermine the priority strategy program for the
management of white shrimp farming in Batukaras
Village, Cijulang District, Pangandaran Regency.
The results of this study will provide an illustration,
whether the pond area in Batukaras Village can becontinued for shrimp farming production or not. If not,inputs are needed to improve the condition of thepond area to be an ideal pond area for vaname shrimp

INTRODUCTION
Aquaculture has a considerable diversity ofpotential superior commodities. According to datafrom the Ministry of Marine Affairs and Fisheries in
2016, the potential for marine aquaculture is 8.3
million ha which consists of 20% for fish farming,
10% for shellfish farming, 60% for seaweed farming,and 10% for others, the potential of brackish wateraquaculture or ponds is 1.3 million ha, and thepotential of 2.2 million ha of freshwater aquaculture
consisting of fish pond with an area of 526.40
thousand ha, public waters (lakes, reservoirs, rivers
and swamps) covering 158.2 thousand ha, and rice
fields for minapadi covering 1.55 million ha. In 2012,
Indonesia ranks 2nd for capture fisheries production
and ranks 4th for aquaculture production in the world.
Pangandaran Regency is one of the districts inWest Java Province. Pangandaran Regency has only
been a District Government since 2012. This district
has an area of 1,680 Km² consisting of 10 subdistricts with 12 urban villages with 81 villages witha population of 422,586. The district is strategicallylocated, because it is on a provincial road lane,
located on the seashore with a beach length of 91 km.
Based on its position, Pangandaran is bordered by
Ciamis Regency and Banjar City in the north, Cilacap
Regency in the east, Indian Ocean in the south, andTasikmalaya Regency in the west.
According [8], Freshwater aquaculture has a
production target of 120 tons consisting of 40 tons of217

SEE - Bangkok, Thailand, Nov.11-13, 2019farming.

temperature [15]. The normal range of water pH for
shrimp ranges from 7.5 to 8.5. The direct effect of low
pH is that it causes the shrimp skin to become porous
and always soft because it cannot form new skin [6].
4. DO
The amount of oxygen needed for respiratory
aquaculture depends on the size, temperature andlevel of activity with a minimum limit of 3 ppm. The
oxygen content in water is considered optimum foraquatic biota cultivation is 4-10 ppm, depending on
the type. The respiration rate is seen to remain at theoxygen solubility limit between 3-4 ppm at atemperature of 20-30 °C [11].
5. Ammonia
Ammonia is a chemical compound in the form ofa gas with a distinctive sharp odor. Ammonia sources
in aquaculture containers originate from the waste offish metabolism and leftovers that are not eaten. [14]states that NH3 in cultivation media must be lower
than 0,8 mg/L.
6. Nitrite
Nitrite is the result of metabolism from thenitrogen cycle. The mid form of nitrification anddenitrification. Nitrite is a nitrogen-containing
component that binds to two oxygen atoms. In natural
waters the nitrite content is in small amounts, because
it is not stable in the presence of oxygen. High nitrite
content can result in disruption of the oxygen binding
process by blood hemoglobin, which in turn forms
methmoglobin which is unable to bind oxygen [9].

REVIEW OF REFERENCES
Biological Vaname Shrimp
The classification of vaname shrimp according to[10] is included in the Kingdom: Animalia, SubKingdom: Metazoa, Genus: Litopenaeus, andSpecies: Litopenaeus Vannamei.
Generally the body of shrimp can be divided into
two parts, namely the head and body parts. The headis fused with the chest part called the cephalothorax
which consists of 13 segments, namely 5 segments in
the head and 8 segments in the chest section. Body
parts and abdomen consist of 6 segments eachsegment (segment) has a pair of limbs (swimminglegs) that are segmented [13].
The vaname shrimp habitat is in the tropical sea
with a water temperature of more than 20 oC. They
lay eggs in the open sea and at the post larval stage
will migrate to the coast to the juvenile stage.
Potential and Management
The potential for shrimp farming has a very large
business opportunity. The utilization of shrimp
farming in 2012 was 22.2%. There are 87.8% or 2.3
million hectares of land that are very potential to be
used as farms for ponds, especially shrimp.
Utilization of shrimp farming in ponds is 22.2% withthe consideration that the majority use traditional andsemi-intensive cultivation technology. However, if
applying advanced technology (intensive and supraintensive) the opportunity to develop ponds can beeven greater, considering that even marginal andsandy land can be utilized.

Sustainable Development
The concept of sustainable development was firstpublished by The World Conservation Strategy in1980 in Gland, Switzerland and became the center ofthought for development and the environment.
According to [7], the sustainability of fisheries
development contains four basic components thatmust be met. The basic components include:
1. Ecological sustainability is a concern to ensurethat crops continue to be sustainable, and that there is
no reduction in fish stock depletion.
2. Socio-economic sustainability is maintaining andincreasing overall long-term socio-economic wellbeing.
3. Community sustainability is focused on the desire
to defend the community as a human system that has
its own rights over its natural resources.
4. Institutional sustainability includes maintaining
the suitability of financial, administrative, andorganizational capabilities throughout all time, as aprerequisite for the three components of sustainability
above.

General Aquatic Parameters
1. Temperature
Some observers have found that shrimp cannot
live at temperatures less than 15ºC or more than 40ºC.
The optimal temperature for shrimp is 28-30 ºC. In
addition to the lethal direct effect, the temperature
also indirectly affects metabolism, the solubility ofgases, including oxygen and various water chemical
reactions [15].
2. Salinity
Salinity is the total ion concentration found in thewaters [3]. Salinity describes the total solids in water,
after all carbonates are converted to oxide, allbromides and ionides are replaced by chloride and allorganic material has been oxidized. Salinity units are
expressed in units of permits (‰).
3. pH
pH shows the activity of hydrogen ions in thesolution and is expressed as the concentration ofhydrogen ions (in moles per liter) at a certainRESEARCH METHODS
Research Data

218

SEE - Bangkok, Thailand, Nov.11-13, 2019

Measurements of physical aspects were carriedout on water quality parameters including
temperature, pH, DO, salinity, nitrite and ammonia
content and production for shrimp weight and length.
This physical data retrieval was carried out in 10 farm
plot points which were currently producing vaname
shrimp with the taking time on the 0th, 30th and 60thdays. Measurement of water quality parameter data iscarried out in situ except the measurement of nitrite
and ammonia content. Measurements of ammonia
and nitrite content were carried out by taking 200 ml
of water samples using plastic sample bottles to beanalyzed at the Laboratory of UPTD of Brackish andSouth Sea Water Fisheries, Pangandaran.
The sustainability status of vaname shrimp was
analyzed by Rapfish software with data sources
derived from respondents who were farmers (pondowners) in the Batukaras Village pond area. The
implementation of the interview is assisted by aquestionnaire list as a tool for collecting data. The
total number of farmers (pond owners) of vaname
shrimp in Batukaras Village is 18 people. Calculationof the number of respondents with Slovin method
obtained a minimum number of respondents as muchas 15.25 rounded up to 15 respondents. Cultivators
who are active in aquaculture chosen as respondents.

Goodness of Fit in MDS is reflected in the amount of
S-Stress value calculated from the value of S. Low
stress values indicate good fit, while high S values
indicate bad fit. In Rapfish, a good model is shown if
the stress value is smaller than 0,25 (S < 0,25).
4. Perform sensitivity analysis (leverage analysis)
and Monte Carlo analysis to take into account aspects
of uncertainty.
The sustainability analysis used in this study
refers to [16] who divides sustainability into 4categories, namely: unsustainable (0-25%), lesssustainable (25-50%), fairly sustainable (50-75%),
and sustainable (75-100%).
Analitycal Hierarchy Process (AHP) is a method
for solving a complex situation that is not structured
into several components in a hierarchicalarrangement, by giving subjective values about theimportance of each variable relative, and determining
which variable has the highest priority to influence
the outcome of the situation.
RESEARCH RESULTS AND DISCUSSION
Physical Condition of Ponds
Tabel 1. Results of Water Quality Parameters [12]Average Standard Results
No Parameter
Value
Value
)*
1 Temperature 29,52 °C 28-31,5 °C Matching
2 Salinity
17,53 g/l 10-35 g/l Matching
3 pH
8,11
7,5-8,5 Matching
4 DO
6,7 mg/l
4-6 mg/l Matching
5 Nitrite
0,6 ppm≤ 1 ppm Matching
6 Ammonia
0,26 mg/l ≤ 0,1 mg/l
Not
matching
7 Soil texture Sandy soil
Matching(Source: Data Processing, 2019)

Data Processing Method
The results of the analysis of recapitulated water
quality parameters in the data tabulation are thencompared with the maximum / minimum standard
values of each water quality parameter. The vaname
shrimp during production was taken as many as 5-10
tails from each sample plot point to measure theaverage weight or ABW (Avarage Body Weight) thenit will be compared with the standard value.
Rapfish is the latest technique developed by the
University of British Columbia Canada, which is ananalysis to evaluate the sustainability ofmultidisciplinary fisheries. Rapfish is based on
ordination techniques (placing something on ameasured sequence of attributes) using MDS (MultiDimensional Scaling). MDS itself is basically astatistical technique that tries tomakemultidimensional transformations into lower
dimensions. The dimensions in Rapfish concern
aspects of sustainability from ecology, social,economic, technological and institutional. Rapfish
analysis in this study was carried out through several
stages, namely:
1. Scoring by referring to the literature (ecology,social, economic, technological, and institutional) of
Rapfish by using MS Excel.
2. Perform MDS analysis to determine theordination and stress values through ALSCAL
Algorithm.
3. Perform "rotation" to determine the position of thefishery in ordination of bad and good with MS Excel.

In this study, the data was taken from a sample of
10 plots of shrimp ponds located in the Shrimp
Village of Batukaras Village. The total sample area ofthe shrimp ponds studied was 14,500 m2. From thesesamples, it is expected to represent the results of theresearch carried out for the whole shrimp farm. The
results of the observation of shrimp farms are shownin Table 1.
Shrimp Quality
Based on Table 2, the results of the measurementof shrimp quality, the majority of shrimp seed stocked
were 9-day post larvae (PL.9), except for plot number
4 ponds using PL.8. The average shrimp weight at the60th day of production was 11.84 grams. This average
weight has met the SNI 01-7246-2006 standard which
explains that in 61-75 day old shrimp shrimp have aweight range of 8.1-14.0 grams. Shrimp that arearound 61 days old have a minimum weight of 8.1
grams. However, there are 3 plots of pond ponds that219

SEE - Bangkok, Thailand, Nov.11-13, 2019

have not been able to reach the minimum limit,
namely in plots P1, P2, and P3. In the three plots ofponds the development of shrimp appears to behampered from the 30th day to the 60th day.
According to the results of interviews in the fieldwith farm owners, this is likely to occur because of
the threat of shrimp disease which makes shrimp
appetite decrease. Allegedly high levels of ammonia
are a cause of decreased appetite for shrimp so thatshrimp do not develop. This is also seen when
feeding, food that is in the container (anco) is stillmuch left.

Regency is seen from the ecological dimension,social dimension, economic dimension andinstitutional dimensions having index values of
51.41, 52.32, 51.62 and 66.13 respectively. The four
dimensions fall into the fairly sustainable category.
While the dimensions of technology include asustainable category with an index value of 76.98.
From these five dimensions, the technology
dimension is the dimension with the best level ofsustainability. This means that technologically,vaname shrimp farming is a benchmark for thesustainability of vaname shrimp management in
Batukaras Village.

Tabel 2. Shrimp Quality Measurement Results
WeightLong
No.
Size of
(gr)
(mm)
Ponds
Fries
60th day
P.1
PL.9
7
94
P.2
PL.9
6,4
87
P.3
PL.9
6,5
90
P.4
PL.8
9,3
115
P.5
PL.9
13,4
130
P.6
PL.9
13
130
P.7
PL.9
10
125
P.8
PL.9
12
130
P.9
PL.9
13,2
134
P.10
PL.9
11,5
130
Average
10,23
116,5(Source: Data Processing, 2019)
Status of Sustainability
Aquacultureof

ShrimpFigure 1. Sustainability Status Diagram
Multidimensional Sustainability
According to [5], the assessment of thesustainability status of fisheries management cannot
be done by looking at the averages of the fivedimensions used as indicators, but it must be done bypairwise comparation tests. Pairwise comparationmust be done because each dimension assessed has
different weights. Based on the assessment that has
been done, a weighted score is obtained as shown in
Table 3 above. The results of pairwise comparation
by weighing index values as in Table 3 obtained aweighted index value of 60.00 which is in the rangeof values 50-75. This means that vaname shrimp
farming activities in Batukaras Village, Pangandaran
Regency are in a fairly sustainable condition.

Pond

Dimension Sustainability
The sustainability status of the vaname shrimp
pond aquaculture in Batukaras Village, Cijulang
District, Pangandaran Regency was determined byanalyzing 5 (five) dimensions used in the Rapfish
method, namely the ecological, social, economic,
technological and institutional dimensions. Based on
the analysis of the five dimensions, we obtained asustainability index for shrimp pond aquaculture in
Batukaras Village, Cijulang District, Pangandaran
Regency. The assessment of the five dimensions is asfollows by Table 3:

Tabel 4. Multidimensional Sustainability Index
Value
ValuesNo Dimension
Weighted
Weight Index
Index
1 Ecological
0,06
51,41
3,08
2 Social
0,14
52,32
7,33
3 Economi
0,43
51,62
22,20
4 Technological
0,27
76,98
20,79
5 Institutional
0,10
66,13
6,61
Total
60,00
Fairly Sustainable(Source: Data Processing, 2019)

Tabel 3. Rapfish Ordination Result
Nilai
No Dimension
R2
StatusIndeks1 Ecological51,41 0,92 Fairly Sustainable
2 Social
52,32 0,91 Fairly Sustainable
3 Economi
51,62 0,92 Fairly Sustainable
4 Technological 76,98 0,95
Sustainable
5 Institutional
66,13 0,91 Fairly Sustainable(Source: Data Processing, 2019)
The status of sustainability of vaname shrimp
cultivation in Batukaras Village, Pangandaran
220

SEE - Bangkok, Thailand, Nov.11-13, 2019

The results of the Rapfish analysis show that all
the attributes assessed for the sustainability status ofvaname shrimp farming are quite accurate. This canbe seen from the stress values ranging from 0.20-0.27
with a relatively large degree of determination
coefficient (R2), which is 0.91-0.95 for all
dimensions assessed. Based on these values it can beillustrated that the attributes used to assess thesustainability status of each dimension are sufficient,as shown in Table 5.

to University of Indonesia for Hibah PublikasiInternasional Terindeks Tugas Akhir (Hibah PITTA
B) in 2019 in accordance with the agreement letter
No. NKB-0624/UN2.R3.1/HKP.05.00/2019.
REFERENCES[1] Badan Standarisasi Nasional, (2006). SNI 017246-2006:
Produksi
udang
vaname(litopenaeus vannamei) ditambak dengan
teknologi intensif, Jakarta.
[2] Bappeda Pemerintah Provinsi Jawa Barat,(2016). Penyusunan rencana kebutuhan
investasi pusat pertumbuhan pangandaran raya
2016. Laporan Akhir.
[3] Boyd C. E, (1988). Water quality management
for pond fish cultura. Elsever. Amsterdam.
[4] BPS Jawa Barat, (2016). Provinsi Jawa Barat
dalam angka 2016.
[5] Budiharsono, S., (2005). Teknik analisis
pembangunan dan pesisir. Pradnya Paramita,
Jakarta.
[6] Buwono, I. D., (1993). Pedoman udang windu
sistem pengelolaan berpola intensif. Kanisius.
Yogyakarta.
[7] Charles, Anthony T, (2001). Suistainablefishery system, Saint Mary’s University,
Halifax, Nova Scotia, Canada.
[8] Dinas Kelautan dan Perikanan Kabupaten
Pangandaran, (2016). Laporan Tahunan
Perikanan Budidaya.
[9] Effendi, H, (2003). Telaah kualitas air bagi
pengelolaan sumber daya dan lingkungan
perairan, Kanisius, Yogyakarta.
[10] Effendie, M, I, (1997). Biologi perikanan,
Yayasan Pustaka Nusatama, Yogyakarta.
[11] Ghufran, M dan Kordi K. (2004).
Penanggulangan hama dan penyakit ikan.
Penerbit Bina Adiaksa dan Rineka Cipta.
Jakarta. 190 hal.
[12] Kementerian Kelautan dan Perikanan, (2006).
Peraturan Menteri Kelautan Dan Perikanan
Republik Indonesia Nomor. 75/PERMENKP/2016 Tentang Pedoman Umum Pembesaran
Udang Windu (Penaeus Monodon) dan Udang
Vaname (Litopenaeus Vannamei).
[13] Kordi, M. G. H. K., dan A. B. Tancung. (2007).
Pengelolaan kualitas air dalam budidaya
perairan. Rineka Cipta, Jakarta. 210 hlm.
[14] Stickney RR, (2005). Aquaculture: An
introductory text, USA: CABI Publishing.
[15] Sumeru, U dan S, Anna, (1992). Pakan udang
windu, Kanisius, Yogyakarta.
[16] Susilo, S, B, (2003). Keberlanjutan
pembangunan pulau-pulau kecil: studi kasus
kelurahan Pulau Panggang dan Pulau Pari,
Kepulauan Seribu, DKI Jakarta, Disertasi,
Program Pascasarjana Institut Pertanian Bogor.

Tabel 5. Value of Rapfish, Stress and Coefficient
ValuesNo Dimension
StatusIndex Stress R2
1 Ecologi51,41 0,24 0,92
Fairlycal
Sustainable
2 Social
52,32 0,27 0,91
FairlySustainable
3 Economi 51,62 0,22 0,92
FairlySustainable
4 Technolo- 76,98 0,20 0,95 Sustainablegical
5 Institutio- 66,13 0,26 0,91
Fairlynal
Sustainable(Source: Data Processing, 2019)
CONCLUSIONa. Water quality and quality of shrimp production in
shrimp ponds in Batukaras Village, Cijulang District,
Pangandaran Regency have conformed to thestandard guidelines for vaname shrimp farming usingsemi-intensive technology. Suitable water quality
parameters include temperature, salinity, pH, DO,
and nitrite, while ammonia levels are above themaximum limit for vaname shrimp cultivation.
b. The status of sustainability of vaname shrimp
cultivation in Batukaras Village which was analyzed
by the Rapfish method is in a fairly sustainable state.
With the technology dimension at the highest level
because this dimension is a leverage factor forincreasing the production of vaname shrimp
cultivation in Batukaras Village.
ACKNOWLEDGMENTS
Dr. Dewi Susiloningtyas, M.Sc as Chair of the
Marine Sciences Master Program, also as the 1st
mentor and Dra. Tuty Handayani, M.S as the 2nd
mentor who have provided much suggestion andguidance during the implementation of the researchand preparation of the thesis. Directorate General of
Aquaculture, and head of the Marine and FisheriesService Pangandaran District which has helped a lot
in providing the data needed. My beloved wife Yesha
Ayudiana, (Alm.) My Mom, My Dad and in-laws andyounger siblings who have given encouragement andenthusiasm so i can complete this thesis. Also, thanks

221

5thInt. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EVALUATION OF THE TOXIC EFFECTS OF SMOKELESSTOBACCO CHEWING MIXTURES BASED ON BIOLUMINESCENCETESTING USING THE EXAMPLE OF NASWAR
Dianna B. Kosyan1.2, Olga V. Kvan1, Elena A. Rusakova1, Inara E. Larjushina1, Elena V. Kiyaeva1,
Galimzhan K. Duskaev1
1
Laboratory of Nanotechnology and Technogenic Nanomaterial, Federal Research Centre of Biological
Systems and Agro-technologies of the Russian Academy of Sciences, 9 th Yanvarya St., 29, 460000,
Orenburg, Russia; 2Department of Microbiology and Contagious Disease, FGBEA Orenburg State Agrarian
University, Chelyuskintsev St., 18, 460000, Orenburg, Russia
ABSTRACTThe tobacco market includes a wide range of smoking and smokeless products. Previously, cigarettes
and other kinds of smoking mixtures mainly comprised tobacco consumption, but with stricter smoking bans in
Russia, there has been an expected increase in smokeless tobacco product consumption. The surging use ofnaswar is of a particular significance. One possible method for rapid toxicity assessment involves
bioluminescence analysis using microorganisms that contain different types of sensory cell structures. To
conduct bioluminescence analyses, researchers use genetically engineered luminescent microorganisms. For ourstudy, we chose lyophilised, commercially available "Ecolum", a genetically engineered luminescent strain ofEscherichia coli K12 TG1 that constitutively expresses luxCDABE genes from Photobacterium leiongnathi
54D10. We also examined E. coli K12 MG1655 strains with inducible luminescence through plasmids with thegene mergers soxS lux and katG lux. Our results allow one to consider a basic toxic mechanism due to oxidative
stress formation: damage to intracellular structures, namely DNA.
Keywords: Bioluminescence, Microorganism, Naswar, Oxidative stress, Toxicity
existing methods should be evaluated and new
assays developed to evaluate the safety of tobacco
products. However, this research is virtually nonexistent in Russia [8, 9].
One possible method for rapid toxicologicalassessment could be bioluminescence analysis using
microorganisms that contain different types of
sensory cell structures [10]. Indicators of toxicity
from a sample will alter luminescence intensity
compared to the control. Bacterial bioluminescenceis extremely sensitive to the effects of various
inhibitors and is therefore used to analyze many
anesthetics, drugs, industrial poisons, insecticides,
toxic and medicinal substances [11]. Based on theneed to develop new analysis methods, the purposeof this work was to evaluate the use of
bioluminescence analysis to evaluate the toxicity ofsmokeless tobacco mixtures (naswar)

INTRODUCTION
The tobacco market includes a wide range ofsmoking (cigarettes, cigars, cigarillos etc.) andsmokeless (chewing, sucking and snuff tobacco)products. Previously, cigarettes and other smoking
mixturesmainlyaccounted
fortobaccoconsumption, but with stricter smoking bans in
Russia, there has been an expected increase insmokeless tobacco product consumption [1, 2]. A
surge in the use of naswar is of particularsignificance. Naswar is a multi-component nicotine
mixture that contains different plants (such as talkan
and sirach) and non-food components (plant ash,quicklime and avian or camel dung); thesecomponents represent potential carcinogens. Naswar
production is usually artisanal and different detectedcomponents may have negative effects on the body
[3-5].
Currently, there is a major push to develop
methods that assess chewing tobacco product safety
because of issues with present diagnostic and testing
methods [6]. Almost all existing toxicologicalmethods have several drawbacks: 1) they are notintended to assess tobacco and tobacco smoke
toxicity; 2) they do not allow quantification of
tobacco products with varying degrees ofcomplexity in their chemical structure; 3) they aredesigned primarily for screening chemicals to
identify possible human carcinogens [7]. Thus,

MATERIALS AND METHOD
Test substance preparation
We analyzed four samples (A through D) of
smokeless chewing tobacco blend 1 (naswar). An
aqueous extract of the test material was performed
according to a methodology used in similar studies
by foreign researchers [12]. One thousand µl of
distilled water was added to 1 g naswar (a 1:1 ratio).
The solution was thoroughly mixed and incubated222

SEE - Bangkok, Thailand, Nov.11-13, 2019for 24 h at room temperature.

bacteria; control wells contained distilled water andluminescent bacteria. Plates were placed in an
Analyzer Infinite PROF200 (TECAN, Austria),
which dynamically registered the luminescenceintensity for each well over 180 min (5 minintervals) in relative light units (RLU).
The data were analyzed using the software
provided with the instrument. Quantification of thebioluminescence inhibition index (I) due tonanoparticle toxicity was calculated by the following
algorithm (1).

Test organism characteristic
Bioluminescence analyses utilize geneticallyengineered luminescent microorganisms withdifferent types of luminescence. We utilized thecommercially available lyophilized "Ecolum"("Immunotech", Moscow, Russia), a geneticallyengineered luminescent strain of Escherichia coli
K12 TG1 that constitutively expressed luxCDABE(lux) genes from the marine microorganism
Photobacterium leiongnathi 54D10. Naswar toxicity
was determined by the degree by which bacterial
luminescence was inhibited.
We also examined bacteria with an inducible
glow, namely E. coli K12 MG1655 that carriedplasmids with lux gene mergers for soxS or katG
(GosNIIgenetika, Russia). This strain wascharacterised by initially low luminescence, but was
induced specifically upon exposure to thesuperoxide anion and hydrogen peroxide

I = RLUc0 × RLUtn/RLUcn × RLUt0(1),

where c and t are the RLU values of the control andtest samples at the 0 and nth minute of themeasurement.
Statistical processing

All experiments were performed in triplicate.
Statistical analysis was performed using a one-way
analysis of variance (ANOVA) followed by the
Newman-Keuls test when appropriate. Values of p <0.05 were considered statistically significant. Factor
inhibition (Fi) was calculated at the most effective
concentration used.

Test strain preparation
Lyophilized “Ecolum” was reconstituted by theaddition of chilled distilled water. The bacterial
suspension was incubated at 2-4°C for 30 min andthen allowed to reach 15-25°C. One hundred μl was
add to wells of opaque plastic 96-well plates prefilled with an equal volume of naswar mixtures.
The E. coli pSoxS lux and pKatG lux strains
were grown for 18-24 h on Luria Broth (LB) agar in
the presence of 100 μg/ml of ampicillin, transferred
into fresh LB broth and then grown to the early
exponential phase (OD540 = 0.35). Bacteria wascollected by centrifugation, slurred in 0.85% NaClsolution and 50 μl bacteria was added to wells of
opaque plastic 96-well plates, pre-filled with anequal volume of the naswar mixture. The mix was
incubated for 15 min and then an additional 150 µl
LB broth was added..

RESULTS
Bioluminescent analysis results
Overall, our bioluminescent results showed
differences in the level of toxicity of each naswar
sample with regards to the test organism depending
upon the concentration and type of luminescence.
Sample A, at concentrations from 1 to 0.031
mg/ml mixed with "Ecolum", inhibited bacterial
luminescence compared to control, a result thatindicated the development of a toxic effect. At 0.015
mg/ml, sample A initially slightly inhibited“Ecolum” bioluminescence, but after 130 min,luminescence was inhibited by 70%. Dilutions from0.008 mg/ml to 0.001 mg/ml did not inhibit
luminescence and thus did not promote toxic effects(Figure 1).

Bioluminescent analysis protocol
Bacterial luminescence inhibition was performedon 96-well opaque plastic plates. Sample wells
contained a 1:1 mixture of naswar and luminescent

223

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 1 Luminescence dynamics for “Ecolum” when in contact with sample A
Results from sample B also revealed
concentration-dependent
negative
effects.
Concentrations of 1, 0.5 and 0.25 mg/ml reduced
luminesce by 95% over the experimental period (180min). These results represented the greatest toxic
effects. Subsequent dilution of sample B from 0.125
to 0.0625mg/ml suppressed 75% of “Ecolum”

bioluminescence by 110 min. At 0.031 mg/ml,
luminescence was decreased after 60 min
incubation, but it returned to the control level as
incubation time progressed. This finding indicatedacute toxicity without prolonged action. Subsequent
dilutions of sample B did not alter luminescence andthus did not promote toxic effects (Figure 2).

Fig. 2 Luminescence dynamics for “Ecolum” when in contact with sample B
In pilot testing, sample C markedly reduced“Ecolum” luminescence by 90%, and subsequent
dilutions (1, 0.5, 0.25 and 0.0625 mg/ml) reduced
the intensity by 50-80% compared to control. These
results indicated high toxicity from this test material.
The
0.031
mg/ml
concentration
reducedbioluminescence by 55%. At 0.015 mg/ml,

luminescence was suppressed over the first 100 min,but gradually returned to the control level. Thus, thisconcentration promoted acute toxicity. Finally,
subsequent sample C dilutions did not alter
luminescence and thus did not promote toxicity(Figure 3).

224

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 3 Luminescence dynamics for “Ecolum” when in contact with sample C
Concentrations of sample D from 1 to 0.031
mg/ml inhibited “Ecolum” bacterial luminescence to
68% relative to the control, a result that indicatedacute toxic action. At 0.015 mg/ml, luminescence

was suppressed by 35%, but only after 70 min
incubation. Subsequent sample D dilutions (0.008
mg/ml to 0.001 mg/ml) did not promote toxic effects(Figure 4).

Fig. 4 Luminescence dynamics for “Ecolum” when in contact with sample D
Our data indicated that the four naswar samples
promoted differential toxicity. We used this data tocalculate the EC50, a measurement that
corresponded to the concentration that caused 50%
bacterial bioluminescence inhibition compared tocontrol after 180 min of exposure. The EC50
concentrations (Table 2) were: 0.125 mg/ml forsample A, 0.031 mg/ml for sample B, 0.008 mg/ml
for sample C and 0.0625 mg/ml for sample D.

Table 1 Percentage of surviving bacteria (%) after exposure to naswar mixtures
SampleConcentration, mg/ml
Сontrol

0.008

0.015

0, 031

0.0625

0.125

0.25

0.5

1

А

100

97,3

84,2

74,5

58,7

51,4

35,5

19,6

10,2

B

100

63,0

58,6

50,2

43,1

36,9

25,6

19,4

7,8

C

100

65,1

50,9

48,9

35,6

19,4

12,8

8,2

4,5

D

100

89

78

65

50,4

47,3

30,1

24,5

16,7

We next examined the effect of the four naswar
samples on bacterial strains with inducible

bioluminescence. The E. coli psoxS lux strain
luminesces in response to increased superoxide
225

SEE - Bangkok, Thailand, Nov.11-13, 2019anion. Measuring glow intensity for this strain
would allow us to assess whether the naswar
samples caused and/or affected stress and theregulation of its dynamics
Our findings indicated that contact of the Ourfindings indicated that contact of the bacteria withthe analysed substances led to reactive oxygen
species formation, specifically through activation of
the psoxS promoter cassette and transcription of thereporter luxCDABE genes (Figure 5).

Finally, we examined luminescence induction in
E. coli pRecA lux bacteria. In this strain,
luminescence induction occurs due to the SOS
response as a result of DNA damage formed duringoxidative stress (Figure 7).

Fig. 7

Fig. 5

Factor induction of luminescence (Fi) for E.
coli K12 MG1655, which carried a plasmidwith pSoxS lux, after contact with naswar
samples.

We found that a wide range of naswar sample
concentrations promoted similar luminescenceinduction as a result of oxidative-stress-induced
DNA damage. Sample C produced the mostpronounced effect compared to the other samples,
whereas sample D promoted minimal damage. Thus,
sample C especially promoted the development ofoxidative stress cascades, effectively generatinghydroxyl radicals that led to pronounced damage tothe genetic apparatus of target cells.

The most pronounced luminescence induction
occurred with exposure to sample B. This finding
indicated that sample B likely led to superoxideanion formation presumably due to electron transfer
frommolecular
oxygenandsubsequenttransformation of the peroxide hydrogen. There wasonly minimal luminescence induction for sample A
We confirmed the observations with the E. colipsoxS lux strain using E. coli pkatG lux (Figure 6).
pkatG is a stronger promoter than psoxS, and thus
this experiment allowed us to rule out luminescenceinduction due to sample peculiarities.

Fig. 6

Factor induction of luminescence (Fi) for E.
coli K12 MG1655, which carried a plasmidwith pRecA lux, when in contact withnaswar samples.

DISCUSSION
To address environmental challenges, as well as
for studies in medicine and agriculture, basic
biology requires fast and convenient analysis
methods substance toxicity [13]. Bioluminescentanalysis is one of the most promising methods forbiological environmental monitoring. Biotests on
luminescent bacteria provide a quantitative toxicity
measure and often surpass older, famous biotests
with regards to speed, accuracy, sensitivity andsimplicity, and allow researchers to examine a
considerable number of toxicants [14, 15]. Using thelux genes as a marker for gene expression isimportant in the study of pathogenicity, virulence,
adaptation and secondary metabolism. There areseveral examples in the literature of how to use thismethod to study transcription. Recombinantbioluminescent strains were created and used todetermine toxicity of different antibiotics and heavy
metals [16, 17]. There were also reported strains ithhigh specificity to a particular toxic agent [18, 19].
Further, there is evidence of the benefit ofbioluminescent reporters to determinate toxicity of

Factor induction of luminescence (Fi) for E.
coli K12 MG1655, which carried aplasmids with pkatG lux, when in contact
with naswar samples.
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SEE - Bangkok, Thailand, Nov.11-13, 2019heavy metals and phenols in water and soil samples[20-22].

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CONCLUSIONS
Our data suggest the possibility of using
this type of research to analyse tobacco chewing
blends. The results obtained here allow us toconsider one of the basic negative toxic
mechanisms, namely oxidative stress formation withconsequent damage to intracellular structures,
particularly DNA. Manifestation of this biologicalactivity severely alters target cell energy metabolism
and results in bacterial growth inhibition anddysregulated luminescence. The main cause of thiseffectcould
bereducedtransmembraneelectrochemical potential with subsequent bacterial
luminescence diminution. Thus, naswar toxicity
results from critical damage to cell structures andsubsequent cell death.
Studying the bioluminescence intensity of“Ecolum” allowed us to assess the quantitative anddynamic components of several naswar samples.
Indeed, we observed a general dose-dependent
reductioninbioluminescence.
Overall,bioluminescent analysis will first provide data about
possible substance toxicity that can serve as thebasis for follow-up examinations.
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Zhang N., Van Sinderen D., High resolution invivo bioluminescent imaging for the study ofbacterial tumour targeting. PLoS One. Vol. 7(1).
2012, pp.30940-30949.
[20] Charrier T., Durand M., Affi M., Jouanneau S.,
GezekelH.,
ThouandG.,
Bacterialbioluminescent biosensor characterization for on-line monitoring of heavy metals pollutions in
waste water treatment plant effluents. In:“Biosensors” book. Vol. 11. 2010, pp. 217-223.
[21] Ranjitha P., Karthy E., Detection of heavy metal
resistance bioluminescence bacteria using
microplate bioassay method. Elixir Pollution.
Vol. 40. 2011, pp.5108-5112.
[22] Thakre N. and Shanware A., Promising
Biological Indicator of Heavy Metal Pollution:
Bioluminescent Bacterial Strains Isolated andCharacterized from Marine Niches of Goa,
India. Indian Journal of Microbiology. Vol. 55.
No. 3. 2015, pp.327-332.

228

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE MODIFIED DECOMPOSITION METHOD FORSOLVING VOLTERRA FREDHOLM INTEGRODIFFERENTIAL EQUATIONS USING MAPLE
1

Dalal Adnan Maturi 1
Departement of Mathematics, Faculty of Science, King Abdulaziz University, P.O.Box 42664,Jeddah 21551,
Saudi Arabia
ABSTRACTIn this paper, Vito Volterra studied the phenomenon of population growth, and new types of equations havebeen developed and termed as the integro–differential equation. Here we will address the Mixed Volterra Fredholm
integro-differential equation. We introduce some basic idea of Modified Decomposition method (MDM) to solve
the Volterra-Fredholm integro-differential equation. The modified decomposition method (MDM) is applied tosolve the Volterra Fredholm integro-differential equation. Based on the proposed after treatment technique, thetruncated series solution obtained by the Modified Decomposition method (MDM) can be expressed as anotherseries in terms of the independent sine and cosine trigonometric functions. In addition, examples that illustrate thepertinent features of this method is presented, and results of the study is discussed. Also, we compare the resultwith exact solution, and we investigate the error between numerical solution and exact solution and draw the graphof function by using Maple18. Finally, the results reveal that the Modified Decomposition method is very effective
and convenient for solving Volterra Fredholm integro-differential equation.
Keywords: Volterra Fredholm Integro-Differential equation, Modified Decomposition method, Maple18 .
equation:

INTRODUCTION𝑥u

Integrated stems from the mathematical modelingof many complex real-life problems of differential
Has been formulated many scientific .equations
phenomena using integrated differential equations
Solution integrative non-linear equation is .]5.6]
much more difficult than the linear equation of the
Therefore, the use of different types of .analyticalnumerical methods to obtain an approximate solution
effective [1-4]. Numerical solution of Volterra
integral equation of second kind using Implicit
Trapezoidal [7,11].Adomian Decomposition method
of Fredholm integral equation of the second kindusing Maple and MATLAB[8,10].Application of
Adomian Decomposition method for solving ofFredholm Integral Equation of the Second Kind [9].
The Modified Decomposition Method for Solving
Volterra Integral Equation of the Second Kind Using
Maple [12].
The main goal in this article is to apply the Modified
Decomposition method (MDM)to the Volterra
Fredholm integro-differential equation using Maple
and then compare the exact solution results with theapproximate results obtained from the algorithm
Maple. By showing some examples we see how thismethod gives the best results.

(𝑛) (𝑥) = 𝑓(𝑥 ) + 𝜆1 ∫ 𝐾1 (𝑥, 𝑡) 𝑢(𝑡)𝑑𝑡𝑎𝑏+ 𝜆2 ∫ 𝐾2 (𝑥, 𝑡) 𝑢(𝑡)𝑑𝑡. (1)𝑎And the mixed form
𝑥 𝑏u(𝑛) (𝑥) = 𝑓 (𝑥 ) + 𝜆 ∫0 ∫𝑎 𝐾(𝑟, 𝑡) 𝑢(𝑡)𝑑𝑡𝑑𝑟,(2)d𝑛 (𝑥)

where u(𝑛) (𝑥) = 𝑑𝑥 𝑛 .
𝑢 (𝑥 )
𝑛−1

=∑
𝑘=0

1
𝑏 𝑢𝑘 + 𝐿−1 (𝑓(𝑥))
𝑘! 𝑘
𝑥 𝑏

−1 (𝜆 ∫ ∫+𝐿

𝐾(𝑟, 𝑡) 𝑢(𝑡)𝑑𝑡𝑑𝑟),

(3)

0 𝑎

where 𝐿 is assumed invertible and 𝐿−1 is an
The standard Adomian method defines the solution
𝑢(𝑥 ) by the series 𝑢(𝑥 ) = ∑∞𝑛=0 𝑢𝑛 (𝑥).
The modified decomposition method
𝑢0 (𝑥 ) = 𝑓1 (𝑥 )𝑥 𝑏𝑢1 (𝑥) = 𝑓2 (𝑥 ) + 𝐿−1 (𝜆 ∫ ∫ 𝐾 (𝑟, 𝑡) 𝑢0 (𝑡)𝑑𝑡𝑑𝑟),
𝒙

0 𝑎
𝒃

𝒖𝒏+𝟏 (𝒙) = 𝑳−𝟏 (𝝀 ∫𝟎 ∫𝒂 𝑲(𝒓, 𝒕) 𝒖𝒏 (𝒕)𝒅𝒕𝒅𝒓).(4)The use of the modified decomposition method not
only minimizes the computations but avoids the useof the heiger order Adomian polynomials for suchcases.

THE MODIFIED DECOMPOSITIONMETHODTo illustrate the basic idea of this method, we
consider the following general non-linear differential
229

SEE - Bangkok, Thailand, Nov.11-13, 2019𝒖(𝟎) = 𝟏, 𝒖′ (𝟎) = 𝟎.
EXAMPLE

Applying the Modified Decomposition Method
using Maple we find

Example1. Consider the Volterra Fredholm integro
differential equation

Table 2 Numerical results and exact solution of
Volterra Fredholm integro differential
equation for example 2𝒙 𝟏

𝒖′ (𝒙) =𝟏 𝟐
𝒙 − 𝒆−𝒙 + ∫ ∫ 𝒓𝒕𝒖(𝒕)𝒅𝒕𝒅𝒓,
𝟒

𝒖 ( 𝟎)

𝟎 𝟎

𝒙

𝒖(𝒙)

0.10000
0.20000
0.30000
0.40000
0.50000
0.60000
0.70000
0.80000
0.90000
1.00000

0.9975000
0.9800000
0.9325000
0.8400000
0.6875000
0.4600000
0.1425000-0.2800000-0.8225000-1.5000000=𝟎
Applying the Modified Decomposition Method
using Maple we findTable 1 Numerical results and exact solution of
Volterra Fredholm integro differential
equation for example 1
𝒙

𝒖(𝒙)

𝑬𝒙𝒂𝒄𝒕

𝑬𝒓𝒓𝒐𝒓

= 𝟏 − 𝒆𝒙0.10000
0.20000
0.30000-0.1051709-0.2214028-0.3498588-0.1051710-0.2214035-0.3498613

0.0000001
0.0000007
0.0000025

0.40000-0.4918247-0.4918306

0.0000059

0.50000-0.6487213-0.6487328

0.0000116

0.60000-0.8221188-0.8221388

0.0000200

0.70000-1.0137527-1.0137845

0.0000318

0.80000-1.2255409-1.2255883

0.0000474

0.90000-1.4596031-1.4596706

0.0000675

1.00000-1.7182818-1.7183744

0.0000926

𝑬𝒙𝒂𝒄𝒕
=𝟏
𝟓
− 𝒙𝟑
𝟐

0.9975000
0.9800000
0.9325000
0.8400000
0.6875000
0.4600000
0.1425000-0.2800000-0.8225000-1.5000000

𝑬𝒓𝒓𝒐𝒓

0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000

Fig. 2 Plot 2D of the exact solutions result Of
Volterra Fredholm integro differential equationfor example 2.
Example 3. Consider the Volterra Fredholm integro
differential equation𝒙

Fig.1 Plot 2D of the exact solutions result Of
Volterra Fredholm integro differential equationfor example 1.

′′(𝒙)

𝒖

𝟎 −𝟏

𝒖(𝟎) = 𝟏, 𝒖′ (𝟎) = 𝟏.
Applying the Modified Decomposition Method
using Maple we find

Example2. Consider the Volterra integral equationof second kind
𝒙 𝟏
′′(𝒙)

𝒖

𝟏

𝟏
= 𝟐𝒙 − 𝒙𝟐 + ∫ ∫(𝒓𝒕𝟐 − 𝒓𝟐 𝒕)𝒖(𝒕)𝒅𝒕𝒅𝒓,
𝟑
𝟑

Table 3 Numerical results and exact solution of
Volterra Fredholm integro differential= −𝟏𝟓𝒙 + ∫ ∫ 𝒓𝒕𝒖(𝒕)𝒅𝒕𝒅𝒓,
𝟎 𝟎

230

SEE - Bangkok, Thailand, Nov.11-13, 2019equation for example 3.
𝒙𝒖(𝒙)0.10000
0.20000
0.30000
0.40000
0.50000
0.60000
0.70000
0.80000
0.90000
1.00000

1.9000000
2.8000000
3.7000000
4.6000000
5.5000000
6.4000000
7.3000000
8.2000000
9.1000000

𝑬𝒙𝒂𝒄𝒕= 𝟏 + 𝟗𝒙1.9000000
2.8000000
3.7000000
4.6000000
5.5000000
6.4000000
7.3000000
8.2000000
9.1000000

10.0000000

10.0000000

Fig. 3This paper was supported by the Deanship ofScientific Research (DSR), King Abdulaziz
University, Jeddah.

𝑬𝒓𝒓𝒐𝒓

REFERENCES

0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000
0.0000000[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.
[3] Abdul-Majid. W., Linear and Nonlinear Integral
Equations, Higher Education Press, Beijing,
China, 2011.
[4] Peter. L., Analytical and Numerical Methods for
Volterra Equations, Studies in Applied
Mathematics 7, SIAM, Philadelphia, 1985.
[5] David M. Doddrell, Lawrence K. Forbes, andStuart Crozier," Calculating current densities
and fields produced by shielded magnetic
resonance imaging probes,"SIAM Jornal on
Applied Mathematicas, vol.57,no2,pp.401425,1997.
[6] Parand .K., Abbasbandy. S., Kazem. S, and Rad
J. A., “A novel application of radial basis
functions for solving a model of first-orderintegro-ordinary differential equation,”
Communications in Nonlinear Science andNumerical Simulation, vol. 16, no. 11, pp.
4250–4258, 2011.
[7] Dalal A.M, Amani..Z.B.l, Badreeh..M. G.,
Numerical Solution of Volterra Integral Equationof Second Kind Using Implicit Trapezoidal,
Journal of Advances In Mathematics,
Vol8,No.2,pp.1540-1553,2014.
[8] 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.
[9] 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 Fredholm integro differential
equation for example 3.

CONCLUSION
In this paper, the Modified Decomposition
Method to the solution of Volterra Fredholm integro
differential equation numerical results demonstratethat our method is an accurate and reliable numerical
technique for solving Volterra Fredholm integro
differential equation. Note that the results ofexamples 1, 2 and 3 show that the exact solution isvery close to the approximate solution and that theerror rate between them is very small, which proves
the efficiency of the method used. This is shown in
the tables and graphics from 1-3. Finally, The
Modified Decomposition Method using Maple can beeasily extended and applied to linear or nonlinear
Fredholm and Volterra integral equations of the firstor second kind.

[10] 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[11] Dalal A.M. and Honida M.M., Numerical
231

SEE - Bangkok, Thailand, Nov.11-13, 2019

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.
[12] Dalal .A.M., The Modified Decomposition
Method for Solving Volterra Integral Equationof the Second Kind Using Maple, International
Journal of GEOMATE, Oct., 2019, Vol. 17,
Issue 62, pp.23-28.Special Issue on Science,
Engineering and Environment, ISSN: 21862982, Japan.

232

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STUDY OF ELECTRON FLUXES IN IONOSPHERE-PLASMASPHERE
COUPLING FROM WHISTLERS OBSERVED AT LOW LATITUDEGROUND STATION JAMMU L= 1.17
M. Altaf
Department of Physics, GDC Pattan, Govt. Higher Education Department J&K, India
ABSTRACTThe downward flux of the ionization are measured by whistlers recorded at low latitude ground station Jammu(geomag lat 220 26/) and L= 1.17, on 5 June 1997. The whistler data shows a variation in dispersion with time. Thisdecrease in dispersion is interpreted in terms of a corresponding decrease in the electron content of tubes ofionization and is compared with that obtained by Park (1972, Technical Report, Stanford university) for midlatitudes. By Park’s (1972) expressions the equatorial electron density and electron tube content NT values werecomputed. Our measurements from whistlers show an average downward flux 2.8×10 8 electrons cm-2 S-1. The
simple diffusion equation which relates the flux to the ionization gradient by the ambipolar diffusion coefficient isagain computed shows that the flux computed is within an order of magnitude less than that derived from thedispersion data. It is, therefore, argued that other processes like E × B drifts should play a dominant role incontrolling the transport of ionization at low latitudes.
Keywords:- flux of the ionization, equatorial electron density, electron tube content, Plasmasphere, Ionosphere,
dispersion
neutral atmosphere drive the ionization up themagnetic field lines where the loss rate of ionization
by dissociative recombination is reduced (Hansen
and Patterson, 1964, Park 1970, Carpenter andBowhill, 1971, Risbeth, 1968). It is found that anight-time production rate of 1 cm-3 s-1 contribute to
the maintenance of the night-time F-layer to go alongwith the critical flux of 1.5× 107 cm-3 s-1 (Risbeth,1968). It appears that the nocturnal F-layer cannot be
explained satisfactorily without involving downward
diffusion of ionization of the order of 108 cm-3s-1
which appears to be sufficient for the night-time
production rate of ionization of 1 cm-3 s-1 due to thecharge exchange with H-ions from plasmasphere(Carpenter and Bowhill, 1971). In many techniques,
whistler methods yield reliable data on themorphology and dynamics of the plasmasphere, on
magnetospheric electric fields and on coupling fluxes
between ionosphere-plasmasphere (Carpenter, 1966,
Park, 1972). Mid-latitude whistler study of theelectron content of magnetospheric tubes ofionization reported the upward daytime fluxes of 3×
108 electrons cm-2 s-1 across 1000km level anddownward flux at night of the order of ~ 1.5 × 10 8electrons cm-2 s-1, an amount is sufficient to maintainthe nocturnal F-layer (Park, 1970). The propagation
characteristics and association of plasma behavior oflaw latitude whistlers have been extensively studies
by Hayakawa and Tanaka (1978). The low latitude
whistlers are very useful for studying the unsolved
problem in this field which is more susceptible topropagation conditions like duct excitation,

INTRODUCTION
An important characteristic of low latitude
whistler propagation is the low value of the
maximum heights reached by the associated L-values
are very low. Thus for Gulmarg L=1.2, for Nainital
L=1.12 and Jammu L =1.17 . It shows that the path
for whistlers observed at Jammu is within the upperboundary of the F-layer, this boundary is not welldefined but is identified as the level where light ions
(hydrogen, helium) becomes more numerous than theheavier ions (Chiefly oxygen). Even though, thisupper boundary is found to exhibit diurnal andgeographical height variations in the range of 6002000 km (Mayer et al., 1967, Somayajulu, 1968,
Brinton et al., 1969). It is fact to identify it at 1000km, which is taken as the lower boundary of theplasmasphere. Thus, a study of whistler at Jammu
gives us information about the top of the F-layer ofthe ionosphere.
In addition to the production and loss mechanism,
the important problem is the study of the upper Flayer which is the transport of ionization. In general,transport of ionization in the top side F-region may
result from (1) E × B drifts (2) ambipolar diffusion
along the magnetic field (3) interaction between
ionization and neutral winds. The combination at theequator of (1) and (2) explains the well known
anomaly called the “equatorial anomaly”.
The important problem is the maintenance of thenocturnal F-layer, in which several effects aresupposed to contribute for this. The wind in the233SEE - Bangkok, Thailand, Nov.11-13, 2019

ionospheric transmission etc. Hayakawa et.al (1990)
on night time low latitude whistlers and theirpropagation mechanism, pointed out that the
propagation of whistlers in the earth-ionospherewave-guide after ionospheric transmission is more
likely to be towards higher latitudes than towards theequator, and sub-ionospheric propagation seems to
exhibit a horizontal beaming around the magnetic
meridian plane. These characteristics of theobservation have interpreted either in terms of nonducted or field aligned propagation and are stronglyof the opinion that this is inductive of field-aligned
propagation for very low latitude whistlers localized
in geomagnetic latitude of 10o – 14o.
In this paper an attempt has been made to
determine the downward flux of ionization from thewhistler studies at low latitude. The data showed asmooth variation in dispersion with time. Thisvariation in dispersion is interpreted in terms of acorresponding decrease in the electron content oftubes of ionization. At low latitudes the maindifficulty in whistler analysis is to determine the nose
frequency (fn) and nose time delay (t n) with areasonable degree of precision.For the analysis of
non nose whistlers, the downward flux of ionizationis computed by means of an accurate curve fitting
method developed by Tarcsai (1975) from thewhistlers recorded on 5 June 1997 at our low latitude
Jammu and is compared with that obtained by Park
(1972) for mid latitudes. The magnetospheric electricfield along with protonosphere coupling fluxes using
simultaneous phase and group path measurements on
whistler mode signals (Andrews et al. 1978). The
flux of ionization is computed again from the simple
diffusion equation which relates the flux to ionization
gradient through the ambipolar diffusion coefficient.
It is shown that the flux computed is within an orderof magnitude less than that derived from thedispersion data. It is argued that the E × B drifts playa very important role in controlling transport ofionization at low latitudes.

whistlers have been recorded (Lalmani et al., 2001).
Altogether more than hundred whistlers wererecorded and the occurrence rate showed a feeble but
discernible periodicity (Rao and Lalmani, 1975).
During this period several whistlers were recorded(Singh et al., 2000).
Fig.1 (a) presents dynamic spectrum of shortwhistlers (marked A, B, C, D, E, F and G, selected
for the analysis) in the frequency band 3-4.5 KHz
recorded at Jammu at 2212 IST on June 5, 1997. In
the frequency band 1.7-3 KHz large number of
frequency components are missing and signals
resemble more like emissions rather than whistlers.
Further, VLF waves in both the frequency bands do
not appear simultaneously, rather they appear
alternately. Fig.1 (b) shows dynamic spectrums ofshort whistlers (marked 1, 2, 3 and 4, selected for the
analysis) and VLF emissions recorded at Jammu at
2147 IST. Whistlers are banded and diffused in thefrequency range 2.7-3.7 KHz and are repeated intime. The time interval between the 55 events is notconstant. Unusual VLF noises are also seen in the
spectrum.

Data Selection and Method of Analysis
At low latitudes, the whistler occurrence rate is
low and sporadic. But once it occurs, its occurrence
rate becomes comparable to that of mid- latitudes(Hayakawa et al., 1988). Similar behavior has also
been observed at our low latitude Indian stations. All
the Indian stations are well equipped formeasurements of VLF waves from natural sources.
For the present study, the whistler data chosencorresponds to June 5, 1997 for Jammu, On 5 June
1997 at Jammu station whistler activity started
around 2140 h IST (Indian Standard Time) andlasted upto 2245h IST. During this period about 100

Fig. 1. (a) Dynamic spectrum of whistlers recorded
at Jammu June 5, 1997. Whistlers are marked by
A,B,C,D,E,F and G. (b) Dynamic spectrum ofwhistler recorded at Jammu June 5, 1997. Whistlers
are marked by 1, 2, 3 and 4.
234

SEE - Bangkok, Thailand, Nov.11-13, 2019

Tarcsai (1975) has developed a curve fitting
technique for the analysis of middle and high latitude
whistlers. This technique has also been applied
successfully to those low latitude whistlers whose
propagation path are low below L = 1.4 (Singh, 1997;
Sonwalker and Inan, 1995; Ohta et al., 1996;Tarcsai,1975). Further technique is found suitable not only
for long and good quality whistlers but also for shortand faint whistlers. The computer programme written
for the purpose requires input data such as frequency
time (f, t) values scaled at several points along
whistler trace appropriate for F2, zero frequency
dispersion (Do), and a suitable ionospheric model etc.
The output results include the L-value of
propagation, equatorial electron density, total tube
content etc. we have adopted this programme for the
analysis of nighttime whistlers recorded at our station
Nanital, Varanasi and Jammu during quiet days.
At low L-values, the curve fitting method ofTarcsai (1975) would not change too much theequatorial electron density and total electron content
values compared to the systematic errors which are
inherent in all of the existing nose extension methods.
These systematic errors originate from theapproximations used for the refractive index and forthe ray path in the derivation of the analytic
expressions for the dispersion and from the difference
between the theoretical and actual distribution plasmaalong the field lines ( Tarcsai et al., 1989). To
examine its validity we analyzed few whistlers
recorded at Jammu using this method as Dowden
Allcock (1971) Q- technique. Both methods yielded
results within ± 10%. Further, it is to be noted that
the Tarcsai’s method has successfully been used in
the analysis of low latitude whistlers (Singh et al.,1992).
For the determination of Do fn and tn Ho andBernards (1973) approximate function for thedispersion of whistlers is given by (Tarcsai 1975)

A

3 n  1
 n (1   n )

n 

fn

(2)
Here

f Heq

Where fn is the nose frequency for which travel time
tn is written as D  2 
tn   1/o2  

f
(1


)
n 
 n 
(3)
If the causative sferic is unknown, and the travel
times at different frequencies of the whistler traces
are measured with respect to an arbitrary time origin,then it is necessary to introduce a new parameter T,

t* ( f )  t( f )  T 

Do ( f Heq  Af )Tf ( f Heq  f ) D f Heq f n ( f Heq  f n )  f (3 f n  f Heq ) 
 o
 T
f n ( f Heq  f )( f Heq  f n ) fwhich gives the difference in time between thechosen origin and the actual causative sferic. Using T
and equation (1) the measured travel time t *(f) can be
written as(4)

In this equation there are four unknown
parameters; Do, fHeq,,T and fn . In the following weproceed in two different ways; either we assume f n to
be an independent parameter or we adopt a model forthe electron density distribution. This helps us in
reducing the number of unknowns to three. In thepresent study, the latter procedure is followed. Thus
those values of Do fHeq, and T searched for, which fit
best to the measurements in the least square sense,
i.e, which minimize the sum of the weighted squaresof residuals ( f Heq  Af ) D( f )  t ( f ) f 1/ 2  Do  f Heq  f 
(1)
Where
Do = zero frequency dispersion
fHeq =
equatorial electron
gyrofrequency
f = Wave frequencyt(f) = travel time at frequency f,

2nM   Wk t

and

k 1

*
mk

 t ( Do , f Heq , T ) 
*
ck

(5)
Where the subscripts m and c refer to themeasured and computed t *values, respectively, wk the235SEE - Bangkok, Thailand, Nov.11-13, 2019weights given to the individual measurements, andthe summation is to be taken over the points of thewhistler trace scaled at frequency fk. As is known
from the theory of least squares estimation, in anonlinear case the determination of the parameterswhich correspond to the condition M= minimum, canbe accomplished through linearization by expanding
the residuals into a Taylor series and then using an
iteration procedure (Tarcsai, 1975), we have done
exactly this. Let us introduce the vector X whose
components are
X1 = DoX2=

diffusive equilibrium model, ( DE-1) of the electron
density distribution, Λn can be calculated from fn as n  (3.5475  0.47351F  0.065879 F 2 ) 1
(11)
Where F = log10 f n
Also as Λn = fn/fHeq, we can write
fn,i+1=Λni(12)Where, Λni is computed from equation (11) with
fni obtained in the preceding step of the iteration.
Thus, for a converging, fni, the nose frequency also
converges. From this it is clear that in the course of
iteration the value of A is also changed successively
but in general rather weakly, and it converges very
fast.The iteration procedure outlined can be stopped,
if the magnitude of the corrections decreases below acertain fixed level, or the sum of weighted squares of
the residuals stabilizes. After the criterion of
convergence has been fulfilled, i.e., the iteration has
been finished, t n can be computed from equation (3).
In order to ensure the procedure against divergence it
is necessary to introduce a multiplicater m into
equation (7) we have

fHeq

(6)
X3 = T
Then assuming that the values of Do , fHeq and T are
known at iteration(i-1), the improved solutions at the ith step can beobtained as
X1

=

Xi-1

+

fHeq,i+1∆X1(7)
Where the vector differential corrections ∆X1 is givenin each step of the iteration byX  A/WY ( A/WY ) 1
(8)

X1

=

Xi-1

+

m∆X1

(13)

In equation (8) the prime indicates matrix
transposition A is then n×3 matrix of the partial
derivatives of t* with respect to the unknown
parameters, whose elements can be computed, using
equation (4)Where 0 < m ≤ 1 and the actual value of m isproperly varied in the course of iteration. Generallym ≤ 0.1 – 0.3 at the first two steps and it is increased
to unity. Using values of Do and fHeq (or fn and tn )obtained by the curve fitting method, we can computethe equatorial radius of the whistler duct (L) the local
electron density at the geomagnetic equator (neq ) andat a height of 1000km (N) ; and the tube electron
content (NT). After Park (1972) and Tarcsai (1975),
and using equation (3) for t n we can write t * akj   x 
 j  f  fk
(9)
W is n×n square matrix of the measurement weights,
which is diagonal for uncorrected measurement
errors, and Y is the column vector of residuals withelements

1/ 3
L  8.735 105 f Heq(14)
Where fHeq is in Hz.

*
Yk  tmk
 tck*(10)
In evaluating the matrix formula of equation (8),those values of Do ,fHeq and T are to be used, ofcourse, which have been obtained in the previous stepof the iteration. No weighting has been used ingeneral (wkk = 1, wkj = 0, k ≠ j). The value of fn has
also been improved in each step, in the following
manner. According to Park (1972) for typical5/ 3
neq  K e f ntn2 L5  K e/ Do2 f Heq

(15)

1/ 3
NT  KT f ntn2 L1  KT/ Do2 f Heq

(16)

5/ 3
N  K1 f ntn2 L5  K1/ Do2 f Heq(17)

Where the constants K/e and K/T are weakly
dependent on fn and Λn Tracsai (1975).
236

SEE - Bangkok, Thailand, Nov.11-13, 2019

TABLE 1. Parameters of whistlers observed at Jammu ground station estimated from the whistler dispersion
analysis using accurate curve fitting technique. W is the whistler number, IST is the Indian Standard Time, D o isthe dispersion of whistler, fn is the whistler nose frequency, fHeq is equatorial gyro frequency , L-value is in earths
radii, ne is the equatorial electron density.
W Station
Dates&Year
IST
Do (sec1/2)
fn (KHz)fHeq (KHz)
L Valuene(cm-3)
NT(cm-2)
1
Jammu
05June 1997 21:40:25 65.5±1.0
4.2±0.03
11.37±0.07
4.25±0.01
159±3
1.9×1013
2
Jammu
05June 1997 21:47:42 81.9±1.1
3.39±0.013 10.59±0.034 4.35±0.005 220±5
2.9×1013
3
Jammu
05June 1997 22:47:50 88.9±1.8
3.82±0.02
10.27±0.05
4.39±0.07
247±8
1.9×1013
4
Jammu
05June 1997 22:47:55 87.6±1.4
3.85±0.01
10.37±0.03
4.38±0.00
244±6
3.4×1013
5
Jammu
05June 1997 22:12:20 28.8±1.2
8.15±0.72
21.98±1.95
3.41±0.10
93±6
3.3×1012
6
Jammu
05June 1997 22:12:51 28.9±0.9
6.29±8.21
16.96±0.55
3.72±0.04
61±1
4.5×1012
7
8
9
10
11

Jammu
Jammu
Jammu
Jammu
Jammu

05June 1997
05June 1997
05June 1997
05June 1997
05June 1997

22:13:22
22:13:53
22:14:24
22:14:55
22:15:26

35.5±1.738.3±1.926.1±0.6
22.8±1.738.9±1.2

6.13±0.25
4.61±0.10
5.76±0.13
5.99±0.41
5.06±0.09

16.51±0.66
12.42±0.28
15.53±0.35
16.17±1.1013.62±0.24

3.75±0.05
4.12±0.03
3.83±0.02
3.78±0.08
4.00±0.02

4.2×1012
6.3×1012
3.3×1012
2.6×1012
7.1×1012

88±2
63±4
43±4
35±1
76±3

Fig. 4. Variation of Electron tube content with LValue

Fig. 2. Variation of equatorial electron density (ne )with L.

Transport of Ionization and Ambipolar Diffusion
The observed flux of ionization at 500km can be
explained by ambipolar diffusion. The ambipolar
diffusion coefficient (δa), the gradient of electron
density ( n ) and the flux of ionization (F) are
related by (Carpenter and Bowhill, 1971)
F = δ a . n

(18)

The ambipolar diffusion coefficient δa (i.e parallel
to magnetic field) is approximately given by



T 
T1 

 a   i 1  e Fig.3. Variation of dispersion with time.

(19)
Where δa = diffusion coefficient of ions = K(Ti/mi
νin),
Here
Te = electron Temperature,
Ti = Ion temperature,237

SEE - Bangkok, Thailand, Nov.11-13, 2019

K = Boltnman Constant,mi = mass of ionand νin = collision frequency between ions andneutral particles.
The value of δa can be easily calculated with thereasonable values of Te , Ti and νin. The determinedvalue of δa at a height of 500 km is 2 × 1011 cm2 s-1(Okuzawa et al, 1971). To compute the magnitude of
n which can be determined from the electron
density distributions derived from whistlerobservatiobs. At a height of 500km this gradient isaround 5.4 × 10-3 cm-3 . Thus the magnitude of flux isabout 14.6 × 107 cm -2 s-1 which is within one orderof magnitude less than the value of 2.8 × 108 cm-2 s-1
obtained earlier.

attempted to explain the duct spreading in terms ofthe diffusion process.
However, most of the mid-latitude observations ofwhistlers suggest strongly that E×B drifts plays animportant role in the transport of ionization(Angerami and Carpenter, 1966, Park, 1970, 1972).
Therefore, it is concluded that the transport processes
like E×B drifts must be operating at these latitudes.
In terms of E×B drifts the downward movement ofionization have been interpreted and the electric field
inferred are westward in the morning sector (Parkand Meng, 1971, Altaf and Ahman, 2014). Tube
content profiles undergo complex and rapid changes
during the substorm (Park,1970,1971, 1972) probably
because of combination of E×B drifts and fluxes
along field lines , for this a westward electric field of~ 1mVm-1 is required. The westward electric field
estimated by whistler data is about 1 mVm-1 (Misra,
1979, Altaf and Ahmad, 2014) from the radial
motions of discrete field-aligned whistler ducts as
indicated by changes in nose frequency (Block andCarpenter, 1974; Hayakawa and Tanaka, 1978)
studied in favour of ducted propagation of low
latitude whistlers on the basis of theoretical andexperimental results. In the geomagnetic latitude of
10o-14o Hayakawa et. al (1990) have shown that the
localization of field-aligned propagation of low
latitude whistlers with the help of a speed direction
finding method. The computed results reported byother workers lie well within the range (Carpenter et.
a., 1972, Block and Carpenter, 1974, Andrews et. al,
1978, Park, 1978) from the ground based
observations, although their result refer to higher
latitudes. This study shows the important relationshipbetween vertical drifts and protonospheric fluxes andshows both are important in the night-time
ionosphere. Hence, it shows that E×B drifts plays anessential role in controlling transport of ionization at
low latitudes.

DISCUSSION OF RESULTS
It is useful information to compare the above
results of total electron content and the flux with thevalues of Park (1970) whose computations for the Lvalues between 3.5 – 5. The total electron content oftubes for the given L- values are according to Park
(1970, 1972)of the order of 1013 electrons cm-2 . Our
results are shown in the Table 1.which cannot makeany direct camparison with Park (1970, 1972). For
the L-values between 3.8 – 4.4, of our observations,the equatorial electron density (ne) and tube electron
content (NT) are 2×102 electron cm -3 and 1012 - 1013
electron cm-2 –tube respectively. This error at low
latitudes as compared with high latitudes may be dueto the use of the nose extension method of a non nose
whistler recorded at our low latitude station Jammu.
During the night time due to interchange ofionization between the ionosphere and protonosphereand downward flux of ionization from 500 km to
1000km at mid latitude. Similar downward flux ofionization is observed by our observations recorded
at low latitude station.
As per our calculations a downward flux ofionization is of the order of 2×108 electron cm-2 S-1
which is in agreement with Park (1970).The main
factor which render our result inaccurate is due to the
non-nose low latitude whistlers are observed. In the
top-side F-region the present studying of the transportof ionization is still worthwhile. If the measurementsof the F-layer by other methods simultaneously (Suchas incoherent scatter) are available then our studies
would have found much more valuable andphysically significant results. However, the value offlux of ionization obtained by ambipolar diffusion
process is 14.4×107 electron cm-2 S-1 which is less oneorder of magnitude than the value of 2×108 electron
cm-2 S-1 .This shows that ambipolar diffusion alone
cannot explain the observed results. The conclusion
is consistent with that of Okuzawa et. al. (1971), who

ACKNOWLEDGEMENT
The Author is thankful to the Govt Higher Education
Department J&K India and Principal GDC Pattan for
their keen interest to the present research.
REFERENCES[1] Park, C G, Methods of determining electron
concentration in the magnetosphere from nose
whistlers. Technical Report No. 3454-1 Radiosci. Lab, Stanford Electronics Lab. Stanford
University, Stanford. (1972)[2] Mayar, H C; Bruce, L H and Dunham G S. Ioncomposition and temperature in the topside
ionosphere, J. Geophys. Res. 72, 4391. (1967)
238

SEE - Bangkok, Thailand, Nov.11-13, 2019[3] Samayajulu, V V. Ph. D Thesis, B. H. U,
Varanasi, India. (1968)[4] Brinton, H C; Pharo, M W, III; Mayar, H C and
Taylor H A, Implications for ionosphericchemistry and dynamics of a direct measurementof ion composition in the F2 region, J.
Geophysics, Res. 74, 2941. (1969)[5] Park, C G and Carpenter, D I, Whistler evidanceof large Scale electron density irregularities in
the plasmasphere. J. Geophysics. Res. 75, 3825.
(1970)[6] Carpenter D L and Bowhill, S A, Aeronomy
Rept. No. 44. Univ. Of Illinois, Urbona IL(1974)[7] Riebeth, H. The effectof winds on theionospheric F2 peak-II. J. Atmos. Terr. Phys. 30,
63. (1968)[8] Carpenter, D L. Whistler studies of theplasmapause in the magnetosphere-I. Tempotal
variation in the position of the knee and someevidance on plasma motions near the knee. J.
Geophys. Res. 71, 693. (1966)[9] Hayakawa, M. And Tanaka, Y. On the
propagation of low latitude whistlers. Rev.
Geophys. Space Phys. 16, 111. (1978)[10] Hayakawa, M; Ohta, K and Shimakuram S.
Spaced directions finding of night time whistlers
at low and equatorial latitudes and theirpropagations mechanism. J. Geophys. Res. 95,
15091. (1990)[11] Tarcsai, G. Routine whistler analysis by meansof accurate curve fitting. J. Atmos. Terr. Phys.
37, 1447. (1975)[12] Dowden, R.L., and Allcock, G. Mak.,
Determination of nose frequency of non-nose
whistlers. J. Atmos. Terr. Phys., 33, 1125-1129,(1971).
[13] Tarcsai,G.,Strangawaya,H.J and Rycroft,M.J.,
Error Sources and travel time residuals inplasmasphericwhistlerinterpretation.
J.
atmos.Terr.phys.,51,249-258,(1989)[14] Singh, U P; Singh, A K; Lalmani; Singh, R P
and Singh, R N. Hybrid mode propagation ofwhistlers at low latitude. Ind. J. . Radio space
Phys. 21, 246-250, (1992)[15] Singh, B. Middle and High latitude whistlers
observes simultaneously in a low latitude station
at Agra. J. Geomag.Geoelectricity.,49, 9951000,1997.
[16] Sonwalkar,V.S, Inan,U.S, Angerson,T.L,

Farrell,W.M. Pfaff.R,J. Geophys.Res.100,77837790,1995.
[17] Ho,D and L.C. Bernard , A fast method todetermine the nose frequency and minimumgroup delay of whistlers when the causative
spheric is unknown., J.Atmos.Terr.Phys. 35,881887.(1973).
[18] Ohta,K; Kitagawa,T;Shima, K; Hayakawa,M and
Dowden, R.R.Chcharacteristics of mod latitude
whistler ducts as deduced from ground based
measurements. Geophys. Res. Lett., 23, 33013304,(1996).
[19] Andrews, M K; Knox, F B and Thmson, N R.
Magnetosphericelectric
fieldsandprotonospheric coupling fluxes inferred fromsimultaneous
phase
and
group
path
measurements on whistler mode signals. Planet
space Sci. 26, 171. (1978)[20] Altaf, M and Ahmad, M M. Estimation ofmagnetospheric plasma parameters from
whistlers observed at low latitudes CURRENTSCIENCE, VOL. 106, NO. 3, 10. (2014)[21] Okuzawa, T ; Yamanka, K and Yashino,T.
Characteristics of low latitude whistler
propagation associated with magnetic storms in
March 1970, Rept. Ionospace. Res. Japan. (1971)[22] Park, C G. Whistler observations of theinterchange of ionization between the ionosphereand the protonosphere. J. Geophys. Res. 75,
4249. (1970)[23] Park, CG. Westward electric fields as the causeof night time enhancements in electron
concentrations in mid latitude F regions. J.
Geophys. Res. 76, 4560. (1971)[24] Block, L P and Carpenter, D L. Derivation ofmagnetospheric electric field from whistler data
in a dynamic geomagnetic field. J. Geophys.
Res, 79, 2783. (1974)[25] Misra, K D; Singh,B D nad Misra, S P. Effect ofthe parallel electric field on the whistler mode
instability in the magnetosphere. J. Geophys.
Res. 84, 5923. (1979)[26] Carpenter, D L; Stone, K; Siren, J C and Crystal,
T L. Magnetospheric electric fields deduced
from drifting whistler paths. J. Geophys. Res, 77,
2819. (1972)[27] Park, C G. Whistler observations of substorm
electric fields in the night side plasmasphere. J.
Geophys. Res. 83, 5773. (1978)239

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

METAL PLASTICITY AND PERIODIC TABLE
1

Lev B. Zuev1, Svetlana A. Barannikova1 and Albina M. Zharmukhambetova1
Strengtth Physics Laboratory, Institute of Strength Physics & Materials Science SB RAS, Russia
ABSTRACT

We consider the autowave mechanism of evolution of a localized plastic deformation of crystalline solids ofdifferent origins. It is found that localization of the plastic flow is determined by the relation between elastic andplastic phenomena in deforming materials. It is shown that parameters of plastic flow localization at the stage of
linear strain hardening in the process of solid body deformation are closely related to characteristics of theelectronic structure of metals. Inverse of the product of wavelength and velocity of the localized plasticity
autowave grows linearly with the number of conduction electrons per unit cell of the metal. The obtained data
directly indicate that the nature of the electron-gas contribution to hindering of dislocations is more complicated.
Thus, the parameters of plastic flow localization are defined by the position of metal in the Mendeleev periodic
table.
Keywords: Plastic deformation, Autowave, Pattern, Electronic structure, Periodic Table𝑉 /𝑉 formed by these four characteristics is thesame for all cases of straining of different metals at
the stages of linear strain-hardening when σ ~ ε. Thissuggested that ratio 𝑉 /𝑉 is invariant in general.
This study aims at the verification of this regularity
not only for metals, but also for other materials witha linear law hardening. It is also important to clarify
the origin of this relation using generalthermodynamic concepts.

INTRODUCTION
Plastic deformation of solids is a complex
physical phenomenon the evolution of which depends
on the crystal lattice and crystal structure defects. The
process of plastic flow is usually described by thedependence σ(ε) of the deforming stress on the strain.
It is important that at all its stages from the beginningof plastic flow (yield stress) to fracture (ultimate
strength), this process is accompanied by plasticstrain localization [1].
The model of evolution of localized plastic strain
proposed in [1] presumes that self-organization of thedefect structure [2] occurs in the form of autowaves
of a localized plastic flow [1], [3], which appear in the
deforming medium as a result of interaction of elastic
waves and relaxation events of breaking of elastic
stress concentrators. Each relaxation event
contributes to the overall plastic deformation andgenerates new stress concentrators. The autowave
pattern of localized plasticity distribution regularlychanges in accordance with the stage nature of theσ(ε) curve so that the deformation process can betreated as a natural evolution of localized plasticity
autowaves [1].
Therefore, autowaves (localized plasticity) andwave (elastic) deformation phenomena coexist in aplastically deforming medium. The former arecharacterized by wavelength  of the localized
plasticity autowave and velocity Vaw of its
propagation, while the latter are determined by theinterplanar distance  in the crystal lattice of thetested material and the velocity Vt of propagation oftransverse elastic waves.
It was noted in earlier experiments with a numberof metals [1], [4], [5] that dimensionless ratio

EXPERIMENTAL DATA
Experimental investigations of localized plastic
flow werecarried out for different metals related toperiods 3–6 of Mendeleev’s Periodic Table (see Table1). The quantitative data on the localized plasticity
patterns were estimated experimentally for linear
stages of the processes at which the deforming
stresses and strains are connected by a linear relation.
In these cases, a phase localized plasticity autowave
corresponding to the condition of the constancy ofphase 2𝜋(𝑡/𝑇 − 𝑥/𝜆) = 𝑐𝑜𝑛𝑠𝑡 is observed, where T
is the period of oscillations in the wave, x is thecoordinate, and t is the running time. The localized
plasticity pattern formed in such cases is stable andcan be observed relatively easily [1].
For estimating ratio 𝑉 /𝑉 characterizing
various materials, the range of metals underinvestigation was extended. In addition, we studied
the localization of plastic deformation in alkali-halide
crystals (KCl, NaCl, and LiF) and rocks such as
sandstone (SiO2) and marble (CaCO2). The method
for observing the patterns of a localized plastic flow
in deforming materials, which was based on speckle
photography, was described in detail earlier [1] andwill not be discussed here. For illustrating thepotentialities of this method, Fig. 1 shows a typical240

SEE - Bangkok, Thailand, Nov.11-13, 2019

work-hardening of metals, easily slip in metal single
crystals, compression of rock samples, and the phasetransformation straining of the NiTi single crystal.
Let us analyze the data obtained in theseexperiments. The values of products Vaw for 19
tested metals are given in Table 2. It can be seen thatthe results differ insignificantly and the mean valueof the product of these quantities is 〈𝜆𝑉 〉=(2.52 ± 0.36) × 10 m2/s.

pattern of local plasticity distribution for sequentialstages of easy slip and linear strain-hardening during
tension with a constant rate for a single crystal sample
of alloy Fe-12 wt %Mn (γ-Fe).

PeriodTable 1 Metals under study

3

4

5

6

Fig. 1

MetalsElement Mg Al
Atomic 12 13
numberElement
AtomicnumberElement
Atomicnumber

Ti
22

V
23

Fe
26

Co
27

Ni
28

Cu
29

Zr

Nb Mo Cd

In

Sn

40

41

42

49

50

Element
Atomicnumber

Hf

Ta

Pb

72

73

82

48

Zn
30

Fig. 2

X–t diagram for Hadfield steel single crystal,plotted for the case shown in Fig. 1.

We managed to supplement these data with the resultsof analogous processing of localized plasticity
patterns observed at the easy slip stages in Cu, Ni, 𝑎Fe, γ-Fe, Zn, and Sn single crystals for which theproportionality σ ~ ε also holds and a phase autowave
is observed. For this stage, we have
〈𝜆𝑉 〉 ~(2.95 ± 1.05) × 10 m2/s (see Table 2).
The stage of linear work-hardening andcorresponding localized plasticity phase autowaves
were observed for compressed samples of alkalihalide crystals and rocks [6], [7]. The results of theseexperiments given in Table 3 lead to 〈𝜆𝑉 〉=(3.44 ± 0.49) × 10
m2/s and 〈𝜆𝑉 〉=(1.44 ± 0.34) × 10 m2/s.
In the case of staining due to the slip of individual
dislocations, the process is usually characterized bydislocation path length l and dislocation velocity Vdisl;these parameters were determined from analysis of
the available data on the mobility of individual
dislocations in single crystals [8]-[12] in the quasiviscous flow regime, in which 𝑉 ~𝜎 [13]. In suchconditions, the characteristic dislocation path lengths
lie in the interval 10-5 m  l  10-4 m and the velocities
of dislocations belong to the range 10-3 m/s  Vdisl 10-2 m/s. The product of these quantities wasestimated using the relation 𝑙𝑉 = 𝑉 𝜏, where τis the duration of the load pulse acting during the
crystal loading. The results of calculations of
products 𝑙𝑉 in these cases are given in Table 4. It
can be seen that 〈𝑙𝑉〉
= (3.2 ± 0.35) × 10 m2/s
in this case.

Strain distribution over a sample of Fe-12 wt%Mn alloy (a) at the easy slip state and (b)at the linear work hardening stage.

The quantitative characteristics  and Vaw required
for analyzing the data on the evolution of localized
plasticity were determined from the processing of theso-called X–t diagrams proposed in [1] for such
purposes and shown in Fig. 2. It can be seen from thefigure that the values of autowave wavelength  andperiod T can be determined from the vertical andhorizontal sections of families of the X(t) curves.
Characteristics  and 𝑉 = 𝜆/𝑇 of localized
plasticity autowaves were determined for linear
241

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Comparison of quantities 𝜒𝑉 and 𝜆𝑉
x107 m2/s
Cu
3.6
4.8
0.75

𝜆𝑉
𝜒𝑉
𝜆𝑉 /𝜒𝑉x107 m2/s

Sn
2.4
5.3
0.65

𝜆𝑉
𝜒𝑉
𝜆𝑉 /𝜒𝑉for metals

Linear strain hardening stage
Zn
Al
Zr
Ti
V
Nb
Ni
Co
𝑎-Fe γ-Fe
3.7
7.9
3.7
2.5
2.8
1.8
2.55
2.2
2.1
3.0
11.9
7.5
11.9
7.9
6.2
5.3
4.7
6.5
6.0
6.0
0.3
1.1
0.3
0.3
0.45 0.33 0.54 0.34 0.35
0.5
Linear strain hardening stage
Easy slip stage
Mg
Cd
In
Pb
Ta
Hf
Cu
Zn
𝑎-Fe γ-Fe
9.9
0.9
2.6
3.2
1.1
1.0
7.4
2.9
1.9
1.0
15.8
3.5
2.2
2.0
4.7
4.2
6.5
6.0
4.7
5.0
0.63
0.2
1.2
1.6
0.2
0.24
1.1
0.49
0.4
0.2

The experimental estimation of the parameters of
a localized plasticity autowave for plastic
deformation of TiNi intermetallide single crystal of
the equiatomic composition (strain-induced phasetransformation [14]) resulted in the value 〈𝜆𝑉 〉 ≈0.85 × 10 m2/s.
Table 3 Comparison of quantities 𝜒𝑉 and 𝜆𝑉
alkali- halide crystals [6] and rocks [7]

Mo
1.2
7.4
0.2
Ni
1.3
6
0.2

Sn
3.3
4.9
0.67

element Z oscillates with respect to the average value
with increasing number of the element within thelimits of 13 ≤ 𝑍 ≤ 82. It has been found that theseoscillations correlate with regularities in the behavior
with an increase in Z of some independently
determined lattice characteristics such as, e.g.,characteristic Debye temperature Θ ≈ ℏ𝜔 /𝑘 ( ℏ = ℎ/2𝜋 is the Planck constant, 𝜔 is the
Debye frequency, and 𝑘 is the Boltzmann constant)[16], density, melting temperature, elastic moduli,
and ionization potential [17]. As an example,
correlation of the discussed dependences is illustrated
by the common mode behavior of the quantities 𝜆𝑉
binding energy Eb and Θ as functions of the atomic
number of the elements under study (Fig. 3).

forx107 m2/s KCl NaCl LiF Marble Sandstone
3.0 3.1
4.3
1.75
0.6
𝜆𝑉
7.0 7.5
8.8
3.7
1.5
𝜒𝑉
0.5
0.5
0.4
0.43 0.4
𝑉 /𝜒𝑉
Comparing pairwise the above data by calculating
the Student t-test [15], we can conclude that theresultant values differ insignificantly (i.e., belong to
the same general population). This leads to
〈𝜆𝑉 〉
〈𝑉 〉

≈ 〈𝑙𝑉〉≈ 〈𝑉 〉≈ 〈𝑉 〉≈(1)

Elastic processes in the tested materials werecharacterized by interplanar distances  in the crystal
lattice [16] and velocities Vt of propagation oftransverse elastic waves [17]. As follows from Tables
2-4, we have 〈𝜒𝑉 〉 = (5.8 ± 0.3) × 10 m2/s for
all tested materials.

Fig. 3

Table 4 Comparison of quantities 𝜒𝑉 and𝑙𝑉 determined by measuring of path
lengths of individual dislocations
x107 m2/s𝑙𝑉𝜒𝑉𝑙𝑉 /𝜒𝑉

NaCl LiF [9] CsI [10] KCl
[8]
[11]
4.1
4.1
1.9
4.1
6.8
7.3
8.6
4.0
0.56 0.47
0.47
0.6

The quantity (1) 𝜆𝑉 , binding energy Eb (2)and (3) Debye temperature Θ as functionsof atomic number of elements Z (III, IV, V,
and VI are numbers of periods)

In addition, in analyzing the behavior of the
product 𝜆𝑉 within the limits of each period ofMendeleev’s periodic law, it has been found that thequantity (𝜆𝑉 ) grows linearly with the number ofconduction electrons per unit cell of the metal n [18];therefore, the relation

Zn
[12]
1.8
4.0
0.45

(𝜆𝑉 )

Analysis of the data array obtained for stages oflinear strain hardening made it possible to establishthat the dependence of 𝜆𝑉 on atomic number of the= 𝐴+B∙n(2)

where A and B are constants different for periods 3, 4,
5, and 6, is valid in each period. The dependences
242

SEE - Bangkok, Thailand, Nov.11-13, 2019

established for the abovementioned periods areshown in Fig. 4.

Mendeleev periodic table respectively.
The existence of a linear relation such as (Eq.2)
was already noted in [19]; however, the separation by
periods of Mendeleev’s Table was not observed
earlier. Processing of experimental data for elementsof periods 4–6 shows that,
𝐵 = 𝐴 ∙ exp(𝛽/𝑁) ,(3)
where A and B are constants. In relation (3), N =4, 5, and 6 is the period number in Mendeleev’s
periodic law (it is well known [20] that the number ofthe period coincides with the number of electron
shells of its atoms) and в is a constant.
It has been found that the quantity 𝜆𝑉 grows
linearly with normalized the Debye temperature Θ[17, 18]; therefore, the relation

Fig. 4

The quantity (𝜆𝑉 ) as a functions of
number of conduction electrons per unit celln (3, 4, 5, and 6 are numbers of periods)𝜆𝑉=𝐴 ∙Θ ∙,

(4)

where constant A = 4.42 · 10−5 m2/s, Eb is binding

It was also noted that the parameter of plasticity
λVaw correlates with different physical properties, as
shown in Fig.5 a-b.

energy and 𝑘 is the Boltzmann constant. The
dependence established for the abovementioned
periods is shown in Fig. 6.

a)Fig. 6The quantity 𝜆𝑉
as a functions ofnormalized the Debye temperature Θ (3, 4,
5, and 6 are numbers of periods)

The coefficient of correlation between the quantities
presented in Fig. 5 is ~0 .9 6 , which indicates theexistence of a functional relationship between them
[1 5].
CONCLUSIONSb)
Fig. 5The obtained data testify that parameters of plastic
flow localization at the stage of linear work hardening
in the process of solid body deformation are closely
related to characteristics of the electronic structure ofmetals. This relation manifests itself as a dependenceof macroscopic characteristics of localized plasticity
autowave propagation at the stage of linear strain
hardening on the period number in Mendeleev’s
Table. In addition, these characteristics depend on thenumber of valence electrons; for most metals but
transition ones, it coincides with the group number inthe periodic system. The obtained data directly

The dependence of parameter of plasticity on
Wigner–Seitz radius (a), the bond energy (b), ■ –elements of the 3rd period (Mg, Al), ● – elementsof the 4th period (Ti, V, α-Fe, γ-Fe, Co, Ni, Cu,
Zn), ▲ – elements of the 5th period периода (Zr,Nb, Mo, Cd, In, Sn); ▼ – elements of the 6th
period (Hf, Ta, Pb). The correlation coefficient:(a) R=1; 0,6; 0,6; 0,9; (b) R=1; 0,53; 0,4; 0,95

In this case, the dependencies are presented in theform of four linear dependencies, which covers ametals related to the 3rd, 4th, 5th and 6th periods of243

SEE - Bangkok, Thailand, Nov.11-13, 2019indicate that the nature of the electron-gas
contribution to hindering of dislocations is more
complicated than is envisaged in existing theories[21] of this effect.
The elastic-plastic invariant necessitates theallowance for the role played by elastic (lattice)characteristics of materials and is important in thedevelopment of models [22-32] and mechanisms ofevolution of a plastic flow [33-42].

of Viscous Deceleration of Dislocations in LiF
Crystals Based on the Mobility of Individual
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p. 1250-1252.
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Viscous Deceleration of Dislocations in CsICrystals at a Temperature of 77–300 K, Fizika
Tverdogo Tela, Vol. 17, 1975, pp. 2421-2422.
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I., Dependence of Dislocation Velocity on
Electric Field Intensity, Kristallografiya, Vol. 19,
1974, pp. 889-891.
[12] Zuev L. B., Gromov V. E., Kurilov V. F, andGurevich L. I., Mobility of Dislocations in Zn
Single Crystals Under the Action of Current
Pulses, Dokl. Akad. Nauk SSSR, Vol. 239, 1978,
pp. 874-876.
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and Probability, Geneva CERN, 1963, pp.1-105.
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Bernshtein and A. G. Rakhshtadt, Moscow,
Metallurgizdat, 1961, in Russian, p. 387.
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Inc., 2003, pp. 75–114.
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approach for modeling scale-dependent yieldstress in polycrystalline metals, International
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897–914.

ACKNOWLEDGMENTS
This work was performed by the financial supportof RSF, grant no. 16-19-10025 P.
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in moving excitable media. Condensed Matter
Physics, Vol. 7, Issue 3, 2004, pp.565-578.
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localization in single crystals of austenite steel
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[5] Barannikova S., Zuev L., Li Y., Plastic flow
heterogeneity and failure of bimetal material,
International Journal of GEOMATE, Vol. 14,
Issue, 43, 2018, pp. 112-117.
[6] Barannikova S. A., Nadezhkin M. V., and Zuev L.
B., Relationship between burgers vectors of
dislocations and plastic strain localization
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crystals, Technical Physics Letters, Vol. 37, 2011,
p. 750.
[7] Zuev L. B., Barannikova S. A., Nadezhkin M. V.,
and Gorbatenko V. V., On the Observation of
Slow Wave Processes in Deforming Rock Sample,
Journal of Mining World Express, Vol.2, Issue 1,
2013, pp. 31-39.
[8] Kurilov V. F., Zuev L. B., Gromov V. E., Sergeev
V. P., and Gershtein G. I., Dynamic Decelerationof Dislocations in NaCl Crystals of Different
Purity, Kristallografiya 22, 1977, pp. 653-654.
[9] Darinskaya E. V., Urusovskaya A. A., Opekunov
V. N., Abramchuk G. A., and Alekhin V. F., Study
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fracture and plasticity, International Journal of
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[35] Lebyodkin M.A., Zhemchuzhnikova D.A.,
Lebedkina T.A., Aifantis E.C., Kinematics offormation and cessation of type B deformation
bands during the Portevin-Le Chatelier effect inan AlMg alloy, Results in Physics, Vol. 12, 2019,
pp. 867-869.
[36] Zuev L. B., Barannikova S. A., Lunev A. G.,
Kolosov S. V., Zharmukhambetova A. M., Basic
Relationships of the Autowave Model of a
Plastic Flow, Russian Physics Journal, Vol. 61,
Issue 9, 2019, pp. 1709-1717.

[25] Zaiser M., Aifantis E.C., Randomness and slip
avalanches in gradient plasticity, International
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1432–1455.
[26] Bilalov D. A., Sokovikov M. A., Chudinov V.
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Engineering

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ECONOMICAL ANALYSIS OF THE GEOGRID REINFORCED
RAILWAY TRACK
Saad Farhan Ibrahim1, Ali Jabbar Kadhim2 and Harith Basim Khalaf2
1
Faculty of Engineering, Isra University, Amman, Jordan;
2
Faculty of Engineering, Al-Mustansiriya University, Baghdad, Iraq
ABSTRACTOne of main challenges in the development of railway transportation is the Reduction of the track costs. The
reduction of track costs is crucial for competitiveness of railway operators, since competing modes oftransportation (e.g. aviation, automotive) have seen a tremendous reduction in LCC in the last 30 years, while
railway maintenance costs have not significantly decreased during the same period. The main objective of thisstudy is to investigate the reduction in the cost of railway track due to the use of geogrid reinforcement. The
results of redaction of track cost for the simulated models were for the sub-ballast reinforced model (4.1%), andballast reinforced model (6.5%) and double reinforced model (3.73%) as compared to the unreinforced track.
Keywords: Railway transportation, geogrid, reinforcement
INTRODUCTION
The total cost of railway transportation is derived
from construction, maintenance and operation of
infrastructure, manufacturing and maintenance ofvehicles, as well as fuel production. Since
maintenance, costs for the conventional ballasted
railway track could be significantly reduced if thedeveloped settlement under loading decreased. Thereis a few existing data concerning the lifetime of thegeosynthetics in the construction of railway. Because
the knowledge about the usage of geosynthetics onrailway constructions is only distinguished in thepast (20) years, so we can state that the experienceand practice of the lifetime of various constructions
methods are still aren’t enough define them properly.
Only little estimates availably from the
manufacturers of geosynthetics who announced thatthe geosynthetics that they produce could rise theballast lifetime for (2 – 4) times its original value.
Since of the deficiency in pervious data, thecalculation of maintenance and renovation work of
railway were very few. In addition, Federici (2003)
noticed that the available studies on railway track
system that take in consideration the infrastructuresin detail are very seldom and largely focused on
vehicles construction. Therefore, the effect ofgeogrid reinforcement on reducing the cost ofrailway track will be studied [1].
Life cycle cost could be functional for projectthrough a wide variety of industries, containing therailway. Railway track cost has not considerablychanged since the past (30) years with comparison toother rival transportation modes [2]. European
Commission (2011) on Sustainable Transportation
settled targets for the reduction of railway life cycle
cost in 2020 by 30%. Therefore, there is anoteworthy focusing on the analysis of life cycle cost
application on railway [3].
The Geogrid was used as part of the
INNOTRACK project through numerical simulations

and laboratory tests. This approaches confirmed thatthe reinforcement using geogrid would cause areduction in operational disturbances and the life
cycle cost. Hall and Sharpe (2007) used a British
Railway case study was done in (1988) where
geogrid was introduced for the renewal of railway
track in the Derby– Leeds line at Shirland. The site
was constructed with 100mm blanketing sand and
300mm of ballast over it, a separation layercomposed from a heat bonded geo-textile and ageogrid with a small mesh to stop the particles ofballast from the penetration the geotextile. A geogrid
with large mesh was furtherly added in order tosupport the soft subgrade. The project condition wasmonitored
through thelong-term
generalperformance and ballast operational life. The resultof monitoring showed that the geogrids decreased therequirements of maintenance to a fraction of theirpast level thus reducing the life cycle cost [4].
Without doubt, the decision-making, maintenanceand operation costs are significantly more important
initial constructions cost. These costs need to bestudied throughout their lifetime so they match theirperformance threshold [5]. It is important that themaking of decisions be based on a life-cycle basis.
This will led to choosing more cost-effective
strategies in the extended time and are cooperated
with the available finance. Latest researches about
railway constructions with the use of geosynthetics
indicated a positive effect. The maintenancerequirements reduced and ballast strength of theballast increases when geotesynthetic were used.
Settlement of the track was 37 to 65 percent less thansettlement of the equivalent portion of theunreinforced test section [6].
The geosynthetics manufacture company Tensar
claims that the usage of their geosynthetics products
will led to an increase in maintenance cycle by 3times from its original value after a railway trackcase study; the railway track is located between
Scotland and London. The railway line has been
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SEE - Bangkok, Thailand, Nov.11-13, 2019

under speed restriction for many times in spite of it
was maintained regularly 2 times a year. The
intrusion of geogrid in that line led to substantial
decrease in the deterioration rate of the railway track
without speed restrictions or maintenance [7].
METHODOLOGY
The Life cycle cost (LCC) and the Whole life cost(WLC) are well known approaches used to computeall the associated cost with the whole life of design
for a specific asset. The Life cycle cost (LCC) andthe Whole life cost (WLC) can be usedinterchangeably while in the (BS ISO 15685-8:2008)
international standard for life cycle costing ofbuildings and constructed stated that the two havedifference meaning [8]:•Life cycle cost is well defined, as “is thecost of a part or its divisions during its cycle life,
thoughaccomplishingtheperformances
requirement”.
•
Whole life cost is well defined as “is theprocedure of regular economic aspects for the
benefits and whole life cost of a known analysis
period”. Whole life cost contains extra costs such assupport cost related to activity in assets, Land cost
and the incomes produced by the assets. The
connection between LCC and WLC is displayed in
Figure 1.
In order to make the appropriate choices on theeconomical benefits of the enhancement works that
include using new technology the life cycle cost and(LCC) must be studied before and after the use of thetechnology. The tool were developed within the
project “SMARTRAIL”, and available onsmartrail.fehrl.org, was used to verify the benefits incost related to the use of geogrid in railway track
system for this research. The smart rail LCC tool wasdeveloped with consideration of ISO EN 15686-5
standard for LCC.
The following costs were used in the tool:•
Construction costs
1.
The Ballast
2.
The Sleepers
3.
Fastening and Rails systems
4.
Elastomeric [Resilient] pads
5.
Geogrid•
Routine maintenance costs:
1.
Stabilization and Tamping
2.
Milling of rail

Fig. 1: Scope of life cycle and whole-life costing(Adapted from BS ISO 15685-8:2008).
Geogrid has been progressively used in railroads
to offer reinforcement and confinement pressure to
the layers of railway track. Four models were tested
experimentally in order to calculate the increase in
the life of the railway track after using geogrid
reinforcement. The model dimensions are(800*800*600 mm), subgrade layer is 400 mm thickand sub-ballast layer and ballast layer are 100 mm
thick. The tested models are unreinforced model,
sub-ballast reinforced model, and ballast reinforcedmodel and double reinforced model consisting ofgeogrid reinforcement in sub-ballast layer and ballast
layer. The result showed that using reinforcement
layer would reduce model settlement. The model
tested look like the sketch in figure (2).
A Cumulative figure (3) used to show thedifference in result of settlement between all tested
models.

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The purpose of this tool is to let the user toexplore the effects of different maintenance option
on the life cycle cost of for a railway asset. The
assessment of life cycle cost is a way to estimate theover-all costs of maintaining an asset with a specified
period for analysis, to be used as an input into a
decision-making procedure. Discounting rate and thecosts in the Future were converted to be Net Present
Value (NPV) to simplify the judgement inmaintenances regimes from total cost point of viewin the present day.
The data input was gathered from “Hajama –Sawa” Railway Project by Ministry of Transportation
Iraqi
Republic
Railways
Companyand“Transportation & Telecommunications of Iraq”
report by United Nations World Bank [9]. It assumed
that the project life span would be for 60 years. In
addition, due to the difficultness of predicting theincrease in the ballast lifetime of due to the use ofgeogrid, a number of scenarios were simulated, andall of these scenarios indicate that the use of geogrid
in the construction will be cheaper in the end. In
addition, this indicate that the maintenancerequirement of the tack will be decreased. The toollayout and the used data for evaluated models areshown in figures (4) (5) (6) (7) (8) accordingly.

Fig. 2: Sketch to show the experimentally tested
model.

Fig. 4: the LCC tool-starting page.

Fig. 3: Load-Settlement relationship for allmodels at every loading stages.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 5: the input data for unreinforced model.

Fig. 7: the input data for ballast reinforced track.

Fig. 6: the input data for sub-ballast reinforced track.

Fig. 8: the input data for double reinforced track.

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RESULTSCONCLUSIONLCC Analyses displayed provision economically
aimed at the choice to use geogrid under in therailway track as shown in figure (8). This has been
proven for all the reinforced models because thelifetime is increasing from the use of the geogrid andthus led to a condition that was extra cheaper andmore profitable to use the reinforcement into thetracklayers. The costs differences for the threevariants and the baseline for the railway track isshown in the net present value of the three variants islesser than that of the baseline in spite of initial costis higher; rising from considerably lesser rate ofmaintenances.

The economical evolution indicated that the useof geogrid proved to be a feasible and cost-effective
in reducing the intervals of maintenance of railway
track. Despite of slightly higher initial construction
cost of railway track when the geogrid used, thelifetime cost will reduced significantly As the ballast
reinforced was the most effective in the reduction of
total cost by(6.5%)and the sub-ballast reinforced was(4.1%) and the double reinforced was (3.73%) ascompared to the unreinforced track.

Fig. 4: The Cumulative Present Value and time
relationship where
Baseline: Unreinforced,
Variant A: The sub-ballast reinforced
Variant B: ballast reinforced
Variant C: double reinforced

REFERENCES[1] Federici, M., S. Ulgiati, et al. (2003).
"Efficiency and sustainability indicators forpassenger and commodities transportation
systems. The case of Siena, Italy." Ecological
Indicators 3: 155-169.
[2] Paulsson B, Platzer M and Ekberg A (2006)“INNOTRACK – Innovative Track System – A
unique approach of infrastructure managers andcompetitive track supply industry for developing
the innovative products of the future”, 7th World
Congress on Railway Research.
[3] European Commission (2011) “White Paper:
Roadmap to a single European Transport Area –Towards a competitive and resource efficienttransport system”.
[4] Hall C D and Sharpe P (2007) “Review ofgeogrid stabilisation of railway ballast withreference to performance and durability”.
[5] European Commission (2013) “Sustainablesteel-composite bridges in built environment(SBRI)”, Final Report[6] Parsons R., Jowkar M., Han J., 2012.
Performance of Geogrid Reinforced Ballast
under Dynamic Loading. Report # MATC-KU:
363, Final Report.
[7] Tensar(2013)“Railways:
Mechanicalstabilization of track ballast and sub ballast”,
March 2013, Issue 11.
[8] British Standards Institution (2008) BS ISO
15685-8:2008, Buildings and constructed assets– Service life planning – Part 5: Life cycle
costing.
[9] Project “Hajama – Sawa”, cost estimate,
Ministry of Transportation of Iraq, Iraqi
Republic Railways Company.

251

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

A STOCHASTIC MODEL OF THE MRO SPARE PARTS
PROCUREMENT PLANNING PROBLEM FOR AIRCRAFT
MAINTENANCE SERVICE PROVIDER
Yichen QIN1,2, Felix T.S. CHAN2, S.H. CHUNG2 and T. QU1
School of Electrical and Information Engineering, Jinan University (Zhuhai Campus), Zhuhai 519070,
China;
2
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hum,
Hong Kong
1

ABSTRACT
Increasing number of outsourcing maintenance requests from different airlines has brought great challenge tothe independent aircraft maintenance service provider to timely complete the maintenance request. From theperspective of aircraft maintenance service provider, having a long-term sustainable MRO procurement practicein aircraft maintenance service provider ensures the smoothness of implementation of maintenance activities.
Given that procurement of consumables and materials varies according to different aircraft maintenance checks,
maintenance company need to maintain the continuously availability of parts and components for maintenanceactivities while minimizing the holding cost of expensive inventory. Considering the uncertainties of maintenancerequests from different clients (airlines), a stochastic model is proposed to formulate the problem. The stochastic
model aims to alleviate the negative impact of the uncertain maintenance demands on the inventory management
operations, and provide a robust procurement strategy while implementing the maintenance operations in realsituations.
Keywords: MRO, Procurement, Stochastic Programming, Aircraft Maintenance, Mixed-integer Linear
Programming

implementation of maintenance activities as the
optimal procurement planning solution can become
infeasible. In this connection, it is necessary toincorporate the uncertainty of maintenance demands
into the procurement planning problem. Therefore,
the contribution of this paper is that: 1) the
procurement planning problem for maintenanceservice provider is studies; 2) the uncertainties inaeronautical component supply and demand areincorporated in the MRO procurement planningproblem. Specifically, the uncertainties arecharacterized as discrete scenarios, and therandomness of different scenarios are associated withprobabilities based on the problem.

INTRODUCTION
Outsource the MRO operations to the professional
maintenance service provider has become the trend inaviation industry. It is estimated by Marcontell [1]that there is a 45% increase of MRO outsource rosefrom the mid-1990s to 2012. Receiving increasing
demands of MRO service with various aircraft
configurations, independent aircraft maintenanceservice company are faced with great challenge tofulfilling these demands. Having respective
aeronautical parts are perquisite before implementing
different aircraft maintenance tasks. Procurement of
the MRO parts can lead to high inventory holding costand long lead time. In this regard, maintaining
sufficient MRO parts and minimizing inventory costare critical for the aircraft maintenance enterprise.
Moreover, the uncertainties of demands may interrupt
the original planning within the maintenancecompany. In reality, maintenance demands ofdifferent clients are difficult to predict since eachairline carries out its own flight plan respectively. In
addition, the supplying capacity of aeronauticalcomponent suppliers are limited, and the stability ofthe supply chain can be affected by the uncertainties
during the productions and transportation process.
The deterministic procurement planning model isunbale to handle the uncertainties during the

LITERATURE REVIEW
Large equipment oriented maintenance, repair
and operation (MRO) is significant to asset-intensive
industries like aeronautics, which involves substantial
investment to maintain sophisticated equipment andspare parts [2]. From the perspective of airlines,
maintenance outsourcing is an important ways toreduce the business costs, maintain competitive
advantages in the market and achieve satisfactory
MRO service [1, 3]. With the increasing trend of
maintenance outsourcing decisions from different
252

SEE - Bangkok, Thailand, Nov.11-13, 2019airlines, efficiently fulfill maintenance requests
associated with respective aircraft model becomes agreat challenge.
Specifically, the MRO spare parts procurement
planning is vital to maintenance checks that are
conducted on the aircraft received from different
clients. All aircraft maintenance activities associatedwith MRO spare parts shall be arranged in advanced
to ensure that the availability of spare parts can fulfill
the maintenance demands. From other side, theinventory of spare parts has to be maintained withinsuitable level. Therefore, fulfilling maintenancedemands with the constraint of limited resources is acommon problem in MRO industry. Zhen and Wang
[4] developed a two-phase stochastic programming
model on the component replenishment decisions foran assemble-to-order (ATO) manufacturer. A multiobjective model for the preventive replacement of aspare part over a planning horizon is proposed by
Nosoohi and Hejazi [5]. A two non-linear
programming models that is used to predict
impending demands based on installed spare parts
failure distribution is developed by Gu et al. [6].
Aircraft maintenance checks shares some similarities
with the assemble-to-order manufacturing practices
and the product configuration problem. Productconfiguration problem selecting components toconstitute a personalized product with specified
configurations [7], and aircraft maintenance checks
consume different MRO spare parts to duringrespective maintenance operations . Somarin et al. [8]studied the emergency resupply policy that helps toimprove the MRO service providers’ flexibility while
the shortage of spare parts occurs.
It is common that the maintenance service
providers are involved in a global MRO supply chain
and they have to purchase necessary spare parts fromdifferent supplier globally, instead of producing thespare parts their own. The product configuration
parameters, spare part demands, and lead time haveto be considered and these data may fluctuate in realworld implementation. Therefore, these uncertainties
can have the negative impact on the MRO operations.
In literature, the uncertainties maintenance demands,
transportation lead-time and suppliers’ capacities areless considered in MRO spare part procurement
problem. A stochastic programming model isdeveloped, which considers uncertain supplying
capacity and maintenance requirement into the
procurement planning. Furthermore, the frameworkof the mathematical formulation envisions the
direction of algorithmic design for further research on
this topic.

Aircraft maintenance check can be classified asline maintenance and hangar maintenance. Line
maintenance get its definition from “on line”
maintenance, referring to the light maintenanceactivities (e.g. A- and some B- checks) that can be
conducted at a gate or apron during a turnover
between two flights, while other maintenanceactivities, i.e. some B-check, C check and D-check,are categorized as “hangar” maintenance carried out
when the aircraft is taken out of service and sent to
the maintenance hangar for heavy maintenance. MRO
spare parts are indispensable for the aircraft heavy
maintenance checks, and different maintenancechecks requires respective MRO spare parts to
conduct the maintenance operations on the aircraft.
Moreover, for different types of aircraft model, it is
the case that the MRO spare parts are different for thesame type of maintenance check.
The maintenance service provider has to obtainsufficient dedicated MRO spare parts before
conducting any maintenance checks on aircraft fromthe clients. To control the inventory level and avoid
holding excessive MRO spare parts, the maintenanceservice provider adopts Procure-To-Order (PTO)
practice and the service provider receives
maintenance order related to aircraft to be serviced
with respective configurations. In reality, the supply
chain is affected by the uncertain maintenancedemands and capacity of suppliers. In particular, themaintenance demands may fluctuate as some urgent
unscheduled maintenance requests arrive atmaintenance company without short notice period,
and the maintenance company does not necessarily
have sufficient components to satisfy the additional
maintenance request. In this connection, the decisionof the maintenance company is to determine the sparepart’s selection and respective supplier’s selection, so
as to satisfy the additional maintenance requests suchthat the total cost of procurement and operations is
minimized within the context of uncertainty.
To reduce the cost of putting urgent procurement
order that induces significant amount of ordering cost,
the pre-procuring practice is used. The maintenancecompany may purchase some mutual spare part inadvance, such that they can be shared with different
aircraft type and minimize the negative effects
induced by uncertain MRO spare parts requirement
and stochastic supply capacity. If the advanced
procurement of MRO spare parts cannot meet the realdemands, the maintenance company is able to procure
additional spare parts to meet the remaining
requirements of MRO parts. In this regard, spare partprocurement considering uncertainties: 1) identify
and select the MRO spare parts required by theclient’s maintenance requirement, and select the spare

MATHEMATICAL MODEL FOR MRO SPAREPARES PROCUREMENT PROBLEM WITH
UNCERTAINTY
Problem Description
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SEE - Bangkok, Thailand, Nov.11-13, 2019

part suppliers; 2) pre-procure spare parts fromselected suppliers; 3) conduct the maintenanceservice on the receiving maintenance request with thepre-procure spare parts and deliver the finishedaircraft; 4) if the maintenance demand cannot be
fulfilled by the pre-procure spare parts, themaintenancecompany
initiates
additional
procurement from the suppliers; 5) conduct themaintenance service by using the additional procured
spare parts and finished the maintenance requests.

Unit cost of extra procurement of
spare part j from spare part providerk
Probability that scenario s occurs

ca jk
Pb s

Decision Variables
Notation
Meanings
Binary decision variable. 1 indicates
xijthat spare part j is used in fulfilling
maintenance request i
Number of procurement spare part j
pp jkfrom spare part provider k inadvanced
Number of additional spare part j
ap sjkfrom spare part provider k underscenario ss
Number of unused spare part j
es j
inducing inventory holding cost
under scenario s

Mathematical Model
The MRO spare parts procurement problem isformulated as a stochastic model. The advanced
procurement process is modeled in the first phase,including spare part and suppliers’ selections, isconducted before considering the stochastic demandand supply. In the second phase, the additional
procurement is determined under different scenarios
to fulfill the unexpected maintenance requests.
The notations of the mathematical model are
listed as follows:
Notations
Meanings
i, h, lAircraft to be served, i, h, l  I
j
MRO spare parts, j  J
mMaintenance module, m  M
Spare part provider, k  K
ks
Scenario, s  S
Set of Aircraft associated withI
maintenance requirements
J
MRO spare parts set
Maintenance module set
M
Spare part provider set
K
S
Scenario set
Set of MRO spare parts belong toSCmmaintenance module m
Demand of maintenance request id isunder scenario s
Inventory holding cost of unused
hc jspare part j
Number of spare part j required fornsij
the maintenance request i, if j isselected
Cost of spare part j in maintenancecsij
requestMaximum storage capacity for spare
mc jpart js
Capacity of supplying spare part j
SC jkfrom provider k under scenario s
Unit cost of transporting spare part j
ts jk
from spare part provider k to themaintenance company
Unit cost of advanced procurement
cpij
component j from spare partprovider kMin  csij  nsij  xij    (cp jk  ts jk )  pp jkiI jJjJ k K
  Pb s   (ca jk  ts jk )  ap sjk   hc j  es sj sSjJ
 j  J k K (1)

 x  1, i  I , m  M

(2)

ij

jSCm

 d  ns  x   pp   ap , j  J , s  S
iI

s
i

ij

ij

k K

jk

k K

s
jk

 pp jk  mc j , j  J

kK pp   d  ns  x  es , j  J , s  S

kK

jk

s
i

iI

ij

ij

xij  {0,1}, i  I , j  J

pp jk , ap , es  0, i  I , j  J , k  K , s  S
s
j

(4)

s
j

ap sjk  SC sjk , j  J , k  K , s  S
s
jk

(3)

(5)
(6)
(7)
(8)

Objective function (1) minimizes the total sparepart cost, including the configuration cost, cost of
procurement, cost of transportation and cost of
inventory holding. Constraint (2) prescribes that one
option of spare part can be chosen from the available
spare part combination in the dedicated module.
Constraint (3) makes sure that that the demands of the
MRO spare parts are met by the procurement.
Constraint (4) impose the storage capacity limit,
meaning that the number of pre-procure andadditional procure spare part cannot exceed thecapacity of the storage house. Constraint (5)determines the number of excessive spare part.
Constraint (6) regulates that the additional
procurements of spare parts is below the maximum
capacity of the supplier. Constrains (7-8) determine
the type of decision variables.
254

SEE - Bangkok, Thailand, Nov.11-13, 2019[2] Li L., Liu M., Shen W.M., Cheng G.Q. An
improved stochastic programming model for
supply chain planning of MRO spare parts.
Applied Mathematical Modelling. 2017;47:189207.
[3] Qin Y., Chan F.T.S., Chung S.H., Qu T., Niu B.
Aircraft parking stand allocation problem withsafety consideration for independent hangar
maintenance service providers. Computers &Operations Research. 2018;91:225-36.
[4] Zhen L., Wang K. A stochastic programming
model for multi-product oriented multi-channel
component replenishment. Computers &Operations Research. 2015;60:79-90.
[5] Nosoohi I., Hejazi S.R. A multi-objective
approach to simultaneous determination of sparepart numbers and preventive replacement times.
AppliedMathematical
Modelling.
2011;35(3):1157-66.
[6] Gu J.Y., Zhang G.Q., Li K.W. Efficient aircraft
spare parts inventory management under demand
uncertainty.
Journalof
Air
Transport
Management. 2015;42:101-9.
[7] Li X.H., Yang D., Hu M.Q. A scenario-based
stochastic programming approach for the productconfiguration problem under uncertainties andcarbon emission regulations. Transportation
Research Part E-Logistics and Transportation
Review. 2018;115:126-46.
[8] Somarin A.R., Asian S., Jolai F., Chen S.L.
Flexibility in service parts supply chain: a study
on emergency resupply in aviation MRO.
International Journal of Production Research.
2018;56(10):3547-62.

CONCLUSION
Outsource the aircraft heavy maintenance to aprofessional maintenance company is becoming a
trend in aviation industry, and the spare parts are
essential for conducting the maintenance operations
on the aircraft. Moreover, procurement of the MRO
parts can lead to high inventory holding cost and longlead time. Maintaining sufficient MRO parts andminimizing inventory cost are critical for the aircraft
maintenance enterprise. To better resolve the sparepart procurement planning problem, a stochastic
programming model for the MRO spare partsprocurement planning problem in developed in thispaper, which assists the maintenance service
company better arrange the maintenance procurement
plan that aligns with the maintenance schedule forfulfilling the maintenance request from clients. The
future research of this topic can be the developmentof efficient exact algorithm to solve thisdecomposable structure mathematical model.
ACKNOWLEDGEMENTS
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-UADM); and The
Hong Kong Polytechnic University under student
account code RUF1.
REFERENCES[1] Marcontell D. MRO's offshore edge shrinking.
Aviation Week & Space Technology.
2013;175(22):56.

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COMPUTING PROGRAM FOR EVALUATING RESSUREMETERTEST RESULTS OF CLAY
1
Radhi Alzubaidi and 2Athra Al-Kanim
College of Engineering, University of Sharjah, UAE
2
MSc Student, College of Engineering, AlNarain University, Iraq
1

ABSTRACTDue to the increasing importance of the results of pressuremeter testing and their reliable applications fordetermining the engineering properties of soils. Different methods and theories been used to analyze and interpretthe pressuremeter parameters, many assumptions reflect the uncertainties of soil properties ,where some assumed thesoil is elastic perfectly plastic and the tests insured plain strain conditions , the horizontal at rest pressure and limit
pressure represent a great value in the design of foundations , a computer program been developed to explore theresults of , conventional and theoretical limit pressure using different methods of analysis ,the importance of thecomputer program is to simplify the methods of determining the conventional and theoretical limit pressure with out
drawings the curves that necessary to determine the different parameters usually used in the analysis and unified all
the symbols of different methods. The results of conventional and theoretical limit pressure showed distinctive
discrepancies when using different methods of analysis.
Keywords: Site investigation, Conventional limit pressure, Theoretical limit pressure, Pressuremeter
regression analysis for generating empirical equation
between the shear strength obtained from unconfined
shear strength tests and limit pressure deduced frompressuremeter testing ,they concluded thatthepresented equations based on the nonlinear regression
analysis may be valuable for similar soils. Ahmadi
and Keshmiri [5] presented a numerical finite
difference model of self-boring pressuremeter test
(SBPM) using FLAC software. Therefore,
determination of limit pressure usually needs
extrapolation. They suggested to use cavity pressure
at 10% strain (P₁₀) for the interpretation of in situ
horizontal stress from SBPM test rather than limit
pressure. Hamidi ,Varaksin and Nikraz [6] studied
the established empirical relationships between thelimit pressure and Menard Modulus , they concluded
that for practical purpose this method is able toprovide Menard Modulus values of the correct
magnitude.The present research developed acomputer program to evaluate the theoretical andconventional limit pressure using different methods.
All the symbols of different method for evaluating
the conventional and theoretical methods been
unified.

INTRODUCTION
Laboratory testing for soil samples have alreadybeen subjected to a number of disturbance effects likeboring operation, act of sampling, transport, removalfrom the sampler, stress relief and trimming andothers .There is much to be said in favor of in-situ
testing when many of these disturbance effects are
eliminated. The pressuremeter testing seems toreceive a great application in site investigation andfoundation design where the deduced results predict
many valuables parameters from one test. Moayed ,Kordnaei and Mola-Abasi[1] used the limit pressure
to calculate the settlement and bearing capacity offoundation. They proposed various empirical
relations to correlate the limit pressure and theModulus to other soil parameter like the moisture
content, plasticity index and SPT counts (N60). Tezel, Hacialioglu , Onal , and Ozmen [2]compared theresults of pre-bored pressuremeter and high pressurepressuremeter tests conducted in soil to construct ahigh rise tower project. They conclude that the net
limit pressure values that could be reached in theHyperPAC test are higher than the values that can bereached by Menard Pressuremeter. Lukas [3] used
Menard pressuremeter to predict the results of thelimit pressure in different type of soils to evaluate thesettlement, with experience, reliable data was
obtained that allowed for more reliable settlement
predictions. Agan and Algin [4] conducting several
pressuremeter testing in clay soil and used non-linear

PRESSUREMETER TESTS RESULTS
The site for carrying the pressurmeter tests locatedon Baghdad - Kut road at Al-Rashid University
proposed site. The soil consists mainly of brown silty
clay layers with different consistencies and different
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SEE - Bangkok, Thailand, Nov.11-13, 2019

gypsum contents, the analysis and application of thecomputer program in the present study carried out by
Al-kanim [7] , used the test results of Al-Rawi[8]Menard pressuremeter tests carried out on the same
site, Fig.1 shows the pressure increment with volume
change reading at 60 second after application of thepressure. The pressure readings recorded during thetests were adjusted to compensate for both, the headof water in the central cell tubing of the probe and theinertia of the rubber.

The Results Of The Conventional Limit Pressure
The values of the conventional limit pressure
evaluated using five methods of analysis ,thesemethods as follow
1- Expansion P- ∆V curve method.
2- The upside -down curve method.
3-P- ln (∆V/V) method
4- The relative volume method
5- Log-log method
The results are shown in Fig.2 to Fig.5 for fourbore holes at different depths, it seems that the P-∆V
method predicted higher values for the conventional
limit pressure ,while the up-side down curve method
and P- ln (∆V/V) method deduced the lower values,the log-log method and relative -volume method arein between. The values of the conventional pressure
in BH.No.87 (Fig.2) deduced from the P-∆V method
are higher than those deduced from up-side down
curve method, P- ln (∆V/V) method, log-log method
and Relative volume method in range from 5% to
48% , 1% to 48% ,3% to 24% , 5% to25%
respectively . The same trend found in BH. No. 62 as
can be seen in Fig.3 ,the values of the conventional
limit pressure deduced from P-∆V method are higher
than those deduced from up-side down curve method,P- ln (∆V/V) method, log-log method and Relative
volume method in range of 1% to 42% , 1% to 36%,0.5% to 19% , 0.4% to20% respectively .

THE COMPUTER PROGRAM
The computer is designed to predict the values of
the horizontal at rest pressure and the limit pressureusing different methods of interpretation. The
computer program evaluates the horizontal at rest
pressure using the inflection point method, while thecomputer program predicts the values of theconventional limit pressure using five method and thetheoretical limit pressure using three methods. The
methods used to evaluate the conventional limit are
as follows:
1- Expansion P- ∆V curve method.
2- The upside -down curve method.
3-P- ln (∆V/V) method
4- The relative volume method
5- Log-log method
The methods used to evaluate the theoretical limit
pressure as follows

2500

1- The up side -down method
2- The P- 1/ εo method
3- The P-ln ∆V/V method
The values of the horizontal at rest pressure evaluatedusing the inflection point method

Convetional Limit Pressure (KN\m2)

2000

1500

P-∆V

Up-sideP-ln∆V
log-log

1000

relative-volume

500

0
0

1

2

3

4

600

6

7

8

9

Fig.2 Conventional limitp pressure using different
methods bh.no.87

500

400

3500

300

3000

200
Conventional limit Pressure (KN/m2)

Volume Change (cm3)5Depth (m)

100

0
0

200

400

600

800

1000

1200

applied pressure(KN/m2)

2500

P-∆V

2000

Up-sideP-ln∆V
1500

log-logrelative-volume

1000

500

Fig.1 Pressuremeter test curve at al-rashid university
site (AlRawi,1985)

0
0

1

2

3

4

5

6

7

8

9

10

Depth (m)Fig.3 Conventional limit pressure using different
methods bh.no.62
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Conventional Limit Pressure (KNlm2)

Also in Fig.4 the values of the conventional of
BH.61evaluated from P-∆V method are higher thanthose deduced from up-side down curve method, Pln (∆V/V) method, log-log method and Relative
volume method in range of 4% to 28% , 4% to 29%,3% to 26% , 3% to16% respectively.In BH.No.92,the results of the conventional limit pressure using
different methods are shown in Fig. 5 , the values of
the conventional evaluated from P-∆V method are
higher than those deduced from up-side down curve
method, P- ln (∆V/V) method, log-log method andRelative volume method in range of 2% to 25% , 3%
to 24% ,3% to 26% , 0.5% to14% respectively.
Manual calculations of the conventional limit showed
good agreements with results evaluated from thecomputer program for the all methods ofinterpretation.

1200
1000

P-∆V
Up-sideP-ln∆V
log-logrelative-volume

800
600
400
200
0
0

2

4

6

8

10

Depth (m)Fig.5 Conventional limit pressure using different
methods bh.no.92
Fig.7 represents the results in BH.No.62 , theresults of theoretical limit pressure analyzed using Pln ∆V/V method are higher than those evaluatedusing up side -down method and P- 1/ εo method in
the range of 9% to 12% and 2% to 11 % respectively. The results of theoretical limit pressure in BH.No.61
can be seen in Fig.8, analyzed using P-ln ∆V/V
method are higher than those evaluated using up side
-down method and P- 1/ εo method in the range of
3% to 21% and 2% to 13 % respectively.The same
trend found in BH.No.92 as can be seen in Fig.9, theresults of the theoretical limit pressure deduced using
P-ln ∆V/V method are higher than those evaluatedusing up side -down method and P- 1/ εo method in
the range of 4% to 15% and 1% to 8 % respectively.
Manual calculations of the theoretical limit showed
good agreements with results evaluated from thecomputer program for the all methods of analysis.

The results of the theoretical limit pressure
The values of the theoretical limit pressureinterpreted using three methods of analysis ,these areas follow
1- The up side -down method
2- The P- 1/ εo method
3- The P-ln ∆V/V method
The results of theoretical limit pressure using thethree methods for the four boreholes are shown in
Fig.6 to Fig.9 .
800
700
600
500

P-∆V
Up-sideP-ln∆V
log-logrelative-volume

400
300

2500
Theoretical Limit Pressure (KN/m2)

Conventional Limit Pressure (KN/m2)

1400

200
100
0
0

1

2

3

4

5

6

7

8

9

Depth (m)Fig.4 Conventional limit pressure using different
methods bh.no.61

2000

Up-sideP-1/εoP-ln∆V

1500

1000

500

0
0

1

2

3

4

5

6

7

8

Depth (M)As can be seen from the results, the values of thetheoretical limit pressures yield from the P-ln ∆V/V
method are little higher than the other two methods,in BH.No.87 as shown in Fig.6 ,the results oftheoretical limit pressure evaluated using P-ln ∆V/V
method are higher than those evaluated using up side
-down method and P- 1/ εo method in the range of
2% to 17% and 3% to 12 % respectively.

Fig.6 Theoretical limit pressure using different
methods bh.no.87

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SEE - Bangkok, Thailand, Nov.11-13, 2019

2- A manual calculation been carried out to calculate
the values of the conventional and theoretical limit
pressure in order to confirm the calculation fromthe computer program and the results showeddistinctive consistency.
3-The conventional limit pressure evaluated using
five methods of analysis using the results of fourboreholes in brown silty clay soil.
4- The values of the conventional pressure deduced
from the P-∆V method are higher than thosededuced from up-side down curve method, P- ln(∆V/V) method, log-log method and Relative
volume method in range from 1% to 48% , 1% to
48% ,0.5% to 26% , 0.4% to25% respectively.
5- The values of the theoretical limit pressure using
three methods of analysis using the results of fourboreholes of the same soil.
6-Tthe results of theoretical limit pressure evaluatedusing P-ln ∆V/V method are higher than thoseevaluated using up side -down method and P- 1/ εomethod in the range of 2% to 21% and 1% to 13 %respectively.

3500

Theoretical Limit Pressure (KN/m2)

Up-sideP-1/εo3000

P-ln∆V

2500
2000
1500
1000
500
0
0

1

2

3

4

5 (M)
Deprth

6

7

8

9

10

Fig.7 Theoretical limit pressure using different
Methods BH.No.62
1200

Theoretical Limit Pressure (KN/m2 )Up-side1000

P-1/εoP-ln∆V

800

600

400

200

0
0

1

2

3

4

5

6

7

8

9

Depth (M)

REFERENCES

Fig.8 Theoretical Limit Pressure Using Different
Methods BH.No.61[1]. Moayed, R ., Kordnaeij, A. and Mola-Abasi, H“Pressuremeter Modulus and Limit Pressure of
Clayey Soils Using GMDH-Type Neural
Network and Genetic Algorithms. Geotechnicaland Geological Engineering · August 2017,DOI:
10.1007/s10706-017-0314-9[2]. Tezel G, Hacialioglu E, Onal O, and Ozmen G“Comparison of High Pressure Pressuremeter(HyperPac) and Pre-Bored Pressuremeter Test
Results - A Case Study.Proceedings of the 18th
International Conference on Soil Mechanics andGeotechnical Engineering, Paris 2013[3]. Lukas R “Pressuremeter Testing in Stiff to Hard
Cohesive
Soils“Seventh
International
Conference on Case Histories in GeotechnicalEngineering - Apr 29th - May 6th ,2013 Missouri
University of Science and Technology Scholars'Mine.
[4]. Agan, C and Algin, H “Determination ofRelationships between Menard Pressuremeter
Test and Standard Penetration Test Data by
Using ANN model: a Case Study on the Clayey
Soil in Sivas, Turkey”. Geotechnical Testing
Journal 37, no. 3, 2014, pp 412-423.
[5]. Ahmadi, M. and Keshmiri ,E “Interpretation ofin situ horizontal stress from self-boringpressuremeter tests in sands via cavity pressureless than limit pressure: a numerical study,
Environmental earth sciences, Vol.76, No.9,
2017

Theoretical Limit Pressure (Kn/m2)

1800
1600

Up-sideP-1/εo1400

P-ln∆V

1200
1000
800
600
400
200
0
0

1

2

3

4

5

6

7

8

9

10

Depth (M)Fig.9 Theoretical Limit Pressure Using Different
Methods BH.No.92
CONCLUSIONSThis research foxed on developing a new computer
program to be considered when analyzing thepressuremeter tests data to deduce the values of theconventional and theoretical limit pressure using
different methods of analysis. Based on the present
research results, some conclusions can be drawn as
follow:
1- A computer program has been developed using
different methods of analysis to evaluate theconventional and theoretical limit pressure, after
unifying all the symbols of all methods.

259

SEE - Bangkok, Thailand, Nov.11-13, 2019[6]. Hamidi, B,. Varaksin, S and Nikraz, H“Predicting Menard Modulus using Dynamic
Compaction Induced Subsidence. International
Conference on Advances in GeotechnicalEngineering, Perth, Australia Nov.7-9, 2011,
ISBN: 978-0-646-55142-5[7]. Al-kanim , A " Pressuremeter Theories in Clay
Testing" ,MSc thesis ,College of Engineering Al
Nahrain University, Baghdad, Iraq ,1999.
[8]. Al-Rawi, R " Comparison of Shear Strength
Between Different In Situ and Laboratory Tests"
MSc Thesis University of Baghdad ,Iraq,1985

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ANALYSIS OF PROBLEMS AND SOLUTIONS IN THE HEATINSULATING GLASS MANUFACTURING INDUSTRY USING FMEA
1,2,4

Natsuda Paiboon1,Nipalai Inplaeng2, Wisitsree Wiyaratn3 and Anucha Watanapa4*
Production Technology Education, Industrial Education and Technology, King Mongkut’s University ofTechnology Thonburi University, Thailand; 3Industrial Education and Technology, King Mongkut’s
University of Technology Thonburi University, Thailand

ABSTRACTThis research project was aimed to analyze the problems and solutions in the heat insulating glass
manufacturing industry by using technical fault analysis, and to conduct an impact analysis to the application whendead time that occurs in the process of insulating glass units. This research was done with several tasks to reduce
the problem based on risk priority number analysis. The 3 problems with the highest RPN value were presented in
Pareto diagram. The problems were as follows: the glass was dirty, the employees took a long time to inspect theglass, and the employees took a long time to clean the glass. The team brainstormed ways to resolve the problem
and then measured the effect. The result of the adjustment showed that the problem of the dirtiness in the glass
manufacturing process decreased by 40%. The employees decreased their inspection time and their cleaning timeby 42%. The total amount of time for the whole manufacturing process in the past was 7.39 minutes per sheet.
After the adjustment, the manufacturing time reduced to 6.30 minutes. In other words, it decreased by 1.09 minutes,
or 14.75%.
Keywords: Heat Insulation Glasses, Failure Mode and Effects Analysis, Pareto Diagram, Cause and EffectDiagramthe data were analyzed using Failure Mode and EffectAnalysis (FMEA) in order to resolve problems in
Phase 2. By doing so, the effectiveness increased andthe manufacturing cost decreased. Moreover, theworking hour decreased and there were fewer
unnecessary jobs. Therefore, FMEA was useful inthis study because it could reduce the waste in the
manufacturing process. This study would look at the
problems in the manufacturing process and solutionsin the heat insulating glass manufacturing industry
using FMEA.

INTRODUCTION
Float glass manufacturing system is a modern
system for manufacturing a sheet of glass which canbe used in households and buildings. It can beconverted to become heat insulation glass for houses
and buildings. Generally, heat insulation glass
contains two layers of glass, one internal and one
external; hence, the ability to reduce the heat into thebuilding. The space between the two layers helps
push the heat outside the building [2]. The
manufacturing process starts with Phase 1 which isthe preparation in which 2 sheets of glass are loaded
to the machine to reduce the sharpness at the margin
by approximately 40% of the whole sheet and thenthey are loaded to the cleaning machine. In Phase 2,
the frame will be fixed to the glass. The frame will bechecked again to meet the requirements and the glass
will be cleaned before the unit is loaded to the glass
compressor. In Phase 3, silicon will be applied to theframe and the glass to make them sealed and then theglass will be put aside to leave it until the silicon dries.
Then, the glass will be checked for 100% accuracy
before it is stored in the warehouse, ready for dispatch
to customers.
Because there are many repetitions as mentioned
above, the bottleneck problem occurs in Phase 2, theframe being fixed to the glass, resulting in waste time.
The researchers were interested in such problem andcollected the data as well as presented the data in
Pareto diagram in order to find out the problem. Then,

LITERATURE REVIEWThe research studies into FMEA started in 1977
when Ford Motors introduced FMEA to address thepotential problems in the Research and Development(R&D) in the early stage of production and publishedthe Potential Failure Mode and Effects Analysis
Handbook in 1984 to promote the method. The
FMEA model was applied in salmon processing andpacking industry in collaboration with ISO 22000 andthere were valuable results from the implementation[7]. FEAM was also used in order to improve thequality continuously and there were multiple casestudies in automobile SMEs. The implementation of
those improvement points shows the definite signs ofcontinuous improvement of the quality of process andproduct as well. The FMEA and subsequent
implementations had reduced the quality rejections
by around 3% to 4% in companies in the case study
261

SEE - Bangkok, Thailand, Nov.11-13, 2019conducted by Tejaskumar S. Parsana and Mihir T.
Patel who conducted “A Process FMEA Tool toEnhance Quality and Efficiency of Manufacturing
Industry”.

minutes and the longest amount of time was forcleaning the first sheet of glass, or 2.59 minutes,
namely 57.05% of the total time. The amount of time
for cleaning the second sheet of glass was 1.12
minutes, or 24.67% of the overall time.
Procedure 3 or the sealing as shown in ManMachine Chart had no difficulty. If there was adifficulty, it was due to the fact that the silicon was
not sealed properly on the glass. This last set ofprocedure for the heat insulating glass manufacturing
process took 1.10 minutes to complete.

THEORYFMEA is a technique which increases thereliability of a product, decreases an interruption
period in the initial and normal stages because it
focuses on the prediction of problems and analyzes
the solutions in order to show risk priority number(RPN).
METHODOLOGY
According to the research study, the waste fromthe manufacturing process would be reduced in theheat insulating glass manufacturing industry using thefollowing steps:
1. Current state would be examined and thengoal would be set in order to improve the
manufacturing process.
2. Steps and procedures to improve would bebased on the principles of FMEA.
3. Steps and procedures would be implemented
after the data collection in accordance with the setup.
4. The results before and after the intervention
would be compared.

Fig. 1 Layout of machines and devices in the heatinsulating glass manufacturing process at the current
state

RESULTS
3.1 A study into the current state of heat insulating
glass manufacturing process
During the heat insulating glass manufacturing
process, from the loading of glass and transferring tothe other steps, there were 3 sets of procedure. The
first set of procedures involved loading. The second
set involved assembly and the third set involved
sealing as shown in Fig.1.
Procedure 1 or the loading could be analyzed
using Man-Machine Chart as shown in Table 1 andthe total amount of time was 1.75 minutes or equal to2.15 minutes when increasing the cleaning work sincebringing the glass into the process. The effectivenesswas compared to the man labor and it was 95.43% out
of 100%. That means humans worked effectively.
Regarding the efficiency of Machine 1, it was 71.43%
because there was dead time as it waited for theloading. The efficiency of machine 2 was 34.29%
because it waited for the loading and for Machine 1
to complete the task. The efficiency of Machine 3 was
23.43% because the dead time was the longest as it
waited for two machines to complete their tasks.
Procedure 2 or the assembly involved Process
Chart because it was about human labor. It was foundthat the total amount of time for Procedure 2 was 4.54

Position
Procedure 1 involves Loading
Number 1 is Pallet for two sheets of glass
Number 2 is Arising Machine
Number 3 is Watching Machine
Procedure 2 involves Assembly
Number 4 is Elevation / Arising Platform?
Number 5 is area for unused frame
Number 6 is Inspection area
Number 7 is Pressing Machine
Number 8 is Desiccant filling machine
Number 9 is Butyl sticking machine
Number 10 is Table for frame
Number 11 is Cabinet and Bin
Number 12 is Table for documents
Procedure 3 involves Sealing
Number 13 is Silicone injector
Number 14 is Pallet for finished glass

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 Man-Machine Chart for Loading Glass (Former)
Man-machine working chart
Man

time
(min)

Machine1 Suckthe glass

time
(min)

Glass preparing

0.2

No
working

0.2

0.25

Suck the
glass

0.25

No
working

0.3

Clear glass

0.3

1

No working
Clear glass

0.11
0.3

No working

0.59

Forced glass
suction machine
into conveyor
prepare thesecond mirror
No working
Forced glass
suction machine
into conveyor

0.22
0.08
1

Suck theglass

Machine 2
Clear glass

time
(min)

No working

0.45

total
1.75
total
1.75
total
NOTE: Total time is 1.75 minutes or equal to 2.15 minutes

It was found that the amount of time for Procedure 1
was 2 . 1 5 minutes and that the amount of time for
Procedure 2 for cleaning was 4 . 1 1 minutes. The
amount of time for Procedure 3 was 1 . 1 0 minutes.
The total amount of time for the whole glass
manufacturing process was 7.39 minutes per sheet. It
was found that the amount of time for cleaning glassin Procedure 2 and for inspection was quite long. It
needed to be reduced because in the heat insulating
glass manufacturing process there was already amachine for cleaning/washing the glass. Therefore, it
was an unnecessary repetition when the glass had to
be cleaned again. This problem would create abottleneck and the amount of time was collected andmeasured and then presented in a Pareto Chart inorder to show the problem as seen in Fig. 2.
3

100.00

2.5

80.00

2

40.00
20.00

0

No
working

0.75

Clean
glass
No
working
total

0.41
0.59
1.75

According to the data analysis of the Pareto Chart,
the dead time for the process was found during thefollowing steps: 1) cleaning the first sheet of glass,and 2) cleaning the second sheet of glass, which is themain reason for dead time and unnecessary waitingtime. If 2 sheets of glass needed to be cleaned and theamount of time was combined, it would be 81.72 per
cent. The dead time was over 50% and it was forcleaning the first sheet of glass because the first sheetof glass was laminate; hence, the longer time forcleaning. In order to reduce the time and to clean both
sheets of glass, the principles of FMEA were used inorder to analyze and resolve the real cause of the
problem in the heat insulating glass manufacturing
process.

60.00

0.5

time
(min)

A. Clean the glass plate 1
B. Clean the glass plate 2
C. Assembling the frame
D. Go to process 3
E. Wait for the second mirror.
F. Go to the mirror compression machine
G. Wait for the mirror sheet 1
H. Walk to pick up the frame.
I. Grab the frame
J. Walk backK. Compress the mirror

1.5
1

1.75

Machine
3
Clean
glass

0.00
A B C D E F G H I J KResults from the adjustment to the heat insulating
glass manufacturing process based on FMEA

Fig. 2 Pareto Chart showing the heat insulating glass
manufacturing process

According to FMEA, the main problem in the heatinsulating glass manufacturing process was the time263

SEE - Bangkok, Thailand, Nov.11-13, 2019spent on cleaning sheets of glass as shown in the
Table 2. The amount of time for Procedure 1 was 2.15
minutes. After the implementation of the adjustment,
Procedure 1 took a longer time to become 3. 1 5
minutes or 2 minutes longer because the glass wascleaned from the beginning. However, Procedure 2
took 1. 31 minutes instead of 4. 11 minutes. In otherwords, the amount of time reduced by 2.8 minutes or
6 8 . 1 3 % . The total amount of time for the whole
manufacturing process in the past was 7 . 3 9 minutes
per sheet. However, the adjustment brought the
manufacturing process down to 6.30 minutes. In otherwords, the manufacturing process reduced by 1 . 0 9
minutes or 14.75%.

glass and the amount of time to clean and inspectremained the same. The other cause of problem which
was not as severe as the first one was that the machine
stopped suddenly, resulting in the glass getting stuck
inside the machine and the new operation time.
The problem could be resolved after the
adjustment and the evaluation of the new RPN
showed that that the severity (S) remained the same
because the dirtiness needed to be cleaned. The
Occurrence (O) decreased from 9 to 7, or 77.78% andthe ability to detect (D) decreased from 9 to 7 , or77.78%.
After the adjustment to the heat insulating glass
manufacturing process based on FMEA, theresearchers collected the data of the samples of theTable 2 Man-Machine Chart for the heat insulating glass manufacturing process (Adjustment)
Man-machine working charttime
Machine 1
time
Machine 3
Machine 2
time
time
Man
(min)
Suck the
(min)
Clean
(min)
Clear glass
(min)
glass
glass
Glass
No
1.2
1.2
preparingworking
Forced glass
No working
1.65
suctionSuck the
0.25
0.25
No
machine into
glass
working
1.95
conveyor
prepare thesecond mirror
0.22
No
0.3
Clear glass
0.3
working
No working
0.08
No working
0.11
Clean glass
0.41
Forced glass
Clear glass
0.3
suctionSuck the11No
machine intoglassNo
working
0.59
working
0.59
conveyor
total

2.75

total

2.75

total

2.75

total

2.75

Note ** Total time is 2.75 minutes or equal to 3.15 minutes
The main problem of FMEA is Risk Priority
Number (or RPN). If a problem has a high level of
RPN, that problem needs to be resolved quickly. In
this case, the problem with the highest RPN was thefact that the glass was dirty and therefore it took along time for employees to clean it. The principles of
FMEA are useful because the results are obvious. In
this case, the value of RPN based on the Severity (S)of the problem due to the dirtiness of the glass
decreased from 1 0 to 6 or decreased by 6 0 % . The
total amount of time for cleaning and inspection
reduced from 10 to 6, or 60%. The Occurrence (O) of
the glass for dirtiness reduced from 10 to 5 or reducedby 5 0 % . The amount of time for cleaning andinspection decreased from 1 0 to 7 or decreased by
70% because the cleanliness improved from the first
Procedure. The ability to detect (D) the dirtiness ofold glass sheets and collected the new data from
Procedure 1 . Because there were more tasks inProcedure 1 to reduce the unnecessary tasks inProcedure 2 , the amount of time for Procedure 1
increased to 3 . 1 5 minutes for 1 pair of glass. The
effectiveness in comparison to human labor was
9 7 . 1 0 % because the cleaning task was added. The
efficiency of Machine 1 was 45 . 45% because there
was dead time while it waited for the loading. The
efficiency of Machine 2 was 2 1 . 8 2 % because it
waited for the loading and Machine 1 to complete thetasks. The efficiency of Machine 3 was 1 4 . 9 1 %because the dead time was the longest.
The amount of time for Procedure 2 in the past
was 2 minutes 5 seconds and after the adjustment it
was 1 minute 7 seconds. It decreased by 32.68%. The
amount of time for cleaning the second sheet of glass
264

SEE - Bangkok, Thailand, Nov.11-13, 2019

decreased to 1 minute 4 seconds, or by 31.22%. It canbe seen that Procedure 2 after the adjustment to thecleaning task which was taken out and put inProcedure 1 made the first Procedure work longer for
1 minute. However, the problem of cleaning wasdifficult and there were limitations as follows:
1 . The washing machine contained a system
which cannot be replaced inside. The cloth inside themachine can be used with any type of glass. If thecloth can be replaced to meet the requirements of eachglass, it will take a longer time to set up and to checkthe quality of the glass sheet.
2 . Employees during the assembly procedureneeded to be trained to assemble and clean the glass.
The distance for viewing is 2 meters and the external
environment must be adjusted every minute inaccordance with the situation.
3 . Check Sheet needs to be used to monitor andcontrol mistake and error. It can also indicate the pasterrors.
After the adjustment based on FMEA, it was
found that the severity (S) and the occurrence (O)decreased but the detection (D) remained the same.
According to the analysis, when a sheet of glass isdirty or contains a stain, it cannot be used in the next
procedure because it needs to be cleaned andinspected, which can take a long time. The glass forcustomers must meet the requirements. Therefore, theglass needs to be checked to reduce the chance ofdirtiness, the time for cleaning and the time forinspection. After the adjustment with the new valuesof RPN, it was found that the severity (S) of the
product decreased to moderate level. In other words,
the dirtiness of the glass decreased from 1 0 to 6 , orby 6 0 % . The amount of time for cleaning andinspection decreased from 1 0 to 6 , or by 6 0 % . The
occurrence (O) of error and mistake was high or
higher than 1 out 2 0 in the past but after the
adjustment it was at a moderate level, or 1 out of
1 , 0 0 0 or 1 out of 8 0 . The dirtiness of the glass
decreased from 1 0 to 5 , or by 5 0 % . The amount oftime for cleaning and inspection decreased from 10 to
7 or by 7 0 % because the cleaning task was done inProcedure 1. The ability to detect (D) the dirtiness ofthe glass and the amount of time to clean and inspect
the glass remained the same because the glass stillneeded to be cleaned and checked for any cracks anddirtiness. The washing machine could cause stain or
dirty spots. According to the analysis, it was foundthat when the washing machine stopped suddenly andone sheet of glass got stuck inside the machine, thepieces of glass would make stain on the glass sheet.
This is the limitation which this machine cannot
resolve. After the adjustment based on FMEA with
RPN, it was found that the severity (S) remained thesame but the effect of the error on the product was at

a moderate level because the stain and the dirtinesscan be cleaned. The occurrence (O) for any error wasquite high or higher than 1 out of 2 0 in the past but
after the adjustment it became 1 out of 1,000 or 1 outof 8 0 . In other words, it decreased from 9 to 7 , or77.78%. The ability to detect (D) was low in the past
but after the adjustment the detection was at amoderate level
CONCLUSIONSThis research was aimed to analyze the problems
and solutions in the heat insulating glass
manufacturing industry using FMEA to analyze thedead time in the heat insulating glass manufacturingindustry. The faults with the top three highest valuesof RPN were presented in a Pareto Chart and they
were fixed. The main problems were the fact that theglass was dirty, that the employees took a long timeto inspect the sample, and that the employee took along time to clean the sheet of glass. After the
adjustment it was found that the dirtiness in the glass
manufacturing process decreased by 40%. The
employees decreased their inspection time and theircleaning time by 42%. The total amount of time forthe glass manufacturing process was 7.39 minutes per
sheet. After the adjustment, the total amount timedecreased to 6.30 minutes. In other words, it
decreased to 1.09 minutes or by 14.75%.
ACKNOWLEDGMENTS
The authors would like to thank the National
Research Council of Thailand for financial support.
REFERENCES[1] Moghal A. A. B., Dafalla M. A., Elkady T. Y., and
Al-Shamrani M.A., Lime Leachability Studies on
Stabilized
Expansive
Semi-Arid
Soil.
International Journal of GEOMATE, Vol. 9, Issue
18, 2015, pp.1467-1471.
[2] 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.
[3] Hossain M.Z., For Chapter in a Book, Soil
Mechanics, 4th ed. Vol. 2, Sakai, Ed. Sankeisha
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[4] Author H., A Book New York Publisher, Year,
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[5] Annnn B., Unpublished Work but Accepted, Vol.,
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[6] Kimura S., Journal Paper Title, J. of Computer
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[7] Islam M.R., Conference proceedings, in Proc. 2ndInt. Conf. on GEOMATE, 2011, pp. 8-13.
265SEE - Bangkok, Thailand, Nov.11-13, 2019[8] Hossain M.Z. and Awal A.S.M.A., Experimental
Validation of a Theoretical Model for Flexural
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Composite, Const. Build. Mat., Vol.25, No.3,
2011, pp.1460-1465.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

APPLICATION OF DEAGGREATION OF SPATIAL PROBABILISTICSEISMIC HAZARD TO DISASTER PREPAREDNESS
1Takayuki Hayashi1 and Harumi Yashiro2
Tokio Marine & Nichido Risk Consulting Co. Ltd., Japan;
2
National Defense Academy, Japan

ABSTRACTIn considering regional disaster prevention, it is important to understand the occurrence area of the strong
ground motion and its occurrence probability. Spatial probabilistic seismic hazard analysis (SPSHA) proposed by
the authors can provide the such information. In SPSHA, the results are expressed by the relation between the area
where a given seismic intensity is generated and the exceedance probability. Results based on such a probabilistic
approach include the effects of various seismic sources. Therefore, to clarify the earthquake scenario that shouldbe the target of regional earthquake countermeasures, it is necessary to grasp the impact of each earthquake source.
In this study, we propose the seismic hazard deaggreagation for SPSHA and show a method for quantitatively
grasping earthquakes that affect the target region. In the application example, SPSHA is conducted for Kanagawa
prefecture in Japan. We also conduct seismic hazard deaggreagation for whole area and sub-area inside and discuss
the differences of dominant earthquake for each area and the application to such information to disaster prevention.
Keywords: PSHA, Seismic hazard deaggreation, Spatial Correlation, Disaster prevention plandamage assessment in the past. Okada et al.[1] havereported that the uncertainty of target earthquake
scenario setting greatly affects the estimated damage.
Also, Tomatsu et al. [2] have proposed a method toselect the target earthquakes using Analytic
Hierarchy Process (AHP) based on the estimateddamage. These are based on a deterministic approach,and the image of earthquake scenario such as theearthquake source and magnitude are clear. However,since a small number of scenarios are basicallytargeted, it cannot be denied the scenario that an
unexpected earthquake occurs. In addition, when
considering the whole area, appropriate target
earthquakes are selected for the entire region, butthere is a possibility that a high impact scenario for a
specified sub-area inside may not be selected.
Alternatively, a probabilistic approach covers all
earthquakes affecting the region comprehensively
and is superior in that it can consider the occurrence
probability of earthquakes and earthquake hazards
simultaneously. In the past, such Probabilistic
Seismic Hazard Analysis (PSHA) have been studied
for specific sites, so the authors have proposed amethod that extends PSHA throughout the area.
Spatial Probabilistic Seismic Hazard Analysis(SPSHA) [3] proposed by the authors is a method of
calculating the relationship between the occurrence
area of given ground motion intensity and its
exceedance probability in the target area taking into
consideration the correlation of spatial groundmotions. In this method, the earthquake motion
prediction equation is corrected based on theearthquake observation records obtained in the target
area, and the spatial correlation of ground motion

INTRODUCTION
In recent years, many big earthquakes haveoccurred in Japan. In the near future, there areconcerns about the occurrence of megathrustearthquake around the Nankai Trough, Tokyo inland
earthquake and soon,and earthquake
countermeasures are urgently needed. Local
governments are considering the measures in advancesuch as the emergency plan, emergency restoration at
the time of disasters, and the reconstruction plan, andconclude them as their regional disaster prevention
plans. In establishing the regional disaster prevention
plan, they will carry out earthquake damage
assessment. Select the earthquake scenarios that
occur in the area, and quantify building damage,casualty, economic damage, etc. This is a necessary
study to make the measures effective and specific.
In this earthquake damage assessment, sometarget earthquakes are often selected after discussions
by the expert committee in consideration of large
earthquakes that occurred in the past and earthquake
activity areas around the target region. The outcomeof the earthquake selection may depend on theknowledge and experience of the expert or thesituation of the discussion. In addition, the way of
selecting target earthquakes by local governments
across the country is diverse in their studying, and nounified way of selection is shown. Authors believethat the criteria for earthquake and earthquake
scenario selection should be based on a moreobjective process.
Several studies have been conducted on theselection of target earthquakes in regional earthquake
267

SEE - Bangkok, Thailand, Nov.11-13, 2019represents a sample number. 𝑥 is a ground motion
intensity sample, 𝑥̂ is a log median value of groundmotion intensity calculated by the GMPE, and 𝛽𝑖 is asite correction coefficient of the GMPE obtained fromdata analysis of earthquake observation records.
𝜀𝑒𝑗 (0, 𝜎𝑒 ) and 𝜀𝑐𝑗 (0, 𝜎𝑐 ) are random variables withan average 0 and a standard deviation of 𝜎𝑒 and 𝜎𝑐 ,respectively.
𝜎𝑐 represents inter-event variation and assumescommon and perfect correlation at all sites. 𝜎𝑐indicates intra-event variation and gives spatial
correlation by the following equation.

intensity is taken into consideration. However, since
the result is expressed by the area of the seismic
ground motion and the occurrence probability, there
is a problem that the image of earthquake scenariothat generates the seismic hazard is hard to recognize.
In this study, in order to grasp the image of resultsby SPSHA, we propose the method of deaggreagationof seismic hazard by SPSHA and the method of
selection of the suitable target earthquake scenario forearthquake damage assessment for the region. In
addition, we apply this method to Kanagawa
Prefecture and discuss the application for regional
disaster prevention.

𝜌 = 𝑒𝑥𝑝(−𝛾 ∙ 𝑧 𝛿 )OUTLINE OF SPSHA

Where, 𝑧 is a separation distance (km) between twosites, 𝜌 is a correlation coefficient, and 𝛾 and 𝛿 areregression constants obtained from data analysis ofearthquake observation records.
By the way, 𝛽𝑖 in Eq. (4) is calculated only atearthquake observation sites. Therefore, after
sampling the ground motion intensity at the sites by
Eq. (5), the ground motion intensity at the center
points of the meshes obtained by spatially discretizing
the target area are calculated by spatial interpolation
using the simple kriging method. The relationshipbetween the area and the exceedance probability
exceeding the given ground motion intensity 𝑦calculated from the above is hereinafter referred to asa seismic area hazard curve.

In Spatial Probabilistic Seismic Hazard Analysis(SPSHA) proposed by the authors [3], the probability𝑃(𝐴 > 𝑎; 𝑡, 𝑦) that area A (or area ratio) of the area
exceeding the strong ground motion intensity 𝑦
exceeds 𝑎 in 𝑡 years due to earthquakes in a certain
area is calculated by the following equation.
𝑷(𝑨 > 𝒂; 𝒕, 𝒚) = 𝟏 − ∏𝒌 {𝟏 − 𝑷𝒌 (𝑨 > 𝒂; 𝒕, 𝒚)} (1)Where, 𝑷𝒌 (𝑨 > 𝒂; 𝒕, 𝒚) is area A (or area ratio) of thearea exceeding the strong ground motion intensity 𝒚
exceeds 𝒂 in next 𝒕 years due to the 𝒌-th earthquake.
𝑷𝒌 (𝑨 > 𝒂; 𝒕, 𝒚) is expressed by Eq. (2) if the
updating process is adopted for the 𝒌-th earthquake
occurrence probability, and Eq. (3) if the Poissonprocess is adopted.
𝑷𝒌 (𝑨 > 𝒂; 𝒕, 𝒚) = 𝑷(𝑬𝒌 ; 𝒕)𝑷(𝑨 > 𝒂; 𝒚|𝑬𝒌 )(5)

EARTHQUAKE SENARIO SELECTION BY
SEISMIC HAZARD DEAGGREGAETION(2)
Deaggaregation of the Seismic Area Hazard

𝑷𝒌 (𝑨 > 𝒂; 𝒕, 𝒚) =𝟏 − 𝒆𝒙𝒑{−𝝂(𝑬𝒌 )𝑷(𝑨 > 𝒂: 𝒚|𝑬𝒌 ) ∙ 𝒕} (3)Seismic hazard deaggregation in PSHA is amethod to measure the contribution of each seismic
source on the seismic hazard for a given exceedance
probability. The deaggreation of seismic hazard at a
specific site is shown by Kameda et al. [4] andMcGuire [5]. First, the magnitude of the influence ofeach seismic source on the seismic hazard with acertain exceedance probability is expressed by thecontribution index. Expected values of magnitude andsource distance are derived from the results of hazard
deaggreagation to get the image of seismic source
corresponding to the probabilistic seismic hazard.
This is the expected target scenario for various
damage assessment based on PSHA. In SPSHA,
target is the area, so the source distance cannot be
determined as same way. Therefore, the degree ofcontribution is calculated by the following procedure,
and the earthquakes that affect the earthquake hazard
are identified from the source model of PSHA.

Where, 𝑷(𝑬𝒌 ; 𝒕) is the occurrence probability of the𝒌-th earthquake in next 𝒕 years, and 𝑷(𝑨 > 𝒂; 𝒚|𝑬𝒌 )is a conditional probability that the area 𝑨 (or area
ratio) of the area where the strong ground motion thatexceeds the ground motion intensity 𝒚 occurs
exceeds 𝒂, when the 𝒌-th earthquake occurs.
We calculate the seismic ground motion
distribution samples for the target area by MonteCarlo simulation (MCS) using the Ground Motion
Prediction Equation (GMPE) corrected by theearthquake observation records obtained in the target
area and the spatial correlation model regressed fromthese data. Then, the ground motion intensity at eachsite is treated probabilistically by the following
equation in consideration of the spatial correlation of
the seismic intensity between sites.
log(𝑥𝑖𝑗 ) = 𝑥̂𝑗 +𝛽𝑖 + 𝜀𝑒𝑗 (0, 𝜎𝑒 ) + 𝜀𝑐𝑗 (0, 𝜎𝑐 )(4)

STEP1: SPSHA for the target region
Conduct SPSHA for the target region to beevaluated and calculate the seismic area hazard curve.

Where, the subscript 𝑖 represents the site, and 𝑗
268

SEE - Bangkok, Thailand, Nov.11-13, 2019

For the risk level 𝑅(𝑎; 𝑦𝑡) where the area of theregion exceeding the earthquake ground motion
intensity 𝑦 exceeds 𝑎 for next 𝑡 years, theexceedance probability 𝑃 (𝑎; 𝑦𝑡) is obtained.

equation on engineering bedrock, and shallow soil
amplification factor are referred to Japanese National
Seismic Hazard Map by HERP [6]. Probability
characteristics of ground motion intensity is sampled
by MCS, considering perfect correlation for interevent error and the spatial correlation for intra-event
error for GMPE based on the author's study [3].
Standard deviation of Inter-event variation and Intraevent variation are 0.192, 0.160, respectively. The
number of earthquake ground motion distribution
samples of each earthquake by MCS is 1,000 times.
Finally, the area of a given ground motion intensity issummed up as seismic area hazard curve.
The earthquake environment of Kanagawa
Prefecture is diverse according to the subarea inside.
The Philippine Sea plate subducts toward the northernpart of Tokyo Bay, and inter-plate and intra-plate
earthquakes have occurred in this area. In addition,from the eastern part, the Pacific plate subducts to a
deeper place than the Philippine Sea plate, and thisarea is also active seismic source area. Furthermore,in the area of A3, A4, A5 and A6, there are many
active shallow crustal faults such as the Miura
Peninsula fault zone with a relatively high probabilityof occurrence among active faults around Japan.

STEP2: Contribution index for each seismic source
For the risk level 𝑅(𝑎; 𝑦𝑡), the contribution index
of each earthquake in the source model are calculated.
The contribution index c𝑘 of earthquake 𝑘 to𝑅(𝑎; 𝑦𝑡) is defined by Eq.(6). c𝑘 means theconditional probability that the event is earthquake 𝑘when the area of the region exceeding the seismic
intensity 𝑦 in the area exceeds 𝑎.
𝑐𝑘 (𝑅𝑎;𝑦𝑡 ) = 𝑃𝑘 (𝐴 > 𝑎; 𝑡, 𝑦)⁄∑𝑘 𝑃𝑘 (𝐴 > 𝑎; 𝑡, 𝑦) (6)Earthquake Scenario Selection by Seismic Area
Hazard Deaggaregation
The earthquakes in the source model used in
SPSHA are divided into several groups in terms ofactivity, area, and type, and the contribution to therisk level 𝑅(𝑎; 𝑦𝑡) is summed up by group. From thegroup with the highest contribution value, let theearthquake with the highest contribution rate be therepresentative scenario of the risk level 𝑅(𝑎; 𝑦𝑡). If
contributions indexes are similar among multiple
groups, it is also necessary to adopt representative
scenarios from multiple groups. According to thisway, earthquakes that affect the region can beselected by probabilistic approach. Target earthquake
scenarios for regional disaster prevention can beselected objectively for an optional probability.

Target area

35°30'

A2
A4

A1

A5

APPLICATION

A6

35°00'

Conduction of SPSHA

A3

Kanagawa Pref.
(A0)

SPSHA is conducted for Kanagawa Prefecture
shown in Fig. 3. There are six subareas in Kanagawa
Prefecture, these are based on administrative
divisions. As shown in Table 1, approximately 57%
of the total population in the prefecture lives in
Yokohama City (A1) and Kawasaki City (A2).
According to the proposed method, correction
term of GMPE and spatial correlation model ofground motion intensity are set based on theearthquake observation records of K-NET/KiK-net in
Kanagawa Prefecture and ground motion intensity issampled at observation stations site. We performsurface interpolation of the ground motion intensity
distribution of the target area by Simple Kriging
method using ground motion intensity samples atobservation sites. The target area is discretized into amesh of about 1 km2 and Peak ground velocity (PGV)
on engineering bedrock at the center point of the meshis estimated. Ground motions intensity distribution is
calculated on a mesh of about 250m2. The earthquake
source model, earthquake ground motion prediction

139°00'140°00'139°30'K-NET station

Fig. 1
Table 1
Area
A1
A2
A3
A4

A5

A6
Total

269

KiK-net station

Target area for this study
Areas and the populations (As of March 2019.)
CitiesYokohama
Kawasaki
Yokosuka, Kamakura,
Zushi, Miura, Hayama
Sagamihara, Atsugi,
Kiyokawa, Yamato,Zama,
Ebina, Ayase, Aikawa,
Hiratsuka, Fujisawa, Oiso,
Chigasaki, Hatano, Isehara,
Aikawa, Ninomiya
Odawara, Nakai, Oi,
Hakone, Minami-Ashigara,
Matsuda, Yamakita, Kaisei,
Manazuru, Yugawara
Kanagawa prefecture

Area(km2)
437
143

Population
3.74 mil.
1.52 mil.

207

0.70 mil.

621

1.57 mil.

372

1.31 mil.

635

0.34 mil.

2,416

9.18 mil.

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Area ratio corresponding to EP30 by SPSHA
PGV(cm/s)

50
or
more

100
or
more

SPSHA. In the grouping, first, earthquakes areclassified into two categories: the identified
earthquakes and the unidentified earthquakes. The
former is called the characteristic earthquakes and thelatter is called the background earthquakes in PSHA.
Next, they are classified into the earthquakes
associated with the plate subduction earthquake ofPacific plate and Philippine sea plate and inland
crustal earthquakes. Characteristic earthquakes of thePhilippine sea plate are further classified into M8class earthquake around Sagami Trough (hereinafter
called “Sagami Trough earthquake”) and M8 class
Nankai Trough earthquakes (hereinafter called“Nankai Trough earthquake”). Characteristic
earthquakes of the crustal inland faults are classified
into major active faults and other active faults.
Subclassification of background earthquakes includes
inter-plate earthquakes, intra-plate earthquakes
around the Pacific and Philippine sea plate, andcrustal faults. However, according to the long-term
evaluation for the earthquakes around Sagami Trough[7] by HERP, the M7 class earthquakes due toPhilippine sea plate subduction (hereinafter called“Tokyo inland earthquake”) have about 70% chancefor next 30 years. It is considered to have a large
impact on the target region, so this is classified as anindependent group. Tokyo inland earthquake ismodeled as a background earthquake (area No.6/7) of
the Philippine Sea plate in the Japanese National
Seismic Hazard Map. Magnitude of these earthquakeis M6.7 or higher.
Figure 3 shows the results of hazard
deaggregation for seismic area hazard of 50 cm/sec ormore and 100cem/sec or more in area A0. The
vertical and the horizontal axis represents thecontribution of each earthquake group and the area
ratio of Area A0, respectively. Figure 3 shows
quantitatively what kind of earthquake groups havethe greatest effect on the extent of strong groundmotion. The lower part of the thick solid line indicatesthe contribution of the characteristic earthquakes andthe upper part indicates the that of the backgroundarea earthquakes. Overall, the contribution of thecharacteristic earthquakes is larger than that of the
background earthquakes, as the strong ground motion
becomes wider. Therefore, when considering
earthquake disaster prevention in a region, an
earthquake scenario which strong ground motion
occurs in a narrow area is expected to set as ahypothetical seismic source, and earthquakes
scenario that generate strong ground motion in a wide
area should be select from characteristic earthquakes.
Next, Table 3 shows the result of deaggregationof seismic area hazard of EP30:6% for the entirearea(A0) and sub-area (A1-6). The Nankai Troughearthquake (C11) with a contribution of 0.36 has thegreatest impact on the risk of strong ground motion
exceeding 100 cm/s in an area of 18% of A0 once
every 475 years. The background earthquakes

Area ratio
Area
A0
A1
A2
A3
A4
A5
A6
A0
A1
A2
A3
A4
A5
A6

EP30
1%
0.76
0.93
0.94
0.92
0.81
0.94
0.82
0.35
0.53
0.64
0.41
0.34
0.66
0.33

EP30
3%
0.65
0.83
0.90
0.80
0.62
0.88
0.68
0.25
0.36
0.54
0.23
0.23
0.52
0.20

EP30
6%
0.57
0.73
0.78
0.66
0.52
0.82
0.59
0.18
0.27
0.50
0.14
0.16
0.41
0.13

EP30
14%
0.45
0.57
0.67
0.44
0.38
0.72
0.46
0.11
0.17
0.38
0.05
0.09
0.25
0.06

EP30
26%
0.34
0.42
0.57
0.27
0.27
0.59
0.30
0.06
0.09
0.21
0.02
0.05
0.13
0.02

Table 2 shows the results of SPSHA for 50 cm/s
or more and 100 cm/s or more of PGVs for the whole
region and sub-regions in the prefecture. EP30 means
the exceedance probability in the next 30 years. The
area ratio here indicates the ratio of the area where
each ground motion occurs to the area of each region.
In addition, Fig.2 shows the seismic area hazard curve.
The larger seismic hazard curves express that theregion has a high hazard that ground motion will be
widespread. In recent big earthquakes in Japan, it is
known that a great damage occurs when PGV exceeds
100 cm/s. So, we compare the seismic area hazard
curves of PGV:100 cm/s or more. The seismic area
hazard curves show that the whole region (A0) andA4 are equivalent. A1, A2 and A4 in the west of theprefecture have a high hazard of PGV 100 cm/s ormore in a wide area compared to A0. Table 2 showsthat strong ground motion occur in the range of morethan twice when the PGV exceeds 50 cm / s,compared with the case of 100 cm / s or more. Table
2 shows that in any region, an area with a PGV of 50
cm/s or more is more than twice as large as an area of
100 cm/s or more, with the same EP30. And, in thecase of EP30:6% which is equivalent to about 1/475
for the annual occurrence frequency, the A2 area has
the highest hazard, resulting in strong motions inexcess of 100 cm/s in half of the A2 area.
On the other hand, in the case where EP30 is 1%,
A5 area has the highest hazard. Depending on EP30,
seismic area hazard has different results. These arecaused by the difference in earthquake environment
in each region.
Conduction of Hazard Deaggregation
Seismic hazard deaggreation for the results of
SPSHA in the previous section are conducted to grasp
quantitatively the contribution of each seismic source
for the seismic area hazard. When deaggregate theseismic area hazard, it is necessary to set earthquake
groups by referring to the seismic source data of270

SEE - Bangkok, Thailand, Nov.11-13, 2019

corresponding to the Tokyo inland earthquake are theintra-plate earthquake (B25) and the inter-plate
earthquake (B26). These contributions are 0.16 and
0.35, respectively. The sum of them is 0.51, which
has a greater impact on A0 than the Nankai Troughearthquake. Therefore, when selecting an earthquake
scenario for A0, it is important to select the inter-plateand intra-plate type earthquakes of the Tokyo inland
earthquake, and the Nankai Trough earthquake.
Figure.4 shows the relationship between thecontribution of seismic sources and the extent ofstrong ground motion, for each area, as in Fig.3. From
Fig.4 and Table 3, it turns out that the tendency of thecontribution is greatly different in each region. From
A1 to A5, the intra-plate earthquake (B26) of thePhilippine sea plate has a large impact, from small tolarge area ratios. Since these are classified as
background earthquakes where the epicenter cannot
be identified, the earthquake damage scenario by
virtually placing the epicenter directly under theregion should be consider in the regional earthquake
risk assessment for these areas. In A3, earthquakes
due to major active faults (C13) have a major impact.
In this area, there is the Miura Peninsula Fault Zone,
which is considered to have a high probability ofoccurrence among active faults in Japan. Since The
influence of this fault zone is significant for A3, it isimportant to understand the damage scenario causedby this fault. A4, A5 and A6 are located west of
Kanagawa Prefecture and close to the Nankai Trough,so they are greatly affected by the Nankai TroughEarthquake (C11). Especially in A6, the Nankai
Trough earthquake has a remarkable influence from asmall area to a wide area. In risk assessment, it isexpected to examine seismic hazards that consider the
spread of such various strong ground motion
distributions caused by the Nankai Troughearthquake. In any area, as the area of strong groundmotion becomes wider, the contribution of the
Sagami Trough earthquake (C10) increases. In
particular, A4 is most affected by the Sagami Troughearthquake. It is necessary to adopt it as a risk
scenario for A4 and A0.
In the report of earthquake damage assessment ofKanagawa prefecture [8], the targets of characteristic
earthquakes are follows: the Sagami TroughEarthquake, the Nankai Trough Earthquake, theMiura Peninsula Fault Zone Earthquake, and theTokai Earthquake. In addition, it is assumed that there
are M7 class earthquakes in the south of central
Tokyo and in western Kanagawa prefecture, as
earthquake scenarios of background earthquakes.
According to above mentioned study, although thetarget earthquakes selected by Kanagawa Prefecture
are appropriate, it is considered that there are notenough earthquake scenarios that occur under theseareas from the viewpoint of damage scenarios for A1
and A2. Thus, this method is effective in the review
of earthquake scenario selection in the target area.

PGV: 50cm/s or more

PGV: 100cm/s or more

Fig. 2

Seismic area hazard curves of each area

PGV:50cm/s or more

PGV:100cm/s or more
B27

B27

B26

B26
B24

B25

B25
B24
B23

B23
B22
B21

C14
C13

C14
C13

C11

C11
C10

C10

Fig.3 Results of hazard deaggregation of area A0271

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 3 Result of seismic area hazard deaggregation : PGV:100cm/s, Exceedance Probability in next 30 years (EP30): 6%
Area ratio of each area corresponding to EP30:6%
Group
CategoryClass
Earthquake group
ID
A0
A1
A2
A3
A4
A5
Sagami Trough Earthquakes
C10
0.07
0.02
0.01
0.02
0.02
0.01
Philippine
sea plate
Nankai Trough Earthquakes
C11
0.36
0.25
0.21
0.27
0.50
0.54
Pacific
Characteristic
Specified Earthquakes
C12
0.00
0.00
0.00
0.00
0.00
0.00
plate
earthquakes
CrustalMajor faults
C13
0.00
0.02
0.01
0.11
0.00
0.01
faultsCrustalOther faults
C14
0.00
0.00
0.00
0.02
0.01
0.03
faultsPacific
Inter-plate earthquakes
B21
0.01
0.09
0.13
0.05
0.02
0.02
plate
Pacific
Intra-plate earthquakes
B22
0.04
0.14
0.18
0.09
0.05
0.04
plate
Inter-plate earthquakes
B23
0.00
0.00
0.01
0.01
0.01
0.01
(Except area No.6/7)
Background
Intra-plate earthquakes
B24
0.01
0.02
0.04
0.02
0.02
0.02
earthquakes(Except area No.6/7)
Philippine
sea plateInter-plate earthquakes
B25
0.16
0.11
0.09
0.10
0.09
0.08
(Area No.6/7)
Intra-plate earthquakes
B26
0.35
0.34
0.31
0.31
0.27
0.24
(Area No.6/7)
CrustalUnknown faults
B27
0.00
0.00
0.01
0.00
0.00
0.01
faults

A1

A2
B26

A3
B26

B22

B25

B22

C13
C11

C11

A4

C14

C11

C10

C10

A5

C10

A6
B26

B26

B24 B22

B26

B25

B22
B21
B25
B25

C11

C11

C11

C10
C10

Fig. 4

0.00
0.01
0.00
0.00
0.00
0.01
0.05
0.12
0.01

[1] Okada, S., Tomatsu, M.: Regional Disaster
Prevention Planning Guide Based on Seismic
Risk Assessment for Earthquakes Occurring near
Urban Districts, Journal of Structural andConstruction Engineering (Transactions of AIJ),
No.530, 2000., pp. 37-44 (in Japanese)[2] Tomatsu, M., Okada., S.: Study on the Priority of
Measuring against Scenario Earthquakes Basedon Seismic Risk Estimation, Journal of Japan
Association for Earthquake Engineering. 2011,
Vol.11, No.2, 2011, pp. 1-19 (in Japanese)[3] Kameda, H., Ishikawa, Y., Okumura, T.,
Nakajima, M.: Probabilistic Scenario Earthquakes.
Definition and Engineering Applications,
Transactions of the Japan Society of Civil
Engineers. 1997, Vol.577 / I-41, 1997, pp. 75-87(in Japanese)[4] McGuire, R. K.: Probabilistic Seismic Hazard
Analysis and Design Earthquake. Closing theLoop, Bulletin of the Seismological Society ofAmerica, Vol.85, No.5, 1995, pp. 1275-1284.
[5] Hayashi, T., Yashiro, H.: Proposal of Spatial
Probabilistic Seismic Hazard Analysis and theApplication to the Disaster Prevention, Journal of
Structural and Construction Engineering(Transactions of AIJ), 2019. (in press) (inJapanese)[6] The Headquarters for Earthquake Research
Promotion: National Seismic Hazard Maps forJapan (2018 Edition), 2018. (in Japanese)[7] Headquartersfor
Earthquake
Research
Promotion: Long Term Evaluation for the
Earthquakes Around Sagami Trough (2nd
Edition), 2014. (in Japanese)[8] Kanagawa Prefecture: Report of Earthquake
Damage Assessment in Kanagawa Prefecture,
2015. (in Japanese)

B25

B22

0.00

REFERENCES
B26

B25

A6
0.02
0.76

C10

Results of hazard deaggregation of each area
(Case of PGV 100cm/s or more)

CONCLUSIONSIn this study, the method of seismic area hazard
deaggreation of SPSHA has proposed. In addition,
based on the application to the region of Kanagawa
Prefecture, utilization in regional disaster prevention
is discussed.
272

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

A CONCRETE WALL ELEMENT TEST TO EVALUATE COMPRESSIVE FRACTURE ENERGY
Tetsuya Ohmura1, Kyouhei Iwasaki1 and Hiroaki Matsufuji1
1
Faculty of Architecture, Tokyo City University, Japan;

ABSTRACT
Concrete walls are significantly effective seismic elements to resist lateral force due to an earthquake, because
they have much stiffness and strength. A building with a number of concrete walls would be generally designed
for just the strength. On the other hand, a building with a few of concrete walls would be designed for not only thestrength but also the ductility. In other words, the ductility of a concrete wall is the key thing considering thesurvey reports of concrete walls damaged by an earthquake. Generally speaking, the ductility of a concrete building
depends on the ductility of the concrete with rebar. According to some previous studies, the fracture energy was
focused to evaluate the ductility. However, their test specimen were cylindrical columns, not to target for a concretewall. In this paper, the ductility of a concrete wall is focused and test the specimen of a concrete wall element. The
fracture energy of a concrete wall element was examined, the thickness of a wall and the amount of their rebar
were evaluated.
Keywords: Concrete wall, Ductility, Element test, Concrete strain
Rots [1] defined the effective band width with integrated point of 4 was two times of root of the element area.
Nishiyama and Watanabe et al. [2] examined therelationship between stress and strain of the axial andtransverse for the concrete cylinder with 135mm ofdiameter in the concrete strength of 25 to 83 N/mm2.
Priestley and Park [3] suggested the model withstrain softening for a concrete cylinder and a cuboid
with enough transverse rebar under one-way cyclicloading.
Higai and Nakamura [4] suggested the compressive fracture energy was 8.8 times of concretes
strength and the compressive fracture zone length of
1,300 divided by the root of the concrete strength
based on the test data of cylinder with no transverse
rebar, concrete strength of 11 to 52 N/mm2 and thediameter of 100 to 150mm and height of 100 to
600mm.
Niwa et al. [5] suggested the equation of the fracture zone length and compressive fracture energy
based on the test data of cylinder with no transverse
rebar, concrete strength of 26 to 48N/mm2 and the diameter of 100mm, the height of 200 to 800mm.
Koshikawa et al. [6] suggested compressive zone
length and compressive fracture energy based on thetest data of cylinder with no transverse rebar, concrete
strength of 29 to 36N/mm2 and diameter of 100 to
200mm, height of 200 to 600mm.
Their specimen shape mentioned above were cylinder and cuboid for making not a wall but a column
concrete model. The fracture energy and fracturezone length of wall in former studies haven’t been referred and they are not obvious.

INTRODUCTION
Lateral strength and ductility significantly dependon the property of the concrete strain softening. It is
well-known that the stress decreasing is controlledeven in the post peak in the confined concrete withrebar. The column well-confined by rebar has great
ductility and hardly collapsed even after a maximum
considered earthquake (MCE). The strength of thegirder well-confined by rebar is not decreased as well.
Those are based on a number of technical reports, andthe amount of the rebar is estimated due to the Japanese code.
The depth of the concrete wall is much larger
than one of the concrete column. Therefore, the concrete strain at the end of the compressive area at thepeak is significantly large, and the compressive area
would be developed at the post peak.
The accurate concrete model considered thestrain softening is needed to estimate the lateralstrength and the ductility of a concrete wall, and theway to estimate the rest of the lateral and axial
strength after MCE is expected.
FE analysis is often used to simulate the lateralstrength, damage and ductility under an earthquake
loading, and to easily have the data that is hard tomeasure at the test. In addition, parametric analyses
could be performed after being verified.
Not to mention, the concrete model is consequence in a FE analysis and sufficient verificationmust be needed for the material property with compressive fracture energy
For example, Drucker Prager fracture criterionand Mohr-Coulomb fracture criterion were wellknown to estimate their maximum compressive stress.
273

SEE - Bangkok, Thailand, Nov.11-13, 2019

Moreover, the confined effect of the transverse rebar in their cylinders might be definitely different
from the one of the vertical and horizontal rebar in awall.
In this paper, several wall element tests were performed for a concrete wall. The concrete strain softening property was examined and the fracture energy
was focused for a wall element with vertical and horizontal rebar.

Specimen
Specimen are shown in Table 1. The number of allof specimen was four. The common factors are concrete material, the width and depth. The parameters
are the wall thickness and the rebar ratio (pw). The
wall thickness is 150 or 180mm. The rebar is locatedsingle or double. pw is 0.24 to 1.11 percent. The diameter of rebar is #3 to #5.
Specimen geometrics are shown in Fig. 1. The
wall consists of the confined area (Focused area), theextra area and stab. The concrete was cast from top.

TEST

Table 1 Specimen#Namet (mm)

1

150-21-024

150

2

180-21-039

f 'c(N/mm2)p w (%)

Rebar

0.24

#3(D10)@200-S

0.39#3(D10)@200-D

0.71#4(D13)@200-D

1.11#5(D16)@200-D

20.7
3

180-21-071

4

180-21-111

180

Note : S and D indicate single and double rebar respectively.

t : Thickness

a-a'

a-a'

b-b'
(a) No.1b-b'(b) No.2 to 4
Fig. 1 Specimen geometrics
Table 2 The material propertyb) Rebara) Concrete
f 'c

Young
modulas(N/mm2)

Strain at f ' c
(%)

Wall

20.7

0.1955

20.9

Stub

43.4

0.1982

29.4

Yield stressTensilestrength(kN/mm2)(N/mm2 )(N/mm2 )#3 (D10)362

0.2123170

495#4 (D13)352

0.1998176

481#5 (D16)351

0.2056171

501(kN/mm2)

274

Young
modulasYield strain
(%)

Rebar

SEE - Bangkok, Thailand, Nov.11-13, 2019

cell and the displacement gage, respectively. The
acrylic column with the strain gages was located at
the center of the specimen. The strain gages were
measured via a data logger as the same strain of theconcrete, because of the ruggedness shape of theacrylic column.

Material property
The material property of concrete and rebar isshown in Table 2. The compressive strength of thecylinder with 100mm of the diameter and 200mm ofthe height (f ’c) was 20.7 N/mm2 for the wall and
43.4N/mm2 for the stub.

TEST RESULTS

Loading

Load and displacement

Repeated compressive load was applied via therigid body of the top and bottom of the specimen by
2,000kN amsler testing machine.
Loading plan is shown in Fig. 2. The repeatedcompressive load was unloaded at the one-third andtwo-third of the f ’c on the material test. Next, it was
unloaded at every 10% decreased load after the maximum load.

The enveloped curve of the relationship between
the compressive load and the displacement are shownin Fig. 4. The compressive displacement (δ) of thespecimen was defined as the two time of the displacement at the center without the elastic displacement of
the rigid body.
The comparison of the enveloped curve between
No.1 and 2 are shown in Fig. 4(a). The displacement
at the maximum load (Pmax) of No.1 with 150mm
thickness and single rebar was larger than one of No.2
with 180mm thickness and double rebar.
For No.1, the displacement of 2.1mm was meas-

Measurement
The measurement plan is shown in Fig. 3. The
compressive load (P) and the vertical displacement at
the center of the specimen were measured by the load

σ

3000

0.9

2700

0.8
0.7
0.6
0.5
0.4

2400

2100

1800

1500

1200

𝜹
𝟐

0.3

900

0.2×

600

300

0

0

0

350

700

1050

1400

1750

2100

2450

2800

3150

Displacement

Fig. 2 Loading plan

Fig. 3 The measurement(1.0, 924) No.2 180-21-039

・・

1000

(2.1, 833) No.1 150-21-024(δ , Pmax) Specimen name500

・

Load(kN)

Load(kN)

1000(1.0, 924) No.2 180-21-039

・・・(1.7, 965) No.3 180-21-071(0.7, 844) No.4 180-21-111(δ , Pmax) Specimen name500

・

: Pmax: Pmax

0

0
0

5

10

15

0

20

5

10

Disp.(mm)Disp.(mm)Disp.(mm)(a) No.1, 2(b) No.2 to 4

Disp.(mm)Fig. 4 The enveloped curve of the relationship between the compressive load and the displacement
275

15

20

SEE - Bangkok, Thailand, Nov.11-13, 2019ured at the Pmax of 833kN and the crack width developed and the eccentricity of damage was observed at
the displacement of 10.7 and load of 286kN, and then
the test was stopped.
For No.2, the displacement of 1.0mm was measured at the Pmax of 924kN and the significant damage
was observed with 82 % of the decreased load, andthen the test was stopped. The eccentricity of damage
as well as No.1 was not observed and stable comparedwith No.1.
The enveloped curves of No2 to 4 are shown in
Fig. 4(b). Their wall thickness was 180mm with double rebar of the pw of 0.39 to 1.11%.
For No.3 and 4, the displacement of 1.7 and 0.7mm at the Pmax of 965 and 844kN were observed, respectively. The eccentricity of damage was not observed as well as No.2.
The enveloped curve of the load of the concrete
resisted (cP) and δ is shown in Fig. 5. cP was definedas the P without the load of rebar resisted (sP). And
then the relative load was defined as cP divided bycPmax .
The strain of the vertical and horizontal rebar
showed approximately yield at around cPmax in all
specimens.
The displacement at the yield was defined as theminimum displacement at the cPmax or 0.01 time of theelastic stiffness.
The same tendency was shown in Fig. 4 and 5, andthe concrete confined effect was not observed even in
the specimen with the rebar ratio of 0.71%.
Damage and Cracking
The final crack behavior was shown in Fig. 6. For
all specimen, about 0.2mm of the crack width was observed before Pmax, the crack was developed and thecrack width was increased following increase of thedisplacement.
Crack was hardly observed in the extra area andstub.
For No.1 with the wall thickness 150mm and single rebar, the crack width surrounded by dashed ellipse shown in Fig. 6(a) was significantly developed
and the eccentricity of the rebar strain and crack damage were observed, then the fragile behavior was
shown.
For No.2 to 4 with the wall thickness 180mm anddouble rebar, the difference of the crack behavior was
not observed independent of the rebar ratio.
Concrete Strain Distribution(1.0, 1.0) No.2 180-21-039(0.7, 1.0) No.4 180-21-111(2.1, 1.0) No.1 150-21-024

1.0
cP/cPmax

cP/cPmax

1.0(δy , cP/cPmax) Specimen name

0.5

: δy

(1. 0,1.0) No.2 180-21-039(1.7, 1.0) No.3 180-21-071(δy , cP/cPmax) Specimen name

0.5

: δy

0.0

0.0
0

5

10
Disp.(mm)

15

0

20

5

10

15

20

Disp. (mm)(a) No.1, 2(b) No.2 to 4

Fig. 5 The enveloped curve of the relationship between the compressive relative load and the displacement
Significant damage
C1
C2
C3
C4
C5
C6

(a) No.1(b) No.2(c) No.3

Note: C1 to C6 indicate the gauge location.
Fig. 6 The final crack behavior
276(d) No.4

SEE - Bangkok, Thailand, Nov.11-13, 2019

C1

3.2

200

𝑷𝒎𝒂𝒙
2.2

C2

C4

160

Gauge Location

C3

8.3~

5.9

C5

0.6𝑷𝒎𝒂𝒙

4.5~
~

4.5

120

8.3~

80

×𝛅𝒚

0.3𝑷𝒎𝒂𝒙
2.3~3.4

0.6Pmax
Pmax

1.9.

40 0.7𝑷𝒎𝒂𝒙

120

0
0

0.9Pmax

2.8~

0.8Pmax

2.3
.

𝑷𝒎𝒂𝒙

0.7Pmax

2.8~

1.6 1

2

Strain(%)

80

40

0.6Pmax

2.3~

2.8~

0

0
0.0

0.5

1.0
1.5
Strain (%)

0.0

2.0

0.5

(a) No.1

200×𝛅𝒚
4.7~8.8

200

3.2

4.9~
0.6𝑷𝒎𝒂𝒙
80

1.9
2.4~

120

3.2~4.9

40

1.7

3.9~
3.9

2.4

120

𝑷𝒎𝒂𝒙

160

2.5

Gauge Location

𝑷𝒎𝒂𝒙

2.0

0.4𝑷𝒎𝒂𝒙

1.9~3.9

160

1.0
1.5
Strain (%)(b) No.2×𝛅𝒚

0.3𝑷𝒎𝒂𝒙

Gauge Location

0.3Pmax

80

160

40

C6

160

120
200

Gauge Location

×𝛅𝒚

0.3𝑷𝒎𝒂𝒙

was appropriate. The amount of over 2% of the stain
was estimated as 2% over. The concrete strain at thecenter of the wall was larger than one of the top andbottom due to the concrete confined effect by rebar.
200

Gauge location

The concrete strain distribution was shown in Fig.
7. The strain gages location number of C1 to C6 wereindicated the location in Fig. 6(b). For all specimen,
it was assessed that up to 2 % of the concrete strain

6.6~
4.7

0.7𝑷𝒎𝒂𝒙

6.6~
6.6

80

8.8
40

0

0
0.0

0.5

1.0

1.5

0.0

2.0

0.5

1.0
1.5
Strain (%)

Strain (%)(c) No.3

2.0(d) No.4

Note:×→ indicates 2% or more.

No.2 180-21-039

No.3 180-21-071
No.4 180-21-111

No.2 180-21-039

t=150

Gfc (N/mm)

No.1 150-21-024

2
cσ (N/mm )2cσ (N/mm )Fig. 7 The concrete strain distribution

t=180

200
100
0
0.0

Disp.(mm)Disp.(mm)(a) No.1，2(b) No.2 to 4

Fig. 8 The envelopment curve between the stress and the displacement
277

0.4

0.8
pw (%)

1.2

Fig. 9 The relationship between Gfc,
wall thickness, and pw

SEE - Bangkok, Thailand, Nov.11-13, 2019

Compressive Fracture Zone Length

Table 3

As mention above, the eccentricity of the concrete
strain distribution was not shown along the wallheight due to concrete confined effect by the wall rebar. In addition, the all concrete strain in all specimens was the strain at the f ’c or more at the Pmax,
therefore the compressive fracture zone length in thispaper was defined as 200mm.

#

P max
(kN)

c P max(kN)δ atc P max
(mm)

δy
(mm)

(cm2 )

eb p
(mm)

No.1

833

807

2.1

1.2

389

260

No.2

924

898

1.0

433

241

No.3

965

889

1.7

429

238

No.4

844

747

361

200

Note: Pmax
c PmaxδδyA'
ebp

Compressive Fracture Energy
The envelopment curve between the concrete
stress and the displacement is shown in Fig. 8. The
concrete stress was the cP divided by the wall thickness and 250mm. The compressive fracture energy(Gfc) [6] was estimated as the area.
The relationship between Gfc, wall thickness, andpw is shown in Fig. 9.
The displacement for Gfc (δconf) was calculated as
the displacement of the focused area i.e. confined area
as below.
ℎ𝑐𝑜𝑛𝑓
𝛿𝑐𝑜𝑛𝑓 =
∙𝛿ℎWhere h is the wall height 200mm, hconf is focusedarea i.e. confined area 200mm.
For the specimen with the wall thickness of
180mm and double rebar in No.2 to 4, Gfc was increased following increasing of the pw and the confined effect.
However, for the specimen with the pw of 0.71%
more in No.4, Gfc was slightly increased, because theconcrete strain was gradually increased.
For the specimen with the wall thickness of
150mm and single rebar in No.1, the Gfc of No.1 waslargest. It should be examined in our future study.

The test result

:
:
:
:
:
:

0.7

0.6

A'

Maximum load
Maximum load of concrete
Displacement
Displacement at Minimum (Pmax or 0.01·K0)
c Pmax divided by f 'c
A' divided by thickness

thickness 180mm and double rebar, the difference ofthe crack behavior was not observed independent of
the rebar ratio.
2) The concrete strain at the center of the wall waslarger than one of the top and bottom due to the concrete confined effect by rebar.
3) For all test specimens the compressive fracturezone length was defined as 200mm.
4) For the specimen with the pw of 0.71% more in
No.4, Gfc was slightly increased, because the concrete
strain was gradually increased.
5) ebp was decreased following increasing of pw.
REFERENCES[1] ROTS, J. G. : Computational Modeling of Concrete Fracture, PhD thesis, Delft University ofTechnology, 1988.
[2] Naoki Takamori, Benny Benni Assa, Minehiro
Nishiyama, Fumio Watanabe : Confined Stressconcrete - Strain Relationship formulation Fundamental Study, Proceedings of the Japan Concrete
Institute, Vol.18, No.3, pp.395-400, 1996.
[3] J. B. Mander, M. J. N. Priestley, R. Park, Fellow,
ASCE : Theoretical Stress-strain Model for Confined Concrete, J. Struct. Eng, Vol.114, Issue.8, pp
1804-1826, Sep.1998.
[4] Hikaru Nakamura, Takeshi Higai : Compressive
Fracture Energy and Fracture Zone Length of Concrete, JCI-C51E Seminor on Post-Peak Behaviorof RC Structures Subjected to Seismic Loads,
Vol.2, pp.259-272, 1999.10.
[5] Ken Watanabe, Junichiro Niwa, Hiroshi Yokota,
Mitsuyasu Iwanami : Formulation of Stress-strain
Relationship of Concrete Considering The Localized Compressive Failure Zone, Journal of JSCE,
Vol.58, No.725, pp 197-211, 2003.2.
[6] Shinya Muramatsu, Koshikawa Takeaki, Takanori Saito, Takuya Hasegawa : Quantitative Evaluation of Strain Softening Characteristics of Concrete Subjected to Uniaxial Compression, Architectural Institute of Japan Hokkaido Branch research report, No.83, pp.81-84,2010

Equivalent Compressive Fracture Zone Width
The test result is shown in Table 3. The equivalent
compressive fracture zone width (ebp) was defined as
Pmax divided by the wall thickness and f ’c.
cP was decreased following increasing of pw, because the sP was increased.
In other word, ebp was decreased following increasing of pw.
CONCLUSION
Basic concrete walls with rebar test was performed applying compressive stress to estimate theircompressive fracture energy for a concrete wall element model with rebar.
We reached several conclusions as below.
1) For the specimen with the wall thickness of
150mm and single rebar, the eccentricity of the rebar
strain and crack damage were observed, then the fragile behavior was shown. For specimen with the wall278

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE EFFECTS OF BATANG KANDIS RIVER FLOOD CONTROL IN
PADANG CITY-PALAPA METROPOLITAN AREA
Benny Hidayat, #Bambang Istijono, Irwan Irwan, Taufika Ophiyandri and Akhmad Junaidi
Civil Engineering Department, Universitas Andalas, Padang, Indonesia

ABSTRACT
Floods often occur in Lubuk Buaya residential housing in Padang city, which has a population of 6,500 citizens
per km2. These natural phenomena happen due to sea level water rises and the change in the new river mouth of
the Batang Kandis river. The construction of a 500 m floodway and a 700 m dike of Batang Kandis river were
proposed to control flooding. The floodway was then damaged during the earthquake on September 30th, 2009,
and wiped out by a flood on March 24th, 2016. Theoretically, to solve flood conditions downstream of Batang
Kandis river with 70 km² of watershed area, the floodway is expected to be able to discharge 307 m3/s. This study
uses a numerical simulation using HEC-RAS software with three scenarios. The first scenario uses the existing
condition of the river width of 50 m and a depth of 1 m, it experienced an inundated area of 0.60 km2 for 5 hours.
The second scenario is done by increasing 2.50 m embankment height, which gave the result of 2x700 m2 floodinundation in several locations. The third scenario also carried out dredging of the river up to the elevation of 0.00
m above sea level, and there was no flood inundation. Thus, the third scenario is the best result that has been
carried out to control the floods downstream of Batang Kandis river.
Keywords: inundation area, floodway, river mouth, simulations.

rainfall and rising sea levels cause natural flood
events at the confluence of the Batang Kandis riverand the Batang Kasang river. The possibility offlooding, together with the construction of the Batang
Kandis River floodway, can increase the risk of tidal
flooding in the lowlands around the new inlet in
Pinang Bungkuk with a distance of about 500 m
upstream of the new inlet of the Batang Kandis river.
The flood control effort that has been carried out
is the construction of a 500 m sea floodway andembankment at approximately 700 m to the left of the
Batang Kandis river flow. The floodway condition
was severely damaged by the 7.9 Richter scale
earthquake on September 30th, 2009, and flooding on
March 24th, 2016. To overcome the flooding that
occurred in the lower reaches of the Batang Kandis
river with a 70 km² river basin area, rehabilitation is
being conducted on the floodways with numericalsimulations using HEC-RAS software so that later it
is expected that the river can discharge as much as
307 m3/s.
The catchment area of Batang Kandis is located in
the Koto Tangah sub-district of Padang city. The
upstream part of the Batang Kandis river originatesfrom the western part of Bukit Barisan (elevation+1.249 m) and has a catchment area of 56 km². The
old Batang Kandis river flows westward through new
residential areas and then joins the Batang Kasang
river which has a catchment area of 14 km² in the areaof Pasir Jambak village. The figure below shows thelocation of the latest Batang Kandis river estuary andthe location of the research area.

INTRODUCTION
Structural flood control has long been carried out
in the city of Padang in the Padang Metropolitan
Urban Area, Lubuk Alung and Pariaman (abbreviatedas Palapa Metropolitan Area). This activity began in
the Dutch era, which was marked by the constructionof the Banda Bakali river. This activity was carriedout to divert a portion of the flow from the Batang
Arau river which passed the Padang City trade centerat that time.
Given the frequent occurrence of floods in the cityof Padang, a more comprehensive study was
conducted for flood prevention in 1983. This study
was conducted by JICA (Japan International
Cooperation Agency) under the name of the Padang
Area Flood Control Project. This activity aims to
conduct in-depth studies on flood control, drainage
plans, and feasibility studies to identify and prioritize
actions to be immediately implemented. The resultsof this study are the basis for flood control projects inthe city of Padang [1].
Some of the activities that have been carried out
for flood control in the city of Padang include thenormalization of Canal Floods (Banda Bakali river)and the Batang Arau River in 1992-1997;
normalization of the Batang Kuranji river, the Air
Dingin river (widening, deepening and strengtheningof concrete cliffs) and repairing the Padang coast in
1997-2001 [2] [3].
Pinang Bungkuk area in Lubuk Buaya Village,
Padang City with a population density of 6,500
people per km2 is an area that is often flooded. High279

SEE - Bangkok, Thailand, Nov.11-13, 2019

Batang Kandis river. Sediment transport simulationon the Batang Anai river with the application of
Alternative 3 shows the most significant trend oferosion and deposition in a location next to the
National Bridge downstream.
The narrowing of the river channel accompanied
by siltation and sediment accumulation causes thevolume of the plan to be incompatible with thecoming discharge, as a result when the rainy season
comes there is some run off and flooding can nolonger be overcome.
Simulations with HEC-RAS are also used toreview the flow of the Cilember river in West Java,also in Segamat town, Malaysia and on the Batang
Takung Sijunjung river, West Sumatra [5] - [7].
Based on the simulation results using HEC-RAS
software in the Cilember river in West Java, theoverflow of Cilember River clearly influences theinundation height on Jalan General H. Amir
Machmud which connects the city of Bandung andthe city of Cimahi.

Fig. 1 Location of Batang Kandis River.

Hydraulics Analysis
The approach performed by HEC-RAS is todivide the cross-sectional area based on the value ofn (Manning roughness coefficient) as the basis forcross-section distribution. Each flow that occurs is
calculated using the Manning equation.

Fig. 2 Area of study in Batang Kandis river.
LITERATURE REVIEW

1Corry Eriza [4] examined the alternative
performance of the flood control of the Batang Anairiver and Batang Kandis river in West Sumatra. The
study aims to review various alternatives in planningthe control of the floods of the Batang Anai river andBatang Kandis river over the current condition of thewatershed. His research uses the HEC-RAS(Hydrological Engineering Center, River Analysis
System) with three alternatives which were based ondata availability. Alternative 1 requires the repair ofgrooves and widening of the face (withembankments) in both rivers and the addition offloodways on the Batang Kandis river. Alternative 2
is similar to Alternative 1, except for the removal ofdikes on the Batang Anai river and additional sluices
on the Batang Kandis river. Alternative 3 for the
Batang Anai river is similar to Alternative 2, and theappearance along the Batang Kandis river is widened.
The analysis includes calculation of the flow
adequacy in flowing the design and analysis of
sediment transport for the best performancealternatives. From the three alternatives, the bestalternative was found as alternative 3 because it wasable to drain the design discharge Q50 (1471 m3/s) on
the Batang Anai river and Q25 (293 m3/s) on the

Q = A x (𝑛. R2/3. S1/2) (1)Where :
Q: discharge (m3/s)
n: manning roughness coefficient
A: cross-section area (m2)
R: hydraulic radius (m)S: energy slack.
For steady flow in the HEC-RAS device, energy
equations are used except in places where the depthof flow exceeds the critical depth [8]. The energy
equation between two cross sections is as follows:
𝒀𝟐 + 𝒁 𝟐 +

𝜶𝟐 𝒗𝟐
𝟐
𝟐𝒈

= 𝒀𝟏 + 𝒁 𝟏 +

𝜶𝟏 𝒗𝟐
𝟏
𝟐𝒈

+ 𝒉𝒆 (𝟐)Where :
Y1, Y2: flow depth (m)Z1, Z2: channel base elevation (m)V1, V2: average speed (m/s)
1, 2 : speed coefficient
g: gravity acceleration (m/s2)
he: lost energy (m)Modeling with HEC-RAS
Analysis of the existing cross section using HEC-

280

SEE - Bangkok, Thailand, Nov.11-13, 2019

Scenario 1: existing conditions
The simulation results of scenario 1 are forconditions that do not experience flooding startingfrom the downstream, namely BKS 0 to BKS 4A
along 315 m (from the new estuary of the Batang
Kandis river to the meeting with the Batang Kasang
river) and BKS 4 to BKS 10 along 562 m (theexistence of flood dam buildings built in the 2007 and2008 fiscal years), while the other parts are generally
affected by the flood inundation of the Batang Kandis
and Batang Kasang rivers [9]. The following are
examples of the existing conditions of the flow that
did not occur with flooding.

Elevation (m)RAS aims to determine the condition of the actual
river (existing) and water level profile during a flood.
HEC-RAS software is integrated with graphical userinterfaces, hydraulic analysis, management and data
storage, graphics, and reporting.
a. Graphical User Interface is the link between
users and HEC-RAS. Things that can be doneusing this feature include file management,
inputting and editing data, doing hydraulicanalysis, displaying input data and analysis
results in the form of tables and graphs,
preparing reports and accessing online help.
b. Hydraulics analysis. The hydraulic analysis
provided includes two analyses, namely, steadyflow, and unsteady flow.
c. Data storage and data management. Storage of
input data in HEC-RAS can be grouped into
projects, plans, geometry, steady flow, unsteadyflow, and sediment data.
d. Graphs and reporting. The graphics facilities
provided by HEC-RAS include X-Y river flow
graphs, cross-views, curves rating, hydrographs,
and other graphs which are X-Y plots of various
hydraulic variables.

Station (m)Fig. 3 BKS 0 (no flooding occurs)

RESEARCH METHODOLOGYThis study is conducted in the following stages:
Collected data on bathymetry maps anddischarge data for the Batang Kandis riverobtained from the Sumatra V River Basin
Office [8].
b. Calculated speed using the Manning formulac. Calculated debit using the Rational formulad. Conducted simulation in HEC-RAS by plotting
previously calculated data and inputting
existing river flow and geometry data.
e. Compared the results of the calculation of thebathymetry measurement data so that theinundation height is obtained based on themeasurement data and the results of running theapplication.
f. Identified flood control efforts towards the
opening of a new estuary on the Batang Kandis
river.

Elevation (m)a.

Station (m)Fig. 4 BKS 1 (no flooding occurs)

Elevation (m)The following is an example of the existing
conditions of the flow that occurred in flood runoff.

RESULTS AND DISCUSSION
In this research, we developed three scenarios offlood simulation as described below. We set up
benchmark stations along the rivers, abbreviated as
BKS for Batang Kandis river and BKSG for Batang
Kasang river.

Station (m)Fig. 5 BKS 16 (in the left part of the flow there is aflood)

281

Elevation (m)Elevation (m)SEE - Bangkok, Thailand, Nov.11-13, 2019

Station (m)Station (m)Fig. 6 BKS 17 (on the left side of the flow there is aflood)

Fig. 8 BKS 10 (no flooding occurs)
The following is an example of the existing
conditions of the flow that occurred in flood runoff.

Scenario 2: given the left and right embankmentsof the flow without any river dredging or flowing

Elevation (m)Scenario 2 is simulated by installing
embankments on flood banks. At the flood point,
embankments were made both on the banks of theriver's left-hand flood, the riverbanks of the righthand floods and the two floodplains by the conditionsof the flooding. From the simulation results of
scenario 2 it can be seen that from BKS station 0 to
BKS 13 along 1,227 m Batang Kandis river and
BKSG 1 to BKSG 6 along 491 m Batang Kasang river
there is no flood inundation; while at BKS station 14
to 17 BKS along 250 m of the Batang Kandis river isstill flooded, this is caused by the inadequate crosssection of the river to pass the flood discharge of the
Batang Kandis river. The following is an example ofthe existing conditions of the flow that did not occur
with flooding.

Station (m)Elevation (m)Elevation (m)Fig. 9 BKS 15 (flood inundation in the upstream part)

Station (m)Fig. 10 BKS 16 (flood inundation in the upstream
part)
StationStation(m) (m)Scenario 3: given the left and right embankmentsof the flow with the dredging and widening of theriver
In scenario 3 it is simulated by combining the
installation of the left and right embankments withriver dredging and widening. The embankment height
was taken at an elevation of 2.50 m above sea level ashigh as the peak height of the Jetty building at the new
estuary of the Batang Kandis river and the peak of theFig. 7 BKS 6 (no flooding occurs)

282

SEE - Bangkok, Thailand, Nov.11-13, 2019

Elevation (m)existing embankment on the left flow between BKS 3
to BKS 10 along 676 m. The width and depth ofdredging are adjusted to the existing conditions byreferring to 0.00 m above sea level. From thesimulation results in scenario 3, it can be seen thatfrom the BKS 0 to BKS 17 stations along the 1,583 m
Batang Kandis river and BKSG 1 to BKSG 6 along
the 810 m Batang Kasang river there is no visible
flood inundation. Therefore, to identify flood
handling in the lower reaches of the Batang Kandis
river, there is no need to do another scenario
simulation.

Station (m)Elevation (m)Elevation (m)Fig. 14 BKSG 5 (no flooding occurs)

Station (m)Station (m)Fig. 11 BKS 9 (no flooding occurs)

Station (m)Fig. 15 BKSG 6 (no flooding occurs)

Elevation (m)CONCLUSIONS AND RECOMMENDATIONS
Conclusion
1. The first scenario with the existing conditions
shows that the existing cross-section of the riversegment is not flooded as it is in the downstream
part of the river, namely: BKS 0 to BKS 4 A (fromthe new estuary the Batang Kandis river to themeeting with the Batang Kasang river), and in
BKS 4 to BKS 10 left flow (the presence of floodembankments built in the 2007 and 2008 fiscal
years by the Sumatra V River Basin Office, while
the other parts in general are affected by the floodinundation of the Batang Kandis river and the
Batang Kasang river.
2. From the simulation results in scenario 2 it can beseen that from BKS station 0 to BKS 13 and
BKSG 1 to BKSG 6 there is no flood inundationon the Batang Kandis river, while at the BKS
station 14 to BKS 17 there is still a floodinundation on the river of Batang Kandis. Thiscondition is caused by the inadequate crosssection of the river to pass the flood discharge of
the Batang Kandis river in the condition of Q10(Rational Method).

Station (m)Elevation (m)Fig. 12 BKS 10 (no flooding occurs)

Station (m)Fig. 13 BKSG 4 (no flooding occurs)

283

SEE - Bangkok, Thailand, Nov.11-13, 2019

Control Construction (Case Study: Controller ofBanjir Batang Anai, West Sumatra) (in Bahasa),
Teknika, Vol.21(2), pp.1-7.
[4] Coorri E. 2008. Alternative Performance of
Batang Anai and Batang Kandis Flood Control inWest Sumatra (in Bahasa: Unjuk Kerja Alternatif
Pengendalian Banjir Batang Anai dan Batang
KandisSumatera Barat.) Tesis, Program
Studi MPBA Sekolah Pasca Sarjana, Universitas
Gadjah Mada, Yogyakarta.
[5] Karnisah I, Yackob A, Bambang SB, Fitra RA
and Reynaldy PH. 2019. Analysis of Drainage
Capacity to Resolve Inundation Problem on Jend.
H. Amir Machmud Street, Cimahi City West Java
Province. International Journal of GEOMATE,
Vol. 16, Issue 57. Geotec., Const. Mat. & Env.,
DOI: https://doi.Org /10.21660/Year.Issue. Paper
ID ISSN: 2186-2982 (Print), 2186-2990 (Online),
Japan.
[6] Romali NS, Yusop Z and Ismail AZ. 2018.
Application of HEC-RAS and Arc GIS for
Floodplain Mapping in Segamat Town, Malaysia.
International Journal of GEOMATE, Vol. 15,
Issue 47. Geotec., Const. Mat. & Env., DOI:
https://doi.org/ 10.21660/Year.Issue. Paper ID
ISSN: 2186-2982 (Print), 2186-2990 (Online),
Japan.
[7] Komalasari N. 2017. Flood Control Simulation of
the Batang Sumani River using the HEC-RAS
model (in Bahasa: Simulasi Pengendalian Banjir
Sungai Batang Sumani dengan menggunakan
HEC-RAS model). Proceeding of Andalas Civil
Engineering Conference, Andalas University.
[8] Istiarto. 2014. 1-Dimensional Flow Simulation
with the help of the HEC-RAS Hydrodynamics
Program package. Training Module, basic level,
Simple Geometry River (in Bahasa: Simulasi
Aliran 1-Dimensi dengan bantuan paket Program
Hidrodinamika HEC- RAS. Modul Pelatihan,
jenjang dasar, Simple Geometry River), page 123. https://www. academia .edu/8781887/HECRAS.Dasar Simple Geometry River, Juli 2014
(accessed at 29 August 2014).
[9] Sumatra V River Basin Office. 2001. AnaiKandis River Improvement, Design Note and
Design Report in Padang area flood control
project (II) West Sumatra (in Bahasa: Proyek
Pengendalian Banjir dan Pengamanan Pantai
Provinsi Sumatera Barat).

3. From the simulation results in scenario 3, it can beseen that from the BKS station 0 to BKS 17 in the
Batang Kandis river and BKSG 1 to BKSG 6 theBatang Kasang river has not seen any inundation.
Therefore, to overcome the inundation that occurs
at the meeting between the Batang Kandis riverand the Batang Kasang river, it is necessary tohandle flooding in the lower reaches of the Batang
Kandis river by simulating scenario 3.
Based on the simulated scenario at this conclusion,
it is stated that scenario 3 is the best result of three
scenarios that have been carried out to overcome
flooding in the Batang Kandis river due to the
opening of the new estuary of the Batang Kandis river.
Suggestion
1. To overcome flooding in the Batang Kandis riverand the Batang Kasang river, serious attention
needs to be paid from the Sumatera V River Basin
Office.
2. For more optimal and proper handling of themeeting between the Batang Kandis river and the
Batang Kasang river, further research is needed on
the effect of sea tides on agricultural land.
ACKNOWLEDGMENTS
This research was funded by University ofAndalasunder
Research
Grant
Number:T/24/UN.16.17/PP.IS-KRP1GB/ LPPM/2019 dated
13 May 2019.

REFERENCES[1] JICA.1983. Study Report on Padang Area FloodControl Project. Japan International Cooperation
Agency (JICA)[2] Istijono B, Aprisal, Ophiyandri T and
Nurhamidah. 2019. A Study of The Quality of
Soil Infiltration at The Downstream of Kuranji
River, Padang City. International Journal of
GEOMATE, Month April, Year 2019 Vol. 16,
Issue 56. Geotec., Const. Mat. & Env., DOI: https://doi.org/10.21660/2019.56. Paper ID ISSN:
2186-2982 (Print), 2186-2990 (Online), Japan.
[3] Istijono B. 2014. Environmentally Friendly Flood284

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

FATIGUE STRENGTH OF HEADED STUDS WELDED WITH
IMPROVED FERRULE IN CONCRETE UNDER UNIDIRECTIONALCYCLIC LOADING

1

Hiroshi Higashiyama1, Kenji Yoshida2, Satoshi Banba3 and Shigeyuki Matsui4
Faculty of Science and Engineering, Kindai University, Japan; 2Kawada Industries, Inc., Japan;
3
Nippon Stud Welding Co., Ltd., Japan; 4Osaka Institute of Technology, Japan

ABSTRACTIn hybrid and composite structures using steel and concrete materials, shear connectors such as headed studs
are generally employed. The authors aim to improve the welding ferrule configuration to increase the fatigue
strength of headed studs. The measuring results for 20 specimens of headed studs welded with conventional andimproved ferrules reveal that the improved headed stud increased the diameter at the weld root and the height of
the weld collar up to the tip of the separated portion between the stud shank and the weld collar in comparison
with the conventional headed stud. In this study, the fatigue tests were carried out under unidirectional cyclicloading on single headed studs with a diameter of 16 mm and a height of 60 mm in concrete to determine thefatigue strength. From the fatigue test results, S-N curves were obtained for the headed studs. The improved
headed stud has higher fatigue strength than the conventional headed stud. Furthermore, in concrete with normal
strength, a fatigue crack initiated from the tip of the separated portion between the stud shank and the weld collar
due to the notch effect and progressed into the stud shank. In concrete with higher strength, a fatigue crack
initiated from the weld toe and progressed into the steel base plate along the heat affected zone.
Keywords: Headed studs, improved welding ferrule, fatigue strength, unidirectional cyclic loading

more than that of the conventional headed studs.
The mechanical behavior and the fatigue strengthof headed studs are generally examined using
standard push-out test specimens. Each standard
push-out specimen consists of an H-shape steel
beam welded with two or four headed studs on eachside of the beam flange and concrete slabs. In theexperiments using such specimens, the mechanicalbehavior and the fatigue strength are affected by thegroup effect of headed studs. This study aims tocompare the fatigue strength of single improved andconventional headed studs in concrete underunidirectional cyclic loading and to evaluate thefatigue strength of the improved headed studs inconcrete with different concrete strength levels. In
the cyclic loading tests, a single headed stud weldedon a steel base plate was used without the groupeffect as Ref. [4]. In this study, the test equipment
was setup to apply shear force to be transferred at
the interface between a steel plate and concrete
without bending moment. The fatigue strength ofindividual headed studs can then be simply
evaluated and compared.
In this study, the fatigue tests carried out on the
improved and the conventional headed studs inconcrete/mortar under unidirectional cyclic loading
to compare the fatigue strength. The shear stressranges were varied to obtain S-N curves for theheaded studs. The concrete/mortar specimens used
had two different strengths to compare the fatigue

INTRODUCTION
In hybrid and composite structures using steel
and concrete materials, shear connectors such asheaded studs are generally employed. Many
researchers have investigated the mechanicalbehavior and/or the fatigue strength of headed studs[1]-[9]. Hiragi and Matsui [10] have attempted to
improve the shape of welding ferrules to increase thefatigue strength of headed studs. For a conventional
welding ferrule, high-temperature gas during
welding spouts out of the castellation placed at thebottom of the welding ferrule, causing welding burrs
to remain radially at the welding toe. They improved
the welding ferrule configuration by closing thecastellation at the bottom of the welding ferrule toallow high-temperature gas to spout out upward. The
weld toe had a smooth shape without welding burrs.
The authors have investigated to improve thewelding ferrule configuration further to increase thefatigue strength of headed studs. The fatigue
strength of headed studs using improved welding
ferrules (improved headed studs) has been verified
in comparison with conventional headed studs undera rotating shear force to employ the headed studs insteel-concrete composite bridge decks [11-13]. In
these research works, depending on the concrete
strength and the shear stress range applied, thefatigue life of the improved headed studs under therotating shear force increased to about three times
285

SEE - Bangkok, Thailand, Nov.11-13, 2019

strength of each headed stud and to observe thefailure condition. Also, the S-N curves depending on
the concrete strength were determined for the
improved headed studs at three different concrete
strengths.
EXPERIMENTAL PROGRAM(a) Conventional headed stud.

Specimens and materials
Specimens used in the fatigue tests consist of asteel base plate of 170 × 270 mm with a thickness of
22 mm, a single headed stud, and a square shapesteel pipe of 100 × 100 mm with a height of 100 mm
and a thickness of 3.2 mm as shown in Fig. 1. The
square shape steel pipe, which was simply placed on
the steel base plate without any mechanical restraint
during the fatigue tests (round bars shown in Fig. 1
were to keep the position of the square shape steel
pipe and were removed before testing), functions as
a mold for concrete/mortar in casting and as theprotection for cracking and/or crushing of
concrete/mortar at the loading point. The concrete or
non-shrinkage mortar was cast in the square shapesteel pipe. Each headed stud had a height of 60 mm
and a diameter of 16 mm. The conventional and theimproved ferrules and their appearance after welding
are shown in Fig. 2. The closing castellation at thebottom of the improved ferrule allows hightemperature gas to spout upward. As can be seenfrom Fig. 2(b), the weld toe of the improved headed
stud was smooth. The proper welding condition was
selected in each headed stud. From the size
measurement of 20 weld collars for the conventional
and the improved headed studs, as given in Table 1,
the average diameter (D) was larger and the averageseparated height between the stud shank and theweld collar (H1–H2) was shorter for the improved
headed stud than for the conventional headed stud.
These headed studs both had the weld collar withalmost the same height.
The headed stud used in this study was made of(b) Improved headed stud.
Fig. 2 Ferrules and weld collars.
Table 1 Weld collar dimensions
Measuringpart
D (mm)
H1 (mm)
H2 (mm)H1–H2 (mm)Conventionalheaded stud
22.6
5.5
2.1
3.4

Improved
headed stud
24.2
5.6
3.7
1.9

H2

H1

D

mild steel with yield strength and ultimate strengthof 364 N/mm2 and 477 N/mm2. The compressive
tests for the concrete/mortar were carried out todetermine the compressive strength. Threecylindrical concrete specimens of 100 mm indiameter and 200 mm in height and three cylindricalmortar specimens of 50 mm in diameter and 100 mm
in height were tested. The compressive strength at
the beginning of each fatigue test, the shear stressranges, and the number of specimens are
summarized in Table 2. Herein, one mortar
specimen with a compressive strength of 57.1
N/mm2 was used for each shear stress range as thepilot test.
Test method

Fig. 1 General view of specimen before concrete
casting.

The test setup in the fatigue tests and details of286

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Summary of shear stress ranges
Headed stud

Conventional

Improved

Shearstressrange(N/mm2)
150
120
100
80
140
130
120
150
120
100
80
120
100
90
150
140
120

Number of
specimens

Compressive
strength(N/mm2)

3
3
3
3
1
1
1
3
3
3
3
3
3
3
1
1
1

23.8

the test equipment are shown in Fig. 3. Eachspecimen was fixed to a frame plate with four bolts.
A shear force was vertically applied to the specimen
through a loading plate with a thickness of 36 mm.
Then, the loading position was 18 mm apart fromthe surface of the steel base plate of the specimen as
close as possible to the root of the headed stud. A
fixed steel plate was welded to the test equipment
because the shear force transferred at the interface
between the steel base plate and the concrete/mortar
was applied without bending moment when theheaded stud deformed due to a fatigue crack.
Moreover, a flat roller was installed between theloading plate and the fixed steel plate to keep theloading position constant and to prevent thefrictional resistance between those. In this study, thecyclic load was applied to the specimen by a 200 kN
hydraulic actuator. The minimum loading level was
kept at 5 kN and the maximum loading level was
varied according to the shear stress ranges given in
Table 2. As the loading condition, a sine wave witha load frequency of 3 or 5 Hz was applied in the load
control.

57.1

23.8

31.8

57.1

Flat roller

RESULTS AND DISCUSSION

Frame plate
Fixed plate

Failure modes

Base plate

Fig. 4 shows failure conditions after the fatigue
tests. In this study, two failure modes were observed
as with the previous study on the fatigue tests under
the rotating shear force [13]. In the specimens withlow and middle compressive strengths of 23.8 and31.8 N/mm2, as shown in Fig. 4(a), a fatigue crack(Type S in Fig. 5) initiated at the tip of the separated
portion between the stud shank and the weld collar
due to the notch effect and progressed into the studshank. In this failure mode, the concrete around theweld collar was crushed during the fatigue tests.
This phenomenon also depends on the applied
loading level. The crushing of the concrete leads tochanges in the stress distribution along the headed
stud. This stress redistribution was analyticallyobserved by Xu and Sugiura [14] in their push-out
specimens.
On the other hand, in the specimens with ahigher compressive strength of 57.1 N/mm2, asshown in Fig. 4(b), a fatigue crack (Type P in Fig. 5)
initiated at the weld toe and progressed into the steel
base plate along the heat affected zone. This type of
failure mode was also observed in the previous study[13]. Then, the mortar did not crush around the weld
collar because the mortar had the higher strength.
The concrete/mortar with higher strength andwithout crushing tends to have more stressconcentration at the weld toe than in the separated
portion between the stud shank and the weld collar.

Specimen(a) Test setup.
Loading plate
Flat roller
Fixed plate
plate
Frame plate

Spring catch
plate
SpringBolts keeping
springs

Bolts
Lifting prevention
plate stud
HeadedSquare shape steel pipe(b) Details of test equipment.
Fig. 3 Test setup and details of test equipment.
287

SEE - Bangkok, Thailand, Nov.11-13, 2019

2.3
180

Shear stress range (N/mm2)

160
2.2

(a) Failure mode of Type S.

140

2.1

120

57.1 N/mm2

2
100
80
1.9

1.8

23.8 N/mm2

60

1.7
1.6
103
1000

Conventional headed stud
Improved headed stud
4

10
10000

5

10
100000
Number of cycles

6

10
1000000

7

10
10000000

Fig. 6 S-N curves for headed studs.
In the failure mode of Type S, the height up to
the tip (H2 shown in Table 1) of the separated
portion between the stud shank and the weld collar ishigher in the improved headed stud than in theconventional headed stud. This means that the lengthfrom the loading point to the tip of the separated
portion is shortened and the maximum principal
stress is decreased. Consequently, the fatigue life of
the improved headed stud increased. In contrast, inthe failure mode of Type P, the diameter (D shownin Table 1) of the weld collar is larger in the
improved headed stud than in the conventionalheaded stud. This means that the fatigue crack
progresses in a larger path than in the conventionalheaded stud. Consequently, the improved headed
stud has a longer fatigue life.

(b) Failure mode of Type P.
Fig. 4 Failure conditions.

Crack initiation point(Type S)

Crack initiation point(Type P)

S-N curve and compressive strength

Fig. 5 Macro view of weld collar.

The fatigue test data of the improved headed studwere obtained at three different compressive
strengths of concrete/mortar. The results are plottedin Fig. 7. When the improved headed studs having
the compressive strengths of 23.8 and 31.8 N/mm2
are compared, the S-N curves crossed in the higher
shear stress range. This phenomenon may beconsidered because in the higher shear stress range,
the concrete around the weld collar was crushed at a
certain stage during the fatigue test, and a fatigue
crack initiated at the tip of the separated portion
between the stud shank and the weld collar andprogressed into the stud shank as discussed above.
Then, the two headed studs showed a similar fatigue
life because each headed stud has the stud shank of
the same diameter. In contrast, in the lower shear
stress range, the headed stud with the higher
compressive strength of concrete showed a longer
fatigue life. This caused a difference in time taken
before the concrete was crushed. Mia andBhowmick [15] analytically showed that an increasein concrete strength leads to an increase in thefatigue strength of headed studs as in this study.

Comparison of fatigue strength
The relationships between the shear stress range
and the number of cycles, namely S–N curves areshown in Fig. 6 to compare the fatigue life between
the conventional and the improved headed studs
with the compressive strength of 23.8 and 57.1
N/mm2. The improved headed stud is about 1.4
times higher at the compressive strength of 23.8
N/mm2 and is about 2.7 times higher at thecompressive strength of 57.1 N/mm2 than theconventional headed stud. The S–N curves can be
expressed using the following equations.
For the improved headed stud,
logN = –4.504log()+14.29 (at 23.8 N/mm2) (1)logN = –11.92log()+31.40 (at 57.1 N/mm2) (2)For the conventional headed stud,
logN = –4.376log()+13.89 (at 23.8 N/mm2) (3)logN = –14.65log()+36.84 (at 57.1 N/mm2) (4)288SEE - Bangkok, Thailand, Nov.11-13, 2019

logN = –7.619log()+20.89

2.3

Shear stress range (N/mm2)

180
160
2.2

From Eqs. (1)-(2) and (5), as shown in thefollowing Eq. (6), the slope, a, and the intercept, b,with respect to the compressive strength of
concrete/mortar, are shown in Fig. 8 and arepresented in the following formulas.

140

2.1

120

57.1 N/mm2

2
100
80
1.9

(5)

31.8 N/mm2
23.8 N/mm2

1.8

60

1.7

1.6
103
1000

4

5

10
10000

6

10
100000
Number of cycles

10
1000000

7

10
10000000

14y = -0.0066x2 + 0.7557x - 9.7491
R² = 1

10

a

8
6

4
2
0
0

10

20

30

40

50

60

(6)

a = –0.0066fc’2+0.7557fc’ –9.7491(7)

b = –0.0123fc’2+1.5083fc’ –14.643(8)Although further data collection is needed, theslope and the intercept of the S–N curve for each
improved headed stud are best fit to the compressive
strength of concrete/mortar by each secondaryfunction approximation. At higher compressive
strength, the slope and the intercept have a tendency
to approach certain values, respectively. Namely, ata higher compressive strength level, the fatigue
strength of the improved headed stud is close to acertain value caused by the failure mode without
concrete crushing in which a fatigue crack initiates
at the weld toe and progresses into the steel baseplate along the heat affected zone. At a lower
compressive strength, the fatigue strength issignificantly affected by the compressive strength of
concrete/mortar.

Fig. 7 S-N curves for improved headed stud.

12

logN = –alog()+b

70

Compressive strength (N/mm2)

CONCLUSIONS(a) Relationship between the slope and thecompressive strength of concrete/mortar.
35

The fatigue tests were carried out for single
headed studs in concrete/mortar in this study. The
fatigue strength of the improved headed stud wascompared with that of the conentional headed studand the S-N curve of the improved headed studdepending on the compressive strength of
concrete/mortar was proposed. The follwing
conclusions were drawn from this study.
(1) From the fatigue tests, two failure modes ofheaded studs were observed. In one failure mode,a fatigue crack initiated at the tip of the separated
portion between the stud shank and the weld
collar and progressed into the sutd shank. In theother failure mode, a fatigue crack initiated at theweld toe and progressed into the steel base plate
along the heat affected zone.
(2) The fatigue strength of the improved headed stud
was higher than that of the conventional headed
stud in concrete/mortar with each compressive
strength. The elongation of the fatigue life
depends on the compressive strength, the shear
stress range, and the failure mode.
(3) The slope and the intercept of S-N curve for the
improved headed stud have a secondary function
with respect to the compressive strength of
concrete/mortar. At higher compressive strength,y = -0.0123x2 + 1.5083x - 14.643
R² = 1

30

25

b

20
15

10
5
0
0

10

20

30

40

50

60

70

Compressive strength (N/mm2)(b) Relationship between the intercept and thecompressive strength of concrete/mortar.
Fig. 8 The slope and the intercept of the S-N curvefor the improved headed stud.
The S-N curve for the improved headed studwith the compressive strength of 31.8 N/mm2 is asfollow.
289

SEE - Bangkok, Thailand, Nov.11-13, 2019the slope and the intercept tend to approachcertain values. At a higher compressive strength
level, the fatigue strength of the improved
headed stud is close to a certain value in the
failure mode without concrete crushing aroundthe weld collar in which the fatigue crack
initiates at the weld toe and progresses into thesteel base plate along the heat affected zone.

[8] Hanswille G., Porshc M. and Ustundag C.,
Resistance of Headed Studs Subjected to Fatigue
Loading Part II: Analytical Study, Journal ofConstructional Steel Research, Vol. 63, No. 4,
2007, pp. 485-493.
[9] Matsui S., Hiragi K. and Fukumoto Y.,
Derivation of Strength of Headed Stud Shear
Connectors – Fatigue Strength –, Journal of
Structural Engineering, JSCE, Vol. 35A, 1989,
pp. 1233-1244 (in Japanese).
[10] Hiragi K. and Matsui S., Investigation on
Remarkable Improvement of Fatigue Strengthfor Headed Studs, Proceedings of Developments
in Short and Medium Span Bridge Engineering,Calgary, 1998, pp. 1681-1693.
[11] Yoshida K. Inamoto K. Matsui S., Higashiyama
H. and Kaido H., Development of Headed Stud
with High Fatigue Strength for Steel-concrete
Composite Deck, Journal of StructuralEngineering, JSCE, Vol. 58A, 2012, pp. 908-919(in Japanese).
[12] Yoshida K., Higashiyama H., Inamoto K.,
Matsui S. and Kaido H., S-N curve for Durable
Headed Stud under Rotating Shear Force,
Journal of the Society of Materials Science,
Japan, Vol. 62, No. 10, 2013, pp. 621-626 (inJapanese).
[13] Higashiyama H., Yoshida K., Inamoto K.,
Matsui S. and Kaido H., Fatigue of Headed Studs
Welded with Improved Ferrules under Rotating
Shear Force, Journal of Constructional Steel
Research, Vol. 92, 2014, pp. 211-218.
[14] Xu C. and Sugiura K., FEM Analysis on Failure
Development of Group Studs Shear Connector
under Effects of Concrete Strength and Stud
Dimension, Engineering Fail Analysis, Vol. 35,
2013, pp. 343-354.
[15] Mia M.M. and Bhowmick A.K., A Finite
Element Based Approach for Fatigue Life
Prediction of Headed Shear Studs, Structures,Vol. 19, 2019, pp. 161-172.

REFERENCES[1] Thürlimann B., Fatigue and Static of Stud Shear
Connectors, ACI Journal, Vol. 30, No. 12, 1953,
pp. 1278-12301.
[2] Mainstone R.J. and Menzies J.B., Shear
Connectors in Steel-concrete Composite Beams
for Bridges; Part 1, Static and Fatigue Tests on
Push-out Specimens, Concrete, Vol. 1, No. 9,
1967, pp. 291-302.
[3] Ollgaard J.G., Slutter R.G. and Fisher J.W.,
Shear Strength of Stud Shear Connectors inLightweight and Normal Concrete, AISCEngineering Journal, Vol. 8, No. 2, 1971, pp. 5564.
[4] Naithani K.C., Gupta V.K. and Gadh A.D.,
Behavior of Shear Connectors under Dynamic
Loads, Materials and Structures, Vol. 21, 1988,
pp. 353-363.
[5] Gattesco N. and Giuriani E., Experimental Studyon Stud Shear Connectors Subjected to Cyclic
Loading, Journal of Constructional Steel
Research, Vol. 38, No. 1, 1996, pp. 1-21.
[6] Johnson R.P., Resistance of Stud Shear
Connectors to Fatigue, Journal of Constructional
Steel Research, Vol. 56, No. 2, 2000, pp. 101–
116.
[7] Hanswille G., Porshc M. and Ustundag C.,
Resistance of Headed Studs Subjected to Fatigue
Loading Part I: Experimental Study, Journal ofConstructional Steel Research, Vol. 63, No. 4,
2007, pp. 475-484.

290

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DESIGN AND ANALYSIS OF FORMULA SPACE FRAME CHASSISWITH SIDE IMPACT
Boonthum Wongchai
Faculty of Engineering at Sriracha, Kasetsart University, Thailand
ABSTRACTSpace frame chassis is one of the popular types of formula car chassis. There are many subjects to design andanalyze formula car chassis. Side impact is the main subject for design and analysis with accurate and safety for
driver. In this article, the 2017-2018 formula SAE (the Society of Automotive Engineers) rules is used for analysis.
The CAD models of formula car chassis are constructed using SolidWorks 2016. Finite element method (FEM) is
used to analyze the CAD models using SolidWorks Simulation. The results show that all formula car chassis
models satisfy the 2017-2018 formula SAE rules. The maximum stress and the maximum deflection are notsignificant affected by varying the distance of the front member joint. While varying the distance of the side impact
member joint affects both of the maximum stress and the maximum deflection. The relationship of the distance ofthe side impact member joint and the maximum stress is increasing linear function. While the relationship of the
distance of the side impact member joint and the maximum deflection is the upside down parabolic function. Using
the goals of the formula car chassis design are low maximum stress and low maximum deflection, the distancefrom the side impact members joint and the front roll hoop should be as low as possible.
Keywords: Formula, Space Frame Chassis, Side Impact, FEM Design and Analysis

frequency when the engine frequency equals thenatural frequency.
The mass-spring-damper with the road shapes areused in the vibration analysis of the formula car. The
quarter-car model is performed for determination thevibration of the tire deflection, the suspension
deflection and the car acceleration [12].
The front impact and the side impact are theimpact analysis in FEM. Impact analysis can be
simplified to static analysis using the relation of theforce due to the formula car chassis in a short time
and the changing of the formula car momentum [13]INTRODUCTION
Nowadays the Formula Society of Automotive
Engineers (Formula SAE) main activity is a studentlevel design competition of formula car which is the
beginning event of the Formula One car racing; themost popular car racing event in the world. There aremany issues to design formula car such as chassis,
suspension, break system, power train, aerodynamics,
impact attenuator, materials, engine and electronicsystem [1]-[6].
Formula car chassis is one of the most importantpart of the formula car. There are many types of theformula car chassis. Space frame chassis, ladderframe chassis and composite monocoque are thepopular types of the formula car chassis [6]-[9]. The
space frame chassis is constructed from the circularor square tube by welding. The ladder frame chassis
has a shapes of the ladder style. Meanwhile, thecomposite monocoque is made from composite
material.
For the car design, torsional rigidity, modal
analysis, vibration analysis, front impact and side
impact are the main analysis. Finite element method(FEM) are usually used for these analysis [10]-[11].
Torsional rigidity or torsional stiffness can be
determined using FEM. The formula car chassis isfixed at one end and the torque is applied at the otherend. The torsional deflection and the torque areapplied to determine the torsional stiffness [8].
Modal analysis is conducted to determine themode shapes and the natural frequencies of theformula car chassis for avoiding the resonant
frequency [7]. High vibration occurs at resonant

F t  m(v2  v1 ),(1)

where F is the impact force, t is the time durationof the impact force due to the formula car chassis, m
is the total formula mass (with the driver), v1 is the
car velocity before crashing, and v2 is the car velocity
after crashing ( v2  0 ).

Fig. 1

291

Formula SAE space frame chassis [1].

SEE - Bangkok, Thailand, Nov.11-13, 2019

The stress and the deflection of the formula car
chassis must not over the allowable limit of thechassis materials. Figure 1 shows the Formula SAE
space frame chassis. For side impact, the 2017-2018
formula SAE rules define that Fy = 7.0 kN applied at
all structural locations between front roll hoop andmain roll hoop of the formula car [1]. For boundary
conditions, the bottom nodes of both side of the front
and main roll hoops are fixed. Failure must not occur
at anywhere and the maximum allowable deflectionof 25 mm
In this study, the space frame chassis isperformed. The shapes of all member locations
between front bulkhead and main roll hoop will be
investigated with the best condition of stress anddeflection of the formula car.

Nine members of side impact members between
front roll hoop and main roll hoop are changed byvarying the distance of c as show in Table 2.
Table 1 Design of members between front bulk head
and front roll hoop.
Front members Fa
F1
F2
F3
F4
F5
Note: a+b = 700 mm.

a(a+b)/62(a+b)/63(a+b)/64(a+b)/65(a+b)/6

Table 2 Design of members between front roll hoop
and main roll hoop.

CHASSIS DESIGN
Figure 2(a) and Figure 2(b) show the 3d view andthe side view of the formula car chassis used in thisstudy respectively.

Side impact members Sc
S1
S2
S3
S4
S5
S6
S7
S8
S9
S10
S11
Note: c+d = 654 mm.

c(c+d)/122(c+d)/123(c+d)/124(c+d)/125(c+d)/126(c+d)/127(c+d)/128(c+d)/129(c+d)/1210(c+d)/1211(c+d)/12

MATERIAL SELECTION(a)
All members of the formula car chassis are madeof carbon steel pipe with the outer diameter of 25.4mm and the thickness of 2.5 mm. The mechanicalproperties of the carbon steel are shown in Table 3.
Table 3 Material properties of carbon steel pipe
Property
Elastic modulus
Poisson’s ratio
Shear modulus
Tensile strength
Yield strength(b)Fig. 2

Value
205
0.29
80
365
305

Units
MPa
GPa
MPa
MPa

FINITE ELEMENT METHOD(a) 3d view (b) side view.

In this study, the side impact members are thedominant factor for side impact. The side impact
force acts directly on the side impact members asshown in Fig. 3. While the front members are notacted directly by the side impact force. The CAD

Six of front members between front bulk head andfront roll hoop are changed by varying the distance ofa as show in Table 1.
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SEE - Bangkok, Thailand, Nov.11-13, 2019models of the formula car chassis are modeled using
SolidWorks 2016. For finite element method,
SolidWorks Simulation is applied to analyze thestress and the deflection of the formula car chassis insome cases of the front member; F1, F3, and F5
combining with all cases of the side impact members
in Table 2; S1 to S12 with the abbreviation FaSc. For
example, the F1Sc is the combination of the front
member F1 and all cases of the side impact members
Sc. The FaS5 is the combination between the front
members F1, F3, and F5 and the side impact member
S5. Moreover, the F5S1 is the combination of F5 andS1.
For load and boundary conditions, this study uses
the 2017-2018 Formula SAE Rules [1]. For side
impact, the force of 7 kN is applied at all members
between front roll hoop and main roll hoop with thedirection toward the driver. The bottom nodes of bothside of the front roll hoop and the main roll hoop are
fixed displacement (x, y, z) but not rotation as shownin Fig. 3.
The CAD models are meshed with beam element.
The upper bound axial and bending stress ( ) is used
to compare the yield strength ( y ).

u  ux2  u y2  uz2 ,where u is the beam deflection, ux, uz and uy are thebeam deflection in x, y and z directions, respectively.
The beam deflection is used to compare the allowabledeflection of 25 mm.

Failure not occur anywhere in structure for   y . The upper bound axial and bending stressFig. 3

Load and boundary condition.

Fig. 4

Combine loading in beam element.

can be computed fromP ( M y I z  M z I yz ) z  ( M z I y  M y I zy ) y,AI y I z  I yz2(2)

where P is the axial force, A is the beam cross section
area, My and Mz are the moment in the direction y andz, respectively, I is the moment inertia of area of thebeam cross section and the subscript indicates its
rotation direction as shown in Fig 4.
The beam deflection can be computed from

Fig. 5(3)

The upper bound axial and bending stress
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SEE - Bangkok, Thailand, Nov.11-13, 2019

RESULT AND DISCUSSION
Figure 5 shows the upper bound axial and bending
stress in the formula car chassis in case F3S5.
For all cases of FaSc (a = 1, 3, and 5 as shown in
Table 1 and c = 1, 2, …, 11 as shown in Table 2,
respectively), the results of the maximum stress  max
can be plotted with c as shown in Fig. 6 to Fig. 8.
From Fig. 6 to Fig. 8, the results show that therelationships of the maximum stress and the distancec are increasing linear equation with R2 more than 0.9
except the case of F5Sc has R2 of 0.8363. The
maximum stress will be increased by varying the
distance c. The lowest maximum stress occur at cases
FaS3 (c = 3(654)/12 = 163.5 mm). For comparing
with yield strength ( y  305 MPa), failure not

Fig. 7

Maximum stress in case F3Sc (a = 3(700)/6
mm).

Fig. 8Maximum stress in case F5Sc (a = 5(700)/6mm).

occurs anywhere in structure for all cases.

Fig. 6

Maximum stress in case F1Sc (a = 700/6
mm).

Fig. 9Deflection of the formula car chassis.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Figure 9 shows the deflection of the formula car
chassis of case F3S5. The maximum deflection andthe distance c can be plotted with the upside down
parabolic equation with R2 more than 0.87 as shownin Fig. 10 to Fig. 12.
The maximum values of the maximum deflection
occur in cases FaS5 (c = 5(654)/12 = 272.5 mm). The
minimum values of the maximum deflection occur incases FaS11 except case F5Sc occurs in case F5S10.
All cases do not exceed the allowable deflection of 25mm.

Fig. 12 Maximum deflection in case F5Sc (a =5(700/6) mm).
From the maximum stress graph and the
maximum deflection graph, using the goal of theformula car chassis design with low stress and low
deflection, the distance c should be as low value as
possible. For this study, case F5S1 with lowest valueof c is the best choice.
By varying the distance a, the results show thatthe distance a is not the main factor that affect the
maximum stress and the maximum deflection.
CONCLUSIONSThis paper presents the formula space frame
chassis design and analysis subjected on side impact.
By varying the distance c of the side impact members
joint, the results show that the relationships between
the maximum stress and the distance c are increasing
linear equation for all cases. The maximum stress canbe increased by increasing the distance c. The
relationships between the maximum deflection andthe distance are the upside down parabolic equation.
The distance of the front member joint a
insignificantly affects the maximum stress and the
maximum deflection.
The distance c should be as low as possible byusing the goal of the formula car chassis design withlow stress and low deflection. Case F5S1 is the best
design for this study.

Fig. 10 Maximum deflection in case F1Sc (a =700/6 mm).

REFERENCES[1] 2017-2018 Formula SAE Rules. https://www.
fsaeonline.com/content/2017-18%20FSAE%20
Rules%209.2.16a.pdf, Access on 10, December
2018.
[2] Chepkasov S., Markin G. and Akulova A.,
Suspension Kinematics Study of the "Formula
SAE" Sports Car, Procedia Engineering, Vol. 150,
2016, pp. 1280-1286.
[3] Mariani F., Poggiani C., Risi F. and Scappaticci
L., Formula-SAE Racing Car: Experimental andNumerical
AnalysisoftheExternal
Aerodynamics. Energy Procedia, Vol. 81, 2015,
pp. 1013-1329.
[4] Hetawal S., Gophane M., Ajay B.K and
Mukkamala Y., Aerodynamic Study of Formula
SAE Car. Procedia Engineering, Vol. 97, 2014, pp.
1198-1207.
[5] Savage G., Formula 1 Composites Engineering.
Engineering Failure Analysis, Vol. 17, 2010, pp.
92-115.
[6] Guimaraes A.V., Brasileiro P.C., Giovanni G.C.,
Costa L.R.O. and Araujo L.S., Failure analysis ofa half-shaft of a formula SAE racing car. Case
Studies in Engineering Failure Analysis, Vol. 7,
2016, pp. 17-23.

Fig. 11 Maximum deflection in case F3Sc (a =3(700/6) mm).

295

SEE - Bangkok, Thailand, Nov.11-13, 2019[7] Anas M.N., Nandu N.C., Anjai K., Arjun R.N. andPramod S., Design, Analysis, Fabrication andTesting of a Formula Car Chassis. Materials
Today, Vol. 5, 2018, pp. 24944-24953.
[8] Limwathanagura
T.,
Sithananun
C.,
Limchamroon T. and Singhanart T., The Frame
Analysis and Testing for Student Formula,International Journal of Mechanical andMechatronics Engineering, Vol. 6, 2012, pp. 9981002.
[9] Mat M.H. and Ghani A.R.Ab., Design andAnalysis of ‘Eco’ Car Chassis. Procedia
Engineering, Vol. 41, 2012. pp. 1756-1760.
[10] Chandan S.N., Sandeep G.M. and Vinayaka N.,
Design, Analysis and Optimization of Race Car
Chassis for its Structural Performance ,International Journal of Engineering Research &Technology , Vol. 5, 2016, pp. 361-367.
[11] Patil R.V., Lande P.R., Reddy Y.P. andSahasrabudhe A.V., Optimization of Three
Wheeler Chassis by Linear Static Analysis,
Materials Today, Vol. 4, 2017, pp. 8806-8815.
[12] Saurabh S.Y., Kumar S., Jain K.K., Behera S.K.,
Gandhi D., Raghavendra S. and Kalita K. Designof Suspension System for Formula Student Race
Car, Procedia Engineering, Vol. 144, 2016, pp.
1138-1149.
[13] Sood A. and Singh P., Analysis of Space Frameof formula SAE at High Speed with Ergonomic
and Vibrational Factors. International Journal of
Mechanical Engineering and Technology, Vol. 6,
2015, pp. 202-212.

296

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

PUBLIC TRANSPORT INITIATIVES IN WEST AFRICA, A CASESTUDY OF ABIDJAN
Leonard Johnstone1 and Vatanavongs Ratanavaraha2
Institute of Engineering, Suranaree University of Technology, Thailand

1,2

ABSTRACT
Abidjan is the principal city of the West African Republic of Côte d’Ivoire. It is the gateway city to West
Africa. In 2014, the population of the city was estimated at four million people. Over the next fifteen years, this is
projected to rise to nearly seven and a half million people. This continuing growth has an associated projected
strong economic growth. This paper addresses the challenges associated with the provision of equitable public
transport services to address the needs of the growing population. Public transport currently in Abidjan is complex
consisting of both formal transport in the form of public bus services and several forms of informal public transport.
In order to understand the existing travel trends and especially the declining public transport proportion in Abidjan,a series of surveys were undertaken for the development of an analytical methodology. This included amongst
others an interview survey of people at the household level and public transport opinion surveys. The methodology
thus developed allowed an understanding of the impact of new proposed infrastructure. The introduction of new
infrastructure in the form of a higher level of public transport and an enhanced regulatory format will enable theimplementation of an environmentally friendly public transport with a growing market share.
Keywords: Public Transport, Côte d’Ivoire, Mode Split, Environment
Equity means that a certain minimum level ofmobility should be assured and provided for all
members of society. Not only automobiles but also
all modes of transport should have a right to share thepublic space and move around the city freely andsafely.

INTRODUCTION
Abidjan is a city of lagoons and parks, a colorfulcity of blue and green as represented in Fig. 1. The
Abidjan vision and long-term city development are
based around three main goals of transportation
system enhancement namely:• Efficiency;• Equity, and• Better Environment .
An efficient transportation system should be
developed to strengthen urban functions, to enhancepeople’s quality of life, to facilitate economic
activities, and to sustain stable economic growth in
Abidjan. It is of great significance to achieve
efficiency by decreasing negative externalities suchas economic loss of travel time caused by increasing
traffic. The efficiency in transportation is achievable
by balancing the growing travel demand within thecity and the transportation infrastructure supply.
An enhanced transport system with a diversion
from the private to the pubic leads to a better green
environment in a similar structure as with thediversion of cargo to green cargo transport[1].
There are three ways to balance the demand andthe supply: 1) by increasing and recovering theinfrastructure capacity to meet the demand; 2) by
optimizing utilization of the existing transport
infrastructure through efficient transportation control
measures; and 3) by decreasing excessive vehiculartraffic demand through transportation demand
management and diverting private vehicle users topublic transport.

Fig. 1

The city of lagoons.

On the other hand, some low-income people
cannot afford to pay for expensive transportation cost.
Some socially vulnerable people including the aged
and the handicapped have difficulties in theirmobility. Affordable and sufficient level oftransportation services should be provided for those
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SEE - Bangkok, Thailand, Nov.11-13, 2019

people especially by the improvement of the public
transport system.
The vision for Greater Abidjan is about,“providing quality living environments,” air pollution
and noises caused by automobiles should be
minimized by promoting public transport use andcontrolling the traffic demand. At the same time, air
pollution and noises should be reduced by applying
stricter vehicle emission standards to reduce air
pollutant emissions and this is enshrined in the Parisclimate accords[2].
The city of Abidjan is divided into administrative
regions or communes. These communes serve in
addition as boundaries for physical transportation. In
some incidences, there is modal restriction between
communes. Some modes of the informaltransportation system are not allowed to enter certain
communes or there is restricted travel between
communes.

operate anywhere with the exception of the central
business area, the commune of the Plateau.
The Woro-woro or intra-communal taxis are
required to perform local services of proximity
existed for several years. They have developed
significantly in recent years due to some of theircompetitiveness compared to other modes, andsecondly thanks to the shortage in supply of Buses
available to the public transport company.
Whilst there are some arguments for thedesirability [4] of the informal sector, it does not meet
the aspiration associated with the overall
improvement of public transport in the city.

THE CURRENT SITUATION

Fig. 2 Informal transport modes.

During the year, 2013, there was an update of the
Abidjan transport master plan [3]. Significant surveys
were undertaken during this revision including
detailed public transport and home interview surveys.
The home interview survey sample size was a little
over two percent of all households in Abidjan. Some
20,000 households were included in the survey.
One key result from the survey was theconfirmation of the importance of both the walk modeand the informal transport sector in the city namely inthe form of the Woro-woro and Gbaka as reported inTable 1. The private or car mode is still relatively low
but significant growth has been seen in this mode.
As these informal public transport modes arelikely unfamiliar, photos of the vehicles associatedwith these informal modes are provided in Fig 2. The
commonly used Gbakas service is provided byminibus vehicles with a capacity of between 14 and
32 seats, and are subject to transport authorization
issued by the government for a particular line ofoperation.

Historical Activity Levels
These informal modes of transport have risen inpercentage terms in recent time by providing adesired service to the public. The public bus service
company locally referred to as SOTRA(Société destransports Abidjanais) has seen its ridership fall froma peak of 700,000 passengers per day to 400,000, a
decline of forty percent as depicted in Fig 3.

Table 1 City wide modal distribution of traffic
Fig. 3 Public bus patronage
Mode
Walk
Car
Taxi with meter
Woro-woro
Gbaka
Bus
Oher

Percentage
53
5
2
20
11
6
3

In 1998[5], the modal share of non- walk trips for
SOTRA bus was twenty-four percent with Gbaka
accounting for a further twenty-five percent whilst
seventeen percent of trips were made by Woro-woro.
By 2013, the modal proportion of bus and Woro-woro
was reversed as reported in Table 2. Woro-woro thenaccounted for thirty- two percent of mechanizedperson trips with public bus accounting for a reduced
mode split of only twelve percent.
The earlier studies on urban transport conducted
revealed a total of 2.2 million person trips per day for

During the review of the transport master plan
study[3], it was estimated that there were 2,900
Gbakas operational during a single day. They may
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SEE - Bangkok, Thailand, Nov.11-13, 2019

the inhabitants of Abidjan who at the time were morethan 8 years old in the inner communes. Public transit
at that time consisted of a healthy share of around fifty
percent consisting of both the bus and Gbaka.
The mode split within other selected major
African cities is reported in Fig 4. Although theinformal modal share of mechanized trips is high inother African cities [6], only Abidjan with aninformal modal share of nearly fifty percent is second
only to Dar Es Salam.

The thalwegs create natural boundaries to quartiers
and are most of the time uninhabited as people are
reluctant to live in those areas that are used as illegal
landfill and can be flooded instantly during raining
days. Planners have used this free space to designroads inside those thalwegs as the land was available.
The Urban structure today
In administration terms, Abidjan, as previously
mentioned is divided into communes. The key innercommunes are depicted in Fig. 5 which also
highlights the proposed transit infrastructure. The
Plateau commune functions as the central area of thecity with the communes of Adjame and Abobo to thenorth. Whilst in the west of the city there are thecommunes of Attecoube and Yopougon. In the east,
there are the communes of Cocody and Bingerville.
In the south, north of the southern waterway are
the communes of Treichville, Marcory, andKoumassi. Then there are the communes of Port
Bouet and Grand Bassam. The later two communes
border the Atlantic Ocean.
The road network has been mainly developed
without any consideration of Public Transport.
Although public transport has been declining inrecent years as discussed earlier, the proposals of the
updated master plan 2030 have as one of its main
objective a restoration the credibility of public
transport lost during the previous ten years.
In order to integrate public transport inside theroad network, and in particular a mass-transit system,
the first step is to secure sufficient space for both road
users and public transport facilities along the targetedroads.

Table 2 Historical mode split of motorized travel
Mode
Private(Car and Motorcycle)
SOTRA
Gbaka
Woro-Woro
Meter Taxi
Employee Bus
Total

Percentage
1998
2013
14.0

11.7

24.0
25.0
17.0
16.0
4.0
100.0

11.7
25.1
31.7
17.5
2.3
100.0

It must be admitted that the physical city
landscape is not so attractive to the provision of long
bus routes and could be considered more conduciveto the informal sector with an emphasis on shorter
trips.

Fig. 4

Fig. 5

Public transport city modal share

Proposed future transit

Around Abidjan, fast urban development can beseen, in particular between Cocody and Bingervillewhere large residential areas have been built at a very
fast pace. To meet the growing demands in habitation,
large residential areas are under development. The

The landscape of Abidjan District is punctuatedby many valleys called thalwegs, surrounded by very
steep slopes that are not even conducive to a goodroad system.
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SEE - Bangkok, Thailand, Nov.11-13, 2019transport master plan and thus the road master plan
must take into account all this latest urban
development to ensure consistency between land use
and infrastructure development.
As the main roads have a high capacity, many
private vehicles take the primary urban roads.
Moreover, since the primary urban roads connect the
major industrial areas in Abidjan such as Yopougon,
Treichville, and Koumassi, via the primary urban
roads to Abidjan Port and other major cities in Coted’Ivoire, these roads also serve as a freighttransportation corridor. Based on the result of thetraffic count surveys undertaken during the masterplan review, compositions of trucks to all traffic are
documented, and the major truck routes have been
identified as part of this analysis. The access from thenorthwest and the west can be regarded as the heavy
vehicle corridors. These corridors then serve the dual
puropses of regional connectivity for cargo plus local
city traffic.
Some key issues are:circumferential routes and suburban feeder bus
services. Alternatively, one may consider three levelsof public transport namely a primary, secondary andtertiary level. With both the circulator and feeder
services set into the later category.
The circumferential routes would provide
linkages between major activity hubs without theneed for coming into the center to access an adjacenthub. The viability of a bus route re- structure needs
consideration in light of existing and future travel
demand. Thus a methodology or a tool is needed tounderstand the impact of future demand in relation to
the proposed future land use planning in order toensure the maintenance of the earlier specified
transport goals.
The analysis needs to define a role for all the citytransport modes. Most line haul routes can become
the prerogative of the formal public transport
structure. The role of the informal sector such as
Gbaka, Intra Communal Taxi or Woro-woro thenfocuses on Circulator and Feeder routes and possibly
the need or otherwise for circumferential routes.
Whilst it is common to have a circular route in thecentral area, in Abidjan consideration should be given
as well for the need for such routes within theindividual communes.

 Congestion points around the central area or
Plateau; Absence of any high capacity public transport
such as a metro system (previously recommended
but never constructed) or Bus Rapid Transit;

METHODOLOGY Limited access routes to the Plateau which islikely to grow in importance;

A classic four step transport model is developed
as the analytical tool for the understanding of the
movement of the people throughout the city as
depicted in Fig. 6.

 Residents in new developments areas in Abobo
and Yopougon(both expected to attract anadditional one million people over the next two
decades) must access the Pateau in a north-south
movement. There is no direct east-west link from
central Yopougon to the Plateau; andGeneration

 Dependence on the private car and informal
public transport.
The key planning issues for public transport is thatthe public transport service is currently provided
largely by the informal sector. Bus services areconcentrated on routes originating from suburban
areas and ending in several city terminals such as
Adjame or the Plateau terminal. The informal sector
accounting for eighty-five percent of public transport
trips is provided across the following modes namely:

Distribution

Mode
Choice Gbaka; Intra Communal Taxis or Woro-woro;
Network
Assignment

 Inter Communal Taxis;
 Fixed Route taxis; and Meter Taxis.
Fig. 6

Bus routes are often categorized into four types
from a planning point of view, namely, line-haul bus
services on high capacity corridors, circulator bus
services within major centers such as the central area,

The city model structure.

The first step is to address the starting and ending
point of each person trip. The number of trips
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SEE - Bangkok, Thailand, Nov.11-13, 2019

generated in each small area or traffic zones is linked
to socio-economic characteristics. In this analysis, thecity of Abidjan was divided into 168 traffic zones.
The second step is the distribution of trips
throughout the city. This distribution is linked to theimpedance of travel between any two traffic zones.
whilst the third step, the focus of this project, is theassignment of the person trip to the various walk,
private or public transport mode. The public transportmode is then split into the formal and informal sector.
This modal choice considers the cost of travel
between any two traffic zones.
The network assignment combines all movement
across all transport network infrastructure and thus
provides an understanding of the movement of people
including the priority and type of infrastructure
proposals[7]. The focus of this research paper is on
the movement of people and the probability of modal
shift.

structure with four levels of mode split analysis
including the walk mode is depicted in Fig 7. Eachmodel level has its own logit mode split curve.
The first curve separates the mechanized trips
from the walk trips whilst at the next level, there is achoice between the public and private modes
including special school buses. On the private side,
there is a distinction between the private car andmotorcycle.
On the public side, there is a distinction between
the non-fixed route and fixed route transit modes
whilst the final level of fixed route transit includes
modal allocation within the phase of the public transit
assignment.

Data Preparation
The base input data are a collation of databases
available from the detailed survey program
undertaken during the Abidjan master plan withparticular reference to the aforementioned extensive
home interview survey. In the model development, amaster transport network is first prepared that
includes all known and proposed transport projects
with particular reference to public transport
proposals.

Fig. 7 Mode split structure.
The Equations
The modal shift equation takes the followingform:

The Key Inputs – the Drivers of Future Demand
The key planning inputs are the distribution bysmall area or traffic zone of population, household,employment, student enrolments, and householdincome. The population of Abidjan is predicted to
grow from 5.8 million in 2015 to 8.8 million in 2030
whilst the city economic growth is forecast to
increase by seven percent per annum over the sametime period.
The emphasis here is on the effort to achievemodal shift from the private sector to the public sector
via infrastructure improvement or at the very least to
reduce the trend away from the public sector. The
model structure under discussion is the mode split
segment of the overall Abidjan transport model.
Other methods of modal shift for Abidjan other than
improvement in the city modal structure may include
the introduction of area pricing [8]. Other suchalternatives are possible for evaluation within thetransport model structure.

1/(1+exp(-λ(𝐶𝑖𝑗2 +δ-𝐶𝑖𝑗1 )))(1)Equation (1) defines the probability of using mode
1 as opposed to mode 2 whereas λ is the scaleparameter and δ is the bias as defined in Table 3; 𝐶𝑖𝑗1 is
the generalized cost of travel for hierarchical mode
choice 1 between any two traffic analysis zones i andj; and 𝐶𝑖𝑗2 is the generalized cost of travel for
hierarchical mode choice 2 between any two traffic
analysis zones i and j.
The generalized cost is a function of travel cost
and travel time. For public transport, the cost is thetotal fare including any access fare to the maintransport mode. Travel time is the total time from thestart of the trip to the end of the trip.
The mode split parameters for only the work trips
representing twenty percent of all trips in Abidjan are
depicted in Table 3. All four logit curves, A throughto D are described for the four levels of economic
activity level in Abidjan. In the model development,
both trip generation and trip distribution were also
prepared for three additional trip purposes namely
school, shopping, and non-home trips. Each curve as

Model Structure
The nested logit model[9] is often used in modecity analysis for both city wide transport and even in
the case of long distance transport[10]. The model301

SEE - Bangkok, Thailand, Nov.11-13, 2019referenced in Table 4 is prepared four levels of
economic activity. The levels of economic activity
are directly related to the different levels of householdincome.
The measure of goodness of fit, in this case, is in
the form of the R2 value which is considered within
acceptable ranges for this form of model calibration.

THE ANALYSISThe focus of this research is on the modal shift orin overall terms the maintenance of the modal balanceby the reversal of the decline in public transport share.
However, prior to the modal allocation step, there is
as previously discussed the trip generation anddistribution of the movement of people. Person
movements are estimated by traffic zone via a
relationship linking population and economic
activity.
The cost and time of travel are the key inputs into
the mode split model, Eq. (1). The travel time
includes all portions of the public transport travel thus
incorporating travel by the main mode in addition toaccess, waiting time, transfer time and any modal
boarding penalties.
The movement pattern that meets the objective ofimprovement in transport within Abidjan is theincorporation of corridor movements and a local
ladder pattern providing residential access from themain corridor movements. This combination forms an
integrated pattern as depicted in Fig 8. is then the
input for analysis within the structure of the transportmodel.

Table 3 Mode split parameters for work trips
Economic
ActivityClass

Curve A
(Mode 1=walk)Curve B
(Mode 2=private)

Class 3

λ
0.46
0.35
0.44

δ
3.9
4.4
2.7

𝐑𝟐
0.60
0.60
0.60

λ
0.01
0.01
0.01

δ
-32.6
-15.7
72.6

𝐑𝟐
0.62
0.63
0.60

Class 4

0.22

1.9

0.63

0.01

-49.0

0.64

Class 1
Class 2Curve C

Curve D

(Mode 3=car)(Mode 4=non fixed)

Class 1
Class 2

.005

-478

0.63

-234

0.59

.019

200

0.85

-48

0.58

Class 3

.005

152

0.61

184

0.58

Class 4

-.01

183

0.57

-252

0.99

5*
𝟏𝟎−𝟑

The Crossing Corridor

Model Calibration

Ladder Pattern

Before a model is usable, it must reproduce theexisting situation. If it can reproduce the existing
situation within reasonable limitations, it is thus
deemed a calibrated model.
In the case of the Abidjan modal split model, as
seen in Table 4, there is a close estimation of both themode split at the macro level for public transport and
The Crossing Corridor
Present Bus Network
the three individual sub- modal levels. The maximum
difference even at the sub-modal level is only seven
The Crossing Corridor
Ladder Pattern
Future Abidjan
percent.
Table 4 Calibration Comparison
Percentage
Difference
Walk
0.3
Private-4.8
6.3
All Public
The Crossing Corridor
4.8
Bus
2.2
Gbaka
7.2
Woro-Woro
Mode

Present Bus Network

Integrated Future

Fig. 8 Future public transport integration.
The decline in public transport is halted in the
future as reported in Table 5 resulting from an
integrated approach to public transport. In terms ofphysical infrastructure, this is achieved in the
additional investment in public transport of the EastWest transit corridor linking the communes of
Yopougon and the Plateau and the North-South
corridor linking the communes of Abobo and PortIn addition, in the calibration phase, it is common
to compare traffic movement across a screenline.
Four such screenlines were defined within the city.
All four scrrenlines reflected a good match between
observed and estimated traffic. The comparison waswithin ten percent.
302

Fu

I

SEE - Bangkok, Thailand, Nov.11-13, 2019

Bouet as depicted in the earlier Fig. 5.

insurance of the safely and maintenance of public
transport in Abidjan. The future will demand a highlevel of training of staff of the new services in
Abidjan. It is thus recommended that the new
operators and relevant agencies provide a high levelof in-house training.
Additional infrastructure in conjunction with an
updated requalatory framework will move Abidhan
towards the amintenance of public transport mode.

Table 5 Modal shift
Mode
Walk
PrivatePublic

2015
39.8
10.1
50.1

2030
34.8
13.8
51.4

The informal sector is also reduced in the futurewith the forecasted estimated modal share of Woroworo by nearly thirty percent. This is a result of abetter environment and improved transit efficiency.

Feasibility of Green Modal Shift
There is an anticipation of haulting the decline inpublic transport in the future as a result of theintroduction of a more efficient and environmentallyfriendly or greener form of transport for Abidjan. The
movement towards an efficient and greener transportsystem is also in accordance with supporting the Parisclimate accords.

RESULTS AND CONCLUSIONSThe trigger for the upgrading of public transport
services in Abidjan is the introduction of the highcapacity transit corridors namely the introduction of
Bus Rapid Transit (BRT) and a Bus Higher Level ofService (BHLS) as depicted in Fig. 9. Without these
services, there will be little incentive for public
transport improvement. The purchase of additional
SOTRA buses will improve the status of SOTRA.
This purchase will enable additional services on
their existing line haul routes in the short term. Whilst
at later stages of the public transport timeline whenbuses are released from this role as the high capacitytransit corridors come on line, SOTRA will then havethe ability to use buses to access these high capacitytransit corridors. SOTRA will provide new services
to access as well as outlying centers not served by
BRT or BHLS.

ACKNOWLEDGEMENTS
The authors acknowledge the support of thegovernment of Côte d’Ivoire and the Japan
International Cooperation Agency (JICA) in the
preparation of existing datasets and the developmentof the analytical 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.
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Fig. 9 Future public transport structure.
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Publics( UITP), Public Transport in Sub-SaharanAfrica Major Trends and Case Studies. 2010.
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Commuter Rail and Road Pricing Alternatives
Using an SP Survey in Abidjan. 2017. 25: p. 2524-

2539.
[9] Ortuzar J. de D., On the development of thenested logit model. Transportation Research 2001.
35B: p. 213-216.
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304

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

PRELIMINARY RESULTS OF SITE-SPECIFIC GROUND RESPONSEANALYSIS
Bambang Setiawan1, Taufiq Saidi2 and Mark B. Jaksa3
Program Studi Teknik Geologi, Fakultas Teknik, Universitas Syiah Kuala, Indonesia
2
Jurusan Teknik Sipil, Fakultas Teknik, Universitas Syiah Kuala, Indonesia
3
School of Civil, Environmental and Mining Engineering, the University of Adelaide, Australia
1

ABSTRACTThe city of Banda Aceh-Indonesia is extremely exposed to a significant seismic hazard. There are three main
seismic sources around the city which are the tectonic subduction, the great Sumatran fault, and the West Andaman
fault. Thus, seismic microzonation study of the Banda Aceh city is urgently required for any mitigation efforts.
Site-specific ground response analysis was carried at eleven sites in the city of Banda Aceh. An analytical modelof the equivalent-linear model was used to achieve ground response analysis. This analytical model of theequivalent-linear approach has demonstrated that they can simulate reasonably well the alteration of seismic
ground motions on the ground surface. Three actual historical time histories recorded at rock site nearby the cityof Banda Aceh and eleven developed sub-surface models in the city of Banda Aceh were used to estimate theseismic characteristics i.e. the peak ground acceleration, peak ground velocity, fundamental frequency, andestimated site amplification of the investigated sites. Furthermore, both spectral velocity and acceleration of theinvestigated sites also are proposed.
Keywords: Seismic, Peak ground acceleration, Fundamental frequency, Site amplification, Banda Aceh

earthquakes along this GSF are 1892 earthquake
around Lembah Batang Gadis and Batang Angkola,1903 Kerinci earthquake [4]. The displacement ofeach GSF’s segment has been measured andcalculated using GPS geodetic. A raw estimation of
the segments near the city of Banda Aceh i.e.
Seulimeum-Aceh-Tripa segments is between about
20 mm/year and 16 mm/year [1].
The tectonic setting of Andaman and thesurrounding area is very complex and under researchscrutiny [5]-[7]. West Andaman Fault was interpreted
as a lateral fault by [8] but proposed as trust fault by[9]. This West Andaman fault can be correlated to
Deligent fault at north and Mentawai fault at the south[10], [11]. Thus, these three faults form a fault zone
along Andaman-Sumatra.
The city of Banda Aceh is founded on thick
Holocene Alluvium [12] and classified in highly
seismic hazard risk [1]. In a recent study on
Indonesian seismic hazard assessment [1], the city ofBanda Aceh can experience high peak groundaccelerations during an earthquake [1]. Furthermore,
based on the deterministic seismic hazard analysis
studies, the city of Banda Aceh exposes to disastrous
onshore seismic with 7.5 magnitude potential value[13]. Therefore, detailed estimation of local site
effects is required for the city of Banda Aceh. For this,microtremor measurement at 11 locations across thecity of Banda Aceh was carried out. Subsurface andgeotechnical data collected from various agencies
were collected. These data were used to develop the

INTRODUCTION
The city of Banda Aceh-Indonesia is a coastal
capital city of the Province of Aceh located in
Northern tip of Sumatra. It is a moderately sized citywith an area of 59 km2 and a population of 300,000
people. The city is located on the delta of Krueng
Aceh river. It is surrounded by the district of Aceh
Besar on the North-East to South-West and Malacca
Straight on the North-West. The city is relatively
close to three seismic source zones of the tectonic
subduction of Indo-Australian and Eurasian Plates,
the great Sumatran fault, and the West Andaman fault.
Recently the tectonic subduction seismic source zone
has produced several seismic strong events such as
the 2004 Aceh earthquake (9.2 Mw), 2005 Nias
earthquake (8.7 Mw), 2007 Bengkulu earthquake (8.5
Mw), and 2010 Mentawai earthquake (7.8 Mw). The
2004 Aceh earthquake is suggested by National
Geographic as the second worst hazard of all the time[1]. This event affected 14 countries, caused morethan 220.000 casualties, caused displacement of morethan 1.5 million people, and caused economic lossesof 10 billion USD [1]. The subduction of IndoAustralian plate under the Eurasian plate at the westof Sumatra has produced 19 main fault segments witha length of 60 ~ 200 km on the shore of Sumatra [2]which is well known as the great Sumatran fault(GSF) [3]. This fault is identified as a dextral-lateral
fault with an estimated length of ±1900 km stretchedfrom Banda Aceh to Sunda Strait. Several
305

SEE - Bangkok, Thailand, Nov.11-13, 2019sub-surface profiles in the study.
Commonly local ground response effect is
examined using one dimensional (1D) model toinvestigate the sub-surface local characteristics
during an earthquake. The basic assumption of this
1D model is the propagation of seismic waves invertical directions through the horizontal layers of thesoil which can be solved using Equivalent-linear or
nonlinear analyses. In practice, equivalent-linear
ground response analysis is widely used to simulate
true nonlinear soil behavior because the model
requires small computational effort and few input
parameters [14]. The computational process of thisequivalent-linear analysis is outlined in [15]. In thisstudy, the effects of local soil conditions onearthquake ground motions have been estimated bycarrying out detailed 1D equivalent linear wave
propagation analysis using EERA software [14]. The
results are useful for structural engineers, town
planners, and the government in any mitigation
strategy. The results also can be used for carrying out
more advance soil-structure dynamic analysis.

(2) to develop the sub-surface profile models forcomputer programs, (3) to run the computer program,and (4) to deduce and interpret the results. The overall
methodology is outlined in Fig. 1. Several main input
data are required in the ground response analysis. In
this study these inputs are classified into three
categories: Site sub-surface model development includes
soil type, thickness, unit weight, shear wave
velocity, and water level. In this study onedimensional (1D) sub-surface model isdeveloped for the site response analysis at 11
locations in the city of Banda Aceh. Field
ambient noise measurements were carried out at
the 11 sites from which the sub-surface profiles
at the measured site were deduced (Fig. 2).
Other related sub-surface data in the city ofBanda Aceh are also elaborated in thedevelopment of the 1D sub-surface profile.
 Dynamic soil type characterization includes theassessment of dynamic soil properties either bylaboratory experimentations of the soil takenfrom the investigated site or by standard curves
and correlations. Modulus reduction anddamping ratio curves have been selected basedon the different type of soil properties. In theabsence of the development of the site-specificmodulus reduction and damping ratio curves,
standard curves proposed in EERA wereapplied.
 Earthquake ground motion time histories
justification comprises the selection ofacceleration time histories based on either
factual time histories or the generation of thesynthetic ones. Generally, the selected time
histories are in line with the expectedearthquake hazard in the study area. The
selection of the factual earthquake groundmotion or the generation of synthetic seismic
ground motion is the final step in groundresponse analysis. This generating or selecting
an acceleration time history must be compatible
with the expected maximum dynamic loading at
the site of interest. The selection of the suitableacceleration time histories can be based on
expected peak ground acceleration (PGA)
value, maximum earthquake magnitude,
distance of the expected most disastrous seismicor seismic site class. This study is based on thefactual acceleration time histories data andignoring this selection of the suitableacceleration time history process. Three
recorded at rock site near the city of Banda
Aceh acceleration time histories of 2012
Simeulue earthquake, the 2013 ManeGeumpang earthquake, and the 2013 Bener
Meriah earthquake were collected from BMKG
earthquake data repository (Table 1). The
distance of these seismic events from the city of

REVIEW OF PREVIOUS STUDIESPolom et al. [16] carried out shallow shear wave
reflection seismic measurements in Krueng Aceh
River basin under the project Management of Georisk(MANGEONAD) of the Federal Institute forGeosciences and Natural Resources (BGR), Hanover,German. Several near-surface shear wave velocity
profiles of the city of Banda Aceh were produced.
Setiawan & Kusuma [17] was enhancing the resultsof [16] to estimate local ground response during the2004 Aceh earthquake. A detailed study of the nearsurface shear wave velocity of the city of Banda Aceh
was carried out by [18] using multichannel analysis
of surface waves (MASW) method at 49 locations.
Seismic site classification based on Indonesianstandard of SNI 1726-2012 for the city of Banda Aceh
was deduced and proposed. Most of the sites in thecity of Banda Aceh are classified as seismic site class
between E and D in accordance to SNI 1726-2012,
which suggests class D for Vs,30 less than 175m/s andD for Vs,30 from 175 m/s to 350 m/s.
In 2018 Saidi et al. [19] simulated typicalshophouse buildings in the city Banda Aceh using
response spectra curve. Yunita et al. [20] investigated
the seismic site amplification of the city of Banda
Aceh’s soft soil. This investigation suggested theground motions amplification of Banda Aceh’s soilsof up to 4.3.
METHODOLOGY
The methodology of this study in the simplest
procedure can be outlined in the following main
steps: (1) to collect the secondary and primary data,
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Banda Aceh are 613km, 45km, and 181km for2012 Simeulue earthquake, the 2013 ManeGeumpang earthquake, and the 2013 Bener
Meriah earthquake, consecutively.

Seismic Site Classification
Generally, it is recommended to use the actual
near-surface shear wave velocity in seismic siteclassification [21]. These factors are based on the
average shear wave velocity of the top 30m of the soil
profile (Vs,30). Average Vs,30 for the soil profile can becalculated using the following equation:𝑑̅̅̅̅̅̅
𝑉𝑠,30 = ∑ 𝑉𝑠𝑖 × (30𝑖 )Fig. 1(1)where Vsi is shear wave velocity at the i-th layer anddi is the thickness of the i-th layer.
As aforementioned the near-surface shear wave
velocity is inverted using joint inversion of HVSR
curve and site fundamental frequency. It has been
observed in this study that all of the investigated sites
come under site class D based on SNI-1726-2012
with the average Vs,30 value for the profiles ranging
from 203 to 235 m/s. These seismic site classification
outputs were compared with the results of a study by[18]. This study is slightly overestimated the seismic
site classes of [18]. This study classifies seismic siteclass D for all the investigated sites, but [18]suggested seismic site class E for sites #2-Jaw, #3Smk, #5-Lam, #08-Pad, and #10-Lon. The detailed
comparison is presented in Table 2.

The methodology of site response analysis.

Table 2 Results of the site response analysis
Site nameFig. 2

Microtremor field measurement campaign inthe city of Banda Aceh.

Table 1 Three historical seismic Events Used in This
Site Response Analysis
Event name
7:43:11 on 1104 2012
Simeulue
05:22:42 on 2201-2013
Mane-Gempang
14:37:03 on 0207-2013
Bener Meriah

Epicentercoordinates

Magnitude

Depth
(km)

N 0.82 &92.42 E

8.1

24

N 5.49 &95.21 E

6.0

84

N 4.70 &96.61 E

6.2

Vs,30 in m/s, (Seismic site class)This study
Muzli et al. [18]#1-Tib205 (D)196 or 142 (D/E)#2-Jaw
218 (D)
173(E)#3-Smk235 (D)
148(E)#4-Uns203 (D)#5-Lam213 (D)
151(E)#6-Ill217 (D)
175(D)#7-Bat219 (D)201(D)#8-Pad210 (D)
148(E)#9-Inie
227 (D)238 or 220 (D)#10-Lon
205 (D)151(E)#11-Pie
227 (D)
Note: The seismic site classification is based on SNI
1726-2016.
Seismic Ground Response Analysis
Seismic ground response analysis was carried out
for 11 sites in the city of Banda Aceh. The main
results of site-specific ground response analysis using
the EERA model are presented in Tables 3 to 5. The
highest peak ground velocity (PGV) of 0.5m/s isestimated at Site #08-Pad. The most peak groundacceleration (PGA) of 0.07g is predicted at two sitesof Site #03-Smk and Site #10-Lon. Site fundamental

10

RESULTSThe results presented in these following sections
are deduced from the ambient noise data analysis andseismic ground response analysis.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

frequency for the city of Banda Aceh is estimatedbetween 0.2 to 1.1 Hz. The highest maximum spectral
velocity and maximum spectral acceleration are
estimated at Site #03-Smk of 0.26cm/s and Site #10Lon of 0.29g, respectively. In this study, the seismic
motion acceleration at the ground surface wascompared with the acceleration at the expected site's
basement. The result is to deduce the site
amplification which suggests from 3.5 to 4.9 in thecity of Banda Aceh. The spatial distribution of thesite-specific ground response analysis results at thecity of Banda Aceh is presented in Fig. 3 to Fig. 8.

Bener Meriah earthquake (2013) have been taken as
input ground motions. Based on the analysis of theresults obtained in this study, the following
conclusions have been drawn: All the 11 sites have been classified as per theprovisions SNI 1726-2012. All the measured
sites have been classified as seismic site class D.
 The site fundamental frequency has been
observed from 0.2 and 1.1 Hz.
 The amplification factors of the soils in the cityof Banda Aceh have been observed in the rangeof 3.5 and 4.7.
The site fundamental frequency and amplification
factor developed in this study can be used for the
dynamic analyses of important structures in the cityof Banda Aceh.

Table 3 Results of the site response analysis
Site name#1-Tib#2-Jaw#3-Smk
#4-Uns#5-Lam#6-Ill
#7-Bat#8-Pad#9-Inie#10-Lon#11-Pie

PGV Soil(m/s)
0.04-0.08
0.03-0.04
0.03-0.04
0.4
0.3-0.4
0.3-0.5
0.3-0.4
0.4-0.5
0.3
0.3-0.4
0.3

PGA Soil(g)
0.03-0.06
0.03-0.06
0.03-0.07
0.03-0.06
0.02-0.06
0.03-0.06
0.03-0.06
0.03-0.06
0.03-0.06
0.04-0.07
0.03-0.06

Table 4 Results of the site response analysis
Site name#1-Tib#2-Jaw#3-Smk
#4-Uns#5-Lam#6-Ill
#7-Bat#8-Pad#9-Inie#10-Lon#11-PieMax. spectral
velocity(cm/s)
0.09-0.18
0.10-0.15
0.12-0.26
0.14-0.25
0.15-0.22
0.14-0.24
0.11-0.17
0.16-0.22
0.10-0.15
0.14-0.23
0.11-0.15

Max. spectra
acceleration(g)
0.12-0.22
0.11-0.22
0.11-0.23
0.11-0.23
0.10-0.22
0.10-0.25
0.10-0.24
0.10-0.21
0.10-0.27
0.13-0.29
0.10-0.20

Fig. 3

Estimated maximum peak ground velocity at
the city of Banda Aceh.

Fig. 4

Estimatedmaximumpeakgroundacceleration at the city of Banda Aceh.

CONCLUSIONS
Local site effect on earthquake ground motions
has been investigated for sites in the city of Banda
Aceh (Indonesia) by carrying out detailed 1D
equivalent linear ground response analysis. Actual
acceleration time histories of Simeulue earthquake(2012), Mane-Geumpang earthquake (2013), and
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 5 Results of the site response analysis
Site
name
#1-Tib#2-Jaw#3-Smk
#4-Uns#5-Lam#6-Ill
#7-Bat#8-Pad#9-Inie#10-Lon#11-Pie

Fig. 5Fund. Frequency (Hz)Theoretical
Exp.
0.4
0.3
0.4
0.4
0.4
0.4
0.4
1.1
0.4
0.6
0.4
0.4
0.4
0.4
0.4
0.2
0.4
0.4
0.4
0.6
0.4
0.4

& Pengembangan, Kementerian Pekerjaan
Umum & Perumahan Rakyat, 2017, ISBN: 978602-5489-01-3.
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[3] O. Bellier, S. Sébrier, T. Pramumijoyo, H.
Beaudouin, I. Harjono, Bahar, O. Fomi.
Paleoseimicity and seismic hazard along the
Ornat Sumatran Fault (Indonesia), J. Geodyn., 24,1997, pp.169-183.
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Archipels bis zum Jahre 1857. Amsterdam,
Muller, 1918.

Max
AF
4.2
3.9
4.0
3.6
3.6
3.5
4.1
4.6
4.0
4.7
3.5

Fig. 6

Estimated maximum spectral acceleration at
the city of Banda Aceh.

Fig. 7

Estimated site fundamental frequency at thecity of Banda Aceh.

Estimated maximum spectral velocity at thecity of Banda Aceh.

ACKNOWLEDGMENTS
We acknowledge the help and assistance given by
Universitas Syiah Kuala for the study under H-Index
Research Scheme Year 2019 of Universitas Syiah
Kuala (Contract No. 523/UN11/SPK/PNPB/2019 ondate 8 February 2019). Also, the authors are gratefulto the Fakultas Teknik Universitas Syiah Kuala for
their support
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[11] M. Mukti, S.C. Singh, I. Deighton, N. D.
Hananto, R. Moeremans, H. Permana. Structural
evolution of backthrusting in the Mentawai fault
zone, offshore Sumatran forearc, Geochem.
Geophys. Geosystems, 13(12), 2012, pp.1-12.

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STUDY OF SEEPAGE THROUGH AN EARTH DAM CASE STUDY(AJDABIYA RESERVOIR)Prof . Salem Al- Sanusi, Mervat J. M. Alarosh
FACULTY OF ENGINEERING , University of Benghazi, LIBYAABSTRACTThe objective of this study is to determine how leakage through a lining system would affect the design ofblanket toe drains in an earth dam. Toe drains decrease the pore pressure at the downstream face and keep theseepage line (or phreatic surface) below the downstream boundary. Simulations will be conducted to determine
the location of the phreatic surface in a homogeneous dam due to the presence of defects in liner. Numericalsimulations will be performed using GEOSTODIO to determine the length of the toe drain needed to prevent
seepage from occurring on the downstream face of the dam. In addition, the effect of the elevation of the phreatic
surface within the dam on the stability of the downstream face of the dam will be considered in analysis. The
study will also provide the benefits of using a geomembrane liner regarding the stability and toe drain in theearth dams.
Keywords: leakage, Seepage, Homogeneous, Numerical simulations, Geostudio.

[2,3,4]. Numerical models are used to makeacceptable approximations for the Laplace equationin complex flow conditions. The methods ofnumerical solution, such as finite element finite
difference, finite volume and boundary element,
were used to analyze the phenomenon of seepage
through earth dams. [5,6,7].

INTRODUCTION
Seepage within and under the embankment must
be controlled to prevent concealed internal erosion
and migration of fine materials, or external erosion
and sloughing. With the homogeneous embankmentof dam, the buildup of excess pore pressures within
the embankment and seepage has been a problem,
especially for a reservoir having high, or rapidly
fluctuating water levels for long periods; or for adam having impervious foundation. If seepage isexcessive, this can lead to instability and eventual
failure of all or part of the downstream face [1].
Seepage through an earth dam is the continuous
movement of water from the upstream face toward
its downstream face. The top seepage line ofpercolating water is known as the phreatic surface.
In order to allow adequate embankment and toeliminate seepage problems in the downstream areasof an embankment on impervious foundation, thephreatic surface should be kept within the dam byproviding a horizontal drainage filter. The amount ofwater seeping through and under an earth dam,
together with the location of the phreatic surface,can be estimated by considering the flow throughporous media. The Laplace equation which governs
water seepage cannot be solved analytically, except
for cases with very simple and special boundary
conditions. Therefore, researchers have invoked toempirical, graphical and recently numericalmethods. Several methods have been developed tosolve exactly or approximately Laplace's equationfor various cases of seepage. One of the most widelyused methods, the flow net, can be adapted to manyof the under seepage and through-seepage problems
found in dams and other projects involving hydraulicstructures. The seepage of flow through earth dams
was studied analytically by a number of researchers

LITERATURE REVIEW
Darcy (1856) gave the basic law of flow throughporous media through his series of experiments onvertical pipe filled with sand. Darcy's Law wasoriginally derived for saturated soil, but later
research has shown that it can also be applied to theflow of water through unsaturated soil (Richards,
1931 and Childs & Collins-George,1950). The only
difference is that under conditions of unsaturated
flow, the hydraulic conductivity is no longer a
constant, but varies with changes in water content
and indirectly varies with changes in pore waterpressure. Various methods are available for seepage
analysis which may be classified as analytical,
experimental and numerical methods. various
computer softwares are used nowadays whichfacilitates researcher to simulate the actual field
conditions for performing seepage. Shivdakumar S.
Athani et al. (2015) have presented the results offinite element modeling of the stability and seepage
analyses of the earth dam using PLAXIS 3D
software. Imran Arshad et al. (2014) have stated that
seepage analysis of earth dam can be efficiently
performed using finite element based SEEP/W
software. This software is capable to estimate
various parameters of flow net such as seepage
discharge, exit gradient, seepage velocity, pore waterpressure, uplift pressure at any desired point inflownet. Hasani et al reviewed safety of earthen dam
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SEE - Bangkok, Thailand, Nov.11-13, 2019by performing using GEOSTUDIO software sub
product Slope/W . G.V.Panthulu et al. (2001) havesuggested that Geophysical methods can also be
efficiently used for mapping seepage paths andmonitoring the changes of the seepage with time.
Kamanbedast et al. (2011) focused on need of using
different methods to investigate the safety of dam soas to decrease any errors in calculation due tomaintenance of water storage especially hydrostructure of the dam.

In the following figures show the current state ofthe dam fig (2) , fig (3) does show the soil profile
lining under reservoir and fig (4) does show thelayered structure of the inner of the dam.

METHODOLOGY
According to the case study we classify the cases
into lining or without lining .with max operationlevel of 8 m height .the dam used with toe draining
system. the case study is then checked for different
values of k from range of 1E-06 to 1E-04. The
methodology of the work is as shown in Fig(1).

Fig. 2 Current state of the dam

Fig. 3 Soil profile lining under reservoir

Fig. 1 The methodology
SOFT WARE (SEEP/W Program)
Fig. 4 Layered structure of the inner of the dam

SEEP/W (which is a sub-program of Geo-Studio)
is a finite element software product for analyzing
groundwater seepage and excess pore-water pressure
dissipation problems within porous materials such as
soil and rock. Its comprehensive formulation allows
you to consider analyses ranging from simple,
saturated steady-state problems to sophisticated,saturated and unsaturated time-dependent problems.
SEEP/W can be applied to the analysis and design of
geotechnical, civil, hydrogeological, and mining
engineering projects . Many previous works studied
different seepage problems by using SEEP/W
program [4,5,6].

GOVERNING EQUATIONS
Following partial differential equation (PDE) is thegoverning equation used for modeling of SEEP/W
program:


H

H

(kx
)
(kx
) Q 
x
x
y
y
t
Where,
H = Hydraulic head
Kx = hydraulic conductivity in x direction
Ky = hydraulic conductivity in y direction

Case Study Of Reservoir

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(1)

SEE - Bangkok, Thailand, Nov.11-13, 2019

Q = applied boundary fluxt = time domain
θ = volumetric water content.
The Eq. (1) is time variant and states that ‘thedifference between the flow entering an elemental
volume and leaving an elemental volume at a point
is equal to the change in the volumetric watercontent in a particular time’.
If the volume of influx equals to the volume of out
flux then the equation caters for steady state
conditions, thus the right hand of the equation
changes to zero.


H

H
(kx
)
(kx
) Q  0
x
x
y
y

Fig.7.variation of flow rate along distance(2)

RЕSULT DISCUSSION
In the operation of the Seep / W program in aearth dam containing a horizontal discharge system
at a maximum operating level of 8 m using threedifferent values of permeability (k) (0.000001,
0.00001 and 0.0001 m / s) and its effect on leakage,
pore water pressure , hydraulic gradient line andhydraulic conductivity
The change in the value of K for the different
values affect the values of I , P ,d and q. The next
figures shows the variation of each variables.
Fig.8. Variation of hydrualic gradient.

We note the folowing points for the variation of
k
1.
2.
3.
4.
Fig.5. Variation of hydraulic coductivity along
distance.

The hydolulic conductivity is increased toabout 4.3 at beging point of filter zone.
The pressure dropped in the zone of filter .
The flow rate is gradually increased to thefilter zone and then remain constant.
The hydraulic gradient is reach value of 4.4
at the start point of filter.

CONCLUSIONS
From the study of the case study we conclude that.
1- The change of hydraulic conductivity isaffect the hydraulic gradient , flow rate,pressure by effective value.
2- The flow rate under the dam is graduallychanged under dam until it reaches certain
value ( 0.5 m3/s).
3- The pressure is suddenly dropped in thedraining system.
4- The hydraulic gradient is suddenly
increased in the filter zone.

Fig.6. Variation of pressure along distance.
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SEE - Bangkok, Thailand, Nov.11-13, 2019[3] Hasani, J. M”amizadeh and H. Karimi ,“Stability of Slope and Seepage Analysis in
Earth Fills Dams Using Numerical Models (CaseStudy: Ilam Dam- Iran), World Applied Sciences
Journal 21 (9): 1398- 1402, 2013,ISSN 18184952.
[4] Geo-Slope Software Example (2007),” Seepage
through A Dam Embankment”.
[5]Geo-Slope International Ltd, Calgary, Alberta,
Canada.
[6]Carastoian Andrea ,“Unsaturated Slope Stability
and Seepage Analysis of a Dam” , Sustainable
Solutions for Energy and Environment,
EENVIRO - YRC 2015, 18-20 November 2015,
Bucharest, Romania[7]Shivakumar S. Athani , Shivamanth, C. H.
Solanki and G. R. Dodagoudar ,“Seepage andStability Analyses of Earth Dam Using Finite
Element Method”, International Conference On
Water Resources, Coastal And Ocean
Engineering (Icwrcoe 2015)

5- The max operation level of dam (8m) leadto max leakage of dam. So the more safe
state operation of the system is advised to
be 5m .
6- The increasing of the value of the filterzone the drop in pressure and the lesscritical values of each of flow rate andhydraulic gradient.
REFERENCES[1] Imran Arshad and M.M. Baber ,“Finite Element
Analysis of Seepage through an Earthen Dam by
using
Geo-Slope(SEEP/W)
software,
International Journal of Research (IJR), Vol-1,
Issue-8, September 2014. ISSN: 2348- 6848.
[2]Ms. Abhilasha P. S. And T. G. Antony Balan,“Numerical Analysis of Seepage in Embankment
Dams”,IOSR Journal of Mechanical and Civil
Engineering (IOSR-JMCE) e-ISSN: 2278-1684,
p-ISSN: 2320-334X PP 13-23.

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ANALYSIS OF SLOPE STABILITY (AJDABIYA RESERVOIR)
Prof. Salem Al- Sanusi, Abier J. M. Alarosh
FACULTY OF ENGINEERING, University of Benghazi, LIBYAABSTRACTThe ability of geotechnical engineers to accurately model slope performance is affected by a variety offactors. This paper research explained about slope stability of earthen dams using GEOSTUDIO software. The
main problem is that the exact behavior of slopes cannot be accurately predicted. Hence, geotechnical engineers
resort to a factor of safety approach to reduce the risk of slope failure. Although, the factor of safety approach
can not quantify the probability of failure associated with the design situation, it offers a conservative way totreat slope stability uncertainties. The uncertainties can be related quantitatively to the design reliability of aslope. The study of the factor of safety based design procedure, in which engineers can combine practicalexperience, judgment, and statistical information is beneficial for analyzing the stability of slopes for anallowable risk criterion. The objective of this research is to develop a general model of slope stability analysis[1] and the safety of dam in bearing and the settlement. The study is performed through different methods ofanalysis, the sensitivity analysis is then applied to the output factor of safety with variables to determine theslope design parameters that have apparent effect on the factor of safety (FOS) is a measure used in engineering
design to represent how much greater the resisting capacity of a structure or component is relative to an assumed
load ,For example a dam with a FOS of (1.4) does not necessarily have a higher probability of failure than a dam
with a FOS of (1.6) . To demonstrate the application of the method developed during this research, themethodology was applied to case study (Ajdabya Reservoir) to present the effect of each variable on the factor ofsafety. The factor of safety is studied for a circular failure surface using different methods of analysis. The study
evaluated four methods for calculating slope stability. We will use the Morgenstern- price method, which isconsidered an accurate method for calculating the factor of safety. The software which will be used for analysisof the model is GEOSTUDIO package. The procedure was performed in scenarios with different soil groups
according to the Unified Soil Classification System (USCS) (ASTM 2011), heights and slope inclinations, andunder conditions of reservoir subject to fast and slow emptying.
Keywords: Slope Stability, allowable risk , factor of safety (FOS) , slope inclinations , Earthen Dam,
GEOSTUDIO Software.
INTRODUCTION

drawdown and steady seepage which can cause
piping through the foundation or within theembankment [1].

In olden days, designing of slopes are based on
the experience of Geotechnical Engineers and design
approach was based on prevailing site conditions.
This approach of designing slopes has resulted inextensive property damage and occasionally resulted
in the loss of life.
Now a day’s there is an increased demand forengineering cut and fill slopes on construction
projects. The construction of finite height sloped
embankments is a common practice in dams,
highways and railway projects. The finite element
analysis of stability failures and seepage analysis
demands increased to handle complex problems in
the construction field[2].
Stability and seepage analysis for earthen dams
are very important to maintain the stability of thestructure. Embankments of earthen dams must be
designed to construct stable against any type of force
conditions which develops in the life of thestructure.
Mostly loading conditions are critical like sudden

To derive factor of safety, slope stability analysisof the embankment may be carried out for the 10m
height of the homogeneous dam. The analysis has
been performed using Mohr-Coulomb constitutive
model. There are many analysis methods such as
Method of Slices, Bishop’s method, Janbu’s method
and Morgenstern Method etc. using any of themethods we can determine the stability analysis [3].
GEOSLOPE is developed by GEO-SLOPE
International, Canada, based on the principle of limit
equilibrium which incorporates a finite element
method which is developed specially for the
deformation and stability of embankment structures.
It includes modeling of stability with (SLOPE/W),
modeling of seepage with (SEEP/W), modeling ofstress.
SLOPE/W and SEEP/W has been used with
“Morgenstern method” to do the stability analysis. It
is designed and developed to be a general software

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SEE - Bangkok, Thailand, Nov.11-13, 2019

tool for the stability analysis of earth structures forthe proposed project of the raw water reservoir.
METHODOLOGY
In this study, two loading conditions studied likesteady state seepage and sudden drawdown analysis.
SEEP/W has been applied together with SLOPE/W.
Two types of slip surface searching techniques:“Entry-exit” and “Grid-radius” were used. The mostcommon limit equilibrium (LE) based method used
is Morgenstern-Price method (M-PM),which isincorporated in SLOPE/W to analyze the model withall four cases to find out the factor of safety on both
upstream and downstream sides of the earthen dam
contains over all height 22 m and maintained waterlevel at 19 m on upstream other details shown in
Figure no. 1 .

Fig. 2 The steps of research work.
CASE STUDYThis research studies some of the phenomena
occurring in the Ajdabiya reservoir located 20 km
southeast of the city of Ajdabiya, in a high position
to provide the natural flow of water for both the
Gardabiya reservoir and Omar Mohktar reservoir.
Water flows by gravity from Sarir and Tazerbo well
field ,through a 4m diameter
pipe-line (381667Km ),to Ajdabiya holding reservoir which isdesigned to hold million cubic meters of water .The
reservoir is considered as a storage facility fromwhich water can be distributed to other systems .
Materials used in the construction of this circularembankment were obtained from borrow adjacent tothe site.

Fig. 1 Earthen dam model.
SLOPE/W uses the SOLVE process to calculate
the FOS. Each slip surface is processed in 3 steps:
1. Initially, no forces are considered between theslices.
2. Normal forces are then considered, with noshear. An iterative process is used to calculate the
FOS within a specified convergence3. Then normal and shear force relationship isconsidered in Morgenstern-Price method.

Characteristics of Ajdabiya Reservoir
storage volume in the reservoir is 4.2 M/day atthe maximum level of 98.4 m (about mean sea level)
and a minimum of 91.92 m . The ultimate in- flow
was given as 3.68 M/day , but it was safe for 4.5
M/day , The reservoir has no natural catchment
and contained by a circular embankment of diameter
923.2m to the inner crest . The reservior operating
rang is 6.48 m.

The steps of the research work can be shown in
the following flow chart Figure no. 2.

SOFTWARE USED IN STABILITY
MODELING AND SEEPAGE ANALYSIS OF
EARTHEN DAMS
Many numerical software’s are developed fromlast six decades to evaluate engineering complex
problems. Based on modeling approach, various
numerical models are determined using software.
In our study, SLOPE/W and SEEP/W are
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windows) is a finite element software product that iscoming under Geostudio, used to model the
movement and pore-water pressure distribution
within porous materials like soil and rock. It is
formulated on the basis that flow of water throughsaturated soil follows Darcy’s Law. The SEEP/W
model is constructed to solve 2-dimensional flow
situations with multiple soil layers. Flow directionsof groundwater can be analyzed. Under steady state
conditions, the difference between input flux andoutput flux is zero at all times. for finite element
calculations, the SEEP/W model is divided by nodes.
The elevation of water level at each node iscalculated. In the SEEP/W models, the following
assumptions are made:(1) The aquifer is homogeneous and isotropic,(2)The aquifer
is partly confined and partly
unconfined.
Good quality output graphics allows a visualdisplay of equipotential lines and flow paths, andcontours can be plotted for different properties likepore pressures, seepage velocities, and gradients.
Computations include flow quantities and upliftpressures at user-selected locations in the model.

components of a complete suite of geotechnicalproducts called GEOSTUDI. SLOPE/W caneffectively analyses both simple and complex
problems like Geometry, soil strength, pore waterpressure, analysis methods and loading conditions
like Steady state seepage and rapid or sudden
drawdown condition applied on both upstream anddownstream sides of the dam.
SLOPE/W is framed in terms of force andmoment equilibrium to get a factor of safety
equations.
The Morgenstern – Price method (1965) defines
both moment and force equilibrium. To analyses theseepage of ground water, SEEP/W tool is used andalso it helps to find the excess of pore water pressure
dissipation problems within rock and soils calledporous materials. Foundation material has asaturated hydraulic conductivity equal to 1x106
m/sec. To define the hydraulic conductivity function
over a range of positive and negative pressure toadequately reflect the decrease in
Hydraulic conductivity that occurs as the soil
becomes unsaturated. Ksat Upper soil = 1E-6 m/day,Ksat Lower soil = 1E- 9 m/day.
According to IS 7894 – 1975, a) “steady seepage
with the reservoir full on downstream side”, theminimum factor of safety is 1.5 and (Duncan &Wright 2005, p.199) explains about a factor of safety
provides a “quantitative indication of slope stability”.
They are:(i) A calculated factor of safety value equal to
1.5 ( FOS = 1.5) represents the forces on the slope
being in equilibrium; that is the forces within theslope causing stability (resisting forces) are inbalance with those which cause the slope to beunstable (driving forces).
(ii) A calculated factor of safety value greaterthan 1.5 (FOS > 1.5) represents the slope being
stable under the given conditions (resisting forces >driving forces), and(iii) A calculated factor of safety value less than
1.0 (FOS < 1) represents the slope is unstable(failing); that is the driving forces out the way theresisting forces.

Equations
The Morgenstern-Price method is a rigorous
method also based on limit equilibrium formulation(GEO-SLOPE International Ltd,2012). [4]The method considers both shear normal inter slice
forces and satisfies both moment and force
equilibrium. Two equations are used for calculating
the factor of safety one with respect to moment
equilibrium, Fm, and the other with respect tohorizontal force equilibrium
see Equation (1) and(2).All input parameters described below and also
Illustrated in Figure 3.
)

)

)

(1)
)

(2)

The variable are defined as follow:= effective cohesion= effective friction angle= pore water pressure= the total weight of a slice= the total normal force on the base of a

According to IS 7894 – 1975, b) “sudden
drawdown condition the maximum head water tominimum with tail water at maximum on upstreamside”, the minimum desired factor of safety is 1.3.
Geostudio software is one of geotechnicalprogram that is based on the finite element and can
do analysis such as, stress-strain, seepage, slope
stability, dynamic analysis. SEEP/W (seepage for

slice
D

= an external point load
= the horizontal seismic load applied
through the centroid of each sliceR= the radius for a circular slip surface

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SEE - Bangkok, Thailand, Nov.11-13, 2019select the interstice force function (GEO-SLOPE
International Ltd2012). There are five different interslice force functions available in Slope withe
constant function ,the half-sine function ,thetrapezoidal function and data point specified
function . Only half-sine function is considered inthis research.
RESULTS AND DISCUSSIONSF= the perpendicular offset of the normal
force from the center of rotation
X = the horizontal distance from the centerlineof each slice to the center of rotatione= the vertical distance from the centroid ofeach slice to the center of rotationd= the perpendicular distance from a point
load to the center of rotationa= the perpendicular distance from theresultant water force to the center of rotation
A = the resultant external water forces= the angle of the point load from thehorizontal= the angle between the tangent to the centerof the base of each slice and the horizontal= the base length of each slice

The results of the case study was performed using
GEO-SlOPE software to evaluate the critical pointof the slip surface then the investigating about thecritical safety factor. The critical factor of safety istaken for the most critical case with lambda.
Fig.(5) shows the distribution of slip surfaces withthe coordinate of the center point of slip surface.
The most critical safety factor is at point x=35.48
m and y=70.865 m with radius of R=59.808. thisfactor of safety is considered in safe side. (i.e F.O.S> 1.50 ).
The F.O.S is then studied for seepage case which
gives value of 1.382.

Fig.3. The forces acting on a slice for a circularslip surface. (GEO-SLOPE International Ltd. 2012)
The ratio between the interstice forces is iterated
until the two factors of safety F m and Ff are equal(GEO-SLOPE International Ltd2012) [4]. In thecase of composite slip surface a rigorous method
generally produce more accurate results that also err
on the safe side. This is illustrated in Figure 4 whichshows a slice force polygon with good closure

Fig.5.critical factor of safety

Fig.6 critical factor of safety
The water flows from upstream slope to downstream
slope of the earthen dam.
The Graphs are generated same as like “Entry &Exit” technique.
factor of safety improved compared to above three
conditions.
The failure of slip circles was generated by
specifying the entry of the slip circle at the toe andexit at the top bank of the embankment.

Fig. 4 A free body diagram of a slice and to theright the corresponding force polygon (GEOSLOPE
International Ltd. 2012) (modified by the authors).
The Morgenstern-Price method allows for the user to
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SEE - Bangkok, Thailand, Nov.11-13, 2019

The critical slip circle locates the corresponding
factor of safety as shown in Figure 5 (SLOPE/W
with critical slip surface) which is 1.804 and Figure
6 (SEEP/W critical slip surface) shows the factor ofsafety 1.382.

and slope stability analysis for earth-dams, whichhave similar dimensions of the case study.
7- One simple equation is enough to give factor ofsafety results without using software’s because it isalready derived through numerical modeling (finite
elements) so there is no need to repeat the numericalmodeling procedures.

CONCIUSION
1-The factor of safety is increased on downstreamside after providing the drain on the downstreamside is 1.804 which is higher than a minimum factorof safety (FOS) specified by IS 7894 (1975) for
steady seepage condition with a full reservoir.
2-In this analysis, the factors of safety values of allcases have been analyzed to find out the stability ofthe earthen dam. Out of all four cases, with draincase is more suitable to stabilize the homogeneous
earthen dam with a higher factor of safety (FOS).
3-Provision of a drain on downstream side improves
the factor of safety (FOS) on the upstream side.
4- It is possible to create new methods of calculating
the factor of safety against sliding by adding morevariables to the commonly used limit equilibrium
methods.
5-Empirical equations can be derived by assuming
different soil conditions in the earth-dam's body.
6-There is no need to use the same soft wares(SLOPE/W and SEEP/W) in performing seepage

REFERENCES[1] Devi, D. D. N. L., & Anbalagan, R. (2017).
Study on Slope Stability of Earthen Dams byusing GEOSTUDIO Software.‫‏‬[2] Hasani, H., Mamizadeh, J., & Karimi, H. (2013).
Stability of slope and seepage analysis in earth
fills dams using numerical models (Case Study:
Ilam Dam-Iran). World Applied Sciences
Journal, 21(9), 1398-1402.‫‏‬[3] Lowe, J. III, “Stability Analysis of
Embankments’, Journal of the Soil Mechanics
and Foundations Division, ASCE, vol.93, No.
SM 4, Proc. Paper 5305, July 1967, pp. 1-33.
[4] Mishal, U. R., & Khayyun, T. S. (2018).
Stability Analysis of an Earth Dam Using GEOSLOPE Model under Different Soil Conditions.
Engineering and Technology Journal, 36(5 Part(A) Engineering), 523-532.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
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PREDICTION OF FLEXURAL STRESS IN UNBONDED POSTTENSIONED STEEL AT DIFFERENT LOADING STAGES
Nazar Oukaili1 and Iqbal Peera2
Professor, University of Baghdad, Iraq; 2Ph.D. Candidate, University of Baghdad, Iraq

1

ABSTRACTOne of the methods for prestressing the structural concrete members is the use of unbounded tendons which ismore economical and simpler in the construction of concrete members. This paper presents the analytical formulation of a methodology that proposed to predict the flexural stress in unbonded prestressed steel and in turn asses the strength and deformability of prestressed concrete members which are subjected to different types of static
loading (axial force only, uniaxial bending moment, or biaxial bending moment with/without axial force). The
suggested methodology uses the real constitutive relationships for each of concrete, non-prestressed and prestressed steel. Since there is no strain compatibility between concrete and prestressed steel due to the lack ofbond between these two materials, the stress increase beyond the effective prestress is estimated depending on
the total member deformation. A uniform stress distribution along the length of the unbounded tendon is assumed. The methodology is verified using previous experimental data for other researchers.
Keywords: Internal unbonded tendon, Post-tensioning, Flexural stress, Constitutive relationship, Stiffness matrix
INTRODUCTION

of concrete in MPa, 𝑓𝑝𝑦 is specified yield strength ofprestressing reinforcement in MPa, and 𝜌𝑝𝑠 is theprestressing steel ratio ( 𝜌𝑝𝑠 = 𝐴𝑝𝑠 ⁄𝑏𝑑𝑝 ) in which
𝐴𝑝𝑠 is the area of the prestressed reinforcement intension zone in mm2, 𝑏 is the width of compression
flange of the member in mm, and 𝑑𝑝 is the distancefrom the extreme compression fiber to the centroidof prestressing reinforcement in mm.
The main objective of this work includes the
proposal of an analytical methodology to estimate
the stress in internal unbonded prestressed steel at
different stages of monotonic static loading and consequently predict the strength and deformability ofthe structural concrete members under different
types of static loading. Also, verification of the proposed methodology with the available experimental
previous studies will be carried out using resultsfrom Pannell [8], Du and Tao [3], Harajli and Kang[4], Campbell and Chouinard [2]. Results of the proposed methodology will be compared to the resultsof ACI 318M-14 prediction equations.

Several equations have been suggested forpredicting the flexural stress at ultimate 𝑓𝑢𝑏 in unbonded prestressed steel based on the experimental
works that carried out by different researchers depending on a number of variables as Warwaruk et al.
[10], Pannell [8], Mattock et al. [6] and Mojtahedi
and Gamble [7]. As a result of these works, different
proposals were recommended for the flexural stressat ultimate 𝑓𝑢𝑏 and consequently to the methodologies adopted in international practice codes.
The ACI 318M-14 code [1] adopted the following expressions to estimate 𝑓𝑢𝑏 in MPa.
when 𝑙 ⁄ℎ ≤ 35
𝑓𝑢𝑏 = 𝑓𝑝𝑒 + 70 +𝑓𝑐′
100 𝜌𝑝𝑠(1)

𝑓𝑢𝑏 ≤ 𝑡ℎ𝑒 𝑙𝑒𝑎𝑠𝑡 𝑜𝑓 (𝑓𝑝𝑒 + 420) 𝑎𝑛𝑑 (𝑓𝑝𝑦 )when 𝑙 ⁄ℎ > 35
𝑓𝑢𝑏 = 𝑓𝑝𝑒 + 70 +𝑓𝑐′
300 𝜌𝑝𝑠

CONSTITUTIVE RELATIONSHIPS(2)

Non-linear stress-strain relationships proposedby Karpenko [5] were used for concrete in tension
and compression and for steel. These relationships
are based on the secant modulus of elasticity of thematerial 𝐸̅𝑚 as formulated below

𝑓𝑢𝑏 ≤ 𝑡ℎ𝑒 𝑙𝑒𝑎𝑠𝑡 𝑜𝑓 (𝑓𝑝𝑒 + 210) 𝑎𝑛𝑑 (𝑓𝑝𝑦 )where 𝑙 is the length of the clear span measured face
to face of support in mm, ℎ is overall thickness,height or depth of member in mm, 𝑓𝑝𝑒 effective
stress in prestressing reinforcement after all prestresslosses in MPa, 𝑓𝑐′ is specified compressive strength

𝑓𝑚 = 𝐸̅𝑚 . 𝜀𝑚

320

(3)

SEE - Bangkok, Thailand, Nov.11-13, 2019𝐸̅𝑚 = 𝐸𝑚 . 𝜈𝑚2
𝜈𝑚 = 𝜈̂𝑚 −+ (𝜈𝑜 − 𝜈̂ 𝑚 ) √1 − 𝑒1𝑚 𝜂𝑚 − 𝑒2𝑚 𝜂𝑚

𝐶11 = 𝐸̅𝑚 ∫𝐴 𝑑𝐴𝑚 , 𝐶12 = 𝐶21 = 𝐸̅𝑚 ∫𝐴 𝑦𝑚 𝑑𝐴𝑚 ,𝑚𝑚2
𝐶13 = 𝐶31 = 𝐸̅𝑚 ∫𝐴 𝑥𝑚 𝑑𝐴𝑚 , 𝐶22 = ∫𝐴 𝑦𝑚
𝑑𝐴𝑚 ,
𝑚
𝑚
2
𝐶23 = 𝐶32 = ∫𝐴 𝑦𝑚 𝑥𝑚 𝑑𝐴𝑚 , 𝐶33 = ∫𝐴 𝑥𝑚 𝑑𝐴𝑚 .
𝑚𝑚
The stiffness matrix in Eq. (12) depends on thevalue of {𝜀̅} which has not determined yet. So an
iteration process should be performed in which

(4)
(5)

where 𝜈̂𝑚 is the value of 𝜈𝑚 at the vertex of thestress-strain diagram, 𝜈𝑜 is the value of 𝜈𝑚 at thestart of the stress-strain diagram, 𝑒1 and 𝑒2 are diagram curvature parameters in which ( 𝑒2𝑚 = 1 −𝑒1𝑚 ) and 𝜂𝑚 is the stress level beyond the proportional limit𝜂𝑚 =𝑓𝑚 − 𝑓𝑚,𝑒𝑙,𝑓̂𝑚 − 𝑓𝑚,𝑒𝑙

0 ≤ 𝜂𝑚 ≤ 1{𝜀̅}𝑖 = [𝐶({𝜀̅}𝑖−1 )]−1 ∗ {𝐹}{𝜀̅}0 = 0 , 𝑖 = 1, 2, 3, … … .

(6)In each iteration the new value of the strain vector {𝜀̅}𝑖 should be compared to the value of theprevious iteration until the convergence process isreached.
Whenever the strain vector is determined, the strain
in each concrete fiber and in each bonded steel reinforcement element can be estimated depending on
the strain compatibility using Eq. (7). In case of theinternal unbonded steel reinforcement element, due
to the lack of bonding and in turn the violation of thestrain compatibility, the strain is determined by integrating the strain value of concrete at the level of theunbonded steel along its length and dividing thisvalue on its length between anchorages.

For more information about Eq. (5), see Ref. [5].
LOAD-DEFORMATION RELATIONSHIPS
According to the Bernoulli’s assumption inwhich the plane section before bending remains
plane after bending, the strain at any fiber can becalculated according to the following expression
𝜀𝑚 = 𝜀𝑚𝑖 + 𝜀𝑜 + 𝜓𝑥 𝑦𝑚 + 𝜓𝑦 𝑥𝑚(7)where 𝜀𝑚𝑖 is the initial strain in the material; 𝜀𝑜 isthe axial strain; 𝜓𝑥 is the curvature of the member
longitudinal axis in the OYZ plane; 𝜓𝑦 is thecurvature of the member longitudinal axis in the
OXZ plane. Equation (7) can be rewritten in matrix
form as follows
𝜀𝑚 = 𝑍 {𝜀̅}ℓ𝑢𝑏

1
∆𝜀𝑢𝑏 =∫ ∆𝜀𝑐𝑢𝑏 (𝑥). 𝑑𝑥ℓ𝑢𝑏𝑥}{𝜀̅} = {𝜀𝑜𝜓𝑥where ∆𝜀𝑢𝑏 is the change in the strain in the unbonded steel due to the applied load, ℓ𝑢𝑏 is thelength of unbonded steel between anchorages, and∆𝜀𝑐𝑢𝑏 is the change in strain in concrete fiber at thelevel of unbonded steel. The value of ∆𝜀𝑢𝑏 is considered as the average change of strain along theunbonded steel. Adding ∆𝜀𝑢𝑏 to the initial prestrain
𝜀𝑢𝑏𝑖 that induced in this steel reinforcement element
and by consequently using the constitutive relationship that represents the mentioned steel element, thetotal stress can be determined.

(9)
𝜓𝑦 }𝑇

(10)

Since the force vector can be expressed as∫ 𝑓𝑚 𝑑𝐴𝑚
𝑁{𝐹} = {𝑀𝑥 } =
𝑀𝑦

(14)

0

(8)

𝑍 = {1 𝑦(13)𝐴𝑚∫ 𝑓𝑚 𝑦𝑚 𝑑𝐴𝑚

(11)

𝐴𝑚

∫ 𝑓𝑚 𝑥𝑚 𝑑𝐴𝑚

{ 𝐴𝑚

}

𝐶12
𝐶22
𝐶32

𝐶13 𝜀𝑜𝐶23 ] {𝜓𝑥 }𝐶33 𝜓𝑦(15)

𝑓𝑢𝑏 = 𝑓(𝜀𝑢𝑏 )(16)

where 𝑓 is the nonlinear function that relates theunbounded steel stress with the unbounded steel
strain.
The ultimate stress value is determined when theforce vector in Eq. (12) represents the ultimate
strength that the critical section can resist.

Substituting Eq. (3) and Eq. (8), Eq. (11) takes a
new form
𝑁𝐶11{𝐹} = {𝑀𝑥 } = [𝐶21𝑀𝑦𝐶31𝜀𝑢𝑏 = 𝜀𝑢𝑏𝑖 + ∆𝜀𝑢𝑏

(12)

VERIFICATIONOFMETHODOLOGY

where 𝐶𝑖𝑗 is the element of the stiffness matrix that
depends on the geometry of the section and the attained stress-strain condition under the applied load.

THE

PROPOSED

To verify the proposed methodology for predicting the stress in unbonded steel elements and in turn
321

SEE - Bangkok, Thailand, Nov.11-13, 2019steel and the failure moments. Harajli and Kanj [4]tested 26 simply supported beams with three groups
having span to depth ratios 𝑆⁄𝑑𝑝 equal to 20, 13 and8, respectively in which 𝑆 was defined as the span
length measured from anchorage to anchorage of thesimply supported member. Three different contents
of tension reinforcement were used. Thirteen beams
were subjected to a single concentrated load at midspan, while the other 13 specimens were exposed tothird-point loading. The comparison of the experimental and the analytical results for the stress inunbonded prestressed steel and the failure moments
are shown in Table (3). Campbell and Chouinard[2] tested six simply supported beams of a rectangular cross-section of (160x220) mm dimensions and(3300) mm span length. All beams were subjected tothird-point loading. The span to depth ratio was 15
for all the beams. The main variable was the amountof bonded nonprestressed reinforcement. Table (4)shows the comparison of the experimental and analytical outcomes. The above comparisons also are
represented
in
Fig.
1
to
Fig.
4.

the load carrying capacity of the structural concrete
member, experimental data for 60 flexural memberswith different effective parameters were collectedfrom other researchers and treated in the present
study. Tam and Pannell [9] tested eight simply supported beams with straight unbonded prestressedreinforcement. The approximate (overall length) toeffective depth 𝑑𝑝 ratio ranged from 20 to 45. All
these beams were exposed to a single concentrated
load at midspan. The experimental and analyticalresults are shown in Table (1). Du and Tao [3] tested
20 simply supported beams with straight unbonded
steel reinforcement. All beams were with the rectangular cross-sectional configuration of (160x280) mm
and a span of (4200) mm. The main variables were
𝐴𝑝𝑠 , 𝑓𝑐′ , and the amount of nonprestressed reinforcement 𝐴𝑠 . Tested specimens were exposed tothird point static loading up to failure. The span todepth ratio of the beams was 19.1. Table (2) showsthe experimental and the calculated, according to the
proposed methodology and the ACI 318M-14 approach, results for the stress in unbonded prestressed

Table 1 Experimental and proposed results for Tam and Pannell tests [9]

Beam
ID

ℓ
𝑑𝑝

Stress at ultimate in unbonded steel, MPa
test
proposed
ACI 318M-14
recordmethodology
approach
𝑒𝑠𝑡
𝑒𝑠𝑡
𝑓
𝑓𝑢𝑏
𝑢𝑏
𝑒𝑥𝑝
𝑒𝑠𝑡
𝑒𝑠𝑡
𝑓𝑢𝑏
𝑓𝑢𝑏
𝑓𝑢𝑏
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑓𝑢𝑏
𝑓𝑢𝑏
962.19914.74 0.951 944.08
0.981
898.43857.36 0.954 877.01
0.976
1046.40 993.13 0.949 1036.38
0.990
969.68963.9
0.994 984.20
1.015
1071.84 1079.08 1.007 1097.42
1.024
944.74964.39 1.021 983.07
1.041
859.97 884.335 1.028 902.43
1.049
732.67772.5
1.054 833.02
1.137

B1
18.0
B2
23.5
B3
27.5
B4
28.6
B5
29.3
B6
31.4
B7
38.8
B8
43.0
Average of
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑒𝑠𝑡
⁄𝑓𝑢𝑏
(𝑓𝑢𝑏
) or (𝑀𝑢𝑒𝑠𝑡 ⁄𝑀𝑢 )Standard of deviation (σ)
Coefficient of variation (COV)

test
record
𝑒𝑥𝑝

𝑀𝑢

40.13
60.65
30.75
38.38
22.14
22.47
22.84
21.01

Failure moment, kN.m
proposed
ACI 318M-14
methodology
approach
𝑒𝑠𝑡
𝑀
𝑀𝑢𝑒𝑠𝑡
𝑢
𝑀𝑢𝑒𝑠𝑡
𝑀𝑢𝑒𝑠𝑡
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑀𝑢
𝑀𝑢
39.92
0.995 42.75 1.065
55.68
0.918 69.91 1.153
35.00
1.138 35.96 1.169
40.24
1.048 47.94 1.249
25.57
1.155 29.46 1.331
27.54
1.226 36.07 1.605
25.67
1.124 31.97 1.400
18.59 0.885 16.21 0.772

0.995

1.027

1.061

1.218

0.040
0.040

0.052
0.051

0.121
0.114

0.247
0.203

Table 2 Experimental and proposed results for Du and Tao tests [3]

Beam
ID
A1
A2
A3
A4
A5
A6
A7

ℓ
𝑑𝑝
19.1
19.1
19.1
19.1
19.1
19.1
19.1

Stress at ultimate in unbonded steel, MPa
test
proposed
ACI 318M-14
recordmethodology
approach
𝑒𝑠𝑡
𝑒𝑠𝑡
𝑓
𝑓𝑢𝑏
𝑢𝑏
𝑒𝑥𝑝
𝑒𝑠𝑡
𝑒𝑠𝑡
𝑓𝑢𝑏
𝑓𝑢𝑏
𝑓𝑢𝑏
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑓𝑢𝑏
𝑓𝑢𝑏
1458
1500
1.029
1213 0.832
1430
1362
0.952
1084 0.758
1176
1242
1.056
959
0.815
1465
1447
0.988
1122 0.766
1315
1303
0.991
1017 0.773
1063
1142
1.074
993
0.934
1436
1329
0.925
1230 0.857
322

test
record
𝑒𝑥𝑝

𝑀𝑢

31.1
46.8
63.6
38.3
51.2
72.4
41.5

Failure moment, kN.m
proposed
ACI 318M-14
methodology
approach
𝑒𝑠𝑡
𝑀
𝑀𝑢𝑒𝑠𝑡
𝑢
𝑀𝑢𝑒𝑠𝑡
𝑀𝑢𝑒𝑠𝑡
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑀𝑢
𝑀𝑢
30.1
0.968
24.6
0.791
41.3
0.882
36.6
0.782
54.3
0.854
50.8
0.799
34.1
0.890
29.3
0.765
46.8
0.914
43.4
0.848
67.9
0.938
66.5
0.919
39.9
0.961
37.9
0.913

SEE - Bangkok, Thailand, Nov.11-13, 2019A8
19.1 1290
1325
A919.1 1108
1099
B1
19.1 1645
1679
B2
19.1 1564
1595
B3
19.1 1361
1443
B5
19.1 1520
1538
B6
19.1 1402
1409
B7
19.1 1603
1583
B9
19.1 1346
1402
C1
19.1 1396
1423
C3
19.1 1316
1249
C7
19.1 1411
1398
C9
19.1 1109
1096
Average of
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑒𝑠𝑡
⁄𝑓𝑢𝑏
(𝑓𝑢𝑏
) or (𝑀𝑢𝑒𝑠𝑡 ⁄𝑀𝑢 )Standard of deviation (σ)
Coefficient of variation (COV)

1.027
0.992
1.021
1.020
1.060
1.012
1.005
0.988
1.042
1.019
0.950
0.991
0.988

1162
1064
1352
1221
1128
1250
1181
1422
1295
1173
969
1322
1047

0.901
0.960
0.822
0.781
0.829
0.822
0.842
0.887
0.962
0.840
0.736
0.937
0.944

59.4
102
30.3
50.4
61.0
53.4
75.8
42.5
89.7
33.6
67.3
44.6
101.0

56.2
90.3
33.5
47.3
62.8
52.5
74.3
43.9
93.5
35.9
59.5
50.5
98.0

0.946
0.886
1.106
0.938
1.030
0.983
0.980
1.033
1.042
1.068
0.884
1.132
0.970

54.1
90.0
26.8
40.4
57.6
48.1
71.4
40.7
92.4
28.6
54.2
44.3
101.6

0.911
0.882
0.884
0.802
0.944
0.901
0.942
0.958
1.030
0.851
0.805
0.993
1.006

1.007

0.850

0.970

0.886

0.038
0.038

0.071
0.084

0.078
0.080

0.079
0.089

Table 3 Experimental and proposed results for Harajli and Kanj tests [4]Beam IDℓ𝑑𝑝

Stress at ultimate in unbonded steel, MPa
test
proposed
ACI 318M-14 aprecord
methodology
proach
𝑒𝑠𝑡
𝑒𝑠𝑡
𝑓
𝑓𝑢𝑏
𝑢𝑏
𝑒𝑥𝑝
𝑒𝑠𝑡
𝑒𝑠𝑡
𝑓𝑢𝑏
𝑓𝑢𝑏
𝑓
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑢𝑏
𝑓𝑢𝑏
𝑓𝑢𝑏
1261.3 1284.6
1.018
1247.70.989
1245.6 1178.4
0.946
1238.00.994
1106.9 1155.7
1.044
1066.10.963
1068.9 1002.1
0.938
1068.91.000
1280.0 1348.7
1.054
1365.81.067
1351.7 1351.1
1.000
1366.1
1.011
1212.4 1262.0
1.041
1055.00.870
1206.9 1147.9
0.951
1046.90.867
1160.7 1178.1
1.015
1033.80.891
1127.6 1107.6
0.982
990.3
0.878
1281.3 1231.0
0.961
1224.00.955
1229.7 1218.7
0.991
1187.60.966
1217.2 1227.5
1.009
1098.80.903
1259.3 1154.6
0.917
1077.90.856
1086.2 1160.5
1.068
1057.70.974
1157.2 1124.9
0.972
1089.20.941
1400.0 1415.2
1.011
1231.50.880
1205.5 1210.7
1.004
1036.80.860
1233.1 1234.8
1.001
1014.40.823
1186.2 1169.9
0.986
1009.50.851
1200.0 1240.4
1.034
1185.80.988
1281.3 1155.4
0.901
1213.00.947
1217.2 1203.0
0.988
1140.90.937
1182.8 1161.9
0.982
1103.60.933
1120.7 1169.5
1.044
1053.20.940
1079.3 1102.9
1.022
1043.3
0.967

PP2R3-3 19.0
PP2R3-0 19.0
PP3R3-3 19.0
PP3R3-0 19.0
P1R3-319.0
P1R3-019.0
P2R3-319.0
P2R3-019.0
P3R3-319.0
P3R3-019.0
PP1R2-3 12.0
PP1R2-0 12.0
PP2R2-3 12.0
PP2R2-0 12.0
PP3R2-3 12.0
PP3R2-0 12.0
P1R2-312.0
P1R2-012.0
P2R2-312.0
P2R2-0
12.0
PP1R1-3
9.6
PP1R1-0
9.6
PP2R1-3
9.6
PP2R1-0
9.6
PP3R1-3
9.6
PP3R1-0
9.6
Average of
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑒𝑠𝑡
⁄𝑓𝑢𝑏
(𝑓𝑢𝑏
) or (𝑀𝑢𝑒𝑠𝑡 ⁄𝑀𝑢 )Standard of deviation (σ)
Coefficient of variation (COV)

0.995

0.933

0.042
0.042

0.060
0.064

323

Failure moment, kN.m
proposed
ACI 318M-14
methodology
approach
𝑀𝑢𝑒𝑠𝑡

𝑀𝑢𝑒𝑠𝑡

21.2
19.3
32.7
32.7
14.0
14.4
20.3
19.6
25.5
24.4
33.21
33.6
41.8
41.2
63.1
63.75
24.1
26.8
34.3
34.4
49.2
49.9
75.1
65.0
79.7
79.6

17.9
15.6
30.2
32.5
7.0
7.0
15.2
15.0
20.5
19.7
30.9
29.7
37.9
37.6
61.2
61.7
18.1
19.8
27.0
26.9
42.7
44.5
68.0
56.7
71.0
70.7

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 4 Experimental and proposed results for Campbell and Chouinard tests [2]

Beam
ID

ℓ
𝑑𝑝

Stress at ultimate in unbonded steel, MPa
test
proposed
ACI 318M-14
recordmethodology
approach
𝑒𝑠𝑡
𝑒𝑠𝑡
𝑓
𝑓𝑢𝑏
𝑢𝑏
𝑒𝑥𝑝
𝑒𝑠𝑡
𝑒𝑠𝑡
𝑓𝑢𝑏
𝑓𝑢𝑏
𝑓𝑢𝑏
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑓𝑢𝑏
𝑓𝑢𝑏
1476
1420
0.962
1228 0.832
1467
1411
0.962
1212 0.826
1381
1320
0.956
1194 0.865
1348
1332
0.988
1254 0.930
1274
1263
0.991
1240 0.973
1269
1223
0.964
1245 0.980

1
15
2
15
3
15
4
15
5
15
6
15
Average of
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑒𝑠𝑡
⁄𝑓𝑢𝑏
(𝑓𝑢𝑏
) or (𝑀𝑢𝑒𝑠𝑡 ⁄𝑀𝑢 )Standard of deviation (σ)
Coefficient of variation (COV)

test
record
𝑒𝑥𝑝

𝑀𝑢

45.5
63.3
81.1
98.0
105.5
120.2

Failure moment, kN.m
proposed
ACI 318M-14
methodology
approach
𝑒𝑠𝑡
𝑀
𝑀𝑢𝑒𝑠𝑡
𝑢
𝑀𝑢𝑒𝑠𝑡
𝑀𝑢𝑒𝑠𝑡
𝑒𝑥𝑝
𝑒𝑥𝑝
𝑀𝑢
𝑀𝑢
42.3
0.930
48.5
0.801
55.7
0.880
63.5
0.832
68.4
0.843
76.5
0.828
85.4
0.871
92.7
0.866
97.8
0.927
103.5
0.929
109.4
0.910
113.2
0.916

0.970

0.901

0.894

0.980

0.015
0.0156

0.070
0.077

0.034
0.038

0.049
0.050

Fig. (1) Experimental and proposed stress relationship for Tam and Pannell tests

Fig. (2) Experimental and proposed stress relationship for Du and Tao tests

Fig. (3) Experimental and proposed stress relationship for Harajli and Kanj tests

Fig. (4) Experimental and proposed stress relationship for Campbell and Chouinard tests

CONCLUSIONS

the concrete fiber located at the centroidal axis of theprestressing steel. The proposed methodology adopts
the fact that the stress in unbonded prestressing steel
is a member-dependent and considers the span-todepth ratio in a uniform manner without any limitations.

The proposed methodology described in this paper
focuses on the determination of the stress in prestressing steel at nominal flexural strength in unbonded members depending on the average strain in
324

SEE - Bangkok, Thailand, Nov.11-13, 2019[6] Mattock, A. H., J. Yamazaki, and B.T. Kattula, Comparative Study of Prestressed
Concrete Beams, With and Without Bond,ACI Journal, Vol. 68, No. 3, Feb. 1971, pp.
116-125.
[7] Mojtahedi S. and Gamble W. L., Ultimate
Steel Stresses in Unbonded Prestressed
Concrete, ASCE, V. 104, No. ST7, July
1978, pp. 1159-1165.
[8] Pannell F. N." The ultimate moment of resistance of unbonded prestressed concretebeams" Magazine of concrete research:
Vol. 21, No. 66, March 1969, pp. 43-54.
[9] Tam A. and Pannell F. N., The ultimate
moment of resistance of unbounded partially prestressed reinforced concrete beams,
Magazine of concrete research, Vol. 28,
No. 97 December 1976, pp. 203-208.
[10] Warwaruk, J., M.A. Sozen, and C.P. Siess,
Investigation of Prestressed Reinforced
Concrete for Highway Bridge, Part III:Strength and Behavior in Flexure of Prestressed Concrete Beams, University of
Illinois Engineering Experiment Station
Bulletin No. 464, Urban, III, August 1962,
pp. 1-105.

REFERENCES[1] ACI Committee 318, Building Code Requirement for Reinforced Concrete (ACI
318-2014), American
Concrete Institute,2014, pp1-506.
[2] Campbell, I.T. and Chouinard, K.I., Influence of non-prestressed reinforcement on
the strength of unbounded partially prestressed concrete members, ACI Structural
Journal, Vol.88, No.5, 1991, pp. 546-551.
[3] Du G. and X. Tao, Ultimate Stress in Unbonded Tendons of Partially Prestressed
Concrete Beams, PCI Journal, Vol. 30, No.
6, November-December, 1985, pp. 72-91.
[4] Harajli, M., and Kanj, M., Ultimate Flexural Strength of Concrete Members Prestressed with Unbonded Tendons, ACI
Structural Journal, V. 88, No. 6, Nov.-Dec.
1991, pp. 663-673.
[5] Karpenko, N.I., Mukhamediev T.A. and Petrov A.N. ,The Initial and Transformed
Stress-strain Diagrams of Steel and Concrete, Special Publication, Stress-Strain
Condition for Reinforced Concrete Construction, Reinforced Concrete ResearchCenter, Moscow, 1986, pp. 7-25.

325

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE DURABILITY OF LIME STABILIZED EXPANSIVE SOIL
Yulvi Zaika1, Eko Andi Suryo2
Engineering Faculty, University of Brawijaya, Indonesia

1,2

ABSTRACTThe failure was caused by expansive soil at the base of the structure can lead to enormous losses and soil
using additives (chemical agents) sometimes still indicate the problem of premature failure. This problem is dueto the difficulty of understanding complex reactions between clay minerals and chemical agents. The results ofthis chemical reaction will determine how substantial the swell /shrinkage reduction and strength improvement. In
this study, the effects of several treatments will be analysed on expansive soils that have been stabilised with lime,
both behaviours that will enhance and reduce their stability. Sample treatment is one way to improve the durabilityof soil mixtures, while immersion and dry-wet processes are a way to reduce durability. Strength measurements
on each treatment were tested with CBR value and measurement of swell potential was carried out by analyzingchanges in the sample volume. Dry-wet cycle treatment increases the potential for expansion even though it is still
smaller than untreated soil; in this case, it is still below 5% with three cycles and does not indicate a tendency toincrease. Lime treated expansive soil could increase durability as subgrade of pavement structure at the limit
certain time.
Keywords: Durability, Lime, Dry, Wet, Cycle.

maximum results, so further research is needed on the
durability of the lime-improved expansive soil as
subgrade of pavement structure due to environmental
conditions.
Previous studies on soil durability and additives
were carried out by [8] which analyzed the effect of
curing time on cohesive soil mixtures with lime andnatural pozzolan on shear strength which showed thatthe effect of lime was more dominant than natural
pozzolan on changes in friction angle and cohesion.
Investigated the occurrence of cracks in the soil due
to environmental changes which is one of the factors
in the occurrence of slope failure.
The researchers [18] analyzed the effect of drywet cycles on the physical and mechanical propertiesof expansive soils that were improved with 0.3%
OTAC and 6% KCL. OTAC-KCL is ameliorant thatcan be soluble in water or other solvents. The additionof these additives provided unconfined compressive
strength and reduced free swell by almost fifty
percent (55% to 25%). Strength development is
crucial in the study of strength characteristics of soils
treated with stabilizers as the structure of suchmaterials evolves with time due to continuing
hydration/pozzolanic reaction. The dry-wet cycle
process which was carried out 14 days with 1 to 4
cycles showed that even though the development still
occurred in the improved soil but it was still muchbigger than the natural expansive soil . Direct shear
test on natural soil and improved soil with dry-wet
cycle showed a decrease in parameters shear strengthwith the increase of the second dry-wet cycle of thesoil but the parameters of the shear strength of the
improved soil are still higher than the natural soil.
The improved soil with lime is considered resistant to

INTRODUCTION
The problems associated with the expansive soils
are not yet widely appreciated outside area of theoccurrence. The amount of damage caused byexpansive soil should be a warning. Several methods
can be done to build structure on it such as using deep
foundations, remove the troublesome ground andreplace it with suitable material, soil reinforcement[1], using additive material that is produced higher
strength and lower compressibility than natural soil.
Soil improvement methods are often used in roadprojects rather than using deep foundations because
they cover a large area.
The most important binder are limes [2-9]]
because it can improve expansive soil properties withincreasing strength and reduce the shrinkage
properties although there are other materials that arealso often used such as fly ash [9-11] cement [8],gypsum [12-13] or waste material such as steel slag[14], rice husk ash [15], bagasse ash [16],nanocomposite [17] or other ingredients. Someconsiderations in choosing additives include:
1. Availability of materials
2. The influence of these materials on changes in soil
properties
3. Workability
4. Costs
5. Durability
In this study, it will discuss the expansive soil withlime because of the considerations. Lime is very
widely available in Indonesia and is commonly used
as an additive soil so that it will not get difficulties in
the implementation. The thing that must be
investigated is the optimum percentage that will give326

SEE - Bangkok, Thailand, Nov.11-13, 2019

the dry-wet cycle[3] which is use to stabilize
subgrade layer [19].
MATERIAL AND MECHANISM

difference in sample height will be calculated as achange in volume and calculated as potential swell.
The carrying capacity of the soil will be measured
after dry conditions in one cycle

Material

Durability of natural soil

Expansive soil used in this study is from Ngasem
Bojonegoro village, East Java, Indonesia. This is soilthat is categorized as that is easy to swell and shrink
due to changes in water content, which causes
damage to the pavement structure in the area. Several
experiments were carried out to determine soil
characteristics, carrying capacity and swell potential.

Natural soil test result are presented in Table 1. Basedon USCS and AASHTO classifications, the soil isclassified as high plasticity clay and a poor soil typeas a road subgrade layer which the value of soil
activity (A) is very high swell potential. The value of
un-soaked California Bearing Ratio is 14.7% andsoaked CBR is 4.6% at 21,9% moisture content anddry density of 0.82 gram/cm3.

Mechanism
Table 1 Physical properties of expansive soil
Expansive soil is clay soil containing
montmorillonite minerals. This mineral structure
consists of one sheet of gibbsite, which is between thesilica sheets. Because the inter-crystal bond by the
Van Der Wall style between the silica sheets is weak
and there is a shortage of negative ions in theoctahedral so that water and other ions easily enterand release the bond. Montmorillonite crystals havevery small size and very large interest in water. Thisis the reason why this clay mineral is easy to swelland shrink due to changes in water content.
Additive substances that are mixed with soil resultin the process of exchanging alkali cations (Na+ andK+) from the soil replaced by cations from additives
so that the size of the clay grains increases(flocculation). After flocculation process occurred,pozzolanic and hydration process follows in soil
stabilization. The pozzolanic process occurs between
calcium hydroxide from soil reacting with silicates(SiO2) and aluminate (AlO3) from additives to form abinding material consisting of calcium silicate or
aluminate silicate. The reaction of Ca2 + ions withsilicates and aluminate from the surface of clay
particles forms a cemented (hydrated gel) paste thatbinds soil particles. The cementation reactions that
occur in soil mixtures with additives form new grainsthat are harder so that they are more resistant to theload given.

No
1
2
3
4
5

Parameters
Specific Gravity (Gs)
Liquid Limit (LL), %Plastic Limit (PL), %Shrinkage Limit (SL), %Plasticity Index (PI), %

Value
2,68
81.5
35.6
6.7
45.9

CBR(%)The sample height increased rapidly on the firstday and grew slowly the following day. Although thesample was air dried for 4 days but could notevaporate the absorbed water when soaked, so that thewater content after drying was still higher than before
soaking. CBR decline in the first cycle is very large
as in Figure 1. The dry-wet cycle shows a tendency to
reduce the strength of the soil until 87%.
16
14
12
10
8
6
4
2
0

0
TESTING PROGRAM AND RESULT
Durability test specified for lime stabilized soil is
specimens are compacted at OMC into molds using
either standard or modified Proctor compaction effort
immediately after mixing, placed in sealedcontainers, and then cured for 7 days. After curing,
specimens are then placed in a chamber that is
subsequently evacuated to a pressure of 24 in. Hg(11.8 psi). After that the chamber is flooded with
distilled water and specimens are allowed to soak.
Dry wet cycle is carried out in 4 days of submerged
conditions and 4 days of dry conditions. The

Fig. 1

1

2
W/D Cycles

3

4

Influence wetting-drying cycle of naturalsoil to CBR

The same phenomenon also occurs in the swell asshown in Figure 2. Because the immersion on the firstday is already very large (Figure 3), the binding ofwater to the next increment in cycles two and three
becomes insignificant. This shows the soil during thefirst rainy season every year has decreased the ability
to withstand the load and show corrugation on the327

SEE - Bangkok, Thailand, Nov.11-13, 2019road surface. If the swell potential test is obtained at
a value of 5.5%, then the wet-dry cycle turns up to
7.1%.

25
20

CBR(%)

8

Swell potensial (%)

7
6

15

y = -0.2068x2 + 2.4968x + 14.74

10

5
5

4
3

0

2

0

1

10

15

Lime (%)

0
4

Fig. 4

Changes in CBR Value based on improved
soil

Influence wettng-draing cycle of natural soil
to swell potential

The second set was tested for swell potential toanalyze the changes due to differences in the dosageof lime mixed with the soil as shown in Figure 5.
Swell potential could be reach less than 0.5% at 4%
lime.

0

Fig. 2

1

2
W/D cycles

3

6

6

5

Swell Potential (%)

Swell Potential(%)

5

4
3
2
1
0
0

1000

2000
3000
Time (minute)

4000

5
4
y = -0.0102x3 + 0.2481x2 - 2.0064x + 5.4999

3
2
1
0
0

Fig. 3 Swell potential in first cycle
Fig. 5The durability of lime improved soil

510Lime content (%)

15

Decrease in swell potential of expansive soil
due to lime

In this study soil mixtures and lime at a dosage of
4% have increased strength by 62% and reduced
swell potential by 90%. W / D testing will be carriedout.
Harichane at.al.[8] investigated effect of different
curing time for lime improved soil on shear stress.
Addition of lime has a significant effect on shear
stress particularly beyond 28 days and in samples
containing 8% lime for both grey and red soils tested.
There is a significant difference in the strength of soil
shear mixed with lime, natural pozzolana and a
combination of lime-pozzolana. The difference in thecontent of additive material other than thecharacteristics of the original soil will determine
curing time.
In this study curing time was also carried out inlime improved soil for seven days. During this time
lime and soil are expected to undergo a process offlocculation, hydration and cementation.

Local lime was used in this study as additive agent.
Thus , five different lime content of 0, 6, 8, 9, 10% by
soil weight were investigated the optimal lime content.
Optimization of lime content is needed to determine
the minimum amount of lime needed in stabilizedsoils to achieve adequate levels of rigidity towithstand environmental conditions and prevent
solubility (Figure 4).

328

SEE - Bangkok, Thailand, Nov.11-13, 2019

After treatment, the initial step of the dry-wet
cycle is carried out on the sample. The initial CBR
was 23.7% had decreased after the first wet cycle sothat its strength was reduced to 42% where there wasa decrease of up to 13.6% (Figure 6).The CBR valuesof untreated and treated samples for different wet-dry
cycle times are presented in Table 1.
However, improved soil has a limit of reliability
to environmental changes. The time needed to
produce a durable mixture is highly recommended byseveral factors such as the type of additive and thetime needed to achieve maximum strength before
being utilized, environmental changes that affect the
mixture.

bonding is not strong, so it is easily removed, so the
CBR drops.
In the early stages of adding lime will cause thehydration process of quicklime.
CaO +H2O  Ca(OH)2 + 12 kJmol-1

Mixing of soil and lime will increase Ca+2 and pH,
cation exchange modification of clay particles thatcause aggregation of clay particles. Short-term results
are improvements in workability and reduced swellpotential (also shrinkage).
Furthermore, the physic-chemical stabilization
process depends on the time of treatment. The
measure of acidity (pH) will cause the release of Si
and Al so that the reaction will occur as follows:
Si + Al + Ca + OH  CAH + CSH + CASH

Table 1 Result CBR during cyclic wetting-drying
procesType of soil

CyclesNatural soil
Improves soil

0
0
1
2
3

CBR
(%)
14.76
23.7
13.60
7.6
7.6

42.62
67.93
67.93

The treated soil is in the first submerging in water
causes a potential swell increase of up to 0.5% , thenincrease until 3% in first cycle. The following drywet cycle of two soil types showed insignificant
changes after the first cycle (Figure 7).

3.5

Swell Potential(%)

25
20
CBR(%)(2)This is the basic process of the hydro setting
reaction where the clinker reaction with water will
form a cementitious compound (CSH CASH, etc.).
The presence of some chemicals can change thereaction settings:- Sulphur lead the formation of ettringite whichcauses swelling- Nitrate causes a decrease in USCS
- Phosphate can interfere with the hydration process- Chloride accelerates hydration but leads to the salt
formation and reduces the strength- Other minerals (mica) prevent reactions and causeswelling of swelling

Strength loss(%)

Based on the Chittoori BCS at al. [20] study, all
the soils dominated by clay minerals will fail early inthe lower additive content. The content ofmontmorillonite
determinesthetechnical
characteristics of stabilized soil. Clay soils with thesame plasticity will have different properties when
given the same dose of additive. In this study, thedosage of lime was indeed under the optimum
mixture so that only 3 cycles of strength degradation
had occurred.

15
10
5

3.0
2.5
2.0
1.5
1.0
0.5
0.0

0
0

2

0

4

W/D cycles

Fig. 6(1)

1

2
W/D cycles

3

4Fig. 7 Swell potential in the wetting-drying cycle oflime improved soil

CBR value in wetting-drying cycle

Due to the subsequent dry-wet process, the soil
strength has decreased, which shows that the lime

Guney et al. [7] conducted a cyclic wetting-drying
experiment to observe the effects of lime stabilization
329

SEE - Bangkok, Thailand, Nov.11-13, 2019

on the swell potential. In that study, both potential
swelling tests and swell pressure were performed on
soil specimens that were not treated and treated withlime, subject to cyclic wetting-drying. It observed thatthe main advance of lime stabilization disappeared
after the first wetting-drying cycle, and the potential
for swelling increased for the next cycle.

Vol.29, No.4, 2011.
[5] Bell .F.G, Lime stabilization of clays minerals andsoils, Engineering Geology, Elsevier, Vol.42,
1996,pp 223-237.
[6] Calik U. and Sadoglu E., Classiﬁcation, shear
strength, and durability of expansive clayey soil
stabilized with lime and perlite, Nat Hazards , 71,
2014, pp.1289–1303.
[7] Guney, Y., Sari, D., Cetin, M., and Tuncan, M.,
Impact of cyclic wetting–drying on swelling
behaviour of lime-stabilized soil." Building andEnvironment, 42(2),2007, pp. 681-688.
[8] Harichane K., Ghrici M. and Kenai S., Effect of
curing time on shear strength of cohesive soils
stabilized with combination of lime and natural
pozzolana, International Journal of Civil
engineering, geotechnical engineering, Vol. 9, No.
2, 2011.
[9] Mir B.A., Some studies on the effect of fly ash andlime on the physical and mechanical properties
expansive clay”, IJCE, 13, 2015, pp.203- 212.
[10] Kathrik S.,Soil Stabilization by Using Fly Ash,IOSR Journal of Mechanical and Civil
Engineering (IOSR-JMCE), Vol.10, Issue 6, 2014.
[11] Zaika Y, Rachmansyah, A, 2017, The estimationof bearing capacity and swell potential of deep
soil mixing on expansive soil by small scalemodel test, International Journal of Geomate,Vol.13, Issue 38, pp.09-15.
[12] Ahmed A. and Ugai K., Environmental effects
on durability of soil stabilized with recycled
gypsum, Cold Regions Science and Technology,
Elsevier ,Vol. 66,2011, pp. 84-92.
[13] Yilmas I and Civelekoglu.I,Gypsum: An additive
for stabilization of swelling clay soils, Appliedclay science, Elsevier, 44, 2009, pp.166-172.
[14] Rahmansyah,A, Zaika. Y.Improvement ofexpansive soil of east java, Indonesia by using
industrial solid waste, Proc. Int. Conf. on
unsaturated soil UNSAT, 2014, Sydney, Australia[15] Zaika Y, Soeharjono A and Anwar R, Improving
Expansive Soil by Using Combination of Rice
Husk Ash and Fly Ash,2015, EJGE, vol. 20, no. 8,
pp. 2055 – 2063.
[16] Zaika Y and Soeharjono A, 2016, Bagasse Ash(BA) and Additive Materials treated Expansive
soil, EJGE, Vol.21, No. 20, pp. 7085-7094.
[17] Azzam W.R.,Durability of expansive soil using
advanced
nanocomposite
stabilization,
International Journal of Geomate, Vol. 7, No. 1,
2014 , pp. 927-937.
[18] Wang B.,Zhang C., Qiu X, Ji,E and Zhang,W,(2015) Research on Wetting-Drying Cycles’
Effect on the Physical and Mechanical Properties
of Expansive Soil Improved by OTAC-KCl,
Advances in Materials Science and Engineering,
2015,Hindawi Publishing Corporation.
[19] Razali N., Sa’don N.M. and Karim A.R, Strengthand durability effect on stabilized subgrade soil,

CONCLUSIONS
Natural soil is an active expansive soil with very
high swell potential which effect to pavement
structure in this area that damaged every year due tohigh rainfall. The addition of lime increases
expansive soil strength and reduces the shrinkage
properties. Improved lime soil with sufficient curing
time will have higher mechanical properties than
without curing. The environment also changes suchas changes in water content and the presence of
certain chemicals can reduce strength and increase theswelling in the soil. The durability of improved soil isdetermined by the optimum lime content, the timeneeded for maximum cementation in addition toenvironmental disturbances that can cause
degradation. The same soil can have different
durability due to different environmental changes.
Untreated specimens have poor water stability, which
will collapse after immersion in water at the firstcycle The strength reduce 83% and almost loss it insecond cycle. Although in the modified soil there wasalso a decrease in strength in the first cycle but still ina fairly good soil condition (CBR> 10%), but in thesecond cycle collapsing occurred. The same thing
happens to swell potential, although swellingincreases but is still lower than natural soil. The
collapse occurs earlier due to a low additive content.
It is recommended to increase the percentage ofadditives in modified soil.

REFERENCES[1] Parihar N.S, Shukla R.P. and Gupta A.K., Shearstrength of medium plastic expansive soil
reinforced with polyester fibers, Slovak journal ofcivil eng., Vol. 26, no.2, 2018, pp. 1-8.
[2] Addison M.B. and Polma F.A., Extending
Durability of Lime Modified Clay Subgrades
With Cement Stabilization, GSP 172 Soil
Improvement, Geo-Denver ,February 18-21, 2007
| Denver, Colorado, United States.
[3] Aldaood A., Bouaskera M. and Al-Mukhtar M. ,Impact of wetting–drying cycles on the
microstructure and mechanical properties of limestabilized gypseous soils, Engineering Geology,
Elsivier ,Vol 174, 2014,pp. 11-21.
[4] Al-Kiki I.M., Al-Atalla M.A. and Al-Zubaydi
A.H., Long term strength and durability of clayeysoil stabilized with lime, Eng. & Tech. Journal,
330

SEE - Bangkok, Thailand, Nov.11-13, 2019

Journal of Civil Engineering, Science andTechnology Vol. 7, Issue 1, 2016.
[20] Chittoori B.C.S, Puppala A.J. and Pedarla A.,
Addressing clay mineralogy effects on

performance of chemically stabilized expansive
soils subjected to seasonal wetting and drying,
Journal of geotechnical and geoevironmental
engineering, Vol. 144, Issue 1, 2018.

331

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DURABILITY OF CONCRETE CONTAINING RECYCLED
ASPHALTIC CONCRETE AGGREGATEAND HIGH CALCIUM FLY ASH
Prinya Chindaprasirt 1, Pornnapa Kasemsiri2, Sompron Leekongbub3 and Patcharapol Posi4*
Sustainable Infrastructure Research and Development Center, Department of Civil Engineering,
Faculty of Engineering, Khon Kaen University
2
Sustainable Infrastructure Research and Development Center, Department of Chemical Engineering,
Faculty of Engineering, Khon Kaen University.
3,4
Department of Civil Engineering, Faculty of Engineering, Rajamangala University of Technology Isan1

ABSTRACTIn this research, the durability of concrete containing recycled asphaltic concrete (RAC) aggregate and fly ash
were studied. The concrete was made from ordinary Portland cement (OPC), fly ash, water, sand and combinationof natural limestone and RAC aggregates. The RAC aggregate was obtained from the discarded asphaltic pavement.
After its service life, the asphaltic concrete is replaced with the new material and this results in a large amount of
discarded old asphaltic concrete. The RAC aggregate was used to replace natural limestone aggregate at the
replacement levels of 0, 10, 20, and 30 % of the total weight of aggregate. In addition, the high calcium fly ash
from Mae Moh power station in the north of Thailand was used to partially replace OPC at the dosages of 0, 20,
and 40 % by mass. The compressive strength, water absorption, porosity, flexural strength, modulus of elasticity
and resistance to sulfuric acid were tested. The results showed that concretes with 28-day compressive strengths
between 22.5 and 33.0 MPa, water absorption between 5.3-5.9 %, porosity between 12.2 and 13.5 %, flexuralstrength between 4.4 and 5.5 MPa, modulus of elasticity between 25.6 and 30.0 GPa were obtained. The
replacement levels of RAC at 10 % and fly ash at 20 % gave the optimum compressive strength and mechanicalproperties of concrete for use as pavement concrete. In addition, the using of RAC aggregate together with fly ash
in concrete work improved water absorption, porosity and sulfuric acid resistance. It has thus been shown that
RAC and high calcium fly ash could be used in the manufacturing of concrete with the emphasis on the use ofwaste material and reduction in OPC which in turn would increase the sustainability of construction industry.
Keywords: Fly ash, Concrete, Durability, Recycled asphaltic concrete, Surface abrasion

pavement. A large amount of RAP materials are
obtained from the scraping off the original pavements
to maintain the pavement level, scraping of from thebulging of original pavement due to the wheel track,or from the construction of new pathway. These RAP
materials are piled up as discarded asphalt as shownin Fig. 1. Some of this RAP material are reused bymixing with asphalt cement to repair road, or mixed
with cement to make concrete products in thepathway, such as concrete curb, concrete barrier, butthere are a lot of RAP materials waiting to be utilized.
In the construction industry, Portland cement isused as the main binding material and a large amountof cement production is thus required each year [1].
The manufacturing process involves rock blasting,digesting, conveying, burning and fine grinding. This
results in large amount of carbon dioxide emissions
and thus increases the greenhouse effect, which
affected the environment negatively [2]. Moreover,the Portland cement production process consumes
enormous energy. Previous researched had shownthat class C high calcium fly ash with some cementing

INTRODUCTION
The economic development and urban growthincrease the utilization of energy and natural
resources in the industrial, agricultural andtransportation sector. The energy consumption inindustrial sector is around 36 percent, and thetransportation sector is around 35 percent with the
majority is in the road transport (87 percent). The
consumption of energy causes air pollution andenvironmental problems,
The road transportation usually consists of good
networks and facilities. The highways in Thailand
cover a distance of over 71,470 kilometers per 2
traffic lanes and are mostly (92 percent) asphalt road.
These roads require maintenance and restoration tostay in good condition for convenience, speed andsafety. The restoration of asphalt concrete pavement
is done using the reclaim asphalt pavement (RAP).
The original pavement was recycled by mixing withcement and used for the pavement layer. The newasphalt concrete is then laid to replace the original
332

SEE - Bangkok, Thailand, Nov.11-13, 2019

property could be used successfully as partial
replacement of Portland cement [3, 4] and as starting
material in geopolymer [5].

Figure 2. RAC aggregate.
Table 1. The physical properties of materials

Figure 1. Discarded asphalt pavement storage
area.
This research, therefore, aims to investigate thereuse of RAP materials as a coarse aggregate in theconcrete mixture and also the use of high calcium fly
ash to partially replace Portland cement. The RAP
material was sorted to obtain the required size and iscalled Recycle Asphalt Concrete Aggregate (RAC
aggregate). It was used to replace natural coarse
aggregates. High calcium fly ash was also used topartially replace Portland cement to improve theconcrete quality. The suitable proportions forconcrete pavements were obtained with cost saving
due to the use of RAC aggregate and fly ash with the
reduced amount of natural aggregate and Portland
cement. It is also a conservation of the environment,
reduce the amount of waste and reduce the use ofnatural resources.
EXPERIMENTAL PROGRAM
Materials
Materials used in this research consisted ofordinary Portland cement (OPC), river sand, crushed
lime stone aggregate, water, fly ash (FA) and RAC
aggregate. The FA was a class C high calcium fromMae Moh power station in Lampang province,
northern Thailand. The RAC aggregate with theparticle size between 4.75-19.10 mm and 3.5 %asphalt was from reclaimed asphalt pavement asshown in Fig. 2. The physical properties of materials
are shown in Table 1. The morphology of FA by SEM
as shown in Fig. 3 indicated that the shape of FA wasspherical with smooth surface. The chemicalcompositions of FA are shown in Table 2. The
specific gravity of FA was 2.66 with median particle
size of 18.6 µm. The FA consisted of a high content
of 36.20% SiO2, 15.52% Al2O3, 14.25% Fe2O3, and22.57% CaO with the loss on ignition (LOI) of
0.88%. The high calcium content in fly ash gave its
cementing property. The XRD of FA as shown in Fig.
4 indicated the high amorphous content withrelatively large hump around 22-38 ᵒ2Ꝋ.

Materials

Sand

OPC

FA

RAC
agg.

Naturalcoarseagg.

Specific gravity
Median particle size(µm)
Fineness modulus

2.61

3.15

2.66

2.39

2.7

-

14.6

18.6

-

-

2.65

-

-

-

-

Unit weight (kg/m3)

1360

1440

-

1266

1598

Abrasion Loss (%)
Water absorption
(%)

-

-

-

29.5

22.4

1.17

-

-

0.36

0.46

Figure 3. The morphology of FA by SEM
Mix proportion
FA and RAC aggregate contents
To study the durability of concrete containing
recycled asphaltic concrete (RAC) aggregate andhigh calcium fly ash, the OPC was replaced with FA
at the levels of 0, 20, and 40 % by weight and thenatural lime stone aggregate was replaced with RAC
aggregate at the replacement levels of 0, 10, 20, and
30 % by weight. The compressive strength, water
absorption, porosity, modulus of elasticity, flexuralstrength and sulfuric acid resistance of concrete
containing recycled asphaltic concrete (RAC)
aggregate and FA were determined. In order to obtainadequate data, three series of mixes totaling 12 mixes
as shown in Table 3 were tested.

333

SEE - Bangkok, Thailand, Nov.11-13, 2019

S

F

CS

CCS

CS

C

F

CS

S

0

10

20

30

40

50

F

S

60

70

80

90

2 ThetaFigure 4. The XRD of FA. F-Maghemite: Fe2O3;
Fe2O3; C-Anhydrite; CS-Gypsum: CaSO4; S-Quartz:
SiO2.

Coarse
Agg.

590

1138

RAC

Water

394

-

-

213

114

213

0F - 20R

394

-

590

910

228

213

0F - 30R

394

-

590

797

341

213

20F-00R

315

79

590

1138

-

213

20F-10R

315

79

590

1024

114

213

20F-20R

315

79

590

910

228

213

20F-30R

315

79

590

797

341

213

40F-00R

236

158

590

1138

-

213

40F-10R

236

158

590

1024

114

213

40F-20R

236

158

590

910

228

213

40F-30R

236

158

590

797

341

213

The resistance to sulfuric acid
The cube specimens size 100x100x100 mm were
tested to determine the resistance to sulfuric acid inaccordance with ASTM C267-01 [10]. The reported
resistance to sulfuric acid was the average of threesamples.
RESULTS AND DISCUSSIONS
Compressive strength
The results of compressive strength of concrete
containing RAC aggregate and fly ash are shown in
Fig. 5. The compressive strength decreased withincreasing RAC aggregate content. For example, thecompressive strength at 28 days of mixes with 20 %FA by weight with 0, 10, 20, and 30 % RAC
aggregate were 32.9, 30.8, 26.7, and 25.5 MPa,
respectively.

Mix
0F - 00R

1024

Flexural strength
The prism specimens size 150x150x500 mm were
tested to determine the flexural strength in accordancewith ASTM C293-02 [9]. The reported flexuralstrength was the average of three samples.

Table 3. Mixture of concrete by weight. (kg/m3)
Fine

590

Modulus of elasticity
The cylindrical specimens size 150x300 mm were
tested to determine the modulus of elasticity inaccordance with ASTM C469/C469M-14 [8]. The
reported modulus of elasticity was the average ofthree samples.

Details of test
Compressive strength
The cylindrical specimens size 150x300 mm were
tested to determine the compressive strength inaccordance with ASTM C39/C39M-18 [6]. The
reported compressive strength was the average ofthree samples.

Agg.

-

Porosity and water absorption
The cube specimens size 100x100x100 mm were
tested to determine the porosity and water absorptionin accordance with ASTM C642-13 [7]. The reported
porosity and water absorption were the average ofthree samples.

Details of Mixing
For mixing, OPC and FA were firstly mixed
together until the mixture was homogenous. Next,
sand was added and mixed for 5 min. Next, crushed
lime stone aggregate and RAC aggregate were added
and mixed for 5 min. Finally, water was added andmixed for another 5 minutes to obtain a homogenous
mixture.
The fresh concrete was placed into 150x300 mm
cylindrical molds, 100x100x100 mm cube molds and150x150x500 mm prism molds. The specimens weredemolded at 1 day and stored in water.

FA

394

0F-00R = fly ash of 0 % and RAC aggregate of 0 %,Fine Agg. = fine aggregate, Coarse Agg. = coarse aggregate.

Table 2. Chemical composition of materials (byweight)ChemicalFA
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

Cement0F - 10R

334

SEE - Bangkok, Thailand, Nov.11-13, 2019with that of natural lime stone aggregate. This
negatively affected the aggregate bonding andreduced the strength of concrete.
With regards to the effect of fly ash content, thecompressive strength development of concrete
containing fly ash was quite good. The general trend
was that the replacement level of 20% improved thecompressive strength of the mixes. This was in linewith the reported result that normally the strength of
concrete with proper amount of fly ash could slightly
increase compared with that of normal concrete [3, 4].
The incorporation of fly ash increased the workabilityof the mix and also resulted in the increases inpozzolanic reaction and filling of the void [11, 12].
Especially when the concrete age was more than 28
days, the pozzolanic effect was more noticeable asindicated by the increases in compressive strengths at
56 and 90 days as shown in Fig. 5(c) and 5(d). For
example, the compressive strengths at 56 days ofmixes with 10 % RAC aggregate and 0, 20, and 40 %FA were 34.2, 36.6, and 32.9 MPa, respectively.

30.0
FA 0%

FA 20%

FA 40%

Comppresive strength (MPa)

25.0
20.0
15.0
10.0
5.0
0.0

RAC aggregate (%)

a.
35.0

7 days

FA 0%

FA 20%

FA 40%

Compressive strength (MPa)

30.0
25.0

20.0
15.0
10.0
5.0

Porosity and water absorption

0.0
RAC aggregate (%)

28 days

FA 0%

FA 20%FA 0%

FA 40%

5.80%

FA 40%

40.0
Compressive strength (MPa)FA 20%

6.20%

Absorption (%)

45.0

b.

35.0
30.0
25.0

5.40%

5.00%

20.0
15.0

4.60%

10.0
RAC aggregate (%)

5.0
0.0

Figure 6. Water absorption at 28 days

RAC aggregate (%)

c.

56 days
14.00%

50.0

FA 0%

FA 20%

FA 40%

45.0
40.0

Porosity (%)

Compressive strength (MPa)FA 0%

FA 20%

FA 40%

13.60%

35.0
30.0

13.20%
12.80%
12.40%

25.0
20.0

12.00%

15.0
11.60%

10.0
5.0

RAC aggregate (%)

0.0

Figure 7. Porosity at 28 days

RAC aggregate (%)

d.

90 days
The results of water absorption and porosity ofconcrete containing RAC aggregate and fly ash are
shown in Figs. 6 and 7. With regards to the effect ofcontent of fly ash, both water absorption and porosity
at 28 days increased with the increasing content of fly
ash. The use of fly ash to partially replace OPC
resulted in changes in paste content, pore size andFigure 5. Compressive strengths at 7, 28, 56 and 90
days
The RAC aggregate was partly covered withasphalt and its use thus resulted in the reduced bond
between cement paste and RAC aggregate compared
335

SEE - Bangkok, Thailand, Nov.11-13, 2019pore structure. However, the early reactions dependon OPC, as a result the pore of fly ash cement paste
was increased compared to that of the mixture
without fly ash. But the distribution of the pore was
improved because the fly ash with circular particles
made the dispersion better in cement paste. This
resulted in the smaller average size of pore withincreasing amount of fly ash [13]. This affected
directly and increased the porosity of the samples atthe early age. For example, the porosities of mixes
with 10 % RAC aggregate and 0, 20, and 40 % fly ash
were 12.88, 13.26, and 13.54 %, respectively. In
contrast, the increase in RAC aggregate improved thewater absorption characteristics and reduced theporosity of concrete. This was due to the fact that thesurface of RAC aggregate was partially coated withasphalt (Fig. 1) and this lowered its water absorption(Table 1). For example, the water absorptions of mix
with 40 % fly ash and 0, 10, 20, and 30 % RAC
aggregate were 5.91, 5.92, 5.88, and 5.66 %,respectively.

content of fly ash beyond 20 %, the flexural strengths
started to decrease. In general, the increase of flexuralstrength was due to the increase in the reaction
products from OPC and fly ash. This was associatedwith the improvement of compressive strength andmodulus of elasticity of fly ash concrete which led tothe improvement in flexural strength [3, 16]. For
example, the flexural strength at 28 days of the mixes
with 20 % RAC aggregate and 0, 20, and 40 % fly ash
were 4.66, 4.99, and 4.61 MPa, respectively. With
regards to the effect of RAC aggregate content, theflexural strength decreased with increasing RAC
aggregate content due to the increase in the amount of
weak bond between the RAC aggregate and thematrix. For example, the flexural strengths at 28 daysof mixes with 40 % FA and 0, 10, 20, and 30 % RAC
aggregate were 4.64, 4.63, 4.61, and 4.40 MPa,
respectively.
5.40

FA 0%

FA 20%

FA 40%

5.20

Flexural (MPa)5.00

Modulus of elasticity
The results of modulus of elasticity of concrete
containing RAC aggregate and fly ash are shown in
Fig. 8. The modulus of elasticity tended to decrease
with the increasing in the content of RAC aggregate
and this trend was similar to the reduction incompressive strength. For example, the modulii ofelasticity at 28 days of the 40 % fly ash mix with 0,
10, 20, and 30 % RAC aggregate were 29.20, 27.10,
26.05, and 25.65 GPa, respectively. The modulus ofelasticity is affected by the properties of aggregate,
water to binder ratio and compressive strength [14,15]. Normally, a higher value of modulus of elasticity
for a given concrete strength indicates the better
quality.

31

FA 0%

FA 20%

4.60
4.40
4.20
4.00
3.80

RAC aggregate (%)

Figure 9. Flexural strengths at 28 days
Sulfuric acid resistance
The results of weight losses in sulfuric acid ofconcrete containing RAC aggregate and fly ash are
shown in Fig. 10. All concrete specimens were
immersed in the 1 % sulfuric acid solution for 84 days
to study the durability in an acidic environment. The
results indicated that the resistance to acid increasedslightly with the increasing fly ash content, which was
in line with previously reported results [17]. The
increase in fly ash reduced the amount of calcium
hydroxide in the mix. The reduced calcium hydroxide
and the resulting calcium silicate hydrate with low
calcium made the sample more durable in the acidenvironment [17]. In addition, the acid resistance ofthe cement paste was shown to be dependent on thecontinuous pore and the acid neutralization capacityof matrix [18]. At the low content of fly ash, theweight loss was high due also to the presence of alarge amount of continuous pore in the concrete (Fig.
9a) which were conducive to the attack from sulfuric
acid. For example, the weight losses after 84 days insulfuric acid of the mixes with 10 % RAC aggregate
and 0, 20, and 40 % fly ash were 0.88, 0.84, and 0.79%, respectively. However, the increase in porosity
was associated with the pore refining resulting andFA 40%

30

Modullus of Elasticity (Gpa)

4.80

29
28
27
26
25
24

23

RAC Aggregate (%)

Figure 8. Modulus of elasticity at 28 days
Flexural strengths
The results of flexural strength of concrete
containing RAC aggregate and fly ash are shown in
Fig. 9. With regards to the effect of content of fly ash,the flexural strengths increased with the incorporationof fly ash at the 20 % replacement levels but at the336

SEE - Bangkok, Thailand, Nov.11-13, 2019the reduction in the average pore size of paste [13].
The high replacement level of fly ash also resulted in
the strength reduction. The resistance to sulfuric acidattack was, therefore, increased but only slightly due
to some of the negative effect as well.

Although the incorporation of 20% RAC resulted in aslight reduction in strength of sample, the porosity
and water absorption were reduced and this increased
the resistance to acid attack as opposed to the
reduction in strength and modulus of elasticity of thesamples.
The increase in the resistance to acid attack ofconcrete containing RAC was thus due to the reduced
porosity of the sample as a result of the presence ofasphalt adhered to the aggregate surface. But theexcessive amount of RAC aggregate at 30 % resulted
in the increased weight loss due to the adverse effecton the compressive strength.
However, the use of RAC aggregate can improvedsome of the important engineering properties
including impermeability, flexibility, and resistanceagainst erosion as also reported by other researchers
[19].

1.20
1.00

0RACA

10RACA

20RACA

30RACA

Weight loss (%)

0.80
0.60

0.40
0.20
0.00
Day

-0.20

a.

FA 0 %

CONCLUSIONS
Based on the obtained data, the following
conclusions can be drawn:
1. The replacement of natural limestone aggregatewith RAC aggregate at the level of 0-30% resulted in
the reduction in compressive strength, modulus ofelasticity and flexural strength due to the decrease in
the bonding of cement paste and aggregate as a resultof the attached asphalt at the surface of aggregate.
2. The incorporation of RAC aggregate resulted in
the improvement of water absorption, porosity andsulfuric acid resistance of concrete.
3. The weight losses from the attack of sulfuric
acid decreased and the optimum content of RAC
aggregate was 20 % replacement level. The
replacement beyond this level resulted in the highweight losses due to the reduction in the strength of
the sample.
4. The results showed that the concrete containing
10 % RAC aggregate and 20 % fly ash had 28-daycompressive strength of 31.0 MPa, flexural strengthof 5.2 MPa and modulus of elasticity of 28.6 GPawith improved water absorption, porosity anddurability in terms of acid resistance. It can be used
to make concrete pavements in areas with low andlight traffic. It can also be used to make simple
concrete structures such as concrete barrier andbarrier curb.
Moreover, it has also been shown that the use of
RAC and fly ash can increase the waste material
utilization, reduce the cement usage and increase thesustainability of construction industry.

1.20

0RACA

10RACA

20RACA

30RACA

1.00

Weight loss (%)

0.80
0.60
0.40
0.20
0.00

Day

-0.20

b.

FA 20 %

1.20
1.00

Weight loss (%)

0.80

0RACA

10RACA

20RACA

30RACA

0.60
0.40
0.20
0.00
Day

-0.20

c.

FA 40 %

Figure 10. Sulfuric acid resistance at 28 days
ACKNOWLEDGEMENT

The results also indicated that the resistance tosulfuric acid increased with the incorporation of RAC
and the optimum RAC content was 20%. The weightlosses after 84 days in sulfuric acid of the mixes with
20 % fly ash and 0, 10, 20, and 30 % RAC aggregate
were 1.11, 0.84, 0.72, and 0.87 %, respectively.

This research is financially supported by the
Faculty of Engineering, Rajamangala University ofTechnology Isan Khon Kaen Campus. The support of
the Thailand Research Fund (TRF) under the TRF

337

SEE - Bangkok, Thailand, Nov.11-13, 2019

Distinguished Research Professor Grant No.
DPG6180002 is also gratefully acknowledged here.

monolithic surfacings and polymer concretes,
Annual Book of ASTM Standard, 2012,
Vol.06.02.
[11] Chindaprasirt, P., S. Homwuttiwong, and V.
Sirivivatnanon, Influence of fly ash fineness on
strength, drying shrinkage and sulfate resistanceof blended cement mortar, Cement and Concrete
Research, Vol.34, Issue 7, 2004, pp. 1087-1092.
[12] Chindaprasirt, P., C. Jaturapitakkul, and U.
Rattanasak, Influence of fineness of rice husk ash
and additives on the properties of lightweightaggregate, Fuel, Vol.88, Issue 1, 2009, pp. 158162.
[13] Chindaprasirt, P., C. Jaturapitakkul, and T.
Sinsiri, Effect of fly ash fineness on compressive
strength and pore size of blended cement paste.
Cement and Concrete Composites, Vol.27, Issue
4, 2005, pp. 425-428.
[14] Khan, M.Z.N., et al., Mechanical properties ofambient cured high strength hybrid steel andsynthetic
fibersreinforced
geopolymer
composites. Cement and Concrete Composites,
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[15] Chi, J.M., et al., Effect of aggregate properties on
the strength and stiffness of lightweight concrete.
Cement and Concrete Composites, Vol.25, Issue
2, 2003, pp. 197-205.
[16] Phoo-ngernkham, T., et al., High calcium fly ash
geopolymer mortar containing Portland cement
for use as repair material. Construction and
Building Materials, Vol.98, 2015, pp. 428-488.
[17] Sata, V., A. Sathonsaowaphak, and P.
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geopolymer mortar to sulfate and sulfuric acidattack. Cement and Concrete Composites,
Vol.34, Issue 5, 2012, pp. 700-708.
[18] Dulsang, N., et al., Characterization of anenvironment friendly lightweight concrete
containing ethyl vinyl acetate waste. Materials &Design, Vol.96, 2016, pp. 305-356.
[19] Tajdini, M., R. Mahinroosta, and H. Taherkhani,
An investigation on the mechanical properties of
granular materials in interface with asphaltic
concrete. Construction and Building Materials,
Vol.62, 2014, pp. 85-95.

REFERENCES[1] Wongkvanklom, A., et al., Structural lightweight
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[3] Posi, P., et al., effect of fly ash fineness oncompressive, flfxural and shear strength of highstrength-high volume fly ash jointing mortar,
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fineness on the chloride penetration of concrete,
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Engineering and Applied Science Research,
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[6] ASTM C39/C39M-18, Standard test method forcompressive strength of cylindrical concrete
specimens, Annual Book of ASTM Standard,
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[7] ASTM C642-13, Standard Test Method for
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for chemical resistance of mortars, grouts, and338

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

WALKING AUTHENTICATION BASED ON POWER SPECTRUM
DENSITY OF ACCELERATION AT LUMBER PART
Masahiro Yoneda1
Department of Civil and Environmental Engineering, Kindai University

1

ABSTRACTGait analysis is used to assess and treat individuals with conditions affecting their ability to walk. It is also
commonly used in sports biomechanics to help athletes run more efficiently and to identify posture-related or
movement-related problems in people with injuries. On the other hand, a lot of gait analyses for healthy subjects
have been conducted in order to investigate the resonant vibration problem of pedestrian bridge in the bridge
engineering field. In the design of the pedestrian bridge, a dynamic walking load that acts on the bridge surface
is necessary. A major feature of gait analysis in the bridge engineering is to calculate the dynamic load factor(DLF). Therefore, in this study, for the six subjects, DLF in three directions (vertical, fore and after, lateral
directions) was calculated using the power spectrum density of the acceleration measured at lumber part. As aresult, it could be said that a walking authentication of all six subjects was able to be done correctly using theRMS 3 summed up with the root mean square (RMS) value of DLF in three directions. The calculated results
clearly demonstrated that the walking authentication using DLF was one of convenient and useful methods.
Keywords: Walking authentication, Dynamic load factor, Accelerometer, Power spectrum density

persons who do not have trouble walking. The
parameters of the subjects are shown in Table 1, but
S6 with the lowest height is a female student. The
experiment was conducted with approval from the
ethical review committee established at Graduate
School of Kindai University (3-4-1 Kowakae
Higashi-Osaka, Osaka, Japan).

INTRODUCTION
Gait analysis is utilized not only in medical fields
such as orthopedic surgery and rehabilitation but
also in form correction of athletes and is also being
conducted as a biometric identification technology
capable of identifying individuals [1],[2]. On theother hand, in the civil engineering field, a lot of gait
analyses for healthy subjects are carried out in order
to investigate the resonant vibration problem ofpedestrian bridge. A major feature of gait analysis in
the civil engineering is to calculate a dynamic
walking load that acts on the bridge surface asdynamic load factor (DLF). This DLF is obtained by
dividing the body mass acceleration a by the gravity
acceleration g, and dynamic walking load can beobtained when DLF is multiplied by the weight ofthe pedestrian [3],[4].
Evaluation of gait characteristics using DLF has
not yet been carried out in other fields including
medical field. Therefore, in this study, for the six
subjects, DLF in three directions (vertical, fore andafter, lateral directions) was calculated using thepower spectrum density of the acceleration
measured on the right lumber part in order toinvestigate the usefulness of the walking
authentication method based on DLF.

Table 1 Subject details
Subject
S1
S2
S3
S4
S5
S6

Sex
Male
Male
Male
Male
Male
FemaleHeight183 cm179 cm165 cm170 cm175 cm157 cmWeight
706 N
669 N
588 N
637 N
784 N
569 N

Experiment method
Measurement method
In healthy subjects, since there is no significant
difference in movement between the left and rightlumber part, small accelerometers were installed on
the right lumber part as shown in Photo 1. The
sampling time for the measurement was Δt = 0.005 s,
and the 10 Hz analog low-pass filter was applied toremove the high frequency component at the rightlumber part. In the experiment, the subject walked adistance of 20 m in accordance with the dial tone of
the electronic metronome (102 times / minute =1.700 Hz and 117 times / minute = 1.950 Hz). One

METHOD
Subjects
The subjects were six university students(average age: 21 years old), all of whom are healthy
339

SEE - Bangkok, Thailand, Nov.11-13, 2019

Photo 1 Setup accelerometers on a person being
tested.

Fig.1 Power spectrum density obtained by FFTanalysis.

week later after the first experiment, similar
walking experiments were also carried out for thesame subject wearing the same shoes.

Wa a sin 2 ft  W  sin 2 ftgg=W×DLF×sin2πft(1)Here, Fd is the dynamic component of the walking
load, m is the mass of the pedestrian, W is the weightof the pedestrian, g (≒9.81 m / s2) is the gravity
acceleration, and f is the pace frequency.
As described above, considering the vibration
problem of the pedestrian bridge, DLF
corresponding to the pace frequency component fw
is generally considered to be the most important.
When FFT analysis is conducted for the acceleration
measured at the right lumber part, not only the fw
component but also many frequency components
including 0.5 fw, 1.5 fw, 2 fw, 2.5 fw, 3 fw are also
observed as shown in Fig. 1. Here, the component
with ".5 fw" such as the 0.5 fw component, the 1.5 fw
component, the 2.5 fw component and the like is acomponent that is in opposite phase on the left andright. As a matter of course, these opposite phasecomponents can’t be observed if a healthy person
wears an accelerometer in the midline.
Fd  m  a sin 2 ft 

Analysis method
Spectral analysis called Fast Fourier Transform(FFT) was conducted for the acceleration data
(2,049 data from 2 seconds after start of walking)measured in the vertical, fore and after and lateral
directions of the lumber part. Since the magnitude of
the acceleration corresponding to each frequency
component can be obtained by FFT analysis, thedifference from the control person was calculated as
RMS (Root Mean Square) after obtaining the DLF
described in the next chapter for each dominantfrequency of 10 Hz or less.
EVALUATION INDICES
Walking load factor DLF in the vertical direction
When a pedestrian passes through the pedestrian
bridges, a large vibration that the user feels
uncomfortable sometimes occurs due to resonancephenomenon. Therefore, in the field of bridge
vibration engineering, a lot of research to estimate
the dynamic walking load (the load excluding thestatic weight component) focusing on the pacecomponent most related to the resonancephenomenon has been conventionally carried out.
Specifically, the method using the spectrum analysis
result is concretely described below.
The walking vertical force can be estimated asshown in equation (1) using the dynamic load factor(DLF) when the measured vertical acceleration a on
the lumbar part is assumed to be a uniform
sinusoidal wave.

Nondimensionalized acceleration in the fore andafter, and lateral directions
Many frequency components are observed in thesame way as the vertical direction when FFTanalysis is conducted for the measured accelerationin the fore and after, and lateral directions. Therefore,
the dimensionalized acceleration in both directions
can be estimated by dividing sinusoidal acceleration
amplitude a by the gravity acceleration g. Although
it is impossible to calculate the walking load bymultiplying these factors (nondimensionalized
acceleration) by the body weight of the subject, theacceleration standardized by the gravity acceleration

340

SEE - Bangkok, Thailand, Nov.11-13, 2019g is also expressed using DLF as well as verticaldirection.

Based on the experimental results mentioned
above, the DLF in three directions is obtained for all
dominant frequencies below 10 Hz. Then, thedifference between the principal and the control
person is calculated as RMS, and when the total
value RMS 3 (= RMS in the vertical direction +RMS in the fore and after direction + RMS in thelateral direction) becomes minimum, it is considered
to be walking of the same person.
RMS 3 was determined for the subject S1 andthe control person Si (i = 1, 2, ⋯ 6) including theprincipal. The results are shown in Fig.8. It can beseen from Fig.8 that S1S1 (2) represents the smallest
RMS 3 for the both pace frequencies of 1.709 Hz
and 1.953 Hz, expressing S1 (2) as the second time
result of S1. Although the estimation accuracy ishigher at the pace frequency of 1.953 Hz, it seemed
to be related to the fact that the pace of each subject
when walking at comfortable speed was all close to1.95 Hz. RMS 3 was also determined for subjects S3and S5 as the principal. The results are shown in
Figs. 9 and 10. It can be seen from these figures thatthe combination of S3S3 (2) and S5S5 (2) shows the

ANALYSIS RESULT AND CONSIDERATION
After calculating DLF in three directions for the
subject S1, the first (walking speed: 1.25 m/s) andsecond time results (one week later; walking speed:
1.27 m/s) were compared. The results are shown in
Figs. 2 to 4. Although slight differences areobserved in the DLF at the first and the second time
results even for the same subject, it can be seen fromthese figures that both results are fairly in good
agreement.
Next, focusing on subjects S1 and S2 (control),the DLF obtained from the first experimental resultsof each are compared. The results are shown in Figs.
5 to 7. It is appended that the walking speed of S2(first time experiment) was 1.42 m/s. It can be seenfrom these figures that the DLF in the fore and after,
and lateral directions clearly differ from each other,although the DLF in the vertical direction is fairly ingood agreement in both subjects S1 and S2.

Fig.2 The results of the first and second
experiments of subject S1 (Vertical direction).

Fig.3 The results of the first and second
experiments of subject S1 ( Fore and after
direction).

Fig.4 The results of the first and second
experiments of subject S1 (Lateral direction).

Fig.5 Comparison of experimental results ofsubjects S1 and S2 (Vertical direction).

341

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig.7 Comparison of experimental results ofsubjects S1 and S2 (Lateral direction).

Fig.6 Comparison of experimental results ofsubjects S1 and S2 (Fore and after direction).

Fig.9 The sum of RMS in three directions when
focusing on subject S3.

Fig.8 The sum of RMS in three directions when
focusing on subject S1.

As a result, it could be said that walking
authentication of all six subjects was able to be done
correctly using the RMS 3 summed up with the root
mean square (RMS) value of DLF in three directions.
The calculated results clearly demonstrated that thewalking authentication using DLF was one ofconvenient and useful methods.
CONCLUDING REMARKS
This
study
investigatedthewalkingauthentication method using power spectrum densityof acceleration measured at the right lumber part. As
a result, it could be said that walking authenticationof all six subjects was able to be done correctly
using the RMS 3 summed up with the root meansquare (RMS) value of DLF in three directions. The
calculated results clearly demonstrated that thewalking authentication using DLF was one ofconvenient and useful methods.
However, since comfortable walking pace isgenerally decided for each subject, DLF may change
when walking pace is different. Therefore, when
applying this method to individual walking

Fig.10 The sum of RMS in three directions when
focusing on subject S5.
minimum value.
On the other hand, although the results for the
subjects Si (i = 2, 4, 6) as the principal are omitted, it
was verified that the combination of first and second
experiments for the same subject showed thesmallest RMS 3 in all subjects.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

authentication, it seems to be necessary to prepare
some basic data in advance by changing somewalking paces.
On the other hand, there seems to be a desire forwomen to walk beautifully like a model potentially.
However, quantification of model walking has notbeen done up until now. It can be expected that the
beautiful walking style of famous models including
pace can be digitized by using DLF. So, I would liketo apply this method also to the field of walking
lessons aiming to acquire a beautiful way of walking.

[2] Imano S.,Nakamura Y.,Shiraishi Y. andTakahashi O., Personal identification method bywalking motion using wearable sensor,
Information Processing Society of Japan, Vol.25,
2015,pp.1-8 (in Japanese).
[3] Yoneda M., A simplified method to identify
human walking force based on the body response
spectrum obtained by FFT analysis，Journal ofJapan Society of Civil Engineers, Ser. A1(StructuralEngineering&
Earthquake
Engineering) ,Vol.67, No.3,2011, pp.539–544 (inJapanese).
[4] Yoneda M., Some considerations on higher
components of human walking vertical force
measured by using FFT power spectrum, Journalof Structural Engineering, Vol.59A, 2013,
pp.332-339 (in Japanese).

REFERENCES[1] Kagaya H, Watanabe , A., Matsuda F. and Kato
Y. , Simple motion analysis for ataxia patients,
The Japanese Journal of Rehabilitation Medicine,Vol.47, No.9, 2010,pp.612-614 (in Japanese).

343

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF SALT CONTENTS ON COMPRESSIVE STRENGTH OF
DMM IN SALINITY CLAY SOFT SOILS FOUNDATION IN VIET NAM

1Tran Thi Nguyen Hao 1, Tran Thi Thanh2 and Vo Phan3
Faculty of construction, University of Architechture HCM City, Vietnam;
2,3Southern Institute of Water Resources Research, Vietnam.

ABSTRACTThe deep mixing method (DMM) has been applied in many construction projects for various improvement
purposes. Can Gio is a coastal suburban district of Ho Chi Minh City, Southeast region, Vietnam. It ischaracterized by a wetland biosystem dominated by mangrove, waterlogged mud and marine shorelines. Stableconditions on construction background in the area of salinity soft soils have to consider unit weight, as soft clay
is much harder undisturbed sampling. The analysis is conducted to study the influence of salinity soft soils, waterand cement contends on Deep Mixing strength, deformability and workability. Therefore, in this paper presents
correlation between soil unit weights to resulting from CTPu have mentioned pore water pressure at the time anddeals with mechanical behavior of the Deep Mixing. The results showed that the exact value of salinity unit
weight influenced variation of the unconfined compressive strength and the wet unit weight of DMM. Relations
and nomograms linking those parameters are proposed, making the results presented directly usable for design
methods and on site applications.
Keywords: Salinity, Soft soils, Deep mixing, Unconfined compressive strength.

INTRODUCTIONSOIL CONDITIONS AT TEST SITE

Deep mixed (DMM) columns have beencommonly used as a soil-improvement technique toincrease stability and to reduce settlement ofembankment. Research on failure modes of DM
columns owing to embankment fill and surcharge
has been the subject of interest for a number ofinvestigators (Miyake 1991; Kitazume 2000; Han
2005; 2006).
The potential failure modes of DM column
include bending, inclination, shearing, rotating, soil
flowing and a combination of these modes(Kitazume and Terashi 1991; Broms 1999). Many
researchers have found that bending failure of DM
columns was more critical than the shear failure. A
centrifuge test was performed by Kitazume (2000)
and the results showed that the columns failed inbending before shear failure.
In this duty, the determined values of unit weight
for salinity clayey silt to silty clay in Can Gio can beobtained by indirectly from correlations based on the
CPTu measurement from probings at the depths
from 20 to 30m in situ. Values measured in the test
(qc, fc and u2) are valuable data for qualitative andquantitative assessment of the soft soil. In addition,
the ground improment execution was carried out by
DMM at a depth 16m below the ground surface. The
results show that the influence of salinity silty clay,
water and cement contents on unconfinedcompressive strength (UCS).

Can Gio is a coastal suburban district of Ho Chi
Minh City, Southeast region, Vietnam. It ischaracterized by a wetland biosystem dominated bymangroved, waterlogged mud and marine shorelines.
High tide brings in salt water, and when the tiderecedes solar evaporation of the seawater in the soil
leads to further increases in salinity.
The geotechnical engineer drilled five
exploratory holes with the depth of 20m at theplanned building site in “Fig. 1” to retrive soil
samples for the pre-construction lab mixing test
program. Data from the lab testing program wereused to confirm the design cement dosage and toprovide a guideline of the soilcrete UCS.

Fig.1 The pilot test in CanGio District,Vietnam.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

The first proposal for determining the unit weight on
the basis of CPT probings was presented by Lunne(1997), based on SBT zones in the classification ofobertson. Insubsequent publication Robertson andCabal (2010) updated the procedure for determining
unit weight.
TESTING PROCEDURE
The Lab Mixing Test
The designed water – ciment ratio for the cement
titious slurry was 0.7 with 220, 240 kg/m3
cementitious material.
Fig. 2 Typical CPT soil profile in Can Gio District.

Table 1 Results of 28 day UCS (MPa) laboratory
testing– Strength vs salinity contents S; ppt.

Depth; (m)The pilot test site location in Can Gio District Ho
Chi Minh City, includes four communes Binh
Khanh, Tam Thon Hiep, Ly Nhon, Long Hoa andthe town of Can Thanh. The piezocone penetration
test (CTPu) static probing is a common researchtechnique applied in identifying soil sub-base in situ.
1.20 1.40 1.60 1.80 2.00
0
S=19ppt
4
S=29ppt
8
S=27ppt
12
S=14ppt
16
20
S=7ppt24
28
32
Dimensionless soil unit weights (/W)

Soil unit weight; kN/m3

Depths

5m

8m

11m

14m

15

14
14

21

28

Depth;
7ppt
19ppt
(m)
3-4
0.91
1.14
5-6
1.15
1.25
13 - 14
1.18
1.17
Note: Cement dosage of 240 kg/m3

29ppt

0.63
1.14
1.18

0.76
0.99
1.06

Deep soil mixing is a ground improvement
technique that improves the characteristics of weaksoils by mechanically mixing them withcementitious binder, such as cement, slag, lime, etc.
To construct columns, a powerful drill advances drill
tooling with radial mixing paddles located near thebottom of the drill string. Binder is injected throughthe drill stell to thee tool as it advances and addition
soil mixing is achieved as the tool is withdrawn. The
technique has been used to increase foundation
capacity, decrease static or seismic settlement,
increase global stability, and mitigate liquefaction
potentialforplannedstructures,tanks,
embankments and levees.
Binder content of columns was pure cement, it
was designed to add 200 and 240 kg/m3.
Undisturbed sampling with coring techniqueusing core pack sampler (diameter of sample is70mm) were carried out as quality assurance test.
Undisturbed samples were taken continuously fromtop (-2.0 m) to bottom of column after a minimum
age of 7 days after installation. Then three
specimens were prepared at depths, with electric

16

7

29ppt

The Deep Mixing Method

Fig. 3 Unit weight variability depending on salinityand depth for clayey silt in Can Gio District HCMC.

17

Depth;
7ppt
19ppt
(m)
2-3
0.75
0.85
5-6
1.18
1.21
12-13
1.25
1.38
Note: Cement dosage of 220 kg/m3

35

Salt content; ppt
Fig. 4 Unit weight variability in depths dependingon salt contents.

345

SEE - Bangkok, Thailand, Nov.11-13, 2019

cutter. Specimens were wrapped in plastic film andcured in a temperature controlled box with 20 degree
Celsius until tested for 28-day UCS.

Fig. 8 Unconfined compression test.
Fig.5 DMM installation.
In addition, undisturbed samples were sunk insalinity water for over 2 years. The result shown in“Fig. 9” that disturbing the edge-to-face structure ina zone around samples, so may assess influence of
USC for DMM in salinity clay soft soils foundation.

Fig. 6. Typical plan view of the DMM.

Fig. 7

Core samples from soilcrete columns.
Fig. 9 Specimens sank in salinity water after 2 years
TEST RESULTS

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Compressive strength; MPa
0.5
1
1.5

0
2
4
6
8
10
12
14

2

0

0.5

UCS; (MPa)
1

1.5

2

0
200kg/m3

200_0.72

220kg/m3

Depth; (m)Depth; m

0240kg/m3

220_0.74240_0.7

6

8
10
12

Salt content S= 7ppt
Fig. 10 Results UCS of core soil cement; S=7ppt.

Fig. 13 Results UCS of core soil cement
before sinking.

0.00
0
2
4
6
8
10
12
14

0.50

1.00

1.50

2.00

0.00
0

200kg/m3

Depth; m

Depth; mCompressive strength; MPa

220kg/m3
240kg/m3

Depth; m

2.00

200_0.7
220_0.74240_0.7

6
10
12

Sinking sample in salinity water
Fig.14 Results UCS of core soil cement after
sinking 27 months.

Fig. 11 Results UCS of core soil cement; S= 29ppt.

0

1.50

8

Salt content; S= 29 ppt

0
2
4
6
8
10
12
14

2

UCS; (MPa)
0.50
1.00

Compressive strength; MPa
0.5
1
1.5

CONCLUSIONS
2
In this study, influence of salt contents on thesoft foundation improved by DMM was analyzed
through the exact value of salinity in depth clay soft
soil unit weight. The following conclusions can be
drawn from numerical results:
Correlation between unit weight and results
CPT of clayey silt in Can Gio district Ho Chi Minh
City. The unit weight evaluation with actual values
variability depending on salinity and depth arepresented in “Fig. 3”.
An increase of the pore fluid salinity causes a
decrease of the moisture content, decrease of theliquid limit, decrease of the compressibility. The wet
unit weight is almost within the range 14 to 16
kN/cm3. This trend is inverted with a decrease in
UCS of DMM in the case of thick clayey silt
deposits with elevated pore fluid salinity. It must be
considered that the Can Gio site could besignificantly altered by construction practices. For
instance, installation of DMM may disturb the edgeto-face structure in a zone around the columns, andthe foundation performance could be affectedaccordingly.

200kg/m3
220kg/m3
240kg/m3

Salt content S= 19ppt
Fig. 12 Results UCS of core soil cement; S= 19ppt.

347

SEE - Bangkok, Thailand, Nov.11-13, 2019[3] Robertson. P. K.; (2009) CPT-DMT Correlations,Geotechnical Journal, ASCE.
[4] Burke, G.K. and Sehn, A.L., An Analysis ofSingle axis Wet mix performance, 2005, pp. 4146.
[5] Filz, G., Adams, T., Navin, M., and Templeton,
A.E., Design of Deep Mixing for Support ofLevees and Floodwalls, 2012, pp. 89–133.

ACKNOWLEDGMENTS
Funding for this study was provided by theSouthern Institute of Water Resources Research(SIWRR) and University of Architechture HCM
City, Vietnam.The above supports and assistance are
greatly appreciated.
REFERENCES[1] Test according to ASTM 5778.
[2] Test methods: ASTM_D2166_06 .

348

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

CORRELATION BETWEEN VIBRATION SIGNALS AND SOUND
SIGNALS OF A PERSONAL CAR WITH GASOLINE ENGINESuphattharachai Chomphan, Boonthum Wongchai
Faculty of Engineering at Sriracha, Kasetsart University, Thailand

ABSTRACTIn the present time, the number of petroleum-fuel vehicles is continuously increasing despite of the arising ofelectric vehicles. Because of the environmental concerns, the EV is being developed in both of its performanceand cost reduction. However, petroleum-fuel vehicles are still popular thanks to their more economical sale prize,
low-cost maintenance, and widely after-sale services. This paper studies the correlation between the vibrationand sound signals of a personal gasoline engine car, since the important interface of the car user are theperceived vibration and sound. In the experimental design, the three vibration sensors and the condensed
microphones at different positions have been allocated systematically according to the most perception of car
users. A quantity of the engine vibration and sound signals have been measured and collected as signal databases.
The signal feature of first pitch is considered due to its indication of main engine frequency. The fast Fouriertransform (FFT) is applied the extracted the frequency spectrum of the signal in all databases. Subsequently, thefirst dominant peak occurring in the spectrum is selected and recorded for both of its frequency and its
magnitude. These attributes are then analyzed as comparison with different engine speeds. Finally, thecorrelations of these attributes between the vibration and sound signals are presented. From the proposedcorrelation function, some pairs of the signal features expose significant relationships, for example, the soundsignal at the exhaust pipe and the vibration signal at the seat when considering the magnitudes at the emerging
dominant frequencies.
Keywords: Correlation study, Vibration, Sound, Fast Fourier transform, Gasoline engine

INTRODUCTION

fault diagnosis and indication [4]. The discrete
wavelet transform was exploited efficiently with thevibration signal of the diesel engine and the gearbox
for the engine fault diagnosis [2]-[3]. The power ofsignal analysis was adaptively conducted due to its
less time consumption and low complexity [5]-[6].
Since the different temperatures of the engine
combustion make the working condition of theengine changed, the problems of LPG-installation
cause the variation in engine vibration and sound.
[7]-[10]. Consequently, the vibration and soundsignals are investigated to distinguish between the
LPG-installation engine and the normal gasoline
engine, because they are ones of importantmeasurable attributes to indicate the causes ofirregular conditions of engines [11]-[12].
A study of vibration and sound signal analysis
for a gasoline engine with LPG-installation and fault
simulations was performed recently, the findingssummarized that, LPG-installation and engine faults
cause degradations in engine efficiency which canbe concretely evidenced by using the proposed
signal processing technique [13]-[15].
The correlation of vibration and sound signal
attributes has been introduced in the study of thispaper. It is expected from the proposed approachthat some significant relations are found andNowadays, a number of alternative sources ofenergy are being developed to utilize in the industry,business, and transportation sectors. The energy
such as gasohol, biodiesel, Hydrogen, and electricity
are very dominant in the incoming future. However,the production cost of these alternative sources ofenergy is still expensive comparing with thepetroleum resources. Therefore, the gasoline anddiesel oil production are still being developed inboth the quality and the efficiency.
Investigating the reviews on the detection anddiagnosis the faults in rotating machinery, it has
been found that the mechanical vibration-based
studies have been widely conducted [1]-[3]. The
related studies are seldom applied with the gasoline
or diesel engines. The utilizations of vibration-based
techniques to these engines are considerablyburdensome due to the transient and non-stationary
nature [1]. The application of vibration signals ofengines brings about the dynamic movement of themechanical system condition. A number of powerful
signal processing techniques have been studied for
fault diagnosis [2]. The power spectrum with highorder, cepstrum, and neural network were
investigated in the specified-type induction motor
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Experimental
DesignData preparation
Experimental
Setup

Measurement ofvibration signal

Measurement ofsound signal

Vibration signal
preparation andcollection

Sound signal
preparation andcollection

Vibration signal
databaseSound signal
database

Vibration signal
feature extraction

Sound signal
feature extraction

Fig. 2 A position of the vibration sensor : the surfaceof the engine pistonsFig. 3 Two positions of the vibration sensors : thebackrest and the bottom seat of the cushion besidethe driver.
Correlation
analysis
Signal processing

Discusstion

Fig. 1 Experimental Proceduresummarized.
In this paper, the experiment is divided into
two stages including data preparation and signal
processing. At the first stage of the experiment, theexperimental setup has been performed firstly.
Subsequently the signal measurement for all
designed cases has been done. Finally the signal
preparation and collection has been conducted toconstruct the signal database. The vibration andsound signal databases have been implemented inparallel in this stage.
In the second stage of this experiment, the signal
processing has been applied. At the beginning, thesignal feature extraction has been performed. The
frequency spectrum of this prepared corresponding
signal has been conducted by using fast Fouriertransform technique. A number of frequencies at thedominant peak points in the frequency spectrum andtheir corresponding amplitudes have been extracted.
The highest peak is assumed to represent thefundamental frequency generated from the moving
machine. These features are therefore analyzed andsubsequently used in the correlation analysis. It has
been stated that the correlation analysis is tomeasure the level of correlations between
corresponding vibration and sound signals by setting
a function criteria. Finally, the discussion of thisstudy has been conducted.

Fig. 4 Connection of all sensors with the NI cards,
NI rackFig. 5 A position of the microphone : a position at
the neck of the backrest of the cushion beside thedriverFig. 6 A position of the microphone : a position
beside the front wheel with 0.5-meter far distance350

SEE - Bangkok, Thailand, Nov.11-13, 2019as depicted in Fig. 3. All vibration signal wire areconnected with the NI cards which are attached with
the NI rack as depicted in Fig. 4. The rack is also
connected to the computer which the signals are
retrieving into the Labview program.
Sound signal retrieving setup

Fig. 7 A position of the microphone : a position at
the rear of the exhaust pipe with a 45-degree angle
to that pipe and a 0.5-meter far distance

The sound signal retrieving setup is almost thesame as that of vibration signal retrieving setup. The
three positions installing the microphones areincluding a position at the neck of the backrest of thecushion beside the driver as shown in Fig. 5, a
position beside the front wheel with 0.5-meter far
distance as shown in Fig. 6, a position at the rear of
the exhaust pipe with a 45-degree angle to that pipe
and a 0.5-meter far distance as shown in Fig. 7.

MATERIAL AND METHODSIn this section, the material and the methods arepresented by using the experimental procedure as
illustrated in Fig. 1. The explanation is reviewed
step by step as follows.
Experimental Design

Measurement of vibration signal

At the beginning, the experimental design
process has been inaugurated. All experimental
equipment includes a personal gasoline engine car(Chevrolet Captiva brand with 2.4 liter engine,
Double CVC, 4 cylinders, and 16 valves), vibration
sensorsand
theiraccessories,
condensed
microphones and their complementary parts, NI cardfor interfacing with computer, and a computer for
signal processing. In parallel, these vibration andsound signal retrieving setups are designed toallocate at the specimen car simultaneously.

The vibration signals of the specimen car aremeasured at three different points as depicted in Figs.
2 and 3. The sampling frequency is at 50,000 Hz.
Ten samples with 5 seconds of the vibration signal
are measured for 6 different engine speeds of idle,
1500, 2000, 2500, 3000, and 3500 rpm, respectively.
Vibration signal preparation and collection
When the signal samples are retrieved throughLabview program, the preliminary process of signal
segmentation are conducted. The collection of signal
from all distinguished sensor positions and alldifferent engine speeds are categorized.

Data Preparation
At the data preparation, the experimental setup is
conducted to retrieve the vibration and sound signal
from the specimen car in a number of engine speeds
at the parking stage in parallel. Subsequently, themeasurement, preparation and collection, anddatabase implementation are performed respectively.

Vibration signal database
Before entering into the signal processing stage,
the database of the categorized signal is
implemented. Three subsets of categorization are
including the signals from the surface of the engine
pistons, the signals from the backrest of the cushion,and the signals from cushion seat. In each subset, thesignal portions are dividing into six groups
corresponding to each engine speeds as describedearlier.

Experimental Setup
At the experimental setup, the vibration andsound signal retrieving setups have been prepared.
Three sets of high-frequency vibration sensors andthree condensed microphones are allocated at
different positions within and nearby the car. The
corresponding signals are then transferred into theprocessing computer through a group of NI
interfacing cards.

Measurement of Sound signal
The sound signals of the specimen car aremeasured at three different points as depicted in Figs.
5-7. The sampling frequency of the sound is also set
at 50,000 Hz. Ten samples with 5 seconds of thesound signal are measured for 6 different engine
speeds as same as those of vibration signal.

Vibration signal retrieving setup
Three sets of high-frequency vibration sensors
are located at three positions including the surface ofthe engine pistons as depicted in Fig. 2, the backrestand the bottom seat of the cushion beside the driver
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Backrest

Seat

PistonBackrest

0.448

0.039
0.063
0.023

0.120
0.214
0.267

0.100

0.055
0.066
0.073

0.200

0.033
0.093
0.029

2500

0.300

0.109

2000

0.000

0.400

1500

2000

2500

3000

3500

0.080

20.000MAGNITUDE (M/S2)

61.20081.60083.0001500

60.000114.000
116.000
85.60066.00066.00063.40080.00099.20099.40084.600100.000

40.000

Piston0.500

120.000

49.80049.80050.200FREQUENCY (HZ)

140.000

Seat

0.000
3000

3500

ENGINE SPEED (RPM)

ENGINE SPEED (RPM)

Fig. 8 The emerging dominant frequencies of thevibration signal at five different engine speeds
Backrest

Front wheel

Fig. 10 The magnitudes of the FFT at the emerging
dominant frequencies of the vibration signals at fivedifferent engine speeds

Exhaust pipe
Backrest

Front wheel

Exhaust pipe

120.000

0.500

3500

3.253
0.055
0.157

1.000

0.019
0.010
1.845

3000

1.500

0.003
0.123
1.198

2500

2.000

0.061
0.006
1.116

2000

98.30098.40098.300

1500

0.000

2.500

0.005
0.006
0.936

20.0003.000

MAGNITUDE (-)

40.00065.90065.90065.90060.00081.60081.60081.60080.000115.000
115.000
115.000

3.500

100.000

50.30048.60050.300FREQUENCY (HZ)

140.000

1

2

3

4

5

0.000

ENGINE SPEED (RPM)

ENGINE SPEED (RPM)

Fig. 9 The emerging dominant frequencies of thesound signal at five different engine speeds
Sound signal preparation and collection

Fig. 11 The magnitudes of the FFT at the emerging
dominant frequencies of the sound signals at fivedifferent engine speeds

The sound signal samples are retrieved throughLabview program, and then the preliminary processof signal segmentation are also conducted. The
collection of sound signal from all three sensor
positions and all different engine speeds are also
categorized.

with all of the portions of the vibration signals for allgroups within the database. From the output
frequency spectrum, the most dominant peak
appearing the frequency domain is extracted. The
frequency and magnitude at the peak are analyzed
and used in the correlation analysis subsequently.

Sound signal databaseSound signal feature extraction

The database of the categorized sound signal is
implemented at the end of data preparation stage.
Three subsets of categorization are including thesignals from the position at the neck of the backrestof the cushion, the position beside the front wheel,
and the position at the rear of the exhaust pipe. In
each subset, the signal portions are also dividing into
six groups of different engine speeds.

The feature calculation for sound signals is assame as that of the vibration signals.
Correlation analysis
A product function in the same sense as the crosscorrelation function has been adopted. A summationof the multiplication of between two set of signal
features at all engine speeds is calculated and usedas this product function. The higher the function
value, the more the mutual relation is. The functions
are defined as follows,Signal Processing
At the signal processing, the feature extraction
and correlation analysis are performed respectively.

𝒄𝒇(𝒔𝒇𝒊 , 𝒗𝒇𝒋 ) = ∑𝑵=𝟑𝟓𝟎𝟎
𝑵=𝟏𝟓𝟎𝟎(𝒔𝒇𝒊 . 𝒗𝒇𝒋 ),(1)

Vibration signal feature extraction
where 𝑠𝑓𝑖 is the peak frequency dominated in thesound spectrum at the ith position, 𝑣𝑓𝑗 is the peak

Fast Fourier transform (FFT) has been applied
352

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 The correlation evaluation by using the
emerging dominant frequencies

frequency dominated in the vibration spectrum at thejth position, N denotes the engine speed ranging from1500 to 3500 rpm, and𝒄𝒎(𝒔𝒎𝒊 , 𝒗𝒎𝒋 ) = ∑𝑵=𝟑𝟓𝟎𝟎
𝑵=𝟏𝟓𝟎𝟎(𝒔𝒎𝒊 . 𝒗𝒎𝒋 ),(2)cf(sfi,vfj)

sf1

sf2

sf3

vf1

34709.620

34634.880

34709.620

vf236623.920

36549.200

36623.920

vf331636.100

31559.220

31636.100

where 𝑠𝑚𝑖 is the magnitude at the peak frequency
dominated in the sound spectrum at the ith
position, 𝑣𝑚𝑗 is the magnitude at the peak frequency
dominated in the vibration spectrum at the jth
position, N is the same as that of Eq.1.

Table 2 The correlation evaluation by using themagnitudes of the FFT at the emerging dominantfrequencies

Discussion

cm(smi,vmj)

sm1

sm2

sm3

vm1

0.010

0.027

0.641

vm2

0.021

0.046

1.416

vm3

0.018

0.052

1.133

The interpretation of the output correlation is
performed. Finally the discussion for all aspects has
been completed.

the FFT at the emerging dominant frequencies of thesound signals are focused, it can be explicitly
observed that those of the exhaust pipe are highest,
meanwhile those of the backrest are lowest. Last but
not least, the magnitudes tend to increase, when theengine speed is raised.

EXPERIMENTAL RESULTS
Emerging Dominant Frequency
As for the vibration signal analysis, the FFT is anefficient tool to determine the frequency spectrum.
The emerging dominant frequencies at the peak
point at five different engine speeds are extracted
and plotted in the following bar chart in Fig. 8.
Meanwhile figure 9 represents the emerging
dominant frequencies for the sound signal analysis.
From Figs. 8 and 9, it can be obvious seen thatthe emerging dominant frequencies of the vibrationand sound signals are approximately directly
proportional to the engine speeds. These emerging
frequencies reflect the fundamental frequencies of𝑖𝑵
the engine which correspond to the relation 𝑓 = 2×60,
where 𝑖 is the number of engine pistons which is 4
for this study, meanwhile 𝑁 denotes the engine
speed in rpm.

Cross Correlation Analysis
The cross correlation function are applied tomeasure the correlation between vibration and soundsignals of the specimen car. Firstly, the correlation
evaluation by using the emerging dominantfrequencies is conducted and depicted in Table 1.
Secondly, correlation evaluation by using themagnitudes of the FFT at the emerging dominantfrequencies is presented Table 2.
From Table 1, it can be noticed that correlationof the emerging dominant frequencies of thevibration signals with the emerging dominantfrequencies of the sound signals is relatively highest
at the position 2 or at the seat, meanwhile it is lowest
at the position 3 or at the piston. As for Table 2, it
can be observed that the magnitudes of the FFT at
the emerging dominant frequencies of the soundsignals with the magnitudes of the FFT at the
emerging dominant frequencies of the vibration
signals is relatively highest at the position 3 or at theexhaust pipe, meanwhile it is lowest at the position 1
or at the backrest. Moreover, the sound signal at
position 3 or the exhaust pipe and the vibration
signal at position 2 or the seat disclose the maximum
correlation function value, when considering allpairs of signals.

Magnitude of the FFT at the Emerging DominantFrequency
At the peak points of the frequency spectrum ofvibration signal, the magnitudes are extracted for all
five different engine speeds. Subsequently thecorresponding averaged values are plotted as a bar
chart and depicted in Fig. 10. Moreover, figure 11
shows the magnitudes for the sound signal.
From Fig. 10, it can be noticed that themagnitudes of the FFT at the emerging dominantfrequencies of the vibration signals are relatively
high at the engine speeds of 1500 and 3500
comparing with the other speeds. Moreover thesemagnitudes are roughly increased when the engine
speed is raised. In Fig. 11 where the magnitudes of

CONCLUSIONSThis paper proposes a study of the correlation
analysis between the vibration and sound signals of353

SEE - Bangkok, Thailand, Nov.11-13, 2019a personal gasoline engine car. Three vibration
sensors and three microphones are located at
different positions according to the most perceptionof car users. The correlations of these attributes
between the vibration and sound signal are finallypresented. FFT has been used with the vibration andsound signals. From the output frequency spectrum,
the most dominant peak appearing the frequency
domain is extracted. The frequency and magnitude
at the peak point are analyzed and used in thecorrelation analysis. From the proposed correlation
function, some pairs of the signal features reveal
significant relationships, for example, the soundsignal at the exhaust pipe and the vibration signal at
the seat when considering the magnitudes of the FFTat the emerging dominant frequencies. In the future
research, the other derivatives of the correlation
functions should be developed to obtain more
efficient indications of relationship between theconsidered signals.

[5] Chomphan S., Chaimanatsakun A., Sakornsin
R., Khumneungratavongsa S., Rattanarat K., A
Comparative Study of LPG-modified Engine
and Normal 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. 289306.
[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] 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.
[14] Chomphan S., Vibration Signal Analysis of A
Motorcycle,
International
Journalof
GEOMATE, Vol.16, Issue 56, pp. 27-32.
[15] Chomphan S., Kingrattanaset T., Boonsit S.,
Signal Analysis for LPG-modified Gasoline
Engine with Engine Faults, International Journalof GEOMATE, Vol.16, Issue 56, pp. 65-72.

ACKNOWLEDGEMENTS
The research was partly sponsored by Kasetsart
University, Faculty of Engineering at Sriracha’s
Fund.
REFERENCES[1] Yujun L., Peter W. T., Xin Y., Jianguo Y.,
EMD-based fault diagnosis for abnormal
clearance between contacting components in adiesel 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.,
Yanyang Z., Zhengjia H., Fault feature
extraction of gearbox by using over complete
rational dilation discrete wavelet transform on
signals measured from vibration sensors.
Mechanical Systems and Signal Processing, Vol.
33, Issue 11, 2012, pp. 275–298.
[4] Liang B., Iwnicki S. D., Zhao Y., Application of
power spectrum, cepstrum, higher order
spectrum and neural network analyses for
induction motor fault diagnosis. Mechanical
Systems and Signal Processing, Vol. 39, Issue
1-2, 2013, pp. 342–360.
354

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STRESS ANALYSIS OF EMBANKMENT DUE
TO DIFFERENT IN CONSTRUCTION
CONDITIONS
Shin-ichi Kanazawa1 and Satoe Suzuki2
National Institute of Technology, Fukushima College, Japan

1,2

ABSTRACTIn recent years, many examples of soil structure collapse due to heavy rainfall have occurred. Because of this,
it is urgent to establish a method to evaluate and examine long-term embankment structure quality. Japan's
conventional design method insufficiently evaluates embankments. Although this method is shifting to a
performance-based design to cope with recent abnormal weather, an effective design method has not yet been
established.
Therefore, this research performs an initial stress analysis of embankment, accounting for differences inconstruction conditions. Notable in this study, is the comparative analysis of results, considering the initial watercontent ratio, one layer of discharge thickness, rolling compaction, and other given structural conditions thatdiffered from conventional design standards. To do this, first the initial moisture content ratio was determined byreproducing the compaction by analysis. Second, based on the dynamics of unsaturated soil, the rainfall intensity
was analyzed in order to confirm the variation of the initial stress due to rainfall. Lastly, and most critically, thedynamic change in embankment performance was analytically expressed, and the optimal structural conditions ofembankment, grouped by by rainfall history, was examined.
Keywords: Embankment, Unsaturated soil, Construction condition, Compaction, Finite element analysis

INTRODUCTION

that the strength of embankment is lowered byintermittent heavy rain. The soil is composed of threephases: solid, liquid, and air. Embankment soil below
the groundwater level often exists in the unsaturated
state containing air or dissolved air. As pore airpressure changes due to rainfall infiltration, thedissolution and release of air into the liquid phaseoccurs, seeming to compress the soil volume. As aresult of not accounting for this factor, present
construction guidelines may not provide sufficientembankment drainage countermeasures for theconcentrated rain observed of late, coupled with thegiven construction compaction management.
Furthermore, the civil engineering evaluation of
performance-based design, essential to meeting therequired performance of engineered structures, is alsochanging. When an earthquake struck Hyogo
Prefecture in 1995, many buildings escaped
destruction but became unusable. This is because
performance-based design, in which the performancefor the assumed load is considered during design, was
not sufficiently implemented. Taking this type ofdisaster as an opportunity for change, structural plansand details have been developed for soil structures,shifting the field to performance-based design toensure that the required performance is satisfied
throughout the service life of the design. It is urgent
to establish the techniques that can evaluate andexamine the long-term quality of embankment
structures and what elements of performance design
will be important in the future. Based on the above,

Soil compaction tests are carried out to improve
embankment construction engineering characteristics,
such as stability and deformation. In selecting the soil
compaction level to use at a construction site, thewater ratio (optimum water ratio) is necessary. Thisis most efficiently obtained from the relationshipbetween the dry density and the water content of thesoil for compaction by changing the water content ofsoil. From this, the soil structure is constructed using
the compaction soil. In recent years, however, manycases of embankment collapse have been reported inJapan due to excessive rainfall and torrential
downpours caused by typhoons. Take for example,
the torrential rain in the northern part of Kyushu in
July 2017 and typhoon No. 18 that hit the Kanto andTohoku regions in 2015. The river embankments androads collapsed, and a landslide on the general
national highway occurred due to the record heavy
rain. At present, the mechanisms of embankment
collapse due to such natural disasters are notsufficiently clarified. According to guidelines, thestability of embankment against heavy rain is strongly
dependent on four factors: treatment of the underlying
ground, quality of embankment material, degree ofcompaction, and drainage. There are many cases
where a drainage issue, in particular, has led toembankment collapse. It is worth mentioning that theconstruction and maintenance of embankment isdeveloped based on empirical engineering rules and355

SEE - Bangkok, Thailand, Nov.11-13, 2019

this study attempted to analyze the effects of rainfall
intensity to grasp the fluctuation due to rainfall ofeach initial stress, based on the dynamics of
unsaturated soil. In addition, changes in the dynamic
behavior of the embankment were expressed
analytically, and the optimum construction condition
for embankment structure at a given to rainfall history
were investigated.

Here, nE is the shape parameter;  is thepplastic volume strain; M is the q/p’ in the limit state;'
D is the dilatancy coefficient; p sat
is the yield stressat saturation; a and ns are the parameters

representing the increase in yield stress due tounsaturation;  is the compression index; and  isthe expansion index. Equation (8) shows pore watervelocity. Equation (9) shows air velocity. Pore waterand air flow follow Darcy’s law.

RESEARCH METHOD
Mathematical model used for soil/water/air
coupled finite element analysis

vw = −k w  gradh

The finite element analysis code [1] (DACSARMP) used in this study formulates the unsaturated soil
constitutive model proposed by Ohno et al [2]. Thismodel is framed as the soil/water/air coupled problem
using the three-phase mixture theory. Equation (1)shows the effective stress. Equation (2) shows thebase stress tensor and suction stress. Equation (3)shows suction.

σ' = σσnet

net+ ps 1va = −k a  gradha , ha =(2)

Sr − Src
1 − Src(3)

velocity; k w is the hydraulic conductivity; k a is thecoefficient of air permeability; h is the total head;pneumatic head. Equations (10)-(11) show hydraulicconductivity and the coefficient of air permeability by
way of Mualem's [3] formula and the Van Genuchten[4] formula.

net

1pore water pressure; S r is the degree of saturation;is the Mualem constant;(11)

k wsat is the hydraulicair permeability in dry conditions. Equations (12)(13) show the continuous formula of pore water and
air using three-phase mixture theory.

(4)

1 + e0ares

conductivity at saturation; k ares is the coefficient ofnEp'MD  q p+ −  = 0'
 psatnE  Mp ' 

 −

) k
2m

k ra is the ratio of coefficient of air permeability; mdegree of saturation at s→∞. Equations (4), (5), (6)and (7) provide the yield function.



1

(10)

Here, k rw is the ratio of hydraulic conductivity;

S e is the effective degree of saturation; and S rc is thens(

k a = krak ares = (1 − Se ) 2 1 − Se msuction stress; pa is the pore air pressure; p w is the



)

(

2

m
1
1 

k w = krwk wsat = Se 2 1 − 1 − Se m  k wsat
Here, σ' is the effective stress tensor; σ is thebase stress tensor; 1 is the second order unit tensor;
σ is the total stress tensor; s is the suction; ps is the = exp (1 − Se ) ln a  , MD =

(9)

w

 w is the unit weight of water; and ha is the= σ − pa 1, ps = Se sf ( σ',  , p ) = MD lnpa

Here, vw is the pore water velocity; va is the air(1)

s = pa − pw , Se =(8)

nSr − S r  v + divvw = 0(5)(1 − Sr )  v + nSr − n (1 − Sr )13
p ' = σ' : 1, q =
s:s
3
2

(6)

1
s = σ' − p ' 1 = A : σ', A = I − 1  1
3

(7)

pa
− divva = 0
pa + p0(12)(13)

Here, n is porosity;  v is volumetric strain; andp0 is atmospheric pressure. The elasto-plastic
constitutive model obtained from Equation (4) and
356

SEE - Bangkok, Thailand, Nov.11-13, 2019

the equilibrium equation [Equations (12) - (13)] areformulated as the soil/water/air coupled problem.
Moisture characteristic curve used by analysis
For a soil-water characteristic curve model, amodel capable of hysteresis expression, as proposedby Kawai et al. [5], is used. In addition, to determine
the logistic curve in the case of DRY and WET,
derived from arbitrary suction and the degree ofsaturation, the logistic curve equation of Sugii andUno [6] was used. This makes it possible to grasp the
moisture conditions of sloped ground where complex
water balance occurs. Figure 1 exhibits the soil-water
characteristic curve used in this study.

Fig. 2 Loading conditions
From the compaction curve shown in Figure 3,
the optimum water content was obtained as w = 18%.
The degree of compaction was set to 95% or greater,
and the initial water content was set to three different
water content ratios: the optimum water content ± 2%
(w =16%; w = 20%) and the optimum water content(wopt).

Fig. 1 Soil water characteristic curve
Compaction analysis

Fig. 3 Compaction curve

In this study, embankment analysis considering
compaction was carried out using the unsaturated
soil/water/air coupled finite element analysis code
(DACSAR-MP). In addition, rainfall andevapotranspiration conditions, as well as different
construction conditions were applied to the analysis.
Initial stress in this study indicates the stress state atcompletion of embankment construction. Table 1
shows material parameters.

Construction analysis of embankment
Figure 4 shows the analysis mesh. The threewater content ratios obtained from Figure 3 in theprevious section were used as the initial watercontents for analyzing embankments withconstruction conditions that differed from convention.
3m
6m

Table 1 Material parameters
λ

κ

M

m

Sr0

0.13

0.013

1.33

0.8

0.15

1.0

n

nE

a

v

Gs

kw(m/day)

e0

1.0

1.3

10.0

0.33

2.7

0.01

1.0

ka(m/day) p'sat (kPa)

15m

20.0

Using these parameters, a compaction test
simulating a 13cm high × 10cm wide mold wasanalytically conducted to grasp the optimum moisture
content of sandy soil. The following are the analysis
conditions. The initial water content ratio was set tow = 10 to 28% at a 2% interval. The loading was set
at 500 kPa, and the time required for loading andunloading was set at 1 minute. Figure 2 shows theloading condition.

45m

Fig. 4 Analysis mesh
The annual rainfall history of Hikone City, Shiga
Prefecture in 2005 was used to simulate the average
rainfall in Japan. The soil-water characteristic curve
357

SEE - Bangkok, Thailand, Nov.11-13, 2019used for the embankment analysis in the previous
section was again employed. The analysis condition
was set at a rolling compaction strength of 500kPa
after a layer of 0.3m of spreading. The compaction
was reproduced by statically loading and unloadingeach layer. The plane strain analysis was carried out
on the displacement boundary with the lower end of
the foundation soil fixed vertically and horizontally.
The hydraulic boundary is set to an undrained
condition above, below, and to the left and right. The
above analysis condition is referred to as Case 1. It is
assumed to be a conventional construction method.
Case 2 is an analysis condition in which the spreading
lift of one layer is changed from 0.3m to 0.5m. In
addition, the embankment analysis was also carriedout under the conditions of Case 3, in which the
spreading lift of one layer was changed to 0.6m. The
above construction conditions used in Cases 1-3 areassumed as conventional construction conditions.
The conditions in Cases 4-6, in which only thecompaction speed was doubled, were assumed. In
addition, the construction conditions as conventional
construction are Case1 only, and Case2-Case6 change
construction conditions from the conventional
construction. Analysis was carried out considering
construction conditions for a total of 6 cases.

Fig. 6 Normal construction (Void ratio)
Comparing the results of Figures 5 and 6 shows thatthe distribution of effective stress and the void ratio
under normal construction (Case 1 through Case 3)
at the optimum moisture content (wopt = 18%)
expands at the surface of the embankment, and thevalue of the effective stress tends to decrease when
the spreading lift of one layer was 0.3m. Furthermore,as the thickness of each layer is increased from 0.3m
to 0.5m and 0.6m, it expands toward the toe of theslope, and the effective stress tended to decrease.
Since the rolling strength of compaction was unified
to 500kPa, it is thought that the rolling compaction
was not sufficiently transmitted to the soil as the
thickness of one layer gradually increased from 0.3m
to 0.5m and 0.6m. This was likely caused by thedifficulty of air discharging from the soil. Resultsfrom the embankment with water content w = 20%
show the same tendency as the embankment with the
optimum moisture content. the consolidation effect inthe embankment was demonstrated, and the partwhich shows the expansion tendency tended to be
distributed most widely as the thickness of one layer
increased. Furthermore, the effective stress ofembankment is low when the water content is 16%,
the effective stress showed low value, and the void
ratio concentrated in the embankment surface layerand showed the expansion tendency. The reason why
the effective stress tended to be low is considered tobe the decrease of suction by rainfall infiltration andthe increase of pore water pressure. Figure 7 shows
the distribution of effective stress under the shortened
construction period, and Figure 8 shows the
distribution of void ratio under the shortened
construction period.

ANALYSIS RESULTS
No large difference in stress change for thefoundation soil in any of the analytical conditions
occurred, but the stress change of the embankment
division is apparent. Figure 5 shows the effective
stress under normal construction conditions, andFigure 6 shows the void ratio, also under normal
construction conditions.

Fig. 5 Normal construction (Effective stress)

358

SEE - Bangkok, Thailand, Nov.11-13, 2019

embankment material, drainage is higher than whensilt or viscous soil are used. It is thought that thisresult is obtained because drainage water flows easily
in the embankment surface layer. In the case of theconstruction condition in which one layer’s spreading
lift was 0.3m, drainage water concentrates in the tip
due to the height of drainage. From these results, thecompaction effect is easily detected. When the
spreading lift of each layer was changed from 0.3m to
0.5m and 0.6m, the shear strain appears
predominantly inside the embankment, not in thesurface layer. Results for embankment with otherwater contents (w = 16%, w = 20%) shows the sametendency. This can be due to the fact that thecompaction effect decreases as the layer thickness
increases because the rolling compaction was kept
constant. Additionally, Figure 10 shows the
distribution of shear strain when the construction
period was shortened to half the normal time period(twice the compaction speed of normal construction).

Fig. 7 Shortening of construction period (Effective
stress)Fig. 8 Shortening of construction period (Void ratio)
The tendency mentioned above is also observed in theanalysis of a construction period shortened from theconventional time period (change of compaction
speed to twice that of normal compaction).
Figure 9 shows the distribution of shear strain
under normal construction conditions.

Fig. 10 Shortening of the construction period (Shearstrain)In comparing the results from Figures 9 and 10, thedistribution of embankment shear strain in Cases 5
and 6 is slightly larger than for embankment undernormal construction. It is likely that the rollingstrength was not well transmitted to the soil and theinside of the embankment was not sufficiently
compacted with thicknesses increasing 0.3m to 0.5m
and 0.6m when the compaction speed increased.
Figure 11 shows the critical condition judgement ratio
for normal construction.

Fig. 9 Normal construction (Shear strain)
The results of embankment analysis using the
optimum water content (w = 18%) as the initial watercontent show that shear strain predominantly occurs
from the surface to the tip of the embankment when
the thickness of one layer was 0.3 m (Case 1). Case 1
is most likely to demonstrate the compaction effect,
because the layer thickness is thinner than otherconstruction conditions. Since sand is used for the359

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 11 Normal construction (Critical condition
judgement ratio)

pronounced when the embankment was constructedwith w = 16% than with wopt = 18%, when comparing
the three water contents obtained from thecompaction analysis. Furthermore, a difference inrainfall infiltration quantity was generated by thedifferent construction conditions, as differences in theconstruction period were generated considering
multiple conditions and spreading lifts. Resultingly,
effective stress and shear strain, factors causing
embankment collapse, were greatly affected. Under
this study, the embankment analysis considereddifferences in water content and construction
conditions. However, there were no major
performance issues due to either construction
conditions or water content at the time of thecompletion of the embankment. The results of thisstudy support shifting to a performance-based design
method.
In the future, it will be possible to evaluate thelong-term quality of precision embankment structuresby numerically understanding stress change during
embankment service life.

The critical condition judgment ratio is an index
indicating the possibility of destruction of a structure
due to low stability when the maximum value exceeds
1.33. In Case 1, the results of embankment analysis
using the optimum water content as the initial watercontent shows excellent values from the surface to thetip of the embankment. The maximum value of 0.283
is not large enough to indicate destruction in theanalytical result of this study, but it does indicate that
surface layer slip may occur depending on futureenvironmental changes at the periphery of theembankment. Case 2 and Case 3 also shows a similartendency, and it seems that the toe of the embankment
slope becomes weak at the time of embankment
completion. The results of the embankment analysis
using w = 16% and w = 20% as the initial watercontent are similar to those of embankments with
optimum water content. Furthermore, Figure 12
shows the critical condition judgment ratio in the caseof shortening the construction period to half of thenormal construction time period.

REFERENCE[1] Kanazawa, S., Toyoshima, K., Kawai, K.,
Tachibana, S. and Iizuka, A.: Analysis ofmechanical behavior of compacted soil with F.E.
method, journal of JSCE, No.68 (2), pp.291-298,
2012.
[2] Ohno, S., Kawai, K. and Tachibana, S.: Elastoplastic constitutive model for unsaturated soil
applied effective degree of saturation as aparameter expressing stiffness, Journal of JSCE,
Vol.63/No.4, pp.1132-1141,2007.
[3] Mualem, Y.: A new model for predicting thehydraulic conductivity of unsaturated porous
media, Water Re-sources Research, Vol.12, No.3,
pp.514-522, 1976.
[4] Van Genuchten: A closed-form equation forpredicting hydraulic of unsaturated soils, Soil
Science Society American Journal, Vol.44,
pp.892-898, 1980.
[5] Kawai, K., Wang, W. and Iizuka, A.: The
expression of hysteresis appearing on water
characteristic curves and the change of stresses inunsaturated soils, Journal of applied mechanics,
Vol.5, pp.777-784,2002.
[6] Sugii T. and Uno T.: Modeling the New Moisture
Characteristic Curve, Journal of JSCE, pp.130-131,
1995.

Fig. 12 Shortening of the construction period (Criticalcondition judgement ratio)
A comparison between Figure 11 and Figure 12
shows that there is no significant difference inperformance even if the construction period isshortened, as the same tendency is observed in all
analytical conditions.
DISCUSSION AND CONCLUSIONS
Under the conditions of this study, thestrength of the embankment interior was more360

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

INVESTIGATION OF OPTIMAL CONTACT TYPE ULTRASONICCOLLECTING DEVICE FOR MEASURING ROUGHNESS USINGAERIAL ULTRASONIC SENSOR*Seiya Nagaoka1, Kenji Okajima1, Mohammad Raihanul Islam2, Ryoei Ito1 and Ken Watanabe3
1
Graduate school of Bioresources, Mie University, Japan2
Department of Farm Structure and Environmental Engineering, Bangladesh Agricultural
University, Bangladesh
3
Maruei Concrete Industry Co., Ltd., Japan
ABSTRACTJapan has many concrete irrigation channels with total length of about 400,000 km. Most of these channels
are now too old for continued use. The concrete surfaces of channels have been abraded by the flow of water andsand. The roughness of the concrete surface causes a decline in the water flow function. Measurement method of
the aerial ultrasonic sensor with 42 kHz is considered to be effective. In this study, we proposed optimal contact
type ultrasonic collecting device. The 2 type shape collecting devices of column and cone were used. The columnar
type were made of PVC (polyvinyl chloride) pipe. The height are 20-100 cm. The inner diagram are 20 and 30 cm.
The conical type were made of plastic traffic cone. The height are 20, 30, 40 and 50 cm. The apex angle are 16
and 20°. We considered relationship between the peak to peak by the aerial ultrasonic with collecting device andthe arithmetical mean roughness of a concrete surface. The result, relationship indicated high correlation. Except
for the columnar type of diameter 30 cm of height 20 cm, the coefficient of determination was indicated over 0.7.
Therefore, the result revealed application for roughness measurement. The gradient of the approximation line from
relationship the peak to peak and the arithmetical mean roughness was indicated measuring accuracy. The gradientof conical type tend to be larger than the columnar type. In particular, the shape of the largest gradient was theconical type of apex angle 16° of height 40cm.
Keywords: Aerial ultrasonic, Irrigation channel, Surface roughness
and the measurement surface with a laser at 0.1mm
intervals. A roughness curve is drawn from themeasured distance. Its use in agricultural channels has
been investigated, achieving high accuracy
measurements. However, it is expensive because it isan exclusive sensor design.
A moulage gauge [3] is made of a plurality ofneedles. It is pressed against the measurement surface
and copies the shape of the surface. This method uses
a cheap tool and applies a simple principle. However,analysis based on this method is time- consuming andlabor-intensive.
An aerial ultrasonic wave [4] reflected from theconcrete surface is diffusely reflected by the concretesurface roughness. Therefore, when roughness issevere, the peak-to-peak voltage is lowered.
Method of the aerial ultrasonic sensor is
economical and wide range measuring system.
However, there are some issues. Nagaoka [5]proposed that influence of windy velocity and as thewind velocity was increased, the peak to peak wasdecreased. Therefore, it is desirable to install awindshield. Okajima [4] indicated it is necessary tokeep the distance constant and set perpendicularity ofthe measurement surface and the sensor. We focusedon the contact type ultrasonic collecting device tosolve the problem. By installing the collecting device
as a measuring jig between a measurement surface

INTRODUCTION
Japan has many concrete irrigation channels,
which have a total length of about 400,000 km. These
were constructed in the 1954-1973 period of higheconomic growth. As canals become too old forcontinued use they are repaired. Hydraulicperformance malfunctions are especially consideredas the repair factor. A hydraulic performance
malfunction is evaluated using the roughness
coefficient of Manning’s equation. However,previous research has suggested that measuring theroughness coefficient is difficult. The hydraulicperformance is affected by the roughness of concretesurfaces due to abrasion. Therefore, considerable
attention has been paid to the study of measuring theroughness of concrete surfaces. Scientists haveproposed the following methods.
The sand patch test is described in ASTM E96596 Standard Test Method for Measuring Pavement
Macrotexture Depth Using a Volumetric Technique.
A quantity of sand is spread in a circular shape on themeasurement surface. The roughness of the surface isevaluated by the sand diameter of the expanded circle.
It can be used for concrete surface roughness
measurements [1].
The laser displacement meter [2] method is doneby measuring the distance between the sensor head
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SEE - Bangkok, Thailand, Nov.11-13, 2019

and a sensor, it becomes to enable a windshield andeasy installation. However, few study have focusedon an aerial ultrasonic sensor was installing withcollecting devices. The purpose of this study isapplication for roughness measurement andinvestigation optimal contact type ultrasoniccollecting device.
MATERIALS AND METHOD
Aerial Ultrasonic Sensor

Voltage V

The LV-Maxsonar-EZ1 (Maxbotic, Inc.) wasused as the aerial ultrasonic sensor. The frequency is
42 kHz. Input voltage is 5.5 V. The sensor was
designed as a distance meter. The aerial ultrasonicwave was acquired by oscilloscope. Fig. 1 shows thereflected wave from a concrete surface. We
calculated a peak to peak voltage. A peak to peak wasindicated reflection intensity.

Fig. 2 Diagram of collecting devices
Concrete samples and previous study results
The concrete samples were made for this study.
Fig. 3 shows the picture of the concrete samples. The
concrete samples are reproduced the abrasion ofirrigation channel. The dimensions were a length of
700 mm, a width of 700 mm and a height of 50 mm.
We prepared three types of roughness condition. The
first type is a smooth concrete surface. The second
and third types were rough concrete surfaces. A
roughness is quantified by an arithmetic meanroughness (Ra). An arithmetic mean roughness is
described in JIS B 0601. An arithmetic meanroughness indicates average of absolute value along
the measuring length. We used the moulage gauge as
the previous method. The length of the moulage
gauge is 150 mm. The number of steel sticks is 180,
and the measurement interval is 0.8 mm. Fig. 4 showsa sample graph of an arithmetical mean roughness.
The f (x) is transcribed a roughness curve of a concretesurface by the moulage gauge. The Y (x) is a liner
approximation that is calculated by the f (x). The Ra is
calculated integral value of | f (x) - Y (x) | from 0 to ldivided by length of the moulage gauge. We
measured four directions for each measuring point.
The Fig. 5 shows the result of the arithmetical meanroughness. The arithmetical mean roughness wasused the average value of four directions. The averagevalue of 9 points of the first type was 0.0 mm, thesecond type was 0.32 mm, and the third type was
1.11 mm. The third type has a variation of roughness.

Peak to peak

Reflected wave

Time ms

Fig. 1 Sample of reflected ULTRASONIC wave
Contact type ultrasonic collecting devices
The contact type ultrasonic collecting devices
were used shape of column and cone. The Fig. 2
shows diagram of the collecting devices. The
columnar type were made of PVC (polyvinyl
chloride) pipe. The inner diagram are 20 and 30 cm.
The height of diagram 20 cm are 20, 30, 40, 50, 60,
70, 80, 90 and 100 cm. The height of diagram 30 cm
are 20, 30, 40 and 50. The conical type were made ofplastic traffic cone. The height are 20, 30, 40 and
50 cm. The apex angle are 16 and 20°.

Fig. 3 Picture of concrete samples (first, Ra: 0.04, second, Ra: 0.32, third, Ra: 1.11)
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SEE - Bangkok, Thailand, Nov.11-13, 2019

collecting device becomes heavier in proportion as
the measurement distance becomes longer, therefore
we consider up to 50 cm.
The Fig. 8, 9 shows result of columnar type ofdiameter 20 and 30 cm. This peak to peak is 9 points
in Fig. 5. The dispersion of the peak to peak waslarger in the second type concrete sample than in thefirst type. Therefore the third type has variation inroughness, the peak to peak has variation. The peak
to peak was decreased as the roughness was increased
at all height. As the roughness increase, the differencein the peak to peak due to the height tended todecrease, that is, the gradient of approximate line
became gradually decrease. The Fig. 8, 9 shows thepeak to peak of height 20 was the smallest value.
The Fig. 10, 11 shows the result of conical type of
apex angle 16 and 20°. The graph shape of conicaltype is similar to the columnar type. The peak to peakof the conical type tended to be larger than the peak
to peak of columnar type. As the roughness increased,
the peak to peak decreased at all height. As theroughness increased, the difference in the peak topeak due to the height tended to decrease. The Fig. 10,
11 shows the peak to peak of height 50 was thesmallest value.
The Fig. 7-11 revealed all collecting devices could
be application for roughness measurement. The Table
1 shows the coefficient of determination. The
coefficient of determination was calculated from theapproximate straight line. The example is shown in
Fig. 8 of H30. Except for the column30 of H20, thecoefficient of determination was showed high value
over 0.7. When collecting devices was set H40, thecoefficient of determination was indicated over 0.9.
This result was revealed that almost collecting
devices applicate roughness measurement with highaccuracy.

y

𝒇(𝒙)

l

𝑌(𝑥)

𝑅𝑎
mu

x

0

The length of the moulage gauge (mm)Fig. 4 Sample graph of arithmetical mean roughness
1.4
1.2

Ra mm

1.0
0.8
0.6
0.4
0.2
0.0
1

2

3

4

5

6

7

8

9

Points〇Ra：0.0 △Ra：0.32 □Ra：1.14

Fig. 5 Result of arithmetical mean roughness
RESULTS AND DISCUSSApplication for roughness measurement
We investigated the relationship between the peak
to peak and the arithmetic mean roughness (Ra) by.
The peak to peak was acquired by the aerial ultrasonicwith the collecting devices. The Ra was acquired by
the moulage gauge. We measured 3 concrete samples
and 9 points in shown Fig. 3. The Fig. 6 shows thestate of experiment.
The Fig. 7 shows the result of the columnar typeof diameter 20 cm. This peak to peak is an average of
9 measuring points. The standard deviation was
showed by the error bar. The peak to peak wasdecreased as the roughness was increased at all.
Except for 20 cm, the peak to peak of Ra 0.0 mm wasdecreased from 30 to 60 cm and similarly wasdecreased from 70 to 100 cm. Ihara [6], the reflection
intensity due to irregular reflection can be evaluatedby the Kirchhoff model. This model indicates thatreflected wave intensity decreased due to theroughness of the concrete surface. The results in Fig.
7 showed a similar phenomenon. Therefore, thisdevice of columnar type of diameter 20 cm wasrevealed application for roughness measurement. The

Fig. 6 Picture of experiment by aerial ultrasonic363

SEE - Bangkok, Thailand, Nov.11-13, 2019

1,600

H20
H50
H80

1,400

H30
H60
H90

2,500

H40
H70
H100

H20

H30

H40

H50

1

1.2

2,000

Peak to peak mV

Peak to peak mV

1,200
1,000
800
600

1,500

1,000

400
500
200
0

0
0

0.2

0.4

0.6

0.8

1

1.2

1.4

0

0.2

0.4

0.6
0.8
Ra mm

Ra mm

Fig. 7 Relationship between peak to peak and Ra bycolumnar type of diameter 20 cm

Fig. 10 Relationship between peak to peak and Ra
by conical type of apex angle 16°

2,500

2,500

H20

H30

H40

H50

H20

H30

H40

H50

1

1.2

2,000

Peak to peak mV

Peak to peak mV

2,000

1,500
H30: y = -698.37x + 1420.3
R² = 0.94
1,000

1,500

1,000

500

500

0

0
0

0.2

0.4

0.6
0.8
Ra mm

1

1.2

1.4

0

Fig. 8 Relationship between peak to peak and Ra bycolumnar type of diameter 20 cm

0.2

0.4

0.6
0.8
Ra mm

1.4

Fig. 11 Relationship between peak to peak and Ra
by conical type of apex angle 20°

2,500

Table 1 Coefficient of determination
H20

H30

H40

Column20

Column30

cone16cone20

H20

0.77

0.46

0.82

0.86

H30

0.94

0.79

0.95

0.93

H40

0.90

0.91

0.92

0.98

H50

0.87

0.86

0.95

0.92

H50

2,000

Peak to peak mV

1.4

1,500

Investigation of optimal collecting device

1,000

The Fig. 7-11 and Table 1 revealed all collecting
devices could be application for roughness
measurement. The relationship the peak to peak andthe roughness are highly correlated by approximate
line. For example in columnar type of diameter 20 cm
height 30 cm, the approximate line was “y = 698.37x + 1420.3”. In order to consider the optimalcollecting device, we focus on the absolute value ofgradient and the intercept of the approximate line.

500

0
0

0.2

0.4

0.6
0.8
Ra mm

1

1.2

1.4

Fig. 9 Relationship between peak to peak and Ra bycolumnar type of diameter 30 cm

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The gradient affects the measurement accuracy. Ad
the gradient is larger, the accuracy is higher. Theintercept influences the sound collecting effect ofultrasonic.
The Fig. 12 shows the absolute value of gradientby collecting devices. The gradient of the conicaltype was relatively larger than the columnar type. The
largest gradient was the conical type of apex angle
16° of height 40 cm. The peak of the gradient bycolumnar type of diameter 20 cm was height 30 cm.
The peak of the gradient by columnar type ofdiameter 30 cm was height 50 cm. Therefore, when
the diameter of collecting device is spread, the peakof gradient tends to shift to higher height of collecting
device. The conical type became similar results. The
peak of the gradient in apex angle 16° was 30 cm. The
peak of the gradient in apex angle 20° was 40 cm.
When the apex angle of collecting device is spread,the peak of gradient tends to shift to higher height ofcollecting device.
The Fig. 13 shows the intercept by collecting
devices. The intercept of conical type was relatively
larger than the columnar type. Except for height
50 cm, the graph shape of intercept became close to
the result of the gradient. The sound collecting effectand the gradient had high correlation. Therefore, acollecting device with high sound collecting effects
tends to be a collecting device with high accuracy.
In this study case, the optimal collecting device
was the conical type of apex angle 16° of height
40 cm.

larger than the columnar type. Except for height
50 cm, the intercept became close to the result of thegradient. In this study case, the optimal collecting
device was the conical type of apex angle 16° ofheight 40 cm. However, if the sensor characteristics
change, the optimal shape of collecting device alsochange. Further studies are needed in order to adapt
to various sensor characteristics.

CONCLUSION

intercept mV

SEE - Bangkok, Thailand, Nov.11-13, 2019

1,000

column20cm
cone16°column30cm
cone20°

Gradient mV

800
600
400
200
0
50

40
30
Height cm

20

Fig. 12 Gradient of approximate line by collecting
devicescolumn20cm
cone16°

2500

column30cm
cone20°2000This study carried out to investigate the optimal
contact type ultrasonic collecting device. By
installing this device as a measuring jig between themeasurement surface and the sensor, it becomes toenable the windshield and easy installation. We
studied application for roughness measurement andinvestigation optimal contact type ultrasoniccollecting device.
The peak to peak was decreased as the roughness
was increased at all collecting devices. All collecting
devices could be application for roughness
measurement. It was found that the coefficient ofdetermination of between the peak to peak and the Ra
was high value. Except for the column30 of H20, thecoefficient of determination was indicated over 0.7.
When collecting devices was set H40, the coefficientof determination was indicated over 0.9 for allcollecting devices.
In order to consider the optimal contact typeultrasonic collecting device, we focus on the absolutevalue of gradient and intercept of the approximate
straight line. The gradient of conical type wasrelatively larger than the columnar type. The largest
gradient was the conical type of apex angle 16° ofheight 40. The intercept of conical type was relatively

1500
1000
500
0
50

40
Height cm

30

20

Fig. 13 Intercept of approximate line by collecting
devices

REFERENCE[1] ASTM E 2380, Standard test method formeasuring pavement texture drainage using an
outflow meter, West Conshohocken (PA)ASTM International, 2005.
[2] Asano I., Tokashiki M., Mori M. and Nishihara
M. , Development of Erosion Monitoring System
on Laser Displacement Meter for Cementitious
Surface Coating Method, Irrigation, Drainage
and Rural Engineering, Vol. 82, No. 5, 2014, pp.
285-296.
365

SEE - Bangkok, Thailand, Nov.11-13, 2019[3] Kitamura K., Honma S. and Kato T.,
Quantitative Evaluation for Forecast of Irrigation
Canal Abrasion, Irrigation, Drainage and RuralEngineering, Vol. 76, No. 9, 2008, pp. 823-828.
[4] Okajima K., Nagaoka S., Ishiguro S., Ito R,
Watanabe K and Ito T, Measurement of theRoghness of the Concrete Surface by the Peak to
Peak Value of the Aerial Ultrasonic Wave,
Irrigation, Drainage and Rural Engineering, Vol.
84, No. 3, 2016, pp. 233-240.
[5] Nagaoka S., Okajima K., Ito R., Raihanul. I. M,

Watanabe K. and Ito T., Influence of Wind
Velocity on Measurement of Concrete Surface
Roughness Using Aerial Ultrasonic Sensor,
Irrigation, Drainage and Rural Engineering, Vol.
86, No. 2, 2017, pp. 197-204[6] Ihara I. and Sukmana. D. D., Surface Roughness
Characterization through the Use of Diffuse
Componentof
Scattered
Air-Coupled
Ultrasound” The Japan Society for Precision
Engineering, Vol. 74, No. 7, 2008, pp. 691-695.

366

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

Experimental Investigation of Multi-axial MechanicalBehavior of Rubber Materials for Base-Isolated Bridges
Hiromichi Narita1, Junji Yoshida2, and Kouichi Takeya3
Faculty of Engineering, University of Yamanashi, Japan;
2,3Faculty of Engineering, Graduate School, University of Yamanashi, Japan.
1

ABSTRACT
Civil engineering structures representing road bridges frequently use laminated rubber bearings for seismic
isolation. In recent earthquakes, there have been damages of the bearings in some bridges. In order to investigate
behavior of those bridges during the earthquakes and causes of the damage of the bearings, an accurate
constitutive model of rubber is required. However, mechanical properties of the rubber such as stress-strain
relations under multi-axial deformation is not generally open to the public.
This research provides sufficient material test data for accurately modeling the rubber. Three types of material
tests are done. The first one is dynamic simple shear test under multi-axial deformation with several loading
frequencies. The experimental results show that the influence of strain amplitudes on stress-strain relation issignificant, and that the influence of the loading frequencies is very small. The second one is tensile andcompressive test of a thin rubber sheet, which is adhered to plates in upper and lower plane, in order toinvestigate relation between volumetric deformation and hydro-static pressure of the rubber. The third one isstatic tensile test. In the test, uniaxial and equi-biaxial tensile test were carried out under quasi-static loading
condition, and relations between stretch and nominal stress are obtained. Using these data, we would be able toidentify material constants of complex constitutive models, such as visco-elastic damage model and visco-elastoplastic damage model.
Keywords: Rubber materials, laminated rubber bearings, Base-isolated bridges, stress-strain relations

INTRODUCTION
The 1995 Kobe Earthquake triggered an increase inearthquake countermeasures such as laminatedrubber bearings for seismic isolation. With theincrease of countermeasures, a large number oflaminated rubber bearings have been used in civilengineering structures representing road bridges.
However, in the 2011 off the Pacific coast of Tohoku
earthquake and the 2016 Kumamoto earthquake,some damages were found in rubber bearings of roadbridges. In order to investigate the cause of thedamages, it is necessary to approximate the behaviorof those bearings with using the accurate constitutive
model [1] for the rubbers. However, mechanicalproperties of those rubbers, which are necessary formodeling, have not been published and, therefore, it
is difficult to precisely trace behavior of the devices
during the earthquakes by numerical simulation.
In this research, the mechanical properties ofrubber material for base-isolated bridges are
examined in detail by several loading experiments,

which are required in simulations using accurate
constitutive models [2],[3].
MATERIAL TESTING OVERVIEW
We picked up a popular natural rubber material forlaminated rubber bearings of base-isolated bridges,
and three types of loading experiments wereconducted for the rubber: dynamic simple shear test,
tensile and compressive test of a constrained rubber
layer, and standard static tensile tests. In thefollowing part of the paper, those tests are called
simply as shear test, constrained tensile/compressive
test, and static tensile test, respectively.
Shear test
In the shear test, the effects of strain levels,
frequencies, and loading paths to stress-strain
relations were investigated. For this test, wedeveloped a loading machine, which can givearbitrary dynamic displacements to specimens
simultaneously in the tri-axial directions.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Touch panel

3-axis load cell

X axisUpper fixed plate

Machine operation button
Z axisSpecimens attachment

Data input/output terminal(a) body

Loading board(b) control system(c) loading board

Fig.1 Dynamic triaxial loading machine
EXPERIMENTAL METHODS
Loading machine

Y axisIn this sub-section, the loading machines of eachtest is explained.
We developed a dynamic tri-axial loading machinefor the shear test and the constrained
tensile/compressive test. Fig.1 shows the outline of
the machine. As shown in the figure, three actuators
can control the displacements of the central lower
plate according to signals given from outside. The
maximum stroke is 20 [mm] in the two horizontal
directions (X and Y axis), and 50 [mm] in the verticaldirection (Z axis). The most characteristic feature of
the machine is the maximum speed of the loading.
The machine has the ability to perform a sine wave
excitation at a frequency of 100 [Hz] with anamplitude of 0.1 [mm] in both X and Y directions.
Fig.2 shows a biaxial loading machine employed
for the static tensile test. This machine can givearbitrary two directional displacements for a sheettype specimen, which is grabbed at the center of themachine. The maximum stroke is 360 [mm] in thehorizontal X direction and 240 [mm] in the horizontal
Y direction. The maximum velocity and load are 20[mm/s] and 2000 [N], respectively.

X axisFig.2 Biaxial tensile testing machine
Constrained tensile/compressive test
In the constrained tensile and compressive test, aspecimen is a thin circular rubber layer sandwichedby steel plates. In the test, the upper plate is fixed,
while cyclic displacements with several small
amplitudes are given to the lower plate. In spite of thesmall displacement, the corresponding load is not sosmall, because high hydrostatic pressure is generated
at the central part of the rubber layer, due to slightcompressibility of the rubber.
It is noted that those experimental results would
need a comparison with its numerical simulation by,
for example, FEM, in order to identify material
constants related to volumetric deformation.
Therefore, in the strict sense, this is not a material test,
since deformation of the test is not uniform.

Specimens
The specimens for the shear test and theconstrained tensile / compressive test are bothcylindrical, and they are adhered to two steel plates
by vulcanization. Drawings of those specimens areshown in Fig3.
In the static tensile test, we employ two types of
specimens. One is a dumbbell shape specimen for theuniaxial tensile test and, the other is a square thinsheet for the biaxial tensile test. Both specimens aredesigned to have different thickness at a part of theedges, at which the machine can tightly grab. Detailed
size of those specimens are shown in Fig4.

Static tensile tests
It is known that parameters of even some simple
constitutive models for rubber, such as MooneyRivlin model or Ogden model [1], can not be
identified only from results of uniaxial tensile tests,
because some parameters have little sensitivity touniaxial tensile deformation.
Therefore, in the static tension tests, two types oftension tests are conducted. One is a standard uniaxial
tension test to grasp the static behavior in a large
strain range of 500% or more. Another is an equibiaxial tensile test to investigate the coupled effect of
deformation in two directions.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

45mm
45mm
30mm
30mm

Upper steel plate
鋼板
RubberUpper鋼板
steel plate

1.7mm
1.7mm

3.7mm
3.7mm

ゴム層
rubberLower
steel plate
ゴム層

Lower steel plate(a) a specimen for the shear test(b) a specimen for the constrained tensile / compressive test

Fig.3 Drawing of the specimens for the shear test and the constrained tensile / compressive test

Point of view

Plan view
R=2.6 quarter arc

Plan view

Cross section
Cross section from point of view(a) A specimen for the uniaxial tensile test(b) A specimen for the equi-biaxial tensile test

Fig.4 Size of the specimens for the static tensile tests
Table.1 Detailed loading conditions for each test
Loading
directions
Uniaxialshear test
Constrained
tensile test
Constrained
compressive test
Static tensile test

BiaxialInput wave
Sine wave
8-shape, circle,
square path

Amplitude(strain/displacement)
25.50.100.150.200.250[%]

0.25,0.50,1,2,4[Hz]25.50.100.150.200[%]

0.25,0.50,1,2,4[Hz]frequency

Uniaxial

Sine wave

0.05-1.0[mm]1[Hz]Uniaxial

Sine wave

0.05-0.25[mm]1[Hz]Uniaxial
BiaxialTriangle wave
Triangle wave

100-750[%]
100-300[%]

0.02[Hz]0.02[Hz]

MATERIAL TEST RESULTS ANDDISCUSSION

Experimental methods
In each test, cyclic sinusoidal displacement of morethan three cycles is given to the specimen at different
amplitudes and different frequencies. Detailed
loading conditions of each test are summarized intable.1.

Shear test
Fig.5 shows a comparison of stress-strain relations
at different strains. The shape of hysteretic loops atload reversal points becomes sharp as the amplitude

369

1.5

2

1

0.25[Hz]
1[Hz]
4[Hz]

2

shear stress [N/mm ]3

2

Shear stress [N/mm ]SEE - Bangkok, Thailand, Nov.11-13, 2019

1
0
-1

0.5
0
-0.5
-1

-2
-3
-300

-200

-100

0

100

200

-1.5
-100

300

-50

Fig.5 A comparison of stress-strain relations at
frequency 1 [Hz]

1.5
2

1
0.5
0

-0.5

-100

-1

-200 -1000100
200Shear strain in X direction [%]

1
0.5
0
-0.5
-1

-2
-200 -150 -100 -50-2-200 -150 -100 -50 0 50 100 150 200
Shear strain[%](a) 8-shaped path

Horizontal one direction
8-shaped route

-1.5

-1.5

-200

100

2
Horizontal one direction
8-shaped routeX

Shear stress [N/mm ]2

Shear stress [N/mm ]Shear strain in Y direction [%]

200

0

50

Fig.6 A comparison of stress-strain relations at
strain 100 [%]

2
1.5

100

0
shear strain [%]Shear strain [%]050

100 150 200

Shear strain [%](b) X direction(c) Y direction

Fig.7 Stress-strain relationships in the shear test
8000

1000
0

6000

Stress[N]Stress[N]

-1000

4000
2000

-2000
-3000
-4000
-5000

0

-6000

-2000

0

0.05

0.1

0.15

-7000

0.2

Displacement[mm]

-1

-0.8

-0.6

-0.4

-0.2

0

Displacement[mm]Fig.8 A result of the constrained compressive test

Fig.9 A results of the constrained tensile test

increases. It is clear from this fact that the amplitude
has a large effect on the stress-strain relationship.
Fig.6 shows a comparison of stress-strain relations at
different loading frequencies. From Fig.6, hysteretic
loops at different frequencies seem to be similar.
Consequently, it is found that the influence of thefrequency on the stress-strain relationship is small.
Fig.7 shows a stress-strain relation (in the X
direction) of the 8-shaped bi-directional path, incomparison with the one in the unidirectional loading.

The graph shows that the shape of the hysteretic
loops is significantly different from the one inunidirectional loading. From this fact, it is understoodthat the hysteretic loops are affected by coupling
effects of bidirectional deformation. Similar results
are observed in the circular and square paths. In thispaper, the 8-shaped path is taken as an example oftwo-directional loading paths.

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25

8

Nominal stress X
Nominal stress Y

2Nominal stress [N/mm ]30

2Nominal stress [N/mm ]SEE - Bangkok, Thailand, Nov.11-13, 2019

20
15
10
5
0

6
4
2
0

-2

-5
1

2

3

4

5

6

7

8

1

1.5

2

2.5

3

Stretch ratio

Stretch ratio(a) uniaxial tensile test(b) equi-biaxial tensile test

Fig.10 Results of the static tensile test
constrained tensile test became highly nonlinear,
especially in the large deformation range.
In the standard static tensile test, cyclic stressstrain relations in several large strain levels are
obtained in the uniaxial and biaxial deformation cases.
From those experimental data, it is expected that
we could identify parameters even for complex
constitutive models, such as visco-elastic damage
models [2] or visco-plastic damage models [3].

Constrained tensile/compressive test
Compressive test
The result of the compressive test is shown in Fig.8.
The figure indicates that the load-displacement
relations were almost elastic. This fact shows that a
relation between shrinking deformation and hydrostatic pressure might be elastic.
Tensile test
A result of the tensile test is shown in Fig.9. The
figure indicates that when deformation is very small,load-displacement relations are almost elastic.
However, when the deformation exceeds a limit value,
the relations suddenly become nonlinear andirreversible. From this fact, it is supposed that a
relation between dilational deformation and hydrostatic pressure would be nonlinear and irreversible.

ACKNOWLEDGEMENTS
The specimens used in the material tests are
manufactured and provided by the Japan Rubber
Bearing Association. We extend our most sincere
thanks.
REFERENCES[1] Holzapfel, G. A.: Nonlinear Solid Mechanics – A
Continuum Approach for Engineering, Wiley,
2000.
[2] Simo, J. C.: On a fully three-dimensional finitestrain viscoelastic damage model: formulation andcomputational aspect, Computer Methods in
Applied Mechanics and Engineering, Vol.60,
pp.153-173,1987.
[3] Miehe, C. and Keck, J.: Superimposed finite
elastic- viscoelastic-plastoelastic stress responsewith damage in filled rubbery polymers.
Experiments,
modeling
andalgorithmic
implementation, Journal of the Mechanics andPhysics of Solids, Vol.48, pp.323-365, 2000.
[4] Treloar, L. R. G: The Physics of Rubber Elasticity.
3rd ed., Oxford University Press, 1975.

Static tensile tests
Those standard tensile tests were done for
capturing static uniaxial and biaxial stress-strain
relations in various strain ranges. Some examples of
the results are shown in Fig.10 as relations between
nominal stress and stretch in various strain ranges.
The Fig.10 shows typical mechanical properties ofrubbers, such as Mullins’ effect, hardening, and smallenergy absorption by hysteresis loops [4].
CONCLUSION
In this study, we conducted a variety of material
tests required for identifying parameters of complex
constitutive models of rubber materials.
From the dynamic simple shear test, it is found thatthe effect of the frequency on stress-strain relations issmall, while the effect of the strain amplitude is large.
From the constrained compressive test of rubber
layer, it is found that load-displacement relations arealmost elastic. On the other hand, the relations in the371

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

HIGHLY ACCURATE ESTIMATION OF DAILY SUSPENDED
SEDIMENT LOAD USING MULTIVARIATE HYDROLOGICAL
Phakawat LAMCHUAN, Adichai PORNPROMMIN, Jiramate CHANGKLOM
Department of Water Resources Engineering, Faculty of Engineering, Kasetsart University, Thailand

ABSTRACT
Sediment rating curves (SRCs) have been applied to estimate daily suspended sediment load (Q s) worldwide
because of its simplicity. In this method, a current Qs was estimated by a power function of a sole variable, acurrent daily water discharge at the same measurement station. However, many studies found that its accuracy is
not very high. In this study, we developed a new approach to estimate Q s using multivariate hydrological data at
the same station and other upstream stations. Using correlation analysis, the additional variables were selected
such as upstream water discharges, rainfall at the current or antecedent day. Therefore, spatial and temporalvariability was simply considered in our new approach. Then, five methods, a multiple linear regression (MLR),a multiple nonlinear regression (SLR, QLR, and PLR) and an artificial neural network model (ANNs), were applied.
The comparison between the SRC method and our new five methods were done using the Q s data at threemeasurement stations in three basins of Thailand between 2000 and 2017. The results showed that our new
approach (SLR, QLR, PLR, and ANNs) except MLR gave better satisfaction with the observed data than the
traditional SRC method. ANN estimated Qs with the highest accuracy (the R2 and EI of 0.96 and 0.96, respectively)
while SRC gave the lowest accuracy (the R2 and EI of 0.89 and 0.71, respectively). Thus, the more complexity ofthe model structure and the consideration of the spatial and temporal variability can provide a higher accurate
estimation of Qs.
Keywords: Suspended sediment load, Artificial neural networks (ANNs), Sediment Rating Curve, Multiple Linear
Regressions, Multiple Non-Linear Regressions

and Bauder [1] studied 60 months of record from the
Red River, Texas, USA, was found between rating
curve derived load estimates and the measured values
for seven sub-periods. The errors for the individual
periods varied between -20 and +14.8% while theerror for the total period was only +1.5 per cent.
Many researchers have proposed other methods toestimate suspended sediment load instead of SRC.
Jain [2] showed that the artificial neural networks(ANNs) method provided the results much better than
SRC at Mississippi River, USA. Kumar et al. [3]studied suspended sediment load at Kopili Riverbasin, India. They used a machine learning approachto construct six models and found that the least squaresupport vector regression (LS-SVR) and ANNs
provided the best satisfactory. In their model, rainfall
was included and gave a better accuracy. Melesse etal. [4] predicted suspended sediment load of threemajor rivers (Mississippi, Missouri and Rio Grande)
in USA using four models. From their results, ANNs
again provided the highest accuracy for both daily
and weekly simulations.
In previous studies, water discharge and sedimentload at the same station and rainfall were used as
independent variables to build models to estimate
suspended sediment load. However, there were no
studies using hydrological data of upstream
measurement stations to estimate suspended sediment

INTRODUCTION
Sediment load data is useful for the design of areservoir storage. Before initiating any water resource
projects, we must know water discharge and sedimentload to estimate dead storage, useful storage andsurcharge of a reservoir. However, it is difficult tomeasure sediment load daily. Thus, it is common to
calculate sediment load using a relationship withwater discharge or other hydrological data. Since
sediment load is critical to indicate the lifespan of areservoir, the underestimation of sediment load
results in insufficient volume of dead storage and,
consequently, a rapidly decrease of reservoir capacity
while the overestimation will lead to higher
construction and management costs. Therefore, it isimportant to determine suspended sediment load
accurately.
The measurement of suspended sediment load
consumes more time and costs higher than other typesof hydrological data. Thus, in Thailand, suspended
sediment load at one station is measured
approximately 8-20 times per year. These data areused to estimate two parameters in the traditional
sediment rating curve (SRC) equation in the form of
the power function of water discharge at the same
station. Although the SRC is very simple and depends
on a sole variable, its accuracy is not high. Campbell
372

SEE - Bangkok, Thailand, Nov.11-13, 2019load. In this study, we investigated the significance of
upstream water discharge in estimating sediment load.
Five mathematical rainfall-runoff-sediment models
were tested and their performances were discussed
and compared with the traditional SRC.

where a and b are coefficients obtained byregression. Qs is suspended sediment load (Tons/day)and Qw is the discharge (m3/s).

STUDY AREA

Model input for the estimation for the suspended
sediment load are P1, P21, P67, and R070391. Thereare 371 data sets in the period 2000-2017.
The cross-correlation between the various input
variables are presented in Table 1. It indicated theoutput variable SP1, t has a strong correlation with
input variables QP1, t, QP21, t, QP67, t, and R070391, t-2

Input data selection

Figure 1 shows a map of the study area of 6,350
km2 which includes P1, P21, P67, and R070391. P1
is a discharge and suspended sediment station locatedat 18o 47' 09" N and 99o 00' 29" E flow into the Ping
Basin in Thailand. P21 and P67 are the discharge
station located at 19o 01' 11" N, 98o 57' 42" E and 18o
55' 29" N, 98o 56' 34" E respectively. R070391 is arainfall station located at 19o 05' 09" N and 98o 45
29" E.

Table 1 Correlation matrix of input variables
QP1, t QP21, t QP67, t R t-2
SP1, t
QP1, t1.00
QP21, t0.85
1.00
QP67, t
0.97
0.80
1.00
Rt-2
0.50
0.49
0.46 1.00
SP1, t0.85
0.65
0.90 0.44 1.00
Note: R t-2 = R070391, t-2
From Table 1, we selected the input data in the
study according to the equation.
𝑺𝑷𝟏,𝒕 = 𝒇(𝑸𝑷𝟏,𝒕 , 𝑸𝑷𝟐𝟏,𝒕 , 𝑸𝑷𝟔𝟕,𝒕 , 𝑹𝒕−𝟐 )(2)Model Training and Testing
It is common on several studies to use 70% of thedata for training and 30% for testing and validation of
the model (The 70-30). Due to the limitations of thedata collection, the suspended sediment load isobserved at least 6 times a month on a random basis.
This study focuses on developing models to estimate
high value suspended sediment load to ensure that it
can be used to estimate accurately.
High values of suspended sediment load do notoccur often and do not occur throughout the whole
data set. If we selected the 70-30, those high values
would be missing for the test data set. Hence, we
decided to use 50% of the date for training and 50%
for testing.

Fig. 1 Map of the study area
METHODOLOGY

Sliding Window Validation

Sediment Rating Curve

This study has been validated for the reliability ofdata for all of the models by using window sliding
validation. A model is trained using a training
window and applied on the testing window tocompute the performance for the first run. For the
next run, the training window is slide to a new set oftraining records and the process is repeated until all
the training windows are used. [7] In this study
divided whole data were 2 set data (Initial 50% and

The maximum sediment concentration may notcoincide with the flood peak and may either precedeor lag behind the maximum water discharge. [5]The Sediment rating curve is a non-linear
relationship between the water discharge andsuspended sediment load. [6] SRC is expressed as:𝑏
𝑄𝑠 = 𝑎. 𝑄𝑤

(1)

373

SEE - Bangkok, Thailand, Nov.11-13, 2019

, where 𝒂, 𝒃, 𝒄 and 𝒅 are the regression
coefficients.
Quadratic linear regression (QLR)

Second window 50%) then sliding window 1 iteration
per data set. This process repeated until the numberof iteration equal to the total amount of whole data.
The process of sliding window is shown in Fig. 2

The QLR equation can be written as
𝑺𝑷𝟏,𝒕 = 𝒂𝟏 + 𝒂𝟐 𝑸𝑷𝟏,𝒕 + 𝒂𝟑 𝑸𝑷𝟐𝟏,𝒕 + 𝒂𝟒 𝑸𝑷𝟔𝟕,𝒕 +𝒃𝟏 𝑸𝑷𝟏,𝒕 𝟐 + 𝒃𝟐 𝑸𝑷𝟐𝟏,𝒕 𝟐 + 𝒃𝟑 𝑸𝑷𝟔𝟕,𝒕 𝟐(5), where 𝒂𝟏 , 𝒂𝟐 , 𝒂𝟑 , 𝒂𝟒 , 𝒃𝟏 , 𝒃𝟐 and 𝒃𝟑 are theregression coefficients.
Power linear regression (PLR)
The PLR equation can be written as

Fig. 2Sliding window validation process

𝑺𝑷𝟏,𝒕 = 𝒂. 𝑸𝑷𝟏,𝒕 𝒃 . 𝑸𝑷𝟐𝟏,𝒕 𝒄 . 𝑸𝑷𝟔𝟕,𝒕 𝒅(6)Performance Evaluation of Various Models
where 𝒂, 𝒃, 𝒄,
coefficients.

The data sets were divided into 2 groups, one fortraining and the other testing. Four indices are used todetermine model performance which are thecoefficient of determination (R2), the root meansquares of errors (RMSE), the mean absolute
percentage error (MAPE), Nash–Sutcliffe coefficient
(EI).

and

𝒅 are

the

regression

Artificial neural networks (ANNs) overview
The Artificial neural networks consist of threelayers of the node: Input layer, Hidden layer, and
Output layer. The data from the input layer was
calculated and passed through the transform function
from the hidden layer to the output layer. The
principal learning process of the model is changing
the weight value of each connection to adjust theresults of the model to be as close to the true value as
possible by the back-propagation method.
The theory of ANNs has been described in several
papers, this study is described here as briefly. The
numbers of hidden layer were found using trial andMultiple linear regression (MLR)
Multiple linear regressions (MLR) analysis was
performed on the same data set to estimate sedimentload and compare the results with output from the
SRC model. The MLR equation is defined as:
𝑺𝑷𝟏,𝒕 = 𝒂 + 𝒃𝑸𝑷𝟏,𝒕 + 𝒄𝑸𝑷𝟐𝟏,𝒕 + 𝒅𝑸𝑷𝟔𝟕,𝒕(3), where 𝒂, 𝒃, 𝒄 and 𝒅 are the regression
coefficients.
Multiple Non-linear regression (MNLR)
Various forms of non-linear equations are used for
regression to compare the ability to estimate thesuspended sediment load. This study uses three formsof multiple non-linear equations i.e. Squared linear
regression (SLR), Quadratic linear regression (QLR),
and Power linear regression (PLR).
Squared linear regression (SLR)The SLR equation can be written as
𝑺𝑷𝟏,𝒕 = 𝒂 + 𝒃𝑸𝑷𝟏,𝒕 𝟐 + 𝒄𝑸𝑷𝟐𝟏,𝒕 𝟐 + 𝒅𝑸𝑷𝟔𝟕,𝒕 𝟐
(4)

374

Fig. 3 Workflow for thewhole process ofinvestigation

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Results of Sliding window validation 50-50 of MLR, SLR, QLR, PLR, and ANNs 371 Days
Input Variables

R2 avg
0.81
0.94
0.89
0.91
0.87
R2 avg
0.78
0.94
0.90
0.89
0.88

Model
MLR
SLR
QLR
PLR
ANNs
Model
MLR
SLR
QLR
PLR
ANNs

𝑺𝑷𝟏,𝒕 = 𝒇(𝑸𝑷𝟏,𝒕 , 𝑸𝑷𝟐𝟏,𝒕 , 𝑸𝑷𝟔𝟕,𝒕 , 𝑹𝒕−𝟐 )Input Variables

𝑺𝑷𝟏,𝒕 = 𝒇(𝑸𝑷𝟏,𝒕 , 𝑸𝑷𝟐𝟏,𝒕 , 𝑸𝑷𝟔𝟕,𝒕 )RMSE avg
3003
1960
2518
3958
1765
RMSE avg
3227
2013
2624
4280
1657

MAPE avg
165
217
189
80
402
MAPE avg
1427
204
207
80
438

Table 3 Results of SRC, MLR, SLR, QLR, PLR, and ANNs during testing period 185 Days (50% of all Data)
Input Variables

Model

R2

RMSE

MAPE

EI

𝑺𝑷𝟏,𝒕 = 𝒇(𝑸𝑷𝟏,𝒕 )

SRC

0.89

1980

150

0.71

𝑺𝑷𝟏,𝒕 = 𝒇(𝑸𝑷𝟏,𝒕 , 𝑸𝑷𝟐𝟏,𝒕 , 𝑸𝑷𝟔𝟕,𝒕 )

MLR
SLR
QLR
PLR
ANNs

0.70
0.96
0.95
0.91
0.96

2493
800
866
1553
769

3107
588
192
138
207

0.54
0.95
0.94
0.82
0.96

error method. The subsampling of all the data fortraining and validation was conducted using thefunction ‘divideblock’ of MATLAB.

only by using the data in 2000-2005, 2007-2010(186 data sets) for the training period, the equation
was Qs = 2.0259Qw1.4856 to be used in the testing
period. Although the SRC provides good results(R2 = 0.89, RMSE = 1980, MAPE = 150, EI = 0.71)
from Fig. 4(a), it can be seen that SRC was unable toestimate the high sediment at all peaks suspended
sediment load and also it underestimates low values
suspended sediment load.
The MLR provided the regression coefficients a0(constant), a1, a2, a3, and a4 during training period
are found to be -1971.25, -75.74 and 138.72,
respectively. The Observed and estimated suspended
sediment graph is shown in Fig. 4(b). It was foundthat the MLR model performs poorly on estimation ofsuspended sediment load. The performance indices ofthe MLR were R2 = 0.70, RMSE = 2493, MAPE =3107, EI = 0.54 respectively.
The performance of the SLR model was also
evaluated and presented in Table 3. It provided ahighly of EI = 0.95 because it can capture almost
every peak of suspended sediment load but it
provided too high estimation for the low suspended
sediments Moreover, it was shown that the SLR isunable to estimate the low suspended sediments. The
estimates for the low sediments are found to bearound 400 tons/day. It was shown that the SLR
cannot estimate for the low suspended sediments.
The QLR model was found to be relatively
accurate. During the testing period, the values of R2,

RESULT AND DISSCUSSIONS
The results of the sliding window validation are
shown in Table 2. The SLR model performed better
than other models (R2 avg = 0.94, RMSE avg = 1960,
MAPE avg = 217) but other models provided
satisfactory model performance as well.
The Rainfall data has been removed from thetesting data because it provided correlation withsuspended sediment lowest (0.44) as shown in
Table 1. Also, we have compared estimation
performance on all model with and without therainfall data and the estimation performance isindifference. Therefore, the input data remained only
the discharge data (QP1 , t, QP2 1 , t, QP6 7 , t). All
performance indices, except for the MAPE, areindifferent whether the model contains rainfall data asa predictor variable or not (as shown in table 2).
In addition, the process of the sliding window
validation verified that the selected data in this study
can be used to further divide the training period andthe testing period.
The results of SRC, MLR, SLR, QLR, PLR, andANNs during the testing period is shown in Table 3.
The result from SRC has derived from therelationship between the discharge (m3/s) andsuspended sediment load (Tons/day) at station P1
375

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 4 Estimation results of various model (a) The SRC, (b) The linear (MLR), (c) The squared linear (SLR),(d) The quadratic (QLR), (e) The power (PLR) and (f) The ANNs.
of R2, RMSE, MAPE, EI of the PLR model were
found 0.91, 1553,138, 0.82 respectively.
The ANNs model presented in Fig. 4(f), it can beobserved that the model converges well and tends tocapture almost all the peaks. The values of RMSE,
MAPE of the ANNs model were found 769 and 206
respectively, compared with the RMSE, MAPE of the
QLR model (866 and 193) it was found that the ANNsmodel provides and accurate prediction on high valueof suspended sediment load. The errors are less thanthose obtained from the QLR.

RMSE, MAPE, EI were found to be 0.95, 866, 193
and 0.94, respectively. From Fig. 4(d), it was foundthat the QLR captured every suspended sediment load
peak accurately including the low suspended
sediment load. The error suspended sediment load isshown in Fig. 4(d). and it was found that errors are
relatively low.
The PLR model provided similar level of accuracy
to the SRC. In comparison of both models, the SRC
generated suspended sediment from only one variable(discharge at P1) but PLR model consists of 3variables (discharge at P1, P21, and P67). The values
376

SEE - Bangkok, Thailand, Nov.11-13, 2019

CONCLUSIONS

the Management (SENSWAT) Kasetsart University
and Mr.Wachira Surin, Irrigation Engineer of theSmart Operation Center (SWOC) for helpful
suggestion and constructive comments.

According to our investigations, we firstly
found that rain data has very little impact on theestimation of the suspended sediments. Therefore, we
decided to take the rain data out for the testingprocess. From the testing results, The ANNs model,
the SLR model, the QLR model, and the PLR model
provided better estimation results than using sediment
rating curves (SRC; the traditional method), given the
input data from nearby stations together.
However, it was found that the MLR model is
not a suitable model for this estimation as most of theestimates are negative (72.97%). The SLR model
estimates well on high values of suspended sediment
but provides too high estimation for the lowsuspended sediments. Although the SLR model canestimate suspended sediment as accurate as theANNs, it has the highest errors in the low suspended
sediment compared to other models.
The QLR model provides a lower EI value thanthe SLR model but can estimate the suspended
sediment well throughout the testing period .
It is clear that the QLR model provides lower RMSE
and MAPE values than the SLR.
The PLR model fails to estimate peaks
suspended sediment accurately, and also it
underestimates low values suspended sediment. The
estimation of suspended sediment loads is significant
for water resource projects, for example, dam
reservoir constructions.
The results of this study show that mathematicalmodels such as Multi-linear regression, Multi nonlinear regression, and ANNs can be used on
multivariate Hydrological data to estimate thesuspended sediment load.

REFERENCES[1] Campbell, F. B. and Bauder, H. A. 1940
A rating-curve method for determining siltdischarge of streams. Trans. Amer. Geophys. Un.
21, 603-607.
[2] Jain, S.K., 2001. Development of integrated
sediment rating curves using ANNs. J.Hydral.
Eng. 127 (1), 30–37[3] Dheeraj Kumar, Ashish Pandey, Nayan Sharma,
Wolfgang-Albert Flügel, Daily suspended
sediment simulation using machine learning
approach, CATENA, Volume 138, March 2016,
Pages 77-90[4] Assefa M. Melesse, Sajjad Ahmad, Michael E.
McClain, Xixi Wang, Yeo Howe Lim,
Suspended sediment load prediction of river
systems: An artificial neural network approach,
Agricultural Water Management, Volume 98,
Issue 5, March 2011, Pages 855-866[5] D.E. Walling, Limitations of the rating curve
technique for estimating suspended sedimentloads, with particular reference to British rivers,
Symposium on Erosion and Solid Matter
Transport in Inland Waters, Paris, France, 1977
[6] Anurag Malik, Anil Kumar, Jamshid Piri, Daily
suspended sediment concentration simulation
using hydrological data of Pranhita River Basin,
India, Computers and Electronics in Agriculture,
Volume 138, 1 June 2017, Pages 20-28[7] Vijay Kotu, Bala Deshpande, Data Science
Concepts and Practice, 2th ed, Morgan
Kaufmann Publisher, 2019, Page 443[8] Jain, S.K., 2001. Development of integrated sed

ACKNOWLEDGMENTS
The authors gratefully thank to the Royal
Irrigation Department (RID) for the data used in the
study, and Mr.Thienchart Suwawong, researcher ofthe Remote Sensing Research for Water Resources377

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

FATIGUE STRENGTH OF HEADED STUDS UNDERROTATIONAL SHEAR LOADING FOCUSING ON WEIGHTREDUCTION OF STEEL-CONCRETE COMPOSITE BRIDGE DECK

1

Kenji Yoshida1, Hiroshi Higashiyama2, Hideki Ogomori3 and Shigeyuki Matsui4
Kawada Industries, Inc., Japan; 2Faculty of Science and Engineering, Kindai University, Japan;
3
Nippon Stud Welding, Co., Ltd., Japan; 4Osaka Institute of Technology, Japan

ABSTRACTHeaded studs as shear connectors are widely used in steel-concrete composite bridge decks. When vehicles
run on the steel-concrete composite bridge deck, horizontal shear force rotationally acts on the headed studs. The
authors have investigated durable headed studs by improving the welding ferrule configuration. In Japan,
reinforced concrete decks that are likely damaged by fatigue and salt attack have been recently replaced byrehabilitating highway bridges. To use steel-concrete composite bridge decks for those constructions, it isnecessary to reduce the dead weight of the bridge decks. Such weight reduction can be achieved by reducing the
thickness of the bottom steel plate to, for example, 6 mm in the steel-concrete composite bridge deck. A
conventional headed stud with a diameter of 16 mm can weld on the 6 mm thick bottom steel plate, whereas an
improved headed stud with a diameter of 16 mm cannot weld on the 6 mm thick bottom steel plate because thebottom steel plate melts with higher heat input during welding. An improved headed stud with a diameter of 13
mm is thus used for the thin bottom steel plate. However, little data is available on the fatigue strength of suchcombination under rotational shear force. In this study, headed studs welded on the thin bottom steel plate underrotational shear force were experimentally investigated. This paper reports the fatigue durability of a headed studwith an improved headed stud with a diameter of 13 mm welded on the 6 mm thick bottom steel plate.
Keywords: Headed studs, improved welding ferrule, fatigue strength, rotational shear loading

INTRODUCTION
Traditionally in Japan, reinforced concrete decks(RC decks) have been widely used for highway
bridges. As many highway bridges constructed in
the last five decades are getting old, the maintenanceof these bridges has become the most serious
problem to extend their service life with appropriate
rehabilitation works. For bridges with RC decks,
replacement of severely deteriorated decks is a
recent trend to minimize the Life Cycle Cost (LCC).
Under these circumstances, the steel-concrete
composite decks have been developed in recent
years as an alternative to RC decks. The steelconcrete composite decks are more used nowadays
not only for new bridges, but also for existingbridges by replacing RC decks.
The steel-concrete composite deck is mainly
used at the span length of 4 m to 8 m, while the span
length of the RC deck is limited up to 4 m in theJapanese Specification of Highway Bridges. This isbecause the steel-concrete composite deck less than
4 m long is less economical than the RC deck.
Furthermore, when replacing the RC deck with thesteel-concrete composite deck, the main girder
supporting the deck is often kept. Therefore, theweight of the steel-concrete composite deck should
be reduced to as light as the existing RC deck.

The steel-concrete composite deck targeted inthis study is a Robinson type steel-concrete
composite deck (SC deck). The SC deck shown in
Fig. 1 consists of a bottom steel plate, headed studs,
transverse ribs and reinforced concrete. A number of
researches have been performed to develop suchsteel-concrete composite decks. As shown in Fig. 2,
the fatigue failure of headed studs in the SC deck
was observed in the wheel load running tests
conducted by Matsui et al [1]. Their research work
has revealed that the fatigue life of headed studs in
the SC deck is significantly shorter than that in thestandard push-out fatigue tests. They have also
revealed that the headed studs break down earlier
because shear force rotationally and repeatedly acts
on headed studs while changing its amplitude. Thisphenomenon is peculiar to the SC deck. Matsui et al.
[2-4] also carried out the fatigue tests on a headed
stud under rotating shear force. They successfully
simulated the reduction of the fatigue strength.
Based on these findings, the fatigue design
method for headed studs in steel-concrete composite
decks was standardized in Design Code for Steel
Structures PART B [5].
In this study, for saving the cost and reducing theweight of the SC deck, specimens with the reduced
thickness of the bottom steel plate from 8 mm to 6
mm and the diameter of the headed stud from 16
378

SEE - Bangkok, Thailand, Nov.11-13, 2019mm

Transverse rib
Headed stud

Bottom steel plate

Headed stud
Fig. 3 General view of specimen before casting
concrete.
Circular steel plate

Fig. 1 Steel-concrete composite deck (SC deck).
Beachmark

Headed stud 1 5

48
24

15

9

159
150
120 30Fatiguecrack section

ƒÓ2 3 2
ƒÓ2 0 224

175(a) Constant direction

Headed stud(b) Rotational shear force

17 5

17 5
ƒÓ3 2 0ƒÓ3 5 015

Fig. 2 Rotational shear force and fatigue failure
condition acting on stud weld.

Table 115

Dimensions of specimen.

Structural dimensions of specimen
Unit

Concrete

EXPERIMENTAL PROGRAM
Circular steel
plateSpecimens and Materials
The general view and dimensions of a specimen
are shown in Fig. 3, Fig. 4 and Table 1. The headed
studs used in this study have diameters of 16 mm
and 13 mm, and a height of 120 mm, which isusually employed in the SC deck. A headed stud waswelded on a circular steel plate at a distance of 24mm from the center. The circular steel plate waswith a diameter of 350 mm and thicknesses of 9 mm
and 6 mm. A steel tube with a diameter of 232 mm,a height of 150 mm and a thickness of 15 mm was
simply placed on the circular steel plate without any
mechanical connections. It functions as a mold for
concrete in casting and as the protection for wear of
concrete when the specimen is horizontally loaded
through a loading roller. The compressive strengthof the used concrete was 30.8 N/mm2 after 28 daysof curing.
The conventional and the improved ferrules andthe state of each headed stud after welding areshown in Fig. 5. The closing castellation at thebottom of the improved ferrule allows the high175
ƒÓ3 2 0ƒÓ3 5 015

Fig. 4mm to 13 mm are manufactured, and the rotational
shear fatigue test was conducted to confirm thefatigue strength of the headed stud.

Steel tube

Thickness
Strength
DiameterThicknessStud

Dimension

Steel tube

DiameterHeightThickness

mm
N/mm2
mm
mm
mm
mm
mm
mm
mm
mm

Structuraldimension
150
30.8
350
9
6
φ16×120
φ13×120232
15015(a) Conventional headed stud.

(b) Improved headed stud.
Fig. 5379

Ferrules and state of weld collar.

15

SEE - Bangkok, Thailand, Nov.11-13, 2019

temperature gas to spout upwards. As shown in Fig.
5(b), the weld toe of the improved headed stud issmoothed.

3333

Horizontal
springUp-lift preventing
bearing

Test Method
SpecimenRotating table
Loading roller

Fig. 6

Rotating shear fatigue testing machine.
STEP-1

STEP-2

At maxi mum l oad
48
2424

Headed st ud( Rot at i on cent er )Di r ect i on of r ot at i on‹60

A rotating shear fatigue testing machine used inthis test is shown in Fig. 6. This machine canrotationally apply shear force to a headed stud by
using four horizontal elastic springs and turn arotating table by 360 degrees with a rotary actuator.
The specimen is fixed on the rotating table by bolts.
The maximum contraction of these horizontal
springs is fixed to 48 mm in this test. Additionally,
vertical force was applied to the specimen by anelastic spring through a free bearing to prevent uplift of the specimen during loading. In advance, therelationship between the vertical force and thehorizontal shear force was computed by FEM
analysis and was verified in the previous research[6]. The loading step of rotating shear force ranging
from rotation angles of 0 to 180 degrees can be
explained as shown in Fig. 7. As the headed stud
position is at a rotating center, at STEP-1 (0 degree),the contracted length of the springs is 48 mm, inwhich the maximum horizontal shear force isapplied to the headed stud. Turning by 60 degrees(STEP-2), 120 degrees (STEP-3) and 180 degrees(STEP-4), when the contracted length becomes 0mm, no horizontal shear force acts on the headed
stud. Thus, changing the contracted length of thesprings by rotation of the specimen varies thehorizontal shear force. As shown in Table 2, in thistest, the shear stress applied to the headed studranged from 57.0 to 104.1 N/mm2 using the various
elastic springs with different spring constants.

Speci men cent er
Rot at i ng t abl e

14024

L- 48 Hor i zont al spr i ng

Headed st ud( r ot at i on cent er )126( =140- 14)
L- 34

Speci men cent er

STEP-4

STEP-3

At mi ni mum l oad
180
‹

24

12
0
‹

92( =140- 48)
L

102( =140- 38)
L- 10

RESULTS AND DISCUSSION
Failure ModeLF Hor i zont al spr i ng( mm)Fig. 8 shows the failure conditions after thefatigue tests. In this study, two failure modes wereobserved as in the previous study on the fatigue tests
under rotating shear force [6]. Fig. 9 shows theincidence of two failure modes classified by three
types of specimen and the ranges of shear stressapplied to headed studs. In I-6-13 specimens and I9-16 specimens with a middle compressive strengthof 30.8 N/mm2, as shown in Fig. 8(a), the fatigue
crack (Type S in Fig. 10) initiated at the tip of theseparated portion between the stud shank and theweld collar due to the notch effect and progressed
into the stud shank. This phenomenon also depends
on the applied loading level.
In N-6-13 specimens, as shown in Fig. 8(b), thefatigue crack (Type P in Fig. 10) penetrated from theFig. 7

Load step of rotating shear force.

Table 2

Summary of shear stress ranges

Specimen Circular

I-6-13N-6-16I-9-16380

Headed stud Shearsteel plate dimension

stressthicknessrange

Number of Compressive
specimens strength

(mm)

(mm)

6

Improved(N/mm2)104.1
3

φ13×120

86.4

3

78.5

3

72.0

2

Conventional 90.3

3

φ16×120

82.5

4

68.7

2

57.0

4

Improved

90.3

3

φ16×120

82.5

3

68.7

4

6

9

(N/mm2)
30.8

30.8

30.8

SEE - Bangkok, Thailand, Nov.11-13, 2019

Comparison of Fatigue Strength(a) Failure mode of Type S.

(b) Failure mode of Type P.
Fig. 8

Failure conditions.

I-6-13

Shear stress range
P

SΔτ = 72.0 N/mm2

P

S

Δτ = 78.5 N/mm2

P

N-6-16

Specimen typeP

S

Δτ = 104.1 N/mm2

P

S Δτ = 57.0 N/mm2

P

S Δτ = 68.7 N/mm2

P

S Δτ = 82.5 N/mm2

P

I-9-16Δτ = 86.4 N/mm2

S

S

Δτ = 90.3 N/mm2

P

S

Δτ = 68.7 N/mm2

P

S

Δτ = 82.5 N/mm2

P

S

Δτ = 90.3 N/mm2

Fig. 9 Incidence of two failure modes classified bythree type specimens and shear stress ranges applied
to headed studs.

The relationships between the shear stress range
and the number of cycles, namely S-N curves, areshown in Fig. 11 and Fig. 12 to compare the fatigue
life between the conventional and the improved
headed studs with different stud diameters. The S-N
curves of I-6-13 specimens (circular steel plate ofthickness 6 mm and improved headed studs ofdiameter 13 mm) and N-6-16 specimens (circular
steel plate of thickness 6 mm and conventionalheaded studs of diameter 16 mm) are shown in Fig.
11 with the Design Code of Japan Society of Civil
Engineers [6], which is the fatigue design standard
for headed studs.
For I-6-13 specimen and N-6-16 specimen,
I-6-13logN = –11.74log(Δτ)+27.41
N-6-16logN = –2.223log(Δτ)+9.142
PART B logN = –19.27log(Δτ)+39.88

(1)
(2)
(3)

The fatigue life of I-6-13 specimen was longer
when the stress amplitude was lower than 80 N/mm2,
and the fatigue life of N-6-16 specimen was longer
in the higher stress range. The comparison of thefatigue life under a stress range of 50 N/mm2, which
is at the practical level, reveals that the fatigue life of
I-6-13 specimen is longer than the fatigue life ofPART B [5]. The slope of the S-N curve is steeper
for N-6-16 specimen than for I-6-13 specimen
seemingly because of the effect of plate bending of
the circular steel plate. The local stress at the weld
collar increases as the larger diameter of the headed
stud tends to induce more bending moment on thethin steel plate. As the influence of plate bending ofa circular steel plate is greater, the failure mode oftype P is more likely to occur, and as the effect ofplate bending is less, the failure mode of type S is
more likely to occur.
2.2
2.1

Shear stress range (N/mm 2)

Crack initiation point(Type S)

Crack initiation point(Type P)

120
1002
1.9
80
1.8

60
1.7
1.6
40
1.5
1.4

I-6-13N-6-161.2

I-6-13N-6-16

1.1

PART B [5]1.3

13.000000

103

4.000000

104

5.000000

105

6.000000

106

7.000000107

Number of cycles

Fig. 10

Macro view of weld collar.

weld toe and progressed into the steel base plate
along the heat affected zone. The fatigue crack
passed through the steel plate, and the headed stud
was wrested due to the thin steel plate.

Fig. 11 S-N curves of improved headed studs.
(I-6-13 and N-6-16)
On the other hand, the S-N curves of I-6-13
specimens and I-9-16 specimens (circular steel plate
381

SEE - Bangkok, Thailand, Nov.11-13, 2019of thickness 9 mm and conventional headed stud of
diameter 16 mm) are shown in Fig. 12 with PART B[5].
For I-9-16 specimen,
I-9-16logN = –7.098log(Δτ)+18.70

E = 2.86×104 N/mm2 and the Poisson's ratio was ν =0.195. For the steel members, the Young's modulus
was E = 2.0×105 N/mm2 and the Poisson's ratio wasν = 0.3.

(4)

Concrete
Steel tube

The test results show that the S-N curves of these
two specimens are almost parallel. By reducing the
thickness of the steel plate, the local stress at theweld collar increases due to the influence of thebending of the steel plate. However, the failuremode of both specimens was type S, and under astress range of 50 N/mm2, which is at the practicallevel, the fatigue life of I-9-16 specimen is shorter
than that of I-6-13 and PART B [5]. This willcontinue to be tested for judgments based on data
accumulation.

Circular steel plate

Rotating table

Qmin = 0kN

Headed stud

2.2

Qmax = 14.11kN

1.8

60
1.7

(a) General view of FEM analysis model.

1.6
40
1.5
1.4

I-6-13I-9-16I-6-13I-9-16

1.3
1.2
1.1

Contact

6.15kNPART B [5]13.000000

103

4.000000

104

5.000000

105

6.000000

106

60mm

Fix

7.000000

107

Fix

Number of cycles

Qmin = 0kN

Qmax = 14.11kN

37.5mmShear stress range (N/mm 2)

2.1

120
1002
1.9
80

Fig. 12 S-N curves of improved and conventionalheaded studs. (I-6-13 and N-6-16)
Fix

Verification by FEM Analysis

Contact

Outline of FEM analytical model
FEM analysis is carried out to verify the
influence of plate bending due to the difference inthickness of circular steel plates. The basic modelfor three-dimensional elastic FEM analysis is shownin Fig. 13. Concrete, studs, and a circular steel platewith the thicknesses of 6 mm and 9 mm,
conventional and improved headed studs with adiameter of 16 mm, a steel tube, and a bearing plate
are assumed to be solid elements. For the boundary
condition, the adhesion between the concrete and thesteel members such as the studs, the circular steel
plate, the steel tube, and the bearing plate wasignored. However, the contact and the non-contact
conditions between them were considered in the
FEM analysis. In addition, the interface between thecircular steel plate and the rotating table andbetween the steel tube and the bearing plate was
fixed at the points of bolts. As the material
properties of the concrete, the Young's modulus was

Fix(b) Contact condition and load condition.
(A-A cross section)
Fig. 13

FEM analytical model.

Analytical results
This analysis is elastic analysis, and theanalytical stress is used as a reference value tocompare the fatigue life from the stress ratio. To
verify fatigue, hot spot stress is applied as nominal
stress. In this research, the stress at a distance of
0.4T and 1.0T (T: thickness of circular steel plate)from the weld toe is recommended by IIW [7].
Using this calculation method, the stressextrapolated straight to the weld toe was consideredas hot spot stress (HSS).
The HSS and FEM analytical stress at the weld
collar of the circular steel plate side of theconventional and improved studs are shown in Fig.
14. When the thickness of the circular steel plate is382

SEE - Bangkok, Thailand, Nov.11-13, 2019

reduced from 9 mm to 6 mm, HSS at the weld collar
on the 6 mm thick steel plate is increased by about
45% in comparison with the 9 mm thick steel plate.

Principal stress (N/mm2)350
FEM-Conventional (N-6-16)

300

FEM-Conventional (N-9-16)

250
200

HSS-Conventional (N-6-16)

142.9

HSS-Conventional (N-9-16)

150
●

100

●

●

50

●

99.3

0
-50

2.4

3.6

9

-100
0

5
10
Distance from stud weld collar (mm)15(a) Conventional headed studs.
350

Principal stress (N/mm2)

moment on the thin steel plate. As the influenceof plate bending of a circular steel plate is greater,
the failure mode of type P is more likely to occur,
and as the effect of plate bending is less, thefailure mode of type S is more likely to occur.
(3) The failure mode of I-6-13 and I-9-16
specimens was type S, and the fatigue life of I9-16 specimen is shorter than that of I-6-13.
This will continue to be tested for judgments
based on data accumulation.

REFERENCES

FEM-improved (I-6-16)300

FEM-improved (I-9-16)

250

HSS-improved (I-6-16)

200

138.4

HSS-improved (I-9-16)

150
●

100

●

●

50

●

94.9

0
-50

2.4 3.6

9

5

10

-100
0

Based on the above test results, rotational shear
fatigue of the headed stud can be secured by
reducing the bottom steel plate from 9 mm to 6 mm
and changing the conventional headed stud of 16
mm to the improved headed stud of 13 mm. In
addition, the weight of SC decks can be reduced.

15

Distance from stud weld collar (mm)(b) Improved headed studs.
Fig. 14 Hot spot stress (HSS) on the side ofcircular steel plate.
CONCLUSIONS
The following conclusions can be drawn fromthe fatigue test results:(1) In the fatigue tests, two failure modes of headed
studs were observed: the fatigue crack initiated at
the tip of the separated portion between the studshank and the weld collar and progressed into thestud shank; and the fatigue crack initiated at theweld toe and progressed into the steel base plate
along the heat affected zone.
(2) The local stress at the weld collar increases
seemingly because the larger diameter of theheaded stud tends to induce more bending[1] Matsui S., Moon T., Fukumoto Y., Watanabe H.,
Kajikawa Y., Fatigue strength of steel plate–concrete composite deck, IABSE Symposium,
Brussels, 1990, pp. 191–196.
[2] Matsui S., Moon T., Fukumoto Y., Fatigue
failure mode of studs in steel plate–concrete
composite decks of highway bridges, Journal of
Structural Engineering, JSCE, Vol. 39A, 1993,
pp. 1303–1311 (in Japanese).
[3] Yoshida K. Inamoto K. Matsui S., Higashiyama
H. and Kaido H., Development of Headed Stud
with High Fatigue Strength for Steel–concrete
Composite Deck, Journal of StructuralEngineering, JSCE, Vol. 58A, 2012, pp. 908-919(in Japanese).
[4] Yoshida K., Higashiyama H., Inamoto K.,
Matsui S. and Kaido H., S–N curve for Durable
Headed Stud under Rotating Shear Force,
Journal of the Society of Materials Science,
Japan, Vol. 62, No. 10, 2013, pp. 621–626.
[5] JSCE, Design Code for Steel Structures PARTB: Composite structures, 9B, 1997 (in Japanese).
[6] Higashiyama H., Yoshida K., Inamoto K.,
Matsui S. and Kaido H., Fatigue of Headed Studs
Welded with Improved Ferrules under Rotating
Shear Force, Journal of Constructional Steel
Research, Vol. 92, 2014, pp. 211–218.
[7] International Institute of Welding (IIW), XIII1539-96/XV 845-96, 1996.

383

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

LABORATORY EXPERIMENT OF CHANNEL HEAD BIFURCATIONBY RADIAL OVERLAND FLOW
Adichai Pornprommin1, Ravicha Thaisiam2 and Wandee Thaisiam3
Department of Water Resources Engineering, Faculty of Engineering, Kasetsart University, Thailand

1,2,3

ABSTRACT
Many studies have shown that incipient channelization can be explained by the interaction between flow andan erodible bed. Our recent theoretical study has shown that an eroding channel head by overland flow can maintainits shape without bifurcation if the flow depth is sufficiently large comparing to the channel head radius. Here, we
performed nine experimental runs using three sediment sizes to provide better understanding of the bifurcation. A
circular pan was filled with sand except at the center, where there were a sink hole and a drain installed at the panbottom. When water had been filled over the sand to a desirable level, the drain was opened and unsteady radial
overland flow accelerated toward the hole. After a while, water formed a downward-concave profile, leading tostrong bed erosion in the vicinity of the hole and, as a result, the hole size expanded. In the initial development
where flow depth was sufficiently large, the hole maintained its circular shape without channel incision while
expanding. As the flow depth and discharge reduced and the hole radius increased, the hole started to lose its
circular shape. Thus, the experimental results confirmed the condition of channel bifurcation proposed by ourprevious study. Main incised channels with large spacing were firstly initiated and elongated upstream in the radial
direction while small rills were generated later between main channels. Using the network circularity as anindicator, we propose the new four phases of channel network development (unchannelization, initiation, extension
and abstraction).
Keywords: Erosion, Channel head bifurcation, Overland flow, Experiment, Channel network development

estimated that channel head does not bifurcate ifchannel head radius is not larger than 10 times the
Froude-critical depth of overland flow divided by thefriction coefficient [3].
A few experiments have been conducted toinvestigate the development of the channel head.
Pornprommin et al. [4] performed an experiment ofchannel inception by seepage erosion on a rectangularbasin with an adjustable bed slope. The sedimentlayer was built by coarse sand and water was fed
upstream. They found that an increase in the slope led
to a larger channel width but more difficulty inchannel bifurcation. A higher discharge also caused alarger channel width but easier initiation of thebifurcation. Thus, they hypothesized that thegeometry of groundwater flow and the resistibility of
sediment material to slope failure play an importantrole in channel head bifurcation. Berhanu et al. [5]studied channel head shapes in a rectangular box
filled with glass beads. Groundwater was fed by an
upstream reservoir or rain. They found that thedifferent sources of groundwater led to change in the
groundwater flow nets and, consequently, impacted
the shape of the channel heads. Their finding wasconsistent with the hypothesis of Pornprommin et al.
[4]. A more comprehensive experiment of channel
formation by seepage due to different groundwaterflow patterns was conducted by [6]. However, to theauthors’ knowledge no experimental studies have

INTRODUCTION
Channel head bifurcation, sometimes called
branching, is one of the most important processes ofchannel network formation because it leads to ahigher complexity in the geometry of the channel
networks. Recently, researchers have tried to study its
mechanics. Perron et al. [1] investigated thebranching river networks of two field sites, theAllegheny Plateau in Pennsylvania and Gabilan Mesa
in California. Using the landscape evolution model
based on soil creep and channel incision equations,they found good agreement between their model andthe field data. Using a groundwater flow equation,
Petroff et al. [2] studied stream bifurcation by seepage.
They compared their model with field observation at
the Panhandle in Florida and found good agreement
between them. Thus, both studies showed thatchannel head bifurcation should be initiated byhydrophysical mechanisms (processes due to water
forces such as erosion), not as a consequence ofrandom topology. Pornprommin et al. [3] performed
a linear stability analysis using the flow equations in
the polar coordination system to investigate incipientchannel head bifurcation. Circular holes wereassumed to be channel heads, toward which radial
overland flow accelerates. Then, channel bifurcation
is defined as the holes lose their circular shapes when
they are unstable to the imposed perturbations. They
384

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 Experimental runs.
Run
Type
𝑑50
𝑑10
(mm) (mm)A-1
Medium
A-2
0.49
0.30
sand
A-3
B-1
Medium
B-2
0.30
0.12
sand
B-3
C-1
C-2 Fine sand 0.18
0.07
C-3

Fig. 1Thickness
(cm)
10
10
5
10
10
5
10
10
5

Three sizes of industrial, sieved sand were used inthis study as shown in Table 1. Their grain size
distributions were analyzed using sieve analysis anda hydrometer test. The first two coarser sizes (sands
A and B) were a non-cohesive, medium sand withmedium diameters ( 𝑑50 ) of 0.49 and 0.30 mm,
respectively. The last and smallest size (sand C) was
fine sand with 𝑑50 of 0.18 mm and had a small
proportion of silt and clay (~8% smaller than 62.5µm) providing some cohesion. We conducted threeexperimental runs for each sand type. The first two
runs were conducted under the same conditions using
a layer thickness of 10 cm. The third run used athickness of 5 cm. Thus, we performed a total of nineruns. Sand was not reused to ensure the same
properties of sediment in each run.
Before the operation, the ring was removed very
slowly to keep a symmetrical circular front of thesand layer at the center, and some debris floating onwater surface was removed. A video camera wasinstalled above the apparatus to record the evolutionof the sand layer from the top view (Top Camera), andtwo video cameras were placed near the chamberedge to record the water levels at the two gauges
attached to the inner edge (Cameras 1 and 2). Whenthe set up was completed, the drain plug was opened.
The video records ended when there was no further
significant change in the sand layer. Two types ofresults were digitized from the records: the evolutionof the sand layer crest from the Top Camera and thetime variation of water levels at the gauges from
Cameras 1 and 2.

Experiment setup.

tried to investigate channel head bifurcation from theperspective of surface sheet flow in detail.
In this paper, we conducted a laboratory
experiment of channel inception by overland flow ina circular chamber following the concept of channel
bifurcation proposed by [3]. Our two main objectives
in this study were; (i) to examine the early stage ofchannel network evolution (channel inception); and(ii) to compare the experimental results with thetheoretical study [3].
EXPERIMENTAL SETUP
The experiment was performed in an apparatus
chamber with 120 cm in diameter and 28.5 cm inheight as shown in Fig. 1. The apparatus was
modified from a class A evaporation pan and placedon a table. The center of the pan and the table under
it were drilled and fitted with a PVC pipe drain of 5
cm diameter and 5 cm length. This drain was used to
let water and sediment flow in the radial direction
toward the center of the apparatus and down into thedrainage tank under the table during operation.
In the preparation stage, the drain was closed witha plug, and an acrylic ring of 28 cm height was placedat the center. The ring had many small holes in it toallow water to pass through. Sand was gently filled
between the ring and the edge of the apparatus to thedesign height and it formed a donut-like sedimentlayer. Then, water was gradually filled inside the ringand flowed into the sediment layer through the small
holes until the sand was saturated and the water level
reached the height of the layer. Based on thehorizontal water surface, the saturated sand layer
surface was delicately adjusted. After that, water was
filled again to 17 cm depth from the chamber bed tocomplete the preparation stage.

EXPERIMENTAL RESULTS
Figure 2 shows the top view of the final drainage
networks from the Top Camera. The lines with dotsshow the digitized hole circumferences according to
the uneroded crest lines of sand layers. Since water
flowed in the radial direction and converged on thecenter drain of our circular apparatus, overall there
385

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 2 Photographs of drainage networks in the final stage. Lines with dots show digitized holecircumferences.
was a centripetal drainage pattern. In every run,fluvial erosion (sheet and rill erosion) and mass
wasting processes always occurred repeatedly andrandomly in the vicinity of the crest and front of sandlayers. Thus, incised channels were initiated at the
crests, where velocities are highest, and extended
upstream. Because the experimental runs happened
on short timescales, weathering processes such as
abrasion did not affect our results, and, thus, welimited our consideration to the sand type and layer
thickness, causing different channel patterns. It can beseen that the runs with sub numbers 1 and 2 of thesame sand type have similar channel patterns. For thecase of the runs with sub number 3, where thethickness was cut by half, less development ofchannel pattern was noticed. A shallower layer
caused less seepage and mass wasting and also a
milder slope of the front at the end. These induced
less erosion and consequently shallower and shorter
incised channels.
For sand A, short incised channels were observedwith smaller rills in the eroded area. Several incisedchannels were able to tap the surface water fromupstream and developed into longer main channels.
In runs A-1 and A-2, long and steep cliffs withcavities at the toes were detected in the area where theoverland flow stopped more rapidly than in otherplaces and main channels were not found. The front
subjected to seepage erosion can be divided into threezones [7]. The sapping zone is the small area near the386

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 3Time variation in centercircumference of run B-2.

flow related to mass wasting.
Sand C contains a small percentage of mud. Dueto having the smallest diameter and the presence ofmud, the lowest hydraulic conductivity can be
expected. Also, physical cohesion imparted by the
mud can significantly influence and reduce theerosive properties of sediment. Many deep, incised
rills of narrow width were found. In sand C, we did
not observe steep cliffs with cavities as were found insands A and B. However, soil creep and large-scale
block slump were observed during the final stage ofthe runs when water at the drain had almost
disappeared. The failure was possibly due to the low
permeability of sand C so that it took a long time forwater in the soil to drain. An increase in the soil
weight due to the high water content without acounter-balance pressure force by the water level
above the drain would be the main factor causing thelarge-scale failure. In addition, we observed a few
step-like, upstream-migrating headcuts within someeroding channels by overland flow. However, they
were decaying and finally disappeared as the surface
water supplying their channel heads became weakerand finally ceased.
An example of the evolution of the center hole bydigitizing sand layer crest lines is illustrated in Fig. 3.
It shows the expansion of the hole circumference ofthe experimental run B-2 from 0 s to 20 s with twosecond intervals, and at 72 s as the final pattern. The
crest line is defined as the edge of the uneroded top
surface of sand layer. We set time 0 when we firstdetected the start of erosion on the crest line. An
initial, almost perfect circular circumference
gradually developed into an irregular shape for the
crest line due to the presence of main channels. At 72s, we counted nine rounded corners from the digitized
line, but the number of incised channels in the eroded
area in the center photo of Fig. 2 was found to begreater than nine because some adjacent incisedchannels shared the same corner. Thus, the initiationof incised channels in the eroded area and theevolution of the crest line of the uneroded top surface
may be generated by the same erosional process byoverland flow and interact with each other, but theirmorphological processes and features can be different.

hole

toe where seepage emerges and the strong force of theeffluent seepage initiates sediment detachment andremoval from the face. Then, slope failure occurs in
the undermining zone on top of the sapping zone due
to losing its stability. Finally, sediment transported byfluvial processes in the fluvial zone downstream fromthe sapping zone helps a repeat of the processes. Thus,
the cavities might be generated by seepage erosion in
the sapping zone and surface tension between waterand sand tends to hold the steep cliffs in the wet
undermining zone. In run A-3, a not very long cliff
was detected due to thinner thickness. The cavities
were less in the experimental runs of sand B, and they
were not found in sand C.
Compared with sand A, more main channels wereobserved in sand B, and they extended further
upstream. Channel formation was very symmetricalin the radial direction. In addition, more small rills
were also spotted caused by an increase in thestrength of channel incision by overland flow becausea smaller sediment size leads to lower threshold shear
stress for erosion. Since a smaller diameter of sand B
provides lower hydraulic conductivity corresponding
to less infiltration, surface sheet flow erosion wasstronger in the runs of sand B. Again, steep cliffs weredetected in runs B-1 and B-2 due to seepage erosion
and slump blocks, but it was not detected in run B-3
because of the lower height of the sand layer. Masswasting is commonly assumed to be a diffusive-type
process that smoothens topographic perturbations,while channel incision due to water flow amplifies
perturbations. Thus, more extensive incised channels
in sand B than in sand A were possibly the results ofthe stronger process of channel incision by overland

ANALYSIS OF CHANNEL HEAD EVOLUTION
At the commencement of drainage evolution in
our experiment, the hole expanded while it still
maintaining its circular shape. This implied that thehole was stable from perturbations. However, after
expanding for a while, the hole became unstable and387

SEE - Bangkok, Thailand, Nov.11-13, 2019same perimeter as follows:
𝑁𝑐 = 𝐴/𝐴𝑐 = 𝐴/𝜋(𝑃/2π)2Fig. 4(1)

where 𝐴 and 𝑃 are the eroded area and perimeterof channel network, respectively, and 𝐴𝑐 is the circle
area computed using 𝑃.
Network circularity 𝑁𝑐 has a value between 0 and
1 where 𝑁𝑐 = 1 means that the shape of the channel
network is perfectly circular. Using 𝑁𝑐 , three phasesof channel network development was proposed asfollows [8]. (1) Initiation is the first stage during
which the main channels elongate upstream rapidly.
𝑁𝑐 decreases steeply in this stage. (2) Extension is thesecond stage in which the channel heads expand
laterally and bifurcate into tributary channels. 𝑁𝑐 still
continues reducing but at a lower rate. (3) Abstractionis the last stage in which the channel heads continue
widening and cause divide decay and consequently 𝑃
may reduce while 𝐴 still increases. 𝑁𝑐 thus begins toincrease.
Figure 4 shows an example of the variation in
network circularity with time for runs A-2, B-2 andC-2. In general, the initial 𝑁𝑐 was close to unity andremained so for some period before reducing rapidly.
With sands A and B, the reduction in 𝑁𝑐 occurred
before the uniform overland flow had disappeared,
while for sand C, it occurred after that and took quite
a long time of about 1 min. As the sand size decreased,
evolution took longer. In run C-2, during the
beginning period, 𝑁𝑐 abruptly dropped and thenregained because there were small, initial, irregular
perturbations along the crest line before the operation.
The perturbations disappeared later because theeroding crest neighboring them migrated upstream ata faster rate, and thus the crest lines around theperturbations became rounder and wider. Thisimplied that the network dynamics favoredmaintaining a circular shape. If we assume thatchannel inception can be indicated by the slope
transition of 𝑁𝑐 , it can be said that in the cases ofsands A and B, channelization took place during
active, uniform overland flow while it happened laterwith sand C. Comparing the slope transition with theprediction by the theory shown in circles, we foundqualitative agreement for sands A and B. Due to thelargest threshold erosion of sand C, it was possiblethat the active erosion time was too short to generatechannelization during the uniform overland flow
period. The channelization in runs using sand C was
due to some incised channels being able to tap waterfrom depressions on the layer surface.

Time series variations in network
circularity. Shaded vertical lines show
predicted time of no uniform sheet
surface flow, and circles show time ofbifurcation predicted by the theory [3].

incised channels were initiated and grew upstream.
Thus, there should be a threshold condition whereby
an initially circular hole transforms into a channelized
drainage. To investigate the threshold condition, we
adopted the recent linear stability analysis [3].
Gomez and Mullen [8] performed an experimenton channel networks by considering groundwater
flow. To describe the shape of their experimental
drainage networks, they adopted the concept ofcircularity by [9] that has been used to quantify theshape of a whole drainage basin. They called it
network circularity (𝑁𝑐 ) defined as the ratio between
the eroded network area and the circle area of the388

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 5

radial symmetry due to high erodibility.
According to [8], network evolution can bedivided into three phases (initiation, extension andabstraction). The initiation phase was the first phaseof the evolution when main channels elongate rapidly.
However, from our experimental runs, circular holes
were not incised by main channels unless the holeradii were sufficiently large compared with the flow
discharge. Thus, we proposed a new first phase called
the unchannelization phase where the shape of theeroded area remains unchanged. The transition
between the unchannelization phase and the initiation
phase is then expected to be the time of incipientchannelization according to the theory by [3].

Revised phases of network evolution
classified by network circularity byincluding unchannelization phase.

In the phases of network evolution proposed by[8], the first phase in our experiment where the
network circularity 𝑁𝑐 maintained its value cannot be
explained. However, this phase was detected in otherexperiments. Hancock and Willgoose [10] studied
network development in a landscape simulator. They
described the first phase in their experiment where
surface water flowed to and concentrated at the basin
outlet, and it caused the expansion of an
unchannelized, large, semi-circular eroded area.
Channelization then took place at this eroded area andthe channel network developed from there upstream
in later phases. Thus, we proposed to include thisphase of the development of unchannelized area into
the original phase diagram. Figure 5 shows therevised phases of network evolution. The first phase,where the shape of eroded area remains or 𝑁𝑐 keeps
constant, was added and was called the“unchannelization” phase.

REFERENCES[1] Perron, J. T., P. W. Richardson, K. L. Ferrier, and
M. Lapoôtre (2012), The root of branching river
networks, Nature, 492, 100-103.
[2] Petroff, A. P., O. Devauchelle, H. Seybold, and D.
H. Rothman (2013), Bifurcation dynamics ofnatural drainage networks, Philos. T. Roy. Soc. A,
371 (2004).
[3] Pornprommin, A., N. Izumi, and G. Parker (2017),
Initiation of channel head bifurcation by overland
flow, J. Geophy. Res.: Earth Surface, 122.
[4] Pornprommin, A., Y. Takei, A. M. Wubneh, andN. Izumi (2010), Channel inception incohesionless sediment by seepage erosion, J.
Hydro-env. Res., 3, 232-238.
[5] Berhanu, M., A. Petroff, O. Devauchelle, A.
Kudrolli, and D. H. Rothman (2012), Shape anddynamics of seepage erosion in a horizontal
granular bed, Physical Review E, 864.
[6] Marra, W. A., S. J. McLelland, D. R. Parsons, B.
J. Murphy, E. Hauber, and M. G. Kleinhans(2015), Groundwater seepage landscapes fromdistant and local sources in experiments and on
Mars, Earth Surf. Dynam., 3, 389-408[7] Howard, A. D., and C. F. McLane III (1988),
Erosion of cohesionless sediment by ground water
seepage, Water Resour. Res., 24 (10).
[8] Gomez, B., and V. T. Mullen (1992), An
experimental study of sapped drainage network
development, Earth Surf. Proc. Land, 17 (5), 465476.
[9] Miller, V. C. (1953), A quantitative geomorphic
study of drainage basin characteristics in the
Clinch Mountain area, Virginia and Tennessee,
Columbia University Technical Report 3, Project
NR 389-042, 68 pp., New York.
[10] Hancock, G., and G. Willgoose (2001), Theinteraction
betweenhydrology
andgeomorphology in a landscape simulator
experiment, Hydrol. Process., 15, 115-133.

CONCLUSION
The experiment of channel bifurcation on acircular hole was performed with three sanddiameters (𝑑50 = 0.49, 0.30 and 0.18 mm) and twolayer heights (10 and 5 cm). The smallest size had asmall proportion of silt and clay and showed thepresence of cohesion and the lowest erodibility. In theruns of the two largest sizes, the combination of slope
failure processes of an upper slump motion and atransformed lower flow was observed. However,slow soil creep and earth flow with large-scale slump
block failure were found in the case of the smallest
size due to cohesion, and step-like upstreammigrating headcuts (cyclic steps) were also detectedduring the runs. Seepage and seepage erosion werestrongest for the largest size due to the highest
hydraulic conductivity. The middle-sized sandshowed the greatest extension of channelization with389

5thInt. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

IDENTIFICATION OF DRAINAGE SYSTEMS CAPACITY USING EPASWMM 5.1 VERSION MODELING IN GUNUNG PANGILUN OF
PADANG CITY-PALAPA METROPOLITAN AREA
Taufika Ophiyandri, Bambang Istijono, Milania, Benny Hidayat, and Aprisal
Faculty of Engineering, University of Andalas, Padang, Indonesia
ABSTRACT
Floods have often occurred in the city of Padang in recent years, this is generally caused by high rainfall andpoor drainage capabilities. NVivo software is utilise to analyse the online news which reported floods occurrence.
Based on the news collected from 2009–2018, it was found that Gunung Pangilun Village, Padang Utara
Subdistrict was often flooded when it rained for more than 3 hours. This area is a densely populated area (1,000
people / km2). The cause of inundation in this area is that drainage is not able to accommodate water and highrainfall intensity with the parent river in the Batang Kuranji watershed. The flooding that occurred in this area
caused several schools, offices and hospitals to be flooded, a number of houses and a number of points on the local
road were flooded. Therefore, it is necessary to know the large drainage capacity that is able to accommodate theamount of runoff discharge when the rain occurs using the 5-year return EPA SWMM software modelling.
Keywords: flood inundation, drainage, EPA-SWMM, NVivo
Therefore, this research aims to identify the abilityof the Gunung Pangilun (Fig. 1) drainage network
against flood using the EPA SWMM (Environmental
Protection Agency Strom Water Management
Model).

INTRODUCTION
Background
The metropolitan Urban Area of Padang, Lubuk
Alung, Pariaman (MUA PALAPA) as a National
Activity Center is oriented to encourage thedevelopment of priority production sectors such asindustry, marine fisheries, tourism, trade andservices. MUA PALAPA is a priority location for thenational urban strategic area as the centre of regional
growth in the Sumatra region.
For this reason, problems need to be identified
that cause damage to the urban environment, whichneeds alternative solutions and immediate treatment.
Environmental damage problems include drainage
conditions, flooding, rainwater inundation, coastal
abrasion and the provision of water resources
infrastructure with good maintenance andenvironmentally conscious communities.
One of the disasters often faced by Padang City is
flooding [2]. Floods are generally caused by highrainfall [3, 4] and poor drainage capabilities [5, 6]. By
using NVivo software news from online media can beevaluated. Based on the news from 2009–2018, it was
found that the location of the frequent flooding in
Padang City is Gunung Pangilun Subdistrict,
especially when it was raining for more than 3 hours(Fig. 1). This area is a densely populated area which
is 1,000 people / km2. The cause of inundation in thisarea is that drainage is not able to accommodate waterand high rainfall intensity with the main drainage inthe Batang Kuranji watershed. The floods that
occurred in this area caused inundation in several
schools, offices and hospitals, houses, and local roadas well.

Location of flood inPrimary School No.
17 Gunung Pangilun
in 2017

Location of flood atsurrounding Alfaiz
Mosque in 2018

Fig. 1 Visualization of the Gunung Pangilun Area
(Source: Google Earth)
Literature Review
Rossman [7] states EPA SWMM is a rainfallrunoff simulation program commonly used for390

SEE - Bangkok, Thailand, Nov.11-13, 2019

quantity simulation and surface runoff quality inurban areas.
NVivo is a software commonly used for
qualitative research. Usually qualitative researchaims to explore and understand data more deeply.
Qualitative data is in-depth and detailed, so it is also
lengthy. As a result, the analysis of qualitative data is
specific, especially to summarize data and unify it inan analytical flow that is easily understood by others.
A Digital Elevation Model (DEM) is a form ofpresentation of the height of the earth's surface
digitally. It can be seen from the distribution of points
representing the shape of the earth's surface that it canbe distinguished in a regular, semi-ordered, andrandom form.
Hidayat [8] in his research on Understanding
flood disasters in the city of Padang with the content
analysis of the news article explained that, articles
were searched using the google.co.id search enginesite with the search term 'flood field site:www.padangekspress.co.id' which produced articles
about floods in the city of Padang that have been
published by the Padang Ekspres website. One by one
the articles were opened and explored whether each
one was related to flooding in the city of Padang.
Articles that met the requirements were stored in theform of Ms-word documents where one article wasstored as an Ms-word file. After the articles have beencollected in the form of Ms-word files, the files areprocessed and analysed using NVivo software
version 8.
Legowo, et al. [9] stated that the DEM appearedin soil surface morphological information was used torepresent the surface runoff hydrology process.
Topographic structure extraction algorithms will besloped and current direction is an important factor indescribing drainage networks.
Vinay, et al. [10] said that SWMM modelling
played an important role in examining problems suchas urban flash floods. SWMM has become aneffective tool for flood simulation in urban areas.
Frequency analysis is done using the most appropriate
distribution, namely, the Gumbel distribution fordifferent return periods and the frequency value used
for the development of the IDF curve (intensity
frequency duration). The intensity of rain derived
from the IDF curve for different return periods is used
to estimate the peak runoff of each sub-watershed
used as an input parameter in a runoff simulation in
SWMM. The GIS methodology is used to handle
spatial data simultaneously.
Waikar, et al. [11] explained that urban floods
were basically caused by damaged and inefficienturban drainage systems, and caused damage to public
and private buildings and disrupted public life. In
order to understand the complexity associated withurban flood management, the EPA SWMM
application is used. Furthermore, daily rainfall data
was obtained from Asarjan closest to the rain gauge
station. Arc-GIS (10.1) is used to process DEM(Digital Elevation Model) and LULC (Land Closureof Land Use) data to obtain height and water
resistance respectively. Topographic data such asarea, width, length, etc. Also taken from Arc-GIS.
The selected extreme daily events are separated into
hourly events using the reduction formula. After that,
EPA SWMM was used to simulate catch response to
rainfall events where runoff, water depth profiles, andoutflow hydrographs were obtained. Runoff is also
obtained from rational formulas for comparison
purposes.
Fairizi [12] in his research used short-term rainfall
data from 2001 to 2012. Rainfall data is tested
according to normal, Normal log, Pearson III log, andGumbel distribution. Select one result from the
distribution with the smallest standard deviation.
Then, it was tested by the Smirnov-Kolmogorov test
to find the rainfall intensity equation. Later, theequation will be used to find the drainage dimension.
To analyse inadequate drainage, SWMM Program isutilised.
Hydrological Analysis
Hydrological analysis was used for the calculationof rainfall with a five-year return period, calculationof rainfall intensity, and hyetograph count of plannedrain using the Alternating Block Method (ABM)
method.
Rainfall Analysis
If the rain data used in the calculation is in the formof a sample (limited population), then the calculationof the rain plan based on the Gumbel Probability
distribution is carried out by the following formulas[13].
XT =𝑋 + S x KT

(1)

where :
X
: rain plan with a return period T (mm)𝑋
: Average value of X (mm)K
: Gumbel frequency factor, depends onthe data Yt, Yn, Sn.

Rainfall Intensity
Calculation of rainfall intensity uses the Mononobe
method with the following formula :
𝟐

𝑹𝟐𝟒

𝟐𝟒 𝟑
I = 𝟐𝟒 𝒙 ( 𝒕 )where :
I
: rainfall intensity (mm/hour)
R24: bulk plan in a return period (mm)t: rain duration (hour)
391

(2)

SEE - Bangkok, Thailand, Nov.11-13, 20196.

Calculate the planned rainfall and do a match test
using the Chi Kaudrat method.
7. Calculate rain intensity using the Mononobe
method.
8. Calculate the hyetograph of the rain plan using
the Alternating Block Method (ABM) method.
9. Simulation of the EPA SWMM 5.1 programusing data that has been analysed.
10. The program simulation results in the form of
runoff discharge that is accommodated by thechannel and the location of the flood points that
occur along the drainage canal.

Hyetograph Rain Plan
Rain distribution models that have beendeveloped to change daily rainfall into rainy days the uniform rain distribution model using theAlternating Block Method (ABM) method [14].
EPA SWMM Version 5.1
EPA SWMM (Environmental Protection Agency
Strom Water Management Model) is a rainfall-runoff
simulation program commonly used for simulating
the quantity and quality of surface runoff in urban
areas. The ability of this software is to be able tocalculate the hydrological process that produces
runoff from urban areas such as rainfall, evaporation,
infiltration and determine the flood point andcalculation in runoff discharge. The objects used inthis research are:
1. Rain gauge includes rainfall intensity data,
observation time intervals, and rainfall data
sources in the form of a time series.
2. Sub-catchment includes determining the outlet ofthe sub-catchment, determining land use,
determining the probable and impervious subarea, determining the slope or slope of the subcatchment, determining the width of subcatchment, determining the manning number forsurface flow, determining the percentage ofimpervious
sub-areas,
determining
thedepression and impervious regions, determining
the percentage of impervious area without
depression.
3. Junction is the point of the drainage system
where the channels join. The data needed iselevation, maximum depth, storage area when
there is a flag (if any), flow from outside thedrainage system (if any).
4. Channels (conduit), parameters to be used areshape (channel shape), max-depth (depth), length(channel length), roughness (channel roughness
coefficient).
5. Storage unit is the point of the drainage system
which is a storage volume. Safety storage units
include: elevation or altitude, maximum depth,
initial depth, potential evaporation, seepage
parameters (if any), external inflow data (if any).

RESULTS AND DISCUSSION
Processing News Using Nvivo
This research uses a news article that discusses
waste that occurs in the city of Pariaman, Lubuk
Alung, Padang (MUA PALAPA), using news datafrom 2009 - 2018. As for the publication of news in 1
event a lot, the news taken has very clear information,
especially the location affected by the flood. In thequotations obtained, flooding in the MUA PALAPA
area was more dominated by poor drainage, anddamaged river basins.
From the results of NVivo processing, the areathat is very often flooded is the Gunung Pangilun subdistrict, Padang City, with 8 times the number ofoccurrences in the period (2012-2018) from thearticles obtained. The problems that occur in thisregion are drainage which is not functioning
optimally, and so on. One example of a quote takenfrom the article is as follows: Sewerage in the GunungPangilun area [15], Jalan Gajah Mada, Padang City,
spilled over to cause a number of residents' houses
and several points of the road in the local area to be
flooded. For this reason, the researcher conducted astudy to identify the ability of Gunung Pangilun's
drainage, which is more precisely in the Jalan Gajah
Mada area.
Conduct Field Investigations
Field investigations aim to take secondary datasuch as locations affected by floods, andmeasurements of existing dimensions, and are used indata processing and guidelines for SWMM 5.1
modelling.

RESEARCH METHODOLOGY

Hydrological Calculation

This study is carried out by:Gather news about floods in the MUA PALAPA
from 2009 - 2018.
2. Processing flood news using NVivo software.
3. Determine locations that often occur in MUAPALAPA based on NVivo output.
4. Determine the slope of watershed by using
DEMNAS data.
5. Check and measure drainage in the field.

Rainfall Calculation Plan

1.

From the rainfall station map obtained, the station
closest to the study location is the Khatib Sulaimanrain station (Table 1), with a total data of 10 years.
This data will be used in the calculation of planned
rainfall.

392

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1. Rainfall data of the Khatib Sulaiman Station
RainfallRainfallYearYear(mm/day)(mm/day)
2009
160
2014
100
2010
220
2015
206
2011
330
2016
270
2012
143
2017
195
2013
128
2018
147
For the calculation of rainfall using the Gumbel
Method, Normal, Normal Log, Persion Type III Log,and the suitability of the planned rain data. With theresults of the compatibility test using the Chi Square
method with the results as shown in Table 2.

Hyetograph calculation of rain plan
X²cr
5.99
5.99
5.99
5.99

Information
AcceptAcceptAcceptNot Accepted

The results of the calculation can be seen in Table 3.
Table 3. Recapitulation of planned rainfall with the
Gumbel Method
XT
PUH(mm/day)
2
180
5
264
10
319
25
389
50
441
100
492

The calculation of the hourly rain distribution pattern
use the Alternating Block Method (ABM) with thedata taken from the results of the calculation of
rainfall intensity in Table 3 with the duration of therain event taken for 3 hours (Table 5 and Fig. 3).
Table 5. Hourly rainfall distribution patterns using
the ABM method
Durati Intensit
RainfallCum.
P
Hyetographon (t)y (It)(It x t)Rainfall
Hour
mm/h
mm
mm
%
%
mm
1.0
91.5
91.5
91.5
69.3
18.0
47.6
2.0
57.6
115.3
23.8
18.0
69.3 183.0
3.0
44.0
132.0
16.7
12.6
12.6
33.4
Total
193.1
338.8
132.0 100.0 100.0 264.0

183.0

200

Rainfall (mm)Table 2. Chi Square
Distribution Probabilities
X²
Gumbel Method
1.00
Normal Method
1.00
Log Normal Method
1.00
Log Pearson Type III
9.00
MethodCompatibility Test Results

Figure 2. Curve Intensity Duration Frequency (IDF)

Calculation of Rainfall Intensity
After obtaining rainfall values the calculation of
rainfall intensity was carried out using the Mononobe
method with a 5-year return period of rain. The resultsof the calculation of rain intensity in the form of an
IDF curve (Fig. 2) which will be used in the
preparation of the Hyetograph rain plan with the
Alternating Block Method (ABM). The calculation of
rainfall intensity using the Mononobe formula isattached to the Table 4 below.

150
100
50

47.6

33.4

0
1.0

2.0

3.0

Duration (Minute)Fig. 3 Rain plan hyetograph with the ABM method
Furthermore, the results of this rain distribution will
be used to calculate runoff discharge in EPA SWMM
5.1 simulations.

Table 4. Recapitulation of the intensity of the 5-year
rainy season with the Mononobe method
Duration
5 Year Period
MinuteHour
263.9530
0.5145.26
60
1
91.51
90
1.5
69.83
120
2
57.65
150
2.5
49.68
180
3
43.99

Simulation results with EPA SWMM 5.1
Runoff discharge
From the simulation, the results are good, where
the continuity error for surface runoff and flow
tracing is -0.19% and -1.62% respectively. The
393

SEE - Bangkok, Thailand, Nov.11-13, 2019quality of the simulation is not good if the continuity
error is> 10%. From the 13 Subscathment found in
this model, the highest peak runoff occurs at the
subcathment6, which is 6.91M3 / second which isseen at 3:00 in Fig. 4 below. This is the peak conditionof rain. While the Subcathment with the smallest
flowrate is Subcathment12 with a flow of 0.62m3 /sec.

In Fig. 5, the overflow channel is shown by a red line,
the channel that is not overflowing is shown in blue,
and the channel that returns to normal or recedes after
overflowing is shown in green. From the simulation
results it can also be seen that there is almost along
the drainage channel of the Jalan Gajah Mada area,
Gunung Pangilun Sub-District (Table 7) cannot
accommodate runoff that occurred at the 03.30
simulation. This is caused by the dimensions of thechannel that cannot accommodate runoff flow.

Fig. 4 Sub-catchment runoff of Gunung Pangilun area

Fig. 5 The channel that overflows at the EPA
SWMM 5.1 of Gunung Pangilun area

Location of flood points
Table 7. Conduit surcharge Summary
Hours
Hours
Hours
Hours
Con Both
Downst Above
Upstream
duit Ends
ream
Normal
Full
Full
Full
Flow
S2
1.03
1.03
1.03
0.07
S3
3.89
3.89
3.89
0.12
S4
4.68
4.68
4.68
4.58
S5
2.48
2.48
2.48
2.51
S6
3.32
3.32
3.32
3.28
S7
2.33
2.33
2.33
0.32
S8
4.72
4.72
4.72
4.66
S9
3.48
3.48
3.48
0.5
S10
1.76
1.76
1.76
1.78
S11
3.54
3.54
3.54
3.54
S12
0.82
0.82
0.82
0.82
S13
1.11
1.11
1.11
1.17

Table 6 below shows the location of the flooded
cross section. In addition, the duration of flooding andthe volume of flooding that occurs in the affected area
can also be known. Junction 6 is the longest point
experiencing flooding with a duration of 4.72 hours.
Junction 6 is the location of Gunung Pangilun
Elementary School 17, which is almost a flood areathat is in accordance with the field review. While thelargest volume occurs at J3junction is a link between
catchment area 3 and drainage channel Jl. Gajah
Mada and is the location of the Alfa Mosque's flood
permit in 2018 from news articles.
Table 6. Node Flooding Summary
Node
J1
J2
J3
J4
J5
J6
J7
J8
J9
J10
J11
J12

Hours
FloodedMax Rate
CMS

Hour ofMax
Flooding

1.04
3.9
4.68
2.48
3.33
4.72
3.72
3.49
1.77
3.56
0.83
1.13

0.456
6.573
6.5
3.095
4.457
5.584
3.614
5.211
4.065
5.518
1.502
1.765

3:00
3:00
3:00
3:00
3:00
3:00
3:00
3:00
3:00
3:00
3:00
3:00

Total
Flood
Volume10^6 ltr
1.312
31.6
41.05
12.14
21.1
21.33
31.92
23.74
13.22
30.91
2.47
4.17

Hours
Capacity
LimitedCONCLUSIONS
From the simulation results using the NVivo
application, the location of frequent flooding was
found in the MUA PALAPA area (Padang, Lubuk
Alung, Pariaman), namely the Gunung Pangilun
Padang area.
Furthermore, the floods were calculated in the
Gunung Pangilun area where the largest peak runoff
occurred at sub-catchment 6, which amounted to
6.91m3 / second, which was the location of GunungPangilun Primary School No. 17, which was almost
flooded according to the field review, and the news
obtained was carried out. Sub-catchment with the

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1.03
3.89
4.68
2.48
3.32
2.33
4.72
3.48
1.76
3.54
0.82
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SEE - Bangkok, Thailand, Nov.11-13, 2019

smallest runoff peak flow is sub-catchment 12 with aflow of 0.622 m3/sec.
There are 8 channels that are the location of flood
points during the simulation hours of 3:30, namely
channels S3, S4, S5, S6, S7, S8, S9, S10, while thechannels that do not overflow during flood arechannels S2, S11, S12 and S13. The overflow ofwater in the channel occurs because of the capacity of
the channel that cannot accommodate runoff
discharge, the waste contained in the channel, and theaccumulation of sediment in the canal.
Risk flood can be minimised by: normalize thedrainage, widened the dimensions of drainage, andcreate a retention pool in a sub-catchment area thathas a large impact discharge.

Unjust waters: climate change, flooding and the urban
poor in Africa. Environment and urbanization, 20(1),pp. 187-205.
[7] Rossman, Lewis A. 2015. Storm Water
management Model User’s Manual Version 5.1. U.S
Environmental Protection Agency, USA.
[8] Hidayat, B, 2017, Understanding Flood Disasters
in Padang ity with Content Analysis of News Articles(in bahasa: Memahami Bencana Banjir di Kota
Padang dengan Content Analysis Artikel Berita),
Civil Engineering Journal, Andalas University.
[9] Legowo, S., Hadihardaja, I. K., Enung, T. S. H,.
2019. Application of the Digital Elevation Method for
Flood Estimates on the Ciliwung River in West Java,International journal of GEOMATE, July 2019,Vol.17, Issue 59, pp.154-165.
[10] Vinay, R., Umamahesh, N., Sriramoju, P. S.,
Kumar, P. A. 2018. Simulation of the Urban Drainage
System using the Storm Water Management Model(SWMM). National Institute of Technology,
Warangal, Andhra Pradesh, India.
[11] Waikar, L, M and Namita, U. 2015. Model ofFlood Transfer using EPA SWMM 5. Department ofCivil Engineering and Water Management, TechnicalInstitute and Guru Shri Guru Gobind Singhji
Teknologi Nanded, (M.S) India.
[12] Fairizi, D, 2015. Drainage Channels Analysis
and Evaluation in Talang Kelapa Housing Area in
Sub watershed Lambidaro, Palembang City.
University of Sriwijaya.
[13] Kamiana, I Made. 2011, Debit Calculation
Techniques for Infrastructure (in bahasa: Teknik
Perhitungan Debit Rencana Bangunan Air), Graha
Ilmu, Yogyakarta[14] Chow, V.T., Maidment, D.R. & Mays (1988)
Applied Hydrology. New York: Mc Graw-Hill Book
Company.
[15] Istijono, B., Aprisal, Ophiyandri T., andNurhamidah. 2019. A Study of the Quality of Soil
Infiltration at the Downstream of Kuranji River,
Padang City. International Journal of GEOMATE,
April 2019, Vol.16, Issue 56, pp. 16-20

ACKNOWLEDGEMENTS
This research was funded by University ofAndalasunder
Research
Grant
Number:T/24/UN.16.17/PP.IS-KRP1GB/ LPPM/2019 dated
13 May 2019.
REFERENCES[1] Book III of National Mid-term Development

Planning 2015-2019.
[2] Istijono, B., Ophiyandri, T., Aprisal andNurhamidah. 2019. The Effect of Flood to Quality
Index of Soil Physical Properties at the Downstreamof Kuranji River Watershed, Padang City.
International Journal of GEOMATE, Feb., 2019Vol.16, Issue 54, pp.74 – 80.
[3] Khan, A. N. (2013). Analysis of 2010-floodcauses, nature and magnitude in the Khyber
Pakhtunkhwa, Pakistan. Natural hazards, 66(2), pp.
887-904.
[4] Gale, E. L., & Saunders, M. A. (2013). The 2011
Thailand flood: climate causes and return periods.
Weather, 68(9), pp. 233-237.
[5] Adelekan, I. O. (2011). Vulnerability assessmentof an urban flood in Nigeria: Abeokuta flood 2007.
Natural Hazards, 56(1), pp. 215-231.
[6] Douglas, I., Alam, K., Maghenda, M., Mcdonnell,Y., McLean, L., & Campbell, J. (2008).

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SIMULATION OF THE COLLAPSE PROCESS OF INFRASTRUCTURE
USING GENERAL-PURPOSE PHYSICS ENGINE
Yoshihiro Kabeyama1, Sunao Fujimura2 and Shinichiro Okazaki3
1,2
Graduate School of Engineering, Kagawa University, Japan;
3
Faculty of Engineering and Design, Kagawa University, Japan;

ABSTRACTIn recent years, tsunamis caused by earthquakes and flooding associated with heavy rainfall have occurred inJapan. It has often been reported that bridges collapsed because of the outflow of the bridge superstructure and thescouring of the bridge pier resulting from these causes. However, to simulate these phenomena, it is necessary to
carry out coupled analysis of three types of behavior of the structure, ground, and fluid, and the calculation cost isvery large. Therefore, the examination of this phenomena has not currently achieved much progress. The purposeof this research was to perform a fluid–ground–structure simulation (such as for the collapse of a bridge pierbecause of flooding) at low cost, using a general-purpose physics engine. In this study, the focus was on thesimulation of large deformations of the fluid, ground, and structure, and all objects were modeled with particles.
First, the parameters that can simulate the behavior of the fluid were set appropriately by using the dam breakproblem. Subsequently, the flooding phenomenon in a river and the scouring phenomenon on a bridge pier on the
ground were simulated using these parameters.
Keywords: Physics simulator, Scouring phenomenon, SPH method

simulate these phenomena, it is necessary to couple
the three-phase behavior of the fluid–ground–structure, and the time and load required for modelingand calculation are very large. The examination ofthis phenomenon using numerical analysis has not
significantly progressed, especially in three
dimensions. Handling river flow is very important,and plays an important role in revetment work and thedesign of the bridge.
In particular, it is difficult for the finite-element
method (FEM) to reproduce complicatedly changing
free surfaces in fluid simulation. In addition, it isnecessary to reproduce the fluctuation of the riverbed
caused by the river flow scooping the ground.
Moreover, in this research, more-complicatedanalysis is required, because the calculation data forthe bridge are included. Although three-dimensional
software that can easily simulate such a large
deformation has been developed, it is expensive.
Therefore, in this research, an attempt was made tosolve the soil–fluid–structure interaction problem,
which has been difficult to study because of the large
computational load, at low cost and in a relatively
short time by using a physical simulator that can beused free of charge and has high versatility.

INTRODUCTION
In recent years, damage such as deep deformationof the lower structure has frequently occurred inJapan, along with damage of the upper structure ofriver bridges due to floods and tsunamis [1]. Heavy
rains in the western Japan region that occurred in July
2018 caused damage to many bridges in the Japan
Railway Shikoku area. This forced the trains to be
shut down and affected many users. In the case of the
Saita River Bridge between the Yosan Line
Motoyama and Kannonji Temple, the bridge piersloped because of the scouring, causing deformationof the superstructure. The Saita River Bridge is built
on a river that usually has a small amount of water.
However, on the day of heavy rains, the water flow
was higher than expected. As a result, the ground wasscoured by the river flow, and the bridge pier was
inclined. This kind of damage has been experienced
frequently since ancient times, and it is thought that it
is possible to avoid damage by studying disaster cases.
In recent years, with the development of numericalcalculators, the study of disaster risk by machinelearning has been carried out, and it is currently
possible to extract a pier having a high risk ofscouring with high accuracy. However, theconstruction of a more accurate forecasting model
requires a high-level understanding of the scouringphenomenon, and studies considering changes in thevaried topography of the river, ground conditions, andthe river flow are necessary. The method of numericalcalculation makes it possible on a computer. To

SIMULATION METHODSoftwareIn this study, a general-purpose physics simulator(Blender) was used. Blender is equipped with a
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physics engine called Bullet, and this software cansimulate an object from rigid body to soft body as adiscrete body or a continuum. In addition, it supports
optimization to the GPU using CUDA and canperform three-dimensional simulation at high speed[2]. This simulator is based on the smoothed-particle
hydrodynamics (SPH) method, and can simulate large
deformation of both fluids and solids. However, thesetting of the parameters that govern the behavior
between particles is very different from generalnumerical analysis, such as the FEM. Therefore, toperform accurate simulation, it is necessary toconfirm the validity of the behavior of the fluid,which is originally a continuum, as a connectedparticle group, and it was examined by comparison
with the existing experimental results whensimulating.

body by expressing the continuum with a finite
number of particles by the Lagrange method. The
SPH method is suitable for problems with large-scalechanges in objects, and it is used in such fields as
structural mechanics and fluid dynamics [4], [5]. In
general, calculation of simulation by a continuum
requires enormous time, and it frequently cannot becalculated by a general-purpose PC. The method
using discrete fields is possible without incurring
much time. However, the calculation accuracy of the
SPH method itself, and the handling of boundary
conditions, are not well established. Further, it isdifficult to reproduce the fluid by discrete bodies;
hence, it is not performed very often. It is necessary
to verify the validity by combining an infinite numberof parameters (with the result of the element
experiment in each component), and the experimental
result in which the interaction between thecomponents is considered, considering the setting ofparameters, etc.

REPRESENTATION TECHNIQUE OF MODEL
Particle and Grid Methods for Rigid-Body
Simulations

Particle System

When simulating a rigid body, it is common to use
polygons to calculate and express accurately.
However, as the shape becomes more complex, theamount of information processed by the model
becomes larger, and complex calculations are
required for continuum collision calculation. In theprocess of calculating such complicated behavior, thedeformation of the mesh may break the calculation.
Therefore, by using particles instead of polygons forrigid-body representation, mesh problems do notoccur, because the interaction between particles iscalculated. It is also possible to reduce the cost ofcomputation by limiting the range of interaction. By
this means, physical simulation close to reality is
performed at high speed [3].

Blender is equipped with Particle System. Particle
System is a computer graphics technology, and verysmall objects called “particles” can represent
irregularly shaped materials that exist in the natural
world. By placing an object called Emitter in Blender,
one can release and control particles from there. Also,
particles can be influenced by gravity and otherexternal forces, and the effects of interference ofdifferent particles can also be expressed. In otherwords, it is considered that the simulation of scouring
can be expressed by interacting different fluid andsoil particles represented by particles.
PARTICLE MODEL SETTING
Blender particles have various parameter settings.
The Bullet installed in Blender has features that allow
parallel computation by a CPU or GPU, and it cansolve various physical phenomena very fast. However,the code is a black box, and viscosity, stiffness, andmass parameters governing particle motion areunitless, so it is impossible to divert actual fluid andsolid parameters as they are. Therefore, in the case of
fluid simulation, for example, it is necessary to set
parameters that can simulate this behavior
appropriately after conducting element experiments
to understand the characteristic behavior of the fluid.
In this research, the focus is on the behavior of thefluid among the phases that describe the scour
phenomenon first, and the fluid-related parameters
are set to be able to reproduce the dam breaking
problem with high accuracy. Subsequently, a model
was constructed that can reproduce the behavior ofsoil particles under the action of fluid appropriately.

Fig. 1. Structure of cubes
SPH Method
In this research, the aim was to solve the ground–
fluid–structure coupled problem of slope by scouringof the bridge by creating a fluid model, soil particle
model, and bridge pier model using the SPH method.
The SPH method is a numerical analysis method
and is classified as a meshless method. Among themeshless methods, the SPH method can replace thebehavior of a continuum with the motion of a discrete
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SEE - Bangkok, Thailand, Nov.11-13, 2019

results for each set value of each parameter. The
validity of this simulation was confirmed by image
comparison with experimental fluid behavior.
Table 1 show the values that are closest to theexperimental fluid behavior as a study of parametervalue.

SIMULATION RESULT
Dam Break
Simulation method
The dam break problem is often used to verify thevalidity of a model that describes the free surface flow
field. In this study, the fluid was represented byparticles, and the experimental device was created bya mesh frame. The scale of the model to be created
was 50 × 100 × 60 mm, as shown in Fig. 2. Then, thefluid was set to a portion 30 mm from the bottom inthe model, the weir was removed at once, and theflow was tracked. This frame ignores the friction withthe particle. In the particle parameter settings, theinitial settings were set with reference to books or theInternet site of simulation [6]-[8]. Above all, size andrest density had a large influence on the interaction
range and fluid behavior, and other parameters wereset based on these. Figure 3 shows the simulated

Fig. 3.

Fig. 2.

Comparing dam break simulation result with parameter
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Mesh frame modelSEE - Bangkok, Thailand, Nov.11-13, 2019

in the following simulations.
Collapse Simulation
Simulation method

Fig. 4.

Infiltration, overflow, erosion, earthquakes, etc.
can be mentioned as factors that cause the dike andbridge of the river to be destroyed. The scouringphenomenon is included in the erosion. Scouring is aphenomenon in which local erosion, which did notoccur in steady-state water flow, happens when theriver flow increases because of floods associated withheavy rainfall and the water flow is disrupted.
Scouring makes the superstructure unstable because
of settlement and outflow of the foundation part. The
progress of such scouring may cause the bridge pierto slope, and even collapse.
In the simulation of the scouring phenomenon,
three types of particle (fluid, foundation, and bridge
structure) were set to solve the fluid–ground–structure interaction problem. Here, to express thefoundation and the pier, Molecular Script was used as
the setting of particle. In Molecular Script, there is amethod called activated particle linking that connects
particles, and it is possible to determine the strengthof the connection (search length) and the number tobe connected (max links) as the setting value among
them. These settings are shown in Table 2.

Result of dam break simulation

Table 2. Settings of understructure and pierThe simulated result of the dam break using thissetting is shown in Table 1. At frame 0, the stored
fluid drains by removing the weir. At the frame 8, The
fluid collides with the opposite wall and bounces up.
Then the fluid bounces back and is approachingequilibrium. This simulation of frame rate is 24 fbs.

Search length
Max links
Broken% linkingTable 1. Setting of fluid

Bridge pier
4.0
16
100.0
0.0

Mesh frame model

Fluid
Particles
Size
Rest Density
Mass
Stiffness
Viscosity

Foundation
1.7
2
5.0
0.06

7000
0.011
0.5
4.0
4.0
1.4

The experimental equipment for simulatin was
created in the same way as a dam break. In thi model,
the water flow path, the foundation to be the ground,and the bridge pier installed on this foundation wereset. In past research, experiments on such conditions
were not conducted, so, in consideration of theperformance of the PC used (Intel Core i7-7820X
CPU ＠ 3.60 GHz, System x64 base processor,
Compute Device: CUDA GeForce GTX 1080
Ti(Display)), a model was set up and solved, as
shown in Fig. 6. Figure 6 shows the setting values ofthe mesh frame.

Simulation results
In Fig. 5, the left side of the figure is theexperimental behavior of the fluid, and to the right is
the result of the simulation by Blender. Comparing
these shows that the fluid did not bound significantly
at 0.6 s, but at other times it showed almost the same
behavior as the experiments. This value was applied

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 5. Comparing dam break simulation result with experiment
CONCLUSIONS

Bridge pierIn this study, the problem of the scouring of abridge pier by a flood was addressed using a generalpurpose physics simulator. To carry out thesimulation at low cost, an attempt was made to solve
the fluid–ground–structure three-phase coupledproblem using the SPH method. The physics engine
Bullet used in Blender does not disclose the physics
formula, so it is very difficult to control theparameters used in the computation. An attempt wasmade to confirm the validity by comparing a dam
break with an experiment to reproduce water byparticles. Although the characteristic movement of
the fluid could be captured partially, it was notpossible to reproduce the surface tension of the waterand the associated bounce. In the simulation ofscouring, three kinds of particle (fluid, groundfoundation, and bridge structure) were treated at thesame time. The aim was to solve the fluid–ground–structure interaction problem by this. Here, to express
the foundation and the bridge pier, New links wasused as the setting of the particles. New links (%linking) can reconnected particles disconnected by
fluid impact. It transpired that New links not only
works on the particle that has been activated, but also
on other particles. Although there was a limit to thesegmentation of the model because of theperformance of the PC, it was possible to simulate theinclination of the bridge pier by scouring.
As a result, although valid parameters wereobtained, when the basic part was subdivided toperform a more accurate simulation, the correct
simulation could not be calculated with the same

River

Foundation
Fig. 6.

Mesh frame model
Water channel:
Height 0.4 m, width 2.0 m, length 6.0 m
Foundation:
Height 1.4 m, width 2.0 m, length 2.0 m
Bridge pier:Height 2.0 m, width 1.2 m, length 0.9 m

Simulation Results
The foundation was excavated by the runningwater, and it was confirmed that the bridge piers were
eventually inclined. In addition, it was confirmed
from the calculation process that the collapse of thebridge pier did not stop and became unnatural.
Therefore, it was decided to handle new linking as a
new setting. With this setting6, the disconnectedparticles can be rejoined, and the bridge was
successfully made to collapse gently. The results areshown in Fig. 7. It was also confirmed that theconnection between particles with these settings
affects not only the set particles, but also otherparticles. To improve the simulation accuracy, it isinevitable to reduce the size and increase the numberof particles. In the future, it will be necessary to study
the object in a more subdivided model by particles.
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SEE - Bangkok, Thailand, Nov.11-13, 2019setting. In other words, the size of the particle andeach parameter value are considered to have a strong
relationship with each other.

Grant-in-Aid for Young Scientists (A) and the Crossministerial Strategic Innovation Promotion Program(SIP) for their financial support.

SettinFrameg count: 1－350
Frame Rate: 24 fps
Rendering time: 6 h
24min

Fig. 7.

REFERENCES[1] Kazuo Ishino et al., A collapse factor and themeasures of the bridge by the heavy rain that
occurred in Japan after 2004, 安全問題研究論文
集, Vol. 5, 2010.
[2] Tomihisa Yuki, CPUとGPUの性能比較 ～ 行列計算およびN体問題を用いて ～, 2011, pp.128.
[3] Tanaka Masayuki. et al., Particle-based Rigid
Body Simulation and Coupling with Fluid
Simulation, Transaction of JSCES, Paper
No.20070007, 2007.
[4] Seiichi KOSHIZUKA, Numerical Analysis of
Flow using Particle Method, Flow21, 2002,
pp.230-239.
[5] Tanabe syoiti. et al., A FLUID-RIGID BODY
SIMULATION BY USING THE SPH
METHODAND ITS APPLICATION TO
BRIGDE RUNOFF SIMULATIONSPH, J.JSCE,
Ser.A2 （ Applied mechanics ） Vol.70, No.2
（JSCE VoL.17）, (2014), pp.329-338.
[6] Todo＋＋, Blender 2.7 Master Book Sculpt &Simulation. Tokyo, Cut system Inc., 2015.6, 459p
[7] Tony Mullen, Physics simulation Blender, Tokyo,
ASCII Media Works Inc., 2008, 12. 458p.
[8] Introducing particle fluids parameters, available
from<https://farsthary.wordpress.com/2010/03/19/intr
oducing-particle-fluids-parametters-function/>,(accessed 2018-07-22)

Collapse simulation result

ACKNOWLDGMENTS
The authors would like to express gratitude to a401

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

MOTORCYCLE-RELATED DEATHS AND HELMET USAGESITUATION IN THAILAND
1

Jetsada Kumphong1, Thaned Satiennam1 and Wichuda Satiennam1
Department of Civil Engineering, Faculty of Engineering, Khon Kaen University, Thailand.
ABSTRACTThe high death of motorcycle riders than drivers of other vehicles and low helmet wearing rate is a serious
problem in Thailand. This study aimed to evaluate the effects of helmet wearing on motorcycle riders’ death rates
nationwide. Data were collected from 77 provinces in Thailand between 2012 and 2016. These data included
number of police stations, helmet usage percentage, motorcycle-related death rates per 100,000 population andmotorcycle-related death rates per 10,000 motorcycles registered in each province. Pearson correlation analysis
was used to test the correlations between studied variables. The correlation between helmet usage percentage andmotorcycle-related death rate was almost significant. The helmet usage percentage was significantly consistent
with number of police stations. Helmet usage was the significant with variable affecting motorcyclists’ death rates,
leading to the conclusion that wearing a motorcycle helmet reduces the head injury and risk of death from a
motorcycle crash. Helmet law enforcement should be effectively supported by the motorcycle safety plan of theRoyal Thai Police.
Keywords: Fatality, Motorcycle, Safety, Helmet usage

Table 1 Thailand motorcycle-related death rates
between 2012 and 2016

INTRODUCTION
According to the traffic fatality data surveyed by
the World Health Organization (WHO) [1-4], theoutcomes of motorcycle-related accidents are
categorized as ASEAN countries’ social as well as
health problems. Motorcycles are widely used fortransportation and sport activities in these countries,
and the number of motorcycles at present is greaterthan the number of cars [5-8].
Thailand has a higher motorcycle-related death
rate than other countries. Motorcyclists are more than
70% likely [3] to die in road accidents than drivers ofother vehicles and low helmet wearing rate as shownin Table 1 and Table 2
Head injury is a major cause of motorcyclerelated deaths from road accidents. However, there
are clear indications that helmets can reduce theseverity of head injuries during crashes [9-10].
Table 1 shows the motorcycle-related death rates
per 100,000 population and the motorcycle-related
death rates per 10,000 motorcycles registered fromthe years 2012 to 2016. It can be seen that during thisperiod, the death rates per 10,000 motorcycles
registered in Thailand has an increasing trend every
year.
Likewise, when the type of motorcycle groups inThailand was considered, it was found then the
motorcycles over 150 CC and 126-150 CC became
increasingly popular among the new generation. In
Table 3, it can be seen that motorcycles over 150 CC
registration continued to increase from 2014, while
the data remained consistent with the motorcyclerelated deaths.

Year

No. ofmotorcyclerelated
deathsThe
motorcyclerelated
death rates
per 100,000

The motorcyclerelated death rates
per
10,000
motorcycles
registered20125798 a9.00 a,c
25.71 a,b
2013
5593 a8.58 a,c
26.38 a,b
20145394 a8.28 a,c
29.67 a,b
a
a,c
2015
5863
8.92
32.40 a,b
a
a,c
2016
6083
9.17
31.81 a,baSources: The Bureau of Non Communicable
Diseases of the Ministry of Public Health [11];bDepartment of Land Transport, 2012-2016[12].
Table 2 Helmet usage rates between 2012 and 2016
Year

Helmetusage
percentage(Mean %)

Helmetusage
percentag
e of riders(Mean %)

Helmetusage
percentag
eofpassengers(Mean %)

2012
43d
52d
20d
d
d
2013
43
51
19d
d
d
2014
42
51
19d
2015
43d
51d
20d
2016
43d
51d
20d
d
Sources: Thai Roads Foundation, 2012-2016 [13]Table 3 The motorcycles registered and number ofmotorcycles registered

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SEE - Bangkok, Thailand, Nov.11-13, 2019

No. ofNo. ofmotorcycles
motorcycles
registeredregistered(126-150 cc)(>150 cc)2012
28970 b47948 b
b
2013
25900
69777 b
b
2014
68706
48703 b2015109166 b
53930 b2016153290 b
80551 bb
Sources: Department of Land Transport, 2012-2016[12].

rates – among motorcyclists – and low percentages ofhelmet usage [7, 15]. In this research, the firstobjective was to study the differences of helmet usage
percentage between riders and passengers, and thesecond was to study the correlation between thehelmet usage percentage, motorcycle-related deaths
and number of police stations. The data collected
covered all of the 77 provinces in the country, from2012 to 2016.

There are 77 provinces and 5 regions in Thailand,
including the North, Northeast, Central, West andSouth, as illustrated in Table 4.

Data retrieval and entry

Year

METHODOLOGYThis study investigated the secondary data on
motorcycle accident numbers obtained from the
Bureau of Non Communicable Diseases of the
Ministry of Public Health, 2016 [11]; helmet usage
percentage report by Thai Roads Foundation,
2016[13]; the size of population by the National
Statistics Bureau, 2016 [16]; the number ofmotorcycles registered from the Department of Land
Transport, 2016[12]; and the number of police
stations from the Royal Thai Police, 2016 [17]. All of
the data were separated into their respective
provinces. The variables were motorcycle-related
deaths, helmet usage percentage, population size,
number of motorcycles and number of police stations.

Table 4 Thailand provinces
Provinces
Chiangrai, Chiangmai, Nan,
Phrae, Phayao, Mae Hong Son,
Lampang, Lamphun, Uttaradit.
The
Khon Kaen, Chaiyaphum,
NorthNakhon Phanom, Nakhon
East
Ratchasima, , Mukdahan,
Yasothon, Roi Et, Loei, Sisaket,
Sakon Nakhon, Surin, Nong
Khai, Nong Bua Lam Phu,
Udon Thani, Ubon Ratchathani,
Amnat Charoen.
CentralBangkok, Kamphaengphet,
Chai Nat, Nakhon Nayok,
Nakhon Pathom, Nakhon
Sawan, Nonthaburi, Pathum
Thani, Phra Nakhon Si
Ayutthaya, Phichit,
Phitsanulok, Phetchabun, Lop
Buri, Samut Prakan, SamutSongkhram, , Sukhothai,Suphan Buri, Ang Thong, Uthai
Thani.
East
Chanthaburi, Chachoengsao,
Chonburi, Trat, Prachin Buri,
Rayong, Sa Kaeo.
West
Kanchanaburi Tak, Prachuap
Khiri Khan, Phetchaburi,
Ratchaburi.
South
Krabi, Chumphon, Trang,
Nakhon Si Thammarat,
Narathiwat, Pattani, Phangnga,
Phatthalung, Phuket, Yala,
Ranong, Songkhla, Satun, Surat
Thani.
RegionNorth

Statistics
T-test was used to test the differences of helmet
usage percentage between the rider group and thepassenger group [18]. Logarithmic transformation of
motorcycle-related death per 100,000 populations
per 10,000 motorcycles registered was performed as
it was the best applicable method [15]. A Pearson
correlation test was used to correlate different
variables [19].
RESULTS AND DISCUSSION
Test of differences of helmet usage percentages
Table 5 shows t-test significant level of differences
between results obtained from helmet usage
percentage of riders and helmet usage percentage ofpassengers by province in Thailand, . As shown in thetable, the significant levels (p<0.001), are less than
0.05. Hence, the significant level of differences is said
to be at 0.05. The t-test analysis indicated that thehelmet usage percentage of riders and helmet usage
percentage of passengers has 0.05 significant
differences.

The above problem is aggravated by otherproblems. On the one hand, helmet law enforcementin Thailand is relatively low. The other involves low
percentage of helmet usage [1-4, 14]. Many studies
similarly show the correlation between high fatality

Correlations between the studied variables
The result of correlations analysis indicates thatthe helmet usage percentage has a significant and403

SEE - Bangkok, Thailand, Nov.11-13, 2019

negative correlation with the log transformation of
motorcycle-related death rate/100,000 population at
the 95 % confidence level (R = -0.224, p <0.001). The
helmet usage percentage of riders has a significant
and negative correlation with the log transformationof motorcycle-related death rate/100,000 population
at the 95% confidence level (R = -0.187, p <0. 001).
Similarly, the helmet usage percentage of passengers
has a significant and negative correlation with the logtransformationofmotorcycle-related
death
rate/100,000 population at the 95% confidence level(R = -0.243, p <0.001). The number of police stations
also has a significant and negative correlation withthe log transformation of motorcycle-related death
rate/100,000 population at the 95 % confidence level(R = -0.174, p =0.001).

concluded that the laws related to helmet wearing canreduce the fatality rates. Some provinces have a low
number of motorcycle-related deaths, possibly owing
to high helmet usage percentage. Also, high helmet
usage percentage results from the high degree ofhelmet enforcement efficiency which in turn is basedon the number of police stations in each province.
Table 6 Correlations between the motorcycle-related
death rate/100,000 population and other variables.
Log transformation of
motorcycle-related
death rate/100,000
population

Table 5 Significant level of differences between
results obtained from helmet usage percentage ofriders and helmet usage percentage of passengers byprovince in Thailand
DifferenceSig.

<0.001

55.23

Std. Error
Mean

0.52

SD.

10.27

(Helmet usage
percentageofriders)–(Helmet usage
percentage
ofpassengers )

28.90

Mean

t

Log transformation of
motorcycle-related
death rate/10,000
motorcycles registered

Pearsoncorrelation.
Sig.

0.620 ๕๕Helmet usage
percentage (Overall)Pearsoncorrelation.
Sig.

-0.224 ๕๕Helmet usage
percentage of riders

Pearsoncorrelation.
Sig.

-0.187 ๕๕Helmet usage
percentage ofpassengers

Pearsoncorrelation.
Sig.

-0.243 ๕๕

Number of police
stations

Pearsoncorrelation.

-0.174 ๕๕

Sig.

0.001

<0.001<0.001<0.001<0.001*

Statistically significant at 5%.
๕๕Statistically significant at 1%.

In addition, the result of correlations analysis
indicates that the helmet usage percentage of riders?
has a significant and negative correlation with the logtransformationofmotorcycle-related
death
rate/10,000 motorcycles registered at the 95%
confidence level (R = -0.117, p =0.022). The helmet
usage percentage of passengers has a significant andnegative correlation with the log transformation of
motorcycle-related death rate/10,000 motorcycles
registered at the 95% confidence level (R = -0.267, p<0. 001). The number of police stations has asignificant and negative correlation with the logtransformationofmotorcycle-related
death
rate/10,000 motorcycles registered at the 95%
confidence level (R = -0.349, p =0.001).
Moreover, the result of correlations analysis
indicates that the overall helmet usage percentage hasa significant and positive correlation with the numberof police stations at the 95% confidence level (R =0.299, p <0.001). The helmet usage percentage ofriders has a significant and positive correlation with
the number of police stations at the 95% confidence
level (R = 0.253, p <0.001). The helmet usage
percentage of passengers also has a significant andpositive correlation with the number of police stations
at the 95% confidence level (R = 0.365, p <0.001) asshown in Table 6, 7, 8, 9, 10 and Table 11. It can be

Table 7 Correlations between the motorcycle-related
death rate/10,000 motorcycles and other variables
Log transformation of
motorcycle-related
death rate/10,000
motorcycles
Log transformationof motorcyclerelated death
rate/100,000
population
Helmet usage
percentage (Overall)Helmet usage
percentage of riders
Helmet usage
percentage ofpassengers
Number of police
stations*

Pearsoncorrelation.

0.620 ๕๕Sig.

<0.001

Pearsoncorrelation.
Sig.
Pearsoncorrelation.
Sig.
Pearsoncorrelation.
Sig.
Pearsoncorrelation.
Sig.

-0.117 ๕

Statistically significant at 5%.
๕๕Statistically significant at 1%.

404

0.022
-0.0580.254-0.267 ๕๕<0.001-0.349 ๕๕<0.001

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 8 Correlations between the helmet usage
percentage (Overall) and other variables.
Helmetusage
percentage(Overall)-0.224 ๕๕

Log transformation of
motorcycle-related
death rate/100,000
population

Pearsoncorrelation.

-0.243 ๕๕

Sig.

<0.001

Log transformation of
motorcycle-related
death rate/10,000
motorcycles registered

Pearsoncorrelation.
Sig.

-0.267 ๕๕Helmet usage
percentage (Overall)Pearsoncorrelation.

0.752 ๕๕Sig.

0.976 ๕๕Helmet usage
percentage of riders

Pearsoncorrelation.

<0.001
0.633 ๕๕<0.0010.752 ๕๕Number of police
stations

Pearsoncorrelation.
Sig.

Log transformation of
motorcycle-related
death rate/100,000
population

Pearsoncorrelation.
Sig.

<0.001

Log transformation of
motorcycle-related
death rate/10,000
motorcycles registered

Pearsoncorrelation.
Sig.

-0.117 ๕Helmet usage
percentage of riders

Pearsoncorrelation.
Sig.

Helmet usage
percentage ofpassengers
Number of police
stations

Pearsoncorrelation.
Sig.
Pearsoncorrelation.
Sig.

Helmet usage
percentage ofpassengers

0.022

Sig.

<0.0010.299 ๕๕<0.001

Table 11 Correlations between the number of police
stations and other variables.

Table 9 Correlations between the helmet usage
percentage of riders and other variables.

Log transformation of
motorcycle-related death
rate/10,000 motorcycles
registered
Helmet usage percentage(Overall)Pearsoncorrelation.
Sig.

Helmet usage percentageof passengers
Number of police
stations

Numberof police
stations

Helmetusage
percentage
of riders-0.187 ๕๕<0.001-0.058Log transformation of
motorcycle-related
death rate/100,000
population

Pearsoncorrelation.
Sig.

-0.174 ๕๕

Log transformation of
motorcycle-related death
rate/10,000 motorcycles
registered
Helmet usage percentage(Overall)Pearsoncorrelation.
Sig.

-0.349 ๕๕

Pearsoncorrelation.
Sig.
Pearsoncorrelation.

0.299 ๕๕Sig.

<0.0010.356 ๕๕0.254

Pearsoncorrelation.
Sig.
Pearsoncorrelation.

0.976 ๕๕Helmet usage percentage
of riders<0.001
0.633 ๕๕Helmet usage percentageof passengers

Sig.

<0.0010.253 ๕๕Pearsoncorrelation.
Sig.

<0.001

Statistically significant at 5%.
๕๕Statistically significant at 1%.

Statistically significant at 5%.
๕๕Statistically significant at 1%.

Pearsoncorrelation.
Sig.

<0.0010.356 ๕๕**Log transformation of
motorcycle-related
death rate/100,000
population<0.001

Pearsoncorrelation.
Sig.

0.001

<0.001<0.0010.253 ๕๕<0.001*

Statistically significant at 5%.
๕๕Statistically significant at 1%.

<0.001
The results of this study show that deaths ofmotorcycle riders in Thailand have tended to increase
every year. This may be a problem related to relaxed
law enforcement among motorcycle riders, resulting
in low rates of helmet wearing in Thailand. Moreover,it was found that the rate of helmet usage among
motorcycle passengers was lower than 20% on
average in each province.
From the problems mentioned above and from thedata available, the relation of variables can be shownand consequently solutions recommended. The*

Statistically significant at 5%.
๕๕Statistically significant at 1%.

Table 10 Correlations between the helmet usage
percentage of passengers and other variables.

405

SEE - Bangkok, Thailand, Nov.11-13, 2019

results of the analysis demonstrate that the problem
of increasing motorcycle fatalities can be managed byencouraging, or enforcing, riders to wear a helmet. As
such, fatal head injuries can be reduced.
Motorcyclists riding without helmets show a 44%
higher chance of the head injuries being intracranial
injuries [20]. The severity of head injuries issignificantly lower when wearing a motorcycle
helmet according to the Glasgow coma scale [15, 21].
Present studies suggest that the life of one person per
million can be saved each year with a 10% increasein motorcyclists wearing helmets. Riders are reluctant
to wear helmets, citing that wearing a helmet causes
discomfort and the use is unsafe [15, 22]. According
to a research study from China, Li et al. (2008) [23]found 70% of motorcyclists perceive wearing ahelmet as uncomfortable. Approximately 40% of
motorcyclists claim that wearing a helmet impairs thevision. 75% of riders only wore a helmet to escapefines from the authority. McKnight et al. (1995) [24]carried out a comprehensive study on the impairmentof sound and vision whilst wearing a helmet. Riders
wearing helmets need to pivot their heads more to
expand the range of vision.
In this research, the number of police stations ineach province was taken as a variable of law
enforcement. The analysis clearly indicates that if thenumber of police stations were to increase in eachprovince, there would be more officers to effectively
enforce the law in that area and the helmet wearing
rate would almost certainly increase. However, in
reality, certain technologies could also be used to
enforce law such as CCTV helmet camera detectorsthat operate 24 hours a day [25-26]. Helmet usage
percentage not only depends on the existence oflegislation but also on the effectiveness of law
enforcement. Kumphong et al. (2017) [27] studied
the social norms and Perceived Behaviour Control(PBC) and found that both are significant and affectthe intention of helmet use. However, some studies
have found Descriptive Norm and Injunctive Norm
were the highest influencing factors that could
account for 25% and 38% of variance of helmet use
intention by Theory of Reasoned Action (TRA)
model and Theory of Planned Behavior (TPB) model.
This is consistent with a study conducted on students
in the city of Ho Chi Minh, Vietnam and Vientiane,
Laos [28-29].To conclude, it is not only the matter oflaw enforcement over motorcyclists’ use of helmet,
but the attitudes and environmental factors also play
an important part in their intention to wear a helmet.

be effectively supported by motorcycle safety
programs of the Royal Thai Police. This finding isuseful as a guideline to set a policy for reducing
motorcycle-related deaths. The available helmet law
issueless if it is not enforced effectively on
motorcyclists all over the country. In addition, thehelmet law should also have a control over thepassengers, as the study found that the motorcycle
death rates correlated significantly with thepercentage of helmet use among the passengers,which found the percentage all over the country wassignificantly very low, i.e. 15%.
This study did not investigate other factors thatcause mortality in motorcycle accidents, i.e., speed
and alcohol level. Nonetheless, further studies should
be conducted on the enforcement of law that is
effective on motorcyclists’ wearing of helmet.
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.
REFERENCES[1] World Health Organization, Global Status Reporton Road Safety 2009, Geneva, Switzerland, 2009.
[2] World Health Organization, Global Status Reporton Road Safety 2013, Geneva, Switzerland, 2013.
[3] World Health Organization, Global Status Reporton Road Safety 2015, Geneva, Switzerland, 2015.
[4] World Health Organization, Global Status Reporton Road Safety 2018, Geneva, Switzerland, 2018.
[5] Tanaboriboon Y., and Satiennam T., Traffic
accidents in Thailand. IATSS RESEARCH, Vol.
29, No. 1, 2005, pp. 88-100.
[6] Kumphong J., Satiennam T., and Satiennam W.,
A correlation of traffic accident fatalities, speed
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[7] Kumphong, J., Satiennam, T., and Satiennam, W.,
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[9] Ichikawa M., Chadbunchachai W., and Marui E.,
Effect of the helmet act for motorcyclists in

CONCLUSIONS AND RECOMMENDATIONSThis study has shown that helmet usage
percentage was the most significant factor affecting
motorcyclists’ death rate. Wearing a motorcycle
helmet reduces the head injury and risk of death froma motorcycle crash. Helmet law enforcement should
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Thailand. Accident Analysis and Prevention,
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[10] Nakahara S., Chadbunchachai W., Ichikawa M.,
Tipsuntornsak N., and Wakai S., Temporal
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while intoxicated in Khon Kaen, Thailand.
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[11] The Bureau of Non Communicable Diseases ofthe Ministry of Public health, Injuries and Deaths
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The determinants of motorcyclists helmet use:
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93-97.
[15] Alaa K.A., Ashraf F.H., Fikri M.A.Z., Does
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and Prevention, Vol. 49, 2012, pp. 249-252.
[16] National Statistics Bureau. Population Report
2012-2016.Thailand; 2016. (In Thai)[17] Royal Thai Police. Police Stations Report 20122016.Thailand; 2016. (In Thai)[18] Park H M., Comparing Group Means: The T-test
and One-way ANOVA Using STATA, SAS, andSPSS. The Trustees of Indiana University, 2005.
(http://stat.smmu.edu.cn/DOWNLOAD/ebook/statistics_course.pdf)[19] Sedgwick P., Pearson’s correlation coefficient.
University of London, London, UK, 2012.
(https://doi.org/10.1136/bmj.e4483)[20] Hossain M., and Iamtrakul P., Medical
investigation of motorcycle accidents in Thailand.
Journal of the Eastern Asia Society forTransportation Studies, Vol. 7, 2007.
[21] Ankarath S., Giannoudis P V., Balow I., Bellamy
M C., Matthews S J., and Smith R M., Injury
patterns associated with mortality following
motorcycle crashes. Injury, Vol. 33, 2002, pp.
473-477.

[22] Skalkidou A., Petridou E., Papadopoulos F C.,
Dessypris N., and Trichopoulos D., Factors
affecting motorcycle helmet use in the
population of Greater Athens, Greece. Injury
Prevention, Vol. 5, 1999, pp. 264-267.
[23] Li L P., Li G L., Cai Q E., Zhang A L., and Lo S
K., Improper motorcycle helmet use in provincial
areas of a developing country. Accident Analysis
and Prevention, Vol. 40, 2008, pp. 1937-1942.
[24] Mcknight A J., and Mcknight A S., The effects
of motorcycle helmets upon seeing and hearing.
Accident Analysis and Prevention, Vol. 27, 1995,
pp. 493-501.
[25] Kumphong J., Satiennam T., and Satiennam W.,
Preliminary evaluation of helmet law
enforcement by CCTV camera: Case of thephatumuang intersection, Khon Kaen City,
Thailand. Injury Prevention, Vol. 24 - Suppl 2(Safety2018
abstracts).
(http://dx.doi.org/10.1136/injuryprevention2018-safety.234)[26] Wonghabut P., Kumphong J., Satiennam T.,
Ung-arunyawee R., and Leelapatra W.,
Automatic helmet-wearing detection for law
enforcement using CCTV cameras. IOP
Conference Series: Earth and Environmental
Science, Vol.143, 2018.
[27] Kumphong J., Satiennam T., and Satiennam W.,
A Study of Social Norms and Motorcycle Helmet
Use Intentions among Student Riders in
University: A comparison of the Theory of
Reasoned Action and the Theory of Planned
Behavior. Conference proceedings, in Proc. 12th
Int. Conf. on the Eastern Asia Society forTransportation Studies, Vol. 11, 2017, pp. 1-14.
[28] Kumphong J., Satiennam T., Satiennam, W., andTu Anh Trinh. Psychological models for thedevelopment of motorcycle helmet use among
students in Vietnam, IOP Conference Series:
Earth and Environmental Science, Vol.143, 2018.
[29] Kumphong J., Satiennam, T., Satiennam W.,
Inthavongsa P., and Pramualsakdikul S.
Motorcycle helmet use and the theory of traffic
psychology for behavior change in Lao PDR.
International Journal of GEOMATE, April. 2019,Vol.16, Issue 56, pp. 203 -208.

407

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STUDY ON SEISMIC LOAD ON BUILDINGS CONSIDERINGRESIDUAL RISK

1

Sei’ichiro Fukushima1, Takayuki Hayashi2 and Mitsuo Tsuzuki3
RKK Consulting Co., Ltd, Japan; 2 Tokio Marine & Nichido Risk Consulting Co., Ltd, Japan;
3
Nagoya University, Japan

ABSTRACTThe concept of performance-based design introduces the multi-level seismic design loads so that the given
performances with proper reliability are assured. However, the seismic design cannot secure the safety against the
ground motions greater than specified levels, since no consideration is required for the situation. So, Authors insist
the necessity of introducing the concept of residual risks into seismic design and examine the seismic loads
considering the residual risks. Two different seismic design loads are considered based on the seismic hazard
curve; one called VaR (Value at Risk) corresponds to the given exceedance probability, and the other called CVaR
(Conditional VaR) corresponds to the centroid of probability distribution greater than VaR. VaR and CVaR are
calculated for 47 sites in Japan to characterize the seismic hazard. The risks of buildings using VaR and CVaR as
design seismic loads are also evaluated. In case that uses VaR as design seismic load, the risks scatter largely
around the mean. On the contrary, the scattering of risks remains small when using CVaR. This tendency leads tothe setting procedure of design seismic loads that realize uniform risk.
Keywords: Performance-based design, Seismic load, Residual risk, Value at risk, Conditional value at risk

Effect of Seismic Hazard Curve on Residual Risk

Recently the concept of performance-based
design has made it common to introduce multi-level
seismic design loads so that the given performanceswith proper reliability are assured. For example, The
term for seismic load in “Recommendation for Loads
on Buildings [1]” illustrates the procedure to obtainthe loads for given recurrence periods based onseismic hazard analysis, so that engineers can conduct
the performance-based structural design by
combining the level of seismic load and building’s
performance in case of earthquake.
By the way, the social requirement to securesafety against ground motions larger than ones given
for specified recurrence period has risen since 2011
off the Pacific coast of Tohoku Earthquake. Though
the current seismic design code can assure theperformance against the ground motions specified, it
is unknown that the performance will be maintained
against the larger ground motion. Namely, there
exists the residual risk as stated in Wenzel et al. [2]and Hayashi et al. [3].
This paper examines the method to obtain theseismic load based on the residual risk.

Figure 1 shows two PSHCs which give theidentical seismic load 𝑥𝑅 for a given annual
exceedance probability 𝑝𝑅 .
Since seismic load is identical to the building atsite A and to one at site B, the capacity of thebuildings are also same. However the annual
exceedance probability of ground motion greater than𝑥𝑅 at site B is larger than one at site A, so that theresidual risk of building at site B as also larger than
one at site A.
It is concluded that “tail” of seismic hazard curve
affects the residual risk. Namely, if “tail” is small, theresidual risk is small, and vice versa.
Annual Exceedance Probability

INTRODUCTIONSEISMIC LOAD BASED ON RESIDUAL RISK

Site A𝒑𝑹

Site B𝒙𝑹

Authors propose the procedure to determine theseismic load from the probabilistic seismic hazard
curve (hereinafter called PSHC).

Ground Motion Intensity

Fig. 1 Shape of PSHC and residual risk

408

SEE - Bangkok, Thailand, Nov.11-13, 2019

Seismic Load Considering “Tail” of PSHC

Seismic Hazard Analysis

Since larger “tail” of PSHC gives larger residual
risk, authors introduces the seismic load considering
the shape of “tail”. Specifically, the seismic loadcorresponding to the centroid of “tail” is proposed,
since the centroid is the representative variable ofprobabilistic distribution.
Let ℎ(𝑥) be annual probabilistic density functionof ground motion. It is noted that seismic hazard
curve 𝐻(𝑥) is related to ℎ(𝑥) by Eq.(1).

In order to examine the characteristics of the
shape of PSHC and increment of design seismic load,
seismic hazard analysis was conducted.
Analysis conditions
Seismic source zone model was established byusing source zone database prepared by NIED [5]. In
order to obtain time-independent result, Poisson’s
process was employed to characterize recurrence
interval of characteristic earthquakes such as large
active faults earthquakes and inter-plate earthquakes.
(Hayashi et al. [6])Kanno et al. [7] was referred as ground motion
prediction equation. The peak ground acceleration(PGA) at engineering bedrock, where averaged shear
velocity is 292m/s, was employed as ground motion
parameter.
The locations of 47 sites are shown in Fig. 3. Eachsite is the prefectural capital.

𝒙

𝑯(𝒙) = 𝟏 − ∫ 𝒉(𝒕)𝒅𝒕(1)𝟎

Let the ground motion intensity corresponding to
the centroid of “tail” be 𝑥 𝑇 (𝑥𝑅 ) as given by Eq.(2).
∞∫𝒙 𝒙𝒉(𝒙)𝒅𝒙∞𝟏∫ 𝒙𝒉(𝒙)𝒅𝒙
𝒙𝑻 ( 𝒙𝑹 ) = ∞
=
𝒑
(
)
𝒉
𝒙
𝒅𝒙
∫
𝑹
𝑹

𝒙𝑹

(2)

𝒙𝑹

Results

By the way, seismic hazard is often given by theseismic hazard curve 𝐻(𝑥) rather than probabilistic
density function ℎ(𝑥) as illustrated in Ebeling [4], so
it is convenient to express 𝑥 𝑇 (𝑥𝑅 ) by 𝐻(𝑥). Eq.(2)can be rewritten by Eq.(3)For each site, calculated were ground motion
intensity 𝒙𝑹 corresponding to reference annual
exceedance probability, ground motion intensity
𝒙𝑻 (𝒙𝑹 ) corresponding to the centroid of “tail” ofseismic hazard curve, and increment of design groundmotion intensity 𝒛(𝒙𝑹 ). It is noted that 𝒛(𝒙𝑹 ) is givenby the ratio of 𝒙𝑻 (𝒙𝑹 ) to 𝒙𝑹 .
Figure 4 shows the ground motions in each site.
From the figure it can be seen that ground motions inthe sites located along the Pacific coast are larger thanthose in other sites, since the seismic hazards at thesites are affected by large earthquakes in Sagami
trough and/or Nankai trough whose recurrence
periods are about 500 years. The ground motion
intensity at site #8 is the largest since the site isaffected large earthquakes such as ones in Sagami
trough, Ibaraki off shore earthquake, and so on. The
tendency of 𝒙𝑹 and 𝒙𝑻 (𝒙𝑹 ) are similar.
Figure 5 shows the increment of ground motion
intensity for each site. It is apparent that the larger
ground motion intensity 𝒙𝑹 is, the smaller incrementof ground motion intensity 𝒛(𝒙𝑹 ) is.
This is because the area “B” in Fig.2 decreases
with the increasing 𝒙𝑹 . This suggests that employing
small ground motion intensity for design may givelarge residual risk. Concretely, combination of large
design load and large threshold is better than the
combination of small design load and small thresholdfrom the viewpoint of avoiding residual risk.

∞𝟏∫ 𝑯(𝒙)𝒅𝒙𝒙𝑻 ( 𝒙𝑹 ) = 𝒙 𝑹 +
𝒑𝑹

(3)

𝒙𝑹

Annual Exceedance Probability

Eq.(3) is expressed by the area, which issurrounded by x-axis, y-axis, line that 𝑥 = 1 , and
PSHC normalized by 𝑝𝑅 , as illustrated by Fig. 2. In
Fig.2, area “A” corresponds to ground motion 𝑥𝑅 , andarea “A+B” corresponds to 𝑥 𝑇 (𝑥𝑅 ).
Hazard Curve
Normalized and TruncatedHazard Curve
Ha

𝟏. 𝟎

𝒑𝑹

A

B

𝒙𝑹
Ground Motion Intensity

Fig. 2 Ground motion intensity derived fromseismic hazard curve409

SEE - Bangkok, Thailand, Nov.11-13, 2019

1

2

3

5

15

25
26

41
42

6

4
7

17 16 20 10 9
8
18
32 31
12
21 19
14
28
22
35 34 33
24
40
36
13
38

46

43

11

23

44

27

45
37

29

30

39

47

Fig. 3 Location of sites for seismic hazard analysis
pR=1/73
2500

xR

PGA[cm/s/s)

2000

xT(xR)

1500

1000

500

0
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
pR=1/475

PGA[cm/s/s)

4000
3500

xR

3000

xT(xR)

2500
2000

1500
1000
500

0
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
pR=1/2475

6000
xR

5000

PGA[cm/s/s)

xT(xR)
4000
3000
2000

1000
0
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Fig. 4 Comparison of ground motion for given annual exceedance probability

410

SEE - Bangkok, Thailand, Nov.11-13, 2019

pR＝1/733.0

pR=1/475
2.5

pR=1/2475

zR(xR)/xR

2.0
1.5
1.0

0.5
0.0

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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Fig. 5 Comparison of increment of ground motion for given annual exceedance probability
Table 1 summarizes 𝑥𝑅 , 𝑥 𝑇 (𝑥𝑅 ) and their ratio𝑧(𝑥𝑅 ) corresponding to 𝑝𝑅 of 1/475 for some sites.
From the table it can be seen that the ratios 𝑧(𝑥𝑅 ) for
the sites located in the Pacific coast are small
comparing with other site, since the seismic hazard ofsites along the Pacific coast are dominated by large
inter-plate earthquakes with high annual exceedance
probability. On the contrary, other sites are dominatedby large active faults.

Definition of risk
Annual expected failure probability which ingiven from the seismic risk curve expressing therelationship between failure probability and annual
exceedance probability as illustrated in Fig. 6. It isnoted the annual expected failure probability can begiven as an area surrounded by risk curve, x-axis andy-axis.

Table 1 Design seismic loads for some major
prefectural capital in japan
𝒙 𝑻 ( 𝒙𝑹 )
386
856
1345
1293
957
868
816
798

𝒛( 𝒙 𝑹 )
1.42
1.36
1.39
1.52
1.38
1.40
1.42
1.83

1.E-01

0.8

Failure Probability

𝒙𝑹
272
628
968
850
694
623
574
436

Annual Exceedance Probability

Pref.
Hokkaido
MiyagiTokyo
Niigata
Aichi
Osaka
Hiroshima
Fukuoka

Seismic Fragility Curve
1.0
0.9

1.E-02

1.E-03

1.E-04

0.7
0.6
0.5
0.4
0.3
0.2
0.1

1.E-05

0.0
0

500

1000

1500

2000

2500

3000

PGA(cm/s/s)

0

500

1000

1500

2000

2500

3000

PGA(cm/s/s)

Risk Curve
1.E+00

Annual Exceedance Probability

No
1
4
13
15
23
27
34
40

Seismic Hazard Curve
1.E+00QUANTIFICATION OF RISK

1.E-01

1.E-02

1.E-03

1.E-04

1.E-05
0

0.2

0.4

0.6

0.8

1

failure Probability

Authors proposed the seismic load 𝒙𝑻 (𝒙𝑹 )considering residual risk in the previous section. Thissection examines the risks of buildings designed by𝒙𝑹 and 𝒙𝑻 (𝒙𝑹 ).

Fig. 6 Outline to obtain risk curve fromPSHC andseismic fragility curve

Seismic capacity of building

Calculation of risk

Authors employ fragility curve to express thecapacity of building. The fragility curve is assumed to
be log-normally distributed, so that two(2) parameters
are needed to express the curve; median and lognormal standard deviation.
Though median of fragility curve is always
greater than design seismic load by conservativenessin design, it is assumed that the median is identical todesign load 𝒙𝑹 or 𝒙𝑻 (𝒙𝑹 ) for simplicity. The lognormal standard deviation is set 0.4 in natural
logarithm based on Fukushima and Yashiro [8].

For some annual exceedance probabilities, theexpected failure probabilities were calculated. Figure
7 shows the risks of two(2) types of buildings; onedesigned using 𝑥𝑅 , and the other using 𝑥 𝑇 (𝑥𝑅 ). Since
design load 𝑥𝑇 (𝑥𝑅 ) is greater than 𝑥𝑅 , the risks ofbuildings designed using 𝑥 𝑇 (𝑥𝑅 ) are smaller.
And it is remarkable that the scattering of risk
along the sites is also smaller when 𝑥 𝑇 (𝑥𝑅 ) is used as
design load. In order to examine this tendency, therelationship between the increment of ground motion𝑧(𝑥𝑅 ) and the risk is arranged as shown in Fig. 8.

411

SEE - Bangkok, Thailand, Nov.11-13, 2019

pR=1/73

Expected Fairure Probability

0.025

xR

xT(xR)

0.020

0.015

0.010

0.005

0.000
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
pR=1/475

0.005

xR

Expected Failure Probability

xT(xR)
0.004

0.003

0.002

0.001

0.000
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
pR=1/2475

Expected Failure Probability

0.0012xR

xT(xR)

0.00100.00080.00060.00040.00020.0000
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 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Fig. 7 Comparison of expected failure probabilities for given annual exceedance probability
Pr=1/73

Pr=1/475xR

0.025

Pr=1/2475
xR

0.005

0.015

0.010

0.005

0.000

0.004

0.003

0.002

0.001

0.000
1.0

1.5

2.0

2.5

Increment of Gorund Motion

3.0

xT(xR)

Expected Failure Probability

0.020

xR

xT(xR)

Expected Failure Probability

Expected Failure Probability

xT(xR)

0.002

0.001

0.000
1.0

1.2

1.4

1.6

1.8

2.0

1.0

Increment of Gorund Motion

1.1

1.2

1.3

1.4

1.5

Increment of Gorund Motion

Fig. 8 Relationship between increment of ground motion intensity and expected failure probability

In the figure, also indicated by dashed line are theregression curves. So it is seen that scattering of
expected failure probability around the regression
curves is smaller in case that 𝑥 𝑇 (𝑥𝑅 ) is used as design
seismic load.
Table 2 summarizes the risks with the ratio 𝑧(𝑥𝑅 )for the major prefectures in Japan in case thatbuildings are designed by ground motion intensity
when 𝑝𝑅 is 1/475. It can be seen that the larger 𝑧(𝑥𝑅 )is, the smaller the risk is, if the buildings are designed
by 𝑥𝑇 (𝑥𝑅 ) . However, such a tendency can beobserved when the buildings are designed by 𝑥𝑅 .

Table 2 Comparison of expected failure probabilityof major prefectural capital in japan

412

No

Pref.

1
4
13
15
23
27
34
40

Hokkaido
MiyagiTokyo
Niigata
Aichi
Osaka
Hiroshima
FukuokaGround Motion𝒙𝑹
𝒙𝑻 ( 𝒙𝑹 )0.398% 0.157%
0.391% 0.170%
0.324% 0.144%
0.265% 0.116%
0.245% 0.123%
0.319% 0.146%
0.310% 0.139%
0.276% 0.096%

𝒛( 𝒙𝑹 )
1.42
1.36
1.39
1.52
1.38
1.40
1.42
1.83

SEE - Bangkok, Thailand, Nov.11-13, 2019

CONCLUSIONREFERENCES

Employing the seismic design load for the given
exceedance probability is the rational way to realize
the uniform performance in case of earthquake.
However, the value is not always a good index since
the effect of the “tail” of PSHC on the risk cannot beignored, especially in case that large earthquake withlow occurrence probability is dominant.
In order solve the problem above, authors
proposed to employ the ground motion intensity
corresponding to the centroid of “tail” of theprobabilistic density function of ground motion
intensity, where “tail” is defined as the portion greaterthan the ground motion intensity corresponding to thegiven annual exceedance probability. It was seen thatless scattered risk is obtainable by introducing thisnew intensity.
Also derived was the monotonic relationshipbetween the increment of ground motion intensity(ground motion intensity ratio) 𝑧(𝑥𝑅 ) and the risk.
This suggests the possibility to realize the setting ofground motion intensity by which the risk of thebuildings will be uniform.
It is noted that above results are given on someassumption. For example, log-normal standard
deviation of fragility curve is set 0.4, seismic load is
identical to median of fragility curve, and so on. So
authors will obtain robust conclusion through further
numerical simulations. Identifying better index than𝑥 𝑇 (𝑥𝑅 ) is still of concern.

[1] Architectural Institute of Japan, Recommendation
for Loads on Buildings, AIJ, 2015. (in Japanese)[2] Wenzel et al., Measuring residual risk inearthquakes, Transaction of Second European
Conference on Earthquake Engineering andSeismology, EAEE & ESC, 2014[3] Hayashi et al., Study on the Seismic Load
Considering Residual Risk, Part1: Ground Motion
Considering Residual Risk, Transaction of annual
meeting of AIJ, AIJ, 2016. (in Japanese)[4] Ebeling, C. E., An Introduction To Reliability and
Maintainability Engineering, McGraw-Hill, 2000.
[5] National Research Institute for Earth Science andDisaster Prevention, Improved Seismic Hazard
Assessment after 2011 Great East Japan
Earthquake, Technical Note of NIED No.399,
NIED, 2015. (in Japanese)[6] Hayashi et al., Study on Application of Uniform
Hazard Spectrum into Seismic Design, Part1:
Uniform Hazard Spectrum, Transaction of annual
meeting of AIJ, AIJ, 2015. (in Japanese)[7] Kanno et al., A new attenuation relation for strong
ground motion in Japan based on recorded data,
Bulletin of Seismological Society of America,
Vol.96, No.3. 879-897, 2006.
[8] Fukushima, S,. H. Yashiro, Seismic Risk Analysis
on Portfolio of Buildings, Journal of Architecture,
Planning and Environmental Engineering, No.552,
169-176, AIJ, 2002. (in Japanese)413

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

CONSTRUCTION OF DAMAGE FUNCTION FOR AN ANALYSIS OF
THE ECONOMIC DAMAGE BY EARTHQUAKES WITH A FOCUS ON
THE RECONSTRUCTION OF SHARED HOUSING
Norikazu Sakaba1, Yashiro Harumi2
Tokio Marine & Nichido Risk Consulting Co., Ltd., Japan, 2,3 National Defense Academy of Japan, Japan

1

ABSTRACT
Conventional economic housing damage estimation methods quantitatively estimate the damage amountfrom the structural damage of the building, cannot consider variability for the repair costs that the decision
making of the victim gives it to. Therefore, in the assessment of economic housing damage, there is a concernthat a large deviation may occur between the estimated value and the actual value. In this research, we will focus
on what kind of system the governments or local government can build for the victims, and the quick rebuilding
will be possible. Economic housing damage was estimated in line with the actual damage situation, in particularby considering the diversity of housing reconstruction methods for apartments. We focused on the damage states
and restoration examples provided in the Act on Special Measures concerning Reconstruction of Condominiums
Destroyed by Disaster, constructed a damage function in line with the actual situation by constructing a
restoration pattern model for housing reconstruction of an apartment house. As a result of the earthquake
simulation, we quantitatively showed that the diversity of housing reconstruction methods of collective housing
gives a large variation to the damage amount. In addition, we showed that the current measures and measuresthat governments and local governments assumed were not sufficient, and pointed out the issues regarding
effective measures and measures in the future.
Keywords: Earthquake, Economic damage Analysis, Damage Function, Housing Reconstruction
INTRODUCTION

earthquake damage, buildings that were judged as
being totally destroyed were restored, whilebuildings that were judged as partially destroyed
were reconstructed. Since shared housing units have
many unit owners, housing reconstruction is carriedout based on diverse values, such as livelihood
rehabilitation and asset formation. Accordingly, if
economic damage is calculated mainly based on the
structural damage of buildings, such as the current
damage estimation, it is impossible to properly grasp
the extent of funding necessary for thereconstruction of shared housing. The proportion ofshared housing, especially in urban areas, is large.
The economic forecast that is necessary for
restoration and reconstruction of housing can beconsidered inadequate. Another issue is that thecategories of total and partial destruction, which areassumed in the current damage estimation process,are not linked to the categories of damage that areused in various support systems that implemented by
the government and municipalities. It is not possible
to measure the funds required for various support
systems quantitatively, because the mode ofcategorizing damage varies. Funding is necessary toprovide various types of support. If planned reserves
are not made, there is a risk that the support system
may become bankrupt. To take disaster prevention
and mitigation measures in the future, it is importantto quantitatively indicate the reconstruction costs
that may be required by the victims and the funding
support that may be necessary for various support

Many earthquakes that have taken place in recent
years have been caused by inland active faults,
including the Kumamoto Earthquake in April 2016,
the Northern Osaka Prefecture Earthquake in June
2018, and the Hokkaido Eastern Iburi Earthquake in
September 2018. Earthquakes caused by inland
active faults have a smaller scale than trench-type
earthquakes. When major local earthquakes occur
near cities, there is a risk of great damage to thelivelihoods of the local residents. For this reason, thegovernment and municipalities implement damage
estimation measures in advance in order to takemeasures for disaster prevention and mitigation. In
estimating damage, the number of buildings that canbe totally or partially destroyed is clarified. This
information helps protect the lives of victims.
Economic damage is monitored to help survivors ofa disaster to restore their lives and to contributetoward the reconstruction of the economy. Economic
damage may include direct damage to the building
and the funds required for the reconstruction ofdamaged housing. In this study, economic damage isdefined as the funds required for housing
reconstruction. Using the number of totally andpartially destroyed buildings, the economic damage
analysis of the government and municipalities example
1
assumes that the rate of economic damage is 100%in the case of total destruction, and 50% in the caseof partial destruction. However, in recent cases of414

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table. 1

List of building damage survey

No.

Survey namePurposeInvestigator

Damage category name1

Damage certification survey

Issuance of disaster certificates

Municipality

Partial destruction, large-scale partial destruction, and2

Damage survey

Earthquake insurance

Non-life insurance company

Partial loss, small and partial loss, large loss, and total

3

Damage degree classification survey

Understanding the degree ofArchitect

Insignificant damage, small damage, intermediate

total destruction
loss
damage, judgment fordamage, large damage, and collapse

continuous use
4

Act on Disaster-Affected Condominiums

Research for clarifying the

Researcher

causes of disaster

Small damage, intermediate damage, large damage,collapse or partial damage, partial destruction, and total
destruction

5

Research survey by the Architectural

Understanding the extent ofInstitute of Japan and the Japan Society ofdamageMunicipality

Partial damage, partial destruction, total destruction

Civil Engineers

Table. 2

Classification and criteria of the Act on Disaster-Affected Condominiums

Unit
Total loss

Act on Disaster-Affected

State

Requirement

Condominium Ownership Act

State in which the main part has disappeared,

Reconstruction

Consent of everyone isConsent

required

requiredand the overall utility of the building has been

Condominiums Buildingsoffour-fifths

isoffour-fifths

isoffour-fifths

isof

everyoneislost from a social and economic viewpoint
Large-scale partial

In cases where the part corresponding to more

Reconstruction

Consent of four-fifths is required

loss

than half the building price is lost

Restoration

Consent of three-fourths is required

Sale of building and site
Demolition and sale of site
Small-scale partial

In cases where the part corresponding to lessloss

than half the building price is lost

Reconstruction
Restoration

systems.

Consent of everyone isConsent

required

requiredConsent of everyone isConsent

required

requiredConsent of everyone isConsent

required

requiredConsent of half of the people

and the names, definitions, and number of categories
vary. Number 1 in the table is implemented relying
on the Act on the Support for Reconstructing Housesof Disaster Victims and the Emergency Repair
System. This legislation covers buildings ranging
from total destruction to large-scale partial
destruction, and the Emergency Repair Systemprovides funding support in cases of total and partial
destruction. Number 2 in the table is implemented
while using earthquake insurance. In earthquake
insurance cases, the insurance amount is paid for
total and partial loss. Number 3 in the table is
implemented when shared housing is affected and a
resolution of reconstruction methods is carried out.
The number of votes necessary to decide upon areconstruction method and the resolution ofreconstruction methods varies based on the categoryof damage. Numbers 4 and 5 are voluntary surveysof academic societies and municipalities. The survey
is conducted in cases of total and partial destruction.
The damage function used in the damage estimationby the government and municipalities has beencreated based on the results of this survey. Even if
the degree of damage is the same, the names,
definitions, and number of categories vary based on
the surveyor. This estimation uses two categories,
total and partial destruction, but these categories do
not correspond to the categories for theinvestigations under the Act on Support for
Reconstructing Houses of Disaster Victims, theIn this study, we focus on the different kinds of
economic disaster prevention and mitigation
measures that the state and the municipalities cantake in order to achieve speedy reconstruction. We
review the evaluation of shared housing thatprovides an element of uncertainty in economic
damage, and create a damage function byconsidering the diversity in the approaches toward
the reconstruction of shared housing. The damage
function should be created in harmony with theclassification of various support systems, in keepingwith the quantitative evaluation of each of these
support systems. We also present an example of an
economic damage analysis of an earthquake forTokyo using the damage function so created.
BUILDING DAMAGE AND
RECONSTRUCTIONClassification of Building Damage
After an earthquake, several surveys are
conducted to understand the extent of damage to thebuilding. There are various ways of detecting
damage to buildings based on the purpose and themethod used in the survey. Table 1 summarizes themain surveys conducted after a disaster and thecategories of damage under each. As shown in thetable, there are various categories for each survey,
415

SEE - Bangkok, Thailand, Nov.11-13, 2019

Damage Ratio
Damage estimation

0.0

0.1

0.2

No Damage

0.3

0.4

0.5

0.6

0.7

Semi-destruction

0.8

0.9

1.0

Total destruction
Large-scale

Damage certification
surveyNo Damage/Insignificant damage

Partial-destruction

partial-

Total destruction

destruction
Large-scale

Damage survey

No DamagePartial damage

Small and partial-destruction

partial-

Total destruction

destruction

Damage degreeclassification assessment
Emergency risk
assessment
Act on Disaster-Affected
Condominiums Buildings

No DamagePartial damage

Small damage

Intermediate damage

SafetyNo Damage

Insignificant

Attention needed
Small-scale partial loss

loss

Large damage

Collapse
DangerLarge-scale partial loss

Total loss

Figure 1. Survey of damage and arrangement of damage category
Seismic Intensity

Damage category
by structure

Damage category
by reconstruction

Reconstruction
methodTotal loss

Total destruction
1-Pc

Large-scale partial loss

0.40
0.60

Partial destruction

Large andPartial destruction

0.10

Large-scale partial loss

0.40
0.60

0.90

Small-scale partial loss

0.10
0.90

Small andPartial destruction

Small-scale partial loss

0.90
0.50

Partial damage

0.10

0.50

Small-scale partial loss
Insignificant damage

0.50
0.50

No DamageOccurrence
probability

Economicdamage rate

Expected value of
economic damage rate

Rebuilding

P11

R11=1.00

C11=P11*R11

Rebuilding

P12

R12=1.00

C12=P12*R12

Rehabilitation

P13

R13=0.65

C13=P13*R13

Rebuilding

P21

R21=1.00

C21=P21*R21

Rehabilitation

P22

R22=0.60

C22=P22*R22

Rebuilding

P23

R23=1.00

C23=P23*R23

Rehabilitation

P24

R24=0.45

C24=P24*R24

Rebuilding

P31

R31=1.00

C31=P31*R31

Rehabilitation

P32

R32=0.30

C32=P32*R32

Rehabilitation

P41

R41=0.15

C41=P41*R41

Rehabilitation

P42

R42=0.05

C42=P42*R42

No repairing

P43

R43=0.00

C43=P43*R43

No repairing

P51

R51=0.00

C51=P51*R51

Figure 2. Event tree related to damages to shared housing
Emergency Repair System, and the earthquake
insurance system. Therefore, it is not possible toquantify funds necessary for these support systems
when different assumptions of damage are made. To
estimate damage, it is necessary to set categories ofdamage that are consistent with various support
systems.

system. The decision to rebuild shared housing isprovided by the Condominium Ownership Act of the
Civil Code or the Act on Disaster-Affected
Condominiums. Here, the Act on Disaster-Affected
Condominiums applies only to shared housing
damaged by large-scale disasters as specified bygovernment decree. Table 2 shows the damage
categories and criteria based on the Condominium
Ownership Act and the Act on Disaster-Affected
Condominiums.
As shown in the table, when shared housing isaffected, it is divided into four categories: completeloss, large-scale partial loss, small-scale partial loss,
and others (minor or no damage). Here, complete
loss means that the utility of the entire building has
been lost, and partial loss means that the utility islost for some parts, but the utility as a whole ismaintained. The loss of utility indicates the loss ofutilization value and not market price. Among thepartial losses, large-scale partial loss indicates a lossof more than half of the building price, and thesmall-scale partial loss indicates a loss of less than

Housing Reconstruction Process
In case of damage to detached houses, decisions
are made to reconstruct or restore such houses
mainly for the purpose of the rehabilitation of
livelihood. This judgment can be made by the ownerof the building at his own discretion. However,when shared housing is damaged, the decision onwhether to opt for reconstruction or restoration ismade not only based on the rehabilitation of
livelihood, but also on diverse values such as asset
formation. This decision must be determined by theconsensus of the unit owners since the building orsite becomes a part of a condominium ownership
416

SEE - Bangkok, Thailand, Nov.11-13, 2019half of the building price. The reconstruction
resolution is different for each damage category, and
it is necessary to proceed with each resolution
according to the method of reconstruction. However,in these resolutions, it is difficult for the unit owners
to arrive at a consensus. In the case of the
Kumamoto earthquake, nearly half of the 18 sharedhouses that had applied for public funded demolition
had difficulties in arriving at a consensus among theunit owners, and the need for demolition was notestablished sufficiently. In other words, the selectionof the building reconstruction method varies widely
among the unit owners as well. It is quite possible totake a decision on restoration instead of rebuilding
when a large-scale partial loss occurs, and to takethe decision of rebuilding instead of restoration
when a small-scale partial loss occurs.

of returning it to the current status. Therefore, thefunds required for housing reconstruction should
correspond sufficiently to the degree of structural
damage. In this study, following the earthquake
insurance payment rate, the economic damage rate is
set to 100% for total destruction, 60% for large-scalepartial destruction, 40% for small-scale partial
destruction, and 5% for partial damage. In the caseof shared housing, it is necessary to determine thereconstruction method through discussions among
unit owners. As seen in the previous chapter, inshared housing, various methods of housing
reconstruction are selected based on the diverse
values held by the unit owners. The funds requiredfor housing reconstruction may show a response
different from what the degree of structural damage
requires. Therefore, in this study, we created amodel of the damage function using the event tree as
seen in Figure 2. After damage categorization basedon the structure, we branched out the damage
categories based on the Act on Disaster-Affected
Condominiums. We also branched out the methods

DAMAGEFUNCTION
FOCUSEDON
RECONSTRUCTION OF SHARED HOUSING

417

Damage Ratio

Damage Ratio

Damage Ratio

Damage Ratio

Ratio Ratio
DamageDamage

Damage Ratio

Damage Ratio

Damage Ratio

Damage Ratio

Event TreeIn the previous chapter, we showed theclassification of building damage based on the
木造1963～1971年
木造1981～1989年
木造2002年以降
木造1963～1971年
木造1972～1980年
木造1981～1989年
木造2002年以降
木造1981～1989年
木造2002年以降
Wooden,before木造1963～1971年
1971木造1972～1980年
Wooden, 木造1972～1980年
1972
to
1980
Wooden,1981
to 2001
木造1963～1971年
木造1972～1980年
木造1981～1989年
木造2002年以降
木造1963～1971年
木造1972～1980年
木造1981～1989年
木造2002年以降
非木造1971年以前
非木造1972～1980年
非木造1981年以降
非木造1971年以前
非木造1972～1980年
非木造1981年以降
非木造1971年以前
非木造1972～1980年
非木造1981年以降
非木造1971年以前
非木造1972～1980年
非木造1971年以前
非木造1972～1980年
非木造1981年以降
木造1963～1971年
木造1972～1980年
木造1981～1989年
木造2002年以降
Non-Wooden,
1972 to非木造1981年以降
1980
Non-Wooden,
before1971
Wooden,after 2001
木造1963～1971年
木造1972～1980年
木造1981～1989年
木造2002年以降
housing damage survey
and presented
the processof
1.0 木造1963～1971年
1.0
1.0
1.0
木造1972～1980年
木造1981～1989年
木造2002年以降
1.0
非木造1971年以前
非木造1972～1980年
非木造1981年以降
非木造1971年以前
非木造1972～1980年
非木造1981年以降
Non-Wooden, after 1981
非木造1971年以前
非木造1972～1980年
非木造1981年以降
1.0
reconstruction of apartment
houses.
In this chapter,
1.0
1.0
0.8 0.8
0.8
0.8
0.8
we create a damage function based on the review of
0.8
0.8
0.8 0.6
damage categories and the reconstruction method
0.6
0.6
0.6
0.6
based on the 0.6Act on 0.6Disaster-Affected
0.6
0.4 0.4
0.4
0.4
0.4
Condominiums. First, the differences in the
0.4
0.4
0.4 0.2
economic damage rates of buildings in each damage
0.2
0.2
0.2
0.2
0.2
survey are summarized
in Figure0.2 1. The economic
0.2 0.0
0.0
0.0
0.0
0.0
damage rates shown 0.0in the figure are organized with0050 0
100 500 50
50 100100 150150 200
200 1500
50 150 100
100 200 150
200
200
0.0
PGV (cm/s)
PGV (cm/s) PGV (cm/s) PGV (cm/s) PGV (cm/s)
2
50 0
100 50150 100 0.0
200 150
reference to Okada 0 et al. (1999). Damage200
PGV (cm/s)
0
50
100
150
200
assessment surveys used in damage certification and PGV (cm/s)
PGV (cm/s)
木造1963～1971年 (a) Damage
木造1972～1980年
木造1981～1989年
木造2002年以降
function of shared housing
damage surveys used in earthquake insurance have
非木造1971年以前
非木造1972～1980年
非木造1981年以降
four damage categories, although the category
1.0
names are different. The economic damage rates
0.8
assumed for each category are similar. On the other
hand, the damage estimates implemented by the
0.6
government and municipalities set two categories:
0.4
total and partial destruction. Partial destruction indamage estimation includes partial destruction and
0.2
large-scale partial destruction. Partial damage is not
0.0
considered. The two main systems that can be used
0
50
100
150
200
PGV (cm/s)
for housing reconstruction are
livelihood
木造1963～1971年
木造1972～1980年
木造1981～1989年
木造2002年以降(b) Damage function of detached housing
rehabilitation support and earthquake insurance. The
非木造1971年以前
非木造1972～1980年
非木造1981年以降
1.0
damage category set in the current damage
estimation is not appropriate while considering the
0.8
formulation of policies for measures and response
0.6
for recovery and reconstruction from earthquake
damage after the estimation of such damage.
0.4
Therefore, we set four damage categories in this
0.2
study: total destruction, large-scale partial
destruction, small-scale partial destruction, and
0.0
0
50
100
150
200
partial damage.
PGV (cm/s)
Next, we look at the method of reconstruction of(c) Damage function of the Cabinet Officehouses. If a detached house is damaged, theFigure 3. Damage function
reconstruction will be considered first with the goal

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 5. Number of households in Tokyo and asset amount data (number of households, 1 billion yen)
Structure

WoodenBuilding Age

Ancient old

Shared housingOld

Non-wooden
New

SubtotalAncient old

Old

New

Subtotal

Total

52,55877,565

627,643757,767

181,667

460,1412,949,199

3,591,007

4,348,774

254,013281,379

1,313,299

1,848,691

5,456

7,209

53,621

66,285

1,914,976

Total

306,571358,944

1,940,942

2,606,457

187,123

467,350

3,002,820

3,657,293

6,263,750

Shared housing

1,808

2,690

21,753

26,252

8,194

20,754

132,967

161,916

188,167

6,836

7,573

35,34549,753

211

279

2,077

2,568

52,321

8,644

10,26357,09876,005

8,405

21,033135,045

164,483

240,489

Number of

Detached

households

housing

Asset amount

Detached
housing
Total

Table 6. Number of households damaged by the Tachikawa fault zone
Structure

Wooden structure

Building Age

Ancient old
Sharedhousing

Proposed method

Detached
housing
Total
SharedCabinet Officemethodhousing
Detached
housing
Total

Non-wooden structure

Old

New

Subtotal

33,85550,334

330,375

414,564

164,014

181,057

695,434

197,870

231,391

25,796

Ancient old

Total

Old

New

Subtotal

106,846

197,996

1,027,438

1,332,279

1,746,843

1,040,505

2,891

3,019

17,817

23,726

1,064,231

1,025,809

1,455,070

109,736

201,014

1,045,255

1,356,005

2,811,075

36,37479,365

141,535

37,12870,374

190,441

297,943

439,479

126,182

131,628

183,611

441,421

904

1,061

3,202

5,167

446,587

151,978

168,001

262,976582,956

38,032

71,435

193,643

303,110886,066

Table 7. Economic damage by the Tachikawa fault zone (billion yen)
Structure

Wooden structure

Building Age

Ancient old
Sharedhousing

Proposed method

Detached
housing
Total
SharedCabinet Officemethodhousing
Detached
housing
Total

Old

New

Non-wooden structure
SubtotalAncient old

Old

New

Subtotal

Total

599

825

2,356

3,780

1,302

2,361

8,042

11,705

15,485

2,449

2,420

3,605

8,473

26

29

98

154

8,627

3,048

3,245

5,961

12,254

1,329

2,390

8,140

11,85924,112

570

770

1,563

2,903

994

1,866

4,765

7,624

10,527

2,596

2,613

3,388

8,597

25

29

82

136

8,733

3,167

3,382

4,951

11,501

1,019

1,895

4,847

7,760

19,261of reconstruction that can be used after theclassification of damage based on the Act on
Disaster-Affected Condominiums. From this, we set
it to select reconstruction and restoration even incases of total destruction. We assumed that thebranching probability Pc of total loss and large-scaleloss after total destruction is the state where allbuildings are lost, and no buildings exist. We
adopted the damage grade of Okada et al. (1999)2
and used the ratio of D5 level damage (equivalent tocollapse) to D4 level damage or above (equivalent tototal destruction.) We set other branchingprobabilities based on the relationship with theeconomic damage rate as seen in Figure 2. However,it may be possible to update the approach using
statistical data such as damage results in the future.

partial destruction, small-scale partial destruction,and partial damage. In this study, the damage ratefunction for partial damage uses data from the NonLife Insurance Rating Organization of Japan,4 partial
destruction and total destruction use data from the
Cabinet Office on damage estimation.1 Further,while dividing the partial destruction into large-scaleand small-scale partial destruction, we use data on
the number of damaged buildings for each damage
category according to Nagao and Yamazaki (2011). 3
Using the ratio of the number of damaged buildingsthat were completely destroyed, largely partiallydestroyed and partial destroyed as indicated in theliterature, we created a damage function of largescale partial destruction by combining the damage
functions of total and partial destruction. From theabove, the damage function obtained is shown in
Figure 3. The damage function used in the damage
estimation of the Cabinet Office is also shown as areference. From the figure, because of the diversity
in the methods of reconstruction, the damage
function of share housing has a damage rate that is

Damage Function
We create a damage function based on the event
tree drawn up in the previous section. To create thedamage function, it is necessary to define thedamage rate function of total destruction, large-scale
418

SEE - Bangkok, Thailand, Nov.11-13, 2019slightly larger than that of the detached houses andthe Cabinet Office in areas where the seismic
intensity is small, and the damage rate is smaller
than that of detached houses and the Cabinet Officein areas where the seismic intensity is large.

structures, and 1.13 times for detached houses
comprising non-wooden structures. As the maindifference between the proposed method and the
Cabinet Office method, we can say that sharedhousing takes into consideration the diversity ofreconstruction methods and the damage cost becauseof partial damage, and also that detached houses take
into consideration the damage cost because of partial
damage. Shared housing is significantly affected
when the diversity of reconstruction methods istaken into consideration.

EXAMPLE OF ECONOMIC DAMAGE
ANALYSIS
Analysis Condition
Using the damage function created in theprevious chapter, we try to determine the number ofdamaged households and the funds necessary for
housing reconstruction. We evaluate Tokyo, which
is densely populated with a large number ofbuildings, many of which are shared housing units.
We make predictions assuming that an earthquake
was caused by the Tachikawa fault, which has raised
concerns of causing significant damage to Tokyo.

CONCLUSION
In the case of shared housing being affected by adisaster, housing reconstruction is selectedaccording the diverse values of unit owners.
Therefore, the funds needed for reconstruction do
not necessarily coincide with the degree of structural
damage. Also, as shown in the case of the
Kumamoto Earthquake, resolutions for thereconstruction and restoration of shared housing arecomplex and require a lot of time to rebuild. The
reconstruction process is complicated when there aremany options such as large-scale partial loss. It isnecessary to take measures in advance so as not tointerfere with rapid restoration and reconstruction.
In this study, we focused on the damage
classification and reconstruction methods that are
related to the Act on Disaster-Affected
Condominiums, and created the damage function ofshared housing by using the event tree of restoration.
By using this damage function, economic damage
analysis can be performed according to the actual
condition of the restoration cost of buildings. We
also used damage categories linked to the support
system for the subsequent restoration andreconstruction measures and because of this, it ispossible to evaluate the costs and effects required forvarious support systems, as well as to evaluate
economic damage. In future studies, we plan to
examine the sufficiency of the current support
system, as well as effective measures and responses
to these economic damages.

Result of Analysis
Table 5 shows the number of households and theasset amount as a summary of the asset data forTokyo. Table 6 shows the number of damaged
households after damage estimation and Table 7
shows the prediction of the economic damage. The
number of damaged households indicates thenumber of households affected by such damage.
Tables 6 and 7 also show the results of the damage
function as adopted by the Central Disaster
Management Council of the Cabinet Office1 forcomparison.
Based on the results, the total number ofdamaged households in the proposed method isabout 2.80 million, which is about 3.1 times morethan the results of the Cabinet Office method. The
proposed method considers the damage category ofpartial damage, but the Cabinet Office method does
not consider this category. Instead, it considers
partial destruction as a category. As a result of thisdifference, the number of damaged households inthe proposed method has significantly increased.
While looking at recent earthquake damage,although non-wooden buildings rarely result incomplete or partial destruction, there are many cases
in which partial damage has occurred. We think thatusing the proposed method can predict a number ofdamaged households that is closer to the actual
situation.
Next, based on the results, the total economic
damage of the proposed method is approximately 24
trillion yen, which is approximately 1.3 times theresult of the Cabinet Office method.
The breakdown of economic damage wasapproximately 1.30 times for shared housing
comprising wooden structures, 1.54 times for sharedhouses comprising non-wooden structures, 0.99
times for detached houses comprising wooden

REFERENCES[1] The Disaster Management in Japan Report,
Cabinet Office Japan, 2013,
http://www.bousai.go.jp/jishin/syuto/taisaku_wg/[2] Okada, S. and Takai, N. (1999). Classificationsof Structural Types and Damage Patterns of
Buildings for Earthquake Field Investigation,
Journal of Structural and Construction
Engineering, Vol. 524, pp.65–72 (in Japanese)[3] Nagao, T. and Yamazaki, F. (2011). Analysis of
Building Damage in Kashiwazaki City due to the2007 Niigata-Ken Chuetsu-Oki Earthquake,
Journal of social safety science, Vol. 15, 2011,
pp. 249-254

419

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

GROUND SURVEY BASED ON THE DISTRIBUTION OF SURFACEWAVE VELOCITY AND ELECTRICAL RESISTIBILITY
1,3

Katsuyuki Kawai1, Ryosuke Hamada2 and Koji Nakashima3
Dept. of Civil and Environmental Engineering, Kindai University, Japan; 2 Toyo Construction Co., Ltd.,Japan
ABSTRACT

Geophysical exploration, which can explore the distribution of material properties underground, has, for lessthan the last half a century, been applied for prospecting groundwater and bedrock. Though simulation techniques
have improved with greater sophistication of the constitutive model for soil material, comprehension of current
soil conditions is important for accurately predicting the behavior of earth structures. Therefore, the importance ofgeophysical exploration is growing. Soil parameters are indirectly identified from physical parameters, such aswave velocity, electric conductivity and so on. In geophysical exploration, calibrating physical parameters withnecessary soil parameters is required for individual soil material and has thus prevented the application ofgeophysical exploration at the site level. In this study, surface wave and electric prospecting were conducted at asite first investigated circumstantially by borings and other soundings. Then, the applicability of surface wave andelectric prospecting were validated through their comparison. Next, geophysical explorations were conducted ona large-size embankment. Consequently, the applicable scope of this type of exploration was demonstrated,
proving its applicability for geotechnical engineering sites.
Keywords: Geophysical Exploration, Surface Wave Velocity, Electrical Resistibility, Embankment
parameters, such as the N-value and soil moisture,
have to be converted from elastic wave velocity andelectric resistibility. These material properties are
influenced by other soil parameters. Consequently,
geophysical exploration is only used as a supplement.
In this study, surface wave and electricprospecting were conducted in ground first surveyed
by borings and various soundings for calibration.
Based on the calibration, geophysical exploration
techniques were applied to a large-size embankment.

INTRODUCTION
Recently, a constitutive model for soil has
improved, and numerical computing techniques havebecome more sophisticated (e.g. Sugiyama et al.,2016). Therewith, numerical simulation has become
more reliable in geotechnical engineering and has
been used for designing and maintaining earth
structures. When we conduct numerical simulation,
the initial condition is needed. In the case of an
existing earth structure, the current condition within
the earth structure is the initial condition forsimulation. Therefore, ground surveys, such as
borings and soundings, are important. However, theseground surveys cannot be conducted at a fine scaledue to economic constraints. Geophysical exploration
is effective for knowing material properties of theground through non-destructive inspection to develop
in-depth cross-sectional information. On the other
hand, in geophysical exploration, necessary soil

GEOPHYSICAL EXPLORATION
Surface wave prospecting
When the ground is hit by a hammer, the surface
wave, called a Rayleigh wave, is transmitted along
the ground surface. A Rayleigh wave has morevertical vibration and 0.9 to 0.95 times velocity of ashear wave. Since the energy of vibration occurs

Data Logger
Accelerometer

Photo 1 Surface wave prospecting

Figure 1 Surface wave prospecting
420

SEE - Bangkok, Thailand, Nov.11-13, 2019

SwitchBox
C1

C2 P1 P2

P1 P2

Electric resistivity
measurement

P1 P2

Electrode

Average electric resistivity along path
Transmitted current：C1, C2
Measured potential：P1, P2

Figure 2 Electric prospecting

Photo 2 Electric prospecting
LevelThickDepth(m) (m) (m)
1
2

Soil

0.90 0.90
0.35 1.25
0.65 1.90

GravelSilty sand
Sandy silt

2.85 4.75
0.55 5.30
0.55 5.85

Gravel
Silt

3
Silt

4
5
6
7
8

Sand with silt

Depth (GL - m)

9
10
11

5.55 11.40

12
13

θ

θ

θ

Silty clay

15
16

Sandy silt

1.6013.00

14

θ

θ

θ

3.0016.00

17
θ

18

θ

θ

19
20
θ

θ

θ

Clay

with shell

21
22
23
θ

24

θ

θ

9.0025.00

Figure 3 Location of borings and soundings

Figure 4 Stratigraphic column

mostly at the ground surface and dampens with depth,
shear wave in shallower depth than wavelength canbe measured. With surface wave prospecting, we canknow the distribution of shear wave velocity within
the ground by catching waves with accelerometersaligned on the ground surface (as in Figure 1 andPhoto 1). All wave shapes measured by eachaccelerometer are applied to frequency analysis, andthe relationship between phase velocity andfrequency are obtained (Park, 1999). It is said that theshear wave velocity correlates well with the stiffnessof soil material and that it is applicable for estimating
ground properties. Various correlation equations
between the shear wave velocity and N-value havebeen proposed. Imai and Tonouchi (1982) proposed
the following equation.

electric resistibility can be identified from thispotential response (as in Figure 2 and Photo 2). The
apparent electric resistibility can be calculated byattenuation from the potential difference between
transmission electrodes (Cm, Cn) to the potential
difference between receipt electrodes (Pm, Pn). Here,apparent electric resistibility means average electric
resistibility along the path from transmission
electrodes to receipt electrodes. The distribution oftrue electric resistibility can be obtained by backanalysis. The finer electrodes are aligned, the higher
the resolution of the electric resistibility distributionthat can be obtained. The obtained electric
resistibility reflects porosity, soil moisture, mineralcontent, temperature and so on. Electric resistibility issaid to correlate to soil moisture in homogeneousmaterial ground.

1 V  0.314
N  s  97 

COMPARISONSEXPLORATIONSOUNDINGS(1)

Here, N is the N-value obtained from the standard
penetration test, and V s is shear wave velocity (m/s).

OF
WITH

GEOPHYSICALBORINGS AND

To verify the results from geophysicalexploration, surface wave and electric prospecting
explorations were conducted at a centrally located sitein Osaka city. There, detailed ground surveys,
including five borings and various soundings, wereconducted. Figure 3 shows the locations of the groundsurveys. Here, the dynamic cone developed by someElectric prospecting
The potential response on the ground surface isgenerated by passing an electric current through theground. In electric prospecting, the distribution of421

SEE - Bangkok, Thailand, Nov.11-13, 2019

-2.0

0

表面波探査解析結果

-1.0

0

-0.0

S波速度

1.0

230

Depth (m)

210

200
200

3.0

深 4.0

190

4

180
180

度 5.0

170

160
160

(m) 6.06

140
140

8

120
120

130

8.0

20

10.0 11.0 12
12.0 13.0 14
14.0 15.0 16
16.0 17.018
18.0 19.0 20
20.0 21.0 22
22.0
00.0 1.0 22.0 3.0 44.0 5.0 66.0 7.0 88.0 9.0 10
距 離 程 (m)(m)
Length
縮尺＝1/100

Figure 5 Shear wave velocity distribution(Line No.2)-2.0

PS logging
Surface wave prospecting

110

100
100
(m/s)
(m/s)

9.0

10

10

150

7.0

10.0

Depth （m)

220
220

2

2.0

100

200

300

400

Shear wave velocity (m/s)

Figure 6 Comparison with PS logging
0

推定N値断面

-1.0

0

換算N値
14
14

1.0

2

13

Depth (m)

2.0

12
12

3.0

11

深 4.0

10
10

度 5.0

88

(m) 6.0666

49Depth (m)

-0.0

10

7

5

7.0

44

8

8.0

Standad penetration test
Surface wave prospect

3

22

9.0

1

10
10.0 11.0 12
12.0 13.0 14
14.0 15.0 16
16.0 17.0 18
18.0 19.0 20
20.0 21.0 22
22.0
00.0 1.0 22.0 3.0 44.0 5.0 66.0 7.0 88.0 9.0 10
距 離 程 (m)(m)
Length
縮尺＝1/100

20
0

10.0

20

30

N-value

Figure 8 Comparison with astandard penetration test

Figure 7 N-value distribution (Line No.2)0Depth (m)0Depth (m)

10

10

10

Swedish sounding
Surface wave prospecting
Cone penetration test
Surface wave prospecting
20
0

10

20

20
0

30

N-value

10

20

30

N-value

Figure 9 Comparison with acone penetration test

Figure 10 Comparison with
Swedish sounding

companies was included and their specifications arevarious. Both the surface wave and the electricprospecting were conducted along survey Lines No.1
and No.2 shown in Figure 3. Figure 4 shows thestratigraphic column obtained from one boring. It
indicates a thick alluvial clayey soil layer under an
alluvial sandy soil layer near the ground surface.
Diluvial sand and clay layers repeatedly appear under
the alluvial layer, and this ground exhibits West
Osaka’s typical plain stratigraphy. The groundwaterlevel appears around 2.0m deep.
Figure 5 shows shear wave velocity distribution
obtained from surface wave prospecting along Line
No.2. The green areas indicate small wave velocity
and low stiffness. On the other hand, red areas
indicate relatively higher stiffness. In this site, PS
logging was conducted at one boring hole. The resultsof PS logging and surface wave prospecting arecompared in Figure 6. A similar tendency can be seen

near the ground surface. It is generally said that
surface wave prospecting is applicable until 15m deep.
Moreover, the results from PS logging show 2 to 3
times of the results from surface wave prospecting.
This is because the shear wave velocity can bedirectly obtained from PS logging, while shear wave
velocity is converted from Rayleigh wave velocity insurface wave prospecting. In soundings, the groundstiffness is expressed by the N-value. Figure 7 shows
N-value distribution calculated from Figure 5 byequation (1). Figures 8, 9 and 10 show comparisonsof the N-value expressed in Figure 7 with the N-value
obtained by each of the soundings. They show good
agreement. However, as seen in the comparison withPS logging, some difference between surface wave
prospecting and soundings appear, and surface wave
prospecting is applicable only at depths shallower
than 10m.
In electric prospecting, measurable area and
422

SEE - Bangkok, Thailand, Nov.11-13, 2019

2.0
1.0
0.0

0

凡例

-1.0
-2.0

220
220

2

200

深度（ｍ）
Depth (m)

-3.0

標
高

(m)

-4.0

180
180

4

160

-5.0
-6.0

140
140

6

120
100
100

-7.0
-8.0

8

80
60
60

-9.0

40

10

-10.0
-11.0

20
20

0

0.0

1.0

2

2.0

3.0

44.0

5.0

66.0

7.0

88.0

10

12

14
16
18
Length
距 離 程(m)
(m)

20

22

24

26

28

30

9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 28.0 29.0 30.0

Figure 11 Electric resistibility distribution with Pole-Pole Array (Line No.2)()

縮尺＝1/100

2.0
1.0

凡例

0

0.0

220

200
200

深度（ｍ）
Depth (m)

-1.0

180

標 -2.0

160
160

2

140

高 -3.0120120(m) -4.04

80
80

100
60

40
40

-5.0

6

-6.0

20

00.0 1.0 22.0 3.0 44.0

5.0

66.0

7.0

()
88.0 9.0 10
12 13.0 14
22 23.0 24
26 27.0 28
10.0 11.0 12.0
14.0 15.0 16
16.0 17.0 18
18.0 19.0 20
20.0 21.0 22.0
24.0 25.0 26.0
28.0 29.0 30
30.0Length
距 離 程(m)(m)
縮尺＝1/100

Figure 12 Electric resistibility distribution with Dipole-Dipole Array (Line No.2)
resolution is dependent not only on electrodeseparation but also on the array of transmission andreceipt electrodes. Here, electrodes were placed 1.0m
apart. Both the two-electrode method (Pole-Pole
Array) and the four-electrode method (Dipole-Dipole
Array) were applied as electrode alignment. It is said
that relatively deeper ground can be explored with
Pole-Pole Arrays and that Dipole-Dipole Arrays
show higher resolution. Moreover, when we apply a
Pole-Pole Array, two reference potential points areneeded, and two electrodes are placed at 5 times the
maximum measurement length apart from themeasurement line. Figures 11 and 12 show theelectrical resistibility distribution obtained from thePole-Pole Array and the Dipole-Dipole Array,
respectively. The bluer area shows lower electricalresistibility. In this site, the groundwater level isabout 2.0m deep. The contour of 40•m electricalresistibility corresponds to the groundwater level. As
detailed before, the electrical resistibility depends not
only on soil moisture but also on mineral and ionic
contents. However, differences in soil properties
apparent deeper than the groundwater level in Figure
4 cannot be identified. We can say that soil moistureis a dominant factor for electrical resistibility in thissite. Moreover, though the water pressure distribution,
indicating existence of perched groundwater, wasfound in borings, it cannot be found in the electricalresistibility distribution. The difference between
Figures 11 and 12 is not large, and both arrays areapplicable for the site condition.
Though geophysical explorations, surface wave

and electric prospecting exhibit some differencesfrom soundings, they show good agreement
qualitatively. Because of this, we can say that they are
effective for comprehensively characterizing
relatively shallow ground.
APPLICATIONOFGEOPHYSICALEXPLORATION FOR EMBANKMENTTo test the applicability of geophysicalexploration to embankment, surface wave andelectrical prospecting were conducted at a large
earthmoving construction site. Figure 13 shows thegeography of the site and the locations of geophysicalexploration. Lines a, b and c are located in what was
originally a valley area and surrounding a sand basin
for construction. In this area, a 40m high embankment
was constructed. Lines d and e are in a cut area andon the construction site access road. The surface wave

e
d
b c
a

Figure 13 Construction site and exploration lines
423

SEE - Bangkok, Thailand, Nov.11-13, 2019-2.0

表面波探査解析結果

-1.0

0

-0.0

S波速度
300
300
290

1.0

2

Depth (m)

2.0

280
270

3.0

260

深 4.0

250
250
240

4

度 5.0

230
220

(m) 6.06

210

200
200
190

7.0

8

180

9.0

160

8.0

170

150
150
10.0
10
(m/s)
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0
(m/s)
0
2
4
6
8
10 12
14 16 18
20 22 24
距 離 程 (m)(m)
縮尺＝1/100
Length(a) Shear wave velocity distribution
2.0
1.0
Legend

0

0.0

150

140
140
130
120
120
110
100
100
90
80
80
70
60
60
50
40
40
30
20
20

Depth (m)
深度（ｍ）
Depth (m)-1.0

標 -2.02
-3.0

高

(m)

4

-4.0
-5.0

6

-6.0
-7.0

()
10.0 11.0 12
12.0 13.0 14
14.0 15.0 16
16.0 17.0 18
18.0 19.0 20
20.0 21.0 22
22.0 23.0 24
24.0 25.0 26
26.0 27.0 28
28.0 29.0 30
30.0 31.0 32
32.0
00.0 1.0 22.0 3.0 44.0 5.0 66.0 7.0 88.0 9.0 10
距離程Length(m)(m)
縮尺＝1/100(b) Electrical resistibility distribution
Figure 14 Geophysical exploration (Line a)-2.0

表面波探査解析結果

-1.0
-0.0

0

S波速度

1.0

300

300
280
260
260
250
240
240
230
220
220
210
200
200
190
180
180
170
160
160
150
(m/s)
(m/s)
290

2

Depth (m)

2.0

280
270

3.0

深 4.0

4

度 5.0

(m) 6.06
7.0

8

8.0
9.0

10
10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0
00.0 1.0 22.0 3.0 44.0 5.0 66.0 7.0 88.0 9.0 101214 16 18
20 22 24
距 離 程 (m)(m)
縮尺＝1/100
Length10.0(a) Shear wave velocity distribution
2.0
1.0

0

0.0

凡例

-1.0
150

2

140
140

-2.0

130

-3.0

120
120

深度（ｍ）
Depth
(m)

標 -4.04
高

(m)

110
100
100

-5.0

90

6

-6.0

80
80
70

-7.0

60
60

8

-8.0

50
40
40

-9.0

30

10

-10.0
-11.0

20
20
()
0.0 1.0 2
2.0 3.0 4
4.0 5.0 6
6.0 7.0 8
8.0 9.0 10
10.0 11.0 12
12.0 13.0 14
14.0 15.0 16
16.0 17.0 18
18.0 19.0 20
20.0 21.0 22
22.0 23.0 24
24.0 25.0 26
26.0 27.0 28
28.0 29.0 30
30.0 31.0 32
32.00
距 離 程(m)(m)
Length
縮尺＝1/100(b) Electrical resistibility distribution
Figure 15 Geophysical exploration (Line c)

prospecting was conducted in September 2018, andthe electric prospecting was conducted in November
2018. The embankment was built up to 5m higharound the sand basin at the time of the surface wave
prospecting. As the construction progressed
afterwards, the embankment had reached 10m high at
the time of the electric prospecting. Figures 14 and 15
show results of geophysical exploration in Line a andc, respectively. Redder areas indicate that higher

shear wave velocity and higher stiffness exists at
depth. A shear wave velocity of 250m/s can beconverted to an N-value of 20. If this is regarded as
the boundary between embankment material andoriginal ground, then it corresponds to about 5m
depth for both Lines a and c, showing good agreementwith the actual construction process. Moreover, in
this site, the valley is inclined from the left to the rightside of Figure 13. Therefore, the embankment of Line
424

SEE - Bangkok, Thailand, Nov.11-13, 2019

表面波探査解析結果

-2.0

-1.0

0

S波速度

-0.0

400
400
390
380
380
370
360
360
350
340
340
330
320
320
310
300
300
290
280
280
270
260
260
250
(m/s)
(m/s)

1.0

2

Depth (m)

2.0
3.0

深 4.0

4

度 5.0

(m) 6.06
7.0

8

8.0
9.0

10

表面波探査解析結果

-1.0

10.0

10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0
00.0 1.0 22.0 3.0 44.0 5.0 66.0 7.0 88.0 9.0 101214 16 18
20 22 24
距 離 程 (m)(m)
縮尺＝1/100
Length

0

S波速度

-0.0
1.0

350
350

2

2.0

Depth (m)

-2.0

340

330
330

3.0

深 4.0

320

4

310
310

度 5.0

300
290
290

(m) 6.06

280

7.0

270
270

8

8.0

260
250
250
(m/s)
(m/s)

9.0

10

10.0

10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0
00.0 1.0 22.0 3.0 44.0 5.0 66.0 7.0 88.0 9.0 101214 16 18
20 22 24
距 離 程 (m)(m)
縮尺＝1/100
Length(a) Shear wave velocity distribution
2.0
1.0
凡例

0

0.0

150

140
140
130
120
120
110
100
100
90
80
80
70
60
60
50
40
40
30
20
20

Depth
(m)
深度（ｍ）
Depth (m)

-1.0

標
高

(m)

2

-2.0
-3.0

4

-4.0
-5.0

6

-6.0
-7.0

()
10.0 11.0 12
12.0 13.0 14
14.0 15.0 16
16.0 17.0 18
18.0 19.0 20
20.0 21.0 22
22.0 23.0 24
24.0 25.0 26
26.0 27.0 28
28.0 29.030
30.0 31.032
32.0
00.0 1.0 22.0 3.0 44.0 5.0 66.0 7.0 88.0 9.0 10
距離程Length(m)(m)
縮尺＝1/100(b) Electrical resistibility distribution
Figure 16 Geophysical exploration (Line e: left and d: right)
a is thicker than that of Line c, and this difference iscaptured in the results of surface wave prospecting.
Considering the construction process, the exploration
area for the electric prospecting, shown in Figure 14(b) and 15 (b), indicate an embankment area. Kawai
et al. (2017) monitored soil moisture distribution ofembankment and clarified seepage behavior withinembankment. They said that water contained inembankment material redistributes due to potential
head difference within embankment after
construction and that it finally forms the phreatic
surface at the bottom of the embankment. The
electrical resistibility shown here indicates theredistribution process of water within embankment.
The difference in electric resistibility between Linesa and c can be regarded as the difference in time
elapsed during construction.
Figure 16 shows the results of geophysicalexploration conducted in Lines d and e. This area is acut slope. Therefore, fairly high shear wave velocity
distributions are seen. The minimum shear wave
velocity in the exploration area is 250m/s, and thiscorresponds to the boundary between embankment
and original ground, as shown in Figure 14 and 15.
The results of electric prospecting illustrate thetendency of higher electrical resistibility at depth.
This tendency is more apparent than in Lines a and c.
Consequently, it appears that geophysicalexploration can express the ground conditions of theconstruction process well, and it is applicable forground surveys.

soundings. In addition, applicability was also
investigated at a huge earth moving construction site.
Consequently, the following conclusions were
determined:(1) Comparing the results of geophysical exploration
with borings and soundings found good
agreement. However, limits in the measurable
area of the geophysical exploration werediscovered. In the case of surface wave
prospecting, the applicable limit is about 10m
depth from the ground surface.
(2) Electric prospecting shows good agreement withthe groundwater level. However, it only indicatessoil moisture and cannot resolve pressure
differences within saturated ground, such as
those caused by perched groundwater.
(3) Geophysical exploration can express the processof embankment construction.
REFERENCES[1] Sugiyama, Y., Kawai, K. and Iizuka, A., Effectsof stress conditions on B-value measurement,
Soils and Foundations, Vol.56, No.5, 2016,
pp.848-860.
[2] Imai, T. and Tonouchi, K., Correlation of Nvalue with S-wave velocity and shear modulus,
Proc. of the second European symposium on
penetration testing, 1982, pp.67-72.
[3] Kawai, K., Hazama, D. and Nose, R., Behaviorof the air phase within embankment due torainfall, Proc. of 2nd PanAm-UNSAT2017, 2017,
pp.1-10.
[4] Park, C. B., Miller, R. D. and Xia, J.,
Multichannel analysis of surface waves,Geophysics, 64, 1999, pp.800-808.

CONCLUSIONSIn this study, investigating the applicability ofgeophysical explorations to embankment, surface
wave and electric prospecting were conducted at asite investigated in detail by borings and various
4255th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

BASIC STUDY ON BRIDGE WEIGH-IN-MOTIONUSING OPTICAL FLOW ANALYSIS

1,2

Kouichi Takeya1, Junji Yoshida2
Faculty of Engineering, Graduate School, University of Yamanashi, Japan

ABSTRACT
Understanding traffic loads on bridges is essential since traffic-induced vibration is a primary factor of damage
in bridge structures. Bridge Weigh-in-Motion (B-WIM) is a method to measure vehicle axle loads by inversing
the analysis of bridge structural responses. In various studies into B-WIM, the influence line of girder deflection
and strain were mainly used and obtained results, especially on highway bridges. However, the accuracy decreasedon regular road bridges since vehicle speeds are variable on bridges due to traffic conditions. In this study, opticalflow analysis was applied using a video camera to precisely measure the location of vehicles on a bridge. A
foreground mask using the Gaussian mixture model and a Kalman filter was then applied to identify the vehicles.
Using results of measurements on a road bridge, first, an influence line of girder deflection was estimatedconsidering vehicle locations for the initial calibration. The deflection responses of local buses and passenger
vehicles were used in the initial calibration. Next, the vehicle axle loads were analyzed by monitoring the locationof vehicles using the video camera. Compared with conventional methods, which estimate vehicle locations fromaverage speeds, the proposed method has demonstrated higher adaptability in variable traffic conditions.
Keywords: Bridge, Bridge Weight-In-Motion, Optical flow, Variable speed

INTRODUCTION

Technical problems in many B-WIM approaches
include weight estimation errors when the vehicle
speed is variable, since the vehicle traveling speed isassumed constant in the calculation of vehicle
weights. Moreover, in the calculation of influencelines, approximation is often based on numericalanalysis and beam theory from the structural responsewhen the test vehicle is traveling, but it has been
noted that accuracy can be further improved if
influence lines that are based on actual measurements
can be used. O’Brien et al. proposed a method to
calculate the influence line from direct strain
measurements [4]. The difference between the two
curves, the measured strain and influence line, isminimized using the least squares method to obtain
the axle loads of traveling vehicles.
However, a disadvantage of the aforementioned
B-WIM algorithms is an assumption of constantvehicle speed. Vehicles travel at a non-constant speed
on bridges, in congested urban areas, or nearintersections or traffic lights. To address this issue,
Takeya et al. proposed a method to measure thepositions of traveling objects by analyzing video
images and applying a basic B-WIM using structural
responses of peak deflection [5]. Andrew et al.
proposed a correction method to B-WIM to adapt
non-constant vehicle speed by a re-sampling process[6].
In this study, a new B-WIM using video images
and deflection responses was devised, and it performs
calibration using local buses and regular traffic
vehicles. In particular, local buses can be treated as

Monitoring bridge traffic is critical to bridge
maintenance since heavy or overloaded vehicles
cause significant impact to bridge deterioration. Static
weigh stations have thus been installed for monitoring
the weight of vehicles, especially on highways.
However, these static weigh stations havedisadvantages of interrupting regular traffic andmeasuring costs.
Bridge Weigh-in-Motion (B-WIM) is a method todetermine the weights of vehicles traveling on bridges
by using the dynamic response of bridges. B-WIM
can be securely implemented without interrupting
regular traffic, since B-WIM is installed under
existing bridges and installation work is not requiredon traffic lanes. The concept of B-WIM wasintroduced as a feasibility study for an agency within
the U.S. Department of Transportation (the Federal
Highway Administration) by Moses in 1979 [1]. The
definition of the influence line, which is the structural
response of bridges proportional to the magnitude andposition of loads, was used to calculate vehicle axle
weights. Other B-WIM methods, such as theinfluence area method [2] and the reaction force
method [3], have also been developed for several
decades. B-WIM performs calibration by running aweight-knownreference
vehicle.
However,calibration is periodically required since structural
response changes due to bridge deterioration andenvironmental changes and so costs the organizationof the reference vehicles.
426

SEE - Bangkok, Thailand, Nov.11-13, 2019reference vehicles in the calibration process, as thesevehicle types are easy to identify and are relatively
heavy. In addition, it is possible to recreate a system
which adapts to various traffic conditions such as
variable traveling speed by using video images. In
this study, axle weights were calculated fromdeflection measurements and the analysis of video
images of traveling vehicles on an existing bridge.

changes in background and the number of Gaussianmodes was manually tuned, as shown in Table 1. The
image erosion and morphological operations wereapplied to the resulting foreground mask to eliminate
noise. Table 2 shows the tuned parameters of thesenoise canceling filters.
Second, blob analysis detects groups of connected
pixels, which are likely to correspond to vehicles. The
association of detections to the same object isestimated by a Kalman filter [7]. The Kalman filter isused to predict the location in each frame anddetermine the likelihood of each detection being
assigned to each track. If an object is detected, theKalman filter first predicts the objects state in thecurrent video frame. In this study, constant velocity is
assumed for prediction. The filter uses the newly
detected location to correct the state, producing afiltered location. Finally, the location of each moving

CALCULATION OF INFLUENCE LINE
USING REGULAR TRAFFIC RESPONSE
Target Bridge and Measurement Instruments
The target bridge is a general road bridge of nine
continuous simple steel girders and RC decks, locatedin Kofu City, Yamanashi Prefecture, Japan. The
cross-section of the bridge is shown in Fig. 1. The
length of each span is ten meters. Figure 2 shows thetarget bridge and the installation of measurement
instruments. The deflection at the center of the second
girder was measured with a laser displacement meter(Keyence, LK-500) installed on a tripod (Fig. 3). The
measured deflection was recorded by the data logger(Keyence, NR-HV04). The frame size and frame rateof the video camera (Sony, FDR-AX55) were 1080p
and 30 fps respectively.

1.3 m

1.3 m
RC decks

0.6 m
Girder 3

Steel girders
Girder 2

Girder 1

Laser displacement sensor

Fig. 1 Cross section of the target bridge and themeasuring point of the deflection

Vehicle Detection with Optical Flow Analysis
Based on Background Subtraction Algorithm
To date, the authors have constructed a method for
tracking objects in video images using a stationary
camera and acquiring their locations [5]. This study
improves the previous method by detecting multiple
vehicles on bridges using a Kalman filter.
Motion-Based Object Tracking

Fig. 2 Target bridge and installation of the video
cameraMotion-based object tracking is divided into threeparts:
1) detecting moving objects in each video frame;2) associating the detections corresponding to thesame object over time; and3) calculating the location of each object over time.
MATLAB 2016b was used for this analysis.
The detection of moving objects uses a backgroundsubtraction algorithm based on the Gaussian mixture
model. To determine whether individual pixels arepart of the background or the foreground, aforeground mask using the Gaussian mixture modelcompared a grayscale video frame to a backgroundmodel. The parameters used in the backgroundsubtraction algorithm using the Gaussian mixture
model are shown in Table 1 and Table 2. Sixty or
more video frames were used for initial learning of
the background. Clouds tended to be noise in the
background subtraction. Therefore, the learning ratio
for adapting the background subtraction to theFig. 3 The target bridge and measuring
equipment for the deflection of bridge
girders.
427

SEE - Bangkok, Thailand, Nov.11-13, 2019

object is calculated. Figure 4 shows how the locationof the vehicle and axle were defined. First, thedetected blob of the vehicle is enclosed in a boundingbox, and the center position of the vehicle is obtainedusing the front and rear positions. Next, all axle
positions are manually selected from each detectedvehicle image, and the locations of the axles arecalculated. An example of an analysis result is shownin Fig. 5. In this study, the location start point is theedge of the second span of the target bridge. After
automatically extracting the center position of thevehicle, the time history data of the axle location is

obtained using the information of the axle position
judged by visual observation.
Consideration
The proposed optical flow analysis based on the
background subtraction method acquires the time
history of the location of traveling vehicles on thebridge. However, it does not consider two-way traffic,
namely cases where vehicles are mutually traveling inboth directions, since the vehicles are detected as
silhouettes. Although the target bridge had two-way
traffic with one lane on each side, the main target was
only when there was traffic on the front lane (vehicles
traveling from right to left in the photo). When thetarget vehicle was much larger than others, theirsilhouette could be tracked even for two-way traffic.
Convolutional Neural Networks (CNN) could
improve the ability of tracking, including two-way
traffic and multiple lanes.

Table 1 Parameters of the Gaussian Mixture
Model for the background subtraction
Gaussianmodes
5
Table 2

Learning ratio
0.005

Parameters of the morphological image
processing for noise elimination

Process
Structuring
elements
pixelsNumber oflearning frames
60 frames or
more

Image
erosionLineshaped
15 px(vertical)

CALCULATION OF INFLUENCEBASED ON MEASUREMENT

Morphologicalclosing
opening
DiskDiskshaped
shaped100 px
10 px(radius)(radius)LINE

In this study, the influence line of deflection was
calculated by synchronizing the time history of theaxle position from optical flow analysis and the time
history of deflection. Instead of using a reference
vehicle in the calibration process, local buses andvehicles detected from video images were used. A
diagram of the necessary steps to predict the influenceline is shown in Fig. 6. First, the initial values of theinfluence line L(x) and axle weight W areapproximately estimated. Next, the influence line isconverted in time domain for each axle (L(t)), as
shown in Fig. 7. Deflection is calculated from a
convolution of each converted influence line L(t)multiplied by the axle weight W. The Euclidean
distance between the calculated distance andmeasured deflection D(t) is evaluated, and theinfluence line and axle weight are modified tominimize the evaluation function by the direct searchmethod. The evaluation function is expressed by thefollowing equation using the influence line converted
in time domain.

Fig. 4 Definition of the location of the target vehicle
and its axle.

f(L(t),W,D(t))=‖L(t)∙W-D(t)‖(1)

To avoid convergence to the local solution, search
for the influence line and the axle weight wererepeated three times in this study. The initial value ofthe influence line is based on beam theory. The initial
axle weight is estimated by dividing the total weightof the vehicle by the number of axes. The vehicles
used were two medium-sized local buses and twopassenger cars. The passengers on the buses or cars
were not observed from the video images. The modelof the passenger cars was estimated from the video
images, and the approximate average weight wasFig. 5 Example of the result of the background subtraction
using GMM analysis.
428

SEE - Bangkok, Thailand, Nov.11-13, 2019used as the initial axle weight. Figure 8 shows themodified influence line L*(x) obtained as a result of
the aforesaid method, and the modified axle weight
W* is shown in Table 3. Although the target bridge isa series of simple girders, the influence line is stillaffected even when the vehicle is traveling on thegirders that are further than the measurement span forthis study. Figure 9 shows the time history ofdeflection obtained from the convolution of influencelines and axle weights. The deflection estimated fromthe modified influence lines and axle weights is
considered to correspond with the measured
deflection.
Consideration
Since the proposed method calculates theinfluence line based on actual measurements, it could
be applied to continuous bridges where deflection
occurs in the negative direction. On the other hand,
one problem in the analysis is time synchronization
between evaluating the video images of the traffic andthe deflection data of the bridge. Timesynchronization error accumulated since the internal
clocks of the measuring instruments were different.
This error depends on the span of the bridge and the
speed of vehicles however, it is necessary tosynchronize the time to the order of 50 ms or less, as
determined from experiment, to calculate the correct
influence line.
In this study, beam deflection was measured usinga laser displacement meter. Nonetheless, if it waspossible to use an accelerometer and obtain deflection
by integrating acceleration, the B-WIM system could
operate with greater ease. The sampling moiré
method is another method considered able to measure
deflection using video images [9].

Influence line L
Axial loads W
iteration
Conversion of influence line
L
Lt

Direct search of influence line
min f L t W D t
Lt
Direct search of axial loads
min f L t W D t
WConversion of influence line
Lt
L

Influence line L
Axial loads W

Fig. 6 Analysis diagram of the influence line basedon measurements

Fig. 7 Explanation of domain exchange of theinfluence line

Fig. 8

Modified influence line calculated through theiterative analysis

Fig. 9Comparison of Measured and calculated
influence line

429

SEE - Bangkok, Thailand, Nov.11-13, 2019

AXLE WEIGHT ESTIMATION

which approximately matches the measured
deflection is shown in Fig. 13. This proposed B-WIM
using video images could estimate the axle weights
and the total vehicle weight with small errors even for
low or variable speeds, which was a difficult
condition for many conventional B-WIM systems.
The time history of a dump truck location, which
was traveling on the bridge (Fig. 14), determined byblob analysis is shown in Fig. 15. The dump truck has
three axles and traveled at an approximately constant
speed of 35 km/h. The time history of measured
deflection and the fitted deflection from theconvolution of the influence lines is shown in Fig. 16.
As a result of calculating the weight of the dump truck,
it was possible to estimate each axle weight.
In this study, there were no patterns where large
vehicles traveled on the same girder since the girder
span was relatively short. However, the proposed
method could in principal, estimate each axle weighteven under continuous traffic conditions on the same
girder.

In previous sections, calibration was performed to
calculate the influence line using local buses andvehicles by processing the data of deflection andvideo images. By combining the obtained influenceline, vehicle location, and beam deflection data, theaxle weights of traveling vehicles were estimated.
Figure 10 shows the calculation process for the axle
weights. The influence line is converted to time
domain using the time history of the vehicle locationof each axle obtained from the video images. The axle
weights are determined so that the difference between
the deflection calculated from the influence lines ofeach axle weight and measured deflection isminimized using the direct search method. The
objective function is a nonnegative linear leastsquares problem.
The results obtained are shown in Table 4. As aresult of estimating the axle weights of medium-sized
local bus C, the difference between the calculated
vehicle weight and the nominal weight was 5.7 %.
Although the speed of another local bus (bus D,
shown in Fig. 11) changed on the bridge due to traffic
congestion (shown in Fig. 12), the difference between
the total vehicle weight calculated from each axle
weight and the nominal weight was less than 1 %. The
time history of deflection obtained from theconvolution of the influence lines of the axle weights,

CONCLUSIONSIn this study, by devising a new B-WIM method,which performs image analysis based on a calculation
process using multiple general local buses andpassenger vehicles, the following findings wereobtained.
Image subtraction based on the Gaussian mixture
model determined the location of traveling vehicles
on the target bridge. The location of all axles in eachvehicle was acquired by manual selection from thevehicle images. A calibration process was proposedusing the iteration process to optimize the axle weightof reference vehicles and the influence line ofdeflection. The total vehicle weights could be
calculated even under variable traffic speed.
The proposed method could estimate each axle
weight even under continuous traffic on the same
girder. If the deep learning method is incorporated
into the proposed system, vehicles under various
traffic conditions, including two-way traffic, could
also be identified.

Influence line L (x)Location of axis X(t)Deformation D(t)Conversion of influence line
L
L t
Solve linear least-squares problem
min f L t W D t
W
Axial weights W

Fig. 10 Calculation process of axle weights
Table 3Comparison of initial and modified axle weights through the analysis process of the influence line

VehiclesLocal bus A
Local bus B
Passenger car A
Passenger car B

Initial weights W
1 axle
2nd axle
3,650 kg
3,650 kg
3,650 kg
3,650 kg
500 kg
500 kg
400 kg
400 kgstModified weights W*
1 axle
2nd axle
3,534 kg
3,699 kg
3,416 kg
3,970 kg
569 kg462 kg
284 kg537 kgst

Table 4 Calculated axle weights and total weight of vehicles
Vehicles (Nominal weight)
Local bus C (7,315 kg)
Local bus D (10,630 kg)
Dump truck (unknown)

1st axle
2,809 kg
4,118 kg
3,548 kg

2nd axle
4,090 kg
6,433 kg
4,812 kg430

3rd axle
2,692 kg

Total
6,899 kg
10,551 kg
11,052 kg

Error
-5.7%
-0.7%
-

SEE - Bangkok, Thailand, Nov.11-13, 2019civil engineers - Bridge Engineering, Vol. 159,
Issue 1, 2006, pp. 31-34.
[5] Takeya K., Ota K., Takagi S., and Yoshida J.,
Analysis of Traffic Environment and Dynamic
Behavior of Bridge Girders based on Image
Sensing Techniques, Fourth International
Conference on Science, Engineering andEnvironment, No. 4721, 2018, pp. 1-6.
[6] Lansdella A., Songa W., and Dixon B.,
Development and Testing of a Bridge Weigh-inMotion Method Considering Nonconstant
Vehicle Speed, Engineering Structures, vol. 152,
2017, pp. 709-726.
[7] Welch G., and Bishop G., An Introduction to the
Kalman Filter, University of North Carolina at
Chapel Hill, Department of Computer Science,
2006.
[8] Ri S., Numayama T., Saka M., Nanbara K., andKobayashiD.,
Noncontact
Deflection
Measurement for Large-Scale Structures by
Advanced Image Processing Technique, Materials
Transactions, Vol. 53, No. 2, 2012, pp. 323-329.

ACKNOWLEDGMENTS
This research was supported by Grants-in-Aid for
Scientific Research for Early-Career Scientists fromJapan Society for the Promotion of Science (JSPS).
REFERENCES[1] Moses F., Weigh-in-Motion System Using
Instrumented
Bridges,
Transportation
Engineering Journal of ASCE, Vol. 105, Issue 3,
1979, pp. 233-249.
[2] Ojio T, Yamada K., Bridge Weigh-in-Motion
Systems using Stringers of Plate Girder Bridges,
Third International Conference on Weigh-inMotion, 2002, pp. 209-218.
[3] Ojio T, Yamada K., Bridge WIM by Reaction
Force Method, Fourth International Conferenceon Weigh-in-Motion, 2005, pp.97-108.
[4] O’Brien E. J., Quilligan M. J., Karoumi R.,
Calculating an Influence Line from Direct
Measurements, Proceedings of the institution ofFig. 11 Out view of the local bus D

Fig. 14 Out view of the dump truck

Fig. 12 Time history of the location of the local bus
D on the target bridge

Fig. 15 Time history of the location of the dump
truck on the target bridge

Fig. 13 The measured and calculated deflection when
the local bus D was traveling on the bridge

Fig. 16 The measured and calculated deflection when
the dump truck was traveling on the bridge431

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF REINFORCEMENT STIFFNESS ARRANGEMENT ON
SEISMIC PERFORMCANCE OF GEOGRID REINFORCED SOIL
WALLS

1,2,3

Albano Acacio Ajuda1, Jiro Kuwano2 and Kosuke Hoshina3
Department of Civil and Environmental Engineering, Saitama University, Japan

ABSTRACT
It is well known that geosynthetics reinforced soil walls are much cheaper and stable compared to traditional
retaining wall. However, most of the existing studies were conducted using a uniform reinforcement stiffness along
the wall height. Very few studies have been conducted regarding the effect of multiple reinforcement stiffness
along the reinforced soil wall height. This type of configuration can be used for construction cost reduction
maintaining adequate seismic response. In order to evaluate the behavior of wall with different stiffnessarrangement, a series of shaking table test were conducted on segmental walls with two different geogrid stiffness
material. The geogrid stiffness arrangement was alternating and grouped schemes. Image analysis based on FEM
allowed shear bands to be identified within the reinforced soil zone. Results showed that wall residual displacement,
shear deformation was dependent on the geogrid stiffness arrangement and despite application of multiple stiffness
the failure surfaces angles observed in the model test remained the same. Additionally, simple shearing and strain
localization was observed within the reinforcement layers. Further results showed that wall with alternated geogrid
stiffness was similar to wall with uniform stiffness in both magnitude and shape. However, by grouping a less stiff
geogrid either in upper half or lower half of the wall the magnitude of wall displacement and shear strain waslarger and bulging deformation was observed at mid-height of the wall before reaching critical acceleration.
Keywords: Earthquake, Shaking table test, Retaining wall, Stiffness arrangement
displacement amount was about 6% and 3%
respectively.
In the field of reduced-scale models, [5]-[7]conducted series of shaking table test on
geosynthetics reinforced soil walls using FHR facing,parameters such as L/H ratio, reinforcement stiffness,wall inclination was investigated. Their results
showed that wall horizontal displacement decreased
with increase in L/H ratio and wall reinforced withhigher reinforcement stiffness generated a shallower
displacement-acceleration response curve compared
to walls reinforced with a less stiff reinforcement. [8]reported that placing longer reinforcement layer at ahigher elevation in the backfill it is possible toincrease substantially the resistance against
overturning failure.
In the field of numerical analysis, [8] investigated
the influence of reinforcement length arrangement
along the wall height. It was found that the
deformation behavior of the surrounding ground wastotally different, by placing shorter reinforcement
length in the upper half and longer in the lower halfof the wall a zone of large shear deformation wasformed in an arc-shaped which extended from thefoundation layer towards the top of the backfill in theretaining area and slippage occurred, on the other
hand it was found that the formation of failuresurfacewas interrupted by the shorter
reinforcement layers. The maximum shear strain
observed in the models was concentrated at the end of

INTRODUCTION
Geosynthetics reinforced soil wall are well known
to be cost-effective and able to resist earthquakeinduced damage as compared to the traditional
retaining wall, for this reason, the number of
constructed walls has been increasing over the years
as reported in [1], [2]. Most of the existing literature
focuses on the application of one type ofreinforcement stiffness or geosynthetics material
along the wall height. According to [3] reinforcement
material can cost about 30 % of the total construction
cost of reinforced soil walls depending on wall height,
backfill type, and design loading condition. A
possible solution to further reduce the construction
cost maintaining an adequate seismic behavior could
be by constructing the wall with multiple
reinforcement stiffness or by using different
geosynthetics material.
In the field of full-scale models, [4] investigatedthe performance of geosynthetic reinforced soil walls
by monitoring the wall behavior over a period of 1
year. The walls were 3.6 m high seated on a clay
foundation, the backfill was constructed using
recycled construction waste to minimize theconstruction cost as well to reduce the environmental
impact. They reported that greater displacement canbe observed in walls constructed with more extensible
nonwoven geotextile as compared to walls withwoven polyester (PET) layers and the maximum
432

SEE - Bangkok, Thailand, Nov.11-13, 2019the reinforcement layers. [10] performed numericalanalysis using a computer program FLAC on wraparound walls subject to static loading. They reported
that wall deformation of walls with alternatedreinforcement stiffness values along the wall heightwas consisted with walls with one type ofreinforcement stiffness in shape and magnitude, bygrouping the reinforcement stiffness either in theupper or lower part of the wall large deformation
occurred in the region where less stiff reinforcement
was placed.
[11] showed three case studies of reinforced soil
walls which were damaged due to heavy rainfall inJapan. The geosynthetics reinforced soil walls wereconstructed with a steel frame facing with a totalheight of 9.5 m and 10.7 m. in one of the reinforced
soils walls the reinforcement layers were a
combination of two different material, geogrid, andgeotextile, which was placed in alternated manner.
Another wall was constructed with two different
lengths, a primary reinforcement with a longer lengthand a secondary with shorter length also placed inalternated manner.
The investigation of multiple reinforcement
stiffness or material type along the geosynthetics
reinforced soil wall is still limited. According to [10]no currently guideline directly considers the influenceof different reinforcement stiffness layers on the
distribution of tensile load in reinforced soil walls
systems. Additionally, for the author best knowledge
no current physical model test of this type ofarrangement is available in the literature. Taking this
into account, the present experimental work consistedof a series of shaking table test to investigate theseismic response of walls constructed with different
reinforcement stiffness along the wall height. Image
analysis technique was used to observe the wall
residual displacement and the failure mechanism atdifferent levels of ground motion amplitudes.

PHYSICAL MODEL TESTIn the present experimental work six segmental
geogrid reinforced soil wall were tested considering
the effect of reinforcement length, layout andstiffness arrangement on seismic performance using ashaking table test which was conducted at Saitama
University, Japan.
The shaking table is compromised on a plan
dimension of 1300 by 1000 mm controlled by acomputer. The shaking table is seated on a pair of low
friction bearing rails which are constrained in thehorizontal direction equivalent to a single degree of
freedom. The soil was poured in a rigid container withthe following dimension: 1300 mm (L), 300 mm (W)and 650 mm (H). One of the sides of the rigid box wasconstructed using a transparent Plexiglas so that walland backfill deformation can be visualized andcompute by a CCD camera. The far end boundary of
the rigid container was mad of steel which could
induce reflective waves and magnification of thestructure dynamic response during model testing as
demonstrated by [14]. However, according to [15] theeffect of reinforcement in reducing the deformation is
independent of container boundary type.
Model Soil and Geogrid
The model soil was Toyoura sand with thefollowing properties: 𝑒𝑚𝑎𝑥 = 0.973, 𝑒𝑚𝑖𝑛 = 0.609,
𝐷50 = 0.19 𝑚𝑚 . The soil foundation and backfill
were constructed using air pluviation method(raining) to achieve a desired relative density of 90%.
Two types of biaxial geogrid were used in thepresent study: a) high tensile strength (stiff) geogrid
and b) low tensile strength (soft) geogrid. The geogrid
was placed horizonal in the reinforced zone with a
total of eight layers spaced at 60 mm vertically.

800

Hydraulicactuator

200

Geogrid Layers

500

650

Shake
controller

Field
Opticaloftargets
forImage analysis
view

50

ii) Backfill Dr = 90%(Toyoura sand)Lightsi) Foundation layer Dr = 90% (Toyoura sand)A1 - Accelerometer
1300

Figure 1. Typical model test setup

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Unit in (mm)SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1. Summary of the tested cases
Test cases

Reinforcement length (mm)Reinforcement arrangement

Wall 1Wall 2
Wall 3
Wall 4Wall 5Wall 6300
200
300/200

Uniform
Uniform
Alternated lengths
Alternated stiffness
GroupedGrouped

200

Vertical spacing
(mm)

60

Model Construction

The wall was built vertically with a total of eightacrylic panels each with the following dimension: 300
mm (W), 75 mm (H) and 30 mm thick, each panel
was stacked on top of each other up to a total heightof 500 mm, without any additional connection
between the panels. On both sides of the wall panels
Teflon sheets were used to minimize friction between
the soil container and the wall panels. Similar wallheight has been investigated by [8], [12]. The toe ofthe wall can slide freely to the horizontal direction
since the first panel is seated on the sand foundation.
The geogrid reinforcement layers were rigidly
connected between two steel clamps with the samelength and width as the wall panels, this arrangement
prevented slippage of the reinforcement layers duringmodel test and finally, the connection was bolted toeach wall panel as illustrated in Figure 2.

The first construction stage consisted in building
the foundation layer which was made of 50 mm layer.
Then the wall panels were placed into the appropriate
position and braced to prevent wall lateral movement
during backfilling. The backfill was then constructedin 30 mm layers to allow optical targets to be placed,
after the backfilling finished unbracing stage started
from the wall top toward the bottom. Finally, the laststage consisted in bolting the light steel frame to thesoil container as well to the shaking table toaccommodate the CCC camera.

Rigid connection

The seismic wave was applied using a sinusoidal
wave with a predominant frequency of 5 Hz. Eachshaking stage was held for 10 seconds corresponding
to a total of 50 cycles/step. The models were
subjected to different amplitudes which started fromthe lowest 1m/s2 with steady increments of 1m/s2
until fully collapsed.

Rigid connection

Bolts

Bolts
Geogrid60

75
45

Geogrid75

Input Ground Motion

15

15

Facing Panels

Hexagonal nuts

15

Acceleration (m/s2)

Hexagonal nuts
Toyoura sandToyoura sand

15

15

Fig. 2 Details of wall panels
Model Instrumentation

Time (s)Two different types of instrumentation were usedin each model to record the seismic response. The
instrumentation consisted in three accelerometers
where the first was attached to the shaking table torecord the input ground motion and one at the midheight and one at the top of the wall in the reinforcedzone and at 100 mm away from the wall to record thesoil dynamic response. Twelve optical targets madeof cartoon was glued to the wall panels to record thewall displacement and 240 optical targets with 8 mm
in diameter made of rubber sponge glued with shortnails was placed in the backfill in a 30 mm by 30 mm
grid to obtain soil displacement for subsequentcalculation of shear strain.

Top Horizontal Displacement (cm)Fig.
3 Input ground motion
54Wall 5Wall 7

Wall 6

Wall 8Similitude Rules
3
Sliplines Formation

2
Geogrid reinforced
soil walls modle test wascaried out using
1g
shaking
table test. The stress1
levels in the experiments do not truly represent the0stresses in the0.0field 0.2because
of 0.6the gravity
and
0.4
0.8
Seismic Coefficent (Kh)boundary effects inHorizontal
model
studies. In the present
experimental program similitude laws proposed by[16] was used with a geometric scaling factor of 10
between model and prototype scale.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

forces at the end of the reinforcement layers as wellat the end of the retained area can observed. For allcases the failure surfaces penetrated the reinforced
soil block suggesting that the bottom reinforcement
did not constrain the sliding component efficiently.
Once the critical acceleration was reached the failuresurfaces angles remained the same throughout themodel shaking. [18] reported that the exact positionof the failure surfaces changes as the amplitude ofshaking increases using Geo-PIV.
In the present work simple shearing and strain
localization along the reinforcement layers wasobserved during model testing. For instance [19]defined strain localization as a high gradient of shear
strain associated with high displacement gradient, it
is possible to notice form Figure 4 a concentration ofhigh magnitude of shear strain along thereinforcement layers especially in the upper half of
the wall during 5 m/s2 at 15 and 30 cycles since large
deformation of the wall and backfill occurs in thisregion due to overturning, therefore pullout
displacement of the reinforcement layers was larger.
[20] conducted pull out test to investigate the soilgeogrid interface mechanism, they reported that the
maximum shear strain occurred close to the soilgeogrid interface and that under pullout conditionpassive resistance is the main contributor of soil
resistance to pullout particularly under low confiningpressures.

EXPERIMENTAL REULTS AND DISCUSSION
Regarding seismic deformation of geogrid
reinforced soil walls, previous researchers [13], [17]showed a displacement of 5% which the reinforcedzone suffered a backfill strength deterioration. In thepresent experimental test, the wall displacement
increased with base acceleration and when the top
displacement reached 3% of the wall height which ishere defied as the critical accretion at this stage
unrecoverable deformation of the backfill wasobserved, at this stage clear failure surfaces wasobserved within the reinforced zone and retained zone.
[7] defined critical acceleration as the sudden change
in the rate of wall rotation and [12] as acceleration atwhich a sharp increase in incremental displacementtakes place.
Figure 4 shows the progressive deformation of thebackfill for wall 2 reinforced with a uniform highstiffness reinforcement from 4m/s2 to 5m/s2. The
failure extended from the wall top toward the bottom
in the lowest reinforcement layer and inclined failuresurfaces the wall toe towards the end of the first
reinforcement layer form this location it inclined
upwards towards the backfill surface in the retainedzone allowing a creation of an active failure wedge
where the soil mass slide downward to the back of thewall, at this point large backfill settlement can beobserved with a “U” shape geometry and drag-down

Fig. 4 Progressive deformation wall 2 a) 4 m/s2 b) 5 m/s2 (15 cycles) c) 5 m/s2 (30 cycles) d) end of 5 m/s
By increasing the geogrid reinforcement length
shallower top displacement-acceleration curve isobserved, therefore less deformation and higher
acceleration the wall can sustain. It is possible tonotice that Wall 1 with longer geogrid reach thecritical acceleration at around 500 gal while Wall 2
with shorter geogrid length reached criticalacceleration at 400 gal, suggesting that shorter
reinforcement length reach the instability stage at
smaller base shaking. However, by alternating longer
435

SEE - Bangkok, Thailand, Nov.11-13, 2019

Top Horizontal Displacement (cm)and shorter reinforcement along the wall height Wall3, the wall showed an intermediate behavior between
Wall 1 and Wall 2 and the critical acceleration wasobserved to be the same as Wall 1. This behavior
could indicate that the wall can maintain
serviceability and performance during seismic
shaking.

height of the wall where the stiff geogrid is placed,from this location the wall horizontal displacement
tends to reduce with increase with increase in wall
elevation. However, due to large amount of sliding
component, the wall top continually moved to theoutward direction.
The shear strain magnitude in the backfill wasdependent on the geogrid stiffness arrangement as
illustrated in Figure 6, the lowest values of shear
strain were observed for wall with stiff geogrid Wall2, similar variation on shear strain can be observed in
Wall 4. However, walls with grouped schemes Wall
5 and Wall 6 showed larger movement of the backfill,consequently large values of shear strain can be seen
compared to Wall 2. From the same figure it ispossible to see the angles of failure surface observedin shaking table test for walls with multiple
reinforcement stiffness. Interesting, even by mixing
or grouping the reinforcement stiffness along the wallheight, failure surfaces were depended only on thehigh stiffness reinforcement and reinforcement length.
For instance, [21] demonstrated that failure surfaces
have different geometry under different geogrid
tensile strength using centrifuge test and two-wedge
method. This behavior could indicate that reinforced
soil wall constructed with different tensile strength
along the wall height can be designed using hightensile strength value only especially for walls withalternating schemes. Additionally, according to [21]if the tensile stiffness of the geogrid is insufficient,strain is concentrated in the reinforced area because
the geogrid reinforcement cannot restrict the
deformation of the backfill. Therefore, wall with stiff
geogrid in this experiment was able to resist most of
the backfill shear deformation as can be seen throughthe magnitude of the shear strain distribution,
followed by wall with alternating stiffness whichshowed about 20% increase in the magnitude of shear
strain. However, wall with grouped schemes showedvery large backfill shear deformation with shear strainof about 80 % increase as compared to stiff geogrid
wall. This behavior may suggest that grouping thelower reinforcement stiffness either in the upper orlower part of the wall may not be appropriate forconstruction cost reduction of GRSW.

10Wall 1Wall 2

Wall 3

8

6

4

2

0
0

200

400

600

800

Input base acceleration (gal)Figure 5 Wall residual displacement against baseacceleration
In Figure 7 are plotted the relationship of top
displacement with the base acceleration of the tested
walls. It is possible to notice that wall with stiff
uniform reinforcement Wall 2 showed an increase instability. However, by substituting half of the stiff
geogrid with soft geogrid in an alternating mannerWall 4, the wall showed almost the same amount of
displacement and shape to Wall 2 constructed withstiff geogrid. By grouping the reinforcement stiffness
Wall 5 or Wall 6 it showed an increase in the top
horizontal displacement and bulging phenomena wasobserved at mid-height before reaching critical stages
as illustrated in Figure 7. It is possible to notice thedifference in the deformation along the wall elevation,for example at 300 gal in Wall 2 the deformation
tends to be linear from to wall toe up to the wall top,
this deformation shape was also observed in the caseof Wall 4, while in grouped schemes the wall
deformation is less in the region where the stiff
geogrid is placed, however, when reaching the midheight of the wall where the geogrid stiffness changes
to a soft geogrid the horizontal displacement
increases considerable. Wall 6 showed an increase insliding component because of this movement the wall
top displacement also increased considerably. It is
possible to notice that in the bottom part of the wall
where soft geogrid is placed the displacement in thisregion tends to increase with elevation up to the mid

436

SEE - Bangkok, Thailand, Nov.11-13, 2019

8

40

6

4

20

2

08

06

05

04

07

0.

0.

0.

0.

0.

03

0

0
0

200

400

Input base acceleration (gal)

600

15

Wall 510Wall 2Top Horizontal Displacement (cm)Wall 260

60

10Wall Elevation (cm)Wall 4

Top Horizontal Displacement (cm)100.

Top Horizontal Displacement (cm)Fig. 6 Maximum shear strain after 4 m/s2 base acceleration a) wall 1 b) wall 2 c) wall 3 and d) wall 4

40

20

5

Bulging
0
0.0

0.1

0.2

0.3

60

Wall 6

Wall 2

8
40

6

4

20

Bulging
20
0.0 0.1 0.2 0.3 0.4 0.5

Horizontal Displacement (cm)

0

0

0

200

400

600

Input base acceleration (gal)

0

200

400

600

Input base acceleration (gal)Fig. 7 Top horizontal displacement with ground acceleration and displacement profile at 3 m/s2.
arrangement; and failure surfaces angles
observed in the backfill were almost the same towall with single reinforcement stiffness;

CONCLUSION
Reduced-scale shaking table tests were performed
to investigate the seismic response of segmental
geogrid reinforced soil retaining wall constructedwith multiple reinforcement stiffness along the wallheight in different configuration. The progressive
failure, shear strain distribution in the backfill andlateral displacements of the wall were compared
under different ground motions amplitudes. The
following conclusions could be drawn:

ACKNOWLEDGEMENT
This research project has been sponsored by JSPS
KAKENHI Grant Number 16H04406 andMonbukagakusho Scholarship (MEXT)REFERENCES[1] Kuwano J., Miyata Y., and Koseki J.
Performance Of Reinforced Soil Walls During
The 2011 Tohoku Earthquake, Geosynthetics
International, Vol. 21, Issue 3, 2014, pp.179-196.
[2] Koseki J., Bathurst, R.J., Guler, E., Kuwano, J.
and Maugeri M., Seismic Stability Of Reinforced
Soil Walls, 8th International Conference ofGeosynthetics, 2006.
[3] FHWA, Mechanically Stabilized Earth Walls
And Reinforced Soil Slopes Design &Construction Guidelines, No. 132042. 2001.
[4] Santos E. C. G., Palmeira E. M., and Bathrust R.
J., Performance of Two Geosynthetic Reinforced
Walls With Recycled Construction Waste
Backfill and Constructed on Collapsible Ground,Vol. 21, Issue. 4, 2014, pp. 256-269.
[5] El-Emam M. M. and Bathrust R. J., Experimental
Design , Instrumentation And Interpretation of
Reinforced Soil Wall Response Using A Shaking
Table, Vol. 4 Issue 4, 2004, pp. 13-32.
[6] El-Emam M. M. and Bathrust R. J., Facing
Contribution To Seismic Response Of ReducedScale Reinforced Soil Walls, Vol. 12, Issue 5,2005, pp. 215-238

I.

Wall residual displacement decrease withincrease of reinforcement length; By mixing
shorter and longer reinforcement it was foundthat the critical acceleration was almost same as
the wall with longer geogrid (300 mm) which
could indicate that the wall may still work atservice level;
II. The predominant failure mode was overturning
accompanied with sliding and bulging
deformation; Failure surface were formed when
the wall horizontal displacement reached 3
percent of the wall height;
III. Results showed that alternating reinforcement
stiffness along the wall height similar wall
deformation and shear strain magnitude to wallswith a single reinforcement stiffness can beobserved;
IV. Grouped schemes clearly showed larger wall
deformation together with an increase of shear
strain magnitude compared to wall with single
reinforcement stiffness;
V. Failure surface angles was observed to be
independent on the reinforcement stiffness
437

SEE - Bangkok, Thailand, Nov.11-13, 2019[7] El-Emam M. M. and Bathrust R. J., Influence ofReinforcement Parameters on the Seismic
Response of Reduced-Scale Reinforced Soil
Retaining Walls, Vol. 25, Issue 1, 2007, pp. 3349
[8] Watanabe K., Munaf Y., Koseki J., TateyamaM., Kojima K., Behaviors Of Several Types Of
Model Retaining Walls Subjected To Irregular
Excitation, Soils and Foudnations, Vol. 43 Issue
5, 2003, pp. 13-27.
[9] Kikumoto, M., Nakai, T., Shahin, H. M.,
Watanabe, A., Ishii, K. and Zhang, F.,
Mechanicalbehaviourofgeosyntheticreinforced soil retaining wall, ASCE
Geotechnical Special Publication (Ground
Improvement and Geosynthetics) 207, pp. 310317[10] Hatami K., Bathrust R. J. and Di Pietro P., Static
Response of Reinforced Soil Retaining Walls
With
Nonuniform
Reinforcement,
The
International Journal of Geomechanics, Vol. 1,
Issue 4, 2001, pp. 477-506.
[11] Miyata Y. and Shinoda M., A case study ofdamages of geogrid reinforced soil walls
triggered by rainfall, 6th Asian Regional
Conference on Geosynthetics, 2016.
[12] Matsuo O., Tsustumi T., Yokoyama K. and Saito
Y., Shaking Table Tests and analyses ofGeosynthetic-Reinforced Soil Retaining W alls,
Geosynthetics International, Vol. 5, 1998, pp.
97–126.
[13] Koseki J., Munaf Y., Tatsuoka F., Tateyama M.,
Kojima K. and Sato T., Shaking and Tilt Table
Tests of Geosynthetic Reinforced Soil walls andConventional-Type
Retaining
Walls,
Geosynthetics International Vol. 5, 1998, pp. 7396.
[14] Bathrust R. J. and Hatami K., Seismic Response

Analysis of a Geosynthetic-Reinforced Soil
Retaining Wall,” Vol. 5, Issue 1-2, 1989, pp.
127–166.
[15] Krishna A. M. and Gali M. L., Container
Boundary Effects In Shaking Table Tests On
Reinforced Soil Wall Models, International
Journal of Physical Modelling in Geotechnics,
2009, pp. 1-14.
[16] Lai S., Similitude For Shaking Table Tests on
Soil-Structure fluid Models in 1G GravitationalField, Soils and Foundtion, Vol. 29, Issue 1, 1989
pp. 105–118.
[17] Huang C. and Wu H., Seismic Displacement
Analysis of a Reinforced Soil Model Wall
Considering Progressive Development ofReinforcement
Force,
Geosynthetcis
International, Volume 16, Issue. 3, 2009, pp.
222–234.
[18] Bowman E. T., Jackson P., Cubrinovski M., andFannin R. J., Progressive Failure And Shear
Band Development Within Model-Scale
Reinforced Soil Walls Subject To Seismic
Shaking, Géotechnique Letters, Vol. 1, No. 3,
2011, pp. 53–57.
[19] Wood D. M., Some Observations Of VolumetricInstabilities In Soils, International Hournal of
Soilds and Structures, Vol. 39, 2002, pp. 3429–
3449.
[20] Abdi M. R. and Mirzaeifar H., Experimental And
Piv Evaluation Of Grain Size And Distribution
On Soil–Geogrid Interactions In Pullout Test,
Soils and Foundtion., Vol. 57, Issue. 6, 2017, Pp.
1045–1058.
[21] Izawa J. and Kuwano J. Centrifuge modelling ofgeogrid reinforced soil walls subjected topseudo-static loading, International Journal of
Physical Modelling in Geotechnics, Vol. 10,
Issue. 1, 2010, pp.1-18.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE IMPACT AGGREGATE QUALITY MATERIAL AS A LINEAR
REGRESSION STUDY ON MIXTURE CONCRETE
Ranti Hidayawanti1, Dicki Dian Purnama2 , Tommy Iduwin3, Supriadi Legino4 and Fahdun Ibnu Wachid5
1,2,3
Department of Civil Engineering, Sekolah Tinggi Teknik PLN, Indonesia; 4Department of InformaticEngineering, Sekolah Tinggi Teknik PLN, Indonesia; 5PT.Pembangkitan Jawa Bali , Indonesia

ABSTRACT
Fine aggregate and coarse aggregate are important components in making concrete for light and structure
concrete. These mixture concretes are one of the elements as structural component in building construction.
Generally, this aggregate is easy to find both coarse and fine aggregates beside the aggregate can be used as acomponent on concrete in the building which needs strong support. The objectives of this study are adding mixture
aggregate with compared to designed result (theory) mixture concrete by using the method of fine modulus andlinear regression. Those two methods will be found out theoretically in optimizing certain components (economic).
In order to get the presentation of aggregate and meet the requirement of standard quality concrete, are used thecomparison of fine and coarse aggregate at 60% - 40%. The method that is used to pass the screening is finemodulus and the counting of mixture aggregate used statistic formula calculation which is regression linear method
to find the percentage comparison between coarse and fine aggregate in designing of a mix that can be used in
making concrete. By knowing the maximum aggregate limit, it is expected to find out the limitation aggregate offine and coarse accurately so that the result of concrete that is used is better because the raw material is correct forthe construction composition. From the test results for fine aggregate R2 = 0.9444 and coarse aggregates R2=0.9541 with linear regression formulation is and compressive strength shows the value of R 2 = 0.9627, then thestrength of the relationship between variables can be expressed by the magnitude of the correlation coefficientvalue on the linear function.
Keywords: fine aggregate, coarse aggregate, fine modulus, concrete, linear regression

grains[3], where the formulation is as follows :𝑘−𝑐
𝑤 = 𝑐−𝑝 𝑥 100%
(1)

INTRODUCTION
Aggregate is a basic material used in buildings
ranging from the lowest structure to the uppermost
structure, both as fine aggregates and coarse
aggregates used in each mixture of concrete mixtures.
It is commonly known that 70% of the building is
concrete[1]. According to SNI 03-2847-2002,
concrete is a material obtained by mixing Portland
cement or other hydraulic cement, fine aggregates,coarse aggregates and water, with or without
additives forming solid mass. The use of material
from concrete can also be used with waste[2]. Besides
that there are still many other uses of fine and roughaggregates in building use such as filling in buildingcolumns, making foundations and road infrastructure.
In determining and grouping the size and type offine and coarse aggregates, it is important to note thatthe quality of the building blocks of building
materials is suitable and ideal. For this reason, it isnecessary to test the gradation in each aggregate to be
used as a mixture.
The index used to show the fineness / coarsenessof aggregate grains is MHB, and the factors that can
influence the search for fine grain modulus (MHB)
are the sieve size used and the size of aggregate

w = Percentage of fine aggregate (sand) in the
mixturek = Fine modulus of coarse aggregate
p = Fine modulus of sandc = Fine modulus mixture
Gradation can be said as smooth or rough modulus
in an aggregate, this difference will affect the use ofaggregate as a building material. All types ofaggregates taken from the source must be processed
before use. Washing and filtering is a processing
process that must be carried out and has been requiredfor its use.
In order to get gradations that are in accordancewith the standard concrete mix, an experiment needs
to be carried out then the results of the experimentwill be processed. Data processing is done using
linear regression formulations.
𝑦̂ = 𝑎 + 𝑏𝑥

(2)𝑦̂ = Estimate value of the dependent variablea439= Intersection point of the regression line on they axis or the estimated value if x = 0

SEE - Bangkok, Thailand, Nov.11-13, 2019b = Gradient of the regression line (change in theestimated value per unit change in the value ofx)x = Free variable value

above are :- Sieve diameter (9.60mm; 4.80mm; 2.40mm;
1.2mm- Cup; 0.60mm; 0.30mm; 0.15mm and PAN)
- Trays- Filters- Pedestals- Sieve shaker tools- Sieve cleaning brush

The formula of linear regression [4] is the datataken based on the dependent and independent
variables. R2 is the coefficient of determination(coefficient of multiple determination) of a regression
model that can be defined, as follows :𝑆𝑆𝑅
𝑆𝑆𝐸
R2 = 𝑆𝑆𝑇𝑂 = 1 − 𝑆𝑆𝑇𝑂
(3)
2
0≤R ≤1
The greater value of R2, the better model used andthe result R2 is the value of regression analysis while
approaching 1 means the data can be used.
This study aims to determine the effect ofaggregate grain size on compressive strength andmodulus of elasticity of concrete. Compressive
strength of concrete with a larger grain size has alower compressive strength value than concrete witha smaller size. A good aggregate gradation and small
aggregate size will be able to produce maximum
density and minimum porosity.
𝑃
f′c = 𝐴(4)
f’c = Value of Concrete Compressive Strength(MPa)
P = Compressive Force that occurs (N)A = Test Surface Area (mm2)Fig. 2 Supporting Equipment
METHODOLOGY
In order to get the quality of the uniformity of theconcrete according to what is required, theimplementation of concrete making must be done
well and in accordance with the standard code
procedures. Elaborate on test method used. The test
results are implemented into statistical formulations
with linear regression formulas. The stages in thedesign are: Analysis of fine aggregate and coarse
aggregate, examination of specific gravity andabsorption of fine aggregate and coarse aggregate,
examination of aggregate content weight, andcompressive strength testing on concrete samples andchecking linear regression formulations.

MATERIALSTEST RESULT AND DISCUSSION
Sieve analysis is a grouping of large items ofcoarse aggregate analysis and fine aggregate into acomposite composition that is reviewed based on thefilter.
The goal of sieve analysis are :a. To obtain concrete that easy to be worked and has
a high level of workability.
b. To obtain economical price of concrete and highdurability.
c. To obtain a solid concrete.
d. To obtain a gradation limit from aggregate
e. To obtain a mix composition of coarse and fineaggregate analysis in the ideal form.
The mixed aggregate is a comparison between
fine aggregate and coarse aggregate in theFig. 1 Mix Design Labolatory
In the laboratory test the sample used are :- Fine Aggregates (Bangka Sand)- Coarse Aggregates- Cement- WaterLaboratory supporting equipment for the sample
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SEE - Bangkok, Thailand, Nov.11-13, 2019

manufacture of concrete in both light and structuralconcrete. The purpose of adding the aggregate of thismixture is to compare the theoretical results of theplanned concrete mixture using a linear regression
formulation to obtain fine modulus.
Fine modulus is a value that is used to show thesmoothness and roughness of the aggregate items thatare left / held above the sieve set. The greater thevalue of fine modulus, the greater the aggregate
items. The following are the results of the STT PLN
laboratory test :

2.4

85

100

98.95

.2

75

100

94.35

0.6

60

79

67.85

0.3

12

40

12.7

0.15

0

10

0

pan

0

0

0

Table 1 Fine Aggregate Data with Bangka Sand
Sieve

Upper Side

9.6

100

Lower
Side
100

4.8

90

100

Result100
99.7
Fig. 3 Analysis of Linear Regression
The strength of the relationship between
variables x and y is measured by the correlation
coefficient. Correlation coefficient values are in
the range -1 hingga 1 (-1≤ r ≤ 1) . When thecoefficient is -1 or 1, then the data is said that therelationship between variables is perfect where
events in variable y can be explained or predictedby variable x without errors.

Table 2 Percentage Cummulative

Percentage Cummulative (%)
Particle size
(mm)

a
38
19
9.6
4.8
2.4
1.2
0.6
0.3
0.15

CoarseAggregates
(K)

Fine
Aggregates(P)

1,5 x K

1xP

d+ef/(P+K)

b
100
53.14
2.64
1.38
0
0
0
0
0

c
100
100
100
99
96.4
83
40.6
11.2
1

d
150
79.71
3.96
2.07
0
0
0
0
0

e
100
100
100
99
96.4
83
40.6
11.2
1

f
250
179.71103.96101.07
96.4
83
40.6
11.2
1

g
100
72
42
40
39
33
16
4
0

441

Specifications of Mixed
Aggregate Gradation Maximum
Grain Size 40 mm

Curve 1
100
74
47
28
18
10
6
4
0

Curve 2
100
86
70
52
40
31
21
11
1

Curve 3
100
93
82
70
57
46
32
19
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SEE - Bangkok, Thailand, Nov.11-13, 2019

RH 1
RH 2
RH 3
RH 1
RH 2
RH 3

21

28

17622.5
17622.5
17622.5
17622.5
17622.5

230
240
250
260
270

13.051
13.61914.18614.75415.321

17622.5280

15.889The magnitude of the correlation coefficient canbe determined based on the distribution of thecoordinates of the x and y variables. If the distributionof points is in a perfectly straight line, it can be said
that the correlation value is 1 or -1 (positive andnegative values depend on the direction of the
distribution of points). Through correlation analysis,
it can be informed that X and Y are closely related

Fig. 4 Mixed Aggregate Gradation
Calculations are carried out statistically to obtain
the amount or ∑ of each calculation. The amount ofeach calculation data above will be used in thecalculation of fine modulus on sand and gravel, theresults of the fine modulus obtained must be inaccordance with SNI standards. Where SNI
requirements for fine modulus of sand are 1.5 - 3.8
and fine aggregate modulus is 6.5 - 7.5. From Fig. 4
above obtained in the calculation in accordance withthe standard. So the fine modulus of the mixture andthe results of the ratio of the percentage of fineaggregate: coarse aggregate = 60%: 40%. The
specification data is based on SNI provisions so thatdata for curve 1, curve 2 and curve 3 are obtained.
From Fig.4 shows that the aggregate gradation
combined for the maximum grain of data obtained isthe amount of fine aggregate (sand) and coarse
aggregate of 40mm, so that the curve obtained has
met the standard. From the calculation of the datausing a linear regression formula, which is throughthe set collected data which is illustrated through thescatterplot [5] to get results that are more accurate andin accordance with the results, namely R2 = 0.8987.

ANALYSIS
Gradation Analysis of Fine Aggregate
The fine aggregate (sand) used in this study isbangka sand, in general the quality of bangka sandhas fulfilled the requirements to be used as building
material. However, the testing phase needs to be
carried out before it is used for concrete mixture. The
following is the result of a sand inspection carried out
in a concrete technology laboratory.

Table 3 . Compressive Strength Test Results

Test
Object(code)
RH 1
RH 2
RH 3
RH 1
RH 2
RH 3
RH 1
RH 2
RH 3

Age
(Days)

3

7

14

CrossSectional
Area
(mm)

Load
(kN)

Compressive
Strength(Mpa)

17622.5
17622.5
17622.5
17622.5
17622.5
17622.5
17622.5
17622.5
17622.5

150
130
140
170
175
160
200
210
220

8.512
7.377
7.944
9.647
9.930
9.079
11.34911.91712.484

Fig. 5 Result of Sand Gradation
In fine aggregate grading testing using a set ofsieves from sieves with particle size 9.6 mm indiameter, 4.8 mm, 2.4 mm, 1.2 mm, 0.6 mm, 0.3 mm,
0.15 mm. The sieve with the largest diameter particle
size is placed at the top then the smallest diameter
sieve is placed at the bottom. After that, the sand issieve using a sieve shaker and the sieve is weighed .

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 6 Fine Aggregate Gradation Analysis
Modulus of Sand Fineness =𝑻𝒐𝒕𝒂𝒍 % 𝑪𝒖𝒎𝒖𝒍𝒂𝒕𝒊𝒗𝒆 𝑳𝒆𝒇𝒕 𝑾𝒆𝒊𝒈𝒉𝒕𝟏𝟎𝟎%

To find out the zone and category of sand types,
it can be seen in the table below :Table 3 Limits and Results of Test
Gradations[5]Fig. 7 Coarse Aggregate Gradation Results

Sand

Coarse aggregate in the form of gravel as shownin Fig. 7 is an aggregate that all the grains are left
above%the 4.8mm sieve. From the results of the coarse
aggregate lab test calculations, the graph calculations
Cummulativeare Fine
as follows :Aggregate(Bangka Sand)100% fine aggregate through a sieve
Numberof Sieve(mm)

9.6

Coarse(Zone
I)

RatherCoarse(Zone
II)

Rather
Fine
(Zone
III)

100

100
90 10085 10075 10060 - 79
12 40
0 - 104.8

100
90 10090 - 100

2.4

60 - 95

75 - 1001.2
0.6

30 - 70
15 - 34

55 - 90
35 - 59

0.3
0.15

5- 20
0 - 108 - 300 - 10

Fine
(Zone
IV)
100
95 - 100

100

95 - 100

99

90 - 100
80 - 100

96.4
83

15 - 50
0 - 15

40.6
11.2
Fig. 8 Coarse Aggregate Gradation Analysis

To find out the zone and type of sand category, it
can be seen in the table above:

Characterization of quality of materials is
important to ensure good use of resources fromenvironmental and economic perspectives. Particle
size distribution of materials is one of the widely used
tests in geotechnical engineering to evaluate qualityof materials. Sieve analysis test has been used as themain method to determine particle size distribution of
granular materials including coarse materials formany decades[6]. Based on the results (fig.8) of thegravel gradation analysis test shows that it hasvarying size shapes with 38.10 mm filter size. The
result for fineness modulus obtained is 7.62 where thevalue of the modulus of fineness meets therequirements according to SNI 03-6820-2002[7]is thevalue of the modulus of fineness is not more than 8%with size around 5-8 mm and this coarse aggregate

Based on the results of testing that Bangka sand isincluded in the fine sand category (Zone I) with amodulus of sand fineness obtained at 3.232 Thisfineness modulus fulfills the requirements specified
in SNI 03-6820-2002, namely with the modulus ofsmoothness of sand 2 - 3 and Bangka sand can be usedas the main material of concrete mixture.
Gradation Analysis of Coarse Aggregate

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SEE - Bangkok, Thailand, Nov.11-13, 2019can be used as the main material for concrete mixture.

and Y variable can be said to have a positive
relationship if the increase in X variable is followedby an increase in Y variable , while the X variable
and Y variable can be said to have a negative
relationship if for every increase in X variable
followed by a decrease in Y variable.
The Pearson values correlation (r) can describe
the extent to which the data cluster around a straightline. Therefore from Figure 9 scatterplot correlation
follows the line with a positive slope, it can be said
that there is a high positive correlation between thetwo variables X and Y

Concrete Compressive Strength Analysis

CONCLUSIONS

From the results of data processing forlaboratory testing results is aggregate gradation
affects the nature of concrete produced by mixing
coarse aggregates and fine aggregates should take
into account their gradations. Therefore:
1. With the use of mixed aggregate comparisons,the quality of concrete is guaranteed.
2. Fine modulus of the grains obtained is inaccordance with SNI, the result is fine aggregate
modulus is 3.232 and coarse aggregate modulus
is 7.62
3. Bangka sand is included in zone I (coarse) andcoarse aggregate is passed requirement
according to SNI 03-6821-2002.
4. From calculations for the results of Linear
Regression R2 for fine aggregate = 0.9441, forcoarse aggregate = 0.9581 and for compressive
strength = 0.9627 it means that it has a strong
relationship for each variable and can be
accounted for the implementation of concrete forgood quality.

Fig. 9 Compressive Strength
Simple linear regression is a linear relationshipbetween one independent variable (X) with adependent variable (Y). These analyzes are used todetermine the direction of the relationship between
the independent variable and dependent whether
positive or negative and to predict the value of thedependent variable if the value of the independent
variable increases or decreases in value[8][9]. Data
used is usually interval scale. Regression analysis
aims to explain or model the relationships between
variables.
Table 4. The value of the Linear Regression
correlation coefficient according to Gulford [10]CorrelationNo.
Coefficient
Notes
ValuesVery small correlation can beconsidered no correlation
1
0 - < 0.2

RECOMENDATION

It is better to do with a sample with morevariation so that it ensures whether the application of
linear regression can be applied.

2≥0.2 - < 0.4

Small relationship / not close3≥ 0.4 - < 0.7

Moderate / Medium relationship4≥ 0.7 - < 0.9

Close relationship5≥ 0.9 - < 1Very close relationship

ACKNOWLEDGMENTS

The author would like to thanks the Ministry of
Research and Technology of Higher Education forproviding funding grants for 2019 based on SK :7/E/KPT/2019 and 225/SP2H/LT/DRPM/2019;
9/AKM/PNT/2019. Chairman of the STT PLN with
SK: 0168.SK/2/A0/2019 and Head of LPPM with No.
Contract; 012/1 / A01 / 2019 concerning Dikti
Research Beginner Lecturer Grants.

Correlation analysis aims to determine whether
there is a relationship between variables and thecloseness of the relationship. Correlation is a numberthat shows the direction and strength of therelationship between the variables studied. The
direction of the relationship between variables can bepositive and negative and 0 (zero) if there is no
relationship at all. The strength of the relationshipbetween variables can be expressed by the magnitudeof the correlation coefficient value on the linear
function. From Fig. 3 Fig.4, Fig.6, Fig.8 (regression
results) can be concluded that the two X variables

REFERENCES[1] R. Hidayawanti, S. Legino, and D. Harjanto,“Optimizing the Utilization Cement Slag and Fly

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Ash of Concrete Quality,” in The IIERInternational Conference, 2018, no. March, pp.
14–18.
[2] R. Hidayawanti, S. Legino, I. Sangadji, R. Panca,
and A. Widodo, “The Efficiency Of Fly Ash And
Cement Slag To Development Building,”
Geomate, vol. 16, no. 57, pp. 95–100, 2019.
[3] M. Velay-Lizancos, I. Martinez-Lage, M. Azenha,
J. Granja, and P. Vazquez-Burgo, “Concrete withfine and coarse recycled aggregates: E-modulus
evolution, compressive strength and nondestructive testing at early ages,” Constr. Build.
Mater., vol. 193, pp. 323–331, 2018.
[4] J. Sun, J. Zhang, Y. Gu, Y. Huang, Y. Sun, and G.
Ma, “Prediction of permeability and unconfinedcompressive strength of pervious concrete using
evolved support vector regression,” Constr. Build.
Mater., vol. 207, pp. 440–449, 2019.
[5] National Standard Indonesia, “Fine Aggregate
Analysis Test Method SNI 03-1968-1990,” pp. 1–
17, 1990.

[6] G. H. A. J. J. Kumara, K. Hayano, and K.
Ogiwara, “Image analysis techniques on
evaluation of particle size distribution of gravel,”Int. J. GEOMATE, vol. 3, no. 1, pp. 290–297,
2012.
[7] SNI 7656: 2012, “Mix Design - SNI 7656 - 2012,”
vol. 2012, pp. 2–7, 2016.
[8] S. Palaniraj, “Evaluation of Compressive Strengthof Mineral Admixed Recycled Aggregate
Evaluation of Compressive Strength of Mineral
Admixed Recycled Aggregate Concrete Using
Multiple Linear Regression Model,” no. June,
2018.
[9] R. Neves, A. Silva, J. De Brito, and R. V Silva,“Statistical modelling of the resistance to chloride
penetration in concrete with recycled aggregates,”
Constr. Build. Mater., vol. 182, pp. 550–560,
2018.
[10] B. W. Silverman, Generalized Linear Models,
2nd ed. London, 2018.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DEVELOPMENT OF A MICROBIAL-BASED GROUTING MATERIAL
WITH CALCIUM CARBONATE PRECIPITATESYoko Sakakihara1, Yoshihiro Kabeyama2 and Shinichiro Okazaki3
1,2
Graduate school of engineering, Kagawa University, Japan;
3
Faculty of engineering and design, Kagawa University, Japan

ABSTRACT
Bio-concrete, which is a concrete with self-repair capability provided by microorganisms, is attracting muchattention. In recent years, crack repair grouts based on microbial metabolism have been studied. Because suchgrouts are flowable aqueous solutions, they differ greatly from grouts based on inorganic or organic compounds
and are expected to penetrate into cracks in concrete by capillary action. Therefore, press fitting of bio-grouts is
unnecessary. As an additional advantage, these grouts do not impose a load on the environment. In this study, we
performed benchtop experiments using conical tubes with a large amount of calcium source. The experimental
results show that the addition of a large amount of calcium shows no substantial change in the amount ofprecipitate. In addition, the amount of precipitated crystals did not substantially differ even when the type of
calcium salt was varied. Prolonging the standing time was led to crystal growth, and the amount of precipitatesobtained increased. As a result of scanning electron microscopy observations of the crystals obtained under eachgrowth condition, we confirmed that many yeast cells were mixed in the crystals. However, difference wasobserved in the crystal structure when calcium salt was varied. Moreover, Calcium carbonate formation wasobserved on concrete as a preliminary experiment for the crack repair of concrete. Crystals were generated evenat room temperature, and better results were obtained when the temperature was set to 40 °C.
Keywords: Grout, Calcium carbonate, Calcite, Microbial metabolism

INTRODUCTION

Outline of Experiments

Concrete is designed to undergo cracking, andsome cracking is considered acceptable to someextent. However, cracking of concrete enables waterand carbon dioxide to flow in at the gaps; theconcrete becomes carbonated, and the cracks
provide channels for the penetration of chloride ionsthat corrode rebar.
Grouting has been investigated as a crack repair
method; however, concerns have arisen about thatenvironmental load imposed by grouting because of
the chemical agents involved. Odor at the time of
construction has also been mentioned as a problem.
Such concerns have spurred recent research into
biomaterials, including bio-grouts.
Last year, we examined the formulation
conditions of bio-grout using the simulation
software PHREEQC, which can be used to carry out
geoscience calculations. Recently, on the basis of
our previous results, we have conducted experiments
thatconsiderbiologicalconditions
andcrystallographic phenomena. [1] - [7]The experimental conditions were assembled
with reference to the conditions selected from theprevious research and the results obtained bysimulation last year [1], [7]. Table 1 shows thecompounding conditions used in our previous study.
Table 1 Formulation of bio-grout as reference.
Materials
Conc.
Yeast
6.0 g/L
D-Glucose
0.40 M
Calcium lactate
0.20 M
Tris(hydroxymethyl)
Buffer
0.75 M
aminomethane
Note: The pH was set to 9.0, and the experimental
temperature was 20 °C.
MicrobeNutrient
Calcium

The simulation results indicated that the
precipitation amount of calcium carbonate can beincreased by setting the temperature high andpreventing a decrease in pH. Yeast is an organism
and, as such, has an optimum temperature for
growth. Yeast is killed at temperatures greater than
40 °C; thus, the setpoint temperature in theseexperiments was 40 °C, and a comparative
experiment was performed at room temperature.
We speculated that the amount of precipitated

IN VITRO EXPERIMENTS
In our recent work, the amount of calcium
carbonate generated from bio-grout was examined ina conical tube, and the results were discussed.
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SEE-Bangkok, Thailand, Nov.11-13, 2019calcium carbonate would increase with increasing
amount of calcium salt. We therefore conducted
experiments in which the concentration of thecalcium salt was varied. In addition, we investigatedwhether the results differ depending on the calcium
salt used in the bio-grout. Table 2 shows theexperimental materials. The experimental conditions
are summarized in Table 3.
Water (40 ml) as a solvent was placed in a 50 ml
conical tube. The buffer and calcium salt weredissolved, the pH was adjusted to 9.0, and theexperiment was started by simultaneously dissolving
glucose and dry yeast in the solution. Both solutions
were covered with silicon, leaving air holes toprevent the evaporation of water.

Fig. 1

Table 2 Proposed formulation of bio-grout.

MicrobeNutrient
Calcium
BufferMaterial
Yeast
D-Glucose
VariousTris(hydroxymethyl)aminomethane

Experimental Results

Conc.
6.0 g/L
0.4 M
Various

The experiment was conducted for 3 days. The
pH change was confirmed every 24 h, and theamount of precipitates was measured. Roomtemperature was between 24 and 28 °C throughout
the experiment.

0.75 M

Table 3 Different experimental conditions using thecomponents from Table 2.

Case 1Case 2
Case 3
Case 4
Case 5

Calcium salt
Calcium acetate
Calcium acetate
Calcium acetate
Calcium lactate
Calcium ascorbate

Microscopic image (magnification: 1600×)
corresponding to Case 4 with calcium
lactate as the calcium salt.

pH change
The decrease in pH was greater for the samples
maintained at 40 °C. We attributed this lower pH to
the enhanced activity of the yeast at the higher
temperature, which caused it to breathe more anddischarge more carbon dioxide than the yeast atroom temperature.

Conc.
0.2 M
0.3 M
0.4 M
0.2 M
0.2 M

Measurement of precipitation amountExperimental Procedure
The precipitate generated in the experiment wascollected by vacuum filtration using filter paper (No.
5C). The amounts of precipitates obtained from thesamples maintained at room temperature and fromthose maintained at 40 °C are shown in Fig. 2 andFig. 3, respectively. Even when no crystal wasobserved on the filter paper, approximately 0.1 g ofmaterial was recovered. We speculated thatapproximately 0.1 g of yeast remained on the filter
paper.
In general, the results of this study show thatthe addition of a large amount of calcium salt did notlead to a large amount of precipitate. This outcome
is attributable to two possible causes. First, theexperimental period may have been too short forappreciable precipitate growth. Second, theconcentration and, therefore, the osmotic pressure
may have been too high for the yeast to survive.
These possibilities are currently being investigatedfurther.
When calcium ascorbate was added, the amountTo observe the progress of the experiment, weobserved the aqueous solution with a microscope on
the second day after the start of the experiment toobserve whether calcium carbonate crystals had
formed.
Microscopic observations
A biological microscope was used forobservations. The objective lens was 40×, theeyepiece was 10×, and the image was taken at amagnification of 4× with a digital camera attached to
the lens barrel.
An image of the aqueous solution in which
calcium lactate was used as the calcium salt isshown in Fig. 1. The small circles are yeast cells,
and the darker objects with shadows are crystals.
Although the amount of precipitates was small, they
could be observed by optical microscopy.

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SEE-Bangkok, Thailand, Nov.11-13, 2019of precipitates increased slightly. The product was
confirmed by X-ray diffraction (XRD) and scanningelectron microscopy (SEM). Then, we confirmedthat the crystals grew and the amount of precipitates
increased with increasing standing time.

XRD analysis
The crystal structure of the precipitate obtainedin the experiment was analyzed by XRD. The
results, presented in Fig. 4, show that the
precipitated crystals are mainly composed of calcite.
In Cases 1-3 and 4, in addition to calcite, vaterite
was detected. In Case 5 to which calcium ascorbate
was added, only calcite was precipitated.

Case 1

0.7

Case 2
0.6

Case 3
Case 4(a)
8000

Case 56000

0.4

countsPrecipitate (g)

0.5

0.3

4000
2000

0.2

0
20

0.1

40

60

(b)

3000

0
24

48

72

Fig. 2

countsTime (hour)
Amount of precipitates collected fromsamples maintained at room temperature.

2000
1000
0

Case 1
0.7

Case 2

40

50

60

20

30

40
θ - 2θ

50

60

Case 4

countsCase 50.5

Precipitate (g)

30

6000

Case 3

0.6

20
(c)

0.4

4000
2000
0

0.3
0.2

Fig. 40.1

XRD patterns: (a) Calcite; (b) Case 1: 0.2M
Calcium acetate; (c) Case 5: 0.2M Calcium
ascorbate

0
24

48

72

SEM analysis

Time (hour)Fig. 3The crystals obtained under each condition wereobserved by FESEM, and SEM. The images
confirmed that many yeast cells were mixed witheach crystal. The crystals themselves were spherical.
It is speculated that this is because the crystal takes
on a vaterite structure at the formation stage. The
SEM images of the precipitates corresponding toCases 1 and 3, where numerous crystals wereobtained, are shown in Fig. 5.

Amount of precipitates collected from thesamples placed in a constant-temperaturebath at 40 °C.

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SEE-Bangkok, Thailand, Nov.11-13, 2019

Although experiments were conducted in two
systems (one at room temperature and the other in aconstant-temperature bath at 40 °C) and the amounts
of precipitates differed, no significant difference wasfound in the crystal structures of the precipitates.
In Case 5 to which calcium ascorbate was added,

a peak of only calcite was observed in the XRD,
however aragonite was also confirmed in the SEM
image. But, the amount is very small. From the SEM
image, it was found that many cavities were found in
the crystal, and it took longer standing times forcrystal growth.

(a)

(b)

(c)

(d)

Fig. 5FESEM, and SEM micrographs: (a) Case 1, room temperature (5000×); (b) Case 1, 40°C (5000×); (c)Case 3, 40 °C (2500×);(d) Case 5, 40 °C (4500×).

ADAPTATION TO CONCRETE

Preliminary Experiment

The optimum environment for the yeast strain
used in this work is approximately pH 4-6; thus, theyeast prefers slightly acidic conditions [8].
However, concrete is alkaline, with a pH ofapproximately 11. Bacteria that grow under basic
conditions are usually selected for use in bioconcrete and bio-grout.
Our rationale for selecting yeast is that they are
inexpensive, easily obtainable anywhere in theworld, and ubiquitous.

Before repairing cracks using bio-grout, tounderstand the growth conditions of the yeast andthe generation of crystals, we conducted
experiments on the concrete. A silicon was placed
as a wall on top of a 10 cm × 10 cm mortar
specimen, and the grout was poured into it. The
selected grout was that of Case 1.
After the start of the experiment, only water wasadded as necessary to prevent dehydration because
an aqueous solution placed on the concrete would
be lost immediately by evaporation and absorption.
The concreate was covered with a wrap to prevent
excessive drying.

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SEE-Bangkok, Thailand, Nov.11-13, 2019

Two specimens were prepared. One was placedindoors at room temperature, and the other wasplaced in a thermostatic chamber at 40 °C.

Microscopy

Five days after the start of the experiment, thesolution was removed and the concrete surface wasobserved.

A microscope was used for the observation; theimages were collected at approximately 200×
magnification.
Pure calcium carbonate crystals appeared on theconcrete surface in the specimen maintained atroom temperature (Fig. 6 (a)). These crystals wereobserved over the whole concrete surface and in theholes.
For the sample maintained at 40 °C, the crystals
apparently aggregated into large flocks (Fig. 6 (b)).
An image of the side not in contact with theaqueous solution is shown in Fig. 6 (c). This image
was collected by expanding the innumerable small
holes in the concrete surface; however, the interiorof the holes was empty, and the surface was flat.
For the sample maintained at 40 °C, the locations of
the crystals on the concrete surface were difficult todetermine; however, the crystals clearly grew large,
as revealed by observation of the interior of theholes (Fig. 6 (d)).

(a)

(b)

(c)

(d)

Fig. 6Microscopic images (200×): (a) crystals generated on the concrete surface at room temperature; (b)crystals generated on the concrete surface at 40 °C; (c) a hole in an untested concrete surface; and (d)crystals formed in the hole at 40 °C.

Experiment Result Day 2
Crystal growth was checked 2 days after the startof the experiment. A biological microscope wasused for the observation; the magnification was
1600×.
As a result of microscopic observation, crystals
were suspended on the water surface of a solution
placed in concrete installed at room temperature.
The solution immediately above the concrete wasalso collected and observed. However, mostly yeast
cells were observed, with very few crystals.
Experimental Result 5th Day

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SEE-Bangkok, Thailand, Nov.11-13, 2019

Laser Raman spectroscopy

ACKNOWLEDGMENTS

When the crystal which precipitated on concrete
was analyzed by laser Raman spectroscopy, thepeak of calcium carbonate was confirmed. The
image of the Raman spectrum is shown in the Fig. 7.

We appreciate the support for this research
provided by the JSPS Grant-In-Aid for Scientific
Research (B) task number 15h04025.
REFERENCES

Intensity ( arbitrary units )

3000

2000
1500
1000
500
0
200

Fig. 7[1] Putri P. Y., Kawai K., Ujike I., and Yamamoto
S., Effect of temperature on precipitation rateof calcium carbonate produced through themicrobial metabolic process of bio materials,
Civil Engineering Dimension, 18(2), 2016, pp.
103-108[2] 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[3] Kawasaki S., Muaro A., Hiroyoshi N.,
Taunekawa M., and Kaneko K., Fundamental
study on novel grout cementing due tomicrobial metabolism, Journal of Japan Societyof Engineering Geology, 47(1), 2006, pp. 2-12
[4] Kubo K., Okazaki S., and Ujike I.,
Development of microbial metabolic processes
to repair concrete joint leakage, Advanced
Material Research, 845, 2013, pp. 158-162[5] Ujike I., Kubo F., Kawai K., and Okazaki S.,
Influencing factors affecting microbial
metabolic processes of biomaterials used forleakage repairs, Concrete Solutions, 2014, pp.
127-133[6] Akiyama M. and Kawasaki S., Application ofnumerical simulation of microbial reaction tobiogrout with ureolytic bacteria, Japanese
Geotechnical Journal, 12(3), 2017, pp. 337-349[7] Sakakihara Y., and Okazaki S., Developmentof a crack repair method using yeast-induced
calcium carbonate precipitation, International
Journal of GEOMATE, May 2019, Vol.16,
Issue 57, pp.89 – 94.
[8] Watanabe S., Shinohara N., Kanai S. andIizuka Y., Properties of natural yeast isolated
from raisin as a baker's yeast, Bulletin of
Seitoku University Junior College of Nutrition,
2005, Vol.36, pp.1-6

2500

700
peak shift ( cm-1 )1200

Raman spectrum of precipitates

CONCLUSIONS
In in vitro experiments, we expected that alarge amount of calcium carbonate could beobtained by adding a large amount of calcium salt;
however, no change was observed. Experiments
confirmed that the amount of calcium carbonate
obtained was almost the same irrespective of thetype of calcium salt. Prolonging the standing time
led to crystal growth, and the amount of precipitates
increased. SEM observations of the crystals
obtained under each condition confirmed that many
yeast cells were mixed with the crystals. Difference
was observed in the crystal structure when calcium
salt was varied.
A preliminary experiment was carried out toadapt the bio-grout to concrete, and the process wasobserved via optical microscopy, and theprecipitates were observed via microscope and laser
Raman spectrophotometer. The precipitating
calcium carbonate on the concrete surface could be
confirmed. Crystals were generated even at room
temperature, and better results were obtained inexperiments conducted at 40 °C.
In the future, we will conduct more practicalexperiments for crack repair, repeat follow-up
observations, and further consider optimal
combinations of grout materials..

451

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov. 11-13, 2019, ISBN: 978-4-909106032 C3051

EVALUATION OF LARGE DIAMETER JET GROUTING TECHNIQUEUSED FOR TUNNEL CONSTRUCTION IN BANGKOKKuo Chieh Chao, Ph.D., P.E.1, Sasirada Seepim2, Ricky K. N. Wong3, Takeshi Iwakubo4, and Morris Wang5
1, 2
Geotechnical and Earth Resources Engineering, Asian Institute of Technology, Pathumthani, Thailand
3, 4Sanshin Construction (Thailand) Co., Ltd., Bangkok, Thailand
5
ISEKI Engineering (Thailand) Co., Ltd., Bangkok, Thailand

ABSTRACTThis paper presents the use of a large diameter jet grouting technique for installation of jet grout piles for 2
different tunnel projects in Bangkok. The first project where the large diameter jet grouting technique was used is
the MRTA Blue Line Extension Project in Bangkok, Thailand. The jet grouted piles were used to seal off the baseof excavation at the ITD TBM retrieval shaft from the high-water pressure. The second project where the large
diameter jet grouting technique was used is the MRTA Orange Line-East Project in Bangkok, Thailand. Preceding
beams with a thickness of 3.0 m were designed and constructed to reduce the overstress that could happen to thepile foundation of the adjacent Srirat Expressway. The procedure and design parameters of the large diameter jet
grouting technique are provided in the paper. The required design parameters for the grouted materials wereverified by conducting laboratory testing of coring samples obtained at the site. Moreover, the required design
parameters were further verified by conducting a pumping test and an electrical resistivity test at the site. The
results of the laboratory and field tests indicate that the design requirements of the treated materials can be met
effectively using the large diameter jet grouting technique in Bangkok. Furthermore, the construction time and theassociated cost were reduced using the large diameter jet grouting technique.
Keywords: jet grouting; soil improvement; TBM; underground structure; electrical resistivity; case study
INTRODUCTION

space and sensitive ground conditions in Bangkok.
The advantages of using the large diameter jet
grouted technique instead of the traditional method
include to minimize the required number of boreholes,
to save drilling time, and to provide higher strengthand lower permeability of the treated materials.
A large diameter jet grouting technique called
Rapid-Jet Method was developed in the jet grouting
industry within the last decade. The Rapid-Jet
Method utilizes high-pressured grout slurry to erode
and mix the in-situ soil to form soil-cement mixture
columns with a diameter up to approximately 3.5 m.
A double-tube grouting system with two nozzles on
the opposite side of the jetting device can carry out
efficient grouting with large-diameter and high-speed
construction. Fig. 1 shows the sketch of the large
diameter jet grouting system.
This paper presents the use of the large diameterjet grouting technique for installation of jet grout piles
for two different tunnel projects in Bangkok. The
first project that the large diameter jet grouting
technique was used is the MRTA Blue Line
Extension Project in Bangkok, Thailand. The jet
grouted piles were used to seal off the base of an
exaction of the ITD TBM retrieval shaft from thehigh-water pressure. The second project that the large
diameter jet grouting technique was used is the
MRTA Orange Line-East Project in Bangkok,
Thailand. Jet grouted preceding beams with a

Jet grouting technique has been widely used forsoft ground improvement in various undergroundprojects to form water-proof base seals and buried
grout supports for deep excavations and tunnel
construction. The process of jet grouting technique isrelating high-pressure erosion, grout injection andmixing of in-situ soil, resulting in both replacement
and reduction of the soil and the construction of atreated soil mass which in most illustrations has theform of a jet grout column. Over the past few decades,
significant progress has been made in the jet grouting
technology, especially in increasing the diameter ofthe jet grout column and improving the jet grouting
equipment (Yoshida, 2010; Burke, 2012, and Chenget al., 2017). The diameter of the jet grout column iscontrolled by the grouting parameters including grout
slurry selection, jet grouting pressure, flow rate of a
jetting fluid, jetting time, jet nozzle size, grouting
layout, withdraw rate, etc. The diameter of the jet
grouting columns constructed in Bangkok by local
contractors is approximately 0.8 to 1.2 m.
Constructing jet grouting columns with a larger
diameter has certain advantages, especially for the
ground improvement work in a limited construction
452

SEE - Bangkok, Thailand, Nov.11-13, 2019

thickness of 3.0 m were designed to reduce theoverstress that could happen to the pile foundation of
the adjacent Srirat Expressway.

Fig. 1

operatingParameters
Jet grouting pressure
Grout flow rate
Air pressure
Air flow rate
Withdrawal rate
Rotation rate
Mix proportion

Unit
MPa
Liter/minkPa
m3/min
min/m
rpm
kg/m3

20
60
700
3
18
10
700

Table 2 presents the common jet grouting
parameters that are used in Thailand. For comparison
purposes, existing grouting methods that are used in
the industry within the region are also included inTable 2. Furthermore, Table 2 shows the grouting
parameters for the Rapid-Jet Method that were used
for both of the MRTA projects. Table 2 indicates that,in general, the jet grouting practice in Thailand uses asingle-tube grouting system with one nozzle. The
diameter of a grout pile can be only installed up to 1.2
m. For the JSG and CJG methods, the diameter of agrout pile can be installed up to 2 m, whereas thediameter of a grout pile for the RJP method can beconstructed up to 3 m. Similar to the JSG method, theRapid-Jet Method uses a double-tube grouting systemwith two nozzles on the opposite side of the monitor.
The latter also uses air and jet stream to cut and mix
the in-situ soil with grout. The grouting parametersthat are used are as follows: grouting pressure = 33 ~37 MPa, grouting rate = 180 or 360 L/min, rod
rotation = 2 ~ 5 rpm, and withdrawal rate = 10 ~ 18
min/m. Using these parameters, the grouting capacity
can be increased to 35.3 m3/hr. So, it can rapidly
install a grout pile with a diameter up to 2.5 ~ 3.5 m
at a depth up to 50 m below the ground surface.

Sketch of large diameter jet grouting
systemThe design parameters and procedure of the large
diameter jet grouting technique were provided in thepaper. The required design parameters for the
grouted materials were verified by conducting
laboratory testing of coring samples obtained at thesite. Moreover, the required design parameters were
further verified by conducting a pumping test and anelectrical resistivity test at the site. The results of thelaboratory tests and the field tests were discussed in
the following sections.
COMPARISONOF
JETPRACTICE IN THE INDUSTRY

Table 1 The optimum jet grouting
parameters (Jaritngam, 2003)

GROUTING

Jet grouting technique has been used for soil
improvement method for many projects in Thailand.
The most well-known project for using jet grouting as
the ground improvement technique is theSuvarnabhumi International Airport (SBIA) Drainage
Project. The construction of jet grouting at this project
has a total length of about 5 kilometers and include
85,300 jet grouted piles with a diameter of 0.8 m. The
single tube jet grouting system was used for the
project.
Another example project of using jet grouting for
ground improvement is the Pak Phanang Diversion
Dam Project located in Nakornsrithammarat,
Thailand (Jaritngam, 2003). Jet grouting piles wereused for the project to minimize settlement andincrease the stability of the dam. The double tube
system was adopted to install the 1.6-m diameter jet
grouted piles with a jet grouted volume of
approximately 144,600 m3. The jet grouting
parameters for this project are presented in Table 1.

APPLICATIONS OF LARGE DIAMETER JET
GROUTING TECHNIQUE
MRTA Blue Line Extension Project
Site conditions
For the MRTA Blue Line Extension Project, theIDT TBM retrieval shaft is located at the Northernend of the Sanam Chai (BS12) Station, which is theextension of Chaloem Ratchamongkhon (or the Blue
Line) of the Bangkok MRT. The Blue Line Extension
Project is 16.51 m long, 9.60 m wide, and 32.5 m
deep. The subsoil conditions at the site are shown in
Fig. 2. The groundwater level was measured at a
depth of 10 m below the ground surface. As indicatedin Fig. 2, the site has mostly soft clay to stiff clay andsand interlayers. A soft clay layer is located within the453

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Comparison of different jet grouting methods (modified from Yong et al., 1996; Yoshida et al., 1996)
MethodItem

Effective diameter
Sand
Geologicalcondition
Clay
Sand
Designstrength
Clay
Drill hole diameter

CommonGroutParametersin Thailand

Jet Special
Grout(JSG method)

Column Jet
Grout(CJG method)Rodin Jet Pile
(RJP method)

Rapid-Jet
Method𝝓 𝟎. 𝟖 ~ 𝟏. 𝟐 𝒎

 1.0 ~ 2.0 m

 1.2 ~ 2.0 m

 2.0 ~ 3.0 m

𝝓 𝟐. 𝟓 ~ 𝟑. 𝟓 𝒎

SPT-N  100

SPT-N  50

SPT-N  200

SPT-N  100

SPT-N  100

SPT-N  5

SPT-N  4

SPT-N  9

SPT-N  5

SPT-N  5

2 ~ 3 MPa

2 ~ 3 MPa

2 ~ 3 MPa

2 ~ 3 MPa

2 ~ 3 MPa

0.3 ~1 MPa－

0.3 ~1 MPa

0.3 ~1 MPa

0.3 ~1 MPa

0.3 ~1 MPa

0.12 ~ 0.15 m

0.14 ~ 0.25 m

0.14 ~ 0.25 m

0.14 ~ 0.25 m

single-tube

0.06 m(double-tube)

0.06 m or 0.09 m(triple-tube)

0.09 m(triple-tube)

0.06 m or 0.09 m(double-tube)

1

1

2

2

2

BinderBinder

Water

Water

Binder𝟐𝟎 ~ 𝟒𝟎 𝑴𝑷𝒂

𝟏𝟖 ~ 𝟐𝟐 𝑴𝑷𝒂

𝟑𝟓 ~ 𝟒𝟎 𝑴𝑷𝒂

𝟐𝟎 𝑴𝑷𝒂𝟑𝟎 ~ 𝟑𝟓 𝑴𝑷𝒂－

𝟔𝟎 𝑳/𝒎𝒊𝒏

𝟕𝟎 𝑳/𝒎𝒊𝒏

𝟓𝟎 𝑳/𝒎𝒊𝒏－

0.6 ~ 0.7 MPa

0.6 ~ 0.7 MPa

0.7 ~1.05 MPa

0.7 ~1.05 MPa－－

2 ~ 5 MPa

40 MPa－－－140 ~180 L / min

190 L / min－

6 - 15 rpm< 10 rpm< 6 rpm< 6 rpm

2 ~ 5 rpm

Withdrawal rate𝟑 ~ 𝟓 𝒎𝒊𝒏/𝒎

𝟏𝟔 ~ 𝟒𝟎 𝒎𝒊𝒏/𝒎

𝟏𝟔 ~ 𝟐𝟓 𝒎𝒊𝒏

𝟏𝟓 ~ 𝟐𝟎 𝒎𝒊𝒏/𝒎/𝒎

Grouting capacity
Binder consumption
Amount of sludge－－－

𝟒. 𝟎 𝒎𝟑 /𝒉𝒓

𝟏𝟏. 𝟖 𝒎𝟑 /𝒉𝒓

𝟏𝟖. 𝟓 𝒎𝟑 /𝒉𝒓

𝟑𝟓. 𝟑 𝒎𝟑 /𝒉𝒓

𝟎. 𝟗 𝒎𝟑 /𝒎𝟑

𝟎. 𝟗 𝒎𝟑 /𝒎𝟑

𝟎. 𝟔 𝒎𝟑 /𝒎𝟑

𝟎. 𝟓 𝒎𝟑 /𝒎𝟑

𝟏. 𝟑 𝒎𝟑 /𝒎𝟑

𝟏. 𝟖 𝒎𝟑 /𝒎𝟑

𝟏. 𝟎 𝒎𝟑 /𝒎𝟑

𝟎. 𝟕 𝒎𝟑 /𝒎𝟑

Drill rod diameter
Number of nozzlesusematerial
total
Jetpressuregrouting
total flow
rate
Total air pressure
totalpressure
Bindertotal flowrate
Rod rotation

Fig. 2 Soil profile and the locations of BS12 station and IDT shaft454

𝟏𝟖𝟎 or 𝟑𝟔𝟎 𝑳/ 𝒎𝒊𝒏

𝟖 ~ 𝟏𝟔 𝒎𝒊𝒏/𝒎

SEE - Bangkok, Thailand, Nov.11-13, 2019

upper 10 m. The 1st stiff clay layer is located at depthsof 10 to 25 m. The 1st sand layer is located at depthsof 25 to 35 m. The 1st sand layer has the SPT-N
values of about 20 to 35 and a fine content of ≈ 0 to
10%. The 2nd stiff clay layer is located at depths of 35
to 38 m. The 2nd stiff clay layer has the SPT-N valuesof about 20 to 60 and a fine content of approximately
70%. The 2nd sand layer is located below a depth of
38 m and is more than 20 m thick. Hence, when
excavating to the designed depth, the impermeable
2nd stiff clay layer (only 0 ~ 4 m thick) is unable toresist the artesian water pressure from the permeable
2nd sand layer and might cause the risk of uplift andpiping in the 2nd stiff clay layer (refer to Fig. 3).

Fig. 3Fig. 4

Jet grouting layout and cross section

Quality control
Four verticality tests were carried out to check theverticality. The results of the verticality tests indicatethat the verticality was less than 1/250 at a depth of
44 m. One coring test was conducted at theintersection of grout points 4, 5, and 12. The
unconfined compression strengths for the coresamples were measured to be on the average of 6 MPa,
which meets the design requirement strength of 3.0
MPa. A field pumping test was carried out, and theresults of the pumping test showed that there was nowater in the IDT shaft. The required hydraulicconductivity of the sandy layer was 5×10-5 cm/sec
after grouting. Fig. 5 shows that the base of the
excavation was in a dry condition after grouting.
Consequently, the design requirement for hydraulicconductivity was met for the MRT underground
retrieval shaft.

Construction risk of IDT shaft and the
purposed jet grouting

When excavating an extremely deep ground andthe groundwater level is relatively high, the thicknessof the impermeable layer under excavation base is the
key factor that influences the safety of construction.
In order to improve construction safety, base seal
grouting, as a compensation measure, is often applied
to increase the thickness of the impermeable layer andto improve the strength and water tightness of
excavation base. This can also reduce the upliftpressure from the artesian water.

Fig. 5

Final excavation base at a depth of 32.5 m
for IDT shaft

Jet grouting at the base of the excavation
MRTA Orange Line East ProjectJet grouting was conducted at the base of the
excavation to prevent the risk of uplift and piping inthe 2nd stiff clay layer. Fig. 4 shows the grouting planand cross-section view of the rapid-jet grouting
dimensions. A total of 30 JGP columns with adiameter of 3.2 m were installed at the site. The
grouting thickness was about 9.86 m and the depth ofdrilling was 43.81 m below the ground surface. The
grouting parameters are provided as follows: groutpressure = 35 MPa; grout flow = 360 L/min; withdraw
rate = 14 min/m; and rod rotation = 4 rpm. The watercement ratio is 758 kg (water):750 kg (cement).

Site conditions
The Pradit Manutham Station (OR15) is anunderground station along the MRTA Orange Line
East (Contract E1) Project, which consists of 3
underground stations (OR13: Thailand Cultural
Center, OR14 MRTA, and OR15: Pradit Manutham).
The portion of this project is approximately 6.3 km in
length. The area under consideration lies within
relatively flat terrain where the ground level varies
from 100.0 to 102.0 mRL. The location of the MRTA
Orange Line East Project is presented in Fig. 6. Alongthe MRTA Orange Line East Project, the OR15
Station is considered to have a high-risk potential to455

SEE - Bangkok, Thailand, Nov.11-13, 2019the nearby Srirat Expressway. Therefore, the OR15
Station was chosen for the jet grouting study. The
plan view of the OR15 Station and the Srirat
expressway is presented in Fig. 7.

Fig. 6

stationJet grouting for preceding beams
The Rapid-Jet Method was used to form thepreceding beams at the site. Fig. 9 shows the design
plan of the jet grouted preceding beam. Fig. 9
indicates that the designed width of the preceding
beam within the grout treated zone ranges from 5 to 6
m. The grouting parameters used at the site areprovided as follows: grouting pressure = 30 ~ 34 MPa,
grouting rate = 360 L/min, rod rotation = 4 rpm, andwithdrawal rate = 10 ~ 12 min/m. The grouting
parameters allowed the contractor to rapidly installgrouting piles with a diameter up to approximately
3.5 m at a depth of up to 50 m below the groundsurface.

MRTA Orange Line East (Contract E1)
6m
5m

Fig. 7

Plan view of OR15 station and Srirat
expressway
Fig. 9Without any protection measures for the Srirat
Expressway viaduct, it was estimated that the
deflection at the base slab of the diaphragm wall
could increase up to 66 mm with an unsatisfied
estimated moment in the piles. To avoid the excessive
amount of deflection, it was determined to install 2
preceding beams with a thickness of 3.5 m using thelarge diameter jet grouting technique. The firstpreceding beam is constructed at a depth of 15 m
below the ground level in a medium clay layer. The
second preceding beam was installed in a sand layer,
which is at a depth of 26.5 m below the groundsurface. The layout plan of the preceding beams at theOR15 Station is shown in Fig. 8.

Fig. 8Design plan of the jet grouted preceding
beam (Block F)

Quality control
An electrical resistivity testing was adopted toverify the constructed width of the preceding beamwith the jet grouted piles installed in the medium clay
layer underneath the OR15 Station. The electricalresistivity testing was conducted at Block F of thestation, as shown in Fig. 8. The testing was conductedwith probes spaced at a distance of 18.8 m across thebeam.
To determine the resistivity values of the grout
treated and untreated soils at the site, the resistivity
test was conducted in the laboratory for soil samples
obtained from the site. The resistivity values of theuntreated clay samples were determined to range
from 1.5 to 1.6 Ohm-m. The resistivity values of thegrout treated clay samples were determined to range
from 7.0 to 30.0 Ohm-m. The resistivity value for thetransition zone between the completely treated clay
and untreated clay was assumed to be 4.25 Ohm-m,
which is the average value of the resistivity values forthe grout treated clay samples and the untreated clay
samples. The resistivity value of 4.25 Ohm-m wasused to determine the effective diameter of the jet

Layout plan of preceding beams at OR15456

SEE - Bangkok, Thailand, Nov.11-13, 2019

grouting.
The results of the electrical resistivity test
performed at Block F are shown in Fig. 10. Fig. 10
indicates that the measured resistivity values for theentire cross section range from 0.6 to 22 Ohm-m.
Using the resistivity value of 4.25 Ohm-m for thetransition zone, the constructed width of thepreceding beam was estimated to be approximately
6.4 m. Field observation was conducted to measure
the constructed width of the preceding beam when thepreceding was exposed. The constructed width of thebeam was measured to range from 5.8 to 6.3 m. The
visual observation confirmed the estimated width of
the beam obtained from the resistivity test. Therefore,
it is concluded that the constructed preceding beam
meets the requirement of the designed width.

2.

3.

CONCLUSIONS AND RECOMMENDATIONSThis paper presented the usage of the large
diameter jet grouting technique for two tunnel
projects in Bangkok. The following conclusions weredrawn from the study of the projects:
1.

excavation was in a dry condition after grouting.
Consequently, the design requirement forhydraulic conductivity was met for the IDT shaft.
The electrical resistivity test and the fieldobservation performed at Block F of the MRTA
Orange East Project indicated that the large
diameter jet grouting technique could be utilized
to meet the width requirement of the preceding
beam constructed in the medium clay layer
underneath the OR15 Station. It is recommended
that the effectiveness of the large diameter jet
grouting technique be verified for sandy
Bangkok soils.
This study demonstrates that the design
requirements of the treated materials can be met
effectively using the large diameter jet grouting
technique. Furthermore, the construction time
and the associated costs were reduced using thelarge diameter jet grouting technique.

ACKNOWLEDGMENTS
The authors wish to thank the following
organizations: Sanshin Construction (Thailand) Co.,
Ltd. and ISEKI Engineering (Thailand) Co., Ltd. forcarrying out the field work of the large diameter jet
grouting; Geotechnical & Foundation Engineering
Co., Ltd; CKST Joint Venture, and Mass Rapid
Transit Authority, Thailand for providing valuable
construction records for conducting this evaluation.

The field pumping test that was conducted for the
MRTA Blue Line Extension Project indicatedthat there was no water at the excavated base of
the IDT shaft. Therefore, the large diameter jet
grouting conducted at the site successfully
prevented the risk of uplift and piping in the 2nd
stiff clay layer. Furthermore, the base of theFig. 10 Results of electrical resistivity test for Block F
REFERENCES
Construction of Soil-Cement Column: Case
Study on Drainage System Suvarnabhumi
International Airport Project, 2009.
[5] Yong, D. M., Hayashi, K. and Chia, B. H., Jet
grouting for construction of a RC canal in soft
marine clay. Grouting and deep mixing: Procds.,
IS Tokyo 96, 2nd International Conference on
Ground Improvement Geosystems Tokyo, Japan,
1996. pp. 375-380.
[6] Yoshida, H., Jimbo, S. and Uesawa, S.,
Development and practical applications of large
diameter soil improvement. Grouting and deep
mixing: Procds., IS Tokyo 96, 2nd International
Conferenceon
GroundImprovement
Geosystems Tokyo, Japan, 1996. pp. 721-726.

[1] Cheng S.H., Risky K.N., Liao H.J., and Hsieh
Y.H., A Large Diameter Jet Grouting Method for
Arrival of Shield Tunnelling Machine. ISSMGE- TC 211 International Symposium on Ground
Improvement IS-GI, Brussels, 2012.
[2] Jaritngam S., Design Concept of The Soil
Improvement for Road Construction on SoftClay. Eastern Asia Society for Transportation
Studies, Vol. 4, 2013.
[3] MRTA, OR15 Pradit Manutham Station Detailed
Design: Diaphragm Wall including Impact
Assessment and Protection Measures for Sirat
Expressway viaduct, 2017.
[4] Sompong R., Soil Properties Effect on457

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STRUCTURAL BEHAVIOR OF NON-DUCTILE REINFORCED
CONCRETE COLUMNS

1

Ari Wibowo1, Rizki Amalia Tri Cahyani2
Department of Civil Engineering, Faculty of Engineering, Brawijaya University, Malang, Indonesia
2
Department of Civil Engineering, Muhammadiyah University, Malang, Indonesia

ABSTRACT
Confinement of columns with non-seismic detailing is prevalent in many old buildings and common in current
detailing practice in many developing countries. This type of columns is believed to have a very low drift capacityfrom a conventional design perspective. To investigate the lateral load-drift behavior and the collapse mechanismof such columns, the experimental tests on four lightly reinforced concrete columns with light transverse
reinforcement ratio have been undertaken. The quasi-static tests were applied on concrete columns with various
longitudinal reinforcement ratio, transverse reinforcement ratio, and lap splice position. Interestingly, the results
showed that the total drift capacities could reach up to 7% well beyond the required maximum drift suggested bymany codes despite the low detailing. Reasonably, the closer the stirrups spacing, the higher the ductility of thecolumns. Whereas, it appeared that the higher the longitudinal reinforcement ratio, the lower the ductility ratio.
Furthermore, the theoretical analyses have been conducted to estimate investigate the lateral load-deflection
behavior of the columns which were in a good agreement with the test results.
Keywords: Lightly reinforced columns, Transverse reinforcement, Seismic performance

INTRODUCTION
Lightly reinforced concrete columns arecommonly found on construction practices in low
seismic region countries and many developing
countries [1]. The practices generally include one or
the combination of some parameters, i.e., low
longitudinal reinforcement ratio, low transverse
reinforcement ratio, inadequate development lengthof steel reinforcement, and lap splice position. Somestudies have studied the effect of several parameters
affecting the seismic performance of reinforced
concrete columns as follows: Sezen [2] examined four columns using both theaxial load ratio and loading history as thevariables in order to investigate the axial load
failure of structures with light transverse
reinforcement, typical of buildings designed
before the requirements for ductile detailingwere introduced in the USA. It was observedthat by increasing the axial load, the lateralstrength increased and the displacement capacity
decreased whilst the loading history did notappear to affect the column lateral drift capacity.
 Rodsin [3] tested three columns S1, S2, and S3
with aspect ratios of 3.75, 2.75 and 2.25
respectively. The specimens were composed of
cantilever columns having 1.4% longitudinal
steel ratio, 0.24% transverse reinforcement area
ratio and a constant axial load ratio of 0.20.
Interestingly, the drift capacities of the







458

specimens with smaller aspect ratios weresimilar or even larger than specimens with thelarger aspect ratio. It was shown that this wasdue to additional rotation at shear cracks which
increased the drift capacity of the columns.
Griffith et al [4] investigated the retrofitted RC
columns including two slender columns(without retrofitting) with low to mid steel
reinforcement ratio. It was observed that theslender columns were still able to sustain axial
load even after extensive concrete crushing andeffectively zero lateral load capacity.
Nakamura and Yoshimura [5] analyzed fourcolumn specimens by varying two parameters;
axial load ratio (0.18 and 0.27) and lateralloading type (monotonic and cyclic loading) toinvestigate the intermediate-story collapse
found in many structures during 1995 Kobe
earthquake. The effect of the axial load ratio on
the shear-dominated column was found verysignificant. Increasing the axial load ratio from
0.18 to 0.27 decreased the lateral drift capacityfrom 20.6% to 3.0% for monotonic lateralloading and from 10.4% to 4.8% for cyclic
lateral loading.
Yoshimura et al [6] conducted a test on eightspecimens representing short columns which
may fail in shear or flexural-shear. Some of theconclusions were: a) the decrease of
longitudinal reinforcement ratio from v =1.69% to 0.94% increased the axial load drift

SEE - Bangkok, Thailand, Nov.11-13, 2019

capacity significantly from 2.0% to 17.8%; b)interestingly, the research showed that shortcolumns with 0.21% transverse reinforcement
could provide considerable drift capacity
compared with flexure-dominated columns.
 Kogoma et al [7] studied three parameters(transverse reinforcement ratio, axial load ratio,
and lateral loading type) in order to study thereinforced concrete column damage pattern andthe maximum strength and displacement
capacities. The axial load failure drift capacityand failure mode were considerably affected by
the amount of transverse reinforcement ratiowith a reduction in the stirrup spacing. An
increase in transverse steel ratio increasing thedrift capacity and shifting the failure mode froma shear failure to a flexure-dominant failuremode.
It appeared from those studies that the lateralload-carrying capacity and collapse mechanism ofsuch columns are mainly affected by longitudinal
reinforcement ratio, transverse reinforcement ratio,
axial load ratio, and aspect ratio. The first two
parameters became the main focus of this research.

ratios of a=4.3). Each four column specimens were
reinforced with 4D8 and 4D10 corresponding to thelongitudinal reinforcement ratios of 0.75% and 1.1%
respectively. All stirrups with a diameter of 6mm
were used for the transverse reinforcements whichwere spaced at 150mm and 250 mm (equivalent to
0.61% and 0.36% of volumetric transverse
reinforcement ratio respectively).
Concrete strength ranging 22-27 MPa (anaverage of 25 MPa) were observed from concrete
compression strength of cylinder concrete andhammer tests on column specimens. The measured
yield strength of steel bar with a diameter of 6mm,
8mm, and 10 mm were about 378MPa, 433 MPa,and 536 MPa respectively, whereas, thecorresponding steel ultimate strength were 538MPa,
646 MPa, and 824 MPa respectively. The column
properties and reinforcement configurations areshown in Table 1 and Fig. 1.
Table 1 Column specimen properties

EXPERIMENTAL TEST
Eight column specimens have been designed torepresent structural columns commonly found indeveloping countries with three parameters studied:longitudinal reinforcement ratio, transverse
reinforcement ratio and location of lap splice. This
study was the extension of previous studies [8,9]which investigated the aspect ratio, the longitudinal
reinforcement ratio and the axial load ratio on
seismic performance of such columns.
Eight concrete columns specimens had a crosssection area of 150160 mm and height of 640 mm(to the location of lateral load point, with the aspect(a) Columns with light transverse
reinforcement ratio
Fig. 1

v

h

(%)

Area

Vol.

L15C

0.76

0.35

0.61

0.1

Lap
SpliceRegion
-

L25C

0.76

0.21

0.36

0.1

-

-

M15C

1.10

0.35

0.61

0.1

-

-

M25C

1.10

0.21

0.36

0.1

-

-

L15SB

0.76

0.35

0.61

0.1

Plastic

200

L15SM

0.76

0.35

0.61

0.1

Elastic

200

M15SB

1.10

0.35

0.61

0.1

Plastic

250

Col.

n

ld
(mm)
-

M15SM 1.10 0.35 0.61 0.1
Elastic250
Note: 𝜌𝑣 = longitudinal reinforcement ratio, 𝜌ℎ =transverse reinforcement ratio, 𝑛 = axial load ratio,
𝑙𝑑 = lap slice length(b) Columns with lap location atbottom of columns

Typical column specimens with various parameters tested.

459(c) Columns with lap location at
mid height of columns

SEE - Bangkok, Thailand, Nov.11-13, 2019

The lateral quasi-static loading tests wereconducted as per ASTM E2126 code.
The
displacement control sequence was applied by using
drift increment of 0.25% up until reaching drift of
2.0% and then followed by drift increment of 0.5%
until the occurrence of lateral load failure which wastaken at about 20% load drop of peak strength. On
each defined discrete drift, the displacement
components were measured (consisting of flexural,shear and total displacement) using LVDTs and dialgauges, and crack propagation recorded.
The LVDTs and dial gauges were set to monitor
and measure three components of column
deformation, i.e., flexural, yield penetration, andshear with configuration as shown in Fig. 2, i.e., no1-5 for flexural deformation, no 5-6 for total lateral
deformation, and no. 8-9 for shear deformation.



Load-Displacement Behavior and Collapse
Mechanism

LateralLoad

Fig. 2

region) respectively.
The closer the spacing of transverse
reinforcement, the higher the ductility ratio dueto the higher the confining effect provided by
the stirrups.
From the curvature distribution over the column
height (refer Fig. 4-5), it shows clearly that byplacing the lap splice at column mid-height, theplastic region tends to spread over to the second
region from the column-foundation interface.
Whilst columns with the continuous bars andlap splice at the bottom of the column had thecurvature distribution concentrated more in theplastic hinge area.

The
collapsemechanisms
and
crack
propagations of column specimens were observed asfollows (refer Fig. 6-7):
 All column specimens exhibited flexuraldominant behavior particularly at the ascending
part of the load-displacement curve.
 However, columns with a larger spacing ofstirrups tended to developed shear cracks at alater stage following the initial flexural cracks.
It showed that the shear strength of columns
started to decrease after a certain point andtriggered the shear cracks once it is below theflexural strength of columns. It can be attributed
to the flexure-shear-critical mechanism of thecolumns (refer Fig. 6) where the shear strength
Vn is higher but relatively close to the flexuralstrength (Mn/L) [7]. On the contrary, the flexurecritical columns with the closer stirrups spacing
could maintain the shear strength of columns
higher than the flexural capacity despite theshear strength reduction with the progression ofdrift.

LVDTs and dial gauges Measurement
Setup.

TEST RESULTS
Peak Strength and Ductility Ratio
The test findings showed interesting results asfollows (refer to Fig. 3 and Table 2):
 Specimens with a lower ratio of longitudinal
reinforcement ratio tended to have higher
ductility ratio. The increase of the longitudinal
reinforcement ratio increases the peak strength
but decrease the ductility ratio.
 The lateral peak strengths of columns with lap
slice located at the half height of the cantilevercolumns were relatively similar to those ofcolumns with continuous reinforcement. On theother hand, the columns with lap splice locatedat plastic hinge region showed the smallest ofpeak lateral strength capacity.
 The continuous reinforcement bar reasonably
provided the larger drift capacity, followed by
the lap-splice location at column mid-height(elastic region) and bottom (plastic hinge

Table 2 Ductility ratio of all column specimens

460

Specimens

Yield
Drift

FailureDrift

Ductility
Ratio

L15C

0.72

4.00

5.55

L25C

0.8

3.67

4.59

M15C

1.19

4.00

3.36

M25C

1.15

3.35

2.91

L15SB

0.92

3.67

3.99

L15SM

0.63

3.35

5.32

M15SB

0.56

2.50

4.46

M15SM

0.68

3.00

4.41

SEE - Bangkok, Thailand, Nov.11-13, 2019



Fig. 3Lateral load-drift behavior for all column
specimens.

700

L15C
L25C

600

The columns with lap slice at mid-height ofcolumn showed wider cracking area and more
severe concrete spalling compared to columns
with lap splice located at the plastic hinge
region. The double amount of reinforcement at
lap splice location provided higher effectivenesswhen it was placed at the plastic hinge region(where the maximum moment occurs)
compared with if it was located within theelastic area of column (outside the plastic hinge
region).
On the other hand, all columns with lap-spliceconnection developed higher damage degreecompared to columns with continuous bars. It
can be attributed to the lack of proper lap splicedevelopment lengths in all columns which were
purposely designed less than the minimum code
requirement in order to investigate the effect ofsuch connection.
F

Column height, mm

M15C
500

M25C

400

Vn

L15SB

Shear-critical

L15SM

Flexuralshear-critical

M15SB

300

Flexurecritical

M15SM

200

a

100

Fig. 6000.00005

0.0001

Displacement Components

Curvature distribution over the column
height at peak load.

700

Column height, mm

Furthermore, the measurement of thedisplacement components of columns (flexural,yield penetration, and shear) showed the different
effect of each studied parameters as follows (refer
Fig. 8-9):
 The shear deformation was the least component
observed in all column specimens up to 5% of
total deformation. It was reasonable since all
specimens were designed with light longitudinal
reinforcement. However, columns L25C and
M25C with lower transverse reinforcement ratio
showed larger shear deformation after reaching
peak strength. It corroborated the observation ofcollapse mechanism and crack propagation oncolumn specimens.
 The yield penetration deformation took about
20%-50% of the total deformation. The larger
percentage of those was found on columns withlower longitudinal reinforcement. The smaller
the diameter of the longitudinal bar, the higher
the yield force developed at the bar for the sameamount of bending moment, and hence theearlier the slip occurrences between concrete

L15C
M15C

600

L15SB
L15SM

500

M15SB
M15SM

400
300

200
100
0
0

Fig. 5

Curvature distribution over the column
height at peak load.

0.00015

Curvature

Fig. 4

0.00005 0.0001 0.00015 0.0002 0.00025
Curvature

Curvature distribution over the column
height at lateral load failure.

461

SEE - Bangkok, Thailand, Nov.11-13, 2019

and steel.
And certainly, the flexural deformations werereasonably the largest component of

deformation ranging 50%-70% of the total
deformation due to the nature of flexuredominant columns.

L15C

L25C(1)

M15C

2M25C

L15SB

L15SM

M15SB

M15SM

Fig. 7

Crack Propagation and collapse mechanism of all column specimens.

Fig. 8

Displacement components for columns with continuous reinforcement.

462

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 9Displacement components for columns with reinforcement lap-splice.

CONCLUSIONSREFERENCES

Reinforced concrete columns with lightreinforcement are commonly found in developing
countries and low-to-moderate seismic region. An
experimental test has been conducted forinvestigating the seismic performance of suchcolumns. The effect of longitudinal reinforcement
ratio, transverse reinforcement ratio, and placing of
reinforcement lap splice were the main parameters forstudying the load-displacement behavior and collapse
mechanism of lightly reinforced concrete columns
when subjected to quasi-static lateral load. The
findings were as follows: The increase of longitudinal reinforcement ratio
increases the lateral peak strength, but decrease
the ductility ratio, resulted in more flexuraldominant behavior and reduce the yield
penetration deformation.
 The increase of transverse reinforcement ratio
the higher the ductility ratio, the smaller the shear
deformation observed. The closer the shear
strength to the flexural strength, columns tend todeveloped flexure-shear dominant behavior
marked with shear collapse mechanism
following the initial flexural crack development.
 Placing the lap-splice closer to the plastic hinge
region resulted in more concentrated curvature
distribution and flexural damage to the bottom of
the column which leads to a smaller
displacement at the column top. And certainly,
the largest displacement capacity can be obtainedby using continuous reinforcement bars.

[1] Kafle, B., Mohyeddin-Kermani, A., Wibowo, A.,
A Report on the Visit to the Region Stricken by
the Wenchuan Earthquake, Electronic Journal of
Structural Engineering, Vol 1, No 1, Appendix
B, 2008, pp. 1-40
[2] Sezen, H., “Seismic Response and Modeling ofReinforced Concrete Building Columns, Ph.D.
Dissertation, Department of Civil andEnvironmental Engineering, University ofCalifornia, Berkeley, 2002.
[3] Rodsin, K., Seismic Performance of Reinforced
Concrete Soft-storey Buildings in Low toModerate
Seismicity
Regions,
Ph.D.
Dissertation, Department of Civil andEnvironmental Engineering, University of
Melbourne, Melbourne, 2007.
[4] Griffith, M.C., Wu, Y.F., Oehlers, D.J.,
Behaviour of Steel Plated RC Columns Subject
to Lateral Loading, Advances in StructuralEngineering, Vol. 8, No. 4, 2005, pp 333-347.
[5] Nakamura, T., Yoshimura, M., Gravity Load
Collapse of Reinforced Concrete Columns with
Brittle Failure Modes, Journal of AsianArchitecture and Building Engineering, Vol 1,
No. 1, 2002, pp. 21-27. (2002)[6] Yoshimura, M., Takaine, Y., Nakamura, T.,
Collapse Drift of Reinforced Concrete Columns,
PEER Report 2003/11, Fifth US-Japan
Workshop on Performance-Based Earthquake
Engineering Methodology for Reinforced
Concrete Building Structures, Hakone, Japan,
2003, pp. 239-253.
463

SEE - Bangkok, Thailand, Nov.11-13, 2019[7] Kogoma, I., Hayashida, T., Minowa, C.
Experimental Studies on the Collapse of RC
Columns During Strong Earthquake Motions,
Tenth World Conference on Earthquake
Engineering, Rotterdam, Holland, 1992, pp.
3013-3017.
[8] Wibowo A, Wilson JL, Lam NTK, Gad EF. Drift
Performance of Lightly Reinforced Concrete

Columns. Engineering Structures Journal,
Elsevier, Volume 59, February 2014, pp 522–
535.
[9] Wibowo A, Wilson JL, Lam NTK, Gad EF.,
Drift Capacity of Lightly Reinforced Concrete
Columns”. Australian Journal of StructuralEngineering, Vol. 15, No. 2, 2014, pp. 131-150.

464

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STATISTICAL ANALYSIS OF THE INFLUENCE OF TRAFFIC ANDENVIRONMENTAL DISTURBANCES ON DAMPING IN A BRIDGE
1,2,3

Koharu Ota1, Kouichi Takeya2, Junji Yoshida3
Faculty of Engineering, Graduate School, University of Yamanashi, Japan;
ABSTRACT

To maintain and improve the performance of infrastructures, Structural Health Monitoring (SHM) has beenstudied in the past few decades. Vibration-based SHM is mainly used for bridge health monitoring that focuses on
structural parameters including the natural frequency, deflection, and damping. Among these parameters, damping
can be considered as an index of the deterioration of structures, since damping is influenced by changing the energy
distribution in bridge structural systems. However, there is difficulty in the long-term monitoring of damping as it
is also influenced by external disturbances such as traffic and temperature. In this study, the damping of bridges
was statistically analyzed by considering the influence of traffic and temperature. In particular, a solar-powered
monitoring system using MEMS accelerometers was constructed and installed on a steel girder bridge. The
Random Decrement method was applied, and the appropriate data length and window size were considered tomeasure the damping ratio with high accuracy. The measured damping ratio from traffic-induced vibrations andmicro-tremors of bridge girders were statistically compared by considering a probability density distribution.
Moreover, the influence of temperature on the damping ratio was also analyzed. Based on the results, generalized
linear models of the measured damping ratio were estimated considering the influence of these external
disturbances.
Keywords: Bridge, Random Decrement method, Modal analysis, Damping ratio

INTRODUCTION

The RD method calculates the damping ratiousing the free vibration waves obtained byconvolution of micro-tremor vibrations. The damping
ratio is calculated from the envelope of the peaks offree vibration waves. [7] This method is generally
used when the damping ratio is small. In addition, thismethod has low enough calculation cost to be
calculated by a microcomputer and so data processing
is possible at the measurement location.
In the ERA method, first, free vibrations arecalculated from micro-tremor observation data byforming a cross-correlation function using the Natural
Excitation Technique (NExT).
Next, the ERA is used to obtain natural frequencies,
mode shapes, and damping ratios based on the
singular value decomposition of a Hankel matrix ofthe free vibrations. [8] This method can estimate thevibration characteristics even in adjacent modes.
However, the calculation cost is remarkably highcompared to other methods, thus it is difficult toimplement the ERA method to microcomputers.
Considering the ease of implementing the analysis
unit to microcomputers, the RD method was selected
as the analysis method for this study.
To date, various types of statistical processing,such as Bayesian estimation, have been studied forevaluating the variations of structural parameters. [9],[10] This study looked at statistical analysis using
probability density and histograms as an evaluation
method of damping ratio.
Furthermore, to evaluate the damping ratio using
the vibration response from bridges, the factor of theBridge Health Monitoring (BHM) using thestructural response of bridges is carried out topromptly detect bridge deterioration and efficiently
manage bridge maintenance.
In BHM, structural parameters such as damping,deflection, and natural frequency are identified by the
inverse analysis of vibration response data. Damping
influences the energy flow in bridge components,
including upper structures such as bridge decks aswell as main girders, supports, piers, and abutments.
Since deterioration or damage changes the energy
flow in bridge components, a change in damping canbe observed. [1]-[5] However, damping is a variable
parameter since the energy flow changes due toenvironmental disturbances such as temperature andtraffic on bridges.
Moreover,measurement
equipment
andcalculation methods also influence the results. The
half power method, the Random Decrement (RD)method, and the Eigen-system Realization Algorithm(ERA) method are generally used to calculate thedamping ratio.
The half-power method estimates the damping
ratio from the frequency response function of astructure which has been excited by base motion or an
applied force. This method calculates theapproximation damping ratio but can only be applied
when the damping ratio is small (about 0.1 or less),
and the frequency-amplitude characteristic shows anevident single-peak characteristic. [6]465SEE - Bangkok, Thailand, Nov.11-13, 2019variation of the damping ratio was organized and theinfluence of temperature and traffic wasquantitatively evaluated. Long-term monitoring on aroad bridge was conducted and the analysis methodof the damping ratio was examined. Statisticalevaluation of the damping ratio considering theinfluence of environmental disturbance was theninvestigated.

Transform (FFT). Band-pass filters are designed andapplied to focus on the target dominant frequency,
and free vibrations are calculated by the RD method.
Finally, the damping ratio is calculated by curve
fitting and the weighted average.
Baseline Correction of Acceleration Data
Acceleration data contains drift components
which influences the acquisition of micro-tremors
and the calculation of the damping ratio. The moving
average filter is therefore applied to the acceleration
data to extract drift components. Figure 5 shows themoving average of acceleration data between 7th and

ACCELERATION MEASUREMENT ON ASTEEL GIRDER BRIDGE
Target Bridge
The target bridge is a nine-span girder bridge; andeach span length is 10m. This bridge was built in
Kofu City, Yamanashi Prefecture, Japan in 1958.
This bridge is made of a Reinforced Concrete (RC)deck with I-shaped steel girders. The traffic on thebridge is two-way traffic, with a single lane in eachdirection. Fig. 1 (a) shows an overview of the bridgeand Fig. 1 (b) shows sensor positions in the crosssection of the bridge.

RC decks

C

Steel girders

B

A

Sensors
Pier 2

Pier 1

G3

G2

Monitoring System

Fig. 1 (a) Overview of the bridge.
(b) Installation location of accelerometers.

A monitoring system was constructed to monitor
damping in the long term. Figure 2 shows an
overview of the monitoring system. Three Micro
Electro Mechanical System (MEMS) type
accelerometers (EPSON, M-A550AC) were used foracceleration measurement with high precision. The
measured acceleration data was logged by a datalogger (KEYENCE, NR-600). Solar panels and shield
batteries supplied electricity to the monitoring system.
Table 1 shows the specification of the accelerometer.
The accelerometer was attached on a plastic baseplate with neodymium magnets for installation on
steel bridge components, as shown in Fig. 3.
CALCULATION OF DAMPING RATIO
Acceleration data obtained from long-term
measurements was used to calculate the damping
ratio. In this study, the measured data was analyzed
using MATLAB 2017a. The proposed analysis
method could be implemented in the monitoring
system with microcomputers as it followed the RD
method of analysis. The flowchart of the proposed
analysis method is shown in Fig. 4. First, the baselineof the acceleration data is corrected by extracting thedrift component. Second, micro-tremors and trafficinduced vibrations are classified using the thresholdof the vibration amplitude. Third, dominantfrequencies are analyzed by the Fast Fourier

Fig. 2 Overview of the monitoring system.
MEMS type accelerometers

RC deck

Table 1 Specification of the accelerometers
Model
M-A550AC

Range
±5 G

G1

2.6 m

Sampling
100 HzSteel girder (G2)Resolution
0.06 μG

Fig. 3 MEMS type accelerometer466

RC deck

SEE - Bangkok, Thailand, Nov.11-13, 201913th August 2018. The baseline of the acceleration
data appears to drift with temperature change. The
baseline is corrected by subtracting the temperaturedrift component from acceleration data.

In the aforementioned process, the dominantfrequencies are determined by modal analysis and thetarget frequency is decided. First, the dominantfrequencies of the bridge were calculated using FFTof acceleration data. Figure. 7 shows the power
spectral density of acceleration data at measurement
position A in Fig. 1.
Next, modal analysis is conducted. The
Frequency Domain Decomposition (FDD) techniqueuses the fact that modes can be estimated from thespectral densities calculated with the assumption ofwhite noise input. FDD can estimate mode shapes
directly from signal processing calculations using
Singular Value Decomposition (SVD) of each
spectral density matrices [11], [12]. The spectral
transfer function which is the ratio of the output
power spectrum to the reference power spectrum, wascalculated at each measuring position. The reference
measurement position was not on a node of avibration mode. In this study, there were three
accelerometers; one was fixed as a reference
measuring point and the remaining two were attachedon all measurement positions, one by one. The

Data Classification
Micro-tremors are generally used to analyze
structural parameters of bridges. In this study, microtremors and traffic-induced vibrations are separated
to analyze the influence of traffic-induced dynamic
load on structural parameters. When the maximum
absolute acceleration in each data segment of 100
samples is 70% or less of all absolute peaks, the data
segment is classified as a micro-tremor. This
percentage acts as a threshold for the absolute
acceleration. On the contrary, when the maximum
absolute acceleration is higher than the threshold, thedata segment is classified into traffic induced
vibration. The image of the data classification process
is shown in Fig. 6.
Acquisition of the Dominant Frequencies

Traffic induced vibration
Acceleration data◼

Baseline correction
Removal of temperature drifts

Acceleration data

Data extraction◼ Acquisition of micro-tremors(without traffic induced vibration)
Traffic induced vibration

Micro-tremors

Acquisition of dominant frequencies◼ FFT Analysis and Modal Analysis

Micro-tremors

Fig. 6 Example of the data classification process
14.5 Hz◼

FIR filter
Filtering by Band-pass filter◼

RD method
Acquisition of Free vibration◼

PSD [mm2/s4/Hz]

Free vibration

19.95 Hz6.05 Hz100
0.8 Hz10-2

Curve fitting
Calculation of damping

100

Damping

Fig. 4 Flowchart of calculating damping ratio

101

Frequency [Hz]Fig. 7 Power spectral density of acceleration andnatural frequencies of the bridge

Amplitude

10

2nd span-10Fig. 5 Moving average of the acceleration data

1st span10
Location [m]20Fig. 8 First vertical vibration mode shape (14.5Hz).
467

SEE - Bangkok, Thailand, Nov.11-13, 2019

measurement period was 5 minutes.
As a result, it was estimated that 14.5 Hz was
close to the state of the first vertical mode. There werefour significant dominant frequencies, and the mainfrequencies were 0.8 Hz, 6.05 Hz, 14.5 Hz, and 19.95
Hz. Figure 8 shows a mode shape of the first andsecond span of the target bridge in 14.5 Hz.

The damping ratio was obtained using curve fittingof the free vibration peaks. Curve fitting calculated in
the RD method process is represented in Fig. 9. Data
from 1st December to 22th December 2018 were used,
and the damping ratio was 5.51%. The determination
coefficient at this time was 0.887.
STATISTICALRATIO

Acquisition of Free Vibration
A Finite Impulse Response (FIR) band-pass filter
was applied to eliminate noise and focus on thenatural frequency of the first vertical vibration mode.
Bandwidth
frequencies
wereautomaticallydetermined with the two closest negative peaks fromthe target frequency, as shown in Fig. 10.
The damping ratio determined from the freevibration waveform and curve fitting are affected by
the analysis process of the RD method. Therefore, itis necessary to analyze the influence of the analysis
parameters, the data length, and the window length in
the RD method. The acceleration data atmeasurement position A was analyzed to observechanges in the damping ratio. Figure 11 shows therelationship between the number of data and theattenuation ratio. The gray line is the attenuation ratiom (n, m) at different time data m, the black dot is theaverage attenuation ratio ζ̅ (n) per data number n, andthe red line is the overall average attenuation ratio ζ̅all.
When n is sufficiently large, ζ̅all is taken as theconvergence value ζ̅* of the damping ratio. The
average damping ratio proposed here is a weighted
average weighted by the determination coefficient R2
given by the following equation.
ζ̅all =∑n ∑m R2(n,m) ζ(n,m)∑n ∑m R2(n,m)

→ ζ̅

*

ANALYSISOFDAMPING

Histograms and probability density distribution
analysis was applied to consider the variance of thedamping ratio against both temperature and traffic.
First, histograms were calculated with the frequency
on the vertical axis and the damping ratio on thehorizontal axis. Next, probability density
distributions of the damping ratio were calculated

Fig. 9 Free vibration and curve fitting to calculate
the damping ratio(1)

The damping ratio converges as the data length
increases. As a result of the analysis, the data length
was set to 1×106 samples, and so if the window lengthis set to 69 samples, 10 cycles of target vibrations areincluded. Table 2 shows the conditions under which
the RD method is applied.

Fig. 10 Power spectral density of acceleration andthe bandwidth frequencies

Table 2 Condition of RD method application
Vibration mode
1st vertical mode
Dominant frequency
14.5 Hz
Filter type
Band-pass
Window
KaiserFilter order
128
Sampling rate
100 Hz (samples/sec.)
Window length
10 cycles (69 samples)
Data length
1×106 samples (104 sec.)
Overlap ratio
0.8
Calculation of Damping Ratio (Curve fitting)Fig. 11 Convergence of damping ratios along thedata length
468

SEE - Bangkok, Thailand, Nov.11-13, 2019using the Gaussian distribution model.
To consider the influence of traffic on thedamping ratio, damping ratio distributions werecompared by analyzing traffic induced vibrations andmicro-tremors. Moreover, damping ratio distributions
in each month were also compared to consider theseasonal effect.

approximation as follows, where air temperature T
represents the weighted average of damping ratio ζ.

ζ = 0.0087T3 -0.3308T2 +2.386T+51.49 (×10-3 ) (2)
CONCLUSIONSIn this study, statistical analysis of the damping
ratio of a bridge was conducted to identify the factor
that causes variance and quantitatively evaluate theTraffic Effect on the Damping Ratio
Figure 12 shows the distribution of damping ratiowith and without traffic effect. Anaysing thehistograms, traffic distribution (Fig. 12(a)) isconcentrated at a damping ratio of around 3.5%,
while the non-traffic distribution (Fig. 12(b)) isconcentrated at around 4.8%. In addition, the varianceof the damping ratio calculated from the traffic
induced vibrations is higher than that from the microtremors. Traffic increases the variance of the damping
ratios, which can be seen from the amplitudedependence of the structural damping and the effectof truck dampers traveling on the bridge.

(a)Seasonal Effect on the Damping Ratio(b)

The seasonal effect on the damping ratio wasanalyzed, and the results of the damping ratio
distribution in August and December are shown in
Fig. 13 (a) and (b), respectively. Comparing thedamping ratio distribution in other months show thatthe damping ratio fluctuated and variances in thedamping ratios are high.
In the probability density distribution, thevariance of damping ratios from micro-tremors was
small however, the variance and average of thedamping ratios changed between seasons. The
seasonal effect on the damping ratio likely
encompasses temperature effect rather thandeterioration of the bridge over time.

Fig. 12 Comparison of histograms and probability
density distributions of damping ratios (a) fromvibration induced vibrations, and (b) microtremors(a)Temperature Effect on the Damping Ratio
Micro-tremors in the acceleration data wereclassified based on air temperature and damping ratio
distributions were analyzed using the RD method.
Figure 14 shows the damping ratio distribution ofdifferent temperature ranges, 0 to 10 °C, 10 to 20 °C,
and 20 to 30 °C. The damping ratio increased as
temperature decreased. Compared to the damping
ratio distribution considering seasonal changes, thevariance of the damping ratio against air temperatureis small.
Figure 15 shows the damping ratio distribution
against air temperature. Orange circles show thedamping ratio distribution at a given temperature andred circles express the mean value of the damping
ratio. The mean value of the damping ratio changed
with temperature. Damping ratio and temperature
variations were formulated by the least squares(b)Fig. 13 Comparison of histograms and probability
density distributions of damping ratios (a) fromacceleration in August, and (b) December.
469

SEE - Bangkok, Thailand, Nov.11-13, 2019influence by temperature and traffic. The following
findings were obtained.
The damping ratios of a road bridge were
calculated from measured acceleration data. Modal
analysis determined the target mode at 14.5 Hz.
Data classification using the threshold of peakacceleration was incorporated into the proposed
analysis process to consider the influence of thetraffic load on the damping of the bridge. It was foundthat traffic load influences the variance of damping
ratios.
It was also clarified that the damping ratio isaffected by air temperature. The relationship between
the damping ratio and air temperature was formulated.
If the cause of variation in damping ratio alongwith temperature and traffic is further clarified, it
could assist SHM to evaluate the structural state fromstructural parameters.

Fig. 14 Histogram of each temperature range.

REFERENCES[1] Yamamoto K., Isemoto R., Oshima Y., Kim C W.,
and Sugiura K., Evaluation of Acceleration
Responses in a Steel Truss Bridge and Passing
Vehicle Before and After Member’s Breakage,
Journal Society of Civil Engineers (JSCE), Vol.
58A, 2013, pp. 180-193.
[2] Mastuoka K., Kaito K., Tokunaga M., WatanabeT., Sogabe M., Identification of the Vibration
Properties of Bridge Using the Axle Acceleration
Response of a Running Train, Journal Society of
Civil Engineers (JSCE) F4(Construction
management), Vol. 68, No. 3, 2012, pp. 175-192.
[3] Takeda T., Yamanobe S., and Nihara Y., Damping
Property of Prestressed Concrete Cable-Stayed
Bridges Based on Measured Data, Journal Societyof Civil Engineers (JSCE) No. 626/1-48, 1999, pp.
147-161.
[4] Watanabe G., Tomohiro Fumiya., Goto S., andEmoto H., Health monitoring and identification of
dynamic characteristic of a skewed bridge basedon the vibration test using a moving vehicle,
Journal Society of Civil Engineers (JSCE),
Journal of structural engineering Vol.60A, 2014.
[5] Yoshioka T., Yamaguchi H., Ito S. and Harada M.,
Identification of vibration characteristic of thesteel truss bridge and influence of diagonal
member damage on damping, Journal Society of
Civil Engineers (JSCE), Journal of structural
engineering Vol.55A, 2009, pp. 295-305.
[6] Okabayashi T., Yamamori K., Sanuki Y., andTamuraT.,
EstimationofDynamic
Characteristics for Structures with Closely Spaced
Eigenvalues, Journal Society of Civil Engineers(JSCE), No. 633/1-49, 1999, pp. 93-102.
[7] Chiu Jen Kua., Jack Edward Cermak., Li-Shu
Chou., Random decrement based method formodalparameter identification of a dynamic

Fig. 15 Damping distribution by temperature.
system using acceleration responses., Journal ofWind Engineering and Industrial Aerodynamics
95, 2007, pp. 389-410.
[8] Prasenjit Mohanty, Daniel J. Rixen., Modified
ERA method for operational modal analysis in thepresence of harmonic excitations, Mechanical
Systems and Signal Processing 20, 2006, pp. 114–
130.
[9] Goi Y., Kim C W. and Au S K., Investigation of
Operational Modal Identification of a CableStayed Bridge Based on Bayesian Estimation
Considering Stochastic Uncertainty, Journal
Society of Civil Engineers (JSCE) A2(Appliedmechanics), Vol. 72, No. 2 (Journal of appliedmechanics Vol. 19), 2016, pp. 751-762.
[10] Nishino M., and Fujino Y., Bayesian Inference
Based Uncertainty Quantification and Calibrationof Numerical Models of Existing Structures,
Journal Society of Civil Engineers (JSCE)
A2(Applied mechanics), Vol. 69, No. 2, 2013, pp.
711-718.
[11] Kaito K., Matsuoka K., Watanabe T., Sogabe M.,
and Fujino Y., Vibration Monitoring for Railway
Bridges Using Passing Train Load, Journal
Society of Civil Engineers (JSCE) F, Vol. 66, No.
3, 2010, pp. 382-401.
[12] Mehdi Batel, Brüel & Kjær, Norcross, Georgia
Operational Modal Analysis – Another Way for
Doing Modal Test.

470

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

REDUCTION IN BEARING CAPACITY OF GYPSEOUS SOILS WITH
CAVITIES
Ahmed A. Al-Obaidi1 and Reem S. Najim2
Engineering College, Tikrit University, Iraq

1, 2

ABSTRACTThe presence of gypsum in the soil will cause problems if the source of fresh water is available and permeablesoil permitting significant movement of water is to take place. The solubility of gypsum by excess water from
irrigation or localized leak into the gypseous soil may cause cavity formation. In this research, a model wasdeveloped for governing the mass-transport to assess the variation of gypsum content of the soil during dissolution.
A general three-dimensional finite element program (PLAXIS TUNNEL) was selected for the numerical analysis
method to generate the solution. Parameters that affect the bearing capacity of a square footing represented by the
gypsum content, the cavity volume, and the location of the cavity which represent by three offset distances fromthe footing center to the cavity center (X, Y, and Z), where (X) represents the horizontal distance, (Y) represents
the vertical (depth) distance, and (Z) represents the diagonal distance. The main results show that the cavity
location found to be the most parameter that affects the bearing capacity ratio (BCR). The minimum values arefound when the cavity locates at the center of the footing base, and the lowest one (0.211) when the gypsum
dissolved equal to 40%, also there is no effect of the cavity location when the ratio of (X/B) and (Z/B) exceed (3.0)
for any depth and when the gypsum dissolved less than 10%. For high gypsum dissolution (more than 30%), thedimensionless ratios (X/B), (Z/B) and (Y/B) of the cavity must be more than 5.0.
Keywords: Gypseous soil, Cavity location, Cavity volume, Gypsum dissolution, BCR.

After site investigation, it was found that a shallow
cavity with dimensions about 5.5m × 2.0m. Also,
many problems have been noticed in different
structures constructed on gypseous soils in the last
three decades among them, Samarra tourist hotel,
Tikrit training center, Kerbala elevated water tank,and the excessive settlement and cracks in Al-Anbar
University Main building, as shown in Plate (1).
The presence of gypsum will cause problems if
the source of fresh water is available and permeablesoil permitting significant movement of water is totake place, [2]. The solubility of gypsum by excesswater from irrigation or localized leak into thegypsiferous layer (Solubility of gypsum 2.6 g per one
liter of water at 20 °C and 1 atm.) will cause sudden
settlement. Degree and amount of settlement is not afunction only of the amount of gypsum but also thestructure of gypsum (whether powder or large
crystals) and also the distribution of gypsum as wellas the quality of water. The solubility of gypsum maycause sinkholes formation and serious damage to thestructures.
The cavity formation often occurs where excesswater infiltrating (soaking and leaching) beneathfoundations into the gypsum-rich layer. This water
will attack and dissolve gypsum particles which act
as cementing bond in soil, and transportation of soil
mass will occur that mass will plug down, and bythese techniques, a collapse of sinkholes occurs as thebridging material over a subsurface carven cannot

INTRODUCTION
The development programs of many areas within
the last years were faced with a problem due to theexistence of the various amount of gypsum. In mostof these areas, the gypsum found as partially gypsum
stratum or soil containing an amount of gypsum.
In Iraq gypseous soils covered wide areas, (morethan 20% of the total area) sometimes with highgypsum content exceeds the soil content, and yet
today engineering properties of these soils in someareas are unknown.
Many major projects have suffered from several
problems related to construction on or by gypseous
soils such as cracks, tilting, collapse and leaching thesoil. These problems could happen due to seepage ofwater into these soils, causing the dissolution of
gypsum, which provides the cementing bonds
between the soil particles. This process leads to thecollapse of soil structure and progressive
compression, and the problem becomes more
complicated if flow occurs, causing continuous lossof soil mass and the formation of serious cavities.
Several cases in the world were recorded in theliterature associated with problems of structures due
to cavity formation [1]. In Iraq, many injuries wererecorded in the buildings due to the existing ofcavities. In 2004, a sudden collapse of the pumping
room and surrounding areas (tanks and stores) in the
Educational Hospital in Saladin was an example.
471

SEE - Bangkok, Thailand, Nov.11-13, 2019support the overlying material. The cover collapses
into the carven and large, funnel-shaped depressions
forms. The cover collapse happens suddenly in small,focused locations. Leaking utility pipes near thebuilding can accelerate this process and may also
cause differential settlement, as shown in Figure (1),[2].

researchers investigate the compressibility andcollapsibility of gypseous soils without considering
the existence of cavities, [6] [7], excluding therelation between the amount of gypsum dissolved andcavity volume. Thus, in this study, the authors aimed
to present an analytic model to simulate the behaviorof gypseous soil as the cavity formed related to theamount of gypsum dissolved, to estimate thereduction of the bearing capacity due to thisphenomenon.
THE FINITE ELEMENT MODELING
A general finite element program (PLAXIS 3D
TUNNEL) was selected to generate the solution. The
gypseous soils idealized as an elastic-perfect plastic
material and follow Moher-Coulomb failure criterion.
The tensile strength is used as one half of the adhesivestrength. The dilatancy angle is given to be zero sothat the volumetric strain does not change after theyield failure, and the plastic strain is obtained
according to the non-associated plastic flow rule.
The soil layer extends by a range equal twenty
times of the footing width in the all horizontal
directions measured from the edge of the footing, thedepth of this layer extends four times the footing
width measured from the surface. The purposes ofthese dimensions are to make the model is sufficiently
large to allow any possible collapse mechanism to be
developed and to avoid any influence from the model
boundaries.
The
verticalandhorizontal
displacements are fixed along the bottom, while thehorizontal displacements are fixed along the side.
Summary of the parameters used is shown in Table 1.
A square footing with dimensions of 1.0m × 1.0m and
0.25m thickness was selected. These dimensions kept
constant in exam all other parameters. The footing isassumed as a linear elastic body, and the physicalproperties are given with typical values of concrete inorder to concede the footing as perfectly rigid withmaterial modulus, Ec = 26 GPa, a unit weight, γc = 24
kN/m3, and a Poisson’s ratio, ν = 0.2.

Plate 1 Collapse of a Building in Al-Ramadi City

Fig. 1 Sinkhole formation in highly gypsiferous soils,[2].

Parameters Studied

Al-Tabba et al., [3] presented an analysis of thedeformation and failure of cavitied ground whensubjected to surface loading using model tests restingon an artificial cohesive-frictional soil containing asingle circular or square cavity. Charles et al., [4]studied the undrained stability of submerged cavities
that lead to sinkhole formation using finite element
analysis techniques in order to obtain upper and lower
bound values of suitable load parameter and thecavity was assumed to be spherical, of diameter D andcover C. The effects of the cavity on the bearing
capacity of footing were investigated by [5] using a
two dimensional elasto-plastic finite element method
using PLAXIS software. On the other hand, otherIn order to examine the effect of gypsum
dissolution and cavity formation on the bearing
capacity and settlement of the foundation, and fromresearches mentioned about the cavity formation [2],[8], [9], and [10], the following model is developed:
As the excess water from pipe leakage, irrigation,and rainfall will percolate through gypseous soil, thesoil wet, the amount and shape of the wetting patterndepend on soil type, [11]. In granular soil, the shapeof the wetting pattern will be parabola withapproximately horizontal line at the bottom, where
the water diffused in three dimensions, as shown in
Fig. 2. The water in this zone will soak and leaches
the gypseous soil dissolving the gypsum and create a
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SEE - Bangkok, Thailand, Nov.11-13, 2019

cavity.
The first case in this study represents a dry
gypseous soil with gypsum content of 60%. As thewater seepage through the soil (second case), thewetting reign will appear, and a cavity represents asize equal to the dissolving of 10% of gypsum will beformatted. Consequently, other cases represent
dissolving of gypsum of 20%, 30%, and 40%
respectively, as shown in Fig. 2.

Table 1 Soil properties used in finite element analysis
Soil property

Case 1 Case 2 Case 3 Case 4 Case 5

Gypsum content

60%

50%

40%

30%

20%

Apparent cohesion
23
17
15
12
9
c (kN/m²)
Angle of internal
41.2
35
30
25
19
friction ∅ °Modulus ofelasticity E
6*105 5*105 4*105 3*105 2*105(kN/m²)
Poisson’s ratio v

0.35

0.33

0.30

0.30

0.25

Knowing these values represent the weight of the
gypsum mass from the total soil mass, and indicatedas a variable (χ%).
In order to examine the effect of cavity positionon the bearing capacity, three offset distances fromthe footing center to the cavity center are considered(X, Y, and Z) as shown in Fig. 3. where (X) represents
the horizontal distance, (Y) represents the vertical(depth) distance, and (Z) represents the diagonal
distance. Since the cavity shape has a negligible effecton the bearing capacity for practical purposes, [5] and[12]. Moreover, cavies that forming in gypseous arealmost like a loaf. This cavity is characterized in
PLAXIS program with three parts (crown, bench, andinvert) as shown in Fig. 4. The cavity shape kept loaf
with equivalent radius (r). The volume of the cavity
is changed depending on the amount of gypsum
dissolution, as shown in Table 2.

Fig. 3 The geometric configuration of the problem

Fig. 2 Cavity shape and cases studied

Fig. 4 Geometry of loaf cavity shape473

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Cavity volume related to gypsum dissolution
Dissolution
Rate
10%
20%
30%
40%

Equivalent
Cavity Radius(r) (m)
0.2
0.3
0.4
0.5

CavityLength(m)
0.2666
0.39970.53320.6666

Table 3 Values of the BCR for different cavity
locations (X/B) and (Y/B) due to gypsum dissolution.

CavityVolume(m³)
0.03350.11300.26800.5236

Y/B
0.0 2.0 2.5
X/B
0 0.69 0.84 0.89

A quarter shape configuration for the finite
element was used, as shown in Fig. 5

Fig. 5 Finite element model of the wet zone and cavity(quarter shape)
CAVITY EFFECTS ON THE
CAPACITY FOR THE FOOTINGBEARINGThe effect of the cavity on the bearing capacity isevaluated by using the Bearing Capacity Ratio(BCR), which is the ratio between the ultimate
bearing capacity of the footing foundation with cavity
and without a cavity.

3.0

3.5 4.5

Gypsumdissolved

0.93 0.97 0.98

10.87 0.94 0.96

0.97 0.98 0.98

2

0.96 0.98 0.99

0.99 1.00 0.99

3

0.98 0.99 0.99

1.00 1.00 1.00

40

0.98 0.99 0.99
0.47 0.73 0.79

1.00 1.00 1.00
0.87 0.93 0.98

1

0.69 0.82 0.87

0.92 0.95 0.99

20.84 0.90 0.92

0.95 0.97 0.99

3

0.92 0.94 0.95

0.96 0.98 1.00

40

0.94 0.96 0.97
0.34 0.65 0.74

0.98 0.99 1.00
0.84 0.90 0.98

1

0.67 0.79 0.85

0.90 0.93 0.99

20.83 0.86 0.91

0.93 0.96 0.99

30.89 0.91 0.94

0.96 0.97 0.99

4 0.92 0.94 0.96
Y/B
0.0 2.0 2.5
X/B
0 0.21 0.53 0.64

0.97 0.99 1.00
3.0

10%

20%

30%

4.0 5.0

0.74 0.87 0.96

1

0.49 0.65 0.75

0.82 0.92 0.97

20.68 0.79 0.84

0.90 0.95 0.98

30.81 0.87 0.91

0.95 0.97 0.99

40.85 0.90 0.94

0.96 0.98 1.00

40%

Table 4 Values of the BCR for different cavity
locations (X/B) and (Y/B) due to gypsum dissolution

Effect of the Cavity Location on the Bearing
Capacity
Table 3 shows the effect of cavity location on the
bearing capacity ratio; the cavity position was
expressed by the dimensionless ratio (X/B) as thecavity move in a horizontal direction and (Y/B) which
represent the cavity location in vertical (depth)
direction. From these figures, it seems that BCR
decreases with decreasing of (X/B), or (Y/B).
Table 4 shows the values of the bearing capacity
for different locations (Z/B) and (Y/B) of the cavity
due to gypsum dissolution.
The behavior of the above relationships arereasonable, since that the reduction in bearing
capacity found when the cavity located in the active
and passive zone in soil that affects the bearing
capacity, also when the cavity found in deep layers of
soil, the effect may be disappearance, which confirms
the stress distribution in the soil.

474

Y/B
0.0 2.0 2.5
Z/B
0 0.69 0.84 0.89

0.93 0.97 0.98

1.5 0.89 0.95 0.97

0.98 0.98 0.99

2.5 0.96 0.98 0.99

0.99 0.99 0.99

3.5 0.98 0.99 0.99

1.00 1.00 1.00

0 0.47 0.73 0.79
1.5 0.73 0.85 0.89

0.87 0.93 0.98
0.93 0.96 0.99

2.5 0.87 0.93 0.95

0.96 0.98 0.99

3.5 0.93 0.96 0.98

0.99 1.00 1.00

4.5 0.94 0.97 0.98
0 0.34 0.65 0.74

0.99 1.00 1.00
0.84 0.90 0.98

1.5 0.71 0.82 0.87

0.91 0.95 0.99

2.5 0.85 0.90 0.93

0.95 0.98 0.99

3.5 0.91 0.93 0.96

0.98 0.99 1.00

4.5 0.93 0.96 0.97

0.99 1.00 1.00

3.0

3.5 4.5

Gypsumdissolved

10%

20%

30%

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 4, cont.
Y/B
0.0 2.0 2.5
Z/B
0 0.21 0.53 0.64

0.74 0.86 0.92

1.5 0.54 0.71 0.78

0.85 0.93 0.96

2.5 0.72 0.83 0.88

0.92 0.96 0.99

3.5 0.81 0.92 0.95

0.97 0.98 1.00

4.5 0.85 0.94 0.97

0.98 0.99 1.00

3.0

than 5.0, so that the BCR may be reached 1.0. The
amount of gypsum dissolution affect the BCR, andthe dangerous case may be found when the cavity
formed near the footing center (X/B and Y/B less than2.0) and when the amount of gypsum dissolved
exceeds 30%. The cavity size has a significant effecton the BCR; low values of BCR were found for large
cavities. The volume of the cavity has little affect on
BCR when the value of (X/B) and (Z/B) more than
4.0. From the results of this study, the minimum
values of factor of safety for the foundation design in
gypseous soils must be not less than 1.5, 2.5, 3.0, and4.75 when the gypsum contains these soils are 10%,
20%, 30%, and 40% respectively.

4.0 5.040%

From these Tables, it is clear that as the amount of
gypsum dissolved increased, the BCR decreased. The
reason behind this behavior can be attributed to theamount of gypsum dissolved, which leads to reducethe bonding between particles and the reduction instrength parameters. The reduction in the BCR isalmost low when the amount of the gypsum dissolved
less than 10% and when the cavity located at depth
more than three times the foundation width. However,if the cavity position is shallow ((Y/B) less than 2.5)
and the amount of gypsum dissolved more than 20%,the value of BCR may reach 0.6. The dangerous casemay be found when the cavity formed near the footing
center (X/B and Y/B less than 2.0) and when theamount of gypsum dissolved exceeds 30%.

Fig. 6 Variation of BCR with cavity volume andcavity position (X/B) for depth ratio (Y/B=0).

Effect of the Cavity Volume on the Bearing
Capacity
The variation of the BCR with the cavity volume
and ratios (Y/B) and (X/B) were shown in Figs. 6 to9, while the variation of the BCR with the cavity
volume and ratios (Y/B) and (Z/B) were shown in
Figs. 10 to 13. The curves in these figures show a
reduction in the BCR as the dimensionless value(Y/B) decreased, this foundation for all cases of (X/B)
and (Z/B). Also, these figures indicated that thevolume of the cavity has little affect on BCR whenthe value of (X/B) and (Z/B) more than 4.0.

Fig. 7 Variation of BCR with cavity volume andcavity position (X/B) for depth ratio (Y/B=2).

CONCLUSIONS
Based on the main results obtained from nonlinear analysis using the finite element method in thisstudy, the following conclusions are drawn:
The cavity location found to be the mostparameter that affects the BCR. The minimum values
are found when the cavity locates at the center of thefooting base, and the lowest one (0.211) when the
gypsum dissolved equally to 40%. There is no effectof the cavity location when the ratio of (X/B) and(Z/B) exceed (3.0) for any depth and when the
gypsum dissolved less than 10%. For high gypsum
dissolution (more than 30%), the dimensionless ratios(X/B), (Z/B) and (Y/B) of the cavity must be more

Fig. 8 Variation of BCR with cavity volume andcavity position (X/B) for depth ratio (Y/B=3).
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 9 Variation of BCR with cavity volume andcavity position (X/B) for depth ratio (Y/B=4).
Fig. 13 Variation of BCR with cavity volume andcavity position (Z/B) for depth ratio (Y/B=4).

REFERENCES[1] Wang, M. C., and Badie, A., Effect ofUnderground Void on Foundation Stability.
Journal of Geotechnical Engineering, ASCE, Vol.
111, No. 8, 1985, pp. 1008-1019.
[2] Al-Khafaji, A.N., Some Chemical Properties ofSouth Al-Jazira Irrigation Project. Soil Report
Submitted to Dijla Irrigation Center, Mosul, Iraq
1990.
[3] Al-Tabbaa, A. and Russell, L. and O’Reilly, M,
Model Test of Footings above Shallow Cavities,
Ground Engineering, October 1989, pp. 39-41.
[4] Charles, E. A., Lyamin, A. V., and Scott W. S.,
Prediction of Undrained Sinkhole Collapse.
Journal of Geotechnical & Geoenvironmental
Engineering, ASCE, Vol. 129, No. 3, 2003,
pp.197-205.
[5] Peng, F. L., Kiyosumi, M., Ohuchi, M., &Kusakabe, O., Cavity Effects on the Bearing
Capacity of Footing Foundations and the
Calculation Method. ASCE, UndergroundConstruction and Ground Movement (GSP 155),
2006, pp.50-57.
[6] Al-Obaidi, A. A. H. and Al-Mafragei, I. H. S.,
Settlement and Collapse of Gypseous Soils. Tikrit
Journal of Engineering Sciences, Vol. 23, No. 1,
2016, pp. 20-31[7] Fattah, M. Y., Al-Ani Mohammad M., and AlLamy M. T. A., Wetting and Drying Collapse
Behavior of Collapsible gypseous Soils Treatedby Grouting. Arabian Journal of Geosciences,
2015 8:2035-2049.
[8] Sputo, T. Sinkhole Damage to Masonry Structures.
Journal of Performance of Constructed Facilities,
ASCE, Vol.7, No.1, 1993, pp. 67-73.
[9] Augarde, C. E., Lyamin, A. V. and Sloan, S W.,
Prediction of Undrained Sinkhole Collapse.

Fig. 10 Variation of BCR with cavity volume andcavity position (Z/B) for depth ratio (Y/B=0).

Fig. 11 Variation of BCR with cavity volume andcavity position (Z/B) for depth ratio (Y/B=2).

Fig. 12 Variation of BCR with cavity volume andcavity position (Z/B) for depth ratio (Y/B=3).

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Journal of Geotechnical and Geoenvironmental
Engineering, ASCE, Vol. 129, No. 3, 2003, pp.
197-205.
[10] Kaufmann J. E., Sinkholes. A study Submit to
U.S. Department of the Interior. Geological
Survey. Mid-Continent Geographic Science
Center, 1400 Independence Road. Rolla, Missouri
65401, 2007.

[11] Al-Dulaymi A. A., A Laboratory Study of Water
Movement in Homogeneous Soils from a Deep
Irrigation Pipe Hole with Constant Flow Rates.
PhD Thesis, Water Resource Engineering
Department, University of Mosul, Iraq, 2007.
[12] Baus, R. L., and Wang, M. C, Bearing Capacityof Strip Footing above Void. Journal of the
Geotechnical Engineering Division, ASCE, Vol.
109, No. 1, 1983, pp. 1-14.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Thailand, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106018 C3051

A STUDY OF THE EFFECTS OF THE FLOOD IN 2554 ON
AGRICULTURAL MACHINERY USE IN RICE PADDY FIELDS IN
PATHUMTHANI PROVINCE
Dowroong Watcharinrat1
Faculty of Agricultural Technology ,Division of Crop Production,
Rajamangala University of Technology Thanyaburi ,Thailand

1

ABSTRACTIn the year 2554, Thailand experienced devastating flooding in the northern and central regions of thecountry. The objective of this research was to study the effects of this flooding on agricultural machinery use inrice paddy fields. The sample population were farmers from seven districts in Pathumthani Province: Muang,
Lamlukka, Nong Suea, Sam Khok, Thanyaburi, Klong Luang and Lad Lum Kaew. The research was conductedfrom January to April 2014. A group of 100 rice farmers were randomly selected by district. Each district
provided a group of 14 to 15 farmers for a total of 100. The questionnaire was created by the researcher with thehelp of three experts in agricultural machinery and research. The questionnaire consisted of general backgroundinformation about the farmers as well as the tools they used, such as soil preparation tools, maintenance tools,
harvesting tools and post-harvesting tools. Seven students functioned as research assistants and were trained inmethods of data collection, questionnaire development and interviewing in order to solicit answers from thefarmers. The results of this study showed that the farmers were primarily males between the ages of 41 and 60
with secondary education as the highest education level reached. Most of the farmers in the random sample of
100 used some sort of agricultural machinery. The use of agricultural machinery was widespread and 94% of the
farmers made a direct link between the use of machinery and the profitability of their rice paddy fields. It was
found that 95% of these farmers claimed that the productivity in rice farming before and after the flood showed
no difference.
Keywords: Rice field, Agricultural machinery, Farm machinery, Flood effect
INTRODUCTION
effectively regain previous yield levels, the methodsof production employed by the farmers needed to bestudied. These studies revealed those aspects of the
farmers’ operations that best affected the quality andyield production of rice. Moreover, this information
could lead to a sustainable career in farming by
developing a variety of agricultural methods andmanagement processes based on a community’s
needs. The farmers should be involved in theconsideration of and decision-making about how tomanage the rice production process most efficiently
and effectively. This will lead to the cooperation of
all sectors that have a role in this process.
Therefore, this research analyzed rice production
factors that affected the model of utilization ofagricultural tools. The knowledge that was gained
from this survey can be used to plan thedevelopment of rice production in the areas thatwere affected by the flood. This will lead to a stableself-reliance.

The major flood which occurred in 2554 had agreat impact on a wide area of agricultural fields
around the lowland areas of Thailand. Especiallyrice fields in these areas were severely affected. The
areas covered by Pathum Thani Province, which
includes 7 districts, namely Muang District, Klong
Luang District, Thanyaburi District, Nong Suea
District, Lat Lum Kaew District, Lam Luk Kaew
District and Sam Khok District, were classified as
areas that were affected by the flood at that time.
Besides affecting the general condition of theenvironment, rice yields in these areas were also
affected. As the rice paddy fields were flooded, they
were not able to meet their expected production.
Therefore, farmers lost huge amounts of revenue asa result of the flood. However, once the flood waters
receded, farmers started farming again to generate
income for their families. In the efforts to restore theaffected areas, it was necessary to understand thepatterns of usage of agricultural machinery.
Effective tool usage became a critical factor in
preparing the areas once again and maximizing thoseareas’ productivity. By recognizing these factors,
farmers were able to fulfill their needs as a whole.
So in order to reclaim these rice paddy fields and

PURPOSE/ OBJECTIVE
1. To know the patterns of agricultural
machinery use in paddy fields before and after theflood.
478

SEE - Bangkok, Thailand, Nov.11-13, 2019

2. To evaluate the efficiency of agricultural
machinery for rice field management and riceproduction.

province and covered seven districts which haveagricultural farming groups. The data collectedspanned a four month period, from January to April
2014.

LIMITS OF THE RESEARCH PROJECTEXPERIMENTAL RESULTS
This research studied only rice paddy fields thatwere farmed with agricultural machinery in Pathum
Thani Province.

The research questionnaire was given to a totalof 100 respondents from the following seven
districts in Pathumthani province: Muang, Samkhok,
Lamlukka, Thanyaburi, Klong Luang, Nong Suea
and Lad Lum Kaew. The results can be summarized
as follows:

EXPECTED BENEFITS
To understand the patterns of agricultural
machinery use in farmers’ rice paddy fields, such as
the methods of selection, purchase and efficient useof this machinery for farming.

Table 1 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by gender (sex)EQUIPMENT AND METHODS
Men
71

This study relied on a survey on agricultural
machinery use in flooded paddy fields in Pathum
Thani province which covers 7 districts, namely
Muang District, Klong Luang District, Thanyaburi
District, Nong Suea District. Lat Lum Kaew District,
Lam Luk Kaew District and Sam Khok District.

Women
29

Total
100

From Table 1: Based on the 100 respondents to
the research questionnaire, it was found that most ofthem were male (71 males to 29 females).
Table 2 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by ageSTUDY METHODS
1). Studied opinions and patterns of utilization ofagricultural machines used in rice fields and theirimpact on rice production.
2). Collected survey data via a questionnairefrom a random sample of 100 rice farmers from 7
districts with 14 to 15 farmers in each district torepresent the study area.
3). Produced a questionnaire which consisted offarmers’ general information and their use of
agricultural machinery in rice farming. All of thiscovered 5 options such as soil preparation tools,
cultivation tools, maintenance tools, harvesting tools
and other tools. This survey tool was developed byasking and getting advice from experts inagricultural machinery and research.
4). Analyzed the data obtained by using
statistics, percentage and mean. Other factors
analyzed were agricultural machinery use in rice
farming, patterns of efficient agricultural machinery
use and participation in selecting, purchasing andusing agricultural machinery.

Less
than
30

3140
year

4150
year

5160
year

6170
year

2

13

30

40

14

More
than
70
year
1

Total

100

From table 2: According to the answers from the
100 respondents to the research questionnaire, mostwere in the age group of 51-60 year olds (40people). The next largest group were the 41-50 year
olds (30 people). The rest of the groups were as
follows in descending order: 61-70 year olds (14people), 31-40 year olds (13 people), less than 30
years old (2 people) and more than 70 years old (1person).
Table 3 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by education

DATA ANALYSIS
Data were presented in the form of tables,
frequencies and percentages together with narration
based on the questionnaire results for each item.

PrimaryschoolSecondaryHigh
SchoolDiplomaBachelor's
Degree or
above

Total

48

33

12

7

100

From Table 3: According to the answers from the
100 respondents of the research questionnaire, 48 of
the respondents completed primary school, 33
completed secondary-high school, 12 completed a
diploma, and 7 completed a Bachelor’s degree.

LOCATION AND DURATION
The area of this study was in Pathum Thani
479

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 4 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by the number of household membersLessthan 3
people43-5people6-8people9-11
people

51

38

6

More
than 11people1income of 400,001-500,000 baht, 10 had a net
income of 100,000-200,000 baht, 9 had a net incomeof 500,001-600,000 baht, 6 had a net income of
600,001-700,000 baht, 3 had a net income of lessthan 100,000 baht and 3 others had a net income ofmore than 800,000 Baht and 1 had a net income of
700,001-800,000 baht.

Total
100

Table 8 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by number of times farming / year

From Table 4: According to the answers from the
100 respondents of the research questionnaire, 51
families had 3-5 members, 38 families had 6-8
members, 6 families had 9-11 members, 4 families
had less than 3 members and 1 family had more than
11 members in the family.
Table 5 Questionnaire data on agricultural
machinery utilization in rice paddy rice fields
classified by other occupations than farming
Farmers

Contractors

Trading /Business

26

39

16

Employees Government
officials /stateenterprises

12

Others
.....

7

Total

100

4160
rai

6180
rai

81100
rai

101120rai

121140rai

141160
rai

37

25

8

2

1

1

0

More
than
160
rai
6

200,
001300,
000
baht
26

300,
001400,
000
baht
28

400,
001500,
000
baht
13

500,
001600,
000
baht
9

600,
001700,
000
baht
6

700,
001800,
000
baht
2

More
than
800,
000
baht
3

18

79

More
than 3
time
3

Total
100

Profit94

The same
5

Total
100

From Table 9: According to the answers fromthe 100 respondents of the research questionnaire,
94 made a profit from farming, 5 said that profit andinvestment were equal and 1 farmer made no profit
in rice farming.

Total

Table 10 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by farming yield.

100

Before thefloodbetter2

After theflood
better3

not different

Total

95

100

From Table 10: According to the answers fromthe 100 respondents of the research questionnaire,
95 farmers answered that there was no significant
difference between the pre-flood and post-flood
periods, 3 farmers said the post- flood period was
better than the pre-flood period and 2 said the preflood period was better than post-flood period.

Table 7 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by net income / year
100,000200,
000
baht
10

0

Loss
1

From Table 6: According to the answers from the
100 respondents of the research questionnaire, 37
had a farming area of 20-40 rai, 26 had less than 20
rai, 25 had 41-60 rai, 8 had 61-80 rai, 6 had morethan 160 rai, 2 had 81-100 rai, 1 had 101-120 rai andno one had 121-140 rai.

Less
than
100,
000
baht
3

3.timeTable 9: Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by profitability in farming

Table 6 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by farm size
2040
rai

2. timeFrom Table 8: According to the answers from the
100 respondents of the research questionnaire, 79
farmers farm 3 times a year, 18 famers farm 2 times
a year, and 3 farmers farm more than 3 times a year.

From Table 5: According to the answers from the
100 respondents of the research questionnaire, 39
were general hired contractors, 26 were employed in
the field of agriculture, 16 were in trading/private
business, 12 were company employees and 7 weregovernment officials / state employees.

Less
than
20
rai
26

1. timeTo
tal

Table 11 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by the type of property used for farming

100

From Table 7: According to the answers from the
100 respondents of the research questionnaire, 28
had a net income of 300,001-400,000 baht, 28 had a
net income of 200,001-300,000 baht, 13 had a net
480

Own

Hire

81

4

Own and
rent
15

Total
100

SEE - Bangkok, Thailand, Nov.11-13, 2019

farmers thought by themselves, 3 farmers asked
fellow farmers in the community and 46 farmers
both thought by themselves and asked fellow
farmers in the community.

From Table 11: According to the answers fromthe 100 respondents of the research questionnaire,
most of the respondents, 81 had their own property
for rice farming, 15 had their own and rented
property for farming and 4 farmers rented property
for farming.

Table 15 Patterns of agricultural machinery
utilization in rice farming classified by type oftillage tool

Table 12 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by efficiency of agricultural machinery utilization
for rice farming.
Excellent
72

Good
25

Fair
3

Little0

Least
0

Tillage
Equipment

Total
100

1.Twowheeled
tractor2. 4 wheel
tractor, 2wheel drive
3. Fourwheel-drive
tractor
4. E-mill(rollers,
mixers,rollers)
5. Plowhead
6. Plow
7. Plowchisel8. Scoop
9. Twist
10.
Spinning
11. Capitaldrag (Lube
Lane board)
12. Rake

From Table 12: According to the answers fromthe 100 respondents of the research questionnaire,
72 commented that the efficiency of using
agricultural machinery in production was excellent,
25 commented that it was good and 3 commented
that that the efficiency of using agricultural
machinery in rice production was fair.
Table 13 Questionnaire data on agricultural
machinery utilization in rice paddy fields classified
by district
District
1. City
2. Lum Lukka
3. Thanyaburi
4. Klong Luang
5 . Nong Seua
6 . Lard lumkaew
7. Sam khok
Total

Number
15
14
14
14
14
14
15
100

32

68

4

28

0

36

64

5

31

0

100

0

19

81

0

4

96

0

4

0

9
0

91
100

0
0

9
0

0
0

12
99
100

88
1
0

0
7
25

12
92
69

0
0
6

100

0

8

85

7

100

0

23

69

8

From Table 15:
The use of agricultural
machinery for rice farming type of tillage tool
showed that 65 farmers used two-wheel walking
tractors, 35 didn’t use walking tractors, 7 farmers
hired a contractor with a 2-wheel tractor pattern and
58 had their own. There were 32 farmers who used 4
wheel tractors with 2 wheel drive, 68 farmers didn’t
use 4 wheel tractors with 2 wheel drive, 28 farmers
used the pattern of hiring a contractor with a 4 wheel
tractor with 2 wheel drive and 1 farmer already had
a 4 wheel tractor with 2 wheel drive. There were 36
farmers who used a 4 wheel tractor with 4 wheel
drive, 68 farmers didn’t use a 4 wheel tractor with 4
wheel drive, 5 farmers used the pattern of hiring acontractor with a 4 wheel tractor with 4 wheel driveand 31 farmers had their own 4 wheel tractor with 4
wheel drive. There were 19 farmers who used e-rolls(rollers, mixers, rollers) all forms use e-rolls (rollers,
mixers, rollers), 19 farmers hired a contractor and 81
had their own. Four farmers used plow heads and 96
did not use plows with heads. Nine farmers used
plows without heads, 91 farmers did not use plows
without heads and 9 farmers used the plow pattern.
Twelve farmers used scraping dishes, 88 farmers did

From Table 13: According to the answers fromthe 100 respondents of the research questionnaire,the 7 districts in Pathum Thani Province weredivided as follows: 15 farmers were from Muang
district and Sam Khok district, and 14 farmers werefrom Lamlukka, Thanyaburi, Khlong Luang, Nong
Suea and Ladlumkaew districts.
Table 14 Test data for using and purchasing
agricultural machinery classified by participation
Participation
1.Think by themselves
2. Ask fellow farmers in
the community.
3.Think by themselves
and ask fellow farmers in
the community
Total

Usage pattern of agricultural machineryDohiring a
Their
Hire
not
contractor
own
contractors
use
and their
own
65
35
7
58
0

use

Number
47
3
46

100

Table 14: According to the answers from the 100
respondents of the research questionnaire, 47
481

SEE - Bangkok, Thailand, Nov.11-13, 2019not use them and 12 farmers had their own. There
were 99 farmers who used a twist, 1 farmer did not,7 farmers hired a contractor pattern and 92 had theirown. All farmers used spinning, 25 farmers hired, 69
had their own and 6 hired and had their own. All
farmers used the capital to drag (Lube Lane boards).
For use of capital drag (Lube Lane Board), 8 farmers
hired, 85 had their own and 7 farmers hired and had
their own. All farmers used rakes, 23 farmers used ahire pattern, 69 had their own and 8 farmers hired
and had their own.
Table 16 Patterns of agriculturalutilization in paddy cultivation
Planting
Equipment

Table 18 Agricultural machinery utilization in rice
fields classified by type of harvest toolmachinery
Harvesting
Equipment

Usage pattern of agricultural machinery
Use

1. Seedermachine2. Sowingmachine3.
Transplant
rice
seedlings

1 did not, 38 farmers hired manure spreaders and 54
hired contractors and had their own. There were 96
farmers who used pump units, 4 farmers did not, 18
used a hire pattern and 78 had their own. There were
93 farmers who used lawn mowers, 7 farmers did
not, 4 used hire pattern and 89 had their own. There
were 4 farmers who used weeding machines, 96
farmers did not, 4 farmers used a pattern of hiring
weeding machines.

Do
not
use

Hiring a Their
contractor own

0

100

0

0

Hire acontractor
and their
own
0

100

0

38

54

8

11

89

3

8

0

1. Combine
harvester
2.Threshingmachine
3.Harvester
4. Turbine

Usage pattern of agricultural machineryUse
Do notHirin Their
Hire ause
gaown
contractor
contr
and their
actor
own
3
97
0
3
0
3

97

0

3

0

97
5

3
95

89
0

8
5

0
0

Table 18: Agricultural machinery utilization inrice fields classified by type of harvest tool foundthat 3 farmers used combine harvesters, 97 farmers
did not, 3 farmers used a hire pattern. There were 3
farmers who used threshing machines, 97 farmers
did not, 3 used the pattern of hiring threshingmachines. There were 97 farmers who used combine
harvesters, 3 farmers did not, 89 used a pattern of
hiring a contractor and 8 farmers had their own.
There were 5 farmers who used milling machines,
95 did not and 5 farmers used their own millingmachines.

From Table 16: The use of agricultural
machinery for rice cultivation found that no farmers
used a seeder, 38 hired a seeder pattern, 54 had theirown seeder and 8 hired and had their own. There
were 11 farmers who used drones, 89 did not use
drones, 3 farmers hired a contractor and 8 had theirown.

Table 19 Patterns of agricultural machinery use inrice farming classified by other types of tools
Table 17 Patterns of agricultural machinery
concerning maintenance tools used in rice farming
Crop
Protection
andFertilizing
Equipment
3.1 Sprayer
3.2 Manure
spreader3.3 Pump
3.4 Lawn
mower
3.5
Harvesting
weeds

Other
Equipment

Usage pattern of agricultural machinery
Do
Hiring a
Their
Hire anotcontractor
own
contractor
use
and their
own
98
2
37
54
7
99
1
38
54
7

Use

96
93

4
7

18
4

78
89

0
0

4

96

0

4

0

1. Rice mill
2. Dehumidifier
3. Mower

Usage pattern of agricultural machineryus
Do notHire aTheir
Hire ae
use
contracown
contractor
tor and
their
own
11
89
4
7
0
2
98
0
2
0
7
93
0
7
0

Table 19: Patterns of agricultural machinery
used in rice farming classified by other types oftools: 11 farmers used rice mills, 89 did not use ricemills, 4 hired and 7 farmers had their own. There
were 2 farmers who used two desiccators, 98 did not
and 2 had their own desiccators. There were 7
farmers who used rice straw mills, 93 did not and 7
farmers had their own rice straw mills.

From Table 17: The use of agricultural
machinery concerning maintenance tools in rice
farming found that there were 98 farmers who used asprayer, 2 did not, 37 hired a contractor, 54 had theirown and 7 hired a contractor and had their own.
There were 99 farmers who used manure spreaders,

EXPERIMENTAL RESULT CONCLUSION
According to this study on rice planting with
482

SEE - Bangkok, Thailand, Nov.11-13, 2019agricultural machinery, it was found that most
farmers, around 81%, had an education backgroundthat included primary and secondary schools, around
62% had a planting area of between 20-60 rai,around 81% had their own planting area, around
55% of the farmers had a net income of between
200,000-400,000 and around 79% planted rice 3
times per year. Agro-based agricultural machinery
was seen as performing better than other methods.
And the process of choosing agricultural machineryor buying agricultural machinery was conductedboth by the farmers thinking for themselves andconsulting a farmer in the community about issues
such as a tractor walks, the tractor seat drive(clutching rollers), the drag capital (lump lane)
maintenance tools such as fertilizer spreaders andsprayers. The villagers bought machinery forthemselves and usually hired a contractor rather thanbuying for themselves.

that using agricultural machinery over other methods
was more efficient and had greater rice production
as well as saved time, expenses and reduced labor
issues. Moreover, agricultural machinery contributed
to more frequent planting (3-4 times a year). The
flood conditions in 2554 had no effect on riceproduction. Farmers said that before and after theflood, their yield did not change in Pathumthani
province. They mostly relied on irrigation on boththe left and right sides of the Chaopraya river which
includes the Rapeepat and Rangsit canals. Most
farmers had their own tractors which could also be
used in other capacities, such as a trucks for tillage
or pumping and even for travel. For harvestingmachines, farmers commonly rented more than theypurchased due to the relatively high prices.
REFERENCES[1] Department of Agriculture ,2012. Rice researchsrtagety ,2012-2016. Source :www.it.doa.go.th/kasikorn/year53/jan_feb.../part-1.pdf, 14 May 2013.
[2] Kasem Jankaew . 2011. Environmental Science.
5th. Kasetsart University, Bangkok.
[3] Chayan Wattanaphuti . 1991 .Concept ofResearch,Research for Job Development,Instituteof Research and Development,Kkon khaen
University[4] Parichart Walaisatien. 2000. Process ofDevelopment. Office of Research Fund,
Bangkok.
[5] Rungreung Kalsirisilk .2004. Using ofAgricultural Machinery in Pathumthani
Province,Research Report ofAgricultural Machinery
Department,Rajamangala University ofTechnology Thanyaburi[6] Financial of Pathumthani Province,2011,Reportof Econmics for Pathumthani,2012,Source:www.klang.cgd.go.th/ptt/cfo_doc/economy/mcq3[7] Rice Research Institutehttp://www.arda.or.th/kasetinfo/rice/rice_cultivat
e_machine/rice-cultivate_cultivate_machine_index.html[8] Samerkwan Tantikul.2007. Farm
Machinery,.Bangkok.The Knowledge
Center,December,2007.
[9] Rawat Phitaksakul2 . 003.Using of Agricultural
Machinery in Lopburi Province,Kasetsart
University.

RECOMMENDATIONS
1. Study the effects of using farm machinery thatis produced domestically versus from abroad
2. Study the benefits of using agricultural
machinery for drowning and sowing
3. Study the economic returns on using
agricultural machinery three times a year and twotimes a year
DISCUSSION
According to this study on the impact of using
agricultural machinery when planting rice, it was
found that 81% of farmers finished primary andsecondary school. If their education was greater thanthis, they would be counted in the industrial orservice sector which requires more knowledge tofind money for funds for labor costs in rice planting.
Some rice farming families worked in rice fields
only on the weekends and used charter methods inevery stage rather than doing it by themselves.
About 62% of rice farmers used agricultural
machinery, farmed a planting area of 20-60 rai andfarmed around 2-4 times a year in Pathumthani
province. This province which is in the central
region of Thailand has many rice fields because it isa low-lying area suitable for rice planting. This area
is located in an irrigation zone that does not have
many water issues and can therefore offer a main
career or part time job in farming. This vast amountof rice farming areas is suitable for using
agricultural machinery. Many rice farmers replied483

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DESIGN AND IMPLEMENT A MONITORING SYSTEM OF TRAFFIC
SIGNAL USING MICROCONTROLLER DEVICES
Aleksander Purba1, Rahayu Sulistyorini1, Agung Ilhami1 and Ageng Sadnowo Repelianto 1
1
Faculty of Engineering, University of Lampung, Lampung Indonesia

ABSTRACTThis project focused on designing traffic signal monitoring tools, based on ideas and concepts developed
previously. Authors used the Arduino Nano module with ATmega328P as the microcontroller, which was chosenbecause it simplifies the scenario of traffic signal anomalies, short messages service (SMS) news content, and time
settings. A microcontroller was used to process data from the interference detection result, and processing the SMS
content, therefore, it is able to quickly inform the types of traffic signal disruptions. Based on result findings it ispossible to utilize this development in building an integrated traffic signal monitoring system services, in the formof mobile applications in the near future.
Keywords: Monitoring system, Traffic signal, Microcontroller, Malfunctioning, Short message service

passing automobile, causes the phase to extend. This
continues as such up to the point where either the
traffic demand ceases and another approach gains
green, or a conflicting demand causes the maximum
timer to count down. Moreover, while vehicle
actuation mode is more responsive than fixed time it
also has the propensity of being inefficient ininstances where long queues build up on conflicting
approaches. The setting of maximum timers is thendifficult due to changes in traffic patterns throughjunctions over time, which should therefore be
regularly updated, in order to maintain effective
operation. This is a labor intensive task for a local
transportation authority, which is often notundertaken, thus leading to the signals becoming lesseffective over time.
As all electronic equipment, these devices are
subject to breakdowns, malfunctions, and power
outages, which could lead to safe intersections
becoming dangerously congested and confusing,
therefore resulting in needless accidents. However, a
study on the city of Boston calculated that simply
reconfiguring the timings of 60 intersections in one
district of the city could save US$1.2 million per year,
in terms of person-hours, safety, emissions, andenergy costs [1]. In situations where malfunctioning
occurs, the entity responsible for maintaining thesignal may be held accountable, as regions andmunicipalities have a statutorily imposed duty, which
ensure roads are safe for users. Furthermore, theProvince of Ontario has set up certain minimum
requirements for the maintenance of roadways, which
include standards related to traffic signals, according
to Regulation 239/02, which states the Minimum
Maintenance Standards for Municipal Highways,
under the Municipal Act. However, section 13 of the
O.Reg 239/02 stipulates that in cases where a

INTRODUCTION
Traffic signal infrastructure is responsible forassigning the right of way to vehicular and pedestrianpassage at intersections. Meanwhile, its management
and operations requires the proper design, location,
operation and maintenance, to provide safe andefficient movements. A lot of mysteries surround its
mechanism of action, although they are relatively
simple as the installation comprises of traffic signal
heads, detection and a controller, which is the ‘brains’
behind the equipment, containing the information
required to force the lights through various sequences.
These signals run under a variety of modes,
dependent on location and time of day, which under
fixed time operation, displays green to each approachfor the same amount of time per cycle, regardless ofthe traffic conditions.
This may be adequate in heavily congested areas,
while instances where a lightly trafficked side road isincluded within the sequence, the system becomesvery wasteful, as no vehicles are waiting in somecycles, and the time could be better allocated to thebusier approach. Vehicle actuation is one of the mostcommon modes of operation, and as the namesuggests, it takes into account demands on all
approaches and also adjusts the green time
accordingly. Furthermore, the requirements toactualize this mechanism are registered through thedetection installed, either in the carriageway or above
the signal heads, which the controller processes andfurther allocates the green time in the mostappropriate way.
However, minimum and maximum periods are
specified, and this cannot be violated, therefore, avehicle passing a detector demands a certain phaseand once that phase is green, any subsequently
484

SEE - Bangkok, Thailand, Nov.11-13, 2019malfunctioning traffic control signal system occurs,
the minimum guideline is to “deploy resources assoon as practicable after the awareness of the defect,in order to commence repairs or replacements” [2].
Meanwhile, most regions and municipalities have nostatutory in this regards as Ontario, and due to the factthat most of the traffic signals are categorized as
isolated intersections, the surveillance system istherefore highly dependent on road users report.
Hence, response time needed is longer, especiallyduring out of work hours.
This project focused on designing traffic signal
monitoring tools, based on ideas and concepts
developed from the research conducted by Sivarao et
al. [3] and Anita Ahmad et al. [4], as well as selfdiagnosis techniques, using the Reed-Solomon Codes
by Tang and Wang [5]. Furthermore, a monitoring
system with Proteus advancement tool, developed in
Africa, was also used [6]. However, activities
including designing concepts, materials selection,assembling tools, and traffic signal monitoring
systems testing are rarely performed.

RESEARCH METHODOLOGY
The product was designed based on electronic
circuit plan, where all blocks were arranged on the
project board and tested individually, and also a
combination on printed circuit board (PCB) was
conducted, at periods of proper function. This study
used the Arduino Nano module with ATmega328P as
the microcontroller, which was chosen because it
simplifies the scenario of traffic signal anomalies,
short messages service (SMS) news content, and time
settings.
This also facilitates programming, possesses amemory capacity that is capable of accommodating
program scripts, it is affordable, readily available, andis relatively small in size.
However, programming was carried out using thebuilt-in Arduino IDE open-source software, and thegeneral description of electronic circuit design is seenin Fig. 1 as developed previously [7, 8, 9].

Start

Design concept
Data collection andanalysis

Casinginstallation

Making a system
circuit scheme

End

Literature review

System model design

No

Selection of component

Fitting a PCB
circuit system

Assembling prototype
on the project board

Solderingcomponent to PCB

Testing prototype
on the project board

Install program into
microcontroller

Design suitablefor prototyping?

Yes

No

Is the systemrunning smoothly?

Yes

Fig. 1 Design circuit flow chart
based on the rational state, guard time and verificationof the programming anomaly scenario. Furthermore,
the microcontroller recognizes the anomaly and
immediately turns all traffic signal display (red,yellow and green) off. Meanwhile, during thetermination process, the microcontroller instructs the
A6 GSM module to dispatch an SMS, at certain time

RESULT AND DISCUSSION
Each traffic signal display is equipped with a formof light sensor, positioned in a way, in order to detectbeams from the traffic signal. This is then processedby the logic gate and microcontroller to be diagnosed,

485

SEE - Bangkok, Thailand, Nov.11-13, 2019

intervals, according to the program (e.g., once everyhour). Therefore, the emergency light flashes
periodically, serving as a visual marker, whichindicates that the signal is under repair. Hence,
mobile or smartphones can be used as an SMS
receiver by entering the recipient's number from thetraffic signal in the microcontroller program.
Switching mode power supply (SMPS) with DC
12V 10A voltage was used as the main source. This

voltage was chosen to supply the relay and a series of
LED lights on the traffic display and emergency flash.
In addition, step-down DC to DC buck converter was
also applied by reducing the DC 12 Volt voltage fromSMPS to DC 5V 3A, which was further used tosupply logical state, guard time, data latch, reflected
light sensor, GSM A6 module, and themicrocontroller as shown in Fig. 2.

Fig. 2 Devices diagram block4. The logical state block is an electronic path,
which uses an integrated circuit (IC) type CD4028(BCD to decimal decoder), designed to identify
different bits of each sequence of statement traffic
signals, in cases of anomaly. Furthermore, the input
pin of this IC is a 4-bit binary number (from 0000 to1111), while the output pin is represented by 10 digits(Y0 to Y9). The following are some identity bits
designed for each traffic signal anomaly statement:
4.1. the red display is given the 0101-bit,characterized by pin Y5.
4.2. the amber demonstration specifies the 0011bit, represented by pin Y3.
4.3. the green exhibition is allotted the 0111-bit,denoted by pin Y7.
5. Guard time block: Anomalous data Y5, Y3,
and Y7 cannot be considered valid when in the guard
time series, which was allotted a time period of 1
second in this study. For example, if Y5 sends an

Referring to Fig. 2, a design of electronic seriesconsists of some blocks:
1. The traffic signal display block consists ofthe combination of a series of light emitted diode(LED) illuminations (red, amber and green), andplaced between them are three light dependent
resistor sensors (LDRs), used to detect reflections
produced by LEDs and other reflectors.
2. The emergency flash display block consistsof a combination of LED beams, functioning as visual
markers, and the main traffic signal, during the repair
process.
3. Reflection sensor block. The readings ofeach LDR (red, amber, and green) are entered into
three voltage comparator circuits. Therefore, if it
obtains reflected light, the sensor produces a LOW
logic, and on the contrary, a HIGH logic is emitted in
the absence of reflected light.
486

SEE - Bangkok, Thailand, Nov.11-13, 2019

under-1 second-anomalous signal, it is not considered
an anomaly and vice versa.
6. Latch data block: After the validity of theanomaly signal has been considered, the block is thenlocked (latch). This is further processed by the
microcontroller, at the end of a cycle of traffic signal.
7. Microcontroller block: This is divided into
five sub-blocks with their respective functions,
including:
7.1. timing traffic signal functions as a time
allocator per cycle.
7.2. Provision of additional bit function forCD4028 IC input (logical statement block), in
determining bit during an anomaly.
7.3. Anomaly data verification scenario, throughthe process of matching results of processing data
latch blocks with anomalous scenarios, which havebeen programmed in the microcontroller.
7.4. SMS sending command, when a change inthe traffic signal anomaly was considered amalfunction (through the verification process) to be
forwarded as news to the A6 GSM module block.
7.5. emergency flash: This sub-block works byflashing, depicting a sign that the main traffic signal
is under maintenance.
8. The GSM block A6 module works bysending SMS on the processing results, from themicrocontroller to the operator. This occurs because
the unit has been recognized by the Arduino library,

therefore, it is easily programmed in the IDE, with the
AT command instruction set.
9. Relay block is a series, consisting of 4 typesof transmissions, while the ULN2803A IC and optocoupler turns ON or OFF the traffic signal display andemergency flash. These conditions for the four typesof relay, follow the order of the microcontroller subblock timing functions.
The traffic signal cycle in this study followed thesequence as shown in Fig 3.
1. Red OFF, Amber ON, Green OFF;
2. Red ON, Amber OFF, Green OFF;
3. Red ON, Amber ON, Green OFF;
4. Red OFF, Amber OFF, Green ON;
5. The second cycle (restarts from Red OFF,
Amber ON and Green OFF).

Fig. 3 Traffic signal cycle
Hence, the implementation of a monitoring
system completely as combined work of Fig. 1 andFig. 2 respectively, shown in the Fig. 4 below.

487

SEE - Bangkok, Thailand, Nov.11-13, 2019

Start

Power ON / Reset

Sending opening SMS

Latch bitanomaly identity

Turn on all
Display lights

Microcontroller stops
traffic signal cycle

Start the traffic
signal cycle

No

Matching anomaly
scenario by
microcontroller
devices

Traffic signal
anomaly?

Sending anomaly SMS

YesTurn on emergency
flash

Bit anomaly
identity bylogical state

End
Yes

No
> GuardTime?

Fig. 4 Flow chart of signal monitoring systemcontent, therefore, it is able to quickly inform thetypes of traffic signal disruptions. Hence, it ispossible to utilize this development in building an
integrated traffic signal monitoring system services,in the form of mobile applications.

CONCLUSION
This research highlights the ability toautonomously diagnose traffic signal device systems,
especially in its work function, with the intent todetect interference on the device, and provide report
via short message service (SMS) to a monitoring unit.
Furthermore, this can be placed in any area coveredby the Global System for Mobile Communication(GSM) wireless communication service. Meanwhile,a microcontroller was used to process data from theinterference detection result, and processing the SMS

ACKNOWLEDGMENTS
Authors would like to express our special thanksof gratitude to Ministry of Research and Higher
Education of Republic of Indonesia through DRPM
(Penelitian Terapan) for providing research funds
during 2017 – 2019.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

IEEE Transactions on Computers, October, 2010,
59(10), pp. 1309-1319.
[6] P. I. Okwu, E. S. Mbonu, C. G. Ezekwe and C. U.
Ajuzie, Quick Prototyping of Real Time
Monitoring System Using Proteus Development
Tool: A Case for Self Diagnostic Traffic signal
System, December, 2013, 6(5), pp. 147-154.
[7] P. Aleksander, S. Rahayu, S. R. Ageng and I.
Agung, Developing Monitoring System ofTraffic Signal Using Microcontroller Device by
SMS of GSM Network, Proceeding of Seminar
Nasional SINTA FT UNILA, 2018, Vol. 1, pp.
273-277.
[8] F. K. Rasha, Traffic Light Control System Using
Microcontroller, AL-Qadisiyah Journal of Pure
Science, 2018, 23(2), pp. 269-280.
[9] T. A. Kareem and M. K. Jabbar, Design and
Implementation Smart Traffic Light Using GSM
and IR, Iraqi Journal for Computers andInformatics, 2018, 44(2), pp. 1-5.

REFERENCES[1] Boston Transportation Department. The benefitsof retiming/rephasing traffic signals in the Back
Bay, 2010.
[2] http://www.cityofboston.gov/images_document
s/The%20Benefits%20of%20Traffic%20Signal%20Retiming%20Report_tcm3-18554.pdf[3] Sivarao, S. K. Subramanian, M. Ezro and T. J.
S. Anand, Electrical & Mechanical Fault Alert
Traffic signal System Using Wireless
Technology, International Journal of
Mechanical & Mechatronics Engineering
IJMME-IJENS, August, 2010, 10(4), pp.15-18.
[4] M. Z. A. Marzuki, A. Ahmad, S. Buyamin, K.
H. Abas and S. Hj. M. Said, Fault Monitoring
System for Traffic signal, Jurnal Teknologi(Science and Engineering), 2015, 73(6), pp. 5964.
[5] X. Tang and S. Wang, A Low Hardware
Overhead Self-Diagnosis Technique Using
Reed-Solomon Codes for Self-Repairing Chips,

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ENHANCING THE ROLE OF BENT-UP BARS IN SHEAR BEYOND
THE CODE REQUIREMENTS BY USING PLANE-CRACKINTERCEPTOR-CROSS DIAGONAL FORM
Ms. Naim Asha
AL QUBA ENGEENERING OFFICEABSTRACT
Swimmer bars are new type of shear reinforcement; these are small inclined bars, with its both ends bent
horizontally for a short distance; welded to both top and bottom flexural steel reinforcement, or welded to hanger
bars when compression reinforcement is absent. Regardless of the number of swimmer bars used in each inclined
plane, the system forms with the added horizontal bars plane-crack interceptor instead of bars-crack interceptors.
The results obtained from testing of beams provided with this system, and the effectiveness of this new system is
discussed. The width of the shear cracks were much smaller than the width of the shear cracks in beams
reinforced by the traditional stirrups system. The equivalent steel amount used to replace the conventional steel
for the same purposes showed a superior performance of this system over the conventional system; especiallywhen a smaller amount of reinforcement was used by the new system preventing shear failure that took place forthe beams which are reinforced with the conventional shear reinforcement. The system used to replace thecongestion of stirrups when high shear forces exist.
single swimmer bar.

INTRODUCTION
Beams carry loads primarily by internal moments
and shears. In the design of a reinforced concrete
member, flexure is usually considered first, leading
to the size of the section and the arrangement ofreinforcement to provide the necessary resistance formoments. Limits are placed on the amounts offlexural reinforcement to ensure ductile type of
failure , beams are then designed for shear. Since
shear failure is frequently sudden with little or noadvanced warning, the design for shear must ensurethat the shear strength for every member in the
structure exceeds the flexural strength. The shear
failure mechanism varies depending upon the crosssectional dimensions, the geometry, the types ofloading, and the properties of the member
Reinforced concrete (RC) beams are important
structural elements that transmit the loads from slabs
to columns. Beams must have an adequate safetymargin against bending and shear forces, so that it
will perform effectively during its service life. At theultimate limit state, the combined effects of bending
and shear may exceed the resistance capacity of thebeam causing tensile cracks. The shear failure isdifficult to predict accurately despite extensive
experimental research. The behavior of reinforced
concrete beams at failure by shear is distinctly
different from their behavior by bending, which may
be un safe. The shear failure of beams is usuallysudden without sufficient advanced warning, and the
diagonal cracks that develop are considerably wider
than the flexural cracks.

Scope of the study
The scope of study is limited by the:a) The study was based on experimental
investigation of two rectangular reinforced concretebeams.
b) All specimens were of the same size andreinforced with identical amount of longitudinal
steel.
c) The beams were tested to fail due to two point
loads by shear given the ratio of a shear span toeffective depth of 2.5.
d) The concrete compressive strength of thespecimens on the testing day was in the range of 25
N/mm2 to 36 N/mm2.
e) The variables in these specimens are the shear
reinforcement systems
Experimental Investigation
Experimental works were carried out at theStructure Laboratory of the Civil Engineering
Department at the University of Jordan. Different
types of shear reinforcement were used. In general,
the objective of this study is to explore the shear
structural behaviors in beams. In this investigation,
all of the tested beams were designed to fail by shear,thus adequate amount of tension and compression
reinforcements were provided to give sufficientbending moment strength in these beams
MODEL OF SHEAR REINFORCEMENTSYSTEMTo achieve the objectives of this study, one
stage of experimental work was done; this stage has
different types of reinforced concrete beams which

OBJECTIVES
In general, the purpose of this research is toinvestigate the behavior of rectangular beams inshear, using special forms of "Swimmer bars" as490

SEE - Bangkok, Thailand, Nov.11-13, 2019contained different types of shear reinforcement.
These beams were designed and prepared forlaboratory testing to serve the main purpose of thisstudy. The dimensions of these tested beams are 200
mm in width, 250 mm in height x 2000 mm inlength. All of these beams were the same grade ofconcrete.
Beams Detail
Figures 1 - 4 shows design detailing of 'B1-5, ' B2-5

Fig. 4: Steel Cage Reinforcement of Beam 'B2-5
Casting of Specimens
Each specimen was marked carefully to insurethat each of the specimens would satisfy the strength
specification. Several steps were carried out inmaking structural concrete beam such including,reinforcement installation, mixing, concreting andcuring. Installation of steel reinforcement was
carried out in the early stage before concreting
works. Shear and nominal links were fastened
together with top and bottom reinforcement. To easethe fastening works, wire and welding were used. It
is important to ensure that cutting and bending
process was prepared with adequate length andanchorage. Before the bars were placed in the
moulds, they were first cleaned of any dirt and thinlayer of oil was applied on its surface. Stabletemporary woods supports were provided to hold theloaded end of the bars in place, while the other end
was placed in the base of the mould. These arereferred as hanging concept. The spacers werewithdrawn slowly during the compaction process.
All the materials for concrete such as, fineaggregate, coarse aggregate, cement and water were
provided according to concrete mix design. The
concrete was prepared in a rotated pan mixer. Water
was added to the materials depends on the aggregate
condition and mixed between two to three minutes
to produce a uniform color and consistency mixes.
Forklift truck was used to carry the fresh concrete
from rotating mixer to formwork. The concrete wasplaced in formwork steel mould manually in twolayers. The concrete was compacted by an internal
vibrator of 25 mm diameter. After leveling andsmoothing the surface, the specimens were covered
with polythene sheeting for at least three days. Afterthe concrete harden or after 3 days, the moulds were
stripped. Control specimens comprising of six 150
mm cubs, were also prepared from the same batch ofconcrete. They were all air cured in the same manneras the test specimens.
Compression Tests: Cube Test
The compressive strength is the most important
property of concrete. To determine the compressive
strength of the concrete, the compression test wasFig. 1: Details of Beam 'B1-5

Fig. 2: Details of Beam 'B2-5

Fig. 3: Steel Cage Reinforcement of Beam 'B1-5

491

SEE - Bangkok, Thailand, Nov.11-13, 2019carried out for each concrete mix proportion. The
fresh concrete was cast in steel or cast-iron moulds
with standard size 150 mm x 150 mm x 150 mm
cube the mould and its base should be clamped
together during casting to reduce leakage of mortar.
The use of a rigidly connected base is essential whencompaction is effected by means of vibration.
About 10 samples of cube concrete were preparedfor each concrete mix prepared for each concrete
mix proportion. The standard practice prescribed by
A.S.T.M C 192-57 is to fill the mould in three layers
and each layer of fresh concrete was compacted by
not less than 35 times of 25mm square steel. Afterthe top surface of the cube has been finished bybeans of a trowel, all of cube concretes were curing
by water. The curing process for cube concrete only
takes 7 days.
After the concrete hardens, themoulds were tested on 7 days and 28 days tomeasure the strength of concrete. The graph forcompressive strength of cubes concrete is given in
Table 1, and Figure 5

Test Procedure
Prior to testing, the surface of the specimens waspainted with white emulsion so that the detection of
the cracks during the test was easier and theirmaking become clearer. At age 28 days reinforced
concrete beams were prepared for testing. The lines
position of point load, support and the middle ofbeam span were marked to ease the installation ofbeam in testing frame. In this experimental
investigation, hydraulic jack was used and thearrangement of test setup .The test was carried out
with the specimen placed horizontally in a simple
loading arrangement. The beam was supported bysolid round steel on their two edges as simply
supported member. The effective length of eachbeam was 1800 mm that is from support to support,
but the total length of the beam was 2000 mm. All
the beams were designed to ensure the beams will
only fail in shear rather than in flexure. To ensurethat shear cracks will occur near the support, twopoint loads were applied symmetrically to the beamwith av less than 2.5d. In this testing, av ≈ 550 mm,
where av is shear span (the distance from the pointof the applied load to the support), and d is theeffective depth of a beam. A loading jack was placedat the mid-span position above the beam. The load
was applied by jacking the beam against the rig basemember at a constant rate until the ultimate load
capacity of the beam was reached. A universal
column section was used to transfer the load to thebeam at two point loads via transfer girder. A
reasonable time interval was allowed in between
20.0 kN load increments for measuring deflections,marking cracks, measuring the shear reinforcement
strain and recording the ultimate load. Each beam
took about two hours to test.
Test Results
Program presents the test result of eachspecimen, covering the specimen behavior, cracks
formation, deflections, strains of mid-section andultimate loads. The concrete compressive strength of
the specimens was obtained by concrete sampling
carried out on the same day of casting. The concrete
compressive strength of the tested samples ranged
from 25 to 36 N/mm2.
Behavior of Beam 'B1-5
This beam is a reference beam, which isreinforced with stirrups as shear reinforcement.
Before starting the test, strain and deflection gages
were fixed as shown in Figure 6 Initially thereadings of strain and deflection gages were taken,
then the beam was loaded by 20 kN, and theTable 1: Compressive Strength Cubes Results.

Days

SampleCubes
resultN/mm2

Averagecubes
result
N/mm2

ƒ'c =
0.80
cubes
resultN/mm2

7 days

1

34.9

2

36.2

3

35.8

28

4

37.1

days

5

36.7

6

37.2

28.50
35.60

37.0

29.60

Strength ( N/mm2)

35
30
25
20
15
10
5
0
0

10

20

30

Days

Fig. 5: Compressive Strength of Concrete vs. Days

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SEE - Bangkok, Thailand, Nov.11-13, 2019

160

20
0
24
0
26
0

8.28

10.11

12.51

14.54

300
200
100
0
-100 0

Test Results of Beam 'B1-5
The ultimate loads, deflections and strains
measurements for beam 'B1-5 were listed in Table 1
Figure 7 shows the load deflection curve and the
maximum deflection of 14.54 mm at the load of 260
kN. Figure 8 shows load - strain data

124.

102.

8

4

164

78.4

133.

103.

6

2

204

168

229.

190.

6

4

8

48.

84

8

20

31.
2

28

2.4

67.

38.

6

4

2

4

70.

46.

14.

4

4

4

10

15

8.8

20

Def. (mm)Fig. 7: Load vs. Deflection for ‘B1-5’

300
200
100
0
-400

-200
0
200
Strain x 10-5 mm/mm

400

Fig. 8: Strain Diagram for ‘B1-5
Fig. 6: 'B1-5 beams Before Test
Table 2: Test Results for Beam ‘B1-5
Deflectio

Strain x 10-5 mm/mm

n
kn

mm

9

8

7

6

5

4

3

2

1

0

0

0

0

0

0

0

0

0

0

0

40

2.78

26.4

21.6

18.4

15.2

12.8

4.8

1.6

80

4.65

56

45.6

36

28

120

6.47

87.2

71.2

53.6

44

23.
2
34.
4

8

12

2.4

9.6

-

-

-

1.6

13.6

0.8

2.4

Fig. 9: ‘B1-5 Cracks at the Load of 100 kN

-20

22.
4

493

4

64.
8

29.

-84

6

106.

121.6

54.

-

133.

152

5

44.

64

Applied Load F(kN)

readings of the strain and deflection gages weretaken again. By raising the load up to 40 kN, haircracks appeared at the bottom face between two
concentrated loads. At the loading of 60 kN morehair cracks appeared, and the deflection was 3.4mm.
When loading reached up to 100 kN there weren’t
any cracks at shear region as shown in Figure 9
When loading reached 140 kN, hair shear cracks
appeared in the shear zone at the right side, and at
200 kN load more shear cracks appeared. As theloading increased up to 240 kN, more and moreshear cracks appeared at both sides of this beam. At
each loading, all strains and deflection gages weretaken as listed in Table 2. Finally, at the load of 280
kN, the beam failed by shear at right side and the
maximum deflection of the beam was measured to
be 14.54 mm as shown in Figure 10.

-

-

31.2

100

-28

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SEE - Bangkok, Thailand, Nov.11-13, 2019

0

0

40

1.48

80

3.05

120

160

4.56

6.77

0
24.8
53.
6
80.
8

111.2

0
20.
8
44

68

0
16.8

36

56

0
12.8
26.
4

41.6

0
7.2

13.6

25.
6

0
2.4
6.4

0

0

0

0

-4

-5.6

-

-

-

2.4

11.2

19.2

12

0.
8

94.

78.

58.

38.

21.

4

4

4

4

6

1.6

200
150
100
50
0
-50 0

Deflectio

F

n

kn

mm

300
200
100
-200

8

7

6

5

4

3

2

0
-100
0
100
-5
Strain x 10 mm/mm

200

Fig. 12: Strain Diagram for 'B2-5

Figure 13: 'B2-5' The Experimental Setup

Strain x 10-5 mm/mm
915

Fig. 11: Load vs. Deflection for 'B2-5'

Table 3: Test Results for Beam ‘B2-5
d10Def. (mm)Test Results of Beam ‘B2-5
Measurements of ultimate loads, deflections andstrains are listed in Table 3. From this table thedeflection was measured to be 6.77 mm at the loadof 160 kN and the maximum strain was measured tobe (0.0011). Figure 11 shows loads – deflections
data and Figure 12 shows strains data through thecross section of beam at a specific load, for example
the maximum compression strain at load 160 kN.

Loa

5Applied Load F(kN)

Fig. 10: ‘B1-5’ Shear Failure at the Load of 280 kN
4.1.3 Behavior of Beam ‘B2-5
This beam was reinforced with four single
swimmer bars of ø8mm diameter as shear
reinforcement at each side of the beam. At the initialload of 20 kN as shown in Figure 13, there wasn’t
any evidence or appearance of cracks, but when theload reached 40 kN, hair cracks appeared at thebottom of face between the two concentrated loads.
After taking all deflection and strain gage readings,
the load was increased up to 60 kN, then to 80 kN
load where there weren’t any shear cracks, but whenloading reached up to120 kN as shown in Figure 4.9,
shear cracks appeared at shear regions at both sidesof the beam and the deflection at this load wasmeasured to be 4.56 mm. When loading reached 140
kN more shear cracks appeared at both sides, and at
the load of 160 kN, shear cracks were increased inlength and width. Finally, when the load reached
181 kN applied load this beam failed in shear as
shown in Figure 15. After removing concrete cover
off the failed beam, it was noticed that the swimmer
bars were loaded beyond the point of necking stage,
which means that this type of shear reinforcement
resist high shear forces.

1

494

-12

24.
8

-

-

12.

32.

8

8

SEE - Bangkok, Thailand, Nov.11-13, 2019of the shear cracks were relatively smaller than thewidth of the shear cracks of the beam 'B1-5, whichmeans that by using swimmer bars as shear
reinforcement reduce the control cracks.

Fig. 14: 'B2-5 Shear Cracks at the Load of 80 kN

Fig. 16: Cracks Pattern of Beam 'B1-5

Fig. 15: 'B2-5 Shear Failure at the Load of 181 kN
Analysis
The results from two beams of reinforced
concrete beams were analyzed and presented. The
performance of each specimen in terms of it isbehavior, crack formation; shear resistance,
deflection, strain and cost of the shear reinforcement
were discussed. It was found that the use ofswimmer bars as a shear reinforcement performed
better than the use of conventional shear
reinforcements such as stirrups. Although variation
among different casts in the same testing was
unavoidable, they were relatively small.
Cracks
It was observed that beams showed several
cracks once the stresses exceeded the cracking
moment, and with the increase in the applied load
the length and width of these cracks were increased.
Crack Pattern of Beams
It was observed that initial flexural cracks
appeared in the bottom face of these beams between
the two applied loads. By increasing the loads,
diagonal cracks were developed in the shear region
at approximately 31º angle with respect to thelongitudinal axis of these beams. The length andwidth of these shear cracks increased gradually until
shear failure took place. The width of shear cracks
of beams, 'B2-5, were relatively smaller than thewidth of the shear cracks of beam 'B1-5 as shown in
Figure 16 and Figure 17 In beams 'B2-5, the widthFig. 17: Cracks Pattern of Beam 'B2-5
Shear Resistance
All beams were tested by one - thirdconcentrator load as shown in previous. Loads usedin this study are listed in tables in 2 and 3. Each ofthese beams failed at its ultimate load.
Shear Resistance of Beams B1-5 and B2-5
All shear resistance of these beams fromexperimental results and the theoretical values arelisted in Table 2. The beam 'B1-5' which is used asa reference beam failed at 280 kN total applied load,
which is 15% higher in value than the theoretical
shear value. Beam 'B2-5 failed at 181 kN which is
25% higher than the theoretical value.
Table 4: The Differences in Shear Resistance
between Theory and Test Results of
Beam

Shear
Resistance
Theory(kN)

Shear
Resistance
Results(kN)% Test /Theory

B1-5

91.44

104

115%

B2-5

495

72.4

90.5

125%

Note

NeckingofaSEE - Bangkok, Thailand, Nov.11-13, 2019

than the strain in beam 'B1-5. These data are shownin Table 6. In summary, Beam which used swimmer
bar system exhibit higher values of stiffness incomparison with Beam 'B1-5 which used stirrups.

swimmerbar

Deflection
The beam tested in this study showed
different values of deflection. The value varies fromstage to stage.

Table 6: Strains in Beams
Load

Deflection in Beams B1-5 and B2-5
Table 5 shows the deflection of Beam 'B1-5 atgiven loads. The deflection of this beam at the loadof 100 kN is 5.48 mm and the deflection at the loadof 160 kN is 8.28 mm and the maximum deflection
at the load of 240 kN is 12.51mm. Beam 'B2-5
deflected at the load of 100 kN by 3.8 mm and at theload of 160 kN by 6.77 mm which is the maximum
deflection. The summary of the deflection of thesebeams in this stage is listed in Table 5.
Table 5: Deflection in Beams
Load

B1-5

kN

Deflection (mm)

100

5.48

3.8

160

8.28

6.77

240

12.51

9.60

kN

B1-5

B2-5
strains100

0.00072

0.00054160

0.001240.00111

CONCLUSION AND RECOMMENDATIONThis study presented a new type of shear
reinforcement called swimmer bar system. This typeof shear reinforcement can be formed in many
shapes such as a single swimmer and rectangle withcross similar to the types of shear reinforcement.
The following are the major highlights of this study.
1. The use of swimmer bar system improved theshear capacity in the reinforced Concrete beams.
2. The use of swimmer bar system reduced the beam
deflection in reinforced concrete beams
3. The width and length of the cracks in beams withswimmer bar system under loads are relatively
smaller than the width and length of the cracks inbeams with traditional stirrups.
4. The cost of reinforced concrete beams reinforced
with swimmers bar system is less than the cost of
reinforced concrete beams reinforced withtraditional stirrups.

B2-5

StrainStrain is the change in length of the crosssection of the beam at the middle. The beams
divided into nine spacing from center line of beam tothe top face as shown in Figure 18. All strains –loads values are listed in Tables.

REFERENCES[1] Abdul Hamid, Noor A. (2005), The Use of
Horizontal and Inclined Bars as Shear
Reinforcement,(Electronic
Version)
Dissertation, University Technology Malaysia.
[2] American Concrete Institute (2008), ACI
Committee 318 Building Code Requirements
for Structural Conctrete, Farmington Hills, MI.
[3] Nawy, Edward G., (2009), Reinforced
Concrete: A Fundamental Approach, by Person
Education, Inc., New Jersey.
[4] Nilson, Arthur H., (1997), Designed of Concrete
Structure, (Twelfth Edition), McGraw Hill.
[5] Piyamahant,
Asohgkram(2002),
Shear
Behavior of Reinforced Concrete Beams with
Small Amount of Web Reinforcement,(Electronic Version)
Adissertation Kochi
University of Technology Kochi, Japan.

Fig.18: Distribution of Strain Gages
Strains for Beams B1-5 and B2-5
Maximum strain of beam 'B1-5' is 0.00124 at theload of 160 kN but the maximum strain of beam 'B25 at the load of 160 kN is 0.00111 which is smaller496

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECT OF EXCESS PORE WATER PRESSURE IN SATURATED SANDYSOIL FOR EVALUATING LIQUEFACTION POTENTIAL DURING
EARTHQUAKE DURATION
Hua Thanh Than1, Nguyen Ngoc Phuc2 and Tran Thi Thanh3
1

Quy Nhon University, Binh Dinh Province, Vietnam
Industrial University of Ho Chi Minh City, Vietnam

2,3

ABSTRACTThe content of this paper is about establishment the ground acceleration record for random phase variations insaturated sandy soil during earthquake duration by using cosine function method. Then, the ground acceleration spectrums
are calculated for many differ damping ratio values. The correlation between the ground acceleration with uniform cycle
numbers (N) and moment magnitude (M) are established for evaluating liquefaction potential, excess pore water pressure
with time history (in cases of N = 15 for M = 6.5 and N = 12 for M = 8.0). At time of 30s in case N=12 for M=8.0, theratio ru of excess pore water pressure is 0.61 in 3 m depth and zero from 4 m to deeper of the depth.

Keywords: Sand foundation, Ground acceleration record, Acceleration spectrum, Excess pore water presure,
Earthquake duration.
On the significance of phrase content in earthquake
ground motion with the value of random phase angle by
Osaki (1979) [11].
Amico (2012) [1] has suggested that the value of theground acceleration record can be expressed as a set of
lognormal distributed random variable and correlated
Gaussian random variables.
According to Glaser (1996) [7], the correlation
between the ground acceleration spectrum and the time
history with the undamped natural frequency isestablished. The ground acceleration spectrum isincreased, the excess pore water pressure is also increased
and the modal contribution factor is established.
Recently, Taciroglu (2016) [12] has built up theground acceleration record funtion according to theoriginal accelerator grid, the modal contribution factor andthe infinite impulse response function. The value of thesemodal contribution factors is determined by Glaser (1996)[7].
And, Doan Thanh Nha (2017) [4] studied thesimulation model of ground accelerated record according
to sin function by Kanai - Tajimi model, Clough model Penzien (1993), and the results are suggested about thevalue of base gound type A and C.
By Idriss et al., (2006) [8], semi-empirical proceduresfor evaluating the liquefaction potential of saturated
cohesionless soils during earthquakes are re-examined.
The earthquake magnitude scaling factor for cyclic stressratios (MSF), number of equivalent stress cycles (N)versus earthquake magnitude (M) is established andrevised relations for use in practice are recommended.
Due to the complex features of ground motion time
histories, relative duration does not depend on the peakvalues. It is the time interval between the points at which
5% and 95% of the total energy has been recorded.
Bracketed duration is the measure of time between the

INTRODUCTION
Most earthquake damage to urban areas is directly or
indirectly related to ground vibration, ie ground vibration
occurring during earthquakes. In fact, earthquake vibration
due to earthquakes is a complex process that depends on
many factors, of which the most important factor is theground conditions at the location of the earthquake. The
most commonly used is the peak horizontal groundacceleration during earthquakes.
Currently, In Vietnam, Design Standards of Civil
Engineering (TCVN 9386-2012) [13] are the ones forearthquake resistant, that is compiled from the design
standard in Eurocode 8 [5], the content shows the elastic
reaction spectrum for substrates from A to E type base andthe peak design ground acceleration values for eachspecific area. However, this the peak design groundacceleration value of the standard sites are not compatible
with some construction sites. Therefore, in order toperform dynamic analysis time history, there should beground accelerators record which are the input data used
for each construction survey site with values consistent of
the elastic response spectrum amplitudes and different
random phase shift phase fluctuations.
The Kanai–Tajimi (1960) [9] model has been widelyused in modelling earthquake ground motions due to its
physical meaning and simplicity. From the power spectral
density function (PSDf) of the ground acceleration record
is obtained by passing a band-limited white noise througha filter that represents the soil layer above the rock level.
Kiureghian (1996) [10] developed Tajimi-Kanai power
spectrum density model, the results of the calculation are
the parameters of model such as the damping ratio, theundamped actural frequencies and power spectral density
for soft, medium and stiff soil, respectively.

497

SEE - Bangkok, Thailand, Nov.11-13, 2019first and last exceedance of a threshold acceleration 0.05g
by Choudhury [3].
Chiaradonna A., et al., (2015) [2] proposed that buildup of excess pore water pressure in sandy soils during
seismic loading causes reduction in stiffness and strengthand can lead to liquefaction. An increase of maximum
accelerations and strains is observed within the layers
where the pore pressure ratio is above 0.4 in the coupledanalysis.
Than et al., (2018) [14] suggested that is theliquefiable soils of M = 8.0 and no liquefation soil of M =6.5 by Dixit method, this liquefaction resistance coeficientis greater than 1 for sandy soil at construction sites ofarear in Quy Nhon city, Binh Dinh province.
The numerical method by Geostudio 2007 software [6]calculated some problems such as ground acceleration
coredo establishment by NewMark method, cyclic shear
stress, strain - stress, excess pore water pressure, ... versus
time history.
This content presents for methods using the techniquetransformation of the cos function is simulated the groundacceleration record with the elastic response spectrum
acceleration amplitude as specified in Eurocode 8 [5] withdifferent phase shift phase variations. At the same time,
the correlation between the power spectral density withdifferent for the undamped natural frequency isestablished, the harmonic ground acceleration relation
with time radution, the peak shear strain history and depth,
excess pore water pressure and time history.

Then, since the absolute acceleration is given in theform:

2. BASIS OF CALCULATION THEORY
2.1 Establishment of Ground Acceleration Record
from the Elastic Reaction Spectrum Acceleration
2.1.1. Determination of the power spectral density S(ω)

where S0 is the (constant) power spectral density of theacceleration at the bedrock, and ξg,t, ωg, ω is the damping
ratio, the undamped and damped natural frequencies of thet   u
g t   2. .ut    2 .ut 
ut t   uwhere m, k, c is the mass of the oscillator, the stiffness,the damping coefficient of the dashpot connecting themass and the bedrock, respectively. u g t  is the absolute
displacement of the bedrock, u t  is the relative
displacement between the mass m and the bedrock, u t t 
is the absolute displacement of the mass m withu t t   ut   ug t  . Here u t  , u t  , ut t  is thedisplacement, the velocity and the acceleration with time,
respectively.
The frequency domain analysis, leads to conclude thatthe power spectral density function (PSDf) of the absolute
acceleration of the ground is simply given as:  
1  4 g2, t   g ,t Su, t    S 0 .
2 22
       4 g , t   
1      g , t  
 g ,t soil

The Tajimi-Kanai model [9] for the earthquake groundmotion is based on the observation that the absolute
acceleration of the ground may be sought as a white noise
process (acceleration at bedrock) filtered throughsuperimposed soil deposit modeled as a single degree of
freedom system (DOFs) as in Fig. 1.
u

u(t)

c
m

ut
f(t)
x

k

(5)

layer,

respectivelywith  g 1   g2,t,

 g  2 Tg  2f g , g  k m and 2  c m damping ratio, fg - frequency. The parameters of TajimiKanai power spectrum density model (Kiureghian .D 1996)[10] and the numerical results are shown in Table 1.

u(t).
c.u(t)..
m.u(t)

Table 1 Parameters of Tajimi-Kanai power spectrum
density model (Kiureghian D., 1996) [10]..
f(t)=-m.ug(t)k.u(t)

ug
(a)

(b)

Fig. 1. DOFs by Tajimi (1957)-Kanai (1960) model [9]The degree of DOFs of the mass m is given as
m.ut t   c.u t   k .u t   0
m. ut   ug t   c.u t   k .u t   0

(1)
(2)

m.ut   c.u t   k .u t    m.ug t 

(3)ut   ug t   

(4)



(6)



c
k
.u t   .u t 
m
m

498

Soil typefg (Hz)ωg (rad/s)

ξg

Soft
Medium
Stiff

0.5π
1.5π
π

π
3π
6π

0.02
0.04
0.06

So
(m2/s3)
0.26
0.53
0.72

SEE - Bangkok, Thailand, Nov.11-13, 2019
Frequency (Hz)Frequency (Hz)

According to Eurocode 8, consistency is considered tobe achieved if the condition:

Fig. 2. Power spectral density function for groundacceleration (Kanai-Tajimi) [10]  max S t   Se t 100  10%
Se t In this regard, the matching can be achieved byadopting the following iterative scheme applied to thestationary component S0.

 GPA 
S 0   .
 GPAG 1 
0



(7)

where S(ωt), Se(t) is the design response spectrum
modeled, the response spectrum from at least threesimulated earthquakes, respectively. To illustrative
purpose the variability of the response spectrum has been
set asis the peak ground acceleration when the value of S0 = 1,
the value GPAG 0 1 = 1.6599g of ground type C. At theS  t   1.5S t 

same time, Doan Thanh Nha (2017) [4] suggested that thevalue of GPAG 0 1 = 2.1750g for ground type A with thecorrection factor α = 1 (Clough - Penzien model) and3.0063g for ground type C with the correction factor α =1.51 (Kanai - Tajimi model).

The determination of the random phase φn is based on
the random probability variable EE(p) with uniformly
distributed in the range (0,1) and the value of random
phase angle can determined in the interval (0 ± 2 π) by
Osaki (1979) [11] derived from Fig. 3, as follows:

The proposed method for generating fully
nonstationary spectrum compatible earthquakes is applied
to the target response spectrum defined in Eurocode 8 [5].
Specifically, for a 5% damping ratio, the response
spectrum of elastic acceleration is written as: n 1   n     n  2EE  p 

1,0
0,8
0,6
0,4
0,2
0

(9)

t 
S e t   a g S 2.5 C  for tC  t  t D
t 

(10)

t t 
S e t   a g S 2.5 C D  for t D  t  4s
 t 

(11)

(15)

p

(8)

S e t   a g S 2.5 for t B  t  tC

(14)

2.1.3. The random phase φn

the response spectrum Se(t)tSe t   ag S 1   2.5  1 for 0  t  t B
 tB


(12)

is satisfied over the range of periods between 0.2t1 to 2t1,
t1 being the fundamental period of the structure understudy in the direction where the ground acceleration
record is applied and(13)
S e 0   a g S

here α is the correction factor for α ≥ 1; GPA is theacceleration of the region's ground acceleration; GPAG 0 1

2.1.2. Determination ofaccording to Eurocode 8



EE(p)
0,2 0,4 0,6 0,8 1,0

Fig. 3. Correlations between EE(p) with p [11]2.1.4. The spectrum acceleration function E(t)The value of the spectrum acceleration E(t) is afunction with a linear with time history in Eurocode 8 [5]:The parameters defined for ground type A have beenused for the applications. Namely, S  1.0, tB  0.1, tC 
0.4 s and tD  3.0 s; furthermore, the maximum groundacceleration ag it has been set equal to 1 m/s2, η is thedamping resistance coffficient with the reference value of  10 5     0.55 and η = 1 for ξ = 5%.

E t  

5t for 0  t  0.05T
gn
Tgn

(16)

E t  15t
 0.5 for 0.05Tgn  t  0.10Tgn
Tgn

(17)

E t   1 for 0.10Tgn  t  0.30Tgn

499

(18)

SEE - Bangkok, Thailand, Nov.11-13, 2019E t   2.5 E t  

15t for 0.30T  t  0.35T
gn
gn
3Tgn

(19)

4
5t for 0.35T  t  0.50Tgn
gn
3 3Tgn

(20)

a



 peak   max rd v
 g t for 0.5T  t  T
gn
gn
3Tgn

a


g



acycle  0.65 a peak

(25)

(26)

In the above expression, MSF is the magnitude scaling
factor, based on the data obtained by Idriss and Boulanger[8] may be approximated by the equation:
MSF  6.9 exp  M 4  0.058 and MSF ≤ 1.8 at small
earthquake magnitudes (M ≤ 5.5), here M is the moment
magnitude, amax is the peak horizontal ground acceleration,acycle is the equivalent uniform stress cycles groundacceleration in the laboratory tests, g is the acceleration ofgravity, g = 9.81 m/s2, rd is depth dependent stress
reduction factor, rd = 1 - 0.015z, where z is the depth, σv isthe total vertical overburden stress at a given deth below
the ground surface.
In addition, Seed also studied actual ground motions andthe resulting increase in pore water pressures, and thencorrelated this with the number N of 0.65 peak uniform

2.1.5 Background acceleration band ag(t) with time
Simulation of the background acceleration band ag(t)and time t with random amplitude An and phase deviation
angle φn [10]:
N

1
MSF

(21)

where Tgt is the the influence duration of the groundmotion of Tgt = 30 s, α is the random variable,  0.01  0.1 and Tgn  Tgt 1.5  2  .

a g t   E t . An cosnt   n (24)Similarly, the value of  cycle can expressed as cycle   cycle rd v

E t   0.75 

1
MSF

(22)

n 1

In which E(t) is the spectrum acceleration function inEurocode 8 [5], An is determined by the power spectrum
density S(ωn) at each equally divided interval ∆ω with ∆ω= 0.005 rad/s and An  2S n  , N is the total

stress cycles that produced similar pore - pressures [6].
The equivalent number of cycles N is presented in Fig. 4.

number of time steps divided with t for time period steps(∆t = 0.01 s).
2.2. Horizontal Ground Acceleration Record ag(t) withTime According to Harmonic Oscillator Functions
Earthquake shaking is highly variable and irregularwhich in turn causes highly variable and irregular shear
stresses  peak in the ground. However, the laboratory tests
are usually done by repeatedly applying a uniform stresscycle  cycle . So our understanding of soil behavior underdynamic loading comes from the application of uniform
stress cycles.
According to Seed et al. (1975b) [6], the most common
procedure is to set the uniform cyclic shear amplitude to
65% of the peak shear stress in the irregular shear stresstime history or 0,65 is a weighting factor to calculate theequivalent uniform stress cycles required to generate samepore water pressure during an earthquake. In equationform: cycle  0.65 peakFig. 4. Number of equivalent stress cycles versus
earthquake magnitude (Seed et al., 1975) [8]3.
TEST
RESULTSAND
CORRELATIONCALCULATION
3.1. Test Results
Test at construction sites of arear in Quy Nhon city,
Binh Dinh province.
Quy Nhon Plaza project, Item for 9-storey house, No.
10-12-14-16 Do Doc Bao street, Quy Nhon City, Binh
Dinh Province, as shown in Table 2.
Location of project is in Quy Nhon city, Binh Dinhprovince, according to Vietnamese Design Standards ofCivil Engineering 9386-2012 [13], the area corresponding(23)

The value of  peak is defined as follows
500

SEE - Bangkok, Thailand, Nov.11-13, 2019
TC = 0.6 s and TD = 2.0 s, importance factor γI = 1. The
peak horizontal design ground acceleration is

to earthquake level M = 6.5 (M is the moment magnitude)
and the peak horizontal ground acceleration amax for thetypes A of soil is 0.0941g, in which g is the acceleration ofgravity.
The characteristics of soil type C with base factor S =1.15, the values of cycle spectral acceleration T B = 0.2 s,

a g   I .a gr .S  (1)( 0.0941 )(1.15 )  0.1082 g

Table 2. Test results of soil physics - Quy Nhon Plaza project
Layer
soil
1
2
3
4

Depth
(m)
0 ÷ 1011 ÷ 13
14 ÷24
> 24

SPT
N30
8÷16
2
10÷20
25

γw
(kN/m3)
17,3
17,2
17,3
18,5

φ
c
pc
(0)
(kN/m2)(kN/m2)
29
24000
4
10
3000
30
31000
16
22
20000
Underground water at 2,5 m

fs(kN/m2)
2267
750
3000
1900

Types soil
Medium sandsilty sandy, loose
Medium sandClay, dense

3.2. Correlation Calculation
3.2.1 Ground acceleration relation for cos method andGeostudio software
Calculation for the cos method with ∆t = 0.01 s theinfluence duration of the ground motion Td = 30 s, thevalue of the horizontal design ground acceleration
sequence with the time history as shown in Fig.5 (a). The
peak of the design background acceleration of cos
function is 0.1168g at time t = 6.31 s. Form that, thedifference ∆(%) calculation value between cos function
and Vietnamese Design Standard is 7.94% (M = 6.5).
The first exceedance time is the 3 seconds and the lastexceedance time is the 23 seconds, the value of groundacceleration record is 0.05g. And, Suitable to select thetime history duration of influence Td = 30 s (Kramer 1996)[3]. The reduction in peak ground acceleration (PGA)
value indicates the improvement effectiveness ofdensification in soil liquefaction by restraining theacceleration record.
In Geostudio 2007 software, the determination of thedesign ground acceleration sequence with time steps of ∆t= 0.06 s and 500 steps, the influence duration Td = 30 s by
the NewMark method in Fig. 5 (b). The value of the peakdesign ground acceleration amax,g = 0.1189g with time
history periods t = 6.42 s.
The duration of the consideration is T d = 30 s, the timeof peak acceleration is time = 6.31 s for cos method and6.42 s according to NewMark method by Geostudiosoftware. The cos method is shorter time period by
NewMark method.

Fig. 5. Correlation between ground acceleration with time
history (M = 6.5), (a) cos function, (b) Geostudio software
3.2.2. Relationship between ground acceleration spectrawith different damping ratio
The accuracy of the proposed procedure is manifested
in Fig. 6 (a) by the positive matching between simulated
and target response spectra. Interestingly, it can be notedin all the case considered the mean target response spectrain perfectly matched, so to satisfy the response-spectrum
compatibility criteria imposed by the seismic

Eurocodes. The value of the peak horizontal spectral
acceleration is 0.39g of target spectrum and 0.27g ofsimulated spectrum with time period 0.4 s.
501

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 7. Ground model for the project by Geostudio 2007
software of the excess pore water pressure shape with M =
6.5 (a), M = 8.0 (b)Fig. 6. Correlation between spectral acceleration with time
periodAs shown in Fig. 6 (b), the damping ratio is small, thespectral acceleration value is large and specific, thespectral acceleration value is 0.54 with the damping ratio
of 0%, 0.41 with the damping ratio of 2%, 0.39 with thedamping ratio of 5%, 0.36 for the with the damping ratioof 10% and 0.32 with the damping ratio of 10% of theearthquake level 6.5, respectively.

When M=6.5
To assess the efficiency of the ground model by
Geostudio 2007 software, at depths of 1 m, 2 m and 3 mwith a horizontal axis position of 16m is determined
conduction, respectively. The results of the cycle shear
strees are 5.25 kPa, 6.072 kPa and 7.254 kPa, cycle peakacceleration are 0.1789g, 0.1829g and 0.19g, respectively.
After calculating, results of the average earthquake level
M is 7.68, the number of cycle N is 15 in Fig. 8.

3.2.3. Establish ground acceleration record according toharmonic oscillator function
According to the simulation results in Fig. 7 forearthquake level M = 6.5 and M = 8.0 by Geostudio 2007
software, the results show that in the area with horizontal
axis from 24 m to 34 m and depth from 0 to 3 m, theexcess water pressure pores will appear. In addition in Fig.
7, the hydrostatic water line (blue lines, a-b) is pushed up,
the highest position with a horizontal axis is 32 m.
Therefore, at a horizontal position of 32 m is considered
because of the largest pore water pressure value. However,
it is difficult to identify the direction of migration.
With the same construction site, the building will
collapse faster when the building is affected by the larger
earthquake leves.

Peak Dynamic vs t, M=6.5,(x=16, z=1,2,3)

Peak Dynamic vs t, M=8.0,(x=16, z=1,2,3)

8

10

Peak Dynamic (q) (kPa)Peak Dynamic (q) (kPa)

7
6
5
4
3

8

6

4

2
2

1
0

0
0

10
Time (sec)

20

30

0

10

20

30

Time (sec)Fig. 8. Correlations between peak dynamic and time
duration
Instead, as shown by the Fig. 9 (a), the harmonic
ground acceleration relation fuction with time radution can
expressed as follows a g t   0.1168 g cost   2 
where numbers of cycles N = 15, influence time total Td =502

SEE - Bangkok, Thailand, Nov.11-13, 2019
30 s, time of a cycles T = 2 s, undamped natural
frequencies n  2 T   rad/s, respectively.

Fig. 9. Time histories of harmonic ground acceleration(a) M = 6.5, (b). M = 8.0

Fig. 10. Correlation between maximum acceleration, shear
strain and depth

When M=8.0
As described in Fig. 8, the cycle shear strees values are
significant between 1 m, 2 m and 3 m depths with 16 m
horizontal axis position, respectively. The results of thecycle shear strees are 6.69 kPa, 7.74 kPa and 9.25 kPa, thecycle peak acceleration are 0.406g, 0.413g and 0.416g,
respectively. Form that, results of average earthquake
level M is 7.68, the number of cycle N is 12.
Here, the number of cycle of M = 8.0 is biger than thenumber of cycle of M = 6.5, the difference about the
number of cycle of M = 8.0 and M = 6.5 is 3 cycle.
In Fig. 9 (b), the harmonic ground acceleration relation
fuction with time radution can be given as follows
a g t   0.1381 g cos2.512 t   2  here numbers of

3.2.5. Shear strain, excess pore water pressure and time
relations
When earthquake level M = 6.5, the liquefaction
phenomenon has not appeared, the value of pore waterpressure is 6.8 kPa for zero depth of the time of 30 s, thevalue of excess pore water pressure is 13.5 kPa for 3 m
depth of the time of 30 s, too and the value of the excess
pore water pressure is zero for a depth of more than 4m, as
shown in Fig. 11.
According to the evaluation of liquefaction capacity byThan et al., (2018) [14] for sand soil type in Quy Nhoncity. Secifically, when earthquake level increase, the peakhorizontal ground acceleration increase too (values - amax).
The liquefiable soils occurs completely by Dixit methodof M = 8.0 and no liquefation soil of M = 6.5, thisliquefaction resistance coeficient is greater than 1. For
silty sandy soil, the values of FSlip <1 calculated according
to the methods for earthquake level, here FSlip is theliquefaction resistance factor of method as shown above.
As shown in Fig. 12, when the depth value is smaller,
the value of the excess pore water pressure is bigger overtime. At the time of 30 s, the value of the excess porewater pressure is 35 kPa with a depth of zero and the valueof excess pore water pressure is zero with depth from 4 m
to deeper. At the time of 30 s, the excess pore waterpressure ratio ru is 0.61 of 3 m depth and from 4 m todeeper of the depth, the excess pore water pressure ratio ru
is zero, too.

cycles N = 12, influence time total Td = 30 s, time of acycles T = 2.5 s, undamped natural frequenciesn  2 T  2.512 rad/s, respectively.
3.2.4. Maximum acceleration, shear strain and depth
relations
The results of decoupled analysis are plotted in Fig.
10, in terms of vertical profiles of peak groundacceleration (PGA) with depth, strain with depth fordifferent earthquake levels (M = 6.5 and M = 8.0). The
distribution of the maximum strain shows the highest
value at depth of 1 m is 0.355% for M = 6.5, PGA =0.1167g at 11.8 m depth and 1m is 0,452% for M = 8.0,
PGA = 0.1461g at 12 m depth, respectively. The value of
PGA, the strain with earthquake level M = 8.0 is greaterthan the value of PGA, earthquake stress level (M = 6.5),
the value of the difference strain is 27.3% at 1m depth. At
the same time, the value of shear strain is reduced withdepth.
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Fig. 12 Correlation between shear stress and excess porewater presure with time history at 0 m, 3 m and 16 m
depth of M = 8.0

Fig. 11 Correlation between shear stress and excess porewater presure with time history at 0 m, 3 m and 16 m
depth of M = 6.5
4. CONCLUSION- At the PGA (peak of ground acceleration), strain ofground in earthquake level M = 8.0 is greater than M =6.5. The different strain value is about 27.3%.
- In depth from 0m to 3m, the value of the excess porewater pressure increases in case of M =6.5 but decreases
in case of M = 8.0. The value of excess pore waterpressure is 13.5 kPa at 3m depth in case of M = 6.5 and 35
kPa at the surface of ground in case of M = 8.0. At time of
30th second in case N=12 for M=8.0, the ratio ru of excess
pore water pressure is 0.61 in 3 m depth and zero from 4
m to deeper of the depth.

- In the value 0.05g (M = 6.5) of ground acceleration
record for C type soil, the influence duration gets startfrom 3rd second to end of 23th second.
- In period 0.4s of the peak horizontal acceleration
spectrum for 0.39g of target spectrum or 0.27g ofsimulated spectrum, the spectral acceleration value islargest and the damping ratio is smallest (Fig.6).
- Relations between the harmonic ground acceleration andtime radution are set up. The cycle number N=15 of theharmonic ground acceleration fits with M = 6.5 of groundacceleration and N = 12 fits with M = 8.0

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REFERENCES[1] Amico L.D. et al., Simulation of SpectralAcceleration Correlated and Response-SpectrumCompatible Ground Motion Accelerograms, No 15,
WCEE, 2012, pp. 1-10.
[2] Chiaradonna A., et al., Application of a Simplified
Model for the Prediction of Pore Pressure Build-up in
Sandy Soils Subjected to Seismic Loading, 6thInternational Conference on Earthquake GeotechnicalEngineering, New Zealand, 2015, pp 1-9.
[3] Choudhury D., Geotechnical Earthquake Engineering,
Department
of
Civil
Engineering,
India,
http://www.civil.iitb.ac.in, 2019, pp 1-10.
[4. Doan Thanh Nha, Simulation of Ground Acceleration
Record from Elastic Reaction Spectrum during
Earthquake, Master thesis, Department of Civil
Engineering, Bach Khoa University, Ho Chi Minh
City, Viet Nam, 2016, pp 79-89.
[5] EN1998, " Eurocode 8: Design of Structures for
Earthquake Resistancee," ed: European Union, 2004.
[6] Geostudio 2007, Dynamic Modeing with Quake/W
2007, Geo - Slope Intrenational Ltd., 2008, Alberta,
Canada,http://www.geo-slope.com,
https://www.youtube.com/watch?v=XVgY6tUXMS.
[7] Glaser .S, Insight into liquefaction by system
identification, Geotechnique, 46, No. 4, 1996, pp.
641-655.

[8] Idriss I.M, Boulanger R.W, Semi-empirical
Procedures for Evaluating Liquefaction Potential
During Earthquakes, Soil Dynamics and Earthquake
Enguneering, 2006, pp. 115 - 130.
[9] Kanai, K. (1957), “Semi Empirical Formula for the
Seismic Characteristics of the Ground Motion”, Bull.
Earthq. Res. Inst.-Univiversity of Tokyo 35, 1957, pp.
309–325.
[10]Moustafa A., Identification of Resonant Earthquake
ground Motion, Vol. 5, Part 3, Indian Academy of
Sciences, 2010, pp. 355-371.
[11]Osaki Y., “On the Significance of Phrase Content inEarthquake Ground Motion”, EESD, Vol.7, 1979.
[12]Taciroglu E., Ghahari S.F., Identification of Spatial
Variability in Bridge Foundation Input Motions:
Theoretical basis, Irvine, Cliforna, 2016, pp. 111-139.
[13]TCVN 9386-2012, Design of structures forearthquake resistances, 2012.
[14]Thanh-Than Hua, Ngoc-Phuc Nguyen, Thi-Thanh
Tran, Effection of Liquefaction by Earthquake due toPore Water Pressure in Sand, Numerical Analysis in
Geotechnics, NAG2018, Ho Chi Minh City,
Vietnam, 2018.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

PREDICTION OF GROUNDWATER LEVEL USING A DISCRETESPACE-STATE MODEL AS AN ALTERNATIVE TO PHYSICALLYBASED GROUNDWATER MODELLING
Dilip Kumar Roy1, Sujit Kumar Biswas1 and Khandakar Faisal Ibn Murad1
1
Bangladesh Agricultural Research Institute, Bangladesh

ABSTRACT
Reliable and accurate prediction of groundwater level is an essential component of sustainable water resourcesmanagement and designing remediation plans. Groundwater simulations and predictions are often performed by
employing physically based models, which are not applicable in many parts of the world especially in developing
countries like Bangladesh due to data limitations. On the other hand, data-driven statistical methods have proven
their applicability in modeling complex and nonlinear hydrological processes with a view to forecasting shortterm and long-term groundwater levels. The purpose of this effort is to develop a non-physical based approach byutilizing a discrete Space-State model as a prediction tool for future scenarios of groundwater level forecasting. In
Space-State modelling approach, a model is identified to accurately compute a dynamic system with response to
an input. The present study utilizes the prediction focused approach of the system identification process in which
the overall goal is to create a realistic dynamic system model. The performance of the proposed approach isevaluated for groundwater level data at three observation wells of Tanore upazilla of Rajshahi district, Bangladesh.
Historical weekly time series of water level data from the three observation wells for 39 (1980-2018) years is used
to develop the time series model, which is used for future water level predictions for a period of the next 22 years(up to 2040). The results of the present study indicate the potential applicability of the proposed discrete SpaceState modelling approach in forecasting future groundwater levels in the observation wells of the study area.
Keywords: Groundwater level prediction, Data-driven methods, Discrete Space-State modelling, Dynamic systemmodel, Bangladesh

groundwater level forecasting that can be used to help
water managers, engineers, and stake-holders manage
groundwater in a more effective and sustainable
manner.
The complexity of aquifer and hydrologicalsystems makes accurate physical process simulations
challenging due to the large agricultural andhydrogeological data requirements for model
development and calibration. Thus, it is appealing toconsider data-driven and machine learning methods
based on nonlinear interdependencies that may beable to predict groundwater level change without
deep knowledge of the underlying physicalparameters. The data-driven models attempt toidentify a direct mapping between the inputs andoutputs of the system without reaching an
understanding of the internal structure of the physicalprocess. That is to say, the data-driven approach
recognizes the hidden patterns in historical data andthen apply those patterns to predict future scenarios.
The commonly used data-driven methods forforecasting groundwater heads are based on the timeseries method [2], Kalman filter [3], artificial neuralnetwork method [4]-[6], and co-kriging technique [7].
Assessments of data-driven modelling applications inhydrology suggest that such methods can achieve
performance comparable to, or even more accuratethan, that of numerical models of physical transport

INTRODUCTION
Groundwater is one of the major sources of watersupply for domestic, urban, agricultural and industrial
purposes, especially in the Barind area of Bangladesh.
However, many problems occur due tooverexploitation of groundwater and unsustainablegroundwater use and management, such as majorwater-level declines, drying up of wells, waterquality degradation, increased pumping costs, land
surface subsidence, loss of pumpage in residential
water supply wells, and aquifer compaction [1].
Reliable and accurate prediction of groundwater levelis an essential component of suitable water resourcesmanagement, predicting contaminant transport, anddesigning
remediationplans.
Groundwater
simulations and predictions are often performed by
employing physically basedmodels (e.g.
MODFLOW, FEEFLOW, FEMWATER etc.), which
are not applicable in many parts of the world
especially in developing countries like Bangladesh
due to data limitations. On the other hand, data-driven
statistical methods have proven their applicability inmodeling complex and nonlinear hydrologicalprocesses with a view to forecasting short-term andlong-term groundwater levels. The purpose of thiseffort is to develop a non-physical based approachwith limited data availability for highly accurate
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8194049 is located at 24.0630N latitude and 88.580E
longitude.

[8]-[10]. Overall, these studies have demonstrated theability of statistical and data-driven machine learning
methods for capturing the nonlinear relation between
climate variables and groundwater, particularly inareas in which physically based models would bechallenging to implement. Keeping these in mind, thiseffort seeks to implement discrete Space-Statemodelling approach as a prediction tool for futurescenarios of groundwater level forecasting in selected
observation wells of Tanore upazilla in Rajshahi
district of Bangladesh.
METHODOLOGY
Study Area and Data
The study area is located at Tanore upazilla ofRajshahi district in the division of Rajshahi,
Bangladesh. It is located between 24˚28'N and24˚44'N lattitudes and between 88˚24'E and 88˚39'E
longitudes. The study area has an aerial extent of
295.40 km², which is surrounded by Niamatpur
Upazila and Manda Upazila of Naogaon District tothe north, Mohanpur Upazila of Rajshahi district tothe east, Paba Upazila and Godagari Upazila ofRajshahi district to the south, Chapai Nawabganj
Sadar Upazila and Nachol Upazila of Chapai
Nawabganj District to the west. The Shiba river flows
through Tanore upazilla providing insufficientquantity of water for irrigation purposes. The geologyof Tanore is composed of Barind Tract (81.8%), Old
Gangetic Floodplain (3%) and Tista Floodplain(4.8%). The rest 10.4% of the total area consists ofhomestead, wetland, ponds, and rivers [11]. Clayloam (46%), Loam (35%), and Clay (8%) are themain constituents of land formation in Tanore
upazilla [12]. The irrigated agriculture in Tanore
upazilla mainly depends on groundwater resources,
which is declining gradually as a result of excessive
withdrawal of water for irrigating crops. Barind area
is basically a flood free zone in Bangladesh becauseof high elevation with respect to mean sea level.
Therefore, rainfall is the only source of water for
groundwater recharge. Nevertheless, thick sticky clay
surface of Barind area in combination with scanty
rainfall hinders the natural aquifer recharge in thisarea. As a result, groundwater level is continuously
falling in response to increasing amount of water
abstracted for irrigation purposes.
Secondary data of weekly groundwater level
fluctuations at selected observation wells arecollected from Bangladesh Water Development
Board. Historical weekly groundwater level data fromJanuary 1980 to September 2018 of three observation
wells of Bangladesh Water Development Board areused. Observation well GT 8194046 is located at
24.680N latitude and 88.530E longitude. Observation
well GT 8194048 is situated at 24.570N latitude and88.550E longitude whereas the observation well GT

Fig. 1

Locations of the observation wells in the
study area.

Historical weekly time series of water table datafor 38 years is used for developing the time seriesmodel, which is used for future water level
predictions for a period of the next 22 years (up to2040).
The original time series of groundwater table data
is divided into identification (training) and validation
data. Eighty percent of the entire time series data isused to train the model whereas the rest 20% is used
to validate the developed model. After satisfactory
training of the models, the trained and validated
models are used for future predictions.
Modelling TechniqueThis study utilizes a discrete Space-State model asa prediction tool for future scenarios of groundwaterlevel forecasting. The groundwater table can bemodelled as a State-Space system with noisy input
and measured water table date as output. The
measured water table is proportional to the system
state, i.e.
𝒙𝒏+𝟏 = 𝑨𝒙𝒏 + 𝑲𝒆𝒏(1)𝒚𝒏 = 𝑪𝒙𝒏 + 𝒆𝒏

(2)

Where, 𝑥𝑛 is the state vector, contains the weekly
water table values; 𝑦𝑛 is the output from the model;
𝑒𝑛 is the noise and 𝐴, 𝐶, 𝐾 are the parameters to be
identified.
In Space-State modelling approach, a model is
identified to accurately compute a dynamic systemwith response to an input. Two different approaches
exist to generate an identified model response: (a)Simulation, which computes model response using
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input data and initial conditions, and (b) Prediction,
which computes the model response at some specified
amount of time in the future using the current and pastvalues of measured input and output values, as wellas initial conditions. The present study utilizes theprediction focused approach of the system
identification process in which the overall goal is tocreate a realistic dynamic system model that can beused or handed off for an application goal. During themodel identification process, a one-step prediction
focus is used as it generally produces the best results.
By using both input and output measurements, onestep prediction accounts for the nature of the
disturbances. Accounting for disturbances provides
the most statistically optimal results.

the most accurate model has the smallest FPE.
Akaike's FPE is defined by the following equation
𝑭𝑷𝑬
𝑵
𝑻
𝟏 + 𝒅⁄𝑵𝟏̂ 𝑵 ) (𝒆(𝒕, 𝜽̂ 𝑵 )) ) ()= 𝐝𝐞𝐭 ( ∑ 𝒆(𝒕, 𝜽𝑵
𝟏 − 𝒅⁄𝑵
𝟏(5)

Where, 𝑵 is the number of values in theestimation data set, 𝒆(𝒕) is a 𝒏𝒚 -by-1 vector of
prediction errors, 𝜽𝑵 represents the estimatedparameters, 𝒅 is the number of estimated parameters.
If number of parameters exceeds the number ofsamples, FPE is not computed when model estimationis performed.

Prediction focused approach

Mean squared error (MSE)

Prediction means projecting the model response 𝒌
steps ahead into the future using the current and pastvalues of measured input and output values. 𝒌 iscalled the prediction horizon, and corresponds topredicting output at time 𝒌𝑻𝒔, where 𝑻𝒔 is the sample
time. In other words, given measured inputs
𝒖𝒎 (𝒕𝟏 , … , 𝒕𝑵+𝑲 )andmeasured
outputs𝒚𝒎 (𝒕𝟏 , … , 𝒕𝑵 ) , the prediction generates the final
output 𝒚𝒑 (𝒕𝑵+𝑲 ). For example, if the input and output
signals of a physical system are 𝒖𝒎 (𝒕) and 𝒚𝒎 (𝒕),respectively, then the first order equation of thissystem can be represented by

𝑴𝑺𝑬 =

𝑵

𝒚𝒑 (𝒕 + 𝟏) = 𝒂𝒚𝒎 (𝒕) + 𝒃𝒖𝒎 (𝒕)

(6)

𝒊=𝟏

MODEL DEVELOPMENTAs the first step of the model development, a 1step ahead prediction is performed for all the threeobservation well locations. For observation well
GT8194046, the system identifies 440 numbers of
free coefficients to develop a Space-State model forwhich estimation data fit is found to be 91.35%(prediction focus). The FPE and MSE values of
0.07358 and 0.06796, respectively are found, whichindicates a very good prediction model. The
corresponding values of free coefficients, FPE andMSE values of observation wells GT8194048 andGT8194049 are presented in Table 1.

(3)

where 𝒚 is the output and 𝒖 is the input. In
general, to predict the model response 𝒌 steps into the
future (𝒌 ≥ 𝟏 ) from the current time 𝒕 , one must
know the inputs up to time 𝒕 + 𝒌 and outputs up to
time 𝒕 such that𝒚𝒑 ( 𝒕 + 𝒌 )= 𝒇(𝒖𝒎 (𝒕 + 𝑲), 𝒖𝒎 (𝒕 + 𝒌− 𝟏), … , 𝒖𝒎 (𝒕), 𝒖𝒎 (𝒕− 𝟏), … , 𝒖𝒎 (𝟎), 𝒚𝒎 (𝒕), 𝒚𝒎 (𝒕 − 𝟏), 𝒚𝒎 (𝒕− 𝟐), … , 𝒚𝒎 (𝟎))𝟏∑(𝑨𝒄𝒕𝒖𝒂𝒍𝒊 − 𝑷𝒓𝒅𝒊𝒄𝒕𝒆𝒅𝒊 )𝟐
𝑵

Table 1 Prediction performance of the developedmodels at observation wells GT8194048 andGT8194049
Observation
Well

(4)
GT8194048
GT8194049

Where, 𝒖𝒎 (𝟎) and 𝒚𝒎 (𝟎) are the initial states.
𝒇( ) represents the predictor, which is a dynamic
model whose form depends on the model structure.
A MATLAB command is used to identify adiscrete state-space model from the measured data.

Fit to estimation
data (prediction
focus), %
81.42
89.98

FPE

MSE

0.29
0.07

0.27
0.07

The identified models minimize the 1-step ahead
prediction. Then, the model is validated using a 10step ahead predictor, i.e., given 𝒚𝟎,…, 𝒚𝒏, the model isused to predict 𝒚𝒏+𝟏𝟎 . Note that the measured and̂ 𝟎 , … , 𝒚𝒏 − 𝒚̂𝒏 , are used to
predicted values, 𝒚𝟎 − 𝒚make the 𝒚𝒏+𝟏𝟎 prediction. The 10-step ahead
prediction results for the identification and thevalidation data for observation wells GT8194046,
GT8194048, and GT8194049 are presented in Figs.
2, 3, and 4, respectively.

Performance Evaluation Criteria
Akaike's final prediction error (FPE)FPE criterion provides a measure of model quality
by simulating the situation where the model is tested
on a different data set. According to Akaike's theory,
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Fig. 2

Fig. 410-step ahead prediction results for theidentification and validation data at
observation well GT8194046.

10-step ahead prediction results for theidentification and validation data at
observation well GT8194049.

It is observed from Figures 2, 3, and 4 that for both
identification and validation datasets at allobservation wells the predictor matches well with themeasured data. Then to further verify the developed
prediction model, forecasting within the range of thevalidation data is performed. Forecasting uses thê𝒏 to computemeasured data record 𝒚𝟎 , 𝒚𝟏 , … , 𝒚𝒏 − 𝒚the model state at time step 𝒏. This value is used as
initial condition for forecasting the model response
for a future time span. We forecast the model
response over the time span of the validation data andthen compare the two.
RESULTS AND DISCUSSION

Fig. 3

Predicted response over the validation data’s timespan at observation wells GT8194046, GT8194048
and GT8194049 are illustrated in Fig. 5.
The plots show that the model response overlaps
the measured value for the validation data. The
combined prediction and forecasting results indicatethat the model represents the measured water level
data quite accurately. Figure 5 shows that there are
relatively good agreements between the simulated
and observed groundwater level for all the threemodels. Thus, it is practically possible to develop
groundwater forecasting models using this datadriven approach. However, there are discrepancies inmatching some of the peak events, where the events
may be under predicted or over predicted values.

10-step ahead prediction results for theidentification and validation data at
observation well GT8194048.
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The forecasting results also show that over large
horizons the model variance is large and for practical
purposes future forecasts should be limited to shorthorizons. For the water level prediction model, ahorizon of 22 years is appropriate given the previous
data available is only for 38 years.

Fig. 6

Fig. 5

Original and future predicted groundwaterlevels at observation wells GT8194046,
GT8194048 and GT8194049.

Figure 7 illustrates groundwater level at the
selected three observation wells on 24/09/2018 andthe projected (model predictions) groundwater table
on 24/09/2040. It is perceived from Figure 7 thatgroundwater level declination almost doubled at all
three observation wells for the next 22 years if thepresent rate of abstraction continues. It is concluded
that the proposed modeling framework can serve as
an alternative approach to simulating groundwaterlevel change and water availability, especially inregions where subsurface properties are unknown.
Of note, the forecasting results are entirely basedon the historical groundwater level data based on theprevious abstraction and recharge rates. As theincreasing demand of water is triggering more andmore groundwater abstraction from the aquifer andthe recharge rate is decreasing due to scanty rainfall

Predicted response over the validation data’stime span at observation wells GT8194046,
GT8194048 and GT8194049.

The properly trained and validated models arethen used to forecast the response 1105 steps into
future for the time span of 22 years (From 25/09/2018
to 24/09/2040). The forecasted results are presented
in Fig. 6.
The green curve shows the measured
identification data whereas the blue curve shows themeasured validation data that spans over 1-1900
weeks. The red curve is the forecasted response for1105 weeks beyond the measured data's time range.
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in that area, the groundwater level declination might
be even more dangerous than the projected ones if
corrective measures are not taken. Moreover, thesticky clay subsurface of the study area slows down
the natural recharge to the aquifer. Therefore,groundwater abstraction should be judiciously
optimized in the study area to protect the alreadyvulnerable groundwater resources.

Fig. 7

Region Using Artificial Neural Network.
Environmental Geology, Vol. 58, Issue 6, 2009,
pp. 1239-1246.
[2] Kontur I., Long-Range Groundwater Level
Prediction Based on Time Series Analysis. In:
Jones G. P., editor. Improvements of Methods ofLong Term Prediction of Variations in
Groundwater Resources and Regimes due to
Human Activity, 1982, pp. 187-193.
[3] Knotters M., and Bierkens M. F. P., Accuracy of
Spatio-Temporal RARX Model Predictions of
Water Table Depths. Stochastic Environmental
Research and Risk Assessment, Vol. 16, Issue 2,
2002, pp.112-126.
[4] Coulibaly P., Anctil F., Aravena R., and Bobée
B., Artificial Neural Network Modeling of Water
Table Depth Fluctuations. Water Resources
Research, Vol. 37, Issue 4, 2001, pp. 885-896.
[5] Daliakopoulos I. N., Coulibaly P., and Tsanis I.
K., Groundwater Level Forecasting Using
Artificial Neural Networks. Journal of
Hydrology, Vol. 309, Issue 1, 2005, pp. 229-240.
[6] Shigidi A., and A. Garcia L. A., Parameter
Estimation in Groundwater Hydrology Using
Artificial Neural Networks. Journal ofComputing in Civil Engineering, Vol. 17, Issue
4, 2003, pp. 281-289.
[7] Ahmadi S. H., and Sedghamiz A., Applicationand Evaluation of Kriging and Co-Kriging
Methods On Groundwater Depth Mapping.
Environmental Monitoring and Assessment, Vol.
138, Issue 1, pp. 357-368.
[8] Coppola E., Szidarovszky F., Poulton M., andCharles E., Artificial Neural Network Approachfor Predicting Transient Water Levels in a
Multilayered Groundwater System under
Variable State, Pumping, and Climate
Conditions. Journal of Hydrologic Engineering,
Vol 8, Issue 6, 2003, pp. 348-360.
[9] Parkin G., Birkinshaw S. J., Younger P. L., RaoZ., and Kirk S., A Numerical Modelling and
Neural Network Approach to Estimate the
Impact of Groundwater Abstractions On River
Flows. Journal of Hydrology, Vol 339, Issue 1,
2007, pp. 15-28.
[10] Nikolos I. K., Stergiadi M., Papadopoulou M. P.,
and Karatzas G. P., Artificial Neural Networks as
an Alternative Approach to Groundwater
Numerical Modelling and Environmental Design.
Hydrological Processes, Vol 22, Issue 17, 2008,
pp. 3337-48.
[11] SRDI. Upazila Land and Soil Resource
Utilization Guide: Tanore, Rajshahi. SRDI (Soil
Resource Development Institute), Dhaka, 2000.
P.10.
[12] SRDI. Land and Soil Statistical Appraisal Book
of Bangladesh. SRDI (Soil Resource
Development Institute), Dhaka, 2010. P. 155.

Present and future scenarios of groundwaterlevels at three observation wells.

CONCLUSIONSThe present study investigates the accuracy of thediscrete Space-State modelling approach forforecasting weekly groundwater levels. The core idea
is to develop a dynamic prediction model using theprediction focused approach to accurately forecast
future groundwater levels at specified observation
wells. The models are developed using the historicalgroundwater level data of the study area. The
combined training, validation and forecasting results
indicate that the model represents the measured waterlevel data quite accurately. Therefore, the modelling
approach presented in this paper can be used as analternative to the complex numerical simulation
models in data scarce situations. A univariate timeseries of groundwater level has been performed andpresented in this paper. Future studies may aim toconsider a multivariate time series analysis thatconsiders the effects of other hydrogeologicalparameters for groundwater level predictions.
ACKNOWLEDGMENTS
The authors gratefully acknowledge the financial
support provided by National Agricultural
Technology Program: Phase II Project, Bangladesh
Agricultural Research Council, Bangladesh.
REFERENCES[1] Banerjee P., Prasad R. K., and Singh V. S.,
Forecasting of Groundwater Level in Hard Rock511

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EXPERIMENTAL INVESTIGATION OF RESPONSE OF SEGMENT
LINING DUE TO ADJACENT PILE UNDER LOADING

1

Pattanasak Chaipanna1, Kisada Trakoonjannak2 and Pornkasem Jongpradist 3
Faculty of Industry and Technology, Rajamangala University of Technology Isan, Thailand
2
Geotechnical & Foundation Engineering Co., Ltd (GFE), Thailand
3
Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Thailand

ABSTRACTThe effect of adjacent pile under loading on the existing tunnel is one of the serious concerns in urban environment.
In this study, the deformation and internal forces of segmental lining due to an adjacent loaded pile, are investigatedthrough a series of physical laboratory tests. Special attention is paid on the relative positions between the key
segment and the pile tip. The experimental results show that the relative pile tip level to the key-segment position
plays a crucial role. The key-segment position at 90 degree (measured from tunnel crown) should be realized inassessment of lining response when the pile tip level is at the tunnel springline. For the pile tip at springline, thekey-segment positions at 90 and 142 degrees should be taken into consideration.
Keywords: Key-segment, Physical model test, Tunnel deformation, Pile-tunnel interaction

polyethylene (HDPE) and nylon sheet are employed
to represent the segment and joints, respectively. The
elastic moduli of HDPE and nylon sheet are equal
1.18E+9 and 6.13E+8 Pa, respectively. The
configuration of the model tunnel is shown in Fig.
1(a). Table 1 shows the geometry of prototype andmodel tunnels. The HDPE is also represented the pile.
The diameter of the model pile is 33 mm which scale
down from 1.0 m diameter of prototype pile. The
figure of pile model is shown in Fig. 1(b).

INTRODUCTION
In the urban areas, some pile foundations areclosely located to the existing tunnel. The pile loadtransfers to the surrounding soil media and induces
the additional internal force and deformation on thetunnel lining. The induced loading can contribute topossible damage to operational safety to the existingtunnel. Especially, tunnels for transport networks canoften tolerate only minimal movement. A grasp ofpile-soil-tunnel interaction is imperative for effect ofpile loading on the functional safety of existingtunnel.
There are several studies on the effects of pileloading effect on the existing tunnel [1-3]. The mostof them model the lining still using continuous
element, which can not response the essential aspectof the segmentail lining
The aim of this paper is to investigate the internal
force and deformation of segmental lining via a seriesof physical model test.

a)b)Fig. 1 a) configuration of tunnel model, b) pile
model

DESIGN OF THE MODEL
Table 1 Geometry of prototype and model segments(mm).

The prototype of this test is the universal subway
tunnel, which generally made by reinforce concretesegments and connected them together with the steelbolts. The elastic moduli of concrete and steel bolt of
the prototype tunnel are equal to 3.45E+7 and2.00E+8 Pa, respectively. The segment are straggly
assembled along the tunnel axis. The prototype tunnel
consists of one key, two adjacent and three standard
segments. The similarity method [4] is used to scale
down the model test. The scaling factor of 30 isselected for performing the test. The high density

Items
Prototype
Model

512

Outsidediameter
6200
210

Thickness

Width

350
12

1000
33

SEE - Bangkok, Thailand, Nov.11-13, 2019

Monitoring and loading control
The strain gauges are installed on both external
and internal surfaces of lining, as shown in Fig. 5.
Strain obtained from strain gauges are used tocompute the bending moment (M) and normal force(N) of the segment as expressed in Eq. 1 and 2,
respectively.

PROCEDURE OF PHYSICAL MODEL TESTThe test preparation
Fig 2 shows the determination of the ultimate
capacity of the pile model from the experimental
load-settlement curve from axial load test using De
beer’s method (1970)[5]. The service load of 121.5 N
was used in the subsequent test. Series of physicaltests are performed in acrylic test box (Fig.3) which
is filled with KMUTT sand. Both lateral sides of thetest box in the longitudinal direction are bored forfacilitating the installation of both the model tunnel
and measuring devices. To control the density anduniform leveling of sand within the test box, the sandis free fallen from the multiple sieving pluviation
apparatus (Fig.4).

( in   ex ) EIt(   )EA
N  in ex
2

M

(2)

where εin and εex are internal and external strains
which measure in tangential direction. E is modulus
of elasticity. A is sectional area. I is moment of inetia
of section. t is the lining thickness.
The deformation of the lining is measured by alaser transducer. The white laser targets are attached
on internal surface of both ends of each segment, asshown in Fig. 5.

10000

QU= 486 N
1000

Load (N)

(1)

100

10

De beer's method
Pile diameter 33 mm
Pile tip -0.5DT

1

1

10

100

Displacement (mm)Fig. 2 Determination of the pile capacity.

Strain gauge
Las er target

Fig. 5 a) installation of strain gauge, b) positions ofstrain gauge and laser target.
During testing, the pile loads and settlement aremeasured via the load cell and linear variable
differential transformation (LVDT), respectively.
The pneumatic control system is used to control thepile loading, which is shown in Fig6.

Fig.3 Arrangement of the experimental test

Fig.4 a) the pluviation apparatus, b) section A-A
multiple sieve layers
Fig. 6 Schematic of the physical model test

513

SEE - Bangkok, Thailand, Nov.11-13, 2019

The strain gauge, laser transducer, load cell and
LVDT are connected to the acquisition device tointerpret and log the data.

Load

4
2

Key-segment position
38 Deg.
330
90 Deg.
142 Deg.

030

0EXPERIMENTAL RESULTS

Pile

-2

300

60

Bending Moment (kN-m)-4

In order to obtain a better understanding of theinfluence of pile tip level on the tunnel response, twolevels of pile tip were considered.
The measured data are distinguish in term of effect of
key-segment position and effect of the pile tip level.
In the test series of various key-segment position, thepile tip level is set at the springline. The key-segments
are set at the 38, 90 and 142 degree measuring
clockwise from the tunnel crown. For various pile tip
levels, the key-segment is set at the 38 degree. The
pile tip levels are set at the tunnel crown andspringline.

Radial deformation (mm)0DTunnel

-0.6
-0.4
120

0.0
210

240

120

210

150

Fig.7(a) shows the radial deformation
measured at different of the key-segment position.
The maximum radial deformation occurs in case of
key-segment 90 degree occurring at the key-segment.
Due to this case, the key-segment is locate near thepile tip. The induced load push the lining moving
away from the pile. Moreover, case of key-segment
locate at 90 degree shows the maximum normal force
which appears at the 135 degree, as show in Fig.7(b).
The measured bending moment is shown in Fig.7(c).
The maximum (+) bending moment appears in caseof the key-segment locating at the 142 degree, which
occur at around the tunnel crown. The minimum (-)
bending moment occurs at the springline.

-0.6

240

-4

Effect of key-segment position

Pile

-0.2

Key-segment-6c) Bending moment
Fig. 7 Influence of key-segment position

60

90

0DTunnel

180

30

270

90

4

-0.4

-0.8

270

-8

2

0

300

-10

0

0.2

-0.2

Segment joint

-8

-2

Load

Key-segment position330
38 Deg.
90 Deg.
0.0
142 Deg.

-6

150

0.2
180

Effect of pile tip levela) Radial deformation

The effect of pile tip levels are shown in Fig.8.
In case of the pile tip level is at the crown, the induced
force pushes the tunnel moving down away the pile
greater than that of pile level at springline, as shownin Fig.8(a). As can be seen in Fig.8(b), the normal
force increase with the increasing of pile length. In
Fig.8(c), the pile tip level at the tunnel crownintroduce the positive bending moment in the lining(compression on outer and tension on inner surfaces)

Load

Key-segment position
38 Deg.
330
0
90 Deg.
142 Deg.
300

60

Segment joint

-20

270

90

0DTunnelKey-segment
-20

-10

240

0

120

0.2

0
210

330

30

0.0

150
180

300

-0.2

b) Normal force

Deformation (mm)Normal force (kN)

30

Pile

-10

-30

0

60

-0.4
-0.6

Pile tip level
Springline
Crown

270

90

-0.4
-0.2

240

120

0.0
0.2

210

150
180

a) Radial deformation
514

SEE - Bangkok, Thailand, Nov.11-13, 2019

relative position between the key-segment and pile tip
positon on the behavior of the existing tunnel lining.
Based on the experimental observations andmeasurements, the following conclusions may be
drawn:(1) The induced deformation will increase if the
key-segment is closely the pile tip position.
(2) The longer pile induces the normal force
greater than that of short pile.
(3) When the pile tip is at the crown level, thepile loading significantly induces the
positive bending moment at the crown andinvert of the lining.

0
8

330

30

0
-8
300

-16

60

Normal force (N)

-24
-32
-40

Pile tip level
Springline
Crown

270

-32

90

-24
-16

240

120

-8
0
210

8

150
180

REFERENCESb) Normal force

330

4[1] Lueprasert, P., Jonpardist, P., Jonpardist, P. and
Suwansawat, S., Numerical investigation oftunnel deformation due to adjacent loaded pileand pile-soil-tunnel interaction. Tunnelling andUnderground Space Technology, Vol. 40, 2017,
pp. 166-181[2] Lueprasert, Pl, Jongpradist, P., Suwansawat, S.,
Tunneling simulation in soft ground using shellelements and grouting layer. International Journalof GEOMATE, Vol.12, Issue 31, 2017, pp.51-57[3] Schroeder, F.C., Potts D.M., Addenbrooke, T.I.,
The influence of pile group loading on existingtunnels, Geotechnique, Vol.54, No.6, 2002,
pp.351-362[4] Ye, F., Gou, C.F., Sun, H.D., Liu, Y.P., Xia, Y.X.,
and Zhou, Z., Model Test Study on Effective
Ratio of Segment Transverse Bending Rigidity of
Shield Tunnel. Tunnelling and UndergroundSpace Technology, Vol. 41, 2014, pp.193-205.
[5] De Beer, E., Experimental Determination of the
Shape Factors and the Bearing Capacity Factorsof Sand Geotechnique, Vol. 20, No 4, 1996, pp.
387-411.

Load

0
8

30
0

Key-segment position330
38 Deg.
300
90 Deg.
0.0
142 Deg.
-4
0.2

30

Radial deformation(mm)
Bending moment
(N-m)

0

Pile

-0.2

300

-8

60

Pile tip level
Springline
Crown

-0.4

-12

270

-0.6

-8
-0.8

60

90

270

90

-4
-0.6

0

240

0DTunnel

120

-0.4

4
-0.2

240

120

210

8

150
180

0.0
210
0.2

150

c) Bending moment
180

Fig. 8 Influence of pile tip level.
CONCLUSION
In the present paper, the results of tests
performed in a laboratory with reduced-scale oftunnel response due to adjacent pile loading ispresented. The objective of the test is to provide
element of understanding about influence of the515

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE STUDY ON EFFECT OF LIGHTWEIGHT CONCRETE BLOCKBY WATER HYACINTH ADDING
1

Prang Subpa-Asa1, Laemthong Laokongthavorn 2, Shigeyuki Date3
Faculty Graduate student, Civil Engineering Department, Faculty of Engineering, King Mongkut’s Institute ofTechnology Ladkrabang, Bangkok, Thailand, 10520.
2
Associate professor, Civil Engineering Department, Faculty of Engineering, King Mongkut’s Institute ofTechnology Ladkrabang, Bangkok, Thailand, 10520.
3
Professor, Civil Engineering Department, Faculty of Engineering, Tokai University, Kanagawa-pref., Japan,
259-1292.
1

ABSTRACTThe objective of this study is to find out the pattern of water hyacinth which is suitable for making lightweighted concrete and use sand replacing in light-weighted concrete production The proportion of cement: sand:water: foam is 1: 1: 0.65: 44.08 and the proportion of water hyacinth that will replace the sand by cement’s weightis 0%, 2.5%, 5%, 7.5% and 10%, to study the density, water absorption, compressive strength (by the standard
of TIS 1505-2541) and heat conduction at 14 days. The results of compressive strength of lightweight concrete(LC) and cellular lightweight concrete (CLC) are 167.56 ksc and 284.94 ksc, respectively. Compressive strengthof cellular lightweight concrete mixed water hyacinth (CLCH) and lightweight concrete mixed water hyacinth(LCH) were investigated. The compressive strength of CLCH and LCH are156.37 ksc and 172.45 ksc. The
percentage loss of CLC and LC compressive strength are 6.68% and 39.83%. The physical properties which aredensity and thermal conductivity decrease. In contrast, water absorption increases by the percentage of water
hyacinth by sand replacement. The optimal of water hyacinth ratio in this study is 5%. Moreover, CLC block is
specified by Thai Industrial Standards Institute 1505-2541 and classified as C16 of CLC block. of your paper will
be formatted further at International Journal of Computer Theory and Engineering. Define all symbols used in the
abstract. Do not cite references in the abstract. Do not delete the blank line immediately above the abstract; it sets
the footnote at the bottom of this column.

Keywords: Water hyacinth, Lightweight concrete, concrete block, Construction materials
eventually form daughter plants. It also produces
large quantities of seeds that are viable for up to 30
years. Because of water hyacinth’s ability to quickly
reproduce, populations often double in size in just two
weeks. [2]Water hyacinth (WH) is a floating perennial plantthat is native to the Amazon and has spread to of thesouthern united states. It prefers warmer climates andhas board, thick, and glossy leaves that are 10-20 cm
across. The hanging roots of the plant feathery andpurplish-black in color.
Once it escapes into waterways, however, water
hyacinth becomes an aggressive invasive species. In
fact, it has been named one of the 10 worst weeds andthe most widespread and damaging aquatic plant
species in the world. But even without seeds, its
growth rate is among the highest in the plant world,
as it reproduces vegetative by short runner stems thatbranch out from the base of the plant.
Therefore, Water hyacinth (WH) are many
advantages. However, there has huge effect toenvironment life cycle. Thus, it will be great which
use weed as cement replacement or concrete
aggregate were supported in concrete properties
According to using biomass as cheap insulation
concrete block materials admixture with difference ofmix proportion by using water hyacinth dried

INTRODUCTION
The growing demand of construction in Thailand
has increased usage of construction materials aslightweight concrete block which many types ofbuilding as residential and warehouse construction.
The benefits of using lightweight aggregate concreteare 1) reduce in dead loads making savings infoundations and reinforcement, 2) improved thermal
properties, 3) improved fire resistance, 4) savetransporting and handling precast units on site and 5)
reduce in formwork and propping. On the other hand,convention concrete making is not entirely
environmentally-friendly, and this has enthused
research on seeking greener alternative material for
concrete.
Light-weight concrete has less density than anormal concrete. It's a new type of concrete thatcreate from a natural material such as Portland
cement, sand, lime, gypsum, water and air bubble
disperser component in a right amount. Property oflightweight concrete: heat proof, sound proof, fire
proof, hardened, light weight, easy to use, energy
saving, reliable size and long age for usage [1]Water hyacinth (WH) has known as one of thefastest growing plant. Its primary means ofreproduction is by way of runners or stolons, which
516

SEE - Bangkok, Thailand, Nov.11-13, 2019

cellulose, sawdust and stone dust by 1:9 ratio which
compressive strength test was half of standard
concrete blocks. Heat conduction coefficient was
0.105 W/m. K so concrete blocks made from mixingof sawdust and stone dust are not suitable forconstruction. [3]Fiber cement material were made of cement paste
containing coconut coir fibers and oil palm residues
which used as roof sheet and siding materials to
reduce heat transfer through buildings and energy
conservation. The investigation focused mainly on
the effects of both cellulose fibers on the physicalmechanical and thermal properties of products which
the results, the mixtures of fiber cement products
containing 5% of both cellulose fibers by weight ofPortland cement yielded optimal physical andmechanical properties. The thermal conductivity of
the fiber cement pastes was 66% less than that of thecontrol specimens. [4]According to previous researches which use
natural fibers derived from agricultural residues todevelop fiber cement products with better soundinsulation properties. To study the parameters that
affect the density, compressive strength, flexuralstrength and sound insulation of the fiber cement
materials. The fiber cement specimens consisted ofPortland cement type 1, limestone powder, water,
sand, natural fibers, including coconut coir fiber andoil palm fiber, at the levels of 5%, 10%, 15% and 20%
by weight replacement and casting fiber cement
specimens of 8, 12 and 16 mm thickness. Increasing
the percentage replacement of the natural fibers, thedensity, compressive strength and flexural strength ofthe materials have decreased. Physical andmechanical properties of the fiber cement boards
containing coconut fibers were better than containing
oil palm fibers. [5]Similarly, the research which investigated on the
behavior of concrete with rice husk ash after exposed
to different high temperatures (200, 300 and 400 C).
Then, samples were measured compressive strength
and water permeability of concrete. The results
showed that the strength of concrete reduced after
exposure to high temperatures compared with control
concrete and tended to decrease with increasing
percentage of replacement of Portland. [6]In particular, the research that study on theproperty of lightweight concrete block made fromexpanded clay pellets and fly ash by focusing on themortar’s compressive strength to the various mixingof fly ash and cement. The result shows that anincreased proportion of fly ash resulted to mortar’s
low compressive strength. Mixtures of fly ash at
proportion of 10% and 20% exhibited at 225 and 224
ksc. respectively which it is higher than compressive
strength of cement. [7]Hence, the research was focusing on thepossibility of making a lightweight concrete with awater hyacinth that pass the qualification fromThailand industrial standard institute (TIS) [1] andthis paper will be researching on the physical andmechanical property of lightweight concrete that mix
with a water hyacinth.
METHODOLOGYPart 0: Materials and mix properties
Water hyacinth was located in Ladkrabang
district, a suburb area in Bangkok, Thailand. The
water hyacinth was cut into about 5 mm in length
using long knife and then dried in a hot air oven at 60̊
C for 48 hours. [ 8] and divided into 2 parts as was
blended and not blend ( by a bender) . There wereclassified in 3 classes 1) 0. 5 cm of length, 2) do notpass through sieves NO.50 and 3) pass through sieves
NO.50 which show in fig 1. The material used and its
quality was show in table 1.

a) b) c)Fig.1. The classification of water hyacinth in 3 classa) Water hyacinth dried powder pass throughsieves NO.50 (WH NO.50)b) Water hyacinth dried powder do not passthrough sieves NO.50 (WHnpNO.50)c) Water hyacinth dried 0.5 cm of length (WH
0.5 cm)Part 1: Compressive strength testing by Trial size ofwater hyacinth
In first part of the research, to find the optimal size ofwater hyacinth dried was used to determine the trendof maximum compressive strength. The water
hyacinth specimens were tested in three sizes as showin fig 1 and mixed proportion show in table 2. The
result was found that mortar by non- water hyacinth
adding, mortar with water hyacinth dried powderwhich pass through sieves NO.50 adding, mortar withwater hyacinth dried powder do not pass throughsieves NO. 50 adding, mortar with water hyacinth
dried 0. 5 cm of length adding were 369. 02, 233. 27,
216. 15 and 165. 39 ksc of compressive strength,
respectively and were presented in table 3. The water
hyacinth dried powder pass through sieves NO. 50
was optimal size for this part of researchPart 2: The experiment for finding optimal ratio ofwater hyacinth dried powder pass through sieves
NO.50
In second part, after found optimal size ofwater hyacinth dried powder was used to determine
the trend of maximum compressive strength for using
in the research. The ratio of water hyacinth by sand
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SEE - Bangkok, Thailand, Nov.11-13, 2019

replacement were classified in 5 states as 0% , 2. 5% ,5.0% 7.5% and 10%.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2: Mixed proportions
Ratio
Description
A

Cement plate

C

S

WH

W

1.00

2.00

-

0.60

1.00

2.00

0.03

0.60

1.00

2.00

0.03

0.60

1.00

2.00

0.03

0.60

Adding Water Hyacinth 3% by mass of cement
B1-B5
C1-C5
D1-D5

Cement plate with water hyacinth dried powder pass throughsieves NO.50
Cement plate with water hyacinth dried powder do not passthrough sieves NO.50
Cement plate with water hyacinth dried 0.5 cm of length

Table 3: Result of compressive strength Test by Trial size of water hyacinth
Description

Weight(g)

Cross-sectional
Area (cm2)

Age(days)

Compressive
Strength (ksc)Mortar by non-water hyacinth adding

258.0125.10

14369.02Mortar with water hyacinth dried powder
pass through sieves NO.50 adding

251.5225.47

14233.27Mortar with water hyacinth dried powder do
not pass through sieves NO.50 adding

252.0825.35

14216.58Mortar with water hyacinth dried 0.5 cm oflength adding

247.2925.32

14165.39

Table 4: Mixed proportions of mortar with water Hyacinth dried powder pass sieves NO.50 adding
Description
A
B1-B5
C1-C5
D1-D5
E1-E5

C
1.00
1.00
1.00
1.00
1.00

MortarMortar with water hyacinth dried powder
pass through sieves NO.50 adding

S
1.00
1.00
1.00
1.00
1.00

Ratio
WHSR*
0%
2.5%
5.0%
7.5%
10%

W
0.65
0.65
0.65
0.65
0.65

Table 5: Mixed proportions of mortar with water Hyacinth dried powder pass through sieves NO. 50 adding and
CLC foaming agent
Description
A
B1-B5
C1-C5
D1D5
E1-E5

MortarMortar with water hyacinth dried powder
pass through sieves NO.50 and CLC
foaming agent adding

519

C
1.00
1.00
1.00

S
1.00
1.00
1.00

Ratio
WHSR*
0%
2.5%
5.0%

1.00

1.00

7.5%

0.68

44.08%

1.00

1.00

10%

0.69

44.08%

W
0.65
0.66
0.67

CLCFA*
44.08%
44.08%
44.08%

SEE - Bangkok, Thailand, Nov.11-13, 2019

hours, wipe surface and harden mortar measured
mass in 3 minutes, follow the equation 1.2

Table 1: Materials and properties
Materials
SymbolProperties
Ordinary Portland
CementC
cementFine aggregate
S
River sand%Absorption =

WH

AD

x 100

(1.2)

WHnp NO.50
RESULTS

WH 0.5 cm
CLC Foaming
agent

Wd

Ws : Wet weight (Kg)
Wd : Dry weight (Kg)

WH NO.50
Water hyacinth

Ws-Wd

Result of part 3. 1 Compressive strength testing of
WHSR mortar and WHSR and CLCFA mortar.
The representative of compressive strength of
WHSR mortar were measured by compressive load
tester in the Table 4 which mass of cement and water
cement ratio were controlled by mortar cement ratio
1 : 1 ( Portland cement type 1 : river sand) . The
general mortar ( non- WHSR) is on dimensinal
specimens of 10x10x10 cm were 284. 94 ksc ofcompressive strength. Fig 2 was presented result of
this study as WH sand replacement retio 2. 5% , 5% ,7.5% and 10% were 225.99 ksc, 171.45 ksc, 6.09 ksc
and 4.23 ksc of compressive strength, respectively.
On the other hand, the CLCFA mortar ( nonWH) on dimensinal specimens of 10x10x10 cm were167. 56 ksc of compressive strength. WHSR and
CLCFA mortar were present on fig 2 as WH sandreplacement retio 2. 5% , 5% , 7. 5% and 10% and
CLCFA adding were 136. 85, 156. 37, 5. 39 and 6. 26
ksc of compressive strength, respectively.

Protein based

Part 2. 1: The sample of mortar with water hyacinth
dried powder pass through sieves NO.50 adding.
Mixed proportion of mortar with water
Hyacinth dried powder which pass through sieves
NO.50 adding was shown in table 4.
Part 2. 2: The sample of mortar with water hyacinth
dried powder pass through sieves NO. 50 and CLC
foaming agent adding.
Mixed proportion of mortar with water
Hyacinth dried powder pass through sieves NO. 50
and CLC foaming agent adding was show in table 5.

Compressive Strength (ksc)Part 3: Physical properties Testing
Part 3.1: Compressive strength testing
The sample, which passed 14 days, were
tested its compressive strength according to Thailand
industrial standard institute TIS. 1505- 2541 bycompressive load was controlling between 0.05 - 0.20
N/mm2/sec until failure.
Part 3.2: Dry density testing
The dry density of mortar testing was
according to Thailand industrial standard institute
TIS. 1505- 2541 by measured volume sample thendried in a hot air oven at 105±5 ̊ C for 24 hours,
weight after dried and follow the equation 1.1.

350
300
250
200
150
100
50
0
0.0

2.5

5.0

7.5

10.0

% of WHSR
WHSR mortar
WHSR and CLCFA mortar

mass of sample

dry density = Volume of sample(1.1)

Fig.2. Compressive strength Test
Result of part 3. 2: Dry density testing of WHSR
mortar and WHSR and CLCFA mortar.
The representative of dry density of WHSR
mortar were measured and followed by equation 1. 1.
The general mortar ( non- WHSR) is on dimensinal
specimens of 10x10x10 cm were 1696. 57 kg/ m3 ofdry density. Fig 3 was presented result of this study
as WH sand replacement retio 2. 5% , 5% , 7. 5% andPart 3.3: Water absorption testing
Water absorption testing also followed by
Thailand industrial standard institute TIS. 1505-2541
which the sample dried in a hot air oven until constantweight more than 24 hour at 105±5 ̊ C then cool down
to room temperature more than 4- hour, measured
mass. Therefore, curing sample in the water, after 24

520

SEE - Bangkok, Thailand, Nov.11-13, 2019

10% were 1656. 59, 1533. 52, 1388. 49 and 1347. 14(kg/m3) of dry density, respectively.
In the same way, the CLCFA mortar ( nonWHSR) is on dimensinal specimens of 10x10x10 cm
were 1526. 98 ( kg/ m3) of dry density. Fig 3 waspresented result of this study as WH sand replacement
retio 2. 5% , 5% , 7. 5% and 10% were 1445. 57 ,1460. 66, 1373. 41 and 1324. 31 ( kg/ m3) of dry
density, respectively.

replacement ratio both of WHSR mortar and WHSR
and CLCFA mortar at 5% of water hyacinth driedsand replacement were 171. 45 and 156. 37 ksc ofcompressive strength, according to TIS 2601-2556.
2) The percentage of water hyacinth driedsand replacement was increase and it caused density
decreasing. The lowest density was obtained for
WHSR mortar, WHSR and CLCFA mortar on 10%
as 1 4 . 1 3 4 7 and 2 1 . 1 3 4 2 ( kg/ m3) respectively.
Nonetheless, there was not pass the standard of TIS
2601-2556. Hence, the optimum percentage of water
hyacinth dried sand replacement ratio was 5% as
WHSR mortar, WHSR and CLCFA mortar, with adensity of 1533. 52 and 1460. 66 kg/ m3, respectively
which be able to classify in lightweight concrete
block type C16 according to TIS 2601-2556.

40

35

Absorption (%)

Density (kg/m3)

Result of part 3.3: Water absorption testing of WHSR
mortar and WHSR and CLCFA mortar.
The representative of water absorption of
WHSR mortar were measured and followed byequation 1.2. The general mortar (non-WHSR) is on
dimensinal specimens of 10x10x10 cm were 16. 29%
of water absorption. Fig 4 was presented result of thisstudy as WH sand replacement retio 2.5%, 5%, 7.5%
and 10% were 14.64%, 17.84%, 30.73% and 33.89%
of water absorption, respectively.
1800
1600
1400
1200
1000
800
600
400
200
0

30
25
20
15
10
5
0
0.0

0.0

2.5
5.0
7.5
% of WHSR

2.5

5.0

7.5

10.0

% of WHSR

10.0

WHSR mortar
WHSR and CLCFA mortar

Fig.4. Water absorption Test

WHSR mortar
WHSR and CLCFA mortar

3) Water absorption was increased by thepercentage of water hyacinth dried sand replacement
increasing. The lowest Water absorption was
obtained for WHSR mortar, WHSR and CLCFA
mortar on 2.5% as % 64 . 14 and . 17 09% respectively
which lower than mortar. For this result, the optimum
percentage of water hyacinth dried sand replacement
ratio was 5% as WHSR mortar, WHSR and CLCFA
mortar, with a density of % 8 4 . 1 7 and . 1 8 15% ,respectively which according to TIS 2601-2556.
This study investigated the mixing of water
hyacinth dried sand replacement ratio, size of water
hyacinth dried sand, compressive strength testing, dry
density and water absorption testing were carried out
in a ratio can be summarized that the optimal size andratio in this study were water hyacinth dried powderwhich pass through sieves NO.50. As a result, thecompressive strength much higher than standard ofTIS 2601-2556 as 20.4 ksc, WHSR mortar whichhave 7.5 and 10% of water hyacinth dried sandreplacement do not pass the standard. Hence, 2.5 and5.0% of water hyacinth dried sand replacement were
optimal conditions for producing lightweight
concrete block. The mortar which contain 2.5% of

Fig.3. Density Test
Similary, the CLCFA mortar )non-WHSR( is on
dimensinal specimens of 10x10x10 cm were 16.95%
of water absorption. Fig 4 was presented the result of
this study as WH sand replacement retio 2.5%, 5%,
7.5% and 10% were 17.09%, 18.15%, 30.8% and34.2% of water absorption, respectively.
CONCLUSIONSThe study has been investigated the possibility ofmaking a lightweight concrete with a water hyacinth
which was qualified from Thailand industrial
standard institute ( TIS) and the physical andmechanical properties. The main result can beconcluded as follow:
1) The compressive strength was decrease
when the percentage of water hyacinth dried sandreplacement was increase. It was found that thecompressive strength was significantly reduced bywater hyacinth dried sand replacement on 7. 5. theoptimum percentage of water hyacinth dried sand
521

SEE - Bangkok, Thailand, Nov.11-13, 2019

WHSR was 225.99 ksc of compressive strength,
which is the highest in this study compared with 5.0%of WHSR and CLCFA was 156.37 ksc ofcompressive strength. In contrast, the density andwater absorption of 5.0% of WHSR and CLCFA were1460.66 kg/m3 and 18.15% which is the best
condition. The optimal condition does not necessary
to have high compressive strength load, it have to beover qualification of the Thailand Institute Standard
and focus on eliminated more water hyacinth volume.
As a result, 5.0% of WHSR and CLCFA mortar was
an optimal condition. Furthermore, it would be
reduced water hyacinth in 1 m2 in the canal bystandard size of lightweight concrete block
production which is an environmentally-friendly
material.

crumb rubber and cement replacing with fly ash
from coal power plant” , Veridian E- Journal,
Science and Technology, Silpakorn University,
vol. 3 (4), 2016.
[4] Lertwattanaruk, P.
and Suntijitto, A. ,“ Properties of natural fiber cement materials
containing coconut coir and oil palm fibers forresidential building applications” , Construction
and Building Materials, vol. 94, pp. 664- 669,
2015.
[5] Lertwattanaruk, P.
and Masuwan, K. ,“Investigation of sound Insulation Properties ofFiber Cement Board Containing Natural Fiber”,
KMUTT research and development Journal, vol38(1), 2015.
[6] Ladbat, N. , Ongwandee, M. , and
Homwuttiwong, S., “Compressive strength andpermeability of concrete with rice- husk ash
exposedtovarioustemperatures,
Mahasarskham
University
Research
Conference, 2014.
[7] D. G. Roy,S. P. Mehrotra and P. C. Kapur,“ Lightweight masonry blocks from fly ashpellets” , Resources and Conservation,
vol.11(1), pp.63-74, 1984.
[8] Ouensanga, A., “Variation of fiber compositionin sugarcan stalks” , Wood and fiber science,
vol.21(2), pp.105-111, 1989.

REFERENCES[1] Thai industrial standard institute, Ministry ofindustry, “ Aerated lightweight concreteelements” , Thailand Institute Standard(TIS.2601-2556), vol. 4562, 2013.
[2] Ekasilp, W. and Boonthanomwong, C. ,“ Thermal Insulator Performance of Water
Hyacinth and Sawdust Hollow Concrete Block”,
National Research Conference, 2014.
[3] Budnumpecth, T. and Tanpaiboonkul, N. ,“Properties of lightweight concrete containing522

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STUDY ON THE PROPERTIES OF CEMENT MILK ADDED WITH
BAKING SODA -COMPRESSION STRENGTH ESTIMATION FROMBLEEDING REDUCTION AND INITIAL ELECTRICAL RESISTIVITY
Yasuhide Mochida 1, Joshua O. Ogunbiyi 2 ,Makoto Minemoto2,and Keisuke Funato3
1
Prof. Ritsumeikan University, Japan
2
Graduate School of Science and Engineering, Ritsumeikan University, Japan
3
Associate Prof. National Institute of Technology, Ishikawa, Japan

ABSTRACT
Cement milk is used for earth retaining structures, pile construction and also for ground improvement throughcement deep mixing and other methods. However, it is quite difficult to estimate or evaluate the compressive
strength of concrete mix during curing phase of the construction process. Excessive bleeding also remains apertinent issue. Excessive absorption of moisture eventually leads to expansion, cracks, and causes reduction in
concrete strength. This research was focused on reducing bleeding of cement solidified materials by adding baking
soda. Baking soda acts as a catalyst and promotes hydration of cement through hydrolysis reaction. An alkali silica
reaction occurs within the cement milk to form alkali silica gel. This shortens the setting time, and curtails excess
moisture. The Laboratory experiments revealed that addition of about 3% of backing soda was the most effective.
Furthermore, from the electrical resistivity and the compressive strength of 24 hours of the cement solidified
material to which 1 to 4% of sodium bicarbonate was added, the compressive strength of 28 days of the material
was also accurately estimated.
Keywords: Cement milk, Bleeding, Baking soda, Electrical resistivity, Compressive strength
majorly in freshly mixed concrete. Bleeding is widely
described as the upward movement of moisture
towards the surface as a result of the unevensettlement of heavier particles constituent of the mix.
Although various researches have been conductedon the possibilities of controlling bleeding including
the use of slag as addictive, bleeding still remains a
concern with regards to quality assurance of the useof cement milk especially in marine.
The purpose of this study is to examine andascertain the hypothesis that backing soda can be usedas addictive in cement milk to control the bleeding
rate of the material during construction process. It is
expected to stabilize the hydration reaction of thecement.

INTRODUCTION
Cement milk or slurry is generally considered asliquefied cement. It is a mixed liquid that is composedof cement, water and other relative chemical additives.
Cement milk has varied densities depending on theapplied degree of mix. Cement milk has uniquemechanical properties as it can flow under gravity andare also capable of being pumped. It can also be usedin under water projects. In the past few decades, theuse of cement milk in relative construction projects
has greatly increased.
In Japan, cement milk is used for earth retaining
structures, pile construction and also for ground
improvement through cement deep mixing. The
Cement Deep Mixing (CDM) method is a techniqueto chemically solidify and strengthen soft ground byin-situ mixing of the soil with cement slurry. Thismethod of ground improvement is environmentallyfriendly and cost effective.
This method has been repeatedly used in ground
improvement applications to prevent embankment
instability and settlement, improve ground stability
for construction projects, as countermeasures againstliquefaction, and as reinforcement of ground to
improve earthquake-response of superstructures [5].
The use of cement milk as a construction material
is widely acceptable. However, bleeding has been amajor constraint to the efficiency of this material inconstruction projects. Bleeding is an importantphenomenon in construction process. This occurs

LITERATURE REVIEWReal time monitoring and control of high-quality
execution is an important aspect in construction
management.
Development of techniques andtechnology with such features has been a growing
concern. Ground improvement processes are also notleft out of these concerns.
For example, while using cement milk material for
in-situ cement deep mixing, it will be important tomonitor the flow rate of the cement slurry, penetration
and retrieval speed, and the rotation speed of themixing shaft including the accuracy of degree mix ofthe constituents.
Different technology has been developed to523

SEE - Bangkok, Thailand, Nov.11-13, 2019

monitor such processes including the use of computer
aided monitor system for real time monitoring andanalysis of the construction process. The use ofelectrical resistivity has also been engaged to provide
instant feedback on the mixing degree between
constituents of the cement milk during placement.
This is accurately deduced from the change inresistivity of the resulting compound.
During the mixing process of concrete or cement
slurry in our previous experiments, it has been
established that with regards to the ion concentrationof the primary materials, the electrical resistivity of
the compound is adequately lower when properly
mixed and increase in cases where the compound isincompletely stirred [3].
Aside the aforementioned issues, another factor
that relatively affects cement mixture is bleeding.
Bleeding is equally important in construction process.
This occurs majorly in freshly mixed concrete.
Bleeding is widely described as the upward
movement of moisture towards the surface as a resultof the uneven settlement of heavier particles
constituent of the mix.
In structures using cement milk such as piles,
ground improvement and cement soil mixture, theoccurrence of excessive bleeding results to theformation of a weak hardened cement milk layer andcause problems relative to level control.
Although bleeding plays an important role duringconcrete setting as it replaces evaporated moistureand thus prevents excessively early hardening.
Excessive bleeding leads to strength loss by
producing laitance at the surface of the concrete. This
also leads to wear resistance and poor bonding
between the layers of the concrete.
Aside the cement water ratio, cement type and thecorresponding size of the fine aggregate also indicatesthe bleeding rate to a large extent. In the cases ofgrouting, factors such as pressure and height also
affect the rate and percentage of bleeding.
Although Addition of supplementary binding
materials, use of finer cements including the
introduction of an air entraining admixture can beeffective in controlling bleeding rate however, caremust be taken to ensure that the rate of chemicalcomposition of the mix does not end up increasing the
bleeding rate.
In this study, we experimentally verified thepossibility of controlling bleeding by adding baking
soda to cement milk. The purpose is to examine thebehavior of baking soda as a catalyst to promote thehydration reaction of cement.
The effect of the addictive on bleeding rate of
cement milk including the electrical resistivity was
also monitored relatively to the compressive strength.
A method of estimating the 28-day compressive
strength of cement milk from the initial electricalresistivity and the compressive strength, using astrength prediction based on the electrical resistanceof the cement milk was proposed.
In this way, we aim to realize a construction
management method which is easy to operate withhigher precision and quality assurance.
MATERIALS
Materials used for this study includes cement, waterand baking soda.
In the experiment, sodium
bicarbonate was mixed with cement milk in four
different ratios. The bicarbonate and cement ratio (B/ C) was at 1%, 2%, 3% and 4%. These were mixed
with 70% water and marked as the W / C ratio. The
detail of each of these samples including the total
weight of each specimen is as shown on Table 1.
Table 1 Recipe of the specimens

Water
14
14
13
13

Weight (Kg)
Backing
Cement
soda
0.2
19
0.4
19
0.6
19
0.8
19

Total

W/C
(%)

B/C
(%)

33.2
33.4
32.6
32.8

70
70
70
70

1
2
3
4

EXPERIMENTAL EVALUATIONS
Bleeding Test
In cases where concrete retains excess moisture,
cracks could occur. This results to a decrease instrength of the concrete. In this study, the impact andinfluence of baking soda through the soda cement
ratio was noticed.
The bleeding rates were noted at the initial age of
0-24 hours including 15 minutes, 30 minutes, and 1
hour. The bleeding rate was also recorded at day 1, 3,
5, 7, 14, 21 and 28.
Table 2 Bleeding Test Results
B/C

VolumeBleeding

Immediate

1day

2days

No1

1%

585

560

570

4%

3%

No2

2%

590

571

581

3%

2%

No3

3%

670

660

660

1%

1%

No4

4%

660

650

660

2%

0%

Table 2 shows the results of bleeding experiments
at each baking soda cement ratio (B / C) within thefirst 48hours of the experiment. Although there is nomuch difference in the result recorded from thespecimens, the material with more bicarbonate shows
the least amount of bleeding.
524

SEE - Bangkok, Thailand, Nov.11-13, 2019

Baking soda acted as a catalyst and the hydrolysis
reaction promotes the continuous hydration of thecement. Alkali silica reaction occurred within the
cement milk to form alkali silica gel. This reaction
shortened the setting time and bleeding was reduced.

the increase of the baking soda cement ratio as shownin Fig. 2. The values at B / C of 1% and 2% showedsimilar tendency until the 28th day. But at B / C of
10

Electric resistivity(Ω・m)Electrical Resistivity
In this experiment, instant feedback on the mixing
degree of the cement milk was achieved
usingelectrical resistivity.
Electrical resistivity quantifies the extent ofresistance of a material to the flow of current. The
sensor is made up of electrodes that measures bothcurrent and voltage when inserted into a compound.
Using the Ohms law, the resistance to current flow
can be calculated.
During the mixing process of constituents ofground improvement bodies, or cement slurry inprevious experiment, the relationship between theion concentration of the primary materials relative tothe electrical resistivity of the compound wasestablished by comparing the resulting values when
the compound is properly mixed and cases where thecompound is incompletely stirred [3]. This has further
improved the quality assurance during construction
management.
2.5

1 day
5days
14days28days

1

0.1

0.01
0.01

0.1
1
10
Material age (day)100

Fig. 2 Relationship between age and the electricalresistivity of the specimens
3% and 4%, there was steady increase in the electricalresistivity values within the first 14days. However,there was a sharp increase in values afterwards andthrough the curing age.

3days
7days
21daysUniaxial Compressive Test

2

Electric resistivity(Ω・m)

1%
2%
3%
4%

In this study, the compressive strength test of eachexperimental sample with different ratio of baking
soda was also conducted.

1.5

20

0.5

15

Compressive
strength(N/mm2)

1

10

0

0

2

4

6
B/C (%)

Fig. 1 Relationship between the B/C ratio and theelectrical resistivity of the specimens

5
1 day
7days
28days00

In this study, the Electrical resistivity of theconcrete mix was recorded at day 1, 3, 5, 7, 14, 21and
28 of curing. Fig. 1 shows the relationship between
sodium bicarbonate cement ratio (B / C) and electricalresistivity at each day.
At the age of 1 to 7 days, the specific resistancevalue increased only moderately regardless of thebaking soda cement ratio, but after 14 days, thespecific resistance value increased remarkably with

3days
14days2

5days
21days4

B/C (％) 6

Fig. 3 Relationship between B/C ratio
compressive strength of the specimensandAs shown in Fig. 3 the compressive strength of
specimens with B/C of 1%, 2%, and 3%, shows only
slight difference in increment between the day 5-21
and rises steadily till the 28th day. However, there wasa huge difference with the 1% B/C specimen. There
was a sharp rise in the compressive strength from thefirst 24hours to the 7th day. A much higher strength
525

SEE - Bangkok, Thailand, Nov.11-13, 2019was recorded at the 28th day compared to the otherspecimens.

Formulas (1) and (2) are used with reference to theevaluation method of prior research [1]. From theTemperature
20
The corresponding temperature differences of thespecimens were monitored during the course of theexperiments.

1%

80

2%

70

temperature(℃)

Compressive strength (N / mm2)

90

18

3%

60

4%

50

40

16
14
12
10
8
6
4
2
0

30

0

1%

2%

3%

4%

1

2

3

Electric resistivity (Ω · m)

20

Fig. 5 Relationship compressive
electric resistivity

10strength

and

0
0.01

0.1

1

10

Material age (day)100

results of these experiments, evaluation equations
were proposed by setting the constants a and b of Eq.
(1) and the coefficients K1 and K2 of Eq. (2).
The relationship between material age andelectrical resistivity is shown in Fig. 6. Since thematerial age and the specific resistance value areclose to a linear relationship, it can be expressed bybthe near-form equation of Y  aX (X: material age,
Y: specific resistance value) based on material age
and specific resistance value.
Since the value of a does not have a big differencein B / C, an average value is used this time. Since thevalue of b varies depending on the amount of baking
soda blended, an approximate expression was usedfrom the tendency of the inclination

Fig. 4 Relationship age and temperature of thespecimens
As shown in Fig. 4, the temperature peaked atabout 75 ° C after 10 hours and showed the sametendency in all baking soda ratios. However, thespecimen with B/C 4% showed a rise in temperatureslightly later than the other samples. Generally, thetemperature dropped back at a drastic rate within thefollowing 15 hours after attaining the peaktemperature.
Also from Fig. 2, it will be observed that eachspecimen increased in specific resistance with rapid
temperature change 5 hours after the start of theexperiment. After 7 hours, the specific resistancevalue gradually increased.

 ( X ) = aX b +  (1) -  (1ave) (1)

ρ(X)： Electric resistivity of the material at age X
Relationship between Compressive Strength andElectric Resistivityday(Ω∙m)
ρ(1)：Measured electrical resistivity of the material

As shown in Fig. 5, the compressive strengths of
all the specimens increase with increase in electricalresistivity although the response followed different
trends. For instance, specimen with B/C of 1% showsa rapid increment in Compressive strength to attainthe peak value compare to others.
EXPERIMENTALEVALUATIONCONSIDERATION

at age 1 day (Ω∙m)ρ(1AVE) = 0.27675[Ω∙m]ρ (1AVE) : the average value of 1 day of thematerials as shown in Table 3

a  0.292925 b  0.3656B0.3984

AND

B: Baking soda cement ratio [%]526

SEE - Bangkok, Thailand, Nov.11-13, 2019qu(28): Compression strength of the material at age
10Electric resistivity(Ω・m)

0%
2%
4%
Power (1%)
Power (3%)

28 day (N/mm2)

1%
3%Power (0%)
Power (2%)
Power (4%)qu(1): Measured compression strength of the material
at age 1 day (N/mm2)
ρ(28): Estimated electrical resistivity of the material
at 28 days of age (Ω∙m)

1

y = 0.3122x0.613
R² = 0.9895
y = 0.1968x0.7205
R² = 0.9994

0.1
1

10



y = 0.2629x0.6084
R² = 0.9876

K1 = 13.278B (-0.868) N / mm 2  (  m) 

y = 0.3494x0.3679
R² = 0.9789

K2: ρ(1)(3)※This time, using the measured electrical resistivity(Ω ∙ m) of 1 day of material age

y = 0.2472x0.4621
R² = 0.9825

Material age (day)100
Table 3 Electric resistivity and average value for 1day material

Fig. 6 Evaluation of material age and electricalresistivity
The electrical resistivity at 1 day of material age in
Fig. 6 shows a somewhat constant value regardless of
B / C. As shown in Fig. 7, in the trends of material
ages 1 to 28 days, changes in specific resistance value
and compressive strength ratio were almost constantat each B / C. As mentioned above, the evaluation
formula was proposed with reference to the following
coefficients K1 and K2.

1da
y

1%

2%

3%

4%

0.34
4

0.23
3

0.24
6

0.28
4

Average value
0.27675SUMMARY AND CONCLUSIONAs shown in Fig. 7 and Fig 8, the electricalresistivity of the specimens within the material age of
28days which was measured and recorded during thecourse of the experiment was verified according to Eq.
(1) and was compared with the estimated value of thecompressive strength according to Eq. (2). It was
deduced that both are highly similar.
Table 4 Validity of evaluation formula
Evaluation
formula(N/mm2)1%
2%18.811
13.59318.07513.8463%
4%

14.771
15.66813.62415.889Also, the electrical resistivity at 1 day of thespecimens was derived using Eq. (1) and used withthe measured compression at 1 day of material age in
Eq. (2). The strengths were used to correctly estimate
the 28-day compressive strength of cement milk
mixed with baking soda.

Fig. 7 Evaluation of electrical resistivity andcompressive strengthqu(28 ) = K1   (28) - K2  qu(1) Experimental
value (N/mm2)

(2)
527

SEE - Bangkok, Thailand, Nov.11-13, 2019

3.0

1%
2%

2.5

Readings (ρ (28))

In addition, it has been verified that this method
can be used to estimate the 28-day compressive
strength of cement milk from the initial electricalresistivity and the compressive strength. This isachieved using strength prediction based on theelectrical specific resistance of the cement milk. Thismethod can also be used as a tool in preempting likely
behavior of the resulting material from the cement
milk mixture towards fostering quality assurance inconstruction management.

3%
2.0

4%

1.5
1.0

REFERENCES
0.5[1] Mochida Y., M. Matsuura, Study on Strength
Estimation of Soil Cement Used In theEmbedded Pile Method by Electrical Resistivity
Measurement.
International
Journalof
GEOMATE,17/59, 74-81,2018/7[2] Mochida Y., Fujii M., Study on the control ofconstruction quality of the fixed solution aroundthe pile of embedded pile using electricalresistivity survey Part 1) Estimation ofcompressive strength by electrical resistivity of
cement milk. Meeting of the Architectural
Institute of Japan Abstracts of Academic
Lectures, 845-846, 2016/8[3] Mochida Y., Indra H. Promotion of ICT
utilization by electric resistivity management influidization treatment process for ground
improvement.
International Journal of
GEOMATE (2016)[4] Mochida Y., Tsukamoto M., Development of
fluidization ground improvement method using
cement-based solidifying material and local soil(Part 1, Construction and management method),Technical Report of the Architectural Institute ofJapan, 19/42, 485-490, 2013/06[5] Aly A., Nabil M., Mohamed H., Takeshi K
Stabilisation of soft soil with recycled plasteradmixtures. Ice proceedings, Volume 171 (2018)
Issue
G11,
Page
12-20
https://www.icevirtuallibrary.com/doi/10.1680/j
grim.16.00038[6] Cement Deep Mixing Association. Corporate
Journal on Cement Deep Mixing, 2015.
www.cdm-gr.com

0.0
0.0

0.5

1.0 1.5 2.0 2.5
Estimated Value (ρ (28))

3.0

Fig. 8 Relationship between estimated values andmeasured electrical resistivity values

20

1%
2%

Readings (qu (28))

15

3%

4%
10

5

0

0

5

10

15

20

Estimated Value (qu (28))
Fig. 9 Relationship between estimated values andmeasured compressive strength values
It was finally deduced that baking soda can beused as a catalyst in controlling the bleeding rate of
cement milk or a cement soil mixture. Through analkali silica reaction within the cement milk to form
alkali silica gel, backing soda can shorten setting timeand reduce bleeding rate while fostering thecontinuous hydration of the cement milk.

528

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SHEAR STRENGTH AND PERMEABILITY ANALYSIS OFGEOTEXTILE FROM PINEAPPLE LEAVES AND LUFFAINZ Baharuddin1, Hairin Taha2, RC Omar 3, R.Roslan4 and S.Nadirah5
1,2,3,4
Institute of Energy Infrastructure,
5
College of Engineering, Universiti Tenaga Nasional, Malaysia.

ABSTRACT
Geotextiles are commonly utilized in many geotechnical and civil engineering applications for soil
reinforcement, erosion control, drainage, filtration and separation. The market trend for geotextiles nowadays
dominates more on synthetic materials such as polyethylene and polyamide. However, synthetic geotextiles canbe costly when the application involves major construction and larger area. In term of environmental concern,
geosynthetic materials may contain chemical additives that could leak into the surroundings. Geotextile products
from natural fiber such as jute and coir are commonly available especially in India but the market for naturalgeotextiles is very competitive against polymeric geotextiles. In view of that, this study was aimed to design
natural geotextile from local plants. Pineapple leaves were used as the main fibre for the fabrication of geotextile
together with luffa and coconut flakes. Four types of designs were developed based on the seam type and numberof rows of stitching. The strength and permeability of the geotextiles were tested using direct shear box test andfalling head method. Results showed that the geotextile design with J seam and two rows of stitches has thehigher strength and lower permeability. This study demonstrated the beneficial use of agricultural waste frompineapple leaves that can be recycled into sustainable product.
Keywords: geotextile; pineapple leaves; luffa; shear strength; permeability
direction based on ASTM D4595 “Standard Test
Method for Tensile Properties of Geotextiles by thewide width strip method”. Another test based on
ASTM D4884 can also be done to test the seamstrength [5].
In general, there are two types of seamcommonly used to produce geotextile, thesuperimposed seam (S seam) or prayer seam, and J
seam. The S seam is made by stitching two fabrics
together with one or more row of stitching. This is
the easiest type of seam. The J seam is more difficult
to make. It is done by superimposing two fabrics andfolded to produce a thickness of four plies which
contributes to higher seam strength [6]. This type ofseam has more strength compared to other type of
seam. For fabric geotextile, the seam is sewn 1 to 1.5
inches from the edge and folded to create a double
plies thickness. The thread type also affects thestrength of the geotextile. It should have similar or
higher durability. Numbers of rows of stitchingserve as the seam type colleague.
Geotextile should have higher mechanicalstrength due to the applied load of soil which is
directly transferred to it. The occurrence of soil
erosion and landslide is mostly caused by the
weakening soil that has losses its strength [7].
Several factors that affect soil failure include rainfall,erosion, construction activities and external loading.
Soil cannot resist tension but can withstandcompression. The shear strength of soil will decrease
when there is excessive water content in the soil.

INTRODUCTION
Geotextile is mainly used for soil reservation
especially in soil reinforcement, erosion control andreducing surface run-off. Other applications ofgeotextile include separation and filtration between
different type of materials, drainage and containment[1]. Geotextile can be defined as permeable textile
used together with soil, rock, earth, foundation or
geo-engineering materials. Some of the typicalmaterials used to produce geotextile include
polypropylene, polyethylene, polyamides orpolyester [2].
There are two categories of geotextile; woven
and non-woven. The woven geotextiles are
manufactured on a loom through the process of
weaving or knitting textiles which has two sets ofparallel threads [3]. This type of geotextile has
excellent tensile strength. Most geosynthetics are
woven type. The non-woven geotextiles are madefrom the process of mechanical or chemicalinterlocking or thermal bonding of non-woven fabric.
The materials are pressed together using adhesive orheat treatment. However, this type has lower tensile
strength compared to that of the woven type.
Several factors need to be considered when
designing geotextile such as the type of geotextile,
seam and stitch type, thread type, numbers of rowsof stitching and sewing equipment [4]. The strengthof geotextile was mainly influenced by the seamstrength and this can be tested using cross machine
529

SEE - Bangkok, Thailand, Nov.11-13, 2019

When the water overflow, the soil structure will
become loose and this results in soil erosion orlandslide. Natural geotextile from plant fiber canhelp reinforce and fertilize the soil at the same time,
unlike geosynthetics [8-9].
In this study, pineapple leaves waste and luffas
were used to produce the natural geotextiles for soil
reinforcement [10]. The concept was to utilize plantfibers which are acquired from local resources suchas the local farms and markets. Malaysia produces
more than one million tonnes of agricultural waste
annually [11]. Instead of burning the agro waste thathighly contribute to greenhouse gas emission, theagro waste could be recycled into sustainableproducts or converted into biomass as renewableenergy.
Pineapple ( Ananas comosus L.Merr) or known
locally as ‘Nenas’ is a tropical plant native to South
East Asia and planted as commodity crop in
Malaysia.
Pineapple
industry
contributes
significantly to the country’s economy and the fiberfrom the leaves can be developed into commercial
products [12].Pineapple leaf is rich in cellulose andbiodegradable. A study on pineapple leave fiber
showed that they are suitable for building andconstruction materials due to its highest cellulosic
content [13-14]. The fibers of pineapple leaves also
have the potential as alternative raw materials in
paper industries due to its good mechanicalproperties and high cellulose contents [15]. In recent
development, pineapple leaves were also found to besuitable alternative natural acoustic material forsound absorption due to the characteristics of its
fiber [16].
Luffa acutangula is extensively used throughout
the world as materials for hybrid biodegradable
geopolymer composites and sound absorbing [1718]. Luffa fiber has high cellulose content, low cost,biodegradable and absorbs water easily. It has athick texture that prevents the water to pass througheasily [19]. For this research, pineapple leaves waste
were obtained from a pineapple plantation in Johor,
Malaysia and Luffa fibers were obtained from
Sarawak, Malaysia.
The objective of this research was to design
natural geotextile from local plant fibers, andevaluate the strength of the geotextile throughpermeability and direct shear box test. The chosen
design based on seam type and number of rows of
stitching will be used to develop the naturalgeotextiles and tested on site to observe theeffectiveness of the geotextiles against erosion.

Four samples of geotextile designs arranged in threelayers were developed based on seam type and rowsof stitching (Fig.2). First, the pineapple leaves andluffa were dried outside for 72 hours until the leaves
and the luffa turned brown in color and completely
dried. This is important to ensure that there was nowater contained in the leaves. When the fiber is fully
dried, the mechanical strength of the fiber will also
increase. Dried coconut flakes were then added asmoisture absorber. Jute thread (5.0 mm thick) wasused to stich the geotextiles. Table 1 shows the typesof geotextile design according to seam type andnumber of rows of stitching which will be tested.

Fig.1 Natural geotextile from luffa and pineapple
leavesFig. 2 Three layers of geotextile

Table 1. Designs of geotextile
2. EXPERIMENTAL
Samples
2.1 Design of Natural Geotextile
The natural geotextile was designed from natural
fibre consist of pineapple leaves and luffa (Fig. 1).
530

Seam Type

Number ofrows ofstitchingSEE - Bangkok, Thailand, Nov.11-13, 2019

A

J

2

B

J

1

C

S

2

D

S

1

The shear strength of the geotextile was
influenced by the seam type and the number of row
of stitching. The results of shear stress at failure
against normal stress for Samples A, B, C and D are
shown in Table 2. Observation showed that the valueof cohesion has decreased, while the friction angles
had similar values but for Sample A, the cohesion
value was 0.00043 and the value for friction angle
was 36.9o. This showed that Sample A has thehigher shear strength compared to that of othersamples.

2.2 Direct shear box test
Laboratory testing was carried out to determine
the most appropriate design of geotextile for soil
reinforcement. The strength of the geotextile sample
was tested using direct shear box test following
ASTM D5321 guidelines. The test equipment
consists of a metal box (100 mm x 100 mm) inwhich the soil specimen and the geotextile will beplaced. The geotextile sample was placed on the top
and below the soil specimen. The strength between
the original soil and soil together with geotextile
sample was compared. The direct shear box test wasdone using different weights (5.0, 10.0 and 15.0 kg).
The type of soil used was sandy SILT withintermediate plasticity.

Table 2. Cohesion and friction angle values
SampleCohesion

Friction angle

A

0.004336.9

B0.002529.5

C

0.0022

28.6

D

0.002

28.4

2.3 Permeability test
The results of the direct shear box test showedsample A has higher strength compared to othersamples, which were 25.83 N/m2, 47.5 N/m2 and69.44 N/m2
for 5.0, 10.0 and 15.0 kg weightrespectively (See Figure 3-5). The shear strength has
decreased from sample A to D. The shear strength of
the geotextile was influenced by the number of rowsof stitching for sample A and C because the stitches
were stronger to hold the fabric together fromshearing.

The permeability of the geotextile wasdetermined through permeability test of falling head
method (ASTM D4491) as described in previous
study [16]. The test consists of flow of water passing
through soil sample connected to a standpipe thatprovides the water head and measures the volume ofpassing water through the sample. The standpipe
diameter is governed by the permeability of thetested soil specimen. Water was allowed to flow
through the sample until it reached the lower limit
and the time was recorded when the water in thestandpipe dropped from the upper to the lower level.
2.4 Experimental application
The geotextile was tested at the selected area.
The soil at the experimental site was classified as
sandy SILT with intermediate plasticity. The
geotextile (20 cm x 20 cm) was arranged on theeroded surface inside a grid measured 600 mm x 800
mm. Prior to that, the subsurface was cleared first to
remove foreign objects. The geotextiles wasproperly arranged on the surface. The sites with
geotextiles were observed for 35 days to monitor the
progress.

Fig. 3 Shear strength using 5.0 kg weigh

3. RESULTS AND DISCUSSION
3.1 Shear Box Test

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Table 3. Percentage of permeability increment
SampleSeam
type

Original
soilFig. 4: Shear strength using 10.0 kg weight

Coefficientofpermeability(k)
7.2 x 10-4

Increment
(%)

-

A

J

2.16 x 10-7

98.98

B

J

2.26 x 10-7

99.87

C

S

2.33 x 10-7

99.85

D

S

2.36 x 10-7

99.8

3.3 Geotextile Application
The results of permeability and shear box test
showed that the design of Sample A geotextile basedon J seam and two rows of stitching has higher
strength compared to other designs. Based on thesecriteria, the natural geotextile was assembled forexperimental site test against soil erosion. The
geotextiles were arranged on the eroded surface andobserved for 35 days. The observation was
documented on day 7, 14, 28 and 35 as shown in
Figure 6-9. After 35 days of geotextile application,
new batch of grass has grown through the naturalgeotextile, and the geotextile has integrated with thesoil. The eroded surface has been covered withvegetation. This study has demonstrated that thegeotextile from pineapple and luffa has performed asprotective cover for the exposed area.

Fig. 5 Shear strength using 15.0 kg weight

3.2 Permeability Test
The results of permeability test showed that
Sample A has low permeability due to the J seamtype design. Sample A has four plies with two rowsof stitching compared to S seam type which only has
two plies. The test demonstrated that the soil
specimen with geotextile was more impermeable.
The value of coefficient of permeability, k, has
increased when the geotextile samples were applied(Table 3). This showed that the presence ofgeotextile has decreased the permeability of the soil
specimen. The flow of water through the geotextile
took longer time to pass through compared to that oforiginal soil.

Fig. 6: Geotextile application on Day 7

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SEE - Bangkok, Thailand, Nov.11-13, 2019

friction force. The fiber from pineapple and luffa
also has lower permeability, thus, suitable for soil
reinforcement.
This study demonstrated the capability of
pineapple leaves and luffa as renewable resource fornatural geotextile. Thus, this innovative method is
cost-effective and can be developed as commercial
product that would contribute to the economy. On
top of that, natural geotextile from pineapple leaves
and luffa can provide green solution for sustainablesoil reinforcement and slope stabilization. The
design of geotextile from pineapple leaves and luffa
can encourage the recycling and processing ofagricultural materials into sustainable products.
Hence, the newly developed natural geotextile frompineapple leaves and luffa can be used to control soil
erosion.

Fig 7: Geotextile application on Day 14

ACKNOWLEDGMENTS
This study was supported by UNITEN grants
J510050884 (UNIIG 2018) and 201901001YCU/02.

REFERENCES[1] Zornberg, JG (2017), Functions and applicationsof geosynthetics in roadways. Procedia
engineering, 189, pp.298-306.
[2] Stepanovic, JM, Trajkovic D, Stojiljkovic D &Djordjic D, (2016),Predicting the behavior of
nonwoven geotextile materials made of polyesterand polypropylene fibers. Textile Research
Journal, 86(13), pp.1385-1397.
[3] Mishra SR, Mohapatra SR, Sudarsanan N,
Rajagopal K & Robinson RG (2017), A simple
image-based deformation measurement
technique in tensile testing of
geotextiles. Geosynthetics International, 24(3),pp.306-320.
[4] Mudgal A, Sarkar R & Shrivastava AK (2018),
Influence of geotextiles in enhancing the shear
strength of Yamuna sand. International Journalof Applied Engineering Research, 13(12),pp.10733-10740.
[5] Allen JM, Ferreira JA and Athanassopoulos C(2017), Laboratory study of geosynthetic clay
liner panel shrinkage forces and seam strength.
Geotechnical Frontiers, pp. 11-21.
[6] Guo W, Chu J & Zhou B (2015), Method toincrease seam efficiency for woven geotextile
materials. Geosynthetics International, 22(6),pp.404-410. Annnn B., Unpublished Work but
Accepted, Vol., Issue, Year.
[7] Haeri SM, Noorzad R & Oskoorouchi AM(2000), Effect of geotextile reinforcement on

Fig. 8: Geotextile application on Day 28

Fig 9: Geotextile application on Day 35

4. CONCLUSION
In this work, natural geotextile was designed
and developed using pineapple leaves waste andluffa for soil reinforcement. The geotextile wastested based on the strength and permeability using
shear box test and falling head method. From theresults, it was demonstrated that the geotextile
design with J seam and two rows of stitching had thehigher shear strength to encounter the application of533

SEE - Bangkok, Thailand, Nov.11-13, 2019the mechanical behavior of sand. Geotextiles
and Geomembranes, 18(6), pp.385-402.
[8] Kalibová, J, Jačka, L, & Petrů, J. (2016). The
effectiveness of jute and coir blankets for
erosion control in different field and laboratory
conditions. Solid Earth, 7(2), pp. 469-479.
[9] Müller, W. W., & Saathoff, F. (2015).
Geosynthetics in geoenvironmental engineering.
Science and technology of advanced materials,
16(3), pp. 034605.
[10] Omar RC, H. Taha, R.Roslan & Baharuddin
INZ(2019).
GEOTEXTILEFROMPINEAPPLE LEAVES AND BIO-GROUT
FOR
SLOPE
STABILIZATIONANDEROSION CONTROL. International Journal,17(60), 219-224.
[11] Saili, R., Muhamad, Z., & Aziz, N. H. (2017). A
Preliminary Study on Sustainable ManagementofPineapple
Waste:
Perspectiveof
Smallholders.
International
Journalof
Academic Research in Business and Social
Sciences, 7(6), pp. 2222-6990.
[12] Yusof, Y., Yahya, S. A., & Adam, A. (2015).
Novel technology for sustainable pineapple leaf
fibers productions. Procedia CIRP, 26, pp.756760.
[13] Laborel-Préneron A, Aubert JE, Magniont C,
Tribout C & Bertron A (2016), Plant aggregatesand fibers in earth construction materials: A
review.Construction and building materials, 111,
pp.719-734.
[14] Asim M, Abdan K, Jawaid M, Nasir M,

Dashtizadeh Z, Ishak MR & Hoque ME (2015),
A review on pineapple leaves fibre and its
composites. International Journal of Polymer
Science.
[15] Laftah WA & Wan Abdul Rahman, WA (2016),
Pulping process and the potential of using nonwood pineapple leaves fiber for pulp and paper
production: A review. Journal of Natural Fibers,
13(1), pp.85-102.
[16] Putra, A., Or, K. H., Selamat, M. Z., Nor, M. J.
M., Hassan, M. H., & Prasetiyo, I. (2018).
Sound absorption of extracted pineapple-leaf
fibres. Applied Acoustics, 136, pp. 9-15.
[17] Koruk H & Genç G (2015), Investigation of theacoustic properties of bio luffa fiber andcomposite materials. Materials Letters, 157,
pp.166-168.
[18] Alshaaer M, Mallouh SA, Al-Faiyz Y, Fahmy T,
Kallel A & Rocha F (2017), Fabrication, microstructural and mechanical characterization of
Luffa Cylindrical Fibre-Reinforced geopolymer
com-posite. Applied Clay Science, 143, pp.
125-133.
[19] Chen Y, Su N, Zhang K, Zhu S, Zhu Z, Qin W,
Yang Y, Shi Y, Fan S, Wang Z (2018), Effectof fiber surface treatment on structure, moistureabsorption and mechanical properties of luffa
sponge fiber bundles. Industrial crops andproducts, 123, pp. 341-352.

534

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

APPLICATION OF WASTE WATER AND GREEN ALGAETO STRENGTHEN SOIL
R.Roslan1, RC Omar2, INZ Baharuddin3, Hairin Taha4 and M.Syafiq5
Institute of Energy Infrastructure, Universiti Tenaga Nasional,Malaysia.
5College of Engineering, Universiti Tenaga Nasional, Malaysia.

1,2,3,4

ABSTRACTThe engineering technology has evolved with the combination of microbiological and geotechnicalengineering knowledge. In the past years, ecological approach has been applied to improve the strength ofliquefiable soil for ground improvement. Traditional methods include chemical and cement grouting require
heavy machinery, and are often costly and not environmental friendly. The potential of biological approach havebeen investigated by many researchers. One study showed that the green alga has the potential to clog soil
particles by creating impermeable layer on soil surface. It was also observed that the accumulation of bacterial
biomass and insoluble bacterial slime or known as extrapolysaccharides make the soil more impermeable towater. This study was aimed to analyze the effect of waste water and algae in improving the soil permeability
and shear strength. The permeability of the soil was evaluated before and after the treatment with waste waterand algae. The results showed that the coefficient of permeability of the treated soil has reduced by 26% and theshear stress increased by 29.5%. Observation using Scanning Electron Microscope showed that the void spacesof the soil particles were filled up and bonded together. This concludes that algae and waste water has thecapacity to improve the mechanical properties of soil.
Keywords: Waste water; Green algae; Bio-grout; Liquefied soil; Ground improvement

clogging the soil and reducing porosity andpermeability [7-8]. The accumulation of bacterial
biomass and insoluble bacterial slime will make thesoil more impermeable for water. This has been
adopted for enhancing oil recovery or soil
bioremediation. The groups of microorganisms that
produce insoluble extracellular polysaccharides tobind the soil particles and fill in the soil pores areoligotrophic bacteria from genus Caulobacter,aerobic Gram-negative bacteria from genera
Acinetobacter,
Agrobacterium,
Alcaligenes,
Arcobacter,
Cytophaga,
Flavobacterium,
Pseudomonas, and Rhizobium [9]. Apart of that,
Exopolysaccharide-producing bacteria may be used
to modify the soil matrix in situ. After growth ofthese bacteria in soil, its permeability for water will
be greatly reduced [10]. Nitrifying bacteria that
produce exopolysaccharides can also be used in soil
bioclogging technique. These bacteria are commonly
found in soil and waste water [11] . It was found thatmicroalgae was capable in precipitating calcite
through photosynthesis process that can be used as
bio-cement to bind soil particles together[12].
Microbial exopolymers have strong potential toreplace cement as sustainable soil treatment material[13].
In this study, laboratory scale experiment was
conducted to investigate the effect of waste waterand algae in improving the strength and texture of
the soil. The shear strength and permeability of the

INTRODUCTION
The civil engineering field has progressively
advanced with the introduction and integration of
biotechnology into geotechnical engineering
applications which utilize microorganisms tostrengthen, stabilize and reinforce engineering
properties of soils [1]. The applications of biomediated method to improve the mechanicalproperties of liquefied soil have been demonstrated
in many studies such as improving the shear strengthand reduce the permeability of soils [2-4]. The biomediated soil improvement technology has
successfully improved the geotechnical properties of
granular soils through calcite precipitation on soil
particles [5].Chemical or cement grouting
techniques are often costly and environmentally
unfriendly which require heavy machinery anddisturb urban infrastructure. Moreover, chemical
grouts can pollute the environment with its toxic
effect. Though these methods work very effectively
to strengthen the soil and reduce its permeability,
they may hinder groundwater flow and limits theinjection distance which is not feasible for largescale treatment [6].
Accumulation of bacterial biomass, insoluble
bacterial slime, and poorly soluble biogenic gas
bubbles in soil will make the soil more impermeable
for water. Production of bacterial exopolymers insitu can be used to modify soil properties by
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untreated and treated soil were analyzed using The
Falling Head Method and Triaxial Test. The micro
images of the soils were observed by ScanningElectron Microscope (SEM).

Falling head test
The Falling Head method was applied todetermine the Coefficient of Permeability of the soil.
Permeability of soil is defined as the ability of water
to flow through soil. As the water permeability
increases, the water seepage also increases. The
permeability test was conducted to analyze theeffects of algae as impermeable layer on the soil
surface against the rate of water seepage.

EXPERIMENTAL
The soil samples were collected from a landslidearea outside the university’s campus where the slope
has failed due to water saturation. The soil
characteristics of the original soil sample collectedfrom the experimental site were analyzed in thelaboratory based on Wet Sieve and Dry Sieve
analysis, Liquid Limit test, Plastic Limit test,
Coefficient of Permeability test and Triaxial with
Unconsolidated Undrained test (Fig. 1). For the biomediated treatment, waste water was obtained fromthe drainage system on the campus and green algae
were acquired from the local aquatic supplier. In thisexperiment, the soil samples were divided into 2
containers (7.0 kg each), one treated with algae andwaste water (treated) and the other container as acontrol (untreated). In the first container, the soil
was mixed with 2 L of waste water and algae (3.0kg) were added on top of the soil (Fig. 2). These
containers were then left at room temperature for 54
days. Occasionally, waste water was sprinkled on
the soil to maintain the moisture content.

Triaxial test-CU
The triaxial test was carried out to the determine
shear strength of undisturbed or remolded soil
sample in the triaxial compression apparatus by
consolidation undrained test without the poremeasurement. This test was conducted on untreated
and treated soil samples. Comparison was made to
study the effects of waste water and algae applied on
soil towards the shear stress. Each sample was tested
3 times with pressures of 100kPa, 200kPa and
400kPa. Reading was taken at every 3mm ofdeformation interval until soil failure occurred. After
that, Mohr Coulombs was plotted from the results tocalculate and compare the shear stress and factor ofsafety of the soil.
Scanning Electron Microscope (SEM)
The morphology and structure of the innersurface of the soil samples were observed by
Scanning Electron Microscope (SEM).

RESULTS AND DISCUSSION
Soil Characteristic
The wet sieve and dry sieve analyses showed thatthe original soil consists of 1.745 % of Gravel, 7.018% of sand, 88.596 % of Silt and Clay. From thegraph of Percentage passing versus Sieve Sizeplotted, the coefficient of uniformity, Cu, andcoefficient of gradation, Cz, were equal to 2.87 and
0.620, respectively. The result of Atterberg limit test
showed that the liquid limit was 47.5% whereby theplastic test equaled to 28%. Under the Plasticity
Chart, the soil sample was categorized under thegroup of OL or ML known as Organic soil of low
plasticity or Silt of Low plasticity which have
WL<50. From the tests, it can be concluded that thesoil was classified as Silty Sand.

Fig. 1 Original soil

Falling Head Test
Table 1 shows the results of Falling Head test
carried out on the original sample (untreated). The

Fig. 2 Treated soil with waste water and algae
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tests were conducted thrice to obtain more accurate
results at 400mm of water elevation difference (h1h2). For the first determination, k equals to
0.0022mm/s, while for the second and the third
determination, k are 0.0022mm/s and 0.0025mm/s.
Thus, the average coefficient of permeability, kequals to 2.3 x 10-3 mm/s.

kN/m2, the deviator stress at failure was 51.25
kN/m2 and by calculations, the major principle
stress, σ1 was 151.25 kN/m2. At cell pressure of 200
kN/m2 and 400 kN/m2, the soil failed at 104.9
kN/m2 and 120.8 kN/m2 where the major principal
stresses were 304.9 kN/m2 and 520.8 respectively.
Graph of deviator stress against axial strain forthe 3 samples were plotted and illustrated in Figure
3. Based on the graph, the soil compressed with 400
kPa of cell pressure having the highest deviator
stress at failure. The soil had the lowest deviator
stress at failure when tested with 100 kPa of cellpressure.

Table 1 Falling head test results of untreated sample
Determination
No.
Time interval,t (sec)h1, (mm)h2, (mm)k = 2.3026 aL
log10 h1

1

2

3

210

210

185

1000
600
0.00221000
600
0.00221000
600
0.0025

Table 3. Summary of results for original soil

Table 2 shows the results of Falling Head test oftreated soil with waste water and algae after 54 days.
The tests were conducted 3 times to obtain moreaccurate results at 400mm of water elevationdifference (h1-h2). For the first determination, kequals to 0.0015mm/s, while for the second and thethird determination, k are 0.0015 mm/s and0.0014mm/s. Thus, the average coefficient of
permeability, k equals to 1.47 x 10-3 mm/s.

No.

Cell
pressure(kN/m2)

Deviatorstress(kN/m2)

1
2
3

100
200
400

51.25
104.9
120.8

Major
principal
stress(kN/m2)151.25304.9
520.8

Table 2. Falling head test results of treated sample
DeterminationNo.
Time
interval, (sec)h1, (mm)h2, (mm)k = 2.3026 aL
log10 h1

1

2

3

310

308

320

1000
600
0.00151000
600
0.00151000
600
0.0014
Fig. 3 Graph of deviator stress against axial strain(untreated soil)

The results showed that the coefficient of
permeability decreased by 36% which is 10% of
reduction. From the original sample, time taken for
the water to seep into the soil in 400mm of water
elevation difference is 200 seconds in average. The
time taken for water to seep into the soil in 400mm
of water elevation difference is 313 seconds inaverage. This shows that the extracellularpolysaccharides (bacterial slime) produced by the
microorganisms have attached the soil particles
together and filled the soil pores thus greatly
reduced the permeability of the soil.

Table 4 shows the summary of results of the 3
Triaxial tests carried out on the treated sample atdifferent cell pressures. At cell pressure of 100
kN/m2, the deviator stress at failure is 88.7 kN/m2
and by calculations, the major principle stress, σ1 is188.7 kN/m2. At cell pressure of 200 kN/m2 and400 kN/m2, the soil failed at 166.208 kN/m2 and146.283 kN/m2 whereby the major principal stresses
are 366.208 kN/m2 and 546.283 respectively. Graphof deviator stress against axial strain for the 3
samples were plotted and shows in Figure 4. Basedon the graph, the soil compressed with 200 kPa ofcell pressure having the highest deviator stress at
failure.

Table 3 displays the summary of results of the 3
Triaxial tests carried out on the untreated sample atdifferent cell pressures. At cell pressure of 100
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Table 4. Summary of results for treated soil
No.

1
2
3

Cell
pressure(KN/m2)
100
200

Deviatorstress
(KN/m2)
88.7
166.208

Major
principal
stress(KN/m2)
188.7
366.208400

146.283546.283

Fig. 5 Stress condition at failure of untreated soil

Fig. 4 Graph of deviator stress against axial strain(treated soil)

Figure 5 and 6 show the Mohr circle of theoriginal soil and treated soil respectively. The Mohr
Circle was developed from the deviator stress results
to calculate the shear strength of both of the soil.
From the plotted Mohr Circles, the shear strengthparameters were referred to as the cohesion intercept
and the angle of shearing resistance. The Cohesionof the soil is equal to 0 whereby the angle ofresistance is 17º. By calculation, the shear strengthof the original soil was 43 kN/m2. Moreover, theshear strength of the soil treated with waste waterand algae was equaled to 61 kN/m2. This shows anincrease in the shear stress of the treated soil by
29.5%.
The shear strength of the treated soil has
increased due to the existence of slimy liquid
produced by the bacteria from the waste water which
filled up the soil pores. Therefore, it has reduced thesoil permeability as well as increased the shear
strength of the soil. However, the shear strength was
not greatly improved due to the short time durationof the experiment.

Fig. 6 Stress condition at failure of treated soil

Scanning Electron Microscope (SEM)
Figure 7 shows the microscope image of theoriginal soil sample before it was treated with waste
water and algae. From the analysis, it was observedthat the soil contains two types of minerals typicallyfound in clay which are Kaolinite, 2Al2Si205(0H)4and Hallosite, 2Al2Si205(0H)4.4H2O. The Hallosite isa mineral that has cylindrical shape and samechemical formula with Kaolite but it contains H20.
Hallosite is normally has length about 1.0 to 15.0
µm with diameter from 10 to 150 nm.
The Kaolinite mineral found in the original soil
formed almost a complete and well organized layer
on top of each other (Figure 8). However, theformation of these Kaolinite were not wellcompacted and not resting completely on top of eachother, therefore allowing water to flow through thepore or void. The amount and velocity of water
seeping through the soil will be minimized bydecreasing the void size of the Kaolinites. Thus, it
can reduce the velocity of groundwater that mightlead to a landslide.

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Fig. 10 SEM image of bounded Kaolinite layers
Fig. 7 SEM image of untreated soil
Figure 9 and 10 show the layers of Kaolinites thathave bound together which has significantly reduced
the soil pores. The pieces of Kaolinite have almost
completely closed the pores and become compacted.
Furthermore, the distance between the minerals is
hardly seen. However, there was still some Kaolinitethat has not closed down the distance between eachlayer. This was probably due to the shorter period ofexperiment. Most bio-mediated treatment takes alonger period to achieve the expected results due tothe natural biological process of the microorganisms[14].
From this analysis, it can be assumed that thenatural microorganisms in the soil and waste water
have produced a biological substance such as the
exopolymer which have closed down the distance
between the minerals. The slime produced by thebacteria have spread in some parts of the soil
particles and created sticky liquid substance thatbound the soil particles together, thus reducing thepermeability of the soil and increasing the shear
strength. Despite that, there are areas where themineral distances are not completely close down.
This is probably because the bacteria did not
distribute into that particular area and therefore
longer time and higher amount of bacteria are
required to accomplish a better result. The microbialactivity in the soil could be incomplete by thelimitation of nutrients needed [15].

Fig. 8 SEM image of Kaolinite layers in original soil

CONCLUSION
In this study, it was demonstrated that waste
water and algae managed to reduce soil permeability
by 26% and increased shear stress by 29.5%. This
showed that waste water and algae could be applied
to improve the mechanical properties of soil in situ.
These methods can replace the more energy
demanding mechanical compaction methods or the
expensive and environmentally unfriendly chemical
grouting methods. However, since the application ofFig. 9 SEM image of Kaolinite layers in treated soil

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green algae and waste water as the catalyst are stillat early stage, to adopt this method effectively, an
integration of engineering, microbiological andecological studies and design consideration are
required. Besides that, further experiment about
waste water application in bioclogging must be done
to fully utilize its potential in biogeotechnicalengineering. Other waste materials such as foodwaste and sewage water may also be used andexplored due to its bigger potential of producing
microbes that grow by consuming inorganic nitrogencompounds such as Nitrosomonas, Nitrosococcus,
Nitrosospira and Nitrosolobus.

biologically based grout material to prevent soilliquefactionforgroundimprovement.
International
Journalof
GeotechnicalEngineering, 13(1), 48-53.
[7] Costa, O. Y., Raaijmakers, J. M., & Kuramae, E.
E. (2018). Microbial extracellular polymeric
substances: ecological function and impact onsoil aggregation. Frontiers in microbiology, 9.
[8] Farah, T., Souli, H., Fleureau, J. M., Kermouche,G., Fry, J. J., Girard, B., & Harkes, M. (2016).
Durability of bioclogging treatment of soils.
Journal of Geotechnical and Geoenvironmental
Engineering, 142(9), 04016040.
[9] Xia, L., Zheng, X., Shao, H., Xin, J., Sun, Z., &Wang, L. (2016). Effects of bacterial cells andtwo types of extracellular polymers on
bioclogging of sand columns. Journal of
Hydrology, 535, 293-300.
[10] Ivanov, V., & Stabnikov, V. (2017). Soil
surfacebiotreatment.
In
Construction
Biotechnology (pp. 179-197). Springer,
Singapore.
[11] Cydzik-Kwiatkowska, A., & Zielińska, M.
(2016). Bacterial communities in full-scale
wastewater treatment systems. World Journal of
Microbiology and Biotechnology, 32(4), 66.
[12] Ariyanti, D. and Handayani, N.A., 2012.
Hadiyanto (2012) Feasibility of Using
Microalgae for Biocement Production throughBiocementation. J Bioprocess Biotechniq,2(111), p.2.
[13] Chang, I., Im, J., & Cho, G. C. (2016).
Introduction of microbial biopolymers in soil
treatment for future environmentally-friendly
and sustainable geotechnical engineering.
Sustainability, 8(3), 251.
[14] Saad, A. H., Nahazanan, H., Yusoff, Z. M.,
Huat, B. K., & Mustafa, M. (2018). Properties
of Biomineralization Process in Various Typesof Soil and Their Limitations. International
Journal of Engineering & Technology, 7(4),4973-4979.
[15] Castle, S. C., Sullivan, B. W., Knelman, J.,
Hood, E., Nemergut, D. R., Schmidt, S. K., &Cleveland, C. C. (2017). Nutrient limitation ofsoil microbial activity during the earliest stagesof ecosystem development. Oecologia, 185(3),513-524

ACKNOWLEDGMENTS
We would like to thank UNITEN grant forconference and publication fund.
REFERENCES[1] Hamdan, N., Kavazanjian Jr, E., Rittmann, B. E.,& Karatas, I. (2017). Carbonate mineral
precipitation for soil improvement throughmicrobial denitrification. Geomicrobiology
journal, 34(2), 139-146.
[2] Zhao, Q., Li, L., Li, C., Li, M., Amini, F., &Zhang,
H.
(2014).
Factors
affecting
improvement of engineering properties of
MICP-treated soil catalyzed by bacteria andurease. Journal of Materials in Civil
Engineering, 26(12), 04014094.
[3] Soon, N. W., Lee, L. M., Khun, T. C., & Ling,
H. S. (2014). Factors affecting improvement inengineering properties of residual soil throughmicrobial-induced calcite precipitation. Journalof Geotechnical and Geoenvironmental
Engineering, 140(5), 04014006.
[4] Umar, M., Kassim, K. A., & Chiet, K. T. P.
(2016). Biological process of soil improvement
in civil engineering: A review. Journal of RockMechanics and Geotechnical Engineering, 8(5),767-774.
[5] DeJong, J. T., & Kavazanjian, E. (2019). Biomediated and Bio-inspired Geotechnics. In
Geotechnical Fundamentals for Addressing
New World Challenges (pp. 193-207). Springer,
Cham.
[6] Kumari, D., & Xiang, W. N. (2019). Review on540

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

QUANTITATIVE INTERPRETATION OF LANDSLIDE OCCURENCE SITE
BY AI TECHNOLOGY OF IMAGE CLASSFICATION AND
TOPOGRAPHICAL ANALYSIS MAP CREATED BY AERIAL LASER DATA
Koki Sakita1, Satoshi Nishiyama1, Teruyuki Kikuchi2, Junsheng Song3 and Yuzo Ohnishi4
1
Graduate School of Environmental and Life Science, Okayama University, Japan;
2,
JP Design Co. Ltd. Japan:
3.
School of Mechanics and Civil Engineering, China University of Mining and Technology, China;
4.
Kyoto University, Japan;

ABSTRACT
It is very important from the point of view of disaster prevention inspection to fully understand the landslide
occurrence site. In the current inspection work, it has been a problem that the information used to predict the site
is insufficient, and the results may vary depending on the skill of the engineer. Therefore, in this research, a twodimensional map is created based on aerial laser surveying and an attempt was made on doing a quantitativeinterpretation for the site of the landslide by applying Artificial Intelligence (AI) technology specialized for image
classification, which is called Convolutional Neural Network (CNN), to the map. There are a variety of maps thatcan be made from aerial laser data. In order to effectively interpret the topographical features, the topographicalanalysis map was used that transparently combined the slope map and the wavelet analysis map in this study. In
the target site, dozens of landslides have occurred due to Typhoon Talus, which occurred in 2011, and in theanalysis of CNN, the AI model was trained on the map before the occurrence of the landslide on the concernedsite. As a result, the interpretation had an accuracy exceeding 80% and it was considered that the topography, suchas scarplets and gravitational deformation, could be the pertinent information needed for the interpretation. Thissuggests that the extraction of topography, which is an inherent factor of landslides, has been successfully
performed in the interpretation of AI, and the method can be used to predict future landslides.
Keywords: Landslide, Artificial intelligence, Aerial Laser Surveying, Terrain analysis filter

INTRODUCTION

data, and they are emphasized and visualized in twodimensional maps. Furthermore, in recent years, withadvances in Artificial Intelligence (AI) technology
there have been remarkable, and various applications
such as the classification of images and the extractionof regions.
In this study that was conducted, a verification of
the quantitative interpretation of a landslide was doneby extracting the occurrence site and organizing the
topographical information contributing to it using anaerial laser survey, terrain analysis filter, and AI
technology.

Many landslides have occurred due to the
influence of climate change and heavy rainfall in
recent years. Therefore, the importance of disastercountermeasures on slopes is increasing. In theinspection work for dealing with slope disasters up tonow, interpretation has been carried out by experts
using maps such as aerial photographs. However, it
has been a problem that the method of selection andjudgment of the suspicious area is qualitative and thatthe result differs depending on each expert’s
interpretation. In the first place, the information forpredicting a landslide area is insufficient. The task is
to organize the information such as what topographic
features contribute to the landslide and what were themain contributing factors so it is necessary toestablish a quantitative inspection method based onthese criteria.
With regard to these problems, the utilization of
aerial laser survey is used as a technology for solving
these problems. In the survey, which can be measured
from the sky, it is suitable for measurements overwide areas such as slopes and rivers, using manyutilization methods for the measurements [1].
Moreover, by using a method called a terrain analysis
filter, feature properties are extracted from the survey

METHODS FORQUANTITATIVE INTERPRETATION
In order to establish the inspection method, anaerial laser survey, topography analysis filter, and AI
technology were utilized. Below, each technologythat was used is described.
Aerial Laser Surveying
The technology of aerial laser surveying is one of
the mobile measurement methods, and it performs
measurements using a combination of three sensors:
Global Navigation Satellite System (GNSS), Inertial
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Measurement Unit (IMU), and a laser range finder.
As mentioned above, it is suitable for measurement ina wide area and has been used in various applications
such as the measurement on slopes or river dikes. The
measured data is acquired as data having a threedimensional shape composed of points which are
spatially defined by three-dimensional coordinates.
However, in the wide area measurement, unnecessary
information is also measured at the same time such as
vegetation. In the case of extracting topographicalfeatures, information of vegetation is unnecessary
because the direction and the unevenness of the slope
are targeted. The unnecessary information from theaerial laser data is removed by filter processing, andthe data is converted into a form that can be handledeasily. The data obtained by the process is called
ground data. I show ground data in the mountainous
area in Fig.1. A river flows in the center, andmountains cover both sides of Fig. 1. The data isexpressed by a set of points having three-dimensional
coordinates and is called a point cloud.

The wavelet analysis map is developed for the
purpose of emphasizing the unevenness of the slope
and is created according to the wavelet coefficient C(s, a, b) calculated by Eq. (2) where s indicates theshift amount and (a, b) indicates x and y coordinates
at an arbitrary point. φ is called a mother wavelet
function, it is shown in Eq. (3), and the magnitude of
the product between the function and the data relates
to the expression of unevenness. Figure 3 shows anexample of the function when s = 1 and a wavelet
analysis map.
S ( a, b) = S x ( a, b) 2 + S y ( a, b) 2

(1)

H 11 + H 21 + H 31 − ( H 13 + H 23 + H 33)
S x ( a, b) =6 * DxS y ( a, b) =H 11 + H 12 + H 13 − ( H 31 + H 32 + H 33)
6 * DyC ( s , a, b) =Terrain Analysis Filter1 x −a y −bz ( x, y ) 
,
dxdy

s
s 
 s

(

)

 1 2

x + y2  2 ( x, y ) = (2 − x 2 − y 2 ) exp −

Although the aerial laser data was subjected to afiltering process, so that the necessary information isleft in, the measurement range is so wide that there is
still too much information to handle as it is. Therefore,
it is necessary to further extract information to befocused on and to use it in a more manageable form.
In this study, a method called terrain analysis filter isused for the purpose of feature extraction andvisualization of the data and the analysis is performed
using the topographical analysis map.

(2)

(3)

Fig. 1

Example of the ground data obtained by theaerial laser survey

Slope map

Fig. 2Chart of the relationship between the points
to calculate the slope amount and slope map

The slope map is a terrain analysis map that uses
the degree of inclination as a feature amount. Using
the 8 points around arbitrary points (a, b) in themeasurement data, the slope amount S of the local
slope can be calculated by Eq. (1), and the map iscreated by allocating light and dark according to thosevalues. Each value in the following equation
corresponds to the elevation value of each point in therelationship of Fig. 2.

Fig. 3Graph of mother wavelet function for s=1
and wavelet analysis map example

Topographical analysis map
In this method, two different terrain analysis
filters are used, and they are created by performing
transmission synthesis so as to use the respective
features that complement both filter methods. The
two terrain analysis maps are wavelet analysis andslope maps.

Wavelet analysis map

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Image Classification by AI

at every landslide site. Therefore, as a proposed
method, tile images are created as shown in Fig. 5 toincrease the number of training data. First, bycomparing the data before and after the landslide, theplace to be the landslide is extracted and cut out of themap. Thereafter, the extracted parts are divided into
square tiles without overlapping. In this research, thelength of one side is set to 50 pix, and a rotation
process at 90 degrees and inversion processing ofleft/right and top/bottom are performed for each tile
finally. Then, the amount of data is expanded by six
times. By tiling the map in this manner, the numberof images to be used as training data increases. Thisis expected to improve classification accuracy. In
addition, the tile images created from other sites isused as the no-landslide site image.

Recent advances in AI technologies are
remarkable, and as computer performance has
improved, the time to compute the analysis has
become shorter, and opportunities for use in many
fields have increased. In particular, image
classification technology is expected to be used in avariety of applications, and it has received a highdegree of attention. Recently a model has beenreleased that performs classification with an accuracyof 96.43% in recognition of images classified into
1000 categories [2]. Among such AIs, is a model
specialized for image classification called
Convolutional Neural Network (CNN), CNN
automatically performs the extraction of the feature
quantities in an image and the inference based on theextracted feature is quantified. In this research, theAI was trained on identifying landslides using the
topographical analysis map created from the aerial
laser survey data, and binary classification of whether
the map has the features characteristic of landslides in
the image. Instead of using the general CNN modelthat has already been proposed for the AI model, a
specific model for interpreting the landslide wascreated. Therefore, the most suitable model in theinterpretation of the landslide site is searched foramongst the combination of model and data. At thattime, Sony's "Neural network Console" is used as thesoftware for AI analysis.

CONTENT OF EXPERIMENT
Proposed method
First, an overview of the method is given. In thismethod, the AI trains using the maps made from theaerial laser data and then the AI extracts landslidefeatures automatically based on the given data andclassifies them.
The data used to let the AI train is a map before
the occurrence of landslides. Therefore, two types ofdata across the area are required: 1) before thelandslide; 2) and, after the landslide. It is necessary tocreate a topographical analysis map from each of thesurvey data and compare the two types of maps toknow where the landslide site is located on the prelandslide map.
The scale value of the wavelet analysis maps must
be determined in order to create the topographicalanalysis map. Here, it is set as s = 1. As an exampleof this map, Fig. 4 shows a topographical analysis
map before and after the landslide. On the AI analysis
part, a CNN model is used. As mentioned above, theinterpretation model is searched in order to obtain amore optimal solution in this study. In this method,
the survey data generated before landslide is required
to train the AI. However, this data cannot be obtained

Fig. 4

543

Topographical analysis map before and after
the Landslide and two color bars
representing map colors

SEE - Bangkok, Thailand, Nov.11-13, 2019

these two steps while rearranging the CNN model.
From the results of these two steps, the model withthe highest accuracy is determined as the optimum
model, and the process proceeds to the last step. The
final step is to validate the model. In the model
verification, the new image sets for the verification is
given to the optimal model and verification is
performed to verify the model accuracy. Each of thesethree steps requires a separate set of data. Therefore,
the 3 sets of tile images need to be prepared. The
number of data sets is shown in the table. The data
sets for learning and evaluation are created by
dividing the generated 9,205 tile images so that theratio of the number of data sets for learning andevaluation is 8: 2.
Table 1 Number of data sets for each category andtypes

Fig. 5

Data type
Training
Evaluation
Total
Validation

Creation flow of tile images from theoriginal map

Landslide
3,348
858
4,206
249

No-Landslide
4,016
983
4,999
527

Total
7,364
1,841
9,205
776

Observation Site
RESULTS

Here, the site information is described as it relates
to the analysis of this research. The target area of thisstudy is the Kii Mountains which is the middle basinof the Totsu river and it is also the Kumano riverwater system which was damaged by Typhoon Talus
in 2011. This Typhoon caused heavy rainfall over2000 mm in the Kii Mountains and caused more than
50 landslides. For countermeasure of this event, aerial
laser surveys were conducted by a nationalorganization, and data of 1 m mesh size wasmaintained. Even more, fortunately, similar surveys
were conducted in 2009 in this area. Therefore, thedata before and after the landslide are available,
making it ideal data for this research.

Accuracy Indicator
Here, three accuracy indices are defined in Eq. (3)to (5) as indices for quantitatively evaluating theclassification. TP, FP, FN, and TN in the equation aredetermined by the correspondence between the truelabel of the image and the classification result of AI.
For images in which the true label is a landslide, thenumber of AI classified as landslide is TP (True
Positive), and conversely, the number of noLandslide is TN (True Negative). Furthermore, when
the true label is a non-landslide site, the number ofimages in which the classification results are similar
to non-landslide sites is FN (False Negative), and thenumber of landslide images that are classified as noLandslide is FP (false positive).

Verification Content
The analysis is performed in three steps. The firsttwo of them are related to the search of the model.
The first step is training. In the training, the AI modelis allowed to train the map having the features of thelandslide or not. As mentioned above, the CNN
model is used in this research. Therefore, the CNN
model which is designated trains the landslide and thenon-landslide tiles, with their respective labels. Next
step is evaluation. In the evaluation, the training result
is evaluated for the accuracy of the classification. For
the trained model, new image sets are given that havealready been labeled as landslide / no-landslide and isdifferent from the training images, and its accuracy isevaluated by comparing the classification results of
the label and the AI. In this research, the most suitablemodel for classification is searched for by performing

Re call =TPTN* 100 ,
* 100
TP + FN
FP + TNPr ecision =TPTN* 100 ,
* 100
TP + FP
TN + FN(5)

TP + TN*100
TP + FP + FN + TN

(6)

Accuracy =

544

(4)

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 3 Validation result in optimal AI model byusing validation data sets

Model Structure Searching
In the structure search of the model, the model
was recombined, and the accuracy verification using
the evaluation data was performed each time todetermine the optimum model. Here, it was decided
that the optimal model is a model that maximizes
Recall. The classification results at that time areshown in Table 2 below. Further, Fig. 6 shows an
optimal model at that time.

Inferred as
landslide
Inferred as
NoLandslide
RecallLandslide

Nolandslide

Precision

Tp:221

FP:61

78.3%

FN:28

TN:466

94.3%

88.8%

88.4%

Accuracy:
88.5%

Table 2 Accuracy evaluation results in optimal AI
model by using evaluation data sets
Estimation of classification basis by AI
Inferred as
Landslide
Inferred as
No-landslide
Total
RecallFig. 6Landslide

No-Landslide

TP:688

FP:77

FN:170

TN:906

858
80.2%

983
92.2%

Here, the topography will be considered which isthe basis for the classification by AI from the results
obtained by validation. As mentioned earlier, theinformation in the interpretation of landslides is stillinsufficient, and it is necessary to reorganize whatshould be focused on in the inspection. In this case,by using the images classified as TP and FN in Table
3 reasons the AI classified landslides and nonlandslides are considered based on the basis, and on
the results, the topography is organized resulting fromthe landslide phenomenon. At the time of the basis
estimation, the middle layer visualization techniqueof the CNN model was used. The model comprises
feature quantity extraction in an image and a neuralnetwork, and feature quantity extraction corresponds
to filtering processing in the image processing field.
Therefore, by executing only feature quantity
extraction processing in the searched optimum modeland forcibly outputting in the middle of the network,
it is possible to obtain an image in which feature
quantities for estimation in the network are extracted
for each image. It is called the interlayer visualization
tile. Note that since the image being used is a tile
image, it is not possible to evaluate the entire
landslide area as it is. Therefore, the interlayer
visualization tile is returned to the original
arrangement, and one landslide area image is
generated. In addition, since each tile image has aresult classified as Landslide or no-Landslide
according to classification by AI, the interlayer
visualized tiles with a probability of belonging toeach class at the time of classification over 80% arehighlighted in red. The images generated from theseresults is called mid-layer visualization images. These
are shown in Fig. 7.
In Fig. 7, two places in the landslide area in thedata set used in Table 3 are shown. The original image
and the mid-layer visualization image are displayed,
and the original image includes the topographic
interpretation comment of the expert. The firstBest classification model in the structure
searching

Validation
The accuracy was verified using the data set forverification and the searched model. The accuracy
verification results are shown in Table 3. About 88%of the recalled and non-collapsed sites are read, andthe accuracy of the entire data set is 88.5%. The
precision was 78.3% in the collapsed area and 94.3%
in the non-collapsed area.
545

SEE - Bangkok, Thailand, Nov.11-13, 2019

original image can be seen to have gravitational
deformation and multiple scarplets. On the other hand,it can be seen that the mid-layer visualization image
is emphasized by black and white. Further, the tiles inwhich they appear are classified as landslides. Next,
looking at the second set, the arc-shape unclear
scarplet found in the center of the original image isalso classified as a landslide in the mid-layer
visualization image. On the contrary, it can be seenthat a relatively gentle slope having an inclination
angle of about 5 degrees or a ridge having a wide
inclination angle of 10 degrees, which is seen in theupper and lower parts of the image, is not classified
as a landslide.

In addition, it was considered that topographysuch as gravitational deformation and scarplets are
the most important elements for the interpretation of
the landslide by the estimation of the judgment basisof AI based on the interpretation result. In addition, it
was found that terrains with relatively gentle
inclination tend to be classified as terrains other thanthe landslide site.
This is the result of judgment based on theinherent factor that causes a landslide. However, it isreported that the information of triggering rainfall isalso an important factor that causes a landslide [3],[4]. That is, in order to carry out further quantitative
and accurate interpretation, it is necessary to develop
an analysis system that interprets AI taking into
consideration both rainfall information andtopographic information. In addition, in the
preparation of this map, the dataset is created with thelandslide site in the rainfall of the 2011 Typhoon
Talus as the landslide site. However, not only thepredisposition for promoting landslide is included in
the whole landslide area in the first place, but it may
be considered that analysis by AI in the case where
unnecessary information was originally included.
This is also the case with no-landslide data sets, anddata sets classified as no-landslide areas may also
include the inherence as landslide areas. That is,depending on events such as future rainfall, landslides
may occur even at locations classified as no-landslideareas. Therefore, it is an urgent task to organize
measurement data and topographical information andquantitatively clarify the relationship between the
topography and landslide represented in the survey
data.

REFERENCES

Fig. 7[1] Suwa. T, Nikaido. R, Hamaguchi. K, Harada. T,

Comparison table between original images
and mid-layer visualization image

Watanabe. K, Nakazono. D, Hara. F, Aoki. S,
Analysis of Topographic Change Using
Aviation Laser Survey due to the 2001 Tohoku
Tsunami, Journal of Japan Society of Civil
Engineers, Ser. B3, Vol.72, No.2, 2016,
pp.I_181-I_186

CONCLUSIONSIn this study, automatic extraction of the slope
landslide was tried by using an aerial laser survey and
AI technology as an attempt to improve efficiency
and quantification of slope disaster inspection. The
topographical analysis maps are created from survey
data using aerial laser survey and terrain analysis
filters. Detailed information of topography was
extracted from 3D survey data, and this topography
information was expressed on the maps. Furthermore,
by applying a model which specialized in image
classification called CNN to these maps, the maps
were classified into the landslide or other topography.
As a result, the study succeeded in the classification
by Recall and Accuracy of over 80%.

[2] He. K, Zhang. X, Ren. S, Sun. J, Deep Residual
Learning for Image Recognition, arXiv preprint
arXiv:1512.03385, 2015
[3] Chigira. M, Civil engineering laboratory

manual Creek extraction manual (draft) that
could cause a collapse of the deep layer,
Journal of Japan Society of Civil Engineers,
Ser. C, Vol.62, No.4, 2006, pp.722-735[4] Chigira. M, Prediction of Potential Sites of
Deep-Seated Catastrophic Landslides and its
Future Research, Jour. Japan Soc. Eng. Geol,
Vol.56, No.5, 2015, pp.200-209
546

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

LIQUEFACTION MAPPING PROCEDURE DEVELOPMENT:
DENSITY AND MEAN GRAIN SIZE FORMULATIONS

1

Abdul Hakam1, Bayu Martanto Adji1 and Junaidi1
Engineering Faculty, Andalas University, Indonesia

ABSTRACTThe assessment of liquefaction potential is very important and is the main step in making a map ofliquefaction hazard in a certain area. The assessment methods of liquefaction potential have been proposed byresearchers since last eight decades. Each method is based on the purposes and completeness of the data obtainedby the developer. In this study, these methods then were modified to propose the new method that is easier andtechnically cheaper. Furthermore, the method will be applied in making liquefaction hazard maps. The method
as a result of this study is a new procedure that is more practical to be applied. This method is associated withsoil parameters that are commonly and easy obtained in general soil investigation. The soil parameters used toassess the potential of liquefaction in this procedure are the density and mean size of soil particles. Soil densityand particle mean size needed for analysis of liquefaction potential can be obtained from laboratory tests or thecorrelation results from the value of field tests, namely the standard penetration test or cone penetration test. This
new procedure is expected to be more applicable and reliable in making liquefaction hazard maps.
Keywords: Liquefaction, Assessment method, Grain size, Density, Nspt, CPTon the liquefaction potential index (LPI) is shown in
Table 1.

INTRODUCTION
An evaluation procedure of soil liquefaction
potential using the simplified method [1] based on
both a liquefaction resistance factor (FL) and aliquefaction potential factor, (PL) has been proposed
in 1981 [2]. The procedure tried to introduce thefactor FL and PL which are is the liquefaction
potential at a calculated depth and at the surface
respectively. The factor PL then used with thefamous name as liquefaction potential index (LPI)
by researchers in Korea, India and Bangladesh [3] [5]. The LPI becomes interesting since it indicatesthe damage level at the surface at the site of interest
related to the factors of safety of liquefaction
potential at the deeper point underneath.
The first LPI is introduced for only 20m of depthwith the formula of:

Table 1 The liquefaction severity - potential index
LPI
IwasakiLuna-Forest
Chung et al
[2]
[6]
[7]
0
Very Low Little to None
None
0-5
Low
Minor
Little to None
5-15
High
Moderate
Moderate. 16 Very High
Major
SevereIn order to show the severity liquefaction fromthe liquefaction potential index (LPI), the typicalillustrations based on field observations in the New
Zealand are presented in Fig. 1 [8].

20

LPI =

 F(z) W(z) dz(1)0

where F(z) = 1 - FS with the minimum 0.0, W(z) =10 - 1/2 z with the minimum 0.0, z and dz are thedepth the incremental depth respectively. The
modified term of severity level of LPI has also been
introduced by the other researcher [Luna 1995] as:
n

LPI =

 Fi Wi Hi

(2)

i 1

where n denotes the number of discretized layers, Hi
denotes the thickness of the discretized layer, Wi
weighting function and Fi is the liquefaction severity
for layer i. The liquefaction severity assessed based

Fig. 1 Bird-eye observed liquefaction [8]547SEE - Bangkok, Thailand, Nov.11-13, 2019

Liquefaction assessment, it will be written thesimple procedure to obtain the relative density
estimation based on the correlation of those filed
tests. In addition it is also given an estimated meanof grain size based on those filed tests' results.

LIQUEFACTION ASSESSMENT
The liquefaction potential assessment is an
important aspect for mapping the earthquake related
hazard for certain area. Since Niigata earthquake in
1964 the simplified method [1] has been widely used.
However this continuously improved method
became complex since it involves many parametersthat rarely used in geotechnical engineering and notas simple as it was named [10] [11]. The method
also has been modified for assessing liquefaction
potential based on Cone Penetration Test results [12].

FIELD TEST CORRELATION
Obtaining of soil parameter generally require
laboratory tests that take time and cost. Fortunately
past engineers and researchers have done a numberof precious works to obtain soil parameters from soil
field test report. This approach is taken in this study
to correlate soil parameters with based on the resultsof the most commonly used soil field investigation
CPT and SPT. The correlation of CPT and SPT test
results also has been proposed by many researcher
as recently it is done [15]. However, each test has its
own advantageous and restriction in engineering
practices.

The liquefaction potential in the soil layer can beassessed based on the mean grain size (D50) and its
relative density (Dr) [13]. This method has been
applied to real cases in the field and gavesatisfactory results [14]. The liquefaction potential atcertain point in the soil layer can be determined byplotting the value of the relative density and theaverage grain size (Fig. 2).

Dr from SPT
In a laboratory, relative density can be calculated
as a relationship result of maximum density, max
minimum density min and at present state of soil
density d, as follows:Dr = d   m in  m ax

 100%
 m ax   m in  d(3)However, in the absence of relative density testof soil samples in laboratory test as it is usually, thevalue of Dr can be taken from the N correlation. In
the past, the researchers then made relationshipbetween the laboratory test values of Dr with thenumber of blows from SPT (N).
The first relative density and penetration resistantcorrelation was revealed in 1948 [16]. Later on a
researcher [17] has conducted the sophisticatedlaboratory investigation on N and Dr relationshipusing a 1.2 m high heavy steel tank with thediameter of 1 m. The more important feature of thistest is it had two different soil grain sizes that are thecoarse sand with D50 of 1.5mm and fine sand with
D50 of 0.3 as shown in Fig. 3.
General result of that study is given in graphs ofrelationship between penetration resistant, N andrelative density, Dr for cohesionless sands as shownin Fig. 4. It seems that for air dry sand, the grain sizeof sand has no significant effect to the penetration
resistant and relative density relationship. However,for saturated sands, the gain size of the sandcontributed very important effect to the penetration

Fig. 2 Dr – D50 for liquefaction assessment
Based on the authors' experience so far, the mostpopular direct in field tests used in Indonesia for
civil works are the Standard Penetration Test (SPT)and Cone Penetration Test (CPT). The Standard
Penetration Test provides a soil parameter value inthe form of N or Nspt. The Standard Penetration
Test usually follows the drilling works that include
soil samples that can involve sieve analysis inadvanced. While the Cone Penetration Test often
produces cone tip resistance parameters (qc) andfriction ratio (Fr). Both of these filed tests have no
relative density value involved in. In order todevelop a general method for using Dr and D50
548

SEE - Bangkok, Thailand, Nov.11-13, 2019used to estimate the type of soil.
The first relative density, Dr correlation fromCPT cone resistance, qc was published in 1975 [18].
The Dr - qc correlation then was updated andpublished in 1978 [19]. Both correlations take into
account the effect of vertical effective stress, v' as
they are shown in Fig. 5.

resistant and relative density relationship. It
indicates that the grain size of sand is a very
important parameter to effect on the behavior of thesoil. So, it must be considered in soil mechanic
analysis. Then, for liquefaction potential analysis
based on Standard Penetration Test results, it must
include the sieve analysis of soil samples that takenfrom the same drilling hole to obtain the grain sizeof the soil.
100
Fine sand

Percent passing (% )

80
60
40
Coarse sand

20
0
0.01

0.1

1
Gain size (mm)10Fig. 3 Gradation of sand used in the Dr-N tests,
reconstructed from [17]Fig. 5 Relative density – qc relationships for sandy
soil, reconstructed from [19]In Indonesia, the Cone Penetration Test is very
famous in engineering practice, then Dr - qc
relationship become very important for liquefaction
potential analysis. It has been known that the qc is
effected by sand density, in-situ effective stress andsand compressibility. Sand compressibility depends
on grain size, grain shape and mineralogy. For theliquefaction potential analysis purpose, the relative
density of the soil can be taken from the cone
resistant correlation in the equation as follows [20]:Fig. 4 Relative density and penetration resistance
relationship for fine and coarse sands,
reconstructed from [17]Dr = C2(-1) ln Q/C0

(1)

Where C0=15.7, C2=2.41 and Q=(qc/pa)/(v’/pa)-0.5.
Here pa is reference pressure taken as 100kPa, in thesame unit as qc and v’.
Using the above equation, the liquefaction
assessment of sand deposit in Pasir Jambak due toPadang earthquake 2009 has been demonstrated [10].

Dr from CPT
Different from the Standard Penetration Test, theCone Penetration Test give two soil parameter; cone
tip resistance (qc) and skin resistance (qs). The
ration of those two values is named a friction ratio(Fr). This ratio is very important value that can be
549

SEE - Bangkok, Thailand, Nov.11-13, 2019

Rf=0.78-1.61 log(D50) for mechanical cone (3)This formulation is practically simple and gave good
estimation of the liquefaction potential in sanddeposits.

For estimating D50 from Rf, the Eq. (2) and Eq. (3)turn into Eq. (4) and Eq. (5) as follows:

D50 from CPT

D50= 3.056 e-1.4302 Rf for electrical cone

Although it is widely used for soil investigation
works, unfortunately CPT is usually not followed bydrilling for soil sampling. So the test of the grain
size of the soil is not possible. But fortunately CPT
also provides information on the skin resistance ofqs, where in the terms of the comparison with the qc
resulting in the value of Fr.
The CPT test result generally can be used toform soil profiling as well as soil type. The cone
resistance, (qc) is generally higher in sands andlower in clays. Then, the friction ratio, Fr
consequently is lower in sands and higher in clays.
The Fr value can not to provide exact estimation ofgrain size but it may provide a guide to soil typewhich has particular characteristic and behavior.
Many researcher had observed soil grain size
using CPT and confirmed that sandy soils tend havehigh cone resistance, qc where consequently gave
low friction ratio Fr, and the reverse for soft clay
soils [21] [22]. Fig. 6 presents the D50 and Rf
correlation, the CPT data were taken frommechanical and electrical cones.

(4)

and respectively,
D50= 13.043 e -1.7712 Rf for mechanical cone (5)In addition, the past studies on soil grain size
distribution had been conducted using SPT and CPT
resistances [22] and [23]. The SPT data is presented
in the terms of N60 values which is corresponding to
the energy ratio of about 60%. They concluded thatthe qc-N ratio is strongly related to the soil grain
size and expressed by the mean grain size (D50) as
shown in Fig.7. It is very useful in practice if both
CPT and SPT are performed in soil investigation.

Fig. 7

CPT-SPT correlation with D50 [23]ASSEESMENT FORMULA DEVELOPMENT

Fig. 6

Based on the previous description, the procedure
for liquefaction potential assessment of soil layers
then can be developed based on the Dr-D50
parameters obtained from the correlation of the test
results of soil investigation in the field using CPT
and SPT. Each penetration test procedure can bemade in the form of a flow chart as shown in Fig. 8
for CPT and Fig. 9 for SPT respectively.
Specifically for SPT testing, soil samples from thesoil layer must be taken to determine the grain sizeof the soil, or there must be a companion CPT test to
determine the correlation of soil grains.

Dr-Rf correlation [21]The best fit equation for the Dr-Rf correlation of[21] is:Rf=1.45-1.3 log(D50) for electrical cone

(2)

and,

550

SEE - Bangkok, Thailand, Nov.11-13, 2019

CONCLUSIONS

Fig. 8In order to produce a liquefaction hazard mapof a specific area, the assessment of liquefaction
potential is very important and become the mainstep. Some liquefaction potential assessment
methods have been proposed by researchers since
the last century. Every method is developed basedon the purposes and the completeness of available
data. The modified method in here is based on soil
relative density and mean grain size which are
obtained from laboratory tests.
In this paper a modified new method that iseasier and technically cheaper is proposed. The
method is developed based on the penetration
resistance data of the standard penetration test, SPT
and/or cone penetration test, CPT. The method is a
new procedure that is more practical to be applied
for general soil investigation test results. Thismethod is associated with soil parameters that are
obtained from the available correlation from soil
investigation test results that turned into the relative
density and mean grain size of the soil layer. This
new procedure is expected to be more applicable andreliable in making liquefaction hazard maps. The
application of the purposed method is under process
and the results in terms of liquefaction potential of
Padang City area will be published soon.

Dr-D50 Procedure for CPT test results

ACKNOWLEDGMENTS
The authors greatly express thank to Andalas
University which provided any support in theprocess of finishing this research.
REFERENCES

Fig. 9[1] Seed H.B. and Idriss I.M., Simplified procedure
for evaluating soil liquefaction potential, J. Soil
Mech. Foundation Division, 97, 1249–1273,
1971[2] Iwasaki, T., Tokida, K. and Tatsuoka, F., Soil
Liquefaction Potential Evaluation with Use ofthe
Simplified
Procedure,International
Conferences on Recent
AdvancesinGeotechnical Earthquake Engineering and Soil
Dynamics. 12. April 26th - May 30th, 1981,
http://scholarsmine.mst.edu/icrageesd/01icragee
sd/session02/12[3] Kim H.S., Cho N.G. and Chung C.K., Realtime LPI-based Assessment of the Liquefaction
Potential of the Incheon Port in Korea, 15
WCEE, Lisboa 2012
[4] Dixit, J., Dewaikar, D.M. and Jangid R.S.,
Assessment of liquefaction potential index for

Dr-D50 Procedure for SPT test results
551

SEE - Bangkok, Thailand, Nov.11-13, 2019

Mumbai city, Nat. Hazards Earth Syst. Sci., 12,2759–2768, 2012[5] Sarker D. and Ansary M.A., Assessment ofLiquefaction Potential Index for Approach Road
of Padma Multipurpose Bridge, IOSR Journalof Mechanical and Civil Engineering (IOSRJMCE), Vol. 12, Issue 2 Ver. VI (Mar - Apr.
2015), PP 132-138[6] Luna, R. and Frost, J. D.: Spatial liquefaction
analysis system, J. Comput. Civil Eng., 12, 48–
56, 1998[7] Chung, J.W. and David Rogers J., Simplified
Method for Spatial Evaluation of Liquefaction
Potential in the St. Louis Area, Journal of
GeotechnicalandGeoenvironmental
Engineering. 137:5,505-515, 2011[8] Maurer B.W., Green R.A., Cubrinovski M. andBradley B.A., Evaluation of Liquefaction
Potential
Index
(LPI)
for
Assessing
Liquefaction Hazard: A Case Study inChristchurch, New Zealand, Poster UC,
Christchurch, NZ, https://core.ac.uk/ download/
pdf/35471699.pdf (Accessed, May 2019)[9] Hakam, A., Laboratory Liquefaction Test of
Sand Based on Grain Size and Relative Density,
J. Eng. Technol. Sci. Vol. 48, No. 3, 2016, 334344[10] Seed, H. Bolton dan Idriss I.M., Ground Motion
and Soil Liquefaction During Earthquake,
Earthquake Engineering Research Institute,
Berkeley, 1982[11] Youd, T. L. and Idriss, I. M., Liquefaction
resistance of soils: Summary report from the1996 NCEER and 1998 NCEER/NSF workshop
on evaluation of liquefaction resistance of soils,
J. Geotechnical and Geoenvironmental Engg.,
ASCE, April 2001, pp. 297-313[12] Shibata, T. and Teparaksa, W., Evaluation ofliquefaction potential of soils using cone
penetration tests, J. Soils and Foundations, Vol.
28, N0. 2, 1998, pp. 49-60[13] Hakam A., Laboratory Liquefaction Test of
Sand Based on Grain Size and Relative Density,
J. Eng. Technology and Science, Vol. 48, No. 3,

2016, 334-344[14] Hakam A., Ismail F.A., Fauzan, Liquefaction
Potential Assessment Based On Laboratory Test,
International Journal of GEOMATE, Oct., 2016,
Vol. 11, Issue 26, pp. 2553-2557[15] Urmi Z.A. and Ansary M.A., Interpretation of
geotechnical parameters from CPT and SPT forthe reclaimed areas of Dhaka, Bangladesh,
Conference:CPT18 At Netherlands, November
2017.
[16] Terzaghi K. and Peck R.B. (1948) Soil
Mechanics in Engineering Practice, Wiley, New
York, USA[17] Gibbs K.J. and Holtz W.G. (1957), Research on
determining the density of sands by spoon
penetration testing, Proceedings of the 4thInternational Conference on Soil Mechanics andFoundation Engineering, London, 35–39[18] Schmertmann J.H. (1975) State of the art paper:measure of in situ strength. Proceedings of
ASCE Conference on in situ Measurements ofSoil Properties, Raleigh, North Carolina, pp.
57–138.
[19] Schmertmann J.H. (1978), Guidelines for Cone
Penetration Test, Performance and Design.
Federal Highway Administration, Washington,
DC, USA, Vol. 145, Report FHWA-TS-78–209.
[20] Robertson P. K. and Cabal K.L., Guide to Cone
Penetration Testing, GREGG inc., 2010[21] Douglas, B. J. and Olsen, R. S. (1981),Soilclassification using electric cone penetrometer
Cone Penetration Testing and Experience, Proc.
of the ASCE National Convention, St.
Louis,209-27, American Society of Civil
Engineers (ASCE)[22] Muromachi T. (1981), Cone penetration testingin Japan, Proc. Symposium on Cone Penetration
TestingandExperience,
GeotechnicalEngineering Division,ASCE,St. Louis, Missouri,
pp. 49–75.
[23] Robertson, P.K., Campanella, R.G. and
Wightman, A., SPT-CPT correlations, Journalof Geotechnical Engineering, ASCE, Vol. 109(11), 1983, pp. 1449–1459

552

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

COMPARISON STUDY ON DAMAGE PATTERN
OF TWO STORIES BUILDING:SIMULATION VS FIELD RECORD
1

1

1

2

Febrin Anas Ismail , Abdul Hakam , Hendri Gusti Putra , M Maisaquddus Hape , M Sofian Asmirza
1

3

2

Engineering Fac., Andalas University, Indonesia; Civil and Environmental Engineering Fac., Institute3

Technology of Bandung, Indonesia, Engineering Fac., North Sumatra University, Indonesia
ABSTRACT
Study on damage pattern of the two-story building is needed for quick assessment soon after theearthquake. In Indonesia, quick assessment is needed at least for two reasons: to determine Government
subsides Fund and to retrofit the damaged houses. The previous article has been analyzed and simulated thecase study of the two-story building due to earthquake load base on Indonesia Earthquake Code byconsidering the soil conditions. It shows that the influence of soil conditions as well as column properties
especially at a lower level are an important factor in determining the damage patterns. However, that study
was not verified yet with the damage data of the two stories building in the field. This paper discussed thecomparison between the simulation results with the field record of two stories building damage in Indonesia.
The data are collected base on the recent earthquakes in Indonesia: Padang Earthquake, Lombok Earthquake,
Solok Selatan Earthquake, and Padang Panjang Earthquake. It shows that they are confirmed the damage
patterns are in line with the simulation results. Base on this study, the guidance for quick assessment of twostory building then is developed.
Keywords: Earthquake, Quick assessment, Non-engineered two-story building, Indonesian code

INTRODUCTION
This study is the continuation of the previous
study regarding quick assessment of two stories
building [1]. Two stories building model has been
analyzed including the soil-structure interaction.
The soil categories are differed based on the
average of soil strength in terms either Standard
penetration value, Nspt, Shear wave velocity, Vs,
or, Soil strength, Su. Based on those values, thenumerical simulation then is conducted to take theadvances of soil-structure interaction methods.
The structural elements of the building aredesigned as reinforced concrete with the minimum
reinforcement. This design then gives theminimum capacity required for two-story building
and will be discussed in the results section. The
typical soil-structure interaction model fornumerical simulation are shown in Fig. 2
The geometry of the finite element model
shown in Fig. 2 has a height of 3.5m every leveland 4.0m between columns.

Fig. 2 Typical soil-structure model for analysis
The applied loads on the models are the selfweight load, live load, and earthquake load. The
earthquake load is adopted from the calculation
results by Ministry of Public Service of Indonesia.
The values of Acceleration Spectrum in a unit of g
are plotted on Y-axis respect to the period, T insecond on X-axis.

553

SEE - Bangkok, Thailand, Nov.11-13, 2019

The displacement pattern due to the earthquake
load is shown in Fig. 4. Meanwhile, the typicalinternal moment is shown in Fig. 5. The values ofdisplacement and internal forces due to the applied
load are given in Table 3.

Middle 2nd storey-28915

2778

-5281

Middle 1st storey-564834559

8236

Medium soil site
Column position

Axial

Shear

MomentEdge 2nd storey

-3661

208

-918

Edge 1st storey

-5973

2937

5918

Side 2nd storey-10474

-490

-1261

Side 1st storey-18821

2913

6132

Middle 2nd storey-28095

2777

-5305

Middle 1st storey-549764708

8429

Soft soil site

Fig. 4 Typical displacement of the models due toapplied earthquake load.

Column position

Axial

Shear

MomentEdge 2nd storey

-3990

-36

-569

Edge 1st storey

-6739

2720

5505

Side 2nd storey-10625

-805

-1776

Side 1st storey-192472761

5920

Middle 2nd storey-27204

2506

-4807

Middle 1st storey-533164359

7744

From the numerical results, it can be seen thateven though the applied earthquake loads for
medium soil site and hard soil site are the same,but the response of the structure give different
values. The medium site gives larger internal
forces in general. Furthermore, the earthquake load
applied to the structure in the soft soil is 10% lessthan the others. But the responses regarding
internal forces give bigger in some points.
The numerical simulations then will becompared to the strength of the structural element
to give the idea for built the quick assessment
procedure. This work is still under theinvestigation and will be reported soon after it
ready to be presented. However, these preliminary
results have given the idea to see the soil
characteristic in the location of the building during
investigating the building assessment, especiallysoon after the earthquake.
The purpose of this study is to compare
between the simulation results with the field recordof two stories building damage in Indonesia.

Fig. 5 Typical internal moment due to loads.
Table 3. Internal force values in column
Hard soil site

Methodology

Column position

Axial

Shear

MomentEdge 2nd storey

-3497

306

-1068

Edge 1st storey-5704.

2876.

5879.

Side 2nd storey-10455-345-977

Side 1st storey-189042744

5800

The methodology used in this comparison
study, as shown in Fig. 6. First, check theearthquake intensity. There are 3 categorizes ofearthquake intensity: small, medium, and high.
The criteria are used base on MMI scale. Second,
554

SEE - Bangkok, Thailand, Nov.11-13, 2019the soil type is checked. There are 3 types of soil:
soft, medium, and hard. Third, the column
condition is identified. In this case, there are 3
position of column to be checked: edge, side, andmiddle, including first and second floor.

earthquake in Aceh, Lombok and Palu.
B. Soil Type
Soil type will influence the shaking of theearthquake. The softer the soil, the bigger theshaking. Building on the soft soil will experience
more vibration due to its amplification. Fig. 5
shows how the building collapse built on soft soil.

a.

Soft Soil

Fig. 6 Field Assessment Procedure

RESULT AND DISCUSSION
In this study, there are a number of two stories
building are evaluated. The taken samples of twostories building are collected from earthquake
impacted area in Indonesia, that are, Aceh
earthquake 2006 (M6.0), Padang earthquake 2009
(M7.9), Lombok earthquake 2017 (M7.0), andPalu earthquake 2017 (M6.1). Each building
selected is located in 3 types of soil, that is, soft,
medium, and hard. Building evaluation thenapplied using procedure in Fig.4.
A. Earthquake Intensity
In general, the bigger the intensity of theearthquake, the havier the damage of building. In
case of un-proper constructed building, it will
collapse severely. It can be seen during Padang
earthquake (M7.9) with intensity in certain area
reach MMI 7. The same thing happens duringb.

Medium Soilc.

Hard Soil

Fig. 7 Damaged building in Assessment
In case of medium soil, due to big earthquake,the building still survived especially its structuralcomponent. However, its non structuralcomponents are collapse since they are not design
555

SEE - Bangkok, Thailand, Nov.11-13, 2019

to withstand to the big earthquake load. Fig 7shows the non structural component are collapse
due to earthquake.
Most building stayed on hard soil and properly
design according to earthquake code, canwithstand against the earthquake load. Hard soil
will keep the shaking constant and the good design
can absorb the earthquake energy properly.

Damage analysis can be seen from the detaildamage of each building. Fig. 8 shows the damageof structural component. It shows that the edgecolumn will first damage due to the shaking. It is
in line with simulation analysis where the internal
forces are bigger in this area. The next damage will
experience the side column and the last is the
middle column.
Conclusions
Padang is the capital city of the West Sumatra
is a very earthquake-prone city in Indonesia. The
city has experienced from many big during the lastyears in this century. There are two main sourcesof the earthquake in Padang, first is coming fromthe subduction boundary in the west part and thesecond source is the great fault of Sumatra theeastern part. Many big earthquakes have resulted
damages in the West Sumatra province from thatsources.
In purpose of build quick assessment tool, it isvery important to accomplish numericalsimulations of typical building structures in the
different soil type sites. Two stories building
generally destroyed by the earthquake, in thispaper the earthquake loaded building in Padang
become the main point. The numerical results
show that for the medium soil site and hard soil
site with the same load, give different responses tothe structure. Furthermore, for the soft soil with
10% less earthquake load, the responses regarding
internal forces give bigger in some points.
The comparison field's data and analysis resultin this study showed a good correlation between
them. More samples of damaged building to becompared to the analysis are still needed. This
work is still under further investigation but thesepreliminary results have given a good idea todevelop a quick procedure in conducting fsthebuilding assessment due to the earthquake.

a. Edge Column

b. Middle Column

ACKNOWLEDGEMENTS
The authors greatly express thank to ourcolleagues who have helped in the process offinishing this research.
REFERENCES[1] Aydan, Ö., Imamura F., Suzuki T., Ismail
F.A., Hakam A., Masmera, Devi P.R., A
Reconnaissance Report On The Bengkulu
Earthquake Of September 12, Japan Societyof Civil Engineers (JSCE) and Japan
Association for Earthquake Engineering(JAEE) With the collaboration of Andalas
University, October 2007

c. Side Column
Fig. 8 Damaged structural components.
C. Damage Analysis
556

SEE - Bangkok, Thailand, Nov.11-13, 2019[2] Hakam, A, "Laboratory Liquefaction Test of
Sand Based on Grain Size and Relative
Density", J. Eng. Technol. Sci., Vol. 48, No.
3, 2016, 334-344[3] SNI-1736-2012, Indonesian Earthquake code,
Indonesian Public Service Ministry, 2012
[4] Wahyuni E., Vulnerability Assessment ofReinforced
Concrete
Building
PostEarthquake, Procedia Earth and Planetary
Science, Volume 14, 2015, Pages 76-82[5] Sarmah
T.,
Earthquake
Vulnerability
Assessment for RCC Buildings of GuwahatiCity using Rapid Visual Screening, Procedia
Engineering Volume 212, 2018, Pages 214221[6] Local Disaster Management Agent, BPBD,
pictures of damages due to Padang earthquake
in 2009. taken in 2018[7] Tumeo R., Soil-Structure Interaction Effects
on the Seismic Performances of Reinforced
Concrete Moment Resisting Frames Procedia
Engineering Volume 199, 2017, Pages 230235[8] Menglin
L.,
Structure–Soil-StructureInteraction: Literature Review, Soil Dynamics
and Earthquake Engineering Volume 31, Issue
12, December 2011, Pages 1724-1731

Andalas University, Indonesia. He was graduatedand got Master from Institute Technology ofBandung. His Doctor is from Yokohama
University, Japan. His research interests include
the general problem in structural engineering anddynamics of the structure. His contact E-mail is
febrin@eng.unand.ac.id.
AUTHOR’S CONTRIBUTIONS
Dr. Febrin Anas Ismail: Conception, design,acquisition, final approval of the version to besubmitted. Dr. Abdul Hakam: Conception, design,
final approval of the version and submit the paper.
Dr. M Sofian Asmirza and Hendri G Putra: Criticalreviewing, analysis. M Maisaquddus H:
Summarizing and Interpretation of data as well as
conducting numerical model.
ETHICSThis article is original and contains
unpublished material. The corresponding author
confirms that all of the other authors have read andapproved the manuscript and no ethical issues
involved.

AUTHOR’S BIOGRAPHY
Dr. Febrin Anas Ismail is an Associate
Professor in the Civil Engineering Department of557

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

LIQUEFACTION POTENTIAL MAPPING OF THE CITY OF
VALENZUELA, PHILIPPINESAngelo S. Enoria, Jr.1, Sophia Joy Q. San Juan1, Hiyasmin F. Ubaldo 1,
Jordan N. Velasco1 and John Lemar M. Tirao 1
1
Department of Civil Engineering, Pamantasan ng Lungsod ng Valenzuela, Philippines

ABSTRACTThe city of Valenzuela in the Philippines has provided several preparedness plans and contingency measuresin anticipation of the 7.2-magnitude earthquake, dubbed as the “Big One”. In studying the movements along thecountry’s Valley Fault System, the said plans and measures were not accomplished. The consideration of the soil’s
potential to liquefy was not included—which is significant in providing hazard maps for the city. The researchers
assessed the soil in Valenzuela using soil investigation reports done from 2008 to 2017. The geotechnicalproperties were utilized to calculate liquefaction potential using Idriss and Boulanger’s Semi-empirical Method
for Factor of Safety against Liquefaction and the formula from Iwasaki, et al. for Liquefaction Potential Index.
Liquefaction potential maps were produced corresponding to moment magnitudes 6, 7, and 8. Based on the results,
67.65% of the city has the potential and probability to liquefy at magnitudes 6 and 7, while 70.59% for magnitude
8. On the same hand, about 32.35% of the city are the least susceptible to liquefaction during earthquake
magnitudes 6 and 7, while 29.41% for magnitude 8. It is therefore concluded that the majority of the soils in
Valenzuela is highly susceptible to liquefaction.
Keywords: Semi-empirical method, Liquefaction, Factor of safety, Liquefaction potential map
The researchers will apply Idriss and Boulanger’s
semi-empirical approach of assessing liquefaction
potential in incorporation with the weighting schemeof Iwasaki et al. using gathered geotechnical surveys
to evaluate liquefaction resistance of soils in a deposit,
or the cyclic shear stress ratio at a particular depth
beneath a level ground surface, determine themaximum or equivalent cyclic shear strength likely to
be induced in the soil deposit, and estimate theliquefaction potential index of the soil. (IB reference)
Utilizing a semi-empirical approach, the data outputs
will be computed as the factor of safety againstliquefaction, the liquefaction potential index, and the
production of liquefaction potential map of
Valenzuela City.

INTRODUCTION
When the pore-water pressure in a saturated soil
increases in a great amount, soil deposits behave likea viscous liquid that causes the soil to suspend inwater. Earthquake shaking further reduces soil
strength and stiffness, triggering a phenomenon
called liquefaction. Failure in ground capacity
happens, added by ground deformations and slope
instability which generates substantial structural
damage. The highly urbanized city of Valenzuela innorthern Metro Manila, Philippines, consists ofthirty-three (33) barangays (or wards), has apopulation of 653,441 as of 2019, and a land area of
47.02 square kilometers, and is one of the many cities
near the West Valley Fault. Liquefaction, in theseareas, is more probable to happen after a massive
earthquake shaking which will greatly affect several
communities alongside the coastal areas of Taguig,
Pasig, Marikina, Muntinlupa, Pasay, Las Piñas,
Pateros, Caloocan, Malabon, Navotas, andValenzuela. (PHIVOLCS 2011) These coastal areas
are most likely to be prone to soil liquefaction.
The main objective of this research is to develop
an earthquake liquefaction potential map of
Valenzuela that can inform the local government of
the liquefaction susceptibility of different barangays
to plan in advance for any liquefaction-related
disasters in the future.

EXPERIMENTAL PROGRAM
The conceptual framework is presented in Fig.
1. This discusses the process of determining whether
the soil in Valenzuela is susceptible to liquefaction
under earthquakes of magnitudes 6, 7, and 8.
In order to satisfy the objectives of this research,geotechnical properties taken from several soil
investigation reports collections were assessed usinga spreadsheet program. Idriss and Boulanger’s
simplified approach of liquefaction analysis in Fig. 2
was then utilized to determine the factor of safety
against liquefaction. Liquefaction potential index wasthen computed using the formula from Iwasaki et al.

558

SEE - Bangkok, Thailand, Nov.11-13, 2019

Geologic maps and production of a liquefaction
potential map were made using ArcGIS®.
𝑭𝑺 =

𝑪𝑹𝑹𝒎
𝑪𝑺𝑹

𝑳𝑷𝑰 = 𝚺𝒘(𝒛) ∗ 𝑭 ∗ 𝑯

RESULTS AND DISCUSSION(1)

Geotechnical Assessment(2)

The map of Valenzuela and its barangays is shownin Fig. 3.

Where
𝐹𝑆 is the factor of safety;
𝐶𝑅𝑅𝑚 is the corrected cyclic resistance ratio;
𝐶𝑆𝑅 is cyclic shear stress ratio;
𝐿𝑃𝐼 is the liquefaction potential index;
𝑤(𝑧) = 10 − 0.5𝑧, where z is the average depth ofsoil layer and its preceding layer from theground surface;𝐹 = 1 − 𝐹𝑆;
𝐻 is the thickness of the soil layer

DATA INPUT• Geotechnical properties• Geologic maps

Fig. 3

Considering water content, N-value (number ofblows required for 12-inch penetration resistance ofthe soil during Standard Penetration Test, or SPT),
and depth of soil penetration, collected data from thelocal government of the were analyzed. After carefulconsiderations, only 34 borehole logs were able todeliver the necessary requirements for this research,as shown in Table 1.

PROCESS• Determining maximum
equivalent cyclic shear
stress ratio and cyclic
resitance ratio• Evaluating factor of safety• Calculating liquefaction
potential index

Fig. 1

The city of Valenzuela and its barangays.

DATA OUTPUT• Factor of safety• Liquefaction potentialindex• Liquefaction potential map

Conceptual framework

Table 1 List of accepted soil investigation
reports/borehole logs for Valenzuela
Barangay nameArkong Bato
Bagbaguin
Balangkas
BignayDalandananGen. T. de Leon
Karuhatan
Mapulang Lupa
MarulasMaysanPalasanParadaPaso de Blas
Rincon
Ugong
Veinte Reales
TOTAL

Fig. 2Idriss and Boulanger (2004) semi-empiricalmethod for evaluating liquefaction potential.

Number of borehole logs
3
2
1
2
3
1
2
2
1
4
4
1
2
1
1
4
34

For calculating moist unit weight and dry unit
weights from the soil reports water content and
559

SEE - Bangkok, Thailand, Nov.11-13, 2019

specific gravity per soil depth were used, as shown ina sample computation in Table 2. The depth andcomputed unit weights were then used to calculate thetotal vertical pressure, pore water pressure, andeffective vertical pressure.

Depth
(m)
1.00
1.50
3.00
4.50
6.00
7.50
9.00

Table 2 Geotechnical properties calculation (Bignay,
Valenzuela)
Depth
(m)

Water
content(%)

NvalueSpecific
gravity

1.00
1.50
3.00
4.50
6.00
7.50
9.00

18.66
71.24
42.03
23.27
30.21
22.34
20.34

1
3
9
12
21
32
35

2.65
2.65
2.65
2.65
2.65
2.65
2.65

Moist
unit
weight(kN/m3)20.6408
15.4150
17.4676
19.822318.7997
19.9773
20.3275Dry
unit
weight(kN/m3)17.3949
9.002012.2985
16.0804
14.4380
16.3294
16.8917

Table 3 Results of factor of safety calculations at
magnitude 6

1.00
1.50
3.00
4.50
6.00
7.50
9.00

w(z)

F
9.75
0.935
9.375
0.922
8.875
0.874
8.125
0.871
7.375
0.132
6.625
0.000
5.875
0.000
LPI
Level of liquefaction severity:

𝑴=𝟔𝒘(𝒛) ∗ 𝑭 ∗ 𝑯
9.112
4.321
11.631
10.612
1.457
0.000
0.000
37.134
Very highContour maps of liquefaction potential indices ofeach location were generated to indicate liquefaction
variability triggered by the effects of earthquake
magnitudes 6, 7, and 8.
LPI values greater than 15 correspond to a very
high level of liquefaction severity, values between 5
and 15 are high, values between 0 and 5 are low, andvalues of 0 indicate a very low chance of liquefaction.
The identification of liquefaction severity in the maps
corresponds to specific colors of the shaded contours
which are based on the LPI values, as shown in
Figures 4 to 6.
Based on the gathered soil investigation reports,
most of the areas that exhibit high liquefaction
potential were found to have soft soils and are in areasin which groundwater tables are at shallow depths. It
can be observed based on these maps that there is avery high probability of liquefaction in majority of
the areas in Valenzuela.

Values of the stress reduction coefficient 𝑟𝑑 ,magnitude scaling factor 𝑀𝑆𝐹, standard penetration
resistance 𝑁1(60), cyclic shear stress ratio 𝐶𝑆𝑅, cyclic
resistance ratio 𝐶𝑅𝑅𝑚 , and factor of safety 𝐶𝑆𝑅 at
magnitudes 6, 7, and 8 respectively, were calculatedusing the previously computed values. Furthermore,
if FS ≤ 1.0, the soil layer is identified as susceptible
to liquefaction, otherwise, that layer has a low
potential to liquefy.

Unitweight(kN/m3)17.3959.002
12.29816.08014.43816.32916.892

H
(m)
1.00
0.50
1.50
1.50
1.50
1.50
1.50

Liquefaction Potential Mapping

Semi-Empirical Method

Depth
(m)

z
(m)
0.50
1.25
2.25
3.75
5.25
6.75
8.25

𝑀=6
𝑁1(60)
3.218
11.71922.98722.53536.57447.30946.734

𝑟𝑑

𝑀𝑆𝐹

𝐶𝑆𝑅

𝐶𝑅𝑅𝑚

𝐹𝑆

0.994
0.986
0.959
0.929
0.896
0.861
0.824

1.482
1.482
1.482
1.482
1.482
1.482
1.482

1.711
2.403
2.825
2.674
2.816
2.628
2.520

0.112
0.188
0.357
0.346
2.445
338.300
226.400

0.065
0.078
0.126
0.129
0.868
1.000
1.000

Liquefaction Potential Index
To compute for the liquefaction potential index,
factor of safety is needed. Iwasaki et al. established acondition where the liquefaction susceptibility forsoils with LPI = 0 is very low, 0 < LPI ≤ 5 is low, 5 <LPI ≤ 15 is high, and LPI > 15 is very high. It can beinferred from the results that as the earthquake
magnitude increases, the LPI also increases. Most of
the locations rendered LPI values greater than 15
which denotes high levels of liquefaction severity.

Fig. 4

Table 6 Computation of liquefaction potential index(LPI) at magnitude 6560

Liquefaction potential map at magnitude 6.

SEE - Bangkok, Thailand, Nov.11-13, 2019

to structural designers and engineers.
Considering soil liquefaction potential isimportant in design and construction. Ground
improvement and strengthening techniques ofbuilding’s foundation systems are recommended forareas that are exhibiting probabilities of liquefaction
to reduce it susceptibility. Suggested approaches forground improvement are vibro-compaction, dynamic
deep compaction, excavation and disposal ofliquefiable soils, and jet grouting or using structural
fills. The use of deep foundations and well-reinforced
or post-tensioned mats are also advisable.
ACKNOWLEDGMENTS
Fig. 5

Liquefaction potential map at magnitude 7.

The researchers would like to acknowledge theLocal Government of Valenzuela City for allowing
them to obtain the borehole logs needed to complete
this study. To the professors who took their time toguide and advise, a heartfelt thanks. To theresearchers’ families and friends, sincerest thanks for
all the patience and support that you have given.
Ultimately, to the One who is able to sustain theenergies of the weary authors, to Him be all the glory.

REFERENCES[1]

Fig. 6[2]

Liquefaction potential map at magnitude 8.

CONCLUSION[3]

Majority of the areas in Valenzuela gaveliquefaction potential indices greater than 15 whichindicate very high liquefaction potential. About
67.65% of the total land area exhibited possibility ofhigh potential to liquefy while 32.35% of the city are
the least susceptible to liquefaction at magnitudes 6
and 7. For magnitude 8, about 70.59% of the total
land area has high probability to liquefy and 29.41%
have low potential to liquefy. With the aid of
ArcGIS®, liquefaction potential maps were easily
generated to provided rapid analysis of various
locations, and in turn, may provide vital information

[4]

[5]

561

G. Castro, S. Poulos, “Factors affecting
liquefaction and cyclic mobility,” Journal of
Geotechnical Engineering Division, ASCE,
1977; Vol.103, No.GT6: 501-506.
E. Dela Vega, “Liquefaction susceptibility plotof Gerona, Central Luzon Philippines,”Tarlac
City, Tarlac, Philippines: Tarlac State
University, 2016.
I. Garcia, J. Go, P. Suspine, N. Concha,“Earthquake liquefaction susceptibility mappingof Pasig City,” Sampaloc, Manila, Philippines:
Far Eastern University Institute of Technology,
2017.
I. Idriss, R. Boulanger, “Semi-empirical
procedures for evaluating liquefaction potential
during earthquakes,” Berkeley, California, USA:
University of California, 2004.
T. Iwasaki, T. Arakawa, and K. Tokida,“Simplified procedures for assessing soilliquefaction during earthquakes,” International
Journal of Soil Dynamics and Earthquake
Engineering, 3(1), 49-58, 1984.

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE PROPERTIES OF POROUS CONCRETE PAVING BLOCKS
1, 2

Nurul Rezuana Buyung1 and Abdul Naser Abdul Ghani2
School of Housing, Building and Planning, Universiti Sains Malaysia, Malaysia

ABSTRACT
Porous concrete paver is a mixture of Portland cement, coarse aggregate or gravel and water. Higher porosity
is achieved by removing the finer particles such as sand from the concrete mixture. This research study theproperties of readymade porous concrete paver blocks. The density and void content of porous concrete pavers
were presented in this study by using 33 samples of porous concrete pavers and were analyzed using statisticalanalysis. Then, all samples are divided into four groups to study the infiltration rate and analyzed with different
design of joint and void content. This study shows the consistency on measurement of density and void content
where all the reading were nearer to the average value. Basically, porous concrete pavers usually contains 15
percent to 25 percent of void content. However, these porous pavers in individual form did not achieve the 15
percent to 25 percent of void content where the highest void content is 6.5 percent. But, the void requirements are
satisfactory when they are placed together on the ground. The joint gap provides for the voids requirement. While,the infiltration rate shows a different reading between two design where there is a different length of joint.
Keywords: Porous concrete pavers, Density, Void content, Infiltration rate

INTRODUCTION
POROUS CONCRETE PAVERS
Interconnected void in the porous pavement
would allow water to go through the pavement
especially during rainfall seasons. Conventional
impermeable asphalts and concrete pavements are
replaced by porous asphalt and porous concrete.
Through porous pavements, water could passes
through and leaves the pavements and it is called as
exfiltrate. Most of the porous pavements type has thesimilar general structure as shown in Fig. 1 [1].

Porous concrete is a mixture of Portland cement,coarse aggregate or gravel and water. Void content ofporous pavement is about 15 percent to 35 percent orin average of 20 percent and this is achieved byremoving the finer particles such as sand from theconcrete mixture. This void allows water to infiltrateunderlying soil and the water either pooling on thesurface or being discharge as runoff [4].
Permeable concrete pavement contain of
aggregates and a Portland cement binder. The
omission of fine aggregates provides the porosity inpermeable pavements. Modular interlocking concrete
blocks of the internal drainage cell type are pre-castor cast-in-place lattice or castellated pavers ofconcrete or plastic, which contain open cells. The
filling of the cells usually soil mixed with grass or
porous aggregates [5]. Permeable paver units such asstone, concrete or another durable material fixedwithin and above a base rock. Water infiltrated to thesub-soils through voids provided by gaps between
pavers [6].

Fig. 1
Cross section of a typical block paver
permeable pavement installation without underdrains
Basically, porous pavements are used as analternative to conventional impermeable pavement
which allows stormwater to stream into it and into astone reservoir [2]. Porous pavement usually haverough surface which could reduce the flows ofstormwater runoff and also improved the quality ofthe stormwater [3]. Porous pavements are usuallyused for low traffic load, car parks, footpaths,
walkways and driveways [2],[3].

Density
The density of pervious concrete depends on theproperties and proportion of the materials used, andthe compaction procedures used in placement. Inplace densities on the order to 1600 kg per cubic
meter to 2000 kg per cubic meter are common, whichis in the upper range of lightweight concretes [7]. The
density of the specimens ranged from 1650 kg per
cubic meter to 1943 kg per cubic meter [8].
562SEE - Bangkok, Thailand, Nov.11-13, 2019

Void content

Material

Typically, around 15 percent to 25 percent voids
are achieved in hardened concrete (Pervious concrete
pavements). A lot of study has been conducted byother researcher and usually, the ranges of voids
percentage are within 15 percent to 30 percent [7](ASTM C1754) The void content of the specimens
ranged from 22.6 percent to 37.0 percent [8].

The readymade porous concrete pavers withhexagonal shape were used for this experiment. The
pavers were produced in the factory with controlledenvironment and production. This pavers have arough texture compared to normal concrete pavers
where it is allow water to go through the pavers.

Infiltration rate
Porous pavements are designed to infiltrate
rainfall falling directly onto the surface [6]. A
pavement’s surface infiltration rate is measured withwater ponded on top of the pavement [9]. The
standards on infiltration tests for two types ofpermeable pavement systems: ASTM C1701 andC1781 were developed for porous concrete andinterlocking concrete pavers, respectively [10]. The
surface infiltration rates of some porous pavementschange over time, due to processes such ascompaction, sedimentation, migration of pavementbinder, and aggregation of soil particles by growing
vegetation [9].
The infiltration rate of a specific pavement surface
at a given moment in time depends on the quality ofmaterials and construction, and the history ofcompaction and sedimentation. The infiltration rate
assigned for the design of a surface should be a typicalvalue which will apply for the life of the pavement [9].
It can be seen from previous research, the infiltration
rate ranges are from the lowest 0.08 cm per second tothe highest 1.33 cm per second. However, based on
ASTM C 1781, the average infiltration rates ranging
from 30 to 1600 inch per hour (0.21 cm per second to
1.13 cm per second) and the average result difference
between two location averages 19.1 percent with a
median value of 12.2 [11].

Fig. 2

Porous concrete pavers

Density and void content
Density and void content test was carried out
using standard test ASTM C642 (Standard Test
Method for Density, Absorption, and Voids inHardened Concrete). The calculation for density andvoid content are as follow:Bulk density = [A/(C – D)] ρ = g1

(1)

Apparent density = [A/(A – D)] ρ = g2

(2)

Where A is the weight of oven-dried sample
measured in grams, B is the weight of surface-dry
sample after immersion measured in grams, C is theweight of surface-dry sample after immersion andboiling measured in grams and D is the apparent massof sample in water after immersion and boilingmeasured in grams. While, ρ is the density of water
which 1 Mg/m3 = 1 g/cm3.

MATERIAL AND METHODS
Moreover, the void content is a percentage of thevolume of permeable pore space (voids) as in Eq. 3.

This research study on the properties ofreadymade porous concrete pavers. The density, void
content and infiltration rate of readymade porous
concrete pavers. The reading of density and void
content are taken to review the consistency of porous
concrete pavers’ production. While, the infiltration
rate reading is taken with different design of jointingof porous concrete pavers.

Void content, % = (g2 – g1)/g2 * 100(3)

Where, g1 is the bulk density, dry, (Mg/m3) andg2 is apparent density (Mg/m3).

563

SEE - Bangkok, Thailand, Nov.11-13, 2019

Infiltration ratenormally distributed. These showed the samples are
consistent in their densities.

Infiltration rate test was carried out using standard
test ASTM C1781 (Standard Test Method for Surface
Infiltration Rate of Permeable Unit Pavement
Systems). A single infiltration ring is used for thistest.

Fig. 3

Dimension of single infiltration ring.

Fig. 4

Infiltration ring

Fig. 5

Standard deviation graph of density

Fig. 6

Normal distribution graph of density

The calculation for infiltration rate is as follow:I = KM/(D2 * t)

(4)

Where, I is the infiltration rate measured in mm/h
(in./h), M is the mass of infiltrated water measured in
kg (lb), D is the inside diameter of infiltration ringmeasured in mm (in.), t is the time required formeasured amount of water to infiltrate the surface
measured in second (s) and K is 4 583 666 000 in SI
units or 126 870 in (inch-pound) units.
RESULT AND DISCUSSION

Consistency of void content of porous concrete
paversThe density and void content of readymade
porous concrete pavers were taken and analyzed
using statistical analysis by measuring the mean andstandard deviation in order to measure theconsistency during production of the pavers. While,
infiltration rate reading is taken too compared
between different designs of jointing.

The result shows the mean of void content is 5.65
percent with 0.432 standard deviation. The values ofvoid content are spread out near the mean value asshown in Fig. 7. it is also shown the void content ofporous concrete pavers are normally distributed andthis shows they are consistent in their void content asshown in Fig. 8.

Consistency of density of porous concrete pavers
The result shows the mean of density is 2.05 Mg
cubic meter with standard deviation 0.041. Based on
Fig. 5, the value of densities are spread out near themean of the samples and Fig. 6 shows the samples are564

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 7

Fig. 10
Standard deviation graph of void content

Joint design B

Table 1.1 shows the result of infiltration rate andlength of jointing. As shown in Table 1.1, theinfiltration rate for Design B is higher compared toinfiltration rate for Design A. It can be seen theinfiltration rate is higher with the longer length ofjointing. Longer length of joint will infiltrated morewater compared to short length of joint.
Table 1 Infiltration rates and length of joint
DesignA
Fig. 8

Normal distribution graph of void content

B

Group

Infiltration
rate(in/h)

Length of
joint
(mm)

Group 1

1199

544

Group 21175

544

Group 31496

867

Group 41415

873

Effects of jointing design on infiltration rates
Fig. 9 and Fig. 10 shows the design of jointing andlocation of infiltration ring for infiltration rates test.

Fig. 9

Joint design A

Fig. 11565

Infiltration test for Design A Group 1

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 14
Fig. 12

Infiltration test for Design B Group 2

Infiltration test for Design A Group 2
The length of jointing were measured by using
AutoCAD 2017 program based on actual
arrangement during infiltration test. The schematiclayoutCONCLUSIONS

Fig. 13

The result of the experimental test for density
and infiltration rate for porous concrete paver were
acceptable where the range density are 1600 kg per
cubic meter to 2000 kg per cubic meter and thedensity of readymade porous concrete pavers range
are between 2000 kg per cubic meter to 2100 kg per
cubic meter. While the infiltration rate of thesesamples are acceptable where the value of infiltration
rates are between 1175 inch per hour to 1496 inch per
hour. As mention in ASTM 1781, the range of
infiltration rates are between 30 inch per hour to 1600
inch per hour. However, the void content of these
porous concrete pavers does not achieve the void
content required for porous ranged are between 15
percent to 30 percent. While in ASTM C1754
mentioned the void content ranged from 22.6 percent
to 37.0 percent. However, the void content of these
porous concrete pavers are between 4.4 percent to 5.6
percent. This shows a large different between
standard void content and actual void content ofpavers. More investigation need to be done on thevariety of arrangement and how they compensate thedeficiency in the individual block. Future study canbe conducted to measure the void content where thespaces of jointing will be included in the void content
measurements.

Infiltration test for Design B Group 1

566

SEE - Bangkok, Thailand, Nov.11-13, 2019[5]

REFERENCES
[1]

[2]

[3]

[4]

I. Abustan, M. O. Hamzah, and M. A. Rashid,‘Review of permeable pavement systems in
Malaysia conditions’, OIDA Int. J. Sustain.
Dev., vol. 4, no. 02, pp. 27–36, 2012.
J. Sansalone, M. Asce, X. Kuang, and V.
Ranieri, ‘Permeable Pavement as a Hydraulicand Filtration Interface for Urban Drainage’,
J. Irrig. Drain. Eng., vol. 134, no. October,pp. 666–674, 2008.
C. Pagotto, M. Legret, and P. L. E. Cloirec,‘COMPARISON OF THE HYDRAULICBEHAVIOUR AND THE QUALITY OF
HIGHWAY RUNOFF WATER’, Water
Res., vol. 34, no. 18, pp. 4446–4454, 2000.
M. Giguère, Urban Heat Island Mitigation
Strategies. 2009.

[6]

[7]
[8]

[9]
[10]

[11]

567

E. P. A. EPA, ‘Reducing Urban Heat Islands :Compendium of Strategies Cool Pavements’,
United State, 2005.
M. Cahill, D. C. Godwin, and M. Sowles,‘Porous Pavement’, Low Impact Dev. Fact
Sheet, p. 12, 2011.
P. D. Tennis, M. L. Leming, and D. J. Akers,
Pervious Concrete Pavements. 2004.
I. ASTM, ‘Standard Test Method for Density
and Void Content of Hardened Pervious
Concrete’, pp. 1–3, 2018.
K. F. Bruce, Porous Pavements. 2005.
C. Valeo and R. Gupta, ‘Determining Surface
Infiltration Rate of Permeable Pavementswith Digital Imaging’, Water, vol. 10, no.
133, pp. 1–22, 2018.
A. International, ‘Standard Test Method for
Surface Infiltration Rate of Permeable Unit
Pavement’, pp. 3–8, 2018.

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

CONSTRUCTING AN ARTIFICIAL INTELLIGENCE MODEL FOR
WATER ENVIRONMENT EVALUATION

1

Shengping Zhang1 and Jie Qi2Professor, Meijo University, Japan; 2 Professor, Utsunomiya University, Japan

ABSTRACTThis study constructs an artificial intelligence (AI) model to evaluate water environments, and applies anartificial neural network system to this AI model construction. This AI model has been tested in a real urban river
basin. The evaluation results based on the model reveal that most parts of the river are not suitable to its
management goal. Therefore, a sensitivity analysis based on the AI Model is carried out to select and rank the riverenvironment improvement measures in terms of the effectiveness of improvement. This study has shown that an
AI Model is able to reveal and simulate the complicated relationships between river management goals and diverse
river environment factors and also is able to make the sensitivity analysis and the selecting of effective riverenvironment improvement measures much more convenient and reliable. This study will contribute to establishinga more reliable river environment planning and management methodology.
Keywords: Water Environment Evaluation, Artificial Intelligence (AI), Neural Network, Sensitivity Analysis

there is one very strong common critism whichapplies to all three methods [3]: each method has only
evaluated the final water quality/environment. No
direct connections between evaluation results and thecauses or related environmental factors inside theriver basins have been taken into any consideration in
all of the methods although water environment is
neccessarily considered as a whole system.
Artificial intelligence (AI) has achieved great
successes in a broad range of fields such as image
recognition, automatic driving, and gaming due toAI’s strong capability to identify causal relations [3],[4]. An AI model is expected to be a powerful analytic
tool for water environment evaluation when the water
environment of a specific river is considered to be a
result caused by all possible water-environmentrelated factors in the river basin. This study will
construct an AI model specifically for water
environment evaluation and establish a more reliable
methodology for river environment planning andmanagement.

INTRODUCTION
Water environment evaluation is neccessery not
only for water environment planning but also forselecting the most effective and most efficient water
environment improvement measures. The traditional
water environment evaluation methods can beclassified into three groups [1]-[3].
The most-widely applied water environment
evaluation method is the one based on the physical,
chemical or biochemical indexes of river water
quality, such as PH, Dissolved Oxygen (DO),Biochemical Oxygen Demand (BOD), and total
coliforms. Objectivity is considered to be the mostsignificant and most important character of thismethod which, however, also leads to critiques that
relatively subjective resident/human demands forwater environments have not been taken into
consideration with this method.
In order to maximize the utility of the residents ina river basin, the water environment evaluation
method based on the satisfaction of all residents has
been applied quite frequently, particularly in urbanriver planning in which resident satisfaction is themain water environment management goal.
Questionnaire survey is the central tool of this method.
The third common method for water environment
evaluation is based on the biodiversity of the water
environment, which takes the perspective that thewater environment is not only for human beings but
also for the entire ecosystem.
Every method is suitable for some specific water
environment planning goals, and there are no
particular standards or characteristics that can be used
to distinguish one from the others as good or bad. But

ARTIFICIAL INTELLIGENCE MODEL
An artificial intelligence model, specifically aneural network model has been adopted to compose awater environment evaluation method for evaluationor prediction problems due to the suitability of neuralnetwork models [4], [5].
Structure of A Neural Network [5]A neural network is a network system constructed
artificially by idealizing the neurons (nerve cells), andconsists of a number of nodes and lines that are called
568

SEE - Bangkok, Thailand, Nov.11-13, 2019

𝑋𝑗 : input the unit 𝑗 of the hidden layer.
𝑓(∙) : unit output function.
w𝑖𝑗 : connection weight between the input
layer unit 𝑖 and hidden layer unit 𝑗.
𝜃𝑗 : threshold value of the hidden layer unit 𝑗
O : output from the output layer unit.
Z : input to the output layer unit.
w𝑗 : connection weight between the hidden
layer unit 𝑗 and the output layer unit.
Θ : threshold value of the hidden layer unit 𝑗units and connections (or links) respectively. Basedon the differences in network structures, neuralnetworks generally are classified into two types:
layered networks and interconnected networks. It has
been shown that a layered network is suitable for
evaluation/prediction problems due to its abilities inlearning (self-organization) and parallel processing of
information.
Figure 1 shows the structure of a typical layered
neural network, which has a layer of input units at thetop, a layer of output units at the bottom, and anumber of hidden layers between the input layer andthe output layer. Connections exist only between theunits in the adjacent layers, and connections within alayer or from a higher to lower layers are forbidden.

For the unit output function 𝑓 (∙) , some
expressions have been proposed. The following
Sigmoid function has been applied frequently.
However, it is not necessarily the best one in terms oflearning efficiency. A testing process for different
output functions is strongly suggested.
𝑓 (𝑥 ) =1
1 + 𝑒 −𝑥(5)

Theoretically, the neural network model
expressed by Eqs. (1) through (5) is able toapproximate any non-linear relationship between
inputs and outputs with any degree of accuracy byusing enough hidden layer units and setting
connection weights and thresholds to be appropriate
through proper learning processes [5].
Learning Process of Neural Network Model
For a neural network model, the process of setting
the connection weights unit thresholds is called
learning. The term learning here means the selforganization process through which the neuralnetwork model automatically adjusts all theparameters (i.e. all the connections and thresholds) tothe appropriate values, when a series of samples of
input-output data (called teacher data or teacher
signals) are shown to the model. If we consider the
information processing in a neural network model asa transformation of input data to output data, thenmodel learning can be considered to be a process
through which the neural network model gradually
becomes capable of imitating the transforming
patterns represented by the teacher data.
A lot of learning algorithms have been proposed,
and among them the Error Back Propagation
Algorithm is the most widely used and mostsuccessful algorithm. The following is the summaryof the Error Back Propagation Algorithm [6].
Suppose T sets of teacher data are given.

Fig. 1 Structure of a layered neural network.
Modelling A Neural Network
For the sake of simplicity, consider a neuralnetwork consisting of three layers.
Let the unit numbers of the input layer, hidden
layer and output layer be N, M, and 1, respectively.
When an input {𝐼𝑖 , 𝑖 = 1,2, ⋯ , 𝑁 } is given to theunits of the input layer, the inputs and outputs of thehidden layer units as well as the output layer units are
represented as follows.
𝑌𝑗 = 𝑓(𝑋𝑗 ), 𝑗 = 1,2, ⋯ , 𝑀(1)𝑁

𝑋𝑗 = ∑ 𝑤𝑖𝑗 𝐼𝑖 + 𝜃𝑖 , 𝑗 = 1,2, ⋯ , 𝑀

(2)

𝑖=1

𝑂 = 𝑓 (𝑍 )(3)𝑀

𝑍 = ∑ 𝑤𝑗 𝑌𝑗 + 𝜃

(𝑡)

(𝑡)

{𝐼1 , 𝐼2 , ⋯ , 𝐼𝑁(𝑡) , 𝑂(𝑡) ; 𝑡 = 1,2, ⋯ , 𝑇}

(4)

𝑗=1

(6)

Notice that the teacher data consists of two parts: the(𝑡) (𝑡)(𝑡)input part {𝐼1 , 𝐼2 , ⋯ , 𝐼𝑁 ; 𝑡 = 1, 2, ⋯ , 𝑇} andWhere 𝑌𝑗 : output from the unit 𝑗 of the hidden layer.

569

SEE - Bangkok, Thailand, Nov.11-13, 2019the output part{𝑂(𝑡) ; 𝑡 = 1,2, ⋯ , 𝑇} .
Now consider an initial value
[𝑘]

[𝑘]

study. The other variables which occurred in the final
learning procedures are defined as follows.

[𝑘]𝑤𝑖𝑗 , 𝑤𝑗 , 𝜃𝑗 , 𝜃 [𝑘] , 𝑘 = 0

𝛿 [𝑘](𝑡) = (𝑂(𝑡) − 𝑈 [𝑘](𝑡) ) ∙ 𝑂(𝑡) ∙ (1 − 𝑂(𝑡) )(7)[𝑘](𝑡)

𝛾𝑗for each of the connection weights and thresholdvalues, respectively. Notice that the superscript [k]indicates the number of learning iterations and [k=0]means the initial values for all the parameters directly
preceding the start of the learning process. Then the
outputs corresponding to the inputs of the teacher data(𝑡) (𝑡){𝐼1 , 𝐼2 , ⋯ , 𝐼𝑁(𝑡) ; 𝑡 = 1, 2, ⋯ , 𝑇} can be obtained
from Eq. (1) ~ Eq. (5). Let these outputs be{𝑈 [𝑘](𝑡) ; 𝑡 = 1, 2, ⋯ , 𝑇 𝑎𝑛𝑑 𝑘 = 0} .
Clearly,{𝑈 [𝑘](𝑡) ; 𝑡 = 1, 2, ⋯ , 𝑇 𝑎𝑛𝑑 𝑘 = 0} are different
from the outputs of the teacher data {𝑂(𝑡) ; 𝑡 =1,2, ⋯ , 𝑇}, and an error function can be defined withthe two different kinds of outputs as follows.
𝑅

2= ∑(𝑂(𝑡) − 𝑈 [𝑘](𝑡) ) , 𝑘 = 0(8)

Obviously, 𝑅 [𝑘] is a function of connection
weights and threshold values because {𝑈 [𝑘](𝑡) ; 𝑡 =[𝑘]1, 2, ⋯ , 𝑇 𝑎𝑛𝑑 𝑘 = 0} are calculated after all 𝑤𝑖𝑗 ,
[𝑘]

𝑇
[𝑘+1]

[𝑘]

= 𝑤𝑗

[𝑘](𝑡)− 𝜂 ⋅ ∑(𝛿 [𝑘](𝑡) ⋅ 𝑌𝑗

(9)

)

𝑡=1
𝑇

𝜃 [𝑘+1] = 𝜃 [𝑘] − 𝜂 ⋅ ∑ 𝛿 [𝑘](𝑡)

(10)

𝑡=1
𝑇
[𝑘+1]

𝑤𝑖𝑗

[𝑘]

[𝑘+1]

= 𝑤𝑖𝑗 − 𝜂 ⋅ ∑(𝛿 [𝑘](𝑡) ⋅ 𝑤𝑗[𝑘](𝑡)⋅ 𝛾𝑗(𝑡)⋅ 𝐼𝑖 )

(11)

𝑡=1
𝑇
[𝑘+1]

𝜃𝑗

(14)

The proposed neural network model has beenverified by applying it to an urban daily water demandprediction problem [7], which has been studied withseveral different models, and for which there is clarity
regarding what is a good or an acceptable prediction
for daily water demand. We will examine whether the
proposed neural network model is able to predict
daily water demand with the same or even higher
accuracy by using the same information as the otherprediction models used.
Specifically, the neural network model has been
compared with three different prediction models:Multiple Regression Model [8], ARIMA (AutoRegressive Integrated Moving Average) Model [9],[10] and Kalman-Filtering Model [10]. All themodels used the same daily water delivery records
from April 1982 to March 1990 for a city in Japan,
the weather information during the same time period
and each day’s characteristics (weekday or weekend/
national holiday) to calibrate or identify the model
parameters. This historical data is used because thecomparison models are composed with these data.
For the neural network model, these records are usedas the teacher data to train the model. As for theweather information, the records of daily hightemperature, weather (sunny, cloudy or rainy) anddaily precipitation are included.
Three accuracy indexes have been applied tocompare the models to identify which model is able
to give the most accurate prediction for daily water
demands. Mean Relative Error (MRE, %) is a verystraight index: the smaller the Mean Relative Error is,the better the predictions are. Correlation Coefficient(CC) between predictions and records indicates how

𝑤𝑗 , 𝜃𝑗 𝑎𝑛𝑑 𝜃 [𝑘] are given.
The Error Back Propagation Algorithm makes useof the connection weights and threshold values thatminimize the above error function 𝑅[𝑘] . Usually anon-linear programming method is required to solve
the optimization problem along with an iteration
process in order to obtain the optimal (but possibly
suboptimal) connection weights and threshold values.
The final iteration procedures derived from a nonlinear programming method known as the Method of
Gradient Descent are as follows.
𝑤𝑗)

Verification of Neural Network Model

𝑡=1

[𝑘]

[𝑘](𝑡)∙ (1 − 𝑌𝑗

In order to avoid the overfitting (or over-learning)problem, a criterion is usually required to make a
judgement when the iterative learning process shouldbe terminated. In this study the learning process will
be stopped when the Mean Relative Error (MRE) of
the outputs is less than a specified relative error
expectation for prediction/evaluation results, which is
a common treatment for a learning process of teacher
data with random errors (i.e. white noise). In thisstudy we have set the error expectation to 2%, whichis considered an accuracy that is good enough for the
expected result in this study. Needless to say, thiserror expectation should be set according to therequired accuracy of the problem which is being dealt
with.

𝑇
[𝑘]

[𝑘](𝑡)

= 𝑌𝑗

(13)

[𝑘]

[𝑘+1]

= 𝜃𝑗 − 𝜂 ∙ ∑(𝛿 [𝑘](𝑡) ⋅ 𝑤𝑗[𝑘](𝑡)

⋅ 𝛾𝑗

)

(12)

𝑡=1

where the superscript [k] indicates the number oflearning iterations as mentioned earlier, and η is asmall positive number that indicates the step size of
the Method of Gradient Descent for optimization
iteration process, and we have set η = 0.25 in this570

SEE - Bangkok, Thailand, Nov.11-13, 2019

good the predictions are: the predictions are perfectwhen CC=1.0, and the predictions are totally random
when CC=0. Relative Root Mean Square Error(RRMSE) are similar to CC and reflect how good thepredictions are: RRMSE=0 for perfect predictions
and RRMSE=1 when all the predictions are equal tothe mean of the records.
Table 1 shows the prediction accuracies of dailywater demands over the course of a year for the samecity from April 1991 to March 1992 by different
models. The neural network model gave the best
predictions by far in terms of all the three accuracy
indexes. The improvement magnitudes of prediction
accuracy in each index show the reliability and thepotential of the neural network model.

environment planning and management.
Table 3 The possible causes for the days witha relative error more than 10%.
Date

Model

MRE(%)CC

RRMSEMultiple Regression Model

2.90

0.764

0.659

ARIMA Model

2.80

0.794

0.623

Kalman Filtering Model

2.69

0.808

0.599

Neural Network Model

2.13

0.877

0.483

Possible causes

320.0

10.8

364.9

319.5

14.2

Hit by typhoon.

362.9

315.0

15.2

Oct.
7

361.4

404.4

10.6

Jan.
2

358.5

315.0

13.8

Heavy rain.
(105.5mm/day)
Sunny after 5
continuous
rainy days.
New Year
Holiday andsunny.

TRAINING OF NEURAL NETWORK MODEL
Teacher Data
The neural network model proposed above is now
ready to be applied to a water environment evaluation
problem, which is the purpose of this study. As for thewater environment evaluation index, the habitabilityof a water environment to Genji fireflies (Luciola
cruciate) is adopted. Genji fireflies are highly prizedin Japanese culture, and are widely regarded as asymbol for a good water environment. Firefly
habitability has even been adopted as a riverenvironment management goal in many urban river
basins in Japan.
As for the factors that affect the habitability of
fireflies, five highly critical factors have been
selected to be included in the teacher data although
there are many factors that impact firefly habitability[11]. Additionally, these five factors have been
selected because they are the main changeable factors
through common river environment improvement
measures. The five factors are 1) Concentration of
Dissolved Oxygen (DO), 2) Brightness of lighting
during nighttime, 3) Inflow of sewage, 4) Riverbed
situation, and 5) Type of revetment construction.

Table 2 Relative error distribution of the predictions
made by the Neural Network Model
No. of
Days
278
61
19
2
5

Relative
error
(%)

354.5

Sept.
17
Oct.
5

In order to understand the error structure of thepredictions given by the neural network model, theprediction error distribution is shown in Table 2, andthe possible causes have been examined for the 5 days
which have a prediction relative error greater than
10%, which is shown in Table 3. Per Table 3, thelargest prediction error was yielded when important
information that affected daily water demands was
missed. In other words, prediction accuracy is
expected to be further improved when this missed
information, such as typhoon, continuous rain periods,
extreme weather events or atypical days, are taken
into consideration by including all of them into theteacher data for neural network training. This
demonstrates that careful teacher data hunting isimportant in artificial intelligence application
research.

Relative Error Range(%)[0.0, 3.0)
[3.0, 5.0)
[5.0, 8.0)
[8.0, 10.)[10. , ∞)Deliveryrecord(m3/day)

The last day ofJapanese
holiday “Golden
Week” andsunny after arainy week.

May
5

Table 1 Prediction accuracy comparison ofdifferent models.

Demandprediction(m3/day)

Composition
(%)
76.2
16.7
5.2
0.5
1.4

Quantification of Habitability and Factors
Firefly habitability and related factors have been
quantified by utilizing information and knowledge
about Genji fireflies from existing research [11], [12].
First, firefly habitability is treated as a continuous
variable which ranges from 0.0 (for extremely
unlivable water environments) to 1.0 (for an idealistic
water environment). Then, all the factors are
categorized although most are usually measured
quantitatively as a continuous figure. This resolves
the issue that the same number can mean different

Based on these results, it is reasonable to conclude
that the proposed neural model is a reliable andcapable tool in information processing of data. In thenext section we will apply this neural network model
to river environment evaluations and predictions inorder to provide better information for water
571

SEE - Bangkok, Thailand, Nov.11-13, 2019things for different rivers. For example, the sewage
inflow rate 1.0 ton/hour is an extremely strong
pollution source for small urban rivers, but could
mean almost nothing for a river with a flow rate ofmore than 100 m3/s.
As an example, Concentration of Dissolved
Oxygen (DO) is categorized as 1 for a DO saturated
situation, 0 for the DO concentration above 6.8 mg/l
(which means a livable environment for fireflies), and-1 for the DO concentration below 6.8 mg/l (whichmeans an undesirable/deadly living environment). In
the same way, the other four factors are also
categorized as shown in Table 4.

order to present the teacher data to the neural networkmodel, and a proper initial network size (layers andunits in each layers). An experienced AI engineer
may be able to assist in accelerating the learning
process.
Figure 2 shows the reproduction accuracy of theteacher data with the trained neural network model.
Here the reproduction accuracy is represented by theabsolute error between the habitability in the teacher
data and the habitability generated with the trainedneural network model. Based on the results in Fig. 2,
there are only 6 out of 162 teacher data that have thesame order of absolute error as the smallest
significant figure (±0.001) of habitability, and all the
156 teacher data have an error less than the smallest
significant figure, which means that the trained neuralnetwork model is able to reproduce the teacher datawith almost no errors. In the next section, this welltrained neural network model will be used to evaluate
the firefly habitability of an urban river.

Table 4 Factor Quantification
FactorCategory
Meaning

Riverbed situation
Type ofrevetment
construction

1
0
-1
1
0
-1
1
0
-1
1
-1
1
0
-1

DO saturated≥6.8mg/l, livable<6.8mg/l, undesirable
No sewage inflow
A small amount of inflow
Constant inflow
Dark (no artificial light)
Relatively dark
BrightNatural riverbed withsoil, sands or pebbles
Artificial riverbed
NaturalPartially natural
Artificial

0.0020Absolute Error

Concentration
Of Dissolved
Oxygen (DO)
InflowofsewageBrightness
Oflighting

Concentration

Inflow of
sewageBrightness oflighting

Riverbed
situation

Type ofrevetment

Habitability

of DO

1
1
1
1
1
1
1

1
1
1
1
1
1
1

0
0
0
0
0
0
1

0.915
0.000
0.875
0.865
0.000
0.000
1.000

-0.00100100-0.0020

WATER ENVIRONMENT EVALUATION
Firefly Habitability of Aise River
The trained neural network model has been
applied to evaluate the firefly habitability of Aise
River. Aise River passes through Inuyama City in
Aichi prefecture, Japan, and is a typical urban riverwhich receives sewage and urban drainage. Aise
River also receives fresh water inflow at its
uppermost location from Kisogawa River, a regional
water supply source with a high flow rate. The fresh
water from Kisogawa River has improved the water
environment of Aise River in its upper segments
significantly, but the improvement effects have been
gradually cancelled out by the constant sewage inflow
when the river runs downstream. In this study, Aise
River has been divided into four segments according
to the present water environment: upper, mid-upper,
mid-lower and lower. Fig. 3 shows the images of thefour segments of Aise River.
The present water environment factors of Aise
River and its firefly habitability yielded by the trainedneural network model are shown in Table 6. The
evaluation results can be summarized as follows.
 The upper segment of Aise River is a habitat
very suitable to Genji fireflies.
 The habitability has decreased sharply

Table 5 Teacher data samples.

1
1
0
0
0
-1
1

0.0000Teacher Data
Fig. 2 Reproduction accuracy of teacher data

The firefly habitability and the five related factors
together make the teacher data. Samples of teacher
data which are used in this study are shown in Table
5. 162 teacher data have been collected from a varietyof research references on Genji firefly habitability[11], [12].

0
-1
1
0
-1
1
1

0.0010Training of Neural Network Model
The neural network model has been trained (putunder a learning process) with the collected teacher
data. The training process is based on the learning
procedures as explained before, but it is still a processof trial and error because there are still a lot of details
that remain undecided, such as a suitable step size of
optimization, a suitable output function, an efficient
572

SEE - Bangkok, Thailand, Nov.11-13, 2019

downstream.
The mid-lower and the lower segments of Aise
River are no longer habitable to Genji fireflies.
The above conclusions derived from theevaluation results that are given by the trained neuralnetwork model match well with the observation that
there are no fireflies during summer along the midlower and lower segments of Aise River for many
years.

Sensibility Analyses of Factors



The trained neural network model has also beenused to carry out a sensibility analysis for all thefactors related to firefly habitability. The sensibility
coefficient of a factor is defined as the partial
derivative of the habitability regarding the factor as
follows.
𝜕𝑂(𝑋1 ,𝑋2 ,⋯,𝑋𝑁)|𝑝𝑟𝑒𝑠𝑒𝑛𝑡 𝑓𝑎𝑐𝑡𝑜𝑟 𝑣𝑎𝑙𝑢𝑒𝑠
𝜕𝑋𝑖

𝑆𝑖 =

(15)

𝑆𝑖 is the sensitivity coefficient of factor 𝑋𝑖 at thepresent factor values. For all the factors, thesensitivity coefficients have been calculated andshown in Table 7. The whole number 0 means acoefficient value less than the smallest significant
figure.

(a) Upper Segment

Table 7 Sensibility coefficients of factors.

Type ofrevetment

Habitability
0.999

1

1

0

1

0

0.874

1

0

0

1

-1

0.471

1

-1

-1

-1

-1

0.003

Type ofrevetment

Riverbed
situation

1

Riverbed
situation

Brightness oflighting

1

Brightness oflighting

Inflow of
Sewage1

Inflow of
SewageConcentrationof DO

Location
Lower

1

of DO

Table 6 The firefly habitability of Aise River

1

Concentration(d) Lower segment
Fig. 3 Images of Aise River

MidUpper
MidLower

Upper

0.00030.00420.00160.00020.0016

MidUpper
MidLower

0.07490.05850.46080.11954.40790.001000.00020.00020.0011

Lower

0

0

0

0

0

For the upper segment of Aise River, all thefactors have a relatively small sensibility coefficient,which is because the present values of all the factors
are good enough and there is no room for further
improvement.
For the mid-lower and lower segments, all thefactors also have a relatively small sensibility
coefficient, which is because the present values of all
the factors are so poor that a small improvement will
not make a meaningful change in firefly habitability
along these river segments.
For the mid-upper segment, the revetment has alarge sensitivity coefficient, this indicates that
improving the present revetment (partially natural)
will increase the firefly habitability significantly. The
brightness factor also has a large sensitivity
coefficient, which means that removing all theartificial lighting will improve the firefly habitability.
The other three factors all have a relatively small
sensitivity coefficient, which is because the present
values of these factors are already good, and there isno need for further improvement.

(c) Mid-Lower Segment

Upper

Location(b) Mid-Upper Segment

573

SEE - Bangkok, Thailand, Nov.11-13, 2019practical research on artificial intelligence
applications will be the gathering of teacher data. In
spite of these difficulties, artificial intelligence is apromising tool for water environment planning andmanagement.

Selecting Improvement Measures
The evaluation results of firefly habitability alongwith the sensibility analysis results have drawn a clear
picture about the most effective water environment
improvement measures, which can be summarized asfollows.
 For the upper segment, no improvement
measures are necessary because the present
situation is already good enough.
 For the mid-upper segment, changing therevetment into natural revetment and removing
all the artificial lighting are expected to raise
firefly habitability significantly.
 For the mid-lower and lower segments,
significant improvement for all factors arenecessary because a small change for either
factor is not expected to cause any meaningfulimprovement in firefly habitability due to thepoor situation at present.

REFERENCES[1] Hagihara R., Takahashi K. and Hagihara K.,
Urban Environment and Waterfront Planning,
Keisoshobo Publisher, 1998.
[2] Hagihara Y. and Hagihara K., Methodology ofPlanning for Water and Green, Kyoto University
Publisher. 2010.
[3] Zhang S. P. and Kido Y., A Study on theEnvironment Evaluation method for Aise Riverand the Effectiveness of River Environment
Improvement Measurees, Urban Science Studies,No. 21, 2016, pp. 45-56.
[4] IPA, WHITE PAPER Artificial Intelligence 2019,
Kadokawa publisher, 2018.
[5] Asou H., The Information Processing by Neural
Network Models, Sangyo Publisher, 1988.
[6] Rumelhart D. E., Hinton G. E., and Williams R. J.,
Learning Representations by Back-propagating
Errors, Nature, Vol. 323, No. 9, 1986, pp. 533-536.
[7] Zhang S. P., Watanabe H., and Yamada Y.,
prediction of Daily Water Demands by Neuralnetworks, Stochastic and Statistical Methods inHydrology and Environmental Engineering, Vol.
3, 1994, pp. 217-227[8] Tsunoi M., An Estimate of Water Supply Basedon Weighted Regression Analysis Using a
Personal Computer, Journal of Japan Water
Works Association, Vol.54, No. 3, 1985, pp.2-6.
[9] Koizumi A., Inakazu T., Chida K., andKawaguchi S., Forecasting Daily Water
Consumption by Multiple ARIMA Model,
Journal of Japan Water Works Association, Vol.
57, No. 12, 1988, pp. 13-20.
[10] Yamada R., Zhang S. P., and Konda T., An
Application of Multiple ARIMA Model to Daily
Water Demand Forecasting, Annual Report of
NSC, Vol. 18, No.1, 1992, pp. 126-136.
[11] Furukawa Y., Encyclopedia of Fireflies, Tokyo
Institute of Firefly Researches, 2001[12] Murada Y., A Study on the Water Qualities for
Firefly Habitats, Proc. Of the 50th Annual Meetingof the Civil Engineering Associations of Japan.
2005.

CONCLUSIONSWith the purpose of developing a bettermethodology for water environment planning andmanagement, a neural network model has been
proposed for water environment evaluation in thisstudy.
The neural network model was tested with thedaily water demand prediction problem, a wellstudied problem suitable for testing. The test has
shown the reliability and potential of an artificial
intelligence model.
The verified neural network model was applied toa water environment evaluation problem, specificallythe Genji firefly habitability problem. The application
results have shown that, with a neural network model,
not only can the environment of an urban river be
evaluated with a high level of accuracy and detail, butalso that the most effective environment
improvement measures can be clearly identified.
These results demonstrate that artificial intelligence isan effective and efficient tool for water environment
evaluation.
The firefly habitability was studied with only
select critical factors in this study, which is
insufficient for genuine habitability research because
there are many other factors which affect firefly
habitability. The factors were limited to the criticalones due to the limitations of data hunting. Thisillustrates that one of the significant challenges of574

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

INFLUENCE OF ERRORS THAT RESULT FROM CONSIDERATION
OF WATER IN-FLOW DIMENSION DIFFERENCES BASED ON
OBSERVATION METHOD FOR MOUNTAIN TUNNELCONSTRUCTION
Yasuyuki Kubota1, Moritada Mori2, Toru Yasuda3, Satoshi Nishiyama4
Environmental Science and Technology, Okayama University, Japan; 2Takenaka Civil Engineering &Construction, Japan; 3 Pacific Consultants Co., Ltd, Japan; 4Graduate School of Environmental and Life
Science, Okayama University, Japan
1

ABSTRACT
Groundwater infiltration during mountain tunnel construction can lead to several problems, including tunnel
face collapses and environmental impacts. To address these issues, it is necessary to be able to evaluate
groundwater flow rapidly and accurately, and hence, Sequential Data Assimilation – System on Water Informationof Ground (SDA-SWING) method was developed. It enables inverse analysis using a simplified model and reflects
observational data from the site. However, groundwater inflow control during tunnel excavation is generally
difficult, as it depends on the heterogeneity of the geological structure. According to the equations for Dupuit
quasi-uniform flow and Bear associated rainfall penetration rate, the SDA-SWING method incorporated a certain
error, in that flow in the vertical and depth directions is not considered, strictly speaking, as isotropic hydraulicconductivity is assumed. In this study, we conducted numerical experiments on simulated tunnels and were able
to verify how the error, which was caused by flow dimension difference, affected Ensemble Kalman Filter (EnKF)
processing. As a result, the error in the SDA-SWING method was small enough compared to each analysis method,which is considered two-dimensional and three-dimensional flow, and the difference could be incorporated into
the analysis at the initial stages of excavation when performing EnKF processing. For this reason, we reported thatthe method has the potential to be a system, which is able to evaluate groundwater flow quickly and accurately.
Keywords: Tunnel excavation, Groundwater, EnKF, SDA-SWING

this type of inverse analysis, and it is difficult to apply
data obtained from observations such as tunnel inflow
and groundwater level, due to numerical model
complexities. Hence, the SWING (System on Water
Information of Ground) method was developed as anevaluation method for groundwater flow. This model
facilitates inverse analysis using a simplified model,
and applies site-based observation data. Control of
the groundwater inflow during tunnel excavation is adifficult issue, because it depends on theheterogeneity of the geological structure. The
SWING method is an evaluation system that follows
the tunnel excavation process, by reconstructing
model steps using data obtained from observations
made at the construction site. In this reconstructing
process, you can determine parameters for the
updated models by using an optimization method. In
the original SWING method, parameter optimization
was performed using trial-and-error, and required
highly skilled personnel, so the method was modified
using an Ensemble Kalman Filter (EnKF)-which is adata assimilation technique. Introduction of the EnKF
allowed automatic optimization of hydraulicparameters, and the modified. The developed SWING
method has been called SDA-SWING (Sequential
Data Assimilation-SWING). According to the

INTRODUCTION
There are various problems associated withgroundwater in mountain tunnel construction,
including collapse of the tunnel face, delays to
excavation schedule, damage to excavation
machinery, and environmental impact. To addressthese problems, it is necessary to be able to evaluate
groundwater flow quickly and accurately. Prediction
analysis is necessary and important, to reduce risks
related to tunnel excavation, such as unexpected
groundwater inflow to the tunnel. Numericalsimulations by the finite element method (FEM) havebeen commonly used as the primary method forpredicting and evaluating groundwater inflow into atunnel and the impact of excavation on thesurrounding groundwater environment. For better
predictions and estimations, sophisticated numerical
three-dimensional models, using suitable geological
data obtained from field measurements, are required.
However, as there are always limits to field
investigations-mostly due to economic and technicalissues, these predictions are not always correct.
Inverse analysis, using value observations from thefield, would be useful, although the threedimensional models for FEM are not compatible with
575

SEE - Bangkok, Thailand, Nov.11-13, 2019equations for Dupuit quasi-uniform flow and Bearassociated rainfall penetration rate, the SWING
method introduce a certain amount of error, by notconsidering flow in both the vertical and depth
directions, and assuming isotropic hydraulicconductivity. The SDA-SWING method is anapproach to find the optimal solution considering theerror. In this study, we conducted numericalexperiments on simulated tunnels and verified how
the error that was caused by flow dimension
differences, affected the EnKF processing.

Calculation of groundwater inflow and the rangeof groundwater level reduction
The SWING method incorporates someassumptions (see Fig. 3). (1) The tunnel is excavatedin an aquifer that is above an impermeable layer. (2)The size of the excavated tunnel is relatively small
compared to the analytical domain. (3) The initial
groundwater table is horizontal above the tunnel (thelocation of the initial groundwater table is Ho fromthe upper boundary of the impermeable layer). (4)The rainwater infiltration rate, ε, is considered in themodel. The SWING method follows the equations
for Dupuit quasi-uniform flow, which the equations,the groundwater inflow to the tunnel per unit length,q(t), and the groundwater level, h(x, t), can becalculated using Eq. (1), as follows:[3]THE SWING METOHD CONCEPTThe SWING method uses slice volumes, reflectssite observation data, and enables inverse analysis
using the simplified model and so is able to improveprediction accuracy. For develop the SWING method,
this analysis should be satisfied with the strength andweakness of conventional tunnel groundwater inflow
prediction methods.

ℎ(𝑥, 𝑡)2 − ℎ𝑜2𝑥=22
𝐻𝑜 − ℎ𝑜𝑅(𝑡)𝐻𝑜2 − ℎ𝑜2q(t) = k2𝑅(𝑡){Slice volumes during tunnel excavation(1)

A slice volume is the tunnel excavation area
divided at equal intervals (see Fig. 1). For each slice,
we analyzed groundwater flow, assuming Dupuit
quasi-uniform flow (see Fig. 2). The groundwaterlevel at slice 1 is lowered after tunnel excavation; i.e.,at the end of slice 1’s excavation, the groundwaterlevel is lowered, but only in slice 1. The new slice
volume (slice 2) was added at the time when slice 2
became the analysis point. The analysis continued
while accumulating slice volumes sequentially, as
excavation progressed.
Fig. 3.
Schematic of groundwater
variation caused by tunnel excavation.

Fig. 1.

level

In Eq.(1), ε is rainfall infiltration rate, k is stratum
hydraulic conductivity, h(x, t) is groundwater level atposition x as a function of time t, Ho is initial
groundwater level, ho is the distance of the tunnel
from the impermeable layer, q(t) is the amount oftunnel groundwater inflow for each slice volume, andR(t) is the range of influence (where the groundwaterlevel is lowered as a result of tunnel excavation) for
each slice volume.
Using Eq. (1), the groundwater level at any
position, and its time evolution during the excavation
process, h(x,t), can be calculated as shown in Eq.(2).

Slice volume during tunnel excavation.

h(x, t) = √𝑥(𝐻2 − ℎ𝑜2 ) + ℎ𝑜2
𝑅(𝑡) 𝑜(2)Considering the water balance, the amount ofgroundwater inflow to the tunnel should equal thesum of the groundwater lost in the aquifer plus

Fig. 2.
Summation of slice volumes during
tunnel excavation.
576

SEE - Bangkok, Thailand, Nov.11-13, 2019

rainwater infiltration (see Fig. 4). This relationship isexpressed in Eq. (3)-which is the Bernoulli equationin which λe and ε are the porosity and rainfall
infiltration rate, respectively.

SWING method, rainwater infiltration is consideredusing the rainfall infiltration rate, ε, which can be
determined using a multi-tank model.
INCORPORATING ENKF INTO THE SDASWING METHOD

𝐻𝑜2 − ℎ𝑜2
𝐻𝑜 − ℎ𝑜qdt = kdt = 𝜆𝑒𝑑𝐿 + 𝜀𝑅𝑑𝑡 (3)2𝑅(𝑡)3EnKF processing is a form of the data assimilation,and incorporating it into the SWING method
improved prediction accuracy and enabled automaticparameter optimization. However, according to theequations for Dupuit quasi-uniform flow and theassociated Bear rainfall penetration rate, the SDASWING method incorporated an error, in that it didn’tstrictly consider flow in both the vertical and depth
directions, as it assumed isotropic hydraulicconductivity. In addition, it included errors associatedwith both observation data, and caused by variations
in hydraulic conductivity. These various errors arefound in the governing equation, and so EnKF
processing was incorporated into the SDA-SWING
method, to derive optimal solutions based on
observation data.

Fig. 4.
Calculation method for groundwater
inflow into the tunnel with each slice volume.
In terms of time, t, with the initial conditions ofR(t) = 0 at t = 0, Eq. (3) can be integrated between
limits, to yield Eq. (4).
16𝜀𝑡2
𝑘(𝐻𝑜2 − ℎ𝑜2 )−R(t) = [{1 − 𝑒 𝜆𝑒(𝐻𝑜 −ℎ𝑜 ) }]2𝜀(4)

The range of influence at t = ∞ can be calculated
as shown in Eq. (5).
1𝑘(𝐻𝑜2 − ℎ𝑜2 ) 2
R(∞) = []2𝜀(5)The instantaneous groundwater inflow (per unit oflength) for each slice volume can then be calculated.
q(t) =

𝑘(𝐻𝑜2 − ℎ𝑜2 )2𝑅(𝑡)Fig. 5.
The SDA-SWING method incorporating
EnKF processing.
Data assimilation has two distinct phases“predict” and “update”. The predict phase uses thestate estimate of the previous time step, t-1, to
produce an estimate of the state at the current time
step, t. Although, it does not include observation
information from the current time step, it is an
estimate of the state at the current time step. In the
update phase, the current prediction is combined withcurrent observation information to refine the state
estimate.

(6)

From the above equations, the amount ofgroundwater inflow to the tunnel and the range ofinfluence of the groundwater table can be calculated
for each tunnel excavation stage (every slice volume),
as shown in Fig. 2. The calculated groundwater
inflow to the tunnel in each slice volume can besummed for the slice volumes’ total, and the total
calculated amount of groundwater inflow can becompared with observational data. The hydraulicconductivity for each slice volume is then backcalculated, based on the observation data. This
process is repeated for each excavation stage and thehydraulic conductivity field can be continually
updated hydraulic conductivity field can then be used
to predict groundwater inflow to the tunnel. In the

System model𝑥𝑡 = 𝑓𝑡 (𝑥𝑡−1 ) + 𝑣𝑡
Observation model𝑦𝑡 = ℎ𝑡 (𝑥𝑡 ) + 𝑤𝑡,,

𝑣𝑡 ～𝑁(0, 𝑄)(7)

𝑤𝑡 ～𝑁(0, 𝑅)(8)

In (7) and (8), vectors xt and yt indicate the stateof a system and observed data at a discrete time, and
577

SEE - Bangkok, Thailand, Nov.11-13, 2019vectors vk and wk denote system noise and observationnoise. Operation ft represents the temporal evolutionof a state from time tk-1 to time tk, according to thesystem model based on the simulation, while Hk
projects the state vector xk to the observation space.
When performing optimization using observation
data, we sought to combine state models that could
reproduce observation data under the assumption thatnoise (vt, wt) was included in the system state andobserved data vectors. Therefore, the system model is
as shown in Eq. (9), where it is assumed that the statetransition matrix does not exist and that system noise
is included.
System model𝑥𝑡 = 𝑥𝑡−1 + 𝑣𝑡,

𝑣𝑡 ～𝑁(0, 𝑄)

Therefore, only the horizontal flow was considered inmethod (a). On the other hand, methods (b) and (c)accounted for flow in the vertical or depth direction.
The error caused by flow dimension differences was
included in calculations (a) to (c). Method (c) was
expected to be able to reproduce the actual
phenomenon, calculating the groundwater flow withhydraulic conductivity set as a constant. We applied
the data assimilation by EnKF to the inverse
calculation of the hydraulic conductivity when the
groundwater flow of (c) represented is theobservation information of (a) and (b). Thus, there
was neither system noise, vk, nor observation noise,
wk. Therefore, comparing the calculated hydraulicconductivity inverses, each value would be differ by
the error caused by flow dimension difference. By
comparing these, the effects of the difference in eachanalysis method can be directly calculated.

(9)

The state variable vector in the SDA-SWING
method is hydraulic conductivity, k, and rainfall
infiltration rate, ε. The observation variable vector is
the groundwater flow. However, vt is applied only to
any k that has a significant effect on the system state
analysis results. In the EnKF, the closer the
probability distribution of the system state to a
Gaussian distribution, the better the accuracy. The
logarithmic value of hydraulic conductivity follows aGaussian distribution, so therefore, system noise isgiven to the logarithmic value of the hydraulicconductivity. From this, the state space model in the
SDA-SWING method can be described as shown in
Eqs. (10) and (11), where ※Σqt(xt) is the amount ofgroundwater.
𝐾𝑡𝐾
𝑥𝑡 = { 𝑡 } + {𝑣𝑡 }𝜆𝑒𝑡0※𝐾𝑡 = ln(𝑘𝑡 )(10)𝑦𝑡 = ℎ𝑡 (𝑥𝑡 ) + 𝑤𝑡 = ∑ 𝑞𝑡 (𝑥𝑡 ) + 𝑤𝑡

(11)Consideration of two-dimensional flow
To consider two-dimensional flow with verticaldirection, it was necessary to carry out twodimensional seepage flow analysis. Herein, an
equation (Nishigaki Formula) has been proposed toallow for two-dimensional flow (horizontal andvertical). In this study, this equation was verified as
equivalent to two-dimensional FEM analysis. In (12)and (13), q(t) is the amount of groundwater inflow to
the tunnel for each slice volume, and R(t) is the range
of influence (where the groundwater level is lowered
as a result of tunnel excavation) for each slice volume.
1

𝑘 2
ℎ𝑜 2
R(t) = 1.22 [( ) − 1] 𝐻𝑜 [1 − ( ) ]𝜀𝐻𝑜𝑘 −0.35
0.72𝐻𝑜−1 𝑘(𝐻𝑜2 −ℎ𝑜2 ) ( )𝜀q(t) =The state space model is updated when theobservation values are obtained, and the parameters
are estimated using the maximum likelihood method.

1
6𝜀𝑡
2
−
[1 − 𝑒 𝜆𝑒(𝐻𝑜 −ℎ𝑜 ) ]ANALYTICAL METHOD

(12)

(13)

Consideration of three-dimensional flow

In this study, in order to verify how the error
caused by the difference in the flow dimension in the
SDA-SWING method affected identification of
hydraulic conductivity by the EnKF, we considered
comparison a using the following three analyses.
(a) SWING method: quasi-uniform flow
(horizontal)(b) Two-dimensional: two-dimensional flow
(horizontal and vertical)(c) Three-dimensional: three-dimensional flow
(horizontal, vertical and depth)
The Bear formula, which is the basic equation of
the SWING method, is a formula for the area ofinfluence associated with tunnel excavation.

Quasi-two and quasi-three dimensional analysis
methods
The SWING method considers horizontal flow,
while the Nishigaki Formula considers horizontal andvertical flows. In order to consider three-dimensional
flow, it is necessary to consider the groundwater level
lowering in front of the tunnel face. The R(t) occurs
in each slice in front of the face, and it is necessary to
add the amount of groundwater in this range, applying
the assumption that the water level reduction range infront of the face is equivalent to the horizontal
direction.

578

SEE - Bangkok, Thailand, Nov.11-13, 2019using each method, and then compared the error
caused by the differences in flow dimensions. For thisexercise, we made λe and ε constant, according to theassumptions previously described.
ANALYTICAL RESULTS
The calculation results from each method
described above were compared, in order to evaluate
the error caused by the differences in the flow
dimensions. Figure 8 shows a comparison ofgroundwater inflow to the tunnel during the tunnel
excavation on day-50. Table 2 shows Q1, Q2 and Q5,
which are the maximum amounts of the slices 1, 2 and5, and k1, k2 and k5, which are the inverse analyses ofhydraulic conductivity from the other method, basedon the Q1, Q2 and Q5 achieved by three-dimensional
see-page flow analysis. For slice 1, groundwater
inflow tended to increase as the flow dimension
increased, in all cases. However, for slices 2 and 5,
groundwater inflow in Case 5 was similar to Case 1.
In order to verify the cause, Fig. 9 was prepared, andshows the groundwater level reduction in Case 5,
when slice 10 was excavated. Fig. 10 shows the rangeof groundwater level reduction in the unexcavatedsection, focusing on slice 1 and slice 2, and from this,it was seen that groundwater level reduction in theunexcavated section unexcavated section did notoccur just before slice 1 excavation. On the other
hand, in the excavation after slice 2, groundwaterlevel reduction was seen in the unexcavated section.
We thought that the groundwater level reduction
range would become larger, through excavation, andthat the amount of groundwater inflow after
excavation would be small. In the Case 2 and Case 4,
this effect is not take into account.

Fig. 6.
Groundwater level lowering in the frontof the tunnel face.
The three-dimensional seepage flow analysis method
This analysis doesn’t consider full threedimensional flow, so it is necessary to conduct threedimensional FEM analysis, as shown in Fig. 7. We
analyzed the amount of groundwater associated withtunnel excavation based on the Bear equation
assumption that it was equal to the well flow rate if awell had been excavated in slice units just above thetunnel.

Fig. 7.
Three-dimensional FEM analysis model(during slice 1 drilling).
ANALYTICAL CONDITIONS
We compared the groundwater inflow calculatedusing each method as drilling progressed, with theinverse analyzed hydraulic conductivity. The purposeof the study was to identify how flow dimension
differences affected EnKF processing, so we compared groundwater inflow using the parameters listed inTable 1. Based on the volume of groundwater inflow
calculated by three-dimensional seepage flow analysis, we conducted hydraulic conductivity inverse
Table. 1. Input parameters
Input data
ε: rainfall infiltration rate
k: stratum hydraulic conductivity
λe: porosity
Ho: initial groundwater level
ho: elevation above impermeable layer

Fig. 8.
method.

Value
5.0×10-8(m/s)
5.0×10-7(m/s)
0.1
30(m)
10(m)

Groundwater inflow predicted by each

As a result, it is considered that the amounts ofgroundwater inflow in Case 1 and Case 5 were closeto actual values, after slice 2. In Table 2, as a result of579

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table. 2.
Analysis step
Case

Formuladimensional

Analysis results
slice 1slice 2slice 5Q１ (m^3/d) k １ (m/s)

In(k １ ) Q2(m^3/d) k2(m/s)

In(k 2) Q5 (m^3/d) k 5 (m/s)

In(k 5 )Case1 SDA-SWING method

one

672.3 13.6×10^(-7)-5.87

876.0 5.1×10^(-7)-6.29

1253.4 3.6×10^(-7)

Case2 SDA-SWING method

quasis-two

911.4 7.1×10^(-7)-6.15

1151.4 3.0×10^(-7)-6.52

1583.9 2.4×10^(-7)-6.62

Case3 Nishigaki Formulatwo

964.8 6.4×10^(-7)-6.19

1257.1 2.9×10^(-7)-6.54

1798.8 2.2×10^(-7)-6.66

Case4 Nishigaki Formulaquasis-three1294.8 3.8×10^(-7)-6.42

1617.4 2.2×10^(-7)-6.66

2201.2 1.8×10^(-7)-6.74

Case5 Three-dimenisonal seepage flow analysis

three1136.5 5.0×10^(-7)
-7

-6.30

883.4 5.0×10^(-7)-6.30

1059.8 5.0×10^(-7)

-6.30

-6.44

※We set the hydraulic conductivity k=5.0×10 (m/s) when calculating Q1 , Q2 and Q5.
※We back calculated k1,k2, and k5 on the basis of Case 5’s Q1, Q2, and Q5.
performing EnKF processing, based on observation
data. In this study, we used one type of virtual tunnel.
It is necessary to confirm that similar outcomes canbe obtained in tunnels with different overhead
structure and hydraulic conductivity. Moreover, field
verification of our method in a real tunnel is very
important. Therefore, in the future, we intend to
improve the SDA-SWING method analysis accuracy,
and to filed-test the method.
Fig. 9.
Groundwater lowering range for Case 5(slice 10).

REFERENCES[1] Takahashi, K., Ohnishi, Y., Yasuda, T., and Xiong,J., Simplified seepage analysis system applied totunnel excavation for assessment of water inflow.
Proceedings of the Symposium on UndergroundSpace, Vol. 13, 2008, pp. 147- 150.
[2] Kogiso, J., Koyama T., Takahashi, K., Yasuda, T.,
and Ohnishi, Y., Development of SWING methodwith sequential data assimilation, Proceeding of
the Japan Society of Civil Engineers F1 (Tunnel
Engineering) Vol. 66, No. 1, 2012, pp. 9- 15.
[3] Bear, J., Dynamics of Fluid in Porous Media,
Dover Publications, 1998, pp. 420- 422.
[4] Nishigaki, M., Komatsu, M., Irie, Akira., Yano,K., and Ota, T., Simple Method for Predicting
Changes of Groundwater Caused by aConstruction of a Mountain Tunnel Digging and
its Applicability, Proceeding of the Japan Societyof Civil Engineers, No.778, Ⅲ-69, 2004, pp. 125137.
[5] Higuchi, T., Ueno, G., Nakano, S., Nakamura, K.,
and Yoshida, J., Introduction to Data
Assimilation-Simulation Technology for the Next
Generation, Asakura Shoten, 2011.
[6] Awaji, T., Kamachi, M., Ikeda, M., and Ishikawa,Y., Data Assimilation, Kyoto University, 2009, pp.
63- 92.
[7] Umeda, K., Yanagisawa, K., and Yoneda, S.,
Creation of hydraulic conductivity database forJapanese ground, Journal of Japan Society ofEngineering Geology, No.37, 1995, pp. 69- 77.
[8] Tomofumi K., Junya, K., Kenji, T., Toru, Y., andYuzo, O., Development of swing method withsequential data assimilation (SDA-SWING) and
its application to groundwater problems in realtunnel construction, Tunneling and UndergroundSpace Technology, No.28, 2012, pp. 229- 237.

Fig. 10.
Groundwater lowering range, focusing
on slices 1 and 2.
conductivity analysis in Case 1-5, the error caused by
the flow dimension difference of slice 1 became about
0.6, becoming 0.4 after slice 2. Generally, adifference <1 in the hydraulic conductivity wasconsidered very small. Considering EnKF processing,we concluded therefore, that the errors caused by the
analysis method differences converged at the initialstage of the excavation.
CONCLUSIONSIn this study, the error caused by flow dimension
difference in the SDA-SWING method was
acceptably small, when compared using analysis
methods that considered, two-dimensional and threedimensional flow, and the small difference convergedat the initial excavation stage in the analysis, when580

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE USE OF SAWDUST WASTE ON PHYSICAL PROPERTIES AND
THERMAL CONDUCTIVITY OF FIRED CLAY BRICK PRODUCTION
Nonthaphong Phonphuak1,2*, Anuwat Srisuwan3, Must Srila2, Siriwan Artbumrung2 and Panuwat Ruenruangrit1
1
Department of Engineering Management, Faculty of Engineering, Rajabhat Maha Sarakham University,
Maha Sarakham 44000, Thailand
2
Department of Industrial Technology, Faculty of Engineering, Rajabhat Maha Sarakham University,
Maha Sarakham 44000, Thailand
3
Faculty of Liberal Art and Science, Sisaket Rajabhat University, Muang, Sisaket 33000, Thailand

ABSTRACTIn this paper, the effects of incorporation of sawdust waste on the properties of fired clay bricks were
investigated. Clay bricks fabricated with 0, 2.5, 5, 7.5 and 10% by weight sawdust waste were tested. The clay
brick specimens were fired at 900, 1000 and 1100 °C to study for water absorption, bulk density, apparent porosityand compressive strength of the fired clay brick specimens were investigated. It was found that the use of sawdust
waste reduced the bulk density and compressive strength of the specimens. It was observed their apparent porosity
ratios up to 30% improved with increasing of sawdust waste up to 10% by weight fired at 900 oC. The compressive
strength of brick specimens with 2.5% by weight sawdust waste fired at 1100 oC were higher than the required
strength values as pre ASTM C62-13a with beneficial reduced density and increased apparent porosity. Thermal
conductivity of the porous fired clay brick specimens with 2.5-10% by weight sawdust waste produced at 1000 oC
compared to the fired clay brick specimens without additive, decreased from 0.47 to 0.22 W/mK. The results thus
showed that sawdust waste was a potential material for use as a pore former additive to raw clay-brick production.
Keywords: Physical properties, Clay brick, Pore forming, Thermal insulation, sawdust waste

INTRODUCTION

material will have a lower conductivity than the samematerial with solid body. The advantage andapplication of high porosity bricks are the lightweight structure and better thermal insulation [13][14]. Sawdust is a waste from the primary
woodworking and timber industry. As it possesses afiring capacity, it is normally used as a fuel source inthe thermal processes (biomass). The main chemicalcomponents of sawdust are; C (60.8%), H (5.2%), O(33.8%) and N (0.9%). Dry wood is primarily
composed of cellulose, lignin, hemicelluloses, andminor amounts (5-10%) of extraneous materials [15][8]. The sawdust waste can be incorporated in clay as
a pore-forming agent in clay brick technology.
Furthermore, such combined products give the fired
clay a more porous microstructure. Okunade (2008)
investigated the use of wood ash and sawdust as
admixtures in laterite-clay bricks. Sawdust (forburning out) and wood ash admixtures with ratio of
70:30 by weight laterite-clay were investigated. The
admixtures were added in various combinations ofproportions by volume (from 0 to 10%). This had
resulted in denser products with high compressive
strengths (with 0% sawdust and 10% wood ash), highsoftening coefficient, low water absorption rates, low
saturation coefficient, low abrasion index, especiallywith addition of wood ash admixture solely.
Conclusively, the results revealed that wood ash on
its own would also result in production of lightweight

One of the oldest construction materials is brick,and it continues to be one of the most popularbuilding materials because it is durable, easy tohandle, aesthetic in look, and inexpensive. Today,
clay bricks are still being used for the same purpose.
Fired clay brick should also contain high amount ofpores to give it a lighter weight and associated low
thermal conductivity [1]-[4]. New construction
materials with friendly environment are interested incurrent research. Therefore, the improvement of fired
clay bricks incorporating sawdust waste that is
especially the development approach [5], [6]. For
environmental
protection
andsustainable
development, a number of researchers haveinvestigated the use of waste materials to produce
clay bricks. A wide variety of waste materials havestudies, including sawdust, coal, coke, papermaking
sludge, grass and coconut shell, corn cob, rice husk,
and inorganic ones are polystyrene, perlite anddolomite or calcite [7]-[11]. Firing temperature is an
important factor in clay brick making industry. It
influences the mineralogical, textural and physicalformation of clay bricks [12]. The porosity of material
is a major factor influencing its thermal conductivity,
but no simple relationship can be formulated to cover
the complexity of various factor. Air is a very good
insulating material, so that a highly porous body
581

SEE - Bangkok, Thailand, Nov.11-13, 2019and more porous products [16]. In this research, theeffects due to the use of sawdust waste were
investigated in laboratory and the firing behavior,
physical properties and thermal conductivity of fired
clay bricks were discussed.

Table 1 Chemical compositions of clay body.
Oxide content
SiO2
Al2O3
Fe2O3
CaO
K2O
Na2O
P 2O 5
TiO2
MnO
MgO
LOI
(Loss on ignition)

EXPERIMENTAL
Characterization of raw materials
The clay body is taken from one of the local
plants. The average particle size distribution of clay
body was analysed by diffraction (Mastersizer
2000+Hydro2000 MU, Melvern Instrument Ltd, UK),
the average particle size distribution of 1 to 200 µm,
with D [4,3] of 14.91 µm (Figure 1). The
mineralogical composition of clay body was achieved
using an X-ray diffractometer technique (XRD: X’
Pert PRO MPD, Philips, Netherland). The major
crystalline phases found in clay body were quartz,
muscovite, rutile and hematite (Figure 2). Chemical
analysis of the clay was carried out using X-ray
fluorescence (XRF) elemental analysis spectrometer(Horiba Mesa-500 w). Chemical compositions of clay
body are given in Table 1.

Clay body (wt.%)
58.76
21.34
5.10
0.21
3.10
0.93
1.18
8.74

Preparation of brick specimens
In order to determine the extent of thepore-forming effect of the use sawdust waste,
additive was dry sieved through No. 45 mesh andfinally the sawdust waste particle sizes was obtainedin the range of 0.5 to 1.0 mm. Then, they were added
in to the raw-brick clay body in different proportions(0, 2.5, 5, 7.5 and 10% by weight), for specimens ofinternal dimension of 14 cm x 6.5 cm x 4.0 cm weremolded with hand. Specimens were dried at 110 oC
for 24 hrs then, fired at 900, 1000 and 1100 oC(soaking time of 30 min).
Fired shrinkage was measured inaccordance with the standard ASTM C326-09 [17].
The water absorption, bulk density and apparent
porosity of brick specimens were tested using theArchimedes method in accordance with ASTM
C373-14a [18]. The mechanical strengths of fired
clay bricks were measured using the methods
specified in ASTM C773-88 [19] and a digital camera
was used to study the surface texture of fired clay
bricks. Thermal conductivity measurement test was
conducted according to an adapted experimental
procedure of international standards ASTM C177-97[20]. The thermal conductivity was calculated byusing the following equation:

Fig. 1 Particle size distribution of clay body.

dq
dT
=k
dA
dx

(1)

Where q is the rate heat flow in direction normal tosurface (W), k is the thermal conductivity (W/m K),
A is the surface area (m2), dT is the temperature
difference, the thickness (K) and dx are the distancemeasured normal to surface (m). Fired brickspecimens mixed with increasing amount of sawdust
waste 0%, 2.5%, 5.0%, 7.5% and 10%. All specimens
were fired at 1000 oC with the size of 30 cm wide, 30
cm long and 25 mm thick for the measurement ofthermal conductivity respectively.

Fig. 2 XRD pattern of clay body.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

RESULTS AND DISCUSSION

the water absorption in the brick body [21].
According to Figure 3c, it could be seen that the water
absorption slightly increased when sawdust waste
increased in the range of 12.3-22.5%. In the part ofdifferent firing temperatures, it was found that water
absorption of clay bricks decreased with increasing
firing temperature where the bricks got stronger.
Reduction in water absorption rate in brick structureassociated with an increase in compressive strength[22], [23]. The control specimens without sawdust
waste addition had comparable water absorption of
10.8-14.5%. The results of water absorption normallyconfirmed with the results of porosity.
Apparent Porosity
Apparent porosity is an importantcharacteristic of fired clay brick and related to thecapacity of water absorption [22]. The high porosityof clay brick affected on the reduction of thermal
conductivity that is required for insulating materials.
The study results that fired clay bricks showedvarious apparent porosity depending on the amount ofsawdust waste addition. The highest porosity was
about 32.40% for 10% sawdust waste addition after
fired at 900 oC. The lowest porosity of 22.80% was
obtained in the bricks containing 2.5% sawdust waste
and fired at 1100 oC, as shown in Figure 3d. Thus,
porosity in fired clay bricks was caused when sawdust
waste addition was burnt out during firing process.
Therefore, the higher the amount of sawdust waste inclay brick, the higher the open porosity and hence themore porous clay brick as a result.

Firing Shrinkage
Firing shrinkage of clay bricks occurred dueto the loss of water from clay structure during firing
process. Clay particles were then moved closer that
affected on higher shrinkage [3], [8]. However, thedegree of shrinkage could be controlled by firing
process. Figure. 3(a) shows the firing shrinkage ofclay bricks with sawdust waste additions after fired at900-1100 oC. In firing factor, shrinkage was increased
with higher firing temperature because of theelimination of the pores. It was observed that thefiring shrinkage tended to increase with increasing
amount of sawdust waste in clay mixture at the same
temperature. This was explained that carbon phase
was eliminated from sawdust residues structure,
leading to high driving force to improve surface area
during firing process. In general, an increase in firing
shrinkage. Generally, a good quality of fired clay
bricks exhibits shrinkage below 8% [11]. The results
showed that the firing shrinkage occurred in the fired
clay brick was in the range of 4.27-7.31% and were
within the limit of ASTM standard C62-13a. The
control samples without any sawdust waste addition
had comparable firing shrinkage of 4.72-6.36%.
Bulk Density
The bulk density of fired clay bricks is an
important parameter on the performance of the fired
clay bricks. This is beneficial in terms of reduction of
the overall dead load and the improvement of thermal
behavior of structure. As the bulk density of clay
bricks decreases, its strength also decreases, while its
water absorption increases. In this study, the bulk
density of fired clay bricks was inversely proportion
to the quantity of sawdust waste added in the mixture.
The bulk density of clay bricks was decreased withincreasing sawdust waste content in the clay bricks.
This behavior was associated some generated pores
from sawdust waste combustion could not be
eliminated in clay structure. The results indicated thatthe values of bulk density of specimens containing
sawdust waste varied from 1.41 to 1.83 g/cm3 (Figure.
3b). The bulk density is related to durability and water
absorption characteristics of clay bricks. The highbulk density indicated the denseness of the clay brickwith usually increased durability and reduced water
absorption.
Water Absorption
The durability of clay brick is related to thewater absorption of clay brick. The durability of clay
brick can be reduced when the brick absorbs water. It
is important that the brick should be dense to reduce

Fig. 3 Physical properties of fired clay brick fired at
900 to 1100 oC: (a) firing shrinkage, (b) bulk density,(c) water absorption and (d) apparent porosity.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

porosity of brick has the advantage in the lightweightand improved thermal conductivity.

Paper Submission Method and CopyrightFig. 4 Compressive strength of fired clay bricks.

Thermal conductivity (W/mK)

Thermal Conductivity of Fired Clay Bricks
The thermal conductivity analyzed was
performed on fired clay bricks mixed with sawdust
waste 0 to 10% by weight and fired at 1000 oC, as
shown in figure 5. The results showed that higher
percentages of sawdust waste (10% by weight)
induced low thermal conductivity to the specimens.
From the results, it could be explained that thermal
conductivity decreased with a decrease in density andincreased with an increase in fired clay bricks
porosity. It was shown that the thermal conductivity
was directly proportional to the density of the fired
clay bricks. An understanding of conduction process
indicated that the determining factor was porosity
which was related to density.

Fig. 3 (continued).
Compressive Strength
The compressive strength of clay brick is themost important engineering-quality index forbuilding materials [22]. According to ASTM C6213a, the Grade MW bricks must have minimum
compressive strength of 17.2 MPa [24]. In this study,
the compressive strength of specimens fired at 900 to1100 oC by varied sawdust waste in different
compositions, as shown in figure 4. With increasing
firing temperature, the strength of the bricks
increased due to a decrease in porosity and anincrease in density. The results showed that thecompressive strengths of the specimens varied from4.35 to 18.2 MPa with corresponding 2.5 to 10 wt.%
sawdust waste. The results in figure 5 showed thatbricks with 2.5 % sawdust waste fired at 1100 ºC had
adequate strength of 18.2 MPa compared to 17.2 MPa
as required by ASTM standard. Moreover, high

0.50
0.40
0.30
0.20

0.10
0.00
0.0

2.5

5.0

7.5

10.0

12.5

Sawdust addition (wt%)
Fig. 5 Thermal conductivity of fired clay bricks at
1000 oC
Surface Texture of Fired Clay Bricks
Surface texture of fired clay bricks with 2.5,
5, 7.5 and 10 wt% sawdust waste are presented infigure 6. The fired clay bricks specimens with
sawdust waste contained visible pores when fired
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SEE - Bangkok, Thailand, Nov.11-13, 2019from 900 to 1100 oC. The results revealed the effectof mixing sawdust waste on the fired clay brickspecimens which can be seen in the cross-section aview. The results correlated well with the water
absorption, porosity and density of the fired clay
brick. The fired clay bricks with high content ofsawdust waste also showed high level of visible
pores. Beside the firing method, the chemicalcomposition of clay and the firing temperature also
affected with the color of fired clay bricks. The colorof fired clay bricks also became darker with theincreasing firing temperature. In our study, the bricks
fired at high temperature (1000 and 1100 °C) werereddish-brown caused of iron oxide. The compressive
strength of the fired clay bricks was reduced with theincrease in the sawdust waste content due to theincreased porosity. However, the compressive
strength was also found to increase with firing
temperatures. The increase in firing temperature from1000 to 1100 oC substantially increases thecompressive strength of fired clay bricks.

ACKNOWLEDGMENTS
The authors also would like to acknowledge
the financial supports from Rajabhat Maha Sarakham
University.
REFERENCES[1] Duggal, S.K., Building materials, 3rd revised ed.
New Age International (P) Ltd., Publishers. 2008,
pp.1.
[2] Phonphuak, N. and Chindaprasirt, P., Types ofwaste, properties and durability of pore forming
waste-based fired masonry bricks 1st End,
Woodhead Publishing, 2014, pp, 103-127.
[3] Karaman, S., Gunal, H. and Ersahin, S.,
Quantitative analysis of pumice effect on somephysical and mechanical properties of clay bricks.
Appl. Clay Sci. Vol.8(7), 2008, pp. 1340-1345.
[4] Madurwar, M.V. Ralegaonkar, R.V. andMandavgane, S.A., Application of agro-waste forsustainable construction materials: A review,Const. Build. Mat., Vol.38, 2013, pp.872-878.
[5] Bories, C., Borredon, M.E. and Vedrenne, E.,
Development of eco-friendly porous fired clay
bricks using pore-forming agent: A review, J. ofEnviron. Manag. Vol.143, 2014, pp.168-196.
[6] Algin, H.M. and Turgut, P., Cotton and limestone
powder wastes as brick material, Const. Build.
Mat., Vol.22, 2008, pp.1074-1080.
[7] Kazmi, S.M.S., Abbas, S., Saleem, M.A., Munir,
M.J. and Khitab, A., Manufacturing of sustainable
clay brick: Utilization of waste sugarcane bagasse
and rice husk ashes, Const. Build. Mat., Vol.120,
2016, pp.29-41.
[8] Eliche-Quesada, D., Corpas-Iglesias, F.A., PérezVillarejo, L. and Iglesias-Godino, F.J., Recyclingof sawdust, spent earth from oil filtration,
compost and marble residues for brickmanufacturing, Const. Build. Mat., Vol.34, 2012,
pp.275-284.
[9] Al-Fakih, A., Mohammed, B.S., Liew, M.S. andNikbakht, E., Incorpoation of waste materials in
the manufacture of masonry bricks: An update
review, J of Build. Eng., Vol.21, 2019, pp.37-54.
[10] Zhang, L., Production of bricks from wastematerials – A review, Const. Build. Mat., Vol.47,
2013, pp.643-655.
[11] Phonphuak, N. and Thiansem, S., Using charcoal
to increase properties and durability of fired test
briquettes, Const. Build. Mat., Vol.29, 2012,
pp.612-618.
[12] Mansaray, K.G. and Ghaly, A.E., Physical andthermochemical properties of rice husk. Energy
Sources Part A: Recovery Utilization andEnvironmental Effects, Vol.19, 1998, pp.9891004.
[13] Ganesan, K., Rajagopa,l K. and Thangavel, K.,
Evaluation of bagasse ash as supplementary

Fig. 6 Surface texture of fired clay bricks specimens
fired at 900 to 1100 oC with different percentages ofsawdust waste.
CONCLUSIONSIn conclusion, the results showed that sawdust
waste could be used as pore forming additive inmaking fired clay bricks. The results indicated thatthe addition of sawdust waste does have a reduction
effect on compressive strength. However, goodstrength bricks which meet the ASTM strength
requirement of 17.2 MPa could be obtained with 2.5% sawdust waste fired at 1100 ºC. The sawdust waste-clay bricks had lower density due to the pore forming
characteristics of sawdust waste when compared tothe control bricks without sawdust waste. The more
porosity is the more thermal performance. Thermal
conductivity of the porous fired clay brick specimens
with 2.5-10% by weight sawdust waste produced at1000 oC compared to the fired clay brick specimens
without additive, decreased from 0.47 to 0.22 W/mK.
Consequently, these clay bricks produced withaddition of sawdust waste can be used as a heatinsulation building materials. The reduced density
was the added beneficial property of fired clay andlightweight bricks.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

cementitious material. Cem. Concr. Comp,Vol.29, 2007, pp.515-524.
[14] Phonphuak. N. and Chindaprasirt, P.,
Utilization of sugarcane bagasse ash to improve
properties of fired clay brick. Chiang Mai J of
Sci, Vol.45(4), 2018, pp.1855-1862.
[15] Horisawa, S., Sunagawa, M., Tamai, Y.,
Matsuoka, Y., Tohru Miura, T. and Terazawa, M.,
Biodegradation of nonlignocellulosic substances
II: physical and chemical properties of sawdust
before and after use as artificial soil. J. Wood. Sci,
Vol.45, 1999, pp.492-497.
[16] Okunade, E.A., The effect of wood ash andsawdust admixtures on the engineering propertiesof a burnt laterite-clay brick, J of Eng. Appl. Sci.
Vol.8, 2008, pp.1042- 1048.
[17] ASTM C326-09., Standard Test Method for
Drying and Firing Shrinkages of Ceramic
Whiteware
Clays,
West
Conshohocken,
Pennsylvania. ASTM Book of Standards. Vol.
15.02., 2014.
[18] ASTM C373-14a., Standard Test Method for
Water Absorption, Bulk Density, Apparent
Porosity, and Apparent Specific Gravity of Fired
Whiteware Products, Ceramic Tiles, and Glass
Tiles, West Conshohocken, Pennsylvania. ASTM
Book of Standards. Vol. 15.02., 2014.
[19] ASTM C773-88., Standard Test Method forCompressive (Crushing) Strength of Fired

Whiteware Materials, West Conshohocken,
Pennsylvania. ASTM Book of Standards. Vol.
15.02., 2011.
[20] ASTM C177-97., Standard test method forsteady-state heat flux measurements and thermaltransmission properties by means of the guardedhot-plate apparatus. West Conshohocken,
Pennsylvania. ASTM Book of standard. Vol.
04.06., 2000.
[21] Demir, I., Reuse of waste glass in building brickproduction, Waste. Manag. Res., Vol.27, 2009,
pp.572-577.
[22] Phonphuak, N., Kanyakam, S. and Chindaprasirt,
P., Utilization of waste glass to enhancephysical-mechanical properties of fired clay
brick, J of Cleaner. Prod., Vol. 112, 2016, pp.
3057-3062.
[23] Görhan, G. and Şimşek, O., Porous clay bricks
manufactured with rice husks, Const. Build. Mat.,
Vol.40, 2013, pp.390–396.
[24] ASTM C62-13a., Standard Specification for
Building Brick (Solid Masonry Units Made From
Clay or Shale), West Conshohocken,
Pennsylvania. ASTM Book of Standards. Vol.
04.05., 2013.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE VERIFICATION OF DIFFERENCE ANALYSIS IN THE HIGHPRECISION INSPECTION TECHNOLOGY FOR SLOPE SURFACE,
USING MOBILE MAPPING SYSTEM
Naoto Samori1, Satoshi Nishiyama2, Koki Sakita3, Michinari Fuziki4, Naoya Ono5 and Junsheng Song6
1
Faculty of environmental science and technology, Okayama University, Japan,
2,3Graduate school of environmental and life science, Okayama University, Japan,
4,5
Kokusai Kogyo Co.,Ltd, Japan,
6
Disaster prevention research institute, School of mechanics and civil engineering,
China University of mining and technology, Beijing. China

ABSTRACTIn recent years, deterioration of road slope has become a problem and deterioration monitoring of road slope
is required. However, it is challenging how to maintain road slope efficiently for local governments because they
don’t have enough civil engineers or financial resources sometimes. ICP (Iterative Closest Points) which isdifference analysis method was tried to verify in the road slope monitoring using MMS (Mobile Mapping System).
ICP, difference analysis method can quantify the deformation of road slope from group points data image. MMS
is a system vehicle equipped with GNSS, IMU, digital camera, laser scanner and trip odometer. MMS can get laser
point cloud data, surrounding image of 360 degrees and spot image. Road slope where there is potential bulging
was monitored by MMS, and the road slope was set to force displacement by setting 10mm~ thick sheet on theslope or chipping the surface of the slope wall. At a result, accuracy of ICP method by using MMS seemed to begood and the monitored slope has confirmed that there is no deformation which is more than 1cm this time.
Keywords: Road slope, MMS, ICP, Difference analysis

In the first verification process, the accuracy of
the analysis method was checked. In the second
verification, it was determined if there was a
deformation of the slope between two periods.

INTRODUCTION
Japan has experienced a period of high economic
growth in the last 40 to 50 years during which large
number of roads were constructed. However, atpresent, the aging of these structures poses a
significant problem. Although regular inspection iscarried out once in every five years, the inspection
rate of the monitored structures is less than 50%.
Therefore, this study focuses on the issue of
deterioration of the slope of road structures.
Although several inspection points are consideredin the existing inspection method of road slopes,
visual inspection throughout the entire road slope
must be performed. Furthermore, in Japan, it isdifficult to efficiently check, maintain, and manage
these structures due to the shortage of engineers andlack of financial resources in the local governments.
At present, techniques using laser measurement
equipment are gaining importance, and methods ofquantifying the displacement and deformation by
point cloud analysis are necessary for the
maintenance and management of structures. In thisstudy, to increase efficiency and to quantify theinspection of road slopes, the MMS and a difference
analysis method conducted two verifications
processes. It was verified whether the analysis
method for slope monitoring using the MMS waspractically feasible.

Fig.1 Photograph of slope observation using the
MMS
METHODS OF STUDY
The MMS, difference analysis method, andequipment used in this study are described below.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Mobile Mapping System(MMS)The MMS is a vehicle equipped with a global
navigation satellite system (GNSS), inertial
measurement unit (IMU), digital camera, laser
scanner, and odometer. Using this vehicle, thepositions and orientations of the vehicle can be
determined, and point cloud data (Fig. 2), of all thesurrounding images, and spot images can be acquired.
The point cloud data is a three-dimensional dataof the topography and shape around the road having
coordinates X, Y, and Z (H). By comparing the firstand second periods of this data, it is possible toquantitatively determine the deformations andfluctuations between the two periods.

Fig.2

Fig.3

Simplified diagram of ICP analysis

Equipment Used for Verification
In the verification processes, they were used, the
MMS equipped with a laser scanner, GNSS receiver,an odometer, IMU, and eight spot cameras (Figs. 4
and 5). This laser scanner was not permeability type,and scans one million points per second by phasedifference type. In addition, in the second verification,
they were used, total station (TS), a stationary laser
scanner for obtaining point cloud data as true values.
The TS is a phase difference type scanner, withapproximately 30million acquisition points.

Reference image of 3D point cloud data

The MMS does not require a large number ofinspectors, but only one driver, to acquire and survey
the point cloud data, and it can be used even if thevolume of traffic is large on the road in front of theslope. It is a measurement technology that is expectedtoreplace conventional maintenance andmanagement of the road.

Fig.4

State of the MMS used in the study (1)Fig.5State of the MMS used in the study (2)Difference Analysis
The difference analysis method applies a point
cloud matching algorithm, known as the ICP.
ICP uses the point cloud data of two periods
acquired by laser scanners and digital cameras,
divides them into meshes of a certain size, andassociates the points in the mesh that minimize thedistance between the first and second period points.
By repeating the rotational and parallel movements,
the position where the corresponding point group of
the two periods matches the most is calculated. This
process is repeated to estimate the position where thetwo points match the most. A displacement vector issubsequently determined using which the data of thesecond period comes closest to first period, and thedisplacement can be obtained (Fig.3).
The difference analysis method using the ICP was
utilized in the present study as it was expected toquantify the displacement and deformation of the 3D
point cloud data obtained by the MMS.

METHODS OF VERIFICATIONThe objective of conducting the two verifications
processes is to verify the analysis method for slope
monitoring using the MMS was practically feasible.
The two verifications were conducted in thefollowing manner.
Verification 1 checked the accuracy of theanalysis method by either placing sheets or dropping
off slope on the slope, causing forced displacement,
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SEE - Bangkok, Thailand, Nov.11-13, 2019

and thereafter analyzing the same.
Verification 2 ascertained whether monitoring of
the slope could be performed by acquiring the point
cloud data of the slope the first and second periods by
the MMS, and analyzing the data obtained whether
the slope in the two periods could be monitored.
Verification 1: “Accuracy Verification”
It was verified that the accuracy of the method bydetermining the deformation when displacement is
forcibly caused to the slope with the possibility ofbulging (Fig. 6). The first measurement period was
January 12, 2018, and the second measurement period
was May 28, 2018. It has not given the slope
deformation in the first period. In the second period,
as shown in Fig. 7, it has not given any deformation
to 1. In 2, it has given the slope a dropping off
approximately 40 mm deep. In 3 and 4, sheets ofthicknesses 10mm and 20mm were installed,respectively. Each of the sheets had an area of 50 mm2

Fig.6

3

2

The map around the slope and surveying
coordinate system

Verification 2: “Slope Monitoring”
This verification process was monitored on thesame slope that was considered during verification 1(Fig. 6).
The survey conditions were also the same as inverification 1. We checked the possibility ofmonitoring the slope using this method by conducting
the following teat:4.
The first test compared the point cloud data of thetargets placed on the slope in the first and second
periods obtained by the TS, and investigated whether
the slope was actually changing.
The second test compared the data obtained by theTS with that obtained by the MMS at the same time,i.e., we determined the difference between the true
data by the TS and that data obtained by the MMS.
The third test compared the data obtained by theTS with that obtained from the MMS at the same time.
The data of the second test were adjusted. Based on
this comparison, there was an improvement in theaccuracy due to the adjustment calculation.
Finally, the fourth test compared the adjustment
calculated data obtained from the MMS in the firstand second periods. The results of the fourth and firsttests were then compared to verify if they agreed witheach other.

Slope to be verified and road
4

Fig.7

Fig.8

1

Forced deformation given to slope

For the survey by the MMS, the car with the MMS
ran in the lane marked in red in Fig. 6, at a speed 50
km/h to obtain high density data with few missing 3D
point cloud data. To improve the self-position
accuracy of the MMS, the survey was conducted attime when the dilution of precision (DOP), of satellite
arrangement) was good, i.e., less than 2.
The method of drawing the analysis results isshown in Fig. 8. The Y-axis component which is
generally in the direction across the slope was
extracted from the displacement vector of each meshobtained by comparison by the ICP method twice.
The method was adopted that is able to visualize thepresence or absence of displacement such as bulging
of the slope, peelings, or floating.

First Test “Comparison for examining slope
deformation”
This verification process used targets for the
purpose of assessment. The targets point cloud data
were obtained for each of the first and second periodsby the TS.
As there are fewer sources of error for data by theTS than for that by the MMS, the former wereassumed to be the true values. Therefore, when there
was a change in the data obtained by the TS between
the first and second periods, it could be seen that the589

SEE - Bangkok, Thailand, Nov.11-13, 2019

slope was actually changing.
In this test, the target was measured with reference
point T1 (Fig. 8). The installation method of T1 wasa GNSS surveying machine where static surveying
was performed for 2 h near both ends of the slope (K1,K2 in Fig. 8) and a reference point was installed.
Subsequently, the position of T1 was observed by the
backward intersection. The point cloud of the target
was obtained from T1 by the radiation method, andwe tried to reduce the error by counter-observation.
A total of eight targets were set for this test as
shown in Fig. 9. At the same time, 6 displacement
verification points were set up.

Fig.9

The point cloud data obtained by the MMS in thefirst and second periods that was calculated for
adjustment was subjected to a difference analysis. It
was verified that the state of the change would be thesame as in the first test which is the true value.
VERIFICATION RESULTS
Verification 1: “Accuracy Verification”
A difference analysis was performed on the point
cloud data between two periods, and the data wascompared. The results are shown in Fig 10.
At point 1, no displacement is observed, as forced
displacement was not given during the second period.
On the other hand, there was a displacement at point
2 (shown blue in the figure). This is because in thesecond period, the slope was dropped off and wasgiven a negative displacement. As a result of this
dropping off, a maximum displacement of about 40
mm occurred, it appeared to be approximately 40 mm(Fig. 10) where the negative displacement was large.
Therefore, it is observed that the displacement was
accurately extracted. In places where sheets ofthickness 10 mm and 20 mm were installed at 3 and4, respectively, the displacement was observed inplaces where the sheets were installed in the samemanner as that of 2. The result clearly confirmed thechange in the forced displacement point, whereas theother minute displacements were ignored andconsidered that the difference analysis method
confirms a negative displacement of approximately
40 mm and positive displacement of approximately
20 mm.

State of target setting

Second Test “Comparison for absolute accuracy
verification”
In this test, the point cloud data of the TS target
obtained in first test were assumed to be true values,and compared with the point cloud data obtained by
the MMS which was not calculated for adjustment
and the difference was determined. Based on thisdifference, the adjustment calculations were added tothe point cloud data obtained by the MMS, and thethird test was performed.

4

3

2

1

Third Test “Comparison for improvement of absoluteaccuracy”
Fig.10 Comparison of forced displacement given toslope, (unit: m)

Based on the true values obtained by the TS
survey of the first and second tests, the data obtainedby the MMS were compared with the values given by
the adjustment calculations. This test improved theabsolute accuracy obtained in the second test.
The accuracy of adjustment calculations wasverified by using two methods: The first method wasa conventional method that performed adjustment
calculations by using the features on the groundsurface such as white lines or curbs, for localization.
The second method was by placing a target placed on
the slope for localization. These two methods werecompared to improve the absolute accuracy.

Verification 2: “Slope monitoring”
First Test “Comparison for examining slope
deformation”
The results of the comparison of the data obtainedby the TS in the first and second periods were as
follows.
The absolute values of the coordinates of thetarget in each axial direction were 1 mm on anaverage, and the difference between the coordinatesof the verification point was 2 mm on an average, andthe difference between the coordinates of theverification point was 2 mm on an average in the X
direction, 0 mm in the Y direction, and 1 mm in the Z

Fourth Test “Two period comparison by difference
analysis method”

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SEE - Bangkok, Thailand, Nov.11-13, 2019

direction (Table. 1).

accuracy”

Table. 1 Comparison of the point cloud data obtainedby TS in the first and second period

The point cloud data obtained by the TS in the firsttest were compared with that obtained by the MMS
which was calculated for adjustment based on thesecond test.
As shown in the first test as a criterion forcomparison, the difference between the observationsin the first and second periods was dependent on theaccuracy of the machine, therefore, we assumed thatno significant change had occurred in the target. To
prevent the error accompanying the measurement, themeasured values obtained by the TS in the first period
were adopted as the true values in the second period.
Consequently, for accuracy in the position after
the adjustment calculations, the difference in thecoordinates when the target was used averages to0.001 m in the X, Y directions (horizontal direction
with respect to the ground) in the first period, Z
direction (height) The average was 0.001 m, in the X
and Y directions in the second period, and 0.001 m in
the Z direction. The difference in the coordinate
values when using one of the conventional features
was 0.035 m on an average in the X and Y directionsin the first period, 0.004 m in the Z direction, and
0.011 m on an average in the X and Y directions inthe second period. The difference was 0.008 m in the
Z direction (Table. 3).

Measured value
point name (TG)

2 period data - 1 period data
dx(m)

dy(m)

dxy(m)

dh(m)

TG01

-0.001-0.0010.001-0.002TG02-0.002-0.001

0.002-0.002

TG03

0.001

0.000

0.001

-0.002

TG04

0.001

0.003

0.003

-0.002

TG05

0.003

0.000

0.003

-0.001TG06-0.001

0.003

0.003

-0.002

TG07

0.001

0.000

0.001

0.000

TG08

0.003

0.003

0.004

0.001

ave

0.001

0.001

0.002

-0.001

σ

0.002

0.002

0.001

0.001

When the observation distance was 30 to 100 m,
the accuracy of the TS machine was 2 mm + 2 ppm *D (<± 2.2 mm) and the angle 3 was sec (<± 1 mm) inthe distance measurement, at the observation distanceof approximately 12 m. Therefore, the difference
between the two periods depends on the accuracy of
the TS machine, and there was no significant change
corresponding to the deformation. It was observedthat the surface of the subject did not change between
January 12, 2018 and May 28, 2018.

Table.3 Comparison of point cloud data obtained byadjusted MMS in the first period and point
cloud data obtained by TS (partial)

Second Test “Comparison for absolute accuracy
verification”

point name (TG)The point cloud data obtained by the TS in the firsttest was compared with that obtained by the MMS.
It was observed that the data obtained by the
MMS differ by a maximum value of 0.077 m, andminimum value of 0.001 m in the horizontal direction(dxy) and maximum value of 0.091 m, and minimum
value of 0.000 m in the vertical direction (dh), withrespect to the value measured by the TS. Thisdifference was less than 0.1 m (Table. 2). Andreached the accuracy of 0.15 m of the map
information level 500. Thus, it can be stated that theaccuracy of measurement by the MMS was generally
good.

Summary
Maximun value

0.077

Adjust using featuresdxy(m)

dy(m)

dh(m)

TG01

0.000

0.000

0.109

-0.002

TG03

0.000

0.000

0.098

0.000

TG04

0.000

0.000

0.102

0.013

TG05

0.000

0.000

0.089

0.001

TG06

0.000

-0.0010.089-0.009

TG07

0.000

0.000

0.085

0.003

TG08

0.000

0.001

0.085

0.002

ave

0.000

0.000

0.094

0.001

σ

0.000

0.001

0.009

0.006

It was observed that the accuracy of position after
the adjustment calculations improved in the method
when the target was used compared to the method
when the conventional features were used. Therefore,
the adjustment calculations were performed in our
method using the target.

Table.2 Comparison of point cloud data obtained by
MMS with that obtained by TS

dxy(m)

Adjust using TG
dx(m)Fourth Test “Two period comparison by difference
analysis method”

dh(m)
0.091

A variation in the slope was observed bycomparing the data of the first and second periods inwhich the adjustment calculations were added to the

Minimum value
0.001
0.000
Third Test “Comparison for improvement of absolute

591

SEE - Bangkok, Thailand, Nov.11-13, 2019

point cloud data obtained by the MMS by thedifference analysis method.

deformation of the slope between the two periods.
From the point cloud data of first test by the TS, it
was observed that the slope did not change, and fromthe point cloud data by the MMS after adjustment
calculations of the fourth test, it was established thatthe slope did not change. As the conditions of the firstand fourth tests were consistent, it was concluded that
this method could monitor the slopes that could be
judged quantitatively.
From the verification processes, it was confirmedthat the analysis method for slope monitoring by the
MMS was practically feasible.
In addition, the height of the slope wasapproximately 7 to 8.5 m in the verifications
processes, and the measurement distance from the
MMS to the present slope was almost 12 m. Although
it was possible to make measurements at the upper
part of the slope at a distance of almost 12 m from theslope, point cloud data cannot be obtained
perpendicular to the slope. The angle becomes steep,
the footprint of the point cloud data obtained becomeslarge, the quality of the data declines, and the numberof available point clouds decreases. For example, inthis survey, in the case of guard fences and targets,
point cloud data would be acquired at an angle ofalmost 60 degrees at a distance of approximately 15
m. As the conditions of measurements in the lower
and upper parts of the slope differ, the difficulty lies
in maintaining the accuracy of measurement by the
MMS.

Fig.11 Comparison of one or two seasons of MMS
data after adjustment calculation
The results are as shown in Fig. 11. The colored
portions indicate the parts where the slope wasdeformed. However, it to be noted that there wasvegetation, safety cones, and nets along the slope. The
appearance of the slope was considered to be local
noise, as the deformation appears locally. Thisanomaly was ignored this in this study. By ignoring
local anomalies, as well as not having widespread
anomaly on the slope, it was found that the present
slope changed by the point cloud data by MMS after
the adjustment calculation and the difference analysis
method.

ACKNOWLEDGMENT

CONCLUSION

This study was supported by KAKENHI(16K01329).

In this study, two verification processes wereconducted with the aim of establishing an analysis
method for slope monitoring using the MMS.

REFERENCES[1] Besl, P.J and McKay, N.D. (1992): A Method for
Registration of 3-D Shapes, IEEE Pattern Analysis
and Machine Intelligence, Vol.14, No. 2, pp. 239- 256.
[2] Is this good? Infrastructure Specialist, Necessary
things for infrastructure repaired period, Gyosei,
pp.130~132.
[3] Doctoral dissertation, Research on Rationalizationof Road Tunnel Inspection Method Utilizing
Traveling Measurement Technology, Takashi
Mizuguchi, 2017, pp.3-1~3-5.
[4] Accuracy verification of analysis method for slope
monitoring method using mobile measuring vehicle,
Koki Sakita, 2018.

Verification 1: “Accuracy Verification”
In this verification, the accuracy of the analysis
method used in this research was checked.
As a result of this verification, it was concluded
that displacement was confirmed when there waspositive displacement and negative displacement, andit was not confirmed when the displacement was not
given. Therefore, information regarded thedeformation could be extracted from the slope using
this method. In addition, the deformation wasdetermined to be approximately 40 mm for negative
displacement and 20 mm for positive displacement.
Verification 2: “Slope Monitoring”
In this verification, the slope monitoring process
was checked to confirm whether there could be a592

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

LESSON LEARNED IN MAINTAINING THE PRECAST CONCRETE
BUILDINGS
Zul-Atfi Ismail
Civil Engineering Program, School of Environmental Engineering, Universiti Malaysia Perlis, Malaysia

ABSTRACTThe contemporary practice of conventional methods in the Precast Concrete (PC) building maintenance entails
many issues due to poor service delivery and defect repetition. A key problem impeding the widespread adoptionof emerging technologies is the lack of competent contractor supporting the effectiveness of implemented
Information and Communication Technology (ICT) than conventional methods and the returns on investment. The
shortcomings of conventional methods are assessed from the perspective of PC buildings. Data were collected
through a case study of eight PC buildings from two type of design which were high-rise and complex building.
The conventional methods had significantly little emphasis on defect diagnosis tools. It had also increased theinadequate strategic decision making to analyse information in improving the maintenance project outcomes for
PC building. Building Information Modelling (BIM) tools is suggested from findings and lessons learned as a goodpractice to reduce the repetition of defect on the design specification used and construction practiced.
Keywords: Maintenance Management, Conventional Method, Maintenance Management System, Building
Information Modelling, Malaysian PC Building

database), which is commonly being conducted in asequential manner using CAFM and CMMS tools
replaced to new business model which integrates
various sources of data and knowledge such as
CMMS with the Building Information Modelling(BIM) of the PC building in the maintenanceactivities [2, 3, 4].

INTRODUCTION
Maintenance management is paramount inensuring the effective and efficient monitoringprocess of maintenance activities, and Information
and Communication Technology (ICT) could playfundamental role in delivering that maintenancemanagement. Precast Concrete (PC) building
maintenance depends on the design type (e.g.
complex and high-rise building), size and building
usability that require quality maintenance in order toachieve life-span prolongation. Structural repairing
practice in managing PC building maintenanceactivities has been a hot issue in recent years due tolack of progress in the area of computer-aided
maintenance management and difficulties withaccessing information and data in maintenancesupport systems such as Computerised MaintenanceManagement System (CMMS) and Computerised
Aided Facility Management (CAFM) [1]. Clients andcontractors should use the high-quality building
information from an emerging application ofcomputerbased technology during the maintenanceactivities of the PC building's lifecycle. In response to
the challenges of dynamic maintenance operations
and the need for improving the quality ofmaintenance process in complex and high-rise
structural building components, clients andcontractors could change their method fromconventional practices to more enabling technology
to increase productivity and a new level ofinteroperability and collaboration. The conventional
modus operandi (paper-based reports/unsystematic

Maintenance staff generally introduces ICT into
PC building maintenance management for providing
maintenance inspection records and results, including
checklists, specification, and maintenance procedureby using software such as CMMS and CAFM. The
CMMS and CAFM application provides various
paper-based reports (such as inventory confirmation)
related to maintenance and repair issues [3].
Furthermore, the traditional 2D Computer-Aided
Design (CAD) technology is widely used formaintenance information illustration and evenintegrating related data for PC building construction
design history purposes [5]. Despite the fact that theuse of ICT solutions in assessing, planning or process
execution takes place at a different scale and function,
the emerging trend such as using sophisticated or
innovative tools and techniques could improve
productivity in PC building maintenance activities
and have a great potential to redefine and re-engineer
the conventional setting. The conventional method(paper-based reports/unsystematic database) is lackof knowledge support in coordination, maintenancemonitoring, maintainability, automation and robot
control systems. The PC building maintenance has
different training or maintenance information to593

SEE - Bangkok, Thailand, Nov.11-13, 2019address the issue of defects for particular component
compared to the conventional building maintenance.
The connection of PC component such as by using
corbel and PCB need the expert knowledge toimprove the quality and reliability of PC scheme inorder to avoid any defect repetition in the long-termof life cycle building services. Failure to capture thedata acquisition and monitor the defects effectively
will influence the assessment process including
maintenance planning and execution. This cancontribute poor quality, productivity and performancein PC building construction projects [6, 7]. There isalso give problematic and inefficient in the handlingof information and integration of data of maintenancecomponents within a post-construction site activity[8].

the highest of IBS building maintenance projects in
Malaysia according to CIDB and almost are using
conventional method and inadequately use of modern
ICT tools. The number is considered very big
indicating that the use of modern ICT is still very
limited for PC system classification in IBS building
maintenance management in Malaysia. The adopted
synthesis of good practices of maintenance operations
is based on the findings of the interviews and casestudies conducted with professional engineers
working in PC building maintenance departments[15]. This paper is part of a larger research and will
only introduce and discuss the entire finding of thecase study. This finding is illustrated in the following
sections.
The interviews consisted of two types of PC
building, namely, “Residential” and “NonResidential”. The case study was based on eight cases(Case A-Case H) of PC buildings in Malaysia. There
were two case studies (Cases A and E) on“Residential” due to housing maintenance operationsuch as the Putrajaya Quarters. In addition, six morecase studies (Cases B, C, D, F, G and H) wereclassified as “Non-Residential” which manages themaintenance operation with fully equipped officebuildings. The interviews reached a saturated point
after the eighth interview session. The justifications
for the selected case studies were according to thefollowing main criteria: exposed to the conventional
method used and major problems, attempted to
implement computerised technology and thewillingness of staff to share their experiences in
improving the maintenance management processes at
the PC building. The differences between the types of
the PC building project provided an opportunity to
explore variations in maintenance management issues
for complex and high-rise PC building projects. The
type of PC building under study for maintenanceproject were all varied from Quarters to Integration
News Centre. The summary on the eight case studies
is presented in Table 1.

BIM FOR PC BUILDING MAINTENANCE
Recently on PC construction sites, there are manyefforts to improve the efficiency of maintenancemanagement activities through the use of more ICTbased systems (i.e. BIM). With the development ofemerging technology such as BIM, maintenancemanagement improvements in PC building
construction has become possible [9]. Several otherindustry projects worldwide, for example real estate,
waste management, transportation, supply chain andfacility management, have been successfullycompleted by implementing BIM technology [10, 11,12]. BIM can assist clients to determine theappropriate technology strategy and scope of eachdeliverable, with the intention of reducing
redundancy and rework while
improvingperformance and productivity of an operation andmaintenance processes effectively in the future [13,14]. Whereas BIM related studies mainly focus on
utilising sophisticated tool and efficient technique,associating decision making support in diagnosis
principles can help in achieving new levels of
efficiency in PC building maintenance performance.
CASE STUDY

Table 1 List of Case Studies
The case studies on the eight PC buildings were
undertaken in order to identify the maintenancemanagement problems, the current approaches toaddressing the problems, the ICT implementation,use of emerging technologies and the maintenancemanagement system (MMS) to obtain information
relating to the maintenance identification, assessment,planning and execution processes. Eight maintenanceclients/contractors are selected based on major
problems of using conventional method (paper-based
reports/unsystematic database) in the comparison toinvestigate the maintenance management practices ineach PC building. There are around 51 contractors ofIndustrialised Building System (IBS) building
maintenance from a classification of PC system haveInterviewee

A

Type of IBS
Building ProjectType of Building
Design of IBS
Building
Interviewee
Type of IBS
Building Project

Quarters

Type of Building

594

Residential
High-riseB
Malaysian Institute ofPharmaceuticals andNutraceuticals(IPHARM)
Non-Residential

SEE - Bangkok, Thailand, Nov.11-13, 2019

Design of IBS
Building
Interviewee
Type of IBS
Building ProjectType of Building
Design of IBS
Building
Interviewee
Type of IBS
Building ProjectType of Building
Design of IBS
Building
Interviewee
Type of IBS
Building ProjectType of Building
Design of IBS
Building
Interviewee
Type of IBS
Building ProjectType of Building
Design of IBS
Building
Interviewee
Type of IBS
Building ProjectType of Building
Design of IBS
Building
Interviewee
Type of IBS
Building ProjectType of Building
Design of IBS
Building

the approaches to address problems, ICT
implementation, use of emerging technologies
including the maintenance management system at the
selected PC building. The problems identified fromthe eight case studies revealed that each case study
experienced similar problems with defect repetition at
the specific component part of PC building and aresummarised and presented as below. The discussion
involves a cross-case analysis and has been grouped
into five main ‘embedded units of analysis’ identified
which are (1) Maintenance Management Problems,(2) Approaches to Address Problems, (3) ICT
Implementation, (4) Use of Emerging Technologies
and (5) Maintenance Management System.

High-riseC
National Youth Skills
Institute (IKBN)
Non-Residential
ComplexD
Anti-Corruption Agency
Office Complex andHousing
Non-Residential
Complex

Table 2 Cross-Case Analysis

E
Double Storey Super link
House
Residential
Complex

Case
Case AF
Inland Revenue Board Of
Malaysia Complex
Non-Residential
High-riseG
National Audit
Department Office
Non-Residential
Complex
H
Integration News Centre
Non-Residential
High-rise

The semi-structured interviews were conducted withthe engineers who were responsible for the
maintenance management of the entire PC’s building
structure under the Facility Management andDevelopment Unit (UPPF) and Maintenance andDevelopment Unit (UPS) including maintenancecontractor. The interview sessions took around five
hours to accumulate the data on the maintenanceprocesses including the demonstration of the current
maintenance management system with theimplementation of the ICT tools by the engineer. All
the data from the interviews were recorded using
video camera and transcribed verbatim.

Case BKEY FINDINGS

Case CThe eight case studies involved in this research wereto identify the maintenance management problems,
595

Element of Analysis: MaintenanceManagement Problems
Lack of commitment for handlingdefect-Report delay and undelivered-Unsystematic databaseLess competent contractor staff-Less engineer competency-Technician’s report is in generaldescription-Technician’s failure to identify defectproblem
Defects repetition (surface cracking,leaking, scaling and jointing)-Fault design
Poor quality work by contractor-Less material quality
Poor buildability (M&E coordination)-Lack coordination between design
and maintenance teamPoor maintainability-Unspecific accessibility to the defectlocation
Poor waterproofing-Poor maintenance method
Poor quality work by contractor-Low repair requirements of thestructure component
Lack of staff-Lack of supervision
Limited Budgets-Budget constraint
Defects repetition (surface cracking
and aircond belting)-Lack of technician-Less defect detection technologies
Less competent contractor staff-Less engineer/technician competency
Defects repetition (surface cracking,leaking and jointing)-Low quality design control

SEE - Bangkok, Thailand, Nov.11-13, 2019

Case D

Case E

Case F

Case G

Case H

Case
Case A

Case B

Surface cracks due to improper
jointing-Less quality of joint material
Deep cracks due to settlement-Less suitable soil
Less competent contractor staff-Less engineer/technician competency
Defects repetition (leaking andjointing)-Design performance for concrete
durability requirements-Structural installation method
Poor waterproofing-Poor installation of the waterproof
membranePoor quality work by contractor-Lack of uniform standard-Poor material quality
Less competent contractor staff-Less engineer/technician competency
Defects repetition (surface cracking,leaking and jointing)-Fault design-Poor material quality-Time gap of building repairs
Poor plumbing fitting-Plumbing installation method
Defects repetition (leaking andjointing)-Design performance for concrete
durability requirements
Less competent contractor staff-Less engineer/technician competency
Defects repetition (leaking, jointing
and overload current trip)-Fault design-Contractor ethics issues-Interested in
making profits
Defects repetition (heavy leaking)-Poor quality of design-Less technician competency
Deep cracking on structure-Limited experience by engineer-Poor maintenance method bycontractor
Less competent contractor staff-Less engineer/technician competency
Element of Analysis: Approaches toAddress Problem-Improve the maintenance assessment
for the building works did bycontractor-Provide more quality staff inmanaging the maintenance of critical
defect-To replace the conventional defectdetection method (e.g. visualinspection) with the sophisticated ICT
application (e.g. CMMS)

Case C

Case D
Case E
Case F
Case G

Case H

Case
Case A

Case B
Case C

Case D
Case E
Case F
Case G
Case H

Case
Case A
Case B
Case C
Case D
Case E
Case F
Case G
Case H
Case
Case A

596-Improve the maintenanceeffectiveness for the building works
did by contractor-Proper supervision of work for thebuilding works did by contractor-Improve the building control for thebuilding works did by main contractor-Critical plan on maintenance repairs-Conduct the maintenance assessment
for evaluating the building works
performance did by contractor-Conduct the maintenance assessment
for evaluating the building works
performance did by contractor
Element of Analysis: ICT
Implementation
mySPATA-Data inventory for
immobile facilities (e.g. building)
mySPA-Data inventory for mobile
facilities (e.g. furniture)
mySMS System-for managing
complaints-Conventional (e.g. MS Word, MS
Excel)mySPATA-Data inventory for
immobile facilities (e.g. building)
mySPA-Data inventory for mobile
facilities (e.g. furniture)-Conventional (e.g. MS Word, MS
Excel)-Conventional (e.g. MS Word, MS
Excel)-Conventional (e.g. MS Word, MS
Excel)-Conventional (e.g. MS Word, MS
Excel)
Building Automation System (BAS)-fordetected building's heating, ventilation
and air conditioning systems
Supervisory Control and Data
Acquisition System (SCADA)-to ensurethat the building systems (e.g. fire
alarm) were in good condition
E-Aduan-for managing complaints
Element of Analysis: Use of
Emerging Technologies
-No
-No
-No
-No
-No
-No
-No
-No
Element of Analysis: MaintenanceManagement System-Conventional (e.g. paper-based
reports/unsystematic database)SEE - Bangkok, Thailand, Nov.11-13, 2019

Case B
Case C
Case D
Case E
Case F
Case G
Case H

electrical control systems. As the overall results
indicated in Table 3, it was deemed necessary toanalyse the use of emerging technology further.
Therefore, the systematic system with the emerging
technology, defect diagnosis and decision making
process should be developed to improve the building
structure and facility performance by conducting
effective knowledge transfer on the structurecomponent maintenance defects.

-Conventional (e.g. paper-based
reports/unsystematic database)-Conventional (e.g. paper-based
reports/unsystematic database)-Conventional (e.g. paper-based
reports/unsystematic database)-Conventional (e.g. paper-based
reports/unsystematic database)-Conventional (e.g. paper-based
reports/unsystematic database)-Conventional (e.g. paper-based
reports/unsystematic database)-Conventional (e.g. paper-based
reports/unsystematic database)Table 3 Suggested Solutions from Case Studies
Case
A,B,C,D,F,G,H

SYNTHESIS OF GOOD PRACTICES

A,B,D,F,G,H

Table 3 below represents the suggested solutions
from the case studies to improve the current practices
on the maintenance management by implementing
three approaches at the PC building. Case A, B, C, D,
F, G and H suggested improving the transfer ofknowledge in the defect diagnosis by combining withthe related software technology such as CMMS and
CAD. In fact, the problem of knowledge transfer inthe defect diagnosis delivery also does affect the otherPC buildings to some extent and the significance of
this factor is quite obvious. The maintenancecontractors will use the inadequate knowledge tohandle the defect problem and less detail of the defectsource explanation to gather accuracy information
record for inspection and planning works. The othersuggestion from the client/contractor was to provide
the transfer of knowledge to improve the maintenancequality of structure and facility at the PC building(Case A, B, D, F, G and H). All the related cases arefacing the impact of problems for the quality
knowledge management, which are associated to thedefect repetition for handling the defect of structuresand facilities with IBS score usage about 70% on its
structure development of PC building.
Case C, D, E, F and G suggested on efficient
controlling of building performance based design andmonitoring the defect diagnostic operation inmaintenance through implementation of emerging
technology (BIM) on the PC building maintenance.
These are also recommended by Case A, B and H tointegrate the design/construction and maintenance’s
database in order to facilitate better decision support
and coordination within and across multiple field (e.g.
civil, mechanical and electrical) for effective
management of the PC building maintenance. Thissuggested solution is ranked as the most importantsolution due to suggest from almost case studies inorder to manage the large and critical maintenanceservices for the PC building structure and facility. The
using of emerging technology is also the lowest interms of existing practice for better managing PC
building components including mechanical and

A,B,C,D,E,F,G,H

Suggested Solutions
Provide more transfer ofknowledge in defectdiagnosis
Provide more transfer ofknowledge to improve themaintenance quality inmaintenance execution
Implementation of emerging
technology (BIM) (efficient
control of building
performance based design/monitor the defect diagnostic
operation in maintenance)

LESSON AND ENLIGHTMENTS
1) The PC building maintenance and theapplication of diagnosis techniques shouldbe paid highly attention. Because of thedefect repetition of structure components
and limitation of understanding about the PC
knowledge, the maintenance approach isvery important. The application of modern
ICT tools such as BIM integration can avoid
or alleviate the defect of critical structure.
2) The appropriate modern ICT tools should beselected in assessment areas (diagnosis anddecision making process on the design
specification used and construction
practiced) for PC buildings. The high-rise orcomplex structure should be given thepriority for these types of PC buildings.
3) The maintenance quality of PC buildings
should be strictly guaranteed.
4) The deficiency of PC buildings knowledge
affected the quality of competentmaintenance staff in Malaysia. The future
work should be strengthened to guarantee
the quality and knowledge in case of defectrepetition.
The repetition of defect was frequent at PC building.
The maintenance inspection and assessment was notable to address the building structure defect problems
at the particular location due to the less knowledgetransfer between all members in maintenance
597

SEE - Bangkok, Thailand, Nov.11-13, 2019

management. Furthermore, the less competentcontractor caused the maintenance faults to be
increased to encourage the deterioration of the IBS
building structure and facility.

Management Issues in IBS Commercial
Building. International Journal of Computer
Informatics & Technological Engineering, 1(1),42-46.
[5] Su, Y., Lee, Y. C., & Lin, Y. C. (2011).
Enhancing Maintenance Management using
Building Information Modeling in Facilities
Management. 2011 Proceedings of the 28th
International Symposium on Automation andRobotics in Construction (ISARC), IAARC,
Seoul, Korea, 752757.
[6] Vaha, P., Heikkila, T., Kilpelainen, P.,
Jarviluoma, M., & Gambao, E. (2013).
Extending
Automationof
Building
Construction-Survey on Potential Sensor
Technologies and Robotic Applications.
Automation in Construction, 36(2013), 168-178.
[7] Kamaruddin, S. S., Mohammad, M. F., Mahbub,
R., & Ahmad, K. (2013). Mechanisation andAutomation of the IBS Construction Approach:
A Malaysian Experience. Procedia Social and
Behavioral Sciences, 105(2013), 106-114.
[8] Babic, N. C., Podbreznik, P., & Rebolj, D.
(2010). Integrating Resource Production andConstruction using BIM. Automation inConstruction, 19(2010), 539-543.
[9] Nawari, N. O. (2012). BIM Standard in Off-Site
Construction.
JournalofArchitecturalEngineering, 18(2), 107-113.
[10] Cheng, J. C. P. & Ma, L. Y. H. (2013). A BIMbased System for Demolition and Renovation
Waste Estimation and Planning. Waste
Management, 33(2013), 1539-1551.
[11] Irizarry, J., Karan, E. P. & Jalaei, F. (2013).
Integrating BIM and GIS to Improve the Visual
Monitoring of Construction Supply Chain
Management. Automation in Construction,
31(2013), 241-254.
[12] Love, P. E. D., Matthews, J., Simpson, I., Hill, A.
& Olatunji, O. A. (2014). A Benefits Realization
Management Building Information Modeling
Framework for Asset Owners. Automation inConstruction, 37(2014), 1-10.
[13] Love, P. E. D., Simpson, I., Hill, A. & Standing,
C. (2013). From Justification to Evaluation:
Building Information Modeling for Asset
Owners. Automation in Construction, 35(2013),
208-216.
[14] Volk, R., Stengel, J. & Schultmann, F. (2014).
Building Information Modeling for Existing
Buildings-Literature Review and Future Needs.
Automation in Construction, 38(2014), 109-127.
[15] Ismail, Z., Mutalib, A. A., & Hamzah, N. (2016).
Case Study to Analyse Problems and Issues in
IBS Building Maintenance. International Journalof Applied Engineering Research, 11(1), 226232.

In this research, the frontline approaches (newsystem development with BIM) is intended to counterthe maintenance management problems on PC
building which are:a) Defect
repetition
information
andknowledge due to failure to identify theactual reason of structure defect;b) Defect repetition (leaking, jointing andcracking) information and knowledge due todesign defect; andc) Less competent contractor due to lack ofknowledge regarding with materials,
method and design of structure repair.
CONCLUSIONS
The data obtained in the case studies revealed that
the PC buildings are using the conventional method
such as paper-based reports in managing themaintenance processes for building structure andfacility. This arise a problematic situation such as
defects repetition (leaking, jointing and cracking) andpoor quality work by contractor that needsophisticated tools towards a solution. Presently, theimplementation of ICT tools in the new system is thebetter improvement to lead the tremendous saving inbudget, time planning and to receive the precise datain handling the defect diagnosis and control. The
suggestion for good practices was through theimplementation of BIM to reduce the repetition of
defect on the design specification used andconstruction practiced for the building structure andfacility.
REFERENCES[1] Duran, O. (2011). Computer-aided MaintenanceManagement Systems Selection based on a
Fuzzy AHP Approach. Advances in Engineering
Software, 42(2011), 821-829.
[2] Espindola, D. B., Fumagalli, L., Garetti, M.,
Pereira, C. E., Botelho, S. S. C., & Henriques, R.
V. (2013). A Model-based Approach for Data
Integration
toImprove
MaintenanceManagement by Mixed Reality. Computers in
Industry, 64(2013), 376-391.
[3] Motamedi, A., Hammad, A., & Asen, Y. (2014).
Knowledge-assisted
BIM-based
VisualAnalytics for Failure Root Cause Detection in
Facilities
Management.
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(2014). A Review Study of Maintenance and598

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ON THE SEASONAL COLORS AND SMELLS ANALYZING SOCIAL
NETWORKING SERVICE

1

Tatsuya Matsuura1, Momoko Tanaka2, Hayate Deguchi3 and Kazunari Tanaka4
Graduate Course in Architecture, Civil Engineering and Urban Design, Graduate School, Osaka Institute ofTechnology, Japan; 2Ohba & co.,ltd, Japan; 3Chuoh consultants co.,ltd, Japan ; 4Osaka Institute ofTechnology, Japan

ABSTRACTThe purpose of this study is to examine a method to extract the “sense of the season” through colors and smells.
The research method is based on the Twenty-four Divisions of the Solar Year as units to extract and categorize
colors and smells from photos and posts on SNS; Twitter and Facebook, where people post about the seasons. We
collect the data using geospatial information system and text mining (KH coder) software. First, we collected
yearly tweets from 2017 posted on Twitter. The photo accompanied in the tweet is subjected to extract the colors
at that point in the season. Sentences are subjected to text mining to extract “smells”. In this research, we try to
extract not just a few typical colors and smells of the seasons, but all colors and smells. The results show that there
are from 64 to 77 seasonal colors. The smells of the season occur in the first half of February, the second half ofMay, the second half of June, the first half of July, the second half of September, and October. Outside of this wecannot significantly detect the seasonal smells.
Keywords: colors, smells, Twenty-four Divisions of the Solar Year, SNS

between modern people and visual information is high.
Therefore, we focus on the vision part of the fivesenses. Also, olfactory information has a strong
relationship with emotion and memory in the brain,
and information collected from this method is retained
for a long time. For this reason, we also focus on thesense of smell along with as the sense of sight. We alsoplan to incorporate an additional sense after thisexamination.

INTRODUCTION
Japan has four distinct seasons, but traditionally inJapan, the seasons were actually divided into 24. So,
the Japanese people were always very sensitive to thechanging seasons. Natural phenomena that change
daily such as seasonal food and events have always
enriched the lives and minds of Japanese people.
However, in the present era it is difficult for Japanesepeople to feel these more subtle changes in theseasons. The modern lifestyle does not allow people tofeel the seasons in the same way as the past. So, I
would argue that Japanese people are missing an
opportunity to enrich their minds. However, at present,with the spread of electronic devices, it can be said thatJapanese people now feel the seasons through TV andInternet, especially with a focus on SNS whereindividual people can post their pictures and feelings.
If one can express a sense of season throughinformation channels, we can use this for analyzing in
the real world.

COLOR ANALYSIS
We collected images from Twitter to extract
seasonal colors. We collected 50 images per period.
We set three conditions such as images not including
illustrations, image of object including backgroundand image not edited. And we resized the image to 60
x 60 pixels (for uniformity of resolution and aspectratio). We then convert RGB values per pixel to the
XYZ color system (to L*a*b* color system.[1]), toeasily express the results of image analysis. This time,
the colors extracted from multiple images weredivided into the same color system, and the ΔE2000
color error formula [2] was used to calculate the colors
and proportions (Figure-1, Figure-2, Figure-3).
Extraction results were not consistent in color order,
hence we used the Munsell color system to arrange theresults. From the results, the proportion of green lines
increase from May to August, and the proportion of
red lines was dominant in October and November.
Although there are events such as beach and pools

PURPOSE AND METHOD OF RESEARCH
In this research, the purpose is to capture thepresent-day colors and smell of the seasons. The
method is by using the images and comments on SNS
to extract this information. The share of informationacquired by the human five senses is overwhelmingly
vision-based at 87%. In recent years, many people areusing photos to transmit information and convey
feeling via SNS, indicating that the relationship
599

SEE - Bangkok, Thailand, Nov.11-13, 2019

opening in July and August, the proportion of blue andlight blue is not significant. Going against what weoriginally thought, that Japanese people would feel asense of the summer season with the color of the water,such as sea etc. This indicates that Japanese people feelsummer from various other things.

Fig. 1by half months. We used text mining software to
analyze the data, and finally created a co-occurrence
network. As an example, the results of the same monthas color analysis. From the results of the Late ofMarch, we could extract the words of morning,
perfume and person have an influence in the season.
From the results of the first half of October, we could
extract the smell of fragrant olive (osmanthus) has agreat influence in the season (Figure-4, Figure-5). We
selected the necessary parts of speech, set theminimum number of co-occurring words, andcorrected co-occurring words when creating a cooccurrence network. As a result of this analysis, it was
found that seasonal words appeared at the turn of theseason, and that changes in the seasonal smells were
present. However, it can be seen that there are few
months when season-specific smells appeared. From
the results of the co-occurrence network, we made thegraph as the number of occurrences of the word on thevertical axis and on the horizontal axis as the first halfand late of the month. Light blue line is words about
seasonal, red line is words about related to people,
gray line is words about food, yellow line is words
about nature, blue line is words about place (Figure-6).
When the smell of one season starts to transition to theExtraction result of color of the all season.
1.83

％

4.23
2.50
0.39

％
％

6.18
2.96
0.54

％
％
％

6.03
0.61
2.16

％
％
％

4.42
1.24
2.32
2.88
2.87
2.67

％
％
％
％
％
％

10.52
0.77
0.70
2.72
0.32
1.31
1.19
1.64
0.47
1.88
0.91
2.51
2.08
1.17

％
％
％
％
％
％
％
％
％
％
％
％
％

2.95
1.76

％
％

6.90
3.28
2.16
0.75

％
％
％
％

R(330～30） Y(30～90)

G(90～150) C(150～210) B(210～270) M(270～330)

front

eye
feeling

5.21
0.29
1.03
0.38
0.74
0.33
0.73

weak

bad

morning

want

％
％
％
％

myselfperfumemood
differencesoftener
cigarette
clothesFig. 2Extraction result of color of the first half ofOctober [3].
1.66
2.49

％
％

5.54

％

8.57

％

personmeat

trebblelight

the other personstrongfragrance

washinghair
a littlewindteacherhead

R(330～30） Y(30～90) G(90～150) C(150～210)B(210～270)M(270～330)

blood

springhair

scaredchestarm
feeling

child
time

10.29

％

5.
.6
40
6
0

％
％

4
0.1
50
7
1.
.4
74
8
0
2.
.8
38
7
0
1.
.7
11
6
0

％
％
％

4.25

％

4.44

％

4.41
3.
24
0
0
.8
3
8
0
7
0
.5
38
2
0
.

％
％
％
％
％

6.42
0
0

％

4.44
1.
.39
5
0
0.7
87
1.06
1.34
1.98
1.51
2.84
1.25
1.44
1.76

％
％
％
％
％
％
％
％
％
％
％
％

next tocute
garlicbus

master％％％％Fig. 4Late of March co-occurrence
lunch box
today
the person in question

handspirit
foot

5.19

good

stinksfragrant olive(osmanthus)

sound

％

in front of you

like

rain

woman

Fig. 3Extraction result of color of the late March
[3].

eye

cosmetic
perfumerecently

myselfbest

morning

wife

ANALYSIS USING TEXT INFORMATION

train

don’t likestinksdislikedaugherari

fullcigarette

As with color analysis, we collected 10 text
tweets/day using Twitter to represent the “smells”.
They were random selected by the Twitter searchsystem on website. Next, the URL contained in the text
data was deleted and the collected data was organizedfragrancebadstrangeyesterday
outsidehemp
weak

fragrant olive(osmanthus)

good
bath

600

shampooautumnSEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 5First half of October co-occurrence

90
80
70
60
50
40
30
20
10
0
First Late First Late First Late First Late First Late First Late First Late First Late First Late First Late First Late First Latehalf Jan half Feb half Mar half Apr half May half Jun half Jul half Aug half Sep half Oct half Nov half Dec
of
of
of
of
of
of
of
of
of
of
of
of
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec

Seasonal

Related to people

Fig. 6Food

NaturePlace

Change of smell of each month
REFERENCES

next season based on the categorization of the cooccurrence word, the influence of other smells
becomes small. With regards to the months that do notemit season-specific smells, it can be considered thatthe season is sensed from a variety of smells rather
than specific smells.

[1] L*a*b* is a color space defined by theInternational Commission on Illumination (CIE) in1976. It expresses color as three values: L* for thelightness from black (0) to white (100), a* fromgreen (−) to red (+), and b* from blue (−) to yellow(+).

CONCLUSIONS[2] ∆𝐸2000 =In this research, seasonal color extraction results
revealed that there are many different colors present
than the standard seasonal colors we imagine. Not only
the main subjects, but also the colors of the subsubjects influenced the surrounding environment
when the seasonal colors were extracted. Regarding
the results of the smells of the season, changes with theseasons and smell became clear. Although we could
infer smell from objects, we found that the smells thatare easy to feel and communicate are food andseasonal goods, and that they are greatly influenced bynature. As a future subject, when collecting photos andtext data from Twitter, we will try to further extract thesense of seasons by region. Furthermore, by increasing
the amount of data collected, we will discover sensory
relationships including additional sensations in eachseason.

2

⊿ L′

2

⊿ C′

2

⊿ H′

⊿ H′

⊿ H′

√(k ・S ) + (k ・S ) + (k ・S ) + (R T (k ・S ) (k ・S ))
L

L

C

C

H

H

H

H

H

H

𝐶̅ ∗ 𝑎𝑏 7

L′ = 𝐿∗ ,𝑎′ = 𝑎 ∗ ,(1 + 𝐺) 𝐺 = 0.5 (1 − √𝐶̅ ∗𝑎𝑏 7 +257)b’𝑏′ = 𝑏 ∗ ,𝐶 ′ 𝑎 = √(a’)2 + (b’)2 ,h′ = tan−1 ( )a’[3] We divided the Hue-ring 6 categories of colors
evrey 60 degrees from the center color (red).

ACKNOWLEDGMENTS
I would like to thank Hikaru NISHIHATA for
useful discussions. I am grateful to Nobuaki
TANAKA and Hiroki KOMAI for assistance with thenumerical simulations.
601

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

PROPOSED ANGAT RIVER WATER IMPOUNDING AND FLOODMITIGATION PROJECTBon Ryan P. Aniban1, Roniel C. Naungayan1, Sheina R. Pallega1
Jordan N. Velasco1, and John Lemar M. Tirao 1
1
Pamantasan ng Lungsod ng Valenzuela, Valenzuela, Philippines

ABSTRACT
Along the Angat river in Bulacan, central Philippines, three existing dams (Ipo, Bustos, and Angat, dams) areinstalled which serve different purposes. These dams release huge volume of water which contributes to the floods
downstream the reservoir. This research aims to reduce flood water downstream and to impound flood water from
Ipo and Angat dams. The researchers conducted data gathering, preliminary investigations and flood simulations
using Global Mapper, ArcGIS and HEC-HMS respectively to compute the maximum decision flood (MDF) forthe basis of the dam. The proposed structure is a gated spillway-gravity dam subdivided into 15 flood storages
where water surface elevations were set as critical levels. Decision floods are formed by dividing the MDF into
15 sub-hydrographs. As a result of routing simulations of the decision floods, a set of 15 spillway gate openings
is identified where all floods from very small magnitudes to the MDF may be routed without overpassing the crestof dam. A 15-stage operation rules are then identified where the gate openings of the primary stages are decreased
as the critical levels increased step by step, with the objective of attenuating smaller floods more effectively andreleasing higher outflows for larger floods close to and including the MDF.
Keywords: Maximum decision flood, Flood mitigation, Gated spillway gravity dam, Water impounding

spillways will be base flood on the upstream ofproposed location of the dam. This will not cover soil
exploration and studies for the foundation, as well as
the bill of quantities of the design.

INTRODUCTION
The province of Bulacan, in central Philippines, islargely affected by heavy rainfall and strong winds
which caused worst floods and landslides in the area.
Huge volume of water coming from the nearby Sierra
Madre mountain range, drainage capacity constraints
and low-lying area elevations are also reasons offlooding in the province. Because of these, the needto develop strategies in flood mitigation is considereda priority. One of the long-term solutions that can beapplied is the construction of flood-regulating dams.
There are three existing dams in Bulacan, the Ipo,
Bustos, and Angat dams, that serve different purposes.
Each dam is operated by a specific water control plan,but due to extreme weather conditions, may
contribute to an impending huge flood. According to
Bulacan’s Provincial Risk Reduction andManagement Council, Angat dam is the only
impounding dam that can store large amount of wateramong the three. If Angat dam reached its criticallevel, flood water starts to overflow its radial gatesand subsequently inundates vast areas of the province.
This study mainly deals with designing a dam thatwill reduce destructive flood impacts in extreme
events and provide alternative water source as well.
This also focuses only in determining good locationof the water impounding and flood mitigation dam,
most efficient dimensions and stability, and designing
the operational openings of the gated spillways during
different flood events. The design of dam and gated

RELATED STUDIES
Throughout history, dams and reservoirs havebeen used successfully in collecting, storing andmanaging water supplies needed to sustain life. It isalso used as a water impounding structure during
heavy rains that reduces flooding [1]. However,
Schultz stated that dams should not be constructedwithout considering the location, choice and size, andstorage capacity [2]. In line with this, the US
Department of Interior published a design manual for
gravity dams presenting instructions, examples andstandards for the design of dams.
Hydrology and hydraulics analysis are required in
dam design and several applications are madeavailable for the process. Blue Marble Geographic
created Global Mapper which handles vector, rasterand elevation data that provides viewing conversion
and other geographic information systems (GIS) [3].
Another GIS software that was produced, called the
ArcGIS, works with maps that can calculate andprovide properties of land cover [4]. For floodmodelling, the US Army Corps introduced the use of
HEC-HMS for simulating precipitation-runoff
processes of dendritic watershed systems [5].
For efficient flood mitigation, inundation dams
602

SEE - Bangkok, Thailand, Nov.11-13, 2019

𝑻𝒍𝒂𝒈

with gated spillways are commonly used, however,
the operation of such gates is difficult, due to its
inconsistency to predict the true magnitude of an
incoming flood [6]. Linsley observed that discharge
regulation from these types of dams is regulated bygates and valves are operated on the basis of thejudgment of a project engineer [7]. Sakakima also
made a similar comment that for extremely large
flood, a reservoir operator has to control the gates toprotect the reservoir and the downstream reference
point by relying on his judgment [8]. With these
problems, numerous solutions were suggested for the
spillway gate operations. For example, Afshar andSalehi [9] proposed a modification of the 6-stage
model presented by Acanal, et al. [10], which takes
into account additional real-time information of the
inflow hydrograph measured at a gauging station
installed at the reservoir entrance [10]. Afshar andSaheli also coded another operation method whichassigns 3 critical water surface elevations associatedwith 3 control discharges with the objective ofminimizing downstream flooding [9]. Haktanir andCitakoglu modified the said 6-stage model into a 15stage model [11]. On their model, the flood retentionof a dam having a gated spillway is divided into 15
sub-storages whose surface elevations are identified
as critical levels.

=(𝑳 × 𝟑. 𝟐𝟖 × 𝟏𝟎𝟑 )𝟎.𝟖 × ((1)

𝟑. 𝟒𝟐 × 𝒀𝟎.𝟓

Where
𝑇𝑙𝑎𝑔 is the lag time (hour);
𝐶𝑁 is the curve number within the catchment area;
𝐿 is the hydraulic length of the catchment(kilometer); and,𝑌 is the average catchment slope
The values of the parameters used in SCS for lag
time calculation were obtained from ArcGIS. Curve
number, on the other hand, was determined from thehydrologic soil group and land use [12].
Design flood
The proposed dam is categorized according to
failure hazard and dam height. Design flood andminimum freeboard is then determined.
Elevation-storage relationshipTo calculate the change in storage in relation toelevation and area, the following equation is used:

METHODOLOGY𝚫𝑺 = (
Preliminary Data and Investigations

𝑨𝟏 + 𝑨𝟐) (𝒉 𝟐 − 𝒉 𝟏 )
𝟐

(2)

Where
Δ𝑆 is the change in storage;
𝐴1 is the surface area of water at previous elevationℎ1 ; and𝐴2 is the surface area of water at current elevationℎ2

Location of dam, catchment area, lag time and curve
number
Google Earth© was used to determine thepossible location of the proposed dam, should bealong Angat river with a narrowing channel, awayfrom major towns and cities, and the area upstream issuitable for a reservoir. To verify if the location is ina narrowing river, SRT-DEM was setup using Global
Mapper software. Contours and elevations are
generated in the SRT-DEM to determine thecatchment area and perimeter of the chosen location.

Spillway design
In designing spillways, the capacity of waterflowing and time must be considered. To check if
discharge will satisfy the time, the following equation
is used:𝒕=

Fig. 1𝟎.𝟕
𝟏𝟎𝟎𝟎
𝑪𝑵 − 𝟗)𝑯
𝟏
𝟎. 𝟕𝟓𝑨∫
𝟑 𝒅𝒉
𝟑𝟔𝟎𝟎 𝟎 𝟐
𝟐
𝑪
𝟐𝒈𝑳𝑯
𝟑 √

(2)

Where
𝑡 is the time required to discharge water (hour);𝐴 is the area (square meter) of water surface at
certain height ℎ (meter);
𝐻 is the height of water from crest of spillway(meter);𝐿 is the length of spillway (meter); and,𝑔 is the acceleration due to gravity (9.81 m/s2)

Digital elevation model of Angat River.

To determine lag time, the soil conservation
service (SCS) formula, adopted by DHI 2009 was
used:
603

SEE - Bangkok, Thailand, Nov.11-13, 2019(

HEC-HMS Simulation
HEC-HMS model components are used tosimulate the hydrologic response in a watershed. A
simulation calculates the precipitation-runoff
response in the basin model given by the input fromthe meteorological model. In this study, to computethe total inflow on the dam location, the rainfallrunoff from the catchment area given by the 100-year
return period and the discharge of Ipo dam during the2009 Typhoon Ketsana. During the simulation, SCS
curve number method is used for the loss rate, SCS
unit hydrograph for transform of sub-basin, anddischarge method for the flow or source creation.

Fig. 2𝑰𝟏 + 𝑰 𝟐
𝑶𝟏 + 𝑶𝟐) 𝚫𝒕 − () 𝚫𝒕 = 𝚫𝑺
𝟐
𝟐

(6)

Where
𝐼1 and 𝐼2 are the inflows at previous and current
time steps respectively;
𝑂1 and 𝑂2 are the outflows at previous and current
time steps respectively;
Δ𝑆 is the change in storage (cu.m.), Δ𝑆 = 𝑆2 − 𝑆1 ;and,
Δ𝑡 is the change in storage in time.
For 15-stage routing mode, stepwise routing
simulations at pre-defined time increments, such as𝑡 = 0.5 hr, each of the 15-decision hydrographs from
5% to 250% of the 100-year flood are repeated as
many times as required. The large loop of routing
computations begins by allocating 1/15th of the floodretention storage to all of the 15 decision floods. The
top elevations of sub-portions of the flood retention
storage are known as the critical levels (𝐻𝑐𝑟𝑟 ) isshown in Figure 3.

Model of the study area in HEC-HMS.

Fifteen-stage Routing Model
Computation of spillway flow
The spillway discharge for the fully-opened andpartially opened gates is computed by the following
equations,
𝟐𝑪√𝟐𝒈𝑳𝑯𝟏.𝟓
𝟑(4)

𝟐
𝑪√𝟐𝒈𝑳(𝑯𝟏 𝟏.𝟓 − 𝑯𝟐 𝟏.𝟓 )
𝟑

(5)

𝑸=

𝑸=

Fig. 3

Where
𝑄 is the total discharge;
𝐶 is the discharge coefficient;
𝐿 is the length of the spillway;
𝐻1 and 𝐻2 are the pressure head at the bottom of
the weir respectively; and,𝑔 is the acceleration due to gravity (9.81 m/s2)

The 15-stage routing model scheme. The
circles on the left and right show the stages
during the rising and recession limbs
respectively of the outflow hydrograph.

General Dimensions and Stability of Dam
The general dimension of the dam includes height,
width and the downstream slope, and a batter, if
necessary. All dimensions must be designed
satisfying stability and factor of safety. In this study,
the factor of safety (FS) used is 1, as stated to be theminimum FS of gravity dams [13]. The downstream
slope in this study followed the 1:2 vertical-horizontal
ratio rule in designing gravity dams [14].
In the design of concrete gravity dams, it isessential to determine the loads required for stability.
The following loads may affect the design: dead load,

Flood routing simulation
The flood routing simulation is performed
stepwise at fixed-time intervals, such as 0.25ℎ bysolving the continuity equation,

604

SEE - Bangkok, Thailand, Nov.11-13, 2019head water and tail water pressures and uplift. It isalso important to check the dimension of the dam if itwill satisfy FS against sliding and overturning.
𝑾 = 𝜸𝒄 𝑽(7)

𝟗. 𝟖𝟏𝑯𝟐 𝑳
𝟐
𝑭 = 𝟗. 𝟖𝟏𝑯𝑩

(8)

𝝁𝑹𝒚
𝑹𝒙
𝑹𝑴
𝑭𝑺𝒐 =
𝑶𝑴

(10)

𝑭=

𝑭𝑺𝒔 =

was determined with the use of contours that close thereservoir from the axis of the dam. It was found thatthe maximum surface elevation is 99 m and the lowest
elevation on the dam location is 56 m. The dam isclassified as Class IV and the design flood is 225% of
100-year flood with a minimum freeboard of 1.25 m.
With the assessment of stability, it was found that thefactors of safety against sliding and overturning is1.21 and 1.38, respectively.

(9)

(11)

Where
W is the concrete weight in kN;
𝛾𝑐 is the unit weight of concrete, 23.6 kN/m3;
𝑉 is the volume of concrete;
𝐹 is the force acting on the dam laterally;
𝐻 is the height of either head or tail water;
𝐿 is the length of dam, usually considering 1-meter
strip length of the dam;
𝐵 is the length of the base of the dam;𝐹𝑆𝑠 is the factor of safety against sliding;𝐹𝑆𝑜 is the factor of safety against overturning;
𝑅𝑦 is the totality of all forces acting vertically to thedam;
𝑅𝑥 is the totality of all forces acting horizontally tothe dam;𝜇 is the coefficient of friction;
𝑂𝑀 is the overturning moment; and,
𝑅𝑀 is the righting moment

RESULTS AND DISCUSSION

Fig. 5General dimension of the dam, in meters.

Fig. 6Storage-elevation curve

Fig. 7

Outflow hydrograph generated in HECHMS.

The proposed dam should be located at
14°53’41.75”N, 121°07’05.80”E, or in barangay San
Mateo, Bulacan, with a catchment area of 18.063 km2.

Fig. 4

Figure 7 shows the hydrograph of the 100-year
flood at the dam axis. It is the combination of thedischarges from the nearby Ipo dam and the rainfall
runoff produced by a 100-year flood from thecatchment area itself. The 15-decision floods shownin Fig. 8 are prepared for optimum management
during flood events.

Catchment area from the dam axis.

The general dimensions of the proposed dam were
determined using trial and error, such that the mostdesirable and most efficient dimension must produce
the smallest volume (Fig. 5). The height of the dam
605Flow rate (m3/S)

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Summary of spillway gate opening step
numbers for 15-operation rule sets, given by
the 15-stage routing for the proposed dam.

2001
1801
1601
1401
1201
1001
801
601
401
201
1
0

20

40

60

80

100

Time (hr)Fig. 8The 250% of 100-year flood of the proposed
dam, the 15th decision flood hydrographalong with the other 14 decisionhydrographs.

Table 1 summarizes the first operation option
along with two other options referred to themethodology. Table 2 shows the summary of 15 rules
for the spillway gate openings.
Figure 9 shows the inflow and outflowhydrographs of the dam. It also reveals that the 2nd
and 3rd options of encroaching the spillway gates forsmaller floods, and having to open them wider for
higher floods, yield outflow hydrographs for the
maximum design flood (MDF) peaks greater than thatof the 1st option (much greater for the 3rd option),while peaks of an intermediate flood, the 7th decisionflood, are considerable smaller than that of the 1 st
option as expected. The 2nd or 3rd options may be
preferred than the 1st option if mitigation of moderate
severity floods is the desired target. The flood
retention storage of the proposed dam is fairly large,
while the total discharge is also high; therefore, the
3rd option, which aims at keeping the spillway gatesclosed as much as possible for smaller decision floods,
results in closed gates up to the 7th decision flood.
However, this defiant policy necessitates large gate
openings after the 10th decision flood (half of MDF)
and fully opened gates beyond the 13th decision floodto the MDF. This implies that effective mitigation ofmoderate floods is paid for by heavy damage
downstream in case a severe flood is arriving to thereservoir.

Table 1 Spillway gate opening and critical lakelevels for the 1st, 2nd and 3rd options ofoperations.

Hb
Hcr₁
Hcr₃
Hcr₄
Hcr₅
Hcr₆
Hcr₇
Hcr₈
Hcr₉
Hcr₁ₒ
Hcr₁₁
Hcr₁₂
Hcr₁₃
Hcr₁₄
Hcr₁₅
Maximum WSE

Critical Levels and Gate Openings (m)First Option
Second Option
Third Option
88.76
88.76
88.76
0.1
0
0
89.17
89.39
89.39
0.2
0
0
89.64
90.1
90.1
0.4
0
0
89.95
90.8
90.8
0.6
0
0
90.24
91.47
91.47
0.8
0.8
0
90.51
91.52
92.13
0.9
0.9
0
91.25
91.79
92.85
1
1
0
91.97
92.33
93.95
1.2
1.2
0
92.57
92.89
95.77
1.4
1.4
1.6
93.12
93.39
95.83
1.8
1.8
3
93.54
93.77
96.11
2
3
4
94.05
93.89
96.15
2.6
3.2
6
94.28
94.17
96.51
3.8
5
Fully Open
96.01
95.61
97.83
6.5
6.5
Fully Open
99.00
99.00
99.00
98.99
98.99
98.97

Fig. 9606

Hydrographs for the 1st, 2nd and 3rd operation
options resulting from routing the parabolic
250% of 100-year flood of the proposed dam
using the 15-stage routing model.

SEE - Bangkok, Thailand, Nov.11-13, 2019

Figure 10 illustrates the variations in water
surface elevation (WSE) together with the criticallevels during routing of MDF during the 1st, 2nd and3rd options.

REFERENCES[1] International Commission on Large Dams,
Benefits and Concerns about Dams, Committee
on Public Awareness and Education, July 1999.
[2] Shultz A., Dam Construction, 2010[3] Blue Marble Geographics – LIDAR Module,
Unpublished Master’s Thesis, 2016.
[4] Environmental Systems Research Institute (ESRI
2001-2004), Master’s thesis, 2004.
[5] Hydrologic Engineering Center (HEC), HEC-5
Simulation of Flood Control and Conservation
Systems, US Army Corps of Engineers, 1998.
[6] Japan International Cooperation Agency,
Feasibility Study on Flood Control, Forecastingand Warning System for Seyhan River Basin:
Final Report, Summary, General Directorate ofState Hydraulic Works and Nippon Koei Co., Ltd.,
1994, pp. 3-39.
[7] Linsley R.K., Water Resources Engineering, 4thed., McGraw-Hill, 1992.
[8] Sakakima S., Kojiri T., and Itoh K., Real-time
Reservoir Operation with Neural Nets Concept,
Proceedings of the 7th International Conference on
Applications of Artificial Intelligence inEngineering(AIENG/92),
Computational
Mechanics Publications, pp. 501-514.
[9] Afshar A., and Salehi A., Gated Spillways
Operations Rules Considering Water Surface
Elevation and Flood Peak: Application to
Karkheh Dam, Proceedings of the World
Environmental and Water Resources Congress,
2011, pp. 3007-3015.
[10] Acanal N., Yurtal R., and Haktanir T., MultiStage Flood Routing for Gated Reservoirs andConjunctive Optimization of Hydroelectricity
Income with Flood Losses, Hydrological Sciences
Journal, Vol. 45, Issue 5, 2000, pp. 675-688.
[11] Haktanir T., Citakoglu H., and Nese A., FifteenStage Operation of Gated Spillways for Routing
Management Through Artificial Reservoirs,
Hydrological Sciences Journal, Vol. 58, Issue 5,
pp. 1013-1031.
[12] National Engineering Handbook, National
Resources Conservation Service, US Departmentof Agriculture, Part 630 Hydrology, Chapter 7,n.d.
[13] Bureau of Reclamation, US Department ofInterior, Design of Gravity Dams, 1976.
[14] New York State Department of Environmental
Conservation, Guidelines for Design of Dam,
1989.

Fig. 10 Rate of change of the lake WSE during the
MDF routing of proposed dam using 1 st, 2nd
and 3rd operation options.
CONCLUSION
The proposed Angat river water impounding andflood mitigation project located at San Mateo,
Bulacan is a viable long-term solution to the recurring
problem flooding in the downstream areas of Ipo andAngat dams. The infrastructure system is envisioned
to provide a solution to the flood-disaster prone lowlying areas in southern Bulacan.
The implementation of 15-stages of fixed
operational gate opening will eliminate the need to
predict the occurrence of flood event by management.
Since it has a fixed set of gate opening values on
different floods, it gives the most efficient routing
method and may avoid flash floods during and after
extreme rainfall events.
RECOMMENDATION
The proposed project is envisioned to provide along-term solution to the flooding in Bulacan. Within
the framework of sustainable development, it isrecommended to adopt the principles of integrated
water resource management and river basin approach.
This shall ensure that the outcomes of the project areconsistent with the general intent and master plan of
the government for a sustainable and functional built
environment.
There are a number of collateral issues andchallenges that concerned government agencies may
face at the implementation of this kind of projects.
Notwithstanding these issues, it is recommended thatthe project be immediately implemented after avalidation and detailed feasibility studies areundertaken, such as soil explorations. The sociopolitical repercussions should have special attention
to ensure smooth implementation of this project.

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5thInt. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

A RISK ASSESSMENT FRAMEWORK FOR HIGH-RISE SCHOOL
BUILDING PROJECT IN METRO MANILA, PHILIPPINES
Michael V. Almeida1 and Andres Winston C. Oreta2
1,2
De La Salle University, Philippines

ABSTRACTThe rapid increase of school building construction in the country was brought by the implementation of anationwide reform in pre-university education cycle from 10 to 12 years in June 2012. The change demanded asignificant increase in school buildings. However, construction of high-rise school building project is unique due
to its varying characteristics as compared to other types of building construction project. Construction of suchbuildings depends on variables such as site, surrounding, size, structure, student population, resources andculture. As a result, its is subject to numerous risk and weakness, which invariably have significant negative
impact on its overall performance. Therefore, risk assessment tools for school buildings must be modified to fit
these varying characteristics. However, there are three major challenges during the planning stage of project risk
management of such buildings, first is the correct identification of the sources and type of risks, second thenecessary statistical information and third, the selection of methods that will successfully estimate the potential
impacts and probabilities of occurrence. Presently, school administrators are experiencing difficulty in dealing
with risk assessment process due to no formal risk management structure in place and the lack of knowledge inrisk management theories and techniques. The skills gap resulting to ambiguity in risk decision making processduring project risk assessment must be bridged. This paper proposed a conceptual framework for developing adecision support tool which allows correct factor identification and assessment of risk associated in high-riseschool building construction in Philippines.
Keywords: High-rise school building, Risk Factor, Risk identification, Risk Assessment
dated 2017 (coaweb@coa.gov.ph) that some schoolbuildings constructed by the Department of Public
Works and Highways (DPWH) cannot be utilized
due to construction issues such as incomplete
utilities, structural defects, and delayed completionand turnover of buildings.
Project risk management approach for building
new schools is different from a private school to thatof a public school. The rules from public schools are
not simple, stakes are higher and considerations arepolitical. Compared in private school projects there
are clear answers to questions on the number ofstudents that will be accommodated, location ofbuilding site, environmental issues, companies andcontractors to hire, funding, attendance boundaries
and no voters reaction to deal with (Lunenburg,
2010). Risk conditions are practices or aspects ofschool building construction environment that may
result to risk occurrence. In January 2009, the Center
for Research on Epidemology of Disaster mentionedthat approximately 1.2 billion students are enrolled
in primary and secondary school; of these, 875
million school children live in high seismic riskzones and hundreds of millions more face regularflood, landslide, extreme wind and fire hazards.
School buildings constructed without considering
these risks during planning phase not only injure or
kill children, but also destroy the physicalinfrastructure where the cost of repair and

INTRODUCTION
School building construction in the Philippines
becomes prevalent since the implementation of anationwide reform in pre-university education cyclefrom 10 to 12 years in June 2012 (Figueroa, Lim,and Lee, 2016). However, such building
construction compared from other types is not
simple and differs in terms of built environment(private or public). School building construction
methods consist of both physical and metaphysicalfactors. The physical factors that will influence theoutcomes are financial resources, limitations of the
proposed project site due to its controlledenvironment, nature of the education program andframework of the age class groups. The
metaphysical nature on the other hand is a criticalfactor before its realization. Compared to otherbuilding construction the stakeholders are notlimited only to designers, contractors, and project
managers but also the participation of school
administrators, teachers, parents and age structure of
students to be served as well. According toLunenburg & Ornstein (2008), schools buildings
deteriorates faster compared to other buildings
because the physical facilities such as plumbing,sewer, electric, roof, masonry and carpentry are outof date and below the standard code. For example,
according to a Commission on Audit (COA) report
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SEE - Bangkok, Thailand, Nov.11-13, 2019reconstruction can be a great economic burden(INEE and GFDR, 2009). For instance, supertyphoon Durian (2006) in the Philippines caused
20m USD damage to school, including 90-100% ofschool buildings in three cities and 50-60% ofschool buildings in two other cities (INEE andGFDR, 2009). The failure of the people responsible
to consider the threat of constructing schoolbuildings in hazard prone areas resulted not only
damages to properties but also loss of lives.
The increasing awareness of the need to establish
a best approach for treating these problems has put
the focus of stakeholders to consider the various
potential risk and impact to prevent any financial
losses. However, there are three major challenges
during the planning stage of project risk
management of such buildings, first is the correct
identification of the sources and type of risks,
second the necessary statistical information and third,
the selection of methods or tools that will be used tosuccessfully estimate the potential impacts andprobabilities of occurrence. Presently, professionals
in the project organization are experiencing
difficulty in dealing with risk assessment process
due to no formal risk management structure in place
and the lack of knowledge in risk management
theories and techniques. Intuition and experience
were used for risk decision making which isinadequate for a controlled construction such as
school buildings resulting to cost overruns, delays,
claims, and disputes. The skills gap resulting toambiguity in risk decision making process during
project risk assessment must be bridged.
There are few published local researches offormal risk assessment techniques challenging the
traditional approach of assessing risk factors forschool building construction projects in thePhilippines such as Oreta and Brizuela (2013) used a
computer-aided earthquake risk management toolthat would allow school administrators to participate
in the decision making process. Miyamoto andGilani (2015) also used computer models, toestimate losses of hazard risks in public schoolbuildings. Figueroa, Lim and Lee (2016) utilized
geographic information system to assess thecondition of school building quality affected bygeography, climate and societal factors. Also, there
are some foreign researchers that developed risk
assessment models for school buildings to improve
the traditional approach, such as Global Facility for
Disaster Reduction and Recovery introduced in 2015
an innovative partnership-based approach an open
source mapping platform to provide a global
baseline to ensure safety of all school facilities atrisk (INEE and GFDR, 2009). Theunynck (2008),
revealed that one of the most economical andeffective approaches to a hazard resilient school
construction in Africa and Asia is a community
driven development approach (CDD). Finn & Dexter(2012), applied the probability-impact (PI) matrix in
identifying, prioritizing and segregating highly
potential risks for a school building projects. The
Institute of Risk Management (2015), also proposeda systematic risk analysis to evaluate risk factors interms of likelihood of occurrence or probability andconsequence of impact using traffic light system orprobability impact diagram. The United States
Department of Education (2008), stated that risk
identification on vulnerability assessment for school
can be done by various techniques such as brain
storming, interview/expert opinion, past experienceand checklists which can minimize cost overruns
and scheduling problems. Grant, D.N. et al. (2006),
carried out vulnerability assessment using score-andindex-based methods to define the earthquake
resistance of school buildings. Coronel & Lopez(2012), developed a computational tool based on
geographical information system (GIS) using
modern seismic attenuation relationships toestimates damages and losses of seismic event onschool buildings. Mudiyanselage & Marasingha(2013), proposed the incremental dynamic analysis(IDA) to assess the performance of a two storey
school building for seismic event using nonlinear
finite element model. Wetterneck, Sass & Davies(2005), assessed risk factors for school buildings
using multivariate analyses of variance (MANOVA).
Panahi, Rezale & Meshkani (2014), developed aseismic vulnerability map of school buildings using
on analytic hierarchy process (AHP) andgeographical information system (GIS). Maziliguney,
L. et al (2012), performed ATC 21 (FEMA 154)
seismic vulnerability assessment method forreinforced concrete school buildings to evaluate
performance of school buildings. The Construction
Industry Institute (CII) developed the project
definition rating index (PDRI) as tool to support
school administrators in decision making processduring the planning stage (Pope, et al. 2016). This
tool attempts to identify uncertainty before schoolbuilding construction (Cho & Gibson, 2000).
Following these developments there is no single
technique that can be considered the best techniquecapable of measuring and treating these uncertainties
and risks that affect school building project outcome.
The study will attempt to address the gap oftraditional risk assessment approach of private
school building projects and the limitations of citedtechniques by developing a weighted simulation
decision support tool using Analytic Network
Process and Monte Carlo Simulation technique.
FRAMEWORK
The theoretical framework underpinning thisstudy, is anchored on building elements whichgovern its development form design to completion
namely: codes and regulations, structural system,
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SEE - Bangkok, Thailand, Nov.11-13, 2019walls, windows and façade, service system andfinancing. Fig. 1 shows that a risk cannot be
accurately analysed and controlled unless its natureand components are first identified and understood.
Standard codes and regulation are indispensible
project requirement that all site works be plannedand executed in such a manner so as to avoid the riskof danger to site personnel and construction area andthe effect to the environment, that all suchoperations are performed in accordance with thefollowing accepted rules and regulations where theproject is located.

steel and concrete.
Buildings today utilize service system andfacilities as required by the National Building Codeof the Philippines and other related legislature.
These facilities are included in the design andconstruction of a building and are provided for the
comfort and safety of the occupants. The following
service system in building projects are verticaltransportation, electrical systems, HVAC systems(heating, ventilating and air conditioning) and fire
protection systems. When specialist designer
specifies the materials to be installed andconstruction details to execute, the contractor should
conform to the use of these materials and details.
However, it is difficult or impossible for thecontractors to determine if the materials and details
specified by the designer are suitable and correct.
For example, unsuitable materials and connections
in plumbing installation will result to damages due
to bursting of pipes; unsuitable materials forinsulation which can produce toxic gases in case offire; incorrect sizes of fixtures suspended in ceilings
or façade components which can cause injury or
damage to property if they fall down. The
consequential losses for the damages and efforts in
the repair works will add on the financial burden of
the owner.
Lastly, the element of financing the costs for theconstruction of a building project is the sole
responsibility of the developer. Costs of constructionof a buildings range to hundreds of millions ofdollars. Financing of building project depends on
what type of business is going to be established.
Basic sources of capital can be through equity
finance, debt finance or internally generated funds.
The owner of the building will rarely be willing toshoulder the construction costs without theassistance of outside financial institution. Without
sufficient financing during the periods of rapid
construction of the building when additional capitalis needed to cover operation, to maintain equipment,
to procure materials, to pay salaries and wages, tocover storage, transportation and reserve will result
to conflicts, disputes and claims which jeopardize
the primary aim of the owner to complete thebuilding on time. On the other hand, any delay incompletion affects the target date of use producing
loss of profit for its owner.

Fig. 1 Building risk framework
The possibility of design errors to occur intoday’s building construction projects is high due to
its time of discovery. The failure to review the plans
and specification makes errors to be discovered
when works has reached its advanced stage. The
attempt to correct the design errors will delay the
project and incur additional cost burden to the ownerunless otherwise at the account of the designer
through the professional indemnity insurance
prescribe in other countries. Because of the highlevel of seismicity here in the Philippines,
earthquake loads govern the structural design of allbuilding, in which wind loads assume prime
importance. The structural system of a building isdesigned to transmit vertical and horizontal loads
from the point of application to the foundations by
the most efficient path with minimum impact on theeconomy and function of the other elements of thebuilding. The structural engineer must consider
many different factors before selecting the final
structural system of a school building project. Basicbuilding properties such as height, shape, and usage
as well as local economic conditions that affect thematerials and labor costs; construction schedule,
design loads both vertical and lateral; building
behavior and occupant behavior; foundationconsiderations and coordination with mechanicalsystems (Cohen, 1986) are factors that influence thestructural system of a building structure. Generally,
structural systems are flexible and limitations only
come from the material used in the construction.
Typical materials used for structural systems are

Developing Risk Assessment Framework for
High-Rise School Building Project
The traditional risk assessment revealed by theliterature such as brain storming, Delphi technique,interview/expert opinion, past experience, check lists,
influence diagram produced level of uncertainty
which are not suitable for projects like schoolbuildings. This traditional approach assumes thatprecise decisions are provided and there is no venue
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SEE - Bangkok, Thailand, Nov.11-13, 2019

for statistical interpretation of results on similar or
close
decisions.
Hence,
theuncertainties
underpinning the risk assessment process in schoolbuilding environment, both explicit and implicit
should be dealt appropriately (David, 1996). Most of
the studies concluded in the improvement of these
traditional approach using qualitatively andquantitatively methods. This methods whencombined allows the quantification of risk in termsof magnitude/impact and frequency or time frame ofeach event (Mills, 2001) as well its probability ofoccurring (Shunmugam and Rwelamila, 2014).
Therefore, this study will attempt to develop an
effective risk assessment using qualitatively andquantitatively methods such as Analytic Network
Process and Monte Carlo Simulation as shown in
Fig. 2.

Carlo a simulation method will produce thefollowing advantages:
1. Provide a more systematic approach;
2. Will handle subjectivity in weighing risks
brought by human factors like personal
experience, intuition and judgment;
3. Will derive potential relation and level ofriskiness between risk factors;
4. Will improve applicability for both quantitativeand qualitative features of risk;
5. Will manage uncertainty in the judgments ofdecision makers by testing the statisticalsignificance of the final rankings of risk factors.
Furthermore, the proposed method will address thefollowing limitations of cited risk assessment
techniques such as:
1. inability to model epistemic uncertainty due tolack of enough information,
2. inability of measuring and including theintangible factors,
3. limitation in representing interdependencies
between different risks and the assumptions
that they are independent,
4. and inability to consider both qualitative andnon-monetary risk.
The use of this method will fill the skills gap
among practitioners in determining the probability
and impact values of potential risks in schoolbuilding projects.

Risks Identification
Decompose risks into hierarchy
network

Identify limits and extent of the
AHP
Distribute survey questionnaire
Perform pair-wise comparisons

METHODOLOGY
The theoretical framework will set thefoundation in formulating the research questions tobe answered. A mixed method approach will be usedin this study to utilize the strengths of both
qualitative and quantitative methods. Lee (1999)
believed that mixed methods are very powerfulwhen carried out correctly for a single researchstudy. The study will first review sources of related
literatures that identify and classify various types ofrisk which are commonly associated in schoolbuilding projects. Based from these reviews, aclassification method will be adopted to arrange risk
factors into groups and sub-groups for the purposeof risk identification and modelling as illustrated inFig. 3.
In this study school building construction risk are
divided into two categories: external risks andinternal risks and 6 risk factors consisting of sub-riskfactors are derived. Based from the presented
literatures, risk in a construction projects are
generally based from two sources, the external risk
which are originated due to the project environment
or usually unique to the country while internal risks
are initiated inside the project (Flanagan & Norman,
1993; Aleshin, 2001; Fang et al., 2004; Ling & Hoi,
2006; El-Sayegh, 2008).
In the second stage of data collection, selection

Define and create the probability
distribution matrices
Compute n times the eigenvector
using Monte Carlo Simulation
MethodIs the consistency ratio
for all simulation morethan 10%YES

NO

Eliminate the simulation runs with CR> 0.10

Formulate the supermatrix using thesimulated weights and network
structure
Raise the supermatrix to limiting
powers
Probability of risk occurrence andlevel of impact

Fig. 2 MCANP weighted simulation framework
The combination of Analytic Network Process amultiple criteria decision-making method and Monte
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SEE - Bangkok, Thailand, Nov.11-13, 2019of group subject matter experts. The group will bedefined first according to skills, knowledge andunique qualities and the sample subject matter expert
will be selected using a probability sampling process.
The subject matter should have undertaken andcompleted school construction projects for the past
10 years and held administrative position in theinstitution. The data acquired from this group willplay a vital role in the successful application of MCANP technique. Therefore, the right people will beselected for best results. Finally, once the group of
subject respondents are selected, a survey
questionnaire will be administered.
This study will perform pairwise comparisons at
every level using the numeric preference of thesubject matter experts judgement as input data fromthe survey questionnaire. Using Analytic Network
Process (ANP) willutilize the derivation of potential
relation and the level of riskiness of between
potential risks factors as illustrated in Fig. 3 is the
proposed risk breakdown network for schoolbuilding. Assuming the factors are interdependentand there is a feedback loop from elements in levelof risk (High, Medium and Low) to factor elements.
Judgment consistency ratio(CR) of CI = (ƛmax- n)/ (n- 1), n is the matrix size with the appropriate value inTable 4. If CR is more than 0.10, the judgment
matrix is inconsistent (Saaty, 1990).

RESULTS AND DISCUSSION

Table 4 Random consistency index (RI)

The proposed model will evaluate potential risk
factors associated in school building projects. Thereareseveralconflicting,weighted,andincommensurable risk factors involved besides theinterrelationships among these factors such as
dependencies and feedbacks. Because of thiscomplicated nature of the problem on hand, it can bemodeled as a network and treated with a network
based multi criteria decision making approach.
The ANP is a multi-criteria theory ofmeasurement used to determine weights of numericpreference from decision maker’s judgements at thesame time allows the assumptions of relative
influence of higher level elements from the lower
level elements (Saaty, 2006). Saaty (1996) proposed
ANP approach that can be utilized for examining
network model representations. The power of ANPlies in its use of special ratio scales (Saaty, 1996) tocapture all kinds of interactions between external
and internal risk factors for making accurate
predictions and better decisions. Because ofinteractions among criteria, the criteria that are lessimportant individually might turn out to be more
important when evaluated collectively in a network(Saaty and Vargas, 2006). Moreover, two types ofinteractions are illustrated in the proposed ANP
model, the outer dependence which is represented bystraight arrows and inner dependence which isrepresented by loops. Furthermore, the decision
problem is characterized by three aspects
namelyThe ANP model for risk assessment
This study proposes a multi-criteria decisionmodel for assessing overall riskiness of schoolbuilding construction project as shown in Fig. 3.

Fig. 3 Risk breakdown network modeln 1 2 3 4 5 6 7 8
9 10
RI 0 0 .58 .90 1.12 1.24 1.32 1.41 1.45 1.49
The local priority vectors from pair-wisecomparisons on the elements of the cluster and subcluster levels will be adopted to achieve asupermatix, which in turn obtain global priorities.
After entering the sub-matrices into the supermatix
and adjusting its values to achieve column stochastic.
The supermatrix is raised to limiting powers until
weights have converged and remain stable (Saaty,
1996; Meade and Sarkis, 1998; Promentilla et al.,2005). The proper decomposition of the problem
into a network is vital for the successful applicationof MC-ANP technique.
To address the ambiguity gap that occurs during
the judgement of the selected group of subject
matter experts in answering the survey
questionnaires, this different judgement will becollected to define the probability distributions inorder to create the probabilistic pair-wisecomparison matrix. Fig. 4 illustrates an example ofthe proposed probabilistic distribution matrix. Since
probabilistic judgment uses random variables thecomputation of eigenvectors and eigen-values
cannot be done in a traditional way, the Monte Carlosimulation technique will be used.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

the goal, risk factors and level of impact. Thus, theoverall goal of this study is to assess the risk ofschool building construction projects.

the use of Monte Carlo simulation is recommended.
Simulation according to Albright (2010) is a useful
tool for modeling random variables. Thus,
constructing a simulation of iterations n will provide
estimates of the probabilities associated with thevector of priorities (Banuelas and Anthony, 2004).

The probability distribution matrix
During the traditional ANP, the pairwise
comparisons in the decision clusters and respective
elements represented by aij are deterministic, where
aij indicates how much more important the ithalternative/criteria is than the jth alternative/criteria
and this will lead to the construction of thecomposite priority vector of alternatives’ importance.
In the MCANP, the aij values are represented by thepij probabilistic judgments. The most rigorous andsuitable method to select the appropriate distributionof pij is using the statistical principles. From thecentral limit theorem, it can be seen that for almost
all populations, the sample distribution can beapproximated closely by a normal distribution,
provided the sample size is sufficiently large(Kiemele et al. 1997). However, it can be difficult toobtain a large sample size of subject-matter experts
to perform the pair-wise comparison (Banuelas &Antony, 2004). Another method can be use
according to Banuelas & Antony (2004) is the chisquared goodness-of-fit test to investigate whether
an underlying distribution (or population) fromwhich the data have been taken is of a specified
form or not. Hauser and Tadikamalla (1996) suggestthat in the extreme case the decision-makers are not‘n’ times. Thus, to quantify variation due touncertainty of the decision maker’s judgements theuse of random variable with a uniform probabilistic
distribution between 1/9 and 9 in the pair-wisecomparison matrix as shown in Table 1.
Rosenbloom (1996) recommended the use ofMonte Carlo simulation to estimate the composite
priority vector from the probabilistic judgment (Pij).
Therefore , each replication would be a realization of
all the aijs in the decision hierarchy followed by thestandard ANP calculation of eigenvectors and eigen
values. Replicating n times will provide estimates ofthe probabilities associated with the priority vector
as shown in Table 2 and Table 3.
The probability distribution function , F(x) is themathematical equation that describes the probability
that a random variable X is less than or equal to x,
given by Eq. (1) (David, 1996):

F ( x)  P( X  x)

Table 1 Normalized probability distribution matrix

F1
F2
F3
F4
F5
F6

F1
1
5
9
1
6
7

F2
.2
1
8
.2
2
4

F3
.111
.125
1
.111
.142
.250

F4
1
5
9
1
3
2

F5
.166
.500
7
.333
1
1

F6
.142
.250
4
.500
1
1

ω
.0297
.0951
.5345
.0420
.1316
.1672

ƛmax= 6.605, CI= 0.12, RI=1.25, CR= 0.097 < 0.10 OK.

Table 2 Simulated priority weights

F1(0.0297)
F2(0.0951)
F3(0.5345)
F4(0.0420)
F5(0.1316)
F6(0.1672)
Overall Level

HIGH
0.16920.1311
0.79280.08900.0881
0.7626
0.5840MED
0.38740.66080.13120.32340.71720.16620.2802LOW
0.44340.20810.07600.5876
0.19470.07260.1360

Table 3. Overall priority weights
Risk Factors & Levels
F1
F2
F3
F4
F5
F6
HIGH
MEDIUM
LOW

Final Ratings
.0451
.0478
.1646
.0300
.0520
.0604
.1000
.0640
.0400

In the proposed MCANP method compared to
traditional approach that assumes precise decisions
are provided and there is no venue for statisticalinterpretation of results on similar or close decisions.
MCANP can quantify the error of uncertainty in thejudgements through the probabilistic judgementswith a confidence level of 95%.

(1)
CONCLUSION

where P(X < x) means the probability of the event X< x. Therefore, in order to meet the Saaty’s pairwise
comparison scale the probability distribution of therandom variable X is equal to or greater than 1/9
and not greater than 9. If X are random variables it
follows that final ratings are also random variables.
To test the statistical significance of the final ratings

Classification of all types of potential risks forhigh-rise school building construction according toprobability of occurrence and consequence wassuggested. The objective of this classification is to
identify the impact of each risk factors on theconstruction of the school buildings For example,
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SEE - Bangkok, Thailand, Nov.11-13, 2019

the total construction cost for structural works in a
typical high-rise building is PhP 300M but due toFinancial risk factor (F1) as shown in Table 3 theprobability of occurrence if not considered during
the planning stage is 16.46% and the level ofriskiness is HIGH with a possible impact in cost of
10% which translate in a risk value of 1.65%
amounting to PhP 4.95M. This cost of risk will be
the maximum value of damage according to theimpact in percent of the construction cost. Therefore,
it is important to determine the potential damage orvalue of losses of each risk factor in the project. The
value of risk is the potential amount of damages
when the event occurs. Thus, the method allows toestimate the probable value of losses and the degreeof influence in the project.

[9] Figueroa, L.L., Lim, S. & Lee, J. (2016). Spatial
analysis to identify disparities in Philippine
public school facilities, Regional Studies,
Regional Science, 3:1, 1-27.
[10] Flanagan, R., and Norman, G. (1993) Risk
management and construction, Blackwell
Publishing, Oxford, UK.
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ACKNOWLEDGMENTS
The author would like to thank De La Salle
University, particularly Dr. Andres Winston Oreta in
his support in completing this paper.
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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ASSESSMENT OF DEBRIS FLOW VELOCITY USING A SIMPLELUMPED MASS MODEL FOR DEBRIS FLOW MOBILIZATION

1

Thapthai Chaithong1
Graduate school of Environmental Studies, Tohoku University

ABSTRACT
Debris flow is a natural phenomenon that is a flow of a mixture of liquid (water) and solid components (soil,rock or wood debris). Considering the triggering factors, extreme or prolonged rainfall is a significant parameterin this phenomenon. The anatomy of debris flow consists of three main parts: initiation zone, transportation zone
and deposition area. The debris flow can destroy infrastructure and housing along its path of flow and depositionarea, including causing loss of human lives. In this study, a simple lumped mass model is used to calculate thevelocity of debris flow and to estimate the potential deposition area of debris flow. The lumped mass model
describes the movement of the centroid of a debris flow. In the analysis, gravity is the driving force and theresistance force is developed based on a combination of Coulomb’s friction law and Terzaghi’s effective stressprinciple. A historical debris flow case in Japan is the case study of this analysis. According to calculation, thesimple lumped mass can estimate the velocities and deposition areas of debris flows.
Keywords: Debris flow, Lumped mass model, Extreme rainfall, Landslide, Typhoon

INTRODUCTIONSLOPESTABILITYANALYSISHILLSLOPE HYDROLOGY

Debris flow is a rapid flow of hillslope materials,
sediment and other debris mixed with water [1], [2].
In general, debris flow can be divided into threemain parts: initiation, flow path and deposition area[2], [3]. Housing and infrastructure such as bridges,
railways and highways are greatly damaged bydebris flow. Considering the debris flow, it causes
harm generally in three different ways, namely
deposition, entrainment and direct impact, in which
direct impact is the major cause of building
destruction [4], [5]. For assessment and design of thebuilding or infrastructure that can resist the debris
flow, there are several important parameters, such asvolume of debris flow, velocity of debris flow andsize of debris fan that need to be considered [6]. In
particular, the velocity of debris flow is a significant
parameter to calculate the impact force of debris
flow because the velocity of debris flow is aparameter in numerous equations of impact force ofdebris flow [4]–[6]. The velocity of debris flow canbe calculated or predicted using the debris flow runout model. In general, the debris flow run-out
models are developed based on two main frames ofreference: Lagrangian and Eulerian approaches suchas DAN, DMM, EDDA 1.0 or EDDA 2.0 [7]–[10].
Therefore, the aim of this study is to calculate thevelocity of debris using a simple lumped massmodel for debris flow mobilization. A historicaldebris flow case in Japan is the example for debris
flow velocity calculation.

AND

The infinite slope stability model is a traditionalslope stability model utilised to analyse shallow
slope failures or shallow landslides. Shallow slope
failures are characterised by a shallow depth andform failure planes parallel to the hillslope surface.
These factors are similar to the assumptions of theinfinite slope stability model. The stability of thehillslope is presented in the form of a safety factor,
as shown in Eq. (1). The safety factor is the ratio ofdriving stress to resisting stress. Resisting stress isdeveloped based on the Mohr–Coulomb failure
criteria.
c′ + ( zγ sat ) + ( B − z ) γ t − ( zγ w )  cos 2 β tan φ ′FS =( zγ ′ ) + ( B − z ) γ t + ( zγ w )  sin β cos β(1)where c′ is the cohesion of soil, z is the saturated
zone (groundwater depth), B is the depth of soil, β
is the slope angle, φ ′ is the effective friction angle,

γ ′ is the effective unit weight of soil, γ t is the total
unit weight of soil, γ w is the unit weight of water.
Conte [11] proposed the equation for groundwater level prediction. Eq. (2) presents thegroundwater table height (z(t)).

z (t ) =615

p
exp [ −kt sin β cos β (t − to ) ]n (1 − S r )(2)

SEE - Bangkok, Thailand, Nov.11-13, 2019

where p is precipitation, B is the channel width, kt isratio of hydraulic conductivity of soil and channel
width, n is the porosity, Sr is the degree ofsaturation, t0 is initial time.

=
R mg (1 − ru ) tan φ cos β

where ru is the pore pressure ratio, φ is the friction
angle.

A SIMPLE LUMPED MASS FOR DEBRISFLOW MOBILIZATIONru =To analyse the run-out behaviour of debris flow,
the previous research assumed the debris flow as afinite mass (finite boundaries at any position) [7],[12]–[14]. Hence, this study applies the sliding blockmodel to analyse the motion of debris flow. The
sliding block model is a lumped mass model utilised
to describe the movement of the centroid of a debris
flow in which the block is treated as a lumped mass
[15]. To analyse the sliding block motion, the acting
force is a significant result of the driving force andmovement resistance. In this analysis, gravity
imposes a driving force and the movement resistanceis developed based on a combination of Coulomb’s
friction law and Terzaghi’s effective stress principle.
The motion of the sliding block model is describedby Newton’s law and the momentum change to thesum of the forces. Figure 1 shows the forces
assumed in the sliding block model.

d ( mv )dt= net force

(5)

u

(6)

γh

where u is the pore fluid pressure on the base ofblock, γ is the unit weight of soil, h is the height ofblock slide.
The pore fluid pressure on the base of block cancalculate using Eq. (7).
=u  zγ sat + ( h − z ) γ  cos 2 β(7)where z is the height of saturated layer, γ sat is theunit weight of saturated soil.
Hutchinson [16] used Terzaghiʼs onedimensional consolidation theory to calculate thedissipation of pore fluid pressure. The time t
required for the basal pore fluid pressure to dissipate
can be written in Eq. (8). The pore fluid pressurechanges with time based on the differential equationof Terzaghiʼs one-dimensional consolidation theory,
which can be written in Eq. (9).

(3)

t=

where net force (Fn) is sum of forces of debris flow(net force = driving force – resisting force), m is themass of debris flow, v is the velocity of debris flow
and t is time interval.

T (h)

2

cv

∂u
∂ 2u
= cv 2
∂t
∂h

(8)

(9)

where T time factor for the degree of dissipation of
the basal pore fluid pressure, cv is the coefficient ofconsolidation.
From Eq. (3), it can be changed the form into Eq.
(10) which is based on the equation of motion on a
curved path.

mv
Fig. 1

Schematic of forces assumed in the sliding
block model.

(10)

Therefore

The driving force (D) can be expressed asfollows:

D = mg ( sin β )dv 2 dm+v=
net force ( Fn )
ds
ds

dv
dm
mv = Fn − v 2
ds
ds

(11)

(4)
where s is the distance of debris flow run-out.
Considering the term of (dm/ds), it can refer to thechanging of mass of debris flow during the run-out
such as erosion, entrainment, or deposition.
Equation (11) can be discretized based on thefinite difference method as follows:

where g is the gravitational acceleration (9.81 m/s2)
and β is the slope angle.
The resisting force (R) is the movement
resistance which can be expressed as follows:

616

SEE - Bangkok, Thailand, Nov.11-13, 2019∆v∆m
mv = Fn − v 2∆s∆sFinally, the velocity of debris changing with
distance will be calculated using Eq. (13). Table 1
summarises the parameters used in the rainfallinduced shallow slope failure, the sliding blockmodel.
In this study, we examined the historicallandslide and flow slide that occurred on the local
slope of the town of Iwaizumi, in Japan’s Iwate
Prefecture, on 30 August 2016. Figure 2 shows the
topography of the case study.

(12)

Therefore=∆vg ∆s ( sin β )v−

g ∆s (1 − ru ) tan φ cos βv−v 2 ∆mmv(13)

Considering the conservation of energy for any
sliding block, this study assumed that the velocity isparallel to the slip path at the base of the block attime t. On motion triggering, the potential energy ofthe block is converted into kinetic energy [17]. The
equation of motion of the sliding block can be
expressed as follows:d 1 2 dd  mg (1 − ru ) tan φ h mv ( mgh ) −  (14)
=dt  2
dt 
tan β
 dt


When; the kinetic energy can be rewritten as:d 1 2
dv
 mv  = mv
dt  2dt


(15)
Fig. 2

And; the potential energy can be rewritten as shownin Eq. (16) when dh/dt represents the velocity (v)ddhmgh ) mg= mgv sin θ
(=
dt
dt

Table 1 Properties used in this study(16)

And; the friction at the base of block and slip
surface can be written as follows:d  mgh (1 − ru ) tan φ  mg (1 − ru ) tan φ dh

=
tan β
tan β
dt 
dt

=

mg (1 − ru ) tan φ
tan β

(17)

Parameters
Hydraulic conductivity
Soil cohesion
Unit weight of water
Soil friction angle
Saturated unit weight of soil
Unit weight of debris flow
Slope angle 1, β1

Unit
m/hr
kN/m2
kN/m3
degrees
kN/m3
kN/m3
degreesValues
0.03
6.8
9.81
24.7
16.7
24.06
22.38

Slope angle 2, β 2degrees

14.04

Slope angle 3, β 3degrees

5.43

v
RESULTS AND DISCUSSION

Using Eqs. (15), to (17), Eq. (14) becomes asfollows:

g (1 − ru ) tan φdv= g sin β −
dt
tan β

Topography and elevation of case study.

Considering the location of landslide initiation,
shallow slope failure occurred at the top of thehillslope and slope angle 1. Figure 3 plots the safety
factor and hourly rainfall on 30 August 2016. In thisstudy, we selected the rainfall data detected at the
Iwaizumi rain gauge operated by Iwate prefecture
because this rain gauge was installed in closest
proximity to our case study. The peak hourly rainfallof 63 mm was recorded at 18:00 on 30 August 2016.
According to our calculations, we found that thesafety factor of the slope was less than 1 between
17:00 and 18:00 on 30 August 2016. The cumulative
rainfall during the period when the safety factor wasless than 1 was approximately 160 mm.

(18)

CALCULATION FRAMEWORK
There are three main parts to the calculation.
First, the initial landslide is calculated using therainfall-induced shallow slope failure model. The
result of the first step is the landslide occurrencetime and safety factor. The second step is tocalculate the initial velocity of debris using Eq. (18).
617

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 3

Safety factor of case study and hourly rainfall at Iwaizumi rain gauge.

Figure 4 shows the plot of the relation between
the velocity of the flow slide and time. Figure 5
shows the plots of the relation between the velocityof the flow slide and horizontal displacement. The
plots show that the velocity of the flow slide
increased at slope angle 1 and decreased slightly atslope angle 2. The velocity of the flow slide sharply
decreased at slope angle 3. The flow slide stopped
and deposited its debris at a horizontal distance of 51
m. The location of the deposition based on thecalculation accords well with our field observations
at the site. According to the calculation, the total
duration of the flow slide from the origin of thelandslide to deposition was approximately 8
seconds. Figure 6 shows a photograph of the sitestudied in this research.

Fig. 4Velocity of flow slide versus time.

Fig. 5Velocity and horizontal displacement.

Fig. 6a) Origin of landslide; b) the condition oftrees at 37 m; and c) the condition of trees
at 46 m.

CONCLUSIONSREFERENCES
The results of the model are a good fit for thedata obtained from the field observation. The
unknown factors of tree and soil parameters are
critical variables in the calculation. The maximum
speed is approximately 9 m/s. The unknown
parameters of parameters are critical variables in thecalculation and an important challenge for backanalysis of debris flow.

[1] Regmi N. R.., Giardino J. R., McDonald E. V.,
and Vitek J. D., Chapter 11-A Review of Mass
Movement Processes and Risk in the Critical
Zone of Earth. Developments in Earth Surface
Processes, Vol. 2, 2015, pp. 319-362.
[2] Gao L., Zhang L. M., Chen H. X., and Shen P.,
Simulating Debris Flow Mobility in Urban
Settings. Engineering Geology, Vol. 214, 2016,
pp. 67-78.
618

SEE - Bangkok, Thailand, Nov.11-13, 2019[3] Franks C. A. M., Characteristics of someRainfall-induced Landslides on Natural Slopes,
Lantau Island, Hong Kong. Quarterly Journal ofEngineerng Geology, Vol. 32, 1999, pp. 247-259.
[4] Hu K. H., Wei F. Q., and Y L., Real-time
Measurement and Preliminary Analysis of
Debris-flow Impact Force at Jiangjia Ravine,
China. Earth Surf. Process. Landforms, Vol. 36,
2011, pp. 1268-1278.
[5] He S., Liu W., and Li X. P., Prediction of Impact
Force of Debris Flows Based on Distribution andSize of Particles. Environ Earth Sci, Vol. 75,
Issue. 298, 2016, pp. 1-8.
[6] Gao L., Zhang L. M., and Chen H. X., Twodimensional Simulation of Debris Flow Impact
Pressures on Buildings. Engineering Geology,
Vol. 226, 2017, pp. 236-244.
[7] Hungr O., A model for the runout analysis of
rapid flow slides, debris flows, and avalanches.
Can. Geotech. J, Vol. 32, 1995, pp. 610-623.
[8] Kwan J. S. H., and Sun H. W., An improved
landslide mobility model. Can. Geotech. J., Vol.
43, 2006, pp. 531-539.
[9] Zhang L. M., and Chen H. X., EDDA 1.0:
integrated simulation of debris flow erosion,
deposition and property changes. Geosci. Model
Dev., Vol. 8, 2015, pp. 829-844.
[10] Shen P., Zhang L., Chen H., and Fan R., EDDA
2.0: integrated simulation of debris flow

initiation and dynamics considering two
initiation mechanisms. Geosci. Model Dev., Vol.
11, 2018, pp. 2841-2856.
[11] Conte E., Donato A., and Troncone A., A
simplified method for predicting rainfallinduced mobility of active landslides.
Landslides, Vol. 14, 2017, pp. 35-45.
[12] Perla R., A Two-parameter Model of Snowavalanche Motion. Journal of Glaciology, Vol.
26, No. 94, 1980, pp. 197-207.
[13] Cannon S. H., and Savage W. Z., A Masschange Model for the Estimation of Debris-flow
Runout. Journal of Geology, Vol. 1988, pp. 221227.
[14] Savage S. B., and Hutter K., The Motion of a
Finite Mass of Granular Material Down a Rough
Incline. J. Fluid Mech, Vol. 199, 1989, pp. 177215.
[15] Ku C. Y., Modeling of Rockfalls Using theLumped Mass Method and DDA. in Proc.
ISRM SINOROCK, 2013.
[16] Hutchinson J. N., A sliding-consolidation model
for flow slides. Can. Geotech. J, Vol. 23, 1986,
pp. 115-126.
[17] Lorenzini G., and Mazza N., Debris Flow:
Phenomenology and Rheological Modelling,
2004, pp. 1-202.

619

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DYNAMIC ANALYSIS OF NAILED SLOPE
Srinivas Ch1, Padmavathi M2 and Sanjeeva P3
P.G student, Jawaharlal Nehru Technological University Hyderabad, India
2
Associate Professor, Jawaharlal Nehru Technological University Hyderabad, India
3
Associate Professor, Malla Reddy Engineering College, India
1

ABSTRACT
Soil nailing technique has been used in many applications to improve the stability of existing natural slopesand excavated vertical cuts under precarious conditions. Dynamic stability of nailed is required in earthquake
prone areas. In the present study, stability analysis is carried out for a nailed slope with 50 0 slope angle and 20m
height. The analysis is carried out by both 2D limit equilibrium and finite element methods using a geotechnicalmodeling software, GeoStudio. The nailed slope is analysed for stability with respect to static, pseudo- static anddynamic conditions. Dynamic response of nailed slope is analysed against an earthquake with PGA of 0.15g by
Finite element method. The acceleration-time history is used as an input to simulate the earthquake in the
numerical model. The variation of factors of safety, shear stresses and displacements during earthquake are
analysed by dynamic analysis. From the analysis, it is found that the slope is unstable without nails with factor ofsafety 1.116 in static condition. And the factor of safety increases to about 1.628 by soil nailing. The factor ofsafety of nailed slope increases on an average of 6% with 1m increase in nail length from 0.5H to 0.7H. The
nailed slope experiences 60mm and 33mm displacements in both horizontal and vertical directions at the top of
the slope. From the results, it is concluded that the soil nails are efficient in improving the stability of slopes inboth static and seismic conditions.
Keywords: Finite element analysis, Slope stability, Soil nailing, Geo studio, Dynamic analysis
walls with different nail lengths, nail spacing’s andnail inclinations for different soils [11]. However theslopes are more prone to failure when they are
subjected to earthquake loading. So the researchers
proposed new methods to analyze the stability ofslopes against dynamic loading. The conventional
seismic stability of slopes is based on Pseudo-static
method [12]. Though it is very simple approach but
its applicability in seismic condition is very limited.
It considers only the earthquake forces and neglects
amplification of waves into soil stratum. Pseudodynamic (Steedman & Zeng, 1990) method is theconcept which imports amplification of vibrations
into the analysis [13]. Numerical methods are used
to study the nailed slope failure pattern,
deformations and stresses during earthquake bydynamic analysis [14].

INTRODUCTION
Soil nailing has become as an effective
stabilization technique especially in case of slope
instability. The unstable slopes can now be
improved and made stable by the insertion of nails
into the slope. The performance of nailed slope issignificantly depends on the interaction between soil,
nails and facing. Additionally various factors such as
the installation method of nails, the construction
sequence etc. influences the stability of the nailed
slope. Generally, the nailed slopes are analyzed forstability by conventional limit equilibrium methods.
Many researchers have developed the limit
equilibrium methods to analyze the stability ofnailed slopes [1]-[3]. The stability of nailed slope ismainly depends on nail pullout strength and nailtensile strength. The laboratory model tests and fieldtests are proposed to determine the pullout strengthand stability of the nailed slope [4]-[6]. Numericalmodeling, limit equilibrium methods and finite
element methods (FEM) are used to analyze thestability of nailed slope, failure zone, soil
nonlinearity and the staged construction effect topredict the actual site conditions [7]-[10]. Numericalmodeling of reinforced slope by finite element
methods has proved very useful in prediction ofslope deformations, stresses. The effect of naillength, nail spacing, nail inclination on stability of
the nailed slope is also analyzed by the numericalmodels. Mohamed proposed design charts for nailed

METHODOLOGY
For the purpose of illustration and better
understanding, a slope with 500 slope angle and 20m
height is considered for the study. The stability
analysis is carried out for static, pseudo-static anddynamic conditions. Pseudo-static and dynamic
conditions refer to seismic condition in limit
equilibrium and finite element analysis respectively.
The analysis is carried out by both 2D limit
equilibrium and finite element methods using ageotechnical modeling software, GeoStudio. In limit
equilibrium analysis, Bishop’s simplified method of621

SEE - Bangkok, Thailand, Nov.11-13, 2019slices is used to find the stability of nailed slope by
SLOPE/w module of GeoStudio. QUAKE/w moduleof GeoStudio is used to carry out the analysis byfinite element method.

present study, entry- exit option is used to simulate
the range of slip surface. SLOPE/W provides
different limit equilibrium methods to analyze theproblem. Bishop’s simplified method is consideredin the present analysis.

NUMERICAL MODELLING
Table 2 Optimum nail details used in the analysis
SLOPE/W Modeling for Static Analysis
Nail property
Yield strength
Nail diameter
Nail length
Nail inclination
Horizontal spacing
Vertical spacing

SLOPE/W is one of the modules of software tool,
GeoStudio. In the present study, stability analysis fora slope with 20m height and 500 slope angle iscarried with and without nails. SLOPE/W module
enables to construct the soil slope by drawing theslope regions. The dimensions of soil slope arescaled down to incorporate into the SLOPE/W tocreate the numerical model. The slope is modeled at
different slope angles by coordinate system present
in the SLOPE/W. Materials of slope are defined andassigned to regions, once the slope regions havebeen determined. The soil properties used in theanalysis are summarized in Table 1 [15]. The
numerical model of the slope is presented in Fig. 1.

Fig. 1

Symbol
Γ
C
Φ
k
μ
E

Value
415N/mm2
25mm
12m (0.6H)
150
1m
1m

SLOPE/W Modeling for Pseudo-Static Analysis
The slope is further analyzed to find the stability
against an earthquake of given PGA. Pseudo- static
analysis considers seismic loading in terms ofhorizontal and vertical seismic coefficients ofearthquake. The slope modeling and assigning
materials in pseudo – static analysis are similar tostatic analysis. The magnitudes of both horizontal
and vertical seismic coefficients of earthquake are
given as input once the modeling of slope is done. In
the present study, seismic coefficients of kh = 0.15
and kv = 0.075 is considered for the analysis. The
failure slip circle and Factor of Safety (FOS) are themajor results from the pseudo- static analysis.

Table 1 Soil properties used in the analysis
Property
Unit weight (kN/m3)
Cohesion (kN/m2)
Friction angle (0)Coefficient of
permeability (m/s)
Poison’s ratio
Young’s modulus(kPa)

Symbol
fy
d
l
λ
Sh
Sv

Value
18 kN/m3
20 kN/m2
280
1.16*10-8m/s
0.3537000kPaQUAKE/W Modeling for Dynamic Analysis
The dynamic analysis is carried out to analyse
the stability of the slope during the period ofearthquake. The acceleration- time history of theearthquake is taken in to consideration to analyse thebehavior of the slope during earthquake. In thepresent study, the optimum nailed slope obtained instatic and pseudo static analysis is considered for
dynamic analysis.
In the present study, the dynamic analysis iscarried out in 4 phases. The first and second phases
are carried out in QUAKE/W and third and fourthphases are carried out in SLOPE/W to find the FOS
by considering the first two phases as parent analysis.
In first stage initial static stresses are calculated in
QUAKE/W. The construction of slope regions bycoordinate system and assigning materials to theregions is similar to the process in SLOPE/W.
QUAKE/W provides an option to input slope
boundaries to the model. History nodes have been
selected where the results are required to retrieve
after the analysis.
The static stresses obtained in first phase are

Numerical model of slope

SLOPE/W module provides the option to input
reinforcement in the form of anchors, nails, piles andgeosynthetics. Nail element option is used to model
reinforcement in the nailed slope. The nail properties
used in the analysis are summarized in Table 2. The
slip surface is simulated by providing the range ofthe slip surface along the ground surface. In the622

SEE - Bangkok, Thailand, Nov.11-13, 2019considered as input in second stage. The dynamic
analysis is carried out by equivalent dynamic
method in the present study. The acceleration – time
history of the earthquake is given as an input in thesecond phase. An earthquake of 0.15g PGA isconsidered for the dynamic analysis. Fig. 2 shows
the acceleration –time history used in the analysis.
The complete slope model is divided into elements
to generate the finite element mesh. Slopedeformation and stresses distribution during theearthquake are the primary results in the dynamic
analysis.

Results of Static Analysis
The factor of safety of slope without nails instatic condition is found to be 1.116 which is far
below the safe value of FOS of 1.5 as shown in Fig.
4.

Fig. 4 Critical slip surface of slope without nails instatic condition (H = 20m, θ = 50⁰)

Fig. 2

Soil nailing technique is employed to stabilize
the slope. The nailed slope design is optimized withthe optimum values of nail length, nail spacing andnail inclinations. To find the optimum design, thenumerical model of nailed slope is analyzed for
different combinations of nail lengths from 0.5H to
0.75H, nail inclinations from 100 to 250 and nailspacing from 1m to 2m in both directions.

Earthquake acceleration-time history

The variation of stresses and displacements
during the earthquake are stored from the above twophases. These stresses are incorporated into
SLOPE/W to find FOS. In third phase, initial static
stresses are considered as parent analysis. The rangeof slip surface is once again specified in this phaselike in static condition. The factor of safety before
earthquake is obtained in this phase as an output. In
final phase, Equivalent linear dynamic analysis isconsidered as parent analysis. This analysis isperformed to find Factor of safety during theearthquake by Newmark’s deformation method in
SLOPE/W. The nailed slope with history nodes ispresented in Fig. 3

Effect of nail inclination
Initially, the nailed slope is analyzed for stability
at different nail inclinations of 100, 150, 200 and 250.
The length and spacing of nails are kept constantwith 0.7H and 1.5m respectively to find the
optimum nail inclination. Fig. 5 depicts the variationof FOS with nail inclination.
Static condition

Factor of safety

1.6

1.4
Seismic condition

1.2
10

15
20
Nail inclination, λ025Fig. 5 Influence of nail inclination on factor ofsafety (H = 20m, θ = 50⁰, l = 0.7H = 14m,
Sh=Sv=1.5m)
Fig. 3 Nailed slope with history nodes A, B, C and D
From the Fig. 5, it is observed that the nailed
slope with 150 nail inclination attains maximum FOS
of 1.577 which is more than minimum value of FOS(as per FHWA manual-2015) of 1.5. Hence nailinclination of 150 is considered as optimum nail

RESULTS AND DISCUSSION

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SEE - Bangkok, Thailand, Nov.11-13, 2019

inclination for the study.
Effect of nail length

Results of Dynamic Analysis
The dynamic analysis helps to analyze thebehavior of slope during earthquake. The variationof FOS, stresses distribution and displacements at
history nodes during the earthquake of 0.15g PGA
are studied in the dynamic analysis.

The nailed slope is further analyzed for stability
at different nail lengths of 0.5H, 0.55H, 0.6H, 0.65H,
0.7H, 0.75H and 0.8H. The nail inclination andspacing are kept constant at 150 and 1m to study theeffect of nail length on stability. The results arepresented in Fig. 6.
Static condition

1.4

Seismic condition

Factor of safety

1.8

Table 3 Results of static & Pseudo-static analysis
Slope
Minimum
Obtained FOS
recommended
FOS (FHWA
manual-2105)
Static Seismic
StaticPseudoanalysisstaticanalysis
Without
1.5
1.1
1.116
0.881
nails

1
0.5

0.6
0.7
Nail length (l= x*H)

0.8

Nailedslope

Fig. 6 Influence of nail length on Factor of Safety(H=20m, θ =500, λ=150, Sh=Sv=1m)

1.5

1.1

1.628

1.288

Shear stress variation during earthquake

The factor of safety increases with increase in
nail length from up to about 0.7H and then shows an
asymptotic variation. Based on the results presented
in Fig. 5 and Fig. 6, the nailed slope with 12m(0.6H) length nails at 150 inclination and 1m spacing
in both directions is considered as optimum with
FOS of 1.628 which is more than minimum
recommended value of FOS of 1.5. The critical slip
circle of nailed slope is with optimum parameters
are given in Fig. 7.

Variation of the maximum shear stresses
developed at history nodes during the earthquake of
PGA 0.15g in the slope without and with nails arepresented in Fig. 8 and Fig. 9 respectively.
NODE ANODE C

Maximum shear stress,
kPa

100

NODE BNODE D50

00

5Time, sec

10

Fig. 8 Variation of shear stresses at history nodes inthe slope without nails
NODE ANODE C

Fig. 7 Nailed slope with critical slip surface (l= 0.6H,
Sh = Sv = 1m, λ= 150)

NODE BNODE D

Maximum shear stress,
kPa

80

Results of Pseudo-Static Analysis

40

The stability of the nailed slope against an
earthquake of 0.15g PGA is analyzed with the helpof numerical model in SLOPE/W module. The
horizontal seismic coefficient, kh = 0.15 and verticalseismic coefficient, kv = 0.5kh = 0.075 are used toimport the seismic loading into the analysis. Table 3
presents the different values of FOS obtained in thepseudo static analysis.

005Time, sec

Fig. 9 Variation of shear stresses at history nodes
in nailed slope
624

10

SEE - Bangkok, Thailand, Nov.11-13, 2019

NODE ANODE CThe maximum shear stress is found at NODE A
which is located at bottom of the slope for both thecases of slope with and without nails. It deceases
from 98.69kPa to 79kPa by the inclusion of nails
into the slope. The minimum shear stress is found at
the top of the slope at NODE C with a value ofabout 10kN in the nailed slope.

Horizontal displacements,
m

0.06

0.03

Nail axial force
The distribution of nail axial force along thelength in both bottom and top nail row is depicted inFig. 10. The maximum nail axial force is developedin bottom nail row.
Bottom nail row

0
0

5

-0.03

10

Time, sec

Fig. 12 variation of horizontal displacements innailed slope (H= 20m, θ =500, l = 0.6H = 12m,
λ=150, Sh=Sv=1m)

Top nail row

Nailed slope experiences maximum horizontal
displacement of 60mm at NODE C which is at the
top of the slope. It experiences minimum horizontal
displacement of 28mm at the bottom of the slope at
NODE A.

60

30

Vertical displacements, m

Axial force, kN

NODE BNODE D

00

6Nail length, l(m)12Fig. 10 Variation of nail axial force along the length
Maximum nail axial forces in top and bottom
nail rows are 24.44kN and 50.38kN respectively.
Nail axial force increases along nail length. It
attains maximum in between the lengths of 0.6L
(7.2m) to 0.9L (10.8m) from nail head and thendecreases towards nail tip. Location of maximum
nail force is presented in Fig. 11.

NODE ANODE BNODE CNODE D

0.04
0.03
0.02
0.01
0
-0.01

0

5

10

-0.02
-0.03

Time, sec

Fig. 13 Vertical displacements of nailed slope (H=20m, θ =500, l = 0.6H = 12m, λ=150, Sh=Sv=1m)
The nailed slope experiences maximum andminimum vertical displacements of 32mm and
17mm at the top (NODE C) and bottom (node A) of
the slope respectively.
Results of Newmark’s deformation analysis
The variation of FOS during the total period of
the earthquake (PGA of 0.15g) are presented in Fig.
14
The nailed slope attains minimum FOS of 1.352
at 7th second of ground motion which is more than
the safe FOS of 1.1 (FHWA manual-2015). Hencethe slope with nails of length, 12m inserted at 15 0
inclination and 1m spacing is stable even during
earthquake of PGA 0.15g.

Fig. 11 Location of maximum nail axial force
The variation of horizontal displacements ofnailed slope at history nodes during the earthquakeof 0.15g PGA are presented in Fig. 12 and Fig. 13.

625

SEE - Bangkok, Thailand, Nov.11-13, 2019

in Residual Soils. Journal of Performance ofConstructed Facilities, Vol. 11, Issue 3, 1997,
pp. 105-112.
[5] Lok Man Chu and Jain-Hua Yin. Comparison ofInterface Shear strength of Soil Nails by both
direct shear box Tests and Pull-out Tests.
Journal of Geotechnical and Geo Environmental
Engineering, Vol. 131, Issue 9, 2005, pp. 10971107.
[6] Seo H. J., Lee and Loizos P., Net Load–
Displacement Estimation in Soil-Nail Pullout
Tests. Geotechnical Engineering, Vol. 170,
2017, pp. 534-547.
[7] Chia Cheng Fan and Jiun Hung Luo., Numerical
Study on the Optimum Layout of Soil Nailed
Slopes. Computers and Geotechnics, Vol. 35,
2008, pp. 585-599.
[8] Sivakumar Babu G. L. and Vikas Pratap Singh.,
2D Numerical Simulations of Soil Nail Walls.
Geotechnical and Geological Engineering, Vol.
28, 2009, pp. 299-309.
[9] Sahoo S., Manna B. and Sharma K. G., Stability
Analysis of Un-Reinforced and Reinforced Soil
Slopes. Geo-China, Vol. 257, 2016, pp. 74-81.
[10] Rawat S. and Gupta A. K., Analysis of a Nailed
Soil Slope Using Limit Equilibrium and Finite
Element Methods. International Journal of Geosynthetics and Ground Engineering, Vol. 2,
Issue 34, 2016, pp. 1-23.
[11] Ahmed Mohamed, Design Charts for Soil
Nailing. Research Gate, pp. 1-221.
[12] Jonathan D. and Thaleia T., Pseudo Static Slope
Stability Procedure. 5th International Conferenceof Earthquake Geotechnical Engineering, Issue
1, 2011, pp. 10-13.
[13] Kramer S. L., Chapter 10, Seismic Slope
Stability, Geotechnical Earthquake Engineering.
Pearson Education, 2018, Singapore.
[14] Rawath P. and Chatterjee K., Seismic Stability
Analysis of Soil Slopes Using Soil Nails.
Geotechnical Earthquake Engineering and Soil
Dynamics. Vol. 293, 2018, pp. 79-87.
[15] Shrestha S., Ravichandran N., Raveendra M.
and Attenhofer J. A., Design and analysis ofretaining wall backfilled with shredded tire andsubjected to earthquake shaking. Soil
Dynamics and Earthquake Engineering, Vol.
90, 2016, pp. 227-239.

Fig. 14 Variation of FOS with time in nailed slope

CONCLUSIONS
Following conclusions are made based on the results
obtained from the study.
1. The slope is stabilized by the inclusion of nailsof length 12m at 150 inclination and 1m
spacing in both directions. The FOS increases
from 1.116 to 1.628 after nailing.
2. From dynamic analysis, the horizontal andvertical displacements of nailed slope
decreases from top to the bottom of the slope.
The slope experiences displacement of 60mm
and 33mm in both horizontal and verticaldirections both at the top of the slope. The
inclusion of 12m nails with 150 inclinations at
1m spacing into the slope leads to 20%
reduction in shear stress.
3. The nailed slope is safe against an earthquakeof PGA, 0.15g with FOS of 1.288 and 1.35 inboth pseudo-static and dynamic analyses
respectively.

REFERENCES[1] Amit Prasanth and Mousumi Mukherjee, Soil
Nailing for Stabilization Steep slopes near
Railway Tracks. Research Gate, pp.1-203.
[2] Federal Highway Administration FHWA.
Reference manual, 7th Edition, U.S.A. 2015,
FHWA-NHI-14-007.
[3] Basudhar P. K., Anubhav and Lakshminarayana
M. R., Three-Dimensional Limit-Equilibrium
Stability Analyses of Slopes and Effect ofInclusion of Soil Nails. International Journal of
Geo-mechanics, Vol. 17, Issue 9, 2017, pp. 111.
[4] Wong I. H., Low B. K., Pang P.Y. and Raju
G.V.R., Field Performance of Nailed Soil Wall626

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SETTLEMENT OF SILTY SOIL UNDER SATURATION USINGMICRO SYNTHETIC FIBERS
Padmavathi, V.1 and Rao, P. N.2
Faculty, JNTUH college of Engg. Hyderabad, India;
2
Faculty, BITS Pilani, Hyderabad Campus, Hyderabad, India
1

ABSTRACT
Loose silty soils are often encountered by the foundation engineers working in semi-arid and arid areas of theworld. The silty soil has low water content and high void ratio. The problems concerning loose silty soil are
instability and considerable settlement due to minor changes in the water content, which can cause remarkabledamages to overlying structures. In dry condition, these soils are strong and appear to provide good support forfoundations. The large differential settlements reduce the serviceability of the civil structure and raise thefrequency and cost of rehabilitation. To avoid these kinds of settlements, it is necessary to identify the potential
settlements and apply mitigation measures. The soil samples are collected at faculty training center near block B,
IDBI campus, Gachibowli, Hyderabad, India. The present study is related to the prediction and identification ofcollapsible nature of silty soil and its behavior under saturation at various loading conditions and quantifying thedegree of settlement by finding the collapsible potential. The study also investigates the effect of micro synthetic
fibers on soil volume change.
Keywords: Silty soil, Micro synthetic fiber, Collapsible nature, Settlements, Oedometer test

and Ali (2017) conducted field and laboratory tests
on loose silty soil and found that field collapsible
potential values are 15% lesser than the laboratory
test values. Eldesouky (2017) reported that the
randomly distributed dry loose 0.5% fiber
reinforcement inclusion in sand increases the shear
strength and dilation of sand as compare to
unreinforced moist sand. Abbeche and Ziani (2014)
studied the effect of the hydraulic gradient and thevertical load on the collapsible potential of soils andconcluded that for 400 kPa of vertical load thecollapse reaches to maximum. Nassima Bakir (2017)
has conducted an experimental study to evaluate thecollapsible potential of loose silty soil with theaddition of glass fibers and concluded that 6%
addition of glass fibers reduces the collapse without
soil disorder. Ziani et al. (2019) studied thestabilization of collapsible soil using industrial waste
and natural pozzolan and found that large decreasein suction and higher degree of compaction byaddition of 5-7% of industrial waste and natural
pozzolan. Lin et al. (2016) depicted enhancing soft
subgrade soil with a sewage sludge ash/cement
mixture and nano-silicon dioxide. However, themain objective of the present study is to predict andidentification of collapsible nature and studying its
behavior under saturation at various loading
conditions and quantifying the degree of settlementby finding the collapsible potential of loose silts
with and without reinforcement of micro synthetic
fiber.

INTRODUCTION
The stability of superstructure is staticallyindeterminate problem when built on soil which hassudden settlement. The collapse of natural ground isdue to excessive settlement of soil and causes
destruction of structure. The collapse phenomenon
can occur in the case of natural soil like loose silts
and silty sands. Generally, collapsible soils aredefined as metastable soils that contain voids within
their soil structure, with grain sizes ranging from silt
to fine sand and fewer amounts of clay and salts. In
dry state, the cementation between particles is
responsible to support heavy loads. However, if thesoil becomes wet or saturated, the soil structure will
collapse due to the loss of binding strength between
soil particles. Experimental and theoretical studies
carried out to understand the uncertainties involvedin the phenomenon of collapse. The collapsible
potential is the difference in the axial strain at an
applied stress, after and before saturation. The
literature reveals that the majority of the research ison the collapse identification, predictions,mechanism and treatment methods. Momeni et al.
(2012) defined the collapsible soils are any
unsaturated soils generally characterized by thesudden and the considerable reduction in volume
that occurs when subjected to inundation underconstant stress. Ayeldeen et al. (2017) studied thecollapsible behavior of soil by adding biopolymers
under dry and curing conditions and found 20 to
30 % decrease in collapsible potential. Abdelmohsen
627

SEE - Bangkok, Thailand, Nov.11-13, 2019

EXPERIMENTAL INVESTIGATION

Specific gravity
Electric conductivity
Acid & salt resistance
Ignition point (◦C)
Thermal conductivity
Melt point (◦C)
Alkali resistanceMaterials used
The soil is collected from block B, Faculty
Training Centre, IDBI campus, Gachibowli,
Hyderabad, India. The soil properties are determinedand presented in the Table 1. The stabilizing
material used is micro synthetic fibers and thephysical and chemical properties are shown in
Table 2.

Oedometer tests are conducted to determine thesettlements under different applied stresses for bothsoils samples without and with fiber reinforcement.
The amount of micro synthetic fibers is taken as
0.1%, 0.3%, 0.5%, 0.7% and 1.0% by weight of thesoil. The soil samples for Oedometer test are
prepared and saturated at applied stress levels of 50,
100 and 200 kPa to observe the settlements. The test
series numbers and particulars are given in Table 3.
Three series of tests T1, T2 and T3 have been
conducted on soil and soil with fiber content. Three
Oedometer tests are conducted in T1 series on soil
only for 50, 100 and 200 kPa stress levels ofsaturation. The soil and micro synthetic fiber
combination tests are given in second series, T2 forfiber content of 0.1, 0.3, 0.5, 0.7 and 1% undersaturation at 200 kPa stress level. The third test
series, T3 is for optimum content of fiber 0.7%
varying with saturation stress levels of 50, 100 and
200 kPa. The shear strength is also obtained bydirect shear tests for untreated and treated soil with
0.1%, 0.3%, 0.5%, 0.7% and 1.0% fiber content.

Testing Methodology
The dry unit weight of the soil is maintained as
12.8 kN/m3, which is about 67% of the maximum
dry unit weight of the soil. The percentage of microsynthetic fiber in the testing varied from 0.1 to 1.0
by weight of the soil. It is very difficult to mix morethan 1.0 % fiber content in preparing the soil
samples due to balling effect.
Table 1 Physical Properties of soil used
S. No.
1

2
3
4
5
6
7
8
9

Property
Description
GRAIN SIZE DISTRIBUTION(% Passing)Gravel (>4.75 mm)05
Coarse Sand08
(2.0 - 4.75 mm)
Medium Sand22
(0.425 - 2.0 mm)
Fine Sand
23(0.075 – 0.425 mm)
Silt (0.075 – 0.002 mm)
42
Clay (<0.002 mm)
0
Liquid limit (%)
33
Plastic limit (%)
Non Plastic
IS Classification
SM
Specific gravity
2.64
Maximum Unit Weight
19.3(kN/m3)
Optimum moisture content
13(%)
Cohesion (kPa)0Internal friction (degrees)
31

Table 3 Oedometer test program

Table 2 Physical and Chemical Properties of Micro
Synthetic Fiber
Property
Diameter of fiber (mm)Fibertensilestrength(MPa)
Elastic modulus (MPa)Melting temperature (◦ C)
Fiber length (mm)Type
Absorption

0.91
Low
High
37
Low
324
alkali proof

Value
0.05
350
1000
165
12
fine monofilament
Nil628

T1 Samples with compacted unit weight of
12.8 kN/m3
S1 Saturated at 50 kPa pressure in
Oedometer (T1S1)
S2 Saturated at 100 kPa pressure in
Oedometer (T1S2)
S3 Saturated at 200 kPa pressure in
Oedometer (T1S3)
T2 Samples with compacted unit weight of
12.8 kN/m3 with micro synthetic fiber
S1 0.1 % fiber Saturated at 200 kPa
pressure in OedometerS2 0.3 % fiber Saturated at 200 kPa
pressure in OedometerS3 0.5 % fiber Saturated at 200 kPa
pressure in OedometerS4 0.7 % fiber Saturated at 200 kPa
pressure in OedometerS5 1.0 % fiber Saturated at 200 kPa
pressure in Oedometer
T3 Samples with compacted with micro synthetic
fiber of 0.7%
S1 Saturated at 50 kPa pressure in
Oedometer
S2 Saturated at 100 kPa pressure in
Oedometer
S3 Saturated at 200 kPa pressure in
Oedometer

SEE - Bangkok, Thailand, Nov.11-13, 2019

It is observed that the collapsible potential values
are progressively decreased with addition of fiber
content and the problem of collapse is reduced fromRESULTS AND DISCUSSION

0

Volumetric Strain (%)

Dry Unit Weight (kN/m3)

The effect of micro synthetic fibers on settlement
or collapsible nature of loose silts upon saturation isobserved. The increase of fiber content in silty soils
from 0.1 to 1.0 % causes a reduction in the dry unit
weight as shown in Fig. 1. This reduction is due tothe less weight of the fiber content compared to thereplaced soil.
1.3

1.25

Applied Stress (kPa)
100

10

1000

6

12
50 kPa100 kPa

200 kPa

1.2
Fig. 2 Volumetric Strain corresponding to 50,
100 and 200 kPa Saturation

1.15
0

0.5
Percentage of Fiber (%)

1
Applied Stress (kPa)

Fig.1 Dry Unit Weight vs Percentage Fiber Content

10

100

1000

0

Volumetric Strain (%)

The oedometer test program is mentioned inTable 3. First test series is nomenclature as T1S1,
T1S2 and T1S3 upon saturation of silty soil at 50, 100
and 200 kPa respectively for a dry unit weight of
12.8 kN/m3 and the results are shown in Fig. 2.
There is a sudden decrease in volumetric strain
corresponding to stress at which saturation takes
place, indicating collapsible nature of the soil. The
axial strain in oedometer test is same as volumetricstrain as the area is constant. The collapsible
potentials are 7.05, 7.15 and 7.5% corresponding tosaturation at 50, 100 and 200 kPa applied stresses
respectively. The collapsible potentials are almost
same even though the applied stress changes from50 to 200 kPa. It is observed that the settlement interms of collapsible potential of silty soil ismoderately severe. Hence, the stabilization isrequired and used micro synthetic fibers in present
study to reduce the volumetric strains or settlements.

6

12
1

0.7

0.5

0.3

% fiber 0.1

Soil

Fig. 3 Effect of Percentage Fiber Content in Soilon Volumetric Strain

Soil is mixed with micro synthetic fibers and thetest series T2 is conducted. Fig. 3 shows theoedometer test results, when the saturation is done at
an applied stress of 200 kPa with 0.1, 0.3, 0.5, 0.7
and 1.0 % fiber content. The collapsible potential at
200 kPa applied stress is observed for the treatedsamples and found as 4.3, 2.8, 1.35, 1.0 and 0.9 %respectively for 0.1, 0.3, 0.5, 0.7 and 1.0 % fiber
content in the soil.

629

Collapsible Potential (%)

SEE - Bangkok, Thailand, Nov.11-13, 2019

The direct shear test results for untreated andtreated soil samples for the 12.8 kN/m3 unit weight
and the fiber content of 0.1, 0.3, 0.5, 0.7 and 1.0%
fibers are presented in Fig. 6. The angle of internal
friction of untreated soil is 31. The shear strength of
the treated soil increases with increase in percentage
of fiber content. The increase in shear strength is due
reinforcement effect of fiber in soil. There is a
development of interlocking mechanism of fiber athigher percentage of fiber content. The angle ofinternal friction increases with increase in fiber
content in soil as shown in Fig. 7. The angle ofinternal friction corresponding to treated soil with
0.1, 0.3, 0.5 and 0.7% fiber is 32.5, 34.5, 36.0 and
36.5 respectively. The treated soil with 0.7% fiber
content shows interlocking of soil and fiber content
apparent cohesion or interlocking stress of 2.5 kPa
where as it is 14 kPa (Fig. 8) for 1.0% fiber content
and angle of internal friction is reduced to 35.

8
TroubleModerate Trouble

4

No Trouble000.5 (%)
Fiber Content

1Fig. 4 Percentage of Fiber vs Collapsible
Potential
moderate severity to no trouble. This behavior canbe attributed to the reinforcing mechanism of fibers
which also reduces the voids in treated soil bybinding action of soil particles and fibers.

200

Shear Stress (kPa)

Fig. 4 shows the variation of collapse potential
with percentage of micro synthetic fiber. For a fiber
content of 0.7%, the severity degree changes from"moderate Trouble" to "no trouble".
The collapsible potential is observed as 1.0% fortreated soil sample with 0.7% of fiber content
saturated at 200 kPa stress level. Hence, 0.7% fiber
content is considered as optimum percentage of fiber
for further testing of test series T3. Collapsible
potential values are obtained for 50 kPa and 100 kPa
stress level saturations with optimum fiber content.

150

100

50

0
0

10

Applied Stress (kPa)
100

50
100
150
Normal Stress (kPa)
Untreated Soil
Soil+0.1% fiber
Soil+0.3% fiber
Soil+0.5% Fiber
Soil+0.7% Fiber
Soil+1.0% Fiber

1000

0

200

Fig. 6 Shear Strength Variation with increase in
Fiber Content

2.5

38.5

Angle of Internal
Friction (°)

Volumetric Strain (%)

Fig. 5 represents the applied stress verses
volumetric strain. The collapsible potentials are 0.3
and 0.75 and 1.0 % respectively for 50, 100 and 200
kPa stress level saturations.

5
50 kPa100 kPa

200 kPa

Fig. 5 Effect of Applied Stress in Stabilization
Based on collapsible potential obtained for thetreated soil, the final settlement is less when thecompaction is done at lower stress level (50 kPa)
than when done at higher stress levels 100 and 200
kPa.

35
31.5
28
0

630

0.5
Fiber Content (%)

1

SEE - Bangkok, Thailand, Nov.11-13, 2019

Cohesion (kPa)

Fig. 7 Effect of Fiber Content on Angle of Internal
Friction of Treated Soil

REFERENCES[1] Abbeche, K. and Ziani, H. (2014). “Effect Studyof the Hydraulic Gradient and the Vertical Loadon the Collapse Potential of Soils”, Proceedingsof Geo-Shanghai, Soil Behaviour andGeomechanics, pp. 173-183.
[2] Abdelmohsen, H. H. and Ali, N. A. (2014).
“Practical Engineering Behavior of Egyptian
Collapsible Soils, Laboratory and In-situ
Experimental Study”, International Conference
on Advances in Structural and GeotechnicalEngineering, pp. 1-7.
[3] Ayeldeen, M., Abdelazim, N., Mostafa ES and
Masaki, K. (2017). “Enhancing MechanicalBehaviors of Collapsible Soil using Two
Biopolymers”, Journal of Rock Mechanics andGeotechnical Engineering, Vol. 9, No. 2, pp.
329-339.
[4] Eldesouky, H. M., Morsy, M. M. and Mansour,
M. F. (2017). “Fiber-reinforced Sand Strengthand Dilation Characteristics”, Ain Shams
Engineering Journal, vol. 7, No. 2, pp. 517–
526.
[5] Lin, D. F., Luo, H. L., Chen, C. T., and Cai, M.
D. (2016). “Study Properties of Soft Subgrade
Soil Stabilized by Sewage Sludge/Lime andNano-SiO2.” Geomechanics and Engineering,Vol. 10, No. 6, pp.793-806.
[6] Momeni, W.M., Shafiee, A.,Heidari, M., Jafari,M.K., Madhavifar M.R .(2012). “Evaluation of
Soil Collapse Potential in Regional Scale”,
Natural Hazards, Vol. 64, pp 459–479.
[7] Nassima Bakir, Khelifa Abbeche and Gerard
Panczer, (2017), “Experimental Study of theEffect of the Glass Fibers on Reducing Collapseof a Collapsible Soil”, Geomechanics andEngineering, vol. 12, pp. 71– 83.
[8] Ziani, H., Abbeche, K., Messaoudene, I. andAndrade Pais, L. J. (2019). “Treatment of
Collapsible Soils by Additions of Granulated
Slag and Natural Pozzolan”, KSCE Journal of
Civil Engineering, Vol. 23, No. 3, pp. 10281042.

18

9

0
0

0.5
Fiber Content (%)

1

Fig. 7 Effect of Fiber Content on Cohesion ofTreated Soil
CONCLUSIONS
The following conclusions are made based on
the experiment results obtained from the laboratory
tests.
1. The soil is Silty Sand with no percentage ofclay. The soil causes ‘trouble’ to the foundation as
the collapsible potential values lie between 5 and 10.
2. The optimum content of micro synthetic
fiber is obtained as 0.7% from compaction test.
3. At 12.8 kN/m3 unit weight of soil atsaturation under 200 kPa applied stress level, with
0.7% of micro synthetic fiber the collapsible
potential of soil is 1.0, which comes under ‘notrouble’ zone.
4. For the soil with unit weight of 12.8 kN/m3
and 0.7% of micro synthetic fiber, the settlements
are calculated at saturation of 50, 100 and 200 kPa
stresses as 0.3, 0.75 and 1%. The total settlement of
the soil reduces, when the saturation is done at lower
stress level (50 kPa) than higher stress levels 100
and 200 kPa.
5. The shear strength of the soil increases withincrease in fiber content due to reinforcement andinterlocking effect of fibers in soil.
ACKNOWLEDGEMENTS
The authors acknowledge Central Public Works
Department (CPWD), India and Industrial
Consultancy Services of JNTU College ofEngineering, Hyderabad, India.

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Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

GROUND IMPROVEMENT USING GEOSYNTHETICS~ A LITERATURE REVIEW
1Mohamed Eltaher1, Zakaria Hossain1, Jim Shiau2, and Hajime Takami3
Graduate School of Bioresources, Mie University, Japan; 2School of Civil Engineering and Surveying,
University of Southern Queensland, Australia; 3Tsuchiya TSCO Co., Ltd., Japan

ABSTRACT
Owing to the rapid growth of population and city urbanization, the need for more development of
infrastructures e.g. highways, airports, railways, bridges, and many other engineered structures demands a varietyof construction activities. Engineers have to be able to put in place new methods, techniques, and materials forstructure sitting on the existing weak and soft soils by improving their strength and other properties. Nowadays,in addition to soil compaction, soil replacement is a convenient ground improvement technique in the construction
processes with the aims of increasing the bearing capacity of the soil and reducing the settlement. But it may not
be the best financial or technical option for a specific project while in the same time there was a great opportunity
in many ways to improve the ground performance e.g. mechanical stabilization, preloading stabilization, sanddrain stabilization, physical and chemical modification stabilization, addition and confinement modification
stabilization and soil reinforcement using geosynthetics. This paper presents a review on the application ofgeosynthetics in construction engineering. Various available commercial types of geosynthetics and mainfunctions in field application are discussed with respect to the reinforcement and separation functions, especiallyin pavement construction. Finally, the environmental and financial benefits of using geosynthetics as a ground
improvement technique are discussed.
Keywords: Geosynthetics, Ground Improvement Technique, Reinforcement, Pavement.

INTRODUCTION
TYPES OF GEOSYNTHETICS
In fact, Geosynthetics is a generic namerepresenting a broad range of planer and threedimensional products manufactured from synthetic
polymeric materials. As shown in table 1, Synthetic
polymers used in the manufacturing of geosynthetics
are generally derived from crude petroleum oils but
also rubber, fiberglass, basalt rock in addition to
many other materials can be used for manufacturing
geosynthetics e.g. natural fabrics but recently organic
natural fabrics are not used due to the rapid
decomposition [1,2].
Table 1 Materials commonly
manufacturing of geosynthetics

used

for

The most common geosynthetics are geotextiles,
geotextile-related products (GTP) as geogrids,
geonets, geomembranes, geocomposites, etc. inaddition to many other types which are used incontact with soil, rock and/or any other civilengineering-related material as an integral part ofman-made projects, structures or systems [3]. And
they are briefly described below.
Geotextile

theType of Material

Abbrev.

Polypropylene (polymer)
Polyester (polyethylene terephthalate) (polymer)
Polyvinyl chloride (polymer)
Polyamide (polymer)
Polystyrene (polymer)
Polyethylene (polymer):
Low-Density Polyethylene
Very-Low-Density Polyethylene
Linear Low-Density Polyethylene
Medium Density Polyethylene
High-Density Polyethylene
Chlorinated Polyethylene
Chlorosulfonated Polyethylene
In addition to many other materials

PP
PET
PVC
PA
PS

It is a planer, permeable, polymeric textile productin the form of a flexible sheet.
Currently available geotextiles are classified into
four main categories based on the manufacturing
process as woven, nonwoven, knitted, and stitchedgeotextiles [1,4,5].
As shown in Fig. 1, Woven geotextiles areproduced by interlacing, usually at the right angles,
two or more sets of yarns (made of one or several
fibers) or other elements using a conventional
weaving process with a weaving loom.
Nonwoven geotextiles like in Fig. 2, are produced
from directionally or randomly oriented fibers into aloose web by bonding with partial melting, needle
punching, or chemical binding agents (glue, rubber,latex, cellulose derivative, etc.).

LDPE
VLDPE
LLDPE
MDPE
HDPE
CPE
CSPE
----

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Stitched geotextiles are one type of geotextile inwhich fibers or yarns or both are interlocked/bonded
by stitching or sewing.
Geogrid
It is a planer, polymeric product consisting of amesh or net-like. Where a regular open network ofintersecting tensile-resistant elements, called ribs,
integrally connected at the junction. The ribs can belinked by bonding, interlacing, or extrusion. So, theresulting geogrids are respectively called bonded
geogrids (Fig. 4), woven geogrids (Fig. 5) andextruded geogrids [8,9].

Fig. 1 Typical Woven Geotextile [6,7]Fig. 4 Typical Bonded Geogrid [7]Fig. 5 Typical Woven Geogrid [7]Fig. 2 Typical Nonwoven Geotextile [6,7]The extruded geogrids are classified into two
categories based on the direction of stretching during
their manufacture process as uniaxial extruding
geogrids and biaxial extruding geogrids [10].
As shown in Fig. 6, Extruded uniaxial geogrids
produced by the longitudinal stretching of a regularly
punched polymer sheet, therefore it possesses a muchhigher tensile strength in the longitudinal direction
than the tensile strength in the transverse direction.

Fig. 3 Typical Knitted Geotextile [6,7]Knitted geotextiles are produced by interloping
one or more yarns (or any other elements) together
with a knitting machine, instead of a weaving loom,
see Fig. 3.

Fig. 6 Typical Extruded Uniaxial Geogrid [7]633SEE - Bangkok, Thailand, Nov.11-13, 2019

Extruded biaxial geogrids produced by stretchingin both the longitudinal and transverse directions of aregularly punched polymer sheet, therefore it
possesses equal tensile strength in both directions
longitudinal and transverse, see Fig. 7.

The material may be polymeric or asphaltic or a
combination thereof. The term barrier applies when
the geomembrane is used inside an earth mass while
the term liner is usually reserved for cases where thegeomembrane is used as an interface or a surface
revetment.
Geocomposite
It is a term applied to the product that is assembled
or manufactured in laminated or composite form fromtwo or more material, of which one at least is
geosynthetic, which, in combination performs a
specific function(s) more effectively than when used
separately, as illustrated in Fig. 10 [12].

Fig. 7 Typical Extruded Biaxial Geogrid [7]GeonetAs Fig. 8 shows, it is a planer, polymeric productconsisting of a regular dense network of integrally
connected parallel sets of ribs overlaying similar sets
at various angles. At first glance, geonets appear
similar to geogrids, however, geonets are different
from geogrids, not mainly in the materials or theirconfiguration only but also in their functions toperform the in-plane drainage of liquids or gases [11].

Fig. 10 Typical Geocomposite [13]GeocellFig. 11 shows a three-dimensional, permeable,
polymeric honeycomb or web structure, assembled
from geogrids and special bodkins couplings intriangular or square cells or produced using strips ofneedle-punched Polyester or solid High-Density Poly
Ethylene (HDPE) known as geocell.

Fig. 8 Typical Geonet [11]Fig. 11 Typical Geocell [14]Geomembrane
GeomeshIt is a planer, relatively impermeable, synthetic
sheet manufactured from materials of low
permeability to control fluid migration in a project asa barrier or liner, see Fig. 9.

It is a geosynthetic or geo-natural generally withplaner woven structure having large pore sizes, whichvary from several millimeters to several centimeters
for use in mainly erosion control works, see Fig. 12.

Fig. 9 Typical Geomembrane [7]Fig. 12 Typical Geomesh [7]634SEE - Bangkok, Thailand, Nov.11-13, 2019

GeomatAs Fig. 13 shows, it is a three-dimensional,
permeable, polymeric structure made of coarse andrigid filaments bonded at their junctions used toreinforce roots of vegetation such as grass and small
plants and extend the erosion control limits ofvegetation for permanent installation.

Fig. 16 Typical Geopipe [7]Geofoam
It is a polymeric material manufactured by theapplication of the polymer in semi-liquid form
through the use of a foaming agent to have alightweight material in slab or block form with highvoid content for use as a lightweight fill, thermal
insulators, and drainage channels. Samples are shownin Fig. 17.

Fig. 13 Typical Geomat [7]Geostrip
It is a polymeric material in the form of a strip
with different width illustrated in Fig. 14.

Fig. 17 Typical Geofoam [16]For convenience in making drawings or diagramsof geosynthetic applications with clarity,
Geosynthetic products can be represented byabbreviations and/or graphical symbols asrecommended by the International Geosynthetics
Society (IGS) described in table 2.

Fig. 14 Typical Geostrip [15]Geospacer
It is a three-dimensional polymeric molded
structure consisting of cuspidated or corrugated plateswith large void spaces, see Fig. 15.

Table 2 Abbreviations and graphical symbols ofgeosynthetic products
Abbrev.
GTX
GGR
GNT
GMB
Fig. 15 Typical Geospacer [7]GCD
GeopipeGCL

As shown in Fig. 16, It is a plastic pipe (smoothor corrugated with or without perforations) placed
beneath the ground surface and subsequently
backfilled.

GCE
GMA
635

Geosynthetic
Product
Geotextile
Geogrid
GeonetGeomembrane
Geocomposite
drainwith geotextile
on both sides
Geocomposite
clay liner
Geocell
GeomatGraphical Symbol

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Continued
GST
Geostrip
GSP
Geospacer
GBL
Geoblanket
GBA
GeobarSurficial
GEC
geosynthetic
erosion control
Electrokinetic
GEK
geosynthetic
GMT
Geomattress
Note: as recommended by the
Geosynthetics Society (IGS) [17].

Geocells perform the confinement function
significantly by preventing the lateral movements ofthe soil volumes confined inside. In the meanwhile,
separation could be achieved using geotextiles andgeocomposites which prevent the contamination
between two different soils or materials with different
granulometry. In addition to that preventing
mechanical damage to structures and materials as aprotection function is a direct result of using
nonwoven geotextiles, geonets, and geocomposites.
A geosynthetic may function as a filter(performing the filtration function) that allows foradequate fluid flow with limited migration of soil
particles across its plane over a projected service
lifetime of the application under consideration. In the
meanwhile, if a geosynthetic allows for adequate
fluid flow with limited migration of soil particles
within its plane from surrounding soil mass to various
outlets over a projected service lifetime of theapplication under consideration, it is said to performthe drainage function. On the other hand, if ageosynthetic act like an almost impermeable
membrane to prevent the migration of liquids or gases
over a projected service lifetime of the application
under consideration, it is said to perform the fluid
barrier function.
Because of their structure geonets andgeocomposites can be used to collect and transportrain waters, groundwaters, and other fluids or gas so
usually, they are used to perform the drainage
function. On the other hand, filtration function could
be performed using geotextile and geocomposites
because they retain the soil subject to hydrodynamic
forces and allow the passage of fluids [10,12].
Furthermore, geomembranes and geocomposites
prevent or limit the migration of fluids. So, engineers
use these products for their waterproofing function.
But in the case of erosion control applications, it ispreferable to utilize geomats and geocells which
prevent the detachment and transport of the soil
caused by meteoric events and allow the vegetation
growth. The coming few paragraphs will discuss thefunctions of reinforcement and separation that can be
performed by some commercially available types ofGeosynthetics.

International

FUNCTIONS OF GEOSYNTHETICS
Geosynthetic products have numerous application
areas in civil engineering. It could be applied forconstruction of transportation infrastructures e.g.
highways, railroads, airports, and ports., water
resources management infrastructures e.g. dams,
canals, surface and subsurface drainage systems.,
environmental protection infrastructures e.g. sanitary
landfills, coastal erosion control measures., slopes
stabilization e.g. natural slopes, embankments
stabilization, retaining walls., and/or many otherapplication areas. That is because of geosynthetics
usually expected to serve more than one function
during its performance life [12,18,19].
The selection of a specific geosynthetic for any
field application is highly governed by the function(s)to be performed by the geosynthetic in that specificapplication. Reinforcement, Separation, Filtration,
Drainage, Fluid barrier, and/or Protection are thebasic geosynthetic functions when it used in contact
with soil, rock and/or any other civil engineeringrelated material [10,12,18]. Reinforcement for walls
and steep slopes in addition to base reinforcement
functions using mono-directional and threedimensional geogrids, woven and nonwoven
geotextiles and geocomposites have been achieved
and utilized in many projects mainly because of theirability to improve the mechanical performances of thesoil adding tensile strength, improve the bearing
capacity, reduce the settlements and the formation ofholes and ruts.
Separation function is performed when thegeosynthetic has the ability to prevent intermixing ofadjacent dissimilar soils and/or fill materials during
construction and over a projected service lifetime of
the application under consideration.
In some applications, a geosynthetic layer isneeded as a localized stress reduction layer to preventor reduce local damage to a geotechnical system.
Therefore, a geosynthetic, placed between twomaterials, performs the protection function as it
alleviates or distributes stresses and strainstransmitted to the material to be protected against any
damage.

Reinforcement
A geosynthetic performs the reinforcement
function by improving the mechanical properties of asoil mass as a result of its inclusion. When soil andgeosynthetic reinforcement are combined, acomposite material, ‘reinforced soil’, possessing highcompressive and tensile strength (and similar, inprinciple, to the reinforced concrete) is produced. In
fact, any geosynthetic applied as reinforcement has
the main task of resisting applied stress or preventing
inadmissible deformations in geotechnical structures.
[1] In this process, and as shown in Fig. 18 the636

SEE - Bangkok, Thailand, Nov.11-13, 2019

geosynthetic act as a tensioned member (a structuralelement that is subjected to axial tensile forces.)
coupled to the soil/fill material by friction, adhesion,interlocking, containment or confinement and thus
maintains the stability of the soil mass [12].

2.

A tensioned member, which supports not only aplanar load but also a normal load, see Fig. 21.
Soil + inextensible
reinforcement
Soil + extensible
reinforcement
soil only

Confinement and interlocking
35
30
25
Soil
Geosyntheti
Geosynthetic

StressFriction
betweensoil andreinforcement

Tensile
Force

20
15
10

Soil

5

0
0

5

10

15

20

25

30

35

40

StrainConfinement and interlocking

Fig. 19 Stress-Strain relationship for soil only andreinforced soils

Fig. 18 Basic mechanism in the reinforcement
function
Different concepts have been developed to define
the basic mechanism of reinforced soils. The effect ofinclusion of relatively inextensible reinforcements(such as metals having a high modulus ofdeformation) in the soil can be explained using either
an induced stresses concept [20] (Schlosser and Vidal,
1969) or an induced deformations concept [21](Bassett and Last, 1978). According to the induced
stresses concept, the tensile strength of thereinforcements and friction at soil-reinforcement
interfaces give an apparent cohesion to the reinforced
soil system. The induced deformations concept
considers that the tensile reinforcements involve
anisotropic restraint of the soil deformations [2,18].
The behavior of the soil reinforced with extensible
reinforcements such as geosynthetics does not fallwithin these concepts, see Fig. 19. And the difference,
between the influences of inextensible and extensible
reinforcements, is significant in terms of loadsettlement behavior of the reinforced soil system. The
soil reinforced with extensible reinforcement (termed
ply-soil by McGown and Andrawes (1977) [22]) has
greater extensibility and smaller losses of post-peakstrength compared to soil alone or even soil
reinforced with inextensible reinforcement (termed
reinforced earth by Vidal (1969)). [4,23]
However, some similarity between ply-soil andreinforced earth exists in that they inhibit thedevelopment of internal tensile strains in the soil anddevelop tensile stress. Fluet (1988) subdivided thereinforcement function into the following two
categories [24]:1. A tensile member, which supports a planner load,
see Fig. 20.

Fig. 20 Reinforcement function as a tensile member[24]

Fig. 21 Reinforcement function as a tensioned
member [24]Jewell (1996) considered not two but threemechanisms for soil reinforcement [2], because when
the geosynthetic works as a tensile member it might
be due to two different mechanisms: shear andanchorage. Therefore, the three reinforcing
mechanisms, concerned simply with the types of loadthat is supported by the geosynthetic, are:
1. Anchorage also called pullout: The geosynthetic
supports a planar load due to its pullout from the
soil.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

2. Shear, also called sliding: The geosynthetic
supports a planar load due to slide of the soil overit.
3. Membrane: The geosynthetic supports both planarand normal load when placed on a deformable soil.

CONCLUSIONS
From this review it can be concluded that theusage of geotextiles, geotextile-related products(GTP) and the other types of geosynthetics for ground
improvement is technically viable and cost-effective
solution for soils which are weak in strength in orderto make them more suitable for construction because
reinforcement is the main function which all types ofgeosynthetics provide.
The usage of various types of geosynthetics havebeen tested and its use has been proven in the recent
past years for a variety of infrastructure projects e.g.
highways, airfields, ports, railways, dams, slope
stabilization, tunneling, and other infrastructures
facilities. Considering that the selection of a specificgeosynthetic is highly governed by the functions to be
performed in that specific application.
Ground improvement using geosynthetics has
been proved not only to enhance infrastructure quality,
performance, and durability but also reduce theinfrastructure life-cycle cost, construction andmaintenance durations in addition to amounts ofnatural recourse used which leads to reducing theenvironmental impacts of constructing andmaintaining these projects.
These types of geosynthetics have been usedworldwide for reinforcement, separation, filtration,
drainage, fluid barrier, and/or protection with avariety of soils e.g. loose sand, silts, clays, and weakrocks. But still, a geosynthetic which suits for routine
application, perhaps not available. For future
development, it is believed that the characterizationof new types of geosynthetics and understanding ofsoil-geosynthetic interface behavior under different
kinds of tests should be explored.

Separation
In many cases, there is a bad need for separation
between two soils or between soil and any othermaterial. The pavement is a clear example since there
are deferent layers of aggregate to be separated fromeach other, as shown in Fig. 22 (subgrade, subbase,
base and surface courses) in addition not to permit theloosening of one layer into another [10,18].
And because of the contamination of aggregatebase material with the underlying soft subgrade soil
is one of the major causes of roadways constructed
over soft foundations failure, the geosynthetic isplaced between the two different particle-size
distributions layers (dissimilar materials) basicallyfor maintaining the functionality and integrity of thetwo layers which is illustrated in Fig. 23 [18,25].
This contamination occurs because of two main
reasons, the first is the penetration of the baseaggregate into the weak subgrade soil due to localized
bearing capacity failure under wheel-load induced
stresses and the second reason is the intrusion of thefine-grained subgrade soils into the base aggregate
because of pumping or subgrade weakening due toexcess pore water pressure. This results in inadequate
structural support due to reduced shear strength anddecreased hydraulic conductivity in addition to a
reduced base layer thickness, leading to premature
failure of the roadway [12,25].

ACKNOWLEDGMENTS
Thanks to Japan International Cooperation
Agency (JICA), African Business Education
Initiative for collaboration with International
Environment Conservation Lab, Graduate School of
Bioresources, Mie University, School of Civil
Engineering and Surveying, University of Southern
Queensland, Australia, Egyptian Airports Company(EAC) and Tsuchiya TSCO Co., Ltd. for theopportunity which they gave me to proceed in thisresearch.

Fig. 22 Roadway designed without geosynthetic

REFERENCES[1] Hossain M.B., Hossain M.Z., and Sakai T.,
Interaction Properties of Geosynthetic withDifferent Backfill Soils. International Journal of
Geosciences, 3, 2012, pp.1033-1039[2] Jewell R.A., Soil Reinforcement with Geotextiles,
CIRIA, Thomas Telford, 1996.
[3] Hossain M.B., Hossain M.Z., and Sakai T.,

Fig. 23 Roadway designed with geosynthetic
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Interface Behaviour of Basalt Geosynthetic with
Sand Using Direct Shear Device. Proceedings ofthe 1st International Conference on Geotechnique,
Construction Materials and Environment, Mie,
21-23 November 2011, pp.191-196.
[4] Islam M.A., Hossain M.Z., Shiau J., andRachmawati S. H., Characterization ofEnvironment-Friendly Geotextiles Embedded in
Soil Under Pullout Test. Proceedings of the 7thInternational Conference on Geotechnique,
Construction Materials and Environment, Mie,
21-24 November 2017, pp.36-42.
[5] Juran I. and Chen C.L., Soil-Geotextile Pull-Out
Interaction Properties: Testing and Interpretation
Transportation Research Record 1188, 1988, pp.
37- 47.
[6] Koerner R. M., Designing with Geosynthetics,
Fifth Edition, Pearson Prentice Hall, Upper
Saddle River, New Jersey, 2005.
[7] Shukla S.K. and Yin J.H., Fundamentals of
Geosynthetic Engineering, Taylor and Francis
Group, London, UK, 2006.
[8] Moayedi H., Kazemian S., Prasad A., and Huat B.
B. K., Effect of Geogrid Reinforcement Locationin Paved Road Improvement. Electronic Journalof Geotechnical Engineering, EJGE, Bund. P, Vol.
14, 2009, pp.1-11.
[9] Lee M.S., Choi Y.S., and Prezzi M. Quality
Assessment of Geogrids Used for Subgrade
Treatment. Publication FHWA/IN/JTRP-2012/27.
Joint Transportation Research Program, Indiana
Department of Transportation and Purdue
University, Indiana, 2012, pp. 1-28.
[10] Hufenus R., Rueegger R., Banjac R., Mayor P.,
and Springman S.M., Brӧnnimann R., FullScale Field Tests on Geosynthetic Reinforced
Unpaved Roads on Soft Subgrade. Geotextiles
and Geomembranes, 24, 2006, pp.21-37.
[11] Jeon H.Y., Short-Term Compressive Properties
and Transmissivity of Geonets. Korean Textile
Engineering Association, Vol. 51, Issue 2, 2014,
pp. 96-100[12] Zornberg J. G., Functions and Applications ofGeosynthetics
in
Roadways.
ProcediaEngineering, 189, 2017, pp.298-306.
[13] Nicholson P. G., Soil Improvement and Ground
Modification Methods, 2015[14] Mehrjardi G. T. and Motarjemi F., Interfacial
Properties of Geocell-Reinforced Granular Soils,
Geotextiles and Geomembranes, 46, 2018, pp.
384–395.

[15] Luo Y., Leshchinsky D., Rimoldi P., Lugli G.,
and Xu C., Instrumented MSE Wall Reinforced
with Polyester Straps, DCT 250, Delaware
Center for Transportation, University of
Delaware, Delaware, 2015.
[16] Khan M. I. and Meguid M. A., Experimental
Investigation of the Shear Behavior of EPS
Geofoam,International
Journalof
Geosynthetics and Ground Engineering, 2018,
pp. 4-12.
[17] Recommended Descriptions of Geosynthetics
Functions, Geosynthetics Terminology, andGraphical Symbols, International Geosynthetics
Society, 5th Ed. 2009, pp. 1-31
[18] Perkins S.W., and Ismeik M., A Synthesis and
Evaluation of Geosynthetic-Reinforced Base
Layers in Flexible Pavements: Part I.
Geosynthetics International, Vol. 4, No. 6, 1997,
pp.549-604.
[19] Mishra B., A Study on Ground Improvement
Techniques and Its Applications. International
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2016, pp.72-86.
[20] Schlosser F., and Vidal H., Reinforced Earth.
Bulletin de Liaison des Laboratories des Ponts
et Chaussees, No. 41, France, 1969.
[21] Bassett R.H., and Last N.C., Reinforcing Earth
Below
Footings
andEmbankments.
Proceedings of the Symposium on EarthReinforcement, ASCE, New York, 1978, pp.
202–231.
[22] McGown A. and Andrawes K.Z., The Influenceof Nonwoven Fabric Inclusions on The StressStrain Behavior of a Soil Mass. Proceedings ofthe International Conference on the Use of
Fabrics in Geotechnics, Paris, 1977, pp. 161–
166.
[23] Vidal H., The Principle of Reinforced Earth.
Highway Research Record, No. 282, 1969, pp.
1–16.
[24] Fluet, J.E., Geosynthetics for Soil Improvement:
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Geosynthetics for Soil Improvement, Tennessee,
1988, pp. 1–21.
[25] Perkins S.W., and Ismeik M., A Synthesis and
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pp.605-62

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Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STATICAL MODEL OF THE PIEZOELECTRIC SELFADJUSTINGGYROSCOPE-ACCELEROMETER
ArifPashayev, AnvarHazarkhanov, ToghrulKarimli,VasifNeymatov
National Aviation Academy of Azerbaijan, Baku
ABSTRACTA critical analysis of gyroscopic accelerometers was carried out, the principle of operation of a piezoelectric selfregulating gyroscope accelerometer with advanced technical capabilities was stated, and static characteristics wereobtained - depending on the difference in frequency and output voltage of the device on changes in the measured
rotation angle of the aircraft. In particular, some existing devices are presented that are more modern inertial masstransducers, their shortcomings are revealed, the essence of the technical solution, design features and principle ofoperation of the developed new accelerometer gyroscope with piezoelectric sensitive elements. On the basis of anelectrical connection scheme in which piezoelectric sensing elements are interconnected in a differential circuit andan input signal conversion sequence - the angle of rotation into an output signal voltage, mathematical equations aredeveloped. On the basis of the composed equations, a computer model was constructed, after the simulation of which
the necessary conclusions were drawn on the basis of the obtained oscillograms.
Keywords:gyro-accelerometer, inertial mass, resonant frequency, deflection angle, the output voltageof adjusted signals, the computation of angles oforientation (Pitch, roll, yaw). When starting theinertial-navigation system (INS) gyroscopes are notable to determine the initial angular positions. Basedon the signals obtained from the accelerometers
algorithm of the initial alignment, the initial values ofangular positions are set.

INTRODUCTION
Inertial navigation system consisting ofgyroscopes and accelerometers is intended for
determination of coordinates, angles of inclination,
stationary and non-stationary objects, and also thedirection of movement and angular velocities ofvarious moving elements and objects, submarine andsurface ships, aircraft [1-4].
In case of termination or absence ofcommunication between receivers and satellites in theobjects on which the corresponding devices are
installed, to solve the problems of navigation it isnecessary to make correction of systematic errors.
PROPOSED APPROACH
The value of angular parameters determined bygyroscopes and the values of angles (roll and pitch)measured by accelerometers are received on theelement of comparison, the difference signal of which
carries information both on the systematic andangular error and serves as the initial informationbase for auto-correction of corresponding parametersof movement.
The disadvantages of this device include theimpossibility of measuring, as well as linear
accelerations, the parallel functioning of gyroscopes
and accelerometers, resulting in their hardware
redundancy.
Fig. 1 shows the Vertical Gyro scheme, which isintended for measuring the course and the spatial
position (roll and pitch) of movable objects.
Girovertikal [5], installed on the movable object,contains gyroscopes, accelerometers, the algorithm of
the initial exhibition, the Kalman filter algorithm, theintegrator, the device of comparison, the computation

Fig. 1. Vertical Gyro
In the process of moving the objects or flight of
the aircraft, the gyro drift is tuned by accelerometers.
The Kalman filter is used to optimally evaluate the640SEE - Bangkok, Thailand, Nov.11-13, 2019

INS errors and reduce the measurement noise.
However, this device is also characterized byexcessive hardware redundancy of gyroscopes andaccelerometers, as well as the need for additional
time-consumingforaccurate
perpendicularadjustment of the axes of the sensitivity of gyroscopes
and Accelerometers in a perpendicular plane.
As it is known, at present the fields of applicationof micromechanical gyroscopes (MG) are very broad.
MG are electromechanical systems in which theenergy of forced oscillations of inertial masses on theelastic resonator at the appearance of a portable
angular velocity is converted into the energy ofsecondary oscillations. This conversion is carried out
due to influence on the resonator of inertia forces ofCoriolis at the rotation of a resonator with a portable
angular speed.
By the type of movement of inertial masses inmotion mode and sensitivity modes, there are MG
LL-type (linear-linear), RR-type (rotate-rotate), LRtype. In the LL-types, inertial masses makeprogressive, in RR-types Rotary, LR (RL)-types ofvarious combinations of progressive and rotary
movements [6-8]. A significant drawback of thesedevices is the redundancy of structural elements, lowsensitivity, a large measurement error and the need to
introduce the initial angular data on the accelerometersignals.
There
areelectro-acoustic
converters,
microaccelerometer on surface acoustic waves [9].
One of the last such developments is presented in thework [10]. Gyroscope-Accelerometer containing thedriver, made, for example, from quartz, niobate
lithium or piezoceramics with carrying electrodes, aswell as connected with each other a sensitive todeformation element and Inertial Mass.
Based on the analysis of the above shortcomings,
modern inertial navigation systems can be formed thetask of their improvement, providing the possibilityof parallel measurement of various parameters (linear
and angular acceleration, angular velocity, angular
position),increaseoflinearacceleration
measurement range, as well as correction(adjustment) of measured angles of inclination, byusing gravitation force [11, 12].
The specificity of the technical solution of thisproblem lies in the fact that the acceleration-sensitiveelements located on the most extreme opposite pointsof the movable object and fixing the values of linear
and angular accelerations, as well as angular
Velocity, at its deviation relative to the vertical plane
are subjected to maximum displacement, overcoming
the maximum differential line. At the same timeinertial masses, being exposed to maximal
displacement, by the elastic gasket with the greatest
force influence on piezoelectric sensors).
To measure such movements proportional tolinear and angular acceleration, it is enough to use
four intakes of the upper side of two piezoelectric

sensors (two for linear, two for angular) and four
inferences of the bottom side of two piezoelectric
sensors (two for linear, two for angular), as well as
two different (one for linear, one for angular)
measuring channels, implemented in a single design,and, the linear acceleration meter has no restriction on
Frequency, in static and dynamic modes dependingon the angle of inclination under the influence of
linear acceleration, and formed angular parameters
adjust (tune) measured angles.
The main advantages of piezoelectric selfadjusted gyroscope-accelerometer can be considered:
the possibility of simultaneous measurement of linear
and angular acceleration, as well as angular velocity,
significantly
increasestheefficiencyofmeasurements, And the lack of frequency limit allows
increasing the range of linear acceleration
measurements.
1. Measured tilt angles are continuously
independently adjusted (adjusted).
The developed device contains 1-case; 2excitative element; 3- piezoelectric sensors; 4-inertial
mass; 5-elastic gaskets; 6-limiter supporting the fixed
positions of elements 3 and 4 (Fig. 2).

Fig. 2. Piezoelectric Self-adjusting GyroscopeAccelerometer.
When moving the sensitivity axis from theposition from OO/ to the OO// position (from thevertical position to the right side) under the influenceof linear and (or) angular acceleration, angularvelocity of displacement of inertial masses 3 on theright side (top and bottom), Perceived by elastic
gaskets 4, contribute to increase the clamping force
on the third-party piezoelectric sensors, at the sametime moving left side inertial masses (top and bottompart), perceived by elastic gaskets, contribute to
reducing the clamping force on the left side
piezoelectric sensors.
641

SEE - Bangkok, Thailand, Nov.11-13, 2019

The location of inertial masses, gaskets,
piezoelectric sensors at the endpoints excitative
piezoelectric elements (drivers) contribute to thegreatest linear movement of these points at the rotary
motion of the device.
As a result, on the right side piezoelectric sensors(top- f 2 and bottom- f 2′ ) frequencies of oscillations
increase, and on the left side of piezoelectric sensors(top - f1 and bottom- f1′ ) the frequency ofoscillations decreases. Linear and (or) angularacceleration, angular velocity are determined by thedifference of frequencies of piezoelectric sensors. By
measuring linear accelerations, the initial (initial)
angular positions are determined (adjusted) or thedrift of the angular velocity channel is corrected.
In case of rest or uniform straight motion, when
the object is in a horizontal position (the axis ofsensitivity of OO/ is in vertical position) frequency ofoscillations in the left side and right-sided (top andbottom) piezoelectric sensors are equal, as inertial
masses and elastic strips exert equal pressing forceson piezoelectric sensors, in the upper block ofdifference of linear accelerations 6 frequency
difference is defined as a1 ~ f1 − f 2 = 0 ; and in
the bottom block of difference of linear accelerations
6
difference
frequency
isdefinedasa 2 ~ f1′ − f 2′ = 0 .
If the object is relative to the horizon at a certain
angle φ (as in the case of rest or uniform motion)(corresponds to the position of OO//), the influence ofgravity left side inertial masses under their elastic
gaskets pressed to the left piezoelectric sensors, andthe right side inertial masses by means of elastic
gaskets apart from the right side. Thus, in the upperand lower part of the left side sensitive piezoelectric
the frequency of oscillations increases equally,
whereas in the upper and lower part of the right side
sensitive piezoelectric the frequency of oscillations//
decreases accordingly ( f1 = f1 , f 2 = f 2 ,(here a1 is determined by the upper block 6, a2
determined The bottom block 6) (Fig.3)

Fig. 3. Functional scheme of the measuring systemof
thepiezoelectric
self-adjustinggyroscopeaccelerometerIn the dynamic mode, when the object is subjected
only to angular acceleration, in the upper block of thedifference of angular accelerations 7 the difference of
frequencies on piezoelectric sensors is proportional toangular acceleration f1 − f 2 ~ ϕ1 , and in the bottom
block of the difference of angular acceleration 7, thisdifference is defined as f1′ − f 2′ ~ ϕ2 . Given the unitof time that the top point is subjected to the maximum
displacement relative to the bottom point, theacceleration of the top point will be greater, thedifference of frequencies in the lower and upper 7
blocks
are
not
equal
to
zero
( f1 − f 2 ) − ( f1′ − f 2′) ≠ 0 . In other words, theangular position of the movable object is determinedby the change of the acceleration difference between
the top and bottom points per unit of time:

f1 > f 2 ). In this case, (given the zero values ofϕ ~ dlinear and angular acceleration, angular velocity,
based
on
the
conditionof( f1 − f 2 ) − ( f1′ − f 2′ )≠0dtLinear acceleration is formed in the block(computer) of formation of linear acceleration 8 on
the basis of signal difference. This signal passing
through Integrator 9 is converted into velocity andmovement values (after double integration). angularacceleration and angular velocity are formed in theblock (computer) of formation of angular acceleration
1 − ϕ2 ,10 on the basis of the difference of signals, ϕ

a1 = a 2 = 0, ϕ1 = ϕ2 = 0, ), ϕ1 = ϕ2 = 0 at

the top and bottom points of the device the differenceof frequencies on piezoelectric sensors changes
proportionally to the angle of inclination ( a1 = a 2
linear acceleration, ϕ1 = ϕ2 angular acceleration,ϕ1 = ϕ 2 angular velocity).
In dynamic mode, when the object is subjected
only to linear acceleration, the acceleration of theupper and lower points are equal, the difference of
frequencies in the upper and lower units of thedifference of linear accelerations 7 are defined as
f1 − f 2 ~ a1 , a1 = a2 , ( f1 − f 2 ) − ( f1′ − f 2′ ) = 0

ϕ1 − ϕ2 . Further, this signal passing through the
integrator is converted into angular velocity ϕ andangle ϕ (after double integration). The angle
correction block 11 is used to adjust (tune) the angle
drift based on the difference of linear accelerations.
642

SEE - Bangkok, Thailand, Nov.11-13, 2019ν

f1 = f 0 1 −
∆F 
 YES

33



In the special case, when the measured angle can be
adjusted (tuned) with high precision by means of asignal: ϕ ~ f1 − f 2 .
In dynamic mode, when the object is subjected tolinear and angular accelerations, linear acceleration isformed by block 8, angular acceleration and angularvelocity is formed by block 10. In this case in theupper block of the difference of angular accelerations
7 the difference of frequencies on piezoelectric1 + a1 , andsensors will be described as f1 − f 2 ~ ϕin the bottom block of the difference of angular2 + a2 , where:
accelerations 7 as f1′ − f 2′ ~ ϕa1 ~d ( f1 − f 2 )≠0,dt

a2 ~ d( f1′ − f 2′ )≠0 ,dtFig. 5. The electrical circuit of connection ofpiezoelectric sensitive elements (PSE)( f − f ) − ( f1′ − f 2′ )≠0ϕ ~ d 1 2
dt

Where α -resonant frequency; E -Jung's module;
S -section of the surface on which the force acts; νAn arrangement of the bottom part of sensitive
piezoelectric in the center of gravity of theinvestigated object, the difference of frequencies inthe bottom block of the difference of angular-Poisson coefficient; α-the turn angle of the movable
object; ∆F -Change of the exerted force; ∆f Frequency difference relative to the resonant
frequency; ∆Z(j ω)-Change the value of the complex
resistance; U(∆f)-voltage of electric output of thevibration and acceleration sensor; К∆Fω - coefficientof conversion "turn angle -power"; Кω∆z - coefficientof conversion "power-frequency"; К∆Fω -coefficientof conversion "frequency-resistance"; К∆ZU coefficient of conversion "resistance-tension".
Thus, a mathematical relationship is given by:accelerations are defined in the form f1′ − f 2′ ~ a2 ,2 = 0 .
where ϕTaking into consideration the wide scope of
application of gyroscope-accelerometer with hightechnical characteristics, we continue to study thedeveloped device for determination of dynamic
characteristics by means of modeling in
MatlabSimulink Software Environment.
Thus, based on the principle of operation of thedevice research of the static characteristic for eachmeasured parameter is needed.
Fig. 4 illustrates the functional scheme of
conversion of "turn angle of the movable objectoutput voltage of the scheme", and Fig. 5 illustrates
the electrical circuit of the connection of piezoelectric
sensitive elements is presented.

U (∆f ) = F ( α )SOLVING THE PROBLEM
According to the theory of measurement ofparameters of mechanical motion on the basis of [1315] work of the researched piezoelectric gyroaccelerometer it is possible to say, that the shift of
frequency from the resonant value of frequency underinfluence of force will be determined by the formula:ν
f = f 0 1 −∆F  .
(1)
 YES

33


This will result in an expression we define thedependence of change of resistance of ∆Z(jω)-on the
difference of frequencies ∆f , we define with the help

Fig. 4. Functional scheme of conversion "turnangle of the movable object-output voltage of thescheme"The main formula showing the dependence of
frequency change on the resonant frequency by force
is the expression:

643

SEE - Bangkok, Thailand, Nov.11-13, 2019



2




 ν∆F 2
1+ Q ⋅ EY S 
 33 
 (8)∆Z = R0 P 1 −
2

 
 YES



33
⋅
+ 1 
E S ν∆F
 

Y
−

 
 33


of a bridge scheme of connection piezoelectric
sensitive elements (PSE) which is presented on fig. 1.
Hence the expression:

∆f =

νω 0
E
2πY33
S

∆F

(2)

It is known that for the non-loaded piezoelectric
converter is: ∆F = 0; ∆Z = 0; Z 0 P = R0 P ; theresonance frequency will be determined by:

ω0 =

1

,

Expression of the voltage of the electric output ofvibration and acceleration sensor U(∆f):U=(3)

L0 P C0 P



2




F
ν
∆


⋅ 
1+ Q2E
Y S 
1 
 33 

U = E 1 −
2
2 
E



 Y33 S ⋅+ 1  Y E S − ν∆F
 

 33
 


Where: L0 P ,C0 P -inductance and capacity.To
find a dependency ∆Z(j ω)=f( ∆f ), it is advisable touse a known formula [16,17]:2

1Z P = R0 P 1 + Q 2  n −  .(4)nWhere: Q = ω0 L / R0 P -the quality of the scheme of

2

1

∆Z = R0 P 1 − 1 + Q 2  n −   , (5)





n 


and also, taking into account the expression for the
relative value of the frequency, composed on the basisof equations (1) and (2)
n=



2




mg
(
1
cos
(
))
ν
α
−




1 + Q2
⋅

ES




Y33




2
1 
E
E
  ,(10)Y33 S + Y33 S
U = E 1 − 

− 
2 
 E
Y S − νmg( 1 − cos( α ))  ⋅  33 νmg( 1 − cos( α ))

−
 

 Y E S − νmg( 1 − cos( α ))  

 33
 



f
ω 
ν
=
= 1 −∆F  ,(6)f 0 ω0  Y E S

33



after the mathematical transformation we get:2 ν∆F 2⋅⋅
1+ Q 
 Y E S 
 33 
Z = R0 P
2
 YES



33
+ 1
 E

Y
S
F
−
ν
∆
 33


.

(9)

Equation (9) is a static characteristic of the device
in question, defining the dependence U = f( ∆F ) .
According to the principle of the deviceis the force
acting on the sensitive elements, more precisely, thegravity of the inertia mass (Figure 3, Position 3):∆F = mg - mgcos( α ) = mg( 1 − cos( α ))Thus, we get the expression for the static
characteristic of the piezoelectric self-adjusting gyroaccelerometer, working in the mode of measuring theturn angle of the object:substitution of piezoelectric sensitive elements(PSE); n = ω / ω0 -Relative frequency change.
According to initial conditions Z0=R0P:



1 ∆Z
,
E
2 R0

ω0 =

(7)

E
1,58 Y33
νω 0, ∆f =∆F ,ρ
с
2πY E S
33



f
ω 
ν
n=
=
= 1 −∆F 
f 0 ω0  Y E S

33



If we consider the resulting expression (7) if we
considerin the expression (5) we will obtain the final
expression for Dependencies∆Z(j ω)=f( ∆f ):In Fig. 6,7the oscillograms obtained after thesimulation of the computer model, constructed on thebasis of equation (10) in the environment of
MATLAB are presented.
644

SEE - Bangkok, Thailand, Nov.11-13, 2019

We choose Piezoceramics PZT-8 withdimensions: a =0,01m; b =0,002m; c=0,005m(thesame dimensions for inertial mass), physicalandtechnical parameters, which according to [18]:EρM=7800 kg/m3; ρ =7720 kg/m3; Q=60; Y33=5.3
910 Pa; υ=0.35. The supply voltage of the device isselected Е=24V. The numerical results are obtained:
Lm=41,14 Hn; Cm= 8,476e-15F ;Rm=131,1Om;
fp=26980 Hs ; α=0-900; U=0-0.18 V.

device depending on the measured angle of thepiezoelectric sensitive elements must be connected ina consistent-differential scheme; in the range ofangular turn measurements of 0-900, the output signal
changes in frequency in the range of 0-140 Hz,
deviation from the resonance frequency is 0.08%.
REFERENCES[1] David L. Churchill. Inertial measurement systemwith a self-correction: Patent US 8,010,308 B1 Int.
Cl.: G01C 25/00 (2006.01), G06F 19/00(2011.01). Aug. 30, 2011, p.20.
[2] Christian Domingues. Challenges for integratinghigh performance Inertial Measurement Unit
(IMU). IP-Embedded System Conference &Exhibition. France, Grenoble: 2013, p.27.
[3] Honeywell. Micro Inertial Reference System.
Product Description. March 2012, p.33.
[4] Boeing 747-8. Maintenance Training Manual.
Navigation1. Boeing Company, 2016. p.393.
[5] www.inertiallabs.com. Vertical Gyro[6] Raspopov V.Y. Micromechanical Devices:
Training manual. Moscow.: Mashinostroyeniye,
2007, p.400.
[7] Matveyev V.V. Mathematical models of LL-type
micromechanical gyroscopes//Izvestia Tula.
Technical Sciences. 2012. Vol. 12, p1, pp. 205213[8] Matveyev V.V., Pogorelov M.G. Analysis oferrors of micromechanical gyroscopes by themethod of variations of Allan//Izvestia Tula.
Technical Sciences, 2015, vol. 3, pp. 123-135.
[9] Petrov
P.N.
Acoustics.
Electro-acoustic
Converters. SpB.: SpBGUAP, 2003, p.80.
[10] Ansev
G.V.,
Bogoyavlenskiy
S.V.,
SapojnikovG.A.
Gyroscope-Accelerometer.
Patent: RU 2381510, 10.02.2010, p.9.
[11] Qurbanov T.B., Karimli T.I., Karimli V.I.
Piezoelectric
self-adjusting
gyroscopeaccelerometer. Patent Application Publication№a20140107. Azerbaijan, Baku, 20.06.2017.
[12] Hazarkhanov A.T., Karimli T.I., Neymatov
V.A., Karimli V.I. Operating modes of
piezoelectric
self-adjusting
gyroscopeaccelerometer//HERALD of the Azerbaijan
Engineering Academy. Vol 10, №1. Baku, 2018,
pp.7-15.
[13] Piezoelectric
sensors.
https://studentslibrary.com/library/read/48485pezoelektriceskie-datciki[14] Steinem C., Janshoff A. Piezoelectric Sensors.
Berlin: Springer-Verlag. 2007, p.484.
[15] Regtien P., Dertien E. Sensors for mechatronics.
2nd edition. Elsevier, 2018, p.380.
[16] Resonant properties RLS-chains
http://elar.urfu.ru/bitstream/10995/45632/1/9785-7996-0831-6_2013.pdf[17] Thomas R.E., Rosa A.J., Toussaint G.J. The

Fig. 6. The oscillograms obtained after thesimulation of the computer model : U = f α( )Fig. 7. The oscillograms obtained after thesimulation of the computer model : ω = f (α )The simulation of measurements was performed
when the turn angle of the object changed in theinterval (0-1800). The main purpose of the choice ofsuch interval was that it was possible to verify the
return of the Electric Bridge scheme to the originalstate. As it can be seen from the obtained
characteristics, the output voltage of the device has
proportional dependence on the change of the turnangle of the object, as the laws of change of bothsignals are similar. Due to the large value of Jung's
module of the chosen piezoceramics, the output
voltage is quite small. This requires the use of a
voltage amplifier with a sufficiently large gain.
CONCLUSION
In this way, the following basic conclusions can be
drawn: the proposed constructive solution of thepiezoelectric acelerometer-gyroscope allows you todesign the device, with relatively smaller mass-size
indicators and relatively high sensitivity, due to theuse of small materials and the use of piezoelectric
converters as sensitive elements; To ensure a
proportional change in the output voltage of the645

SEE - Bangkok, Thailand, Nov.11-13, 2019

piezoceramic materials in ultrasonic transducers
sciencedirect.com/science/article/pii/S18753892
16304175

Analysis and Design of Linear Circuits. 8th edition.
Hoboken: Wiley, 2016. p.912 .
[18] Performance of PZT-8 versus PZTT4646

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

PROPORTION AND PROPERTY SPECIFICATIONS AND STRENGTHBEHAVIOR OF MORTAR USING WOOD ASH AS PARTIAL
REPLACEMENT OF LIME
Robert Michael Tampus1, Janine R. Lardizabal1, Dennise Linoel M. Acena1, Michaela Angelica M. Uy1, andKenneth Vance R. Arcenal1
1
Mapúa University Young Innovators Research Center, Mapúa University, Philippines

ABSTRACT
Wood ash is produced by the incineration of wood and wood products; thus, it is a waste product generated
from various sources such as household fireplaces, agricultural activities, or manufacturing plants. By reusingwood ash wastes as lime-replacement additives, the resulting lime mortar would become a more practical building
material. This study utilized varying proportions of wood ash (25%, 50%, 75%, and 100%) as partial replacementof lime in manufacturing Type N mortars through the provision of proportion and property specifications thatadhere to known industry standards. The proportion specification for Type N Mortar was modified as one part
Type 1 Portland cement, one part Type S Hydraulic Lime and/or wood ash, and six parts of coarse sand aggregate(1:1:6). The air content, initial and final setting times, 7- and 28-day compressive strengths of the mixed mortars
were shown to be heavily affected by the presence of wood ash within the mortar mix. Furthermore, the use ofwood ash as a partial replacement of lime caused an increase in air content and a decrease in setting times of themortar mix. Mortars with 100% replacement of lime with wood ash showed the highest compressive strength forboth 7- and 28-day tests. Therefore, the incorporation of wood ash as a lime replacement was determined to be a
viable option for Type N mortars.
Keywords: Air content, Compressive strength, Mortar, Setting time, Wood ash

much easier and simpler to repair [4].
The trend of using lime mortar was certainly
altered due to the difficulties experienced regarding
the application of lime mortars, such as long setting
and hardening times, especially at a very high relative
humidity as well as weak mechanical properties [5].
Lime mortar is not water-resistant, but it allows thewall block to breathe. However, segregation of theoriginal material and the lime might occur as themortar dries and hardens. The resulting mortar will be
seriously weakened, with a poorly-formed pore
structure leaving it very susceptible to frost damage
and deterioration.
This study aimed to fill the gap of previous studies,
wherein most literature focused on testing thestrength behavior of the mortars using various limereplacement additives such as slags and ashes.
Several studies about wood ash [6] – [8] discovered
the potential use of wood ash in several applications
such as mortar and concrete production, and forest
road construction, but most studies lacked focus on
the importance of the proportion and property
specifications of wood ash in manufacturing lime
mortars.
This study was generally aimed to utilize woodash as a partial replacement of lime in manufacturing
mortars for masonry construction. Specifically, thisstudy addressed the following objectives: (1) todetermine the proportion specification of the mortars

INTRODUCTION
In construction, mortars are building materials
that fill the gaps between blocks of a structure; thesematerials are typically composed of fine aggregates,a binder, and water. According to [1], different typesof mortars can be classified according to the type ofbinding material: earth mortar, cement-sand mortar,
gypsum mortar, and lime mortar. Lime mortar iscomparable to other mortar types except for its
breathability; this provides flexibility and strength tothe structure. In terms of plasticity and workability, alime mortar can quickly adhere to blocks as it canaccommodate changes in moisture within themasonry construction. It also reduces the potential
damage caused by the accumulation of salt from theweathering of the blocks [2].
Lime mortar serves as sacrificial layers topreserve structures from excessive exposure against
mechanical and environmental influence. These
mortars are cohesive and adhesive to the structure. It
is necessary to choose the right materials, formulation,and preserving conditions of the mortar to meetfunctional and aesthetic requirements and fulfill theprinciples of compatibility, while maintaining thestructure’s integrity and durability [3]. Lime is aweaker element than stone, brick, or cob, whichenables it to resist cracking from a certain amount of
movement. When the lime mortar is applied, it is647

SEE - Bangkok, Thailand, Nov.11-13, 2019with 0%, 25%, 50%, 75%, and 100% replacement oflime by wood ash conforming to the requirements ofAmerican Society for Testing and Materials (ASTM)
C270, and (2) to compare the property specificationsof the mixed mortars in terms of setting time, aircontent, and compressive strength.
This study had contributed to the development of
the masonry construction industry. Wood ash is
produced by the incineration of wood and wood
products; thus, it is a waste product generated fromvarious sources such as household fireplaces,
agricultural activities, or manufacturing plants. By
reusing wood ash wastes as lime-replacement
additives, the resulting mortar would become a morepractical building material. Also, the process of lime
production involves the emission of large quantities
of carbon dioxide which contributes to global climatechange [9]. The partial replacement of lime withwood ash wastes could lessen environmental
problems associated with manufacturing mortars,
such as air, water and soil pollution. Thus, this study
can significantly contribute to achieving sustainable
development by reducing the ecological footprint ofdisposing wood ash and manufacturing lime mortars.
This study is limited only to the concept of
specifying the proportion, properties, andcompressive strength of the mortars mixed with woodash as partial replacement of lime. However, thisstudy does not indicate the specific type of woodburnt to generate the wood ashes. The researchers
used the American Society for Testing and Materials(ASTM) C270 [10] as the standard speciﬁcation for
mortars used in unit masonry. In conformity with theAmerican Association of State Highway andTransportation Officials (AASHTO) standard
specifications, different mortar testing equipment
were used such as a flow table to measure air content(AASHTO T 137-04) [11]; a Gillmore needle torecord setting time (AASHTO T 154-06) [12]; and a
Universal Testing Machine (UTM) to measure thecompressive strength of the mortars (AASHTO T
106M/T 106-07) [13]. However, as a consequence oftime constraints, the preliminary tests for thecompressive strength of the mortars were conducted
only after 7 and 28 days of curing.

water. Type S Hydrated Lime conforming to ASTM
C-207 was used in the study. Type 1 Portland cement
was also used as the binder as specified in ASTM C150. A well-graded coarse sand aggregate (4.75 mm
in diameter) was used. Wood ashes were utilized as
partial lime-replacement additives; the ashes werecollected from household fireplaces. Water was
prepared and kept free from oils, acids, alkalis, salts,
organic materials, or other substances that weredeleterious to mortar.
Preparation of Lime Mortar with Varying
Proportions of Wood Ash as Lime Replacement
In accordance with ASTM C270 [10], several
batches of Type N Mortar were made with a mortar
mix ratio of one-part Portland cement, one-parthydrated lime, and six-parts sand (1:1:6). However,
the hydrated lime was partially replaced with varying
proportions (25%, 50%, 75%, and 100%) of woodash. Proportion specifications of the mortars were
determined depending on the sample weight requiredby each test. A reference mortar containing 0% woodash and 100% lime was also evaluated.
Determination of Air Content (AASHTO T 13704)
Mortars were mixed using 350 g of cement to1400 g of 20-30 standard sand and sufficient water togive a flow of 87.5 ± 7.5%. A layer of mortar about
25 mm in thickness was placed in the mold andtamped 20 times to ensure uniform filling of the mold.
An approximately 20-mm layer of mortar was added
to the top of the mold and tamped again. The mortar
was separated from the mold and then placed on aplanar surface. Prior to determining the air content of
the mortar, its flow rate was calculated using
Equation (1):

R flow 

Dmold
100%
Dmortar(1)

where Rflow is the flow rate (in percent), Dmold is thediameter of mold (in mm), and Dmortar is the diameterof mortar (in mm).
The flow table and mold used were conforming to
the requirements of AASHTO 152M/M 152 [11]. The
flow table should be clean and dry, so any water fromaround the edge of the mold was removed. After the
mixing operation, the flow table was dropped 10
times and the flow rate was recorded as the resulting
increase in average diameter of the mortar mass.
Several trial mortars with varying percentages ofwater were made until a desired flow of 87.5 ± 7.5%
was obtained.
Air content of the mortar was determined using
the mass of 400 mL of mortar and the physical

METHODOLOGY
In conformity to both American Society for
Testing and Materials (ASTM) and American
Association of State Highway and Transportation
Officials (AASHTO) standard specifications, thissection presents the different procedures andequipment used in the study.
Material Sourcing and Preparation
The mortars were composed of the following
components: lime, cement binder, aggregate, and
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SEE - Bangkok, Thailand, Nov.11-13, 2019

properties of its components used, as shown in Eq. (2)and Eq. (3):D

W1  W2  Vw
W1 W2

 Vw
S1 S 2A  100 Wm
4D

a moist room and conditioned in the laboratory
meeting the requirements of ASTM C511. One-thirdof the mold was filled with mortar and pressed 25
times with the help of a tampering rod; this procedureof filling and tapping was repeated thrice. A trowel
was used to smoothen the upper surface and was kept
open air for one day. Afterwards, the cube specimens
were cured in a lime bath for 7 and 28 days. To
determine the compressive strength of the mortar, theUniversal Testing Machine (UTM) was used byapplying incremental load to the cube specimen. As
the load was applied on the cube, it developed cracks
at a certain load. The application of load was stopped
when the cube has been crushed. The compressive
strength of the mortar was calculated using Eq. (4):

(2)

(3)

where D is the density of air-free mortar (in g/cm3),
W1 is the mass of cement (in grams), W2 is the massof sand (in grams), Wm is the mass of 400 mL of
mortar (in grams), VW is the millilitres-gram of waterused (in mL-g), S1 is the density of cement (in g/cm3),
S2 is the density of standard sand (2.65 g/cm3), and A
is the volume percent of entrained air (%). The aircontent was compared to the ratio of mixing water tothe binding materials; this ratio is calculated using thevolume of mixing water (in mL) divided by the total
mass of binding materials (cement ± lime ± wood ash)used (in grams).

fm 

P
A

(4)

where fm is the compressive strength of the mortar (inMPa), P is the total maximum load (in N), and A isthe area of loaded surface (in mm2). The compressive
strength was reported as an average of two trials.
RESULTS AND DISCUSSION

Determination of Setting Time (AASHTO T 15406)

Five (5) sets of mortars with Type 1 Portland
cement, well-graded coarse sand, and gradualreplacement of Type S Hydraulic Lime with woodash were tested to determine the appropriate
proportion specification with the right volume of
mixing water as well as its mechanical properties
such as setting time, air content, and compressive
strength.

Mortars were batched using 650 g of cement with thepercentage of mixing water required for normal
consistency. To mold the mortars, a pat was madewith a flat top by drawing the trowel from the outeredge toward the center. The prepared mortars were
tested to meet the required consistency using theneedles of the Gillmore apparatus. The time required
to obtain the stipulated penetration of the Gillmore
needle is the time of setting. The needles were held ina vertical position and applied lightly to the surface ofthe pat. The initial set was acquired when the initial
Gillmore needle touched the surface of the pat
without appreciable indentation. The Gillmore initialtime of setting was determined when the elapsed time,in minutes, between the time of contact of mortar andthe time when the mortar acquired its initial set. The
final set was also acquired when the final Gillmore
needle touched the surface of the pat without
appreciable indentation. The Gillmore final time ofsetting was determined when the elapsed time, in
minutes, between the time of contact of mortar andthe time when the mortar acquired its final set.

Proportion Specifications of Lime Mortar with
Varying Proportions of Wood Ash as Lime
Replacement
Modified from ASTM C270 [10], several batchesof Type N Mortar were made with a mortar mix ratioof one-part Type 1 Portland cement, one-part Type S
Hydrated Lime and/or wood ash, and six-parts coarse
sand aggregate (1:1:6). As presented in Table 1, a
total sample weight of 800 grams was used in every
batch of mortars in the determination of air content
and compressive strength conforming to AASHTO T
137-04 [11] and AASHTO T 106M/T 106-0 [13],respectively. Furthermore, a total sample weight of
650 grams was sampled in every batch of mortars forthe determination of initial and final setting times inaccordance with AASHTO T 154-06 [12], as shownin Table 2. Upon determination of the proportion
specifications, Mortar A is the reference mortar
having no partial replacement of lime with wood ash.

Compressive Strength Testing (AASHTO T
106M/T 106-07)
A compressive strength test was conducted on themortars that were proportioned, mixed andconditioned in the testing laboratory. Two-inch
mortar cubes were used as compressive strength
specimens cast in non-absorbent molds and cured in
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Table 1 Mortar
Mix
Proportions
fortheDetermination of Air Content and Compressive
Strength Test (AASHTO T 137-04; AASHTO T
106M/T 106-07)
Sample:800 g
Mortar A
Mortar B
Mortar C
Mortar D
Mortar E

Table 3 Experimental Results of Air Content
MW/BM

Air Content of Mortars (%)

A
B
C
D
E
0.65
15.89 17.28 18.54 19.46 20.11
0.70
13.15 15.76 16.12 15.46 16.62
0.75
10.98 14.00 13.86 12.60 14.04
0.80
9.52 12.51 11.06 10.85 12.17
0.80
8.16
9.58
8.98
9.15
9.95
Note: MW/BM means ratio of mixing water tobinding materials (cement ± lime ± wood ash).

Cement : Lime : Sand = 1:1:6
Cement
Lime
Wood
Sand
(g)
(g)
Ash (g)
(g)
100
100
0
600
100
75
25
600
100
50
50
600
100
25
75
600
100
0
100
600

Table 2 Mortar
Mix
Proportions
fortheDetermination of Initial and Final Setting Times(AASHTO T 154-06)
Sample:650 g
Mortar A
Mortar B
Mortar C
Mortar D
Mortar E

Cement : Lime : Sand = 1:1:6
Cement
Lime
Wood
Sand
(g)
(g)
Ash (g)
(g)
81.25
81.25
0
487.5
81.25
60.94
20.31
487.5
81.25
40.625 40.625
487.5
81.25
20.31
60.94
487.5
81.25
0
81.25
487.5

Fig. 1 Relationship between air content and waterto-binding material ratio of the mixed mortars. Error
bars represent standard errors. L means lime and WA
means wood ash.

Air Content
The flow was first determined to identify the ratio of
mixing water to the binding materials with theresulting flow of 87.5 +/- 7.5%, as stated in AASHTO
T 137-04 [11]. In particular, the mixed mortars got
the desired flow between 0.65 to 0.80 ratio of mixing
water to the binding materials when the volume of
mixing water was varied from 130 – 170 mL. The
ASTM C91/ C91M-18 property specification
provided an allowable range of 8 - 21% for the aircontent of Type N mortars [14]. All of the set ofmortars have an average air content within thestandard range; however, Mortar E with 0% lime and100% wood ash had the highest air content of
14.58%, as shown in Table 3 and graphicallypresented in Figure 1. Furthermore, the air content of
Mortar E will be at its maximum at 0.65 ratio of
mixing water to the binding materials. The air content
of mixed mortars generally increased as the amountof wood ash increased. A possible explanation wasthat the angularity of the wood ash particles as
described by [6], allocated larger pore spaces between
sand aggregates and binding materials.

Setting TimeThe AASHTO T-154 [12] limits the initial time ofsetting on samples testing between 100 to 341
minutes. Basically, the mortar with time closest to
100 minutes is said to have the best initial setting
time. As shown in Table 4 and Fig. 2, Mortar C with
50% lime and 50% wood ash has an average initial
setting time closest to 100 minutes, having 108
minutes. On the other hand, Mortar A with 100% lime
has the longest average of initial setting time. This issimilar to the study of [5] which stated that lime
mortar shows difficulties including slow setting andhardening times. Moreover, the AASHTO T-154 [12]also limits the final time of setting on samples testing
between 239 and 561 minutes. Basically, the mortar
with time closest to 239 minutes is said to have thebest final setting time. Mortar B with 75% lime and
25% wood ash has an average final setting timeclosest to a minimum of 239 minutes, having 243
minutes, followed by mortar C which had the best
initial setting time. On the other hand, Mortar A with
100% lime has the longest average of final setting
time. The initial and final setting times of mixedmortars were drastically reduced when gradualreplacement of lime by wood ash (25%, 50%, 75%,
and 100%) was involved.

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Table 4 Experimental Results of Setting Time
Composition

Table 5 Experimental
Strength Test

Setting Time (mins)
InitialFinal

Composition

Mortar A
162
348(100% L; 0% WA)
Mortar B
114
243(75% L; 25% WA)
Mortar C
108
246(50% L; 50% WA)
Mortar D
123
270(25% L; 75% WA)
Mortar E
147
321(0% L; 100% WA)
Note: L means lime and WA means wood ash.

ResultsofCompressiveCompressive Strength
(MPa)
7-day
28-dayMortar A
4.625
5.185
(100% L; 0% WA)
Mortar B
4.59
7.095(75% L; 25% WA)
Mortar C
4.5
6.91(50% L; 50% WA)
Mortar D
4.01
6.54(25% L; 75% WA)
Mortar E
4.935
6.98(0% L; 100% WA)
Note: L means lime and WA means wood ash.

Fig. 2 Relationship between the Initial and Final
Setting Times and Wood Ash/Lime Ratio. L means
lime and WA means wood ash.
Compressive Strength

Fig. 3 Variation of Compressive Strength at 7 and
28 days curing period. Error bars represent standard
errors. L means lime and WA means wood ash.

When prepared and tested in accordance withASTM C91/ C91M – 18 [14], the compressive
strength of Type N mortars should be equal or greaterthan 3.4 MPa for 7-day test and 6.2 MPa for the 28day test. As presented in Table 5 and Fig. 3, all of themortars exhibited 7- and 28-day compressive
strengths greater than the specified standards;
however, Mortar A has a below standard 28-daycompressive strength. Mortar E with 100% wood ash
and 0% lime yielded the highest compressive strengthfor both day-tests. The 28-day compressive strengthof mixed mortars was significantly enhanced whenvarying amounts of wood ash were incorporated. The
improved 28-day compressive strengths could be
attributed to wood ash as a pozzolanic material,
similar to the findings of [15]. Mixed mortars with atleast 25% partial replacement of lime with wood ash
could possibly be sufficient in exhibiting pozzolanic
reaction; however, it is notable that the amount ofType 1 Portland cement was kept constant across all
mixed mortars.

CONCLUSIONSThis study aimed to utilize wood ash as a partial
replacement of Type S Hydraulic Lime inmanufacturing Type N mortars through the provisionof proportion and property specifications that adhere
to known industry standards such as American
Society for Testing and Materials (ASTM) andAmerican Association of State Highway andTransportation Officials (AASHTO). The air content,
initial and final setting times, 7- and 28-daycompressive strengths of the mixed mortars wereshown to be heavily affected by the presence of woodash within the mortar mix. Based on the results of thisstudy, the following conclusions were made:1. Modified from ASTM C270, the proportion
specification for Type N Mortar is one part Type
1 Portland cement, one part Type S HydraulicLime and/or wood ash, and six parts of coarse
sand aggregate (1:1:6). Furthermore, the ideal
water-to-binding material ratio was 0.65, wherein
651

SEE - Bangkok, Thailand, Nov.11-13, 2019the mixed mortars typically exhibited higher air
content.
2. Based on the proportion specification of themortars with 0%, 25%, 50%, 75%, and 100%
replacement of lime by wood ash, the following
property specifications were most favorable:
a. The value of air content was highest when lime
was completely replaced by 100% wood ash.
As the amount of wood ash content increased,
the air content significantly increased
resulting from the angularity of wood ash
particles.
b. The initial time of setting was fastest when lime
was partially replaced by 50% wood ash,whereas the longest initial setting time wasobserved in the reference mortar. Gradualreplacement of wood ash caused the mixedmortars to have significantly faster initial
setting times as compared to the reference
mortar.
c. The final time of setting was fastest when lime
was replaced by 25% of wood ash. Gradualreplacement of wood ash caused the mixedmortars to exhibit significantly faster final
setting times as compared to the reference
mortar.
d. Mortars with 100% replacement of lime withwood ash showed the highest compressive
strength for both 7- and 28-day tests. Thus, theincorporation of wood ash as a lime
replacement is a viable option for Type N
mortars.

of Three Hydraulic Lime Mortar Systems: Natural
Hydraulic Lime Mortar, Cement-aerial Limebased Mortar and Slag-aerial Lime-based Mortar,
Construction and Building Materials, Vol. 186,
2018, pp. 42-52.
[5] Elert, K., Rodriguez-Navarro, C., Pardo, E. S.,
Hansen, E., and Cazalla, O., Lime Mortars for theConservation of Historic Buildings, Studies inConservation, Vol. 47, Issue 1, 2013, p. 62.
[6] Ban, C. and Ramli, M., The Implementation ofWood Waste Ash as a Partial Cement
Replacement Material in the Production of
Structural Grade Concrete and Mortar: An
overview,
Resources,
Conservation
andRecycling, Vol. 55, Issue 7, 2011, pp. 669-685.
[7] Ramos, T., Matos, A. M., and Sousa-Coutinho, J.,
Mortar with Wood Waste Ash: MechanicalStrength Carbonation Resistance and ASR
Expansion, Construction and Building Materials,
Vol. 49, 2013, pp. 343-351.
[8] Oburger, E., Jäger, A., Pasch, A., Dellantonio, A.,
Stampfer, K., and Wenzel, W., Environmental
Impact Assessment of Wood Ash Utilization in
Forest Road Construction and Maintenance — A
Field Study, Science of the Total Environment,
Vol. 544, 2016, 711-721.
[9] Gutierrez, A., Caneghem, J., Martinez, J., andVandecasteele,C., Evaluation of The
Environmental Performance of Lime Production
in Cuba, Journal of Cleaner Production, Vol. 31,
2012, pp. 126-136.
[10] ASTM C270, Standard Specification for Mortar
for Unit Masonry, ASTM International WestConshohocken, PA, 2019.
[11] AASHTO T 137- 04, Air Content of Hydraulic
Cement Mortar, American Association of State
Highway and Transportation Officials,
Washington, D.C., 2018.
[12] AASHTO T-154, Standard Method of Test forTime of Setting of Hydraulic Cement Paste by
Gillmore Needles, American Association ofState Highway and Transportation Officials,
Washington, D.C., 2018.
[13] AASHTO T-106, Standard Method of Test for
Compressive Strength of Hydraulic Cement
Mortar (Using 50-mm or 2-in. CubeSpecimens), American Association of State
Highway and Transportation Officials,
Washington, D.C., 2018.
[14] ASTM C91 / C91M-18, Standard specification
for masonry cement, ASTM International, WestConshohocken, PA, 2018.
[15] Sebastian A., Manapurath, Balachandran, andSebastian D., Partial Replacement of Cementwith Wood Ash, International Journal of
Science Technology & Engineering, Vol. 2,
Issue 11, 2016, pp. 666-670.

ACKNOWLEDGMENTS
The authors would like to thank the Soil Mechanics
and Material Testing Laboratory and the Universal
Testing Machine Laboratory of Mapúa University forproviding assistance during experimentation.
REFERENCES[1] Dhir, R., De Brito, J., Lynn, C., and Silva, R.,
Sustainable Construction Materials Cambridge
Woodhead Publishing, 2018, pp.139-195.
[2] Ingham, J. P., Geomaterials Under theMicroscope a Colour Guide: Building Stone,
Roofing Slate, Aggregate, Concrete, Mortar,
Plaster, Bricks, Ceramics, and Bituminous
Mixtures United States, Academic Press, 2012,
pp.7-20.
[3] Veiga, M. D., Fragata, A., Velosa, A. L.,
Magalhães, A. C., and Margalha, G., Lime-based
Mortars: Viability for Use as Substitution Renders
in Historical Buildings, International Journal ofArchitectural Heritage, Vol. 4, Issue 2, 2010, pp
177-195.
[4] Zhang, D., Zhao, J., Wang, D., Xu, C., Zhai, M.,
and Ma, X., Comparative Study on the Properties652

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

IMPACTS OF WEATHER VARIABLES ON URBAN WATER DEMAND
AT MULTIPLE TEMPORAL SCALES

1,2,3

Chinnapan Makpiboon1, Adichai Pornprommin2 and Surachai Lipiwattanakarn3
Department of Water Resources Engineering, Faculty of Engineering, Kasetsart University, Thailand

ABSTRACT
Population growth and urban development have contributed to increase in base urban water demand in a longterm temporal scale. However, if we consider a short-term temporal scale, weather variability is an important factor
affecting daily, monthly, seasonal and annually water demands. This study examines the relationship between
urban water demand in the Metropolitan Waterworks Authority (MWA) service area, including Bangkok,
Nonthaburi and Samut Prakan provinces, and two weather variables; temperature and rainfall at various temporalscales. The growth of water demand was detrended and then normalized. The multiple linear regressions wereused for analysis of impacts from weather variables to urban water demand. Temperature had a strong negative
impact on the demand and the impacts were stronger for larger time scales. On the other hand, rainfall had a weak
positive impact on the demand but also gave more impact for larger time scales. As climate changes will affectboth temperature and rainfall, MWA should consider the weather variability for a better management of waterproduction and distribution.
Keywords: Unban Water Demand, Water Consumption, Multiple Temporal Scales, Weather Impact

on large metropolitan water demand in the hot humid
tropical climate. One of the models used for timeseries data analysis is time series linear regression
model [1]In this study, daily, monthly, seasonal andannually weather variables have been related to
MWA water demand. We then analyzed the temporal
effects with different time scales of these weather
variables on the water demand.

INTRODUCTION
The global water demand for domestic uses is
expected to increase significantly, especially in cities
and countries with developing economic growth [14].
In 1900, the global population lived in urban areas
just 13% and has been rising to 49% in 2005. As aprediction, the global population lives in urban areas
will rise to 60% in 2030. [13]. Bangkok as Thailand
capital city and its vicinity provinces (Nonthaburi andSamut Prakarn provinces) are growing rapidly, thewater demand provided by Metropolitan Waterworks
Authority (MWA) has increased from 4.76 million
cubic meters per day (MCM/day) in 2007 to 5.38
MCM/day in 2016. Understanding and forecasting
the water demand is one of the challenging tasks for
MWA.
Urban water demand is influenced by many
variables based on whether it is analyzed on temporalor spatial bases. The common explanatory variables
for temporal analysis are temperature, precipitation,wind speed, evaporation, water price, rate structure,income and population [4]. For weather related
variables, temperature and precipitation are the mostcommon ones. Impacts of climate and weather
variables on urban water demand have been studied
for nonlinear [7], linear [3] or a combination of bothlinear and nonlinear effects [11].
Urban water demand is also sensitive to timescale, especially seasonal time scale as pointed out by[4]. The temporal effects on urban water demand
whether on daily, monthly, seasonally or annuallytime scales have not been explicitly studied especially

STUDY AREA AND DATA
MWA is a sole water utility agency providing
potable water for Bangkok and its vicinity areas withmore than 10 million population. MWA provides
approximately 1,800 million cubic meters of potablewater in 2018. Our study area is the MWA service
area covering Bangkok, Nonthaburi and SamutFig. 1 Study area and weather stations
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 Detailed Information of Urban Water Demand Temporal Scales Dataset
Urban Water
Demand Dataset

Seasonal
Rainy

Daily

Monthly

Period1 Oct 2007 30 Sep 2017

Oct 2007 Sep 2017

Winter 2007 – Summer 2017

Number of Data

3,424 days*

116 months*

30 seasons*

Summer

Water Demand
Max (MCM/Day)
4.30
4.11
4.03
Min (MCM/Day)
3.04
3.23
3.54
Average (MCM/Day)
3.67
3.67
3.81
Temperature
Max ( oc)
34.15
31.90
31.10
Min ( oc)
18.20
25.12
28.72
Average ( oc)
29.17
29.19
30.24
Rainfall
Max (mm/day)
115.9017.65
5.89
Min (mm/day)
0.00
0.00
0.72
Average (mm/day)
5.09
5.16
2.81
Note:* exclude long holidays and during a 2011 mega flood (229 days)
Prakan provinces [6] MWA provides water demand
dataset consisting of daily water discharge andmonthly water demand. To obtain daily demand, we
assumed daily water loss by subtracting monthly
water discharge with water demand and averaging it
for daily water loss. The monthly and seasonal water
demand are then based on these daily data. Seasonal
data are sum of the daily data during a range ofseasons.
Weather dataset obtains from 5 Thai
Meteorological Department (TMD) stations, namely
Bangkok (455201), Khlong Toei Port (455203),
Bangna (455301), Don Muang Airport (455601) andSamut Prakarn (429301). TMD provided daily
temperature and rain data. According to TMD,
Thailand weather can be divided into 3 seasons.
Summer is between 16 February and 15 May, rainyseason is from 16 May to 15 October, and winter isfrom 16 October to 15 February. The period of thedata used in this study was between 1 October 2007
to 30 September 2017, totaling of 10 years.
According to the demand data, we foundextremely low water demand during October 2011January 2012 caused by a mega flood in 2011. We
also found that during long holidays (more than 3days) water demand was significantly lower thanusual. Therefore, we did not include these
unrepresentative demand data in our study. Detailed
information of urban water demand temporal scales
dataset is described in Table 1. Since our study is in
the tropical zone, the daily temperature was between
18.20oc and 34.15oc, and the seasonal water demand andtemperature did not vary greatly like those in thetemperate zone. However, in the rainy season, theamount of rainfall could be 3-5 times higher than that inother seasons.

Winter

3.90
3.42
3.68

3.80
3.32
3.58

29.90
29.06
29.47

29.02
26.80
28.05

10.75
6.33
9.00

3.50
0.69
1.86

METHODOLOGY
Normalization
To investigate the impact of weather on water
demand, we assumed that all other major variables
except weather-related variables present in the water
demand as a long-term time series trend. Afterremoving this trend, we then can relate weather data
to urban water demand. The time series model ofurban water demand can be expressed as:
𝐷𝑡 = 𝛼0 + ∑𝑣𝑗=1 𝛼𝑗 𝑡𝑗(1)where Dt is water demand at time t, α0 is theregression intercept and j is a polynomial term in thetrend component, v is a polynomial order and αj is thetrend coefficient. For our model, we used v as 1 for alinear trend component. We considered that all
growth-related variables such as population,
economics, and an urban growth are included in thetrend. After the model is constructed with daily data,
we removed this trend by subtracting it from water
demand such that̂𝑡 = 𝐷𝑜𝑏𝑠,𝑡 − 𝛼1 𝑡𝐷(2)̂𝑡 is the detrended water demand at time t.
where 𝐷̂ by using an
We then tested the stationarity of 𝐷
Augmented Dickey-Fuller (ADF) test [8]. The test is
aimed for an unknown lag time autoregressivemoving average model. However, for this study, a klag autoregressive model, AR(k), is considered andcan be given by the equation:

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Water Consumption
Normalized
Water DemandD'

T (oc)

Temparature

October 18, 2017

April 1, 2017

July 10, 2017

December 22, 2016

June 5, 2016

September 13, 2016

February 26, 2016

November 18, 2015

May 2, 2015

August 10, 2015

January 22, 2015

July 6, 2014

October 14, 2014

March 28, 2014

December 18, 2013

June 1, 2013

September 9, 2013

February 21, 2013

November 13, 2012

April 27, 2012

August 5, 2012

January 18, 2012

July 2, 2011

October 10, 2011

March 24, 2011

December 14, 2010

May 28, 2010

September 5, 2010

February 17, 2010

November 9, 2009

April 23, 2009

August 1, 2009

January 13, 2009

June 27, 2008

October 5, 2008

March 19, 2008

September 1, 2007

40
35
30
25
20
15

December 10, 2007

1.2
1.1
1.0
0.9
0.8
0.7

(a) Normalized water demand (D’) and temperature (T)D'

Normalized Water Demand

R (mm/day)

Rain

1.2
1.1
1.0
0.9
0.8
0.7

0
50
100
150

October 18, 2017

July 10, 2017

April 1, 2017

December 22, 2016

September 13, 2016

June 5, 2016

February 26, 2016

November 18, 2015

August 10, 2015

May 2, 2015

January 22, 2015

October 14, 2014

July 6, 2014

March 28, 2014

December 18, 2013

September 9, 2013

June 1, 2013

February 21, 2013

November 13, 2012

August 5, 2012

April 27, 2012

January 18, 2012

October 10, 2011

July 2, 2011

March 24, 2011

December 14, 2010

September 5, 2010

May 28, 2010

February 17, 2010

November 9, 2009

August 1, 2009

April 23, 2009

January 13, 2009

October 5, 2008

June 27, 2008

March 19, 2008

September 1, 2007

December 10, 2007

200(b) Normalized water demand (D’) and rainfall (R)Fig. 2

Temporal changes of daily normalized water demand with (a) temperature and (b) rainfall

̂𝑡 = 𝛼𝐷̂𝑡−1 + ∑𝑘−1̂∆𝐷
𝑗=1 𝛽𝑗 ∆𝐷𝑡−1 + 𝑒𝑡

𝐷𝑡′ = 𝛽0 + ∑𝑛𝑖=1 𝛽𝑖 𝑥𝑖,𝑡(3)

where 𝐷𝑡′ is the normalized water demand at timet, 𝛽0 is the regression intercept and i is an index of ith
independent variable, n is the number of variables and𝑥𝑖,𝑡 is a value of ith independent variable at time t. Our
independent variables are temperature (i = 1) andrainfall (i = 2).

where ∆ is the difference operator, 𝑒𝑡 is a white
noise sequence of random variables, α and 𝛽𝑗 are thecoefficients. The null hypothesis of the unit root testis that the time series data has a unit root and is notstationary. If the null hypothesis is rejected then thetime series data is stationary.
After proving for its stationarity, we normalized
the detrended daily water demands by dividing themwith 𝛼0 from (1) to analyze the demands as a ratio.
This would give an easy understanding on impact ofweather variables to the water demand.
̂𝑡 /𝛼0𝐷𝑡′ = 𝐷(5)

RESULTS AND DISCUSSION
Normalized Water Demand
To find the urban growth trend of daily water
demands, a simple time series model (1) was adopted.
We found the relationship based on the start of ourdata (October 2011) to be(4)

Multiple Regression Analysis

𝐷𝑡 = 3.3846 + 1.5696 ∗ 10−4 𝑡

A multiple regression is a simple linear regression
extension used when we predict two or more the valueof a variable. The variables we predict are called
dependent variables or target variables. A linear
relationship is assumed between two variables. Linear
regression is a commonly used statistical analysis inwater demand while nonlinear regression is used tovarious growth models [10]. Results in one variable
can be predicted from the others [9].
After removing the long-term trend andnormalizing the detrended data, the influences ofweather-related variables on normalized water
demand can be described by a multiple linear
regression model which is based on the basis ofrelationship between water demand and its
determinants. Our model can be expressed as:(6)

where 𝛼0 = 3.3846 MCM/day and 𝛼1 =1.5696x10-4 MCM/day2. Thus, the yearly average
growth of water demand of MWA for 2007-2017 wasroughly 0.0573 MCM/year (+1.7%).
We removed this trend for a zero-slope
adjustment by subtracting it from water demand tô𝑡 in (2). We thenobtain the detrended water demand 𝐷
̂𝑡 by dividing it with 𝛼0 in (4).
normalized 𝐷
Consequently, we have the normalized water demand𝐷𝑡′ that ranged between 0.8 to 1.2 due to temperature(T) and rainfall (R) as shown in Fig.2.

655

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Results of multivariable linear regression of the normalized water demand (D’) to the averagetemperature (T) and the rainfall (R) in the daily, monthly and seasonally temporal scales.
Coefficients
𝜷𝟏 for T
𝜷𝟐 for R(1/ oc)(day/mm)Daily
0.0152-0.00017
Monthly
0.0187-0.00189
Seasonal
0.0238-0.00291
Note:*Significant at the 0.01 level
Normalized
water demandt Stat𝜷𝟎 asintercept
0.55710.4656
0.3224P-value

T

R

T

R

40.5224
7.66678.6211-2.9464-2.8275-3.3784

1.23E-293
8.54E-12
3.09E-90.00320.00560.0022

Weather Variability Analysis

Impact of Weather Variables on Demand

Impacts of weather variables, temperature andrainfall, were analyzed using a multiple linear
regression in the following equation:

The results of multiple linear regression for daily,
monthly and seasonal were compared with the datasets in
Figs. 3, 4 and 5, respectively, showing the impact oftemperature and rainfall on MWA water demand.
From Fig. 3, the normalized daily water demands
ranged between 0.8 and 1.2 with the daily temperature
between 21oc and 34oc. A clear trend between
temperature and water demand can be seen. The line ofrainfall at levels 2, 6 and 10 mm/day are overlapping line.
Many previous research studies in the temperate climate
have found the temperature and rainfall thresholds forurban water demand. For example, [2] show that
residential water use for East Doncaster, Victoria,
Australia is not affected by temperature changes at 15.3oc
or below and at rainfall level of 4.8 mm or higher. For ourstudy area in the tropical climate, however, we cannot findthose thresholds. It is possible that our lowest temperature
is still higher than the threshold value.
Fig. 4 shows monthly water demand related totemperature and rainfall. Rainfall line at levels 2, 6 and 10
mm/day show a slight difference. A similar tendency as
the daily case that water demand increases withtemperature and decrease with rainfall can be found.
However, the range of temperature decreases to be
between 26oc and 32oc due to monthly averaging.
Rainfall lines at levels 2, 6, and 10 mm/day show
clearer differences in Fig 5a and 5b. Then, clearer
impact on temperature and rainfall on water demand canbe observed in the seasonal case in Fig. 5a. Also, in Fig.
5b where the data were divided according to seasons,
it is clear that temperature and rainfall in each season
are different. In summer, high water demand is due tohigh temperature while, in winter, low temperaturecauses low water demand. As the temperature in rainyseason is moderate, water demand is low due torainfall.
In Fig. 3 shows the amount of data, the data has a highfrequency, but there is an unclear relationship with theweather. While Fig. 4 and 5 use the monthly and seasonal
solutions, but clearly show the relationship of weather
conditions and higher water demand.

𝐷𝑡′ = 𝛽0 + 𝛽1 𝑇𝑡 + 𝛽2 𝑅𝑡(7)where 𝑻𝒕 is temperature and 𝑹𝒕 is rainfall.
Table 2 shows the results from the regression. The
statistics in the table are composed of coefficients of
the regression variables, t Stat and P-value. The
coefficient values show how strong the impact ofeach variable on the normalized water demand. From
the results, an increase in 1c of the temperaturecaused an increase in 1.52%, 1.87% and 2.38% of thewater demands in the cases of the daily, monthly andseasonal time scales, respectively. However, an
increase in 10 mm/day of the rainfall caused adecrease in 0.17%, 1.89% and 2.91% of the water
demands in the cases of the daily, monthly andseasonal time scales, respectively. In conclusion,
temperature generates a higher demand while rainfall
leads to a lower demand. Also, the time scale became
larger, the impact was stronger.
We tested the significance of the independent
variables, the temperature (T) and the rainfall (R)using t stat and P-value at the 0.01 significance levelas shown in Table 2. The t stat values show how large
the coefficients compare to the standard error. The
larger value of t stat indicates the more significanceof the variable. The P-value is the probability that thevariables have no effect on the dependent, thenormalized urban demand in this case.
For temperature, the T-stat value for daily is muchhigher than monthly and seasonal values, indicatingthat the model for daily tends to be more accurate.
Also, the P-value for daily is significantly lower thanthose for monthly and seasonal, indicating the samemessage. The t Stat and P-value results show thatrainfall is less significant than temperature. In
addition, the daily, monthly and seasonal models with
rainfall tend to have the same accuracy.

656

SEE - Bangkok, Thailand, Nov.11-13, 2019

D'

1.20
1.10
1.00
0.90
0.80

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

T (oc)

Fig. 3 Relationship between daily normalize urban water demand dataset, temperature and rainfall dataset
during winter 2007 – summer 2017
D'
1.10

0<R<4
4 <R<8R>8Line R = 2 mm/day
Line R = 6 mm/day
Line R = 10 mm/day

1.05
1.00
0.95
0.90
26

27

28

29

30

31

o

32 T ( c)Fig. 4 Relationship between monthly normalize urban water demand dataset, temperature and rainfall dataset
during winter 2007 – summer 2017 in the MWA service area
D'
1.10
1.05

0<R<4
4<R<8
R>8
Line R=2 mm/day
Line R = 6 mm/day
Line R = 10 mm/day(a) vary with rainfall

1.00
0.95
0.90
26

27

28

29

30

31

32

(T)oc

D'
1.10

Rainy
Summer
WinterLine R=2 mm/day
Line R = 6 mm/day
Line R = 10 mm/day(b) vary with seasons

1.05
1.00
0.95
0.90
26

27

28

29

30

31

32 (T)oc

Fig. 5 Relationship between seasonal normalize urban water demand dataset, temperature and rainfall dataset
during winter 2007 – summer 2017 (a) and show the amount of rainfall of each season. (b)0.024 oc per years, especially in the metropolitan areas
where the urban temperature is higher than otherplaces due to a dome heat island effect [12]. Thiscondition will increase urban water demand.
Statistical analyzes of urban water demand of
Bangkok, Nonthaburi and Samut Prakan provinces

CONCLUSIONS
The average temperature of the world isconstantly rising. Thailand is also affected by global
warming. Over the past 40 years, between 1970 –2009, the average temperature in Thailand rose about
657

SEE - Bangkok, Thailand, Nov.11-13, 2019

water demand modeling: Review of concepts,
methods, and organizing principles. Water
Resources Research, 47, 15[5] Meteorological Department. (2018), Website ofMeteorological Department (Thailand), Topic“Academic: Meteorological Book "Season ofThailand"”https://www.tmd.go.th/info/info.php?FileID=53[6] Metropolitan
Waterworks
Authority.
(2018),Website of Metropolitan Waterworks
Authority (Thailand), Topic “About MWA:The
Metropolitan Waterworks Authority’s History”
https://www.mwa.co.th/ewtadmin/ewt/mwa_internet_eng/ewt_news.php?nid=349[7] Miaou, S., (1990), A Class of Time Series Urban
Water Demand Model with Nonlinear Climatic
Effects, Water Resources Research, Vol. 26(2),169-178.
[8] Said, E.S. & Dickey, D.A. (1984), Testing for unit
roots in autoregreive-moving average models of
unknown order, Biometric, 71, 3, pp. 599-607.
[9] Indian Agricultural Statistics Research Institute(IASRI), (2018), Regression Analysis Library
Avenue, PUSA, New Delhi - 110 012 (INDIA)
www.iasri.res.in/ebook/win_school_aa/notes/Re
gression_Analysis.pdf[10] Statistics Solution. (2018), website Complete
Dissertationby
Statistics
Solution,
http://www.statisticssolutions.com/what-ismultiple-linear-regression/[11] Toth, E., Bragalli, C. & Neri., M. (2018),
Assessing the significance of tourism and climate
on residential water demand: Panel-data analysis
andnon-linear
modellingofmonthly
consumptions, Environmental Modelling &Software, 103, 2-61.
[12] Limsakul, S. L. a. A. 2012. AtmosphericResearch: Trends in Thailand pan evaporationfrom 1970 to 2007. ELSEVIER: 6.
[13] United Nations, (2018), World Urbanization
Prospects: The 2018 Revision [Key Facts]. United
Nations.
[14] WWAP (United Nations World Water
Assessment Programme) (2014), The United
Nations World Water Development Report 2014:
Water and Energy (Paris: UNESCO)

showed that temperature and rainfall influence theurban water demand in the daily, monthly andseasonal time scale. While an increase in 1c of thetemperature caused an increase in 1.52%, 1.87% and2.38% of the water demands in the cases of the daily,
monthly and seasonal time scales, respectively, an
increase in 10 mm/day of the rainfall caused adecrease in 0.17%, 1.89% and 2.91% of the water
demands, respectively. Using t stat and P-value,
temperature is a more significant variable thanrainfall, especially in the daily time scale. Unlike inthe temperate climate, we could not find thetemperature and rainfall thresholds for urban water
demand in our tropical climate study area. The
weather effect to water demand with different scalelevels will provide a clear result for evaluating thequantity requirements as well, depending on the
purpose of short-term and long-term water demandplanning. These weather factors can be accompaniedwith other urban growth factors, such as population
density, immigration or expansion, type of urban landuse, the network of transport routes and etc.
ACKNOWLEDGEMENTS
The authors would like to thank the Metropolitan
Waterworks Authority (MWA) and the Thai
Meteorological Department (TMD) for supporting
the data used in this study.
REFERENCES[1] Donkor, E. A., Mazzuchi, T.A., Soyer, R., &Roberson, J.A., (2014), Urban Water Demand
Forecasting: Review of Methodsand Models, J.
Water Resour. Plann. Manage., 140(2): 146-159[2] Gato, S., Jayasuriya, N. and Roberts, P. (2007),
Temperature and rainfall thresholds for baseuse urban water demand modelling. Journal of
Hydrology 337 (3-4), pp.364– 376[3] Goodchild., C. W. (2003). Modelling the impact
of climate change on domestic water demand. The
Journal. V17 N1: 5.
[4] House-Peters, L. A., & Chang, H. (2011). Urban658

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

GROUNDWATER LEVEL RISE IN MUSCAT AIRPORT AREA AND
WAYS OF MANAGING THE ISSUE

1, 2, 3

Luminda Gunawardhana1, Mahad Baawain2 and Ahmed Sana3
Civil and Architectural Engineering Department, Sultan Qaboos University, Oman

ABSTRACT
Despite the arid climate and scare water resources, groundwater level rises in some areas of Muscat, thecapital city of Oman. Consequent impacts have already been detected in manholes around the new runaway,
where groundwater seepage into basements of utility lines. The objective of this study is to simulate thegroundwater flow in the airport area, which then can be used to propose countermeasures for lowering the
groundwater levels as applicable. There are 8 pumping wells and 16 monitoring wells were drilled around the
runaway and the terminal building to conduct pumping test and to estimate the aquifer properties such as thetransmissivity and specific yield. Estimated aquifer properties were then used to develop a three-dimensional
groundwater flow model using MODFLOW software. Steady state model calibration and verification were doneusing two independent data sets in 15 monitoring wells in 2017 and 2018. Four pumping scenarios wereconsidered for lowering the average groundwater level by 0.5m. Model results show that potential water volume
that can be withdrawn from existing pumping wells with highest pumping rates is about 8.4% of water coming
into the model from the upstream mountain area. It was estimated that altogether 24 pumping wells with thepumping rates vary from 222 to 1564 m3/day, are required to achieve the expected reduction. Two pumping
scenarios were proposed to guide the operations in different situations. It is expected to carry out further
investigations to calibrate the proposed pumping rates and to understand aquifer response for long-term pumping.
Keywords: Pumping test, Neuman method, MODFLOW, Numerical modelingbirds strike during runaway operations, flooding ofunderground tunnels and low-lying infrastructures,erosion into underground utilities lines and cables
and decrease groundwater quality due tocontaminants in shallow subsurface layers and interaquifer leakage [3].
In recent years, continuous increase in shallow
groundwater table has been observed in many
manholes installed in the Muscat International
Airport. Under drains beneath the foundation of thestructures and groundwater pumping wells arecommon strategies apply to prevent undergroundflooding. For example, groundwater within 1m of
the ground surface was a major challenge to the
runaway operations in Munich airport, West
Germany. Two longitudinal ditches and a system ofdrains between the runways were able to lower the
groundwater table by around 2m [4]. Mohamed [5]used finite difference numerical modeling approachto show that the local groundwater level can belowered by means of pumping wells operate in thevicinity of the area of interest.
Current problems and aticipated issues withrising groundwater level can be prevented bypumping adequate amount of water from the shallow
aquifer. The objective of this study is to simulate thegroundwater flow in the Muscat airport area andpropose operational plans to lower the groundwaterlevel around the runaway.

INTRODUCTION
Over the past decades, economic development,
rapid population growth and agricultural activities
have increased the stress on groundwater aquifers in
Gulf Cooperation Council (GCC) countries.
Sultanate of Oman is no exception to this. Annual
total rainfall averaged over the country isapproximately 130mm, which is about 10% of the
global average annual rainfall [1]. Consequently,
over exploiting aquifers became vulnerable to theseawater intrusion. For example, the total land area
affected in the governorates of Batinah, which
locates next to the Muscat governorate, grew from
840 hectares in 1995 to 6930 hectares in 2010 [2].
Muscat airport area, which is located in the heartof the Muscat city, however experiences opposite
phenominon over the last decade. Oman Airport
Management Company (OAMC) was alarmed when
the groundwater level rises over 1.5m in most of its
observation wells since 2010. This effect is likely aresult of the groundwater recharge from extreme
rainfall events occured in 2007 (Cyclone Gonu) and2010 (Cyclone Phet), decline in agriculturalactivities in the area due to increase urbanization andwater lecage from sewer lines and septic tanks.
The potential impacts of rising groundwaterlevels include, increase in uplift forces on buried
water infrastructure and buildings, increase risk of659

SEE - Bangkok, Thailand, Nov.11-13, 2019

8 production wells and 16 monitoring wells (Fig. 3).
Each production well (PW) is 25m deep and consists
with 2 monitoring wells at 10m and 50m distances.

STUD AREA AND DATA COLLECTION
Muscat is the capital city of Oman located at thesoutheast tip of the Arabian Peninsula. It is a coastal
city where the Muscat International Airport islocated in the vicinity of the coast. Upstream side of
the catchment area consists of a series of rugged
mountains and Ophiolite hills run parallel to thecoastline. According to the rainfall records during
1991 to 2010, annual total rainfall is approximately
87mm with 73% of that occurred from November toApril when the cold frontal troughs are active [6].
Tropical cyclones such as Cyclone Gonu in 2007
and Cyclone Phet in 2010 are rare but brings
extreme rainfall causing substantial damages.
There are 15 observation wells maintained by
the OAMC to monitor the groundwater level inside
the airport (Fig. 1). Among them, 11 wells have themonthly observations from 2010 to 2018 (W1-W11).
Of these 11 wells, four wells (W8-W11) are locatedadjacent and parallel to the coastline. Observation
wells W13-W15 have the observations from 2017 to
2018.

(a)
Averaged water level change (m)

2.0

W1-W7

1.5

1.0

0.5

0.0

-0.5
2010

2014

2016

2018

2020

(b)
Averaged water level change (m)

0.6

W4

W8-W11

0.4
0.2
0.0
-0.2
-0.4
-0.6
2010

Fig. 1

2012

2012

2014

2016

2018

2020

Fig. 2Averaged water level changes in W8-W11.

Fig. 3

Production wells used for the pumping test.

Study area and the location of wells.

Figure 2 shows the change in groundwater levelcompared to the monthly averaged water level in2010. All the wells in the interior (W1-W7) show asimilar pattern where groundwater levels risesignificantly between 2010 and 2015. When thewater level changes were averaged in seven wells(W1-W7), Fig. 2a depicts nearly a 1.5m rise over 5
years. The large mass of seawater body with aconstant head is acting as a barrier for groundwaterlevel variation near to the coastal line. Therefore,groundwater level rise in W8-W11 (Fig. 2b) is not assignificant as in interior wells.
Simulation of the groundwater level requires
proper understanding of aquifer properties such as
hydraulic conductivity and specific yield. Therefore,a series of pumping tests were conducted by drilling
660

SEE - Bangkok, Thailand, Nov.11-13, 2019

𝑄

Figure 4 shows the groundwater levels recorded in
an observation well during the one and halve
daylong test. The observation well is located at a
10m distance from the production well (PW6).
Water was pumped at a constant rate of 18
liters/second in PW6 for 24 hours and recovery test
was conducted for another 12 hours. Water levels
were recorded in all three wells (production well andtwo observation wells) at 15 seconds interval at the
beginning of the test. The time interval was
gradually increased to 1-hour during the later stageof the test. The drawdown is significant in the
production well (4.18m in PW-6) but decreases
greatly towards the observation wells (1.56m and
0.78m at 10m and 50m wells, respectively).

𝑠 = 4𝜋𝑇 𝑊(𝑢𝑎 , 𝑢𝑦 , 𝜂)
here,
𝑟 2𝑆

𝑢𝑎 = 4𝑇𝑡 (applicable for early drawdown data)𝑟 2𝑆

𝑢𝑦 = 4𝑇𝑡𝑦 (applicable for later drawdown data)𝑟 2𝐾

𝜂 = 𝑏2 𝐾𝑧

Water level (m)

2.0

1.5
1.0
0.5
0.0
-0.5
6:00

14:00

22:00

Day-1

Fig. 4

6:00

14:00

22:00
𝜕

Day-2

𝜕𝑥

Groundwater levels in the observation well.

The recovery test is used to estimate thetransmissivity of the aquifer. It is assumed that if awell is pumped for a known period of time and thenshutdown, the drawdown thereafter (known as theresidual drawdown) will be identically the same as if
the pumping had been continued and a hypothetical
recharge well with the same flow rate weresuperposed on the pumping well at the instant theactual pumping is stopped [7]. Accordingly,
transmissivity (T in m2/day) can be written as:
2.3𝑄

𝑡

[𝑘𝑥

𝜕ℎ
𝜕𝑥

]+

𝜕
𝜕𝑦

[𝑘𝑦

𝜕ℎ
𝜕𝑦

]+

𝜕
𝜕𝑧

[𝑘𝑧

𝜕ℎ
𝜕𝑧

] − 𝑊 = 𝑆𝑠

𝜕ℎ
𝜕𝑡

(6)

where, kx, ky and kz are hydraulic conductivities(m/day) in x, y and z directions, respectively, h (m)is the groundwater head, W is the groundwater
recharge or discharge per unit volume (day-1) and Ss
is the specific storage (m-1).
The aquifer is an alluvial, unconfined layer withan average thickness of 70m from the mean sea level.
The modeled area is approximately 12.5 km longand 5 km wide (Fig. 5). The entire area was divided
into 294092 active square cells of size 20 by 20 m.
The top elevations of the cells were assigned based
on topography contour maps prepared by OAMC.
The western and eastern boundaries of the model
were assumed to follow the catchment boundary andassigned no-flow boundary condition (Fig. 5). A
constant head boundary condition was used for thecoastal side boundary. The upstream boundary
condition was determined based on water level datain the observation well maintained by the Ministryof Regional Municipality and Water Resources(MRMWR). An automated parameter calibration
was carried out to estimate the recharge rate and tofine-tune the hydraulic conductivity values obtained
from pumping test data. Steady state model
calibration and verification were done using two
independent data sets in 2017 and 2018. For this,observations in 15 monitoring wells shown in Fig. 1
were used.

THEORY AND METHOD

𝑇 = 4𝜋𝑠 ′ log (𝑡 ′ )(4)where, r is the distance from the pumping well to theobservation well, Sy is the specific yield, b is theinitial saturated thickness of the unconfined aquiferand Kh and Kv are the horizontal and verticalhydraulic conductivity, respectively. Plotting thegraph of drawdown versus time and matching it with
the Neuman’s theoretical curves, hydraulicconductivities and the specific yield can be
estimated.
Aquifer properties found from the pumping tests
were used for simulating the groundwater flow inthe study area. A three-dimensional groundwaterflow model was developed using the MODFLOW
software. The principal governing equation used tosimulate the water flow is as follows [9].

Pumping test
Recovery test
Ground surface
Static water level

2.5

(3)

(5)

ℎ

3.5
3.0

(2)

(1)

where, Q is the pumping rate (m3/day), s′ is theresidual drawdown (m), t (min) is the time since thepumping test was started and t′ (min) is the timesince the recovery test was started. The gradient of aplot of s′ versus the logarithm of t/t′ is used toestimate T.
Neuman [8] theory on unsteady radial flow in
unconfined aquifer can be used to estimate thehydraulic conductivity and specific yield. The
drawdown (s) subjected to a constant pumping rate
is given as follows.
661

SEE - Bangkok, Thailand, Nov.11-13, 2019(a)
Residual drawdown (m)1.2

Recovery test

1.0
0.8
0.6
0.4

s′ = 0.28 Log (t/t′)
R² = 0.90

0.2
0.0
0.0

Fig. 5Boundary conditions of the model.

Dradown after 1- day (m)Fig. 7

Figure 8 shows the comparison of observed andsimulated groundwater levels during model
calibration (2017) and verification (2018) stages. In
general, calibration standards for numericalgroundwater flow simulation agree that the numberof observation wells with an absolute error level lessthan 0.5m in simulation must be greater than 70% of
all observation wells [10]. Model results indicatethat 93% of all wells have absolute error less than
0.5m with estimated RMSE of 0.14m duringcalibration stage. Two wells in 2018 simulation
show a significant error approximately equals to
1.5m. This can be attributed to the local pumping in
the airport. Consequently, model verification depicts
that about 69% of the wells have absolute error lessthan 0.5m with estimated RMSE of 0.47m.
Contour lines drawn for the simulated
groundwater levels indicates that the dominantgroundwater flow is from southwest to northeast
direction of the study area (Fig. 9). Total water
volume that can be withdrawn from the PWs (Fig. 3)
when they are operated at the highest yield is about

3.0
MW-15
MW-16

0.0
10

20

30

40

50

Distance from the pumping well (m)Fig. 6

Pumping test results at MW-15

MODFLOW model calibration and verification

PW-6

0

4.0

Neuman test

5.0

1.0

3.0

(b)

Figure 6 shows the drawdown in the pumping
well PW-6 and in two observation wells at 10m and
50m distances away (MW-15 and MW-16,
respectively) from the pumping well. It wasobserved that the drawdown is significant closer tothe pumping well, but decays exponentially as the
distance from the pumping well increases. The
recovery test was carried out for 24 data sets (8 PWs
and 16 MWs). Figure 7a shows the relation between
residual drawdown (s′) and the logarithm of t/t′ ratio
for the observations in MW-15. The gradient of thebest-fit line along with the Eq. (1) were used to
calculate the transmissivity and the corresponding
hydraulic conductivity.
Similarly, drawdown data and residual
drawdown data in 24 wells were used to fit the
Neuman type curves using AQTESOLV software.
Figure 7b shows the fitted curve for the observationsin MW-15 well. Based on results of two tests andobservation in three wells, the estimated hydraulicconductivity ranges from 37 m/day to 49 m/day forthe pumping test in PW-6. The average hydraulicconductivity estimated from all the wells range from
6.4 m/day in PW-1 to 169 m/day in PW-7. These
values were used for defining different hydrologicalzones in the study area and further adjusted during
the calibration process of the MODFLOW model.

2.0

2.0

Time ratio in log scale (Log (t/t′))

RESULTS AND DISCUSSION

4.0

1.0

Change in drawdown with the distance.

662

SEE - Bangkok, Thailand, Nov.11-13, 20197943 m3/day. It is approximately equals to 8.4% of
the water enters to the study area through the
upstream boundary (94091 m3/day). By applying aproper strategy, it is expected to lower the
groundwater level by 0.5m around the runaway.
Therefore, an additional set of wells with anappropriate operational plan would be required toachieve the above reduction in groundwater levels.

2.

3.

Model Calibr ation (2017)

Computed Gr ouundwater Level (m)7R² = 0.95

65

All three scenarios were continued for four more
pumping sessions extending the total model
simulations for 98 days. Figure 9a shows acomparison of groundwater level change between
initial stage (prior to the pumping starts) and after
five sessions of pumping according to Scenario 2.
When the runaway area is considered, Point A in
Fig. 9a showed the highest groundwater level of
3.8m, which according to Scenario 2 can be reduced
to 3.1m after five pumping sessions (Fig. 9b). The
lowest groundwater level of 1m was simulated in the
runaway area at Point B. This water level can be
reduced to 0.6m during the same time.
Model results show that pumping only fromexisting wells with the highest yield (Scenario 1) is
not sufficient to lower groundwater level by 0.5m. It
was able to lower the groundwater levels by 0.11m
and 0.13m at points A and B, respectively. Scenario
3 explores the possibility of shutting down somepumps for the maintenance purposes while
maintaining the lowered water levels. Model results
estimated that approximately 0.57m and 0.34m
water level reduction can be expected at points A
and B, respectively with operating 50% of thepumps at a time.

4
3
2
1
0
0

1

2
3
4
5
6
Obser ved Gr ouundwater Level (m)7Model Ver ification (2018)

Computed Gr oundwater Level (m)7R² = 0.84

6production wells (PWs) continuously for two
weeks and recovery for one week. Repeat thesame steps for four more times.
Two-week pumping and one-week recovery
from all 24 wells (8 PWs and 16 NPWs). An
average pumping rate of 1500 m3/day was
assigned for the NPWs.
Two Set of pumps with only one set operating
at a time. All 24 wells were divided to two
equal sets with each set covering the entire
focused area. While the first set of pumps
operates for two weeks, the other set remained
nonoperational. While the recovery is started forthe first set of pumps for one-week, the other setof pumps operate.

5
4
3
2
1

CONCLUSION
This study was conducted to simulate thegroundwater flow in the Muscat airport area for
proposing countermeasures to lower the water levels
about 0.5m near the runaway area. According to themodel results, drawdown due to pumping fromexisting eight production wells is significant only
near to the pumping wells. Reducing water level
over a large area surrounding the runaway therefore
requires additional set of wells. Among the threepumping scenarios were simulated, two of them withan additional set of pumps indicated the possibilityof achieving the required water level reduction.
However, further studies with actual field testing
pumping sessions are required to understand thelong-term pumping effects on reducing the
groundwater levels.

0-10Fig. 82
4
6Obser ved Gr oundwater Level (m)Observed and simulated water levels.

Pumping Scenarios
Due to the significant amount of water enters to
the study area through the upstream boundary, 16
new production wells (NPWs) were added aroundthe runaway and the terminal building. Threepumping scenarios were considered as follows.
1. Pumping with maximum yield (range from 222
m3/day to 1564 m3/day) in existing eight663

SEE - Bangkok, Thailand, Nov.11-13, 2019(a) Initial groundwater levels from steady state

Point B

Point A(b) Groundwater levels after five pumping sessions

Fig. 9Groundwater levels in Scenario 2.
Under Buildings. International Journal ofApplied Engineering Research, Vol. 9, 2014, pp.
9989-10003.
[6] Gunawardhana L. N., and Al-Rawas G. A., A
Comparison of Trends in Extreme Rainfall Using
20-Year Data in Three major Cities in Oman.
The Journal of Engineering Research, Vol. 13,
Issue 2, 2016, pp. 137-148.
[7] Todd D. K., and Mays L. W., Groundwater
Hydrology, John Wiley & Sons, 2004, pp. 170172.
[8] Neuman, S. P., Theory of Flow in Unconfined
Aquifers Considering Delayed Response of theWater Table. Water Resources Research, Vol. 81972, pp. 1031-1045.
[9] McDonald M. G., and Harbaugh A. W., A
Modular Three-Dimensional Finite-Difference
Ground-Water Flow Model. Techniques ofWater-Resources Investigations of the UnitedStates Geological Survey, 1988.
[10] Du X., Lu X., Hou J., and Ye X., Improving the
Reliability of Numerical Groundwater Modelingin a Data-Spares Region. Water, Vol. 10, paper
289, 2018, pp. 1-15.

REFERENCES[1] Gunawardhana L. N., Al-Rawas G. A., Kwarteng
A. Y., Al-Wardy M., and Charabi Y., Potential
Changes in the Number of Wet Days and ITS
Effect on Future Intense and Annual
Precipitation in Northern Oman. Hydrology
Research, Vol. 49, Issue 1, 2018, pp. 237-250.
[2] ICBA., Oman Salinity Strategy. International
Center for Biosaline Agriculture. 2012, pp. 1130.
[3] Washington State Department of Transportation
Aviation Division, Guidance for Developing a
Stormwater
Management
Manualfor
Washington State: Mitigating Hazards due toWildlife Attractions at Airports. Technical
Memorandum, Arlington, Washington, 2007.
[4] Munich Airport Environmental Statement(2008).
https://www.munichairport.de/media/download/general/publikationen/en/Umwelterkl__rung_2008_englisch.pdf[5] Mohamed H. I., Effect of Dewatering Schemeson Uplift Pressure and Groundwater Variation

664

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

LIGHTWEIGHT FOAMED CONCRETE INTERLOCKING BLOCKUTILISING UNGROUND OIL PALM ASH
Hanizam Awang 1, Mohammed Zuhear Al-Mulali 2 and Wenny Arminda 3
School of Housing, Building and Planning, Universiti Sains Malaysia, Malaysia;
2
Department of Civil Engineering, Al-Mustaqbal University College, Babylon, Iraq
1,3

ABSTRACTThis study examines the properties of lightweight foamed concrete interlocking block with a density of
1300kg/m3 and containing 35% unground oil palm ash (UOPA) as cement replacement. The UOPA foamed
concrete interlocking blocks were produced in three shapes including stretcher, base and the half block. From
the testing conducted, it was found that the compressive strength of the stretcher, half block, and the baseblock is 3.75, 4.29 and 3.00 MPa, respectively. The UOPA foamed concrete interlocking block achieved ahigher strength than the specified minimum strength of 2.8MPa by BS 5628.
Keywords: Foamed concrete, Oil palm ash, Cement replacement, Interlocking block

economic value dumps or selected types of landsuch as swamp lands and abandoned sand quarries[10]. These disposal methods are conductedwithout taking into consideration the surrounding
environment or taking precautions to compact,
cover and prevent the spreading of pollutants into
the ground water levels [11]. In addition, due to its
fine particles, OPA can be easily carried away
causing smog in humid days [12].
Although OPA is a relatively new pozzolanicmaterial, a number of researchers have used it as a
cement replacement or as a filler replacement in
the production of concrete [13], high strength
concrete [14], aerated concrete [15] andlightweight concrete [16]. The OPA used has beenprocessed by either grinding to achieve a higher
fineness, by heat treatment to reduce the amount ofcarbon content or using both treatments. Althoughthese enhancements are beneficial in making OPA
a good pozzolanic material, they considerablyincrease the cost [17]. As a result of thisutilisation, the prospect of broadening therecycling methods of this waste is increased.
This study introduced the OPA to manufacture
a new designed interlocking block. Interlocking
block systems are known to be made fromconventional concrete. As a result, these blocks areheavy and poor in thermal insulation properties.
The newly design will be made out of OPA
foamed concrete, hence, it is lightweight andpossess all the good properties of thermal and fire
resistance. The block system is environmentallyfriendly due to the utilisation of a waste material in
its fabrication.
In this study, the foamed concrete specimens
using unground OPA (UOPA) passing through a
300 μm sieve were cast into three different shapeof interlocking block. This study was conducted to

INTRODUCTION
Foamed concrete is a mortar based or slurrymaterial with mechanically entrained air bubbles
that have a minimum volume of 20%. In foamed
concrete, air bubbles are introduced to the basemix (mortar or cement slurry) by mixing a stablepre-formed foam which, in itself, is a mixture ofcompressed air and a suitable foaming agent [1].
Due to its energy saving and environmentallyfriendly features, the construction industry iscurrently paying considerable attention to foamed
concrete [2]. Foamed concrete is becoming an
innovational product because it offers a better fire
protection, superior heat and sound insulation as
well as diverse range of densities lower than thatof conventional concrete (1000 kg/m3 to 1600kg/m3) [3]. However, to improve the properties of
foamed concrete and cost saving, many studies
have endeavored to use supplementary cementing
materials as cement replacements [4]. One of thepotential supplementary cementing materials is oilpalm ash.
Oil palm ash (OPA) is an agriculturally based
waste material existing in countries with abooming palm oil industry. As an alternative fuelsource, palm oil mills use the biomass (shell andfibres) as boiler fuel for producing steam [5] andelectricity for the mill’s internal use [6]. In
Malaysia alone, about 4 million tonnes of OPA are
produced annually and the amount increase every
year [7] [8]. OPA amounts are deemed to rise in
Malaysia due to the implementation of a project
introduced by the Malaysian government which
utilises the biomass produced by the palm oil
industry to generate power [9]. OPA is commonly
disposed of by either spreading the waste over thepremises of the mill or dumping it in low
665

SEE - Bangkok, Thailand, Nov.11-13, 2019

investigate the strength and failure mechanism of
the foamed concrete interlocking blocks.

MATERIALS AND MIXTURE DESIGNThe foamed concrete having design density of
1300kg/m3 and filler to binder ratio of 1.5 has beencast using Type I cement complying with BS EN
196 [18] and unground oil palm ash (UOPA) as
cement replacement.
The raw UOPA that was collected from anearby oil palm mill is a product from the
combustion of palm oil biomass at thetemperatures exceeding 1000ºC. The UOPA wasdried in an oven for 24 hours at a temperature of
105 ºC then sieved through a 300 μm sieve to
remove any unburned fibress and large size
particles. Table 1 lists the chemical compositionand physical properties of both cement and UOPA
used in this study.

(a) SEM imagery of cement particles at a 10000X
magnification

Table 1 Chemical and physical properties of
cement and UOPA
Chemical Composition (%)
Silicon Dioxide (SiO2)
Aluminium Oxide (Al2O3)
Iron Oxide (Fe2O3)
Calcium Oxide (CaO)
Magnesium Oxide (MgO)
Sulphur Trioxide (SO3)
Alkalis (Na2O)
Loss on Ignition (LOI)
SiO2+Al2O3+Fe2O3Median particle size d50 (μm)
Specific gravity
Loose bulk density (kg/m3)
Blaine surface area (cm2/g)

Cement
19.98
5.17
3.27
63.17
0.79
2.38
---5.73
2.85
1180
3924

(b) SEM imagery of UOPA particles at a 10000X
magnification

UOPA
66.64
3.82
3.69
5.23
2.29
0.43
0.15
6.09
74.15
101.81
1.65
833.6
1952

Fig. 1

SEM imagery for (a) cement and (b)UOPA

INTERLOCKING BLOCK PRODUCTION
The foamed concrete interlocking block was
produced using 35% UOPA (by the weight ofbinder) to replace cement and the filler-to-binder
ratio of 1.5. The mixture design is shown in Table
2.
Table 2 Calculated mix constituents (kg/m3)
Constituent Material
Cement
UOPA
Sand
SP
Water

Fine sand from a local river bed was used as
filler. The foaming agent that was used to produce
the pre-formed foam is a locally made proteinbased foaming agent. The foaming agent was
diluted in water at a percentage of (1:30) enabling
it to produce table foam with a density of 65 kg/m3.
From the SEM image, UOPA particles tend to
be angular and irregular in shape (Fig. 1). Hence,these particles require more water to lubricate theirsurface for the purpose of maintaining the needed
consistency. Therefore, a naphthalene based superplasticiser with a pH number of 7.5 was used with
foamed concrete mixes containing UOPA toproduce a mixture with reduced water demand andhigher flowability.

315.06
169.65727.06
4.85
218.12The compressive strength of UOPA foamed
concrete was tested using cube specimen of 100 ×
100 × 100 mm. The given mixture achieved thecompressive strength of 7.28 MPa. This mixture
has a porosity reading of 55.23%.
Block design consideration and sizes
The design philosophy for the interlocking
block is that it should have an interlocking
mechanism that allows self-alignment and mortarless, has dimensions that agree with the modular
system and can be used to build none, semi and
666

SEE - Bangkok, Thailand, Nov.11-13, 2019loadbearing walls. The interlocking mechanism
depends on intrusion and protrusions on the upperand lower face of the block. The newly designed
system is called BTechLiTe Block (Fig. 2) withthe dimension is shown in the Table 3.

block, two linear variable differential transformers(LVDTs), one vertical and one horizontal wereplaced on top and perpendicular to the face of theblock. In addition to the two LVDTs, three strain
gauges were placed on the face and side of thestretcher block. The testing setup is illustrated inFig. 3.

(a) Stretcher Block(a) Stretcher block test set-up(b) Half Block(b) Prism test set-up(c) Base Block

Fig. 2

BTechLite Block(c) Wall panel test set-up
Fig. 3

Table 3 Physical characteristics of the individual
blocksBlock type
Dimension (mm)Length
Width
HeightAverage mass (kg)Volume (m3×10-3)
Bearing area (mm2)Stretcher

Half

Base

300
150
200
7.72
5.56
37500

150
150
200
4.22
3.0
20000

300
150
200
9.14
6.5
37500

Experimental setup for block, prism andpanel

The prisms have the dimensions of three blocks
high (600 mm) and a width of one block (150 mm)
giving them a slenderness ratio of 4. The standard
prisms usually can be built to various heights
ranging between 1.5 and 5 times the thicknesses ofthe block (ASTM C90-75). As in the case of theindividual block, the stability of the prisms wasinvestigated using two LVDTs. A vertical LVDT
to investigate the prism’s vertical displacement anda horizontal LVDT was located at the centre of the
middle course of the prism. The panel selected had
a dimension of 0.8 m in height and 0.9 m in length.
The panel consists of base blocks, stretcher andhalf blocks. The panels were tested using a loadingcell of a maximum load capacity of 1000 kN and a

Experimental program
The blocks were tested for their compressive
strength using a universal testing machine with amaximum capacity of 3000 kN and a loading cellof a 500 kN capacity. In the case of the stretcher
667

SEE - Bangkok, Thailand, Nov.11-13, 2019loading frame. The test was conducted byincreasing the load until total failure occurred.

RESULTS AND DISCUSSION
Strength and failure mechanism
The average maximum loads that the stretcher,base and half blocks reached are 82.07 kN, 84.5
kN and 37.5 kN respectively (Table 4). The
stretcher block have the same shape on the top andbottom; therefore, the area that resists the load is
22500 mm2, hence, the strength is 3.75 MPa. The
half block has a smaller area than the stretcher
block of 8750 mm2; hence, the stress is determined
as 4.29 MPa. Meanwhile, the base block has two
different top and bottom faces; therefore, top andbottom stress are determined and then the average
is taken [19]. The stress that the base withstands is
3.00 MPa.
Since the blocks are made out of foamed
concrete; therefore, they have to be compared toaerated concrete blocks. The most common
strength that the aerated concrete blocks possess is
2.8 MPa [20]. So, it is safe to say that the newly
designed block is higher in compressive strengththan aerated concrete blocks. In addition, theminimum requirement for a load bearing concrete
block is 2.9 MPa [21]; hence, the newly designed
block system can be used in constructing walls thatcan bear medium loads.

(a) Face(b) Back
Fig. 4

It is obvious that cracks occur at the area
where the compressive stresses transform totensile stresses. Therefore, a shear line is createdin the transformation area; hence, creating theexhibited crack lines shown in Fig. 5. The cracks
started at the small protrusions on top thenextended towards the lower parts of block. The
cracks moved in line with the end of a protrusion
to the beginning of the protrusion beneath it. At
the centre of the distance between the two
protrusions, a crack appeared which extended
towards the centre of the block’s face thendivided itself into two smaller cracks.
The prisms’ compressive strengths were
determined using a loading cell with a maximum
capacity of 500 kN. The average compressive
strength of the prism was 3.69 N/mm2 with the
maximum load of 110.66 kN. Once the load
compresses the first block, the load divides into
two because of the two half blocks that lie
underneath. The load coming down from the two
half blocks is transferred through the protrusions
and intrusions of the upper facial of the baseblock then goes across to the base of the baseblock. The staggered joints helped in enhancing
the load transfer from the top block through thehalves and then to the base block. After loading,prism showed the first cracks at a load of 60 kN(54% of the maximum load). The cracks
occurred in the centre of the half block which
extended upwards and at the base of the
protrusion of the base block which extended
downwards. A crack occurred at a load of 80 kN
which extended from the joint in the middle

Table 4 Compressive strength of the individual
blocksBlock shape
Maximum Load (kN)
Strength (N/mm2)

Stretcher
84.27
3.75

Half
37.5
4.29

Cracking of the stretcher block

Base
84.5
3.00

The vertical deformation detected at the
maximum load of 84.27 kN was 0.82 mm. Once
failure occurs, the load drops and the displacement
continues to occur. When the load is subjected
onto the upper protrusions, the compressive
stresses extend downwards. The load tends to push
the block downwards; hence, expanding the lower
part of the block. The expansion movementtranslates to tensile stresses near the connection
point of the lower protrusions and the body of theblock. Maximum tensile stresses occur at theconnection points at in-plane and out-of-planeconnection areas of between the lower protrusions
and the upper body of the block. These connection
points will be the areas where cracks will first
appear when loaded. Fig. 4 shows the cracks
exhibited by the stretcher block when loaded until
failure.
668

SEE - Bangkok, Thailand, Nov.11-13, 2019

course upwards towards the stretcher block on
top. At 109.5 kN the cracks which werepreviously observed on the single blockappeared but on the first stretcher block only.
The reduction in the compressive strength of theprism compared to the individual stretcher block
unit was due to the effect of the slenderness ofthe prism specimen. Fig. 5(a) shows the cracks
that occurred when testing prism.

lower strained areas. Figure 5(b) shows the failuremode exhibited by wall panel.

Strength correlations
From analysing the cracking patterns that
occurred in the individual, prisms and wall panels,
similar patterns of cracks occur in the three types.
When testing the blocks individually, the crack
extended from the end of a protrusion towards the
beginning of the protrusion beneath it. It seems
that the crack is following a path which separates
two areas. The first area, when loading the upward
protrusions, the area beneath the protrusion ispushed downwards. The second area is the
opposite case, when loading the downward
protrusion pushes the area above it upwards.
Hence, a shear failure occurs between the twoareas.
The strength correlations between block, prismand panel are investigated. The stretcher blockachieved a compressive strength (fcB) of 3.75MPa,and Prism achieved a compressive strength (fcP) of
3.69 and Panel achieved a compressive strength(fcW) of 1.16MPa. From the numbers mentioned, it
is obvious that fcB ˃ fcP ˃ fcW the same observations
were made by [19]. The following equations
describe the relationship between block, prism andwall.

(a) Cracks on prism

𝑓𝑐𝑃 = 0.98 𝑓𝑐𝐵𝑓𝑐𝑊 = 0.314 𝑓𝑐𝑃
𝑓𝑐𝑊 = 0.309 𝑓𝑐𝐵

(1)
(2)
(3)

CONCLUSIONS(b) Cracks on the panel
Fig. 5The BTechLiTe block has a number of good
properties such as its lightweight (average weightof stretcher block is about 7 kg), it has thedimensions that agree with the modular system andits interlocking mechanism insures that the blockinterlocks with other blocks in all directions. The
block has achieved an average strength of 3.75
MPa for the stretcher block, 4.29 MPa for the half
block and 3.00 MPa for the base block, a higher
strength than the specified minimum strength of
2.8 MPa stated by BS 5628. The newly designed
block showed that the stretcher block achieved acompressive strength of 3.75MPa, higher than theprism (3.69 MPa). Meanwhile the compressive
strength of prism was higher than the panel which
achieved 1.16 MPa.
The failure mode that was observed while
testing the newly designed block system is that it
cracking occurs due to shear. The cracks occurred

Cracks on the prism and panel

In the case of maximum load and strength
obtained, wall panels achieved an average load of
130 kN and a compressive strength of 1.16 MPa.
The higher slenderness ration and larger number ofinterlocking joints may have been responsible forthis further reduction in the compressive strength
capacity of the panel. The first cracking occurredin the area where lower strain readings weredetected. However, the cracks did not extend
upwards or downwards and they did not threaten
the integrity of the wall panel in whole. Reaching
failure, chips from the wall panel started to shave
off at the areas connecting the high strain with the669

SEE - Bangkok, Thailand, Nov.11-13, 2019in a region where areas on the block move in
opposite sides of each other due to the loading of
the protrusions.
Eventually, the fabrication of BTechLite blocks
with 35% UOPA as the cement replacement offersa lighter blocks with superior compressive strength
which resulting in further cost reductions andenvironmentally friendly.

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ACKNOWLEDGMENTS
The authors gratefully acknowledge thefinancial support of the Universiti Sains Malaysia
under the Research University Grant (RUI) (Ref.
No. 1001 / PPBGN / 8014015).
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670

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

FINANCIAL AND INSTITUTIONAL ASPECT FOR APPLICATION OFA CENTRALIZED DOMESTIC WASTEWATER MANAGEMENTSYSTEM IN SUKOLILO DISTRICT, SURABAYA, INDONESIA
Dwi Agustiang Ningsih1, Eddy Setiadi Soedjono 2 and Nurina Fitriani3
Environmental Engineering Department, Institut Teknologi Sepuluh Nopember (ITS), Surabaya,
Indonesia, 3Study Program of Environmental Engineering, Department of Biology, Universitas Airlangga,
Surabaya, Indonesia
1,2

ABSTRACT
Sukolilo district is one of the sub-districts in Surabaya City which still uses the on-site system for its wastewater
treatment. This sub-district is one of the areas that designate for the centralized domestic wastewater management
system (CDWMS) plan. The application of CDWMS itself based on the strategic plan of system and infrastructuredevelopment of Surabaya City 2015-2034, namely the provision of centralized Wastewater Treatment Plan.
Reflecting on these policies and strategies, in the future there will be efforts to shift the localized (on-site)wastewater treatment and management infrastructure into the centralized one. For this reason, it is necessary to
conduct a study of the application of CDWMS in terms of technical aspects and community involvement. The
community involvement aspect is examined with real demand survey method related to the participation,
willingness, and ability to use the CDWMS. The result of this study indicates that the community readiness in the
CDWMS implementation plan shows that the community still does not know the procedures as well as the benefitsof it. Hence, even though the community shows vast willingness to use this system, it is not backed with thecommunity’s ability to pay the pipeline connections and the charges of retribution. The community is only able topay pipeline connections at < IDR 500,000 and pay charge of retribution at IDR 6,000 - IDR 10,000.
Keywords: Domestic wastewater, community involvement, CDWMS, Sukolilo
obligation that must be borne by the community tomaintain a sustainable CDWMS service [4].
This community support is in the form ofawareness in using a centralized system, given thatmost people today have used the local system [5].
Community is assigned to collect retribution,
operation and maintenance of physical infrastructure[6].
Community preparation must be done correctly
and precisely because it refers to the Surabaya City
Regulation which mentioned the obligations of thecommunity [7]. The application of CDWMS requires
support from the community in order to realize thesustainability of the system. Based on the reason, in
this study will identify the level of community
readiness in the use of CDWMS both in terms ofwillingness and ability.

INTRODUCTION
Based on the Surabaya City Sanitation Strategy in2016, the city of Surabaya is currently planningcentralized domestic wastewater management system(CDWMS) with a long-term target of regional scaleuse of CDWMS reaching 21.52% and city-scale
reaching 67.20%. Sukolilo District is one of thelocations to execute this plan [1].
Sukolilo District consists of seven sub-districts.
The environmental conditions of the settlements inthis district can be categorized as dense residential
neighborhoods. The wastewater management in
Sukolilo District is currently using the on-site system.
One of the sub-district not declared yet as open
defecation free (ODF). The largest number of people
who still practice open defecation is in Keputih Subdistrict [2]. Most of the residents use shared toilets,
private toilets, and septic tanks. The blackwater istreated in the septic tanks while the greywater will bedischarged to the nearest drainage [1].
Looking at these policies and strategies, in the
future, there will be an effort to transform the on-sitewastewater infrastructure and management system
into a centralized system. To implement the CDWMS
in Sukolilo district in accordance to the Surabaya
Sanitation Strategy, build of community support isalso needed to maintain the sustainable
implementation of CDWMS [3]. This is related to the

METHOD
Community surveys were conducted at selected
locations for the application of CDWMS. Analysis of
the participation aspects of the communityemphasized the involvement of the community inrelation to their participation to CDWMS pipeline
connection, willingness, and the ability to use
CDWMS.
To find out the community participation in the
management of domestic wastewater, data collection
671

SEE - Bangkok, Thailand, Nov.11-13, 2019was carried out using questionnaires. The number ofsample questionnaires use the formula [3]:N. p (1-p)

n = (N-1) D + p (1-p)

(1)

B2

D = t2(2)

Where: n = number of samples, N = number of
population (house hold), p = element ratio in thesample that have desirable properties (0.5), B =allowable error rate for each sample 5%, and t = levelof confidence (1-B)
The selection of respondents in this study is basedon the distribution of samples by stratified random
sampling because the study area has a heterogeneous
population.

ON-SITE SYSTEMCENTRALIZED SYSTEM (AREA STUDY)

Fig. 1 Map of Area Study in Sukolilo District

Correlation between Education Levels, PublicCounseling and Knowledge About CDWMS
Apart from public counseling, knowledge ofBased on the calculation refer to Eq. (1) and Eq.
wastewater
management can be obtained through(2) the number of questionnaires was 80
formal education. The results of the analysis of thequestionnaires distributed in the study area. The study
relationship between education levels, publicarea is presented in the Fig. 1.
counseling and the level of public knowledge of the
CDWMS implementation plan can be seen in Table
1.
Table 1. Availability of Public Counseling * Knowledge of the Definition, Benefit, and Ways of Work of
CDWMS * Education Level of the Head of the Family Cross Tabulation

Education Level of the Head of the Family
Elementary
schoolAvailability of PublicCounselingNotavailable
Available

Total
Junior highschoolAvailability of PublicCounselingNotavailable
Available

Total
SeniorHighschoolAvailability of PublicCounselingNotavailable
Sometimes
available
Available

Total

Bachelor

Total

Availability of PublicCounseling
Total
Availability of PublicCounselingNotavailable
Sometimes
available
AvailableNotavailable

672

Knowledge of the definition, benefit,
and ways of work of CDWMS
Know theKnow theDobenefit andways ofnotthe ways of
work
know
work
0
2
12

Total

RESULTS AND DISCUSSION

14

0
0
0

0
2
0

2
14
4

2
16
4

1
1
1

1
1
3

0
4
25

2
6
29

0

1

0

1

0
1
0

1
5
1

2
27
18

3
33
19

2

1

0

3

2
4
1

0
2
6

1
19
59

3
25
66

SEE - Bangkok, Thailand, Nov.11-13, 2019

Sometimes
available
Available
Total

Based on the results of the analysis in Table 1, it
can be seen that all levels of education do not know
the definition, benefit, and ways of work of CDWMS.
The lack of community knowledge is due to theabsence of public counseling carried out by the
CDWMS implementation program. This can beproven in the number of criteria of not knowing thedefinition, benefit and how CDWMS works isrelatively large when there is no counseling. Thus the
public counseling program is very influential on
people's knowledge about the definition, benefit andhow CDWMS works.

2

2

0

4

3
6

2
10

5
64

10
80

Correlation
between
PublicCounseling,
Knowledge about CDWMS, and Community
Willingness to Use CDWMS
Although many people answered that they did notknow about CDWMS, after a brief explanation about
the benefits of CDWMS, the community wasinterested and willing to participate in using it. The
relationship between extension programs, the level ofcommunity knowledge, and community willingness
to use CDWMS can be seen in Table 2.

Avaibility of Public Counseling
Knowledge of thedefinition, benefit, andNotways of work ofavailable
CDWMS

Know the benefit and theways of work
Know the ways of work
Do not know

Sometimes
available

3
33

6
59

29

37

66

1

1

2

1

1

2

2

2

4

0

3

3

0
0

2
5

2
5

Total

0

10

10

Know the benefit and theways of work
Know the ways of work
Do not know
Total

1

5

6

4
26
31

6
38
49

10
64
80

Know the benefit and theways of work
Know the ways of work

Total
Available

Total

Knowledge of thedefinition, benefit, andways of work of
CDWMS
Knowledge of thedefinition, benefit, andways of work of
CDWMS

1

3
26

Total
Knowledge of thedefinition, benefit, andways of work of
CDWMS

Willingness to use
CDWMS
Unwilling
Willing toto use
use
0
1

Total

Table 2. Knowledge of The Definition, Benefit, and Ways of Work of CDWMS * Availability of PublicCounseling Cross Tabulation

Know the benefit and theways of work
Know the ways of work
Do not know

Based on the results of the analysis in Table 2, canbe seen that overall the community is more willing to
use CDWMS even though many do not receive
counseling. Through a brief explanation of what
CDWMS is and its benefits, many people are willingto use CDWMS, especially if a routine public
counseling program is held. In this condition, itmeans that counseling is needed to increase publicknowledge about the benefits and how CDWMS
works thus encourage the availability of people to useit.
One of the basic factors in the sustainability of thesanitation system is community preparation thatneeds to be done properly. This means that themeaning is not just public counseling, but thecommunity really has the need for sanitation facilities[8].
Correlation between Income Level, Willingness to
Tap to CDWMS Network, and Ability to Tap to
CDWMS
The sustainability of a program and the usefulness
of infrastructure will succeed if it is supported by
673

SEE - Bangkok, Thailand, Nov.11-13, 2019

community participation both in terms of willingness
to use and the ability to use it. The level of community
ability can be seen from the amount of income. The
relationship between the three criteria is presented inTable 3.
Based on the results of the analysis in Table 3, it
is known that the greater the level of income, the more
willing to pay the CDWMS connection fees.
However, in majority only willing to pay the network
tapping fee if the amount is less than IDR 500,000.00.

The willingness of the community to use
CDWMS is extensive, however, it is not supported by
the community's ability to pay. This is indicated by
the majority of people in the study who only willingto pay around IDR 500,000.00 even though theconnection costs itself range from IDR 1,500,000.00- IDR 4,000,000.00 [9]. The community obligations
are to contribute to the thinking, time, and finances
both for construction (minimum cost of homeconnections), and maintenance operations throughthe payment of regular monthly contributions [10].

Income level (IDR)
Ability to connect to
CDWMS sewerage<1 million
network<500,000
UnwillingTotal
1-2.5 million

Ability to connect to
CDWMS sewerage
network<500,000
600,000-1,000,000
UnwillingTotal
2.6-4.5
millionAbility to connect to
CDWMS sewerage
network

4.6-6.5
millionAbility to connect to
CDWMS sewerage
network<500,000
600,000-1,000,000
1,100,000-2,000,000
Unwilling

Total<500,000
600,000-1,000,000
UnwillingTotal
6.6-8.5
million<500,000
600,000-1,000,000
1,100,000-2,000,000
Unwilling

Ability to connect to
CDWMS sewerage
network

Total>8.5 million

Ability to connect to
CDWMS sewerage
network

600,000-1,000,000
Unwilling

Total
Total

<500,000
600,000-1,000,000
1,100,000-2,000,000
Unwilling

Ability to connect to
CDWMS sewerage
network
Total

Willing to pay the
CDWMS network tapping
cost
Unwilling
Willing toto pay
pay
0
1
2
0

Total

Table 3. Ability to Connect to CDWMS Sewerage Network * Willing to Pay the CDWMS Network Tapping
Cost * Income Level Cross Tabulation

1
2

2

1

3

0
0
15

12
3
0

12
3
15

15

15

30

0
0
0
12

6
4
3
2

6
4
3
14

12

15

27

0
0
4

4
4
0

4
4
4

4

8

12

0
0
0
1

1
1
1
0

1
1
1
1

1

3

4

0
1

3
0

3
1

1

3

4

0
0
0
35
35

24
15
4
2
45

24
15
4
37
80

measuring the ability of the community to pay
retribution for the sustainability of CDWMS mustalso be considered. The results of the analysis of therelationship between income levels, willingness topay for O & M, and the ability to pay retribution canbe seen in Table 4.

Correlation between Income Level, Willingness to
Pay Operation and Maintenance Cost, and Ability
to Pay CDWMS Retribution Fee
In addition to the importance of considering theability of the community to connect to CDWMS,
674

SEE - Bangkok, Thailand, Nov.11-13, 2019

Based on the results of the analysis in Table 4 itcan be seen that the higher the income, more are thepeople willing to pay. The majority of this group arethose who have the ability to pay fees less than orequal to IDR 6,000.00 - 10,000.00. The value of theability to pay levies is still in the range of the value of
CDWMS retribution, which ranges from IDR
5,000.00 - 20,000.00 [9].

Income Level (IDR)
Ability to pay CDWMS<1retribution
million
Total

1-2,5
millionAbility to pay CDWMS
retribution<5,000
Unwilling<5,0006,000-10,000
11,000-15,000
16,000-20,000
UnwillingTotal
2,6-4,5millionAbility to pay CDWMS
retribution<5,0006,000-10,000
11,000-15,000
UnwillingTotal

4,6-6,5millionAbility to pay CDWMS
retribution<5,0006,000-10,000
11,000-15,000
16,000-20,000
UnwillingTotal
6,6-8,5millionAbility to pay CDWMS
retribution<5.00011,000-15,000
Unwilling

Total
>8,5
millionAbility to pay CDWMS
retribution<5,0006,000-10,000
16,000-20,000
Unwilling

Total

Total

Ability to pay CDWMS
retribution<5,0006,000-10,000
11,000-15,000
16,000-20,000
Unwilling

Total

Willing to pay the O & M cost
Unwilling toWilling to
pay
pay
0
1
2
0
2
1
0
6
0
3
0
1
0
5
13
2
13
17
0
2
0
9
0
2
13
1
13
14
0
1
0
3
0
2
0
2
4
0
4
8
0
1
0
2
1
0
1
3
0
1
0
1
0
1
1
0
1
3
0
12
0
16
0
7
0
8
34
3
34
46

Total

Table 10. Ability To Pay CDWMS Retribution * Willingness To Pay The Operation And Maintenance Cost
* Income Level Cross tabulation

1
2
3
6
3
1
5
15
30
2
9
2
14
27
1
3
2
2
4
12
1
2
1
4
1
1
1
1
4
12
16
7
8
37
80

2) The community is only able to pay pipeline
connestions at < IDR 500,000 and pay charge of
retribution at IDR 6,000 - IDR 10,000.

CONCLUSIONS
Conclusions from this study are:1) The community readiness in the centralized
domestic wastewater treatment implementation
plan shows that the community still does not know
the procedures as well as the benefits of it. Hence,even though the community shows vast
willingness to use this system, it is not backed
with the community’s ability to pay the pipeline
connections and the charges.

REFERENCES[1] City of Surabaya Sanitation Working Group.
2016. Sanitation Strategy in Surabaya.
Surabaya: Health Agency of Surabaya City.
[2] Tucunan, K.P., Ridwan, Y.H., Putri, A.S.,
Soedjono, E.S.. 2018. Sustainable kampongmodel in Kelurahan Keputih, Kejawan Putih
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Tambak and Gebang Putih of Surabaya City.
IOP
Conference
Series:EarthandEnvironmental Science. Sci. 202 012075: 1-8.
[3] Directorate General of Human Settlements.
2016. Technical Guidance on Preparation of
Feasibility Study of Sewerage System.
[4] Soedjono, S.S., Fitriani, N., Setiawan, A. Mulia,
G. J. T., Ningsih, D.A. 2019. Study on
Communal Wastewater Treatment Plants(CWWTPs) in Gresik, Indonesia. International
Journal Of Integrated Engineering. 11 (2): 236 242[5] Mazaya, G.I., Noya, H., dan Soedjono, E.S.
2015. Study on Open Defecation Free in
Kelurahan Kelayan Tengah Banjarmasin City.
Prosiding of International Conference on
Science, Technology, and Humanity: Surakarta.
[6] The Center Regulation Policy and Governanceand Institute for Sustainable Future. (2015).
Review of Regulatory Framework for Local
Scale ―Air Limbah‖. (Sydney: Institute for

Sustainable Futures, University of Technology
Sydney).
[7] Surabaya City Regulation No. 12 of 2016 about
The Management Of Water Quality And
Control Of Wastewater[8] Iskandar, S., Fransisca, I, Arianto, E., dan
Ruslan, A.. 2016. Centralized Domestic
Wastewater Management System, Volume 3.
Minister For Public Works and Human
Settlements: Jakarta[9] Japan International Coorporate Agancy. 2012.
Project for Capacity Development of the
Wastewater Sector Through Review of the
Wastewater Management Master Plan in DKI
Jakarta, Indonesia.
[10] Sunarti. 2003. Community Participation inGroup Housing Development. Jurnal Tata Loka.
Semarang: Planologi UNDIP

676

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ANALYSIS OF CHANGES IN SHEAR STRENGHT AND STIFFNESS OF
HO CHI MINH CITY’ SOFT SOIL UNDER THE UNLOADING STRESSPATHS FOR DEEP EXCAVATIONS CALCULATION

1

Trung Ngo Duc1, Phan Vo2 and Thanh Tran Thi3
Civil Engineering Department, Van Hien University, Ho Chi Minh City, Vietnam,
2
Ho Chi Minh City University of Technology, Vietnam,
3
The Industrial University of Ho Chi Minh City, Vietnam

ABSTRACTIn urban areas, underground space are growing demand and deep excavations are often used to solve thisproblem. In Ho Chi Minh City, deep excavation is often constructed in areas close to existing buildings,
infrastructure or public services, so limiting the displacement of the retaining wall and surface subsidence is very
important to ensure that the surrounding works are not affected or affected by the level of permission. In order toanalyze the displacement and deformation of the excavation pit, it is necessary to determine the soil characteristicsof the excavation pit foundation for inclusion in the soil models. However, the construction design of the projectis mainly taken from normal geological experiments, yet it does not describe the behavior of the surrounding soil.
Therefore, the problem is to use an experimental model with a reasonable stress path to determine input parametersthat are appropriate to the behavior of the ground around the pit, expressed by the change the stiffness of the soil
during the excavation work, which the current experimental process is considered unchanged. This paper uses
triaxial tests to evaluate the shear strength behavior of soft soil in Ho Chi Minh City with stress paths for calculation
deep excavations. The experiments were carried out on a undraining fixture scheme of 50, 100, 200kPa pressure
ratings to determine the shear strength and deformation modulus parameters of the E50 during the unloading
process.
Keywords: strain, stress paths, nonlinearity, deep excavation, soil model, unloading

wall at the lowest level, so it is necessary to determine
the actual stress state of the soil around the deep
excavations.
Many studies [4][5] have divided the area affectedby the excavation process into four parts, as shown in
Figure 1.

INTRODUCTION
In recent years, the demand for underground space
has been increasing in urban areas. Deep excavations
are often used to solve this problem. In Ho Chi Minh
City, deep excavations has usually constructed inareas close to existing buildings, infrastructure or
public services, so it is important to limit thedisplacement of retaining walls and surface
settlement. to ensure the surrounding buildings are
not affected or affected by the permitted level.
Due to the lack of laboratory data in the room,
engineers often use conventional geological test dataor correlate design parameters from available
parameters and are often limited to simple model landin design of deep excavations. In fact, theconstruction of excavation can be considered aloading and unloading problem for the ground, thisunloading changes the deformation stress state in the
ground. If the correlation is irrelevant or determine
parameters from test with improper stress paths, theengineer often faces the problem of deformation theactual deep excavations will be different from thepredicted value.
Deep excavations is influenced by geotechnicalconditions, the most important calculation is thecontrol of horizontal displacement of the retaining

Fig. 1 Area of influence of deep excavationand stress paths
Zone I: when removing soil out of the excavation,
horizontal displacement of the retaining wall will
occur and horizontal stress decreases while verticalstress remains unchanged. Stress paths as the ACsegment in Figure 1.
Zone II: during excavation, vertical stressdecreases and lateral stress increases due to wall
displacement, reduced soil strength, and ductile
region may appear at the bottom of the pit. The stress
path for this region is represented by the AMF
segment in Figure 1.
677

SEE - Bangkok, Thailand, Nov.11-13, 2019

Zone III: During the excavation process, verticalstress decreases continuously; horizontal stresschanges a little; and stress path is shown in the AS
segment in Figure 1.
Region IV: Vertical stress is basically constant;
there is a slight change in horizontal stress; the main
shaft of the stress is deflected by shear; and the stress
path is still near the AC segment in Figure 1.
The most significant effect on the deformation of
the deep excavation is Zone I and Zone II, in which
Zone I is the main factor causing horizontal
displacement and Zone II causing bottom heave,
which has important effects on deformation of deep
excavation. Zone I and Zone II correspond to stresspaths AC and AMF. In the AMF, the AM part is theunloading part and the MF part is loaded, which canbe analyzed by a general geotechnical model. The ACline is the horizontal unloading stress line. Unlike AB
stress lines in conventional experiments, there aredifferent behaviors and stress paths.
In practice, the soil productivity change is very
complicated. It can be seen that in order to analyze
the behavior of Zone I (behind the retaining wall) andZone II (at the bottom of the excavation pit), theanalysis of soil strength and stiffness parameters ofthese two areas is a major issue focus on solving.
In order to have accurate data on the deformationof the excavation, it is necessary to have the soil
characteristics of the area around the excavation toprovide input data to be included in the calculation
models. However, the current design of construction
activities is mainly taken from normal geologicaltests, not describing the behavior of the land aroundthe excavation pit. Therefore, the question is to use an
experimental model with a reasonable stress path todetermine the input parameters in accordance with the
behavior of the ground around the excavation,
expressed through change soil stiffness during
excavation, which the current experimental procedure
is considered to be constant.
In this study, the author performed a series ofthree undrained triaxial tests (CU) on 27 soft soil
samples with a depth of 4 to 24m with load levels of
50, 100, 200 kPa, respectively, with the stress paths.
Different stresses for evaluating shear and stiffness
behavior of soft soil in Ho Chi Minh City.

Fig. 2 Humboldt tri-axial equipment system
Principles for design of the compression cell of
the experiment with loading models based on Bishop
and Wesleys's hydraulics (1975) [1][2][3] to control
the different stresses during the unloading
experiment.
Testing samples and testing parameters according
to different stress paths shows in Table 2. A total of
27 soft soil samples were tested, of which 18 samplesof very soft clays and 9 samples of soft clays,
experimented according to the stress paths. The stressprogram is as follows:- Conventional triaxial compression model (CTC increase 1 and fixed 3): Saturated soil samples are
isotropic consolidation and undrained samples
according to the usual compression schedule: 9
samples;- Triaxial drag model (RTE - reduced 1 and fixed3): Saturated soil samples are isotropic consolidationand non-draining samples according to vertical stress
reduction schedule: 9 samples;- Model of cell pressure reduction (RTC - reduction
3 and fixed 1): Saturated soil samples are isotropic
consolidation and non-draining samples according tohorizontal stress reduction schedule: 9 samples;
Table 2 Soil parameters for soft soil in Ho Chi Minh
City and the stress paths in the tri-axial test
Depth Stress
[m]
paths
Very soft clays
CTC
46

APPARATUS
The test was carried out with the load frame
system of Humboldt (USA) according to ASTM
D4767. This system includes pressure, deformation,pressure and volume sensors connected to ADAM
View 32-channel datalogger system. Advantech
Adam view software allows collecting data fromsensors over time. The system is connected to thecomputer via a network card to allow chamberpressure control and testing to be performed
automatically from the beginning to the end.

RTE

RTC

1214

678

CTC

n

c

Test
No.

Wn
[%]

[kN/m3] [kPa]

1
2
3
4
5
6
7
8
9
10
11
12

88.55
88.38
81.47
88.55
88.38
81.47
88.55
88.38
81.47
78.87
78.70
75.80

15.7
16.0
15.9
15.7
16.0
15.9
15.7
16.0
15.9
15.6
15.4
15.9

50
100
200
50
100
200
50
100
200
50
100
200

SEE - Bangkok, Thailand, Nov.11-13, 2019

RTE

RTC

Soft clays
1820 CTC
RTE

RTC

2426

CTC

RTE

RTC

13
14
15
16
17
18

78.87
78.70
75.80
78.87
78.70
75.80

15.6
15.4
15.9
15.6
15.4
15.9

50
100
200
50
100
200

19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36

71.83
62.86
65.89
71.83
62.86
65.89
68.45
65.76
65.76
50.14
66.27
54.21
50.14
66.27
54.21
50.14
66.27
54.21

15.6
15.7
15.6
15.6
15.7
15.6
15.8
15.7
15.9
16.4
16.6
16.7
16.4
16.6
16.7
16.4
16.6
16.7

50
100
200
50
100
200
50
100
200
50
100
200
50
100
200
50
100
200

Fig. 5 Relationship (q - ε) of stress paths at depths 18-20m

ANALYSIS AND EVALUATION OF TESTINGRESULTSStress and strain relationship (q-1)

Fig. 6 Relationship (q - ε) of stress paths at depths 24-26m

In the above section, the triaxial test according to
the three stresses CTC, RTE and RTC is performed
with the CU diagram. The relationship of stress deformation and change of pore water pressure with
deformation with the above 3 stress paths at the cellpressure levels (3) are respectively 50kPa, 100kPa
and 200kPa are shown from Figure 3 to Figure 6.
In conventional triaxial compression test with
CTC stress curve, stress relationship - deformation isprogressively nonlinear and deformed withincreasing deviation stress until the sample isdestroyed, value maximum deviation stress increases
with cell pressure level. The pore water pressure isalways positive and also increases immediately alongwith the deformation in the axial stress increase
process.
In contrast, for the RTE stress paths in a triaxial
tensile test, the pore water pressure decreases at low
stress levels and gradually increases at higher stresslevels. The initial pressure of the pore water isnegative and the positive sign is changed according to
the increase of the deviation stress due to the
reduction of 1. Therefore, the destructive stress andthe change of pore water pressure for triaxial tensile
tests also depend on the stress paths. Experimental
results with RTE stress paths show that axial strain
corresponding to maximum stress increases with cellFig. 3 Relationship (q - ε) of stress paths at depths 4-6m

Fig. 4 Relationship (q - ε) of stress paths at depths 12-14m

679

SEE - Bangkok, Thailand, Nov.11-13, 2019pressure and pore water pressure represents elasticity,which corresponds to the corresponding. The
expansion of volume of ground soil outside reality
when unloading during construction of excavation
pits. This expansion behavior may be partly explainedby the change in the pore water pressure of the soil
sample at the end of the saturation and consolidation
period during shear stress. In most cases, these soil
samples were damaged by declining deformation.
The destruction of the sample is seen in the middle ofthe sample like the bottleneck shape as shown in Fig.
7. It can be seen that, during the increase in stress, thepore water pressure also increases similarly
corresponding to each stress paths. The destructive
pattern when deforming is about 6 ÷ 8%.
Testing results show that in the axial stress strain
RTE paths, it increases more slowly than CTC stresspaths, especially shown at the maximum cell pressurelevel, which means that the intial tangent modulus ishigher in the RTE stress paths and has a lower value
for the CTC stress paths. From this, it can beconcluded that the elastic parameters depend on theinitial stress and strain modulus paths in the processof unloading.

characteristics of soil samples will change as cellpressure increases. The initial deformation module Ei
in experiments with unloading path is also of different
value than when determining from the usual tri-axial
compressive stress paths. Therefore, with the problem
of designing deep excavations, the determination of
input parameters with appropriate stress paths will
give economical and safety results.
Analysis of deformation modules of stress paths
The relation (q, 1) Figure 3 to Figure 6 calculate
the deformation module E50 of soft clays samples atdifferent depths and different cell pressures as
determined stiffness parameters of HS model. The
results are shown in Table 3.
The magnitude of the E50 strain module increases
gradually with depth. At the same depth, thedistortion module will also have a greater value if
tested with a larger cell pressure level.
Testing results show that the stiffness of soil
depends on the stress paths. With HDS, the selectionof stiffness parameters in the displacement
calculation should be taken from the test with theunloading stress paths.
Table 3 E50 deformation modules from CTC, RTE
and RTC stress paths
RTE

Fig. 7 Sample destruction by RTE(left picture) and RTC stress path (right picture)
With the triaxial compression stress paths
reducing horizontal stress RTC, when the horizontal
stress is reduced during the sample cutting process,the deformation also increases but is slower than the
deformation compared to CTC stress paths, so thestrain deformation modulus The intention to calculate
deep excavation by HS model has much greater
results than CTC stress paths due to the curvature ofstress strain relationship with greater slope. The porewater pressure in the RTC route is opposite to the
CTC stress path but has a significantly smaller
magnitude and has a different nonlinearity, thispressure gradually increases to the destructive
threshold of the sample and decreases when thesample starts destructive. Testing results indicate thatthe parameter values determined from the strain stressrelationship of the ground soil depend on the stress
path of the triaxial test. Different stress paths will givedifferent shear strength values and the deformation

RTC

CTC

Depth
E50
E50
E50 E50,RTE E50,RTC
c
[m]
[kPa]
[kPa]
[kPa] E50,CTC E50,CTC[kPa]
Very soft clays
4÷6 503611
3494
2085 1.73 1.68
100 8202
7495
4774 1.72 1.57
200 14528 13997 8553 1.70 1.64
12÷14 502750
2968
1853 1.48 1.60
100 11575 9427
5981 1.94 1.58
200 15194 17774 9389 1.62 1.89
Soft clays
18÷20 50
5811
5391
3673 1.58 1.47
100 8640
6442
4510 1.95 1.48
200 14652 14121 9273 1.58 1.52
24÷26 504579
4201
2861 1.60 1.47
100 7765
7026
4922 1.58 1.43
200 16688 15107 9161 1.82 1.65
The difference in the value of the elastic modulus
according to the stress paths can be explained by thedependence of the elastic modulus according to eachstress paths on the plastic strain level. The magnitudeof plastic deformation depends on the flexible
potential function and flexible flow function. Thus,
the elastic modulus of the ground at some point has
only one value in the state without deformation.
When the ground is deformed, the value of the elastic
modulus decreases with a degree of dependence on
the stress path. The value of the elastic modulus of theground soil is determined by the initial slope of the680

SEE - Bangkok, Thailand, Nov.11-13, 2019

strain-strain relationship curve in such a conventional
tri-axial compression test that results in a large error
in the calculation. Therefore, it is recommended touse the value of the elastic module from the unloading
tri-axial compression test.
With triaxial test according to RTE and RTC
stresses, the results of the deformation modulus aremuch larger than those calculated from the test results
according to the normal tri-axial compressive stresspath:
E50, RTE E50, RTC
 [1.48  1.57](1)E50,CTC E50,RTC
Strength resistance of soil with different stresspaths

Fig. 10 Mohr circle according to stress paths at
depth of 18-20m

From the above diagrams of stress-strain
relationship (Figure 3 to Figure 6), destructive
contour lines can be drawn to determine the effective
shear resistance parameters for soil layers as follows:

Fig. 11 Mohr circle according to stress paths at
depth of 24-26m
The slope of the Kf destructive lines according to
the stress paths is clearly different.
The effective friction angle of the RTE and RTC
unloading route is similar and smaller than the CTC
schedule. For each load level, the stress circle of RTE
and RTC routes is back to the origin of thecoordinates compared to the normal tri-axial
compression stress paths CTC.
From the diagrams of Figure 8 to Figure 11,
determine the effective shear strength parameters of
the soil as shown in Table 4.

Fig. 8 Mohr circle according to stress paths at depthof 4-6m

Table 4 Value of c' and ’ of soft soil in HCMC.
according to stressed paths
Depth Stress
[m]
paths
Very soft clays
4÷6
CTC
RTC
RTE
12÷14 CTC
RTC

Fig. 9 Mohr circle according to stress paths at depthof 12-14m

681

c’
[kPa]
13.58
11.21
11.17
13.87
11.12

c’
[%]

0.83
0.82
0.80

’

’

[0 ]

[%]

21.56
18.62
18.26
21.90
18.63

0.86
0.85
0.85

SEE - Bangkok, Thailand, Nov.11-13, 2019

RTE
Soft clays
18÷20 CTC
RTC
RTE
24÷26 CTC
RTC
RTE

11.39
15.32
12.45
12.17
14.94
11.72
11.64

0.82

0.81
0.79
0.78
0.78

18.35
22.00
18.87
18.08
22.70
18.51
18.01

0.84

- The effective friction angle of the ground (') in thetri-axial test calculated by RTE and RTC is similarand smaller, determined by the usual tri-axial
compression stress path (CTC), which is smaller
between 15% and 23%:

0.86
0.82

 'RTE  'RTC
 0.77  0.85
 'CTC  'CTC

0.82
0.79

- Deformation modulus of soil also depends on stresspaths. The linear sand deformation module of thetriaxial test reduces the stress greater than theconventional triaxial test. Triaxial test according to
RTE and RTC stresses results in equivalent modulus
of modulus but larger than conventional tri-axial CTC
stress path. With soft soil, scale ranges from [1.48 ÷
1.57] times:
E50, RTE E50, RTC
 1.48  1.57
E50,CTC E50,CTC

From the results of the analysis, it can be seen thatthe effective friction angle of the ground (') in thethree-axis test calculated by RTE and RTC is similarand smaller than that determined by the usual triaxial
compression stress paths (CTC), this value is about
15% to 23% smaller:

 'RTE  'RTC
 0.77  0.85
 'CTC  'CTC

(2)

Experimental results show that the effective shear
strength (’) of soft soil in HCMC declined from 15%
to 23% under the unloading stress schedule in case ofdeep excavations.

REFERENCES[1] Bishop, A. W. and Garga, V. K., Drained Tension
Tests on London Clay, Géotechnique Volume 19
issue 2, June 1969, pp. 309-313;[2] Bishop, A.W. and Henkel, D.J., The measurementof soil properties in the triaxial test, London : E.
Arnold, 1962, ©1957.
[3] Bishop, A.W. and Wesley, L.D. (1975), A
Hydraulic Triaxial Apparatus for Controlled
Stress Path Testing, Geotechnique, vol. 25(4), pp.
657–670;[4] Taha, M.R., Mofiz, S.A., Hossain, M.K. andAsmirza, M.S. (1999). Model simulation ofresidual soil in triaxial extension tests. Proc. of theFifth Geotechnical Eng. Conference, Geotropika99, pp. 105–114.
[5] Wong, K. S. (2009), A Short Course on Deep
excavations, New Zealand;

CONCLUTIONS- Behavior of soil depends greatly on stress paths.
Determining the shear strenght parameters as well as
the stiffness parameters for the deep excavation
problem should be determined from the tri-axial
experiment with the unloading stress paths because
these experiments describe the actual working state of
the ground during the construction process- In the experiment with the unloading schedule, theshear resistance of the soil is significantly reduced
compared to the conventional tri-axial compression
test, because the excavation process is the process of
unloading so the horizontal displacement of the soil
will cause the soil to deteriorate (soft soil when
digging).

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SELF -SUPPORT SHELTER AS AN ALTERNATIVE SOLUTION
IN THE TSUNAMI-PRONE AREA
Anas Febrin Ismail1 *, Taufika Ophiyandri1, Abdul Hakam1, Afdilla Yofianda1, Dicky Kurnia Adha1, Tria Yuli
Anggraini1
1
Civil Engineering of Andalas University, Padang, Indonesia

ABSTRACT
Padang City, as the capital of West Sumatra province, has the potential to be hit by tsunamis. It is located about 200
km from subduction zone near Mentawai island. History shows that the city has experienced to the tsunami in 1797 and
1833. This situation has been realized by all stakeholders in the area, including the Government, Private Sector, NGOs,
and Communities. Today, there are approximately 600,000 residents exposed to the tsunami. So far, tsunami mitigation
efforts have been carried out by many parties. The Government, with a limited budget, has built five shelters with a capacityof 2000-3000 people. This number is still far from enough. As a solution, the Government invites the owners of multistories buildings to function their building as shelters. However, this invitation is not responding well since a lot of costs
to strengthen the building to meet the shelter criteria. One promising alternative is Self-Support Shelters that are built by
the community. The Self-Support Shelters are utilizing the existing public facilities such as Mosques or Mushollas (small
mosque) where they are closed to community residence. The shelter may be built a base on the concept of upgrading thequality and capacity of the Mosque or Musholla. The construction costs are based on the infaq, that is, a kind of charity or
donation by the Moslem to build religious facilities that will be rewarded by God in the hereafter. With this concept, theconstruction of shelters that require high costs can be done hand in hand by the community. This paper discusses theprocedures for building Self-Support Shelter in terms of its capacity, accessibility, management, and construction methods.
The results may be adopted as the guidance in building the Self-Support Shelters in Indonesia.
Keywords: tsunami, public facilities, self-support shelter, procedures
INTRODUCTION
The series of big earthquakes in the last two decades
have stricken the western part of Sumatra Island. Those
earthquakes, so far, do not trigger a tsunami. However,experts still predict a big earthquake that can generate atsunami is very potential to happen in the near future [1,2, 3]. It is due to what so-called seismic gap that available
near the Mentawai Islands. Padang City as the capital ofWest Sumatra province, where is about 200 km from the
Mentawai Islands, has the potential to be destroyed by thistsunami. This information has been well understood bystakeholders in the area including Government, Private
Sector, NGOs and Communities. There are approximately
600,000 residents exposed to the tsunami, as shown in
Fig. 1.
Tsunami mitigation efforts have been carried out[4,5,6]. The Government with a limited budget has built
five shelters with a capacity of 2000-3000 people. This
number is still far from enough. As a solution, theGovernment invites the owners of multi stories buildings
to function their building as shelters. This effort requires
an assessment process to make sure the buildings arereliable [7, 8, 9, 10]. Unreliable buildings must be
retrofitted to meet the shelter requirements [4, 5]. The
expensive additional cost for retrofitting results rejection
the Government proposal.

Fig. 1. Tsunami exposed area of Padang City
Therefore, it is necessary to find an alternative shelter
that can be built in a massive and fast way without theGovernment budget. One alternative is what so-called the
Self-Support Shelter. The Self-Support Shelter is a shelter
that built and operated by the community. It is utilizing
the existing public facilities such as Mosques or
Mushollas (small mosque) where are close to houses. In
683

SEE - Bangkok, Thailand, Nov.11-13, 2019

Padang City, each RW (a community group of about 100200 households) at least has one Musholla located on anarea about 100 to 400 m2. So, the Mosque and Musholla
are easy to be found in the Muslim community like in
Padang City.
At least there are three advantages using Mosque or
Musholla as shelter. First, the land is already available, so
it does not need to buy new land that is quite expensive.
Second, Mosque or Musholla close to community so it canaccommodate the surrounding community as a tsunami
evacuation shelter, in time. Third, to build shelters require
substantial funds, therefore, if the concept of upgrading
the quality and capacity of the Mosque or Musholla,
people are interested in donating their money because
they will get a reward from God in the hereafter. Although
it requires a long time period in its construction, however,using step by step concept depending on the incoming
donation, the shelter finally will be completed. By using
proper construction method, the existing Mosque or
Musholla no need to be destroyed before the shelters
completed.
This paper discusses the procedures for building
Self-Support Shelter in terms of its capacity, accessibility,
management, and construction methods. The procedure
may be adopted as the guidance to build the Self-Support
Shelters in Indonesia.
METHODOLOGY
The study is conducted in the selected Kelurahan(Sub-Sub-District) which is the the lowest level unit ofGovernment authority. It is chosen because the Kelurahancoordinates the grass root of the community. Under Lurah(Head of Sub-Sub District), there is Ketua RW(Coordinator several blocks of residence). Under Ketua
RW, there is Ketua RT (Coordinator one block ofresidence). Both Ketua RW and Ketua RT, chosen by thecommunity. Meanwhile, Lurah, is chosen by theGovernment.
The procedure in building the Self Supported Shelterthen is applied as seen in the Flow Chart in Fig.2.
Kelurahan Pasie Nan Tigo is selected as the case study
for Self Supported Shelter. It is one out of 104 Kelurahan
in Padang City. Its location can bee seen Fig. 3.
Identification of Mosque or Musholla
Fig 2. Procedure in building Self Support Shelter

Each of Mosque or Musholla within Kelurahan Pasie
Nan Tigo was surveyed and identified. After identifying
all Mosques or Mushola, the next step is giving the scorebase on the defined criteria. The defined criteria are
including the population distribution, land area, distancefrom the beach, accessibility, and the availability of theadministrators.

Identify and give the score all theMosque or Musholla in Kelurahan(Sub-Sub-District) based on the defined
criteria

684

SEE - Bangkok, Thailand, Nov.11-13, 2019

NO

1

2

MOSQUE NAME

3

4

5

6

7

8

NOTES

Masjid Al
FurqanAddress : Muaro Pengaliran
Kelurahan Pasie Nan Tigo
Building Area : 322 m²
Land Area : 1345 m²
Distance from Shore Line : 980 m
Ownership Status : Community
At Evacuation Route : Yes
Administrator : Available
Located at Dense Residence : Yes

Masjid Nurul
Falah

Address : Kompleks Kuala Nyiur II
Kelurahan Pasie Nan Tigo
Building Area : 245 m²
Land Area : 666 m²
Distance from Shore Line : 647 m
Ownership Status : Government
At Evacuation Route : Yes
Administrator : Available
Located at Dense Residence : Yes

MasjidBaiturrahmah

Address :Kelurahan Pasie Nan Tigo
Building Area : 216 m²
Land Area : 390 m²
Distance from Shore Line : 480 m
Ownership Status : Government
At Evacuation Route : Yes
Administrator : Available
Located at Dense Residence : Yes

Masjid Darul
Islah

Address : Jalan Pasir Sebelah
Kelurahan Pasie Nan Tigo
Building Area : 318 m²
Land Area : 537 m²
Distance from Shore Line : 232 m
Ownership Status : Government
At Evacuation Route : Yes
Administrator : Available
Located at Dense Residence : Yes

MasjidUniversitas
Muhammadiah
Sumatera Barat

Address : Kelurahan Pasie Nan Tigo
Building Area : 710 m²
Land Area : 3465 m²
Distance from Shore Line : 367 m
Ownership Status : Government
At Evacuation Route : Yes
Administrator : Available
Located at Dense Residence : Yes

MasjidTabiYestul‘Ulum

Address : Kelurahan Pasie Nan Tigo
Building Area : 377 m²
Land Area : 671 m²
Distance from Shore Line : 212 m
Ownership Status : Government
At Evacuation Route : Yes
Administrator : Available
Located at Dense Residence : Yes

MusalaDarussalam

Address : Kelurahan Pasie Nan Tigo
Building Area : 250 m²
Land Area : 347 m²
Distance from Shore Line : 328 m
Ownership Status : Government
At Evacuation Route : Yes
Administrator : Available
Located at Dense Residence : Yes

Masjid Darul
Muttaqin

Address : Kelurahan Pasie Nan Tigo
Building Area : 184 m²
Land Area : 597 m²
Distance from Shore Line : 224 m
Ownership Status : Government
At Evacuation Route : Yes
Administrator : Available
Located at Dense Residence : Yes

Fig 4. Map of Kelurahan Pasie Nan Tigo
Each of the criterion then is scoring. Population
Distribution has score 4, 3, and 2 for Large, Medium, andSmall, respectedly. Land Area has score 3 and 0 for >600
m2 and < 600 m2, respectedly. Distance from the beachhas score 2 and 0 for > 200 m and < 200 m, respectedly.
Accessibilty has score 2 and 0 for high and low,respectedly. Administrator has score 2 and 0 for available
and unavailable, respectedly.
There are twenty one Mosque or Musholla spreding in
Kelurahan Pasie Nan Tigo have been identified. Eight ofthem including their attributes can be seen in Fig 5. The
scoring result for all the Mosque and Musholla aresummarized in Table 1.
It can be seen that there are 10 Mosque or Mushollathat has the highest score. The ten Mosques and Musholla
can be as seen in Table 2.
The next step is to ask the approval of each Mosque or
Musholla administrator. Out of the 10 Musholla or
Mosque, 4 of them are objection to be shelter due to somereasons. One reason is the birocracy process amomg theadministrators. Therefore, only six are nominated to be
Self Support Shelter as seen in Fig.2

PHOTO

Fig 5. Some of the Mosques or Mushollas in
Kelurahan Pasie Nan Tigo

685

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1. Recapitulation of Mosque or Musholla score
Mosque/Distance fromLand Area
AccessAdministrators
Musala Name of Musque/Musala Population Distribution
the beach >> 600 m2
Code
200 m
Large Medium Small Yes No Yes No High Lower Yes
No
4
3
2 3 0
2
0
2
0
2
0
1
Masjid Al Furqan
1
1
1
1
1
2
Masjid Nurul Falah
1
1
1
1
1
3
Masjid Baiturrahman
1
1
1
1
1
4
Masjid Darul Islah
1
1
1
1
1
Masjid Cahaya Rohani
5
1
1
1
1
1
UMSB
6
Masjid Tabiyatul 'Ulum
1
1
1
1
1
7
Musala Darussalam
1
1
1
1
1
8
Masjid Darul Muttaqin
1
1
1
1
1
9
Masjid Iqra'
1
1
1
1
1
10
Musala Al Muqqarabin
1
1
1
1
1
11
Musala Al Ikhlas
1
1
1
1
1
12
Masjid Asra
1 1
1
1
1
Musala Ihdinasshiratol
13
1
1
1
1
1
Mustaqim
14
Masjid Al Mannar
1
1
1
1
1
Musala Nurul Ikhlas Talao
15
1
1
1
1
1
Sapek
16
Musala Darul Iman
1
1
1
1
1
17
Musala Nurul Ikhlas
1
1
1
1
1
18
Musala Muslimin
1 1
1
1
1
19
Musala Al Falah
1
1
1
1
1
20
Masjid At Taubah
1 1
1
1
1
21
Musala As salam
1 1
1
1
0
1

Total
Score

12
13
10
9
13
12
9
9
9
6
12
11

Fig 3. The distance between the mosque

12

Furthermore, comparing the six Mosque or Musholla
based on its land capacity and its location to thecommunity will come up with the best Self Support
Shelter or the determined Self Support Shelter. They are

13
9
7
8
9
12
11
9

1.
2.
3.
4.

Masjid Al-Furqan (Land Area: 1345 m2)
Masjid UMSB (Land area: 3465 m2)
Musholla Al Ikhlas (Land area: 945 m2)
Masjid Asra (Area of land: 1355 m2)

Table 2. The highest score of Mosque or Musholla
Each Mosque or Musholla above has its own cluster.
Cluster 1, Cluster 2, Cluster 3, and Cluster 4 are belong to
Masjid Al-Furqan, Masjid UMSB, Musholla Al Ikhlas,
and Masjid Asra, respectedly. The next step is todetermine the RW included in each cluster. Table 3 shows
the distribution of the population represents by RW foreach cluster. The air view of cluster can be seen in Fig.4.

No. Name of Mosque/Musala No. Name of Mosque/Musala
Masjid Al Furqan
Masjid Asra
1
6
Masjid Nurul Falah
2
7 Musala Ihdinasshiratol Mustaqim
Masjid Al Mannar
3 Masjid Cahaya Rohani UMSB 8
Masjid Tarbiyatul ‘Ulum
Musala Al Falah
49Musala Al Ikhlas
Masjid At Taubah
5
10

Table 3. Cluster Distribution
Total
Name of
Total
population perRW
Population
Cluster
CLUSTER 1 RW 01
1141
3153
RW 02
865
RW 14
679
RW11
468
CLUSTER 2 RW 03
641
4904
RW04
1195
RW13
558
RW08
1613
RW12
457
RW05
440
CLUSTER 3 RW 05
441
2410
RW 09
910
RW 06
1059
CLUSTER 4 RW 07
743
1476
RW 10
733
Zone

Fig 2. Approval Mosque or Musholla
The name of the approval Mosque or Musholla are
1.
2.
3.
4.
5.
6.

Masjid Al Furqan
Masjid UMSB
Musholla Al Ikhlas
Masjid Asra
Mushala Ihdinasshiratol Mustaqim
Masjid Tarbiyatul Uloom

The location of the Mosque and Musholla can be seenin Fig.3.

686

SEE - Bangkok, Thailand, Nov.11-13, 2019especially earthquake and tsunami must be applied [15,16]. Space function analysis must be designed according
to the shelter need.
In building the shelter, the construction methods isimportant. Since the existing Mosque or Musholla is still
function during the construction process, therefore, theconstruction procedure must be convinced not to disturb
the daily services. To meet these criteria, then, theselected material, the step of construction, the supported
equipment, as well as safety criteria, must be considered.
Evacuation Accessibility Analysis
The analysis of evacuation accessibility is conducted
to find an effective and efficient evacuation route to theshelter. Some studies have been done [17]. All
infrastructure and facilities within the cluster must be
identified and analyzed. Fig.5 shows the infrastructure
within Cluster 1. The study of accessibility is still inprogress.

Fig 4. Cluster Division
Shelter Capacity Calculation
According to FEMA 2012 [7], the tsunami evacuation
space requirement is 3 ft2 per person or about 1 m2 perperson. Base on this data, then, the capacity of the shelter
floor can be calculated. The following is the procedure ofcalculation in Cluster 1.

Fig 4. Infrastructure in Cluster 1
Evacuation Systems
To evacuate the people within cluster need the systemand procedure base on local wisdom. Some model has
been developed in a certain area [9, 10]. However, it need
to be reviewed in order to be implemented in different
area. The agreement among all stakeholders to select theproper system is necessary. Coordination and discussion
among stakeholders are needed. The study of theevacuation system is still in progress.

Fig 5. Planning Shelter in Al Furqan
The total population of Cluster 1 is RW 01 + RW 02+ RW14+ RW11= 1141 + 865 + 679 + 468 = 3153
population. If 1 m² at the shelter can accommodate one
person, then the total area required is 3153 m². The
Mosque or Musholla located in this cluster is Masjid Al
Furqan with the availability of the land is 1345 m².
Shelter to be built is a rectangular shape with area 30 m x
28 m. It means that this mosque will be built 4 floors
which are 3 floors functioned as evacuation place witharea 840 m² per floor.

CONCLUSIONS
From the study has been conducted, it can beconcluded as follows:
1. The Self Support Shelter is the promising alternative
shelter to fulfill the limited Government capacity inproviding the shelters in a tsunami-prone area
2. Mosque or Musholla is the best public facilities to be
designed as a shelter since it has some advantages:
land free, donation scheme for construction,
availability of Administrator, and availability inalmost all Kelurahan (Sub-Sub District) in Moeslim
Community that means close to the residential area.
3. The selection of the Mosque or Musholla needs someprocedure in order to get the best designed shelter.

Detail Engineering Design and Construction Method
Detail Engineering Design (DED) must be carried out
according to the current Standard or Code [11, 12, 13].
Structural analysis must be conducted using proper modeland structural analysis software [14]. All the loads
687

SEE - Bangkok, Thailand, Nov.11-13, 2019[8] Fauzan, Febrin Anas Ismail, Nurpadila Siregar, and
Zev Al Jauhari, The Effect Of Tsunami Loads On
Pasar Raya Inpres Block III Building In Padang City
Based On FEMA P-646[9] E. Rita, R. Permata, H. Yonne, and N. Carlo, Tsunami
shelter in Padang city: Location suitability andmanagement issue, Proceedings of the 3rd
ICONBUILD (2017)[10] F. Ashar, D. Amaratunga, R. Haigh, The analysis of
tsunami vertical shelter in Padang city, 4thInternational Conference on Building Resilience,(Salford Quays, United Kingdom 2014)[11] National Standardization Agency of Indonesia,
Design Method of Earthquake Resistance for
Buildings and Other Structures SNI 1726-2012,
Jakarta, Indonesia (2012)[12] Federal Emergency Management Agency, FEMA P646 (April 2012): Guidelines for Design of Structure
for Vertical Evacuation from Tsunami 2ndedition,Washington D.C, USA (2012)[13] National Standardization Agency of Indonesia,
Minimum load for the design of buildings and otherstructures SNI 1727:2013, Jakarta, Indonesia (2013)14] Computers and Structures Inc., Manual ETABS(Integrated Building Design Software), California,
USA (2016)[15] Y. Nakano, Structural Design Requirements for
Tsunami Evacuation Buildings in Japan, Volume:313, Date: 3/1/2017, ACI (American Concrete
Institute) Journal. First ACI & JCI Joint Seminar.
[16] K. H. Pacheco, Evaluation of Tsunami Loads andTheir Effect on Reinforced Concrete Buildings, A
Thesis Master of Science in Civil Eng., Universityof Hawai’i Library (2005)[17] Yosritzal, BM Kemal, Purnawan, and H Putra, An
Observation of the Walking Speed Evacuation in a
Simulated Tsunami Evacuation in Padang
Indonesia: IOP Conference Series: Earth andEnvironmental Science, 2018.

4. The evacuation system must be established inoperating of Self Support Shelter base on local
wisdom.
REFERENCES[1] Natawidjaja, D.H., Sieh, K., Chlieh, M., Galetzka, J.,
Suwargadi, B.W., Cheng, H., Edwards, R.L.,
Avouac, J.-P., and S.N. Ward. Source parameters of
the great Sumatran megathrust earthquakes of 1797and 1833 inferred from coral microatolls, Journal ofGeophysical Research 111, B06403, , 2006.
[2] Sieh, K., D. H. Natawidjaja, A. J. Meltzner, C. Shen,
H. Cheng, K. Li, B. W. Suwargadi, J. Galetzka, B.
Philibosian, R. L. Edwards. Earthquake Supercycles
Inferred from Sea-Level Changes Recorded in the
Corals of West Sumatra, Science 322, 1674 – 1678,
2008.
[3] Omer AYDAN, Seismicand Tsunami Hazard
Potentials in Indonesiawith a special emphasis on
Sumatra Island, Journal of The School of Marine
Science and Technology, Tokai University,Vol.6,
No.3,pp.19-38,2008[4] V Cedillos, N Canney, G Deierlein, S Henderson, F
Ismail, A Syukri, J Toth, K Wood, An Evaluation of
Infrastructure For Tsunami Evacuation In Padang,West Sumatra, Indonesia, 2010.
[5] Febrin Anas Ismail, Jafril Tanjung, Syah Bintang
Aruan, On The Use Of A Simple Tuned Mass
Damper Model For Reducing The Excessive
Vibration Of Tsunami Evacuation Suspension
Footbridge, MATEC Web of Conferences 229,
01013 (2018)[6] Hannes Taubenböck1, Joachim Post, Ralph Kiefl,
Achim Roth, Febrin A. Ismail, Günter Strunz andStefan Dech, Risk and Vulnerability Assessment To
Tsunami Hazard Using Very High Resolution
Satellite Data: The Case Study Of Padang,Indonesia, EARSeL eProceedings 8, 1/2009[7] U.S. Guidelines for Design and Construction of
Cyclones / Shelter Tsunamis, 2006688

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

GREEN CONCRETE HOLLOW BLOCKS UTILIZINGBASIC OXYGEN FURNACE STEEL SLAG
1

Santiago, Karen Joyce B.1; and Juan, Jose Arnel P. 2
Faculty, Mariano Marcos State University, Philippines; 2Faculty, Mapua University, Philippines
ABSTRACTThis study presented the effects of replacement of fine aggregates with high percentages of steel slag (BOF)
on the properties of Concrete Hollow Blocks (CHB). The mix proportions of 1:3:4, 1:4:3, and 1:3.5:3.5 (cement: fineaggregates: coarse aggregates) incorporating various percentages of steel slag were designed. Fine aggregate was
replaced 25, 50, 75, and 100 percentages of BOF steel slag by volume of fine aggregate. Elemental and chemical tests
were conducted to determine the toxicity of BOF slag to the environment and its use as a partial replacement of fineaggregates thru optical microscopy and xrf spectrometer. Compressive test and statistical inference reveal that
inclusion of steel slag as partial replacement with fine aggregates in CHB has a greater compressive strength than theconventional CHB. Moreover, the results of the xrf indicates the presence of calcium and iron oxides. Iron oxides,
which are non-toxic, have inert, opaque, and water resistant properties. In raw cement manufacturing, calcium oxideand silica oxides are components and considered to be non-toxic.
Keywords: BOF Steel Slag, Compressive Strength, Green Concrete Hollow Blocks, Toxicity
natural resources especially on natural aggregates isunder question. This led to the conduct of studies using
alternatives and replacements of natural aggregatesusing solid waste.
A global sand importer, Omnico Natural
Resources (ONRI), has been exporting construction
sand from Ilocos Norte, Philippines to Japan andSingapore since 2009. It has also been importing
furnace slag aggregates from Taiwan since 2015 todevelop a 112 hectare seaport reclamation project inCurrimao, Ilocos Norte [6]. However, the use of thisslag for embankment and backfilling materials has
been stopped by the Ilocos Norte Provincial Quarry
Council due to the alleged toxic slag elements. The
council needed the slag to be re-examined in its
toxicity and threat to the marine ecosystem ofCurrimao [7]. Due to the discontinue of the use of the
BOF steel slag, which appears like mixed gravel andsand and furnace slag steel, wastes are stockpiled in thenorthern portion of ONRI seaport complex, measuring
as high as 20 meters [8].
Yildirim and Prezzi [9] stated that it is essential tohave knowledge of the chemical, mineralogical, andmorphological properties of steel slag to utilize BOF
steel slag as a replacement material in concrete
development to produce green concrete. The use of theCurrimao BOF steel slag will take care of theenvironmental issue as well as the scarcity of the useof natural aggregates for concrete. The use of the slag
as a partial replacement for fine aggregates will lessen
and eventually eliminate the stockpiled BOF steel slag
in Currimao. It will address the problem in industrial

INTRODUCTION
In the Philippines, Concrete Hollow Blocks(CHB) are commonly used for exterior and interior
walls of buildings especially residential projects [1]. It
is also used for perimeter fence, tank, septic vault,
drainage canal, and many more. Fajardo [2] adds that
CHBs are classified as bearing and non-bearing blocks.
Load bearing blocks are those which thickness ranges
from 15 cm to 20 cm and are used to carry load aside
from their own weight. Non-bearing blocks, on theother hand, have thickness ranging from 7.5 cm to10cm blocks and are intended for walls and partition
fences carrying their own weight.
Hua-dong and Liu’s [3] study as cited in Yi, Xu,
Cheng, Wang, Wan and Chen [4] stated that basic
oxygen furnace (BOF) steel slag is a solid waste fromsteel production. This slag is formed when scrap
metals, molten iron, and various fluxes like lime areoxidized by injecting large amounts of pure oxygen
into the molten mix to create molten steel and molten
slag [5].
In the construction industry, concrete is one of themost commonly used material in variety ofenvironment such as dry, water, underground and evenin hot or cold climate zones. One of the advantages ofconcrete is the material’s possibility to change its
properties depending on the requirements of theconstruction project and the price. Concrete consists ofthree components: binder, filler, and water. Natural
aggregates with different proportions are the mostcommon filler. However, the status of depleting
689

SEE - Bangkok, Thailand, Nov.11-13, 2019

waste and apply the recycle, reuse, and recover
implementing rules and regulation of the Philippine’s
Ecological Solid Waste Management Act of 2000 (RA9003)[10].
The study focused on the utilization of the BOF
steel slag as a partial replacement of fine aggregates to
produce green concrete hollow blocks. Establishmentof proportions for the BOF as a partial replacement offine aggregates was observed and its possibility as a
substitute for natural aggregates.

Slump Test
All procedures and test methods conducted werein accordance with ASTM C143, “Standard Test
Method for Slump of Hydraulic-Cement Concrete”
specification. Slump was maintained at 5 inches for all
mix designs.
Compressive Strength of Cylindrical Concrete
Specimens
One hundred fifty (150) 4 x 8 inches concrete
cylinders have been tested in the uni-axial compressive
test in order to obtain compressive strength. Every five(5) concrete cylinders was tested, respectively, on thesame age set to 14th and 28th day period. The
development of compressive strength of BOF steelslag aggregate at the age of 14 and 28 days wasinvestigated.

METHODOLOGY
Concrete Mix Design
Sample design mixes of proportions 1:3:4;
1:3.5:3.5; and 1:4:3 (cement: fine aggregates: coarse
aggregates) were used as presented in Table 1. The
fine aggregates were replaced by BOF steel slag withvarious percentage replacement of 25%, 50%, 75%,
and 100%, respectively.

Green Concrete Hollow Blocks Development
BOF steel slag was incorporated in the productionof CHB to produce green concrete hollow blocks.
Based on the results of the compressive test of thecylindrical samples, the mixture with the highest
compressive strength value served as the proportion to
be used in the fabrication of the green concrete hollow
blocks.

Elemental Test by Optical Microscopy
Natural aggregates and BOF slag were collected,
sorted, and dried before undergoing elemental analysis
using OEM optical microscope.
Table 1. Concrete Mix Design

RESULTS AND DISCUSSIONS
Mixture(Cement : Fine :Course)
1:3:4

1:3.5:3.5

1:4:3

Natural Fine
Aggregates
%
0
25
50
75
100
0
25
50
75
100
0
25
50
75
100

BOF SlagAggregate
%
100
75
50
25
0
100
75
50
25
0
100
75
50
25
0

Optical Microscopy
The results obtained from the optical
microscopy shows that the sample course aggregate
had a 12.21mm diameter. This value conforms to thestandard size used in concrete mix wherein the usual
range employed is between 9.5mm and 37.5mm indiameter. Likewise, the sample fine aggregate had
1.432mm and 1.064mm diameter, respectively. Lastly,
the result obtained for BOF steel slag aggregate had
1.218mm and 1.163mm diameter, as shown in Fig. 1.
These values of fine aggregates and BOF steel slag
conforms to the standard size of fine aggregate used inconcrete mix with a range less than 9.5mm.

Material Characterization
Natural aggregates and BOF steel slag werepulverized and characterized by the handheld X-Ray
Fluorescence Spectrometer.
690

Figure 1. BOF steel slag

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2. Traced Chemical Composition of BOF Steel
Slag
Element
Ca
Fe
LE
Si
Mg
Al
Mn
P
Ti
Cr
S
V
Sr
Zn
Cu
Nb
Zr
Ni
Pb
Mg
Se

PPM
37.61%
23.99%
16.32%
7.72%
7.10%
3.38%
1.90%
1.34%
3072
1010
936
509
259
178
142
93
82
69
25
21
9

Table 3. Oxides present in BOF Steel Slag
Range Percentage (%)+/0.3706%
0.2423%0.2215%0.1664%0.8808%0.1362%0.0305%0.0266%286.6881.84
61.47
123.64
6.57
14.08
17.84
5.11
4.54
21.12
7.30
3.64
2.89

Oxides

Low

High

CaO

33.12

72.13

Fe2O3

25.99

42.61

SiO2

13.77

19.26

MgO

1.40

22.15

Al2O3

5.52

7.26

MnO

2.38

2.53

P2O5

2.99

3.15

Compressive Strength Test
One hundred fifty cylindrical samples were
subjected to compressive test. On the 14th and 28th daysof curing, the cylindrical samples were tested at the
Universal Testing Machine (UTM) to determine theircompressive strength. The 150 samples comprised of 3
mixture proportions, namely 1:3:4, 1:4:3, and 1:3.5:3.5(cement: fine sand: coarse aggregate) with different
percentages of fine aggregates replaced by BOF steelslag of percentages 0%, 25%, 50%, 75%, and 100%,
respectively.
Five samples on different percentages of slag
(0%,25%,50%,75% and 100%) on the different
proportions of cement, fine sand, and coarse aggregate(1:3:4, 1:4:3, and 1:3.5:3.5) were subjected tocompressive test as presented in Table 4. From Fig. 2,
it was presented that the proportion 1:3:4 (cement: finesand: coarse aggregate) with 25% partial replacementof BOF slag had the highest compressive strength of
4.34 MPa. Furthermore, five samples on different
percentages of slag (0%, 25%, 50%, 75%, and 100%)on the different proportions of cement, fine sand, andcoarse aggregate (1:3:4,1:4:3, and 1:3.5:3.5) were
subjected to compressive test as presented in Table 4
for 28 days curing. It presented that the proportion
1:3:4 (cement: fine sand: coarse aggregate) with 75%
partial replacement of BOF slag had the highest
compressive strength of 5.38 MPa.
The proportion of 1:3:4 (cement: fine sand:coarse aggregate) significantly presents a higher
compressive strength compared to the conventional
mix. In the mixture, the 25% BOF steel slag
replacement attained the highest value of compressive
strength for a 14-day-old concrete while a 75% BOF
steel slag replacement attained the highest compressive
strength for a 28-day-old concrete. Results indicatethat the use of BOF steel slag in the 1:3.5:3.5
proportion yields a lower compressive strength thanMaterial Characterization
Table 2 shows the weight percentage of theelement present on BOF steel slag. Its main chemical
constituents are CaO, FeO/ Fe2O3, and SiO2. The ironoxide (FeO/ Fe2O3) content of BOF slag was 23.99%
which could be as high as 31%. This is the amount ofoxidized iron that cannot be recovered during theconversion of molten iron into steel. The silica (SiO2)
content of BOF slag was 7.72% ranging from 6.9449%
to 8.4951%. The Al2O3 and MgO contents were 3.38%
and 7.10% ranging from 2.92-3.84% and 0.84-13.35%,
respectively. Large quantities of lime were used during
the process of conversion from iron to steel; hence, theCaO content of BOF steel slag was 37.61%, which was
typically very high (CaO>35%).
In Table 3, Calcium oxides (ranges from 52.25 %to 72.15% parts per million) and iron oxide (ranges
from 25.99 % to 42.61% parts per million) are the two
major chemical constituent of BOF steel slag.
According to Egirani, Latif, Poyi, Wessey and
Acharjee [11] as discussed by Ohimain [12], oxides ofiron ore are highly values and possess non-toxic, inert,
opaque and water resistant properties. Calcium oxideand silica oxides are likewise non- toxic substances
since these oxides are raw materials in producing raw
cement [13].

691SEE - Bangkok, Thailand, Nov.11-13, 2019

those of the conventional mix made from the similar
mix proportions.
In addition, there was a difference among thecompressive strength of concrete which depended
upon the percentage of BOF steel slag it contained.
There was also a significant increase of the mean
compressive strength between the 14 day age and 28
day age. The highest compressive strength of concrete
was considered for the 28 day age since their meanvalues were significantly higher than the mean
compressive strength of the 14 day age. For the
mixture 1:3:4, 75% replacement of BOF steel slag
showed the highest compressive among the different
replacement with the value 5.38 MPa. In the mixture
1:4:3, 50% replacement of BOF steel slag presented
the highest compressive strength of 4.39 MPa. Whilein the 1:3.5:3.5 mixture, 100% replacement of BOF
steel slag had the highest mean compressive strengthof 5.33MPa. Although the value of the mean
compressive strength of the 100% BOF steel slag
replacement was high, the values presented in the
1:3.5:3.5 proportions were not recommended since thevalues were all lower than the compressive strength ofthe control sample (0% BOF steel slag replacement)
which was 5.53MPa.

Compressive Strength, MPa

6

Mixture

1:3:4

1:4:3

1:3.5:3.5

Compressive
Strength, MPa
14 day28 dayAge
Age

0% BOF

2.76

4.84

25% BOF

4.34

5.28

50% BOF

3.06

5.31

75% BOF

2.86

5.38

100%BOF

2.84

4.44

0% BOF

3.11

3.65

25% BOF

2.47

4.25

50% BOF

3.01

4.39

75% BOF

2.71

4.34

100%BOF

2.47

4.29

0% BOF

3.21

5.53

25% BOF

2.32

3.31

50% BOF

2.42

3.85

75% BOF

2.57

4.74

100%BOF

3.31

5.33

4
3
2
1

0% BOF
25% BOF
50% BOF
75% BOF
100%BOF
0% BOF
25% BOF
50% BOF
75% BOF
100%BOF
0% BOF
25% BOF
50% BOF
75% BOF
100%BOF

0

1:3:4

1:4:3

1:3.5:3.5

Various BOF % Replacement
14 day age

28 day Age

Figure 2. Comparison of compressive strength ofvarious BOF percentages

Table 4. Comparison of Compressive Strength

Percentage
Replaced by
BOF (%)

5

Statistical Analysis T Test
The t-test analysis with 95% confidence ispresented in Table 5. In the design mix 1:3:4, the tcritical 2.54 was higher than the t actual 1.20 and the pvalue of 0.28 was higher than the level of significance.
There was no significance between the control mix andthe highest compressive strength generated of thedesign mix 1:3:4. However, this design mix actually
generated the highest compressive strength among themixes. Likewise, the two design mixes of 1:4:3 and1:3.5:3.5, showed that most of the t actual was greaterthan the t critical (t> tcritical). Moreover, the p values
Figure 6. Comparisonactualof compressive
strength of variousof these two design mixes were less than 0.05, the level
BOF percentagesof significance. Hence, the results show that there is asignificance difference between the control mix andthe fine aggregates replaced by BOF steel slag in thedesign mix 1:4:3 and 1:3.5:3.5. Likewise, the presenceof BOF slag in the mixture of concrete increases thecompressive strength of the concrete.

692

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 5 Statistical Analysis T test for the compressive
strength of concrete of all design mixes
Parameters
1:3:4
Compressive
Strength,
Control Design Mix,
MPa
HighestCompressive
Strength, MPa
Fine aggregates
replaced by BOF
steel slag, %T actual
T critical
P value

CONCLUSION
Green concrete, also known as a sustainable or‘high performance’ concrete, uses sustainable
materials which are made from recyclable materials
or green materials. They are more efficient than the
traditional products because they require fewer
resources to produce. Green concrete is a material thatexhibits better functional performance and capabilities
than ordinary concrete. It is considered a maintainable
construction material as it consumes less natural
resources and less energy and emits a smaller amountof carbon dioxide. The concrete wastes are slag, power
plant wastes, recycled concrete, mining and quarrying
wastes, waste glass, incinerator residue, red mud, burnt
clay, sawdust, combustor ash and foundry sand.
The results obtained from the optical microscopyshows that the BOF steel slag conforms to the standard
size of fine aggregate used in concrete mix with a range
less than 9.5mm. In determining the elements andoxides present in pure BOF steel slag specimen, it was
found out that it contained oxides that had similarelements to the results of the previous studies. Calciumoxides (ranges from 52.25 % to 72.15% parts per
million) and iron oxide (ranges from 25.99 % to42.61% parts per million) are the two major chemical
constituent of BOF steel slag. Iron oxides, which are
non-toxic, have inert, opaque, and water resistantproperties. In raw cement manufacturing, calciumoxide and silica oxides are components and considered
non-toxic. Thus it can be concluded that the BOF steelslag treated specimen does not contain any toxic andharmful elements that can harm the environment. The
slag can then be used as a suitable material for
replacement of natural aggregates and can be
categorized as a sustainable material to produce green
concrete products.
This study attempts to optimize and develop
proportions that can include steel slags as an ingredientfor concrete hollow block. BOF slag replaced a certain
percentage of fine natural aggregates and thespecimens were tested according on the specimens
curing days. Concrete hollow block proportion 1:4:3
has the highest value for compressive strength of afourteen-day old CHB having a value of 4.34 MPa with
50% fine aggregate replacement by BOF steel slag.
Likewise, concrete hollow block proportion of 75%
replacement from the 1:3:4 proportion governed thevalue for compressive strength of a twenty-eight-day
old concrete hollow block with a compressive strengthof 5.38 MPa.
Based on statistical analysis, there was a greatsignificance of the replacement of BOF steel slag in theconcrete mixture. There was a significant increase of
the compressive strength of concrete as the percentage

Mix Design
1:4:3 1:3.5:3.5

4.84

3.65

5.53

5.38

4.39

5.33

75

50

100

1.20
2.45
0.28

20.91
2.45
0

2.71
2.45
0.04

Figure 3. Green CHB

Development of Green Concrete Hollow Blocks
The proportion 1:3:4 served as the basis for the
fabrication of the green concrete hollow blocks since it
generated the highest compressive strength of 5.38
MPa. Conventional procedure in the fabrication ofhollow blocks was implemented. Fine aggregates were
replaced by 75% BOF steel slag. After the molding ofgreen CHB, a maximum of 10 days curing wasobserved to attain its maximum strength.
693

SEE - Bangkok, Thailand, Nov.11-13, 2019of BOF replacement also increases until it reaches its
maximum strength. Also, the three mixture proportions
were treated independently and presented increase ofcompressive strength as its age from 14 to 28 days, aswell as the addition of BOF steel slag as a replacementof fine sand. As the percentage of fine aggregates
replaced by steel slag increased, compressive strengthof concrete samples slowly increased.
It can be concluded that BOF steel slag can beused as an aggregate in the manufacture of concrete
hollow blocks. It can reduce the solid wastes present inCurrimao, Ilocos Norte as well as environmental
impacts. Moreover, the use of BOF steel slag makes it
possible to reduce the consumption of natural sandwhich causes potential environmental damage inriverbeds.

[6]

[7]

[8]

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[5]

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Oyster Shell as Component of theAggregates. UNP Research Journal, 19(1).
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Fajardo, M. B. (1980). Simplified
Construction Estimate. National Bookstore.
Hua-dong, M. E. N. G., & Liu, L. I. U. (2009).
Stability processing
technology andapplication prospect of steel slag [J].
Steelmaking, 25(6), 74.
Yi, H., Xu, G., Cheng, H., Wang, J., Wan, Y.,& Chen, H. (2012). An overview ofutilization of steel slag. Procedia Environ Sci
16: 791–801.
Shi, C. (2004). Steel slag—its production,
processing, characteristics, and cementitious
properties. Journal of Materials in Civil
Engineering, 16(3), 230-236.

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Ilocos Norte’s Global Sand Exporter Pushes
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Ilocos Norte Gov’t Halts Importation ofAlleged Toxic Materials for Port Expansion
Project. (2015). Balita. Retrieved fromhttp://balita.ph/2015/04/17/ilocos-nortegovt-halts-importation-of-alleged-toxicmaterials-for-port-expansion-project/
Adriano, Leilanie. (2015, April 17). Entry of‘toxic’ materials for port project stopped.
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Yildirim, I., & Prezzi,M. (2011). Chemical,
Mineralogical, and Morphological Propertiesof Steel Slag. Advances in Civil Engineering,
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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

RESPONSE OF A SINGLE PILE LOCATED ON SLOPING GROUNDUNDER DYNAMIC LOADING
1

Deendayal Rathod 1, D. Nigitha2 and Krishnanunni K T 3
Asst.Professor, National Institute of Technology (NIT), Tiruchirappalli (Trichy),
India; 2,3 Research Scholars, National Institute of Technology (NIT), India

ABSTRACT
Pile foundations are extensively used to support the laterally loaded structure. The structures like high-risebuilding, transmission tower, power station and offshore structures are subjected to lateral load in addition to thevertical load. The behavior of the piles on sloping ground under earthquake loading is different from the behaviorof the pile located on the horizontal ground surface because of the large permanent displacement. In the present
study, the numerical analysis has been carried out by using PLAXIS 2D. The analyses are carried out on single
model pile under dynamic loading to determine the behavior of the soil-pile system. A single pile of embedment
length to diameter ratio (L/D) of 16, 25 and 33 were located on the horizontal ground surface and slope angle of
1V:1.5H, 1V:2H and 1V:3H. The pile was subjected to dynamic loading (Bhuj earthquake, Gujarat) at its base.
From the analysis, the acceleration, displacement and bending moment of the pile under each case was studied.
Based on the results, it is concluded that as L/D ratio increases, the acceleration and maximum displacement andbending moment of the pile decreases
Keywords: Dynamic loading; Numerical analysis; Sloping ground; Single pile, PLAXIS 2D.
INTRODUCTION

LITERATURE REVIEWA study of laterally loaded piles under dynamic
loading has received considerable attention from thedesigners and researchers for more than three
decades. The dynamic response of a pile subjected toexternal excitation is a complex phenomenon
resulting from the interactions between the pile andthe surrounding soil. The structures like high risebuildings, transmission towers and offshore
structures are subjected to large lateral loads due tostrong winds or earthquakes. The behavior of pilefoundations under earthquake loading is an important
issue that widely affects the performance of thestructure. And also, many big cities in the world arebuilt on sloped ground. Most of the structures which
are constructed on soft clay with sloped groundsurface are subjected to large displacements due tohigh lateral loads. Most of the coastline have surface
which are sloping towards the waterfront. The designof pile foundation in coastal region to resist lateralload is primarily based on the limiting deflection
criterion, considering the safe operation of thesuperstructure. Lateral loading on pile foundations
due to wave and earthquake loadings are cyclic innature, which bring additional complexity to the soilstructure interaction problem. In such cases, studying
the interaction between the soil and the pilefoundation due to lateral load is essential. In thispaper, the numerical analysis are carried out todetermine the effect of acceleration, displacement andbending moment for piles of different embedment
length to diameter ratio (L/D) installed on various
sloping ground conditions.

The dynamic response of pile subjected tohorizontal excitation is a complex matter involving
the non-linearity at large displacements, pileseparation and slippage. Gaul (1958) conducted staticand dynamic model tests on instrumented aluminium
pipes embedded in bentonite soil medium. The
dynamic load is applied by means of a mechanicaloscillator and highly amplified strain variations
during the vibrations are recorded. Their study showsthat at relatively low frequency, magnitude andlocation of maximum bending moment does not varysignificantly as compared with static case. Hayashi
and Miyajima (1962) performed tests on vertical steel
H-piles installed in sand of different relative density.
Forced vibration tests are conducted and bending
moment, lateral deflection of pile head andacceleration response is measured. Frequency
response curves of single piles are plotted and natural
frequency of single pile is obtained from these tests.
However, the results of such dynamic 1-g model tests
are affected by the ‘box effect’ and inappropriate
stress levels. Prakash and Aggarwal (1965) reported
that the zone of influence of a dynamically loaded pilecan extend to greater distances such as 30 times thewidth of pile in the direction of loading and 15 times
the pile width in the orthogonal direction. Tajimi(1969) proposed an analytical model considering thepile to support a concentrated mass and theunderlying soil is assumed as viscoelastic (linearly
elastic material with frequency dependent viscousdamping). Nogami and Novak (1977) obtained closed
form solutions for the same problem neglecting the695

SEE - Bangkok, Thailand, Nov.11-13, 2019

effect of superstructure on the pile head response but
considering hysteretic type material damping of thesoil layer. Nogami and Konagai (1988) worked on theanalytical expression in frequency-domain for the
dynamic response of a single pile assumed as amassless cylinder embedded in an elastic infinite
medium. El Naggar and Novak (1996) developed acomputationally efficient model that accounts for
non-linear behavior of soil, discontinuity conditions
like slippage and gapping at soil-pile interface andenergy dissipation through different types of damping.
Dou and Byrne (1996) applied dynamic loading
through shake table test and preserved the stresslevels of the prototype for the model throughhydraulic gradient similitude technique. It is observedthat the bending moment in model pile reached its
peak value when the frequency applied is close to theresonant frequency. It is also found that the locationof maximum bending moment shifted downwards as
the pile head load is increased. In addition to this,dynamic p-y curves in dense sand are also presented
which exhibited highly non-linear characteristics up
to a depth of four times the pile diameter for a stronglevel shaking. Dou and Byrne (1997) demonstrated
that wave reflections at the boundary walls are
negligible when the loading frequencies are far below
the fundamental frequency of the soil layer. Bentley
and El Naggar (2000) used 3D FE program ANSYS
to develop a model that can account for kinematicsoil-structure interaction of piles and used it toevaluate the dynamic pile response with respect to
input ground motion. It is shown that for anelastoplastic soil with separation allowed, the lateral
response of pile head is very close to the free field
response at very low frequency of seismic excitation.
Abdoun and Dobry (2002) discuss the criticallocations in shear and bending response of deep
foundations in liquefied soil based on the reported
case history. Maheshwari et al. (2003) studied theeffects of plasticity and work hardening of soil on thefree field response and also the kinematic response of
single piles using the advanced plasticity-basedmodel in a finite element formulation. Maheshwari etal. (2004) confirmed that the material non-linearity
significantly affects seismic response of pilefoundation which in turn is dependent on thefrequency of excitation. Boominathan andAyothiraman (2007) carried out a comprehensive
investigation on single piles installed in soft clay
under static and dynamic lateral loads. It is noted thatthe dynamic magnification factor reduces with anincrease in magnitude of load due to large hysteretic
damping originating from the extreme non-linear
behaviour of soft clay. The active length underdynamic lateral load is increased by about 1.5 times
compared to that under static lateral load. Maiorano
et al. (2009) performed 3D finite element analysis ona pile subjected to dynamic lateral load to examine
the kinematic bending moments in different subsoil

conditions. The piles are represented as elastic beams
while the soil is modelled using linear elastic
constitutive model. The results are used to predict thetransient peak bending moments at the soil layerinterface. Yang et al. (2011) through his shaking table
test demonstrates that the dynamic p-y curves arehighly affected by the input acceleration amplitude.
Di Laora and Rovithis (2015) carried out a numericaltreatment using the rigorous finite element techniqueto evaluate the kinematic bending moment of long
piles embedded in a continuously non-homogenous
soil resting over a rigid base. During the analysis, soil
stiffness is allowed to vary with depth in a parabolic
fashion with its initial value at the ground surface tobe zero or a finite quantity. The active length of pilein non-homogenous soil layer is finally proposedconsidering the effect of kinematic interaction.
Deendayal et al. (2016) investigated the effect of theearthquake on a single pile located on the sloping
ground. A single pile was located on varying slopewith different length to diameter (L/D) ratios. It isobserved that the acceleration, displacement andbending moment decreases with the increase in L/Dratio. And also, the displacement and bending
moment increases significantly as slope increases
from horizontal ground surface to the slope underconsideration.
NUMERICAL MODELING
Governing Factor
Finite element method requires several
approximations to obtain the solution during
numerical modeling. The suitability of theapproximation used in the modeling approach isbased on the conditions in the field. Plane strain
conditions are assumed to hold in the plastic
deformation regime developed during the dynamic
loading. The problem being modeled is complex andhas to be simplified to obtain a solution. Two major
factors affecting the lateral response of piles are: (1)the properties of the soil (2) soil-pile interaction at theinterface.
Constitutive Model
A constitutive model to be satisfactory it must beable to define the material behavior for the concerned
range of stress and strain, identify the model
parameter by standard material test and physically
represent the material response to change in appliedstress and strain. In the present study, a twodimensional finite element program PLAXIS 2D isused for the analysis. PLAXIS automatically imposesa set of general boundary conditions (standard
fixities) to the actual geometry model. The MohrCoulomb model is used for depicting the soil
behavior.
The
Mohr-Coulomb
model
isstraightforward and quick and accounts for the696

SEE - Bangkok, Thailand, Nov.11-13, 2019elastoplastic behavior of the soil with utmost
simplicity.

Material Properties
The parameter values for soil and pile are adopted
from (Abdoun, T and Dobry R, 2002). A single
concrete pile of diameter 0.6 m is used for the FEM
analysis in the present study. An axial modulus (EA)
is taken as 3.56 x 105 (kN/m) and Rigidity modulus(EI) is taken as 8000 (kN/m2).An embedment pileconsists of a beam element and it provides theinterface between the beam and the soil enclosed by
the pile. The angle of internal friction (ϕ) anddilatancy angle (ψ) for sand-1 is 32 and 2, and forslightly cemented sand-2 is 35 and 5 respectively. The
detailed properties of soil and pile used for modelingare listed in Table 1 and 2.

Geometry Model
A geometry model is a composition of points,
lines and cluster. Points and lines are created in thedraw area by entering the coordinates in the commandline. Then the clusters are generated by program.
Each cluster gives the properties to simulate thebehavior of soil. The clusters are divided into soil
element during mesh generation. In addition to this,structural object such as the beam representing a pilecan be assigned to the geometry. Once the geometry
model has been created, the pile parameters are
assigned to the corresponding geometry component.
When the full geometry model is defined and all
geometry components have their initial properties,
then the finite element mesh is generated. Fig. 1
shows the typical models in case of L/D 33 forsloping ground.

Table 1 Values of soil and interface properties.
Description

Unit weight ()(kN/m3)
Material model
Young’smodulus(Es)(kN/m2)
Poisson’s ratio ()Angle of internal
friction (φ)
Dilation angle (ψ)
Interface strength
reduction factor(Rinter)Fig. 1 Geometric model for L/D = 33, 1V:3H.
Soil-Pile Interaction
The Mohr-coulomb model describes the behavior
of interfaces for the modeling of soil-pile interaction.
The pile consists of the beam element with special
interface elements providing the interaction between
the pile and the surrounding soil. The pile isconsidered as linear elastic and its behavior isrepresented by using stiffness properties. Theinterface strength reduction factor accounting for theeffect of soil-structure interaction at the interface ischosen on a conservative basis in the current study.

Sand - 1

25

Slightly
cementedsand -2
28

Mohrcoulomb
38000

Mohrcoulomb
49000

0.25
32°

0.3
35°

2°
0.67

5°
0.8

Table 2 Values of pile properties.
Description
Axial modulus (EA) (kN/m)
Rigidity modulus (EI) (kN-m2)
Equivalent thickness (t) (m)Diameter (D) (m)Pile
3.56 x105
8000
0.519
0.6

Finite Element Mesh Generation and Calculation

Boundary Condition

The geometry of the soil-pile model is divided
into finite elements forming the mesh. After
generating the finite element mesh, the actual finite
element calculations are executed. The calculation
involves two phases. First, the prescribed
displacement is activated while defining the
calculation phases. Second, the earthquakes havebeen simulated in the dynamic analysis. The
displacements are reset to zero in order to analyze theeffect of the earthquake in detail. Earthquake loads

An absorbent boundary is aimed to absorb theincreasing stress in the boundaries caused by the
dynamic loading; otherwise, it will be reflected inside
the soil body. In this model, the absorbent boundaries
are generated at the left, right and the bottom
boundary.

697

SEE - Bangkok, Thailand, Nov.11-13, 2019are usually applied by means of prescribed horizontal
displacements. The earthquake loading is applied at
the bottom of the pile. In the present study, aftershockof the Bhuj Earthquake (Gujarat) data presented inFig. 2 is used. The analysis has been carried out for
all cases and variation of bending moment andmaximum displacement is observed. Fig. 3 shows thedeformed mesh for L/D ratio 33 on 1V:3H slope.

pile (at pile head) with different L/D ratios (16, 25 and33) installed at the crest of 1V:1.5H slope. The
percentage decrease in maximum acceleration withchange in L/D ratio 16-25, 25-33 and 16-33 for thehorizontal ground and slope of 1V:3H and 1V:1.5H
are shown in Table 3, Table 4 and Table 5
respectively. From the results, it is observed that as
L/D ratio increases, the maximum acceleration
decreases irrespective of slopes. When L/D ratiochanges from 16-33, the maximum acceleration isobserved to decrease by 61.50% and 43.25% on
slopes of 1V:3H and 1V:1.5H respectively. The
magnitude of maximum acceleration recorded onrelatively steeper slope of 1V:1.5H is much higher for
L/D ratio of 33. This is because of the reduced passive
wedge of soil in front of the pile which may lead tolower inertial resistance from the soil present in theregion of active pile length. This can cause the net
earthquake force to predominate over the weaker
resistance forces resulting in higher acceleration at
the pile head.

Fig. 2 Acceleration-time data for the
Bhuj/Kachchh aftershock recorded at the Bhuj
station.

Fig 3. Deformed Mesh for L/D = 33, 1V:3H
RESULTS AND DISCUSSIONS

Fig 4. Acceleration-time response for different L/Dratio’s on horizontal ground

The lateral load behavior of a single pile due todynamic loading is studied by using lateral load –deflection curves. The variations of acceleration aredetermined for different L/D ratio in case ofhorizontal and sloping ground. The effect of slope andL/D ratio on maximum bending moment andmaximum displacement is also analyzed.
Effect of L/D Ratio on Acceleration Curves For
Horizontal And Sloping Ground.
The pile head/cap is more vulnerable to failure
due to reduction in soil resistance along its shaft andalso due to high slenderness of pile. In the present
study, maximum acceleration is measured at pile head.
Fig. 4 shows the variation of acceleration versus time
graphs of a pile (at pile head) for different L/D ratios(16, 25 and 33) for horizontal ground surface. From
the results, it is observed that as L/D ratio increases,
the maximum acceleration decreases. When L/D ratiochanges from 16-25, the maximum acceleration isobserved to decrease by 59.82%. This behavior isobserved due to increase in embedded length of pileor increase in the flexibility of soil-pile system. Fig. 5
shows the variation of acceleration with time for a

Fig 5. Acceleration-time response for different L/Dratio’s on 1V:1.5H slope
Table 3. Percentage decrease in maximum
acceleration due to change in L/D ratio for horizontal
ground.
Horizontal ground Surface
L/D ratios
16
25
33
Max. Acceleration 0.326 0.131
0.110(m/s2)
Change in L/D
16-25 25-33
16-33
ratios% Decrease
59.82% 16.03%
66.25%

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 4. Percentage decrease in maximum
acceleration due to change in L/D ratio for 1V:3H
slope
L/D RatioMax.
Acceleration(m/s2)
Changein
L/D ratio% Decrease

16
1.46

Slope 1V:3H
25
0.985

33
0.562

16-25

25-33

16-33

32.53%

42.94%

61.50%

Fig 6. Maximum Displacement vs Depth curve for
L/D = 16 with different slope.

Table 5. Percentage decrease in maximum
acceleration due to change in L/D ratio for 1V:1.5H
slope
L/D RatioMax.
Acceleration(m/s2)
Changein
L/D ratio% Decrease

Slope 1V:1.5H
16
25
2.00
1.459

33
1.135

16-25

25-33

16-33

27.05%

22.20%

43.25%

Effects of L/D Ratio and Slope on Bending
Moment
The effect of slope on the maximum bending
moment is shown in Fig.7 for different L/D ratio.
From the graph, it is observed that the increase inembedment length to diameter ratio, the maximum
bending moment of the pile decreases. This behavior
is due to the increased depth of fixity arising from thelarger relative stiffness of the soil-pile system. And
also, if the slope increases from ground surface (zeroslope) and becomes steeper (1V:1.5H), the bending
moment also increases. This is due to the reduction in
the passive resistance of the soil in front of the pile. It
can be noted that the bending moment increases by
50-80% as the slope approaches 1V:1.5H for therange of L/D ratio’s (16-33) considered in the study.

Effects of L/D Ratio and Slope on
Displacement
Table numbers and labels should be placed on topof the table, hanging by 12.5 mm, and left- and rightjustified. Number the tables consecutively and locate
them after and close to where they are first referenced.
Leave at least one line space between the table, label
and the text. Tables should be auto-fit to a single
column or the whole width over two columns and novertical lines or borders are needed. Fig. 6 shows thevariation of maximum displacement with slope fordifferent L/D ratios. From the graph, it is observedthat as L/D ratio increases, the maximum
displacement decreases. It is also noted that as slope
increases from horizontal ground surface to steeper
1V:3H, 1V:2H and 1V:1.5H slope, the maximum
displacement increases significantly. The maximum
displacement observed on a slope of 1V:1.5H for
L/D=16 increased considerably for the present
dynamic loading considered at the pile base. This ismainly due to the heavy reduction in inertial
resistance from the soil in the wedge. The present
result is found to be good agreement with theliterature results (Deendayal R and Sitharam T G,
2016).

Fig 7. Variation of maximum bending moment withslope for different L/D ratio.
CONCLUSIONS
A finite element analysis has been performed toevaluate the seismic response of a single pile installed
on slopes. The developed analysis has been validatedwith the similar study carried out by Deendayal et al.
(2016). The major conclusions from the study arepresented below.
1. As L/D ratio increases, the maximum
acceleration decreases irrespective of slopes. WhenL/D ratio increases from 16-25, 25-33 and 16-33 themaximum acceleration observed a percentage
reduction of 16.03-66.25%, 32.53-61.50% and 27.05699

SEE - Bangkok, Thailand, Nov.11-13, 2019[4] R. Di Laora and E. Rovithis, “Kinematic
BendingofFixed-Head
Piles
in
Nonhomogeneous
Soil,”J.
Geotech.
Geoenvironmental Eng., vol. 141, no. 4, p.
04014126, 2014.
[5] Huaren Dou and Peter M.Byrne, “Dynamic
response of single piles and soil-pile interaction,”
Can. Geotech. J., vol. 33:80-96, p. 43, 1996.
[6] H. Dou and P. M. Byrne, “Model studies ofboundary effect on dynamic soil response,” Can.
Geotech. J., vol. 34, no. 3, pp. 460–465, 2012.
[7] R. Deendayal, T. G. Sitharam, and K.
Muthukkumaran, “Effect of earthquake on asingle pile located in sloping ground,” Int. J.
Geotech. Earthq. Eng., vol. 7, no. 1, pp. 57–72,
2016.
[8] M. H. El Naggar and M. Novak, “Nonlinear
analysis for dynamic lateral pile response,” Soil
Dyn. Earthq. Eng., vol. 15, no. 4, pp. 233–244,
1996.
[9] B. K. Maheshwari, K. Z. Truman, P. L. Gould,
and M. H. El Naggar, “Three-Dimensional
Nonlinear Seismic Analysis of Single Piles
Using Finite Element Model: Effects of Plasticity
of Soil,” Int. J. Geomech., vol. 5, no. 1, pp. 35–
44, 2005.
[10] T. Nogami and M. Novak, Resistance of soil to ahorizontally vibrating pile, vol. 5. 1977.
[11] K. K. Toyoaki Nogami, “Time Domain Flexural
Response of Dynamically Loaded Single Piles,”Am. Soc. Civ. Eng., vol. 114, no. 9, pp. 1512–
1525, 1989.
[12] S. L. A. Shamsher Prakash, “Study of verticalpile under lateral load.pdf,” Proc. Third World
Conf. Earthq. Eng., vol. 1, pp. 215–229, 1965.
[13] H. Tajimi, “Dynamic analysis of a structure
Embedded in an Elastic Stratum,” Proc. 4th
World Conf. Earthq. Eng. Santiago, vol. 3, pp.
54–69, 1969.
[14] E. K. Yang, J. I. Choi, S. Y. Kwon, and M. M.
Kim, “Development of dynamic p-y backbone
curves for a single pile in dense sand by 1g
shaking table tests,” KSCE J. Civ. Eng., vol. 15,
no. 5, pp. 813–821, 2011.
[15] Gaul, R. D. “Model study of a dynamicallylaterally loaded pile,” Journal of the Soil
Mechanics and Foundations Division, 84(1), pp.
1–33, 1958.
[16] Hayashi, S and Miyajima, N. “Dynamic lateralload tests on steel H-piles,” Proceedings, Japan
National
Symposiumon
Earthquake
Engineering, Tokyo, Japan, 1962.

43.25% for horizontal ground surface, 1V:3H slopeand 1V:1.5H slope respectively. This behavior was
due to the increase in embedded length that enhanced
the flexibility of soil-pile system.
2. From the study, it is very clear that as L/D ratio
increases, the maximum displacement has been
reducing. This is due to the decrease in active pilelength that contributes to deflection as L/D ratio
increases. And also, when ground surface changes
from horizontal to steeper slopes, the maximum
displacement increases tremendously especially forthe case of L/D = 16.
3. It is noted that the bending moment decreases
significantly with increase in L/D ratios. It is also
observed that steeper slopes like 1V:1.5H has aconsiderable effect on increasing the bending
moment.
INFERENCE
A Kinematic soil-pile interaction study isconducted to evaluate the effect of slenderness ratio(L/D) of long piles installed on sloping ground. The
dynamic loading of pile affecting the free-fieldmotion of the soil and their combined response assoil-pile system is studied through a finite element
package Plaxis 2D. It may be inferred that as the pile
becomes more flexible as a result of enhancement oflength, it is able to deform and rather bend more
freely with the soil thus attracting less forces. The
consequences of this has been evidently shown
through a reduction in acceleration, displacement
amplitude and bending moment. However, the study
shows that the effect of steeper slopes like 1V:1.5H
on increasing the maximum displacement andbending moment of relatively lower flexible piles(L/D = 16) is still alarming and requires caution
through proper design considering the dynamic
parameters. It is also noted that increasing the L/Dratio has only a marginal effect on such steep slopes.
REFERENCES[1] T. Abdoun and R. Dobry, “Evaluation of pilefoundation response to lateral spreading,” Soil
Dyn. Earthq. Eng., vol. 22, pp. 1051–1058, 2002.
[2] R. M. S. Maiorano, L. de Sanctis, S. Aversa, and
A. Mandolini, “Kinematic response analysis of
piled foundations under seismic excitation,” Can.
Geotech. J., vol. 46, no. 5, pp. 571–584, 2009.
[3] A. Boominathan and R. Ayothiraman, “Anexperimental study on static and dynamic
bending behaviour of piles in soft clay,”
Geotech. Geol. Eng., vol. 25, no. 2, pp. 177–189,
2007.

700

5thInt. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

BIM-BASED SIMPLIFIED APPROACH TO AUTOMATICALLYESTIMATE BUILDING COSTS FOR PROJECTS IN THAILAND

1

Suon Tokla1, and Kumpon Subsomboon2
Faculty of Engineering, Naresuan University, Thailand

ABSTRACT
Cost estimating is a significant and critical phase of construction projects. Traditional cost estimating
methods count on 2D drawings and human interpretation result in time-consuming and prone to errors. Emerging
Building Information Modeling (BIM) is a process that can enhance the quantity takeoff and cost estimating witha higher level of accuracy. BIM-based cost estimating approaches can be done by integrating 3D BIM with BIMbased estimating software. These approaches are complicated, expensive, and required skilled-personnel to reap
the full benefits from every estimating tools integrating with the external database. This research presents adeveloped BIM algorithm that is capable of automatically estimating building costs. 3D BIM intelligent objects
were integrated with a custom built database with specialized templates, thereby providing ease of use whileeliminating the need to manually re-enter cost changes. This algorithm creates a list of the specialized work
breakdown structure (WBS) containing construction specifications, and unit costs, based on the Thai standard
system. A typical BOQ was generated from the 3D BIM case study, and linked to the specialized templates that
automatically estimate building cost. Estimating costs of the traditional and BIM-based approaches werecompared and showed approximately closed value. This research offers a simplified but essential BIM-based
cost estimating algorithm for Small and Medium Enterprises (SMEs) with a simple, fast and accurate process.
Keywords: Building information modeling, Bill of quantity, Quantity takeoff, Cost estimatesis able to offer an accurate QTO process as well as
facilitate to decrease the variation of the costestimations [4].
This research presents a BIM algorithm that
automatically estimates building costs based on BIM
3D models that integrate with custom built databaseand specialized templates. This approach will
facilitate ease of use without the needs of updating
unit costs in BIM applications; also it is capable ofenhancing
BIM-based
QTO
process
andautomatically estimating costs. This research offers a
BIM-based simplified approach with an essential
process based on the CGD format for AEC industry
and SMEs use to implement in their building
construction projects in order to increase accuracy,
minimize time and costs.
The following sections in this paper will present
the overview of related researches, custom built
database and specialized templates, develop objects
properties and model a 3D building in BIM
application, link typical BOQ with specialized
templates for automatically generating total costestimation.

INTRODUCTION
Construction cost estimating is a complicated,time-consuming and error-prone process. It is one ofa significant and critical phase of construction
projects. Traditionally applied cost estimating
methods are performed that the process reliedheavily on 2D drawings and human interpretations
for generating the quantity takeoff (QTO): every
single building element is measured and counted
then inputted onto excel platforms to keep aninventory of all items and produce a bill of quantity(BOQ) [1]. Eastman [2] mentioned that using
traditional
methods
areusually
missedinterpretations and incorrect inputs because of thehard process and complex relationships between
large amounts of building elements.
In Thailand, traditional cost estimating method isstill using manually quantity takeoff based on a
spreadsheet of BOQ according to Thailand’sComptroller General Department (CGD), Ministryof Commerce’s format. The BOQ based on the CGD
format is still required for bidders in every
government building work.
In the modern information technology, Building
Information Modeling (BIM) is a high tech process
being used in different construction aspects such as
visualization, simulation, cost estimation, facility
management, and construction project lifecycle [3].
As a visualized database of building elements, BIM

LITERATURE REVIEW
Cost Estimation
Cheng [5] defined the cost estimate as an
essential task for all projects because it affects
701

SEE - Bangkok, Thailand, Nov.11-13, 2019planning, bidding, design, and budget. The accurate
cost estimating is a crucial aspect of any
organization liable for budget submission, contract
negotiation, and financial decision making [6]. The
benefit of estimation is that it allows decision
makers to select adequate alternatives as well as todecrease misjudged solutions [7]. The significant
goal of doing cost estimating is to assist owners andother decision makers to clearly visual the detailinginformation of the construction projects that basedon this, they can consider to continue or alter theprocess according to the suitable budget and time
period requirements for project completion.

building that is modeled by using smart objects canenhance of extracting quantities that then link toestimating software for pricing [13]. Linking BIM
components to the estimating software is capable ofmapping BIM objects and matching with external
database to produce estimating costs in their system.
Estimating costs using a BIM-based QTO tool isable to extract the data from BIM tools to estimating
software by their readable format [14]. BIM-based
cost estimating process is capable of providing theaccurate QTO with essential effort and time savings.

Traditional cost estimation

This research developed a BIM-based simplified
approach for estimating building costs based on BIM
tool that integrates with a custom built database andspecialized templates. The whole process of thismethod is illustrated in Fig. 1.

METHODOLOGY

The traditionally applied methods of costestimating start during clients got preliminary 2D
drawings from designers and then offered tocontractors for manually calculating a summary
QTO and brief cost estimate [8]. The traditional
process of QTO is involved the design objects
measurement and other related documents such as
2D shop drawings that contain top views, left andright views, and section views of building
specifications. These 2D based documents, either
hand designed or facilitated by CAD software, areused for extracting the materials quantities by humaninterpretation to produce BOQ [9]. In the organized
BOQ, material and labor unit costs then will be
inputted manually by estimators for multiplying with
the quantities in order to get the final costs. The
traditional estimating process is time-consuming andlow level of accuracy.
BIM-based cost estimation
Building Information Modeling (BIM) is a highprototype technology and process in architecture,engineering, and construction industry. BIM iscapable of enhancing visualization, simulation, costestimation, and facility management in theconstruction project lifecycle. BIM visualization andsimulation of construction specification analysis
offers design alternatives for decision makers
communicate with stakeholders to avoid reworks
and conflicts when the design is changed [10]. BIM
can fulfill a process-related requirement series, nongeometric data, interoperability and automateddigital data sharing for a successful facility
management [11]. BIM can enhance interoperation
between project teams in the AEC industry as well
as facilitate the construction performances anddecrease project expense [12].
BIM applications allow users to access 3D
building models with quickly analyze, select, andapply the material specifications for every building
component in order to create the intelligent objects
that will support a BIM-based QTO process. The 3D

Fig. 1 Flowchart of a BIM-based simplified
approach to automatically estimate building costs.
Custom Built Database
The custom built database represents an excel listof special work breakdown structure (SpecializedWBS) that is created based on the combination oflabor and material unit cost lists. The Practical
Guidelines and Details for Calculating Construction
Cost, Thai handbook updated in October 2017,contain lists of labor costs/operations forconstruction cost calculation that used as an original
702

SEE - Bangkok, Thailand, Nov.11-13, 2019

basic data for creating the excel labor unit cost list.
The excel list of material unit cost is created basedon lists of standard materials price, Bureau of Tradeand Economic Indices, produced by Thai Ministry ofCommerce. The created list of Specialized WBS
contains specifications such as codes, descriptions,units, and unit costs. The codes applied to items of
the WBS have six levels, which level 1 to level 3
followed the Engineering Institute of Thailand (EIT)
standard cost codes and the level 4 to level 6 are
manual codes created based on the Thai Standard
System as illustrated in Fig. 2.

from the custom built database and generating acompleted BOQ and total costs.
Develop Object Properties in a BIM tool
In this research, AECOsim Building Designer
V8iTM is used as the BIM tool for developing theobject properties. This BIM application provides“building primary tool” within “dataset explorer”
that contains “Parts” and “Components” for users todevelop objects geometries depend on their projects’
requirements. The process of the objects properties
development is shown in Fig. 3.

Fig. 2 Schema of the specialized WBS codes.
This research requires the custom built databasein order to transfer the labor and material unit costs
into the estimating template for automaticallygenerating a total cost. This database is significant
and efficient for the BIM-based cost estimating
approaches,
therebyprovidingsufficientconstruction WBS that is easy to observe costing ofan original estimate according to cost changes whileeliminates re-enter the unit costs multiple times.

Fig. 3 The system of developing objects properties
in a BIM application.
Part (WBS) and components (materials properties)
AECOsim Building Designer V8iTM allows users
to create WBS specifications, which the definitions
and rendering properties can be applied by“Families” and “Parts.” This BIM tool also offers“Components” tool that allows users to creatematerials specifications by applying the density,
unit, unit price and level of accuracy to each ofthem. By using this BIM tool, users can put either
the labor or material unit price to the material
specifications that will support the QTO process to
produce directly an estimating BOQ with unit cost,
but all will need to be re-entered again when thecosts are changed. Moreover, some of existing
objects properties provided by BIM tools contained
the incorrect assigned data information even they are
not well-organized that this could be complicatedand make users difficult to find the existing objects
properties as well as cause to be error for theestimating process. So, this present research is trying
to resolve those problems by creating well-organizedobjects properties based on the Thai standard system

Specialized Templates
The specialized templates (received data andestimating) are created in different excel sheets
linking each other by the assigned formulas andfunctions. The received data template contains thesame columns heading with those of the typical
BOQ that can facilitate the data exporting process.
The estimating template is a special detailing sheetthat “if function” and “v-lookup” are assigned into
every cell for linking with the received data templateand custom built database. Once the received data
template got the data such as WBS codes,
descriptions, quantities and units from the typical
BOQ, that information will be automaticallytransferred into the estimating template. Especially,
based on the WBS codes, this estimating template iscapable of automatically searching for unit costs
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SEE - Bangkok, Thailand, Nov.11-13, 2019that can utilize for construction projects in Thailand.
This research creates “Part families” and “Parts” that
represent all construction activities in the list of
specialized WBS. “Part families” are referred to allmain activities that contain codes level 1 to 5.
“Parts” are all of the sub-activities that contain codeslevel 6. The main activities and sub-activities thatare created will be shown in “active families” and“active parts” respectively in the “building primary
tool.” This can facilitate users to utilize depend on
objects specifications during drawing process.

case, users can consider placing the 3D intelligent
objects developed by the author in two ways; 1)
Select for the developed objects at “Active families”
and then “Active parts” respectively during theprocess of objects placement; 2) Place all the 3D
objects to complete the 3D model then modify all ofthem after the process completion by using either“Apply parts” or “Building element info” tools.
Moreover, the shape of every object can be modified
by connecting, applying cutbacks or modifying ends.
BIM-based QTO (Typical BOQ)

Combine WBS with materials properties
BIM tool is capable of extracting material
takeoffs from the 3D models and export that data
information in the form of spreadsheets, databases,
or word processing files. The reported BOQ is basedon settings completed using the “Quantify” tool andcomponent definitions defined by the “Families” and“Parts” in the “Dataset explorer” that the level ofaccurate results is highly affected by the intelligent
3D objects. This present approach modeled acompleted 3D building by using the intelligent
objects, which contains specific codes that can
associate with the Thai material specifications. This
completed 3D model is then extracted due to a BIMbased QTO process in order to produce the typical
BOQ, which have only building WBS specifications
and quantities. So, this algorithm requires linking thetypical BOQ with specialized templates that is
capable of deriving labor and material unit price andgenerating a completed BOQ.

This is the important part of the objects
properties development in order to create thecompleted smart elements that can affect to thequantity takeoff process. The WBS represent objects
definitions and the material properties represent
objects specifications, If both are not combined thesoftware will not recognize the materials to be taken
off as well as error will happen during the takeoff
process. According to the existing objects properties
provided by BIM tool are not sufficient for
construction projects in Thailand as well as theformulas assigned are not suitable for Thai material
specifications. The present mechanism creates thebuilding WBS with material properties based on theThai standard system and combines them with thedata information and formulas assigned are correct
as well as adequate due to the Thai construction
requirements. The mechanism to combine is toselect for “Report component” at “Part view” thenopen property for one of sub-activity at “Parts
groups” that need to be combined. Next, click on“New report component” to show columns ofFamily, Name, and Formula that users can selectrespectively for “Component families” and“Components” then assign formula based on theobject specifications.
This research creates a schematic database in
BIM tool in order to support the 3D building models
as well as quantity takeoff process with higher
accuracy, thereby providing the adequate intelligent
objects based on the Thai material specification.
This database is a necessary requirement andsufficient for SME utilizing to estimate theirbuilding projects in Thailand.

Link Typical BOQ with Specialized Templates
The typical BOQ is a summary of data
information in an excel sheet, which is extracted
from the completed BIM-based intelligent 3Dmodels. Specialized templates are also the excel
sheets that created for linking with the typical BOQ.
The received data template contained the same
columns heading to those of the typical BOQ inorder to facilitate the linking process. All data
information in the received data template will be
automatically reflected to the estimating templatethat is capable of deriving unit costs from the custom
built database due to the WBS codes thenautomatically generates for the completed BOQ as
well as total costs. Linking between two excel
workbooks is a simple process and it is sufficient for
the estimators implement in their building
construction project in order to get the accurate
results and time saving.

Model a 3D building Using Developed Objects
This present research developed the intelligent
objects based on the Thai standard system that is anecessary requirement for users utilize for modeling
3D building in BIM tool in order to produce anaccurate BOQ. The way to place a 3D object in
AECOsim Building Designer V8iTM is by entering
data points using “AccuDraw” or by selecting object
types from which the shapes are generated. In thisRESULTS AND DISCUSTIONS
As a result, this research offers a BIM-based
simplified approach that automatically estimatesbuilding costs based on BIM 3D models that704

SEE - Bangkok, Thailand, Nov.11-13, 2019

integrate with custom built database and specialized
templates. This approach is compared to the
traditional and BIM-based estimating software
methods as below discussion consecutively.
Traditional cost estimating methods are timeconsuming and error-prone because they rely
heavily on 2D drawings and human interpretation to
generate the BOQ. Zhao [15] mentioned that cost
control-based traditional method requires muchtime, 23% of training time and 77% for
implementing cost control process.
Emerging BIM technology provides users withthe capability of modeling 3D smart elements andproduces a BOQ with unit costs, but that informationneeds to be inputted manually into the BIM tools or
by linking via plug-in/third-party with the estimating
software that derives cost data from the iClouddatabase. To grasp the benefits from BIM based
estimating software approaches, the experienced on
software using, habitual modeling, and high level ofusers training are necessary requirements [16]. Thismethod is also time-consuming, 65% for software
training and 23% on 3D modeling, and have thecauses for inaccuracies; an inadequate classification
system of BIM compatibilities; insufficient ofconstruction material definition; incomplete BIM
compatible calculating rules properties; and lackeffort in a way of operability for data exchange
requirements [17].
This research presents a BIM algorithm that theprocess of QTO is to export the building component
quantities from BIM application to Microsoft Excel
for producing the typical BOQ. This BOQ does notcontain unit prices, so it requires the custom built
database and specialized templates to fulfill thisgaps. Custom built database is a well-organized listof WBS based on the required CGD’s format, whichcontains construction activities codes, labor andmaterial unit costs. These data then will betransferred to the estimating template that
automatically generates a completed BOQ and total
costs. The created mechanism provides a simplified,
fast and accurate process because it needs only a
BIM application and Microsoft Excel, not requires
for interoperating with estimating software andiCloud database. This BIM algorithm is capable offacilitating SMEs to implement their building
construction projects in order to minimize time andincrease the accuracy. A case study, Start-Up andInnovation Building, was estimated for its
construction costs by two different methods. The
building is located in Faculty of Engineering,
Naresuan University, Thailand. It is a mixed ofreinforced concrete and steel structure, which has
total floor area is 1469.54 m2. The estimating cost
results using the Thai Manual Method, produced byan estimator of the design team in Faculty ofEngineering, Naresuan University, and those results
estimated by the author using BIM-based simplified

approach were compared that is shown theapproximately close values as illustrated in Table 1.
This proposed method will limit to estimate only
a structural and an architectural parts of a building
construction project. Users also need to know well
BIM software, custom build database, and the Thai
cost estimated system.
Table 1 The results of estimating costs produced by
the Thai manual method and BIM-based approach
Building
WBS
SubStructure
SuperStructure
Floor
Wall
Ceiling
Door
Window
Stair
ToiletRoof
Total

Thai Manual
Method(Dollars)

BIM Simple
Approach(Dollars)Different
Values(%)

14922.43$

14,740.38$

1.22%115117.34$

116,326.08$-1.05%

26355.36$
30323.71$7753.57$
33197.41$
22131.61$
6851.72$
14140.56$
53012.20$
323805.92$

26,010.11$
30,008.35$
7,850.50$
32,948.43$
21,965.62$
6,753.73$
14,006.24$
52,572.19$
323,181.60$

1.31%
1.04%
-1.25%
0.75%
0.75%
1.43%
0.95%
0.83%
0.19%

CONCLUSION
The research provides a BIM-based simplified
approach for automatically estimating building costs
based on BIM 3D intelligent objects that integrates
with custom built database and specialized templates
based on the CGD’s requirement. This algorithm iscapable of enhancing the BIM-based quantity
takeoff process and automatic cost estimations. Thismethod created a custom built database on that
contains WBS specifications and unit costs. This is asignificant list with well-organized information thatallows users to update either WBS or unit costs dueto their construction projects’ requirements in
Thailand. The developed objects that are created in a
BIM tool is the schematic database, which will
support the 3D building models in order to produce atypical BOQ with a higher accuracy. The process iscompleted by creating the specialized templates tolink with the typical BOQ and search for the laborand material unit cost from the custom built databasethat automatically generates the completed
estimating BOQ as well as total costs. This BIM
algorithm is capable of contributing the estimatorsand decision makers to reduce the time and increase
accuracy for the process of cost estimation.
Resulting from this research, a simplified but
essential cost estimating algorithm was created for
SME to implement and prepare estimating costs on
their governmental building construction projects

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SEE - Bangkok, Thailand, Nov.11-13, 2019

based on the Thailand CGD’s requirements with afast, simple, and accurate process in term of timeand cost savings. This method is a necessary
requirement for the AEC industry that installs theirbuilding projects in Thailand. Especially, theindustry that interoperated with the Thai government
construction sectors, which the projects will need tobe estimated with the monthly updated material
costs produced by the Ministry of Commerce andthe labor unit cost updated by the Comptroller
General’s Department (CGD).

Estimation of Buildings Construction Projects
Using Artficial Neural Networks. Journal of
Artificial Intelligence, Vol. 1, Issue 4, 2011,
pp.63-75.
[8] Wang S. W., and Park S. M., Building
Information Modeling (BIM) for Project Value:
Quantity Take-Off of Building Frame Approach.
International Journal of Applied Engineering
Research, Vol. 12, Issue 11, 2016, pp.77497757.
[9] Sattineni A., and Bradford R. H., Estimatingwith BIM: A Survey of US Construction
Companies, in Proc. 28th Int. Conf. on ISARC,
2011, pp. 564-569.
[10] Li J., Hou L., Wang X., Wang J., Guo J., Zhang
S., and Jiao Y., A Project-based Quantificationof BIM Benefits. International Journal ofAdvanced Robotic Systems, Vol. 8, Issue 11,2014, pp.123.
[11] Becerik-Gerber B., Jazizadeh F., Li N., andCalis G., Application Areas and Data
Requirements for BIM-Enabled Facilities
Management.
JournalofConstruction
Engineering and Management, Vol. 3, Issue 138,
2012, pp.431-442.
[12] Azhar S., Building Information Modeling(BIM): Trends, Benefits, Risks, and Challenges
for the AEC Industry. Leadership andManagement in Engineering, Vol. 3, Issue 11,2011, pp.241-252.
[13] Lee N., Dossick C. S., and Foley S. P.,
Guideline for Building Information Modeling inConstruction Engineering and Management
Education. Journal of Professional Issues inEngineering Education and Practice, Vol. 4,
Issue 139, 2013, pp.266-274.
[14] Nassar K., Assessing Building Information
Modeling Estimating Techniques Using Data
from the Classroom. Journal of Professional
Issues in Engineering Education and Practice,Vol. 3, Issue 138, 2012, pp.171-180.
[15] Zhao P. A., and Wang C. C., A Comparison ofUsing Traditional Cost Estimating Software andBIM for Construction Cost Control. ICCREM:
Smart Construction and Management in theConstruction and Management in the Context of
New Technology, 2014, pp.256-264.
[16] Choi J., Kim H., and Kim I., Open BIM-Based
Quantity Take-Off System for Schematic
Estimation of Building Frame in Early DesignStage. Journal of Computational Design andEngineering, Vol. 1, Issue 2, 2015, pp.16-25.
[17] Zhao P. A., and Wang C. C., A Comparison ofUsing Traditional Cost Estimating Software andBIM for Construction Cost Control. ICCREM:
Smart Construction and Management in theConstruction and Management in the Context of
New Technology, 2014, pp.256-264.

ACKNOWLEDGEMENT
The authors gratefully to acknowledge the Royal
Scholarship under Her Royal Highness Princess
Maha Chakri Sirindhorn Education Project for
Cambodia and Naresuan University that offered thefull scholarship and supported for this research. And
also would like to thanks the Integrated Facility
Engineering and Management (iFEM) in the
Department of Civil Engineering, Faculty ofEngineering, Naresuan University for providing
research facilities.
REFERENCES[1] Jadid M. N., and Idrees M. M., Cost Estimationof Structural Skeleton Using an Interactive
Automation Algorithm: A Conceptual Approach.
Automation in Construction, Vol. 6, Issue 16,
2007, pp.797-805.
[2] Eastman C., Teicholz, P., and Sacks R., BIM
handbook: A guide to building information
modeling for owners, managers, designers,
engineers and contractors, John Wiley and Sons,
2011.
[3] Bryde D., Broquetas M., and Volm J. M., The
Project Benefits of Building Information
Modeling (BIM). International Journal of
Project Management, Vol. 7, Issue 31, 2013,
pp.971- 980.
[4] Li J., Hou L., Wang X., Wang J., Guo J., Zhang
S., and Jiao Y., A Project-based Quantificationof BIM Benefits. International Journal ofAdvanced Robotic Systems, Vol. 8, Issue 11,2014, pp.123.
[5] Cheng M. Y., Tsai H. C., and Sudjono E.,
Conceptual Cost Estimates Using Evolutionary
Fuzzy Hybrid Neural Network for Projects inConstruction Industry. Expert Systems with
Applications, Vol. 6, Issue 37, 2010, pp.42244231.
[6] Jrade A., and Alkass S., Computer-Integrated
System for Estimating the Costs of Building
Projects. Journal of Architectural Engineering,Vol. 4, Issue 13, 2007, pp.205-223.
[7] Arafa M., and Alqedra M., Early Stage Cost

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5thInt. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EMOTIONAL QUOTIENT ASSESSMENT PROGRAM FOR
STUDENTS
1

Nualsawat Hiransakolwong1
Department of Computer Science, Faculty of Science, KMITL, BKK, Thailand

ABSTRACT
Emotional Quotient means being able to realize feelings of oneself and others to create self-motivation andcan manage various emotions to be good, smart, and happy. Nowadays, most students use smartphones. This
research presents Emotional Quotient assessment Program for students aging 12-17 years processing on
smartphones with Android OS. There were randomly selected 30 students from the Protpittayapayat School totest this software. The experiment results show that the software can help these students to know their
Emotional Quotient assessment results reported to their parents and counselor teachers. At the same time, theexecutive board of school can use the histogram of Emotional Quotient assessment results to plan suitable forschool activities for developing emotional quotient to their students. All users gave an excellent level ofsatisfaction of this software with an average of 4.88 from 5.
Keywords: Emotional Quotient, Student, School, Android

assessment that can record the results. Guidance orclass teachers can print the evaluation report andattach it in the students' report books to their parents
for acknowledging as well. At the same time,
guidance teachers are aware of the results of theemotional quotient assessment of students, bothindividual, and all. Therefore, the executive boardof school able to use the information to plan
activities [5] to develop emotional intelligence tosuit students that will benefit students, academics
and the nation.

INTRODUCTION
Emotional Quotient [1-5] is the ability torecognize and understand the emotions of yourself
and the emotions of others by playing an importantrole in social life. Due to the current lifestyle of Thaiyouth, social and cultural changes that affectemotional development cause problems that young
people cannot solve problems on their own.
Emotional quotient assessment software for Thaichildren has a role in assessing emotional quotientthat can tell the tester how to develop or improvethe emotional quotient.
Nowadays, mobile phones or smartphones havebeen developed to be able to use the internet andvarious applications that reach users of all ages.
Especially in adolescents, the behavior of this age
persons needs convenience, speed, and modernity.
But with the change of teenagers both physicallyand mentally, sometimes they do not dare to ask foradvice to adults directly. Smartphone technology
may help young people to be enthusiastic andinterested in self-assessing emotional quotient. This
assessment form is an assessment of emotional
quotient from the Department of Mental Health.
After users do assessments complexly, there will bea report of the results in three aspects: good, smart
and happy, which will be very useful for those who
do the assessment. In previous work, there are web
applications [6, 7] assessing mental health that canbe done and evaluated online. But they cannot
record data and results of the assessment. At thesame time, teenagers spend most of their time at theschool, where is a place for teaching students andteachers give advice to students. This paper presentsa mobile application doing Emotional Quotient

ALGORITHM
The Emotional Quotient (EQ) assessment
program for students aging 12-17 years. The
registration function is divided into 2 statuses; as ateacher or as a student. A teacher can create aclassroom and classroom code. Students can do the
Emotional Quotient assessment running question
randomly with a total of 52 questions. The result of
Emotional Quotient assessment is divided into 2
statuses either normal or abnormal. Thensuggestions based on the evaluation results areshown also. Students can send their assessment
results into the classroom with the classroom code.
The Emotional Quotient assessment of students’
results will be shown to their counselor teacher.
Teachers can see functions as follows: Students
Assessment results in each student or summary
table for all students. The Emotional Quotient
assessment results will show in both text and graph.
Emotional Quotient assessment results can be

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SEE - Bangkok, Thailand, Nov.11-13, 2019printed and also report to their parents as well.
The flowchart of the EQ assessment program isshown in Fig. 1 and its use case diagram is shownin Fig. 2.

PROGRAMThe Adobe Photoshop CS6 is used for interface
design. The EQ Assessment Program is createdwith Android Studio programming language andthe Firebase software is used for handling database.
The content of the EQ Assessment comes from the
Department of Mental Health, Ministry of Public
Health, Nonthaburi 11000 Thailand.
The EQ assessment program for students withaging 12-17 Years is processed on smartphones
with Android OS. After installing the EQ
assessment program on the smartphone, and thenclick open the application shown the interface as Fig.
3. This application is called EQ 101.

Fig.1 Flowchart for the EQ assessment program

Fig. 3 An interface of the EQ assessment program
For the first time use, users can choose a register
button. Then the monitor will ask for theregistration status either teachers or students asshown in Fig. 4. If a user clicks on the teacher
button, the monitor will ask for private informationsuch as name, surname, school name, email,password, and the confirm password as shown on
Fig. 5. If a user clicks on student button, the monitor
will ask for more private information such as name,surname, school name, email, password, theconfirm password, and more information about
their parents. For the next time use, users only clickon the Sign In button, and then the monitor will ask
only for email and password as on Fig. 6. Then the
program will show functions for each type of

Fig. 2 Use case diagram
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SEE - Bangkok, Thailand, Nov.11-13, 2019

registration either teachers or students.

Fig. 4 Registration status either teachers or students

Fig. 6 Sign In after the registration
In Fig. 7, when a user has a status as a teacher
after the user login, the monitor will show functions,such as Classroom for creating a classroom,
Information for editing teacher’s information, theEQ questions showing 52 questions in the EQ
Assessment, Advice for EQ showing examples ofadvice to develop EQ that teachers can learn, andAssessments showing the EQ assessment results foreach student or the all students in a class/school.
Teachers can create, edit, and delete classrooms.
When a teacher creates a classroom by pressing the+ sign on the bottom right in Fig 8, the program will
generate a classroom code for a teacher to inform
his/her students. Students will use a classroom code
to add name and send the EQ assessment results intheir classrooms as shown in Fig. 9. Teachers canview and print the EQ assessment results for each
student to inform the student’s parents. The EQ
assessment results will show in a graph with 3
categories such as being good, smart, and happy. In
Fig. 10, a teacher view the EQ assessment results inbeing in the good category of one student who ever
did the EQ assessment twice. Its results will show
both times: #1 and #2. Being good is consist of selfregulation, empathy, and responsible. The parents
will know the EQ assessment results of theirchildren, and then they can adjust activities in thefamily to develop QE for their children.
When the user has a student status after entering
the system of the user, the screen will display
functions such as assessments for doing EQ

Fig. 5 Private information for registration

709

SEE - Bangkok, Thailand, Nov.11-13, 2019assessments, assessment results to show the historyof QE assessment results, Information for editing
his/her information, Advices for EQ showing
examples of advice to develop EQ that students canlearn.

Fig. 8 An example for creating a classroom 101

Fig. 9 The EQ assessment results of each student

Fig. 7 Functions for teachers

Fig. 10 EQ assessment results in being good
From Fig. 10, the more detail will show in Fig.
11 and Fig. 12. Being good consists of selfregulation, empathy, and responsible. Being smart
710

SEE - Bangkok, Thailand, Nov.11-13, 2019consists of motivation one-self, decide the solution,and build relationships. Happiness consists of selfesteem, satisfied in life, and calm. There are totallynine items of the EQ assessment results, such as
self-regulation, empathy, responsible, motivation
one-self, decide the solution, build relationships,
self-esteem, satisfied in life, and calm. From Fig. 11
and Fig. 12, the results of a student whose name is
Mr. B Park is shown all of nine items. There is an
opening bracket in front of each item. If the opening
bracket is blue, the evaluation results of that item
are normal and it is written “normal" at the end of
the item also. On another hand, if the opening
bracket is red, the evaluation results of that item areabnormal and it is written "should improve" at theend of the item also. Fig. 12 is a screen continue
from Fig. 11 after sliding its slide bar. There are two
buttons of the bottom in Fig. 12. The Advice button
will show some advice on how to improve in eachabnormal item from the EQ assessment results. The
Create PDF button will create the EQ assessment
results and advice on how to improve abnormal
items into the PDF file. Teachers can print the PDF
file and also report to students’ parents as well.
Teachers and their parents will aware of the EQ
assessment results and know how to arrange
activities [5] for their children. Teachers can selectactivities [9-10] that help student’s improvement intheir EQ. At the same time, their parents can also
adjust activities in the family more suitable for
improving the EQ of their children.

Fig. 12 The EQ assessment results (continue)
Teachers not only know the results of each student's
EQ assessment in the classroom but also know theunusual frequency of each item of the EQ
evaluation of all students in their school, as shownin Fig. 13. From Fig. 13, the table shows each row
is consist of a student name and EQ evaluation innine columns composed self-regulation, empathy,
responsible, motivation one-self, decide thesolution, build relationships, self-esteem, satisfied
in life, and calm. The EQ assessment result in eachcolumn represents color. For example, white means
the normal result and red means abnormal or shouldbe improved. At the bottom of the table is asummary of the frequency of irregularities in eachcolumn.

Fig. 13 The EQ assessment results of all students

Fig. 11 EQ assessment results of Mr. B Park
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Table 4 Average user satisfaction of the EQ 101

EXPERIMENTAL RESULTS
After the EQ 101 was finish coding program,
this application was installed into five smartphones
on Android OS. There were randomly selected one
teacher and ten students from the Protpittayapayat
School, a local school to test this software. In thefirst time, after the application had been used byteacher and students, each user was an interview
and gave with some comments to develop theapplication more benefits, such as creating the EQ
assessment results into PDF file that can print toreport student's parents and summary results of all
students in school, then the executive board ofschool can use histogram of Emotional Quotient
assessment results to plan suitable of school
activities for developing emotional quotient to theirstudents. Then the EQ 101 had been adjusted the
new version following the comments.
On the second time, there were randomly
selected 31 students and 2 teachers from the same
local school to test this new version software. Afterusers were finished the test, they did questionnaires
and were an interview. The survey results were as
follows: For the personal information, users are 10
male (about 30.30 %) and 23 female (about 69.70%) as shown in Table 1, and there are 2 teachers and
31 students as shown in Table 2. For percentages of
the grade level of students, there are 2 students ofGrade 9th, 11 students of Grade 10th, and 18
students of Grade 11th as shown in Table 3.

Satisfaction
1. Able to study usage
quickly and easily
2. Satisfied with themodernization of
application design
3. The application candisplay correctly
4. The appropriatenessof the font size used in
the application
5. The suitability of
the colors used in theuse
6. Response speed
7. The application isuseful to users
8. Satisfaction in using
the applicationw = (H – L)/N

Number10
23
33

Percent
30.30
69.70
100.00

Table 2 Frequency distribution: status of users
StatusTeachers
Students
Total

Number2
31
33

Percent
6.06
93.94
100.00

Number
2
11
18
31

4.52

excellent

4.45

excellent

4.58

excellent

4.45

excellent

4.82
4.88

excellent
excellent

4.79

excellent(1)

From Table 4, the average user satisfaction of theEQ 101 was shown. For example, users gave an
average of satisfaction with 4.52 for able to study
usage quickly and easily means excellent. Users
gave excellent satisfaction in all dimensions ofusing this application. The application is useful tousers get the highest satisfaction with the averagevalue 4.88 identifying the high quality of the EQ
assessment for students, teachers, and schools.

Table 3 Percentages of grade level for users
Grade level
Grade 9Grade 10
Grade 11
Total

4.52

Level ofsatisfaction
excellent

Where w = the width of the class
H = the highest value of the scale
L = the lowest value of the scale
N = the number of levels
From [8] Likert scale of five levels will compute thewidth of the class by using Eq. (1). The highest
value of the scale is five and the lowest value of thescale is one. The number of levels is five.
Therefore, H = 5, L = 1, N = 5, the width of the classis equal to 0.8 (w = 0.8). The level of satisfaction
can transform as follows:
The value of satisfaction 1.00 – 1.80 means poor.
The value of satisfaction 1.81 – 2.60 means fair.
The value of satisfaction 2.61 – 3.40 means good.
The value of satisfaction 3.41 – 4.20 means very
good, and the value of satisfaction 4.21 – 5.00
means excellent.

Table 1 Frequency distribution: gender of users
GenderMale
FemaleTotal

Average

Percent
6.45
35.48
58.07
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SEE - Bangkok, Thailand, Nov.11-13, 2019

CONCLUSION

https://www.talentsmart.com/media/uploads/p
dfs/eq-what-it-is.pdf[3] DanielGoleman(1996),
EmotionalIntelligence: Why It Can Matter More than IQ,
Learning, v24 n6 p49-50 May-Jun 1996.
[4] M.L.Somchai Chakrabhand, Community
Mental Health: Thailand Country Report 2008,
Department of Mental Health, Ministry of
Public Health, Nonthaburi 11000 Thailand,
August 2009.
[5] Project TO BE NUMBER ONE, Practicethinking to solve problems, develop EQ, Event
handbook for Volunteers, Kaew Chao ChomMedia and Publications Center, Suan Sunandha
Rajabhat University, Revised version July
2015.
[6] Webpage IQEQDEKTHAI is available at
http://rajanukul.go.th/iqeq/index.php.
[7] Department of Mental Health is available athttps://www.dmh.go.th/test/.
[8] Rensis Likert (1961), New Patterns ofManagement, New York: McGraw-Hill Book
Company Inc.
[9] Yaowanat P., Sajee S., Kaliyakorn K., Pruksa
P., Activity guide to strengthen students' EQ,
Department of Mental Health, Ministry of
Public Health, Nonthaburi 11000 Thailand,
August 2014.
[10] Yaowanat P., Sajee S., Kaliyakorn K., Pruksa
P., Activity guide to strengthen students' EQ,
Department of Mental Health, Ministry of
Public Health, Nonthaburi 11000 Thailand,
August 2018.

The Benefits of the applications are as follows:
1. Students can do the EQ assessment moreconvenient, know their EQ assessment results, andknow how to improve their EQ.
2. Teachers can check the EQ assessment resultsof students either the results for each student orwhole students in a class/school more convenient.
3. Students can develop and improve themselves
appropriately from the results of the EQ assessment
and its recommendations.
4. Teachers and parents know how to organize
activities to improve emotional intelligence
behavior more suit with students.
5. At the same time, the executive board ofschool can use the histogram of Emotional Quotient
assessment results to plan suitable of school
activities for developing emotional quotient to theirstudents that will benefit students, academics andthe nation.
ACKNOWLEDGMENTS
I would like to thank you, Miss. Tharinee
Vatesee and Miss. Bongkot Chatchawan to help me
coding the program.

REFERENCES[1] Robert K. Cooper (1998), Executive EQ,
Texere Publishing, US 1998.
[2] Cary Cherniss (2000), Emotional Intelligence:
What it is and Why it Matters, Consortium for
Research on Emotional Intelligence in
Organizations, Psychology, New Orleans, LA,
April 15, 2000, available online at,713

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ELECTROMAGNETIC SWITCHING TRANSIENTSIN TRANSMISSION LINE COOPERATINGWITH THE LOCAL SUBSYSTEM

1Pawel Sowa1, Daria Macha1
Silesian University of Technology, Gliwice, Poland

ABSTRACTThe article investigates the overvoltage occurring during switching states in the line cooperating with the local
subsystem. Overvoltages appearing in the line connected to the local subsystem during switching operations,forced by the change of network operation conditions. Electromagnetic transients in the unloaded line were tested
after its sudden disconnection from the power supply. In the research, particular attention was paid to the conditionsof switching off the line (moment and disconnection unity), the influence of surge protection devices, the type ofthe voltage transformer and the short-circuit power of the power subsystems.
Keywords: Overvoltages, Switching Surges, Electromagnetic Transients, Equivalent Network

subsystems of the power supply.
Figure 1 presents a schematic diagram of thestudied system and a graphic model introducing the
input data to the MicroTran [1] program (UBC
version of the Electromagnetic Transients Program EMTP) used by simulation. The program provides
tabular display, printer plots and high resolution
graphic plots as output. The method used in programis based on Bergeron's method for transmission lines
and trapezoidal rule of integration for lumped
parameters.

INTRODUCTION
In the 400 kV transmission network theovervoltages can occur which are mainly caused by
the following factors:
 maintaining normal voltages in relation to therated voltage of the network, expansion of the 400 kV transmission network(lines, especially in low-load states, are a sourceof reactive power, and as a result, increase thevoltage level), insufficient equipment of the 400 kV transmission
network in devices for capacitive reactive powercompensation (parallel reactors),
 development of local production sources that
relieve the transmission network.
The waveforms of electrical quantities in thehighest voltage lines depend on many factors ofwhich for the steady state the most important are:shunt parameters, short-circuit power and line
symmetry. This influence is emphasized in the caseof a weak line load or if the line is opened at one end.
However one-side opened transmission line is asource of reactive power (the value of generated
reactive power is proportional to the length of the line
- 1 km of the 400 kV line generates approx. 0.5
MVAr). If the attached end of the line is connected toa weak system, it can cause a large voltage boost.
During transient states there are many importantfactors affecting the maximum values ofelectromagnetic transitent components.
For a full assessment of critical value, acomprehensive analysis was carried out, including the
moment of switching off the line, thenonsimultaneously disconnection, the influence of
surge protection devices, the type of the voltage
transformer and the short-circuit power of the

SYSTEM

Fig. 1

LOCAL SUBSYSTEM

Diagram of tested system.

Using MicroTran program it is shown that alltransients in high voltage system can be determined
and the most severe conditions can be modeled
without risk and with very flexible possibility todetermine the performance of electrical equipment in
the high voltage line under all possible fault
conditions in transmission system.
Analysis was made for the signals with very highlevel of high-frequency component. Methods were
tested with the help of MicroTran program and
NETOMAC – program [2].
714SEE - Bangkok, Thailand, Nov.11-13, 2019transformer, the effective counteracting of
ferroresonance phenomena for both harmonics andsubharmonics is protracted. Figure 3 is a substitutediagram of an inductive voltage transformer,
The errors in the transfer of the voltage signaltransformer to the secondary side can be caused
primarily by the impedance values of the load and themagnetization inductance Lμ and loss resistance in theRFe core.
The schematic diagram of the capacitive voltage
transformer is shown in Fig. 4. During transient
voltage transformers accurately transmit the voltage
signal. The share of a non-periodic component in thevoltage signal is small - there is no threat of saturationof the transformer. All significant harmonics are
reproduced exactly on the secondary side and theimpact of the magnetizing currents appearing duringswitching the transformers is damped very quickly.
Signal transfer errors can only occur for very highfrequency.

SELECTION OF SIMULATION METHODTransmission line modelTransmission line in real is the only one elementof the power system with distributed parameters, andtherefore for the simulation the adequate numericalmodels and methods must be used. Figure 2 shows theelementary dx section of the transmission line.
Line modeling by means of a series of substituteelements connected in series – three-phase PI-gliders
taking into account inductive and capacitive
couplings - can lead to erroneous results manifestedby the presence of artificial components that do notexist in real systems.
For the model of lines with distributed parameters,
the dependence of parameters on the frequency istaken into account by the use of the so-called Martimodel [3], which is the optimal solution from thepoint of view of accuracy and speed of calculation.

L1

R1
Lμ Φ

uL2x+dx

uL1x+dx

L2

R2

Zo

RFe

uL3x+dx

CL1L3dx
CL1L2dx
CL1zdx
GL1L3dx
GL1L2dx

CL2L3dx

Fig. 3CL3zdxCL2zdx
GL2L3dx

GL1zdxGL2zdxC1
GL3zdx

LL1L2dx
R L1dx

uL1x

LL1zdx

RL2dx

uL2x

LL2dx
LL2zdx

LL2L3dx

LL3dx

R L3dx

LL3zdx

C2

Cps

C1

Rp
Lμ Φ

Cs

Ferroresonancesuppression
systemZo

uL3x

Fig. 4
Fig. 2

C1
Lt

LL1L3dx
LL1dx

Model of inductive voltage transformer.

Representation of the transmission line
section length dx.

Model of capacitive voltage transformer.

To protect the electrical apparatus against transient
overvoltages, surge arresters (lightning arresters) areused to limit the duration and frequency of thesubsequent current. In MicroTran program twomodels of the surge arrester are available to the user:
using non-linear resistance (Fig. 5) and built of a nonlinear element - usually ZnO (Fig. 6).

Primary equipment models
In order to obtain reliable results ofelectromagnetic studies of transient phenomena, apartfrom the overhead line model, it is very important to
get the correctly representation of primary equipment
such as voltage transformers and surge arresters.
There are two constructions of voltage transformers:
 inductive, which are measuring transformers witha primary winding connected directly to the
network; capacitive, in which the measuring transformer is
supplied from a capacitive voltage divider, thanks
to which the insulation of the transformer itself
can be built to a much lower voltage than in thecase of inductive transformers;
In many constructions of inductive voltage

Fig. 5715

Representation of surge arrester with nonlinear resistance.

SEE - Bangkok, Thailand, Nov.11-13, 2019

The modification of least-square method
proposed in [4] was tested for signals with high levelof high frequency free components with MicroTranprogram and for signals with low level of thiscomponents with NETOMAC program.
The new idea using artificial neural network(ANN) determine the new direction of search ofequivalent solution for the range of electromagnetictransient [5]. The aim is to replace part of systems bysuitable universal ANN-based dynamic equivalents.
Fig. 6

Model of surge arrester used ZnO element.

SIMULATION TESTS FOR VARIOUS WORKAND DISTURBANCE VARIANTS

Equivalent system

Verification of computer simulation with thevalues measured during the fault test

During analysis in complex system call inquestion both the necessity of detailed representationof each element and the range of reduction of network
and its influence on credibility of results ofinvestigation. Generally to get correct results ofcalculation in equivalent system is possible onlywhen: element of system, for which transient (voltage orcurrent) should be determined, must be modeled
in detail without any simplification taking into
consideration every factor having influence on
result of investigation,
 remaining part of system which will be reduced
must be represented by equivalent network but theparameters must by identified with the help ofaccording optimization method.

Comparison of computed transient waveforms
with those measured on an actual system allow someassessment to be made of the methods of calculation.
The measurement techniques must be free of error
and comprehensive system data must be provided inorder to achieve maximum computational accuracy.
In Figure 7 the comparison of two measured voltage
transient are presented.

uL2

1.53

Time [s]By process of identification for given transient
input signals there are searching the parameters ofdetermined mathematical model representing part ofsystem designed for reduction. For solution of suchproblem it is assumed at begin unchanged structure ofinvestigated model and possibility of unlimited
choice of parameter for equivalent.
By lack of information of identified equivalentsystem the identification process is going in 4 steps
after preparation of input and output data signals:
 determination of structure of equivalent system, choice of optimization criterion,
 choice of numerical method and determination ofparameters according to chosen criterion,
 testing of structure of model taking into accountthat for each new structure new parameter
identification will be performed.
The choice of structure depend on later
application but critical verification must be only after
determination of optimal parameters of equivalentsystem. Very important is optimization method.

CASE 1
CASE 2

Fig. 7

Recorded voltage waveforms.

The results were recorded during two measurements
at the beginning of 260 km line length, during
disconnection at the end of line. To be able to use thetest results the values measured during the tests havebeen transferred into a mathematical model for theMicroTran program. The computer simulation wasused for very detailed transmission line model andsimple equivalents of complex transmission networks.
Comparison of the measured and calculated values
for the voltage and current transients indicates that thesystem modeling was precise enough for furthertransient analyses.
Determination of the value and nature ofovervoltages occurring for the unloaded line
The research has shown a huge number of factors
affecting the surge coefficients, whereby repeatedly
716

SEE - Bangkok, Thailand, Nov.11-13, 2019changing individual parameters for a given system
configuration does not cause a significant change inthe values of these factors, but only a change in"circumstances", e.g. time of peak voltage during an
ongoing transient process. numerical analysis todetermine the phasing delay times during which
maximum overvoltages can occur is very tedious andtime-consuming.
The maximum amplitudes of free components
occur in the phase whose voltage at the moment ofswitching off reaches the maximum value. From theextremely different conditions of maximum transient
voltage values (maximum overvoltages for the initialmoment of the disturbance, when the disconnection
phase voltage reaches the maximum) it follows that
virtually always during the interferences there are freecomponents with different amplitudes and damping
times. Taking into account the phenomenon ofsuperimposition of these components during nonsimultaneous disturbances, there is the problem of theincrease of these amplitudes and damping times inrelation to these values calculated for simultaneous
disturbances. The inconsistency of the switching
disturbances results in a significant increase of theovervoltage coefficients in relation to the maximum
calculated during these disturbances treated assimultaneous.
Figures 8 and 9 show the example of transients on
the secondary side of the capacitive and inductive
transformers installed at the beginning of the line
when the circuit breakers are off at each of the twotransmission line systems.
Overvoltage coefficients obtained during nonsimultaneous switching off significantly exceed thesevalues (as can be seen in the presented drawings) anddespite the fact that overvoltages are transient, but
due to the repetition of this phenomenon may pose athreat to the primary apparatus.

ucvL1
ucvL2
ucvL3
Time [s]Delay 15 ms
2,37

Fig. 9 Waveforms on the secondary side of thecapacitive transformer installed at the
beginning of the line after 15 millisecond
delay of shutting down the second system.
Figure 10 shows the same example of transientsbut on the primary system.

us2L2
us1L3

us1L3
Time [s]Delay 15 ms

us1L2
2,25

us1L1

us2L1

Fig. 10 Waveforms on the primary side of thecapacitive transformer installed at the
beginning of the line at the 15 millisecond
delay of switching off the second system.
Discussion of the impact of data on test results
Situation in the line after disconnection from thepower supply is stable. The voltage remains at a
certain level - keeping the instantaneous value as it
was before the disturbance. This is due to the fact thatthe voltage in the line is not possible (or they areminimal) for unloading. Connecting the equipment voltage limiters on both sides of the line improves thissituation.
Note that both types of representation of surgearresters do not contribute to large differences in thevalues of extreme surge coefficients.
There is clearly faster damping in the case ofmodeling using a resistive model, but there is no
major difference in the obtained surge coefficients,
what is illustrated in the Fig. 11 and 12.

2,19

ucvL1
ucvL2
ucvL3
Time [s]Delay 5 ms

Fig. 8 Waveforms on the secondary side of thecapacitive transformer installed at the
beginning of the line after 5 millisecond delayof shutting down the second system.

717

SEE - Bangkok, Thailand, Nov.11-13, 2019

200

uL3

Representation of arresterwith non-linear resistance

There are also free lower frequency components
damping very slowly.
During the disturbance state on the primary sideof the capacitive transformer, the energy stored in thecapacities and inductances results in transientoscillations on its secondary side. Transient
waveforms are a combination of low frequency signal
oscillation (2-15 Hz) and high frequency oscillation
signal (900-4000 Hz). The free frequency componentof the higher frequency is suppressed in a short time(less than 10 ms), whereas the low frequency
oscillation signal lasts longer.
The overlapping of free components created on
the primary side of the transformer and its own
oscillations may cause false signals from thesecondary side. This mainly applies to freecomponents of higher frequencies that determine theamplitude of induced overvoltages.
The cause of the disturbing phenomena
investigated in the paper is the problem of switchingovervoltages arising when switching off the unloadedline of considerable length, but still equipped withcapacitor voltage transformers. The line with a fairly
complex course is over 260 km long, so the power ofcharging it is about 150 MVar. It follows that theswitch is designed to disable the capacitance ofsignificant value.
Therefore, to determine the correct conditions for
conducting mergers, one or several of the remedial
measures resulting from the analysis should beapplied: for the suppression of transient states, the simplest
remedy could be to replace capacitive transducers
with inductive voltage transformers. This isparticularly important for the tested line ofconsiderable length.
 it would be advisable to use high-voltage
transverse chokes to reduce the overvoltages ofthe mains frequency (the so-called compensatedline).
 discharge resistors, a short-term bypass switch,would be helpful.
 a good damping effect of oscillations afterswitching off the line could give short-term
switching of resistors
Generally, for the elimination or reduction of theovervoltage in the line after disconnection of line - thebest and the fastest solution would be to replace thecapacitive voltage transformers with the use of
inductive voltage transformers.
However, this causes the risk of occurrence offerroresonance phenomena (in particular chaotic

uL1

100

uL2

2.27

Time [s]

uL3

uL1

-100

-200

Representation of arresterwith ZnO

uL2

2.25

Fig. 11 Comparison of transients calculated on thesecondary side of the capacitive transformer
with two representation of surge arrester.

uL3

ZnO
R

ZnO

uL1

R

R

Time [s]

uL2

R

ZnO

Fig. 12 Comparison of transients calculated on the
primary side of the capacitive transformer
with two representation of surge arrester.
Transient waveforms occurring on the secondary sideof capacitive voltage transformers do not change theircharacter along with a change in the representation ofsurge arresters in the transmission system on the
primary side. In both cases these waveforms are faster
suppressed than the primary voltage, but there are
oscillations resulting from the free components of thehigher frequencies. Overlapping of these components
causes a large number of voltages on the secondaryside of capacitive voltage transformers. However, thisdoes not pose a threat to the transformer due to thevoltage value on the secondary side of thetransformer.
CONCLUSIONSAs stated in the research, the high frequency
components that disappear relatively quickly have asignificant impact on the peak values of instantaneousvoltages on both sides of capacitive voltage
transformers. The extreme peak of the instantaneousvoltage was noted at both ends of the switched off linewith multiples significantly value = 2 in relation to
the maximum phase voltage of the line.
718

SEE - Bangkok, Thailand, Nov.11-13, 2019

simulations, IEEE Trans. PAS-101, 1982 s.147157.
[4] Sowa P., Search of Optimum Equivalent
Representation for Transient Investigations
during non-Simultaneous Faults, Proceedings ofthe IASTED, Int. Conference Modeling and
Simulation,
Pittsburgh,
USA,
1998,
IASTED/ACTA Press, ISBN: 0-88986-252-4,
ISSN: 1021-818, pp.466-470.
[5] Azmy A.M., Erlich I., Sowa P., Artificial Neural
Network-Based Dynamic Equivalents forDistribution Systems Containing Active Sources,
IEEE Power Systems, 2004.
[6] Sowa P., Comparison of results of optimization by
searching of equivalent system, Power
Symposium, NAPS '08, 40th North American,
10.1109/NAPS, 2008, 5307379, pp. 1-4[7] Sowa P.: Representation of power system forelectromagnetictransientcalculation,
International Journal of Electrical Power &Energy Systems Engineering, 2008, Vol. 1, No. 3,
pp. 152-155.
[8] Optimization of Equivalent Networks forTransient Simulation in H.V. Transmission
Systems, IASTED, International Conference Modeling, Simulation and Optimization, Gold
Coast, Australia, May. 6-9, Paper#: 242-205,
1996.
[9] Castellanos F., Marti J.R.: Full FrequencyDependent Phase-Domain Transmission Line
Model, IEEE Transactions on Power Systems,
Vol. 12, No. 3, August 1997, pp. 1331-1339.

ones).
The use of controlled energoelectronic regulators
system is not - from the point of view of developmentof network conditions conducive to the generation offerrorezonance chaos - only the risks, but it can be aneffective means of great potential to prevent or
mitigate the effects of the phenomenon offerroresonance or ferroresonance chaos in the powersystem.
Effective and efficient use of energoelectronic
controllers, must be preceded by a series ofsimulation studies and not limited only to determine
the presence and impact of regulatory options tochange the substitute driver impedance parameters of
the network and the resulting possibility of preventing
ferrorezonance chaos but also taking into account, theimpact of network parameters control using
energoelectronic devices on systems stability especially dynamic - power system or selected partsof system.
REFERENCES[1] MicroTran, Transients Analysis Program for
Personal Computers, MicroTran Power System
Analysis Corporation, June 1991, Vancouver,B.C., Canada[2] Kulicke B., Simulationsprogram Netomac:
Differenzen
Leitwertverfahrenbeikontinuierlichenunddiskontinuierlichen
Systemen, Siemens Forsch.– und Entwickl. Ber
Bd. 10 (1981), 5, pp. 299-302[3] Marti J.R., Accurate modelling of frequencydependent lines in electromagnetic transient719

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SAFETY, CONNECTIVITY, AND COMFORTABILITY AS
INDICATORS TO IMPROVE WALKABILITY TO THE BUS STOPS IN
PENANG ISLAND*Nur Sabahiah Abdul Sukor1 and Siti Fadhlina Muhammad Fisal2
School of Civil Engineering, Universiti Sains Malaysia, Engineering Campus, Pulau Pinang, Malaysia

1,2

ABSTRACTLess walkability will result in various negative impacts if not addressed immediately. Among theconsequences are increased in private vehicles which contributes to environmental degradation and fatalities.
Hence, this study investigates the determinants of walkability by evaluating the assessment indicators concerning
one of the active modes of transport i.e., walkability, by constructing a path model from structural equation
modeling (SEM) based on on-site data collected in Penang. Based on the path analysis, safety (β3=0.598),
connectivity (β1 = 0.371) and comfort (β3 = 0.257) obtained positive impacts towards walkability which safety
possessed the strongest correlation with four statistically significant indicators (W6; t=15.194, W7; t=7.149, W9;t=18.062; W10; t=9.115) contributing to walkability. The findings from the study give weight to the related
authorities to focus more on enhancing the safety for walking facilities to access the bus stops. Thus it will likely
to increase the likeliness to use the public bus services. The findings from this study also reveal the underlying
factors to boost the preference of public to adopt walking as an active mode of transport thereby, reducing thedependency on private vehicles.
Keywords: Walkability, Structural Equation Modelling (SEM), Factor Analysis, Sustainable Transport, Public
Transport

major contribution to this fatalities is none other thehigh reliance of vehicles. In conjunction to achieve
40:60 modal split by 2030 as per enforced by thegovernment, this issue should be dealt withimmediately. Safety and built environment factors
should be put forth to encourage walkability. The
less walkable area will discourage walkability which
in turn causes people to depend on vehiculartransportation modes. Thus, an inherent environmentis crucial to engage the vibes of walkability in an
area.

INTRODUCTION
Walkability is recognized as a sustainable activemode element which has tremendous social andenvironmental benefits. In terms of health,walkability is proven to be associated with obesity
where people are more likely to become obese if
settled in a less walkable area [1-6]. Moreover, theprevious study stated that walking will not only
decreases the risk of obesity but also prevents theincidence of other chronic diseases [7]. In this 21st
century, it is noticeable that there is a decline in thewalking behavior among people due to increasing
reliance on the use of private vehicles. Regardless ofthe negative health consequences that may arise due
to less walking, people still tend to opt and rely moreon private vehicles instead of practicing activemodes.
Apart from negative health consequences, lesswalkability gives adverse consequences to theenvironment as well. Increase in private vehicles
will deteriorate the environment by causing air
pollution and noise pollution. Moreover, an alarming
rate of vehicles also exposes people to fatalities.
Statistics from the World Health Organization(WHO) reported that Malaysia was ranked as one of
the top three countries in the world with thedeadliest roads after Thailand and South Africa [8].
Adding to that, a total of 7,152 deaths from roadaccidents was recorded in Malaysia in the year 2016
which mainly involved the motorcyclists. One of the

LITERATURE REVIEWThe previous study ascertained that the major
factor to encourage walkability is the accessibility toa good walking environment [9]. They listed out few
determinants of walking behavior such as land use
mix, street connectivity, distance to transit stops anddestination accessibility. This can also be associatedwith highly urbanized areas [10], destination types[11] and the aesthetics factors on choosing a routefor walking [12]. Another study figured out thatconnectivity is an important attribute to ensure highquality public transit, considering the end-to-end
connectivity from the origins of the trip to respective
destinations [13]. In addition, the physical distances
between stations also have an impact on thewillingness to walk. Physical connectivity criteriasuch as continuously connected sidewalks and placebased barriers to segregate with the vehicular traffic
720

SEE - Bangkok, Thailand, Nov.11-13, 2019

do affect the last-mile trip. It is also claimed that theorigin and destination of the walking trip is one of
the built-in environmental factors that affect thewillingness to walk [14].
Walkability is also affected by the social
demographic factors such as walking distance,
walking time and the purpose of the trip [15]. In
addition to the above factors, gender, age, marital
status, income, education, and vehicle ownershipwere also claimed as contributing factors towalkability [10], [16], [17]. In addition, shorter
travel time and travel distance are also among theinfluencing determinants [12]. Safety is anothersocial feature that has been prioritized by pedestrians.
A previous study proved that the majority of
motorcycle-taxi users are reluctant to walk becauseof safety concerns and most of them are afraid ofaccidents [18]. Similarly, young adults also would
likely to have perception towards safety whilechoosing their preference for transportation modes[19]. A high rate of accidents involving pedestrians
is also discouraging their willingness to walk which
in turn increase their dependency on vehicles
reliance. In addition, comfort is also associated withwalkability where most of the people would like towalk if the walkway is comfortable [20]. This is also
should be supported by good environmental design,proper space for walking and good surfaces to walk[21]. It is believed that comfortable walkways
should also not be obstructed, safe and smooth forstroller and wheelchair users [22].
As a result, this study will focus on identifying
the criteria to improve walkability especially for theaccessibility to the public buses. The significant
criteria will be selected through the path modeling
analyses. Next subtopics will explain themethodology used in this study, the indicators foreach criteria and the results from data analyses.

800 meters walking distance from the transit stations
as per suggested in previous studies [18], [23], [24].
Fig. 1 shows the site location of the study with acircular radius of 800 meters. The selected bus stops
were divided into 19 zones as shown in Table 1

Fig 1 Site location according to BLLRT alignment[25]
The data collection involved two types of on-sitedata collection, which were traffic volume forprivate vehicles and transport assessment audit. The
traffic count was conducted for 3 working days
(Tuesday, Wednesday, Thursday) during 2 peak
hours (630-930) and (1715-1930) within 5 months.
Meanwhile, the traffic count focused on private carsand motorcycles. Transport Assessment Checklist
was designed, and the auditing tasks were done at
the selected bus stops. The indicators were audited
based on the score options; 1= does not exist, 2= Not
following the guidelines and 3= Following theguidelines. The criteria of walkability elements were
derived from numerous studies in the literature andreports. The elements were selected based on thefrequency of mention by scholars. Table 2 shows thesources for walkability criteria that is considered inthis study.

METHODOLOGY
The study was conducted along the alignment of
the proposed Bayan Lepas Light Rail Transit(BLLRT) in Penang Island. The objective ofselecting the proposed BLLRT alignment as the site
location is to explore the futuristic possibility for an
integrated transportation network for publicconveyance involving both the LRT and the publicbus. There are 27 proposed LRT stations altogether,
but the study only involves 19 stations on the islandas the other 8 stations are on the 3 proposed
reclaimed islands which haven’t been developed yet.
Even though the proposed BLLRT alignment is stillin the proposal stage, this study can still be abaseline for the walkability study. 123 bus stops
were evaluated along the alignment, and the selectedbus stops were located in a radius of approximately

721

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 Zones and bus stops involved in this study
Site Zones
1. Komtar Zone (KMZ)
2. Macallum Zone (MZ)
3. Bandar Sri Pinang Zone (BSPZ)
4. Skycab Zone (SKYZ)
5. East Jelutong Zone (EJZ)
6. The Light Zone (TLZ)
7. Gelugor Zone (GZ)
8. USM Zone (USMZ)
9. Batu Uban Zone (BUZ)
10. Pesta Zone (PZ)
11. Sg. Nibong Zone (SNZ)
12. Bukit Jambul Zone (BJZ)
13. SPICE Zone (SZ)
14. Jalan Tengah Zone (JTZ)
15. FIZ North Zone (FNZ)
16. FIZ South Zone (FSZ)
17. Sg Tiram Zone (STZ)
18. Penang Airport Zone (PAZ)
19. Permatang Damar Laut Zone (PDLZ)

Number of Bus Stops
23
9
8
7
6
7
3
2
9
9
7
3
8
8
2
1
2
7
2

Table 2 Walkability Criteria based on previous literature reviews
Indicator ID
Connectivity
W1
W2
Safety
W3
W4
W5
W6
W7
W8
W9
W10
W11
Comfort
W12
W13
W14
W15
W16
W17
W18

Walkability

Source/Previous Study

Connecting pedestrian walkways either paved or unpaved to thenearest main attraction within 400 meters to/from bus stop
The walkway should not be obstructed by any things (for ex: trees,
shrubs, etc) to the nearest main attractions[26], [27], [28], [29],[30][30], [31]Provision of bollards/shrubs/fence/ditch at the end of the walkway
to segregate from the car lanes
Provision of bollards at road intersections (if there areintersections)
Provision of median refuge island with a minimum of 1.0 meter atcrossings for the road that exceed 2 lanes
Provision of crosswalk at road intersections for a pedestrian to
cross
Well maintained walkways (smooth pavement/not overgrownshrubs and trees/not broken)
Signages in good condition (clearly seen/not broken)
Crosswalk/markings are clearly seen
Pedestrian signals must be in good condition (functional/not
broken)Walkways have smooth incline at the end of walkways or towards
road intersection which can be used by wheelchairs and strollers[32]

Have seats at bus stop
Have a rubbish bin at the bus stop
Sidewalk width must not less than 1.50m width
Availability of street trees/awnings/arcades
Provision of signage for a pedestrian walkway
Provision of signage to warn motorist about the presence ofpedestrian walkway
Provision of minimum 1.0-meter divider width (lowshrubs/plants/fence/any safety barriers) between road andwalkway.
722

[28]
[33]
[34], [35][29], [32][26], [28][30], [31][28], [34]

SEE - Bangkok, Thailand, Nov.11-13, 2019

walkability. It consists of three latent variables, ζ(Connectivity; Comfort; Safety) directing towards“Walkability”, and 11 indicators for safety, 7
indicators for comfort and 2 indicators forconnectivity

Data Analysis
The aim of the study was to investigate theindicators for walkability by developing a structural
equation path model. SPSS software was used fordata computation and analysis. Data analysis was
conducted in three stages; Exploratory Factor
Analysis (EFA), Reliability test and development of
PLS Path-Modelling.
i.

RESULTS AND ANALYSIS
Exploratory Factor Analysis (EFA)

Exploratory Factor Analysis (EFA)

Before a model is constructed, factor analysis is
implied to summarize the data by assessing thestructure of variables for further analysis [36].
Theoretically, factor analysis was used to solve theproblem by combining variables that are collinear[37]. A principal component analysis (PCA) was
conducted on the 18 walkability indicators withoblique rotation (varimax). Table 3 shows theretained walkability indicators with extraction values
more than 0.6 and less than 0.6. The indicators ofless than 0.6 were deleted from the model.
Meanwhile, the Kaiser-Meyer-Olkin measureverified the sampling adequacy for the analysis,
KMO = 0.93 [38]. Based on Table 4, all KMO
values for the items were >0.7, which is well above
the limit of 0.50. Bartlett’s test of sphericity (105) =358.275, p = 0.000, indicating that the correlations
between items were sufficiently large for PCA.
Hence, the remaining variables were sufficient to beanalyzed. Cronbach’s alpha reliability test revealed
that all 8 walkability items satisfy the acceptablevalue of 0.6 (α=0.786). Thus, all 8 items wereadvanced for path model construct.

Exploratory factor analysis (EFA) was conducted
to investigate the relationship between the indicators
and walkability. EFA identifies the individual
constructs and explores the consistency of the
proposed latent factors with the actual data. The
principal component extraction (PCA) method wasused to examine the factor loading among themeasurement items for each factor. The thresholdvalue for cross-loading of the measurement items
should be more than 0.5. For rotated factor analysis,
varimax rotation was applied to determine thedegree of relationship between variables. The
numbers of components in the latent variables wereextracted based on the output values of KaiseMeyer-Olkin (KMO) measures. The components
possessing higher factor loading of Kaiser criterion
i.e., more than 0.55 were accepted.
ii.

Reliability Test

The reliability test was conducted based on
Cronbach’s alpha value. The acceptable value for
Cronbach’s alpha is 0.7. However, it is suggested toaccept the lower value (0.6) to be adapted in the
research model [35].
iii.

Reliability Assessment
Table 5 shows the reliability and validity results
applied to the constructed model. Connectivity andsafety were found to fulfill all requirements bypossessing a value of Cronbach’s Alpha higher than
0.6 which has been suggested by previous studies[39], [40] whereas, comfort obtained below than thesuggested value (0.284). Meanwhile [41] and [42]suggested >0.6 for indicator loadings and >0.6 forcomposite reliability [43]. For Average Variance
Extracted (AVE), >0.5 is the suggested thresholdvalue [44]. From Table 5, the results for connectivity
and safety confirmed the convergent validity andgood internal consistency of the measurement model.

PLS Path-modelling

The path model was constructed with a
Structural Equation Model (SEM) by using
SmartPLS 3.0 software. In this study, SEM-PLS waschosen because it can be applied for theoreticalconfirmation or theory development. It is compatible
with the aim of the study which is to identify the
relationship of connectivity, comfort, and safety
towards walkability.
Figure 2 shows the conceptual path model for

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 2Conceptual Path Model for Walkability

Table 3 Results of Extraction Communalities
Extraction Before Variables
Deleted
WALKABILITY 1.731
WALKABILITY 2.687
WALKABILITY 3.646
WALKABILITY 4.662
WALKABILITY 5.702
WALKABILITY 6.804
WALKABILITY 7.627
WALKABILITY 8.691
WALKABILITY 9.817
WALKABILITY 10.658
WALKABILITY 11.586
WALKABILITY 12.399
WALKABILITY 13.689
WALKABILITY 14.698
WALKABILITY 15.619
WALKABILITY 16.679
WALKABILITY 17.452
WALKABILITY 18.248
Extraction Method: Principal Component Analysis

Extraction After Variables
Deleted
.703
.705

.734
.602
.788
.697

.685
.967

Table 4 KMO and Bartlett’s test Results
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.770

Bartlett's Test of Sphericity

Approx. Chi-Square358.275

df

28

Sig.
.000
the standard value of SRMR=<0.08 for a good fit
model and lower than that for a better fit model [45]The Standardized Root Mean Square Residual(SRMR) measures the estimated model fit by having.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 5 Assessment results of the model

Variable/Indicator
Comfort
W14: Sidewalk width must not be less than 1.50m
width
W16: Provision of signage for a pedestrian
walkway
Connectivity
W1: Connecting pedestrian walkways either
paved or unpaved to the nearest main attraction
within 500 meters to/from the bus stop
W2: The walkway should not be obstructed byphysical objects (for ex: trees, shrubs, etc) to thenearest main attractions
SafetyW6: Provision of crosswalk at road intersections
for pedestrian to cross
W7:
Well-maintained
walkways(smoothpavement/not overgrown shrubs and trees/not
broken)
W9: Crosswalk/markings are clearly seen
W10: Walkways have smooth incline at the end of
walkways or towards road intersection which canfacilitate easier wheelchairs and strollers
movement

Cronbach's
Alpha

0.284

Indicator
loading

Composite
Reliability

Average
Variance
Extracted
(AVE)

0.798

0.736

0.582

0.893

0.806

0.846

0.582

0.726

0.759

0.898

0.897

0.753

0.800
0.706
0.871
0.742

p = 0.000), connectivity (β1 = 0.371, t = 9.595, p =0.000). The path analysis shows positive results
which depicting direct effect towards walkability.
Safety shows strong correlation due to a higher
value of the coefficient, β towards walkability
compared to connectivity and comfort. This also
shows that safety had a greater value of variance andhigh effect with regard to affecting walkability [45].
Hence, safety had a huge influence on walkability
which parallels with had been put forth by theprevious studies [47] [48]. Nevertheless, the findings
also revealed positive impacts of connectivity andcomfort towards walkability. Based on the β values,
connectivity possessed the second strongest impact
on walkability followed by comfort.

Path Analysis
As shown in Figure 3, the latent variables
namely safety, connectivity, and comfort wererelated to the latent variable; walkability.
Meanwhile, connectivity, safety, and comfort wereconnected to their indicators respectively.
Bootstrapping was performed on the model to test
the significance of the relationships between
adjacent constructs [46]. Based on figure 3, the tstatistics for all indicators were satisfying thethreshold value; (t= >1.96), [44]. All of the tstatistics are larger than 1.96 which shows that thevariables are highly significant.
Based on the result run by PLS-Algorithm,
safety shows a path coefficient value of β2=0.598 (t=11.189, p = 0.000), comfort (β3 = 0.257, t = 10.368,

725

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 3The constructed path model for walkability
safety element, walkability criteria in an area can befurther improved. The concept of sustainability intransportation system demands more than just social
or environmental supports but also an effective
engagement in policy. These indicators could be themain elements in encouraging the acceptablemobility paradigm by promoting walkability andindirectly to reduce the reliance on private vehicles.

CONCLUSIONS
Based on the path analysis, it is found thatsafety (β2=0.598, t= 11.189, p = 0.000), connectivity(β1 = 0.371, t = 9.595, p = 0.000) and comfort (β3 =0.257, t = 10.368, p = 0.000), possessed positive
impacts towards walkability which safety has thestrongest correlation depicting that safety should behighly concerned to encourage walkability.
Exploratory factor analysis revealed the indicatorsthat are significant to boost safety which are;••••ACKNOWLEDGMENTS
This study was funded by the Transdisciplinary
Research Grant Scheme (TRGS) from the MinistryofHigher
Education,
MOHE(203/PAWAM/67610002)

Provision of crosswalk at road intersections for apedestrian to cross.
Well-maintained
walkways(smoothpavement/not overgrown shrubs and trees/not
broken).
Crosswalk/markings are clearly seen
Walkways have smooth incline at the end of
walkways or towards road intersection facilitate
easier wheelchairs and strollers movement.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

APPLICATION OF CONDITIONAL CULTURE ALGORITHM AND
SIMULATION FOR OPTIMAL RESERVOIR RULE CURVESPROJECTS
Anujit Phumiphan1 and Anongrit Kangrang2
Faculty of Engineering, Rajabhat Maha Sarakham University, Maha Sarakham, Thailand, 44000
2
Faculty of Engineering, Mahasarakham University, Kantarawichai, Mahasarakham, Thailand 44150
1

ABSTRACTThe uncertainties of rapid population growth have directly impacted the water resource management. In
reservoir operation, rule curves are used to determine water release in response to water demand over long-term
operation. This study applied the conditional cultural algorithm (CCA) technique to connect with the reservoir
simulation model in order to search optimal reservoir rule curves for Huai Luang reservoir located in Udon Thani
province in the northeast of Thailand. Their four hundred samples of generated inflow data of the reservoir wereused to evaluate the performance of the proposed technique, and the results were compared with those of genetic
algorithm technique (GAs) and current reservoir usage. The results found that the new rule curve patterns producedby the CCA were similar as compared with the rule curves provided by genetic algorithm technique. Moreover,the patterns were different from the existing pattern. The situations of water shortage and flood when using the
new rule curves with generated inflow were lower than those of using the existing rule curves. Nevertheless, thesesituations were close to the situations of using the rule curves of genetic algorithms technique. In conclusion, theproposed model could enhance the performance of the Huai Luang Reservoirs, and it could be applied easily toother reservoirs to modify the objective functions and searching constraints.
Keywords: Water resource management, Reservoir rule curves, Simulation model, Cultural algorithm, Genetic
algorithm.

perform. Later, dynamic programming (DP) wasapplied to solve non-linear problems in water
resource areas including rule curves search. The
genetic algorithm (GA) was applied to search rulecurves of reservoir subsequently, it has been inseveral studies [3][4]. The differential evolution (DE)is another search technique that was developed by
Storn and Price [5][6]. It uses a simulation of natural
evolution, the same as the GA. The DE was applied
to search optimal rule curves in several studies. Then,a simulated annealing algorithm (SA) was applied tosolve the optimization problem [7][8]. The SA has
been applied to connect with simulation for searching
the optimal reservoir rule curves [8]. It revealed that
the SA could be used to find the optimal rule curves
effectively.
Recently, a genetic algorithm (GA) is ametaheuristic inspired by the process of natural
selection that belongs to the larger class ofevolutionary algorithms (EA). Genetic algorithms arecommonly used to generate high-quality solutions to
optimization and search problems by relying on bioinspired operators such as mutation, crossover andselection. John Holland introduced genetic
algorithms in 1960 based on the concept of Darwin’s
theory of evolution. GAs has been widely applied invarious problems [9]. Lately, a conditional genetic
algorithm technique was applied to search the optimal
rule curves of the Huai Luang reservoir. The results

INTRODUCTION
Nowadays, water resource problems such as floodand drought situations are increasing that concern
with rapid population growth and economic
expansion. Water resource management consists ofdemand management site and supply managementsite. Effective reservoir operation is achieved using
suitable rule curves to control the release of water
following the release criteria. A reservoir operationthat uses rule curves to consider release water
responds to water demands in long-term operation.
Generally, reservoir operation functions with awater release budget and amount of storage water
monthly. The stored water in reservoir is released
under certain conditions that are defined by water
demand criteria and reservoir rule curves. The rulecurves have been improved to provide the bestsolution for long term operation of reservoir.
Typically, reservoir operating system has been large
and complex especially area having both drought andflood situations [1]A searching optimal rule curve is non-linear
optimization problem. The optimization technique
was applied to search the optimal rule curves that
performed with a reservoir simulation model [2]. The
rule curves provided by this method are notguaranteed to yield the optimal curves because ofhuman adjustment in the trial and error process during
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SEE - Bangkok, Thailand, Nov.11-13, 2019

showed that CGAs technique can be use find rulecurves. Moreover, the situations of flood and drought
when operated by rule curves of both techniques wereclosed together. Later, there are many alternative
tools to solve complex computational problems. The
cultural algorithm is a computational model of social
evolution based upon a general model of the cultural
evolution process. The key idea behind culturalalgorithm is to acquire problem-solving knowledge(beliefs) from the evolving population and in return
make use of that knowledge to guide the searchingprocess [10][11]. Cultural Algorithms have beensuccessfully applied in a number of diverse
application areas [12]. In the process of doing this,five general types of knowledge have been gradually
added to the cultural space that represent genericknowledge found in cultural systems. The knowledge
sources include normative knowledge, spatial
knowledge (topographic), temporal (historic),
domain knowledge, and exemplar knowledge.
This study proposed Conditional Cultural
Algorithm (CCA) to connect with simulation model
for searching the optimal reservoir rule curves. A
minimum function for searching procedure. The
proposed model has applied to determine the optimal
rule curves of the Huai Luang Reservoir in the
Northeast region of Thailand. Comparisons of the
CCA and the CGA as well as the existing simulation
model were shown to demonstrate the effectivenessof the proposed CCA model.

the next generation of the population through the
influence() function. This supports the idea of dual
inheritance in that the population and the belief space
are updated each time step based upon feedback fromeach other. The CA repeats this process for eachgeneration until the pre-specified termination
condition is met. In this way, the population
component and the belief space component interact
with, and support each other in a manner analogous
to the evolution of human culture. Fig. 1 describes
such a framework of cultural algorithm is given as
follows:

Fig. 1 Framework of the cultural algorithm
The procedure of development model consists ofreservoir simulation model and conditional culturalalgorithm that combined together for searching the
optimal rule curves. The detail of each model will be
described as following.

METHODOLOGY
The culture algorithm was introduced by
Reynolds as a vehicle for modeling social evolution
and learning in agent-based societies [13]. A culturalalgorithm consists of an evolutionary population of
agents whose experiences are integrated into a belief
space consisting of various forms of symbolic
knowledge. The cultural algorithm framework easily
lends itself to supporting various types of learning
activities including ensemble learning. The various
knowledge sources in the belief space can be viewed
as an ensemble of classifiers with the acceptancefunction collecting sample data using techniques suchas bagging and boosting from the agent population.
The influence function reflects the influence of theensemble on the agent actions.
As a dual inheritance system, cultural algorithm
has two basic components: The population space andthe belief space. In each generation, individuals in the
population space are first evaluated with aperformance function obj(). An acceptance function
accept() is then used to determine which individuals
will be allowed to update the belief space.
experiences of those chosen individuals are thenadded to the contents of the belief space via function
update(). Next, knowledge from the belief space isallowed to influence the selection of individuals forReservoir operation model
Generally, reservoir system comprises available
water that flows into the reservoir with a single ormultipurpose downstream covering watershed area.
The reservoirs are usually operated under water usage
criteria and reservoir rule curves with monthly data
for long term perform. The reservoir rule curves havebeen found to offer the most equitable solution to all
operational problems. A modified reservoir operation
model was constructed on the concept of waterbalance, and it can be used to simulate reservoir
operation effectively as well as the Huai Luang
Reservoir. The reservoir operation policies are basedon the monthly rule curves of individual reservoirs
and the principles of water balance equation underreservoir simulation model. The reservoir system isoperated along the standard operating policy as
expressed equation (1):730

SEE - Bangkok, Thailand, Nov.11-13, 2019 D  W ,  y , for W ,  y  D
 D , for x  W  y  D


 ,


R ,   
D

W

x
,
for
x

D
 W ,  x


,






0,
otherwise.
(1)Which R , is the release discharges from thereservoir during year υ and period τ (τ = 1 to 12,
representing January to December); D is the waterrequirement of month τ; x is lower rule curve of
curve of month τ; y is upper rule curve of month τ;and W , is the available water calculated by simple

Fig. 2. Conditional cultural algorithm with reservoir
simulation for searching rule curves.

water balance as described in equation (2):W , 1  S ,  Q ,  R ,  E  DS

Conditional cultural algorithm connected withreservoir simulation(2)

Where S , is the stored water at the end ofFirstly, the conditional cultural algorithm wascreated with the reservoir simulation model. The
procedure starts from creating an initial population ofrule curves, boundary search, probable crossover andmutation, objective function and stopping criteria.
Then the population initial rule curves were sent toreservoir simulation model for operating reservoir byconsidering input data and physical information of thereservoir. The monthly release was calculated using
initial rule curves for all moths along the inflow
period. Then all monthly releases were used to
calculate objective function and to evaluate the set of
initial rule curves for accepting of first generation.
Next, the new accepted rule curves (the selected
populations for the first generation after cross overand mutation processes) were used to replace theinitial population. This procedure was repeated until
the new accepted rule curves were appropriate and thesearch was stopped [14]. The integrating conditional
cultural algorithm and reservoir simulation model forsearching optimal rule curves is described in Fig. 2.
Three objective functions were considered. Firstly,
the minimum average water shortage per year (H)was used as the objective function of the searchingprocedure subject to the constraints on the simulation
model as in the following:

month τ; Q , is monthly reservoir inflow; E isaverage value of evaporation loss; and DS is theminimum reservoir storage capacity (the capacity ofdead storage).
In the Equation (1), if available water is in the rangof the upper and lower rule level, then demands are
satisfied in full. If available water over the top of theupper rules level, then the water is spilled from thereservoir in downstream river in order to maintainwater level at the upper rule level. If available wateris under the lower rules level, a reduction of supply isrequired. The policy usually reserves the available
water ( W , )for reducing the risk of water shortage inthe future, when 0  W ,  x  D under long term
operation.
After operation for all months along theconsidered inflow period, all monthly releases ofwater from the reservoir (R for all months) were used
to calculate the objective function in the searchingprocedure. Results of each objective function wererecorded and used in the CCA model until met thestop criteria and the optimal rule curves wereobtained as described in Fig.2. The details of eachobjective function will be described in the next
section.

1 n


Sh
v
n
v

1



Fitness = Min H (Xi) = 

(3)

12

if R  D ; Then Shv    D  R 

(4)

 1

Else Shv  0
where n is the total number of considered years,
Sh is the water shortage during year  (year that
releases does not meet 100% of target demand) and iis the iteration number.

731

SEE - Bangkok, Thailand, Nov.11-13, 2019Illustrative application of proposed model

Huai Luang River
Huai Luang
Reservoir

In this study the Huai Luang reservoir in Udon
Thani province, is located in the Mae Klong Basinwith an upstream watershed area of 4,122 km2 (seeFig. 3). The annual rainfall over the watershed varies
from 1,145–2,174 mm which results in an annual
average of 1,564 mm and the mean annual
temperature is 26.3 °C. The normal storage capacity
and average annual inflow are 136 MCM and 165.60
MCM/year, respectively.

Irrigation Project
50,431 ha
Huai Luang River

Water Supply andEnvironmental
Conservation

Reservoir
Flow Direction

Mae Klong River

Fig. 4. Schematic diagram of the Huai Luang basin.
The study used CCA in connection with areservoir operation model to find optimal rule curves
through the MATLAB toolbox. The optimal rulecurve can then be applied to an actual scenario
depending on whether the rule curve can be used tocover every case or event that might occur. Thus, theHEC-4 model was used to create the synthetic inflow
data into the monthly inflows as a synthetic data setof 500 events. Then, input synthetic inflow data wereused to assess the efficiency of the new rule curves
and compare them with the existing rule curves andalso between the CCA model, CGA model and theexisting SM model under the same conditions(objective function and constraints). Moreover, the
new rule curves ware assessed in various othersituations, i.e., irrigation area increases to judge theimpact of how these things will affect future
operations.

Fig. 3. Location of Huai Luang watershed

RESULTS AND DISCUSSION

The schematic diagrams of above reservoirs arepresented in Fig. 4. They indicate that the water
demands from reservoirs are electricity generation,
irrigation, flood control, industrial demand, domestic
water supply and environmental conservation.

The historic data of inflow, evaporation, waterrequirement and monthly rainfall were imported forprocessing in the CCA model; the optimal rule curves
were obtained. These obtained rule curves are plottedin order to compare them with the rule curves of CGA
and existing rule curves of the SM approach as shownin Fig. 5 The results show that the patterns of rulecurves obtained from the proposed CCA, The CGA
and the SM. Are similar. The obtained rule curves
also indicated that the eater storage levels of the CCA
lower rule curves are lower than the existing rulecurves during the dry season (January - May) in orderto release more water to reduce water scarcity. In the
beginning of rainy season (May - August) the CCA
upper curves are lower than their curves of SM inorder to add a volume for flood protection. Whereas
732

SEE - Bangkok, Thailand, Nov.11-13, 2019

during August – November, their upper curves arehigher than the curves of SM because of decreasing
spill water in order to meet a full capacity at the endof rainy season. This will help alleviate water
shortages in the next year. These patterns of theobtained curves are similar to the pattern of the otherreservoirs in Thailand on the other studies because of
seasonal effect. However, the different points of eachreservoir are on lower rule curves during dry season(December - May) and on the upper rule curves
during wet season (Jun - November).

(new and existing system)
The proposed CCA model is another search
optima technique, so the results are near optimalitythat closed to the results of the results of the othersearch techniques based on the same condition.
However, the efficiency of each technique wascarried out on many studies.
The performance of the proposed model was
evaluated with monthly synthetic inflow data. These
results of the Huai Luang Reservoir are shown in
Table 1. The results show that, the average frequencyof water shortage was 0.479 per year, the averagemagnitude of water shortage was 25.288 million
cubic meters (MCM) per year and the maximum
magnitude of water shortage was 77.549 MCM/year.
These are smaller than the results of using rule curvesof CGA. The average frequency of excess water
release was 0.835 times per year, the averagemagnitude of excess water release was 30.384
MCM/year and the maximum magnitude of excesswater release was 44.268 MCM/year. These are lessthan the results of using both existing curves but nearby the CGA’s curves.

Fig. 5. Optimal rule curves of Huai Luang reservoir.
Table 1 Situations of water shortage and excess release of the system
Magnitude (MCM/year)
Frequency
Situations
Rule curves(times/year)
Average
Maximum
0.955
32.57290.213

Existing-SM
0.171
7.223
26.262

0.622
28.21882.821
Water

CGA
shortage
0.153
7.105
25.425
0.479
25.28877.549

CCA
0.167
3.774
3.681

0.876
28.52385.635

Existing-SM
0.107
19.57134.955
0.547
12.47550.840
Excess

CGA
water
0.118
8.249
40.273
0.835
30.38444.268CCA
0.052
119.719
26.248Duration (year)
Average
Maximum
12.24218.251
7.892
3.681
1.452
2.788
0.624
1.715
19.212
14.139
0.000
0.000
5.376
7.019
1.402
2.961
2.537
5.161
0.846
2.160
7.643
6.018
5.713
3.454

well as the existing simulation. The proposed CCA
model is an effective method for application to findoptimal reservoir rule curves.

CONCLUSIONSThis study proposed alternative algorithm forsearching optimal reservoir rule curves. The
conditional shuffled frog leaping (CCA) and reservoir
simulation model was applied to search the optimal
rule curves of the Huai Luang Reservoir. The results
found that the new obtained rule curves are moresuitable for reservoir operation than the existing rulecurves. The frequency and magnitude of water
shortage and excess water release for using new
obtained rule curves are lower than their existing rulecurves. When comparing the new obtained rulecurves with the rule curves of the CGA method as

ACKNOWLEDGMENTS
This research was financially supported by
Rajabhat Maha Sarakham University Grant 2019; theauthors would like to acknowledge Rajabhat Maha
Sarakham University.
REFERENCES[1] S. K. Jain, M. K. Goel, and P. K. Agarwal,
733

SEE - Bangkok, Thailand, Nov.11-13, 2019

“Reservoir operation study of sabamati system,
India,” Journal of Water Resources Planning andManagement, vol. 124, no. 1, pp. 31–38, 1998.
[2] M. Azizipour, V. Ghalenoei, M. H. Afshar, and S.
S. Solis, “Optimal operation of hydropower
reservoir systems using weed optimization
algorithm, Water Resources Management, vol. 30,
no. 11, pp. 3995–4009, 2016.
[3] C. Chaleeraktrakoon, and A. Kangrang,“Dynamic programming with the principle ofprogressive optimality for searching rule curves,”
Canadian Journal of Civil Engineering, vol. 34,
pp. 170-176, 2007.
[4] F. J. Chang, L. Chen, and L. C. Chang,“Optimizing the reservoir operating rule curves
by genetic algorithms,” Hydrological Processes,
vol. 19, pp. 2277-2289, 2005.
[5] A. Kangrang, S. Compliew, and R. Hormwichian,“Optimal reservoir rule curves using simulated
annealing”, Proceedings of the Institution of Civil
Engineers - Water Management, vol. 164, no.
WM1, pp. 27–34, 2011.
[6] R. Hormwichian, A. Kangrang, A. Lamom, C,
Chaleeraktrakoon, and P. Patamatamkul,“Coupled-operations model and a conditional
differential evolution algorithm for improving
reservoir management,” International Journal of
Physical Sciences, vol. 7, no. 42, pp. 5701-5710,
2012.
[7] A. Kangrang, and R. Homwichian, “Optimalreservoir rule curves using conditional shuffled
frog leaping algorithm and simulation”,
International Journal of Earth Sciences andEngineering, vol. 6, no. 6, pp. 1392-1399, 2013.
[8] A. Kangrang, W. Pakoktom, W. Nualnukul, and
C. Chaleeraktrakoon, “Adaptive Reservoir Rule

Curves by Optimization and Simulation”,
Proceedings of the Institution of Civil Engineers Water Management, vol. 170, no. WM5, pp. 219230, 2017.
[9] Mitchell, Melanie (1996). An Introduction to
Genetic Algorithms. Cambridge, MA: MIT Press.
ISBN 9780585030944.
[10] Reynolds RG (1994) An introduction to culturalalgorithms. In: Proceedings of the 3th annual
conference on evolution programming, Sebalk,A.V. Fogel, World Scientific, River Edge, NJ,
pp 131–136.
[11] Jin X, Reynolds RG (1999) Using knowledge
based evolutionary computation to solve
nonlinear constraint optimization problems: acultural algorithm approach. In: Proceedings ofthe 1999 Congress on Evolutionary
Computation, Washington DC, IEEE Service
Center, pp 1672–1678[12] Reynolds, G. R. 1979. An Adaptive Computer
Model of the Evolution of Agriculture for
Hunter-Gatherers in the Valley of Oaxaca
Mexico. Ph.D. Dissertation, Department ofComputer Science, University of Michigan.
[13] Reynolds, G. R. 1994. An Introduction to
Cultural Algorithms. In Proceedings of the 3rd
AnnualConferenceon
Evolutionary
Programming, 131-139: World Scientific
Publishing.
[14] A. Kangrang, and C. Lokham, “Optimalreservoir rule curves considering conditional ant
colony optimization with simulation model”,
Journal of Applied Sciences, vol. 13, no. 1, pp.
154-160, 2013.

734

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

A STUDY OF FLOOD FORECASTING AND MAPPING FOR THE
ATTANAGALU OYA
W.C.P. Wickramarachchi1, N.K. Gunasekara 2, W.C.D.K. Fernando3 and S.S. Wickramasuriya4
1,2,3,4
Faculty of Engineering, General Sir John Kotelawala Defence University,Sri Lanka
ABSTRACTThis research focuses on developing a hydrological model and a hydraulic model using HEC-HMS and HECRAS respectively to enable flood projection in the basin around the only available downstream gauging station at
Dunamale. Dunamale is a defective gauging station that gives erroneous readings at high flows. Despite, reliableflood inundation maps were produced and were validated. This study intends to forecast flood for a catchmentwith minimal data as in many developing countries. Soil Conservation Services Curve Number Method was usedas the loss method while the Snyder unit hydrograph was employed as the transform method. Monthly minimum
ﬂows were considered as the base ﬂow of the corresponding months from the Dunamale gauging station. 2011
and 2010 daily discharge data were used to calibrate and validate the hydrological model. Nash Sutcliffe
coefficients (NSC) of 0.836 and 0.825 were found for calibration and validation respectively. The computed
water surface elevation was compared with actual flood levels to calibrate the model. Thus, the Manning’s
coefficient was determined. The identified rainfall patterns for 25, 50, 100 year return periods were used in therainfall-runoff model to obtain the corresponding flow hydrographs. Using the hydraulic model, it was observedin the maps that a low lying area of 9.5 km2 downstream of Dunamale will be inundated. The resulting floodinundation maps can be used to develop a proper mitigation plan to assist the affected people and direct them tosafe locations. Thus, the loss of lives and damage to property can be minimized immensely.
Keywords: Dunamale, Flood, Inundation Maps, Hydrological, Modelling
INTRODUCTION
Sri Lanka being a small island in the Indian
Ocean in the path of two monsoons in frequently
affected by tropical hazards such as floods. During
the period of 1974-2004, over three million people
were affected due to flood disasters which was 48%
when compared with other destructive natural
disasters [1]. Adverse consequences of flood ranges
from direct damages such as loss of lives to indirect
damages such as spread of diseases. It was recordedthat the flood occurred in 2014 [2] was the most
severe and the most destructive hydrological eventthat occurred after the devastating flood in 1989 [3].
The floods recurred in 2016 [4], 2017 [5] and 2018as well and severely affected the people settled in
the vicinity of the Attanagalu oya. Table 1 illustrates
the severity of the recent floods. The occurrence offloods is more frequent in the Attanagalu Oyacatchment and hence, rapid and viable solutions are
essential to mitigate flood disasters.
Table 1 The severity of floods
Flood occurred year
People affected
1989
Over 300000
2014
Over 107000
2016
Over 425000
2017
Over 500000
STUDY AREA
Attanagalu Oya is situated in the Western

Province between two major rivers, Kelani Riverand Maha Oya with an extent of 727 km2 [6]. 64%
of its basin area are in the lower valley with a meansea level lower than 30 meters. This basin
experiences a mean annual rainfall of 2000 mm2500 mm. Rainfall received by the basin is welldistributed and frequently experienced from April to
December [7].

Dunamale Gauging Station
Fig. 1

Study Area

METHODOLOGY
Daily rainfall data from the Pasyala gauging
station was obtained for ten years (2005-2015), daily
discharge data and flood level heights were obtained
from the Dunamale gauging station for the same
years. Land use data was obtained from the Urban
Development Authority.
A digital elevation model (DEM) of 2 m
accuracy was used to delineate the watershed andwas further developed to perform digital terrain
735

SEE - Bangkok, Thailand, Nov.11-13, 2019analysis. The generated stream network was overlaid
on Google earth pro and was validated.
Figure 2 illustrates the watershed delineated at
Dunamale gauge. The area of the watershed is 148
km2.

Fig. 2Delineated Watershed (scale 1:600,000)

These results were subsequently used in thehydrological and hydraulic models. HEC-HMS is acommonly used reliable hydrological modelling
software which provide acceptable simulations offlood events when compared with other modelling
tools such as WBNM [8]. In the HEC-HMS model,
the water budget equation is used in order tocompute the precipitation-runoff model.
(1)
Where:𝞓S - Storage, P - Precipitation, R - rainfall excess or
runoff, B – subsurface flow, I – Infiltration, E –Evaporation, T – Transpiration [1]The precipitation that do not get subjected toponding or infiltration, will flow overland to a
stream channel. Hence, the resultant stream flow at
Dunamale gauging station due to runoff, interflow,
baseflow and the precipitation is considered as thetotal watershed outflow for this study.
The study was conducted by using two loss
methods, namely Soil Conservation Service Unit
Hydrograph method (SCS-UH) and Deficit andConstant loss method. Later a comparison of the two
was carried out. The SCS curve number method has
been developed using the following equations by
estimating excess rainfall as a function of
cumulative precipitation, soil cover, land use, andantecedent moisture.
Pe =(P - Ia)

2(P - Ia) + S

(2)

(3)

(4)
Pe = Accumulated precipitation excess at time t
P = Accumulated Rainfall depth at time t (mm)Ia = Initial Abstractions (initial loss)

S = potential maximum retention
The Deficit and Constant Loss method is acontinuous simulation method which uses a single
soil layer to account for continuous changes inmoisture content. This method consists of threeparameters, namely, Initial Deficit, Maximum
Deficit and Constant Rate. Initial condition isreferred to as the amount of water initially required
to fill the soil layer to the maximum storage. The
maximum deficit is the maximum amount of water
the soil layer can hold [9]. These three parameters
were obtained through trial and error as they requirea great amount of data which is unavailable for the
Attanagalu Oya catchment.
The direct-runoff model of HEC-HMS facilitates
seven transformation methods including Snyder Unit
Hydrograph method. The Snyder Unit Hydrographmethod simulates flows more reliably than othertransformation methods for Attanagalu Oya basin[10]. It requires only two parameters and they are
the standard lag (t p) and the peaking coefficient (𝐶𝑝).
The eqaution proposed for standard lag is
as follows;(5)
Ct= basin coefficient, L = length of the mainstream from the outlet to the divide, Lc = length
along the main stream from the outlet to the nearest
point to the centroid, C = a conversion constant(0.75) [9]. The basin coefficient (Ct) has beencalibrated to be 3.75 with a Mean Ratio of Absolute
Error (MRAE) of 0.2 for the Attanagalu Oya basin.
This value has been directly used to calculate thestandard lag [11]. The 𝐶𝑝 for the Attanagalu Oyabasin was initially estimated as 0.38 as this value
was recommended in [11] and was optimized to get
the best goodness-of-fit for the simulated andmeasured hydrographs.
Baseflow of a tropical catchment with year round
precipitation is very significant as the groundwaterflow contribution is very high. The minimum
constant discharge of each month was assumed to be
the monthly baseflow [10].
Through a sensitivity analysis it was determinedthat evaporation has no effect on the results from themodel. Daily precipitation data for a duration ofseven months were input to calibrate and validate
the model. The parameters were estimated andoptimized using the Nelder - Mead search algorithm.
The goodness of fit was assessed using the NSC as
the objective function. The hydraulic model wasdeveloped to analyze the extent of inundation andplot the water surface elevations for the selected
return period storm events. As it was a river flood
analysis, two dimensional unsteady flow modelling
was carried out [12]. MIKE11 is another widelyused hydraulic. However, HEC-RAS has theadvantage over MIKE11 as it is able to generateriver flood flow velocity map which is not available
in MIKE11. The flood flow velocity is one of the736

SEE - Bangkok, Thailand, Nov.11-13, 2019

most important factors that is used, flood mitigation,
flood management, classification and evaluation ofriver flood risk [13].
As the terrain data have been collected using
Light Detection and Ranging (LiDAR), certain
stream channels may not have bathymetric data. The
conventional forms of LiDAR do not penetratewater. Therefore, it is necessary to incorporate crosssection data into the terrain for a single
comprehensive terrain model that includes
bathymetry when carrying out two dimensionalmodelling. Manning’s coefficient was the only
parameter that was varied to calibrate and validate
the hydraulic model. The Manning’s n value thatcomputes the actual water surface elevation wasdetermined. It is highly dependent on a number offactors such as surface roughness, vegetation,
channel irregularities, channel alignment, scour anddeposition, obstructions, size and shape of thechannel, stage and discharge [14].
The flow hydrograph was given as the upstream
boundary condition and the normal depth wasconsidered as the downstream boundary condition.
Observed discharge of Dunamale guage was input
for the upstream flow hydrograph and the bed slope
was considered as the normal depth at thedownstream.
The Attanagalu Oya experiences no flow
conditions twice a year. Therefore, the simulation
was started when the river begins to have any flowin order to consider the initial condition as zero.
A flood frequency analysis was done todetermine the storm hydrographs for 25, 50, 100
year return periods using IDF curves developed forColombo. Obtained rainfall patterns computed were
input as precipitation to the developed rainfallrunoff model and the runoff was calculated. The
obtained discharge was input at the inlet ofDunamale in order to compute the flood simulationand develop the inundation maps.

January to 31st July were used to calibrate the modeland obtain the optimized parameters.
The Figure 3 shows the goodness-of-fit of thesimulated and the observed hydrographs which was
satisfactory with a NSC of 0.836. Therefore, theparameters obtained from the simulation were
accepted and are presented in the Table 2. The SCS
CN method is applied for very large watershed areas
without considering the substantial transmission
losses, which results in overestimation of the runoff[10]. This problem is overcome as the SCS CN loss
method is applied only to a sub-catchment ofAttanaglau Oya and also transmission losses were
accurately calculated and optimized as explained in
the methodology. Hence, successful results wereobtained for the hydrological model developed using
the SCS CN loss method.
However, it was noted that the optimized Curve
Number is significantly low. This could be justified
by the fault of the gauging station location. It wasobserved that the Dunamale gauging station is
bypassed by a naturally developed bypass channel
during periods of high flow. Hence, the observed
discharge data are undervalued as it includes theflow measurement of the main channel only. This
causes the high flows to be read lower than actual
while the other flows are gauged accurately. The
Figure 4 shows the Dunamale gauging station andthe bypass channel.

RESULTS AND DISCUSSION

Table 2 Parameters used in the hydrological modelSCS CN loss method
Parameter
Optimized values
Loss method
Curve number
6.5
Impervious Percentage (%)
6
Transform method
Standard lag (hours)
20
Peaking coefficient
0.35

A hydrological model was developed using the
SCS Curve Number loss method. The Land use dataobtained from the Urban Development Authority
valid for the years 2010- 2015 were analyzed and theimpervious percentage was calculated as 5.8% witha majority land use cover of rubber and garden. The
spatial features of the watershed and the longest
path, watershed area, length along the main stream
from the outlet to a point nearest the watershed
centroid was found using a GIS tools. Hence, thestandard lag was calculated as 16.22 hrs. It wasobserved that the runoff simulation model did notshow any sensitivity towards evapotranspiration.
Precipitation data of the year 2011, from 01st

Fig. 3

737

Runoff Simulation for the year 2011 using
SCS CN Loss Method for calibration

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 5Model validation for 2010 using SCS CN
Loss Method

Table 3 Hydrological model parameters using
Deficit and Constant method
Parameters
Loss Method
Initial Deficit (mm)Maximum Deficit (mm)Constant Rate (mm/hr)
Impervious percentage
Transform Method
Standard lag (hours)
Peaking coefficientFig. 4 The Dunamale Guaging Station and thebypass channel (Scale 1:40000)
Curve number 100 represents 100 percent
imperviousness of the catchment [1]. Therefore, CN
6.5 suggests high perviousness. Since the observed
discharge is under measured, the developedhydrological model attempts to decrease thesimulated results to match the defected observed
discharge readings by adjusting perviousness to ahigher value. Further, the literature reveals that theestimate of stream flows with CN estimations basedonstandard tables were of lesser quality whencompared with those with the use of average CN
value from observed event calibrations [14]. It wasalso noted that different curve numbers were
optimized for the same catchment by differenthydrological models. Red Yellow was determined as
the major soil type appearing in the Attanagalu Oyabasin. Therefore, based on the characteristics of thebasin and the soil type 45 was selected for the curve
number for the Attanagalu Oya [15]. Another
Literature suggests an average CN value of 70.11
was calibrated with a MRAE of 0.4 to model peakflow magnitudes reasonably for Attanagalu Oya[14]. The calibrated hydrological model was
validated using rainfall data from 01st January 2010
to 31st July 2010. The modelled runoff matched themeasured runoff with a NSC of 0.825. The
goodness-of-fit of the observed and the simulated
graphs is shown in the Fig 5.
Similarly, the model was run changing the loss
method to Deficit and Constant loss method. The
loss parameters were estimated and optimized. The
simulation was run by keeping the transformparameters and the base flow values same as in the
SCS CN method. The simulation obtained a NSC of
0.813. It was observed that the constant rate and theimpervious percentage

Optimized Values
0.5
1.2
1.3
6
20
0.23

Table 3 Hydrological model parameters using
Deficit and Constant method were the only loss
parameters that contributed to the goodness-of-fit of
the two graphs and the initial deficit and the
maximum deficit showed no sensitivity to improve
the NSC.
were the only loss parameters that contributed to thegoodness-of-fit of the two graphs and the initial
deficit and the maximum deficit showed nosensitivity to improve the NSC.
The model was validated for the year 2010 from
1st January to 31st July. The NSC was 0.660. Even
though the coefficient is above the threshold of theminimum acceptable value, some peaks are highly
overvalued and some are highly undervalued.
Moreover, due to the consistency of the highgoodness-of-fit of the SCS method, the hydrologicalmodel developed using the SCS CN loss method canbe justified as more accurate.
The hydraulic model was calibrated in terms of
the Manning’s coefficient. Dunamale discharge data
was input to the model at the upstream inlet and theinundation heights produced by the model werecompared also at the same upstream inlet location as
observed flood heights were not available in thedownstream. The best Manning’s value for themodel that enabled to obtain the observed heights
Fig. 6 Simulation of the 30/10/2009 Flood event
Event 140

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 4 Analysis of the Error Percentage of the
Simulation for the Year 2009 (Event 1) andin 2008 (Events 2-5
Error percentage of Error in thethe simulated and dateofobserved
flood occurrence inheights
days
Event 1-2.37%
01 dayEvent 20.93%
02 days
Event 3
−5.47%
01 dayEvent 4
−1.57%
01 DayEvent 5−2.99%-02 Daysfrom the flood simulation was identified throughcalibration. The simulation was run for the entire
year of 2009 as shown in the Figure 6 and thecalibrated Manning’s coefficient obtained was 0.02.
The published Manning coefficients for
mountain rivers consisting gravel, stones and naturalvegetation were ranging from 0.025- 0.035 [16]. The
calibrated Manning’s coefficient of 0.02 very close
although it is not within the range. Manning’s
coefficients are difficult to be determined forcatchments with significant spatial variations andtherefore a coefficient with least overall
discrepancies
betweensimulations
andmeasurements should be selected [1].
The model was validated by running a simulation
for the year 2008 and four flood events wereobserved for the year. The simulation for the year
2008 were almost the same as measured data and theresults are as depicted in the Figure 7.
Event 2

Event 3

Event 4model. The parameters which were calibrated andvalidated using the SCS curve number method wereused. The constant monthly base flow method wasused in the Basin Model Manager and the averagemonthly base flow from 2009-2016 was input for all
return periods. The values obtained from thehydrological model for the three return periods areshown in the Table 5.
Table 5 Analysis of the Results from theHydrological Model
Return Period

25-yr

50-yr

100-yrPeak Discharge( m3/s)Direct Runoff Volume(106m3)
Flood heights in meansea levelat thegauging station (m)

32.5

39.5

50

8.82

10.70

13.91

20.7

20.9

21.0

The inundation maps which were laid on Google
Satellite images shows that the flood is mostly
contained in the low lying areas on either sides ofthe stream. The inundation area was obtained as 9.5
km2 and by laying the inundation layer on Google
Earth the land use types that are inundated can be
identified. The inundation map obtained from thehydraulic maps for the 100 year return period isshown in Figure 8.

Event 5

Fig 8

Inundation Map of the 100-Yr Return
Period Flood (scale 1: 70000)

CONCLUSION
Fig. 7 Simulation of the Four Floods in 2008
It was observed that the error 2 was the only
error with a positive error and these errors may haveresulted due to temporal changes of the stream bed
profile. The Manning’s coefficient of 0.02 wasaccepted after the calibration done for the single
event of 2009 and the validation done for the four
flood events of 2008.
However, it was notable that the simulated
heights were lower than the observed heights andthis could be due to several reasons such as the errorof the location of the Dunamale gauging station anderrors of the digital elevation model.
The runoff simulations for each return period
was obtained by using the developed hydrological

Dunamale gauging station from where thedischarge data were obtained is a station which gives
erroneous discharge rates during high peaks due tothe bypass channel. This is an ungagged watershed
where many essential data like flood heights in thedownstream were not available. However, very
reliable results were obtained from the models withsatisfactory NSC values.
HEC-HMS model was reliably used to simulate
flood flows of Attanagalu Oya using SCS CN loss
method and Synder UH method as the transform
method. The basic parameters obtained from thecalibration were 6.5 as the curve number, 20 hours
as the lag time, 0.35 as the peaking coefficient, basincoefficient used to calculate the standard lag was
3.75 and this value was obtained from literature. By
739

SEE - Bangkok, Thailand, Nov.11-13, 2019using these parameters, a goodness-of-fit of 0.836
NSC was obtained. The manning’s coefficient forthe basin was calibrated to be 0.02.
The results were subsequently used to map theinundation due to 25-yr, 50-yr, 100-yr return period
storms and it was observed in the maps that a low
lying area of 9.5 km2 will be inundated. These maps
will be contributory for mitigation of future floods
and also such maps can be further analysed to devise
a proper risk assessment and a risk management plan
to support the affected individuals.
As a future direction, the error in the Dunamale
gauging station due to the diversion of the channel
can be addressed when modelling to obtain moreaccurate results. Further, a study for a suitable flood
mitigation structure for the modelled area can besuggested as another future direction. The flood
extents and the intensities can be obtained from thisstudy and a suitable structure can be proposed tominimize the flood damages.
ACKNOWLEDGEMENT
The authors wish to extend their gratitude toEng. P.A.A.P.K Pannala, Deputy Project Director of
the Climate Resilience Improvement Project (CRIP).
The support extended by the Department of
Irrigation and the Department of Meteorology forproviding the required data is gratefully
acknowledged.
REFERENCES[1] "Hazard Profile of Sri Lanka," Ministry ofDisaster Management, 21 May 2019. [Online].
Available:
http://www.disastermin.gov.lk/web/index.php?option=com_content&view=article&id=57:hazar
d-profile-of-srilanka&catid=73:reports&Itemid=70&lang=en.
[Accessed 13 June 2019].
[2] M. Johnney, "The International Federation of
Red Cross," 4 June 2014. [Online]. Available:
https://www.ifrc.org/en/news-and-media/newsstories/asia-pacific/sri-lanka/sri-lanka-flashfloods-affect-over-40000-in-western-sri-lanka-66090/. [Accessed 13 June 2019].
[3] H. Gehrels, "Protecting Colombo against future
floods,"Deltares,[Online].
Available:
https://www.deltares.nl/en/projects/protectingcolombo-against-future-floods/. [Accessed 13
June 2018][4] A. Sathisraja, "Special reports – Floods," The
Sunday Times, 22 May 2016. [Online].
Available:
http://www.sundaytimes.lk/160522/news/specia
l-reports-floods-194617.html. [Accessed 13
June 2018].
[5] A. Ameen, "News," BBC, 27 May 2017.

[Online].
Available:
https://www.bbc.com/news/av/world-asia40071230/sri-lanka-floods-rescuers-reachworst-affected-area. [Accessed 13 June 2019].
[6] R. Wijesekara and C. Kudahetty, "Preliminary
groundwater assessment and water quality study
in the shallow aquifer system in the Attanagalu
Oya Basin," in National Conference on Water,
Food Security and Climate Change in Sri
Lanka. Water Quality, Environment andClimate Change, 2010.
[7] I. d. Hydrology Division.
[8] F. Laouacheria and R. Mansouri, "Comparison
of WBNM and HEC-HMS for runoffhydrograph prediction in a small urban
catchment," Water Resources Management, vol.
29, no. 8, pp. 2485-2501, 2015.
[9] A. D. Feldman, "Hydrologic Modeling System
HEC-HMS: Technical Reference Manual," US
Army
Corps
of
Engineers,Hydrologic
Engineering Center, 2000.
[10] D. Halwatura and M. M. M. Najim,"Application of the HEC-HMS model for runoff
simulationinatropicalcatchment,"
Environmental modelling & software, vol. 46 ,pp. 155-162, 2013.
[11] G. Thapa and N. T. S. W. ", "Computation and
Optimization of Snyder’s Synthetic Unit
Hydrograph Parameters," 2018.
[12] G. W. Brunner, "HEC-RAS, River Analysis
System Hydraulic Reference Manual, Version
5," US Army Corps of Engineers, Hydrologic
engineering Center , 2016.
[13] S. Alaghmand, R. bin Abdullah, I. Abustan and
S. Eslamian, "Comparison between capabilities
of HEC-RAS and MIKE11 hydraulic models inriver flood risk modelling (a case study ofSungai Kayu Ara River basin, Malaysia,"
International Journal of Hydrology Science andTechnology, vol. 2, no. 3, pp. 270-291, 2012.
[14] S. Tobgay, "A CASE STUDY OF
ATTANAGALU
OYABASINKARASNAGALA,SRILANKA,"EVALUATION OF RUNOFF ESTIMATION
USING
SCS
METHODFORINFRASTRUCTURE DESIGN, 2015.
[15] T. Pushpakumara and T. Isuru, " Flood
Modelling and Analyzing of Attanagalu OyaRiver Basin Using Geographic Information
System," International Journal of Advanced
Remote Sensing and GIS, vol. 7, no. 1, pp.
2712-2718, 2018..
[16] M. Iosub, I. Minea, O. Hapciuc and G.
Romanescu, "The use of Hec-Ras modelling inflood risk analysis," Aerul si Apa. Componente
ale Mediului, p. 315, 2015.

740

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

LAO KHAM’S VARISCITE PROPERTIES AND APPLICATION IN
CHEMICALLY BONDED PHOSPHATE CEMENT
Watcharagon Wongkamjan1 and Thanawat Jumepaeng2
Faculty of Liberal Arts and Science, Roi Et Rajabhat University, Thailand
2
Faculty of Sports and Health Science, Thailand National Sports University Udon Thani Campus, Thailand
1

ABSTRACTThis study aims to investigate properties and application of Lao Kham Variscite, LKV, variscite at Lao Khamvillage, Roi Et province Thailand. The samples were investigated properties included mineral composition analysis,Thin-section analysis and microscopic characteristics analysis with digital stereomicroscope. The applications of
LKV in chemically cement were also investigated. The results indicated that LKV is itself a composite with several
crystalline in microstructure characterization. It was found that LKV calcined at 600°C has best reactive with
NaOH 3M solution and tendency to develop for used as chemically bonded phosphate cement (CBPC).
Keywords: Variscite, Chemically Bonded Phosphate Cement
and study the guidelines for use. Guidelines for thedevelopment of Varisite at Lao Kham Village or Lao
Kham’s Variscite; LKV, in material and application,is necessary for further development In this study.
The aim of this work is to apply LKV for chemicallybonded phosphate cement (CBPC).

INTRODUCTION
Aluminum phosphate is an aluminum compoundfound in natural minerals, including: angelite
coeruleolactite, evansite, lucinite, metavariscite,
sterretite, variscite, vashegyite, wavellite, andzepharovicht. According to a recent study, theseminerals can be used as an additive in cement by
mixing with calcium sulfate and sodium silicate
solutions as concrete, flux for ceramics, dental
cements, waterproofing and catalyst in organic
synthesis [1], [2]Chemically Bonded Cements/Ceramics (CBCs)
have been widely applied, especially radiation
protection systems, solid nuclear waste coagulationand encapsulation, active structure in hightemperature composites and medical applications,especiallychemicallybondedphosphatecement/ceramics. CBPCs, which are ceramicmaterials that have complete mechanical properties
from chemical reactions at low temperatures (below
300 degrees Celsius), instead of normal ceramic
properties at high temperatures. Practically, thismaterial has both cements and ceramics qualities. The
original CBCs were primarily studied and researched
in dentistry [3] and since 1970, magnesium phosphate
ceramics had been used in construction materials forconstruction work, started by the Brookhaven
National Laboratory (BNL) in the United States.
After that, aluminum phosphate (found in the target
local material source) has also been applied to CBPCs
as well [4].
According to a study of Japakasetr, 1982 [5];Sheldon, 1984 [6] the phosphate group of aluminum
phosphate was found “Variscite” (Al(PO4) (H2O) 2) at
Lao Kham Village, Si Kaeo Sub-District, Mueang
Roi Et District. However, there are no studies to test

MATERIALS AND METHODS
Materials
The material is a mineral that is composed
aluminum phosphate. From Sheldon's study (1984) atthe Lao Kham Village area of Roi Et Province,
Thailand which was a mineral that is likely to be thesecondary mineral of the phosphate group ofaluminum phosphate, namely “Variscite” (Al(PO4)(H2O)2). The two groups of samples were collected,
random sample, which was randomly collected fromrocks containing mineral. Also screen sample, which
was extracted the mineral from streak in the origin
rock. In the screen sample group, the sample will becalcined by heat to determine the effect of thetemperature, ie, non- calcining sample (LKVNOR),
sample calcined at 400, 600, 800 and 1,000 ° C(LKV400, LKV600, LKV 800 and LKV1000
respectively). Type I Portland cement, according to
ASTM C150-07 [7] was used for a reference cementin this study.
MethodMicroscope analysis
The cold mount method was used for prepared
the mounted sample and polished section. This is amethod for preparing brittle parts and may cause
breakage when polishing the surface by applying the741

SEE - Bangkok, Thailand, Nov.11-13, 2019

sample in the mold. Then it was applied with epoxy
and setting at room temperature for 24 hours. Thenremoved the sample from the mold and polish until
surface was smooth. Indispensable prerequisites forthe success of investigations using transmitted orreflected light microscopy [8].
Petrographic analysis
Fig. 1 Random sample.

Thin section petrography was carried out using
Olympus BX-41 imaging petrographic microscope
equipped with plane and cross polarization
illumination mode. The petrographic analysis wasused to study the microstructure of the aggregates, toidentify the constituent minerals and to classify theaggregates. When placed between two polarizing
filters set at right angles to each other, the opticalproperties of the minerals in the thin section alter thecolor and intensity of the light as seen by the viewer.
As different minerals have different opticalproperties, most rock forming minerals can be easily
identified [9].

Microscope analysis
In the polished section analyzed with a digital
microscope, at magnification at 15 times and 35
times, the rock sample has the white mineral line in
the red-brown coarse particle of sandstone (Fig. 2aand Fig. 2b). Variscite had a very fine grain size ofparticle compared to the particle size of the quartz
crystals (Quartz, SiO2) in sandstone. Also iron oxide(Iron, Fe) distributed in the rock with the yellow todark brown color particles.

Chemical compositions and Mineral analysis
The chemical compositions were analyzed
with X-ray Fluorescence spectroscopy (XRF) and Xray diffraction spectroscopy (XRD).
Initial Setting Time and Final Setting Time Testing
Initial setting time and final setting time testingof cement paste and LKV mixed with NaOH 3M werealso test in this study with ASTM C 191: Time of
Setting of Hydraulic Cement by Vicat needle [10].

(a)Compressive Strength
Compressive strength index (%) of cement
paste and LKV mixing sample were test at the age of
14 days.
RESULTS AND DISCUSSION
Random Sample(b)

The random sample, which was randomly
collected from rocks containing mineral as show in
Fig.1.

V: Variscite (AlPO4·2H2O)
Q: Quartz (SiO2)

Fig.2 Digital Microscope of Random Sample LKV(a) at 15X (b) at 35X
Petrographic analysis
The result of Petrographic analysis, it foundthat the Nordstrandite and Variscite microscopic
texture, both of which consists of quartz mineral

742

SEE - Bangkok, Thailand, Nov.11-13, 2019

Nordstrandite and Variscite ore as shown in Fig. 2
and 3.

Variscite
Nordstrandite
Bayerite, syn

Al(PO4)(H2O)2
Al(OH)3
Al(OH)3

6.9
7.2
4.8

Table 2 X-ray fluorescence of Random Sample LKVFormula
SiO2
P2O5
Na2O
Fe2O3
Al2O3
CaO
MgO
K2O
SrO
Total

(a)

Concentration
(wt%)
33.90
13.95
19.59
11.44
10.11
4.73
5.48
0.20
0.60
100

Screening Sample
Based on the polished Section test a whitemineral, Varisite, had a very fine grain size comparedto the particle size of the sand which could beobserved with apparent, as shown in Fig. 4 (a).
Therefore this study will separated the mineral fromthe sandstone to be the main example in the study ofscreening sample group, Fig. 4 (b).
(b)
Fig. 3 Thin section microscopy of Random Sample
LKV the (a) without using polarized light and (b)using polarized light.
X-ray diffraction spectroscopy(a)(b)
Fig. 4 (a) the mineral from the sandstone texture (b)White mineral obtained from sandstone extraction

The XRD result shown in Table 1 found thatthe randomly sample consisting of quartz (SiO2),
mostly (81.0%) making the majority of the elements
are sandstone, because the test samples were tested
without the separation of the mineral. However 6.9
percent of Variscite (Al(PO4)(H2O)2) has been found.

X-ray diffraction spectroscopy
The XRD result shown in Table 3 found thatthe survey sample consisted of the same amount ofquartz (SiO2) (46.12% - 56.72%). LKVNOR with
Variscite (Al (PO4) (H2O)2, 23.51%, which wassignificantly higher than random Sample. While a ll
the calcined samples were not found Variscite, but
the mineral composition was changed to Aluminum
Phosphate (AlPO4) altogether. Aluminum Phosphate
Hydrate (AlPO 4 x (H 2 O) only found in LKV400.
When the temperature rises from 600 degrees, someparts of Aluminum Phosphate Hydrate had changed
to Aluminum Phosphate (AlPO4) which wascomposed of Aluminum Phosphate equal to 34.12%,
34.51% and 30.44% for LKV600 LKV800 and

X-ray Fluorescence spectroscopy
As shown in Table 2, it was found that mostof the samples were silica oxide (SiO 2) or Quartz(33.90%), followed by Phosphorus pentoxide (P2O5), with 13.95%.

Table 1 X-ray diffraction of Random Sample LKV
MineralFormulaQuartzSiO2Concentration
(wt%)
81.0
743

SEE - Bangkok, Thailand, Nov.11-13, 2019

LKV1000 respectively. In addition, some parts of
Phosphate (PO4) appeared in Calcium Iron Phosphate
and Calcium Hydrogen Iron Phosphate for the
samples that are calcined with temperatures up to
6 0 0 d e g r e e s w hi le not found this mineral in thesample calcined at 400 degrees.

Table 3 X-ray Diffractrometer of Screening LKV Sample
SampleQuartzFormulaSiO2

LKVNOR
46.12

LKV40048.51

LKV60052.6

LKV80055.81

LKV1000
56.72

Kaolinite

Al2(Si2O5) (OH)4

15.61

13.1

-

-

-

Variscite

AlPO4(H2O)2

23.51

-

-

-

Aluminum
Phosphate
Aluminum Iron
Phosphate
Aluminum
Phosphate
HydrateCrandallite

AlPO4

-

18.42

34.12

34.51

30.44

Al 0.67Fe0.33(PO4)

-

8.6

-

-

-

AlPO4x(H2O)

-

6.24

-

-

-

CaAl3(OH)6(PO3(O0.5(OH)0.5))2

5.43

5.12

-

-

-

Ca9Fe2(PO4)14

2.56

-

6.91

7.37

8.23

Ca9FeH(PO4)7

6.77

-

6.37

2.31

4.61

Calcium Iron
Phosphate
Calcium
Hydrogen Iron
Phosphate
Setting Time

400

Mixing of NaOH 3M with LKV conducted tofind the setting time. While 3M was the amount of
NaOH estimated by the chemical equation balance by
weight, to make the reaction even with AlPO4 in LKV(average of 30% AlPO4 in the sample and the mixture
ratio of solution and LKV was 0.35). It was found thatthe non-calcined LKVNOR did not setting whenmixed with the 3M NaOH solution while the LKV600
had the fastest formation (initial setting time 15
minutes, and final setting time was 90 minutes),
which indicates that the LKV 600 was most likely toreact with the NaOH 3M solution, followed by
LKV800 LKV1000 and LKV400 respectively, asshow in Fig.5.

350

375
300

300

240

250

Time (min)Innitial
Setting
time

200
150

150

Final
Setting
time

150
90

100
50

90

15

0
LKV400

LKV600

LKV800 LKV1000

Mixture Composition

Fig. 5 Setting Time results of calcined LKVCompressive Strength
Compressive strength index (%) of cement
paste and LKV mixing sample at the age of 14 days
found that LKV600 had the highest compressive
strength (24.5%) followed by LKV800 LKV1000 and
LKV400 respectively (14.9%, 6.2%, and 3.3%).
While LKVNOR, no formation was found so the744

SEE - Bangkok, Thailand, Nov.11-13, 2019ACKNOWLEDGEMENTS

compressive strength test was not possible. Whichcorresponds to the previous setting time test resultsthat LKV600 has the fastest formation. However,
LKV600 has only 24.5% compressive strength whencompared with the reference cement (REF).
Therefore, it should be studied in terms of the solution
type and the appropriate concentration to optimize
solution mixing LKV as show in Fig.6.

This research was supported by National
research council of Thailand (NRCT). We thank ourcolleagues from Roi Et Rajabhat University who
provided insight and expertise that greatly assisted theresearch, although they may not agree with all of theinterpretations/conclusions of this paper.

Relative Compressive Strength (%)

120

REFERENCES

100
100

[1] Kawasaki S. and Akiyama M., Unique GroutMaterial Composed of Calcium Phosphate
Compounds, International Journal of GEOMATE,
Vol. 4, No. 1, 2013, pp. 429-435[2] Pangdaeng S., Sata V. and Chindaprasirt P., Effectof Sodium Hydroxide Concentration and Sodium
Silicate to Sodium Hydroxide Ratio on Propertiesof Calcined Kaolin-White Portland Cement
Geopolymer,
International
Journalof
GEOMATE, Vol.14, Issue 46, 2018, pp.121-128.
[3] Colorado H. A., Hiel C., Hahn T., and Yang J. M.,
Wollastonite-Based
ChemicallyBondedPhosphate Ceramic Composites, Metal, Ceramicand Polymeric Composites for Various Uses,
2011.pp.265-282.
[4] Wagh A. S., Chemically Bonded Phosphate
Ceramics, 2016, pp.1-283.
[5] Japakasetr, T., Phosphate in Thailand; Economic
Geology Division, DMR, 1982, 7p.
[6] Sheldon, R.P., 1984, Phosphate Resource
Assessment and Exploration in Thailand, Thai
Department of Mineral Resources, 52 p.

80

60
40
24.5
14.9

20
3.3

6.2

0
REF

LKV400 LKV600 LKV800 LKV1000
Mixture Composition

Fig. 6 Compressive strength index (%) of cement
paste and LKV mixing sample at the age of 14 days.

CONCLUSIONS
1. LKV, which was screen sample, had
Variscite mineral of 23.5% which was significantly
higher than random sample.
2. Calcination affected the mineral state of
LKV. All samples that had calcined were not foundVariscite, but the mineral composition changed to
Aluminum Phosphate (AlPO4).
3. Non-calcined LKVNOR found no formation
when mixed with 3M NaOH solution. While LKV600
had the fastest setting time when mixed with 3M
NaOH solution. It indicated that LKV 600 was themost reactive with NaOH 3M.
4. The LKV600 had the highest compressive
strength. However, when compared to the reference
cement, LKV600 only received 24.5% ofcompressive strength when compared with thereference cement. There should be a study of thesolution and the appropriate concentration to
optimize solution mixing LKV.

[7] American Society for Testing and Materials.
Standard Specification for Portland Cement,
2007, ASTM C150-07.
[8] Moreland G.G., Preparation of Polished Thin
Sections, American Mineralogist, Vol. 53, Issue
5-6, 1968. pp. 2070-2074.
[9] Barber, D.J. 1981. Demountable polished extrathin sections and their use in transmission electron
microscopy. Mineralogical Magazine 44:357-359.
[10] American Society for Testing and Materials.
Time of Setting of Hydraulic Cement by Vicat
needle, 2018, ASTM C 191-18a.

745

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

PERFORMANCE EVALUATION OF CONCRETE WITH RECYCLED
WASTE POLYPROPYLENE

1

N. Haque1, M.J Islam2, A. Tahsin3 & T. Mehdi4
Department of Civil Engineering, Military Institute of Science and Technology, Dhaka, Bangladesh; 2,3,4

ABSTRACT
Production and application of plastic waste has become a severe environmental problem worldwide where
polypropylene (PP) possesses around 35% of the total plastic waste. Using recycled PP in concrete could be asolution for the problem. This study aims at evaluating structural and durability performance of various strength
concrete mixed with recycled waste polypropylene as a partial replacement of coarse aggregate. Performance ofconcrete was evaluated in terms of compressive strength, chloride ion penetration and high temperature exposure
at different ages. In order to determine the optimum proportion of polypropylene in concrete, samples wereprepared with 0%, 10%, & 20% replacement of PP as coarse aggregate for two different w/c ratios (0.35 and0.40). It was found that for maximum 20% of PP replacement, compressive strength reduction was only 21%
which could still produce more than 25 MPa of concrete and at high temperature exposure (more than 200° C)
for 1 hour the strength of concrete was still more than 20 MPa. Moreover, PP can also be used to produce lightweight concrete due to its lower unit weight, as relative reduction was up to 10% in density for 20% of PP
replacement, than regular concrete. Therefore, concrete with optimum proportion of PP as partial replacement ofcoarse aggregate can produce strong and durable structure concrete.

Keywords: Concrete, Polypropylene; Compressive strength; Chloride ion penetration; High temperature
exposure;

which results in a reduction in the dead load of astructural concrete member of a building. Reductionin the self-weight of a building will help to reduce
the seismic risk of the building since the earthquake
forces linearly dependent on the dead-weight.
Furthermore, it can also be concluded that the use ofrecycled PP as a partial replacement of coarse
aggregate in concrete provides some advantages, i.e.,
reduction in the use of natural resources, disposal ofpolymer wastes, low cost alternative to regularaggregates, prevention of environmental pollution,and energy saving.
Polypropylene (PP) is a cheap and plentiful
thermoplastic used in a wide variety of applications
including food packaging, textiles, laboratory
equipment, automotive components, and polymer
banknotes. It is slightly harder, more heat resistant,mechanically rugged material; and has a highchemical resistance [5]. It is the second-most widely
produced commodity plastic and can be used in
making composite concrete for its excellent material
property [6]. The melting point of polypropylene is
exceptionally high compared to numerous otherplastics at 320°F (160°C).
There were several researches done on suchtypes of composites in recent years but in terms ofdurability, the question still arises if it is durable
against chloride ion penetration and hightemperature exposure. Chloride penetration refers to

INTRODUCTION
With the technological advancement around theworld, disposal of wastes and waste management
has gotten to be a major natural issue all over theworld. Among all these waste materials, plasticbased waste materials are worst as they don't
effectively debase or decayed [1]. Plastic isaccessible nearly all over and its utilization aroundthe world expanded from 5 million tons to almost
335 million tons amid the year 1950–2016 [2]. Onlyaround 7% of these produced plastics are recycled
and rest are polluting the earth. According tostatistical report, around 34.20% of these hugeplastic wastes are polypropylene found in municipal
solid waste [3].
Construction industry is getting a quick
expansion every day, so researchers are always
working to develop a cleaner, cheaper and energy
efficient construction material to cope up with theadvancement. Currently, the global concrete
consumption is estimated around 25 Billion tons per
year and annual coarse aggregate (stone) usage ismore than 3.9 billion tones (2016) [4]. The use ofwaste product like plastics in concrete not only
makes it economical but also helps in reducing theplastic waste disposal problems.
The use of polypropylene (PP), due to its low
unit weight, reduces the unit weight of concrete
746

SEE - Bangkok, Thailand, Nov.11-13, 2019

the depth to which chloride ions from theenvironment penetrate into the concrete which canlead to corrosion in RCC structures [7]. This
research emphasizes on finding out compressive
strength and durability performance of engineered
concrete in terms of Chloride penetration and hightemperature exposure with polypropylene replacingcoarse aggregates at various proportion.

for all combination of fresh concrete. The specificgravity of admixture was 1.21.
Table 1 Properties of coarse and fine aggregate
Description

CrushedStone

Polypropylene (PP)

Sand

19

12

-

2.61

0.85

2.7

0.36

0.3

2.8

8.12

6.77

2.46

Maximum Size(mm)
Specific Gravity
Water
Absorption (%)
Fineness
Modulus

MATERIALS
For the experimental work, stone chips andrecycled waste PP were used as two different typesof coarse aggregates. According to the ASTM C33,
the gradation of the coarse aggregates was
performed. Ordinary Portland Cement (OPC) has
been used as binding material for this research work.
River (Sylhet) sand has been collected and used asfine aggregates (FA). Coarse aggregate (CA) as
Crushed stones were purchased from local market
according to required quantities. Shredded PP
aggregate, as shown in Fig. 1, was used as partial
replacement of coarse aggregate. Polypropylene wasprepared through a process of collection, cleaningand scraping. After that, it had been melted andcooled into certain shape. Those cooled plastic
molds were then shredded into specific sizes.

METHODOLOGY
Using Polypropylene (PP) in construction is an
economical and green concept of modern civilengineering [8]. To achieve the objectives, a numberof experiments have been done in the laboratories.
The concrete samples were prepared with 0%, 10%
and 20% replacement of PP as coarse aggregate withtwo different w/c ratios (0.35 and 0.40). Concrete
cylinder samples, 100 mm x 200 mm, were preparedas per requirement of the test methods following
ASTM C 192. After 24 hours of humidity curing thesamples were water cured for 28 days, except for 7
days test. Samples were tested for compressive
strength following ASTM C39 at 7, 28 and 90 days.
Samples were also tested for chloride ion penetration
by surface resistivity meter following AASHTO TP
95 at 28 days and compressive strength test after
high temperature exposure (more than 200° C for 1hour) at 90 days.
Mix Design

Fig. 1

Mix design for the concrete specimens was
proposed considering stone chips with threedifferent partial replacement of PP (0%, 10% and20%) along with two different water cement ratios(0.35 and 0.40). Table 2 shows the mix proportionfor 1 m3 of concrete.

Processed polypropylene (PP) aggregate

Table 2 Mix design for 1m3 of concreteFig. 2

Designation
WC35P0WC35P10
WC35P20
WC40P0
WC40P10
WC40P20

Water
(kg)

OPC
(kg)

CA
(kg)

PP
(kg)

FA
(kg)

Total

206
589
977 0
487 4112206
589
879 39474 4041206
589
781 78461 3969
206
514
975 0
552 3480
206
514
877 39539 3409206
514
780 78526 3337
Note: in the designation, WCXPY, “X” stands forthe water cement ratio and “Y” stands for percentage
of PP replacement.

Coarse and Fine Aggregate

Material properties have been found out by
performing specific tests in the laboratory according
to the ASTM standards. Materials properties of theaggregates are summarized in Table 1.
Water-reducing admixture following ASTM C494, for maintaining uniform workability, was used
747

SEE - Bangkok, Thailand, Nov.11-13, 2019

RESULTS AND DISCUSSION
For evaluating the physical properties ofconcrete, relative density reduction, compressive
strength reduction and chloride ion penetration test
was analyzed. Compressive test of concrete was
performed at different stages from 7 to 90 days andchloride ion penetration test using a surface
resistivity meter was performed at 28 days of the ageof concrete, as shown in Fig. 3.
Also, higher temperature exposure was
performed in oven shown in Fig. 4 at 200°C andcompressive strength test
was performed
accordingly.
Fig. 5Comparison of density reduction of PP
replaced concrete
Based on the data, it can be said that, maximum
relative reduction of density was around 10% for 20
percent PP replaced concrete, which implies that it
can produce lighter concrete with reduced dead loadand seismic vulnerability.
Effect on Compressive Strength

Fig. 3Compressive test and Chloride penetration
test of concreteFig. 4High temperature exposure in oven

The compressive strengths at 7, 28 and 90 days
after casting were measured for all type of concretes.
Compressive strength test results of w/c ratios 0.35
and 0.40 for various ages are described in Fig. 6 and7. Based on the test data it can be said that concretewith PP will produce lower strength compare to theregular concrete with no PP content. This is
expected as synthetic PP does not bond well with thebinding material used in content. However, withincrease in concrete age interfacial transition zone
between the aggregate and cement matrix gainstrength and reduction of compressive strength
becomes smaller and smaller.

Effect on Density reduction
The density of concrete was determined for all
type of combinations and compared, as presented inFig. 5, with the standard sample of concrete (without
any PP replacement) to measure the relative
reduction of density.

Fig. 6748

Compressive strength of concrete at various
ages for water cement ratio of 0.35

SEE - Bangkok, Thailand, Nov.11-13, 2019

The results of the chloride ion penetrability of PP
replaced concrete gives the indication withreplacement of PP there is almost no effect on
durability aspect in terms of chloride ion penetrationcompare to the regular concrete without PP.
Effect on High Temperature exposure

Fig. 7For high temperature exposure, the concrete
cylinders were heated evenly in an enclosed furnacechamber at the age of 90 days. The temperatureloading curve shown in Fig. 9 indicate that theconcrete cylinders were exposed to 200°C for overan hour. After the application of temperature, thesamples were cooled down to room temperature at
the laboratory. Samples were then tested forcompressive strength. Compressive strength results,
as presented in Fig. 10, are compared with for all
three PP replaced concrete (0, 10 and 20%) for w/c
ratios of 0.35 and 0.40.
The results of the compressive strength after hightemperature exposure indicates that, even after anhour, the PP replaced concrete may retain
sustainable compressive strength (more than 24
MPa).

Compressive strength of concrete at various
ages for water cement ratio of 0.40

For the water cement ratio of 0.35,
compressive strength reductions for 10% and 20%
PP replaced concrete compare to 0% PP replaced
concrete is only 12% and 21%, respectively. On theother hand, for the water cement ratio of 0.40
compressive strength reductions for 10% and 20%
PP replacement compare to 0% PP replaced concrete
is only 7% and 19%, respectively. The results of the
PP replaced concrete gives the indication ofadequate strength of the concrete even with higher
percentage of PP replacement.
Effect on Chloride Ion Penetration
The surface resistivity test was performed
according to AASHTO TP 95. In this test method,
the specific resistance of concrete was measured bysurface resistivity meter and the data was correlated
to the chloride penetrability classification of theconcrete. According to this test method, specificresistance value of 12 KOhm-cm to 21 KOhm-cm isconsidered as moderate category. Fig. 8 shows the
specific resistance in KOhm-cm for two different
water-cement ratios and three different PP
replacement percentages. For the all the cases,
chloride ion penetrability of concrete falls under low
to moderate category.

Fig. 8Fig. 9Temperature loading graphFig. 10 Compressive strength of concrete after hightemperature exposure

Chloride ion penetrability of concrete
749

SEE - Bangkok, Thailand, Nov.11-13, 2019

-production-of-plastics-since-1950. [Accessed 12
June 2019].
[3] Islam, Md, Sarwar, Navid and Al shafian, Sultan,
Conference
proceedinginInternational
Conference on Recent Innovation in Civil
Engineering for Sustainable Development(IICSD-2015), An Investigation of Concrete
Properties with Polypropylene (PP) as Partial
Replacement of Coarse Aggregate. pp. 1.
[4] USGS Mineral Commodity Summaries, 2017.
[online].
Availableat:https://mineralsmakelife.org/wpcontent/uploads/2017/04/Mineral_Commodity_S
ummaries_2017.pdf [Accessed 12 June 2019][5] Whiteley, K. S., Heggs,T. G., Koch, H., Mawer,
R. L., & Immel, W. 2005. Polyolefins in
Ullmann's Encyclopedia of Industrial Chemistry.
Weinheim: Wiley-VCH Verlag GmbH & Co.
[6] Bagherzadeh R., Pakravan, H. R., Sadeghi, A. H.,
Latifi, M., & Merati, A. A. 2012. An
Investigation on Adding Polypropylene Fibers toReinforce Lightweight Cement Composites(LWC). Journal of Engineered Fabrics & Fibers(JEFF). 7 (4): 13-21.
[7] Zhang, J., Shi, C., Li, Y., et al, 2015a. Influenceof carbonated recycled concrete aggregate on
properties of cement mortar. Construction and
Building Materials 98, 1–7.
[8] Islam, M. J., Meherier, M. S., Islam, A. K., M.
R. 2016. Effects of waste PET as coarse
aggregate on the fresh and harden properties ofconcrete. Construction and Building Materials,
125,946-951.

CONCLUSION
Compared to regular concrete, PP concrete has
the lower compressive strength as well as the lower
durability against high temperature exposure. With
the increasing amount of PP percentage in theconcrete, both compressive strength and surface
resistivity of the concrete is decreasing albeit inlower percentage. It is to be expected as thesynthetic nature of the PP provides lesser bonding
with the cement mortar compare to the natural stoneaggregate. However, at water-cement ratio 0.40 thisreduction is about 21% for 20% PP replaced
concrete and still it produces concrete withcompressive strength higher than 25 MPa.
Furthermore, more than 33 MPa strength for
20% PP replaced concrete gives the indication that
PP can be used for structural concrete safely.
Furthermore, structure made by PP concrete islighter than regular concrete due to the lower unit
weight of PP. Therefore, it can be concluded that therecycled PP can be adopted as partial replacement ofcoarse aggregate in concrete used for structural
purposes.

REFERENCES[1] Frigione, M. 2010. Recycling of PET bottles asfine aggregate in concrete. Waste Management,
30 (6): 1101–1106.
[2] Statista, 2016. Global production of plastic since
1950.
[online].
Availableat:https://www.statista.com/statistics/282732/global750

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

LIFE CYCLE COST ANALYSIS FOR REINFORCED GEOGRIDRAILWAY TRACK
Saad Farhan Ibrahim Alabdullah1, Ali Jabbar Kadhim2 and Harith Basim Khalaf2
1
Faculty of Engineering, Isra University, Amman, Jordan;
2Faculty of Engineering, Al-Mustansiriya University, Baghdad, Iraq
ABSTRACTThe development of railway transportation is facing many challenges and one of main challenges is the
Reduction of the track costs. The reduction of railway track costs is critical for competitiveness of railway
operators, since other competing modes of transportation (e.g. automotive, aviation) have seen a tremendous
reduction in life cycle cost in the previous years, while the costs of railway maintenance has not decreased
significantly through the same time. The objective of this study is mainly focus on the reduction in of therailway track cost due to the use of geogrids reinforcement. The results showed a redaction of railway track
cost for the sub-ballast reinforced model (4.1%), the ballast reinforced model was (6.5%) and the double
reinforced model was (3.73%) as compared to the unreinforced track.
Keywords: Railway, life cycle cost, Geogrid, Reinforcement, maintenance.

Commission (2011) on Sustainable Transportation
settled goals for the reduction of railway life cycle
cost by 30% in 2020. Thus, there is a importantfocusing on the study of life cycle cost application
on railway track [3].
INNOTRACK project used the Geogrid as apart of its numerical simulations and laboratory
tests. This approach proved that the geogrid
reinforcement would cause a reduction in the life
cycle cost and operational disturbances. Hall andSharpe (2007) used a British Railway case study
was done in (1988) where geogrid was introduced
for the renewal of railway track in the Derby–
Leeds line at Shirland. The railway site wasconstructed with 300mm of ballast and a 100mm
blanketing sand below it, a separation layercomposed from a heat bonded geo-textile and ageogrid with a small mesh to stop the particles ofballast from the penetration the geotextile. A newgeogrid having large mesh was furtherly added asa way to support often the soft subgrade. The
undertaking condition seemed to be monitored
over the long-term performance in addition tooperational life of the ballast. The end result ofmonitoring exhibited that the geogrids decreased
the requirements of routine maintenance to a tiny
proportion of their past level so reducing the cycle
cost [4].
thedecision-making,
maintenanceandoperation costs Without doubt are significantly
more vital than initial cost of constructions. Thesetypes of costs have to be studied all through thelife time of the project so they match up theiroverall performance threshold [5].It is necessarythat the making of decisions must be based on thelife-cycle foundation. This will be resulted inchoosing cheaper strategies within the extended

INTRODUCTION
The entire cost of railway transportation comesfrom construction, repairing and the operating offacilities, manufacturing and maintenance ofrailway vehicles, as well as fuel production.
Because maintenance, expenses for the traditional
ballasted train track might be significantly
decreased if the final settlement below loading is
reduced. There are a few current data regarding the
lifetime of the actual geosynthetics within theconstruction associated with railway. Since theknowledge about using geosynthetics upon railway
tracks is only recognized in the past (20) years, andwe can claim that the experience as well aspractice from the lifetime of numerous
constructions techniques are still are not enoughregulate them correctly. Just little estimations
available through the geosynthetics manufacturers
involving geosynthetics who announced that thematerials which they produce might rise the ballast
life time by (2 - 4) times the original life. Since ofthe deficiency within the pervious data, thecomputation of repairing and renewal work related
to railway tracks had been very few. Additionally,
Federici (2003) noticed that the main available
scientific studies on railway track method thatingest consideration the infrastructures in depth arevery hardly ever and mainly focused on cars
construction. Consequently, the effect of geogrid
support on lowering the cost of train track willprobably be studied [1].
Life cycle cost could be functional for projectthrough a wide variety of industries, containing therailway. Railway track cost has not considerablychanged since the past (30) years with comparison
to other rival transportation modes [2]. European
751

SEE - Bangkok, Thailand, Nov.11-13, 2019

time and cooperated with the available finance.
Newest researches concerning railway track
improvements with the use of geosynthetics
reinforcement indicated a positive effect. The
maintenance requirement dropped and the strengthof the ballast was boosted when thegeotesynthetics were applied. Settlement of the
track was 37 to 65 percent less than settlement of
the equivalent portion of the unreinforced test
section [6].
The geosynthetics manufacture company
Tensar stated that the using of their geosynthetics
products will cause a rise in maintenance cycle by
3 times from its original value after a railway trackcase study; the railway track was located between
London and Scotland. The railway track has been
under speed limit for many times in spite of it wasmaintained frequently 2 times a year. The intrusionof geogrid in that track caused a considerable
decrease in the deterioration rate of the railway
track without speed restrictions or maintenance[7].

The following costs were used in the tool:• Construction costs
1. The Ballast layer
2. The Sleepers
3. Fastening and Rails systems
4. Elastomeric [Resilient] pads
5. Geogrid• Routine maintenance costs:
1. Stabilization and Tamping
2. Milling of rail

METHODOLOGY
The Life cycle cost (LCC) and the Whole life
cost (WLC) are well known methods used to
calculate all the related cost with the whole life ofdesign for a specific asset. The Life cycle cost
(LCC) and the Whole life cost (WLC) could be
used interchangeably while in the (BS ISO 156858:2008) international standard for life cycle costingof buildings and constructed specified that the twohave difference meaning [8]:•Life cycle cost is well defined, as “is thecost of a part or its divisions during its cycle life,
thoughaccomplishingtheperformances
requirement”.
•
Whole life cost is well defined as “is theprocess of regular economic aspects for the
benefits and whole life cost of a known analysistime”. Whole life cost covers the extra costs such
as Land cost, support cost related to activity inassets, and the incomes produced by the assets.
The connection between LCC and WLC is showed
in Fig.1.
In order to make the suitable choices on theeconomical profits of the enhancement works that
include using an innovative technology the life
cycle cost and (LCC) should be calculated before
and after the use of the technology. The tool was
created within the project SMARTRAIL, andavailable on smartrail.fehrl.org, was used tovalidate the cost benefits related to the use ofgeogrid reinforcement in railway track system forthis research. The smart LCC rail tool wasdeveloped with Taking into account the ISO EN
15686-5 standard for LCC.

Fig.1 Scope of life cycle and whole-life costing(Adapted from BS ISO 15685-8:2008).
Geogrid has been increasingly used in railroads
to offer reinforcement and confinement pressure to
railway track layers. Four models were studied
experimentally to measure the difference in thelife of the railway track after using the geogrid.
The
testedmodel
dimensions
were(800*800*600 mm), the subgrade layer was 400
mm and both ballast and sub-ballast layers were
100 mm thick each. The tested models are
unreinforced model, sub ballast-reinforced model,
and ballast-reinforced model and doublereinforced
model
containingageogridreinforcement under ballast layer and sub-ballast
layer. The result demonstrated that using
reinforcement layer would reduce the settlement inmodels. The tested model looks like the sketch infig.2. A Cumulative fig.3 used to show thedifference in result of settlement between allmodels that had been tested.

752

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig.3 Load-Settlement relationship for all models
at every loading stage.

Fig.2 Sketch to show the experimentally tested
model.
The used tool let the user to discover the effects
of different maintenance choices on the life cycle
cost of for a railway track system. The calculationof life cycle cost is a way to estimate the over-all
costs of maintaining an asset with a specified
period for analysis, to be used as an input into a
decision-making procedure. The costs in the
Future and Discounting rate were transformed to
be Net Present Value (NPV) to make thejudgement simpler in maintenances regimes fromtotal cost point of view in the present day.
The input data was collected from“Transportation & Telecommunications of Iraq”
report by United Nations World Bank and“Hajama – Sawa” Railway Project done by Iraqi
Ministry of Transportation Republic Railways
Company [9]. The project life span was assumed
would be 60 years. Due to the difficultness of
predicting the increase in the ballast lifetime of due
to the use of geogrid, a number of scenarios were
tested, and all of these scenarios show that theusing of the geogrid in the railway track will be
more economical in the end. In addition, this meanthat the requirement of maintenance of the tackwill be reduced. The tool layout and the used data
for evaluated models are shown in figs. (4) (5) (6)(7) (8) accordingly.

Fig.4 The LCC tool-starting page.

753

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig.7 The input data for ballast reinforced track.

Fig.5 The input data for unreinforced model.

Fig.8 The input data for double reinforced track.
Fig.6 The input data for sub-ballast reinforced
track.

754

SEE - Bangkok, Thailand, Nov.11-13, 2019

RESULTSREFERENCES:

Life cycle cost Analyses showed a provision
economically towards the choice of using geogrid
under in the railway track as shown in fig.8. Thishas been confirmed for all the models that havebeen tested because the lifetime is increasing fromthe use of the geogrid and thus directed us to asituation that it was cheaper and extra profitable touse the geogrid reinforcement into the railway
track layers. The expenses differences for the threevariants and baseline variant for the railway trackis shown in the net present value of the threevariants is lesser than that of the baseline despiteof the initial cost is higher; rising fromsignificantly lesser rate of maintenances.

[1] Federici, M., S. Ulgiati, et al. (2003).
"Efficiency and sustainability indicators forpassenger and commodities transportation
systems. The case of Siena, Italy." Ecological
Indicators 3: 155-169.
[2] Paulsson B, Platzer M and Ekberg A (2006)“INNOTRACK – Innovative Track System –A unique approach of infrastructure managers
and competitive track supply industry fordeveloping the innovative products of the
future”, 7th World Congress on Railway
Research.
[3] European Commission (2011) “White Paper:
Roadmap to a single European Transport
Area – Towards a competitive and resource
efficient transport system”.
[4] Hall C D and Sharpe P (2007) “Review ofgeogrid stabilisation of railway ballast withreference to performance and durability”.
[5] European Commission (2013) “Sustainablesteel-composite bridges in built environment(SBRI)”, Final Report[6] Parsons R., Jowkar M., Han J., 2012.
Performance of Geogrid Reinforced Ballast
under Dynamic Loading. Report # MATCKU: 363, Final Report.
[7] Tensar (2013) “Railways: Mechanicalstabilization of track ballast and sub ballast”,
March 2013, Issue 11.
[8] British Standards Institution (2008) BS ISO
15685-8:2008, Buildings and constructedassets – Service life planning – Part 5: Life
cycle costing.
[9] Project “Hajama – Sawa”, cost estimate,
Ministry of Transportation of Iraq, Iraqi
Republic Railways Company.

CONCLUSION
The economical evolution indicated that theuse of geogrid proved to be a feasible and costeffective in reducing the intervals of maintenanceof railway track. Despite of slightly higher initialconstruction cost of railway track when thegeogrid used, the lifetime cost will reduced
significantly As the ballast reinforced was the mosteffective in the reduction of total cost by(6.5%)andthe sub-ballast reinforced was (4.1%) and the
double reinforced was (3.73%) as compared to theunreinforced track.

Fig.8 The Cumulative Present Value and time
relationship where
Baseline: Unreinforced,
Variant A: The sub-ballast reinforced
Variant B: ballast reinforced
Variant C: double reinforced755

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

CHARACTERIZATION OF NEW TYPES OF GEOSYNTHETICSEMBEDDED IN SOIL USING CALIFORNIA BEARING RATIO TEST
1

Mohamed Eltaher1, Zakaria Hossain1, Jim Shiau2, and Hajime Takami3
Graduate School of Bioresources, Mie University, Japan; 2School of Civil Engineering and Surveying,
University of Southern Queensland, Australia; 3Tsuchiya TSCO Co., Ltd., Japan

ABSTRACT
Characterizing of geosynthetics is essential for its effective use in various field applications of reinforced soil
structures. The success of a reinforced soil structure depends very much on the type of reinforcements used.
Therefore, a total of six types of geosynthetics is evaluated in this paper for its bearing capacity using the California
bearing ratio (CBR) test. Based on the analyses of the experimental data, the penetration strength and thepenetration displacement of specimens due to the variation of the type of geosynthetic are examined. As a resultof this study, the load-penetration behavior of the backfill soil with the six types of geosynthetic shows different
significant increments in the bearing capacity. It is found that in sandy soil, the embedment of a double layer of
eco-friendly geogrids (GGR 1, 2) as a reinforcement displays higher bearing capacity than all the othergeosynthetics. Also, geotextile (GTX 2) showed the highest bearing capacity as a single layer reinforcement.
Therefore, it would be the most promising one for ground improvement compared to the rest of the tested
geosynthetics in this study.
Keywords: Geosynthetics, Sandy Soil, California Bearing Ratio Test, Bearing Capacity.

geosynthetics which are made from basalt and plastic
fibers. A series of CBR tests on the geosynthetic
embedded inside one type of backfill soil have been
conducted. Based on the test results, the loadpenetration behavior of the reinforced subgrade soil
along with different mechanical characteristics has
been evaluated and discussed shortly.

INTRODUCTION
Airfields, embankments, highways, and manyother public facilities are mainly earth-fill structures
and they must be stable under all static and dynamic
loadings during construction and in-service as well[1]. Resistance to deformation under load is a corerequirement of subgrade soils and that is why thestrong subgrade soil can reduce the cost of the airfieldor highway construction.
Additionally, the required thickness of a flexible
pavement using reinforced subgrade (which could becomplex depending on the nature and properties of
the reinforcement) can be reduced as compared to
weaker subgrades [2]. Therefore, this will result in asignificant cost saving advantage due to resourcesaving and durability [3,4,5]. This is the reason thatreinforcing the soft soil using various types ofgeosynthetics is a well-known technique to improve
the ground performance, enhance its bearing capacity
and reducing the settlements.
The strength and performance of subgrade soils,
sub-base, and base course material for the design ofthe pavement thickness are widely evaluated by using
the California bearing ratio (CBR) test which often
forms the basis of pavement design. For this reason,
it finds favor with some design and control methods.
Several researchers investigated the bearing
capacity of soils reinforced with geosynthetics using
the CBR test. They used various types of geosynthetic
materials i.e. polypropylene (PP), High-density
polyethylene (HDPE), Polyester (PET) yarns, etc. [4]The present study dealt with new types of

PURPOSE OF THE STUDY
1. To investigate the influence of embedding of new
types of basalt and plastic geosynthetics in theeffective embedding position(s) of one backfill
soil on bearing capacity behavior, through a seriesof CBR tests.
2. Evaluating load-penetration behavior and soilgeosynthetics California bearing ratio.
3. Characterizing of new geosynthetics.
MATERIALS AND METHODS
Backfill Material
In this study, one type of soil collected from
Handa area, Tsu City, Mie Prefecture, Japan was usedas backfill material in combination with different
geosynthetic materials to evaluate its bearing
behavior.
According to the Japanese Geotechnical Society
engineering classification system (JGS), this soil isclassified as SF (sandy soil). The gradation curve andthe major physical properties of this soil are
addressed by Eltaher 2019. [5].
755SEE - Bangkok, Thailand, Nov.11-13, 2019

For the convenience of the readers, the importantcomponents of the CBR penetration testing machine
shown in Fig. 5 are numbered numerically.
Additionally, the complete used set of equipment,
tools, and its specifications are listed and describedby Eltaher 2019 [5].

Geosynthetic Materials
The woven and nonwoven geosynthetics used inthis study are made of basalt fiber and provided by
Tsuchiya TSCO Co., Ltd. The chemical composition
and basic characteristics of basalt fiber used for
manufacturing these geosynthetics are discussed indetail in another research on the influence ofembedding position on the performance of basalt
geosynthetics which had been conducted in early2019 by same authors [5,6]. Also, anothergeosynthetic made of plastic fiber has been used inthis study.
Totally, six types of geosynthetics have been used,
two woven basalt fiber geotextiles, one nonwovenbasalt fiber geotextile (with soft texture), two wovenbasalt fiber geogrids (with stiff texture), and one
plastic fiber geomat. For the purpose of discussion,
the geotextiles are noted as GTX1,2,3, the geogrids
are noted as GGR1,2 and the geomat is noted as GMA
respectively as shown in Fig. 1.

GTX1

GGR1

CBR Specimen’s Preparation
In the beginning, the CBR control specimen (soilonly specimen) as shown in Fig. 2 was prepared in the
CBR mold.
To prepare the control specimen layers, soil andwater (12% of the soil weight) were mixed
homogeneously. Then the soil was added into themold after it had been assembled with the perforated
bottom plate, spacer disc, and mold extension. The
soil had been added into the mold in three layers andtamped uniformly 67 times per layer using a manual
hammer.

GTX3

GTX2

Fig. 2 Typical schematic diagram of CBR control
specimen using a divided three layers of soil onlywith an indication of the surface of layers where
geosynthetic(s) will be laid on in the test specimens.

GMA

GGR2

Fig. 1 Types of the six geosynthetics used
For the preparation of CBR test specimens, in thesame way, the mold had been assembled, then the wet
soil sample was poured into it. The wet soil sample
was divided into three layers then tamped uniformly
67 times per layer. Considering that in these CBR test
specimens, the surface of each soil layer was leveled
precisely and geosynthetic(s) of the same diameter ofthe mold was/were laid on the surface of the chosensoil layer(s) which had been tamped before to achieve
the best reinforcement and highest CBR value
resulting in two patterns of CBR test specimens witha total number of six specimens according to theposition and the type of the geosynthetics used.
The two patterns of the CBR test specimens wereclassified into two groups, in which the first group(pattern I) contained three specimens of one
geotextile layer laid on the surface of the lower soil
layer (lower GTX 1, lower GTX 2, and lower GTX 3)
as shown in Fig. 3. while the second group (patternII) contained three specimens of two geosynthetic

For convenience in drawing CBR specimens, theused geosynthetic products were represented byabbreviations and graphical symbols and described intable 1 as recommended by the International
Geosynthetics Society (IGS) [7].
Table 1. Abbreviations and graphical symbols of theused geotextile, geogrid, and geomat products
Abbrev.
GTX
GGR
GMA

Product
Geotextile
Geogrid
GeomatGraphical Symbol

CBR Test Apparatus and Equipment
In this research, many tools have been used e.g.
CBR stainless steel Mold, and CBR penetration
testing machine, etc.
756

SEE - Bangkok, Thailand, Nov.11-13, 2019layers laid on the surfaces of the upper and the lower
soil layers (upper and lower GGR 1, upper and lower
GGR 2, and upper and lower GMA) as shown in Fig.4.

(No.6, Fig. 5) considering the penetration depths of
0.5 mm, 1.0 mm, 1.5 mm, 2.0 mm, 2.5 mm, 3.0 mm,
4.0 mm, 5.0 mm, 7.5 mm, 10.0 mm, and 12.5 mm.

Fig. 3 Pattern I: three different CBR test specimens of
one geotextile layer embedded on the surface of thelower layer of compacted soil using three different
geotextiles (GTX1, GTX2, and GTX3)

Fig. 5 CBR testing machine and its components
Then the stress (psi) on the piston by dividing theload by the area of the piston was calculated. And agraph for the stress (psi) or load (kN) versus the depthof penetration (inches) relationship was plotted.
The bearing value is the stress (psi) corresponding
to a depth of penetration of the piston of 0.10 in.
(2.54mm). This bearing value is converted to a ratio
by dividing it by 1000 psi, which represents thepenetration resistance of compacted standard crushed
rock. This bearing ratio, which is a fraction, is
multiplied by 100 and reported as the California
Bearing Ratio [9].
In this study, the CBR tests were carried out for
one control specimen and six test specimens with
their repetitions.
The loads were recorded up to a penetration depthof 12.5 mm according to the Japanese Industrial
Standards (JIS-A-1211) [10] and the CBR value wascalculated according to the following equation:

Fig. 4 pattern II: three different CBR test specimensof two geosynthetic layers embedded on the surfacesof upper- and lower-layers of compacted soil using
three different geosynthetics (GGR1, GGR2, and
GMA)
CBR Test Setup and Procedures
In 1930 the California Division of highways, USA
invented the California Bearing Ratio (CBR) test andit has been widely used all over the world to evaluate
the bearing capacity of soils and subgrades since its
invention [8]. And in this research, the CBR test was
performed as follows:
After the specimen had been set up in the moldthen the specimen is placed on the top board of the
CBR apparatus jack (No.7, Fig. 5). The tests wereconducted.
While operating the CBR testing machine, theload (pounds) was measured using proving ring dialgauge (No.2, Fig. 5) versus depth of penetration(inches) of the piston as it is being pushed into the soil
was recorded using penetration measuring dial gauge

𝐶𝐵𝑅 % =

𝐿𝑜𝑎𝑑 𝑆𝑡𝑟𝑒𝑛𝑔ℎ𝑡
× 100
𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝐿𝑜𝑎𝑑 𝑆𝑡𝑟𝑒𝑛𝑔𝑡ℎ(1)

RESULTS AND DISCUSSION
In the present investigation, six types of new
geosynthetics (three basalt geotextiles (GTX1,2,3),
two basalt geogrids (GGR1,2), and one plastic
geomat (GMA)) were embedded inside soil layerswith the purpose of reinforcing the subgrade soil. The
CBR test was used for evaluation of the performance
757

SEE - Bangkok, Thailand, Nov.11-13, 2019of the non-reinforced and reinforced subgrade
specimens. A high CBR value indicates the excellent
quality of the material, although other relevant
parameters may be necessary to re-confirm thematerial’s performance. Typical CBR values range
from less than 5 for soft clays up to 80 for dense sandy
gravel as shown in table 2 [11,12].

In the first group (pattern I) which contains three
specimens, only one layer of geotextile product wasembedded inside the subgrade soil layers forming
three different specimens according to the used
geotextile type which were GTX1, GTX2, and GTX3
on the surface of the lower layer of the subgrade soil
as shown in Fig. 3.

Table 2. CBR values for soils by the unified soil
classification system (USCS) [11].
Soil type
Graveland gravelly soils
Coarsegrained
soils
Sand
and sandy soils

Finegrained
soils

Low
compressibility soils
LL < 50
High
compressibility soils
LL > 50

Field CBR value
GW
GP
GU
GM
GC
SW
SP
SU
SM
SC
ML
CL
OL
MH
CH
OH

60-80
35-60
25-50
40-80
20-40
20-40
15-25
10-20
20-40
10-20
5-15
5-15
4-8
4-8
3-5
3-5

Fig. 6 The most effective position patterns for using
geotextiles and geogrids to reinforce the subgrade soil
respectively [5].
On the other hand, also the second group (patternII) contained three test specimens but in which a
combined layer of geosynthetics (geogrid or geomat)
was embedded inside the subgrade soil layers forming
three different specimens according to the usedgeosynthetic type which were GGR1, GGR2, and
GMA on surfaces of upper and on lower layers of thesubgrade soil as shown in Fig. 4.
The results for the effects of different
geosynthetic types embedded in the effective depths
of soil are depicted and a discussion comparing theresults with the control specimen is presented.

As a result of the research on the influence of theembedding position of geotextile and geogrid (GTX1and GGR1) inside same backfill soil on the CBRvalue conducted by Eltaher in 2019, it was found that
there are effective embedment positions according to
the geosynthetic type to increase the bearing capacity
to its highest values [5].
Also, Eltaher found that the CBR value for thecontrol specimen (soil only) was 47.93% and it wasobserved that while using the geogrid type, thehighest CBR value (74.61%) was reached by using
double layers of GGR1 on the upper-lower layers andwhile using the geotextile type, the highest CBRvalue (59.28%) was obtained by using the subgrade
soil reinforced with one-layer of GTX1 on the lower
soil layer [5].
Considering these results [5], only the mosteffective position patterns for using geotextiles andgeogrids to reinforce the subgrade soil as shown in
Fig. 6 were selected in this research for characterizing
the new geosynthetics (GTX 1, 2, 3, GGR 1, 2 and
GMA). Therefore, two-position patterns forming six
different CBR test specimens of subgrade soil
reinforced with different geosynthetics were tested inthis study to understand their performance response.
Therefore, the types of test specimens in thepresent study were classified into two groups
according to the effective embedding position pattern.

Influence of Embedding Different Geosynthetics
Inside Subgrade Soil on CBR Value
A series of CBR tests were conducted to obtainthe load-penetration relationship of CBR control andtest specimens to understand the Influence ofgeosynthetic type embedded in the effective position
inside subgrade soil on the CBR value.
Influence of reinforcing the subgrade soil with one
layer of basalt GTX1,2, or 3
The CBR test results for the subgrade soil control
and test specimens containing one layer of basalt
GTX 1, GTX 2, and GTX 3 on the lower soil layer all
together are shown in Fig. 7.
From this figure, it can be seen that all curves
follow a typical trend of a CBR test. Also, the resultsof the test specimens especially the woven geotextile
758

SEE - Bangkok, Thailand, Nov.11-13, 2019

GTX1 and GTX2 display higher trends before andafter penetration depth of 2.5 mm than the control
specimen.
The calculated CBR test values for penetration
depths of 2.5 mm in the subgrade soil reinforced with
one layer of GTX1,2, and 3 are given in table 3. From
this table, it can be observed that the CBR values
increase significantly while using GTX1,2, and 3 on
the lower soil layer. As in the GTX2 case, thesupporting force was maximized. The CBR values for
subgrade soil reinforced with one layer of GTX1,
GTX2, and GTX3 on the lower soil layer are 59.28,
69.69, and 64.08% respectively.
The CBR value of the control specimen (soil only)in this research is 47.93%. This means that CBRvalues can approximately 45.4% higher be achievedby embedding the GTX 2 on the lower subgrade soil
layer compared to the CBR value of the control.

comparison to the previous group (Pattern I) of one
layer of geosynthetic (GTX1,2,3), the current CBR
results show higher increments especially while using
planner products (GGR1 and GGR2) on the upperlower layers. The CBR values for a penetration depthof 2.5 mm for subgrade double layers of GGR1,
GGR2, and GMA upper-lower are 74.61, 71.69 and,
66.94% respectively.

Fig. 8 Load penetration curves of control specimen
and three subgrade soil test specimens containing twolayers of GGR1, GGR2, and GMA respectively on
the surfaces of the upper and lower soil layers
Although GGR 2 is stiffer than GGR 1 which may
indicate that GGR 2 might raise the CBR value higher
than GGR 1 would do, it is found that the smaller thegeogrid apertures (as in the used woven GGR1), thehigher the bearing capacity and the CBR value
increases drastically. In contrast, the wider thegeogrid apertures (as in the used woven GGR2), thelower the increment in the bearing capacity.
Table 3 summarizes the CBR values of control
and test specimens with various types ofgeosynthetics. It shows that embedding the ecofriendly basalt geosynthetic (geogrid and geotextile)
and also the plastic geomat inside the subgrade soil atthe effective positions has a significant effect on
improving the CBR value.

Fig. 7 Load penetration curves of control specimen
and three subgrade soil test specimens containing one
layer of basalt GTX 1, GTX 2, and GTX 3
respectively on the surface of the lower soil layer.
Also, it is noticed that the stiffer the geotextile (asthe used woven GTX2), the higher the bearing
capacity and the CBR value increases drastically. In
contrast, the softer the geotextile (as the used
nonwoven GTX3), the lower the increment in the
bearing capacity and therefore the CBR value
increases slightly.

Table 3 CBR values of subgrade soil specimen types
Influence of reinforcing the subgrade soil with twolayers of GGR1,2, or GMA

Specimen typeorlayering pattern

In addition to the CBR control specimen curve,
three load-penetration curves obtained from the CBRtests of the three subgrade test specimens containing
two layers of geosynthetic in which three different
geosynthetics (GGR1, GGR2, and GMA) were laidon the upper and lower soil layers are shown in Fig.8.
The CBR curves for the GGR 1, 2 and GMA
double layer in subgrade soil are more pronounced incomparison to the previous group of single layer GTX.
It is evident that the penetration load increased for thiscase.
The CBR values for the penetration depth of
2.5mm penetration are shown in table 3. In

GTX 1
One layer
test
Lower
GTX 2
specimen
GTX 3
GGR 1
Two layers
test
Upper & lower
GGR 2specimen
GMA
Control specimen (soil only)

CBR
Value
%
59.28
69.69
64.08
74.61
71.69
66.94
47.93

Table 3 could be illustrated by a bar graph tocompare the difference in the CBR values dependingon the geosynthetic type and layering pattern inside
759

SEE - Bangkok, Thailand, Nov.11-13, 2019the subgrade soil where the CBR value is plotted on
the vertical axis and the specimen type is plotted on
the horizontal axis. see Fig. 9.
From Fig. 9, it can be seen that the CBR value of
one layer of GTX1 embedded on the lower subgrade
soil layer specimen has the lowest value, whilst the
specimen of GTX2 flattened on the lower subgrade
soil layer has the highest CBR value among the onelayer GTX pattern. At one-layer geotextile
embedment in the subgrade soil, the maximum
increment in the CBR value was 45.4% in the woven
black geotextile GTX2 lower layer case.
On the other hand, changing the one-layer GTX
pattern into two layers of GGR or GMA pattern alters
the behavior of the ground conspicuously. It isobserved that the GGR1 upper-lower double layer inthe subgrade soil gave the highest CBR value
compared to the other two double-layer cases, whilst
the GMA upper-lower double-layer showed thelowest CBR value in this pattern. In the two layers
geosynthetic embedment case, the maximum
increment in the CBR value was 55.7% in the wovenbasalt geogrid 1 upper lower layers case.

subgrade soil layers has a significant effect on
improving the CBR value. Since it was found that the
CBR value increases by a range from 24 to 55 % fromthe CBR value of the control specimen according to
the used geosynthetic type.
It could also be concluded that there are effective
embedment positions for these geosynthetics
according to its type to increase the bearing capacity
where the highest CBR value (74.61%) was reached
by using double layer of GGR1 on the upper-lower
layers and the lowest CBR value (59.28%) was
obtained by using the subgrade soil reinforced with
one-layer of GTX1 on the lower soil layer. It was alsointeresting to note that the double geosynthetic layers
patterns are not as beneficial as originally expected
when compared to a single lower layer in the case ofusing GTX2. This conclusion has certain economic
implications for optimizing design and construction
using these new geosynthetics.
Practically and economically, it is recommended
to use the pattern of the GTX2 lower layer for thefield application. Even though the GGR1 two layers
upper-lower pattern gives the highest CBR value, theGTX2 lower layer is more effective for field
application due to materials supplied and economic
reasons. It has a benefit on the budgeting aspect for
design and construction when using this geosynthetic.
ACKNOWLEDGMENTS
Thanks to Japan International Cooperation
Agency (JICA), for collaboration with International
Environment Conservation Lab, Graduate School of
Bioresources, Mie University, School of Civil
Engineering and Surveying, University of Southern
Queensland, and Tsuchiya TSCO Co., Ltd. for theopportunity which they gave me to proceed in thisresearch.

Fig. 9 Comparison between CBR values of control
and test specimens.

REFERENCES[1] Hossain M.B., Sakai T., and Hossain M.Z.,
Evaluation of Sand/Geosynthetic Interface
Behavior for Earth Reinforcement. International
Journal of Geosciences Engineering, Vol. 7,
No.3, 2013, pp.452-465.
[2] Shukla, S.K., Discussion of Applications ofgeosynthetics for soil reinforcement by M.I.M.
Pinto, Ground Improvement, 7, 2004, pp. 61-72.
[3] Choudhary A.K., Jha J.N., and Gill K.S., A
Study on CBR Behavior of Waste Plastic Strip
Reinforced Soil. Emirates Journal forEngineering Research, 15 (1), 2010, pp.51-57.
[4] Eltaher M., Hossain M.Z., Shiau J., and Takami
H., Ground Improvement Using Geosynthetics
A Literature Review. Proceedings of the 5thInternational
Conferenceon
Science,Engineering & Environment (SEE), Bangkok,
11-13 November 2019, an accepted paper.

It was interesting to note that the geosynthetics(GGR1,2, or GMA) double layers embedded inside
the subgrade soil layers are not as beneficial asoriginally expected when compared to a single GTX2
lower layer. Indicating that there is no benefit in using
a double GGR1, 2, or GMA layer for the purpose of
subgrade soil reinforcement in constructions. In
general, even though the double layer gives thehighest CBR values, the single layer is more effective
and recommended for field application due toeconomic reasons where it has the benefit on thebudgeting aspect for design and construction.
CONCLUSIONS
Based on the above study, it can be concluded thatembedding of these new types of eco-friendly basalt
geotextiles, geogrids and the plastic geomat inside the760

SEE - Bangkok, Thailand, Nov.11-13, 2019[5] Eltaher M., Hossain M.Z., Shiau J., and Takami
H., Influence of Embedding Position on The
Performance of The Basalt Geosynthetics.
Proceedings of the 9th International Conference
on Geotechnique, Construction Materials andEnvironment (GEOMATE), Tokyo, 20-22
November 2019, an accepted paper.
[6] Basalt Fiber Products Report, Tsuchiya TESCO
Co., Ltd., 2nd Ed., 2018, pp. 1-15.
[7] Recommended Descriptions of Geosynthetics
Functions, Geosynthetics Terminology, andGraphical Symbols, International Geosynthetics
Society, 5th Ed. 2009, pp. 1-31.
[8] Hossain M.Z., and Sakai T., The Effectivenessof Nominal Dosage of Ordinary Cement on
Strength and permeability of Clay Soil, Journalof Japanese Society of Soil Physics, No.110,
2008, pp.25-35.
[9] Yildirim B. and Gunaydin O., Estimation of
California Bearing Ratio by Using Soft
Computing Systems, Journal of Expert Systems
with Applications, Vol.38, 2011, pp: 6381-6391.
[10] Test Method for the California Bearing Ratio
CBR of Soils in Laboratory, Japan Industrial
Standards Committee (JIS-A-1211), 2009.
[11] Yoder E. J., and Witczak M.W., Principles ofPavement Design. John Wiley and Sons, Inc. 2ndEd., 1975.
[12] Ekeocha N.E., and Egesi N., Evaluation of
Subgrade Soils using California Bearing Ratio(CBR) in Parts of Rivers State, Journal ofApplied Sciences Environmental Management,
Vol.18, 2, 2014, pp.185-187.

761

Environment763

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

A STUDY ON HUMAN DAMAGE IN EVACUATION FROM TSUNAMICONSIDERING STREET-BLOCKADES CAUSED BY
DESTROY OF BUILDINGS

1

Ken-ichi Fujita1, Harumi Yashiro2
Faculty of Engineering, Nagasaki Institute of Applied Science, Japan;
2
School of Systems Engineering, National Defense Academy, Japan

ABSTRACT
Damage estimation and disaster prevention plan for a Nankai megathrust earthquake which occurrence isassumed in the future have been formulated cabinet office of Japan based on lesson learned from the huge humandamage caused by the tsunami of The Great East Japan Earthquake in 2011. Damage estimation for earthquake
and tsunami is usually evaluated independently. For the damage estimation by tsunami, the human damage inevacuation from tsunami has been carried out. However, any street-blockades have not been considered. Whenevacuation routes are changed by the street-blockades, configuration of the human damage in evacuation fromtsunami seems to be different in no street-blockades. This study presents an evaluation method of human damage
in evacuation from tsunami considering street-blockades using area-wide mesh. The author’s method considering
variances of tsunami run-up speed and walking speed is used to the evaluation. Moreover, the difference inconfiguration of the human damage by consider the street-blockades and no blockades is discussed.
Keywords: Tsunami evacuation, Human damage, Street-blockade, Human damage probability, Area-wide meshhuman damage in evacuation from a tsunami seems
to be different in no street-blockades.
This study presents an evaluation method of
human damage in evacuation from tsunami
considering street-blockades by destroy of buildings.
Area-wide mesh is used to the evaluation of thehuman damage. The author’s method [4]-[6] for thehuman damage taking account of variances oftsunami run-up speed and walking speed is also used
to the evaluation considering the street-blockades.
Moreover, the difference in configuration of thehuman damage between the street-blockades and nostreet-blockades by using the evaluation method.

INTRODUCTIONIN
In disaster prevention planning for large scaled
natural disasters such as mega-class earthquake,tsunami and eruption, estimation of buildings damage
and human damage is extremely important. Damage
estimation for the natural disaster in cabinet officeand local governments of Japan has been usually
evaluated independently for each disaster [1], [2].
Using the damage estimation results, disasterprevention planning for both structural measures andnon-structural measures are projected.
The disaster prevention planning for tsunami areas follows; construction of tide embankment,
relocation to higher ground of town, education on
evacuation and so on. Evacuation planning fromtsunami is especially important item for tsunami
disaster prevention. Evaluation of human damage fortsunami is carried out for evacuation action to safetyarea. In evaluation of the human damage, difference
between evacuation time and tsunami arriving time toevacuation facilities is usually used. In evaluating of
human damage in evacuation from tsunami, the effectof damage of buildings by earthquake before arriving
tsunami has not been considered in many studies anddamage estimation. In evacuation planning fromtsunami, to consider street-blockade by destroy ofbuildings, fallen down of street walls and fire causedby large earthquakes becomes important. Streetblockade has been considered to lifesaving activities
and fire-fighting in the disaster estimation for large
earthquakes [3]. When street-blockades are causedchange of evacuation routes, configuration of the

EVALUATION FLOW OF HUMAN DAMAGE
The area-wide mesh is used to the evaluation of
the human damage. Population composition, height
above sea level, tsunami inundation depth, seismic
intensity, street-blockade ratio, and evacuation
awareness are set up for each mesh based on a realarea data. The population composition and the height
above sea level of GIS (Geographic Information
System) data are used.
Evacuation route from an evacuation mesh to an
evacuation facility is defined as the route along themesh. Evacuation distance including difference ofelevation between mesh is assumed to be 1.5 times oflength of plane distance. The human damage
probability is evaluated by using relation between
evacuation time and tsunami arriving time after
earthquake occurrence. The human damage ratio to764

SEE - Bangkok, Thailand, Nov.11-13, 2019

GIS

Scenario earthquake

Seismic hazard

Area-wide mesh

Tsunami hazard

Completely destroyed ratio andpartially destroyed ratio of buildings

Population and elevation

Tsunami inundation area

Street-blockage ratio
Effective width of street

Evacuation mesh
Decrement ratio of walking speed
Conditions of evacuation

Evacuation time

Tsunami arriving time
Tsunami fragility on
human damage

Damage probability

Survive

Evacuation completion

DamageEvacuation completion

Evacuation incompletion

Fig.1 Evaluation flow of human damage in evacuation from tsunami
tsunami inundation depth in each mesh can beobtained by the tsunami fragility curve [7]. The streetblockade is evaluated by the fragility of buildings forearthquakes [8]. Decrement of the walking speed isdetermined by effective sidewalk width which
passing is possible. From the above, the evaluation
flow on the human damage can be shown in Figure 1.
The following assumptions are used in this study.
1) The human damage is counted when a person iscaught up with tsunami.
2) The evacuation is only walk. The walking is only
permitted on sidewalk.
3) The evacuation facility is designated for each
evacuation mesh. The facilities are not damaged toearthquakes.
4) The street-blockades are occurred by destroy ofbuildings by large earthquakes5) The evacuation direction is not toward to coast.
6) In emergency, to across any railroad crossing is
prohibited because crossing gates keeps down.

run-up speed, respectively. The variation of thetsunami run-up speed is considered for evaluation of
the tsunami arriving time. The tsunami run-up time
can be obtained by the relation of the run-up speed
and the minimum distance between coast andevacuation facilities. The mean value of the run-up
speed can be determined by the tsunami inundation
depth [9]. Average tsunami inundation depth from thecoast to the evacuation facilities is considered in thisstudy. The standard deviation of the run-up speed isevaluated by the geometric standard deviation [10]which indicates the adaptation between tsunami
height marks on land and tsunami simulation results.
In this study, the reliability evaluation method forstructures [11] applied to the evaluation of the humandamage. The evaluation equation of the humandamage can be provided the following equation.

PR  1  ( P /  P )(1)

where,  is the standard normal distributionfunction with the mean value 0 and the standard
deviation 1. The function of  is also shown in
Figure 2.  P and  P are provided by the following
equations, respectively;

HUMAN DAMAGE PROBABILITY
Damage Probability of Human in Evacuation
The human damage probability is evaluated by
the Author’s method [5], [6]. The probability isdefined by a function of evacuation time and tsunami
arriving time after earthquake occurrence. The
evacuation time and the tsunami run-up time fromcoast to evacuation facilities are assumed to follow
the normal distribution. The tsunami arriving time isdivided into the time of tsunami propagation and runup. The evacuation time and the tsunami run-up time
can be evaluated from walking speed and tsunami P  T   E(2)

 P   T2   E2

(3)

where,  E and T are the mean value of total
evacuation time and the tsunami arriving time toevacuation facilities after earthquake, respectively, E and  T are the standard deviation of  E and T, respectively.
765

SEE - Bangkok, Thailand, Nov.11-13, 2019

1

1.0

0.8

Destruction ratio

1-PR

ft(t)

fe(t)

μE

fe(t)：probability density
function ofevacuation time.
ft(t)：probability density
function of tsunami
arriving time.

μT

0

Wooden (Completely destroyed)
non-wooden (Completely destroyed)
Wooden (Total destroyed)
non-wooden (Total destroyed)

0.6

0.4
0.2
0

5.5

μP/σP

6
6.5
Instrumental seismic intensity

7

Fig.3 Fragility curves of buildings [8]Fig.2 Probability function of human damage
impassable for less than 0.5m. The Deterioration ratio
Rw may be evaluated by the following equation;

Street-Blockage by Destroy of Buildings

1.0(1.5m  Wes )
Rw  0.8Wes  0.2 (0.5m  Wes  1.5m)
0(Wes  0.5m)
In this study, the street-blockage is assumed to becaused by completely destruction and partial
destruction of buildings. The destroy ratio can beobtained by using fragility of buildings for wooden
and non-wooden structures shown in Figure 3 [8].
The partial destruction ratio is also obtained by adifference completely destruction number and partial
destruction number of buildings. The street-blockage
ratio is evaluated for each mesh by using thecompletely and partially destruction ratios. Effective
sidewalk width Wes by the street-blockage of eachmesh can be obtained from the following equation;Wes  (1  Rd )Ws

The walking speed in evacuation is evaluated bymultiplying Rw the walking speed in normal period.
EVALUATION OF HUMAN DAMAGE
Evaluation Conditions
The human damage in evacuation from tsunami
using the method in this study is discussed underconditions of street-blockage and no street-blockage.
The area-wide mesh and population distribution oftarget area [13] is shown in Figure 4. The mesh size
is 250m x 250m and the population is 23,345.
Tsunami inundation depth and seismic intensity
used in this study are based on a Meio type scenario
earthquake (moment magnitude scale, Mw 8.4) and a
scenario earthquake along the Miura peninsula faults(Mw7.0), respectively. To investigate the maximum
case of the human damages considered the effect of
the street- blockage, two types scenario earthquakes
which are the maximum case of the damage(4)

where, Ws is the sidewalk width in normal period,
Rd is the street-blockage ratio which given for rangeof Ws represented by the following equation;

 1.28DrbRd  0.604Drb
0.194Drb(Ws  3m)
(3m  Ws  5.5m)(5)(5.5m  Ws  13m)

where, Drb is the destruction ratio represented by
the following equation [3];Drb  Dc Dp / 2

(7)

16

(6)

223

274

127 490

where, Dc and D p are the completely andpartially destruction ratio of buildings, respectively.
Deterioration of the walking speed is assumed to
be proportional to the effective width. The
deterioration ratio of the speed maybe expressed byusing consideration of the decrement ratio of walking
speed of crowded with people [12]. In this study, thesidewalk width is assumed to be proportional to thecrowded with people per area. In evacuation, no
deterioration of the walking speed is considered forWes more than 1.5m, the speed is linearly deteriorated
with proportional to Wes within 0.5m to 1.5m and64 597518 645 438
705 518326 168
410 473 408 526 603 312 459

752 863 640 384 499 684 726 660 339 464 538
542 347 730 491 652 617 506
87 642 441 499 590
350 516 428
142 331
63 2990 239

Number: Population: Evacuation facility: Evacuation upland: Separated line of evacuationroute by railroad

Fig.4 Area-wide mesh
766

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 Population ratio for evacuation awarenessEvacuation immediately
Urgency evacuation
after earthquake
after work
(Weak awareness)(Strong awareness) (Weak awareness)
80%
10%
5%

Evacuation
awareness
Strong

No evacuation(Weak awareness)
5%

Average

50%

25%

15%

10%

Weak

15%

35%

30%

20%

Buildings and roads are uniformly allocated toeach mesh because of the evaluation to be
simplification. Total number of buildings in the area
is 9,256 (wooden: 6,664, non-wooden: 2,592). Road
area including sidewalk per mesh is 7,375m2 which is
11.8% of one mesh area.
Population ratio of the evacuation activity is
divided into four type; evacuation immediately,
evacuation after work, urgency evacuation and noevacuation [14]. The population ratio is set up by
combining the following three types evacuation
awareness; strong awareness, average awareness andweak awareness. The evacuation awareness and thestart time of evacuation after earthquake occurrence
are shown in Tables 1 and 2, respectively.
The mean value and standard deviation ofwalking speed is 1.34m/s and 0.167m/s in normal
period [15]. In addition, the mean value isdeteriorated by the effect of the street-blockade andthe standard deviation is assumed to be not variable
for the blockade in this study.

Table 2 Start time of evacuation after
earthquake occurrence
Evacuation
Evacuation
immediately after immediately after
an earthquake
finished the
5 (min.)Urgency
evacuation
tsunami arrivingtime

15 (min.)

0.7
1.0

1.0

2.5 1.6

3.5 1.6

1.6 2.5 2.5

2.5 2.5

3.5 3.5

3.5 3.5 2.5 2.5 0.7 0.0 0.0

4.5 4.5 3.5 3.5 4.5 3.5 2.5 2.5 0.7 0.0 0.0
6.5 4.5 4.5 4.5 4.5 4.5 2.5
7.5 7.5 5.5 4.5 4.5
7.5 6.5 5.5
7.5 6.5
5.5 5.5

Number: Tsunami inundation depth (m)6.5 6.5

Evaluation Results without Street-Blockage
The human damage for several evacuation
awareness under no street-blockade condition isshown in Figure 7. The large number of the damageis also shown with deep color. The number of thedamage with the strong awareness is the minimum.
The damage near the evacuation area is less than thatof the other mesh. The damage on mesh of the coastand the railroad crossing becomes large.
The number of the human damage is shown in
Table 3. The human damage with the strong
awareness decreased to 22% of the damage with the
weak awareness. The evacuation awareness is large
influence to decrease the human damage.

Fig.5 Tsunami inundation depth
6+
6+

6+ 6+

6+ 6+

6-

6-

6-

6-

6+ 6+ 6+ 6+ 6+ 6+ 6+

6-

6-

6+ 6+ 6+ 6+ 6+ 6+ 6+ 6+ 6+

6-

6+ 6+ 6+ 6+ 6+ 6-

6-

6+ 6+ 6+ 6+

66-

66-

6-

6-

6+ 6-

6-

6-

6-

6+

Number: Seismic intensity

6-

Evaluation Results with Street-Blockage
The street-blockages ratio by destroyed ofbuildings is shown in Figure 8 The ratio becomeslarge for strong seismic intensity. In addition, thenumbers of destroyed buildings simulated in thisstudy are 1,801 for completely destroyed and 1,114
for partially destroyed. The decrement ratio of thewalking speed by the blockade is shown in Figure 9
The number shown in the figure represents thedestined walking speed ratio for each evacuation

Fig.6 Seismic intensity
estimation in the target area [13] is selected. Tsunami
inundation depth and seismic intensity are shown in
Figures 5 and 6, respectively. The maximum tsunami
height is 8.94m. Though tsunami arriving time tocoast is 59 minute [13], to clear the difference ofevacuation awareness, tsunami arriving time in thisstudy is set to 20 minute.
767

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 3 Total number of human damage

1
16

17

11 40

5 34

37 62 36

25

66 79

9

Damaged population (persons)Evacuation
awareness

No blockage

Blockage

34 36 34 76 76

00Strong

2,631

4,181

114 158 125 49 49 128 119 98 30

00Middle

6,543

8,401

Weak

11,997

13,85759 35 140 49 64 60 48
18 69 45 61 61
70 95 46
27 35

0.60

12 29

Damaged population: 2,631

0 44

1.00

0.60

0.60 0.60

0.60 0.60

1.00 0.87 0.80(a) Strong awareness1.00 0.60

1.00 1.00

0.60 0.60 0.80 0.60 0.60 0.60 0.60

1.00 1.00 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60

20.80 0.60 0.60 0.60 0.60 0.60 1.00

39

41

0.73 0.60 0.60 0.60 0.60

26 99

11 84

92 154 89

0.87 0.80 1.00

62 22

164 197

1.00 1.00

84 89 84 190 188

00284 395 312 123 123 319 296 245 74

001.00 1.00
1.00 1.00

Number: Destined walking speed ratio foreach evacuation mesh population

147 87 349 121 160 148 120
44 173 111 153 153

Figure 10 Decrement ratio of walking speed bystreet blockade

173 237 114
67 87
29 72

Damaged population: 6,543

The number of the human damage for theblockade is also shown in Table 3. The damage isincreased to 1.58, 1.28 and 1.16 times for the strong,
middle and weak awareness, respectively. To
consider the decrement of walking speed by theblockage is important for the human damage
estimation from tsunami. Enhancing of evacuation
awareness as well as seismic strengthening ofbuildings become the one way to decrease the humandamage in evacuation.

0 110(b) Middle awareness
4
77

82

51 19721 167175 292 177
326 339

123 44164 178 163 334 342

00500 672 530 228 245 545 509 428 14800

CONCLISIONS

287 174 596 241 320 296 234
74 337 221 285 285

The evaluation method of the human damage
considering the street-blockade by destroy ofbuildings is proposed. The human damage inevacuation from tsunami is discussed for the streetblockade and no street blockade conditions. The
following conclusions can be drawn.
1) The human damage under the street-blockade
becomes large compared to that of no streetblockade because of decrement of the walking
speed by the blockade.
2) To consider the effect of the street-blockage inevacuation planning is important.
3) The human damage in evacuation from tsunami
can be decreased by enhancing evacuation
awareness for evacuation and education on
disaster prevention.
4) A Seismic strengthening of buildings is the one
way to decrease the street-blockage for large
earthquakes.

294 408 223
114 171
49 141

Damaged population: 11,997

0 186(c) Weak awarenessFig.8 Human damage distribution without streetblockademesh population. The ratio is variable with the scaleof the blockades.
The human damage for several evacuation
awareness under street-blockade condition is shownin Figure 10 The human damage becomes large inspite of the evacuation awareness compare to that of
the no blockage. The number of the damage with thestrong awareness is the minimum.
768

SEE - Bangkok, Thailand, Nov.11-13, 2019

Inundation Forecast, 2012. (in Japanese)[3] Cabinet Office, Damage Estimation of Nankai
Trough Earthquake (2st. Report), 2013. (inJapanese)[4] Yashiro, H., Fujita, K., Evaluation Method of
Evacuation Safety Performance for Tsunami
using Area-Wide Mesh, Second European
Conference on Earthquake Engineering andSeismology, 2014, CD-ROM.
[5] Fujita, K., Yashiro, H., A Study on the Number ofInstalled and Installation Location of Tsunami
Evacuation Facilities Using Area-wide Mesh,
Journal of Japan Society of Civil Engineers, Ser.
F6 (Safety Problem), Vol. 72, No.2, 2016,
p.I_151-I_156. (in Japanese)[6] Fujita, K., Yashiro, H., Evaluation of Human
Damage in Tsunami Evacuation Considered the
Variance of Walking and Tsunami Run-up Speeds,
Internet Journal of Social Management Systems,
Issue 11 Vol.1, sms17-8200, 2017, pp.213-223.
[7] Koshimura, S., Namegawa, Y., Yanagisawa, H.,
Fragility Functions for Tsunami Damage
Estimation, Journal of Japan Society of Civil
Engineers, ser. B, Vol.65，No.4，2009, pp.320331. (in Japanese)[8] Midorikawa, S., Ito, Y., Miura, H., Vulnerability
Functions of Buildings Based on Damage Survey
Data of Earthquake after the 1995 Kobe
Earthquake, Journal of Japan Association for
Earthquake Engineering, Vol.11, No.4, 2011,
pp.34-43. (in Japanese)[9] Shuto, N., et al., eds., Encyclopedia of Tsunami,
Asakura Publishing Co., Ltd., 2007. (in Japanese)[10] Aida, I., Simulations of Large Tsunamis
Occurring in the Past off the Coast of the Sanriku
District, Bulletin of the Earthquake ResearchInstitute, Univ. of Tokyo, Vol.52, No.1, 2009,
pp.71-101. (in Japanese)[11] Hoshiya, M., Ishii, K., Reliability Based Design
for Structures, Kajima Institute Publishing Co.,
Ltd., 1986. (in Japanese)[12] Cabinet Office, Simulation results on returnhome action, 2007. (in Japanese)[13] Zushi City Homepage, http://www.city.zushi.
kanagawa.jp/[14] Ministry of Land, Infrastructure, Transport andTourism, Present State Survey in Tsunami
Affected Area of the Great East Japan
Earthquake (3rd. Report), Results of Actual
Survey on Tsunami Evacuation (Preliminary),
2011. (in Japanese)[15] Matsumoto, N., Kiyota, S., Ito, M., Relationshipbetween the Characteristics of Streetscape andWalking Speed, Journal of Architecture andPlanning, Vol.74, No.640, 2009, pp.1371-1377.
(in Japanese)

1
16

17

11 42

9 35

37 77 38

25 11

66 79

57 48 44 195 156

00

114 158 391 75 81 295 323 206 36

00

90 53 325 80 71 97 48
25 123 67 95 95
75 101 46
27 35

Damaged population: 4,181

12 29
0 44

(a) Strong awareness
2
39

43

28 10418 87

92 192 95

62 26

164 197

141 120 110 291 290

00284 395 479 185 202 429 438 342 89

00

224 131 470 198 177 242 120
48 307 166 233 233
177 252 114
67 87

Damaged population: 8,401

29 72
0 110

(b) Middle awareness
4
77

85

54 20428 172175 346 185

123 49326 339244 221 199 405 447

00500 672 582 314 355 587 572 502 16900394 235 641 350 343 427 234
75 525 299 395 395
295 429 223
114 171
49 141

Damaged population: 13,857

0 186(c) Weak awarenessFig.10 Human damage distribution with streetblockade

REFERENCES[1] Cabinet Office, Damage Estimation of Nankai
Trough Earthquake (1st. Report), 2012. (inJapanese)[2] Kanagawa Prefecture, Manual of Tsunami769

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DEVELOPING AGE-FRIENDLY CITY: CASE STUDY FROMDEPOKFatmah Fatmah
Faculty of Public Health, Universitas Indonesia
ABSTRACT
Depok, as one of the largest cities in Indonesia, has great potential to be an Age-Friendly City (AFC).
Before the formation of AFC is established, eight dimensions of AFCs had been studied by the WHO in
2013, but since 2013, these dimensions have not been assessed. The study aimed to assess the
preparedness of Depok to be an AFC with a qualitative approach from the stakeholders’ point of view.
This study used a qualitative design involving 50 informants through in-depth interviews and Focus
Group Discussion (FGD) techniques using purposive sampling. The findings indicate that Depok wasdeemed not yet prepared to be an AFC due to an abundance of infrastructure deficiencies. There were notmany changes in the facilities, such as infrastructure improvements in AFC indicators and existing
Regional Regulations of AFCs, except for buildings and open green spaces. In general, Depok still needs
time to achieve the AFC where is the community will have a good place to live, grow, and age in it.
Keywords: Age-Friendly City, older people, buildings and open green spaces, indicator, infrastructure
seen with the difficulty that older people have inaccessing public facilities. A concrete example
is the road to the bus stop, which is built at avery high and steep elevation and is extremely
difficult for older people to access. There arestill many multiple-story buildings that do notprovide lifts and force people to climb stairs.
There are eight areas that require special
treatment for older people, which are health,sociallife,
environment,
informationcommunication, infrastructure, transportation,
law, and art. In Indonesia, the Surabaya City
Government, the capital of East Java Province
in Indonesia, has local regulations for theservice and empowerment of older people. 6 In
comparison, Depok, as a suburban city in WestJava Province in Indonesia (Figure 1, 2), hasbeen singled out by regional leaders and leadersof care organizations for older people who wantto achieve an AFC.
Depok has a growing population of older
people. This population is currently estimated tobe 114,060 people out of 1,570,949 people.
Depok has a life expectancy of 73 years.7
Therefore, Depok has a great opportunity to
become an AFC because of the implementationof the integrated service posts for older people(there are nearly 500 integrated service posts forolder people). Currently, there is no pension
plan, and there is an insufficient social
infrastructure and not enough facilities geared
towards older people. The mayor of Depok has
supported the existence of Depok as an AFC.
One indication that Depok is ready to be anolder people-friendly city is the construction ofa special crossing in front of both the Bhakti

INTRODUCTION
Increased life expectancy is one of theconsequences of development and has an impact
on the increasing number of older people inIndonesia. The increase in the population ofolder people must be balanced with efforts toachieve active ageing goals.1 Active ageing
consists of three main pillars, namely, income
security, health, and space to participate. These
three pillars are the basis for the formation of anolder people-friendly city. The WHO developed
eight domains of Age-Friendly Cities (AFCs):
housing, transportation, outdoor spaces andbuildings; community support and healthservices; communication and information; civic
participation and employment; respect andsocial inclusion; and social participation. 2 Somestudies on developing AFCs in Brussels,
Manchester, Australia, and Malaysia described
their preparedness and implementation. 3-5 A
study on AFCs from community stakeholders inBrussels and Manchester identified key
elements and resources needed for an AFC.
Another study in Australia mentioned that the
impact of AFCs on government mainstream
actions has been limited by uncertain politicalcommitment and growing fiscal austerity. A
study in Malaysia stated that public
transportation and housing, healthcare services,and older people-friendly outdoor spaces andbuildings have a role in building an age-friendly
environment.
To support the formation of an older peoplefriendly society, it is necessary to design anAFC, which Indonesia still lacks. This can be

770

SEE - Bangkok, Thailand, Nov.11-13, 2019

Yudha Hospital and the Depok Governmentbuilding. The crossing is equipped with a button
to activate a red light if an older people needs tocross the road. In addition, Depok has 344
integrated development posts (the integrated
service post for older people) spread across six
sub-districts.7 Depok has great potential to be an
Age-Friendly City (AFC) considering the
successful implementation of the integrated
service posts for older people and the support of
the Depok Government for declaring Depok an
AFC. However, various preparations need to be
made.
Before the formation of DAFC (Depok AgeFriendly City), two previous studies establishedeight indicators of an AFC in 2010 and 2014. 8-9
These two studies found that the majority of thecommunityand government stakeholders considered Depok to
be ready to become a DAFC as long as it was
supported by a budget and programmesthat prioritize the interests of older people, as well as
good coordination among the Depok Government,
the community and related institutions. As a resultof these stipulations, Depok is not yet ready to fully
assume the status of an AFC. The existenceof Regional Regulations, laws and policies
that regulate the formation of the Depok Local
Committee of Older people can indirectly accelerate
the realization of DAFC.
With reference to the findings of the two
aforementioned studies, there should be a study
to evaluate the extent of preparedness of Depok
towards becoming an AFC from 2010 to thepresent based on the eight indicators of an AFC.
It is expected that this study can identify theeight indicators of DAFC based on a qualitative
assessment
bystakeholders
and related
agencies. The objective was to assess Depok
preparedness towards becoming an AFC witha qualitative approach from the viewpointof stakeholders.

have a position as a chairman, operational
manager, and head of division who are
implementing the program for older person.
They were recruited by the research teamthrough formal invitations. The research teammade a list of some private and government
institutions associated with programmes forolder people. Then, the research team visitedtheir offices to conduct in-depth interviews. The
key informants from the 4 FGDs (n = 40) wererecruited on the basis of their institutional rolesin empowering programmes and having policies
and laws geared towards older people. The
research team recruited the informants bysending formal invitations requesting theirattendance at the CAS UI office in Depok todevelop schedules for the FGDs. The inclusion
criteria for the informants were those fromprivate and/or government institutions who were
either male or female, who were involved
directly as stakeholders and who acted inconjunction with older people, male or female.
There were no sample sizes calculated since thestudy applied a qualitative approach. The
exclusion criteria were informants who did notattend the FGD scheduling when invited, who
did not fully attend the FGDs due to theirbusiness, and who cancelled the interview. Each
FGD took 90 minutes and each indepth
interview will be finished in 60 minutes. The
research team acted as the FGD facilitator andindepth interview enumerator who well-trained
before.
Data Collection
Qualitative data collection involved theresearch
team
memberasthefacilitator/moderator of the FGD and organizerof the in-depth interviews. Recruitment of
informants was accomplished through purposive
sampling with the help of a research secretary
who followed-up on confirmations. In-depth
interviews were conducted by direct visits to theinformants’ offices after an appointment was
made. The research goals and purpose of thestudy explained by the research team at FGD
and indepth interview sessions. The questions
asked in the FGD covered the following: thedefinition of an AFC; the description of andopinion about the cleanliness of open spaces andbuildings; the housing conditions; and thecondition of civic participation and employment
for older people. In-depth interview guidelines
covered the AFC policies and programmes andthe facts and real status of the eight dimensionsof the AFC determined by the WHO. The FGDs

METHODS
Design Study and Subjects
The study utilized a qualitative approach byusing 10 in-depth interviews with 10 key
informants in policy and practices and 4 groupsof Focus Group Discussion/FGD (Figure 3).
The ten informants for the indepth interviews
came from private sectors (lapaklansia, Depok
Industrial Chamber of Commerce, politicalparties, The Indonesian Businesswomen Bondof Depok Branch, Depok Center of Small andMedium Enterprises, and Head of Depok
Central Family Welfare Program Team). They

771

SEE - Bangkok, Thailand, Nov.11-13, 2019and in-depth interview guidelines werevalidated in a previous study in 2013.9
To ensure validity of research, a well-trained
and skilled moderator/facilitator was chosenfrom the research team. Another way topromote internal validity (credibility) was toemploy triangulation by using several
moderators
withdifferentscientificbackgrounds and multiple individuals analysing
the same data. Method triangulation through
FGD and in-depth interviews was also used in
the study to increase internal validity.
Triangulation method has objective to eliminate
or reduce biases and increase the validity of thestudy. Triangulation can be used to improve thestudy validity by confirming the analysis resultswith other methods, such as open or structured
interviews, observation, or any alternate
research method.10
Variation of participants selection fromdifferent position such as the cadres ofintegrated service post of older person,
community health centre staffs, sub-district
office staffs, and community/organization inolder persons was one of the efforts to establish
the external validity.
Discussions were held at the Centre for
Ageing Studies UI office in Depok. The
independent interview process was conductedby the researcher at the informants’ offices. All
informants were given verbal explanations
about the research objectives and data collection
procedures. The research team collected all
informed consent from each informant in the
FGDs and in-depth interviews. Informants were
provided with local transportation afterparticipating in the study. All FGDs and indepth interviews were audiotaped andtranscribed, and the quality was confirmed bycomparing the transcriptions with the audio
recordings by the moderators of the researchgroup.

Socio-demographicof Informants

Characteristics

Table 1 illustrates the socio-demographic
characteristics of the informants, including age,sex, final education, and employment status.
The older people (more than 60 years old)comprise one-third of the pre-older people agegroup (less than 60 years old). The proportion of
female informants was four times greater thanthat of male informants. More than threequarters of all informants graduated fromcolleges and universities. Some informants evenpossessed masters (10%) and doctoral degrees(0.4%), and none had a low level of education(0%). The majority of informants worked as
civil servants (24%) and private employees(38%).
Perceptions of Age-Friendly Cities and DAFC
Policies
Generally, most informants had heard about
AFCs and the DAFC. All the integrated service
posts for older informants had heard the term
AFC. In their view, an AFC took into accountaspects suchas thehealthof olderpeople, facilities for older people such as parks,
easy access to health care, absence of neglect,availability of special lines in the sub-districtlevel community health centres, providing
priority necklaces for older people in district
health centres since 2016, special roadcrossings, elder care, handrails in offices, andslip-resistant flooring. An older people-friendly
city is a city that can support the desires andneeds of older people.
Most of the informants stated that an AFC(specifically for older people) means a cityin which security and comfort are provided forolder people and in which their desires and needs
are understood. This could be seen fromthe availability of facilities and infrastructure that
support the comfort of older people andprovide special treatment for them given thelimitations they encounter in some of theiractivities. However, an older people-friendly city
has not become a priority because the priority is a
Depok Healthy City, Depok Child-friendly City,and Depok Cyber City.
Nonetheless, the development of andprocess towards an AFC continues to this day. Whatmight hamper the formation of DAFC is theabsence of data collection on the number ofolder people and their socio-demographic
characteristics
by
the
Depok
SocialService Office. Almost all informants from theData Analysis
Content analysis was used to analyse theinformation collected from all informants. Three
researchers performed the qualitative analysis(F, VPD, and Y). They read and checked thetranscription several times individually andcreated a single coding for the themes agreed
upon. Matrix analysis was performed tosummarize the findings from the two methods.
An ethical review license for this study was
obtained from the Faculty of Public Health,
Universitas Indonesia.
RESULTS

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SEE - Bangkok, Thailand, Nov.11-13, 2019

political parties said that they did not know
about DAFC. They were only familiar with the
Depok Child-friendly City programme. The
existence of the integrated service posts forolder persons at the local level, such as the freeof-charge medical examination
for
older
people, showed that the government of Depok
had some active older people programmes.
The older person friendly city is a city thatcan support the desires and needs of the older
person so that the community's stigma about theolder people can be changed to good andpositive views (older people NGO figure). Yes,
Depok Aged Friendly City has no older person
feel set aside, still able to be productive, feelthey are still being used, and there are noneglected older person. Community healthcenters have a special counter for older person(the integrated service post cadre)in synergy with the concepts of a Depok Cyber
City, Depok Healthy City, and Depok Childfriendly City. In addition, the Mayor Regulation
has been published regarding the Realizationof DAFC.
There were several efforts from the Depok
Government in cooperation with the Depok
Local Committee of the Older People. Staff
members
weresent
directly
to the village level to socialize regarding DAFC.
An informant suggested that DAFC be projected
as a pilot project because the characteristics ofthe region were different. Each region would bebetter prepared if it adjusted to the conditions
and needs of each individual territory. Previous
surveys were necessary to identify older people’needs, considering that each territory had its
own issues. If the social environment supports
the programme, perhaps the City Governmentof Depok can build facilities for older people.
For example, if the Depok government were tobuild a garden for older people, but the social
environment did not support this plan, then thepark would be used by children for graffiti,
causing older people to be reluctant to use thepark.
Judging from the preparedness of DAFC,
development should be focused on community
support,healthservices andparticipation becausetheimplementationof these two indicators was the most effective in
Depok. Health examination and older people’
activities in Depok were going well.
Several efforts to improve service facilities forolder people aimed at the realization of an AFC
by the Depok Government were thesocialization of the AFC at the sub-district levelwithin the community and the provision of
special lines or counters for older people at the
sub-district level community health centre as anolder people-friendly health centre. Private
hospitals, government hospitals, and villagelevel community health centres do not yet havespecial services for older people. In addition, theissues surrounding older people are healthrelated, because those who came were generally
still productive and able to work, but thesepeople also needed a place to vent their feelings.
Older people also need more attention, not justtreatment. Most of the older people weretreated alone and were not brought by theirfamilies. This showed a lack of attention fromfamilies towards older people. According to mostinformants, when seeking treatment, older people need
to be taken by their families as stated by one of theinformants:
For health issues, there are alreadymonthly routine checks for older person

Depok's Preparedness for Becoming an AFC
Generally, the informants said that Depok’s
preparedness to be an AFC was not optimized.
Several informants even doubted that thisprogramme would be successful. Depok's
unpreparedness to become an AFC was mainly
due to the absence of a sufficient budget and of
programmes. Becoming an AFC was not yet apriority, and there were still many neglected older
people in Depok. In addition, the FGD informantsfrom the community health centre stated that tosupport DAFC, it was necessary to build several
facilities to make it easier for older people toconduct their activities. For example, thegovernment should increase the number of cityparks for older people to relax in or take walks
through; maintain special treatment for older
people, such as the availability of special seatson commuter line trains, an increase in waiting
places or the creation of special lines for older
person people in hospitals, health centres, banks
and other community service places. Even
though Depok was not prepared, Depok still has topioneer the realization of an AFC because the life
expectancy in Depok is quite high (79-80 years), andthe increase in the population of older people in
Depok is quite rapid. Older people should be given
special attention in order not to be a burden to thegovernment and society. To prepare for therealization of DAFC, the Depok Government
issued Regional Regulation No. 09 in 2017
concerning Depok as a Family Friendly Cityand Regional Regulation No. 15 in 2013
concerning Depok as a Child-Friendly City. An
AFC was contained in the Regional Regulation
on Depok as a Family-Friendly City. However,the Depok Government will realize DAFC

773

SEE - Bangkok, Thailand, Nov.11-13, 2019

people. However, the problem is that there
are no families in the home or family
members who can take them (sub-district
health centre staff)
Regarding the health of older people,
some informants said that they tend to sufferfrom non-communicable diseases such as
hypertension. In addition, most informants said that
health services for older people were not
optimal because they were not focused only on older
people. Other informants stated that there was a lackof understanding about older people, especially about
how to communicate with them. Clear cooperationfrom all involved parties was essential, where
monitoring and evaluation for each activity wereneeded.

become volunteers, provided that they were
physically healthy. The involvement of the older
people in volunteer activities was usually
personal, such as functioning as a social worker
at the mosque, being involved in community
service or in a celebration of the birth of theprophet Muhammad), participating in art
events , various kinds of competitions (exercise,choir), and helping in landslides, floods, etc.
Older people can take part in the community byparticipating in social activities, such as community
service or as entrepreneurs. For work as office
staff, only managerial work was available forolder people who had not reached the age of 65
years. Non-managerial positions were more
focused on a younger and productive agegroups.
The
study
results
showedthatmost informants agreed that there was a need to
improve the quality of work of older people in
Depok. Furthermore, the informants assessed theneed for training opportunities for older people
after retirement as well as for policies on the
recruitment of workers, promotions, training, andsupport for entrepreneurship. Some informants
agreed on the existence of flexible employment
opportunities with good income for older people.
However, employment opportunities for older
people in both formal and informal sectors werestill low due to the lack of expertise and low
education. Usually, older people are involved in
activities such as cooking, crafts, and reciting
the Al Quran. An older people’s profession thatwas still considered suitable was to become aparking attendant or a security guard. The
training of older people was truly limited, wasonly given
one time andwasnotroutinely conducted.
For
example,one
government institution conducted recycling ofwaste(WasteBank) andofferedculinary courses;
Depok
Muslimat
NU
organized bridal makeup courses for the public,
but there were no specified programmes forolder people, and after training, kits were
provided. Activities specified for the older
people were usually health-related, such as
exercise, the Healthy Heart Club, Older people
Family Development and Increased Income for
Families Program. Older people with footdefects in Depok were usually employed in theprivate sector in administration and notin production. Depok civil servants planning toenter retirement
were given training for
retirement
preparation such as
farming,
gardening, and baking.
There was no specified economic support forthe older people, and only a general programme
existed for all age groups. According to theSocial Participation
The social participation of older people in
Depok was considered by most informants to bequite good. Many older people were still
actively involved in community activities.
However, there was no access to social
activities that were specifically for older
people, except for activities created by thecommunity, such as volunteering to procure
food during elections and engaging in postdisaster activities. Informants stated that manyolder people did not want to engage in activities
even though they were still productive. Some
informants said that most of the so cialactivities
attended
by
the
older
people were recitation or religious activities
and sports, such as exercise sports or exercise
activities usually carried out at public facilities
in housing areas. When asked whether the
informants were involved in community activities,
most informants stated that they were active
in religious activities such as recitation andcommunity meetings. The remaining informants
were active in sports activities, the integrated
service posts for older people, and the arts.
Social participation has encouraged theparticipation of older person people. Olderperson people are specifically involved. In the
sub-district, there is the implementation of
National Older people’ Day, several games,
and competitions for older person people.
These activities are monitored and evaluated.
(by the sub-district community health centre
staff)
Civil
Participation
Economics

andEmployment /Most of the informants stated that the older
people still had the opportunity to work or

774

SEE - Bangkok, Thailand, Nov.11-13, 2019

integrated service posts for older informants,
there were several efforts to improvethe creative economy by
the
Depok
Government, namely, 1) producing
candy, banana chips, star fruit, processed
products,
cassava
chips,
andcheesesticks; 2) providing non-interest loan funds instages starting from IDR 100,000, 200,000,
500,000 and so on; 3) assistance in the form of
bazaars can be followed by older peoplebusiness groups, catering groups (consisting of
4 people, with the number of older people from
1-2 people); and 4) the use of females in headsof household programmes involving 10-20% of
older people for the past 2 years to lend funds of
IDR 10 million per - group (10 people)
for home industries such as vegetables mixed
with peanut sauce, fried rice cake, andhandcrafts such as sticking and making handbags from recycled materials.
Until now, all informants revealed that there
were no policies or government regulations
regarding the age limit of workers, promotions
or job training for older people; there was noopportunity to get post-retirement training or togetsupport in
self-employment activities.
However, decision-making agencies in Depok
such as the Health Office, Representative Officeand private companies encouraged theparticipation and membership of older people,
especially in the health sector in the integrated
service posts for older persons, venting
activities for older people, participation(National Older People Day), etc.

centres; special seats for older people on the
train; the absence of a separation between
bicycle lanes and pedestrians; and toilets
in public places were not older people-friendly .
Buildings and open spaces are not yet
optimal for older people. There are no older
people-friendly parks or green open spaces.
Public parks have not prioritized older people(sub-district community health centre staff).
Generally, Depok housing is flood free, whichis around 70%, except for houses on the banksof rivers.
Housing of Ambassador in
Cimanggis Sub-district always flooded (theintegrated service post cadres)Transportation and Housing
For transportation facilities, some informants
stated that transportation did not support theneeds of older people, but some stated that citytransportation was relatively comfortable. Public
transportation for older people is already being
planned. The conditions in public transportation
have not supported older people because it isdifficult to ride on public transportation.
Transportation in Depok is still lacking,especially long-distance transportation. In thecity, there are still minibuses. These models areold, and in my observation, the braking may not
be sufficient, which shows that there is no
special attention given to transportation (amember of a political party)
For housing indicators in Depok, some
informants considered that housing was still notolder people-friendly both for private and rental /contracted houses because they did not have apedestrian walkway. Housing prices were still notaffordable for older people. Other informants
suggested that the size of the housing should makeit free from flooding. If the residents of the housecome from a certain socioeconomic group, they areable to usually renovate parts of a room in thehouse, such as toilets and floors, to meet the needsof an older people.
Currently, the Depok housing developer has
not fulfilled the needs of older people
because it prioritizes homes for young families.
Depok has yet to have flats specificallydesigned for older people because such housing
has not been planned by the government andthe developer. However, some informants
considered that the construction of flats forolder people in Depok was not suitable and wasinappropriate because it was better for older
people to live with their families. There wereno older people-friendly homes because
the developer had not designed the housein accordance with the physical needs of older

Buildings and Open Spaces
Most people thought that buildings and open
spaces were still inadequate for older people.
However,there
were
alreadysomeimprovements, although not significant, suchas bettercleanlinessin public places(streets, sidewalks, parks, andmarkets); sufficient and well-preserved seatingin parks; the existence of older people-friendly
parks; slip resistant sidewalks for pedestrians
that were still used by street vendors andmotorbike riders; places and buttons for older
people at special crossings had not fully
functioned, creating the need for officers to
help them cross the street; generally continued
adherence to crossing signs for older people by
car and motorcycle drivers; quite good level of
security
because security
officers
wereon duty for 24 hours; relatively fewer lighting
lamps, especially if the lights were off, whichtakes a long time to repair; special lines andcounters for older people at health775

SEE - Bangkok, Thailand, Nov.11-13, 2019

people, such as flat roads, a wide entrance, anda bathroom, kitchen, and toilet specificallydesigned for older people. Some housing andapartments in Depok were not older peoplefriendly because of their location, which is far
from public facilities such as public healthcentres and hospitals, except for motorcycletransportation. In fact, according to theinformant from one political party, housing in
Depok originally had open spaces, but thesespaces were then converted into parking areas.
Housing conditions are not older peoplefriendly. Owners are more responsible formaking the house comfortable. The developer
has not built an older people-friendly
house (sub-district community health centre
staff)

informant, health examination activities should
be carried out continuously, but theimplementation depends on the condition of theagency. Sometimes people were diligent inchecking themselves into the centre, while there
were also people who were too lazy to go to thehealth centre. What I look at is the health aspect.
Health access is better in terms of financing andaccess because this programme is for all levelsof society. With government support, financing
and access are better. (member of a politicalparty)
Social Respect and Inclusion
Older people should gain respect from theirinvolvement in social activities and theirassimilation in the society, but their role wasmostly kept at a domestic level, such as taking
care of children/grandchildren, which is likely
to accelerate the ageing process. Thus far, there
has been almost no involvement of older
people in official community organizations at
the government level because it was consideredappropriate for young people, and the youth
population was large. The health and physicalconditions of older people also declined,causing them to be reluctant to blend in with
community organizations/NGOs, etc. Anothersource of appreciation for older people was their
inclusion as community leaders or in activities
such as the Independence Day celebration orelections. Other activities seem to depend on
their health conditions. According to one
informant, older people must be active, andif they were retired, they must be cared for. If
you do not manage yourself after retirement,
you will become senile. Although older people
are physically weak, they need to remain active.
Do not just leave our old parents at home; wehave to be affectionate and considerate (memberof a political party)

Communication, Information, and Education
Communication and obtaining informationin the present era were better with thetechnology of mobile communication. Sunday
meetings for older people were quite supportive
and, when coupled with social media, allowed
older people to keep up with information. Every
year, the celebration held talk shows related
to National Older people Day. It was expectedthat seniors received information about various
issues when engaged in these activities.
However, some informants said that information
did not address the needs of older people. There
still needed to be an information centre to meetthe needs of older people.
Community Support and Infrastructure forOlder People’ Health Services
The implementation of community support for theolder people in Depok was very good. This was
revealed by all informants from political parties who
expressed concern that the Depok Health Office isimproving the quality of life of older people throughexercise and health services in the integrated service
posts for older people every month. Health services
were adequate in terms of access and financing.
Health services are programmes that arequite adequate both from an access and afinancial perspective, with the availability offree health checks and health insurance. All
first-level community health centres in Depok
have already become older people-friendly
health centres, while second-level centres arestill in the process of developing. Visits tothe community health centre were quite high.
The types of diseases that commonly affectolder people are hypertension and NCDs (NonCommunicable Diseases). According to theDiscussion
The increased number of older people has an
impact on socio-economics at the family,community
andgovernment
levels.
Therefore, an AFC must be created so that older
people can engage in activities and be
productive. An AFC will be a testament to thereadiness of a nation to face an era that
continues to move to reduce the number of
dependent people in life. The population ofolder people is no longer a burden on families,
communities, and nations.11
When combined with the increasing numberof older people, it appears that local regulation

776

SEE - Bangkok, Thailand, Nov.11-13, 2019is needed to accommodate regional specificities
and improve regional welfare. However, in
reality, the Regional Regulation on older
people, especially that related to AFCs, whichwere originally planned to be issued, wascancelled and replaced with the Mayor's
Regulation, which is still in the drafting stage.
The existence of these policy regulations
guarantees that the principles of administrative
actions and every event that deals with equality,
legal certainty, and actions are based on certain
regulations.12-14
The large number of older people whochoose to go to health care centres makes older
people-friendly health facilities the issue thatneeds to be addressed.15-16 Visits of older people
to community health centres are quite high. All
first-level community health centres are older
people-friendly,
while
the
second-levelcommunity health centres are still in the processof becoming so. In addition, with free treatment
for older people and a health insurance
programme, it is easier for them to receive
treatment. The emergence of health problems
and the number of older people who seek
treatment at health facilities reflect the demandfor health services to meet the needs of older
people in a friendly manner so that their healthcan be guaranteed. The findings in the study arein line with the study in Malaysia that foundcommunity health services to be one of the mostimportant for developing an age-friendly
environment.5 Eight dimensions of the older
people-friendly city designed by the WHO
support a person's life, not just as a friendly
place for older people but for all age groups,
including children and disabled people.13
Therefore, within the context of the older
people, an AFC is a city that accommodates theneeds of older people with all the limitations
that accompany them. In addition, Depok City
has challenges encountered to realize DAFC
such as developing housing friendly city. One of
the strength of DAFC readiness is active
community participation at the integrated
service post. These two findings is supportingby a similar study in Netherland.17
The Depok Government has strived tocreatean olderpeoplefriendly area/community/city, but it is not yet
optimal because it has to prioritize other facilities.
Therefore, policies related to older people-friendly
communities and cities, especially for Depok, arevery important because of the high population ofolder people in this region. The preparation of older
people programmes in annual activities must be
increased and must involve the community so thatthe programmes that are prepared can respond to

the interests of older people. In addition, it
is necessary to prepare the infrastructure, budget(funds), government support (policies), andconcern for older people.18-19
Older people play roles as job seekers who
garner financial income, and they also play anactive role in giving to the community inaccordance with the capabilities/skills of eacholder person. However, older people havenot been optimally empowered, even though there
are still many older people who have potential intheir fields. Several factors that Depok’s
preparedness for DAFC contained were 1)
optimized older people programmes and budgets;
2) insufficient infrastructure, primarily buildings
and open spaces, transportation, housing, civil
participation and employment of older people;
and 3) lack of coordination between the Depok
Government and related institutions, where
each programme is running independently.
Depok's preparedness to become an AFC
is not yet optimized because of the lack ofrealization of the commitment of the Depok
Government to focus on the interests of theolder people, except for the idea of a healthy citythat has been implemented even though older
people are not mentioned specifically. Today,
Depok focuses more on child-friendly cities thanon DAFC. DAFC should also receive special
attention and receive its own Special Regional
Regulation of DAFC, which is separate from the
Depok Regional Regulation on Child-Friendly
Cities. The existence of Regional Regulations,
national policies, and the law, including theissuance of the Depok Mayor's Regulation
concerning the establishment of the Depok Local
Committee for the Older People, will bring therealization of DAFC in the future.
The potential for public support in Depok torealize DAFC is quite large. This can be seen fromthe enthusiastic participation of all age groups,
including older people in the integrated service
posts for older people activities and healthy heart
exercises The socialization of DAFC is being
realized by the AFC. The Working Group from the
sub-district to the citizen association level supports
the dissemination of information and broad publicknowledge about DAFC. When compared withthe findings of a similar study in 2013, it was
concluded that there had been no significant
changes from the 3 indicators of AFCs that wereconsidered unfavourable, namely, open buildings
and green spaces, housing, and social and work
participation. There is little importance in the2018's study given to such factors as additionalparks for older people, including Lembah Gurame
Park, Terapi Lansia Park, and Mekarsari Park.
Approximately 33% of Depok's land already has

777

SEE - Bangkok, Thailand, Nov.11-13, 2019103 parks20, and the issuance of Regional
Regulation No. 09 of 2017 concerning Depok asa family-Friendly City includes DAFC. There
has been no changes in housing and civil
participation or work indicators in the findingsof this study.

The Author(s) declare(s) that there is no conflictof interest.
ETHICAL APPROVALThis study was conducted according to theguidelines laid down in the Declaration of
Helsinki and all procedures involving humansubjects/patients were approved by The
Research and Community Engagement EthicalCommittee Faculty of Public Health Universityof Indonesia. Written informed consent was
obtained from all subjects. Applicable (approval
numberof
ethicalclearance:
666/UN2.F10/PPM.00.02/2018).

Limitations
The study has several limitations, such as thedifficulty of determining the timing of in-depth
interviews and FGDs for several informantsfrom government stakeholders. As a result, a
number of relevant government stakeholders,such as the Housing Agency, the Manpower
Office, the SME (Small Medium Enterprises),and Market Office could not attend. Likewise,
when they were visited, they refused toparticipate without giving any explanation.
Another limitation was the presence of FGD
informants from organizations of older people
aged 70 years and over who experienced
hearing loss and had difficulty concentrating on
moderator questions. They could not answer thequestions correctly and tended to provide
lengthy explanations that deviated far from thecontents of the question.

PERMISSION TO REPRODUCE FIGURESOF MAP AND DESCRIPTION OF DEPOK
CITY
Depok District Health Office had given
permission to reproduce map and thedescription of Depok City to authors (takenfrom Depok City Profiles Year 2017, Depok
District Health Office).
FUNDING ACKNOWLEDGEMENTCONCLUSIONS
Directorate of Community Engagement andResearch of Universitas Indonesia (UI) for theirfund of student final research project grant(No.5283/UN2.R3.1/HKP 05.00/2018). UI had
no role in the design, analysis, or writing of thisarticle, except covering the publication/handling
cost of the journal publication

Depok still needs time to achieve the AFC,
however, the existence of regional laws andpolicies regulating the Depok Local Committee for
the Older People formation can indirectly
accelerate therealization
of
DAFC.
These policies or regulations are designed toensure local government cares about the
population irrespective of age. In addition,
there is a regional policy that provides legal
certainty for older people that their needs areguaranteed. The best practices that have been
carried out by relevant agencies in Depokthat relate to older people are the formation of the
Local Committee of the Older people by thegovernment and the community health centre
Santun Lansia that provides good services forolder people.

REFERENCES[1] Fatmah. Geriatric nutrition. Jakarta:
Erlangga Publisher, 2010, p.2-3.
[2] WHO. Global Age Friendly-Cities: a guide.
France: WHO, 2007, no page.
[3] Buffel T, McGarry P, Phillipson C, et al.
Developing age-friendly cities: case studies
from Brussels and Manchester andimplications for policy and practice. J Aging
Soc Policy. 2014;26 (1-2):52-72[4] Kendig H., Elias AM., Matwijiw P., Anstey
K. Developing age-friendly cities andcommunities in Australia. J Aging Health2014; 26(8): 1390-414.
[5] Ming L.M, Shi Y.L., Shiok H.L., Ming L.L.
Modeling age-friendly environment, active
aging, and social connectedness in an
emerging Asian economy. Journal of Aging
Research 2016; 1-14.

ACKNOWLEDGEMENTS
We express our appreciation for all theinformants for their participation in the study.
This study received a specific grant from theGrant of Improving Research Working Group
Universitas
Indonesia
2018(No:5283/UN2.R3.1/HKP 05.00/2018).
CONFLICT OF INTEREST

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SEE - Bangkok, Thailand, Nov.11-13, 2019[6] No author. Surabaya of Age Friendly City.
Gapura XIV, 2012, page 15.
[7] Depok City Statistic Center Bureau,.
Population growth of Depok City in 2017.
Depok: Depok City Statistic Center Bureau,
2017, no page.
[8] Survey Meter. One final step into dream on
Age Friendly City 2030. Report, Survey
Meter Yogyakarta, 2013.
[9] Fatmah, Vita, Dina, et al. The assessment of
Depok as Age Friendly City (AFC). Journalof Biosciences and Medicines 2014; 2:1-40.
[10] Jonsen K, Jehn KA. Using triangulation tovalidate themes in qualitative studies.
Qualitative Research in Organizations 2009;
4: 123-150.
[11] Dewi VP, Raden II, Lindawati. Training
program to support preparedness of older
persons health services”. ASEAN Journal ofCommunuity Engagement 2018; 2:120-133.
[12] Older persons Regional Commission ofWest Java Province. Guidelines for thedevelopment of older persons friendly areasin West Java Province. Bandung: Older
Persons Regional Commission of West Java
Province, 2017, no page.
[13] Saepudin. Fungsi peraturan daerah padaperundangan Tahun 2011 (Function ofregional regulation in legislation 2011),
https://saepudinonline.wordpress.com/2013/05/01/fungsi-perda-dalam-peraturanperundang-undangan (2011, accessed 25
September 2018).
[14] Ahmad. Fungsi kebijakan peraturan dalammelengkapi sistem legislasi administrasi
negara (Function of policy regulations incompleting the legislation system of stateadministration),
http://asaad36.blogspot.com/2010/11/fungsi-

peraturan-kebijakan-dalam.html(2010,
accessed 1 October 1 2018).
[15] UNFPA. Executive summary of aging
population in the twentieth century: acelebration and challenge. UNFPA, 2012, no
page.
[16] National Family Planning Coordinating
Board. Kota ramah lansia membentuk lansia
tangguh (Older persons friendly cities form
tough
older
persons),
https://keluargaindonesia.id/kabar/kotaramah-lansia-upaya-membentuk-lansiatangguh (2017, accessed 16 September2018).
[17] Van Hoof J., Kazak JK, Jolanta MPB,
Sebastiaan TMP. The challenges of urban
ageing: making cities aged friendly inEurope. Int. J. Environ. Res. Public Health
2018; 15 (11): 2473.
[18] Hermawati. Study on Age Friendly City.
In: Age Friendly City Seminar andWorkshop. Yogyakarta.
[19] Agustiningsih, Aryanti P. Pentingnya
fasilitas kesehatan yang ramah lansia (The
Importance of older persons friendly healthfacilities),
https://www.kompasiana.com/aryantipuji/59
2c10349397739b 381ff541/pentingnya fasilitas-kesehatan-yang-ramah-lansia (2017,
accessed 15 August 2018).
[20] Berita Satu. Hanya 33% kelurahan di
Depok memiliki taman (Only 33% ofvillages
in
Depok
have
parks),
www.beritasatu.com/satu/477652-baru-33kelurahan-di-depok-yang-miliki-taman. html
(2018, accessed 1 November 2018).

779

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

Figure 1. Map of Depok City (reproduce from Profile of Depok City Profile Year 2017, Depok DHO)

Figure 2. Description of Depok City (reproduce from Profile of Depok City Profile Year 2017, Depok
DHO)

0

5

10

15

20

NGOs / political parties
The integrated post service of older people cadres
Organization/ community of older people
Government stakeholder
Private stakeholder

Figure 3. Type of key informant
Table 1
Variable

Socio-demographic characteristic of informants ( n = 50)
Level

Age (years)

Pre-older people (< 60)
Older people(>= 60)Sex
Male
FemaleEducational background Senior high school
Academy/University
Working status
Yes:
Government employee
Private employee
No

780

n

%

37
13
11
11
39

74.0
26.0
22.0
78.0
22.0
78.0

12
19
19

24.0
38.0
38.0

39

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

BIOMONITORING OF WATER POLLUTION IN LAKE CHEBARKULBY THE CONTENT OF HEAVY METALS IN MACROPHYTE
ORGANS, RUSSIA
I.V. Mashkova1, A.M. Kostryukova 2, E.E. Schelkanova3, V.V. Trofimenko4 and A.I. Slavnaya5
1, 2, 3, 5
Department of Chemistry, South Ural State University, Chelyabinsk, Russia
4
Department of Philosophy and Culturology South Ural State Humanitarian Pedagogical University
Chelyabinsk, Russia

ABSTRACTThis paper studies bioconcentration of heavy metals (HMs) in macrophytes.The high content of heavy metalcompounds in Lake Chebarkul is natural. However, in some parts of the lake higher heavy metal content isobserved. This is typical for the areas with an increased man-made impact on the lake. In these areas heavy
metals get into the water together with partly treated sewage. The goal of our research is to determine themacrophyte species diversity of Lake Chebarkul, as well as the bioconcentration of heavy metals inmacrophytes. In our research we identified species diversity, water flora taxonomic structure for each sampling
point. We made flora lists for each profile and lake part and the total lists of differences and similarities of all thestudied sites. The final flora list includes about 90 plants. According to the research macrophyte species
composition of the studied sites is different. The article discusses the issues of bioaccumulation andbioindication of heavy metals (TM: Cu, Zn, Mn and Fe) in three types of macrophytes - Potamogéton lucens,
Phragmites australis and Elodéa canadénsis of Lake Chebarkul (Russia). The research revealed that HMs inplants were actively accumulated from water. Potamogéton lucens and Phragmites australis showed higher
average HM accumulation values.
Keywords: Aquatic Macrophytes, Bioaccumulation, Heavy Metals, Biomonitoring

attached mode of life makes them especiallyeffective in bioindicating heavy metal pollution ofparticular zones. Besides, there is research showing
significant differences in heavy metal accumulation
by different macrophyte species [14], [15].
Macrophytes take a priority part in the methods oftreatment and detoxification of water-bodies.
Submergent vegetation accumulate heavy metals
more than coastal.
So far, few studies have investigated macrophyte
biodiversity in South Ural. Taking into account thefact that the problem has been little investigated in
the South Ural region [16], we continued to study
the peculiarities of heavy metal accumulation
analyzing the macrophyte biodiversity. As there is
growing concern to the problem of heavy metal
pollution, particularly of water-bodies, thediscussions emerged have become timely. The
current paper aims to identify macrophyte
biodiversity of Lake Chebarkul (Russia) and to study
the total concentration of heavy metals in three mostdispersed species of macrophytes in the coastal
water.

INTRODUCTION
Water quality in water-bodies has become of anincreased interest. Overland water pollution by
heavy metals is one of the main environmental
issues [1]. Heavy metals get into water systems invarious ways including industrial, municipal andagricultural effluents [2]-[4]. Being very persistent,
heavy metals tend to accumulate in soil, water,
sediment and pass through trophic chains.
Heavy metal toxicity is explained by their ability
to bind with proteins and prevent DNA replication[5]. Most of the metals provoke the production offree radicals and reactive oxygen intermediate (ROI)
which leads to oxidative stress [6]. But someelements such as Cu, Fe, Zn, Mn, Ni are necessary
for plants to grow. And some macrophytes canaccumulate metals and metalloids [7]-[9].
Macrophytes are very important for the community
as they take part in oxygen production, nutrient
cycle, stabilizing sediments and providing habitat forwater life [10], [11]. Macrophytes actively
accumulate metals from sediment and water so thatthey become accessible for epiphytic phytoplankton
and other herbivores and detrivores [12]. So, taking
into account the importance of macrophytes inecology, the assessment of heavy metal content inmacrophytes presents interest [13]. Macrophytes’

MATERIALS AND METHODS
Study Area

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Lake Chebarkul is on the eastern slope of theUrals range of mountains. Its altitude is 320 m above
sea level. It is a low-land lake with tough shores
overgrown with reeds. The creeks are full of water
vegetation. Chebarkul is of tectonic origin. Its
eastern part is very deep, the northern and western
shores are steep and rocky, eastern and southern areflat flooded in spring. There are rocky promontories.
Western coasts are forested. The bottom is covered
with silt, sand, pebble and shells. It is the lake where
the meteorite fell in 2013 (Chelyabinsky, Fig. 1,
point 6). Several small dry in summer rivers fall into
the lake. The lake area is 19.8 km2, its volume is0.154 km2, the deepest part is 12 m, the average
depth is 2.3 m. the water level varies between 1.5 m,
the highest water is in June. The lake is frozen earlyin November, and is opened in May. There are many
health resorts and recreation facilities on the lakecoasts. It is also of much fishery importance. Lake
Chebarkul has extensive resources of quality fresh
drinking water of 154 million m3. It is a source ofdrinking water supply for the town of Chebarkul andits neighbouring villages. The water level has
dropped almost by 3 m for the last 70 years. As aresult, the natural hydrological regime wasdisturbed. The lake has become shallow, its southernand eastern coasts got swamped, weeds have grown
not only on the coasts but also away from them.

12 sampling points were chosen to study
macrophyte species diversity (Fig. 1).
The samples of water and macrophytes wereselected at the points. To determine species diversity
all the existing macrophyte species were collected ateach sampling point with their further taxonomic
identification. Five-grade scale was used to give aquantitative characteristic of species occurrence:
1 - rarely or isolatedly occurred species; 2 - rarely or
sporadically occurred; 3 - occurred frequently
enough but without dominating; 4 - occurred
frequently, able to form communities; 5 - widely
occurred species that make coenosis. To measure
heavy metal content 3 - 6 samples of the widely
occurred macrophyte species were selected at eachsampling point: Potamogéton lucens, Phragmites
australis и Elodéa canadénsis.
To remove sediment, roots and rhizomes werecleaned in river water and put into plastic bags.
Water samples were kept in one-litre plastic bottles.
Climatically identical days were chosen forsampling to eliminate weather impact on the
research results. The days were sunny and notwindy. Sampling was made in June - September
2017-2018. The period from June to September waschosen deliberately, as this is the vegetation time formacrophyte in the studied area. It is in this periodthat bioaccumulation tends to reach highconcentration in macrophyte. Each sampling point
was surveyed twice over the period.
Ten plant samples of each species identical insize were collected.

Sample Collection

Fig. 1 Map of Lake Chebarkul and location of the sampling stations.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

The plants were thoroughly washed with the streamof tub water until they appeared clean. To remove
water they were intensively shaken and then weredried under the sun for 3 days. The plants were
further packed in paper and delivered into thelaboratory, where they were washed with distilledwater, air-dried and put into the oven at 700 oC for
6 hours. Microscopy of plant surface did not reveal
any evident sediment. To make a composite sample,
ten plants of each group were milled with a stainlesssteel atomizer and then homogenized. Before
analyzing the aliquots of the powder were dried
again at 700 oC for a night.

graphs were calculated using a special softwaremodule “Graphs” [18].
RESULTS AND DISCUSSION
The lake vegetation is diverse enough and welldeveloped. In shallow waters macrophytes are
distributed evenly with the zones covering relatively
large areas towards the basin (covering up to 100 %locally). The formed communities cover the bottom
up to the depth of 3.0-4.0 m in average. Some
species such as Fontinalis antipyretica andrepresentatives of Charophytes are met at the depthof 5 m.
About 90 species of macrophytes of 35 families
were identified, 53 (59 %) of them are water plants
and 33 (41 %) are coastal. We think that somespecies were not covered, as we did not take tree
species into account. Besides, the given research
aimed to study lake ecosystem, so the small rivers
and streams entering the lake were not considered.
Analyzing sampling points results in classifying
them into four groups according to the common
vegetation associations and man-made impact thatwas described in grades (Fig. 2).

Analytical Determination of Metal Content inMacrophytes
X-ray patterns were registered in the laboratoryof the Nanotechnology Centre of the South Ural
State
University.
Spectrometer
RigakuSuperMini200 XRF was used to make an XRF
analysis. The following standard samples were used:
the standard sample of birch leaves GSO 8922-2007,of the mix of herbs, algae and OSO 10-150-2008(laminaria) and GSO 8921-2007 Elodea Canadensis.
Relative standard deviation was not more than 5%.
Analytical Determination of Metal Content in
Water
Water samples were acidized with concentrated
HNO3 as described in APHA [17]. Heavy metal
content in water samples was determined with theatomic absorption spectrometer Analyst 400 (PerkinElmer) with a flame spraying mode. To get astandard curve in accordance with GOST 51309-99,
the standard metal solution was used. All the metal
concentrations were measured in the laboratory of
the South Ural Public Centre of the Ilmen State
Reserve of the Ural Department of Russian
Academy of Sciences.

Fig. 2

The four groups of sampling points.

The first group (0 grade) comprises the sampling
points that are not under a man-made impact (6, 1012). The second group (1 grade) presents arecreation territory that is under a significant touristmade impact (7-9). The third (2 grades) is located in
the zone that is affected by the households of small
villages on the coasts (1-3). The fourth point(3 grades) is the area under an adverse impact ofboth domestic and commercial character, its situatedwithin the limits of Chebarkul (a town in the
Chelyabinsk region).
Heavy metal concentrations in the sampling pints
do not exceed the maximum permissible
concentration, but their statistically significant
differences are marked (Table 1). Heavy metal
content in water is not homogenous in space anddepends on the proximity to the pollutant.

Data Processing
The total weight of each heavy metal can becalculated on the results of XRF. The data about thecontent (mkg/g) used in the present study is made of
the heavy metal weight divided into the dry weight(DW) of macrophyte samples. Software Microsoft
Excel 2013 and SPSS 24.0 was used to manage andanalyze data. The difference in heavy metal
concentrations between species and lakes wasanalyzed with the help of ANOVA with subsequentcomparison performed using the least significant
Fisher difference (LSD).
The data was analyzed using graphs that weremade by calculating similarity based on the Serensen
coefficient as the affinity index, taking into accountthe positive matches for the cluster analysis. The
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 Metal content in lake water, mg·L-1
Metal
Mn
Fe
Cu
Zn

Group
1
2
0.015±0.002
0.028±0.005
0.026±0.006
0.031±0.006
0.0018±0.0008 0.0012±0.0008
0.002±0.001
0.0018±0.001

Mn
Fe
Cu
Zn

3
0.021±0.006
0.028±0.006
0.0020±0.0006
0.0032±0.001

Table 2 Meanvalues(±standard
errors),mg·kg-1DW, for all HM concentrations inmacrophytes
Metal

Group
2
3
4
P. lucens
Mn 790±121a 818±104a 821±58a 990±68a
Fe 503±132a 536±118a 590±67a 689±68a
Cu
36±6a
35±5a
46±5a
49±5a
Zn
22±4a
27±6a
38±5a
39±5a
P. australis L.
Mn 890±101a 857±115a 921±67b 1098±118a
Fe
519±32a 521±108b 691±77a 789±54a
Cu
37±5a
42±5a
53±6a
58±6b
Zn
26±4a
29±4b
38±4b
38±5a
E. canadénsis L.
Mn 779±119a 793±125b 802±117a 956±61a
Fe 398±108b 403±82c 452±97b 487±106b
Cu
35±6b
34±5b
41±6b
45±6c
Zn
21±6b
27±5b
28±4a
28±4b
Note: Different letters indicate significant
differences among the species according to Fisher’s
LSD (p<0.05).
1

4
0.025±0.002
0.028±0.006
0.0023±0.0008
0.0039±0.002

Species diversity of some families differs withthe groups of sampling points, e.g., Potamogeton,
Hydrocharitaceae, Polygonaceae, Nymphaeaceae,
Characeae and Ranunculaceae. Unlike groups 3 and4, groups 1 and 2 have a richer diversity of these
species.
The qualitative analysis shows that the studied
areas do not significantly differ in taxonomic
diversity of water flora. According to the collected
data macrophyte species composition of group 1
includes 90 species of 35 families. Many species are
met here including Characeae, water moss
(Fontinalis), some species of Potamogeton, somespecies of hygrophytes growing in swamps. The listof macrophytes of this group includes all theregistered in the lake Chebarkul species belonging to
the general list. Groups 2 (82 species of 34 families)
and 1 are 91 % close in species composition. Species
composition of group 3 is even lower (71 species of
32 families). Group 4 is characterized by a muchpoor species diversity (69 % of the general list, 62
species of 26 families, namely). Rare species ofsome families such as, Alismataceae, Araceae,
Ranunculaceae,
Primulaceae,
Lamiaceae,
Scrophulariaceae,
Lentibulariaceae,
Potamogetonaceae, Characeae are met in groups 1
and 2. That can be associated with natural
eutrophicationofthesesampling
points.
Overgrowing of the sampling points of group 3 and4 is accelerated due to the man-made impact of theterritory: the flora of sensitive species becomes poor,
but weeds do richer, on the contrary.
The analysis shows that the studied lake parts
significantly differ in the frequency of occurrence ofgeneral species. Overgrowing, which is higher ingroups 4 and 5, contributes to it.
The research reveals the abundant growth ofPotamogéton lucens L., Phragmites australis L. andElodéa canadénsis L in all the studied lake parts.
These species were chosen to study heavy metal
content.
Mn >Fe >Cu >Zn is the ratio we got as a result(Table 2).

Mn content in plant organs is usually from 10 to
25 mg/kg [19], which is enough for most of theplants in terms of physiology. Very high levels of
Mn were registered in P. lucens (790-990
mg·kg-1DW) and E. canadénsis L. (779-956
mg·kg-1DW). Such concentrations in water are
known as toxic for most of the plants [20], [21]. But,
as it was stated before, water was not polluted by
Mn. The higher Mn content in the plant organs canshow a positive effect macrophytes have on the
purification of the lake water from Mn compounds
in relation to physiological needs, and can be a
genetic feature [19].
Fe content remains at 398-789 mg·kg-1DW. The
metal is necessary for the plant metabolism [22]. Asa rule, Cu content (36-58 mg·kg-1DW) and Zncontent (21-39 mg·kg-1DW) in the studied
macrophytes are within the natural level for water
plants [19]. All plants have a high accumulation ofmanganese and iron (Table 2), while theaccumulation of copper and zinc is negligible.
CONCLUSIONS
Thus, the composition of ecological groups ofmacrophytes in relation to the water factor is one of
the most of water-bodies. The local flora of even one
water-body has some differences. The first group
has a higher level of taxonomic diversity and thediversity of ecological forms of plants. This is due tothe large variety of microbiotopes and the lack of
man-made
impact.
Statisticallysignificant
differences were found between the accumulation of784

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fe > Cu > Zn in E. canadensis L. compared to P.
lucens L., P. australis L. No such trend was foundfor Mn. There is an urgent need for such studies to
identify more species capable of the greatest
bioaccumulation.

macrophytes in biogeochemical cycling of heavy
metals—relevance to soil: sediment continuum
detoxification and ecosystem health, in
Detoxification of Heavy Metals. Soil Biology, I.
Sherameti and A. Varma, Eds., Springer-Verlag
Berlin Heidelberg, Vol. 30, 2011, pp. 345-368.
[11] Krupnova T.G., Mashkova I.V., Kostryukova
A.M., Schelkanova E.E. and Gavrilkina S.V.
Gastropods as potential biomonitors ofcontamination caused by heavy metals in South
Ural lakes, Russia, Ecological Indicators, Vol.
95, 2018, pp. 1001-1007.
[12] Cardwell
A.J.,
HawkerD.W.
andGreenway M., Metal accumulation in aquatic
macrophytes from southeast Queensland,
Australia, Chemosphere, Vol. 48, 2002, pp. 653663.
[13] Mashkova I.V., Krupnova T.G. andKostryukova A.M., Water quality and aquatic
macrophytes interrelationships for selected
reserved lakes of south ural, International
Multidisciplinary Scientific GeoConference
Surveying Geology and Mining Ecology
Management, SGEM, Vol. 1, Issue 3, 2015, pp.
763-770.
[14] Prasad M.N.V. and Freitas H., Metal
hyperaccumulation in plants - Biodiversity
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(Review article), Electronic Journal of
Biotechnology, Vol. 6, 2003, pp. 275-321.
[15] Krupnova T.G., Mashkova I.V., Kostryukova
A.M. and Artyukov E.V., The distribution andaccumulation of chemical elements in theecosystem of lake Ilmenskoe, International
Journal of GEOMATE, Vol. 12, Issue 34, 2017,
pp. 82-88.
[16] Krupnova T.G., Mashkova I.V., Kostryukova
A.M., Egorov N.O. and Gavrilkina S.V.,
Bioconcentration of heavy metals in aquatic
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Biodiversitas, Vol. 19, Issue 1, 2018, pp. 296302.
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[18] Nowakowski A.B., Possibilities and principles
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[19] Parzych A, Cymer A. and Macheta K., Leaves
and roots of Typha latifolia L. and Iris
pseudacorus L. as bioindicators of contaminationof bottom sediments by heavy metals, Limnol.
Rev., Vol. 16, Issue 2, 2016, pp. 77-83.
[20] Bonanno G., Comparative performance if traceelement bioaccumulation and biomonitoring in
the plants species Typha domingensis,
Phragmites australis and Arundo donax,

REFERENCES[1] Bastian R.K. and Hammer D., The Use ofConstructed Wetlands for Wastewater Treatment
and Recycling, In Constructed Wetlands for
Water Quality Improvement, Moshiri, Ed., Lewis
Publishers, CRC Press: Boca Raton, Fl, 1993, pp.
1-59.
[2] Guzma H.M. and Jimenez C.E., Contaminationof coral reefs by heavy metals along the
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and Panama), Marine Pollution Bulletin, Vol. 24,
1992, pp. 554-561.
[3] Gonzalez H., Pomares M., Ramirez M. andTorres I., Heavy metals in organism andsediments from the discharge zone of thesubmarine sewage outfall of Havanna city, Cuba,
Marine Pollution Bulletin, Vol. 38, 1999, pp.
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[4] Echols K.R., Meadows J.C. and Orazio C.E.,
Pollution of aquatic ecosystems II: hydrocarbons,synthetic organics, radionuclides, heavy metals,
acids, and thermal pollution. In Encyclopedia of
inland waters, Likens G.E., Ed., Cambridge:
Elsevier/Academic Press, 2009, pp. 120-128.
[5] Kar R.N., Sahoo B.N. and Sukla L.B.,
Removal of heavy metal from mine water using
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[6] Gratão P.L, Prasad M.N.V., Cardoso P.F., Lea
P.J. and Azevedo R.A., Phytoremediation: green
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Physiology, Vol. 17, 2005, pp. 53-64.
[7] Mejare M. and Bulow L., Metal-binding
proteins and peptides in bioremediation andphytoremediation of heavy metals, Trends
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[8] Prasad M.N.V., Freitas H. and Pratas J., Metal
tolerant plants and biodiversity prospecting topromote phytotechnologies for cleanup of metals
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K.S.Sajwan, and Ravi Naidu, Eds, 2005, pp. 483506.
[9] Vardanyan L.G. and Ingole B., Studies on
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[10] Malec P., Mysliwa-Kurdziel B., Prasad M.N.V.,
Waloszek A. and Strzałka K., Role of aquatic785

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Ecotoxicol Environ Saf, Vol. 97, 2013, pp. 124130.
[21] Bonanno G and Lo Giudice R., Heavy metal
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[22] Kumari M. and Tripathi B.D., Efficiency of
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786

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

GROUND REACTION FORCE OF STEP MARCHING: A PILOT
STUDYPairaya Sitthiracha1, Wichai Eungpinichpong2,3Human Movement Science, Faculty of Associate Medical Sciences,
Khon Kaen University, Thailand
2
School of Physical Therapy, Faculty of Associated Medical Sciences, Khon Kaen University, Thailand
3
BNOJHP research center, Khon Kaen University, Thailand
1

ABSTRACTStep marching is rhythmic movement of lower extremity which combines with hip, knee and ankle joints
movement. The rhythmic movement requires standing on one leg that involves voluntary action of moving thecenter of mass over the upcoming stance leg. Step marching has been used for body balance training methods for
elderly people because it is relatively simple and save for practicing. The amount and direction of groundreaction force during step marching, that affect standing balance, have not been thoroughly explored. The
objective of this study was to compare effect of two difference types of marching (comfortable marching andmarching at 90-degree of hip and knee flexion) with walking on vertical ground reaction force (VGRF). Ten
healthy subjects (5 males and 5 females), aged 27.6±3.9 years (mean ± SD) participated. Each of the subjects
underwent tested with step marching with the two conditions for 2 minutes, and 10 rounds of preferred-speed
walking on 2 force platforms. VGRF was measured by Smart analyzer®, BTS Bioengineering software. Paired ttest revealed significantly difference in VGRF among the two conditions of step marching and walking wherestep marching of the 90-degrees hip and knee flexion showed the highest mean value (11.23±0.5 N/kg) whereas
walking condition showed the lowest (10.09±0.6 N/kg). Two types of step marching provide slightly higher
VGRF than walking. They could be used to challenge on balance training for the elderly people in case of weightbearing to bones and joints are required for progressive strength training of the lower limbs.
Keywords: Marching, Walking, Vertical ground reaction force, Healthy
sending shock waves through receptors from lower
extremity to central nervous system [9]. Moreover,the ground reaction force in other conditions such as
fast walking, jogging and running are 1.15-2.45 BW
which could be harmful to the joints of the elderly
due to the high speed of movement and body weight[10].
Ground reaction force of step marching was most
likely investigated in military field. Carden andcolleagues are studied ground reaction force in 24
trained soldiers and 12 untrained civilians in
performed marching and five drill maneuvers on 2
separated force platforms foot. They found thatground reaction force of marching range between
1.1-1.3 N/BW [11]. Nevertheless, the amount anddirection of ground reaction force during stepmarching, that may positively affect standingbalance, have not been thoroughly explored. The
objective of this study was to compare effect of two
difference types of marching (comfortable marching
and marching at 90-degree of hip and knee flexion)
with walking on vertical ground reaction force.

INTRODUCTION
Step marching is rhythmic movement of lower
extremity which required hip, knee and ankle joint
movement. This movement requires 2 main
movements where one leg stands and another one
leg raises from the ground. While standing on one
leg, center of mass of the body was adjusted byvoluntary action of upcoming stance and stand legs[1]. Dingenen investigated muscle activating indouble leg stance to single leg stance. The resultshows that lower limb muscles are included Vastus
lateralis, Tibialis anterior, Peroneus, Vastus medialis,
Tensor fasciae latae, Hamstring, Gluteus medius,
Gastrocnemius were activated [2]. Similarly, Iverson
indicated that performance of single leg standing in
relation with the torques of the hip flexors, extensors,
and abductor [3]. Step marching, has been applied asa simple field test for assessment for aerobic
endurance of the elderly people. Moreover, it has
been frequently used as one of balance exercises toreduce falls in the elderly [4]-[6].
While doing step marching, vertical groundreaction will deliver force to the feet into 3
directions including vertical, antero-posterior andmedio-lateral [7], [8]. Among these, the verticalground reaction force (VGRF) has been known to be
the most prominent. Ground reaction forces can playin a role in challenging body balance control by

METHODS
Design and Setting
Quasi-experimental study was conducted inlaboratory room at College of sport science, Mahidol
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SEE - Bangkok, Thailand, Nov.11-13, 2019

University Thailand.

9260AA3; Klister Group, Winterthur, Switzerland)
and was generated data from Smart analyzer®, BTS
Bioengineering software (BTS Bioengineering,
Milan, Italy).

Participants
Ten healthy subjects (5 males and 5 females),aged 27.6±3.9 years (Mean±Standard deviation)
participated in the study. Subjects were interviewed
their demographic data and their physical problem
by the researcher. Inclusion criteria of the study
consists of no pain in lower limb extremity morethan three weeks before the experimental, no limit
range of motion of hip joint and knee joint, nounderlying disease and abnormality of lower limb
joint. Subjects were wearing a comfort shirt andshorts to avoid any uncomfortable movement.

Statistical Analyses
Descriptive statistics were used to describe
baseline demographics and findings of the study. A
Shapiro-wilk test was used to ensure the normal
distribution of the data. Paired t-test was used todetermine the differences of VGRF within group. Pvalue was set as less than 0.05 which defines as
significantly difference within group.
RESULTSIntervention
All 10 subjects (5 males and 5 females), aged
26.9 ±4.1 (Mean±SD) were participated in the study.
Subjects demographic data as show in Table 1.

Before starting intervention, subjects were sat on
the chair for 5 minutes and were asked for any signand symptoms such as dizziness and vertigo. They
were instructed an intervention procedure by the
researcher which included 3 trials are comfortablestep marching, Marching at 90-degree and walking(Fig. 1).

Table 1 Demographic data of ten subjects
Characteristic

Mean ± SD (n=10)

Age (year)

26.9±4.1

Height (cm)170.6±8.7

Weight (kg)67.6±12.2

2

23.1 ± 2.5

BMI (Kg/m )Paired t-test revealed no significantly differenceof VGRF (N/Kg) between right and left side inmarching 90 degrees (M90_Rt and M90_Lt), stepmarching (SM_Rt and SM_Lt), and walking (W_Rt
and W_Lt). All variables data are normal
distribution as show in Table 2.
Table 2 Comparison VGRF between right and left
side

Fig. 1 Pictures from left to right are comfortable stepmarching trials including marching at 90-degree trial
and walking trial, respectively.

Variables
VGRF (N/Kg)
p-value
M90_Rt11.25±0.52
0.764
M90_Lt11.23±0.54
SM_Rt
10.37±0.43
0.343
SM_Lt
10.43±0.51
W_Rt
10.13±0.84
0.678
W_Lt
10.09±0.62
Note: Mean±SD., Paired t-test., p-value<0.05
Abbreviation: M90_Rt and M90_Lt are VGRF of
Marching in 90 degrees of right and left side.,
SM_Rt and SM_Lt are VGRF of step marching ofright and left side., W_Rt and W_Lt are VGRF
walking of right and left side

Comfortable step marching trial is participant
flexion their hip and knee joint with comfortablespeed and raise the knee to the middle of thigh for 2
minutes. The researcher measured thigh length ofindividual and prepared reference rope that
instructed participant to reach the height level whilemarching. Marching at 90-degree trial is participant
flexion hip and knee joints at 90 degrees with theirindividuals speed for 2 minutes. Walking trial issubjects were instructed to walk barefoot with theirpreferred walking speed for 10 rounds on 2 force
plates.
Subjects were instructed to walk placing
their side handed foot on first force plate andfollowed by foot on second force plate. Verticalground reaction force data was collected by Klister
force plate with sampling rate 100 hertz (Klister

No difference between VGRF of left and right so
the researcher selected VGRF values of right side asa reference value. Step marching in 2 conditions andwalking was significantly difference when compare
788

SEE - Bangkok, Thailand, Nov.11-13, 2019

between each condition as shown in Table 3.

CONCLUSION

Table 3 Comparison between VGRF of 3 conditionsof right side

The objective of this study was to compare effectof two difference types of marching with walking on
average VGRF. The average VGRF were collectedfrom force plate and computed by software.
Marching at 90 degrees has higher average VGRF
more than comfortable step marching and walking
conditions. Interestingly, the similarity of average
VGRF between comfortable step marching andwalking may lead to conduct marching (1-1.2 BW)
as an exercise for elderly which should not induce
physical activity injurious as jogging and running(1.5-2.45 BW) may do.

Variables
p-value
M90_Rt and SM_Rt<0.001*
M90_Rt and W_Rt
0.004*
SM_Rt and W_Rt
0.438
Note: *= Significantly difference (p-value<0.05)
DISCUSSION
The objective of this study is to compare effectof two difference types of step marching withwalking on vertical ground reaction force (VGRF).
The result shows that average VGRF of marchingwith 90 degrees has significantly highest whencompared with step marching and walking. In
addition, no significantly difference between stepmarching and walking conditions. Previous studied
is investigated VGRF and running speed. They
founded VGRF increasing due to a speed movement[10]. According to factor that influences VGRF arebody mass and acceleration. In marching with 90
degrees, subjects need to move their segment toreach 90 degrees by pushing down against the force
plate more than other 2 conditions. According tosimilarly average VGRF between step marching andwalking, it seems to participant exert their force toachieve the movement equally.
The result shows that while marching an average
between 1-1.2 bodyweight of impact force in female
and male young adults and have per 1 bodyweighton walking. In similarly with previous study, Carden
and collogues founded marching has average VGRF
between 1.1 -1.2 percent bodyweight in trained men
and women but VGRF has increased to 1.3 percent
bodyweight in untrained men [11]. Hamill andcolleagues also examined VGRF on running andwalking conditions. They revealed that walking withspeed 1.36 m/s-1 has average VGRF is 7.78 N/kg[12]. Keller and colleagues demonstrated thatmaximum VGRF also gradually increase for 1.152.45 and 1.23-2.38 of percent body weight in female
and male, respectively when speed is also increasingfrom 1.5-6.0 m/s-1 [10]. The result indicates thatmarching exercise seem to gain less impact force
than jogging which not induces physical activity
injurious in the elderly especially in running. There
were four limitations in the study. Firstly, theresearcher did not use metronome to control speedof marching in both conditions. Secondly, theresearcher did not control movement of upper
extremity while marching. Thirdly, this study should
increase number of subjects to ensure effect ofmarching on VGRF. Fourthly, the future study
should increase sample size and control speed ofstep marching.

ACKNOWLEGMENT
I would like to grateful thanks to Dr. Wichai
Eungpinichpong, Ph.D. for kindly suggest and editorof my study. I would like to appreciate helpful to lab
officer for kindly help about the instrumentation inthis study and all participants from College of sportscience, Mahidol University.
REFERENCES
[1]

[2]

[3]

[4]

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[6]

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Jonsson E, Henriksson M, Hirschfeld H., Agerelated differences in postural adjustments inconnection with different tasks involving
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Dingenen B, Janssens L, Claes S, Bellemans J,
Staes FF., Lower extremity muscle activation
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cruciate ligament reconstructed subjects.
Clinical Biomechanics, Vol. 35, 2016, pp. 116–
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Iverson BD, Gossman MR, Shaddeau SA,
Turner ME., Balance performance, force
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Thiamwong L, Suwanno J., Effects of Simple
Balance Training on Balance Performance andFear of Falling in Rural Older Adults.
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Sherrington C, Tiedemann A., Physiotherapy inthe prevention of falls in older people. Journalof Physiotherapy, Vol. 61, Issue 2, 2015, pp.
54–60.

SEE - Bangkok, Thailand, Nov.11-13, 2019[7] Tresilian J., Sensorimotor Control andLearning: An Introduction to the Behavioral
Neuroscienceof
Action.
Macmillan
International Higher Education, 2012, pp. 1192.
[8] Redfern MS, Cham R, Gielo-Perczak K,
Grönqvist R, Hirvonen M, Lanshammar H.,
Biomechanics of slips. Ergonomics, Vol. 44,
Issue 13, 2001, pp. 1138–1166.
[9] Nigg BM, Wakeling JM. Impact Forces andMuscle Tuning, A New Paradigm. Exercise
and Sport Sciences Reviews, Vol, 29, Issue 1,
2001, pp. 37.
[10] Keller T, Weisberger A, Ray J, Hasan S, Shiavi
R, Spengler D., Relationship between verticalground reaction force and speed during
walking, slow jogging, and running. Clinical
Biomechanics, Vol. 11, Issue 5, 1996, pp. 253–
259.
[11] Carden PPJ, Izard RM, Greeves JP, Lake JP,
Myers
SD.,
Force
and
acceleration
characteristics of military foot drill:
implications for injury risk in recruits. BMJ
Open Sport Exercise Medicine, Vol. 1, Issue 1,
2015, pp. 1-7.
[12] Hamill J, Bates BT, Knutzen KM., Ground
Reaction Force Symmetry during Walking andRunning. Research Quarterly for Exercise andSport, Vol. 55, Issue 3, 1984, pp. 289–293.

790

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE EFFECTS OF WATERING RATES USING THE DRIP
IRRIGATION METHOD ON THE ROOT MASS GROWTH OF BIRD’S
NEST FERNS
1

Sawat Pimsuwan1 and Dowroong Watcharinrat1
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi, Thailand

ABSTRACTThe increasing demands of gardeners have made peat moss a popular option as a planting material. However,the price of peat moss has increased recently. Therefore, alternative substances for use as a planting material need
to be studied. The root of the bird’s nest fern offers a cheaper, easier to produce and more readily available source
for a planting material than peat moss. The objective of this research was to increase root mass growth by using
drip irrigation. With an experimental design using CRD, two-year old bird’s nest ferns with root mass sizes of 5
inches were watered by means of a drip irrigation method at rates of 200, 400, 600, 800 and 1,000 ml every 3 days.
The data measured were root mass height, root mass diameter, leaf length, leaf width and canopy width. The data
were analyzed by ANOVA and the differences between the means of treatment were compared by DMRT. The
research found that the ferns which received water at a rate of 800 ml produced a root mass height of 11.06 cm
and a root mass diameter of 11.93 cm. They were significantly different (p<0.05). The ferns which received waterat a rate of 200 ml produced a leaf length of 29.52cm and a leaf width of 9.55 cm. The amount of water causes
fern growth to significantly different (p<0.01). The 800 ml rate of drip irrigation also produced the largest canopy
width of 48.12 cm.
Keywords: Drip irrigation, Asplenium nidus, root mass bird-nest fern, peat moss
The roots of the bird’s nest fern develop cellulose
in cell wall appositions with yellow-brown pigments.
There are different shapes and sizes which occur inthe epidermal and the cortex of old roots [10]. Whenconsidering the benefits of natural materials such asthese ferns, it is especially interesting to explore theiruse in making planting material.
Currently, the most popular plant growing
material in horticulture is peat moss. In world
production, about 50 percent of peat moss is used for
agriculture purposes and the rest is used for energy[11]. In the growing media of almost all commercial
greenhouses, peat moss is used because of its nutrient
content and low pH [12]. Furthermore, it doesn’t
damage young plant roots, leaves plenty of air spacefor oxygen flow and allows for greater absorption ofwater for plant growth. This is why peat moss ispopular for use as a planting material; it offers a highquality horticultural growing media [13], [14], [15],16]. Also, peat moss is suitable for fern spore
germination in the early development stage of
gametophytes and transitioning into the young
sporophyte phase [17]. Gardeners can buy peat mossfrom garden centers or specialty shops but the pricehas increased rapidly [18]. Peat land is a source of
atmospheric methane (CH4) and a source of carbon(C) in the form of dissolved organic carbon (DOC)[19], [20]. Greater use of peat moss has been shownto damage the environment [21], [22]. Peat moss
extraction is a significant source of greenhouse gases

INTRODUCTION
The bird’s nest fern (Asplenium nidus) is an
epiphyte fern. It is native to the tropical rain forests inSouth East Asia and Africa [1]. The fronds (leaves)are slender, like a sword, and grow from the top centerof the rhizome in the root mass. The fronds can have
many shapes: wide-short, narrow-long or some frond
tips are forked. In the rainy season, some fronds cangrow to lengths of 150 cm and widths of 20 cm.
Fronds are shiny green, smooth, thin leaves with curly,
black midribs. Dark brown indusium covered sorus,
which develop from sporangium (spore producers),
have many parallel lines arranged obliquely toward
the center of the back of the fronds [2].
This fern provides an important role for thenatural nutrient cycle in tropical rain forest canopies[3], [4], [5]. Moreover, it offers a cool and moist
microhabitat for the canopy [6].
The bird’s nest fern offers many advantages. It
can be used for ornamental plants, potted plants,
hanging plants, and even mounted plants on tree
branches in gardens. It also possesses medicinal
benefits. Its antibacterial qualities justify its usage in
traditional medicines [ 7], [8]. Furthermore, it can beused as food [9].
In its natural state, the root mass of this fern
protects the rhizomes which grow in the middle of it.
These can attach to large tree branches or other things
with root masses.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 The growth of bird’s nest ferns by drip
irrigation every three days over 12 weeks

as well as a user of large amounts of land for its
growth [23], 24].
Research objectives need to focus on thepossibility of using bird’s nest fern roots instead ofpeat moss. This fern can be easily grown in thegeneral climate [25]. But the roots of this fern cansometimes not be of sufficient size. Increasing root
size by watering using the drip irrigation method has
been shown to be successful in previous experimentswith vegetables [26], [27]. Therefore, applying thismethodology to the bird’s nest fern roots should
produce results that enhance their size.

Water
Growth of bird’s nest fern (x̄/cm)
rate(ml)
RMH
RMD
200
10.93ab11.68b400
10.70ab11.68b600
10.56b
11.86ab800
11.06a11.93a1,000
10.98ab11.73ab
CV%
2.78
1.14
F test**
RMH = Root Mass Height, RMD = Root Mass
Diameter* = significantly different (p<0.05)

METHOD
Material preparation

Table 2 The growth of bird’s nest ferns by drip
irrigation every three days over 12 weeks

Preparation of plants: A total of 80 plants wereused in this study. All plants were two-year old bird’s
nest ferns. They were all planted in 6 inch pots.
Preparation of drip irrigation system: The
system is made up of a drip head, capillary tube, joints
and a water tank. All of these parts are connected tocreate the system, along with a cylinder and ameasurement tool.
Preparation of finely ground of bird nest fernroot: The bird’s nest fern is finely ground using agrinder and sieve.

Growth of bird’s nest fern (x̄/cm)
Water
rate(ml)
LL
LW
CW
200
29.52a
9.55a
47.19
400
25.03ac
8.32c
44.81
600
24.72c
8.12c
45.19
800
27.11b
9.21ab48.12
1,000
25.15c
8.86b
46.56
CV%
4.68
3.95
6.55
F test****ns
LL = Leaf Length, LW = Leaf Width, CW = Canopy
Width.
ns = non-significant, ** = significantly different(p<0.01)

MethodWith an experimental design using CRD, twoyear old bird’s nest ferns with root mass sizes of 5
inches were watered by means of a drip irrigation
method at rates of 200, 400, 600, 800 and 1,000 ml
every 3 days. The data measured were root mass
height, root mass diameter, leaf length, leaf width andcanopy width. The data were analyzed by ANOVA
and the differences between the means of treatment
were compared by DMRT.

Figures

RESULT
The growth of the root mass of bird’s nest ferns as
a result of using a drip irrigation method was studied
over 12 weeks. The ferns which received water at a
rate of 800 ml developed the best root mass height of
11.06 cm and the biggest root mass diameter of 11.93
cm. (Table 2, Fig.4,6,7) They were significantly
different (p<0.05). The ferns which received water at
a rate of 200 ml produced the longest leaf length of
29.52 cm and the widest leaf width of 9.55 cm. (Table
2, Fig.1,8) The amount of water causes fern growth tosignificantly different (p<0.01). The ferns which
received water at a rate of 800 ml produced the largest
canopy width of 48.12 cm. (Table 2, Fig.4,9)Fig. 1 watering rate at 200 ml

792

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 2 watering rate at 400 ml

Fig. 5 watering rate at 1,000 ml
Root Mass Height

11
10.5

cm

10
9.5
9
0

4

8

12

Week
Fig. 6 Root Mass HeightFig. 3 watering rate at 600 ml
Root Mass Diameter
12
11.5
cm

11
10.5
10
9.5
9
0

4

8
Week

Fig. 4 watering rate at 800 ml

Fig. 7 Root Mass Diameter

793

12

SEE - Bangkok, Thailand, Nov.11-13, 2019season [28]. The root mass of this fern can be used asa fern planting material [29].
However, drip irrigation is not the best method forincreasing the bird’s nest fern root mass because theroot epiphyte cannot absorb enough water. New
studies of other methods of irrigation, including fog
or mist watering, should be conducted to look for abetter alternative.

Leaf Length

35

cm

30
25
20
15
10
0

4

8

12

ACKNOWLEDGMENTS

Week
This research was partially funded by The Facultyof Agricultural Technology, Rajamangala Universityof Technology Thanyaburi, Thailand. And this text
was edited by Mr. Bruce Groening.

Fig. 8 Leaf Length
Leaf Width

cm

12
10

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different rates of watering by the drip irrigation
method. The study revealed that the largest root mass
height and diameter came from the watering rate of
800 ml every 3 days. Some epiphyte ferns like dry andwet water such as stag horn ferns [17]. In addition,
when the root mass of the bird’s nest fern becomes
dry, it can absorb a lot of water during the rainy

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795

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE INFLUENCES OF HEAVY METALS AND MAJOR IONS INSTREAM WATERS, RUNNING IN SERPENTINE, LIMESTONE, AND
CLOSED-MINE AREAS, ON MACROINVERTEBRATECOMMUNITIES, KINKI AND CHUGOKU, JAPANAkio Nishida1 and Hiroyuki Ii2
CLERK Memorial International High School, Hyogo, Japan
2
Faculty of System Engineering, Wakayama University, Wakayama, Japan
1

ABSTRACTThe influences of water chemistry on macroinvertebrate communities were investigated at 24 study sites infour areas with different geological characteristics: closed-mine, serpentine, limestone and reference areas. Ouraims of this study were to clarify how macroinvertebrate communities in different geological areas are affectedby chemical variables. Based on the results from nonmetric multidimensional scaling and distance-based
redundancy analysis data, chemical variables in running waters had the strong relationships to macroinvertebrate
communities. In a closed-mine area, they were affected by Zn and Pb, and only Baetis spp. was the dominant
species in an environment polluted by heavy metals. In serpentine areas, water chemistry was characterized byhigh concentrations of Mg2+ and Ni, and those chemical variables affected macroinvertebrate communities. From
the result of distance-based redundancy analysis, we noted that the communities in this area were classified into
three groups: (1) affected by Ni, (2) affected by Mg2+, and (3) affected by other heavy metals such as Zn. In
limestone areas, water chemistry was characterized by a high Ca2+ concentration. However, we could not detect
clear influences of this ion on invertebrate communities in this area. As a whole, we saw that macroinvertebrate
communities were influenced by the geological characteristics of their habitats, and also saw that thosecharacteristics were a main environmental factor in community construction.
Keywords: macroinvertebrate, heavy metals, serpentine, limestone, geology

serpentine geology influences macroinvertebrate
communities, we carried out this study at 24 sites
with four geological characteristics: closed-mine,
serpentine, limestone and reference areas.

INTRODUCTION
Benthic macroinvertebrates in mountain streams,
are greatly affected by chemical and physicalfactors. These factors include the nature of
substrates forming streambeds, water temperature,
and water quality, especially concerning waterpollution. The size of main streambed materials
affects their mobility and contributes to greatermacroinvertebrate biomass. Especially, the watertemperature in running water affects the emergenceof aquatic insects such as stenopsyche marmorata(Trichoptera), which is a dominant species inJapanese rivers [1]. Water pollution has often beenstudied as a factor affecting macroinvertebrate
community structures. Water pollution arising fromdrainage of industrial and closed-mine areas has
been shown to affect macroinvertebrates [2]. Similar
studies have also been conducted in the United
Kingdom, Australia and the United States, studies
that made clear that macroinvertebrate communities
had been influenced by heavy metals such as Zn andPb [3]. Water quality in running water is impacted
by human activities, land use, vegetation, and main
drainage. However, studies, especially those
focusing on geological characteristics, of how waterchemistry affects macroinvertebrate communities
have been rarely conducted. Based on the hypothesisthat water chemistry in running waters withSTUDY SITES
Eight sites (st.1–st.8) were located in the closedmine area around the Ikuno mine in the central partof Hyogo Prefecture (Fig. 1). That mine was closed
in late March, 1973 after operating for about 1200
years. The elevations of sites in this area ranged
from 343 m to 513 m. Eleven sites (st.9–st.19) ofserpentine geology were mostly located in Yabu
City in the northern part of Hyogo Prefecture, with
two of these sites (st.11 and st.12) in Oecho,
Fukuchiyama City, Kyoto Prefecture (Fig. 1). All of
the streambeds of the 11 sites in this area arecomposed of serpentine rocks and the land aroundthe sites is largely covered by serpentine soils
produced after weathering of the rocks.
Serpentine rocks in Japan, described by Suzuki [4],are found along two south–northeast-trending belts
in Kyushu, Shikoku, and central and southern
Honshu. The serpentine areas in Yabu City andOecho, are two wide belts in Honshu.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Benthic macroinvertebrates were qualitatively
collected in spring and autumn, 2012 using a net(mesh size 0.22 mm) with a wire gauze (25 cm × 25cm). Sampling was replicated four to eight times.
The net was placed just downstream and then stones
larger than about 5 cm were carefully removed.
Stones were washed into the net, and substrates
within the area were distributed to depths of 20 to 30
cm so that detached organisms would flow into thenet. The organisms collected in the net were
removed to a container half-filled with water, andthose attached to stones and the net were picked off
with tweezers. The contents, including theorganisms, were placed into a plastic bag with astopper and preserved in 5% formaldehyde solution.
After removal to the laboratory, the organisms were
sorted and counted[5]. Early instar larvae and someother organisms were not identified at species levels.

Fig. 1 Twenty-four study sites

Data Analysis

Two sites in the limestone area were located in
Taishaku Valley, Tojocho, in the northern part ofHiroshima Prefecture (Fig. 1). Two sites, st.20 andst.21, were selected in the Mito and the Taishaku
rivers, respectively. The streambeds of the two rivers
have substrates of limestone rocks, and aresurrounded by huge limestone walls.
In addition to these sites, we selected threereference sites that were established in the YadaRiver system in the northern part of Hyogo
Prefecture. The three sites (st.22, st.23 and st.24
were located in the Yamada, Kumanami and Konyo
rivers, respectively (Fig. 1). These sites were chosen
for their geological characteristics (Yamada River:sedimentary rocks; Kumanami River; quartz
porphyry; Konyo River; basalt).

Multivariate analysis and ordination ofmacroinvertebrate communities
First, macroinvertebrate communities wereclustered into several groups by K-medoids (nonhierarchical clustering method) [6]. The number ofclusters was decided by maximizing the averagesilhouette width[6]. Indicator species of each cluster
were selected using the indicator values (IndVal)[6].
Second, we performed nMDS (nonmetricmultidimensional scaling ) to investigate among the
24 invertebrate communities and environmental
variables. After carrying out that analysis, we
conducted dbRDA (distance-based redundancy
analysis) to determine the appropriate analyticalmethod. For investigating the relationship between
feeding groups of macroinvertebrates and chemicalvariables, dbRDA was also carried out. We
performed the estimation of species diversity,
clustering, nMDS and dbRDA using packages ofcluster (pam), labdsv (IndVal) and vegan [7] in thesoftware environment R 3.3.2 [8].

SAMPLING AND ANALYTICAL METHODS
Water Sampling and Analytical Methods
Water samples were collected in spring and autumn
from 2010 to 2012. Water temperatures, pH,
conductivity (EC), dissolved oxygen (DO) andtotal dissolved solids (TDS) were measured at thesites using a sensor probe (Horiba W-23XD). Water
samples were collected in two polyethylene
bottles(100 mL) before transportation to thelaboratory. The water samples were analyzed by
ICP-AES (inductivity coupled plasma atomic
emission spectroscopy)(SPS1700HVR)
formeasurements of heavy metal concentrations. Ion
chromatographic analysis (DIONEX ICS-1500) wasused to analyze other nonmetallic ions, includingCa2+ and Mg2+. Water samples were stored in arefrigerator at about 10°C until chemical analysis
was performed.

RESULT
Faunal Composition and Species Diversity
Faunal composition
Sixty-two macroinvertebrate taxa were identified
from 24 sites, collected in spring and autumn, 2012.
A total of 4517 individual species, were collected at
24 sites. We clustered 24 communities into six
groups using the K-medoids method [6]. The resultsof nonhierarchical clustering were as follows:cluster1 (st.1, st.11, st.18 and st.23), cluster2 (st.2,
st.3, st.14), cluster3 (st.4, st.5, st.6-st.10, st.15, st.19),
cluster4 (st.13), cluster5 (st.16 and st.17) andMacroinvertebrate Collection and Identification

797

SEE - Bangkok, Thailand, Nov.11-13, 2019cluster6 (st.20-st.22, st.24). Average silhouette
values of cluster1 showed a lower value (0.065) thanthose of other clusters, because cluster1 wasrepresented in a variety of communities. Especially,
those values at st.1 and st.11 were −0.097 and−0.036, respectively. However, the average value ofcluster5 was 0.800, indicating a high resemblance ofcommunities within that cluster. Indicator species ofeach cluster, estimated by the IndVal method, areshown in Table 1. From cluster1 to cluster3, we
could not detect a significant species (p<0.05).
Significant indicator species from permutations wereas follows: Ephemera orientalis

fourth column shows the IndVal values and p-valuesof permutations
ClusterNumberof sites

Averagesilhouettewidthcluster1
cluster2
cluster3
cluster4

5
3
9
1

0.007
0.121
0.280
0.000

cluster520.800

cluster6

4

0.220

Total

24

0.24

[A]: Closed-mine area

Fig. 2 Silhouette plots of 24 study sites; averagesilhouette width = 0.24
Ephemera japonica, Epeorus ikanois and Epeorus
curvatulus (Ephemeroptera); and Stenopsyche
marmorata (Trichoptera).

[B]: Serpentine area

Species Diversity
The exponential Shannon–Wiener diversity index(ESI) and Simpson’s inverse diversity index (SDI)
were estimated at each site (Fig. 3[A]–[D]). In theclosed-mine area, the two indexes are lower thanthose values in another areas. Especially, the ESI atst.4 and st.5 were quite low, at 1.153 and 1.384,
respectively, in comparison with sites in thereference area. In the serpentine area, the highest
value of the ESI was 12.057 at st.11, and the lowest
value was 2.834 at st.16, with slightly lower values
obtained in the reference area sites. In the limestonearea, the ESI and SDI at two sites were quite similar
with those at sites in reference area. Especially, the
ESI of 11.680at st.20, which was similar to thehighest value of 12.340 at st.22.

[C] : Limestone area

[D] Reference area

Table 1. Indicator species of each cluster. The
798

Indicator species(IndVal;permutation
p<0.05)

Ephemeraorientalis (0.900;
p<0.0386)
Ephemerajaponica (0.809;
p<0.0112)
Epeorus ikanois(0.776; p<0.0256)
Epeoruscurvatulus(0.938; p<0.0002)
Stenopsyche
marmorata(0.779; p<0.0006)

SEE - Bangkok, Thailand, Nov.11-13, 2019

St.20

L

0.004

0.001>

0.001

0.002

St.21

L

0.002

0.001>

0.002

0.001

St.22

R

0.004

0.001>

0.001

0.001

St.23

R

0.004

0.001>

0.001

0.001

St.24

R

0.001>

1.30

0.001

0.001>

Note: Geology: M = closed-mine area, S =serpentine area, L = limestone area and R =reference area with sedimentary rocks and basalt

Fig. 3 Left figure (0) shows taxa number sampling at
the study sites. Middle figure (1) shows the
exponential Shannon–Wiener diversity index{expH’= exp[-∑piloge(pi)], where pi is the proportion ofabundance for species i}. Right figure (2) shows
Simpson’s inverse diversity index (1/D). The dashedlines express the expectations by attenuation, and thedotted lines express the expectation by extrapolation.
The shaded cones show 95% confidence intervals
obtained by bootstrap methods. [A] Closed-minearea (st.1–st.8), [B] Serpentine area (st.9–st.19), [C]Limestone area (st.20–st.21).[D] Reference area(st.22–st.24)
Water Chemistry
Table 2. Chemical variables (mean values) of the 24
study sites, especially for heavy metals, measured
from spring 2010 to autumn 2012. The (*) shows thesite samplings and measurements in spring, 2012
Study
sites

Geology

Pb

Cu

Zn

Ni

mgL-1

mgL-1

mgL-1

mgL-1

St.1

M

0.007

0.001>

0.046

0.002

St.2
St.3
St.4
St.5
St.6
St.7

M
M
M
M
M
M

0.057
0.013
0.021
0.116
0.087
0.098

0.001>

0.138

0.004
0.430
1.273
1.457
0.014
0.039

0.003
0.014
0.005
0.005
0.002
0.002

St.8

M

0.007

0.001>

0.018

0.001>

St.9

S

0.008

0.001

0.001

0.022

St.10

S

0.007

0.002

0.003

0.062

St.11

S

0.014

0.001

0.111

0.011

St.12

S

0.008

0.001>

0.003

0.010

St.13

S

0.080

0.082

0.010

0.448

*St.14

S

0.115

0.764

0.001

0.588

*St.15S

0.042

0.001>

0.021

0.019

*St.16

S

0.207

0.231

0.021

0.568

*St.17

S

0.110

0.232

0.003

0.838

*St.18

S

0.129

0.247

0.001

0.532

St.19

S

0.113

0.253

0.006

0.519

0.001>

0.035
0.043
0.001>

799

Fig.4 Scatter plots between
environmental variables

all

pairs

of

Mean pH values at the 24 sites ranged from 7.1 to
8.3 with the highest values of 8.1and 8.3 at st.20 andst.21 in limestone area. The pH values in thereference area ranged from 7.6 to 7.8, which wereslightly higher than in the closed-mine andserpentine areas. The water chemistry at eight sites(st.1–st.8) in the closed-mine area was characterizedby high concentrations of heavy metals, such as Zn,
Pb, Cu, Fe and Mn, compared with that of three sites(St.22–st.24) in the reference area. Mean
concentrations of Zn were 1.27 mgL-1 at st.4 and1.46 mgL-1 at st.5, the highest values of all the sites.
The other heavy metals measured at sites in theclosed-mine area also were in high concentrations

SEE - Bangkok, Thailand, Nov.11-13, 2019

(Ca2+, Mg2+, Fe, Zn, Cu and Ni). In this model, theconstrained inertia (sum of the squared distance) was
2.613 (51.6% of the total inertia). The Eigenvalues
for the constrained axes were 1.381 (axis 1) and
0.708 (axis 2). We evaluated this model by ANOVA,
then obtained the significant value (Pr(>F)=0.13). In
this analysis, the six clusters located separately.
Cluster1 and cluster4 were widely spread above axis
1, representing the relationship to Mg2+. Cluster5,
located at the top of right side, showed a strong
relationship to Ni. Moreover, cluster3, situated on
the opposite side of cluster5, had a strong
relationship to Zn.

(Table 2). Water chemistry in the serpentine area
was characterized by very high Mg2+ and Ni
concentrations (Table 2). In the serpentine area, themaximum concentration was 21.3 mgL-1 at st.10 andthe minimum was 11.9 mgL-1 at st.19 (Table 2). The
water chemistry of the sites in the limestone area
was characterized by high calcium (Ca 2+)
concentrations at two sites, 31.2 mgL-1 at st.20 and
18.0 mgL-1 at st.21. These values were about three orfive times higher than the calcium concentrations of
the reference area. Correlations based on Pearson’s
correlation coefficient (r) among chemical variables
are shown in Fig. 4. We identified greater values in
the relationships between two chemical variables asfollows: Ca2+–F- (r=0.69), Mg2+–Ni (0.52), Pb–Ni(0.73), Zn–F- (0.96) and Ni–Cu (0.74) (Fig. 4).
Ordinations
We carried out nMDS mainly to investigate therelationships
among24
macroinvertebrate
communities. Eigenvalues of the two axes were
1.252 (axis 1) and 1.001 (axis 2). We intended todisplay

Fig. 6 Ordination by dbRDA with biplots of six
chemical variables
DISCUSSION
In the serpentine area, the richness of the chemicalvariables, such as Mg2+ and Ni, depend on theprocess of serpentinization, which involves theconversion of peridotite to a serpentine form mainly
by hydration of primary igneous minerals[13].
Under those conditions, it might be said that thecommunities in serpentine area are divided into threegroups: (1) one in which nickel (Ni) influences theconstruction of the community, (2) one that is
affected by the influence of magnesium ions (Mg2+),and (3) one that is influenced by other chemicalvariables, such as Zn and SO42-. From the result ofdbRDA, we see that heavy metals have importantroles in controlling the construction of invertebrate
communities. Ii and Nishida [9] reported that
Protohemes grandis (Neuroptera) accumulated
heavy metals in their bodies. In the limestone area, it
is possible that invertebrate communities are slightly
affected by Ca2+. However, we could not detect clear
influences on invertebrate communities because ofother factors, such as substratum instability, watervelocity, suspended solids, and benthic algae. In theFig. 5 Ordination by nMDS of 24 sites {distance =Morisita–Horn, stress = 0.152 (three dimension k =3)}six clusters, but they were impossible to describe
because of nonhierarchical clustering. This nMDS
ordination picked up seven significant (Pr<0.1)chemical variables, pointed out as vectors, such as
water T (water temperature) ( Pr=0.004), F- (0.077),
Na+ (0.023), K+ (0.100), Ca2+ (0.012), Pb (0.004)
and Ni (0.035). Moreover, we performed dbRDA(distance-based redundancy analysis) to investigate
in more detail the relationship between two. We
constructed the model with six chemical variables
800

SEE - Bangkok, Thailand, Nov.11-13, 2019closed-mine area, invertebrate communities might
be effected by Zn, as is true in the st.10, st.15, andst.19 communities in the serpentine area. Moreover,these high concentrations probably result from thesphalerite and metal sulfides of the stream beds inthis area. Under these conditions, the dominant
species were Baetis spp. (Phemeroptera) andAthericidae spp. (Diptera). These species could beresistant to water pollutions, and might be a possible
macroinvertebrate index of water pollution.
Therefore, it is clear that most of macroinvertebrate
communities in the serpentine, closed-mine andlimestone areas are affected by geology, and that thegeological characteristics of their habitats are themain factors that define their community structuresand feeding methods.

REFERENCES[1] Nishida A., and Nishimura N.., Life history
Stenopsychidae) in the Sugihara River of
Stenopsyche marmorata Navas (Tricoptera:of Kakogawa River System.1. Voltinism,
survival numbers of larvae and pupae andphotoperiodic influence on the life cycle, Hyogo
Fresh Water Biology, Vol.60, 2008, pp.31-51.
[2] Watanabe N., Harada S., and Komai Y., Longterm recovery from mine drainage disturbance ofa macroinvertebrate community in the Ichi-kawa
River, Japan, Hydrobiologia, Vol.429, 2000,
pp.171-180.
[3] Schultheis A.S., Sanchez M., and Hendricks
A.C., Structural and functional responses of
streaminspects
tocopperpollution,
Hydrobiologia, Vol.346, 1997, pp.85-93.
[4] Suzuki J., Ultramafic rocks and associated ore
deposits of Hokkaido Japan, Journal of theFaculty of Science Hokkaido University, Series 5,
Vol.8, 1952, pp175-210.
[5] kawai T., and Tanida K., Aquatic insects ofJapan: manual with keys and Illustrations, Tokai
university Publishing, 2005, Tokyo.
[6] Borcard D., Gillet F., and Legendre P.,
Numerical ecology with R -Second Edition- ,Springer, New York, USA, 2011, pp59-160.
[7] Oksanen J., Blanchet FG., Kindt R., legendre P.,
Minchin PR., O’Hara RB., Simpson GL.,
Solymos P., Stevens MHH., and Wagner H.,
vegan: Community Ecology package. R package
version 2.0-10., Available from: http://CRAN. Rproject. org/package=vegan, 2013.
[8] R Core Team, R: A language and environment
for statistical computing. R Foundation for
statistical computing. Vienna, Austria, 2014.
[9] Ii H., and Nishida A., Effectiveness of using
river insect larvae as index of Cu, Zn and As
contaminations in rivers, Japan, Second
International Conference on Science, Engineering& Environment (proceeding paper), 2016.

CONCLUSION
From this study, the water chemistry of runningwaters in four areas with different geologicalcharacteristics contain higher concentrations ofchemical variables. Macroinvertebrate communities
in the serpentine area were affected by Ni and Mg2+.
Depending on the effectiveness of the two ions,those communities can be classified into threegroups. This is very interesting to us when
considering the relationship between the communityand geology. However, we cannot identify the
influence of geology on the construction ofcommunities.
Onthewhole,
geologicalcharacteristics of habitats are the main factors for theconstruction of macroinvertebrate communities.
ACKNOWLEDGEMEMENTS
We thank Dr. Noboru Nishimura, Presidentof Hyogo Freshwater Biology, for providing us withmuch useful advice and promoting our study inadvance. We also thank Dr. Yoshinari and Dr.
Miyahara of Idea Co., Dr. Taniguchi of Wakayama
University and Mr. Nobutaka Uemura of Mitsubishi
Electric Business Systems Co. for their help withanalyzing the concentrations of chemical ions in therunning waters and biostatical analysis.

801

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

LANDSCAPE OPPORTUNITIES AND PREFERENCES FORCHOOSING RECREATIONAL PLACES OF MEGALOPOLISRESIDENTS (ON EXAMPLE OF ST. PETERSBURG)
Pogodina V.1, Matveevskaya A.2, Filippova I.3, Evseeva L.4 and Evseev V.5
Institute of Business Communication, Saint-Petersburg State University of Industrial Technologies andDesign, Russia
2
Department of International Relations, Saint-Petersburg State University, Russia
3
Institute of Humanities and Social Sciences, Saint-Petersburg University of Management Technologies andEconomics, Russia
4
Humanitarian Institute, Peter the Great St. Petersburg Polytechnic University, Russia
5Institute of Physical Culture, Sports and Tourism, Peter the Great St. Petersburg Polytechnic University,
Russia1

ABSTRACT
A resident of a large city is increasingly in need of a complete rest in the bosom of nature, enjoy the peace andbeauty of landscapes. The administration of megacities is concerned about the problems of preserving the naturalenvironment and creating within the city limits a network of recreational areas where recreational activities can beorganized. The necessity and importance of establishing a network of specially protected natural areas within themetropolis is not in doubt. But the status of the created nature reserves implies, for the most part, prohibitions andrestrictions for the organization of recreational activities. A detailed description of recreational opportunities forthe rational use of individual components of the city's natural environment is presented. The authors conducted ageoecological analysis of the allocation of recreational areas in large cities. Features of nature that should beconsidered when designing recreational areas in large cities, on example of St. Petersburg, are noted. The processof using network of specially protected natural areas of megacities as destinations for ecological excursion andtourism activities will be optimal if the landscape features of these areas are considered, the use of modern world
and domestic experience in the designing of conditions for the stay of recreants and excursionists.
Keywords: Recreational places, Specially protected natural areas (SPNA), Geoecological analysis, Ecologicaltourism, Tourism-recreation activity

The concept of the Federal target program“Development of domestic and inbound tourism inRussian Federation (2019-2025)” was approved by
the order of Government of Russian Federation No.
872-p, signed on May 5, 2018. The head ofGovernment Dmitry Medvedev points out thefollowing: “Growing interest in cultural, educationaland ecological tourism focused on recreational
activities in nature is considered a global trend. This
makes Russian Federation an even more attractive
tourist destination for Russian and foreign tourists.
The main regions for the development of eco-tourism
in Russia are concentrated in Siberian, Far Eastern,
Volga, Ural, North-Western, North Caucasian andSouthern federal districts. The Agency of Tourism
Statistics reports that more than 9 million people visit
natural national parks and reserves of Russia
annually” [3].
Landscape features play a leading role in ecotourism. Natural parameters are considered asresources and conditions for organization ofrecreational activities by the nature of the impact on

INTRODUCTION
One of the tasks of tourist-recreational activity is
to optimize environmental management. Recreationin the lap of nature, using natural resources andconditions, occupies a special place in this regard.
Organization of this type of recreation is designed tominimize damage to the environment [1]. Experts,
discussing the organization of eco-tourism, use thefollowing terms for its characteristics: "biotourism","natural", "green", "soft", "quiet", "non-tech". The
Russian law on tourism explains ecotourism as travel
for the purpose of environmental education andtraining. At the same time, eco-tourism should
consider the protection of local socio-cultural sphere,be economically effective and contribute to thedevelopment of those regions where it is organized[2]. Environmental protection activity (for example,
garbage-collecting) is not a mandatory feature thatshould determine the recreational program related to
eco-tourism.

802

SEE - Bangkok, Thailand, Nov.11-13, 2019

recreation. Natural components and their
combinations are evaluated as factors contributing to
the development of certain types of recreational
activities. Conducting the estimation of touristrecreational potential of territory, it is necessary to
determine the complex of leading conditions andfactors, both contributing to and limiting theecological and recreational development of the region[4].
St. Petersburg is known as the main center oftourism in Russia. 8.3 million tourists visited the city
in 2018 [5]. Unfortunately, only a few visitors seek to
re-visit St. Petersburg. At the same time, the numberof residents of megapolis and the adjacent Leningrad
Region exceeds 7 million people [6]. The city has
gained fame as the cultural capital of country with a
combination of developed infrastructure and culturaland historical resources. Traditional types of tourism
are cultural, educational, business and sports andrecreational. A variety of landscape conditions is anecessary and enough potential for development
health, ecological, cruise and extreme types of
tourism. Rural and ethnic travels are developing.
City parks and urban specially protected naturalareas are the most important condition for effective
recreation for residents of megalopolises and tourists
arriving, and this city with different purposes.
Traditional activities for the territory of Large St.
Petersburg are visiting recreational natural objects,
rest on nature.

protected areas can create a certain socio-cultural load
and leads to a change in nature [8], although its scale
is usually incomparably smaller compared to those inindustrial and agricultural production. Uncontrolled
flow of tourists can worsen the environmental
situation [9]. Consequently, it minimizes thepossibility of further functioning of the territory, notonly as protected, but also as recreational.
The following types of assessments are necessary
for research of ecological and recreational potentialof SPNR:- ecological (determination of the backgroundecological state of territories and water areas,
identification of local areas attractive for organizing
eco-tours and at the same time possessing enoughenvironment sustainability, diagnostics of the level ofenvironmental safety for tourists);- technological (consideration of the functional
suitability of resources);- physiological (determining the degree ofcomfort conditions);- psychological (revealing the level of aesthetic
qualities);- cost (for the calculation of tourist rent) [10].
Modern domestic practice offers tourists as an
eco-tourism tours within SPNA - national and naturalparks, nature reserves, etc. The objects of ecologicalexcursion show and the territories of visiting within
the framework of eco-tourism are not only natural,
but also cultural attractions, including naturalanthropogenic landscapes of different genesis [11].
The choice of visited objects is determined not somuch by uniqueness, but by the degree of awarenessof possible visitors. One of sustainable directions of
tourism development is associated with trips tounique natural and geographical objects. Destinationsof eco-tourism world level are the objects of the world
Natural Heritage List of UNESCO [12].
Modern vacationers are showing increasing
interest in areas classified as areas with extreme
natural conditions for human life. These can be spaces
with a harsh cold climate, with animals that areespecially dangerous to human life and health; areas
which are particularly affected by the consequencesof natural disasters, or anthropogenic accidents,
activities that turned the area into a territory
dangerous to the life and health of the person on it.
Tour operators are looking for new forms oforganization in such areas of recreational activities[13].
Modern man especially needs a kind of rest fromthe intense rhythm of city life [14]. The most common
trips using natural resources are recreational(relaxation) and health (rehabilitation). Active, sports
recreation takes the second place. These are rafting onrivers and lakes, including yachting, trekking,mountaineering and climbing, skiing tourism, etc.
Popular leisure activities among Russian are hunting
and fishing, as well as amateur collection of

MATERIALS AND METHODS
Landscapes intended for use for recreation arestudied by a special type of landscape geography recreational landscape science. Determination ofeffective ways of using such complexes is the mostimportant tasks of recreational landscape studies.
Many countries worked out and widely apply avariety of techniques that allow to give acomprehensive assessment of projects of tourist andrecreational development of territories. Foreign
methodologies that are used to assess the projects of
tourist and recreational development territories are
considered: Environment Impact Assessment (EIA);
Assessment of current capacity (Assessment ofCarrying); Visitor load accounting (Visitor Impact
Management - VIM); Limits of Acceptable Change(LAC) [7].
One of the forms of environmental management
is the allocation and development of specially
protected natural reservation (SPNR). Such territories
have different status. Placing of industrial enterprises
and carrying out agricultural work is prohibited inmost of them. In some of them recreational activities
are allowed. The main task of protected areas, related
to nature conservation, is often in conflict with thetask of increasing the intensity of tourist visits to theprotected area. Recreational development of803

SEE - Bangkok, Thailand, Nov.11-13, 2019mushrooms, berries, medicinal plants. Some tourists
decide on nature-oriented tours with a desire to test
themselves in extreme programs. So-called "survival"
tours. Numerous offers on the market of recreational
services relate to adventure recreation (diving,caving, visiting the area, the natural features of which
are exclusively exotic, etc.) [15].
Visits of the so-called “Norwegian (rope) parks”
have become very popular. Norwegian parks are
particularly attractive for lowland areas devoid ofsignificant rock formations that can attract climbers
to natural obstacles [16]. The most significant
problems of the development of a network of suchparks are: not mandatory, but voluntary certification;lack of proper control and security; possible
aggravation of environmental problems in the area
where such parks are created and actively used.
Another trend of our time is the desire to use
unconventional types of vehicles. Cycling is one of
the available alternatives to the car. Cycling tourism
is one of the types of sports tourism, which consistsof cycling routes containing bicycle-specificobstacles. The problem for organizing cycling is thelack of the necessary infrastructure, including all theelements that ensure the functioning of cycling: thecycle path or cycle track system, cycle parking, signs,
traffic lights, road signs for cyclists, recreation
centers, rental centers and the system of supporting
bicycle traffic. Cycling is becoming an increasingly
popular form of outdoor activities. The growth of its
popularity is associated with the fashion for a healthy
lifestyle.
Experts consider equestrian tourism as a form of
eco-tourism. It is gaining popularity in the global
tourism industry. Equestrian tours are a range ofservices, including horseback riding training, classes
in the open arena, rides on equestrian routes ofvarying degrees of difficulty, equestrian equipment,
accommodation, feed and additional services. Riding
skills are not required, as beginning of tourist rest is
educating to the receptions of handling a horse andtraining on riding. The organization of equestrianroutes can have a negative impact on the naturalcomplexes along which they will pass. Designers
need to consider the ecological capacity of landscape,use technologies for cleaning routes from household
waste, the appearance of which is inevitable.

observed at times. Changeable mode of atmosphericpressure is determined by the geographical locationof the territory. Sudden pressure drops can negatively
affect the well-being of even healthy people. People
with diseases of the cardiovascular system suffer the
most. Variability, instability of weather creates
serious difficulties for synoptic forecasting in St.
Petersburg [17].
From average data a steady snow cover lies in thesuburbs of St. Petersburg for about 140 days. The
height of the snow cover is small due to thaws and is30-40 cm by the end of winter [18]. However,
especially warm years were observed repeatedly,
when the snow-cover was not formed during all
winter. This makes it difficult to predict theorganization of recreation for people in the territory
in winter. In general, the climatic conditions of St.
Petersburg are characterized as relatively favorable:
summer rest is short, unstable weather conditions; inwinter, frosty weather can be replaced by long thaws.
Therapeutic recreation is organized on a largehilly or ridge relief, where the slightly hilly or
undulating terrain is relatively favorable. The relief ofgreater part of the described territory is exactly likethat. The area, where forested hills are combined withdeep hollows, is very picturesque. This nature of thesurface contributes to the development of hiking andcycling. The most favorable conditions fortherapeutic and recreation are available on the
Karelian Isthmus in the Northern and North-Westernregions of Greater St. Petersburg.
Urban areas are washed by the Gulf of Finland of
the Baltic Sea. Neva connects St. Petersburg with thewaters of the largest European lake - Ladoga. In St.
Petersburg, the swimming season averages 60 days from mid-June until the end of August (the durationof the swimming season is determined by the numberof days with water temperatures above +170 C) [19].
The shores of the Gulf of Finland are characterized bygood sandy beaches and sandy bottoms. Beaches
along the Northern coast of the Gulf of Finland areespecially popular in St. Petersburg. However, thebeaches are not equipped with the necessary
infrastructure everywhere. Vacationers accumulate inareas of equipped beaches, as a result of sanitaryhygienic indicators of the beach area are reduced.
When designing a recreation area near the water, it isnecessary to specify the rate of additional recreationalload along the length of the coastline, depending on
the specific natural complex.
Conditions for yachting are available in the Gulf
of Finland. This is a large area with enough depth(from three meters) and significantly indented
coastline (sailing ships can take refuge in a strongwind). However, the infrastructure for maintenanceof yachts in the city still does not exist. Large urban
water reservoirs are increasingly used for jet skiing,
motorboats and windsurfing. The Gulf of Finland,

RESULTS
The main feature of the climate of St. Petersburg
is the lack of heat and excess moisture. The territory
is in area with a shortage of ultraviolet rays. Real
opportunities for climate therapy are available on the
territory of Large St. Petersburg. However, theoptimal period for its implementation is short.
Possible strong winds of winter and autumn can beconsidered negative factors for the development ofrecreation. Squall winds with considerable power are
804

SEE - Bangkok, Thailand, Nov.11-13, 2019lakes and rivers of the region are covered with ice formore than four winter months.
Most of the rivers that flow through the territoryof St. Petersburg and its suburbs have a calm,balanced character. Rivers and lakes of the suburbs of
St. Petersburg allow to develop family tourism onboats and rafts. This type of tourism does not pursue
sports goals, it can be practiced by people who lovemeasured rest on the water. Water cruises (includinginternational ones) are one of the priorities of tourism
development. Large water areas can be used more
intensively for motor ship, cruise tourism (Baltic,
Neva, Ladoga, Svir, Onega). Some limitations to thedevelopment of ship rest will be in high rates of storm
frequency, especially in the autumn months. Shortwaves are ways to induce a strong pitching on theBaltic and Lake Ladoga. A serious obstacle to thefurther development of motor ship tours is the lack ofappropriate berths along the routes of vessels running.
The Central part of St. Petersburg offers tourists
especially popular walks on boats, river ships(including those capable of passing under low small
bridges of the central part of the city).
Mineral waters and therapeutic muds are available
on the territory of St. Petersburg. Sodium chloride
sources related to the Cambrian deposits are foundalmost everywhere. These waters are represented
most widely on the Karelian Isthmus (Sestroretsk,
Gorskaya, Lysii Nos, Devyatkino, Vsevolozhsk).
These waters are used for balneotherapy in local
health resorts, they normalize the body's metabolism,and have a beneficial effect on the activity of thecentral nervous system. The most famous mineralwater - Polyustrovskie located on the right bank of theNeva. Sources were discovered at the beginning of
the XVIII century by a court physician of Peter I, L.
Blumentrost. One of the first resorts in Russia
functioned here from 1721 to 1865. based on thesesources [20]. Doctors prescribe the use of this water
for some forms of anemia, stomach diseases, as well
as a table drink. Conditions for mud therapy are alsofavorable. Significant reserves of sapropel mud were
found on the lakes. Peat mud resources are practicallyinexhaustible in this territory. The use of medicinal
properties of the famous Cambrian clay in St.
Petersburg is just beginning.
The predominant type of vegetation is coniferous
forests, characteristic of the subzone of the middle
and southern taiga. The predominant tree species in
the forests are spruce, pine and small-leaved trees:
birch, aspen, mountain ash, etc. Taiga forests have agreat healing effect on the human body due to theionization and phytoncidal properties of plants. Pine
forests have a high ionization ability, which has acleansing effect on the human body. They are widelyrepresented on the Karelian Isthmus, along thesouthern coast of the Gulf of Finland. Pine forests are
considered the most favorable for recreation in thesuburbs of St. Petersburg. Psychologically, a person

feels more comfortable in the pine forests ofheathlands, bilberries, lingonberries [21]. These
forests are light, easily passable, they are not fornothing called park forests. Feeling in a spruce, dark,
damp, sometimes difficult forest is less comfortable
psychologically. Seasonal recreational loads on theforests of St. Petersburg's suburban area aresignificant, but their intensity varies in different areas.
Trampling oppressive effect on taiga species(especially shrubs). Trampling leads to damage anddisease of roots and shoots, primarily woody. The
oppression and partial destruction of shrubs and treesof lower tier leads to lightening of the forest, which,in turn, leads to the displacement of forest species ofplants by meadow turf soils.
Swamp complexes occupy both huge areas andsmall areas in forest in the taiga zone. Swamps on the
territory of the Greater St. Petersburg are rich inberries, can be used for limited extent for picking
berries (cranberries, cloudberries, lingonberries,
blueberries, etc.), mushrooms or for hunting.
Uncontrolled, intensive visits by tourists to swamps
causes changes in vegetation cover, as a result of
which their biological productivity decreases. Plantsthat can harm human health grow on this territory.
These are, for example, poisonous plants: black
henbane, poisonous milestone, crow's eye, wolf's
bark, hogweed, etc. Each summer-autumn season
registers cases of mushroom poisoning. It isnecessary to inform people who decide to relax innature.
The fauna of the city is rich and diverse. Several
hunting species, numerous in the suburbs of St.
Petersburg, virtually absent in European countries.
About 80 species of fish are found in the waters ofrivers and lakes. These are such species of fish,
including valuable species, like salmon, brown trout,whitefish, sturgeon, grayling. Nature preserves aredesigned to preserve fauna. Restrictions on visits tocertain areas are introduced during the bird nesting
period. Some unfavorable features of individual
representatives of the local fauna are also observed
here. This is the abundance of bloodsucking insects(midges) in the summer. Some members of the fauna
can be dangerous to humans, because they are carriersof various infections. All this is important to consider
when organizing various types of recreational
activities. Among the actual poisonous animals thatare dangerous to human life, we can single out only
the common viper. Danger can also come from large
animals. Cases of attacks on humans are extremely
rare, but collisions with them on the roads, especiallywith elks, often cause tragedies. Consequently,
expressways should be equipped properly (forexample, install a special barrier along the tracks).
DISCUSSION
Recreational programs can be combined with
805

SEE - Bangkok, Thailand, Nov.11-13, 2019other activities (sports, recreational, informational,
educational, classes of interest) in St. Petersburg [22].
The natural resources of Greater St. Petersburg makeit possible to develop health tourism - a sanatoriumand resort vacation in order to strengthen or restore
health. The nature of the territory of Greater St.
Petersburg is largely anthropogenically transformed.
However, many landscapes are unique, classified as
specially protected. One of the largest megacities in
Europe is the five-millionth of St. Petersburg,
surrounded by a network of satellite cities withpowerful industrial and agricultural potential. Natural
systems within a radius of 100–150 km of a city andits suburbs occupy no more than 20% of the entire
territory. On the territory of St. Petersburg, specially
protected natural areas are allocated. These include
areas of land, water surface and air space above them,where natural complexes and objects of special
environmental, scientific, cultural, aesthetic,
recreational and recreational importance are located.
These territories were withdrawn by decisions ofpublic authorities in whole or in part from economic
use, for them a special protection regime has been
established. Natural reserves and monuments ofnature (geological, geomorphological, hydrological,
botanical) are located on the territory of Greater St.
Petersburg. The possibility of visits by recreants
determines the prospects for the further developmentof ecological tourism.
On the territory of St. Petersburg allocatedspecially protected natural areas, where areas withhigh-rise buildings and industrial zones dominate.
The organization of a network of specially protectednatural areas is the most important condition for theformation of a harmonious urban environment. Such
territories improve the aesthetics of urban landscapes,
along with the artificially created vegetation ofgardens and parks, greenery on the streets [23].
15 protected areas are allocated within the city
limits of Greater St. Petersburg. The total area of the
fifteen currently existing protected areas in St.
Petersburg is 6,140 hectares (more than 4% of theentire city territory). Most of them are close to thecoast of the Gulf of Finland. A comparison of theurban landscape map and SPNA located within theirboundaries allows to make a conclusion about
unequal representation of each landscape. This should
be considered when designing new protected areas
within the city limits. The first place in terms of thenumber and area of specially protected natural areas
will be taken by the Kurortny district. It is planned
that protected areas will occupy 1/10 of its area by
2025.
Eight
naturereserves:
Yuntolovsky,
Gladyshevsky, the Northern coast of the Neva Bay,
Lake Shchuchye, the Sestroretsk swamp, West Kotlin
island, the Southern coast of the Neva Bay, theNovoorlovsky are of importance for recreation
purposes. They are created to preserve or restore

several components of nature and to maintain theoverall ecological balance. Some types of economic
activities are limited on their territory. It is difficult tooverestimate the importance of SPNA within a largecity [24], such as St. Petersburg. A program forfurther expansion of the network of territories withthis status exists.
Some park areas need to be given the status ofprotected areas (for example, by analogy with thenature monument Elagin Island, or the park
"Sergievka"). For example, Shuvalovsky Park is
located on the Northern outskirts of St. Petersburg.
This is a popular holiday destination of citizens.
The authorities failed to implement somedecisions on granting the status of protected areas.
Here are some examples. In 1996, the decision wasmade in order to preserve the unique natural complexof the Suzdal Lakes. Establish the status of protectedareas for the natural complex of Suzdal Lakes in the
Vyborg and Primorsky districts of the city. Suzdal
Lakes are a unique natural formation, representing asystem of three lakes. Bizarre coastal outlines, flat
terrain from the west, hilly from the east, combinedwith the water surface, predetermine landscapediversity and determine aesthetic appeal. The
functional use of the lakes has a wide range, including
recreational. The decision is not made.
In 1997, the city government determined the needto establish an integrated (landscape) St. Petersburg
state natural reserve of regional significance in the
territories of the city of Pavlovsk and the city ofPetrodvorets. The decision was not made.
CONCLUSIONSThe General plan of St. Petersburg provides forthe organization of a system of SPNA in order toimprove the environmental protection. New SPNA
will be created before 2025. Some of them, forexample, "Levashovo forest", "Coastal ledge
Serovo", "Puhtolova mountain" can be examples of
new types of SPNA, that solve both environmental
and recreational tasks.
Natural parks of different profiles can be createdon the territory of the city. From the point of view ofmodern scientific approaches, the most promising
forms of natural parks should be parks which provide:- Zones of scientific and educational importance(for scientific ecological and landscape researcheswith arrangement of ecological trails and routes),- Recreational zone (with construction of
walkways, stops, tent camps and parking for tourists,mini-camp sites, tourist sites);- Sports tourist parks (with specially organized
territories, including facilities and areas for training
and amateur qualifying tourism, as well as
educational and sports tourist events-tourist rallies,
competitions, seminars, etc.).),

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SEE - Bangkok, Thailand, Nov.11-13, 2019

- Fishing and hunting parks (with speciallydesignated territories for carrying out hunting andamateur fisheries regulated by licenses, as well as
ecological, zoological, ichthyological research andactivities);- Water parks (focused on water areas andterritories suitable for the development of water
tourism-yachting, swimming, boating, relaxing on thebeach, etc.).),- Agricultural parks, and in the version of St.
Petersburg-natural - historical dacha zones (withdedicated special areas designed for agriculturalactivities, exhibiting its tourists, as well as thecreation of country museums, ethnic museums,
museums demonstrating the achievements of modern
science and technology in the arrangement of dacha
farms, not harmful to the natural environment).
In any case, SPNA should have visit centers
equipped in accordance with international experienceand modern requirements for the organization of ecoexcursion and tourism activities. Eco-tourism can andshould become for the economy of St. Petersburg not
only an urban, but also a Federal specialization, witha correctly built policy based on the integrated use of
tourism and reclamation resources, considering all
conditions that can contribute to the development ofrecreation.

recreational areas in large cities. MATEC Web ofConferences,
Vol.
265,
2019.
DOI:10.1051/matecconf/201926506012[8] Paranina A., Archaeological objects as elements
of informational life support system and sourcesof information about the evolution of theenvironment.
International
Journalof
GEOMATE, Vol. 13, Issue 35, 2017, pp.100-107
DOI: 10.21660/2017.35.6722[9] Stefănica M., Butnaru G. I., Research on tourists’perception of the relationship between tourism
and environment. Procedia Economics andFinance. 2015, pp. 595-600.
[10] Matveevskaya A. S., Pogodina V. L, Tarakanova
T. S., Evseev V. V. and Nesterova I. E.,
Technologies of Tourism in the Modern Urban
Environment. International Journal of Civil
Engineering and Technology (IJCIET) Vol.9,
Issue 10, 2018. pp. 1566-1574.
[11] Paranina A. N., Paranin R. V., Information in
geographical space as the basis of crossdisciplinary researches in culture geography.
European Journal of Geography 8 (3) 2017,
pp.67-77[12] Baranov A. S., Drapeko E. G., Bogdanov E. I.,
World Heritage of St. Petersburg in the context ofcultural tourism, 2011, pp.42-48.
[13] Pozdeeva E. G., Trostinskaya I. R., Evseeva L.
I., Ivanova R. A., Problems of personality typetransformation in current conditions of Russian
society. International conference on researchparadigms transformation in social sciences(RPTSS 2017) European Proceedings of Social
and Behavioral Sciences, 35, pp. 1092-1099 DOI:
10.15405/epsbs.2018.02.128.
[14] Shipunova O. D., Kolomeitsev I. V.,
Sociotechnical system and socio-culturalenvironment in modern society. Scientific andtechnical statements, №1 (105), 2010, pp. 15-21.
[15] The Geography of Tourism of Central andEastern European Countries. K. Widawski,
J. Wyrzykowski (Ed.) 2017, P. 551 DOI:
10.1007/978-3-319-42205-3[16] Pogodina V., Filippova I. Geography of Tourism,
2015, P. 256.
[17] Matveevskaya A., Pogodina V. New objects of
tourist interest and their reflection in the registerof tourist resources of St. Petersburg. Tourism and
Education, 2017, pp. 44-50.
[18] Belkina I., Pogodina V. Eco-recreational featuresof Leningrad region’ landscape. Geology andevolutionary geography, 2003, pp. 156-166.
[19] Grigoriev A., Zelyutkina L., Isachenko T.,
Korostelev E., Paranina A and Sevastiyanov D.
The Heritage of the North-West of Russia andrecreational environment management, 2013,
P.152.
[20] Gaidai A., Pogodina V. Features of the design ofecological trails in protected areas of St.

REFERENCES[1] Schirru, M.R. Montalto di Castro, Sustainable
tourism as an opportunity for urban andenvironmental regeneration. (Conference Paper)
DOI: 10.1007/978-3-319-92102-0_70[2] Nikolaeva J. V., Bogoliubova N. M., Shirin S.
S. Ecological tourism in the state image policy
structure. Experience and problems of modern
Russia. Current Issues in Tourism. Vol. 21,
Issue
5,
2018,
pp.
547-566
DOI: 10.1080/13683500.2015.1100588[3] The Federal target program "Development
internal and entrance tourism in RussianFederation (2019-2025)", available at: URL:
https://www.russiatourism.ru (Accessed 5 May
2019)[4] Slater S. J., Tarlov E., Jones K., Matthewa S. A.,
Wing C. and Zenk S. N., Would increasing accessto recreational places promote healthier weights
and a healthier nation? Health and Place, Vol. 56,
2019,
pp.
127-134.
DOI:
10.1016/j.healthplace.2019.01.013[5] Official website of World Tourism Organization(UNWTO),availableat:URL:
http://unwto.org/ru (Accessed 10 June 2019)[6] Official website of Russian Federal Agency for
Tourism,
availableat:URL:
https://www.russiatourism.ru/ (Accessed 7 June
2019)[7] Matveevskaya A., Pogodina V., Ermolina M.,
Geoecological approach to the design of807

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Petersburg. Natural and cultural heritage, 2016,
pp. 440-445.
[21] Nutsford, D., Pearson, A.L., Kingham, S. An
ecological study investigating the association
between access to urban green space and mental
health. Public Health, 127 (11), 2013, pp. 10051011. DOI: 10.1016/j.puhe.2013.08.016[22] Problems of development of domestic andinbound tourism in Russian Federation, 2018, P.
223.
[23] Thongdejsri, M., Nitivattananon, V. Assessing
impacts of implementing low-carbon tourism

program for sustainable tourism in a world
heritage city. Tourism Review, Vol. 74, Issue 2,
2019, pp. 138-156. DOI: 10.1108/TR-04-20170082[24] Kovnova, T., Koleva, V., Dragoeva, A. P. andNatchev N. Peri-urban national parks as green
spaces for recreation: A case study of nature park
Shumen plateau. International Journal of Social
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46-58
DOI: 10.4018/IJSESD.2019010104

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ANALYSING THE INFLUENCE OF COGNITIVE, AFFECTIVE,
CONATIVE AND MOTIVATION ASPECTS ON TRAIN PASSENGER’SDEVIANT BEHAVIOUR: COMMUTER LINE, INDONESIA

1

Ahmad Zubair1, Chotib1
Urban Studies, School of Strategic and Global Studies, Universitas Indonesia, Indonesia

ABSTRACT
Commuter Line in Jakarta and surrounding cities became the best public transportation for urban choice.
However, there are still many problems related to behavior deviations carried out by passengers. These forms ofdeviant behavior such as pickpocketing, sexual abuse, smoking in the station, aggressive passengers, eating anddrinking in the carriage, priority seat abuse and many other passenger behaviors. The purpose of this paper is toanalyze whether there is a significant influence between the conative, affective, conative and motivation aspectsof passengers simultaneously and partially to deviant behavior. A mixed method research is conducted tounderstand behavior aspects. The Sequential Exploratory research model is used with the main focus is to explore
a phenomenon of train passenger deviant behavior. This research model is divided into two stages. The first stage
is the collection of qualitative data using observation and in-depth interview methods. The second stage iscollecting quantitative data with the survey and distributing questionnaires methods. Multiple linear regression
and triangulation analysis are used in this study with several test such as hypothesis test and coefficient ofdetermination test. The results showed some implication about passenger deviant behavior based on four aspects:
cognitive, affective, conative and motivation. The conclusions explained cognitive, motivation and conative
aspects showing a very strong influence on deviant behavior.
Keywords: Passenger behaviour, Deviant behaviour, Train passenger, Multiple linear regression, Commuter line

behavior is viewed from policy implementation offacilities and infrastructure within the station [7].
Research on passenger behavior modeling using
regression analysis has also been carried out [8] but
the factors used have not been specific regarding
deviant behavior itself.
From the various studies above, this paper tries tocombine and complement the research of passenger
behavior in terms of the passengers deviant behavior
aspects. How does the influence of cognitive,
affective, conative and motivation aspects onpassengers deviant behavior? Do each variable
partially influence the deviation? How about its
influence simultaneously? If there is any relations,what is the power of the relation? And which
variables most influence passengers deviant
behavior?

INTRODUCTION
Wesley Woodson [1] argued that thetransportation space should pay more attention to thecharacteristics of passengers, it was attitude andbehavior. Understanding passenger attitudes andbehavior is important to anticipate operational andservice problems.
Sears [2] suggested that there were threecomponents to seeing the form of attitudes, including
the cognitive, affective and conative. Based on thesmall findings in the pre-research stage, it showedthat the relationship between cognitive, affective andpassenger behaviors can be in one direction, but notalways compatible [2]. Most of the passengers form
an anomie so the use of facilities and regulations inthe station sometimes becomes biased. Passengers nolonger know which one can be said to be 'correct' andwhich one is 'wrong' in using the facility. This
research was conducted to enrich the patterns ofCommuter Line passengers deviant behavior both instations and train cars based on three components
coupled with motivation aspect [3].
The study of train passengers behavior has been
carried out starting from how the passengers behavior
during boarding [4] and forms of commuter line
passenger deviant behavior up the train roof [5] how
passengers did affordances and adaptation in
Commuter Line trains [6] and how passenger

METHODOLOGYThis study used a quantitative approach. Data
collection is done by survey method withquestionnaire instruments. The distribution ofquestionnaires was conducted to complete theanalysis of quantitative data. Data is also collected tostrengthen data interpretation/tabulation. Respondent
data in this study can be analyzed descriptively to findout the characteristics of respondents and deviant
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(passengers) to be chosen randomly. Sampling data
can also be taken incidentally [9] which is thedetermination of respondents by chance (whoever
meets the surveyor can be used as a sample).
Percentage of allowance used is 10% and the results
can be rounded up so that the number of samples is
110 respondents.

behavior factors based on three components(cognitive, affective & conative) and an additional
component, motivation aspect.
The questionnaire was distributed to passengers
using the Tangerang-Duri route with the intention thatpassengers who were given a questionnaire werewilling to respond according to the questions asked.
The scale used in this study is the Likert scale tomeasure attitudes, opinions and passenger
perceptions of deviant behavior that occurs.

Variables
In this study there are four independent variables(Cognitive, Affective, Conative and Motivation) and1 dependent variable (Passenger Deviant Behavior).
The variables are operationalized as follows:

Table 1 Likert Scale Answer Sheet
Answer
SD
D
Do
A
SA
Score
1
2
3
4
5
Note: Strongly Disagree (SD), Disagree (D),Doubtful (Do), Agree (A), Strongly Agree (SA)Table 3 Variables’ Operationalization
Variable
Cognitive

Population and Sample
The population in this study were passengers on
weekdays and weekends observed at peak and offpeak hours. The sample in question is a portion of theCommuter Line population of the Tangerang-Duriroute whose characteristics are to be investigated andcan represent the entire population. Sugiyono [9]explained that one technique in drawing samples must
be representative by using the Slovin formula below.

𝑛=𝑁
1+𝑁 𝑒 2Affective(1)

Conativen= sample/total respondentN= populatione= the percentage of sampling accuracy errorsthat can still be tolerated
Table 2 Research Population

Motivation

Time

Average Passenger
in Station
Tangerang
Duri
Weekdays
Peak
2670
3751
Off Peak
1530
2458
Weekend
Peak
1774
1846
Off Peak
1121
1507
Average Passenger
17731
23902
Population (1+2)
4163

Passenger
Deviant
Behavior

Indicator
a. Knowledge about deviant
behaviorb. Understanding of regulations
c. Understanding of station andtrain facilities
d. Understanding of space andtime resources
a. Response of deviant behavior
b. Reaction to deviant behavior
c. Passenger amenities
d. Passenger safety
a. Passenger action to deviant
behaviorb. Passenger readiness to deviant
behaviorc. Passenger anticipation todeviant behavior
a. Passenger basic needs
fulfillment
b. Passenger opportunity incommitting deviant behavior
a. Understanding of
regulation/norms
b. Regulation socializationc. Passenger toleranced. Station and train facilities
e. Space and time limitation

Analysis
The population in this study was 4163 passengers.
The population is the sum of the average passengers
at Tangerang and Duri Station on weekdays andweekends. Data was collected through initialobservation by manual counting.
Samples taken based on random samplingtechniques where researchers provide equal
opportunities for each member of the population

The questionnaire data was processed through thetabulation and Statistical Package for the Social
Sciences (SPSS) program. The results of processing
data will be analyzed using multiple linear regression
and hypothesis test. Multiple linear regression is usedbecause of several aspects that will be tested. This
analysis is the most suitable for the research model.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Multiple Linear Regression Analysis

Respondent
profile data describes thecharacteristics of 110 respondents. The profile of the
respondents can be elaborated through the identity of
the respondents based on the characteristics of age,gender, occupation and time of Commuter Line
usage.

Regression analysis is a method of correlation
between cause and effect relations and to makepredictions for the topic by using the relation [10].
The multiple linear regression analysis in this study
aims to determine the magnitude of the influence offour independent variables namely Cognitive (X 1),
Affective (X2). Conative (X3) and Motivation (X4) tothe dependent variable namely Deviant Behavior (Y).
The multiple linear regression equation models usedin this study are as follows:
Y = α + b1X1 + b2X2 + b3X3 + b4X4+ εY
αb1,2,3,4
X1
X2
X3
X4
ε

(2)

: Dependent Variable: Constanta Coefficient: Regression Coefficient X1, X2, X3, X4: Cognitive: Affective: Conative: Motivation: ErrorFig. 1

Total Respondent by Age

Based on the survey results, respondents in thisstudy had the youngest age range of 18 years to theoldest 65 years. Most of the respondents werepassengers aged 21-30 years as many as 59 people(53.6%) and passengers aged 31-40 years as many as
24 people (21.8%) and passengers aged 41-50 years
as many as 12 people (10.9%). This distribution
shows that respondents are dominated by productive
age passengers. Productive age passengers usuallywork in the Jakarta area and come from the suburban
area (Tangerang, Depok, Bogor and Bekasi). Basedon research from the Ministry of Transportation, mostworkers in productive age in Jakarta prefer to use
public transportation modes rather than private
vehicles, most of them using Commuter Line.

Hypothesis Test
Hypothesis test is divided into two methods,
which are t test (partial) and F test (simultaneous).
The t test, known as the partial test, is conducted todetermine the effect of the independent variable (X)on the dependent variable (Y) separately / one by one/ each [11]. According to Ghozali [12], the t test is
said to be significant if the value of t count > t tableor significance value (p value) < probability.
This F test is also often referred to as asimultaneous test, to test whether the independent
variables used in the model are able to explainchanges in the value of variables [12]. F test is said tobe significant if the value of F count > f table orsignificance value (p value) < probability. The
description of the calculation can be seen in the
ANOVA table.
RESULTS AND DISCUSSIONS
The distribution of the questionnaire was carriedout for approximately two months (December 2018
until January 2019). The questionnaire wasdistributed to complement the primary data needs that
had been identified through observation and semiinterviews with both passengers and PT. KCI. The
results of distributing questionnaires can be in theform of characteristics of respondents' profiles andtabular data filling in questions to be tested withmultiple linear regression analysis.

Fig. 2

Total Respondent by Gender

Based on gender, the respondents in this study
were dominated by women as many as 65 people(59.1%). Meanwhile, there were 45 male respondents(40.9%). That is, Commuter Line in Indonesia is moreused by women. The results of the observation also
showed that on the Tangerang-Duri route, woman
passengers were dominated especially mothers
carrying children during off-peak hours.

Respondent Profile

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SEE - Bangkok, Thailand, Nov.11-13, 2019

these passengers are usually dominated by passengers
carrying families. While as many as 36 respondents(32.7%) used Commuter Line on both weekdays andweekend.
Multiple Linear Regression Model
Based on table, the values in the table output areincluded in the following terms of multiple linear
regression.
Fig. 3Y = (α) 28,671 + (X1) 0,929 - (X2) 0,019 - (X3) 0,746+ (X4) 0,589(3)

Total Respondent by Profession

The types of profession identified are
Army/Police, Civil Servants (PNS), private
employees, entrepreneurs, laborers, freelancers,
students/college students, housewives and others.
The majority of respondents worked as private
employees as many as 49 people (44.5%). The next
most respondents were housewives as many as 18
people (16.4%) and students /college students(12.7%). Of the 110 respondents, 75 passengers weredaily workers (68.2%) and 35 passengers did notwork (31.8%).

Fig. 4Equation (3) shows a constant value of (28,671),
it can be interpreted that if the value of otherindependent variables is 0, then the value of thedependent variable (deviant behavior without being
influenced by the independent variable is equal to(28,671).
Cognitive variable coefficient (X1) is 0.929;
meaning that every increase 1 unit in Cognitive
variable, it will increase deviant behavior by 0.929
units, assuming other independent variables are fixedvalues. Beta Standardized Coefficients Cognitive
variable (X1) of 0.540 means that Cognitive variables
have a positive influence of 54% on deviant behavior
variables (Y).
The Affective variable coefficient (X2) is -0,019;
meaning that every increase 1 unit in Affective
variable, it will reduce deviant behavior by 0.019
units, assuming other independent variables are fixedvalues. Beta Standardized Coefficients Affective
variable (X2) of -0.016 means that Affective variables
have a negative effect of 1.6% on variable deviation
behavior (Y).
The Conative variable coefficient (X3) is -0,746;
meaning that every increase 1 unit in Conative
variable, it will reduce deviant behavior by 0.746
units, assuming the other independent variables are
fixed values. Beta Standardized Coefficients
Conative variable (X3) is -0.320, which means that
the Conative variable has a negative influence of 32%
on the deviant behavior variable (Y). Motivation
variable coefficient (X4) is -0,589; meaning that every

Total Respondent by Time of Using Train

Time of using train is divided into weekdays(working days), weekends and both (weekdays andweekend). 43 respondents (39.1%) used theCommuter Line only on weekdays. 31 respondents(28.2%) using Commuter Line only on weekend,
Table 4 Multiple Linear Regression Output
Model

1 (Constant)Cognitive
Affective
Conative
Motivation

Unstandardized CoefficientsB
28.671
.929
-.019
-.746
.589

Std. Error
6.445
.141
.095
.191
.240

Standardized
Coefficients
Beta
0.540
-.016
-.320
.229

812

t

Sig.

4.448
6.610
-.206
-3.914
2.451

.000
.000
.837
.000
.016

SEE - Bangkok, Thailand, Nov.11-13, 2019

The limit of R2 is 0 ≤ R2 ≥ 1 so that if R2 equals zero(0) means that the dependent variable cannot be
explained by the independent variable simultaneously,
whereas if R2 is equal to 1 means that the independent
variable can explain the dependent variable
simultaneously.
Table 5 shows that the correlation between thedependent variables Deviation Behavior and the four
independent variables in general is 0.668. This showsthat the Cognitive, Affective, Conative andMotivation variables towards Deviant Behavior are in
the strong category.
The Adjusted R Square value is 0.426 (42.6%).
This shows that the variation of the independent
variables used in the model (cognitive, affective,
conative and motivation) is able to explain 42.6% of
the variation in the behavioral deviation variables,
while the remaining 57.4% is explained by othervariables not included in this research model.

increase 1 unit in Motivation variable, it will increasedeviant behavior by 0.589 units, assuming otherindependent variables are fixed values. Beta
Standardized Coefficients Motivation variable (X3) of
0.229 means that the Motivation variable has apositive effect of 22.9% on deviant behavior variable(Y).
The multiple linear regression model above showsthat Cognitive variable (X1) and Motivation variable(X4) are positively related to deviant behavior.
Meanwhile, Affective variable (X2) and Conative
variables (X3) are negatively related to deviant
behavior. Based on Beta Standardized Coefficients,
the most influences variable to deviant behavior is the
Cognitive variable (X1). This can be seen in the formof passenger behavior due to a lack of understandingof the rules and norms in the station and train.
After analyzing the independent variables that
influence deviant behavior as explained by Sears [2],all variables simultaneously influence behavior
deviations. Cognitive variables have the greatest
influence indicating that aspects of knowledge andunderstanding of passengers in implementing rules
and norms are important to be discussed further.
Imron and Harianto’s research [13] also showed thathuman cognitive factors greatly determine the formof deviations made. Sujatmiko and Harianto’s
research [5] also showed that there are several
motives that cause passengers deviant behavior intrain cars. Four of the five motives found by
Sujatmiko & Harianto [5] explained that they
(passengers) were more influenced by cognitive
aspects and passenger motivation than affective
aspects. Partially, affective variables show no
significant effect on deviant behavior. For this reason,
affective variable should be substituted with variable
that predominantly influence such as motivation
variable. The addition of motivational variable from
Maslow [3] can finally explain that deviant behavior
was positively carried out to meet the needs of thepassengers themselves. Deviant behavior also tends
to occur because of the special or urgent motivationof these passengers.

Hypothesis Test
The partial test results (t test) can be seen in Table
4. Conclusions can be drawn based on the following
requirements: If the t count is greater than t table or pvalue is smaller than 0.1, then hypothesis 0 is rejected
and the initial hypothesis is accepted which means theindependent variable affect the dependent variable.
Based on the table 4, the t count of cognitive
variables is 6.610, motivation variable is 2,451,
conative variable is -3,914 and the significance value
is 0,000. The t table value can be seen from thestatistical table with a significance of 0.1 and degrees
of freedom (df) n-k-1 or 110 - 4 - 1 = 105. With the2-sided test the results are obtained for t table of 1,289/ -1,289. That is, t count> t table (6.610, 2,451, 3,914> 1,289 / -1,289) significance value <from α(0,000 <0,1). Therefore, it can be concluded that
Cognitive and Motivational variables partiallyinfluence the deviation of Commuter Line passenger
behavior. Positive t count value, meaning that theincreasing assessment of the cognitive aspects andmotivation of a passenger will increase deviant
behavior. The results of calculations on the conative
variables show a negative t count, which means thatthe increased assessment of the conative aspects of apassenger will reduce behavioral deviations.
On the other hand, Affective variable shows thevalue of t count is -0.206 and the significance value is0.837. The t table value can be seen from the same
statistical table. That is, t count <t table (-0.206 <1,289) significance value > of α (0.837> 0.1). Then it
can be concluded that the Affective variable partiallydoes not affect Commuter Line passenger deviant
behavior.
In addition to the t test, the F test is used todetermine whether the independent variables
simultaneously influence the dependent variable or

Coefficient of Determination Test
The coefficient of determination shows how muchthe percentage of the regression model is able toexplain the dependent variable.
Table 5 Coefficient of Determination Test
Model

R

R
SquareAdjusted
Std.
R
Error of
Square Estimate
a
1
.668
.447
.426
4.08145
Note: a. Predictors: (Constant), Motivation, Affective,
Cognitive, Conative
813

SEE - Bangkok, Thailand, Nov.11-13, 2019not. The hypothesis 0 is accepted if F count ≤ F table
Hypothesis is rejected if F count> F table. The F test
results obtained after the processed data are presented
in the following ANOVA table.

cultural and economic aspects of passengers which
can influence deviant behavior.
ACKNOWLEDGMENTS

Table 6. ANOVA
Model

SST

df

Mean
Squar
e

F

Sig

Regression
Residual
Total

1411
1749
3160

4
105
109

352.9
16.6

21.189.000bThis article is part of Grant of International
Publications for Students Final Project of Universitas
Indonesia: Urban Public Transportation and Planning.
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Information and Guidlines for the Design ofSystems, Facilities, Equipment and Products for
Human Use. New York, McGraw-Hill, 1981.
[2] Sears D., Freedman J., Peplau L., Social
Psychology 5th Ed. Jakarta, Erlangga, 1992.
[3] Maslow AH., Motivation and Personality:
Motivation Theory with a Hierarchy of Human
Needs Approach., Jakarta, PT PBP, 1994.
[4] Oliveira L. CR., Fox C., Birrell S., Cain R.,
Analysing Passenger’s Behaviours when
Boarding Trains to Improve Rail Infrastructure
and Technology. Robotics and ComputerIntegrated Manufacturing, Vol. 57, 2019, pp.282291.
[5] Sujatimko., Harianto S., Phenomenology Studyof Passenger Behavior on Train Car. Paradigma
Journal, Vol. 2, Issue 1, 2014, pp.1-5.
[6] Basyarah Z., Affordances and Passenger
Adaptation on KRL Commuter Line Train. Depok,
Universitas Indonesia, 2014.
[7] Kusumaningtyas B., Railway Implementation
Policies(StudyofDuri-TangerangCommuterline Facilities and Infrastructure).
Depok, Universitas Indonesia, 2014.
[8] de Ona J., de Ona R., Eboli L., Forciniti C.,
Mazzulla G., An Ordered Regression Model toPredict
Transit
Passengers’
Behavioural
Intentions. Case Studies on Transport Policy, Vol.
6, Issue 4, 2018, pp.449-455.
[9] Sugiyono., Quantitative, Qualitative and R&D
Research Method. Bandung, Afabeta, 2011.
[10] Uyanik G.K., Gűller N., A Study on Multiple
Linear Regression Analysis. Procedia – Social
and Behavioral Sciences, Vol. 106, 2013, pp.234240.
[11] Sudjana., Regression and Correlation Analysis
Techniques for Researchers. Bandung, Tarsito,
1996.
[12] Ghozali I., Application of Multivariate Analysis
with the SPSS Program, 4th Ed. Semarang,
Universitas Diponegoro, 2011[13] Imron A., Harianto S., Social Deviation andSocial Control. Jakarta, Ministry of Education
and Culture.

Note: a. Dependent Variable: Deviant Behavior, b.
Predictors: (Constant), Motivation, Affective,
Cognitive, Conative
Based on the ANOVA table above, the calculated
F value is 21,189. F table can be seen in the statistical
table using a significance level of 0.1 and df 1
(number of variables - 1) or 4-1 = 3 and df 2 (nk-1) or
110-4-1 = 105. Results obtained for F tableamounting to 2,136. That is, the value of F count> F
table (21,189> 2,136), then hypothesis 0 is rejected
and the initial hypothesis is accepted. Therefore, it
can be concluded that the cognitive, affective,
conative and motivation variables simultaneously
influence the Commuter Line passenger deviant
behavior.
Based on the F test table above, the significancevalue of the Cognitive variable (X1), Affective
variable (X2), Conative variable (X3) and Motivation
variable (X4) is 0,000 <value of α (0,1) so that all
independent variables together has an effect on
Commuter Line passenger deviant behavior at
stations and train cars.
CONCLUSIONS
Deviant behaviors in this study are interpreted
specifically as all forms of passenger behavior that
violate the rules and norms that apply both in thestation and train cars. Previous research about deviant
behavior discussed irregularities in train cars bylinking passenger motives to behavior. There has
been no discussion about the relationship between theeffects of deviant behavior aspects. Cognitive,
motivation and conative aspects show a very strong
influence on passenger deviant behavior. The
tendency of these deviant behaviors can ultimately
show the lack of cognitive abilities of Commuter Linepassengers accompanied by strong motivation to
fulfill their needs. Future research is expected to beable to include other aspects such as the social,814

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

IMMEDIATE EFFECTS OF THAI MASSAGE ON GAIT SPEEDS AND
BALANCE PARAMETERS IN ELDERLY
Nutthanun Tatchananusorn1, and Wichai Eungpinichpong2
Research and Training Center for Enhancing Quality of Life of Working Age People, Khon Kaen
University, Thailand
2
Department of Physical Therapy, Faculty of Associated Medical Sciences, Khon Kaen University, Thailand
1,2

ABSTRACTThe purpose of this study was to determine the immediate effects of Thai massage on gait parameters, balance
performance, and trunk flexibility in elderly aged 60-80 years. A randomized control trial was used. Sixteen elderly
participants (12 females and 4 males) participated. They were divided into a Thai massage group and a control
group. Participants in Thai massage group received 1-hour whole body Thai massage while those in the control
group were assigned to rest for one-hour. Changes in all parameters after receiving each of the sessions werecompared by independent T-test. Within-group comparisons were analyzed by dependent t-test. Significantly
differences were found for within-group comparison in right gait cycle duration of maximal gait speed (0.0023 s;
p-value = 0.0023), single leg stance of left leg with open eye (15.17 s.; p-value = 0.034), and close eye conditions(2.3 s.; p-value = 0.022), and right leg with open eye (12.41 s.; p-value = 0.0294) and close eye conditions (4.06s.; p-value = 0.0087), and trunk flexibility (2.14 cm.; p-value = 0.0003). However, there are little improvement ofgait speed, stride length, gait cycle duration, cadences, and time-up-and-go test. We concluded that one session ofThai massage could provide immediate improvement in some gait parameters, balance performances, and body
flexibility.
Keywords: Elderly, Thai massage, Gait, Balance, Flexibility
improve physical fitness of soccer players [9],improved recovery performance after fatigue ofbasketball player, [10] decreased spasticity, andimproved quality of life and psychological conditionin stroke patients [11]. According to previous study,
Thai massage may improve walking and balance
performances in elderly people but there is noprevious study investigate about this topic. Thus,
propose of this study was to investigate the immediate
effects of Thai massage on gait speed and balance
performances in elderly adults compare with restingor control session.

INTRODUCTION
Worldwide, elderly population is increasing faster.
Number of elderly people aged 60 years or over in2000 and 2012 were 607 and 900 million respectively
and it is projected to reach 2,092 million in 2050. The
world will be turned to ageing society [1]. The healthstatus of elderly people is degenerated by the physicalchanges in many systems with decrease inperformances and capabilities of physiologicalprocesses [2]. Moreover, these changes also influencemobility and activities of elderly people that are
affected to health problems and considered as fall risk
[3].
Exercise is found to help improve gait and balance
performance of elderly by improve muscle strength,delivery and extraction of oxygen to the muscle, andjoint range of motion [4]. Furthermore, othertreatment that also help improve balance and gaitwere therapeutic massage [5], [6], and foot massage[7].
Lately, Thai massage is a practicable, and cheap
traditional treatment for Thai people. There are many
benefits of Thai massage including increasing blood
flow, skin temperature, and tissue flexibility, anddecreasing pain and muscle spasm. In addition, Thai
massage may improve arousal or body awareness inelderly that resulted from response of brain activating.
Previous study also found that Thai massage
improved walking performances in normal adults [8],METHOD
Design and Setting
A randomized control trial was conducted at Nong
Wang Community Health Center, Khon Kaen
hospital. The study was approved by the ethicalcommittees of Khon Kaen University, and Khon
Kaen Hospital
Participants
Elderly participants were recruited from Khon
Kaen province using bulletin boards and oral requests
for participants during 2 months period between
November and December 2018. Participants who 6080 years old with ability to walk equal or more than815

SEE - Bangkok, Thailand, Nov.11-13, 201910 meters without walking aid and good co-operation
were included in this study. They were excluded ifthey had history of brain injury, acute or unstablechronic
illness,
uncontrolled
hypertension,communicable diseases, osteoporosis, deep veinthrombosis, acute arthritis at upper and lower limb,
vestibular, neurological and cardiovascular problem,
fracture and dislocation, deformities of lower
extremities, pain more than 5/10 on visual analog
scale, opened wound at back, upper and lower
extremity, and visual problems than could not be
solved by glasses.

Fig.2. Massage lines of back area.

Intervention
A whole body of Thai Massage session was used
as an intervention in this study. The 1-hour Thai
massage protocol consisted of deep pressure massage
and stretch on major muscles of the body. Firstly,
therapist applied gently and deep thumb pressure
massage along the meridian lines that covered neck,back, lower and upper extremities and footconsequently (Fig. 1 – 9). Thumb pressure wasmaintained at each point on the meridian lines for 510 seconds each point and repeated 3 times. The
intensity of thumb pressure was not exceeded
pressure pain threshold of participants and was
adjusted by the therapist. After massage session, thetherapist applied gentle stretch for those muscles
including calf, hamstring, and quadriceps as shown in
Fig. 10 – 12. Participants in control group was
assigned to rest on the bed in the same environment
as massage group.

Fig.3 Massage lines of lower extremity (medial side)

3. PROCEDURE
Randomization
Twenty participants who met the above
inclusion/exclusion criteria were recruited andrandomly allocated into one of two groups using
block-randomized allocation with block sizes of 2 and4. The groups were assigned using a pre-generated
random assignment scheme enclosed in envelopes,
which resulted in a total of 11 participants per group.

Fig.4 Massage lines of lower extremity (lateral side)

Fig.1 Massage lines of neck area
Fig.5 Massage lines of lower extremity (anterior
side)
816

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig.11 Hamstrings muscle stretchingFig.6 Massage lines of lower extremity (posteriorside)
Fig.12 Calf muscle stretching
Treatment
Participants in group A received 2 sessions of onehour Thai massage per week for 4 weeks. Whereas
participants in group B took one-hour rest in supine
lying position 2 times per week for 4 weeks.
In keeping with the recommendation of Khon
Kaen University’s ethical committee and Board in
Human Research Khon Kaen Hospital Institute
Review, all participants gave informed consent before
participation in the study.

Fig.7 Massage lines of upper extremity (anterior side)

ASSESSMENT
On the baseline session, immediate session after
the 1st session of treatment, short-term session (before
the last session) and follow-up session (after the lastsession for 1 week), all outcome measures wereassessed by one physical therapist. Details ofoutcome measures and assessments are described
below.

Fig.8 Massage lines of upper extremity (posterior
side)

Gait Parameters
Gait parameters were assessed by walking inpreferred gait speed and maximal gait speed on 10meter walkway. Participants were assigned to wear
the Opal sensors of APDM at the sternum, posterior
lower back, and both foot while walking. Outcomesconsisted of gait speed, stride length, cadences, gait
cycle duration of preferred gait speed and maximal
gait speed. This test was repeated 3 times andcalculated for the average values for each speed.

Fig.9 Massage lines of feet

Static Balance Performance
The Single-leg-stance test (SLS) was assessed
static balance over the stance leg. The SLS was
measured standing time on each foot in condition ofopen eyes and close eyes. The assessor started time
when participants lifted feet from the floor.

Fig.10 Quadriceps muscle stretching817

SEE - Bangkok, Thailand, Nov.11-13, 2019

Participant were able to balance their body by move
hand or body but they were not allowed to touchanything while controlling their body. Time wasstopped when they moved their stance feet or otherfeet touched the floor [12].

Assessed for eligibility (n=16)
4 were exclude because of theopened wound

Dynamic Balance Performance

Baselinemeasurement

The time-up-and-go test (TUG) was measured
dynamic balance by timing the 5 sequences of test
including standing up from armchair, walking 3meter distance, turning, walking 3-meter distanceback to chair, and sitting down. Using stop-watch totime the tasks of 5 sequences. Time was started whenassessor said “go” and stopped when participants sit
and lean to the back rest of chair [13].

Randomized(n=16)
Control
group
(n=8)

Thai massage
group
(n=8)

Post-test
measurement

Post-test
measurement

Body Flexibility
A sit-and-reach box was used to measure body
flexibility. Participants sat long-sitting to the sit-andreach box and reached both hands forward as much as
possible to the measuring bar. [14]. Participants wereallowed to practice in the 1st trial. and they wererecorded on the other 2 trials. The value consideredas the test result was the best value of 2 trials.

Data analysis (n = 16)

STATISTICAL ANALYSES

Fig.13 Diagram of study design and participants

Changes in all parameters between Thai massage
session and control session results were analyzed byindependent t-test. Changes between pretest andposttest for both sessions were performed bydependent t-test. All statistical analyses were
calculated by Stata 10 software (StataCorp LP, 4905
Lakeway Drive College Station, Texas 77845, USA).
A p-value of less than 0.05 was considered
statistically significant.

DISCUSSION
This study showed that one session of 1-hour wholebody Thai massage could improve walking
performance, balance performances and trunk
flexibility in elderly on stride lengths of maximal gait
speed, gait cycle duration of maximal gait speed,
single-leg-stance test, and sit-and-reach test results.
Thai massage is to use deep pressure on meridianlines that covers all muscles of the whole body andfollow by passive stretching. Possible mechanisms ofThai massage on improving flexibility, gait andbalance may base on the neuro-mechanical andmechanical effects.
Massage may arouse the
proprioceptive nerve endings, adjust sarcomere
length, stretch muscle, tendon, and ligament
structures that begin reflex muscle relaxation [15][16].
Mechanical pressure of massage may decrease tissueadhesion by lengthen reduced or adhered connective
tissue [17]. Thai massage may help improveflexibility as measured by sit-and-reach test [8].
Furthermore, flexibility may help improve stride
length and gait cycle duration [18].
Moreover, massage found to affect thesomatosensory systems. It may arouse muscle,
tendons, joints, and ligaments to provoke the
proprioceptors including cutaneous, Golgi tendon
organ, joint receptors, and muscle spindles bypressure distribution, muscle tension, changing joint

RESULTS
Twenty potential participants responded to flyers
or word-of-mouth; Four were excluded after
screening for eligibility. 16 adults who met theinclusion and exclusion criteria were randomly
assigned to the treatment group and the control group.
A flow chart of participant progression through thetrial is presented in Fig.13 The characteristic of thestudy population is shown in Table 1. There were 12
females and 4 males. The mean age of control groupand massage group were 70.63 and 66.91 years. The
mean weight of control group and massage groupwere 65.93 and 69.09 kilograms. The mean height ofcontrol group and massage group were 160.64
centimeters and 159.18 centimeters.
Gait cycle duration of maximal gait speed, singleleg-stance test of all conditions and sit and reach test
showed significant improvement after Thai massage
session. (Table 2)818

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1. Characteristics of the study population
ParticipantGroup AGroup B
Data
Gender
6/2
6/2(female/male)Age (year)
70.63 ± 6.38
66.91 ± 5.52
Weight (kg)65.93 ± 9.1
69.09 ± 10.94
Height (cm)160.64 ± 9.48
159.18 ± 8.32

angle, and changing muscle length respectively.
Massage methods also activated the resetting of
unproductive reflex actions [19]. These effects mayhelp improve balance performance.
In addition, our results were related with earlier
studies found that Thai massage could improve gaitparameters, balance performances, and trunk
flexibility. Thai massage might improve stride lengthand trunk flexibility in normal adult with hamstring
tightness [8]. Thai massage on the lower leg might
decreased pain and duration of TUGT in elderly withknee pain [20]. Thai foot massage also found to
improve TUGT and Single-leg-stance in diabetes
patients with peripheral neuropathy [21]. Moreover,many researchers studied the effects of other type of
massage which is similar to Thai massage. 15-minuteof therapeutic massage might improve gait speed,
stride length, and step length in adult with DOMS[22]. 1-hour whole body therapeutic massage might
improve balance performance in elderly [5]. 25
minutes of Chinese massage might improve walking
speed in elderly with knee osteoarthritis [23]. A small
improvement of some gait parameters after 1-hour
Thai massage were founded because of a few Thai
massage sessions. One session of 1-hour whole bodyThai massage could not give a great result. Further
study should investigate the multiple sessions withfollow-up session on these effects. This study was thepilot study with few participants. Further study also
should investigate with proper number of participants.

Table 2. Evaluation of outcome measures(Mean±SD). Variables showing a significant
interaction effects between groups have been signedwith * (p-value is less than 0.05).
Parameter
Pre-A Post-A Pre-B Post-B
Maximal gait speed
1.42 1.45
1.46
1.51
Gait speed (m/s) ±0.18 ±0.16 ±0.16 ±0.25
Left stride length1.25 1.26
1.27
1.3
(m) *
±0.11 ±0.11 ±0.17 ±0.17
Right stride
1.25 1.25
1.27
1.29
length (m) *±0.11 ±0.1 ±0.17 ±0.18
Left cadence
125.5 126.4 127.9 130.4(bpm)±11.87 ±10.7 ±9.27 ±10.87
Right cadence
125.4 126.2 127.7 130.3(bpm)±11.94 ±11.04 ±9.51 ±11.07
Left gait cycle
0.96 0.97
0.94
0.93
duration (s)±0.08 ±0.06 ±0.08 ±0.08
0.96 0.98
0.95
0.92
Right gait cycle
duration (s) *±0.08 ±0.06 ±0.08 ±0.09
Preferred gait speed
1.1
1.11 1.07 1.12
Gait speed (m/s) ±0.15 ±0.09 ±0.14 ±0.19
Left stride length 1.12
1.12
1.1
1.12
(m)
±0.09 ±3.39 ±0.12 ±0.11
Right stride
1.1
1.11 1.09 1.12
length (m)±0.09 ±0.07 ±0.12 ±0.11
Left cadence
111.3 109.7 112.6 114.6(bpm)±7.04 ±6.23 ±6.88 ±9.49
Right cadence
110.9 109.3 112.5 114.4(bpm)±6.93 ±6.34 ±6.92 ±9.35
Left gait cycle
1.1
1.1
1.08 1.07
duration (s)±0.08 ±0.07 ±0.09 ±0.09
Right gait cycle
1.1
1.1
1.08 1.07
duration (s)±0.09 ±0.07 ±0.09 ±0.09
Single-leg-stance test
Opened eye
23.72 25.87 24.9 40.06
Left side (s) * ±11.02 ±12.53 ±10.98 ±30.17
Opened eye
25.68 25.47 26.16 38.57
Right Side (s) * ±9.95 ±10.59 ±14.12 ±28.27
Closed eye
4.85
6.14 5.12 7.42
Left side (s) *±2.69±3.8 ±1.81 ±3.7
Closed eye
5.48
6.32 4.48 8.55
Right Side (s) * ±3.33 ±4.55 ±4.85 ±4.53
8.81
9.25 8.79 8.26
TUG test (s) *±1.44 ±1.25 ±1.94 ±1.92
Sit and Reach
1.54
1.45 1.64 3.77(cm) *±9.03 ±9.82 ±11.02 ±10.65

CONCLUSIONS
According to the results of this study, we
concluded that 1-hour Thai massage session may
provide some immediate improvement of gaitparameters, balance performance, and trunk
flexibility, especially for stride length of maximal gait
speed, gait cycle duration of maximal gait speed,
single-leg-stance test, time-up-and-go test, and sitand-reach test. In a further study, long-term treatment
with following up are suggested.
ACKNOWLEDGMENTS
The authors would like to thank Mr. Daniel Seng,
product manager of Biofit Technology and Services,
for providing equipment, and thank Khon Kaen
Hospital for arranging a study visit at Nong Wang
Community Health Center. The study was financially
supported by the Research and Training Center for
Enhancing Quality of Life of Working Age People,
Khon Kaen University, Thailand.

819

SEE - Bangkok, Thailand, Nov.11-13, 2019

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820

5thInt. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

A COMPARISON STUDY BETWEEN CHEMICAL COAGULATIONAND ELECTRO-COAGULATION PROCESSES FOR THE
TREATMENT OF WASTEWATER CONTAINING REACTIVE BLUEDYE
NIDAA ADIL JASIM, TAMARA KAWTHER HUSSEIN
Faculty of Engineering, Al-Mustansiriyah University, Baghdad, Iraq , nidaa.albayati@uomustansiriyah.edu.iq

ABSTRACTThis study examined the possibility to remove reactive blue dye from simulated wastewater by chemical
coagulation, in comparison with electro-coagulation. Ferric sulphate Fe2(SO4)3, ferrous sulphate (FeSO4), polyaluminum chloride (PACl) and alum (Al2SO4.5H2O) were used as coagulants. Optimum pH, coagulants dosages
and initial concentration were determined by jar tests, and the maximum dye removal was obtained. The
maximum removal efficiency were 96%, where the best coagulant was Fe 2(SO4)3 at optimum pH and dosage of
6, 200 mg/L. On the other hand, electrochemical cell is designed using aluminum plates as the anode andcathode with dimensions of (7*4*0.3) cm3. Many experimental runs were done at a different operating
conditions (pH, NaCl concentration, initial concentration and electrical supply voltage) to study the removal
performance of electro-coagulation for reactive blue dye removal. The results indicated that, the maximum
removal were 99 %, at optimum pH of 2 and NaCl concentration of 1000 mg/L, initial concentration of 100
mg/L and 15 volt. The study proved that, the percentage removal of reactive blue is better by electrochemicalsystem than in chemical coagulation.
Keywords: Chemical coagulation, Fe2(SO4)3, Electro-coagulation, NaCl, Reactive blue.

flow to the nature. The textile industry utilizes about
10,000 dyes and pigments [2]. In general one
method of treatment is not sufficient for a perfecttreatment. A combined treatment with physical ,chemical and biological treatment are used toremove the heavy pollutants from textile wastewater[3-5].
More recently, studies have focused on color
removal from real combined textile wastewater andreactive dye bath effluent [5, 6] as well as aqueous
textile dyes [7-10].
It can see that the combination of physical,
chemical and biological methods are the mosttraditional treat the textile wastewater. This attributeto the high molecular weight of dye and presence ofaromatic rings. Clearly, there is low and slow
degradation when using biological methods [6-8].
Precipitation and adsorption are consume time andmoney as they are physical methods, on the other
hand, most of chemical treatments generatesecondary pollutants, such as, adding of aluminum
sulfate and chlorine.
Some other advanced technologies such as
photo oxidation by UV/H2O2 or UV/TiO2 also
generate secondary pollutants [9]. Biologicaltreatment of textile wastewater has low efficiency
because of the toxicity of dye molecules to active
microorganisms.
Electro-coagulation (EC) process has beenmostly used to treat many pollutants in wastewaters

INTRODUCTION
The reuse and recycle are the main factors toface the challenges of depletion of reserves andenvironmental troubles in the new world age where.
Wastewater is not only one of the main pollutant
that damages the environment, but also leads to thedeficit of the earth water. A lot of industrial
processes are managed at the spend of plenty offresh water, which is haggard as a wastewater, andneed to be treated to eliminate or uproot thepollutants and to produce a pure treated water inorder to be reused as a sustain environment natural
resource [1].
Textile industry wastewater is strongly polluted
with many chemical pollutants, its percentage
emission to the nature is 70%. The wastewater fromtextile processing as follows: water bath frompreparation, dyeing, finishing, slashing , printing,coloring and other operations, In the textile
industries and during the dyeing process a lot of
fresh water are used which are the main consumersof synthetic dyes. The industrial wastewater contains
many kinds of pollutants: chemical oxygen demand,dyes, suspended solids, high temperature, salts andvariable pH. These pollutants damage theenvironment. Wastewater should be treated before itis drained to the rivers or seas. However , thesepollutants could be treated for minimum harmful forthe environment or for better behavior after they821

SEE - Bangkok, Thailand, Nov.11-13, 2019because it is a simple and effective method. This
process was based on the forming of coagulants via
electrolytic reactions at electrode column. The
formulization of destabilization agents brings about
neutralization of electric charge for removing
pollutant [10]. EC process also facilitatesflocculation by turbulence generated by oxygen andhydrogen transformation at the cathode and anodeelectrodes. With the gas evolution, particles aredestabilized and they start attracting each other andgenerate bigger particles. EC process depends onparticle size, pH, conductivity , and theconcentrations of the continuous phase. Theseexperimental factors affect the results in different
ways. EC has some advantages like simple
apparatus, easy automation of the process,versatility, environmental compatibility, quick
reactions and smaller systems [11, 12].
This study aims is to conduct anexperimental investigation on the removal of areactive blue from the wastewater using thechemical coagulation and electro-coagulation
methods. Several fundamental aspects regarding theeffects of type of coagulants, pH, coagulants dosage,
voltage, pH, electrolyte concentration and dye initialconcentration.

concentration, coagulant doses (for each coagulant).
Jar tests were done with six bakers size 1000 ml.
Reactive blue solution was prepared previously. pH
was adjusted to the desired value by the addition of
0.1M HCl or/and 0.1M NaOH solutions as required.
The samples were mixed for 2 min, 200 rpm (rapid
mixing), then slow mixing for 30 min, 50 rpm. The
coagulation process was taken place, with theconsistence of flocculants, precipitation andsettlements. The mixers were left for 30 min toallow the agglomerates to settle down. Samples weretaken from 1-2 mm below the solution surface.
Electro-coagulation cell
The experiments were conducted in a beaker 1L
in capacity .The anode and cathode were positioned
vertically and in parallel to each other with an interelectrode gap of 3.5 cm Both anode and cathodewere an aluminum plates 7cm high, 4cm width and0.3 cm thickness. These electrodes were dipped in
the electrolyte solution .Stabilized DC power supply
was used as the source of electrical current (Figure.
1) .The solution was constantly stirred at 200 rpm
using a magnetic stirrer in order to maintain uniform
concentration of the electrolyte solution ,a stirrer
Model LMS-1003 Korea was used .

MATERIALS AND METHODS
Preparation of reactive blue dye
Reactive blue dye (Commercial Name :Forosyn Blue (SE) was supplied from 14 Ramadan
factory of textile industries_ ministry of industry,
with molecular weight 1309.87 gm/gmol, molecular
formula C38H28C12N14O18S5Na was used in thisstudy as model pollutant for textile dyes . Dye stock
solution was prepared by dissolving 1 g of dye in 1
liter distilled water, the final concentration is 1000
mg/L. The experimental solutions were obtained bydiluting the dye stock solutions in accurate
proportions to obtain different initial concentrations.
ChemicalsFig. 1

Experimental set up

Ferrous sulfate [FeSO4],
ferric sulfate[Fe2(SO4)3],alum[Al2SO4.5H2O]
andpolyaluminium chloride or PACl [AlCl3.6H2O],wereused as a coagulant using stock solution (1000mg/L). Sodium chloride NaCl was used aselectrolyte. For pH adjustment, sodium hydroxide,
NaOH and hydrochloric acid were used. All thechemicals used were supplied from BDH company,
England.

Analytical methods

Jar Tests

Re moval (%) The mixture of reactive blue dye of thesamples was drawn, centrifuged using electricalcentrifuge device at 5000 rpm for 20 minutes and un
adsorbed supernatant liquid was analyzed for the
residual dye concentration using Elico make UVSpectrophotometer (CI 73) at a max wavelength of
592 nm. Reactive blue dye removal efficiencies
was calculated by:

Jar tests were conducted in the coagulation
process to find the optimum pH, initial

C r C t
 100 (1)Ct

where, Cr and Ct are the concentration in raw

822

SEE - Bangkok, Thailand, Nov.11-13, 2019

and treated solutions, respectively.

(10, 50, 100, 150, 200 and 300 mg/L). The optimum
coagulant dose was found to be 200 mg/L. Above
this value there is no increase in the percentage
removal of reactive blue. As the coagulant dosage
increases, the number of binding sites for the dyealso increases. After some point (200 mg/L),
coagulant capacity was steady due to a screen effectbetween coagulant molecules, this produced a blockof the coagulant active sites by an increase of
coagulant dosage in the system. The maximum
removal efficiency is 90, 85 , 40 and 94% for alume,
PACL, FeSO4 and Fe2(SO4)3
respectively. The
same results were reported by some otherresearchers [16]. Figure 3 reveals the maximum dyeremoving versus the optimum coagulant dosage.

RESULTS AND DISCUSSIONSFor chemical coagulation
pH effect's
pH plays an important role in the coagulation
process. The charge percentage for what precipitatefrom metal hydroxide and hydrolysis product arecontrolled by pH whatever is increasing or
decreasing. Thus, pH must be controlled to establish
optimum conditions for coagulation [13]. To
examine the effect of pH on reactive blue dyeremoval efficiency, dosage of 150 mg/L of eachcoagulants were taken, while varying pH of thesamples using 0.1M HCl and/or 0.1M NaOH from
(2-12). Reactive blue dye concentration was fixed at
50 mg/L during the experiments.
Figure 2 shows the maximum removal ofreactive blue, and they are as follows 86, 75, 35 and
91 % at pH 8, 10, 4 and 6 for alum, PACL, FeSO4
and Fe2(SO4)3 respectively. The reason for theseresults can be explained by, that every coagulant had
its point of zero charge. Below this pH, thecoagulant is protonated and the surface is positively
charged; however, attractive of negatively charged
ions (for examples, dyes) is favorable. Above thispH, the coagulant surface becomes negatively
charged, so in this region of pH, dye ions cannot be
attracted effectively. Gaceva et al., 2008 [14] studied
the removal of color from wastewater containing
water base color using polyaluminium chloride(PACl). The optimal results for reactive dyeenabling almost 80% dye removal, were obtained at
pH=7.1 and PACl concentration of 20 mg/L [15].
Fe2(SO4)3

90

FeSO4

80

PACL

70

Alum

%Dye removal

100

100
90

%Dye removal

80

100
150
coagulant dose (mg/L)

200

300

Reactive blue removal as a function of
coagulant dosages at optimum pH and dye
concentration 50 mg/L.

The experiments were performed to determine
the effect of initial reactive blue concentration on
percentage removal, using a fixed coagulant dosage(the optimum is 200 mg/L). The results areillustrated in Figure 4 for reactive blue, with theincrease of initial concentration from 20 -100 mg/l,
the removal efficiency, increased suddenly from 81
to 93%, 77 to 87 %, 26 to 41%, 88 to 96% for alum,
PACL, FeSO4 and Fe2(SO4)3 respectively. While,for concentrations more than 100 mg/L, theefficiency goes down and reached to 78, 70, 28 and
79% for the same sequence, for initial concentrationof 150 mg/L.
According to the data of Zonoozi group, atthe optimum coagulant (polyaluminum chloride andalum) dosage, the removal degree was associatedwith the initial concentration of the selected dyes,
and the smallest removal degree was obtained forsmallest concentrations of the dyes [17]. This result
is inconsistent with the results obtained for the usedcoagulants in this study, which showed the smallest
values of removal efficiency for smaller initialconcentration.

0

Fig. 250

Initial concentration effect's

10
10

30

Fig.3

20

8

40

10

30

pH

Alum

50

0

40

6

PACL

10

50

4

60

FeSO4

20

60

2

70

Fe2(SO4)312

Reactive blue removal as a function of pH
at dye concentration 50 mg/L.

Coagulant dosage effect's
To study the effect of coagulant dose, the pH
was fixed at optimum value from previous
experiment and the initial concentration of reactive
blue is 50 mg/L . The coagulant doses were varied as
823

SEE - Bangkok, Thailand, Nov.11-13, 2019130

concentration of 50 mg/L and voltage of 5V isillustrated in Figure 6. It is clear from this figure
that, the reactive blue removal was increased when
NaCl concentration increased from 200 to 500 mg/L,
and when NaCl concentration increased up to 1000
mg/L, dye removing increased and equal 95%,
because the conductivity of solutions rise when
NaCl concentration increased and resistancedecreases, so the passed current increases and the
produced amount of metallic hydroxide and dye
removal increases, also, hypochlorite ions produced
at the anode causes the increasing in dye removal byoxidation of dye molecules [20-22].

Fe2(SO4)3
FeSO4
PACL
Alum

110

%Dye removal

90
70
50
30
10
-10

20

50

75

100

120

150

Initial concentration (mg/L)

Fig.4

Reactive blue removal as a function of
initial concentration at optimum pH anddosage.

10080%Dye removal

For Electro-coagulation
pH effect's
Experiments were conducted under acid,alkaline and neutral conditions as mentioned inchemical coagulation process by adjusting theelectrolyte with 0.1M NaOH and/or 0.1M HCl. The
observations are given in Figure 5, where theremoval of reactive blue increased with decreasing
the pH of the solution. The reason may be due to theincreasing of the hypochlorite ion in an acidic
medium and in low pH solutions the presences of
hypochlorous acid (HOCl), which possesses higher
oxidation potential than that of hypochlorite ion.
It can be ascertained from Figure 5 that, themaximum removal for reactive blue was 88% at pH
2 for NaCl concentration 500 mg/L and voltage of 5
V after about 30 minutes reaction time. Some
researches achieved maximum removal of color in
the pH range of 1.5 – 4 [18, 19].

0
200

Fig.6

4

6
pH

8

10

500
NaCl (mg/L)

1000

Percentage removal of reactive blue, as afunction of NaCl concentration

Initial concentration effect's
The reactive blue percentage removal decreases
with an increase in the initial concentration, because
the number of metal hydroxide flocs formed may beinsufficient to absorb all of the pollutant molecules
when the initial pollutant concentrations are rather
high [23]. Dye solutions with the following
concentrations (50, 75, 100, 200, and 300 mg/L) wasused in order to test the effect of initial dye
concentration on degradation efficiency at optimum
pH and NaCl concentration. Results showed that,when dye concentration increased to 100 mg/L, dyeremovals increased to 96% as shown in Figure 7.
However, when the concentration raised up to 300
mg/L, the removal decreased to 51%, because of dye
molecule adsorption on metallic hydroxide flocs. At
the same voltage, the amount of Al3+ that released
from anode to solution is constant, thus, the amountof flocs is also constant, therefore, a specific amountof dye molecules would adsorbed onto the flocs, nomore dye molecule adsorption, therefore, theefficiency of dyeremoval decreases whenconcentration increase [24, 25].

%Dye removal

Fig.5

2

40
20

100
90
80
70
60
50
40
30
20
10
0
0

60

12

Percentage removal of reactive blue, as afunction of pH.

NaCl concentration effect's
The effect of changing the electrolyte
concentration (200, 500 and 1000 mg/L) on dye
removal efficiency at optimum pH obtained fromprevious experiment, fixed dye and initial
824

SEE - Bangkok, Thailand, Nov.11-13, 2019

electrolytes to 200 mg/L and 1000 mg/L. The
removal efficiency, increased with increase in theinitial concentration to certain values then decreased.
The performance of electro-coagulation isrelatively better than chemical coagulation. To
overcome problems associated with chemical
coagulation, EC could be advocated as a novel
approach in removing wide range of wastewaterpollutants such as dye.

120

%Dye removal

100
80
60
40
20
0
50

75

100

200

300

ACKNOWLEDGMENTS

Initial concentration (mg/L)

Fig.7

The author would like to thank theMustansiriyah
university(www.uomustansiriyah.edu.iq) Baghdad - Iraq for
its support in the present work.

Percentage removal of reactive blue as afunction of initial concentration

Voltage variation effect's
The effect of varying the voltage in the ranges
5 and 15 V at optimum operation conditions wasinvestigated. Reactive blue removal increases whenthe voltage increased. The removal efficiency
reached to 90% when the voltage is 5, and 99% at
15 V, as shown in Figure 8. The maximum removal
is registered at 15 V. However, after 60 min theremoval was at a constant rate. . It is clear that, dyeremoval depend on many factors, first of all,aluminum dosage, and this depends on the voltage
and time of reaction, because of that, when thevoltage increase, coagulants and flocs amountincrease, so, dye is removed. The same results wereobtained by other researchers [26, 27].
120

[1] Eddy M.A., Inc Wastewater Engineering,
Treatment and Reuse. 4th Edition, 2003.
McGraw-Hill, New York, 2003, pp. 545-644.
[2] Korbahti
K.B.,
Abdurrahman
T.,
Electrochemical Treatment of Simulated Textile
Wastewater with Industrial Components andLevafix Blue CA reactive dye , j.haz mat, 2006,
pp. 422-31.
[3] Sheng H.L., Chi M.L., Treatment of textile waste
effluents by ozonation and chemical coagulation,
Water Research J.,Vol. 27, Issue 12,1993, pp.
1743-1748.
[4] Ghoreishi R., Chemical catalytic reaction andbiological oxidation for treatment of nonbiodegradable textile effluent, Haghighi,
Chemical Engineering Journal, Vol. 95, Issues13, 2003, pp. 163–169.
[5] Daneshvar N., Oladegaragoze A., Djafarzadeh,N., Decolorization of basic dye solutions byelectrocoagulation: an investigation of the effectof operational parameters, J. Hazard. Mater.
B129, 2006, pp. 116–122.
[6] Shaul G.M., Holdsworth T.J, Dempsey C.R.,
Dostall K.A., Fate of water soluble azo dyes in
the activated sludge process, Chemosphere, Vol.
22, 1991,pp.107-109.
[7] Swamy J., Ramsay J.A., The evaluation of white
rot fungi in the decoloration of textile dyes,
Enzyme and Microbial Technology, 1999,
Volume 24, 2004, pp.130-137.
[8] Muthukumar M., Sargunamani D., Selvakumar
N., Rao., J.V., Optimisation of ozone treatment
for colour and COD removal of acid dye effluent
using central composite design experiment, Vol.
63, Issue 2 , 2004, pp.127–134.
[9] Pablo C., Fabiola M. , Carlos J., Justo L. ,and Manuel
A.R.,
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andElectrocoagulation of Wastes Polluted withDyes, Environ. Sci. Technol., 2006, Vol. 40, No.

V15

100
%Dye removal

REFERENCES

V5

80

60
40
20
0
0

Fig.8

20

40

60
Time (min.)

80

100

120

Percentage removal of reactive blue as afunction of voltage

CONCLUSIONS
After treatment by both electro-coagulation andchemical coagulation processes, the obtained
removal efficiency of reactive blue are very high,the values is 96% when chemical coagulation wasused, while it's 99% with electro-coagulation
treatment. The optimum pH for both processes
occurred under acidic condition where the value is 6
and 2 for chemical coagulation and electrocoagulation respectively. The removal efficiency
increase with increased dosages of coagulants and825

SEE - Bangkok, Thailand, Nov.11-13, 201920, 2006 pp. 6418–6424.
[10] Usha N.M., Rekha H.B., Mahaveer D.,
Contribution of Electrochemical Treatment inTreating Textile Dye Wastewater, World
Academy of Science, Engineering andTechnology International Journal of Materials
and Textile Engineering Vol. 8, No. 2, 2014.
[11] Guohua C., Electrochemical technologies inwastewater
treatment,
Separation
andPurification Technology, Vol. 38, 2004, pp. 11–
41[12] Humberto R., Carlos B., Ivonne L., Cheikh F.,
Bilyeu B., A Combined ElectrocoagulationElectrooxidation
Processfor
CarwashWastewater Reclamation, Int. J. Electrochem.
Sci., Vol. 10, 2015, pp. 6754 – 6767.
[13] Mitra G., Ahmad, J.J., Niyaz M.M., Dye
Removal, Energy Consumption and Operating
Cost of Electro-coagulation of Textile
Wastewater as a Clean Process, Clean- Soil Air
Water, 2011.
[14] Gaceva G. B., Aleksandra B. and Bojan D.,
Discoloration of Synthetic Dyeing Wastewater
Using Polyaluminium Chloride. G.U. Journalof Science, Volume 2, No.4, 2008, pp. 123-128.
[15] Baoyou
S., Guohong
L., DongshengW., ChenghongF., Hongxiao
T.,The
performance of preformed polymeric aluminumspecies, Journal of Hazardous Materials, Vol.
143, Issues 1–2, 2007, pp. 567–574.
[16] Akshaya K.V., Rajesh R.D., Puspendu B., A
review on chemical coagulation/flocculation
technologies for removal of colour from textile
wastewaters, Journal of Environmental
Management, Vol. 93, 2012, pp. 154-168.
[17] Zonoozi M. H., Mohammad R.A., Mokhtar A.,
Removal of Acid red 398 dye from aqueous
solutions by coagulation/flocculation process,Environmental Engineering and Management
Journal, Vol. 7, No.6, 2008, pp. 695-699.
[18] Chen, G. and Hung,Y.T., Electrochemical
Wastewater Treatment Processes, in Handbook
of Environmental Engineering, The Humana

Press Inc.,: Totowa, NJ., Vol. 5, 2007, pp. 57105.
[19] Li F., Li S., Zhang C., Zhao H., Application of
corrosive cell process in treatment of printing
and dyeing wastewater, Chem. Eng. Environ.
Protect., Vol. 15, 1995, pp. 157–161.
[20] Yang, Y., Electrochemistrical decolorization of
C.I. Reactive black KN-B simulated wastewater,
Chin. J. Environ. Sci, 2009.
[21] Wong H.M, Shang C., Cheung Y.K., Chen G.,
Chloride Assisted Electrochemical Disinfection,
in: Proceedings of the Eighth Mainland-Taiwan
Environmental Protection Conference, TsinChu, Taiwan, 2002.
[22] Vinita K., Electrocoagulation for the treatmentof textile industry effluent - A review Article in
Journal of Environmental Management, 2013.
[23] Song,S He,Z.,Qiu,J., Chen, X. L., Ozone
Assisted Electrocoagulation for Decolorizationof C.I. Reactive Black 5 in Aqueous Solution:
An Investigation of the Effect of Operational
Parameters, Sep. Purif. Technol. Vol. 55, 2007,
pp. 238–245.
[24] Fatiha Z., Patrick D., Brahim L. , Jalila B.,
Jean,F.,¸ Ois B., Said B. , Kacem
K.,
Decolourization of dye containing effluent
using mineral coagulants produced byelectrocoagulation, Journal of Hazardous
Materials, Vol. 155, 2008, pp. 153–163.
[25] Zhang, Y., Cong, Y., Sun, P., Experiment andkinetic model for methyl orange wastewater
removal by electrocoagulation. J. Chem. Ind.
Eng. Soc. Chin., 2009.
[26] Arslan, A., Tuerkoglu, I., Kabdash, G.I.,
Chemical pretreatment of a spent disperse
dyebath analogue by coagulation andelectrocoagulation. Fresenius Environ. Bull.
Vol. 17, 2008, pp. 1809-1815.
[27] Jiang J.Q., Development of coagulation theory
and pre-polymerized coagulants for water
treatment, Separation and Purification Methods,
Vol. 30, 2001, pp.127-141.

826

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

INDOOR PLANT SPECIES SURVIVAL UNDER DIFFERENTENVIRONMENT IN INDOOR VERTICAL GARDEN
1

Sukanya Chaipong1
Faculty of Agricultural Technology, Rajamangala University of Technology Thanyaburi, Thailand
ABSTRACTOne way to measure the efficacy of a vertical garden is the survival of the plants that cover the growing area,
which affects the beauty of a vertical garden. Thus, this research aimed to study the survival of some indoor plant
species in with and without air conditioning. We selected plants from 15 families in a total of 20 plant species byreview the documents related to the indoor plant and based on duplication of the top 20 plant species, and popularin the market. The study was conducted by incubating in a room with air conditioning ( average of temperatureand light at 25. 6 Celsius and 396. 6 Lux, respectively) and without air conditioning ( average of temperature andlight at 31. 9 Celsius and 2,044. 1 Lux, respectively) , 8 hrs. / day average light, watering one time in the initial
experiment and noticed the water saturated soil. The survival condition was recorded in 3 levels, namely, thenormal condition was 1, the wilted condition was 2 and the dead condition was 3. The data was collected for 15
days. The results were 7 species of plants that tolerated both conditioning included as Philodendron 'Moonlight',
Aechmea fasciata, Tradescantia zebrina, Chlorophytum comosum, Dracaena surculosa, Tillandsia usneoides andNephrolepis cordifolia. There were in Araceae, Commelinaceae, Agavaceae, Neprolepidaceae and Bromeliaceae
families.
Keywords: Indoor plant species, Vertical garden, Plant species survival, Indoor vertical garden
garden, 23 species, using the planting sheet ( Felt)
attached to the structure and penetrate the planting
box. Using 4 plants per species, first watering once,
until the soil is saturated with water.
2) Place in the interior of the building with air
conditioning and without air conditioning turned tothe east, both conditions.
3) Recording data for 15 days by temperature andlight ( Light intensity meter model TM- 213
TENMARS), which 3 times daily at 9. 00 am. , 12. 00
am. and 16. 00 am. and also the survey record insurvival landscape ( The survival landscape is thesurvival plants, which beauty in landscape visibility.)
was representative 1 as normal, 2 as wizened ( With
more than 50% wilted leaves of the leaves) and 3 asdead.

INTRODUCTION
The limitation on space for landscaping byvertical gardening is a more popular choice, and also
has many benefits, especially improving the urban
environment. Nowadays, it is popular both inside andoutside the building. A living wall with a fabricsystem is one of the types that is used inside thebuilding. The efficiency of this system depends on thewater supply system, structure, and plants that affectthe efficacy of cover and beauty. It was found that 510 percent of a plant in the indoor living wall deathand must be planted to replace. This high-cost was
loss by planted to replace [1]. Considerations forchoosing plants depend on moisture and light which
may not be direct sunlight but it can be light bulbs [2].
Therefore, the efficiency maintenance of living wall
which is the plant selection for an aesthetic and living.
This research aims to test the survival plants that arearranged in a vertical garden, both with air
conditioning and without air conditioning. This
information is useful for the landscape designers andgardeners for choosing a plant that anesthetic andliving to save on the maintenance cost.

3 = Died

MATERIALS AND METHODS

Fig. 1

1) Establish a vertical garden structure from steel
material, box size 1.00 x 2.00 meters, choose the typeof plants that are popularly planted on the vertical

2 = wizened

1 = Normal

Survival landscape status4) Using the data to analyze with descriptive
827

SEE - Bangkok, Thailand, Nov.11-13, 2019

Peperomia obtusifolia (Piperaceae) and Episcia spp.
& Hybrid (Gesneriaceae) which is wizened in the air
conditioning and normally in the without air
conditioning.
It can be seen species that found to survive bothconditions is Araceae but found that some species
wizened in both conditions in this family include
Syngonium podophyllum and Epipremnum aureum.
Pellionia repens (Lour.) Merr. and Pilea cadierei isin the Urticaceae, were died in both conditioning, but
Pilea cadierei survived without air conditioning. The
air-conditioned rooms have a “dead” plant rather thanin a room without air conditioning. While in a room
without air conditioners were found less " wilted"
plants and also " dead" plants condition than rooms
with air conditioning.

statistics and interpretation of values obtained fromthe average survival conditions in the landscape, therewas 1.00 - 1.67 means normal, 1.68 - 2.33 means
wilted and 2.34 - 3.00 means death. Comparing thesurvival conditions of both plant conditions with the
Chi-Square hypothesis test.
RESULTS
Survival Landscape Survey Results.
Based on the study of ornamental plants that aresuitable for use in vertical garden, comprising 16
families [3]-[5] including Araceae, Aspleniaceae,
Liliaceae, Commelinaceae, Bromeliaceae, Labiatae,
Polypodiaceae,
Urticaceae,
Gesneriaceae,
Apocynaceae,
Acroleanidae,
Neprolepidaceae,
Convallariaceae, Lythraceae, Piperaceae andAgavaceae. There were chosen 23 species of plantsthat the book recommends, and also considered the
popularity and available in the market. 23 Plants
experimented with 16 Families as shown in Table 1
and 2.
The results found both landscape survival
conditions were " normal" including Chlorophytum
comosum ( Anthesicum Vittatum) , Aechmea fasciata,
Tradescantia
zebrina Loudon (Zebrinapendula Schnizl. ) , Philodendron 'Moonlight',
Dracaena surculosa, Nephrolepis cordifolia andTillandsia usneoides, which are in family ofBromeliaceae Commelinaceae Araceae Agavaceae
Neprolepidaceae and Bromeliaceae, respectively. On
the other hand, Fittonia albivenis, Pilea cadierei,
Lectranthus scutellarioides and Cuphea hyssopifolia
died in both conditions, which are in family of
Acanthaceae Urticaceae Labiatae Lythraceae,
respectively. Further, it was found that wizened plants
in both conditions, Platycerium holttumii, Asplenium
nidus, Syngonium podophyllum, and Epipremnum
aureum, which are the family of Polypodiaceae,
Aspleniaceae, Araceae, respectively.
In additional Pellionia repens ( Lour. ) Merr was
found dead in air condition but the normal conditionin without air conditioner, which belongs to the
Urticaceae and also two species are Ophiopogonjaponicus ( Convallariaceae) and Chlorophytum
comosum ( Anthesicum Picturatum) ( Liliaceae) ,which died in air conditioning but wizened in the
without air conditioning. Moreover, there are two
types of Araceae; Epipremnum aureum 'Marble
Queen' and Philodendron erubescens K. Koch &Augustin ‘ Lemon Lime’ , and Dischidia ‘ White
Diamond’ (Apocyneceae), there were normally in air
conditioning but wizened in without air conditioning.
On the other hand, it was found two species;

Table 1 23 Plant species of experimented
Scientific nameNo.
1 Fittonia albivenis
2 Pilea cadierei
3 lectranthus scutellarioides
4 Cuphea hyssopifolia
5 Platycerium holttumii
6 Asplenium nidus
7 Syngonium podophyllum
8 Epipremnum aureum
Chlorophytum comosum
9 (Anthesicum Vittatum)
10 Aechmea fasciata
Tradescantia
zebrina Loudon (Zebrina
11 pendula Schnizl.)
12 Philodendron 'Moonlight'
13 Dracaena surculosa
14 Nephrolepis cordifolia
15 Tillandsia usneoides
16 Ophiopogon japonicus
Pellionia repens (Lour.)
Merr.
17
Chlorophytum
comosum (Anthesicum
18 Picturatum)
Epipremnum
19 aureum 'Marble Queen'
Philodendron
erubescens K.Koch &20 Augustin ‘Lemon Lime’
Dischidia ‘White
21 Diamond’828

Family name
Acanthaceae
Urticaceae
Labiatae
Lythraceae
Polypodiaceae
Aspleniaceae
AraceaeAraceae
Liliaceae
Bromeliaceae
Commelinaceae

Araceae
Agavaceae
Neprolepidaceae
Bromeliaceae
Convallariaceae
Urticaceae
Liliaceae

AraceaeAraceae

Apocyneceae

SEE - Bangkok, Thailand, Nov.11-13, 2019

Scientific name
No.
22 Peperomia obtusifolia
23 Episcia spp. & hybrid

Based on the main hypothesis that plants are in theair- conditioning and without air- conditioning haveno difference in a survival landscape. It is found thatsignificance at 1.88, therefore both conditions had nodifference in a survival landscape of a significant
level at 0.05.

Family name
Piperaceae
Gesneriaceae

Table 2 landscape survival status in air-conditioning
and without air-conditioning

DISCUSSION

Without air condition
Air condition room
room
(Temperature(Temperature
average 25.6)
average 31.9)
No.
landscapelandscapesurvival SD Mean- survival SD Meaninging
status (x‾)
status (x‾)
D
D
2.69
0.24
2.73
0.59
1
2

2.40

0.26

D

2.57

0.67

D

3

2.58

0.26

D

2.35

0.88

D

4

2.47

0.27

2.57

0.77

5

1.76

0.14

D
w

2.20

0.51

D
w

2.08

0.86

w

6

2.32

0.26

w

7

2.24

0.24

w

1.77

0.73

w

8

2.30

0.23

w

2.00

0.93

w

9

1.00

0.00

1.60

0.51

N

10

1.00

0.00

N
N

1.15

0.58

N

11

1.00

0.00

N

1.40

0.51

N

1.40

0.51

N

12

1.00

0.00

N

13

1.48

0.13

N

1.53

0.52

N

14

1.00

0.00

N

1.13

0.52

N

15

1.00

0.00

N

1.23

0.42

N

16

2.34

0.27

D

2.20

0.94

w

17

2.47

0.21

D

1.62

0.31

18

2.54

0.17

D

1.98

0.93

N
w

19

1.67

0.17

1.93

0.88

w

20

1.11

0.06

N
N

1.68

0.71

w

21

1.00

0.00

N

1.83

0.94

22

1.77

0.20

w

1.52

0.59

w
N

Light temperature and relative humidity wereaveraged relative rooms with and without air
conditioning 25. 6, 31. 9 degrees Celsius, and 396. 6,
2,044.1 lux and 56.45% 51.25%, respectively. There
was a light average of 8 hours/day. Gunawardena K.
and Steemers K. [6] said that the relative humidity ofhumans and plants are that occupant comfort in theroom is 20- 28 degrees Celsius and 30- 50% relative
humidity and also Blanc P. [ 7] said that some plant
species selected tend to require high canopy humidity
to maintain good foliage health ( RH85– 95% ) . This
comfort level RH may present the risk of foliage
water stress. Vertical plant canopies however rareobserved to maintain a self- hydrating micro climatethat mitigates this risk to an extent. In additional,
Jongrungklang N. [ 8] said that the temperature andhumidity in the air is a factor that affects thedehydration of plants. This affects the growth processof plants, and Techawongstien S. “In press” [9] saysthat moisture in the air is a low effect on a lot of
dehydration plants. This is consistent with the resultsof the study that air-conditioned rooms have a "dead"landscape survival rather than in rooms without air
conditioning. Therefore, the relative humidity level inthe experiment was at the level that humans andplants are occupant comfort but a relative humiditythat likely to be more maintained to good foliage
health. As corresponds to the results of the air
condition room which the lower relative humidity,
was “dead” plant rather than in another.
The study was found that the plants survival
landscape both conditions are Tradescantia zebrina
Loudon ( Zebrina pendula Schnizl. )of theCommelinaceae family which is a plant with craterand leaf similar to succulent characteristics.
According to the study Gunawardena K. and
Steemers K. [ 10] , one of the most popular plants is
succulentplants.
This corresponded to
Rochanavibhata [ 11] found that indoor shrub plantsthat are resistant to low- light environments or lightfrenzy are mostly succulent plants. The family issimilar to succulent plants namely the Philodendron
in the Araceae and the Dracaena surculosa in the
Agavaceae which is Semi- succulent plants [ 12] . In
additional plants that tolerate both conditions were

w

N
0.20
1.52
0.59
23 1.77
Remarks: D is died, W is wizened and N is Normal
Hypothesis Results
Comparison of survival landscape of plant species
in each condition was found that each plant is notdifferent in both conditions of a survival landscape.
There were the same results as 0.317, therefore it was
accepted the main hypothesis that each plant notsignificantly different at the level of 0. 05 of survival
landscape.

829

SEE - Bangkok, Thailand, Nov.11-13, 2019[3] Flower Ornament Club, Ornamental Plants
Manual. Bangkok: United Books, 1993, pp 1138.
[4] Promthong W., Bunnak C. and Chaimongkol C.,
Indoor Plotted Plant (2nd edition). Bangkok,
Pikanesh Publishing, 2000, pp. 1-103.
[5] Bunnak T., Vertical Garden Plants (1st edition).
Bangkok: Baanlaesuan Publishing, 2012, pp 1129.
[6] Giordano R., Montacchinia, E., Tedescoa, S. andPeronea, A Living Wall Systems: a technicalstandard proposal. Energy Procedia, Vol. 111,2017, pp. 298 – 307.
[7] Blanc P., The Vertical Garden: from Nature to
the City (Revised Ed), W.W. Norton, New York,2012, pp. 208.
[8] Jongrungklang N., Crop growth modeling: a
novel way to supplement conventional trial.
KHON KAEN AGR. J., Vol. 41, Issue 3, 2013,
pp. 359-368.
[9] Techawongstien S., Factors Affecting Plant
Growth and Development, Horticultural field,
Department of Plant Science and Agricultural
Resources, Faculty of Agriculture, Khon Kaen
Universit, 2017, Available
Source: https://ag.kku.ac.th/suntec/1341/134101
20%01Factors%20affecting%20GD%)20note).pdf, August 1, 2017.
[10] Gunawardena K. and Steemers K., Living walls
in indoor environments. Building andEnvironment, Vol. 148, 2019, pp.478-487.
[11] Rochanavibhata S., Plant Roofing Plates to help
reduce heat. Independent Study, Master ofArchitecture, Department of Architecture,
Kasetsart University, Bangkok, Thailand, 2008.
[12] Chayamrit K., Key Characters of Plant Families
No.3. Forest and Plant Conservation Research
Office, Department of National Parks, Wildlife
and Plant Conservation. 90 pages, 2008, pp 1-90.
[13] Shackleton K., Bell N., Smith H. and Davies
L., The role of shrubs and perennials in thecapture and mitigation of particulate air pollution
in London, Centre for Environmental Policy,
Imperial College London, 2012, Available
Source:https://www.tfl.gov.uk/cdn/static/cms/documents/role-gi-pmpollution.pdf, August 1,
2017

Nephrolepis cordifolia in the Neprolepidaceae,
Aechmea fasciata and Tillandsia usneoides in theBromeliaceae both families are generated with wax
leaf. These plants are suitable for planting in a verticalgarden especially in a living wall. Due to the leaves
can reduce dehydration and also reduce the capture ofdust “In press” [13].
CONCLUSION
The hypothesis test shown that the survival
landscape conditions of each plant and bothconditions do not differ at the significance level 0.05.
These results of temperature and relative humidity
have affected the survival of plants. The indoor
should have a temperature of 20- 28 degrees Celsius
and relative humidity of 30- 50% so that people andplants are comfortable. It can maintain good foliage
health in an indoor vertical garden without air
conditioning, which a temperature of 28- 32 degrees
Celsius and relative humidity at 85-95%. On the other
hand, an indoor vertical garden with air conditioning
suggests to Commelinaceae, Araceae, Agavaceae,
Neprolepidaceae, and Bromeliaceae.
From the results, appropriate plants arerecommended in the vertical garden ( Living wall) ,which with and without air conditioning, including
Philodendron 'Moonlight', Aechmea fasciata,
Tradescantia zebrina, Chlorophytum comosum,
Dracaena surculosa, Tillandsia usneoides, andNephrolepis cordifolia.
ACKNOWLEDGEMENTS
Thank you to the Faculty of Agricultural Technology,
Rajamangala University of Technology Thanyaburi
for the research budget.
LITERATURE CITED[1] Pérez-Urrestarazu L., Fernández-Cañero R.,
Franco-Salas A. and Gregorio E., Verticalgreening systems and sustainable cities. Journalof Urban Technology, Vol. 22, Issue 4, 2015, pp.
65-85.
[2] Fernández-Cañero R., Urrestaraz, LP. and Salas
FA., Assessment of the Cooling Potential of an
Indoor Living Wall Using Different Substrates in
a Warm Climate, Indoor and Built Environment,
Vol. 21, Issue 5, 2012, pp. 642–650

830

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE CONSIDERATIONS FOR URBAN DESIGN REGARDING THE
PRESENCE OF ONLINE TAXI BIKE

1, 2

Heidy Octaviani Rachman1, Chotib2 and Kemas Ridwan Kurniawan3
School of Strategic and Global Studies, Universitas Indonesia, Indonesia; 3 Department of Architecture,
Universitas Indonesia, Indonesia

ABSTRACTThe online taxi bike gives some convenience to customers since its first launch. The demand for using online
taxi bike from the public is quite high. Unfortunately, the high demand is not accompanied by the adaptation ofurban space. Streets and circulation nodes begin to be filled with online taxi bike which is hanging or waiting forpassengers. This activity causes congestion and misuse of urban infrastructure. This development must be
maintained by the government so that the presence of online taxi bike can run optimally without harming any
parties. This study will examine how significant the impact of the presence of online taxi bike in urban areas,
related to the use of space and urban infrastructure. This study uses qualitative method is done by observing several
strategic points in the city and synthesize through the map. The research is complemented by literature studies andenriches the latest information through the city news. The result prove that the existence of online taxi bike canreach the blank spot of the city and complete the public access to the destination. Nevertheless, its existence canlead to conflict especially with other public transportation services. On the other hand, passengers feel great helpedby the presence of online taxi bike. The meeting between the two can be arranged by the government in terms ofinter-reaching, so that the congestion is reduced and more orderly.
Keywords: Online Taxi Bike, Demand, Urban Space, Infrastructure, Environmental Behavior.

in the world by working to produce history, science,and self-awareness (Lefebvre, 1974). We canunderstand that the civilization of human life
originates from a long and undefined history of space
production because humans can only reach the world
to the extent that it can be sensed. But we canrecognize how space is formed by probing its origin,that is a human social activity.
According to Lefebvre, there are 3 concepts ofhumans create space according to the way they live insocial life. First, perceived space is all physical spacethat can be sensed by humans. Perceived space or
spatial practice is the first space where the occurrenceof social interaction between humans formed tohuman civilization for the first time. Second,
conceived space is all space that comes from nonphysical aspects or only exists in one's mental state.
This second space is only formed after real social
interactions occur in physical space. This spacedevelops because humans use their minds to makeideas, make their own perceptions about what they
have experienced. With this idea or perception, it will
shape the way every human being acts in physicalspace. Physical space that has been reinterpreted byhumans then gradually changes the shape of existing
spaces. These spaces are lived space. The threemeanings of space do not occur linearly, the process
can be intervened by various things, one of them istechnology. These three concepts of space arecommonly called Triad of Social Space.

INTRODUCTION
Human activity has been made easier by thepresence of technology because space and time canbe reduced. With technology, we can now orderwhatever we need through our hands without steppingout of the house. In terms of transportation, now we
no longer need to step into the taxi bike base to get
the services, the taxi bike will approach us.
Previously, to get these transportation services,
we must walk or visit the terminal or base so that it iseasier to get services. But not now, with thesophistication of connectivity technology, certain
spaces can turn into close proximity. We know it by
the term, online-based transportation.
This research will examine how space can beformed through social processes and also with theintervention of technology. The case study in thisissue was an online taxi bike. The formation of online
taxi bike spaces is observed from the production
process of space in the city, a review of social space
and its impact on space.
The area of the study is Margonda street, Depok,
agglomeration area from the capital city, Jakarta. In
observations on the field, there will be many objective
results from the author.
From the book The Production of Space, Lefebvre
said that space is a product of social activity [1].
Understanding of space production according toHegelianism is one of which is human beings living
831

SEE - Bangkok, Thailand, Nov.11-13, 2019

If the production of space has reached lived space,then humans will stay in it and eventually become
accustomed to interpreting the lived space to become
the new perceived space. As proof of this is thedevelopment of human history from ancient times tothe present. Humans and space are constantly
changing. Changes and additions in this space areinterpreted as a reproduction of space or can be called
the effect of surplus production. The production
surplus is not a separate space, but a new idea of man
in interpreting his space.
The definition of production here is a process that
includes various kinds of activities and forms ofspace. The production concept is simplified into three
concepts, that is an actor (labor), production process(production) and product (product). In this case, spacebecomes part of a historical production, which
includes the intersection of time, space and social
beings.

Fig. 2 The illustration of triad of space with interventionof technology.
According to Lefebvre in The Production ofSpace, in the context of space production, a city is aspace formed and invigorated by social activities fora limited period of time and then changed again in the
future.
The city consists of physical elements, social
systems, and individuals who act in cities (Wirth,1938). Factors that affect the physical city include
economy, social, politics, culture, security and thedevelopment of science and technology. The city
consists of buildings and activities that are above theground, sub-surface installations and above-ground
activities. City design can control and limit a person's
movement, can even decide and intervene (Lynch,1960). We can experience the city with vision,
hearing, smell and another sensing. More than that,the city presents interesting sights and layout toexplore (Lynch, 1960).
A city is formed from every activity carried out
by the community. They act in it, organize space,work together and try to create a better space for the
future. This is what is called the social system in thecity. In terms of population, cities generally havedensely populated and heterogeneous populations,and have political, economic, religious and culturalorganizations (Sirjamaki, 1964).
A good city is a city full of opportunities andexpectations. There is room for fulfilling the main,
secondary and tertiary needs. Inside is an
infrastructure that can connect one place to another,both by walking and riding a vehicle. Without
supportive infrastructure, the development of the city
becomes slow and human activities become
hampered. The network makes all the potential in thecity connected to each other and creates greater
opportunities for human life.
Each city has spatial planning, but no region is100% organized by the authorities. This spurred thedevelopment of the informal sector in certain areas.
Like street vendors and online motorcycle taxi
drivers, he has no place so he uses a weak space frompower to make a place to stay.

Actor (labour)• Humans with various background andcultureProduction process (production)• The aims or the meaning of space• Time• Social relation

Product• The product of space

Fig. 1 The process of production space.
Production of space in the city cannot be separated
from the social relations between the actors
themselves. The conflict that occurred and the driver's
personal life in the community certainly had an
impact on the space production process that occurredin the city. Personal social relationships of online taxi
bike drivers allow them to get a place to stay.
The presence of technology is intended so thathumans can make smaller efforts for results that are
equal or greater and more accurate. Technology not
only facilitates the work of a job, saves time, spaceand energy, but technology also permeates humanactivities and changes the pattern of activities and thespace it produces. Technology also has the power tochange the movements and space produced. The
following is a diagram that explains the changes inspace that occur in terms of Triad of Social Space.

832

SEE - Bangkok, Thailand, Nov.11-13, 2019

interesting thing or the closest node or the name of a
district location. After that, passengers and drivers
negotiate prices. When they have reached anagreement, then they leave.
So, the space produced by taxi bike bases is still
considering district, lane, knot, interesting things andthe edge of an area. Shelters built sometimes do notdamage the existing and disturb activities that occur
there.
Online Taxi Bike and Smart Phone Applications
In this digital era, motorcycle taxis have begun totransform. A more modern taxi bike management
system has emerged, an application that functions asa means of finding motorbike services provided bythird parties (taxi bike drivers). The smartphone
application makes online taxi bike drivers work
anywhere without having to meet each other and getpassengers from the closest radius of their existence.
Because of this, online motorcycle taxis can at any
time access the territory of the base motorcycle taxi.
This is often made as a 'scapegoat' for the reduction
in base taxi bike customers, so there have been
several conflicts between online taxi bike drivers andconventional taxi bike drivers who maintain power intheir territory.

METHODS
The author begins his research by examining thetheory of space production from Lefebvre's
perspective. The author shows how social interaction
forms a space divided into the triad of social space.
Furthermore, Space Production theory is associatedwith the current conditions, that is the era oftechnology use. From there it can be seen how space
can change because of social activities that areintervened by technology.
Data obtained from direct observation andinterviews with objects. Data analysis was carried out
by mapping synthesizing field findings.
The area of the study is Margonda Street, Depok,
an agglomeration area of Greater Jakarta. The
Margonda area is filled with rental and retail housingthat continues to grow throughout the year given theexistence of 2 major universities around this road.
The availability of various needs in this place makes
many people visit to buy their needs and just relax.
Therefore, the Margonda road should be a pedestrianfriendly road, such as the availability of decent
sidewalks and crossing bridges.
FINDINGS AND RESULTTaxi bike is a bicycle or motorbike that is added
by riding passengers or renters. In this discussion,
motorcycle taxi drivers act as central actors forming
space. The personal life of actors outside the work
area influences the choice of space (Lefebvre, 1988:
78).
The Base of Conventional Taxi Bike
The taxi bike base is present in an area through along unplanned process. The process starts with agroup of productive-aged citizens who live in an area.
They gathered to carry out social interactions
including room negotiations until finally theyroutinely carried out motorcycle taxi activities in theroom. The space chosen by the taxi bike base isusually at the end of the road to the fork orintersection and its position can be seen from various
angles. This they use so that prospective passengers
can easily find their presence. While waiting forcustomers to arrive, often these motorcycle taxi
drivers do other activities.
Taxi bike bases usually operate and deliver
passengers around the base area. They rely on spaceknowledge as a signpost. Passengers who use theirservices must walk to the base first to get a
motorcycle taxi. After arriving at the base, it is likely
he will immediately get a taxi bike because usually
the base is occupied by more than 3 motorcycle taxi
drivers. To get to the destination, the passenger tells
the destination by mentioning the spatial code to thedriver. The spatial code can be a street name, anFig. 3 The cycle of conventional taxi bike.
Online taxi bike drivers can choose to stopsomewhere because the place belongs to a friend or
the place is not maintained at all so it is easy to stop
there.

833

SEE - Bangkok, Thailand, Nov.11-13, 2019rest and wait for the next call. Here is a comparison
table of the behavior of online and conventional taxi
bike drivers in city spaces.
Table 1. The Comparation between Online andConventional Taxi Bike
Variable
Conventional
OnlineFormerNeighborhood

Company

Base

Negotiation withthe landlord to
make a base
Rely on existenceon the base

Negotiation or not

PriceStandard
andflexible prices

Price depends on
distance (km) andcongestion levelThe
destination

Use spatial code
to get to thedestination.
Usuallythedestination is stillinthesurrounding area
Operates aroundthe base area andforms
acentralized
network on thebase.

Using spatial code
and GPS to get tothe destination, no
more than 25km.

Drivers
information

Driverdata
cannotbeobtained directly

Driver data can beaccessed throughthesmartphone
application

The
productionof spaceThe
resultingspaceispermanentorsemi-permanent
with a simple
shelterThe
space
produced is semipermanent or juststops(overlaps
with other spacefunctions)

How to getcustomerFig. 4 Travel online taxi bike drivers at a time. Eachdriver is not related to each other, but his activities
can intersect.
The Comparation between
Conventional Taxi Bike

OnlineandTable numbers and labels should be placed on topof the table, hanging by 12.5 mm, and left- and rightjustified. Number the tables consecutively and locate
them after and close to where they are first referenced.
Leave at least one line space between the table, label
and the text. Tables should be auto-fit to a single
column or the whole width over two columns and novertical lines or borders are needed.
OnlinedriverDriving

Conventio
nal Taxi
Bike Base

Conventon
al driver

Driving +app guide

Nomad
OnlineTaxi Bike
BaseThe
location ofdriving

Rely
on
applications,internet
signalaccess, telephoneor smsOperate anywhere
and
form
a
network
notcentered in urban
space
but
centralizedincyberspace.

Fig. 5 The comparation of online and conventional
taxi bike.
Technology injection in conventional humanactivities produces a different space than before.
Conventional motorbike drivers need a certain
amount of space that is fixed for their activities. He
needed the space so that his presence in the city space
could be realized by the local people, so they could
use his services. But for online taxi bike drivers, thefunction of the base as a media of existence isreplaced by smartphone application technology. So
the space produced by online motorcycle taxi drivers
is not space for residents to realize, but as a place to834

SEE - Bangkok, Thailand, Nov.11-13, 2019The Observation
The observation took place in Margonda Street,
Depok which is one of the artery road that connect theagglomeration area and Jakarta.

The presence of information technology that is soeasy makes the structure of activities not always
centered on physical space. Before the presence of an
online taxi bike, we have to walk to the taxi bike baseto get a taxi bike. That means the taxi bike base is a
center for finding transportation services. Since thepresence of online applications, looking for taxi bikeservices no longer need to walk out, just order via
online media, then motorcycle taxis will come towhere we are. This indicates that the center is almost
merged or decentralized.
Discussion of human activities in the city spacecertainly depends on where he is. In this study, I
focused my observation on Margonda Street, Depok
so that I could see the link between space and activity
that occurred. Margonda Street is a primary arterial
road in the city of Depok which is known for its highdensity. This road is the main access for the driver toJakarta or from the direction of Jakarta to Depok. At
07.00-08.30 AM and 16.30-19.00 PM, several points
on this road are crowded by passing vehicles. Online
motorcycle taxis also colored the traffic on themorning and evening on Margonda Street.

CONCLUSIONSThe existence of a taxi bike in a crowded place canbe done because they are looking for passengers byshowing themselves. However, online taxi bike muststill order through the application. The purpose of
online taxi bike is just to get and get orders because
GPS radar will ask for approval in the crowd so that
opportunities are needed to get larger orders.
The impact of courageous online taxi bike trips tocity space is access to access to go anywhere. No needto leave the house to get what he wants. From theobservations made we can conclude that technology
really helps human activities that can be done toimprove the space carried out both mentally andphysically. Social space is formed because of thesocial activities of the community which are usually
hit by conflict because they are not aware of whether
the community is aware of the space negotiations that
occur. Unlike the social space formed bytechnological assistance, it can develop in a relatively
fast time but can cause pros and cons of thesurrounding community because of their impure
participation through social activities.
Taxi bike dares to use technology and social
relations in forming space in the city. Courageous
motorcycle taxi drivers cannot choose as an antisocial space, because attending to it still considers thesocial aspects. As at the first point, the social relations
between former base taxi bike drivers and relations
with coffee shop owners make it easy to get a decent
shelter.

Fig. 6 The location of observation.

Fig. 7 The space organization by online taxi bikedriver.
835

SEE - Bangkok, Thailand, Nov.11-13, 2019

The choice of online taxi bike is done
spontaneously. Weak spaces of guarding or masteryare more likely to be used as transit points. Low
guarded space like the courtyard of a building withlow sidewalks; shophouse without fence or iron chain
barrier; and on the circulation path of vehicles
without police/security guards / regional thugs who
control vehicles. The production of courageous taxi
bike spaces is one of the expressions of adaptation to
the environment and response to social relations,which ultimately makes the face of the city more
dynamic. However, many courageous taxi bikedrivers make traffic jams and pedestrians have towalk on the road instead of on the sidewalk.

[6] Atkinson, Robert D., 1998. Technological
Change and Cities dalam Cityscape: A Journal of
Policy Development and Research, Volume 3,
Number 3.
[7] Bloomer, K. C. & Moore, C. W., 1977. Body,
Memory and Architecture. New Haven: Yale
University Press.
[8] Carmona, M. & Tiesdell, S., 2007. Urban Design
Reader. Great Britain: Architectural Press.
[9] Daimtri, 2014. Persepsi Terhadap Ruang(Perkotaan) – 1. itscomma9.com/persepsiterhadap-ruang-perkotaan-1/. Oktober 9, 2014.
Diakses 19 Agustus 2016.
[10] Gehl, J., 2011. Life Between Building.
Washington: Island Press.
[11] Hardt, M. & Negri, A., 2004. Multitude: War and
Democracy in The Age of Empire. New York:
Penguin.
[12] Neighborhood Placemaking in Chicago.
Chicago: Project for Publik Space (PPS) andMetropolitan Planning Council (MPC).
[13] Katznelson, Ira., 1992, Marxism and the City.
New York: Oxford University Press. Reviewed
by Robert A. Beauregard, University ofPittsburgh.
[14] Licara, M., 2010. Ojek dan Taktik Produksi
Ruang dalam Kehidupan Sehari-hari. Depok:
Universitas Indonesia.
[15] Lynch, K., 1960. The Image of The City.
Cambridge: The Technology Press & Harvard
University Press.
[16] M, Gottdiener., 1993, A Marx for Our Time:
Henri Lefebvre and The Production of Space.
Ebook.
[17] National Association of City Transportation
Officials. 2012. Urban Street Design Guide
Overview. Newyork: Ebook.
[18] Official website of PT. Go-Jek Indonesia.
http://www.go-jek.com/. Accessed May 19,
2016, 06.15 AM.

ACKNOWLEDGMENTS
This article is part of Grant of International
Publications for Student Final Project of Universitas
Indonesia (Hibah PITMA). Thank you to Mr. Chotib
and Mr. Kemas Ridwan Kurniawan for the advice andbrainstorming through this topic and being a
supportive lecturer. Thank you to Department ofArchitecture (Faculty of Engineering) and Urban
Development Studies (School of Strategic and Global
Studies) Universitas Indonesia.
REFERENCES[1] Lefebvre, H., 1974. The Production of Space.
Cambridge: Basil Blackwell.
[2] Wirth, L. 1938. Urbanism as a Way of Life.
American Journal of Sociology, 44(1), 1-24.
Retrievedfrom
http://www.jstor.org/stable/2768119[3] Lynch, K., 1960. The Image of The City.
Cambridge: The Technology Press & Harvard
University Press.
[4] Sirjamaki, J., 1964. The Sociology of Cities. New
York: Random House.
[5] Arendt, Hannah. (1958). The Human Condition.
Chicago & London: The University of Chicago
Press.

836

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SERVICE QUALITY GAP ANALYSIS OF WATER SUPPLY IN URBAN
AREAS: WATER SUPPLY COMPANY, KABUPATEN BOGOR

1

Armeinita Octavia1 and Chotib1
School of Strategic and Global Studies, Universitas Indonesia, Indonesia

ABSTRACTHigh population growth in urban areas has led to higher activities which increase the needs of clean water.
Efforts to provide water in urban areas come from the government known as Water Supply Companies. The
increasing demand will affect the quality of clean water itself, because of water resources capacity is limited andcould create water service quality gap in the end. The purpose of this thesis is to identify the level of customer
satisfaction with the service performance of PDAM Kota Wisata, to identify factors which influence service qualityof Water Supply Company, and to analyze service quality gaps between water supply and the benefits received by
the users (customers). This research uses a qualitative and quantitative approach, data collection is done througharea observation, agency visits, and questionnaires, as well as literature reviews. The assessment of service quality
is carried out through weighting based on the Likert scale, data processing and analysis methods are carried out
through the Structuring Equation Modelling (SEM) method. The results showed some of the service quality aspects
caused by several factors, starts from the water resources capacity, the management of the water supply company,
and the operational standards and procedures in serving water to the users. The conclusions can be done by forming
irreparable factors and give alternative solution to reduce the gap of service quality between water supply andbenefits to the users.
Keywords: Water supply company, Service quality, Water resources, Gap analysis

owned enterprises (BUMD) are not able to financethe need for SPAM management with a pipeline
network or outside the service area of BUMN and
BUMD, it could be done by cooperation with private
sector (Pubic-Private Partnership/KPBU).
PDAM Tirta Kahuripan classify customers as
follows: I, IIA, IIB, IIIA, IIIB, IIIC, IVA, IVB, IVC,
IVD, IVE, V. PDAM Tirta Kahuripan is a member ofInternational Organization (PERPAMSI) and its
performance received rank 10th of Healthy PDAM
[1]. PDAM performance has been measured from 4
aspects of performance indicators: finance (25%),
service (25%), operational (35%), and humanresources (15%). The operational aspect gets thehighest weight because it is an important factor inrevenue generation (coverage of production
efficiency, water loss rates, service hours, waterpressureoncustomerconnections
andreplacement/calibration of customer water meters).
The other influential thing is the determination of
PDAM tariff rates. Based on Permendagri 23/2006,
tariffs are set based on the principle of affordability
and fairness, service quality, cost recovery, efficientuse of water, transparency and accountability andprotection of raw water/water resource, divided into
4 types of tariffs: 1) low tariff (tariff which value
lower than the basic cost; 2) basic tariff (tariff withthe same value or equivalent to the basic cost; 3) full
tariff (higher value than the basic cost); 4) agreement
rates (tariff which are based on agreements between

INTRODUCTION
The increasing of urban population requires theavailability of clean water. SDG's number 6 challenge
is to ensure the availability and management ofsustainable water and sanitation for all, then the
Government's target to achieve 100% clean water in2019 is not an easy thing to do without the help andcoordination of various stakeholders, both ingovernment and the community itself, including
assistance from the private sector.
The management of Bogor Regency drinking
water is managed by the Regional Water Supply
Company (PDAM) Tirta Kahuripan which isdesignated as a water services BUMD (Permendagri
2/2007), and the management characteristics is nonrivalry and join consumption, but there areexcludability (people will be charged of consumingwater, the higher the usage, the higher the cost, andthere is a market mechanism). And to achieve service
for all, water management must be done properly,
from water source, production and distribution
system, including providing scales of services.
Permen PUPR 19/PRT/M/2016 has regulated
cooperation in Drinking Water Supply System(SPAM) implementation related to Government
Support (DPP) on SPAM cooperation, procedures for
granting Government Support, and management ofcentral/regional assets from Government Support. In
case state-owned enterprises (BUMN) or regional
837

SEE - Bangkok, Thailand, Nov.11-13, 2019

PDAM and customers).
One of PDAM Tirta Kahuripan service area
located in separate watersheds of ground water basins(CAT) Bogor is Gunung Putri and Cileungsi (locatedin CAT Bekasi-Karawang) with the highest and third
highest population in Bogor Regency (7.9% and 6%of the total population in 40 sub-districts of Bogor
Regency). The largest service area is managed by
PDAM Kota Wisata Services Unit with 400 liters per
second capacity, and 120 liters per second to serve
Kota Wisata housing area (775 Ha), which is thelargest and integrated housing area with PDAM
facilitation.

need to be improved).
The purpose of this study is to identify the level ofcustomer satisfaction with the service performance of
PDAM Kota Wisata, to identify factors which
influence service quality of Water Supply Company,
and to analyze service quality gaps between watersupply and the benefits received by the users(customers). The result of this study will be useful as
an input to PDAM Tirta Kahuripan in improving thequality of services, as well as for the local
government in terms of regulating water supply
policy for PDAM.
LITERATURE REVIEWThe literature review will start from theexplanation regarding drinking water supply system(SPAM), then the urban areas which is the location of
the study, and ends with the service quality, factor andgap analysis of the quality service.
Drinking Water Supply
System (SPAM)SPAM Development

Water resourcesmanagement:
Integrative, Control,
Investment,
Law & Institutional

Urban Areas:
Kota Wisata

Consumption
pattern & Needs
of water

SPAM pipeline
networks development

Service Quality

Factor analysis
Gap analysis

Fig. 2

Literature review concept.

The research location in the scope of CAT
Bekasi-Karawang.

Drinking Water Supply System (SPAM), SPAM
Development, and Water Resources Management

Although PDAM services for Kota Wisata has
been integrated, and the group rates are included in
IVA (luxury houses), there are still problems, both inwater quality and service system that affect customer
satisfaction. This has caused the users has switched
their source of water from PDAM to other, such as
ground water. Some of the alleged problems occur
include the water discharge capacity received byusers decreases from year to year, frequent turbidityof water (especially during the dry season), and theabsence of notification for repairing leaks so it cannot
be anticipated by the users. These problems occurredbecause of the increasing number of PDAM users(debit capacity is still not increasing) and declining
infrastructure conditions (maintenance efforts that

The government regulation 122/2015 has
stipulated that the Drinking Water Supply System(SPAM) is provided by the Government to fulfill
people’s need of water, and to create water services
and management with quality and at affordable prices,
effective and efficient, balanced between customers
and water supply providers.
In urban drinking water supply system, there is 3
components: water resources, water management,
and water services distribution. Water resources
consists of surface water (air permukaan) and groundwater (air tanah). These water resources are strongly
influenced by the water balance in the area (conceptof watershed/DAS and sub-watershed/Sub-DAS).
And their water flow discharge is strongly influenced
by the ground water basin.

Fig. 1

838

SEE - Bangkok, Thailand, Nov.11-13, 2019

And for the water management, Ministry
Regulation of Public Works & Housing
27/PRT/M/2016 has explained that SPAM
development has to follow the basic processes ofmanagement that are interrelated, the principle of
implementing based on sustainable development,
good governance/corporate governance, including
new development, improvement, expansion,
management of SPAM (operation and maintenance,
improvement, human resource and institutional
development). And management of water resources is
inseparable from management principles in the formof utilization, protection, control, which are carriedout in an integrated manner/multisector (Laws
32/2009).

Table 1 Standards of Domestic Water Needs [3]Population

City Size

Needs of Water(liter/person/day)> 2,000,000

Metropolitan> 210> 1,000,000 – 2,000,000

Metropolitan> 150 – 210> 500,000 – 1,000,000

Big> 120 – 150> 100,000 – 500,000

Big> 100 – 150> 20,000 – 100,000

Medium> 90 – 100> 3,000 – 20,000

Small> 60 – 100

SPAM Pipeline Networks Development, Service
Quality, Factors and Gap Analysis

Urban Areas: Kota Wisata, Consumption Pattern
and The Needs of Water

The SPAM pipeline network development needs
to apply the principles of Water Governance [4]: *)Approach: open and transparent, inclusive andcommunicative, coherent and integrative, fair andethical; *) Performance and operations: accountable,
efficient, responsive and sustainable.
The increasing of water needs will affect theservice quality, the problem occurs especially at thequality and quantity aspects. And these problems
usually lead to the lack of management in providing
services to the customers. One of the descriptive
methods to describe customer satisfaction level (inthis case is PDAM service quality) is Service Quality(ServQual). Quality of service can also be defined as
everything that focuses on the business to meet theneeds and desires of consumers which areaccompanied by the accuracy in delivering it, so thatcompatibility is matched with consumer expectations[5]. Thus, Service Quality can be defined as ananalysis of the expectation achievement level ofcustomers/consumers of services received.
Service Quality can be identified in 5 dimensions:
1) reliability, 2) responsiveness, 3) assurance, 4)
empathy, and 5) tangibles [6] - [8]. The assessment ofservice quality will be differed in the order ofdimensions according to the needs of the study.
Related to service quality that affects PDAM
customer satisfaction, the order of 5 dimensions are[9]: 1) services are real and show direct evidence
including physical facilities, equipment, employees,
and means of communication (tangible); 2) trusted
and reliable, that is, providing services in accordancewith the promised, accurate and satisfying(reliability); 3) responsive in the form of the desire ofstaff and employees to help and provide services
quickly and responsively (responsiveness); 4) can
guarantee include knowledge, ability, politeness,

In fulfilling clean water needs, the government
distinguishes the authority to carry out its
implementation. For rural areas more is carried out by
local governments (Pemerintah Daerah), while forurban areas in general it is left to BUMD, one of themis PDAM. One of the urban areas is Kota Wisata
which has the urban characteristics such as located in
1 wide-range area and integrated with the supply ofclean water piping systems and managed by the
PDAM.
In general, it has regulated how to create
sustainable water resources, the procedures for
exploiting water resources, the water management
including the alternatives of management. But it still
does not lead to a management concept whose
approach is more to the paradigm (mindset) ofpeople's behavior towards water itself. Based on the
directives of existing regulations, all of thememphasize more on treating water as an unlimited
resource. Although water pollution control has been
regulated, it does not explicitly emphasize that water
will be rare at times if it is not managed efficiently
and effectively. We all know that the pattern of water
consumption needs to be a major concern because theuse of water starts from the individual. Water
consumption factors are influenced by individual
factors (character of each user) and economic factors(income level, family size, etc.) [2].
The Ministry of Public Works and Housing has set
the standards for domestic water requirements thatcurrently apply in urban areas according to the size ofthe population.

839

SEE - Bangkok, Thailand, Nov.11-13, 2019independent variables are 5 dimensions of ServQual:
responsiveness, reliability, emphaty, assurance, andtangible. The measurement of each independent
variable is based on certain indicators and using
Likert scale from 1 to 4.

trustworthiness that is owned by staff, free fromdanger, risk and doubt (assurance); 5) shows sincerityin the form of personal attention to customers(empathy).
To analyze and measure which dimension factors
most influence service quality, it will be done byusing confirmatory factor analysis in Structural
Equation Modeling (SEM) method, through AMOS
Statistic Program. There are observed an unobserved
variable in SEM, the unobserved variables can bemeasured from analysis factor indicators.
For the gap analysis, it will be used one of 5 gaps
in ServQual [10]: *) Gap 1: customer expected
service vs. company perception of customer
expectations; *) Gap 2: company perceptions ofcustomer expectations vs. design services that are
portrayed/driven by customers; *) Gap 3: service
design that is portrayed/customer driven vs. service
delivery; *) Gap 4: external communication vs.
service delivery; *) Gap 5: expected service vs.
perceived service.

Employee speed & response
4Q
Complaint service

Administrative & Payment
Services

9Q

Flow of water

Changes in the use ofwater by users

Reliability

Clerk’s attitude at the counter
4Q

Attitude of the administration
officer

Emphaty

Service
Quality of
PDAM

Attitude of the engineering
officer

8Q

Hospitality, courtesy, &honesty of officers
Assurance
Skills of employees &technical officers
Information on waterprovision

Population growth  increasing water needs

Efforts to improve
PDAM supply &management

Quality & stability of cleanwaterPhysical quality of water

Water supply by PDAM

PDAM
characteristics

Responsiveness

7Q

User
characteristics

Cleanliness & tidinessTangible

Comfort facilities

Fig. 4Service Quality of PDAM

Framework for analysis of factors affecting
PDAM service quality.

5 Dimensions of ServQual: Resposiveness,
Reliability, Emphaty, Assurance, Tangible•••

The qualitative approach has been done by fieldobservations, in-depth interviews, documentation.
The observation consists of passive participation
observation, gathering documents from the field
related to the study. In-depth interviews consist ofsemi structure interview with PDAM Kota Wisata,and Gunung Putri Installation (IPA Gunung Putri),using recording and transcription, and it is equippedwith documentation.
Data analysis has been done through quantitative
data analysis (univariate and multivariate) andqualitative data analysis (triangulation). The statistic
data will be analyzed using SEM method with
Analysis Moment of Structure (AMOS).

To identify the level of customer satisfaction with theservice performance of PDAM Kota Wisata
To identify factors which influence service quality ofWater Supply Company
To analyze service quality gaps between water supply
and the benefits received by the users (customers)

Findings
Conclusions andReccomendations

Fig. 3

Research conceptual framework.

METHODOLOGYThis study used mix-methods (quantitative andqualitative approach) with cross-sectional type ofsurvey. The quantitative approach has been done byquestionnaire distribution and structured interview.
Choice of sampling came from the population
characteristics that had been facilitated by PDAM forproviding water. The sample size had been measured
by using 90% reliability, which is 100 respondents,using slovin formula from 8.568 population, and the
choice of sample is proportional fit to size. The study
variables consist of dependent variables (Y) andindependent variables (X). The dependent variable isservice quality of PDAM Kota Wisata, and the

RESULT AND DISCUSSION
The study location is at the end of DAS KaliBekasi, CAT Bekas-Karawang. According to
Kabupaten Bogor Spatial Plan, the area is designatedas a high intensity urban zone. The low slope rate is
only around 0-15%, making the area potential fordevelopment especially urban settlements. But
according to ground water basins data, the study
location is designated as prone zones of greater 4060% zone drop, with 250-600 mg/l chloride content.
840

SEE - Bangkok, Thailand, Nov.11-13, 2019

Map of Ground Water
BasinsFig. 5Service Area of PDAM
Kota Wisata

Fig. 7

Map of ground water basins.

PDAM Kota Wisata as one of the service units of
PDAM Tirta Kahuripan, Branch Cileungsi, which has
1 installation named IPA Gunung Putri, with Cikeas
River as the water resource (surface water). The
capacity is 400 liter/second. It served several
settlements, and the biggest one is at Perumahan Kota
Wisata, which has 8.568 active connections(SR/Sambungan Rumah).
The number of employees working at PDAM
Kota Wisata is 15 people including 1 Head of theService Unit. The 14 staff consist of: customer
relations (including 5 meter-readers), engineering,
engineering administration, and cashier/financial
administration.

Service area of PDAM Kota Wisata.

Identification the Level of Customer Satisfaction
with The Service Performance of PDAM Kota
WisataThe most important thing in this study is the
respondents' assessment of PDAM service
performance. There is a questionnaire has been given
to the respondents to measure the service quality
based on Likert scale 1 to 4 (lowest to highest). And
it will be compared with the level of importance(respondents’ expectation). To describe mean scoreof each item, the indicators and variables are usingclass intervals based on the equation below:(1)
Table 2 Basic Interpretation of Indicator Scores in
Research Variables

Fig. 6

Scheme for the Implementation of Drinking
Water Supply Systems for Kota Wisata.
841

Interpretation of
Performance Quality
Very Low

No

Score

1

1 - 1,75

2> 1,75 - 2,5

Low4> 2,5 - 3,25

High

5

>3,25 - 4,0

Very HighSEE - Bangkok, Thailand, Nov.11-13, 2019laboratory tests (once a month).
With this low satisfaction for water quality andquantity, the result shows that about 20% respondents
have switched or added other water resource (groundwater).
On the other side, the importance of this reliability
dimension is related to easiness for payment system,
accuracy of water meter-reading, and the stability of
PDAM water quality and quantity.

Interpretation of
Expectation/Importance
Very Low

No

Score

1

1 - 1,75

2> 1,75 - 2,5

Low

4
5

> 2,5 - 3,25
>3,25 - 4,0

High
Very High

Service Performance: Responsiveness

Table 4 Distribution of Respondents' Response to
the Reliability Variable (X2)

Based on the results of an in-depth survey incarrying out payments, the clerk is quite alert and fast
to serve residents who want to pay the PDAM bill at
the payment counter. This is also in accordance with
the SOP for administrative and financial services for
PDAM customers.
On the other side, the importance of item 1 is low
because all respondents who have PDAM facilities
have never dealt with customer administration
services, especially in registering as new customers,
because it has been integrated with housing
construction, so that when the handover of the house,
the PDAM is installed.

Items of Reliability (X2)SP

Satifaction Level
P
TP

STP

Easiness in the customer registration
process
Easiness of payment at the payment
counters

F
%
F
%

(4)
13
6.5
25
12.6

(3)
143
71.9
139
69.8

(2)
41
20.6
32
16.1

(1)
2
1.0
3
1.5

3

Meter-reading at the customer's home4

Quality and stability of PDAM water
quality
Smooth flow of water during peakhours
Smooth water off-peak hours

F
%
F
%
F
%
F
%
F
%
F
%
F
%
F
%

12
6.0
8
4.0
12
6.0
22
11.1
11
5.5
8
4.0
5
2.5
116
6.48

111
55.8
67
33.7
81
40.7
124
62.3
64
32.2
73
36.7
87
43.7
889
49.64

64
32.2
80
40.2
66
33.2
42
21.1
89
44.7
91
45.7
89
44.7
594
33.17

12
6.0
44
22.1
40
20.1
11
5.5
35
17.6
27
13.6
18
9.0
192
10.72

No
1
2

5

6
7

8
9

Physical quality of water (water
clarity)
Physical quality of water (wateraroma)
Physical quality of water (taste ofwater)

Accumulation of respondents' answers

Table 3 Distribution of Respondents' Response to
the Responsiveness Variable (X1)
No
1

2
3
4

Satisfaction Level
SP
P
TP
STP

Mean

Performance
Quality

F
%

(4)
9
4.5

(3)
126
63.3

(2)
56
28.1

(1)
8
4.0

2.68

High

F
%
F
%
F
%
F
%

20
10.1
8
4.0
7
3.5
44
5.53

140
70.4
106
53.3
105
52.8
477
59.92

36
18.1
74
37.2
68
34.2
234
29.40

3
1.5
11
5.5
19
9.5
41
5.15

2.89

High

2.56

High

2.50

High

2.66

High

Itmes of Responsiveness (X1)
The speed and responsiveness of
employees in customer
administration services
The speed and responsiveness of
employees in the payment process
Speed of employees in resolving
complaints at the counters
Speed of field officers responds andserves complaints

Accumulation of respondents' answers

Mean

Performance
Quality

2.84

High

2.93

High

2.62

High

2.20

Low

2.33

Low

2.79

High

2.26

Low

2.31

Low

2.40

Low

2.52

High

Service Performance: Empathy
Based on the result of in-depth survey, therespondents felt that they were always wll received
when making complaints, and the location of theoffice is very accessible (inside residential area).
However, the important item ‘Sensitivity of officers
in providing information regarding tariff changes’ has
the lowest quality performance, lots of respondents
did not receive notification of the tariff changes. Even
though PDAM has the SOP of service to customers
related to tariffs: socializing through online media,
distributing letter of notification regarding tariffchanges, and posting information at the payment
counter.
And on the other side, ‘Sensitivity of officers inproviding information regarding tariff changes’
becomes the highest expectations of respondents.
This is what most respondents do not feel. This
problem may occurred because of the coordinationand information delivery system from PDAM to theusers are still not optimal, due to conventional styleof delivering information (still using letter of
notification/non online/non digital), and PDAM does
not have all the RW contacts on each cluster in Kota
Wisata.

Service Performance: Reliability
Easiness of payment at the payment counters has
the highest satisfaction among others, because there
are other alternatives besides the payment counter in
the PDAM office, such as paying throughGovernment Bank ATMs (Mandiri, BNI, BRI, BTN),
Alfamart and Indomaret, Online (Tokopedia,
Bukalapak), etc.
Although it generally shows high quality
performance, there are several important and vital
items for customer service that are still relatively low,such as the aspect of water quality and quantity.
Whereas the PDAM has implemented a Standard,
Operational, and Procedure (SOP) for clean water
fulfillment in maintaining the quality and stability ofclean water, as well as maintaining the smoothrunning of water and the physical quality of water,
including: Permenkes 492/Menkes/Per/IV/2010
concerning Requirements for Quality of Drinking
Water, then the arrangement of water discharge
through a distribution pump adjustment for peak andoff-peak hours, and water quality monitoring by
842

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 5 Distribution of Respondents' Response to
the Empathy Variable (X3)No

SP

Items of Emphaty (X3)

1

Officers’ attitudes at the payment counters

2

Sensitivity of employees on receiving
complaints and gives information

3

Sensitivity of officers in providing
information regarding tariff changes

4

The attitude of the technical officer
towards the customer in carrying out theirduties
Accumulation of respondents' answers

F
%
F
%
F
%
F
%

(4)
15
7.5
11
5.5
9
4.5
9
4.5

Satifaction Level
P
TP
STP
(3)
139
69.8
116
58.3
82
41.2
117
58.8

(2)
41
20.6
63
31.7
84
42.2
63
31.7

(1)
4
2.0
9
4.5
24
12.1
10
5.0

Mean

Table 6 Distribution of Respondents' Response to
the Assurance Variable (X4)

Performance
Quality

No
1

2.83

High
2

2.65

High
3

2.38

Low
4

2.63

High
5

F
%

44
5.53

454
57.04

251
31.53

47
5.90

2.62

High
6

Service Performance: Assurance
7

The skills of employees and Engineering officers
based on the survey results, did not encountersignificant problems, but there were problems related
to the attitude and friendliness of the officers in
resolving complaints. If we compare it with the SOPof recruiting PDAM employees already refers to
Perda Kabupaten. Bogor 7/2007 about theOrganizations and Staffing of PDAM Tirta
Kahuripan. And it requires that the employees mustpegawai Perusahaan Daerah must have the education,
skills and expertise needed, with a maximum age of
35 years, and pass the selection, and for the service
section it has been facilitated with various types oftraining.
Item of Assurance which has the lower quality
performance is the information of water supply
system aspect (condition of water resources,
infrastructures, management and monitoring system).
It is also in accordance with there is no SOP regarding
the information of water supply system, unless there
are users who request it. There is also an evidence thataround 36% of the respondents did not even know
where the water source of PDAM is came from. Even
though lots of them can answer the source is from theriver, but 42% of them have failed to mention which
one is the correct river.
‘Honesty of employees regarding newconnections paying process’ gets the less important
item among other, but there still lots of respondents
wish to have employees to be honest regarding newconnections paying process, considering there was acase with the customer regarding the process of
installing a new connection, but the details of thecosts are not included in the billing system. This is
one of the problems of transparency that occurred and
it is become inconsistency with of the principle ofwater governance.

8

SP

Items of Assurance (X4)

Satisfaction Level
P
TP
STP

Mean

Performance
Quality

2.79

High

2.82

High

2.90

High

2.71

High

2.18

Low

2.19

Low

2.15

Low

34
17.1

2.19

Low

166
10.43

2.49

Low

(4)
15
7.5
10
5.0

(3)
136
68.3
146
73.4

(2)
40
20.1
40
20.1

(1)
8
4.0
3
1.5

F
%
Skills of technical officers in handling F
technical problems
%

14
7.0
10
5.0

154
77.4
128
64.3

29
14.6
54
27.1

2
1.0
7
3.5

PDAM provides information services related F
to the condition & availability of water %sources (water discharge conditions, water
source problems, etc.)
PDAM provides information regarding the F
condition
of
PDAM
water
supply %infrastructure (news about the condition of
piping networks, pumping equipment, water
treatment plants, etc.)
PDAM provides information regarding the F
condition of the PDAM management system %(maintenance scheduling information such as
water drainage, leak repair, etc.)

7
3.5

56
28.1

101
50.8

35
17.6

8
4.0

54
27.1

104
52.3

33
16.6

8
4.0

58
29.1

89
44.7

44
22.1

The PDAM provides information regarding F
the PDAM water use monitoring system
%

7
3.5

57
28.6

101
50.8

F
%

79
4.96

789
49.56

558
35.05

Friendliness and politeness of the complaint F
department officer%
Honesty of employees regarding new F
connections paying process%

Employee skills in the payment process

Accumulation of respondents' answers

Service Performance: Tangible
Based on the survey results, tangible items do notaffect the level of satisfaction too much, because there
are many alternatives on the payment system.
However, for some respondents who still relied on
traveling to the payment counter, several assessmentsof dissatisfaction were more related to the conditionof the service office that was less feasible. There is no
SOP for service facilities at the PDAM, only
adjusting to service requirements, at least having apayment counter and a complaint office.
Although there are many alternative paymentsthat can be done, the respondents' expectations
regarding PDAM service office facilities still need to
be improved, because some respondents still choose
to pay manually to the counters, especially those who
do a lot of activities around their houses.
Table 7 Distribution of Respondents' Response to
the Tangible Variable (X5)Satisfaction Level

Items of Tangible (X5)

SP

P

TP

STP

1

Cleanliness of payment counters

F
%

(4)
7

(3)
130

(2)
57

(1)
5

3.5

65.3

28.6

2.5

2

Cleanliness and tidiness of clerks/staffs

F
%

12

147

39

1

6.0

73.9

19.6

0.5

8

102

80

9

No

3

Comfort of the service office waiting
room

F
%

4

Parking facilities at the service officeF%

5

Public facilities such as toilets

F%

6

The easiness of obtaining a guide bookabout service information

7

The easiness of obtaining information
related to PDAM policy

Accumulation of respondents' answers

843

F
%
F
%
F
%

4.0

51.3

40.2

4.5

19

134

42

4

9.5

67.3

21.1

2.0

8

94

80

17

4.0

47.2

40.2

8.5

9

93

80

17

4.5

46.7

40.2

8.5

10

76

89

24

5.0

38.2

44.7

12.1

73

776

467

77

5.24

55.71

33.52

5.53

Mean

Performance
Quality

2.70

High

2.85

High

2.55

High

2.84

High

2.47

Low

2.47

Low

2.36

Low

2.61

High

SEE - Bangkok, Thailand, Nov.11-13, 2019

Identification of Factors Which Influence Service
Quality of Water Supply Company

Service Quality Gap Analysis Between Water
Supply and The Benefits Received by The Users(Customers)

To get the key factors and indicators that have
major role in Service Quality, the method used is
Confirmatory Factor Analysis (CFA), using AMOS
software as the analysis tool which is used in one of
the SEM (Structural Equation Modeling) procedures.
With this analysis, it can be identified whichindicatorsthatcanexplainaconstruct/concept/variable.
As we can see at the table and figure below, theaspect on Assurance dimension has the highest
loading factor (0.94), with the best indicators forming
Assurance variables are the skills of employees andtechnical officers.

This gap analysis will give the information about
how much the level of customer satisfaction for
Service Quality. This level of customer satisfaction
can be determined by means of the average value of
expectations then disputed by the average value of
performance, which can result 3 categories:
1. Positive (+), category: Very Satisfied
2. Zero (0), category: Satisfied
3. Negative (-), category: Not Satisfied
Table 9 Gap
Analysis
Between Consumers
Satisfaction and Service Quality (Variable:
Responsiveness/X1)

Table 8 Measurement Model Evaluation Phase 2 (2ndOrder Outer Model)
LatentVariable

Service
Quality(X)

Manifest Variables
Responsiveness (X1)
Reliability (X2)
Emphaty (X3)Assurance (X4)
Tangible (X5)

Loading/
Weight
0,927
0,882
0,926
0,941
0,85

Rule of
Thumb
0,500
0,500
1,500
2,500
0,500

Note

Rank

Valid
Valid
Valid
Valid
Valid

2
4
3
1
5

Variable

Item

C1

Responsiveness (X1)

C2

C3

C4

Statement
The speed andresponsiveness of
employees incustomeradministration
services
The speed andresponsiveness of
employees in thepayment process
Speed of employees
in resolving
complaints at thecounters
Speed of field officers
responds and servescomplaints

Mean
Perfor- Expectmance
ation

Gap

Category

2,68

2,46

0,22

Very Satisfied

2,89

3,33

-0,44

Not Satisfied

2,56

3,38

-0,82

Not Satisfied

2,50

3,40

-0,90

Not Satisfied

Table 10 Gap Analysis Between Consumers
Satisfaction and Service Quality (Variable:
Reliability/X2)
Variable

Item

Reliability(X2)

Easiness in the customer
registration process
Easiness of payment at
C6
the payment counters
Meter-reading at theC7customer's home
Quality and stability of
C8
PDAM water quality
Smooth flow of water
C9
during peak hours
Smooth water off-peak
C10
hours
Physical quality of water
C11(water clarity)
Physical quality of water
C12(water aroma)
Physical quality of water
C13(taste of water)
C5

ServQual

Fig. 7

Diagram of Confirmatory Factor Analysis.

844

Statement

Mean
Perfor- Expectmance
ation

Gap

2,84

3,32

-0,48 Not Satisfied

2,93

3,39

-0,46 Not Satisfied

2,62

3,36

-0,74 Not Satisfied

2,20

3,55

-1,35 Not Satisfied

2,33

3,49

-1,17 Not Satisfied

2,79

3,40

-0,61 Not Satisfied

2,26

3,64

-1,38 Not Satisfied

2,31

3,61

-1,30 Not Satisfied

2,40

3,61

-1,21 Not Satisfied

Category

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 11 Gap Analysis Between Consumers
Satisfaction and Service Quality (Variable:
Empathy/X3)
Variable

Item

Statement

Officers’ attitudes at thepayment counters
Sensitivity of
employees on receiving
C15complaints and gives
information
Sensitivity of officers in
C16 providing information
regarding tariff changes
The attitude of thetechnical officer
C17
towards the customer incarrying out their duties
C14

Empathy(X3)

Mean
Perfor- Expectmance ation

Gap

Category

2,83

3,40

-0,57 Not Satisfied

2,65

3,42

-0,77 Not Satisfied

2,38

3,45

-1,07 Not Satisfied

2,63

3,40

Table 13 Gap Analysis Between Consumers
Satisfaction and Service Quality (Variable:
Tangible/X2)-0,77 Not Satisfied

Table 12 Gap Analysis Between Consumers
Satisfaction and Service Quality (Variable:
Assurance/X2)
Variable

Item

Statement

Assurance(X4)

Friendliness andpoliteness of the
C18complaint department
officerHonesty of employees
regarding new
C19connections paying
process
Employee skills in the
C20
payment process
Skills of technical officers
C21 in handling technicalproblems
PDAM provides
information services
related to the condition &D1 availability of water
sources (water discharge
conditions, water source
problems, etc.)
PDAM provides
information regarding thecondition of PDAM watersupply infrastructure
D2 (news about the conditionof piping networks,
pumping equipment,water treatment plants,
etc.)
PDAM provides
information regarding thecondition of the PDAM
D3 management system(maintenance schedulinginformation such as waterdrainage, leak repair, etc.)
PDAM provides
information regarding the
D4
PDAM water use
monitoring system

Mean
PerforExpectmance
ation

Gap

2,79

3,43

-0,64 Not Satisfied

2,82

2,51

0,31

2,90

3,37

-0,47 Not Satisfied

2,71

3,41

-0,70 Not Satisfied

Variable

Item

Statement

Tangible(X5)

Cleanliness of
C22
payment counters
Cleanliness andC23
tidiness of clerks/staffs
Comfort of the service
C24
office waiting room
Parking facilities at
C25
the service officePublic facilities such
C26
as toilets
The easiness ofobtaining a guide book
C27
about service
information
The easiness ofobtaining information
C28
related to PDAM
policyMean
Perfor- Expectmance
ation

Gap

Category

2,70

3,34

-0,64

Not Satisfied

2,85

3,30

-0,45

Not Satisfied

2,55

3,33

-0,78

Not Satisfied

2,84

3,30

-0,46

Not Satisfied

2,47

3,25

-0,78

Not Satisfied

2,47

3,31

-0,84

Not Satisfied

2,36

3,37

-1,01

Not Satisfied

The highest quality service gap is found in thequality and stability of clean water; quantity (debit)
and physical quality of water (water clarity);
sensitivity of officers in providing information on
tariff changes; and information regarding thecondition of water sources, conditions of watersupply infrastructure, conditions of management
systems, and supervision of water use; including theeasiness of obtaining information related to PDAM
policies.

Category

Very
Satisfied

CONCLUSIONS
2,18

3,37

-1,19 Not Satisfied

2,19

3,36

-1,18 Not Satisfied

2,15

3,43

-1,28 Not Satisfied

2,19

3,37

-1,18 Not Satisfied

PDAM Kota Wisata service is still not able toprovide maximum service quality for its customers.
Although the planning has been integrated between
the developer and PDAM, and has been equippedwith several service SOPs, the problem of service
quality is still occured.
There is still customer dissatisfaction especiallyin the aspect of quality and quantity. This became aconcern because of the tariff applied for Kota Wisata
area is IVA (luxury houses), which should be able toobtain better services. And with kind of high tariff, it
can make PDAM more flexible to manage theirfinancing and budgeting, especially in terms ofdevelopment and maintenance, as well as providing
training to employees and officers.
Aspek utama untuk peningkatan kualitas
layanan berdasarkan hasil analisis statistik adalah
keterampilan karyawan dan petugas Teknik. Namun
hal ini tidak terbatas hanya pada keterampilan saat
melaksanakan proses pembayaran dan pelaksanaan
teknis di lapangan, namun juga perlu adanya
perbaikan sikap dalam melayani pelanggan, untuk
menghindari konflik dan kesalahpahaman saat terjadi
keluhan. Hal ini sangat berkaitan dengan peningkatan
sumber daya manusia terutama petugas yang
melayani langsung konsumen PDAM.
The main aspect for improving service quality
based on the statistical analysis result is the skills of845

SEE - Bangkok, Thailand, Nov.11-13, 2019

employees and technical/engineering officers. But it
is not limited only on skills at payment process andtechnical implementation in the field, but also needs
to improve attitudes in serving customers, to avoid
conflicts and misunderstandings when complaints
occured. This means it needs to improve the humanresources, especially who serve directly to the users(costumers).
Di sisi lainnya, penyediaan dan pengelolaan air
bersih untuk kawasan perkotaan tidak dapat hanya
ditangani oleh PDAM saja, namun perlu koordinasi
dari berbagai sektor, mulai dari pemerintah hingga
masyarakat penggunanya, termasuk pelibatan pihakswasta, sehingga prinsip pemerintahan air yaitu
accountable, efficient, responsive and sustainable.
On the other hand, the provision andmanagement of clean water for urban areas cannot
only be handled by PDAM, but it needs coordinationfrom various sectors, from the government to the user
community, including the involvement of private
sector, so it can achieve the principle of water
governance, which is accountable, efficient,
responsive and sustainable.

Cibinong. Kabupaten Bogor: STIE Dewantara.
[3] Meutia, A. (2013). Arahan Pengembangan Sistem
Penyediaan Air Minum Kota Bogor. Bogor:
Institut Pertanian Bogor.
[4] Batchelor, C. (2008). Water Governance
Literature Assessment. London: IIED.
[5] Purnamawati, E. (2012). Analisis Kualitas
Layanan dengan Metode Servqual dan AHP di
Dinas Kependudukan dan Pencatatan Sipil di
Surabaya. Surabaya: FTI - UPN Veteran Jatim.
[6] Parasuraman, A. P., Berry, L., & Zeuthaml, V. A.
(1988). SERVQUAL: A Multiple - Item Scale for
Measuring Consumer Perceptions of Service
Quality. Journal of Retailing, 12-40.
[7] Nugraha, L., Yuniar, & Harsono, A. (2015).
Usulan Peningkatan Kualitas Pelayanan Jasa
Pendidikan Bahasa Inggris Menggunakan Metode
Service Quality (Servqual) di LBPP Lia
Martadinata Kota Bandung. Jurnal Online Institut
Teknologi Nasional, Vol. 3 No. 1, 61-72.
[8] Triwibowo, S., Rukmi, H. S., & Harsono, A.
(2014). Usulan Peningkatan Kualitas Pelayanan
Pada Kawasan Wisata Kawah Putih Perum
Perhutani Jawa Barat dan Banten dengan
Menggunakan
MetodeService
Quality(SERVQUAL). Jurnal Online Institut Teknologi
Nasional, Vol. 2 No. 1, 13-23.
[9] Affandi, H., Zaki, M., & Azmeri. (2017).
Pengaruh Kualitas Pelayanan Terhadap Kepuasan
Pelanggan Pada Perusahaan Daerah Air Minum(PDAM) Tirta Mon Pase Kabupaten Aceh Utara.
Jurnal Teknik Sipil Universitas Syiah Kuala, Vol.
6 No. 3, 297-308.
[10] Maass, W. (2011). Servie Management - Service
Quality. Saarbrucken: Chair in Economics Information and Service Systems (ISS).

ACKNOWLEDGMENTS
This article is part of Grant of International
Publication for Students Final Projects of Universitas
Indonesia: Urban Clean Water Fulfillment.
REFERENCES[1] BPPSPAM. (2017). Buku Kinerja PDAM 2017.
Jakarta: Kementerian Pekerjaan Umum dan
Perumahan Rakyat.
[2] Hendriawan, F., & Cahyadi, A. (2016). Analisis
Faktor-Faktor Yang Mempengaruhi Konsumsi
Air Bersih Pelanggan Kelompok Rumah Tangga
Menengah (K3B) Di PDAM Tirta Kahuripan
Kabupaten Bogor Wilayah Cabang Pelayanan XI

846

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ISOLATION OF HEAVY METAL DEGRADABLE HALOPHILICBACTERIA FROM SOIL IN SAMUT SAKHON PROVINCE,THAILAND
Jaruwan Chutrtong1 and Waradoon Chutrtong2
Faculty of Science and Technology, Suan Sunandha Rajabhat University, Thailand;2
Faculty of Science, Srinarinwirot University, 10110 Bangkok, Thailand Company, Country1

ABSTRACTThis research was conducted to select halophilic microorganisms that can reduce heavy metals in water to be
used in wastewater treatment. Halophilic bacteria from salt field soil were isolated in nutrient broth containing 5
heavy metals compound (Zn, Co, Cr, Hg, and Cu). 20 isolates which growth in heavy metal containing media werescreened. After that, Experiment was conducted to determine the maximum concentration of heavy metals that theisolated could growth. The concentration of heavy metals was obtained from 50-500 mg/L. In media which add
Zn, Co, Cr and Cu compound, the isolated were found to be able to grow at concentrations of 450-500 mg/L but
not growth in media which add Hg (50-500 mg/L). To check the heavy metal degrading ability, the isolates were
cultured in nutrient broth which add the most concentrated of heavy metal and incubated at 37 ° C for 15 days.
Measured the remaining heavy metals and counted the number of microorganisms on days 3, 5,7,10 and 15. It was
found that microorganisms were capable to reduce two heavy metals, Cr and Co. Cr reduced by the isolated HL7
and 10-20. Co reduced by the isolated HL1, 3, 4, 5, 7, 8, 10, 11 and 15. Zn and Cu decreased at the decimal level,
which was not significant. The results of this research showed that the isolated halophilic bacteria had the ability
to reduce some heavy metals, which can be applied in wastewater treatment.
Keywords: Halophilic bacteria, Heavy metal, Isolation, Soil, Thailand

the San Joaquin community in California, was able togrow in water containing 2M of Selenium (Se). The
concentration of Selenium at this level could kill fishand poultry. This type of microorganism could
convert Selenium to dimethyl selenite form, nontoxic substance. The rate of change was 1.65 mg/hr.
[6]. These show that saline-tolerant microbes have theability to reduce heavy metals. Therefore, theresearcher was interested to find microorganisms thatcan degrade other heavy metals in water. This is thesource of this study by separating the salt tolerant
bacteria that is capable to grow in the presence ofheavy metals and studying its ability to reduce heavy
metals in the water of the microorganisms. If theselected microorganism is highly capable, it will beapplied in the treatment of heavy metal contaminatedwastewater.

INTRODUCTION
In the present situation, chemicals are used
increasingly to facilitate life. They are used in manyindustries such as smelting industry, tannery industry,dying industry, agricultural products’ industry(insecticides, pesticides, chemical fertilizers) andhousehold products’ industry [1]. These products may
contain more or less heavy metal contaminants. Using
heavy metal contaminants products can cause
contamination in the environment which harmful tolife, for example, arsenic from smelting outflow inwater resources in Ron Piboon District in Thailandthat caused black fever [2]. Because heavy metals arestable substances, they do not decompose by naturalprocesses in a short time. It must be treated before
released to environments to reduce toxicity [3]. There
are many ways to treat heavy metal contaminatedwastewater, but the friendly way is biologicaltreatment using microorganisms, although it takes
longer to heal [4]. It can save money and does notcause any chemical contamination.
From the former studies, salinity tolerant
microorganisms were able to grow in heavy metals
such as copper, lead, cadmium, chromium and zinc[5]. It also found that saline tolerant microorganisms
could transform toxic substances into non-toxic
substances and absorbed into their cells. Halomonas
spp., salinity-sensitive bacteria, which isolated fromPROCEDURE
In this research, salt-tolerant microorganisms
from soil which collected from salt pan were isolated.
Subsequently, cultured the isolates in broth to study
the efficiency of heavy metals reducing in liquid
environments. The steps are as follows

847

SEE - Bangkok, Thailand, Nov.11-13, 2019

Isolation of Halophilic Bacteria in Metallic
Conditions

RESULT
Isolation of Halophilic Bacteria in Metallic
Conditions

1. Weigh soil, which collected from salt pan in
Samut Sakhon province in Thailand, 10 g.
2. Put the weighing soils in flask containing 100
mL of 0.5% NaCl Nutrient broth.
3. Shake flask to mix soil with media.
4. Incubate at 37 ° C for 5 days.
5. Take 500 μl of culture from 4. Inoculate innutrient broth flask which supplemented with
0.05 mg /ml. of Co, Cu, Hg, Cr and Zn.
6. Incubate at 37 ° C for 72 hours.
7. Take 100 μl of culture from 6. Inoculate on
nutrient agar with 0.5% NaCl. Spread over the plate
and then incubated at 37 ° C for 24 hours.
8. Select different types of colonies and re-streak
on nutrient agar with 0.5% NaCl to get purecolonies.
9. Incubate at 37 ° C for 24 h. Study physicalcharacter by Gram’s stain and microscope.

After a few days of cultivation, bacteria wereisolated and purified. Different morphology colonies
were selected and re-cultured for purification. Total
20 different pure bacterial isolates were collected.
Primary screening was performed by Gram’s staining
and microscopic examination. Characterization ofisolate colonies were carried out and the results areshown in table 1 and 2.
Table 1 Isolate colonies form, elevate and margin.
sample
HL 1
HL 2
HL 3
HL 4
HL 5
HL 6
HL 7
HL 8
HL 9
HL 10
HL 11
HL 12
HL 13
HL 14
HL 15
HL 16
HL 17
HL 18
HL 19
HL 20

Study Resistance of Halophilic Bacteria on Heavy
Metal by Plate Diffusion Method
1. Culture the purely isolated bacteria in 0.5%
NaCl nutrient broth. Incubated at 37 ° C for 18 h fornutrient broth.
2. Divide nutrient agar plate with 0.5% NaCl to 6
equal parts.
3. Spread 100 μl of 18-hour-old broth from 1. onnutrient agar in 2.
4. Drill a hole on 6 divided part of Nutrient Agar
plates in 3.
5. Drop 40 μl of CoSO4 • 7H2O, ZnSO4 • 7H2O,
Hg (NO3) 2, Cr (NO3) 3 • 9H2O and CuSO4 • 5H2O perhole at different concentration (50,100,150, 200, 250,
300, 350,400, 450,500 mg /ml).
6. Incubate at 37 °C for 24 h. Check clear zone
around the hole.

form
circularcircularcircularcircularcircularcircularcircularcircularcircularcircularcircularcircularcircularcircularcircularirregular
irregular
irregular
irregular
circularelevateraisedraisedraisedraisedraisedraisedraisedraisedconvexraisedraisedraisedconvexraisedraisedflat
flat
convexconvexraisedmarginundulate
entireundulate
undulate
entireentireentireentireundulate
undulate
undulate
entireundulate
entireundulate
undulate
entireentireentireentireTable 2 Isolate colonies color, Gram and shape.

Testing the ability to degrade heavy metals inwater

sample
HL 1
HL 2
HL 3
HL 4
HL 5
HL 6
HL 7
HL 8
HL 9
HL 10
HL 11

1. Add the highest concentration of heavy metal
solution from the plate diffusion method to 0.5%
NaCl Nutrient broth.
2. Inoculate 1 ml of 108 CFU/ml of the isolates
and incubate at 37 ° C for 15 days.
3. Examine the remaining heavy metals in thesample on days 3, 5,7,10 and 15 with Atomic
Absorption Spectrophotometer (AA).

848

color
creamycreamycreamygreyishgreyishcreamywhite
white
creamygreyishwhite

Gram
positive
positive
positive
positive
positive
positive
negative
positive
positive
positive
positive

shape
rod
rod
rod
rod
rod
rod
rod
rod
rod
rod
rod

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 (continue)
sample
HL 12
HL 13
HL 14
HL 15
HL 16
HL 17
HL 18
HL 19
HL 20

color
white
greyishcreamywhite
greyishwhite
white
greyishgreyishGram
positive
positive
positive
positive
positive
positive
positive
positive
positive

Table 4 Capability to grow in heavy metal atconcentrations 250-500 mg /ml.

shape
rod
rod
rod
rod
rod
rod
rod
rod
rod

sample
Co
Cr
Hg
Cu
Zn
HL 1
+
HL 2
+
HL 3
+
HL 4
+
HL 5
+
HL 6
+
+*
HL 7
+
HL 8
+
HL 9
+
HL 10
+
HL 11
+
HL 12
+
HL 13
+
HL 14
+
HL 15
+
HL 16
+
HL 17
+
HL 18
+
HL 19
+
+
HL 20
+
+
- = do not found clear zone
+ = found clear zone
* = found clear zone at 500 mg/ml

Resistance of Halophilic Bacteria on Heavy Metal
by Plate Diffusion Method
Result of growth performance of 20 isolates in thepresence of cobalt, chromium, mercury and zinc are
shown in the table 3. and 4.
Table 3 Capability to grow in heavy metal atconcentrations 50-250 mg /ml.
sampleCo Cr Hg
Cu
Zn
HL 1
+
HL 2
+
HL 3
+
HL 4
+
HL 5
+
HL 6
+
HL 7
+
HL 8
+
HL 9
+
HL 10
+
HL 11
+
HL 12
+
HL 13
+
HL 14
+
HL 15
+
HL 16
+
HL 17
+
HL 18
+
HL 19
+
HL 20
+
- = do not found clear zone + = found clear zone

The Ability to Degrade Heavy Metals in Water
Result of ability to degrade heavy metals in water
are shown in the table 5 and 6.
Table 5 Heavy metal residue in Nutrient broth

Sample

HL1

HL2

HL3

849

Day
3
5
7
10
15
3
5
7
10
15
3
5
7
10
3

Remaining quantity in broth
(ppm)
Zn
Co
Cr
Cu
19.73 77.69 69.51 23.92
19.72 77.67 69.36 22.78
19.75 77.63 69.54 22.08
19.73 73.76 69.42 22.93
19.73 73.71 69.21 21.88
19.59 73.95 64.95 24.74
19.57 73.06 64.41 24.46
19.56 72.95 64.12 24.42
19.55 72.90 64.08 24.21
19.53 72.51 63.92 24.14
19.45 77.29 75.84 25.45
19.44 76.91 75.61 25.15
19.43 75.86 75.42 23.72
19.43 75.63 75.11 23.36
19.41 75.21 75.10 23.23

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 5 (continue)

Sample

HL4

HL5

HL6

HL7

HL8

HL9

HL10

HL11

HL12

HL13

Day
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15

Table 5 (continue)
Remaining quantity in broth
(ppm)
Zn
Co
Cr
Cu
19.58 76.64 68.62 25.91
19.56 76.05 68.51 25.61
19.54 75.99 68.45 23.78
19.53 74.93 68.44 23.17
19.52 74.16 68.19 23.07
19.68 78.49 65.91 24.44
19.67 78.28 65.81 24.04
19.67 75.51 65.47 24.27
19.66 74.63 65.41 23.55
19.66 74.19 65.27 23.54
19.75 73.68 58.88 24.81
19.74 73.66 58.71 24.72
19.73 73.53 58.55 23.40
19.73 73.25 58.52 23.81
19.73 73.16 58.28 22.37
19.94 80.85 77.38 22.88
19.94 80.82 72.49 22.60
19.78 79.14 61.42 22.36
19.71 78.21 51.19 21.38
19.71 76.09 49.78 20.05
19.86 78.37 77.64 24.64
19.85 78.28 77.36 24.46
19.83 75.66 77.37 24.15
19.79 75.18 77.04 23.74
19.53 75.10 77.02 22.31
19.76 76.73 70.59 23.76
19.75 76.23 70.49 23.40
19.74 75.98 70.74 23.13
19.66 75.61 70.18 23.10
19.65 75.15 70.07 23.08
20.10 77.73 88.93 24.52
19.85 77.13 88.51 24.21
19.76 77.05 61.31 24.41
19.55 75.31 53.05 23.15
19.55 75.71 49.66 22.06
19.92 78.98 82.71 23.63
19.91 78.24 77.93 23.19
19.91 77.53 63.64 23.16
19.85 77.10 63.92 22.52
19.72 76.72 38.89 22.33
19.70 77.72 88.13 23.91
19.67 77.12 78.20 23.08
19.63 77.47 77.02 22.98
19.60 77.05 50.57 22.41
19.58 76.84 50.45 22.01
19.92 77.18 79.37 23.16
19.81 77.09 75.97 22.95
19.77 77.08 73.46 22.91
19.66 77.04 57.34 22.56
19.54 77.01 55.40 22.51

Sample

HL14

HL15

HL16

HL17

HL18

HL19

HL20

Day
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15
3
5
7
10
15

Remaining quantity in broth
(ppm)
Zn
Co
Cr
Cu
19.93 77.60 76.62 23.90
19.93 77.58 75.28 23.53
19.83 77.28 70.87 23.16
19.75 77.08 70.57 22.92
19.68 76.92 70.03 22.65
19.77 78.21 79.30 22.86
19.76 76.24 73.98 22.80
19.76 76.09 71.09 22.63
19.71 76.09 59.49 22.27
19.70 76.09 56.42 22.11
19.86 77.08 82.91 23.51
19.85 77.07 82.38 23.17
19.83 77.06 76.36 23.03
19.76 77.02 62.99 22.22
19.62 77.01 62.24 22.08
19.75 76.64 75.72 24.45
19.72 76.56 74.60 23.19
19.66 76.47 72.15 22.87
19.66 76.41 66.24 22.67
19.60 76.04 63.68 22.34
19.96 76.60 76.60 22.84
19.91 76.51 76.43 22.83
19.71 76.46 76.47 22.53
19.67 76.30 59.56 22.42
19.60 76.12 58.21 22.02
19.72 76.16 84.19 24.64
19.71 75.85 84.15 24.02
19.66 75.53 75.50 23.77
19.59 75.43 63.26 22.70
19.59 74.91 62.24 22.53
19.74 77.37 87.45 21.80
19.68 77.34 74.26 21.34
19.63 76.51 74.03 21.16
19.63 76.47 70.65 21.01
19.62 76.08 70.23 20.68

CONCLUSIONS
The major focus of this study is to isolate andidentify bacterial that help recovery of surroundings
from heavy metal contamination. 20 isolates of halotolerance microorganisms which could grow in
medium contain 5 heavy metals (Cu, Cr, Co, Zn andHg) were isolated from salt soil in Samut Sakorn
province. Characters of colonies were varied. All ofthem had rod shape. Only HL 7 was Gram’s negative.
All of them were tested for the highest concentrationof heavy metals that they could tolerance by Plate
diffusion method in nutrient agar. Incubated at 37 ° C
for 15 days. All of the isolates, HL1-20, could not
grow on media which had Hg. The best Co reducing
isolate was HL1, which reduced Co quantity from77.68 to 73.76 (5.05 %). Reduction of Co conducted
850

SEE - Bangkok, Thailand, Nov.11-13, 2019from the tenth day to the fifteenth day. The best Cr
reducing isolate was HL7, which reduced Cr from77.38 to 49.78 (35.66 %). The decline of Cr wascontinuous from the beginning to the last day ofexperiment (15 days). The best Co reducing isolate
was HL1, which reduced Co quantity from 77.68 to
73.76 (5.05 %). Reduction of Co conducted from thetenth day to the fifteenth day. For Zn and Cu, all theisolates (HL1-20) reduced heavy metals at thedecimal level, which was not significant.
These four heavy metals (Cu, Cr, Co, and Zn)
are used in a variety of industries. Exposure to thesesubstances causes harm to health. Getting Zn into thebody causes liver and kidney failure and may also
cause anemia. Cr causes inflammation of the skin andirritate epithelium of the internal organs. Getting Cu
into the body causes red blood cells breaking. If the
body has copper accumulated in the amount of 25-30
mg/kg of body weight, the symptoms of cirrhosis andmania may occur. Getting Co into the body can cause
allergies, asthma, difficulty breathing and also cause
skin allergy. For this reason, wastewatercontaminated with these four heavy metals needs tobe treated before released to natural water source.
Therefore, the microorganisms isolated from thisexperiment can be utilized to decrease the heavy
metal pollutant in future. However, more study on
this matter should be executed in order to reconfirm
the bioremediation activity by these bacteria, thepresence of the bacteria, as well as bacteria
identification genotype and the concentration ofheavy metal pollution in the environment.

REFERENCES[1] Marzan L.W., Hossain M., Sohana Akter , Mina
Y.A., and Chowdhury A.M. M.A., Isolation andbiochemical characterization of heavy-metal
resistant bacteria from tannery effluent in
Chittagong city, Bangladesh: Bioremediation
viewpoint. The Egyptian Journal of Aquatic
Research, Vol. 43, Issue 1, 2017, pp. 65-74.
[2] Meenambigai P., Vijayaraghavan R., Gowri R.S.,
Rajarajeswari P., and Prabhavathi P.,
Biodegradation of Heavy Metals: A Review.
International Journal of Current Microbiology
and Applied Sciences, Vol. 5. Issue 4, 2016, pp.
375-383.
[3] Ayangbenro A.S., and Babalola O.O., A New
Strategy
for
Heavy
Metal
Polluted
Environments: A Review of Microbial
Biosorbents. Int J Environ Res Public Health,Vol. 14, Issue 1, 2017, pp. 94.
[4] Chutrtong, J., Comparison of Corncob and Corn
Using as Fungal Culture Medium. Procedia Social and Behavioral Sciences, Vol. 197, 2015,
pp. 797-800.
[5] Gupta A., Joia J., Sood A., Sood R., Sidhu C.,
and Kaur G., Microbes as Potential Tool for
Remediation of Heavy Metals: A Review. J
Microb Biochem Technol, Vol.8, 2016, pp. 364372.
[6] Dixit R., and Malaviya D., Bioremediation of
Heavy Metals from Soil and Aquatic
Environment: An Overview of Principles andCriteria
ofFundamental
Processes,
Sustainability. Vol. 7, 2015, pp. 2189-2212.

ACKNOWLEDGMENTS
This work was supported by Suan Sunandha
Rajabhat University. I thank my colleagues who
provided insight and expertise that greatly assisted theresearch, although they may not agree with all of theinterpretations/conclusions of this paper.

851

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

FACTORS AFFECTING COMMUNITY PERCEPTION AROUNDBETAWI CULTURE TOURISM ACTIVITIES SETU BABAKAN
JAKARTA SELATAN

1,2

Dwinanto1 and Chotib2
Dept.of Urban Studies, School of Strategic and Global Studies, University of Indonesia, Indonesia
ABSTRACTThe purpose of this study was to analyze community perceptions of the Setu Babakan Betawi Cultural
Village in South Jakarta and find out the significance of the factors that influence it. A total of 345
questionnaires were distributed to the community sample using simple random sampling method and carried out
analysis on environmental, economic and social variables using descriptive and quantitative analysis methods.
Descriptive analysis is used to determine the frequency distribution of scores and the mean of each variableindicator item. While quantitative analysis uses Structural Equation Modeling (SEM) analysis techniques that
aim to measure the effect of the relationship between variables and indicators. Based on the results of pathanalysis from structural equation models it is known that public perception of the Setu Babakan Betawi Cultural
Village is significantly influenced by Economic Factors and Social Factors while environmental factors do notsignificantly influence people's perceptions. The research findings show that the people who live around the area
are very helpful and economically dependent on the activities of the Betawi Cultural Village. In the future it isnecessary to develop economic activities in the region so that people are more prosperous and develop existingsocial networks to improve social ties so that the goal of preserving Betawi culture in this region is sustainable.
Keywords: community perception, factors that influence perception, social, economic and environmental
variables, Betawi Cultural Village
dodol, tape uli, geplak, wajik and others. There are
two Setu in the area, namely Setu Babakan and Setu
Mangga Bolong which at first this area wasovergrown with fruiting trees such as harp, starfruit,rambutan, sapodilla, melinjo, banana, guava andjackfruit.
After fourteen years since the Jakarta
Government's establishment of the Betawi Cultural
Village, the government's perception of the Betawi
CulturalVillagehaspassed,does
theimplementation of conservation development havethe desired impact, Does the program have support
from the community with Betawi culture. The
Betawi Culture Village can only be successful andsustainable if it receives support from the local
community.
The purpose of this study is to analyze
community perceptions of the Setu Babakan Betawi
Cultural Village in South Jakarta and find out thesignificance of the factors that influence it. Thus,
this study was designed as follows. Based on theprevious researches, the section on hypotheses
proposed a series of hypotheses on the 4 types of
local community involvement in tourism activities
namely, participation in decision making, knowledge
sharing, empowerment, and community knowledge
about tourism on sustainable rural tourism
development namely, social, cultural, economic, andenvironmental sustainability. The methodology
section presents the data and the method used toanalyse empirically the hypotheses developed in

INTRODUCTION
The increasing number of people will reduce theland to support the ideal life of urban residents.
Geographical conditions in cities, for example in theform of water catchment areas, floodplains,waterfronts and so on will influence and shape theculture of the community and the environment inwhich they live. The city of Jakarta is a miniature ofIndonesia which is home to and activities of various
cultures. Castles (1967) [1] mentions Sundanese,
Javanese, Batak, Chinese, Arabic and other cultures
as one in urban life in Jakarta. Betawi culture is oneof the cultures in Jakarta that is formed from theacculturation (mixing) of various cultures that haveexisted before.
As the development of Betawi culture time will
be tested for its existence by the times. To preserve
Betawi ethnic arts and culture, the Government hasdetermined the Betawi ethnic conservation efforts by
establishing the Setu Babakan Betawi Cultural
Village in South Jakarta. The Setu Babakan Betawi
Cultural Village is the center of Betawi culture in
Jakarta which is quite complete by seeking thedevelopment of landscapes, natural and betawi
traditions such as religious (religious), Betawi
culture and arts. In the area there are typical Betawi
activities such as Pencak Silat, Aqiqah, Injek tanah,
Ngarak Penganten Circumcision, until Betawi
specialties such as Soto Betawi, Pecak Fish, Gabus
Pucung, Laksa, Boiled Toge, Egg Crust, beer pletok,
852

SEE - Bangkok, Thailand, Nov.11-13, 2019rural tourism inmake the perceptions of each individual will bedifferent from an object. The community feels theimpact of the quality of life from services andconditions in society on various aspects of life, forexample, family, social, entertainment, health,finance, culture, consumers, work, spiritual, andenvironment. This perception affects the overall
perception of society.
Some researchers have conceptualized thesatisfaction of staying as an evaluation or feeling of
being liked or disliked towards the environment
referred to in a sense of values. Therefore,satisfaction with one's residence is captured as a
combination of satisfaction with physical and social
environmental features - features such as perceived
attractiveness of the environment, evaluation ofmaintenance of housing, similarities with neighbors,and level of noise pollution. The quality of urban life
is a result of human and urban environment
interactions. The level of satisfaction with the urban
environment is one indicator of quality of life (Sirgy
and Cornwell, 2001) [5].

THEORITICAL REVIEWS
Perception
Perception is a human awareness of theconditions and the surrounding environment .
Mulyana : 168 in Sereno and Cohen, (2005) [2]states that perception is knowledge that appears
outside its surroundings that determines someone toaccept or ignore information or knowledge. The
more similarities and similarities of individual
perceptions, the more intense and easy it is tointeract and communicate. Perception is the result of
the accumulation of acceptance of the senses against
the conditions of the surrounding environment.
Effendy (1984) [3]. Acceptance of perception is
influenced by the level of knowledge and experienceof a person. The more knowledge and experience a
person has, the stronger and complete his perception
will be. In general, a person's perception can be
influenced by three factors. Siagian (1989) [4]namely, the person concerned (attitude, motivation,interests, experience and expectations); perception
goals (people, objects or events); situation(environmental conditions).
Aspects that influence perceptions according to
Mulyana are perceptions based on experience, areselective, evaluative, and contextual. The pattern of
human behavior towards the subject, object orreaction is the result of past experience and notbased on initial assumptions or guesses. In
connection with the limitations of the human mind
and mind, human interpretation and understandingof all objects or events will be selected andinfluenced by internal and external factors. Internal
factors, such as gender, religion, education level,
occupation, income level, behavior patterns,
experience, motivation, needs, expectations and soon while external factors, namely intensity, contrast
and repetition. Individual perceptions to interpret
objects based on information that are often
incomplete so that allegations are needed to makeconclusions. The perception of each person will vary.
Perception is the result of cognitive processes basedon individual experiences of attitudes, beliefs, values
and expectations of objects or events so thatperceptions are personal and subjective. Context isthe biggest influence in determining one's perception
when seeing objects or events that will affectcognitive structures and ultimately affect one's
perception.

Economic Factors
Economic factors influence perception. looks at
the proximity to work locations looks at economic
factors from accessibility. Describe the economic
aspects of the physical condition of the location thatprovides income for the population, for example
locations that have the opportunity to work,smoothen the business / business, there are people
who want to provide financial assistance, including
providing loans when needed. Pitana (2005) [6] theinfluence of tourism on surrounding communities
will lead to a relationship between local
communities and visitors that causes economictransactions. Relationships are generally unequal
because local people tend to feel tourists are more
prosperous and more educated. an explanation of thesuccess of tourist areas that are located aroundcommunity settlements, namely preserving anddeveloping the existing physical environment,
Providing economic prosperity to communities
around the area, ensuring the quality of services totourists who come, involving communities aroundtourist area and development zone.
Social Factors
In some social science literature, people's
perceptions are influenced by social factors which
are shown by the intensity of interaction withneighbors, concern when neighbors experiencedisaster and a sense of togetherness with the people

Environmental factor
A person's perception of his living environmentis influenced by the five senses, experience, values
and ways of life and psychological conditions that853

SEE - Bangkok, Thailand, Nov.11-13, 2019around them in the neighborhoo. Social values suchas cooperation, trust or reciprocal relationships
between individuals become social capital in society
in life.
Participation in decision making has a large
impact on individual attitudes, beliefs, andmotivations. The theory of participation is widely
known from Arnstein (1969) [7], which is eightlevels or degrees of community participation. The
success and sustainability of government programs
depends on the active involvement of the community.
Therefore, community participation in decision
making can be done because it will increase
productivity and profit from certain goals.
Used German Economic data to examine therelevance of environmental aspects to life
satisfaction. The study findings revealed a positive
relationship between social cohesiveness and life
satisfaction. That is, people who are closer to theirneighbors tend to report higher levels of life
satisfaction than people who are less close show that
community involvement is an important determinant
in the pride of the neighborhood [5].

No

Criteria

Total

(%)

Sum

172
173
345

50
50
100

Sum

45
141
79
50
30
345

13
41
23
14
9
100

237
108
345

69
31
100

58
41
188
58
345

17
12
54
17
100

299
46
345

87
13
100

14
81
69
122
59
345

3
24
20
36
17
100

110
7
2
40
8
10
136
32
345

32
2
1
12
2
3
39
9
100

Gender
1
Male
2
Woman
Age
1
2
3
4
5

< 30
31 – 45
46 – 55
55 – 64> 64

Ethnic1
Betawi2
Non Betawi
Sum
Education
1
Primary school
2
Junior High School
3
Senior High School
4
ScholarSum
Housing Ownership Status
1
Right of ownership
2
Rent/Contract
Sum
Neighbourhood
1
RW 5
2
RW 6
3
RW 7
4
RW 8
5
RW 9
Sum
Occupation
1
Private Employee
2
Retired3
Scholar Student
4
Entrepreneur
5
Teacher
6
Civil servant
7
Housewife
8
OthersSum

METHODOLOGY
Hipotheses
From the results of direct observations it can betaken the initial conclusion that the communities
around the Setu Babakan Betawi Cultural Village
area feel positive social, economic andenvironmental benefits so that the hypothesis of thisstudy is that social, economic and environmental
factors have a significant relationship with thesurrounding community perceptions of Settlements
Setu Babakan Betawi Culture.
This study uses a mixed quantitative andqualitative methods. Descriptive analysis uses afrequency distribution table that will be used asmaterial to obtain statements from the public on the
Setu Babakan Betawi Cultural Settlement area using
the Likert scale technique with a score of 1-5 oneach questionnaire with a value of 1 means strongly
agree; 2 means Disagree; 3 means hesitation; 4means agree; 5 means Strongly agree. The results ofthe distribution of questionnaires will be processed
and will be discussed in table form. Determinationof sample size from the population using the methodof simple random sampling randomly with the aimthat all members of the population have the same
opportunity to be chosen regardless of the strata thatexist in the population.
Table 1 Profile of Respondents by place ofresidence, Gender, Age, Population Status,
Education, Employment and Length of Stay
854

SEE - Bangkok, Thailand, Nov.11-13, 2019

No

Criteria

Total

Tabel 3 Resume Model Evaluation/Outer Model(Measurement Model)(%)

Length of Stay
1
>50 years
2
3
4

48

30-50 years
10-30 years<10 years

101
156
40
Sum
345
Occupation related to Betawi Culture
Tourism
1
Yes
97
2
No
248
Sum
345

14
29
45
12
100

Variable
Manifest

SocialNetwork(X1.1)

X1.1.1X1.1.2
X1.1.3X1.2.1X1.2.2X1.3.1X1.3.2
X2.1
X2.2
X2.3

Loading
Factors
0,879
0,799
0,904
0,800
0,890
0,750
0,733
0,854
0,860
0,744

X2.4

0,394

X2.5
X3.1
X3.2
X3.3
X3.4
X3.5
Y1
Y2
Y3
Y4
Y5
Y6
Y7
Y8
Y9
Y10

0,571
0,680
0,620
0,527
0,684
0,711
0,632
0,681
0,613
0,643
0,545
0,833
0,613
0,558
0,764
0,785

Mutual
(X1.2)
Participation(X1.3)
Environment
Factor
(X2)

28
72
100

Economic
Factor(X3)

Structural Equation Model (SEM)
Community
Perception(Y)

According to Sugiyono (2009) [8] Structural
equation model (SEM) consists of 2 elements,
namely the measurement model (outer model) andthe structural model (inner model). Where in SEM
three analysis activities were carried out at once in
one analysis, namely 1) CFA validity (Confirmatory
factor Analysis); 2) Path Analysis 3) Goodness of fit
test. Before discussing the results of SEM analysis,
it is necessary to test assumptions which in this caseinclude evaluating data normality and evaluating
outliers.
The overall suitability test of the model relates tothe analysis of GOF statistics produced by the
program, in this case AMOS 20. Using the GOF
measurement guidelines and GOF statistical results,
the overall model compatibility analysis can be
carried out as follows:
Table 2 Evaluation of Structural Model
Compatibility
Model modification)
Table Evaluation of Structural(After
Model Compatibility(After Model modification)
Goodnessof fit Index
Chi-Square/ CMINCut of value< ChiTabel : Good fit

ResultNote

469,108

Model Poor Fit

0,000

Model Poor Fit

2,076

Marginal Fit

0,056

Model Good fit> ChiTabel : Poor fit

P-valueCMIN> 0,050 : Good fit

CMIN/DF< 3,000 : Marginal Fit< 0,050 : Poor fit< 2,000 : Good Fit> 3,000 : Poor Fit< 0,080 : Good fit

RMSEA< 0,100 : Marginal Fit> 0,100 : Poor fit

GFI> 0,900 : Good fit

0,909

Model Good fit

AGFI> 0,800 : Marginal fit

0,848

Model Marginal fit

TLI< 0,800 : Poor fit

0,933

Model Good fit

0,957

Model Good fit

CFI

855

(LF > 0,5=Valid)

Rank

Validity Konvergen
Variable
Laten

value
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Tidak
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid
Valid

2
3
1
2
1
1
2
2
1
3

Validity
Diskriminant(AVE >
0,5=Valid)

Construct
Reliability (CR> 0,7)

AVE

Conclusion

CR

value

0,865

Valid

0,896 Reliabel

0,783

Valid

0,834 Reliabel

0,573

Valid

0,710 Reliabel

0,715

Valid

0,824 Reliabel

0,603

Valid

0,782 Reliabel

0,790

Valid

0,890 Reliabel

5
4
3
4
5
2
1
6
4
7
5
10
1
7
9
3
2

The measurement model is a model withcalculation results based on calculations using theAMOS 20 program. The method used is
Confirmatory Factor Analysis, where using this tool
it is known that the existing indicators can reallyexplain a construct. The purpose of the measurement
model is to describe how well the indicators in thisstudy can be used as instruments for measuring
latent variables. The main concepts used in this caseare measurement, validity and reliability. The
indicators used to reflect a variable also containerrors, so they must also be considered in statisticalanalysis.
Based on the table above, it can be seen thatmost of the Loading factor values ≥ 0.50 (Valid),
even though there are some items partially declaredinvalid (item X2.4) but still fixed can be maintained
because OverAll is good / feasible, that is with value
AVE ≥ 0.50 (Valid). Thus it can be concluded thatthe validity of all manifest variables on the latentvariable is good. While the results of reliability
calculations show that all values of constructreliability (CR) ≥ 0.70 (reliable), thus it can beconcluded that all these latent variables have good
reliability.

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 4 Evaluation Model measurement Phase 2(2nd Order Outer Model)
Var
LatentVariable
Manifest

Social(X1)

Network(X1.1)
Mutual
(X1.2)
Participation(X1.3)

Loading
Factor

Rule
of
Thum

value

Rank

0,926

0,500

Valid

1

0,880

0,500

Valid

2

0,639

0,500

Valid

3

The best aspect in forming the Social variable(X1) is Social Network (X1.1) with the highest
loading factor of 0.926. So that if the decision makerwants to increase Social Value (X1), the statistic
recommendation is to prioritize the increase in valueon the Social Network Aspect (X1.1).

Figure 1 Model Path Diagram
Structural Equation Modelling (SEM)

Structural Model

In order to facilitate the evaluation of the outermodel which is also integrated with path analysis(path analysis), the following are presented in thepath diagram of the measurement model (outermodel) and structural models (structural models)This section deals with evaluating thecoefficients or parameters that indicate a causal
relationship or the effect of one latent variable onother latent variables. A causal relationship is
declared not significant if the value of the criticalratio (C.R.) is between the range -1.96 and 1.96 witha significance level of 0.05. With the help of theAMOS 20 program application, the results of theestimation of the critical ratio of the structural modelare obtained.
Table Results
Hypothesesof Estimates

Variable
Eksogen--> Endogen

SocialCommunity-->
Factor (X1)
Perception (Y)Environment
Community-->
Factor (X2)
Perception (Y)Economic
Community-->
Factor (X3)
Perception (Y)Coefisien
Path

and

Testing

Result of
Hypotheses
pCR
value

The path diagram of the Structural equation
model can be converted in the form of equations asfollows
Y = 0,24 X1 + 0,05 X2 + 0,53 X3+ e1
From the structural equation above it can be seen
the relationship of exogenous latent constructs toendogenous latent constructs. it can be seen that the
public perception variable (Y) is more dominantly
influenced by the latent variable economic factor(X3), which is the highest influence value of 0.53.
where the indicator (manifest variable) is best in
forming the economic factor variable (X3) is X3.5
(facilities for trading / services) with the highest
loading factor of 0.711, so that if the decision makerwants to increase the value of economic factors (X3)then the recommendation statistically is prioritizing
the improvement of values on the X3.5 indicator(facilities for trading / services).

of

Score

0,237

3,249

0,001

Significan

0,054

0,912

0,362

Not
Significan

0,534

6,582

0,000

Significan

The Social Factor variable (X1) and Economic
Factor Variable (X3) have an influence (Pathcoefficient) on Community Perception (Y) Because
the CR value is in the range -1.96 and 1.96 and thep-value <0.05, the statistical hypothesis states Horejected, meaning Social Factor (X1) and Economic
Factor (X3) have a significant effect on Community
Perception (Y).
The Environmental Factor variable (X2) has an
influence (Path coefficient) on Community
Perception (Y) of 0.054 with a CR value of 0.912
and p-value of 0.362. Because the CR value isoutside the range -1.96 and 1.96 and the p-value is<0.05, the statistical hypothesis states Ho is
accepted, meaning that the Environmental Factor(X2) has no significant effect on Community
Perception (Y).

CONCLUSIONS
The validity of all manifest variables on thelatent variable is good, where the best aspect informing the Social variable (X1) is Network (X1.1)
with the highest loading factor of 0.926. So that if
the decision maker wants to increase Social Value(X1), the statistic recommendation is to prioritize theincrease in value on the Network Aspect (X1.1).
Based on the results of path analysis fromstructural equation models it is known that public
perception of the Setu Babakan Betawi Cultural
856

SEE - Bangkok, Thailand, Nov.11-13, 2019by the publications grant for thesis anddissertation of Universitas Indonesia (PITMAUI grant).

Village is significantly influenced by Economic
Factors and Social Factors while environmental
factors do not significantly influence people's
perceptions.
The research findings show that the people wholive around the area are very helpful andeconomically dependent on activities from the
Betawi Cultural Village. In the future it is necessary
to develop economic activities in the region so thatthe people are more prosperous
Community support for the development of the
Betawi Cultural Village area can be strengthened bydeveloping existing social networks to improvesocial ties so that the objectives and conservation
programs of the Betawi culture in the region can besustainable and supported by the community.
The Social Network intended for the Community
has been made by the Community in this casemarked by Life in the Community as a Family that
Maintain Public Relations Can Be Required to
Arrange Plans and Activities That Can Be Done By
the Community Alone Can Be Responded toPrograms or Assistance Coming from theGovernment For example by forming a communityof cooking experts, Betawi cultural communities orother communities for information and knowledge
within the framework of developing activities within
the region.

REFERENCES[1] Castles, Lance. 2007. Ethnic Profil Jakarta.
Masup Jakarta.
[2] Mulyana, Dedy. 2005. Introduction Science of
Comunication. Remaja Rosdakarya. Bandung[3] Efendi, Usman. 1984. Introduction of
Physcology. Bandung : Angkasa[4] Siagian, Sondang P. 1989. Theory of Motivation
and application. Bina Aksara, Jakarta[5] Sirgy, M. J., & Cornwell, T. (2001). Further
validation of the Sirgy et al.’s measure ofcommunity quality of life. Social Indikators
Research, 56 , 125–143[6] Pitana, I. Gde dan Putu G. Gayatri. 2005.
Tourism Sociology. Yogyakarta: Andi Offset.
[7] Arnstein, Sherry R., Eight Rungs on the Ladderof Citizen Participation in Edgar S. Cahn andBarry A. Passet, Citizen Participation: Affecting
Community Change, New York: Praeger
Publishers, 1971.
[8] Wijanto, Hari, Setyo. (2015). The Research
Method use Structural Equation Modeling with
Lisrel 9. Faculty of Economics. University ofIndonesia. Jakarta

ACKNOWLEDGMENTS

The authors wish to acknowledge the gratefulacknowledgment that this research is supported857

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

QUALITY OF VERMICOMPOST BY Pheretima peguana On Different
Organic Wastes
Pornpailin Boonna 1, *Nipapun Kungskulniti 1,2 , Rochana Tangkoonboribun 3, Naowarut Charoenca 1,2
1
Faculty of Public Health, Mahidol University, Thailand
2
Center of Excellence on Environmental Health and Toxicology, Thailand
3
Thailand Institute of Scientific and Technological Research, Thailand
ABSTRACTThis research studied the quality of compost using earthworms (vermicompost) developed with three different
organic wastes: water hyacinth scraps, food wastes, and corncobs as base materials. One kilogram of local Thai
earthworms, Pheretima peguana, was introduced into wastes of three different organic-based materials (either water
hyacinth scraps, food wastes, or corncobs) in the vermibin with a constant ratio of rice bran, and cow dung. Eachorganic waste was tested for a high, medium and low ratio by weight with rice bran, and cow dung. The set
materials were vermicomposted for 45 days. Physico-chemical parameters and phytotoxicity as germination index of
the compost were analyzed from vermicompost samples taken from the final day of composting. Values of pH,
electrical conductivity, moisture content, total nitrogen, total phosphorus, total potassium, total organic carbon, C/Nratio, and germination index were determined. The vermicompost from all ratios of water hyacinth scraps and foodwastes with rice bran and cow dung had acceptable nutrient levels (total nitrogen, total phosphorus, total potassium)
as specified by the Thai agricultural standard, National Bureau of Agricultural Commodity and Food Standards,
Ministry of Agriculture and Cooperative.
Keywords: Pheretima peguana, Vermicompost, Organic wastes

INTRODUCTION
farmers can reduce the use of chemical fertilizer,
which leads to environmental, and health hazards.
Earthworms, Pheretima peguana, have uniquecapabilities to disintegrate organic wastes. They
producevermicompost
withvermicast,homogeneous,odor-free,peat-likematerial
containing significant quantities of nutrients with alow level of toxicants [2]. Vermicomposting is asuitable technique due to its simplicity, costeffectiveness and can be used for all types of nontoxic biodegradable wastes. Municipal solid wastes
are mostly composed of organic wastes with thehighest ratio of around 64% for food wastes.
Composting technology has gained interest for largescale practice and disposal of a wide variety oforganic wastes; hence, vermicomposting could be auseful means of handling and treating these organic
wastes.
The aim of this study is to investigate organic
wastes such as food wastes, corncobs, and water
hyacinth scraps as a base material forvermicomposting. The quality of vermicompost
derived in this study was determined according to theThai agricultural standard, National Bureau of

The rapid increase of organic wastes in Thailand
with large volumes of water hyacinth wastes cleared
from canals generates a major disposal problem. Thishuge amount of biomass waste produces
environmental pollution. Water hyacinths are freefloating offensive aquatic macrophytes rich inorganic matter, nitrogen, phosphorus, potassium andmicronutrients. Corncobs are also an abundantorganic waste particularly after the harvest season.
However, composting corncobs takes a longer timethan leafy material like cornhusks. Vermicompostingis a suitable biological process for disposing oforganic wastes involving interactions between
earthworms and microorganisms. The role ofearthworms is to convert different types of organic
wastes into nutrient-rich manure [1]. Mutual actionof earthworms and microorganisms change thebiological, physical and chemical properties of wastematerials and convert them into vermicompost.
Research shows that use of earthworms can compost
organic wastes faster than common composting.
Physico-chemical and biological properties of soil
with ameliorated fertility are obtained from the bioprocessing before the reuse of these wastes. Hence,

858

SEE - Bangkok, Thailand, Nov.11-13, 2019

Agricultural

Commodity

and

Food

Standards,

Ministry of Agriculture and Cooperative.
MATERIALS AND METHODS
T4-T6 Food wastes
T7-T9 Corncobs
RB= Rice bran
CD= Cow dungCollection of waste material and earthworms
Food wastes were collected from themunicipal landfill at Tandeaw subdistrict, Kaengkhoi
district, Saraburi province, Thailand by the collector.
Water hyacinth scraps were collected from the local
canal. Corncobs were collected from local cornfields.
Rice bran was collected from the local rice mill. Cow
dung was collected from a dairy farm in Saraburiprovince. Earthworms, Pheretima peguana, wereobtained from a local vendor in Mae-on, Chiangmai
province using cow dung as culture medium.
Preparation of experimental media
Vermicomposting was carried out in a
cement vermibin with dimensions of 80 cm(diameter) and 40 cm (depth). Net fabric covered the
top of the vermibin to protect from any animals
entering the bin.

Figure 1. Illustration of different material layers forvermicomposting in vermibin
Physico-chemical analysis of vermicompost
Physico-chemical characteristics of thevermicompost were measured for various parameters,
including pH, electrical conductivity (EC), organiccarbon (OC), organic matter (OM), C/N ratio, total
nitrogen (TN), total potassium (K), total phosphorus(P), and Germination Index (%). About 500 grams ofeach grab sample was collected from six different
locations by hand for a representative samples for the
analysis [3]. The upper layer produced in thevermibin was analyzed for nutrient elements because
the upper layer is changed to vermicast [4]. The pH
was determined using a pH meter (AOAC973.04).
EC was determined using a Conductivity Meter, BS
EN 13038. Organic carbon was determined byorganic matter multiplied by 1.72. Organic matter
was determined by the Wet Oxidation method. The
C/N ratio was determined by organic carbon divided
by total nitrogen. Total nitrogen was measured by the
Kjeldahl method and colorimetric measurement wasdone by spectrophotometer. Potassium was detectedby colorimetric method using ammonium molybdate
in HCl. Phosphorus was determined byspectrophotometer. Germination Index (GI) wastested using mung beans mixed with distilled water at
the ratio of 1:10 (vermicompost to distilled). The
percentage germination index (GI) were calculated
according to the following formula:

Feedstock materials collection and preparation
Nine sets of treatment were studied withdifferent ratios of the three different organic basematerials (water hyacinths, food wastes andcorncobs) on layers of rice bran and cow dung in aconstant ratio as shown in Table 1. The vermibin
was arranged to do vermicomposting with six
separate layers of media with rice bran and cow dung
as illustrated in Figure 1. One kilogram of local Thai
earthworms, Pheretima peguana, were introduced ineachtreatment.
The
process
periodofvermicomposting took 45 days with moisture content
monitored periodically and maintained at 60-70% bysprinkling water manually.
Table 1. Combination of organic waste materials invermicomposting
Treatment
Materials
Total Quantity
Ratio Quantity(Kilogram)(OW:RB:CD)
T1
7:4:3
14
T2
6:4:3
13
T3
5:4:3
12
T4
7:4:3
14
T5
6:4:3
13
T6
5:4:3
12
T7
7:4:3
14
T8
6:4:3
13
T9
5:4:3
12
Note: OW = Organic wastes are Base materials forthe earthworm
T1-T3 Water hyacinth scraps

GI (%) =% 𝑠𝑒𝑒𝑑 𝑔𝑒𝑟𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑐𝑜𝑚𝑝𝑜𝑠𝑡 ×% 𝑟𝑜𝑜𝑡 𝑔𝑟𝑜𝑤𝑡ℎ 𝑜𝑓 𝑐𝑜𝑚𝑝𝑜𝑠𝑡
×100% 𝑠𝑒𝑒𝑑 𝑔𝑒𝑟𝑚𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑐𝑜𝑛𝑡𝑟𝑜𝑙 ×% 𝑟𝑜𝑜𝑡 𝑔𝑟𝑜𝑤𝑡ℎ 𝑜𝑓 𝑐𝑜𝑛𝑡𝑟𝑜𝑙

RESULTS AND DISCUSSION
Among all parameter analyze for organic
base materials in Table 2, water hyacinth scraps
859

SEE - Bangkok, Thailand, Nov.11-13, 2019contained the highest values, except for total nitrogenand total phosphorus; food waste contained higher
values of phosphorus than water hyacinth scraps andcorncobs waste. Parameter analysis results ofcompost materials (cow dung and rice bran) are
shown in Table 3, The moisture content of these twocompost materials was less than in the study ofKavita Sharma [4] and Zongqi Shoua. [5], but
potassium was of incomparable amounts in theirstudies.

process, the weight of the compost had fallen to
about half of the original amount due to the oxidation
reaction of carbon to carbon dioxide and the loss ofmoisture [7]. The moisture content of thevermicompost is shown in Table 4. During thevermicomposting process for each treatment,
moisture content was controlled to between 40 and60%. Vermicomposting requires optimum moisture
content for the microorganisms to grow and support
the movement of earthworms. When the moisture
content is too high, it will affect the organic matterdecomposition process. The moisture content of eachtreatment product was 30. 3%, 32.7% and 34.1% for
T1, T2, and T3, respectively; 28.6%, 22.0% and33.9% for T4, T5, and T6, respectively; 29.7%,
32.2% and 33.3% for T7, T8, and T9, respectively.
The moisture content values were acceptable for mosttreatments. The pH values of compost were 7.9, 7.8,
7.7, 6.7, 6.3, 6.7 7.1, 7.2, and 7.4 for T1 – T9
respectively. It can be seen that throughout thecomposting process in all treatments, pH values wereslightly alkaline. The increase in pH was caused by
the degradation of organic acids and the release ofammonia. The low-molecular-weight fatty acids andCO2 greatly contributed to the decrease in the pH of
the compost [8]. When compared with the standard,
the pH values were acceptable in all experiments.
The electrical conductivity of compost was 1.53,
2.37, 2.26, 1.56, 1.26, 1.45, 2.07, 2.54, and 1.97
mS/cm. for T1-T9, respectively. When comparedwith the standard, values of less than 10 dS/m were
acceptable in all experiments showing that thevermicompost product is suitable for use inagriculture. The organic matter values ofvermicompost were 71.98%, 67.06%, 56.89%,
65.94%, 53.46%, 41.39%, 40.36%, 36.82% and33.37% for T1- T9, respectively. When comparedwith the standard, the organic matter percentages
were acceptable in all experiments. Further, analysisof organic matter throughout the composting process
showed that the trend was in the same direction. The
organic matter of the composting process decreased,
indicating an increased degradation rate, whichcorresponds to findings in the study of Benjawan [9].
It was explained that organic carbon and organic
matter decreased throughout the compostingprocesses due to the composting process withdegradation occurring continuously. When it isstable, organic matter degradation slows which might
be due to the temperature, so that the easily
degradable organic matter is decreased. This leads toreduced microbial activity [10]. The results of C/Nratios were 30.13, 19.42, 17.90, 13.23, 10.23, 7.84,
16.25, 16.43, and 15.24 for T1-T9, respectively.
When compared with the standard, the C/N ratios
were acceptable in T2-T9 except for T1 which

Table 2. The initial physico-chemical characteristicsof organic base materials used for vermicompostingPara
X̅±SD *
meter
Water
Food
Corncobs
hyacinthwastesscraps
pH
7.70
5.80
7.30
Moisture
96.18±0. 92.74±0. 4.75±0.5
content
452
2(%)
42.75±0. 28.54±0. 19.32±0.
OC (%)33
1
34
OM (%)
73.70±0. 49.20±0. 33.31±0.
TN (%)
595
17
TP (%)
0.72±0.0 0.88±0.1 0.93±0.0
TK (%)
9
7
0
C/N ratio0.57±0.0 1.06±0.2 0.34±0.1
437
3.03±0.0 1.08±0.3 0.95±0.0
7
3
1
59.40
32.43
20.77
Note: *Mean ± Standard Deviation
Table 3. The initial physico-chemical characteristics
of compost materials used for vermicompostingPara
X̅±SD *
meter
Cow dung
Rice bran
pH
7.80
7.35
Moisture
10.91±0.02
8.93±0.80
content
45.25±0.90
28.54±0.02(%)
78.01±0.33
49.20±0.00
OC (%)
1.32±0.95
0.58±0.17
OM (%)
0.65±0.55
1.38±0.01TN(%)
2.73±0.00
0.39±0.27
TP(%)
34.27
49.20
TK (%)
C/N ratio
Note: * Mean ± Standard Deviation
Physico-chemical changes in the compostingprocess
Moisture content is a key factor for the
movement of earthworms since moisture is essential
for microorganism survival [6]. After the composting860

SEE - Bangkok, Thailand, Nov.11-13, 2019

exceeded 20. The composting period of T1 should be
more than 45 days to adjust its C/N ratio to less than
20 before being used.
Major nutrients
The major nutrients analyzed were total nitrogen,total phosphorus and total potassium as shown in
Figure 2 with values of 0.59-2.14%, 1.5%-2.93%,
1.80%-2.67%, 1.14%-3.39%, 1.04%-3.03%, 0.94%3.06%, 0.45%-1.44%, 0.39%-1.3%, and 0.33%1.27% for T1-T9, respectively. When compared withthe standard, total nitrogen and total potassium were
acceptable in all experiments. Total phosphorus was
unacceptable for T7- T9 (corncobs) since they wereless than the standard of the Thai Agricultural
Commodity and Food Standards, 2005. However, this
could be resolved by adding some manure to help
decrease the decomposition period and increase
nitrogen and phosphorus of the vermicompost.
Germination index (GI)
Germination index (GI) is the most commonly usedparameter to evaluate the phytotoxicity of the final
compost and the effect on seed germination [11]. The
germination index (GI) test results of compost at 45days is shown in Table 4. The germination index forT1-T9 was 88.50%, 85.71%, 82.95%, 95.21%,

92.71%, 89.72%, 82.50%, 81.50%, and 80.5%
respectively, which corresponds to findings in a study
by Ponsa [12] which reported that the germinationindex in all treatments met the standard.
Additionally, Tiquia and Tam [13] reported that thegermination index values in their study were morethan 80%, phytotoxic-free and were considered tohave complete maturity. Therefore, the germinationindex in this study similarly showed nonphytotoxicity to plant growth.
4
3
TN(%)
2

TP(%)

1

TK(%)

0
T1 T2 T3 T4 T5 T6 T7 T8 T9Figure 2. Results of major
vermicomposting for 45 days.

nutrients

after

Table 4. Parameters of vermicompost products compared with the Thai Agricultural Commodity and FoodStandards, 2005
Treatments
Parameters
T1
T2
T3
T4
T5
T6
T7
T8
T9
Moisture34.
28.6±0.4 22.0±0.2 33.9±0.3 29.7±0.0 32.2±0. 33.2±0.5
30.3±0.9 32.7±0.1
content (%)
01±0.33
5
1
0
0
03
5
0
pH
7.9
7.6
7.3
6.7
6.3
6.7
7.1
7.2
7.4
EC (ds/m)
Organic
carbon (%)
Organic
matter (%)
C/N ratio
TN (%)TP (%)TK (%)
Germinationindex (%)

Std.*
≤ 30
5.58.5≤ 10

1.53±0.192.37±0.062.26±0.081.56±1.081.26±0.321.45±0.942.07±1.082.54±2.
08

1.97±0.5
841.75±0.
7038.90±1.
0433.01±1.
2538.25±1.
2531.01±1.
4324.01±2.
2523.41±0.
9521.36±1.719.36±1.
75-71.98±1.
2030.25±0.
97
1.38±0.050.59±0.082.14±0.8867.06±1.
7919.45±0.
18
2.0±0.88

65.94±0.
313.23±1.
95
2.89±0.003.39±1.261.14±1.5
8

53.46±1.
3310.23±2.
113.03±0.952.45±1.501.04±0.3
841.39±1.
05
7.84±1.3
2
3.06±0.002.31±1.850.94±1.9
740.36±1.
0516.25±0.
97
1.44±0.710.45±1.060.54±0.1
136.82±1.616.43±1.6
1.3±0.02
0.39±1.
080.52±1.
48

33.37±0.
0515.24±0.
55
1.27±0.010.33±0.550.49±0.52≥201.50±0.051.69±0.8856.89±2.
1517.90±0.
32
1.84±0.142.67±0.061.80±0.9
488.50±1.
9485.71±0.
5482.95±1.
3095.21±0.
992.71±1.
789.72±1.
182.50±1.
4581.50±0.080.50±2.
06

861

≤
20:1
≥1.0
≥0.5
≥0.5
≥80

SEE - Bangkok, Thailand, Nov.11-13, 2019

Note: * from Thai agricultural standard, National
Bureau of Agricultural Commodity and FoodStandards, Ministry of Agriculture and Cooperative,
2005.
[5]Kavita Sharmaa, V.K. Garga. Comparative
analysis of vermicompost quality produced fromrice straw and paper waste employing earthworm
Eisenia fetida (Sav.).Journal of Bioresource
Technology 2018; 250:708-715.
[6] Norliyana Sailila r. AziziAbu Bakar. Noor Zalina
Mahmood. Jaime A. Teixeira da Silva.
NoorlidahAbdullahr.AdiAinurzaman Jamaludint.
Nutrient Elements of Different Agricultural
Wastes from Vermicomposting
Activity.
Globalscience Books 2010[7]Singh J, Kalamdhad AS. Assessment ofbioavailability and leachability of heavy metals
during rotary drum composting of green waste(waterhyacinth).Journalof Ecological Engineering
2013; 52:59– 69.
[8]FAO. Soil management: compost production anduse in tropical and subtropical environment. FAO
Soils Bulletin 56. Food and Agriculture
Organization of the United Nations, Rome;
1987.p.177.
[9] Benjawan L, Kaewsuwan U, Kungskulniti N,
Sihawong S, Chayaprasert W. Development of
aerobic organic wastes composter prototypes with
automatic mixing for household and community
users. National Research Council of Thailand,
Thailand; 2012.
[10]Liu W, Huo R, Xu J, Liang S, Li J, Zhao T, et al.
Effects of biochar on nitrogen transformation andheavy metal in sludge composting. Journal of
B io r e so u r ce T e c hno lo g y2 0 1 7 ; 2 3 5 : 4 3 - 4 9 .
[11] Chan MT, Selvam A, Wong JWC. Reducing
nitrogen loss and salinity during struvite foodwaste composting by zeolite amendment. Journalof Bioresource Technology 2016; 200:838-844.
[12] Ponsa S, Pagans E, Sanchez A. Composting of
dewatered wastewater sludge with various ratiosof pruning waste used as a bulking agent andmonitored by respirometer. Journal of Biosystems
Engineering 2009; 102:433-443.
[13] Tiquia SM, Tam NFY, Hodgkis I J. Effect ofcomposting on phytotoxicity of spent pig-manure
sawdust Litter. Journal of Environmental
Pollution 1996;93:249-256.

CONCLUSION
The vermicompost from all ratios of water
hyacinth scraps and food wastes with rice bran andcow dung had acceptable nutrient levels (total
nitrogen, total phosphorus, total potassium) as
specified by the Thai agricultural standard, National
Bureau of Agricultural Commodity and FoodStandards, Ministry of Agriculture and Cooperative.
The color of vermicompost products by pheretima
peaguana earthworms was brown or black color andhad no odor.
Corncob materials can be employed forvermicomposting but will take a longer time thanwith water hyacinths and food wastes. Therefore,
corncobs is not considered suitable for composting.
The final vermicompost products in this study weresoft with rich nutrients. Besides, the organic materials
werecompletelydegraded.Moreover,vermicomposting can help reduce the volume oforganic wastes while reducing disposal costs andvisual pollution.
ACKNOWLEDGMENTS
The success of this thesis was possible
through the kind support of my advisors. Research
work is financially supported by the Thailand
Institute of Scientific and Technological Researchand Mahidol University.
REFERENCES[1]Amouei,Yousefi and Khosrav.Comparison ofvermicompost characteristics produced fromsewage sludge of wood and paper industry andhousehold solid wastes. Journal of Environmental
Health Science and Engineering 2017;15(1)[2] Ndegwa and Thompson . Integrating composting
ad vermicomposting in the treatment andbioconversion of biosolids. Journalof Bioresource
Technology 2011; 76(2):107-12[3] Kasamsuk K. Assessment of school composters
with different power source of mixing.
Department of sanitary engineering, Faculty of
Public Health,Mahidol university; 2013.
[4] Liu N, Zhou J, Han L, Ma S, Sun X, Huang G.
Role and multi-scale characterization of bamboo
biocharduringpoultry manure
aerobic
composting. Journal of Bioresource Technology
2017; 241:190-199.

862

5thInt. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EVALUATION OF METHANE AND CARBON DIOXIDE EMISSIONSFROM LIVESTOCK WASTE, COMPOST, AND BIOGAS SLUDGE
Ambar Pertiwiningrum1, Margaretha Arnita Wuri2, Dina Setiyana3, Benito Heru Purwanto4, Andang Widi
Harto5 and Misri Gozan6
1,3Faculty of Animal Science, Universitas Gadjah Mada, Indonesia; 1,2,5Center for Development of
Sustainable Region (CDSR), 2Center of Energy Studies, Universitas Gadjah Mada; 4Faculty of Agriculture,
Universitas Gadjah Mada, 5Faculty of Engineering, Universitas Gadjah Mada, Indonesia; 6Faculty ofEngineering, Universitas Indonesia, Indonesia

ABSTRACT
Livestock sector contributes to greenhouse gases (GHGs) emission especially methane and carbon dioxidegases that produced from digestive system and manure of ruminants. GHGs mitigation was conducted by cattle
manure waste management through biogas and compost technologies. In this study we evaluated methane andcarbon dioxide emissions from untreated and treated cattle manure in cattle farm group of Ngudi Mulyo,
Yogyakarta. Test equipment that used in this study is 25-liters chamber to isolate gas emissions from naturally
digested untreated and treated cattle manure for eight weeks. Gas samples were analyzed by gas chromatography(GC). The results shows that buried cattle manure produced the highest methane emission of 173100 ppm while
compost from cattle manure produced of 2963.33 ppm. There is the decrease in methane emission of compostand sludge biogas from cattle manure of 98.18 and 98.10% respectively compared to fresh cattle manure. The
highest carbon dioxide emission was produced by fresh cattle manure of 580215.371 ppm. Conversion of cattle
manure to biogas sludge and compost could reduce carbon dioxide emission of 80.85 and 86.23% respectively
compared to fresh cattle manure. We concluded that cattle manure waste management by biogas and compost
technologies are important role in GHGs mitigation especially in livestock sector.
Keywords:Cattle manure, Methane, Carbon dioxide, Biogas, Compost

But unfortunately, manure from cattle livestock isjust being stockpiled in these cages. And theconsequence the accumulation of cattle manure
enhances GHGs emission. The high level ofemissions opens up large opportunities for climatechange mitigation through livestock action.
Mitigation strategic to reduce GHGs emissionthat generated from livestock manure is utilizing
cattle manure as substitute of fossil fuel energies
through biogas technology. Cattle manure is themost typical forms of waste that used in as source of
biogas production because its composition consistsof carbohydrates, proteins, fats, cellulose, andhemicelluloses [4]. Cattle manure is suitable to beconverted to biogas and compost because of its highorganic content. Methane that produced from cattle
manure by biogas technology through threepathways are hydrolysis, acidification andmethanogenesis [5]. Hydrolysis pathway is whencomplex organic content in cattle manure to beconverted to monomers or simple organic
compounds while acidification is when organic
monomers to be converted to organic acids. Last
step, methanogenesis pathway, organic acids will be
converted to methane by anaerobic bacteria.
Livestock waste management by utilizing cattle
manure to produced biogas and compost will reduce

INTRODUCTION
Global warming is due to the increase ingreenhouse gases (GHGs) like carbon dioxide (CO2),methane (CH4), chloro-fluoro-carbon (CFC), hydrofluoro-carbon (HFC), nitrous oxide (NOx), andsulfur hexafluoride (SF6). All of these gases, carbon
dioxide and methane are the most abundant GHGs in
the atmospheric. In addition, methane has 21 times
higher global warming potential. One of sectors thatgenerate methane and carbon dioxide emissions is
livestock sector. In United Nations’ books,
Livestock Long Shadow in 2016 reported thatlivestock activities generate 18% from total GHGs
emission [1]. Pete et al. [2] were also reported that
agriculture sector included livestock sector
contributes 10-12% of total anthropogenic emissionsof GHGs. CH4 contributes approximately 50% of
total emissions. It means livestock have a substantial
impact on climate change. Emissions of methaneand carbon dioxide were produced from digestivesystem of ruminants and livestock waste. Based on
Livestock and Animal Health Directorate [3], inIndonesia number of cattle population undergone theincrease from year 2013 until 2017. A dramatic
expansion livestock sector has been driven by
population growth and rising income in Indonesia.
863

SEE - Bangkok, Thailand, Nov.11-13, 2019

methane emission [6]-[8]. Biogas is a clean, efficient,and renewable energy that substitutes coal energy[9].
Evaluation of methane and carbon dioxide is rarestudied so in this study we evaluated methane andcarbon dioxide emission from untreated cattle
manure and treated cattle manure that taken fromfarmer group in Yogyakarta.

turned out to make homogenized gas when gas
sampling was taken by a syringe.
Methane and carbon dioxide concentration in gas
samples were analyzed by gas chromatography (GC).
Methane or carbon dioxide concentration was used
to calculate methane or carbon dioxide flux withformula in Eq. (1) [5].
𝑚𝑔
2

𝑑𝑐

𝑉𝑐ℎ

𝑚𝑊

273,2

𝑚
𝐸 ( 𝑚𝑖𝑛𝑢𝑡𝑒) = 𝑑𝑡 𝑥 𝐴𝑐ℎ 𝑥 𝑚𝑉 𝑥 273,2+𝑇 (1)METHODOLOGY
Equation (1) is formula to calculate methane orcarbon dioxide emission per unit of area and time𝑑𝑐(E). 𝑑𝑡 refers to difference concentration of methaneor carbon dioxide per unit time (ppm). 𝑉𝑐ℎ isvolume of chamber (m3) while 𝐴𝑐ℎ is area of top
chamber (m2). 𝑚𝑊is the molecular weight of gas,
𝑚𝑉 is the volume of gas molecule (22.4 liters), andT is average temperature in gas sampling (oC). We
conducted T-test to analyzed methane and carbon
dioxide emission in ppm.

Materials
Cattle manure that used in this study was takenfrom cattle farmer group of Ngudi Mulyo in
Yogyakarta. In this study, we evaluated methane andcarbon dioxide emissions from untreated and treatedcattle manure. Sample of untreated cattle manure
were taken from fresh cattle manure and 3 months
buried cattle manure. Sample of treated cattle
manure were taken from compost which processed
for five weeks and biogas sludge which digested for
one week.
The test equipment that used to calculate
methane and carbon dioxide emissions is 25-literchambers equipped with fan and thermometer. Eachchamber is also equipped with a rubber cap above its
surface to take gas sample. The design of chamber
can be seen in Fig. 1.

RESULTS AND DISCUSSION
Methane and Carbon Dioxide Emissions
In this study, methane and carbon dioxide are
GHGs emission that generate from untreated andtreated cattle manure. Tubiello [10] reported thatmethane and carbon dioxide emission are produced
from cattle’s digestive system and manure. Cattle
have a special digestive system which there ismethanogenics bacteria in their rumen that convert
organic matter to be methane and carbon dioxidegases and carried out together with their manure. To
reduce methane and carbon dioxide emissions, cattle
manure waste could be managed by biogas andcompost technology [6]-[8]. We have evaluated andcompared GHGs emission from untreated andtreated cattle manure. In this study we reported thatmanagement of cattle manure by biogas andcompost can reduce GHGs emission. Methane andcarbon dioxide total emissions of cattle manure
showed in Table 1 and Table 2 respectively.

Fig. 1 The design of chamber (A. chamber withheight of 38 cm and diameter of 26,5 cm, B.
untreated/treated cattle manure, C. thermometer, D.
fan, E. rubber cap).

Table 1 Total emissions of methane from cattle
manureMethane and Carbon Dioxide Data Collection
Each of fresh cattle manure, buried cattle manure,compost, and biogas sludge was put in a 25-literchamber. Each sample was naturally digested for 8
weeks. Gas that produced from this chamber was
analyzed to calculate of methane and carbon dioxide
emissions. Gas samplings were carried out in every
week for 8 weeks. The time interval for each gas
sampling per week are 10 minutes, 20 minutes, and30 minutes respectively. In addition, the fan must be

SampleFreshmanureBuriedmanureSludgebiogas864

CH4 emission (ppm)
Total CH4
Average of CH4
162797.10

32559.4±107a173101.00

34620.2±981a

3070.55

614.1±981a

SEE - Bangkok, Thailand, Nov.11-13, 2019

2933.89586.78±43,0b
CompostNote: a, b different superscripts at the same column
indicates significant differences (P<0,05).

compost were able to reduce carbon dioxide of 80.85
and 86.23% respectively. Many cattle farmers inIndonesia are not capable to manage organic waste
to biogas or compost. Some of them still maintainwaste management by piling up cattle manure in
specific place. So, biogas and compost technologies
are recommended as alternative mitigation action in
reducing GHGs emission.

Table 2 Total emissions of carbon dioxide fromcattle manure

Methane or Carbon Dioxide Flux

SampleMethane or carbon dioxide flux are thedifferences of methane or carbon dioxide
concentration that produced in certain time and area
units. In this study, we also investigated methane
emissions from untreated and treated cattle manure.
Figure 2 is methane flux from fresh and buried cattle
manure, biogas sludge, and compost.

CO2 emission (ppm)
Total CH4
Average of CH4

Fresh
580215.371
116043.8±197a
manureBuried535458.552
107091.6±844a
manureSludge3070.55
614.11±51,0b
biogas2933.89586.78±43,0b
CompostNote: a, b different superscripts at the same column
indicates significant differences (P<0,05).

methane flux
(mg/m2/minute)

1200

In this study, fresh and buried cattle manure are
not significantly different in producing high methane
emissions. When cattle manure was buried, it will
make the condition increasingly anaerobic, a goodcondition to generate more methane gases [11]. But
based on the data on Table 1, methane gas emissions
from fresh cattle manure is higher significantly
compared to cattle manure that converted to besludge of biogas and compost. In compost
production, the surface material was incorporated
into the pile while material at the bottom so thechance of CH4 production by anaerobic condition
were minimal [12]. The turning of compost resulted
in more uniform and smaller-sized aggregates makessome anaerobic microsites could have not developed
inside in the pile [13]. Amanda [9] explained thatbiogas sludge is product of anaerobic degradationthat has lower methane gases emission because it
was utilized as resource of renewable energy.
Methane is flammable gas that converted to energy
for cooking or electricity. Utilization of cattle
manure to biogas and compost was proven to be able
to reduce methane emission of 98.11 and 98.18%
respectively. The same phenomenon also occurred incarbon dioxide emission. Utilization cattle manure tobiogas and compost reduced carbon dioxide
emission significantly. The significant reducing ofcarbon dioxide in biogas because anaerobic
condition makes carbon dioxide production can be
minimized. Anaerobic condition would prefer toconvert carbon content in cattle manure to methanegases compared to carbon dioxide. In this study,
buried cattle manure reduced 7.71% of carbon
dioxide while cattle manure treatment by biogas andburied manure
fresh manurecompostsludge

1000
800
600
400
200
0
0

5

10

week
Fig. 2 Methane flux of fresh cattle manure (A),buried cattle manure (B), biogas sludge (C), andcompost (D)Methane flux of fresh cattle manure at the firstweek was 183.21 mg/m2/minute, at the second week
was 354.97 mg/m2/minute, at the third week was
608.57 mg/m2/minute, at the sixth week was 1027
mg/m2/minute, and at the eighth week was 173.06
mg/m2/minute. There was the increase in methane
flux by increasing time of observation. The same
trend showed by buried cattle manure. Methane fluxof buried cattle manure were 435.19, 324.96, 388.15,
1022.78, 310.53 mg/m2/minute at the first, second,
fourth, sixth, and eighth week of observation. At
first day to 30 days naturally methanogenic bacteria
started to convert organic matter in fresh and buried
cattle manure to methane gases [14]. In this study, atthe last week of observation, production of methanegases was limited because the methane production
was optimal until sixth week. At the sixth week,methanogenic bacteria have already multiplied to
produce the highest methane gases. After that,methane production would decrease day by day.
This phenomenon also was reported by Lise [14]and Puspitasari [15]. Methane flux of cattle manure
increased from the first until sixth week and after
that, at the eighth week it would decrease.
Lower methane flux was showed by treated865

SEE - Bangkok, Thailand, Nov.11-13, 2019

CO2 flux (mg/m2/minute)cattle manure, biogas sludge and compost. Methane
flux of biogas sludge were 7.66, 72.23, 8.14, 7.01,
and 10.29 mg/m2/minute at the first, second, fourth,
sixth, and eighth week of observation. Whilemethane flux of biogas sludge were 2.68, 73.09,
2.64, 69.32, and 75.80 mg/m2/minute at the first,
second, fourth, sixth, and eighth week ofobservation. Methane flux on biogas sludge andcompost were relatively stable in the eighth week. Itmeans carbon conversion of cattle manure to biogas
and compost have ended.

emission at 98.11 and 98.18% respectively whilecarbon dioxide emission at 80.85 and 86.23%
respectively. Biogas and compost technologies wereproven and recommended to be one of actions in
GHGs mitigation especially in livestock sector.
ACKNOWLEDGMENTS
The research was supported by Grant Programfrom Universitas Gadjah Mada, Indonesia through
PTUPT program. We gratefully acknowledge thesupport from USAID through the SHERA program –Centre for Development of Sustainable Region(CDSR). In year 2017-2021 CDSR is led by Center
for Energy Studies - UGM. Authors also would liketo thank for students of Faculty of Animal Sciencethat contributed in collecting the data.

6000
buried manure
fresh manurecompostsludge

5000
4000
3000
2000
1000
0

REFERENCES
0

5

10

[1] Food and Agriculture Organization (FAO),
Livestock’s Long Shadow, FAO, 2011,
http://www.fao.org/3/a-a0701e.pdf.
[2] Pete S., Daniel M., Zucong C., Daniel G., Henry
J., Pushpam K., Bruce M., Frank O., Charles R.,
Bob S., and Oleg S., 2007, Agriculture, Climate
Change 2007, Mitigation Contribution ofWorking Group III to the Fourth Assessment
Report Intergovernmental Panel on Climate
Change, 2007, pp.498-540.
[3] Livestock and Animal Health Directorate,
Ministry of Agriculture, 2017, pp. 83.
[4] Spyridon A., Vasileios A., and Gerrit J.W.E., A
Technological Overview of Biogas Production
from Biowaste, Engineering, Vol.3., 2017,
pp.299-307.
[5] Peter J.J., Biogas – Green Energy, Faculty ofAgriculture Sciences, Aarhus University, 2009,
pp.1-35.
[6] H. Pathak, N. Jain, A. Bhatia, S. Mohanty, andNavindu G., Global Warming Mitigation
Potential of Biogas Plants in India, Environ.
Monit. Assess., Vol.157, Issue 1-4, 2009,
pp.407-418.
[7] Leila K., Ngudiantoro, M. Faizal, and P.K.S.
Halim., Evaluation of CO2 and CH4 Emission at
Peat Swamp Forest Under Different Land Cover,in Proc. 3rd International Conference on
Chemical, Ecology and Environmental Science,
2013, pp. 185-189.
[8] Amanda D.C. and Michael E.W., Cow Power:
The Energy and Emissions Benefits ofConverting Manure to Biogas, Environ. Res.
Lett., Vol. 3, 2018, pp.1-8.
[9] Liu Y., Kuang Y., Huang N., Wu Z., and Xu L.,
Popularizing Household-Scale Biogas Digester
for Rural Sustainable Energy Development andGreenhouse Gas Mitigation, Renewable Energy,

week
Fig. 3 Carbon dioxide flux of fresh cattle manure(A), buried cattle manure (B), biogas sludge (C), andcompost (D)Beside generating methane, carbon dioxide wasalso generated after one week observation. In thisstudy carbon dioxide flux decreased with theincreasing time. Figure 3 showed that carbon
dioxide flux of fresh manure were 1007.36, 4824.73,
700.89, 178.01, and 254.69 at the first, second,
fourth, sixth, and eighth week respectively. The
highest carbon dioxide flux of fresh cattle manure
was occurred at the second week because fresh cattle
manure contained high organic matter that used by
microorganism to produced carbon dioxide. The
decreasing of carbon dioxide flux of biogas sludge
and compost were not significant for eight weeks
observation. Carbon dioxide flux of biogas sludge
were 282.14, 230.56, 11.07, and 5.97 mg/m2/minuteat the first, second, fourth, sixth, and eighth week
respectively while carbon dioxide flux of compost
were 226.11, 101.85, 60.15, 12.51, and 5.98
mg/m2/minute at the first, second, fourth, sixth, andeighth week respectively. These carbon dioxide flux
were relatively stable and lower compared to freshand buried cattle manure because cattle manure havedecomposed and converted to energy and others
material content. Decomposition and stabilization of
cattle manure by biogas and compost technology
would emit GHGs emission [6]-[8],[16].
CONCLUSIONS
Based on this study, we concluded thatconversion of cattle manure by biogas and compost
technologies were able to decrease in methane
866

SEE - Bangkok, Thailand, Nov.11-13, 2019Vol.33, 2008, pp.2027-2035.
[10] F.N. Tubiello, M. Salvatore, R.D. Condor Golec,
A. Ferrara, S. Rossi, R. Biancalani, S. Federici,
H. Jacobs, and A. Falmmini, Agriculture,
Forestry and Other Land Use Emissions by
Sources and Removals by Sinks, FAO (Food andAgriculture Organization, 2014, pp.1-75.
[11] Ari M.I., Effect of Maturity of Waste on
Methane Gas Production in Putri Cempo
Mojosongo
Landfill,
PostgraduateofEnvironment Science of Sebelas Maret
University, 2007, pp.1-52.
[12] G.Singh, O.G. Clark, and J. Leonard,
Comparison of GHG emissions from A Compost
Pile and Manure Stockpile, in Proc. The
Canadian Society for Engineering in Agricultural,
Food, and Biological Systems, Vol.05, 2005.
[13] Y.Fukumoto, T. Osada, D. Hanajima, andK.Haga, Patterns and Quantities of Ammonia

Nitrous Oxide and Methane Emissions during
Swine Manure Composting with Forced
Aeration-Effect of Compost Pile Scale, Biores.
Technol., Vol.89, 2003, pp.109-114.
[14] Lise A., Jan B., Jan D., and Raf D., Principles
and Potential of The Anaerobic Digestion ofWaste-Activated Sludge, Prog. In Energy andComb. Sci., Vol.34, Issue 6, 2008, pp.755-781.
[15] R. Puspitasari, Muladno, A. Atabany, andSalundik, Methane Gas Production from
Lactating Dairy Cow Feces by Feeding with
Elephant Grass and Rice Straw, Jurnal Ilmu
Produksi dan Tek. Hasil Peternakan, Vol.3, No.1,
2015, pp.42-44.
[16] Xiying H., Chi C., Francis J.L., and Greg R.T.,
Greenhouse Gas Emissions during Cattle Manure
Composting, J. Environ. Qual., Vol.30, 2011,
pp.376-386.

867

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STUDY ON ELUTION REDUCTION OF HEXAVALENT CHROMIUMFROM RECYCLED BASE COURSE MATERIALUSING WASTE SYRUP
Keiichiro Shibata1, Hidenori Yoshida2, Hiroki Yokoyama3, Shinichiro Okazaki4 and Matsumoto Naomichi5
1
Graduate school of engineering, Kagawa university, 2, 3, 4 Faculty of engineering and design, Kagawa
university, Japan; 5 Technical staff, Kagawa university, Japan

ABSTRACTIn the civil engineering field, the utilization of recycled materials is promoted so as to reduce environmental
burden. In particular, the utilization of concrete accessory product generated by the dismantlement of the concrete
construct is an urgent issue in the light of both environment conservation and the shortage of repository site. Most
concrete accessory products are recycled as the recycled base course material. However, it is at risk of the elutionof the trace of hexavalent chromium from the recycled base course material. A major countermeasure to thisproblem is the reduction treatment to harmless trivalent chromium by reducing substances. There are manydifferent types of the reducing substances. Among them, low cost is required for the reduction material because
the recycled base course material is inexpensive. Therefore, in this study, waste sugar syrup is focused on withattention to two points such as reducibility and low cost. The elution test for the hexavalent chromium in cement
paste is conducted, and the reducibility of the sugar contained in the waste syrup is verified. As a result of the
reduction test using the waste syrup, it becomes clear that the eluted hexavalent chromium concentration decreases
below the effluent standard.
Keywords: Waste syrup, Hexavalent Chromium, Recycled base course material, Reducing property

a harmful substance in the environmental standard by
the Ministry of Environment. On the other hand, it iseasily reduced to harmless trivalent chromium.
Therefore, hexavalent chromium is often detoxified
by reduction treatment using a reducing substance.
Though the kinds of reducing substances are various,
the low cost is also required for reducing substances
due to the cheapness of the recycled roadbed material.
Thus, in this study, the discarded sugar syrup is
focused on with considering two points, i.e., reducing
characteristics and low cost.
There is a past research which verified the
reduction of Cr6 + elution from regenerated roadbed
material by reducing sugar as in [7]. Concretely
speaking, the fruit juice and six kinds of sugar
solution including reducing sugar are sprayed or
immersed in crushed concrete material. The reduction
sugar and the fruit juice containing it are confirmed
to have the effect of reducing the elution for Cr6+.
Among them, fructose and glucose have highreducing ability for Cr6+. In this study, two test
methods are devised to verify the reduction of Cr 6+
elution from the roadbed material is examined with aview to verification of the reduction of Cr 6+ elution
from cement-improved soil in near future. One is amethod to immerse crushed concrete in sugar solution
as in the past research, and the other is a method tomix sugar solution as admixture in mixing concrete.
An availability of the waste syrup on the elution of
the Cr6+ is examined by each different approach.

INTRODUCTION
The utilization of recycled materials for the
purpose of environmental loading reduction is
promoted in the civil engineering field in Japan whichshifts from the mass production, mass consumption
and mass disposal society to the recycling society.
Especially, the utilization of concrete by-products
generated from the demolition of concrete structures
is promoted from the viewpoint of environmental
conservation and tightening of disposal sites, andmost of them are recycled as in [1]. The transition of
the recycling rate of concrete by-products is shown in
Fig. 1 as in [2]. More than 99 % of the by-products
are recycled, and most of them are recycled as
roadbed material. The utilization of recycled roadbed
material is expected to be promoted in future from theviewpoint of reduction of environmental load byrecycling and low material cost. However, trace ofhexavalent chromium (Cr6+) contained in the cement
may be detected from the recycled roadbed material
as in [3], [4]. It is recommended to confirm the degreeof the elution in the case of using recycled roadbed
material. In addition, Cr6+ may elute from not only
recycled roadbed materials but also cementitious
solidification materials used for cement-improved
soil, when the soil in which the significant inhibitionof hydrate formation is occurred such as a volcanic
cohesive soil is improved as in [5], [6]. Hexavalentchromium has very strong toxicity, and is specified as
868

SEE - Bangkok, Thailand, Nov.11-13, 2019100%

Recycling rate (%)

method of recycled roadbed material. According to
the past research, the elution amount of Cr6+ increases
as the grain size decreases. Therefore, it is consideredthat the possibility of Cr6+ elution increases by the
mixture of crushed concrete with extremely small
grain size. Furthermore, the using site of recycled
roadbed material is mainly the topper roadbed or the
lower roadbed (see Fig. 2), and the runoff of Cr6+ tosoil may occur because the recycled roadbed material
is in contact with soil. Thus, the elution
countermeasure of Cr6+ before the usage as recycled
roadbed material is very important from a safety pointof view.

99.3%
96.2% 97.6% 98.1% 97.3%

90%

Concrete…

80%
70% 64.6%
60%
50%

1995 2000 2002 2005 2008 2012

WASTE SYRUP AND REDUCING ABILITYOF SUGAR

Fig. 1 Transition of recycling rate of concrete byproducts

Waste syrup is selected as a reducing agent for
Cr6+ in view of low material costs, reducing ability
and waste recycling. The syrup contains several kindsof sugars such as allose, glucose and fructose, and theexpired syrup is used in the test. Sugars are divided
into reducing and non-reducing sugars. The
difference between reducing and non-reducing sugars
is the existence or non-existence of reducing group,
and it is known that the sugar with aldehyde group in
the structure shows reducing property as in [9]. For
example, glucose has the structure shown in Fig. 3, in
which the aldehyde moiety shows reducing property.
On the other hand, the sucrose which is a disaccharide
does not show reducing property because the glucose
and fructose which belong to the reducing group link
together. In the test, the glucose, allose and sucrose
are prepared as the reducing agents in addition to thewaste syrup in order to confirm the usefulness of thewaste syrup and to clarify each reducibility.

ELUTION MECHANISM OF HEXAVALENTCHROMIUM
In nature, chromium exists in a trivalent state aswell as in cement raw materials. Trivalent chromium(Cr3+) in the raw material is partly changed to Cr6+ inthe cement manufacturing process. Previous studies
have shown that Cr6+ is not only adherent to cement
minerals but also present as water-soluble Cr6+ as in[8]. Water soluble Cr6+ in the cement is dissolved in
the liquid phase during the elution process of thehydration reaction and is fixed to the precipitatedhydrate. Therefore, the concentration of Cr6+ in theliquid phase decreases as the hydrate is formed.
As has described above, the cement contains Cr6+,
and Cr6+ is eluted with the hydration reaction. On theother hand, when concrete is crushed and used as arecycled roadbed material, Cr6+ may be eluted fromthe recycled roadbed material due to its use under theenvironment in contact with rain, groundwater, etc.,
and due to the influence of the particle size of thematerial. Alternatively, advanced processing such as
crushing, grinding and classification is not conductedbecause there is no regulation in the processing

Fig. 3 Examples of reducing sugars and nonreducing sugars
TEST METHOD
As has already mentioned above, two kinds oftests are conducted to evaluate the reducibility ofsugars to Cr6+. One is a method to mix sugar in

Fig. 2 Materials used for roadbed material
869

SEE - Bangkok, Thailand, Nov.11-13, 2019

method is shown in the figure. The Cr6+ is reduced bymixing in advance before cement is set. The
advantage of this method is that there is not necessary
to treat for sample after construction.

cement before solidification, and the other is amethod to immerse sample after solidification andgrinding in sugar aqueous solution. The former iscalled the mixing method and the latter is called the
reduction test by the immersion method. Each test is
conducted by reference to the elution test which isnoticed by the Ministry of Environment Notification
No. 46 as in [10], and three times of each test are
conducted under the same conditions to ensure
reproducibility.

Immersion method
The purpose of the immersion test is to reduce
Cr6+ by immersing the crushed sample in a sugar
solution. Though the test procedure is almost thesame as that described in 4-1, the sugar is not mixed.
Four kinds (waste syrup, glucose, allose, and sucrose)of sugar aqueous solution are respectively adjusted atthree kinds of concentrations, and the crushed sample
is immersed in the sugar solution for 24 hours. There
are 12 patterns of specimens. Test conditions in theimmersion method are shown in Table 2. Also, themixture method is shown in Fig. 5. The operation
added to the immersion method is shown in the figure.
Most of Cr6+ remains in the concrete by hydration of
cement. However, immersion in sugar solution may
reduce Cr6+ which is slightly eluted from the concrete.
Table 2 Test condition (Immersion method)

Mixture method
The purpose of this method is to reduce the elution
amount of Cr6+ by mixing the sugar which has the
reducibility as an admixture. Cement paste of 70 %water-cement ratio is produced, and the mold for
cement is removed after 7 days and sealed curing iscarried out for 21 days. Samples are prepared bymixing Cr6+ standard solution and waste syrup. There
are nine patterns of specimens, and the test conditions
are shown in Table 1. After curing, the specimen isfinely crushed with a hammer, and the sample having
grain size of less than 2 mm is collected by sieving.
Thereafter, the concentration of Cr6+ in the solution
obtained by the elution test is measured. The
concentration of Cr6+ is determined bydiphenylcarbazide adsorptiometry coupled withcollecting on membrane filter. The mixture method isshown in Fig. 4. The operation added to the mixture

Water-cement ratio
Formwork size
Form removal
Sealed curing
Adding Cr6+
Sugar solution
concentration

Table 1 Test condition (Mixture method)
Water-cement ratio
Formwork size
Form removal
Sealed curing
Adding Cr6+
Waste syrup
concentration

70 %φ5 * 10 cm
After 7days
21 days0, 1, 2 ppm
0.1, 0.5, 1.0 %(/water)70 %φ5 * 10 cm
After 7days
21 days0, 1, 2 ppm
0.000, 0.125,
0.250 % (/cement)

Fig. 5 Immersion method
TEST RESULTS
The test results for each method are shown ingraphs. Each test is conducted three times to ensure a
reproducibility, and the average value for threebatches is listed in the graphs.
Fig. 4 Mixture method
870

SEE - Bangkok, Thailand, Nov.11-13, 2019

addition, it is necessary to examine the usage as a
cement-based solidifying agent since the reduction
effect by mixing is confirmed. The detectedconcentration of Cr6+ and kinds of immersed sugar
solution are shown in the vertical and horizontal axes,
respectively. The graph also includes the elution
results from the blank test, i.e., the elution resultsfrom the test for samples which is not immersed in thesugar solution, as the reference value.

Test results of mixing method
Fig. 6 shows the results of the elution test on a
specimen mixed with waste syrup as a mixture agent.

Cr6+ concentration (ppm)

0.05
0.04

0.046
0.042
0.038

Cr6+ 0 ppm
Cr6+ 1 ppm
Cr6+ 2 ppm

0.03
0.02

Test results of immersion method
0.021
0.017

Fig. 7, 8 and 9 show the results of the elution testof the test specimen which is immersed in each sugar
solution. The elution amount of Cr6+ is summarized
in the graph when three kinds of Cr6+ are added ineach RSS addition amount. As in the test of themixing method, there is no effect of the concentrationof Cr6+ on the elution amount in the immersion test.
The Cr6+ is not reduced regardless of theconcentration of sucrose since sucrose is a nonreducing sugar. On the other hand, the concentrationof Cr6+ decreases in all cases and the concentration of
Cr6+ decreased as the concentration of sugar solution
increased when the waste syrup, allose and glucosewith reducing groups are used. Additionally, theconcentration of Cr6+ decreases as the concentrationof sugar solution increases. When the sugarconcentration exceeded 0.5%, the concentration of
Cr6+ falls below the detection limit of 0.005 ppm.
Among them, the glucose solution has the highest
reducing ability, followed by glucose, waste syrup,
allose and sucrose in order of decreasing ability.
Since most of the components of the waste syrup are
glucose, it is considered that the waste syrup has
higher reducing ability than the allose solution. In
both the mixing method and the immersion method,the elution amount of Cr6+ is deceased, and it is

0.011
0.01

0.008
0.005
<0.005

0.00
0.000
0.125
0.250
Mixed ration of waste syrup (%)

Fig. 6 Test results of elution test by mixture
methodThe vertical axis of the graph represents theconcentration of detected Cr6+, and the horizontal axis
represents the concentration of mixed waste syrup.
Focusing on the concentration of Cr6+ in the sample
without waste syrup, it is revealed that the addedconcentration of Cr6+ does not affect theconcentration of Cr6+ eluted from the sample.
According to the past research, an amount of watersoluble Cr6+ in cement is about 5 ~ 10 mg/kg, whichmeans that 0.3 -0.6 ppm is contained according to thepresent test conditions. This suggests that most of the
Cr6+ is immobilized in the cement setting process, andthat the elution amount of water-soluble Cr6+ form thecement does not change. The detected concentrationof Cr6+ decreases in the specimen to which waste
syrup is added. Furthermore, the detectedconcentration of Cr6+ decreases as the concentrationof waste syrup increases. From these results, it isclarified that mixing waste syrup is effective for the
reduction of elution amount of Cr6+. When waste
syrup was mixed by 0.25%, the concentration of Cr6+
is lower than the environmental quality standards forsoil as well as the effluent standard. The waste syrup
is a highly effective admixture, because it has
sufficient reducibility in a small amount and leads to
the recycling of waste. In order to establish the waste
syrup as an admixture, it is necessary to examine not
only reducibility but also workability factors such ascompressive strength and slump value. Alternatively,
only the specimen using waste syrup is prepared andthe elution test is performed in the mixing method.
Therefore, in the future, the test in which other sugar
solutions are mixed is conducted in order toinvestigate the effects of each type of sugar. In

Cr⁶⁺ concentration (ppm)

0.05

0.04

0.045
0.042 0.041
0.043

Sugar
Concentration
0.5%

0.03
0.020
0.02

0.01

Sugar
Concentration
0.1%

Sugar
Concentration
1.0%
0.012
0.006

<0.005 <0.005 <0.005
0.00
Blank Sucrose Allose Waste Glucose
syrup
Fig. 7 Test results of elution test by immersion
method (adding Cr6+ concentration of 0 ppm)
871

SEE - Bangkok, Thailand, Nov.11-13, 2019clarified that the waste syrup has an enough ability as
the elution reducing material for Cr6+ in the recycledbase material.

Cr⁶⁺ concentration (ppm)

0.05

0.046

0.048
0.044
0.047

0.04
0.03

0.023
0.02

solution, some sugar solutions show reducing
property to Cr6+. Sucrose solution does not show
reducing property, while the waste syrup, allose andglucose solution show high reducing property.
･ The relative merits in reducibility are confirmed in
the Reducing sugars, and it is necessary to exam its
cause.
･ The reducing effect is higher test using immersion
method than mixing method when the two methods
are compared with the specimens using waste syrup.
In addition, it is revealed that the waste syrup is therecycled material that has a reducing effect on theelution of Cr6+ from recycled roadbed material by two
methods.

Sugar
Concentration
0.1%
Sugar
Concentration
0.5%
Sugar
Concentration
1.0%
0.015

0.01

0.006
<0.005 <0.005 <0.005

ACKNOWLEDGMENTS

0.00
Blank Sucrose Allose Waste Glucose
syrup

Cr⁶⁺ concentration (ppm)Fig. 8 Test results of elution test by immersion
method (adding Cr6+ concentration of 1 ppm)
Sugar
0.05
Concentration
0.042
0.1%
0.041
0.038 0.036
0.04
Sugar

REFERENCES[1] Mikami T., Takahama T., Niihata T., Yamamori
K., Yamashita T., Kawamoto Y., Imaoka T.,
Study on promotion of use of recycled aggregate,
Proceedings of the Annual Conference of Japan
Society of Material Cycles and Waste
Management, No. 28, 2017, pp189-190.
[2] Ministry of Land, Infrastructure, Transport andTourism, 2012 construction by-product factfinding result reference materials, 2012, pp. 1- 15.
[3] Kuroda Y., Koshiishi N., INFLUENCE OF
VARIOUS FACTORS ON LEACHING OFHEXAVALENTCHROMIUMFROMCEMENT CONCRETE, Journal of Structural
and Construction Engineering, Vol. 75, Issue 650,
2010, pp. 715-722.
[4] Ugajin T., The Effects of the Trace Elements in
Cement on the Environment, Concrete Journal,
Vol. 39, Issue, 2001, pp. 14-19.
[5] Tsuneoka N., Mori H., Sakamoto H., Itonaga S.,
Moriya M., INFLUENCE OF ADSORPTION
AND REDUCTION BY SURROUNDING
SOIL ON HEXAVALENT CHROMIUM
LEACHED FROM CEMENT TREATED SOIL,
Proceedings of the Japan Society of Civil
Engineering, Vol. 2004, Issue 764, 2004, pp.
133-145.
[6] Yoshida M., Kitamura T., Katsushima H., Kondo
K., ELUTION CONTROL OF Cr (VI) FROM
VOLCANIC
COARSE-GRAINEDSOILIMPROVED WITH CEMENT, Cement Science
and Concrete Technology, Vol. 71, Issue 1, 2017,
pp. 661-666.

Concentration
0.5%

0.03

0.02
0.014

Sugar
Concentration
1.0%
0.010

0.01

This work was supported by Japan Society for the
Promotion of Science, the Grants-in-Aid for
Scientific Research (C) (Grant number: 18J12343).
Additionally, this work was Program for Building
Regional Innovation Ecosystems (MEXT).

<0.005 <0.005<0.005
0.00
Blank Sucrose Allose Waste Glucose
syrup
Fig. 9 Test results of elution test by immersion
method (adding Cr6+ concentration of 2 ppm)
CONCLUSIONS･ The elution amount of Cr6+ eluted from the cement
paste is roughly determined according to the amountof cement, and the elution amount of Cr 6+ does notchange even if Cr6+ is added.
･ In the elution test by the mixing method using waste
syrup, the detected concentration of Cr6+ decreased
with the increase of the mixed concentration. The
reducibility of the waste syrup is confirmed, and thepossibility of the application to cement-based fixation
agent is suggested.
･ In the elution test by immersion method in the sugar
872

SEE - Bangkok, Thailand, Nov.11-13, 2019[7] Niida R., Nitta H., Nishizaki I., METHOD FOR
REDUCING HEXAVALENT CHROMIUM
ELUTED FROM RECYCLED BASE COURSE
MATERIAL USING REDUCING SUGAR,
Journal of Japan Society of Civil Engineers, Ser.
E1 (Pavement Engineering), Vol. 71, Issue 3,
2015, pp. I_211-I_216.
[8] Sakai E., Hisada M., Sugiyama T., Leaching ofTrace Elements and Hydrated Products from

Cement and Concrete, Concrete Journal, Vol. 41,
Issue. 12, 2003, pp. 18-22.
[9] Ono T., Experiment to confirm the nature ofsaccharides, CHEMISTRY & EDUCATION,
Vol. 57, Issue 2, 2009, pp. 92-93.
[10] Ministry of the Environment, Ministry of theEnvironment notification No. 46, 1991.

873

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

GEOINFORMATICS OF TUBERCULOSIS (TB) DISEASE IN JAKARTA
CITY YEAR 2017
*Titin Siswantining1, NPC Purwandani2, MHD Susilowati2, and Adi Wibowo2
Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, 16424,
Depok, Jawa Barat, Indonesia;
2
Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Indonesia
1

ABSTRACT
Tuberculosis (TB) disease are still become the leading cause of morbidity and mortality in Indonesia. The TB
had a relationship between human and their environment, especially in the urban area. The urban area had thehighest population and density, that is the way the accurate information about the urban environment of the TB
area is critical. The research objective to representing characteristic spatial of TB patients lived in Jakarta year
2017. The research used a method using visual interpretation from superimposed spatial data. Spatial datacollection from google earth data, household area (RW boundary), and TB patient addressed from the hospital.
The total TB patients in Jakarta City year 2017 was 114 patient from a hospital and distributed in 108 householdarea (RW boundary). The result of geoinformatics of the urban environment, first building population, building
density, vegetated covered, and distance from the main road. The TB area characteristic had two classified highand low, based on total patient TB disease in a household area (RW boundary). The research concluded of thegeoinformatics of TB disease in Jakarta City year 2017 with highly classified is high building population andbuilding density, lowest vegetated covered (high temperature) and near the main road.
Keywords: Geoinformatics, TB disease, Characteristic spatial

INTRODUCTION(sometimes Geospatial) Information Sciences [5].
The term Geomatics is derived from the French word
Geomatique, coined by the French photogrammetrist
Dubuisson and widely used in North America [6}.
Geoinformatics seems to be popular in Europe,
whereas Geographic Information Science usuallyindicates a Geography background [7], [1]. In thefollowing, the term Geoinformatics will use because
it emphasizes a formal scientific approach to handle
geoinformation, which Geomatics does not imply. TB
disease are still become the leading cause ofmorbidity and mortality in Indonesia.
A spatial approach can examine the geosphere
phenomenon of the complexity of the symptoms withthe concept of a regional paradigm [8]. The territoryis a characteristic similarity in a part of the Earth's
surface [9]. The spatial approach in each region cancope with the health problems that considered as the
top priority, with the resources being able to be used
more effectively [10]. The TB had a relationshipbetween human and their environment, especially inthe urban area with the highest population anddensity.
The TB had a relationship between human andtheir environment, especially in the urban area. A
person with a history of taking a breaking drug at riskof 5.36 times becomes resistant to TB compared witha history of taking his drug that does not break [11].

Tuberculosis (TB) is one of the infectious diseases
caused by Gercobacterium tuberculosis with thename of acid-resistant bacteria (ARB) [1]. In the year2017 there have been 6.4 million official new TB
cases reported to the WHO, this number increased
since 2013 with a total of 5.8 million new cases that
occurred in the year 2017, then the country with the
top number of cases India (26%), Indonesia (11%),and Nigeria (9%) [2]. Based on the results of primary
health research in 2013, DKI Jakarta is one of theprovinces that has the highest TB prevalence rate inIndonesia because it occupies the second position of
the equivalent to Papua is 0.6 [3]. The case of apositive ARB pulmonary tuberculosis or bacteria thatis red and rod-shaped in Indonesia in 2016 according
to the most age group found in the age group 45-54
years, and the record that the sufferer occurs at a
productive age Compared to non-productive age. In
the year 2016, DKI Jakarta recorded the mostsignificant Case Notification Rate number of 241
cases, and the success rate of treatment is only 73%[4].
The tools for dealing with geospatial information,
however, have primarily been developed within thecontext of an emerging discipline, named
Geoinformatics,
Geomatics,orGeographic
874

SEE - Bangkok, Thailand, Nov.11-13, 2019

The urban area had the highest population anddensity, that is the way the accurate information about
the urban environment of the TB area is critical. The
research objective to representing characteristic
spatial of TB patients lived in Jakarta year 2017.

Based on nutritional status, patients withtuberculosis disease who have a lean nutritional status(BMI value < 17-18.4) amounted to 36 sufferers or
32%, normal nutritional status (BMI value 18.5-25)
amounted to 63 or 55%, and fat nutritional status(BMI value 25-27) amounted to 15 or 13%.

METHODS
The research conduct in Jakarta Province in July
until November 2018. The unit of analysis used is thepoint of the sufferer of TB and the household areaadministrative boundary (RW boundary) whose
recorded as tuberculosis disease in the year 2017. The
local characteristic variables in the TB-sufferer or
RW in the study include building density, airtemperature, and distance from the river, and thequality of the settlement. Data on residential
environmental conditions from Google Earth andsurveys. The data used includes TB disease sufferersof 114 patients with tuberculosis disease from the
National Center General Hospital of Dr. Cipto
Mangunkusumo in 2017.
The research used visual interpretation fromspatial data collection from google earth data, RW
boundary, and TB patient addressed from the hospital.
The total TB patients in Jakarta City year 2017 was
114 patient from a hospital and distributed in 108
household area (RW boundary).

Fig. 1

Areas with TB disease in DKI Jakarta year 2017
amounted to 108, which includes 114 people with TB(see fig. 2). The lowest area of TB sufferers or 1 TB
sufferer per RW as much as 102 regions are in an RW
that spreads from the edge to the city center. While in
the height of TB sufferers or 2 TB sufferers per RW
as many as six regions located in the central to theeast side of the city, which precisely located in thevillage of Malacca Sari, Paseban, Rawasari, Senen,
and Tanah Tinggi.

RESULTS AND DISCUSSIONSDistribution of Patient with TB Disease
Patients with TB disease in Jakarta in 2017
amounted to 114 sufferers (see fig. 1) which scatteredin 35 sub-districts, 80 villages, and 108 pillars.
Location of the people of TB is seen by spatial manyoccur in central Jakarta, South Jakarta, and East
Jakarta. Based on the data of TB patients, there arethree characteristics of sufferers, including gender,
age, and nutritional status. Patients with maletuberculosis disease total 79 sufferers or 69%, andfemale-sex sufferers total 35 or 31%. Based on age,patients with tuberculosis disease who are productive(15-64 years) total 87 sufferers or 77%, and nonproductive age (< 15 and > 64 years) amounted to 27
sufferers or 23%.
Table 1 Number of TB Suffers based on Gender
GenderNumberMale
79
Female35
Total
114
Source: data processing

Spatial Distribution of TB Sufferers in DKI
Jakarta year 2017.

Spatial Distribution of Building Density
Building Density obtained from the Intersect
results of Open Street Map building with the regionof TB sufferers, then classified into three namely low
density (< 60 units/ha), Moderate (60-100 units/ha),and high (> 100 units/ha). Based on the building
density map (see fig. 3), the characteristics of areas
with a high density of buildings located in the central
and eastern regions. In the downtown area, which TB
sufferers have a group of the pattern, as for the eastpart has a pattern spread from east to southeast.
The density of building Data with TB region donecross-tabulation which produces six classifications,
so it is symbolized with six different colors to see thedifference of area characteristic of sufferer based onbuilding density (see fig. 4). Based on the explanation,
it shown that TB sufferers not only occur at the highdensity of buildings can even happen at the density of
low and medium buildings.

Percentage
(%)
69
31
100

875

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 2

Spatial Distribution of TB Sufferers Regions in DKI Jakarta year 2017.

Fig. 3

The Building Density of TB Sufferer in DKI Jakarta.

876

SEE - Bangkok, Thailand, Nov.11-13, 2019

The density of building Data with TB region donecross-tabulation which produces six classifications,
so it is symbolized with six different colors to see thedifference of area characteristic of sufferer based onbuilding density (see fig. 4). Based on the explanation,
it shown that TB sufferers not only occur at the highdensity of buildings can even happen at the density of
low and medium buildings.
Environment Quality
The first quality of settlement in parameters is thelayout of the building in an RW. The Data shows thatpeople with TB has the orientation of different
buildings that are good, moderate and bad so that thecondition of the building layout can be infected by TB
disease (see fig. 5).

Fig. 5

Fig. 4The Characteristics of TB Sufferers Region
Based on Building Density in DKI Jakarta.

The Building Density.
(see fig. 7). There was tree cover in the RW, which isassumed to increase the temperature of the air andcause the air cycle is not optimal in the absorption ofpollutants. When the air temperature rises, thecondition inversely proportional to the humidity of
the air decreases, making it easier for germs to breed.

The people with TB disease have the condition of
the building with cold, no air circulation, no sun entry
to the building so that terms will be infected by TB
disease (see fig. 6).

Vegetation
CoveredFig. 7
Fig. 6

The Tree Covered in House Hold (RW).

The third is the width of the road; it sees that TB
can occur in a residential area that has a category ofgood or easy to go through two cars, medium or only
traversed one car, or harmful or without a vehicle canpass. However, when viewed based on a high area of
TB sufferers, tends to occur in the regions that have a

The Building Layout of TB Patient.

Second is the protective tree; it has seen that the
low or high of TB sufferers have a protective tree
condition or the existence of harmful trees or < 25%
877

SEE - Bangkok, Thailand, Nov.11-13, 2019

narrow or steep road width traversed with fourwheeled vehicles and they have a moderate to highdensity (see fig. 8).

activities (see fig 10).
CONCLUSIONS
The research concluded that the geoinformatics
of TB disease in Jakarta City year 2017 with highlyclassified is high building population and building
density, lowest vegetated covered, and near the mainroad.

Fig. 8ACKNOWLEDGMENTS
The research supported by the University ofIndonesia.

The Road Width.

Fourth, based on the location of the settlement
against the source of pollution and activities, poor
settlement environment condition following the higharea of TB sufferers, it is explained that the closer tothe cause of pollution, In this case, the main road will
facilitate the occurrence of transmission in TB disease.
The result appropriate with previous research by
Fitriana [12], which explains that the activity centeror source of pollution is a place to interact to facilitate
the transmission of TB (see fig. 9).

Fig. 9REFERENCES[1] Data Center and Information Ministry of HealthRepublik Indonesia, Tuberculosis. Kementerian
Kesehatan RI, 2018, Jakarta Selatan[2] World Health Organization, Global Tuberculosis
Report, 2018[3] The Research Agency and Health Development,Indonesian Ministry of Health, Laporan Riset
Kesehatan Dasar (RISKESDAS), 2013, Jakarta[4] Ministry of Health Rep. Indonesia, Data andInformation Indonesia Health Profile 2016, Pusat
Data dan Informasi Kementerian Kesehatan RI,
2017[5] Chandarasekaran S.K., and Arivarignan G.,
Disease mapping using mixture distribution,
Indian Journal of Medical Research, Vol. 123,
Issue 6, 2006, pp. 788-798.
[6] Ehler M., Geoinformatics and digital earth
initiatives: a German perspective, International
Journal of Digital Earth, Vol. 1, Issue 1, 2008, pp.
17-30.
[7] Goodchild, M. F., Geographical Information
Science. International Journal of Geographical
Information Systems, Volume 6, Issue 1, 1992, pp.
31-45.
[8] Yunus, H. S., Metodologi Penelitian Wilayah
Kontemporer, 2010, Yogyakarta: Pustaka Pelajar[9] Sumaatmadja, N, Studi Geografi: Suatu
Pendekatan dan Analisa Keruangan, 1981,
Bandung: Alumni[10] Fauzan A., Achmadi U. F., and Susanna D.,
Analisis Spasial Penyakit Tuberkulosi Paru BTA
Positif di Kota Sukabumi Tahun 2010-2012,
Universitas Indonesia, 2014.
[11] T Siswantining, A Malylinda, T Kamilia and A
Bustamam, Risk factors for resistancetuberculosis,
Citation:
AIP
Conference
Proceedings 2023, 020224 (2018); doi:
10.1063/1.5064221.
[12] Fitriana N., Saraswati E., and Widayani P.,
Apikasi Penginderaan Jauh dan Sistem Informasi
Geografi untuk Pemetaan Tingkat Kerentanan
Penyakit Tuberkulosis (TB) di Kecamatan
Imogiri, Kab, Bantul, Yogyakarta, Jurnal Bumi
Indonesia, Vol. 3, Issue 2, 2014, pp. 110-120.

The Road Density.

Lastly, the health service parameters appear thatfrom the six regions can still be affordable to healthfacilities because it is in the classification well tomoderate. DKI Jakarta is certainly a metropolitan citythat has health facilities almost spread evenly so thatin TB, people who are close to health services canalso occur TB sufferers. Because of not only thetreatment factors available but also needed routine inmedicine for the sufferer.

Fig. 10 The Health Facilities Around House Hold.
Based on the explanation, spatial uniqueness that
occurred in 6 TB sufferers turned out to have acommon characteristic of the region that isirregularities in the layout of buildings, road width
tends to narrow, the existence of protective trees andclose to the main road as a place of activity or878

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SPATIAL AND TEMPORAL PATTERN OF SOIL CONSERVATION IN
MOUNTAIN ECOSYSTEM: CASE STUDY OF PATUHA MOUNTAIN,
WEST JAVA - INDONESIA
Satia Nisa Firdhauzi1, Astrid Damayanti1, Jarot Mulyo Semedi1, Muhammad Dimyati1
1
Department of Geography - Universitas Indonesia, Indonesia

ABSTRACTThe Patuha Mountain area located 50 km south of Bandung City and the upstream of the longest river in West
Java, The Citarum River. 12% of Patuha Mountain area categorized as the steep slope area (>25o). Agriculture andplantations on steep slope locations require appropriate soil conservation methods to reduce erosion rates and avoid
the threat of landslides. Land use in The Patuha Mountain area dominated by tea plantations, paddy fields andvarious agriculture commodities such as coffee, corn, scallion, and beans. The objective of this study is to identify
the spatial and temporal patterns of soil conservation applied by farmers from 1990 to 2018 and project it to 2036
to understand the possible impact in the future. The scenario used in the analysis is the Business as Usual (BAU)
scenario. The method used to model the changes in agricultural land use is Cellular Automata - Markov Chain byvarious driving factors, such as distance from the road, river, settlements, forests, and percent slope. The slope andother driving factor are then correlated with agriculture land to identify soil conservation methods and later
validated by field survey. The results indicate that the spatial pattern of soil conservation methods carried out by
the community is closely related to slope conditions and the changes in agricultural land caused by development
pressure and type of commodities planted by farmers. Agricultural land on <15% slope adopt chemical andvegetative conservation methods, while agricultural land on >40% slopes adopts mechanical, vegetative, andchemical conservation method.
Keywords: Soil conservation, Agriculture, Spatial and temporal pattern, Markov chain

supporting human activities in certain regions. The
process mentioned will lead to further escalate
erosion process so that land use planning and erosion
management are needed to avoid large losses.
Therefore, the application of soil conservation needs
to be carried out and examined as a solution to
problems caused by degraded soil.
The Patuha Mountain area was chosen as a
research area because of the existence of physicalcharacteristics such as steep slopes and high rainfall
intensity and social processes that could potentiallycause disasters. Social factors such as population
growth and economic factors often lead to changes inland use. Studies show the increasing population
number and changes in population structure
inevitably led to land use conversion [3], whilenumbers of socio-economic factors influence itschange like shifting cultivation, increasing demand
for forest and farm products and migration [4], towhich can also deliver pressure to soil resulting inlandslides disaster. It can be seen that the Patuha
Mountain Area captured the ecological processes of
erosion and its relation to human aspects such as
agriculture and hazard. Based on the previous
description and the occurrence of landslides and landuse dominated by plantations and agriculture in the
research area, it is necessary to review conservation
actions in the research area, Especially conservationof soil in agriculture of Patuha Mountain area.

INTRODUCTION
Erosion is the loss of land or parts of the land froma place by wind or water [1]. On a large scale, erosion
is a potential landslide disaster that can threaten
human life and also capable of damaging facilities
and community buildings in various locations. The
impact of erosion can be seen in the loss of nutrientslocated in the topsoil caused by the force of water
worn away and removed various soil materials thus
resulting in reduced soil productivity [2].
Resisting high soil loss rate and Reducing theimpact of damage due to erosion requires soil
conservation activities [1]. Based on this, in order toavoid the negative impacts of soil erosion, soil
conservation activities are needed not only to prevent
disasters but also to increase productivity by
optimizing the use of soil. The importance of soil
conservation activities is inseparable from land use
conversion and physical aspects of it, such as
topography and soil type. The relationship built
between soil conservation and land use conversion
illustrates the importance of information on future
land use projections or future trends for a reevaluationof current conservation planning and analysis thathave been carried out by stakeholders in the researcharea.
Increasing developments in society tend to
stimulate land conversion as a complex process of879

SEE - Bangkok, Thailand, Nov.11-13, 2019of its reliable archive and rich collections spanningfrom 1972 to recent years globally with 30 m
resolution freely available [7]. The need for a long
period of data in our research leads us to use Landsat
5 and 8 for land use variables. The gap in data
availability was solved by implementing different
Landsat imagery because Landsat 5 imagery is only
available up to 2012 while Landsat 8 starts from 2013.
Landsat 5 was used for deriving land use data in 1990
and 2000. Landsat 8 imagery is used for land use dataprocessing in 2018. Slope, distance from the road,distance from the river, distance from the forest, anddistance from the settlement were used as the driving
factors for changes in land use.
Land use and slope were overlaid based on recent
data to determine survey points. Stratified Random
Sampling is used to identify the sampled points, thus
population classification is applied based on previous
overlaid results. Number of samples is determined bya random selection system [8] and a total of 30 points
samples is randomly selected in three sub-districts in
the Patuha Mountain Area: Rancabali, Pasirjambu,
and Ciwidey District.

MATERIALS AND METHODS
Research Area
The Patuha Mountain area is part of theadministrative area of Bandung Regency, West Java.
Three Districts included in the Patuha Mountain Area,
namely Ciwidey, Rancabali, and Pasirjambu Districts.
Astronomically, the Patuha Mountain Area locatedbetween 107°12" E - 107°30" E and 7°6" S - 7°12" S.
The Patuha Mountain covers an area of 43,642
hectares. The Patuha Mountain region which consistsof 3 Districts then divided into 22 villages. The
Majority of Residents in The Patuha Mountain Area
derive their livelihood from agricultural activities orbest known as farmers livelihood. Our research area
is also known for its agricultural products such as tea
and coffee, reaching 550 ton production for coffee in2017 [5]. The regional policy also states that in 2007
Ciwidey sub-district was set to be an agropolitan area
through Ciwidey Agropolitan Masterplan, thus
confirming the functionality of the research area [6].
The Patuha Mountain area is still parts of the
upstream zone of the Citarum watershed and followedby the physical condition of a relatively steep slope.
The slope of the Patuha Mountain area was classified
into three classes, namely <15%, 15-40%, and> 40%.
When viewed from Fig. 1, the dominant steep area ison the Southeast side of the Patuha Mountain Region.
The slope class that dominates the research area isclass 15-40% with an area of 21,714 Ha or about 54%of the total area of research, while the slope class withthe smallest area is a slope class of 40% which has anarea of 8,179 Ha or 20% of the area scattered research.

Data Processing
In processing land use data, the initial step taken
was to visually interpret the imagery to produce land
use maps in 1990, 2000, and 2018, to first acquire theinformation of land use changes in 1990 to 2018.
Visual interpretation with Landsat 5 and Landsat 8
was done in natural colour composite bands of eachLandsat image; 321 and 432 respectively, to identify
vegetation and other land use. National classification
system was used to classify various land use in our
research area and 11 class was identified which canbe seen in Table 1.
Land use maps in 1990 and 2000 were used forland use modelling in 2018. The land use model in2018 was tested with the kappa method to determine
the accuracy of the predicted results. Kappa
validation is done by comparing the 2018 land use
prediction from IDRISI software with visuallyinterpret 2018 land use maps. The kappa value
threshold according to Landis [9] is K> 0.75 shows avery good agreement, 0.4≤ K <0.75 shows a pretty
good agreement and K <0.4 indicates a weakagreement. The expected kappa value is ≥75% if it isless than this number, the data repair process must be
carried out until it reaches ≥75%. After we obtained
the appropriate validation value then we can proceedwith predicting land use in 2036 with 2018 as the baseyear input. The year 2036 was selected for the upper
threshold based on the Regional Spatial Plan
(RTRW ) Bandung Regency which applies from 2016
to 2036.
We used Markov Chain-Celular Automata modelwith five driving factors to predict and project theland use in 2036, which is: the distance from the road,Fig. 1 Slope map of the Patuha Mountain area
Data and variables
The variables used to analyze and predict land usechanges are land use of 1990, 2000, and 2018, slope,
distance from the road, distance from the river,distance from the forest, and distance from thesettlement. Landsat was used in our research because
880

SEE - Bangkok, Thailand, Nov.11-13, 2019

Decreasing rate of Plantation and agricultural land
is observed from 1990 to 2000, this is likely to occur
because of the impact of the monetary crisis that
occurred in that period in Indonesia. In 1997 theindustrialization process shifted the agricultural
sector resulting in reduced production of basic
commodities produced by the agricultural sector sothat Indonesia had to import 9 million tons of rice [11].
In 2000-2018 there was an increase of plantation,
dryland agriculture and paddy area. Significant
changes occurred in plantations and dryland
agriculture. This happens because according to thecommunity, plantations, dry land agriculture has ahigher economic value compared to rice fields. So
that many people use the land as dryland farming
compared to rice fields.
In this study, the prediction of land use in 2018
was carried out with an accuracy test with actual land
use in 2018 using kappa validation. K standard values
show results of 0.9082 or 90% which indicates a highlevel of accuracy (>75%). High Accuracy test results
confirm the model to continue projecting for land use
in 2036.
Modelling of land use in 2036 in the process
requires the influence of driving factors. The driving
factor is the variables used to estimate the probability
value of each pixel in the research area. The driving
factor estimates the probability value of each pixel toremain or change to another element. Each variable isclassified and scored to determine the value ofcompatibility for plantation and agricultural land use.
The variables used are the distance from the road,distance from the river, distance from the settlement,
distance from the forest, and slope. Closer the area is
to roads, settlements, and forests show that the land ishighly prospective to change, while the more it
located closer to the river indicates that the land has
little chance to change and the more level or flat theland is, it is more likely to change.
Modelling of land use in 2036 is carried out with
Business as Usual scenario. BAU scenario refers to
the condition given in specific period without any
policy applied or regulation intervention [12] which
can cause the model to behave differently withvarious base year or starting points. Modelling of land
use in 2036 was used as a reference in determining
the spatial distribution of soil conservation methods
applied in 2036 prediction model. Can be seen in Fig.
2, in 2036 results predicted that there will be asignificant change in the area and distribution of landuse, However plantation and agricultural land is still
the dominant class in the region. Changes often occur
within area nearer to roads and directly adjacent to theforest area. Land use that experienced the mostsignificant increase was dryland agriculture reaching
to 2871 Ha or 7% of the total area of research.
Meanwhile, the land use which experienced the mostsignificant decline in 2036 was primary forest which
was 2,944 Ha.

the distance from the river, the distance from thesettlement, the distance from the forest, and slope.
Variables data was Processed using ArcGIS 10.5 andIdrisi Selva Software was used to analyze land usechanges and to perform the accuracy test. The driving
factor variable is calculated using the Euclidean
distance method to produce distance from plantation
and agriculture. Euclidean distance is the physicaldistance in two or three-dimensional space tomultidimensional space [10]. The results of the fieldsurvey are used as a basis for determining landconservation parameters and then used to model soil
conservation on the land use map.
RESULTS AND DISCUSSION
Land Use Changes
Land use in 1990, 2000 and 2018 was used as thebasis for analyzing land use changes in the Patuha
Mountain Area for the past 28 years. Land use in the
Patuha Mountain region in 1990, 2000 and 2018 wasdominated by the use of plantation and agriculturalland as a whole. Land use in the Patuha Mountain areain 3 Period Year shows that almost all land uses
continue to change each year, but not the case withwater bodies. Significant changes in land use changes
that can be observed from 1990 to 2018 are theplantation and primary forest, resulting in increasing
14,767 Ha of plantation and the declining 4,086 Ha ofprimary forest in 2018 (Table 1).
Major changes occurred on the south andsoutheast side of the Patuha mountain area. The
central part of the Gunung Patuha area in 1990 was
only a small portion of open land, which was 6 ha.
However, in 2000 open land increased significantly
to 303 ha. This shows that in 1990-2000 there had
been a lot of land clearing which would be converted
into other land, and it could be proven in 2018 that theland had been turned into plantation land.
Table 1 Land use area in the Patuha Mountain
Land Use

1990
5.068
5.138
5.099
892
13.864
1.693
66

Area (ha)
2000
4.828
5.004
5.180
873
13.894
1.752
66

2018
4.087
5.030
5.662
183
14.768
1.817
66

1.647

2.094

2.137

1.910

4.395
303

4.450
12

Primary Forest
Secondary Forest
Forest Plantation
ShurbsPlantation
Settlement
Water
Dryland1.679
Agriculture
Dryland Mixed
2.124
Agriculture
Paddy
4.450
Bare Land
6
Source : Analysis Result (2019)

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SEE - Bangkok, Thailand, Nov.11-13, 2019supplemented with mechanical conservation methods
to achieve stronger soil structure and reduces the riskof landslides.
In the Patuha Mountain Area, soil conservation
with the use of a combination of three methods is themost dominant one, which is an area of 16,005 Ha or
69% of the total area conserved (Table 2). Soilconservation using a combination of three methods
requires a greater cost than soil conservation using
two combinations. However, using a combination of
three methods on steep slopes can better protect theland to avoid landslides.
Table 2 Land Area Conserved in the Patuha Mountain
Area in 2018

Fig. 2 Land use map in 2036

Soil Conservation
Area
Method(Ha)
Vegetative and Chemical
7.205
Vegetative, Mechanical,
16.005and Chemical
Source : Analysis Result (2019)

Figure 3 shows a graph of plantation andagricultural area in 2018 and 2036 in the Patuha
Mountain Area. In 2036 results predicted that the areaof plantations, mixed dryland agriculture, and paddy
fields decreased. However, dryland agriculture
experienced a significant increase. This change in thearea can cause changes in the area of land conservedin 2036, assuming the physical condition of the slope
is fixed.

Percentage
(%)
31
69

The local community has conducted several
means to implement vegetative conservation methods
i.e by using crop residues, using cover crops, and crop
rotation. The method of vegetative soil conservation
using plant residues is carried out in the form ofmulch which is spread over the surface of the soil.
Mulch can be in the form of organic and inorganic(Fig. 4). Organic mulch is like the remains of plants
or straw, while inorganic mulch is made of synthetic
materials such as plastic. Vegetative soil conservation
method using plants to cover the topsoil is done inthree ways, by using low soil cover plants (grasses orvines), medium ground cover plants (shrubs), highcover crops (trees). Crop rotation as a vegetative
conservation method in the Patuha Mountain Area is
identified with three patterns including all season
paddy fields, paddy to vegetable crops, and all season
vegetables crops.

Fig. 3 Plantation and agriculture land area in 2018 and
2036
Soil Conservation
Vegetative, mechanical and chemical soil
conservation methods are applied by the community
on plantation and agricultural land in 2018. However,the community does not only apply one conservation
method in each field but is divided into 2, namely acombination of two soil conservation methods(vegetative and chemical) and combinations three soil
conservation methods (vegetative, mechanical, andchemical). The combination of the two methods isused for plantation and agricultural land on slopes<15% while the combination of the three methods isused for plantation and agricultural land on slopes
between 15% and 179% degree. Plantations andagriculture that are on relatively steep slopes (15% 179%) have a higher risk of landslides, so
conservation activities carried out must be

Fig. 4 Organic mulch and inorganic mulch
Mechanical conservation methods are conductedby the local community in several means, including
by making guludan which is a pile of dirt or soil,
trenches, terrace, rorak which is a dead-hole to trap
and absorb water into the soil and accommodate
sediments, and irrigation. Mechanical conservation
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SEE - Bangkok, Thailand, Nov.11-13, 2019

method implemented by making guludan is done bymaking soil piles, the size of it is determined by thetype of plant and the structure of the soil. Trenches
are carried out in order to accommodate or channel
surface flow. Trenches can be made in the directionof contour lines or cutting slopes. Trenches areusually made on areas with long slopes. The terrace
is done by cutting contour lines often carried out onland that has a relatively steep slope (Fig. 5). There
are two types of terraces, which is wide-based terrace
and terrace stairs or bench terraces.

Potassium Chloride (KCl), ZN, and kieserite. The
content in each fertilizer is very diverse, such as
nitrogen, carbon, hydrograph, oxygen, phosphate,potassium, sulfur, calcium, magnesium, and sulfur.
Soil conservation in the Patuha Mountain Area in2036 is predicted to continue using two types ofcombine methods, namely a combination of two(vegetative and chemical) and a combination of three(vegetative, mechanical, and chemical) soil
conservation methods (Fig. 7). The land use model in2036 predicted that plantation and agricultural land in2036 is still dominating and expanding. Therefore in
2036, the whole region is predicted as having an
increased total of conserved soil area by 23,722
hectares or 59% of the total area of the study.

Fig. 5 Mechanical soil conservation method bymaking the terrace
Mechanical soil conservation method by making
rorak is done by making a hole between plants. Largerorak varies greatly depending on needs, but usuallyrorak has a depth of 50 cm. Rorak is used to store
plant debris which can later be used as organic
fertilizer, rorak can also be used to hold and absorb
water. Irrigation Method is executed to provide andregulate water (Fig. 6). Irrigation channels are madeto irrigate plants so that the plants get enough watersupply. Irrigation channels are usually used on
agricultural wetlands so that the plants remainsubmerged in water achieving no shortage of watersupply.

Fig. 7 Soil conservation method in 2036
Can be seen in Fig. 8, is predicted that the
combination of three methods of soil conservation
used in 2036 still dominates, which expand to 16,584
Ha or 69% of all land that is conserved. While the
combination of the two methods in 2036 decreased to
7,200 hectares or 31% of all the land that wasconserved in the study area. This shows thatplantation and agricultural land on relatively steep
slopes (15% - 179%) in 2036 is predicted to increase
while plantations and agriculture on relatively flat
slopes (15%) decreased, so in 2036 the prediction of
combination three methods of soil conservation aremostly carried out compared to the combination of
two soil conservation methods.

Fig. 6 Mechanical soil conservation method bymaking irrigation
Several chemical conservation method carried out
by the local people of Mount Patuha is by providing
chemical fertilizers such as phonska, Triple Super
Phosphate (TSP), Zwavelzure Ammoniac (ZA), urea,

Fig. 8 Soil conservation methods area in 2018 and
2036
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CONCLUSIONSREFERENCES

Land use in the Patuha Mountain area in 1990,
2000 to 2018 experienced significant changes andplantation and agricultural land always dominatedevery year. Changes in the plantation area andagriculture will affect changes in the land that must
be conserved. Vegetative, mechanical and chemicalsoil conservation methods are applied by thecommunity on plantation and agricultural land in
2018, but the community does not only apply one
conservation method in each field but rather acombination of two methods (vegetative andchemical) and a combination of three methods(vegetative, mechanical, and chemical). The
combination of the two methods is carried out by thecommunity on the plantation and agricultural land
which is on a relatively flat slope (<15%) and a
combination of three methods are done on plantation
and agricultural land which is on relatively steep
slopes (15% - 179%). In 2036 plantation andagricultural land are predicted to increase, resulting inincreasing conserved land in 2036. Plantations andagriculture on relatively steep slopes (15% - 179%)
increased while plantations and agriculture on
relatively flat slopes (<15) decrease, resulting inhigher application of three combination methods inour research area rather than two by 2036, this occurs
most likely because of the combination of threemethods applied on steep slopes that can better
protect the soil to avoid landslides and degrade thequality of soil in certain area. .

[1] Arsyad, S. (2010). Konservasi Tanah dan Air.
Bogor: Departemen Ilmu-Ilmu Tanah Fakultas
Pertanian IPB.
[2] Suripin. (2004). Pelestarian Sumber Daya Tanahdan Air. Yogyakarta: ANDI.
[3] Lau S S V, Giridharan R, Ganesan S, 2005.
Multiple and intensive land use: Case studies inHong Kong. Habitat International, 29(3): 527546.
[4] Nzunda, N.G., Munishi, P.K.T., Soka, G.E.,
Monjare, J.F. (2013). Influence of Socioeconomic Factors on Land Use and Vegetation
Cover Changes In And Around Kagoma Forest
Reservein Tanzania. Ethiopian Journal ofEnvironmental Studies and Management, Vol 6
No. 5 2013.
[5] BPS. (2017). Kabupaten Bandung dalamAngka. Kabupaten Bandung: BPS Kabupaten
Bandung.
[6] BAPPEDA. (2007). Penyusunan Masterplan
Pembangunan Ekonomi Daerah (Kawasan
Agropolitan Ciwidey). Kabupaten Bandung.
[7] Woodcock, C.E., Allen, R.G., Anderson, M.,
Belward, A., Bindschadler, R., Cohen, W.B.,
Wynne, R. (2008). Free access to Landsat
imagery. Science, 320(5879), 1011.
[8] Tika, M. P. (2005). Metode Penelitian Geografi.
Jakarta: Bumi Aksara.
[9] Landis, J. R., & Koch, G. G. (2012). The
Measurement of Observer Agreement for
Categorical Data Data for Categorical of
Observer Agreement The Measurement.
International Biometric Society, 33(1), 159–17.
[10] Greenacre, M. (2008). Correspondence Analysis
and Related Methods. Barcelona: Department of
Statistics, Stanford University.
[11] Tyas, N. K. (2013). Dinamika Ekonomi Pabrik
Gula Sumberharjo Pemalang pada Tahun 19852005. Universitas Negeri Yogyakarta.
[12] Teng, F., and S.-Q. Xu, 2012: Definition ofBusiness as Usual and its impacts on assessmentof mitigation efforts. Adv. Clim. Change Res.,
3(4), doi: 10.3724/SP.J.1248.2012.00212 .

ACKNOWLEDGEMENT
The author would like to express our gratitude to
the Directorate of Research and Community Service(DRPM) Universitas Indonesia, which has supported
this research in PITTA B UI 2019 Grant. This
research is also part of soil ecosystem services
mapping in Patuha Area under the ongoing PhD
research of Jarot Mulyo Semedi with the title‘Quantifying the spatial-temporal impact ofgeothermal development on ecosystem services inIndonesia.’884

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SPATIO-TEMPORAL RICE PHENOLOGY USING UAVIN PARAKAN SALAK, SUKABUMI REGENCY, INDONESIA

1

Rokhmatuloh1, Supriatna1, Adi Wibowo1 and Iqbal Putut Ash Shidiq1
Department of Geography, Faculty of Mathematics and Natural Sciences, University of Indonesia,
Indonesia

ABSTRACT
Paddy is the primary food source for the Indonesian. Accurate information about the stage of rice or phenology
is very crucial. The phenology was land preparation, vegetative, generative, and harvest. The study aims to analyze
the spatial and temporal of rice phenology and productivity using unnamed vehicles (UAV) or DRONE in Parakan
Salak. In the study used high-resolution imagery and object-based image analysis (OBIA) method to classifying
the phenology of the paddy field. The result from image analysis of phenology vegetative until the harvest of
NDVI was indicating 0.21 until 0.84. The results from the estimation of rice productivity in Parakan Salak of 5 0
tons/hectares. Finally, the research concluded that the harvest area from UAV (DRONE) imagery could provide
an estimation of productivity on the paddy field in Parakan Salak, Sukabumi Regency.
Keywords: Paddy field, obia, phenology, spatial-temporal

flowering until maturation (harvest). The growth willreach maximum on the initiation of interest where forthe initial rice varieties, it takes 55-60 days from theinadequate phase, and for the final variation, it takes
65-75 days. The next stage is the flowering phase,where the rice plants begin to grow flowers, and theleaves of the leaf begin to turn yellow. For the initialrice varieties, this phase reaches 85-100 days after the
inadequate phase, and for variations of rice varieties,
it takes 100115 days. The last phase is a harvest,
where rice has been developed and ready to harvest.
The initial varieties of rice need 130-145 days after
the sproachment phase to be harvested, whereas forother varieties it takes 140-165 days (long time).
Satellite utilization in agricultural land monitoringhas constraints such as low spatial resolution anddepends on the quantity of cloud cover (Moeslah,2015). The phenology was land preparation,
vegetative, generative, and harvest. The study aims toanalyze the spatial and temporal of rice phenology
and productivity using unnamed vehicles (UAV) or
DRONE in Parakan Salak.

INTRODUCTION
According to Statistics Indonesia (or known as
Badan Pusat Statistik) in 2015, about 51.69% of thenational rice production has been produced in Javaisland. It is recorded as much as 51.69% of thenational rice production in the production by rice
fields on the island of Java. However, on the other
hand, BPS Data also mentioned that in the last ten
years, the population of Java Island increased by
1.15% with a decrease in the rate of the land area of
0.02%. Sukabumi Regency is one of the riceproducers and becomes one of the West Java RiceBarn located in the southern region. Sukabumi
Regency recorded in BPS has an area of rice farmingand horticultural area of ± 3,816 Ha and produce
64.97 Quintal/Ha rice paddy field. The availability of
the rice of West Java will depend heavily on the
districts that become the barn.
In general, rice in Indonesia can be harvested
twice for irrigated rice fields and one harvest on therain field. Rice has three phases in one harvest,
namely the vegetative phase (0-60 days), thegenerative phase (60-90 days), and the cooking phase(90-120 days). In irrigated paddy fields, paddy fields
have a planting period of 80-90 days. Meanwhile, forrain rice field has planting period 100-130 days.
Before rice seedlings planted, rice fields need togiven plenty of water (flooded). Once the seeds areplanted or in the germination phase, it takes 25-30
days to reach the initiation stage of the saplings, andthe rice leaves begin to grow. The leaf color thentransforms from yellow to green in the early phase of
the saplings and intermediate stripping phase. The
generative phase is plant growth, ranging fromMETHODS
The research area took the agricultural land in
Parakan Salak District, Sukabumi Regency. Locatedat coordinates 6.786809 º LS and 106.699957 º BT.
This region chose due to the different type of land use
conditions, namely rice fields mixed with plantations
and Tegalan. The condition is ideal to see how well
the methods of analysis used able to separate the rice
field with other farmland. Besides, the chosen land isa rice field that has a condition of growing age/phaseof rice that varies, namely from the vegetative,
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SEE - Bangkok, Thailand, Nov.11-13, 2019

generative, and fallow phases.

of spectral values in imagery by creating ahomogeneous polygon by considering spectral andspace characteristic. Segmenting algorithms not only
relies on one single pixel value, but also on the shape,
texture, and continuity of the pixels.
Vegetation index was generated using different
bands from the sensor. This study used NDVI as atool to differentiate different types of crop. NDVI has
widely used in many applications, and one of them isfor identifying plant characteristics in the ground[4,5,6]. NDVI calculated with the following equation(1) [7]:NDVI NIR  red
NIR  red(1)

where ρred and ρNIR are reflectance value of red
and near-infrared bands.
RESULT AND DISCUSSIONS
Figures or Tables should be sized the whole widthof a column, as shown in Table 1 or Fig.1 in thepresent example, or the whole width over twocolumns.
Fig. 1This is the example for figure formatting.

The Object-Based Identification Analysis
The photo or image of the drone recording is
processed and classification to get the area of paddy
fields based on the growth phase. In the classification
process, there are two methods, which are the Objectbased classification and pixel-based (Pixel based)
method. The classification method used in thisresearch is the Object-based Classification method.
This method has a characteristic that the smallest unit
is not a pixel but a segment, where this segment is acombination of several pixels that have acharacteristic resemblance.
Based on the experiments conducted by Weih
(Weihl et al., 2010), the classification results using
Object-based techniques provide better accuracy thanpixel-based methods. Also, some researchers find the
pixel-based classification results performed on highresolution satellite imagery have a "salt and pepper"
effect, where this effect describes the emerging noiseor pixels with minority classes (Gao and Mas, 2008;
Van de Voorde et al., 2004). These noise effects makeclassification with pixel-based methods less accurate.
In the classification process, the Pixel based
method only looks at the parameters of the pixel value,
while the object based method not only looks at the
pixel value but from the spatial aspect. Object-BasedClassification is a classification method that can
produce similarity of objects based on segmentation

Fig. 2Land use/Land cover in Parakan Salak.

Based on Fig. 3. Data from google earth shows
the Parakan Salak area with land cover rice filed,plantation (tea and oil palm), river, and settlement.

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Table 2 Range of NDVI values for paddy in Parakan
Salak
Rice Field

Fig. 3

Sarengui Paddy
Sarengui Paddy(45 days)
Sarengui Paddy(to beharvested)
Super Paddy

The Parakan Salak from Google Earth Data.

Figure 4 shows the rice filed from a drone on final
generative. (planting phase 12-15 weeks/100 days).

Ma
x
0.80

Area
(ha)
10

0.84

10

4.8

0.85

10

5.3

0.83

10

5.2

Average
0.83
10Source: Data Processing and Survey

Fig. 5productivity
5.6

5.0

The final vegetative phase.

Based on Fig. 5, the figure shows information on rice
field in final vegetative phase (planting phase 4 - 5
weeks/30 days), characterized by tight plants, soils,
and water are barely visible.

Fig. 4

The rice field from UAV.

Table 1 Range of NDVI values for paddy in Parakan
Salak
Rice Field

Min

Max

Mean

Stdev

Paddy
Sarengui Paddy
Sarengui Paddy(45 days)
Sarengui Paddy(to be harvested)
Super Paddy

0.21
0.21

0.85
0.80

0.61
0.58

0.25
0.27

0.79

0.84

0.82

0.02

0.38

0.85

0.66

0.25

0.31

0.83

0.64

0.19

Fig. 6

The final generative phase.

Based on Fig. 6, the figure shows information on therice field in the final generative phase (planting phase12-15 weeks/100 days) marked with a foam or
panicles that start to yellow and immediately enter the
harvest period.

Source: Data Processing and Survey

CONCLUSIONS

Note: should be placed under the table leaving nospace in-between; 10-pt font; and left- and rightjustified.

The result from image analysis of phenology
vegetative until the harvest of NDVI was indicating
0.21 until 0.84. The results from the estimation of rice887

SEE - Bangkok, Thailand, Nov.11-13, 2019

productivity in Parakan Salak of 5.0 tons/hectares.
Finally, the research concluded that the harvest areafrom UAV (DRONE) imagery could provide anestimation of productivity on the paddy field in
Parakan Salak, Sukabumi Regency.

Behaviour of Concrete Containing Waste Carpet
Fiber, International Journal of GEOMATE, Vol.
9, Issue 17, 2015, pp. 1441-1446.
[5] Hossain M.Z., For Chapter in a Book, Soil
Mechanics, 4th ed. Vol. 2, Sakai, Ed. Sankeisha
Publisher’s Name, Year, pp. 11–60.
[6] Author H., A Book New York Publisher, Year,
pp.1-200.
[7] Jensen J.R., Remote Sensing of the Environment:
An Earth Resources Perspective, Prentice Hall,
New Jersey, 2000, pp.
[8] Shidiq I.P.A., Wibowo A., Kusratmoko E.,
Indratmoko S., Ardhianto R., and Nugroho B.P.,
Urban forest topographical mapping using UAV
LIDAR. In IOP Conference Series: Earth andEnvironmental Science, Vol. 98, Issue. 1, 2017,
pp. 012034.
[9] Walter-Shea E.A., and Biehl L.L Measuring
Vegetation Spectral Properties, Remote Sensing
Reviews, Vol. 5, Issue 1, 1990, pp.179-205.
[10] Weih Jr. R.C., and Riggan Jr. N.D., ObjectBasedClassification
vs.
Pixel-BasedClassification Comparative Importance ofMulti-Resolution Imagery. The International
Archives of the Photogrammetry, Remote
Sensing and Spatial Information Sciences, 2010,
XXXVIII- 4/C7.

ACKNOWLEDGMENTS
The study funded by the Ministry of Research andHigher Education, under the Penelitian Dasar
Unggulan Perguruan Tinggi (PDUPT) or the BasicPrimary Research for Higher Education with grant
number: 378/UN2.R3.1/HKP.05.00/2018.
REFERENCES[1] Mosleh M.K., Hassan Q.K., and Chowdhury E.H.,
Application of Remote Sensors in Mapping RiceArea and Forecasting Its Production: A Review.
Sensors, Vol. 15, 2015, pp.769-791.
[2] Richards J.A., and Jia Xiuping, Remote Sensing
Digital Image Analysis. An Introduction, 3rdrevised and enlarged edition. Springer-Verlag
Berlin Heidelberg, 1999, pp.
[3] Rouse Jr. J., Haas R.H., Schell J.A., and Deering
D.W., Monitoring vegetation systems in the
Great Plains with ERTS. NASA Special
Publication 35`, 1974, pp. 309.
[4] Gnyp A.S.M.A, Hosseini H. and Hossain M.Z.,
Strength, Modulus of Elasticity and Shrinkage888

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

RICE PRODUCTIVITY ESTIMATION BY SENTINEL-2A IMAGERY IN
KARAWANG REGENCY, WEST JAVA, INDONESIASuprianta1, Rokhmatuloh1, Adi ibowo1and Iqbal Putut Ash Shidiq1
Department of Geography, Faculty of Mathematics and Natural Sciences, University of Indonesia,
Indonesia

1

ABSTRACT
Karawang Regency is the top rice producer within West Java, Indonesia. Accurate information about the
number of harvest area is essential in rice production in Indonesia with population majority eat rice. The Sentinel2A imagery which has a spatial resolution of 10 meters. The study aims to spatial analysis pattern of rice phenology
and estimation of rice productivity using Sentinel-2A imagery in Karawang Regency. The NDVI algorithm method
used to determine the age of rice plants, which then used to estimate rice productivity. The Karawang Regency
had 30 districts with rice field. The stage of rice was land preparation (NDVI=-0.096-0.036), vegetative (NDVI=0.0 36-0.24), generative (NDVI=-0.24-0.45) and harvesting (NDVI=-0.45-0.63). The result from the estimation of
harvest area is 109,338.27 hectares, and the estimation of rice productivity is 5.5 tons/ha until 6.0 tons/hectares in
Karawang Regency. Finally, the research concluded that the harvest area from Sentinel-2A imagery could provide
an estimation of productivity on the paddy field in Karawang Regency.
Keywords: Rice field, Sentinel-2A, phenology, rice productivity

INTRODUCTION

The Sentinel-2A imagery has a spatial resolutionof 10 meters. The study aims to spatial analysis
pattern of rice phenology and estimation of riceproductivity using Sentinel-2A imagery in Karawang
Regency.

West Java province is the largest rice producer inIndonesia, especially Karawang Regency. Based on
the national statistic report, in 2014-2015, riceproduction has been reduced from 11.085.544 to
10.856.438 tons from [1]. From the report, it ispossible to acknowledge that efforts to maintain foodsecurity in West Java Province are necessary.
Karawang Regency is the top rice producer withinWest Java, Indonesia. Accurate information about the
number of harvest area is essential in rice productionin Indonesia with population majority eat rice.

METHODSThe Karawang Regency had 30 districts with rice
field. The rice field observed in this study is ricepaddies planted in rice fields that grow in a cycle ofthree main periods, which are planting period,
growing period, and harvesting period. Five classes
took from these three main periods according to aliterature study on Sentinel-2A using index
vegetation values, which are land preparation, earlyvegetative, late vegetative, generative, andharvesting/ripening. The spatial analysis approach isused to achieve a spatial pattern of the rice growthphase, and temporal analysis is used to achieve a
temporal pattern of the rice growth phase.

Rice phenology defined as the changes that occur
within the rice from the moment rice is planted in the
ground and proceeds to grow during the harvestingstage [2], [3] (Supriatna, Rokhmat). The detection ofrice phenology could be done using a remote sensing([4]; [5]; [6]; [7];[8]; [9]; [10]; [11]). Spatial
information shows that the actual conditions on
indicators of food security and food vulnerability canobtain from remote sensing data that has high spectral
and temporal resolutions such as LANDSAT 8 data
and MODIS [12]. The results of the growth detection[12], indicating that the initial planting time of rice
crops can know from the value of the Maximum Of
Vegetation Index (EVI Max). By implementing the
Vegetation Index (NDVI) value and the temporal
analysis of Zheng [13] can determine the dates on thestage in the age of rice crops.

The study aims to spatial analysis pattern of ricephenology and estimation of rice productivity using
Sentinel-2A imagery in Karawang Regency. The
NDVI algorithm method used to determine the age ofrice plants, which then used to estimate riceproductivity. The stage of rice was land preparation(NDVI=-0.096-0.036), vegetative (NDVI=-0.0 360.24), generative (NDVI=-0.24-0.45) and harvesting(NDVI=-0.45-0.63).

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RESULT AND DISCUSSIONS
Spatial patterns of the rice paddy Vegetation
Index show that in June and July, there are different
spatial patterns. The spatial distribution of vegetationindex in June 2017 saw in Fig 1, and spatial
distribution of vegetation index in July 2017 saw in
Fig. 2. The high greenish index is in the southern
regions of the district of Karawang in June and July.
The difference in the relationship pattern occurs
based on the area of the high-speed vegetation index.

Fig. 2The NDVI Rice Field on July 2017.

The hight of the vegetation index was not present
in July because it was already in the harvest phase.
The NDVI July but that was a low vegetation index
to an index of 9,077.92 hectares of vegetation. Thismedium vegetation index area shows the potential ofrice harvesting in July (Table 2)
Table 2 The NDVI and Vegetation Index in July
2017
Fig. 1

NDVI
0.096-0.036
0.036-0.240
0.240-0.450
0.450-0.630

Green Index
No Veg.
Very Low
Low
MediumTotal Area
Source: Data Processing

The NDVI Rice Field in June.

There is a high and medium vegetation index areaof 23,335.85 hectares and 6,950.78 hectares. (Table1). Table 1 shows that the potential rice harvest area
in June is 30,186.63 hectares.
Table 1 The NDVI and Vegetation Index in June
2017
NDVI
0.096-0.036
0.036-0.240
0.240-0.450
0.450-0.630
0.450-0.630

Green Index
No Veg.
Very Low
Low
MediumHight
Total Area
Source: Data Processing

Area (Ha)15,973.56
59,507.50
24,785.00
9,077.92
109,338.27

Spatial patterns The rice planting phase isassociated with the rice field vegetation index
showing the different patterns of between in June andJuly (Fig 1 and Fig. 2)

Area (Ha)6,114.98
44,560.09
28,376.57
23,335.85
6,950.78
109,338.27

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Fig. 3The phenology based on NDVI in June2017.

Fig. 4The phenology based on NDVI in July 2017.

CONCLUSIONS
Table 3 The NDVI and Phenology in June 2017
NDVI
Phenology
Area (Ha)0.096-0.036<36,114.98
0.036-0.240
3-4
44,560.09
0.240-0.450
4-6
28,376.57
0.450-0.630
6-8
23,335.85
0.450-0.630
8-10
6,950.78
Total Area
109,338.27
Source: Data Analysis

The result from the estimation of harvest area is
109,338.27 hectares, and the estimation of riceproductivity is 5.5 tons/ha until 6.0 tons/hectares in
Karawang Regency. Finally, the result concluded thatthe harvest area from Sentinel-2A imagery could
provide an estimation of productivity on the paddy
field in Karawang Regency.
ACKNOWLEDGMENTS
This study is supported by the Ministry of
Research and Higher Education, under the Penelitian
Dasar Unggulan Perguruan Tinggi (PDUPT) or the
Basic Primary Research for Higher Education Grant
basedon
contract
no:382/UN2.R3.1/HKP.05.00/2018.

The harvest area in June was 30,286.63 hectareswith average productivity of 7 ton/hectare thenproduction in June reached 212,006.41 tons. July
harvest area of 9,077.92 hectares with 7 tons/hectare
productivity will reduce 63,545.44 tons of rice in July.
Table 4 The NDVI and Phenology in July 2017
NDVI
Phenology
Area (Ha)0.096-0.036<315,973.56
0.036-0.240
3-4
59,507.50
0.240-0.450
4-6
24,785.00
0.450-0.630
6-8
9,077.92
Total Area
109,338.27
Source: Data Analysis

REFERENCES[1] BPS – Agency for Statistic. 2015. Rice production
report. Annual Report.
[2] Rokhamtuloh, Supriatna, TG Pin, R Hernina, R
Ardhianto, IPA Shisiq, and A Wibowo, Paddy
Field Mapping Using UAV Multi-Spectral
Imagery. International Journal of Geomate Vol.
17, Issue 61, 2019, pp. 241-247[3] Supriatna, Rokhamtuloh, IPA Shidiq, GP
Pratama, L Gandharum, and A Wibowo, SpatioTemporal Analysis of Rice Field Phenology
Using Sentinel-1 Image In Karawang Regency,
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SEE - Bangkok, Thailand, Nov.11-13, 2019[9] Küçük Ç., Taşkın G., and Erten, E., Paddy-ricephenology classification based on machinelearning methods using multitemporal co-polar Xband SAR images. IEEE Journal of Selected
Topics in Applied Earth Observations andRemote Sensing, Vol. 9, Issue 6, 2016, pp.25092519.
[10] Chaparro D., Piles M., Vall-llossera M., Camps
A., Konings A.G., and Entekhabi D., L-band
vegetation optical depth seasonal metrics for crop
yield
assessment.
RemoteSensingofEnvironment, Vol. 212, 2018, pp.249-259.
[11] Xu X., Ji X., Jiang J., Yao X., Tian Y., Zhu Y.,
Cao W., Cao Q., Yang H., Shi Z., Cheng T.,
Evaluation of One-Class Support Vector
Classification for Mapping the Paddy Rice
Planting Area in Jiangsu Province of China fromLandsat 8 OLI Imagery. Remote Sensing, Vol. 10,
Issue 4, 2018, pp. 546.
[12] Domiri, D. D., The method for detecting a
biological parameter of rice growth and earlyplanting of paddy crop by using multi temporal
remote sensing data. In IOP Conference Series:
Earth and Environmental Science (Vol. 54, No.
1, pp.012002, 2017). IOP Publishing.
[13] Zheng, H., Cheng, T., Yao, X., Deng, X., Tian,
Y., Cao, W., and Zhu, Y, Detection of ricephenology through time series analysis ofground-based spectral index data. Field Crops
Research, Volume 198, 2016, pp. 131-139.

West Java, Indonesia. International Journal of
Geomate Vol. 17, Issue 62, 2019, pp. 101-106[4] Lopez-Sanchez J.M., Cloude S.R., and BallesterBerman J.D., Rice Phenology monitoring bymeans of SAR polarimetry at X-band. IEEE
Transactions on Geoscience and Remote Sensing,Vol. 50, Issue 7, 2012, pp. 2695-2709.
[5] Semedi J.M., Rice Crop Spatial Distribution and
Production Estimation using Modis Evi (CaseStudy of Karawang, Subang, and Indramayu
Regency). Master Thesis, Graduate School,
Bogor Agriculture University[6] Lopez-Sanchez J.M., Vicente-Guijalba F.,
Ballester-Berman J.D., and Cloude S.R.,
Polarimetric Response of Rice Fields at C-band:
Analysis and phenology retrieval. IEEE
Transactions on Geoscience and Remote Sensing,Vol. 52, Issue 5, 2014, pp. 2977-2993.
[7] Nelson A., Setiyono T., Rala A.B., Quicho E.D.,
Raviz J.V., ….and Thongbai P., Towards anoperational SAR-based rice monitoring system in
Asia: Example from 13 demonstration sites
across Asia in the RIICE project. Remote
Sensing, Vol. 6, Issue 11, 2014, pp. 1077310812.
[8] Dong J., Xiao X., Kou W., Qin Y., Zhang G., Li
L., Jin C., Zhou Y., Wang J., Biradar C. and Liu,J., Tracking the dynamics of paddy rice planting
area in 1986-201 through time series Landsat
images and phenology-based algorithms. Remote
Sensing of Environment, Vol. 160, Issue 1, 2015,
pp. 99-113.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECTS OF OZONE SPARGING ON GROUNDWATER PHYSICALCHEMICAL PARAMETERS DURING IN SITU REMEDIATION OF A
SITE CONTAMINATED WITH CHLORIDES
Erica Kotani Caram1 and Maria Eugênia Gimenez Boscov2
1,2
Escola Politécnica da Universidade de São Paulo, Brazil
ABSTRACTThis paper’s objective was to evaluate the effects of in-situ chemical oxidation (ISCO) for groundwater
remediation using ozone sparging in a site contaminated with vinyl chloride (VC) and trichloroethene (TCE).
The studied area, located in São Paulo, Brazil, has been investigated for over 10 years, and remediation started
two years ago. This paper is based on results obtained before the remediation startup and during its operation.
Geotechnical and hydrogeological characterization is discussed to support analysis of results. The remediation
system includes 86 monitoring wells, 31 vapor extraction wells (above water table) and 33 ozone sparging wells(saturated zone). Periodic monitoring campaigns were executed in 14 monitoring wells, called control points.
Groundwater physical-chemical parameters such as: pH, dissolved oxygen (DO), electrical conductivity (EC),oxidation/reduction potential (ORP), temperature and water table, were obtained from low flow samples
collected during periodic monitoring campaigns in control points chosen according to their location and hot spot
proximity. In general, the control points have shown an ORP elevation, indicating a more oxidative undergroundenvironment than before remediation startup, and EC reduction, probably due to a lower ionic concentration in
groundwater after remediation started. Dissolved oxygen levels have also increased due to ozone degradation.
Keywords: Remediation, In Situ Chemical Oxidation (ISCO), Ozone, Groundwater, Physical-chemicalparameters.

flows in subsurface which can interfere in
remediation efficiency [6].
This paper will approach ozone sparging ISCO
remediation effects on the subsoil saturated zone in a
decommissioned industrial contaminated site. The
studied area is located in São Paulo city and presents
groundwater contamination by organochlorides,
mainly Vinyl Chloride (VC) and Trichloroethylene(TCE). The main objective was to verify ozone
range through physical-chemical parameters analysis
in groundwater samples collected in control points,
considering the presence of fine-grained soils which
can impair the technique efficiency.

INTRODUCTION
A São Paulo State law defines remediation as agroup of techniques used in contaminated sites, thatcan be classified as treatment or containment
techniques [1]. Choice of the proper technique
should consider aspects such as geology,
contamination data, theoretical efficiency andremediation time [2].
In situ chemical oxidation (ISCO) comprises the
mixture of a chemical oxidant in a contaminatedmatrix, promoting its reaction with the contaminant,mineralizing the contaminant and converting it into
water, carbon dioxide and inorganic ions, or evenintermediate byproducts formed during the reaction[3]. Oxidants usage has its origin in wastewater
treatment, and only in 1990 researchers started
exploring its application to soil and groundwater
remediation [4].
Among ISCO’s positive aspects are highefficiency, absence of direct contact between
workers and contaminants, no need for large
excavation or civil works, and the fact that the main
byproduct is oxygen, non-pollutant and commonly
found in subsurface [6], [7]. On the other hand, theshort half-life of oxidants, health and safety risks,and possible oxidant consumption by othercompounds can be listed as negative aspects [5].
Another worry is the existence of preferable paths

SITE CHARACTERIZATION
Field data showed in this paper were obtained
from investigation and remediation studies over the
past ten years. The area is provided with 86
monitoring wells from 4-6 meters deep (A level) to
30 meters deep (E level).
Environmental management history
Preliminary assessment of the area identified
pasts land uses as an automotive industrial plant
between 1930 and 1968, and as a construction
deposit from 2001 to 2008. Vehicles were producedin large scale in the 1950s and 1960s, before thecreation of São Paulo State Environmental Agency
893

SEE - Bangkok, Thailand, Nov.11-13, 2019

(CETESB) in 1968. This is the probable reason why
no documents have been found that could indicate
the location of the primary sources.
However, 2 brickwork oil tanks were foundduring excavation works in the northwest limit of
the studied area. They were both removed in 2009,
and the whole area was covered with a 3-metercompacted layer. Investigation of groundwater andcontaminated plumes started after that, and 5 studies
were carried out in order to define the plumes limits.
During the 5th and last investigation study [8], 30
monitoring wells were drilled (in 3 different depths),
but still the plumes could not be totally defined.
Moreover, new hot spots, detected upstream of thearea, couldn’t be related to the oil tanks. This study
also established health risk due to vapor inhalationin open and closed spaces over the plumes area,
based on CETESB risk assessment method.
Following CETESB’s Manual for theManagement of Contaminated Sites [9], anintervention plan was studied, and a remediation
system with ozone sparging and vapor extraction
was recommended. Remediation goals were to
reduce VC and TCE concentrations, and to eliminate
health risks pathways [10].
Remediation of sites contaminated with solvent
chlorides is especially difficult and expensive.
Different techniques have been developed andapplied with a limited success rate. Besides,
remediation time can be long and usually measured
in decades [5].

Figure 1: Organochlorides degradation pathways[12].
Depending on primary sources, VC can bereleased to environment through air, water or soil.
The most critical pathways are probably air andgroundwater, where VC is most commonly found.
When released to air, VC is expected to exist almost
exclusively in vapor phase. However, VC half-life in
air is limited by its reaction with Oh radicals
produced photochemically [11].
VC solubility in water is relatively low but canbe raised depending on salts present in water. VC
volatilization acts as a significant transportmechanism, considered the most rapid pathway toremove it from superficial water, but an unlikely
pathway for groundwater removal [13]. Someparameters such as vapor pressure and Henry’s law
constant indicate that VC is highly volatile, but ingroundwater it can exist for months or years [14].
Local geological characterization
Site geology is composed by a 3 -meters thickclay layer overlying plastic clay and clay-sand layers
up to 15 meters deep [15]. Groundwater flow
directions are mainly northwest, north and northeast
in shallow (6 meters) and intermediate (9 meters)monitoring wells [15].
In order to understand contaminants behavior ingroundwater, slug tests were executed in 7
multilevel monitoring wells (21 in total) to
determine hydraulic conductivity (K). These tests
were based on USEPA standard [16] and consisted
on measurements of the water level in a monitoring
well, before and after the introduction of a solid
cylinder that causes an artificial elevation of thewater level. Hvorslev equation was applied to thesedata to determine hydraulic conductivity and theresults are shown in Table 1.
Location of the monitoring wells is shown in
Figure 2. In CM-505A and CM-508C wells, the tests
couldn’t be finalized in a day period, which can
indicate the presence of low permeability soil layers
in these wells. CM-504B test presented water tablefluctuations possibly related to interferences in the
study area (trains and subways nearby). Those
occurrences are common in field data, and do notbring important losses to the study.

Contaminant characterization
Since 1940, chloride solvents have been usedwith different purposes, from machinery degreasing
and dry-cleaning to chemical industries. Their
incorrect disposal has caused a variety ofenvironmental problems such as groundwater andsoil contamination, which reflected in the reductionof chloride solvents production and usage [5].
Vinyl chloride (VC) doesn’t occur naturally insubsurface and its anthropogenic sources are related
to PVC production or VC formation in landfill areas
due to organochlorides degradation [11].
However, VC has been detected in groundwaterin landfill areas where there was no VC or PVC
production nearby. VC can also be formed inanaerobic conditions from the reduction ofchloroethylenes:
Perchloroethylene(PCE),
Trichloroethylene (TCE) and Dichloroethylene
isomers (cis-1,2-DCE, trans-1,2-DCE and 1,1-DCE).
Some studies indicate that in anaerobic conditions,
PCE and TCE can degrade into ethenes by the actionof methanogenic, acetogenic and sulfate reduction
bacteria. On the other hand, in aerobic conditions a
direct or co-metabolic oxidation of DCE and VC canoccur. Figure 1 shows contaminants degradation
pathways [12].
894SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1. Hydraulic conductivity in monitoring wells
HydraulicGeometric Mean
Well
Conductivity (cm/s)
K (cm/s)
CM-503A
3.60E-06
CM-504A
3.50E-04
CM-506A
2.,30E-04
6.60E-05
CM-507A
1.60E-05
CM-508A
5.20E-04
CM-509A
3.50E-05
CM-503B
7.40E-04
CM-505B
1.50E-02
CM-506B
3.60E-04
1.20E-03
CM-507B
5.90E-03
CM-508B
2.20E-04
CM-509B
6.60E-04
CM-503C
5.10E-06
CM-504C
6.20E-06
CM-505C
2.60E-04
2.60E-05
CM-506C
2.60E-06
CM-507C
4.20E-05
CM-509C
3.50E-04

presents the higher hydraulic conductivity and also
the major part of the contaminant mass.
Remediation system
The remediation system, composed of 31 vapor
extraction wells (in the vadose zone, above the watertable) and 33 ozone sparging wells (in the saturated
zone, below the water table), operated from April
2015 to November 2017.
Remediation wells were drilled in 8” holes withhollow stem auger, as presented in Fig. 3 (soil vapor
extraction wells) and Fig. 4 (ozone sparging wells).

Figure 3: Soil vapor extraction well [17]Ozone sparging well – B Level
Ozone sparging well – C Level
Monitoring well – A Level
Monitoring well – B Level
Monitoring well – C Level
Monitoring well – D Level
Monitoring well – E Level
Junction box
SVE container

Figure 2. Remediation and monitoring wells
Analyzing the results, deep wells (C level)
present lower K, followed by the shallow wells (Alevel), therefore, the intermediate wells (B level)
presented the higher K. Those data are importantsince organochlorides contaminants (PCE, TCE andDCE) are usually heavier than water and a low K
can slow the vertical downwards movement of thecontaminants. Moreover, the intermediate layer

Figure 4: Air sparging well [18]Groundwater sampling plan
During remediation, all 86 monitoring wells
were sampled at several campaigns to determine
TCE and VC concentrations. Sampling campaigns toregister physical-chemical parameters were also895

SEE - Bangkok, Thailand, Nov.11-13, 2019carried out at 14 monitoring wells (control points):
pH, dissolved oxygen (DO), electric conductivity(EC), temperature and oxidation/reduction potential(ORP). Among the control points, 7 wereintermediate wells (B – 9m deep) and 7 profoundwells (C – 12m deep), selected accordingly to hot
spot and plume configurations.
When groundwater samples were collected tomeasure TCE and VC concentrations, theremediation system was shut down to avoid
interferences in the samples [6]. Groundwater
monitoring campaigns were executed by the low
flow method, following Brazilian procedures forgroundwater sampling [19] and guidelines fromCETESB’s Manual for the Management ofContaminated Sites [9].

+103,5mV (B level) and +69,0 (C level) in 2016.
Those results were expected since higher ORP
solutions tend to oxidize other compounds and lower
ORP solutions tend to reduce them, and positive
ORP is required for aerobic oxidation of chlorinatedsolvents and hydrocarbons [22].

RESULTS

Figure 7: DO at B level wells (9m deep)

DO, ORP and EC results are presented to view
ISCO remediation effects on groundwater and toverify the extension of the subsoil affected by ozone
sparging. Figures 5 to 10 present data from before
remediation until 16 months after startup. Results
are presented and sorted by depth in order to avoid
possible lithology interferences in the results
analysis.

Figure 8: DO at C level wells (12m deep)
DO values showed fluctuation, with results fromC level wells slightly higher than B level wells, andan overall trend of DO increase with time. DO ingroundwater is usually lower than in surface water,
but in this case, oxygen is an ozone byproduct [6],[7]. In Fig. 7 and 8, DO peaks can be observed,
probably due to shut down and re-activation of theremediation system during sampling. Besides, DO
equipment may have malfunctioned in the campaign
carried out 5 months after startup, since all DO data
are higher than the other campaigns, especially CM509C.

Figure 5: ORP at B level wells (9m deep)

Figure 6: ORP at C level wells (12m deep)
According to the literature and specifically forozone as oxidant, an increase of groundwater ORP(due to oxidant action) and DO (due to ozone
degradation into oxygen) is expected [4], [20], [21].
A tendency to ORP increase can be observed:
means in B and C wells were -110,2 mV and -105,5mV respectively in 2014, and increased to

Figure 9: EC at B level wells (9m deep)

896

SEE - Bangkok, Thailand, Nov.11-13, 2019

discussion of the efficiency of ozone sparging ISCO
technique in reducing contaminants concentration.
Acknowledgments
The authors thank WALM Engenharia eTecnologia Ambiental Ltda. for the incentive to thedevelopment of a M.Sc. program. The authors also
thank the owner of the study area for making data
and results available and for allowing the publicationof data and results.

Figure 10: EC at C level wells (12m deep)

REFERENCES

A reduction in EC in the control points is also
observed, directly related to ionic concentrations andpresence of salts in groundwater, representing andindirect measure of pollutants concentration.
Groundwater is considered damaged when EC
values exceed 100 µS/cm [23], as presented in Table
2.

[1] São Paulo State. Decree nº. 59.263, June, 05th,
2013. Regulates the law nº 13.577, July, 08th,
2009, which provides guidelines and proceduresfor the protection of soil quality and managementof contaminated áreas and provides related
measures.
Availablein<
http://www.al.sp.gov.br/repositorio/legislacao/decreto/2013/decreto-59263-05.06.2013.html>. In
Aug, 19th , 2017.
[2] Interstate Technology & Regulatory Council –ITRC. Technical / Regulatory Guidance –Integrated DNAPL Site Strategy. November,2011. 209p.
[3] Instituto de Pesquisas Tecnológicas do Estado deSão Paulo – IPT. Guia para elaboração de Planosde Intervenção para o Gerenciamento de Áreas
Contaminadas. BNDS, 2014.
[4] SIEGRIST, R. L., CRIMI, M., SIMPKIN, T. J.
In situ Chemical Oxidation for Groundwater
Remediation. SERDP, ESTCP, Springer Science,
New York, New York, United States of America,
2011.
[5] STROO, H. F.; WARD, C. H. In situ
Remediation of Chlorinated Solvent Plumes.
SERDP, ESTCP, Springer Science, New York,New York, United States of America, 2010.
[6] HULLING, S.G.; KO, S.; PIVETZ, B.
Groundwater Sampling at ISCO Sites: Binary
Mixtures of Volatile Organic Compounds andPersulfate.
Groundwater
monitoring&
Remediation 31 issue 2. 72-79.
[7] MAHMOUD, A.; FREIRE, R. S. Métodos
emergentes para aumentar a eficiência do ozônio
no tratamento de águas contaminadas. Centro deCapacitação e Pesquisa em Meio ambiente,
Cubatão – SP, 2006. (Química Nova, Vol, 30, nº,1, 198-205, 2007)[8] WALM Engenharia e Tecnologia Ambiental
Ltda. RT-2.00.00.00/1Y9-011 – Investigação
Ambiental Detalhada – Etapa 5. 2014a.
[9] CETESB – Companhia Ambiental do Estado deSão Paulo. Manual de Gerenciamento de Áreas
Contaminadas. São Paulo: CETESB, 2013a.
389p.

Table 2. Physical-chemical parameters results incontrol points
Level

B levelwells

Data
C.0 (2014)*
C.16**

C levelwells

C.0 (2014)*
C.16**

Mean

ORP
(mv)
-110,2DO
EC(mg/L) (µS/cm)
0,48
577,4

SD

-

0,48

167

Mean

103,5

0,63

326,4

SD

-

1,42

93,1

Mean

-105,5

0,72

556,7

SD

-

0,56

333,5

Mean

69

0,87

257,3

SD

-

2,01

60,35

* C.0 (2014) - before remediation start-up** C.16 - 16 months after remediation startup

Temperature and pH parameters were also
monitored during remediation, however those results
fluctuated more due to seasonality than remediationand ozone action, and therefore they aren’t presented
in this paper.
CONCLUSIONS
Analyzinggroundwater
physical-chemicalparameters at control points indicates that theoxidant (ozone) has reached subsurface in all desired
depths, since there was in general an increase inoxidation/reduction potential (ORP), dissolved
oxygen (DO) growth and electrical conductivity(EC) reduction in groundwater. This behavior was
expected for an area with ozone sparging ISCO
remediation, according to the literature.
Besides ozone reaching desired depths and since
the control points are distributed throughout thecontaminated area, it can also be said that chemical
oxidation occurred in the subsoil. The research willcontinue with the analysis of CV concentrations and897

SEE - Bangkok, Thailand, Nov.11-13, 2019[10] WALM Engenharia e Tecnologia Ambiental
Ltda. RT-2.00.00.00/1Y9-013 – Plano deIntervenção e Concepção do Sistema deRemediação. 2014b.
[11] World
HealthOrganizationWHO.
Environmental Health Criteria 215 – Vinyl
Chloride.
UnitedNations
Environment
Programme, International Labour Organization,
World Health Organization e Inter-Organization
Programme for the Sound Management ofChemicals. Geneva, Switzerland, 1999.
[12] United States Environmental Protection Agency- USEPA. Natural Attenuation Decision Support
System User’s Manual. Version 1.0. UnitedStates of America. January, 2000.
[13] SMITH, LR; DRAGUN, J. Degradation of
Volatile Chlorinated Aliphatic Priority Pollutantsin Groundwater. Environmental International,Vol. 10, pp. 291-298. 1984.
[14] Agency for toxic substances and disease registry- ATSDR. ATSDR Case studies inenvironmental medicine: Vinyl Chloride toxicity.
Clin. Toxicol, 28: 267-285. United States ofAmerica, 1990.
[15] WALM Engenharia e Tecnologia Ambiental
Ltda. RT-2.00.00.00/1Y5-032 – 2º Relatório de
Monitoramento da Eficiência e Eficácia dos
Sistemas de Remediação. 2016a.
[16] United States Environmental Protection Agency- USEPA. Standard Operating Procedures # 2046
– Slug tests. United States of America, March,
1994.
[17] United States Environmental Protection Agency- USEPA. How to evaluate alternative cleanup

technologies for underground storage tank sites.
A guide for corrective action plan reviewers,
Chapter II – Soil Vapor Extraction. United Statesof America, 2017. (EPA/510/B-17-003).
[18] United States Environmental Protection Agency- USEPA. How to evaluate alternative cleanup
technologies for underground storage tank sites.
A guide for corrective action plan reviewers,
Chapter VII – Air Sparging. United States ofAmerica, 2017. (EPA/510/B-17-003).
[19] ABNT – Associação Brasileira de Normas
Técnicas. NBR-15.487. Amostragem de águasubterrânea em poços de monitoramento –métodos de purga, 2010.
[20] BHUYAN, S. J. e LATIN, M. R. BTEX
Remediation under challenging site conditions
using in-situ ozone injection and soil vapor
extraction technologies: a case study. Soil andSedimnet Contamination, 21:545-556, 2012.
[21] BANHIDI, M. Metal Finishing 93 - pH and
ORP. 544;546;548-550. 1995.
[22] United States Environmental Protection Agency- USEPA.. Introduction to in situ bioremediationof groundwater. Office of Solid Waste andEmergency
Response,
December,
2013.
(EPA/542/R-13-018).
[23] CETESB – Companhia Ambiental do Estado deSão Paulo. Qualidade das Águas Interiores no
Estado de São Paulo – Apêndice A. Significado
ambiental e sanitário das variáveis de qualidadedas águas e dos sedimentos e metodologias
analíticas e de amostragem. São Paulo, 2013b.
43p.

898

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DAIRY WASTEWATER TREATMENT BY VERMI-BIOFILTRATION
Rabee Rustum 1, Shebin Akbar K 2 and Adebayo J. Adeloye 3
School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Dubai Campus, UAE
3
School of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, Edinburgh, UK,
1,2

ABSTRACTThe treatment of dairy wastewater using traditional wastewater treatment plants such as the activated sludge is
not feasible as it will require high energy rate to provide the required oxygen. This paper presents experimental
results of using Vermi Bio-filtration to treat wastewater from dairy industry. Samples of wastewater were collectedfrom Prasanthi Farms located in a small village of Kollam district, India. The sample characteristics of pH, Total
Dissolved Solids, Total Suspended Solids, Chemical Oxygen Demand, Oil & Grease and Dissolved Oxygen were
measured before and after vermi bio-filtration treatment. The characteristics were measured at different timeintervals of 12 hours (12, 24, 36, 48, and 60 hours). The percentage changes of the above parameters after 60 hours
are -18, 79, 75, 67, 69 and -31% respectively. the method is inexpensive, it can capture all organic materials,
capital and working expenses are low, there is no foul scent, worm biomass would be used as nourishment for thecows, fish agro-business.
Keywords: Dairy, Wastewater treatment, Vermi Bio-filtration, Vermi composting.

sustainable wastewater treatment of dairy wastewatersuch as stabilization ponds [6] and constructedwetlands [7]. Nevertheless, these methods requirelarge area of land. Thus, several researchers
undertake researches to use vermi-bio-filtration
treatment for dairy wastewater like [8], [9].
The use of night crawlers in wastewater or sludge
treatment is called vermi-bio-filtration [9]. In thisprocess, dissolved and suspended natural andinorganic solids are caught by adsorption andadjustment through complex biodegradation forms
that happen in the "living soil" possessed by worm
andthevigorous
microorganisms[10].
Microorganisms that are present inside the earthworm
helps in biochemical degradation of organic matterpresent in the wastewater [9].
Thus, vermi-filtration have several advantages. It
has a low energy dependency; 100% capturing of theorganic materials is certain; there is less capital andworking expenses, and with the addition of highvalued additional finished product (vermi compost);
there is no foul scent while the worms capture
decomposing and decay of every single putrescible
matters in the wastewater; large amounts of worm
biomass would be accessible as nourishment for thecows, fowls, and fish agro-business, after the
principal year of vermi-treatment; sludge is releasedin the vermi-filter bed as excreta (vermi compost)
which is a valuable soil added substance for farming
and cultivation [11].
Hughes, Nair, and Ho [12] also reported that
Vermi-technology is reasonable for dispersed
wastewater treatment. It is very efficient in regard toeliminating COD, BOD, SS and some N and P. It wasalso observed that there was no foul odor throughout

INTRODUCTION
Dairy industry is engaged with the assembling ofdifferent sorts of drain items from dairy processing.
The largest part of wastewater is generated fromcleaning activities. The industry produces between
0.2to 10 liters of effluent per liter of processed milkwith an average distribution of around 2.5 liters ofwastewater for every liter of the milk prepared [1].
The planned volumetric load is 1 m3 of waste for eachton of produced milk [2].
The composition, concentration and effluentsvolume emerging within dairy plants remain reliant
on the nature of products that is handled, plan of the
production, operating techniques, processing planpatterns, and the level of management of water use forcleaning the equipments [3]. In general, the dairy
wastewater comprises higher biological loadings
denoted as BOD (Biological Oxygen Demand), COD(Chemical Oxygen Demand), and total solids thatmight be in liquefied or colloidal system. It also hashigh amounts of nitrogen and phosphorus that are, toa great extent, connected with milk proteins [4].
Hence, arrival of untreated dairy wastewater into thestream prompts consumption of dissolved oxygen(DO).
Aerobic & anaerobic techniques are usually usedin treating dairy wastewaters because of the very
biodegradable contaminants. A review on different
aerobic and anaerobic treatment methods in dairy
industry wastewater can be found in [5]. However,conventional treatment procedures of dairy
wastewater are costly, since they have constant
supply of power, which is an issue in developing
countries. Thus, several alternatives are proposed for899

SEE - Bangkok, Thailand, Nov.11-13, 2019

the treatment.
Arora, Rajpal, and Kazmi [13] reported thatvermi-filtration showed a greater potential forchemical pollutants and pathogen removal fromwastewater. Higher percentage of BOD, COD, TSS,
FC, FS, Salmonella and Escherichia coli removal wasobserved to the accepted level for reuse in irrigation
purpose. It was seen that vermi-filter (VF) diminishedbiochemical oxygen demand and chemical oxygen
demand by 84.8% and 73.9%, respectively.
Sinha, Bharambe, and Chaudhari [9] examinedthe vermi-filtration of sewage acquired from the
Oxley Wastewater Treatment Plant in Brisbane,
Australia. Results demonstrated that the worms
expelled BOD heaps of sewage by more than 99 % atwater powered maintenance time, hydraulic retention
time of 1-2 hours. Normal COD expelled from the
sewage by night crawlers is more than 50 %. Worms
additionally evacuated the total suspended solids(TSS) by more than 90 %.
Patel [14] conducted the analysis on the waste
water generated from dairy industry and found a highremoval efficiency for most water quality parameters:
BOD - 97.95%; COD - 91.64%; TSS -76.39%; TDS- 84.27%; Oil & grease - 84.13%.
However, it is necessary for the wastewater to stayin contact with the worms in the filter bed for sometime. This time depends on the flow rate and theporosity of the filter. This paper investigate the effects
of retention time on the performance of Vermi filter
used to treat dairy wastewater.

Young specimens of Earthworms, Eisiena Fetida
and Eudrilos eugeniae were gotten from composting
unit kept up at temperature of 25°C in cow dungsituated in Kollam, India. Kollam locale is one of 14
regions of the territory of Kerala, India. The region
has a cross-segment of Kerala's normal traits; it isinvested with a long coastline, a noteworthy
Laccadive Sea seaport and an inland lake, Ashtamudi
Lake. The area has numerous waterbodies, Kallada
stream is one among them, and the east side place
where there is waterway is EastKallada and the westside land is West Kallada. As per the 2011 statistics
Kollam area has a populace of 2,629,703[15].
The bio filter consisted of four layers throughwhich the wastewater filtered through. The bottom
layer was 6-7 cm of 40 mm size aggregate, overwhich 20 mm size aggregate was placed at a depth of
4-5 cm. Another layer of aggregate of 10 mm size was
set up to a depth of 2-3 cm. The top most layer was
the garden soil mixed with earthworms (Fig.2). The
different depths of the layers were adopted in order totreat a maximum of 3L of wastewater at a time suchthat the vermi bed is not submerged. If the vermi bed
is submerged, it would prevent the earthworms fromobtaining the oxygen they require, since earthworms
breathe through their skin.

MATERIALS AND METHOD
For the ease of comparison, the work used almost
the same methodology presented Telang and Patel[14]. The vermi bio-filter was made by using a plastic
bucket of 20-liter capacity for the breeding of theworms. Holes are drilled on the curved surface areaof the drum for natural aeration. The schematic detailsof the experiment is shown in Fig. 1.

Fig. 2 Garden soil mixed with earthworms.
The influent was conveyed into the bio filter
through an irrigation system, which was made to
distribute the water over the entire surface area of thebio-filter. The irrigation system was prepared with thehelp of a polyvinyl hose into which holes of about
3mm diameter at a spacing of 6 to 7 cm. The
experimental procedure was carried out using dairy
farm wastewater. The samples were collected fromthe Prasanthi Farms located in a small village of
Kollam district, India. This wastewater is produced
from the dairy product manufacturing and washing of
the milk containers. This water is found to be simply
discarded into the ground without any sort oftreatment. The initial characteristics of thewastewater are given in Table 1. The influent
characteristics were found out for each trial and thenit was subjected to vermi bio filtration treatment andthe effluent characteristics are noted at different trials.
The wastewater samples were retained in the bio-

Fig.1 Vermi Bio filter.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

filter for different durations, that is, 12 hours, 24hours, 36 hours, 48 hours and 60 hours.

560
470
340
210
700
400
540
240
610
190

12
24
36
48
60

-8
-12
-13
-19
-18

18
37
56
78
79

17
43
47
71
75

8
41
63
66
67

17
22
-18
-28
-31

Oil & Grease (mg/l)

9.5
7.9
9.4
7.3
9.6
11.3
9.9
12.7
10
13.1

DO (mg/l)

2480
2280
3600
2120
3200
1200
2200
750
2560
850

COD (mg/l)

120
100
140
80
170
90
140
40
160
40

TSS (mg/l)

2440
1990
2960
1870
3080
1340
2480
540
2680
560

TDS (mg/l)

6.5
7
6.5
7.3
7
7.9
6.5
7.7
6.3
7.5

pH

Oil & Grease (mg/l)

INF.
EFF.
INF.
EFF.
INF.
EFF.
INF.
EFF.
INF.
EFF.

Time

DO (mg/l)

60

COD (mg/l)

48

Table 2 Removal efficiency (%) of measured
parameters

TSS (mg/l)

36quality

TDS (mg/l)

24

water

pH

12

effluent

Influent/ Effluent

Retention time (hours)

Table 1 Influent andparameters

between 8 and 19%. However, the pH values stays
within the range of 7-7.9, and this implies that theearthworms neutralize the dairy wastewater within
the vermi bio-filter.

16
38
43
56
69

Total Dissolved Solids (TDS)The TDS values of the raw data used for thisexperiment ranges from 2440 to 2080 mg/l. These
values have been reduced over time as seen from
Table 2 and Fig.3 and the maximum removal
efficiency achieved after 60 hours was 79%. This
imply that the worms can convert the dissolved solids
to suspended solids stay in the filter and hence
enhance the removal efficiency of the TDS in thevermi-filter.

To ensure the presence of the earthworms in the
bio-filter, dry leaves, dried cow dug, fruits andvegetable waste materials are added to enhance thegrowth of the worms. The container was protectedfrom direct sunlight and was aerated properly. Blacksoil and dry cow dug are mixed together and are filled
to a depth of 3 – 5 cm along with the earthworms. A
layer of kitchen waste is filled as the fourth layer
above which the dry leaves are placed.
The 20L influent container is placed at a height
above bio-filter to ensure continuous flow ofwastewater into the filter. The tap was fitted to thebase of the influent container and the bio-filter. The
irrigation pipe, which allows distributed flow into thebio-filter, is connected to the pipe at the base of theinfluent container. The effluent is collected in a 20L
capacity effluent bucket. About 3L of the wastewater
sample was treated for each trial.

Total Suspended Solids (TSS)The range of TSS values of the raw dairy
wastewater introduced to the vermi-filter ranges
between 120 and 170 mg/l. The results presented inTable 2 shows that the vermi-filter reduces the TSS
values and this reduction increases with elapsed time
and the maximum removal efficiency was 75% over
60 hours. These solids were consumed by earthworms
and converted to small particles stayed in the filter orpassed with the effluent.

RESULTS AND DISCUSSION

Chemical Oxygen Demand (COD)

Different parameters have been used to determine
the effect of retention time on the removal efficiency
of vermi – filter.

COD values presented to the vermi filter ranges
from 2200 to 3600 mg/l. The overall removal
efficiencies of the COD increase over time andreached to 67% after 60 hours as seen from Fig. 3.
This results are close to the results found by [9] who
have done similar experiment for soaking wastewaterand found that the COD reduction using earthworm ismore than 50%.
Patel [14] reached almost to the same results

Variation in Hydrogen Ion (pH)As seen from Table 2 and Fig. 3, the pH values
has generally increased after the dairy wastewater
passed through the filter, and this increase ranges
901

SEE - Bangkok, Thailand, Nov.11-13, 2019(84.27 % removal efficiency), but with a shorter time,
24 hours. However, it is difficult to compare theresults as the mass of earthworms has not been
determined in both cases, which must have an effecton the removal efficiency of the measured parameters.
Similar removal efficiency were observed by [16]who have also made a research on the up flow
anaerobic fixed bed reactor for processing of dairy
industry waste utilizing polypropylene pall rings as apressing media and discovered that regular COD
removal efficiency of 87% and highest biogas
creation of 9.8 l/d was accomplished. A down flow
fixed-film digester was also utilized by [17] for thetreatment of deprotinized cheese with a regularchemical oxygen demand of 59,000 mg/L, thedigester accomplished a COD decrease of 90– 95% at
a hydraulic retention time of 2.0– 2.5 days.

was 69% after 60 hours. Similar results was observedby [14] who found that the removal efficiency of Oiland Grease was 84.13% after 24 hours.
CONCLUSION
This study presented the results of anexperimental study to investigate the effect ofretention time on the performance of vermi bio filter
used to treat dairy wastewater. The results showedthat the removal efficiency of the vermi filter increaseover time and the maximum value for TDS, TSS,
COD and Oil & Grease after 60 hours were 79, 75, 67
and 69% respectively. The pH buffering ability wasattained as the pH of the wastewater was neutralized
by the earthworms within the bio filter and increaseby 18%. DO value shows some decrease at the first
24 hours and then increases by 31% after 36 hours.
Clogs within the filter, due to sludge accumulation,
were not witnessed during the experiment. This is dueto the action of earthworms that consume the solids
and hence clear the path for water. There was no foulsmell with vermi-filtration unit all through theexperiment and there was no sludge development in
the vermi-filtration procedure.
The filtered water can be used for irrigation andthe produced vermi compost can be used as fertilizer.
Other design parameters such as the depth and thesurface of the filter should be taken into considerationin the future. Also the effect of the mass ofearthworms need to be investigated further, which isthe next step of this research. Thus, vermi-filtration isa viable technology for the treatment of dairy
wastewater.

Dissolved oxygen (DO) Variation
The behavior of DO in the experiment is different
from other parameters. The DO is reduced during theinitial stages and then started to increase in the laterstages. This reduction is due to other microorganismsthat use the DO to consume the organic materials inthe sample, and since the oxygen is supplied by theatmosphere to the wastewater, the DO concentration
started to increase.
Oil & Grease
Similar to other organic parameters, the removal
efficiencies of the oil & grease using the vermifiltration increases with time as indicated by the result
presented in Table 2 and the highest observed value

902

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 3

distribution of water quality parameters over time.
Sewage treatment by vermifiltration withsynchronous treatment of sludge by earthworms:
a low-cost sustainable technology overconventional systems with potential fordecentralization. The Environmentalist, Vol. 28,
Issue 4, 2008, pp.409-420.
[10] Emamjomeh, M.M., Tahergorabi, M., Farzadkia,
M. and Bazrafshan, E., A review of the use ofearthworms and aquatic worms for reducing
sludge produced: an innovative ecotechnology.
Waste and biomass valorization, Vol. 9, Issue 9,
2018, pp.1543-1557.
[11] Lourenço, N. and Nunes, L.M., Optimization ofa vermifiltration process for treating urban
wastewater. Ecological engineering, Vol. 100,
Issue 1, 2017, pp.138-146.
[12] Hughes, R.J., Nair, J. and Ho, G., The risk of
sodium toxicity from bed accumulation to key
species in the vermifiltration wastewater
treatment process. Bioresource technology, Vol.
100, Issue 16, 2009, pp.3815-3819.
[13] Arora,
S.,
Rajpal,A.
andKazmi,
A.A.,.Antimicrobial activity of bacterial
community for removal of pathogens duringvermifiltration. Journal of Environmental
Engineering, Vol. 142, Issue 5, 2016, pp. 1-10.
[14] Telang, S. and Patel, H., Vermi-biofiltration-a
low cost treatment for dairy wastewater. Int J Sci
Res, Vol. 4, Issue 7, 2015, pp.595-599.
[15] Kuruvilla, K.,. Census towns in Kerala:
Challenges of urban transformation. Researchnotebooks, School of Habitat Studies, 2014, pp. 112.
[16] Deshannavar, U.B., Basavaraj, R.K. and Naik,
N.M., High rate digestion of dairy industry
effluent by upflow anaerobic fixed-bed reactor.
Journal of Chemical and Pharmaceutical Research,
Vol. 4, Issue 6, 2012, pp.2895-2899.
[17] Canovas-Diaz, M. and Howell, J.A.,. Stability ofa percolating anaerobic downflow fixed film
reactorunder
overloading
conditions.
Biotechnology letters, Vol. 8, Issue 5, 1986,
pp.379-384.

REFERENCES[1] Shete, B.S. and Shinkar, N.P., Dairy industry
wastewater sources, characteristics & its effects
on environment. International Journal of Current
Engineering and Technology, Vol. 3, Issue 5,2013, pp.1611-1615.
[2] Nadais, M.H.G., Capela, M.I.A., Arroja, L.M.G.
and Hung, Y.T.,. Anaerobic treatment of milk
processing wastewater. In Environmental
Bioengineering, Humana Press, Totowa, NJ.,
2010, pp. 555-627.
[3] Karadag, D., Köroğlu, O.E., Ozkaya, B. andCakmakci, M., A review on anaerobic biofilm
reactors for the treatment of dairy industry
wastewater. Process Biochemistry, Vol. 50, Issue
2, 2015, pp.262-271.
[4] Vidal, G., Carvalho, A., Mendez, R. and Lema,
J.M., Influence of the content in fats and proteinson the anaerobic biodegradability of dairy
wastewaters. Bioresource Technology, Vol. 74,
Issue 3, 2000, pp.231-239.
[5] Goli, A., Shamiri, A., Khosroyar, S.,
Talaiekhozani, A., Sanaye, R. and Azizi, K., A
Review on Different Aerobic and Anaerobic
Treatment Methods in Dairy Industry Wastewater.
Journal of Environmental Treatment Techniques,Vol. 6, Issue 1, 2019, pp.113-141.
[6] Boruszko,
D.,
ResearchofEffective
Microorganisms on Dairy Sewage Sludge
Stabilization. Journal of Ecological Engineering,Vol. 20, Issue 3, 2019, pp.241-252.
[7] Dąbrowski, W., Karolinczak, B., Gajewska, M.
and Wojciechowska, E., Application of
subsurface vertical flow constructed wetlands toreject water treatment in dairy wastewater
treatment plant. Environmental technology, Vol.
38, Issue 2, 2017, pp.175-182.
[8] Kaur, S. and Cheema, P.P.S., Vermifiltration
Using Garden Waste as Padding Media for
Treatment of Dairy Wastewater. In International
Conference on Sustainable Waste Management
through Design, Springer, Cham, 2018, pp. 51-58.
[9] Sinha, R.K., Bharambe, G. and Chaudhari, U.,903

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

System Dynamic Modelling for Sword and White Pomfret Fish Resourcesat Depok Coast, Bantul Regency
Dewi Susiloningtyas1, Hengki Tasman2, Tuty Handayani3 and Arti Aulia4
Department of Geography, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Indonesia;
2
Department of Mathemathics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Indonesia
1

ABSTRACT
Depok Coast in Bantul Regency popular for fishing activities. The potential for considerable marine resourcesin Depok Coast is a major factor in progress of fisheries business. The potential of these marine resources canprovide a great opportunity for the development of capture fisheries and raise the economy of coastal communities.
Sword and white pomfret fish are the main commodities in capture fisheries households in Depok Coast. However,if the occurrence of continuous arrests without further study is feared to cause the end of the sword and white
pomfret fish resources in the future. This study aims to know the policies and the relationship between theecological, economic and social sub-systems in the resources of sword and white pomfret on the Depok Coast.
The method used in this research is the modeling of dynamic systems, where the sub-systems of the ecological,
economic and associated social and serve as a model system dynamic of sword and white pomfret fish resources.
Data for the ecological sub-system is an inventory of sword and white pomfret fish and the condition of the watersof Depok Coast. Furthermore, for the economic sub-system interviews were conducted by focus group discussion
for the fishermen on Depok Coast and results in quantitative form. Data for the social sub-system is the number offishermen and the population of Depok Village. The results of this modeling shows that overfishing can reduce
sword and white pomfret fish resources if it is not compensated by fish preservation.
Keywords: System Dinamic, Sword Fish, White Pomfert Fish, Depok Coastgeneral so that the use of these resources tends to be
free without any limitations as long as there arebenefits / benefits obtained. The above conditions if
it is not immediately managed (managed) properly
sooner or later it is feared that it will threaten thesustainability of fish resources. It is estimated that 47
percent of the world's fisheries resources haveexperienced full exploited, 19 percent were declared
overexplored, 9 percent have been depleted. Thus 75
percent of fish resources have experienced critical[3].
Depok Coastal is the largest fishery products in
Bantul Regency [4]. The potential for considerable
marine resources in Depok Coast is a major factor in
the progress of fisheries fisheries. High potential ofmarine resources in Depok Coast made many
fishermen from outside Bantul Regency migrate to
Depok Coast to find decent income for fish at there.
According to data from TPI MinaBahari 45, themain commodity in Depok Coast are sword and white
pomfret. In 2015, sword became the largest catch(32.42%) of the 13 types of fish available. Whereas
white pomfret is the most expensive type of fish withthe third largest catch result after Sword and Snapper.
Therefore, the management of capture fisheries
with characteristics of densely captured andmultifunctional waters requires an integrated policyof coastal and marine natural resource utilization andmanagement in order to be able to improve thewelfare of fishing communities. To make it happen, a

INTRODUCTION
Fisheries system consists of a human system anda fisheries management system. The natural system
consists of subsystems, namely fish, ecosystem andbiophysical environment [1]. The human system
consists of four subsystems, namely fishers, harvest
sector and consumer posts, fishing household andcommunities and ecomomic / cultural environment.
The management system is grouped into four
subsystems, namely fishery policy and planning,fishery management, fishery development and fisheryresearch. The three components of the fishery systeminteract with each other to form a dynamic fisheriessystem.
The activities of fishermen in carrying out marine
fisheries have various obstacles both from physicaland non-physical factors. The constraints that many
face in Indonesian fisheries and maritime affairs lie in
their management systems. The potential of fisheries
which is quite large but managed by the people
without the knowledge of fisheries conditions isfeared that overfishing will occur.
The increasing exploitation of fish resources as aresult of increasing demand for these resources will
have an impact on the increasing pressure on thesustainability of fish resources [2]. Coupled with thenature of the use of marine resources, which ingeneral are open access, which means that theirutilization is open to anyone and their ownership is904

SEE - Bangkok, Thailand, Nov.11-13, 2019

resource management instrument is needed which
focuses more on the ability of carrying capacity of thenature without ignoring the economic interests of thecommunity. This study aims to determine fisheries
resources especially Sword and White Pomfret in
Depok coast waters with dynamic system models up
to 2030.

process as a cause that will produce a condition, or
vice versa a situation as a cause will produce a process
while a flow diagram is made based on the equationof the dynamic model which includes state variables(level), flow/rate, auxiliary, and constant.

METHODSThis research was conducted in Depok coast, Bantul
district using secondary data from TPI Mina Bahari
45. The model used was a dynamic system modelusing Powersim 8 software.
Production Surplus Model
This surplus production model is used to see carriying
cappacity and capture capabilities in a fishery waters.
This study uses a surplus model produced by Waltersand Hilborn (1992). In general the regression form of
the Walters and Hilborn production surplus model
can be written as follows:

Fig 1.

Causal Loop Diagram for Fish Resources

In the end, validation is carried out to determine thecompatibility between the simulation results and thesimulated symptoms or processes. The model can bestated either if the error or deviation of the simulation
results against the symptoms or process is simulated
small. The validation of the performance of the model
is done by a simple statistical method, namely
Average Mean Error (AME) between the simulation
data and empirical data. The formula used is:(1)
Where :

(2)Equation 1 is a regression equation with dependent or
non-dependent variables is the rate of biomass change
and independent or independent variables are CPUEand effort (Walters and Hilborn 1992). Those
equation can be used to estimate the biologicalparameters K (carrying capacity) and q (capture
ability) separately from the three regression equation
coefficients.

(3)(4)
Where :A = Actuall Value
S = Simulation Value
N = Time Unit

System Dynamics Model

Equation 2 until 4 are validation between simulationand empirical data on model. Model can be declaredvalid if the deviation between the simulation results
and actual data is <30% [6].

Fisheries resources are dynamic natural resources,
as well as pertubasi that occurs in these resources bothin the form of a relationship between catch dam
effort, Therefore the management of fisheries
resources which are relatively dynamic and complex
requires a dynamic analysis approach as well. For thisreason, dynamic analysis needs to be done to see theinteraction between the components of resources andtheir changes [5].
System Dynamics analysis is carried out throughtwo stages, namely making a causal loop diagram andflow diagram. The causal loop diagram shows therelationship between variables in the system process
being examined. The basic principle of making it is a

RESULTS
Model for Sword Resources
Fishing data for Sword is obtained from Tempat
Pelelangan Ikan (TPI) Mina Bahari 45. We got 54
months historical data, that is from January 2014 until
April 2018. In this 54 months, fishermen went to sea
as many as 23.067 trips. Which means that the total
effort of fishermen was 23.067 times.

905

SEE - Bangkok, Thailand, Nov.11-13, 2019

120,000.00
107,489.30

100,000.00
80,000.00
60,000.00

48,581.78
40,000.00

39,984.30

20,000.00 22,646.52

13,273.98

0.00
2014

Fig 2.

2015

2016

2017

2018

Captured of Sword per Year
Fig. 5Figure 2 is that the highest sword catch is in 2017,
which is 107.489,30 kg. While the lowest catch is in
2016, which is 13.273,98 kg. This is because there isa west monsoon that causes strong waves so that it isdifficult to sail. The average sword catch per year is46.395,18 kg.
Results of the production surplus model to see
carrying capacity and capture capabilities seen fromCPUE data are 0.9986 and 0.9302. Then this value areincluded in the stock flow diagram for Sword
Resources.

Simulation Results for Sword ResourcesKg

22.00021.000STO CK SWO RD (Kg)

20.00019.00018.00014 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Fig. 6Graphic for Sword Stock in Model

Based on figure 6, we know that stock for sword fish
will decrease during the simulation. this indicates thatthe sword fish will be depleted at a certain time. Afterthe simulation is done. then the AME test is
performed to determine the validity of the simulation
results of the model and to find out whether the model
can be predicted further.
50,000.00

Fig 3.

40,000.00

Stock Flow Diagram for Sword Resources

30,000.00

After the Stock Flow Diagram is made, the modelis ready to be simulated. The simulation results in
Figure 4 show that the stock of swords decreases
every year. this is related to the decline in growth andalso fish mortality, while the effort made byfishermen continues to increase each year. the fewer
fish stocks there are, the less the number of catches
obtained by fishermen. In 2030 the growth of sword
fish was only 98 kg with a much higher death orcapture rate of 105.45 kg and 273.78 kg which would
result in the depletion of sword resources on the coastof Depok.

20,000.00
10,000.00
0.00

2014

2015

2016

ActuallFig 7.

2017

2018

Simulation

AME for Sword Stock

Results for AME test showed that the simulation
results and acute data have a difference of 14.55%
which means that the simulation results can bepredicted further.
906

SEE - Bangkok, Thailand, Nov.11-13, 2019by fishermen continues to increase each year. The
fewer fish stocks there are, the less the number ofcatches obtained by fishermen. In 2030 the growth ofsword fish was only 50,63 kg, but this difference is
not too far from the death rate of only 54,41 kg. But
also, the number of arrests is far greater than the deathof 83,27 kg.

Model for White Pomfret Resources
The data for white pomfret is also obtained fromTPI Mina Bahari 45. With 54 months, and total tripsof fishermen went to sea as many as 23.067 trips. Data
showed that average white pomfret catch per year is9.501,92 kg (figure 8). The highest catch in 2015 witha total of 15.198,95 kg. Different from sword fish, in2017 white pomfret actually got the lowest catch of
only 3.569,40 kg. This could be because in that year
white pomfret was still migrating due to the existinghigh waves.
15,198.95

14,000.00

STOCK WP

16,000.00

Kg
7.000

14,330.90

6.500

6.000

12,000.00
5.500

10,000.00
8,000.00
6,000.00

14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

7,489.70

6,920.65

Fig 10. Graphic for White Pomfret Stock

4,000.00

3,569.40

After the simulation is done, result of AME test
showed that the simulation results and acute data havea difference of 8,98% which means that thesimulation results can be predicted further.

2,000.00
0.00
2014

2015

2016

2017

2018

Fig 8. Captured of White Pomfret each Year
12,000.00

Results for production surplus model to see
carrying capacity and capture capabilities seen fromCPUE data same as the results for sword fish are
0.9986 and 0.9302. It is just the difference is value of
intrinsic growth / death for white pomfret which isequal to 0.95 per year.

10,000.00
8,000.00
6,000.00
4,000.00
2,000.00
0.00
2014

2015

ActualFig.11

2016

2017

2018

Simulation

AME for White Pomfret Model

Figure 11 is value of AME in white pomfret model.
Graphic showed for simulation white pomfret stockfrom 2014 until 2018- stable between 6000-8000 kg,
but in reality stock of white pomfret has increased anddecreased (fluctuated).
CONCLUSION
Fig 9. Simulation Results for White PomfretResources

The model shows that both sword fish and white
pomfret will decline in stock until 2030. This is also
followed by a smaller growth rate than the death rateor catching rate. If this condition still continues it willcauses depletion of sword fish and white pomfretresources in the waters of Depok Coast. Therefore itis necessary for government efforts to provide a

Stock flow diagram for white pomfret is the sameas that used for sword fish. The simulation results in
Figure 10 showed that the stock of white pomfretdecreases every year. This is related to the decline ingrowth and also fish mortality, while the effort made907

SEE - Bangkok, Thailand, Nov.11-13, 2019balance between the desires of the market andexisting resources.

Coastal Waters). Indonesian Coastal and Ocean
Journal Vol 4 (2) pp: 36-49.
[4] Bantul Regency Marine and Fisheries Service.
2015. Bantul Regency Fisheries Production.
[5] Muhammadi. et. al. 2001. Dynamic System
Analysis: Environment, Social, Economy andManagement. Jakarta :UMJ Press.
[6] Hilborn R and CJ Walters. 1992. Quantitative
Fisheries Stock Asessment, Choice, Dynamic andUncertainty.
[7] Supriatna, Supriatna, J., Koestoer, R. H., &Takarina, N. D. (2016). Spatial Dynamics Modelfor Sustainability Landscape in Cimandiri
Estuary, West Java, Indonesia. Journal Procedia
Social and Behavioral Sciences, 227, 19-30.
[8] Muhammadi, Aminullah, E., Soesilo, B. (2001).
Systems Dynamics Analysis: Environmental,
Social, Economic, Management. Jakarta: UMJ
Press.

ACKNOWLEDGMENTS
We would like to thank for Hibah PDUPT 2019
from
DIKTI
(1/E1/KP.PTNBH/2019
and234/PKS/R/UI/2019) have supported in funding of
this research.
REFERENCES[1] Charles AT. 2001. Sustainable Fishery Systems.
United Kingdom: Blackwell Science Ltd. 370 p.
[2] Mulyani, Tri Ayu. 2013. Economic Development
Policy Sustainable Captain Fisheries In Dki
Jakarta Province. Postgraduate. Bogor Agricultur
Institute.
[3] Fauzi A dan S Anna. 2002. Evaluation of Fisheries
Development Sustainability Status: Applicationof Rapfish Approach (Case Study of DKI Jakarta

908

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

FRESH PROPERTIES PERFORMANCE OF ALKALINE ACTIVATEDPALM OIL PASTE
Aidan N1, Nuradila Izzaty H1, Muhd Norhasri M.S2, Sharifah A2
Student, Faculty of Civil Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor,
Malaysia; 2Lecturer, Faculty of Civil Engineering, Universiti Teknologi MARA, 40450 Shah Alam,
Selangor, Malaysia
1

ABSTRACT
Cement powder has been used as the basic construction material throughout the years. As the demand increases,
so does the production. Researchers have been trying to find an alternative to replace the usage of cement to reduce
the production that resulted in increase of carbon dioxide emission. Palm Oil Fuel Ash (POFA) is one of thealternatives. POFA usage has been proven to be beneficial. However, the use of activator with POFA cement paste
might enhance these benefits even more. This research highlights the fresh properties of Palm Oil Fuel Ash cement
paste with activator through experimental investigation. In this research, the activator used are sodium-based
solution; sodium silicate and sodium hydroxide. This sodium-based solution is generally used in geopolymer
cement to improve its mechanical and fresh properties. In this research, cement is replaced by 5% weight of POFA
whereas water is partially replaced by alkaline activator with ratio of 1kg of water to 200ml activator. The fresh
properties of the paste in this study emphasis on flow, setting time and consistency, which are the important
properties to improve effectiveness and efficiency of repairing work such as grouting and patching. Sodium
Silicate POFA cement paste tends to have the highest consistency and the fastest setting time for both initial andfinal. Other than that, the presence of POFA tends to reduce flowability of paste. Sodium Hydroxide POFA cement
paste has highest flowability, however Sodium Silicate POFA cement paste decrease in flow percentage compare
to OPC.
Keywords: POFA; Sodium Hydroxide; Sodium Silicate; Flow; Setting Time; Consistency

cement mortar resulted from high Calcium-Silicate Hydroxide gel formed from high content of silica in
POFA [5]. Other than that, due to its fine particle,
POFA can also acts as filler. When used to replace
cement in a high amount, the fine particle of POFA
has the ability to increases the concrete workability as
well as the setting time [5]. Other than mechanicalbehavior, the usage of POFA also improve the fresh
properties of concrete. Improved finishing surfaces
and workability is produced by the ability of POFA
to absorb water from the mixture and retained it in thesystem [6]. However, to improve the efficiency of
POFA usage in cement replacement, activator isneeded.
Since Alkali-activated binders production uses amoderate amount of energy, they are consideredenviron-mental friendly [7]. Alkaline activator has
the ability to dissolve the acidic oxides of POFA
which normal water is not able to do [8]. For thisresearch, sodium-based solution is used as alkaline
activator; Sodium Hydroxide and Sodium Silicate.
Sodium Silicate has been proven to decrease thesetting time of cement. Although there is no increasein strength of concrete, sodium silicate has the ability
to make the concrete to undergone fast setting [9].
Whereas, Sodium Hydroxide has the ability toincrease the strength of concrete. The compressive
strength properties of geopolymer concrete is

INTRODUCTION
Palm Oil Fuel Ash (POFA) waste has been
increasing day by day which contribute to large usageof land disposal. Lately, the use of POFA insustainability development has open an opportunity
to solve this environmental issue. POFA has beenused as cement replacement due to its pozzolanic
properties. As our economical, technological andecological advancement grew by days, the usage of
pozzolanic material as cement replacement also
increases and is expected to continue in years to come[1]. Other than addressing the issue of increase in landdisposal usage, the use of POFA also could
potentially decrease the effects of carbon footprint
due to cement production. Cement productionindustry has contributed up to 5% of the world’s
carbon dioxide emission [2]. Tons of carbon dioxide
are release into the atmosphere from the decarbonation process of limestone and the combustionof fossil fuel during the cement manufacturing
process [3]Previous studies manage to prove that the usageof POFA in concrete can improve the compressive
strength and the durability. High content of silicon
dioxide or calcium oxide in POFA can produce extra
hydration process that will improve the concrete
strength and durability [4]. A denser and durable
909

SEE - Bangkok, Thailand, Nov.11-13, 2019improved because the higher concentration of
Sodium Hydroxide produced a good bonding of
aggregate and paste [10]. A Higher amount of Sodium
Hydroxide also reduces the cement setting time [11].
This activator will be a partial replacement for waterin the design mix. During the hydration process of
cement, small amount of calcium hydroxide is
produced when less amount of cement is used. The
small amount of calcium hydroxide is insufficient forhydration with large amount of reactive silica. So, inorder to activated the reaction of excessive reactive
silica, sodium hydroxide is needed [12]. With this, theusage of alkaline activator might be able to enhancethe efficiency of POFA replacement in cement.
This research also emphasis on the patching andrepair work application. The use of POFA has been
proved to enhancing cement properties used in repair
works. When POFA is incorporated, the compressive
strength of cement grout increased up to 20% [13].
However, better performance can be achieved withthe usage of alkaline activators.
This research is conducted in hoping to discover
new types of material that can be used in patch andrepair work.The goal of this research is to evaluate thefresh properties of POFA cement paste reacted withsodium-based solution. This research also hopes tocontribute to the reduction in cement manufacture
which resulted in increasing of carbon dioxide release,
reduction of the POFA waste which will consume
large amount of land for disposal as well as improving
concrete repair works material.

This research emphasis on the fresh properties of
cement paste since it is one of the most important
properties that will influence the effectiveness andefficiency of repairing and rehabilitation work. The
fresh properties tests are standard consistency test,
setting time test and flow table test.
Standard Consistency Test
Standard consistency test is used to obtained thewater demand of the paste. Paste consistency is an
important attribute since it could affect theworkability of a freshly mixed paste as well as thestrength of the paste after it hardens. Too much water
could increase workability but reduce the strength andvice versa. In order to get the optimum water demand,
this test is needed. This test is conducted accordance
to ASTM C191 standards.
Setting Time Test
Setting time test is conducted after conducting
standard consistency test. The optimum water
demand obtained in standard consistency test is usedin this test. Setting time test consist of initial setting
time and final setting time. Initial setting time isobtained to determine the time when the paste started
to losses its plasticity. Whereas, the final setting time
is obtained to determine the time the paste started tolosses its plasticity completely and hardened. Setting
time is also an important attribute since in repairing
works, paste needed to set quickly so that the repaired
structure can be operational again. Since this test is acontinuity to standard consistency test, therefore it isalso conducted in accordance to ASTM C191
standards.

METHODOLOGY
Sample Preparation
The sample used in this research are preparedbased on the design mix shown in table 2.1. OPC has
no replacement in cement and water. Whereas, 5P has
a 5% replacement of cement with POFA but noreplacement in water. For 5P5.2H and 5P5.2S has a
5% cement replacement to POFA and a replacementof water with a ratio of 1kg of water to 200ml of withsodium hydroxide and silicate solution respectively.

Flow Table Test
The workability of the paste is obtained byconducting flow table test. Water cement ratio
obtained from the standard consistency test is used inthis test. Workability of the paste is essential to beaccess especially in repairing work since somerequires the paste to be injected in cracks. This test is
conducted in accordance to ASTM C1437 standards
where the flow table will be dropped for 25 times in
15 seconds.

SampleCement(kg/m3)

POFA(kg/m3)Water(kg/m3)

Activator(kg/m3)

Table 1: Design Mix

OPC
5P
5P5.2H
5P5.2S

380
360
360
360

0
20
20
20

205
205
163
163

0
0
42
42

RESULTS
Standard Consistency Test
Table 2: Standard Consistency Test Result

Fresh Properties Testing910

Amount of
Sodium (ml)Penetration(mm)
Percentage of
Water (%)

400
400
400
400

0
5
5
5

0
0
28
31

119
130
112
124

6
6
6
5

Fig 1: Relationship between Setting Time (min) andConsistency (%)
As cement consistency increase, the it will makethe cement setting time to increase as well. However,with activator, it can be seen that it could reduce thesetting time. Sodium Silicate could decrease thesetting time more compare to Sodium Hydroxide as
seen by sample 5P5.2S and 5P5.2H in Fig 1. Thisshows that both alkaline activators have the ability toaccelerate hydration which reduce the setting time of
the cement. However, the presence of POFA in
cement increases the setting time. This is probably
due to the porous particle of POFA that is able toabsorb more water hence retaining more water in thesystem for a longer period of time.

29.8
32.51
35
38.8

Setting Time Test
Table 3: Setting Time Test Result
Initial Setting Time(min)

Final Setting Time
(min)

OPC
5P

178
220

292
365

5P5.2H
5P5.2S

280
58

289
62

Flow (%)

DesignMix120.0050

100.00

40

80.00

30

60.00
20

40.00

10

20.00

Flow Table Test

0.00

SampleAve. diameter (mm)OPC
5P
5P5.2H
5P5.2S

172.67163.00216.33102.33Sample69.28
59.80
112.09
0.33

40
30
20
10
0

Flow (%)

Fig 2: Relationship between Flow (%) andConsistency (%)
Supposedly, the higher the cement consistency will
make cement paste to flow better. But as seen in Fig
2, when POFA is partially replace with cement, it
tends to reduce the flow. Basically, this is due to the
POFA that’s absorb the water in the system. But, thepresence of Sodium Hydroxide tends to increase theflow due to its ability to disperse the POFA cement
particle. On the other hand, Sodium Silicate reacts ina different way. The presence of Sodium Silicate
tends to make the paste less flowable. This isprobably because Sodium Silicate might haveincreased the hydration process immediately it has
been mixed with POFA cement.

Percentage of Water (%)

Setting Time

50

5P

5P5.2H 5P5.2S

Percentage of Water (%)

Based on the data obtained, a few discussions havebeen made.

OPC

5P

Flow (%)

DISCUSSION

400
350
300
250
200
150
100
50
0

0
OPC

Table 4: Flow Table Test Result

Percentage of Water (%)

Percentage of
POFA (%)
Amount of
Water (ml)OPC
5P
5P5.2H
5P5.2S

Weight of
Cement (g)Design Mix

SEE - Bangkok, Thailand, Nov.11-13, 2019

CONCLUSIONSFresh properties have been the focus of this researchdue to its applications in repairing and rehabilitation
works. POFA and sodium-based solution are used toenhance the fresh properties in order for them to fit
for their purpose. Based on all the test conducted anddata obtained, below are the findings;

5P5.2H 5P5.2S

SamplePercentage of Water (%)
final setting time1.

initial setting time911

In consistency test, sodium silicate sample
shows to have high water percentage, which

SEE - Bangkok, Thailand, Nov.11-13, 20192.

3.

[2] M. T. Carrasco, “Alkaline activation of different
aluminosilicates as an alternative to Portland
cement : Alkali activated cements or ... Alkaline
activation of different aluminosilicates as analternative to Portland cement : alkali activatedcements or geopolymers La ac,” no. August, pp.
4–12, 2017.
[3] S. V. Joshi and M. S. Kadu, “Role of Alkaline
Activator in Development of Eco-friendly Fly
Ash Based Geo Polymer Concrete,” Int. J.
Environ. Sci. Dev., vol. 3, no. 5, pp. 417–421,
2012.
[4] K. Wi, H. S. Lee, S. Lim, H. Song, M. W. Hussin,
and M. A. Ismail, “Use of an agricultural byproduct, nano sized Palm Oil Fuel Ash as asupplementary cementitious material,” Constr.
Build. Mater., vol. 183, pp. 139–149, 2018.
[5] H. M. Hamada, G. A. Jokhio, F. M. Yahaya, A.
M. Humada, and Y. Gul, “The present state of theuse of palm oil fuel ash (POFA) in concrete,”
Constr. Build. Mater., vol. 175, pp. 26–40, 2018.
[6] N. F. Imran, M. N. Hasri, N. A. K. Fitri, D. Hasan,
and M. Z. Ramli, “Effects of palm oil fuel ash( POFA ) towards consistency and setting time
properties of concrete Effects of Palm Oil FuelAsh ( POFA ) Towards Consistency and Setting
Time Properties of Concrete,” vol. 020035, no.
October 2018, 2020.
[7] G. F. Huseien, M. M. Tahir, J. Mirza, M. Ismail,K. W. Shah, and M. A. Asaad, “Effects of POFA
replaced with FA on durability properties of
GBFS included alkali activated mortars,” Constr.
Build. Mater., vol. 175, pp. 174–186, 2018.
[8] O. A. Abdulkareem and M. Ramli,“Optimization of Alkaline Activator Mixing andCuring Conditions for A fly Ash-BasedGeopolymer Paste System,” Mod. Appl. Sci., vol.
9, no. 12, p. 61, 2015.
[9] A. M. Ifrah Habib Lone, Javid Ahmad, Syed
Mohammad Jasim, Mintazir Ali, Mushtaq
Ahmad Khan, and Amir Hussain Malik,“Experimental Study of Effect of Sodium
Silicate (Na2Sio3) on Properties of Concrete,”Int. J. Civ. Eng. Technol. , vol. 6, no. 12, pp. 39–
47, 2015.
[10] A. R. M. Ridzuan, M. M. Al Bakri Abdullah, M.
F. Arshad, M. F. Mohd Tahir, and A. A.
Khairulniza, “The Effect of NaOH Concentration
and Curing Condition to the Strength andShrinkage
Performanceof
Recycled
Geopolymer Concrete,” Mater. Sci. Forum, vol.
803, no. August 2014, pp. 194–200, 2014.

is 38.8% compared to OPC which is 29.8%
in order to achieved standard consistency.
This is due to the fast hydration reaction
between the sodium silicate and the cement
when they are in contact.
In both initial and final setting time test,
sample with sodium silicate activator shows
to have fast setting time compared to theother 3 samples with a reading of 58 and 62
minutes respectively. Compare to OPC,
sample with sodium silicate has a decrementof 67.41% in initial setting time and 78.76%
decrement in final setting time. Since there
is fast hydration process after the activator
mixed with the cement, therefore this is
expected to happen. Fast setting happens
when higher rate of hydration occurs.
However, fast setting result in poor
workability over time. In this case, sodiumhydroxide tends to have better workability
since it has higher initial setting time.
In flow table test, the presence of POFA in
the paste stun the flowability where the flow
percentage recorded is 59.80% compare to
OPC with 69.28%. However, when POFA
cement is reacted with Sodium Hydroxide, it
improves the flowability even more compare
to OPC with a value of 112.09%. However,Sodium Silicate presence in POFA cement
tends to decrease the flow with a reading of
0.33% flow compare to OPC.

Based on the findings above, it is concluded that theuses of sodium silicate as activator is suitable to beuses as external repairing work in need of immediate
operation. It can be used to seal cracks. However, forinternal repairing like cracks filling, sodiumhydroxide activator is suitable since it has better
ability to flow into the cracks. Other than that, the useof sodium-based solution also proves to improvecertain properties of the POFA cement paste.
ACKNOWLEDGMENTS
I would like to take this opportunity to express mygratitude and most sincere thanks to my supervisor Dr.
Muhd Norhasri Bin Muhd Sidek for guiding me
throughout this research. I also would like to thankthe technicians for their involvement in heavy
structure laboratory. Many thanks to my friends andfamily for supporting me mentally in order for me tocomplete this research.
REFERENCES[1] A. S. M. Abdul Awal and M. Warid Hussin,“Effect of palm oil fuel ash in controlling heat ofhydration of concrete,” Procedia Eng., vol. 14, pp.
2650–2657, 2011.
912

SEE - Bangkok, Thailand, Nov.11-13, 2019[11] Y. Huang and Z. Lin, “Effect of sodiumhydroxide on the properties of phosphogypsum
based cement,” J. Wuhan Univ. Technol. Mater.
Sci. Ed., vol. 25, no. 2, pp. 342–345, 2010.
[12] B. Bahadure and N. Naik, “Effect of Alkaline
Activator on Workability and Compressive

Strength of Cement Concrete with RHA,” Int. J.
Comput. Eng. Res., vol. 03, no. 5, 2013.
[13] D. Mujah, “Compressive strength and chloride
resistance of grout containing ground palm oil
fuel ash,” J. Clean. Prod., vol. 112, pp. 712–722,
2016.

913

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ANALYSIS OF THE PERFORMANCE AND ELEMENTAL ANALYSISON LIME ACTIVATOR POFA
Nuradila Izzaty H1, Aidan N1, Muhd Norhasri M.S2, Sharifah A2
Student, Faculty of Civil Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor,
Malaysia; 2Lecturer, Faculty of Civil Engineering, Universiti Teknologi MARA, 40450 Shah Alam,
Selangor, Malaysia
1

ABSTRACT
Utilization of waste products by replacing and addictive in cement is growing robustly in the constructionindustries in order to give a result of high strength of concrete especially by using Supplementary Cementitious
Material (SCM) such as Rice Husk Ash (RHA), Slag (SG) and Palm Oil Fuel Ash (POFA). An experimental study
is done on the cement paste incorporating Palm Oil Fuel Ash (POFA) and lime activator solution to assess on its
performance and elementary analysis for development of aging 1, 3, 7 and 28 days. The 50 mm x 50 mm x 50 mm
cube specimens were cast by partially replacing cement with 5% of POFA as pozzolons and partially replacing
water with lime activator, with ratio of water to lime activator, 1kg to 200ml. It was observed that cube specimens
with 5% partial replacement of cement with POFA with the inclusion of lime activator give contribution on highelement of calcium that gives a result on fast hardened cement paste with an adequate compressive strength which
can be beneficial on patching and repairing concrete with demand on time constraint in the construction industries.
Keywords: Lime activator; Compressive strength; Elementary analysis; Repairing

framed in Ninth Malaysian Plan (RMK-9), palm oil
also has is export worldwide as Malaysia is now
aiming on biotechnology industry which estimated togenerate improved quality of agriculture products[3].According to study by Mohd Hilton Ahmad &Noor [4] , the industrial sector in Malaysia has
produced huge number of waste which more than 10
million ton per year. Waste such as POFA, rice husk
and fly ashes are the most interest waste to be study
among engineers and scientist. The waste can bereuse in construction material as pozzolans.
Pozzolans is a siliceous or siliceous and aluminous
material when the particles react with the calcium
hydroxide from the cement and produce cementitious
properties [4]. Several studies have done on the usesof pozzolans as cement replacement in concrete
improving on the construction material and encounter
waste disposal problem.

INTRODUCTION
Urbanization worldwide has make cement
standout as one of the significant building material
among other in construction industry. Cement
properties that versatile and durable makes it theutmost sustainable choice for both residential andcommercial construction. However, the cement
production gives negative impact to the environment
which releases greenhouse gas emissions both
directly through calcination process and indirectly
produced by burning fossil fuels to heat the kiln. As aconsequence, CO2 emissions cause harm and pollutethe environment. Sooraj VM [1] has states that 5%from total amount of each ton of cement production
has release CO2 emission to the atmosphere and byimproving on the production process in cement
manufacturing can reduce the emission of CO2.
Reducing the CO2 emissions from the calcination
process in the cement production means looking to amaterial that having the same properties as cement.
Environmental have concern on the huge amount of
CO2 that have been release from the cement
manufacturing that produce expanding widely andthis lead an enthusiasm the study on the field of
supplemental cementitious materials (SCMs) with aparticular ultimate objective to decrease the amountof cement in the concrete production [2].

Palm Oil Fuel Ash (POFA) is the ash that a
product from burning of palm oil husk and palm
kernel shell in palm oil mill boiler [5]. POFA ashes
are usually disposed with no commercial as the return
effect on the environmental pollution. With thecontribution of POFA in concrete, the disposal effectsof this waste are reducing. In addition, the uses of
POFA as a supplementary cementing material inconcrete reduces the amount of cement used andmakes the concrete mixtures to be more economical.

Palm oil production gives a big contribution ineconomy of Malaysia as the product comes as thesecond world's largest producer after Indonesia. As

However, the addition of POFA with alkaline
based in the cement paste have enhance the cement914

SEE - Bangkok, Thailand, Nov.11-13, 2019

properties. Due to high content of silicon dioxide andcalcium oxide in POFA, the concrete strength anddurability can be affected [6]. The presence ofalkaline activator gives effect on the polymerizationin the pozzolanic materials [7]. Silicate, carbonate,
and hydroxide, sulphate forms of sodium andpotassium ions are some of the alkaline activators that
commonly used. However, sodium hydroxide andliquid sodium silicate is a choice of alkaline activator
for a geopolymer material [8]. This research wasundertaken to analyses the performance and theelemental analysis on Lime activator POFA.

Raw material
Water
Normal tap water is use in this study in theconcrete mix design.
CementOrdinary Portland cement (OPC) obtained from
Tasek Corporation Sdn. Bhd. was used in this study.
Due to the replacement of cement with POFA, eachmixing used different weight of cement. The
percentage of POFA used for this procedure is 5%.

METHODOLOGY

Mixing, Handing a test on compressive strengthand elemental analysis of cement paste.

Cement Paste Preparation
For this study, cement paste is prepared consist of
OPC as control samples, 5PP5.2SH which is 5%
replacement of cement with POFA and replacementof water with ratio 1kg: 200ml with sodiumhydroxide, and 5PP5.2S which is 5% replacement of
cement with POFA and replacement of water withratio 1kg: 200ml with sodium silicate.Table 2.1
shows the design mix for the cement paste
preparation.

Compression test
The performance of the cement paste is observed
through compression test. The compressive strength
results are obtained by breaking down the specimen
into the compression-testing machine cement. BS
18881-108:1983 was used as reference for this study.
XRF Analysis

Table 1: Design Mix Preparation

Material Preparation

The elemental analysis of cement paste estimatedthe proportions of each element present in the sample
were performed with the X-Ray Fluorescence (XRF)
by S1 TITAN Handheld XRF Spectrometer. The
XRF machine uses polarized energy dispersion. The
samples of XRF analysis for each condition were fourcubes, which each cube per trial mix of 0.000125 m3.
Each sample will be analyses for 1, 3, 7 and 28 days.

Palm Oil Fuel Ash (POFA)RESULT AND DISCUSSION

There are four steps on the POFA preparation.
Firstly, is finding the POFA. The POFA that used forthis study is obtained the incinerated palm oil wastefrom United Palm Oil SDN BHD factory at Sungai
Kecil, Nibong Tebal, Pulau Pinang, Malaysia. Next,
to remove the coarse particles as small particle that
useful to get a better control over the filler effect, thePOFA were sieved passing 212μm sieving. Aftersieving, the POFA will be stored inside a clean, dry
and airtight humidity-controlled room inside thelaboratory to ensure its purity. The liquidated POFA
were used in this study, which is the POFA isliquefied using ratio 1kg total volume of water usedin the study with 200ml lime activator solution.

Compressive strength

SampleCement(kg/m3)Water(kg/m3)OPC
5PP5.2H
5PP5.2S

380
360
360

0
20
20

POFA
(kg/m3
)
205
163
163

Lime
Activator(kg/m3)042
42Results of compressive strength of this study wereshown in the figure and table below.

Fig 1: Compressive strength

915

SEE - Bangkok, Thailand, Nov.11-13, 2019

explanation on the lowest compressive strength.
Based on the XRF analysis shown, 5PP5.2H and5PP5.2S consist of high element of calcium compare
to control samples and this this gives an explanationon the result on fast setting cement. However, thehigh element of calcium gives less contribution in
affecting the final binder since the silica element inboth 5PP5.2H and 5PP5.2S decreasing over time.

The compressive strength results for this study are
represented in Figure3.1. The aging effect on the
cement paste plays an important role in compressive
strength. Based on figure 3.1, it shown that incrementin age corresponds to a higher compressive strength.
5PP5.2H give result of high early strength on day 1,
day 3, day 7 and day 14 followed by OPC and
5PP5.2S. The explanation behind this rate is due toadhesion mechanisms between CSH and POFA as
fillers affect a great significance when it employed asa cement replacement. However, OPC tends toincrease its strength on day 28. 5PP5.2S shows thelowest compressive strength compare to others.

CONCLUSIONSThe conclusions drawn are both 5PP5.2H and5PP5.2S contribute to accelerate on setting timecompare to control sample which the cement paste areharden faster. Even though both 5PP5.2H and5PP5.2S gives the lower result on compressive
strength compared to OPC, but it has a moderate
strength that can be used for repairing work such as
patching and grouting. This gives a benefit inconstruction since construction site is normallyhighlighted on the time constraint for repairing work.

XRF Analysis
Based on the XRF analysis on the elemental
analysis, the calcium and silicate element of each
design mix is shown in table 3.3, 3.4 and 3.5.

ACKNOWLEDGMENTS

Table 2: Elemental analysis of Calcium and Silica in
OPC
OPC DAY 1
OPC DAY 3
OPC DAY 7
OPC DAY 28

CaO
65.04
78.69
85.12
60.49

The author would like express profound gratitude
to Dr. Muhd Norhasri bin Muhd Sidek for theirguidance during this study. The author also wishes tothank to technicians of Heavy laboratory Universiti
Teknologi Mara (UiTM) for their kind assistance inthis research.

SiO2
23.38
34.25
24.52
26.63

REFERENCES
Table 3: Elemental analysis of Calcium and Silica in
5PP5.2H
5PP5.2H DAY 1
5PP5.2H DAY 3
5PP5.2H DAY 7
5PP5.2H DAY 28

CaO
74.31
75.83
87.29
91.31

[1] Sooraj VM, “Effect of Palm Oil Fuel Ash(POFA) on Strength Properties of Concrete,” Int.
J. Sci. Res. Publ., vol. 3, no. 6, pp. 2250–3153,
2013.
[2] N. M. Altwair, S. Kabir, and W. Brameshuber,“Palm Oil Fuel Ash (Pofa): an EnvironmentallyFriendly Supplemental Cementitious Material
for Concrete Production,” Int. Rilem Conf. Mater.
Sci. (Matsci), Vol Iii, vol. 77, pp. 113–126, 2010.
[3] V. S. Ahamed and A. Pradesh, “STUDY OF
STRENGTH OF CONCRETE WITH PALM
OIL
FUEL
ASH
AS
CEMENT
REPLACEMENT,” vol. 7, no. 3, pp. 337–341,
2016.
[4] M. H. Ahmad and N. M. Noor, “Chemical Attackof Malaysian Pozzolans Concrete,” pp. 11–24,
2009.
[5] S. K. Nguong and A. S. M. A. Awal, “FUEL
ASH ( POFA ) CONCRETE A SHORT-TERM
INVESTIGATION ON HIGH VOLUMEPALM OIL FUEL ASH ( POFA ) CONCRETE,”
2010.

SiO2
25.23
31.83
28.72
25.24

Table 4: Elemental analysis of Calcium and Silica in
5PP5.2S
5PP5.2S DAY 1
5PP5.2S DAY 3
5PP5.2S DAY 7
5PP5.2S DAY 28

CaO
78.44
87.41
87.52
93.89

SiO2
9.88
3.18
3.79
0.31

From results, we can see that Calcium element
increase over time for 5PP5.2H and 5PP5.2S.
However, the Silica element for OPC and 5PP5.2H
give high result on day 1 and increase on day 3,
decreasing from day 7 to day 28. Silica element for
5PP5.2S is decreasing over time as this gives an
916

SEE - Bangkok, Thailand, Nov.11-13, 2019[6] K. Wi, H. S. Lee, S. Lim, H. Song, M. W. Hussin,
and M. A. Ismail, “Use of an agricultural byproduct, nano sized Palm Oil Fuel Ash as asupplementary cementitious material,” Constr.
Build. Mater., vol. 183, pp. 139–149, 2018.
[7] U. J. Alengaram and S. M. Alamgirkabir,“Engineering properties of oil palm shell andpalm oil clinker based geopolymer concrete,” vol.
38, pp. 34–48, 2015.

[8] D. Hardjito, S. E. Wallah, D. M. J. Sumajouw,
and B. V. Rangan, “On The Development of Fly
Ash-based Geopolymer Concrete On theDevelopment of Fly Ash-Based,” no. October,pp. 467–472, 2015.

917

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

PHYSICAL AND CHEMICAL PROPERTIES OF WATER:
CASE OF TAAL LAKE, PHILIPPINES

1,2

Merlita C. Medallon1, Ed.D. & Enrico Garcia2
Faculty, Lyceum of the Philippines University Laguna, Philippines

ABSTRACT
Water quality can affect the ecosystem at several trophic levels. It is very important for an ecosystem to have
healthy water bodies as lives of aquatic species depend upon them. Taal, with a small lake located in the southernpart of Luzon in the Philippines is teeming with aquatic resources, yet it is observed that its water quality isdeteriorating. The lake is surrounded by several municipalities with tributaries contributing to its quality. This
study evaluated Taal lake ecosystem in six sample sites in terms of physical and chemical attributes utilizing
secondary data obtained from the Department of Environment and Natural Resources (DENR). Mean values ofpH, temperature and total soluble solids (TSS) were within the standards set by the agency. However, there wasa slight increase in dissolved oxygen (DO) and a low biological oxygen demand (BOD). There is high nitrogenand heavy metal contamination with one highly contaminated site. This was attributed to high municipal andkitchen waste disposal and high amounts of fertilizers used in fields. Taal lake aquatic ecosystem can be classified
as severely polluted based on the chemical parameters. Nitrate, phosphate, oil and grease, pH, temperature andDO levels vary significantly from site to site. Levels of arsenic, chromium, TSS and BOD do not show any
significant difference among the sites.
Keywords: Chemical, Physical, Quality, Taal Lake, Water
The resource is used for aquaculture, recreation,
tourism, navigation, and water source for Tagaytay.
The Lake is known for its ecosystem that supports adiverse aquatic fauna comprising of both freshwaterand marine species. Records of fish found in the lake
by Albert W. Herre revealed 32 families of varied
finfish resource, consisting of about 100 species, most
(76 species) of which are migratory (BFAR Profile).
In 2016, Taal Lake has a total fish production of
80,690MT, a majority of which comes from fish cage
production.
A total number of thirty-seven (37) side streams
surge into the Lake and its only outlet is the Site F [1].
The lake quality is determined by the effluentsdischarge in the tributaries. This is turn characterizes
the aquatic conditions where fishes and otherfreshwater lake organisms live.
Global climate change is modifying freshwaterproductivity by changing the global area of theseecosystems by increasing their temperature andrevising stratification. Extreme heating of surface
waters between 30° N and S, associated with the highheat of vaporization of water, will result into rise insalinity of inland waters at low latitudes and loss of
productivity of key organisms [2].
Water quality monitoring can help researchers
predict and learn from natural processes in theenvironment and determine human impacts in an
ecosystem. These measurement efforts can also assist
in restoration projects and ensure that environmental
standards are being met. Human intervention also has
noticeable effects on water quality. Activities that

INTRODUCTION
The health condition of every human is co-related
to the environment or surrounding where he or she
lives. With the rapid urbanization, increasing
population, human and industrial activities and moreso the extreme climatic condition, the world has seensome drastic changes to acknowledge that ourenvironment is severely affected. Lakes and otherfreshwater ecosystems provide essential services tothe society. Most important of these services is fresh
drinking water, power generation, water for bathing,sites for recreational activities and important fisheries.
One of the most important body of water in thesouthern island of Luzon in the Philippines is Taal
Lake. Taal Volcano, a famous site is seated in the
middle of the Taal Lake. Taal Lake, formerly known
as Bombon Lake, is also the deepest and the thirdlargest Lake in the Philippines. Taal Lake is locatedinSouthern
Luzon,
Batangas
Province,(approximately 60 km. south of Manila) issurrounded by nine (9) towns and two (2) cities
translating into 287 barangays. It has a total area:
24,356 hectares, with a circumference of 120
kilometers; a maximum depth of 198 meters or an
average of 60 meters (PCCARD, 1981) and ashoreline of 82,500 m.
The lake is a major source of livelihood for mostof the local dwellers. Fishing as one of the main jobs
provides for the living of the community. Lake
fisheries provide livelihood to around 20,000
fisherfolk.
918

SEE - Bangkok, Thailand, Nov.11-13, 2019

harm the environment directly by severely polluting
them like discharge of domestic, industrial, urban andother wastewaters into the water course, whether
intentional or accidental, and the spreading ofchemicals on agricultural land in the drainage basin
are the most obvious anthropologic destruction
brought to the aquatic ecosystem. Any significant
changes to the natural water quality are usually
disruptive to the ecosystem [3].
The quality of a lake’s water depends mostly on
their physical, chemical and biological well-being.
The degradation of water quality can affect not only
the aquatic life but the surrounding ecosystem as well.
Thus, a thorough assessment of water quality is an
integral part of the lake’s environmental monitoring.
In this research, water quality was determined byreviewing the physical and chemical properties ofwater. The physical parameters such as temperature,
pH, total dissolved solids, dissolved oxygen andbiological oxygen demand was evaluated. Chemical
properties include concentration levels of arsenic,
chromium, nitrates, phosphates, oil and grease.
The temperature of water has less to do with thetype, and more to do with the depth of water. Smaller
bodies of water, like ponds, lakes and rivers, fluctuate
more easily. This affects what kind of life can live
there [4]. The significance of excessive turbidity inwater on fish and other aquatic life begins by altering
the temperature structure of lakes. Bottom-level
temperatures are usually lower in turbid lakes orponds than in clear ones. Generally, in many lakes,
lower temperatures mean lower productivity.
Turbidity also prohibits with the piercing of light.
This reduces photosynthesis and thereby decreases
the primary productivity upon which the fish foodorganisms survive. As a result, fish production is
reduced. Also, by prohibiting light, turbidity makes it
difficult for aquatic life to find food. Adversely, someorganisms may be similarly protected from predators[5].
In streamlets, increased sedimentation andsiltation can take place, which can result in
degradation to habitat areas for fish and other aquatic
life. Particles also supply attachment places for otherpollutants, notably metals and bacteria. For thisreason, turbidity readings can be used as an indicatorof probable pollution in a water body. The particles
of turbidity provide "shelter" for microbes byminimizing their subjection to attack by antiseptics.
Microbial attachment to particulate material has been
contemplated to aid in microbial existence [6].
pH is a measure of how acidic/basic water is. It
ranges from 0 - 14, with 7 being neutral. Total
dissolved solids (TDS) comprise inorganic salts(principally calcium, magnesium, potassium, sodium,bicarbonates, chlorides, and sulfates) and some small
amounts of organic matter that are dissolved in water.
Dissolved Oxygen is the amount of gaseous
oxygen (O2) dissolved in the water. Oxygen enters

the water by direct absorption from the atmosphere,by rapid movement, or as a waste product of plant
photosynthesis. Water temperature and the volume ofmoving water can affect dissolved oxygen levels.
Biochemical Oxygen Demand is an important water
quality parameter because it provides an index toassess the effect discharged wastewater will have on
the receiving environment. The higher the BOD value,
the greater the amount of organic matter or “food”
available for oxygen consuming bacteria.
Arsenic, although being toxic and probably
carcinogenic when exposed through drinking water,
has received very little attention in these past years.
Potential pollution hazard of arsenic comes fromingesting it rather than eating arsenic-containing
aquatic organisms. Although arsenic is greatly
concentrated in aquatic organisms, it is evidently not
progressively concentrated along a food chain.
Additionally, arsenic in flesh has low toxicity, in
general. Use of arsenic, the burning of fossil fuels,
increased erosion of land, and the mining andprocessing of sulfide minerals have increased theamount of arsenic entering the lakes [7].
A range of 10 to 70 ppm arsenic has beencommonly detected in household detergents and presoaks. Arsenic is present in detergents in arsenate
state (V) and not in arsenide (III), a toxic form that is
prepared for pesticide-use available commercially.
Chromium (VI) is a well-known priority polluting
as well as highly toxic heavy metal. Maximum
allowable concentration of chromium (VI) in
drinking water is 0.05 mg/L [8]. Hexavalentchromium forms many soluble salts that can enter
body membranes and induce a toxic response. Rats,
mice, beagle, aquatic plants and fish species, all areaffected adversely because of Cr (VI) pollution [9].
Nitrate is colorless, odorless and tastelesscompound present in water. Common sources ofnitrogen are fertilizers, manure, municipal
wastewater, sludge, animal feedlots, septic systems,
etc. Purification of nitrate-contaminated water can bedone by treatments of distillation, reverse osmosis,
ion-exchange, blending, charcoal filters and watersofteners. Other health factors such as diarrhea andrespiratory disease have also been associated withhigh nitrate levels in water [10].
Discharge of organic matter to water is one of the
major sources of nutrients to seep through, since
aerobic decomposition of such organic matter can
result in release of phosphates, nitrates, etc.,
especially on domestic sewage containing highphosphate concentrations coming from detergents[11]. Agricultural run-offs and food-processing
effluents are high in phosphate. Water analysis ofwater entering and leaving nine commercial trout
farms three times during summer showed thatconcentrations of ortho-phosphate in the water may
increase substantially during passage through thefarm. Hence, magnetic separation can be applied to919

SEE - Bangkok, Thailand, Nov.11-13, 2019

all waterborne contaminants and removing thedissolved orthophosphate from the aqueous slurry[12].
The main cause of oil and grease water pollution
is anthropologic activities. Water bodies situated nearcolleges, parks and other public institutions had highconcentration of oil and grease particles in water due
to drainage of cafeteria which also cause BOD and
TSS value to be higher than normal in the lake. This
has now been declared as one of the main factors thatcause mass fish death in lake ecosystems [13].
It is important here to note that oil which forms asurface film on the river can coat plants and animals
cutting or reducing their supply of oxygen from theabove lying atmosphere. Transmission of light isaffected due to the formation of oil film that floats
above the body of water. This disturbs thephotosynthesis process of aquatic plants. In animals,
insulating properties of furs and feathers are affected.
Mobility is also reduced due to increased stickinessonce the oil starts to dry [14]. Eventually, in mostcases, this leads to death. Oil bio accumulates in thehigher animals and further enters the food chain.
Detergents create frothing and can harm invertebrates
and fish, as they are a major source of phosphates.
Moreover, petroleum or grease spilled over water also
produces chemicals that are extremely harmful formarine animals[14].
With the foregoing significance of Taal Lake tothe community, it is but noting that quality of its water
be monitored. The Department of Environment andNatural Resources (DENR) and the Bureau ofFisheries and Aquatic Resources (BFAR) are the twomain government agencies that look after the qualityof the Philippine waters. Water monitoring isregularly done to ensure preservation of the water
quality and safety of the consumers. The study
summarizes the physical and chemical properties of
Taal Lake from six different sites where a comparison
is also done.
Natural resources are the important wealth of ourcountry, and water is one of them. Water is a wonderof nature. “No life without water’’ is a common
saying given the fact that water is the one of thenaturally occurring essential requirement of all life
supporting activities [15]. Impurities present in water
reduce its quality and its use. This would affect thehealth of both cultured and wild species as water
quality is a major factor controlling them. The qualityof water can easily be described by the physical,
chemical and biological parameters or characteristics[16]. Physio-chemical variables are importantenvironmental factors of water in which all biologicalcommunities live in association with each other [17].

and chemical properties of water from different sites
and compare them with the acceptable standards. The
physical properties of the water include pH,
temperature, total soluble solids, dissolved oxygenand biological oxygen demand. The chemical
properties include Arsenic, Chromium, Nitrates,
Phosphates, and Oil and Grease were also presented.
A comparative analysis of the physical and chemicalparameters among sites was done.
METHOD
This study utilized a descriptive research design
aimed to present the concentration level of different
chemicals in the locality of Taal Lake’s aquatic
ecosystem. The study used a mixed method which
consists of both quantitative and qualitative data.
Secondary data collected from 2013 to 2018 by the
Department of Environment and Natural Resources[DENR] in Site A, Batangas was used in the analysis.
Water samples were taken from six different
sample sites within the vicinity of Taal Lake. Taal
Lake is the third largest lake present in thesouthwestern region of Luzon in the Philippines. It
occupies a volcanic crater with a maximum width of
24 kilometers and is 3 meters above sea level. At least
four samples per site was collected for physical andchemical analysis.
Water samples were collected and placed in 1L
sample in PET bottle and 1L sample in wide mouth
glass bottle. Samples were immediately taken to thelaboratory located in local BFAR office for analysis.
Some data such as temperature and pH were collectedon site.
Water analysis was performed following theprocedures in the Standard Methods for the
Examination of Water and Wastewater, 22nd ed,
APHA, AWWA, WEF, Washington DC 2012.
Standard values used for comparison is contained in
DAO No. 2016-08 Water Quality Guidelines andGeneral Effluent Standards of 2016. Physicalparameters measured were pH, temperature, totalsoluble solids, dissolved oxygen and biologicaloxygen demand. Chemical parameters measured
were arsenic, chromium, phosphate, nitrate and oil
and grease.
All chemical tests collected were compared to thestandard parameter table from the Bureau of Fisheries
and Aquatic Resources (BFAR). Weighted mean has
also been used to identify the average value ofdifferent study sites.
RESULTS AND DISCUSSION
Physical Properties of the Lake Water.
Physical water quality parameters such as pH,
temperature, total soluble solids and dissolved
oxygen fall under control set by DENR-EMB
whereas levels of biological oxygen demand fall short

OBJECTIVES OF THE STUDYThis study aimed to present the water quality of
Taal Lake in the Philippines by analyzing the physical920

SEE - Bangkok, Thailand, Nov.11-13, 2019

to the standards set.
The pH concentration levels were found highest
in Site F is more than 8 whereas lowest in Site B
counting some less than 7. All sites show acceptable
pH levels. Changes in the pH value of water areimportant to many organisms. Most organisms haveadapted to life in water of a specific pH and may die
if it changes even slightly. This is especially true ofaquatic macroinvertebrates and fish eggs and fry. The
pH is a critical factor determining the health of awaterway. The factors that control it are obviously
complicated. As with many environmental concerns,
we need to be aware of the implications of any
impacts we have upon the environment. [18].
Changes in pH is caused by natural conditions(especially in swamps), dumping of waste (batteries)
and farm runoff (lime). Most aquatic life cannot
withstand water outside the optimum pH thus
resulting in death.
Highest mean temperature recorded was around27.6 from Site F while lowest was less than 26 from
Site B. Site F being the only outlet of the lake and isa large stream, has a larger surface area which also
encourages higher temperature compared to othersites [19]. Elements such as sunlight, heat transferfrom the atmosphere, stream confluence and turbidity
affect water temperature. Shallow and surface waters
are more easily influenced by these factors than deep
water.

Table 1. Physical Property Measurements

Physical parameters

Standard Values by
DENR-EMB (forclass B)

Sample sizepH
Temperature
Total Soluble
Solids

6.5 – 8.5
24-27 degree C
Not more than 30%
increase

Dissolved Oxygen
Biological Oxygen
DemandSite A

Site B

Site C

Site D

Site E

Site F

7
7.25
27.35

5
6.97
25.92

13
7.25
26.47

4
7.36
25.96

5
7.51
26.96

4
8.23
27.58

22.48

11.28

31.48

29.56

32.35

10.31

5(minimum)

4.41

3.95

6.51

5.7

6.66

6.43

5(minimum) 10(maximum)

8

2.95

3.26

3.33

2.18

3.19

Site E, Site C and Site F had most levels of meandissolved oxygen (DO) which is more than 6 whereas
Site B was lowest falling few short of level 4. Just as
we need air to breathe, aquatic organisms needdissolved oxygen to respire. It is necessary for thesurvival of fish, invertebrates, bacteria, andunderwater plants.
DO is also needed for the decomposition oforganic matter. Water with high concentrations of
dissolved minerals such as salt will have a lower DO
concentration than fresh water at the same
temperature. Low dissolved oxygen (DO) primarily
results from excessive algae growth caused byphosphorus. As the algae die and decompose, theprocess consumes dissolved oxygen [22]. All oursites except site B have good levels of dissolved
oxygen which is healthy and no sign of threat.
Oxygen enters the water by direct absorption from theatmosphere, by rapid movement, or as a waste
product of plant photosynthesis. Water temperatureand the volume of moving water can affect dissolved
oxygen levels [23]. Dissolved Oxygen is foundabundant from each sample that showcases thestandard of ecosystem persisting in the premises is in
healthy condition.
Ideally, the average level of DO desirable foraquatic habitat is 9.0 ppm (parts per million). This

provides good habitat for abundant fish population.
Below 9ppm but higher than 7 ppm supports growth
and aquatic activities while 5 ppm can still support
spawning. When the level of DO is below 5, thecondition becomes stressful for aquatic animals andthere is about 12 to 24 hours of tolerance for growth.
Below 3 ppm could hardly support fish population.
Site A region of Taal Lake has almost double
levels of BOD compared to others and highest at 8
whereas lowest stands in Site E levelling a few morethan 2. Oxygen consumption is affected by a numberof variables: temperature, pH, the presence of certain
kinds of microorganisms, and the type of organic andinorganic material in the water [24]. When the water
body has high BOD, aerobic bacteria will utilize theavailable DO of water. In case of excessive BOD
there will be deficiency of DO and water will be inanaerobic condition resulting in mortality of living
aquatic organisms; release of ammonia, methane,
CO2 etc. In absence of oxygen, anaerobic bacteria
become active. When BOD value is medium, water
will possess excessive nutrients causing algal bloom.
Such condition is again dangerous because during day
time water will be supersaturated with oxygen (due tophotosynthesis in presence of sun light), but at latenight DO may be zero or close to zero. This is
primarily due to utilization of oxygen for respiration
921

SEE - Bangkok, Thailand, Nov.11-13, 2019by plants and animals (without any production ofoxygen in absence of sunlight). For this purpose,
BOD must be maintained up to certain level in any
surface waterbody [25]. All other sites except site A
falls below the minimum requirement for BOD.
Somehow the physical factors of the Lake Taal
have a corresponding influence on each other. Higher
amounts of total dissolved solids will lower thetemperature because these solids won’t allow sunlightto reach enough depth of the water body. The physicalproperties do not correlate even if they are from samestructure since its properties depend upon different
factors like the surrounding it is situated or humaninteraction around. Temperature and pH levels also
should be suitable for the life survival existing in thewater body with abundant supply of Oxygen.
According to Galera & Martinez [26], the water
surface temperature, pH, total dissolved solids, totalsuspended solids, color and dissolved oxygen of Taallake in 2009 conformed the class C water standards(DENR AO 34, 1990) and was therefore safe foraquaculture use.
Chemical Parameters of the Lake Water. In
Site A, the levels of arsenic, chromium and nitrogenare found to be over the standard limit set by BFAR
with nitrogen levels being almost 6 times higher than
the standard limit. The levels of phosphorous, and oil.
Table 2. Chemical Property Measurements
Standard
Chemical parameters
ValuesSite A
Sample sizeand grease are within the standard limit but
dangerously close to the threshold value. A sampling
point has given output of 180 mg/L nitrogen while
7mg/L is the standard set. A sample point shows
nitrogen levels of 66mg/L.
Highernitrogen levels
mean possible
overstimulation of algae and aquatic plants which
could lead to lack of oxygen for fishes. In Site B,
every chemical parameter was more or less near the
standard limits set by BFAR. Only one sample fromthe five sampling points had minimal nitrogen
pollution. This means that there will soon be an algal
bloom and possible eutrophication, if not taken careof. Nitrogen in water comes mainly from fertilizers
and insecticides.
Site C shows very unsatisfactory data results with
only phosphorous levels being within tolerable
standards while all other chemical parameters
exceeded the standard limit. Nitrogen pollution was
in excess with samples from two sampling points
showing levels higher than 30 mg/L. Heavy metal
pollution of arsenic and chromium show heavy
unregulated industrial discharge which may be adetermining source in Site C. Nitrogen in water
comes from kitchen wastes and fertilizers and causes
eutrophication in water causing death of the lake, if
not controlled soon enoughSite B

Site C

Site D

Site E

Site F

7

5

13

4

5

4

Arsenic
Chromium
Nitrogen as NO3.01 mg/L.001 mg/L
7 mg/L

0.025
0.029
41.813

0.03
0.03
3.94

0.028
0.034
18.571

0.021
0.023
7.149

0.024
0.052
9.277

0.025
0.024
375.05

Phosphorous as PO4
Oil & Grease

0.5 mg/L
1 mg/L

0.435
0.939

0.245
1.46

0.084
1.519

0.416
0.781

0.072
1.62

0.587
1.081

Site D samples show heavy metal pollution withhigher levels of arsenic and chromium. Otherchemical parameters (nitrates, phosphates, oil andgrease) are found to be within standard limits. The
levels of arsenic and chromium are not dangerously
high as seen in previous sample sites, but still, any
situation can amplify if not taken seriously. Thismeans industrial effluents loom in large amountpolluting waters near Site D. Constant erosion of
volcanic rocks with arsenic and chromium content isanother possible source.
Site E is another problematic place as arsenic,
chromium, nitrate, and oil and grease levels are all
found to be above the standard limit with only
phosphorous being within tolerable limit. Most
nitrogen and chromium outputs are found from twoof the five sampling points. Nitrogen can cause
eutrophication and lack of oxygen. Their possible
source can be pesticides and insecticides. Chromium

excess happens when volcanic rocks erode and heavy
industrial effluents are dumped into the lake water.
Site F had all other chemical parameters in
optimum levels except nitrogen. In fact, nitrogen
pollution looms at large as values reach as high as
592mg/L (standard is 7mg/L) which indicates highlevel of eutrophication. Heavy use of fertilizers andpesticides in the area around Site F and domestic
sewage could be the reason for excess nitrogen.
Highest amount is found in one of the four sampling
points (592mg/L), followed by 487mg/L and
420mg/L found at the two other sampling points.
The standard limit for arsenic set by BFAR is 0.01
mg/L. All the sample sites have higher values (highest
to lowest: Site C, Site B, Site A, Site F, Site E, SiteD) than the standard limit indicating arsenic pollution
in Taal Lake. After Metro Manila, Batangas is known
for being an industrial growth sector in its region. Site
C is known for its booming agriculture and real estate922

SEE - Bangkok, Thailand, Nov.11-13, 2019industries.
Hence, industries can be a major
contributing arsenic pollutant. Arsenics are used inindustrial processes to produce antifungal woodpreservatives, cosmetics, for making residential
structures, playhouses, decks, fences, picnic houses,
insecticides and pesticides [27]. The values, however,
do not show significant differences when comparedamong the sample sites.
Phosphate levels in Taal ecosystem is in better
control with only Site F having levels above standard
limit. Standard value for phosphate is 0.5mg/L. Allother sites have levels lower than that of Site E
showing level of just 0.07mg/L. Taal Lake has manyillegally built fish cages and this cause eutrophication
problem as fishermen would throw nutrients in water
without any regulation. But in the recent times, allillegal cages have been removed but Site F still shows
low amounts of phosphate contamination, possibly
still due to excessive nutrient being laid in water for
fishes [28].
Values for oil and grease vary among sites withhighest value in Site E (1.6mg/L). The standard value
set by BFAR is 1mg/L. Site C had value of 1.5mg/L.
The rest of the sample sites are more or less withintolerable value range, with Site F showing levels of
1.08mg/L, followed by Site A with 0.9mg/L and Site
D with 0.7mg/L. Again, Site C and Site E haveslightly higher levels of oil and grease than thestandard parameter set by BFAR. Sources of oil andgrease are mostly anthropogenic with most oil andgrease accumulating in lakes from residential sewage
drains and dumping of industrial byproducts. The
more people using automobiles and moving
machineries, the more oil and grease are being used,
thus, contribute more to the pollution [29].
All physical attributes of water quality of Taallake were found fit into the criteria set by DENREMB except the balance of Oxygen levels whichwere more than required; hence, lowering biologicaloxygen demand of water. No significant differenceswere found in mean measures of total soluble solids
and biological oxygen demand whereas meanevaluation of parameters such as pH, temperature anddissolved oxygen show notable differences. Based on
the overall results of the study, Taal Lake water canstill be classified as Class B (DENREMB, 2005),
Recreational Water Class I. The classification is thesame with two other river basins in the Philippines(DENR-EMB, 2005). Taal lake aquatic ecosystem
can be classified as severely polluted based on thechemical parameters analyzed in this study. Nitrate,
phosphate, and oil and grease levels vary significantly
from site to site. Values of all other parameters suchas arsenic and chromium do not show any significant
difference. All the sample sites have heavy metal
contamination. Taal Lake shows very high levels ofarsenic and chromium with Site C having highest

arsenic levels and Site E having highest chromium
levels. When it comes to nitrate levels that determine
algal content in a lake, all sample sites, except Site B,
have higher values than the set standard levels. Site F
shows extremely high levels of nitrogen. Phosphatelevels are under control. Site C and Site E also showshigh oil and grease levels. This data indicates highindustrialization in Site C and Site E. A common
contaminant found through this study is nitrogen.
This indicates high municipal waste disposal, kitchen
waste disposal, and high fertilizers used in fields
around Taal Lake.
A major problem that Taal Lake’s ecosystem iscombating is heavy metal pollution. Arsenic andchromium levels are above standard levels in all
sample sites. There are costly methods like ion
exchange and membrane technology but local
communities in developing countries cannot afford it.
Many other alternative methods are available. One of
the suggestions is switching from an arsenic-unsafe
well to an arsenic-safe drinking water source or use
deep tube wells (which are generally arsenic free).
Technologies for arsenic removal include oxidation,
coagulation-precipitation, absorption, ion exchange,
and membrane techniques. There are increasing
number of effective and low-cost options forremoving arsenic from small or household supplies.
Nitrate pollution looms at large in Taal Lake aslevels are extremely high and eutrophication isinevitable. Eutrophication can possibly lead to deathof the precious, endangered, endemic species residing
in Taal Lake due to lack of sunlight and oxygen.
Excess of nitrate also leads to excess oxidation andexcess phosphates. Nitration can be treated byadsorption techniques by using best adsorbent
according to the location [30]. For preventive
measures, nitrogen leaching into water from soil canbe prevented by avoiding over-irrigation as itincreases the chances of nitrate leaching. Upgrading
manure storage sites can reduce manure leaking.
Efforts should be made to reduce the amount of
nitrogen applied to older sites and collect drainage
water instead of allowing it to drain in Taal Lake.
In order to maintain and conserve the condition ofwater in Taal Lake, safety, security, andenvironmental management plan should be carriedout by concerned local government units (LGUs).
This way the best favorable use of the Lake is likely
to be encouraged. Likewise, information campaign on
the protection and preservation of the Lake has to get
in touch with the nearby natives and mountaineers to
reduce the quantity of contaminants in thesurrounding locale.
ACKNOWLEDGMENTS
The researchers would like to acknowledge thePhilippine government agencies that provided theprimary data for the analysis; The Department ofEnvironment and Natural Resource (DENR) and the923

SEE - Bangkok, Thailand, Nov.11-13, 2019

Bureau of Fisheries and Aquatic Resources (BFAR)
both in Region IV-A. register and make payment after
the registration deadline will not be guaranteed that
their papers are included in the proceedings. Try tofollow the reference style below.

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Water quality characterization of varsity lake,
University of Malaya, Kuala Lumpur, Malaysia.
Journal of Chemistry, 7(S1), S245-S254.
[15] Simpi, B., SM Hiremath, KNS Murthy. 2011.
Analysis of water quality using physicochemical parameters Hosahalli Tank in
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D. V. (2010). Analysis of water quality using
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[17] Sharma, R.C., A. Sharma and A. Anthawal.
(2008). Surveying of aquatic insect diversity of
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[18] Scheffer, M. (2004). The story of some shallow
lakes. In Ecology of shallow lakes (pp. 1-19).
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[19] Warner, B., & Breon, S. R. (2004). Temperature
Scales and Absolute Zero. In Cryogenics andFluids Branch.
[20] Zeigler, A. C. (2002). Issues Related to the Useof Turbidity Measurements as a Surrogate forSuspended Sediment. InTurbidity and Other
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[21] Lucas JS, Southgate PC (2012) Aquaculture:
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[22] Katznelson R,2004). Dissolved oxygen
measurement principles and methods. DQMInformation Paper 3.1.1.
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rograms/swamp/docs/cwt/guidance/311.pdf[23] Hargreaves, J. A., & Tucker, C. S. (2002).
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[24] Wetzel, R. G. (2001). Limnology: Lake andRiver Ecosystems (3rd ed.). San Diego, CA:
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[25] Dasgupta M, Yildiz Y (2016) Assessment ofBiochemical Oxygen Demand as Indicator of
Organic Load in Wastewaters of Morris County,
New Jersey, USA. J Environ Anal Toxicol
6:378. doi:10.4172/2161-0525.1000378

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M. A., & Pemsl, D. E. (2011). Technicalefficiency of Genetically Improved Farmed
Tilapia (GIFT) cage culture operations in thelakes of Laguna and Batangas, Philippines.
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Global Environmental Change (pp. 221-229).
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quality guidelines for the management of pond
fish culture. International Journal ofEnvironmental Sciences 3, 1980–2009.
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ecosystems: an Australian perspective.
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(2005). Potential impacts of salinity andturbidity in riverine ecosystems. The State ofQueensland, 72.
[7] Förstner, U., & Wittmann, G. T. (2012). Metal
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SEE - Bangkok, Thailand, Nov.11-13, 2019[26] Galera IC, Martinez FV (2011) Monitoringand evaluation of the water quality of Taal
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Monitoring and evaluation of the water qualityof Taal Lake, Talisay, Batangas, Philippines.
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593330.2012.706646

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DURABILITY STUDY OF MALAYSIA ROCK MASS FORTUNNELLING CONSTRUCTION
RC Omar1, R.Roslan2, INZ Baharuddin3, Hairin Taha4 and Vigneswaran V5
1,2,3,4
Institute of Infrastructure Energy,
5College of Engineering,
Universiti Tenaga Nasional, 43000 Kajang, Malaysia

ABSTRACT
Malaysia is dominated by forested mountains made up of old igneous and metamorphic rocks withcompressive strength less than 50 MPa which are susceptible to weathering which can cause faults, shear zones
and thrust zones. These conditions impose a challenging task for rock tunnel constructions in Malaysia. Rapid
development and population in Malaysia has generated the constructions of many infrastructure and facilities
that include tunnel constructions to facilitate the network system and expand traffic flow. For the safe andeconomical design of tunnels, it is important to assess the strength and behavior of the rock mass to prevent the
ground collapse that can lead to loss of life and property. The main objective of this study is to investigate thedurability of Malaysia Rock Mass for tunneling purposes by using the point load test, direct shear test and slake
durability test. The results of the study showed that the worse weathering grade for Granite rock and SchistPhyllite rock were II and II respectively, with all rocks suitable with durability classification of longer span. This
study concludes the most suitable place at particular rock mass of each rock type based on durability.
Keywords: durability study; rock mass; point load test; direct shear test; slake durability test

conditions unless exposed toward water or climatechanges.
Durability factor for tunneling construction in
Malaysia needs to be considered since Malaysia
rocks narrowed toward igneous and metamorphic
rocks only. This is because most of the sedimentaryrocks in Malaysia undergo deformation orrecrystallization and evolved to metamorphic rocks.
Climate changes were one of the major elements thatcaused irreversible changes in rocks or in otherwords weathering. Weathering effect on the igneousand metamorphic rock in particular place can be
determined by performing study and test on sample
of rocks for ensure that the strength of the rock [68].
Knowledge of rock and the environments inwhich they were formed and the way the rocks
response toward weathering, erosion and tectonic
processes are essential in conducting site
investigation survey especially on rock durability oftunneling [9]. Tunnels will be constructed andmaintained by taking several mitigations to ensure
the tunnel is durable for a long time. The strength ofrock strength can indirectly affect the durability oftunnel. Hence, durability of the rock should be
evaluated prior to the construction of a tunnel byperforming various assessments on the rock itself[10-11].
In this study, laboratory testing such Point Load
Test, Schmidt Rebound Hammer Test, Slake
Durability test and Uniaxial Compression Test were

INTRODUCTION
Rock tunneling can be defined as construction
in a material which cannot be excavated by ordinary
digging tools. In many countries, tunnels wereconstructed to facilitate transportation and traffic
network connection due to rapid population andindustrialization including lack of space [1].
Normally, tunnels were built through mountains toconnect to areas and cities. Malaysia is one of thecountries which embarked on tunnel construction toaddress problems such as traffic congestion andrepeated flooding in the cities [2-3]. Malaysia is a
mountainous country covered mostly by old igneousand metamorphic rocks with compressive strength >50 MPa. However, these rocks suffered withweathering and even earth movement which cause
faults, shear zones and thrust zones.
Rock tunneling has great influence on the
behavior and type of the rock due to weathering,erosion and tectonic processes. In common term,
rocks are described as hard or weak rocks but inengineering term the main classes of rocks aredescribed as igneous, sedimentary and metamorphic
rocks. The difference between hard and weak rocktunneling can be estimated when the rock massstrength is greater than the induced stresses imposedby tunneling [4-5]. The rocks have their own local
weak zones and discontinuity properties. Normally,
weak rock tunneling is hard and its design
construction must be carried out carefully. Hardrocks have no loss of strength on actual or closed
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SEE - Bangkok, Thailand, Nov.11-13, 2019

done to identify the durability of the rocks and theirweathering classification.
Study Area
Two different areas with different rockcharacteristics were selected. Granite rock samples
originally from igneous family were collected fromrock mass of Kajang Silk Highway (KM 17) (Figure
1 and 2) and Schist-Phyllite Rock Mass werecollected from Putrajaya which has metamorphic
rock (Figure 3 and 4).
Fig 4. Samples of Schist-Phyllite Rock Mass

METHODOLOGY
Schmidt Rebound Hammer Test
Schmidt rebound hammer test was done toestimate the unconfined compressive strength andmodulus elasticity of the intact rocks to estimate thestrength of the rocks. It operates by measuring
rebound of the steel hammer mass when propelledwith 0.075 kg.m of energy against the rock surface.
Energy against a rock surface is proportional to thehardness of the material which is related withstrength. Test followed ISRM standard.

Fig.1 Kajang Silk Highway site

Direct Shear Test
Shear strength test is important to assess the
behavior of rock mass. The test was carried out
according to ISRM standard (Figure 5)

Fig. 2 Samples of granite rock mass

Fig.5 Direct shear test apparatus

Point Load Test
Point load test is a tensile based test where
uniaxial compressive strength and modulus ofelasticity are obtained experimentally (Figure 6). It
is a variation of the Brazil tensile strength test. The
point load test is useful to determine the maximum
and minimum strengths which results due to rockFig 3. Putrajaya Site

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SEE - Bangkok, Thailand, Nov.11-13, 2019

anisotropy, such as foliated metamorphic rock. The
test was done following ISRM code.

strength of Schmidt Rebound Hammer Test was
based on Uniaxial Compression Strength value(UCS).
Table 1. Weathering of Granite Rock Based on Schmidt
Hammer Analysis (SHV)

Fig 6. Point load test machine

Slake Durability Test
Slake durability test was carried out to identify
the weatherability of the rock samples following thestandard methods ISRM and ASTM (Figure 7).
Slake durability test consist of placing weighed,oven dried samples of rock in a drum having a 2 mmmeshed exterior. Water is placed in a trough at alevel below the drum axle and the drum is rotatedwithin specified number of times. The sample thatremains in drum is oven dried and the test isrepeated for a second cycle. After the second cycle,
the slake durability index is obtained, Id.
Standardized procedures for the slake durability test
have been established by the International Society
for Rock Mechanics (ISRM, 1979b). If the second
cycle index is in between of 0% to 10%, hence firstcycle slake durability index is preferred but with thestatement provided.

The results in Table 1 shows that Granite 1,
Granite 4 and Granite 6 satisfied all the parameterswith weathering grade of IB due to the rocks
experienced discoloration on major discontinuity
surfaces. At the same time, the rocks are preserved
100% in texture and structure. Granite 2 and Granite
3 have weathering grade of II, also preserved
completely in texture. Granite 5 underwent complete
discoloration that should have weathering grade II
instead of III.
Table 2. Weathering of Schist-Phyllite Rock Based on
Schmidt Hammer Analysis (SHV)RESULTS AND DISCUSSION

Table 2 shows all Schist-Phyllite rock samples(1-6) satisfied all the parameters where partial
discoloration was observed. The texture andstructure of the rock samples were 100% preserved
indicating weathering grade of II.

Weathering of Rock Samples

Direct Shear Test

The study on rock strength is important toestablish its relation to the weathering effect. This isbecause the weathering grade of rock can be related
to rock durability of tunneling. In this study, theBased on the results shown in Table 3, Granite
rocks (1-6) shows that the rocks own strength ranged
from high to very high. This shows that the rock has

Fig. 7 Slake Durability Equipment

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SEE - Bangkok, Thailand, Nov.11-13, 2019very good strength which indirectly shows thatdurability of the rock based on shear strength is very
good. Similarly, all Schist-Phyllite rocks showed thestrength of high indicating that the rock durability isalso good (Table 4).

Table 6. Strength Classification of Schist-Phyllite RockBased on Point Load Test Analysis

Table 3. Direct Shear Analysis for Granite Rock

Slake Durability Test
Slake durability test clearly shows that
Granite 1- 6 having durability strength of very highwhich is proportional to Point Load Test and Direct
Shear Test results. Visual descriptions of rocks for
Granite 1- 6 except for Granite 3 were I and II,
respectively. Visual descriptions of I represent thatremaining rock pieces were virtually unchanged andvisual descriptions of II represents that remaining
pieces consist of large and small in size. For SchistPhyllite rock samples, the results also showed
extremely higher in durability strength. This
indicates that the rock materials are able towithstand higher strength of load but still maintainits origin and texture of the rock itself. All the
Schist-Phyllite rock showed visual description of I
except for Schist-Phyllite 2 and Schist-Phyllite 3
which was II (Table 8).

Table 4. Direct Shear Analysis for Schist-Phyllite Rock

Point Load Test

Table 7. Durability Strength of Granite Rock

Table 5 shows that the rock strength for samples
Granite 1-6 was very high due to less weathering
effect. The rock samples for Schist-Phyllite 1,
Schist-Phyllite 3, Schist- Phyllite 4 and SchistPhyllite 6 showed extremely high rock strength
which has no or less weathering effect (Table 6).
Among all the rock types, metamorphic rock showedvery strong and extremely quality rock.
Table 5. Strength Classification of Granite Rock Based on
Point Load Test Analysis

Table 8.Durability Strength of Schist-Phyllite Rock

Table 4. Strength Classification of Schist-Phyllite RockBased on Point Load Test Analysis

929

SEE - Bangkok, Thailand, Nov.11-13, 2019tunnelling in mixed face conditions resulting
from tropical weathering of igneous rock.
Tunnelling and underground space technology,
57, 225-240.
[5] Liu, L., Rong, Y., Zhang, C. K., Mao, M. Y., &Zhang, L. L. (2017). Instability Mechanism of
Du Yun Pass Tunnel Entrance Weathered
Stacking Area Analysis. In Applied Mechanics
and Materials (Vol. 858, pp. 81-85). Trans Tech
Publications.
[6] Momeni, A., Hashemi, S. S., Khanlari, G. R., &Heidari, M. (2017). The effect of weathering on
durability and deformability properties of
granitoid rocks. Bulletin of Engineering
Geology and the Environment, 76(3), 10371049.
[7] Abad, S. A. N. K., Tugrul, A., Gokceoglu, C., &Armaghani, D. J. (2016). Characteristics ofweathering zones of granitic rocks in Malaysia
forgeotechnicalengineering
design.
Engineering geology, 200, 94-103.
[8] Yusoff, Z. M., Daud, N. N., Nahazanan, H.,
Omar, H., Aziz, A., & Ab Razak, M. S. (2017,
July). Granites in Malaysia: From Hard Rock to
Clay Minerals. In Global Civil Engineering
Conference(pp.
1295-1305).
Springer,
Singapore.
[9] Ko, J., & Jeong, S. (2017). A Study on Rock
Mass Classifications and Tunnel Support
Systems in Unconsolidated Sedimentary Rock.
Sustainability, 9(4), 573.
[10] Sharma, L. K., Vishal, V., & Singh, T. N.
(2017). Developing novel models using neuralnetworks and fuzzy systems for the predictionof strength of rocks from key geomechanicalproperties. Measurement, 102, 158-169.
[11] Prokopov, A., Matua, V., & Akopyan, V.
(2016). Monitoring of the Geotechnical State of
the Array During the Reconstruction of the RokiTunnel. Procedia Engineering, 150, 2255-2260.

CONCLUSIONSIn this study, two types of rock mass samples
were collected from two proposed sited for tunnelingconstruction were assessed by Point Load Test,
Direct Shear Test and Slake Durability Test toevaluate the strength of rock fragments and its
relation to durability and weathering. The results of
the laboratory tests verified that the strength of therock samples was the same as the strength of rock at
the rock mass. Hence, if the rocks samples areclassified as durable, then the rock mass should also
have the same durability classification. This
indirectly shows that the particular rock mass arevery suitable for tunneling construction.
ACKNOWLEDGMENTS
This study was funded by UNITEN grant.

REFERENCES[1] Chen, Mengchong, and Fusheng Niu.
"Reasonable
Construction
MethodsforTunneling Beneath an Operating Highway."
Stability
Assessment
for
Underground
Excavations and Key Construction Techniques.
Springer, Singapore, 2017. 105-121.
[2] Jeong, H., Ha, S., & Kim, H. (2018). Floodprotection cost allocation using cooperative
game theory for adapting infrastructure toclimate change. Journal of Water Resources
Planning and Management, 144(4), 04018010.
[3] Tan, Y. C., Koo, K. S., & Chow, C. M. (2016).
Underground stations excavation of up to 45m
deep for mass rapid transit in limestone
formation, Malaysia. Japanese GeotechnicalSociety Special Publication, 2(2), 170-175.
[4] Shirlaw, J. N. (2016). Pressurised TBM

930

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

H2 PRODUCTION FROM LACTIC ACID RICH MEDIUM
AND CASSAVA STARCH WASTEWATER BY
Klebsiella pneumoniae subsp. pneumoniae
Piyawadee Saraphirom1, Napapach Chainamom1, Piyarat Namsena1,
Ornanong Chaiyachet 1, Weeranuch Wonkaonoi1 and Mullika Teerakun2*
1
Faculty of Science and Technology, Rajabhat Maha Sarakham University, Maha Sarakham, Thailand;2
Faculty of Agricultural Technology, Kalasin University, Thailand

ABSTRACTH2 production from lactic acid rich medium and H2 production from cassava starch wastewater by isolated
strains were investigated. The isolation of H2 producing bacteria from heat treated sludge was carried out. The H 2
production from lactic acid rich medium which used 1.5 g/L sodium acetate, 1.5 g/L sodium lactate and 1 g/L
sucrose as carbon sources. The effects of inoculums size of 10, 20, 30 and 40 % (v/v) and incubation temperatureof 35, 45 and 55 ºC using cassava starch wastewater as substrate on H2 production by isolation strains were
investigated. Results shown 6 isolated strains i.e. isolation code of MK01to MK06 indicated the H 2 production
capability when cultured in lactic acid rich medium. However, 3 isolated strains i.e. MK01, MK04 and MK06
were preferred to use as seed inoculums for further experiment depend on a high H2 production capacity obtained.
Results indicated that the optimal condition of H2 production from cassava starch wastewater was 30% (v/v)
inoculum size of MK06 under 35 ºC of incubation temperature. The maximum Ps, H2 yield and H2 production rateof 4.20 L H2/L medium, 1.47 L H2/g substrate consumed, and 14.00 mL H2/L/h were obtained. Identification andcharacterization of MK06 was investigated using 16S rRNA gene sequence analysis followed by phylogenetic
analysis. The 100% similarity of 16S rDNA compare with closely related species was indicated Klebsiellapneumoniae subsp. pneumoniae DSM 30104(T).
Keywords: Hydrogen production, Lactic acid rich medium, Cassava starch wastewater.
studied as substrate for H2 production and despite
reports of CH4 production from lactate [7], no
considerable H2 production was reported when lactate
was used as the individual substrate [2].
Although previous report on H2 production frommixture of lactic acid and acetic acid by Clostridium
diolis showed the promise on efficient H2 production
process in batch scale but the information on the H2
production from lactic acid rich wastewater are stilllacking. Therefore, this research aims to isolate H 2
producing bacteria which capable to use lactic acid assubstrate for H2 production. Effects of inoculum size
and incubation temperature on H2 production
parameters were investigated. Means of H2
production parameters which indicated the highefficiency of H2 producing strain were selected to
produce H2 from cassava starch wastewater. The
results from this study provided high efficiency ofhydrogen producing strain and the optimum condition
could improve hydrogen yield from lactic acid richwastewater.

INTRODUCTION
H2 producing bacteria such Clostridiaceae canferment the carbohydrates in agricultural wastewaterto H2, CO2 and volatile organic acids – mainly acetic
and butyric acids. However, these bacteria are notable to further break down the organic acids to H2 dueto the positive Gibbs free energy of the reaction [1].
The genus Clostridium i.e. Clostridium butyricum,
Clostridium diolis and C. beijerinckii have beenreported their ability to produce hydrogen from a
mixture of acetic acid and lactic acid [2]. A mole ratio
of depletion of acetic acid to lactic acid of 1:2 could
be obtained from the biological H2 production from a
mixture of acetic and lactic acids by C. diolis JPCC
H-3 [2]. Cassava starch wastewater is an industrial
residue composed mainly of lactic acid bacteria withexcess of the genera Lactobacillus, and organic acids[3]. The cassava starch wastewater is excluded, and it
is returned an effluent with high chemical oxygen
demand [4]. However, this residue presents a
motivating component for prospective use ininnovative products. The cassava starch wastewater
has a low pH and it is an organic acid rich wastewater[4]. The major organic acids include lactic acid, acetic
acid, butyric acid and other components include
starch residual. In dark fermentative H2 production,
the presence of lactic acid as a metabolite during H2production is frequently regarded as a sign of lower
H2 production [5, 6, 7]. Lactic acid has been rarely

METERIALS AND METHODS
Anaerobic Sludge
The anaerobic sludge of UASB was pretreated bydry heating method using hot air oven under 105°C
for 2 h for suppressing the methanogen. After heating,
the UASB sludge was dispersed into an aqueous
suspension by vertexing it in PBS buffer (pH 7.2, 10
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SEE - Bangkok, Thailand, Nov.11-13, 2019

mM Na2HPO4, and 0.13% NaCl) for 5 min. The
suspension was diluted serially, plated on an NB
medium (pH 6.8, 0.3% beef extract, and 0.5%
peptone) and incubated at 30 °C under anaerobic
conditions. After incubating for 24-36 h, colonies
were selected randomly and transferred to fresh NB
plates.

headspace and to create the anaerobic condition. The
bottles were incubated at room temperature andoperated in an orbital shaker with a rotation speed of
120 rpm to provide better contact among substrates.
After 24 h, the total gas volume was measured byreleasing the pressure in the bottles using wetted glass
syringe. The 3 mL of biogas produced were collected
into another serum bottle then measured the H2concentration by gas chromatography analysis.

H2 Production Confirmation
Each isolated bacterium obtained was use as seed
inoculums for the H2 production confirmation
experiment. The experiment was accompanied in 25
mL serum flasks with a working volume of 15 mL.
The H2 production medium was contained 10% (v/v)
inoculum. The H2 production capability of isolated
bacteria was performed by cultured in synthetic
medium (M solution) [8]. Serum flasks were flushedwith nitrogen gas to eliminate oxygen in headspace
and to generate the anaerobic condition thenincubated at room temperature. After 24 h, the totalgas volume was measured by releasing the pressurein the flasks using wetted glass syringe.

Analytical Method and Kinetics Model
H2 content was measured using a gas
chromatograph under the same analytical condition as[9]. Helium was used as the carrier gas at a flow rateof 25 mL/min. H2 production was calculated from theheadspace measurement of gas composition and thetotal volume of H2 produced, at each time interval,
using the mass balance equation [9].
𝑽𝜢,𝒊 = 𝑽𝜢,𝒊−𝟏 + 𝑪𝜢,𝒊 (𝑽𝑮,𝒊 − 𝑽𝑮,𝒊−𝟏 ) + 𝑽𝜢,𝟎 (𝑪𝜢,𝒊 − 𝑪𝜢,𝒊−𝟏 )Where 𝑉𝛨,𝑖 and 𝑉𝛨,𝑖−1 are the cumulativehydrogen gas volumes at the current (𝑖 ) and previous
time interval(𝑖 − 1), respectively; 𝑉𝐺,𝑖 and 𝑉𝐺,𝑖−1 aretotal biogas volume at the current and previous timeinterval; 𝐶𝛨,𝑖 and 𝐶𝛨,𝑖−1 are the fraction of hydrogengas in the headspace at the current and previous timeinterval; 𝑉𝛨 is the volume of headspace of serum
bottles. A modified Gompertz equation was used toadequate the H2 production profiles [9]. Total sugar,
volatile fatty acid (VFAs) and dry cell weight (DW)
are measure according to the procedures described instandard methods [10].
𝑹𝒎 𝒆(𝝀 − 𝒕) + 𝟏]}
𝑯 = 𝑷 𝒆𝒙𝒑 {− 𝒆𝒙𝒑 [𝑷

H2 Production from Lactic Acid Rich Medium by
Isolated Strain
Isolated colonies indicated H2 production capacity
obtained from 2.2 were cultured in synthetic medium(M solution) [8]. H2 production ability of all isolated
strains were conducted in the same size of serum
flasks with a liquid volume of 70 mL and 50 mL ofhead space volume. The H2 production capability of
isolated bacteria was accomplished by cultured inlactic acid rich medium (M solution contained sodium
acetate, 1.5 g/L sodium lactate and 1 g/L sucrose ascarbon sources). The 10% (v/v) inoculum was
inoculated into 120 mL serum flasks then incubatedat room temperature and activated in an orbital shaker
with a rotation speed of 120 rpm. The biogas volume
was continuously measured and collected by gas tightsyringe for biogas composition analysis.

Where, 𝐻 represents the cumulative volume ofhydrogen produced (mL), 𝑃𝑠 the hydrogen production
potential (mL), 𝑅𝑚 the maximum production rate
(mL/h), 𝜆 the lag-phase time (h), 𝑡 the incubation
time (h), and 𝑒 is 2.718281828. Parameters (𝑃𝑠 ,𝑅𝑚and 𝜆) were estimated using the solver function in
Microsoft Excel version 5.0 (Microsoft, Inc.).
ANOVA was used for selecting forecasting H2producing strain isolate based on comparison ofmeans between forecasting results; that is for testinga significant different between group means [11].
When differences between groups exist, a post hoc
test then conducted to identify which group thatdiffers from the others. In this paper, Duncan multiple
range test was used.

H2 Production from Cassava Starch Wastewaterby Isolated Bacteria
Isolated strains showed the high H2 production
capacity were enriched in lactic acid rich medium for
48 h under anaerobic condition before used as seed
inoculums. The cassava starch wastewater used assole substrate for H2 production consisted of 2.78 g/L
starch, 4.59 g/L volatile fatty acid i.e. 0.89 g/L acetic
acid, 1.33 g/L lactic acid, 1.09 g/L propionic acid and1.28 g/L butyric acid. The variation inoculums size of
10, 20, 30 and 40 % (v/v) was adjusted then the effectof incubation temperature at 35, 45 and 55 ºC on H2
production from cassava starch wastewater by
isolated bacteria was investigated. The difference
inoculums size was inoculated into cassava starch
wastewater in 25 mL serum flasks with a liquidvolume of 70 mL under adjusted initial pH of 5.5.
Serum flasks were flushed with N2 to remove O2 in

16S rDNA Sequencing
PCR amplification of 16S rDNA
DNA templates for PCR amplification wereprepared by using “Genomic DNA mini kit(Blood/culture cell)” (Geneaid Biotech Ltd., Taiwan).
DNA coding for 16S rRNA regions was amplified bymeans of PCR with Taq polymerase, as described by

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SEE - Bangkok, Thailand, Nov.11-13, 2019[12-13]. A PCR product for sequencing 16S rDNA
regions was prepared by using the following two
primers, 20F (5’-GAG TTT GAT CCT GGC TCA G3’, positions 9-27 on 16S rDNA by the E. coli
numbering system and 1500R (5’-GTT ACC TTGTTA CGA CTT-3’, position 1509-1492 on 16S
rDNA by the E. coli numbering system [14]. The PCR
amplification was carried out with DNA Engine
Dyad® Thermal Cycler (Bio-Rad Laboratories). One
hundred μl of a reaction mixture contained 15-20 ng
of template DNA, 2.0 μmoles each of the two primers,
2.5 units of Taq polymerase, 2.0 mM MgCl2, 0.2 mM
dNTP and 10 μl of 10xTaq buffer, pH 8.8, containing(NH4)2SO4, which was comprised of 750 mM TrisHCl, 200 mM (NH4)2SO4 and 0.1% Tween 20. The
PCR amplification was programmed to carry out an
initial denaturation step at 94 ºC for 3 min, 25 cycles
of denaturation at 94 ºC for 1 min, annealing at 50 ºC
for 1 min and elongation at 72 ºC for 2 min, followed
by a final amplification step at 72 ºC for 3 min. The
PCR product was analyzed by 0.8% (w/v) agarose gelelectrophoresis and purified with a GenepHlowTM
Gel/PCR Kit (Geneaid Biotech Ltd., Taiwan). The
purified PCR product was stored at -20 ºC for further
step.

method [20]. Phylogenetic trees were constructed by
the neighbor-joining method [21]. The robustness forindividual branches was appraised by 100
replications bootstrapping [22] with the program
MEGA Version 6.0 [23].
RESULTS AND DISCUSSION
H2 Production from Lactic Acid Rich Medium by
Isolated Strains
The 6 colonies isolated from heat-treated sludge(isolation code MK01-MK06) were selected as the H2
producing bacteria depend on H2 production
capability obtained. They were subsequently
characterized by gram-staining, optical microscopy
and the colony shape. Results showed the negative
gram, circular form and smooth surface of colonies
with the different of colonies edge and cell size.
Based on the microscopic observation, each colony
was characterized with rod shape and endospore
formation. The H2 fermentation of isolated strains
was performed in batch experiment under anaerobic
condition and analyzed the H2 production by the gas
chromatography. The cumulative H2 profile ofisolated strains was shown in Fig. 1. It was found thateach isolate obtained showed the H2 production
capacities when cultured under an adjusted condition.
H2 production from lactic acid rich medium by
isolated strain was performed in batch fermentation.
The inoculum was cultivated in the serum bottle andtransferred anaerobically during the late-exponential
phase by a sterile hypodermic disposable syringe intoanother serum bottle containing with a lactic acid richmedium. The lactic acid rich medium using 1.5 g/L
sodium acetate, 1.5 g/L sodium lactate and 1 g/L
sucrose as carbon sources was prepared for H2
production test for each isolate.

Direct sequencing of 16S rDNA
Direct sequencing of the single-banded andpurified PCR products (ca. 1500 bases, on 16S rDNA
by the E. coli numbering system [14] was carried out.
Then, sequencing of the purified PCR products was
performed on an ABI Prism® 3730XL DNA
Sequence (Applied Biosystems, Foster City,
California, USA) by sequencing service provider.
The two primers 27F (5’-AGA GTT TGA TCM TGG
CTC AG-3’) or 800R (5’-TAC CAG GGT ATC TAA
TCC-3’) and 518F (5’-CCA GCA GCC GCG GTAATA CG-3’) or 1492R (5’-TAC GGY TAC CTTGTT ACG ACT T-3’) for single strand 16S rDNA
sequencing, and 4 primers of 27F, 518F, 800R and
1492R for double strands 16S rDNA sequencing wereused 3 sequence analyses. The nucleotide sequences
obtained from all primers were assembled using Cap
contig assembly program, an accessory application in
BioEdit (Biological sequence alignment editor)
Program. The identification of phylogenetic
neighbors was initially carried out by the BLASTN[15] program against the database containing typestrains with validly published prokaryotic names [16].
The top thirty sequences with the highest scores werethen selected for the calculation of pairwise sequencesimilarity using global alignment algorithm, which
was implemented at the EzTaxon-e server [16-17].
The DNA sequences determined and obtained fromdatabases were aligned with a program CLUSTAL X(version 1.8) [18] in BioEdit Program [19].
Alignment gaps and unidentified bases were
eliminated. The evolutionary distances werecomputed using the Maximum Composite Likelihood

MK01
MK03
MK05

Cumulative H2 (mL H2.L)

200

MK02
MK04
MK06

150
100
50
0
0

20

40

60

80

100 120 140 160 180

Incubaton time (h)Fig. 1

Cumulative H2 profile of all isolated strains.

Table 1 showed that all the isolates produced theamounts of H2 until 120 h of incubation time. The
highest amounts of the H2 production potential and H2yield (170.18 mL/L and 3.98 mL/g DW/L) obtained
from MK01. The summarizes the batch fermentation
results and volatile fatty acids produced with the newisolates when 1.5 g/L sodium acetate, 1.5 g/L sodium
lactate and 1 g/L sucrose were used as carbon sources

933

SEE - Bangkok, Thailand, Nov.11-13, 2019

(Table 2).

performed as lactic acid rich medium. The increasing
in total volatile fatty acid produced was obtained fromalmost isolated strain.

Table 1 H2 production from lactic acid rich medium
by isolated strains.
Isolationcode

H2 production
Ps
Rm(mL/L)(mL/L.h)H2 yield*(mL/g DW.L)


)h(
MK01
170.18a0.44d21.78a3.98a
MK02
50.58f0.58c
12.96c
0.92c
d
a
d
MK03
84.95
1.05
10.72
1.95bcMK04
96.99b0.94b16.31b
2.27b
MK05
70.98e0.51c
16.02b
1.63bcMK06
90.90c0.85b11.55c2.09b*H2 yield (milliliter H2 per gram of cell dry weight per literof medium)

A high lactate and acetate of 1.5 g/L and a
relatively low glucose concentration of 5 g/L were
employed in this experiment because the medium wasFactors Affecting on H2 Production from Cassava
Starch Wastewater by Isolated Strains
The study of effects of inoculums size on H2
production from cassava starch wastewater by
isolated bacteria was performed in batch experimentusing 25 mL serum bottles. Three isolated strains i.e.
MK01, MK04 and MK06 were preferred to use as
seed inoculums depend on high H2 production
capacity (Table 2). The H2 production capability of
isolated bacteria was performed by adjusted initial pHof 5.5. The initial concentration of starch in cassava
starch wastewater was 4.63 g/L and total volatile fatty
acids including acetic acid, lactic acid, propionic acidand butyric acid were also used as carbon source toproduce H2.

Table 2 Summarizes of the batch fermentation results of H2 production from lactic acid rich medium by isolated strains.
Isolation code
Dry cell weight
TVFAs*
Volatile fatty acid composition (g/L)
(g/L)
(g/L)
Acetic acid
Lactic acid
Propionic acid Butyric acid
Init.
final
Init. final Init. final Init. final Init.
final
Init. final
MK01
13.3
11.9
5.0
11.2
1.0
2.2
1.4
3.2
1.2
2.7
1.4
3.2
MK02
14.8
14.7
5.0
14.3
1.0
2.8
1.4
4.1
1.2
3.4
1.4
4.0
MK03
13.6
12.8
6.5
15.9
1.2
3.1
1.9
4.6
1.6
3.8
1.8
4.5
MK04
12.6
10.7
5.0
14.3
1.0
2.8
1.4
4.1
1.2
3.4
1.4
4.0
MK05
13.3
11.9
6.5
12.8
1.2
2.5
1.9
3.7
1.6
3.0
1.8
3.6
MK06
13.4
10.8
11.2 14.3
2.1
2.8
3.2
4.1
2.7
3.4
3.2
4.0
*TVFAs is total volatile fatty acids; Init. is in the initial of fermentation; Final is in the final of fermentation.

Table 3 indicated that increasing in inoculums
size of MK01 was improved biogas and H2
production including content, Ps and yield. The
maximum Ps and H2 yield of MK01 were 836.8 mL/L
and 255.9 mL H2/g substrate consumed obtained from40% (v/v) of inoculums size. On the other hand,biogas and H2 production was suppressed by theincreasing in inoculums size of MK04. The maximumPs and H2 yield of MK04 were 804.2 mL/L and 175.2
mL H2/g substrate consumed obtained from 10%(v/v) of inoculums size. However, the optimum of
inoculums size in this experiment was 30% (v/v) of
MK06 caused the highest Ps and H2 yield of 1033.3
mL/L and 467.5 mL H2/g substrate consumed.
Results suggested that Ps obtained from MK06 was 5
and 6.6 folds greater than MK01 and MK04,
respectively. In addition, optimum H2 yield of MK06
obtained caused 1.3 and 2.7 folds greater than MK01
and MK04, respectively (Table 3).
Results suggested that MK01 has higher ranging
of starch consumed than MK04 and MK06. The
optimum condition for substrate consumption wasunder 30% (v/v) inoculums size of MK01 that
illustrated 99.54% substrate consumption efficiency.
Results also noteworthy that the low substrateconsumption efficiency of MK04 and MK06 might beindicated the different of H2 producing bacteria andstarch might adversely affect the biodegradability.

Table 3 Effects of inoculums size on H2 production
from cassava starch wastewater.
Isolation
code

MK01

MK04

MK06

inoculums
size(% v/v)

H2 Production
Content(% v/v)Ps(mL/L)

10
20

2.71d
0.30fg207.86d15.66jYield(mL H2 /g
substrate
consumed)
70.94d
3.38gh30
40

0.32fg10.50b

18.25i
836.85b4.25fg255.92b

10
20
30

9.88c
0.70ef0.89e

804.23c44.94f48.41e175.21c12.15e13.45e40
10200.55ef0.37efg-

27.55g20.57h
-11.34e
7.27f-

30

11.38a1033.30

467.56a

a

40

-

-

-

Kapdan and Kargi [24] reported that many
agricultural and food industry wastes contain starch
may adversely affect the biodegradability. Starchcontaining solid wastes is easier to process forcarbohydrate and H2 formation. Starch can behydrolyzed to glucose and maltose by acid or
enzymatic hydrolysis followed by conversion ofcarbohydrates to organic acids and then to H2 [24].
However, others organic components in cassava

934

SEE - Bangkok, Thailand, Nov.11-13, 2019

starch wastewater could be used as the substrates to
produce H2 by isolated H2 producing bacteria in thisstudy.
The effect of incubation temperature on H2
production from cassava starch wastewater by
isolated bacteria was investigated after the optimum
inoculums size obtained. Table 3 indicated the
optimum of inoculums size was 30% (v/v) of MK06.
H2 producing bacteria strain MK06 was used as seed
inoculums at the inoculums size of 30% (v/v) for H2
production from cassava starch wastewater undervarious incubation temperatures of 35, 45 and 55 ºC.
Table 4 showed effect of incubation temperature on
H2 production from cassava starch wastewater by H2
producing bacteria strain MK06 at the optimum
inoculum size (30% v/v). Results illustrated that the
maximum cumulative H2, yield and production rate of
4.20 L H2/L medium, 1.47 L H2/g substrate consumed,
and 14.00 mL H2/L/h were obtained under incubation
temperature of 35 ºC.

were constructed by the neighbor-joining method of[21] which shown in Fig. 2. The percentage of
replicate trees in which the associated taxa clustered
together in the bootstrap test (1000 replicates) are
shown next to the branches [19]. The tree is drawn toscale, with branch lengths in the same units as thoseof the evolutionary distances used to infer thephylogenetic tree. The evolutionary distances werecomputed using the maximum composite likelihood
method [21] and are in the units of the number of basesubstitutions per site. The analysis involved 11
nucleotide sequences. All positions containing gaps
and missing data were eliminated. There were a totalof 1246 positions in the final dataset. Evolutionary
analyses were conducted in MEGA6 [20].

Table 4 Effects of incubation temperatures on H2
production from cassava starch wastewaterby MK06.
H2 Production by
MK06 at 10% (v/v) of inoculums size
Incubation
temperaturesPs(L H2/L
medium)Yield(L H2 /gsubstrate
consumed)

H2 productionrate(mL H2/L.h)

35°C

4.20a

1.47a

14.00a

45°C

2.89c

0.99c

9.30b

55°C

b

b

12.70a3.78

1.26

Fig. 2 The phylogenetic relationships based on 16S
rDNA.
CONCLUSIONSThe 6 isolated strains i.e. isolation code of MK0106 indicated the H2 production capability when
cultured in lactic acid rich medium. MK01, MK04
and MK06 were selected to use as seed inoculum forH2 production from cassava starch wastewater which
consisted of starch and volatile fatty acid i.e. lactic
acid and acetic acid in composition. The optimal
condition of H2 production from cassava starch
wastewater was 30% (v/v) of MK06 as inoculum
under 35 ºC which obtained the maximum Ps, H2yield and H2 production rate of 4.20 L H2/L medium,1.47 L H2/g substrate consumed, and 14.00 mL
H2/L/h,respectively.
Identification
andcharacterization of MK06 indicated that 100%
similarity of 16S rDNA compare with closely related
species was indicated Klebsiella pneumoniae subsp.
pneumonia DSM 30104(T).

16S rDNA and phylogenetic analysis of isolated H2
producing bacteria
Isolation of new H2 producing bacteria with highcapacity or unique properties in H2 production wasinvestigated using 16S rRNA gene sequence analysis.
H2 producing bacteria strain MK06 was preferred for
identification of the new isolates via sequencing of
the full 16S rDNA followed by phylogenetic analysis.
Results showed the 100% similarity of 16S rDNA
compare with closely related species was indicatedKlebsiella pneumoniae subsp. pneumonia DSM
30104(T) reported by Schroeter (1886) and Trevisan(1887). In order to better understand the process, themicrobial identification was investigated and linked
to the H2 production performance. The used method
for microbial characterization in H2 production is 16S
rRNA based DGGE combined with sequencing andsimilarity-based phylogenetic analysis [25]. The
DNA sequences determined and obtained fromdatabases were aligned with a program CLUSTAL X(version 1.8) [18] in BioEdit Program [19].
Alignment gaps and unidentified bases were
eliminated. The evolutionary distances werecomputed using the Maximum Composite Likelihood
method [20]. Phylogenetic trees of 16S rRNA genes

ACKNOWLEDGMENTS
This research work was financially granted by theThailand Research Fund and Rajabhat Maha
Sarakham University under the TRF Research
Scholar Grant No. MRG5580247. The author would
like to thank Prof. Dr.Alissara Reungsang for her
suggestion and supporting for the research.
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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

OPTIMIZATION OF PARAQUAT DEGRADATION WITH
MICROBIAL CONSORTIUM FROM CONTAMINATED SOIL USINGSTATISTIC METHOD
Mullika Teerakun1 Alissara Reungsang2 Monrodee Chaowarat3 and Piyawadee Saraphirom4*
Faculty of Agricultural Technology, Kalasin University, Thailand; 2Faculty of Technology, Khon Kaen
University, Thailand; 3Faculty of Technology, Mahasarakham University, Thailand; 4Faculty of Science andTechnology, Rajabhat Mahasarakham University, Thailand
1

ABSTRACT
Paraquat is one of non-selective herbicides, widely used in Thailand and other countries that can be used toprevent and mitigate problems with weeds that have become resistant. It has broad spectrum to weed knockdown
herbicide which can be easily distributed in an aquatic environment due to its high solubility in water. The aim ofresearch is to study the optimization condition for biodegradation of paraquat by microbial consortium using an
orthogonal array design in culture media. Microbial consortium which can degrade paraquat were isolated fromcassava rhizosphere soil with a history area of using paraquat in Kalasin, Thailand. Analysis of the 16S rDNA
gene sequences compared with the database in Gen Bank demonstrated that microbial consortium showed thesimilarity with Sphingomicrobium marinum (97%), Ferrovibrio xuzhouensis (93%), Azospirillum lipoferum (93%),
Altererythrobacter xinjiangensis (94%), Xanthobacter autotrophicus (92%) and Azospirillum amazonense (99%). To
achieve the biodegradation experiments, orthogonal arrays design was investigated, with the three independent
variables: glucose concentration (1-20 g/L), paraquat concentration (10-100 mg/L) and inoculum concentration(1-10%). The biodegradation consortium was done triplicate in 250 mL Erlenmeyer flask at 30°C 150 rpm for 35
days. Paraquat biodegradation was reported as biodegradation percentage. The results demonstrated that the
optimum concentrations of glucose, paraquat and inoculum for paraquat biodegradation were 1 g/L, 10 mg/L and
5%, respectively. The paraquat removal efficiency of 95.69% was achieved under the optimal condition.
Keywords: Paraquat, Biodegration, Orthogonal arrays design, Microbial consortiumgroup of pesticide. [4]-[8]. Paraquat is classified as amoderately toxic chemical for lethal toxicity, with arelatively low potential to bio-accumulate in theaquatic environment [9]. Therefore, the removal of
paraquat from contaminated environment isnecessary.
Bioremediation is biological processes or activityof the organisms to transform contaminants into lesstoxic compound. This method is presently the
inexpensive and has greater efficiency in the removalof contaminants than conventional physicochemical
methods [10]. Previous researches revealed theeffient pesticide removal by microorganisms.
Brevibacterium frigoritolerans, Bacillus aerophilus
and Pseudomonas fulva were isolated from aged
phorate contaminated soil and could degrade phorate
with the percentage of removal ranged between 97.65
and 98.31% [11]. Kafilzadeh et al. [12] isolated
bacteria from sediments and water samples from highagricultural activity areas. They belong to genus i.e.
klebsiella, acinetobacter, alcaligenes, flavobacterium,and bacillus. Bacillus sp., Micrococcus sp., Klebsiellasp., Pseudomonas sp., Listeria sp., Proteus sp.,
Streptococcus sp., and Staphylococcus sp. were
found as the bacteria capable of utilizing the herbicide(paraquat dichloride) [13].

INTRODUCTION
Nowadays, chemicals substances are widely used
for agriculture in Thailand. One group of thesechemical substance is pesticides. Pesticides have been
an important part of agriculture to protect crops andincrease an agriculture yield [1]. The group ofpesticide that commonly used for eliminating weed isparaquat.
Paraquat(1,1-dimethyl-4,4-bipyridyl
dichloride) is non-selective contact herbicide, quickacting and killing green plant tissue on contact. It isclassified as non-moving herbicides due to strong
adsorption on soil particles. However, repeated use of
paraquat over the years or the used in large quantities
caused an accumulation of paraquat in environment
by adsorption to the soil. The interrill erosion and runoff water can cause the leaching of paraquat andspreading to the river bed [2], [3]. In Thailand, it had
been reported that paraquat is the main pesticide
disseminated to the aquatic environment, forexample, in the Chao Phraya River (0.28 and 0.40µg/L), Pa Sak River (0.22 and 3.23 µg/L), Tha ChinRiver (0.01-0.79 µg/L), Namphong River (0.02-26.8ng/L) and Chanthaburi River (0.50-15.00 μg/L)
which paraquat in the sample water from those rivers
was found to have a higher residue content than other937

SEE - Bangkok, Thailand, Nov.11-13, 2019previously described by Teerakun et al. [19]. The
isolated consortium was used in the further
experiment. Bacterial community in the isolated
consortium was analyzed by Denaturing gradient gelelectrophoresis (DGGE) technique.

Design of Experiments techniques was widelyused to optimize experimental parameters andenabled to determine simultaneously the individual
and interactive effects of many factors that could
affect the output results in experiment [14]-[15]. A
full factorial experiment tests all possiblecombinations of the factor levels and can therefore
find the overall optimum setting. However, thisprocess became excessive as the number of design
parameters or levels increases [16]. An orthogonalarray led to the reduction of variability in the process,compliance that is close to the desired result and adecrease of operating costs [17]. This technique has
two major requirements consisting of the levels of
any factor must occur with the same frequency andtwo factors, which each possible combination oflevels must occur with the same frequency. If all
factors have q levels, an orthogonal array is typically
expressed as LM(qm), where m is the number offactors and M represents the number of rows in thearray [16].
The aim of this research was to isolate thebacterial consortium capable of paraquat degradation.
The paraquat removal efficiency of the isolated
bacterial consortium were also examined in the batch
experiment with statistical experimental design. In
addition, the optimal conditions for paraquat removal
by isolated consortium were determined in order toachieve the highest parquat removal efficiency.

Analysis on Community Structure of Bacterial
Consortium by DGGE Technique
The genomic DNA of isolated consortium was
extracted by using TIANamp Soil DNA Kit(TIANGEN Biotech (Beijing) Co., Ltd.). The 16S
rRNA was amplified by the first polymerase chain
reaction (PCR) with universal primer 1525r (5’AAGGAGGTGWTCCARCC 3’) and 27f 5’
GAGTTTGATCCTT GGCTCAG 3’). In the second
PCR, primer 518r (5’GTATTACCGCGGCTGCTGG3’)
and 357f (5’CTCCTACGGGAGGCAGCAG3’) with
CG clamp (CGCCCGCCGCGCGCGGCGGGCGG
GGCGGGGGCACGGGG GG) were used to amplify
the fragment of V3 region of 16S rDNA product fromfirst PCR. PCR products were stored at 4°C andanalyzed on 1.0% agarose before DGGE analysis.
The DGGE analysis of the PCR products was
performed by electrophoresis (DGGE unit, V20HCDC, Scie-Plas Limited, UK) according to themethod previously described by Kongjan et al. [20].
The closest matches for partial 16S rRNA genesequences were identify base on the sequence data ofribosomal database project (http://rdp. cme.msu.edu/).
The Seq Match program and basic local alignment
search tool (BLAST) with nucleotide database in the
National Center for Biotechnology Information were
employed [21].

MATERIALS AND MEHODS
Soil Sampling
Cassava rhizosphere soil sample was collectedfrom the field, with a history of paraquat application,in Kalasin province, Thailand and used as a source forparaquat degrading bacteria isolation. It waspreserved in plastic bag and kept at 4oC for maintainthe activity of microorganisms until the usage.

Determination of Optimal Conditions for
Degradation of Paraquat in Culture Media using
Orthogonal Arrays Design
Degradation of paraquat by isolated consortium
was investigated in 250 mL Erlenmeyer flask with theworking volume of 150 mL. The experimental
conditions were designed by orthogonal arrays design,with the three independent variables: glucose
concentration (A; 1, 10 and 20 g/L), paraquat
concentration (B: 10, 50 and 100 mg/L) and inoculum
isolated concentration (C: 1, 5 and 10%) on paraquatbiodegradation. All experimental runs wereconducted in triplicate. The L9 (34) orthogonal test
parameters was showed in Table 1. The blank factor
was a dummy and was used for error assessment.

Isolation of Bacterial Consortium Capable ofDegrading Paraquat
Isolation of microbial consortium capable ofdegrading paraquat from rhizosphere soil was carriedout by enrichment culture technique. Soil samples (10g) were put into 250 mL Erlenmeyer flasks containing
90 mL of the mineral salt medium [18] supplemented
with 10 mg/L paraquat. Flasks were incubated at
30°C with shaking at 150 rpm. After 7 days, 10 mLof broth from flask was inoculated to fresh mineralsalt medium containing 10 g/L of paraquat. This
process was repeated until the paraquat removal at
day 7 was less than 50% of the initial value. Isolated
consortium was then harvested using method

Table 1. The L9 (34) orthogonal design for theparaquat biodegradation.

938

Experimentalrun

A:
glucose(g/L)

B:
praquat(mg/L)

Blank

C:
inoculum
(%)

1

20

100

2

1

SEE - Bangkok, Thailand, Nov.11-13, 2019

2
3
4
5
6
7
8
9

20
20
10
1
1
1
10
10

50
10
50
50
100
10
10
100

1
3
3
2
3
1
2
1

10
5
1
5
10
1
10
5

Azospirillum sp. and decrease the ammonification
process [29]. X. autotrophicus could degraded 2chloroethanol (2-CE) that are metabolite of Tris (2chloroethyl) phosphate into glycolic acid [30] andgrowing cells of of X. autotrophicus strain GJ10
completely degraded 180 μM of 2-CE within 24 h
[31].
Table 2 Identification of dominant fragments in
DGGE patterns in paraquat biodegradation
isolation consortium

Analysis of Paraquat Residue in Culture MediaThe culture media was taken at the interval timeand centrifuged for 15 min at 4,000 rpm. One
milliliter of supernatant was filled in the glass tube
with 1 mL of 2% Na2S2O4 in 0.3 M NaOH. Paraquat
concentration was examined by Spectrophotometer
UV-1800 (SHIMADZU, Japan) at 600 nm [22]. The
paraquat recovery efficiency of this method was 93%.

Bands

1
2

RESULTS AND DISCUSSION
3The Community Structure of a Bacterial
Consortium Capable of Degrading Paraquat by
DGGE

4
5

The community structure of a bacterial
consortium capable of degrading Paraquat was
analyzed by DGGE. The fingerprints obtained fromthe bacterial community of isolated consortium
demonstrated 6 differently visible bands as shown in
Fig. 1. The sequences of the bands were identified
base on 16s rRNA gene and exhibited a greater than
92% identity to the sequences deposited in the
databases (Table 2) which were closet matched to 6
genera i.e., Sphingomicrobium marinum, Ferrovibrio
xuzhouensis,
Azospirillum
lipoferum,
Altererythrobacter xinjiangensis, Xanthobacter
autotrophicus and Azospirillum amazonense.
Sphingomicrobium sp. is members of genus
Sphingomonas which are often reported as thebacteria capable of degrading recalcitrant natural,
anthropogenic compounds and different herbicides
and pesticides [23]. Song et al. [24] reported
cyhalothrin,
synthetic
pyrethroid
pesticide,degradation by F. xuzhouensis. It was isolated from acyhalothrin contaminated wastewater. Azospirillum isof the genera that able to degrade organic andinorganic contaminants in soil [25]-[26] and werecapable of biodegradation ethion in minimal salt
media [27]. Romeh and Hendawi [28] found that A.
lipoferumhascapabilityofutilizingorganophosphorus
insecticides,
chlorpyrifos,
chlorpyrifos-methyl, cyanophos and malathion inmineral salts media as carbon and phosphorus source.
Azospirillum sp. could tolerate to pesticides such as
monocrotophos
andchlorpyrifos
atlow
concentrations. However, the higher concentrationsof these pesticides could cause antagonistic effects on

6

Fig. 1

Closet Identify Relative
Accession
Bacterial species
No.
Sphingomicrobium
NR_135708.1
marinum
Ferrovibrio
NR_145543.1
xuzhouensis
Azospirillum
NR_116846.1
lipoferum
Altererythrobacter
NR_108901.1
xinjiangensis
Xanthobacter
NR_074255.1
autotrophicus
Azospirillum
NR_104981.1
amazonense%
Identity
97%
93%
93%
94%
92%
99%

DGGE fingerprint of 16S rDNA fragmentsof paraquat biodegradation isolation
consortium. Sequence of bands was
searched in the GenBank with the BLAST
program to determine the closest known
relatives of the partial 16S rDNA sequences
obtained (Table 2).

The Orthogonal Experiment Results of Paraquat
Biodegradation
Batch
paraquatbiodegradation(theexperimental runs 1 to 9) was examined. The resultsof orthogonal experiment of paraquat biodegradation
939

SEE - Bangkok, Thailand, Nov.11-13, 2019at day 35 were showed in Table 3. The paraquatremoval on the orthogonal experiments ranged from70.02 to 97.87% (Table 3). Range analysis wasapplied to clarify the important sequence of glucose
concentration (factor A), paraquat concentration(factor B) and inoculum concentration (factor C) in
the orthogonal experiments (Table 4). The highest
range value (R) of 13.63 was found for factor B, while
the lowest range value of 7.79 was found for factor A.
The bigger R value of a factor represents a greater
effect on the paraquat removal. According to therange, the order of influence on the paraquat removal
was paraquat concentration > inoculum concentration> glucose concentration. Thus, the optimum
condition for improving paraquat removal was
determined as A1B1C2 corresponding to glucose
concentration, 1 g/L; paraquat concentration, 10
mg/L and inoculum, 5%.
In order to verify the reliability of the results inflasks, an additional experiment with thecorresponding parameters under the optimum
nutrient condition A1B1C2 was performed in flask
250 mL (data not show). Under the optimum
condition, the observed paraquat removal of 95.69%
was obtained. This indicated that the statisticalexperimental design i.e. orthogonal experiment
design, is a useful tool for optimizing paraquatremoval conditions.
Addition of glucose could lead to higher
degradation of pesticide [32]. This is in accordancewith a study by Hashemi et al. [33] who reported thatparaquat biodegradation increased in the presence of
glucose by Achromobacter xylosoxidans andStreptomyces sp. Kanissery and Sims [34] reported
that the addition of glucose was enhanced the extent
of mineralization herbicide at a low herbicideconcentration.
Paraquat was used as nitrogen source by
microorganism [19], [35]-[36]. However, theparaquat concentration was impact affected on
growth of the organisms. According to report of Andyet al. [37] found that the cell mass yield of the
microbes decreased with increased concentration of
the paraquat. Paraquat had toxic effect on the
microorganisms leading to the higher counts obtained
from the lowest concentration of 25 mg/kg and thelowest counts from the highest concentration of 100
mg/kg [38].
Microbial population density is an important
determinant in the biodegradation rate [39]. When the
inoculum size is small and viable cell fraction is low,
there may be a pseudo-lag phase, which is not a resultof adaptation but of the small inoculums size [40]. In
addition, higher inoculum sizes would contain alarger population of microorganism that would
consume more oxygen. The optimal condition,

especially in terms of specific degradation rate of
substrate, did not occur at initial optical density (OD)of 3 [41].
Table 3 Orthogonal experiment results of paraquatbiodegradation at the remediation time of 35
days.
Experimentalrun

A:
glucose(g/L)

B:
praquat(mg/L)

C:
inoculum(%)

Paraquatremoval
(%)

1
2
3
4
5
6
7
8
9

20
20
20
10
1
1
1
10
10

100
50
10
50
50
100
10
10
100

1
10
5
1
5
10
1
10
5

70.02
91.28
95.15
87.88
97.87
86.72
95.23
93.96
86.70

Table 4 The range analysis of L9 (34) orthogonal
experiment for paraquat biodegradation.

K1
K2
K3
k1
k2
k3
R
Q

A:
glucose(g/L)
279.82268.54
256.45
93.27
89.51
85.48
7.79
A1

B:
praquat(mg/L)
284.34277.03243.44
94.78
92.34
81.15
13.63
B1

Blank
273.21
261.85269.75
91.07
87.28
89.92
3.79

C:
inoculum(%)
253.13279.72271.97
84.38
93.24
90.66
8.86
C2

CONCLUSIONS
Microbial consortium capable of degrading
paraquat were isolated from cassava rhizosphere soil.
The microbial analysis using the PCR-DGGE
technique demonstrated 6 differently visible bands
identified as S. marinum, F. xuzhouensis, A.
lipoferum, Al. xinjiangensis, X. autotrophicus and A.
amazonense. The orthogonal arrays design results
indicate that the optimum conditions for paraquatremoval was 1 g/L glucose concentration, 10 mg/L
paraquat concentration and 5% inoculum
concentration possessing paraquat removal efficiencyof 95.69%.
ACKNOWLEDGMENTS
This project was partially supported by ResearchCentre for Environmental and Hazardous SubstanceManagement, Khon Kaen University. The authors are
grateful to the Research Group for Development ofMicrobial Hydrogen Production Process from
Biomass, Khon Kaen University and Department of
Biotechnology, Kalasin University for providing the940

SEE - Bangkok, Thailand, Nov.11-13, 2019necessary laboratory facilities. We would like tothank Dr. Pensri Plangklang and Dr. Khakhanang
Ratanikom for providing the comment.

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942

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

CRAFTING A THEORETICAL FRAMEWORK ON WASTE
MANAGEMENT: A CASE FOR SUSTAINABLE CITIES
1

Jennie Lagman-Bautista1
Faculty, Holy Angel University, Philippines; PhD Candidate, University of Santo Tomas, Philippines

ABSTRACT
Theory formulation is crucial in search of a genuine panacea on Solid Waste Management Disposal. Wastes
disposal turned out to be a global phenomenon. Urban transformation amidst economic development poses
environmental degradation. Stagnation proliferates when this condition exhibited longer than necessary and cities
turned into an ecological sacrificial zone. To mitigate, the formulation of policy and implementation instruments
are vital tools to reinvent Waste Management Theory. The inner desire to preserve the future’s generation can betaken as a staggering investment in transforming urban ecology to sustainable cities. Environmental Sustainability
is entrenched on pro-active policy-making theory, delivered through practical eco-innovations, beautifully
wrapped into a well-developed waste management program and effectively measured using the triple-bottom lines.

Keywords: Waste management theory, urbanism, Policy making, Eco-innovations, Sustainability
productive and creative per capita than ruralcommunities [2].
Drakakis-Smith reiterated the principle ofsustainable development requires a triangular
relationship between economic, environmental andsocial agents in a particular community [4]. Further,
Urban sustainability compels effective policy andplanning, good governance, as well as theparticipation of local enterprises and residents [5]. Weshould not wait longer than necessary on said cities
that are highly industrialized to transform its focus onwidespread economic advancement with expensive
environmental costs and detrimental impacts to
mankind, to effect restoration phase before final
sustainability transformation occurs where and whenirreparable costs have already been inflicted [5].

INTRODUCTION
Solid Waste Management Disposal is a prevalentglobal concern, not solely in terms of waste-relateddiseases affecting living conditions, but more so froman environmental, societal, and economic aspect [1].
The world can no longer afford the time or the
resources to produce and insatiably consume endlessnovelty and needless change [2]. There is a need todeal with multiple problems at the same time,
mindfully and synergistically. UNEP lamented that
one of the central tenets of Inclusive Green Growth
Programs is that environmentally friendly
development can become a driver of job creation,
investments and economic development and these are
not economically inferior to “dirtier” sustainable
progress [3]. Hence we should start the journey inreinforcing the theories behind waste management.

Policy Making Theory
Citizens and communities tend to resist existing
policy frameworks that require to “include” them in
the implementation process, not unless direct benefits
can be derived. They oppose being “stuck” into prearranged programs that would limit their participation
to a menu of equally unacceptable options. As
alternative methods and practices evolve, this is a“fitting moment to heed to socio-environmental
methods and innovations forged not out of a social
accord, but out of social dissensus” [6]. It is thenthrough disruptions and practices of dissent by thepeople, that can possibly serve as living indicators ofwhat immediately requires to be addressed andwhere[6].
The government can proactively recognize stagesof urban transformation, promote economic growth,establish attainable goals, assign responsibilities andfacilitate strategy implementation [5]. In order to

Theory of Urban Ecology
Antrop illustrates urbanization in denoting thetransformation process of a rural living condition into
an urban-like lifestyle [4]. It involves a move fromold-fashioned cultural environments, including
informal economic and political institutions, creating
relative anonymity leading to formalized societies ofurban settings [4]. In contrast, Kelbaugh recognized
the “Theory of Urbanism” as a controlling but
neglected strategy to mitigate ecological footprint andglobal climate change [2]. The author claimed, cities
become an ecological sacrifice zone that even thegreenest of cities inflict local environmental wounds
that nature must heal, they leave wounds in pursuit ofeconomic development. Nevertheless, in the arena ofrevenue realization, Cities are generally more
943

SEE - Bangkok, Thailand, Nov.11-13, 2019achieve sustainable development, the government
must establish environmental regulations andprogrammes for supporting financial systems andfostering eco-markets [7]. Policies once formed are
implemented by means of policy instruments [7].
Vedung classified these instruments as “set oftechniques used by governmental authorities to wield
their power in order to ensure adherence and support”[7]. Government plays a crucial role as enforcer ofpolicies.
The main principle of policies on waste
programs is to protect both human health andenvironmental condition by imposing normative
behavioral consumption changes [8]. Public
perceptions can pose a threat to the acceptability andcompliance rate on the legal frameworks.
Implementing government agencies need topositively side-track public pulse [9]. Public
involvement prior to approval and implementation on
said regulations can be seen as a strategy to influence
perception, drive public effort, and produce
legitimacy for a specific regulatory proposal [9].

Eco-innovation
The initial scope of eco-innovation includes inpart the productions and processes, then on the
improvement of the management system, the creationof new markets, material flows and social ecoinnovation [7]. Eco-innovation is well-defined as “allmeasures of relevant actors which develop new
behavior, new ideas, process and products, to apply
or introduce them in the attainment of ecologicallyspecified sustainability targets that contributes tolessen environmental burdens” [13]-[7]. Simply
stated, eco-innovation is innovation in “any form”,
which is beneficial to the environment [14]. EcoSustainability innovation includes also a social aspectthat emphasizes one of the elements in TBL which
extends its scope to include institutions, markets andsocial actors [7].
Innovations include but not limited to the use ofrenewable energy technologies, green products, andpollution prevention schemes [7]. Cross-disciplinary
technological trials related to eco-innovations are thefurthermost precarious and problematic issues whena city or organization moves toward sustainability[13]. Effective eco-innovations lead the way towards
sustainable development based on the triple bottom
line sustainability [7]-[13].
The benefits of eco-innovation other thancomplying environmental regulations will also
improve economic aspect, the competitiveness ofcompanies and countries by supporting the creationof a new market for green growth products andprocesses, corresponding employment effects and soon [7]. Hence, the execution of multidisciplinary
systems and technologies concerning eco-innovationis the road toward sustainability [14].

Theory of Waste Management
The traditional waste management view is centeredon assurance compliance, risks management, healthand environmental protection that are short term
tactical [10]. The same authors reshaped traditional
waste management view into new value creation thatcan raise productivity, enhance relations, support ecoinnovations, and enable growth for long term
endeavors. But the focal point of practical waste
management lies on three vital objectives; (1) wastequantification (2) waste characterization and (3)waste management methods or practices [10]. And
the three waste management practices classification
include: (1) prevention practices comprisingstrategies on waste minimization, (2) end-of-pipe
strategies involves recovering the economic value on
waste through waste separation, recycling, proper
landfilling, incineration and (3) environmental
restoration practices, aimed at repairing leakages anddamages to the environment [11].
Cooper correspondingly classified improving
resident’s awareness and legislation as preventive
practices [10]. Hence, purportedly instrumental in theattainment of environmental and societal wellbeing aspart of the two pillars of the triple bottom line. In thesame context, end-of-pipe strategies cover waste
segregation methods that are either origin-separated
collection or destination-separated collection [12].
These end-of-pipe strategies are classified as ecoinnovations. And shredding their shadows on the lightof economic boundaries, the prevention practices areless costly but offer the highest effectiveness rate,
while environmental restorations are the mostexpensive yet yield the least effectiveness [10].

Triple Bottom-Line Concept
The triple bottom line (TBL) term was coined in the
1990s by business consultant John Elkington todescribe the economic, environmental, and social
value of an investment that may accrue outside afirm’s financial bottom line [15]. TBL or sustainableeconomic development was defined as activities,
programs or policies designed to provide or retain
jobs and wealth in ways that contribute to economic,
social, and environmental well-being over time [16].
It is distinct from economic growth or development,
which may or may not contribute to overall wellbeing including fiscal health, quality of life, resource
stewardship, and resilience [16]. This line of thinking
suggests that economic systems exist to serve humanwell-being, that human and economic well-being is
inextricably linked to environmental well-being, andthus, that human, environmental, and economic well-

944

SEE - Bangkok, Thailand, Nov.11-13, 2019

the environment [13]. Businesses must innovate torespond to environmental needs while creating a
product’s value in ever-changing consumer’s demandand lifestyle toward environmental sustainability[13]-[14].
Urbanism once embraced does not necessarily
imply placing environmental sustainability at arm’s
length. Sustainable cities may seek ways to use thecapabilities of disruptive technologies toward making
proper changes in human behavior, disruptive
technologies that change consumer behavior toward
pro-environmental
behavior.
Citiesrequireinnovative, cross-industry solutions to facilitate thecollection and disposal of solid waste. The solutions
should be replicable, adaptable, and scalable [21].
The term ‘Throw Away society’ denotes a society
with an exceptionally lofty consumption pattern anddepletion of resources generates huge volumes ofrefuse [22]. The waste volumes did not only expand
with a growing population but also evolved incharacteristics.

being must be considered in the design and evaluationof economic development efforts [16].
By considering social, environmental, andeconomic factors, TBL, or sustainable economic
development, provides a more meaningful,productive framework for achieving and measuring
economic development [16]. Specific programs withregard to training, incentives, assessment, andresearch that can advance theory and practice are
central to the success of the TBL approach.
Sustainability
Moving towards sustainability is also a social
challenge that entails international and national law,urban planning, local and individual lifestyles, andethical consumerism. The science of sustainability
has emerged in the past 30 years and at its core is aholistic approach to generate “solution-oriented
discipline that studies the complex relationshipbetween nature and humankind” [17]. Lin further
emphasize the need for Ecological Footprint to trackdown the occurrences of biocapacity deficiency, theanthropogenic impact on ecosystem and biodiversity
in order to measure sustainability. According to
Hawken like biocapacity, sustainability occurs when
the demand placed by the people and industries upon
the environment can be met without plummeting thecapacity of the environment to sustain even the needsof future generations [18].
A favorable result occurs when a National
Footprint is lesser than the ability of the environment
and natural resources to regenerate there is what wecall biocapacity reserve [19]. The presence of
biocapacity reservation does not necessarily imply
sustainability but as explained by Bastianoni andKitzes, it is essentially the minimum condition forsustainability [19]. Consistent with Daly’s two
principles of sustainability, “harvest rates should notexceed regeneration rates, and that waste emission
rates should not exceed the natural assimilative
capacities of the ecosystems into which the wastes are
emitted” [19].
A sustainable environment is the end product ofsustainable consumption. Ajzen's theory of planned
behavior was the foremost that considers end user’s
behavior in purchasing [13]. Rationality dictates theconsumer’s intention by considering these aspects:
social norms observed behavioral control and aperson’s attitude. Much of the environmental glitches
are due to human behavior when put into actions arecalledanthropogenic.
Therefore,changing
consumers' behavior toward sustainable consumption
is a necessity for a business or successful community
modeling [20]. Research studies have enunciated thata significant reduction in environmental damage ispossible if users’ behavioral purchases conform toenvironmental protection [13]. In this context, proenvironmental behavior causes minimal or no harm to

Fig. 1 Theoretical Framework on Waste Management
FRAMEWORK ANALYSIS AND VALIDATION
Progress is inevitable, hence urban transformation
occurs. The upward pressure from economic
development creates downward pressure on
environmental degradation. This condition whenexhibited longer than necessary, stagnation
proliferates and cities turned into an ecologicalsacrificial zone. To mitigate, formulation of policy

945

SEE - Bangkok, Thailand, Nov.11-13, 2019

Ecological
Sacrificial Zone

Urban Transformation

Metamorphosis to
Sustainable Cities
Implementation Instrument“A Waste Management Program”

Formulation of Policy Instruments

Economic
Development

Societal Well-being

Environmental
Degradation

TripleBottom-Line

Supported by Eco-Innovations

Fig. 2 Crafted Theoretical Framework on Waste
Management of Sustainable Cities

instruments as government sticks must transpire. And
at the end of the spectrum, regulations and policies
embodied in the implementation instruments basedon Waste Management Theory must be supported by
eco-innovations. These innovations inclusive of new
ideas, new behavior, processes, and products in sync
in a Waste Management Program measured throughenvironmental preservation/restoration, economic
resilience, and social wellbeing commonly called asthe“Triplebottom-line”.
Thereafter,themetamorphosis of cities from the ecological sacrificezone into sustainable cities will transpire.

REFERENCES[1]Cervantes D., Martinez A., Hernandez M., &Cortazar A., Using indicators as a tool toevaluate municipal solid waste management: A
critical review. Waste Management. 2018.
[2]Kelbaugh, D., The Environmental Paradox of theCity, Landscape Urbanism, and New
Urbanism. Consilience, (13), 2015, 1-15.
Retrieved fromhttp://www.jstor.org/stable/26427272[3]UNEP IGG retrieved fromfile:///C:/Users/poi/Desktop/Measuring_Inclusi
ve_Green_Growth_at_the_Country_Level.pdf[4]Zhang X., “Sustainable urbanization: a bidimensional matrix model”. Journal of Cleaner
Production 134, 2016, pp 425-433.
[5]Li Y., Beeton R., Sigler T., Halog A., (2016).
Modelling the transition toward urban
sustainability: a case study of the industrial cityof Jinchang, China. Journal of Cleaner
Production 134, 2016, pp. 22-30.
[6]Kaika, Maria. (2017). “‘Don’t Call Me Resilient
Again!’: The New Urban Agenda as
Immunology…or… What Happens When
Communities Refuse to be Vaccinated With
‘Smart Cities’ and Indicators.” Environment &Urbanization Vol. 29, Issue 1, 2017, pp. 89–
102.
[7]Jang E., Park M., Roh T., Han K., JO J., and Kim
S., Research Gate /World Sustainability Forum2014 – Conference Proceedings Paper/ EcoInnovation Policies Toward Sustainability in
Asian Countries, 2014, DOI: 10.3390/wsf-4a007.
[8] Greene K., Tonjes D., Quantitative
assessessment of municipal waste management

CONCLUSIONCity competitiveness is an important part of thenational economy. A competitive city generates wider
sources of investments and employment, not only forthe benefit of the current generation but more so insecuring the future of our grandchildren. Economic
growth will not lead to environmental degradation in
the presence of strong responsible consumption,rather it can cultivate environmental consciousness.
The inner desire to preserve the future’s generation
can be taken as a staggering investment intransforming urban ecology to sustainable cities.
Environmental Sustainability is entrenched on proactive policy-making theory, delivered through ecoinnovations and beautifully wrapped into an effective
waste management program that is satisfactorily
measured by the triple-bottom lines.

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systems: Using different indicators to compare
and rank programs in New York State. Waste
Management. Vol. 34. Issue 4, 2014, pp. 825836.
[9]Rolf Lidskog (2016). Public at Risk—Public as
Risk: Regulating Nature by Managing People,
Society & Natural Resources, 29:3, 284-298,
DOI: 10.1080/08941920.2015.1054570[10]Esmaeilian B., Wang B., Lewis K., Duarte F.,
Ratti, C., Behdad, S., 2018. The future of waste
management in smart and sustainable cities: A
review and concept paper. Waste Management
81, 2018, pp177-195[11] Zaman A., Identification of key assessment
indicators of the zero waste management
systems. Ecological Indictors. 36, 2014, pp.
682-693.
[12]Sukholthaman, Pitchayanin, Sharp, Alice. A
system dynamics model to evaluate effects ofsource separation of municipal solid waste
management: a case of Bangkok, Thailand,
Waste Manage. (Oxford) 52, 2016, pp. 50-61.
[13]Kuo T., & Smith, S., A systematic review oftechnologies involving eco-innovation forenterprises moving towards sustainability.
Journal of Cleaner Production 192, 2018, pp.
207-220.
[14]Bossle, M.B., Dutra de Barcellos, M., Vieira,L.M., & Sauv_ee, L., The drivers for adoptionof eco-innovation. J. Clean. Prod. 113, 2016,
pp. 861-872.
[15]Elkington, J., Enter the Triple Bottom Line.
2004,

http://www.johnelkington.com/archive/TBLelkington-chapter.pdf[16]Hammer & Pivo, The Triple Bottom Line andSustainable Economic Development Theory
and Practice. 2016.
[17]Lin D., Hanscom L., Murthy A., Galli A., Evans
M, Neill E.,… Wackernagel M., 2018.
Ecologicial Footprint Acounting for countries:
Updates and results of the National Footprint
Accounts, 2012-2018. Resources p7-58.
[18]Jerzy A Filar, Jacek B Krawczyk & Manju R
Agrawal, Sustainability screw: role of relative
production and abatement time scales, Journalof the Operational Research Society, Vol. 66,
Issue 8, 2015, pp. 1259-1269, DOI:
10.1057/jors.2014.39[19]Galli, A., “On the Rationale and Policy
Usefulness of Ecological Footprint Accounting(The Case of Morocco)”. Environmental
Science and Policy 48, 2015, pp. 210-224.
[20]Pialot, O., Millet, D., Bisiaux, J. “Upgradable
PSS”. Clarifying a new concept of sustainableconsumption/production based on
upgradability. J. Clean. Prod. 2017, 141, 538550. [Google Scholar][Cross Ref][21] Patil, Shivani, Zavare, Shradda, Parashare,
Rashmi, Rathod, Pooja, Babanne, Vanita,
Smart city waste management. Int. J. Eng. Sci.
2017, p. 3990.
[22]Makarichia L., Jutidamrongphan, W., Techato,K., “The evolution of waste-to-energy
incineration: A review”. Renewable andSustainable Energy Reviews 91, 2018, pp.812–
821.

947

5thInt. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C5689

HUMAN BEHAVIOUR AND WORKPLACE SAFETYOF READYMADE GARMENT FACTORIES IN DHAKA DURING FIRE: A
CURRENT SCENARIO

1

A S M Fahad Hossain1, Ishraq Tasnim Hossain2 and Prof. Dr. Mehedi Ahmed Ansary3
Faculty of Civil Engineering, Ahsanullah University of Science and Technology, Bangladesh;2Faculty of
Civil Engineering, World University of Bangladesh, Bangladesh and 3Faculty of Civil Engineering,
Bangladesh University of Engineering and Technology, Bangladesh.

ABSTRACT
Safety in a Ready-Made Garments (RMG) factory is the most salient issue especially during fire. The
precautions that should be taken by the authorities is a well-studied phenomenon but how the workers working
there are prepared to face and perform against fire during an incident is still not evaluated. Metropolitan Fire andEmergency Services Board (MFB) in Melbourne, U.S. Fire Administration’s National Fire Incident Reporting
System, National Fire Protection Association, Fire and Security Association of India and other organisations has
their regular investigation in their country about workplace safety where we have a small amount of survey inBangladesh though fire incidents have become very frequent now a days which are costing lives. These shows
despite of less facilities in factories most of the fatal injuries will not occur if they have proper knowledge ofevacuation and training of facing incidents which directs improvement of system and workers behavior. A predetermined series of questions were asked from different reputed RMG factory workers from top to bottom level
and the data was analysed to the condition of facility and psychology of workers.
Keywords:Human Behaviour, Workplace Fire Safety, Ready-Made Garments.
Government of the People’s Republic ofBangladesh. Factories operating in old buildings(buildings those were built before the code wasformulated but was in practice), have to collect
another fitness certificate from the BFSCDA, whichallows them to get a second certificate from the
Ministry of Housing and Public Works. According
to BFSCDA regulations, garment factories have totake an operational certificate at the very beginningof operation from them and this certificate have tobe renewed in every month by the respective zone
officials. BFSCDA officials check a total of 61
parameters of which 41 parameters are structural or'hard' in nature. It was defined as ‘hard’ factors as
those whose conditions cannot be changed very
quickly. Since the buildings are expected to havebeen built following the building code, our initialexpectation is that the ‘hard’ parameters would be ina better condition as compared to the ‘soft’parameters, the performance in which can change
from day-to-day due to management practices.
Two international groups of stakeholders - Alliancefor Bangladesh Worker Safety (Alliance) and
Accord on Fire and Building Safety in Bangladesh(Accord) - are currently conducting regulatory
checks and suggesting remedies for every RMG
factory of Bangladesh. Although the focus is wider

INTRODUCTION
The Ready-Made Garments (RMG) industry
occupies a unique position in the economy of
Bangladesh. It is the largest exporting industry,
which experienced phenomenal growth during thelast 25 years. It attained a high profile in terms offoreign exchange earnings, exports, industrializationand contribution to GDP of Bangladesh within ashort span of time. The industry plays a key role inemployment generation and in the provision ofincome to the poor. In this study an attempt has been
made to describe the overall scenario of Bangladesh
Ready Made Garments industry. Despite thephenomenal success of the RMG industry inremittance earning and employment potential, in thelast two decades, this sector has experienced someworst industrial accidents in the history the fire.
All factories including those in the RMG sector in
Bangladesh, have to obtain certification from
Bangladesh Fire Service and Civil Defense
Authority (BFSCDA) for their compliance with fire
regulations. Purpose-built factories that constructed
after 1993 have to comply with Bangladesh National
Building Code of 1993 (BNBC-93) and have toobtain the certification of local authorities assigned
from the Ministry of Housing and Public Works,
948

SEE - Bangkok, Thailand, Nov.11-13, 2019as “undecided”. Any other answer was considered inother category.

safety environment, fire safety forms a part of theirmonitoring process as well.
METHODOLOGY
The survey work was done in two phases. One
analysis the human behavior during fire and theother phase analyse the workplace safety for fire
hazard. In the first phase team randomly selects four
garments factory in Bangladesh for survey work.
After that the team randomly selects some workers
from the garments and asked them some predetermined questions. Then SPSS (Statistical
Package for the Social Sciences) tool is used toanalyse the survey data collected from the garments
factory. In the second phase the team collected some
information from the garments factory relevant tofire safety. The information was about factory
structure, emergency exit system arrangements for
firefighting and workers training facilities.

Figure1: Fire evacuation behavior in different
factories workers.

Data was collected by questionnaire survey fromfour factories in Dhaka named Pearl Garments
Company Ltd., MBM Garments Ltd., Cutting Edge
Garments Factory Ltd. and Cosmopolitan Industries
Pvt. Ltd- CIPL-Epic group. Data was collected using
real interaction with people in the site from officers
to workers without informing them earlier so thatcompany cannot give any training to the worker tomanipulate their opinion. There were variations intheir answers. Questions were asked to both male &female of different ages about their preparation,
attitude, training, expected time for leaving thedanger place, behavior to others while evacuating &their willing if they would help to overcome thedanger situation. Some of them were previously
experienced with fire in their workplace. Some were
new comer who didn't take training yet.
Company name
CIPL

Collected data
(person)
701

MBM
CUTTING EDGE
PGCL

364
414
291

These pie charts show us that in the event of fire in
the garments factories the workers behavior
regarding evacuating that place. In all the factories,
more than 95% which is the majority of worker will
evacuate that place as early as possible. Other 5%
workers have mix opinion about staying in the place,wait for rescue and some have no idea about what
they will do in the case of fire hazard in theirfactory. These indecisions are mostly from newly
joined people who did not get any fire training yet
and a few are because of age.
Fire Evacuation Timing Based on Gender:
Following tables show the cross tabulation between
gender and time to stop the work and leave if there isany effect or not.
Table 1: Fire Evacuation Timing on Gender (CuttingEdge)
In case of
emergency, howmuch time would ittake to stop yourwork and leave
Count
Less than
5 minuets % of
Total
Count
More
than 5% ofminutes
Total
Count
Total
% of
Total

Collected survey data was then processed in twostages. First, from the survey data an excel file wascreated for each garments factory. Then the excel
file was converted to a data dictionary. Secondly, thedata dictionary was converted to SPSS file foranalysis.
ANALYSIS AND RESULT
Evacuation Behavior: Workers were asked
about their evacuation plan and they were provided
with the options like shelter in place, evacuate. Ifthey fail to make choice, then it was considered the949

what is yourgenderMale
Female

Total

196

217

413

47.3%

52.4%

99.8%

1

0

1

0.2%

0.0%

0.2%

197

217

414

47.6%

52.4%

100.0%

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2: Fire Evacuation Timing on Gender (MBM)
In case of emergency,
what is yourTotal
how much time would it
gendertake to stop your work
Male Female
and leave
Count
191
170
361
Less than 5%ofminutes
52.5% 46.7% 99.2%
Total
Count
0
3
3
More than% of
5 minutes
0.0% 0.8%
0.8%
Total
Count
191
173
364
Total

% of

situated inside the factory. But this quantity is very
low as most of the female workers are unmarried.
Fire Evacuation Timing Based on Age: Following
bar chart summarized the cross tabulation between
escape time and age. It was asked that if the people
think they will be able to stop the work what they
are doing, stop the machine and can leave thecompound in less than 5 minutes. The age of theworkers is divided into many groups forconvenience.

52.5% 47.5% 100.0%

Total
Table 3: Fire Evacuation Timing on Gender (CIPL)
In case ofwhat is yourTotalemergency, howgendermuch time would it
Male
Femaletake to stop yourwork and leave
Count
305
384
689
Less than%of
5 minutes
43.5%
54.8%
98.3%
Total
Count
5
7
12
More
than 5
% of
0.7%
1.0%
1.7%
minutes
Total
Count
310
391
701
Total
% of
44.2%
55.8%
100.0%
Total

Figure: Cross Tabulation between Escape Time andAge (Cutting Edge)

Figure: Cross Tabulation between Escape Time andAge (MBM)

Table 4: Fire Evacuation Timing on Gender (PGCL)
In case ofwhat is yourTotalemergency, howgendermuch time would
Male
Femaleit take to stop yourwork and leave
Count
85
197
282
Less than
5 minutes % of
29.2%
67.7%
96.9%
Total
Count
0
9
9
More
than 5
% of
0.0%
3.1%
3.1%
minutes
Total
Count
85
206
291
% of

29.2%

70.8%

Figure: Cross Tabulation between Escape Time andAge (CIPL)

100.0%

Total
From the data chart it is seen that from 1770 workers
almost all the workers believe that they can stop
what they will be doing and leave the incident place
within five minutes. Only 24 workers that they willtake more than five minutes where 19 of them arefemale. This is because they are may be concern
about their children staying in day care centre

Figure: Cross Tabulation between Escape Time andAge (PGCL)

950

SEE - Bangkok, Thailand, Nov.11-13, 2019

From the bar chart it is seen that most of the workers
are from 21 to 30 years old except one factory
named CIPL where they have around 34% workers
are 19 to 20 years old. In Cutting Edge factory,
among 414 workers 412 of them said that they will
be able to move less than 5 minutes. Only 2 out of
414 workers said that they may take more than 5
minutes. This is due to position working place, andage as those people are around or above 40 years
old. In other factories, the bar chart illustrates that nomatter what the age group is majority of the people
think they will be able to stop the work what they
are doing, stop the machine and can leave thecompound in less than 5 minutes. Only a few
workers gave voice that 5 minutes is an inadequate
time for leaving. This might be due to their position
working place, and some of them are willing to help
in stopping fire and in some case the machine on
which they are working with is complicated to stop.

positive result that all the workers conduct regularfire drill. Authority also learnt from previous fatal
accidents and they are more aware about there
workers safety now. Some garments have committee
to find out the lackings of fire sare safety and to
conduct regular fire drill. Almost all the factories
have warning system in each floor which isreachable to all part of the floor.
Evacuation Plan: The next pie charts below
illustrate the opinion of the workers about how they
prefer to evacuate in case of fire incident. They have
options like evacuate themselves alone or along with
their colleagues.

Capacity to Protect Against Injury: The following
pie charts show the result of the question “Do you
have necessary preparation to protect yourself frompossible injury?” The answer was limited to yes andno.

Figure: Capacity to protect against injury in different
factories workers.

Figure: Evacuation plan in different factories
workers.
From the pie charts it is seen that in all of the four
garments around 70% of theworkers want toevacuate with their colleagues where rest people
think they will evacuate themselves alone as early as
possible. This is because they are going throughregular training and fire drill from company. But still
most of the elder people aged above 35 who havefamily do not want to take risk in case of fire as they
have seen some fatal incidents earlier. In total, it is apositive motivation among most of the workers.

From the pie charts it is clear that majority of thepeople think they can protect themselves in the caseof injury during fire. This is a great turnover in thementality of workers as they get regular trainingfromthecompany
authority.
In
the
COSMOPOLITAN INDUSTRY PRIVET LIMITED(CIPL) all the 701 workers are confident about there
protection against injury. Only a few workers fromother garments do not have the necessary knowledge
about how to protect themselves in the event where
injury can occur. This is because they are new andyet to receive training from the company.

Education and Evacuation Plan:The following
charts represent changes in evacuation plan with thelevel of education of different level of employees.
Most of the workers have studied from Primary
School Certificate (PSC) to maximum Higher
Secondary Certificate (HSC). Only manger and toplevel employees are graduated from university.
Some of them has masters but they were consideredin University group as well. Security guards andother staffs who are not directly related to
production have no educational qualification insome case and they are introduced by ‘None’.

Regular Fire Drill: Total 1770 people werequestioned from four garments factory that if they
have regular fire drill in their factory. It is a very
951

SEE - Bangkok, Thailand, Nov.11-13, 2019

Figure: Willingness to stop fire in case of fireincident in different garments workers.
The bar charts show that more than half workers
from all the garments are willing to help stopping
fire during a fire emergency. Among them more than
70% of CIPL workers have positive thinking about it
where PGCL have 53.6%. This is because they haveless worker and CIPL has 2.5 times more worker
than PGCL and most of them are young andenergetic. This is a positive scenario in RMG
factories. It is happening because authority andworkers both are conscious about their safety andrules during an incident. And the dramatic changes
in mentality and behavior of workers are the resultsof regular training and fire drill in working place.
CONCLUSION
This paper explored the current behavior of workers
in different RMG factories from manager to operator
during a fire incidence. The response is very positive
specially their willingness to evacuate withcolleagues and help stopping fire. These are becauseof regular training and fire drill arranged from theauthority. This positive behavior will not only save
lives but also it will save a lot of goods and reduce a
lot of property damage. This is a significant
movement in RMG sector of Bangladesh forworkers as well as authority after some big fatal
incident and bad reputation regarding workplacesafety. This observation gives an insight to theturnover in workers behavior during fire incident
and allows the investors a second thought before
leaving this sector. By conducting this type of
behavior analysis will help to avoid accident related
injury or death it will also provide perception aboutstrength and weakness of that company to face fire
hazard.

Figure: Education and Evacuation plan in different
factories workers.
These charts show the relation between escape planand highest level of education. It shows that nomatter what the level of education is majority of thepeople will always try to evacuate with theircolleagues.
Help Stopping Fire:The following bar chart shows
the outcome of the question “In case of fire, will you
help stopping the fire or evacuate?”. Option was ‘I
will help stopping fire’ and ‘I will evacuate’.

ACKNOWLEDGMENTS
Authors like to give special thanks to Ahsanullah
University of Science and Technology (AUST),
Dhaka, Bangladesh for giving the opportunity to
conduct the survey. Authors also like to give special
952

SEE - Bangkok, Thailand, Nov.11-13, 2019[4] Campbell R., "Fires in Structures underConstruction, Undergoing Major Renovation or
Being Demolished", NFPA research, April
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thanks to S. M. Tanveer Anjum, Jenath Sultana Joya
andAfsana Zaman Pranty for helping in the survey
and collecting data.
REFERENCES[1] Wadud Z.,Huda F.Y., "Fire Safety in the
Readymade Garment Sector in Bangladesh:
Structural
Inadequacy
vs.
Management
Deficiency", May, 2016.
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953

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ULTRAFINE PARTICLE FILTER DESIGN FOR MOTORCYCLEEMISSION EXHAUST SYSTEM: A HIGH VOLTAGE
ELECTROSTATIC-BASED SYSTEM
Arinto Y. P. Wardoyo 1, Hari A. Dharmawan1, Muhammad Nurhuda1, and Arif Budianto1
1
Mathematics and Natural Sciences Faculty, University of Brawijaya, Indonesia

ABSTRACTA large number of motor vehicles in the world have been linked to the increase of the emissions, such as
particulate matters and gases. These pollutants, especially for the particulate matters with the diameter less than
0.1 micrometer or ultrafine particles, become detrimental thing to the natural environment and human health.
There is a need to develop a better method to decrease the particles. Thus, one step ahead of the technologicalimprovement in the transportation sector is the development of an emission filter applied in a motor vehicle
exhaust system. According to this background, we developed an ultrafine particle filtering system based on anelectrostatic principle using a direct current - high voltage. The filter is based on a electrostatic principle by using
uses aluminum as the anode and cathode. This filter was tested under the different DC voltage of 100, 200, 300,
and 400 Volt. The efficiency of the filter was tested by measuring the motor cycle ultrafine particles before andafter applying the electrostatic filter. The particle concentrations were measured by using a TSI P-Trak Ultrafine
Particle Counter model 8525. The result shows that the designed filter works well in reducing the ultrafine
particles., with the efficiency of 7% to 46%. The filter efficiency depends on the applied voltage.
Keywords: Electrostatic filter, Motorcycle emission, Ultrafine particles, Efficiency
matter with a diameter less than 0.1 μm) with theemission factors up to 5 g/ km for nitrogen oxides
and 0.001 g/ km for PM0.1 [9]. A recent study also
shows that vehicular traffic becomes a contributor to
air pollution. It shows a high amount of CO2, CO,
NO, SO2, and PM in which dominantly emitted byfour-wheeler gasoline vehicles [10].
A proper approach to dealing with the motor
vehicle emissions must be integrated with efforts todecrease the emissions. For an example, improving
or mitigating motor vehicle emissions only inexisting and future vehicles and traffic by improving
engine efficiency and traffic management is notquite adequate to decrease the emissions in theambient air. Selecting different fuels, or developing
more efficient vehicle technologies or fuel additive
also need more systems. Another proper approach isurgently needed.
One step of technological improvement in thetransportation sector is the development of anemission filter applied in a motor vehicle exhaustsystem. This particulate matter filtration system canbe found as an electrostatic filter, a radiation filter,
and a porosity filter. The electrostatic principle is anelectricity-based filtration system for reducing
particulate matter, i.e., a DPS (electrostatic diesel
particulate matter filtration system) technology for adiesel heavy-duty vehicle exhaust system [11]. Thiskind of filtration technology had also been studied
with a combination of a diesel oxidation catalyst andhad been applied in non-road diesel machines [12].

INTRODUCTION
The transportation sector has been growing fromyear to year. It is not only the developing
technology, but also the motor vehicle usage in theworld is increasing, as expected in Asian countries[1,2]. As the impact of this growing usage, theactivity of transportation mode, especially for the
motorcycle, exceeds the other kinds of motor
vehicles. This phenomenon can be found in many
big cities in the world, such as Hanoi, Jakarta, andMacao [3,4].
Besides, due to transportation sector activities
using a motor vehicle, a large number of emissions
accumulate and spread around ambient air. As
confirmed in emission modeling, the emission isstrongly related to vehicle number [5]. Furthermore,these emissions can be found as gaseous and PM(particulate matter) pollutants. For example, PM10
(particulate matter with a diameter less than 10 μm)
with a high concentration of heavy metals (such as
Ba, Fe, and Cu) can be identified in the area with ahigh traffic intensity [6]. Transportation sector also
contributes to CO2 (gaseous emissions), as the resultof a combustion process [7]. As confirmed in theprevious study of International Energy Agency(IEA), 23% of the total carbon dioxide emissions in
the world was contributed by the transportation
sector, including automobiles, light trucks, freighttrucks, and buses [8]. A heavy duty vehicle such as
bus can emit nitrogen oxides and PM0.1 (particulate
954

SEE - Bangkok, Thailand, Nov.11-13, 2019In a motorcycle exhaust system, a porosity-based
filter has been developed to reduce PM2.5 emission
with the efficiency of 35 – 64% [13]. Another study
shows a significant performance (up to 24%) of aheat radiation-based filter when applied in a
motorcycle exhaust system [14].
It is true that emission filter technology is a needto reduce air pollutant in ambient air, especially forthe contaminant emitted by the motor vehicle.
However, different sides must be taken into accountwhen developing an exhaust emission filtration
system. As an alternative approach, electrostatic
principle has a high potential for the real applicationin decreasing motor vehicle exhaust emissions. This
principle somehow needs less energy and budget.
Moreover, the performance and application ofelectrostatic filtration system are relatively better
than the other methods.
MATERIALS AND METHODS
Motorcycle Samples
A standard motorcycle (in good condition, no
modification) was used as the ultrafine particles
source. This motorcycle sample had an automatictransmission with the engine cubication of 125 cm3.
It used CDI (Capacitor Discharge Ignition) for theelectronic ignition system (fuel type: gasoline,
research octane number 90) and carburetor for thefuel supply system.

Fig. 2The schematic of the signal conditioning
circuit.

The signal conditioning circuit consists of avariable resistor to generate different voltage. A
center tap transformator (T1) and 2N3055 transistors(Q1 and Q2) are used to amplify the input voltage(12 Volt) to 220 Volt AC (alternating current). Then,
this resulted voltage is inverted using a diode bridge
circuit (BR1). The output signal is filtered using anelectrolytic capacitor (C2).

Filter Fabrication
The electrostatic filter (Fig.1) was made ofaluminum plates that were consisted of anodes andcathodes. These electrodes were 1.4 mm apart (d).
This filter gap was chosen due to the dimension of
the motorcycle exhaust system. The filter probes
were connected to the high voltage source with adirect current (DC). This voltage was obtained byamplifying the standard accumulator voltage, 12Volt DC, with a signal conditioning circuit (Fig.2).
As the result, there were four different voltages togenerate an electric field (E), with the variations ofV1 (100 Volt), V2 (200 Volt), V3 (300 Volt), and V4(400 Volt). Each voltage variation was applied toeach filter to investigate the best efficiency.

Filter Performance Test
Figure 3 shows the set-up of the filter
performance test. Each filter was tested toinvestigate the filter performance related to filter
efficiency (Ef) in reducing ultrafine particles
concentration. This test was applied in the 125 cm3
motorcycle sample for 60 minutes per voltage
variation (with the interval time of five minutes)[13]. Ultrafine particle concentrations before (Cin)and after (Cout) applying the electrostatic filter were
measured using a TSI P-Trak Ultrafine Particle
Counter, model 8525. The input and output emission
temperatures (Tin and Tout) were measured using
digital thermometers (with thermocouple type-K
sensors). The flow-rate of the emission (vout) was
measured using a Kanomax Anemomaster, model A031. The filter efficiency was calculated using Eq.
(1) below [13].
C -C

Fig. 1

Ef = inC out x 100%in

The schematic of the filter.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 Ultrafine particle concentrations before
passing through the filters, Cin, from threetimes measurements (1st - 3rd)Times(minutes)Fig. 3

5
10
15
20
25
30
35
40
45
50
55
60

The set-up of the filtration test using
motorcycle sample.

Ultrafine Particles(x103 particles/ cm3)
1st
2nd
3rd
18.5
18.2
18.2
18.5
18.4
18.5
18.4
18.1
18.4
18.4
19.3
18.2
17.5
20.2
17.7
17.8
19.5
17.6
17.7
18.2
17.8
17.6
16.9
17.4
17.4
16.7
17.2
17.1
17.2
17.4
16.8
16.7
17.3
16.1
15.7
17.1

Statistical Analysis
Table 2 Ultrafine particle concentrations of thetested filter after passing through the filter,
Cout (mean ± SD)

All recorded values were expressed as mean ±SEM (standard of means). The difference between
filter performance was analyzed using an ANOVA(analysis of variance) test, in which p < 0.05 wasconsidered statistically different. The correlation
between applied voltage and filter performance wasapproached using a 2nd order of polynomial
regression model, in which R2 < 0.70 was consideredcorrelated [15]. All statistical analysis was
performed using Microsoft Excel 2016.

t
(min)
5
10
15

RESULTS AND DISCUSSION
20
Ultrafine Particles Concentration
25
The filters were installed on the motorcycle
exhaust system in order to measure the ultrafine
particle concentrations. These measurements wererepeated three times for each voltage variation, V1,
V2, V3, and V4. These measurements were done for
60 minutes for each measurement, with the interval
time of five minutes. All results were shown in
Table 1-2 below.
According to the results, the filters were tested
under different voltage variation in order toinvestigate the influence of the high voltage level inthe filtration system. On each measurement result,the ultrafine particle concentrations without filters
had a similar trend, where the highest concentrations
were obtained at the first minute (minute 5).
Meanwhile,theseconcentrations
decreasedsignificantly in the last measurement time.
Interestingly, the installed filters, with the used ofvoltage variations generated lower concentrations,compared to Cin (as seen in Table 2).

30
35
40
45
50
55
60

956

Ultrafine Particles (x103 particles/cm3)
V1
17.1 ±
0.5
16.8 ±
0.3
16.5 ±
0.7
16.8 ±
0.9
16.4 ±
1.3
16.1 ±
0.9
15.8 ±
1.1
15.8 ±
1.4
15.2 ±
2.0
15.5 ±
1.3
15.5 ±
1.3
15.2 ±
0.8

V2
16.5 ±
0.1
16.1 ±
1.1
15.6 ±
1.3
15.4 ±
1.9
15.3 ±
2.1
15.2 ±
1.9
15.2 ±
1.9
14.8 ±
2.2
14.9 ±
2.0
14.9 ±
1.6
14.6 ±
1.7
14.6 ±
1.9

V3
15.0 ±
0.5
14.6 ±
1.2
14.5 ±
1.3
14.4 ±
1.9
13.9 ±
2.1
13.3 ±
1.9
13.2 ±
1.9
12.8 ±
2.2
12.7 ±
2.0
13.0 ±
1.6
12.4 ±
1.7
12.4 ±
1.9

V4
12.6 ±
0.8
11.1 ±
1.1
11.2 ±
0.6
11.4 ±
0.1
10.4 ±
0.6
10.4 ±
0.8
10.0 ±
0.7
10.0 ±
0.2
10.0 ±
0.5
0.9 ±
0.9
0.9 ±
0.3
0.9 ±
0.3

SEE - Bangkok, Thailand, Nov.11-13, 2019

After using the filters, the ultrafine particle
concentrations decreased significantly, compared toCin (p < 0.05). These results were consistent for all
voltage samples. According to Table 2, V4 yields thelowest ultrafine particle concentrations. On eachsampling time, V4 emitted least ultrafine particle
concentrations compared to V3, V2, and V1. The
highest concentration in V4 is 12.6±0.8 particles/
cm3, in which this value is obtained from three
repeated measurements. Meanwhile, the lowest
concentration in V4 is referred to minute 60 (lastminute). These values are significantly different withthe results yielded by V1, as the lowest applied
voltage.
V1 has more ultrafine particle concentrations,compared to V4. The lowest ultrafine particle
concentrations in V1 is up to 15.2±0.8 particles/ cm3.
When we compare the values, the highest
concentrations of V4 is only 74% of the highest
concentration obtained in V1. These results indicatethat the applied high voltage influences the reductionof ultrafine particle concentrations emitted by
motorcycle sample.

Fig. 4

The association of applied voltages andfilter efficiencies (mean±SD).

According to the measurement results, there is alittle difference between emission velocity before
and after passing through the filter. This value is not
significant, since p < 0.05. However, a little changeof emission velocity may indicate that there is noemission feedback to the engine due to the filter
construction (filter blocking effect).
The filter performance is mostly influenced by
the electrostatic force F and electric field E. In theelectrostatic theory, voltage (V) is linearly correlatedwith the electric field, E (Eq. (2-4)). According tothis theory, a higher electric field is caused by ahigher voltage given.

Filter Efficiencies
Having measured the ultrafine particle
concentration, we compared the filter performancefrom the first minute (minute 5) to the last minute(minute 60). Statistically, there is a significant
difference in filter efficiency, since p < 0.05
(illustrated in Fig.4). V1, as the lowest voltage,
generates 7% to 12% of filter efficiency, in which
the highest efficiency is obtained from the 30th
minute. This result indicates that V1 has a saturated
trend in a half time of the measurement, indicating
the saturated zone of the filtration performance.
The similar trend can be found in V2 and V3. In
V2, the efficiency is 9% in the first five minutes.
This value increases until 17% in minute 30. After
that, the performance was drop to 11% in the lastminute after passing the saturated point. Comparedto V2, V3 has better efficiency. V3 has 17% to 27%,
10% higher than V2 and 15% higher than V1.
Meanwhile, the largest voltage V4 has the best
filter performance with the highest filter efficiency,
46% on the last minute (60th minute). From thegraphic below (Fig.4), a different trendline can be
identified, since the saturated point is not pointing
the half-time (30th minute) of the measurement
anymore. Statistically, the difference between eachsampling time is shown by the p-value (p-value isless than 0.5). It shows that the filter performances
are time-dependent and voltage-dependent.

V

E =d

(2)

so:
V=Ed

(3)

and:
F

E =q

(4)

As the impact, V4, as the highest voltage, has thehighest E. Meanwhile, the lowest voltage V1, has thelowest E. According to Eq. (4), E is linearlycorrelated with force F. That is why, by using a
constant filter gap (d = 1.4 cm), the value of F isonly influenced by the used V. As espected, we
found that the correlation between the applied
voltage and filter efficiency was positive linear, as
the usage of a constant filter gap (R2 > 0.89). Basedon the calculation, the electric field of the filters is in
the range of 7.14 x 103 N/C to 28.57 x 103 N/C. The
highest electric field is referred to 400 Volt, V4,
while the lowest one is referred to the lowest voltage
used, 100 Volt (V1) Fig.5.

957

SEE - Bangkok, Thailand, Nov.11-13, 2019ACKNOWLEDGMENTS
All authors wish to acknowledge the role of theIndonesian Ministry of Research, Technology, andHigher Education as the funding source. The
author’s team also acknowledge all members ofLaboratory of Air Quality Research and Astro
Imaging, Physics Department, Brawijaya University:
Eko Teguh P. Adi, Buyung Wisma, Agung, Nia,
Alma, Vio, Lisa, and Hamid, for their excellent
hands and efforts during the experiment.
Fig. 5

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The association of electric field and filter
efficiencies (mean±SD).

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In the case of time-dependent ant the influent ofengine temperature (Teng), a longer time means that
more fuels (m) are used to produce energy. As afundamental law, energy is neither created nor
destroyed, and it only changes its form. As aconsequent, many formulas of energy exist. Thus,
this energy can be found as thermal energy (Q) andother forms of energies, where:
Q = m c ΔT

(5)

Based on Eq. (5) above, it is shown that Q depends
on fuel consumption in the quantity of mass, m, witha constant c (specific heat). A higher heat Q meansthat the change of temperature (∆T) is also higher.
According to the previous studies, the time of
motorcycle warming up process may influence theengine temperature Teng. In an idling and static
position (1000 RPM, cold start of warming up), we
found that a longer time (t) generated a higher
engine temperature [16,17]. This term may impact
the increase of output emission temperature, since
the emission flows are laminer inside the system.
This increase is linearly correlated with the increaseof time and engine temperature.
CONCLUSIONSThis paper integrates high voltage DC
electricity with electrostatic principle to decrease theultrafine particle concentrations of motorcycle
emissions. An electrostatic-based filtration system is
adapted to capture the particulate matters with thediameter less than 0.1 μm emitted by the motorcycle
exhaust system. The high voltage variations, 100
Volts to 400 Volts DC, enable to estimate emissions
decreasing due to the applied voltage. According to
the results, a higher voltage generates a higher
filtration performance. The highest efficiency, 46%,
is obtained from 400 Volts DC. Meanwhile, thelowest voltage, 100 Volts DC, generates the lowest
filter efficiency, 7%.
958

SEE - Bangkok, Thailand, Nov.11-13, 2019

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Cho G. B., Lee Y. K., and Kim Y. J.,
Development of electrostatic diesel particulatematter filtration systems combined with ametallic flow-through filter and electrostatic
methods, Int. J. Automot. Technol., Vol. 11,
2010, pp. 447–453.
[12] Dou D., Application of diesel oxidation
catalyst and diesel particulate filter for diesel
engine powered non-road machines, Platin.
Met. Rev., Vol. 56, 2012, pp. 144–154.
[13] Hajar U., Wardoyo A. Y. P., and Masruroh,
Developing and characterization of an ultrafine
filter made of banana leaf and water hyacinth
to reduce motorcycle emission, Applied
Ecology and Environmental Research, Vol. 17,
2019, pp. 1959–1965.

[14] Wardoyo A. Y. P. and Dharmawan H. A.,
Developing reheated motorcycle exhaust forPM2.5 emission, International Journal of
GEOMATE, Vol. 16, 2019, pp.109–116.
[15] Wardoyo A. Y. P., Budianto A., andAbdurrouf, Filtration of submicron particles
from motorcycle emission using a DC low
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pp. 1725–1728.
[16] Bokde K. K. and Waghmare A. V., Cold start
performance enhancement of motorcycle
catalytic convertor by latent heat storage
system, Int. J. Innov. Res. Sci. Eng. Technol.,Vol. 2, 2013, pp. 372–377.
[17] Iodice P. and Senatore A., Exhaust emissionsof new high-performance motorcycles in hot
and cold conditions, International Journal ofEnvironmental Science and Technology, Vol.
12, 2015, pp. 3133–3144.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EXPERIMENTAL STUDY ON SOIL IMPROVEMENT OFCOHESIVE SOIL FOR CONSTRUCTION FIELD
Shoji Kamao
Department of Civil Engineering, Nihon University, Japan
ABSTRACT
Treatment and disposal of construction waste soil and sludge is one of major problem in Japan. The author
tries to make effective use of construction waste soil and sludge, in particular, aim to improve the soil propertiesof cohesive soil and to make it a resource for backfill materials and something like that. Many recycling
technologies for construction waste soil and sludge has been proposed so far. The purposes of this study were tounderstand the change characteristics of water permeability and water retention by adding soil improvement
materials (stabilizer) to cohesive soil, and to understand the effect of additive rate of stabilizer and initial watercontent of cohesive soil. Permeability test and water retention test were conducted with the change of bothconditions, as the parameters in this study.
Keywords: Construction waste soil, Permeability test, Water retention test, Laboratory experiments, cohesive soil,laboratory water permeability test and water retention
test in order to make clear the effects of the additive
rate of stabilizer and initial water content of cohesive
soil, which was marine clay sampled in Tokyo.
As the experimental results, it was found that ahigh stabilized effects can be obtained by using thisstabilizer, and this treated soil has the possibility ofapplying to construction materials.

INTRODUCTION
Treatment and disposal of construction wastecohesive soil is one of the major problem in Japan.
Until recently, both construction waste cohesive soil
which has low water content, and construction sludge
which has high water content, were disposed to thereclamation. However, the environmental impact by
the reclamation with waste cohesive soil andconstruction sludge became serious problem, "therecycling and the re-use" has been required instead ofreclamation.
The method of dehydrating the water from theconstruction sludge and adding soil stabilizer such as
cement is one of the major recycling methods.
Tsuchida et-al [1] have been carried out a series oflaboratory experiments to propose the prediction
method of the unconfined compressive strength ofcement treated soil. However, chemical andenvironmental effects on soil due to cement cannot beignored, various methods have been proposed bymany researchers (for example, Tran et-al [2]).
In this study, the author has been investigated theusefulness of the soil stabilizer which are newly
developed by Environmental Health Laboratory CO.,LTD. [3] for agricultural purpose, to the construction
field. This stabilizer is featured by the low impact on
the environment because it is made of shelly fossil
and gluten. Moreover, it has been recognized that it
has the effect of improving the soil and keeping thesolidification state for a long time when even a small
amount is added. We conducted a laboratory
permeability tests and water retention tests to study
the changing properties of the soil by adding thestabilizer to soft clay.
In this paper, the author carried out a series of

USED SOIL AND THE SOIL STABILIZER
The soil used for this study were the cohesive soil
(marine clay) sampled in the Tokyo metropolitan area.
The typical properties of used soil are shown in
Table-1.
Table 1 Typical profiles of cohesive soil (clay)

The soil stabilizer is produced in the following
process: the shell fossil is heated up to 400 to 800°C;
it is broken into particles with 0.1 to 10-9 mmdiameter; and the particles are mixed with gluten
heated to 50 to 95°C. The main improvement effectof the soil stabilizer is to aggregate the soil particles,
960

SEE - Bangkok, Thailand, Nov.11-13, 2019shows the water retention test apparatus. Whileleaving them for 24 hours (1 day), the amount ofwater coming out from the bottom of the specimens
was measured. In this study, the water retention was
defined from the amount of water coming out of thesaturated specimens due to gravity, whichcorresponds to a pF value of 1.8. [5]which enlarges the voids to make the soil specimens
more water retainable and air permeable. Highworkability is also the improvement effect due torapid solidification.
PERFORMED TESTS
Permeability Test
The falling head permeability test method was asfollows [4]:The specimen for the permeability test was madeby adjusting the improved soil to a specified densityand filling it in molds with 6.0 cm diameter and 2.0
cm height. Fig. 1 shows the permeability test
apparatus using oedometer device. Porous stones
were placed at the top and bottom of the specimens,
and they were permeated from the bottom surface
through a standpipe for certain period of time.
Coefficient of permeability of the specimen is
calculated using Eq. (1).

𝑘

.

log

Fig. 2 the water retention test apparatus
Improvement Method of Cohesive Soil

(1)

Improvement method for cohesive soil in thesetests, a predetermined of soil stabilizer was added tothe dried cohesive soil whose initial water content
was adjusted to be 30 to 85% and mixed thoroughly.
The additive rate of the stabilizer was varied from 0
to 30 % of dry soil weight in Eq. (2).

where a is cross sectional area of standpipe, A is crosssectional area of soil specimen, L is height of soil
specimen, t is time and h is head of water, respectively.

aw= c / ms * 100(%)(2)

where c is weight of the added stabilizer and ms isweight of dry soil.
When the initial water content was a high value
exceeding 50%, 3% of bentonite was added to makethe soil viscous.
EXPERIMENTAL RESULTS
Relationship between the additive rate of soil
stabilizer and coefficient of permeability
Fig. 1 The permeability test apparatus(oedometer device)

Addition of the soil stabilizer to the cohesive soil
with a 40% water content aggregates the particles of
the cohesive soil, which increases permeability of thecohesive soil. Fig. 3 is the graph showing thecoefficient of permeability and additive rate of soil
stabilizer from the results of the water permeability
tests for the improved soil. The vertical axis of thegraph represents the coefficient of permeability andthe horizontal axis, additive rate of stabilizer. The

Water Retention Test
The water retention test method was as follows:
The improved soil was put into plastic molds with 5.0
cm diameter and 10.0 cm height, and water waspoured to 1 to 2 cm above the soil surface to prevent
dryness from the specimen after saturation. Fig-2
961

SEE - Bangkok, Thailand, Nov.11-13, 2019

tests were conducted at the 0 to 30% stabilizer
additive rate, where the 0% stabilizer additive ratemeans only the cohesive soil. It should be noted thatthe additive rate is defined as the weight ratio of thestabilizer to the dry soil in Eq. (2).
A change in the coefficient of permeability of thecohesive soil by solidification tends to be
proportional to the stabilizer additive rate. The results
indicated the coefficient of permeability at the 30%
stabilizer additive rate was higher by approximately 3orders than that at the 0% additive rate.

Fig.3

Relationship between coefficient
permeability k and additive rate aw

Results of the tests with various initial watercontent
After the cohesive soil before improvement was
adjusted to achieve the various water content (initialwater content) ranging from 30 to 80%, the soil
stabilizer was added to it and mixed to improve thesoil. The water permeability tests were conducted forthis improved soil. The stabilizer additive rate was set
to a fixed value of 10%.
Fig. 5 shows the relationship between the water
permeability coefficient and initial water content
obtained from the water permeability tests. The
coefficient of permeability tended to slightly increase
up to about 60% of the initial water content, but it
tended to slightly decrease more than that. This may
have been caused by inhibition of solidification byexcessive water. Thus, we conducted the similarwater permeability tests for the improvement soil
with 3% of bentonite added to reduce the amount ofwater in the soil, and to increase viscosity of the soil.
As shown in Fig. 6, the coefficient of permeabilityrose with a rise in the initial water content whenbentonite was added. It can be thought that thecoefficient of permeability rose because bentonite
absorbed water in the soil, which avoided inhabitationof solidification. The results demonstrated thepossibility in which the solidification effect of the soil
stabilizer for the specimens with high water content
such as construction sludge could be obtained byadjusting the water content. Figure 7 is an
overlapping drawings of Fig. 5 and Fig. 6.

ofResults of the water retention tests
Fig. 4 shows the relationship between elapsed
time and the amount of dehydration (water comingout) of the improved and saturated soil specimens, foreach stabilizer additive rate. No significant difference
was observed between 10% and 20% additive rate;
however, the dewatering amount tended to decrease
with an increase in the stabilizer additive rate. It was
confirmed that addition of the stabilizer improved
water retainability of the particle surface of thesolidified improved soil.

Fig.

Fig. 4 Relationship between elapsed time andamount of dehydration
962

5

Relationship between coefficient of
permeability k and initial water content w0(30<w0<70%, without bentonite)

SEE - Bangkok, Thailand, Nov.11-13, 2019

proportional to the stabilizer additive rate. Coefficientof permeability at the 30% stabilizer additive rate washigher by approximately 3 orders than that at the 0%
additive rate.
The dewatering amount tended to decrease withan increase in the stabilizer additive rate. It was
confirmed that addition of the stabilizer improved
water retainability of the particle surface of thesolidified improved soil.
The initial water content will affect thesolidification. However, it was found that the effectcan be reduced by increasing the viscosity.
Fig.

Fig.

6

7

Relationship between coefficient of
permeability k and initial water content w0(50<w0<90%, with bentonite)

ACKNOWLEDGMENTS
All laboratory experiments were done by thestudent member of Environmental Geotechnics
Laboratory, College of Science & Technology, Nihon
University. I would like to express the deepest
appreciation to them.
REFERENCES[1] Tuchida, and Tang: Estimation of compressive
strength of cement-treated marine clays with different
initial water contents, soils and Foundation, pp359374, Vol.55, No.2, 2015.
[2] Tran, Satomi and Takahashi: Study on strength
behavior of cement stabilized sludge reinforced with
waste cornsilk fiber, International Journal of
GEOMATE, Nov., Vol.13, Issue 39, pp.140-147,
2017.
[3] Environmental Health Laboratory CO., LTD:
http://www.kankyo-eisei.co.jp/index.html,(In
Japanese only)[4] JIS (Japanese Industrial standard) A 1218: Test
methods for permeability of saturated soils.
[5] Water retention test (DOBOKUKANRI SOGO
SHIKENJYO),
http://www.dksiken.co.jp/wordpress/uploads/2015/0
6/tuthinohosui.pdf, (In Japanese only)

Relationship between coefficient of
permeability k and initial water content w0(30<w0<90%)

SUMMARY
The summary of this study is as follows:
A change in the coefficient of permeability of thecohesive soil by solidification tends to be963

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ANALYSIS OF HABITAT AREA FOR ENDANGERED SPECIESUSING MAXENT BY ROAD CONSTRUCTION AND
HOUSING LAND DEVELOPMENT IN CHIBA, JAPAN

1,4

Hideyuki Ito1, Koji Hayakawa2, Makoto Ooba3 and Takahiro Fujii4
College of Science and Technology, Nihon University, Japan; 2Chiba Prefecture, Japan;
3
National Institute for Environmental Studies, Japan

ABSTRACT
Chiba prefecture in Japan is abound with rich nature and surrounded by many rivers and sea. But, the numberof endangered species in Chiba has been increasing after the World War II because various habitat have been
destroyed by rapid urbanization. However, there are few researches that analyzed the time-series change of amountof green area and habitat area for endangered species taking adverse impacts by constructing roads and residential
land development into consideration in Chiba, Japan. Thus, in this research, we estimated the change of green areaand habitat area for some endangered species using MaxEnt (Maximum Entropy Modeling) software for modelingspecies niches and distributions. As the result, it was shown that the green space area and water environment
including rivers, lakes, ponds and coastal area has decreased while the buildup area has increased from 1976 to
2009. Also, it was concluded that total habitat possibility area of the ruddy crake, red fox, Japanese skink andTokyo salamander have decreased by 3.6%, 6.0%, 1.6% and 0.7%, respectively.

Keywords: MaxEnt, GIS, Endangered Species, Green Area

MaxEnt estimates the parameters of the appearance
characteristic function by applying the principle ofmaximum entropy algorithm (Phillips et al. [6]). In
this MaxEnt, the following three analyses are
possible; 1) quantification (visualization) of suitable
habitat area, 2) calculation of contribution rate forrespective environmental factors, 3) comparison of
before and after time series by model construction.
For example, MaxEnt is utilized to estimate thesuitable habitat area of Chinese Alligator that is a
critically endangered crocodilian and predicted its
distribution in Anhui Province, China (Pan et al. [7]).
West et al. [8] developed a presence-only model ofinvasive cheat grass (Bromus tectorum) distribution
in Rocky Mountain National Park, Colorado, USA infrom 2007 through 2013 fit with limited data tocompare with the result of GLM (Generalized Linear
Model). Remya et al. [9] showed current and future
habitat suitability distribution of Myristica
dactyloides Gaertn, a medicinally and ecologicallyimportant tree species by using a MaxEnt species
distribution model in order to implement sustainable
conservation or adaptation strategy. Matyukhina et al.
[10] constructed the model of the geographic
distribution of Amur tigers required based on the
MaxEnt algorithm using a dataset of 1,027 tiger trackrecords and a set of environmental variables, such as
distance to rivers, elevation and habitat type, andanthropogenic variables, such as distance to forestand main roads, distance to settlements andvegetation cover change in the Russian Far East.

INTRODUCTION
Chiba Prefecture is blessed with water and green
nature, because it is surrounded by the sea and rivers
on all sides. On one hand, with the rapid developmentof transportation infrastructure such as the opening ofrailways, Narita Airport, and Aqua line, urbanization
has progressed, resulting in a decrease in the habitatsof organisms such as forests and wetlands, andendangered species tend to be increasing.
For the changes in land used, many of theprevious studies have analyzed the area and green
coverage depending on the land use classification.
For example, Iwasaki et al. [1] discussed the habitatof Japanese monkeys based on the analysis of thetemporal changes in land use. Gon et al. [2], Ikemi etal. [3] and Ohara et al. [4] have developed methods tocomparatively analyze previously documented dataand electronic data using GIS (Geographic
Information System). However, the land use
classification must be reorganized to compare fairly,
because it changes depending on the publication yearof the maps. Miyamoto [5] evaluated suitable habitat
areas using MaxEnt (Maximum Entropy Modeling),
which can estimate the habitat probability of animals.
MaxEnt is an open source for modeling tool in which
the habitat area is estimated by modeling theexistence probability of species and various
environmental factors using the appearance data oforganisms whose existence has been confirmed andvarious environmental data from the whole target area.
964

SEE - Bangkok, Thailand, Nov.11-13, 2019

Moreno et al. [11] identified potential habitats for two
endemic birds of high ecological value, the Blackthroated Huet-Huet (Pteroptochos tarnii), and theOchre-flanked Tapaculo (Eugralla paradoxa) andthen showed most important variables that explain thepresence of each species. Pratumcharta et al. [12]predicted the distribution of B. s. goniomphalos inThailand on the basis of environmental and climatic
factors and also indicated that altitude, land cover,normalized difference vegetation index (NDVI),
precipitation in the driest month, land surface
temperature and soil pH affected its distribution.
Khadka and James [13] made the distribution map ofcurrent and future climatic niche of endangered
Himalayan musk deer, a species endemic to Asia.
Mohammadi et al. [14] analyzed the current potential
distribution of the Blanford's Jerboa Jaculus
blanfordi and the Arabian Jerboa Jaculus loftusi in
Iran and predicted the impact of climate change on
their future potential distributions using two different
modelling software packages: Maxent and SDM(Species distribution model).
In existing researches concerning MaxEnt, thedistribution and suitability habitat of various
endangered animals and plants are predicted and thenrepresent the environmental factors that affects themin the world.
However, there have been few studies that havequantitatively analyzed the changes in the habitat areaof many endangered species especially in Japan fortaking the improvement of transportation
infrastructure and urbanization into account.
Therefore, the purpose of this research is toquantitatively evaluate the effect of endangered
species on the habitat due to the improvement oftransportation infrastructure, focusing on the changes
in land use in Chiba Prefecture, Japan.

the respective land use was investigated, and the land
use was arranged according to the following nine
categories; paddy fields, the other agricultural land,
forest, wasteland, buildup area, main transportationsites, rivers, lakes and ponds, and coastal area, theother sites.
For selecting the target species, as endangered
species with high conservation priority, the following
eleven species were chosen and analyzed from the listof red data book in Chiba Prefecture as the target
species; quail, ruddy crake, marsh grass bird,
Japanese large-footed bat, red fox, Japanese pond
turtle, Japanese skink, Japanese mamushi, Tokyo
salamander, Japanese fire belly newt, and wrinkled
frog. To estimate the existence probability of these
species in Chiba Prefecture, it is required to have plot
data wherein the existence in the area has been
confirmed. Therefore, the suitable habitat area of
endangered species was analyzed using MaxEnt
based on the habitat spot data written in the red data
book of the Chiba Prefecture. In this research, weespecially focused on the results for the ruddy crake(Porzana fusca), red fox (Vulpes vulpes), Japaneseskink (Plestiodon japonicus), and Tokyo salamander(Hynobius tokyoensis) as representative species ofbirds, mammals, reptiles, and amphibians,
respectively (Fig. 1).
Table 2 Data set for inputting into MaxEnt
Data

Mesh size

Year

Source

100m

2009
2006
1997
1991
1987
1976

Geospatial
Information
Authority of
Japan

１km

2012

Japan
Meteorological
Agency2009

Geospatial
Information
Authority ofJapan

Land use

Average rainfall amount
Annual average temperature

METHOD

Annual total daylight hours
Average annual amount ofsolar radiation

As environmental variables used in MaxEnt, thefollowing seven kinds of data in Chiba Prefecture
were used; 1) land use data from 1976, 1987, 1991,
1997, 2006 and 2009, 2) average rainfall amount over
30 years, 3) annual average temperature over 30 years,4) annual total daylight hours over 30 years, 5) annual
average global solar radiation over 30 years, 6) dataof average altitudes in 2009 and 7) data of averageslope angles in 2009 (Table 2).
Data from 1976 was selected because that was theoldest available GIS data on land used in Chiba
Prefecture. The land use data from 2009 and theabove data were input into MaxEnt. The change over
the years was analyzed by inputting the land use datafrom the other years using the obtained models andparameters from the analysis result of MaxEnt. Since
the land use classification differs depending on thefiscal year of the land use preparation, it was arranged
based on the newly unified land use. The definition of

Average altitudes
250m
Average slope angles

Fig. 1 Targeted species
965

SEE - Bangkok, Thailand, Nov.11-13, 2019

RESULTS

Result of suitable habitat area predicted by
MaxEntResult of comparative analysis of land use area
The suitable habitat area of 4 endangered species
by MaxEnt in 1976 and 2009 is shown in Fig. 2. Inthese figures, the habitat possibility is represented incolors according to 0–1 values per each mesh (100 m
× 100 m) based on the plot data that the habitat was
confirmed and the environmental variables.
Ruddy crake lives in common reed, Manchurian
wild rice (Zizania latifolia) and the grass near wetlandsuch as lake, river and paddy field. It is reported thata lot of Ruddy crake are found in the north of Chiba[15]. As shown in Fig.2, the high habitat possibility
area is concentrated in north coastal area and riverside.
Comparing between north and south area in Chiba,
north area is higher habitat possibility than south one.
Red fox prefers the area mixed with forest,
grassland and agricultural land, and riverside andgrassland are usually used as resting place [15]. Since
there are many rivers, lake and ponds in north of

Table 1 shows the land use area for each year in
Chiba Prefecture. It was shown that the green spacethat consists of rice paddy, forest and otheragricultural land and water environment including
rivers, lakes, ponds and coastal area have decreased
while the buildup area has increased. From theseresults, it was demonstrated that there is a possibility
that the habitat area for species has been also
decreasing due to the expansion of the city area.
According to the statistical yearbook of Chiba
Prefecture, total road length has been increasing
every year. But, it was shown the decrease of “Areaof main roads” in Table 1. This is because maximum
area of “buildup area” that occupy in 100m mesh ofland use has been increasing instead of “Area of main
roads” by progress of urbanization.

Table 1Comparison result of area of each land use
Land Use

1976

1987

1991

1997

2006

2009

Rice Paddy
Other Agricultural Land
ForestWaste Land
Buildup Area
Area of Main Roads
Rivers, Lakes and Ponds
Coastal Area
Others

127.3
80.8
187.9
8.0
53.6
1.7
16.2
3.9
35.4

121.3
75.6
179.4
15.0
71.5
2.9
16.0
2.3
31.0

121.4
75.5
174.9
13.8
73.1
3.2
14.7
2.3
36.0

119.1
72.5
167.6
10.6
86.4
4.0
14.8
2.3
37.6

112.1
69.2
161.3
12.3
95.3
5.7
14.8
2.0
42.2

108.9
68.1
170.8
8.9
111.2
1.3
12.6
1.7
31.5

Fig. 2

Result of suitable habitat area of each endangered species by MaxEnt
966

Comparison between
1976 and 2009-14.4%-15.7%-9.1%+11.0%+107.4%-22.9%-22.7%-57.9%-11.1%

SEE - Bangkok, Thailand, Nov.11-13, 2019

Chiba in particular, the habitat possibility area covers
mainly north area and part of south area as shown in
Fig.2. However, it is revealed that the low habitat
possibility area expanded slightly from 1976 to 2009.
Japanese skink usually lives in grassland andslope of mountainous area that has good exposure to
sunlight. The suitable habitat area of Japanese skink
predicted by MaxEnt is concentrated in the south areathat the Kazusa-hills expand, whereas Japanese skink
does not prefer the east coastal area and west urban
area.
Tokyo salamander generally inhabits broadleaved forests and artificial forest covered by planted
Japanese cedar and cypress in hilly area and low
mountains. The aquatic environment is also necessary
to spawn near forest. The suitable habitat area
predicted by MaxEnt is seen in south and east areathat expands forest area including hilly area.

environmental factors. AUC is the expectation valuethat means the ratio between the area identified theexistence of targeted species and predicted habitat
area by MaxEnt, it is indicated from 0 to 1. Since theresults of AUC for all species were over 0.7, allpredicted models by MaxEnt were assessed good fit
models.
Contribution rate is the rate that eachenvironmental variable affects the habitat probability.
From this table, it was observed that the “annual total
daylight hours” and “land use” considerably affect the
habitat probability of the red fox, while the “average
rainfall amount” influences that of the Tokyo
salamander because this species prefers a water
environment. It was also demonstrated that many of
the Japanese skinks were confirmed in the south area
where the slope angle is large, while many ruddy
crakes were confirmed in the north area with a small
slope angle. These results showed that thecontribution rate of the slope angle is high for these
species. Thus, it was found that there were differenceof preference on habitat among targeted species.
Fig. 3 represents the result of response curve on

Result of AUC and contribution rate
Table 2 shows the AUC (Area under the receiver
operator curve [6]) and contribution rate of respective
Table 2

Result of AUC and contribution rate of respective environmental factors
AUC

Land use(%)

Ruddy crake

0.789

16.5

0.4

6.1

18.7

0.0

17.7

40.6

Red fox

0.797

28.7

16.7

16.4

29.1

1.2

5.8

2.0

Japanese skink

0.713

6.4

12.1

1.0

16.9

2.8

12.2

48.5

Tokyo salamander

0.789

1.5

61.8

5.1

1.1

0.0

6.1

24.5

Fig. 3

Average rainfall Annual average
Annual total
Average annual amount
Average Average slope
amount (%)
temperature (%) daylight hours (%)
of solar radiation (%) altitudes (%) angles (%)

Result of response curve on each land use
967

SEE - Bangkok, Thailand, Nov.11-13, 2019each land use. This response curve estimated by
MaxEnt was able to reproduce the characteristics ofhabitat on each species. “Rivers, lakes and ponds”
and “Paddy fields” had commonly an influence on
almost all species in particular because they preferfreshwater environment near their habitat. “Other
agricultural land” and “Forest” are also affected as
suitable habitat for many species.
Result of time-series change of potential suitable
habitat area
The area of potential suitable habitat considering
the existence probability was estimated bymultiplying the suitable habitat area rate 0–1,
obtained by MaxEnt, by the area of each mesh (Fig. 4
and Table 3).
As a result, it was shown that when comparing theresults in 1976 with those in 2009, total habitat
possibility area of the ruddy crake, red fox, Japaneseskink and Tokyo salamander have decreased by 3.6%,
6.0%, 1.6% and 0.7%, respectively. As reasons for
this, since the residential land area and road length
has increased by 74.5% and 13.6% respectively inthis period, the suitable habitat area of each species is
considered to have decreased with the expansion of
the city area. Especially, the habitat for red fox
resulted in significant decrease for 33 years because
their habitat is near area that is progressing housing
land development. Also, in the northwestern area of
Chiba, it has been found total potential suitable
habitat area for all species have decreased remarkably
in particular.

Table 3Fig. 4 Relationship between potential suitable
habitat area, residential area and road length

Result of detailed potential suitable habitat area between 1976 and 2009

Road length(104km)
Buildup area (102km2)
Species

Ruddy crake

Red foxJapanese skinkTokyosalamander

1976

1987

1991

1997

2006

2009

Comparison
between1976 and 2009

3.5
4.4

3.7
5.5

3.7
5.9

3.8
6.5

3.9
7.5

4.0
7.7

13.6%
74.5%

17.7
7.8
6.1
3.7
19.2
7.8
5.6
5.8
21.3
7.8
5.3
8.2
15.2
2.3
4.5
8.3

Potential suitable habitat area (102km2)
17.5
17.4
17.2
17.1
7.7
7.6
7.5
7.4
6.1
6.1
6.0
5.9
3.7
3.7
3.7
3.7
18.9
18.9
18.6
18.4
7.6
7.6
7.4
7.3
5.5
5.5
5.4
5.4
5.8
5.8
5.8
5.8
21.1
21.1
21.1
21.0
7.6
7.6
7.7
7.6
5.3
5.3
5.3
5.2
8.1
8.2
8.2
8.1
15.1
15.1
15.1
15.1
2.3
2.3
2.3
2.3
4.5
4.5
4.5
4.5
8.2
8.3
8.3
8.2

17.0
7.4
6.0
3.7
18.0
7.0
5.3
5.7
21.0
7.6
5.2
8.1
15.1
2.3
4.5
8.2

-3.6%
-4.8%
-3.0%
-2.3%
-6.0%
-9.8%
-4.4%
-2.4%
-1.6%
-2.2%
-1.3%
-1.2%
-0.7%
-1.3%
-0.6%
-0.7%

Area
Whole area
Northwestern
Northeastern
South
Whole area
Northwestern
Northeastern
South
Whole area
Northwestern
Northeastern
South
Whole area
Northwestern
Northeastern
South

968

SEE - Bangkok, Thailand, Nov.11-13, 2019

CONCLUSIONS

190, 2006, pp.231–259.
[7] T. Pan, H. Wang, S. Duan, I. Ali, P. Yan, R. Cai,
M. Wang, J. Zhang, H. Zhang, B. Zhang and X.
Wu, Historical population decline and habitat
loss in a critically endangered species, theChinese alligator (Alligator sinensis), Global
Ecology and Conservation, Vol.20, 2019,e00692.
[8] A. M. West, S. Kumar, C. S. Brown, T. J.
Stohlgren and J. Bromberg, Field validation of aninvasive species MaxEnt model, Ecological
Informatics, Vol.36, 2016, pp.126-134.
[9] K. Remya, A. Ramachandran and S. Jayakumar,
Predicting the current and future suitable habitat
distribution of Myristica dactyloides Gaertn using
MaxEnt model in the Eastern Ghats, India,
Ecological Engineering, Vol.82, 2015, pp.184-188.
[10] D.S. Matyukhina, D. G. Miquelle, A. A. Murzin,
D. G. Pikunov, P. V. Fomenko, V. V. Aramilev,
M. N. Litvinov, G. P. Salkina, I. V. Seryodkin, I.
G. Nikolaev, A. V. Kostyria, V. V. Gaponov, V.
G. Yudin, Y. M. Dunishenko, E. N. Smirnov, V.
G. Korkishko, J. Marino, Assessing the Influenceof Environmental Parameters on Amur Tiger
Distribution in the Russian Far East Using a
MaxEnt Modeling Approach, Achievements in
the Life Sciences, Vol.8, Issue 2, 2014, pp.95-100.
[11] R. Moreno, R. Zamora, J. R. Molina, A. Vasquez,M. Á. Herrera, Predictive modeling of
microhabitats for endemic birds in South Chilean
temperate forests using Maximum entropy(MaxEnt), Ecological Informatics, Vol.6, Issue 6,
2011, pp.364-370.
[12] K. Pratumcharta, K. Suwannatrai, C. Sereewong,
K. Thinkhamrop, J. Chaiyos, T. Boonmars and A.
T. Suwannatrai, Ecological Niche Model basedon Maximum Entropy for mapping distributionof Bithynia siamensis goniomphalos, firstintermediate host snail of Opisthorchis viverrini
in Thailand, Acta Tropica, Vol.193, 2019,
pp.183-191.
[13] K. K. Khadka and D. A. James, Modeling andmapping the current and future climatic-niche ofendangered Himalayan musk deer, Ecological
Informatics, Vol.40, 2017, PP.1-7.
[14] S. Mohammadi, E. Ebrahimi, M. S. Shahriari, L.
Bosso, Modelling current and future potential
distributions of two desert jerboas under climatechange in Iran, Ecological Informatics, Vol.52,
2019, pp.7-13.
[15] Chiba Prefecture, Natural History of Chiba
Prefecture, Vol6, No.45, 2002, pp.989.

In the research, we analyzed the environmental
factors that affected the habitat probability andestimated the possible habitat area for endangered
species using MaxEnt in Chiba Prefecture, Japan.
In Japan, it is not required to conduct
compensatory mitigation for all developers by law inthe preocess of environmental impact assessment.
Thus, the number of endangered species has been
increasing every year due to destruction of the naturalenvironment including their valuable habitat. For
solving this problem, it is necessary to consider how
to avoid, minimize and companesate the adverse
impact to their habitat at the planning phase ofdevelopment based on the potential habitat area
predicted by MaxEnt in this research. Since surveying
existence of all animal and plant on whole area is
impossible, potential habitat area estimated by
MaxEnt is valuable information to consider
environment conservation countermeasures.
Further research is needed to improve theaccuracy of the plot data for habitat places bycollecting more data and improve the accuracy by theestimation of the contribution rate including otherenvironmental variables for MaxEnt.
REFERENCES[1] N. Iwasaki and S. David, A study of the land use
history in the Japanese macaque habitat
expansion area of the Boso Peninsula, Japan.
Journal of Rural Planning Association. Vol.24,
Special issue, 2005, pp.S1-S6.
[2] J. Kwon and M. Miyawaki, A STUDY ABOUTTHE STABILITY OF LANDSCAPE BASEDON LAND-USE BY GIS, Journal of architecture,planning and environmental engineering, Vol.75,
No.658, 2010, pp.2863-2872.
[3] H. Ikemi, T. Esaki, Y. Mitani and T. Tran, Spatial
Distribution of Human Impacts on Terrain Based
On Landuse Change Analysis Development and
GIS Analysis of Landuse Maps since 1900 in the
Fukuoka Prefecture Area, Journal of the Japan
Society of Engineering Geology, Vol.52, No.3,
2011, pp.97-108.
[4] Y. Ohara and A. Yamashita, Mesh Data Analysis
on Land Use Change and Its Correlation with
Topographic Condition in Sapporo, Tokyo andOsaka Metropolitan Areas, Geographical Studies,
No.86, No.1, 2011, pp.55-71.
[5] M. Miyamoto, Attempts to estimate habitat ofcold-water corals, Aquabiology, Vol.36(5), 2014,
pp.461-468.
[6] Steven J. Phillips, Robert P. Anderson, Robert E.
Schapire, Maximum entropy modeling of species
geographic distributions, Ecological Modelling969

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SOLID WASTE GENERATION IN THE PHILIPPINES: A
CORRELATIONAL ANALYSIS ON ECONOMIC AND SOCIALMETRICS
Jennie Lagman-Bautista1
Faculty, Holy Angel University, Philippines; Ph.D. Candidate, University of Santo Tomas, Philippines

1

ABSTRACTThe Philippines’ waste generation continues to rise from 37∙10³ kg∙aˉ¹ in 2012 to 40·10³ kg∙aˉ¹ in 2016, with adaily waste generation per capita oscillating from 300 to 700 grams for both rural and urban areas, respectively.
The study depicted a five-year correlational analysis on waste generation per capita as against Philippine
Economic and Social Metrics for: (1) Average Family Income (2) Average Family Expenditure (3) Population
Density and (4) Human Development Index. Both national and regional secondary panel data were analyzed thatlead to identifying Average Family Expenditure as an ecological footprint indicator with a direct and highest
correlation on waste generation per capita (WgC). On the National Level Analysis, for the five-year observation,
all independent variables exhibited a probability value lower than the significant threshold error value of 0.05.
Hence, changes in waste generation per capita for the five year sample size is also recurring prior and beyond thesampling period of 2012 to 2016. Based on Regional Level Analysis, the Equation Model was generated in orderto predict the degree of changes per unit, stated in gram of WgC (with coefficient = 0.319) in relation to the three
EFA Indicators with the exclusion of HDI. As depicted in the Equation Model, for every person increase inpopulation density expressed in per km2, it will generate a positive increases on WgC by 0.0000714; while forevery peso (Philippine monetary denomination) increases in family expenditure, has a decreasing effect on WgC
by 0.0000009479; and that for every one peso increases in family income, WgC will generate an increase by
0.0000008573.
Keywords: National footprint accounting, Ecological Footprint Indicators, Waste generation per capita, Multi
Regression Analysis

substantial disparity between rhetoric statutes enacted
by legislators and real outcomes on Solid Waste
Management. There is a need to understand andpredict the impact of indicators on national
economy’s improvement as against final waste
generation, a globally considered as chaotic humanecological footprint.

INTRODUCTION
The Philippines is at a precarious juncture in its
urbanization process and posited for having thesecond highest average urban density in East Asia andPacific Region [1]. Like any other developing
economy, solid waste management remains a major
challenge [2]. The Philippines’ waste generation
continues to rise from 37∙10³ kg∙aˉ¹ in 2012 to 40·10³kg∙aˉ¹ in 2016, with a daily waste generation percapita oscillating from 300 to 700 grams for both ruraland urban areas [3]. Unlike developed worlds who’s
into waste-energy conversion, Philippine regions
must efficiently utilize landfill, promote wastes
avoidance, reduction, re-use, rethink waste recycling
and periodically assess waste generation per capita.
The result of the waste assessment per region is vitalin relation to Republic Act 9003, known as the
Ecological Solid Waste Management Act of 2000.
The Philippines has commendable enacted
environmental regulatory policy frameworks [4]. But
Sta. Romana lamented that policy implementation in
the Philippine government agencies, however,remains a challenge [4]. There is an apparent

Ecological Footprint Accounting Indicators
The study proposed a scientific method toascertain the degree of significant changes in the four
ecological footprint indicators [5] on (a) level ofconsumption using average family expenditures (b)quality of population quality using Human
Development Index (c) Level of Income or averagefamily income and (d) quality of habitat using
population density.
The ecological footprint is used to gauge theexerted degree of consumption of human beings on
its ecological environment. According to Galli, It canbe applied at scales from global to local and gives
insight on the ecosystem services to humanrequirements to sustain changing lifestyle [6]. To
quantify sustainable development amidst the970

SEE - Bangkok, Thailand, Nov.11-13, 2019

escalating environmental degradation is to utilize aresource accounting tool called Ecological Footprint(EFA) [7]. It measures human demand on natural
resources and services [8]. Based on Millennium
Ecosystem Assessment, EFA can track past humanpressure on ecosystem, it requires an analysis ofhistorical data in order to predict [9]. A favorable
result occurs when a National Footprint is lesser than
the ability of the environment and natural resources
to regenerate, favorably, there is what we callbiocapacity reservation [9].
Four indicators of Ecological Footprints [5] wereapplied in the study. The major source of Ecological
Footprint is explained by the European Environment
Agency as anthropogenic effects, these are processes,
objects, materials or those that are derived fromhuman activities as opposed to those occurring in
natural environments without human influences [10].
Tools such as Ecological indicators can be used as
early warning signal and can quantify anthropogenic
effects on the ecosystem brought by the growing levelof human and global metabolism [11]. The National
Footprint Accounting (NFA) are prevalently usedsince 1961 [12]. To synthesize further, EFA for
Municipal Solid Waste (MSW) provides policymakers with new insights on how to mitigate
territorial footprints and just as important as thepolicy development and implementation [9].

workers or consumers are bound to productconsumption of scarce resources and later subject for
disposal [16]. The Central Asia, Middle East andAsia-Pacific regions experienced an escalating
Ecological Footprint due to population growth of
154% and 465% from 1961 to 2014 generating per
capita Footprint equivalent to 126% and 146%
respectively [12]. Provinces that have larger urban
population and higher economic activities generate
greater volume of solid waste [3].
Human Development Index (HDI)
In the study, National progress concerning
sustainable development dwelled on comparing the
NFA results and explored the degree of relationshipof WgC as against the Philippine HDI, as publishedby United Nation Development Programme (UNDP).
HDI is the aggregate of education, longevity, andincome into a single metric [12]. The same authors inthe study entitled “Ecological Footprint Accounting
for Countries: Updates and Results of the National
Footprint Accounts, 2012-2018” used HDI as a major
indicator of Ecological Footprint. Further, the UNDP
defines 0.70 HDI as the threshold for a highly
developed economy. As stated previously, bio
capacity deficiency on the planet earth is gauged at
1.7 gha per capita in 2014. And they reasonably
concluded said deficiency combined with HDI
measures globally sustainable development ofmankind as a minimum condition set. HDI is a social
metrics that measures social sustainability. Social
sustainability was defined by Western Australia
Council of Social Services as "Social sustainability
occurs when the formal and informal processes;
systems; structures; and relationships actively
support the capacity of current and future generations
to create healthy and liveable communities. In
addition, socially sustainable communities areequitable, diversely connected, and generally
provides a good quality of life [13].

Average Family Income
Auci and Vignani explained the increase ineconomy’s income at a certain high level has adomino effect, people started to be environmental andmay demand imposition of regulatory policies to halt
pollution impacts on social and economic activities[4]. In the study the average family income was used
as economic metrics. When a systems approach isused for technology evaluation, the economic
dimension of the system life cycle cannot be omitted.
The purpose of economic metrics is to provide thequantitative information needed to make a judgment
or a decision on the deployment of a new technology
in selecting an alternative option [13].

Average Family Expenditure
Average Family Expenditure is another economic
metrics as a basis for consumption per capita.
Philippine Statistics Authority (PSA) [17] showedthat the current average annual family income ofFilipinofamilies
wasapproximately 267
thousand pesos in 2015. In comparison, the averageannual family expenditure for the same year was 215
thousand pesos. Hence, Filipino families have anannual average savings of 52 thousand pesos.

Population Density
Population density is the number of individuals
that live in a unit area in a specified time [14]. It is
computed by dividing the total population by its landarea. When there are a larger number of people living
in a smaller amount of space, the area is densely
populated while the reversed is called sparsely
populated [15]. The effects of population rate on
economic development stem on the type of industry
classified either as labor intensive or not, humanresources is a principal replacement for diminishedinput in service oriented industries [16]. Eventually,

METHODOLOGY AND MATERIALS
Waste assessment is a vital phase of Solid Waste
Management and preferably enclosed by macro
and/or micro level analysis. Consequently, an
971

SEE - Bangkok, Thailand, Nov.11-13, 2019assessment called National Footprint Accounting on
wastes will be analyzed using multivariate regression
analysis for both level of consumption, level ofincome, quality of population and quality of habitatin terms of population density. These indicators wereintroduced by Guo et al. (2018) and adapted in the
study to establish empirical data that will provide
deeper linkages on economic and social metrics as
depicted in Figure 1. The result of the study is vitalfor the program planning of National Solid Waste
Management Commission (NSWMC) to forecast thewaste generation per Philippine Region based on theforeseeable economic growth, human development
and population growth. The Commission shalloversee the implementation of solid waste
management plans and prescribe policies to achieve
the objectives of the law on “Ecological Solid Waste
Management Act of 2000”.

(presented in ratio scale for a parametric test) pertains
to the waste generation per capita per region. The
three independent variables (classified as interval
scale) will also be on a per region basis as follows: (1)Average Family Expenditure per Region (2) Average
Family Income per Region (3) Population Density
was computed based on regional area per square
kilometer divided by population per region. While thelast indicator or the quality of Population waspresented based on parametric variables (ratio scale)on Human Development Index a secondary data. The
adjusted R2 determined the causal effect relationshipbetween the dependent and independent variables.
Further the p-value higher than 0.05 was excluded as
an independent variable in generating a Regression
Model and to be interpreted that no significant
relationship exist with the dependent variable
representing the waste generation per capita. One ofthe purpose of the statistical analysis is to generate a
Regression Equation Model by transmutation ofcoefficient values of each independent variables
based on the line-intercept.

Fig. 1 Conceptual Framework of NFA•HumanDevelopm
ent Index•Average
FamilyExpenditure
Level of
Quality ofConsumpti
PopulationonRegression Equation Model (Regional Level)
WgC=0.319+B1*(0.0000714)+B2*(-0.0000009479)+ B3*(0.0000008573)(1)

Quality of
Quality of
Employme
Habitatnt•Average
FamilyIncomeResearch Hypothesis: There is a significant
relationship between Waste generation per capita(WgC) and:(B1) Population Density(B2) Average Family Expenditure(B3) Average Family Income(B4) Human Development Index•Population
Density

The term regression is credited to Francis Galton[18]. Regression analysis allows researchers toquantify how the average of one variable
systematically varies according to the levels of
another variable. The former variable is often calleda dependent variable or outcome variable and thelatter an independent variable, predictor variable, or
explanatory variable [18]. Regression analysis is aform of predictive modelling technique whichinvestigates the relationship between a dependent(target) and independent variables (predictors). This
technique is used for forecasting, time seriesmodelling and finding the causal effect relationshipbetween the variables [19]. It also indicatesthe strength of impact of multiple independent
variables on a dependent variable.
In the study, secondary national waste assessment
panel data from the PSA and UNDP, covering theperiods from 2012 to 2016 was utilized.
Subsequently, the Correlational Analysis generated
85 observations from the total 17 Philippine Regions
over the five-year period. National Ecological
Footprint Accounting Data, known as waste
generation per capita were processed together withthe four EFA indicators using SPSS for Multi
Regression Analysis. The dependent variable

RESULTS AND DISCUSSION
Table 1 presents the panel data for the four
independent variables and the dependent variable,
waste generation per capita based on the national
level.
Table 1 Panel Data for National Level
*Pop
*Ave.
** Family
Year
WgC
HDI Income
2012 0.3878 0.677 182294
2013 0.3879 0.685 206765
2014 0.3880 0.689 216824
2015 0.3904 0.693 227118
2016 0.3912 0.696 238059
Philippine Statistics Authority*
United Nations**

972

*Ave.
FamilyExp.
168471173588179706
187294
195353

ulati
on
Dens
ity

301
306
311
315
319

SEE - Bangkok, Thailand, Nov.11-13, 2019

The average waste generation per capita between
2012 to 2016 on a nationwide basis is at 389 grams
per day which is lesser than the global average of 740
grams per day in 2016 [21]. The HDI Mean is 0.688,
a bit lower in comparison to 0.70 as the threshold fora highly developed economy [22]. The five year
(2012 to 2016) average annual family income wasapproximately 214 thousand pesos with averageannual family expenditure of 181 thousand pesos,
giving Filipino families an annual savings of 60
thousand pesos. While the average five-year national
population density is at 310 km2 using
total
Philippine land area of 300 000 km2 (refer to Table 2).

Table 4 Correlations

PearsonCorrelation
Sig. (1tailed)N

Mean
0.38906
0.68800
214 212180 882
310

Table 3 shows that 88% of the variation in waste
generation per capita is explained by the variation in
Average Family expenditure.

1

0.84

0.831

0.938

0.888

0
5

0.04
5

0.041
5

0.009
5

0.022
5

Multiple R
R Square0.0000001414
0.88
0.018
5

Waste generation per Capita has significant
positive correlation with the following independent
variables: (a) Average Family Expenditure (r = 0.938,
p = 0.009), yield the highest and direct correlation
with waste generation per capita which means anincrease in family expenditure will increase wastes
generation; (b) followed by Population Density (r =0.888, p = 0.022) also directly predicting that thelarger the number of people in a given land area will
escalate waste generation; (c) the same is true withHDI (r = 0.837, p = 0.04) to be interpreted that thegreater the human development liken to an economic
development, poses greater ecological footprint on
wastes; (d) and that positive increases on Average
Family Income (r = 0.831, p = 0.041) has also strong
and direct impact on waste generation per capita. All
independent variables exhibited a probability value oflower than the significant threshold error value of0.05. Hence, changes in waste generation per capita
for the five year sample size is also recurring priorand beyond the period of study (2012 to 2016).

Population
Density

Table 5 Regression Statistics (Regional)

Table 3 Regression Statistics
Pearson’s Coefficient ofCorrelation
R Square Change
Sig. F Change
Observations

HDI

Ave.
FamilyExp.

Table 5 shows the statistical analysis for the four
independent variables in relation to waste generation
per capita for each of the 17 regions in thePhilippines. It shows that there is a strong positive
correlation (R = 0.933684) between waste generation
per capita and the 4 independent variables namely:
Ave. Family Income, Ave. Family Expenditure,
Population Density and HDI and 87.1765% of thevariation or changes in waste generation per capita is
explained by the changes in the 4 independent
variables.

Table 2 Descriptive Statistics (National Level)

WgC
HDI
Ave. Family Income
Ave. Family Expenditure
Population Density

WgC

Ave.
FamilyIncome0.933684
0.871765

Observations

85

The regional weighted waste generation per capita
between the periods of 2012 and 2016 is at 368 grams
per day which is a bit lower than the national averageof 389 grams. HDI per region is not available hence, areflection of the same five-year national average HDIof 0.688. The regional average annual family income
was approximately higher by 13 thousand incomparison per Table 2 (228 less 214 thousand pesos)
but with the same average annual family expenditureof 181 thousand pesos. While the average five-year
regional population density is at 1 481 km2 for a total
Philippine land area of 300 000 km2 (refer to Table 6).
Table 6 Descriptive Statistics (Regional Level)

WgC
HDI
Ave. Family Income
Ave. Family Expenditure
Population Density

Mean
0.3680.6880
227 553
180 882
1 481

Table 7 based on regional panel data and in coming
up with a Regression Equation Model, HDI was
excluded among the indicators, generating (r = 0.20, p
973

SEE - Bangkok, Thailand, Nov.11-13, 2019family income, WgC will generate an increase by
0.0000008573.

= 0.429) which is above the p-value of 0.05, therefore
not significant factor of waste generation per capita. But
the result of the causal relationship on the regional levelis attributable to lack of regional data for Human
Development Index, see previously presented Eq. (1).

REFERENCES[1] World Bank. Population growth (annual%),2017. http://data.worldbank.org/indicator[2] Moriguchi, Y., Hashimoto, S., Material ﬂow
analysis and waste management. In: Clift, R.,
Druckman, A. (Eds.), Taking Stock of Industrial
Ecology, https://doi.org/10. 1007/978-3-31920571-7_12, 2016.
[3] National Solid Waste Management Commission,
National Solid Waste Management Strategy
2012-2016.
Retrievedfromhttps://nswmc.emb.gov.ph/wpcontent/uploads/2016/NSWM-Strategy-20122016.pdf, 2016.
[4] Martinico-Pereza, Schandla H., Tanikawaa H.,
Sustainability indicators from resource ﬂow
trends in the Philippines Marianne Faith G.
Graduate School of Environmental Studies,
Nagoya University, Japan Commonwealth
Scientiﬁc and Industrial Research Organisation(CSIRO), Australia. Resources, Conservation
and Recycling, 2018.
[5] Guo, Y., Xia, D., Sun, B., Wang, X., Zhang, D.,& Li, J., “Ecological footprints and development
trends in Hefei, China”. Management ofEnvironmental Quality: An International
Journal Vol. 29, Issue 1, 2018, pp. 2-14.
[6] Mancini, Kamaruddin, Hafiz, Suffian & Alrozi.
An overview of municipal solid waste
management and landfill leachate treatment:
Malaysia and Asian perspective. Environmental
Science and Pollution Research Vol. 77, 2017,
pp.123-128.
[7] Zhang L., Dzakpasu M, Chen R., Wang X.,
Validity and utility of ecological footprintaccounting:A
state-of-the-art
review.
Sustainable Cities and Society. Vol. 32, 2017, pp.
411-416.
[8] Isman M., Archambault M., Racette P., Konga
C., Llaque R., Lin David., Iha K., QuelletPlamondon, Ecological Footprint Assessment fortargeting climate change mitigation in cities: A
case study of 15 Canadian cities according tocensus metropolitan areas. Journal of Cleaner
Production. Vol. 171, 2017, pp. 1032-1043.
[9] Galli, A., “On the Rationale and Policy
Usefulness of Ecological Footprint Accounting(The Case of Morocco)”. Environmental Scienceand Policy Vol.48, 2015, pp. 210-224.
[10] EEA-European Environment Agency, Waste
Generation(WWW
Document).
URL
http://www.eea.europa.eu/data-andmaps/indicators/waste-generation-1/assessment,
2015.

Table 7 Correlations
Stand
ard
Error

t
Sta
t

Sig.

0.319

0.00

1.5
25

0.131

1.714
E-05

0.000

13.
935

0.000

9.479
E-07

0.004

3.0
70

0.003

8.573
E-07

0.001

3.4
58

0.001

CoefficientsIntercept
PopulationDensity
Ave.
FamilyExpenditure
Ave.
FamilyIncomeAfter HDI removal having a p-value ( greater than thealpha (p > 0.05), That every unit of change on a pergram of waste generation per capita is attributable tothe three remaining independent variables classified
as fit for the regression equation model; (a)population density (b) average family expenditureand (c) average family income per Table 7.
CONCLUSIONSThe study depicted a five-year correlational
analysis on WgC for the four ecological footprint
indicator on: (1) Average Family Income (2) Average
Family Expenditure (3) Population Density and (4)HDI. Both national and regional secondary panel data
were analyzed that lead to identifying Average
Family Expenditure as an EFA indicator with a directand highest correlation on WgC. On the National
Level Analysis, for the five-year observation, allindependent variables exhibited a p-value lower than
the significant threshold error value of 0.05. Hence,changes in waste generation per capita for the five
year sample size is also recurring prior and beyond
the sampling period of 2012 to 2016.
Based on Regional Level Analysis, the Equation
Model was generated in order to predict the degree ofchanges per unit, stated in gram of WgC (withcoefficient = 0.319) in relation to three Ecological
Footprint Accounting Indicators, excluding HDI. As
depicted in the Equational Model, for every person
increase in population density expressed in per km2,
it will generate a positive increases on WgC by
0.0000714; while for every peso (Philippine
monetary denomination) increases in family
expenditure, has a decreasing effect on WgC by
0.0000009479; and for every one peso increases in
974

SEE - Bangkok, Thailand, Nov.11-13, 2019[11] Weinzettel, Steen-Olsen, Hertwich, Borucke &Galli 2014. Ecological footprint of nations:Comparison of process analysis, and standard
and hybrid multiregional input-output analysis.
Ecological Economics Vol. 101, pp.115-126.
[12] Lin D., Hanscom L., Murthy A., Galli A., Evans
M, Neill E.,… Wackernagel M., Ecologicial
Footprint Acounting for countries: Updates andresults of the National Footprint Accounts, 20122018, Resources, 2018, pp.7-58[13] Department of Energy and Mineral Engineering,Technologies
forSustainable
System.
https://www.eeducation.psu.edu/eme807/node/584) by John
and Willie Leone Family date retrieved April 26,
2019.
[14] Lakna, PEDIAA. https://pediaa.com/differencebetween-population-density-and-populationdistribution/ 2018, retrieved on April 26, 2019.
[15] REFENCE.https://www.reference.com/worldview/population-density-9fcc8f4fbc8beada)[16] Bretschger L., Climate policy and economic
growth. Resource and Energy Economics Vol.
49, 2017, pp. 1-15.
[17] PSA. Philippine Statistics Authority. Angeles
city population index. Retrieved fromhttps://psa.gov.ph/sites/default/files/03_Angeles%20City.pdf[18] Gordon, R., Regression analysis for the social
sciences, Second edition. Published by Routledge
711 Third Avenue, New York, NY 10017, 2015,
pp. 4-6.
[19] Sunil R., Analystics Vidhya.
https://www.analyticsvidhya.com/blog/2015/08/
comprehensive-guide-regression/, 2015.
[20] World Bank. Solid Waste Management 2018.
Retrievedfrom
http://www.worldbank.org/en/topic/urbandevelo
pment/brief/solid-waste-management, 2018[21] UNEP.http://www.ph.undp.org/content/philippi
nes/en/home/library/human_development/2016
HumanDevelopmentReport.html

Appendix A: Regional Secondary Panel Data
Year Region
2012
1
2012
2
2012
3
2012
4
2012
5
2012
6
2012
7
2012
8
2012
9
2012
10
2012
11
2012
12
2012
13
2012
14
2012
15
2012
16
2012
17
2013
1
2013
2
2013
3
2013
4
2013
5
2013
6
2013
7
2013
8
2013
9
2013
10
2013
11
2013
12
2013
13
2013
14
2013
15
2013
16
2013
17
2014
1
2014
2
2014
3
2014
4
2014
5
2014
6
2014
7
2014
8
2014
9

Population
Average Family
Density HDI Income Expenditure WgC
376.56 0.68 204000
159000 0.35
118.43 0.68 195000
140000 0.33
482.72 0.68 259000
211000 0.34
797.71 0.68 284000
243000 0.31
96.45 0.68 179000
138000 0.32
309.6 0.68 162000
144000 0.33
353.37 0.68 202000
163000 0.37
458.3 0.68 209000
164000 0.37
182.23 0.68 166000
132000 0.35
208.3 0.68 162000
162000 0.39
219.41 0.68 190000
143000 0.38
229.35 0.68 194000
156000 0.39
192.55 0.68 163000
140000 0.31
117.37 0.68 180000
142000 0.35
269.63 0.68 130000
114000 0.27
19981.6 0.68 379000
325000 0.69
92.08 0.68 257000
188000 0.37
380.86 0.69 215000
165000 0.35
119.98 0.69 208000
146000 0.33
491.76 0.69 272000
219000 0.34
819.46 0.69 293000
251000 0.31
97.97 0.69 193000
144000 0.32
313.89 0.69 170000
149000 0.34
357.79 0.69 210000
167000 0.37
465.98 0.69 218000
172000 0.37
184.42 0.69 176000
138000 0.35
211.71 0.69 171000
155000 0.39
223.36 0.69 200000
148000 0.38
233.28 0.69 211000
165000 0.39
196.73 0.69 171000
146000 0.31
119 0.69 186000
147000 0.35
273.46 0.69 133000
113000 0.2720320.54 0.69 394000
332000 0.7
93.61 0.69 265000
194000 0.37
385.09 0.69 226000
173000 0.35
121.51 0.69 222000
153000 0.33
500.85 0.69 285000
228000 0.34
841.57 0.69 302000
259000 0.3
99.46 0.69 208000
152000 0.32
318.08 0.69 178000
154000 0.34
362.22 0.69 218000
171000 0.37
473.67 0.69 228000
181000 0.37
186.53 0.69 186000
146000 0.35

Year Region
2014
10
2014
11
2014
12
2014
13
2014
14
2014
15
2014
16
2014
17
2015
1
2015
2
2015
3
2015
4
2015
5
2015
6
2015
7
2015
8
2015
9
2015
10
2015
11
2015
12
2015
13
2015
14
2015
15
2015
16
2015
17
2016
1
2016
2
2016
3
2016
4
2016
5
2016
6
2016
7
2016
8
2016
9
2016
10
2016
11
2016
12
2016
13
2016
14
2016
15
2016
16
2016
17

975

Population
Density215.05227.31
237.26200.95120.63277.2920657.88
95.08
386.24122.25509.57854.31100.03319.29427.76390.12190.96212.82228.78240.35201.88120.91301.6220783.77
94.1
387.39122.99518.43867.23100.6
320.5
499.18321.29195.47210.59230.24243.5
202.81121.19328.0220909.66
93.11

Average Family
HDI Income Expenditure WgC
0.69 180000
149000 0.39
0.69 210000
154000 0.38
0.69 229000
176000 0.39
0.69 179000
153000 0.31
0.69 192000
152000 0.35
0.69 136000
112000 0.27
0.69 409000
3400000.7
0.69 273000
202000 0.37
0.69 238000
182000 0.36
0.69 237000
162000 0.34
0.69 299000
239000 0.34
0.69 312000
2690000.3
0.69 222000
161000 0.32
0.69 187000
160000 0.34
0.69 226000
176000 0.38
0.69 239000
193000 0.37
0.69 197000
156000 0.35
0.69 190000
1440000.4
0.69 221000
161000 0.38
0.69 247000
190000 0.39
0.69 188000
162000 0.31
0.69 198000
159000 0.36
0.69 139000
111000 0.25
0.69 425000
3490000.7
0.69 282000
210000 0.38
0.7 250000
192000 0.36
0.7 252000
171000 0.34
0.7 313000
251000 0.34
0.7 322000
2790000.3
0.7 236000
171000 0.33
0.7 196000
166000 0.35
0.7 234000
181000 0.37
0.7 250000
205000 0.37
0.7 208000
167000 0.35
0.7 200000
138000 0.42
0.7 232000
169000 0.38
0.7 265000
205000 0.39
0.7 197000
171000 0.32
0.7 204000
166000 0.36
0.7 142000
110000 0.24
0.7 441000
359000 0.71
0.7 291000
220000 0.39

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ANALYSIS ON SPATIAL USE AND LAND USE
IN NORTH JAKARTA ADMINISTRATIVE CITY
Galih Jati Utomo1, Hafid Setiadi2, Rudy P. Tambunan3 and Komara Djaja4
1,2,3,4
School of Strategic and Global, University of Indonesia, Indonesia

ABSTRACT
North Jakarta City as part of the Special Capital Region of Jakarta Province has a typical regional characteristicof coastal areas with varied land use functions. Urban development that occurs along with population growth anddevelopment activities increases the demand for land. In fact, this city is designed in a planological manneraccording to the type of allocation and land use that has been determined. This resulted in the occurrence of land
use non conformity with the North Jakarta City Regional Spatial Planning (RTRW). This study aims to determine
the pattern of changes in land use and utilization (spatial and temporal), the amount of non conformity and to know
the implications of the spatial use non conformity and approaches to overcome those problems. The method usedin this study was map analysis with overlay using Geographic Information System, qualitative data collection, andquantitative descriptive analysis by identifying and conducting field survey observations.
The results showed a change in the pattern and the amount of spatial use in 2008 to 2018 for some types ofland use. Based on the analysis results, the land use in 2018 that complied with the Spatial Plan was 51.05%,
supported the Spatial Plan of 12.48%, not complied with the Spatial Plan of 29.48% and the plan that had not been
approved was 6.96%. The impact of land use non conformity was the emergence of urban problems such as
irregular housing, traffic congestion, natural vulnerability such as floods, damage to environmental quality,
reduced public space and the inability to implement government development programs. And approach toovercome these problems is by reviewing spatial plans, increasing the role of the government in monitoring andcontrolling spatial use, and making priority programs and areas with a tight control system.
Keywords: Spatial Analysis, Spatial Violation, Spatial Planning, Spatial Use, Land Usevalue in controlling space utilization in the DKI
Jakarta Province.
Problems in the City of Jakarta related to thecontrol of spatial use are land use and spatial use thatare not comply with applicable laws and regulations.
This is a factor that triggers the non conformity ofurban space utilization. This problem also occurred in
the North Jakarta Administrative City, limited land
and the high price of land in Jakarta and North Jakarta
in particular caused an increase in the intensity of land
use in each ownership.
This study is very important considering the great
benefits obtained when the land use and spatial use
can be identified. Through this study, it is expected tobe known to what extent the conditions, dynamics andthe extent of non conformity that occurred in spatialplanning in the North Jakarta Administrative City.
Thus, evaluations can be carried out in the context ofproposed changes or providing input on the revisionof the Regional Spatial Plan (RTRW) throughapproaches that are in line with environmental
conditions and problems. Based on the facts
described above, the authors are interested to conduct
a study entitled "Analysis on Spatial Use and Land
Use in North Jakarta Administrative City”.

INTRODUCTION
A common problem faced by big cities inIndonesia is the high growth of urban population.
This is due to natural population growth andurbanization factors. These two factors ultimately
have an impact on the emergence of various problems
in urban areas such as the lack of space for the needsof housing, offices, trade and services. Current urban
development has an impact on increasing the need forspace in urban areas and the high demand for land.
Therefore spatial planning is needed to regulate
utilization patterns based on activities, types ofactivities, location functions, space quality andenvironmental aesthetics [1]Based on the DKI Jakarta 2030 Spatial Planning(RTRW), in order to control the development ofactivities so as not to exceed the carrying capacity andaccommodative capacity of the environment, one
strategy is to prioritize the development of cities tothe east, west and north and limit development tosouthward [2]. This is also in line with the vision of
the North Jakarta Administrative City, namely torealize the North Jakarta Administrative City as amodern coastal city that is neatly organized,
advanced, comfortable and prosperous and has acultured society and a government-oriented public
service. As a coastal city, North Jakarta has a strategic

LITERATURE REVIEW

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SEE - Bangkok, Thailand, Nov.11-13, 2019Human and Spatial Planning
According to Kivell [3] the main urban activities
that plays an important role in the development of thecity are: (a) trading activities; (b) industrial activities;and (c) settlement activities. Land is permanent andlimited, as a result a land will be contested for various
types of activities which have criteria located inaccordance with the land. Even though the city isdesigned in a planological manner according to thetype of allocation and land use that has been
determined in the Regional Spatial Planning.



Limit the use of permitted space;
Guarantee the balance of land use for all
activities in all strategic areas; andAvoid non-strategic land use.

Changes in Land Use and Land Use Conformity
The theory of changes in an area and its
surroundings as part of a wider urban area according
to Gallion and Eisner [6] in the book entitled The
Urban Pattern, may cause distortions in land usechanges. Based on Chapin and Kaiser's theory [7]urban development will always be associated withurban land use where there are three key systems that
influence. The three systems include (a) the city
activity system; (b) environmental system; and (c)land development system.
Meanwhile, land conformity is the level ofconformity of a plot of land for a particular use. The
conformity of the land can be assessed for current
conditions (actual land conformity) or after
improvements have been made (potential land
conformity) [8].

Spatial Planning, Spatial and Land Use
According to Law No. 26 of 2007 concerning
spatial planning, space is a place which includes land
space, sea space, and air space, including space within
the earth as a unitary area, where humans and othercreatures live, carry out activities, and maintain theirsurvival. Spatial planning is a form of spatial structureand spatial pattern. Spatial structure is thearrangement of residential centers and network
systems of infrastructure and facilities that function
as supporters of socio-economic activities ofcommunities that have a functional relationshiphierarchically. [4]Hamid Shirvani [5] in the book entitled Urban
Design Process states that every city design must pay
attention to the existing design elements so that laterthe city will have clear characteristics. There are 8(eight) elements that form a city (especially the city
center) namely land use, building and mass building,open space, parking and circulation, signages,
pedestrian ways, supportive activities andpreservation. Land use must pay attention to or adjust
to problems in how to develop the city. In this book it
is also mentioned that zoning ordinance is a practicaland useful control mechanism in urban design. The
main emphasis lies in the three-dimensional problem,
namely the relationship of harmony between
buildings and environmental quality. This is the basisof a city spatial planning.
Hamid Shirvani [5] also mentions that zoning
ordinance is intended so that the plan runs according
to what has been determined, including in themechanism of permits (building permits) and special
provisions that govern it. In addition, zoning
ordinance can encourage the creation of public
facilities and a humanized city environment,
especially in creating a pedestrian atmosphere onstreet level and providing space for activity support.
Furthermore, Kivell [3] states that land use
planning and zoning are instruments in spatialplanning. These two instruments are generally
detailed in the structure plan or in more detail in thearea plan that shows where development can bepermitted and in what form of building. The
objectives of the area plan are:Land Use Classification
Based on the 2011-2030 DKI Jakarta Spatial
Planning, the types of land use classification are as
follows:
1. Protected Green Area
2. Cultural Green Area
3. Housing Area
4. Park Housing Area
5. Office, Trade and Service Areas
6. Office, Trade and park Service Areas
7. Blue Open Space
8. Industrial and Warehousing Areas.
Based on those theories and conditions, the study
questions are to determine the pattern of changes inland use and utilization (spatial and temporal) in 2008
and 2018, the amount of spatial use non conformity
in North Jakarta Administrative City with the DKI
Jakarta Regional Spatial Planning (RTRW), to know
the implications of spatial use non conformity andapproaches to overcome it.
METHODOLOGYThis study uses a mix-method approach with a
stepwise method, namely map analysis, quantitativeand qualitative descriptive analysis by conducting indepth interview with key informant. Changes in land
use in the North Jakarta Administrative City area
were obtained by analyzing digital maps by
overlaying 2008 land use map and 2018 land use map
as the secondary data from local government agencies.
The results of the overlay produced a map of land usechanges at the specified year spacing.
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Then to obtain the amount of land use nonconformity, it was obtained by classifying the formsof land use or classifications of space allocation on
the RTRW which were determined based on theclassification standards of the themes listed in the
2011-2030 RTRW Jakarta Spatial Pattern Map. The
map used was a comparison of Detailed Spatial
Planning map with land use map in 2018.
The amount of space utilization and the nonconformity to spatial planning were obtained fromvisual interpretation using Geographic Information
Systems (GIS). Geographic Information System(GIS) is a computer-based system of work that has theability to enter, manage, analyze and reactivate datathat have spatial references for various purposes
related to mapping and planning. The final result(output) in the form of geographical display is very
useful for decision making [9]𝐀
𝐱𝟏𝟎𝟎% = a%𝐗(1)
a = Land Use Conformity Value
A = Existing Physical ShapeV = Area According to Spatial PlanRESULTS AND DISCUSION
Changes in Land Use in 2008 and 2018
Based on the analysis of changes in land use,
Figure 1 shows the land use patterns in 2008 and
Figure 2 shows the land use patterns in 2018 in North
Jakarta City. Spatially, subdistricts that have access toor directly adjacent to ports and infrastructure in theform of accessibility to activity centers and adequate
road networks had a high level of change.

Land Use Conformity
As a benchmark for conducting an overlay
analysis, the matrix was first set as a tool for the land
use conformity assessment. The matrix in this study
was used to compare two factors, in which the column
section was the Spatial Planning zoning and the row
section was the classification of land use. The column
and row show the strength of the relationship between
items or non-linear relationship.
The 2018 land use conformity matrix for Detailed
Spatial Planning in North Jakarta City can be seen intable 2. Matrix analysis referred to the approach
adapted to Minister of Public Works Regulation No.
20 of 2011 concerning Guidelines for Preparation of
Detailed Spatial Planning and District/City Zoning
Regulation [10]. The author limited the determinationthat did not refer to zoning regulation where activities
were conditional and limited to the ITBX table
Regional Regulation No.1 of 2014 concerning
Detailed Spatial Planning and Zoning Regulation in
DKI Jakarta Province [11] however the determinationof land use conformity was close to that.
Especially for reclamation islands in this study
were included in the classification of other land
allocation with a study matrix in the form of "plansthat have not been approved". This is because thereclamation islands do not yet have zoning andregulations that are set as the legal basis in the
management of coastal areas and small islands
located in Jakarta Bay (Regional Regulation on theManagement Zoning of Small Coastal Areas andIslands (RZWP3K)).
In calculating the conformity amount, this study
used the Minister of Agrarian and Spatial Planning(ATR)/Head of National Land Agency (BPN)
Regulation No. 6 of 2017 concerning Procedures for
Reviewing the Regional Spatial Planning to calculate
the percentage of the area of each planned area [12].

978Fig. 1

Map of Land Use in North Jakarta
Administrative City in 2008.

Fig. 2

Map of Land Use in North Jakarta
Administrative City in 2018.

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 1 land Use in North Jakarta Administrative
City in 2008 and 2018Land Use (in hectare)

Penjaringan
Pademangan
Tanjung Priok
Koja
Kelapa Gading
Cilincing
Total
(%)

Occupation/Housing

Industrial and
Warehousing

Office, Tradeand Service

Open Space,
Cemetery,
Plantation,
Agriculture, andEmpty Land

2018

2008

2018

2008

2018

2008

2018

2008

2018

2008

2018

140.77137.44131.87117.95132.43344.371004.88.32

1497.5532.171327
723.83843.99784.095708.646.80

993.8
300.24871.11533.59646.35876.214221.334.97

173.28136.18282.2675.397203.58474.041344.7
11.02

463.74149.44518.69215.09144.71
956.292448
20.28

252.84150.3
17.12921.6889.74279.2821460.993.78

177.11110.65154.4167.257171.8754.328735.62
6.09

420.18138.1298.30967.759122.91
1814.32661.621.82

591.94177.82169.9790.127225.771365.12620.721.71

435.4911.097111.254.356
129.01581.551272.810.43

584.51
150.3
83.63724.85621.858175.441040.6
8.62

Facility andInfrastructure

2008
132.18105.34186.08152.99134.7337.052748.37
6.13

Subdistrict
Regionbe done through increasing land carrying capacity andintensifying land use through vertical development.
As a coastal area and to facilitate the need forspace, plans to develop industrial estates andwarehouses are indeed part of the Spatial Pattern Planin North Jakarta City. In addition, in the spatial
pattern plan referred to in the cultivation area plan, aplan to develop industrial estates and warehouses wasestablished to support the activities of Tanjung Priok
Port. This can be seen from the increased use of spacein the form of processing industries and warehousing
services. Based on the results of the analysis, there
was an increase of 9.26% (from 11.02% to 20.28%)
for industrial and warehousing use.

Land Use in North Jakarta Administrative City in 2008(%)

Facility and Infrastructure

6%
Occupation/Housing

10%

Industrial and Warehousing

22%

Office, Trade and Service

47%
4%Open Space, Cemeterty, Plantation,
Agriculture and Empty Land

11%

OthersFig. 3

Land Use in North Jakarta Administrative
City in 2008.

Impact and Carrying Capacity ofEnvironment on Land Use in North Jakarta

Land Use in North Jakarta Administrative City in 2018(%)

Occupation/Housing

9% 8%
Industrial and Warehousing

22%

6%

20%

Office, Trade and Service

Open Space, Cemeterty, Plantation,
Agriculture and Empty Land
OthersFig. 4

the

Changes in land use influenced spatial patterns
and also had environmental impacts. The occurrenceof changes in land use either due to spatial plans orunmet environmental requirements can have anegative impact on land quality. Things that mightoccur include decreased capacity of ground water,
reduced water absorption (infiltration) so that surface
run off may increase and impacts on erosion andsedimentation and increases flood potential.
The classic problems faced by North Jakarta City
are flood and tidal flood. Artificial landscapes
through the Regional Spatial Planning from year toyear have changed the ability of land to infiltrate. Asa downstream part of the 13 (thirteen) rivers, North
Jakarta City is the estuary where the rivers flow. The
flood in North Jakarta is also caused by the increase
in sea level, so that water cannot be directly flowed
into the sea, especially in the north coast area of DKI
Jakarta. With land surface lower than sea level, thenumber of buildings that continue to grow and theloss of coastal areas make this region vulnerable tosubmergence. Flood is also related to land subsidence

Facility and Infrastructure

35%

OthersLand Use in North Jakarta Administrative
City in 2018.

The results of the analysis showed that the use ofresidential land experienced a significant decline in
the period of 2008 to 2018. This is in accordance withcases of land use in urban areas, where housing iscurrently directed as vertical housing. In accordancewith the DKI Jakarta Spatial Planning which statesthat to achieve good density condition for Jakarta can
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SEE - Bangkok, Thailand, Nov.11-13, 2019and spring tide due to development in coastal areas
and groundwater extraction. Flood phenomena
related to this cause are clearly seen in North Jakartasuch as Pademangan, Muara Baru, part of Gunung
Sahari in the north and Tanjung Priok. Often the floodthat occurs in this area is not directly related to thehigh intensity of rainfall.
Referring to the City Master Plan of 1965-1985 inland use planning, North Jakarta was not planned as
an 'available land' area because the topography is notpossible. Environmental engineering through efforts
to prevent flood and tidal flood in North Jakarta has
been carried out by the Regional Government,
including through the normalization of river water
flow, making sodetan, boundary embankments, sheet
pile installation and so on. But the threat still exists,
considering that the North Jakarta area is basically abasin area. The delay in the construction of polders
and reservoirs, the development of residential areas
around the watershed (DAS) and the lack on the use

Table 2 Analysis Matrix of Land Use Conformity with
the Regional Spatial Planning of North Jakarta
City
Mixed Zone

Recreational Zone

Industrial and Warehousing Zone

Road Zone

Green Zone

Protected Zone

Public Service and Social Zone

Regional Government Zone

National Government Zone

Office, Trade and Service Zone

Office, Trade and Service Zone
Low Building Basic Coefficient

Village Housing Zone

Housing Zone
Low Building Basic Coefficient

Housing Zone
Moderate-High Building Basic Coefficient

Vertical Housing Zone

Vertical Housing Zone Low Building Basic
Coefficient

Cemetery Zone

Reclamation Zone

City Park Zone /Environment

Blue Open Zone

Health Facility
Government
Facility
Education Facility
Religious Facility
Telecommunication
Facility

M
S

TS
TS

TS
S

TS
TS

TS
TS

TS
TS

S
S

S
S

S
S

S
M

S
M

M
TS

M
TS

M
TS

M
TS

M
TS

TS
TS

TS
TS

TS
TS

TS
TS

S
M
M

TS
TS
TS

TS
M
M

TS
TS
TS

TS
TS
TS

TS
TS
TS

S
S
S

S
M
M

S
M
M

M
M
M

M
M
M

M
M
M

M
M
M

M
M
M

M
M
M

M
M
M

TS
TS
TS

TS
TS
TS

TS
TS
TS

TS
TS
TS

M

TS

TS

TS

TS

TS

S

M

M

M

M

M

M

M

M

M

TS

TS

TS

TS

7.

Art and Culture
Facility
Market

M

TS

TS

TS

TS

TS

S

S

S

S

S

TS

TS

TS

TS

TS

TS

TS

TS

TS

8.
9.

Public Service
Study and Research

M
M

TS
TS

M
TS

TS
TS

TS
TS

TS
TS

S
S

M
M

M
M

M
M

M
M

M
TS

M
TS

M
TS

M
TS

M
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS

TS

TS

TS

TS

M

TS

TS

M

M

S

S

S

S

S

TS

TS

TS

TS

TS
TS

TS
TS

S
S

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

M
M

M
M

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

S

TS

M

TS

TS

TS

TS

TS

TS

S

S

TS

TS

TS

TS

TS

TS

TS

TS

TS

Open Space
Forest Area
1. Empty Land

M
M

S
M

M
TS

TS
TS

S
M

S
M

M
M

M
M

M
M

M
M

M
M

M
M

M
M

M
M

M
M

M
M

M
M

TS
TS

S
S

TS
TS

2.
3.

Cemetery
Plantation

TS
TS

TS
M

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

S
TS

TS
TS

M
S

TS
TS

4.
5.

Agriculture
Open Space

TS
M

TS
S

TS
M

TS
TS

TS
S

TS
M

TS
M

TS
M

TS
M

TS
M

TS
M

TS
M

TS
M

TS
M

TS
M

TS
M

TS
M

TS
TS

S
S

TS
TS

6. Agricultural Field
Other Allocation

TS

TS

M

TS

S

M

M

M

M

M

M

M

M

M

M

M

M

TS

S

TS

1.
2.
3.

TS
TS
TS

TS
TS
TS

TS
TS
S

TS
TS
TS

TS
TS
TS

S
TS
TS

TS
TS
S

TS
TS
S

TS
TS
S

TS
M
TS

TS
M
TS

TS
TS
TS

TS
TS
TS

TS
TS
TS

TS
TS
TS

TS
TS
TS

TS
TS
TS

TS
TS
TS

M
TS
TS

S
S
TS

4.
5.

WatersFishery
Defense andSecurity
Transportation
Tourism

TS
TS

TS
S

M
TS

S
TS

TS
TS

TS
TS

S
M

TS
TS

TS
TS

TS
M

TS
M

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
TS

TS
S

TS
TS

6.

Others

TS

TS

TS

S

S

TS

TS

TS

TS

TS

TS

TS

TS

TS

TS

TS

TS

BS

M

S

Detailed Spatial
Planning(RDTR)

Land Use
Facility and Infrastructure
1.
2.
3.
4.
5.
6.

Residential/Housing
1. Residential,
S
Housing,
Settlement
Industrial and Warehousing
1.
2.

Industrial
Warehousing

Office, Trade and Service
1. Office, Trade andService

Information
S:
Appropriate
M:
Supportive
TS:
Inappropriate
BS:
Not Approved

980

SEE - Bangkok, Thailand, Nov.11-13, 2019of land as a green open space (RTH), still make thisarea vulnerable to floods.

accordance with regional functions in the
Detailed Spatial Planning (RDTR).
3. Supportive (M), if land use was not inaccordance with regional functions but its
existence could be maintained or adjusted aslong as it did not interfere and could contributeto the realization of regional functions as
stipulated in the Detailed Spatial Planning(RDTR).
4. Not Approved Yet (BS), if the land allocation
conditions had not been established or had notbeen approved in the Detailed Spatial Planning(RDTR).

Land Use Non Conformity in North Jakarta City
Inconsistencies between spatial planning and theuse can be identified from existing activity andexisting land use. The consistency assessment process
was carried out by qualitative analysis of theconformity between spatial planning and spatial use
identified with existing land use data. The Regional
Spatial Planning was considered consistent if there
was conformity between the two.
From the results of the overlapping analysis using
2018 land use map with spatial planning, it can beseen that there were 'inappropriate' land use with'supportive' land use to the North Jakarta
Administrative City plan. In conducting the analysis,
the authors calculated the appropriate, not appropriate
and supportive land area. Conformity between thetypes of land use for the functions planned in the
Spatial Planning in the North Jakarta Administrative
City was based on four criteria as follows:
1. Appropriate (S), if land use has been fully
was in accordance with regional functions in
the Detailed Spatial Planning (RDTR).
2. Inappropriate (TS), if land use was not in

Fig. 5

The results of the conformity overlay between
spatial pattern plan contained in the Regional Spatial
Planning and Detailed Spatial Planning with the Land
Use Map in 2018 can be seen in Figure 6 for the entire
North Jakarta City and Figure 7 shows the results
based on Subdistrict. The Conformity map ispresented in Figure 5.

Map of Land Use Conformity in 2018 with
North Jakarta City Detailed Spatial
Planning, North Jakarta City

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Tanjung Priok
Koja
Kelapa Gading
Cilincing
Total

Appropiate

7%1423.24
661.041033.901562.34
7650.24

63.49
57.80
64.16
35.32
51.05

Inappropriate

30%

Table 4 Amount of Land Use in 2018 Based on
North Jakarta City Detailed Spatial Planningwith the Supportive Category

51%
Supportive
12%

Subdistrict

Not Approved Yet

Fig. 6

Penjaringan
Pademangan
Tanjung Priok
Koja
Kelapa Gading
Cilincing
Total

Percentage of Land Use Conformity in 2018with North Jakarta City Detailed Spatial
Planning

70
64.16

63.49

Table 5 Amount of Land Use in 2018 Based on
North Jakarta City Detailed Spatial Planningwith the Category of Inappropriate

57.8

60

Supportive
Area (hectare) Percentage
416.779.85
278.2520.87
330.6014.75
116.77
10.21
187.57
11.64
539.8912.20
1869.85
12.48

54.43
49.98
50

45.63

Subdistrict

40

35.32

Penjaringan
Pademangan
Tanjung Priok
Koja
Kelapa Gading
Cilincing
Total

31.94
30

25.26
19.52 20.87
16.2

20

24.2
21.67
14.75
10.21

9.85

11.64

10

12.2
6.85

3.89
0.09

0.05

0

Table 6 Amount of Land Use in 2018 Based on
North Jakarta City Detailed Spatial Planningwith the Category of The Plan Had Not
Approved Yet

0

Fig. 7

Appropiate

Innapproriate

Supportive

Not Approved Yet

Subdistrict
Penjaringan
Pademangan
Tanjung Priok
Koja
Kelapa Gading
Cilincing
Total

Percentage of Land Use Conformity in 2018with North Jakarta City Detailed Spatial
Planning Based on Subdistrict

Table 3 Amount of Land Use in 2018 Based on
North Jakarta City Detailed Spatial Planningwith the Category of Appropriate
Subdistrict
Penjaringan
Pademangan

Inappropriate
Area (hectare) Percentage
826.0419.52
336.8625.26
485.7321.67
365.2031.94
389.9124.20
2118.6845.63
4422.42
29.51

Appropriate
Area (hectare) Percentage
2303.3254.43
666.4049.98

The Plan Had Not Approved
Yet

Area (hectare)685.28
51.88
2.12
0.57
0.00
303.021042.87

Percentage
16.20
3.89
0.09
0.05
0.00
6.85
6.96

The percentage of conformity between spatial
pattern plan contained in the Regional Spatial
Planning and Detailed Spatial Planning with land use
in 2018 can be seen in Figure 6 while the conformity
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SEE - Bangkok, Thailand, Nov.11-13, 2019

map is presented in Figure 5 as the result ofoverlaying the two. Based on figure 5, 6, and 7 it was
known that 7650.24 ha of land use in 2018 or 51.05%
of the total area of North Jakarta City wereappropriate based on the Spatial Pattern Plan.
Whereas 1869.85 ha (12.48%) were Supportive
Spatial Pattern Plan, 4422.42 ha (29.51%) were notappropriate and 1042.87 ha (6.96%) of the plans had
not yet been approved yet. The region with thehighest conformity value was Kelapa Gading Districtof 64.16% and the lowest was Cilincing District of
35.32%.
Then based on the Minister of Agrarian Affairs
and Spatial Planning (ATR)/Head of National Land
Agency (BPN) No. 6 of 2017 concerning Proceduresfor Reviewing Regional Spatial Planning, calculationof utilization conformity (space pattern) could betaken as follows:
𝟕𝟔𝟓𝟎,𝟐𝟒 𝐡𝐞𝐜𝐭𝐚𝐫𝐞
𝟏𝟒𝟗𝟖𝟓,𝟑𝟖 𝐡𝐞𝐜𝐭𝐚𝐫𝐞

allegedly influenced the occurrence of land use nonconformity in North Jakarta City included:
1. Land/Space Ownership System
Regarding land planning, the government plans
to use land in legal individual or corporation
ownership status. The Indonesian state does notadhere to state ownership of land or development
right, but adheres to a property right system. This
results in difficult planning and determination of
spatial patterns. Land rights such as Property
Rights Certificates (SHM) are the basis of thehighest ownership rights in Indonesia.
2. Economic Benefits
Changes in land use were caused by the higheconomic benefits of land in North Jakarta City.
Urban development has led to an increase ineconomic activity, especially in service activities
in the form of industry and warehousing. The
need for spatial use related to houses andbusiness places encouraged changes in the spatialuse, whereas land has a limited nature. Thisencouraged land owners in North Jakarta tochange the functions, open new land or toconsume and utilize their land not in accordancewith the applicable spatial planning regulations.
3. Neighborhood Unit
The theory about Neighborhood Unit is one of
the factors mentioned which could influence thechanges in the use of land functions. This theory
was first created by Clerence Arthur Perry in1929. This idea was later adapted into ideal
settlement planning along with the development
or birth of new cities. Register [16] mentioned
the concept of the Neighborhood Unit to bring up'Integral Neighborhood Area', which was theintegration of neighborhood areas regarding
locations and functions. In the North Jakarta City
area, the Neighborhood Unit factor influenced
the occurrence of non compliance with the city
plan due to the strategic value of the region which
is currently dominated by types of businessactivities.

𝐱𝟏𝟎𝟎% = 51,05 %(1)

With a conformity value of 51.05% and viewed
from the aspect of realization of the type and amountof spatial utilization implementation, North Jakarta
City could be said to had a moderate category. Thiswas due to the realization value of the space
utilization implementation was between 51.05% up to
62.53% if the support category was also included in
the calculation value.
Factors That Affected Land Use Non Conformity
According to Lee [13] in Yunus [14], there were
6 (six) determinant factors that could influencechanges in land use, including: (1) facilities andpublic utilities factors; (2) accessibility factor; (3)fiscal characteristic factor; (4) characteristics oflandowners and land ownership pattern; (5) spatial
regulation factor; and (6) initiative of the developer
factor.
Whereas according to Kikuchi [15], the factorsthat influenced changes in land use could be divided
into 2 (two) factors, namely direct and indirect factors.
Direct factors consisted of population, economic
activities, regional policies, physical resources andsocial systems. Meanwhile, indirect factors consistedof innovation in technology, value systems, lifestyleand national policies. Broadly speaking, deviations
were also influenced by 3 (three) actors, including (1)the community; (2) government; and (3) market or
private power. These three factors did not stand alone,
but affected each other.
Based on the result of interview conducted with
key informant namely the Head of Cipta Karya Office,Spatial Planning and Land Administration of North
Jakarta City and field observations, the factors that

Implications and Approaches in Resolving
Problems as Directions for Preparation of New
Spatial Planning and Evaluation
Coastal areas have a vulnerability to higher landchange and development. The implication as aconsequence of land use non conformity towards
spatial planning may cause threats to the carrying
capacity and sustainability of life in the future.
Problems that arise as a result of the spatial utilization
non conformity that coincide with the unavailabilityof environmental infrastructure in North Jakarta City
resulted in the emergence of irregular housing, traffic
congestion, natural vulnerabilities (floods), damage
to environmental quality, reduced public space andinability to implement government development983

SEE - Bangkok, Thailand, Nov.11-13, 2019

programs and so on.
For this reason, an evaluation of the spatialplanning is needed by conducting a review in the
Regional Spatial Planning document. This is done on
the location of existing land that are still possible tobe corrected and in accordance with applicableregulations. The approach in future planning is thatutilization and management of space must be
harmonious in order to support the development
process. For this reason, every planning must refer tothe nature of sustainable development with an ecoregion approach in accordance with the character ofNorth Jakarta City which is a coastal area.
The direction for the preparation of spatialplanning based on existing land use conditions anddeviations by considering North Jakarta City as anurban area is to encourage the process of designing aspatial planning that is not top-down, but balancedwith a bottom-up process (participatory planning
process).

with a tight control system.
ACKNOWLEDGMENTS
This study is part of the Master's IndexedInternational Publication STUDY (PITMA) of the
University of Indonesia with the theme of "Practices
of Planning and Conflict of Spatial Use in Urban
Development".
REFERENCES[1] Sugandhy, Aca. 1994. Operationalization of
Spatial Planning and Development Trilogy. In the
PRISMA Economic and Social Study Magazine,
No. February 2, 1994.
[2] Special Capital Region of Jakarta Province, 2012.
Regional Regulation Number 1 of 2012
concerning Regional Spatial Planning in 20102030[3] Kivell, Philips. 1993. Land and The City: Pattern
and Process of Urban Changes, London:
Routledge[4] Republic of Indonesia, 2007. Law No. 26 of 2007
concerning Spatial Planning[5] Shirvani, Hamid. 1985. The Urban Design
Process, New York: Van Nostrand Reinhold
Company, Inc[6] Gallion, Arthur B and Simon Eisner. 1986. The
Urban Pattern: City Planning and Design. New
York: Van Nostrand.
[7] Chapin, F.S and J. Kaiser. 1979. Urban Land Use
Planning. Chicago : University of Chicago Press.
[8] Sitorus, S. R. 1998. Evaluation of Land Resources.
Third Edition. TARSITO Publisher Bandung.
[9] Muta’ali, Lutfi. 2013. Regional and City Spatial
Organization (Normative-Technical Review).
Yogyakarta: Publisher Agency of Faculty of
Geography (BPFG), Gajah Mada University[10] Republic of Indonesia, 2011. The Minister of
Public Works Regulation No. 20/PRT/M/2011
concerning Guidelines for Preparation of Detailed
Spatial Planning(RDTR) and District/City
Zoning Regulation[11] Special Capital Region of Jakarta Province, 2014.
Regional Regulation Number 1 of 2014
concerning Detailed Spatial Planning and Zoning
Regulation[12] Republic of Indonesia, 2017. The Minister ofAgrarian Affairs and Spatial Planning/Head of
National Land Agency (BPN) Regulation No. 6 of2017 concerning Procedures for Reviewing
Regional Spatial Planning[13] Lee, L. 1979. Factors Affecting Land Use
Change at the Rural Urban Fringe. Growth andChange : A journal of Regional Development. Vol.
X, Oktober 1979.
[14] Yunus, H.S. 2005. City Management; Spatial
Perspective. Yogyakarta: Pustaka Pelajar.

CONCLUSIONS
Changes in land use utilization in the North
Jakarta Administrative City occurred in several land
uses. Land with increased utilization in North Jakarta
between 2008 and 2018 were industrial andwarehousing of 9.26%. Meanwhile, the land with themost decreased utilization was residential/housing of
11.83%. The increase in changes in land use is inaccordance with the direction of the DKI Jakarta
Spatial Plan, which states that the spatial pattern ofNorth Jakarta City is to provide warehousing andindustrial facilities to support trade activities andservices to support the activities of Tanjung Priok
Port
Compliance between existing land use in 2018with Detailed Spatial Planning in North Jakarta
Administrative City showed a value of 51.05% up to
62.53% which was included in support category. This
figure was categorized in moderate level in theevaluation of spatial use conformity based on
Minister of Agrarian Affairs and Spatial Planning(ATR)/Head of National Land Agency (BPN) No. 6
of 2017 concerning Procedures for Reviewing
Regional Spatial Planning. Based on the results ofinterviews, the factor that allegedly influenced theoccurrence of spatial use non conformity in North
Jakarta City was economic (economic determinant).
The implications of land use non conformity inNorth Jakarta City included the emergence of
irregular housing, traffic congestion, naturalvulnerabilities such as floods, damage toenvironmental quality, reduced public space andinability to implement government development
programs and so on. And approach to overcome these
problems is by reviewing spatial plans, increasing therole of the government in monitoring and controlling
spatial use, and making priority programs and areas
984

SEE - Bangkok, Thailand, Nov.11-13, 2019[15] Kikuchi, T. 1999. Analysis of LUCC And
Forecast With Map Method: A Case of Beijing
Metropolitan Area, China. Proceeding of 1999
NIES Workshop on Information Bases andModelling for Land Use and Land Cover Change

Studies in East Asia. Centre for Global
Environment Research, Tokyo.
[16] Register, Richard. 1987. Ecocity Berkeley:
Building Cities for Healthy Future. North Atlantic
Books, California.

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5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE PATHWAY TO THE ORGANIZATION SUSTAINABILITY
THROUGH THE LAND FOOTPRINT METHOD
Karin Kandananond
Faculty of Industrial Technology, Valaya Alongkorn Rajabhat University, Thailand

ABSTRACTAny supply chains depend on the land use in order to produce the output products or services since all activitiesof the supply chain occurs on the land. Since the availability of the land is a critical global problem, especially, inthe developing countries. The capability to assess the actual amount of land used by an organization or to produce
a product is important to understand how effective the organization has utilized the limited amount of land. Thispilot study was conducted on the land use of an organization which provides the integrated services to thecommunity. At the first phase, the service outcome of the organization is clearly defined. Afterwards, the land useof the organization is measured in order to determine the relationship between the amount of land use and theoutcome. The latter phase is to create the roadmap leading to the sustainability of the land use for the organization.
Keywords: hectare per student, Land footprint, Organization

section, Ruiter et al. [4] studied the agricultural land
footprint of the United Kingdom (UK), and the results
showed that the meat and dairy production mainly
contributed to the large amount of footprint. Ferng [5]utilized the land multiplier to estimate the land
footprint based on the production activities.

INTRODUCTION
Ecological footprint is the consumption-based
indicator which is used to quantify the amount of
resources needed to produce a product. Anotheraspect is of the ecological footprint is the indicatoron the impact of a product produced on theenvironment. The examples of the environmental
footprints are water and Carbon footprint. Since land
use is also important to the production, there isanother indicator which was applied to quantify theamount of land which was used by an organization or
to produce a product. University is an organization
which is in charge of educating the tertiary-level
students including undergraduate and graduate
students. The land is needed by a University in orderto carry out the activities regarding the education of
students. As a result, if the amount of real land iscorrectly quantified, it will be used to indicate theeffect of the organizational operation on theenvironment.

METHODOLOGY
The land footprint is the measurement standard of
biologically productive land where an individual
uses. Therefore, the method used in this study is basedon the global hectare (gha) which is a unit formeasuring the biological production for human use(biocapacity) per hectare of land. The standard
hectare is equivalent to 10,000 square metres.
Biocapacity (BC) is the amount of land, and it isweighted by the productivity of the land. The
biocapacity is calculated by:
BC = YF * EQF * A,where BC is the biocapacity,
YF is the yield factors,
EQF is the equivalence factors, andA is the amount of available area or land.
The concept of biocapacity depends on theamount of equivalent amount of land area used forfive different categories:

LITERATURE REVIEW
Weinzettel et al. [1] Studied the use of land andocean area through the whole process of supply chain
from the production to the final consumption. The
focusing area is the production of agriculture products,
food, and forestry products. For the institutional
footprint, Klein-Banai and Theis [2] conducted theecological footprint analysis for a public University
with many campuses. The footprint was calculated in
the unit of global hectares per total faculty, staff, andstudents. Bruckner et al. [3] investigated theevaluation of the model for calculating land footprintsof the supply chains and studied the contribution of
the footprint on the environment. For the agricultural-Cropland-Fisheries-Forestry-Grazing ground-Built-up land.
The measuring unit is hectare per unit per year.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

ORGANIZATION AREA

Overall area

The study on land footprint of an organization was
conducted on a public University, Valaya Alongkorn
Rajabhat University, Thailand. The University offers
several degrees in both undergraduate and graduatelevels. The main campus is located in Prathumthani
province (Fig. 1). The aerial view of the University
campus is shown in Fig. 2 and 3 respectively.

The land area of the University campus is divided
into many zones, namely education, residential, sport,commercial, self-learning center, recreation area, andagricultural demonstration. Each area with theamount of land is listed in the following table 1.
Table 1 Land for each zone
Zone
Education
Residential
Commercial
Self-learning centerSport
Recreation
Agricultural

Amount of land (rai)
140
40
62
18
50
66
5

The total area is 381 rai or 60.96 hectare. The amountof land in each zone is represented in a pie-chart (Fig.
4).

Fig. 1 University campus

Fig. 4 Amount of land in each zone
Number of students
The number of undergraduate and graduate
students from academic year 2014-2019 is shown in
Table 2.

Fig. 2 Satellite map of the campus

Table 2 Number of students
Academic year
2014
2015
2016
2017
2018
2019

Fig. 3 Campus map

987

Number of students
11,734
11,144
10,97010,365
10,412
10,313

SEE - Bangkok, Thailand, Nov.11-13, 2019

Agriculture area
Since the University has the agricultural
demonstration farm and the crops mainly grown arerice and banana, the biocapacity of these two crops
are calculated.

Fig. 7 Banana plantation area

RESULTS

Fig. 5 Agricultural area

Since all the land is fully utilized to accomplish the
University mission, the yield factor and equivalent
factor were set at 1. Therefore, the global hectare
from academic year 2013 to 2018 is shown in thefollowing table 3.

Rice
Since the approximate amount of land used to growpaddy rice is 1 rai or 0.16 hectare, and the rice yieldis 980 kg or 0.98 ton. The rice was grown andharvested in a yearly basis. As a result, thebiocapacity of the paddy rice is 6.125 ton per hectare
per year.

Table 3 Hectare per student
Academicyear
2013

hectare per
student
192.492014

182.81

2015

179.952016

170.032017

170.802018

169.18

According to table 3, the hectare per student
gradually decreases. The simple reason is that theamount of productive land remains constant, but the
number of students keep dropping from academic
year 2013 to 2018.
For the agricultural farm, two crops, rice andbanana, were grown, and the biocapacity due to thesecrops were also calculated. The biocapacity of the
paddy rice is 6.125 ton per hectare per year, while thatof the banana is 12.5 ton per hectare per year

Fig.6 Paddy rice field
BananaAnother crop grow on the campus is banana(Namwa), and the crop yield is while the land is 1 rai.
The number of banana trees grown is about 100, andthe average yield per tree is 20 kg. Therefore, thebiocapacity of banana is about 12.5 ton per hectare
per year.

CONCLUSIONS
It is interesting to note that the University has
several duties, so different areas of the campus werealso utilized to fulfil the goal of University. As aresult, the whole area of land is fully utilized. The
results indicate that the hectare gradually decreases
every year, since the number of students slightly drop.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Therefore, it is difficult to increase the efficiency ofland use in this aspect. Alternative option to thesustainability through the land use is the agriculturalarea in the University. Since there is the agricultural
demonstration farm on the campus, it is possible toincrease the biocapacity by increasing the yield per an
area unit. This can be done by the productivity
improvement in the farm.

Issue 3, 2011, pp. 857-860.
[3] Bruckner M., Fischer G., and Giljun S.,
Measuring telecouplings in the global landsystem: a review and comparative evaluation ofland footprint accounting methods, Ecological
Economics, Vol. 114, 2015, pp. 11-21.
[4] De Ruiter H., Macdiarmid J.I., Mathew R.B.,
Kastner T., Lynd L.R., and Smith P., Total global
agricultural land footprint associated with UK
food supply 1986–2011, Global Environmental
Change, Vol. 43, 2017, pp. 72-81.
[5] Ferng J.-J., Using composition of land multiplierto estimate ecological footprints associated withproduction activity, Ecological Economics, Vol.
37, Issue 2, 2001, pp. 159-172.

REFERENCES[1] Weinzettel J., Hertwich E.G., Peters G.P., SteenOlsen K., and Galli A., Affluence drives theglobal displacement of land use, Global
Environmental Change, Vol. 23, Issue 2, 2013,
pp. 433-438.
[2] Klein-Banai C, and Theis T.L., An urban
university's ecological footprint and the effect ofclimate change, Ecological Indicators, Vol. 11,989

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

DESIGN AND ASSESSMENT OF A BATTERY OPERATED ROTARY TYPE LOWCOST WEEDER FOR NON-CHEMICAL UP-LAND CROP MANAGEMENT
Mohammad Ashrafuzzaman Gulandaz1, Dr. Md. Israil Hossain2, Dr. Md. Ayub Hossain3
1,2&Bangladesh Agricultural Research Institute

ABSTRACTThe overall goal of this experiment was to reduce the production cost and drudgery of labor in weeding purpose anduse of renewable energy for upland crop production. Adverse effects on environment and cost of chemical weeding are
making farmers to consider mechanical methods of weed control. Manual weeding is common practices in Bangladesh
but it is labor intensive. The mechanical weeder is to reduce drudgery and cost which ensure a comfortable posture of the
farmer during weeding. Weeder is designed and fabricated considering methodological steps. For performance evaluationof weeder, field trials are done among battery operated weeder, BARI push and pull weeder and manual weeding. The
performance of battery operated weeder is quite acceptable for wide row crop. We made fields trial on maize at different
locations of Bangladesh such as Breeding and Irrigation field of Bangladesh Agricultural Research Institute and Bograsadar upazila, Debiganj upazila. Weeding index of battery operated weeder for maize is 92.52 % which is very close to
manual weeding. Again effective field capacity of weeder for maize is 0.046ha/hr and area coverage of weeder is 12
decimals per hr. Plant damage ratio is very few at low height and low canopy crop. A linear relationship is found between
weed density and effective field efficiency. Cost of weeding by battery operated weeder is almost one third compare to
BARI weeder and almost one fourth compare to manual weeding. But there is no significant difference in yield is foundamong these three methods.
Keyword: Weeder, Battery Operated, Weed Management, Environment friendly, Cost effective
transplanted and direct seeded rice due to weeds alone
was assessed as 34 percent and 45 percent respectively.
The research result of Bangladesh Agricultural ResearchInstitute (BARI) showed that weeds affect 80 percent
for eggplant production, 43 percent for potato
production, and 22 percent for Maize production.
Reduction of yield goes more severe when a weed act as
harbor of insects. The losses caused by weeds exceed
the losses caused by any other category of agricultural
pests.
The weeder is to reduce drudgery and ensure a
comfortable posture of the farmer or operator during
weeding and increase production [6]. Mechanicalweeding also keeps the soil surface loose ensuring soil
aeration and water intake capacity. Rotary operation
will always produce the best result [12]. The Rotary
weeder can be made to operate various working depths,
widths and soil conditions [12]. The rotating bladeschop and mix the residues evenly throughout theworking depth, outperforming any other mechanism [3].
Chemical method of weed control i.e. Herbicide
technologies can contribute to reduced production
losses. However, through negative effects on crop,
environment and human health, incorrect herbicide use
may unintentionally counteract efforts to increase foodsecurity [11]. Excessive use of herbicides over a longtime make leads herbicide resistant weeds. There are

Introduction
A weed considers any plant growing in the wrong
place at the wrong time and doing more harm than good[8]. Weeds are plant that competes with crops for water,
nutrients and light. Crop production can be reduced
significantly due to excessive weeds. Weeding andhoeing is generally done 15 to 20 days after sowing.
The weed should be controlled and eliminated at theirearly stage. Depending upon the weed density, 20 to 30
percent loss in grain yield is quite usual which might
increase up to 80 per cent if adequate crop management
practice is not observed [7]. Weeds waste excessive
proportions of farmers’ time, thereby acting as a brakeon development [5]. Weed control is one of the mostdifficult tasks in agriculture that accounts for aconsiderable share of the cost involved in agricultural
production [6]. Farmers commonly expressed theirconcern for effective weed control measures to seizure
the growth and propagation of weeds.
Weeds pose major problem during warm and humid
climate especially affecting Kharif crops. The high costof weeding can be understood from a comparative studyof the losses in the farm due to various causes. Under
plant protection, weed control plays an important rolefor increasing the yield [10]. According to International
Rice Research Institute (IRRI), the yield loss in
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SEE - Bangkok, Thailand, Nov.11-13, 2019some factors including shifting ability of weed
population, increase in environmental concerns andincrease in cost of management, all these factors madefarmers difficult to control resistant weeds within theirlimited resources [1]. All these adverse effects aremaking farmers to consider and accept mechanicalmethods of weed control. Manual weeding is common
in Bangladeshi agriculture. It is the most widely used
weed control method but it is labor intensive.
Agriculture labor is becoming scarce day by day in
Bangladesh. The costs associated with mechanicalweeding such as operating cost can be lowered; as suchmechanical weeding can represent a viable and costeffective option to majority of medium and small scale
farmers in developing countries like Bangladesh.

and growth stages. The need for non-chemical weed
control techniques has steadily increased in the last few
years, as a consequence of the environmental pollution
originated by the intensive application of pesticides inagriculture. Use of rechargeable dry cell battery is also
ensuring the sustainable energy use in weeding purpose.
The overall goal of the research is to evaluate theperformance of a DC motor operated rotary type weeder
intended for fossil fuel operated mechanical weeding in
upland crop production. The specific objective of thisweeder is to remove weeds by using battery power
rather than manual operated weeder to reduce time, savemoney and increase work effort of labor. Therefore, thisresearch was undertaken with the following objectives:a) To design and develop of a DC motor operated dry
land weeder.
b) To test and evaluate performances of weeder byadaptive trail.

The main objective is to develop a battery operated
rotary type weeder which can be used in different crops,
plant spacing systems, various plant intra-row distances
Materials and Methods:
Assumptions:

Motor Sprocket(15 No Teeth)
RPM=700

The assumptions made in the design of the rotary
weeder are presented in terms of field conditions,
machine capacity and energy requirement required to
power it. The machine is to be powered by a 48 volt
750-watt motor which is operated by 48-volt
rechargeable dry cell battery. Belt and sprocket
arrangement shall be employed for transmission of
power. Motor speed is 700 rpm, Number of teeth on
Sprocket = 15, Number of teeth on Sprocket of rotary
shaft= 15x2 = 30, Rotary shaft speed = 350 rpm,
maximum soil resistance value = 1.05 kgf/cm2,
coefficient of friction = 0.1, efficiency of transmission
system = 90%. Transmission of power is shown infigure-1.

Rotary Sprocket(30 No Teeth)
RPM=350

Figure-1: Power transmission system
Design Process:In the design process, calculation of power requirement,
motor selection, chain and sprocket selection and design
and arrangement of tines are needed to be considered.
There is no power in the wheel; so, weeder should be
pushed manually but continuous pushing of tines makes
weeder to go forward easily. The power supply on
rotary shaft should be taken into consideration. There
are two parts of the weeder, one is body and another ishandle. Body part consists of motor, battery, wheel androtary shaft but handle consists of auto switch andconverter. Figure-2 represents the drawing of weeder
with dimension. And figure-3 represents the 3D drawingof weeder.

991

SEE - Bangkok, Thailand, Nov.11-13, 2019

The total power required is estimated as 1.89 hp asfollows
Pd
Pt= 𝜂 = 1.01=1hp
Where,
Pd = Power required to dig the soil
η= Transmission efficiency (0.90).
Thus, a prime mover of 1.0 hp was required for thisweeder.
b. Chain and sprocket selection:
Chain and sprocket arrangement was adopted fortransmission of power. The chain, sprocket and shaft
selection was based on Agricultural Machinery
Management Data.
The size of chain is 60B andnumber of teeth of sprocket is 14. Chain and sprocket
and shaft is shown in figure-4.

Figure.2: Battery operated dry land rotary weeder
with dimension

Figure.4: Chain and sprocket for dry land power weeder
Figure.3: Top, isometric, side and front view Battery
operated dry land rotary weedera.

Power requirement:

The power requirement was calculated using thefollowing equations [4]:𝑆𝑟 𝑥 𝑑 𝑥 𝑤 𝑥 𝑣
Pd=(hp) ------------------- (1)75Where,
Sr = soil resistance, kgf/cm2;
d = depth of cut =2.5 cm;
w = effective width of cut = 26 cm;
v = linear velocity of the tine at the point of contact withthe soil= 1cm;

c. Weeding Tines and Tines arrangement:
A j-shaped tine is designed on the shaft which is shownin figure-4. Length and width of the tine is 80mm, curve
angle of tine is 1200 and 18mm respectively (Fig.5).
Dimension of the shaft is 245 mm and 73 mm
respectively. The shaft consists tines of equal lengths
and arranged in spiral shaped determined as follows(Fig.6).

Hence, power requirement is estimated as
Pd=

𝑆𝑟 𝑥 𝑑 𝑥 𝑤 𝑥 𝑣
75=1.05 𝑥 2.5 𝑥 26 𝑥 1
75= 0.91Figure.5: J-shaped tine for dry land power weeder

Total power required:992

SEE - Bangkok, Thailand, Nov.11-13, 2019shown as Figures 7.
shown in table-1.

The specification of weeder isFigure.6: Spiral Arrangement of J-shaped tine for dry
land power weeder
Machine Description:
The powers to the rotary hoe are supplied from the
motor through chain and sprocket. The various
components of the machine were constructed whileother standard components, such as prime mover andtransmission elements were sourced locally and theparts were assembled at the fabrication workshop of theFarm Machinery and Post-harvest Process Engineering
Division, Bangladesh Agricultural Research Institute(BARI). The pictorial view of the rotary weeder was

Figure.7: Pictorial view of Battery operated dry landrotary weeder

Table.1. Specification of weeder
Sl
no

Items

1

Power

2

Dimensiontine)

Measurement

Motor

1 hp (750watt)

Battery

48 volt Dry cell
Rechargeable
Battery(withRotary1560 mm
mm

7

Shaft

Diameter
Shaft

of

73 mm

Tine

Number of Tine

14

Type of Tine

J-shaped

Tine
Arrangement

SpiralWidth of tine

18 mm

Length of tine

75 mm

x 350

3

Weeder Forward Speed

2 km/hr4

Rated Motor Speed

700 rpm

8

Diameter of wheel

160mm

5

Rated rotary Speed

350 rpm

9

Starting System

Auto switch

6

Rotary245 mm10

Net Weight

27 kg

LengthPerformance Test and evaluation:a.

b. Site and experimental condition:
The experiment was conducted at Plant breeding
research farm of Bangladesh Agricultural ResearchInstitute (BARI), Irrigation and water management
research farm of Bangladesh Agricultural ResearchInstitute (BARI) Gazipur and Debiganj upazila under
Panchagar district during kharif season 2017-18. The
soil was clay loam and soil penetration was recorded
before each treatment imposed. The experiment plot
was well pulverized and leveled with a tractor.

Laboratory Test:

The laboratory test result is summarized in Table.2.
Parameter
Average Value
Rated motor Speed, rpm
700
Rotary blade speed, rpm
350
Theoretical field capacity,
0.10
ha/h

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Weeding index is a ratio between the number of weeds
removed by a weeder and the number present in a unit
area and is expressed as a percentage [9].

c. Crop and weeds
BARI Hybrid Maize 5 (BHM 5) was planted manuallyin the experimental plot (6 x 4 m each) with 60 cm row
to row spacing. Each plot accommodated 6 rows. The
planting date was 6 th December, 2017. Density ofweed was recorded before and after treatment imposed.
The weed sampling was done randomly in middle threerows in 1 x 1 m quadrants. Width of cut is 28 cm, so
double pass is done to cover 60 cm width. Number ofplant damage is recorded and weeds partially damaged
but not up rooted were counted as uncontrolled. Interrow weeds were not removed by mechanical method
but all weeds are removed by manual method. The
common species of weeds were recorded. The
following weeds are significantly present in the testingplots which are shown in table 3.

Six plots of 6m x 4m each were marked out of the main
plot for sampling. Weeds in each plot were counted
before and after weeding using the constructed battery
operated rotary weeder. The time taken to perform thisoperation was noted. Equation 1 was used to calculate
weeding index.
𝑤 −𝑤2

Weeding Index, Iw = 1𝑤

Where,
W1 = weeds before weeding
W2 = weeds after weeding

Table.3. Weeds available in the testing plot
Local
Name

Specifications

Comments

ChapraDurba

Eleusine indica L.
Cynodon dactylon
L.
Elusine indica
Cyperus rotundus
Enhydra fluctuans
L.
Oryza sativa

First threewere
dominant

ChapraMutha
Helencha
Paddy
seedlings-------------------- (1)12.

Plant Damage:

Plant damage was observed in mechanical method andrecorded. Plants damaged completely or uprooted werecounted as 'damaged' and expressed as percent of eachplot the plant damage percent was evaluated by using
equation 2.
𝑤 −𝑤2

Plant Damage percent, Σ = 1𝑤

1

x 100 ----------- (2)Where,
W1 = number of Plant before weeding,
W2 = number of damaged plant after weeding,Σ = Plant Damage percent
3. Field Capacity

d. Fertilizer, Irrigation and earthling up:
Fertilizer and irrigation was applied as BARI
recommended dose. And earthling up is done manuallyat 45 days after sawing.

The weeding tools were tested on the same plots todetermine the field capacity of each of them. Field
capacity is the amount of area that a weeding tool cancover per unit time as shown in equation 3 (Hunt, 1983).

e. Experimental Design:
The study included three treatments replicated four.
The experiment was designed in Randomized
Complete Block. The treatments were:T1 - Weeding by Battery Operated
weeder at 25-45 DAS
T2 - Weeding by BARI push and pullweeder at 25-45 DAS
T3 - Manual Weeding at 25-45 DAS

Field Capacity (ha/h) = 𝑡 x10000 ---------------- (3)f.

60Where,A = Area covered (m2),t = Time taken in hour

Statistical Analysis
All statistical analyses in this experiment were carriedout using statistical package “R 3.4.4” for Windows
Version 2010. Analysis of variance (ANOVA),
Coefficient of variance (CV) and least significant
difference (LSD) between mean values were calculated
at 5% significance level.

Test Procedure:

Performance indicators used for this experiment
includes the following:
1.

𝐴

Weeding Index

Results and Discussion:
994

SEE - Bangkok, Thailand, Nov.11-13, 2019

damage of battery operated weeder (0.50%) and manual
weeding (0.50%) is found insignificant but little plantdamage was found for BARI push and pull weeder(0.75%). Time of weeding was found insignificant
between battery weeder (21.61 hr/ha), however battery
operated weeder was performed better compare to otherpractices. Also inconsequential relation was foundbetween BARI push and pull weeder (73.53 hr/ha) andmanual weeding (70.84 hr/ha). There were no
significant differences in grain yields among thetreatments. But battery operated weeder shown better
performance among the treatments for weeding in maize
field.

Experimental Factors:
Experimental factors used in the field evaluation ofrotary power weeder were approximately same speed inthree blocks. The weeding performance will comparewith the BARI manual weeder and traditional weeding
method. Weeding is only done in maize field.
The performance evaluations were done to investigate
the effect of weed density on performance of three
weeding methods such as battery operated weeder (T1),
BARI push and pull weeder (T2), and manual weedingby spade (T3). Prior to each weeding schedule, weed
density in each experimental unit was determined bylaying-out a squared grid (1 m x 1 m) in the plot andweeds in the grid were counted. Four suchdeterminations were made for each experimental unit.

Field capacity and field efficiency of weeding in maizewere 0.046 ha/h, 92% respectively for battery operated
weeder but for BARI push and pull weeder were 0.021
ha/h, 47% respectively. Plant damage ratio was very
low which less than 1% for battery operated weeder,
Cutting width was 200 mm and depth of cut was 49.3mm of battery operated weeder. Weeding cost per ha ofbattery operated weeder was (1843 tk/ha) lower than

Table. 4. Field performance of different weeding
methods in maize fields
Treatment

T1 (Battery
weeder)T2 (BARI
weeder)T3 (Manual
weeding)
CV
LSD

Field
capacity(ha/h)
0.04643a

Weeding index(%)

Time of weeding(hr/ha)Plant damage
ratio (%)

Yield of maizegrain (t/ha)

92.52

b

21.61

b

0.50

8.90

0.01370

c

86.19

c

73.53

a

0.75

8.42

0.01413

c

93.48

b

70.84

a

0.50

8.42

3.8087

1.92

9.27

37.82

10.89

0.0033

3.57

8.86

0.33

1.83

that
Field capacity, weeding index, plant damage, time of
weeding and grain yield in weeding by battery operated
weeder, BARI push and pull weeder and Manual
weeding by spade in maize fields and their coefficientof variance (CV) as well as least significant difference(LSD) values are shown in Table 4. Significantly thehighest field capacity was found in battery operated
weeder (0.04643 ha/h) followed but field capacity of
BARI push and pull weeder and manual weeding arescored lowest. Almost similar weeding index was foundbetween battery operated weeder and manual weeding
method but the lowest weeding index was found for
BARI push and pull weeder. These results indicated that
more than 90% weeds were removed by battery
operated weeder and manual weeding method and there
was no significant difference between them. Plant

of BARI push and pull weeder (4818 tk/ha) and manual
weeding (7500 tk/ha). Cost of battery weeder was foundhalf compare to BARI push and pull weeding and one
third compare to manual weeding. The performancedata of battery weeder for maize is shown in Table 5.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 5. The performance of battery operated rotary
type weeder for maize, compare to other weedingpractices

Items
Row to row
distance (cm)Number ofturns per row
Average
Weeding depth(cm)
Cutting width(mm)
Average Soil
penetration,psi (10 cm
height)Forward speed(km/h)
Theoreticalfield capacity (
ha/h)
Field
efficiency,( %)Average Plant
height (mm)Battery
weeder60

BARI
weeder60

Manualweeding
60

3

4

N/A

4.93

1.5

N/A

200

150

180

94

94

94

2.5

2

1.5

0.050

0.030

0.027

92.82

45.67

52.32

153

145.67146.67

Economic analysis:
For economic analysis, we need to consider that weeder
is used for business purpose that is rental farming.
Table.8 illustrates the economic analysis of Battery
operated weeder.
Table.8. Economic analysis of Battery operated weeder

Cost
Purchase Priceof weeder
Salvage Value(5% ofPurchase Priceof weeder)
Machine Life
Depreciation
cost per year
Days ofoperation
Depreciation
cost per day
Operatorrequired for
MachineOperation
Cost of
Operator
Total weeding
cost for weeder
per day
Area covered
per ha per day
Number of
WeederTotal weeding
cost for weeder
per haReturnWeeding,
Decimal/hr
Average Area
(decimal) of
weeding
covered perday (8 hr /day)
Rent perA linear relationship is found between weed density andeffective field efficiency which is shown in figure-7.
Here, lower weed density indicates higher weeding
efficiency

y = -0.0534x + 101.39
R² = 0.605

Effective Field Efficiency,%

94
92
90
88
86
84
82
80
78
76
0

100

200
300
400
Weed density, No/sqm
Field Efficiency, %500

Figure.8. Relationship between weed density andeffective field efficiency

996

Battery
Operated
WeederBARI
Push and
Pull
WeederManualweeding

25000

3000

1250

150

5
4750

5
570

30

30

158

19

1

1

25

800

800

7500

958

819

0.52

0.17

N/A

1

1

N/A

1843

4818

7500

17

5

130

42

20

20

SEE - Bangkok, Thailand, Nov.11-13, 2019decimalIncome per day
Net income perday
Net income per
year
BCR
Payback
period in day

CONCLUSION
2600
1642

835
16

49250

486

2
15.23

0.16
185.19The performance of battery operated rotary type low
cost weeder is found quite satisfactory and it is an
excellent weeding technology for farmers. Weeding
index of battery operated weeder is very close to manual
weeding. Effective field capacity and plant damage ratio
is acceptable. Cost of weeding by battery operated
weeder is very low compare to other two weeding
method. Though inter plant weed removal is notpossible but it has no significant effect on yield. But
multipurpose use of battery can ensure the sustainabilityof weeder.

The net benefit cost ratio (BCR) of Battery operated low
cost weeder is 2 which is greater than 1, so it is justified
or acceptable. On the other hand, payback period ofBattery operated low cost weeder is 15 that mean byusing 15 days, farmer can get their investment.

[9] Rangasamy, K., Balasubramanian, M. andSwaminuthan, K. R. 'Evaluation of Power Weeder
Performance.' AMA. vol.24 (4), 1993, pp-16-18.
[10] Rathod r.k., Munde P.A. and Nadre. R. G.
'Development of tractor drawn inter-row rotary
weeder'. International Journal of AgriculturalEngineering, Vol. 3 No. 1, April, 2010, pp- 105109[11] Rodenburg, J., Johnson, JM., Dieng, I. et al.
Food
Sec.
(2019)
11:69.
https://doi.org/10.1007/s12571-018-0878-0[12] Subrata Kr.
Mandal, Basudeb Bhattacharyya,
Somenath
Mukherjee,
andPriyabrata
Chattopadhyay Design & Development of
Rotavator blade: Interrogation of CAD Method,
ISSN: 2322-4541; ©2013 ijsrpub

REFERENCE[1] Asad M, Zahid M, Muhammad M, Adnan A,
Muhammad U R, Wajiha A., Bio-economic
assessment of non-chemical weed management
strategies in minor crops: A review on Weedresearch issues, challenges, and opportunities inPakistan. Journal of Research in Weed Science,
2019, 2(2), 127-140.
[2] Bainer, R., Barger, E. L. and Kepner, R. A.
'Principles of Farm Machinery.' Avi publication Co.
Inc. Westport, Connecticus. 3rd Edition,1978.
[3] Gavali M., Kulkarni S.' Development of rotary
weeder blades by Finite Element Method'
International Journal of Scientific ResearchEngineering & Technology (IJSRET), Vol. 3,2014,
pp-941-945[4] Hunt, D. 'Farm Power and Machinery
Management.' 8th Edition. Iowa State University
Press. AMES. Iowa USA, 1983.
[5] Lavabre, E. M. Weed Control. Macmillian
Education Ltd., London, 1991.
[6] Olaoye J. O., Samuel O. D., and T. A. Adekanye.
'Performance Evaluation of an Indigenous Rotary
Power Weeder.', Energy and Environmental
EngineeringJournal, Vol.1(2), 2012, pp-94-97[7] Oni, K. C. Performance Analysis of a Ridge Profile
Weeder. Proceeding of Nigerian Society ofAgricultural Engineers.Vol.3, 1990, pp189-199.
[8] Parish S. 'A review of non-chemical weed control
techniques'.
Biological
Agriculture
andHorticulture, Vol. 7, 1990, pp-117-137.
997

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

SHEAR STRENGTH AND PERMEABILITY ANALYSIS OFGEOTEXTILE FROM PINEAPPLE LEAVES AND LUFFAINZ Baharuddin1, Hairin Taha2, RC Omar 3, R.Roslan4 and S.Nadirah5
1,2,3,4
Institute of Energy Infrastructure,
5
College of Engineering, Universiti Tenaga Nasional, Malaysia.

ABSTRACT
Geotextiles are commonly utilized in many geotechnical and civil engineering applications for soil
reinforcement, erosion control, drainage, filtration and separation. The market trend for geotextiles nowadays
dominates more on synthetic materials such as polyethylene and polyamide. However, synthetic geotextiles canbe costly when the application involves major construction and larger area. In term of environmental concern,
geosynthetic materials may contain chemical additives that could leak into the surroundings. Geotextile products
from natural fiber such as jute and coir are commonly available especially in India but the market for naturalgeotextiles is very competitive against polymeric geotextiles. In view of that, this study was aimed to design
natural geotextile from local plants. Pineapple leaves were used as the main fibre for the fabrication of geotextile
together with luffa and coconut flakes. Four types of designs were developed based on the seam type and numberof rows of stitching. The strength and permeability of the geotextiles were tested using direct shear box test andfalling head method. Results showed that the geotextile design with J seam and two rows of stitches has thehigher strength and lower permeability. This study demonstrated the beneficial use of agricultural waste frompineapple leaves that can be recycled into sustainable product.
Keywords: geotextile; pineapple leaves; luffa; shear strength; permeability
direction based on ASTM D4595 “Standard Test
Method for Tensile Properties of Geotextiles by thewide width strip method”. Another test based on
ASTM D4884 can also be done to test the seamstrength [5].
In general, there are two types of seamcommonly used to produce geotextile, thesuperimposed seam (S seam) or prayer seam, and J
seam. The S seam is made by stitching two fabrics
together with one or more row of stitching. This is
the easiest type of seam. The J seam is more difficult
to make. It is done by superimposing two fabrics andfolded to produce a thickness of four plies which
contributes to higher seam strength [6]. This type ofseam has more strength compared to other type of
seam. For fabric geotextile, the seam is sewn 1 to 1.5
inches from the edge and folded to create a double
plies thickness. The thread type also affects thestrength of the geotextile. It should have similar or
higher durability. Numbers of rows of stitchingserve as the seam type colleague.
Geotextile should have higher mechanicalstrength due to the applied load of soil which is
directly transferred to it. The occurrence of soil
erosion and landslide is mostly caused by the
weakening soil that has losses its strength [7].
Several factors that affect soil failure include rainfall,erosion, construction activities and external loading.
Soil cannot resist tension but can withstandcompression. The shear strength of soil will decrease
when there is excessive water content in the soil.

INTRODUCTION
Geotextile is mainly used for soil reservation
especially in soil reinforcement, erosion control andreducing surface run-off. Other applications ofgeotextile include separation and filtration between
different type of materials, drainage and containment[1]. Geotextile can be defined as permeable textile
used together with soil, rock, earth, foundation or
geo-engineering materials. Some of the typicalmaterials used to produce geotextile include
polypropylene, polyethylene, polyamides orpolyester [2].
There are two categories of geotextile; woven
and non-woven. The woven geotextiles are
manufactured on a loom through the process of
weaving or knitting textiles which has two sets ofparallel threads [3]. This type of geotextile has
excellent tensile strength. Most geosynthetics are
woven type. The non-woven geotextiles are madefrom the process of mechanical or chemicalinterlocking or thermal bonding of non-woven fabric.
The materials are pressed together using adhesive orheat treatment. However, this type has lower tensile
strength compared to that of the woven type.
Several factors need to be considered when
designing geotextile such as the type of geotextile,
seam and stitch type, thread type, numbers of rowsof stitching and sewing equipment [4]. The strengthof geotextile was mainly influenced by the seamstrength and this can be tested using cross machine
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SEE - Bangkok, Thailand, Nov.11-13, 2019

When the water overflow, the soil structure will
become loose and this results in soil erosion orlandslide. Natural geotextile from plant fiber canhelp reinforce and fertilize the soil at the same time,
unlike geosynthetics [8-9].
In this study, pineapple leaves waste and luffas
were used to produce the natural geotextiles for soil
reinforcement [10]. The concept was to utilize plantfibers which are acquired from local resources suchas the local farms and markets. Malaysia produces
more than one million tonnes of agricultural waste
annually [11]. Instead of burning the agro waste thathighly contribute to greenhouse gas emission, theagro waste could be recycled into sustainableproducts or converted into biomass as renewableenergy.
Pineapple ( Ananas comosus L.Merr) or known
locally as ‘Nenas’ is a tropical plant native to South
East Asia and planted as commodity crop in
Malaysia.
Pineapple
industry
contributes
significantly to the country’s economy and the fiberfrom the leaves can be developed into commercial
products [12].Pineapple leaf is rich in cellulose andbiodegradable. A study on pineapple leave fiber
showed that they are suitable for building andconstruction materials due to its highest cellulosic
content [13-14]. The fibers of pineapple leaves also
have the potential as alternative raw materials in
paper industries due to its good mechanicalproperties and high cellulose contents [15]. In recent
development, pineapple leaves were also found to besuitable alternative natural acoustic material forsound absorption due to the characteristics of its
fiber [16].
Luffa acutangula is extensively used throughout
the world as materials for hybrid biodegradable
geopolymer composites and sound absorbing [1718]. Luffa fiber has high cellulose content, low cost,biodegradable and absorbs water easily. It has athick texture that prevents the water to pass througheasily [19]. For this research, pineapple leaves waste
were obtained from a pineapple plantation in Johor,
Malaysia and Luffa fibers were obtained from
Sarawak, Malaysia.
The objective of this research was to design
natural geotextile from local plant fibers, andevaluate the strength of the geotextile throughpermeability and direct shear box test. The chosen
design based on seam type and number of rows of
stitching will be used to develop the naturalgeotextiles and tested on site to observe theeffectiveness of the geotextiles against erosion.

Four samples of geotextile designs arranged in threelayers were developed based on seam type and rowsof stitching (Fig.2). First, the pineapple leaves andluffa were dried outside for 72 hours until the leaves
and the luffa turned brown in color and completely
dried. This is important to ensure that there was nowater contained in the leaves. When the fiber is fully
dried, the mechanical strength of the fiber will also
increase. Dried coconut flakes were then added asmoisture absorber. Jute thread (5.0 mm thick) wasused to stich the geotextiles. Table 1 shows the typesof geotextile design according to seam type andnumber of rows of stitching which will be tested.

Fig.1 Natural geotextile from luffa and pineapple
leavesFig. 2 Three layers of geotextile

Table 1. Designs of geotextile
2. EXPERIMENTAL
Samples
2.1 Design of Natural Geotextile
The natural geotextile was designed from natural
fibre consist of pineapple leaves and luffa (Fig. 1).
999

Seam Type

Number ofrows ofstitchingSEE - Bangkok, Thailand, Nov.11-13, 2019

A

J

2

B

J

1

C

S

2

D

S

1

The shear strength of the geotextile was
influenced by the seam type and the number of row
of stitching. The results of shear stress at failure
against normal stress for Samples A, B, C and D are
shown in Table 2. Observation showed that the valueof cohesion has decreased, while the friction angles
had similar values but for Sample A, the cohesion
value was 0.00043 and the value for friction angle
was 36.9o. This showed that Sample A has thehigher shear strength compared to that of othersamples.

2.2 Direct shear box test
Laboratory testing was carried out to determine
the most appropriate design of geotextile for soil
reinforcement. The strength of the geotextile sample
was tested using direct shear box test following
ASTM D5321 guidelines. The test equipment
consists of a metal box (100 mm x 100 mm) inwhich the soil specimen and the geotextile will beplaced. The geotextile sample was placed on the top
and below the soil specimen. The strength between
the original soil and soil together with geotextile
sample was compared. The direct shear box test wasdone using different weights (5.0, 10.0 and 15.0 kg).
The type of soil used was sandy SILT withintermediate plasticity.

Table 2. Cohesion and friction angle values
SampleCohesion

Friction angle

A

0.004336.9

B0.002529.5

C

0.0022

28.6

D

0.002

28.4

2.3 Permeability test
The results of the direct shear box test showedsample A has higher strength compared to othersamples, which were 25.83 N/m2, 47.5 N/m2 and69.44 N/m2
for 5.0, 10.0 and 15.0 kg weightrespectively (See Figure 3-5). The shear strength has
decreased from sample A to D. The shear strength of
the geotextile was influenced by the number of rowsof stitching for sample A and C because the stitches
were stronger to hold the fabric together fromshearing.

The permeability of the geotextile wasdetermined through permeability test of falling head
method (ASTM D4491) as described in previous
study [16]. The test consists of flow of water passing
through soil sample connected to a standpipe thatprovides the water head and measures the volume ofpassing water through the sample. The standpipe
diameter is governed by the permeability of thetested soil specimen. Water was allowed to flow
through the sample until it reached the lower limit
and the time was recorded when the water in thestandpipe dropped from the upper to the lower level.
2.4 Experimental application
The geotextile was tested at the selected area.
The soil at the experimental site was classified as
sandy SILT with intermediate plasticity. The
geotextile (20 cm x 20 cm) was arranged on theeroded surface inside a grid measured 600 mm x 800
mm. Prior to that, the subsurface was cleared first to
remove foreign objects. The geotextiles wasproperly arranged on the surface. The sites with
geotextiles were observed for 35 days to monitor the
progress.

Fig. 3 Shear strength using 5.0 kg weigh

3. RESULTS AND DISCUSSION
3.1 Shear Box Test

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 3. Percentage of permeability increment
SampleSeam
type

Original
soilFig. 4: Shear strength using 10.0 kg weight

Coefficientofpermeability(k)
7.2 x 10-4

Increment
(%)

-

A

J

2.16 x 10-7

98.98

B

J

2.26 x 10-7

99.87

C

S

2.33 x 10-7

99.85

D

S

2.36 x 10-7

99.8

3.3 Geotextile Application
The results of permeability and shear box test
showed that the design of Sample A geotextile basedon J seam and two rows of stitching has higher
strength compared to other designs. Based on thesecriteria, the natural geotextile was assembled forexperimental site test against soil erosion. The
geotextiles were arranged on the eroded surface andobserved for 35 days. The observation was
documented on day 7, 14, 28 and 35 as shown in
Figure 6-9. After 35 days of geotextile application,
new batch of grass has grown through the naturalgeotextile, and the geotextile has integrated with thesoil. The eroded surface has been covered withvegetation. This study has demonstrated that thegeotextile from pineapple and luffa has performed asprotective cover for the exposed area.

Fig. 5 Shear strength using 15.0 kg weight

3.2 Permeability Test
The results of permeability test showed that
Sample A has low permeability due to the J seamtype design. Sample A has four plies with two rowsof stitching compared to S seam type which only has
two plies. The test demonstrated that the soil
specimen with geotextile was more impermeable.
The value of coefficient of permeability, k, has
increased when the geotextile samples were applied(Table 3). This showed that the presence ofgeotextile has decreased the permeability of the soil
specimen. The flow of water through the geotextile
took longer time to pass through compared to that oforiginal soil.

Fig. 6: Geotextile application on Day 7

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SEE - Bangkok, Thailand, Nov.11-13, 2019

friction force. The fiber from pineapple and luffa
also has lower permeability, thus, suitable for soil
reinforcement.
This study demonstrated the capability of
pineapple leaves and luffa as renewable resource fornatural geotextile. Thus, this innovative method is
cost-effective and can be developed as commercial
product that would contribute to the economy. On
top of that, natural geotextile from pineapple leaves
and luffa can provide green solution for sustainablesoil reinforcement and slope stabilization. The
design of geotextile from pineapple leaves and luffa
can encourage the recycling and processing ofagricultural materials into sustainable products.
Hence, the newly developed natural geotextile frompineapple leaves and luffa can be used to control soil
erosion.

Fig 7: Geotextile application on Day 14

ACKNOWLEDGMENTS
This study was supported by UNITEN grants
J510050884 (UNIIG 2018) and 201901001YCU/02.

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Fig. 8: Geotextile application on Day 28

Fig 9: Geotextile application on Day 35

4. CONCLUSION
In this work, natural geotextile was designed
and developed using pineapple leaves waste andluffa for soil reinforcement. The geotextile wastested based on the strength and permeability using
shear box test and falling head method. From theresults, it was demonstrated that the geotextile
design with J seam and two rows of stitching had thehigher shear strength to encounter the application of1002

SEE - Bangkok, Thailand, Nov.11-13, 2019the mechanical behavior of sand. Geotextiles
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[13] Laborel-Préneron A, Aubert JE, Magniont C,
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pp.719-734.
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Dashtizadeh Z, Ishak MR & Hoque ME (2015),
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[16] Putra, A., Or, K. H., Selamat, M. Z., Nor, M. J.
M., Hassan, M. H., & Prasetiyo, I. (2018).
Sound absorption of extracted pineapple-leaf
fibres. Applied Acoustics, 136, pp. 9-15.
[17] Koruk H & Genç G (2015), Investigation of theacoustic properties of bio luffa fiber andcomposite materials. Materials Letters, 157,
pp.166-168.
[18] Alshaaer M, Mallouh SA, Al-Faiyz Y, Fahmy T,
Kallel A & Rocha F (2017), Fabrication, microstructural and mechanical characterization of
Luffa Cylindrical Fibre-Reinforced geopolymer
com-posite. Applied Clay Science, 143, pp.
125-133.
[19] Chen Y, Su N, Zhang K, Zhu S, Zhu Z, Qin W,
Yang Y, Shi Y, Fan S, Wang Z (2018), Effectof fiber surface treatment on structure, moistureabsorption and mechanical properties of luffa
sponge fiber bundles. Industrial crops andproducts, 123, pp. 341-352.

1003

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

PARTICIPATION IN WASTE MANAGEMENT BY UNDERGRADUATESTUDENTS OF RAJAMANGALA UNIVERSITY OF TECHNOLOGY
THANYABURI.

1

Korntouch Kosidphokin1
Faculty of Liberal Arts, Rajamangala University of Technology Thanyaburi, Thailand

ABSTRACTThe objective of this research was to 1) study participation of waste management in undergraduate ofRajamangala University of Technology Thanyaburi 2) study knowledge attitude and practice on participation ofwaste management in undergraduate of Rajamangala University of Technology Thanyaburi, 3) study comparisonof knowledge attitude and practice with difference grade and gender of undergraduate of Rajamangala Universityof Technology Thanyaburi. This research was survey research. Populations were 1,280 undergraduates who
enrolled in general education course of social science. Samples were sampling on Simple Random Sampling anddetermined by Taro Yamane table to obtain 300 undergraduates. The research instruments consisted ofquestionnaire for participation of waste management, knowledge test of waste management, questionnaire for
attitude of waste management and questionnaire for practice of waste management. Results were analyzed bypercentage, mean, standard deviation, t–test (Independent) and F–test (One–way ANOVA).The research found
that: Undergraduates of Rajamangala University of Technology Thanyaburi were medium level on participationof waste management with 2.83 of mean scores and 0.90 of standard deviation, Knowledge score at 87.03percent,good level on attitude of waste management with 3.75 of mean scores and0.91 of standard deviation and medium
level on practice of waste management with3.23 of mean scores and 0.86 of standard deviation.
Keywords: Participation , Waste Management, Undergraduate Student and Thailand

institution, that has been placed as a tool for solving
the problems of the country. Therefore, university has
a duty to find solutions for social problem and should
develop teaching and learning that conducive tohelping solve problems. Solid waste problems is the
major problem form environmental pollution and allenvironmental problems. [3]Solid waste wasconsidered to closest problem to humans, that is,humans are the produce solid waste from daily
consumption. One managing approach is allow
waste-contributors participate in solid waste
management at the start from the real cause thatbuilding consciousness in solid waste management
for students, which university will be able to support
the appropriately solution and allowing students
introduce knowledge to families and households thatwill result in the learning and manage solid waste
within households and communities.

INTRODUCTION
Currently, Thailand has experienced problems
from the imbalance in national development resulting
various economic problems encountered due todependence on foreign capital and technology that
resulted in enormously use of natural resources for
production. Until the destruction of natural resources
and ruin culture and local wisdom due decreased
depend upon themselves and migration to work inlarge cities is causing a variety of problems. From
above, there is a tendency of more serious andprovide more broadly. The solution of this problem
therefore requires cooperation from many segments,
including the government, private firm, citizen andinvolved organizations. Regarding the policy toencourage people to realize and aware the importanceof the environment Therefore, in order to easily foster
the right knowledge and values for theenvironment,[1] it is necessary start to from the youth
group by using the educational system as a medium
to aware impact on the environment and cooperate insolving problems and developing the environment.
[2]Solid waste affects the environment and people’s
health directly. The foster consciousness forparticipation in the community for allow people learnsystematically solid waste management to support theincreasing garbage problem. Rajamangala Universityof Technology Thanyaburi is higher education

Method1 Prepared a research area and prepared a researchplan.
2 Meeting of the team of research assistants for datacollection
3 Conduct research according to the research plan.
4 Conferences, research conclusions
The researcher collected data by surveying theparticipation in waste management of undergraduate
1004

SEE - Bangkok, Thailand, Nov.11-13, 2019students at Rajamangala University of Technology
Thanyaburi. And collecting data by testingknowledge Inquire, attitude and practice in theparticipatory waste management of Rajamangala
University of Technology Thanyaburi
RESULTS
Table 1 The participation in waste management fromundergraduate students of Rajamangala University ofTechnology Thanyaburi

Study results, knowledge, attitudes and practices inwaste management from undergraduate students ofRajamangala University of Technology Thanyaburifound percentage of knowledge score at 8 7 . 0 3
percent, while most correct answers is knowledge inthe subject What kind of waste in Rajamangala
University of Technology Thanyaburi Followed byknowledge of Classification of waste, what is 3Rs for
waste reduction and What are the benefits of trash
Respectively.
Table 3 The attitude analysis of waste managementof undergraduate students at Rajamangala Universityof Technology Thanyaburi

The participation in waste management fromundergraduate students of Rajamangala University ofTechnology Thanyaburi are as follows: It was foundthat undergraduate students Rajamangala Universityof Technology Thanyaburi Participate in waste
management in the overall at a moderate level where
the average participation score is 2.83, the standard
deviation is 0.90.
Table 2 Study results, knowledge, attitudes andpractices in waste management from undergraduate
students of Rajamangala University of Technology
Thanyaburi

The attitude analysis of waste management ofundergraduate students at Rajamangala University ofTechnology Thanyaburi found that the attitude ofwaste management of undergraduate students overall
at a good level with an average of attitude level of
3.75, standard deviation of 0.91
Table 4 The results of the analysis of waste
management practices of undergraduate students at
Rajamangala University of Technology Thanyaburi

1005

SEE - Bangkok, Thailand, Nov.11-13, 2019

From Table 6 , it was found that male students had ahigher attitude towards waste management thanfemales in different average scores with statisticalsignificance at the level of 0.05 and no difference inknowledge and practical skills between male andfemale students.

The results of the analysis of waste management
practices of undergraduate students at Rajamangala
University of Technology Thanyaburi found thatpractice in waste management of undergraduate
students is moderate level with overall average of
3.23, standard deviation equal to 0.86

CONCLUSIONS
1. Participation in waste management ofundergraduted students at Rajamangala University ofTechnology Thanyaburi Participate in moderate
waste management
2 Knowledge measurement in waste management ofundergraduted students at Rajamangala University ofTechnology Thanyaburi students is 87.03 percent.
3. Measurement of attitude in waste management ofundergraduted students Rajamangala University ofTechnology Thanyaburi Overall at a good level Withan average of 3.75
4.Waste management skills of undergraduted
students at Rajamangala University of Technology
Thanyaburi At a moderate level with an average of
3.23
Discussion of research results
1. Discuss the results of the participation of students
at Rajamangala University of Technology
Thanyaburi. Participation in waste management is at
a moderate level, consistent with the study of[4] [6] It
was found that knowledge about solid waste disposalof people at moderate level and the participation ofpeople in the disposal of solid waste is relatively low.
And the relationship between knowledge and public
participation in solid waste disposal is related tostatistical significance at the level of 0.05
2. Discussion of the study of knowledge in waste
management of students at Rajamangala Universityof Technology Thanyaburi Consistent with the studyof[4] That knowledge of solid waste management of
the people is related to the participation of people insolid waste disposal with statistical significance at thelevel of 0.05 and [5] People have a high level ofunderstanding and consciousness in waste
management. And knowledge and understanding of
the community were significantly related toparticipation in waste management

Table 5 The comparative study of knowledge,
attitude and practical skill in waste sorting
management by student’s year of Rajamangala
University of Technology Thanyaburi

The results of data analysis, comparative study ofknowledge, attitude and practical skill in wastesorting management by student’s year ofRajamangala University of Technology Thanyaburifound undergraduate students at the levels of Year 1,
2, 3 and 4 or in different years, there is a different
knowledge, attitude and practical skills in waste
management.
Table 6 The comparative study of knowledge,
attitude and practical skill in waste sorting
management by student’s sex of Rajamangala
University of Technology Thanyaburi

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SEE - Bangkok, Thailand, Nov.11-13, 2019

3. Discuss the results of the study on the attitude ofwaste management of Rajamangala University ofTechnology Thanyaburi students. [5] People have ahigh level of consciousness in waste management.
There is a reason to participate in waste management
activities to make the community clean. With
beautiful scenery During reducing environmental
problems and increasing family income.
4. Discuss the results of the study of practical skills in
waste management of Rajamangala University ofTechnology Thanyaburi students. [5] found that thecommunity can separate garbage And take the waste
to a high level There is a high level of properhousehold waste disposal behavior. The main reason
that communities participate in waste management
activities is to make the communities clean, clean,withbeautifulscenery.
Duringreducing
environmental problems and increasing family
income.
5. Discuss the results of the study comparing
knowledge, attitudes and practical skills in waste
management classified by grade level of Rajamangala
University of Technology Thanyaburi students.
Residence time Sources that receive information andfrequency of receiving different information There isa different behavior in participation in solid waste
disposal. [7]It was found that gender, age, education
were different in participation in different sorting ofwaste at statistical significance level. 0.05 [5] foundthat knowledge Community understanding has asignificant relationship with participation in waste
management.

Liberal Arts and the Institute of Research andDevelopment,
Rajamangala
UniversityofTechnology Thanyaburi (RMUTT), for their financial
support.
REFERENCES[1] DepartmentofEnvironmental
Quality
Promotion.2000.Environmental
Knowledge.
Bangkok. Environmental Quality Promotion
Department, Ministry of Science andTechnology[2] Pollution Control Department .Thailand State of
Pollution Report 2011. Pollution
Control
Department, Ministry of Science andTechnology[3] Suchada Chaisawadi , Penprapa Buoy andAnchalee Chimphalee .2007. Recycling waste
management within King Mongkut's Universityof Technology Thonburi.
[4] Preecha Kulavanich. 2005. The relationshipbetween knowledge about participation in solid
waste disposal: a case study of the Saen Phu Dat
Subdistrict Administrative Organization Ban
Pho District Chachoengsao[5] Kapkaew Panyathai. 2011. Participation ofcommunity in waste management in Kokha
Municipality, Lampang Province. pp 1-105[6] Supot
Subphadungchan.
2004.
Peopleparticipation behavior in solid waste disposal: acase study of Ban Chang Municipality, Ban
Chang District, Rayong Province.
[7] Chatchai Nuanphen. 2006. Public participationin waste sorting in Roi - Et Municipality.

ACKNOWLEDGMENTS
The author would like to express sincere
appreciation to my family ,my friends, the Faculty of1007

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

ENVIRONMENTAL MANAGEMENT FOR GREEN UNIVERSITY
BASED ON THE UI GREEN METRIC OF UNIVERSITY SUCCEED.
1

Korntouch Kosidphokin1
Faculty of Liberal Arts, Division of Social Sciences Rajamangala University of Technology Thanyaburi,
Thailand

ABSTRACTThe aim of this study was to study the environmental strategic of technical university succeed for green
university based on the UI Green Metric World. This research was conducted data collection at two technicaluniversities, King Mongkut's University of Technology Thonburi (KMUTT) and King Mongkut's University ofTechnology North Bangkok (KMUTNB). This research was study by qualitative research surveys. Observationand in-depth interviews with key persons from universities’ officer were used as research tool for collecting theconcept data. Data were analyses in content analysis with combination analyzing including observation, in-depth
interviews, plan and policy, final and meeting report of related to the UI Green Metric World. The result of thisstudy revealed that the two universities have an action plan based on 5 topics in the UI Green Metric World
including 1) green position and infrastructure 2) energy management system and climate change 3) waste
management 4) water Management and 5) green transportation. Summarize of this research shown that the
KMUTT have had five topic of environmental strategic in same direction with the KMUTNB. However, differenceof concept and action plan of each environmental strategic were found. Moreover, this research shown that the
KMUTT, where have a master plan for becoming green university based on the UI Green Metric World, whichhave an environmental management systems continuous and modern for support the global trends.
Keywords: Green university, environmental management, Green metric world, University Succeed
with the ecological system, taking into account the
integrationofenvironmental
management(Stitmannaithum, 2016; Mahidol University 2014 ).
Assessment criteria to become a green university
has risen from the University of Indonesia since 2010
until the present. In order to rank the green
universities which was run by the University ofIndonesia, the assessment criteria are six aspects: thesystem of infrastructure, energy management andclimate change, waste management, water
management, transportation and environmental
education (UI GreenMetric World University
Ranking, 2016). With reference to universities inThailand, there are 7 universities that have beenranked, namely, Mahidol University. King Mongkut's
University of Technology Thonburi, Chulalongkorn
University, Kasetsart University, Mahasarakrm
University, King Mongkut's University ofTechnology North Bangkok and Burapha University(UI GreenMetric World University Ranking, 2016;
Mahidol University 2014). (Suwanna Ruangchanaset
2013; Stit mannaithum, 2016). It has been acceptedthat the management and systems that the universities
had developed with an aim to be recognized as a green
university at an international level can be used todrive important factors that supports educational
institutes at the higher education around the world,
especially imposing policies and organizing theenvironmental management systems within theuniversity to be sustainable and conducive to reducethe impact that causes global warming by considering

INTRODUCTION
Green University means a university that has goodmanagement to make use of resources effectively,
using energy efficiently with the prevention ofpollution or minimizing emissions of the pollution,enhancing the quality of life with a good and safe
working environment as well as preserving theenvironment and integration for sustainability (UIGreenMetric World University Ranking, 2016, QS
Worldwide university rankings, 2012). In order tobecome the Green University, the university must
consider the three vital dimensions: social dimension,
economic dimension, and environmental dimension.
According to the social dimension, the university has
an explicit policy to closely build relationships withsurrounding
communities
bydeveloping
communities continuously and organizing usefulactivities in cooperation with the community
corporately implementing projects to expand
educational opportunities for the surrounding
communities and educational institutions in the area.
Regarding to economic dimension, the university
arranges some parts of their areas for the private
sectors to do their business such as restaurants,
convenience stores, banks, a post office to provide
services for university staffs working in the university
and surrounding communities. Regarding toenvironmental dimension, the university has anaccessible development plan for the landscape systemand has research and development that is consistent
1008

SEE - Bangkok, Thailand, Nov.11-13, 2019energyconservation,
good
environmental
management and increasing green space andpromoting the use of renewable energy (Suwanna
Ruangchanaset 2013; Stit mannaithum, 2016)(Kunnatham Santitham, 2549; Mahidol University
2014; Stitmannaithum, 2016). However, theimplementation of the green university development
policy In Thailand is varied in terms of activities. The
activities depend on the readiness of personnel, thereadiness of areas and budget of the university as wellas participation in the development of the university(Kunnatham Santitham, 2006; Mahidol University
2014; Stitmannaithum, 2016). Therefore, this study
focuses on gathering strategies, visions, missions,
goals and strategies for green university development
within the universities that have achieved their goals
and complied with the Green University criteria to be
used as a guideline for raising the quality of life forpeople both inside and outside the university, forconserving sustainable environment and also forbeing a guideline for driving the planning andimplementation of environmental management
strategies.

environmental management strategies according to
the green university criteria of King Mongkut's
University of Technology Thonburi and King
Mongkut's University of Technology North Bangkok,
the findings obtained from the document analysis andthe opinions of university executive group andpersonnel group who were responsible forenvironmental management operations can bedivided into six aspects.
Aspect 1 Location and Infrastructure
King Mongkut's University of Technology
Thonburi had a policy to increase green space in theuniversity by implementing projects and activities in
the following topics: 1) management of the locationand structure whose the responsible division was the
Building of Safety, Environment and Occupational
Health Center, 2) building standardized green
buildings, 3) brainstorming opinions of university
personnel for making Master Plan of Green
University, 4) creating Green Heart for students to beleaders and practitioners of which would affect thesustainability of the green university, 5) training thehousewives in the separation of garbage at least oncea year, and 6) using the Academic Affair Division asa key division to organize activities about the Green
University starting from the orientation of how to
reduce the amount of energy use in the previous year
until at the present time and to continue this reduction
to the future. This has been implemented by 1)
creating a garden, a fence, and a tree plantation atpresent and 2) establishing a green university’s
master plan commencing in 2010 to 2020.
King Mongkut's University of Technology North
Bangkok had a policy to increase green space in theuniversity by focusing on providing exercise space byimplementing the projects and activities in thefollowing topics: 1) designing the Rayong Campus tobe a natural university, 2) creating a green
environment area on the decks of the multi-purposesbuildings at Bangkok Campus focusing on creating
green environment to motivate personnel to do
exercises, 5) building roof covers between lecturebuildings to reduce energy use, 6) improving thelandscape of both sides in front of the university
entrance at Prachinburi Campus, 7) implementing
Rayong Plantation Project to create gardens, signs,
fences with grown perennial plants, providing
exercise equipment and supplementary environments
for exercises such as bicycle paths.
Aspect 2 Energy Management and Climate
ChangeKing Mongkut's University of Technology
Thonburi had a policy to reduce the energy use andreduce pollution within the university byimplementing projects and activities as follows: 1)
building a control building to perform energy
consumption analysis aiming to send information to
the Ministry of Energy by reporting annually, 2)
having students conduct research on the university's

METHODOLOGY
1. Study essential and related contents fromdocuments and websites of King Mongkut's
University of Technology Thonburi and King
Mongkut's University of Technology North Bangkok.
2. Interview in-depth and observe university staffs
of King Mongkut's University of Technology
Thonburi and King Mongkut's University ofTechnology North Bangkok.
Two universities focusing on technology havebeen selected according to the criteria of the Green
University of 2015, namely King Mongkut's
University of Technology Thonburi and King
Mongkut's University of Technology North Bangkok.
Each of the universities was divided into two sample
groups: university executive group consisting of thepresident or vice president of the university, andpersonnel group who was responsible forenvironmental management in accordance with theuniversity's green criteria. Two people in eachselected university were selected as informants.
The research tool is an unstructured interview togain in-depth information on the environmental
management strategies based on the Green University
criteria of King Mongkut's University of Technology
Thonburi and King Mongkut's University ofTechnology North Bangkok. Content analysis model
was used to analyze the data obtained from the indepth interviews and observations in accordance withthe policy of the action plans, project of recording
meetings, summary reports and other
FINDINGS
Regarding to the study using unstructured
interviews to gain information about the1009

SEE - Bangkok, Thailand, Nov.11-13, 2019energy consumption at the faculty level, 3) appointing
a working group at the faculty level to be responsible
for the energy of the faculty, 4) setting up a working
group at the faculty level to control the amount ofenergy use, 5) supporting the saving of electricity
within every faculty, 6) using renewable energy in the
Faculty of Industrial and Agricultural Technology, 7)
designing the building which is energy-saving andenvironmentally friendly, 8) promoting cycling
within the university, 9) using the electric buses witha golf cart style in the university, 10) arranging
electric shuttle buses between the campus. To reduce
the energy use, the activities undertaken were as
follows: 1) switching off all classrooms’ electric
lights and air-conditioners 15 minutes before theclasses ended, 2) using renewable energy, forexample, biogas and solar energy, 3) providing
bicycle loan for riding within the university, 4) “Hopup electric cars service” for travelling around theuniversity, and 5) electric motorcycle loan to ride
within the university.
King Mongkut's University of Technology North
Bangkok had a policy to reduce the energy
consumption of the university staff and the pollution
within the university by undertaking projects andactivities in the following topics: 1) changing the lightbulbs from T5 to LED, 2) turning off electricity at a
specific time and turning off the air-conditioners
before the end of classes and meetings, 3) arranging
transportation within the university, 4) adjusting airconditioning system as a separate air-conditioning
system, 5) cleaning air conditioners carried out by
students, 6) using renewable energy in daily life, inindustry and agricultural technology, 7) designing
energy-saving and environmentally friendly building,8) building roof covers by using solar roof on campus
and guardhouses, 9) building solar farm power station
at Rayong Campus. The reduction performance ofenergy use has been undertaken as follows: 1)changing 30,000 light bulbs within the university, 2)setting the specific time of 15 minutes for turning off
electricity and air-conditioners in every classroom
before the end of the class, 3) providing electric buses
for transportation within the university, 4) graduallychanging the air-conditioners to be the ones certified
with electricity saving no. 5, while the university also
supporting budget for the project of cleaning airconditioners by students, 6) every building in theuniversity was certified by energy-saving building
standards in both good and very good levels, 7) solar
roof producing electricity fed into the surrounding
buildings, and 8) conducting research study on station
generating electricity, solar farm aiming to be ademonstration station and learning center of solar
farm for surrounding communities.
Aspect 3 Waste Management
King Mongkut's University of Technology
Thonburi had a policy to reduce waste, promoting
energy production from waste and processing waste

and treatment of wastewater with the projects andactivities in the following topics: 1) creating
KMUTT's waste management system by using 5colors-coded bins: green, blue, red, yellow, and gray,2) treatment of toxic waste which was sent toeliminate once a year, 3) treatment of organic waste,4) treatment of inorganic waste water, 5)
implementing recycle to cycle project, and 6)
treatment of waste water in the university. To reduce
the energy use, the activities carried out were as
follows: 1) There were specialist for toxic waste
treatment in the laboratories. Some toxic waste wasrecycled. 2) Garbage was made into compost andproduced as biogas. 3) There was a waste bankestablishment for everyone in the university to be amember. 4) Garbage of bottles and cans from wastebanks was sold and the money received was spent on
buying bicycles for bicycle loan. 5) There were
working staff, volunteer students, who were
responsible for bicycle loan. Moreover, if they wereable to teach how to fix the bicycles, they would earnmore scores for their courses when awarding thegrade. 6) The process of borrowing and returning thebicycles in the bicycle loan arose from the scores ofcans deposited into the waste bank. If the member ofthe waste bank were not able to exchange the scoresin time as specified in the campaign, he could get acap from the sponsor, Coke Company Limited as areward instead. 7) Wastewater treatment from thesources was not combined with chemicals which wasinspected throughout the process and there was astandard inspection pond prior to the separation of
toxic water and dirty water.
King Mongkut's University of Technology North
Bangkok had a policy to reduce waste, promoting
energy production from waste and processing waste.
There were projects and activities in the following
topics: 1) waste recycling campaign and waste
separation to put into the correct waste bins, 2)organic and inorganic waste treatment, 3) wastewater
treatment in each building, 4) waste water treatment
before being released into the canal, 5) creating apollution-free kiln that was eco-friendly, 6) proper
waste management of chemicals used in teaching andlearning, 7) promoting the use of 3 Rs principles:
Reuse Reduce, and Recycle, 8) Integrated waste andwaste management project at Rayong Campus. To
reduce the energy use, the following activities were
undertaken: 1) providing color-coded waste bins toseparate the waste in every area under the buildings
and along the pathway, 2) the collected garbage sent
to garbage trucks of Bangkok by separating garbage
types, 3) wastewater treatment in each building, 4) a
total wastewater treatment system before being
released into the public canal, 5) reduction of paperuse, use of electronic files instead, and use of doublesided paper, and 6) separating plastic water bottles
from general waste and separating A4 waste paper
prior to sale.
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SEE - Bangkok, Thailand, Nov.11-13, 2019

Part 4Water Management
King Mongkut's University of Technology
Thonburi had a policy to reduce water consumption
and reduce waste water. There were projects andactivities in the following topics: 1) installation of awater meter connected to a power meter to check theusage, 2) continuously check the quality of
wastewater in the reservoir, 3) measuring the progressof achieving the main factors of water management
success by using key performance indicators (KPIs)
by means of establishing a joint committee consistingof personnel from various faculties in the university,4) flushing the toilet using recycle water in thebuildings starting from the new buildings, 5) using
water-saving devices and using water from natural
ponds to water trees, and 6) promoting awareness ofwater management for sustainable water use by
granting shirts, certificates and trophy.
King Mongkut's University of Technology North
Bangkok had a policy to reduce water consumption
and reduce waste water with projects and activities in
the following topics: 1) conservation of water use inscientific laboratories, 2) changing of sanitary ware tosave water, 3) applying treated water to watering
plants at Prachinburi Campus and 4) reusing water at
the Rayong Campus. To reduce the energy use, thefollowing projects and activities were undertaken: 1)
water circulation in the laboratory which produced nowaste water, 2) installing the urinal system for maleusing automatic system and water-saving toilet, 3)
bringing waste water to a connected pipe line forwatering the trees around the buildings, and 4)
reusing the treated wastewater for watering the trees
and cleaning the streets.
Aspect 5 Environment-Friendly Transportation(Eco-Friendly Transportation)
King Mongkut's University of Technology
Thonburi had a policy to reduce vehicles use and touse vehicles that do not use gasoline-based fuel. The
projects and activities to reduce energy use have been
carried out as follows: 1) to promote walking and useof bicycles for students, staff and personnel byloaning to use bicycles within the university, and 2)
to provide electric golf carts as a service for lecturers
and staff by arranging the points for borrowing andreturning the bicycles and the points for passengers
disembarking the electric golf carts.
King Mongkut's University of Technology North
Bangkok had a policy to reduce vehicle use and to use
vehicles that did not use gasoline-based fuel. Theirprojects and activities were as follows: 1)
construction of walking paths with roof cover, 2) bikeriding campaign, 3) electric golf carts for lecturers
and university staff in the university and at Rayong
Campus, and 4) 15-seat electric cars. The activities toreduce energy use have been carried out as follows:1) construction of walking paths with roof cover, 2)scheduling the service of electric golf carts related tothe specified time, 3) reducing the amount of using

private cars, 4) providing three 15-seat electric cars
using solar power generation at Rayong Campus.
Summary and discussion of research results
The findings of the research study can besummarized as follows:
1. Regarding to the criteria for location andinfrastructure, it was revealed that King Mongkut's
University of Technology Thonburi and King
Mongkut's University of Technology North Bangkok
had a policy pulled in the same direction, which was
to increase the green areas in the university. Their
effective policy implementation was creating gardens
and signs, building fences and growing perennial
plants. These activities had been done to increase thegreen areas in other universities in Thailand as well.
( Stit mannaithum, 2016; Kunnatham Santitham,
2006; Thannapat Jarernpanit, 2015; Mahidol
University. 2014).
However, when considering the concept ofcreating a green area, it was shown that King
Mongkut's University of Technology North Bangkok
focused on providing green space for doing exercises.
This project had been piloted at Bangkok Campus byproviding the exercise equipment and organizing thegreen environment in the exercise area. On the other
hand, King Mongkut's University of Technology
Thonburi developed green areas in the university byfocusing on increasing the quantity of the green areas
and maintaining the sustainability of themsimultaneously. This had been implemented byconstructing the Green Campus Master Plan which
represented their concept of and determination insustainably eco-friendly management and sustainably
environmental
conservationininstitutions
Kunnatham Santitham, (2006).
. 2 Regarding to energy management and climatechange criteria, it was revealed that King Mongkut's
University of Technology Thonburi and King
Mongkut's University of Technology North Bangkok
had a policy pulled in the same direction in terms of
reducing the energy use of the organization andreducing pollution within the university. Bothuniversities had implemented some activities for the
reduction of energy use similarly as follows: ) 1
saving electricity by setting the time to turn off theelectricity and the air-conditioners, ) 2 use ofrenewable energy, namely bio-gas and solar energy,) 3 changing the use of common electrical appliances
to that of energy-saving ones, especially airconditioners and light bulbs, and ) 4 management ofusing a separate air-conditioning system. However,King Mongkut's University of Technology Thonburi
had a different policy, that was the provision ofelectric cars within the university and electricmotorcycle loan service within the university.
. 3 Regarding waste management criteria, it was
found that King Mongkut's University of Technology
Thonburi and King Mongkut's University ofTechnology North Bangkok had a policy pulled in the1011

SEE - Bangkok, Thailand, Nov.11-13, 2019same direction in terms of reducing the amount ofwaste, promoting energy production from waste andprocessing waste, together with waste water treatment
Kunnatham Santitham, (2006).
However, when considering the concept of waste
management, it was found that there were different
implementations. This means that King Mongkut's
University of Technology Thonburi had a variety ofactivities including 1) reducing waste while
promoting energy production from waste andprocessing waste which were carried out by
university staff, 2) transforming garbage into compost
and producing as biogas, 3) setting up a waste bankfor everyone in the university to be a member, 4)
bringing cans from garbage banks to sell and using
the money earned to buy bicycles for bicycle loan, 5)
recruiting volunteer students to take care of the loan
bicycles with extra points earned if repairing thebikes. 6) borrowing and returning the bicycles orbicycle loan depended on the points earned when
delivering the garbage cans into the garbage bank. If
the member was not able to redeem his points in time,
he would receive other thing as a reward from the
support of the soft drink company (sponsor). 7)
Wastewater treatment from the sources was not
combined with chemicals which has been inspected
throughout the process and there was a standard
inspection pond prior to the separation of toxic waterand dirty water Kunnatham Santitham, (2006).
Regarding King Mongkut's University of Technology
North Bangkok, there were only two activities
implemented: placing waste separation bins at every
point under the buildings along the pathway andtransferring the separated waste to the garbage truckof Bangkok( Kunnatham Santitham, 2006; Thannapat
Jarernpanit, 2015).
4. Regarding to water management criteria, it was
found that King Mongkut's University of Technology
Thonburi and King Mongkut's University ofTechnology North Bangkok had a policy pulled in thesame direction that is to reduce water consumption
and waste water. When considering the concept ofwaste water management, there were different
operations. King Mongkut's University ofTechnology Thonburi implemented projects andactivities of 1) installing a water meter connected to a
power meter to check the usage, 2) checking thequality of wastewater in the reservoir continuously,
3) measuring the progress of achievement in the main
factors of success in water management by using the
key performance indicators (KPIs) by means ofestablishing a joint committee consisting of personnel
from various faculties in the university, 4) installing
toilets flushing with recycled water in the buildings,
starting at newly constructed buildings, 5) using
water saving equipment and water from natural ponds
for watering plants, and 6) promoting awareness ofwater management for sustainable water use by

granting shirts, certificates and trophy KunnathamSantitham, 2006; Thannapat Jarernpanit, 2015).
King Mongkut's University of Technology North
Bangkok had fewer implementations which were 1)
water circulation in the laboratory without waste
water, 2) installing the urinal system for male using
automatic system and water-saving toilet, 3) using
treated wastewater in the pipe line to water plants
around the buildings, and 4) applying treatedwastewater to water plants and cleaning the streets.
5) Regarding the criteria of eco-friendly
transportation, it was found that King Mongkut's
University of Technology Thonburi and King
Mongkut's University of Technology North Bangkok
had a policy pulled in the same direction in terms of
reducing vehicle use and using vehicles that did notuse gasoline-based fuel. There was one similar
operation that is providing electric golf carts service
for teachers and staff as well as promoting walking
within the university to reduce energy consumption.
However, when considering the concept of ecofriendly transport management, it was found that
King Mongkut's University of Technology Thonburi
had different ways to promote the reduction ofvehicle use by promoting the use of ordinary bicycles
and creating a pilot project for using electricmotorcycles within the university. This pilot projectfor using electric motorcycles has never been
implemented in Thailand before.
CONCLUSIONS. This research shows that successfulenvironmental management based on the green
university criteria for universities that focus ontechnology and whose policies, activities, and masterplans have already been started for implementation
and are work-in-progress at present like King
Mongkut's University of Technology Thonburi
depends heavily on continuous environmental
management with extension and modernization to
support the world’s future situations
ACKNOWLEDGMENTS
The author would like to express sincere
appreciation to my family ,my friends, the Faculty of
Liberal Arts and the Institute of Research andDevelopment,
Rajamangala
UniversityofTechnology Thanyaburi (RMUTT), for theirfinancial support.
REFERENCES[1] Mahidol University. (2014). Mahidol University
has been ranked 1st in Thailand and 31st
worldwide by UI Green Metric World
Universities Ranking 2013 [In Thai]. Retrieved
May
1,
2016,
from
http://www.mahidol.ac.th/th/latest_news57/UI_Green.html
1012

SEE - Bangkok, Thailand, Nov.11-13, 2019[2] Stitmannaithum.(2016).Chulalongkorn
University Sustainability Report 2013-2014.
Chulalongkorn University. 52 P
[3] QS Worldwide university rankings. (2015).
Green Universities. Retrieved on: May 1, 2016.
https://www.topuniversities.com/universityrankings/world-university-rankings/2015[4] UI
GreenMetricWorld
University
Ranking.(2016). Criteria & Indicator. Retrieved
on:May1,2016,from
http://greenmetric.ui.ac.id/page/criteria[5] Kunnatham Santitham, 2006. Guidelines for
improvement of site layout and management toclean green university: Thammasat University,
RangsitCampus.
JournalofArchitectural/Planning Research and Studies 4(2). 157-185p.
[6] Thannapat Jarernpanit. 2015. Application of
public policy processes in the development ofgreen universities Of Pibulsongkram Rajabhat
University Phitsanulok ProvinceJournal ofEnvironmental Management11 (1). 86-97 p[7] Chakrapong Phuwichan. 2012. Report the
project results according to the strategic plan
Maejo University Fiscal Year 2012: The GreenLand Project, Maejo-Phrae University honor.
Maejo University - Phrae honor. 13 p.

1013

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

INVESTIGATING OZONE LEVELS IN MUSCAT AREA, OMAN BY
USING ARTIFICIAL NEURAL NETWORKS

1Mahad Baawain1, Hasina Al-Hinai1 and Abdullah Almamun1
Department of Civil and Architectural Engineering, Sultan Qaboos University, Oman

ABSTRACTThe economic, industrial and infrastructural developments in Muscat Governorate (Oman) has increased theemissions of some air pollutants from several sources. These air pollutants may pose adversely affect the publichealth in city through cardiorespiratory and pulmonary diseases. The effects of air pollution were not limited only
to the health effects of the exposed population but also could have detrimental effects on the quality of theecosystem, buildings and artifacts. This study aims at assessing the quality of ambient air in Muscat Governorate
by assessing the ground level ozone (O3) concentrations and its primary sources of emission. It also focuses onfinding the non-linear relationship between ozone concentrations and other pollutants concentrations (e.g. nitrogenoxides and volatile organic compounds) including meteorological parameters (e.g. temperature, atmosphericpressure, humidity, wind speed and direction). The concentrations of O3, NO2 and VOC and the metrologicalparameters were measured by mobile monitoring station in six different administrative locations in Muscat
Governorate (Al-Amerat, Al-Seeb, Al-Khuwair, Ruwi, Al-Rusayl and Mutrah). In addition, field datasets weremodeled and validated with artificial neural networks by using Python software for ozone concentration levels.
The results of the study showed that road transportation and industrial activities were the main sources of air
pollution in Muscat Governorate. It was also found that cities of Muscat were subjected to a considerable ozone
concentrations which exceeded the local standards of 120 µg/m³ occasionally.
Keywords: Ambient air quality, Modeling, Ozone, Artificial neural networks

Therefore, the applications of models and forecasting
techniques for assessing air pollution levels haveattracted attention by many air quality experts inrecent years. Many developed countries haveestablished air quality standards and guidelines forassessing the public health and ecological system [5].

INTRODUCTION
Rapid growth of Oman's population and dramaticincrease in on-road traffic emissions and industrial
activities could lead to a deterioration in the ambient
air quality especially in the capital city (Muscat). Air
pollution levels require a robust and accurate
assessment of air pollutant levels including emission
sources in order to address the current air quality levelin Muscat. The study focuses on the changes ofambient air quality in general and the changes ofozone (O3) concentration in particular. In addition,measured pollutant concentrations will be comparedwith the international standards such as WHO,
European Union and United States Environmental
Protection Agency (US EPA) standards.
Transportation is considered as one of the major
sources of air pollution [1]. In addition, theproduction and distribution activities of petroleum
fuel emits a large amount of air pollutants that form
the O3 due to accidental releases, loading andoffloading of fuel [2]. During combustion processes
transportation leads to the emission of CO, NOx, andVOC which ultimately forms the secondary air
pollutants like O3 that are associated with humanhealth risks, damage to properties and vegetation [3].
The ground or field based measurement of air
pollutants concentrations is still a major problem as it
is very laborious and expensive to conduct [4].

METHODOLOGY
The study includes data collection of ozone (O3),nitrogen oxides (NOx|) and volatile organic
compounds (VOC) in the ambient air from six
locations in Muscat over one year along withmetrological conditions. The collected data was used
to predict O3 levels using artificial neural network(ANN).
Description of the study area
Muscat Governorate is the capital city of Oman
which is characterized by high residential population
with heavy traffic density, energy intensive industries,
and constructional activities. In 2017, the city had apopulation of about 1,560,330. The city covers an
area of approximately 3,500 km2 (1,400 sq mi). It
contains six provinces (AlAmerat, Bawshar, Muscat,
Muttrah, Qurayyat and AlSeeb). It is located on
23°35'09.26" N and 58°24'21.32" E. The climate ofMuscat is semi-arid and arid. The major seasons are1014

SEE - Bangkok, Thailand, Nov.11-13, 2019

summer where average temperatures could reach as
high as 49°C and winter season with relatively lower
temperature (average 21°C). Rainfall occurs mostly
between December and April with total amount of
100 mm.

Metrological factors and air pollutants
The results from the correlation analysis areshown in Table 2. It is clearly illustrated that the O3
concentrations (g/m3) negatively correlated withNO (g/m3), NO2 (g/m3), relative humidity (RH, %),VOCs (g/m3) and wind direction (WD, degree).
While other variables (Temperature (T, °C), Pressure(P, mbar), Wind Speed (WS, m/s)) were moderately
correlated to O3.

Field measurements
The meteorological parameters (air temperature,
ambient pressure, relative humidity, wind direction
and wind speed) and air pollutants (NOX, NO, NO2,
VOC and O3) concentrations were measured with air
pointer instrument. This equipment is designed tosatisfy the European Norms and the regulations of the
US Environmental Protection Agency. Table 1 shows
the locations of the air quality monitoring sites.

Table 2 Correlation between input variables and O3
concentration for the sites*
Inputs
T
P
RH
WS
WD
NO
NO2
VOCs

Table 1 Air quality monitoring sites
Location

Longitude

Latitude

Al Amerat
AL Khwair
MuttrahAl Seeb
Ruwi
Al RysailN 23°28'.102"
N23° 35'.630"
N23°36'.915"
N 23°40'.955"
N 23°35'.645"
N 23°33'.264"

E 58°29'.412"
E58° 26'.527"
E58° 35'.367"
E 58°11'.155"
E 58°32'.636"
E 58°12'.749"

A
0.3
0.2
0.6
-0.4
-0.6
-0.7
- 0.1

B
0.3
0.2
0.2
-0.2
-0.2
-0.3
-0.1

C
0.5
0.6
-0.1
-0.1
-0.2
-0.2
-0.3

D
-0.4
-0.2
-0.2
-0.4
- 0.4

E
0.2
0.1
0.1
0.7
-0.3
-0.2
-0.2
-

F
0.8
1
-0.6
0.1
-0.6
-0.5
- 0. 5* A: AlAmerat, B: AlKhwair, C: Muttrah, D: AlSeeb, E:
Ruwi, F: AlRysail

Mean hourly O3 concentration
Artificial neural network (ANN) model
The results indicated that the maximum mean ofO3 concentrations during daylight. The mean hourly
O3 concentration was in the range of 17 to 119 µg/m³
in Al Amerat, 15 to 91 µg/m³ in Al Khwair, 60 to 105µg/m³ in Muttrah, 87 to 177 µg/m³ in Al Seeb, 29 to
116 µg/m³ in Ruwi and 50 to 179 µg/m³ in Al Rysail.
AlSeeb and Muttrah had the highest mean values
compared to other sites. This may be due to theirgeographical locations and their natural condition as
coastal areas with high humidity percentage andtraffic density.
Al Rysail is considered as an industrial area wheremost of companies are located. The industrial
activities emit different types of air pollutants withhigh concentration levels such as NOx and VOC
which can form O3. The results illustrated relatively
high mean hourly O3 concentration in AlRysail area.
However, in AlAmerat and AlKhwair, there were
big differences between the minimum and maximum
values of mean O3 concentration which may be
explained by the big difference in the range of windspeed. The wind speed ranged from 0.04 to 3 (m/s) in
AlAmerat and from 0 to 4.51 (m/s) in AlKhwair. This
could cause a dispersion and mixing of accumulated
O3 concentrations.

Six ANN models were developed to assess andpredict O3 concentration in six cities of Muscat
governorate (AlAmerat, AlSeeb, AlKhuwair, Ruwi,
AlRusayl and Muttrah). Eight variables were selected
as input parameters (NO, NO2, VOCs, temperature,pressure, relative humidity, wind direction, and windspeed) while O3 was selected as an output variable.
The architecture of ANN contains an input layer of 8
neurons, two hidden layers of 30 neurons in each one
and an output layer of one neuron as shown in Fig. 1.

Fig. 1

Architecture of ANN models

1015

SEE - Bangkok, Thailand, Nov.11-13, 2019

ANN Modeling Approach
The collected data were divided into 3 sets: training
set (70% of the data), testing test (15%) andvalidation set (15%) as shown in Table 3. The models
consisted of only completed measured data of eachhour. Any row containing missing data were entirely
deleted. The number of completed recorded data was
6273 for AlAmerat, 12717 for Muttrah, 6588 for
Ruwi, 7722 for AlSeeb, 6651 for AlKhwair and11456 for AlRysail.
Table 3The distribution of data to training,
testing and validation sets.
City

Training

Testing

Validating

AlAmerat
AlKhwair

4391
4655

941
998

941
998

Muttrah

8903

1907

1907

AlSeeb

5406

1158

1158

Ruwi

4612

988

988

AlRysail

8018

1719

1719

There were close fits between the measured andobserved values of O3 for all cities as shown in theFig. 2 to Fig. 7 which show the modeling work for all
combined sets (training, testing and validation) of
each site. The models showed very good matching
between simulated and measured O3 values in allsites. All models have shown R2 > 0.9 for training set
except Al Rysail which got R2 = 0.81, while Al Seeb
had the highest R2 of 0.997. The study have shownthat the variability of O3 concentration was greatly
influenced by the variables which were used for themodels development. After training the models, they
were tested by 15% and validated by 15% of
measured datasets. The results represented goodmodels performances where R2 were ranged between
0.70 and 0.88.
In the comparison of upper and lower peaks
values, Ruwi had the highest peaks in both predicted
and measured O3 which reached above 1000 µg/m³. It
is followed by AlRysail with upper peak values of419.3 µg/m³ for predicted O3 and 364.22 µg/m³ formeasured O3. AlRysail also shows the highest lower
peaks values for both measured and predicted O3(47.1 and 28.83 µg/m³, respectively). Muttrah had
higher O3 peaks between in February 2018 comparedwith its O3 peaks in May 2018. Al Amerat showed
223.81 µg/m³ as an upper peak for measured and217.78 µg/m³ as an upper peak for predicted O3 which
are also considerable peaks values.

1016

Fig. 2

Al Amerat ANN model.

Fig. 3

Al Khuwair ANN model.

Fig. 4Al Rysail ANN model.

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 4 illustrates the contribution percentage ofmetrological factors and air pollutants in the ANN
models. The summation of metrological factors
contribution percentage ranged between 31% and
63% where Ruwi had the highest percentage. In
contrast, the summation of air pollutants (NO, NO2
and VOC) contribution percentage ranged between
37% and 69% where Al Amerat had the highest
percentage.
Table 4City

Fig. 5

AlAmerat
AlKhwairMuttrah
AlSeebRuwi
AlRysail

Mattrah ANN model.

Contribution percentages of input data
Contribution Percentage (%)
Air PollutantsMeteorological(NO,NO2,VOC)
Factors
68.9
31.1
45.0
55.0
54.0
46.0
44.7
55.3
36.8
63.2
55.7
44.3

CONCLUSIONS

Fig. 6

Al Seeb ANN model.

Fig. 7

Ruwi ANN model.

The emission of O3 from road transportation andindustrial sectors has received a serious attention
from government and the scientific communities as it
may cause considerable effects to the public healthand environment. The O3 levels in Muscat wereassessed through application of ANN models in six
sites. The O3 concentration was predicted talking into
consideration the metrological parameters and the O3
precursors (NOx and VOCs) concentrations.
The obtained results showed that O3 levels
exceeded the 120 µg/m³ (maximum level set by
Ministry of Environmental and Climate Affairs) in allareas at different times of the days. The most affectedarea was Ruwi which had O3 concentration 10 times
compared to the recommended standard (1162.27µg/m³ as measured O3 concentration and 1171.6µg/m³ as predicted O3 concentration).
The obtained results showed strong relationshipbetween O3 and input parameters (NOx, VOC andmeteorological). There were closed fit between themeasured O3 and the predicted O3 from theseparameters which indicated the dependency of O3
concentration on these parameter. The negative
correlation between O3 and NOx and VOCs haveshown that these pollutants are the precursors of O 3.
It should be noted that the difference among O3
concentration between cities may be due to theirdifferences in geographical locations, the time
periods of O3 measurements (summer and winter), thepresence of industrial areas, the number of vehicles
and the presence of green vegetation.

1017

SEE - Bangkok, Thailand, Nov.11-13, 2019[3] Alimissis A., Philippopoulos K., Tzanis C.G., andDeligiorgi D., Spatial Estimation of Urban Air
Pollution with the use of Artificial Neural
Network Models. Atmos. Environ., Vol. 191,
2018, pp. 205–213.
[4] Bowman K.W., Toward the Next Generation of
Air Quality Monitoring: Ozone. Atmos. Environ.,Vol. 80, 2013, pp. 571–583.
[5] Li R., Dong Y., Zhu Z., Li C., and Yang H., A
Dynamic Evaluation Framework for Ambient Air
Pollution Monitoring. Appl. Math. Model., Vol.
65, 2019, pp. 52–71.

REFERENCES[1] Kinnon M. M., Zhu S., Carreras-Sospedra M.,
Soukup J.V., Dabdub D., Samuelsen G.S., andBrouwer J., Considering Future Regional Air
Quality Impacts of the Transportation Sector.
Energy Policy, Vol. 124, 2019, pp. 63–80.
[2] Vijayaraghavan K., Cho S., Morris R., Spink D.,
Jung J., Pauls R., and Duffett K., Photochemical
Model Evaluation of the Ground-Level Ozone
Impacts on Ambient Air Quality and Vegetation
Health in the Alberta Oil Sands Region: Using
Present and Future Emission Scenarios. Atmos.
Environ., Vol. 141, 2016, pp. 209–218.

1018

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STUDY ON MUSRENBANG MECHANISM IN INDONESIA TO
PROMOTE SANITATION
Eddy Soedjono1 , Wahyu Wijaya2 and Nurina Fitriani3*
1,2
Environmental Engineering Department
Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
3
Study Program of Environmental Engineering, Department of Biology, Universitas Airlangga, Surabaya,
Indonesia
ABSTRACT
Development in Indonesia is conducted both ways using top-down and bottom-up approach. A top-down
approach is a kind of national development program from the central government to the lowest level of local
government like desa or kelurahan. Musrenbangdes is a way to get feedback right from the grassroot for theCentral Government. The aim of this research is to study on the musrenbang mechanism for sanitation. This study
was conducted in the province of Bali, Jawa Timur (East Java), and Kalimantan Tengah (Central Kalimantan).
Bali was selected to represent best sanitation program in Indonesia, while Kalimantan Tengah was selected torepresent poor sanitation program. Jawa Timur is a mediocre province which can be easily assessed as ITS issurely in East Java. The selected districts in Bali, Jawa Timur, and Kalimantan Tengah are Karangasem,
Bojonegoro, and Katingan. Musrenbang was mostly a male dominated forum. Although in Karangasem, Bali themusrenbang was conducted at day time, but still the participants were dominated by men. The musrenbang alone
was conducted at night time during weekend. Women were not considered polite to go out at night to join theMusrenbang. Either it is good or poor it is not because of Musrenbang but it is caused by other mechanisms.
However, it may be more formal in Bali, although the involvement of women were not that strong. Musrenbang
was conducted at morning time which mean musrenbang is treated as formal as even compared in Kalimantan
Tengah and Jawa Timur.
Keywords: Musrenbang, Sanitation, Women attendance, Wastewater treatment

budget allocation or Anggaran Dana Desa).
Musrenbang mechanism is shown in Figure 1.
Musrenbang functions as a forum to produce
agreement between development actors regarding
the design of the RKP and the draft RKPD, which
focuses on the discussion to synchronize work plansbetween ministries / institutions / units work ofregional apparatus and between the Government, theGovernment Regions and communities in achieving
development goals national and regional [3]. Society
always involved in the policy making process
produced by the government. This causes every
policy produced by the government has big
implications for the community [4].
Musrenbang is divided into 3 stages: premusrenbang, musrenbang, and post-musrenbang.
Musrenbang must prioritize discussion on basic
human rights like health, education, sanitation, job
opportunities, and feeling secure. On practice,musrenbang is for beyond rich experience nor
aspirative forum. It is more to an annual ritualdevelopment process with poor content and even isirrelevant for women and poor people. According toMusrenbang Guidance, the gathering must be
attended by at least by 30% women and poor
communities. Representatives from village must

INTRODUCTION
Top-down approach is national development
mechanism following the long term development
planning or Rencana Pembangunan Jangka Panjang(RPJP) at national level down to the Rencana
Pembangunan Jangka Menengah Daerah (RPJMD)
or Village Medium Development Plant at village
level [1]. Musrenbang (musyarawah perencanaan
pembangunan) or development planning forum is
an official development process which implements
the principle of bottom-up approach. This type ofdevelopment approach could be merely used inIndonesia. This annual forum starts in January toapprove next year work plan (RKP or Rencana Kerja
Pembangunan) for musrenbangdes or musrenbang
kelurahan (village musrenbang). Annual RKP is
detail of the village five year medium development
plan (RPJM Desa or Rencana Pembangunan Jangka
Menengah Desa). In order to educate any citizen to
actively involved in development governance, theMusrenbang was held to facilitate them withparticipatory and dialogical forum [2]. Some output
for musrenbangdes would be list of village
development priorities and use of ADD (village

1019

SEE - Bangkok, Thailand, Nov.11-13, 2019

comprise of at least 1 woman if there are 3 membersor 2 women if 5 members. Community participation
is influenced by interested parties and have an
influence on the program. In this case, for theguidance and provision of information to the public,
the role of the government and the private sector isneeded [5].
Three provinces were selected to get to knowwhether Musrenbang was related to sanitation
promotion. Bali was selected to represent goodsanitation program while Kalimantan Tengah wasselected to represent poor sanitation program. Jawa
Timur was also assessed as it was mediocre andlocated where the ITS was around. Overall, thesanitation condition in Indonesia is as shown in
Figure 2a and 2b. The objective of this study is toaccess the impact of musrenbang mechanism topromote sanitation in order to achieve open
defecation free (ODF) target of GOI (Governmentof Indonesia) universal access by 2019.

Fig. 1 Musrenbang mechanism

Fig. 2a Sanitation condition based on ODF achievement rank in Indonesia by 2017

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 2b Sanitation condition based on progress in Indonesia by 2017consisted of 8 sub-districts. Muntigunung Village aspart of Kubu Sub-district was selected as case study
area. Karangasem had a lot number of poor people
and lacking of decent housing [6]. One problem thatwas still exist in Karangasem was the availability ofclean water in several sub-district areas. From 78
sub-districts in Karangasem district, there are 19
sub-districts that have not been served clean waterby the PDAM (Perusahaan Daerah Air Minum)
Karangasem district [7]. In the field of sanitation,
Karangasem had communal wastewater treatment insome areas. In collaboration with Karangasem
BAPPEDA, local government made campaign in all
districts in term of sanitation practice. Regular social
gathering with latrine as the subject was regularly
held by the local community. This agenda belonged
to the Community Based Total Sanitation (STBM)
which was regulated by Health Ministry. In thiscase, the local government had a role as facilitator.
STBM in Karangasem District was held in 52
villages and resulted of 180 ODF households. The
implementation of sanitation program in
Karangasem was the result of collaboration between
sanitation working group, public health office, andlocal community. Musrenbang practice in
Karangasem was then followed by Kubu andTianyar Barat as representative of sub-district andvillage level, respectively.
Beginning with Musrenbang forum at village
level, there were many sanitation programs
proposed to the sub-district level. This forum wasattended by representative of related institutions,
local communities, and community leaders.
Musrenbangdes was conducted at day time during
working hour. Musrenbang was mainly attended by

MATERIALS AND METHOD
Feed-back for the Musrenbang was conducted
through interview and focus group discussion(FGD). The selected districts at Bali, Jawa Timur,dan Kalimantan Tengah were subsequently
Karangasem, Bojonegoro, dan Katingan. Interview
and FGD were conducted to follow the Musrenbang
guidance started from the village level, then to SubDistrik, Distrik, than the Provincial level. As
Musrenbang Forum was not coincide with theinterview and FGD, then Musrenbang Forum could
not be attended and the condition during thediscussion was asked in the interview or FGD. Theinterview and FGD was basically around how
Musrenbang was conducted in the three selecteddistricts. Important information that was asked were:when the Musrenbang was conducted, was it
attended by women, and was sanitation discussed
during the Musrenbang.
RESULTS AND DISCUSSION
Musrenbang visits have been conducted at
Karangasem District of Bali Province, Bojonegoro
District of Jawa Timur, and Katingan District ofKalimantan Tengah. The musrenbang visits weredone from the lowest level of local government orvillage up to the highest level which were provinces.
These results are below.
Musrenbang at Karangasem District, Bali
The province of Bali consisted of 8 districts and1 city. Karangasem District as one of the district
1021

SEE - Bangkok, Thailand, Nov.11-13, 2019men where sanitation was hardly ever discussed in
the forum. Tianyar Barat was selected as
representative of village level in Musrenbang
practice. Some households in Tianyar Barat had
private latrine in their house. Health Department of
Karangasem Regency stated that the use of latrine inTianyar Barat reached 57,7%. Currently, Tianyar
Barat had sanitation committee with the objectivesof sanitation planning although they were not
optimal yet. Several sanitation programs have been
proposed in the Musrenbang forum in Tianyar Barat,such as latrine provision and sanitation counselling.
The programs, however, have not been in priority ascompared with road construction, house reparation,
and water supply. Low level of knowledge of thecommunity caused sanitation was not an urgent
issue.
Musrenbang in Kubu Sub-District was held
annualy in February as continuation of theMusrenbang in Tianyar Barat as lowest level. Kubu
Sub-District is divided into 4 villages (Ban, Tianyar,
Tianyar Barat, Tianyar Tengah). Musrenbang forum
was attended by all village chiefs, community, andrelated institutions. Musrenbang in sub-district level
was a forum to accommodate proposed programsfrom each village and ranked based on priority scale.
Those proposed programs could not be funded byvillage government would be funded by higher levelof government. In arranging scale priority, themeeting was divided into 3 groups to discuss
economic, public facility, and environment healthand culture. All about this proposals would be
discussed in district musrenbang to make bigger
priority programs from different sub-district. As theresults, each programs would be ranked based on theurgency and budgeting. The feedback from district
musrenbang wuld be given to all sub-districts andvillages as confirmation.

Women were not considered polite to attend meeting
during night-time. Musrenbangdes was attended by
local government, local public figures, religious
figure, and the representative of farmer community,
fisherman community, woman community, children
protection community, environment community andpoor people community. There was some triggering
practice from the local government and healthservice (midwife) regarding sanitation. This
regularly practice has encouraged sanitation
proposed programs. The village government would
provide subsidies to latrine installment for poor
community; they had to make a statement letter
about their willingness to have and use latrines.
Musrenbang in regional level generally was heldin April and attended by government, private sector
representatives, society, and even students ofuniversities. The forum of regional level would be
plenary session I, group session, and plenary session
II. Those session aimed to align the needs of each
community with the government work plan. In
terms of sanitation development plan, the discussion
carried out as follows:a. Aspirations from the community fromperiodical discussion held by the related
institutions,b. Sanitation development plan confirmed by
Bupati (head of the district) or Mayors,c. Third party involvement in form ofCorporate Social Responsibility (CSR)
especially in sanitation development,d. Collaboration of many institutions insanitation development plan, such as healthagency, public works, environmental
agency, and others,
Generally, the group plenary was divided into 4
main fields namely economic (group I),
infrastructure and regional development (group II),
government, social, statistic and reporting (group
III), and Non-Government Financing (group IV).
The group plenary would be conducted by chairman
and moderator. The group plenary included theexposure of RKPD draft by each chairman in orderto get responses and clarification from all of theparticipant. Then representative of each groups
joined the plenary session II. In this session, each
representative presented the results of groupplenary. The summary of plenary session was
included to the agreement of result of Musrenbang.
The results of Musrenbang in regional level
involved some appropriate programs and financed
by Regional APBD.

Musrenbang at Bojonegoro District, Jawa Timur
The province of Jawa Timur consisted of 29
districts and another 9 cities. Bojonegoro District
consisted of 12 sub-districts. Pagerwesi Village aspart of Trucuk Sub-district was selected as casestudy area. The pre-musrenbang or agencies/SKPD
musrenbang was coordinated by Badan Koordinator
Wilayah (Bakorwil; a kind of Provincial Office
Representative) of Jawa Timur Province. This was
based on Provincial Regulation
regardingGovernance and Responsibility of Bakorwil [8].
Main function of Bakorwil was to arrange technicalpolicy to support the regional administration anddevelopment. On this forum, all related SKPD andrepresentatives of each district were to discuss andbargain the proposed programs for priorities.
Musrenbangdes was generally conducted atnight time and mostly during weekends.
Musrenbang was mainly attended by men whichsanitation were almost not discussed in the forum.

Musrenbang at Katingan District, Kalimantan
TengahThe province of Kalimantan Tengah consisted of
13 districts and 1 city. Katingan District as one ofthe districts consisted of 7 sub-districts. Kalimantan
1022

SEE - Bangkok, Thailand, Nov.11-13, 2019

Tengah Province became representative of worst
sanitation case in this research. According tonational sanitation index, Kalimantan Tengah
placed on rank 24 of 34 provinces in Indonesia.
According to the data of latrine and wastewater
treatment utilization, the ownership and coverage
were very low. It was only 10,7% of ODF had beenachieved in 2014. As onsite system for wastewater
treatment, about 86,7% of community still used unstandard septic tank; only 2,2% was standard septic
tank. The provision of sanitation facilities in
Katingan District was still limited. There was nowastewater treatment plants nor fecal sludge
processing facility yet. Open defecation still
happened particularly for communities who lived
along the river. Open defecation became habit of thecommunities which was coupled with having toilets
above the river directly [9]. Most challenge ofsanitation development in Katingan was to increase
the environmental awareness [10]. Government
support in providing proper sanitation system would
be recommended.
A different case arose in Kalimantan Tengah
Province in term of sanitation development, i.e.:
little number of proposed program in sanitation ofmusrenbangdes. This was to indicate that sanitation
was still not an urgent issue. Musrenbang was
mainly attended by men which sanitation were
almost not discussed in the forum. Most issues
mostly involved in the proposed program were roadand bridge construction, housing improvement, andwater supply. Katingan had already Environmental
Health Risk Assessment (EHRA) study andMemorandum Program for Sanitation (MPS) whichbecame the guideline for sanitation development. As
the same case with Tianyar Barat, Kalimantan
Tengah had also sanitation work group (POKJA
Sanitasi) in provincial level although the group was
not active yet.

REFERENCE[1] Undang-Undang Nomor 25 Tahun 2004
tentang Sistem Perencanaan Pembangunan
Nasional.
[2] Soedjono, E.S., Fitriani, N., Rahman, R.,
Wijaya, I., M., W. 2017. Achieving Water
Sensitive City Concept Through Musrenbang
Mechanism in Surabaya City, Indonesia.
International Journal of Geomate, 15 (49), 9297.
DOI:
https://doi.org/10.21660/2018.49.3649.
[3] Petunjuk
TeknisPenyelenggaraan
Musrenbang (PTPM) Tahun 2006.
[4] Azhar, F. 2015. Partisipasi Masyarakat Dalam
Musyawarah Perencanaan Pembangunan(MUSRENBANG) di Kelurahan Pegirian
Kecamatan Semampir Kota Surabaya, Jurnal
Kebijakan dan Manajemen Publik 3(2): ISSN
2303-341X.
[5] Gedeona, A. B. 2014. Partisipasi Masyarakat
Dalam
Musyawarah
Perencanaan
Pembangunan
Kecamatan
Larantuka
Kabupaten Flores Timur, Jurnal Administrasi
Publik dan Birokrasi 1(3).
[6] Badan Pusat Statistik Kabupaten Karangasem,
2015, Kabupaten Karangasem Dalam Angka
2015, report.
[7] Perda Kab. Karangasem No. 9 Thn. 2011.
Rencana Pembangunan Jangka Menengah
Daerah (RPJMD) Kabupaten Karangasem
Tahun 2010-2015. Perda Kab. Karangasem,
Karangasem.
[8] Peraturan Daerah Provinsi Jawa Timur No 12
Tahun 2008 Tentang Organisasi dan Tatakerja
Badan Koordinasi Wilayah Pemerintahan dan
Pembangunan Jawa Timur.
[9] Dahal, K. R., Adhikari, B., Tamang, J. 2014.
Sanitation Coverage and Impact of OpenDefecation Free (ODF) Zone with Special
Reference to Nepal. A Review, International
Journal of Engineering Research andApplication 4(8): 118-128.
[10] Manullang, Z. D. 2014. Evaluasi Dampak
Program Sanitasi Berbasis Masyarakat(SANIMAS)
Dalam
Pemberdayaan
Masyarakat (Studi di Kelurahan Bagan Deli
Kecamatan Medan Belawan Kota Medan):
Master’s Thesis, Medan Universitas Sumatera
Utara.

CONCLUSION
Village musrenbang (musrenbangdes) at
Muntigunung Village of Bali was conducted moreformal as compared to other villages in Jawa Timurand Kalimantan Tengah. Musrenbang was done
during working hours as compared to Jawa Timur
which was conducted during night time and evenduring weekends. The participants of musrenbang,
however, it was a male dominated forum in all
musrenbangdes. Furthermore, sanitation and watersupply as one of basic human rights, were notdiscussed in the forum. This also concluded that
good or poor provincial sanitation condition was notaffected by musrenbang.

1023

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE IMPACT OF EXPOSURE TO AEROSOL MOSQUITOESREPELLENT RELATED TO FREE RADICALS ON THE ORGANS
OF MALE RATS
Unggul P. Juswono1, Arinto Y. P. Wardoyo 1, Chomsin S. Widodo1, Johan A. E. Noor1, and Didik R. Santoso1
1
Mathematics and Natural Sciences Faculty, University of Brawijaya, Indonesia

ABSTRACT
From year to year, human activities using chemical substances lead to pollute ambient air and affect humanhealth. This pollutant can pass through the respiratory system and disrupts the organ function, including lung,
liver, blood, and kidney. It can be identified by the deformation found in the structure and function change of therelated cells in these organs and the existence of free radical. On the other hand, each substance has a different
composition and health effect. The possibility of the free radical type that is formed is also different and related
to the substance. According to this background, it a need to determine the presence of free radicals in the rat’sorgans exposed to one push aerosol mosquito repellents as the substance. This study aimed to investigate the free
radicals on the rat’s organs due to the exposure to aerosol mosquito repellent and its relation with the organ
damage of cell deformation. This study used male rats as the experimental animals that were divided into control
and treatment groups. The study included two types of repellents, Type-A (25% of aerosol concentration) andType-B (21.3% of aerosol concentration). Free radicals were detected using an electron spin resonance device.
The results showed that the cell deformation due to the exposure of one push aerosol was different for eachorgan. The deformation levels were about 36% to 74% that depended on the aerosol concentration. The exposed
aerosol generated anion superoxide (O2-) and singlet oxygen radicals (1O2) as the free radicals found in theobserved organs.
Keywords: Aerosol; Free radical; Organ damage; Pollutant; Rat.
INTRODUCTION
Indonesia is a big country that has a tropicalclimate, where the tropical climate is very suitable
for the breeding process of insects, especiallymosquitoes. Mosquitoes themselves can cause
various diseases. That is why it needs some efforts
to overcome the increasing number of diseases
caused by mosquitoes.
Eradication of mosquitoes tends to be carried out
using free-selling insecticides. The effort toeradicate mosquitoes by using insecticides is only atemporary thing and has no preventive effects for alonger period. Insecticides that are widely used by
the community can have a negative impact on theenvironment and humans due to the dangerous
chemical compounds contained in the insecticide.
One push aerosol mosquito repellent is one of thesubstances that are often used in Indonesia,
especially in daily life due to its practice use
compared to another insecticide. However, the usageof this mosquito repellent is growing from time totime. As a consequent, it also contributes to apollutant in the ambient air. It contains transfluthrin,
as an insecticide ingredient.
In the human body, transfluthrin tends to bereactive because it has unpaired electrons [1]. Theseelectrons come from oxygen atoms in transfluthrin
in cyclic rings, as a result of their reaction to themono oxidase acid (H+) enzyme [2]. These unpaired
electrons will look for pairs from other parts of thecell [3]. Transfluthrin which enters the body may
trigger the formation of free radicals.
Free radicals are atoms, elements, compounds, ormolecules that have one or more unpaired electrons
in their outer orbitals [4]. These unpaired electrons
are very reactive and tend to look for pairs byattacking and binding electrons to stable moleculesaround them [5–7]. The mechanism or process offree radical formation has several stages. The stagesof free radical formation are initiation (initialformation of free radicals), propagation (propagationor new radical formation), and termination(destruction or conversion into stable and unreactive
free radicals) [3]. The impact of free radicals on
cells is the disruption of cell function or treating
abnormal cell function [8]. Disorders of cell function
consist of short-age cells characterized by wrinkled
skin, premature aging, and degenerative diseases.
The body's defense system is reduced so that the
body becomes weak and easily injured [9].
Abnormal reactions from cells can grow new cells
that trigger tumor cell growth and cancer [10,11].
According to this background, it is urgently
required to identify free radicals generation in the
body related to the use of one push aerosol mosquito
repellent. Thus, the purpose of this study was to
identify the types of free radicals in rat’s organs that1024

SEE - Bangkok, Thailand, Nov.11-13, 2019were exposed to one push aerosol mosquito
repellent. This study also investigated the influenceof different transfluthrin concentrations on the free
radical existence, so that an alternative step can besought to deal with further organ damage.

B with five times sprays. These treatments weredone in a similar time and controlled room
temperature. These treatments were conducted fortwenty minutes per day within 30 consecutive days.
Organs Preparation

MATERIALS AND METHODS
Experimental Animals
This study used healthy male Wistar rats with theage of 2-3 months old (with 23-30 grams of BW(body weight)). The rats were treated humanely andfeed with food and water ad libitum and kept incontrolled animal cages (temperature: 24 - 27oC,
relative humidity: 75 – 78%) with 12 h dark/ lightcycle [12]. All of them (n = 21) were acclimatized in
an experimental chamber (20 x 20 x 30 cm3) for
three consecutive days before being divided
randomly into two treatment groups (Group-A andGroup-B) and one control group (Group-C). The rats
in each treatment group received similar treatment
related to the transfluthrin concentration (n = 7 pergroup, Table 1). All procedures were in accordancewith the Animal Care and Use Committee ofBrawijaya University, Malang, East Java, Indonesia(Ethical Clearance Number: 541-KEP-UB).
Table 1 Scheme of the experimental animals used in
the study (n = 21)
GroupsNumberof Sprays

Rats

Group-A

5 sprays

7Group-B

5 sprays

7Group-C-

7

Transfluthrin
Type
Type-A(25% oftransfluthrin)
Type-B(21.3%
transfluthrin)-

Transfluthrin Content
This study used two different one push aerosol
mosquito repellents. They were Type-A and Type-B
mosquito repellents with different transfluthrin
concentrations. Type-A and Type-B mosquito
repellent had 25% and 21.3% of transfluthrin
concentrations, respectively.

After exposure procedures, all rats weresacrificed by cervical dislocation. The kidneys,
livers, and lungs (organ samples) were cleaned using
NaCl (0.9%) and were fixed in buffered formalin(10%) for a week before being dehydrated in
upgraded ethanol series. After that, they were
processed to the paraffinization and cutting, thencolored using hematoxylin and eosin. For the blood
samples, the blood smears on the object glass were
fixed with methanol solution (70%) and dried. After
that, these samples were colored using Giemsa andbuffer pro-Giemsa solution. All resulted samples
were observed under a microscope (400x of
magnification) to investigate the level of cell
physical damages (blind counting method) [12–14].
Free Radicals Investigation
The presence of free radicals in the samples was
detected using ESR (Electron Spin Resonance,
Fig.1). The sample was placed in a magnetic fieldand given interference with electromagnetic waves
in radio frequency f. The magnitude of the magnetic
field given depending on the amount of electric
current I flowing in the Helmholtz coil and could be
calculated using Eq. (1) below.
(1)
where,
μ0 :
B :
I :

1.2566 x 10-6 (T.m/A)
external magnetic field (T)current on the Helmholtz coil (A)The number of turns of Helmholtz coil wasinterpreted as n (n = 320 coils), with the radius (r) of
6.8 cm.
The type of the detected free radicals isdetermined using Lande factor (g factor) calculation,
as expressed in Eq. (2).
(2)

Animal Treatments
According to Table 1, Group A was a group ofrats exposed to one push aerosol Type-A mosquito
repellent as much as five sprays. Group B was agroup of rats which were exposed to one push Type-where,
μB :
h :
f :
1025

Bohr magneton (9.273 x 10-24 J/T)
Planck constant (6.625 x 10-34 Js)
resonance frequency (Hz)SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 Values of g factor of singlet oxygen andsuperoxide free radicals
Free Radical Name
1

O2
O2Fe3+MnO2FeS
Hydroperoxide
CO2Cu
SO4Hydroxyl
CO2
AlkoxylHeliumMethanol
Alkyl
Hydrogen
Methil
DPPH
SO3EthylC
PeroxyCuOx
CuGeO3YBa2Cu3O7
Cu-HA
Hg

g Factor Value
1.501
1.501 - 1.750
1.77
1.83671.86
1.98961.996
1.997
1.99762.000472.00072.00160 - 2.00197
2.002
2.00205
2.00206
2.00232
2.00255 – 2.00286
2.00362.00372.00442.00505 – 2.00548
2.0155 – 2.0265
2.098
2.154
2.24
2.289
4.0 – 4.5

According to Eq.(2), f was determined from theexistence of RF wave resonance. This wave
resonance was identified by forming a V-shaped
curve on the oscilloscope. This curve was a
combination of two RF waves with a phasedifference of 135º (Lissajous curve).

Statistical Analysis
The resulted values were shown as mean ± SEM(standard of means). All statistical analysis was
performed using Microsoft Excel 2016.
RESULTS AND DISCUSSIONESR Calibration
For a better result, a DPPH calibrator (DPPH
radical is a stable free radical) was used to calibrate
ESR [15]. The resulted g factor was compared to theliterature. Table 3 below shows the result of thecalibration using DPPH. According to thecalibration, the resulted calibration factor was
0.9964. The V-shaped curve (RF wave resonance)
and a Lissajous curve are shown in Fig.2-Fig.3.
Table 3 Result of ESR calibration using DPPH
f (MHz)

I (A)

23.7

0.199

g Factor(literature)
2.0036g Factor(calibration)
2.0109Fig. 2

DPPH resonance curve.

Fig. 3

The Lissajous curves for (a) research tube;(b) control group; and (c) treatment group.

Formed Free Radicals
Fig. 1The set up of Leybold-Heracus ESR
devices, where: 1). radio frequency control
unit; 2). ESR control unit; 3) oscilloscope;4). multimeter; 5). sample place; and 6).
Helmholtz coil.

The exposure to one push aerosol mosquito
repellents (Type-A and Type-B) had a direct impact
in rat’s organs. According to ESR analysis, theexposure treatments generated some free radicals
1026

SEE - Bangkok, Thailand, Nov.11-13, 2019with similar g factor value (Table 4). The presencesof O2- (superoxide) and 1O2 (singlet oxygen) in rat’sorgans indicate the form of ROS (reactive oxygen
species) [9,16,17]. ROS in the rat’s organs can beused to predict the presence of oxidative stress incells, showing the inability of cells in overcoming
the excess amount of free radicals.
Based on the results, the level of organ damage
varies. The most damage organ is the lung cells(alveolar cells, 74-78%), where Type-B with lesser
transfluthrin concentration has 74% of cell physicaldamage. Liver cells (hepatocytes) has 36% and 40%of cell physical damages, respectively for Type-A
and Type-B, having the least impact of transfluthrin
exposure. According to these results (see Table 4),
we can see that the cell physical damages and free
radical generation is directly correlated with thedifferent concentration of the exposed transfluthrin.
As an active substance, transfluthrin belongs to thepyrethroid group. According to the previous study,
pyrethroids have low toxicity that is safe to use in

humans. Occasionally, the pyrethroid group can be
categorized to toxin when the level of depositedpyrethroid exceeds the normal dose. As an impact, if
toxin enters the body continuously, it may
accumulate and may cause damage to the organ due
to the free radicals.
In the human body, free radical is generated
during normal cellular metabolism [15]. Besides, thehuman body has its antioxidant defense mechanisms
to equilibrate the free radicals formations [9,17].
However, any disruption in this mechanism may
disturb the equilibrium in the body resulting inoxidative stress, including cell deformation or cell
physical damage [18].
The mechanism of cell damage due totransfluthrin begins when transfluthrin attaches tothe cell membrane. When transfluthrin is inhaled by
the respiratory organ, it may follow the bloodstream,passes through the lungs.

Table 4 The detected free radicals in rat’s organ exposed to one push aerosol mosquito repellents

OrgansLiver

Kidney

Blood

Lung

g Factor
1.560
1.526
1.518
1.492
1.560
1.568
1.542
1.466
1.483
1.509
1.545
1.577
1.628
1.550
1.557
1.535
1.576

Type-AFree
RadicalsO2O2O21O2
O2O2O21
O2
1
O2
O2O2O2O2O2O2O2O2-

Cell PhysicalDamage (%)

1.500
1.490
1.517
1.593
1.560
1.576
1.584
1.474
1.483
1.509
1.526
1.560
1.577
1.507
1.517
1.508
1.543

40±3

47±3

71±3

74±4

Besides, the function of normal blood related tothe hemoglobin as an oxygen binder may be
disrupted. Hemoglobin may tend to bindtransfluthrin rather than oxygen to be circulated
throughout the body and becomes a toxin in the
body. This process then triggers other disruptions,
including the bad impacts of nutrients, fats,hormones, and proteins. Moreover, pyrethroid canmanifold cypermethrin and fenvalerate, resulting inoxidative stress and changes in antioxidant enzymes[19]. They have a high potential to interfere withnerve activity, membrane depolarization, andsynaptic disorders [20]. They then may trigger theg Factor

Type-BFree
Radicals
1O2
1O2
O2O2O2O2O21
O2
1O2
O2O2O2O2O2O2O2O2-

Cell PhysicalDamage (%)
36±3

49±3

72±4

72±4

formation of free radical. This free radical formation(singlet oxygen) process occurs during the processof oxidative metabolism where there is an electron
leak that can form O2- [3,21]. The entry oftransfluthrin as toxins into cells may trigger
mitochondria to produce more O2- (Fig.4).

1027

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 4Singlet oxygen electron configuration [22].

The main formation of ROS (reactive oxygen
species) such as superoxide occurs in the
mitochondria through the interaction of O2 with
Coenzyme Q (KoQ) [23]. Some electrons movingfrom NADH and other compounds to O2 may passwhen KoQH interacts with O2 and form superoxide
radicals [24]. Moreover, mitochondria also containhigh SOD (superoxide dismutase) and glutathione[25]. Dismutase is determined as the main defense
against oxidative stress that occurs in the body, inwhich it is triggered by chemical enzyme induction
or conditions that increase superoxide formation[25].
CONCLUSIONS
Exposure to transfluthrin contained in one pushaerosol mosquito repellents on rats has an influenceon the existence of the free radical on the rat’sorgans. They are detected as superoxide anions (gfactor 1.501 - 1.750, O2-) and singlet oxygen (gfactor 1.501, 1O2), in which generating 36% to 74%
of cell deformation levels (depending on thetransfluthrin concentration and rat’s organs). The
forming process of free radicals likely takes apartduring the oxidative metabolic process where there
is an electron leak that can form O2-. The entry oftransfluthrin into cells can trigger mitochondria to
produce more 1O2.
ACKNOWLEDGMENTS
The author’s team acknowledge all members of
the Laboratory of Advanced Physics and Biophysics,
Physics Department, Brawijaya University (Malangcity, East Java province, Indonesia), for their
excellent hands and efforts during the experiment.
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[23] Zabik N.L., Anwar S., Ziu I., and Martic-milneS., Electrochemical reactivity of bulky-phenols
with superoxide anion radical, Electrochim.
Acta., Vol. 296, 2019, pp. 174–180.
[24] Min D.B. and Boff J.M., Chemistry andreaction of singlet oxygen in foods, Compr.
Rev. Food Sci. Food Saf., Vol. 1, 2002, pp. 58–
72.
[25] Li R., Zhou X., Liu D., and Feng W.,
Enhancing the activity and stability of Mnsuperoxide dismutase by one-by- one ligation
to catalase, Free Radic. Biol. Med., Vol. 129,2018, 138–145.

1029

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

VARIATIONS IN WATER QUALITY ALONG ACIDIC RIVERS IN
VOLCANIC AREAS OF EASTERN JAPANTakeshi Saito1 and Naoki Watanabe2
Graduate School of Science and Engineering, Saitama University, Japan;
2
Research Institute for Natural Hazards and Disaster Recovery, Niigata University, Japan
1

ABSTRACT
There are many acidic rivers in Japan, caused by acidic drainage from mines and hot springs. Low pH values
and relatively high concentrations of harmful heavy metals and other toxic elements are often detected in theacidic rivers. In this study, water quality parameters such as pH and concentrations of heavy metals and otherelements were investigated in seven representative acidic river basins located in volcanic areas in the Easternpart of Japan. Generally, the lowest pH values were ranged from 1.31 to 5.64. As an example of the positiveeffects of neutralization treatment, pH values markedly increased and concentrations of As, Pb, Fe, and Al
dramatically decreased and reached acceptable values after treatment in the Agatsuma river basin. Opposite in
the Nagase river basin, being an example of no specific treatment applied, the pH values gradually increased andconcentrations of As, Pb, Fe, and Al steadily decreased along (downstream) the river, mainly due to the dilution
effect by the inflow from other rivers. In both acidic river basins, harmful heavy metals such as As and Pb were
probably coprecipitated with Fe and Al hydroxides. The sediments deposited in the Nagase river bed may
therefore contain much higher concentrations of harmful heavy metals including As and Pb as previously
reported in the Shinaki dam of the Agatsuma river basin.
Keywords: Water quality, pH, Heavy metals, Acidic rivers, Eastern part of Japan

treatment must be continuously applied [8]. Since
the limestone as one of the most common
neutralizers is a natural and scarce resource, it ishighly important to reduce the usage for achieving
the recycle-based society. Therefore, alternative
neutralizers which have low cost and highly efficientneutralization capacity are needed to be developed.
In this study, water quality parameters including
pH and concentrations of heavy metals and otherelements were investigated in seven representative
acidic river basins located in volcanic areas in the
Eastern part of Japan. The expected outcomes fromthis study will provide fundamental and important
knowledges for developing the alternative
neutralizers.

INTRODUCTION
Acid mine drainage is one of the most serious
environmental issues, resulting in the discharge of
the water with low pH values and relatively highconcentrations of harmful heavy metals and othertoxic elements. The drainage is naturally produced,
typically from the oxidation of sulfide minerals suchas pyrite reacted with air and water. The mining
activities can highly accelerate the amount of thedischarge by an increase in possibility for sulfide
mineral oxidation [1]-[5].
Especially, in Japan, there are many acidic hot
springs associated with volcanic activities. The
drainage from acidic hot springs also shows low pH
values and relatively high concentrations of harmful
heavy metals such as As (arsenic) and Pb (lead). The
acidic drainage produced from mines and hot springs
discharges into rivers causing the acidic rivers.
For example, the acidic water significantly
affects the degradation of infrastructures mainlycomposed of concrete and iron materials in therivers. Also, there are possible negative risks for thebiosphere in the acidic river basins. In some ofacidic rivers in Japan, the neutralization treatmentusing limestone mainly consisting of calcium
carbonate (CaCO3) is applied to reduce the acidity
and concentrations of harmful heavy metals andother toxic elements [6], [7]. The problem applying
the neutralization treatment is high cost because the

MATERIALS AND METHOD
Water quality investigation was carried out inseven acidic river basins, Urakawa (Nagano
Prefecture), Iougawa (Niigata Prefecture), Nagase(Fukushima Prefecture), Agatsuma(GunmaPrefecture), Sukawa (Yamagata Prefecture),
Tamagawa (Akita Prefecture), and Matsukawa(Iwate Prefecture) river basins all in volcanic areasin the Eastern part of Japan (Figs. 1 and 2). In allseven river basins, totally more than 70 water
sampling points were selected.

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SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 1(August 2018), and 1.93 (May 2019) in the upstream
parts of the Urakawa, Iougawa, and Sukawa river
basins, respectively. Also, very low pH values of
1.66 (July 2017), 1.82 (June 2017), 1.31 (July 2018),
and 3.41 (July 2018) were observed in the Iougawa,
Yukawa, Shibukuro, and Akagawa rivers located in
the Nagase, Agatsuma, Tamagawa, and Matsukawa
river basins, respectively. The neutralization
treatment using limestone is applied to the Yukawa,
Shibukuro, and Akagawa rivers, while in the
Urakawa, Iougawa, Nagase, and Sukawa river basins,there are no specific treatments applied towards
increasing river pH values. Especially in the
Akagawa river of the Matsukawa river basin, the pH
value of 3.41 mentioned above was obtained in thesampling location after the neutralization treatment
plant. Therefore, the original pH value was expected
to be significantly lower. In the following sections,the results acquired in the Agatsuma river basin as
an example of the neutralization treatment applied
and Nagase river basin as an example of no specifictreatment applied are discussed.

Study areas of the Urakawa, Iougawa,Nagase, and Agatsuma river basins (orange
plots indicate water sampling locations)(the base map was taken from Google
LLC).

Variations of water quality along the Agatsuma
river basin

Fig. 2In the upstream of the Agatsuma river basin, theKusatsu hot spring is one of the most famous acidic
springs in Japan and closed mines mainly elluting
Sulphur are located in the Eastern foot of an active
volcano, Mt. Kusatsu-Shirane. Especially, theYukawa river dominated by the discharged waterfrom the Kusatsu hot spring shows very low pH
value, usually less than pH 2.0. Therefore, theneutralization treatment has been applied by the
Ministry of Land, Infrastructure, Transport andTourism (Government of Japan) over 50 years [6],[7]. The resulting compounds from neutralization
treatment are continuously produced and finallydeposited in an artificial lake named Shinaki dam
located approximately 3 km downstream of theneutralization plant (Fig. 3). The water from the
Shinaki dam finally discharges to the Tone river (via
the mainstream of the Agatsuma river) which is thebiggest water resource for the Tokyo Metropolitan
area of Japan having a population more than 30
million.
The variation in water quality regarding pH, EC,
and concentrations of As, Pb, Fe (iron), and Al(aluminum) from the upstream to downstream along
the Agatsuma river basin is illustrated in Fig. 4. The
pH value of 1.82 was observed in the Yukawa river
before the neutralization treatment plant. After thetreatment, the pH value markedly increased toapproximately 4.5. Subsequently, the water from the
Shinaki dam discharges to the mainstream of theStudy areas of Sukawa, Tamagawa, andMatsukawa river basins (orange plots meanwater sampling locations) (the base map
was taken from Google LLC).

Additionally, on-site measurements of watertemperature, pH, electric conductivity (EC), andturbidity were performed using portable analyzers(WM-32EP, DKK-TOA CORPORATION, Japanand 2100P Potable Turbidimeter, HACH, USA)calibrated for each measurement. In the laboratory,
the sampled river water was filtered using a 0.20 mmembrane filter (DISMIC-25CS, Toyo Roshi
Kaisha, Ltd., Japan). Then, major cations and anions(Na+, NH4+, K+, Mg2+, Ca2+, F-, Cl-, NO3-, and SO42-)
and heavy metals and other elements (Li, Al, Si, Cr,
Mn, Fe, Ni, Cu, Zn, Se, Sr, Cd, and Pb) wereanalyzed using an ion chromatograph (ICS-1500,
Nippon Dionex K.K., Japan) and inductivity coupledplasma (ICP) mass spectrometer (MS) (ICPM-8500,
SHIMADZU CORPORATION, Japan).
RESULTS AND DISCUSSION
Levels of acidity in seven acidic river basins of
the Eastern part of Japan
The pH values were 5.64 (October 2017), 4.32
1031

SEE - Bangkok, Thailand, Nov.11-13, 2019

Agatsuma river where the pH already increased to aneutral value (7.38), while the concentrations of both
As and Pb dramatically decreased with applying theneutralization treatment. The Fe and Al
concentrations also decreased significantly after thetreatment as shown in Fig. 4. These chemicalcomponents were almost not detected in themainstream of the Agatsuma river. The metalhydroxides, especially Fe and Al, are in general easy
to precipitate by increasing the pH value in the water.
One of the most harmful elements, As, can be
simultaneously coprecipitated with metal hydroxides[9], [10]. Therefore, As and Pb were probably
coprecipitated with the Fe and Al hydroxides during
the neutralization process. The produced compounds
deposited in the Shinaki dam contains extremely
high concentrations of these harmful chemicalcomponents as reported in annual monitoring databy the Ministry of Land, Infrastructure, Transport
and Tourism [11].

Fig. 3Fig. 4the concentration of As, Pb, Fe, and Al
from the upstream to downstream along theAgatsuma river basin (1: Yukawa river(before neutralization), 2: Yukawa river(after neutralization), 3: Shinaki dam, 4:
Agatsuma river (upstream), 5: Agatsuma
river (middle stream), 6: Agatsuma river(downstream), 7: Agatsuma river (the mostdownstream)).
Variations of water quality along the Nagase
river basin
In the upstream of the Nagase river basin, acidic
hot springs and Sulphur mines already closed arealso located in the Western foot of Mt. Adatara thatis an active volcano. The Iougawa river which shows
the pH value of 1.66 dominated by the hot springwater. The water from the Iougawa river discharges
to the lake Inawashiro (via the mainstream of theNagase river). Then, the water from the lake
discharges to Nippashigawa river (Fig. 5) and finally
flows into the Agano river which is one of thebiggest rivers in Japan.

Study area of the Agatsuma river basin(yellow circles are representative water
sampling locations and the acquired datafrom these locations were illustrated in Fig.
4) (the base map was taken from Google
LLC).

Fig. 5

Study area of the Nagase river basin(yellow circles are representative water
sampling locations and the acquired datafrom these locations were presented in Fig.
6) (the base map was taken from Google
LLC).

The variation in water quality regarding pH, EC,
and the concentrations of As, Pb, Fe, and Al fromthe upstream to downstream along Nagase river
basin are also presented in Fig. 6. As describedabove, the pH value of 1.66 was observed in the
Iougawa river due to inflow of the hot spring water.
After that, the pH values gradually increased along
the river mainly due to the dilution effect by the
inflow from other rivers. In the most downstream
part of the Nagase river, the pH still showed a low
value, around 4.0. It, however, finally became aneutral value in the Nippashigawa river. Also, in the
Nagase river basin, the As, Pb, Fe, and Al
concentrations gradually decreased. The harmful
heavy metals of both As and Pb were probably

Variations of water quality for pH, EC, and
1032

SEE - Bangkok, Thailand, Nov.11-13, 2019coprecipitated with the Fe and Al hydroxides. At
least, the Fe hydroxide was clearly deposited in theriver bed (Fig. 7). Similarly, in the Nagase river
basin, the sediments in the river bed likely containhigh concentrations of harmful heavy metals such as
As and Pb. The next step of the investigation is toevaluate the chemical stability of these harmful
heavy metals in sediments of the river bed in the
Nagase river basin and of the Shinaki dam in theAgatsuma river basin.

In the Agatsuma river basin as an example ofthe possitive effects of neutralization treatment, thepH values markedly increased and concentrations ofAs, Pb, Fe, and Al dramatically decreased after thetreatment. Then, these values reached acceptablelevels. On the other hand, in the Nagase river basin,
being an example of no specific treatment applied,the pH values gradually increased andconcentrations of As, Pb, Fe, and Al steadilydecreased along the river, mainly due to the dilution
effect by the inflow from other rivers.
In both acidic river basins, harmful heavy
metals of As and Pb were probably coprecipitatedwith the Fe and Al hydroxides. The sediments
deposited in the river bed of the Nagase river basin
may therefore contain much higher concentrations ofharmful heavy metals including As and Pb aspreviously reported in the Shinaki dam of theAgatsuma river basin. The next step is to evaluate
the chemical stability of these harmful components
in the sediments.
ACKNOWLEDGMENTS

Fig. 6

Fig. 7This research was supported from a Grant-in Aid
for Scientific Research (no. 26889015) by the Japan
Society for the Promotion of Science, a research
grant by JFE 21st Century Foundation and theCollaborative Research Project (2017-17, 2018-13,
and 2019-15) by the Research Institute for Natural
Hazards and Disaster Recovery, Niigata University,
Japan.

Variations of water quality for pH, EC, andthe concentration of As, Pb, Fe, and Al
from the upstream to downstream along theNagase river basin (1: Iougawa river, 2:
Sukawa river (upstream), 3: Sukawa river(downstream), 4: Nagase river, 5: Nagase
river
(the
most
downstream),
6:
Nippashigawa river).

REFERENCES[1] Akcil A., and Koldas S., Acid Mine Drainage(AMD): causes, treatment and case studies.
Journal of Cleaner Production, Vol. 14, Issue 1213, 2006, pp.1139-1145.
[2] Herrera S.P., Uchiyama H., Igarashi T., Asakura
K., Ochi Y., Ishizuka F., and Kawada S., Acid
mine drainage treatment through a two-stepneutralization ferrite-formation process innorthern Japan: Physical and chemical
characterization of the sludge. Minerals
Engineering, Vol. 20, Issue 14, 2007, pp.13091314.
[3] Nieto J.M., Sarmiento A.M., Olías M., Canovas
C.R., Riba I., Kalman J., and Dlvalls T. A., Acid
mine drainage pollution in the Tinto and Odiel
rivers (Iberian Pyrite Belt, SW Spain) andbioavailability of the transported metals to the
Huelva Estuary. Environment International, Vol.
33, Issue 4, 2007, pp.445-455.
[4] Gaikwad R.W., and Gupta D.V., Review on
removal of heavy metals from acid minedrainage. Applied Ecology and Environmental
Research, Vol. 6, Issue 3, 2008, pp.81-98.
[5] Lei L., Song C., Xie X., Li Y., and Wang F.,

The river bed conditions in the Nagase river
basin (left: Sukawa river (upstream), right:
Nagase river)

CONCLUSIONS
Water quality parameters such as pH andconcentrations of heavy metals and other elements
were investigated in seven representative acidic river
basins located in volcanic areas in the Eastern part ofJapan. Generally, the lowest pH values ranged from1.31 to 5.64 in each river basin.

1033

SEE - Bangkok, Thailand, Nov.11-13, 2019

Acid mine drainage and heavy metal
concentration in groundwater of metal sulfide
mine at arid territory (BS mine, Western
Australia). Transactions of Nonferrous Metals
Society of China, Vol. 20, Issue 8, 2010,
pp.1488-1493.
[6] Kikawada Y., Kawai S., Shimada K., and Oi T.,
Arsenic originating in Kusatsu hot springs,
Gunma, Japan, and arsenic pollution status of
Kusatu rivers. Journal of Disaster Research, Vol.
3, Issue 4, 2008, pp.261-269.
[7] Mitsuya D., Hayashi T., Wang Y., Tanaka M.,
Okai M., Ishida M., and Urano N., Isolation of
aquatic yeasts with the ability to neutralize acidic
media, from an extremely acidic river near
Japan’s Kusatsu-Shirane Volcano. Journal of
Bioscience and Bioengineering, Vol. 123, Issue 1,
2017, pp.43-46.
[8] Sasaki A., Yoshikawa E., Mizuguchi H., andEndo M., The improvement of water quality inan acidic river environment using waste concrete
aggregates. Journal of Water and Environment
Technology, Vol. 11, Issue 3, 2013, pp.235-247.
[9] Violante, A., Ricciardella, M., Gaudio, S.D., andPigna, M., Coprecipitation of arsenate with metaloxides: Nature, mineralogy, and reactivity ofaluminum precipitates. Environmental Scienceand Technology, Vol. 40, Issue 16, 2006,
pp.4961-4967.
[10] Jia Y., and Demopoulos G.P., Coprecipitationof arsenate with iron (III) in aqueous sulfate
media: Effect of time, lime as base and co-ionson arsenic retention. Water Research, Vol. 42,
Issue 3, 2008, pp.661-668.
[11] Ministry of Land, Infrastructure, Transport andTourism(Government of Japan), Annual
monitoring data for sediments in the Shinaki dam,
http://www.ktr.mlit.go.jp/sinaki/sinaki_index013.html (accessed on June 5, 2019) (in Japanese).

1034

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

WATER FOOTPRINT OF RICE IN MYAUNGMYA TOWNSHIP,
MYANMARMay Myo Han
Faculty of Environment and Resource Studies, Mahidol University, Thailand

ABSTRACT
Rice is the major crop for Myanmar and water crisis has been one of the challenges in livelihoods andagriculture sectors. This research was conducted to account the Water footprint of Rice in Myaungmya Township,
located in delta area and the results are to be used as an indicator for local water resources management. Climate
and soil data, cropping patterns and fertilizers consumption are accessed by SEA START, CLIMWAT 2.0 and
Myaungmya Agricultural Department. The Green and Blue Water footprints are calculated using the crop
evapotranspiration values from CROPWAT Model 8.0. Mainly, rice in the target area is grown in monsoon andsummer seasons. Since the target area gets high rainfall, the Green Water Footprint of monsoon 1163 m3 per ton
is higher than the summer, 71 m3 per ton. And the Blue water footprint for monsoon is assumed as zero meanwhile
the summer is 1886 m3 per ton. According to the practice by the farmers, the fertilizers rate used in summer isrelatively higher than monsoon. Therefore, the grey water footprint for monsoon is 252 m3 per ton and the summer
season is 558 m3 per ton. The total water footprint of rice in monsoon is 1407 m3 per ton and the summer season
is 2515 m3 per ton, respectively.
Keywords: Water Footprint, Rice, CROPWAT MODEL 8.0

sown in more areas than summer rice because of thewater availability. But when comparing the yield, theyield of summer rice is higher than monsoon rice [9].
Natural disasters such as unusual floods in rainyseason untimely rain and severe drought become thefactor urging the local government to prepare theenough amount of water for rice fields seasonally andin different locations [14].
Water foot print concept could help farmers to use
the new practice of rice planting and moreover, local
government could be benefit from this research forwater resources management. This research aims togive the estimate data to prepare the amount of waterthat farmers needed for their rice fields in seasonallyand also during drought period or for drought prone
area in Myanmar.

INTRODUCTION
Water crisis has already become one of the mostchallenges in Myanmar recently. About 700 millionof people in 43 countries, especially in China, India
and Sub-Saharan Africa, were under the water deficit
problems as well (Human Development report, 2006).
Agriculture and farming are the main businesses ofMyanmar and rice farming depends on water
resources. Developing countries including Myanmar
account more than 80% for water in agriculture
meanwhile the high-income countries account over
40% for agriculture and industries [5].
This research was taken place from January to
April during the year of 2017. Myaungmya Township,
is located at 16° 35´ N and 94° 54´ E and has the areaof 1146. 2 km2 (Myanmar Department of population,
2015a). Typically, there are three seasons; rainyseason (June to October), summer (March to May)and cold season (November to February). It gets theTropical monsoon weather and has high temperaturesand heavy rainfall [17].The area gets the precipitation
not over 2500 mm per year [].The temperature range
is 36 °C -15 °C and the humidity 76% in average.
Generally, the land is the level plain and lies on thedelta region of the 290 km long and 240m wide of
Irrawady river basin [10],[15]. Tube pump wells arefor drinking water source and the rainfall is mainly
for agriculture and there is Myaungmya River nearby[13].
There are two rice cultivating seasons in
Myanmar; monsoon and summer. Monsoon rice is

METHODOLOGY
Water footprint is the volume of water used in acertain process of producing the goods or products
measured by the formulas at a certain point of
production [1],[3]. During the plantation of rice to theharvesting time, Total Water Footprint (WFT) is
calculated on the values of Green Water Footprint(WFrg), Blue Water Footprint (WFrb) and Grey Water
Footprint (WFrgy). For Myaungmya rice fields, Total
Water Footprint of monsoon rice and summer rice
will be the output water footprint according to twoplanting seasons.

WFT  WFrg  WFrb  WFrgy
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(1)

SEE - Bangkok, Thailand, Nov.11-13, 2019

Green Water Footprint and Blue Water Footprint
is based on the calculation of Crop Water Use per
production or yield of rice. Crop Water Use values
can be computed by the evapotranspiration values
exported by CROPWAT 8.0 model to calculate thecrop water requirements and irrigation requirements
based on the collected input data such as soil, climate
and crop data [7].

calculation has been done as green water footprint(WFrg) which the crop water use (m3/ acre) for blue
water is divided by the Y (yield ton/ acre). In this case,crop blue water use (CWUrb) is the total irrigation
evaporated from the field Eq. (7).
When the crop evapotranspiration (ETc), also
known as crop water requirement, is larger than theeffective rainfall (Peff), irrigation is needed for thecrop and it is calculated by taking the difference
between (ETc) and (Peff). For monsoon season,
farmers only depend on the rainfall as Myaungmya
receives heavy rainfall. When crop water requirement
is smaller than the effective rainfall (Peff) in
CROPWAT 8.0, blue water evapotranspiration (ETrb)
will become zero according to Eq. (5). Then we canassume blue Water Footprint as zero especially forthis case.

Data Collection
This research collected the secondary Data (20132016) from Myaungmya Agricultural Department
and Myaungmya Research Farm for crop pattern,
primary crop and secondary crop data, yearly yield
per acre covering the targeted area, fertilizers typeused for the plant growth, amount of fertilizer use(especially nitrogen) and soil characteristic of the area.
And for climatic data, this study used the secondary
climatic Data at least 30 years (1987 - 2016) of
Myangmya Township from SEA START and
CLIMWAT 2.0 Climatic Database (1971-2000).

ETrb  max( 0, ETc  Peff )

(5)

Lgp

CWU rb  10  0.4 ETrb

(6)

WFrb  CWU rb  Y

(7)

d 1

Green Water Footprint
The irrigation is needed when the effective
rainfall does not meet the requirement of crop
evapotranspiration during a period since the effective
rainfall will be decreasing before the harvest time.
This gap is also depending on the availability ofeffective irrigation water supply from the nearest blue
water resources. Mostly, the farmers in rain fed
agriculture of Myanmar lean on the green water
resource and no irrigation system in Myaungmya
Township although there are many cases that farmers
had to put or pump the blue water to be able tomaintain the desired water level.

To get the Total Green Water Footprint (m3 ton1), the climatic parameters and the crop parameters
will have to put into CROPWAT 8.0 and it generates
the values of the effective rainfall available (P eff) andthe crop evapotranspiration (ETc) during the rice
plantation period as the output in the model. Green
water evapotranspiration of rice (ETrg ) is theminimum value upon the effective rainfall available(Peff) and the crop evapotranspiration (ETc) Eq. (2)Crop Green Water Used (CWUrg) is thesummation of ETrg counted from planting day toharvest day multiply with water depth according to
Eq. (3). The factor 10 is used to convert water depths
in mm into water volumes per land surface in m3/ ha.
And since the land area unit for Myanmar is used inacre, 0.4 is the value to convert acre to hectare. Lgp
means for the length of growing period in days and it
started counted from the day of planting (day=1).
When the Crop Green Water Used (CWUrg) per
acre is divided by the yield of the rice per acre (Y),the value of Green Water Footprint is obtained Eq. (4).

ETrg  min( Peff , ETc )Grey Water Footprint
From the Equation (8), the Grey Water Footprint(WFrgy in m3 ton-1) of rice counts on fertilization rateapplied (AR in kg/acre) to the field per acre. Nitrogenis regarded as the representative of the grey water
calculation [2]. The leaching of Nitrogen in the
paddy will be taken account as 10% of the leachingrate although the leaching run-off varies according tosoil texture, amount of precipitation of the region andthe irrigation frequencies [2]. The maximum
acceptable concentration will be considered as 10 mg
nitrate per liter [12].

(2)

Lgp

CWU rg  10  0.4 ETrg

(3)

WFrg  CWU rg  Y

(4)

d 1

WF rgy  ( . AR) / (c m ax - c nat ) / Y

Blue Water Footprint(8)

In Equation (8), α is the leaching-run-off fraction,
Cmax (kg/m3) is the maximum acceptable

For blue water footprint (WFrb), the same
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SEE - Bangkok, Thailand, Nov.11-13, 2019

concentration, Cnat (kg/m3) is the naturalconcentration for the pollutant considered in thereceiving water body and Y is the crop yield (ton/acre).

and booting stage and the usage of Urea during theperiod is varied according to farmers’ favorite
practice. From the following Table 2, the averagevalue of the Urea used (ton/acre) is calculated by
dividing the amount of Urea used in monsoon season
to the total planted area.

RESULTS AND DISCUSSION
The results from the research are classified
according to two crops seasons. During the period of
the 2013 to 2016, the Green Water Footprint formonsoon rice is 1155 m3 per ton. From this research,
Blue Water Footprint is considered as zero as thecultivation practice is rain-fed system and the total
water footprint of monsoon rice 1407 m3 per ton ismeasured over the entire township which owns a
164,493 acre of rice fields. Grey Water Footprint is
252 m3 per ton (Table 1).
Planting the monsoon rice is based on the rain fed
cultivation system and the farmers started the land
preparation according to the weather condition which
is suitable and has the enough rain water to puddle.
Hence, the blue Water Footprint for the monsoon rice
can be considered as zero in this research (Table 1).
Farmers are introduced to use compound fertilizer
as for nutrients to rice plants before seeding. The typeof fertilizer is 15-15-15 and use one bag (50kg
loaded) per acre in a few areas [9]. Althoughcompound fertilizer is famous in recent years since2010, Urea is widely used because the nitrogen isregarded as the most important nutrients to the plants
by farmers. Urea (46%, 50 kg loaded) has been put
into the soil in vegetative phase, reproductive phase

Table 2 Amount of fertilizer uses in Myaungmya
Township
ton/acreYear
Season
0.10
2013
Rainy
0.20
2014
Summer
0.16
2014
Rainy
0.26
2015
Summer
0.70
2015
Rainy
2016
Summer
0.26
2016
Rainy
0.10
Source: Myaungmya Agricultural Department (2017)
For summer rice, green water footprint is 71 m3
per ton and blue water footprint is 1886 m3 per ton.
As for grey water footprint, the result shows 558 m3
per ton which is a bit higher value comparing with thegrey water footprint for monsoon rice, 252 m3 per ton(Table 1). The application rate of the fertilizer for
Monsoon Rice is obviously different as a half of theSummer Rice. Therefore, the Grey Water Footprint of
the Summer Rice is three times larger than the
Monsoon Rice.

Table 1 Comparison between Water footprints (m3 per ton) of Rice fields over Myaungmya Township, Tha Wang
Pha district, Thailand, South Korea and water footprint for Myanmar in Hoekstra & Chapagain (2011)
Period20132016
20132016
20112012(July –
October)
20042009
20042009

Location

Crop
MonsoonRice
Summer
Rice

WFrg

WFrb

WFrgy

WFT

Source

1155

0

252

1407

From this research

71

1886

558

2515

From this research

Tha Wang
Pha district,ThailandOryza
sativa L.

1470.3
3

0788.492258.82[5]South Korea

Wetland
Rice

294.5

501.6

48.4

844.5

[16]

Myanmar

Rice

846

378

50

1274

[4]

Myaungmya
Myaungmya

Although the starting date of cultivation ofsummer rice is different among farmers, the average
starting date is set up as the first of January. In
Myanmar, rain can be expected in some areas during
the earlier stage of the year. Myaungmya is located at
the delta region and near to sea. As a result, the Green
Water Footprint can be calculated as a small amountof value (Table 1).
The yield in average for the period of 2013 - 2016

for the Summer Rice (2.17 ton per acre) is also higher
than the Monsoon Rice (1.8 ton per acre). Therefore,
it can be assumed as the yield of the paddy directly
depends on the fertilizer usage of the farmers to theirfields. And the floods and untimely rain which occurs
in Monsoon Season due to the climate change cause
deficit to the yield (Table 3).

1037

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 3 Yield in Myaungmya Townshipvalues as weather data were used from SEA START
and CLIMWAT 2.0. The results may not accurate
because of long term climate prediction based on thesimulation process of scenarios and the datasets of the
scenarios based on the 360 calendar year. Based on
the location of land area and noises in some grid insome years, the result may not be equally accurate
throughout the domain especially for rainfall data.
The necessary data like humidity and the sunshine
hours could not be accessed from this database.
Myaungmya is not a well-connected Townshipcontrast with another beneficial city which could
support the research facilities to get the data of Cropcoefficient (Kc), rooting depth (m), Puddling depth(m), nursery area (%), critical depletion (fraction),yield response and crop height (m). CROPWAT 8.0
model provides the essential crop data to calculate thewater footprint of the various types of crop. Hence,the crop data for this research is used from the datafrom FAO which is attached to CROPWAT 8.0.
Although the amount of Urea, potash and T-superused is recorded from the farmers, the amount of 1515-15 compound could get for some seasons andyears. Therefore, Actual Grey Water Footprint will bea little higher in reality than the values in thisresearch. The rate of chemicals applied to the rice
field can be accumulated, but it is difficult to measure
the fraction of applied chemicals which is not used
and reaches the ground and surface water. As a result,the natural nitrogen concentration for the pollutant is
considered as zero and the estimated value of thefraction of applied chemicals that enter the water
system is used in common.
The calculations of the water footprints of the
production of rice are not measured due to the time
limit and the difficulties to get the data from theproduction process of the millers. Besides, theconsequences to the environmental pollution due tothe grey water footprint and the actual run-off ofNitrogen are hard to measure in the targeted area.

ton/acreYear
Season
1.70
2013
Rainy
2.12
2014
Summer
1.80
2014
Rainy
2.20
2015
Summer
1.80
2015
Rainy
2016
Summer
2.20
2016
Rainy
1.80
Source: Myaungmya Agricultural Department (2017)
As a total for two seasons, Total Water Footprintfor Summer Rice (2515 m3 per ton) is higher than the
Total Water Footprint for Monsoon Rice (1407 m3
per ton). In Hoekstra & Chapagain [4], the averagevalue of green water footprint for Myanmar is 846 m3
per ton, blue water footprint is 378 m3 per ton andgrey water footprint 50 m3 per ton. Therefore, theresults in Myaungmya Township are higher than the
average value of the whole country in Myanmar.
Moreover, Tha Wang Pha District from Thailand has
1470.33 m3 per ton of Green Water Footprint and788.49 m3 per ton of Grey Water Footprint in 20112012 which is less in a number comparing with thisresearch in both Grey Water footprints for two
seasons.
The period for 2000-2004 of Hoekstra &Chapagain [4] has a less number in value while
comparing with the research. Nonetheless, the global
average water footprint in the period 2000 – 2004 forpaddy rice was 1325 m3 per ton. Therefore, the valueof this research is higher in value of the global
average.
In contrast, the data for the Hoesktra &Chapagain [4] has accessed from the FAO in 2004 2009 and this research is accessed from the local data
sources in current time. The fact that the key factors
for the Green Water Footprint and the Blue Water
Footprint, the climatic data which can have somedifferences as the whole country and the spotted
township, has to be considered in this case.
For grey water has the impact to the environment,
the appropriate application rate of the paddy fields isimportant to considered in the near future as thefertilizers usage are increased although it is still lessthan comparing with the neighboring countries.
This research is based on the heavy precipitation
region and extensive water resource (Myaungmya
River). Therefore, the results from the research could
give the data to build up the policy or the management
plan to sustain the existing water resource of the water
stress region, especially drought prone area of
Myanmar.

Recommendation
Based on the data and values of this study, thebetter accurate values of water footprint of othercrops and production of goods and products areencouraged to improve. Further researches on water
footprint approach, benefits of using organic
fertilizers such as cow manure for the rice plants, rice
varieties that used less water footprint arerecommended. In past times before the machine are
not widely used in farms, cows are used to paddle theground and manure is stored and preserved withplants to get the fertilizer. This fertilizer could help toreduce the cost of fertilizer and has the benefit forsustainable environment [14].
While comparing with the global average water
footprint in the period of 2000 – 2004 (1325 m3 perton), both season have higher water footprint (Total

Limitations
The above Water Footprint values are estimated1038

SEE - Bangkok, Thailand, Nov.11-13, 2019

Water Footprint for Summer Rice - 2515 m3 per ton
and the Total Water Footprint for Monsoon Rice 1407 m3 per ton). The effective agricultural practiceis needed to introduce with the traditional farmers.

global component of freshwater demand andsupply: An assessment of virtual water flows
between nations as a result of trade in agriculturaland industrial products.Water International,
33(1),19-2.doi:10.1080/02508060801927812[4] Chapagain, A., & Hoekstra, A. Y. (2011). The
blue, green and grey water footprint of rice fromproduction and consumption perspectives.
Ecological Economics, 70(4), 749-758.
doi:10.1016/j.ecolecon.2010.11.012[5] Chatpanyacharoen, W., Hungspreug, N.,
Anurugsa, B., & Taweesuk, S. (2015). Water
Footprint Evaluation of Oryza sativa L. Tha
Wang Pha District, Nan Province. Thammasat
International Journal of Science andTechnology, 20(4), 21-28.
[6] Hoekstra, A.Y. (2003).Virtual water trade:
Proceedings of the International Expert Meetingon Virtual Water Trade, Value of Water
Research Report Series No.12, UNESCO-IHE,
Delft.
[7] FAO (2015). Water Management andDevelopment Unit. Food and Agriculture
Organization of the United Nations. FAO Water
Unit | Water News: water scarcity[8] Human development report (2006): Beyond
scarcity: Power, poverty and the global watercrisis. (2006). Basingstoke: Palgrave Macmillan[9] Myaungmya Agriculture Department (2017).
Agricultural database of crops and fertilizers[10] Mani, M. S. (1974). Biography of the Eastern
Borderlands. Ecology and Biography in India pp648-663[11] Ministry of Agriculture and Irrigation Union of
Myanmar. (2001). Myanmar Agriculture[12] Ministry of Agriculture, Livestock and Irrigation(2016). Overview of the Water Environment
Standards and Effluent Standards and its
Implementation, Myanmar.
[13] Myanmar family clinic & Garden (MFCG)(2016). Myanmar family clinic & Garden
Project Final Report 1 : Improving the healthknowledge and social status in Myaungmya
Region, Myanmar[14] Proximity Designs. (2016). Paddy to Plate. The
rice ecosystems in Myanmar: Challenges andopportunities. ISBN: 978-1-939727-05-3[15] Simmance, A. (2013). Environmental Flows for
the Ayeyarwady (Irrawaddy) River Basin,
Myanmar. Unpublished. UNESCO-IHE Online
Course on Environmental Flows[16] Yoo, S., Choi, J., Lee, S., & Kim, T. (2013).
Estimating water footprint of paddy rice in Korea.
Paddy and Water Environment, 12(1), 43-54.
doi:10.1007/s10333-013-0358-2[17] Tint, K. K. (2012). Study on “THIN” cultivationin Ayeyawady. Pathein University Research
Journal Vol. 4. 2012

CONCLUSIONS
The role of agriculture perspective in Myanmar
plays as an essential business career for the Myanmar
people. The whole country depends on the productfrom the agriculture and the excess products areexported to neighboring countries. The water
availability is unbalance as the central Myanmar bec
omes the drought prone area while the delta areas are
faced with unusual flood. And Water scarcity is oneof the challenges in central Myanmar andmountainous region. Therefore, the development in
the rice practice to reduce Water Footprint and using
the amount of water efficiently is important in the
future.
ACKNOWLEDGMENTS
I would like to express my deepest
acknowledgement to the “Mahidol-Norway Capacity
Building Initiative for ASEAN” from Mahidol
University and faculty of Environment and Resource
Studies,
Mahidol
University,
Myaungmya
Agriculture Department and Myaungmya Agriculture
Farm for giving me an opportunity to be able toaccomplish this research. With their supports in bothfinancial and supervision, I would be able to finish themaster study. And I would like to give my deepest
appreciation to Assoc. Professor Nathsuda
Pumijumnong, my major advisor for her professional
knowledge, wisdom of advices, and support during
the study period. I would like to send my honest
thanks to my advisors Asst. Professor Achara
Ussawarujikulkai and Lecturer Dr. Uthai
Chareonwong for their academic interest in my study,
excellent
academic
guidanceandhonestencouragements throughout the process of my study.
REFERENCES[1] Chapagain, A. K., & Hoekstra, A. Y. (2004).
Water Footprints of Nations. Value of Water
Research Report Series No. 16.UNESCO-IHE,
Delft, the Netherlands.
[2] Chapagain A.K.,Hoekstra, A.Y., Savenije,
H,H,G., Gautam, R., 2006. The water footprint ofcotton consumption: an assessment of the impact
of worldwide consumption of cotton products on
the water resources in the cotton producing
countries. Ecological Economics 60 (1), 186 203[3] Chapagain, A. K., & Hoekstra, A. Y. (2008). The

1039

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

THE EFFECT OF INSIDE CIRCUMSTANCE OF THE HAZARDOUS
WASTE LANDFILL ON THE LEACHING BEHAVIOR OF HARMFULHEAVY METALS
Yasumasa Tojo1, Taira Ikeda1, Takayuki Matsuo1 and Toshihiko Matsuto1
1
FacultyGraduate School of Engineering, Hokkaido University, Japan

ABSTRACT
Influence of interior condition in the hazardous waste landfill on the leaching behavior of heavy metals were
examined from the accelerated weathering experiments for dust which is a kind of wastes to be disposed of at thehazardous waste landfill. Among the main components, a decrease in the leaching amount of Cd, Pb, Mn, and Zn
was confirmed in a wet environment where adsorbed water was present on the particle surface. On the other
hand, in the dry and CO2 saturated environment, an increase in leaching amount was observed. The former
phenomenon was thought to be the formation of hydroxide through particle surface adsorbed water, and the latter
was considered to be the influence of adsorption of gas phase CO2 to Fe3O4 and ZnO. However, further scientificverification is required for each phenomenon. The findings obtained in this study indicate that the leaching ofheavy metals from hazardous wastes disposed of in the hazardous waste landfill may change over time.
Keywords: Hazardous waste landfill, Dust, Weathering, Heavy metals, Leachingwaste. For incineration residue, the aging
phenomenon is known to be effective for reducing
the mobility of heavy metals [2]-[4]. The aging or
weathering of the incineration residue is occurred by
the contact with rainwater and carbon dioxide in air.
As mentioned above, the hazardous waste landfill issurrounded by concrete walls and roof. The waste
inside the landfill is isolated from the outsideenvironment. This means that active control ofinside circumstance is necessary to create thecondition preferable for aging or weathering.
However, it is not clear what kind of on-sitemanagement(humidity,gas
atmosphere,
temperature, etc.) is desirable for insolubilization ofheavy metals. Storage of hazardous waste in thecontainment-type hazardous waste landfill is semipermanent. That is, an extremely long time can beused. There is room for study whether there can befavorable inside circumstance that can graduallychange the heavy metals contained in the hazardous
waste into a hardly soluble state within that longtime. Controllable parameters may be gas
atmosphere, humidity, temperature, etc. These need
to be made clear.
In this study, the effect of inside circumstance ofthe hazardous waste landfill on the leaching
behavior of harmful heavy metals was investigated.
The electric furnace dust that is designated ashazardous waste was used and it was subjected tothe accelerated weathering experiment. The
objective of the study is to elucidate suitablecondition for reducing heavy metal leachingpotential from the waste disposed of in thehazardous waste landfill and to propose the active

INTRODUCTION
In Japan, solid waste landfill is classified into
three types. They are inert waste landfill, nonhazardous waste landfill, and hazardous waste
landfill [1]. Among them, in hazardous waste
landfill, hazardous waste which exceeds criteria forhazardous heavy metals leaching is disposed of. The
hazardous waste landfill is required to be designed
and constructed with robust concrete wall and base,and the top is capped. The concept of this landfill is
containment of hazardous substance and eliminates
the chance of reaction with water and air. In general,in non-hazardous waste landfill, various substances
are subjected to many reactions and graduallystabilized. Even for hazardous heavy metals, it is
known that their leaching potentials reduce due tothe long-term weathering effect. But according to
the concept of the hazardous waste landfill, thesereactions cannot be expected. This means that theleaching potential of hazardous heavy metals will be
kept forever. However, there is no guarantee that thecontainer structure will be permanently maintained
because of the impact of natural deterioration of
structure or disaster.
In order to prevent sudden emission of hazardous
substance due to these occasions in future, somemeasure must be taken. There are two candidates
considered to be able to achieve it. The one is multibarrier system. To surround the site by various
barrier systems such as clay barriers, impact ofheavy metal to the surrounding environment can be
mitigated. The other is to reduce the leachingpotential of hazardous substance itself from solid
1040

SEE - Bangkok, Thailand, Nov.11-13, 2019

control method to achieve it.

hydrofluoric acid digestion. Also, the leachingamount was measured again by the JLT-13 leaching
test of liquid-solid ratio 10. ICP analysis(SHIMADZU ICPE-9000) was used for quantitative
analysis in content analysis and leaching test.
Table 2 shows the measurement results of themetal content and the leaching amount. Although theleaching ratio (= leaching amount / content) of mainelements such as Fe and Ca is low and it seems toexist in a hardly soluble form, about 43% of thecontent of cadmium was leached out.

MATERIAL AND METHODS
Material
According to the statistics of Ministry ofEnvironment, Japan, there are 24 hazardous waste
landfills registered [5]. However, among them, thelandfill in operation is only one or two. At one
hazardous waste landfill, interview was performed
regarding kinds of waste accepted at the site. The
major waste accepted and disposed of were sludge,
cinder, and dust. However, it was difficult to obtainthese waste samples at the landfill site due to theircontracts. Thus, similar hazardous waste samples
were obtained from waste treatment company which
generates these wastes. The waste samples were
sludge and two dusts. At first, leaching test
(Japanese leaching test, JLT-13 [6]) was conducted
for each of them. Since one dust sample fromelectric furnace had high heavy metal leachingpotential, it was selected for the experiment in thisstudy.
For the electric furnace dust, elemental
composition was analyzed by XRF (Horiba MESA800) at first, then, mineral composition was analyzed
by XRD (Rigaku Rint-2000). Table 1 shows theelemental composition of the dust and Fig.1 shows
the diffractogram by XRD analysis. As can be seen
Table 1, major component of the dust is Fe and Zn.
Besides, from Fig. 1, Fe is contained as Magnetite(Fe2O3) and Zn is contained as Zincite (ZnO). Sinceboth compounds have adsorption capability, they
may affect heavy metal leaching characteristics fromthe dust.

600

Fe
32.6
Si
5.3

Zn
21.0
Cl
3.8

Cr
12.0
K
3.7

Ca
8.6
Mn
3.0

Intensity [-]

400

300
200
100

0
10

20

30

40

50

60

70

80

2θ

Fig. 1

Diffractogram of the dust sample by XRD

Accelerated Weathering Experiment
By considering possible circumstance as theinside condition of hazardous waste landfill, a totalof 12 series of combinations of gas, humidity, andtemperature were set up (Namely, 3 gas conditions,
2 humidity conditions, and 2 temperature conditions(3*2*2=12).). Samples were put in the dish and it
was placed in the chamber of which condition was
set at each weathering condition. Each condition was
set as follows;
Gas: a) Air, b) N2 gas, c) CO2 gas, the chamber
was purged by each gas.
Humidity: a) Dry (hygroscopic silica gel was
filled in the bottom of the chamber), b) wet (A metal
tray was placed at the bottom of the chamber andfilled with distilled water)
Temperature: a) Leave at room temperature (Just
leave as it is), b) Freeze and thaw repetition (thesealed chamber was put in the freezer once a day.

Table 1 Elemental composition of the electric
furnace dust analyzed by XRF
Element%
Element%

Fe3 O4 MagnetiteZnO Zncite

500

Ni
5.8
Pb
2.7

Next, for determining of the more accuratecontent, the contents of Ca, Cd, Cr, Fe, Mn, Ni, Si,
Pb, and Zn, which were the main components of thedust by XRF analysis, were measured by
Table 2 Content and Leaching amount of metals
Element
Ca
Cd
Content [mg/kg]
64139
117
Leaching [mg/kg]
63.5
50.5
Ratio [%]
0.1
43.3
Ratio = Leaching amount / Content

Cr
23045
0.1
0.0

Fe
176074
0.1
0.0

1041

Mn
12866
110.2
0.9

Ni
29301
47.8
0.2

Pb
10210
6.8
0.1

Si
29903
49.7
0.2

Zn
84528
1109.5
1.3

SEE - Bangkok, Thailand, Nov.11-13, 2019

RESULTS AND DISCUSSIONS

Under wet conditions (right in each figure (wet)),the Cd, Pb, Mn, and Zn were confirmed to decrease

50

Dry
40
30
20
10

N2
2

3

Fig. 2

4

5 6
week

7

8

9

8
6
4
2

0
3

Fig. 3

4

5
6
week

7

8

9

100
80
60
40

N2

CO2

4

5
6
week

Air

0
2

3

Fig. 4

10
0
2

3

4

5 6
week

7

8

9

10

10

Wet
8

N2

Air

CO2

6
4

Blank (Dry N2)

2

0
1

2

3

4

5 6
week

7

8

9

10

Change of Pb leaching from dust under each weathering condition
Dry

1

20

10

120

20

Blank (Dry N2)

30

1

Leaching amount of Pb [mg/kg]

Dry

2

Wet
40

Change of Cd leaching from dust under each weathering condition

10

1

50

10

Leaching amount of Mn [mg/kg]

Leaching amount of Pb [mg/kg]

Air

CO2

0
1

Leaching amount of Mn [mg/kg]

Leaching amount of Cd [mg/kg]

The influence of the repetition of freezing andthawing on the leaching behavior of heavy metals
was not observed. Thus, only the results of standingat room temperature are explained below. Moreover,in the following, drying conditions with N2 gas
atmosphere is considered as blanks. This is because,
under this condition, no change in the leaching wasobserved for any of the metal elements (this isconsidered to be the condition that weathering
hardly occurs). The results of Cd and Pb are shownin Fig. 2 and Fig. 3. In addition, Fig. 4 shows the Mn
results that showed similar behavior to Cd. And Fig.
5 shows the results of Zn that showed a marked
change in the leaching behavior especially among
the elements with high contents.

Leaching amount of Cd [mg/kg]

After the sample was frozen, leave it in the room andthaw it).
The samples were cured in chambers under eachcondition. Ten samples were prepared per system,
collected one by one weekly, and subjected to theleaching test.
Leaching test was conducted as follows;
approximately 2g of a sample taken from eachweathering series and then it was weighed. thesample was put into a screw bottle, and 20mL of
distilled water was added to make L/S = 10, then it
was shaken at 200 rpm for 6 hours with a bench
shaker. Thereafter, the supernatant was filteredthrough a 0.45 μm membrane filter to obtain a test
solution, and the concentration of the target metal
was analyzed by ICP. The pH was also measured
with a HORIBA pH meter.

7

8

9

10

120

Wet
100

Blank (Dry N2)

80
60
40
20
0
1

2

3

4

5 6
week

7

Change of Mn leaching from dust under each weathering condition
1042

8

9

10

Leaching amount of Zn [mg/kg]

Leaching amount of Zn [mg/kg]

SEE - Bangkok, Thailand, Nov.11-13, 2019

2500

Dry
2000
1500
1000
500

0
1

2

3

Fig. 4

4

5 6
week

7

8

9

10

2500

Wet
2000

N2

Air

CO2

1500
1000
500

Blank (Dry N2)

0
1

2

3

4

5 6
week

7

8

9

10

Change of Zn leaching from dust under each weathering conditionin the amount of leaching regardless of the gas
atmosphere, and the results were below the blankline (i.e., the average of the leaching amount under
dry/N2 condition) shown in the figure. Under wet
conditions, adsorbed water is present on the particle
surface, and a gradual increase in pH is confirmed,
so it is considered that the formation of hydroxidesof these metals is a factor in the decrease in leachingamount. Cd shows a remarkable decrease in leachingamount under wet/CO2 conditions. It is consideredthat CO2 in the gas phase is dissolved in surface
adsorbed water of the particles to form carbonate.
On the other hand, under the drying conditions
shown in the left figure, an increase in the leachingamount of Cd, Pb, Mn, and Zn was confirmed underCO2 exposure conditions, and a significant increase
was particularly observed in Zn. Since there is nowater in the dry atmosphere, the increase in theleaching amount is likely to be the influence of thereaction between the gas phase CO2 and the dust
sample. It is possible that Fe3O4 and ZnO, which are
the predominant components of the sample, bothhave adsorption capability, and have suppressed theleaching of heavy metals by working as an adsorbent
during the leaching test. There is some reports thatthese oxides adsorb gas phase CO2 [7]-[8]. As aresult of the dust sample being exposed to CO2 for along time, the adsorption capacity is lowered due tothe occupation of the adsorption site by CO2,
resulting in the increase of metal leaching amount
may have happened.

and CO2 saturated environment, an increase inleaching amount was observed. The former
phenomenon was thought to be the formation ofhydroxide through particle surface adsorbed waterand the formation of carbonate for Cd by CO2 gas
dissolution, and the latter was considered to be theinfluence of adsorption of gas phase CO2 to Fe3O4
and ZnO, but further scientific verification isrequired for each of them. The findings obtained inthis study indicate that the leaching of heavy metals
from hazardous wastes disposed of in a hazardous
waste landfill may change over time. And it meansthat active control of the inside circumstance ofcontainment structure may be effective to reduce therisk of future emission of these hazardous heavy
metals.
More specifically, if electric furnace dust is
disposed of in a hazardous waste landfill, it iseffective to control the humidity to a high level forturning hazardous heavy metals into insoluble state.
In particular, if it is desired to suppress Cd leaching,
to make the gas atmosphere inside landfill to highCO2 gas concentration (by using CO2 gas injection,etc.) is effective for carbonate formation. In thisstudy, the conditions of saturated vapor pressure andCO2 of 100% were adopted to accelerate weathering.
However, since the storage period of waste in thehazardous waste landfill is extremely long, it isdeemed to be possible to progress insolubilization of
hazardous metals without making these conditions
extremely high. Until now, no attention has been
paid to the internal condition of hazardous waste
landfills, and there has been no particular control. Of
course, the conditions under which leaching
suppression proceeds depend on the type of waste(dust, sludge, ash, etc.). One pit in hazardous waste
landfill sites in Japan is regulated to 250m3 or less,so the size is small. Therefore, it is possible toaccept only a single waste in each pit and control thecircumstance. What this research suggests is thatleaching suppression of hazardous heavy metals is
possible to progress by the control of insidecondition because extremely long-term storage isrequired.

CONCLUSIONS
The influence of the inside circumstance in thehazardous waste landfill on the leaching behavior ofheavy metals were examined from the accelerated
weathering experiment for electric furnace dust
which is a kind of hazardous wastes to be disposedat the hazardous waste landfill. Among the main
components, a decrease in the leaching amount of
Cd, Pb, Mn, and Zn was confirmed in a wet
environment where adsorbed water was present on
the particle surface. On the other hand, in the dry
1043

SEE - Bangkok, Thailand, Nov.11-13, 2019

for the modeling and trapping of heavy metals,
Applied Geochemistry, 19, 2004, pp.1891–1904.
[4] Meima, J. A., Comans, R. N. J., The leaching oftrace elements from municipal solid waste
incinerator bottom ash at different stages ofweathering, Applied Geochemistry, 14, 1999,
pp,159-171.
[5] Ministry of Environment, Japan, Survey on admi
nistrative organization of industrial waste, https://www.env.go.jp/press/files/jp/108899.pdf.
[6] Sakanakura, H. and Miyawaki, K., Role ofJapan’s Compliance Leaching Test for Landfills
and Related Issues, Material Cycles and Waste
Management Research, 20(6), 2009, pp. 287-291.
[7] Tang, Q-L. and Luo, Q-H., Adsorption of CO2 at
ZnO: A surface structure effect from DFT+U
Calculation, The Journal of Physical Chemistry,
117(44), 2013, pp.22954-22966[8] Chen, Q. and Bahnemann, W., Reduction of
Carbon Dioxide by Magnetite: Implications for
the Primordial Synthesis of Organic Molecules,
J. Am. Chem. Soc. 122, (2000) pp.970-971.

ACKNOWLEDGMENTS
This research was supported by the Environment
Research and Technology Development Fund (31802) of the Environmental Restoration andConservation Agency of Japan.
REFERENCES[1] Ministry of Environment, Japan, Waste disposal
and Recycling measures, https://www.env.go.jp/
en/recycle/manage/waste.html[2] Speiser, C., Baumann, T., Niessner, R.,
Morphological and Chemical Characterization ofCalcium-Hydrate Phases Formed in Alteration
Processes of Deposited Municipal Solid Waste
Incinerator Bottom Ash, Environmental Scienceand Technology, 34, 2000, pp.5030-5037.
[3] Piantone, P., Bodenan, F., Chatelet-Snidaro, L.,
Mineralogical study of secondary mineral phasesfrom weathered MSWI bottom ash: implications1044

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

COSTS AND BENEFITS OF USING PARABOLIC GREENHOUSESOLAR DRYERS FOR DRIED HERB PRODUCTS IN THAILAND
Samatcha Krungkaew1, Kanokwan Kingphadung1, Suphaphat Kwonpongsagoon2, Busarakorn Mahayothee1
1
Department of Food Technology, Faculty of Engineering and Industrial Technology,
Silpakorn University, Thailand;
2
Department of Sanitary Engineering, Faculty of Public Health, Mahidol University, Thailand;Center of Excellence on Environmental Health and Toxicology (EHT), Thailand

ABSTRACTParabolic greenhouse solar dryers have been developed to overcome product quality and postharvest loss
problems. It uses solar energy, a renewable source of energy. Due to their high investment costs, economic
feasibility and the potential of carbon dioxide (CO2) mitigation were investigated. Owners and managers of 17
enterprises, producing several varieties of herb products, investing in different sizes of solar dryers and using
various traditional drying methods before investing in solar dryers, were interviewed in depth to create a data set.
The net present value (NPV), internal rate of return (IRR), payback period and CO2 mitigation were evaluated.
The enterprises with annual production capacities higher than 1,200 kg or the annual revenues higher than solar
dryer investment costs tended to have positive NPV indicating that the investments were attractive. Most
enterprises showing CO2 mitigation higher than 130 tCO2e over 15 years had positive NPV. The annual
production capacity, annual revenue and the amount of CO2 mitigation could be used to assess investing ingreenhouse solar dryers.
Keywords: Carbon dioxide mitigation, Food loss, Drying selection, Medicinal plants, Renewable energy

benefits gained from both economic andenvironmental aspects to determine their investment.
The purpose of this study was to investigate theeconomic viability and potential CO2 mitigation inusing greenhouse solar drying systems for dried herb
production in Thailand.

INTRODUCTION
Drying is an important method used for herb
preservation in tropical countries [1]. Traditionally,
open sun drying is mostly used due to its simplicity
and low cost [2]. Because the process is slow, rawmaterial or product losses can occur. Moreover, it
has several limitations that affect the product quality
due to dust, wind, pests and insects [3].
In rainy season, open sun drying cannot be
conducted. Some enterprises continue the production
process using auxiliary heat for which fossil fuelmay be used as the heat source. Enterprises
endeavoring to avoid raw material losses andproduct quality problems use other drying methods
employing fossil fuel as the major heat source.
However, fuel combustion causes greenhouse gas
emissions which increase climate change impacts[4].
A solar dryer is a system that uses solar power, arenewable source of energy. It can be used to reducethe cost of energy and decrease carbon dioxide
emissions [5]. The parabolic greenhouse solar dryer(Fig.1) has been developed which could support
high production capacity and overcome production
problems [6]. The systems are W6 × L8.2 m2, W8 ×
L12.4 m2 and W8 × L20.8 m2 for small, medium,and large size of solar dryers, respectively. Due tothe high price of solar dryers and the different costsof each size, entrepreneurs need to consider the

Fig. 1

Large sized parabolic greenhouse solar
dryer.
Source: Janjai [6]METHODOLOGY
Data Collection
A primary data set was obtained from enterprisesthat invested in various sizes of parabolic
greenhouse solar dryers whose main products weredried herbs. The selected enterprises produced the1045

SEE - Bangkok, Thailand, Nov.11-13, 2019

dried herb products using various traditional drying
methods before investing in solar dryers todetermine the benefits gained from their investment.
The owners or managers of the seventeen enterprises
were interviewed in depth after completing tested
questionnaires, covering product data, quantity andtype of fuel used for drying before investment,
annual production capacity, annual revenues, solar
dryer size and annual savings gained.

PBP 

CI
ST

(5)

Carbon Dioxide Mitigation
Total carbon dioxide mitigation was calculatedusing the following formula:

CM T  CM f  CM w

(6)

Economic Analysis
where CMT denotes the total carbon dioxide
mitigation; CMf is the carbon dioxide mitigationfrom reducing fuel consumption, and CM w is the
carbon dioxide mitigation from waste reduction.
Carbon dioxide mitigation from fuel use
reduction was determined by the following formula:

The value of annual total savings per annual
revenue (Vs/r) was determined as:Vs / r 

ST
Ra

(1)

CM f  CE f ,b  CE f ,awhere Ra represents the annual revenues and ST
denotes the total savings gained from investing
calculated using the following formula:ST  Sf  Sw  Sl

where CE f,b and CEf,a represent the carbon
dioxide emissions from fuel consumption before andafter investing in the solar dryer, respectively.
Carbon dioxide mitigation from waste reduction
was calculated using the following formula:(2)

where Sf is the savings gained from fuelreduction; Sw denotes the savings gained from foodwaste or raw material loss reduction, and Sl is thesavings gained from labor cost reduction.
The most commonly used economic indicators,
namely, net present value (NPV), internal rate of
return (IRR) and payback period (PBP) were
investigated in this study. NPV was calculated using
the following formula [7]:t kNPV  CI  

ST , tt  0 (1  d )t

CM w  CE w ,b  CE w ,a

t k

S

T,t
0
 (1  IRR)t(8)

where CEw,b and CEw,a represent carbon dioxide
emissions from food waste before and afterinvesting in the solar dryer, respectively.
Carbon dioxide emissions from fuel consumption
and food waste can be estimated using the following
expressions:(3)

where CI denotes the investment cost of the solar
dryers which is negative because it represents theexpense at the beginning of investing; d denotes thediscount rate; t denotes the specific year of investing
and k is the total number of years of investing which
was 15 years in this study according to the lifespanof the solar dryer [6].
The IRR is one of the economic parameters used
to indicate economic feasibility. It is the discountrate that makes NPV equal to zero and wasdetermined using the formula below:
NPV  CI (7)

CE f ,b  Q i,b  EFi(9)

CE f ,a  Q i,a  EFi(10)

CE w ,b  Q j,b  EFj(11)

CE w ,a  Q j,a  EFj(12)

where Qi,b and Qi,a are the quantity of fuel i used
before and after investing in the solar dryer; EFi isthe carbon dioxide emission factor of fuel i; Qj,b andQj,a are the quantity of food waste before and afterinvesting, and EFj is the carbon dioxide emission
factor of food waste. The study assumed that all thefood waste would be disposed of by landfill and therelated emission factor was 2.53 kgCO2e/kg waste[9].
Carbon dioxide mitigation cost was calculatedusing the following formula:

(4)

t 0

The PBP is the amount of time required torecover the cost of investing and was calculatedusing the formula below [8]:1046SEE - Bangkok, Thailand, Nov.11-13, 2019

MC 

CI
CM T

Enterprise investing in small and medium solar
dryers exhibited an annual production capacity morethan 1,300 kg and those investing in large solar
dryers had 9,600 kg. This indicated that high annual
production capacity could generate a positive NPV.
The result was similar to the enterprise group using
fuel before the solar dryer investment for which
85.71% of these enterprises having a positive NPV
exhibited an annual production capacity higher than
1,200 kg. However, some enterprises, having anannual production capacity higher than 1,200 kg,
had a negative NPV while some enterprises, having
an annual production capacity lower than 1,000 kg,
had a positive NPV.
Enterprises FS1 and FS3 invested in small solar
dryers and could gain a high amount of savings
resulting in the highest IRR and the lowest PBP of
0.69 years for FS1 and 1.11 years for FS3 (Fig.2).
Fifty-five percent of the enterprises that had apositive NPV invested in small solar dryers showingthat small dryers tended to provide higher economic
viability. According to Janjai and Tung [1], anothertype of solar dryer for drying herbs was investigated
and they reported that its payback period of 3.9
years was a feasible investment in Thailand.

(13)

where MC denotes the mitigation cost.
RESULTS AND DISCUSSION
Economic Analysis
Nine enterprises had positive NPV indicatingthat the investment was worthwhile (Table 1). Sixtyseven percent of the enterprises having positive NPV
were those that replaced fuel with solar energy. Allenterprises in the group using fuel as traditional
drying method that invested in small and medium
size solar dryers, except enterprise FM3, had
positive NPV. Enterprise FM3 gained low savings
from fuel reduction. Moreover, enterprise FM3 had
incurred expenses using more labor forces to moveproducts from the solar dryer to the drying oven. It
showed that lowered savings from one factor andincreased expenses from another factor could createa negative NPV.
Only 37.50% of the enterprises using sun drying
as a traditional method had a positive NPV.
Table 1 Summary data of enterprises and calculated NPV.
No.

Code*

Dried product

Conventional
fuel used

Annualproduction
capacity (kg)
1,380
1,445

Annualrevenues(USD***)
157,500
4,141

NPV(USD***)

Moringa leaf, Bamboo grass-**
13,637Jewel vine, Indian gooseberry,-**- 4,239
Kariyat, Butterfly pea
3SS3Bael, Long pepper
-**
555
1,276
- 5,771
4
SS4
Kaffir lime peel, Barbed grass
-**
229
1,653
- 6,792
5
SM1
Kariyat, Turmeric
-**
1,800
61,25032,1006
SM2
Cat whiskers plant, Turmeric
-**
758
2,619
- 13,014
7
SM3
Pandan leaf
-**
744
1,976
- 17,270
8
SL1
Stevia-**9,600
180,000
75,9549
FS1
Mixed herbs
LPG and Wood
9,733
1,520,781
113,228
10
FS2
SteviaWood
2,850
26,7192,571
11
FS3Kariyat, Stephania venosa,
Electricity
2,000
187,500
67,263
Curcuma zanthorrhiza
12
FS4
Butterfly pea, Sabah snake grass Electricity
650
14,2195,125
13FM1
Turmeric, Cassumunar ginger
Electricity
1,200
25,125
15,077
14
FM2
Turmeric, Pandan leaf
Electricity
1,243
14,1292,308
15FM3Ginger, Galangal
Electricity
1,609
13,134- 14,631
16
FL1
Mixed Tom Yum herbs
Electricity
375
28,125- 30,277
17
FL2
ChilliLPG
4,320
16,200- 10,018
Note: *The first code letter represents the traditional drying method (S = sun drying and F = fuel), the second
code letter represents solar dryer size (S = small, M = medium and L = large); **The enterprises used open sun
drying as a traditional method before investing in solar dryers; ***1 USD = 32 THB
1
2

SS1
SS2

1047

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 2 PBP and IRR of enterprises having positive NPV (a) and negative NPV (b).

Fig. 3 Total savings per annual product revenue of each enterprise.

Fig. 4FS4 could reduce the use of fuel and invested in asmall dryer, so it could achieve a positive NPV.
Figure 3 illustrates small solar dryer enterprises,
having low savings per annual revenue including
SS1, FS1, FS2 and FS3, had a positive NPV,
whereas enterprises having high savings per annual
revenue, namely, SS2, SS3 and SS4, had a negative
NPV. It reveals that the savings per annual revenue
did not indicate economic viability. However, theprice of the products affected economic feasibility.
According to the enterprises that had negative
NPV, except FL1, the price of their products waslow, less than 9 USD/kg. In contrast, the enterprises
with positive NPV had product prices higher than 9
USD/kg. Nevertheless, enterprise FL1, with anaverage product price at 75 USD/kg, had a negative
NPV because its annual production capacity was as
low as 375 kg. The results showed that the totalsavings gained per annual revenue did not affecteconomic viability and enterprises having low priced
products or low annual production capacity might
not be suitable for the investment.

Savings ratio of the enterprise group that
had positive NPV, negative NPV and allenterprises.

All enterprises that had an annual production
capacity less than 1,000 kg, except enterprise FS4,
had the PBP longer than the lifespan of the dryer.
They could hardly breakeven. However, enterprise
1048

SEE - Bangkok, Thailand, Nov.11-13, 2019

The group of the enterprises that had a positive
NPV gained savings of 30% from reduced fuel, 39%from reduced raw material loss, and 31% fromreduced labor cost (Fig.4). Thus, reduced raw
material loss played an important role providing
benefits to the enterprises.
The investment costs of the solar dryer invested
by each enterprise are presented in Fig. 5.

Enterprises with annual revenue higher than theinvestment costs would have a positive NPV.
Entrepreneurs could use annual revenues to decide
to invest in a greenhouse solar dryer. However,enterprise FM2, reporting annual revenues less thaninvestment costs, also had a positive NPV. FM2
could gain a positive NPV as a direct result of highsavings.

Fig. 5 Annual revenue and the investment cost of each enterprise.
cost. Its savings gained were low compared with theinvestment cost; thus, NPV was negative and IRR
was low at 2%. Thus, selecting the appropriate size
solar dryer is also an important factor to beconsidered for investing.
When comparing among three different sizes ofsolar dryers, a lower CO2 mitigation was related to ahigher mitigation cost. For example, enterprise FL1
had almost the same CO2 mitigation as enterpriseFS3, FS4, SS3, and SM2, but its mitigation cost wasmuch higher than the others because of the highinvestment cost of a large solar dryer. The enterprise
FL1 could reduce CO2 emission to a low amountcompared with high investment cost (Fig.5); thus,
the mitigation cost was as high as 1,383 USD/tCO2e.
From the case of enterprises FL1 and FL2, thesize of solar dryer was the factor that entrepreneurs
needed to consider because its investment cost could
affect either NPV or mitigation cost. When theenterprises invested in smaller solar dryers, whichstill matched their annual production capacity, atover 1,200 kg, they might achieve a positive NPV or
the mitigation cost would be decreased [5].

Carbon Dioxide Mitigation
Seven enterprises could reduce more than 130
tCO2e during 15 years of using greenhouse solar
dryers (Fig.6). Eighty-six percent had a positive
NPV, except FL2. The highest CO2 mitigation wasfrom enterprise FS1. This enterprise alone could
reduce 956 tCO2e, with 402 tCO2e from reduced fueland 554 tCO2e from reduced waste due to the highamount of fuel replaced and waste reduced. All
these seven enterprises could reduce CO2 up to
1,318 tCO2e from reduced fuel and 929 tCO2e fromreduced waste.
Among nine enterprises using fuel (LPG, wood,and electricity), FS1, FS2 and FL2 could reducehigh CO2 from the use of LPG or wood fuel at thefirst, the third and the fourth rank, respectively. It
showed that enterprises which could reduce the useof LPG or wood fuel tended to have high CO2
mitigation.
Although enterprise FL2 was in the top seven
mitigation rankings, it had a negative NPV. The
enterprise invested in the large solar dryer at a high1049

1,000
900
800
700
600
500
400
300
200
100
0
-100

10,000
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
-1,000Mitigation cost (USD/tCO2e)

15 years CO2 mitigation (tCO2e)

SEE - Bangkok, Thailand, Nov.11-13, 2019

FS1 FM1 FS2 SL1 FL2 FM2 SS1 FM3 SM1 SM2 FS3 FL1 FS4 SS3 SM3 SS4 SS2Fuel mitigation

Enterprise
Waste mitigation

Mitigation cost

Fig. 6 CO2 mitigation during 15 years of solar dryer life time.
[2] Chauhan P. S., Kumar A., and Nuntadusit C.,
Thermo-environomical and Drying Kinetics ofBitter Gourd Flakes Drying under North Wall
Insulated Greenhouse dryer, Solar Energy, Vol.
162, 2018, pp. 205-216.
[3] VijayaVenkataRaman S., Iniyan S., and Goic R.,
A Review of Solar Drying Technologies,
Renewable and Sustainable Energy Reviews,
Vol. 16, Issue 5, 2012, pp. 2652-2670.
[4] de Gracia A., Barzin R., Fernández C., Farid M.
M., and Cabeza L. F., Control Strategies
Comparison of a Ventilated Facade with PCM –Energy Savings, Cost Reduction and CO2
Mitigation, Energy and Buildings, Vol. 130,
2016, pp. 821-828.
[5] El Hage H., Herez A., Ramadan M., Bazzi H.,
and Khaled M., An Investigation on Solar
Drying: A Review With Economic andEnvironmental Assessment, Energy, Vol. 157,
2018, pp. 815-829.
[6] Janjai S., A Greenhouse Type Solar Dryer for
Small-scale Dried Food Industries: Development
and Dissemination, International Journal ofEnergy and Environment, Vol. 3, Issue 3, 2012,
pp. 383-398.
[7] Christersson M., Vimpari J., Junnila S.,
Assessment of Financial Potential of Real Estate
Energy Efficiency Investments–A Discounted
Cash Flow Approach, Sustainable Cities andSociety, Vol. 18, 2015, pp. 66-73.
[8] Saravanan D., Vincent H. W., Kumarasamy S.,
Life Cycle Cost of Solar Biomass Hybrid Dryer
Systems for Cashew Drying of Nuts in India,
Environmental and Climate Technologies, Vol.
15, Issue 1, 2015, pp. 22-33.
[9] Thailand
Greenhouse
Gas
Management
Organization,“Emission
Factor”,
2019,
http://thaicarbonlabel.tgo.or.th/products_emission/products_emission.pnc, 03 June, 2019. (inThai)

CONCLUSIONSThe enterprises with annual revenues higher thantheir investment costs of solar dryers would have apositive NPV indicating that the investment was
attractive. The enterprises that used fuel in the
traditional drying method should invest in small or
medium sized solar dryers because they tended toobtain a positive NPV. The enterprises with aproduct price less than 9 USD/kg or annual
production capacity less than 1,000 kg should notinvest due to the high possibility of obtaining anegative NPV. Enterprises that could substitute theuse of fuel by investing in solar dryers would gain
more benefits than enterprises using sun drying in
the traditional drying method. Most enterprises
showing CO2 mitigation higher than 130 tCO2e
during 15 years had a positive NPV. To gain themost benefit regarding both economic andenvironmental aspects in terms of a positive NPV,
high IRR and short PBP together with high CO2
mitigation, entrepreneurs should select the mostappropriate size solar dryer for their investments.
However, other uncertain parameters, including
inflation rate and enterprises’ marketing strategies,
should be considered in a future study.
ACKNOWLEDGEMENTS
The authors would like to thank the Departmentof Alternative Energy Development and Efficiency
for inviting and funding Silpakorn University under
the solar dryer subsidy program.
REFERENCES[1] Janjai S. and Tung P., Performance of a Solar
Dryer Using Hot Air From Roof-integrated Solar
Collectors for Drying Herbs and Spices,
Renewable Energy, Vol. 30, Issue 14, 2005, pp.
2085-2095.

1050

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

AIR POLLUTION CONCENTRATION AND COST
FOR THE DIFFERENT ROAD CORRIDORS
LasminiAmbarwati, Amelia K. Indriastuti2
Faculty of Engineering, Brawijaya University, Malang, East Java, Indonesia
2
Faculty of Engineering, DiponegoroUniversity, Semarang, Central Java, Indonesia
1

ABSTRACT
A lot of disadvantages and disadvantages are caused by the rapid growth of transportation in developing
countries. One of advantages is increasing mobility giving negative impact such as decreasing a roadperformance as well as rising air pollution. Currently, a suitable policy has not formulated to overcome air
pollution concentration related to different road corridors. Therefore, traffic demand management (TDM) should
be arranged in order to decrease air pollution regards to the different road corridors. This study aims tounderstand the influence of traffic flow to air pollution concentration and cost in several types of road corridors
such as business and residential places in the city of Malang, East Java, Indonesia. This analysis is based on
IHCM (Indonesian Highway Capacity Manual) and an approach based on speed in each road corridor. Highway
performances of business place have bad service level. On the other hand, road corridor as residential place gives
good service level. Based on speed analysis, huge air pollution concentration such as NO and CO 2 givesignificant negative impact on road corridor as business area. As consequences of the concentration, roadcorridor as business place give high air pollution cost. The local government should have an effort to reduce air
pollution cost by implementing some strategies of TDM such as arrangement of green space, setting up roadpricing, minimizing side friction, etc.
Keywords: Highway performance, Air pollution concentration, Air pollution cost, Road corridor, Travel
distance, Speed analysis.

The largest single source of global air pollution
comes from the vehicle fleet. Carbon 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].
Sustainable transport concept should be
implemented in big cities, such as Malang City as
the recommended study area. This city is the second
biggest city in East Java Province - Indonesia, as
tourism and education city, and an inter-province
connection city. The growth of motor vehicles andtrips around Malang and surrounding areas (known
as Greater Malang) is significantly increased, thus
has the effects on high traffic volume, as recorded
253,904 and 274,664 vehicles in 2006 and 2007
respectively. This condition stimulates the worse air
quality as a result of the increasing motor vehicle
emission, higher road safety risks and discomfort forpeople.
Some activities in concentration areas, theimpacts deteriorate, since the activities concentration
triggers traffic movement. Different land use
generates different amount of traffic, thus causes
different level of traffic delay and air pollutant.
An insufficient number of studies haveconsidered the air pollution parameters on different
road corridors and economic losses due to reduction

INTRODUCTION
Transportation is not the main contributor of air
pollutant; however, transportation is the dominantsector that emits 70% air pollutant to the ambient airof urban area [1]. One of the pollutant parameters is
CO which is approximately 59.2% emitted frommotor-vehicle emission due to traffic congestion.
CO emission in human body will react withhemoglobin (Hb) in their blood and further will form
CO2Hb. In concentration up to 2-5%, this element
develops unusual response to five senses andinfluences the central nerve [2]. CO parameter will
decrease air quality causing other impacts such aseye irritation, breath infection, air aesthetic, acid rain,
worst visibility that may cause accident, etc. [3].
A strategy was held to reduce air pollution
considering on sustainable transport concept.
Sustainable transportation refers to transportation
with low impact on environment, social andeconomic aspects. An integrated environment aspect
into traffic management becomes a vital necessity inthe arrangement of transport policies in order toreduce air pollution and to improve highway
capacity [4]. Without a strategic transport system
and land use arrangement, the travel demand andemission level of air pollutant will significantly rise
[5].
1051

SEE - Bangkok, Thailand, Nov.11-13, 2019of air quality. Therefore, this study has attention on
assessment of air emission parameters on different
road corridors and air pollution cost imposed onroad users.
The study aims to reveal the disadvantage of air
pollution caused by transportation using cost
analysis of air pollutant. Since different land use
produces different level of air pollutant as mentioned
before, the analysis is conducted for three areas in
Malang City with different combination of land use
type and road function. The results of this research
are expected to diminish air pollutant in those areas
and as a reference in traffic management policies.
This paper is organized as follows: datacollection and methodology are elaborated in
Section ‘‘Methods” consisting of backgroundinformation on the existing traffic characteristics andhighway performance on 3 road sections withdifferent road corridors in the city of Malang.
Section ‘‘Results” details an analysis of estimating
traffic
characteristics
relatedtohighway
performance, measurement of air pollution values aswell air pollution cost and concentration. Thissection discusses the estimation of emission
parameters and compares the impacts of each
emission parameter as well as air pollution cost foreach parameter. Section ‘‘Conclusions andrecommendations” presents conclusions andrecommendations for further research.

data was collected from the Department of theEnvironment.

Fig.1 The study area (Malang City), located in EastJava Province, Indonesia and location of three roadsectionsPrimary data:
Road geometriccondition
Traffic flow
Speed

Speed





Distance

Traffic Flow

Existing
Traffic

Performa

METHODS

Secondary data:
Road network map
Air ambient quality
Socio-economic
condition

Air Pollution Emission of eachvehicleTravel distance

Total Air
Pollution
Emission

Traffic
Performance

Research Framework

Air Pollution
Cost

The case study area is Malang City, comprising 5
districts and 57 villages (Fig.1) with the total area of
110 km² and population of 861,414 [7]. The average
population density in 2017 was estimatedapproximately 7,826 people per km². High traffic
volume loads highway networks serving as gateways
to the city center due to expansion of housingdevelopment in the suburbs.
This study is focused on some different roadcorridors with high traffic generation on different
road function, in which the areas are around Kyai
Tamin, Sulfat, and SP Soedarmo Streets. Thosestreets are some of major access roads to the city
center, as shown in Fig. 1.
Primary data was collected by surveying traffic
counting, speed study and road geometry for threeroad sections with different road corridors as
business areas (Kyai Tamin Street), residential areas(Sulfat Street), warehousing areas (SP Darmo Street).
Vehicle emission values were determined based on
traffic volume and speed. The surveys were carriedout on Saturday and Monday during peak and offpeak period (06.00-09.00 am, 11.00-14.00 pm, and15.00-18.00 pm) in 15 minutes intervals. Secondary

Traffic Performance
Improvement,
Air Pollution Cost Decrease

Fig. 2 The research framework
The research framework consists of survey ofprimary and secondary data in order to assess trafficcharacteristics, air pollution emission and travel
distance. These data are analyzed to estimate traffic
performance and concentration and cost for each
emission parameter. The result is expected to reduce
air pollution emission and to increase the beneficial
received from improvement of traffic performance
as illustrated in Fig. 2. The result will berecommended the strategies to improve traffic
performance and to reduce air pollution cot imposedto the road users.
Assessment of Highway Performance
Two main parameters determined in this study
are traffic performance and air pollution cost. The
1052

SEE - Bangkok, Thailand, Nov.11-13, 2019traffic performance is analyzed using the Indonesian
Highway Capacity Manual [8] and the air pollution
cost is calculated based on speed [9].
The traffic performance indicator is the degree ofsaturation, which is calculated as follow:
C = Co x FCw x FCsp x FCsf x FCcs
(1)
DS = Q/C(2)
in which C is the capacity (pcu/hour), Co is thebasic capacity (pcu/hour), FCw, FCsp, FCsf, andFCcs are the correction factors due to road width,traffic distribution (directional split), side
friction, and city size, respectively, DS is thedegree of saturation, and Q is the traffic flow
(pcu/hour).
The future traffic flow is predicted using the
growth of traffic volume.
Assessment of Emission Load

Table 1. Emission value for each vehicle(gram/person-mile)

Calculation of Air Pollution Cost
The air pollution cost is approached by several
steps as follows: air pollution cost can be obtainedfor each gas emission type of each vehicle type. The
air pollution cost is determined by the equation 4.
Air pollution cost ($) =air pollution cost
constant ($/veh-mile) x peak hour traffic
volume (veh) x road length (mile)(4)

Passengers

HC

CO

NOx

SOx

PM

2

5

12

na

-

-

Automobile
Diesel Bus(medium orlarge bus,
truck)

(1)

3

3,15

23,57

1,91

0,07

(2)
0,01

30, 55, 2

0,11

1,50

0,67

0,09

0,17

Source: [9]The air pollution cost constant is shown in Table 2.
Table 2. Air pollution cost content ($/veh-mile)
HC

CO

7.20

Air pollutant emissions of each vehicle types
are assessed based on traffic speed, whereas thecomposition of air pollutant is based on traffic
volume for each point observation. Thus, the valuesof pollutant can be calculated based on traffic
volume and traffic composition [9], as follows:
Air pollutant (gr) =traffic flow of eachvehicle class (veh) x emission value for eachparameter for each type of vehicles (g/veh.mile) x
road length mile (3)Unit emission loads (g/veh mile) are various fordifferent modes and different speeds. Relevant
emission substances are CO, CO2, NOx, SO, HC and
PM. The number of passengers was based on the
average vehicle occupancy, i.e. automobiles/privatecars, minibuses, medium buses, large buses, trucks
and motorcycles accommodate 3 passengers, 8
passengers, 30 passengers, 55 passengers, 2passengers, and 2 passengers respectively. The
standard value of motorized vehicle emissions basedon traffic volume and traffic composition is shownin Table 1.

Mode
Motorcycle

NOx

SOx

PM

12
0.60 – 8.40
0.01 – 0.36
0.08-0.13
Source: [9].
Note : the value will convert from USD into IDRRESULTS
Vehicle Speed
Speed for each vehicle type (motorcycle, car, andheavy vehicle) on each road is analyzed for 85percentile and is shown in Table 3. Generally, thelowest speed occurs on SP. Sudarmo Street in themorning and evening time, on the other hand, in thenormal time (11.00 am-14.00 pm), all types ofvehicles pass on Kyai Tamin Street within lowest
speed.
Table 3. The 85-percentile speed data on observed
roads
Kyai Tamin
Time

06.00 - 09.00

11.00 - 14.00

15.00 - 18.00

Vehicle type

Motor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselSP Sudarmo

SulfatSaturdayMondaySaturdayMondaySaturdayMonday

44.4
36.8
37.0
21.4
19.4
18.5
41.0
35.4
31.0

44.6
35.2
33,8
23.6
19.8
17.6
36.8
35.4
30.0

39.0
34.2
28.2
42.0
36.8
32.0
41.6
37.0
31.0

31.5
29.4
24.4
37.4
31.6
26.2
33.0
30.4
24.8

41.0
39.2
37.0
41.6
40.6
37.0
42.0
38.6
32.2

44.0
38.4
37.3
41.0
36.8
35.4
43.2
39.4
34.0

Traffic Performance (Level of Service)
Traffic performance is relied on the road capacity
and traffic flow, thus road capacity is depended onroad geometry and the presence of the side friction
which is related to the activities around the road.
The side friction value is affected by the number ofpedestrians, stopping vehicles, car parking, andaccessing vehicles along the road [8]. The highway
performance of each road is as seen in Table 4. Kyai
Tamin and Sulfat Street have good service level
which is indicated by degree of saturation (DS) ≤Evaluation of the results
The results are evaluated to produce two
expected recommendations, that is an action tocontrol air pollution impact and, at the same time, tosolve the traffic congestion considering theenvironment and transportation aspects.

1053

SEE - Bangkok, Thailand, Nov.11-13, 2019

0.7. On the other hand, the level of service of SP
Sudarmo Street approaches traffic jam since hugetraffic within heavy vehicles loads this road.

StreetTime

Type of vehicle

06.00 - 09.00

11.00 - 14.00

Table 4. The level of service of the observed roads

15.00 - 18.00

Road

KYAI TAMINSPSOEDARMOSULFAT

Time

Capacity(C )(pcu/hour)

06.00 - 09.00
11.00 - 14.00
15.00 - 18.00

2184.642210.66
2252.0906.00 - 09.00
11.00 - 14.00
15.00 - 18.00

2080.38
2208.06
2354.2906.00 - 09.00
11.00 - 14.00
15.00 - 18.00

3476.893575.98
3570.1606.00 - 09.00
11.00 - 14.00
15.00 - 18.00

3387.933426.393538.6806.00 - 09.00
11.00 - 14.00
15.00 - 18.00

3007.56
3166.50
3002.0406.00 - 09.00
11.00 - 14.00
15.00 - 18.00

2868.453156.683093.82

Traffic
Flow (Q)(pcu/hour)
Saturday
1040.60
1019.55
1005.90
Monday1335.701239.30
1141.15

Saturday
2773.052308.35
2623.70
Monday3313.75
2497.102889.95
Saturday
1722.90
1815.201505.20
Monday2144.501517.90
1620.30

Road
width
(m)

Degree ofSaturation(DS=Q/C)

Level ofService
(LoS)

8.00
8.00
8.00

0.48
0.46
0.45

C
C
B

8.00
8.00
8.00

0.64
0.56
0.48

C
C
C

10.00
10.00
10.00

0.80
0.65
0.73

D
C
C

10.00
10.00
10.00

0.98
0.73
0.82

E
C
D

8.00
8.00
8.00

0.57
0.57
0.50

C
C
C

8.00
8.00
8.00

0.75
0.48
0.52

C
C
C

KYAI TAMIN
06.00 - 09.00

11.00 - 14.00

15.00 - 18.00
StreetTime

06.00 - 09.00
S. PRIYO
SOEDARMO

11.00 - 14.00

15.00 - 18.00
StreetTime

06.00 - 09.00

11.00 - 14.00

15.00 - 18.00

06.00 - 09.00

Emission Parameters for Different Road
Corridors
From the analysis, concentration of each
emission parameter and cost are determined on
different road corridors. The emission concentration
is based on vehicle speed investigated. A significant
difference in emission concentration and cost is
described in Table 5 and Table 6. The value of air
pollutant can be analyzed using the Equation (3) andTable 1.
From the analysis, it can be concluded that theamount of CO2 pollutant is major emission
parameter due to predominantly due to increasing
numbers of motorcycles and private cars. Current
mode choices are private car (30%), motorcycle(66%), and other vehicle types (4%, minibuses,
buses and trucks).
Table 5 explains that CO2 is the major
component of the motorized vehicle emission. Thus,
motorcycle gives the largest contribution to air
pollution, followed by automobile. The amount of
air pollution is influenced by the characteristics ofthe vehicle engine.
The air pollution costs imposed to users on eachstreet can be calculated after the value of air
pollutant on Kyai Tamin St. Sunandar P.Sudarmo St.
and Sulfat St. were identified, using the Equation(2), and converted into IDR (1 USD = 13,500 IDR).
The results of air pollution cost are explained inTable 6.
Table 5. Analysis of air pollutant value for eachvehicle unit based on speed measured (gram)

SULFAT

11.00 - 14.00

15.00 - 18.00

SULFAT

06.00 - 09.00
11.00 - 14.00

Motor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselType of vehicle
Motor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselType of vehicle
Motor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle
Automobile
DieselMotor cycle

HC
Saturday
15,290.6
3,090.6
27.4
16,909.0
5,702.4
24.711352.0
3,580.2
26.8
Monday17,923.9
4,972.8
82.5
21,975.0
4,989.4
50.5
17,061.2
4,998.7
107.1
HCSaturday
39,368.7
8,062.65
214.7525,665.9
11,492.0
92.9
29,447.0
11,492.0
88.7
HC
Monday61,659.9
11,648.6
179.6
27,808.6
13,353.7
195.0
43,059.6
13,509.0
201.6
Saturday
25,171.2
5,910.0
40.6
20,787.3
7,850.9
54.4
17,165.9
7,412.1
17.7
Monday30,109.3
8,552.3
35.2
22,335.5

CO

NO

CO2

11,7620.0
23,634.0
6.8
146,240.0
52,272.0
24.7
90,816.0
38,610.0
10.7

13,585.1
2,099.8
84.9
8,545.9
2,898.7
234.6
9,411.8
3,299.4
182.2

915,083.6
151,439.4
27,400.0
812,089.0
299,059.2
55,698.5
629,520.0
236,574.0
57,754.0

139,174.2
36,960.0
16.5
169,940.0
44,642.0
25.2
130,468.0
37,152.5
17.8
CO16,166.7
3,185.3
224.4
11,427.0
2,429.1
414.1
11,591.5
3,201.8
267.7
NO

1,071,922.5
229,152.0
73,332.6
1,057,730.0
256,691.5
121,452.5
835,998.8
230,345.5
82,288.5
CO2299,952
82,606.8
17.18
202,874.0
87,880.0
27.9
235,576.0
87,880.0
35.5
CO28,620.42
6,648.15
558.3521,514.1
7,807.8
659.6
24,414.2
7,807.8
603.2
NO

2,018,427
488,002.5
179,101.5
1,401,246.0
563,108.0
195,554.5
1,632,970.0
563,108.0
191,148.5
CO2443,650.5
82,572.0
10.0
212,654.0
125,394.5
104
303,012.0
99,864.0
23.7

35,191.3
6,723.7
748.5
18,893.5
7,719.1
936.0
24,666.2
7,729.2853.9

2,684,461.5
517,549.5
195,109.0
1,296,371.5
560,855.4
263,250.0
1,812,756.0
634,410.0
247,281.0

207,552.0
45,901.0
10.2
166,298.0
65,424.0
13.6
135,686.5
56,905.8
5.3

20,401.9
4,550.7
125.9
17,234.5
6,514.6
168.6
14,389.1
5,618.9
125.7

1,435,200.0
306,335.0
40,600.0
1,152,747.5
455,184.0
54,400.0
937,183.5
376,582.5
37,258.5

229,512.4
65,703.0
3.2
184,169.5

26,587.1
6,570.3
99.2
18,103.5

1,778,153.0
437,658.0
31,760.0
1,234,327.5

Table 6. Analysis of air pollutant cost for eachvehicle unit based on speed measured (IDR)
Street

Time

KYAI
TAMIN

06.00 - 09.00
11.00 - 14.00
15.00 - 18.00

606,909.45
746,285.05
493,180.28

06.00 - 09.00
11.00 - 14.00
15.00 - 18.00

757,598.30
890,648.84
730,819.39

Time
SP
SUDARMOSULFATHC

06.00 - 09.00
11.00 - 14.00
15.00 - 18.00

HC
4,712,504.23
3,684,344.50
4,057,902.11

06.00 - 09.00
11.00 - 14.00
15.00 - 18.00

7,268,442.42
4,090,501.66
5,614,938.09

06.00 - 09.00
11.00 - 14.00
15.00 - 18.00

2,708,767.78
2,497,329.87
2,140,753.23

06.00 - 09.00
11.00 - 14.00
15.00 - 18.00

3,368,073.49
2,525,611.88
2,405,425.96

cost of emission gas (IDR)
CONO
Saturday
7,762,001.19
324,945.44
10,909,194.59
240,657.20
7,112,288.89
265,676.60
Monday9,679,128.66
403,381.10
11,792,239.17
294,043.58
9,211,392.06
310,343.56
Saturdaycost of emission gas (IDR)
CO
NO
63,065,354.85 2,214,694.80
47,933,646.58 1,853,349.54
53,325,629.53 2,029,138.98
Monday86,746,266.93 2,637,307.01
55,742,410.71 1,702,956.80
66,415,601.44 2,055,359.06
Saturday
36,768,053.96 1,364,232.20
33,616,196.46 1,301,088.57
27,938,733.17 1,095,238.04
Monday42,825,213.11 1,809,108.73
34,072,584.08 1,240,160.60
30,851,385.15 1,229,131.30

CO2

Air pollution
cost (IDR)

475,861.97
507,584.15
401,878.50

9,169,718.05
12,403,720.99
8,273,024.27

597,873.96
624,612.37
499,661.01

11,437,982.02
13,601,543.95
10,752,216.01

CO23,504,658.24
2,818,712.99
3,115,366.39

Air pollution
cost (IDR)
73,497,212.11
56,290,053.61
62,528,037.00

4,433,292.56
2,767,254.16
3,516,293.75

101,085,308.93
64,303,123.32
77,602,192.35

2,046,627.36
1,909,043.44
1,551,534.37

42,887,681.29
39,323,658.33
32,726,258.81

2,581,140.20
1,864,470.31
1,764,220.95

50,583,535.53
39,702,826.86
36,250,163.36

Tabel 7. The difference of air pollution cost
between existing speed and standard speed

1054

SEE - Bangkok, Thailand, Nov.11-13, 2019

StreetTime

Air pollution cost (IDR)
Existing speed (85%)
Standard speed
Saturdaydiferences

Kyai Tamin and Sulfat Streets have a slightly
goodroad performance (C service level) service
11.00 - 14.00
Rp 12,403,720.99 Rp 5,693,958.58
Rp 6,709,762.41
15.00 - 18.00
Rp
8,273,024.27 Rp 7,632,211.90
Rp
640,812.37 level. This level means that those roads have stable
KYAI
TAMIN
Mondayflow and speed, as well the movements are limited
06.00 - 09.00
Rp 11,437,982.02 Rp 9,166,813.48
Rp 2,271,168.54
by traffic volume. On the other hand, Priyo Sudarmo
11.00 - 14.00
Rp 13,601,543.95 Rp 7,601,303.56
Rp 6,000,240.39
15.00 - 18.00
Rp 10,752,216.01 Rp 9,166,813.48
Rp 1,585,402.53 Street has worse performance (E service level) at
Saturdaypeak hour meaning that traffic volume is
Rp 56,541,451.40
06.00 - 09.00
Rp 73,497,212.11
Rp 16,955,760.71
Rp 44,367,873.50 approaching value of road capacity and in unstable
11.00 - 14.00
Rp 56,290,053.61
Rp 11,922,180.11
Rp 45,572,276.29 condition, rarely traffic jam occurred. The highest
15.00 - 18.00
Rp 62,528,037.00
Rp 16,955,760.71
PRIYO
SOEDARMO
Mondaytraffic volume occurs at 07.15-08.15 in Monday
Rp 88,799,119.57
06.00 - 09.00
Rp 101,085,308.93
Rp 12,286,189.36(3,313 pcu/hour), due to a lot of activities done inRp
53,352,322.64
11.00 - 14.00
Rp 64,303,123.32
Rp 10,950,800.68
Rp 65,316,002.99 the morning in the road corridors.
15.00 - 18.00
Rp 77,602,192.35
Rp 12,286,189.36
Air pollution cost (IDR)
StreetTime
The highest air pollutant occurs on Priyo
Existing speed (85%)
Standard speed
diferences
SaturdaySudarmo Street at 06.00-09.00 a.m. consisting of
Rp 30,724,120.93
06.00 - 09.00
Rp 42,887,681.29
Rp 12,163,560.36
SULFAT
73,588.1 kg HC, 526,232.5 kg CO, 42,663.5 kg NOx
Rp 28,993,800.37
11.00 - 14.00
Rp 39,323,658.33
Rp 10,329,857.96
Rp 20,562,698.45 and 3,397,120 kg CO2. Furthermore, the maximum
15.00 - 18.00
Rp 32,726,258.81
Rp 12,163,560.36
Mondayair pollution cost imposed to road users is
Rp 26,297,751.00
06.00 - 09.00
Rp 50,583,535.53
Rp 24,285,784.53
approximately Rp 101,085,309.93 at speed
Rp 30,391,669.11
11.00 - 14.00
Rp 39,702,826.86
Rp 9,311,157.75
Rp 11,964,378.83 investigated, whilst Rp. 12,286,189.00 at normal
15.00 - 18.00
Rp 36,250,163.36
Rp 24,285,784.53
speed (40 km/hour).
Traffic management in order to improve traffic
From Table 6, the highest air pollution cost
performance is the program with minimizing sideoccurs on Priyo Sudarmo Street on Monday atfriction from car parking and stop of public transits.
06.00-09.00 a.m. (approximately 101,085,308.93
These efforts can decline negative impact as well air
IDR). Using comparison analysis of the standard
pollution cost declined.
speed (40 km/hour) and the existing speed, thedifference of air pollution cost is 88,799,119.57
IDR, as seen in Table 7. Briefly, the disadvantage
ACKNOWLEDGMENTS
cost of those three roads is about 89 million IDR atpeak hour. It means that this cost will be charged toThis research is supported grant from Directorateneighboring communities and road users.
of General Higher Education of Indonesia (DGHE).
Consequently, it is necessary to improve traffic
We would like to express deep thank to DGHE andperformance in order to decrease the air pollution
Department of Research, Brawijaya University.
cost.
We also want to thank to Dr. B.H. Setiadji, theAn action program of traffic performance
Associate Professor in Department of Civil
improvement that can simply occupied is toEngineering, Diponegoro University for his review
minimize side friction on road section, particularly
to the content of this paper and to M. Nuzulul Anwar
from the stopping public transit and car parking onin assisting to collect and process data.
the road, since the highest values of side friction is
occurred at most roads at certain time (normal andpeak hour condition). Side friction contributes in
REFERENCES
reducing highway performance in terms of roadcapacity.
[1] Thomas, L. and Cousins, W., The compact city:
The strategies to improve highway performance
successful, desirable and achievable? In Jenks,
are considered by equipping a lay-by-lay bus stop
M., Burton, E. & Williams, K. (eds.) thefor paratransit access, for passenger boarding andCompact City: A Sustainable Urban Form?
alighting. The strategies aim to prevent the traffic
Oxford: Oxford Brookes University, 1996.
flow blocked. Parking lots should be prepared at all[2] Yoky ES., The impact and influences of NOx tobuilding or office in order to decrease on-street
the human health, 2009. (in Indonesian)parking in around the areas. Finally, conducting 40<http://www.chem-iskm/hour as vehicle speed limit will support thistry.org/artikel_kimia/kimia_lingkungan/dampak
program.
-pencemaran-nitrogen-oksida-nox-danpengaruhnya-terhadap-kesehatan/ > Accessed 3
August 2009.
[3] Stoker, H. S. and Seager S.L., Environmental
Chemistry: Air and Water Pollution. London :Scott, Foresman and Co., 1972.
CONCLUSIONS
06.00 - 09.00

Rp

9,169,718.05

Rp

7,632,211.90

Rp

1,537,506.15

1055

SEE - Bangkok, Thailand, Nov.11-13, 2019[4] Armijaya, H., Application of Environmental
Capacity in Measurement Highway Capacity inIndonesia), Proceeding FSTPT III, Yogyakarta,
2000. (in Indonesian)[5] Lubis, H., Environment Effect to Transportationand Urban Land Use, Proceeding FSTPT III,
Yogyakarta, 2000. (in Indonesian)[6] Carley, M., & Christie, I., Managing sustainable
development. Routledge, 2017.

[7] Statistic Bureau of Malang City, the Figures ofMalang City in 2017 (in Indonesian).
[8] Department of Public Works, Republic ofIndonesia, Indonesia Highway Capacity Manual(IHCM), Indonesia, 1997.
[9] Litman, T., Transportation Cost Analysis.
Victoria, 1995.

1056

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

MICROBIOLOGICAL AND CHEMICAL PROPERTIESOF THE CHI RIVER, MAHA SARAKHAM PROVICE, THAILAND
Yuwadee Insumran 1, Jackaphan Sriwongsa1, Panuwat Ruenruangrit 2 and Supattra Chinakool1
1
Faculty of Science and Technology, Rajabhat Maha Sarakham University, Maha Sarakham
2
Faculty of Engineering, Rajabhat Maha Sarakham University, Maha Sarakham, Thailand

ABSTRACTContamination of water, particularly microbiological aspect has been emerging and influencing human health.
The aim of this research was to assess the pathogenic contamination of Chi River in Maha Sarakham Province,
Thailand. Surface water samples were collected from six stations along the river bimonthly from January to
December 2016. Coliforms and fecal coliform bacteria, pathogenic index bacteria, were enumerated by using
multiple-tube fermentation approach which was estimated the concentration as MPN index/100 ml. Results
indicated that the level of total coliform and fecal coliform bacteria were in the range of less than 4x102 to 9x103
MPN index/100 ml. Of 72 collected samples, 67 sample possessed the level of total coliform and fecal coliform
exceeding the water quality according to Thai Industrial Standard No.257-2549. Furthermore, chemical qualitiesof the water samples were determined and results found differently; water temperature = 21.20 -34.17, pH = 6.8410.00, DO=2.51-9.82 mg/l, BOD = 1.10- 6.07 mg/l, NO3-N = 0.30-1.13 mg/l, PO4-3-P = 0.08-0.47 mg/l). In
conclusion, these findings demonstrated the Chi River in Maha Sarakham had been contaminated and must be
managed and improved intensively for the purpose of human consumption.

Keywords: Coliform Bacteria, Fecal Coliform, the Chi River, Surface Water Quality

animal fecal material [3-4]. The presence of E.coli inwater indicates recent fecal contamination it may
show the possible presence of disease causing
Pathogens such as bacteria, Virus and Parasites. [5].
Indicating the presence of coliform bacteria in thewaters of Chi river in Maha Sarakham . Most of thepeople cause the diseases due to the unavailability offresh water for drinking purpose This crisis is due tothe unplanned urbanization and rapid growth of
population in Thailand. Finally, this leads to majorwater pollution and water crisis by generating manysources of contamination in water in our nation. This
research aims to evaluate the microbiological andchemical quality of the water from Chi river in Maha
Sarakham, Thailand.

INTRODUCTION
Chi River is one of the main rivers of thenortheastern Thailand. Its total length of 765 km is
recognised the longest river in the country.
Origination starts from the Phetchabun Mountains,
flows through Chaiyaphum, Nakhon Ratchasima,
Khon Kaen, Maha Sarakham, Kalasin, Roi Et,
Yasothon, Ubon Ratchathani and Sri Sa Ket
Provinces of Thailand. However, the river having alength of 60 km occurs in Maha Sarakham Province
across Muang, Kosum Phisai and Kantharawichai
districts. At least 6 irrigation projects have been
located along the river in Maha Sarakham andfunction as the water sources of domestic, agriculturaland industrial utilities. Interestingly, the main
consumption and drinking water in Muang and
Kosum Phisai depend on water of this river [1].
Coliform bacteria are a large group of various
bacteria species including both fecal coliform
bacteria and non-fecal coliform bacteria. The fecal
coliforms found naturally in the intestines of warmblooded animals, consisting pathogenic and a nonpathogenic species. Coliforms are frequently used as
hygiene indicators, and there are regulatory levels forthe presence of coliforms in water for consumption,consequently determination of coliforms plays animportant role in the quality control of water [2].
The presence of fecal coliform bacteria indicatescontamination of the water body by human and/or

MATERIALS AND METHODS
Sample Collection
Water samples at littoral and limnetic zones of six
stations along the Chi river Maha Sarakham Province,(Fig. 1) were separately collected bimonthly during
January-December 2016. Locations and geographicalpositions of the sampling stations are shown in Table
1. One liter of each sample was taken at the depth of
50 cm by using a water sampler, transferred to asterile water bottle which was kept in a cooling box
and then transported to a laboratory at Faculty of1057

SEE - Bangkok, Thailand, Nov.11-13, 2019

Science and Technology, Rajabhat Maha Sarakham
University. The samples were stored at 4°C andanalyzed within 24 hr.

Fig. 1 Sampling sites stations at the Chi river Maha Sarakham Province [6]Table 1 List of sampling locations at the Chi river Maha Sarakham Province
Stations
S01
S02
S03
S04
S05
S06

Locations
Kok, Kosum Phisai
Loeng Tai, Kosum Phisai
Tha Khon Yang, Kantharawichai
Koeng, Muang Maha Sarakham
Muang, Muang Maha Sarakham
Tha Tum, Muang Maha Sarakham

Geographic positions
16ₒ20.869” N 102ₒ57.770” E
16ₒ12.941” N 103ₒ07.864” E
16ₒ13.965” E 103ₒ16.124” E
16ₒ13.003” N 103ₒ20.438” E
16ₒ14.017” N 103ₒ25.846” E
16ₒ10.888” N 103ₒ 27.131” Esampling stations by using portable electronic meters.
On the other hand, concentrations of NO3- N, PO4-3P, as well as total organic carbon were analyzed
according to the method of [7] FAO (2009) at thelaboratory.
Dissolved oxygen analysis was carried out by
using a DO meter. Two bottles of each water sample
were set, one bottle was for DO analysis at day 0 andanother bottle was incubated at 20°C for 5 days.

Microbiological Analysis
Microbiological analysis was focused on ahygiene indicator by counting of coliform bacteria inwater samples. Most probable number approach wasused for total and fecal coliforms enumeration. The
number of positive tubes was compared to a standard
Most Probable Number chart that expressed in theterm MPN/100ml.
Chemical Analysis

RESULTS
Chemical properties of water samples, including
temperature, pH were measured directly at theMicrobiological Analysis
1058

SEE - Bangkok, Thailand, Nov.11-13, 2019

Chemical Analysis
Total of 72 water samples collected from the Chi
river located in Maha Sarakham Province wereanalyzed for total coliform and fecal coliform.
Results are presented in Table 2 and Table 3. Total
coliform concentration over a period of year ranged
from 1.20x103 to 6.25x103MPN/100 ml, respectively.
Fecal coliform concentration ranged from 4x102 and9x103 MPN/100 ml, respectively. Of the total water
samples, 93.05% possessed the total coliform andfecal coliform concentrations exceeding the water
quality according to Thai Industrial Standard No.2572549. It demonstrates that water contaminated humanand animal faeces.

Chemical analysis of the water samples resulted
in Table 4. The water temperature ranged from 21.20
to 34.17 ºC, while the water pH values were from 6.84
to 10.00. The suitable range of pH for potable water
is between 6.5 to 8.5 [8], however the pH valued
could be extended to 9.5. For dissolved oxygen
analysis, DO values were between 2.51 and 9.82 mg/l
and BOD determination ranged from 1.10 to 6.07
mg/l. The concentrations of nitrate were ranged
between 0.30 to 1.13 mg/l, while PO4-3-P value werefrom 0.08 to 0.47 mg/l.

Table 2 Total coliform of water sample collected from the Chi river Maha Sarakham Province
Sampling site
S01
S02
S03
S04
S05
S06

Littoral zone
Limnetic zone
Littoral zone
Limnetic zone
Littoral zone
Limnetic zone
Littoral zone
Limnetic zone
Littoral zone
Limnetic zone
Littoral zone
Limnetic zone

Jan
6.10x103
6.24x1034.24x103
4.19x103
5.40x1035.24x103
3.04x103
3.19x103
2.84x103
2.70x103
2.01x103
2.39x103Mar
5.98x103
6.04x103
4.10x103
4.14x103
5.30x103
5.36x103
3.82x103
3.79x103
2.94x103
2.89x103
2.50x103
2.00x103

Total coliform (MPN/100ml)
May
July
Sept
5.70x103
5.69x103
5.64x103
5.64x103
5.74x103
5.50x103
4.20x103
3.76x103
4.38x1033
3
4.56x103.43x104.50x1033
3
5.40x10
3.23x103.78x1033
3
5.35x103.20x103.70x103
3.30x103
2.78x103
2.90x1033
3
3.24x102.60x102.82x1033
3
2.40x102.20x101.90x1033
3
2.35x102.00x101.60x1032.10x103
1.50x103
1.20x1033
3
1.98x101.28x101.24x103Nov
5.50x103
5.64x103
4.25x103
4.56x103
6.10x103
6.25x103
3.76x103
3.50x103
2.78x103
2.54x103
2.50x1032.24x103

Table 3 Fecal coliform of water sample collected from the Chi river Maha Sarakham Province
Sampling site
S01
S02
S03
S04
S05
S06

Littoral zone
Limnetic zone
Littoral zone
Limnetic zone
Littoral zone
Limnetic zone
Littoral zone
Limnetic zone
Littoral zone
Limnetic zone
Littoral zone
Limnetic zone

Jan
4.90x103
4.6 x103
3.30x103
3.10x103
3.10x103
2.30x103
2.96x103
2.90x103
1.70x103
1.30x103
1.10x103
1.10x103

Fecal coliform (MPN/100ml)
Mar
May
July
3
3
4.30x104.60x104.60x1033
3
3.10x104.30x104.30x1033
3
2.70x102.66x102.20x1033
3
2.60x102.20x101.70x103
2.60x103
2.56x103
1.30x1033
3
2.20x102.10x101.10x1033
3
1.70x102.60x101.50x1033
3
1.30x101.70x101.70x103
1.90x103
1.60x103
1.20x1033
3
1.60x106.0x109.0x10332
1.40x108.0x106.0x1023
2
1.40x107.0x105.0x1021059

Sept
3.70x103
3.30x103
2.20x103
1.83x103
1.70x103
1.30x103
1.70x103
1.30x103
9.0x1027.0x1024.0x1024.0x102Nov
3.10x103
2.56x103
2.13x103
1.70x103
3.30x103
3.10x103
2.35x1032.10x103
1.20x103
1.70x103
1.30x103
1.10x103

SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 4 Chemical properties of water sample collected from the Chi river Maha Sarakham Province
Sampling site
S01

Littoralzone

Limneticzone

S02

Littoralzone

Limneticzone

S03

Littoralzone

Limneticzone

S04

Littoralzone

Limneticzone

Parameter
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)
pH

Jan
24.00
8.22
2.51
3.67
0.65
0.23
24.00
8.40
2.88
3.37
0.60
0.37
25.33
8.61
6.48
2.47
0.60
0.23
25.76
9.13
6.29
2.57
0.50
0.26
26.00
9.12
6.03
1.93
0.60
0.12
26.00
9.24
5.99
2.73
0.50
0.20
27.20
9.50
6.36
2.50
0.45
0.11
26.83
9.63

Mar
28.90
9.28
2.76
5.90
0.63
0.25
29.43
9.38
2.00
5.40
0.53
0.27
30.00
9.76
3.62
6.03
0.70
0.14
30.00
9.34
3.75
6.07
0.77
0.14
30.00
9.65
6.60
4.57
0.67
0.19
30.00
9.40
6.60
3.88
0.77
0.17
27.00
9.41
7.13
3.53
0.60
0.112
27.67
9.60
1060

May
30.53
7.53
4.06
4.27
1.10
0.26
30.57
7.43
3.80
4.45
1.13
0.23
31.97
7.67
4.03
4.07
0.97
0.25
32.00
7.80
4.13
4.27
1.05
0.26
34.00
7.57
5.54
2.88
0.70
0.12
33.00
7.77
6.14
2.43
0.83
0.12
34.00
8.03
5.76
3.08
0.60
0.07
34.00
8.00

Month
July
25.00
7.03
7.78
3.60
0.70
0.26
25.00
7.03
7.79
3.80
0.60
0.35
25.00
6.93
8.08
3.63
0.63
0.08
25.00
6.90
8.08
3.15
0.53
0.10
26.00
7.23
7.61
2.55
0.70
0.21
26.00
7.21
7.60
2.55
0.57
0.20
27.00
7.67
7.92
3.55
0.67
0.11
27.00
7.67

Sept
21.00
6.84
6.84
2.75
0.71
0.38
21.20
6.84
6.84
2.15
0.68
0.30
22.10
7.01
7.01
2.55
0.77
0.28
22.10
7.02
7.02
2.85
0.75
0.28
22.40
6.89
6.89
2.50
0.87
0.33
22.40
6.89
6.89
2.50
0.93
0.30
27.80
7.06
7.06
2.55
0.94
0.25
27.80
7.05

Nov
27.50
7.26
4.10
3.90
0.77
0.26
27.50
7.24
4.20
3.80
0.73
0.38
27.00
7.30
4.45
3.25
0.77
0.34
27.50
7.30
4.50
3.20
0.73
0.37
27.50
7.30
3.90
3.30
0.93
0.47
27.50
7.30
4.00
3.25
0.83
0.45
27.00
7.36
4.20
3.90
0.80
0.45
27.00
7.36

SEE - Bangkok, Thailand, Nov.11-13, 2019

Sampling site

S05

Littoralzone

Limneticzone

S06

Littoralzone

Limneticzone

Parameter
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)
T (ºC)pH
DO (mg/l)
BOD (mg/l)
NO3-N (mg/l)
PO4-3-P (mg/l)

Jan
6.37
2.90
0.45
0.19
27.07
9.72
7.41
1.93
0.40
0.13
26.00
9.75
7.48
1.10
0.40
0.12
26.00
9.62
7.23
2.03
0.40
0.16
26.00
9.81
7.41
1.00
0.30
0.15

Mar
7.33
3.73
0.57
0.13
29.47
9.90
7.42
2.88
0.43
0.31
28.53
9.78
7.45
3.07
0.43
0.23
29.17
10.03
7.45
3.63
0.57
0.40
29.00
10.00
7.43
3.63
0.53
0.40

May
6.15
3.53
0.67
0.08
33.67
8.03
5.92
3.43
0.60
0.15
34.00
8.03
6.27
3.30
0.60
0.16
34.17
7.73
5.32
2.57
0.50
0.14
34.00
7.80
5.01
2.53
0.50
0.15

Month
July
7.90
3.65
0.40
0.19
27.00
7.54
7.30
3.00
0.50
0.08
27.00
7.53
7.30
3.25
0.40
0.12
28.00
7.43
9.82
2.45
0.40
0.15
28.00
7.42
9.80
2.20
0.40
0.21

Sept
7.05
2.45
0.95
0.24
25.90
7.24
7.24
1.90
0.87
0.18
25.90
7.24
7.24
1.40
0.71
0.16
27.10
7.21
7.21
1.26
0.48
0.13
27.10
7.20
7.20
1.20
0.48
0.14

Nov
4.25
3.95
0.80
0.45
27.00
7.50
4.30
3.10
0.63
0.37
27.00
7.45
4.30
3.00
0.67
0.39
27.00
7.45
6.20
2.80
0.53
0.23
27.00
7.45
6.25
2.90
0.57
0.26

CONCLUSIONSACKNOWLEDGMENTS

The microbiiological and chemical analyses ofwater samples from the Chi river located in Maha
Sarakham Province demomstrated that the water is
not suitable for drinking. According to the Thai
Industrial Standard No.257-2549, water sample did
not comply the microbiological parameters. In
conclusion, these findings demonstrated the Chi
River in Maha Sarakham had been contaminated andmust be managed and improved intensively for the
purpose of human consumption.

This research was supported by National ResearchCouncil of Thailand, grant number 2556
NRCT531148. Authors would like to thank ourcolleagues from Faculty of Science and Technology
for their suggestions.

1061

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

EFFECTS OF CLIMATE CHANGE ON MILK YIELD AND MILKCOMPOSITION IN THAI CROSSBRED HOLSTEIN COWS

1

Doungnapa Promket 1*, Wootichai Kenchaiwong2, and Khanitta Ruangwittayanusorn1
Lecture of Animal science, Department of Agricultural Technology, Faculty of Technology, Mahasarakham
University, Thailand
2
Lecture of Veterinary Sciences, Faculty of Veterinary Sciences, Mahasarakham University, Thailand
ABSTRACTThe purpose of this research was to study the effects of climate changes on milk yield and milk compositionof Holstein crossbred in Thailand. This study uses milk yield and milk composition data (from 2013–2017) ofeach farm from a dairy cooperative member in Mahasarakham Province, Northeast of Thailand. This study useddata recording total milk production per farm each day and milk composition data: fat percentage (% Fat),protein percentage (% Pro), solid not fat percentage (% SNF) and total solid percentage (% TS) from 79 dairy
farmers in Mahasarakham Province. The temperature and relative humidity data for the period 2013–2017 wereobtained from the records of the meteorological center closest to each dairy farm. Using temperature and relative
humidity for calculate the temperature humidity index (THI). The effects of THI on milk yield and milk
composition in Thai crossbred Holstein cows were assessed by the procedure REG using SAS. The study
indicated that, the weather was hot and humid. The temperature ranged from 20.88 – 33.01 ° C. and averagehumidity was 72.59%. The highest temperature in April (30.85°C) and the lowest temperature in December(23.57 °C). Daily temperature and humidity data from provincial weather station were used to calculate thetemperature humidity index (THI). The highest THI (82.07) was in May. The relationship between THI and milkyield was negatively related. The slope value was -0.099, it meaning that when the THI value increased by 1 unit
the milk yield decreased by 0.099 kg / cow / day. The THI group for effect of THI on milk yield and milk
composition was set to 4 groups (THI 1 = THI ≤70, THI 2 = 74 ≤THI <70, THI 3 = 78 ≤THI <74, THI 4 = THI>
78). The highest THI values (THI 4) effect on low milk yield. In contrast, low THI value (THI 1 and THI 2)
effect on high milk yields. Effect of climate changes on Thai Holstein crossbred increase greatly with THI > 78
(THI 4). The climate change, the temperature and humidity increase effects on milk production of dairy cows to
decrease.
Keywords: Climate Change, Milk Yield, Milk Composition
The Temperature Humidity Index (THI) is
widely used in hot areas all over the world to assess
the impact of heat stress on dairy cows [3].
According to [4] the effect of heat stress on Thai
Holstein crossbreds increased greatly with parity andwas especially large after a THI of 80 for cows witha high percentage of Holstein genetics (HS ≥93.7%). Moreover, [5] showed that heat stressconditions indicated by mean daily values of THI>72 were determined during spring and summer
season. The daily THI at which milk production
started to decline for milk yield and milk
composition ranged from 65 to 76 [6]. When THI
reaches 72, milk production as well as feed intake
begins to decrease. Milk production during thesummer season will be lower than in the winterseason by about 10-40% [5].
In addition, heat stress could also cause changes
in milk composition, milk somatic cell counts (SCC)
and mastitis frequencies. A study comparing milk
protein fractions in milk collected from cows inspring and summer, found that the α-casein and β-

INTRODUCTION
Thailand, has a tropical climate with highambient temperatures and relative humidity.
Average temperature is 35.0–39.9 °C and averagerelative humidity is 72–74 % [1]. Dairy cows thathave experienced high temperature and humidity fora long time will reduce milk production and milk
quality. Heat stress could be significant reason
reduced dairy production in many countries. The
exposure of lactating dairy cows to high ambient
temperatures, high relative humidity and solar
radiation for extended periods decreases their ability
to disperse heat. Under heat stress conditions,lactating dairy cows exhibit several physiologicalresponses including a voluntary reduction of feedintake, an increase in maintenance requirements,
decrease in milk yield, and milk composition [2]. In
addition, heat stress also effects the health of dairy
cows because they are at high temperature andhumidity and will not be able to maintain balance ofthe body due to heat stress.
1062

SEE - Bangkok, Thailand, Nov.11-13, 2019

casein in serum decreased in the summer season [7].
Some studies have estimated the genetic
components for both milk yield and reproduction
traits under heat stress. The results showed an
unfavorable genetic relationship between THI and
productive and reproductive traits. Those findings
indicate that the intensive selection (especially formilk production traits) applied to dairy cows might
have led to higher heat stress susceptibility in theseanimals [8]. Therefore, the objective of this research
was to study the effects of climate changes on milkyield and milk composition of Thai crossbred
Holstein cows in Thailand.

The means of milk yield and milk composition
were analyzed by PROC MEANS using SAS 1998.
[13]
The relationships between THI and milk yieldand milk composition assessed by the procedure
REG in SAS version 8.02 [10].
RESULTS AND DISCUSSION
Climatic Condition in Mahasarakham Provinceof Thailand
Climatic conditions in Mahasarakham Province,
Thailand could be characterized as hot and humid
with temperature between 23.57 – 33.85 °C andmean relative humidity of 72.59 % (Table 1). The
highest temperatures occurred between April– May(30.85 – 30.44°C) and lowest in December(23.57°C). The THI was highest in May (82.07),
associated with the summer season and was lowest
in December (71.66) in the winter season (Fig 1).
The average of milk/day was 12.69 kg. The milk
composition had average values of %fat, %protein,%SNF, and %TS of 3.47% 2.90% 8.33% and11.79%, respectively. The research of [11] reported% fat and %protein from their study as 3.91% and3.10% which is higher than this study. Milk
production from this study was lower because it was
the milk yield from small dairy farms and of poor
farm management. Moreover, THI from this study
corresponded with values of 72 - 80 reported [12]from Mahasarakham province, with an average
higher than the critical point at THI 75. [4] reported
that, for third parity, test-day milk yield started to
decline above a THI of 74 for cows with ≥87.5%
Holstein genetics and declined more rapidly above a
THI of 82.

MATERIALS AND METHODS

Data and Data Preparation
This study uses data to record total milk
production per farm each day and milk composition
data: fat percentage (% Fat), protein percentage (%Pro), solid not fat percentage (% SNF) and total
solid percentage (% TS) from farms of the Khok
Kao Dairy Cooperative Limited (79 farms) in
Mahasarakham Province. Data was collected fromJanuary 2013 until December 2017. All the dairy
farms were managed and maintained in the same
way and all dairy cows were raised in an open
house. The diet was mixed and fed as TMR. The
ratio of concentrate to forage was 4:6 based on DM
content. Cows were milked 2 times per day at 06.00
a.m and 17.00 p.m using a milking machine.
The temperature and relative humidity data (fromJanuary 2013 – December 2017) obtained from therecords of the meteorological center closest to eachdairy farm based on postal code. The weather
information included daily temperature and relative
humidity recorded every 3 h, which were used to
calculate the temperature humidity index (THI) by
using the equation bellow [9].

Table 1 Data structure of milk production and milk
composition in Thai x Holstein crossbreeds
Variable
N
Mean
SD.
Min
Max
Milk/day(kg)
3438 12.69
5.03
5.27 37.07
Fat (%)
2610
3.47
0.59
1.65 10.72
Pro (%)
2682
2.90
0.45
2.13 22.87
SNF (%) 2621
8.33
0.85
2.69 13.82
TS (%)
2609 11.79
1.10
3.92 18.77
Ta (°C)3746 27.79
2.45
23.57 30.85
RH (%)
3746 72.59
6.97
63.21 82.73
THI3746 78.34
3.70
71.66 82.07

THI = (0.8*Ta) + (RH/100)*(Ta-14.4) + 46.4

Where Ta is temperature in °C and RH is relative
humidity as a percentage.
The THI values were divided into 4 groups asfollows:- THI 1 is THI ≤70, THI 2 is 74 ≤THI<70,
THI 3 is 78 ≤THI<74 and THI 4 is THI > 78.
These THI groups (group 1–4) were used for
estimating the effects of THI on milk production andmilk composition in dairy cattle.
Statistical Analysis

1063

SEE - Bangkok, Thailand, Nov.11-13, 2019

Fig. 1 The average THI in each month of theNortheast of Thailand.

The relationship between THI and
Milk composition

Fig.2 The relationship between THI and milk/day
yield, % fat in Thai crossbred Holstein cows

Rate of decline of milk and milk composition

Milk andThe Slope (Fig.2) is rate of decline on milk yieldand milk compositions. This regression indicates
that, in general, for each point increase in the THI
value, there was a decrease in milk yield of 0.099
kg/ cow/ day (slope -0.099). A large part of thevariation in milk yield could therefore be attributed
to heat stress. Hot weather conditions are associatedwith reductions in dairy cow feed intake and milkyield [13]. In addition, it can be seen that when the
THI value is increased, the % protein value will be
reduced 0.004%. The results of this study show thatdairy cows suffer from heat stress (higher THI),
resulting in reduced milk yield. However, theincreased THI values effected an increase in % fat,
% SNF and % TS values but did not affect %protein (Table 2). Because of the genetic correlation
between the milk yield and milk composition value
in milk (%fat, %SNF and %TS) is negative genetic
correlation. Approximated genetic correlations
between fat and milk production traits in first parity
of Canadian Holsteins [14]. The results showed that
average daily genetic correlations were negative forthe fatty acid groups with milk production (−0.62 to−0.59) and with protein yield (−0.32 to −0.25). The
research of [3] calculated correlations indicated thatmilk yield was negatively genetic correlated to THI(r = –0.75). Moreover, the THI values one, two andthree days prior had a greater effect on milk yieldthan the same day measure. The respective
correlation values between milk yield and THI were–0.83, –0.87, –0.89.

Fig. 2 shows the relationship between THI andmilk yield and milk compositions in Thai crossbred
Holstein cows. The negative slope of the regression
line indicates that milk yield decreases as THI
increases. The equation for predicting milk is Milk
production (kg/cow/day) = -0.795(X) + 81.82 (R2 =0.361). However, when the THI value is increased,
the % fat value increases (Fig. 2). This may be
because the % fat value has a negative genetic
correlation with the milk yield (data not showed).
Season, especially the high-temperature season,significantly affected milk production and milk
composition. The Wood equation was appropriate
for a quantitative description of seasonal variation inmilk composition in individual cows or herds. Thechanging patterns of milk composition and related
indices in different months provide scientificevidence to reasonably improve the feeding
management and nutritional supplementation ofChinese Holstein cows [11].

1064SEE - Bangkok, Thailand, Nov.11-13, 2019

Table 2 The relationship of THI on Milk yield and
Milk composition in dairy cattle
traitsMilk/day(kg)
Fat (%)Pro (%)
SNF (%)
TS (%)

N

Slope

3437

-0.0990.03

Pvalue<0.001

2610
2628
2621
2609

0.016
-0.004
0.022
0.038

0.002
0.005
0.006
0.003

<0.0010.164<0.001<0.001values in milk having a negative correlation with themilk production. Therefore THI 1 (THI ≤70) resultsin the highest values of milk/day thus, resulting in
low %Fat %SNF and %TS values in milk.
The research report that the third parity, test-day
milk yield started to decline after a THI of 74 forcows with ≥87.5% Holstein genetics and declined
more rapidly after a THI of 82 [4]. Another report inthree climactic regions (East, Mediterranean andcentral) Croatia. Found that heat stress conditions
indicated by mean daily values of THI >72 were
present during spring and summer season in all
regions [5]. Moreover, high THI conditions were
negatively associated with milking frequency andmilk yield in pasture-based automatic milking
systems and that research into management andinfrastructure (cow cooling) in these systems iswarranted to reduce production losses [15]. Dry
matter intake and milk yield declined linearly withrespective increases in air temperature or THI during
the hot period and milk temperature increased
linearly with increasing air temperature. Dry matterintake and milk yield both exhibited a curvilinear
relationship with milk temperature [16]. Heat stress
had negative effects on milk production traits and
SCS. The heat stress resulted in decreasing milkyield, fat, and protein percentages, and increasing
SCS [17].

SE

The effect of THI on Milk and Milk composition
The results in Table 3 show a significant
relationship (P < 0.01) between THI groups on
milk/day, %fat, %SNF and %TS. The milk/day of
the THI 4 group (THI >78) was lower than the THI
1 THI 2 and THI 3, with an average of 12.50, 14.04,
13.50 and 12.68 kg, respectively (P <0.01).
The %Fat, %SNF and %TS values were highest
in
the
THI
4
range
(THI>
78).
The % fat in THI 3 is the highest. However, there is
non-significant with THI 4, which is 3.49% and3.48%, respectively. The %fat in THI 1 is the lowest(2.89%). Additionally, the %SNF and %TS values in
THI 4 were the highest, 8.38 % and 11.86 %,respectively. The %SNF values in THI1, THI2 and
THI3 were 8.09%, 8.22% and 8.13%, respectively(P> 0.05). The reason is that when the THI value ishigher, the value of milk composition (%Fat, %SNF
and %TS) will increase as well; milk composition
Table 3 The effect of THI on Milk and Milk composition

parameter

THI 1
LSM

SE

THI 2
LSM

SE

THI 3
LSM

SE

THI 4
LSM

SE

p-value

Milk/Day (kg)14.04a0.38

13.50a0.30

12.68b

0.21

12.50c0.10**

Fat (%)

2.89a

0.02

3.39b

0.04

3.49bc

0.03

3.48c

0.01

**

Pro (%)

2.96

0.07

2.92

0.03

2.87

0.02

2.90

0.01

ns

SNF (%)

8.09a

0.13

8.22a

0.06

8.13a

0.04

8.38b

0.02

**

TS (%)

10.98a0.16

11.61b

0.08

11.59b

0.05

11.86c

0.02

**

Note:

THI 1 = (THI ≤70), THI 2 = 74 ≤THI<70, THI 3 =78 ≤THI<74, THI 4 =THI > 78**
The effect was significance at P<0.01
a,b,c
Value within the column with different superscripts are significantly different (P<0.01)

yield with a slope value of -0.099. The slope value
explains that when the THI value increased by 1
unit, the milk yield decreased by 0.099 kg / body /day. Dividing the THI group into 4 groups (THI 1 =THI ≤70, THI 2 = 74 ≤THI <70, THI 3 = 78 ITHI
<74, THI 4 = THI> 78), the result showed that when
the highest THI (THI 4) effect on milk yield is the

CONCLUSIONSThis study found that Mahasarakham province
has temperature between 20.88 - 33.01 ° C and theaverage humidity is 72.59%. Temperature Humidity
Index (THI) is the highest in May (82.07). There
was negative relationship between THI and milk
1065

SEE - Bangkok, Thailand, Nov.11-13, 2019

lowest, while THI1 and THI2 was effect on highmilk yield. Temperature and humidity increases willcause a in decrease milk production of dairy cows.

[8] Aguilar I., Misztal I., and Tsuruta S., Genetic
Components of Heat Stress in Dairy Cattle with
Multiple Loactations, Journal Dairy Science,Vol. 92, 2009, pp. 5702–5711.
[9] Mader T. L., Davis M. S., and Brown-Brandl T.,
Environmental Factors Influencing Heat Stressin Feedlot Cattle, Journal of Animal Science,Vol. 84, 2006, pp. 712–719.
[10] SAS, User’s Guide: Statistics, V.6.12, 1998,
SAS Institute Inc., Cary. NC.
[11] Yang, L., Yang Q., Yi M., Pang Z. H., andXiong B. H., Effects of seasonal change andparity on raw milk composition and related
indices in Chinese Holstein cows in northern
China, Journal Dairy Science, Vol. 96, 2013, pp.
6863-6869.
[12] Winai K., Effects of Heat Stress and β-Carotene
Supplementation on Postpartum Reproductive
Performance in Dairy Cows. Chulalongkorn
University, 2011, Bangkok, Thailand.
[13] Garner, J. B., Douglas M., Williams S. R. O.,
Wales W. J., Marett L. C., DiGiacomo K.,
Leury B. J., and Hayes B. J., Responses of dairy
cows to short-term heat stress in controlledclimate chambers. Journal of Animal Production
Science, Vol. 57, 2017, pp.1233–1241.
[14] Fleming A., Schenkel F. S., Malchiodi F., Ali R.
A., Mallard B., Sargolzaei M., Jamrozik J.,
Johnston J., and Miglior F., Genetic correlationsof mid-infrared-predicted milk fatty acid groups
with milk production traits, Journal Dairy
Science, Vol. 101, 2018, pp. 4295-4306.
[15] Ashleigh M. W., Thomson P. C., Garcia S. C.,
John A. J., Jongman E. C., Clark C. E. F., andKerrisk K. L., Short communication: The effectof temperature-humidity index on milk yieldand milking frequency of dairy cows in pasturebased automatic milking systems, Journal Dairy
Science, Vol. 101, 2018, pp. 4479-4482.
[16] West J. W.,. Mullinix B. G, and Bernard J. K.,
Effects of Hot, Humid Weather on Milk
Temperature, Dry Matter Intake, and Milk Yield
of Lactating Dairy Cows, Journal Dairy
Science, Vol. 86, 2003, pp. 232–242.
[17] Lambertz C., Sanker C., and Gauly M.,
Climatic effects on milk production traits andsomatic cell score in lactating Holstein-Friesiancows in different housing systems, Journal
Dairy Science, Vol. 97, 2014, pp. 319–329.

ACKNOWLEDGMENTS
The research team would like to thankKhok- Koen Dairy Farm Cooperative Limited anddairy farmers, Mahasarakham Province, Thailand formilk yield and milk composition data. Thank you to
the Meteorological Department Kosum Phisai
District Mahasarakham province, Thailand fortemperature and humidity data. Thank you to
Faculty of Technology, Mahasarakham University
Mahasarakham province.
REFERENCES[1] Meteorological Department, Thai Weather,
2018,
Available
From
https://www.tmd.go.th/info/climate_of_thailand-2524-2553.pdf.
[2] Cowley F. C., Barber D. C., Houlihan A. V.,
and Poppi D. P., Immediate and Residual
Effects of Heat Stress and Restricted Intake on
Milk Protein and Casein Composition andEnergy Metabolism. Journal Dairy Science, Vol.
98, 2015, pp. 2356–2368.
[3] Bouraoui R., Lahmar M., Majdoub A., Djemali
M.,
BelyeaR., TheRelationshipofTemperature-Humidity Index with Milk
Production of Dairy Cows in a Mediterranean
Climate . Journal Animal. Res, Vol. 51, 2002,
pp. 479–491.
[4] Boonkum W., Misztal I., Duangjinda M.,
Pattarajinda V., Tumwasorn S., and Sanpote J.,
Genetic Effects of Heat Stress on Milk Yield ofThai Holstein Crossbreds. Journal Dairy
Science, Vol. 94, 2011, pp. 487–492.
[5] Gantner V., Mijic P., Kuterovac K., Solic D.,
and Gantner R., Temperature-Humidity Index
Values and Their Significance on the Daily
Production of Dairy Cattle . Journal Dairy
production of dairy cattle, Vol. 61 (1), 2011, pp.
56-63.
[6] Bernabucci S., Biffani L.,
Buggiotti A.,
Lacetera N., and Nardone A., The Effects ofHeat stress in Italian Holstein Dairy Cattle,
Journal Dairy Science, Vol. 97, 2014, pp. 471–
486.
[7] Bernabucci U., and Calamai L., Effects of HeatStress on Bovine Milk Yield and Composition,
Journal of Zoot Nutrition Animal, Vol.24, 1998,
pp. 247-257.

1066

5th Int. Conf. on Science, Engineering & Environment (SEE),
Bangkok, Thailand, Nov.11-13, 2019, ISBN: 978-4-909106032 C3051

STEADY STATE GROUNDWATER FLOW MODEL OF WADI SAMAILCATCHMENT
Sharifa AL-Hashmi 1, Luminda Hewawasam 2 , Ahmed Sana 3 and Mahad Baawain 4
1

College of Engineering, Sultan Qaboos University, Oman
College of Engineering Sultan Qaboos University, Oman
3
College of Engineering, Sultan Qaboos University, Oman
4
College of Engineering, Sultan Qaboos University, Oman
2

ABSTRACT
Climate in most of Gulf Cooperation Council (GCC) countries are considered arid with limited water resources.
Proper management of scarce water resources is therefore necessary for sustainable water supply while meeting
the growing water demands. A three dimensional finite difference groundwater flow model of Wadi Samail
Catchment was developed to simulate groundwater flow and to evaluate the sensitivity of model to the varying of
input parameters. The model contained historical information of the aquifer and real data of water levels, rainfall,borehole and hydraulic conductivity. The aquifer was divided into 4 layers. The steady state calibration was carriedout using data in 14 monitoring wells in July 2016.The hydraulic conductivity (K) and recharge values were
calibrated with the estimated root mean squared error (RMSE) of 0.8m. The estimated parameters were verified
with groundwater levels in October 2016. The RMSE between observed and simulated water levels was 0.81m.The
calibrated model was then used to assess the sensitivity of the model results to the changes in pumping rate,
hydraulic conductivity (k) and recharge. Results showed that the water levels were most sensitive to hydraulicconductivity of first layer. While pumping rates and recharge were less sensitive compare to the hydraulicconductivity. In conclusion, the sensitivity analysis results can be used as a management tool for sustainable water
resource.
Keywords: Numerical groundwater model; Calibration; Sensitivity analysis; Wadi Samail catchment

the groundwater condition and contaminant transport[5].Therefore, the numerical groundwater model has
been used as solution to handle the real world systems[6].Also for management and protection of water
resources by predicting the future status under current
circumstances.
The aim of the study is to simulate groundwaterlevel through steady state groundwater model
simulation of July 2016 .Also to assess the sensitivityof model to the change in pumping rates, hydraulicconductivity (k) and recharge from the calibrate
values.

INTRODUCTION
Groundwater is a precious, very limited resourceand shared without having any fixed boundaries.It is
exposed to many risks and great pressure as a resultof the rapid increase in population, along with social,
agricultural, and industrial development. All thesefactors have resulted in substantial increase in water
demands, placing great pressures on the limited water
resources. The main threats to water resources are
population growth, urbanization and climate change[1].
Most of Gulf Cooperation Council (GCC)
countries are considered as arid region with limited
water resources and dependency on groundwater anddesalination to meet water demand. The annual
rainfall is less than 100 mm/yr and the evaporation
rates more than 3000 mm/yr [2].The limitation inwater resources especially in arid regions Like Oman
has led to improve the level of water management andconservation for continuous water supply for
population growth and development demands[3].Also, it is necessary to find a way to increase
artificial recharge especially in arid regions [4].
For management purpose, the aquifer properties
should be examined adequately in order to understand

STUDY AREA
The Sultanate of Oman is picturesquely located in
the south-east of the Arabian Peninsula[3].It has atotal area of 309,500 km² and a coastline of almost
3,165 km. It is located in an arid region of the world
and characterised by limited water resources. Mean
annual rainfall throughout most of Oman is relatively
low, less than 100 mm and sporadic but in mountainareas rainfall is greater up to 350 mm[7].Wadi Samail
catchment has a total area of 1720 km2 and it is1067

SEE - Bangkok, Thailand, Nov.11-13, 2019

triangular in shape as shown in Fig.1. The catchment
divided to two part upper and lower which areconnected by narrow gorge at AlKhod town[8].

creating the conceptual model and 3-D cross section,
they were mapped to MODFLOW to simulate thegroundwater water level. The steady state
groundwater model was run for period of July 2016.

Fig. 1 Study area

Fig. 2 Study area boundaries

DATA AND METHODRESULTS AND DICUSSION

Data:

The calibration of steady state groundwater model
was conducted by using the water level of 14
observation wells that cover the whole catchment.
Two methods of calibration were used for calibration:
the automated parameter estimation (PEST) andmanual trial and error method. The manual trial anderror method showed reasonable results than the othermethod if we compared with the initial values ofaquifer parameters such as hydraulic conductivity andrecharge. Since the geology of the aquifer is very
complex so the automated parameter estimation(PEST) cannot handle it properly. The results ofmanual calibration are shown in Table 1.We can seethat the residual head was less than 2m. The root
mean squared error (RMSE) for the steady state
simulation was calculated and the result found to be
0.8m.
Once the aquifer parameters estimated, anothersimulation was run using groundwater levels ofOctober 2016 in order to verify the accuracy of thecalibrated parameters. Table 2 displays the computed
heads from the simulation and the residual heads. The
mean residual head was 0.35m and the RMSE is
0.81m.

1.

2.

3.

4.
5.

Borehole data: the Ministry of Regional
Municipality and Water Resources (MRMWR)
provides data of 47 borehole cover the wholecatchment area.
Groundwater level: the data of groundwaterlevel was provided from MRMWR database ofobservation wells.
Wells: pumping well data for water supply from
Public Authority of Water (PAW) and irrigation
wells data from National Well Inventory(NWI)
from MRMWR
Recharge: rainfall station data from MRMWR
database
Hydraulic conductivity: based on borehole data
which classify type of material and previous
studies

Method:
MODFLOW2000:
using
modularthree
dimensional finite difference groundwater flow
model which use governing equation to simulate theflow [9].

Table 1 Calibration result
METHODOLOGY
Observation
well ID
PZ-7
SMA-11B
SLU2B
SJA-2B
SNA-3B
SMN-1B
WRD-10The conceptual model was created from obtained
data of observation wells, pumping wells andborehole. The boundaries of the study area were set
as shown in Fig.2.The aquifer was divided to 4 layer:
upper gravel, clayey gravel, cemented gravel andophiolites. Based on borehole data, 3-D cross section
was built in order to identify the properties andthickness of layers for 3-D grid construction. After
1068

Observed
head
569.26404.54307.31
253.99242.6369.91
3.32

Computedhead
569.95404.33307.26253.33241.6670.52
2.7

Residual
head
-0.69
0.21
0.05
0.66
0.97
-0.61
0.62

SEE - Bangkok, Thailand, Nov.11-13, 2019

3.14
1.84
7.19
7.7
0.47
1.47
9.62

4.77
2.57
6.7
7.2
1.4
2.05
8.47

-1.63
-0.73
0.49
0.5
-0.93
-0.58
1.15

6
4
RMSE

WRD-02
WRD-12
21-6D
21-6S
RGS-5HS
RGS-5F
21-7S-100
Table 2 Validation results
Observation
well ID
PZ-7
SMA-11B
SLU2B
SJA-2B
SNA-3B
SMN-1B
WRD-4
WRD-10
WRD-3
WRD-02
WRD-12
WRD-2421-6D
21-6S
RGS-5HS
RGS-5F

Observed
head
564.43404.19307.22254
241.74
69.94
1.08
0.68
1.09
0.86
0.92
-0.73
5.03
6.01
-0.57
0.4

2
0
-50

-2

0

50

-4
Computedhead
564.75402.82306.41252.6
240.95
69.71
1.55
-0.28
1.42
1.98
-0.2
-0.46
4.48
5
-0.24
0.16

Residual
head
-0.32
1.37
0.81
1.4
0.79
0.23
-0.47
0.96
-0.33
-1.12
1.12
-0.27
0.55
1.01
-0.33
0.24

100
RMSE
ME

-6
Change from calibrated value %Fig. 3 Sensitivity of pumping parameter
It was notable that the hydraulic conductivity oflayer 1 was the most sensitive to the change compare
to other layers as shown in Fig. 4 and 5.The value of
RMSE reached 83 in zone 2 this can be explained dueto the absence of pumping wells so by decreasing thek values the water level increased and the residual
error increased. In Fig.5 the calibrated value ofhydraulic conductivity in zone1 layer 1 is 40.9. As thehydraulic conductivity decreased the RMSE
increased to reach 19 while increasing the hydraulicconductivity reduced the RMSE and this means thecomputed water level match the observed water levelwith minimum residual error. The remaining layers
were less sensitive to the change from the calibrated
values as it was remarkable in Fig.6.

SENSTIVITY ANALYSIS

For the recharge zone 2 was more sensitive
compare to other zones as shown in Fig.7.

Sensitivity analysis was conducted using thecalibrated groundwater flow model by varying thepumping rates, hydraulic conductivity and recharge
from the calibrated values. The parameters wereanalysed their sensitivity to the change fromcalibrated values. Each of the former parameters wereincreased consistently by 10%, 20% to 100% above
the calibrated values and decreased on the same
pattern. The sensitivity of groundwater level wasvalued by root mean squared error (RMSE) and meanerror (ME).Figures 3 to Fig.7 show the sensitivity ofpumping, hydraulic conductivity and recharge.

100

RMSE

80
60
40

Zone 1
Zone2
Zone3
Zone4
Zone5

20

For the case sensitivity of pumping (Fig.3), as we
increased the pumping rates the mean error increasedin positive values .For example for the 70% increase
from the calibrated value the ME was 2.81 and thismeans the observed water level was higher than thecomputed water level. While for 70% decrease fromthe calibrated value the ME was -2.7 and thisindicates that the computed water level was higher
than the observed water level. While the RMSE
showed that as the pumping increased the residual
error increased and the same pattern occurred for
reduction in pumping rates.

0
-100

-50
0
50
Change from calibrated value %100

Fig. 4 Sensitivity of hydraulic conductivity of layer 1

1069

RMSE

SEE - Bangkok, Thailand, Nov.11-13, 201925

CONCLUSION

20

The numerical groundwater model has beencreated to simulate the groundwater level.The model
consist of four computational layers which areclassified based on borehole data. From the model
simulation results we can concluded that thecalibrated parameters were matching the initial values
since the computed water levels were matching theobserved water levels with minimum residual error.
This conclusion was supported by the calculated
RMSE value which was 0.8m.From sensitivity
analysis we noticed that hydraulic conductivity oflayer 1 was the most sensitive to the change fromcalibrated values. Also, pumping and recharge weresensitive to the change from calibrated value but lesscompare to sensitivity of hydraulic conductivity. For
water resource management purpose the groundwaterlevels should be regularly monitored and the effect ofpumping should also be evaluated.

15
10
5
0
0

20

40

60

80

100

Change from calibrated value
Fig. 5 Sensitivity of hydraulic conductivity of zone1
at layer1

RMSE

1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0

-80

layer2layer 3layer4-30
20
Change from calibrated value %REFERENCES[1] Akbarpour.S., and Niksokhan.M., Investigating
effects of climate change, urbanization, and sea
level changes on groundwater resources in acoastal aquifer.an integrated assessment. Environ
Monit Assess, (2018) 190: 579.
[2] AL-ZUBARI.W.K., Alternative Water Policies
for the Gulf Cooperation Council Countries.
Elsevier Science 2003. p. 155-167.
[3] MRMWR, Water Resources in Oman. 2008.
[4] Dragoni. W., and Sukhija. B.S., Climate change
and groundwater: a short review. GeologicalSociety, London, Special Publications, 2008.
288(1): p. 1-12.
[5] Di Maio. R., Fabbrocino.S. Forte. G. andPiegarie.E,Athree-dimensional hydrogeological–
geophysical model of a multi-layered aquifer inthe coastal alluvial plain of Sarno River (southern
Italy). Hydrogeology Journal (2014) 22: 691–703.
[6] Rabbani. M.G., and Warner.J.W., A finiteelement linked model for analysis of solutetransport in 3-D space of multilayer subsurface
systems. Journal of Hydrology. 199 (1997) 163182.
[7] MRMWR, Water Resources in Oman. 2012. 3rd.
[8]
Abdalla.O.A.E.,
and
Al-Rawahi.A.S.,
Groundwater recharge dams in arid areas as tools
for aquifer replenishment and mitigating seawater
intrusion: example of AlKhod, Oman.
Environmental Earth Sciences, (2013) 69:1951–
1962[9] McDonald. M.G., and Harbaugh. A.W., A
modular three-dimensional finite-difference
ground-water flow model. U.S.Geological Survey
report, 1984. 83-875.

70

Fig. 6 Sensitivity of hydraulic conductivity

30

RMSE

Zone 125

Zone 220

Zone 3

15
10
5

-60

0
-10

40

Change from calibrated value %Fig.7 Sensitivity of recharge

1070

The Sixth International Conference on

18-20 November 2020

The "International Journal of
GEOMATE" is a Scientific Journal of
the GEOMATE International Societythat encompasses a broad area inGeotechnique, Construction Materials
and Environment.
The key objective of this journal is topromote interdisciplinary researchfrom various regions of the globe.
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researchers, academicians, scientists
from Japan and other countries of theworld.
It is peer-reviewed Journal that is
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